Merge branch 'develop' into volumeList_enhanced_filter

This commit is contained in:
Matthias 2019-11-09 15:34:47 +01:00
commit 748fe94603
52 changed files with 958 additions and 672 deletions

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@ -32,14 +32,15 @@ jobs:
name: backtest
- script:
- cp config.json.example config.json
- freqtrade --datadir tests/testdata hyperopt -e 5
- freqtrade --datadir tests/testdata --strategy SampleStrategy hyperopt --customhyperopt SampleHyperOpts -e 5
name: hyperopt
- script: flake8
name: flake8
- script:
# Test Documentation boxes -
# !!! <TYPE>: is not allowed!
- grep -Er '^!{3}\s\S+:' docs/*; test $? -ne 0
# !!! <TYPE> "title" - Title needs to be quoted!
- grep -Er '^!{3}\s\S+:|^!{3}\s\S+\s[^"]' docs/*; test $? -ne 0
name: doc syntax
- script: mypy freqtrade scripts
name: mypy

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@ -214,6 +214,11 @@ If this is configured, the following 4 values (`buy`, `sell`, `stoploss` and
`emergencysell` is an optional value, which defaults to `market` and is used when creating stoploss on exchange orders fails.
The below is the default which is used if this is not configured in either strategy or configuration file.
Since `stoploss_on_exchange` uses limit orders, the exchange needs 2 prices, the stoploss_price and the Limit price.
`stoploss` defines the stop-price - and limit should be slightly below this. This defaults to 0.99 / 1%.
Calculation example: we bought the asset at 100$.
Stop-price is 95$, then limit would be `95 * 0.99 = 94.05$` - so the stoploss will happen between 95$ and 94.05$.
Syntax for Strategy:
```python
@ -223,7 +228,8 @@ order_types = {
"emergencysell": "market",
"stoploss": "market",
"stoploss_on_exchange": False,
"stoploss_on_exchange_interval": 60
"stoploss_on_exchange_interval": 60,
"stoploss_on_exchange_limit_ratio": 0.99,
}
```
@ -253,7 +259,7 @@ Configuration:
!!! Note
If `stoploss_on_exchange` is enabled and the stoploss is cancelled manually on the exchange, then the bot will create a new order.
!!! Warning stoploss_on_exchange failures
!!! Warning "Warning: stoploss_on_exchange failures"
If stoploss on exchange creation fails for some reason, then an "emergency sell" is initiated. By default, this will sell the asset using a market order. The order-type for the emergency-sell can be changed by setting the `emergencysell` value in the `order_types` dictionary - however this is not advised.
### Understand order_time_in_force

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@ -8,7 +8,7 @@ If no additional parameter is specified, freqtrade will download data for `"1m"`
Exchange and pairs will come from `config.json` (if specified using `-c/--config`).
Otherwise `--exchange` becomes mandatory.
!!! Tip Updating existing data
!!! Tip "Tip: Updating existing data"
If you already have backtesting data available in your data-directory and would like to refresh this data up to today, use `--days xx` with a number slightly higher than the missing number of days. Freqtrade will keep the available data and only download the missing data.
Be carefull though: If the number is too small (which would result in a few missing days), the whole dataset will be removed and only xx days will be downloaded.

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@ -210,14 +210,15 @@ This part of the documentation is aimed at maintainers, and shows how to create
### Create release branch
``` bash
# make sure you're in develop branch
git checkout develop
First, pick a commit that's about one week old (to not include latest additions to releases).
``` bash
# create new branch
git checkout -b new_release
git checkout -b new_release <commitid>
```
Determine if crucial bugfixes have been made between this commit and the current state, and eventually cherry-pick these.
* Edit `freqtrade/__init__.py` and add the version matching the current date (for example `2019.7` for July 2019). Minor versions can be `2019.7-1` should we need to do a second release that month.
* Commit this part
* push that branch to the remote and create a PR against the master branch
@ -225,23 +226,18 @@ git checkout -b new_release
### Create changelog from git commits
!!! Note
Make sure that both master and develop are up-todate!.
Make sure that the master branch is uptodate!
``` bash
# Needs to be done before merging / pulling that branch.
git log --oneline --no-decorate --no-merges master..develop
git log --oneline --no-decorate --no-merges master..new_release
```
### Create github release / tag
Once the PR against master is merged (best right after merging):
* Use the button "Draft a new release" in the Github UI (subsection releases)
* Use the button "Draft a new release" in the Github UI (subsection releases).
* Use the version-number specified as tag.
* Use "master" as reference (this step comes after the above PR is merged).
* Use the above changelog as release comment (as codeblock)
### After-release
* Update version in develop by postfixing that with `-dev` (`2019.6 -> 2019.6-dev`).
* Create a PR against develop to update that branch.
* Use the above changelog as release comment (as codeblock).

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@ -26,7 +26,7 @@ To update the image, simply run the above commands again and restart your runnin
Should you require additional libraries, please [build the image yourself](#build-your-own-docker-image).
!!! Note Docker image update frequency
!!! Note "Docker image update frequency"
The official docker images with tags `master`, `develop` and `latest` are automatically rebuild once a week to keep the base image uptodate.
In addition to that, every merge to `develop` will trigger a rebuild for `develop` and `latest`.
@ -170,6 +170,9 @@ docker run -d \
!!! Note
All available bot command line parameters can be added to the end of the `docker run` command.
!!! Note
You can define a [restart policy](https://docs.docker.com/config/containers/start-containers-automatically/) in docker. It can be useful in some cases to use the `--restart unless-stopped` flag (crash of freqtrade or reboot of your system).
### Monitor your Docker instance
You can use the following commands to monitor and manage your container:

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@ -55,6 +55,44 @@ If you have restricted pairs in your whitelist, you'll get a warning message in
If you're an "International" Customer on the Bittrex exchange, then this warning will probably not impact you.
If you're a US customer, the bot will fail to create orders for these pairs, and you should remove them from your Whitelist.
### How do I search the bot logs for something?
By default, the bot writes its log into stderr stream. This is implemented this way so that you can easily separate the bot's diagnostics messages from Backtesting, Edge and Hyperopt results, output from other various Freqtrade utility subcommands, as well as from the output of your custom `print()`'s you may have inserted into your strategy. So if you need to search the log messages with the grep utility, you need to redirect stderr to stdout and disregard stdout.
* In unix shells, this normally can be done as simple as:
```shell
$ freqtrade --some-options 2>&1 >/dev/null | grep 'something'
```
(note, `2>&1` and `>/dev/null` should be written in this order)
* Bash interpreter also supports so called process substitution syntax, you can grep the log for a string with it as:
```shell
$ freqtrade --some-options 2> >(grep 'something') >/dev/null
```
or
```shell
$ freqtrade --some-options 2> >(grep -v 'something' 1>&2)
```
* You can also write the copy of Freqtrade log messages to a file with the `--logfile` option:
```shell
$ freqtrade --logfile /path/to/mylogfile.log --some-options
```
and then grep it as:
```shell
$ cat /path/to/mylogfile.log | grep 'something'
```
or even on the fly, as the bot works and the logfile grows:
```shell
$ tail -f /path/to/mylogfile.log | grep 'something'
```
from a separate terminal window.
On Windows, the `--logfilename` option is also supported by Freqtrade and you can use the `findstr` command to search the log for the string of interest:
```
> type \path\to\mylogfile.log | findstr "something"
```
## Hyperopt module
### How many epoch do I need to get a good Hyperopt result?

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@ -23,17 +23,23 @@ Configuring hyperopt is similar to writing your own strategy, and many tasks wil
Depending on the space you want to optimize, only some of the below are required:
* fill `populate_indicators` - probably a copy from your strategy
* fill `buy_strategy_generator` - for buy signal optimization
* fill `indicator_space` - for buy signal optimzation
* fill `sell_strategy_generator` - for sell signal optimization
* fill `sell_indicator_space` - for sell signal optimzation
Optional, but recommended:
!!! Note
`populate_indicators` needs to create all indicators any of thee spaces may use, otherwise hyperopt will not work.
Optional - can also be loaded from a strategy:
* copy `populate_indicators` from your strategy - otherwise default-strategy will be used
* copy `populate_buy_trend` from your strategy - otherwise default-strategy will be used
* copy `populate_sell_trend` from your strategy - otherwise default-strategy will be used
!!! Note
Assuming the optional methods are not in your hyperopt file, please use `--strategy AweSomeStrategy` which contains these methods so hyperopt can use these methods instead.
Rarely you may also need to override:
* `roi_space` - for custom ROI optimization (if you need the ranges for the ROI parameters in the optimization hyperspace that differ from default)
@ -156,7 +162,7 @@ that minimizes the value of the [loss function](#loss-functions).
The above setup expects to find ADX, RSI and Bollinger Bands in the populated indicators.
When you want to test an indicator that isn't used by the bot currently, remember to
add it to the `populate_indicators()` method in `hyperopt.py`.
add it to the `populate_indicators()` method in your custom hyperopt file.
## Loss-functions
@ -270,6 +276,14 @@ For example, to use one month of data, pass the following parameter to the hyper
freqtrade hyperopt --timerange 20180401-20180501
```
### Running Hyperopt using methods from a strategy
Hyperopt can reuse `populate_indicators`, `populate_buy_trend`, `populate_sell_trend` from your strategy, assuming these methods are **not** in your custom hyperopt file, and a strategy is provided.
```bash
freqtrade --strategy SampleStrategy hyperopt --customhyperopt SampleHyperopt
```
### Running Hyperopt with Smaller Search Space
Use the `--spaces` argument to limit the search space used by hyperopt.
@ -341,8 +355,7 @@ So for example you had `rsi-value: 29.0` so we would look at `rsi`-block, that t
(dataframe['rsi'] < 29.0)
```
Translating your whole hyperopt result as the new buy-signal
would then look like:
Translating your whole hyperopt result as the new buy-signal would then look like:
```python
def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:

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@ -34,10 +34,12 @@ Freqtrade provides a Linux/MacOS script to install all dependencies and help you
```bash
git clone git@github.com:freqtrade/freqtrade.git
cd freqtrade
git checkout develop
./setup.sh --install
```
!!! Note "Version considerations"
When cloning the repository the default working branch is name `develop`. This branch contains the last features (can be considered as relatively stable thanks to automated tests). The `master` branch contains the code of the last release (done once per month with a one week old snapshot of the `develop` branch to prevent packaging bugs so potentially more stable).
!!! Note
Windows installation is explained [here](#windows).
@ -95,29 +97,26 @@ sudo apt-get update
sudo apt-get install build-essential git
```
#### Raspberry Pi / Raspbian
### Raspberry Pi / Raspbian
Before installing FreqTrade on a Raspberry Pi running the official Raspbian Image, make sure you have at least Python 3.6 installed. The default image only provides Python 3.5. Probably the easiest way to get a recent version of python is [miniconda](https://repo.continuum.io/miniconda/).
The following assumes the latest [Raspbian Buster lite image](https://www.raspberrypi.org/downloads/raspbian/) from at least September 2019.
This image comes with python3.7 preinstalled, making it easy to get freqtrade up and running.
The following assumes that miniconda3 is installed and available in your environment. Since the last miniconda3 installation file uses 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` and `pandas` takes a long time.
Additional package to install on your Raspbian, `libffi-dev` required by cryptography (from python-telegram-bot).
Tested using a Raspberry Pi 3 with the Raspbian Buster lite image, all updates applied.
``` bash
conda config --add channels rpi
conda install python=3.6
conda create -n freqtrade python=3.6
conda activate freqtrade
conda install pandas numpy
sudo apt-get install python3-venv libatlas-base-dev
git clone https://github.com/freqtrade/freqtrade.git
cd freqtrade
sudo apt install libffi-dev
python3 -m pip install -r requirements-common.txt
python3 -m pip install -e .
bash setup.sh -i
```
!!! Note "Installation duration"
Depending on your internet speed and the Raspberry Pi version, installation can take multiple hours to complete.
!!! Note
This does not install hyperopt dependencies. To install these, please use `python3 -m pip install -e .[hyperopt]`.
The above does not install hyperopt dependencies. To install these, please use `python3 -m pip install -e .[hyperopt]`.
We do not advise to run hyperopt on a Raspberry Pi, since this is a very resource-heavy operation, which should be done on powerful machine.
### Common

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@ -79,7 +79,7 @@ The `-p/--pairs` argument can be used to specify pairs you would like to plot.
Specify custom indicators.
Use `--indicators1` for the main plot and `--indicators2` for the subplot below (if values are in a different range than prices).
!!! tip
!!! Tip
You will almost certainly want to specify a custom strategy! This can be done by adding `-s Classname` / `--strategy ClassName` to the command.
``` bash

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@ -16,10 +16,10 @@ Sample configuration:
},
```
!!! Danger Security warning
!!! Danger "Security warning"
By default, the configuration listens on localhost only (so it's not reachable from other systems). We strongly recommend to not expose this API to the internet and choose a strong, unique password, since others will potentially be able to control your bot.
!!! Danger Password selection
!!! Danger "Password selection"
Please make sure to select a very strong, unique password to protect your bot from unauthorized access.
You can then access the API by going to `http://127.0.0.1:8080/api/v1/version` to check if the API is running correctly.

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@ -51,13 +51,13 @@ freqtrade --strategy AwesomeStrategy
**For the following section we will use the [user_data/strategies/sample_strategy.py](https://github.com/freqtrade/freqtrade/blob/develop/user_data/strategies/sample_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
avoid index referencing (`df.iloc[-1]`), but instead use `df.shift()` to get to the previous candle.
!!! Warning Using future data
!!! Warning "Warning: Using future data"
Since backtesting passes the full time interval to the `populate_*()` methods, the strategy author
needs to take care to avoid having the strategy utilize data from the future.
Some common patterns for this are listed in the [Common Mistakes](#common-mistakes-when-developing-strategies) section of this document.
@ -330,12 +330,12 @@ if self.dp:
ticker_interval=inf_timeframe)
```
!!! Warning Warning about backtesting
!!! Warning "Warning about backtesting"
Be carefull when using dataprovider in backtesting. `historic_ohlcv()` (and `get_pair_dataframe()`
for the backtesting runmode) 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
!!! Warning "Warning in hyperopt"
This option cannot currently be used during hyperopt.
#### Orderbook
@ -405,6 +405,52 @@ if self.wallets:
- `get_used(asset)` - currently tied up balance (open orders)
- `get_total(asset)` - total available balance - sum of the 2 above
### Additional data (Trades)
A history of Trades can be retrieved in the strategy by querying the database.
At the top of the file, import Trade.
```python
from freqtrade.persistence import Trade
```
The following example queries for the current pair and trades from today, however other filters can easily be added.
``` python
if self.config['runmode'] in ('live', 'dry_run'):
trades = Trade.get_trades([Trade.pair == metadata['pair'],
Trade.open_date > datetime.utcnow() - timedelta(days=1),
Trade.is_open == False,
]).order_by(Trade.close_date).all()
# Summarize profit for this pair.
curdayprofit = sum(trade.close_profit for trade in trades)
```
Get amount of stake_currency currently invested in Trades:
``` python
if self.config['runmode'] in ('live', 'dry_run'):
total_stakes = Trade.total_open_trades_stakes()
```
Retrieve performance per pair.
Returns a List of dicts per pair.
``` python
if self.config['runmode'] in ('live', 'dry_run'):
performance = Trade.get_overall_performance()
```
Sample return value: ETH/BTC had 5 trades, with a total profit of 1.5% (ratio of 0.015).
``` json
{'pair': "ETH/BTC", 'profit': 0.015, 'count': 5}
```
!!! Warning
Trade history is not available during backtesting or hyperopt.
### Print created dataframe
To inspect the created dataframe, you can issue a print-statement in either `populate_buy_trend()` or `populate_sell_trend()`.

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@ -107,6 +107,22 @@ trades = load_trades_from_db("sqlite:///tradesv3.sqlite")
trades.groupby("pair")["sell_reason"].value_counts()
```
## Analyze the loaded trades for trade parallelism
This can be useful to find the best `max_open_trades` parameter, when used with backtesting in conjunction with `--disable-max-market-positions`.
`analyze_trade_parallelism()` returns a timeseries dataframe with an "open_trades" column, specifying the number of open trades for each candle.
```python
from freqtrade.data.btanalysis import analyze_trade_parallelism
# Analyze the above
parallel_trades = analyze_trade_parallelism(trades, '5m')
parallel_trades.plot()
```
## Plot results
Freqtrade offers interactive plotting capabilities based on plotly.

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@ -93,7 +93,7 @@ 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
!!! 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

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@ -1,4 +1,5 @@
from freqtrade.configuration.arguments import Arguments # noqa: F401
from freqtrade.configuration.check_exchange import check_exchange, remove_credentials # noqa: F401
from freqtrade.configuration.timerange import TimeRange # noqa: F401
from freqtrade.configuration.configuration import Configuration # noqa: F401
from freqtrade.configuration.config_validation import validate_config_consistency # noqa: F401

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@ -10,6 +10,19 @@ from freqtrade.state import RunMode
logger = logging.getLogger(__name__)
def remove_credentials(config: Dict[str, Any]):
"""
Removes exchange keys from the configuration and specifies dry-run
Used for backtesting / hyperopt / edge and utils.
Modifies the input dict!
"""
config['exchange']['key'] = ''
config['exchange']['secret'] = ''
config['exchange']['password'] = ''
config['exchange']['uid'] = ''
config['dry_run'] = True
def check_exchange(config: Dict[str, Any], check_for_bad: bool = True) -> bool:
"""
Check if the exchange name in the config file is supported by Freqtrade
@ -21,7 +34,8 @@ def check_exchange(config: Dict[str, Any], check_for_bad: bool = True) -> bool:
and thus is not known for the Freqtrade at all.
"""
if config['runmode'] in [RunMode.PLOT] and not config.get('exchange', {}).get('name'):
if (config['runmode'] in [RunMode.PLOT, RunMode.UTIL_NO_EXCHANGE, RunMode.OTHER]
and not config.get('exchange', {}).get('name')):
# Skip checking exchange in plot mode, since it requires no exchange
return True
logger.info("Checking exchange...")

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@ -118,7 +118,8 @@ def _validate_whitelist(conf: Dict[str, Any]) -> None:
"""
Dynamic whitelist does not require pair_whitelist to be set - however StaticWhitelist does.
"""
if conf.get('runmode', RunMode.OTHER) in [RunMode.OTHER, RunMode.PLOT]:
if conf.get('runmode', RunMode.OTHER) in [RunMode.OTHER, RunMode.PLOT,
RunMode.UTIL_NO_EXCHANGE, RunMode.UTIL_EXCHANGE]:
return
for pl in conf.get('pairlists', [{'method': 'StaticPairList'}]):

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@ -17,7 +17,7 @@ from freqtrade.configuration.directory_operations import (create_datadir,
from freqtrade.configuration.load_config import load_config_file
from freqtrade.loggers import setup_logging
from freqtrade.misc import deep_merge_dicts, json_load
from freqtrade.state import RunMode
from freqtrade.state import RunMode, TRADING_MODES, NON_UTIL_MODES
logger = logging.getLogger(__name__)
@ -101,14 +101,16 @@ class Configuration:
# Keep a copy of the original configuration file
config['original_config'] = deepcopy(config)
self._process_runmode(config)
self._process_common_options(config)
self._process_trading_options(config)
self._process_optimize_options(config)
self._process_plot_options(config)
self._process_runmode(config)
# Check if the exchange set by the user is supported
check_exchange(config, config.get('experimental', {}).get('block_bad_exchanges', True))
@ -133,6 +135,22 @@ class Configuration:
setup_logging(config)
def _process_trading_options(self, config: Dict[str, Any]) -> None:
if config['runmode'] not in TRADING_MODES:
return
if config.get('dry_run', False):
logger.info('Dry run is enabled')
if config.get('db_url') in [None, constants.DEFAULT_DB_PROD_URL]:
# Default to in-memory db for dry_run if not specified
config['db_url'] = constants.DEFAULT_DB_DRYRUN_URL
else:
if not config.get('db_url', None):
config['db_url'] = constants.DEFAULT_DB_PROD_URL
logger.info('Dry run is disabled')
logger.info(f'Using DB: "{config["db_url"]}"')
def _process_common_options(self, config: Dict[str, Any]) -> None:
self._process_logging_options(config)
@ -149,25 +167,9 @@ class Configuration:
config.update({'db_url': self.args["db_url"]})
logger.info('Parameter --db-url detected ...')
if config.get('dry_run', False):
logger.info('Dry run is enabled')
if config.get('db_url') in [None, constants.DEFAULT_DB_PROD_URL]:
# Default to in-memory db for dry_run if not specified
config['db_url'] = constants.DEFAULT_DB_DRYRUN_URL
else:
if not config.get('db_url', None):
config['db_url'] = constants.DEFAULT_DB_PROD_URL
logger.info('Dry run is disabled')
logger.info(f'Using DB: "{config["db_url"]}"')
if config.get('forcebuy_enable', False):
logger.warning('`forcebuy` RPC message enabled.')
# Setting max_open_trades to infinite if -1
if config.get('max_open_trades') == -1:
config['max_open_trades'] = float('inf')
# Support for sd_notify
if 'sd_notify' in self.args and self.args["sd_notify"]:
config['internals'].update({'sd_notify': True})
@ -215,6 +217,10 @@ class Configuration:
self._args_to_config(config, argname='position_stacking',
logstring='Parameter --enable-position-stacking detected ...')
# Setting max_open_trades to infinite if -1
if config.get('max_open_trades') == -1:
config['max_open_trades'] = float('inf')
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 ...')
@ -223,7 +229,7 @@ class Configuration:
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:
elif config['runmode'] in NON_UTIL_MODES:
logger.info('Using max_open_trades: %s ...', config.get('max_open_trades'))
self._args_to_config(config, argname='stake_amount',

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@ -7,7 +7,7 @@ from typing import Dict
import numpy as np
import pandas as pd
import pytz
from datetime import timezone
from freqtrade import persistence
from freqtrade.misc import json_load
@ -52,16 +52,18 @@ def load_backtest_data(filename) -> pd.DataFrame:
return df
def evaluate_result_multi(results: pd.DataFrame, freq: str, max_open_trades: int) -> pd.DataFrame:
def analyze_trade_parallelism(results: pd.DataFrame, timeframe: str) -> pd.DataFrame:
"""
Find overlapping trades by expanding each trade once per period it was open
and then counting overlaps
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
:param timeframe: Timeframe used for backtest
:return: dataframe with open-counts per time-period in timeframe
"""
dates = [pd.Series(pd.date_range(row[1].open_time, row[1].close_time, freq=freq))
from freqtrade.exchange import timeframe_to_minutes
timeframe_min = timeframe_to_minutes(timeframe)
dates = [pd.Series(pd.date_range(row[1].open_time, row[1].close_time,
freq=f"{timeframe_min}min"))
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')
@ -69,8 +71,23 @@ def evaluate_result_multi(results: pd.DataFrame, freq: str, max_open_trades: int
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]
df_final = df2.resample(f"{timeframe_min}min")[['pair']].count()
df_final = df_final.rename({'pair': 'open_trades'}, axis=1)
return df_final
def evaluate_result_multi(results: pd.DataFrame, timeframe: 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 timeframe: 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
"""
df_final = analyze_trade_parallelism(results, timeframe)
return df_final[df_final['open_trades'] > max_open_trades]
def load_trades_from_db(db_url: str) -> pd.DataFrame:
@ -89,8 +106,8 @@ def load_trades_from_db(db_url: str) -> pd.DataFrame:
"stop_loss", "initial_stop_loss", "strategy", "ticker_interval"]
trades = pd.DataFrame([(t.pair,
t.open_date.replace(tzinfo=pytz.UTC),
t.close_date.replace(tzinfo=pytz.UTC) if t.close_date else None,
t.open_date.replace(tzinfo=timezone.utc),
t.close_date.replace(tzinfo=timezone.utc) if t.close_date else None,
t.calc_profit(), t.calc_profit_percent(),
t.open_rate, t.close_rate, t.amount,
(round((t.close_date.timestamp() - t.open_date.timestamp()) / 60, 2)
@ -106,7 +123,7 @@ def load_trades_from_db(db_url: str) -> pd.DataFrame:
t.stop_loss, t.initial_stop_loss,
t.strategy, t.ticker_interval
)
for t in Trade.query.all()],
for t in Trade.get_trades().all()],
columns=columns)
return trades

View File

@ -9,12 +9,11 @@ Includes:
import logging
import operator
from copy import deepcopy
from datetime import datetime
from datetime import datetime, timezone
from pathlib import Path
from typing import Any, Dict, List, Optional, Tuple
import arrow
import pytz
from pandas import DataFrame
from freqtrade import OperationalException, misc
@ -56,10 +55,10 @@ def trim_dataframe(df: DataFrame, timerange: TimeRange) -> DataFrame:
Trim dataframe based on given timerange
"""
if timerange.starttype == 'date':
start = datetime.fromtimestamp(timerange.startts, tz=pytz.utc)
start = datetime.fromtimestamp(timerange.startts, tz=timezone.utc)
df = df.loc[df['date'] >= start, :]
if timerange.stoptype == 'date':
stop = datetime.fromtimestamp(timerange.stopts, tz=pytz.utc)
stop = datetime.fromtimestamp(timerange.stopts, tz=timezone.utc)
df = df.loc[df['date'] <= stop, :]
return df
@ -148,7 +147,6 @@ def load_pair_history(pair: str,
timerange_startup = deepcopy(timerange)
if startup_candles > 0 and timerange_startup:
logger.info('Using indicator startup period: %s ...', startup_candles)
timerange_startup.subtract_start(timeframe_to_seconds(ticker_interval) * startup_candles)
# The user forced the refresh of pairs
@ -204,6 +202,8 @@ def load_data(datadir: Path,
exchange and refresh_pairs are then not needed here nor in load_pair_history.
"""
result: Dict[str, DataFrame] = {}
if startup_candles > 0 and timerange:
logger.info(f'Using indicator startup period: {startup_candles} ...')
for pair in pairs:
hist = load_pair_history(pair=pair, ticker_interval=ticker_interval,

View File

@ -1,4 +1,5 @@
from freqtrade.exchange.exchange import Exchange, MAP_EXCHANGE_CHILDCLASS # noqa: F401
from freqtrade.exchange.common import MAP_EXCHANGE_CHILDCLASS # noqa: F401
from freqtrade.exchange.exchange import Exchange # noqa: F401
from freqtrade.exchange.exchange import (get_exchange_bad_reason, # noqa: F401
is_exchange_bad,
is_exchange_known_ccxt,

View File

@ -0,0 +1,124 @@
import logging
from freqtrade import DependencyException, TemporaryError
logger = logging.getLogger(__name__)
API_RETRY_COUNT = 4
BAD_EXCHANGES = {
"bitmex": "Various reasons.",
"bitstamp": "Does not provide history. "
"Details in https://github.com/freqtrade/freqtrade/issues/1983",
"hitbtc": "This API cannot be used with Freqtrade. "
"Use `hitbtc2` exchange id to access this exchange.",
**dict.fromkeys([
'adara',
'anxpro',
'bigone',
'coinbase',
'coinexchange',
'coinmarketcap',
'lykke',
'xbtce',
], "Does not provide timeframes. ccxt fetchOHLCV: False"),
**dict.fromkeys([
'bcex',
'bit2c',
'bitbay',
'bitflyer',
'bitforex',
'bithumb',
'bitso',
'bitstamp1',
'bl3p',
'braziliex',
'btcbox',
'btcchina',
'btctradeim',
'btctradeua',
'bxinth',
'chilebit',
'coincheck',
'coinegg',
'coinfalcon',
'coinfloor',
'coingi',
'coinmate',
'coinone',
'coinspot',
'coolcoin',
'crypton',
'deribit',
'exmo',
'exx',
'flowbtc',
'foxbit',
'fybse',
# 'hitbtc',
'ice3x',
'independentreserve',
'indodax',
'itbit',
'lakebtc',
'latoken',
'liquid',
'livecoin',
'luno',
'mixcoins',
'negociecoins',
'nova',
'paymium',
'southxchange',
'stronghold',
'surbitcoin',
'therock',
'tidex',
'vaultoro',
'vbtc',
'virwox',
'yobit',
'zaif',
], "Does not provide timeframes. ccxt fetchOHLCV: emulated"),
}
MAP_EXCHANGE_CHILDCLASS = {
'binanceus': 'binance',
'binanceje': 'binance',
}
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

View File

@ -14,137 +14,18 @@ from typing import Any, Dict, List, Optional, Tuple
import arrow
import ccxt
import ccxt.async_support as ccxt_async
from ccxt.base.decimal_to_precision import ROUND_UP, ROUND_DOWN
from ccxt.base.decimal_to_precision import ROUND_DOWN, ROUND_UP
from pandas import DataFrame
from freqtrade import (DependencyException, InvalidOrderException,
OperationalException, TemporaryError, constants)
from freqtrade.data.converter import parse_ticker_dataframe
from freqtrade.exchange.common import BAD_EXCHANGES, retrier, retrier_async
from freqtrade.misc import deep_merge_dicts
logger = logging.getLogger(__name__)
API_RETRY_COUNT = 4
BAD_EXCHANGES = {
"bitmex": "Various reasons.",
"bitstamp": "Does not provide history. "
"Details in https://github.com/freqtrade/freqtrade/issues/1983",
"hitbtc": "This API cannot be used with Freqtrade. "
"Use `hitbtc2` exchange id to access this exchange.",
**dict.fromkeys([
'adara',
'anxpro',
'bigone',
'coinbase',
'coinexchange',
'coinmarketcap',
'lykke',
'xbtce',
], "Does not provide timeframes. ccxt fetchOHLCV: False"),
**dict.fromkeys([
'bcex',
'bit2c',
'bitbay',
'bitflyer',
'bitforex',
'bithumb',
'bitso',
'bitstamp1',
'bl3p',
'braziliex',
'btcbox',
'btcchina',
'btctradeim',
'btctradeua',
'bxinth',
'chilebit',
'coincheck',
'coinegg',
'coinfalcon',
'coinfloor',
'coingi',
'coinmate',
'coinone',
'coinspot',
'coolcoin',
'crypton',
'deribit',
'exmo',
'exx',
'flowbtc',
'foxbit',
'fybse',
# 'hitbtc',
'ice3x',
'independentreserve',
'indodax',
'itbit',
'lakebtc',
'latoken',
'liquid',
'livecoin',
'luno',
'mixcoins',
'negociecoins',
'nova',
'paymium',
'southxchange',
'stronghold',
'surbitcoin',
'therock',
'tidex',
'vaultoro',
'vbtc',
'virwox',
'yobit',
'zaif',
], "Does not provide timeframes. ccxt fetchOHLCV: emulated"),
}
MAP_EXCHANGE_CHILDCLASS = {
'binanceus': 'binance',
'binanceje': 'binance',
}
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:
_config: Dict = {}
@ -994,6 +875,22 @@ class Exchange:
@retrier
def get_trades_for_order(self, order_id: str, pair: str, since: datetime) -> List:
"""
Fetch Orders using the "fetch_my_trades" endpoint and filter them by order-id.
The "since" argument passed in is coming from the database and is in UTC,
as timezone-native datetime object.
From the python documentation:
> Naive datetime instances are assumed to represent local time
Therefore, calling "since.timestamp()" will get the UTC timestamp, after applying the
transformation from local timezone to UTC.
This works for timezones UTC+ since then the result will contain trades from a few hours
instead of from the last 5 seconds, however fails for UTC- timezones,
since we're then asking for trades with a "since" argument in the future.
:param order_id order_id: Order-id as given when creating the order
:param pair: Pair the order is for
:param since: datetime object of the order creation time. Assumes object is in UTC.
"""
if self._config['dry_run']:
return []
if not self.exchange_has('fetchMyTrades'):
@ -1001,7 +898,8 @@ class Exchange:
try:
# Allow 5s offset to catch slight time offsets (discovered in #1185)
# since needs to be int in milliseconds
my_trades = self._api.fetch_my_trades(pair, int((since.timestamp() - 5) * 1000))
my_trades = self._api.fetch_my_trades(
pair, int((since.replace(tzinfo=timezone.utc).timestamp() - 5) * 1000))
matched_trades = [trade for trade in my_trades if trade['order'] == order_id]
return matched_trades

View File

@ -318,7 +318,6 @@ class FreqtradeBot:
(bidstrat_check_depth_of_market.get('bids_to_ask_delta', 0) > 0):
if self._check_depth_of_market_buy(_pair, bidstrat_check_depth_of_market):
buycount += self.execute_buy(_pair, stake_amount)
else:
continue
buycount += self.execute_buy(_pair, stake_amount)
@ -633,8 +632,8 @@ class FreqtradeBot:
Force-sells the pair (using EmergencySell reason) in case of Problems creating the order.
:return: True if the order succeeded, and False in case of problems.
"""
# Limit price threshold: As limit price should always be below price
LIMIT_PRICE_PCT = 0.99
# Limit price threshold: As limit price should always be below stop-price
LIMIT_PRICE_PCT = self.strategy.order_types.get('stoploss_on_exchange_limit_ratio', 0.99)
try:
stoploss_order = self.exchange.stoploss_limit(pair=trade.pair, amount=trade.amount,
@ -767,7 +766,7 @@ class FreqtradeBot:
buy_timeout_threshold = arrow.utcnow().shift(minutes=-buy_timeout).datetime
sell_timeout_threshold = arrow.utcnow().shift(minutes=-sell_timeout).datetime
for trade in Trade.query.filter(Trade.open_order_id.isnot(None)).all():
for trade in Trade.get_open_order_trades():
try:
# FIXME: Somehow the query above returns results
# where the open_order_id is in fact None.

View File

@ -33,8 +33,8 @@ def setup_logging(config: Dict[str, Any]) -> None:
# Log level
verbosity = config['verbosity']
# Log to stdout, not stderr
log_handlers: List[logging.Handler] = [logging.StreamHandler(sys.stdout)]
# Log to stderr
log_handlers: List[logging.Handler] = [logging.StreamHandler(sys.stderr)]
if config.get('logfile'):
log_handlers.append(RotatingFileHandler(config['logfile'],

View File

@ -10,9 +10,10 @@ from pathlib import Path
from typing import Any, Dict, List, NamedTuple, Optional
from pandas import DataFrame
from tabulate import tabulate
from freqtrade import OperationalException
from freqtrade.configuration import TimeRange
from freqtrade.configuration import TimeRange, remove_credentials
from freqtrade.data import history
from freqtrade.data.dataprovider import DataProvider
from freqtrade.exchange import timeframe_to_minutes, timeframe_to_seconds
@ -21,7 +22,6 @@ from freqtrade.persistence import Trade
from freqtrade.resolvers import ExchangeResolver, StrategyResolver
from freqtrade.state import RunMode
from freqtrade.strategy.interface import IStrategy, SellType
from tabulate import tabulate
logger = logging.getLogger(__name__)
@ -57,11 +57,7 @@ class Backtesting:
self.config = config
# Reset keys for backtesting
self.config['exchange']['key'] = ''
self.config['exchange']['secret'] = ''
self.config['exchange']['password'] = ''
self.config['exchange']['uid'] = ''
self.config['dry_run'] = True
remove_credentials(self.config)
self.strategylist: List[IStrategy] = []
self.exchange = ExchangeResolver(self.config['exchange']['name'], self.config).exchange
@ -245,7 +241,8 @@ class Backtesting:
ticker: Dict = {}
# Create ticker dict
for pair, pair_data in processed.items():
pair_data['buy'], pair_data['sell'] = 0, 0 # cleanup from previous run
pair_data.loc[:, 'buy'] = 0 # cleanup from previous run
pair_data.loc[:, 'sell'] = 0 # cleanup from previous run
ticker_data = self.strategy.advise_sell(
self.strategy.advise_buy(pair_data, {'pair': pair}), {'pair': pair})[headers].copy()

View File

@ -4,12 +4,13 @@
This module contains the edge backtesting interface
"""
import logging
from typing import Dict, Any
from tabulate import tabulate
from freqtrade import constants
from freqtrade.edge import Edge
from typing import Any, Dict
from freqtrade.configuration import TimeRange
from tabulate import tabulate
from freqtrade import constants
from freqtrade.configuration import TimeRange, remove_credentials
from freqtrade.edge import Edge
from freqtrade.exchange import Exchange
from freqtrade.resolvers import StrategyResolver
@ -29,12 +30,8 @@ class EdgeCli:
self.config = config
# Reset keys for edge
self.config['exchange']['key'] = ''
self.config['exchange']['secret'] = ''
self.config['exchange']['password'] = ''
self.config['exchange']['uid'] = ''
remove_credentials(self.config)
self.config['stake_amount'] = constants.UNLIMITED_STAKE_AMOUNT
self.config['dry_run'] = True
self.exchange = Exchange(self.config)
self.strategy = StrategyResolver(self.config).strategy

View File

@ -4,9 +4,9 @@
This module contains the hyperopt logic
"""
import locale
import logging
import sys
from collections import OrderedDict
from operator import itemgetter
from pathlib import Path
@ -14,10 +14,10 @@ from pprint import pprint
from typing import Any, Dict, List, Optional
import rapidjson
from colorama import init as colorama_init
from colorama import Fore, Style
from joblib import Parallel, delayed, dump, load, wrap_non_picklable_objects, cpu_count
from colorama import init as colorama_init
from joblib import (Parallel, cpu_count, delayed, dump, load,
wrap_non_picklable_objects)
from pandas import DataFrame
from skopt import Optimizer
from skopt.space import Dimension
@ -28,8 +28,8 @@ from freqtrade.optimize.backtesting import Backtesting
# Import IHyperOpt and IHyperOptLoss to allow unpickling classes from these modules
from freqtrade.optimize.hyperopt_interface import IHyperOpt # noqa: F4
from freqtrade.optimize.hyperopt_loss_interface import IHyperOptLoss # noqa: F4
from freqtrade.resolvers.hyperopt_resolver import HyperOptResolver, HyperOptLossResolver
from freqtrade.resolvers.hyperopt_resolver import (HyperOptLossResolver,
HyperOptResolver)
logger = logging.getLogger(__name__)
@ -216,7 +216,7 @@ class Hyperopt:
if print_all:
print(log_str)
else:
print('\n' + log_str)
print(f'\n{log_str}')
else:
print('.', end='')
sys.stdout.flush()
@ -335,7 +335,9 @@ class Hyperopt:
return (f'{trades:6d} trades. Avg profit {avg_profit: 5.2f}%. '
f'Total profit {total_profit: 11.8f} {stake_cur} '
f'({profit: 7.2f}Σ%). Avg duration {duration:5.1f} mins.')
f'({profit: 7.2f}\N{GREEK CAPITAL LETTER SIGMA}%). '
f'Avg duration {duration:5.1f} mins.'
).encode(locale.getpreferredencoding(), 'replace').decode('utf-8')
def get_optimizer(self, dimensions, cpu_count) -> Optimizer:
return Optimizer(

View File

@ -5,10 +5,9 @@ This module defines the interface to apply for hyperopts
import logging
import math
from abc import ABC, abstractmethod
from abc import ABC
from typing import Dict, Any, Callable, List
from pandas import DataFrame
from skopt.space import Dimension, Integer, Real
from freqtrade import OperationalException
@ -42,15 +41,6 @@ class IHyperOpt(ABC):
# Assign ticker_interval to be used in hyperopt
IHyperOpt.ticker_interval = str(config['ticker_interval'])
@staticmethod
@abstractmethod
def populate_indicators(dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Populate indicators that will be used in the Buy and Sell strategy.
:param dataframe: Raw data from the exchange and parsed by parse_ticker_dataframe().
:return: A Dataframe with all mandatory indicators for the strategies.
"""
@staticmethod
def buy_strategy_generator(params: Dict[str, Any]) -> Callable:
"""

View File

@ -8,17 +8,16 @@ from typing import Any, Dict, List, Optional
import arrow
from sqlalchemy import (Boolean, Column, DateTime, Float, Integer, String,
create_engine, inspect)
create_engine, desc, func, inspect)
from sqlalchemy.exc import NoSuchModuleError
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.orm import Query
from sqlalchemy.orm.scoping import scoped_session
from sqlalchemy.orm.session import sessionmaker
from sqlalchemy import func
from sqlalchemy.pool import StaticPool
from freqtrade import OperationalException
logger = logging.getLogger(__name__)
@ -52,9 +51,11 @@ def init(db_url: str, clean_open_orders: bool = False) -> None:
raise OperationalException(f"Given value for db_url: '{db_url}' "
f"is no valid database URL! (See {_SQL_DOCS_URL})")
session = scoped_session(sessionmaker(bind=engine, autoflush=True, autocommit=True))
Trade.session = session()
Trade.query = session.query_property()
# https://docs.sqlalchemy.org/en/13/orm/contextual.html#thread-local-scope
# Scoped sessions proxy requests to the appropriate thread-local session.
# We should use the scoped_session object - not a seperately initialized version
Trade.session = scoped_session(sessionmaker(bind=engine, autoflush=True, autocommit=True))
Trade.query = Trade.session.query_property()
_DECL_BASE.metadata.create_all(engine)
check_migrate(engine)
@ -393,6 +394,37 @@ class Trade(_DECL_BASE):
profit_percent = (close_trade_price / open_trade_price) - 1
return float(f"{profit_percent:.8f}")
@staticmethod
def get_trades(trade_filter=None) -> Query:
"""
Helper function to query Trades using filters.
:param trade_filter: Optional filter to apply to trades
Can be either a Filter object, or a List of filters
e.g. `(trade_filter=[Trade.id == trade_id, Trade.is_open.is_(True),])`
e.g. `(trade_filter=Trade.id == trade_id)`
:return: unsorted query object
"""
if trade_filter is not None:
if not isinstance(trade_filter, list):
trade_filter = [trade_filter]
return Trade.query.filter(*trade_filter)
else:
return Trade.query
@staticmethod
def get_open_trades() -> List[Any]:
"""
Query trades from persistence layer
"""
return Trade.get_trades(Trade.is_open.is_(True)).all()
@staticmethod
def get_open_order_trades():
"""
Returns all open trades
"""
return Trade.get_trades(Trade.open_order_id.isnot(None)).all()
@staticmethod
def total_open_trades_stakes() -> float:
"""
@ -405,11 +437,38 @@ class Trade(_DECL_BASE):
return total_open_stake_amount or 0
@staticmethod
def get_open_trades() -> List[Any]:
def get_overall_performance() -> List[Dict[str, Any]]:
"""
Query trades from persistence layer
Returns List of dicts containing all Trades, including profit and trade count
"""
return Trade.query.filter(Trade.is_open.is_(True)).all()
pair_rates = Trade.session.query(
Trade.pair,
func.sum(Trade.close_profit).label('profit_sum'),
func.count(Trade.pair).label('count')
).filter(Trade.is_open.is_(False))\
.group_by(Trade.pair) \
.order_by(desc('profit_sum')) \
.all()
return [
{
'pair': pair,
'profit': rate,
'count': count
}
for pair, rate, count in pair_rates
]
@staticmethod
def get_best_pair():
"""
Get best pair with closed trade.
"""
best_pair = Trade.session.query(
Trade.pair, func.sum(Trade.close_profit).label('profit_sum')
).filter(Trade.is_open.is_(False)) \
.group_by(Trade.pair) \
.order_by(desc('profit_sum')).first()
return best_pair
@staticmethod
def stoploss_reinitialization(desired_stoploss):

View File

@ -34,6 +34,9 @@ class HyperOptResolver(IResolver):
self.hyperopt = self._load_hyperopt(hyperopt_name, config,
extra_dir=config.get('hyperopt_path'))
if not hasattr(self.hyperopt, 'populate_indicators'):
logger.warning("Hyperopt class does not provide populate_indicators() method. "
"Using populate_indicators from the strategy.")
if not hasattr(self.hyperopt, 'populate_buy_trend'):
logger.warning("Hyperopt class does not provide populate_buy_trend() method. "
"Using populate_buy_trend from the strategy.")

View File

@ -9,7 +9,6 @@ from enum import Enum
from typing import Dict, Any, List, Optional
import arrow
import sqlalchemy as sql
from numpy import mean, NAN
from pandas import DataFrame
@ -154,12 +153,11 @@ class RPC:
for day in range(0, timescale):
profitday = today - timedelta(days=day)
trades = Trade.query \
.filter(Trade.is_open.is_(False)) \
.filter(Trade.close_date >= profitday)\
.filter(Trade.close_date < (profitday + timedelta(days=1)))\
.order_by(Trade.close_date)\
.all()
trades = Trade.get_trades(trade_filter=[
Trade.is_open.is_(False),
Trade.close_date >= profitday,
Trade.close_date < (profitday + timedelta(days=1))
]).order_by(Trade.close_date).all()
curdayprofit = sum(trade.calc_profit() for trade in trades)
profit_days[profitday] = {
'amount': f'{curdayprofit:.8f}',
@ -192,7 +190,7 @@ class RPC:
def _rpc_trade_statistics(
self, stake_currency: str, fiat_display_currency: str) -> Dict[str, Any]:
""" Returns cumulative profit statistics """
trades = Trade.query.order_by(Trade.id).all()
trades = Trade.get_trades().order_by(Trade.id).all()
profit_all_coin = []
profit_all_perc = []
@ -225,11 +223,7 @@ class RPC:
)
profit_all_perc.append(profit_percent)
best_pair = Trade.session.query(
Trade.pair, sql.func.sum(Trade.close_profit).label('profit_sum')
).filter(Trade.is_open.is_(False)) \
.group_by(Trade.pair) \
.order_by(sql.text('profit_sum DESC')).first()
best_pair = Trade.get_best_pair()
if not best_pair:
raise RPCException('no closed trade')
@ -389,11 +383,8 @@ class RPC:
return {'result': 'Created sell orders for all open trades.'}
# Query for trade
trade = Trade.query.filter(
sql.and_(
Trade.id == trade_id,
Trade.is_open.is_(True)
)
trade = Trade.get_trades(
trade_filter=[Trade.id == trade_id, Trade.is_open.is_(True), ]
).first()
if not trade:
logger.warning('forcesell: Invalid argument received')
@ -423,7 +414,7 @@ class RPC:
# check if valid pair
# check if pair already has an open pair
trade = Trade.query.filter(Trade.is_open.is_(True)).filter(Trade.pair.is_(pair)).first()
trade = Trade.get_trades([Trade.is_open.is_(True), Trade.pair.is_(pair)]).first()
if trade:
raise RPCException(f'position for {pair} already open - id: {trade.id}')
@ -432,28 +423,20 @@ class RPC:
# execute buy
if self._freqtrade.execute_buy(pair, stakeamount, price):
trade = Trade.query.filter(Trade.is_open.is_(True)).filter(Trade.pair.is_(pair)).first()
trade = Trade.get_trades([Trade.is_open.is_(True), Trade.pair.is_(pair)]).first()
return trade
else:
return None
def _rpc_performance(self) -> List[Dict]:
def _rpc_performance(self) -> List[Dict[str, Any]]:
"""
Handler for performance.
Shows a performance statistic from finished trades
"""
pair_rates = Trade.session.query(Trade.pair,
sql.func.sum(Trade.close_profit).label('profit_sum'),
sql.func.count(Trade.pair).label('count')) \
.filter(Trade.is_open.is_(False)) \
.group_by(Trade.pair) \
.order_by(sql.text('profit_sum DESC')) \
.all()
return [
{'pair': pair, 'profit': round(rate * 100, 2), 'count': count}
for pair, rate, count in pair_rates
]
pair_rates = Trade.get_overall_performance()
# Round and convert to %
[x.update({'profit': round(x['profit'] * 100, 2)}) for x in pair_rates]
return pair_rates
def _rpc_count(self) -> Dict[str, float]:
""" Returns the number of trades running """

View File

@ -25,5 +25,12 @@ class RunMode(Enum):
BACKTEST = "backtest"
EDGE = "edge"
HYPEROPT = "hyperopt"
UTIL_EXCHANGE = "util_exchange"
UTIL_NO_EXCHANGE = "util_no_exchange"
PLOT = "plot"
OTHER = "other" # Used for plotting scripts and test
OTHER = "other"
TRADING_MODES = [RunMode.LIVE, RunMode.DRY_RUN]
OPTIMIZE_MODES = [RunMode.BACKTEST, RunMode.EDGE, RunMode.HYPEROPT]
NON_UTIL_MODES = TRADING_MODES + OPTIMIZE_MODES

View File

@ -10,7 +10,7 @@ import rapidjson
from tabulate import tabulate
from freqtrade import OperationalException
from freqtrade.configuration import Configuration, TimeRange
from freqtrade.configuration import Configuration, TimeRange, remove_credentials
from freqtrade.configuration.directory_operations import create_userdata_dir
from freqtrade.data.history import (convert_trades_to_ohlcv,
refresh_backtest_ohlcv_data,
@ -33,10 +33,8 @@ def setup_utils_configuration(args: Dict[str, Any], method: RunMode) -> Dict[str
configuration = Configuration(args, method)
config = configuration.get_config()
config['exchange']['dry_run'] = True
# Ensure we do not use Exchange credentials
config['exchange']['key'] = ''
config['exchange']['secret'] = ''
remove_credentials(config)
return config
@ -74,7 +72,7 @@ def start_download_data(args: Dict[str, Any]) -> None:
"""
Download data (former download_backtest_data.py script)
"""
config = setup_utils_configuration(args, RunMode.OTHER)
config = setup_utils_configuration(args, RunMode.UTIL_EXCHANGE)
timerange = TimeRange()
if 'days' in config:
@ -123,7 +121,7 @@ def start_list_timeframes(args: Dict[str, Any]) -> None:
"""
Print ticker intervals (timeframes) available on Exchange
"""
config = setup_utils_configuration(args, RunMode.OTHER)
config = setup_utils_configuration(args, RunMode.UTIL_EXCHANGE)
# Do not use ticker_interval set in the config
config['ticker_interval'] = None
@ -144,7 +142,7 @@ def start_list_markets(args: Dict[str, Any], pairs_only: bool = False) -> None:
:param pairs_only: if True print only pairs, otherwise print all instruments (markets)
:return: None
"""
config = setup_utils_configuration(args, RunMode.OTHER)
config = setup_utils_configuration(args, RunMode.UTIL_EXCHANGE)
# Init exchange
exchange = ExchangeResolver(config['exchange']['name'], config, validate=False).exchange

View File

@ -1,9 +1,9 @@
# requirements without requirements installable via conda
# mainly used for Raspberry pi installs
ccxt==1.18.1346
ccxt==1.19.14
SQLAlchemy==1.3.10
python-telegram-bot==12.2.0
arrow==0.15.2
arrow==0.15.4
requests==2.22.0
urllib3==1.25.6
wrapt==1.11.2

View File

@ -4,7 +4,7 @@
-r requirements-hyperopt.txt
coveralls==1.8.2
flake8==3.7.8
flake8==3.7.9
flake8-type-annotations==0.1.0
flake8-tidy-imports==3.0.0
mypy==0.740

View File

@ -2,4 +2,4 @@
-r requirements-common.txt
numpy==1.17.3
pandas==0.25.2
pandas==0.25.3

View File

@ -10,7 +10,7 @@ from freqtrade.data.btanalysis import (BT_DATA_COLUMNS,
create_cum_profit,
extract_trades_of_period,
load_backtest_data, load_trades,
load_trades_from_db)
load_trades_from_db, analyze_trade_parallelism)
from freqtrade.data.history import load_data, load_pair_history
from tests.test_persistence import create_mock_trades
@ -32,7 +32,7 @@ def test_load_backtest_data(testdatadir):
@pytest.mark.usefixtures("init_persistence")
def test_load_trades_db(default_conf, fee, mocker):
def test_load_trades_from_db(default_conf, fee, mocker):
create_mock_trades(fee)
# remove init so it does not init again
@ -84,6 +84,17 @@ def test_extract_trades_of_period(testdatadir):
assert trades1.iloc[-1].close_time == Arrow(2017, 11, 14, 15, 25, 0).datetime
def test_analyze_trade_parallelism(default_conf, mocker, testdatadir):
filename = testdatadir / "backtest-result_test.json"
bt_data = load_backtest_data(filename)
res = analyze_trade_parallelism(bt_data, "5m")
assert isinstance(res, DataFrame)
assert 'open_trades' in res.columns
assert res['open_trades'].max() == 3
assert res['open_trades'].min() == 0
def test_load_trades(default_conf, mocker):
db_mock = mocker.patch("freqtrade.data.btanalysis.load_trades_from_db", MagicMock())
bt_mock = mocker.patch("freqtrade.data.btanalysis.load_backtest_data", MagicMock())

View File

@ -103,9 +103,7 @@ def test_load_data_startup_candles(mocker, caplog, default_conf, testdatadir) ->
datadir=testdatadir, timerange=timerange,
startup_candles=20,
)
assert log_has(
'Using indicator startup period: 20 ...', caplog
)
assert ltfmock.call_count == 1
assert ltfmock.call_args_list[0][1]['timerange'] != timerange
# startts is 20 minutes earlier
@ -354,8 +352,12 @@ def test_load_partial_missing(testdatadir, caplog) -> None:
start = arrow.get('2018-01-01T00:00:00')
end = arrow.get('2018-01-11T00:00:00')
tickerdata = history.load_data(testdatadir, '5m', ['UNITTEST/BTC'],
startup_candles=20,
timerange=TimeRange('date', 'date',
start.timestamp, end.timestamp))
assert log_has(
'Using indicator startup period: 20 ...', caplog
)
# timedifference in 5 minutes
td = ((end - start).total_seconds() // 60 // 5) + 1
assert td != len(tickerdata['UNITTEST/BTC'])

View File

@ -14,13 +14,13 @@ from pandas import DataFrame
from freqtrade import (DependencyException, InvalidOrderException,
OperationalException, TemporaryError)
from freqtrade.exchange import Binance, Exchange, Kraken
from freqtrade.exchange.exchange import (API_RETRY_COUNT, timeframe_to_minutes,
from freqtrade.exchange.common import API_RETRY_COUNT
from freqtrade.exchange.exchange import (market_is_active, symbol_is_pair,
timeframe_to_minutes,
timeframe_to_msecs,
timeframe_to_next_date,
timeframe_to_prev_date,
timeframe_to_seconds,
symbol_is_pair,
market_is_active)
timeframe_to_seconds)
from freqtrade.resolvers.exchange_resolver import ExchangeResolver
from tests.conftest import get_patched_exchange, log_has, log_has_re
@ -1586,8 +1586,9 @@ def test_name(default_conf, mocker, exchange_name):
@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, tzinfo=timezone.utc)
since = datetime(2018, 5, 5, 0, 0, 0)
default_conf["dry_run"] = False
mocker.patch('freqtrade.exchange.Exchange.exchange_has', return_value=True)
api_mock = MagicMock()
@ -1623,7 +1624,8 @@ def test_get_trades_for_order(default_conf, mocker, exchange_name):
assert api_mock.fetch_my_trades.call_args[0][0] == 'LTC/BTC'
# Same test twice, hardcoded number and doing the same calculation
assert api_mock.fetch_my_trades.call_args[0][1] == 1525478395000
assert api_mock.fetch_my_trades.call_args[0][1] == int(since.timestamp() - 5) * 1000
assert api_mock.fetch_my_trades.call_args[0][1] == int(since.replace(
tzinfo=timezone.utc).timestamp() - 5) * 1000
ccxt_exceptionhandlers(mocker, default_conf, api_mock, exchange_name,
'get_trades_for_order', 'fetch_my_trades',

View File

@ -3,7 +3,6 @@ import logging
from unittest.mock import MagicMock
import pytest
from pandas import DataFrame
from freqtrade.data.history import get_timeframe
from freqtrade.optimize.backtesting import Backtesting
@ -313,7 +312,7 @@ def test_backtest_results(default_conf, fee, mocker, caplog, data) -> None:
pair = "UNITTEST/BTC"
# Dummy data as we mock the analyze functions
data_processed = {pair: DataFrame()}
data_processed = {pair: frame.copy()}
min_date, max_date = get_timeframe({pair: frame})
results = backtesting.backtest(
{

View File

@ -714,9 +714,9 @@ def test_backtest_multi_pair(default_conf, fee, mocker, tres, pair, testdatadir)
results = backtesting.backtest(backtest_conf)
# Make sure we have parallel trades
assert len(evaluate_result_multi(results, '5min', 2)) > 0
assert len(evaluate_result_multi(results, '5m', 2)) > 0
# make sure we don't have trades with more than configured max_open_trades
assert len(evaluate_result_multi(results, '5min', 3)) == 0
assert len(evaluate_result_multi(results, '5m', 3)) == 0
backtest_conf = {
'stake_amount': default_conf['stake_amount'],
@ -727,7 +727,7 @@ def test_backtest_multi_pair(default_conf, fee, mocker, tres, pair, testdatadir)
'end_date': max_date,
}
results = backtesting.backtest(backtest_conf)
assert len(evaluate_result_multi(results, '5min', 1)) == 0
assert len(evaluate_result_multi(results, '5m', 1)) == 0
def test_backtest_record(default_conf, fee, mocker):

View File

@ -1,4 +1,5 @@
# pragma pylint: disable=missing-docstring,W0212,C0103
import locale
from datetime import datetime
from pathlib import Path
from unittest.mock import MagicMock, PropertyMock
@ -149,6 +150,7 @@ def test_hyperoptresolver(mocker, default_conf, caplog) -> None:
patched_configuration_load_config_file(mocker, default_conf)
hyperopt = DefaultHyperOpt
delattr(hyperopt, 'populate_indicators')
delattr(hyperopt, 'populate_buy_trend')
delattr(hyperopt, 'populate_sell_trend')
mocker.patch(
@ -156,8 +158,11 @@ def test_hyperoptresolver(mocker, default_conf, caplog) -> None:
MagicMock(return_value=hyperopt(default_conf))
)
x = HyperOptResolver(default_conf, ).hyperopt
assert not hasattr(x, 'populate_indicators')
assert not hasattr(x, 'populate_buy_trend')
assert not hasattr(x, 'populate_sell_trend')
assert log_has("Hyperopt class does not provide populate_indicators() method. "
"Using populate_indicators from the strategy.", caplog)
assert log_has("Hyperopt class does not provide populate_sell_trend() method. "
"Using populate_sell_trend from the strategy.", caplog)
assert log_has("Hyperopt class does not provide populate_buy_trend() method. "
@ -561,8 +566,9 @@ def test_generate_optimizer(mocker, default_conf) -> None:
}
response_expected = {
'loss': 1.9840569076926293,
'results_explanation': ' 1 trades. Avg profit 2.31%. Total profit 0.00023300 BTC '
'( 2.31Σ%). Avg duration 100.0 mins.',
'results_explanation': (' 1 trades. Avg profit 2.31%. Total profit 0.00023300 BTC '
'( 2.31\N{GREEK CAPITAL LETTER SIGMA}%). Avg duration 100.0 mins.'
).encode(locale.getpreferredencoding(), 'replace').decode('utf-8'),
'params': optimizer_param,
'total_profit': 0.00023300
}

View File

@ -10,12 +10,12 @@ import pytest
from jsonschema import Draft4Validator, ValidationError, validate
from freqtrade import OperationalException, constants
from freqtrade.configuration import (Arguments, Configuration,
from freqtrade.configuration import (Arguments, Configuration, check_exchange,
remove_credentials,
validate_config_consistency)
from freqtrade.configuration.check_exchange import check_exchange
from freqtrade.configuration.config_validation import validate_config_schema
from freqtrade.configuration.deprecated_settings import (check_conflicting_settings,
process_deprecated_setting,
from freqtrade.configuration.deprecated_settings import (
check_conflicting_settings, process_deprecated_setting,
process_temporary_deprecated_settings)
from freqtrade.configuration.directory_operations import (create_datadir,
create_userdata_dir)
@ -545,12 +545,24 @@ def test_check_exchange(default_conf, caplog) -> None:
# Test no exchange...
default_conf.get('exchange').update({'name': ''})
default_conf['runmode'] = RunMode.OTHER
default_conf['runmode'] = RunMode.UTIL_EXCHANGE
with pytest.raises(OperationalException,
match=r'This command requires a configured exchange.*'):
check_exchange(default_conf)
def test_remove_credentials(default_conf, caplog) -> None:
conf = deepcopy(default_conf)
conf['dry_run'] = False
remove_credentials(conf)
assert conf['dry_run'] is True
assert conf['exchange']['key'] == ''
assert conf['exchange']['secret'] == ''
assert conf['exchange']['password'] == ''
assert conf['exchange']['uid'] == ''
def test_cli_verbose_with_params(default_conf, mocker, caplog) -> None:
patched_configuration_load_config_file(mocker, default_conf)

View File

@ -14,7 +14,6 @@ import requests
from freqtrade import (DependencyException, InvalidOrderException,
OperationalException, TemporaryError, constants)
from freqtrade.constants import MATH_CLOSE_PREC
from freqtrade.data.dataprovider import DataProvider
from freqtrade.freqtradebot import FreqtradeBot
from freqtrade.persistence import Trade
from freqtrade.rpc import RPCMessageType
@ -49,16 +48,6 @@ def test_freqtradebot_state(mocker, default_conf, markets) -> None:
assert freqtrade.state is State.STOPPED
def test_worker_state(mocker, default_conf, markets) -> None:
mocker.patch('freqtrade.exchange.Exchange.markets', PropertyMock(return_value=markets))
worker = get_patched_worker(mocker, default_conf)
assert worker.state is State.RUNNING
default_conf.pop('initial_state')
worker = Worker(args=None, config=default_conf)
assert worker.state is State.STOPPED
def test_cleanup(mocker, default_conf, caplog) -> None:
mock_cleanup = MagicMock()
mocker.patch('freqtrade.persistence.cleanup', mock_cleanup)
@ -68,69 +57,6 @@ def test_cleanup(mocker, default_conf, caplog) -> None:
assert mock_cleanup.call_count == 1
def test_worker_running(mocker, default_conf, caplog) -> None:
mock_throttle = MagicMock()
mocker.patch('freqtrade.worker.Worker._throttle', mock_throttle)
mocker.patch('freqtrade.persistence.Trade.stoploss_reinitialization', MagicMock())
worker = get_patched_worker(mocker, default_conf)
state = worker._worker(old_state=None)
assert state is State.RUNNING
assert log_has('Changing state to: RUNNING', caplog)
assert mock_throttle.call_count == 1
# Check strategy is loaded, and received a dataprovider object
assert worker.freqtrade.strategy
assert worker.freqtrade.strategy.dp
assert isinstance(worker.freqtrade.strategy.dp, DataProvider)
def test_worker_stopped(mocker, default_conf, caplog) -> None:
mock_throttle = MagicMock()
mocker.patch('freqtrade.worker.Worker._throttle', mock_throttle)
mock_sleep = mocker.patch('time.sleep', return_value=None)
worker = get_patched_worker(mocker, default_conf)
worker.state = State.STOPPED
state = worker._worker(old_state=State.RUNNING)
assert state is State.STOPPED
assert log_has('Changing state to: STOPPED', caplog)
assert mock_throttle.call_count == 0
assert mock_sleep.call_count == 1
def test_throttle(mocker, default_conf, caplog) -> None:
def throttled_func():
return 42
caplog.set_level(logging.DEBUG)
worker = get_patched_worker(mocker, default_conf)
start = time.time()
result = worker._throttle(throttled_func, min_secs=0.1)
end = time.time()
assert result == 42
assert end - start > 0.1
assert log_has('Throttling throttled_func for 0.10 seconds', caplog)
result = worker._throttle(throttled_func, min_secs=-1)
assert result == 42
def test_throttle_with_assets(mocker, default_conf) -> None:
def throttled_func(nb_assets=-1):
return nb_assets
worker = get_patched_worker(mocker, default_conf)
result = worker._throttle(throttled_func, min_secs=0.1, nb_assets=666)
assert result == 666
result = worker._throttle(throttled_func, min_secs=0.1)
assert result == -1
def test_order_dict_dry_run(default_conf, mocker, caplog) -> None:
patch_RPCManager(mocker)
patch_exchange(mocker)
@ -224,18 +150,13 @@ def test_get_trade_stake_amount_no_stake_amount(default_conf, mocker) -> None:
freqtrade._get_trade_stake_amount('ETH/BTC')
def test_get_trade_stake_amount_unlimited_amount(default_conf,
ticker,
limit_buy_order,
fee,
markets,
mocker) -> None:
def test_get_trade_stake_amount_unlimited_amount(default_conf, ticker,
limit_buy_order, fee, mocker) -> None:
patch_RPCManager(mocker)
patch_exchange(mocker)
patch_wallet(mocker, free=default_conf['stake_amount'])
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
markets=PropertyMock(return_value=markets),
get_ticker=ticker,
buy=MagicMock(return_value={'id': limit_buy_order['id']}),
get_fee=fee
@ -296,7 +217,7 @@ def test_edge_overrides_stake_amount(mocker, edge_conf) -> None:
assert freqtrade._get_trade_stake_amount('LTC/BTC') == (999.9 * 0.5 * 0.01) / 0.21
def test_edge_overrides_stoploss(limit_buy_order, fee, markets, caplog, mocker, edge_conf) -> None:
def test_edge_overrides_stoploss(limit_buy_order, fee, caplog, mocker, edge_conf) -> None:
patch_RPCManager(mocker)
patch_exchange(mocker)
@ -317,7 +238,6 @@ def test_edge_overrides_stoploss(limit_buy_order, fee, markets, caplog, mocker,
}),
buy=MagicMock(return_value={'id': limit_buy_order['id']}),
get_fee=fee,
markets=PropertyMock(return_value=markets)
)
#############################################
@ -337,7 +257,7 @@ def test_edge_overrides_stoploss(limit_buy_order, fee, markets, caplog, mocker,
assert trade.sell_reason == SellType.STOP_LOSS.value
def test_edge_should_ignore_strategy_stoploss(limit_buy_order, fee, markets,
def test_edge_should_ignore_strategy_stoploss(limit_buy_order, fee,
mocker, edge_conf) -> None:
patch_RPCManager(mocker)
patch_exchange(mocker)
@ -358,7 +278,6 @@ def test_edge_should_ignore_strategy_stoploss(limit_buy_order, fee, markets,
}),
buy=MagicMock(return_value={'id': limit_buy_order['id']}),
get_fee=fee,
markets=PropertyMock(return_value=markets),
)
#############################################
@ -377,7 +296,7 @@ def test_edge_should_ignore_strategy_stoploss(limit_buy_order, fee, markets,
def test_total_open_trades_stakes(mocker, default_conf, ticker,
limit_buy_order, fee, markets) -> None:
limit_buy_order, fee) -> None:
patch_RPCManager(mocker)
patch_exchange(mocker)
default_conf['stake_amount'] = 0.0000098751
@ -387,7 +306,6 @@ def test_total_open_trades_stakes(mocker, default_conf, ticker,
get_ticker=ticker,
buy=MagicMock(return_value={'id': limit_buy_order['id']}),
get_fee=fee,
markets=PropertyMock(return_value=markets)
)
freqtrade = FreqtradeBot(default_conf)
patch_get_signal(freqtrade)
@ -522,7 +440,7 @@ def test_get_min_pair_stake_amount(mocker, default_conf) -> None:
assert result == min(8, 2 * 2) / 0.9
def test_create_trades(default_conf, ticker, limit_buy_order, fee, markets, mocker) -> None:
def test_create_trades(default_conf, ticker, limit_buy_order, fee, mocker) -> None:
patch_RPCManager(mocker)
patch_exchange(mocker)
mocker.patch.multiple(
@ -530,7 +448,6 @@ def test_create_trades(default_conf, ticker, limit_buy_order, fee, markets, mock
get_ticker=ticker,
buy=MagicMock(return_value={'id': limit_buy_order['id']}),
get_fee=fee,
markets=PropertyMock(return_value=markets)
)
# Save state of current whitelist
@ -556,7 +473,7 @@ def test_create_trades(default_conf, ticker, limit_buy_order, fee, markets, mock
def test_create_trades_no_stake_amount(default_conf, ticker, limit_buy_order,
fee, markets, mocker) -> None:
fee, mocker) -> None:
patch_RPCManager(mocker)
patch_exchange(mocker)
patch_wallet(mocker, free=default_conf['stake_amount'] * 0.5)
@ -565,7 +482,6 @@ def test_create_trades_no_stake_amount(default_conf, ticker, limit_buy_order,
get_ticker=ticker,
buy=MagicMock(return_value={'id': limit_buy_order['id']}),
get_fee=fee,
markets=PropertyMock(return_value=markets)
)
freqtrade = FreqtradeBot(default_conf)
patch_get_signal(freqtrade)
@ -575,7 +491,7 @@ def test_create_trades_no_stake_amount(default_conf, ticker, limit_buy_order,
def test_create_trades_minimal_amount(default_conf, ticker, limit_buy_order,
fee, markets, mocker) -> None:
fee, mocker) -> None:
patch_RPCManager(mocker)
patch_exchange(mocker)
buy_mock = MagicMock(return_value={'id': limit_buy_order['id']})
@ -584,7 +500,6 @@ def test_create_trades_minimal_amount(default_conf, ticker, limit_buy_order,
get_ticker=ticker,
buy=buy_mock,
get_fee=fee,
markets=PropertyMock(return_value=markets)
)
default_conf['stake_amount'] = 0.0005
freqtrade = FreqtradeBot(default_conf)
@ -596,7 +511,7 @@ def test_create_trades_minimal_amount(default_conf, ticker, limit_buy_order,
def test_create_trades_too_small_stake_amount(default_conf, ticker, limit_buy_order,
fee, markets, mocker) -> None:
fee, mocker) -> None:
patch_RPCManager(mocker)
patch_exchange(mocker)
buy_mock = MagicMock(return_value={'id': limit_buy_order['id']})
@ -605,7 +520,6 @@ def test_create_trades_too_small_stake_amount(default_conf, ticker, limit_buy_or
get_ticker=ticker,
buy=buy_mock,
get_fee=fee,
markets=PropertyMock(return_value=markets)
)
default_conf['stake_amount'] = 0.000000005
@ -625,7 +539,6 @@ def test_create_trades_limit_reached(default_conf, ticker, limit_buy_order,
buy=MagicMock(return_value={'id': limit_buy_order['id']}),
get_balance=MagicMock(return_value=default_conf['stake_amount']),
get_fee=fee,
markets=PropertyMock(return_value=markets)
)
default_conf['max_open_trades'] = 0
default_conf['stake_amount'] = constants.UNLIMITED_STAKE_AMOUNT
@ -638,7 +551,7 @@ def test_create_trades_limit_reached(default_conf, ticker, limit_buy_order,
def test_create_trades_no_pairs_let(default_conf, ticker, limit_buy_order, fee,
markets, mocker, caplog) -> None:
mocker, caplog) -> None:
patch_RPCManager(mocker)
patch_exchange(mocker)
mocker.patch.multiple(
@ -646,7 +559,6 @@ def test_create_trades_no_pairs_let(default_conf, ticker, limit_buy_order, fee,
get_ticker=ticker,
buy=MagicMock(return_value={'id': limit_buy_order['id']}),
get_fee=fee,
markets=PropertyMock(return_value=markets)
)
default_conf['exchange']['pair_whitelist'] = ["ETH/BTC"]
@ -660,7 +572,7 @@ def test_create_trades_no_pairs_let(default_conf, ticker, limit_buy_order, fee,
def test_create_trades_no_pairs_in_whitelist(default_conf, ticker, limit_buy_order, fee,
markets, mocker, caplog) -> None:
mocker, caplog) -> None:
patch_RPCManager(mocker)
patch_exchange(mocker)
mocker.patch.multiple(
@ -668,7 +580,6 @@ def test_create_trades_no_pairs_in_whitelist(default_conf, ticker, limit_buy_ord
get_ticker=ticker,
buy=MagicMock(return_value={'id': limit_buy_order['id']}),
get_fee=fee,
markets=PropertyMock(return_value=markets)
)
default_conf['exchange']['pair_whitelist'] = []
freqtrade = FreqtradeBot(default_conf)
@ -699,7 +610,7 @@ def test_create_trades_no_signal(default_conf, fee, mocker) -> None:
@pytest.mark.parametrize("max_open", range(0, 5))
def test_create_trades_multiple_trades(default_conf, ticker,
fee, markets, mocker, max_open) -> None:
fee, mocker, max_open) -> None:
patch_RPCManager(mocker)
patch_exchange(mocker)
default_conf['max_open_trades'] = max_open
@ -708,7 +619,6 @@ def test_create_trades_multiple_trades(default_conf, ticker,
get_ticker=ticker,
buy=MagicMock(return_value={'id': "12355555"}),
get_fee=fee,
markets=PropertyMock(return_value=markets)
)
freqtrade = FreqtradeBot(default_conf)
patch_get_signal(freqtrade)
@ -719,7 +629,7 @@ def test_create_trades_multiple_trades(default_conf, ticker,
assert len(trades) == max_open
def test_create_trades_preopen(default_conf, ticker, fee, markets, mocker) -> None:
def test_create_trades_preopen(default_conf, ticker, fee, mocker) -> None:
patch_RPCManager(mocker)
patch_exchange(mocker)
default_conf['max_open_trades'] = 4
@ -728,7 +638,6 @@ def test_create_trades_preopen(default_conf, ticker, fee, markets, mocker) -> No
get_ticker=ticker,
buy=MagicMock(return_value={'id': "12355555"}),
get_fee=fee,
markets=PropertyMock(return_value=markets)
)
freqtrade = FreqtradeBot(default_conf)
patch_get_signal(freqtrade)
@ -747,13 +656,12 @@ def test_create_trades_preopen(default_conf, ticker, fee, markets, mocker) -> No
def test_process_trade_creation(default_conf, ticker, limit_buy_order,
markets, fee, mocker, caplog) -> None:
fee, mocker, caplog) -> None:
patch_RPCManager(mocker)
patch_exchange(mocker)
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
get_ticker=ticker,
markets=PropertyMock(return_value=markets),
buy=MagicMock(return_value={'id': limit_buy_order['id']}),
get_order=MagicMock(return_value=limit_buy_order),
get_fee=fee,
@ -782,13 +690,12 @@ def test_process_trade_creation(default_conf, ticker, limit_buy_order,
)
def test_process_exchange_failures(default_conf, ticker, markets, mocker) -> None:
def test_process_exchange_failures(default_conf, ticker, mocker) -> None:
patch_RPCManager(mocker)
patch_exchange(mocker)
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
get_ticker=ticker,
markets=PropertyMock(return_value=markets),
buy=MagicMock(side_effect=TemporaryError)
)
sleep_mock = mocker.patch('time.sleep', side_effect=lambda _: None)
@ -800,13 +707,12 @@ def test_process_exchange_failures(default_conf, ticker, markets, mocker) -> Non
assert sleep_mock.has_calls()
def test_process_operational_exception(default_conf, ticker, markets, mocker) -> None:
def test_process_operational_exception(default_conf, ticker, mocker) -> None:
msg_mock = patch_RPCManager(mocker)
patch_exchange(mocker)
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
get_ticker=ticker,
markets=PropertyMock(return_value=markets),
buy=MagicMock(side_effect=OperationalException)
)
worker = Worker(args=None, config=default_conf)
@ -819,14 +725,12 @@ def test_process_operational_exception(default_conf, ticker, markets, mocker) ->
assert 'OperationalException' in msg_mock.call_args_list[-1][0][0]['status']
def test_process_trade_handling(
default_conf, ticker, limit_buy_order, markets, fee, mocker) -> None:
def test_process_trade_handling(default_conf, ticker, limit_buy_order, fee, mocker) -> None:
patch_RPCManager(mocker)
patch_exchange(mocker)
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
get_ticker=ticker,
markets=PropertyMock(return_value=markets),
buy=MagicMock(return_value={'id': limit_buy_order['id']}),
get_order=MagicMock(return_value=limit_buy_order),
get_fee=fee,
@ -846,15 +750,14 @@ def test_process_trade_handling(
assert len(trades) == 1
def test_process_trade_no_whitelist_pair(
default_conf, ticker, limit_buy_order, markets, fee, mocker) -> None:
def test_process_trade_no_whitelist_pair(default_conf, ticker, limit_buy_order,
fee, mocker) -> None:
""" Test process with trade not in pair list """
patch_RPCManager(mocker)
patch_exchange(mocker)
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
get_ticker=ticker,
markets=PropertyMock(return_value=markets),
buy=MagicMock(return_value={'id': limit_buy_order['id']}),
get_order=MagicMock(return_value=limit_buy_order),
get_fee=fee,
@ -891,7 +794,7 @@ def test_process_trade_no_whitelist_pair(
assert len(freqtrade.active_pair_whitelist) == len(set(freqtrade.active_pair_whitelist))
def test_process_informative_pairs_added(default_conf, ticker, markets, mocker) -> None:
def test_process_informative_pairs_added(default_conf, ticker, mocker) -> None:
patch_RPCManager(mocker)
patch_exchange(mocker)
@ -902,7 +805,6 @@ def test_process_informative_pairs_added(default_conf, ticker, markets, mocker)
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
get_ticker=ticker,
markets=PropertyMock(return_value=markets),
buy=MagicMock(side_effect=TemporaryError),
refresh_latest_ohlcv=refresh_mock,
)
@ -948,7 +850,7 @@ def test_balance_bigger_last_ask(mocker, default_conf) -> None:
assert freqtrade.get_target_bid('ETH/BTC') == 5
def test_execute_buy(mocker, default_conf, fee, markets, limit_buy_order) -> None:
def test_execute_buy(mocker, default_conf, fee, limit_buy_order) -> None:
patch_RPCManager(mocker)
patch_exchange(mocker)
freqtrade = FreqtradeBot(default_conf)
@ -970,7 +872,6 @@ def test_execute_buy(mocker, default_conf, fee, markets, limit_buy_order) -> Non
}),
buy=buy_mm,
get_fee=fee,
markets=PropertyMock(return_value=markets)
)
pair = 'ETH/BTC'
@ -1067,7 +968,7 @@ def test_add_stoploss_on_exchange(mocker, default_conf, limit_buy_order) -> None
def test_handle_stoploss_on_exchange(mocker, default_conf, fee, caplog,
markets, limit_buy_order, limit_sell_order) -> None:
limit_buy_order, limit_sell_order) -> None:
stoploss_limit = MagicMock(return_value={'id': 13434334})
patch_RPCManager(mocker)
patch_exchange(mocker)
@ -1081,7 +982,6 @@ def test_handle_stoploss_on_exchange(mocker, default_conf, fee, caplog,
buy=MagicMock(return_value={'id': limit_buy_order['id']}),
sell=MagicMock(return_value={'id': limit_sell_order['id']}),
get_fee=fee,
markets=PropertyMock(return_value=markets),
stoploss_limit=stoploss_limit
)
freqtrade = FreqtradeBot(default_conf)
@ -1168,7 +1068,7 @@ def test_handle_stoploss_on_exchange(mocker, default_conf, fee, caplog,
def test_handle_sle_cancel_cant_recreate(mocker, default_conf, fee, caplog,
markets, limit_buy_order, limit_sell_order) -> None:
limit_buy_order, limit_sell_order) -> None:
# Sixth case: stoploss order was cancelled but couldn't create new one
patch_RPCManager(mocker)
patch_exchange(mocker)
@ -1182,7 +1082,6 @@ def test_handle_sle_cancel_cant_recreate(mocker, default_conf, fee, caplog,
buy=MagicMock(return_value={'id': limit_buy_order['id']}),
sell=MagicMock(return_value={'id': limit_sell_order['id']}),
get_fee=fee,
markets=PropertyMock(return_value=markets),
get_order=MagicMock(return_value={'status': 'canceled'}),
stoploss_limit=MagicMock(side_effect=DependencyException()),
)
@ -1203,7 +1102,7 @@ def test_handle_sle_cancel_cant_recreate(mocker, default_conf, fee, caplog,
def test_create_stoploss_order_invalid_order(mocker, default_conf, caplog, fee,
markets, limit_buy_order, limit_sell_order):
limit_buy_order, limit_sell_order):
rpc_mock = patch_RPCManager(mocker)
patch_exchange(mocker)
sell_mock = MagicMock(return_value={'id': limit_sell_order['id']})
@ -1217,7 +1116,6 @@ def test_create_stoploss_order_invalid_order(mocker, default_conf, caplog, fee,
buy=MagicMock(return_value={'id': limit_buy_order['id']}),
sell=sell_mock,
get_fee=fee,
markets=PropertyMock(return_value=markets),
get_order=MagicMock(return_value={'status': 'canceled'}),
stoploss_limit=MagicMock(side_effect=InvalidOrderException()),
)
@ -1340,8 +1238,7 @@ def test_handle_stoploss_on_exchange_trailing(mocker, default_conf, fee, caplog,
def test_handle_stoploss_on_exchange_trailing_error(mocker, default_conf, fee, caplog,
markets, limit_buy_order,
limit_sell_order) -> None:
limit_buy_order, limit_sell_order) -> None:
# When trailing stoploss is set
stoploss_limit = MagicMock(return_value={'id': 13434334})
patch_exchange(mocker)
@ -1356,7 +1253,6 @@ def test_handle_stoploss_on_exchange_trailing_error(mocker, default_conf, fee, c
buy=MagicMock(return_value={'id': limit_buy_order['id']}),
sell=MagicMock(return_value={'id': limit_sell_order['id']}),
get_fee=fee,
markets=PropertyMock(return_value=markets),
stoploss_limit=stoploss_limit
)
@ -1409,7 +1305,7 @@ def test_handle_stoploss_on_exchange_trailing_error(mocker, default_conf, fee, c
def test_tsl_on_exchange_compatible_with_edge(mocker, edge_conf, fee, caplog,
markets, limit_buy_order, limit_sell_order) -> None:
limit_buy_order, limit_sell_order) -> None:
# When trailing stoploss is set
stoploss_limit = MagicMock(return_value={'id': 13434334})
@ -1427,7 +1323,6 @@ def test_tsl_on_exchange_compatible_with_edge(mocker, edge_conf, fee, caplog,
buy=MagicMock(return_value={'id': limit_buy_order['id']}),
sell=MagicMock(return_value={'id': limit_sell_order['id']}),
get_fee=fee,
markets=PropertyMock(return_value=markets),
stoploss_limit=stoploss_limit
)
@ -1728,8 +1623,7 @@ def test_update_trade_state_sell(default_conf, trades_for_order, limit_sell_orde
assert not trade.is_open
def test_handle_trade(default_conf, limit_buy_order, limit_sell_order,
fee, markets, mocker) -> None:
def test_handle_trade(default_conf, limit_buy_order, limit_sell_order, fee, mocker) -> None:
patch_RPCManager(mocker)
patch_exchange(mocker)
mocker.patch.multiple(
@ -1742,7 +1636,6 @@ def test_handle_trade(default_conf, limit_buy_order, limit_sell_order,
buy=MagicMock(return_value={'id': limit_buy_order['id']}),
sell=MagicMock(return_value={'id': limit_sell_order['id']}),
get_fee=fee,
markets=PropertyMock(return_value=markets)
)
freqtrade = FreqtradeBot(default_conf)
patch_get_signal(freqtrade)
@ -1769,8 +1662,7 @@ def test_handle_trade(default_conf, limit_buy_order, limit_sell_order,
assert trade.close_date is not None
def test_handle_overlpapping_signals(default_conf, ticker, limit_buy_order,
fee, markets, mocker) -> None:
def test_handle_overlpapping_signals(default_conf, ticker, limit_buy_order, fee, mocker) -> None:
patch_RPCManager(mocker)
patch_exchange(mocker)
mocker.patch.multiple(
@ -1778,7 +1670,6 @@ def test_handle_overlpapping_signals(default_conf, ticker, limit_buy_order,
get_ticker=ticker,
buy=MagicMock(return_value={'id': limit_buy_order['id']}),
get_fee=fee,
markets=PropertyMock(return_value=markets)
)
freqtrade = FreqtradeBot(default_conf)
@ -1884,7 +1775,7 @@ def test_handle_trade_use_sell_signal(
def test_close_trade(default_conf, ticker, limit_buy_order, limit_sell_order,
fee, markets, mocker) -> None:
fee, mocker) -> None:
patch_RPCManager(mocker)
patch_exchange(mocker)
mocker.patch.multiple(
@ -1892,7 +1783,6 @@ def test_close_trade(default_conf, ticker, limit_buy_order, limit_sell_order,
get_ticker=ticker,
buy=MagicMock(return_value={'id': limit_buy_order['id']}),
get_fee=fee,
markets=PropertyMock(return_value=markets)
)
freqtrade = FreqtradeBot(default_conf)
patch_get_signal(freqtrade)
@ -2222,14 +2112,13 @@ def test_handle_timedout_limit_sell(mocker, default_conf) -> None:
assert cancel_order_mock.call_count == 1
def test_execute_sell_up(default_conf, ticker, fee, ticker_sell_up, markets, mocker) -> None:
def test_execute_sell_up(default_conf, ticker, fee, ticker_sell_up, mocker) -> None:
rpc_mock = patch_RPCManager(mocker)
patch_exchange(mocker)
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
get_ticker=ticker,
get_fee=fee,
markets=PropertyMock(return_value=markets)
)
patch_whitelist(mocker, default_conf)
freqtrade = FreqtradeBot(default_conf)
@ -2269,14 +2158,13 @@ def test_execute_sell_up(default_conf, ticker, fee, ticker_sell_up, markets, moc
} == last_msg
def test_execute_sell_down(default_conf, ticker, fee, ticker_sell_down, markets, mocker) -> None:
def test_execute_sell_down(default_conf, ticker, fee, ticker_sell_down, mocker) -> None:
rpc_mock = patch_RPCManager(mocker)
patch_exchange(mocker)
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
get_ticker=ticker,
get_fee=fee,
markets=PropertyMock(return_value=markets)
)
patch_whitelist(mocker, default_conf)
freqtrade = FreqtradeBot(default_conf)
@ -2318,15 +2206,13 @@ def test_execute_sell_down(default_conf, ticker, fee, ticker_sell_down, markets,
def test_execute_sell_down_stoploss_on_exchange_dry_run(default_conf, ticker, fee,
ticker_sell_down,
markets, mocker) -> None:
ticker_sell_down, mocker) -> None:
rpc_mock = patch_RPCManager(mocker)
patch_exchange(mocker)
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
get_ticker=ticker,
get_fee=fee,
markets=PropertyMock(return_value=markets)
)
patch_whitelist(mocker, default_conf)
freqtrade = FreqtradeBot(default_conf)
@ -2374,8 +2260,7 @@ def test_execute_sell_down_stoploss_on_exchange_dry_run(default_conf, ticker, fe
} == last_msg
def test_execute_sell_sloe_cancel_exception(mocker, default_conf, ticker, fee,
markets, caplog) -> None:
def test_execute_sell_sloe_cancel_exception(mocker, default_conf, ticker, fee, caplog) -> None:
freqtrade = get_patched_freqtradebot(mocker, default_conf)
mocker.patch('freqtrade.exchange.Exchange.cancel_order', side_effect=InvalidOrderException())
sellmock = MagicMock()
@ -2384,7 +2269,6 @@ def test_execute_sell_sloe_cancel_exception(mocker, default_conf, ticker, fee,
'freqtrade.exchange.Exchange',
get_ticker=ticker,
get_fee=fee,
markets=PropertyMock(return_value=markets),
sell=sellmock
)
@ -2404,9 +2288,8 @@ def test_execute_sell_sloe_cancel_exception(mocker, default_conf, ticker, fee,
assert log_has('Could not cancel stoploss order abcd', caplog)
def test_execute_sell_with_stoploss_on_exchange(default_conf,
ticker, fee, ticker_sell_up,
markets, mocker) -> None:
def test_execute_sell_with_stoploss_on_exchange(default_conf, ticker, fee, ticker_sell_up,
mocker) -> None:
default_conf['exchange']['name'] = 'binance'
rpc_mock = patch_RPCManager(mocker)
@ -2423,7 +2306,6 @@ def test_execute_sell_with_stoploss_on_exchange(default_conf,
'freqtrade.exchange.Exchange',
get_ticker=ticker,
get_fee=fee,
markets=PropertyMock(return_value=markets),
symbol_amount_prec=lambda s, x, y: y,
symbol_price_prec=lambda s, x, y: y,
stoploss_limit=stoploss_limit,
@ -2458,10 +2340,8 @@ def test_execute_sell_with_stoploss_on_exchange(default_conf,
assert rpc_mock.call_count == 2
def test_may_execute_sell_after_stoploss_on_exchange_hit(default_conf,
ticker, fee,
limit_buy_order,
markets, mocker) -> None:
def test_may_execute_sell_after_stoploss_on_exchange_hit(default_conf, ticker, fee,
limit_buy_order, mocker) -> None:
default_conf['exchange']['name'] = 'binance'
rpc_mock = patch_RPCManager(mocker)
patch_exchange(mocker)
@ -2469,7 +2349,6 @@ def test_may_execute_sell_after_stoploss_on_exchange_hit(default_conf,
'freqtrade.exchange.Exchange',
get_ticker=ticker,
get_fee=fee,
markets=PropertyMock(return_value=markets),
symbol_amount_prec=lambda s, x, y: y,
symbol_price_prec=lambda s, x, y: y,
)
@ -2526,124 +2405,14 @@ def test_may_execute_sell_after_stoploss_on_exchange_hit(default_conf,
assert rpc_mock.call_count == 2
def test_may_execute_sell_stoploss_on_exchange_multi(default_conf,
ticker, fee,
limit_buy_order,
markets, mocker) -> None:
"""
Tests workflow of selling stoploss_on_exchange.
Sells
* first trade as stoploss
* 2nd trade is kept
* 3rd trade is sold via sell-signal
"""
default_conf['max_open_trades'] = 3
default_conf['exchange']['name'] = 'binance'
patch_RPCManager(mocker)
patch_exchange(mocker)
stoploss_limit = {
'id': 123,
'info': {}
}
stoploss_order_open = {
"id": "123",
"timestamp": 1542707426845,
"datetime": "2018-11-20T09:50:26.845Z",
"lastTradeTimestamp": None,
"symbol": "BTC/USDT",
"type": "stop_loss_limit",
"side": "sell",
"price": 1.08801,
"amount": 90.99181074,
"cost": 0.0,
"average": 0.0,
"filled": 0.0,
"remaining": 0.0,
"status": "open",
"fee": None,
"trades": None
}
stoploss_order_closed = stoploss_order_open.copy()
stoploss_order_closed['status'] = 'closed'
# Sell first trade based on stoploss, keep 2nd and 3rd trade open
stoploss_order_mock = MagicMock(
side_effect=[stoploss_order_closed, stoploss_order_open, stoploss_order_open])
# Sell 3rd trade (not called for the first trade)
should_sell_mock = MagicMock(side_effect=[
SellCheckTuple(sell_flag=False, sell_type=SellType.NONE),
SellCheckTuple(sell_flag=True, sell_type=SellType.SELL_SIGNAL)]
)
cancel_order_mock = MagicMock()
mocker.patch('freqtrade.exchange.Binance.stoploss_limit', stoploss_limit)
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
get_ticker=ticker,
get_fee=fee,
markets=PropertyMock(return_value=markets),
symbol_amount_prec=lambda s, x, y: y,
symbol_price_prec=lambda s, x, y: y,
get_order=stoploss_order_mock,
cancel_order=cancel_order_mock,
)
wallets_mock = MagicMock()
mocker.patch.multiple(
'freqtrade.freqtradebot.FreqtradeBot',
create_stoploss_order=MagicMock(return_value=True),
update_trade_state=MagicMock(),
_notify_sell=MagicMock(),
)
mocker.patch("freqtrade.strategy.interface.IStrategy.should_sell", should_sell_mock)
mocker.patch("freqtrade.wallets.Wallets.update", wallets_mock)
freqtrade = FreqtradeBot(default_conf)
freqtrade.strategy.order_types['stoploss_on_exchange'] = True
# Switch ordertype to market to close trade immediately
freqtrade.strategy.order_types['sell'] = 'market'
patch_get_signal(freqtrade)
# Create some test data
freqtrade.create_trades()
wallets_mock.reset_mock()
Trade.session = MagicMock()
trades = Trade.query.all()
# Make sure stoploss-order is open and trade is bought (since we mock update_trade_state)
for trade in trades:
trade.stoploss_order_id = 3
trade.open_order_id = None
freqtrade.process_maybe_execute_sells(trades)
assert should_sell_mock.call_count == 2
# Only order for 3rd trade needs to be cancelled
assert cancel_order_mock.call_count == 1
# Wallets should only be called once per sell cycle
assert wallets_mock.call_count == 1
trade = trades[0]
assert trade.sell_reason == SellType.STOPLOSS_ON_EXCHANGE.value
assert not trade.is_open
trade = trades[1]
assert not trade.sell_reason
assert trade.is_open
trade = trades[2]
assert trade.sell_reason == SellType.SELL_SIGNAL.value
assert not trade.is_open
def test_execute_sell_market_order(default_conf, ticker, fee,
ticker_sell_up, markets, mocker) -> None:
ticker_sell_up, mocker) -> None:
rpc_mock = patch_RPCManager(mocker)
patch_exchange(mocker)
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
get_ticker=ticker,
get_fee=fee,
markets=PropertyMock(return_value=markets)
)
patch_whitelist(mocker, default_conf)
freqtrade = FreqtradeBot(default_conf)
@ -2689,7 +2458,7 @@ def test_execute_sell_market_order(default_conf, ticker, fee,
def test_sell_profit_only_enable_profit(default_conf, limit_buy_order,
fee, markets, mocker) -> None:
fee, mocker) -> None:
patch_RPCManager(mocker)
patch_exchange(mocker)
mocker.patch.multiple(
@ -2701,7 +2470,6 @@ def test_sell_profit_only_enable_profit(default_conf, limit_buy_order,
}),
buy=MagicMock(return_value={'id': limit_buy_order['id']}),
get_fee=fee,
markets=PropertyMock(return_value=markets)
)
default_conf['ask_strategy'] = {
'use_sell_signal': True,
@ -2721,7 +2489,7 @@ def test_sell_profit_only_enable_profit(default_conf, limit_buy_order,
def test_sell_profit_only_disable_profit(default_conf, limit_buy_order,
fee, markets, mocker) -> None:
fee, mocker) -> None:
patch_RPCManager(mocker)
patch_exchange(mocker)
mocker.patch.multiple(
@ -2733,7 +2501,6 @@ def test_sell_profit_only_disable_profit(default_conf, limit_buy_order,
}),
buy=MagicMock(return_value={'id': limit_buy_order['id']}),
get_fee=fee,
markets=PropertyMock(return_value=markets)
)
default_conf['ask_strategy'] = {
'use_sell_signal': True,
@ -2751,7 +2518,7 @@ def test_sell_profit_only_disable_profit(default_conf, limit_buy_order,
assert trade.sell_reason == SellType.SELL_SIGNAL.value
def test_sell_profit_only_enable_loss(default_conf, limit_buy_order, fee, markets, mocker) -> None:
def test_sell_profit_only_enable_loss(default_conf, limit_buy_order, fee, mocker) -> None:
patch_RPCManager(mocker)
patch_exchange(mocker)
mocker.patch.multiple(
@ -2763,7 +2530,6 @@ def test_sell_profit_only_enable_loss(default_conf, limit_buy_order, fee, market
}),
buy=MagicMock(return_value={'id': limit_buy_order['id']}),
get_fee=fee,
markets=PropertyMock(return_value=markets)
)
default_conf['ask_strategy'] = {
'use_sell_signal': True,
@ -2781,7 +2547,7 @@ def test_sell_profit_only_enable_loss(default_conf, limit_buy_order, fee, market
assert freqtrade.handle_trade(trade) is False
def test_sell_profit_only_disable_loss(default_conf, limit_buy_order, fee, markets, mocker) -> None:
def test_sell_profit_only_disable_loss(default_conf, limit_buy_order, fee, mocker) -> None:
patch_RPCManager(mocker)
patch_exchange(mocker)
mocker.patch.multiple(
@ -2793,7 +2559,6 @@ def test_sell_profit_only_disable_loss(default_conf, limit_buy_order, fee, marke
}),
buy=MagicMock(return_value={'id': limit_buy_order['id']}),
get_fee=fee,
markets=PropertyMock(return_value=markets)
)
default_conf['ask_strategy'] = {
'use_sell_signal': True,
@ -3115,7 +2880,7 @@ def test_tsl_only_offset_reached(default_conf, limit_buy_order, fee,
def test_disable_ignore_roi_if_buy_signal(default_conf, limit_buy_order,
fee, markets, mocker) -> None:
fee, mocker) -> None:
patch_RPCManager(mocker)
patch_exchange(mocker)
mocker.patch.multiple(
@ -3127,7 +2892,6 @@ def test_disable_ignore_roi_if_buy_signal(default_conf, limit_buy_order,
}),
buy=MagicMock(return_value={'id': limit_buy_order['id']}),
get_fee=fee,
markets=PropertyMock(return_value=markets)
)
default_conf['ask_strategy'] = {
'ignore_roi_if_buy_signal': False
@ -3422,7 +3186,7 @@ def test_get_real_amount_open_trade(default_conf, mocker):
assert freqtrade.get_real_amount(trade, order) == amount
def test_order_book_depth_of_market(default_conf, ticker, limit_buy_order, fee, markets, mocker,
def test_order_book_depth_of_market(default_conf, ticker, limit_buy_order, fee, mocker,
order_book_l2):
default_conf['bid_strategy']['check_depth_of_market']['enabled'] = True
default_conf['bid_strategy']['check_depth_of_market']['bids_to_ask_delta'] = 0.1
@ -3434,7 +3198,6 @@ def test_order_book_depth_of_market(default_conf, ticker, limit_buy_order, fee,
get_ticker=ticker,
buy=MagicMock(return_value={'id': limit_buy_order['id']}),
get_fee=fee,
markets=PropertyMock(return_value=markets)
)
# Save state of current whitelist
@ -3450,6 +3213,8 @@ def test_order_book_depth_of_market(default_conf, ticker, limit_buy_order, fee,
assert trade.open_date is not None
assert trade.exchange == 'bittrex'
assert len(Trade.query.all()) == 1
# Simulate fulfilled LIMIT_BUY order for trade
trade.update(limit_buy_order)
@ -3458,7 +3223,7 @@ def test_order_book_depth_of_market(default_conf, ticker, limit_buy_order, fee,
def test_order_book_depth_of_market_high_delta(default_conf, ticker, limit_buy_order,
fee, markets, mocker, order_book_l2):
fee, mocker, order_book_l2):
default_conf['bid_strategy']['check_depth_of_market']['enabled'] = True
# delta is 100 which is impossible to reach. hence check_depth_of_market will return false
default_conf['bid_strategy']['check_depth_of_market']['bids_to_ask_delta'] = 100
@ -3470,7 +3235,6 @@ def test_order_book_depth_of_market_high_delta(default_conf, ticker, limit_buy_o
get_ticker=ticker,
buy=MagicMock(return_value={'id': limit_buy_order['id']}),
get_fee=fee,
markets=PropertyMock(return_value=markets)
)
# Save state of current whitelist
freqtrade = FreqtradeBot(default_conf)
@ -3481,7 +3245,7 @@ def test_order_book_depth_of_market_high_delta(default_conf, ticker, limit_buy_o
assert trade is None
def test_order_book_bid_strategy1(mocker, default_conf, order_book_l2, markets) -> None:
def test_order_book_bid_strategy1(mocker, default_conf, order_book_l2) -> None:
"""
test if function get_target_bid will return the order book price
instead of the ask rate
@ -3490,7 +3254,6 @@ def test_order_book_bid_strategy1(mocker, default_conf, order_book_l2, markets)
ticker_mock = MagicMock(return_value={'ask': 0.045, 'last': 0.046})
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
markets=PropertyMock(return_value=markets),
get_order_book=order_book_l2,
get_ticker=ticker_mock,
@ -3506,7 +3269,7 @@ def test_order_book_bid_strategy1(mocker, default_conf, order_book_l2, markets)
assert ticker_mock.call_count == 0
def test_order_book_bid_strategy2(mocker, default_conf, order_book_l2, markets) -> None:
def test_order_book_bid_strategy2(mocker, default_conf, order_book_l2) -> None:
"""
test if function get_target_bid will return the ask rate (since its value is lower)
instead of the order book rate (even if enabled)
@ -3515,7 +3278,6 @@ def test_order_book_bid_strategy2(mocker, default_conf, order_book_l2, markets)
ticker_mock = MagicMock(return_value={'ask': 0.042, 'last': 0.046})
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
markets=PropertyMock(return_value=markets),
get_order_book=order_book_l2,
get_ticker=ticker_mock,
@ -3532,14 +3294,13 @@ def test_order_book_bid_strategy2(mocker, default_conf, order_book_l2, markets)
assert ticker_mock.call_count == 0
def test_check_depth_of_market_buy(default_conf, mocker, order_book_l2, markets) -> None:
def test_check_depth_of_market_buy(default_conf, mocker, order_book_l2) -> None:
"""
test check depth of market
"""
patch_exchange(mocker)
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
markets=PropertyMock(return_value=markets),
get_order_book=order_book_l2
)
default_conf['telegram']['enabled'] = False
@ -3554,7 +3315,7 @@ def test_check_depth_of_market_buy(default_conf, mocker, order_book_l2, markets)
def test_order_book_ask_strategy(default_conf, limit_buy_order, limit_sell_order,
fee, markets, mocker, order_book_l2) -> None:
fee, mocker, order_book_l2) -> None:
"""
test order book ask strategy
"""
@ -3576,7 +3337,6 @@ def test_order_book_ask_strategy(default_conf, limit_buy_order, limit_sell_order
buy=MagicMock(return_value={'id': limit_buy_order['id']}),
sell=MagicMock(return_value={'id': limit_sell_order['id']}),
get_fee=fee,
markets=PropertyMock(return_value=markets)
)
freqtrade = FreqtradeBot(default_conf)
patch_get_signal(freqtrade)

159
tests/test_integration.py Normal file
View File

@ -0,0 +1,159 @@
from unittest.mock import MagicMock
from freqtrade.persistence import Trade
from freqtrade.strategy.interface import SellCheckTuple, SellType
from tests.conftest import get_patched_freqtradebot, patch_get_signal
from freqtrade.rpc.rpc import RPC
def test_may_execute_sell_stoploss_on_exchange_multi(default_conf, ticker, fee,
limit_buy_order, mocker) -> None:
"""
Tests workflow of selling stoploss_on_exchange.
Sells
* first trade as stoploss
* 2nd trade is kept
* 3rd trade is sold via sell-signal
"""
default_conf['max_open_trades'] = 3
default_conf['exchange']['name'] = 'binance'
stoploss_limit = {
'id': 123,
'info': {}
}
stoploss_order_open = {
"id": "123",
"timestamp": 1542707426845,
"datetime": "2018-11-20T09:50:26.845Z",
"lastTradeTimestamp": None,
"symbol": "BTC/USDT",
"type": "stop_loss_limit",
"side": "sell",
"price": 1.08801,
"amount": 90.99181074,
"cost": 0.0,
"average": 0.0,
"filled": 0.0,
"remaining": 0.0,
"status": "open",
"fee": None,
"trades": None
}
stoploss_order_closed = stoploss_order_open.copy()
stoploss_order_closed['status'] = 'closed'
# Sell first trade based on stoploss, keep 2nd and 3rd trade open
stoploss_order_mock = MagicMock(
side_effect=[stoploss_order_closed, stoploss_order_open, stoploss_order_open])
# Sell 3rd trade (not called for the first trade)
should_sell_mock = MagicMock(side_effect=[
SellCheckTuple(sell_flag=False, sell_type=SellType.NONE),
SellCheckTuple(sell_flag=True, sell_type=SellType.SELL_SIGNAL)]
)
cancel_order_mock = MagicMock()
mocker.patch('freqtrade.exchange.Binance.stoploss_limit', stoploss_limit)
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
get_ticker=ticker,
get_fee=fee,
symbol_amount_prec=lambda s, x, y: y,
symbol_price_prec=lambda s, x, y: y,
get_order=stoploss_order_mock,
cancel_order=cancel_order_mock,
)
mocker.patch.multiple(
'freqtrade.freqtradebot.FreqtradeBot',
create_stoploss_order=MagicMock(return_value=True),
update_trade_state=MagicMock(),
_notify_sell=MagicMock(),
)
mocker.patch("freqtrade.strategy.interface.IStrategy.should_sell", should_sell_mock)
wallets_mock = mocker.patch("freqtrade.wallets.Wallets.update", MagicMock())
freqtrade = get_patched_freqtradebot(mocker, default_conf)
freqtrade.strategy.order_types['stoploss_on_exchange'] = True
# Switch ordertype to market to close trade immediately
freqtrade.strategy.order_types['sell'] = 'market'
patch_get_signal(freqtrade)
# Create some test data
freqtrade.create_trades()
wallets_mock.reset_mock()
Trade.session = MagicMock()
trades = Trade.query.all()
# Make sure stoploss-order is open and trade is bought (since we mock update_trade_state)
for trade in trades:
trade.stoploss_order_id = 3
trade.open_order_id = None
freqtrade.process_maybe_execute_sells(trades)
assert should_sell_mock.call_count == 2
# Only order for 3rd trade needs to be cancelled
assert cancel_order_mock.call_count == 1
# Wallets should only be called once per sell cycle
assert wallets_mock.call_count == 1
trade = trades[0]
assert trade.sell_reason == SellType.STOPLOSS_ON_EXCHANGE.value
assert not trade.is_open
trade = trades[1]
assert not trade.sell_reason
assert trade.is_open
trade = trades[2]
assert trade.sell_reason == SellType.SELL_SIGNAL.value
assert not trade.is_open
def test_forcebuy_last_unlimited(default_conf, ticker, fee, limit_buy_order, mocker) -> None:
"""
Tests workflow
"""
default_conf['max_open_trades'] = 5
default_conf['forcebuy_enable'] = True
default_conf['stake_amount'] = 'unlimited'
default_conf['exchange']['name'] = 'binance'
default_conf['telegram']['enabled'] = True
mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
mocker.patch('freqtrade.wallets.Wallets.get_free', MagicMock(
side_effect=[1000, 800, 600, 400, 200]
))
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
get_ticker=ticker,
get_fee=fee,
symbol_amount_prec=lambda s, x, y: y,
symbol_price_prec=lambda s, x, y: y,
)
mocker.patch.multiple(
'freqtrade.freqtradebot.FreqtradeBot',
create_stoploss_order=MagicMock(return_value=True),
update_trade_state=MagicMock(),
_notify_sell=MagicMock(),
)
freqtrade = get_patched_freqtradebot(mocker, default_conf)
rpc = RPC(freqtrade)
freqtrade.strategy.order_types['stoploss_on_exchange'] = True
# Switch ordertype to market to close trade immediately
freqtrade.strategy.order_types['sell'] = 'market'
patch_get_signal(freqtrade)
# Create 4 trades
freqtrade.create_trades()
trades = Trade.query.all()
assert len(trades) == 4
rpc._rpc_forcebuy('TKN/BTC', None)
trades = Trade.query.all()
assert len(trades) == 5
for trade in trades:
assert trade.stake_amount == 200

View File

@ -35,6 +35,8 @@ def create_mock_trades(fee):
fee_open=fee.return_value,
fee_close=fee.return_value,
open_rate=0.123,
close_rate=0.128,
close_profit=0.005,
exchange='bittrex',
is_open=False,
open_order_id='dry_run_sell_12345'
@ -59,7 +61,7 @@ def test_init_create_session(default_conf):
# Check if init create a session
init(default_conf['db_url'], default_conf['dry_run'])
assert hasattr(Trade, 'session')
assert 'Session' in type(Trade.session).__name__
assert 'scoped_session' in type(Trade.session).__name__
def test_init_custom_db_url(default_conf, mocker):
@ -835,3 +837,38 @@ def test_stoploss_reinitialization(default_conf, fee):
assert trade_adj.stop_loss_pct == -0.04
assert trade_adj.initial_stop_loss == 0.96
assert trade_adj.initial_stop_loss_pct == -0.04
@pytest.mark.usefixtures("init_persistence")
def test_total_open_trades_stakes(fee):
res = Trade.total_open_trades_stakes()
assert res == 0
create_mock_trades(fee)
res = Trade.total_open_trades_stakes()
assert res == 0.002
@pytest.mark.usefixtures("init_persistence")
def test_get_overall_performance(fee):
create_mock_trades(fee)
res = Trade.get_overall_performance()
assert len(res) == 1
assert 'pair' in res[0]
assert 'profit' in res[0]
assert 'count' in res[0]
@pytest.mark.usefixtures("init_persistence")
def test_get_best_pair(fee):
res = Trade.get_best_pair()
assert res is None
create_mock_trades(fee)
res = Trade.get_best_pair()
assert len(res) == 2
assert res[0] == 'ETC/BTC'
assert res[1] == 0.005

View File

@ -19,7 +19,7 @@ def test_setup_utils_configuration():
config = setup_utils_configuration(get_args(args), RunMode.OTHER)
assert "exchange" in config
assert config['exchange']['dry_run'] is True
assert config['dry_run'] is True
assert config['exchange']['key'] == ''
assert config['exchange']['secret'] == ''

81
tests/test_worker.py Normal file
View File

@ -0,0 +1,81 @@
import logging
import time
from unittest.mock import MagicMock, PropertyMock
from freqtrade.data.dataprovider import DataProvider
from freqtrade.state import State
from freqtrade.worker import Worker
from tests.conftest import get_patched_worker, log_has
def test_worker_state(mocker, default_conf, markets) -> None:
mocker.patch('freqtrade.exchange.Exchange.markets', PropertyMock(return_value=markets))
worker = get_patched_worker(mocker, default_conf)
assert worker.state is State.RUNNING
default_conf.pop('initial_state')
worker = Worker(args=None, config=default_conf)
assert worker.state is State.STOPPED
def test_worker_running(mocker, default_conf, caplog) -> None:
mock_throttle = MagicMock()
mocker.patch('freqtrade.worker.Worker._throttle', mock_throttle)
mocker.patch('freqtrade.persistence.Trade.stoploss_reinitialization', MagicMock())
worker = get_patched_worker(mocker, default_conf)
state = worker._worker(old_state=None)
assert state is State.RUNNING
assert log_has('Changing state to: RUNNING', caplog)
assert mock_throttle.call_count == 1
# Check strategy is loaded, and received a dataprovider object
assert worker.freqtrade.strategy
assert worker.freqtrade.strategy.dp
assert isinstance(worker.freqtrade.strategy.dp, DataProvider)
def test_worker_stopped(mocker, default_conf, caplog) -> None:
mock_throttle = MagicMock()
mocker.patch('freqtrade.worker.Worker._throttle', mock_throttle)
mock_sleep = mocker.patch('time.sleep', return_value=None)
worker = get_patched_worker(mocker, default_conf)
worker.state = State.STOPPED
state = worker._worker(old_state=State.RUNNING)
assert state is State.STOPPED
assert log_has('Changing state to: STOPPED', caplog)
assert mock_throttle.call_count == 0
assert mock_sleep.call_count == 1
def test_throttle(mocker, default_conf, caplog) -> None:
def throttled_func():
return 42
caplog.set_level(logging.DEBUG)
worker = get_patched_worker(mocker, default_conf)
start = time.time()
result = worker._throttle(throttled_func, min_secs=0.1)
end = time.time()
assert result == 42
assert end - start > 0.1
assert log_has('Throttling throttled_func for 0.10 seconds', caplog)
result = worker._throttle(throttled_func, min_secs=-1)
assert result == 42
def test_throttle_with_assets(mocker, default_conf) -> None:
def throttled_func(nb_assets=-1):
return nb_assets
worker = get_patched_worker(mocker, default_conf)
result = worker._throttle(throttled_func, min_secs=0.1, nb_assets=666)
assert result == 666
result = worker._throttle(throttled_func, min_secs=0.1)
assert result == -1

View File

@ -2,12 +2,11 @@
from functools import reduce
from typing import Any, Callable, Dict, List
from datetime import datetime
import numpy as np
import numpy as np # noqa
import talib.abstract as ta
from pandas import DataFrame
from skopt.space import Categorical, Dimension, Integer, Real
from skopt.space import Categorical, Dimension, Integer, Real # noqa
import freqtrade.vendor.qtpylib.indicators as qtpylib
from freqtrade.optimize.hyperopt_interface import IHyperOpt
@ -34,34 +33,6 @@ class SampleHyperOpts(IHyperOpt):
Sample implementation of these methods can be found in
https://github.com/freqtrade/freqtrade/blob/develop/user_data/hyperopts/sample_hyperopt_advanced.py
"""
@staticmethod
def populate_indicators(dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Add several indicators needed for buy and sell strategies defined below.
"""
# ADX
dataframe['adx'] = ta.ADX(dataframe)
# MACD
macd = ta.MACD(dataframe)
dataframe['macd'] = macd['macd']
dataframe['macdsignal'] = macd['macdsignal']
# MFI
dataframe['mfi'] = ta.MFI(dataframe)
# RSI
dataframe['rsi'] = ta.RSI(dataframe)
# Stochastic Fast
stoch_fast = ta.STOCHF(dataframe)
dataframe['fastd'] = stoch_fast['fastd']
# Minus-DI
dataframe['minus_di'] = ta.MINUS_DI(dataframe)
# Bollinger bands
bollinger = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=2)
dataframe['bb_lowerband'] = bollinger['lower']
dataframe['bb_upperband'] = bollinger['upper']
# SAR
dataframe['sar'] = ta.SAR(dataframe)
return dataframe
@staticmethod
def buy_strategy_generator(params: Dict[str, Any]) -> Callable:

View File

@ -37,6 +37,9 @@ class AdvancedSampleHyperOpts(IHyperOpt):
"""
@staticmethod
def populate_indicators(dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
This method can also be loaded from the strategy, if it doesn't exist in the hyperopt class.
"""
dataframe['adx'] = ta.ADX(dataframe)
macd = ta.MACD(dataframe)
dataframe['macd'] = macd['macd']
@ -229,8 +232,10 @@ class AdvancedSampleHyperOpts(IHyperOpt):
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Based on TA indicators. Should be a copy of from strategy
must align to populate_indicators in this file
Based on TA indicators.
Can be a copy of the corresponding method from the strategy,
or will be loaded from the strategy.
Must align to populate_indicators used (either from this File, or from the strategy)
Only used when --spaces does not include buy
"""
dataframe.loc[
@ -246,8 +251,10 @@ class AdvancedSampleHyperOpts(IHyperOpt):
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Based on TA indicators. Should be a copy of from strategy
must align to populate_indicators in this file
Based on TA indicators.
Can be a copy of the corresponding method from the strategy,
or will be loaded from the strategy.
Must align to populate_indicators used (either from this File, or from the strategy)
Only used when --spaces does not include sell
"""
dataframe.loc[

View File

@ -68,9 +68,7 @@
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"scrolled": true
},
"metadata": {},
"outputs": [],
"source": [
"# Load strategy using values set above\n",
@ -169,6 +167,31 @@
"trades.groupby(\"pair\")[\"sell_reason\"].value_counts()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Analyze the loaded trades for trade parallelism\n",
"This can be useful to find the best `max_open_trades` parameter, when used with backtesting in conjunction with `--disable-max-market-positions`.\n",
"\n",
"`analyze_trade_parallelism()` returns a timeseries dataframe with an \"open_trades\" column, specifying the number of open trades for each candle."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from freqtrade.data.btanalysis import analyze_trade_parallelism\n",
"\n",
"# Analyze the above\n",
"parallel_trades = analyze_trade_parallelism(trades, '5m')\n",
"\n",
"\n",
"parallel_trades.plot()"
]
},
{
"cell_type": "markdown",
"metadata": {},

View File

@ -107,16 +107,16 @@ class SampleStrategy(IStrategy):
# RSI
dataframe['rsi'] = ta.RSI(dataframe)
"""
# ADX
dataframe['adx'] = ta.ADX(dataframe)
"""
# Awesome oscillator
dataframe['ao'] = qtpylib.awesome_oscillator(dataframe)
# Commodity Channel Index: values Oversold:<-100, Overbought:>100
dataframe['cci'] = ta.CCI(dataframe)
"""
# MACD
macd = ta.MACD(dataframe)
dataframe['macd'] = macd['macd']
@ -126,6 +126,7 @@ class SampleStrategy(IStrategy):
# MFI
dataframe['mfi'] = ta.MFI(dataframe)
"""
# Minus Directional Indicator / Movement
dataframe['minus_dm'] = ta.MINUS_DM(dataframe)
dataframe['minus_di'] = ta.MINUS_DI(dataframe)
@ -149,12 +150,13 @@ class SampleStrategy(IStrategy):
stoch = ta.STOCH(dataframe)
dataframe['slowd'] = stoch['slowd']
dataframe['slowk'] = stoch['slowk']
"""
# Stoch fast
stoch_fast = ta.STOCHF(dataframe)
dataframe['fastd'] = stoch_fast['fastd']
dataframe['fastk'] = stoch_fast['fastk']
"""
# Stoch RSI
stoch_rsi = ta.STOCHRSI(dataframe)
dataframe['fastd_rsi'] = stoch_rsi['fastd']
@ -178,12 +180,11 @@ class SampleStrategy(IStrategy):
dataframe['ema50'] = ta.EMA(dataframe, timeperiod=50)
dataframe['ema100'] = ta.EMA(dataframe, timeperiod=100)
# SAR Parabol
dataframe['sar'] = ta.SAR(dataframe)
# SMA - Simple Moving Average
dataframe['sma'] = ta.SMA(dataframe, timeperiod=40)
"""
# SAR Parabol
dataframe['sar'] = ta.SAR(dataframe)
# TEMA - Triple Exponential Moving Average
dataframe['tema'] = ta.TEMA(dataframe, timeperiod=9)