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Merge pull request #1777 from freqtrade/new_release

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Version to 0.18.5
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Misagh 2019-04-19 15:57:07 +02:00 committed by GitHub
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1
.gitignore vendored
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@ -81,6 +81,7 @@ target/
# Jupyter Notebook
.ipynb_checkpoints
*.ipynb
# pyenv
.python-version

1
.pyup.yml
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@ -22,6 +22,7 @@ requirements:
- requirements.txt
- requirements-dev.txt
- requirements-plot.txt
- requirements-pi.txt
# configure the branch prefix the bot is using

14
.travis.yml
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@ -23,22 +23,25 @@ install:
- pip install -r requirements-dev.txt
- pip install -e .
jobs:
include:
- stage: tests
script:
- pytest --cov=freqtrade --cov-config=.coveragerc freqtrade/tests/
# Allow failure for coveralls
- coveralls || true
name: pytest
- script:
- cp config.json.example config.json
- python freqtrade/main.py --datadir freqtrade/tests/testdata backtesting
- python freqtrade --datadir freqtrade/tests/testdata backtesting
name: backtest
- script:
- cp config.json.example config.json
- python freqtrade/main.py --datadir freqtrade/tests/testdata hyperopt -e 5
- python freqtrade --datadir freqtrade/tests/testdata hyperopt -e 5
name: hyperopt
- script: flake8 freqtrade
- script: flake8 freqtrade scripts
name: flake8
- script: mypy freqtrade
- script: mypy freqtrade scripts
name: mypy
- stage: docker
@ -47,9 +50,6 @@ jobs:
- build_helpers/publish_docker.sh
name: "Build and test and push docker image"
after_success:
- coveralls
notifications:
slack:
secure: 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

4
Dockerfile
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@ -1,7 +1,7 @@
FROM python:3.7.2-slim-stretch
FROM python:3.7.3-slim-stretch
RUN apt-get update \
&& apt-get -y install curl build-essential \
&& apt-get -y install curl build-essential libssl-dev \
&& apt-get clean \
&& pip install --upgrade pip

40
Dockerfile.pi Normal file
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@ -0,0 +1,40 @@
FROM balenalib/raspberrypi3-debian:stretch
RUN [ "cross-build-start" ]
RUN apt-get update \
&& apt-get -y install wget curl build-essential libssl-dev libffi-dev \
&& apt-get clean
# Prepare environment
RUN mkdir /freqtrade
WORKDIR /freqtrade
# Install TA-lib
COPY build_helpers/ta-lib-0.4.0-src.tar.gz /freqtrade/
RUN tar -xzf /freqtrade/ta-lib-0.4.0-src.tar.gz \
&& cd /freqtrade/ta-lib/ \
&& ./configure \
&& make \
&& make install \
&& rm /freqtrade/ta-lib-0.4.0-src.tar.gz
ENV LD_LIBRARY_PATH /usr/local/lib
# Install berryconda
RUN wget https://github.com/jjhelmus/berryconda/releases/download/v2.0.0/Berryconda3-2.0.0-Linux-armv7l.sh \
&& bash ./Berryconda3-2.0.0-Linux-armv7l.sh -b \
&& rm Berryconda3-2.0.0-Linux-armv7l.sh
# Install dependencies
COPY requirements-pi.txt /freqtrade/
RUN ~/berryconda3/bin/conda install -y numpy pandas scipy \
&& ~/berryconda3/bin/pip install -r requirements-pi.txt --no-cache-dir
# Install and execute
COPY . /freqtrade/
RUN ~/berryconda3/bin/pip install -e . --no-cache-dir
RUN [ "cross-build-end" ]
ENTRYPOINT ["/root/berryconda3/bin/python","./freqtrade/main.py"]

39
README.md
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@ -68,39 +68,40 @@ For any other type of installation please refer to [Installation doc](https://ww
### Bot commands
```
usage: main.py [-h] [-v] [--version] [-c PATH] [-d PATH] [-s NAME]
[--strategy-path PATH] [--customhyperopt NAME]
[--dynamic-whitelist [INT]] [--db-url PATH]
{backtesting,edge,hyperopt} ...
usage: freqtrade [-h] [-v] [--logfile FILE] [--version] [-c PATH] [-d PATH]
[-s NAME] [--strategy-path PATH] [--dynamic-whitelist [INT]]
[--db-url PATH] [--sd-notify]
{backtesting,edge,hyperopt} ...
Free, open source crypto trading bot
positional arguments:
{backtesting,edge,hyperopt}
backtesting backtesting module
edge edge module
hyperopt hyperopt module
backtesting Backtesting module.
edge Edge module.
hyperopt Hyperopt module.
optional arguments:
-h, --help show this help message and exit
-v, --verbose verbose mode (-vv for more, -vvv to get all messages)
--version show program\'s version number and exit
-v, --verbose Verbose mode (-vv for more, -vvv to get all messages).
--logfile FILE Log to the file specified
--version show program's version number and exit
-c PATH, --config PATH
specify configuration file (default: config.json)
Specify configuration file (default: None). Multiple
--config options may be used.
-d PATH, --datadir PATH
path to backtest data
Path to backtest data.
-s NAME, --strategy NAME
specify strategy class name (default: DefaultStrategy)
--strategy-path PATH specify additional strategy lookup path
--customhyperopt NAME
specify hyperopt class name (default:
DefaultHyperOpts)
Specify strategy class name (default:
DefaultStrategy).
--strategy-path PATH Specify additional strategy lookup path.
--dynamic-whitelist [INT]
dynamically generate and update whitelist based on 24h
BaseVolume (default: 20) DEPRECATED.
Dynamically generate and update whitelist based on 24h
BaseVolume (default: 20). DEPRECATED.
--db-url PATH Override trades database URL, this is useful if
dry_run is enabled or in custom deployments (default:
None)
None).
--sd-notify Notify systemd service manager.
```
### Telegram RPC commands

3
config.json.example
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@ -30,7 +30,8 @@
"secret": "your_exchange_secret",
"ccxt_config": {"enableRateLimit": true},
"ccxt_async_config": {
"enableRateLimit": false
"enableRateLimit": true,
"rateLimit": 500
},
"pair_whitelist": [
"ETH/BTC",

3
config_binance.json.example
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@ -30,7 +30,8 @@
"secret": "your_exchange_secret",
"ccxt_config": {"enableRateLimit": true},
"ccxt_async_config": {
"enableRateLimit": false
"enableRateLimit": true,
"rateLimit": 200
},
"pair_whitelist": [
"AST/BTC",

12
config_full.json.example
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@ -9,6 +9,7 @@
"trailing_stop": false,
"trailing_stop_positive": 0.005,
"trailing_stop_positive_offset": 0.0051,
"trailing_only_offset_is_reached": false,
"minimal_roi": {
"40": 0.0,
"30": 0.01,
@ -38,18 +39,19 @@
"buy": "limit",
"sell": "limit",
"stoploss": "market",
"stoploss_on_exchange": "false",
"stoploss_on_exchange": false,
"stoploss_on_exchange_interval": 60
},
"order_time_in_force": {
"buy": "gtc",
"sell": "gtc",
"sell": "gtc"
},
"pairlist": {
"method": "VolumePairList",
"config": {
"number_assets": 20,
"sort_key": "quoteVolume"
"sort_key": "quoteVolume",
"precision_filter": false
}
},
"exchange": {
@ -59,6 +61,7 @@
"ccxt_config": {"enableRateLimit": true},
"ccxt_async_config": {
"enableRateLimit": false,
"rateLimit": 500,
"aiohttp_trust_env": false
},
"pair_whitelist": [
@ -76,7 +79,8 @@
"pair_blacklist": [
"DOGE/BTC"
],
"outdated_offset": 5
"outdated_offset": 5,
"markets_refresh_interval": 60
},
"edge": {
"enabled": false,

71
config_kraken.json.example Normal file
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@ -0,0 +1,71 @@
{
"max_open_trades": 5,
"stake_currency": "EUR",
"stake_amount": 10,
"fiat_display_currency": "EUR",
"ticker_interval" : "5m",
"dry_run": true,
"db_url": "sqlite:///tradesv3.dryrun.sqlite",
"trailing_stop": false,
"unfilledtimeout": {
"buy": 10,
"sell": 30
},
"bid_strategy": {
"ask_last_balance": 0.0,
"use_order_book": false,
"order_book_top": 1,
"check_depth_of_market": {
"enabled": false,
"bids_to_ask_delta": 1
}
},
"ask_strategy":{
"use_order_book": false,
"order_book_min": 1,
"order_book_max": 9
},
"exchange": {
"name": "kraken",
"key": "",
"secret": "",
"ccxt_config": {"enableRateLimit": true},
"ccxt_async_config": {
"enableRateLimit": true,
"rateLimit": 1000
},
"pair_whitelist": [
"ETH/EUR",
"BTC/EUR",
"BCH/EUR"
],
"pair_blacklist": [
]
},
"edge": {
"enabled": false,
"process_throttle_secs": 3600,
"calculate_since_number_of_days": 7,
"capital_available_percentage": 0.5,
"allowed_risk": 0.01,
"stoploss_range_min": -0.01,
"stoploss_range_max": -0.1,
"stoploss_range_step": -0.01,
"minimum_winrate": 0.60,
"minimum_expectancy": 0.20,
"min_trade_number": 10,
"max_trade_duration_minute": 1440,
"remove_pumps": false
},
"telegram": {
"enabled": false,
"token": "",
"chat_id": ""
},
"initial_state": "running",
"forcebuy_enable": false,
"internals": {
"process_throttle_secs": 5
}
}

70
docs/backtesting.md
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@ -24,37 +24,37 @@ The backtesting is very easy with freqtrade.
#### With 5 min tickers (Per default)
```bash
python3 ./freqtrade/main.py backtesting
python3 freqtrade backtesting
```
#### With 1 min tickers
```bash
python3 ./freqtrade/main.py backtesting --ticker-interval 1m
python3 freqtrade backtesting --ticker-interval 1m
```
#### Update cached pairs with the latest data
```bash
python3 ./freqtrade/main.py backtesting --refresh-pairs-cached
python3 freqtrade backtesting --refresh-pairs-cached
```
#### With live data (do not alter your testdata files)
```bash
python3 ./freqtrade/main.py backtesting --live
python3 freqtrade backtesting --live
```
#### Using a different on-disk ticker-data source
```bash
python3 ./freqtrade/main.py backtesting --datadir freqtrade/tests/testdata-20180101
python3 freqtrade backtesting --datadir freqtrade/tests/testdata-20180101
```
#### With a (custom) strategy file
```bash
python3 ./freqtrade/main.py -s TestStrategy backtesting
python3 freqtrade -s TestStrategy backtesting
```
Where `-s TestStrategy` refers to the class name within the strategy file `test_strategy.py` found in the `freqtrade/user_data/strategies` directory
@ -62,43 +62,15 @@ Where `-s TestStrategy` refers to the class name within the strategy file `test_
#### Exporting trades to file
```bash
python3 ./freqtrade/main.py backtesting --export trades
python3 freqtrade backtesting --export trades
```
The exported trades can be read using the following code for manual analysis, or can be used by the plotting script `plot_dataframe.py` in the scripts folder.
``` python
import json
from pathlib import Path
import pandas as pd
filename=Path('user_data/backtest_data/backtest-result.json')
with filename.open() as file:
data = json.load(file)
columns = ["pair", "profit", "opents", "closets", "index", "duration",
"open_rate", "close_rate", "open_at_end", "sell_reason"]
df = pd.DataFrame(data, columns=columns)
df['opents'] = pd.to_datetime(df['opents'],
unit='s',
utc=True,
infer_datetime_format=True
)
df['closets'] = pd.to_datetime(df['closets'],
unit='s',
utc=True,
infer_datetime_format=True
)
```
If you have some ideas for interesting / helpful backtest data analysis, feel free to submit a PR so the community can benefit from it.
The exported trades can be used for [further analysis](#further-backtest-result-analysis), or can be used by the plotting script `plot_dataframe.py` in the scripts folder.
#### Exporting trades to file specifying a custom filename
```bash
python3 ./freqtrade/main.py backtesting --export trades --export-filename=backtest_teststrategy.json
python3 freqtrade backtesting --export trades --export-filename=backtest_teststrategy.json
```
#### Running backtest with smaller testset
@ -109,7 +81,7 @@ you want to use. The last N ticks/timeframes will be used.
Example:
```bash
python3 ./freqtrade/main.py backtesting --timerange=-200
python3 freqtrade backtesting --timerange=-200
```
#### Advanced use of timerange
@ -245,6 +217,28 @@ On the other hand, if you set a too high `minimal_roi` like `"0": 0.55`
profit. Hence, keep in mind that your performance is a mix of your
strategies, your configuration, and the crypto-currency you have set up.
### Further backtest-result analysis
To further analyze your backtest results, you can [export the trades](#exporting-trades-to-file).
You can then load the trades to perform further analysis.
A good way for this is using Jupyter (notebook or lab) - which provides an interactive environment to analyze the data.
Freqtrade provides an easy to load the backtest results, which is `load_backtest_data` - and takes a path to the backtest-results file.
``` python
from freqtrade.data.btanalysis import load_backtest_data
df = load_backtest_data("user_data/backtest-result.json")
# Show value-counts per pair
df.groupby("pair")["sell_reason"].value_counts()
```
This will allow you to drill deeper into your backtest results, and perform analysis which would make the regular backtest-output unreadable.
If you have some ideas for interesting / helpful backtest data analysis ideas, please submit a PR so the community can benefit from it.
## Backtesting multiple strategies
To backtest multiple strategies, a list of Strategies can be provided.

36
docs/bot-optimization.md
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@ -14,7 +14,7 @@ Let assume you have a class called `AwesomeStrategy` in the file `awesome-strate
2. Start the bot with the param `--strategy AwesomeStrategy` (the parameter is the class name)
```bash
python3 ./freqtrade/main.py --strategy AwesomeStrategy
python3 freqtrade --strategy AwesomeStrategy
```
## Change your strategy
@ -41,13 +41,13 @@ The bot also include a sample strategy called `TestStrategy` you can update: `us
You can test it with the parameter: `--strategy TestStrategy`
```bash
python3 ./freqtrade/main.py --strategy AwesomeStrategy
python3 freqtrade --strategy AwesomeStrategy
```
**For the following section we will use the [user_data/strategies/test_strategy.py](https://github.com/freqtrade/freqtrade/blob/develop/user_data/strategies/test_strategy.py)
file as reference.**
!!! Note: Strategies and Backtesting
!!! Note Strategies and Backtesting
To avoid problems and unexpected differences between Backtesting and dry/live modes, please be aware
that during backtesting the full time-interval is passed to the `populate_*()` methods at once.
It is therefore best to use vectorized operations (across the whole dataframe, not loops) and
@ -250,22 +250,19 @@ class Awesomestrategy(IStrategy):
self.cust_info[metadata["pair"]["crosstime"] = 1
```
!!! Warning:
!!! Warning
The data is not persisted after a bot-restart (or config-reload). Also, the amount of data should be kept smallish (no DataFrames and such), otherwise the bot will start to consume a lot of memory and eventually run out of memory and crash.
!!! Note:
!!! Note
If the data is pair-specific, make sure to use pair as one of the keys in the dictionary.
### Additional data (DataProvider)
The strategy provides access to the `DataProvider`. This allows you to get additional data to use in your strategy.
!!!Note:
The DataProvier is currently not available during backtesting / hyperopt, but this is planned for the future.
All methods return `None` in case of failure (do not raise an exception).
Please always check if the `DataProvider` is available to avoid failures during backtesting.
Please always check the mode of operation to select the correct method to get data (samples see below).
#### Possible options for DataProvider
@ -278,20 +275,23 @@ Please always check if the `DataProvider` is available to avoid failures during
``` python
if self.dp:
if dp.runmode == 'live':
if ('ETH/BTC', ticker_interval) in self.dp.available_pairs:
data_eth = self.dp.ohlcv(pair='ETH/BTC',
ticker_interval=ticker_interval)
if self.dp.runmode in ('live', 'dry_run'):
if (f'{self.stake_currency}/BTC', self.ticker_interval) in self.dp.available_pairs:
data_eth = self.dp.ohlcv(pair='{self.stake_currency}/BTC',
ticker_interval=self.ticker_interval)
else:
# Get historic ohlcv data (cached on disk).
history_eth = self.dp.historic_ohlcv(pair='ETH/BTC',
history_eth = self.dp.historic_ohlcv(pair='{self.stake_currency}/BTC',
ticker_interval='1h')
```
!!! Warning: Warning about backtesting
!!! Warning Warning about backtesting
Be carefull when using dataprovider in backtesting. `historic_ohlcv()` provides the full time-range in one go,
so please be aware of it and make sure to not "look into the future" to avoid surprises when running in dry/live mode).
!!! Warning Warning in hyperopt
This option cannot currently be used during hyperopt.
#### Available Pairs
``` python
@ -317,7 +317,7 @@ def informative_pairs(self):
]
```
!!! Warning:
!!! Warning
As these pairs will be refreshed as part of the regular whitelist refresh, it's best to keep this list short.
All intervals and all pairs can be specified as long as they are available (and active) on the used exchange.
It is however better to use resampling to longer time-intervals when possible
@ -327,7 +327,7 @@ def informative_pairs(self):
The strategy provides access to the `Wallets` object. This contains the current balances on the exchange.
!!!NOTE:
!!! Note
Wallets is not available during backtesting / hyperopt.
Please always check if `Wallets` is available to avoid failures during backtesting.
@ -355,7 +355,7 @@ The default buy strategy is located in the file
If you want to use a strategy from a different folder you can pass `--strategy-path`
```bash
python3 ./freqtrade/main.py --strategy AwesomeStrategy --strategy-path /some/folder
python3 freqtrade --strategy AwesomeStrategy --strategy-path /some/folder
```
### Further strategy ideas

175
docs/bot-usage.md
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@ -6,50 +6,81 @@ This page explains the different parameters of the bot and how to run it.
## Bot commands
```
usage: main.py [-h] [-v] [--version] [-c PATH] [-d PATH] [-s NAME]
[--strategy-path PATH] [--customhyperopt NAME]
[--dynamic-whitelist [INT]] [--db-url PATH]
{backtesting,edge,hyperopt} ...
usage: freqtrade [-h] [-v] [--logfile FILE] [--version] [-c PATH] [-d PATH]
[-s NAME] [--strategy-path PATH] [--dynamic-whitelist [INT]]
[--db-url PATH] [--sd-notify]
{backtesting,edge,hyperopt} ...
Free, open source crypto trading bot
positional arguments:
{backtesting,edge,hyperopt}
backtesting backtesting module
edge edge module
hyperopt hyperopt module
backtesting Backtesting module.
edge Edge module.
hyperopt Hyperopt module.
optional arguments:
-h, --help show this help message and exit
-v, --verbose verbose mode (-vv for more, -vvv to get all messages)
--version show program\'s version number and exit
-v, --verbose Verbose mode (-vv for more, -vvv to get all messages).
--logfile FILE Log to the file specified
--version show program's version number and exit
-c PATH, --config PATH
specify configuration file (default: config.json)
Specify configuration file (default: None). Multiple
--config options may be used.
-d PATH, --datadir PATH
path to backtest data
Path to backtest data.
-s NAME, --strategy NAME
specify strategy class name (default: DefaultStrategy)
--strategy-path PATH specify additional strategy lookup path
--customhyperopt NAME
specify hyperopt class name (default:
DefaultHyperOpts)
Specify strategy class name (default:
DefaultStrategy).
--strategy-path PATH Specify additional strategy lookup path.
--dynamic-whitelist [INT]
dynamically generate and update whitelist based on 24h
BaseVolume (default: 20) DEPRECATED.
Dynamically generate and update whitelist based on 24h
BaseVolume (default: 20). DEPRECATED.
--db-url PATH Override trades database URL, this is useful if
dry_run is enabled or in custom deployments (default:
None)
None).
--sd-notify Notify systemd service manager.
```
### How to use a different config file?
### How to use a different configuration file?
The bot allows you to select which config file you want to use. Per
The bot allows you to select which configuration file you want to use. Per
default, the bot will load the file `./config.json`
```bash
python3 ./freqtrade/main.py -c path/far/far/away/config.json
python3 freqtrade -c path/far/far/away/config.json
```
### How to use multiple configuration files?
The bot allows you to use multiple configuration files by specifying multiple
`-c/--config` configuration options in the command line. Configuration parameters
defined in the last configuration file override parameters with the same name
defined in the previous configuration file specified in the command line.
For example, you can make a separate configuration file with your key and secrete
for the Exchange you use for trading, specify default configuration file with
empty key and secrete values while running in the Dry Mode (which does not actually
require them):
```bash
python3 freqtrade -c ./config.json
```
and specify both configuration files when running in the normal Live Trade Mode:
```bash
python3 freqtrade -c ./config.json -c path/to/secrets/keys.config.json
```
This could help you hide your private Exchange key and Exchange secrete on you local machine
by setting appropriate file permissions for the file which contains actual secrets and, additionally,
prevent unintended disclosure of sensitive private data when you publish examples
of your configuration in the project issues or in the Internet.
See more details on this technique with examples in the documentation page on
[configuration](configuration.md).
### How to use **--strategy**?
This parameter will allow you to load your custom strategy class.
@ -65,20 +96,21 @@ In `user_data/strategies` you have a file `my_awesome_strategy.py` which has
a strategy class called `AwesomeStrategy` to load it:
```bash
python3 ./freqtrade/main.py --strategy AwesomeStrategy
python3 freqtrade --strategy AwesomeStrategy
```
If the bot does not find your strategy file, it will display in an error
message the reason (File not found, or errors in your code).
Learn more about strategy file in [optimize your bot](https://github.com/freqtrade/freqtrade/blob/develop/docs/bot-optimization.md).
Learn more about strategy file in
[optimize your bot](bot-optimization.md).
### How to use **--strategy-path**?
This parameter allows you to add an additional strategy lookup path, which gets
checked before the default locations (The passed path must be a folder!):
```bash
python3 ./freqtrade/main.py --strategy AwesomeStrategy --strategy-path /some/folder
python3 freqtrade --strategy AwesomeStrategy --strategy-path /some/folder
```
#### How to install a strategy?
@ -89,29 +121,13 @@ This is very simple. Copy paste your strategy file into the folder
### How to use **--dynamic-whitelist**?
!!! danger "DEPRECATED"
Dynamic-whitelist is deprecated. Please move your configurations to the configuration as outlined [here](/configuration/#dynamic-pairlists)
This command line option is deprecated. Please move your configurations using it
to the configurations that utilize the `StaticPairList` or `VolumePairList` methods set
in the configuration file
as outlined [here](configuration/#dynamic-pairlists)
Per default `--dynamic-whitelist` will retrieve the 20 currencies based
on BaseVolume. This value can be changed when you run the script.
**By Default**
Get the 20 currencies based on BaseVolume.
```bash
python3 ./freqtrade/main.py --dynamic-whitelist
```
**Customize the number of currencies to retrieve**
Get the 30 currencies based on BaseVolume.
```bash
python3 ./freqtrade/main.py --dynamic-whitelist 30
```
**Exception**
`--dynamic-whitelist` must be greater than 0. If you enter 0 or a
negative value (e.g -2), `--dynamic-whitelist` will use the default
value (20).
Description of this deprecated feature was moved to [here](deprecated.md).
Please no longer use it.
### How to use **--db-url**?
@ -121,7 +137,7 @@ using `--db-url`. This can also be used to specify a custom database
in production mode. Example command:
```bash
python3 ./freqtrade/main.py -c config.json --db-url sqlite:///tradesv3.dry_run.sqlite
python3 freqtrade -c config.json --db-url sqlite:///tradesv3.dry_run.sqlite
```
## Backtesting commands
@ -129,27 +145,27 @@ python3 ./freqtrade/main.py -c config.json --db-url sqlite:///tradesv3.dry_run.s
Backtesting also uses the config specified via `-c/--config`.
```
usage: main.py backtesting [-h] [-i TICKER_INTERVAL] [--timerange TIMERANGE]
[--eps] [--dmmp] [-l] [-r]
[--strategy-list STRATEGY_LIST [STRATEGY_LIST ...]]
[--export EXPORT] [--export-filename PATH]
usage: freqtrade backtesting [-h] [-i TICKER_INTERVAL] [--timerange TIMERANGE]
[--eps] [--dmmp] [-l] [-r]
[--strategy-list STRATEGY_LIST [STRATEGY_LIST ...]]
[--export EXPORT] [--export-filename PATH]
optional arguments:
-h, --help show this help message and exit
-i TICKER_INTERVAL, --ticker-interval TICKER_INTERVAL
specify ticker interval (1m, 5m, 30m, 1h, 1d)
Specify ticker interval (1m, 5m, 30m, 1h, 1d).
--timerange TIMERANGE
specify what timerange of data to use.
Specify what timerange of data to use.
--eps, --enable-position-stacking
Allow buying the same pair multiple times (position
stacking)
stacking).
--dmmp, --disable-max-market-positions
Disable applying `max_open_trades` during backtest
(same as setting `max_open_trades` to a very high
number)
-l, --live using live data
number).
-l, --live Use live data.
-r, --refresh-pairs-cached
refresh the pairs files in tests/testdata with the
Refresh the pairs files in tests/testdata with the
latest data from the exchange. Use it if you want to
run your backtesting with up-to-date data.
--strategy-list STRATEGY_LIST [STRATEGY_LIST ...]
@ -159,7 +175,7 @@ optional arguments:
this together with --export trades, the strategy-name
is injected into the filename (so backtest-data.json
becomes backtest-data-DefaultStrategy.json
--export EXPORT export backtest results, argument are: trades Example
--export EXPORT Export backtest results, argument are: trades. Example
--export=trades
--export-filename PATH
Save backtest results to this filename requires
@ -189,29 +205,30 @@ To optimize your strategy, you can use hyperopt parameter hyperoptimization
to find optimal parameter values for your stategy.
```
usage: freqtrade hyperopt [-h] [-i TICKER_INTERVAL] [--eps] [--dmmp]
[--timerange TIMERANGE] [-e INT]
[-s {all,buy,roi,stoploss} [{all,buy,roi,stoploss} ...]]
usage: freqtrade hyperopt [-h] [-i TICKER_INTERVAL] [--timerange TIMERANGE]
[--customhyperopt NAME] [--eps] [--dmmp] [-e INT]
[-s {all,buy,sell,roi,stoploss} [{all,buy,sell,roi,stoploss} ...]]
optional arguments:
-h, --help show this help message and exit
-i TICKER_INTERVAL, --ticker-interval TICKER_INTERVAL
specify ticker interval (1m, 5m, 30m, 1h, 1d)
Specify ticker interval (1m, 5m, 30m, 1h, 1d).
--timerange TIMERANGE
Specify what timerange of data to use.
--customhyperopt NAME
Specify hyperopt class name (default:
DefaultHyperOpts).
--eps, --enable-position-stacking
Allow buying the same pair multiple times (position
stacking)
stacking).
--dmmp, --disable-max-market-positions
Disable applying `max_open_trades` during backtest
(same as setting `max_open_trades` to a very high
number)
--timerange TIMERANGE
specify what timerange of data to use.
--hyperopt PATH specify hyperopt file (default:
freqtrade/optimize/default_hyperopt.py)
-e INT, --epochs INT specify number of epochs (default: 100)
-s {all,buy,roi,stoploss} [{all,buy,roi,stoploss} ...], --spaces {all,buy,roi,stoploss} [{all,buy,roi,stoploss} ...]
number).
-e INT, --epochs INT Specify number of epochs (default: 100).
-s {all,buy,sell,roi,stoploss} [{all,buy,sell,roi,stoploss} ...], --spaces {all,buy,sell,roi,stoploss} [{all,buy,sell,roi,stoploss} ...]
Specify which parameters to hyperopt. Space separate
list. Default: all
list. Default: all.
```
@ -220,22 +237,22 @@ optional arguments:
To know your trade expectacny and winrate against historical data, you can use Edge.
```
usage: main.py edge [-h] [-i TICKER_INTERVAL] [--timerange TIMERANGE] [-r]
[--stoplosses STOPLOSS_RANGE]
usage: freqtrade edge [-h] [-i TICKER_INTERVAL] [--timerange TIMERANGE] [-r]
[--stoplosses STOPLOSS_RANGE]
optional arguments:
-h, --help show this help message and exit
-i TICKER_INTERVAL, --ticker-interval TICKER_INTERVAL
specify ticker interval (1m, 5m, 30m, 1h, 1d)
Specify ticker interval (1m, 5m, 30m, 1h, 1d).
--timerange TIMERANGE
specify what timerange of data to use.
Specify what timerange of data to use.
-r, --refresh-pairs-cached
refresh the pairs files in tests/testdata with the
Refresh the pairs files in tests/testdata with the
latest data from the exchange. Use it if you want to
run your edge with up-to-date data.
--stoplosses STOPLOSS_RANGE
defines a range of stoploss against which edge will
assess the strategythe format is "min,max,step"
Defines a range of stoploss against which edge will
assess the strategy the format is "min,max,step"
(without any space).example:
--stoplosses=-0.01,-0.1,-0.001
```

224
docs/configuration.md
View File

@ -14,18 +14,20 @@ Mandatory Parameters are marked as **Required**.
| Command | Default | Description |
|----------|---------|-------------|
| `max_open_trades` | 3 | **Required.** Number of trades open your bot will have. If -1 then it is ignored (i.e. potentially unlimited open trades)
| `stake_currency` | BTC | **Required.** Crypto-currency used for trading.
| `stake_amount` | 0.05 | **Required.** Amount of crypto-currency your bot will use for each trade. Per default, the bot will use (0.05 BTC x 3) = 0.15 BTC in total will be always engaged. Set it to `"unlimited"` to allow the bot to use all available balance.
| `stake_currency` | BTC | **Required.** Crypto-currency used for trading. [Strategy Override](#parameters-in-the-strategy).
| `stake_amount` | 0.05 | **Required.** Amount of crypto-currency your bot will use for each trade. Per default, the bot will use (0.05 BTC x 3) = 0.15 BTC in total will be always engaged. Set it to `"unlimited"` to allow the bot to use all available balance. [Strategy Override](#parameters-in-the-strategy).
| `amount_reserve_percent` | 0.05 | Reserve some amount in min pair stake amount. Default is 5%. The bot will reserve `amount_reserve_percent` + stop-loss value when calculating min pair stake amount in order to avoid possible trade refusals.
| `ticker_interval` | [1m, 5m, 30m, 1h, 1d] | The ticker interval to use (1min, 5 min, 30 min, 1 hour or 1 day). Default is 5 minutes. [Strategy Override](#parameters-in-strategy).
| `ticker_interval` | [1m, 5m, 15m, 30m, 1h, 1d, ...] | The ticker interval to use (1min, 5 min, 15 min, 30 min, 1 hour or 1 day). Default is 5 minutes. [Strategy Override](#parameters-in-the-strategy).
| `fiat_display_currency` | USD | **Required.** Fiat currency used to show your profits. More information below.
| `dry_run` | true | **Required.** Define if the bot must be in Dry-run or production mode.
| `process_only_new_candles` | false | If set to true indicators are processed only once a new candle arrives. If false each loop populates the indicators, this will mean the same candle is processed many times creating system load but can be useful of your strategy depends on tick data not only candle. [Strategy Override](#parameters-in-strategy).
| `minimal_roi` | See below | Set the threshold in percent the bot will use to sell a trade. More information below. [Strategy Override](#parameters-in-strategy).
| `stoploss` | -0.10 | Value of the stoploss in percent used by the bot. More information below. More details in the [stoploss documentation](stoploss.md). [Strategy Override](#parameters-in-strategy).
| `trailing_stop` | false | Enables trailing stop-loss (based on `stoploss` in either configuration or strategy file). More details in the [stoploss documentation](stoploss.md). [Strategy Override](#parameters-in-strategy).
| `trailing_stop_positive` | 0 | Changes stop-loss once profit has been reached. More details in the [stoploss documentation](stoploss.md). [Strategy Override](#parameters-in-strategy).
| `trailing_stop_positive_offset` | 0 | Offset on when to apply `trailing_stop_positive`. Percentage value which should be positive. More details in the [stoploss documentation](stoploss.md). [Strategy Override](#parameters-in-strategy).
| `dry_run_wallet` | 999.9 | Overrides the default amount of 999.9 stake currency units in the wallet used by the bot running in the Dry Run mode if you need it for any reason.
| `process_only_new_candles` | false | If set to true indicators are processed only once a new candle arrives. If false each loop populates the indicators, this will mean the same candle is processed many times creating system load but can be useful of your strategy depends on tick data not only candle. [Strategy Override](#parameters-in-the-strategy).
| `minimal_roi` | See below | Set the threshold in percent the bot will use to sell a trade. More information below. [Strategy Override](#parameters-in-the-strategy).
| `stoploss` | -0.10 | Value of the stoploss in percent used by the bot. More information below. More details in the [stoploss documentation](stoploss.md). [Strategy Override](#parameters-in-the-strategy).
| `trailing_stop` | false | Enables trailing stop-loss (based on `stoploss` in either configuration or strategy file). More details in the [stoploss documentation](stoploss.md). [Strategy Override](#parameters-in-the-strategy).
| `trailing_stop_positive` | 0 | Changes stop-loss once profit has been reached. More details in the [stoploss documentation](stoploss.md). [Strategy Override](#parameters-in-the-strategy).
| `trailing_stop_positive_offset` | 0 | Offset on when to apply `trailing_stop_positive`. Percentage value which should be positive. More details in the [stoploss documentation](stoploss.md). [Strategy Override](#parameters-in-the-strategy).
| `trailing_only_offset_is_reached` | false | Only apply trailing stoploss when the offset is reached. [stoploss documentation](stoploss.md). [Strategy Override](#parameters-in-the-strategy).
| `unfilledtimeout.buy` | 10 | **Required.** How long (in minutes) the bot will wait for an unfilled buy order to complete, after which the order will be cancelled.
| `unfilledtimeout.sell` | 10 | **Required.** How long (in minutes) the bot will wait for an unfilled sell order to complete, after which the order will be cancelled.
| `bid_strategy.ask_last_balance` | 0.0 | **Required.** Set the bidding price. More information [below](#understand-ask_last_balance).
@ -36,20 +38,21 @@ Mandatory Parameters are marked as **Required**.
| `ask_strategy.use_order_book` | false | Allows selling of open traded pair using the rates in Order Book Asks.
| `ask_strategy.order_book_min` | 0 | Bot will scan from the top min to max Order Book Asks searching for a profitable rate.
| `ask_strategy.order_book_max` | 0 | Bot will scan from the top min to max Order Book Asks searching for a profitable rate.
| `order_types` | None | Configure order-types depending on the action (`"buy"`, `"sell"`, `"stoploss"`, `"stoploss_on_exchange"`). [More information below](#understand-order_types). [Strategy Override](#parameters-in-strategy).
| `order_time_in_force` | None | Configure time in force for buy and sell orders. [More information below](#understand-order_time_in_force). [Strategy Override](#parameters-in-strategy).
| `order_types` | None | Configure order-types depending on the action (`"buy"`, `"sell"`, `"stoploss"`, `"stoploss_on_exchange"`). [More information below](#understand-order_types). [Strategy Override](#parameters-in-the-strategy).
| `order_time_in_force` | None | Configure time in force for buy and sell orders. [More information below](#understand-order_time_in_force). [Strategy Override](#parameters-in-the-strategy).
| `exchange.name` | bittrex | **Required.** Name of the exchange class to use. [List below](#user-content-what-values-for-exchangename).
| `exchange.sandbox` | false | Use the 'sandbox' version of the exchange, where the exchange provides a sandbox for risk-free integration. See [here](sandbox-testing.md) in more details.
| `exchange.key` | key | API key to use for the exchange. Only required when you are in production mode.
| `exchange.secret` | secret | API secret to use for the exchange. Only required when you are in production mode.
| `exchange.pair_whitelist` | [] | List of currency to use by the bot. Can be overrided with `--dynamic-whitelist` param.
| `exchange.pair_blacklist` | [] | List of currency the bot must avoid. Useful when using `--dynamic-whitelist` param.
| `exchange.ccxt_rate_limit` | True | DEPRECATED!! Have CCXT handle Exchange rate limits. Depending on the exchange, having this to false can lead to temporary bans from the exchange.
| `exchange.ccxt_config` | None | Additional CCXT parameters passed to the regular ccxt instance. Parameters may differ from exchange to exchange and are documented in the [ccxt documentation](https://ccxt.readthedocs.io/en/latest/manual.html#instantiation)
| `exchange.ccxt_async_config` | None | Additional CCXT parameters passed to the async ccxt instance. Parameters may differ from exchange to exchange and are documented in the [ccxt documentation](https://ccxt.readthedocs.io/en/latest/manual.html#instantiation)
| `exchange.markets_refresh_interval` | 60 | The interval in minutes in which markets are reloaded.
| `edge` | false | Please refer to [edge configuration document](edge.md) for detailed explanation.
| `experimental.use_sell_signal` | false | Use your sell strategy in addition of the `minimal_roi`. [Strategy Override](#parameters-in-strategy).
| `experimental.sell_profit_only` | false | Waits until you have made a positive profit before taking a sell decision. [Strategy Override](#parameters-in-strategy).
| `experimental.ignore_roi_if_buy_signal` | false | Does not sell if the buy-signal is still active. Takes preference over `minimal_roi` and `use_sell_signal`. [Strategy Override](#parameters-in-strategy).
| `experimental.use_sell_signal` | false | Use your sell strategy in addition of the `minimal_roi`. [Strategy Override](#parameters-in-the-strategy).
| `experimental.sell_profit_only` | false | Waits until you have made a positive profit before taking a sell decision. [Strategy Override](#parameters-in-the-strategy).
| `experimental.ignore_roi_if_buy_signal` | false | Does not sell if the buy-signal is still active. Takes preference over `minimal_roi` and `use_sell_signal`. [Strategy Override](#parameters-in-the-strategy).
| `pairlist.method` | StaticPairList | Use Static whitelist. [More information below](#dynamic-pairlists).
| `pairlist.config` | None | Additional configuration for dynamic pairlists. [More information below](#dynamic-pairlists).
| `telegram.enabled` | true | **Required.** Enable or not the usage of Telegram.
@ -66,14 +69,18 @@ Mandatory Parameters are marked as **Required**.
| `strategy` | DefaultStrategy | Defines Strategy class to use.
| `strategy_path` | null | Adds an additional strategy lookup path (must be a folder).
| `internals.process_throttle_secs` | 5 | **Required.** Set the process throttle. Value in second.
| `internals.sd_notify` | false | Enables use of the sd_notify protocol to tell systemd service manager about changes in the bot state and issue keep-alive pings. See [here](installation.md#7-optional-configure-freqtrade-as-a-systemd-service) for more details.
| `logfile` | | Specify Logfile. Uses a rolling strategy of 10 files, with 1Mb per file.
### Parameters in strategy
### Parameters in the strategy
The following parameters can be set in either configuration or strategy.
Values in the configuration are always overwriting values set in the strategy.
The following parameters can be set in either configuration file or strategy.
Values set in the configuration file always overwrite values set in the strategy.
* `minimal_roi`
* `stake_currency`
* `stake_amount`
* `ticker_interval`
* `minimal_roi`
* `stoploss`
* `trailing_stop`
* `trailing_stop_positive`
@ -87,7 +94,7 @@ Values in the configuration are always overwriting values set in the strategy.
### Understand stake_amount
`stake_amount` is an amount of crypto-currency your bot will use for each trade.
The `stake_amount` configuration parameter is an amount of crypto-currency your bot will use for each trade.
The minimal value is 0.0005. If there is not enough crypto-currency in
the account an exception is generated.
To allow the bot to trade all the available `stake_currency` in your account set
@ -104,7 +111,7 @@ currency_balanse / (max_open_trades - current_open_trades)
### Understand minimal_roi
`minimal_roi` is a JSON object where the key is a duration
The `minimal_roi` configuration parameter is a JSON object where the key is a duration
in minutes and the value is the minimum ROI in percent.
See the example below:
@ -117,18 +124,19 @@ See the example below:
},
```
Most of the strategy files already include the optimal `minimal_roi`
value. This parameter is optional. If you use it, it will take over the
Most of the strategy files already include the optimal `minimal_roi` value.
This parameter can be set in either Strategy or Configuration file. If you use it in the configuration file, it will override the
`minimal_roi` value from the strategy file.
If it is not set in either Strategy or Configuration, a default of 1000% `{"0": 10}` is used, and minimal roi is disabled unless your trade generates 1000% profit.
### Understand stoploss
`stoploss` is loss in percentage that should trigger a sale.
For example value `-0.10` will cause immediate sell if the
The `stoploss` configuration parameter is loss in percentage that should trigger a sale.
For example, value `-0.10` will cause immediate sell if the
profit dips below -10% for a given trade. This parameter is optional.
Most of the strategy files already include the optimal `stoploss`
value. This parameter is optional. If you use it, it will take over the
value. This parameter is optional. If you use it in the configuration file, it will take over the
`stoploss` value from the strategy file.
### Understand trailing stoploss
@ -137,40 +145,51 @@ Go to the [trailing stoploss Documentation](stoploss.md) for details on trailing
### Understand initial_state
`initial_state` is an optional field that defines the initial application state.
The `initial_state` configuration parameter is an optional field that defines the initial application state.
Possible values are `running` or `stopped`. (default=`running`)
If the value is `stopped` the bot has to be started with `/start` first.
### Understand forcebuy_enable
`forcebuy_enable` enables the usage of forcebuy commands via Telegram.
The `forcebuy_enable` configuration parameter enables the usage of forcebuy commands via Telegram.
This is disabled for security reasons by default, and will show a warning message on startup if enabled.
You send `/forcebuy ETH/BTC` to the bot, who buys the pair and holds it until a regular sell-signal appears (ROI, stoploss, /forcesell).
For example, you can send `/forcebuy ETH/BTC` Telegram command when this feature if enabled to the bot,
who then buys the pair and holds it until a regular sell-signal (ROI, stoploss, /forcesell) appears.
This can be dangerous with some strategies, so use with care.
Can be dangerous with some strategies, so use with care
See [the telegram documentation](telegram-usage.md) for details on usage.
### Understand process_throttle_secs
`process_throttle_secs` is an optional field that defines in seconds how long the bot should wait
The `process_throttle_secs` configuration parameter is an optional field that defines in seconds how long the bot should wait
before asking the strategy if we should buy or a sell an asset. After each wait period, the strategy is asked again for
every opened trade wether or not we should sell, and for all the remaining pairs (either the dynamic list of pairs or
the static list of pairs) if we should buy.
### Understand ask_last_balance
`ask_last_balance` sets the bidding price. Value `0.0` will use `ask` price, `1.0` will
The `ask_last_balance` configuration parameter sets the bidding price. Value `0.0` will use `ask` price, `1.0` will
use the `last` price and values between those interpolate between ask and last
price. Using `ask` price will guarantee quick success in bid, but bot will also
end up paying more then would probably have been necessary.
### Understand order_types
`order_types` contains a dict mapping order-types to market-types as well as stoploss on or off exchange type and stoploss on exchange update interval in seconds. This allows to buy using limit orders, sell using limit-orders, and create stoploss orders using market. It also allows to set the stoploss "on exchange" which means stoploss order would be placed immediately once the buy order is fulfilled. In case stoploss on exchange and `trailing_stop` are both set, then the bot will use `stoploss_on_exchange_interval` to check it periodically and update it if necessary (e.x. in case of trailing stoploss).
This can be set in the configuration or in the strategy. Configuration overwrites strategy configurations.
The `order_types` configuration parameter contains a dict mapping order-types to
market-types as well as stoploss on or off exchange type and stoploss on exchange
update interval in seconds. This allows to buy using limit orders, sell using
limit-orders, and create stoploss orders using market. It also allows to set the
stoploss "on exchange" which means stoploss order would be placed immediately once
the buy order is fulfilled. In case stoploss on exchange and `trailing_stop` are
both set, then the bot will use `stoploss_on_exchange_interval` to check it periodically
and update it if necessary (e.x. in case of trailing stoploss).
This can be set in the configuration file or in the strategy.
Values set in the configuration file overwrites values set in the strategy.
If this is configured, all 4 values (`"buy"`, `"sell"`, `"stoploss"` and `"stoploss_on_exchange"`) need to be present, otherwise the bot warn about it and will fail to start.
The below is the default which is used if this is not configured in either Strategy or configuration.
If this is configured, all 4 values (`buy`, `sell`, `stoploss` and
`stoploss_on_exchange`) need to be present, otherwise the bot will warn about it and fail to start.
The below is the default which is used if this is not configured in either strategy or configuration file.
```python
"order_types": {
@ -184,22 +203,44 @@ The below is the default which is used if this is not configured in either Strat
!!! Note
Not all exchanges support "market" orders.
The following message will be shown if your exchange does not support market orders: `"Exchange <yourexchange> does not support market orders."`
The following message will be shown if your exchange does not support market orders:
`"Exchange <yourexchange> does not support market orders."`
!!! Note
stoploss on exchange interval is not mandatory. Do not change it's value if you are unsure of what you are doing. For more information about how stoploss works please read [the stoploss documentation](stoploss.md).
Stoploss on exchange interval is not mandatory. Do not change its value if you are
unsure of what you are doing. For more information about how stoploss works please
read [the stoploss documentation](stoploss.md).
!!! Note
In case of stoploss on exchange if the stoploss is cancelled manually then
the bot would recreate one.
### Understand order_time_in_force
`order_time_in_force` defines the policy by which the order is executed on the exchange. Three commonly used time in force are:<br/>
**GTC (Goog Till Canceled):**
This is most of the time the default time in force. It means the order will remain on exchange till it is canceled by user. It can be fully or partially fulfilled. If partially fulfilled, the remaining will stay on the exchange till cancelled.<br/>
The `order_time_in_force` configuration parameter defines the policy by which the order
is executed on the exchange. Three commonly used time in force are:
**GTC (Good Till Canceled):**
This is most of the time the default time in force. It means the order will remain
on exchange till it is canceled by user. It can be fully or partially fulfilled.
If partially fulfilled, the remaining will stay on the exchange till cancelled.
**FOK (Full Or Kill):**
It means if the order is not executed immediately AND fully then it is canceled by the exchange.<br/>
It means if the order is not executed immediately AND fully then it is canceled by the exchange.
**IOC (Immediate Or Canceled):**
It is the same as FOK (above) except it can be partially fulfilled. The remaining part is automatically cancelled by the exchange.
<br/>
`order_time_in_force` contains a dict buy and sell time in force policy. This can be set in the configuration or in the strategy. Configuration overwrites strategy configurations.<br/>
possible values are: `gtc` (default), `fok` or `ioc`.<br/>
It is the same as FOK (above) except it can be partially fulfilled. The remaining part
is automatically cancelled by the exchange.
The `order_time_in_force` parameter contains a dict with buy and sell time in force policy values.
This can be set in the configuration file or in the strategy.
Values set in the configuration file overwrites values set in the strategy.
The possible values are: `gtc` (default), `fok` or `ioc`.
``` python
"order_time_in_force": {
"buy": "gtc",
@ -208,11 +249,12 @@ possible values are: `gtc` (default), `fok` or `ioc`.<br/>
```
!!! Warning
This is an ongoing work. For now it is supported only for binance and only for buy orders. Please don't change the default value unless you know what you are doing.
This is an ongoing work. For now it is supported only for binance and only for buy orders.
Please don't change the default value unless you know what you are doing.
### What values for exchange.name?
### Exchange configuration
Freqtrade is based on [CCXT library](https://github.com/ccxt/ccxt) that supports 115 cryptocurrency
Freqtrade is based on [CCXT library](https://github.com/ccxt/ccxt) that supports over 100 cryptocurrency
exchange markets and trading APIs. The complete up-to-date list can be found in the
[CCXT repo homepage](https://github.com/ccxt/ccxt/tree/master/python). However, the bot was tested
with only Bittrex and Binance.
@ -224,35 +266,65 @@ The bot was tested with the following exchanges:
Feel free to test other exchanges and submit your PR to improve the bot.
### What values for fiat_display_currency?
#### Sample exchange configuration
A exchange configuration for "binance" would look as follows:
```json
"exchange": {
"name": "binance",
"key": "your_exchange_key",
"secret": "your_exchange_secret",
"ccxt_config": {"enableRateLimit": true},
"ccxt_async_config": {
"enableRateLimit": true,
"rateLimit": 200
},
```
This configuration enables binance, as well as rate limiting to avoid bans from the exchange.
`"rateLimit": 200` defines a wait-event of 0.2s between each call. This can also be completely disabled by setting `"enableRateLimit"` to false.
!!! Note
Optimal settings for rate limiting depend on the exchange and the size of the whitelist, so an ideal parameter will vary on many other settings.
We try to provide sensible defaults per exchange where possible, if you encounter bans please make sure that `"enableRateLimit"` is enabled and increase the `"rateLimit"` parameter step by step.
### What values can be used for fiat_display_currency?
The `fiat_display_currency` configuration parameter sets the base currency to use for the
conversion from coin to fiat in the bot Telegram reports.
The valid values are:
`fiat_display_currency` set the base currency to use for the conversion from coin to fiat in Telegram.
The valid values are:<br/>
```json
"AUD", "BRL", "CAD", "CHF", "CLP", "CNY", "CZK", "DKK", "EUR", "GBP", "HKD", "HUF", "IDR", "ILS", "INR", "JPY", "KRW", "MXN", "MYR", "NOK", "NZD", "PHP", "PKR", "PLN", "RUB", "SEK", "SGD", "THB", "TRY", "TWD", "ZAR", "USD"
```
In addition to FIAT currencies, a range of cryto currencies are supported.
In addition to fiat currencies, a range of cryto currencies are supported.
The valid values are:
```json
"BTC", "ETH", "XRP", "LTC", "BCH", "USDT"
```
## Switch to dry-run mode
## Switch to Dry-run mode
We recommend starting the bot in dry-run mode to see how your bot will
behave and how is the performance of your strategy. In Dry-run mode the
We recommend starting the bot in the Dry-run mode to see how your bot will
behave and what is the performance of your strategy. In the Dry-run mode the
bot does not engage your money. It only runs a live simulation without
creating trades.
creating trades on the exchange.
1. Edit your `config.json` file
2. Switch dry-run to true and specify db_url for a persistent db
1. Edit your `config.json` configuration file.
2. Switch `dry-run` to `true` and specify `db_url` for a persistence database.
```json
"dry_run": true,
"db_url": "sqlite:///tradesv3.dryrun.sqlite",
```
3. Remove your Exchange API key (change them by fake api credentials)
3. Remove your Exchange API key and secrete (change them by empty values or fake credentials):
```json
"exchange": {
@ -263,37 +335,47 @@ creating trades.
}
```
Once you will be happy with your bot performance, you can switch it to
production mode.
Once you will be happy with your bot performance running in the Dry-run mode,
you can switch it to production mode.
### Dynamic Pairlists
Dynamic pairlists select pairs for you based on the logic configured.
The bot runs against all pairs (with that stake) on the exchange, and a number of assets (`number_assets`) is selected based on the selected criteria.
The bot runs against all pairs (with that stake) on the exchange, and a number of assets
(`number_assets`) is selected based on the selected criteria.
By default, a Static Pairlist is used (configured as `"pair_whitelist"` under the `"exchange"` section of this configuration).
By default, the `StaticPairList` method is used.
The Pairlist method is configured as `pair_whitelist` parameter under the `exchange`
section of the configuration.
**Available Pairlist methods:**
* `"StaticPairList"`
* uses configuration from `exchange.pair_whitelist` and `exchange.pair_blacklist`
* `"VolumePairList"`
* Formerly available as `--dynamic-whitelist [<number_assets>]`
* Selects `number_assets` top pairs based on `sort_key`, which can be one of `askVolume`, `bidVolume` and `quoteVolume`, defaults to `quoteVolume`.
* `StaticPairList`
* It uses configuration from `exchange.pair_whitelist` and `exchange.pair_blacklist`.
* `VolumePairList`
* Formerly available as `--dynamic-whitelist [<number_assets>]`. This command line
option is deprecated and should no longer be used.
* It selects `number_assets` top pairs based on `sort_key`, which can be one of
`askVolume`, `bidVolume` and `quoteVolume`, defaults to `quoteVolume`.
* There is a possibility to filter low-value coins that would not allow setting a stop loss
(set `precision_filter` parameter to `true` for this).
Example:
```json
"pairlist": {
"method": "VolumePairList",
"config": {
"number_assets": 20,
"sort_key": "quoteVolume"
"sort_key": "quoteVolume",
"precision_filter": false
}
},
```
## Switch to production mode
In production mode, the bot will engage your money. Be careful a wrong
In production mode, the bot will engage your money. Be careful, since a wrong
strategy can lose all your money. Be aware of what you are doing when
you run it in production mode.

31
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@ -0,0 +1,31 @@
# Deprecated features
This page contains description of the command line arguments, configuration parameters
and the bot features that were declared as DEPRECATED by the bot development team
and are no longer supported. Please avoid their usage in your configuration.
### The **--dynamic-whitelist** command line option
Per default `--dynamic-whitelist` will retrieve the 20 currencies based
on BaseVolume. This value can be changed when you run the script.
**By Default**
Get the 20 currencies based on BaseVolume.
```bash
python3 freqtrade --dynamic-whitelist
```
**Customize the number of currencies to retrieve**
Get the 30 currencies based on BaseVolume.
```bash
python3 freqtrade --dynamic-whitelist 30
```
**Exception**
`--dynamic-whitelist` must be greater than 0. If you enter 0 or a
negative value (e.g -2), `--dynamic-whitelist` will use the default
value (20).

217
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@ -3,165 +3,213 @@
This page explains how to use Edge Positioning module in your bot in order to enter into a trade only if the trade has a reasonable win rate and risk reward ratio, and consequently adjust your position size and stoploss.
!!! Warning
Edge positioning is not compatible with dynamic whitelist. it overrides dynamic whitelist.
Edge positioning is not compatible with dynamic whitelist. If enabled, it overrides the dynamic whitelist option.
!!! Note
Edge won't consider anything else than buy/sell/stoploss signals. So trailing stoploss, ROI, and everything else will be ignored in its calculation.
Edge does not consider anything else than buy/sell/stoploss signals. So trailing stoploss, ROI, and everything else are ignored in its calculation.
## Introduction
Trading is all about probability. No one can claim that he has a strategy working all the time. You have to assume that sometimes you lose.<br/><br/>
But it doesn't mean there is no rule, it only means rules should work "most of the time". Let's play a game: we toss a coin, heads: I give you 10$, tails: You give me 10$. Is it an interesting game ? no, it is quite boring, isn't it?<br/><br/>
But let's say the probability that we have heads is 80%, and the probability that we have tails is 20%. Now it is becoming interesting ...
That means 10$ x 80% versus 10$ x 20%. 8$ versus 2$. That means over time you will win 8$ risking only 2$ on each toss of coin.<br/><br/>
Let's complicate it more: you win 80% of the time but only 2$, I win 20% of the time but 8$. The calculation is: 80% * 2$ versus 20% * 8$. It is becoming boring again because overtime you win $1.6$ (80% x 2$) and me $1.6 (20% * 8$) too.<br/><br/>
The question is: How do you calculate that? how do you know if you wanna play?
Trading is all about probability. No one can claim that he has a strategy working all the time. You have to assume that sometimes you lose.
But it doesn't mean there is no rule, it only means rules should work "most of the time". Let's play a game: we toss a coin, heads: I give you 10$, tails: you give me 10$. Is it an interesting game? No, it's quite boring, isn't it?
But let's say the probability that we have heads is 80% (because our coin has the displaced distribution of mass or other defect), and the probability that we have tails is 20%. Now it is becoming interesting...
That means 10$ X 80% versus 10$ X 20%. 8$ versus 2$. That means over time you will win 8$ risking only 2$ on each toss of coin.
Let's complicate it more: you win 80% of the time but only 2$, I win 20% of the time but 8$. The calculation is: 80% X 2$ versus 20% X 8$. It is becoming boring again because overtime you win $1.6$ (80% X 2$) and me $1.6 (20% X 8$) too.
The question is: How do you calculate that? How do you know if you wanna play?
The answer comes to two factors:
- Win Rate
- Risk Reward Ratio
### Win Rate
Means over X trades what is the percentage of winning trades to total number of trades (note that we don't consider how much you gained but only If you won or not).
Win Rate (*W*) is is the mean over some amount of trades (*N*) what is the percentage of winning trades to total number of trades (note that we don't consider how much you gained but only if you won or not).
W = (Number of winning trades) / (Total number of trades) = (Number of winning trades) / N
`W = (Number of winning trades) / (Total number of trades)`
Complementary Loss Rate (*L*) is defined as
L = (Number of losing trades) / (Total number of trades) = (Number of losing trades) / N
or, which is the same, as
L = 1 – W
### Risk Reward Ratio
Risk Reward Ratio is a formula used to measure the expected gains of a given investment against the risk of loss. It is basically what you potentially win divided by what you potentially lose:
Risk Reward Ratio (*R*) is a formula used to measure the expected gains of a given investment against the risk of loss. It is basically what you potentially win divided by what you potentially lose:
`R = Profit / Loss`
R = Profit / Loss
Over time, on many trades, you can calculate your risk reward by dividing your average profit on winning trades by your average loss on losing trades:
`Average profit = (Sum of profits) / (Number of winning trades)`
Average profit = (Sum of profits) / (Number of winning trades)
`Average loss = (Sum of losses) / (Number of losing trades)`
Average loss = (Sum of losses) / (Number of losing trades)
`R = (Average profit) / (Average loss)`
R = (Average profit) / (Average loss)
### Expectancy
At this point we can combine *W* and *R* to create an expectancy ratio. This is a simple process of multiplying the risk reward ratio by the percentage of winning trades and subtracting the percentage of losing trades, which is calculated as follows:
At this point we can combine W and R to create an expectancy ratio. This is a simple process of multiplying the risk reward ratio by the percentage of winning trades, and subtracting the percentage of losing trades, which is calculated as follows:
Expectancy Ratio = (Risk Reward Ratio x Win Rate) – Loss Rate
Expectancy Ratio = (Risk Reward Ratio X Win Rate) – Loss Rate = (R X W) – L
So lets say your Win rate is 28% and your Risk Reward Ratio is 5:
`Expectancy = (5 * 0.28) - 0.72 = 0.68`
Expectancy = (5 X 0.28) – 0.72 = 0.68
Superficially, this means that on average you expect this strategy’s trades to return .68 times the size of your losers. This is important for two reasons: First, it may seem obvious, but you know right away that you have a positive return. Second, you now have a number you can compare to other candidate systems to make decisions about which ones you employ.
Superficially, this means that on average you expect this strategy’s trades to return .68 times the size of your loses. This is important for two reasons: First, it may seem obvious, but you know right away that you have a positive return. Second, you now have a number you can compare to other candidate systems to make decisions about which ones you employ.
It is important to remember that any system with an expectancy greater than 0 is profitable using past data. The key is finding one that will be profitable in the future.
You can also use this number to evaluate the effectiveness of modifications to this system.
You can also use this value to evaluate the effectiveness of modifications to this system.
**NOTICE:** It's important to keep in mind that Edge is testing your expectancy using historical data , there's no guarantee that you will have a similar edge in the future. It's still vital to do this testing in order to build confidence in your methodology, but be wary of "curve-fitting" your approach to the historical data as things are unlikely to play out the exact same way for future trades.
**NOTICE:** It's important to keep in mind that Edge is testing your expectancy using historical data, there's no guarantee that you will have a similar edge in the future. It's still vital to do this testing in order to build confidence in your methodology, but be wary of "curve-fitting" your approach to the historical data as things are unlikely to play out the exact same way for future trades.
## How does it work?
If enabled in config, Edge will go through historical data with a range of stoplosses in order to find buy and sell/stoploss signals. It then calculates win rate and expectancy over X trades for each stoploss. Here is an example:
If enabled in config, Edge will go through historical data with a range of stoplosses in order to find buy and sell/stoploss signals. It then calculates win rate and expectancy over *N* trades for each stoploss. Here is an example:
| Pair | Stoploss | Win Rate | Risk Reward Ratio | Expectancy |
|----------|:-------------:|-------------:|------------------:|-----------:|
| XZC/ETH | -0.03 | 0.52 |1.359670 | 0.228 |
| XZC/ETH | -0.01 | 0.50 |1.176384 | 0.088 |
| XZC/ETH | -0.02 | 0.51 |1.115941 | 0.079 |
| XZC/ETH | -0.03 | 0.52 |1.359670 | 0.228 |
| XZC/ETH | -0.04 | 0.51 |1.234539 | 0.117 |
The goal here is to find the best stoploss for the strategy in order to have the maximum expectancy. In the above example stoploss at 3% leads to the maximum expectancy according to historical data.
Edge then forces stoploss to your strategy dynamically.
Edge module then forces stoploss value it evaluated to your strategy dynamically.
### Position size
Edge dictates the stake amount for each trade to the bot according to the following factors:
Edge also dictates the stake amount for each trade to the bot according to the following factors:
- Allowed capital at risk
- Stoploss
Allowed capital at risk is calculated as follows:
**allowed capital at risk** = **capital_available_percentage** X **allowed risk per trade**
Allowed capital at risk = (Capital available_percentage) X (Allowed risk per trade)
**Stoploss** is calculated as described above against historical data.
Stoploss is calculated as described above against historical data.
Your position size then will be:
**position size** = **allowed capital at risk** / **stoploss**
Position size = (Allowed capital at risk) / Stoploss
Example:<br/>
Let's say the stake currency is ETH and you have 10 ETH on the exchange, your **capital_available_percentage** is 50% and you would allow 1% of risk for each trade. thus your available capital for trading is **10 x 0.5 = 5 ETH** and allowed capital at risk would be **5 x 0.01 = 0.05 ETH**. <br/>
Let's assume Edge has calculated that for **XLM/ETH** market your stoploss should be at 2%. So your position size will be **0.05 / 0.02 = 2.5ETH**.<br/>
Bot takes a position of 2.5ETH on XLM/ETH (call it trade 1). Up next, you receive another buy signal while trade 1 is still open. This time on BTC/ETH market. Edge calculated stoploss for this market at 4%. So your position size would be 0.05 / 0.04 = 1.25ETH (call it trade 2).<br/>
Note that available capital for trading didn’t change for trade 2 even if you had already trade 1. The available capital doesn’t mean the free amount on your wallet.<br/>
Now you have two trades open. The Bot receives yet another buy signal for another market: **ADA/ETH**. This time the stoploss is calculated at 1%. So your position size is **0.05 / 0.01 = 5ETH**. But there are already 4ETH blocked in two previous trades. So the position size for this third trade would be 1ETH.<br/>
Available capital doesn’t change before a position is sold. Let’s assume that trade 1 receives a sell signal and it is sold with a profit of 1ETH. Your total capital on exchange would be 11 ETH and the available capital for trading becomes 5.5ETH. <br/>
So the Bot receives another buy signal for trade 4 with a stoploss at 2% then your position size would be **0.055 / 0.02 = 2.75**.
Example:
Let's say the stake currency is ETH and you have 10 ETH on the exchange, your capital available percentage is 50% and you would allow 1% of risk for each trade. thus your available capital for trading is **10 x 0.5 = 5 ETH** and allowed capital at risk would be **5 x 0.01 = 0.05 ETH**.
Let's assume Edge has calculated that for **XLM/ETH** market your stoploss should be at 2%. So your position size will be **0.05 / 0.02 = 2.5 ETH**.
Bot takes a position of 2.5 ETH on XLM/ETH (call it trade 1). Up next, you receive another buy signal while trade 1 is still open. This time on **BTC/ETH** market. Edge calculated stoploss for this market at 4%. So your position size would be 0.05 / 0.04 = 1.25 ETH (call it trade 2).
Note that available capital for trading didn’t change for trade 2 even if you had already trade 1. The available capital doesn’t mean the free amount on your wallet.
Now you have two trades open. The bot receives yet another buy signal for another market: **ADA/ETH**. This time the stoploss is calculated at 1%. So your position size is **0.05 / 0.01 = 5 ETH**. But there are already 3.75 ETH blocked in two previous trades. So the position size for this third trade would be **5 – 3.75 = 1.25 ETH**.
Available capital doesn’t change before a position is sold. Let’s assume that trade 1 receives a sell signal and it is sold with a profit of 1 ETH. Your total capital on exchange would be 11 ETH and the available capital for trading becomes 5.5 ETH.
So the Bot receives another buy signal for trade 4 with a stoploss at 2% then your position size would be **0.055 / 0.02 = 2.75 ETH**.
## Configurations
Edge has following configurations:
Edge module has following configuration options:
#### enabled
If true, then Edge will run periodically.<br/>
(default to false)
If true, then Edge will run periodically.
(defaults to false)
#### process_throttle_secs
How often should Edge run in seconds? <br/>
(default to 3600 so one hour)
How often should Edge run in seconds?
(defaults to 3600 so one hour)
#### calculate_since_number_of_days
Number of days of data against which Edge calculates Win Rate, Risk Reward and Expectancy
Note that it downloads historical data so increasing this number would lead to slowing down the bot.<br/>
(default to 7)
Note that it downloads historical data so increasing this number would lead to slowing down the bot.
(defaults to 7)
#### capital_available_percentage
This is the percentage of the total capital on exchange in stake currency. <br/>
As an example if you have 10 ETH available in your wallet on the exchange and this value is 0.5 (which is 50%), then the bot will use a maximum amount of 5 ETH for trading and considers it as available capital.<br/>
(default to 0.5)
This is the percentage of the total capital on exchange in stake currency.
As an example if you have 10 ETH available in your wallet on the exchange and this value is 0.5 (which is 50%), then the bot will use a maximum amount of 5 ETH for trading and considers it as available capital.
(defaults to 0.5)
#### allowed_risk
Percentage of allowed risk per trade.<br/>
(default to 0.01 [1%])
Percentage of allowed risk per trade.
(defaults to 0.01 so 1%)
#### stoploss_range_min
Minimum stoploss.<br/>
(default to -0.01)
Minimum stoploss.
(defaults to -0.01)
#### stoploss_range_max
Maximum stoploss.<br/>
(default to -0.10)
Maximum stoploss.
(defaults to -0.10)
#### stoploss_range_step
As an example if this is set to -0.01 then Edge will test the strategy for [-0.01, -0,02, -0,03 ..., -0.09, -0.10] ranges.
Note than having a smaller step means having a bigger range which could lead to slow calculation. <br/>
if you set this parameter to -0.001, you then slow down the Edge calculation by a factor of 10. <br/>
(default to -0.01)
As an example if this is set to -0.01 then Edge will test the strategy for \[-0.01, -0,02, -0,03 ..., -0.09, -0.10\] ranges.
Note than having a smaller step means having a bigger range which could lead to slow calculation.
If you set this parameter to -0.001, you then slow down the Edge calculation by a factor of 10.
(defaults to -0.01)
#### minimum_winrate
It filters pairs which don't have at least minimum_winrate.
This comes handy if you want to be conservative and don't comprise win rate in favor of risk reward ratio.<br/>
(default to 0.60)
It filters out pairs which don't have at least minimum_winrate.
This comes handy if you want to be conservative and don't comprise win rate in favour of risk reward ratio.
(defaults to 0.60)
#### minimum_expectancy
It filters paris which have an expectancy lower than this number .
Having an expectancy of 0.20 means if you put 10$ on a trade you expect a 12$ return.<br/>
(default to 0.20)
It filters out pairs which have the expectancy lower than this number.
Having an expectancy of 0.20 means if you put 10$ on a trade you expect a 12$ return.
(defaults to 0.20)
#### min_trade_number
When calculating W and R and E (expectancy) against historical data, you always want to have a minimum number of trades. The more this number is the more Edge is reliable. Having a win rate of 100% on a single trade doesn't mean anything at all. But having a win rate of 70% over past 100 trades means clearly something. <br/>
(default to 10, it is highly recommended not to decrease this number)
When calculating *W*, *R* and *E* (expectancy) against historical data, you always want to have a minimum number of trades. The more this number is the more Edge is reliable.
Having a win rate of 100% on a single trade doesn't mean anything at all. But having a win rate of 70% over past 100 trades means clearly something.
(defaults to 10, it is highly recommended not to decrease this number)
#### max_trade_duration_minute
Edge will filter out trades with long duration. If a trade is profitable after 1 month, it is hard to evaluate the strategy based on it. But if most of trades are profitable and they have maximum duration of 30 minutes, then it is clearly a good sign.<br/>
**NOTICE:** While configuring this value, you should take into consideration your ticker interval. as an example filtering out trades having duration less than one day for a strategy which has 4h interval does not make sense. default value is set assuming your strategy interval is relatively small (1m or 5m, etc).<br/>
(default to 1 day, 1440 = 60 * 24)
Edge will filter out trades with long duration. If a trade is profitable after 1 month, it is hard to evaluate the strategy based on it. But if most of trades are profitable and they have maximum duration of 30 minutes, then it is clearly a good sign.
**NOTICE:** While configuring this value, you should take into consideration your ticker interval. As an example filtering out trades having duration less than one day for a strategy which has 4h interval does not make sense. Default value is set assuming your strategy interval is relatively small (1m or 5m, etc.).
(defaults to 1 day, i.e. to 60 * 24 = 1440 minutes)
#### remove_pumps
Edge will remove sudden pumps in a given market while going through historical data. However, given that pumps happen very often in crypto markets, we recommend you keep this off.<br/>
(default to false)
Edge will remove sudden pumps in a given market while going through historical data. However, given that pumps happen very often in crypto markets, we recommend you keep this off.
(defaults to false)
## Running Edge independently
You can run Edge independently in order to see in details the result. Here is an example:
```bash
python3 ./freqtrade/main.py edge
python3 freqtrade edge
```
An example of its output:
@ -185,28 +233,31 @@ An example of its output:
| NEBL/BTC | -0.03 | 0.63 | 1.29 | 0.58 | 0.44 | 19 | 59 |
### Update cached pairs with the latest data
```bash
python3 ./freqtrade/main.py edge --refresh-pairs-cached
python3 freqtrade edge --refresh-pairs-cached
```
### Precising stoploss range
```bash
python3 ./freqtrade/main.py edge --stoplosses=-0.01,-0.1,-0.001 #min,max,step
python3 freqtrade edge --stoplosses=-0.01,-0.1,-0.001 #min,max,step
```
### Advanced use of timerange
```bash
python3 ./freqtrade/main.py edge --timerange=20181110-20181113
python3 freqtrade edge --timerange=20181110-20181113
```
Doing --timerange=-200 will get the last 200 timeframes from your inputdata. You can also specify specific dates, or a range span indexed by start and stop.
Doing `--timerange=-200` will get the last 200 timeframes from your inputdata. You can also specify specific dates, or a range span indexed by start and stop.
The full timerange specification:
* Use last 123 tickframes of data: --timerange=-123
* Use first 123 tickframes of data: --timerange=123-
* Use tickframes from line 123 through 456: --timerange=123-456
* Use tickframes till 2018/01/31: --timerange=-20180131
* Use tickframes since 2018/01/31: --timerange=20180131-
* Use tickframes since 2018/01/31 till 2018/03/01 : --timerange=20180131-20180301
* Use tickframes between POSIX timestamps 1527595200 1527618600: --timerange=1527595200-1527618600
* Use last 123 tickframes of data: `--timerange=-123`
* Use first 123 tickframes of data: `--timerange=123-`
* Use tickframes from line 123 through 456: `--timerange=123-456`
* Use tickframes till 2018/01/31: `--timerange=-20180131`
* Use tickframes since 2018/01/31: `--timerange=20180131-`
* Use tickframes since 2018/01/31 till 2018/03/01 : `--timerange=20180131-20180301`
* Use tickframes between POSIX timestamps 1527595200 1527618600: `--timerange=1527595200-1527618600`

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@ -1,4 +1,6 @@
# freqtrade FAQ
# Freqtrade FAQ
### Freqtrade commons
#### I have waited 5 minutes, why hasn't the bot made any trades yet?!
@ -17,8 +19,7 @@ of course constantly aim to improve the bot but it will _always_ be a
gamble, which should leave you with modest wins on monthly basis but
you can't say much from few trades.
#### I’d like to change the stake amount. Can I just stop the bot with
/stop and then change the config.json and run it again?
#### I’d like to change the stake amount. Can I just stop the bot with /stop and then change the config.json and run it again?
Not quite. Trades are persisted to a database but the configuration is
currently only read when the bot is killed and restarted. `/stop` more
@ -29,42 +30,60 @@ like pauses. You can stop your bot, adjust settings and start it again.
That's great. We have a nice backtesting and hyperoptimizing setup. See
the tutorial [here|Testing-new-strategies-with-Hyperopt](bot-usage.md#hyperopt-commands).
#### Is there a setting to only SELL the coins being held and not
perform anymore BUYS?
#### Is there a setting to only SELL the coins being held and not perform anymore BUYS?
You can use the `/forcesell all` command from Telegram.
### How many epoch do I need to get a good Hyperopt result?
### Hyperopt module
#### How many epoch do I need to get a good Hyperopt result?
Per default Hyperopts without `-e` or `--epochs` parameter will only
run 100 epochs, means 100 evals of your triggers, guards, .... Too few
run 100 epochs, means 100 evals of your triggers, guards, ... Too few
to find a great result (unless if you are very lucky), so you probably
have to run it for 10.000 or more. But it will take an eternity to
compute.
We recommend you to run it at least 10.000 epochs:
```bash
python3 ./freqtrade/main.py hyperopt -e 10000
python3 freqtrade hyperopt -e 10000
```
or if you want intermediate result to see
```bash
for i in {1..100}; do python3 ./freqtrade/main.py hyperopt -e 100; done
for i in {1..100}; do python3 freqtrade hyperopt -e 100; done
```
#### Why it is so long to run hyperopt?
Finding a great Hyperopt results takes time.
If you wonder why it takes a while to find great hyperopt results
This answer was written during the under the release 0.15.1, when we had
:
This answer was written during the under the release 0.15.1, when we had:
- 8 triggers
- 9 guards: let's say we evaluate even 10 values from each
- 1 stoploss calculation: let's say we want 10 values from that too to
be evaluated
- 1 stoploss calculation: let's say we want 10 values from that too to be evaluated
The following calculation is still very rough and not very precise
but it will give the idea. With only these triggers and guards there is
already 8*10^9*10 evaluations. A roughly total of 80 billion evals.
already 8\*10^9\*10 evaluations. A roughly total of 80 billion evals.
Did you run 100 000 evals? Congrats, you've done roughly 1 / 100 000 th
of the search space.
### Edge module
#### Edge implements interesting approach for controlling position size, is there any theory behind it?
The Edge module is mostly a result of brainstorming of [@mishaker](https://github.com/mishaker) and [@creslinux](https://github.com/creslinux) freqtrade team members.
You can find further info on expectancy, winrate, risk management and position size in the following sources:
- https://www.tradeciety.com/ultimate-math-guide-for-traders/
- http://www.vantharp.com/tharp-concepts/expectancy.asp
- https://samuraitradingacademy.com/trading-expectancy/
- https://www.learningmarkets.com/determining-expectancy-in-your-trading/
- http://www.lonestocktrader.com/make-money-trading-positive-expectancy/
- https://www.babypips.com/trading/trade-expectancy-matter

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@ -152,7 +152,7 @@ Because hyperopt tries a lot of combinations to find the best parameters it will
We strongly recommend to use `screen` or `tmux` to prevent any connection loss.
```bash
python3 ./freqtrade/main.py --hyperopt <hyperoptname> -c config.json hyperopt -e 5000 --spaces all
python3 freqtrade -c config.json hyperopt --customhyperopt <hyperoptname> -e 5000 --spaces all
```
Use `<hyperoptname>` as the name of the custom hyperopt used.
@ -163,7 +163,7 @@ running at least several thousand evaluations.
The `--spaces all` flag determines that all possible parameters should be optimized. Possibilities are listed below.
!!! Warning
When switching parameters or changing configuration options, the file `user_data/hyperopt_results.pickle` should be removed. It's used to be able to continue interrupted calculations, but does not detect changes to settings or the hyperopt file.
When switching parameters or changing configuration options, the file `user_data/hyperopt_results.pickle` should be removed. It's used to be able to continue interrupted calculations, but does not detect changes to settings or the hyperopt file.
### Execute Hyperopt with Different Ticker-Data Source
@ -178,7 +178,7 @@ you want to use. The last N ticks/timeframes will be used.
Example:
```bash
python3 ./freqtrade/main.py hyperopt --timerange -200
python3 freqtrade hyperopt --timerange -200
```
### Running Hyperopt with Smaller Search Space
@ -285,11 +285,16 @@ This would translate to the following ROI table:
### Validate backtest result
Once the optimized strategy has been implemented into your strategy, you should backtest this strategy to make sure everything is working as expected.
To archive the same results (number of trades, ...) than during hyperopt, please use the command line flag `--disable-max-market-positions`.
This setting is the default for hyperopt for speed reasons. You can overwrite this in the configuration by setting `"position_stacking"=false` or by changing the relevant line in your hyperopt file [here](https://github.com/freqtrade/freqtrade/blob/develop/freqtrade/optimize/hyperopt.py#L283).
To archive the same results (number of trades, ...) than during hyperopt, please use the command line flags `--disable-max-market-positions` and `--enable-position-stacking` for backtesting.
!!! Note:
Dry/live runs will **NOT** use position stacking - therefore it does make sense to also validate the strategy without this as it's closer to reality.
This configuration is the default in hyperopt for performance reasons.
You can overwrite position stacking in the configuration by explicitly setting `"position_stacking"=false` or by changing the relevant line in your hyperopt file [here](https://github.com/freqtrade/freqtrade/blob/develop/freqtrade/optimize/hyperopt.py#L191).
Enabling the market-position for hyperopt is currently not possible.
!!! Note
Dry/live runs will **NOT** use position stacking - therefore it does make sense to also validate the strategy without this as it's closer to reality.
## Next Step

30
docs/index.md
View File

@ -19,27 +19,27 @@ Freqtrade is a cryptocurrency trading bot written in Python.
Always start by running a trading bot in Dry-run and do not engage money before you understand how it works and what profit/loss you should expect.
We strongly recommend you to have coding and Python knowledge. Do not hesitate to read the source code and understand the mechanism of this bot.
We strongly recommend you to have basic coding skills and Python knowledge. Do not hesitate to read the source code and understand the mechanisms of this bot, algorithms and techniques implemented in it.
## Features
- Based on Python 3.6+: For botting on any operating system - Windows, macOS and Linux
- Persistence: Persistence is achieved through sqlite
- Dry-run: Run the bot without playing money.
- Backtesting: Run a simulation of your buy/sell strategy.
- Based on Python 3.6+: For botting on any operating system — Windows, macOS and Linux.
- Persistence: Persistence is achieved through sqlite database.
- Dry-run mode: Run the bot without playing money.
- Backtesting: Run a simulation of your buy/sell strategy with historical data.
- Strategy Optimization by machine learning: Use machine learning to optimize your buy/sell strategy parameters with real exchange data.
- Edge position sizing Calculate your win rate, risk reward ratio, the best stoploss and adjust your position size before taking a position for each specific market. Learn more
- Whitelist crypto-currencies: Select which crypto-currency you want to trade or use dynamic whitelists.
- Edge position sizing: Calculate your win rate, risk reward ratio, the best stoploss and adjust your position size before taking a position for each specific market.
- Whitelist crypto-currencies: Select which crypto-currency you want to trade or use dynamic whitelists based on market (pair) trade volume.
- Blacklist crypto-currencies: Select which crypto-currency you want to avoid.
- Manageable via Telegram: Manage the bot with Telegram
- Display profit/loss in fiat: Display your profit/loss in 33 fiat.
- Daily summary of profit/loss: Provide a daily summary of your profit/loss.
- Performance status report: Provide a performance status of your current trades.
- Manageable via Telegram: Manage the bot with Telegram.
- Display profit/loss in fiat: Display your profit/loss in any of 33 fiat currencies supported.
- Daily summary of profit/loss: Receive the daily summary of your profit/loss.
- Performance status report: Receive the performance status of your current trades.
## Requirements
### Uptodate clock
The clock must be accurate, syncronized to a NTP server very frequently to avoid problems with communication to the exchanges.
### Up to date clock
The clock on the system running the bot must be accurate, synchronized to a NTP server frequently enough to avoid problems with communication to the exchanges.
### Hardware requirements
To run this bot we recommend you a cloud instance with a minimum of:
@ -50,7 +50,7 @@ To run this bot we recommend you a cloud instance with a minimum of:
### Software requirements
- Python 3.6.x
- pip
- pip (pip3)
- git
- TA-Lib
- virtualenv (Recommended)
@ -59,7 +59,7 @@ To run this bot we recommend you a cloud instance with a minimum of:
## Support
Help / Slack
For any questions not covered by the documentation or for further information about the bot, we encourage you to join our slack channel.
For any questions not covered by the documentation or for further information about the bot, we encourage you to join our Slack channel.
Click [here](https://join.slack.com/t/highfrequencybot/shared_invite/enQtMjQ5NTM0OTYzMzY3LWMxYzE3M2MxNDdjMGM3ZTYwNzFjMGIwZGRjNTc3ZGU3MGE3NzdmZGMwNmU3NDM5ZTNmM2Y3NjRiNzk4NmM4OGE) to join Slack channel.

18
docs/installation.md
View File

@ -315,7 +315,6 @@ Before installing FreqTrade on a Raspberry Pi running the official Raspbian Imag
The following assumes that miniconda3 is installed and available in your environment. Last miniconda3 installation file use python 3.4, we will update to python 3.6 on this installation.
It's recommended to use (mini)conda for this as installation/compilation of `numpy`, `scipy` and `pandas` takes a long time.
If you have installed it from (mini)conda, you can remove `numpy`, `scipy`, and `pandas` from `requirements.txt` before you install it with `pip`.
Additional package to install on your Raspbian, `libffi-dev` required by cryptography (from python-telegram-bot).
@ -327,7 +326,7 @@ conda activate freqtrade
conda install scipy pandas numpy
sudo apt install libffi-dev
python3 -m pip install -r requirements.txt
python3 -m pip install -r requirements-pi.txt
python3 -m pip install -e .
```
@ -407,7 +406,7 @@ pip3 install -e .
If this is the first time you run the bot, ensure you are running it in Dry-run `"dry_run": true,` otherwise it will start to buy and sell coins.
```bash
python3.6 ./freqtrade/main.py -c config.json
python3.6 freqtrade -c config.json
```
*Note*: If you run the bot on a server, you should consider using [Docker](#automatic-installation---docker) a terminal multiplexer like `screen` or [`tmux`](https://en.wikipedia.org/wiki/Tmux) to avoid that the bot is stopped on logout.
@ -428,6 +427,19 @@ For this to be persistent (run when user is logged out) you'll need to enable `l
sudo loginctl enable-linger "$USER"
```
If you run the bot as a service, you can use systemd service manager as a software watchdog monitoring freqtrade bot
state and restarting it in the case of failures. If the `internals.sd_notify` parameter is set to true in the
configuration or the `--sd-notify` command line option is used, the bot will send keep-alive ping messages to systemd
using the sd_notify (systemd notifications) protocol and will also tell systemd its current state (Running or Stopped)
when it changes.
The `freqtrade.service.watchdog` file contains an example of the service unit configuration file which uses systemd
as the watchdog.
!!! Note
The sd_notify communication between the bot and the systemd service manager will not work if the bot runs in a
Docker container.
------
## Windows

2
docs/plotting.md
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@ -84,5 +84,5 @@ The `-p` pair argument, can be used to plot a single pair
Example
```
python3 scripts/plot_profit.py --datadir ../freqtrade/freqtrade/tests/testdata-20171221/ -p BTC_LTC
python3 scripts/plot_profit.py --datadir ../freqtrade/freqtrade/tests/testdata-20171221/ -p LTC/BTC
```

41
docs/sql_cheatsheet.md
View File

@ -1,5 +1,5 @@
# SQL Helper
This page constains some help if you want to edit your sqlite db.
This page contains some help if you want to edit your sqlite db.
## Install sqlite3
**Ubuntu/Debian installation**
@ -44,6 +44,14 @@ CREATE TABLE trades (
open_date DATETIME NOT NULL,
close_date DATETIME,
open_order_id VARCHAR,
stop_loss FLOAT,
initial_stop_loss FLOAT,
stoploss_order_id VARCHAR,
stoploss_last_update DATETIME,
max_rate FLOAT,
sell_reason VARCHAR,
strategy VARCHAR,
ticker_interval INTEGER,
PRIMARY KEY (id),
CHECK (is_open IN (0, 1))
);
@ -55,38 +63,45 @@ CREATE TABLE trades (
SELECT * FROM trades;
```
## Fix trade still open after a /forcesell
## Fix trade still open after a manual sell on the exchange
!!! Warning
Manually selling a pair on the exchange will not be detected by the bot and it will try to sell anyway. Whenever possible, forcesell <tradeid> should be used to accomplish the same thing.
It is strongly advised to backup your database file before making any manual changes.
!!! Note
This should not be necessary after /forcesell, as forcesell orders are closed automatically by the bot on the next iteration.
```sql
UPDATE trades
SET is_open=0, close_date=<close_date>, close_rate=<close_rate>, close_profit=close_rate/open_rate-1
SET is_open=0, close_date=<close_date>, close_rate=<close_rate>, close_profit=close_rate/open_rate-1, sell_reason=<sell_reason>
WHERE id=<trade_ID_to_update>;
```
**Example:**
##### Example
```sql
UPDATE trades
SET is_open=0, close_date='2017-12-20 03:08:45.103418', close_rate=0.19638016, close_profit=0.0496
SET is_open=0, close_date='2017-12-20 03:08:45.103418', close_rate=0.19638016, close_profit=0.0496, sell_reason='force_sell'
WHERE id=31;
```
## Insert manually a new trade
```sql
INSERT
INTO trades (exchange, pair, is_open, fee_open, fee_close, open_rate, stake_amount, amount, open_date)
VALUES ('BITTREX', 'BTC_<COIN>', 1, 0.0025, 0.0025, <open_rate>, <stake_amount>, <amount>, '<datetime>')
INSERT INTO trades (exchange, pair, is_open, fee_open, fee_close, open_rate, stake_amount, amount, open_date)
VALUES ('bittrex', 'ETH/BTC', 1, 0.0025, 0.0025, <open_rate>, <stake_amount>, <amount>, '<datetime>')
```
**Example:**
##### Example:
```sql
INSERT INTO trades (exchange, pair, is_open, fee_open, fee_close, open_rate, stake_amount, amount, open_date) VALUES ('BITTREX', 'BTC_ETC', 1, 0.0025, 0.0025, 0.00258580, 0.002, 0.7715262081, '2017-11-28 12:44:24.000000')
INSERT INTO trades (exchange, pair, is_open, fee_open, fee_close, open_rate, stake_amount, amount, open_date)
VALUES ('bittrex', 'ETH/BTC', 1, 0.0025, 0.0025, 0.00258580, 0.002, 0.7715262081, '2017-11-28 12:44:24.000000')
```
## Fix wrong fees in the table
If your DB was created before
[PR#200](https://github.com/freqtrade/freqtrade/pull/200) was merged
(before 12/23/17).
If your DB was created before [PR#200](https://github.com/freqtrade/freqtrade/pull/200) was merged (before 12/23/17).
```sql
UPDATE trades SET fee=0.0025 WHERE fee=0.005;

3
docs/stoploss.md
View File

@ -55,8 +55,11 @@ Both values can be configured in the main configuration file and requires `"trai
``` json
"trailing_stop_positive": 0.01,
"trailing_stop_positive_offset": 0.011,
"trailing_only_offset_is_reached": false
```
The 0.01 would translate to a 1% stop loss, once you hit 1.1% profit.
You should also make sure to have this value (`trailing_stop_positive_offset`) lower than your minimal ROI, otherwise minimal ROI will apply first and sell your trade.
If `"trailing_only_offset_is_reached": true` then the trailing stoploss is only activated once the offset is reached. Until then, the stoploss remains at the configured`stoploss`.

82
docs/telegram-usage.md
View File

@ -1,13 +1,13 @@
# Telegram usage
This page explains how to command your bot with Telegram.
## Prerequisite
To control your bot with Telegram, you need first to
[set up a Telegram bot](installation.md)
and add your Telegram API keys into your config file.
## Telegram commands
Per default, the Telegram bot shows predefined commands. Some commands
are only available by sending them to the bot. The table below list the
official commands. You can ask at any moment for help with `/help`.
@ -16,6 +16,7 @@ official commands. You can ask at any moment for help with `/help`.
|----------|---------|-------------|
| `/start` | | Starts the trader
| `/stop` | | Stops the trader
| `/stopbuy` | | Stops the trader from opening new trades. Gracefully closes open trades according to their rules.
| `/reload_conf` | | Reloads the configuration file
| `/status` | | Lists all open trades
| `/status table` | | List all open trades in a table format
@ -27,6 +28,9 @@ official commands. You can ask at any moment for help with `/help`.
| `/performance` | | Show performance of each finished trade grouped by pair
| `/balance` | | Show account balance per currency
| `/daily <n>` | 7 | Shows profit or loss per day, over the last n days
| `/whitelist` | | Show the current whitelist
| `/blacklist [pair]` | | Show the current blacklist, or adds a pair to the blacklist.
| `/edge` | | Show validated pairs by Edge if it is enabled.
| `/help` | | Show help message
| `/version` | | Show version
@ -43,22 +47,34 @@ Below, example of Telegram message you will receive for each command.
> `Stopping trader ...`
> **Status:** `stopped`
## /status
### /stopbuy
> **status:** `Setting max_open_trades to 0. Run /reload_conf to reset.`
Prevents the bot from opening new trades by temporarily setting "max_open_trades" to 0. Open trades will be handled via their regular rules (ROI / Sell-signal, stoploss, ...).
After this, give the bot time to close off open trades (can be checked via `/status table`).
Once all positions are sold, run `/stop` to completely stop the bot.
`/reload_conf` resets "max_open_trades" to the value set in the configuration and resets this command.
!!! warning
The stop-buy signal is ONLY active while the bot is running, and is not persisted anyway, so restarting the bot will cause this to reset.
### /status
For each open trade, the bot will send you the following message.
> **Trade ID:** `123`
> **Trade ID:** `123` `(since 1 days ago)`
> **Current Pair:** CVC/BTC
> **Open Since:** `1 days ago`
> **Amount:** `26.64180098`
> **Open Rate:** `0.00007489`
> **Close Rate:** `None`
> **Current Rate:** `0.00007489`
> **Close Profit:** `None`
> **Current Profit:** `12.95%`
> **Open Order:** `None`
> **Stoploss:** `0.00007389 (-0.02%)`
## /status table
### /status table
Return the status of all open trades in a table format.
```
@ -68,7 +84,7 @@ Return the status of all open trades in a table format.
123 CVC/BTC 1 h 12.95%
```
## /count
### /count
Return the number of trades used and available.
```
@ -77,7 +93,7 @@ current max
2 10
```
## /profit
### /profit
Return a summary of your profit/loss and performance.
@ -94,17 +110,19 @@ Return a summary of your profit/loss and performance.
> **Avg. Duration:** `2:33:45`
> **Best Performing:** `PAY/BTC: 50.23%`
## /forcesell <trade_id>
### /forcesell <trade_id>
> **BITTREX:** Selling BTC/LTC with limit `0.01650000 (profit: ~-4.07%, -0.00008168)`
## /forcebuy <pair>
### /forcebuy <pair>
> **BITTREX**: Buying ETH/BTC with limit `0.03400000` (`1.000000 ETH`, `225.290 USD`)
Note that for this to work, `forcebuy_enable` needs to be set to true.
## /performance
[More details](configuration.md/#understand-forcebuy_enable)
### /performance
Return the performance of each crypto-currency the bot has sold.
> Performance:
@ -115,7 +133,7 @@ Return the performance of each crypto-currency the bot has sold.
> 5. `STORJ/BTC 27.24%`
> ...
## /balance
### /balance
Return the balance of all crypto-currency your have on the exchange.
@ -129,7 +147,7 @@ Return the balance of all crypto-currency your have on the exchange.
> **Balance:** 86.64180098
> **Pending:** 0.0
## /daily <n>
### /daily <n>
Per default `/daily` will return the 7 last days.
The example below if for `/daily 3`:
@ -143,6 +161,38 @@ Day Profit BTC Profit USD
2018-01-01 0.00269130 BTC 34.986 USD
```
## /version
### /whitelist
Shows the current whitelist
> Using whitelist `StaticPairList` with 22 pairs
> `IOTA/BTC, NEO/BTC, TRX/BTC, VET/BTC, ADA/BTC, ETC/BTC, NCASH/BTC, DASH/BTC, XRP/BTC, XVG/BTC, EOS/BTC, LTC/BTC, OMG/BTC, BTG/BTC, LSK/BTC, ZEC/BTC, HOT/BTC, IOTX/BTC, XMR/BTC, AST/BTC, XLM/BTC, NANO/BTC`
### /blacklist [pair]
Shows the current blacklist.
If Pair is set, then this pair will be added to the pairlist.
Also supports multiple pairs, seperated by a space.
Use `/reload_conf` to reset the blacklist.
> Using blacklist `StaticPairList` with 2 pairs
>`DODGE/BTC`, `HOT/BTC`.
### /edge
Shows pairs validated by Edge along with their corresponding winrate, expectancy and stoploss values.
> **Edge only validated following pairs:**
```
Pair Winrate Expectancy Stoploss
-------- --------- ------------ ----------
DOCK/ETH 0.522727 0.881821 -0.03
PHX/ETH 0.677419 0.560488 -0.03
HOT/ETH 0.733333 0.490492 -0.03
HC/ETH 0.588235 0.280988 -0.02
ARDR/ETH 0.366667 0.143059 -0.01
```
### /version
> **Version:** `0.14.3`

42
docs/webhook-config.md
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@ -1,7 +1,5 @@
# Webhook usage
This page explains how to configure your bot to talk to webhooks.
## Configuration
Enable webhooks by adding a webhook-section to your configuration file, and setting `webhook.enabled` to `true`.
@ -39,34 +37,30 @@ Different payloads can be configured for different events. Not all fields are ne
The fields in `webhook.webhookbuy` are filled when the bot executes a buy. Parameters are filled using string.format.
Possible parameters are:
* exchange
* pair
* market_url
* limit
* stake_amount
* stake_amount_fiat
* stake_currency
* fiat_currency
* `exchange`
* `pair`
* `limit`
* `stake_amount`
* `stake_currency`
* `fiat_currency`
### Webhooksell
The fields in `webhook.webhooksell` are filled when the bot sells a trade. Parameters are filled using string.format.
Possible parameters are:
* exchange
* pair
* gain
* market_url
* limit
* amount
* open_rate
* current_rate
* profit_amount
* profit_percent
* profit_fiat
* stake_currency
* fiat_currency
* sell_reason
* `exchange`
* `pair`
* `gain`
* `limit`
* `amount`
* `open_rate`
* `current_rate`
* `profit_amount`
* `profit_percent`
* `stake_currency`
* `fiat_currency`
* `sell_reason`
### Webhookstatus

2
freqtrade.service
View File

@ -6,7 +6,7 @@ After=network.target
# Set WorkingDirectory and ExecStart to your file paths accordingly
# NOTE: %h will be resolved to /home/<username>
WorkingDirectory=%h/freqtrade
ExecStart=/usr/bin/freqtrade --dynamic-whitelist 40
ExecStart=/usr/bin/freqtrade
Restart=on-failure
[Install]

30
freqtrade.service.watchdog Normal file
View File

@ -0,0 +1,30 @@
[Unit]
Description=Freqtrade Daemon
After=network.target
[Service]
# Set WorkingDirectory and ExecStart to your file paths accordingly
# NOTE: %h will be resolved to /home/<username>
WorkingDirectory=%h/freqtrade
ExecStart=/usr/bin/freqtrade --sd-notify
Restart=always
#Restart=on-failure
# Note that we use Type=notify here
Type=notify
# Currently required if Type=notify
NotifyAccess=all
StartLimitInterval=1min
StartLimitBurst=5
TimeoutStartSec=1min
# Use here (process_throttle_secs * 2) or longer time interval
WatchdogSec=20
[Install]
WantedBy=default.target

10
freqtrade/__init__.py
View File

@ -1,5 +1,5 @@
""" FreqTrade bot """
__version__ = '0.18.1'
__version__ = '0.18.5'
class DependencyException(BaseException):
@ -17,6 +17,14 @@ class OperationalException(BaseException):
"""
class InvalidOrderException(BaseException):
"""
This is returned when the order is not valid. Example:
If stoploss on exchange order is hit, then trying to cancel the order
should return this exception.
"""
class TemporaryError(BaseException):
"""
Temporary network or exchange related error.

123
freqtrade/arguments.py
View File

@ -6,9 +6,7 @@ import argparse
import os
import re
from typing import List, NamedTuple, Optional
import arrow
from freqtrade import __version__, constants
@ -55,6 +53,11 @@ class Arguments(object):
"""
parsed_arg = self.parser.parse_args(self.args)
# Workaround issue in argparse with action='append' and default value
# (see https://bugs.python.org/issue16399)
if parsed_arg.config is None:
parsed_arg.config = [constants.DEFAULT_CONFIG]
return parsed_arg
def common_args_parser(self) -> None:
@ -63,11 +66,18 @@ class Arguments(object):
"""
self.parser.add_argument(
'-v', '--verbose',
help='verbose mode (-vv for more, -vvv to get all messages)',
help='Verbose mode (-vv for more, -vvv to get all messages).',
action='count',
dest='loglevel',
default=0,
)
self.parser.add_argument(
'--logfile',
help='Log to the file specified',
dest='logfile',
type=str,
metavar='FILE'
)
self.parser.add_argument(
'--version',
action='version',
@ -75,15 +85,16 @@ class Arguments(object):
)
self.parser.add_argument(
'-c', '--config',
help='specify configuration file (default: %(default)s)',
help='Specify configuration file (default: %(default)s). '
'Multiple --config options may be used.',
dest='config',
default='config.json',
action='append',
type=str,
metavar='PATH',
)
self.parser.add_argument(
'-d', '--datadir',
help='path to backtest data',
help='Path to backtest data.',
dest='datadir',
default=None,
type=str,
@ -91,7 +102,7 @@ class Arguments(object):
)
self.parser.add_argument(
'-s', '--strategy',
help='specify strategy class name (default: %(default)s)',
help='Specify strategy class name (default: %(default)s).',
dest='strategy',
default='DefaultStrategy',
type=str,
@ -99,23 +110,15 @@ class Arguments(object):
)
self.parser.add_argument(
'--strategy-path',
help='specify additional strategy lookup path',
help='Specify additional strategy lookup path.',
dest='strategy_path',
type=str,
metavar='PATH',
)
self.parser.add_argument(
'--customhyperopt',
help='specify hyperopt class name (default: %(default)s)',
dest='hyperopt',
default=constants.DEFAULT_HYPEROPT,
type=str,
metavar='NAME',
)
self.parser.add_argument(
'--dynamic-whitelist',
help='dynamically generate and update whitelist'
' based on 24h BaseVolume (default: %(const)s)'
help='Dynamically generate and update whitelist'
' based on 24h BaseVolume (default: %(const)s).'
' DEPRECATED.',
dest='dynamic_whitelist',
const=constants.DYNAMIC_WHITELIST,
@ -126,11 +129,17 @@ class Arguments(object):
self.parser.add_argument(
'--db-url',
help='Override trades database URL, this is useful if dry_run is enabled'
' or in custom deployments (default: %(default)s)',
' or in custom deployments (default: %(default)s).',
dest='db_url',
type=str,
metavar='PATH',
)
self.parser.add_argument(
'--sd-notify',
help='Notify systemd service manager.',
action='store_true',
dest='sd_notify',
)
@staticmethod
def backtesting_options(parser: argparse.ArgumentParser) -> None:
@ -139,29 +148,28 @@ class Arguments(object):
"""
parser.add_argument(
'--eps', '--enable-position-stacking',
help='Allow buying the same pair multiple times (position stacking)',
help='Allow buying the same pair multiple times (position stacking).',
action='store_true',
dest='position_stacking',
default=False
)
parser.add_argument(
'--dmmp', '--disable-max-market-positions',
help='Disable applying `max_open_trades` during backtest '
'(same as setting `max_open_trades` to a very high number)',
'(same as setting `max_open_trades` to a very high number).',
action='store_false',
dest='use_max_market_positions',
default=True
)
parser.add_argument(
'-l', '--live',
help='using live data',
help='Use live data.',
action='store_true',
dest='live',
)
parser.add_argument(
'-r', '--refresh-pairs-cached',
help='refresh the pairs files in tests/testdata with the latest data from the '
help='Refresh the pairs files in tests/testdata with the latest data from the '
'exchange. Use it if you want to run your backtesting with up-to-date data.',
action='store_true',
dest='refresh_pairs',
@ -178,8 +186,8 @@ class Arguments(object):
)
parser.add_argument(
'--export',
help='export backtest results, argument are: trades\
Example --export=trades',
help='Export backtest results, argument are: trades. '
'Example --export=trades',
type=str,
default=None,
dest='export',
@ -203,14 +211,14 @@ class Arguments(object):
"""
parser.add_argument(
'-r', '--refresh-pairs-cached',
help='refresh the pairs files in tests/testdata with the latest data from the '
help='Refresh the pairs files in tests/testdata with the latest data from the '
'exchange. Use it if you want to run your edge with up-to-date data.',
action='store_true',
dest='refresh_pairs',
)
parser.add_argument(
'--stoplosses',
help='defines a range of stoploss against which edge will assess the strategy '
help='Defines a range of stoploss against which edge will assess the strategy '
'the format is "min,max,step" (without any space).'
'example: --stoplosses=-0.01,-0.1,-0.001',
type=str,
@ -226,27 +234,51 @@ class Arguments(object):
"""
parser.add_argument(
'-i', '--ticker-interval',
help='specify ticker interval (1m, 5m, 30m, 1h, 1d)',
help='Specify ticker interval (1m, 5m, 30m, 1h, 1d).',
dest='ticker_interval',
type=str,
)
parser.add_argument(
'--timerange',
help='specify what timerange of data to use.',
help='Specify what timerange of data to use.',
default=None,
type=str,
dest='timerange',
)
parser.add_argument(
'--max_open_trades',
help='Specify max_open_trades to use.',
default=None,
type=int,
dest='max_open_trades',
)
parser.add_argument(
'--stake_amount',
help='Specify stake_amount.',
default=None,
type=float,
dest='stake_amount',
)
@staticmethod
def hyperopt_options(parser: argparse.ArgumentParser) -> None:
"""
Parses given arguments for Hyperopt scripts.
"""
parser.add_argument(
'--customhyperopt',
help='Specify hyperopt class name (default: %(default)s).',
dest='hyperopt',
default=constants.DEFAULT_HYPEROPT,
type=str,
metavar='NAME',
)
parser.add_argument(
'--eps', '--enable-position-stacking',
help='Allow buying the same pair multiple times (position stacking)',
help='Allow buying the same pair multiple times (position stacking).',
action='store_true',
dest='position_stacking',
default=False
@ -255,14 +287,14 @@ class Arguments(object):
parser.add_argument(
'--dmmp', '--disable-max-market-positions',
help='Disable applying `max_open_trades` during backtest '
'(same as setting `max_open_trades` to a very high number)',
'(same as setting `max_open_trades` to a very high number).',
action='store_false',
dest='use_max_market_positions',
default=True
)
parser.add_argument(
'-e', '--epochs',
help='specify number of epochs (default: %(default)d)',
help='Specify number of epochs (default: %(default)d).',
dest='epochs',
default=constants.HYPEROPT_EPOCH,
type=int,
@ -271,7 +303,7 @@ class Arguments(object):
parser.add_argument(
'-s', '--spaces',
help='Specify which parameters to hyperopt. Space separate list. \
Default: %(default)s',
Default: %(default)s.',
choices=['all', 'buy', 'sell', 'roi', 'stoploss'],
default='all',
nargs='+',
@ -288,19 +320,19 @@ class Arguments(object):
subparsers = self.parser.add_subparsers(dest='subparser')
# Add backtesting subcommand
backtesting_cmd = subparsers.add_parser('backtesting', help='backtesting module')
backtesting_cmd = subparsers.add_parser('backtesting', help='Backtesting module.')
backtesting_cmd.set_defaults(func=backtesting.start)
self.optimizer_shared_options(backtesting_cmd)
self.backtesting_options(backtesting_cmd)
# Add edge subcommand
edge_cmd = subparsers.add_parser('edge', help='edge module')
edge_cmd = subparsers.add_parser('edge', help='Edge module.')
edge_cmd.set_defaults(func=edge_cli.start)
self.optimizer_shared_options(edge_cmd)
self.edge_options(edge_cmd)
# Add hyperopt subcommand
hyperopt_cmd = subparsers.add_parser('hyperopt', help='hyperopt module')
hyperopt_cmd = subparsers.add_parser('hyperopt', help='Hyperopt module.')
hyperopt_cmd.set_defaults(func=hyperopt.start)
self.optimizer_shared_options(hyperopt_cmd)
self.hyperopt_options(hyperopt_cmd)
@ -364,7 +396,7 @@ class Arguments(object):
"""
self.parser.add_argument(
'--pairs-file',
help='File containing a list of pairs to download',
help='File containing a list of pairs to download.',
dest='pairs_file',
default=None,
metavar='PATH',
@ -372,7 +404,7 @@ class Arguments(object):
self.parser.add_argument(
'--export',
help='Export files to given dir',
help='Export files to given dir.',
dest='export',
default=None,
metavar='PATH',
@ -380,16 +412,17 @@ class Arguments(object):
self.parser.add_argument(
'-c', '--config',
help='specify configuration file, used for additional exchange parameters',
help='Specify configuration file (default: %(default)s). '
'Multiple --config options may be used.',
dest='config',
default=None,
action='append',
type=str,
metavar='PATH',
)
self.parser.add_argument(
'--days',
help='Download data for number of days',
help='Download data for given number of days.',
dest='days',
type=int,
metavar='INT',
@ -398,7 +431,7 @@ class Arguments(object):
self.parser.add_argument(
'--exchange',
help='Exchange name (default: %(default)s). Only valid if no config is provided',
help='Exchange name (default: %(default)s). Only valid if no config is provided.',
dest='exchange',
type=str,
default='bittrex'
@ -407,7 +440,7 @@ class Arguments(object):
self.parser.add_argument(
'-t', '--timeframes',
help='Specify which tickers to download. Space separated list. \
Default: %(default)s',
Default: %(default)s.',
choices=['1m', '3m', '5m', '15m', '30m', '1h', '2h', '4h',
'6h', '8h', '12h', '1d', '3d', '1w'],
default=['1m', '5m'],
@ -417,7 +450,7 @@ class Arguments(object):
self.parser.add_argument(
'--erase',
help='Clean all existing data for the selected exchange/pairs/timeframes',
help='Clean all existing data for the selected exchange/pairs/timeframes.',
dest='erase',
action='store_true'
)

102
freqtrade/configuration.py
View File

@ -4,15 +4,19 @@ This module contains the configuration class
import json
import logging
import os
import sys
from argparse import Namespace
from typing import Any, Dict, Optional
from logging.handlers import RotatingFileHandler
from typing import Any, Dict, List, Optional
import ccxt
from jsonschema import Draft4Validator, validate
from jsonschema.exceptions import ValidationError, best_match
from freqtrade import OperationalException, constants
from freqtrade.misc import deep_merge_dicts
from freqtrade.state import RunMode
logger = logging.getLogger(__name__)
@ -45,8 +49,19 @@ class Configuration(object):
Extract information for sys.argv and load the bot configuration
:return: Configuration dictionary
"""
logger.info('Using config: %s ...', self.args.config)
config = self._load_config_file(self.args.config)
config: Dict[str, Any] = {}
# Now expecting a list of config filenames here, not a string
for path in self.args.config:
logger.info('Using config: %s ...', path)
# Merge config options, overwriting old values
config = deep_merge_dicts(self._load_config_file(path), config)
if 'internals' not in config:
config['internals'] = {}
logger.info('Validating configuration ...')
self._validate_config_schema(config)
self._validate_config_consistency(config)
# Set strategy if not specified in config and or if it's non default
if self.args.strategy != constants.DEFAULT_STRATEGY or not config.get('strategy'):
@ -55,9 +70,6 @@ class Configuration(object):
if self.args.strategy_path:
config.update({'strategy_path': self.args.strategy_path})
# Add the hyperopt file to use
config.update({'hyperopt': self.args.hyperopt})
# Load Common configuration
config = self._load_common_config(config)
@ -93,11 +105,7 @@ class Configuration(object):
f'Config file "{path}" not found!'
' Please create a config file or check whether it exists.')
if 'internals' not in conf:
conf['internals'] = {}
logger.info('Validating configuration ...')
return self._validate_config(conf)
return conf
def _load_common_config(self, config: Dict[str, Any]) -> Dict[str, Any]:
"""
@ -110,13 +118,30 @@ class Configuration(object):
config.update({'verbosity': self.args.loglevel})
else:
config.update({'verbosity': 0})
# Log to stdout, not stderr
log_handlers: List[logging.Handler] = [logging.StreamHandler(sys.stdout)]
if 'logfile' in self.args and self.args.logfile:
config.update({'logfile': self.args.logfile})
# Allow setting this as either configuration or argument
if 'logfile' in config:
log_handlers.append(RotatingFileHandler(config['logfile'],
maxBytes=1024 * 1024, # 1Mb
backupCount=10))
logging.basicConfig(
level=logging.INFO if config['verbosity'] < 1 else logging.DEBUG,
format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
handlers=log_handlers
)
set_loggers(config['verbosity'])
logger.info('Verbosity set to %s', config['verbosity'])
# Support for sd_notify
if self.args.sd_notify:
config['internals'].update({'sd_notify': True})
# Add dynamic_whitelist if found
if 'dynamic_whitelist' in self.args and self.args.dynamic_whitelist:
# Update to volumePairList (the previous default)
@ -169,7 +194,7 @@ class Configuration(object):
logger.info(f'Created data directory: {datadir}')
return datadir
def _load_backtesting_config(self, config: Dict[str, Any]) -> Dict[str, Any]:
def _load_backtesting_config(self, config: Dict[str, Any]) -> Dict[str, Any]: # noqa: C901
"""
Extract information for sys.argv and load Backtesting configuration
:return: configuration as dictionary
@ -192,14 +217,24 @@ class Configuration(object):
config.update({'position_stacking': True})
logger.info('Parameter --enable-position-stacking detected ...')
# If --disable-max-market-positions is used we add it to the configuration
# If --disable-max-market-positions or --max_open_trades is used we update configuration
if 'use_max_market_positions' in self.args and not self.args.use_max_market_positions:
config.update({'use_max_market_positions': False})
logger.info('Parameter --disable-max-market-positions detected ...')
logger.info('max_open_trades set to unlimited ...')
elif 'max_open_trades' in self.args and self.args.max_open_trades:
config.update({'max_open_trades': self.args.max_open_trades})
logger.info('Parameter --max_open_trades detected, '
'overriding max_open_trades to: %s ...', config.get('max_open_trades'))
else:
logger.info('Using max_open_trades: %s ...', config.get('max_open_trades'))
# If --stake_amount is used we update configuration
if 'stake_amount' in self.args and self.args.stake_amount:
config.update({'stake_amount': self.args.stake_amount})
logger.info('Parameter --stake_amount detected, overriding stake_amount to: %s ...',
config.get('stake_amount'))
# If --timerange is used we add it to the configuration
if 'timerange' in self.args and self.args.timerange:
config.update({'timerange': self.args.timerange})
@ -268,6 +303,11 @@ class Configuration(object):
Extract information for sys.argv and load Hyperopt configuration
:return: configuration as dictionary
"""
if "hyperopt" in self.args:
# Add the hyperopt file to use
config.update({'hyperopt': self.args.hyperopt})
# If --epochs is used we add it to the configuration
if 'epochs' in self.args and self.args.epochs:
config.update({'epochs': self.args.epochs})
@ -281,7 +321,7 @@ class Configuration(object):
return config
def _validate_config(self, conf: Dict[str, Any]) -> Dict[str, Any]:
def _validate_config_schema(self, conf: Dict[str, Any]) -> Dict[str, Any]:
"""
Validate the configuration follow the Config Schema
:param conf: Config in JSON format
@ -299,6 +339,35 @@ class Configuration(object):
best_match(Draft4Validator(constants.CONF_SCHEMA).iter_errors(conf)).message
)
def _validate_config_consistency(self, conf: Dict[str, Any]) -> None:
"""
Validate the configuration consistency
:param conf: Config in JSON format
:return: Returns None if everything is ok, otherwise throw an OperationalException
"""
# validating trailing stoploss
self._validate_trailing_stoploss(conf)
def _validate_trailing_stoploss(self, conf: Dict[str, Any]) -> None:
# Skip if trailing stoploss is not activated
if not conf.get('trailing_stop', False):
return
tsl_positive = float(conf.get('trailing_stop_positive', 0))
tsl_offset = float(conf.get('trailing_stop_positive_offset', 0))
tsl_only_offset = conf.get('trailing_only_offset_is_reached', False)
if tsl_only_offset:
if tsl_positive == 0.0:
raise OperationalException(
f'The config trailing_only_offset_is_reached needs '
'trailing_stop_positive_offset to be more than 0 in your config.')
if tsl_positive > 0 and 0 < tsl_offset <= tsl_positive:
raise OperationalException(
f'The config trailing_stop_positive_offset needs '
'to be greater than trailing_stop_positive_offset in your config.')
def get_config(self) -> Dict[str, Any]:
"""
Return the config. Use this method to get the bot config
@ -324,11 +393,6 @@ class Configuration(object):
raise OperationalException(
exception_msg
)
# Depreciation warning
if 'ccxt_rate_limit' in config.get('exchange', {}):
logger.warning("`ccxt_rate_limit` has been deprecated in favor of "
"`ccxt_config` and `ccxt_async_config` and will be removed "
"in a future version.")
logger.debug('Exchange "%s" supported', exchange)
return True

34
freqtrade/constants.py
View File

@ -3,9 +3,10 @@
"""
bot constants
"""
DEFAULT_CONFIG = 'config.json'
DYNAMIC_WHITELIST = 20 # pairs
PROCESS_THROTTLE_SECS = 5 # sec
TICKER_INTERVAL = 5 # min
DEFAULT_TICKER_INTERVAL = 5 # min
HYPEROPT_EPOCH = 100 # epochs
RETRY_TIMEOUT = 30 # sec
DEFAULT_STRATEGY = 'DefaultStrategy'
@ -19,23 +20,13 @@ REQUIRED_ORDERTYPES = ['buy', 'sell', 'stoploss', 'stoploss_on_exchange']
ORDERTYPE_POSSIBILITIES = ['limit', 'market']
ORDERTIF_POSSIBILITIES = ['gtc', 'fok', 'ioc']
AVAILABLE_PAIRLISTS = ['StaticPairList', 'VolumePairList']
DRY_RUN_WALLET = 999.9
TICKER_INTERVAL_MINUTES = {
'1m': 1,
'3m': 3,
'5m': 5,
'15m': 15,
'30m': 30,
'1h': 60,
'2h': 120,
'4h': 240,
'6h': 360,
'8h': 480,
'12h': 720,
'1d': 1440,
'3d': 4320,
'1w': 10080,
}
TICKER_INTERVALS = [
'1m', '3m', '5m', '15m', '30m',
'1h', '2h', '4h', '6h', '8h', '12h',
'1d', '3d', '1w',
]
SUPPORTED_FIAT = [
"AUD", "BRL", "CAD", "CHF", "CLP", "CNY", "CZK", "DKK",
@ -50,7 +41,7 @@ CONF_SCHEMA = {
'type': 'object',
'properties': {
'max_open_trades': {'type': 'integer', 'minimum': -1},
'ticker_interval': {'type': 'string', 'enum': list(TICKER_INTERVAL_MINUTES.keys())},
'ticker_interval': {'type': 'string', 'enum': TICKER_INTERVALS},
'stake_currency': {'type': 'string', 'enum': ['BTC', 'XBT', 'ETH', 'USDT', 'EUR', 'USD']},
'stake_amount': {
"type": ["number", "string"],
@ -59,6 +50,7 @@ CONF_SCHEMA = {
},
'fiat_display_currency': {'type': 'string', 'enum': SUPPORTED_FIAT},
'dry_run': {'type': 'boolean'},
'dry_run_wallet': {'type': 'number'},
'process_only_new_candles': {'type': 'boolean'},
'minimal_roi': {
'type': 'object',
@ -67,10 +59,12 @@ CONF_SCHEMA = {
},
'minProperties': 1
},
'amount_reserve_percent': {'type': 'number', 'minimum': 0.0, 'maximum': 0.5},
'stoploss': {'type': 'number', 'maximum': 0, 'exclusiveMaximum': True},
'trailing_stop': {'type': 'boolean'},
'trailing_stop_positive': {'type': 'number', 'minimum': 0, 'maximum': 1},
'trailing_stop_positive_offset': {'type': 'number', 'minimum': 0, 'maximum': 1},
'trailing_only_offset_is_reached': {'type': 'boolean'},
'unfilledtimeout': {
'type': 'object',
'properties': {
@ -169,7 +163,8 @@ CONF_SCHEMA = {
'type': 'object',
'properties': {
'process_throttle_secs': {'type': 'number'},
'interval': {'type': 'integer'}
'interval': {'type': 'integer'},
'sd_notify': {'type': 'boolean'},
}
}
},
@ -200,6 +195,7 @@ CONF_SCHEMA = {
'uniqueItems': True
},
'outdated_offset': {'type': 'integer', 'minimum': 1},
'markets_refresh_interval': {'type': 'integer'},
'ccxt_config': {'type': 'object'},
'ccxt_async_config': {'type': 'object'}
},

67
freqtrade/data/btanalysis.py Normal file
View File

@ -0,0 +1,67 @@
"""
Helpers when analyzing backtest data
"""
from pathlib import Path
import numpy as np
import pandas as pd
from freqtrade.misc import json_load
# must align with columns in backtest.py
BT_DATA_COLUMNS = ["pair", "profitperc", "open_time", "close_time", "index", "duration",
"open_rate", "close_rate", "open_at_end", "sell_reason"]
def load_backtest_data(filename) -> pd.DataFrame:
"""
Load backtest data file.
:param filename: pathlib.Path object, or string pointing to the file.
:return a dataframe with the analysis results
"""
if isinstance(filename, str):
filename = Path(filename)
if not filename.is_file():
raise ValueError("File {filename} does not exist.")
with filename.open() as file:
data = json_load(file)
df = pd.DataFrame(data, columns=BT_DATA_COLUMNS)
df['open_time'] = pd.to_datetime(df['open_time'],
unit='s',
utc=True,
infer_datetime_format=True
)
df['close_time'] = pd.to_datetime(df['close_time'],
unit='s',
utc=True,
infer_datetime_format=True
)
df['profitabs'] = df['close_rate'] - df['open_rate']
df = df.sort_values("open_time").reset_index(drop=True)
return df
def evaluate_result_multi(results: pd.DataFrame, freq: str, max_open_trades: int) -> pd.DataFrame:
"""
Find overlapping trades by expanding each trade once per period it was open
and then counting overlaps
:param results: Results Dataframe - can be loaded
:param freq: Frequency used for the backtest
:param max_open_trades: parameter max_open_trades used during backtest run
:return: dataframe with open-counts per time-period in freq
"""
dates = [pd.Series(pd.date_range(row[1].open_time, row[1].close_time, freq=freq))
for row in results[['open_time', 'close_time']].iterrows()]
deltas = [len(x) for x in dates]
dates = pd.Series(pd.concat(dates).values, name='date')
df2 = pd.DataFrame(np.repeat(results.values, deltas, axis=0), columns=results.columns)
df2 = df2.astype(dtype={"open_time": "datetime64", "close_time": "datetime64"})
df2 = pd.concat([dates, df2], axis=1)
df2 = df2.set_index('date')
df_final = df2.resample(freq)[['pair']].count()
return df_final[df_final['pair'] > max_open_trades]

6
freqtrade/data/converter.py
View File

@ -4,8 +4,8 @@ Functions to convert data from one format to another
import logging
import pandas as pd
from pandas import DataFrame, to_datetime
from freqtrade.misc import timeframe_to_minutes
from freqtrade.constants import TICKER_INTERVAL_MINUTES
logger = logging.getLogger(__name__)
@ -65,9 +65,9 @@ def ohlcv_fill_up_missing_data(dataframe: DataFrame, ticker_interval: str) -> Da
'close': 'last',
'volume': 'sum'
}
tick_mins = TICKER_INTERVAL_MINUTES[ticker_interval]
ticker_minutes = timeframe_to_minutes(ticker_interval)
# Resample to create "NAN" values
df = dataframe.resample(f'{tick_mins}min', on='date').agg(ohlc_dict)
df = dataframe.resample(f'{ticker_minutes}min', on='date').agg(ohlc_dict)
# Forwardfill close for missing columns
df['close'] = df['close'].fillna(method='ffill')

12
freqtrade/data/dataprovider.py
View File

@ -37,23 +37,23 @@ class DataProvider(object):
@property
def available_pairs(self) -> List[Tuple[str, str]]:
"""
Return a list of tuples containing pair, tick_interval for which data is currently cached.
Return a list of tuples containing pair, ticker_interval for which data is currently cached.
Should be whitelist + open trades.
"""
return list(self._exchange._klines.keys())
def ohlcv(self, pair: str, tick_interval: str = None, copy: bool = True) -> DataFrame:
def ohlcv(self, pair: str, ticker_interval: str = None, copy: bool = True) -> DataFrame:
"""
get ohlcv data for the given pair as DataFrame
Please check `available_pairs` to verify which pairs are currently cached.
:param pair: pair to get the data for
:param tick_interval: ticker_interval to get pair for
:param ticker_interval: ticker_interval to get pair for
:param copy: copy dataframe before returning.
Use false only for RO operations (where the dataframe is not modified)
"""
if self.runmode in (RunMode.DRY_RUN, RunMode.LIVE):
if tick_interval:
pairtick = (pair, tick_interval)
if ticker_interval:
pairtick = (pair, ticker_interval)
else:
pairtick = (pair, self._config['ticker_interval'])
@ -65,7 +65,7 @@ class DataProvider(object):
"""
get stored historic ohlcv data
:param pair: pair to get the data for
:param tick_interval: ticker_interval to get pair for
:param ticker_interval: ticker_interval to get pair for
"""
return load_pair_history(pair=pair,
ticker_interval=ticker_interval,

26
freqtrade/data/history.py
View File

@ -12,10 +12,12 @@ from typing import Optional, List, Dict, Tuple, Any
import arrow
from pandas import DataFrame
from freqtrade import misc, constants, OperationalException
from freqtrade import misc, OperationalException
from freqtrade.arguments import TimeRange
from freqtrade.data.converter import parse_ticker_dataframe
from freqtrade.exchange import Exchange
from freqtrade.arguments import TimeRange
from freqtrade.misc import timeframe_to_minutes
logger = logging.getLogger(__name__)
@ -99,7 +101,7 @@ def load_pair_history(pair: str,
download_pair_history(datadir=datadir,
exchange=exchange,
pair=pair,
tick_interval=ticker_interval,
ticker_interval=ticker_interval,
timerange=timerange)
pairdata = load_tickerdata_file(datadir, pair, ticker_interval, timerange=timerange)
@ -149,7 +151,7 @@ def make_testdata_path(datadir: Optional[Path]) -> Path:
return datadir or (Path(__file__).parent.parent / "tests" / "testdata").resolve()
def load_cached_data_for_updating(filename: Path, tick_interval: str,
def load_cached_data_for_updating(filename: Path, ticker_interval: str,
timerange: Optional[TimeRange]) -> Tuple[List[Any],
Optional[int]]:
"""
@ -163,7 +165,7 @@ def load_cached_data_for_updating(filename: Path, tick_interval: str,
if timerange.starttype == 'date':
since_ms = timerange.startts * 1000
elif timerange.stoptype == 'line':
num_minutes = timerange.stopts * constants.TICKER_INTERVAL_MINUTES[tick_interval]
num_minutes = timerange.stopts * timeframe_to_minutes(ticker_interval)
since_ms = arrow.utcnow().shift(minutes=num_minutes).timestamp * 1000
# read the cached file
@ -190,7 +192,7 @@ def load_cached_data_for_updating(filename: Path, tick_interval: str,
def download_pair_history(datadir: Optional[Path],
exchange: Exchange,
pair: str,
tick_interval: str = '5m',
ticker_interval: str = '5m',
timerange: Optional[TimeRange] = None) -> bool:
"""
Download the latest ticker intervals from the exchange for the pair passed in parameters
@ -200,7 +202,7 @@ def download_pair_history(datadir: Optional[Path],
Based on @Rybolov work: https://github.com/rybolov/freqtrade-data
:param pair: pair to download
:param tick_interval: ticker interval
:param ticker_interval: ticker interval
:param timerange: range of time to download
:return: bool with success state
@ -208,17 +210,17 @@ def download_pair_history(datadir: Optional[Path],
try:
path = make_testdata_path(datadir)
filepair = pair.replace("/", "_")
filename = path.joinpath(f'{filepair}-{tick_interval}.json')
filename = path.joinpath(f'{filepair}-{ticker_interval}.json')
logger.info('Download the pair: "%s", Interval: %s', pair, tick_interval)
logger.info('Download the pair: "%s", Interval: %s', pair, ticker_interval)
data, since_ms = load_cached_data_for_updating(filename, tick_interval, timerange)
data, since_ms = load_cached_data_for_updating(filename, ticker_interval, timerange)
logger.debug("Current Start: %s", misc.format_ms_time(data[1][0]) if data else 'None')
logger.debug("Current End: %s", misc.format_ms_time(data[-1][0]) if data else 'None')
# Default since_ms to 30 days if nothing is given
new_data = exchange.get_history(pair=pair, tick_interval=tick_interval,
new_data = exchange.get_history(pair=pair, ticker_interval=ticker_interval,
since_ms=since_ms if since_ms
else
int(arrow.utcnow().shift(days=-30).float_timestamp) * 1000)
@ -231,5 +233,5 @@ def download_pair_history(datadir: Optional[Path],
return True
except BaseException:
logger.info('Failed to download the pair: "%s", Interval: %s',
pair, tick_interval)
pair, ticker_interval)
return False

154
freqtrade/edge/__init__.py
View File

@ -203,6 +203,22 @@ class Edge():
return self._final_pairs
def accepted_pairs(self) -> list:
"""
return a list of accepted pairs along with their winrate, expectancy and stoploss
"""
final = []
for pair, info in self._cached_pairs.items():
if info.expectancy > float(self.edge_config.get('minimum_expectancy', 0.2)) and \
info.winrate > float(self.edge_config.get('minimum_winrate', 0.60)):
final.append({
'Pair': pair,
'Winrate': info.winrate,
'Expectancy': info.expectancy,
'Stoploss': info.stoploss,
})
return final
def _fill_calculable_fields(self, result: DataFrame) -> DataFrame:
"""
The result frame contains a number of columns that are calculable
@ -351,91 +367,93 @@ class Edge():
return result
def _detect_next_stop_or_sell_point(self, buy_column, sell_column, date_column,
ohlc_columns, stoploss, pair, start_point=0):
ohlc_columns, stoploss, pair):
"""
Iterate through ohlc_columns recursively in order to find the next trade
Iterate through ohlc_columns in order to find the next trade
Next trade opens from the first buy signal noticed to
The sell or stoploss signal after it.
It then calls itself cutting OHLC, buy_column, sell_colum and date_column
Cut from (the exit trade index) + 1
It then cuts OHLC, buy_column, sell_column and date_column.
Cut from (the exit trade index) + 1.
Author: https://github.com/mishaker
"""
result: list = []
open_trade_index = utf1st.find_1st(buy_column, 1, utf1st.cmp_equal)
start_point = 0
# return empty if we don't find trade entry (i.e. buy==1) or
# we find a buy but at the of array
if open_trade_index == -1 or open_trade_index == len(buy_column) - 1:
return []
else:
open_trade_index += 1 # when a buy signal is seen,
# trade opens in reality on the next candle
while True:
open_trade_index = utf1st.find_1st(buy_column, 1, utf1st.cmp_equal)
stop_price_percentage = stoploss + 1
open_price = ohlc_columns[open_trade_index, 0]
stop_price = (open_price * stop_price_percentage)
# Return empty if we don't find trade entry (i.e. buy==1) or
# we find a buy but at the end of array
if open_trade_index == -1 or open_trade_index == len(buy_column) - 1:
break
else:
# When a buy signal is seen,
# trade opens in reality on the next candle
open_trade_index += 1
# Searching for the index where stoploss is hit
stop_index = utf1st.find_1st(
ohlc_columns[open_trade_index:, 2], stop_price, utf1st.cmp_smaller)
stop_price_percentage = stoploss + 1
open_price = ohlc_columns[open_trade_index, 0]
stop_price = (open_price * stop_price_percentage)
# If we don't find it then we assume stop_index will be far in future (infinite number)
if stop_index == -1:
stop_index = float('inf')
# Searching for the index where stoploss is hit
stop_index = utf1st.find_1st(
ohlc_columns[open_trade_index:, 2], stop_price, utf1st.cmp_smaller)
# Searching for the index where sell is hit
sell_index = utf1st.find_1st(sell_column[open_trade_index:], 1, utf1st.cmp_equal)
# If we don't find it then we assume stop_index will be far in future (infinite number)
if stop_index == -1:
stop_index = float('inf')
# If we don't find it then we assume sell_index will be far in future (infinite number)
if sell_index == -1:
sell_index = float('inf')
# Searching for the index where sell is hit
sell_index = utf1st.find_1st(sell_column[open_trade_index:], 1, utf1st.cmp_equal)
# Check if we don't find any stop or sell point (in that case trade remains open)
# It is not interesting for Edge to consider it so we simply ignore the trade
# And stop iterating there is no more entry
if stop_index == sell_index == float('inf'):
return []
# If we don't find it then we assume sell_index will be far in future (infinite number)
if sell_index == -1:
sell_index = float('inf')
if stop_index <= sell_index:
exit_index = open_trade_index + stop_index
exit_type = SellType.STOP_LOSS
exit_price = stop_price
elif stop_index > sell_index:
# if exit is SELL then we exit at the next candle
exit_index = open_trade_index + sell_index + 1
# Check if we don't find any stop or sell point (in that case trade remains open)
# It is not interesting for Edge to consider it so we simply ignore the trade
# And stop iterating there is no more entry
if stop_index == sell_index == float('inf'):
break
# check if we have the next candle
if len(ohlc_columns) - 1 < exit_index:
return []
if stop_index <= sell_index:
exit_index = open_trade_index + stop_index
exit_type = SellType.STOP_LOSS
exit_price = stop_price
elif stop_index > sell_index:
# If exit is SELL then we exit at the next candle
exit_index = open_trade_index + sell_index + 1
exit_type = SellType.SELL_SIGNAL
exit_price = ohlc_columns[exit_index, 0]
# Check if we have the next candle
if len(ohlc_columns) - 1 < exit_index:
break
trade = {'pair': pair,
'stoploss': stoploss,
'profit_percent': '',
'profit_abs': '',
'open_time': date_column[open_trade_index],
'close_time': date_column[exit_index],
'open_index': start_point + open_trade_index,
'close_index': start_point + exit_index,
'trade_duration': '',
'open_rate': round(open_price, 15),
'close_rate': round(exit_price, 15),
'exit_type': exit_type
}
exit_type = SellType.SELL_SIGNAL
exit_price = ohlc_columns[exit_index, 0]
result.append(trade)
trade = {'pair': pair,
'stoploss': stoploss,
'profit_percent': '',
'profit_abs': '',
'open_time': date_column[open_trade_index],
'close_time': date_column[exit_index],
'open_index': start_point + open_trade_index,
'close_index': start_point + exit_index,
'trade_duration': '',
'open_rate': round(open_price, 15),
'close_rate': round(exit_price, 15),
'exit_type': exit_type
}
# Calling again the same function recursively but giving
# it a view of exit_index till the end of array
return result + self._detect_next_stop_or_sell_point(
buy_column[exit_index:],
sell_column[exit_index:],
date_column[exit_index:],
ohlc_columns[exit_index:],
stoploss,
pair,
(start_point + exit_index)
)
result.append(trade)
# Giving a view of exit_index till the end of array
buy_column = buy_column[exit_index:]
sell_column = sell_column[exit_index:]
date_column = date_column[exit_index:]
ohlc_columns = ohlc_columns[exit_index:]
start_point += exit_index
return result

733
freqtrade/exchange/__init__.py
View File

@ -1,730 +1,3 @@
# pragma pylint: disable=W0603
""" Cryptocurrency Exchanges support """
import logging
import inspect
from random import randint
from typing import List, Dict, Tuple, Any, Optional
from datetime import datetime
from math import floor, ceil
import arrow
import asyncio
import ccxt
import ccxt.async_support as ccxt_async
from pandas import DataFrame
from freqtrade import constants, OperationalException, DependencyException, TemporaryError
from freqtrade.data.converter import parse_ticker_dataframe
logger = logging.getLogger(__name__)
API_RETRY_COUNT = 4
# Urls to exchange markets, insert quote and base with .format()
_EXCHANGE_URLS = {
ccxt.bittrex.__name__: '/Market/Index?MarketName={quote}-{base}',
ccxt.binance.__name__: '/tradeDetail.html?symbol={base}_{quote}'
}
def retrier_async(f):
async def wrapper(*args, **kwargs):
count = kwargs.pop('count', API_RETRY_COUNT)
try:
return await f(*args, **kwargs)
except (TemporaryError, DependencyException) as ex:
logger.warning('%s() returned exception: "%s"', f.__name__, ex)
if count > 0:
count -= 1
kwargs.update({'count': count})
logger.warning('retrying %s() still for %s times', f.__name__, count)
return await wrapper(*args, **kwargs)
else:
logger.warning('Giving up retrying: %s()', f.__name__)
raise ex
return wrapper
def retrier(f):
def wrapper(*args, **kwargs):
count = kwargs.pop('count', API_RETRY_COUNT)
try:
return f(*args, **kwargs)
except (TemporaryError, DependencyException) as ex:
logger.warning('%s() returned exception: "%s"', f.__name__, ex)
if count > 0:
count -= 1
kwargs.update({'count': count})
logger.warning('retrying %s() still for %s times', f.__name__, count)
return wrapper(*args, **kwargs)
else:
logger.warning('Giving up retrying: %s()', f.__name__)
raise ex
return wrapper
class Exchange(object):
_conf: Dict = {}
def __init__(self, config: dict) -> None:
"""
Initializes this module with the given config,
it does basic validation whether the specified
exchange and pairs are valid.
:return: None
"""
self._conf.update(config)
self._cached_ticker: Dict[str, Any] = {}
# Holds last candle refreshed time of each pair
self._pairs_last_refresh_time: Dict[Tuple[str, str], int] = {}
# Holds candles
self._klines: Dict[Tuple[str, str], DataFrame] = {}
# Holds all open sell orders for dry_run
self._dry_run_open_orders: Dict[str, Any] = {}
if config['dry_run']:
logger.info('Instance is running with dry_run enabled')
exchange_config = config['exchange']
self._api: ccxt.Exchange = self._init_ccxt(
exchange_config, ccxt_kwargs=exchange_config.get('ccxt_config'))
self._api_async: ccxt_async.Exchange = self._init_ccxt(
exchange_config, ccxt_async, ccxt_kwargs=exchange_config.get('ccxt_async_config'))
logger.info('Using Exchange "%s"', self.name)
self.markets = self._load_markets()
# Check if all pairs are available
self.validate_pairs(config['exchange']['pair_whitelist'])
self.validate_ordertypes(config.get('order_types', {}))
self.validate_order_time_in_force(config.get('order_time_in_force', {}))
if config.get('ticker_interval'):
# Check if timeframe is available
self.validate_timeframes(config['ticker_interval'])
def __del__(self):
"""
Destructor - clean up async stuff
"""
logger.debug("Exchange object destroyed, closing async loop")
if self._api_async and inspect.iscoroutinefunction(self._api_async.close):
asyncio.get_event_loop().run_until_complete(self._api_async.close())
def _init_ccxt(self, exchange_config: dict, ccxt_module=ccxt,
ccxt_kwargs: dict = None) -> ccxt.Exchange:
"""
Initialize ccxt with given config and return valid
ccxt instance.
"""
# Find matching class for the given exchange name
name = exchange_config['name']
if name not in ccxt_module.exchanges:
raise OperationalException(f'Exchange {name} is not supported')
ex_config = {
'apiKey': exchange_config.get('key'),
'secret': exchange_config.get('secret'),
'password': exchange_config.get('password'),
'uid': exchange_config.get('uid', ''),
'enableRateLimit': exchange_config.get('ccxt_rate_limit', True)
}
if ccxt_kwargs:
logger.info('Applying additional ccxt config: %s', ccxt_kwargs)
ex_config.update(ccxt_kwargs)
try:
api = getattr(ccxt_module, name.lower())(ex_config)
except (KeyError, AttributeError):
raise OperationalException(f'Exchange {name} is not supported')
self.set_sandbox(api, exchange_config, name)
return api
@property
def name(self) -> str:
"""exchange Name (from ccxt)"""
return self._api.name
@property
def id(self) -> str:
"""exchange ccxt id"""
return self._api.id
def klines(self, pair_interval: Tuple[str, str], copy=True) -> DataFrame:
# create key tuple
if pair_interval in self._klines:
return self._klines[pair_interval].copy() if copy else self._klines[pair_interval]
else:
return DataFrame()
def set_sandbox(self, api, exchange_config: dict, name: str):
if exchange_config.get('sandbox'):
if api.urls.get('test'):
api.urls['api'] = api.urls['test']
logger.info("Enabled Sandbox API on %s", name)
else:
logger.warning(name, "No Sandbox URL in CCXT, exiting. "
"Please check your config.json")
raise OperationalException(f'Exchange {name} does not provide a sandbox api')
def _load_async_markets(self) -> None:
try:
if self._api_async:
asyncio.get_event_loop().run_until_complete(self._api_async.load_markets())
except ccxt.BaseError as e:
logger.warning('Could not load async markets. Reason: %s', e)
return
def _load_markets(self) -> Dict[str, Any]:
""" Initialize markets both sync and async """
try:
markets = self._api.load_markets()
self._load_async_markets()
return markets
except ccxt.BaseError as e:
logger.warning('Unable to initialize markets. Reason: %s', e)
return {}
def validate_pairs(self, pairs: List[str]) -> None:
"""
Checks if all given pairs are tradable on the current exchange.
Raises OperationalException if one pair is not available.
:param pairs: list of pairs
:return: None
"""
if not self.markets:
logger.warning('Unable to validate pairs (assuming they are correct).')
# return
stake_cur = self._conf['stake_currency']
for pair in pairs:
# Note: ccxt has BaseCurrency/QuoteCurrency format for pairs
# TODO: add a support for having coins in BTC/USDT format
if not pair.endswith(stake_cur):
raise OperationalException(
f'Pair {pair} not compatible with stake_currency: {stake_cur}')
if self.markets and pair not in self.markets:
raise OperationalException(
f'Pair {pair} is not available at {self.name}'
f'Please remove {pair} from your whitelist.')
def validate_timeframes(self, timeframe: List[str]) -> None:
"""
Checks if ticker interval from config is a supported timeframe on the exchange
"""
timeframes = self._api.timeframes
if timeframe not in timeframes:
raise OperationalException(
f'Invalid ticker {timeframe}, this Exchange supports {timeframes}')
def validate_ordertypes(self, order_types: Dict) -> None:
"""
Checks if order-types configured in strategy/config are supported
"""
if any(v == 'market' for k, v in order_types.items()):
if not self.exchange_has('createMarketOrder'):
raise OperationalException(
f'Exchange {self.name} does not support market orders.')
if order_types.get('stoploss_on_exchange'):
if self.name != 'Binance':
raise OperationalException(
'On exchange stoploss is not supported for %s.' % self.name
)
def validate_order_time_in_force(self, order_time_in_force: Dict) -> None:
"""
Checks if order time in force configured in strategy/config are supported
"""
if any(v != 'gtc' for k, v in order_time_in_force.items()):
if self.name != 'Binance':
raise OperationalException(
f'Time in force policies are not supporetd for {self.name} yet.')
def exchange_has(self, endpoint: str) -> bool:
"""
Checks if exchange implements a specific API endpoint.
Wrapper around ccxt 'has' attribute
:param endpoint: Name of endpoint (e.g. 'fetchOHLCV', 'fetchTickers')
:return: bool
"""
return endpoint in self._api.has and self._api.has[endpoint]
def symbol_amount_prec(self, pair, amount: float):
'''
Returns the amount to buy or sell to a precision the Exchange accepts
Rounded down
'''
if self._api.markets[pair]['precision']['amount']:
symbol_prec = self._api.markets[pair]['precision']['amount']
big_amount = amount * pow(10, symbol_prec)
amount = floor(big_amount) / pow(10, symbol_prec)
return amount
def symbol_price_prec(self, pair, price: float):
'''
Returns the price buying or selling with to the precision the Exchange accepts
Rounds up
'''
if self._api.markets[pair]['precision']['price']:
symbol_prec = self._api.markets[pair]['precision']['price']
big_price = price * pow(10, symbol_prec)
price = ceil(big_price) / pow(10, symbol_prec)
return price
def buy(self, pair: str, ordertype: str, amount: float,
rate: float, time_in_force) -> Dict:
if self._conf['dry_run']:
order_id = f'dry_run_buy_{randint(0, 10**6)}'
self._dry_run_open_orders[order_id] = {
'pair': pair,
'price': rate,
'amount': amount,
'type': ordertype,
'side': 'buy',
'remaining': 0.0,
'datetime': arrow.utcnow().isoformat(),
'status': 'closed',
'fee': None
}
return {'id': order_id}
try:
# Set the precision for amount and price(rate) as accepted by the exchange
amount = self.symbol_amount_prec(pair, amount)
rate = self.symbol_price_prec(pair, rate) if ordertype != 'market' else None
if time_in_force == 'gtc':
return self._api.create_order(pair, ordertype, 'buy', amount, rate)
else:
return self._api.create_order(pair, ordertype, 'buy',
amount, rate, {'timeInForce': time_in_force})
except ccxt.InsufficientFunds as e:
raise DependencyException(
f'Insufficient funds to create limit buy order on market {pair}.'
f'Tried to buy amount {amount} at rate {rate} (total {rate*amount}).'
f'Message: {e}')
except ccxt.InvalidOrder as e:
raise DependencyException(
f'Could not create limit buy order on market {pair}.'
f'Tried to buy amount {amount} at rate {rate} (total {rate*amount}).'
f'Message: {e}')
except (ccxt.NetworkError, ccxt.ExchangeError) as e:
raise TemporaryError(
f'Could not place buy order due to {e.__class__.__name__}. Message: {e}')
except ccxt.BaseError as e:
raise OperationalException(e)
def sell(self, pair: str, ordertype: str, amount: float,
rate: float, time_in_force='gtc') -> Dict:
if self._conf['dry_run']:
order_id = f'dry_run_sell_{randint(0, 10**6)}'
self._dry_run_open_orders[order_id] = {
'pair': pair,
'price': rate,
'amount': amount,
'type': ordertype,
'side': 'sell',
'remaining': 0.0,
'datetime': arrow.utcnow().isoformat(),
'status': 'closed'
}
return {'id': order_id}
try:
# Set the precision for amount and price(rate) as accepted by the exchange
amount = self.symbol_amount_prec(pair, amount)
rate = self.symbol_price_prec(pair, rate) if ordertype != 'market' else None
if time_in_force == 'gtc':
return self._api.create_order(pair, ordertype, 'sell', amount, rate)
else:
return self._api.create_order(pair, ordertype, 'sell',
amount, rate, {'timeInForce': time_in_force})
except ccxt.InsufficientFunds as e:
raise DependencyException(
f'Insufficient funds to create limit sell order on market {pair}.'
f'Tried to sell amount {amount} at rate {rate} (total {rate*amount}).'
f'Message: {e}')
except ccxt.InvalidOrder as e:
raise DependencyException(
f'Could not create limit sell order on market {pair}.'
f'Tried to sell amount {amount} at rate {rate} (total {rate*amount}).'
f'Message: {e}')
except (ccxt.NetworkError, ccxt.ExchangeError) as e:
raise TemporaryError(
f'Could not place sell order due to {e.__class__.__name__}. Message: {e}')
except ccxt.BaseError as e:
raise OperationalException(e)
def stoploss_limit(self, pair: str, amount: float, stop_price: float, rate: float) -> Dict:
"""
creates a stoploss limit order.
NOTICE: it is not supported by all exchanges. only binance is tested for now.
"""
# Set the precision for amount and price(rate) as accepted by the exchange
amount = self.symbol_amount_prec(pair, amount)
rate = self.symbol_price_prec(pair, rate)
stop_price = self.symbol_price_prec(pair, stop_price)
# Ensure rate is less than stop price
if stop_price <= rate:
raise OperationalException(
'In stoploss limit order, stop price should be more than limit price')
if self._conf['dry_run']:
order_id = f'dry_run_buy_{randint(0, 10**6)}'
self._dry_run_open_orders[order_id] = {
'info': {},
'id': order_id,
'pair': pair,
'price': stop_price,
'amount': amount,
'type': 'stop_loss_limit',
'side': 'sell',
'remaining': amount,
'datetime': arrow.utcnow().isoformat(),
'status': 'open',
'fee': None
}
return self._dry_run_open_orders[order_id]
try:
order = self._api.create_order(pair, 'stop_loss_limit', 'sell',
amount, rate, {'stopPrice': stop_price})
logger.info('stoploss limit order added for %s. '
'stop price: %s. limit: %s' % (pair, stop_price, rate))
return order
except ccxt.InsufficientFunds as e:
raise DependencyException(
f'Insufficient funds to place stoploss limit order on market {pair}. '
f'Tried to put a stoploss amount {amount} with '
f'stop {stop_price} and limit {rate} (total {rate*amount}).'
f'Message: {e}')
except ccxt.InvalidOrder as e:
raise DependencyException(
f'Could not place stoploss limit order on market {pair}.'
f'Tried to place stoploss amount {amount} with '
f'stop {stop_price} and limit {rate} (total {rate*amount}).'
f'Message: {e}')
except (ccxt.NetworkError, ccxt.ExchangeError) as e:
raise TemporaryError(
f'Could not place stoploss limit order due to {e.__class__.__name__}. Message: {e}')
except ccxt.BaseError as e:
raise OperationalException(e)
@retrier
def get_balance(self, currency: str) -> float:
if self._conf['dry_run']:
return 999.9
# ccxt exception is already handled by get_balances
balances = self.get_balances()
balance = balances.get(currency)
if balance is None:
raise TemporaryError(
f'Could not get {currency} balance due to malformed exchange response: {balances}')
return balance['free']
@retrier
def get_balances(self) -> dict:
if self._conf['dry_run']:
return {}
try:
balances = self._api.fetch_balance()
# Remove additional info from ccxt results
balances.pop("info", None)
balances.pop("free", None)
balances.pop("total", None)
balances.pop("used", None)
return balances
except (ccxt.NetworkError, ccxt.ExchangeError) as e:
raise TemporaryError(
f'Could not get balance due to {e.__class__.__name__}. Message: {e}')
except ccxt.BaseError as e:
raise OperationalException(e)
@retrier
def get_tickers(self) -> Dict:
try:
return self._api.fetch_tickers()
except ccxt.NotSupported as e:
raise OperationalException(
f'Exchange {self._api.name} does not support fetching tickers in batch.'
f'Message: {e}')
except (ccxt.NetworkError, ccxt.ExchangeError) as e:
raise TemporaryError(
f'Could not load tickers due to {e.__class__.__name__}. Message: {e}')
except ccxt.BaseError as e:
raise OperationalException(e)
@retrier
def get_ticker(self, pair: str, refresh: Optional[bool] = True) -> dict:
if refresh or pair not in self._cached_ticker.keys():
try:
if pair not in self._api.markets:
raise DependencyException(f"Pair {pair} not available")
data = self._api.fetch_ticker(pair)
try:
self._cached_ticker[pair] = {
'bid': float(data['bid']),
'ask': float(data['ask']),
}
except KeyError:
logger.debug("Could not cache ticker data for %s", pair)
return data
except (ccxt.NetworkError, ccxt.ExchangeError) as e:
raise TemporaryError(
f'Could not load ticker due to {e.__class__.__name__}. Message: {e}')
except ccxt.BaseError as e:
raise OperationalException(e)
else:
logger.info("returning cached ticker-data for %s", pair)
return self._cached_ticker[pair]
def get_history(self, pair: str, tick_interval: str,
since_ms: int) -> List:
"""
Gets candle history using asyncio and returns the list of candles.
Handles all async doing.
"""
return asyncio.get_event_loop().run_until_complete(
self._async_get_history(pair=pair, tick_interval=tick_interval,
since_ms=since_ms))
async def _async_get_history(self, pair: str,
tick_interval: str,
since_ms: int) -> List:
# Assume exchange returns 500 candles
_LIMIT = 500
one_call = constants.TICKER_INTERVAL_MINUTES[tick_interval] * 60 * _LIMIT * 1000
logger.debug("one_call: %s", one_call)
input_coroutines = [self._async_get_candle_history(
pair, tick_interval, since) for since in
range(since_ms, arrow.utcnow().timestamp * 1000, one_call)]
tickers = await asyncio.gather(*input_coroutines, return_exceptions=True)
# Combine tickers
data: List = []
for p, ticker_interval, ticker in tickers:
if p == pair:
data.extend(ticker)
# Sort data again after extending the result - above calls return in "async order"
data = sorted(data, key=lambda x: x[0])
logger.info("downloaded %s with length %s.", pair, len(data))
return data
def refresh_latest_ohlcv(self, pair_list: List[Tuple[str, str]]) -> List[Tuple[str, List]]:
"""
Refresh in-memory ohlcv asyncronously and set `_klines` with the result
"""
logger.debug("Refreshing ohlcv data for %d pairs", len(pair_list))
input_coroutines = []
# Gather corotines to run
for pair, ticker_interval in set(pair_list):
# Calculating ticker interval in second
interval_in_sec = constants.TICKER_INTERVAL_MINUTES[ticker_interval] * 60
if not ((self._pairs_last_refresh_time.get((pair, ticker_interval), 0)
+ interval_in_sec) >= arrow.utcnow().timestamp
and (pair, ticker_interval) in self._klines):
input_coroutines.append(self._async_get_candle_history(pair, ticker_interval))
else:
logger.debug("Using cached ohlcv data for %s, %s ...", pair, ticker_interval)
tickers = asyncio.get_event_loop().run_until_complete(
asyncio.gather(*input_coroutines, return_exceptions=True))
# handle caching
for res in tickers:
if isinstance(res, Exception):
logger.warning("Async code raised an exception: %s", res.__class__.__name__)
continue
pair = res[0]
tick_interval = res[1]
ticks = res[2]
# keeping last candle time as last refreshed time of the pair
if ticks:
self._pairs_last_refresh_time[(pair, tick_interval)] = ticks[-1][0] // 1000
# keeping parsed dataframe in cache
self._klines[(pair, tick_interval)] = parse_ticker_dataframe(
ticks, tick_interval, fill_missing=True)
return tickers
@retrier_async
async def _async_get_candle_history(self, pair: str, tick_interval: str,
since_ms: Optional[int] = None) -> Tuple[str, str, List]:
"""
Asyncronously gets candle histories using fetch_ohlcv
returns tuple: (pair, tick_interval, ohlcv_list)
"""
try:
# fetch ohlcv asynchronously
logger.debug("fetching %s, %s since %s ...", pair, tick_interval, since_ms)
data = await self._api_async.fetch_ohlcv(pair, timeframe=tick_interval,
since=since_ms)
# Because some exchange sort Tickers ASC and other DESC.
# Ex: Bittrex returns a list of tickers ASC (oldest first, newest last)
# when GDAX returns a list of tickers DESC (newest first, oldest last)
# Only sort if necessary to save computing time
try:
if data and data[0][0] > data[-1][0]:
data = sorted(data, key=lambda x: x[0])
except IndexError:
logger.exception("Error loading %s. Result was %s.", pair, data)
return pair, tick_interval, []
logger.debug("done fetching %s, %s ...", pair, tick_interval)
return pair, tick_interval, data
except ccxt.NotSupported as e:
raise OperationalException(
f'Exchange {self._api.name} does not support fetching historical candlestick data.'
f'Message: {e}')
except (ccxt.NetworkError, ccxt.ExchangeError) as e:
raise TemporaryError(
f'Could not load ticker history due to {e.__class__.__name__}. Message: {e}')
except ccxt.BaseError as e:
raise OperationalException(f'Could not fetch ticker data. Msg: {e}')
@retrier
def cancel_order(self, order_id: str, pair: str) -> None:
if self._conf['dry_run']:
return
try:
return self._api.cancel_order(order_id, pair)
except ccxt.InvalidOrder as e:
raise DependencyException(
f'Could not cancel order. Message: {e}')
except (ccxt.NetworkError, ccxt.ExchangeError) as e:
raise TemporaryError(
f'Could not cancel order due to {e.__class__.__name__}. Message: {e}')
except ccxt.BaseError as e:
raise OperationalException(e)
@retrier
def get_order(self, order_id: str, pair: str) -> Dict:
if self._conf['dry_run']:
order = self._dry_run_open_orders[order_id]
order.update({
'id': order_id
})
return order
try:
return self._api.fetch_order(order_id, pair)
except ccxt.InvalidOrder as e:
raise DependencyException(
f'Could not get order. Message: {e}')
except (ccxt.NetworkError, ccxt.ExchangeError) as e:
raise TemporaryError(
f'Could not get order due to {e.__class__.__name__}. Message: {e}')
except ccxt.BaseError as e:
raise OperationalException(e)
@retrier
def get_order_book(self, pair: str, limit: int = 100) -> dict:
"""
get order book level 2 from exchange
Notes:
20180619: bittrex doesnt support limits -.-
20180619: binance support limits but only on specific range
"""
try:
if self._api.name == 'Binance':
limit_range = [5, 10, 20, 50, 100, 500, 1000]
# get next-higher step in the limit_range list
limit = min(list(filter(lambda x: limit <= x, limit_range)))
# above script works like loop below (but with slightly better performance):
# for limitx in limit_range:
# if limit <= limitx:
# limit = limitx
# break
return self._api.fetch_l2_order_book(pair, limit)
except ccxt.NotSupported as e:
raise OperationalException(
f'Exchange {self._api.name} does not support fetching order book.'
f'Message: {e}')
except (ccxt.NetworkError, ccxt.ExchangeError) as e:
raise TemporaryError(
f'Could not get order book due to {e.__class__.__name__}. Message: {e}')
except ccxt.BaseError as e:
raise OperationalException(e)
@retrier
def get_trades_for_order(self, order_id: str, pair: str, since: datetime) -> List:
if self._conf['dry_run']:
return []
if not self.exchange_has('fetchMyTrades'):
return []
try:
# Allow 5s offset to catch slight time offsets (discovered in #1185)
my_trades = self._api.fetch_my_trades(pair, since.timestamp() - 5)
matched_trades = [trade for trade in my_trades if trade['order'] == order_id]
return matched_trades
except ccxt.NetworkError as e:
raise TemporaryError(
f'Could not get trades due to networking error. Message: {e}')
except ccxt.BaseError as e:
raise OperationalException(e)
def get_pair_detail_url(self, pair: str) -> str:
try:
url_base = self._api.urls.get('www')
base, quote = pair.split('/')
return url_base + _EXCHANGE_URLS[self._api.id].format(base=base, quote=quote)
except KeyError:
logger.warning('Could not get exchange url for %s', self.name)
return ""
@retrier
def get_markets(self) -> List[dict]:
try:
return self._api.fetch_markets()
except (ccxt.NetworkError, ccxt.ExchangeError) as e:
raise TemporaryError(
f'Could not load markets due to {e.__class__.__name__}. Message: {e}')
except ccxt.BaseError as e:
raise OperationalException(e)
@retrier
def get_fee(self, symbol='ETH/BTC', type='', side='', amount=1,
price=1, taker_or_maker='maker') -> float:
try:
# validate that markets are loaded before trying to get fee
if self._api.markets is None or len(self._api.markets) == 0:
self._api.load_markets()
return self._api.calculate_fee(symbol=symbol, type=type, side=side, amount=amount,
price=price, takerOrMaker=taker_or_maker)['rate']
except (ccxt.NetworkError, ccxt.ExchangeError) as e:
raise TemporaryError(
f'Could not get fee info due to {e.__class__.__name__}. Message: {e}')
except ccxt.BaseError as e:
raise OperationalException(e)
from freqtrade.exchange.exchange import Exchange # noqa: F401
from freqtrade.exchange.kraken import Kraken # noqa: F401
from freqtrade.exchange.binance import Binance # noqa: F401

27
freqtrade/exchange/binance.py Normal file
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@ -0,0 +1,27 @@
""" Binance exchange subclass """
import logging
from typing import Dict
from freqtrade.exchange import Exchange
logger = logging.getLogger(__name__)
class Binance(Exchange):
_ft_has: Dict = {
"stoploss_on_exchange": True,
"order_time_in_force": ['gtc', 'fok', 'ioc'],
}
def get_order_book(self, pair: str, limit: int = 100) -> dict:
"""
get order book level 2 from exchange
20180619: binance support limits but only on specific range
"""
limit_range = [5, 10, 20, 50, 100, 500, 1000]
# get next-higher step in the limit_range list
limit = min(list(filter(lambda x: limit <= x, limit_range)))
return super().get_order_book(pair, limit)

691
freqtrade/exchange/exchange.py Normal file
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# pragma pylint: disable=W0603
""" Cryptocurrency Exchanges support """
import logging
import inspect
from random import randint
from typing import List, Dict, Tuple, Any, Optional
from datetime import datetime
from math import floor, ceil
import arrow
import asyncio
import ccxt
import ccxt.async_support as ccxt_async
from pandas import DataFrame
from freqtrade import (constants, DependencyException, OperationalException,
TemporaryError, InvalidOrderException)
from freqtrade.data.converter import parse_ticker_dataframe
from freqtrade.misc import timeframe_to_seconds, timeframe_to_msecs
logger = logging.getLogger(__name__)
API_RETRY_COUNT = 4
def retrier_async(f):
async def wrapper(*args, **kwargs):
count = kwargs.pop('count', API_RETRY_COUNT)
try:
return await f(*args, **kwargs)
except (TemporaryError, DependencyException) as ex:
logger.warning('%s() returned exception: "%s"', f.__name__, ex)
if count > 0:
count -= 1
kwargs.update({'count': count})
logger.warning('retrying %s() still for %s times', f.__name__, count)
return await wrapper(*args, **kwargs)
else:
logger.warning('Giving up retrying: %s()', f.__name__)
raise ex
return wrapper
def retrier(f):
def wrapper(*args, **kwargs):
count = kwargs.pop('count', API_RETRY_COUNT)
try:
return f(*args, **kwargs)
except (TemporaryError, DependencyException) as ex:
logger.warning('%s() returned exception: "%s"', f.__name__, ex)
if count > 0:
count -= 1
kwargs.update({'count': count})
logger.warning('retrying %s() still for %s times', f.__name__, count)
return wrapper(*args, **kwargs)
else:
logger.warning('Giving up retrying: %s()', f.__name__)
raise ex
return wrapper
class Exchange(object):
_config: Dict = {}
_params: Dict = {}
# Dict to specify which options each exchange implements
# TODO: this should be merged with attributes from subclasses
# To avoid having to copy/paste this to all subclasses.
_ft_has: Dict = {
"stoploss_on_exchange": False,
"order_time_in_force": ["gtc"],
}
def __init__(self, config: dict) -> None:
"""
Initializes this module with the given config,
it does basic validation whether the specified exchange and pairs are valid.
:return: None
"""
self._config.update(config)
self._cached_ticker: Dict[str, Any] = {}
# Holds last candle refreshed time of each pair
self._pairs_last_refresh_time: Dict[Tuple[str, str], int] = {}
# Timestamp of last markets refresh
self._last_markets_refresh: int = 0
# Holds candles
self._klines: Dict[Tuple[str, str], DataFrame] = {}
# Holds all open sell orders for dry_run
self._dry_run_open_orders: Dict[str, Any] = {}
if config['dry_run']:
logger.info('Instance is running with dry_run enabled')
exchange_config = config['exchange']
self._api: ccxt.Exchange = self._init_ccxt(
exchange_config, ccxt_kwargs=exchange_config.get('ccxt_config'))
self._api_async: ccxt_async.Exchange = self._init_ccxt(
exchange_config, ccxt_async, ccxt_kwargs=exchange_config.get('ccxt_async_config'))
logger.info('Using Exchange "%s"', self.name)
# Converts the interval provided in minutes in config to seconds
self.markets_refresh_interval: int = exchange_config.get(
"markets_refresh_interval", 60) * 60
# Initial markets load
self._load_markets()
# Check if all pairs are available
self.validate_pairs(config['exchange']['pair_whitelist'])
self.validate_ordertypes(config.get('order_types', {}))
self.validate_order_time_in_force(config.get('order_time_in_force', {}))
if config.get('ticker_interval'):
# Check if timeframe is available
self.validate_timeframes(config['ticker_interval'])
def __del__(self):
"""
Destructor - clean up async stuff
"""
logger.debug("Exchange object destroyed, closing async loop")
if self._api_async and inspect.iscoroutinefunction(self._api_async.close):
asyncio.get_event_loop().run_until_complete(self._api_async.close())
def _init_ccxt(self, exchange_config: dict, ccxt_module=ccxt,
ccxt_kwargs: dict = None) -> ccxt.Exchange:
"""
Initialize ccxt with given config and return valid
ccxt instance.
"""
# Find matching class for the given exchange name
name = exchange_config['name']
if name not in ccxt_module.exchanges:
raise OperationalException(f'Exchange {name} is not supported')
ex_config = {
'apiKey': exchange_config.get('key'),
'secret': exchange_config.get('secret'),
'password': exchange_config.get('password'),
'uid': exchange_config.get('uid', ''),
}
if ccxt_kwargs:
logger.info('Applying additional ccxt config: %s', ccxt_kwargs)
ex_config.update(ccxt_kwargs)
try:
api = getattr(ccxt_module, name.lower())(ex_config)
except (KeyError, AttributeError):
raise OperationalException(f'Exchange {name} is not supported')
self.set_sandbox(api, exchange_config, name)
return api
@property
def name(self) -> str:
"""exchange Name (from ccxt)"""
return self._api.name
@property
def id(self) -> str:
"""exchange ccxt id"""
return self._api.id
@property
def markets(self) -> Dict:
"""exchange ccxt markets"""
if not self._api.markets:
logger.warning("Markets were not loaded. Loading them now..")
self._load_markets()
return self._api.markets
def klines(self, pair_interval: Tuple[str, str], copy=True) -> DataFrame:
if pair_interval in self._klines:
return self._klines[pair_interval].copy() if copy else self._klines[pair_interval]
else:
return DataFrame()
def set_sandbox(self, api, exchange_config: dict, name: str):
if exchange_config.get('sandbox'):
if api.urls.get('test'):
api.urls['api'] = api.urls['test']
logger.info("Enabled Sandbox API on %s", name)
else:
logger.warning(name, "No Sandbox URL in CCXT, exiting. "
"Please check your config.json")
raise OperationalException(f'Exchange {name} does not provide a sandbox api')
def _load_async_markets(self, reload=False) -> None:
try:
if self._api_async:
asyncio.get_event_loop().run_until_complete(
self._api_async.load_markets(reload=reload))
except ccxt.BaseError as e:
logger.warning('Could not load async markets. Reason: %s', e)
return
def _load_markets(self) -> None:
""" Initialize markets both sync and async """
try:
self._api.load_markets()
self._load_async_markets()
self._last_markets_refresh = arrow.utcnow().timestamp
except ccxt.BaseError as e:
logger.warning('Unable to initialize markets. Reason: %s', e)
def _reload_markets(self) -> None:
"""Reload markets both sync and async, if refresh interval has passed"""
# Check whether markets have to be reloaded
if (self._last_markets_refresh > 0) and (
self._last_markets_refresh + self.markets_refresh_interval
> arrow.utcnow().timestamp):
return None
logger.debug("Performing scheduled market reload..")
self._api.load_markets(reload=True)
self._last_markets_refresh = arrow.utcnow().timestamp
def validate_pairs(self, pairs: List[str]) -> None:
"""
Checks if all given pairs are tradable on the current exchange.
Raises OperationalException if one pair is not available.
:param pairs: list of pairs
:return: None
"""
if not self.markets:
logger.warning('Unable to validate pairs (assuming they are correct).')
# return
for pair in pairs:
# Note: ccxt has BaseCurrency/QuoteCurrency format for pairs
# TODO: add a support for having coins in BTC/USDT format
if self.markets and pair not in self.markets:
raise OperationalException(
f'Pair {pair} is not available on {self.name}. '
f'Please remove {pair} from your whitelist.')
def validate_timeframes(self, timeframe: List[str]) -> None:
"""
Checks if ticker interval from config is a supported timeframe on the exchange
"""
timeframes = self._api.timeframes
if timeframe not in timeframes:
raise OperationalException(
f'Invalid ticker {timeframe}, this Exchange supports {timeframes}')
def validate_ordertypes(self, order_types: Dict) -> None:
"""
Checks if order-types configured in strategy/config are supported
"""
if any(v == 'market' for k, v in order_types.items()):
if not self.exchange_has('createMarketOrder'):
raise OperationalException(
f'Exchange {self.name} does not support market orders.')
if (order_types.get("stoploss_on_exchange")
and not self._ft_has.get("stoploss_on_exchange", False)):
raise OperationalException(
'On exchange stoploss is not supported for %s.' % self.name
)
def validate_order_time_in_force(self, order_time_in_force: Dict) -> None:
"""
Checks if order time in force configured in strategy/config are supported
"""
if any(v not in self._ft_has["order_time_in_force"]
for k, v in order_time_in_force.items()):
raise OperationalException(
f'Time in force policies are not supported for {self.name} yet.')
def exchange_has(self, endpoint: str) -> bool:
"""
Checks if exchange implements a specific API endpoint.
Wrapper around ccxt 'has' attribute
:param endpoint: Name of endpoint (e.g. 'fetchOHLCV', 'fetchTickers')
:return: bool
"""
return endpoint in self._api.has and self._api.has[endpoint]
def symbol_amount_prec(self, pair, amount: float):
'''
Returns the amount to buy or sell to a precision the Exchange accepts
Rounded down
'''
if self.markets[pair]['precision']['amount']:
symbol_prec = self.markets[pair]['precision']['amount']
big_amount = amount * pow(10, symbol_prec)
amount = floor(big_amount) / pow(10, symbol_prec)
return amount
def symbol_price_prec(self, pair, price: float):
'''
Returns the price buying or selling with to the precision the Exchange accepts
Rounds up
'''
if self.markets[pair]['precision']['price']:
symbol_prec = self.markets[pair]['precision']['price']
big_price = price * pow(10, symbol_prec)
price = ceil(big_price) / pow(10, symbol_prec)
return price
def dry_run_order(self, pair: str, ordertype: str, side: str, amount: float,
rate: float, params: Dict = {}) -> Dict[str, Any]:
order_id = f'dry_run_{side}_{randint(0, 10**6)}'
dry_order = { # TODO: additional entry should be added for stoploss limit
"id": order_id,
'pair': pair,
'price': rate,
'amount': amount,
"cost": amount * rate,
'type': ordertype,
'side': side,
'remaining': amount,
'datetime': arrow.utcnow().isoformat(),
'status': "open",
'fee': None,
"info": {}
}
self._store_dry_order(dry_order)
return dry_order
def _store_dry_order(self, dry_order: Dict) -> None:
closed_order = dry_order.copy()
if closed_order["type"] in ["market", "limit"]:
closed_order.update({
"status": "closed",
"filled": closed_order["amount"],
"remaining": 0
})
self._dry_run_open_orders[closed_order["id"]] = closed_order
def create_order(self, pair: str, ordertype: str, side: str, amount: float,
rate: float, params: Dict = {}) -> Dict:
try:
# Set the precision for amount and price(rate) as accepted by the exchange
amount = self.symbol_amount_prec(pair, amount)
rate = self.symbol_price_prec(pair, rate) if ordertype != 'market' else None
return self._api.create_order(pair, ordertype, side,
amount, rate, params)
except ccxt.InsufficientFunds as e:
raise DependencyException(
f'Insufficient funds to create {ordertype} {side} order on market {pair}.'
f'Tried to {side} amount {amount} at rate {rate} (total {rate*amount}).'
f'Message: {e}')
except ccxt.InvalidOrder as e:
raise DependencyException(
f'Could not create {ordertype} {side} order on market {pair}.'
f'Tried to {side} amount {amount} at rate {rate} (total {rate*amount}).'
f'Message: {e}')
except (ccxt.NetworkError, ccxt.ExchangeError) as e:
raise TemporaryError(
f'Could not place {side} order due to {e.__class__.__name__}. Message: {e}')
except ccxt.BaseError as e:
raise OperationalException(e)
def buy(self, pair: str, ordertype: str, amount: float,
rate: float, time_in_force) -> Dict:
if self._config['dry_run']:
dry_order = self.dry_run_order(pair, ordertype, "buy", amount, rate)
return dry_order
params = self._params.copy()
if time_in_force != 'gtc' and ordertype != 'market':
params.update({'timeInForce': time_in_force})
return self.create_order(pair, ordertype, 'buy', amount, rate, params)
def sell(self, pair: str, ordertype: str, amount: float,
rate: float, time_in_force='gtc') -> Dict:
if self._config['dry_run']:
dry_order = self.dry_run_order(pair, ordertype, "sell", amount, rate)
return dry_order
params = self._params.copy()
if time_in_force != 'gtc' and ordertype != 'market':
params.update({'timeInForce': time_in_force})
return self.create_order(pair, ordertype, 'sell', amount, rate, params)
def stoploss_limit(self, pair: str, amount: float, stop_price: float, rate: float) -> Dict:
"""
creates a stoploss limit order.
NOTICE: it is not supported by all exchanges. only binance is tested for now.
TODO: implementation maybe needs to be moved to the binance subclass
"""
ordertype = "stop_loss_limit"
stop_price = self.symbol_price_prec(pair, stop_price)
# Ensure rate is less than stop price
if stop_price <= rate:
raise OperationalException(
'In stoploss limit order, stop price should be more than limit price')
if self._config['dry_run']:
dry_order = self.dry_run_order(
pair, ordertype, "sell", amount, stop_price)
return dry_order
params = self._params.copy()
params.update({'stopPrice': stop_price})
order = self.create_order(pair, ordertype, 'sell', amount, rate, params)
logger.info('stoploss limit order added for %s. '
'stop price: %s. limit: %s' % (pair, stop_price, rate))
return order
@retrier
def get_balance(self, currency: str) -> float:
if self._config['dry_run']:
return constants.DRY_RUN_WALLET
# ccxt exception is already handled by get_balances
balances = self.get_balances()
balance = balances.get(currency)
if balance is None:
raise TemporaryError(
f'Could not get {currency} balance due to malformed exchange response: {balances}')
return balance['free']
@retrier
def get_balances(self) -> dict:
if self._config['dry_run']:
return {}
try:
balances = self._api.fetch_balance()
# Remove additional info from ccxt results
balances.pop("info", None)
balances.pop("free", None)
balances.pop("total", None)
balances.pop("used", None)
return balances
except (ccxt.NetworkError, ccxt.ExchangeError) as e:
raise TemporaryError(
f'Could not get balance due to {e.__class__.__name__}. Message: {e}')
except ccxt.BaseError as e:
raise OperationalException(e)
@retrier
def get_tickers(self) -> Dict:
try:
return self._api.fetch_tickers()
except ccxt.NotSupported as e:
raise OperationalException(
f'Exchange {self._api.name} does not support fetching tickers in batch.'
f'Message: {e}')
except (ccxt.NetworkError, ccxt.ExchangeError) as e:
raise TemporaryError(
f'Could not load tickers due to {e.__class__.__name__}. Message: {e}')
except ccxt.BaseError as e:
raise OperationalException(e)
@retrier
def get_ticker(self, pair: str, refresh: Optional[bool] = True) -> dict:
if refresh or pair not in self._cached_ticker.keys():
try:
if pair not in self._api.markets:
raise DependencyException(f"Pair {pair} not available")
data = self._api.fetch_ticker(pair)
try:
self._cached_ticker[pair] = {
'bid': float(data['bid']),
'ask': float(data['ask']),
}
except KeyError:
logger.debug("Could not cache ticker data for %s", pair)
return data
except (ccxt.NetworkError, ccxt.ExchangeError) as e:
raise TemporaryError(
f'Could not load ticker due to {e.__class__.__name__}. Message: {e}')
except ccxt.BaseError as e:
raise OperationalException(e)
else:
logger.info("returning cached ticker-data for %s", pair)
return self._cached_ticker[pair]
def get_history(self, pair: str, ticker_interval: str,
since_ms: int) -> List:
"""
Gets candle history using asyncio and returns the list of candles.
Handles all async doing.
"""
return asyncio.get_event_loop().run_until_complete(
self._async_get_history(pair=pair, ticker_interval=ticker_interval,
since_ms=since_ms))
async def _async_get_history(self, pair: str,
ticker_interval: str,
since_ms: int) -> List:
# Assume exchange returns 500 candles
_LIMIT = 500
one_call = timeframe_to_msecs(ticker_interval) * _LIMIT
logger.debug("one_call: %s msecs", one_call)
input_coroutines = [self._async_get_candle_history(
pair, ticker_interval, since) for since in
range(since_ms, arrow.utcnow().timestamp * 1000, one_call)]
tickers = await asyncio.gather(*input_coroutines, return_exceptions=True)
# Combine tickers
data: List = []
for p, ticker_interval, ticker in tickers:
if p == pair:
data.extend(ticker)
# Sort data again after extending the result - above calls return in "async order"
data = sorted(data, key=lambda x: x[0])
logger.info("downloaded %s with length %s.", pair, len(data))
return data
def refresh_latest_ohlcv(self, pair_list: List[Tuple[str, str]]) -> List[Tuple[str, List]]:
"""
Refresh in-memory ohlcv asyncronously and set `_klines` with the result
"""
logger.debug("Refreshing ohlcv data for %d pairs", len(pair_list))
input_coroutines = []
# Gather coroutines to run
for pair, ticker_interval in set(pair_list):
if (not ((pair, ticker_interval) in self._klines)
or self._now_is_time_to_refresh(pair, ticker_interval)):
input_coroutines.append(self._async_get_candle_history(pair, ticker_interval))
else:
logger.debug("Using cached ohlcv data for %s, %s ...", pair, ticker_interval)
tickers = asyncio.get_event_loop().run_until_complete(
asyncio.gather(*input_coroutines, return_exceptions=True))
# handle caching
for res in tickers:
if isinstance(res, Exception):
logger.warning("Async code raised an exception: %s", res.__class__.__name__)
continue
pair = res[0]
ticker_interval = res[1]
ticks = res[2]
# keeping last candle time as last refreshed time of the pair
if ticks:
self._pairs_last_refresh_time[(pair, ticker_interval)] = ticks[-1][0] // 1000
# keeping parsed dataframe in cache
self._klines[(pair, ticker_interval)] = parse_ticker_dataframe(
ticks, ticker_interval, fill_missing=True)
return tickers
def _now_is_time_to_refresh(self, pair: str, ticker_interval: str) -> bool:
# Calculating ticker interval in seconds
interval_in_sec = timeframe_to_seconds(ticker_interval)
return not ((self._pairs_last_refresh_time.get((pair, ticker_interval), 0)
+ interval_in_sec) >= arrow.utcnow().timestamp)
@retrier_async
async def _async_get_candle_history(self, pair: str, ticker_interval: str,
since_ms: Optional[int] = None) -> Tuple[str, str, List]:
"""
Asyncronously gets candle histories using fetch_ohlcv
returns tuple: (pair, ticker_interval, ohlcv_list)
"""
try:
# fetch ohlcv asynchronously
logger.debug("fetching %s, %s since %s ...", pair, ticker_interval, since_ms)
data = await self._api_async.fetch_ohlcv(pair, timeframe=ticker_interval,
since=since_ms)
# Because some exchange sort Tickers ASC and other DESC.
# Ex: Bittrex returns a list of tickers ASC (oldest first, newest last)
# when GDAX returns a list of tickers DESC (newest first, oldest last)
# Only sort if necessary to save computing time
try:
if data and data[0][0] > data[-1][0]:
data = sorted(data, key=lambda x: x[0])
except IndexError:
logger.exception("Error loading %s. Result was %s.", pair, data)
return pair, ticker_interval, []
logger.debug("done fetching %s, %s ...", pair, ticker_interval)
return pair, ticker_interval, data
except ccxt.NotSupported as e:
raise OperationalException(
f'Exchange {self._api.name} does not support fetching historical candlestick data.'
f'Message: {e}')
except (ccxt.NetworkError, ccxt.ExchangeError) as e:
raise TemporaryError(
f'Could not load ticker history due to {e.__class__.__name__}. Message: {e}')
except ccxt.BaseError as e:
raise OperationalException(f'Could not fetch ticker data. Msg: {e}')
@retrier
def cancel_order(self, order_id: str, pair: str) -> None:
if self._config['dry_run']:
return
try:
return self._api.cancel_order(order_id, pair)
except ccxt.InvalidOrder as e:
raise InvalidOrderException(
f'Could not cancel order. Message: {e}')
except (ccxt.NetworkError, ccxt.ExchangeError) as e:
raise TemporaryError(
f'Could not cancel order due to {e.__class__.__name__}. Message: {e}')
except ccxt.BaseError as e:
raise OperationalException(e)
@retrier
def get_order(self, order_id: str, pair: str) -> Dict:
if self._config['dry_run']:
order = self._dry_run_open_orders[order_id]
return order
try:
return self._api.fetch_order(order_id, pair)
except ccxt.InvalidOrder as e:
raise InvalidOrderException(
f'Tried to get an invalid order (id: {order_id}). Message: {e}')
except (ccxt.NetworkError, ccxt.ExchangeError) as e:
raise TemporaryError(
f'Could not get order due to {e.__class__.__name__}. Message: {e}')
except ccxt.BaseError as e:
raise OperationalException(e)
@retrier
def get_order_book(self, pair: str, limit: int = 100) -> dict:
"""
get order book level 2 from exchange
Notes:
20180619: bittrex doesnt support limits -.-
"""
try:
return self._api.fetch_l2_order_book(pair, limit)
except ccxt.NotSupported as e:
raise OperationalException(
f'Exchange {self._api.name} does not support fetching order book.'
f'Message: {e}')
except (ccxt.NetworkError, ccxt.ExchangeError) as e:
raise TemporaryError(
f'Could not get order book due to {e.__class__.__name__}. Message: {e}')
except ccxt.BaseError as e:
raise OperationalException(e)
@retrier
def get_trades_for_order(self, order_id: str, pair: str, since: datetime) -> List:
if self._config['dry_run']:
return []
if not self.exchange_has('fetchMyTrades'):
return []
try:
# Allow 5s offset to catch slight time offsets (discovered in #1185)
my_trades = self._api.fetch_my_trades(pair, since.timestamp() - 5)
matched_trades = [trade for trade in my_trades if trade['order'] == order_id]
return matched_trades
except ccxt.NetworkError as e:
raise TemporaryError(
f'Could not get trades due to networking error. Message: {e}')
except ccxt.BaseError as e:
raise OperationalException(e)
@retrier
def get_fee(self, symbol='ETH/BTC', type='', side='', amount=1,
price=1, taker_or_maker='maker') -> float:
try:
# validate that markets are loaded before trying to get fee
if self._api.markets is None or len(self._api.markets) == 0:
self._api.load_markets()
return self._api.calculate_fee(symbol=symbol, type=type, side=side, amount=amount,
price=price, takerOrMaker=taker_or_maker)['rate']
except (ccxt.NetworkError, ccxt.ExchangeError) as e:
raise TemporaryError(
f'Could not get fee info due to {e.__class__.__name__}. Message: {e}')
except ccxt.BaseError as e:
raise OperationalException(e)

12
freqtrade/exchange/kraken.py Normal file
View File

@ -0,0 +1,12 @@
""" Kraken exchange subclass """
import logging
from typing import Dict
from freqtrade.exchange import Exchange
logger = logging.getLogger(__name__)
class Kraken(Exchange):
_params: Dict = {"trading_agreement": "agree"}

380
freqtrade/freqtradebot.py
View File

@ -4,23 +4,22 @@ Freqtrade is the main module of this bot. It contains the class Freqtrade()
import copy
import logging
import time
import traceback
from datetime import datetime
from typing import Any, Callable, Dict, List, Optional
from typing import Any, Dict, List, Optional, Tuple
import arrow
from requests.exceptions import RequestException
from freqtrade import (DependencyException, OperationalException,
TemporaryError, __version__, constants, persistence)
from freqtrade import (DependencyException, OperationalException, InvalidOrderException,
__version__, constants, persistence)
from freqtrade.data.converter import order_book_to_dataframe
from freqtrade.data.dataprovider import DataProvider
from freqtrade.edge import Edge
from freqtrade.exchange import Exchange
from freqtrade.misc import timeframe_to_minutes
from freqtrade.persistence import Trade
from freqtrade.rpc import RPCManager, RPCMessageType
from freqtrade.resolvers import StrategyResolver, PairListResolver
from freqtrade.resolvers import ExchangeResolver, StrategyResolver, PairListResolver
from freqtrade.state import State
from freqtrade.strategy.interface import SellType, IStrategy
from freqtrade.wallets import Wallets
@ -42,21 +41,22 @@ class FreqtradeBot(object):
to get the config dict.
"""
logger.info(
'Starting freqtrade %s',
__version__,
)
logger.info('Starting freqtrade %s', __version__)
# Init bot states
# Init bot state
self.state = State.STOPPED
# Init objects
self.config = config
self.strategy: IStrategy = StrategyResolver(self.config).strategy
self.rpc: RPCManager = RPCManager(self)
self.exchange = Exchange(self.config)
self.wallets = Wallets(self.exchange)
exchange_name = self.config.get('exchange', {}).get('name', 'bittrex').title()
self.exchange = ExchangeResolver(exchange_name, self.config).exchange
self.wallets = Wallets(self.config, self.exchange)
self.dataprovider = DataProvider(self.config, self.exchange)
# Attach Dataprovider to Strategy baseclass
@ -72,24 +72,12 @@ class FreqtradeBot(object):
self.config.get('edge', {}).get('enabled', False) else None
self.active_pair_whitelist: List[str] = self.config['exchange']['pair_whitelist']
self._init_modules()
def _init_modules(self) -> None:
"""
Initializes all modules and updates the config
:return: None
"""
# Initialize all modules
persistence.init(self.config)
# Set initial application state
# Set initial bot state from config
initial_state = self.config.get('initial_state')
if initial_state:
self.state = State[initial_state.upper()]
else:
self.state = State.STOPPED
self.state = State[initial_state.upper()] if initial_state else State.STOPPED
def cleanup(self) -> None:
"""
@ -97,114 +85,69 @@ class FreqtradeBot(object):
:return: None
"""
logger.info('Cleaning up modules ...')
self.rpc.cleanup()
persistence.cleanup()
def worker(self, old_state: State = None) -> State:
"""
Trading routine that must be run at each loop
:param old_state: the previous service state from the previous call
:return: current service state
"""
# Log state transition
state = self.state
if state != old_state:
self.rpc.send_msg({
'type': RPCMessageType.STATUS_NOTIFICATION,
'status': f'{state.name.lower()}'
})
logger.info('Changing state to: %s', state.name)
if state == State.RUNNING:
self.rpc.startup_messages(self.config, self.pairlists)
if state == State.STOPPED:
time.sleep(1)
elif state == State.RUNNING:
min_secs = self.config.get('internals', {}).get(
'process_throttle_secs',
constants.PROCESS_THROTTLE_SECS
)
self._throttle(func=self._process,
min_secs=min_secs)
return state
def _throttle(self, func: Callable[..., Any], min_secs: float, *args, **kwargs) -> Any:
"""
Throttles the given callable that it
takes at least `min_secs` to finish execution.
:param func: Any callable
:param min_secs: minimum execution time in seconds
:return: Any
"""
start = time.time()
result = func(*args, **kwargs)
end = time.time()
duration = max(min_secs - (end - start), 0.0)
logger.debug('Throttling %s for %.2f seconds', func.__name__, duration)
time.sleep(duration)
return result
def _process(self) -> bool:
def process(self) -> bool:
"""
Queries the persistence layer for open trades and handles them,
otherwise a new trade is created.
:return: True if one or more trades has been created or closed, False otherwise
"""
state_changed = False
try:
# Refresh whitelist
self.pairlists.refresh_pairlist()
self.active_pair_whitelist = self.pairlists.whitelist
# Calculating Edge positiong
if self.edge:
self.edge.calculate()
self.active_pair_whitelist = self.edge.adjust(self.active_pair_whitelist)
# Check whether markets have to be reloaded
self.exchange._reload_markets()
# Query trades from persistence layer
trades = Trade.query.filter(Trade.is_open.is_(True)).all()
# Refresh whitelist
self.pairlists.refresh_pairlist()
self.active_pair_whitelist = self.pairlists.whitelist
# Extend active-pair whitelist with pairs from open trades
# ensures that tickers are downloaded for open trades
self.active_pair_whitelist.extend([trade.pair for trade in trades
if trade.pair not in self.active_pair_whitelist])
# Calculating Edge positioning
if self.edge:
self.edge.calculate()
self.active_pair_whitelist = self.edge.adjust(self.active_pair_whitelist)
# Create pair-whitelist tuple with (pair, ticker_interval)
pair_whitelist_tuple = [(pair, self.config['ticker_interval'])
for pair in self.active_pair_whitelist]
# Refreshing candles
self.dataprovider.refresh(pair_whitelist_tuple,
self.strategy.informative_pairs())
# Query trades from persistence layer
trades = Trade.get_open_trades()
# First process current opened trades
for trade in trades:
state_changed |= self.process_maybe_execute_sell(trade)
# Extend active-pair whitelist with pairs from open trades
# It ensures that tickers are downloaded for open trades
self._extend_whitelist_with_trades(self.active_pair_whitelist, trades)
# Then looking for buy opportunities
if len(trades) < self.config['max_open_trades']:
state_changed = self.process_maybe_execute_buy()
# Refreshing candles
self.dataprovider.refresh(self._create_pair_whitelist(self.active_pair_whitelist),
self.strategy.informative_pairs())
if 'unfilledtimeout' in self.config:
# Check and handle any timed out open orders
self.check_handle_timedout()
Trade.session.flush()
# First process current opened trades
for trade in trades:
state_changed |= self.process_maybe_execute_sell(trade)
# Then looking for buy opportunities
if len(trades) < self.config['max_open_trades']:
state_changed = self.process_maybe_execute_buy()
if 'unfilledtimeout' in self.config:
# Check and handle any timed out open orders
self.check_handle_timedout()
Trade.session.flush()
except TemporaryError as error:
logger.warning(f"Error: {error}, retrying in {constants.RETRY_TIMEOUT} seconds...")
time.sleep(constants.RETRY_TIMEOUT)
except OperationalException:
tb = traceback.format_exc()
hint = 'Issue `/start` if you think it is safe to restart.'
self.rpc.send_msg({
'type': RPCMessageType.STATUS_NOTIFICATION,
'status': f'OperationalException:\n```\n{tb}```{hint}'
})
logger.exception('OperationalException. Stopping trader ...')
self.state = State.STOPPED
return state_changed
def get_target_bid(self, pair: str) -> float:
def _extend_whitelist_with_trades(self, whitelist: List[str], trades: List[Any]):
"""
Extend whitelist with pairs from open trades
"""
whitelist.extend([trade.pair for trade in trades if trade.pair not in whitelist])
def _create_pair_whitelist(self, pairs: List[str]) -> List[Tuple[str, str]]:
"""
Create pair-whitelist tuple with (pair, ticker_interval)
"""
return [(pair, self.config['ticker_interval']) for pair in pairs]
def get_target_bid(self, pair: str, tick: Dict = None) -> float:
"""
Calculates bid target between current ask price and last price
:return: float: Price
@ -221,8 +164,11 @@ class FreqtradeBot(object):
logger.info('...top %s order book buy rate %0.8f', order_book_top, order_book_rate)
used_rate = order_book_rate
else:
logger.info('Using Last Ask / Last Price')
ticker = self.exchange.get_ticker(pair)
if not tick:
logger.info('Using Last Ask / Last Price')
ticker = self.exchange.get_ticker(pair)
else:
ticker = tick
if ticker['ask'] < ticker['last']:
ticker_rate = ticker['ask']
else:
@ -251,7 +197,7 @@ class FreqtradeBot(object):
avaliable_amount = self.wallets.get_free(self.config['stake_currency'])
if stake_amount == constants.UNLIMITED_STAKE_AMOUNT:
open_trades = len(Trade.query.filter(Trade.is_open.is_(True)).all())
open_trades = len(Trade.get_open_trades())
if open_trades >= self.config['max_open_trades']:
logger.warning('Can\'t open a new trade: max number of trades is reached')
return None
@ -267,12 +213,10 @@ class FreqtradeBot(object):
return stake_amount
def _get_min_pair_stake_amount(self, pair: str, price: float) -> Optional[float]:
markets = self.exchange.get_markets()
markets = [m for m in markets if m['symbol'] == pair]
if not markets:
raise ValueError(f'Can\'t get market information for symbol {pair}')
market = markets[0]
try:
market = self.exchange.markets[pair]
except KeyError:
raise ValueError(f"Can't get market information for symbol {pair}")
if 'limits' not in market:
return None
@ -308,14 +252,19 @@ class FreqtradeBot(object):
interval = self.strategy.ticker_interval
whitelist = copy.deepcopy(self.active_pair_whitelist)
if not whitelist:
logger.warning("Whitelist is empty.")
return False
# Remove currently opened and latest pairs from whitelist
for trade in Trade.query.filter(Trade.is_open.is_(True)).all():
for trade in Trade.get_open_trades():
if trade.pair in whitelist:
whitelist.remove(trade.pair)
logger.debug('Ignoring %s in pair whitelist', trade.pair)
if not whitelist:
raise DependencyException('No currency pairs in whitelist')
logger.info("No currency pair in whitelist, but checking to sell open trades.")
return False
# running get_signal on historical data fetched
for _pair in whitelist:
@ -366,7 +315,6 @@ class FreqtradeBot(object):
:return: None
"""
pair_s = pair.replace('_', '/')
pair_url = self.exchange.get_pair_detail_url(pair)
stake_currency = self.config['stake_currency']
fiat_currency = self.config.get('fiat_display_currency', None)
time_in_force = self.strategy.order_time_in_force['buy']
@ -425,13 +373,11 @@ class FreqtradeBot(object):
stake_amount = order['cost']
amount = order['amount']
buy_limit_filled_price = order['price']
order_id = None
self.rpc.send_msg({
'type': RPCMessageType.BUY_NOTIFICATION,
'exchange': self.exchange.name.capitalize(),
'pair': pair_s,
'market_url': pair_url,
'limit': buy_limit_filled_price,
'stake_amount': stake_amount,
'stake_currency': stake_currency,
@ -452,9 +398,13 @@ class FreqtradeBot(object):
exchange=self.exchange.id,
open_order_id=order_id,
strategy=self.strategy.get_strategy_name(),
ticker_interval=constants.TICKER_INTERVAL_MINUTES[self.config['ticker_interval']]
ticker_interval=timeframe_to_minutes(self.config['ticker_interval'])
)
# Update fees if order is closed
if order_status == 'closed':
self.update_trade_state(trade, order)
Trade.session.add(trade)
Trade.session.flush()
@ -485,23 +435,7 @@ class FreqtradeBot(object):
:return: True if executed
"""
try:
# Get order details for actual price per unit
if trade.open_order_id:
# Update trade with order values
logger.info('Found open order for %s', trade)
order = self.exchange.get_order(trade.open_order_id, trade.pair)
# Try update amount (binance-fix)
try:
new_amount = self.get_real_amount(trade, order)
if order['amount'] != new_amount:
order['amount'] = new_amount
# Fee was applied, so set to 0
trade.fee_open = 0
except OperationalException as exception:
logger.warning("Could not update trade amount: %s", exception)
trade.update(order)
self.update_trade_state(trade)
if self.strategy.order_types.get('stoploss_on_exchange') and trade.is_open:
result = self.handle_stoploss_on_exchange(trade)
@ -566,6 +500,47 @@ class FreqtradeBot(object):
f"(from {order_amount} to {real_amount}) from Trades")
return real_amount
def update_trade_state(self, trade, action_order: dict = None):
"""
Checks trades with open orders and updates the amount if necessary
"""
# Get order details for actual price per unit
if trade.open_order_id:
# Update trade with order values
logger.info('Found open order for %s', trade)
order = action_order or self.exchange.get_order(trade.open_order_id, trade.pair)
# Try update amount (binance-fix)
try:
new_amount = self.get_real_amount(trade, order)
if order['amount'] != new_amount:
order['amount'] = new_amount
# Fee was applied, so set to 0
trade.fee_open = 0
except OperationalException as exception:
logger.warning("Could not update trade amount: %s", exception)
trade.update(order)
def get_sell_rate(self, pair: str, refresh: bool) -> float:
"""
Get sell rate - either using get-ticker bid or first bid based on orderbook
The orderbook portion is only used for rpc messaging, which would otherwise fail
for BitMex (has no bid/ask in get_ticker)
or remain static in any other case since it's not updating.
:return: Bid rate
"""
config_ask_strategy = self.config.get('ask_strategy', {})
if config_ask_strategy.get('use_order_book', False):
logger.debug('Using order book to get sell rate')
order_book = self.exchange.get_order_book(pair, 1)
rate = order_book['bids'][0][0]
else:
rate = self.exchange.get_ticker(pair, refresh)['bid']
return rate
def handle_trade(self, trade: Trade) -> bool:
"""
Sells the current pair if the threshold is reached and updates the trade record.
@ -602,7 +577,7 @@ class FreqtradeBot(object):
else:
logger.debug('checking sell')
sell_rate = self.exchange.get_ticker(trade.pair)['bid']
sell_rate = self.get_sell_rate(trade.pair, True)
if self.check_sell(trade, sell_rate, buy, sell):
return True
@ -616,11 +591,25 @@ class FreqtradeBot(object):
is enabled.
"""
result = False
logger.debug('Handling stoploss on exchange %s ...', trade)
# If trade is open and the buy order is fulfilled but there is no stoploss,
# then we add a stoploss on exchange
if not trade.open_order_id and not trade.stoploss_order_id:
stoploss_order = None
try:
# First we check if there is already a stoploss on exchange
stoploss_order = self.exchange.get_order(trade.stoploss_order_id, trade.pair) \
if trade.stoploss_order_id else None
except InvalidOrderException as exception:
logger.warning('Unable to fetch stoploss order: %s', exception)
# If trade open order id does not exist: buy order is fulfilled
buy_order_fulfilled = not trade.open_order_id
# Limit price threshold: As limit price should always be below price
limit_price_pct = 0.99
# If buy order is fulfilled but there is no stoploss, we add a stoploss on exchange
if (buy_order_fulfilled and not stoploss_order):
if self.edge:
stoploss = self.edge.stoploss(pair=trade.pair)
else:
@ -629,31 +618,47 @@ class FreqtradeBot(object):
stop_price = trade.open_rate * (1 + stoploss)
# limit price should be less than stop price.
# 0.99 is arbitrary here.
limit_price = stop_price * 0.99
limit_price = stop_price * limit_price_pct
stoploss_order_id = self.exchange.stoploss_limit(
pair=trade.pair, amount=trade.amount, stop_price=stop_price, rate=limit_price
)['id']
trade.stoploss_order_id = str(stoploss_order_id)
trade.stoploss_last_update = datetime.now()
try:
stoploss_order_id = self.exchange.stoploss_limit(
pair=trade.pair, amount=trade.amount, stop_price=stop_price, rate=limit_price
)['id']
trade.stoploss_order_id = str(stoploss_order_id)
trade.stoploss_last_update = datetime.now()
return False
# Or the trade open and there is already a stoploss on exchange.
# so we check if it is hit ...
elif trade.stoploss_order_id:
logger.debug('Handling stoploss on exchange %s ...', trade)
order = self.exchange.get_order(trade.stoploss_order_id, trade.pair)
if order['status'] == 'closed':
trade.sell_reason = SellType.STOPLOSS_ON_EXCHANGE.value
trade.update(order)
result = True
elif self.config.get('trailing_stop', False):
# if trailing stoploss is enabled we check if stoploss value has changed
# in which case we cancel stoploss order and put another one with new
# value immediately
self.handle_trailing_stoploss_on_exchange(trade, order)
except DependencyException as exception:
logger.warning('Unable to place a stoploss order on exchange: %s', exception)
return result
# If stoploss order is canceled for some reason we add it
if stoploss_order and stoploss_order['status'] == 'canceled':
try:
stoploss_order_id = self.exchange.stoploss_limit(
pair=trade.pair, amount=trade.amount,
stop_price=trade.stop_loss, rate=trade.stop_loss * limit_price_pct
)['id']
trade.stoploss_order_id = str(stoploss_order_id)
return False
except DependencyException as exception:
logger.warning('Stoploss order was cancelled, '
'but unable to recreate one: %s', exception)
# We check if stoploss order is fulfilled
if stoploss_order and stoploss_order['status'] == 'closed':
trade.sell_reason = SellType.STOPLOSS_ON_EXCHANGE.value
trade.update(stoploss_order)
self.notify_sell(trade)
return True
# Finally we check if stoploss on exchange should be moved up because of trailing.
if stoploss_order and self.config.get('trailing_stop', False):
# if trailing stoploss is enabled we check if stoploss value has changed
# in which case we cancel stoploss order and put another one with new
# value immediately
self.handle_trailing_stoploss_on_exchange(trade, stoploss_order)
return False
def handle_trailing_stoploss_on_exchange(self, trade: Trade, order):
"""
@ -669,8 +674,8 @@ class FreqtradeBot(object):
update_beat = self.strategy.order_types.get('stoploss_on_exchange_interval', 60)
if (datetime.utcnow() - trade.stoploss_last_update).total_seconds() > update_beat:
# cancelling the current stoploss on exchange first
logger.info('Trailing stoploss: cancelling current stoploss on exchange '
'in order to add another one ...')
logger.info('Trailing stoploss: cancelling current stoploss on exchange (id:{%s})'
'in order to add another one ...', order['id'])
if self.exchange.cancel_order(order['id'], trade.pair):
# creating the new one
stoploss_order_id = self.exchange.stoploss_limit(
@ -835,11 +840,18 @@ class FreqtradeBot(object):
trade.open_order_id = order_id
trade.close_rate_requested = limit
trade.sell_reason = sell_reason.value
Trade.session.flush()
self.notify_sell(trade)
profit_trade = trade.calc_profit(rate=limit)
current_rate = self.exchange.get_ticker(trade.pair)['bid']
profit_percent = trade.calc_profit_percent(limit)
pair_url = self.exchange.get_pair_detail_url(trade.pair)
def notify_sell(self, trade: Trade):
"""
Sends rpc notification when a sell occured.
"""
profit_rate = trade.close_rate if trade.close_rate else trade.close_rate_requested
profit_trade = trade.calc_profit(rate=profit_rate)
# Use cached ticker here - it was updated seconds ago.
current_rate = self.get_sell_rate(trade.pair, False)
profit_percent = trade.calc_profit_percent(profit_rate)
gain = "profit" if profit_percent > 0 else "loss"
msg = {
@ -847,14 +859,13 @@ class FreqtradeBot(object):
'exchange': trade.exchange.capitalize(),
'pair': trade.pair,
'gain': gain,
'market_url': pair_url,
'limit': limit,
'limit': trade.close_rate_requested,
'amount': trade.amount,
'open_rate': trade.open_rate,
'current_rate': current_rate,
'profit_amount': profit_trade,
'profit_percent': profit_percent,
'sell_reason': sell_reason.value
'sell_reason': trade.sell_reason
}
# For regular case, when the configuration exists
@ -868,4 +879,3 @@ class FreqtradeBot(object):
# Send the message
self.rpc.send_msg(msg)
Trade.session.flush()

49
freqtrade/main.py
View File

@ -10,10 +10,9 @@ from typing import List
from freqtrade import OperationalException
from freqtrade.arguments import Arguments
from freqtrade.configuration import Configuration, set_loggers
from freqtrade.freqtradebot import FreqtradeBot
from freqtrade.state import State
from freqtrade.rpc import RPCMessageType
from freqtrade.configuration import set_loggers
from freqtrade.worker import Worker
logger = logging.getLogger('freqtrade')
@ -27,7 +26,7 @@ def main(sysargv: List[str]) -> None:
sysargv,
'Free, open source crypto trading bot'
)
args = arguments.get_parsed_arg()
args: Namespace = arguments.get_parsed_arg()
# A subcommand has been issued.
# Means if Backtesting or Hyperopt have been called we exit the bot
@ -35,20 +34,12 @@ def main(sysargv: List[str]) -> None:
args.func(args)
return
freqtrade = None
worker = None
return_code = 1
try:
# Load and validate configuration
config = Configuration(args, None).get_config()
# Init the bot
freqtrade = FreqtradeBot(config)
state = None
while True:
state = freqtrade.worker(old_state=state)
if state == State.RELOAD_CONF:
freqtrade = reconfigure(freqtrade, args)
# Load and run worker
worker = Worker(args)
worker.run()
except KeyboardInterrupt:
logger.info('SIGINT received, aborting ...')
@ -59,31 +50,11 @@ def main(sysargv: List[str]) -> None:
except BaseException:
logger.exception('Fatal exception!')
finally:
if freqtrade:
freqtrade.rpc.send_msg({
'type': RPCMessageType.STATUS_NOTIFICATION,
'status': 'process died'
})
freqtrade.cleanup()
if worker:
worker.exit()
sys.exit(return_code)
def reconfigure(freqtrade: FreqtradeBot, args: Namespace) -> FreqtradeBot:
"""
Cleans up current instance, reloads the configuration and returns the new instance
"""
# Clean up current modules
freqtrade.cleanup()
# Create new instance
freqtrade = FreqtradeBot(Configuration(args, None).get_config())
freqtrade.rpc.send_msg({
'type': RPCMessageType.STATUS_NOTIFICATION,
'status': 'config reloaded'
})
return freqtrade
if __name__ == '__main__':
set_loggers()
main(sys.argv[1:])

42
freqtrade/misc.py
View File

@ -8,6 +8,7 @@ import re
from datetime import datetime
from typing import Dict
from ccxt import Exchange
import numpy as np
from pandas import DataFrame
import rapidjson
@ -113,3 +114,44 @@ def format_ms_time(date: int) -> str:
: epoch-string in ms
"""
return datetime.fromtimestamp(date/1000.0).strftime('%Y-%m-%dT%H:%M:%S')
def deep_merge_dicts(source, destination):
"""
>>> a = { 'first' : { 'rows' : { 'pass' : 'dog', 'number' : '1' } } }
>>> b = { 'first' : { 'rows' : { 'fail' : 'cat', 'number' : '5' } } }
>>> merge(b, a) == { 'first' : { 'rows' : { 'pass' : 'dog', 'fail' : 'cat', 'number' : '5' } } }
True
"""
for key, value in source.items():
if isinstance(value, dict):
# get node or create one
node = destination.setdefault(key, {})
deep_merge_dicts(value, node)
else:
destination[key] = value
return destination
def timeframe_to_seconds(ticker_interval: str) -> int:
"""
Translates the timeframe interval value written in the human readable
form ('1m', '5m', '1h', '1d', '1w', etc.) to the number
of seconds for one timeframe interval.
"""
return Exchange.parse_timeframe(ticker_interval)
def timeframe_to_minutes(ticker_interval: str) -> int:
"""
Same as above, but returns minutes.
"""
return Exchange.parse_timeframe(ticker_interval) // 60
def timeframe_to_msecs(ticker_interval: str) -> int:
"""
Same as above, but returns milliseconds.
"""
return Exchange.parse_timeframe(ticker_interval) * 1000

113
freqtrade/optimize/backtesting.py
View File

@ -17,11 +17,11 @@ from freqtrade import optimize
from freqtrade import DependencyException, constants
from freqtrade.arguments import Arguments
from freqtrade.configuration import Configuration
from freqtrade.exchange import Exchange
from freqtrade.data import history
from freqtrade.misc import file_dump_json
from freqtrade.data.dataprovider import DataProvider
from freqtrade.misc import file_dump_json, timeframe_to_minutes
from freqtrade.persistence import Trade
from freqtrade.resolvers import StrategyResolver
from freqtrade.resolvers import ExchangeResolver, StrategyResolver
from freqtrade.state import RunMode
from freqtrade.strategy.interface import SellType, IStrategy
@ -65,10 +65,19 @@ class Backtesting(object):
self.config['exchange']['uid'] = ''
self.config['dry_run'] = True
self.strategylist: List[IStrategy] = []
exchange_name = self.config.get('exchange', {}).get('name', 'bittrex').title()
self.exchange = ExchangeResolver(exchange_name, self.config).exchange
self.fee = self.exchange.get_fee()
if self.config.get('runmode') != RunMode.HYPEROPT:
self.dataprovider = DataProvider(self.config, self.exchange)
IStrategy.dp = self.dataprovider
if self.config.get('strategy_list', None):
# Force one interval
self.ticker_interval = str(self.config.get('ticker_interval'))
self.ticker_interval_mins = constants.TICKER_INTERVAL_MINUTES[self.ticker_interval]
self.ticker_interval_mins = timeframe_to_minutes(self.ticker_interval)
for strat in list(self.config['strategy_list']):
stratconf = deepcopy(self.config)
stratconf['strategy'] = strat
@ -80,19 +89,21 @@ class Backtesting(object):
# Load one strategy
self._set_strategy(self.strategylist[0])
self.exchange = Exchange(self.config)
self.fee = self.exchange.get_fee()
def _set_strategy(self, strategy):
"""
Load strategy into backtesting
"""
self.strategy = strategy
self.ticker_interval = self.config.get('ticker_interval')
self.ticker_interval_mins = constants.TICKER_INTERVAL_MINUTES[self.ticker_interval]
self.ticker_interval_mins = timeframe_to_minutes(self.ticker_interval)
self.tickerdata_to_dataframe = strategy.tickerdata_to_dataframe
self.advise_buy = strategy.advise_buy
self.advise_sell = strategy.advise_sell
# Set stoploss_on_exchange to false for backtesting,
# since a "perfect" stoploss-sell is assumed anyway
# And the regular "stoploss" function would not apply to that case
self.strategy.order_types['stoploss_on_exchange'] = False
def _generate_text_table(self, data: Dict[str, Dict], results: DataFrame,
skip_nan: bool = False) -> str:
@ -199,6 +210,32 @@ class Backtesting(object):
logger.info('Dumping backtest results to %s', recordfilename)
file_dump_json(recordfilename, records)
def _get_ticker_list(self, processed) -> Dict[str, DataFrame]:
"""
Helper function to convert a processed tickerlist into a list for performance reasons.
Used by backtest() - so keep this optimized for performance.
"""
headers = ['date', 'buy', 'open', 'close', 'sell', 'low', 'high']
ticker: Dict = {}
# Create ticker dict
for pair, pair_data in processed.items():
pair_data['buy'], pair_data['sell'] = 0, 0 # cleanup from previous run
ticker_data = self.advise_sell(
self.advise_buy(pair_data, {'pair': pair}), {'pair': pair})[headers].copy()
# to avoid using data from future, we buy/sell with signal from previous candle
ticker_data.loc[:, 'buy'] = ticker_data['buy'].shift(1)
ticker_data.loc[:, 'sell'] = ticker_data['sell'].shift(1)
ticker_data.drop(ticker_data.head(1).index, inplace=True)
# Convert from Pandas to list for performance reasons
# (Looping Pandas is slow.)
ticker[pair] = [x for x in ticker_data.itertuples()]
return ticker
def _get_sell_trade_entry(
self, pair: str, buy_row: DataFrame,
partial_ticker: List, trade_count_lock: Dict, args: Dict) -> Optional[BacktestResult]:
@ -293,7 +330,6 @@ class Backtesting(object):
position_stacking: do we allow position stacking? (default: False)
:return: DataFrame
"""
headers = ['date', 'buy', 'open', 'close', 'sell', 'low', 'high']
processed = args['processed']
max_open_trades = args.get('max_open_trades', 0)
position_stacking = args.get('position_stacking', False)
@ -301,54 +337,50 @@ class Backtesting(object):
end_date = args['end_date']
trades = []
trade_count_lock: Dict = {}
ticker: Dict = {}
pairs = []
# Create ticker dict
for pair, pair_data in processed.items():
pair_data['buy'], pair_data['sell'] = 0, 0 # cleanup from previous run
ticker_data = self.advise_sell(
self.advise_buy(pair_data, {'pair': pair}), {'pair': pair})[headers].copy()
# to avoid using data from future, we buy/sell with signal from previous candle
ticker_data.loc[:, 'buy'] = ticker_data['buy'].shift(1)
ticker_data.loc[:, 'sell'] = ticker_data['sell'].shift(1)
ticker_data.drop(ticker_data.head(1).index, inplace=True)
# Convert from Pandas to list for performance reasons
# (Looping Pandas is slow.)
ticker[pair] = [x for x in ticker_data.itertuples()]
pairs.append(pair)
# Dict of ticker-lists for performance (looping lists is a lot faster than dataframes)
ticker: Dict = self._get_ticker_list(processed)
lock_pair_until: Dict = {}
# Indexes per pair, so some pairs are allowed to have a missing start.
indexes: Dict = {}
tmp = start_date + timedelta(minutes=self.ticker_interval_mins)
index = 0
# Loop timerange and test per pair
# Loop timerange and get candle for each pair at that point in time
while tmp < end_date:
# print(f"time: {tmp}")
for i, pair in enumerate(ticker):
if pair not in indexes:
indexes[pair] = 0
try:
row = ticker[pair][index]
row = ticker[pair][indexes[pair]]
except IndexError:
# missing Data for one pair ...
# missing Data for one pair at the end.
# Warnings for this are shown by `validate_backtest_data`
continue
# Waits until the time-counter reaches the start of the data for this pair.
if row.date > tmp.datetime:
continue
indexes[pair] += 1
if row.buy == 0 or row.sell == 1:
continue # skip rows where no buy signal or that would immediately sell off
if not position_stacking:
if pair in lock_pair_until and row.date <= lock_pair_until[pair]:
continue
if (not position_stacking and pair in lock_pair_until
and row.date <= lock_pair_until[pair]):
# without positionstacking, we can only have one open trade per pair.
continue
if max_open_trades > 0:
# Check if max_open_trades has already been reached for the given date
if not trade_count_lock.get(row.date, 0) < max_open_trades:
continue
trade_count_lock[row.date] = trade_count_lock.get(row.date, 0) + 1
trade_entry = self._get_sell_trade_entry(pair, row, ticker[pair][index + 1:],
trade_entry = self._get_sell_trade_entry(pair, row, ticker[pair][indexes[pair]:],
trade_count_lock, args)
if trade_entry:
@ -356,11 +388,10 @@ class Backtesting(object):
trades.append(trade_entry)
else:
# Set lock_pair_until to end of testing period if trade could not be closed
# This happens only if the buy-signal was with the last candle
lock_pair_until[pair] = end_date
lock_pair_until[pair] = end_date.datetime
# Move time one configured time_interval ahead.
tmp += timedelta(minutes=self.ticker_interval_mins)
index += 1
return DataFrame.from_records(trades, columns=BacktestResult._fields)
def start(self) -> None:
@ -410,7 +441,7 @@ class Backtesting(object):
min_date, max_date = optimize.get_timeframe(data)
# Validate dataframe for missing values (mainly at start and end, as fillup is called)
optimize.validate_backtest_data(data, min_date, max_date,
constants.TICKER_INTERVAL_MINUTES[self.ticker_interval])
timeframe_to_minutes(self.ticker_interval))
logger.info(
'Measuring data from %s up to %s (%s days)..',
min_date.isoformat(),

39
freqtrade/pairlist/IPairList.py
View File

@ -60,32 +60,27 @@ class IPairList(ABC):
def _validate_whitelist(self, whitelist: List[str]) -> List[str]:
"""
Check available markets and remove pair from whitelist if necessary
:param whitelist: the sorted list (based on BaseVolume) of pairs the user might want to
trade
:return: the list of pairs the user wants to trade without the one unavailable or
:param whitelist: the sorted list of pairs the user might want to trade
:return: the list of pairs the user wants to trade without those unavailable or
black_listed
"""
sanitized_whitelist = whitelist
markets = self._freqtrade.exchange.get_markets()
markets = self._freqtrade.exchange.markets
# Filter to markets in stake currency
markets = [m for m in markets if m['quote'] == self._config['stake_currency']]
known_pairs = set()
for market in markets:
pair = market['symbol']
# pair is not int the generated dynamic market, or in the blacklist ... ignore it
if pair not in whitelist or pair in self.blacklist:
sanitized_whitelist = set()
for pair in whitelist:
# pair is not in the generated dynamic market, or in the blacklist ... ignore it
if (pair in self.blacklist or pair not in markets
or not pair.endswith(self._config['stake_currency'])):
logger.warning(f"Pair {pair} is not compatible with exchange "
f"{self._freqtrade.exchange.name} or contained in "
f"your blacklist. Removing it from whitelist..")
continue
# else the pair is valid
known_pairs.add(pair)
# Market is not active
# Check if market is active
market = markets[pair]
if not market['active']:
sanitized_whitelist.remove(pair)
logger.info(
'Ignoring %s from whitelist. Market is not active.',
pair
)
logger.info(f"Ignoring {pair} from whitelist. Market is not active.")
continue
sanitized_whitelist.add(pair)
# We need to remove pairs that are unknown
return [x for x in sanitized_whitelist if x in known_pairs]
return list(sanitized_whitelist)

34
freqtrade/pairlist/VolumePairList.py
View File

@ -1,5 +1,5 @@
"""
Static List provider
Volume PairList provider
Provides lists as configured in config.json
@ -26,6 +26,7 @@ class VolumePairList(IPairList):
'for "pairlist.config.number_assets"')
self._number_pairs = self._whitelistconf['number_assets']
self._sort_key = self._whitelistconf.get('sort_key', 'quoteVolume')
self._precision_filter = self._whitelistconf.get('precision_filter', False)
if not self._freqtrade.exchange.exchange_has('fetchTickers'):
raise OperationalException(
@ -52,9 +53,9 @@ class VolumePairList(IPairList):
-> Please overwrite in subclasses
"""
# Generate dynamic whitelist
pairs = self._gen_pair_whitelist(self._config['stake_currency'], self._sort_key)
# Validate whitelist to only have active market pairs
self._whitelist = self._validate_whitelist(pairs)[:self._number_pairs]
self._whitelist = self._gen_pair_whitelist(
self._config['stake_currency'], self._sort_key)[:self._number_pairs]
logger.info(f"Searching pairs: {self._whitelist}")
@cached(TTLCache(maxsize=1, ttl=1800))
def _gen_pair_whitelist(self, base_currency: str, key: str) -> List[str]:
@ -68,8 +69,27 @@ class VolumePairList(IPairList):
tickers = self._freqtrade.exchange.get_tickers()
# check length so that we make sure that '/' is actually in the string
tickers = [v for k, v in tickers.items()
if len(k.split('/')) == 2 and k.split('/')[1] == base_currency]
if (len(k.split('/')) == 2 and k.split('/')[1] == base_currency
and v[key] is not None)]
sorted_tickers = sorted(tickers, reverse=True, key=lambda t: t[key])
pairs = [s['symbol'] for s in sorted_tickers]
# Validate whitelist to only have active market pairs
valid_pairs = self._validate_whitelist([s['symbol'] for s in sorted_tickers])
valid_tickers = [t for t in sorted_tickers if t["symbol"] in valid_pairs]
if self._freqtrade.strategy.stoploss is not None and self._precision_filter:
stop_prices = [self._freqtrade.get_target_bid(t["symbol"], t)
* (1 - abs(self._freqtrade.strategy.stoploss)) for t in valid_tickers]
rates = [sp * 0.99 for sp in stop_prices]
logger.debug("\n".join([f"{sp} : {r}" for sp, r in zip(stop_prices[:10], rates[:10])]))
for i, t in enumerate(valid_tickers):
sp = self._freqtrade.exchange.symbol_price_prec(t["symbol"], stop_prices[i])
r = self._freqtrade.exchange.symbol_price_prec(t["symbol"], rates[i])
logger.debug(f"{t['symbol']} - {sp} : {r}")
if sp <= r:
logger.info(f"Removed {t['symbol']} from whitelist, "
f"because stop price {sp} would be <= stop limit {r}")
valid_tickers.remove(t)
pairs = [s['symbol'] for s in valid_tickers]
return pairs

58
freqtrade/persistence.py
View File

@ -5,7 +5,7 @@ This module contains the class to persist trades into SQLite
import logging
from datetime import datetime
from decimal import Decimal
from typing import Any, Dict, Optional
from typing import Any, Dict, List, Optional
import arrow
from sqlalchemy import (Boolean, Column, DateTime, Float, Integer, String,
@ -83,7 +83,7 @@ def check_migrate(engine) -> None:
logger.debug(f'trying {table_back_name}')
# Check for latest column
if not has_column(cols, 'stoploss_last_update'):
if not has_column(cols, 'stop_loss_pct'):
logger.info(f'Running database migration - backup available as {table_back_name}')
fee_open = get_column_def(cols, 'fee_open', 'fee')
@ -91,10 +91,13 @@ def check_migrate(engine) -> None:
open_rate_requested = get_column_def(cols, 'open_rate_requested', 'null')
close_rate_requested = get_column_def(cols, 'close_rate_requested', 'null')
stop_loss = get_column_def(cols, 'stop_loss', '0.0')
stop_loss_pct = get_column_def(cols, 'stop_loss_pct', 'null')
initial_stop_loss = get_column_def(cols, 'initial_stop_loss', '0.0')
initial_stop_loss_pct = get_column_def(cols, 'initial_stop_loss_pct', 'null')
stoploss_order_id = get_column_def(cols, 'stoploss_order_id', 'null')
stoploss_last_update = get_column_def(cols, 'stoploss_last_update', 'null')
max_rate = get_column_def(cols, 'max_rate', '0.0')
min_rate = get_column_def(cols, 'min_rate', 'null')
sell_reason = get_column_def(cols, 'sell_reason', 'null')
strategy = get_column_def(cols, 'strategy', 'null')
ticker_interval = get_column_def(cols, 'ticker_interval', 'null')
@ -112,8 +115,9 @@ def check_migrate(engine) -> None:
(id, exchange, pair, is_open, fee_open, fee_close, open_rate,
open_rate_requested, close_rate, close_rate_requested, close_profit,
stake_amount, amount, open_date, close_date, open_order_id,
stop_loss, initial_stop_loss, stoploss_order_id, stoploss_last_update,
max_rate, sell_reason, strategy,
stop_loss, stop_loss_pct, initial_stop_loss, initial_stop_loss_pct,
stoploss_order_id, stoploss_last_update,
max_rate, min_rate, sell_reason, strategy,
ticker_interval
)
select id, lower(exchange),
@ -128,9 +132,11 @@ def check_migrate(engine) -> None:
open_rate, {open_rate_requested} open_rate_requested, close_rate,
{close_rate_requested} close_rate_requested, close_profit,
stake_amount, amount, open_date, close_date, open_order_id,
{stop_loss} stop_loss, {initial_stop_loss} initial_stop_loss,
{stop_loss} stop_loss, {stop_loss_pct} stop_loss_pct,
{initial_stop_loss} initial_stop_loss,
{initial_stop_loss_pct} initial_stop_loss_pct,
{stoploss_order_id} stoploss_order_id, {stoploss_last_update} stoploss_last_update,
{max_rate} max_rate, {sell_reason} sell_reason,
{max_rate} max_rate, {min_rate} min_rate, {sell_reason} sell_reason,
{strategy} strategy, {ticker_interval} ticker_interval
from {table_back_name}
""")
@ -183,14 +189,20 @@ class Trade(_DECL_BASE):
open_order_id = Column(String)
# absolute value of the stop loss
stop_loss = Column(Float, nullable=True, default=0.0)
# percentage value of the stop loss
stop_loss_pct = Column(Float, nullable=True)
# absolute value of the initial stop loss
initial_stop_loss = Column(Float, nullable=True, default=0.0)
# percentage value of the initial stop loss
initial_stop_loss_pct = Column(Float, nullable=True)
# stoploss order id which is on exchange
stoploss_order_id = Column(String, nullable=True, index=True)
# last update time of the stoploss order on exchange
stoploss_last_update = Column(DateTime, nullable=True)
# absolute value of the highest reached price
max_rate = Column(Float, nullable=True, default=0.0)
# Lowest price reached
min_rate = Column(Float, nullable=True)
sell_reason = Column(String, nullable=True)
strategy = Column(String, nullable=True)
ticker_interval = Column(Integer, nullable=True)
@ -201,8 +213,22 @@ class Trade(_DECL_BASE):
return (f'Trade(id={self.id}, pair={self.pair}, amount={self.amount:.8f}, '
f'open_rate={self.open_rate:.8f}, open_since={open_since})')
def adjust_min_max_rates(self, current_price: float):
"""
Adjust the max_rate and min_rate.
"""
logger.debug("Adjusting min/max rates")
self.max_rate = max(current_price, self.max_rate or self.open_rate)
self.min_rate = min(current_price, self.min_rate or self.open_rate)
def adjust_stop_loss(self, current_price: float, stoploss: float, initial: bool = False):
"""this adjusts the stop loss to it's most recently observed setting"""
"""
This adjusts the stop loss to it's most recently observed setting
:param current_price: Current rate the asset is traded
:param stoploss: Stoploss as factor (sample -0.05 -> -5% below current price).
:param initial: Called to initiate stop_loss.
Skips everything if self.stop_loss is already set.
"""
if initial and not (self.stop_loss is None or self.stop_loss == 0):
# Don't modify if called with initial and nothing to do
@ -210,24 +236,20 @@ class Trade(_DECL_BASE):
new_loss = float(current_price * (1 - abs(stoploss)))
# keeping track of the highest observed rate for this trade
if self.max_rate is None:
self.max_rate = current_price
else:
if current_price > self.max_rate:
self.max_rate = current_price
# no stop loss assigned yet
if not self.stop_loss:
logger.debug("assigning new stop loss")
self.stop_loss = new_loss
self.stop_loss_pct = -1 * abs(stoploss)
self.initial_stop_loss = new_loss
self.initial_stop_loss_pct = -1 * abs(stoploss)
self.stoploss_last_update = datetime.utcnow()
# evaluate if the stop loss needs to be updated
else:
if new_loss > self.stop_loss: # stop losses only walk up, never down!
self.stop_loss = new_loss
self.stop_loss_pct = -1 * abs(stoploss)
self.stoploss_last_update = datetime.utcnow()
logger.debug("adjusted stop loss")
else:
@ -266,6 +288,7 @@ class Trade(_DECL_BASE):
logger.info('%s_SELL has been fulfilled for %s.', order_type.upper(), self)
elif order_type == 'stop_loss_limit':
self.stoploss_order_id = None
self.close_rate_requested = self.stop_loss
logger.info('STOP_LOSS_LIMIT is hit for %s.', self)
self.close(order['average'])
else:
@ -371,3 +394,10 @@ class Trade(_DECL_BASE):
.filter(Trade.is_open.is_(True))\
.scalar()
return total_open_stake_amount or 0
@staticmethod
def get_open_trades() -> List[Any]:
"""
Query trades from persistence layer
"""
return Trade.query.filter(Trade.is_open.is_(True)).all()

1
freqtrade/resolvers/__init__.py
View File

@ -1,4 +1,5 @@
from freqtrade.resolvers.iresolver import IResolver # noqa: F401
from freqtrade.resolvers.exchange_resolver import ExchangeResolver # noqa: F401
from freqtrade.resolvers.hyperopt_resolver import HyperOptResolver # noqa: F401
from freqtrade.resolvers.pairlist_resolver import PairListResolver # noqa: F401
from freqtrade.resolvers.strategy_resolver import StrategyResolver # noqa: F401

55
freqtrade/resolvers/exchange_resolver.py Normal file
View File

@ -0,0 +1,55 @@
"""
This module loads custom exchanges
"""
import logging
from freqtrade.exchange import Exchange
import freqtrade.exchange as exchanges
from freqtrade.resolvers import IResolver
logger = logging.getLogger(__name__)
class ExchangeResolver(IResolver):
"""
This class contains all the logic to load a custom exchange class
"""
__slots__ = ['exchange']
def __init__(self, exchange_name: str, config: dict) -> None:
"""
Load the custom class from config parameter
:param config: configuration dictionary
"""
try:
self.exchange = self._load_exchange(exchange_name, kwargs={'config': config})
except ImportError:
logger.info(
f"No {exchange_name} specific subclass found. Using the generic class instead.")
self.exchange = Exchange(config)
def _load_exchange(
self, exchange_name: str, kwargs: dict) -> Exchange:
"""
Loads the specified exchange.
Only checks for exchanges exported in freqtrade.exchanges
:param exchange_name: name of the module to import
:return: Exchange instance or None
"""
try:
ex_class = getattr(exchanges, exchange_name)
exchange = ex_class(kwargs['config'])
if exchange:
logger.info("Using resolved exchange %s", exchange_name)
return exchange
except AttributeError:
# Pass and raise ImportError instead
pass
raise ImportError(
"Impossible to load Exchange '{}'. This class does not exist"
" or contains Python code errors".format(exchange_name)
)

2
freqtrade/resolvers/hyperopt_resolver.py
View File

@ -63,7 +63,7 @@ class HyperOptResolver(IResolver):
hyperopt = self._search_object(directory=_path, object_type=IHyperOpt,
object_name=hyperopt_name)
if hyperopt:
logger.info('Using resolved hyperopt %s from \'%s\'', hyperopt_name, _path)
logger.info("Using resolved hyperopt %s from '%s'", hyperopt_name, _path)
return hyperopt
except FileNotFoundError:
logger.warning('Path "%s" does not exist', _path.relative_to(Path.cwd()))

8
freqtrade/resolvers/iresolver.py
View File

@ -31,7 +31,11 @@ class IResolver(object):
# Generate spec based on absolute path
spec = importlib.util.spec_from_file_location('unknown', str(module_path))
module = importlib.util.module_from_spec(spec)
spec.loader.exec_module(module) # type: ignore # importlib does not use typehints
try:
spec.loader.exec_module(module) # type: ignore # importlib does not use typehints
except (ModuleNotFoundError, SyntaxError) as err:
# Catch errors in case a specific module is not installed
logger.warning(f"Could not import {module_path} due to '{err}'")
valid_objects_gen = (
obj for name, obj in inspect.getmembers(module, inspect.isclass)
@ -47,7 +51,7 @@ class IResolver(object):
:param directory: relative or absolute directory path
:return: object instance
"""
logger.debug('Searching for %s %s in \'%s\'', object_type.__name__, object_name, directory)
logger.debug("Searching for %s %s in '%s'", object_type.__name__, object_name, directory)
for entry in directory.iterdir():
# Only consider python files
if not str(entry).endswith('.py'):

2
freqtrade/resolvers/pairlist_resolver.py
View File

@ -48,7 +48,7 @@ class PairListResolver(IResolver):
object_name=pairlist_name,
kwargs=kwargs)
if pairlist:
logger.info('Using resolved pairlist %s from \'%s\'', pairlist_name, _path)
logger.info("Using resolved pairlist %s from '%s'", pairlist_name, _path)
return pairlist
except FileNotFoundError:
logger.warning('Path "%s" does not exist', _path.relative_to(Path.cwd()))

40
freqtrade/resolvers/strategy_resolver.py
View File

@ -46,18 +46,21 @@ class StrategyResolver(IResolver):
# Set attributes
# Check if we need to override configuration
# (Attribute name, default, experimental)
attributes = [("minimal_roi", None, False),
("ticker_interval", None, False),
("stoploss", None, False),
("trailing_stop", None, False),
("trailing_stop_positive", None, False),
("trailing_stop_positive_offset", 0.0, False),
("process_only_new_candles", None, False),
("order_types", None, False),
("order_time_in_force", None, False),
("use_sell_signal", False, True),
("sell_profit_only", False, True),
("ignore_roi_if_buy_signal", False, True),
attributes = [("minimal_roi", {"0": 10.0}, False),
("ticker_interval", None, False),
("stoploss", None, False),
("trailing_stop", None, False),
("trailing_stop_positive", None, False),
("trailing_stop_positive_offset", 0.0, False),
("trailing_only_offset_is_reached", None, False),
("process_only_new_candles", None, False),
("order_types", None, False),
("order_time_in_force", None, False),
("stake_currency", None, False),
("stake_amount", None, False),
("use_sell_signal", False, True),
("sell_profit_only", False, True),
("ignore_roi_if_buy_signal", False, True),
]
for attribute, default, experimental in attributes:
if experimental:
@ -149,17 +152,20 @@ class StrategyResolver(IResolver):
strategy = self._search_object(directory=_path, object_type=IStrategy,
object_name=strategy_name, kwargs={'config': config})
if strategy:
logger.info('Using resolved strategy %s from \'%s\'', strategy_name, _path)
logger.info("Using resolved strategy %s from '%s'", strategy_name, _path)
strategy._populate_fun_len = len(
getfullargspec(strategy.populate_indicators).args)
strategy._buy_fun_len = len(getfullargspec(strategy.populate_buy_trend).args)
strategy._sell_fun_len = len(getfullargspec(strategy.populate_sell_trend).args)
return import_strategy(strategy, config=config)
try:
return import_strategy(strategy, config=config)
except TypeError as e:
logger.warning(
f"Impossible to load strategy '{strategy}' from {_path}. Error: {e}")
except FileNotFoundError:
logger.warning('Path "%s" does not exist', _path.relative_to(Path.cwd()))
raise ImportError(
"Impossible to load Strategy '{}'. This class does not exist"
" or contains Python code errors".format(strategy_name)
f"Impossible to load Strategy '{strategy_name}'. This class does not exist"
" or contains Python code errors"
)

71
freqtrade/rpc/rpc.py
View File

@ -83,7 +83,7 @@ class RPC(object):
a remotely exposed function
"""
# Fetch open trade
trades = Trade.query.filter(Trade.is_open.is_(True)).all()
trades = Trade.get_open_trades()
if not trades:
raise RPCException('no active trade')
else:
@ -94,7 +94,7 @@ class RPC(object):
order = self._freqtrade.exchange.get_order(trade.open_order_id, trade.pair)
# calculate profit and send message to user
try:
current_rate = self._freqtrade.exchange.get_ticker(trade.pair, False)['bid']
current_rate = self._freqtrade.get_sell_rate(trade.pair, False)
except DependencyException:
current_rate = NAN
current_profit = trade.calc_profit_percent(current_rate)
@ -103,22 +103,29 @@ class RPC(object):
results.append(dict(
trade_id=trade.id,
pair=trade.pair,
market_url=self._freqtrade.exchange.get_pair_detail_url(trade.pair),
base_currency=self._freqtrade.config['stake_currency'],
date=arrow.get(trade.open_date),
open_rate=trade.open_rate,
close_rate=trade.close_rate,
current_rate=current_rate,
amount=round(trade.amount, 8),
stake_amount=round(trade.stake_amount, 8),
close_profit=fmt_close_profit,
current_profit=round(current_profit * 100, 2),
stop_loss=trade.stop_loss,
stop_loss_pct=(trade.stop_loss_pct * 100)
if trade.stop_loss_pct else None,
initial_stop_loss=trade.initial_stop_loss,
initial_stop_loss_pct=(trade.initial_stop_loss_pct * 100)
if trade.initial_stop_loss_pct else None,
open_order='({} {} rem={:.8f})'.format(
order['type'], order['side'], order['remaining']
order['type'], order['side'], order['remaining']
) if order else None,
))
return results
def _rpc_status_table(self) -> DataFrame:
trades = Trade.query.filter(Trade.is_open.is_(True)).all()
trades = Trade.get_open_trades()
if not trades:
raise RPCException('no active order')
else:
@ -126,7 +133,7 @@ class RPC(object):
for trade in trades:
# calculate profit and send message to user
try:
current_rate = self._freqtrade.exchange.get_ticker(trade.pair, False)['bid']
current_rate = self._freqtrade.get_sell_rate(trade.pair, False)
except DependencyException:
current_rate = NAN
trade_perc = (100 * trade.calc_profit_percent(current_rate))
@ -214,7 +221,7 @@ class RPC(object):
else:
# Get current rate
try:
current_rate = self._freqtrade.exchange.get_ticker(trade.pair, False)['bid']
current_rate = self._freqtrade.get_sell_rate(trade.pair, False)
except DependencyException:
current_rate = NAN
profit_percent = trade.calc_profit_percent(rate=current_rate)
@ -281,9 +288,9 @@ class RPC(object):
else:
try:
if coin == 'USDT':
rate = 1.0 / self._freqtrade.exchange.get_ticker('BTC/USDT', False)['bid']
rate = 1.0 / self._freqtrade.get_sell_rate('BTC/USDT', False)
else:
rate = self._freqtrade.exchange.get_ticker(coin + '/BTC', False)['bid']
rate = self._freqtrade.get_sell_rate(coin + '/BTC', False)
except (TemporaryError, DependencyException):
continue
est_btc: float = rate * balance['total']
@ -329,6 +336,16 @@ class RPC(object):
self._freqtrade.state = State.RELOAD_CONF
return {'status': 'reloading config ...'}
def _rpc_stopbuy(self) -> Dict[str, str]:
"""
Handler to stop buying, but handle open trades gracefully.
"""
if self._freqtrade.state == State.RUNNING:
# Set 'max_open_trades' to 0
self._freqtrade.config['max_open_trades'] = 0
return {'status': 'No more buy will occur from now. Run /reload_conf to reset.'}
def _rpc_forcesell(self, trade_id) -> None:
"""
Handler for forcesell <id>.
@ -357,7 +374,7 @@ class RPC(object):
return
# Get current rate and execute sell
current_rate = self._freqtrade.exchange.get_ticker(trade.pair, False)['bid']
current_rate = self._freqtrade.get_sell_rate(trade.pair, False)
self._freqtrade.execute_sell(trade, current_rate, SellType.FORCE_SELL)
# ---- EOF def _exec_forcesell ----
@ -366,7 +383,7 @@ class RPC(object):
if trade_id == 'all':
# Execute sell for all open orders
for trade in Trade.query.filter(Trade.is_open.is_(True)).all():
for trade in Trade.get_open_trades():
_exec_forcesell(trade)
Trade.session.flush()
return
@ -437,17 +454,43 @@ class RPC(object):
for pair, rate, count in pair_rates
]
def _rpc_count(self) -> List[Trade]:
def _rpc_count(self) -> Dict[str, float]:
""" Returns the number of trades running """
if self._freqtrade.state != State.RUNNING:
raise RPCException('trader is not running')
return Trade.query.filter(Trade.is_open.is_(True)).all()
trades = Trade.get_open_trades()
return {
'current': len(trades),
'max': float(self._freqtrade.config['max_open_trades']),
'total_stake': sum((trade.open_rate * trade.amount) for trade in trades)
}
def _rpc_whitelist(self) -> Dict:
""" Returns the currently active whitelist"""
res = {'method': self._freqtrade.pairlists.name,
'length': len(self._freqtrade.pairlists.whitelist),
'length': len(self._freqtrade.active_pair_whitelist),
'whitelist': self._freqtrade.active_pair_whitelist
}
return res
def _rpc_blacklist(self, add: List[str]) -> Dict:
""" Returns the currently active blacklist"""
if add:
stake_currency = self._freqtrade.config.get('stake_currency')
for pair in add:
if (pair.endswith(stake_currency)
and pair not in self._freqtrade.pairlists.blacklist):
self._freqtrade.pairlists.blacklist.append(pair)
res = {'method': self._freqtrade.pairlists.name,
'length': len(self._freqtrade.pairlists.blacklist),
'blacklist': self._freqtrade.pairlists.blacklist,
}
return res
def _rpc_edge(self) -> List[Dict[str, Any]]:
""" Returns information related to Edge """
if not self._freqtrade.edge:
raise RPCException(f'Edge is not enabled.')
return self._freqtrade.edge.accepted_pairs()

5
freqtrade/rpc/rpc_manager.py
View File

@ -2,7 +2,7 @@
This module contains class to manage RPC communications (Telegram, Slack, ...)
"""
import logging
from typing import List, Dict, Any
from typing import Any, Dict, List
from freqtrade.rpc import RPC, RPCMessageType
@ -61,6 +61,8 @@ class RPCManager(object):
stake_currency = config['stake_currency']
stake_amount = config['stake_amount']
minimal_roi = config['minimal_roi']
stoploss = config['stoploss']
trailing_stop = config['trailing_stop']
ticker_interval = config['ticker_interval']
exchange_name = config['exchange']['name']
strategy_name = config.get('strategy', '')
@ -69,6 +71,7 @@ class RPCManager(object):
'status': f'*Exchange:* `{exchange_name}`\n'
f'*Stake per trade:* `{stake_amount} {stake_currency}`\n'
f'*Minimum ROI:* `{minimal_roi}`\n'
f'*{"Trailing " if trailing_stop else ""}Stoploss:* `{stoploss}`\n'
f'*Ticker Interval:* `{ticker_interval}`\n'
f'*Strategy:* `{strategy_name}`'
})

128
freqtrade/rpc/telegram.py
View File

@ -4,7 +4,7 @@
This module manage Telegram communication
"""
import logging
from typing import Any, Callable, Dict
from typing import Any, Callable, Dict, List
from tabulate import tabulate
from telegram import Bot, ParseMode, ReplyKeyboardMarkup, Update
@ -20,7 +20,10 @@ logger = logging.getLogger(__name__)
logger.debug('Included module rpc.telegram ...')
def authorized_only(command_handler: Callable[[Any, Bot, Update], None]) -> Callable[..., Any]:
MAX_TELEGRAM_MESSAGE_LENGTH = 4096
def authorized_only(command_handler: Callable[..., None]) -> Callable[..., Any]:
"""
Decorator to check if the message comes from the correct chat_id
:param command_handler: Telegram CommandHandler
@ -91,7 +94,10 @@ class Telegram(RPC):
CommandHandler('daily', self._daily),
CommandHandler('count', self._count),
CommandHandler('reload_conf', self._reload_conf),
CommandHandler('stopbuy', self._stopbuy),
CommandHandler('whitelist', self._whitelist),
CommandHandler('blacklist', self._blacklist, pass_args=True),
CommandHandler('edge', self._edge),
CommandHandler('help', self._help),
CommandHandler('version', self._version),
]
@ -125,7 +131,7 @@ class Telegram(RPC):
else:
msg['stake_amount_fiat'] = 0
message = ("*{exchange}:* Buying [{pair}]({market_url})\n"
message = ("*{exchange}:* Buying {pair}\n"
"with limit `{limit:.8f}\n"
"({stake_amount:.6f} {stake_currency}").format(**msg)
@ -137,7 +143,7 @@ class Telegram(RPC):
msg['amount'] = round(msg['amount'], 8)
msg['profit_percent'] = round(msg['profit_percent'] * 100, 2)
message = ("*{exchange}:* Selling [{pair}]({market_url})\n"
message = ("*{exchange}:* Selling {pair}\n"
"*Limit:* `{limit:.8f}`\n"
"*Amount:* `{amount:.8f}`\n"
"*Open Rate:* `{open_rate:.8f}`\n"
@ -191,21 +197,34 @@ class Telegram(RPC):
for result in results:
result['date'] = result['date'].humanize()
messages = [
"*Trade ID:* `{trade_id}`\n"
"*Current Pair:* [{pair}]({market_url})\n"
"*Open Since:* `{date}`\n"
"*Amount:* `{amount}`\n"
"*Open Rate:* `{open_rate:.8f}`\n"
"*Close Rate:* `{close_rate}`\n"
"*Current Rate:* `{current_rate:.8f}`\n"
"*Close Profit:* `{close_profit}`\n"
"*Current Profit:* `{current_profit:.2f}%`\n"
"*Open Order:* `{open_order}`".format(**result)
for result in results
]
messages = []
for r in results:
lines = [
"*Trade ID:* `{trade_id}` `(since {date})`",
"*Current Pair:* {pair}",
"*Amount:* `{amount} ({stake_amount} {base_currency})`",
"*Open Rate:* `{open_rate:.8f}`",
"*Close Rate:* `{close_rate}`" if r['close_rate'] else "",
"*Current Rate:* `{current_rate:.8f}`",
"*Close Profit:* `{close_profit}`" if r['close_profit'] else "",
"*Current Profit:* `{current_profit:.2f}%`",
# Adding initial stoploss only if it is different from stoploss
"*Initial Stoploss:* `{initial_stop_loss:.8f}` " +
("`({initial_stop_loss_pct:.2f}%)`" if r['initial_stop_loss_pct'] else "")
if r['stop_loss'] != r['initial_stop_loss'] else "",
# Adding stoploss and stoploss percentage only if it is not None
"*Stoploss:* `{stop_loss:.8f}` " +
("`({stop_loss_pct:.2f}%)`" if r['stop_loss_pct'] else ""),
"*Open Order:* `{open_order}`" if r['open_order'] else ""
]
messages.append("\n".join(filter(None, lines)).format(**r))
for msg in messages:
self._send_msg(msg, bot=bot)
except RPCException as e:
self._send_msg(str(e), bot=bot)
@ -250,7 +269,8 @@ class Telegram(RPC):
headers=[
'Day',
f'Profit {stake_cur}',
f'Profit {fiat_disp_cur}'
f'Profit {fiat_disp_cur}',
f'Trades'
],
tablefmt='simple')
message = f'<b>Daily Profit over the last {timescale} days</b>:\n<pre>{stats_tab}</pre>'
@ -311,13 +331,20 @@ class Telegram(RPC):
output = ''
for currency in result['currencies']:
if currency['est_btc'] > 0.0001:
output += "*{currency}:*\n" \
curr_output = "*{currency}:*\n" \
"\t`Available: {available: .8f}`\n" \
"\t`Balance: {balance: .8f}`\n" \
"\t`Pending: {pending: .8f}`\n" \
"\t`Est. BTC: {est_btc: .8f}`\n".format(**currency)
else:
output += "*{currency}:* not showing <1$ amount \n".format(**currency)
curr_output = "*{currency}:* not showing <1$ amount \n".format(**currency)
# Handle overflowing messsage length
if len(output + curr_output) >= MAX_TELEGRAM_MESSAGE_LENGTH:
self._send_msg(output, bot=bot)
output = curr_output
else:
output += curr_output
output += "\n*Estimated Value*:\n" \
"\t`BTC: {total: .8f}`\n" \
@ -362,6 +389,18 @@ class Telegram(RPC):
msg = self._rpc_reload_conf()
self._send_msg('Status: `{status}`'.format(**msg), bot=bot)
@authorized_only
def _stopbuy(self, bot: Bot, update: Update) -> None:
"""
Handler for /stop_buy.
Sets max_open_trades to 0 and gracefully sells all open trades
:param bot: telegram bot
:param update: message update
:return: None
"""
msg = self._rpc_stopbuy()
self._send_msg('Status: `{status}`'.format(**msg), bot=bot)
@authorized_only
def _forcesell(self, bot: Bot, update: Update) -> None:
"""
@ -428,12 +467,10 @@ class Telegram(RPC):
:return: None
"""
try:
trades = self._rpc_count()
message = tabulate({
'current': [len(trades)],
'max': [self._config['max_open_trades']],
'total stake': [sum((trade.open_rate * trade.amount) for trade in trades)]
}, headers=['current', 'max', 'total stake'], tablefmt='simple')
counts = self._rpc_count()
message = tabulate({k: [v] for k, v in counts.items()},
headers=['current', 'max', 'total stake'],
tablefmt='simple')
message = "<pre>{}</pre>".format(message)
logger.debug(message)
self._send_msg(message, parse_mode=ParseMode.HTML)
@ -457,6 +494,38 @@ class Telegram(RPC):
except RPCException as e:
self._send_msg(str(e), bot=bot)
@authorized_only
def _blacklist(self, bot: Bot, update: Update, args: List[str]) -> None:
"""
Handler for /blacklist
Shows the currently active blacklist
"""
try:
blacklist = self._rpc_blacklist(args)
message = f"Blacklist contains {blacklist['length']} pairs\n"
message += f"`{', '.join(blacklist['blacklist'])}`"
logger.debug(message)
self._send_msg(message)
except RPCException as e:
self._send_msg(str(e), bot=bot)
@authorized_only
def _edge(self, bot: Bot, update: Update) -> None:
"""
Handler for /edge
Shows information related to Edge
"""
try:
edge_pairs = self._rpc_edge()
edge_pairs_tab = tabulate(edge_pairs, headers='keys', tablefmt='simple')
message = f'<b>Edge only validated following pairs:</b>\n<pre>{edge_pairs_tab}</pre>'
self._send_msg(message, bot=bot, parse_mode=ParseMode.HTML)
except RPCException as e:
self._send_msg(str(e), bot=bot)
@authorized_only
def _help(self, bot: Bot, update: Update) -> None:
"""
@ -466,6 +535,8 @@ class Telegram(RPC):
:param update: message update
:return: None
"""
forcebuy_text = "*/forcebuy <pair> [<rate>]:* `Instantly buys the given pair. " \
"Optionally takes a rate at which to buy.` \n"
message = "*/start:* `Starts the trader`\n" \
"*/stop:* `Stops the trader`\n" \
"*/status [table]:* `Lists all open trades`\n" \
@ -473,13 +544,18 @@ class Telegram(RPC):
"*/profit:* `Lists cumulative profit from all finished trades`\n" \
"*/forcesell <trade_id>|all:* `Instantly sells the given trade or all trades, " \
"regardless of profit`\n" \
f"{forcebuy_text if self._config.get('forcebuy_enable', False) else '' }" \
"*/performance:* `Show performance of each finished trade grouped by pair`\n" \
"*/daily <n>:* `Shows profit or loss per day, over the last n days`\n" \
"*/count:* `Show number of trades running compared to allowed number of trades`" \
"\n" \
"*/balance:* `Show account balance per currency`\n" \
"*/stopbuy:* `Stops buying, but handles open trades gracefully` \n" \
"*/reload_conf:* `Reload configuration file` \n" \
"*/whitelist:* `Show current whitelist` \n" \
"*/blacklist [pair]:* `Show current blacklist, or adds one or more pairs " \
"to the blacklist.` \n" \
"*/edge:* `Shows validated pairs by Edge if it is enabeld` \n" \
"*/help:* `This help message`\n" \
"*/version:* `Show version`"

66
freqtrade/strategy/interface.py
View File

@ -12,8 +12,8 @@ import warnings
import arrow
from pandas import DataFrame
from freqtrade import constants
from freqtrade.data.dataprovider import DataProvider
from freqtrade.misc import timeframe_to_minutes
from freqtrade.persistence import Trade
from freqtrade.wallets import Wallets
@ -73,6 +73,7 @@ class IStrategy(ABC):
trailing_stop: bool = False
trailing_stop_positive: float
trailing_stop_positive_offset: float
trailing_only_offset_is_reached = False
# associated ticker interval
ticker_interval: str
@ -220,7 +221,7 @@ class IStrategy(ABC):
# Check if dataframe is out of date
signal_date = arrow.get(latest['date'])
interval_minutes = constants.TICKER_INTERVAL_MINUTES[interval]
interval_minutes = timeframe_to_minutes(interval)
offset = self.config.get('exchange', {}).get('outdated_offset', 5)
if signal_date < (arrow.utcnow().shift(minutes=-(interval_minutes * 2 + offset))):
logger.warning(
@ -246,6 +247,9 @@ class IStrategy(ABC):
"""
This function evaluate if on the condition required to trigger a sell has been reached
if the threshold is reached and updates the trade record.
:param low: Only used during backtesting to simulate stoploss
:param high: Only used during backtesting, to simulate ROI
:param force_stoploss: Externally provided stoploss
:return: True if trade should be sold, False otherwise
"""
@ -253,14 +257,16 @@ class IStrategy(ABC):
current_rate = low or rate
current_profit = trade.calc_profit_percent(current_rate)
trade.adjust_min_max_rates(high or current_rate)
stoplossflag = self.stop_loss_reached(current_rate=current_rate, trade=trade,
current_time=date, current_profit=current_profit,
force_stoploss=force_stoploss)
force_stoploss=force_stoploss, high=high)
if stoplossflag.sell_flag:
return stoplossflag
# Set current rate to low for backtesting sell
# Set current rate to high for backtesting sell
current_rate = high or rate
current_profit = trade.calc_profit_percent(current_rate)
experimental = self.config.get('experimental', {})
@ -284,8 +290,9 @@ class IStrategy(ABC):
return SellCheckTuple(sell_flag=False, sell_type=SellType.NONE)
def stop_loss_reached(self, current_rate: float, trade: Trade, current_time: datetime,
current_profit: float, force_stoploss: float) -> SellCheckTuple:
def stop_loss_reached(self, current_rate: float, trade: Trade,
current_time: datetime, current_profit: float,
force_stoploss: float, high: float = None) -> SellCheckTuple:
"""
Based on current profit of the trade and configured (trailing) stoploss,
decides to sell or not
@ -293,13 +300,33 @@ class IStrategy(ABC):
"""
trailing_stop = self.config.get('trailing_stop', False)
trade.adjust_stop_loss(trade.open_rate, force_stoploss if force_stoploss
else self.stoploss, initial=True)
stop_loss_value = force_stoploss if force_stoploss else self.stoploss
# Initiate stoploss with open_rate. Does nothing if stoploss is already set.
trade.adjust_stop_loss(trade.open_rate, stop_loss_value, initial=True)
if trailing_stop:
# trailing stoploss handling
sl_offset = self.config.get('trailing_stop_positive_offset') or 0.0
tsl_only_offset = self.config.get('trailing_only_offset_is_reached', False)
# Don't update stoploss if trailing_only_offset_is_reached is true.
if not (tsl_only_offset and current_profit < sl_offset):
# Specific handling for trailing_stop_positive
if 'trailing_stop_positive' in self.config and current_profit > sl_offset:
# Ignore mypy error check in configuration that this is a float
stop_loss_value = self.config.get('trailing_stop_positive') # type: ignore
logger.debug(f"using positive stop loss: {stop_loss_value} "
f"offset: {sl_offset:.4g} profit: {current_profit:.4f}%")
trade.adjust_stop_loss(high or current_rate, stop_loss_value)
# evaluate if the stoploss was hit if stoploss is not on exchange
if ((self.stoploss is not None) and
(trade.stop_loss >= current_rate) and
(not self.order_types.get('stoploss_on_exchange'))):
(trade.stop_loss >= current_rate) and
(not self.order_types.get('stoploss_on_exchange'))):
selltype = SellType.STOP_LOSS
# If Trailing stop (and max-rate did move above open rate)
if trailing_stop and trade.open_rate != trade.max_rate:
@ -314,25 +341,6 @@ class IStrategy(ABC):
logger.debug('Stop loss hit.')
return SellCheckTuple(sell_flag=True, sell_type=selltype)
# update the stop loss afterwards, after all by definition it's supposed to be hanging
if trailing_stop:
# check if we have a special stop loss for positive condition
# and if profit is positive
stop_loss_value = force_stoploss if force_stoploss else self.stoploss
sl_offset = self.config.get('trailing_stop_positive_offset') or 0.0
if 'trailing_stop_positive' in self.config and current_profit > sl_offset:
# Ignore mypy error check in configuration that this is a float
stop_loss_value = self.config.get('trailing_stop_positive') # type: ignore
logger.debug(f"using positive stop loss mode: {stop_loss_value} "
f"with offset {sl_offset:.4g} "
f"since we have profit {current_profit:.4f}%")
trade.adjust_stop_loss(current_rate, stop_loss_value)
return SellCheckTuple(sell_flag=False, sell_type=SellType.NONE)
def min_roi_reached(self, trade: Trade, current_profit: float, current_time: datetime) -> bool:

141
freqtrade/tests/conftest.py
View File

@ -4,7 +4,6 @@ import logging
import re
from datetime import datetime
from functools import reduce
from typing import Dict, Optional
from unittest.mock import MagicMock, PropertyMock
import arrow
@ -13,9 +12,11 @@ from telegram import Chat, Message, Update
from freqtrade import constants
from freqtrade.data.converter import parse_ticker_dataframe
from freqtrade.exchange import Exchange
from freqtrade.edge import Edge, PairInfo
from freqtrade.exchange import Exchange
from freqtrade.freqtradebot import FreqtradeBot
from freqtrade.resolvers import ExchangeResolver
from freqtrade.worker import Worker
logging.getLogger('').setLevel(logging.INFO)
@ -36,6 +37,7 @@ def log_has_re(line, logs):
def patch_exchange(mocker, api_mock=None, id='bittrex') -> None:
mocker.patch('freqtrade.exchange.Exchange._load_markets', MagicMock(return_value={}))
mocker.patch('freqtrade.exchange.Exchange.validate_pairs', MagicMock())
mocker.patch('freqtrade.exchange.Exchange.validate_timeframes', MagicMock())
mocker.patch('freqtrade.exchange.Exchange.validate_ordertypes', MagicMock())
mocker.patch('freqtrade.exchange.Exchange.id', PropertyMock(return_value=id))
@ -49,7 +51,11 @@ def patch_exchange(mocker, api_mock=None, id='bittrex') -> None:
def get_patched_exchange(mocker, config, api_mock=None, id='bittrex') -> Exchange:
patch_exchange(mocker, api_mock, id)
exchange = Exchange(config)
config["exchange"]["name"] = id
try:
exchange = ExchangeResolver(id.title(), config).exchange
except ImportError:
exchange = Exchange(config)
return exchange
@ -82,24 +88,32 @@ def get_patched_edge(mocker, config) -> Edge:
# Functions for recurrent object patching
def get_patched_freqtradebot(mocker, config) -> FreqtradeBot:
def patch_freqtradebot(mocker, config) -> None:
"""
This function patch _init_modules() to not call dependencies
:param mocker: a Mocker object to apply patches
:param config: Config to pass to the bot
:return: None
"""
patch_coinmarketcap(mocker, {'price_usd': 12345.0})
mocker.patch('freqtrade.freqtradebot.RPCManager', MagicMock())
mocker.patch('freqtrade.freqtradebot.persistence.init', MagicMock())
patch_exchange(mocker, None)
mocker.patch('freqtrade.freqtradebot.RPCManager._init', MagicMock())
mocker.patch('freqtrade.freqtradebot.RPCManager.send_msg', MagicMock())
def get_patched_freqtradebot(mocker, config) -> FreqtradeBot:
patch_freqtradebot(mocker, config)
return FreqtradeBot(config)
def patch_coinmarketcap(mocker, value: Optional[Dict[str, float]] = None) -> None:
def get_patched_worker(mocker, config) -> Worker:
patch_freqtradebot(mocker, config)
return Worker(args=None, config=config)
@pytest.fixture(autouse=True)
def patch_coinmarketcap(mocker) -> None:
"""
Mocker to coinmarketcap to speed up tests
:param mocker: mocker to patch coinmarketcap class
@ -165,6 +179,10 @@ def default_conf():
"LTC/BTC",
"XRP/BTC",
"NEO/BTC"
],
"pair_blacklist": [
"DOGE/BTC",
"HOT/BTC",
]
},
"telegram": {
@ -220,8 +238,8 @@ def ticker_sell_down():
@pytest.fixture
def markets():
return MagicMock(return_value=[
{
return {
'ETH/BTC': {
'id': 'ethbtc',
'symbol': 'ETH/BTC',
'base': 'ETH',
@ -246,7 +264,7 @@ def markets():
},
'info': '',
},
{
'TKN/BTC': {
'id': 'tknbtc',
'symbol': 'TKN/BTC',
'base': 'TKN',
@ -271,7 +289,7 @@ def markets():
},
'info': '',
},
{
'BLK/BTC': {
'id': 'blkbtc',
'symbol': 'BLK/BTC',
'base': 'BLK',
@ -296,7 +314,7 @@ def markets():
},
'info': '',
},
{
'LTC/BTC': {
'id': 'ltcbtc',
'symbol': 'LTC/BTC',
'base': 'LTC',
@ -321,7 +339,7 @@ def markets():
},
'info': '',
},
{
'XRP/BTC': {
'id': 'xrpbtc',
'symbol': 'XRP/BTC',
'base': 'XRP',
@ -346,7 +364,7 @@ def markets():
},
'info': '',
},
{
'NEO/BTC': {
'id': 'neobtc',
'symbol': 'NEO/BTC',
'base': 'NEO',
@ -370,8 +388,80 @@ def markets():
},
},
'info': '',
},
'BTT/BTC': {
'id': 'BTTBTC',
'symbol': 'BTT/BTC',
'base': 'BTT',
'quote': 'BTC',
'active': True,
'precision': {
'base': 8,
'quote': 8,
'amount': 0,
'price': 8
},
'limits': {
'amount': {
'min': 1.0,
'max': 90000000.0
},
'price': {
'min': None,
'max': None
},
'cost': {
'min': 0.001,
'max': None
}
},
'info': "",
},
'ETH/USDT': {
'id': 'USDT-ETH',
'symbol': 'ETH/USDT',
'base': 'ETH',
'quote': 'USDT',
'precision': {
'amount': 8,
'price': 8
},
'limits': {
'amount': {
'min': 0.02214286,
'max': None
},
'price': {
'min': 1e-08,
'max': None
}
},
'active': True,
'info': ""
},
'LTC/USDT': {
'id': 'USDT-LTC',
'symbol': 'LTC/USDT',
'base': 'LTC',
'quote': 'USDT',
'active': True,
'precision': {
'amount': 8,
'price': 8
},
'limits': {
'amount': {
'min': 0.06646786,
'max': None
},
'price': {
'min': 1e-08,
'max': None
}
},
'info': ""
}
])
}
@pytest.fixture
@ -590,6 +680,7 @@ def tickers():
'vwap': 0.01869197,
'open': 0.018585,
'close': 0.018573,
'last': 0.018799,
'baseVolume': 81058.66,
'quoteVolume': 2247.48374509,
},
@ -637,6 +728,28 @@ def tickers():
'quoteVolume': 1401.65697943,
'info': {}
},
'BTT/BTC': {
'symbol': 'BTT/BTC',
'timestamp': 1550936557206,
'datetime': '2019-02-23T15:42:37.206Z',
'high': 0.00000026,
'low': 0.00000024,
'bid': 0.00000024,
'bidVolume': 2446894197.0,
'ask': 0.00000025,
'askVolume': 2447913837.0,
'vwap': 0.00000025,
'open': 0.00000026,
'close': 0.00000024,
'last': 0.00000024,
'previousClose': 0.00000026,
'change': -0.00000002,
'percentage': -7.692,
'average': None,
'baseVolume': 4886464537.0,
'quoteVolume': 1215.14489611,
'info': {}
},
'ETH/USDT': {
'symbol': 'ETH/USDT',
'timestamp': 1522014804118,

21
freqtrade/tests/data/test_btanalysis.py Normal file
View File

@ -0,0 +1,21 @@
import pytest
from pandas import DataFrame
from freqtrade.data.btanalysis import BT_DATA_COLUMNS, load_backtest_data
from freqtrade.data.history import make_testdata_path
def test_load_backtest_data():
filename = make_testdata_path(None) / "backtest-result_test.json"
bt_data = load_backtest_data(filename)
assert isinstance(bt_data, DataFrame)
assert list(bt_data.columns) == BT_DATA_COLUMNS + ["profitabs"]
assert len(bt_data) == 179
# Test loading from string (must yield same result)
bt_data2 = load_backtest_data(str(filename))
assert bt_data.equals(bt_data2)
with pytest.raises(ValueError, match=r"File .* does not exist\."):
load_backtest_data(str("filename") + "nofile")

40
freqtrade/tests/data/test_dataprovider.py
View File

@ -9,31 +9,31 @@ from freqtrade.tests.conftest import get_patched_exchange
def test_ohlcv(mocker, default_conf, ticker_history):
default_conf["runmode"] = RunMode.DRY_RUN
tick_interval = default_conf["ticker_interval"]
ticker_interval = default_conf["ticker_interval"]
exchange = get_patched_exchange(mocker, default_conf)
exchange._klines[("XRP/BTC", tick_interval)] = ticker_history
exchange._klines[("UNITTEST/BTC", tick_interval)] = ticker_history
exchange._klines[("XRP/BTC", ticker_interval)] = ticker_history
exchange._klines[("UNITTEST/BTC", ticker_interval)] = ticker_history
dp = DataProvider(default_conf, exchange)
assert dp.runmode == RunMode.DRY_RUN
assert ticker_history.equals(dp.ohlcv("UNITTEST/BTC", tick_interval))
assert isinstance(dp.ohlcv("UNITTEST/BTC", tick_interval), DataFrame)
assert dp.ohlcv("UNITTEST/BTC", tick_interval) is not ticker_history
assert dp.ohlcv("UNITTEST/BTC", tick_interval, copy=False) is ticker_history
assert not dp.ohlcv("UNITTEST/BTC", tick_interval).empty
assert dp.ohlcv("NONESENSE/AAA", tick_interval).empty
assert ticker_history.equals(dp.ohlcv("UNITTEST/BTC", ticker_interval))
assert isinstance(dp.ohlcv("UNITTEST/BTC", ticker_interval), DataFrame)
assert dp.ohlcv("UNITTEST/BTC", ticker_interval) is not ticker_history
assert dp.ohlcv("UNITTEST/BTC", ticker_interval, copy=False) is ticker_history
assert not dp.ohlcv("UNITTEST/BTC", ticker_interval).empty
assert dp.ohlcv("NONESENSE/AAA", ticker_interval).empty
# Test with and without parameter
assert dp.ohlcv("UNITTEST/BTC", tick_interval).equals(dp.ohlcv("UNITTEST/BTC"))
assert dp.ohlcv("UNITTEST/BTC", ticker_interval).equals(dp.ohlcv("UNITTEST/BTC"))
default_conf["runmode"] = RunMode.LIVE
dp = DataProvider(default_conf, exchange)
assert dp.runmode == RunMode.LIVE
assert isinstance(dp.ohlcv("UNITTEST/BTC", tick_interval), DataFrame)
assert isinstance(dp.ohlcv("UNITTEST/BTC", ticker_interval), DataFrame)
default_conf["runmode"] = RunMode.BACKTEST
dp = DataProvider(default_conf, exchange)
assert dp.runmode == RunMode.BACKTEST
assert dp.ohlcv("UNITTEST/BTC", tick_interval).empty
assert dp.ohlcv("UNITTEST/BTC", ticker_interval).empty
def test_historic_ohlcv(mocker, default_conf, ticker_history):
@ -54,15 +54,15 @@ def test_historic_ohlcv(mocker, default_conf, ticker_history):
def test_available_pairs(mocker, default_conf, ticker_history):
exchange = get_patched_exchange(mocker, default_conf)
tick_interval = default_conf["ticker_interval"]
exchange._klines[("XRP/BTC", tick_interval)] = ticker_history
exchange._klines[("UNITTEST/BTC", tick_interval)] = ticker_history
ticker_interval = default_conf["ticker_interval"]
exchange._klines[("XRP/BTC", ticker_interval)] = ticker_history
exchange._klines[("UNITTEST/BTC", ticker_interval)] = ticker_history
dp = DataProvider(default_conf, exchange)
assert len(dp.available_pairs) == 2
assert dp.available_pairs == [
("XRP/BTC", tick_interval),
("UNITTEST/BTC", tick_interval),
("XRP/BTC", ticker_interval),
("UNITTEST/BTC", ticker_interval),
]
@ -71,10 +71,10 @@ def test_refresh(mocker, default_conf, ticker_history):
mocker.patch("freqtrade.exchange.Exchange.refresh_latest_ohlcv", refresh_mock)
exchange = get_patched_exchange(mocker, default_conf, id="binance")
tick_interval = default_conf["ticker_interval"]
pairs = [("XRP/BTC", tick_interval), ("UNITTEST/BTC", tick_interval)]
ticker_interval = default_conf["ticker_interval"]
pairs = [("XRP/BTC", ticker_interval), ("UNITTEST/BTC", ticker_interval)]
pairs_non_trad = [("ETH/USDT", tick_interval), ("BTC/TUSD", "1h")]
pairs_non_trad = [("ETH/USDT", ticker_interval), ("BTC/TUSD", "1h")]
dp = DataProvider(default_conf, exchange)
dp.refresh(pairs)

14
freqtrade/tests/data/test_history.py
View File

@ -242,10 +242,10 @@ def test_download_pair_history(ticker_history_list, mocker, default_conf) -> Non
assert download_pair_history(datadir=None, exchange=exchange,
pair='MEME/BTC',
tick_interval='1m')
ticker_interval='1m')
assert download_pair_history(datadir=None, exchange=exchange,
pair='CFI/BTC',
tick_interval='1m')
ticker_interval='1m')
assert not exchange._pairs_last_refresh_time
assert os.path.isfile(file1_1) is True
assert os.path.isfile(file2_1) is True
@ -259,10 +259,10 @@ def test_download_pair_history(ticker_history_list, mocker, default_conf) -> Non
assert download_pair_history(datadir=None, exchange=exchange,
pair='MEME/BTC',
tick_interval='5m')
ticker_interval='5m')
assert download_pair_history(datadir=None, exchange=exchange,
pair='CFI/BTC',
tick_interval='5m')
ticker_interval='5m')
assert not exchange._pairs_last_refresh_time
assert os.path.isfile(file1_5) is True
assert os.path.isfile(file2_5) is True
@ -280,8 +280,8 @@ def test_download_pair_history2(mocker, default_conf) -> None:
json_dump_mock = mocker.patch('freqtrade.misc.file_dump_json', return_value=None)
mocker.patch('freqtrade.exchange.Exchange.get_history', return_value=tick)
exchange = get_patched_exchange(mocker, default_conf)
download_pair_history(None, exchange, pair="UNITTEST/BTC", tick_interval='1m')
download_pair_history(None, exchange, pair="UNITTEST/BTC", tick_interval='3m')
download_pair_history(None, exchange, pair="UNITTEST/BTC", ticker_interval='1m')
download_pair_history(None, exchange, pair="UNITTEST/BTC", ticker_interval='3m')
assert json_dump_mock.call_count == 2
@ -298,7 +298,7 @@ def test_download_backtesting_data_exception(ticker_history, mocker, caplog, def
assert not download_pair_history(datadir=None, exchange=exchange,
pair='MEME/BTC',
tick_interval='1m')
ticker_interval='1m')
# clean files freshly downloaded
_clean_test_file(file1_1)
_clean_test_file(file1_5)

4
freqtrade/tests/edge/test_edge.py
View File

@ -122,8 +122,8 @@ def test_edge_results(edge_conf, mocker, caplog, data) -> None:
for c, trade in enumerate(data.trades):
res = results.iloc[c]
assert res.exit_type == trade.sell_reason
assert res.open_time == _get_frame_time_from_offset(trade.open_tick)
assert res.close_time == _get_frame_time_from_offset(trade.close_tick)
assert arrow.get(res.open_time) == _get_frame_time_from_offset(trade.open_tick)
assert arrow.get(res.close_time) == _get_frame_time_from_offset(trade.close_tick)
def test_adjust(mocker, edge_conf):

544
freqtrade/tests/exchange/test_exchange.py
View File

@ -4,16 +4,22 @@ import copy
import logging
from datetime import datetime
from random import randint
from unittest.mock import Mock, MagicMock, PropertyMock
from unittest.mock import MagicMock, Mock, PropertyMock
import arrow
import ccxt
import pytest
from pandas import DataFrame
from freqtrade import DependencyException, OperationalException, TemporaryError
from freqtrade.exchange import API_RETRY_COUNT, Exchange
from freqtrade.tests.conftest import get_patched_exchange, log_has
from freqtrade import (DependencyException, OperationalException,
TemporaryError, InvalidOrderException)
from freqtrade.exchange import Binance, Exchange, Kraken
from freqtrade.exchange.exchange import API_RETRY_COUNT
from freqtrade.resolvers.exchange_resolver import ExchangeResolver
from freqtrade.tests.conftest import get_patched_exchange, log_has, log_has_re
# Make sure to always keep one exchange here which is NOT subclassed!!
EXCHANGES = ['bittrex', 'binance', 'kraken', ]
# Source: https://stackoverflow.com/questions/29881236/how-to-mock-asyncio-coroutines
@ -24,16 +30,17 @@ def get_mock_coro(return_value):
return Mock(wraps=mock_coro)
def ccxt_exceptionhandlers(mocker, default_conf, api_mock, fun, mock_ccxt_fun, **kwargs):
def ccxt_exceptionhandlers(mocker, default_conf, api_mock, exchange_name,
fun, mock_ccxt_fun, **kwargs):
with pytest.raises(TemporaryError):
api_mock.__dict__[mock_ccxt_fun] = MagicMock(side_effect=ccxt.NetworkError)
exchange = get_patched_exchange(mocker, default_conf, api_mock)
exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
getattr(exchange, fun)(**kwargs)
assert api_mock.__dict__[mock_ccxt_fun].call_count == API_RETRY_COUNT + 1
with pytest.raises(OperationalException):
api_mock.__dict__[mock_ccxt_fun] = MagicMock(side_effect=ccxt.BaseError)
exchange = get_patched_exchange(mocker, default_conf, api_mock)
exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
getattr(exchange, fun)(**kwargs)
assert api_mock.__dict__[mock_ccxt_fun].call_count == 1
@ -106,6 +113,55 @@ def test_init_exception(default_conf, mocker):
Exchange(default_conf)
def test_exchange_resolver(default_conf, mocker, caplog):
mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=MagicMock()))
mocker.patch('freqtrade.exchange.Exchange._load_async_markets', MagicMock())
mocker.patch('freqtrade.exchange.Exchange.validate_pairs', MagicMock())
mocker.patch('freqtrade.exchange.Exchange.validate_timeframes', MagicMock())
exchange = ExchangeResolver('Bittrex', default_conf).exchange
assert isinstance(exchange, Exchange)
assert log_has_re(r"No .* specific subclass found. Using the generic class instead.",
caplog.record_tuples)
caplog.clear()
exchange = ExchangeResolver('Kraken', default_conf).exchange
assert isinstance(exchange, Exchange)
assert isinstance(exchange, Kraken)
assert not isinstance(exchange, Binance)
assert not log_has_re(r"No .* specific subclass found. Using the generic class instead.",
caplog.record_tuples)
exchange = ExchangeResolver('Binance', default_conf).exchange
assert isinstance(exchange, Exchange)
assert isinstance(exchange, Binance)
assert not isinstance(exchange, Kraken)
assert not log_has_re(r"No .* specific subclass found. Using the generic class instead.",
caplog.record_tuples)
def test_validate_order_time_in_force(default_conf, mocker, caplog):
caplog.set_level(logging.INFO)
# explicitly test bittrex, exchanges implementing other policies need seperate tests
ex = get_patched_exchange(mocker, default_conf, id="bittrex")
tif = {
"buy": "gtc",
"sell": "gtc",
}
ex.validate_order_time_in_force(tif)
tif2 = {
"buy": "fok",
"sell": "ioc",
}
with pytest.raises(OperationalException, match=r"Time in force.*not supported for .*"):
ex.validate_order_time_in_force(tif2)
# Patch to see if this will pass if the values are in the ft dict
ex._ft_has.update({"order_time_in_force": ["gtc", "fok", "ioc"]})
ex.validate_order_time_in_force(tif2)
def test_symbol_amount_prec(default_conf, mocker):
'''
Test rounds down to 4 Decimal places
@ -119,10 +175,7 @@ def test_symbol_amount_prec(default_conf, mocker):
markets = PropertyMock(return_value={'ETH/BTC': {'precision': {'amount': 4}}})
type(api_mock).markets = markets
mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=api_mock))
mocker.patch('freqtrade.exchange.Exchange.validate_timeframes', MagicMock())
mocker.patch('freqtrade.exchange.Exchange._load_async_markets', MagicMock())
exchange = Exchange(default_conf)
exchange = get_patched_exchange(mocker, default_conf, api_mock)
amount = 2.34559
pair = 'ETH/BTC'
@ -143,10 +196,7 @@ def test_symbol_price_prec(default_conf, mocker):
markets = PropertyMock(return_value={'ETH/BTC': {'precision': {'price': 4}}})
type(api_mock).markets = markets
mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=api_mock))
mocker.patch('freqtrade.exchange.Exchange.validate_timeframes', MagicMock())
mocker.patch('freqtrade.exchange.Exchange._load_async_markets', MagicMock())
exchange = Exchange(default_conf)
exchange = get_patched_exchange(mocker, default_conf, api_mock)
price = 2.34559
pair = 'ETH/BTC'
@ -165,11 +215,7 @@ def test_set_sandbox(default_conf, mocker):
url_mock = PropertyMock(return_value={'test': "api-public.sandbox.gdax.com",
'api': 'https://api.gdax.com'})
type(api_mock).urls = url_mock
mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=api_mock))
mocker.patch('freqtrade.exchange.Exchange.validate_timeframes', MagicMock())
mocker.patch('freqtrade.exchange.Exchange._load_async_markets', MagicMock())
exchange = Exchange(default_conf)
exchange = get_patched_exchange(mocker, default_conf, api_mock)
liveurl = exchange._api.urls['api']
default_conf['exchange']['sandbox'] = True
exchange.set_sandbox(exchange._api, default_conf['exchange'], 'Logname')
@ -187,12 +233,8 @@ def test_set_sandbox_exception(default_conf, mocker):
url_mock = PropertyMock(return_value={'api': 'https://api.gdax.com'})
type(api_mock).urls = url_mock
mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=api_mock))
mocker.patch('freqtrade.exchange.Exchange.validate_timeframes', MagicMock())
mocker.patch('freqtrade.exchange.Exchange._load_async_markets', MagicMock())
with pytest.raises(OperationalException, match=r'does not provide a sandbox api'):
exchange = Exchange(default_conf)
exchange = get_patched_exchange(mocker, default_conf, api_mock)
default_conf['exchange']['sandbox'] = True
exchange.set_sandbox(exchange._api, default_conf['exchange'], 'Logname')
@ -214,29 +256,54 @@ def test__load_async_markets(default_conf, mocker, caplog):
def test__load_markets(default_conf, mocker, caplog):
caplog.set_level(logging.INFO)
api_mock = MagicMock()
mocker.patch('freqtrade.exchange.Exchange.name', PropertyMock(return_value='Binance'))
api_mock.load_markets = MagicMock(return_value={})
mocker.patch('freqtrade.exchange.Exchange._init_ccxt', api_mock)
mocker.patch('freqtrade.exchange.Exchange.validate_timeframes', MagicMock())
mocker.patch('freqtrade.exchange.Exchange._load_async_markets', MagicMock())
expected_return = {'ETH/BTC': 'available'}
api_mock.load_markets = MagicMock(return_value=expected_return)
mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=api_mock))
default_conf['exchange']['pair_whitelist'] = ['ETH/BTC']
ex = Exchange(default_conf)
assert ex.markets == expected_return
api_mock.load_markets = MagicMock(side_effect=ccxt.BaseError())
mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=api_mock))
mocker.patch('freqtrade.exchange.Exchange.validate_pairs', MagicMock())
mocker.patch('freqtrade.exchange.Exchange.validate_timeframes', MagicMock())
mocker.patch('freqtrade.exchange.Exchange._load_async_markets', MagicMock())
Exchange(default_conf)
assert log_has('Unable to initialize markets. Reason: ', caplog.record_tuples)
def test_validate_pairs(default_conf, mocker):
expected_return = {'ETH/BTC': 'available'}
api_mock = MagicMock()
api_mock.load_markets = MagicMock(return_value={
api_mock.load_markets = MagicMock(return_value=expected_return)
type(api_mock).markets = expected_return
default_conf['exchange']['pair_whitelist'] = ['ETH/BTC']
ex = get_patched_exchange(mocker, default_conf, api_mock, id="binance")
assert ex.markets == expected_return
def test__reload_markets(default_conf, mocker, caplog):
caplog.set_level(logging.DEBUG)
initial_markets = {'ETH/BTC': {}}
def load_markets(*args, **kwargs):
exchange._api.markets = updated_markets
api_mock = MagicMock()
api_mock.load_markets = load_markets
type(api_mock).markets = initial_markets
default_conf['exchange']['markets_refresh_interval'] = 10
exchange = get_patched_exchange(mocker, default_conf, api_mock, id="binance")
exchange._last_markets_refresh = arrow.utcnow().timestamp
updated_markets = {'ETH/BTC': {}, "LTC/BTC": {}}
assert exchange.markets == initial_markets
# less than 10 minutes have passed, no reload
exchange._reload_markets()
assert exchange.markets == initial_markets
# more than 10 minutes have passed, reload is executed
exchange._last_markets_refresh = arrow.utcnow().timestamp - 15 * 60
exchange._reload_markets()
assert exchange.markets == updated_markets
assert log_has('Performing scheduled market reload..', caplog.record_tuples)
def test_validate_pairs(default_conf, mocker): # test exchange.validate_pairs directly
api_mock = MagicMock()
type(api_mock).markets = PropertyMock(return_value={
'ETH/BTC': '', 'LTC/BTC': '', 'XRP/BTC': '', 'NEO/BTC': ''
})
id_mock = PropertyMock(return_value='test_exchange')
@ -250,7 +317,9 @@ def test_validate_pairs(default_conf, mocker):
def test_validate_pairs_not_available(default_conf, mocker):
api_mock = MagicMock()
api_mock.load_markets = MagicMock(return_value={'XRP/BTC': 'inactive'})
type(api_mock).markets = PropertyMock(return_value={
'XRP/BTC': 'inactive'
})
mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=api_mock))
mocker.patch('freqtrade.exchange.Exchange.validate_timeframes', MagicMock())
mocker.patch('freqtrade.exchange.Exchange._load_async_markets', MagicMock())
@ -259,54 +328,25 @@ def test_validate_pairs_not_available(default_conf, mocker):
Exchange(default_conf)
def test_validate_pairs_not_compatible(default_conf, mocker):
api_mock = MagicMock()
api_mock.load_markets = MagicMock(return_value={
'ETH/BTC': '', 'TKN/BTC': '', 'TRST/BTC': '', 'SWT/BTC': '', 'BCC/BTC': ''
})
default_conf['stake_currency'] = 'ETH'
mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=api_mock))
mocker.patch('freqtrade.exchange.Exchange.validate_timeframes', MagicMock())
mocker.patch('freqtrade.exchange.Exchange._load_async_markets', MagicMock())
with pytest.raises(OperationalException, match=r'not compatible'):
Exchange(default_conf)
def test_validate_pairs_exception(default_conf, mocker, caplog):
caplog.set_level(logging.INFO)
api_mock = MagicMock()
mocker.patch('freqtrade.exchange.Exchange.name', PropertyMock(return_value='Binance'))
api_mock.load_markets = MagicMock(return_value={})
type(api_mock).markets = PropertyMock(return_value={})
mocker.patch('freqtrade.exchange.Exchange._init_ccxt', api_mock)
mocker.patch('freqtrade.exchange.Exchange.validate_timeframes', MagicMock())
mocker.patch('freqtrade.exchange.Exchange._load_async_markets', MagicMock())
with pytest.raises(OperationalException, match=r'Pair ETH/BTC is not available at Binance'):
with pytest.raises(OperationalException, match=r'Pair ETH/BTC is not available on Binance'):
Exchange(default_conf)
mocker.patch('freqtrade.exchange.Exchange._load_markets', MagicMock(return_value={}))
mocker.patch('freqtrade.exchange.Exchange.markets', PropertyMock(return_value={}))
Exchange(default_conf)
assert log_has('Unable to validate pairs (assuming they are correct).',
caplog.record_tuples)
def test_validate_pairs_stake_exception(default_conf, mocker, caplog):
caplog.set_level(logging.INFO)
default_conf['stake_currency'] = 'ETH'
api_mock = MagicMock()
api_mock.name = MagicMock(return_value='binance')
mocker.patch('freqtrade.exchange.Exchange._init_ccxt', api_mock)
mocker.patch('freqtrade.exchange.Exchange.validate_timeframes', MagicMock())
mocker.patch('freqtrade.exchange.Exchange._load_async_markets', MagicMock())
with pytest.raises(
OperationalException,
match=r'Pair ETH/BTC not compatible with stake_currency: ETH'
):
Exchange(default_conf)
def test_validate_timeframes(default_conf, mocker):
default_conf["ticker_interval"] = "5m"
api_mock = MagicMock()
@ -320,6 +360,7 @@ def test_validate_timeframes(default_conf, mocker):
mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=api_mock))
mocker.patch('freqtrade.exchange.Exchange._load_markets', MagicMock(return_value={}))
mocker.patch('freqtrade.exchange.Exchange.validate_pairs', MagicMock())
Exchange(default_conf)
@ -336,6 +377,7 @@ def test_validate_timeframes_failed(default_conf, mocker):
mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=api_mock))
mocker.patch('freqtrade.exchange.Exchange._load_markets', MagicMock(return_value={}))
mocker.patch('freqtrade.exchange.Exchange.validate_pairs', MagicMock())
with pytest.raises(OperationalException, match=r'Invalid ticker 3m, this Exchange supports.*'):
Exchange(default_conf)
@ -353,6 +395,7 @@ def test_validate_timeframes_not_in_config(default_conf, mocker):
mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=api_mock))
mocker.patch('freqtrade.exchange.Exchange._load_markets', MagicMock(return_value={}))
mocker.patch('freqtrade.exchange.Exchange.validate_pairs', MagicMock())
Exchange(default_conf)
@ -362,6 +405,7 @@ def test_validate_order_types(default_conf, mocker):
type(api_mock).has = PropertyMock(return_value={'createMarketOrder': True})
mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=api_mock))
mocker.patch('freqtrade.exchange.Exchange._load_markets', MagicMock(return_value={}))
mocker.patch('freqtrade.exchange.Exchange.validate_pairs', MagicMock())
mocker.patch('freqtrade.exchange.Exchange.validate_timeframes', MagicMock())
mocker.patch('freqtrade.exchange.Exchange.name', 'Bittrex')
default_conf['order_types'] = {
@ -403,6 +447,7 @@ def test_validate_order_types_not_in_config(default_conf, mocker):
api_mock = MagicMock()
mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=api_mock))
mocker.patch('freqtrade.exchange.Exchange._load_markets', MagicMock(return_value={}))
mocker.patch('freqtrade.exchange.Exchange.validate_pairs', MagicMock())
mocker.patch('freqtrade.exchange.Exchange.validate_timeframes', MagicMock())
conf = copy.deepcopy(default_conf)
@ -423,6 +468,61 @@ def test_exchange_has(default_conf, mocker):
assert not exchange.exchange_has("deadbeef")
@pytest.mark.parametrize("side", [
("buy"),
("sell")
])
@pytest.mark.parametrize("exchange_name", EXCHANGES)
def test_dry_run_order(default_conf, mocker, side, exchange_name):
default_conf['dry_run'] = True
exchange = get_patched_exchange(mocker, default_conf, id=exchange_name)
order = exchange.dry_run_order(
pair='ETH/BTC', ordertype='limit', side=side, amount=1, rate=200)
assert 'id' in order
assert f'dry_run_{side}_' in order["id"]
assert order["side"] == side
assert order["type"] == "limit"
assert order["pair"] == "ETH/BTC"
@pytest.mark.parametrize("side", [
("buy"),
("sell")
])
@pytest.mark.parametrize("ordertype,rate", [
("market", None),
("limit", 200),
("stop_loss_limit", 200)
])
@pytest.mark.parametrize("exchange_name", EXCHANGES)
def test_create_order(default_conf, mocker, side, ordertype, rate, exchange_name):
api_mock = MagicMock()
order_id = 'test_prod_{}_{}'.format(side, randint(0, 10 ** 6))
api_mock.create_order = MagicMock(return_value={
'id': order_id,
'info': {
'foo': 'bar'
}
})
default_conf['dry_run'] = False
mocker.patch('freqtrade.exchange.Exchange.symbol_amount_prec', lambda s, x, y: y)
mocker.patch('freqtrade.exchange.Exchange.symbol_price_prec', lambda s, x, y: y)
exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
order = exchange.create_order(
pair='ETH/BTC', ordertype=ordertype, side=side, amount=1, rate=200)
assert 'id' in order
assert 'info' in order
assert order['id'] == order_id
assert api_mock.create_order.call_args[0][0] == 'ETH/BTC'
assert api_mock.create_order.call_args[0][1] == ordertype
assert api_mock.create_order.call_args[0][2] == side
assert api_mock.create_order.call_args[0][3] == 1
assert api_mock.create_order.call_args[0][4] is rate
def test_buy_dry_run(default_conf, mocker):
default_conf['dry_run'] = True
exchange = get_patched_exchange(mocker, default_conf)
@ -433,7 +533,8 @@ def test_buy_dry_run(default_conf, mocker):
assert 'dry_run_buy_' in order['id']
def test_buy_prod(default_conf, mocker):
@pytest.mark.parametrize("exchange_name", EXCHANGES)
def test_buy_prod(default_conf, mocker, exchange_name):
api_mock = MagicMock()
order_id = 'test_prod_buy_{}'.format(randint(0, 10 ** 6))
order_type = 'market'
@ -447,7 +548,7 @@ def test_buy_prod(default_conf, mocker):
default_conf['dry_run'] = False
mocker.patch('freqtrade.exchange.Exchange.symbol_amount_prec', lambda s, x, y: y)
mocker.patch('freqtrade.exchange.Exchange.symbol_price_prec', lambda s, x, y: y)
exchange = get_patched_exchange(mocker, default_conf, api_mock)
exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
order = exchange.buy(pair='ETH/BTC', ordertype=order_type,
amount=1, rate=200, time_in_force=time_in_force)
@ -478,34 +579,33 @@ def test_buy_prod(default_conf, mocker):
# test exception handling
with pytest.raises(DependencyException):
api_mock.create_order = MagicMock(side_effect=ccxt.InsufficientFunds)
exchange = get_patched_exchange(mocker, default_conf, api_mock)
exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
exchange.buy(pair='ETH/BTC', ordertype=order_type,
amount=1, rate=200, time_in_force=time_in_force)
with pytest.raises(DependencyException):
api_mock.create_order = MagicMock(side_effect=ccxt.InvalidOrder)
exchange = get_patched_exchange(mocker, default_conf, api_mock)
exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
exchange.buy(pair='ETH/BTC', ordertype=order_type,
amount=1, rate=200, time_in_force=time_in_force)
with pytest.raises(TemporaryError):
api_mock.create_order = MagicMock(side_effect=ccxt.NetworkError)
exchange = get_patched_exchange(mocker, default_conf, api_mock)
exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
exchange.buy(pair='ETH/BTC', ordertype=order_type,
amount=1, rate=200, time_in_force=time_in_force)
with pytest.raises(OperationalException):
api_mock.create_order = MagicMock(side_effect=ccxt.BaseError)
exchange = get_patched_exchange(mocker, default_conf, api_mock)
exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
exchange.buy(pair='ETH/BTC', ordertype=order_type,
amount=1, rate=200, time_in_force=time_in_force)
def test_buy_considers_time_in_force(default_conf, mocker):
@pytest.mark.parametrize("exchange_name", EXCHANGES)
def test_buy_considers_time_in_force(default_conf, mocker, exchange_name):
api_mock = MagicMock()
order_id = 'test_prod_buy_{}'.format(randint(0, 10 ** 6))
order_type = 'market'
time_in_force = 'ioc'
api_mock.create_order = MagicMock(return_value={
'id': order_id,
'info': {
@ -515,7 +615,27 @@ def test_buy_considers_time_in_force(default_conf, mocker):
default_conf['dry_run'] = False
mocker.patch('freqtrade.exchange.Exchange.symbol_amount_prec', lambda s, x, y: y)
mocker.patch('freqtrade.exchange.Exchange.symbol_price_prec', lambda s, x, y: y)
exchange = get_patched_exchange(mocker, default_conf, api_mock)
exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
order_type = 'limit'
time_in_force = 'ioc'
order = exchange.buy(pair='ETH/BTC', ordertype=order_type,
amount=1, rate=200, time_in_force=time_in_force)
assert 'id' in order
assert 'info' in order
assert order['id'] == order_id
assert api_mock.create_order.call_args[0][0] == 'ETH/BTC'
assert api_mock.create_order.call_args[0][1] == order_type
assert api_mock.create_order.call_args[0][2] == 'buy'
assert api_mock.create_order.call_args[0][3] == 1
assert api_mock.create_order.call_args[0][4] == 200
assert "timeInForce" in api_mock.create_order.call_args[0][5]
assert api_mock.create_order.call_args[0][5]["timeInForce"] == time_in_force
order_type = 'market'
time_in_force = 'ioc'
order = exchange.buy(pair='ETH/BTC', ordertype=order_type,
amount=1, rate=200, time_in_force=time_in_force)
@ -528,7 +648,8 @@ def test_buy_considers_time_in_force(default_conf, mocker):
assert api_mock.create_order.call_args[0][2] == 'buy'
assert api_mock.create_order.call_args[0][3] == 1
assert api_mock.create_order.call_args[0][4] is None
assert api_mock.create_order.call_args[0][5] == {'timeInForce': 'ioc'}
# Market orders should not send timeInForce!!
assert "timeInForce" not in api_mock.create_order.call_args[0][5]
def test_sell_dry_run(default_conf, mocker):
@ -540,7 +661,8 @@ def test_sell_dry_run(default_conf, mocker):
assert 'dry_run_sell_' in order['id']
def test_sell_prod(default_conf, mocker):
@pytest.mark.parametrize("exchange_name", EXCHANGES)
def test_sell_prod(default_conf, mocker, exchange_name):
api_mock = MagicMock()
order_id = 'test_prod_sell_{}'.format(randint(0, 10 ** 6))
order_type = 'market'
@ -552,11 +674,12 @@ def test_sell_prod(default_conf, mocker):
})
default_conf['dry_run'] = False
exchange = get_patched_exchange(mocker, default_conf, api_mock)
mocker.patch('freqtrade.exchange.Exchange.symbol_amount_prec', lambda s, x, y: y)
mocker.patch('freqtrade.exchange.Exchange.symbol_price_prec', lambda s, x, y: y)
exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
order = exchange.sell(pair='ETH/BTC', ordertype=order_type, amount=1, rate=200)
assert 'id' in order
assert 'info' in order
assert order['id'] == order_id
@ -578,25 +701,74 @@ def test_sell_prod(default_conf, mocker):
# test exception handling
with pytest.raises(DependencyException):
api_mock.create_order = MagicMock(side_effect=ccxt.InsufficientFunds)
exchange = get_patched_exchange(mocker, default_conf, api_mock)
exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
exchange.sell(pair='ETH/BTC', ordertype=order_type, amount=1, rate=200)
with pytest.raises(DependencyException):
api_mock.create_order = MagicMock(side_effect=ccxt.InvalidOrder)
exchange = get_patched_exchange(mocker, default_conf, api_mock)
exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
exchange.sell(pair='ETH/BTC', ordertype=order_type, amount=1, rate=200)
with pytest.raises(TemporaryError):
api_mock.create_order = MagicMock(side_effect=ccxt.NetworkError)
exchange = get_patched_exchange(mocker, default_conf, api_mock)
exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
exchange.sell(pair='ETH/BTC', ordertype=order_type, amount=1, rate=200)
with pytest.raises(OperationalException):
api_mock.create_order = MagicMock(side_effect=ccxt.BaseError)
exchange = get_patched_exchange(mocker, default_conf, api_mock)
exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
exchange.sell(pair='ETH/BTC', ordertype=order_type, amount=1, rate=200)
@pytest.mark.parametrize("exchange_name", EXCHANGES)
def test_sell_considers_time_in_force(default_conf, mocker, exchange_name):
api_mock = MagicMock()
order_id = 'test_prod_sell_{}'.format(randint(0, 10 ** 6))
api_mock.create_order = MagicMock(return_value={
'id': order_id,
'info': {
'foo': 'bar'
}
})
default_conf['dry_run'] = False
mocker.patch('freqtrade.exchange.Exchange.symbol_amount_prec', lambda s, x, y: y)
mocker.patch('freqtrade.exchange.Exchange.symbol_price_prec', lambda s, x, y: y)
exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
order_type = 'limit'
time_in_force = 'ioc'
order = exchange.sell(pair='ETH/BTC', ordertype=order_type,
amount=1, rate=200, time_in_force=time_in_force)
assert 'id' in order
assert 'info' in order
assert order['id'] == order_id
assert api_mock.create_order.call_args[0][0] == 'ETH/BTC'
assert api_mock.create_order.call_args[0][1] == order_type
assert api_mock.create_order.call_args[0][2] == 'sell'
assert api_mock.create_order.call_args[0][3] == 1
assert api_mock.create_order.call_args[0][4] == 200
assert "timeInForce" in api_mock.create_order.call_args[0][5]
assert api_mock.create_order.call_args[0][5]["timeInForce"] == time_in_force
order_type = 'market'
time_in_force = 'ioc'
order = exchange.sell(pair='ETH/BTC', ordertype=order_type,
amount=1, rate=200, time_in_force=time_in_force)
assert 'id' in order
assert 'info' in order
assert order['id'] == order_id
assert api_mock.create_order.call_args[0][0] == 'ETH/BTC'
assert api_mock.create_order.call_args[0][1] == order_type
assert api_mock.create_order.call_args[0][2] == 'sell'
assert api_mock.create_order.call_args[0][3] == 1
assert api_mock.create_order.call_args[0][4] is None
# Market orders should not send timeInForce!!
assert "timeInForce" not in api_mock.create_order.call_args[0][5]
def test_get_balance_dry_run(default_conf, mocker):
default_conf['dry_run'] = True
@ -604,23 +776,24 @@ def test_get_balance_dry_run(default_conf, mocker):
assert exchange.get_balance(currency='BTC') == 999.9
def test_get_balance_prod(default_conf, mocker):
@pytest.mark.parametrize("exchange_name", EXCHANGES)
def test_get_balance_prod(default_conf, mocker, exchange_name):
api_mock = MagicMock()
api_mock.fetch_balance = MagicMock(return_value={'BTC': {'free': 123.4}})
default_conf['dry_run'] = False
exchange = get_patched_exchange(mocker, default_conf, api_mock)
exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
assert exchange.get_balance(currency='BTC') == 123.4
with pytest.raises(OperationalException):
api_mock.fetch_balance = MagicMock(side_effect=ccxt.BaseError)
exchange = get_patched_exchange(mocker, default_conf, api_mock)
exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
exchange.get_balance(currency='BTC')
with pytest.raises(TemporaryError, match=r'.*balance due to malformed exchange response:.*'):
exchange = get_patched_exchange(mocker, default_conf, api_mock)
exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
mocker.patch('freqtrade.exchange.Exchange.get_balances', MagicMock(return_value={}))
exchange.get_balance(currency='BTC')
@ -631,7 +804,8 @@ def test_get_balances_dry_run(default_conf, mocker):
assert exchange.get_balances() == {}
def test_get_balances_prod(default_conf, mocker):
@pytest.mark.parametrize("exchange_name", EXCHANGES)
def test_get_balances_prod(default_conf, mocker, exchange_name):
balance_item = {
'free': 10.0,
'total': 10.0,
@ -645,17 +819,18 @@ def test_get_balances_prod(default_conf, mocker):
'3ST': balance_item
})
default_conf['dry_run'] = False
exchange = get_patched_exchange(mocker, default_conf, api_mock)
exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
assert len(exchange.get_balances()) == 3
assert exchange.get_balances()['1ST']['free'] == 10.0
assert exchange.get_balances()['1ST']['total'] == 10.0
assert exchange.get_balances()['1ST']['used'] == 0.0
ccxt_exceptionhandlers(mocker, default_conf, api_mock,
ccxt_exceptionhandlers(mocker, default_conf, api_mock, exchange_name,
"get_balances", "fetch_balance")
def test_get_tickers(default_conf, mocker):
@pytest.mark.parametrize("exchange_name", EXCHANGES)
def test_get_tickers(default_conf, mocker, exchange_name):
api_mock = MagicMock()
tick = {'ETH/BTC': {
'symbol': 'ETH/BTC',
@ -670,7 +845,7 @@ def test_get_tickers(default_conf, mocker):
}
}
api_mock.fetch_tickers = MagicMock(return_value=tick)
exchange = get_patched_exchange(mocker, default_conf, api_mock)
exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
# retrieve original ticker
tickers = exchange.get_tickers()
@ -681,20 +856,21 @@ def test_get_tickers(default_conf, mocker):
assert tickers['BCH/BTC']['bid'] == 0.6
assert tickers['BCH/BTC']['ask'] == 0.5
ccxt_exceptionhandlers(mocker, default_conf, api_mock,
ccxt_exceptionhandlers(mocker, default_conf, api_mock, exchange_name,
"get_tickers", "fetch_tickers")
with pytest.raises(OperationalException):
api_mock.fetch_tickers = MagicMock(side_effect=ccxt.NotSupported)
exchange = get_patched_exchange(mocker, default_conf, api_mock)
exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
exchange.get_tickers()
api_mock.fetch_tickers = MagicMock(return_value={})
exchange = get_patched_exchange(mocker, default_conf, api_mock)
exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
exchange.get_tickers()
def test_get_ticker(default_conf, mocker):
@pytest.mark.parametrize("exchange_name", EXCHANGES)
def test_get_ticker(default_conf, mocker, exchange_name):
api_mock = MagicMock()
tick = {
'symbol': 'ETH/BTC',
@ -704,7 +880,7 @@ def test_get_ticker(default_conf, mocker):
}
api_mock.fetch_ticker = MagicMock(return_value=tick)
api_mock.markets = {'ETH/BTC': {}}
exchange = get_patched_exchange(mocker, default_conf, api_mock)
exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
# retrieve original ticker
ticker = exchange.get_ticker(pair='ETH/BTC')
@ -719,7 +895,7 @@ def test_get_ticker(default_conf, mocker):
'last': 42,
}
api_mock.fetch_ticker = MagicMock(return_value=tick)
exchange = get_patched_exchange(mocker, default_conf, api_mock)
exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
# if not caching the result we should get the same ticker
# if not fetching a new result we should get the cached ticker
@ -738,20 +914,21 @@ def test_get_ticker(default_conf, mocker):
exchange.get_ticker(pair='ETH/BTC', refresh=False)
assert api_mock.fetch_ticker.call_count == 0
ccxt_exceptionhandlers(mocker, default_conf, api_mock,
ccxt_exceptionhandlers(mocker, default_conf, api_mock, exchange_name,
"get_ticker", "fetch_ticker",
pair='ETH/BTC', refresh=True)
api_mock.fetch_ticker = MagicMock(return_value={})
exchange = get_patched_exchange(mocker, default_conf, api_mock)
exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
exchange.get_ticker(pair='ETH/BTC', refresh=True)
with pytest.raises(DependencyException, match=r'Pair XRP/ETH not available'):
exchange.get_ticker(pair='XRP/ETH', refresh=True)
def test_get_history(default_conf, mocker, caplog):
exchange = get_patched_exchange(mocker, default_conf)
@pytest.mark.parametrize("exchange_name", EXCHANGES)
def test_get_history(default_conf, mocker, caplog, exchange_name):
exchange = get_patched_exchange(mocker, default_conf, id=exchange_name)
tick = [
[
arrow.utcnow().timestamp * 1000, # unix timestamp ms
@ -764,8 +941,8 @@ def test_get_history(default_conf, mocker, caplog):
]
pair = 'ETH/BTC'
async def mock_candle_hist(pair, tick_interval, since_ms):
return pair, tick_interval, tick
async def mock_candle_hist(pair, ticker_interval, since_ms):
return pair, ticker_interval, tick
exchange._async_get_candle_history = Mock(wraps=mock_candle_hist)
# one_call calculation * 1.8 should do 2 calls
@ -830,7 +1007,8 @@ def test_refresh_latest_ohlcv(mocker, default_conf, caplog) -> None:
@pytest.mark.asyncio
async def test__async_get_candle_history(default_conf, mocker, caplog):
@pytest.mark.parametrize("exchange_name", EXCHANGES)
async def test__async_get_candle_history(default_conf, mocker, caplog, exchange_name):
tick = [
[
arrow.utcnow().timestamp * 1000, # unix timestamp ms
@ -843,11 +1021,10 @@ async def test__async_get_candle_history(default_conf, mocker, caplog):
]
caplog.set_level(logging.DEBUG)
exchange = get_patched_exchange(mocker, default_conf)
exchange = get_patched_exchange(mocker, default_conf, id=exchange_name)
# Monkey-patch async function
exchange._api_async.fetch_ohlcv = get_mock_coro(tick)
exchange = Exchange(default_conf)
pair = 'ETH/BTC'
res = await exchange._async_get_candle_history(pair, "5m")
assert type(res) is tuple
@ -861,12 +1038,12 @@ async def test__async_get_candle_history(default_conf, mocker, caplog):
# exchange = Exchange(default_conf)
await async_ccxt_exception(mocker, default_conf, MagicMock(),
"_async_get_candle_history", "fetch_ohlcv",
pair='ABCD/BTC', tick_interval=default_conf['ticker_interval'])
pair='ABCD/BTC', ticker_interval=default_conf['ticker_interval'])
api_mock = MagicMock()
with pytest.raises(OperationalException, match=r'Could not fetch ticker data*'):
api_mock.fetch_ohlcv = MagicMock(side_effect=ccxt.BaseError)
exchange = get_patched_exchange(mocker, default_conf, api_mock)
exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
await exchange._async_get_candle_history(pair, "5m",
(arrow.utcnow().timestamp - 2000) * 1000)
@ -919,12 +1096,13 @@ def test_refresh_latest_ohlcv_inv_result(default_conf, mocker, caplog):
assert log_has("Async code raised an exception: TypeError", caplog.record_tuples)
def test_get_order_book(default_conf, mocker, order_book_l2):
default_conf['exchange']['name'] = 'binance'
@pytest.mark.parametrize("exchange_name", EXCHANGES)
def test_get_order_book(default_conf, mocker, order_book_l2, exchange_name):
default_conf['exchange']['name'] = exchange_name
api_mock = MagicMock()
api_mock.fetch_l2_order_book = order_book_l2
exchange = get_patched_exchange(mocker, default_conf, api_mock)
exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
order_book = exchange.get_order_book(pair='ETH/BTC', limit=10)
assert 'bids' in order_book
assert 'asks' in order_book
@ -932,19 +1110,20 @@ def test_get_order_book(default_conf, mocker, order_book_l2):
assert len(order_book['asks']) == 10
def test_get_order_book_exception(default_conf, mocker):
@pytest.mark.parametrize("exchange_name", EXCHANGES)
def test_get_order_book_exception(default_conf, mocker, exchange_name):
api_mock = MagicMock()
with pytest.raises(OperationalException):
api_mock.fetch_l2_order_book = MagicMock(side_effect=ccxt.NotSupported)
exchange = get_patched_exchange(mocker, default_conf, api_mock)
exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
exchange.get_order_book(pair='ETH/BTC', limit=50)
with pytest.raises(TemporaryError):
api_mock.fetch_l2_order_book = MagicMock(side_effect=ccxt.NetworkError)
exchange = get_patched_exchange(mocker, default_conf, api_mock)
exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
exchange.get_order_book(pair='ETH/BTC', limit=50)
with pytest.raises(OperationalException):
api_mock.fetch_l2_order_book = MagicMock(side_effect=ccxt.BaseError)
exchange = get_patched_exchange(mocker, default_conf, api_mock)
exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
exchange.get_order_book(pair='ETH/BTC', limit=50)
@ -957,8 +1136,9 @@ def make_fetch_ohlcv_mock(data):
return fetch_ohlcv_mock
@pytest.mark.parametrize("exchange_name", EXCHANGES)
@pytest.mark.asyncio
async def test___async_get_candle_history_sort(default_conf, mocker):
async def test___async_get_candle_history_sort(default_conf, mocker, exchange_name):
def sort_data(data, key):
return sorted(data, key=key)
@ -976,9 +1156,9 @@ async def test___async_get_candle_history_sort(default_conf, mocker):
[1527830700000, 0.07652, 0.07652, 0.07651, 0.07652, 10.04822687],
[1527830400000, 0.07649, 0.07651, 0.07649, 0.07651, 2.5734867]
]
exchange = get_patched_exchange(mocker, default_conf)
exchange = get_patched_exchange(mocker, default_conf, id=exchange_name)
exchange._api_async.fetch_ohlcv = get_mock_coro(tick)
sort_mock = mocker.patch('freqtrade.exchange.sorted', MagicMock(side_effect=sort_data))
sort_mock = mocker.patch('freqtrade.exchange.exchange.sorted', MagicMock(side_effect=sort_data))
# Test the ticker history sort
res = await exchange._async_get_candle_history('ETH/BTC', default_conf['ticker_interval'])
assert res[0] == 'ETH/BTC'
@ -1038,36 +1218,39 @@ async def test___async_get_candle_history_sort(default_conf, mocker):
assert ticks[9][5] == 2.31452783
def test_cancel_order_dry_run(default_conf, mocker):
@pytest.mark.parametrize("exchange_name", EXCHANGES)
def test_cancel_order_dry_run(default_conf, mocker, exchange_name):
default_conf['dry_run'] = True
exchange = get_patched_exchange(mocker, default_conf)
exchange = get_patched_exchange(mocker, default_conf, id=exchange_name)
assert exchange.cancel_order(order_id='123', pair='TKN/BTC') is None
# Ensure that if not dry_run, we should call API
def test_cancel_order(default_conf, mocker):
@pytest.mark.parametrize("exchange_name", EXCHANGES)
def test_cancel_order(default_conf, mocker, exchange_name):
default_conf['dry_run'] = False
api_mock = MagicMock()
api_mock.cancel_order = MagicMock(return_value=123)
exchange = get_patched_exchange(mocker, default_conf, api_mock)
exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
assert exchange.cancel_order(order_id='_', pair='TKN/BTC') == 123
with pytest.raises(DependencyException):
with pytest.raises(InvalidOrderException):
api_mock.cancel_order = MagicMock(side_effect=ccxt.InvalidOrder)
exchange = get_patched_exchange(mocker, default_conf, api_mock)
exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
exchange.cancel_order(order_id='_', pair='TKN/BTC')
assert api_mock.cancel_order.call_count == API_RETRY_COUNT + 1
assert api_mock.cancel_order.call_count == 1
ccxt_exceptionhandlers(mocker, default_conf, api_mock,
ccxt_exceptionhandlers(mocker, default_conf, api_mock, exchange_name,
"cancel_order", "cancel_order",
order_id='_', pair='TKN/BTC')
def test_get_order(default_conf, mocker):
@pytest.mark.parametrize("exchange_name", EXCHANGES)
def test_get_order(default_conf, mocker, exchange_name):
default_conf['dry_run'] = True
order = MagicMock()
order.myid = 123
exchange = get_patched_exchange(mocker, default_conf)
exchange = get_patched_exchange(mocker, default_conf, id=exchange_name)
exchange._dry_run_open_orders['X'] = order
print(exchange.get_order('X', 'TKN/BTC'))
assert exchange.get_order('X', 'TKN/BTC').myid == 123
@ -1075,67 +1258,32 @@ def test_get_order(default_conf, mocker):
default_conf['dry_run'] = False
api_mock = MagicMock()
api_mock.fetch_order = MagicMock(return_value=456)
exchange = get_patched_exchange(mocker, default_conf, api_mock)
exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
assert exchange.get_order('X', 'TKN/BTC') == 456
with pytest.raises(DependencyException):
with pytest.raises(InvalidOrderException):
api_mock.fetch_order = MagicMock(side_effect=ccxt.InvalidOrder)
exchange = get_patched_exchange(mocker, default_conf, api_mock)
exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
exchange.get_order(order_id='_', pair='TKN/BTC')
assert api_mock.fetch_order.call_count == API_RETRY_COUNT + 1
assert api_mock.fetch_order.call_count == 1
ccxt_exceptionhandlers(mocker, default_conf, api_mock,
ccxt_exceptionhandlers(mocker, default_conf, api_mock, exchange_name,
'get_order', 'fetch_order',
order_id='_', pair='TKN/BTC')
def test_name(default_conf, mocker):
@pytest.mark.parametrize("exchange_name", EXCHANGES)
def test_name(default_conf, mocker, exchange_name):
mocker.patch('freqtrade.exchange.Exchange._load_markets', MagicMock(return_value={}))
default_conf['exchange']['name'] = 'binance'
default_conf['exchange']['name'] = exchange_name
exchange = Exchange(default_conf)
assert exchange.name == 'Binance'
assert exchange.name == exchange_name.title()
assert exchange.id == exchange_name
def test_id(default_conf, mocker):
mocker.patch('freqtrade.exchange.Exchange._load_markets', MagicMock(return_value={}))
default_conf['exchange']['name'] = 'binance'
exchange = Exchange(default_conf)
assert exchange.id == 'binance'
def test_get_pair_detail_url(default_conf, mocker, caplog):
mocker.patch('freqtrade.exchange.Exchange._load_markets', MagicMock(return_value={}))
default_conf['exchange']['name'] = 'binance'
exchange = Exchange(default_conf)
url = exchange.get_pair_detail_url('TKN/ETH')
assert 'TKN' in url
assert 'ETH' in url
url = exchange.get_pair_detail_url('LOOONG/BTC')
assert 'LOOONG' in url
assert 'BTC' in url
default_conf['exchange']['name'] = 'bittrex'
exchange = Exchange(default_conf)
url = exchange.get_pair_detail_url('TKN/ETH')
assert 'TKN' in url
assert 'ETH' in url
url = exchange.get_pair_detail_url('LOOONG/BTC')
assert 'LOOONG' in url
assert 'BTC' in url
default_conf['exchange']['name'] = 'poloniex'
exchange = Exchange(default_conf)
url = exchange.get_pair_detail_url('LOOONG/BTC')
assert '' == url
assert log_has('Could not get exchange url for Poloniex', caplog.record_tuples)
def test_get_trades_for_order(default_conf, mocker):
@pytest.mark.parametrize("exchange_name", EXCHANGES)
def test_get_trades_for_order(default_conf, mocker, exchange_name):
order_id = 'ABCD-ABCD'
since = datetime(2018, 5, 5)
default_conf["dry_run"] = False
@ -1162,13 +1310,13 @@ def test_get_trades_for_order(default_conf, mocker):
'amount': 0.2340606,
'fee': {'cost': 0.06179, 'currency': 'BTC'}
}])
exchange = get_patched_exchange(mocker, default_conf, api_mock)
exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
orders = exchange.get_trades_for_order(order_id, 'LTC/BTC', since)
assert len(orders) == 1
assert orders[0]['price'] == 165
ccxt_exceptionhandlers(mocker, default_conf, api_mock,
ccxt_exceptionhandlers(mocker, default_conf, api_mock, exchange_name,
'get_trades_for_order', 'fetch_my_trades',
order_id=order_id, pair='LTC/BTC', since=since)
@ -1176,22 +1324,8 @@ def test_get_trades_for_order(default_conf, mocker):
assert exchange.get_trades_for_order(order_id, 'LTC/BTC', since) == []
def test_get_markets(default_conf, mocker, markets):
api_mock = MagicMock()
api_mock.fetch_markets = markets
exchange = get_patched_exchange(mocker, default_conf, api_mock)
ret = exchange.get_markets()
assert isinstance(ret, list)
assert len(ret) == 6
assert ret[0]["id"] == "ethbtc"
assert ret[0]["symbol"] == "ETH/BTC"
ccxt_exceptionhandlers(mocker, default_conf, api_mock,
'get_markets', 'fetch_markets')
def test_get_fee(default_conf, mocker):
@pytest.mark.parametrize("exchange_name", EXCHANGES)
def test_get_fee(default_conf, mocker, exchange_name):
api_mock = MagicMock()
api_mock.calculate_fee = MagicMock(return_value={
'type': 'taker',
@ -1199,11 +1333,11 @@ def test_get_fee(default_conf, mocker):
'rate': 0.025,
'cost': 0.05
})
exchange = get_patched_exchange(mocker, default_conf, api_mock)
exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
assert exchange.get_fee() == 0.025
ccxt_exceptionhandlers(mocker, default_conf, api_mock,
ccxt_exceptionhandlers(mocker, default_conf, api_mock, exchange_name,
'get_fee', 'calculate_fee')

67
freqtrade/tests/exchange/test_kraken.py Normal file
View File

@ -0,0 +1,67 @@
# pragma pylint: disable=missing-docstring, C0103, bad-continuation, global-statement
# pragma pylint: disable=protected-access
from random import randint
from unittest.mock import MagicMock
from freqtrade.tests.conftest import get_patched_exchange
def test_buy_kraken_trading_agreement(default_conf, mocker):
api_mock = MagicMock()
order_id = 'test_prod_buy_{}'.format(randint(0, 10 ** 6))
order_type = 'limit'
time_in_force = 'ioc'
api_mock.create_order = MagicMock(return_value={
'id': order_id,
'info': {
'foo': 'bar'
}
})
default_conf['dry_run'] = False
mocker.patch('freqtrade.exchange.Exchange.symbol_amount_prec', lambda s, x, y: y)
mocker.patch('freqtrade.exchange.Exchange.symbol_price_prec', lambda s, x, y: y)
exchange = get_patched_exchange(mocker, default_conf, api_mock, id="kraken")
order = exchange.buy(pair='ETH/BTC', ordertype=order_type,
amount=1, rate=200, time_in_force=time_in_force)
assert 'id' in order
assert 'info' in order
assert order['id'] == order_id
assert api_mock.create_order.call_args[0][0] == 'ETH/BTC'
assert api_mock.create_order.call_args[0][1] == order_type
assert api_mock.create_order.call_args[0][2] == 'buy'
assert api_mock.create_order.call_args[0][3] == 1
assert api_mock.create_order.call_args[0][4] == 200
assert api_mock.create_order.call_args[0][5] == {'timeInForce': 'ioc',
'trading_agreement': 'agree'}
def test_sell_kraken_trading_agreement(default_conf, mocker):
api_mock = MagicMock()
order_id = 'test_prod_sell_{}'.format(randint(0, 10 ** 6))
order_type = 'market'
api_mock.create_order = MagicMock(return_value={
'id': order_id,
'info': {
'foo': 'bar'
}
})
default_conf['dry_run'] = False
mocker.patch('freqtrade.exchange.Exchange.symbol_amount_prec', lambda s, x, y: y)
mocker.patch('freqtrade.exchange.Exchange.symbol_price_prec', lambda s, x, y: y)
exchange = get_patched_exchange(mocker, default_conf, api_mock, id="kraken")
order = exchange.sell(pair='ETH/BTC', ordertype=order_type, amount=1, rate=200)
assert 'id' in order
assert 'info' in order
assert order['id'] == order_id
assert api_mock.create_order.call_args[0][0] == 'ETH/BTC'
assert api_mock.create_order.call_args[0][1] == order_type
assert api_mock.create_order.call_args[0][2] == 'sell'
assert api_mock.create_order.call_args[0][3] == 1
assert api_mock.create_order.call_args[0][4] is None
assert api_mock.create_order.call_args[0][5] == {'trading_agreement': 'agree'}

9
freqtrade/tests/optimize/__init__.py
View File

@ -3,11 +3,11 @@ from typing import NamedTuple, List
import arrow
from pandas import DataFrame
from freqtrade.misc import timeframe_to_minutes
from freqtrade.strategy.interface import SellType
from freqtrade.constants import TICKER_INTERVAL_MINUTES
ticker_start_time = arrow.get(2018, 10, 3)
tests_ticker_interval = "1h"
tests_ticker_interval = '1h'
class BTrade(NamedTuple):
@ -28,11 +28,12 @@ class BTContainer(NamedTuple):
roi: float
trades: List[BTrade]
profit_perc: float
trailing_stop: bool = False
def _get_frame_time_from_offset(offset):
return ticker_start_time.shift(minutes=(offset * TICKER_INTERVAL_MINUTES[tests_ticker_interval])
).datetime.replace(tzinfo=None)
return ticker_start_time.shift(minutes=(offset * timeframe_to_minutes(tests_ticker_interval))
).datetime
def _build_backtest_dataframe(ticker_with_signals):

65
freqtrade/tests/optimize/test_backtest_detail.py
View File

@ -14,10 +14,10 @@ from freqtrade.tests.optimize import (BTrade, BTContainer, _build_backtest_dataf
from freqtrade.tests.conftest import patch_exchange
# Test 0 Minus 8% Close
# Test 1 Minus 8% Close
# Test with Stop-loss at 1%
# TC1: Stop-Loss Triggered 1% loss
tc0 = BTContainer(data=[
tc1 = BTContainer(data=[
# D O H L C V B S
[0, 5000, 5025, 4975, 4987, 6172, 1, 0],
[1, 5000, 5025, 4975, 4987, 6172, 0, 0], # enter trade (signal on last candle)
@ -30,10 +30,10 @@ tc0 = BTContainer(data=[
)
# Test 1 Minus 4% Low, minus 1% close
# Test 2 Minus 4% Low, minus 1% close
# Test with Stop-Loss at 3%
# TC2: Stop-Loss Triggered 3% Loss
tc1 = BTContainer(data=[
tc2 = BTContainer(data=[
# D O H L C V B S
[0, 5000, 5025, 4975, 4987, 6172, 1, 0],
[1, 5000, 5025, 4975, 4987, 6172, 0, 0], # enter trade (signal on last candle)
@ -49,11 +49,10 @@ tc1 = BTContainer(data=[
# Test 3 Candle drops 4%, Recovers 1%.
# Entry Criteria Met
# Candle drops 20%
# Candle Data for test 3
# Test with Stop-Loss at 2%
# TC3: Trade-A: Stop-Loss Triggered 2% Loss
# Trade-B: Stop-Loss Triggered 2% Loss
tc2 = BTContainer(data=[
tc3 = BTContainer(data=[
# D O H L C V B S
[0, 5000, 5025, 4975, 4987, 6172, 1, 0],
[1, 5000, 5025, 4975, 4987, 6172, 0, 0], # enter trade (signal on last candle)
@ -71,7 +70,7 @@ tc2 = BTContainer(data=[
# Candle Data for test 3 – Candle drops 3% Closed 15% up
# Test with Stop-loss at 2% ROI 6%
# TC4: Stop-Loss Triggered 2% Loss
tc3 = BTContainer(data=[
tc4 = BTContainer(data=[
# D O H L C V B S
[0, 5000, 5025, 4975, 4987, 6172, 1, 0],
[1, 5000, 5025, 4975, 4987, 6172, 0, 0], # enter trade (signal on last candle)
@ -83,10 +82,10 @@ tc3 = BTContainer(data=[
trades=[BTrade(sell_reason=SellType.STOP_LOSS, open_tick=1, close_tick=2)]
)
# Test 4 / Drops 0.5% Closes +20%
# Test 5 / Drops 0.5% Closes +20%
# Set stop-loss at 1% ROI 3%
# TC5: ROI triggers 3% Gain
tc4 = BTContainer(data=[
tc5 = BTContainer(data=[
# D O H L C V B S
[0, 5000, 5025, 4980, 4987, 6172, 1, 0],
[1, 5000, 5025, 4980, 4987, 6172, 0, 0], # enter trade (signal on last candle)
@ -99,10 +98,9 @@ tc4 = BTContainer(data=[
)
# Test 6 / Drops 3% / Recovers 6% Positive / Closes 1% positve
# Candle Data for test 6
# Set stop-loss at 2% ROI at 5%
# TC6: Stop-Loss triggers 2% Loss
tc5 = BTContainer(data=[
tc6 = BTContainer(data=[
# D O H L C V B S
[0, 5000, 5025, 4975, 4987, 6172, 1, 0],
[1, 5000, 5025, 4975, 4987, 6172, 0, 0], # enter trade (signal on last candle)
@ -115,10 +113,9 @@ tc5 = BTContainer(data=[
)
# Test 7 - 6% Positive / 1% Negative / Close 1% Positve
# Candle Data for test 7
# Set stop-loss at 2% ROI at 3%
# TC7: ROI Triggers 3% Gain
tc6 = BTContainer(data=[
tc7 = BTContainer(data=[
# D O H L C V B S
[0, 5000, 5025, 4975, 4987, 6172, 1, 0],
[1, 5000, 5025, 4975, 4987, 6172, 0, 0],
@ -130,14 +127,47 @@ tc6 = BTContainer(data=[
trades=[BTrade(sell_reason=SellType.ROI, open_tick=1, close_tick=2)]
)
# Test 8 - trailing_stop should raise so candle 3 causes a stoploss.
# Set stop-loss at 10%, ROI at 10% (should not apply)
# TC8: Trailing stoploss - stoploss should be adjusted candle 2
tc8 = BTContainer(data=[
# D O H L C V B S
[0, 5000, 5050, 4950, 5000, 6172, 1, 0],
[1, 5000, 5050, 4950, 5000, 6172, 0, 0],
[2, 5000, 5250, 4750, 4850, 6172, 0, 0],
[3, 4850, 5050, 4650, 4750, 6172, 0, 0],
[4, 4750, 4950, 4350, 4750, 6172, 0, 0]],
stop_loss=-0.10, roi=0.10, profit_perc=-0.055, trailing_stop=True,
trades=[BTrade(sell_reason=SellType.TRAILING_STOP_LOSS, open_tick=1, close_tick=3)]
)
# Test 9 - trailing_stop should raise - high and low in same candle.
# Candle Data for test 9
# Set stop-loss at 10%, ROI at 10% (should not apply)
# TC9: Trailing stoploss - stoploss should be adjusted candle 2
tc9 = BTContainer(data=[
# D O H L C V B S
[0, 5000, 5050, 4950, 5000, 6172, 1, 0],
[1, 5000, 5050, 4950, 5000, 6172, 0, 0],
[2, 5000, 5050, 4950, 5000, 6172, 0, 0],
[3, 5000, 5200, 4550, 4850, 6172, 0, 0],
[4, 4750, 4950, 4350, 4750, 6172, 0, 0]],
stop_loss=-0.10, roi=0.10, profit_perc=-0.064, trailing_stop=True,
trades=[BTrade(sell_reason=SellType.TRAILING_STOP_LOSS, open_tick=1, close_tick=3)]
)
TESTS = [
tc0,
tc1,
tc2,
tc3,
tc4,
tc5,
tc6,
tc7,
tc8,
tc9,
]
@ -148,8 +178,9 @@ def test_backtest_results(default_conf, fee, mocker, caplog, data) -> None:
"""
default_conf["stoploss"] = data.stop_loss
default_conf["minimal_roi"] = {"0": data.roi}
default_conf['ticker_interval'] = tests_ticker_interval
mocker.patch('freqtrade.exchange.Exchange.get_fee', MagicMock(return_value=0.0))
default_conf["ticker_interval"] = tests_ticker_interval
default_conf["trailing_stop"] = data.trailing_stop
mocker.patch("freqtrade.exchange.Exchange.get_fee", MagicMock(return_value=0.0))
patch_exchange(mocker)
frame = _build_backtest_dataframe(data.data)
backtesting = Backtesting(default_conf)
@ -157,7 +188,7 @@ def test_backtest_results(default_conf, fee, mocker, caplog, data) -> None:
backtesting.advise_sell = lambda a, m: frame
caplog.set_level(logging.DEBUG)
pair = 'UNITTEST/BTC'
pair = "UNITTEST/BTC"
# Dummy data as we mock the analyze functions
data_processed = {pair: DataFrame()}
min_date, max_date = get_timeframe({pair: frame})

61
freqtrade/tests/optimize/test_backtesting.py
View File

@ -14,7 +14,9 @@ from arrow import Arrow
from freqtrade import DependencyException, constants
from freqtrade.arguments import Arguments, TimeRange
from freqtrade.data import history
from freqtrade.data.btanalysis import evaluate_result_multi
from freqtrade.data.converter import parse_ticker_dataframe
from freqtrade.data.dataprovider import DataProvider
from freqtrade.optimize import get_timeframe
from freqtrade.optimize.backtesting import (Backtesting, setup_configuration,
start)
@ -315,7 +317,28 @@ def test_start(mocker, fee, default_conf, caplog) -> None:
assert start_mock.call_count == 1
def test_backtesting_init(mocker, default_conf) -> None:
ORDER_TYPES = [
{
'buy': 'limit',
'sell': 'limit',
'stoploss': 'limit',
'stoploss_on_exchange': False
},
{
'buy': 'limit',
'sell': 'limit',
'stoploss': 'limit',
'stoploss_on_exchange': True
}]
@pytest.mark.parametrize("order_types", ORDER_TYPES)
def test_backtesting_init(mocker, default_conf, order_types) -> None:
"""
Check that stoploss_on_exchange is set to False while backtesting
since backtesting assumes a perfect stoploss anyway.
"""
default_conf["order_types"] = order_types
patch_exchange(mocker)
get_fee = mocker.patch('freqtrade.exchange.Exchange.get_fee', MagicMock(return_value=0.5))
backtesting = Backtesting(default_conf)
@ -324,8 +347,10 @@ def test_backtesting_init(mocker, default_conf) -> None:
assert callable(backtesting.strategy.tickerdata_to_dataframe)
assert callable(backtesting.advise_buy)
assert callable(backtesting.advise_sell)
assert isinstance(backtesting.strategy.dp, DataProvider)
get_fee.assert_called()
assert backtesting.fee == 0.5
assert not backtesting.strategy.order_types["stoploss_on_exchange"]
def test_tickerdata_to_dataframe_bt(default_conf, mocker) -> None:
@ -660,40 +685,32 @@ def test_backtest_alternate_buy_sell(default_conf, fee, mocker):
assert len(results.loc[results.open_at_end]) == 0
def test_backtest_multi_pair(default_conf, fee, mocker):
def evaluate_result_multi(results, freq, max_open_trades):
# Find overlapping trades by expanding each trade once per period
# and then counting overlaps
dates = [pd.Series(pd.date_range(row[1].open_time, row[1].close_time, freq=freq))
for row in results[['open_time', 'close_time']].iterrows()]
deltas = [len(x) for x in dates]
dates = pd.Series(pd.concat(dates).values, name='date')
df2 = pd.DataFrame(np.repeat(results.values, deltas, axis=0), columns=results.columns)
df2 = df2.astype(dtype={"open_time": "datetime64", "close_time": "datetime64"})
df2 = pd.concat([dates, df2], axis=1)
df2 = df2.set_index('date')
df_final = df2.resample(freq)[['pair']].count()
return df_final[df_final['pair'] > max_open_trades]
@pytest.mark.parametrize("pair", ['ADA/BTC', 'LTC/BTC'])
@pytest.mark.parametrize("tres", [0, 20, 30])
def test_backtest_multi_pair(default_conf, fee, mocker, tres, pair):
def _trend_alternate_hold(dataframe=None, metadata=None):
"""
Buy every 8th candle - sell every other 8th -2 (hold on to pairs a bit)
Buy every xth candle - sell every other xth -2 (hold on to pairs a bit)
"""
multi = 8
if metadata['pair'] in('ETH/BTC', 'LTC/BTC'):
multi = 20
else:
multi = 18
dataframe['buy'] = np.where(dataframe.index % multi == 0, 1, 0)
dataframe['sell'] = np.where((dataframe.index + multi - 2) % multi == 0, 1, 0)
if metadata['pair'] in('ETH/BTC', 'LTC/BTC'):
dataframe['buy'] = dataframe['buy'].shift(-4)
dataframe['sell'] = dataframe['sell'].shift(-4)
return dataframe
mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
patch_exchange(mocker)
pairs = ['ADA/BTC', 'DASH/BTC', 'ETH/BTC', 'LTC/BTC', 'NXT/BTC']
data = history.load_data(datadir=None, ticker_interval='5m', pairs=pairs)
# Only use 500 lines to increase performance
data = trim_dictlist(data, -500)
# Remove data for one pair from the beginning of the data
data[pair] = data[pair][tres:]
# We need to enable sell-signal - otherwise it sells on ROI!!
default_conf['experimental'] = {"use_sell_signal": True}
default_conf['ticker_interval'] = '5m'

7
freqtrade/tests/optimize/test_optimize.py
View File

@ -1,7 +1,8 @@
# pragma pylint: disable=missing-docstring, protected-access, C0103
from freqtrade import optimize, constants
from freqtrade import optimize
from freqtrade.arguments import TimeRange
from freqtrade.data import history
from freqtrade.misc import timeframe_to_minutes
from freqtrade.strategy.default_strategy import DefaultStrategy
from freqtrade.tests.conftest import log_has, patch_exchange
@ -37,7 +38,7 @@ def test_validate_backtest_data_warn(default_conf, mocker, caplog) -> None:
min_date, max_date = optimize.get_timeframe(data)
caplog.clear()
assert optimize.validate_backtest_data(data, min_date, max_date,
constants.TICKER_INTERVAL_MINUTES["1m"])
timeframe_to_minutes('1m'))
assert len(caplog.record_tuples) == 1
assert log_has(
"UNITTEST/BTC has missing frames: expected 14396, got 13680, that's 716 missing values",
@ -61,5 +62,5 @@ def test_validate_backtest_data(default_conf, mocker, caplog) -> None:
min_date, max_date = optimize.get_timeframe(data)
caplog.clear()
assert not optimize.validate_backtest_data(data, min_date, max_date,
constants.TICKER_INTERVAL_MINUTES["5m"])
timeframe_to_minutes('5m'))
assert len(caplog.record_tuples) == 0

80
freqtrade/tests/pairlist/test_pairlist.py
View File

@ -1,6 +1,6 @@
# pragma pylint: disable=missing-docstring,C0103,protected-access
from unittest.mock import MagicMock
from unittest.mock import MagicMock, PropertyMock
from freqtrade import OperationalException
from freqtrade.constants import AVAILABLE_PAIRLISTS
@ -33,7 +33,7 @@ def whitelist_conf(default_conf):
def test_load_pairlist_noexist(mocker, markets, default_conf):
freqtradebot = get_patched_freqtradebot(mocker, default_conf)
mocker.patch('freqtrade.exchange.Exchange.get_markets', markets)
mocker.patch('freqtrade.exchange.Exchange.markets', PropertyMock(return_value=markets))
with pytest.raises(ImportError,
match=r"Impossible to load Pairlist 'NonexistingPairList'."
r" This class does not exist or contains Python code errors"):
@ -44,7 +44,7 @@ def test_refresh_market_pair_not_in_whitelist(mocker, markets, whitelist_conf):
freqtradebot = get_patched_freqtradebot(mocker, whitelist_conf)
mocker.patch('freqtrade.exchange.Exchange.get_markets', markets)
mocker.patch('freqtrade.exchange.Exchange.markets', PropertyMock(return_value=markets))
freqtradebot.pairlists.refresh_pairlist()
# List ordered by BaseVolume
whitelist = ['ETH/BTC', 'TKN/BTC']
@ -58,7 +58,7 @@ def test_refresh_market_pair_not_in_whitelist(mocker, markets, whitelist_conf):
def test_refresh_pairlists(mocker, markets, whitelist_conf):
freqtradebot = get_patched_freqtradebot(mocker, whitelist_conf)
mocker.patch('freqtrade.exchange.Exchange.get_markets', markets)
mocker.patch('freqtrade.exchange.Exchange.markets', PropertyMock(return_value=markets))
freqtradebot.pairlists.refresh_pairlist()
# List ordered by BaseVolume
whitelist = ['ETH/BTC', 'TKN/BTC']
@ -73,14 +73,14 @@ def test_refresh_pairlist_dynamic(mocker, markets, tickers, whitelist_conf):
}
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
get_markets=markets,
markets=PropertyMock(return_value=markets),
get_tickers=tickers,
exchange_has=MagicMock(return_value=True)
)
freqtradebot = get_patched_freqtradebot(mocker, whitelist_conf)
# argument: use the whitelist dynamically by exchange-volume
whitelist = ['ETH/BTC', 'TKN/BTC']
whitelist = ['ETH/BTC', 'TKN/BTC', 'BTT/BTC']
freqtradebot.pairlists.refresh_pairlist()
assert whitelist == freqtradebot.pairlists.whitelist
@ -96,7 +96,7 @@ def test_refresh_pairlist_dynamic(mocker, markets, tickers, whitelist_conf):
def test_VolumePairList_refresh_empty(mocker, markets_empty, whitelist_conf):
freqtradebot = get_patched_freqtradebot(mocker, whitelist_conf)
mocker.patch('freqtrade.exchange.Exchange.get_markets', markets_empty)
mocker.patch('freqtrade.exchange.Exchange.markets', PropertyMock(return_value=markets_empty))
# argument: use the whitelist dynamically by exchange-volume
whitelist = []
@ -107,28 +107,27 @@ def test_VolumePairList_refresh_empty(mocker, markets_empty, whitelist_conf):
assert set(whitelist) == set(pairslist)
def test_VolumePairList_whitelist_gen(mocker, whitelist_conf, markets, tickers) -> None:
@pytest.mark.parametrize("precision_filter,base_currency,key,whitelist_result", [
(False, "BTC", "quoteVolume", ['ETH/BTC', 'TKN/BTC', 'BTT/BTC']),
(False, "BTC", "bidVolume", ['BTT/BTC', 'TKN/BTC', 'ETH/BTC']),
(False, "USDT", "quoteVolume", ['ETH/USDT', 'LTC/USDT']),
(False, "ETH", "quoteVolume", []), # this replaces tests that were removed from test_exchange
(True, "BTC", "quoteVolume", ["ETH/BTC", "TKN/BTC"]),
(True, "BTC", "bidVolume", ["TKN/BTC", "ETH/BTC"])
])
def test_VolumePairList_whitelist_gen(mocker, whitelist_conf, markets, tickers, base_currency, key,
whitelist_result, precision_filter) -> None:
whitelist_conf['pairlist']['method'] = 'VolumePairList'
mocker.patch('freqtrade.exchange.Exchange.exchange_has', MagicMock(return_value=True))
freqtrade = get_patched_freqtradebot(mocker, whitelist_conf)
mocker.patch('freqtrade.exchange.Exchange.get_markets', markets)
mocker.patch('freqtrade.exchange.Exchange.markets', PropertyMock(return_value=markets))
mocker.patch('freqtrade.exchange.Exchange.get_tickers', tickers)
mocker.patch('freqtrade.exchange.Exchange.symbol_price_prec', lambda s, p, r: round(r, 8))
# Test to retrieved BTC sorted on quoteVolume (default)
whitelist = freqtrade.pairlists._gen_pair_whitelist(base_currency='BTC', key='quoteVolume')
assert whitelist == ['ETH/BTC', 'TKN/BTC', 'BLK/BTC', 'LTC/BTC']
# Test to retrieve BTC sorted on bidVolume
whitelist = freqtrade.pairlists._gen_pair_whitelist(base_currency='BTC', key='bidVolume')
assert whitelist == ['LTC/BTC', 'TKN/BTC', 'ETH/BTC', 'BLK/BTC']
# Test with USDT sorted on quoteVolume (default)
whitelist = freqtrade.pairlists._gen_pair_whitelist(base_currency='USDT', key='quoteVolume')
assert whitelist == ['TKN/USDT', 'ETH/USDT', 'LTC/USDT', 'BLK/USDT']
# Test with ETH (our fixture does not have ETH, so result should be empty)
whitelist = freqtrade.pairlists._gen_pair_whitelist(base_currency='ETH', key='quoteVolume')
assert whitelist == []
freqtrade.pairlists._precision_filter = precision_filter
freqtrade.config['stake_currency'] = base_currency
whitelist = freqtrade.pairlists._gen_pair_whitelist(base_currency=base_currency, key=key)
assert whitelist == whitelist_result
def test_gen_pair_whitelist_not_supported(mocker, default_conf, tickers) -> None:
@ -145,7 +144,7 @@ def test_gen_pair_whitelist_not_supported(mocker, default_conf, tickers) -> None
@pytest.mark.parametrize("pairlist", AVAILABLE_PAIRLISTS)
def test_pairlist_class(mocker, whitelist_conf, markets, pairlist):
whitelist_conf['pairlist']['method'] = pairlist
mocker.patch('freqtrade.exchange.Exchange.get_markets', markets)
mocker.patch('freqtrade.exchange.Exchange.markets', PropertyMock(return_value=markets))
mocker.patch('freqtrade.exchange.Exchange.exchange_has', MagicMock(return_value=True))
freqtrade = get_patched_freqtradebot(mocker, whitelist_conf)
@ -154,17 +153,24 @@ def test_pairlist_class(mocker, whitelist_conf, markets, pairlist):
assert isinstance(freqtrade.pairlists.whitelist, list)
assert isinstance(freqtrade.pairlists.blacklist, list)
whitelist = ['ETH/BTC', 'TKN/BTC']
@pytest.mark.parametrize("pairlist", AVAILABLE_PAIRLISTS)
@pytest.mark.parametrize("whitelist,log_message", [
(['ETH/BTC', 'TKN/BTC'], ""),
(['ETH/BTC', 'TKN/BTC', 'TRX/ETH'], "is not compatible with exchange"), # TRX/ETH wrong stake
(['ETH/BTC', 'TKN/BTC', 'BCH/BTC'], "is not compatible with exchange"), # BCH/BTC not available
(['ETH/BTC', 'TKN/BTC', 'BLK/BTC'], "is not compatible with exchange"), # BLK/BTC in blacklist
(['ETH/BTC', 'TKN/BTC', 'LTC/BTC'], "Market is not active") # LTC/BTC is inactive
])
def test_validate_whitelist(mocker, whitelist_conf, markets, pairlist, whitelist, caplog,
log_message):
whitelist_conf['pairlist']['method'] = pairlist
mocker.patch('freqtrade.exchange.Exchange.markets', PropertyMock(return_value=markets))
mocker.patch('freqtrade.exchange.Exchange.exchange_has', MagicMock(return_value=True))
freqtrade = get_patched_freqtradebot(mocker, whitelist_conf)
caplog.clear()
new_whitelist = freqtrade.pairlists._validate_whitelist(whitelist)
assert set(whitelist) == set(new_whitelist)
whitelist = ['ETH/BTC', 'TKN/BTC', 'TRX/ETH']
new_whitelist = freqtrade.pairlists._validate_whitelist(whitelist)
# TRX/ETH was removed
assert set(['ETH/BTC', 'TKN/BTC']) == set(new_whitelist)
whitelist = ['ETH/BTC', 'TKN/BTC', 'BLK/BTC']
new_whitelist = freqtrade.pairlists._validate_whitelist(whitelist)
# BLK/BTC is in blacklist ...
assert set(['ETH/BTC', 'TKN/BTC']) == set(new_whitelist)
assert set(new_whitelist) == set(['ETH/BTC', 'TKN/BTC'])
assert log_message in caplog.text

14
freqtrade/tests/rpc/test_fiat_convert.py
View File

@ -8,7 +8,7 @@ import pytest
from requests.exceptions import RequestException
from freqtrade.rpc.fiat_convert import CryptoFiat, CryptoToFiatConverter
from freqtrade.tests.conftest import log_has, patch_coinmarketcap
from freqtrade.tests.conftest import log_has
def test_pair_convertion_object():
@ -40,7 +40,6 @@ def test_pair_convertion_object():
def test_fiat_convert_is_supported(mocker):
patch_coinmarketcap(mocker)
fiat_convert = CryptoToFiatConverter()
assert fiat_convert._is_supported_fiat(fiat='USD') is True
assert fiat_convert._is_supported_fiat(fiat='usd') is True
@ -49,7 +48,6 @@ def test_fiat_convert_is_supported(mocker):
def test_fiat_convert_add_pair(mocker):
patch_coinmarketcap(mocker)
fiat_convert = CryptoToFiatConverter()
@ -72,8 +70,6 @@ def test_fiat_convert_add_pair(mocker):
def test_fiat_convert_find_price(mocker):
patch_coinmarketcap(mocker)
fiat_convert = CryptoToFiatConverter()
with pytest.raises(ValueError, match=r'The fiat ABC is not supported.'):
@ -93,15 +89,12 @@ def test_fiat_convert_find_price(mocker):
def test_fiat_convert_unsupported_crypto(mocker, caplog):
mocker.patch('freqtrade.rpc.fiat_convert.CryptoToFiatConverter._cryptomap', return_value=[])
patch_coinmarketcap(mocker)
fiat_convert = CryptoToFiatConverter()
assert fiat_convert._find_price(crypto_symbol='CRYPTO_123', fiat_symbol='EUR') == 0.0
assert log_has('unsupported crypto-symbol CRYPTO_123 - returning 0.0', caplog.record_tuples)
def test_fiat_convert_get_price(mocker):
patch_coinmarketcap(mocker)
mocker.patch('freqtrade.rpc.fiat_convert.CryptoToFiatConverter._find_price',
return_value=28000.0)
@ -134,21 +127,18 @@ def test_fiat_convert_get_price(mocker):
def test_fiat_convert_same_currencies(mocker):
patch_coinmarketcap(mocker)
fiat_convert = CryptoToFiatConverter()
assert fiat_convert.get_price(crypto_symbol='USD', fiat_symbol='USD') == 1.0
def test_fiat_convert_two_FIAT(mocker):
patch_coinmarketcap(mocker)
fiat_convert = CryptoToFiatConverter()
assert fiat_convert.get_price(crypto_symbol='USD', fiat_symbol='EUR') == 0.0
def test_loadcryptomap(mocker):
patch_coinmarketcap(mocker)
fiat_convert = CryptoToFiatConverter()
assert len(fiat_convert._cryptomap) == 2
@ -174,7 +164,6 @@ def test_fiat_init_network_exception(mocker):
def test_fiat_convert_without_network(mocker):
# Because CryptoToFiatConverter is a Singleton we reset the value of _coinmarketcap
patch_coinmarketcap(mocker)
fiat_convert = CryptoToFiatConverter()
@ -205,7 +194,6 @@ def test_fiat_invalid_response(mocker, caplog):
def test_convert_amount(mocker):
patch_coinmarketcap(mocker)
mocker.patch('freqtrade.rpc.fiat_convert.CryptoToFiatConverter.get_price', return_value=12345.0)
fiat_convert = CryptoToFiatConverter()

131
freqtrade/tests/rpc/test_rpc.py
View File

@ -2,19 +2,20 @@
# pragma pylint: disable=invalid-sequence-index, invalid-name, too-many-arguments
from datetime import datetime
from unittest.mock import MagicMock, ANY
from unittest.mock import ANY, MagicMock, PropertyMock
import pytest
from numpy import isnan
from freqtrade import TemporaryError, DependencyException
from freqtrade import DependencyException, TemporaryError
from freqtrade.edge import PairInfo
from freqtrade.freqtradebot import FreqtradeBot
from freqtrade.persistence import Trade
from freqtrade.rpc import RPC, RPCException
from freqtrade.rpc.fiat_convert import CryptoToFiatConverter
from freqtrade.state import State
from freqtrade.tests.conftest import patch_exchange
from freqtrade.tests.test_freqtradebot import patch_get_signal
from freqtrade.tests.conftest import patch_coinmarketcap, patch_exchange
# Functions for recurrent object patching
@ -27,14 +28,13 @@ def prec_satoshi(a, b) -> float:
# Unit tests
def test_rpc_trade_status(default_conf, ticker, fee, markets, mocker) -> None:
patch_coinmarketcap(mocker)
mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
_load_markets=MagicMock(return_value={}),
get_ticker=ticker,
get_fee=fee,
get_markets=markets
markets=PropertyMock(return_value=markets)
)
freqtradebot = FreqtradeBot(default_conf)
@ -51,14 +51,19 @@ def test_rpc_trade_status(default_conf, ticker, fee, markets, mocker) -> None:
assert {
'trade_id': 1,
'pair': 'ETH/BTC',
'market_url': 'https://bittrex.com/Market/Index?MarketName=BTC-ETH',
'base_currency': 'BTC',
'date': ANY,
'open_rate': 1.099e-05,
'close_rate': None,
'current_rate': 1.098e-05,
'amount': 90.99181074,
'stake_amount': 0.001,
'close_profit': None,
'current_profit': -0.59,
'stop_loss': 0.0,
'initial_stop_loss': 0.0,
'initial_stop_loss_pct': None,
'stop_loss_pct': None,
'open_order': '(limit buy rem=0.00000000)'
} == results[0]
@ -72,27 +77,31 @@ def test_rpc_trade_status(default_conf, ticker, fee, markets, mocker) -> None:
assert {
'trade_id': 1,
'pair': 'ETH/BTC',
'market_url': 'https://bittrex.com/Market/Index?MarketName=BTC-ETH',
'base_currency': 'BTC',
'date': ANY,
'open_rate': 1.099e-05,
'close_rate': None,
'current_rate': ANY,
'amount': 90.99181074,
'stake_amount': 0.001,
'close_profit': None,
'current_profit': ANY,
'stop_loss': 0.0,
'initial_stop_loss': 0.0,
'initial_stop_loss_pct': None,
'stop_loss_pct': None,
'open_order': '(limit buy rem=0.00000000)'
} == results[0]
def test_rpc_status_table(default_conf, ticker, fee, markets, mocker) -> None:
patch_coinmarketcap(mocker)
patch_exchange(mocker)
mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
get_ticker=ticker,
get_fee=fee,
get_markets=markets
markets=PropertyMock(return_value=markets)
)
freqtradebot = FreqtradeBot(default_conf)
@ -121,14 +130,13 @@ def test_rpc_status_table(default_conf, ticker, fee, markets, mocker) -> None:
def test_rpc_daily_profit(default_conf, update, ticker, fee,
limit_buy_order, limit_sell_order, markets, mocker) -> None:
patch_coinmarketcap(mocker, value={'price_usd': 15000.0})
patch_exchange(mocker)
mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
get_ticker=ticker,
get_fee=fee,
get_markets=markets
markets=PropertyMock(return_value=markets)
)
freqtradebot = FreqtradeBot(default_conf)
@ -174,7 +182,6 @@ def test_rpc_trade_statistics(default_conf, ticker, ticker_sell_up, fee,
'freqtrade.rpc.fiat_convert.Market',
ticker=MagicMock(return_value={'price_usd': 15000.0}),
)
patch_coinmarketcap(mocker)
patch_exchange(mocker)
mocker.patch('freqtrade.rpc.rpc.CryptoToFiatConverter._find_price', return_value=15000.0)
mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
@ -182,7 +189,7 @@ def test_rpc_trade_statistics(default_conf, ticker, ticker_sell_up, fee,
'freqtrade.exchange.Exchange',
get_ticker=ticker,
get_fee=fee,
get_markets=markets
markets=PropertyMock(return_value=markets)
)
freqtradebot = FreqtradeBot(default_conf)
@ -270,7 +277,7 @@ def test_rpc_trade_statistics_closed(mocker, default_conf, ticker, fee, markets,
'freqtrade.exchange.Exchange',
get_ticker=ticker,
get_fee=fee,
get_markets=markets
markets=PropertyMock(return_value=markets)
)
freqtradebot = FreqtradeBot(default_conf)
@ -332,7 +339,6 @@ def test_rpc_balance_handle(default_conf, mocker):
'freqtrade.rpc.fiat_convert.Market',
ticker=MagicMock(return_value={'price_usd': 15000.0}),
)
patch_coinmarketcap(mocker)
patch_exchange(mocker)
mocker.patch('freqtrade.rpc.rpc.CryptoToFiatConverter._find_price', return_value=15000.0)
mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
@ -362,7 +368,6 @@ def test_rpc_balance_handle(default_conf, mocker):
def test_rpc_start(mocker, default_conf) -> None:
patch_coinmarketcap(mocker)
patch_exchange(mocker)
mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
mocker.patch.multiple(
@ -385,7 +390,6 @@ def test_rpc_start(mocker, default_conf) -> None:
def test_rpc_stop(mocker, default_conf) -> None:
patch_coinmarketcap(mocker)
patch_exchange(mocker)
mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
mocker.patch.multiple(
@ -408,8 +412,26 @@ def test_rpc_stop(mocker, default_conf) -> None:
assert freqtradebot.state == State.STOPPED
def test_rpc_stopbuy(mocker, default_conf) -> None:
patch_exchange(mocker)
mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
get_ticker=MagicMock()
)
freqtradebot = FreqtradeBot(default_conf)
patch_get_signal(freqtradebot, (True, False))
rpc = RPC(freqtradebot)
freqtradebot.state = State.RUNNING
assert freqtradebot.config['max_open_trades'] != 0
result = rpc._rpc_stopbuy()
assert {'status': 'No more buy will occur from now. Run /reload_conf to reset.'} == result
assert freqtradebot.config['max_open_trades'] == 0
def test_rpc_forcesell(default_conf, ticker, fee, mocker, markets) -> None:
patch_coinmarketcap(mocker)
patch_exchange(mocker)
mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
@ -426,7 +448,7 @@ def test_rpc_forcesell(default_conf, ticker, fee, mocker, markets) -> None:
}
),
get_fee=fee,
get_markets=markets
markets=PropertyMock(return_value=markets)
)
freqtradebot = FreqtradeBot(default_conf)
@ -510,7 +532,6 @@ def test_rpc_forcesell(default_conf, ticker, fee, mocker, markets) -> None:
def test_performance_handle(default_conf, ticker, limit_buy_order, fee,
limit_sell_order, markets, mocker) -> None:
patch_coinmarketcap(mocker)
patch_exchange(mocker)
mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
mocker.patch.multiple(
@ -518,7 +539,7 @@ def test_performance_handle(default_conf, ticker, limit_buy_order, fee,
get_balances=MagicMock(return_value=ticker),
get_ticker=ticker,
get_fee=fee,
get_markets=markets
markets=PropertyMock(return_value=markets)
)
freqtradebot = FreqtradeBot(default_conf)
@ -546,7 +567,6 @@ def test_performance_handle(default_conf, ticker, limit_buy_order, fee,
def test_rpc_count(mocker, default_conf, ticker, fee, markets) -> None:
patch_coinmarketcap(mocker)
patch_exchange(mocker)
mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
mocker.patch.multiple(
@ -554,27 +574,24 @@ def test_rpc_count(mocker, default_conf, ticker, fee, markets) -> None:
get_balances=MagicMock(return_value=ticker),
get_ticker=ticker,
get_fee=fee,
get_markets=markets
markets=PropertyMock(return_value=markets)
)
freqtradebot = FreqtradeBot(default_conf)
patch_get_signal(freqtradebot, (True, False))
rpc = RPC(freqtradebot)
trades = rpc._rpc_count()
nb_trades = len(trades)
assert nb_trades == 0
counts = rpc._rpc_count()
assert counts["current"] == 0
# Create some test data
freqtradebot.create_trade()
trades = rpc._rpc_count()
nb_trades = len(trades)
assert nb_trades == 1
counts = rpc._rpc_count()
assert counts["current"] == 1
def test_rpcforcebuy(mocker, default_conf, ticker, fee, markets, limit_buy_order) -> None:
default_conf['forcebuy_enable'] = True
patch_coinmarketcap(mocker)
patch_exchange(mocker)
mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
buy_mm = MagicMock(return_value={'id': limit_buy_order['id']})
@ -583,7 +600,7 @@ def test_rpcforcebuy(mocker, default_conf, ticker, fee, markets, limit_buy_order
get_balances=MagicMock(return_value=ticker),
get_ticker=ticker,
get_fee=fee,
get_markets=markets,
markets=PropertyMock(return_value=markets),
buy=buy_mm
)
@ -623,7 +640,6 @@ def test_rpcforcebuy(mocker, default_conf, ticker, fee, markets, limit_buy_order
def test_rpcforcebuy_stopped(mocker, default_conf) -> None:
default_conf['forcebuy_enable'] = True
default_conf['initial_state'] = 'stopped'
patch_coinmarketcap(mocker)
patch_exchange(mocker)
mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
@ -636,7 +652,6 @@ def test_rpcforcebuy_stopped(mocker, default_conf) -> None:
def test_rpcforcebuy_disabled(mocker, default_conf) -> None:
patch_coinmarketcap(mocker)
patch_exchange(mocker)
mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
@ -649,7 +664,6 @@ def test_rpcforcebuy_disabled(mocker, default_conf) -> None:
def test_rpc_whitelist(mocker, default_conf) -> None:
patch_coinmarketcap(mocker)
patch_exchange(mocker)
mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
@ -661,7 +675,6 @@ def test_rpc_whitelist(mocker, default_conf) -> None:
def test_rpc_whitelist_dynamic(mocker, default_conf) -> None:
patch_coinmarketcap(mocker)
patch_exchange(mocker)
default_conf['pairlist'] = {'method': 'VolumePairList',
'config': {'number_assets': 4}
@ -675,3 +688,51 @@ def test_rpc_whitelist_dynamic(mocker, default_conf) -> None:
assert ret['method'] == 'VolumePairList'
assert ret['length'] == 4
assert ret['whitelist'] == default_conf['exchange']['pair_whitelist']
def test_rpc_blacklist(mocker, default_conf) -> None:
patch_exchange(mocker)
mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
freqtradebot = FreqtradeBot(default_conf)
rpc = RPC(freqtradebot)
ret = rpc._rpc_blacklist(None)
assert ret['method'] == 'StaticPairList'
assert len(ret['blacklist']) == 2
assert ret['blacklist'] == default_conf['exchange']['pair_blacklist']
assert ret['blacklist'] == ['DOGE/BTC', 'HOT/BTC']
ret = rpc._rpc_blacklist(["ETH/BTC"])
assert ret['method'] == 'StaticPairList'
assert len(ret['blacklist']) == 3
assert ret['blacklist'] == default_conf['exchange']['pair_blacklist']
assert ret['blacklist'] == ['DOGE/BTC', 'HOT/BTC', 'ETH/BTC']
def test_rpc_edge_disabled(mocker, default_conf) -> None:
patch_exchange(mocker)
mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
freqtradebot = FreqtradeBot(default_conf)
rpc = RPC(freqtradebot)
with pytest.raises(RPCException, match=r'Edge is not enabled.'):
rpc._rpc_edge()
def test_rpc_edge_enabled(mocker, edge_conf) -> None:
patch_exchange(mocker)
mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
mocker.patch('freqtrade.edge.Edge._cached_pairs', mocker.PropertyMock(
return_value={
'E/F': PairInfo(-0.02, 0.66, 3.71, 0.50, 1.71, 10, 60),
}
))
freqtradebot = FreqtradeBot(edge_conf)
rpc = RPC(freqtradebot)
ret = rpc._rpc_edge()
assert len(ret) == 1
assert ret[0]['Pair'] == 'E/F'
assert ret[0]['Winrate'] == 0.66
assert ret[0]['Expectancy'] == 1.71
assert ret[0]['Stoploss'] == -0.02

229
freqtrade/tests/rpc/test_rpc_telegram.py
View File

@ -4,8 +4,9 @@
import re
from datetime import datetime
from random import randint
from unittest.mock import MagicMock, ANY
from random import choice, randint
from string import ascii_uppercase
from unittest.mock import MagicMock, PropertyMock
import arrow
import pytest
@ -13,16 +14,16 @@ from telegram import Chat, Message, Update
from telegram.error import NetworkError
from freqtrade import __version__
from freqtrade.edge import PairInfo
from freqtrade.freqtradebot import FreqtradeBot
from freqtrade.persistence import Trade
from freqtrade.rpc import RPCMessageType
from freqtrade.rpc.telegram import Telegram, authorized_only
from freqtrade.strategy.interface import SellType
from freqtrade.state import State
from freqtrade.strategy.interface import SellType
from freqtrade.tests.conftest import (get_patched_freqtradebot, log_has,
patch_exchange)
from freqtrade.tests.test_freqtradebot import patch_get_signal
from freqtrade.tests.conftest import patch_coinmarketcap
class DummyCls(Telegram):
@ -74,7 +75,7 @@ def test_init(default_conf, mocker, caplog) -> None:
message_str = "rpc.telegram is listening for following commands: [['status'], ['profit'], " \
"['balance'], ['start'], ['stop'], ['forcesell'], ['forcebuy'], " \
"['performance'], ['daily'], ['count'], ['reload_conf'], " \
"['whitelist'], ['help'], ['version']]"
"['stopbuy'], ['whitelist'], ['blacklist'], ['edge'], ['help'], ['version']]"
assert log_has(message_str, caplog.record_tuples)
@ -90,7 +91,6 @@ def test_cleanup(default_conf, mocker) -> None:
def test_authorized_only(default_conf, mocker, caplog) -> None:
patch_coinmarketcap(mocker)
patch_exchange(mocker, None)
chat = Chat(0, 0)
@ -118,7 +118,6 @@ def test_authorized_only(default_conf, mocker, caplog) -> None:
def test_authorized_only_unauthorized(default_conf, mocker, caplog) -> None:
patch_coinmarketcap(mocker)
patch_exchange(mocker, None)
chat = Chat(0xdeadbeef, 0)
update = Update(randint(1, 100))
@ -145,7 +144,6 @@ def test_authorized_only_unauthorized(default_conf, mocker, caplog) -> None:
def test_authorized_only_exception(default_conf, mocker, caplog) -> None:
patch_coinmarketcap(mocker)
patch_exchange(mocker)
update = Update(randint(1, 100))
@ -178,14 +176,12 @@ def test_status(default_conf, update, mocker, fee, ticker, markets) -> None:
default_conf['telegram']['enabled'] = False
default_conf['telegram']['chat_id'] = 123
patch_coinmarketcap(mocker)
patch_exchange(mocker)
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
get_ticker=ticker,
get_pair_detail_url=MagicMock(),
get_fee=fee,
get_markets=markets
markets=PropertyMock(markets)
)
msg_mock = MagicMock()
status_table = MagicMock()
@ -195,14 +191,19 @@ def test_status(default_conf, update, mocker, fee, ticker, markets) -> None:
_rpc_trade_status=MagicMock(return_value=[{
'trade_id': 1,
'pair': 'ETH/BTC',
'market_url': 'https://bittrex.com/Market/Index?MarketName=BTC-ETH',
'base_currency': 'BTC',
'date': arrow.utcnow(),
'open_rate': 1.099e-05,
'close_rate': None,
'current_rate': 1.098e-05,
'amount': 90.99181074,
'stake_amount': 90.99181074,
'close_profit': None,
'current_profit': -0.59,
'initial_stop_loss': 1.098e-05,
'stop_loss': 1.099e-05,
'initial_stop_loss_pct': -0.05,
'stop_loss_pct': -0.01,
'open_order': '(limit buy rem=0.00000000)'
}]),
_status_table=status_table,
@ -228,13 +229,12 @@ def test_status(default_conf, update, mocker, fee, ticker, markets) -> None:
def test_status_handle(default_conf, update, ticker, fee, markets, mocker) -> None:
patch_coinmarketcap(mocker)
patch_exchange(mocker)
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
get_ticker=ticker,
get_fee=fee,
get_markets=markets
markets=PropertyMock(markets)
)
msg_mock = MagicMock()
status_table = MagicMock()
@ -269,19 +269,25 @@ def test_status_handle(default_conf, update, ticker, fee, markets, mocker) -> No
# Trigger status while we have a fulfilled order for the open trade
telegram._status(bot=MagicMock(), update=update)
# close_rate should not be included in the message as the trade is not closed
# and no line should be empty
lines = msg_mock.call_args_list[0][0][0].split('\n')
assert '' not in lines
assert 'Close Rate' not in ''.join(lines)
assert 'Close Profit' not in ''.join(lines)
assert msg_mock.call_count == 1
assert '[ETH/BTC]' in msg_mock.call_args_list[0][0][0]
assert 'ETH/BTC' in msg_mock.call_args_list[0][0][0]
def test_status_table_handle(default_conf, update, ticker, fee, markets, mocker) -> None:
patch_coinmarketcap(mocker)
patch_exchange(mocker)
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
get_ticker=ticker,
buy=MagicMock(return_value={'id': 'mocked_order_id'}),
get_fee=fee,
get_markets=markets
markets=PropertyMock(markets)
)
msg_mock = MagicMock()
mocker.patch.multiple(
@ -326,7 +332,6 @@ def test_status_table_handle(default_conf, update, ticker, fee, markets, mocker)
def test_daily_handle(default_conf, update, ticker, limit_buy_order, fee,
limit_sell_order, markets, mocker) -> None:
patch_coinmarketcap(mocker, value={'price_usd': 15000.0})
patch_exchange(mocker)
mocker.patch(
'freqtrade.rpc.rpc.CryptoToFiatConverter._find_price',
@ -336,7 +341,7 @@ def test_daily_handle(default_conf, update, ticker, limit_buy_order, fee,
'freqtrade.exchange.Exchange',
get_ticker=ticker,
get_fee=fee,
get_markets=markets
markets=PropertyMock(markets)
)
msg_mock = MagicMock()
mocker.patch.multiple(
@ -397,7 +402,6 @@ def test_daily_handle(default_conf, update, ticker, limit_buy_order, fee,
def test_daily_wrong_input(default_conf, update, ticker, mocker) -> None:
patch_coinmarketcap(mocker, value={'price_usd': 15000.0})
patch_exchange(mocker)
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
@ -433,14 +437,13 @@ def test_daily_wrong_input(default_conf, update, ticker, mocker) -> None:
def test_profit_handle(default_conf, update, ticker, ticker_sell_up, fee,
limit_buy_order, limit_sell_order, markets, mocker) -> None:
patch_coinmarketcap(mocker, value={'price_usd': 15000.0})
patch_exchange(mocker)
mocker.patch('freqtrade.rpc.rpc.CryptoToFiatConverter._find_price', return_value=15000.0)
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
get_ticker=ticker,
get_fee=fee,
get_markets=markets
markets=PropertyMock(markets)
)
msg_mock = MagicMock()
mocker.patch.multiple(
@ -538,7 +541,6 @@ def test_telegram_balance_handle(default_conf, update, mocker) -> None:
'last': 0.1,
}
patch_coinmarketcap(mocker, value={'price_usd': 15000.0})
mocker.patch('freqtrade.exchange.Exchange.get_balances', return_value=mock_balance)
mocker.patch('freqtrade.exchange.Exchange.get_ticker', side_effect=mock_ticker)
@ -587,6 +589,45 @@ def test_balance_handle_empty_response(default_conf, update, mocker) -> None:
assert 'all balances are zero' in result
def test_balance_handle_too_large_response(default_conf, update, mocker) -> None:
balances = []
for i in range(100):
curr = choice(ascii_uppercase) + choice(ascii_uppercase) + choice(ascii_uppercase)
balances.append({
'currency': curr,
'available': 1.0,
'pending': 0.5,
'balance': i,
'est_btc': 1
})
mocker.patch('freqtrade.rpc.rpc.RPC._rpc_balance', return_value={
'currencies': balances,
'total': 100.0,
'symbol': 100.0,
'value': 1000.0,
})
msg_mock = MagicMock()
mocker.patch.multiple(
'freqtrade.rpc.telegram.Telegram',
_init=MagicMock(),
_send_msg=msg_mock
)
freqtradebot = get_patched_freqtradebot(mocker, default_conf)
patch_get_signal(freqtradebot, (True, False))
telegram = Telegram(freqtradebot)
telegram._balance(bot=MagicMock(), update=update)
assert msg_mock.call_count > 1
# Test if wrap happens around 4000 -
# and each single currency-output is around 120 characters long so we need
# an offset to avoid random test failures
assert len(msg_mock.call_args_list[0][0][0]) < 4096
assert len(msg_mock.call_args_list[0][0][0]) > (4096 - 120)
def test_start_handle(default_conf, update, mocker) -> None:
msg_mock = MagicMock()
mocker.patch.multiple(
@ -625,7 +666,6 @@ def test_start_handle_already_running(default_conf, update, mocker) -> None:
def test_stop_handle(default_conf, update, mocker) -> None:
patch_coinmarketcap(mocker)
msg_mock = MagicMock()
mocker.patch.multiple(
'freqtrade.rpc.telegram.Telegram',
@ -645,7 +685,6 @@ def test_stop_handle(default_conf, update, mocker) -> None:
def test_stop_handle_already_stopped(default_conf, update, mocker) -> None:
patch_coinmarketcap(mocker)
msg_mock = MagicMock()
mocker.patch.multiple(
'freqtrade.rpc.telegram.Telegram',
@ -664,8 +703,26 @@ def test_stop_handle_already_stopped(default_conf, update, mocker) -> None:
assert 'already stopped' in msg_mock.call_args_list[0][0][0]
def test_stopbuy_handle(default_conf, update, mocker) -> None:
msg_mock = MagicMock()
mocker.patch.multiple(
'freqtrade.rpc.telegram.Telegram',
_init=MagicMock(),
_send_msg=msg_mock
)
freqtradebot = get_patched_freqtradebot(mocker, default_conf)
telegram = Telegram(freqtradebot)
assert freqtradebot.config['max_open_trades'] != 0
telegram._stopbuy(bot=MagicMock(), update=update)
assert freqtradebot.config['max_open_trades'] == 0
assert msg_mock.call_count == 1
assert 'No more buy will occur from now. Run /reload_conf to reset.' \
in msg_mock.call_args_list[0][0][0]
def test_reload_conf_handle(default_conf, update, mocker) -> None:
patch_coinmarketcap(mocker)
msg_mock = MagicMock()
mocker.patch.multiple(
'freqtrade.rpc.telegram.Telegram',
@ -686,7 +743,6 @@ def test_reload_conf_handle(default_conf, update, mocker) -> None:
def test_forcesell_handle(default_conf, update, ticker, fee,
ticker_sell_up, markets, mocker) -> None:
patch_coinmarketcap(mocker, value={'price_usd': 15000.0})
mocker.patch('freqtrade.rpc.rpc.CryptoToFiatConverter._find_price', return_value=15000.0)
rpc_mock = mocker.patch('freqtrade.rpc.telegram.Telegram.send_msg', MagicMock())
mocker.patch('freqtrade.rpc.telegram.Telegram._init', MagicMock())
@ -695,7 +751,8 @@ def test_forcesell_handle(default_conf, update, ticker, fee,
_load_markets=MagicMock(return_value={}),
get_ticker=ticker,
get_fee=fee,
get_markets=markets
markets=PropertyMock(return_value=markets),
validate_pairs=MagicMock(return_value={})
)
freqtradebot = FreqtradeBot(default_conf)
@ -721,7 +778,6 @@ def test_forcesell_handle(default_conf, update, ticker, fee,
'exchange': 'Bittrex',
'pair': 'ETH/BTC',
'gain': 'profit',
'market_url': 'https://bittrex.com/Market/Index?MarketName=BTC-ETH',
'limit': 1.172e-05,
'amount': 90.99181073703367,
'open_rate': 1.099e-05,
@ -736,7 +792,6 @@ def test_forcesell_handle(default_conf, update, ticker, fee,
def test_forcesell_down_handle(default_conf, update, ticker, fee,
ticker_sell_down, markets, mocker) -> None:
patch_coinmarketcap(mocker, value={'price_usd': 15000.0})
mocker.patch('freqtrade.rpc.fiat_convert.CryptoToFiatConverter._find_price',
return_value=15000.0)
rpc_mock = mocker.patch('freqtrade.rpc.telegram.Telegram.send_msg', MagicMock())
@ -746,7 +801,8 @@ def test_forcesell_down_handle(default_conf, update, ticker, fee,
_load_markets=MagicMock(return_value={}),
get_ticker=ticker,
get_fee=fee,
get_markets=markets
markets=PropertyMock(return_value=markets),
validate_pairs=MagicMock(return_value={})
)
freqtradebot = FreqtradeBot(default_conf)
@ -776,7 +832,6 @@ def test_forcesell_down_handle(default_conf, update, ticker, fee,
'exchange': 'Bittrex',
'pair': 'ETH/BTC',
'gain': 'loss',
'market_url': 'https://bittrex.com/Market/Index?MarketName=BTC-ETH',
'limit': 1.044e-05,
'amount': 90.99181073703367,
'open_rate': 1.099e-05,
@ -790,18 +845,17 @@ def test_forcesell_down_handle(default_conf, update, ticker, fee,
def test_forcesell_all_handle(default_conf, update, ticker, fee, markets, mocker) -> None:
patch_coinmarketcap(mocker, value={'price_usd': 15000.0})
patch_exchange(mocker)
mocker.patch('freqtrade.rpc.fiat_convert.CryptoToFiatConverter._find_price',
return_value=15000.0)
rpc_mock = mocker.patch('freqtrade.rpc.telegram.Telegram.send_msg', MagicMock())
mocker.patch('freqtrade.rpc.telegram.Telegram._init', MagicMock())
mocker.patch('freqtrade.exchange.Exchange.get_pair_detail_url', MagicMock())
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
get_ticker=ticker,
get_fee=fee,
get_markets=markets
markets=PropertyMock(return_value=markets),
validate_pairs=MagicMock(return_value={})
)
freqtradebot = FreqtradeBot(default_conf)
@ -823,7 +877,6 @@ def test_forcesell_all_handle(default_conf, update, ticker, fee, markets, mocker
'exchange': 'Bittrex',
'pair': 'ETH/BTC',
'gain': 'loss',
'market_url': ANY,
'limit': 1.098e-05,
'amount': 90.99181073703367,
'open_rate': 1.099e-05,
@ -837,7 +890,6 @@ def test_forcesell_all_handle(default_conf, update, ticker, fee, markets, mocker
def test_forcesell_handle_invalid(default_conf, update, mocker) -> None:
patch_coinmarketcap(mocker, value={'price_usd': 15000.0})
mocker.patch('freqtrade.rpc.fiat_convert.CryptoToFiatConverter._find_price',
return_value=15000.0)
msg_mock = MagicMock()
@ -877,14 +929,14 @@ def test_forcesell_handle_invalid(default_conf, update, mocker) -> None:
def test_forcebuy_handle(default_conf, update, markets, mocker) -> None:
patch_coinmarketcap(mocker, value={'price_usd': 15000.0})
mocker.patch('freqtrade.rpc.rpc.CryptoToFiatConverter._find_price', return_value=15000.0)
mocker.patch('freqtrade.rpc.telegram.Telegram._send_msg', MagicMock())
mocker.patch('freqtrade.rpc.telegram.Telegram._init', MagicMock())
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
_load_markets=MagicMock(return_value={}),
get_markets=markets
markets=PropertyMock(markets),
validate_pairs=MagicMock(return_value={})
)
fbuy_mock = MagicMock(return_value=None)
mocker.patch('freqtrade.rpc.RPC._rpc_forcebuy', fbuy_mock)
@ -913,14 +965,14 @@ def test_forcebuy_handle(default_conf, update, markets, mocker) -> None:
def test_forcebuy_handle_exception(default_conf, update, markets, mocker) -> None:
patch_coinmarketcap(mocker, value={'price_usd': 15000.0})
mocker.patch('freqtrade.rpc.rpc.CryptoToFiatConverter._find_price', return_value=15000.0)
rpc_mock = mocker.patch('freqtrade.rpc.telegram.Telegram._send_msg', MagicMock())
mocker.patch('freqtrade.rpc.telegram.Telegram._init', MagicMock())
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
_load_markets=MagicMock(return_value={}),
get_markets=markets
markets=PropertyMock(markets),
validate_pairs=MagicMock(return_value={})
)
freqtradebot = FreqtradeBot(default_conf)
patch_get_signal(freqtradebot, (True, False))
@ -935,7 +987,6 @@ def test_forcebuy_handle_exception(default_conf, update, markets, mocker) -> Non
def test_performance_handle(default_conf, update, ticker, fee,
limit_buy_order, limit_sell_order, markets, mocker) -> None:
patch_coinmarketcap(mocker)
patch_exchange(mocker)
msg_mock = MagicMock()
mocker.patch.multiple(
@ -947,7 +998,8 @@ def test_performance_handle(default_conf, update, ticker, fee,
'freqtrade.exchange.Exchange',
get_ticker=ticker,
get_fee=fee,
get_markets=markets
markets=PropertyMock(markets),
validate_pairs=MagicMock(return_value={})
)
mocker.patch('freqtrade.freqtradebot.RPCManager', MagicMock())
freqtradebot = FreqtradeBot(default_conf)
@ -974,7 +1026,6 @@ def test_performance_handle(default_conf, update, ticker, fee,
def test_count_handle(default_conf, update, ticker, fee, markets, mocker) -> None:
patch_coinmarketcap(mocker)
patch_exchange(mocker)
msg_mock = MagicMock()
mocker.patch.multiple(
@ -986,7 +1037,7 @@ def test_count_handle(default_conf, update, ticker, fee, markets, mocker) -> Non
'freqtrade.exchange.Exchange',
get_ticker=ticker,
buy=MagicMock(return_value={'id': 'mocked_order_id'}),
get_markets=markets
markets=PropertyMock(markets)
)
mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
freqtradebot = FreqtradeBot(default_conf)
@ -1015,7 +1066,6 @@ def test_count_handle(default_conf, update, ticker, fee, markets, mocker) -> Non
def test_whitelist_static(default_conf, update, mocker) -> None:
patch_coinmarketcap(mocker)
msg_mock = MagicMock()
mocker.patch.multiple(
'freqtrade.rpc.telegram.Telegram',
@ -1033,7 +1083,6 @@ def test_whitelist_static(default_conf, update, mocker) -> None:
def test_whitelist_dynamic(default_conf, update, mocker) -> None:
patch_coinmarketcap(mocker)
msg_mock = MagicMock()
mocker.patch.multiple(
'freqtrade.rpc.telegram.Telegram',
@ -1054,8 +1103,71 @@ def test_whitelist_dynamic(default_conf, update, mocker) -> None:
in msg_mock.call_args_list[0][0][0])
def test_blacklist_static(default_conf, update, mocker) -> None:
msg_mock = MagicMock()
mocker.patch.multiple(
'freqtrade.rpc.telegram.Telegram',
_init=MagicMock(),
_send_msg=msg_mock
)
freqtradebot = get_patched_freqtradebot(mocker, default_conf)
telegram = Telegram(freqtradebot)
telegram._blacklist(bot=MagicMock(), update=update, args=[])
assert msg_mock.call_count == 1
assert ("Blacklist contains 2 pairs\n`DOGE/BTC, HOT/BTC`"
in msg_mock.call_args_list[0][0][0])
msg_mock.reset_mock()
telegram._blacklist(bot=MagicMock(), update=update, args=["ETH/BTC"])
assert msg_mock.call_count == 1
assert ("Blacklist contains 3 pairs\n`DOGE/BTC, HOT/BTC, ETH/BTC`"
in msg_mock.call_args_list[0][0][0])
assert freqtradebot.pairlists.blacklist == ["DOGE/BTC", "HOT/BTC", "ETH/BTC"]
def test_edge_disabled(default_conf, update, mocker) -> None:
msg_mock = MagicMock()
mocker.patch.multiple(
'freqtrade.rpc.telegram.Telegram',
_init=MagicMock(),
_send_msg=msg_mock
)
freqtradebot = get_patched_freqtradebot(mocker, default_conf)
telegram = Telegram(freqtradebot)
telegram._edge(bot=MagicMock(), update=update)
assert msg_mock.call_count == 1
assert "Edge is not enabled." in msg_mock.call_args_list[0][0][0]
def test_edge_enabled(edge_conf, update, mocker) -> None:
msg_mock = MagicMock()
mocker.patch('freqtrade.edge.Edge._cached_pairs', mocker.PropertyMock(
return_value={
'E/F': PairInfo(-0.01, 0.66, 3.71, 0.50, 1.71, 10, 60),
}
))
mocker.patch.multiple(
'freqtrade.rpc.telegram.Telegram',
_init=MagicMock(),
_send_msg=msg_mock
)
freqtradebot = get_patched_freqtradebot(mocker, edge_conf)
telegram = Telegram(freqtradebot)
telegram._edge(bot=MagicMock(), update=update)
assert msg_mock.call_count == 1
assert '<b>Edge only validated following pairs:</b>\n<pre>' in msg_mock.call_args_list[0][0][0]
assert 'Pair Winrate Expectancy Stoploss' in msg_mock.call_args_list[0][0][0]
def test_help_handle(default_conf, update, mocker) -> None:
patch_coinmarketcap(mocker)
msg_mock = MagicMock()
mocker.patch.multiple(
'freqtrade.rpc.telegram.Telegram',
@ -1072,7 +1184,6 @@ def test_help_handle(default_conf, update, mocker) -> None:
def test_version_handle(default_conf, update, mocker) -> None:
patch_coinmarketcap(mocker)
msg_mock = MagicMock()
mocker.patch.multiple(
'freqtrade.rpc.telegram.Telegram',
@ -1100,7 +1211,6 @@ def test_send_msg_buy_notification(default_conf, mocker) -> None:
'type': RPCMessageType.BUY_NOTIFICATION,
'exchange': 'Bittrex',
'pair': 'ETH/BTC',
'market_url': 'https://bittrex.com/Market/Index?MarketName=BTC-ETH',
'limit': 1.099e-05,
'stake_amount': 0.001,
'stake_amount_fiat': 0.0,
@ -1108,7 +1218,7 @@ def test_send_msg_buy_notification(default_conf, mocker) -> None:
'fiat_currency': 'USD'
})
assert msg_mock.call_args[0][0] \
== '*Bittrex:* Buying [ETH/BTC](https://bittrex.com/Market/Index?MarketName=BTC-ETH)\n' \
== '*Bittrex:* Buying ETH/BTC\n' \
'with limit `0.00001099\n' \
'(0.001000 BTC,0.000 USD)`'
@ -1129,7 +1239,6 @@ def test_send_msg_sell_notification(default_conf, mocker) -> None:
'exchange': 'Binance',
'pair': 'KEY/ETH',
'gain': 'loss',
'market_url': 'https://www.binance.com/tradeDetail.html?symbol=KEY_ETH',
'limit': 3.201e-05,
'amount': 1333.3333333333335,
'open_rate': 7.5e-05,
@ -1141,8 +1250,7 @@ def test_send_msg_sell_notification(default_conf, mocker) -> None:
'sell_reason': SellType.STOP_LOSS.value
})
assert msg_mock.call_args[0][0] \
== ('*Binance:* Selling [KEY/ETH]'
'(https://www.binance.com/tradeDetail.html?symbol=KEY_ETH)\n'
== ('*Binance:* Selling KEY/ETH\n'
'*Limit:* `0.00003201`\n'
'*Amount:* `1333.33333333`\n'
'*Open Rate:* `0.00007500`\n'
@ -1156,7 +1264,6 @@ def test_send_msg_sell_notification(default_conf, mocker) -> None:
'exchange': 'Binance',
'pair': 'KEY/ETH',
'gain': 'loss',
'market_url': 'https://www.binance.com/tradeDetail.html?symbol=KEY_ETH',
'limit': 3.201e-05,
'amount': 1333.3333333333335,
'open_rate': 7.5e-05,
@ -1167,8 +1274,7 @@ def test_send_msg_sell_notification(default_conf, mocker) -> None:
'sell_reason': SellType.STOP_LOSS.value
})
assert msg_mock.call_args[0][0] \
== ('*Binance:* Selling [KEY/ETH]'
'(https://www.binance.com/tradeDetail.html?symbol=KEY_ETH)\n'
== ('*Binance:* Selling KEY/ETH\n'
'*Limit:* `0.00003201`\n'
'*Amount:* `1333.33333333`\n'
'*Open Rate:* `0.00007500`\n'
@ -1256,7 +1362,6 @@ def test_send_msg_buy_notification_no_fiat(default_conf, mocker) -> None:
'type': RPCMessageType.BUY_NOTIFICATION,
'exchange': 'Bittrex',
'pair': 'ETH/BTC',
'market_url': 'https://bittrex.com/Market/Index?MarketName=BTC-ETH',
'limit': 1.099e-05,
'stake_amount': 0.001,
'stake_amount_fiat': 0.0,
@ -1264,7 +1369,7 @@ def test_send_msg_buy_notification_no_fiat(default_conf, mocker) -> None:
'fiat_currency': None
})
assert msg_mock.call_args[0][0] \
== '*Bittrex:* Buying [ETH/BTC](https://bittrex.com/Market/Index?MarketName=BTC-ETH)\n' \
== '*Bittrex:* Buying ETH/BTC\n' \
'with limit `0.00001099\n' \
'(0.001000 BTC)`'
@ -1284,7 +1389,6 @@ def test_send_msg_sell_notification_no_fiat(default_conf, mocker) -> None:
'exchange': 'Binance',
'pair': 'KEY/ETH',
'gain': 'loss',
'market_url': 'https://www.binance.com/tradeDetail.html?symbol=KEY_ETH',
'limit': 3.201e-05,
'amount': 1333.3333333333335,
'open_rate': 7.5e-05,
@ -1296,8 +1400,7 @@ def test_send_msg_sell_notification_no_fiat(default_conf, mocker) -> None:
'sell_reason': SellType.STOP_LOSS.value
})
assert msg_mock.call_args[0][0] \
== '*Binance:* Selling [KEY/ETH]' \
'(https://www.binance.com/tradeDetail.html?symbol=KEY_ETH)\n' \
== '*Binance:* Selling KEY/ETH\n' \
'*Limit:* `0.00003201`\n' \
'*Amount:* `1333.33333333`\n' \
'*Open Rate:* `0.00007500`\n' \
@ -1307,7 +1410,6 @@ def test_send_msg_sell_notification_no_fiat(default_conf, mocker) -> None:
def test__send_msg(default_conf, mocker) -> None:
patch_coinmarketcap(mocker)
mocker.patch('freqtrade.rpc.telegram.Telegram._init', MagicMock())
bot = MagicMock()
freqtradebot = get_patched_freqtradebot(mocker, default_conf)
@ -1319,7 +1421,6 @@ def test__send_msg(default_conf, mocker) -> None:
def test__send_msg_network_error(default_conf, mocker, caplog) -> None:
patch_coinmarketcap(mocker)
mocker.patch('freqtrade.rpc.telegram.Telegram._init', MagicMock())
bot = MagicMock()
bot.send_message = MagicMock(side_effect=NetworkError('Oh snap'))

3
freqtrade/tests/rpc/test_rpc_webhook.py
View File

@ -48,7 +48,6 @@ def test_send_msg(default_conf, mocker):
'type': RPCMessageType.BUY_NOTIFICATION,
'exchange': 'Bittrex',
'pair': 'ETH/BTC',
'market_url': "http://mockedurl/ETH_BTC",
'limit': 0.005,
'stake_amount': 0.8,
'stake_amount_fiat': 500,
@ -73,7 +72,6 @@ def test_send_msg(default_conf, mocker):
'exchange': 'Bittrex',
'pair': 'ETH/BTC',
'gain': "profit",
'market_url': "http://mockedurl/ETH_BTC",
'limit': 0.005,
'amount': 0.8,
'open_rate': 0.004,
@ -127,7 +125,6 @@ def test_exception_send_msg(default_conf, mocker, caplog):
'type': RPCMessageType.BUY_NOTIFICATION,
'exchange': 'Bittrex',
'pair': 'ETH/BTC',
'market_url': "http://mockedurl/ETH_BTC",
'limit': 0.005,
'stake_amount': 0.8,
'stake_amount_fiat': 500,

20
freqtrade/tests/strategy/test_strategy.py
View File

@ -1,17 +1,19 @@
# pragma pylint: disable=missing-docstring, protected-access, C0103
import logging
import warnings
from base64 import urlsafe_b64encode
from os import path
from pathlib import Path
import warnings
from unittest.mock import Mock
import pytest
from pandas import DataFrame
from freqtrade.resolvers import StrategyResolver
from freqtrade.strategy import import_strategy
from freqtrade.strategy.default_strategy import DefaultStrategy
from freqtrade.strategy.interface import IStrategy
from freqtrade.resolvers import StrategyResolver
from freqtrade.tests.conftest import log_has_re
def test_import_strategy(caplog):
@ -94,6 +96,16 @@ def test_load_not_found_strategy():
strategy._load_strategy(strategy_name='NotFoundStrategy', config={})
def test_load_staticmethod_importerror(mocker, caplog):
mocker.patch("freqtrade.resolvers.strategy_resolver.import_strategy", Mock(
side_effect=TypeError("can't pickle staticmethod objects")))
with pytest.raises(ImportError,
match=r"Impossible to load Strategy 'DefaultStrategy'."
r" This class does not exist or contains Python code errors"):
StrategyResolver()
assert log_has_re(r".*Error: can't pickle staticmethod objects", caplog.record_tuples)
def test_strategy(result):
config = {'strategy': 'DefaultStrategy'}
@ -194,11 +206,13 @@ def test_strategy_override_ticker_interval(caplog):
config = {
'strategy': 'DefaultStrategy',
'ticker_interval': 60
'ticker_interval': 60,
'stake_currency': 'ETH'
}
resolver = StrategyResolver(config)
assert resolver.strategy.ticker_interval == 60
assert resolver.strategy.stake_currency == 'ETH'
assert ('freqtrade.resolvers.strategy_resolver',
logging.INFO,
"Override strategy 'ticker_interval' with value in config file: 60."

15
freqtrade/tests/test_arguments.py
View File

@ -16,7 +16,7 @@ def test_parse_args_none() -> None:
def test_parse_args_defaults() -> None:
args = Arguments([], '').get_parsed_arg()
assert args.config == 'config.json'
assert args.config == ['config.json']
assert args.strategy_path is None
assert args.datadir is None
assert args.loglevel == 0
@ -24,10 +24,15 @@ def test_parse_args_defaults() -> None:
def test_parse_args_config() -> None:
args = Arguments(['-c', '/dev/null'], '').get_parsed_arg()
assert args.config == '/dev/null'
assert args.config == ['/dev/null']
args = Arguments(['--config', '/dev/null'], '').get_parsed_arg()
assert args.config == '/dev/null'
assert args.config == ['/dev/null']
args = Arguments(['--config', '/dev/null',
'--config', '/dev/zero'],
'').get_parsed_arg()
assert args.config == ['/dev/null', '/dev/zero']
def test_parse_args_db_url() -> None:
@ -139,7 +144,7 @@ def test_parse_args_backtesting_custom() -> None:
'TestStrategy'
]
call_args = Arguments(args, '').get_parsed_arg()
assert call_args.config == 'test_conf.json'
assert call_args.config == ['test_conf.json']
assert call_args.live is True
assert call_args.loglevel == 0
assert call_args.subparser == 'backtesting'
@ -158,7 +163,7 @@ def test_parse_args_hyperopt_custom() -> None:
'--spaces', 'buy'
]
call_args = Arguments(args, '').get_parsed_arg()
assert call_args.config == 'test_conf.json'
assert call_args.config == ['test_conf.json']
assert call_args.epochs == 20
assert call_args.loglevel == 0
assert call_args.subparser == 'hyperopt'

108
freqtrade/tests/test_configuration.py
View File

@ -1,15 +1,16 @@
# pragma pylint: disable=missing-docstring, protected-access, invalid-name
import json
from argparse import Namespace
import logging
from argparse import Namespace
from copy import deepcopy
from unittest.mock import MagicMock
from pathlib import Path
import pytest
from jsonschema import validate, ValidationError, Draft4Validator
from jsonschema import Draft4Validator, ValidationError, validate
from freqtrade import constants
from freqtrade import OperationalException
from freqtrade import OperationalException, constants
from freqtrade.arguments import Arguments
from freqtrade.configuration import Configuration, set_loggers
from freqtrade.constants import DEFAULT_DB_DRYRUN_URL, DEFAULT_DB_PROD_URL
@ -22,7 +23,7 @@ def test_load_config_invalid_pair(default_conf) -> None:
with pytest.raises(ValidationError, match=r'.*does not match.*'):
configuration = Configuration(Namespace())
configuration._validate_config(default_conf)
configuration._validate_config_schema(default_conf)
def test_load_config_missing_attributes(default_conf) -> None:
@ -30,7 +31,7 @@ def test_load_config_missing_attributes(default_conf) -> None:
with pytest.raises(ValidationError, match=r'.*\'exchange\' is a required property.*'):
configuration = Configuration(Namespace())
configuration._validate_config(default_conf)
configuration._validate_config_schema(default_conf)
def test_load_config_incorrect_stake_amount(default_conf) -> None:
@ -38,7 +39,7 @@ def test_load_config_incorrect_stake_amount(default_conf) -> None:
with pytest.raises(ValidationError, match=r'.*\'fake\' does not match \'unlimited\'.*'):
configuration = Configuration(Namespace())
configuration._validate_config(default_conf)
configuration._validate_config_schema(default_conf)
def test_load_config_file(default_conf, mocker, caplog) -> None:
@ -50,18 +51,49 @@ def test_load_config_file(default_conf, mocker, caplog) -> None:
validated_conf = configuration._load_config_file('somefile')
assert file_mock.call_count == 1
assert validated_conf.items() >= default_conf.items()
assert 'internals' in validated_conf
assert log_has('Validating configuration ...', caplog.record_tuples)
def test_load_config_max_open_trades_zero(default_conf, mocker, caplog) -> None:
default_conf['max_open_trades'] = 0
file_mock = mocker.patch('freqtrade.configuration.open', mocker.mock_open(
mocker.patch('freqtrade.configuration.open', mocker.mock_open(
read_data=json.dumps(default_conf)
))
Configuration(Namespace())._load_config_file('somefile')
assert file_mock.call_count == 1
args = Arguments([], '').get_parsed_arg()
configuration = Configuration(args)
validated_conf = configuration.load_config()
assert validated_conf['max_open_trades'] == 0
assert 'internals' in validated_conf
assert log_has('Validating configuration ...', caplog.record_tuples)
def test_load_config_combine_dicts(default_conf, mocker, caplog) -> None:
conf1 = deepcopy(default_conf)
conf2 = deepcopy(default_conf)
del conf1['exchange']['key']
del conf1['exchange']['secret']
del conf2['exchange']['name']
conf2['exchange']['pair_whitelist'] += ['NANO/BTC']
config_files = [conf1, conf2]
configsmock = MagicMock(side_effect=config_files)
mocker.patch('freqtrade.configuration.Configuration._load_config_file', configsmock)
arg_list = ['-c', 'test_conf.json', '--config', 'test2_conf.json', ]
args = Arguments(arg_list, '').get_parsed_arg()
configuration = Configuration(args)
validated_conf = configuration.load_config()
exchange_conf = default_conf['exchange']
assert validated_conf['exchange']['name'] == exchange_conf['name']
assert validated_conf['exchange']['key'] == exchange_conf['key']
assert validated_conf['exchange']['secret'] == exchange_conf['secret']
assert validated_conf['exchange']['pair_whitelist'] != conf1['exchange']['pair_whitelist']
assert validated_conf['exchange']['pair_whitelist'] == conf2['exchange']['pair_whitelist']
assert 'internals' in validated_conf
assert log_has('Validating configuration ...', caplog.record_tuples)
@ -453,15 +485,6 @@ def test_check_exchange(default_conf, caplog) -> None:
):
configuration.check_exchange(default_conf)
# Test ccxt_rate_limit depreciation
default_conf.get('exchange').update({'name': 'binance'})
default_conf['exchange']['ccxt_rate_limit'] = True
configuration.check_exchange(default_conf)
assert log_has("`ccxt_rate_limit` has been deprecated in favor of "
"`ccxt_config` and `ccxt_async_config` and will be removed "
"in a future version.",
caplog.record_tuples)
def test_cli_verbose_with_params(default_conf, mocker, caplog) -> None:
mocker.patch('freqtrade.configuration.open', mocker.mock_open(
@ -516,6 +539,23 @@ def test_set_loggers() -> None:
assert logging.getLogger('telegram').level is logging.INFO
def test_set_logfile(default_conf, mocker):
mocker.patch('freqtrade.configuration.open',
mocker.mock_open(read_data=json.dumps(default_conf)))
arglist = [
'--logfile', 'test_file.log',
]
args = Arguments(arglist, '').get_parsed_arg()
configuration = Configuration(args)
validated_conf = configuration.load_config()
assert validated_conf['logfile'] == "test_file.log"
f = Path("test_file.log")
assert f.is_file()
f.unlink()
def test_load_config_warn_forcebuy(default_conf, mocker, caplog) -> None:
default_conf['forcebuy_enable'] = True
mocker.patch('freqtrade.configuration.open', mocker.mock_open(
@ -542,3 +582,29 @@ def test__create_datadir(mocker, default_conf, caplog) -> None:
cfg._create_datadir(default_conf, '/foo/bar')
assert md.call_args[0][0] == "/foo/bar"
assert log_has('Created data directory: /foo/bar', caplog.record_tuples)
def test_validate_tsl(default_conf):
default_conf['trailing_stop'] = True
default_conf['trailing_stop_positive'] = 0
default_conf['trailing_stop_positive_offset'] = 0
default_conf['trailing_only_offset_is_reached'] = True
with pytest.raises(OperationalException,
match=r'The config trailing_only_offset_is_reached needs '
'trailing_stop_positive_offset to be more than 0 in your config.'):
configuration = Configuration(Namespace())
configuration._validate_config_consistency(default_conf)
default_conf['trailing_stop_positive_offset'] = 0.01
default_conf['trailing_stop_positive'] = 0.015
with pytest.raises(OperationalException,
match=r'The config trailing_stop_positive_offset needs '
'to be greater than trailing_stop_positive_offset in your config.'):
configuration = Configuration(Namespace())
configuration._validate_config_consistency(default_conf)
default_conf['trailing_stop_positive'] = 0.01
default_conf['trailing_stop_positive_offset'] = 0.015
Configuration(Namespace())
configuration._validate_config_consistency(default_conf)

584
freqtrade/tests/test_freqtradebot.py
View File

File diff suppressed because it is too large Load Diff

68
freqtrade/tests/test_main.py
View File

@ -7,8 +7,8 @@ import pytest
from freqtrade import OperationalException
from freqtrade.arguments import Arguments
from freqtrade.freqtradebot import FreqtradeBot
from freqtrade.main import main, reconfigure
from freqtrade.worker import Worker
from freqtrade.main import main
from freqtrade.state import State
from freqtrade.tests.conftest import log_has, patch_exchange
@ -22,7 +22,7 @@ def test_parse_args_backtesting(mocker) -> None:
main(['backtesting'])
assert backtesting_mock.call_count == 1
call_args = backtesting_mock.call_args[0][0]
assert call_args.config == 'config.json'
assert call_args.config == ['config.json']
assert call_args.live is False
assert call_args.loglevel == 0
assert call_args.subparser == 'backtesting'
@ -35,7 +35,7 @@ def test_main_start_hyperopt(mocker) -> None:
main(['hyperopt'])
assert hyperopt_mock.call_count == 1
call_args = hyperopt_mock.call_args[0][0]
assert call_args.config == 'config.json'
assert call_args.config == ['config.json']
assert call_args.loglevel == 0
assert call_args.subparser == 'hyperopt'
assert call_args.func is not None
@ -43,17 +43,14 @@ def test_main_start_hyperopt(mocker) -> None:
def test_main_fatal_exception(mocker, default_conf, caplog) -> None:
patch_exchange(mocker)
mocker.patch.multiple(
'freqtrade.freqtradebot.FreqtradeBot',
_init_modules=MagicMock(),
worker=MagicMock(side_effect=Exception),
cleanup=MagicMock(),
)
mocker.patch('freqtrade.freqtradebot.FreqtradeBot.cleanup', MagicMock())
mocker.patch('freqtrade.worker.Worker._worker', MagicMock(side_effect=Exception))
mocker.patch(
'freqtrade.configuration.Configuration._load_config_file',
lambda *args, **kwargs: default_conf
)
mocker.patch('freqtrade.freqtradebot.RPCManager', MagicMock())
mocker.patch('freqtrade.freqtradebot.persistence.init', MagicMock())
args = ['-c', 'config.json.example']
@ -66,17 +63,14 @@ def test_main_fatal_exception(mocker, default_conf, caplog) -> None:
def test_main_keyboard_interrupt(mocker, default_conf, caplog) -> None:
patch_exchange(mocker)
mocker.patch.multiple(
'freqtrade.freqtradebot.FreqtradeBot',
_init_modules=MagicMock(),
worker=MagicMock(side_effect=KeyboardInterrupt),
cleanup=MagicMock(),
)
mocker.patch('freqtrade.freqtradebot.FreqtradeBot.cleanup', MagicMock())
mocker.patch('freqtrade.worker.Worker._worker', MagicMock(side_effect=KeyboardInterrupt))
mocker.patch(
'freqtrade.configuration.Configuration._load_config_file',
lambda *args, **kwargs: default_conf
)
mocker.patch('freqtrade.freqtradebot.RPCManager', MagicMock())
mocker.patch('freqtrade.freqtradebot.persistence.init', MagicMock())
args = ['-c', 'config.json.example']
@ -89,17 +83,17 @@ def test_main_keyboard_interrupt(mocker, default_conf, caplog) -> None:
def test_main_operational_exception(mocker, default_conf, caplog) -> None:
patch_exchange(mocker)
mocker.patch.multiple(
'freqtrade.freqtradebot.FreqtradeBot',
_init_modules=MagicMock(),
worker=MagicMock(side_effect=OperationalException('Oh snap!')),
cleanup=MagicMock(),
mocker.patch('freqtrade.freqtradebot.FreqtradeBot.cleanup', MagicMock())
mocker.patch(
'freqtrade.worker.Worker._worker',
MagicMock(side_effect=OperationalException('Oh snap!'))
)
mocker.patch(
'freqtrade.configuration.Configuration._load_config_file',
lambda *args, **kwargs: default_conf
)
mocker.patch('freqtrade.freqtradebot.RPCManager', MagicMock())
mocker.patch('freqtrade.freqtradebot.persistence.init', MagicMock())
args = ['-c', 'config.json.example']
@ -112,21 +106,18 @@ def test_main_operational_exception(mocker, default_conf, caplog) -> None:
def test_main_reload_conf(mocker, default_conf, caplog) -> None:
patch_exchange(mocker)
mocker.patch.multiple(
'freqtrade.freqtradebot.FreqtradeBot',
_init_modules=MagicMock(),
worker=MagicMock(return_value=State.RELOAD_CONF),
cleanup=MagicMock(),
)
mocker.patch('freqtrade.freqtradebot.FreqtradeBot.cleanup', MagicMock())
mocker.patch('freqtrade.worker.Worker._worker', MagicMock(return_value=State.RELOAD_CONF))
mocker.patch(
'freqtrade.configuration.Configuration._load_config_file',
lambda *args, **kwargs: default_conf
)
mocker.patch('freqtrade.freqtradebot.RPCManager', MagicMock())
mocker.patch('freqtrade.freqtradebot.persistence.init', MagicMock())
# Raise exception as side effect to avoid endless loop
reconfigure_mock = mocker.patch(
'freqtrade.main.reconfigure', MagicMock(side_effect=Exception)
'freqtrade.main.Worker._reconfigure', MagicMock(side_effect=Exception)
)
with pytest.raises(SystemExit):
@ -138,19 +129,21 @@ def test_main_reload_conf(mocker, default_conf, caplog) -> None:
def test_reconfigure(mocker, default_conf) -> None:
patch_exchange(mocker)
mocker.patch.multiple(
'freqtrade.freqtradebot.FreqtradeBot',
_init_modules=MagicMock(),
worker=MagicMock(side_effect=OperationalException('Oh snap!')),
cleanup=MagicMock(),
mocker.patch('freqtrade.freqtradebot.FreqtradeBot.cleanup', MagicMock())
mocker.patch(
'freqtrade.worker.Worker._worker',
MagicMock(side_effect=OperationalException('Oh snap!'))
)
mocker.patch(
'freqtrade.configuration.Configuration._load_config_file',
lambda *args, **kwargs: default_conf
)
mocker.patch('freqtrade.freqtradebot.RPCManager', MagicMock())
mocker.patch('freqtrade.freqtradebot.persistence.init', MagicMock())
freqtrade = FreqtradeBot(default_conf)
args = Arguments(['-c', 'config.json.example'], '').get_parsed_arg()
worker = Worker(args=args, config=default_conf)
freqtrade = worker.freqtrade
# Renew mock to return modified data
conf = deepcopy(default_conf)
@ -160,11 +153,10 @@ def test_reconfigure(mocker, default_conf) -> None:
lambda *args, **kwargs: conf
)
worker._config = conf
# reconfigure should return a new instance
freqtrade2 = reconfigure(
freqtrade,
Arguments(['-c', 'config.json.example'], '').get_parsed_arg()
)
worker._reconfigure()
freqtrade2 = worker.freqtrade
# Verify we have a new instance with the new config
assert freqtrade is not freqtrade2

137
freqtrade/tests/test_persistence.py
View File

@ -510,6 +510,7 @@ def test_migrate_new(mocker, default_conf, fee, caplog):
assert trade.pair == "ETC/BTC"
assert trade.exchange == "binance"
assert trade.max_rate == 0.0
assert trade.min_rate is None
assert trade.stop_loss == 0.0
assert trade.initial_stop_loss == 0.0
assert trade.sell_reason is None
@ -585,7 +586,58 @@ def test_migrate_mid_state(mocker, default_conf, fee, caplog):
caplog.record_tuples)
def test_adjust_stop_loss(limit_buy_order, limit_sell_order, fee):
def test_adjust_stop_loss(fee):
trade = Trade(
pair='ETH/BTC',
stake_amount=0.001,
fee_open=fee.return_value,
fee_close=fee.return_value,
exchange='bittrex',
open_rate=1,
max_rate=1,
)
trade.adjust_stop_loss(trade.open_rate, 0.05, True)
assert trade.stop_loss == 0.95
assert trade.stop_loss_pct == -0.05
assert trade.initial_stop_loss == 0.95
assert trade.initial_stop_loss_pct == -0.05
# Get percent of profit with a lower rate
trade.adjust_stop_loss(0.96, 0.05)
assert trade.stop_loss == 0.95
assert trade.stop_loss_pct == -0.05
assert trade.initial_stop_loss == 0.95
assert trade.initial_stop_loss_pct == -0.05
# Get percent of profit with a custom rate (Higher than open rate)
trade.adjust_stop_loss(1.3, -0.1)
assert round(trade.stop_loss, 8) == 1.17
assert trade.stop_loss_pct == -0.1
assert trade.initial_stop_loss == 0.95
assert trade.initial_stop_loss_pct == -0.05
# current rate lower again ... should not change
trade.adjust_stop_loss(1.2, 0.1)
assert round(trade.stop_loss, 8) == 1.17
assert trade.initial_stop_loss == 0.95
assert trade.initial_stop_loss_pct == -0.05
# current rate higher... should raise stoploss
trade.adjust_stop_loss(1.4, 0.1)
assert round(trade.stop_loss, 8) == 1.26
assert trade.initial_stop_loss == 0.95
assert trade.initial_stop_loss_pct == -0.05
# Initial is true but stop_loss set - so doesn't do anything
trade.adjust_stop_loss(1.7, 0.1, True)
assert round(trade.stop_loss, 8) == 1.26
assert trade.initial_stop_loss == 0.95
assert trade.initial_stop_loss_pct == -0.05
assert trade.stop_loss_pct == -0.1
def test_adjust_min_max_rates(fee):
trade = Trade(
pair='ETH/BTC',
stake_amount=0.001,
@ -595,37 +647,66 @@ def test_adjust_stop_loss(limit_buy_order, limit_sell_order, fee):
open_rate=1,
)
trade.adjust_stop_loss(trade.open_rate, 0.05, True)
assert trade.stop_loss == 0.95
trade.adjust_min_max_rates(trade.open_rate)
assert trade.max_rate == 1
assert trade.initial_stop_loss == 0.95
assert trade.min_rate == 1
# Get percent of profit with a lowre rate
trade.adjust_stop_loss(0.96, 0.05)
assert trade.stop_loss == 0.95
# check min adjusted, max remained
trade.adjust_min_max_rates(0.96)
assert trade.max_rate == 1
assert trade.initial_stop_loss == 0.95
assert trade.min_rate == 0.96
# Get percent of profit with a custom rate (Higher than open rate)
trade.adjust_stop_loss(1.3, -0.1)
assert round(trade.stop_loss, 8) == 1.17
assert trade.max_rate == 1.3
assert trade.initial_stop_loss == 0.95
# check max adjusted, min remains
trade.adjust_min_max_rates(1.05)
assert trade.max_rate == 1.05
assert trade.min_rate == 0.96
# current rate lower again ... should not change
trade.adjust_stop_loss(1.2, 0.1)
assert round(trade.stop_loss, 8) == 1.17
assert trade.max_rate == 1.3
assert trade.initial_stop_loss == 0.95
# current rate "in the middle" - no adjustment
trade.adjust_min_max_rates(1.03)
assert trade.max_rate == 1.05
assert trade.min_rate == 0.96
# current rate higher... should raise stoploss
trade.adjust_stop_loss(1.4, 0.1)
assert round(trade.stop_loss, 8) == 1.26
assert trade.max_rate == 1.4
assert trade.initial_stop_loss == 0.95
# Initial is true but stop_loss set - so doesn't do anything
trade.adjust_stop_loss(1.7, 0.1, True)
assert round(trade.stop_loss, 8) == 1.26
assert trade.max_rate == 1.4
assert trade.initial_stop_loss == 0.95
def test_get_open(default_conf, fee):
init(default_conf)
# Simulate dry_run entries
trade = Trade(
pair='ETH/BTC',
stake_amount=0.001,
amount=123.0,
fee_open=fee.return_value,
fee_close=fee.return_value,
open_rate=0.123,
exchange='bittrex',
open_order_id='dry_run_buy_12345'
)
Trade.session.add(trade)
trade = Trade(
pair='ETC/BTC',
stake_amount=0.001,
amount=123.0,
fee_open=fee.return_value,
fee_close=fee.return_value,
open_rate=0.123,
exchange='bittrex',
is_open=False,
open_order_id='dry_run_sell_12345'
)
Trade.session.add(trade)
# Simulate prod entry
trade = Trade(
pair='ETC/BTC',
stake_amount=0.001,
amount=123.0,
fee_open=fee.return_value,
fee_close=fee.return_value,
open_rate=0.123,
exchange='bittrex',
open_order_id='prod_buy_12345'
)
Trade.session.add(trade)
assert len(Trade.get_open_trades()) == 2

42
freqtrade/tests/test_wallets.py
View File

@ -23,13 +23,13 @@ def test_sync_wallet_at_boot(mocker, default_conf):
freqtrade = get_patched_freqtradebot(mocker, default_conf)
assert len(freqtrade.wallets.wallets) == 2
assert freqtrade.wallets.wallets['BNT'].free == 1.0
assert freqtrade.wallets.wallets['BNT'].used == 2.0
assert freqtrade.wallets.wallets['BNT'].total == 3.0
assert freqtrade.wallets.wallets['GAS'].free == 0.260739
assert freqtrade.wallets.wallets['GAS'].used == 0.0
assert freqtrade.wallets.wallets['GAS'].total == 0.260739
assert len(freqtrade.wallets._wallets) == 2
assert freqtrade.wallets._wallets['BNT'].free == 1.0
assert freqtrade.wallets._wallets['BNT'].used == 2.0
assert freqtrade.wallets._wallets['BNT'].total == 3.0
assert freqtrade.wallets._wallets['GAS'].free == 0.260739
assert freqtrade.wallets._wallets['GAS'].used == 0.0
assert freqtrade.wallets._wallets['GAS'].total == 0.260739
assert freqtrade.wallets.get_free('BNT') == 1.0
mocker.patch.multiple(
@ -50,13 +50,13 @@ def test_sync_wallet_at_boot(mocker, default_conf):
freqtrade.wallets.update()
assert len(freqtrade.wallets.wallets) == 2
assert freqtrade.wallets.wallets['BNT'].free == 1.2
assert freqtrade.wallets.wallets['BNT'].used == 1.9
assert freqtrade.wallets.wallets['BNT'].total == 3.5
assert freqtrade.wallets.wallets['GAS'].free == 0.270739
assert freqtrade.wallets.wallets['GAS'].used == 0.1
assert freqtrade.wallets.wallets['GAS'].total == 0.260439
assert len(freqtrade.wallets._wallets) == 2
assert freqtrade.wallets._wallets['BNT'].free == 1.2
assert freqtrade.wallets._wallets['BNT'].used == 1.9
assert freqtrade.wallets._wallets['BNT'].total == 3.5
assert freqtrade.wallets._wallets['GAS'].free == 0.270739
assert freqtrade.wallets._wallets['GAS'].used == 0.1
assert freqtrade.wallets._wallets['GAS'].total == 0.260439
assert freqtrade.wallets.get_free('GAS') == 0.270739
assert freqtrade.wallets.get_used('GAS') == 0.1
assert freqtrade.wallets.get_total('GAS') == 0.260439
@ -81,11 +81,11 @@ def test_sync_wallet_missing_data(mocker, default_conf):
freqtrade = get_patched_freqtradebot(mocker, default_conf)
assert len(freqtrade.wallets.wallets) == 2
assert freqtrade.wallets.wallets['BNT'].free == 1.0
assert freqtrade.wallets.wallets['BNT'].used == 2.0
assert freqtrade.wallets.wallets['BNT'].total == 3.0
assert freqtrade.wallets.wallets['GAS'].free == 0.260739
assert freqtrade.wallets.wallets['GAS'].used is None
assert freqtrade.wallets.wallets['GAS'].total == 0.260739
assert len(freqtrade.wallets._wallets) == 2
assert freqtrade.wallets._wallets['BNT'].free == 1.0
assert freqtrade.wallets._wallets['BNT'].used == 2.0
assert freqtrade.wallets._wallets['BNT'].total == 3.0
assert freqtrade.wallets._wallets['GAS'].free == 0.260739
assert freqtrade.wallets._wallets['GAS'].used is None
assert freqtrade.wallets._wallets['GAS'].total == 0.260739
assert freqtrade.wallets.get_free('GAS') == 0.260739

1
freqtrade/tests/testdata/backtest-result_test.json vendored Normal file
View File

File diff suppressed because one or more lines are too long

39
freqtrade/wallets.py
View File

@ -1,15 +1,16 @@
# pragma pylint: disable=W0603
""" Wallet """
import logging
from typing import Dict, Any, NamedTuple
from typing import Dict, NamedTuple
from freqtrade.exchange import Exchange
from freqtrade import constants
logger = logging.getLogger(__name__)
# wallet data structure
class Wallet(NamedTuple):
exchange: str
currency: str
free: float = 0
used: float = 0
@ -18,17 +19,19 @@ class Wallet(NamedTuple):
class Wallets(object):
def __init__(self, exchange: Exchange) -> None:
self.exchange = exchange
self.wallets: Dict[str, Any] = {}
def __init__(self, config: dict, exchange: Exchange) -> None:
self._config = config
self._exchange = exchange
self._wallets: Dict[str, Wallet] = {}
self.update()
def get_free(self, currency) -> float:
if self.exchange._conf['dry_run']:
return 999.9
if self._config['dry_run']:
return self._config.get('dry_run_wallet', constants.DRY_RUN_WALLET)
balance = self.wallets.get(currency)
balance = self._wallets.get(currency)
if balance and balance.free:
return balance.free
else:
@ -36,10 +39,10 @@ class Wallets(object):
def get_used(self, currency) -> float:
if self.exchange._conf['dry_run']:
return 999.9
if self._config['dry_run']:
return self._config.get('dry_run_wallet', constants.DRY_RUN_WALLET)
balance = self.wallets.get(currency)
balance = self._wallets.get(currency)
if balance and balance.used:
return balance.used
else:
@ -47,25 +50,25 @@ class Wallets(object):
def get_total(self, currency) -> float:
if self.exchange._conf['dry_run']:
return 999.9
if self._config['dry_run']:
return self._config.get('dry_run_wallet', constants.DRY_RUN_WALLET)
balance = self.wallets.get(currency)
balance = self._wallets.get(currency)
if balance and balance.total:
return balance.total
else:
return 0
def update(self) -> None:
balances = self.exchange.get_balances()
balances = self._exchange.get_balances()
for currency in balances:
self.wallets[currency] = Wallet(
self.exchange.id,
self._wallets[currency] = Wallet(
currency,
balances[currency].get('free', None),
balances[currency].get('used', None),
balances[currency].get('total', None)
)
logger.info('Wallets synced ...')
logger.info('Wallets synced.')

188
freqtrade/worker.py Executable file
View File

@ -0,0 +1,188 @@
"""
Main Freqtrade worker class.
"""
import logging
import time
import traceback
from argparse import Namespace
from typing import Any, Callable, Optional
import sdnotify
from freqtrade import (constants, OperationalException, TemporaryError,
__version__)
from freqtrade.configuration import Configuration
from freqtrade.freqtradebot import FreqtradeBot
from freqtrade.state import State
from freqtrade.rpc import RPCMessageType
logger = logging.getLogger(__name__)
class Worker(object):
"""
Freqtradebot worker class
"""
def __init__(self, args: Namespace, config=None) -> None:
"""
Init all variables and objects the bot needs to work
"""
logger.info('Starting worker %s', __version__)
self._args = args
self._config = config
self._init(False)
# Tell systemd that we completed initialization phase
if self._sd_notify:
logger.debug("sd_notify: READY=1")
self._sd_notify.notify("READY=1")
def _init(self, reconfig: bool):
"""
Also called from the _reconfigure() method (with reconfig=True).
"""
if reconfig or self._config is None:
# Load configuration
self._config = Configuration(self._args, None).get_config()
# Init the instance of the bot
self.freqtrade = FreqtradeBot(self._config)
self._throttle_secs = self._config.get('internals', {}).get(
'process_throttle_secs',
constants.PROCESS_THROTTLE_SECS
)
self._sd_notify = sdnotify.SystemdNotifier() if \
self._config.get('internals', {}).get('sd_notify', False) else None
@property
def state(self) -> State:
return self.freqtrade.state
@state.setter
def state(self, value: State):
self.freqtrade.state = value
def run(self):
state = None
while True:
state = self._worker(old_state=state)
if state == State.RELOAD_CONF:
self.freqtrade = self._reconfigure()
def _worker(self, old_state: State, throttle_secs: Optional[float] = None) -> State:
"""
Trading routine that must be run at each loop
:param old_state: the previous service state from the previous call
:return: current service state
"""
state = self.freqtrade.state
if throttle_secs is None:
throttle_secs = self._throttle_secs
# Log state transition
if state != old_state:
self.freqtrade.rpc.send_msg({
'type': RPCMessageType.STATUS_NOTIFICATION,
'status': f'{state.name.lower()}'
})
logger.info('Changing state to: %s', state.name)
if state == State.RUNNING:
self.freqtrade.rpc.startup_messages(self._config, self.freqtrade.pairlists)
if state == State.STOPPED:
# Ping systemd watchdog before sleeping in the stopped state
if self._sd_notify:
logger.debug("sd_notify: WATCHDOG=1\\nSTATUS=State: STOPPED.")
self._sd_notify.notify("WATCHDOG=1\nSTATUS=State: STOPPED.")
time.sleep(throttle_secs)
elif state == State.RUNNING:
# Ping systemd watchdog before throttling
if self._sd_notify:
logger.debug("sd_notify: WATCHDOG=1\\nSTATUS=State: RUNNING.")
self._sd_notify.notify("WATCHDOG=1\nSTATUS=State: RUNNING.")
self._throttle(func=self._process, min_secs=throttle_secs)
return state
def _throttle(self, func: Callable[..., Any], min_secs: float, *args, **kwargs) -> Any:
"""
Throttles the given callable that it
takes at least `min_secs` to finish execution.
:param func: Any callable
:param min_secs: minimum execution time in seconds
:return: Any
"""
start = time.time()
result = func(*args, **kwargs)
end = time.time()
duration = max(min_secs - (end - start), 0.0)
logger.debug('Throttling %s for %.2f seconds', func.__name__, duration)
time.sleep(duration)
return result
def _process(self) -> bool:
state_changed = False
try:
state_changed = self.freqtrade.process()
except TemporaryError as error:
logger.warning(f"Error: {error}, retrying in {constants.RETRY_TIMEOUT} seconds...")
time.sleep(constants.RETRY_TIMEOUT)
except OperationalException:
tb = traceback.format_exc()
hint = 'Issue `/start` if you think it is safe to restart.'
self.freqtrade.rpc.send_msg({
'type': RPCMessageType.STATUS_NOTIFICATION,
'status': f'OperationalException:\n```\n{tb}```{hint}'
})
logger.exception('OperationalException. Stopping trader ...')
self.freqtrade.state = State.STOPPED
# TODO: The return value of _process() is not used apart tests
# and should (could) be eliminated later. See PR #1689.
# state_changed = True
return state_changed
def _reconfigure(self):
"""
Cleans up current freqtradebot instance, reloads the configuration and
replaces it with the new instance
"""
# Tell systemd that we initiated reconfiguration
if self._sd_notify:
logger.debug("sd_notify: RELOADING=1")
self._sd_notify.notify("RELOADING=1")
# Clean up current freqtrade modules
self.freqtrade.cleanup()
# Load and validate config and create new instance of the bot
self._init(True)
self.freqtrade.rpc.send_msg({
'type': RPCMessageType.STATUS_NOTIFICATION,
'status': 'config reloaded'
})
# Tell systemd that we completed reconfiguration
if self._sd_notify:
logger.debug("sd_notify: READY=1")
self._sd_notify.notify("READY=1")
def exit(self):
# Tell systemd that we are exiting now
if self._sd_notify:
logger.debug("sd_notify: STOPPING=1")
self._sd_notify.notify("STOPPING=1")
if self.freqtrade:
self.freqtrade.rpc.send_msg({
'type': RPCMessageType.STATUS_NOTIFICATION,
'status': 'process died'
})
self.freqtrade.cleanup()

12
mkdocs.yml
View File

@ -3,18 +3,20 @@ nav:
- About: index.md
- Installation: installation.md
- Configuration: configuration.md
- Start the bot: bot-usage.md
- Stoploss: stoploss.md
- Custom Strategy: bot-optimization.md
- Telegram: telegram-usage.md
- Web Hook: webhook-config.md
- Stoploss: stoploss.md
- Start the bot: bot-usage.md
- Control the bot:
- Telegram: telegram-usage.md
- Web Hook: webhook-config.md
- Backtesting: backtesting.md
- Hyperopt: hyperopt.md
- Edge positioning: edge.md
- Plotting: plotting.md
- Deprecated features: deprecated.md
- FAQ: faq.md
- SQL Cheatsheet: sql_cheatsheet.md
- Sanbox testing: sandbox-testing.md
- Sandbox testing: sandbox-testing.md
- Contributors guide: developer.md
theme:
name: material

10
requirements-dev.txt
View File

@ -1,12 +1,12 @@
# Include all requirements to run the bot.
-r requirements.txt
flake8==3.7.6
flake8==3.7.7
flake8-type-annotations==0.1.0
flake8-tidy-imports==2.0.0
pytest==4.3.0
pytest-mock==1.10.1
pytest==4.4.1
pytest-mock==1.10.3
pytest-asyncio==0.10.0
pytest-cov==2.6.1
coveralls==1.6.0
mypy==0.670
coveralls==1.7.0
mypy==0.701

23
requirements-pi.txt Normal file
View File

@ -0,0 +1,23 @@
ccxt==1.18.472
SQLAlchemy==1.3.3
python-telegram-bot==11.1.0
arrow==0.13.1
cachetools==3.1.0
requests==2.21.0
urllib3==1.24.1
wrapt==1.11.1
scikit-learn==0.20.3
joblib==0.13.2
jsonschema==3.0.1
TA-Lib==0.4.17
tabulate==0.8.3
coinmarketcap==5.0.3
# Required for hyperopt
scikit-optimize==0.5.2
# find first, C search in arrays
py_find_1st==1.1.3
#Load ticker files 30% faster
python-rapidjson==0.7.0

2
requirements-plot.txt
View File

@ -1,5 +1,5 @@
# Include all requirements to run the bot.
-r requirements.txt
plotly==3.6.1
plotly==3.8.0

17
requirements.txt
View File

@ -1,17 +1,17 @@
ccxt==1.18.270
SQLAlchemy==1.2.18
ccxt==1.18.472
SQLAlchemy==1.3.3
python-telegram-bot==11.1.0
arrow==0.13.1
cachetools==3.1.0
requests==2.21.0
urllib3==1.24.1
wrapt==1.11.1
numpy==1.16.1
pandas==0.24.1
scikit-learn==0.20.2
numpy==1.16.2
pandas==0.24.2
scikit-learn==0.20.3
joblib==0.13.2
scipy==1.2.1
jsonschema==2.6.0
jsonschema==3.0.1
TA-Lib==0.4.17
tabulate==0.8.3
coinmarketcap==5.0.3
@ -22,5 +22,8 @@ scikit-optimize==0.5.2
# find first, C search in arrays
py_find_1st==1.1.3
#Load ticker files 30% faster
# Load ticker files 30% faster
python-rapidjson==0.7.0
# Notify systemd
sdnotify==0.3.2

55
scripts/download_backtest_data.py
View File

@ -1,16 +1,19 @@
#!/usr/bin/env python3
"""This script generate json data"""
"""
This script generates json data
"""
import json
import sys
from pathlib import Path
import arrow
from typing import Any, Dict
from freqtrade import arguments
from freqtrade.arguments import Arguments
from freqtrade.arguments import TimeRange
from freqtrade.exchange import Exchange
from freqtrade.data.history import download_pair_history
from freqtrade.configuration import Configuration, set_loggers
from freqtrade.misc import deep_merge_dicts
import logging
logging.basicConfig(
@ -21,7 +24,7 @@ set_loggers(0)
DEFAULT_DL_PATH = 'user_data/data'
arguments = arguments.Arguments(sys.argv[1:], 'download utility')
arguments = Arguments(sys.argv[1:], 'download utility')
arguments.testdata_dl_options()
args = arguments.parse_args()
@ -29,25 +32,33 @@ timeframes = args.timeframes
if args.config:
configuration = Configuration(args)
config = configuration._load_config_file(args.config)
config: Dict[str, Any] = {}
# Now expecting a list of config filenames here, not a string
for path in args.config:
print(f"Using config: {path}...")
# Merge config options, overwriting old values
config = deep_merge_dicts(configuration._load_config_file(path), config)
config['stake_currency'] = ''
# Ensure we do not use Exchange credentials
config['exchange']['key'] = ''
config['exchange']['secret'] = ''
else:
config = {'stake_currency': '',
'dry_run': True,
'exchange': {
'name': args.exchange,
'key': '',
'secret': '',
'pair_whitelist': [],
'ccxt_async_config': {
"enableRateLimit": False
}
}
}
config = {
'stake_currency': '',
'dry_run': True,
'exchange': {
'name': args.exchange,
'key': '',
'secret': '',
'pair_whitelist': [],
'ccxt_async_config': {
'enableRateLimit': True,
'rateLimit': 200
}
}
}
dl_path = Path(DEFAULT_DL_PATH).joinpath(config['exchange']['name'])
@ -84,18 +95,18 @@ for pair in PAIRS:
pairs_not_available.append(pair)
print(f"skipping pair {pair}")
continue
for tick_interval in timeframes:
for ticker_interval in timeframes:
pair_print = pair.replace('/', '_')
filename = f'{pair_print}-{tick_interval}.json'
filename = f'{pair_print}-{ticker_interval}.json'
dl_file = dl_path.joinpath(filename)
if args.erase and dl_file.exists():
print(f'Deleting existing data for pair {pair}, interval {tick_interval}')
print(f'Deleting existing data for pair {pair}, interval {ticker_interval}')
dl_file.unlink()
print(f'downloading pair {pair}, interval {tick_interval}')
print(f'downloading pair {pair}, interval {ticker_interval}')
download_pair_history(datadir=dl_path, exchange=exchange,
pair=pair,
tick_interval=tick_interval,
ticker_interval=ticker_interval,
timerange=timerange)

14
scripts/get_market_pairs.py
View File

@ -1,5 +1,10 @@
"""
This script was adapted from ccxt here:
https://github.com/ccxt/ccxt/blob/master/examples/py/arbitrage-pairs.py
"""
import os
import sys
import traceback
root = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
sys.path.append(root + '/python')
@ -49,8 +54,12 @@ def print_supported_exchanges():
try:
id = sys.argv[1] # get exchange id from command line arguments
if len(sys.argv) < 2:
dump("Usage: python " + sys.argv[0], green('id'))
print_supported_exchanges()
sys.exit(1)
id = sys.argv[1] # get exchange id from command line arguments
# check if the exchange is supported by ccxt
exchange_found = id in ccxt.exchanges
@ -88,6 +97,7 @@ try:
except Exception as e:
dump('[' + type(e).__name__ + ']', str(e))
dump(traceback.format_exc())
dump("Usage: python " + sys.argv[0], green('id'))
print_supported_exchanges()
sys.exit(1)

62
scripts/plot_dataframe.py
View File

@ -24,23 +24,22 @@ Example of usage:
> python3 scripts/plot_dataframe.py --pairs BTC/EUR,XRP/BTC -d user_data/data/
--indicators1 sma,ema3 --indicators2 fastk,fastd
"""
import json
import logging
import sys
from argparse import Namespace
from pathlib import Path
from typing import Dict, List, Any
from typing import Any, Dict, List
import pandas as pd
import plotly.graph_objs as go
import pytz
from plotly import tools
from plotly.offline import plot
from freqtrade import persistence
from freqtrade.arguments import Arguments, TimeRange
from freqtrade.data import history
from freqtrade.data.btanalysis import BT_DATA_COLUMNS, load_backtest_data
from freqtrade.exchange import Exchange
from freqtrade.optimize.backtesting import setup_configuration
from freqtrade.persistence import Trade
@ -56,7 +55,8 @@ def load_trades(args: Namespace, pair: str, timerange: TimeRange) -> pd.DataFram
trades: pd.DataFrame = pd.DataFrame()
if args.db_url:
persistence.init(_CONF)
columns = ["pair", "profit", "opents", "closets", "open_rate", "close_rate", "duration"]
columns = ["pair", "profit", "open_time", "close_time",
"open_rate", "close_rate", "duration"]
for x in Trade.query.all():
print("date: {}".format(x.open_date))
@ -71,38 +71,18 @@ def load_trades(args: Namespace, pair: str, timerange: TimeRange) -> pd.DataFram
columns=columns)
elif args.exportfilename:
file = Path(args.exportfilename)
# must align with columns in backtest.py
columns = ["pair", "profit", "opents", "closets", "index", "duration",
"open_rate", "close_rate", "open_at_end", "sell_reason"]
if file.exists():
with file.open() as f:
data = json.load(f)
trades = pd.DataFrame(data, columns=columns)
trades = trades.loc[trades["pair"] == pair]
if timerange:
if timerange.starttype == 'date':
trades = trades.loc[trades["opents"] >= timerange.startts]
if timerange.stoptype == 'date':
trades = trades.loc[trades["opents"] <= timerange.stopts]
trades['opents'] = pd.to_datetime(
trades['opents'],
unit='s',
utc=True,
infer_datetime_format=True)
trades['closets'] = pd.to_datetime(
trades['closets'],
unit='s',
utc=True,
infer_datetime_format=True)
file = Path(args.exportfilename)
if file.exists():
load_backtest_data(file)
else:
trades = pd.DataFrame([], columns=columns)
trades = pd.DataFrame([], columns=BT_DATA_COLUMNS)
return trades
def generate_plot_file(fig, pair, tick_interval, is_last) -> None:
def generate_plot_file(fig, pair, ticker_interval, is_last) -> None:
"""
Generate a plot html file from pre populated fig plotly object
:return: None
@ -110,7 +90,7 @@ def generate_plot_file(fig, pair, tick_interval, is_last) -> None:
logger.info('Generate plot file for %s', pair)
pair_name = pair.replace("/", "_")
file_name = 'freqtrade-plot-' + pair_name + '-' + tick_interval + '.html'
file_name = 'freqtrade-plot-' + pair_name + '-' + ticker_interval + '.html'
Path("user_data/plots").mkdir(parents=True, exist_ok=True)
@ -155,20 +135,20 @@ def get_tickers_data(strategy, exchange, pairs: List[str], args):
:return: dictinnary of tickers. output format: {'pair': tickersdata}
"""
tick_interval = strategy.ticker_interval
ticker_interval = strategy.ticker_interval
timerange = Arguments.parse_timerange(args.timerange)
tickers = {}
if args.live:
logger.info('Downloading pairs.')
exchange.refresh_latest_ohlcv([(pair, tick_interval) for pair in pairs])
exchange.refresh_latest_ohlcv([(pair, ticker_interval) for pair in pairs])
for pair in pairs:
tickers[pair] = exchange.klines((pair, tick_interval))
tickers[pair] = exchange.klines((pair, ticker_interval))
else:
tickers = history.load_data(
datadir=Path(_CONF.get("datadir")),
datadir=Path(str(_CONF.get("datadir"))),
pairs=pairs,
ticker_interval=tick_interval,
ticker_interval=ticker_interval,
refresh_pairs=_CONF.get('refresh_pairs', False),
timerange=timerange,
exchange=Exchange(_CONF)
@ -206,7 +186,7 @@ def extract_trades_of_period(dataframe, trades) -> pd.DataFrame:
Compare trades and backtested pair DataFrames to get trades performed on backtested period
:return: the DataFrame of a trades of period
"""
trades = trades.loc[trades['opents'] >= dataframe.iloc[0]['date']]
trades = trades.loc[trades['open_time'] >= dataframe.iloc[0]['date']]
return trades
@ -279,7 +259,7 @@ def generate_graph(
)
trade_buys = go.Scattergl(
x=trades["opents"],
x=trades["open_time"],
y=trades["open_rate"],
mode='markers',
name='trade_buy',
@ -291,7 +271,7 @@ def generate_graph(
)
)
trade_sells = go.Scattergl(
x=trades["closets"],
x=trades["close_time"],
y=trades["close_rate"],
mode='markers',
name='trade_sell',
@ -419,7 +399,7 @@ def analyse_and_plot_pairs(args: Namespace):
strategy, exchange, pairs = get_trading_env(args)
# Set timerange to use
timerange = Arguments.parse_timerange(args.timerange)
tick_interval = strategy.ticker_interval
ticker_interval = strategy.ticker_interval
tickers = get_tickers_data(strategy, exchange, pairs, args)
pair_counter = 0
@ -442,7 +422,7 @@ def analyse_and_plot_pairs(args: Namespace):
)
is_last = (False, True)[pair_counter == len(tickers)]
generate_plot_file(fig, pair, tick_interval, is_last)
generate_plot_file(fig, pair, ticker_interval, is_last)
logger.info('End of ploting process %s plots generated', pair_counter)

34
scripts/plot_profit.py
View File

@ -12,26 +12,24 @@ Optional Cli parameters
--timerange: specify what timerange of data to use
--export-filename: Specify where the backtest export is located.
"""
import json
import logging
import sys
import json
from argparse import Namespace
from pathlib import Path
from typing import List, Optional
import numpy as np
import numpy as np
import plotly.graph_objs as go
from plotly import tools
from plotly.offline import plot
import plotly.graph_objs as go
from freqtrade.arguments import Arguments
from freqtrade.configuration import Configuration
from freqtrade import constants
from freqtrade.data import history
from freqtrade.misc import common_datearray, timeframe_to_seconds
from freqtrade.resolvers import StrategyResolver
from freqtrade.state import RunMode
import freqtrade.misc as misc
logger = logging.getLogger(__name__)
@ -39,7 +37,7 @@ logger = logging.getLogger(__name__)
# data:: [ pair, profit-%, enter, exit, time, duration]
# data:: ["ETH/BTC", 0.0023975, "1515598200", "1515602100", "2018-01-10 07:30:00+00:00", 65]
def make_profit_array(data: List, px: int, min_date: int,
interval: int,
interval: str,
filter_pairs: Optional[List] = None) -> np.ndarray:
pg = np.zeros(px)
filter_pairs = filter_pairs or []
@ -78,7 +76,7 @@ def plot_profit(args: Namespace) -> None:
in helping out to find a good algorithm.
"""
# We need to use the same pairs, same tick_interval
# We need to use the same pairs, same ticker_interval
# and same timeperiod as used in backtesting
# to match the tickerdata against the profits-results
timerange = Arguments.parse_timerange(args.timerange)
@ -114,7 +112,7 @@ def plot_profit(args: Namespace) -> None:
else:
filter_pairs = config['exchange']['pair_whitelist']
tick_interval = strategy.ticker_interval
ticker_interval = strategy.ticker_interval
pairs = config['exchange']['pair_whitelist']
if filter_pairs:
@ -122,9 +120,9 @@ def plot_profit(args: Namespace) -> None:
logger.info('Filter, keep pairs %s' % pairs)
tickers = history.load_data(
datadir=Path(config.get('datadir')),
datadir=Path(str(config.get('datadir'))),
pairs=pairs,
ticker_interval=tick_interval,
ticker_interval=ticker_interval,
refresh_pairs=False,
timerange=timerange
)
@ -133,10 +131,10 @@ def plot_profit(args: Namespace) -> None:
# NOTE: the dataframes are of unequal length,
# 'dates' is an merged date array of them all.
dates = misc.common_datearray(dataframes)
dates = common_datearray(dataframes)
min_date = int(min(dates).timestamp())
max_date = int(max(dates).timestamp())
num_iterations = define_index(min_date, max_date, tick_interval) + 1
num_iterations = define_index(min_date, max_date, ticker_interval) + 1
# Make an average close price of all the pairs that was involved.
# this could be useful to gauge the overall market trend
@ -156,7 +154,7 @@ def plot_profit(args: Namespace) -> None:
avgclose /= num
# make an profits-growth array
pg = make_profit_array(data, num_iterations, min_date, tick_interval, filter_pairs)
pg = make_profit_array(data, num_iterations, min_date, ticker_interval, filter_pairs)
#
# Plot the pairs average close prices, and total profit growth
@ -180,7 +178,7 @@ def plot_profit(args: Namespace) -> None:
fig.append_trace(profit, 2, 1)
for pair in pairs:
pg = make_profit_array(data, num_iterations, min_date, tick_interval, pair)
pg = make_profit_array(data, num_iterations, min_date, ticker_interval, [pair])
pair_profit = go.Scattergl(
x=dates,
y=pg,
@ -191,12 +189,12 @@ def plot_profit(args: Namespace) -> None:
plot(fig, filename=str(Path('user_data').joinpath('freqtrade-profit-plot.html')))
def define_index(min_date: int, max_date: int, interval: str) -> int:
def define_index(min_date: int, max_date: int, ticker_interval: str) -> int:
"""
Return the index of a specific date
"""
interval_minutes = constants.TICKER_INTERVAL_MINUTES[interval]
return int((max_date - min_date) / (interval_minutes * 60))
interval_seconds = timeframe_to_seconds(ticker_interval)
return int((max_date - min_date) / interval_seconds)
def plot_parse_args(args: List[str]) -> Namespace:

2
setup.sh
View File

@ -235,7 +235,7 @@ function install() {
echo "-------------------------"
echo "Run the bot !"
echo "-------------------------"
echo "You can now use the bot by executing 'source .env/bin/activate; python freqtrade/main.py'."
echo "You can now use the bot by executing 'source .env/bin/activate; python freqtrade'."
}
function plot() {