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1
.coveragerc
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@ -3,3 +3,4 @@ omit =
scripts/*
freqtrade/tests/*
freqtrade/vendor/*
freqtrade/__main__.py

169
README.md
View File

@ -22,33 +22,10 @@ expect.
We strongly recommend you to have coding and Python knowledge. Do not
hesitate to read the source code and understand the mechanism of this bot.
## Table of Contents
- [Features](#features)
- [Quick start](#quick-start)
- [Documentations](https://github.com/freqtrade/freqtrade/blob/develop/docs/index.md)
- [Installation](https://github.com/freqtrade/freqtrade/blob/develop/docs/installation.md)
- [Configuration](https://github.com/freqtrade/freqtrade/blob/develop/docs/configuration.md)
- [Strategy Optimization](https://github.com/freqtrade/freqtrade/blob/develop/docs/bot-optimization.md)
- [Backtesting](https://github.com/freqtrade/freqtrade/blob/develop/docs/backtesting.md)
- [Hyperopt](https://github.com/freqtrade/freqtrade/blob/develop/docs/hyperopt.md)
- [Support](#support)
- [Help](#help--slack)
- [Bugs](#bugs--issues)
- [Feature Requests](#feature-requests)
- [Pull Requests](#pull-requests)
- [Basic Usage](#basic-usage)
- [Bot commands](#bot-commands)
- [Telegram RPC commands](#telegram-rpc-commands)
- [Requirements](#requirements)
- [Min hardware required](#min-hardware-required)
- [Software requirements](#software-requirements)
## Branches
The project is currently setup in two main branches:
- `develop` - This branch has often new features, but might also cause
breaking changes.
- `master` - This branch contains the latest stable release. The bot
'should' be stable on this branch, and is generally well tested.
## Exchange marketplaces supported
- [X] [Bittrex](https://bittrex.com/)
- [X] [Binance](https://www.binance.com/)
- [ ] [113 others to tests](https://github.com/ccxt/ccxt/). _(We cannot guarantee they will work)_
## Features
- [x] **Based on Python 3.6+**: For botting on any operating system -
@ -65,74 +42,50 @@ strategy parameters with real exchange data.
- [x] **Daily summary of profit/loss**: Provide a daily summary of your profit/loss.
- [x] **Performance status report**: Provide a performance status of your current trades.
### Exchange marketplaces supported
- [X] [Bittrex](https://bittrex.com/)
- [X] [Binance](https://www.binance.com/)
- [ ] [113 others to tests](https://github.com/ccxt/ccxt/). _(We cannot guarantee they will work)_
## Table of Contents
- [Quick start](#quick-start)
- [Documentations](https://github.com/freqtrade/freqtrade/blob/develop/docs/index.md)
- [Installation](https://github.com/freqtrade/freqtrade/blob/develop/docs/installation.md)
- [Configuration](https://github.com/freqtrade/freqtrade/blob/develop/docs/configuration.md)
- [Strategy Optimization](https://github.com/freqtrade/freqtrade/blob/develop/docs/bot-optimization.md)
- [Backtesting](https://github.com/freqtrade/freqtrade/blob/develop/docs/backtesting.md)
- [Hyperopt](https://github.com/freqtrade/freqtrade/blob/develop/docs/hyperopt.md)
- [Basic Usage](#basic-usage)
- [Bot commands](#bot-commands)
- [Telegram RPC commands](#telegram-rpc-commands)
- [Support](#support)
- [Help](#help--slack)
- [Bugs](#bugs--issues)
- [Feature Requests](#feature-requests)
- [Pull Requests](#pull-requests)
- [Requirements](#requirements)
- [Min hardware required](#min-hardware-required)
- [Software requirements](#software-requirements)
## Quick start
This quick start section is a very short explanation on how to test the
bot in dry-run. We invite you to read the
[bot documentation](https://github.com/freqtrade/freqtrade/blob/develop/docs/index.md)
to ensure you understand how the bot is working.
### Easy installation
The script below will install all dependencies and help you to configure the bot.
```bash
./setup.sh --install
```
### Manual installation
The following steps are made for Linux/MacOS environment
**1. Clone the repo**
Freqtrade provides a Linux/macOS script to install all dependencies and help you to configure the bot.
```bash
git clone git@github.com:freqtrade/freqtrade.git
git checkout develop
cd freqtrade
./setup.sh --install
```
**2. Create the config file**
Switch `"dry_run": true,`
```bash
cp config.json.example config.json
vi config.json
```
**3. Build your docker image and run it**
```bash
docker build -t freqtrade .
docker run --rm -v /etc/localtime:/etc/localtime:ro -v `pwd`/config.json:/freqtrade/config.json -it freqtrade
```
_Windows installation is explained in [Installation doc](https://github.com/freqtrade/freqtrade/blob/develop/docs/installation.md)_
### Help / Slack
For any questions not covered by the documentation or for further
information about the bot, we encourage you to join our slack channel.
- [Click here to join Slack channel](https://join.slack.com/t/highfrequencybot/shared_invite/enQtMjQ5NTM0OTYzMzY3LWMxYzE3M2MxNDdjMGM3ZTYwNzFjMGIwZGRjNTc3ZGU3MGE3NzdmZGMwNmU3NDM5ZTNmM2Y3NjRiNzk4NmM4OGE).
## Documentation
We invite you to read the bot documentation to ensure you understand how the bot is working.
- [Index](https://github.com/freqtrade/freqtrade/blob/develop/docs/index.md)
- [Installation](https://github.com/freqtrade/freqtrade/blob/develop/docs/installation.md)
- [Configuration](https://github.com/freqtrade/freqtrade/blob/develop/docs/configuration.md)
- [Bot usage](https://github.com/freqtrade/freqtrade/blob/develop/docs/bot-usage.md)
- [How to run the bot](https://github.com/freqtrade/freqtrade/blob/develop/docs/bot-usage.md#bot-commands)
- [How to use Backtesting](https://github.com/freqtrade/freqtrade/blob/develop/docs/bot-usage.md#backtesting-commands)
- [How to use Hyperopt](https://github.com/freqtrade/freqtrade/blob/develop/docs/bot-usage.md#hyperopt-commands)
- [Strategy Optimization](https://github.com/freqtrade/freqtrade/blob/develop/docs/bot-optimization.md)
- [Backtesting](https://github.com/freqtrade/freqtrade/blob/develop/docs/backtesting.md)
- [Hyperopt](https://github.com/freqtrade/freqtrade/blob/develop/docs/hyperopt.md)
### [Bugs / Issues](https://github.com/freqtrade/freqtrade/issues?q=is%3Aissue)
If you discover a bug in the bot, please
[search our issue tracker](https://github.com/freqtrade/freqtrade/issues?q=is%3Aissue)
first. If it hasn't been reported, please
[create a new issue](https://github.com/freqtrade/freqtrade/issues/new) and
ensure you follow the template guide so that our team can assist you as
quickly as possible.
### [Feature Requests](https://github.com/freqtrade/freqtrade/labels/enhancement)
Have you a great idea to improve the bot you want to share? Please,
first search if this feature was not [already discussed](https://github.com/freqtrade/freqtrade/labels/enhancement).
If it hasn't been requested, please
[create a new request](https://github.com/freqtrade/freqtrade/issues/new)
and ensure you follow the template guide so that it does not get lost
in the bug reports.
### [Pull Requests](https://github.com/freqtrade/freqtrade/pulls)
Feel like our bot is missing a feature? We welcome your pull requests!
Please read our
[Contributing document](https://github.com/freqtrade/freqtrade/blob/develop/CONTRIBUTING.md)
to understand the requirements before sending your pull-requests.
**Important:** Always create your PR against the `develop` branch, not
`master`.
## Basic Usage
@ -170,10 +123,6 @@ optional arguments:
"tradesv3.dry_run.sqlite" instead of memory DB. Work
only if dry_run is enabled.
```
More details on:
- [How to run the bot](https://github.com/freqtrade/freqtrade/blob/develop/docs/bot-usage.md#bot-commands)
- [How to use Backtesting](https://github.com/freqtrade/freqtrade/blob/develop/docs/bot-usage.md#backtesting-commands)
- [How to use Hyperopt](https://github.com/freqtrade/freqtrade/blob/develop/docs/bot-usage.md#hyperopt-commands)
### Telegram RPC commands
Telegram is not mandatory. However, this is a great way to control your
@ -193,6 +142,48 @@ bot. More details on our
- `/help`: Show help message
- `/version`: Show version
## Development branches
The project is currently setup in two main branches:
- `develop` - This branch has often new features, but might also cause
breaking changes.
- `master` - This branch contains the latest stable release. The bot
'should' be stable on this branch, and is generally well tested.
## Support
### Help / Slack
For any questions not covered by the documentation or for further
information about the bot, we encourage you to join our slack channel.
- [Click here to join Slack channel](https://join.slack.com/t/highfrequencybot/shared_invite/enQtMjQ5NTM0OTYzMzY3LWMxYzE3M2MxNDdjMGM3ZTYwNzFjMGIwZGRjNTc3ZGU3MGE3NzdmZGMwNmU3NDM5ZTNmM2Y3NjRiNzk4NmM4OGE).
### [Bugs / Issues](https://github.com/freqtrade/freqtrade/issues?q=is%3Aissue)
If you discover a bug in the bot, please
[search our issue tracker](https://github.com/freqtrade/freqtrade/issues?q=is%3Aissue)
first. If it hasn't been reported, please
[create a new issue](https://github.com/freqtrade/freqtrade/issues/new) and
ensure you follow the template guide so that our team can assist you as
quickly as possible.
### [Feature Requests](https://github.com/freqtrade/freqtrade/labels/enhancement)
Have you a great idea to improve the bot you want to share? Please,
first search if this feature was not [already discussed](https://github.com/freqtrade/freqtrade/labels/enhancement).
If it hasn't been requested, please
[create a new request](https://github.com/freqtrade/freqtrade/issues/new)
and ensure you follow the template guide so that it does not get lost
in the bug reports.
### [Pull Requests](https://github.com/freqtrade/freqtrade/pulls)
Feel like our bot is missing a feature? We welcome your pull requests!
Please read our
[Contributing document](https://github.com/freqtrade/freqtrade/blob/develop/CONTRIBUTING.md)
to understand the requirements before sending your pull-requests.
**Note** before starting any major new feature work, *please open an issue describing what you are planning to do* or talk to us on [Slack](https://join.slack.com/t/highfrequencybot/shared_invite/enQtMjQ5NTM0OTYzMzY3LWMxYzE3M2MxNDdjMGM3ZTYwNzFjMGIwZGRjNTc3ZGU3MGE3NzdmZGMwNmU3NDM5ZTNmM2Y3NjRiNzk4NmM4OGE). This will ensure that interested parties can give valuable feedback on the feature, and let others know that you are working on it.
**Important:** Always create your PR against the `develop` branch, not
`master`.
## Requirements
### Min hardware required

9
config.json.example
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@ -5,7 +5,11 @@
"fiat_display_currency": "USD",
"ticker_interval" : "5m",
"dry_run": false,
"unfilledtimeout": 600,
"trailing_stop": false,
"unfilledtimeout": {
"buy": 10,
"sell": 30
},
"bid_strategy": {
"ask_last_balance": 0.0
},
@ -31,7 +35,8 @@
},
"experimental": {
"use_sell_signal": false,
"sell_profit_only": false
"sell_profit_only": false,
"ignore_roi_if_buy_signal": false
},
"telegram": {
"enabled": true,

10
config_full.json.example
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@ -5,6 +5,8 @@
"fiat_display_currency": "USD",
"dry_run": false,
"ticker_interval": "5m",
"trailing_stop": false,
"trailing_stop_positive": 0.005,
"minimal_roi": {
"40": 0.0,
"30": 0.01,
@ -12,7 +14,10 @@
"0": 0.04
},
"stoploss": -0.10,
"unfilledtimeout": 600,
"unfilledtimeout": {
"buy": 10,
"sell": 30
},
"bid_strategy": {
"ask_last_balance": 0.0
},
@ -38,7 +43,8 @@
},
"experimental": {
"use_sell_signal": false,
"sell_profit_only": false
"sell_profit_only": false,
"ignore_roi_if_buy_signal": false
},
"telegram": {
"enabled": true,

129
docs/backtesting.md
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@ -1,17 +1,19 @@
# Backtesting
This page explains how to validate your strategy performance by using
Backtesting.
## Table of Contents
- [Test your strategy with Backtesting](#test-your-strategy-with-backtesting)
- [Understand the backtesting result](#understand-the-backtesting-result)
## Test your strategy with Backtesting
Now you have good Buy and Sell strategies, you want to test it against
real data. This is what we call
[backtesting](https://en.wikipedia.org/wiki/Backtesting).
Backtesting will use the crypto-currencies (pair) from your config file
and load static tickers located in
[/freqtrade/tests/testdata](https://github.com/freqtrade/freqtrade/tree/develop/freqtrade/tests/testdata).
@ -19,70 +21,108 @@ If the 5 min and 1 min ticker for the crypto-currencies to test is not
already in the `testdata` folder, backtesting will download them
automatically. Testdata files will not be updated until you specify it.
The result of backtesting will confirm you if your bot as more chance to
make a profit than a loss.
The result of backtesting will confirm you if your bot has better odds of making a profit than a loss.
The backtesting is very easy with freqtrade.
### Run a backtesting against the currencies listed in your config file
**With 5 min tickers (Per default)**
#### With 5 min tickers (Per default)
```bash
python3 ./freqtrade/main.py backtesting --realistic-simulation
```
**With 1 min tickers**
#### With 1 min tickers
```bash
python3 ./freqtrade/main.py backtesting --realistic-simulation --ticker-interval 1m
```
**Update cached pairs with the latest data**
#### Update cached pairs with the latest data
```bash
python3 ./freqtrade/main.py backtesting --realistic-simulation --refresh-pairs-cached
```
**With live data (do not alter your testdata files)**
#### With live data (do not alter your testdata files)
```bash
python3 ./freqtrade/main.py backtesting --realistic-simulation --live
```
**Using a different on-disk ticker-data source**
#### Using a different on-disk ticker-data source
```bash
python3 ./freqtrade/main.py backtesting --datadir freqtrade/tests/testdata-20180101
```
**With a (custom) strategy file**
#### With a (custom) strategy file
```bash
python3 ./freqtrade/main.py -s TestStrategy backtesting
```
Where `-s TestStrategy` refers to the class name within the strategy file `test_strategy.py` found in the `freqtrade/user_data/strategies` directory
**Exporting trades to file**
#### Exporting trades to file
```bash
python3 ./freqtrade/main.py backtesting --export trades
```
**Exporting trades to file specifying a custom filename**
The exported trades can be read using the following code for manual analysis, or can be used by the plotting script `plot_dataframe.py` in the scripts folder.
``` python
import json
from pathlib import Path
import pandas as pd
filename=Path('user_data/backtest_data/backtest-result.json')
with filename.open() as file:
data = json.load(file)
columns = ["pair", "profit", "opents", "closets", "index", "duration",
"open_rate", "close_rate", "open_at_end"]
df = pd.DataFrame(data, columns=columns)
df['opents'] = pd.to_datetime(df['opents'],
unit='s',
utc=True,
infer_datetime_format=True
)
df['closets'] = pd.to_datetime(df['closets'],
unit='s',
utc=True,
infer_datetime_format=True
)
```
#### Exporting trades to file specifying a custom filename
```bash
python3 ./freqtrade/main.py backtesting --export trades --export-filename=backtest_teststrategy.json
```
#### Running backtest with smaller testset
**Running backtest with smaller testset**
Use the `--timerange` argument to change how much of the testset
you want to use. The last N ticks/timeframes will be used.
Example:
```bash
python3 ./freqtrade/main.py backtesting --timerange=-200
```
***Advanced use of timerange***
#### Advanced use of timerange
Doing `--timerange=-200` will get the last 200 timeframes
from your inputdata. You can also specify specific dates,
or a range span indexed by start and stop.
The full timerange specification:
- Use last 123 tickframes of data: `--timerange=-123`
- Use first 123 tickframes of data: `--timerange=123-`
- Use tickframes from line 123 through 456: `--timerange=123-456`
@ -92,11 +132,12 @@ The full timerange specification:
- Use tickframes between POSIX timestamps 1527595200 1527618600:
`--timerange=1527595200-1527618600`
#### Downloading new set of ticker data
**Downloading new set of ticker data**
To download new set of backtesting ticker data, you can use a download script.
If you are using Binance for example:
- create a folder `user_data/data/binance` and copy `pairs.json` in that folder.
- update the `pairs.json` to contain the currency pairs you are interested in.
@ -119,33 +160,55 @@ This will download ticker data for all the currency pairs you defined in `pairs.
- To download ticker data for only 10 days, use `--days 10`.
- Use `--timeframes` to specify which tickers to download. Default is `--timeframes 1m 5m` which will download 1-minute and 5-minute tickers.
For help about backtesting usage, please refer to
[Backtesting commands](#backtesting-commands).
For help about backtesting usage, please refer to [Backtesting commands](#backtesting-commands).
## Understand the backtesting result
The most important in the backtesting is to understand the result.
A backtesting result will look like that:
```
====================== BACKTESTING REPORT ================================
pair buy count avg profit % total profit BTC avg duration
-------- ----------- -------------- ------------------ --------------
ETH/BTC 56 -0.67 -0.00075455 62.3
LTC/BTC 38 -0.48 -0.00036315 57.9
ETC/BTC 42 -1.15 -0.00096469 67.0
DASH/BTC 72 -0.62 -0.00089368 39.9
ZEC/BTC 45 -0.46 -0.00041387 63.2
XLM/BTC 24 -0.88 -0.00041846 47.7
NXT/BTC 24 0.68 0.00031833 40.2
POWR/BTC 35 0.98 0.00064887 45.3
ADA/BTC 43 -0.39 -0.00032292 55.0
XMR/BTC 40 -0.40 -0.00032181 47.4
TOTAL 419 -0.41 -0.00348593 52.9
======================================== BACKTESTING REPORT =========================================
| pair | buy count | avg profit % | total profit BTC | avg duration | profit | loss |
|:---------|------------:|---------------:|-------------------:|---------------:|---------:|-------:|
| ETH/BTC | 44 | 0.18 | 0.00159118 | 50.9 | 44 | 0 |
| LTC/BTC | 27 | 0.10 | 0.00051931 | 103.1 | 26 | 1 |
| ETC/BTC | 24 | 0.05 | 0.00022434 | 166.0 | 22 | 2 |
| DASH/BTC | 29 | 0.18 | 0.00103223 | 192.2 | 29 | 0 |
| ZEC/BTC | 65 | -0.02 | -0.00020621 | 202.7 | 62 | 3 |
| XLM/BTC | 35 | 0.02 | 0.00012877 | 242.4 | 32 | 3 |
| BCH/BTC | 12 | 0.62 | 0.00149284 | 50.0 | 12 | 0 |
| POWR/BTC | 21 | 0.26 | 0.00108215 | 134.8 | 21 | 0 |
| ADA/BTC | 54 | -0.19 | -0.00205202 | 191.3 | 47 | 7 |
| XMR/BTC | 24 | -0.43 | -0.00206013 | 120.6 | 20 | 4 |
| TOTAL | 335 | 0.03 | 0.00175246 | 157.9 | 315 | 20 |
2018-06-13 06:57:27,347 - freqtrade.optimize.backtesting - INFO -
====================================== LEFT OPEN TRADES REPORT ======================================
| pair | buy count | avg profit % | total profit BTC | avg duration | profit | loss |
|:---------|------------:|---------------:|-------------------:|---------------:|---------:|-------:|
| ETH/BTC | 3 | 0.16 | 0.00009619 | 25.0 | 3 | 0 |
| LTC/BTC | 1 | -1.00 | -0.00020118 | 1085.0 | 0 | 1 |
| ETC/BTC | 2 | -1.80 | -0.00071933 | 1092.5 | 0 | 2 |
| DASH/BTC | 0 | nan | 0.00000000 | nan | 0 | 0 |
| ZEC/BTC | 3 | -4.27 | -0.00256826 | 1301.7 | 0 | 3 |
| XLM/BTC | 3 | -1.11 | -0.00066744 | 965.0 | 0 | 3 |
| BCH/BTC | 0 | nan | 0.00000000 | nan | 0 | 0 |
| POWR/BTC | 0 | nan | 0.00000000 | nan | 0 | 0 |
| ADA/BTC | 7 | -3.58 | -0.00503604 | 850.0 | 0 | 7 |
| XMR/BTC | 4 | -3.79 | -0.00303456 | 291.2 | 0 | 4 |
| TOTAL | 23 | -2.63 | -0.01213062 | 750.4 | 3 | 20 |
```
The 1st table will contain all trades the bot made.
The 2nd table will contain all trades the bot had to `forcesell` at the end of the backtest period to prsent a full picture.
These trades are also included in the first table, but are extracted separately for clarity.
The last line will give you the overall performance of your strategy,
here:
```
TOTAL 419 -0.41 -0.00348593 52.9
```
@ -161,6 +224,7 @@ strategy, your sell strategy, and also by the `minimal_roi` and
As for an example if your minimal_roi is only `"0": 0.01`. You cannot
expect the bot to make more profit than 1% (because it will sell every
time a trade will reach 1%).
```json
"minimal_roi": {
"0": 0.01
@ -173,6 +237,7 @@ profit. Hence, keep in mind that your performance is a mix of your
strategies, your configuration, and the crypto-currency you have set up.
## Next step
Great, your strategy is profitable. What if the bot can give your the
optimal parameters to use for your strategy?
Your next step is to learn [how to find optimal parameters with Hyperopt](https://github.com/freqtrade/freqtrade/blob/develop/docs/hyperopt.md)

12
docs/bot-usage.md
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@ -160,13 +160,12 @@ the parameter `-l` or `--live`.
## Hyperopt commands
It is possible to use hyperopt for trading strategy optimization.
Hyperopt uses an internal json config return by `hyperopt_optimize_conf()`
located in `freqtrade/optimize/hyperopt_conf.py`.
To optimize your strategy, you can use hyperopt parameter hyperoptimization
to find optimal parameter values for your stategy.
```
usage: main.py hyperopt [-h] [-i TICKER_INTERVAL] [--realistic-simulation]
[--timerange TIMERANGE] [-e INT] [--use-mongodb]
[--timerange TIMERANGE] [-e INT]
[-s {all,buy,roi,stoploss} [{all,buy,roi,stoploss} ...]]
optional arguments:
@ -176,11 +175,8 @@ optional arguments:
--realistic-simulation
uses max_open_trades from config to simulate real
world limitations
--timerange TIMERANGE
specify what timerange of data to use.
--timerange TIMERANGE specify what timerange of data to use.
-e INT, --epochs INT specify number of epochs (default: 100)
--use-mongodb parallelize evaluations with mongodb (requires mongod
in PATH)
-s {all,buy,roi,stoploss} [{all,buy,roi,stoploss} ...], --spaces {all,buy,roi,stoploss} [{all,buy,roi,stoploss} ...]
Specify which parameters to hyperopt. Space separate
list. Default: all

51
docs/configuration.md
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@ -1,12 +1,15 @@
# Configure the bot
This page explains how to configure your `config.json` file.
## Table of Contents
- [Bot commands](#bot-commands)
- [Backtesting commands](#backtesting-commands)
- [Hyperopt commands](#hyperopt-commands)
## Setup config.json
We recommend to copy and use the `config.json.example` as a template
for your bot configuration.
@ -16,13 +19,16 @@ The table below will list all configuration parameters.
|----------|---------|----------|-------------|
| `max_open_trades` | 3 | Yes | Number of trades open your bot will have.
| `stake_currency` | BTC | Yes | Crypto-currency used for trading.
| `stake_amount` | 0.05 | Yes | Amount of crypto-currency your bot will use for each trade. Per default, the bot will use (0.05 BTC x 3) = 0.15 BTC in total will be always engaged.
| `stake_amount` | 0.05 | Yes | Amount of crypto-currency your bot will use for each trade. Per default, the bot will use (0.05 BTC x 3) = 0.15 BTC in total will be always engaged. Set it to 'unlimited' to allow the bot to use all avaliable balance.
| `ticker_interval` | [1m, 5m, 30m, 1h, 1d] | No | The ticker interval to use (1min, 5 min, 30 min, 1 hour or 1 day). Default is 5 minutes
| `fiat_display_currency` | USD | Yes | Fiat currency used to show your profits. More information below.
| `dry_run` | true | Yes | Define if the bot must be in Dry-run or production mode.
| `minimal_roi` | See below | No | Set the threshold in percent the bot will use to sell a trade. More information below. If set, this parameter will override `minimal_roi` from your strategy file.
| `stoploss` | -0.10 | No | Value of the stoploss in percent used by the bot. More information below. If set, this parameter will override `stoploss` from your strategy file.
| `unfilledtimeout` | 0 | No | How long (in minutes) the bot will wait for an unfilled order to complete, after which the order will be cancelled.
| `trailing_stoploss` | false | No | Enables trailing stop-loss (based on `stoploss` in either configuration or strategy file).
| `trailing_stoploss_positve` | 0 | No | Changes stop-loss once profit has been reached.
| `unfilledtimeout.buy` | 10 | Yes | How long (in minutes) the bot will wait for an unfilled buy order to complete, after which the order will be cancelled.
| `unfilledtimeout.sell` | 10 | Yes | How long (in minutes) the bot will wait for an unfilled sell order to complete, after which the order will be cancelled.
| `bid_strategy.ask_last_balance` | 0.0 | Yes | Set the bidding price. More information below.
| `exchange.name` | bittrex | Yes | Name of the exchange class to use. [List below](#user-content-what-values-for-exchangename).
| `exchange.key` | key | No | API key to use for the exchange. Only required when you are in production mode.
@ -31,6 +37,7 @@ The table below will list all configuration parameters.
| `exchange.pair_blacklist` | [] | No | List of currency the bot must avoid. Useful when using `--dynamic-whitelist` param.
| `experimental.use_sell_signal` | false | No | Use your sell strategy in addition of the `minimal_roi`.
| `experimental.sell_profit_only` | false | No | waits until you have made a positive profit before taking a sell decision.
| `experimental.ignore_roi_if_buy_signal` | false | No | Does not sell if the buy-signal is still active. Takes preference over `minimal_roi` and `use_sell_signal`
| `telegram.enabled` | true | Yes | Enable or not the usage of Telegram.
| `telegram.token` | token | No | Your Telegram bot token. Only required if `telegram.enabled` is `true`.
| `telegram.chat_id` | chat_id | No | Your personal Telegram account id. Only required if `telegram.enabled` is `true`.
@ -40,13 +47,22 @@ The table below will list all configuration parameters.
| `strategy_path` | null | No | Adds an additional strategy lookup path (must be a folder).
| `internals.process_throttle_secs` | 5 | Yes | Set the process throttle. Value in second.
The definition of each config parameters is in
[misc.py](https://github.com/freqtrade/freqtrade/blob/develop/freqtrade/misc.py#L205).
The definition of each config parameters is in [misc.py](https://github.com/freqtrade/freqtrade/blob/develop/freqtrade/misc.py#L205).
### Understand stake_amount
`stake_amount` is an amount of crypto-currency your bot will use for each trade.
The minimal value is 0.0005. If there is not enough crypto-currency in
the account an exception is generated.
To allow the bot to trade all the avaliable `stake_currency` in your account set `stake_amount` = `unlimited`.
In this case a trade amount is calclulated as `currency_balanse / (max_open_trades - current_open_trades)`.
### Understand minimal_roi
`minimal_roi` is a JSON object where the key is a duration
in minutes and the value is the minimum ROI in percent.
See the example below:
```
"minimal_roi": {
"40": 0.0, # Sell after 40 minutes if the profit is not negative
@ -61,6 +77,7 @@ value. This parameter is optional. If you use it, it will take over the
`minimal_roi` value from the strategy file.
### Understand stoploss
`stoploss` is loss in percentage that should trigger a sale.
For example value `-0.10` will cause immediate sell if the
profit dips below -10% for a given trade. This parameter is optional.
@ -69,56 +86,70 @@ Most of the strategy files already include the optimal `stoploss`
value. This parameter is optional. If you use it, it will take over the
`stoploss` value from the strategy file.
### Understand trailing stoploss
Go to the [trailing stoploss Documentation](stoploss.md) for details on trailing stoploss.
### Understand initial_state
`initial_state` is an optional field that defines the initial application state.
Possible values are `running` or `stopped`. (default=`running`)
If the value is `stopped` the bot has to be started with `/start` first.
### Understand process_throttle_secs
`process_throttle_secs` is an optional field that defines in seconds how long the bot should wait
before asking the strategy if we should buy or a sell an asset. After each wait period, the strategy is asked again for
every opened trade wether or not we should sell, and for all the remaining pairs (either the dynamic list of pairs or
the static list of pairs) if we should buy.
### Understand ask_last_balance
`ask_last_balance` sets the bidding price. Value `0.0` will use `ask` price, `1.0` will
use the `last` price and values between those interpolate between ask and last
price. Using `ask` price will guarantee quick success in bid, but bot will also
end up paying more then would probably have been necessary.
### What values for exchange.name?
Freqtrade is based on [CCXT library](https://github.com/ccxt/ccxt) that supports 115 cryptocurrency
exchange markets and trading APIs. The complete up-to-date list can be found in the
[CCXT repo homepage](https://github.com/ccxt/ccxt/tree/master/python). However, the bot was tested
with only Bittrex and Binance.
The bot was tested with the following exchanges:
- [Bittrex](https://bittrex.com/): "bittrex"
- [Binance](https://www.binance.com/): "binance"
Feel free to test other exchanges and submit your PR to improve the bot.
### What values for fiat_display_currency?
`fiat_display_currency` set the base currency to use for the conversion from coin to fiat in Telegram.
The valid values are: "AUD", "BRL", "CAD", "CHF", "CLP", "CNY", "CZK", "DKK", "EUR", "GBP", "HKD", "HUF", "IDR", "ILS", "INR", "JPY", "KRW", "MXN", "MYR", "NOK", "NZD", "PHP", "PKR", "PLN", "RUB", "SEK", "SGD", "THB", "TRY", "TWD", "ZAR", "USD".
In addition to central bank currencies, a range of cryto currencies are supported.
The valid values are: "BTC", "ETH", "XRP", "LTC", "BCH", "USDT".
## Switch to dry-run mode
We recommend starting the bot in dry-run mode to see how your bot will
behave and how is the performance of your strategy. In Dry-run mode the
bot does not engage your money. It only runs a live simulation without
creating trades.
### To switch your bot in Dry-run mode:
1. Edit your `config.json` file
2. Switch dry-run to true and specify db_url for a persistent db
```json
"dry_run": true,
"db_url": "sqlite///tradesv3.dryrun.sqlite",
```
3. Remove your Exchange API key (change them by fake api credentials)
```json
"exchange": {
"name": "bittrex",
@ -132,19 +163,23 @@ Once you will be happy with your bot performance, you can switch it to
production mode.
## Switch to production mode
In production mode, the bot will engage your money. Be careful a wrong
strategy can lose all your money. Be aware of what you are doing when
you run it in production mode.
### To switch your bot in production mode:
1. Edit your `config.json` file
2. Switch dry-run to false and don't forget to adapt your database URL if set
```json
"dry_run": false,
```
3. Insert your Exchange API key (change them by fake api keys)
```json
"exchange": {
"name": "bittrex",
@ -152,10 +187,10 @@ you run it in production mode.
"secret": "08a9dc6db3d7b53e1acebd9275677f4b0a04f1a5",
...
}
```
If you have not your Bittrex API key yet,
[see our tutorial](https://github.com/freqtrade/freqtrade/blob/develop/docs/pre-requisite.md).
If you have not your Bittrex API key yet, [see our tutorial](https://github.com/freqtrade/freqtrade/blob/develop/docs/pre-requisite.md).
## Next step
Now you have configured your config.json, the next step is to
[start your bot](https://github.com/freqtrade/freqtrade/blob/develop/docs/bot-usage.md).
Now you have configured your config.json, the next step is to [start your bot](https://github.com/freqtrade/freqtrade/blob/develop/docs/bot-usage.md).

334
docs/hyperopt.md
View File

@ -1,156 +1,114 @@
# Hyperopt
This page explains how to tune your strategy by finding the optimal
parameters with Hyperopt.
parameters, a process called hyperparameter optimization. The bot uses several
algorithms included in the `scikit-optimize` package to accomplish this. The
search will burn all your CPU cores, make your laptop sound like a fighter jet
and still take a long time.
## Table of Contents
- [Prepare your Hyperopt](#prepare-hyperopt)
- [1. Configure your Guards and Triggers](#1-configure-your-guards-and-triggers)
- [2. Update the hyperopt config file](#2-update-the-hyperopt-config-file)
- [Advanced Hyperopt notions](#advanced-notions)
- [Understand the Guards and Triggers](#understand-the-guards-and-triggers)
- [Configure your Guards and Triggers](#configure-your-guards-and-triggers)
- [Solving a Mystery](#solving-a-mystery)
- [Adding New Indicators](#adding-new-indicators)
- [Execute Hyperopt](#execute-hyperopt)
- [Hyperopt with MongoDB](#hyperopt-with-mongoDB)
- [Understand the hyperopts result](#understand-the-backtesting-result)
## Prepare Hyperopt
Before we start digging in Hyperopt, we recommend you to take a look at
your strategy file located into [user_data/strategies/](https://github.com/freqtrade/freqtrade/blob/develop/user_data/strategies/test_strategy.py)
## Prepare Hyperopting
We recommend you start by taking a look at `hyperopt.py` file located in [freqtrade/optimize](https://github.com/freqtrade/freqtrade/blob/develop/freqtrade/optimize/hyperopt.py)
### 1. Configure your Guards and Triggers
There are two places you need to change in your strategy file to add a
new buy strategy for testing:
- Inside [populate_buy_trend()](https://github.com/freqtrade/freqtrade/blob/develop/user_data/strategies/test_strategy.py#L278-L294).
- Inside [hyperopt_space()](https://github.com/freqtrade/freqtrade/blob/develop/user_data/strategies/test_strategy.py#L244-L297) known as `SPACE`.
### Configure your Guards and Triggers
There are two places you need to change to add a new buy strategy for testing:
- Inside [populate_buy_trend()](https://github.com/freqtrade/freqtrade/blob/develop/freqtrade/optimize/hyperopt.py#L278-L294).
- Inside [hyperopt_space()](https://github.com/freqtrade/freqtrade/blob/develop/freqtrade/optimize/hyperopt.py#L218-L229)
and the associated methods `indicator_space`, `roi_space`, `stoploss_space`.
There you have two different type of indicators: 1. `guards` and 2.
`triggers`.
1. Guards are conditions like "never buy if ADX < 10", or never buy if
current price is over EMA10.
There you have two different type of indicators: 1. `guards` and 2. `triggers`.
1. Guards are conditions like "never buy if ADX < 10", or "never buy if
current price is over EMA10".
2. Triggers are ones that actually trigger buy in specific moment, like
"buy when EMA5 crosses over EMA10" or buy when close price touches lower
bollinger band.
"buy when EMA5 crosses over EMA10" or "buy when close price touches lower
bollinger band".
HyperOpt will, for each eval round, pick just ONE trigger, and possibly
multiple guards. So that the constructed strategy will be something like
Hyperoptimization will, for each eval round, pick one trigger and possibly
multiple guards. The constructed strategy will be something like
"*buy exactly when close price touches lower bollinger band, BUT only if
ADX > 10*".
If you have updated the buy strategy, means change the content of
If you have updated the buy strategy, ie. changed the contents of
`populate_buy_trend()` method you have to update the `guards` and
`triggers` hyperopts must used.
`triggers` hyperopts must use.
## Solving a Mystery
Let's say you are curious: should you use MACD crossings or lower Bollinger
Bands to trigger your buys. And you also wonder should you use RSI or ADX to
help with those buy decisions. If you decide to use RSI or ADX, which values
should I use for them? So let's use hyperparameter optimization to solve this
mystery.
We will start by defining a search space:
```
def indicator_space() -> List[Dimension]:
"""
Define your Hyperopt space for searching strategy parameters
"""
return [
Integer(20, 40, name='adx-value'),
Integer(20, 40, name='rsi-value'),
Categorical([True, False], name='adx-enabled'),
Categorical([True, False], name='rsi-enabled'),
Categorical(['bb_lower', 'macd_cross_signal'], name='trigger')
]
```
Above definition says: I have five parameters I want you to randomly combine
to find the best combination. Two of them are integer values (`adx-value`
and `rsi-value`) and I want you test in the range of values 20 to 40.
Then we have three category variables. First two are either `True` or `False`.
We use these to either enable or disable the ADX and RSI guards. The last
one we call `trigger` and use it to decide which buy trigger we want to use.
So let's write the buy strategy using these values:
```
def populate_buy_trend(dataframe: DataFrame) -> DataFrame:
conditions = []
# GUARDS AND TRENDS
if 'adx-enabled' in params and params['adx-enabled']:
conditions.append(dataframe['adx'] > params['adx-value'])
if 'rsi-enabled' in params and params['rsi-enabled']:
conditions.append(dataframe['rsi'] < params['rsi-value'])
# TRIGGERS
if params['trigger'] == 'bb_lower':
conditions.append(dataframe['close'] < dataframe['bb_lowerband'])
if params['trigger'] == 'macd_cross_signal':
conditions.append(qtpylib.crossed_above(
dataframe['macd'], dataframe['macdsignal']
))
As for an example if your `populate_buy_trend()` method is:
```python
def populate_buy_trend(dataframe: DataFrame) -> DataFrame:
dataframe.loc[
(dataframe['rsi'] < 35) &
(dataframe['adx'] > 65),
reduce(lambda x, y: x & y, conditions),
'buy'] = 1
return dataframe
return populate_buy_trend
```
Your hyperopt file must contain `guards` to find the right value for
`(dataframe['adx'] > 65)` & and `(dataframe['plus_di'] > 0.5)`. That
means you will need to enable/disable triggers.
Hyperopting will now call this `populate_buy_trend` as many times you ask it (`epochs`)
with different value combinations. It will then use the given historical data and make
buys based on the buy signals generated with the above function and based on the results
it will end with telling you which paramter combination produced the best profits.
In our case the `SPACE` and `populate_buy_trend` in your strategy file
will look like:
```python
space = {
'rsi': hp.choice('rsi', [
{'enabled': False},
{'enabled': True, 'value': hp.quniform('rsi-value', 20, 40, 1)}
]),
'adx': hp.choice('adx', [
{'enabled': False},
{'enabled': True, 'value': hp.quniform('adx-value', 15, 50, 1)}
]),
'trigger': hp.choice('trigger', [
{'type': 'lower_bb'},
{'type': 'faststoch10'},
{'type': 'ao_cross_zero'},
{'type': 'ema5_cross_ema10'},
{'type': 'macd_cross_signal'},
{'type': 'sar_reversal'},
{'type': 'stochf_cross'},
{'type': 'ht_sine'},
]),
}
The search for best parameters starts with a few random combinations and then uses a
regressor algorithm (currently ExtraTreesRegressor) to quickly find a parameter combination
that minimizes the value of the objective function `calculate_loss` in `hyperopt.py`.
...
def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
conditions = []
# GUARDS AND TRENDS
if params['adx']['enabled']:
conditions.append(dataframe['adx'] > params['adx']['value'])
if params['rsi']['enabled']:
conditions.append(dataframe['rsi'] < params['rsi']['value'])
# TRIGGERS
triggers = {
'lower_bb': dataframe['tema'] <= dataframe['blower'],
'faststoch10': (crossed_above(dataframe['fastd'], 10.0)),
'ao_cross_zero': (crossed_above(dataframe['ao'], 0.0)),
'ema5_cross_ema10': (crossed_above(dataframe['ema5'], dataframe['ema10'])),
'macd_cross_signal': (crossed_above(dataframe['macd'], dataframe['macdsignal'])),
'sar_reversal': (crossed_above(dataframe['close'], dataframe['sar'])),
'stochf_cross': (crossed_above(dataframe['fastk'], dataframe['fastd'])),
'ht_sine': (crossed_above(dataframe['htleadsine'], dataframe['htsine'])),
}
...
```
### 2. Update the hyperopt config file
Hyperopt is using a dedicated config file. Currently hyperopt
cannot use your config file. It is also made on purpose to allow you
testing your strategy with different configurations.
The Hyperopt configuration is located in
[user_data/hyperopt_conf.py](https://github.com/freqtrade/freqtrade/blob/develop/user_data/hyperopt_conf.py).
## Advanced notions
### Understand the Guards and Triggers
When you need to add the new guards and triggers to be hyperopt
parameters, you do this by adding them into the [hyperopt_space()](https://github.com/freqtrade/freqtrade/blob/develop/user_data/strategies/test_strategy.py#L244-L297).
If it's a trigger, you add one line to the 'trigger' choice group and that's it.
If it's a guard, you will add a line like this:
```
'rsi': hp.choice('rsi', [
{'enabled': False},
{'enabled': True, 'value': hp.quniform('rsi-value', 20, 40, 1)}
]),
```
This says, "*one of the guards is RSI, it can have two values, enabled or
disabled. If it is enabled, try different values for it between 20 and 40*".
So, the part of the strategy builder using the above setting looks like
this:
```
if params['rsi']['enabled']:
conditions.append(dataframe['rsi'] < params['rsi']['value'])
```
It checks if Hyperopt wants the RSI guard to be enabled for this
round `params['rsi']['enabled']` and if it is, then it will add a
condition that says RSI must be smaller than the value hyperopt picked
for this evaluation, which is given in the `params['rsi']['value']`.
That's it. Now you can add new parts of strategies to Hyperopt and it
will try all the combinations with all different values in the search
for best working algo.
### Add a new Indicators
If you want to test an indicator that isn't used by the bot currently,
you need to add it to the `populate_indicators()` method in `hyperopt.py`.
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`.
## Execute Hyperopt
Once you have updated your hyperopt configuration you can run it.
@ -165,12 +123,12 @@ python3 ./freqtrade/main.py -c config.json hyperopt -e 5000
The `-e` flag will set how many evaluations hyperopt will do. We recommend
running at least several thousand evaluations.
### Execute hyperopt with different ticker-data source
### Execute Hyperopt with Different Ticker-Data Source
If you would like to hyperopt parameters using an alternate ticker data that
you have on-disk, use the `--datadir PATH` option. Default hyperopt will
use data from directory `user_data/data`.
### Running hyperopt with smaller testset
### Running Hyperopt with Smaller Testset
Use the `--timeperiod` argument to change how much of the testset
you want to use. The last N ticks/timeframes will be used.
Example:
@ -179,7 +137,7 @@ Example:
python3 ./freqtrade/main.py hyperopt --timeperiod -200
```
### Running hyperopt with smaller search space
### Running Hyperopt with Smaller Search Space
Use the `--spaces` argument to limit the search space used by hyperopt.
Letting Hyperopt optimize everything is a huuuuge search space. Often it
might make more sense to start by just searching for initial buy algorithm.
@ -194,122 +152,44 @@ Legal values are:
- `stoploss`: search for the best stoploss value
- space-separated list of any of the above values for example `--spaces roi stoploss`
### Hyperopt with MongoDB
Hyperopt with MongoDB, is like Hyperopt under steroids. As you saw by
executing the previous command is the execution takes a long time.
To accelerate it you can use hyperopt with MongoDB.
## Understand the Hyperopts Result
Once Hyperopt is completed you can use the result to create a new strategy.
Given the following result from hyperopt:
To run hyperopt with MongoDb you will need 3 terminals.
**Terminal 1: Start MongoDB**
```bash
cd <freqtrade>
source .env/bin/activate
python3 scripts/start-mongodb.py
```
**Terminal 2: Start Hyperopt worker**
```bash
cd <freqtrade>
source .env/bin/activate
python3 scripts/start-hyperopt-worker.py
```
**Terminal 3: Start Hyperopt with MongoDB**
```bash
cd <freqtrade>
source .env/bin/activate
python3 ./freqtrade/main.py -c config.json hyperopt --use-mongodb
```
**Re-run an Hyperopt**
To re-run Hyperopt you have to delete the existing MongoDB table.
```bash
cd <freqtrade>
rm -rf .hyperopt/mongodb/
```
## Understand the hyperopts result
Once Hyperopt is completed you can use the result to adding new buy
signal. Given following result from hyperopt:
```
Best parameters:
{
"adx": {
"enabled": true,
"value": 15.0
},
"fastd": {
"enabled": true,
"value": 40.0
},
"green_candle": {
"enabled": true
},
"mfi": {
"enabled": false
},
"over_sar": {
"enabled": false
},
"rsi": {
"enabled": true,
"value": 37.0
},
"trigger": {
"type": "lower_bb"
},
"uptrend_long_ema": {
"enabled": true
},
"uptrend_short_ema": {
"enabled": false
},
"uptrend_sma": {
"enabled": false
}
}
Best Result:
2197 trades. Avg profit 1.84%. Total profit 0.79367541 BTC. Avg duration 241.0 mins.
Best result:
135 trades. Avg profit 0.57%. Total profit 0.03871918 BTC (0.7722Σ%). Avg duration 180.4 mins.
with values:
{'adx-value': 44, 'rsi-value': 29, 'adx-enabled': False, 'rsi-enabled': True, 'trigger': 'bb_lower'}
```
You should understand this result like:
- You should **consider** the guard "adx" (`"adx"` is `"enabled": true`)
and the best value is `15.0` (`"value": 15.0,`)
- You should **consider** the guard "fastd" (`"fastd"` is `"enabled":
true`) and the best value is `40.0` (`"value": 40.0,`)
- You should **consider** to enable the guard "green_candle"
(`"green_candle"` is `"enabled": true`) but this guards as no
customizable value.
- You should **ignore** the guard "mfi" (`"mfi"` is `"enabled": false`)
- and so on...
- The buy trigger that worked best was `bb_lower`.
- You should not use ADX because `adx-enabled: False`)
- You should **consider** using the RSI indicator (`rsi-enabled: True` and the best value is `29.0` (`rsi-value: 29.0`)
You have to look inside your strategy file into `buy_strategy_generator()`
method, what those values match to.
So for example you had `adx:` with the `value: 15.0` so we would look
at `adx`-block, that translates to the following code block:
So for example you had `rsi-value: 29.0` so we would look
at `rsi`-block, that translates to the following code block:
```
(dataframe['adx'] > 15.0)
(dataframe['rsi'] < 29.0)
```
Translating your whole hyperopt result to as the new buy-signal
would be the following:
Translating your whole hyperopt result as the new buy-signal
would then look like:
```
def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
dataframe.loc[
(
(dataframe['adx'] > 15.0) & # adx-value
(dataframe['fastd'] < 40.0) & # fastd-value
(dataframe['close'] > dataframe['open']) & # green_candle
(dataframe['rsi'] < 37.0) & # rsi-value
(dataframe['ema50'] > dataframe['ema100']) # uptrend_long_ema
(dataframe['rsi'] < 29.0) & # rsi-value
dataframe['close'] < dataframe['bb_lowerband'] # trigger
),
'buy'] = 1
return dataframe
```
## Next step
## Next Step
Now you have a perfect bot and want to control it from Telegram. Your
next step is to learn the [Telegram usage](https://github.com/freqtrade/freqtrade/blob/develop/docs/telegram-usage.md).

2
docs/index.md
View File

@ -1,4 +1,5 @@
# freqtrade documentation
Welcome to freqtrade documentation. Please feel free to contribute to
this documentation if you see it became outdated by sending us a
Pull-request. Do not hesitate to reach us on
@ -6,6 +7,7 @@ Pull-request. Do not hesitate to reach us on
if you do not find the answer to your questions.
## Table of Contents
- [Pre-requisite](https://github.com/freqtrade/freqtrade/blob/develop/docs/pre-requisite.md)
- [Setup your Bittrex account](https://github.com/freqtrade/freqtrade/blob/develop/docs/pre-requisite.md#setup-your-bittrex-account)
- [Setup your Telegram bot](https://github.com/freqtrade/freqtrade/blob/develop/docs/pre-requisite.md#setup-your-telegram-bot)

71
docs/installation.md
View File

@ -8,6 +8,7 @@ To understand how to set up the bot please read the [Bot Configuration](https://
* [Table of Contents](#table-of-contents)
* [Easy Installation - Linux Script](#easy-installation---linux-script)
* [Manual installation](#manual-installation)
* [Automatic Installation - Docker](#automatic-installation---docker)
* [Custom Linux MacOS Installation](#custom-installation)
- [Requirements](#requirements)
@ -55,6 +56,28 @@ Reset parameter will hard reset your branch (only if you are on `master` or `dev
Config parameter is a `config.json` configurator. This script will ask you questions to setup your bot and create your `config.json`.
## Manual installation - Linux/MacOS
The following steps are made for Linux/MacOS environment
**1. Clone the repo**
```bash
git clone git@github.com:freqtrade/freqtrade.git
git checkout develop
cd freqtrade
```
**2. Create the config file**
Switch `"dry_run": true,`
```bash
cp config.json.example config.json
vi config.json
```
**3. Build your docker image and run it**
```bash
docker build -t freqtrade .
docker run --rm -v /etc/localtime:/etc/localtime:ro -v `pwd`/config.json:/freqtrade/config.json -it freqtrade
```
------
## Automatic Installation - Docker
@ -184,6 +207,26 @@ docker start freqtrade
You do not need to rebuild the image for configuration changes, it will suffice to edit `config.json` and restart the container.
### 7. Backtest with docker
The following assumes that the above steps (1-4) have been completed successfully.
Also, backtest-data should be available at `~/.freqtrade/user_data/`.
``` bash
docker run -d \
--name freqtrade \
-v /etc/localtime:/etc/localtime:ro \
-v ~/.freqtrade/config.json:/freqtrade/config.json \
-v ~/.freqtrade/tradesv3.sqlite:/freqtrade/tradesv3.sqlite \
-v ~/.freqtrade/user_data/:/freqtrade/user_data/ \
freqtrade --strategy AwsomelyProfitableStrategy backtesting
```
Head over to the [Backtesting Documentation](https://github.com/freqtrade/freqtrade/blob/develop/docs/backtesting.md) for more details.
*Note*: Additional parameters can be appended after the image name (`freqtrade` in the above example).
------
## Custom Installation
@ -225,17 +268,7 @@ cd ..
rm -rf ./ta-lib*
```
#### 3. [Optional] Install MongoDB
Install MongoDB if you plan to optimize your strategy with Hyperopt.
```bash
sudo apt-get install mongodb-org
```
> Complete tutorial from Digital Ocean: [How to Install MongoDB on Ubuntu 16.04](https://www.digitalocean.com/community/tutorials/how-to-install-mongodb-on-ubuntu-16-04).
#### 4. Install FreqTrade
#### 3. Install FreqTrade
Clone the git repository:
@ -243,7 +276,7 @@ Clone the git repository:
git clone https://github.com/freqtrade/freqtrade.git
```
#### 5. Configure `freqtrade` as a `systemd` service
#### 4. Configure `freqtrade` as a `systemd` service
From the freqtrade repo... copy `freqtrade.service` to your systemd user directory (usually `~/.config/systemd/user`) and update `WorkingDirectory` and `ExecStart` to match your setup.
@ -267,19 +300,7 @@ sudo loginctl enable-linger "$USER"
brew install python3 git wget ta-lib
```
#### 2. [Optional] Install MongoDB
Install MongoDB if you plan to optimize your strategy with Hyperopt.
```bash
curl -O https://fastdl.mongodb.org/osx/mongodb-osx-ssl-x86_64-3.4.10.tgz
tar -zxvf mongodb-osx-ssl-x86_64-3.4.10.tgz
mkdir -p <path_freqtrade>/env/mongodb
cp -R -n mongodb-osx-x86_64-3.4.10/ <path_freqtrade>/env/mongodb
export PATH=<path_freqtrade>/env/mongodb/bin:$PATH
```
#### 3. Install FreqTrade
#### 2. Install FreqTrade
Clone the git repository:

48
docs/stoploss.md Normal file
View File

@ -0,0 +1,48 @@
# Stop Loss support
At this stage the bot contains the following stoploss support modes:
1. static stop loss, defined in either the strategy or configuration
2. trailing stop loss, defined in the configuration
3. trailing stop loss, custom positive loss, defined in configuration
## Static Stop Loss
This is very simple, basically you define a stop loss of x in your strategy file or alternative in the configuration, which
will overwrite the strategy definition. This will basically try to sell your asset, the second the loss exceeds the defined loss.
## Trail Stop Loss
The initial value for this stop loss, is defined in your strategy or configuration. Just as you would define your Stop Loss normally.
To enable this Feauture all you have to do is to define the configuration element:
``` json
"trailing_stop" : True
```
This will now activate an algorithm, which automatically moves your stop loss up every time the price of your asset increases.
For example, simplified math,
* you buy an asset at a price of 100$
* your stop loss is defined at 2%
* which means your stop loss, gets triggered once your asset dropped below 98$
* assuming your asset now increases to 102$
* your stop loss, will now be 2% of 102$ or 99.96$
* now your asset drops in value to 101$, your stop loss, will still be 99.96$
basically what this means is that your stop loss will be adjusted to be always be 2% of the highest observed price
### Custom positive loss
Due to demand, it is possible to have a default stop loss, when you are in the red with your buy, but once your buy turns positive,
the system will utilize a new stop loss, which can be a different value. For example your default stop loss is 5%, but once you are in the
black, it will be changed to be only a 1% stop loss
This can be configured in the main configuration file and requires `"trailing_stop": true` to be set to true.
``` json
"trailing_stop_positive": 0.01,
```
The 0.01 would translate to a 1% stop loss, once you hit profit.

2
freqtrade/__init__.py
View File

@ -1,5 +1,5 @@
""" FreqTrade bot """
__version__ = '0.17.0'
__version__ = '0.17.1'
class DependencyException(BaseException):

2
freqtrade/__main__.py
View File

@ -7,8 +7,8 @@ To launch Freqtrade as a module
"""
import sys
from freqtrade import main
from freqtrade import main
if __name__ == '__main__':
main.set_loggers()

85
freqtrade/analyze.py
View File

@ -10,9 +10,9 @@ import arrow
from pandas import DataFrame, to_datetime
from freqtrade import constants
from freqtrade.exchange import get_ticker_history
from freqtrade.exchange import Exchange
from freqtrade.persistence import Trade
from freqtrade.strategy.resolver import StrategyResolver, IStrategy
from freqtrade.strategy.resolver import IStrategy, StrategyResolver
logger = logging.getLogger(__name__)
@ -98,7 +98,14 @@ class Analyze(object):
"""
return self.strategy.ticker_interval
def analyze_ticker(self, ticker_history: List[Dict], pair: str) -> DataFrame:
def get_stoploss(self) -> float:
"""
Return stoploss to use
:return: Strategy stoploss value to use
"""
return self.strategy.stoploss
def analyze_ticker(self, ticker_history: List[Dict]) -> DataFrame:
"""
Parses the given ticker history and returns a populated DataFrame
add several TA indicators and buy signal to it
@ -111,14 +118,14 @@ class Analyze(object):
dataframe = self.populate_sell_trend(dataframe, pair)
return dataframe
def get_signal(self, pair: str, interval: str) -> Tuple[bool, bool]:
def get_signal(self, exchange: Exchange, pair: str, interval: str) -> Tuple[bool, bool]:
"""
Calculates current signal based several technical analysis indicators
:param pair: pair in format ANT/BTC
:param interval: Interval to use (in min)
:return: (Buy, Sell) A bool-tuple indicating buy/sell signal
"""
ticker_hist = get_ticker_history(pair, interval)
ticker_hist = exchange.get_ticker_history(pair, interval)
if not ticker_hist:
logger.warning('Empty ticker history for pair %s', pair)
return False, False
@ -149,7 +156,7 @@ class Analyze(object):
# Check if dataframe is out of date
signal_date = arrow.get(latest['date'])
interval_minutes = constants.TICKER_INTERVAL_MINUTES[interval]
if signal_date < arrow.utcnow() - timedelta(minutes=(interval_minutes + 5)):
if signal_date < (arrow.utcnow() - timedelta(minutes=(interval_minutes + 5))):
logger.warning(
'Outdated history for pair %s. Last tick is %s minutes old',
pair,
@ -173,33 +180,79 @@ class Analyze(object):
if the threshold is reached and updates the trade record.
:return: True if trade should be sold, False otherwise
"""
current_profit = trade.calc_profit_percent(rate)
if self.stop_loss_reached(current_rate=rate, trade=trade, current_time=date):
return True
experimental = self.config.get('experimental', {})
if buy and experimental.get('ignore_roi_if_buy_signal', False):
logger.debug('Buy signal still active - not selling.')
return False
# Check if minimal roi has been reached and no longer in buy conditions (avoiding a fee)
if self.min_roi_reached(trade=trade, current_rate=rate, current_time=date):
if self.min_roi_reached(trade=trade, current_profit=current_profit, current_time=date):
logger.debug('Required profit reached. Selling..')
return True
# Experimental: Check if the trade is profitable before selling it (avoid selling at loss)
if self.config.get('experimental', {}).get('sell_profit_only', False):
if experimental.get('sell_profit_only', False):
logger.debug('Checking if trade is profitable..')
if trade.calc_profit(rate=rate) <= 0:
return False
if sell and not buy and self.config.get('experimental', {}).get('use_sell_signal', False):
if sell and not buy and experimental.get('use_sell_signal', False):
logger.debug('Sell signal received. Selling..')
return True
return False
def min_roi_reached(self, trade: Trade, current_rate: float, current_time: datetime) -> bool:
def stop_loss_reached(self, current_rate: float, trade: Trade, current_time: datetime) -> bool:
"""
Based on current profit of the trade and configured (trailing) stoploss,
decides to sell or not
"""
current_profit = trade.calc_profit_percent(current_rate)
trailing_stop = self.config.get('trailing_stop', False)
trade.adjust_stop_loss(trade.open_rate, self.strategy.stoploss, initial=True)
# evaluate if the stoploss was hit
if self.strategy.stoploss is not None and trade.stop_loss >= current_rate:
if trailing_stop:
logger.debug(
f"HIT STOP: current price at {current_rate:.6f}, "
f"stop loss is {trade.stop_loss:.6f}, "
f"initial stop loss was at {trade.initial_stop_loss:.6f}, "
f"trade opened at {trade.open_rate:.6f}")
logger.debug(f"trailing stop saved {trade.stop_loss - trade.initial_stop_loss:.6f}")
logger.debug('Stop loss hit.')
return True
# update the stop loss afterwards, after all by definition it's supposed to be hanging
if trailing_stop:
# check if we have a special stop loss for positive condition
# and if profit is positive
stop_loss_value = self.strategy.stoploss
if 'trailing_stop_positive' in self.config and current_profit > 0:
# Ignore mypy error check in configuration that this is a float
stop_loss_value = self.config.get('trailing_stop_positive') # type: ignore
logger.debug(f"using positive stop loss mode: {stop_loss_value} "
f"since we have profit {current_profit}")
trade.adjust_stop_loss(current_rate, stop_loss_value)
return False
def min_roi_reached(self, trade: Trade, current_profit: float, current_time: datetime) -> bool:
"""
Based an earlier trade and current price and ROI configuration, decides whether bot should
sell
:return True if bot should sell at current rate
"""
current_profit = trade.calc_profit_percent(current_rate)
if self.strategy.stoploss is not None and current_profit < self.strategy.stoploss:
logger.debug('Stop loss hit.')
return True
# Check if time matches and current rate is above threshold
time_diff = (current_time.timestamp() - trade.open_date.timestamp()) / 60

28
freqtrade/arguments.py
View File

@ -2,12 +2,13 @@
This module contains the argument manager class
"""
import os
import argparse
import logging
import os
import re
from typing import List, NamedTuple, Optional
import arrow
from typing import List, Optional, NamedTuple
from freqtrade import __version__, constants
@ -203,12 +204,6 @@ class Arguments(object):
type=int,
metavar='INT',
)
parser.add_argument(
'--use-mongodb',
help='parallelize evaluations with mongodb (requires mongod in PATH)',
dest='mongodb',
action='store_true',
)
parser.add_argument(
'-s', '--spaces',
help='Specify which parameters to hyperopt. Space separate list. \
@ -268,17 +263,15 @@ class Arguments(object):
stop: int = 0
if stype[0]:
starts = rvals[index]
if stype[0] == 'date':
start = int(starts) if len(starts) == 10 \
else arrow.get(starts, 'YYYYMMDD').timestamp
if stype[0] == 'date' and len(starts) == 8:
start = arrow.get(starts, 'YYYYMMDD').timestamp
else:
start = int(starts)
index += 1
if stype[1]:
stops = rvals[index]
if stype[1] == 'date':
stop = int(stops) if len(stops) == 10 \
else arrow.get(stops, 'YYYYMMDD').timestamp
if stype[1] == 'date' and len(stops) == 8:
stop = arrow.get(stops, 'YYYYMMDD').timestamp
else:
stop = int(stops)
return TimeRange(stype[0], stype[1], start, stop)
@ -342,3 +335,10 @@ class Arguments(object):
nargs='+',
dest='timeframes',
)
self.parser.add_argument(
'--erase',
help='Clean all existing data for the selected exchange/pairs/timeframes',
dest='erase',
action='store_true'
)

19
freqtrade/configuration.py
View File

@ -1,18 +1,18 @@
"""
This module contains the configuration class
"""
import os
import json
import logging
import os
from argparse import Namespace
from typing import Optional, Dict, Any
from typing import Any, Dict, Optional
import ccxt
from jsonschema import Draft4Validator, validate
from jsonschema.exceptions import ValidationError, best_match
import ccxt
from freqtrade import OperationalException, constants
logger = logging.getLogger(__name__)
@ -62,8 +62,8 @@ class Configuration(object):
conf = json.load(file)
except FileNotFoundError:
raise OperationalException(
'Config file "{}" not found!'
' Please create a config file or check whether it exists.'.format(path))
f'Config file "{path}" not found!'
' Please create a config file or check whether it exists.')
if 'internals' not in conf:
conf['internals'] = {}
@ -109,7 +109,7 @@ class Configuration(object):
config['db_url'] = constants.DEFAULT_DB_PROD_URL
logger.info('Dry run is disabled')
logger.info('Using DB: "{}"'.format(config['db_url']))
logger.info(f'Using DB: "{config["db_url"]}"')
# Check if the exchange set by the user is supported
self.check_exchange(config)
@ -188,11 +188,6 @@ class Configuration(object):
logger.info('Parameter --epochs detected ...')
logger.info('Will run Hyperopt with for %s epochs ...', config.get('epochs'))
# If --mongodb is used we add it to the configuration
if 'mongodb' in self.args and self.args.mongodb:
config.update({'mongodb': self.args.mongodb})
logger.info('Parameter --use-mongodb detected ...')
# If --spaces is used we add it to the configuration
if 'spaces' in self.args and self.args.spaces:
config.update({'spaces': self.args.spaces})

21
freqtrade/constants.py
View File

@ -11,6 +11,8 @@ RETRY_TIMEOUT = 30 # sec
DEFAULT_STRATEGY = 'DefaultStrategy'
DEFAULT_DB_PROD_URL = 'sqlite:///tradesv3.sqlite'
DEFAULT_DB_DRYRUN_URL = 'sqlite://'
UNLIMITED_STAKE_AMOUNT = 'unlimited'
TICKER_INTERVAL_MINUTES = {
'1m': 1,
@ -44,7 +46,11 @@ CONF_SCHEMA = {
'max_open_trades': {'type': 'integer', 'minimum': 0},
'ticker_interval': {'type': 'string', 'enum': list(TICKER_INTERVAL_MINUTES.keys())},
'stake_currency': {'type': 'string', 'enum': ['BTC', 'ETH', 'USDT', 'EUR', 'USD']},
'stake_amount': {'type': 'number', 'minimum': 0.0005},
'stake_amount': {
"type": ["number", "string"],
"minimum": 0.0005,
"pattern": UNLIMITED_STAKE_AMOUNT
},
'fiat_display_currency': {'type': 'string', 'enum': SUPPORTED_FIAT},
'dry_run': {'type': 'boolean'},
'minimal_roi': {
@ -55,7 +61,15 @@ CONF_SCHEMA = {
'minProperties': 1
},
'stoploss': {'type': 'number', 'maximum': 0, 'exclusiveMaximum': True},
'unfilledtimeout': {'type': 'integer', 'minimum': 0},
'trailing_stop': {'type': 'boolean'},
'trailing_stop_positive': {'type': 'number', 'minimum': 0, 'maximum': 1},
'unfilledtimeout': {
'type': 'object',
'properties': {
'buy': {'type': 'number', 'minimum': 3},
'sell': {'type': 'number', 'minimum': 10}
}
},
'bid_strategy': {
'type': 'object',
'properties': {
@ -73,7 +87,8 @@ CONF_SCHEMA = {
'type': 'object',
'properties': {
'use_sell_signal': {'type': 'boolean'},
'sell_profit_only': {'type': 'boolean'}
'sell_profit_only': {'type': 'boolean'},
"ignore_roi_if_buy_signal_true": {'type': 'boolean'}
}
},
'telegram': {

232
freqtrade/exchange/__init__.py
View File

@ -12,16 +12,8 @@ from freqtrade import constants, OperationalException, DependencyException, Temp
logger = logging.getLogger(__name__)
# Current selected exchange
_API: ccxt.Exchange = None
_CONF: Dict = {}
API_RETRY_COUNT = 4
_CACHED_TICKER: Dict[str, Any] = {}
# Holds all open sell orders for dry_run
_DRY_RUN_OPEN_ORDERS: Dict[str, Any] = {}
# Urls to exchange markets, insert quote and base with .format()
_EXCHANGE_URLS = {
@ -48,12 +40,40 @@ def retrier(f):
return wrapper
def init_ccxt(exchange_config: dict) -> ccxt.Exchange:
class Exchange(object):
# Current selected exchange
_api: ccxt.Exchange = None
_conf: Dict = {}
_cached_ticker: Dict[str, Any] = {}
# Holds all open sell orders for dry_run
_dry_run_open_orders: Dict[str, Any] = {}
def __init__(self, config: dict) -> None:
"""
Initializes this module with the given config,
it does basic validation whether the specified
exchange and pairs are valid.
:return: None
"""
self._conf.update(config)
if config['dry_run']:
logger.info('Instance is running with dry_run enabled')
exchange_config = config['exchange']
self._api = self._init_ccxt(exchange_config)
logger.info('Using Exchange "%s"', self.name)
# Check if all pairs are available
self.validate_pairs(config['exchange']['pair_whitelist'])
def _init_ccxt(self, exchange_config: dict) -> ccxt.Exchange:
"""
Initialize ccxt with given config and return valid
ccxt instance.
:param config: config to use
:return: ccxt
"""
# Find matching class for the given exchange name
name = exchange_config['name']
@ -73,32 +93,17 @@ def init_ccxt(exchange_config: dict) -> ccxt.Exchange:
return api
@property
def name(self) -> str:
"""exchange Name (from ccxt)"""
return self._api.name
def init(config: dict) -> None:
"""
Initializes this module with the given config,
it does basic validation whether the specified
exchange and pairs are valid.
:param config: config to use
:return: None
"""
global _CONF, _API
@property
def id(self) -> str:
"""exchange ccxt id"""
return self._api.id
_CONF.update(config)
if config['dry_run']:
logger.info('Instance is running with dry_run enabled')
exchange_config = config['exchange']
_API = init_ccxt(exchange_config)
logger.info('Using Exchange "%s"', get_name())
# Check if all pairs are available
validate_pairs(config['exchange']['pair_whitelist'])
def validate_pairs(pairs: List[str]) -> None:
def validate_pairs(self, pairs: List[str]) -> None:
"""
Checks if all given pairs are tradable on the current exchange.
Raises OperationalException if one pair is not available.
@ -107,12 +112,12 @@ def validate_pairs(pairs: List[str]) -> None:
"""
try:
markets = _API.load_markets()
markets = self._api.load_markets()
except ccxt.BaseError as e:
logger.warning('Unable to validate pairs (assuming they are correct). Reason: %s', e)
return
stake_cur = _CONF['stake_currency']
stake_cur = self._conf['stake_currency']
for pair in pairs:
# Note: ccxt has BaseCurrency/QuoteCurrency format for pairs
# TODO: add a support for having coins in BTC/USDT format
@ -121,24 +126,21 @@ def validate_pairs(pairs: List[str]) -> None:
f'Pair {pair} not compatible with stake_currency: {stake_cur}')
if pair not in markets:
raise OperationalException(
f'Pair {pair} is not available at {get_name()}')
f'Pair {pair} is not available at {self.name}')
def exchange_has(endpoint: str) -> bool:
def exchange_has(self, endpoint: str) -> bool:
"""
Checks if exchange implements a specific API endpoint.
Wrapper around ccxt 'has' attribute
:param endpoint: Name of endpoint (e.g. 'fetchOHLCV', 'fetchTickers')
:return: bool
"""
return endpoint in _API.has and _API.has[endpoint]
return endpoint in self._api.has and self._api.has[endpoint]
def buy(pair: str, rate: float, amount: float) -> Dict:
if _CONF['dry_run']:
global _DRY_RUN_OPEN_ORDERS
def buy(self, pair: str, rate: float, amount: float) -> Dict:
if self._conf['dry_run']:
order_id = f'dry_run_buy_{randint(0, 10**6)}'
_DRY_RUN_OPEN_ORDERS[order_id] = {
self._dry_run_open_orders[order_id] = {
'pair': pair,
'price': rate,
'amount': amount,
@ -152,7 +154,7 @@ def buy(pair: str, rate: float, amount: float) -> Dict:
return {'id': order_id}
try:
return _API.create_limit_buy_order(pair, amount, rate)
return self._api.create_limit_buy_order(pair, amount, rate)
except ccxt.InsufficientFunds as e:
raise DependencyException(
f'Insufficient funds to create limit buy order on market {pair}.'
@ -169,12 +171,10 @@ def buy(pair: str, rate: float, amount: float) -> Dict:
except ccxt.BaseError as e:
raise OperationalException(e)
def sell(pair: str, rate: float, amount: float) -> Dict:
if _CONF['dry_run']:
global _DRY_RUN_OPEN_ORDERS
def sell(self, pair: str, rate: float, amount: float) -> Dict:
if self._conf['dry_run']:
order_id = f'dry_run_sell_{randint(0, 10**6)}'
_DRY_RUN_OPEN_ORDERS[order_id] = {
self._dry_run_open_orders[order_id] = {
'pair': pair,
'price': rate,
'amount': amount,
@ -187,7 +187,7 @@ def sell(pair: str, rate: float, amount: float) -> Dict:
return {'id': order_id}
try:
return _API.create_limit_sell_order(pair, amount, rate)
return self._api.create_limit_sell_order(pair, amount, rate)
except ccxt.InsufficientFunds as e:
raise DependencyException(
f'Insufficient funds to create limit sell order on market {pair}.'
@ -204,28 +204,26 @@ def sell(pair: str, rate: float, amount: float) -> Dict:
except ccxt.BaseError as e:
raise OperationalException(e)
@retrier
def get_balance(currency: str) -> float:
if _CONF['dry_run']:
@retrier
def get_balance(self, currency: str) -> float:
if self._conf['dry_run']:
return 999.9
# ccxt exception is already handled by get_balances
balances = get_balances()
balances = self.get_balances()
balance = balances.get(currency)
if balance is None:
raise TemporaryError(
f'Could not get {currency} balance due to malformed exchange response: {balances}')
return balance['free']
@retrier
def get_balances() -> dict:
if _CONF['dry_run']:
@retrier
def get_balances(self) -> dict:
if self._conf['dry_run']:
return {}
try:
balances = _API.fetch_balance()
balances = self._api.fetch_balance()
# Remove additional info from ccxt results
balances.pop("info", None)
balances.pop("free", None)
@ -239,14 +237,13 @@ def get_balances() -> dict:
except ccxt.BaseError as e:
raise OperationalException(e)
@retrier
def get_tickers() -> Dict:
@retrier
def get_tickers(self) -> Dict:
try:
return _API.fetch_tickers()
return self._api.fetch_tickers()
except ccxt.NotSupported as e:
raise OperationalException(
f'Exchange {_API.name} does not support fetching tickers in batch.'
f'Exchange {self._api.name} does not support fetching tickers in batch.'
f'Message: {e}')
except (ccxt.NetworkError, ccxt.ExchangeError) as e:
raise TemporaryError(
@ -254,15 +251,13 @@ def get_tickers() -> Dict:
except ccxt.BaseError as e:
raise OperationalException(e)
@retrier
def get_ticker(pair: str, refresh: Optional[bool] = True) -> dict:
global _CACHED_TICKER
if refresh or pair not in _CACHED_TICKER.keys():
@retrier
def get_ticker(self, pair: str, refresh: Optional[bool] = True) -> dict:
if refresh or pair not in self._cached_ticker.keys():
try:
data = _API.fetch_ticker(pair)
data = self._api.fetch_ticker(pair)
try:
_CACHED_TICKER[pair] = {
self._cached_ticker[pair] = {
'bid': float(data['bid']),
'ask': float(data['ask']),
}
@ -276,11 +271,11 @@ def get_ticker(pair: str, refresh: Optional[bool] = True) -> dict:
raise OperationalException(e)
else:
logger.info("returning cached ticker-data for %s", pair)
return _CACHED_TICKER[pair]
return self._cached_ticker[pair]
@retrier
def get_ticker_history(pair: str, tick_interval: str, since_ms: Optional[int] = None) -> List[Dict]:
@retrier
def get_ticker_history(self, pair: str, tick_interval: str,
since_ms: Optional[int] = None) -> List[Dict]:
try:
# last item should be in the time interval [now - tick_interval, now]
till_time_ms = arrow.utcnow().shift(
@ -294,7 +289,7 @@ def get_ticker_history(pair: str, tick_interval: str, since_ms: Optional[int] =
data: List[Dict[Any, Any]] = []
while not since_ms or since_ms < till_time_ms:
data_part = _API.fetch_ohlcv(pair, timeframe=tick_interval, since=since_ms)
data_part = self._api.fetch_ohlcv(pair, timeframe=tick_interval, since=since_ms)
# Because some exchange sort Tickers ASC and other DESC.
# Ex: Bittrex returns a list of tickers ASC (oldest first, newest last)
@ -315,7 +310,7 @@ def get_ticker_history(pair: str, tick_interval: str, since_ms: Optional[int] =
return data
except ccxt.NotSupported as e:
raise OperationalException(
f'Exchange {_API.name} does not support fetching historical candlestick data.'
f'Exchange {self._api.name} does not support fetching historical candlestick data.'
f'Message: {e}')
except (ccxt.NetworkError, ccxt.ExchangeError) as e:
raise TemporaryError(
@ -323,14 +318,13 @@ def get_ticker_history(pair: str, tick_interval: str, since_ms: Optional[int] =
except ccxt.BaseError as e:
raise OperationalException(f'Could not fetch ticker data. Msg: {e}')
@retrier
def cancel_order(order_id: str, pair: str) -> None:
if _CONF['dry_run']:
@retrier
def cancel_order(self, order_id: str, pair: str) -> None:
if self._conf['dry_run']:
return
try:
return _API.cancel_order(order_id, pair)
return self._api.cancel_order(order_id, pair)
except ccxt.InvalidOrder as e:
raise DependencyException(
f'Could not cancel order. Message: {e}')
@ -340,17 +334,16 @@ def cancel_order(order_id: str, pair: str) -> None:
except ccxt.BaseError as e:
raise OperationalException(e)
@retrier
def get_order(order_id: str, pair: str) -> Dict:
if _CONF['dry_run']:
order = _DRY_RUN_OPEN_ORDERS[order_id]
@retrier
def get_order(self, order_id: str, pair: str) -> Dict:
if self._conf['dry_run']:
order = self._dry_run_open_orders[order_id]
order.update({
'id': order_id
})
return order
try:
return _API.fetch_order(order_id, pair)
return self._api.fetch_order(order_id, pair)
except ccxt.InvalidOrder as e:
raise DependencyException(
f'Could not get order. Message: {e}')
@ -360,15 +353,14 @@ def get_order(order_id: str, pair: str) -> Dict:
except ccxt.BaseError as e:
raise OperationalException(e)
@retrier
def get_trades_for_order(order_id: str, pair: str, since: datetime) -> List:
if _CONF['dry_run']:
@retrier
def get_trades_for_order(self, order_id: str, pair: str, since: datetime) -> List:
if self._conf['dry_run']:
return []
if not exchange_has('fetchMyTrades'):
if not self.exchange_has('fetchMyTrades'):
return []
try:
my_trades = _API.fetch_my_trades(pair, since.timestamp())
my_trades = self._api.fetch_my_trades(pair, since.timestamp())
matched_trades = [trade for trade in my_trades if trade['order'] == order_id]
return matched_trades
@ -379,46 +371,35 @@ def get_trades_for_order(order_id: str, pair: str, since: datetime) -> List:
except ccxt.BaseError as e:
raise OperationalException(e)
def get_pair_detail_url(pair: str) -> str:
def get_pair_detail_url(self, pair: str) -> str:
try:
url_base = _API.urls.get('www')
url_base = self._api.urls.get('www')
base, quote = pair.split('/')
return url_base + _EXCHANGE_URLS[_API.id].format(base=base, quote=quote)
return url_base + _EXCHANGE_URLS[self._api.id].format(base=base, quote=quote)
except KeyError:
logger.warning('Could not get exchange url for %s', get_name())
logger.warning('Could not get exchange url for %s', self.name)
return ""
@retrier
def get_markets() -> List[dict]:
@retrier
def get_markets(self) -> List[dict]:
try:
return _API.fetch_markets()
return self._api.fetch_markets()
except (ccxt.NetworkError, ccxt.ExchangeError) as e:
raise TemporaryError(
f'Could not load markets due to {e.__class__.__name__}. Message: {e}')
except ccxt.BaseError as e:
raise OperationalException(e)
def get_name() -> str:
return _API.name
def get_id() -> str:
return _API.id
@retrier
def get_fee(symbol='ETH/BTC', type='', side='', amount=1,
@retrier
def get_fee(self, symbol='ETH/BTC', type='', side='', amount=1,
price=1, taker_or_maker='maker') -> float:
try:
# validate that markets are loaded before trying to get fee
if _API.markets is None or len(_API.markets) == 0:
_API.load_markets()
if self._api.markets is None or len(self._api.markets) == 0:
self._api.load_markets()
return _API.calculate_fee(symbol=symbol, type=type, side=side, amount=amount,
return self._api.calculate_fee(symbol=symbol, type=type, side=side, amount=amount,
price=price, takerOrMaker=taker_or_maker)['rate']
except (ccxt.NetworkError, ccxt.ExchangeError) as e:
raise TemporaryError(
@ -426,12 +407,11 @@ def get_fee(symbol='ETH/BTC', type='', side='', amount=1,
except ccxt.BaseError as e:
raise OperationalException(e)
def get_amount_lots(pair: str, amount: float) -> float:
def get_amount_lots(self, pair: str, amount: float) -> float:
"""
get buyable amount rounding, ..
"""
# validate that markets are loaded before trying to get fee
if not _API.markets:
_API.load_markets()
return _API.amount_to_lots(pair, amount)
if not self._api.markets:
self._api.load_markets()
return self._api.amount_to_lots(pair, amount)

4
freqtrade/fiat_convert.py
View File

@ -7,10 +7,12 @@ import logging
import time
from typing import Dict, List
from coinmarketcap import Market
from requests.exceptions import RequestException
from coinmarketcap import Market
from freqtrade.constants import SUPPORTED_FIAT
logger = logging.getLogger(__name__)

155
freqtrade/freqtradebot.py
View File

@ -7,18 +7,16 @@ import logging
import time
import traceback
from datetime import datetime
from typing import Dict, List, Optional, Any, Callable
from typing import Any, Callable, Dict, List, Optional
import arrow
import requests
from cachetools import TTLCache, cached
from freqtrade import (
DependencyException, OperationalException, TemporaryError,
exchange, persistence, __version__,
)
from freqtrade import constants
from freqtrade import (DependencyException, OperationalException,
TemporaryError, __version__, constants, persistence)
from freqtrade.analyze import Analyze
from freqtrade.exchange import Exchange
from freqtrade.fiat_convert import CryptoToFiatConverter
from freqtrade.persistence import Trade
from freqtrade.rpc.rpc_manager import RPCManager
@ -54,7 +52,7 @@ class FreqtradeBot(object):
self.fiat_converter = CryptoToFiatConverter()
self.rpc: RPCManager = RPCManager(self)
self.persistence = None
self.exchange = None
self.exchange = Exchange(self.config)
self._init_modules()
@ -66,7 +64,6 @@ class FreqtradeBot(object):
# Initialize all modules
persistence.init(self.config)
exchange.init(self.config)
# Set initial application state
initial_state = self.config.get('initial_state')
@ -161,7 +158,7 @@ class FreqtradeBot(object):
if 'unfilledtimeout' in self.config:
# Check and handle any timed out open orders
self.check_handle_timedout(self.config['unfilledtimeout'])
self.check_handle_timedout()
Trade.session.flush()
except TemporaryError as error:
@ -186,13 +183,13 @@ class FreqtradeBot(object):
:return: List of pairs
"""
if not exchange.exchange_has('fetchTickers'):
if not self.exchange.exchange_has('fetchTickers'):
raise OperationalException(
'Exchange does not support dynamic whitelist.'
'Please edit your config and restart the bot'
)
tickers = exchange.get_tickers()
tickers = self.exchange.get_tickers()
# check length so that we make sure that '/' is actually in the string
tickers = [v for k, v in tickers.items()
if len(k.split('/')) == 2 and k.split('/')[1] == base_currency]
@ -210,7 +207,7 @@ class FreqtradeBot(object):
black_listed
"""
sanitized_whitelist = whitelist
markets = exchange.get_markets()
markets = self.exchange.get_markets()
markets = [m for m in markets if m['quote'] == self.config['stake_currency']]
known_pairs = set()
@ -245,27 +242,78 @@ class FreqtradeBot(object):
balance = self.config['bid_strategy']['ask_last_balance']
return ticker['ask'] + balance * (ticker['last'] - ticker['ask'])
def _get_trade_stake_amount(self) -> Optional[float]:
stake_amount = self.config['stake_amount']
avaliable_amount = self.exchange.get_balance(self.config['stake_currency'])
if stake_amount == constants.UNLIMITED_STAKE_AMOUNT:
open_trades = len(Trade.query.filter(Trade.is_open.is_(True)).all())
if open_trades >= self.config['max_open_trades']:
logger.warning('Can\'t open a new trade: max number of trades is reached')
return None
return avaliable_amount / (self.config['max_open_trades'] - open_trades)
# Check if stake_amount is fulfilled
if avaliable_amount < stake_amount:
raise DependencyException(
'Available balance(%f %s) is lower than stake amount(%f %s)' % (
avaliable_amount, self.config['stake_currency'],
stake_amount, self.config['stake_currency'])
)
return stake_amount
def _get_min_pair_stake_amount(self, pair: str, price: float) -> Optional[float]:
markets = self.exchange.get_markets()
markets = [m for m in markets if m['symbol'] == pair]
if not markets:
raise ValueError(f'Can\'t get market information for symbol {pair}')
market = markets[0]
if 'limits' not in market:
return None
min_stake_amounts = []
limits = market['limits']
if ('cost' in limits and 'min' in limits['cost']
and limits['cost']['min'] is not None):
min_stake_amounts.append(limits['cost']['min'])
if ('amount' in limits and 'min' in limits['amount']
and limits['amount']['min'] is not None):
min_stake_amounts.append(limits['amount']['min'] * price)
if not min_stake_amounts:
return None
amount_reserve_percent = 1 - 0.05 # reserve 5% + stoploss
if self.analyze.get_stoploss() is not None:
amount_reserve_percent += self.analyze.get_stoploss()
# it should not be more than 50%
amount_reserve_percent = max(amount_reserve_percent, 0.5)
return min(min_stake_amounts)/amount_reserve_percent
def create_trade(self) -> bool:
"""
Checks the implemented trading indicator(s) for a randomly picked pair,
if one pair triggers the buy_signal a new trade record gets created
:return: True if a trade object has been created and persisted, False otherwise
"""
stake_amount = self.config['stake_amount']
interval = self.analyze.get_ticker_interval()
stake_amount = self._get_trade_stake_amount()
if not stake_amount:
return False
stake_currency = self.config['stake_currency']
fiat_currency = self.config['fiat_display_currency']
exc_name = exchange.get_name()
exc_name = self.exchange.name
logger.info(
'Checking buy signals to create a new trade with stake_amount: %f ...',
stake_amount
)
whitelist = copy.deepcopy(self.config['exchange']['pair_whitelist'])
# Check if stake_amount is fulfilled
if exchange.get_balance(stake_currency) < stake_amount:
raise DependencyException(
f'stake amount is not fulfilled (currency={stake_currency})')
# Remove currently opened and latest pairs from whitelist
for trade in Trade.query.filter(Trade.is_open.is_(True)).all():
@ -278,19 +326,29 @@ class FreqtradeBot(object):
# Pick pair based on buy signals
for _pair in whitelist:
(buy, sell) = self.analyze.get_signal(_pair, interval)
(buy, sell) = self.analyze.get_signal(self.exchange, _pair, interval)
if buy and not sell:
pair = _pair
break
else:
return False
pair_s = pair.replace('_', '/')
pair_url = exchange.get_pair_detail_url(pair)
pair_url = self.exchange.get_pair_detail_url(pair)
# Calculate amount
buy_limit = self.get_target_bid(exchange.get_ticker(pair))
buy_limit = self.get_target_bid(self.exchange.get_ticker(pair))
min_stake_amount = self._get_min_pair_stake_amount(pair_s, buy_limit)
if min_stake_amount is not None and min_stake_amount > stake_amount:
logger.warning(
f'Can\'t open a new trade for {pair_s}: stake amount'
f' is too small ({stake_amount} < {min_stake_amount})'
)
return False
amount = stake_amount / buy_limit
order_id = exchange.buy(pair, buy_limit, amount)['id']
order_id = self.exchange.buy(pair, buy_limit, amount)['id']
stake_amount_fiat = self.fiat_converter.convert_amount(
stake_amount,
@ -305,7 +363,7 @@ with limit `{buy_limit:.8f} ({stake_amount:.6f} \
{stake_currency}, {stake_amount_fiat:.3f} {fiat_currency})`"""
)
# Fee is applied twice because we make a LIMIT_BUY and LIMIT_SELL
fee = exchange.get_fee(symbol=pair, taker_or_maker='maker')
fee = self.exchange.get_fee(symbol=pair, taker_or_maker='maker')
trade = Trade(
pair=pair,
stake_amount=stake_amount,
@ -315,7 +373,7 @@ with limit `{buy_limit:.8f} ({stake_amount:.6f} \
open_rate=buy_limit,
open_rate_requested=buy_limit,
open_date=datetime.utcnow(),
exchange=exchange.get_id(),
exchange=self.exchange.id,
open_order_id=order_id
)
Trade.session.add(trade)
@ -348,7 +406,7 @@ with limit `{buy_limit:.8f} ({stake_amount:.6f} \
if trade.open_order_id:
# Update trade with order values
logger.info('Found open order for %s', trade)
order = exchange.get_order(trade.open_order_id, trade.pair)
order = self.exchange.get_order(trade.open_order_id, trade.pair)
# Try update amount (binance-fix)
try:
new_amount = self.get_real_amount(trade, order)
@ -372,7 +430,7 @@ with limit `{buy_limit:.8f} ({stake_amount:.6f} \
def get_real_amount(self, trade: Trade, order: Dict) -> float:
"""
Get real amount for the trade
Necessary for exchanges which charge fees in base currency (e.g. binance)
Necessary for self.exchanges which charge fees in base currency (e.g. binance)
"""
order_amount = order['amount']
# Only run for closed orders
@ -388,7 +446,8 @@ with limit `{buy_limit:.8f} ({stake_amount:.6f} \
return new_amount
# Fallback to Trades
trades = exchange.get_trades_for_order(trade.open_order_id, trade.pair, trade.open_date)
trades = self.exchange.get_trades_for_order(trade.open_order_id, trade.pair,
trade.open_date)
if len(trades) == 0:
logger.info("Applying fee on amount for %s failed: myTrade-Dict empty found", trade)
@ -420,12 +479,13 @@ with limit `{buy_limit:.8f} ({stake_amount:.6f} \
raise ValueError(f'attempt to handle closed trade: {trade}')
logger.debug('Handling %s ...', trade)
current_rate = exchange.get_ticker(trade.pair)['bid']
current_rate = self.exchange.get_ticker(trade.pair)['bid']
(buy, sell) = (False, False)
if self.config.get('experimental', {}).get('use_sell_signal'):
(buy, sell) = self.analyze.get_signal(trade.pair, self.analyze.get_ticker_interval())
experimental = self.config.get('experimental', {})
if experimental.get('use_sell_signal') or experimental.get('ignore_roi_if_buy_signal'):
(buy, sell) = self.analyze.get_signal(self.exchange,
trade.pair, self.analyze.get_ticker_interval())
if self.analyze.should_sell(trade, current_rate, datetime.utcnow(), buy, sell):
self.execute_sell(trade, current_rate)
@ -433,13 +493,16 @@ with limit `{buy_limit:.8f} ({stake_amount:.6f} \
logger.info('Found no sell signals for whitelisted currencies. Trying again..')
return False
def check_handle_timedout(self, timeoutvalue: int) -> None:
def check_handle_timedout(self) -> None:
"""
Check if any orders are timed out and cancel if neccessary
:param timeoutvalue: Number of minutes until order is considered timed out
:return: None
"""
timeoutthreashold = arrow.utcnow().shift(minutes=-timeoutvalue).datetime
buy_timeout = self.config['unfilledtimeout']['buy']
sell_timeout = self.config['unfilledtimeout']['sell']
buy_timeoutthreashold = arrow.utcnow().shift(minutes=-buy_timeout).datetime
sell_timeoutthreashold = arrow.utcnow().shift(minutes=-sell_timeout).datetime
for trade in Trade.query.filter(Trade.open_order_id.isnot(None)).all():
try:
@ -449,7 +512,7 @@ with limit `{buy_limit:.8f} ({stake_amount:.6f} \
# updated via /forcesell in a different thread.
if not trade.open_order_id:
continue
order = exchange.get_order(trade.open_order_id, trade.pair)
order = self.exchange.get_order(trade.open_order_id, trade.pair)
except requests.exceptions.RequestException:
logger.info(
'Cannot query order for %s due to %s',
@ -462,9 +525,11 @@ with limit `{buy_limit:.8f} ({stake_amount:.6f} \
if int(order['remaining']) == 0:
continue
if order['side'] == 'buy' and ordertime < timeoutthreashold:
# Check if trade is still actually open
if order['status'] == 'open':
if order['side'] == 'buy' and ordertime < buy_timeoutthreashold:
self.handle_timedout_limit_buy(trade, order)
elif order['side'] == 'sell' and ordertime < timeoutthreashold:
elif order['side'] == 'sell' and ordertime < sell_timeoutthreashold:
self.handle_timedout_limit_sell(trade, order)
# FIX: 20180110, why is cancel.order unconditionally here, whereas
@ -475,7 +540,7 @@ with limit `{buy_limit:.8f} ({stake_amount:.6f} \
:return: True if order was fully cancelled
"""
pair_s = trade.pair.replace('_', '/')
exchange.cancel_order(trade.open_order_id, trade.pair)
self.exchange.cancel_order(trade.open_order_id, trade.pair)
if order['remaining'] == order['amount']:
# if trade is not partially completed, just delete the trade
Trade.session.delete(trade)
@ -502,7 +567,7 @@ with limit `{buy_limit:.8f} ({stake_amount:.6f} \
pair_s = trade.pair.replace('_', '/')
if order['remaining'] == order['amount']:
# if trade is not partially completed, just cancel the trade
exchange.cancel_order(trade.open_order_id, trade.pair)
self.exchange.cancel_order(trade.open_order_id, trade.pair)
trade.close_rate = None
trade.close_profit = None
trade.close_date = None
@ -525,15 +590,15 @@ with limit `{buy_limit:.8f} ({stake_amount:.6f} \
exc = trade.exchange
pair = trade.pair
# Execute sell and update trade record
order_id = exchange.sell(str(trade.pair), limit, trade.amount)['id']
order_id = self.exchange.sell(str(trade.pair), limit, trade.amount)['id']
trade.open_order_id = order_id
trade.close_rate_requested = limit
fmt_exp_profit = round(trade.calc_profit_percent(rate=limit) * 100, 2)
profit_trade = trade.calc_profit(rate=limit)
current_rate = exchange.get_ticker(trade.pair)['bid']
current_rate = self.exchange.get_ticker(trade.pair)['bid']
profit = trade.calc_profit_percent(limit)
pair_url = exchange.get_pair_detail_url(trade.pair)
pair_url = self.exchange.get_pair_detail_url(trade.pair)
gain = "profit" if fmt_exp_profit > 0 else "loss"
message = f"*{exc}:* Selling\n" \
@ -561,12 +626,8 @@ with limit `{buy_limit:.8f} ({stake_amount:.6f} \
# Because telegram._forcesell does not have the configuration
# Ignore the FIAT value and does not show the stake_currency as well
else:
message += '` ({gain}: {profit_percent:.2f}%, {profit_coin:.8f})`'.format(
gain="profit" if fmt_exp_profit > 0 else "loss",
profit_percent=fmt_exp_profit,
profit_coin=profit_trade
)
gain = "profit" if fmt_exp_profit > 0 else "loss"
message += f'` ({gain}: {fmt_exp_profit:.2f}%, {profit_trade:.8f})`'
# Send the message
self.rpc.send_msg(message)
Trade.session.flush()

2
freqtrade/indicator_helpers.py
View File

@ -1,4 +1,4 @@
from math import exp, pi, sqrt, cos
from math import cos, exp, pi, sqrt
import numpy as np
import talib as ta

5
freqtrade/main.py
View File

@ -74,10 +74,7 @@ def reconfigure(freqtrade: FreqtradeBot, args: Namespace) -> FreqtradeBot:
# Create new instance
freqtrade = FreqtradeBot(Configuration(args).get_config())
freqtrade.rpc.send_msg(
'*Status:* `Config reloaded ...`'.format(
freqtrade.state.name.lower()
)
)
'*Status:* `Config reloaded {freqtrade.state.name.lower()}...`')
return freqtrade

2
freqtrade/misc.py
View File

@ -2,10 +2,10 @@
Various tool function for Freqtrade and scripts
"""
import gzip
import json
import logging
import re
import gzip
from datetime import datetime
from typing import Dict

32
freqtrade/optimize/__init__.py
View File

@ -7,12 +7,10 @@ import os
from typing import Optional, List, Dict, Tuple, Any
import arrow
from freqtrade import misc, constants
from freqtrade.exchange import get_ticker_history
from freqtrade import misc, constants, OperationalException
from freqtrade.exchange import Exchange
from freqtrade.arguments import TimeRange
from user_data.hyperopt_conf import hyperopt_optimize_conf
logger = logging.getLogger(__name__)
@ -56,11 +54,8 @@ def load_tickerdata_file(
:return dict OR empty if unsuccesful
"""
path = make_testdata_path(datadir)
pair_file_string = pair.replace('/', '_')
file = os.path.join(path, '{pair}-{ticker_interval}.json'.format(
pair=pair_file_string,
ticker_interval=ticker_interval,
))
pair_s = pair.replace('/', '_')
file = os.path.join(path, f'{pair_s}-{ticker_interval}.json')
gzipfile = file + '.gz'
# If the file does not exist we download it when None is returned.
@ -83,8 +78,9 @@ def load_tickerdata_file(
def load_data(datadir: str,
ticker_interval: str,
pairs: Optional[List[str]] = None,
pairs: List[str],
refresh_pairs: Optional[bool] = False,
exchange: Optional[Exchange] = None,
timerange: TimeRange = TimeRange(None, None, 0, 0)) -> Dict[str, List]:
"""
Loads ticker history data for the given parameters
@ -92,14 +88,15 @@ def load_data(datadir: str,
"""
result = {}
_pairs = pairs or hyperopt_optimize_conf()['exchange']['pair_whitelist']
# If the user force the refresh of pairs
if refresh_pairs:
logger.info('Download data for all pairs and store them in %s', datadir)
download_pairs(datadir, _pairs, ticker_interval, timerange=timerange)
if not exchange:
raise OperationalException("Exchange needs to be initialized when "
"calling load_data with refresh_pairs=True")
download_pairs(datadir, exchange, pairs, ticker_interval, timerange=timerange)
for pair in _pairs:
for pair in pairs:
pairdata = load_tickerdata_file(datadir, pair, ticker_interval, timerange=timerange)
if pairdata:
result[pair] = pairdata
@ -123,13 +120,14 @@ def make_testdata_path(datadir: str) -> str:
)
def download_pairs(datadir, pairs: List[str],
def download_pairs(datadir, exchange: Exchange, pairs: List[str],
ticker_interval: str,
timerange: TimeRange = TimeRange(None, None, 0, 0)) -> bool:
"""For each pairs passed in parameters, download the ticker intervals"""
for pair in pairs:
try:
download_backtesting_testdata(datadir,
exchange=exchange,
pair=pair,
tick_interval=ticker_interval,
timerange=timerange)
@ -187,6 +185,7 @@ def load_cached_data_for_updating(filename: str,
def download_backtesting_testdata(datadir: str,
exchange: Exchange,
pair: str,
tick_interval: str = '5m',
timerange: Optional[TimeRange] = None) -> None:
@ -220,7 +219,8 @@ def download_backtesting_testdata(datadir: str,
logger.debug("Current Start: %s", misc.format_ms_time(data[1][0]) if data else 'None')
logger.debug("Current End: %s", misc.format_ms_time(data[-1][0]) if data else 'None')
new_data = get_ticker_history(pair=pair, tick_interval=tick_interval, since_ms=since_ms)
new_data = exchange.get_ticker_history(pair=pair, tick_interval=tick_interval,
since_ms=since_ms)
data.extend(new_data)
logger.debug("New Start: %s", misc.format_ms_time(data[0][0]))

169
freqtrade/optimize/backtesting.py
View File

@ -6,23 +6,42 @@ This module contains the backtesting logic
import logging
import operator
from argparse import Namespace
from typing import Dict, Tuple, Any, List, Optional
from datetime import datetime
from typing import Any, Dict, List, NamedTuple, Optional, Tuple
import arrow
from pandas import DataFrame
from tabulate import tabulate
import freqtrade.optimize as optimize
from freqtrade import exchange
from freqtrade import DependencyException, constants
from freqtrade.analyze import Analyze
from freqtrade.arguments import Arguments
from freqtrade.configuration import Configuration
from freqtrade.exchange import Exchange
from freqtrade.misc import file_dump_json
from freqtrade.persistence import Trade
logger = logging.getLogger(__name__)
class BacktestResult(NamedTuple):
"""
NamedTuple Defining BacktestResults inputs.
"""
pair: str
profit_percent: float
profit_abs: float
open_time: datetime
close_time: datetime
open_index: int
close_index: int
trade_duration: float
open_at_end: bool
open_rate: float
close_rate: float
class Backtesting(object):
"""
Backtesting class, this class contains all the logic to run a backtest
@ -45,7 +64,8 @@ class Backtesting(object):
self.config['exchange']['password'] = ''
self.config['exchange']['uid'] = ''
self.config['dry_run'] = True
exchange.init(self.config)
self.exchange = Exchange(self.config)
self.fee = self.exchange.get_fee()
@staticmethod
def get_timeframe(data: Dict[str, DataFrame]) -> Tuple[arrow.Arrow, arrow.Arrow]:
@ -73,15 +93,15 @@ class Backtesting(object):
headers = ['pair', 'buy count', 'avg profit %',
'total profit ' + stake_currency, 'avg duration', 'profit', 'loss']
for pair in data:
result = results[results.currency == pair]
result = results[results.pair == pair]
tabular_data.append([
pair,
len(result.index),
result.profit_percent.mean() * 100.0,
result.profit_BTC.sum(),
result.duration.mean(),
len(result[result.profit_BTC > 0]),
len(result[result.profit_BTC < 0])
result.profit_abs.sum(),
result.trade_duration.mean(),
len(result[result.profit_abs > 0]),
len(result[result.profit_abs < 0])
])
# Append Total
@ -89,27 +109,37 @@ class Backtesting(object):
'TOTAL',
len(results.index),
results.profit_percent.mean() * 100.0,
results.profit_BTC.sum(),
results.duration.mean(),
len(results[results.profit_BTC > 0]),
len(results[results.profit_BTC < 0])
results.profit_abs.sum(),
results.trade_duration.mean(),
len(results[results.profit_abs > 0]),
len(results[results.profit_abs < 0])
])
return tabulate(tabular_data, headers=headers, floatfmt=floatfmt, tablefmt="pipe")
def _store_backtest_result(self, recordfilename: Optional[str], results: DataFrame) -> None:
records = [(t.pair, t.profit_percent, t.open_time.timestamp(),
t.close_time.timestamp(), t.open_index - 1, t.trade_duration,
t.open_rate, t.close_rate, t.open_at_end)
for index, t in results.iterrows()]
if records:
logger.info('Dumping backtest results to %s', recordfilename)
file_dump_json(recordfilename, records)
def _get_sell_trade_entry(
self, pair: str, buy_row: DataFrame,
partial_ticker: List, trade_count_lock: Dict, args: Dict) -> Optional[Tuple]:
partial_ticker: List, trade_count_lock: Dict, args: Dict) -> Optional[BacktestResult]:
stake_amount = args['stake_amount']
max_open_trades = args.get('max_open_trades', 0)
fee = exchange.get_fee()
trade = Trade(
open_rate=buy_row.close,
open_date=buy_row.date,
stake_amount=stake_amount,
amount=stake_amount / buy_row.open,
fee_open=fee,
fee_close=fee
fee_open=self.fee,
fee_close=self.fee
)
# calculate win/lose forwards from buy point
@ -121,15 +151,37 @@ class Backtesting(object):
buy_signal = sell_row.buy
if self.analyze.should_sell(trade, sell_row.close, sell_row.date, buy_signal,
sell_row.sell):
return \
sell_row, \
(
pair,
trade.calc_profit_percent(rate=sell_row.close),
trade.calc_profit(rate=sell_row.close),
(sell_row.date - buy_row.date).seconds // 60
), \
sell_row.date
return BacktestResult(pair=pair,
profit_percent=trade.calc_profit_percent(rate=sell_row.close),
profit_abs=trade.calc_profit(rate=sell_row.close),
open_time=buy_row.date,
close_time=sell_row.date,
trade_duration=(sell_row.date - buy_row.date).seconds // 60,
open_index=buy_row.Index,
close_index=sell_row.Index,
open_at_end=False,
open_rate=buy_row.close,
close_rate=sell_row.close
)
if partial_ticker:
# no sell condition found - trade stil open at end of backtest period
sell_row = partial_ticker[-1]
btr = BacktestResult(pair=pair,
profit_percent=trade.calc_profit_percent(rate=sell_row.close),
profit_abs=trade.calc_profit(rate=sell_row.close),
open_time=buy_row.date,
close_time=sell_row.date,
trade_duration=(sell_row.date - buy_row.date).seconds // 60,
open_index=buy_row.Index,
close_index=sell_row.Index,
open_at_end=True,
open_rate=buy_row.close,
close_rate=sell_row.close
)
logger.debug('Force_selling still open trade %s with %s perc - %s', btr.pair,
btr.profit_percent, btr.profit_abs)
return btr
return None
def backtest(self, args: Dict) -> DataFrame:
@ -145,17 +197,12 @@ class Backtesting(object):
processed: a processed dictionary with format {pair, data}
max_open_trades: maximum number of concurrent trades (default: 0, disabled)
realistic: do we try to simulate realistic trades? (default: True)
sell_profit_only: sell if profit only
use_sell_signal: act on sell-signal
:return: DataFrame
"""
headers = ['date', 'buy', 'open', 'close', 'sell']
processed = args['processed']
max_open_trades = args.get('max_open_trades', 0)
realistic = args.get('realistic', False)
record = args.get('record', None)
recordfilename = args.get('recordfn', 'backtest-result.json')
records = []
trades = []
trade_count_lock: Dict = {}
for pair, pair_data in processed.items():
@ -170,6 +217,8 @@ class Backtesting(object):
ticker_data.drop(ticker_data.head(1).index, inplace=True)
# Convert from Pandas to list for performance reasons
# (Looping Pandas is slow.)
ticker = [x for x in ticker_data.itertuples()]
lock_pair_until = None
@ -187,28 +236,18 @@ class Backtesting(object):
trade_count_lock[row.date] = trade_count_lock.get(row.date, 0) + 1
ret = self._get_sell_trade_entry(pair, row, ticker[index + 1:],
trade_entry = self._get_sell_trade_entry(pair, row, ticker[index + 1:],
trade_count_lock, args)
if ret:
row2, trade_entry, next_date = ret
lock_pair_until = next_date
if trade_entry:
lock_pair_until = trade_entry.close_time
trades.append(trade_entry)
if record:
# Note, need to be json.dump friendly
# record a tuple of pair, current_profit_percent,
# entry-date, duration
records.append((pair, trade_entry[1],
row.date.strftime('%s'),
row2.date.strftime('%s'),
index, trade_entry[3]))
# For now export inside backtest(), maybe change so that backtest()
# returns a tuple like: (dataframe, records, logs, etc)
if record and record.find('trades') >= 0:
logger.info('Dumping backtest results to %s', recordfilename)
file_dump_json(recordfilename, records)
labels = ['currency', 'profit_percent', 'profit_BTC', 'duration']
return DataFrame.from_records(trades, columns=labels)
else:
# Set lock_pair_until to end of testing period if trade could not be closed
# This happens only if the buy-signal was with the last candle
lock_pair_until = ticker_data.iloc[-1].date
return DataFrame.from_records(trades, columns=BacktestResult._fields)
def start(self) -> None:
"""
@ -223,7 +262,7 @@ class Backtesting(object):
if self.config.get('live'):
logger.info('Downloading data for all pairs in whitelist ...')
for pair in pairs:
data[pair] = exchange.get_ticker_history(pair, self.ticker_interval)
data[pair] = self.exchange.get_ticker_history(pair, self.ticker_interval)
else:
logger.info('Using local backtesting data (using whitelist in given config) ...')
@ -234,6 +273,7 @@ class Backtesting(object):
pairs=pairs,
ticker_interval=self.ticker_interval,
refresh_pairs=self.config.get('refresh_pairs', False),
exchange=self.exchange,
timerange=timerange
)
@ -259,24 +299,22 @@ class Backtesting(object):
)
# Execute backtest and print results
sell_profit_only = self.config.get('experimental', {}).get('sell_profit_only', False)
use_sell_signal = self.config.get('experimental', {}).get('use_sell_signal', False)
results = self.backtest(
{
'stake_amount': self.config.get('stake_amount'),
'processed': preprocessed,
'max_open_trades': max_open_trades,
'realistic': self.config.get('realistic_simulation', False),
'sell_profit_only': sell_profit_only,
'use_sell_signal': use_sell_signal,
'record': self.config.get('export'),
'recordfn': self.config.get('exportfilename'),
}
)
if self.config.get('export', False):
self._store_backtest_result(self.config.get('exportfilename'), results)
logger.info(
'\n==================================== '
'\n======================================== '
'BACKTESTING REPORT'
' ====================================\n'
' =========================================\n'
'%s',
self._generate_text_table(
data,
@ -284,6 +322,17 @@ class Backtesting(object):
)
)
logger.info(
'\n====================================== '
'LEFT OPEN TRADES REPORT'
' ======================================\n'
'%s',
self._generate_text_table(
data,
results.loc[results.open_at_end]
)
)
def setup_configuration(args: Namespace) -> Dict[str, Any]:
"""
@ -298,6 +347,10 @@ def setup_configuration(args: Namespace) -> Dict[str, Any]:
config['exchange']['key'] = ''
config['exchange']['secret'] = ''
if config['stake_amount'] == constants.UNLIMITED_STAKE_AMOUNT:
raise DependencyException('stake amount could not be "%s" for backtesting' %
constants.UNLIMITED_STAKE_AMOUNT)
return config

514
freqtrade/optimize/hyperopt.py
View File

@ -4,33 +4,33 @@
This module contains the hyperopt logic
"""
import json
import logging
import multiprocessing
import os
import pickle
import signal
import sys
from argparse import Namespace
from functools import reduce
from math import exp
from operator import itemgetter
from typing import Dict, Any, Callable, Optional
from typing import Any, Callable, Dict, List
import numpy
import talib.abstract as ta
from hyperopt import STATUS_FAIL, STATUS_OK, Trials, fmin, hp, space_eval, tpe
from hyperopt.mongoexp import MongoTrials
from pandas import DataFrame
from sklearn.externals.joblib import Parallel, delayed, dump, load
from skopt import Optimizer
from skopt.space import Categorical, Dimension, Integer, Real
import freqtrade.vendor.qtpylib.indicators as qtpylib
from freqtrade.arguments import Arguments
from freqtrade.configuration import Configuration
from freqtrade.optimize import load_data
from freqtrade.optimize.backtesting import Backtesting
from user_data.hyperopt_conf import hyperopt_optimize_conf
logger = logging.getLogger(__name__)
MAX_LOSS = 100000 # just a big enough number to be bad result in loss optimization
TICKERDATA_PICKLE = os.path.join('user_data', 'hyperopt_tickerdata.pkl')
class Hyperopt(Backtesting):
"""
@ -41,13 +41,11 @@ class Hyperopt(Backtesting):
hyperopt.start()
"""
def __init__(self, config: Dict[str, Any]) -> None:
super().__init__(config)
# set TARGET_TRADES to suit your number concurrent trades so its realistic
# to the number of days
self.target_trades = 600
self.total_tries = config.get('epochs', 0)
self.current_tries = 0
self.current_best_loss = 100
# max average trade duration in minutes
@ -59,130 +57,38 @@ class Hyperopt(Backtesting):
# check that the reported Σ% values do not exceed this!
self.expected_max_profit = 3.0
# Configuration and data used by hyperopt
self.processed: Optional[Dict[str, Any]] = None
# Previous evaluations
self.trials_file = os.path.join('user_data', 'hyperopt_results.pickle')
self.trials: List = []
# Hyperopt Trials
self.trials_file = os.path.join('user_data', 'hyperopt_trials.pickle')
self.trials = Trials()
def get_args(self, params):
dimensions = self.hyperopt_space()
# Ensure the number of dimensions match
# the number of parameters in the list x.
if len(params) != len(dimensions):
raise ValueError('Mismatch in number of search-space dimensions. '
f'len(dimensions)=={len(dimensions)} and len(x)=={len(params)}')
# Create a dict where the keys are the names of the dimensions
# and the values are taken from the list of parameters x.
arg_dict = {dim.name: value for dim, value in zip(dimensions, params)}
return arg_dict
@staticmethod
def populate_indicators(dataframe: DataFrame) -> DataFrame:
"""
Adds several different TA indicators to the given DataFrame
"""
dataframe['adx'] = ta.ADX(dataframe)
dataframe['ao'] = qtpylib.awesome_oscillator(dataframe)
dataframe['cci'] = ta.CCI(dataframe)
macd = ta.MACD(dataframe)
dataframe['macd'] = macd['macd']
dataframe['macdsignal'] = macd['macdsignal']
dataframe['macdhist'] = macd['macdhist']
dataframe['mfi'] = ta.MFI(dataframe)
dataframe['minus_dm'] = ta.MINUS_DM(dataframe)
dataframe['minus_di'] = ta.MINUS_DI(dataframe)
dataframe['plus_dm'] = ta.PLUS_DM(dataframe)
dataframe['plus_di'] = ta.PLUS_DI(dataframe)
dataframe['roc'] = ta.ROC(dataframe)
dataframe['rsi'] = ta.RSI(dataframe)
# Inverse Fisher transform on RSI, values [-1.0, 1.0] (https://goo.gl/2JGGoy)
rsi = 0.1 * (dataframe['rsi'] - 50)
dataframe['fisher_rsi'] = (numpy.exp(2 * rsi) - 1) / (numpy.exp(2 * rsi) + 1)
# Inverse Fisher transform on RSI normalized, value [0.0, 100.0] (https://goo.gl/2JGGoy)
dataframe['fisher_rsi_norma'] = 50 * (dataframe['fisher_rsi'] + 1)
# Stoch
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']
dataframe['fastk_rsi'] = stoch_rsi['fastk']
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_middleband'] = bollinger['mid']
dataframe['bb_upperband'] = bollinger['upper']
# EMA - Exponential Moving Average
dataframe['ema3'] = ta.EMA(dataframe, timeperiod=3)
dataframe['ema5'] = ta.EMA(dataframe, timeperiod=5)
dataframe['ema10'] = ta.EMA(dataframe, timeperiod=10)
dataframe['ema50'] = ta.EMA(dataframe, timeperiod=50)
dataframe['ema100'] = ta.EMA(dataframe, timeperiod=100)
# SAR Parabolic
dataframe['sar'] = ta.SAR(dataframe)
# SMA - Simple Moving Average
dataframe['sma'] = ta.SMA(dataframe, timeperiod=40)
# TEMA - Triple Exponential Moving Average
dataframe['tema'] = ta.TEMA(dataframe, timeperiod=9)
# Hilbert Transform Indicator - SineWave
hilbert = ta.HT_SINE(dataframe)
dataframe['htsine'] = hilbert['sine']
dataframe['htleadsine'] = hilbert['leadsine']
# Pattern Recognition - Bullish candlestick patterns
# ------------------------------------
"""
# Hammer: values [0, 100]
dataframe['CDLHAMMER'] = ta.CDLHAMMER(dataframe)
# Inverted Hammer: values [0, 100]
dataframe['CDLINVERTEDHAMMER'] = ta.CDLINVERTEDHAMMER(dataframe)
# Dragonfly Doji: values [0, 100]
dataframe['CDLDRAGONFLYDOJI'] = ta.CDLDRAGONFLYDOJI(dataframe)
# Piercing Line: values [0, 100]
dataframe['CDLPIERCING'] = ta.CDLPIERCING(dataframe) # values [0, 100]
# Morningstar: values [0, 100]
dataframe['CDLMORNINGSTAR'] = ta.CDLMORNINGSTAR(dataframe) # values [0, 100]
# Three White Soldiers: values [0, 100]
dataframe['CDL3WHITESOLDIERS'] = ta.CDL3WHITESOLDIERS(dataframe) # values [0, 100]
"""
# Pattern Recognition - Bearish candlestick patterns
# ------------------------------------
"""
# Hanging Man: values [0, 100]
dataframe['CDLHANGINGMAN'] = ta.CDLHANGINGMAN(dataframe)
# Shooting Star: values [0, 100]
dataframe['CDLSHOOTINGSTAR'] = ta.CDLSHOOTINGSTAR(dataframe)
# Gravestone Doji: values [0, 100]
dataframe['CDLGRAVESTONEDOJI'] = ta.CDLGRAVESTONEDOJI(dataframe)
# Dark Cloud Cover: values [0, 100]
dataframe['CDLDARKCLOUDCOVER'] = ta.CDLDARKCLOUDCOVER(dataframe)
# Evening Doji Star: values [0, 100]
dataframe['CDLEVENINGDOJISTAR'] = ta.CDLEVENINGDOJISTAR(dataframe)
# Evening Star: values [0, 100]
dataframe['CDLEVENINGSTAR'] = ta.CDLEVENINGSTAR(dataframe)
"""
# Pattern Recognition - Bullish/Bearish candlestick patterns
# ------------------------------------
"""
# Three Line Strike: values [0, -100, 100]
dataframe['CDL3LINESTRIKE'] = ta.CDL3LINESTRIKE(dataframe)
# Spinning Top: values [0, -100, 100]
dataframe['CDLSPINNINGTOP'] = ta.CDLSPINNINGTOP(dataframe) # values [0, -100, 100]
# Engulfing: values [0, -100, 100]
dataframe['CDLENGULFING'] = ta.CDLENGULFING(dataframe) # values [0, -100, 100]
# Harami: values [0, -100, 100]
dataframe['CDLHARAMI'] = ta.CDLHARAMI(dataframe) # values [0, -100, 100]
# Three Outside Up/Down: values [0, -100, 100]
dataframe['CDL3OUTSIDE'] = ta.CDL3OUTSIDE(dataframe) # values [0, -100, 100]
# Three Inside Up/Down: values [0, -100, 100]
dataframe['CDL3INSIDE'] = ta.CDL3INSIDE(dataframe) # values [0, -100, 100]
"""
# Chart type
# ------------------------------------
# Heikinashi stategy
heikinashi = qtpylib.heikinashi(dataframe)
dataframe['ha_open'] = heikinashi['open']
dataframe['ha_close'] = heikinashi['close']
dataframe['ha_high'] = heikinashi['high']
dataframe['ha_low'] = heikinashi['low']
return dataframe
@ -190,15 +96,16 @@ class Hyperopt(Backtesting):
"""
Save hyperopt trials to file
"""
logger.info('Saving Trials to \'%s\'', self.trials_file)
pickle.dump(self.trials, open(self.trials_file, 'wb'))
if self.trials:
logger.info('Saving %d evaluations to \'%s\'', len(self.trials), self.trials_file)
dump(self.trials, self.trials_file)
def read_trials(self) -> Trials:
def read_trials(self) -> List:
"""
Read hyperopt trials file
"""
logger.info('Reading Trials from \'%s\'', self.trials_file)
trials = pickle.load(open(self.trials_file, 'rb'))
trials = load(self.trials_file)
os.remove(self.trials_file)
return trials
@ -206,22 +113,27 @@ class Hyperopt(Backtesting):
"""
Display Best hyperopt result
"""
vals = json.dumps(self.trials.best_trial['misc']['vals'], indent=4)
results = self.trials.best_trial['result']['result']
logger.info('Best result:\n%s\nwith values:\n%s', results, vals)
results = sorted(self.trials, key=itemgetter('loss'))
best_result = results[0]
logger.info(
'Best result:\n%s\nwith values:\n%s',
best_result['result'],
best_result['params']
)
if 'roi_t1' in best_result['params']:
logger.info('ROI table:\n%s', self.generate_roi_table(best_result['params']))
def log_results(self, results) -> None:
"""
Log results if it is better than any previous evaluation
"""
if results['loss'] < self.current_best_loss:
current = results['current_tries']
total = results['total_tries']
res = results['result']
loss = results['loss']
self.current_best_loss = results['loss']
log_msg = '\n{:5d}/{}: {}. Loss {:.5f}'.format(
results['current_tries'],
results['total_tries'],
results['result'],
results['loss']
)
log_msg = f'\n{current:5d}/{total}: {res}. Loss {loss:.5f}'
print(log_msg)
else:
print('.', end='')
@ -234,7 +146,8 @@ class Hyperopt(Backtesting):
trade_loss = 1 - 0.25 * exp(-(trade_count - self.target_trades) ** 2 / 10 ** 5.8)
profit_loss = max(0, 1 - total_profit / self.expected_max_profit)
duration_loss = 0.4 * min(trade_duration / self.max_accepted_trade_duration, 1)
return trade_loss + profit_loss + duration_loss
result = trade_loss + profit_loss + duration_loss
return result
@staticmethod
def generate_roi_table(params: Dict) -> Dict[int, float]:
@ -250,87 +163,44 @@ class Hyperopt(Backtesting):
return roi_table
@staticmethod
def roi_space() -> Dict[str, Any]:
def roi_space() -> List[Dimension]:
"""
Values to search for each ROI steps
"""
return {
'roi_t1': hp.quniform('roi_t1', 10, 120, 20),
'roi_t2': hp.quniform('roi_t2', 10, 60, 15),
'roi_t3': hp.quniform('roi_t3', 10, 40, 10),
'roi_p1': hp.quniform('roi_p1', 0.01, 0.04, 0.01),
'roi_p2': hp.quniform('roi_p2', 0.01, 0.07, 0.01),
'roi_p3': hp.quniform('roi_p3', 0.01, 0.20, 0.01),
}
return [
Integer(10, 120, name='roi_t1'),
Integer(10, 60, name='roi_t2'),
Integer(10, 40, name='roi_t3'),
Real(0.01, 0.04, name='roi_p1'),
Real(0.01, 0.07, name='roi_p2'),
Real(0.01, 0.20, name='roi_p3'),
]
@staticmethod
def stoploss_space() -> Dict[str, Any]:
def stoploss_space() -> List[Dimension]:
"""
Stoploss Value to search
Stoploss search space
"""
return {
'stoploss': hp.quniform('stoploss', -0.5, -0.02, 0.02),
}
return [
Real(-0.5, -0.02, name='stoploss'),
]
@staticmethod
def indicator_space() -> Dict[str, Any]:
def indicator_space() -> List[Dimension]:
"""
Define your Hyperopt space for searching strategy parameters
"""
return {
'macd_below_zero': hp.choice('macd_below_zero', [
{'enabled': False},
{'enabled': True}
]),
'mfi': hp.choice('mfi', [
{'enabled': False},
{'enabled': True, 'value': hp.quniform('mfi-value', 10, 25, 5)}
]),
'fastd': hp.choice('fastd', [
{'enabled': False},
{'enabled': True, 'value': hp.quniform('fastd-value', 15, 45, 5)}
]),
'adx': hp.choice('adx', [
{'enabled': False},
{'enabled': True, 'value': hp.quniform('adx-value', 20, 50, 5)}
]),
'rsi': hp.choice('rsi', [
{'enabled': False},
{'enabled': True, 'value': hp.quniform('rsi-value', 20, 40, 5)}
]),
'uptrend_long_ema': hp.choice('uptrend_long_ema', [
{'enabled': False},
{'enabled': True}
]),
'uptrend_short_ema': hp.choice('uptrend_short_ema', [
{'enabled': False},
{'enabled': True}
]),
'over_sar': hp.choice('over_sar', [
{'enabled': False},
{'enabled': True}
]),
'green_candle': hp.choice('green_candle', [
{'enabled': False},
{'enabled': True}
]),
'uptrend_sma': hp.choice('uptrend_sma', [
{'enabled': False},
{'enabled': True}
]),
'trigger': hp.choice('trigger', [
{'type': 'lower_bb'},
{'type': 'lower_bb_tema'},
{'type': 'faststoch10'},
{'type': 'ao_cross_zero'},
{'type': 'ema3_cross_ema10'},
{'type': 'macd_cross_signal'},
{'type': 'sar_reversal'},
{'type': 'ht_sine'},
{'type': 'heiken_reversal_bull'},
{'type': 'di_cross'},
]),
}
return [
Integer(10, 25, name='mfi-value'),
Integer(15, 45, name='fastd-value'),
Integer(20, 50, name='adx-value'),
Integer(20, 40, name='rsi-value'),
Categorical([True, False], name='mfi-enabled'),
Categorical([True, False], name='fastd-enabled'),
Categorical([True, False], name='adx-enabled'),
Categorical([True, False], name='rsi-enabled'),
Categorical(['bb_lower', 'macd_cross_signal', 'sar_reversal'], name='trigger')
]
def has_space(self, space: str) -> bool:
"""
@ -340,17 +210,17 @@ class Hyperopt(Backtesting):
return True
return False
def hyperopt_space(self) -> Dict[str, Any]:
def hyperopt_space(self) -> List[Dimension]:
"""
Return the space to use during Hyperopt
"""
spaces: Dict = {}
spaces: List[Dimension] = []
if self.has_space('buy'):
spaces = {**spaces, **Hyperopt.indicator_space()}
spaces += Hyperopt.indicator_space()
if self.has_space('roi'):
spaces = {**spaces, **Hyperopt.roi_space()}
spaces += Hyperopt.roi_space()
if self.has_space('stoploss'):
spaces = {**spaces, **Hyperopt.stoploss_space()}
spaces += Hyperopt.stoploss_space()
return spaces
@staticmethod
@ -364,63 +234,26 @@ class Hyperopt(Backtesting):
"""
conditions = []
# GUARDS AND TRENDS
if 'uptrend_long_ema' in params and params['uptrend_long_ema']['enabled']:
conditions.append(dataframe['ema50'] > dataframe['ema100'])
if 'macd_below_zero' in params and params['macd_below_zero']['enabled']:
conditions.append(dataframe['macd'] < 0)
if 'uptrend_short_ema' in params and params['uptrend_short_ema']['enabled']:
conditions.append(dataframe['ema5'] > dataframe['ema10'])
if 'mfi' in params and params['mfi']['enabled']:
conditions.append(dataframe['mfi'] < params['mfi']['value'])
if 'fastd' in params and params['fastd']['enabled']:
conditions.append(dataframe['fastd'] < params['fastd']['value'])
if 'adx' in params and params['adx']['enabled']:
conditions.append(dataframe['adx'] > params['adx']['value'])
if 'rsi' in params and params['rsi']['enabled']:
conditions.append(dataframe['rsi'] < params['rsi']['value'])
if 'over_sar' in params and params['over_sar']['enabled']:
conditions.append(dataframe['close'] > dataframe['sar'])
if 'green_candle' in params and params['green_candle']['enabled']:
conditions.append(dataframe['close'] > dataframe['open'])
if 'uptrend_sma' in params and params['uptrend_sma']['enabled']:
prevsma = dataframe['sma'].shift(1)
conditions.append(dataframe['sma'] > prevsma)
if 'mfi-enabled' in params and params['mfi-enabled']:
conditions.append(dataframe['mfi'] < params['mfi-value'])
if 'fastd-enabled' in params and params['fastd-enabled']:
conditions.append(dataframe['fastd'] < params['fastd-value'])
if 'adx-enabled' in params and params['adx-enabled']:
conditions.append(dataframe['adx'] > params['adx-value'])
if 'rsi-enabled' in params and params['rsi-enabled']:
conditions.append(dataframe['rsi'] < params['rsi-value'])
# TRIGGERS
triggers = {
'lower_bb': (
dataframe['close'] < dataframe['bb_lowerband']
),
'lower_bb_tema': (
dataframe['tema'] < dataframe['bb_lowerband']
),
'faststoch10': (qtpylib.crossed_above(
dataframe['fastd'], 10.0
)),
'ao_cross_zero': (qtpylib.crossed_above(
dataframe['ao'], 0.0
)),
'ema3_cross_ema10': (qtpylib.crossed_above(
dataframe['ema3'], dataframe['ema10']
)),
'macd_cross_signal': (qtpylib.crossed_above(
if params['trigger'] == 'bb_lower':
conditions.append(dataframe['close'] < dataframe['bb_lowerband'])
if params['trigger'] == 'macd_cross_signal':
conditions.append(qtpylib.crossed_above(
dataframe['macd'], dataframe['macdsignal']
)),
'sar_reversal': (qtpylib.crossed_above(
))
if params['trigger'] == 'sar_reversal':
conditions.append(qtpylib.crossed_above(
dataframe['close'], dataframe['sar']
)),
'ht_sine': (qtpylib.crossed_above(
dataframe['htleadsine'], dataframe['htsine']
)),
'heiken_reversal_bull': (
(qtpylib.crossed_above(dataframe['ha_close'], dataframe['ha_open'])) &
(dataframe['ha_low'] == dataframe['ha_open'])
),
'di_cross': (qtpylib.crossed_above(
dataframe['plus_di'], dataframe['minus_di']
)),
}
conditions.append(triggers.get(params['trigger']['type']))
))
dataframe.loc[
reduce(lambda x, y: x & y, conditions),
@ -430,7 +263,9 @@ class Hyperopt(Backtesting):
return populate_buy_trend
def generate_optimizer(self, params: Dict) -> Dict:
def generate_optimizer(self, _params) -> Dict:
params = self.get_args(_params)
if self.has_space('roi'):
self.analyze.strategy.minimal_roi = self.generate_roi_table(params)
@ -440,10 +275,11 @@ class Hyperopt(Backtesting):
if self.has_space('stoploss'):
self.analyze.strategy.stoploss = params['stoploss']
processed = load(TICKERDATA_PICKLE)
results = self.backtest(
{
'stake_amount': self.config['stake_amount'],
'processed': self.processed,
'processed': processed,
'realistic': self.config.get('realistic_simulation', False),
}
)
@ -451,32 +287,20 @@ class Hyperopt(Backtesting):
total_profit = results.profit_percent.sum()
trade_count = len(results.index)
trade_duration = results.duration.mean()
trade_duration = results.trade_duration.mean()
if trade_count == 0 or trade_duration > self.max_accepted_trade_duration:
print('.', end='')
sys.stdout.flush()
if trade_count == 0:
return {
'status': STATUS_FAIL,
'loss': float('inf')
'loss': MAX_LOSS,
'params': params,
'result': result_explanation,
}
loss = self.calculate_loss(total_profit, trade_count, trade_duration)
self.current_tries += 1
self.log_results(
{
'loss': loss,
'current_tries': self.current_tries,
'total_tries': self.total_tries,
'result': result_explanation,
}
)
return {
'loss': loss,
'status': STATUS_OK,
'params': params,
'result': result_explanation,
}
@ -484,14 +308,36 @@ class Hyperopt(Backtesting):
"""
Return the format result in a string
"""
return ('{:6d} trades. Avg profit {: 5.2f}%. '
'Total profit {: 11.8f} {} ({:.4f}Σ%). Avg duration {:5.1f} mins.').format(
len(results.index),
results.profit_percent.mean() * 100.0,
results.profit_BTC.sum(),
self.config['stake_currency'],
results.profit_percent.sum(),
results.duration.mean(),
trades = len(results.index)
avg_profit = results.profit_percent.mean() * 100.0
total_profit = results.profit_abs.sum()
stake_cur = self.config['stake_currency']
profit = results.profit_percent.sum()
duration = results.trade_duration.mean()
return (f'{trades:6d} trades. Avg profit {avg_profit: 5.2f}%. '
f'Total profit {total_profit: 11.8f} {stake_cur} '
f'({profit:.4f}Σ%). Avg duration {duration:5.1f} mins.')
def get_optimizer(self, cpu_count) -> Optimizer:
return Optimizer(
self.hyperopt_space(),
base_estimator="ET",
acq_optimizer="auto",
n_initial_points=30,
acq_optimizer_kwargs={'n_jobs': cpu_count}
)
def run_optimizer_parallel(self, parallel, asked) -> List:
return parallel(delayed(self.generate_optimizer)(v) for v in asked)
def load_previous_results(self):
""" read trials file if we have one """
if os.path.exists(self.trials_file) and os.path.getsize(self.trials_file) > 0:
self.trials = self.read_trials()
logger.info(
'Loaded %d previous evaluations from disk.',
len(self.trials)
)
def start(self) -> None:
@ -506,79 +352,35 @@ class Hyperopt(Backtesting):
if self.has_space('buy'):
self.analyze.populate_indicators = Hyperopt.populate_indicators # type: ignore
self.processed = self.tickerdata_to_dataframe(data)
dump(self.tickerdata_to_dataframe(data), TICKERDATA_PICKLE)
self.exchange = None # type: ignore
self.load_previous_results()
if self.config.get('mongodb'):
logger.info('Using mongodb ...')
logger.info(
'Start scripts/start-mongodb.sh and start-hyperopt-worker.sh manually!'
)
db_name = 'freqtrade_hyperopt'
self.trials = MongoTrials(
arg='mongo://127.0.0.1:1234/{}/jobs'.format(db_name),
exp_key='exp1'
)
else:
logger.info('Preparing Trials..')
signal.signal(signal.SIGINT, self.signal_handler)
# read trials file if we have one
if os.path.exists(self.trials_file) and os.path.getsize(self.trials_file) > 0:
self.trials = self.read_trials()
self.current_tries = len(self.trials.results)
self.total_tries += self.current_tries
logger.info(
'Continuing with trials. Current: %d, Total: %d',
self.current_tries,
self.total_tries
)
cpus = multiprocessing.cpu_count()
logger.info(f'Found {cpus} CPU cores. Let\'s make them scream!')
opt = self.get_optimizer(cpus)
EVALS = max(self.total_tries//cpus, 1)
try:
best_parameters = fmin(
fn=self.generate_optimizer,
space=self.hyperopt_space(),
algo=tpe.suggest,
max_evals=self.total_tries,
trials=self.trials
)
with Parallel(n_jobs=cpus) as parallel:
for i in range(EVALS):
asked = opt.ask(n_points=cpus)
f_val = self.run_optimizer_parallel(parallel, asked)
opt.tell(asked, [i['loss'] for i in f_val])
results = sorted(self.trials.results, key=itemgetter('loss'))
best_result = results[0]['result']
except ValueError:
best_parameters = {}
best_result = 'Sorry, Hyperopt was not able to find good parameters. Please ' \
'try with more epochs (param: -e).'
# Improve best parameter logging display
if best_parameters:
best_parameters = space_eval(
self.hyperopt_space(),
best_parameters
)
logger.info('Best parameters:\n%s', json.dumps(best_parameters, indent=4))
if 'roi_t1' in best_parameters:
logger.info('ROI table:\n%s', self.generate_roi_table(best_parameters))
logger.info('Best Result:\n%s', best_result)
# Store trials result to file to resume next time
self.save_trials()
def signal_handler(self, sig, frame) -> None:
"""
Hyperopt SIGINT handler
"""
logger.info(
'Hyperopt received %s',
signal.Signals(sig).name
)
self.trials += f_val
for j in range(cpus):
self.log_results({
'loss': f_val[j]['loss'],
'current_tries': i * cpus + j,
'total_tries': self.total_tries,
'result': f_val[j]['result'],
})
except KeyboardInterrupt:
print('User interrupted..')
self.save_trials()
self.log_trials_result()
sys.exit(0)
def start(args: Namespace) -> None:
@ -589,18 +391,14 @@ def start(args: Namespace) -> None:
"""
# Remove noisy log messages
logging.getLogger('hyperopt.mongoexp').setLevel(logging.WARNING)
logging.getLogger('hyperopt.tpe').setLevel(logging.WARNING)
# Initialize configuration
# Monkey patch the configuration with hyperopt_conf.py
configuration = Configuration(args)
logger.info('Starting freqtrade in Hyperopt mode')
config = configuration.load_config()
optimize_config = hyperopt_optimize_conf()
config = configuration._load_common_config(optimize_config)
config = configuration._load_backtesting_config(config)
config = configuration._load_hyperopt_config(config)
config['exchange']['key'] = ''
config['exchange']['secret'] = ''

130
freqtrade/persistence.py
View File

@ -5,12 +5,11 @@ This module contains the class to persist trades into SQLite
import logging
from datetime import datetime
from decimal import Decimal, getcontext
from typing import Dict, Optional, Any
from typing import Any, Dict, Optional
import arrow
from sqlalchemy import (Boolean, Column, DateTime, Float, Integer, String,
create_engine)
from sqlalchemy import inspect
create_engine, inspect)
from sqlalchemy.exc import NoSuchModuleError
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.orm.scoping import scoped_session
@ -21,8 +20,8 @@ from freqtrade import OperationalException
logger = logging.getLogger(__name__)
_CONF = {}
_DECL_BASE: Any = declarative_base()
_SQL_DOCS_URL = 'http://docs.sqlalchemy.org/en/latest/core/engines.html#database-urls'
def init(config: Dict) -> None:
@ -33,9 +32,7 @@ def init(config: Dict) -> None:
:param config: config to use
:return: None
"""
_CONF.update(config)
db_url = _CONF.get('db_url', None)
db_url = config.get('db_url', None)
kwargs = {}
# Take care of thread ownership if in-memory db
@ -49,10 +46,8 @@ def init(config: Dict) -> None:
try:
engine = create_engine(db_url, **kwargs)
except NoSuchModuleError:
error = 'Given value for db_url: \'{}\' is no valid database URL! (See {}).'.format(
db_url, 'http://docs.sqlalchemy.org/en/latest/core/engines.html#database-urls'
)
raise OperationalException(error)
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()
@ -61,7 +56,7 @@ def init(config: Dict) -> None:
check_migrate(engine)
# Clean dry_run DB if the db is not in-memory
if _CONF.get('dry_run', False) and db_url != 'sqlite://':
if config.get('dry_run', False) and db_url != 'sqlite://':
clean_dry_run_db()
@ -69,6 +64,10 @@ def has_column(columns, searchname: str) -> bool:
return len(list(filter(lambda x: x["name"] == searchname, columns))) == 1
def get_column_def(columns, column: str, default: str) -> str:
return default if not has_column(columns, column) else column
def check_migrate(engine) -> None:
"""
Checks if migration is necessary and migrates if necessary
@ -76,18 +75,32 @@ def check_migrate(engine) -> None:
inspector = inspect(engine)
cols = inspector.get_columns('trades')
tabs = inspector.get_table_names()
table_back_name = 'trades_bak'
for i, table_back_name in enumerate(tabs):
table_back_name = f'trades_bak{i}'
logger.info(f'trying {table_back_name}')
# Check for latest column
if not has_column(cols, 'max_rate'):
open_rate_requested = get_column_def(cols, 'open_rate_requested', 'null')
close_rate_requested = get_column_def(cols, 'close_rate_requested', 'null')
stop_loss = get_column_def(cols, 'stop_loss', '0.0')
initial_stop_loss = get_column_def(cols, 'initial_stop_loss', '0.0')
max_rate = get_column_def(cols, 'max_rate', '0.0')
if not has_column(cols, 'fee_open'):
# Schema migration necessary
engine.execute("alter table trades rename to trades_bak")
engine.execute(f"alter table trades rename to {table_back_name}")
# let SQLAlchemy create the schema as required
_DECL_BASE.metadata.create_all(engine)
# Copy data back - following the correct schema
engine.execute("""insert into trades
engine.execute(f"""insert into trades
(id, exchange, pair, is_open, fee_open, fee_close, open_rate,
open_rate_requested, close_rate, close_rate_requested, close_profit,
stake_amount, amount, open_date, close_date, open_order_id)
stake_amount, amount, open_date, close_date, open_order_id,
stop_loss, initial_stop_loss, max_rate
)
select id, lower(exchange),
case
when instr(pair, '_') != 0 then
@ -97,21 +110,18 @@ def check_migrate(engine) -> None:
end
pair,
is_open, fee fee_open, fee fee_close,
open_rate, null open_rate_requested, close_rate,
null close_rate_requested, close_profit,
stake_amount, amount, open_date, close_date, open_order_id
from trades_bak
open_rate, {open_rate_requested} open_rate_requested, close_rate,
{close_rate_requested} close_rate_requested, close_profit,
stake_amount, amount, open_date, close_date, open_order_id,
{stop_loss} stop_loss, {initial_stop_loss} initial_stop_loss,
{max_rate} max_rate
from {table_back_name}
""")
# Reread columns - the above recreated the table!
inspector = inspect(engine)
cols = inspector.get_columns('trades')
if not has_column(cols, 'open_rate_requested'):
engine.execute("alter table trades add open_rate_requested float")
if not has_column(cols, 'close_rate_requested'):
engine.execute("alter table trades add close_rate_requested float")
def cleanup() -> None:
"""
@ -154,15 +164,57 @@ class Trade(_DECL_BASE):
open_date = Column(DateTime, nullable=False, default=datetime.utcnow)
close_date = Column(DateTime)
open_order_id = Column(String)
# absolute value of the stop loss
stop_loss = Column(Float, nullable=True, default=0.0)
# absolute value of the initial stop loss
initial_stop_loss = Column(Float, nullable=True, default=0.0)
# absolute value of the highest reached price
max_rate = Column(Float, nullable=True, default=0.0)
def __repr__(self):
return 'Trade(id={}, pair={}, amount={:.8f}, open_rate={:.8f}, open_since={})'.format(
self.id,
self.pair,
self.amount,
self.open_rate,
arrow.get(self.open_date).humanize() if self.is_open else 'closed'
)
open_since = arrow.get(self.open_date).humanize() if self.is_open else 'closed'
return (f'Trade(id={self.id}, pair={self.pair}, amount={self.amount:.8f}, '
f'open_rate={self.open_rate:.8f}, open_since={open_since})')
def adjust_stop_loss(self, current_price: float, stoploss: float, initial: bool = False):
"""this adjusts the stop loss to it's most recently observed setting"""
if initial and not (self.stop_loss is None or self.stop_loss == 0):
# Don't modify if called with initial and nothing to do
return
new_loss = float(current_price * (1 - abs(stoploss)))
# keeping track of the highest observed rate for this trade
if self.max_rate is None:
self.max_rate = current_price
else:
if current_price > self.max_rate:
self.max_rate = current_price
# no stop loss assigned yet
if not self.stop_loss:
logger.debug("assigning new stop loss")
self.stop_loss = new_loss
self.initial_stop_loss = new_loss
# evaluate if the stop loss needs to be updated
else:
if new_loss > self.stop_loss: # stop losses only walk up, never down!
self.stop_loss = new_loss
logger.debug("adjusted stop loss")
else:
logger.debug("keeping current stop loss")
logger.debug(
f"{self.pair} - current price {current_price:.8f}, "
f"bought at {self.open_rate:.8f} and calculated "
f"stop loss is at: {self.initial_stop_loss:.8f} initial "
f"stop at {self.stop_loss:.8f}. "
f"trailing stop loss saved us: "
f"{float(self.stop_loss) - float(self.initial_stop_loss):.8f} "
f"and max observed rate was {self.max_rate:.8f}")
def update(self, order: Dict) -> None:
"""
@ -170,6 +222,7 @@ class Trade(_DECL_BASE):
:param order: order retrieved by exchange.get_order()
:return: None
"""
order_type = order['type']
# Ignore open and cancelled orders
if order['status'] == 'open' or order['price'] is None:
return
@ -177,16 +230,16 @@ class Trade(_DECL_BASE):
logger.info('Updating trade (id=%d) ...', self.id)
getcontext().prec = 8 # Bittrex do not go above 8 decimal
if order['type'] == 'limit' and order['side'] == 'buy':
if order_type == 'limit' and order['side'] == 'buy':
# Update open rate and actual amount
self.open_rate = Decimal(order['price'])
self.amount = Decimal(order['amount'])
logger.info('LIMIT_BUY has been fulfilled for %s.', self)
self.open_order_id = None
elif order['type'] == 'limit' and order['side'] == 'sell':
elif order_type == 'limit' and order['side'] == 'sell':
self.close(order['price'])
else:
raise ValueError('Unknown order type: {}'.format(order['type']))
raise ValueError(f'Unknown order type: {order_type}')
cleanup()
def close(self, rate: float) -> None:
@ -257,7 +310,8 @@ class Trade(_DECL_BASE):
rate=(rate or self.close_rate),
fee=(fee or self.fee_close)
)
return float("{0:.8f}".format(close_trade_price - open_trade_price))
profit = close_trade_price - open_trade_price
return float(f"{profit:.8f}")
def calc_profit_percent(
self,
@ -277,5 +331,5 @@ class Trade(_DECL_BASE):
rate=(rate or self.close_rate),
fee=(fee or self.fee_close)
)
return float("{0:.8f}".format((close_trade_price / open_trade_price) - 1))
profit_percent = (close_trade_price / open_trade_price) - 1
return float(f"{profit_percent:.8f}")

258
freqtrade/rpc/rpc.py
View File

@ -2,24 +2,33 @@
This module contains class to define a RPC communications
"""
import logging
from datetime import datetime, timedelta, date
from abc import abstractmethod
from datetime import date, datetime, timedelta
from decimal import Decimal
from typing import Dict, Tuple, Any
from typing import Any, Dict, List, Tuple
import arrow
import sqlalchemy as sql
from pandas import DataFrame
from numpy import mean, nan_to_num
from pandas import DataFrame
from freqtrade import exchange
from freqtrade.misc import shorten_date
from freqtrade.persistence import Trade
from freqtrade.state import State
logger = logging.getLogger(__name__)
class RPCException(Exception):
"""
Should be raised with a rpc-formatted message in an _rpc_* method
if the required state is wrong, i.e.:
raise RPCException('*Status:* `no active trade`')
"""
pass
class RPC(object):
"""
RPC class can be used to have extra feature, like bot data, and access to DB data
@ -30,97 +39,104 @@ class RPC(object):
:param freqtrade: Instance of a freqtrade bot
:return: None
"""
self.freqtrade = freqtrade
self._freqtrade = freqtrade
def rpc_trade_status(self) -> Tuple[bool, Any]:
@abstractmethod
def cleanup(self) -> None:
""" Cleanup pending module resources """
@property
@abstractmethod
def name(self) -> str:
""" Returns the lowercase name of this module """
@abstractmethod
def send_msg(self, msg: str) -> None:
""" Sends a message to all registered rpc modules """
def _rpc_trade_status(self) -> List[str]:
"""
Below follows the RPC backend it is prefixed with rpc_ to raise awareness that it is
a remotely exposed function
:return:
"""
# Fetch open trade
trades = Trade.query.filter(Trade.is_open.is_(True)).all()
if self.freqtrade.state != State.RUNNING:
return True, '*Status:* `trader is not running`'
if self._freqtrade.state != State.RUNNING:
raise RPCException('*Status:* `trader is not running`')
elif not trades:
return True, '*Status:* `no active trade`'
raise RPCException('*Status:* `no active trade`')
else:
result = []
for trade in trades:
order = None
if trade.open_order_id:
order = exchange.get_order(trade.open_order_id, trade.pair)
order = self._freqtrade.exchange.get_order(trade.open_order_id, trade.pair)
# calculate profit and send message to user
current_rate = exchange.get_ticker(trade.pair, False)['bid']
current_rate = self._freqtrade.exchange.get_ticker(trade.pair, False)['bid']
current_profit = trade.calc_profit_percent(current_rate)
fmt_close_profit = '{:.2f}%'.format(
round(trade.close_profit * 100, 2)
) if trade.close_profit else None
message = "*Trade ID:* `{trade_id}`\n" \
"*Current Pair:* [{pair}]({market_url})\n" \
"*Open Since:* `{date}`\n" \
"*Amount:* `{amount}`\n" \
"*Open Rate:* `{open_rate:.8f}`\n" \
"*Close Rate:* `{close_rate}`\n" \
"*Current Rate:* `{current_rate:.8f}`\n" \
"*Close Profit:* `{close_profit}`\n" \
"*Current Profit:* `{current_profit:.2f}%`\n" \
"*Open Order:* `{open_order}`"\
.format(
trade_id=trade.id,
pair=trade.pair,
market_url=exchange.get_pair_detail_url(trade.pair),
date=arrow.get(trade.open_date).humanize(),
open_rate=trade.open_rate,
close_rate=trade.close_rate,
current_rate=current_rate,
amount=round(trade.amount, 8),
close_profit=fmt_close_profit,
current_profit=round(current_profit * 100, 2),
open_order='({} {} rem={:.8f})'.format(
order['type'], order['side'], order['remaining']
) if order else None,
)
result.append(message)
return False, result
fmt_close_profit = (f'{round(trade.close_profit * 100, 2):.2f}%'
if trade.close_profit else None)
market_url = self._freqtrade.exchange.get_pair_detail_url(trade.pair)
trade_date = arrow.get(trade.open_date).humanize()
open_rate = trade.open_rate
close_rate = trade.close_rate
amount = round(trade.amount, 8)
current_profit = round(current_profit * 100, 2)
open_order = ''
if order:
order_type = order['type']
order_side = order['side']
order_rem = order['remaining']
open_order = f'({order_type} {order_side} rem={order_rem:.8f})'
def rpc_status_table(self) -> Tuple[bool, Any]:
message = f"*Trade ID:* `{trade.id}`\n" \
f"*Current Pair:* [{trade.pair}]({market_url})\n" \
f"*Open Since:* `{trade_date}`\n" \
f"*Amount:* `{amount}`\n" \
f"*Open Rate:* `{open_rate:.8f}`\n" \
f"*Close Rate:* `{close_rate}`\n" \
f"*Current Rate:* `{current_rate:.8f}`\n" \
f"*Close Profit:* `{fmt_close_profit}`\n" \
f"*Current Profit:* `{current_profit:.2f}%`\n" \
f"*Open Order:* `{open_order}`"\
result.append(message)
return result
def _rpc_status_table(self) -> DataFrame:
trades = Trade.query.filter(Trade.is_open.is_(True)).all()
if self.freqtrade.state != State.RUNNING:
return True, '*Status:* `trader is not running`'
if self._freqtrade.state != State.RUNNING:
raise RPCException('*Status:* `trader is not running`')
elif not trades:
return True, '*Status:* `no active order`'
raise RPCException('*Status:* `no active order`')
else:
trades_list = []
for trade in trades:
# calculate profit and send message to user
current_rate = exchange.get_ticker(trade.pair, False)['bid']
current_rate = self._freqtrade.exchange.get_ticker(trade.pair, False)['bid']
trade_perc = (100 * trade.calc_profit_percent(current_rate))
trades_list.append([
trade.id,
trade.pair,
shorten_date(arrow.get(trade.open_date).humanize(only_distance=True)),
'{:.2f}%'.format(100 * trade.calc_profit_percent(current_rate))
f'{trade_perc:.2f}%'
])
columns = ['ID', 'Pair', 'Since', 'Profit']
df_statuses = DataFrame.from_records(trades_list, columns=columns)
df_statuses = df_statuses.set_index(columns[0])
# The style used throughout is to return a tuple
# consisting of (error_occured?, result)
# Another approach would be to just return the
# result, or raise error
return False, df_statuses
return df_statuses
def rpc_daily_profit(
def _rpc_daily_profit(
self, timescale: int,
stake_currency: str, fiat_display_currency: str) -> Tuple[bool, Any]:
stake_currency: str, fiat_display_currency: str) -> List[List[Any]]:
today = datetime.utcnow().date()
profit_days: Dict[date, Dict] = {}
if not (isinstance(timescale, int) and timescale > 0):
return True, '*Daily [n]:* `must be an integer greater than 0`'
raise RPCException('*Daily [n]:* `must be an integer greater than 0`')
fiat = self.freqtrade.fiat_converter
fiat = self._freqtrade.fiat_converter
for day in range(0, timescale):
profitday = today - timedelta(days=day)
trades = Trade.query \
@ -131,11 +147,11 @@ class RPC(object):
.all()
curdayprofit = sum(trade.calc_profit() for trade in trades)
profit_days[profitday] = {
'amount': format(curdayprofit, '.8f'),
'amount': f'{curdayprofit:.8f}',
'trades': len(trades)
}
stats = [
return [
[
key,
'{value:.8f} {symbol}'.format(
@ -157,13 +173,10 @@ class RPC(object):
]
for key, value in profit_days.items()
]
return False, stats
def rpc_trade_statistics(
self, stake_currency: str, fiat_display_currency: str) -> Tuple[bool, Any]:
"""
:return: cumulative profit statistics.
"""
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()
profit_all_coin = []
@ -186,7 +199,7 @@ class RPC(object):
profit_closed_percent.append(profit_percent)
else:
# Get current rate
current_rate = exchange.get_ticker(trade.pair, False)['bid']
current_rate = self._freqtrade.exchange.get_ticker(trade.pair, False)['bid']
profit_percent = trade.calc_profit_percent(rate=current_rate)
profit_all_coin.append(
@ -201,13 +214,13 @@ class RPC(object):
.order_by(sql.text('profit_sum DESC')).first()
if not best_pair:
return True, '*Status:* `no closed trade`'
raise RPCException('*Status:* `no closed trade`')
bp_pair, bp_rate = best_pair
# FIX: we want to keep fiatconverter in a state/environment,
# doing this will utilize its caching functionallity, instead we reinitialize it here
fiat = self.freqtrade.fiat_converter
fiat = self._freqtrade.fiat_converter
# Prepare data to display
profit_closed_coin = round(sum(profit_closed_coin), 8)
profit_closed_percent = round(nan_to_num(mean(profit_closed_percent)) * 100, 2)
@ -224,9 +237,7 @@ class RPC(object):
fiat_display_currency
)
num = float(len(durations) or 1)
return (
False,
{
return {
'profit_closed_coin': profit_closed_coin,
'profit_closed_percent': profit_closed_percent,
'profit_closed_fiat': profit_closed_fiat,
@ -238,28 +249,24 @@ class RPC(object):
'latest_trade_date': arrow.get(trades[-1].open_date).humanize(),
'avg_duration': str(timedelta(seconds=sum(durations) / num)).split('.')[0],
'best_pair': bp_pair,
'best_rate': round(bp_rate * 100, 2)
'best_rate': round(bp_rate * 100, 2),
}
)
def rpc_balance(self, fiat_display_currency: str) -> Tuple[bool, Any]:
"""
:return: current account balance per crypto
"""
def _rpc_balance(self, fiat_display_currency: str) -> Tuple[List[Dict], float, str, float]:
""" Returns current account balance per crypto """
output = []
total = 0.0
for coin, balance in exchange.get_balances().items():
for coin, balance in self._freqtrade.exchange.get_balances().items():
if not balance['total']:
continue
rate = None
if coin == 'BTC':
rate = 1.0
else:
if coin == 'USDT':
rate = 1.0 / exchange.get_ticker('BTC/USDT', False)['bid']
rate = 1.0 / self._freqtrade.exchange.get_ticker('BTC/USDT', False)['bid']
else:
rate = exchange.get_ticker(coin + '/BTC', False)['bid']
rate = self._freqtrade.exchange.get_ticker(coin + '/BTC', False)['bid']
est_btc: float = rate * balance['total']
total = total + est_btc
output.append(
@ -272,55 +279,50 @@ class RPC(object):
}
)
if total == 0.0:
return True, '`All balances are zero.`'
raise RPCException('`All balances are zero.`')
fiat = self.freqtrade.fiat_converter
fiat = self._freqtrade.fiat_converter
symbol = fiat_display_currency
value = fiat.convert_amount(total, 'BTC', symbol)
return False, (output, total, symbol, value)
return output, total, symbol, value
def rpc_start(self) -> Tuple[bool, str]:
"""
Handler for start.
"""
if self.freqtrade.state == State.RUNNING:
return True, '*Status:* `already running`'
def _rpc_start(self) -> str:
""" Handler for start """
if self._freqtrade.state == State.RUNNING:
return '*Status:* `already running`'
self.freqtrade.state = State.RUNNING
return False, '`Starting trader ...`'
self._freqtrade.state = State.RUNNING
return '`Starting trader ...`'
def rpc_stop(self) -> Tuple[bool, str]:
"""
Handler for stop.
"""
if self.freqtrade.state == State.RUNNING:
self.freqtrade.state = State.STOPPED
return False, '`Stopping trader ...`'
def _rpc_stop(self) -> str:
""" Handler for stop """
if self._freqtrade.state == State.RUNNING:
self._freqtrade.state = State.STOPPED
return '`Stopping trader ...`'
return True, '*Status:* `already stopped`'
return '*Status:* `already stopped`'
def rpc_reload_conf(self) -> str:
def _rpc_reload_conf(self) -> str:
""" Handler for reload_conf. """
self.freqtrade.state = State.RELOAD_CONF
self._freqtrade.state = State.RELOAD_CONF
return '*Status:* `Reloading config ...`'
# FIX: no test for this!!!!
def rpc_forcesell(self, trade_id) -> Tuple[bool, Any]:
def _rpc_forcesell(self, trade_id) -> None:
"""
Handler for forcesell <id>.
Sells the given trade at current price
:return: error or None
"""
def _exec_forcesell(trade: Trade) -> None:
# Check if there is there is an open order
if trade.open_order_id:
order = exchange.get_order(trade.open_order_id, trade.pair)
order = self._freqtrade.exchange.get_order(trade.open_order_id, trade.pair)
# Cancel open LIMIT_BUY orders and close trade
if order and order['status'] == 'open' \
and order['type'] == 'limit' \
and order['side'] == 'buy':
exchange.cancel_order(trade.open_order_id, trade.pair)
self._freqtrade.exchange.cancel_order(trade.open_order_id, trade.pair)
trade.close(order.get('price') or trade.open_rate)
# Do the best effort, if we don't know 'filled' amount, don't try selling
if order['filled'] is None:
@ -334,18 +336,18 @@ class RPC(object):
return
# Get current rate and execute sell
current_rate = exchange.get_ticker(trade.pair, False)['bid']
self.freqtrade.execute_sell(trade, current_rate)
current_rate = self._freqtrade.exchange.get_ticker(trade.pair, False)['bid']
self._freqtrade.execute_sell(trade, current_rate)
# ---- EOF def _exec_forcesell ----
if self.freqtrade.state != State.RUNNING:
return True, '`trader is not running`'
if self._freqtrade.state != State.RUNNING:
raise RPCException('`trader is not running`')
if trade_id == 'all':
# Execute sell for all open orders
for trade in Trade.query.filter(Trade.is_open.is_(True)).all():
_exec_forcesell(trade)
return False, ''
return
# Query for trade
trade = Trade.query.filter(
@ -356,19 +358,18 @@ class RPC(object):
).first()
if not trade:
logger.warning('forcesell: Invalid argument received')
return True, 'Invalid argument.'
raise RPCException('Invalid argument.')
_exec_forcesell(trade)
Trade.session.flush()
return False, ''
def rpc_performance(self) -> Tuple[bool, Any]:
def _rpc_performance(self) -> List[Dict]:
"""
Handler for performance.
Shows a performance statistic from finished trades
"""
if self.freqtrade.state != State.RUNNING:
return True, '`trader is not running`'
if self._freqtrade.state != State.RUNNING:
raise RPCException('`trader is not running`')
pair_rates = Trade.session.query(Trade.pair,
sql.func.sum(Trade.close_profit).label('profit_sum'),
@ -377,19 +378,14 @@ class RPC(object):
.group_by(Trade.pair) \
.order_by(sql.text('profit_sum DESC')) \
.all()
trades = []
for (pair, rate, count) in pair_rates:
trades.append({'pair': pair, 'profit': round(rate * 100, 2), 'count': count})
return [
{'pair': pair, 'profit': round(rate * 100, 2), 'count': count}
for pair, rate, count in pair_rates
]
return False, trades
def _rpc_count(self) -> List[Trade]:
""" Returns the number of trades running """
if self._freqtrade.state != State.RUNNING:
raise RPCException('`trader is not running`')
def rpc_count(self) -> Tuple[bool, Any]:
"""
Returns the number of trades running
:return: None
"""
if self.freqtrade.state != State.RUNNING:
return True, '`trader is not running`'
trades = Trade.query.filter(Trade.is_open.is_(True)).all()
return False, trades
return Trade.query.filter(Trade.is_open.is_(True)).all()

51
freqtrade/rpc/rpc_manager.py
View File

@ -1,11 +1,10 @@
"""
This module contains class to manage RPC communications (Telegram, Slack, ...)
"""
from typing import Any, List
import logging
from typing import List
from freqtrade.rpc.telegram import Telegram
from freqtrade.rpc.rpc import RPC
logger = logging.getLogger(__name__)
@ -15,36 +14,23 @@ class RPCManager(object):
Class to manage RPC objects (Telegram, Slack, ...)
"""
def __init__(self, freqtrade) -> None:
"""
Initializes all enabled rpc modules
:param config: config to use
:return: None
"""
self.freqtrade = freqtrade
""" Initializes all enabled rpc modules """
self.registered_modules: List[RPC] = []
self.registered_modules: List[str] = []
self.telegram: Any = None
self._init()
def _init(self) -> None:
"""
Init RPC modules
:return:
"""
if self.freqtrade.config['telegram'].get('enabled', False):
# Enable telegram
if freqtrade.config['telegram'].get('enabled', False):
logger.info('Enabling rpc.telegram ...')
self.registered_modules.append('telegram')
self.telegram = Telegram(self.freqtrade)
from freqtrade.rpc.telegram import Telegram
self.registered_modules.append(Telegram(freqtrade))
def cleanup(self) -> None:
"""
Stops all enabled rpc modules
:return: None
"""
if 'telegram' in self.registered_modules:
logger.info('Cleaning up rpc.telegram ...')
self.registered_modules.remove('telegram')
self.telegram.cleanup()
""" Stops all enabled rpc modules """
logger.info('Cleaning up rpc modules ...')
while self.registered_modules:
mod = self.registered_modules.pop()
logger.debug('Cleaning up rpc.%s ...', mod.name)
mod.cleanup()
del mod
def send_msg(self, msg: str) -> None:
"""
@ -52,6 +38,7 @@ class RPCManager(object):
:param msg: message
:return: None
"""
logger.info(msg)
if 'telegram' in self.registered_modules:
self.telegram.send_msg(msg)
logger.info('Sending rpc message: %s', msg)
for mod in self.registered_modules:
logger.debug('Forwarding message to rpc.%s', mod.name)
mod.send_msg(msg)

220
freqtrade/rpc/telegram.py
View File

@ -12,11 +12,12 @@ from telegram.error import NetworkError, TelegramError
from telegram.ext import CommandHandler, Updater
from freqtrade.__init__ import __version__
from freqtrade.rpc.rpc import RPC
from freqtrade.rpc.rpc import RPC, RPCException
logger = logging.getLogger(__name__)
logger.debug('Included module rpc.telegram ...')
def authorized_only(command_handler: Callable[[Any, Bot, Update], None]) -> Callable[..., Any]:
"""
@ -25,9 +26,7 @@ def authorized_only(command_handler: Callable[[Any, Bot, Update], None]) -> Call
:return: decorated function
"""
def wrapper(self, *args, **kwargs):
"""
Decorator logic
"""
""" Decorator logic """
update = kwargs.get('update') or args[1]
# Reject unauthorized messages
@ -54,9 +53,12 @@ def authorized_only(command_handler: Callable[[Any, Bot, Update], None]) -> Call
class Telegram(RPC):
"""
Telegram, this class send messages to Telegram
"""
""" This class handles all telegram communication """
@property
def name(self) -> str:
return "telegram"
def __init__(self, freqtrade) -> None:
"""
Init the Telegram call, and init the super class RPC
@ -74,12 +76,7 @@ class Telegram(RPC):
Initializes this module with the given config,
registers all known command handlers
and starts polling for message updates
:param config: config to use
:return: None
"""
if not self.is_enabled():
return
self._updater = Updater(token=self._config['telegram']['token'], workers=0)
# Register command handler and start telegram message polling
@ -115,16 +112,11 @@ class Telegram(RPC):
Stops all running telegram threads.
:return: None
"""
if not self.is_enabled():
return
self._updater.stop()
def is_enabled(self) -> bool:
"""
Returns True if the telegram module is activated, False otherwise
"""
return bool(self._config.get('telegram', {}).get('enabled', False))
def send_msg(self, msg: str) -> None:
""" Send a message to telegram channel """
self._send_msg(msg)
@authorized_only
def _status(self, bot: Bot, update: Update) -> None:
@ -143,13 +135,11 @@ class Telegram(RPC):
self._status_table(bot, update)
return
# Fetch open trade
(error, trades) = self.rpc_trade_status()
if error:
self.send_msg(trades, bot=bot)
else:
for trademsg in trades:
self.send_msg(trademsg, bot=bot)
try:
for trade_msg in self._rpc_trade_status():
self._send_msg(trade_msg, bot=bot)
except RPCException as e:
self._send_msg(str(e), bot=bot)
@authorized_only
def _status_table(self, bot: Bot, update: Update) -> None:
@ -160,15 +150,12 @@ class Telegram(RPC):
:param update: message update
:return: None
"""
# Fetch open trade
(err, df_statuses) = self.rpc_status_table()
if err:
self.send_msg(df_statuses, bot=bot)
else:
try:
df_statuses = self._rpc_status_table()
message = tabulate(df_statuses, headers='keys', tablefmt='simple')
message = "<pre>{}</pre>".format(message)
self.send_msg(message, parse_mode=ParseMode.HTML)
self._send_msg(f"<pre>{message}</pre>", parse_mode=ParseMode.HTML)
except RPCException as e:
self._send_msg(str(e), bot=bot)
@authorized_only
def _daily(self, bot: Bot, update: Update) -> None:
@ -179,31 +166,29 @@ class Telegram(RPC):
:param update: message update
:return: None
"""
stake_cur = self._config['stake_currency']
fiat_disp_cur = self._config['fiat_display_currency']
try:
timescale = int(update.message.text.replace('/daily', '').strip())
except (TypeError, ValueError):
timescale = 7
(error, stats) = self.rpc_daily_profit(
try:
stats = self._rpc_daily_profit(
timescale,
self._config['stake_currency'],
self._config['fiat_display_currency']
stake_cur,
fiat_disp_cur
)
if error:
self.send_msg(stats, bot=bot)
else:
stats = tabulate(stats,
headers=[
'Day',
'Profit {}'.format(self._config['stake_currency']),
'Profit {}'.format(self._config['fiat_display_currency'])
f'Profit {stake_cur}',
f'Profit {fiat_disp_cur}'
],
tablefmt='simple')
message = '<b>Daily Profit over the last {} days</b>:\n<pre>{}</pre>'\
.format(
timescale,
stats
)
self.send_msg(message, bot=bot, parse_mode=ParseMode.HTML)
message = f'<b>Daily Profit over the last {timescale} days</b>:\n<pre>{stats}</pre>'
self._send_msg(message, bot=bot, parse_mode=ParseMode.HTML)
except RPCException as e:
self._send_msg(str(e), bot=bot)
@authorized_only
def _profit(self, bot: Bot, update: Update) -> None:
@ -214,55 +199,48 @@ class Telegram(RPC):
:param update: message update
:return: None
"""
(error, stats) = self.rpc_trade_statistics(
self._config['stake_currency'],
self._config['fiat_display_currency']
)
if error:
self.send_msg(stats, bot=bot)
return
stake_cur = self._config['stake_currency']
fiat_disp_cur = self._config['fiat_display_currency']
try:
stats = self._rpc_trade_statistics(
stake_cur,
fiat_disp_cur)
profit_closed_coin = stats['profit_closed_coin']
profit_closed_percent = stats['profit_closed_percent']
profit_closed_fiat = stats['profit_closed_fiat']
profit_all_coin = stats['profit_all_coin']
profit_all_percent = stats['profit_all_percent']
profit_all_fiat = stats['profit_all_fiat']
trade_count = stats['trade_count']
first_trade_date = stats['first_trade_date']
latest_trade_date = stats['latest_trade_date']
avg_duration = stats['avg_duration']
best_pair = stats['best_pair']
best_rate = stats['best_rate']
# Message to display
markdown_msg = "*ROI:* Close trades\n" \
"∙ `{profit_closed_coin:.8f} {coin} ({profit_closed_percent:.2f}%)`\n" \
"∙ `{profit_closed_fiat:.3f} {fiat}`\n" \
"*ROI:* All trades\n" \
"∙ `{profit_all_coin:.8f} {coin} ({profit_all_percent:.2f}%)`\n" \
"∙ `{profit_all_fiat:.3f} {fiat}`\n" \
"*Total Trade Count:* `{trade_count}`\n" \
"*First Trade opened:* `{first_trade_date}`\n" \
"*Latest Trade opened:* `{latest_trade_date}`\n" \
"*Avg. Duration:* `{avg_duration}`\n" \
"*Best Performing:* `{best_pair}: {best_rate:.2f}%`"\
.format(
coin=self._config['stake_currency'],
fiat=self._config['fiat_display_currency'],
profit_closed_coin=stats['profit_closed_coin'],
profit_closed_percent=stats['profit_closed_percent'],
profit_closed_fiat=stats['profit_closed_fiat'],
profit_all_coin=stats['profit_all_coin'],
profit_all_percent=stats['profit_all_percent'],
profit_all_fiat=stats['profit_all_fiat'],
trade_count=stats['trade_count'],
first_trade_date=stats['first_trade_date'],
latest_trade_date=stats['latest_trade_date'],
avg_duration=stats['avg_duration'],
best_pair=stats['best_pair'],
best_rate=stats['best_rate']
)
self.send_msg(markdown_msg, bot=bot)
f"∙ `{profit_closed_coin:.8f} {stake_cur} "\
f"({profit_closed_percent:.2f}%)`\n" \
f"∙ `{profit_closed_fiat:.3f} {fiat_disp_cur}`\n" \
f"*ROI:* All trades\n" \
f"∙ `{profit_all_coin:.8f} {stake_cur} ({profit_all_percent:.2f}%)`\n" \
f"∙ `{profit_all_fiat:.3f} {fiat_disp_cur}`\n" \
f"*Total Trade Count:* `{trade_count}`\n" \
f"*First Trade opened:* `{first_trade_date}`\n" \
f"*Latest Trade opened:* `{latest_trade_date}`\n" \
f"*Avg. Duration:* `{avg_duration}`\n" \
f"*Best Performing:* `{best_pair}: {best_rate:.2f}%`"
self._send_msg(markdown_msg, bot=bot)
except RPCException as e:
self._send_msg(str(e), bot=bot)
@authorized_only
def _balance(self, bot: Bot, update: Update) -> None:
"""
Handler for /balance
"""
(error, result) = self.rpc_balance(self._config['fiat_display_currency'])
if error:
self.send_msg('`All balances are zero.`')
return
(currencys, total, symbol, value) = result
""" Handler for /balance """
try:
currencys, total, symbol, value = \
self._rpc_balance(self._config['fiat_display_currency'])
output = ''
for currency in currencys:
output += "*{currency}:*\n" \
@ -274,7 +252,9 @@ class Telegram(RPC):
output += "\n*Estimated Value*:\n" \
"\t`BTC: {0: .8f}`\n" \
"\t`{1}: {2: .2f}`\n".format(total, symbol, value)
self.send_msg(output)
self._send_msg(output, bot=bot)
except RPCException as e:
self._send_msg(str(e), bot=bot)
@authorized_only
def _start(self, bot: Bot, update: Update) -> None:
@ -285,9 +265,8 @@ class Telegram(RPC):
:param update: message update
:return: None
"""
(error, msg) = self.rpc_start()
if error:
self.send_msg(msg, bot=bot)
msg = self._rpc_start()
self._send_msg(msg, bot=bot)
@authorized_only
def _stop(self, bot: Bot, update: Update) -> None:
@ -298,8 +277,8 @@ class Telegram(RPC):
:param update: message update
:return: None
"""
(error, msg) = self.rpc_stop()
self.send_msg(msg, bot=bot)
msg = self._rpc_stop()
self._send_msg(msg, bot=bot)
@authorized_only
def _reload_conf(self, bot: Bot, update: Update) -> None:
@ -310,8 +289,8 @@ class Telegram(RPC):
:param update: message update
:return: None
"""
msg = self.rpc_reload_conf()
self.send_msg(msg, bot=bot)
msg = self._rpc_reload_conf()
self._send_msg(msg, bot=bot)
@authorized_only
def _forcesell(self, bot: Bot, update: Update) -> None:
@ -324,10 +303,10 @@ class Telegram(RPC):
"""
trade_id = update.message.text.replace('/forcesell', '').strip()
(error, message) = self.rpc_forcesell(trade_id)
if error:
self.send_msg(message, bot=bot)
return
try:
self._rpc_forcesell(trade_id)
except RPCException as e:
self._send_msg(str(e), bot=bot)
@authorized_only
def _performance(self, bot: Bot, update: Update) -> None:
@ -338,11 +317,8 @@ class Telegram(RPC):
:param update: message update
:return: None
"""
(error, trades) = self.rpc_performance()
if error:
self.send_msg(trades, bot=bot)
return
try:
trades = self._rpc_performance()
stats = '\n'.join('{index}.\t<code>{pair}\t{profit:.2f}% ({count})</code>'.format(
index=i + 1,
pair=trade['pair'],
@ -350,7 +326,9 @@ class Telegram(RPC):
count=trade['count']
) for i, trade in enumerate(trades))
message = '<b>Performance:</b>\n{}'.format(stats)
self.send_msg(message, parse_mode=ParseMode.HTML)
self._send_msg(message, parse_mode=ParseMode.HTML)
except RPCException as e:
self._send_msg(str(e), bot=bot)
@authorized_only
def _count(self, bot: Bot, update: Update) -> None:
@ -361,11 +339,8 @@ class Telegram(RPC):
:param update: message update
:return: None
"""
(error, trades) = self.rpc_count()
if error:
self.send_msg(trades, bot=bot)
return
try:
trades = self._rpc_count()
message = tabulate({
'current': [len(trades)],
'max': [self._config['max_open_trades']],
@ -373,7 +348,9 @@ class Telegram(RPC):
}, headers=['current', 'max', 'total stake'], tablefmt='simple')
message = "<pre>{}</pre>".format(message)
logger.debug(message)
self.send_msg(message, parse_mode=ParseMode.HTML)
self._send_msg(message, parse_mode=ParseMode.HTML)
except RPCException as e:
self._send_msg(str(e), bot=bot)
@authorized_only
def _help(self, bot: Bot, update: Update) -> None:
@ -399,7 +376,7 @@ class Telegram(RPC):
"*/help:* `This help message`\n" \
"*/version:* `Show version`"
self.send_msg(message, bot=bot)
self._send_msg(message, bot=bot)
@authorized_only
def _version(self, bot: Bot, update: Update) -> None:
@ -410,9 +387,9 @@ class Telegram(RPC):
:param update: message update
:return: None
"""
self.send_msg('*Version:* `{}`'.format(__version__), bot=bot)
self._send_msg('*Version:* `{}`'.format(__version__), bot=bot)
def send_msg(self, msg: str, bot: Bot = None,
def _send_msg(self, msg: str, bot: Bot = None,
parse_mode: ParseMode = ParseMode.MARKDOWN) -> None:
"""
Send given markdown message
@ -421,9 +398,6 @@ class Telegram(RPC):
:param parse_mode: telegram parse mode
:return: None
"""
if not self.is_enabled():
return
bot = bot or self._updater.bot
keyboard = [['/daily', '/profit', '/balance'],

32
freqtrade/strategy/__init__.py
View File

@ -0,0 +1,32 @@
import logging
from copy import deepcopy
from freqtrade.strategy.interface import IStrategy
logger = logging.getLogger(__name__)
def import_strategy(strategy: IStrategy) -> IStrategy:
"""
Imports given Strategy instance to global scope
of freqtrade.strategy and returns an instance of it
"""
# Copy all attributes from base class and class
attr = deepcopy({**strategy.__class__.__dict__, **strategy.__dict__})
# Adjust module name
attr['__module__'] = 'freqtrade.strategy'
name = strategy.__class__.__name__
clazz = type(name, (IStrategy,), attr)
logger.debug(
'Imported strategy %s.%s as %s.%s',
strategy.__module__, strategy.__class__.__name__,
clazz.__module__, strategy.__class__.__name__,
)
# Modify global scope to declare class
globals()[name] = clazz
return clazz()

1
freqtrade/strategy/interface.py
View File

@ -3,6 +3,7 @@ IStrategy interface
This module defines the interface to apply for strategies
"""
import warnings
from abc import ABC, abstractmethod
from typing import Dict
from abc import ABC

12
freqtrade/strategy/resolver.py
View File

@ -8,9 +8,10 @@ import inspect
import logging
import os
from collections import OrderedDict
from typing import Optional, Dict, Type
from typing import Dict, Optional, Type
from freqtrade import constants
from freqtrade.strategy import import_strategy
from freqtrade.strategy.interface import IStrategy
logger = logging.getLogger(__name__)
@ -70,7 +71,7 @@ class StrategyResolver(object):
"""
current_path = os.path.dirname(os.path.realpath(__file__))
abs_paths = [
os.path.join(current_path, '..', '..', 'user_data', 'strategies'),
os.path.join(os.getcwd(), 'user_data', 'strategies'),
current_path,
]
@ -79,10 +80,13 @@ class StrategyResolver(object):
abs_paths.insert(0, extra_dir)
for path in abs_paths:
try:
strategy = self._search_strategy(path, strategy_name)
if strategy:
logger.info('Using resolved strategy %s from \'%s\'', strategy_name, path)
return strategy
return import_strategy(strategy)
except FileNotFoundError:
logger.warning('Path "%s" does not exist', path)
raise ImportError(
"Impossible to load Strategy '{}'. This class does not exist"
@ -99,7 +103,7 @@ class StrategyResolver(object):
"""
# Generate spec based on absolute path
spec = importlib.util.spec_from_file_location('user_data.strategies', module_path)
spec = importlib.util.spec_from_file_location('unknown', module_path)
module = importlib.util.module_from_spec(spec)
spec.loader.exec_module(module) # type: ignore # importlib does not use typehints

116
freqtrade/tests/conftest.py
View File

@ -2,8 +2,8 @@
import json
import logging
from datetime import datetime
from typing import Dict, Optional
from functools import reduce
from typing import Dict, Optional
from unittest.mock import MagicMock
import arrow
@ -11,8 +11,9 @@ import pytest
from jsonschema import validate
from telegram import Chat, Message, Update
from freqtrade.analyze import Analyze
from freqtrade import constants
from freqtrade.analyze import Analyze
from freqtrade.exchange import Exchange
from freqtrade.freqtradebot import FreqtradeBot
logging.getLogger('').setLevel(logging.INFO)
@ -26,6 +27,20 @@ def log_has(line, logs):
False)
def patch_exchange(mocker, api_mock=None) -> None:
mocker.patch('freqtrade.exchange.Exchange.validate_pairs', MagicMock())
if api_mock:
mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=api_mock))
else:
mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock())
def get_patched_exchange(mocker, config, api_mock=None) -> Exchange:
patch_exchange(mocker, api_mock)
exchange = Exchange(config)
return exchange
# Functions for recurrent object patching
def get_patched_freqtradebot(mocker, config) -> FreqtradeBot:
"""
@ -39,7 +54,7 @@ def get_patched_freqtradebot(mocker, config) -> FreqtradeBot:
mocker.patch('freqtrade.freqtradebot.Analyze', MagicMock())
mocker.patch('freqtrade.freqtradebot.RPCManager', MagicMock())
mocker.patch('freqtrade.freqtradebot.persistence.init', MagicMock())
mocker.patch('freqtrade.freqtradebot.exchange.init', MagicMock())
patch_exchange(mocker, None)
mocker.patch('freqtrade.freqtradebot.RPCManager._init', MagicMock())
mocker.patch('freqtrade.freqtradebot.RPCManager.send_msg', MagicMock())
mocker.patch('freqtrade.freqtradebot.Analyze.get_signal', MagicMock())
@ -85,7 +100,10 @@ def default_conf():
"0": 0.04
},
"stoploss": -0.10,
"unfilledtimeout": 600,
"unfilledtimeout": {
"buy": 10,
"sell": 30
},
"bid_strategy": {
"ask_last_balance": 0.0
},
@ -174,7 +192,10 @@ def markets():
'max': 1000,
},
'price': 500000,
'cost': 500000,
'cost': {
'min': 1,
'max': 500000,
},
},
'info': '',
},
@ -196,7 +217,10 @@ def markets():
'max': 1000,
},
'price': 500000,
'cost': 500000,
'cost': {
'min': 1,
'max': 500000,
},
},
'info': '',
},
@ -218,7 +242,85 @@ def markets():
'max': 1000,
},
'price': 500000,
'cost': 500000,
'cost': {
'min': 1,
'max': 500000,
},
},
'info': '',
},
{
'id': 'ltcbtc',
'symbol': 'LTC/BTC',
'base': 'LTC',
'quote': 'BTC',
'active': False,
'precision': {
'price': 8,
'amount': 8,
'cost': 8,
},
'lot': 0.00000001,
'limits': {
'amount': {
'min': 0.01,
'max': 1000,
},
'price': 500000,
'cost': {
'min': 1,
'max': 500000,
},
},
'info': '',
},
{
'id': 'xrpbtc',
'symbol': 'XRP/BTC',
'base': 'XRP',
'quote': 'BTC',
'active': False,
'precision': {
'price': 8,
'amount': 8,
'cost': 8,
},
'lot': 0.00000001,
'limits': {
'amount': {
'min': 0.01,
'max': 1000,
},
'price': 500000,
'cost': {
'min': 1,
'max': 500000,
},
},
'info': '',
},
{
'id': 'neobtc',
'symbol': 'NEO/BTC',
'base': 'NEO',
'quote': 'BTC',
'active': False,
'precision': {
'price': 8,
'amount': 8,
'cost': 8,
},
'lot': 0.00000001,
'limits': {
'amount': {
'min': 0.01,
'max': 1000,
},
'price': 500000,
'cost': {
'min': 1,
'max': 500000,
},
},
'info': '',
}

472
freqtrade/tests/exchange/test_exchange.py
View File

@ -2,44 +2,54 @@
# pragma pylint: disable=protected-access
import logging
from copy import deepcopy
from datetime import datetime
from random import randint
from unittest.mock import MagicMock, PropertyMock
import ccxt
import pytest
import freqtrade.exchange as exchange
from freqtrade import OperationalException, DependencyException, TemporaryError
from freqtrade.exchange import (init, validate_pairs, buy, sell, get_balance, get_balances,
get_ticker, get_ticker_history, cancel_order, get_name, get_fee,
get_id, get_pair_detail_url, get_amount_lots)
from freqtrade.tests.conftest import log_has
API_INIT = False
from freqtrade import DependencyException, OperationalException, TemporaryError
from freqtrade.exchange import API_RETRY_COUNT, Exchange
from freqtrade.tests.conftest import get_patched_exchange, log_has
def maybe_init_api(conf, mocker, force=False):
global API_INIT
if force or not API_INIT:
mocker.patch('freqtrade.exchange.validate_pairs',
side_effect=lambda s: True)
init(config=conf)
API_INIT = True
def ccxt_exceptionhandlers(mocker, default_conf, api_mock, fun, mock_ccxt_fun, **kwargs):
"""Function to test ccxt exception handling """
with pytest.raises(TemporaryError):
api_mock.__dict__[mock_ccxt_fun] = MagicMock(side_effect=ccxt.NetworkError)
exchange = get_patched_exchange(mocker, default_conf, api_mock)
getattr(exchange, fun)(**kwargs)
assert api_mock.__dict__[mock_ccxt_fun].call_count == API_RETRY_COUNT + 1
with pytest.raises(OperationalException):
api_mock.__dict__[mock_ccxt_fun] = MagicMock(side_effect=ccxt.BaseError)
exchange = get_patched_exchange(mocker, default_conf, api_mock)
getattr(exchange, fun)(**kwargs)
assert api_mock.__dict__[mock_ccxt_fun].call_count == 1
def test_init(default_conf, mocker, caplog):
caplog.set_level(logging.INFO)
maybe_init_api(default_conf, mocker, True)
get_patched_exchange(mocker, default_conf)
assert log_has('Instance is running with dry_run enabled', caplog.record_tuples)
def test_init_exception(default_conf):
def test_init_exception(default_conf, mocker):
default_conf['exchange']['name'] = 'wrong_exchange_name'
with pytest.raises(
OperationalException,
match='Exchange {} is not supported'.format(default_conf['exchange']['name'])):
init(config=default_conf)
Exchange(default_conf)
default_conf['exchange']['name'] = 'binance'
with pytest.raises(
OperationalException,
match='Exchange {} is not supported'.format(default_conf['exchange']['name'])):
mocker.patch("ccxt.binance", MagicMock(side_effect=AttributeError))
Exchange(default_conf)
def test_validate_pairs(default_conf, mocker):
@ -50,18 +60,17 @@ def test_validate_pairs(default_conf, mocker):
id_mock = PropertyMock(return_value='test_exchange')
type(api_mock).id = id_mock
mocker.patch('freqtrade.exchange._API', api_mock)
mocker.patch.dict('freqtrade.exchange._CONF', default_conf)
validate_pairs(default_conf['exchange']['pair_whitelist'])
mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=api_mock))
Exchange(default_conf)
def test_validate_pairs_not_available(default_conf, mocker):
api_mock = MagicMock()
api_mock.load_markets = MagicMock(return_value={})
mocker.patch('freqtrade.exchange._API', api_mock)
mocker.patch.dict('freqtrade.exchange._CONF', default_conf)
mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=api_mock))
with pytest.raises(OperationalException, match=r'not available'):
validate_pairs(default_conf['exchange']['pair_whitelist'])
Exchange(default_conf)
def test_validate_pairs_not_compatible(default_conf, mocker):
@ -71,25 +80,27 @@ def test_validate_pairs_not_compatible(default_conf, mocker):
})
conf = deepcopy(default_conf)
conf['stake_currency'] = 'ETH'
mocker.patch('freqtrade.exchange._API', api_mock)
mocker.patch.dict('freqtrade.exchange._CONF', conf)
mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=api_mock))
with pytest.raises(OperationalException, match=r'not compatible'):
validate_pairs(conf['exchange']['pair_whitelist'])
Exchange(conf)
def test_validate_pairs_exception(default_conf, mocker, caplog):
caplog.set_level(logging.INFO)
api_mock = MagicMock()
api_mock.name = 'Binance'
mocker.patch('freqtrade.exchange._API', api_mock)
mocker.patch.dict('freqtrade.exchange._CONF', default_conf)
mocker.patch('freqtrade.exchange.Exchange.name', PropertyMock(return_value='Binance'))
api_mock.load_markets = MagicMock(return_value={})
mocker.patch('freqtrade.exchange.Exchange._init_ccxt', api_mock)
with pytest.raises(OperationalException, match=r'Pair ETH/BTC is not available at Binance'):
validate_pairs(default_conf['exchange']['pair_whitelist'])
Exchange(default_conf)
api_mock.load_markets = MagicMock(side_effect=ccxt.BaseError())
validate_pairs(default_conf['exchange']['pair_whitelist'])
mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=api_mock))
Exchange(default_conf)
assert log_has('Unable to validate pairs (assuming they are correct). Reason: ',
caplog.record_tuples)
@ -99,22 +110,35 @@ def test_validate_pairs_stake_exception(default_conf, mocker, caplog):
conf = deepcopy(default_conf)
conf['stake_currency'] = 'ETH'
api_mock = MagicMock()
api_mock.name = 'binance'
mocker.patch('freqtrade.exchange._API', api_mock)
mocker.patch.dict('freqtrade.exchange._CONF', conf)
api_mock.name = MagicMock(return_value='binance')
mocker.patch('freqtrade.exchange.Exchange._init_ccxt', api_mock)
with pytest.raises(
OperationalException,
match=r'Pair ETH/BTC not compatible with stake_currency: ETH'
):
validate_pairs(default_conf['exchange']['pair_whitelist'])
Exchange(conf)
def test_exchangehas(default_conf, mocker):
exchange = get_patched_exchange(mocker, default_conf)
assert not exchange.exchange_has('ASDFASDF')
api_mock = MagicMock()
type(api_mock).has = PropertyMock(return_value={'deadbeef': True})
exchange = get_patched_exchange(mocker, default_conf, api_mock)
assert exchange.exchange_has("deadbeef")
type(api_mock).has = PropertyMock(return_value={'deadbeef': False})
exchange = get_patched_exchange(mocker, default_conf, api_mock)
assert not exchange.exchange_has("deadbeef")
def test_buy_dry_run(default_conf, mocker):
default_conf['dry_run'] = True
mocker.patch.dict('freqtrade.exchange._CONF', default_conf)
exchange = get_patched_exchange(mocker, default_conf)
order = buy(pair='ETH/BTC', rate=200, amount=1)
order = exchange.buy(pair='ETH/BTC', rate=200, amount=1)
assert 'id' in order
assert 'dry_run_buy_' in order['id']
@ -128,12 +152,10 @@ def test_buy_prod(default_conf, mocker):
'foo': 'bar'
}
})
mocker.patch('freqtrade.exchange._API', api_mock)
default_conf['dry_run'] = False
mocker.patch.dict('freqtrade.exchange._CONF', default_conf)
exchange = get_patched_exchange(mocker, default_conf, api_mock)
order = buy(pair='ETH/BTC', rate=200, amount=1)
order = exchange.buy(pair='ETH/BTC', rate=200, amount=1)
assert 'id' in order
assert 'info' in order
assert order['id'] == order_id
@ -141,30 +163,30 @@ def test_buy_prod(default_conf, mocker):
# test exception handling
with pytest.raises(DependencyException):
api_mock.create_limit_buy_order = MagicMock(side_effect=ccxt.InsufficientFunds)
mocker.patch('freqtrade.exchange._API', api_mock)
buy(pair='ETH/BTC', rate=200, amount=1)
exchange = get_patched_exchange(mocker, default_conf, api_mock)
exchange.buy(pair='ETH/BTC', rate=200, amount=1)
with pytest.raises(DependencyException):
api_mock.create_limit_buy_order = MagicMock(side_effect=ccxt.InvalidOrder)
mocker.patch('freqtrade.exchange._API', api_mock)
buy(pair='ETH/BTC', rate=200, amount=1)
exchange = get_patched_exchange(mocker, default_conf, api_mock)
exchange.buy(pair='ETH/BTC', rate=200, amount=1)
with pytest.raises(TemporaryError):
api_mock.create_limit_buy_order = MagicMock(side_effect=ccxt.NetworkError)
mocker.patch('freqtrade.exchange._API', api_mock)
buy(pair='ETH/BTC', rate=200, amount=1)
exchange = get_patched_exchange(mocker, default_conf, api_mock)
exchange.buy(pair='ETH/BTC', rate=200, amount=1)
with pytest.raises(OperationalException):
api_mock.create_limit_buy_order = MagicMock(side_effect=ccxt.BaseError)
mocker.patch('freqtrade.exchange._API', api_mock)
buy(pair='ETH/BTC', rate=200, amount=1)
exchange = get_patched_exchange(mocker, default_conf, api_mock)
exchange.buy(pair='ETH/BTC', rate=200, amount=1)
def test_sell_dry_run(default_conf, mocker):
default_conf['dry_run'] = True
mocker.patch.dict('freqtrade.exchange._CONF', default_conf)
exchange = get_patched_exchange(mocker, default_conf)
order = sell(pair='ETH/BTC', rate=200, amount=1)
order = exchange.sell(pair='ETH/BTC', rate=200, amount=1)
assert 'id' in order
assert 'dry_run_sell_' in order['id']
@ -178,12 +200,11 @@ def test_sell_prod(default_conf, mocker):
'foo': 'bar'
}
})
mocker.patch('freqtrade.exchange._API', api_mock)
default_conf['dry_run'] = False
mocker.patch.dict('freqtrade.exchange._CONF', default_conf)
order = sell(pair='ETH/BTC', rate=200, amount=1)
exchange = get_patched_exchange(mocker, default_conf, api_mock)
order = exchange.sell(pair='ETH/BTC', rate=200, amount=1)
assert 'id' in order
assert 'info' in order
assert order['id'] == order_id
@ -191,53 +212,57 @@ def test_sell_prod(default_conf, mocker):
# test exception handling
with pytest.raises(DependencyException):
api_mock.create_limit_sell_order = MagicMock(side_effect=ccxt.InsufficientFunds)
mocker.patch('freqtrade.exchange._API', api_mock)
sell(pair='ETH/BTC', rate=200, amount=1)
exchange = get_patched_exchange(mocker, default_conf, api_mock)
exchange.sell(pair='ETH/BTC', rate=200, amount=1)
with pytest.raises(DependencyException):
api_mock.create_limit_sell_order = MagicMock(side_effect=ccxt.InvalidOrder)
mocker.patch('freqtrade.exchange._API', api_mock)
sell(pair='ETH/BTC', rate=200, amount=1)
exchange = get_patched_exchange(mocker, default_conf, api_mock)
exchange.sell(pair='ETH/BTC', rate=200, amount=1)
with pytest.raises(TemporaryError):
api_mock.create_limit_sell_order = MagicMock(side_effect=ccxt.NetworkError)
mocker.patch('freqtrade.exchange._API', api_mock)
sell(pair='ETH/BTC', rate=200, amount=1)
exchange = get_patched_exchange(mocker, default_conf, api_mock)
exchange.sell(pair='ETH/BTC', rate=200, amount=1)
with pytest.raises(OperationalException):
api_mock.create_limit_sell_order = MagicMock(side_effect=ccxt.BaseError)
mocker.patch('freqtrade.exchange._API', api_mock)
sell(pair='ETH/BTC', rate=200, amount=1)
exchange = get_patched_exchange(mocker, default_conf, api_mock)
exchange.sell(pair='ETH/BTC', rate=200, amount=1)
def test_get_balance_dry_run(default_conf, mocker):
default_conf['dry_run'] = True
mocker.patch.dict('freqtrade.exchange._CONF', default_conf)
assert get_balance(currency='BTC') == 999.9
exchange = get_patched_exchange(mocker, default_conf)
assert exchange.get_balance(currency='BTC') == 999.9
def test_get_balance_prod(default_conf, mocker):
api_mock = MagicMock()
api_mock.fetch_balance = MagicMock(return_value={'BTC': {'free': 123.4}})
mocker.patch('freqtrade.exchange._API', api_mock)
default_conf['dry_run'] = False
mocker.patch.dict('freqtrade.exchange._CONF', default_conf)
assert get_balance(currency='BTC') == 123.4
exchange = get_patched_exchange(mocker, default_conf, api_mock)
assert exchange.get_balance(currency='BTC') == 123.4
with pytest.raises(OperationalException):
api_mock.fetch_balance = MagicMock(side_effect=ccxt.BaseError)
mocker.patch('freqtrade.exchange._API', api_mock)
get_balance(currency='BTC')
exchange = get_patched_exchange(mocker, default_conf, api_mock)
exchange.get_balance(currency='BTC')
with pytest.raises(TemporaryError, match=r'.*balance due to malformed exchange response:.*'):
exchange = get_patched_exchange(mocker, default_conf, api_mock)
mocker.patch('freqtrade.exchange.Exchange.get_balances', MagicMock(return_value={}))
exchange.get_balance(currency='BTC')
def test_get_balances_dry_run(default_conf, mocker):
default_conf['dry_run'] = True
mocker.patch.dict('freqtrade.exchange._CONF', default_conf)
assert get_balances() == {}
exchange = get_patched_exchange(mocker, default_conf)
assert exchange.get_balances() == {}
def test_get_balances_prod(default_conf, mocker):
@ -253,33 +278,57 @@ def test_get_balances_prod(default_conf, mocker):
'2ST': balance_item,
'3ST': balance_item
})
mocker.patch('freqtrade.exchange._API', api_mock)
default_conf['dry_run'] = False
mocker.patch.dict('freqtrade.exchange._CONF', default_conf)
exchange = get_patched_exchange(mocker, default_conf, api_mock)
assert len(exchange.get_balances()) == 3
assert exchange.get_balances()['1ST']['free'] == 10.0
assert exchange.get_balances()['1ST']['total'] == 10.0
assert exchange.get_balances()['1ST']['used'] == 0.0
assert len(get_balances()) == 3
assert get_balances()['1ST']['free'] == 10.0
assert get_balances()['1ST']['total'] == 10.0
assert get_balances()['1ST']['used'] == 0.0
ccxt_exceptionhandlers(mocker, default_conf, api_mock,
"get_balances", "fetch_balance")
with pytest.raises(TemporaryError):
api_mock.fetch_balance = MagicMock(side_effect=ccxt.NetworkError)
mocker.patch('freqtrade.exchange._API', api_mock)
get_balances()
assert api_mock.fetch_balance.call_count == exchange.API_RETRY_COUNT + 1
def test_get_tickers(default_conf, mocker):
api_mock = MagicMock()
tick = {'ETH/BTC': {
'symbol': 'ETH/BTC',
'bid': 0.5,
'ask': 1,
'last': 42,
}, 'BCH/BTC': {
'symbol': 'BCH/BTC',
'bid': 0.6,
'ask': 0.5,
'last': 41,
}
}
api_mock.fetch_tickers = MagicMock(return_value=tick)
exchange = get_patched_exchange(mocker, default_conf, api_mock)
# retrieve original ticker
tickers = exchange.get_tickers()
assert 'ETH/BTC' in tickers
assert 'BCH/BTC' in tickers
assert tickers['ETH/BTC']['bid'] == 0.5
assert tickers['ETH/BTC']['ask'] == 1
assert tickers['BCH/BTC']['bid'] == 0.6
assert tickers['BCH/BTC']['ask'] == 0.5
ccxt_exceptionhandlers(mocker, default_conf, api_mock,
"get_tickers", "fetch_tickers")
with pytest.raises(OperationalException):
api_mock.fetch_balance = MagicMock(side_effect=ccxt.BaseError)
mocker.patch('freqtrade.exchange._API', api_mock)
get_balances()
assert api_mock.fetch_balance.call_count == 1
api_mock.fetch_tickers = MagicMock(side_effect=ccxt.NotSupported)
exchange = get_patched_exchange(mocker, default_conf, api_mock)
exchange.get_tickers()
api_mock.fetch_tickers = MagicMock(return_value={})
exchange = get_patched_exchange(mocker, default_conf, api_mock)
exchange.get_tickers()
# This test is somewhat redundant with
# test_exchange_bittrex.py::test_exchange_bittrex_get_ticker
def test_get_ticker(default_conf, mocker):
maybe_init_api(default_conf, mocker)
api_mock = MagicMock()
tick = {
'symbol': 'ETH/BTC',
@ -288,10 +337,9 @@ def test_get_ticker(default_conf, mocker):
'last': 0.0001,
}
api_mock.fetch_ticker = MagicMock(return_value=tick)
mocker.patch('freqtrade.exchange._API', api_mock)
exchange = get_patched_exchange(mocker, default_conf, api_mock)
# retrieve original ticker
ticker = get_ticker(pair='ETH/BTC')
ticker = exchange.get_ticker(pair='ETH/BTC')
assert ticker['bid'] == 0.00001098
assert ticker['ask'] == 0.00001099
@ -304,38 +352,32 @@ def test_get_ticker(default_conf, mocker):
'last': 42,
}
api_mock.fetch_ticker = MagicMock(return_value=tick)
mocker.patch('freqtrade.exchange._API', api_mock)
exchange = get_patched_exchange(mocker, default_conf, api_mock)
# if not caching the result we should get the same ticker
# if not fetching a new result we should get the cached ticker
ticker = get_ticker(pair='ETH/BTC')
ticker = exchange.get_ticker(pair='ETH/BTC')
assert api_mock.fetch_ticker.call_count == 1
assert ticker['bid'] == 0.5
assert ticker['ask'] == 1
assert 'ETH/BTC' in exchange._CACHED_TICKER
assert exchange._CACHED_TICKER['ETH/BTC']['bid'] == 0.5
assert exchange._CACHED_TICKER['ETH/BTC']['ask'] == 1
assert 'ETH/BTC' in exchange._cached_ticker
assert exchange._cached_ticker['ETH/BTC']['bid'] == 0.5
assert exchange._cached_ticker['ETH/BTC']['ask'] == 1
# Test caching
api_mock.fetch_ticker = MagicMock()
get_ticker(pair='ETH/BTC', refresh=False)
exchange.get_ticker(pair='ETH/BTC', refresh=False)
assert api_mock.fetch_ticker.call_count == 0
with pytest.raises(TemporaryError): # test retrier
api_mock.fetch_ticker = MagicMock(side_effect=ccxt.NetworkError)
mocker.patch('freqtrade.exchange._API', api_mock)
get_ticker(pair='ETH/BTC', refresh=True)
with pytest.raises(OperationalException):
api_mock.fetch_ticker = MagicMock(side_effect=ccxt.BaseError)
mocker.patch('freqtrade.exchange._API', api_mock)
get_ticker(pair='ETH/BTC', refresh=True)
ccxt_exceptionhandlers(mocker, default_conf, api_mock,
"get_ticker", "fetch_ticker",
pair='ETH/BTC', refresh=True)
api_mock.fetch_ticker = MagicMock(return_value={})
mocker.patch('freqtrade.exchange._API', api_mock)
get_ticker(pair='ETH/BTC', refresh=True)
exchange = get_patched_exchange(mocker, default_conf, api_mock)
exchange.get_ticker(pair='ETH/BTC', refresh=True)
def make_fetch_ohlcv_mock(data):
@ -361,10 +403,10 @@ def test_get_ticker_history(default_conf, mocker):
]
type(api_mock).has = PropertyMock(return_value={'fetchOHLCV': True})
api_mock.fetch_ohlcv = MagicMock(side_effect=make_fetch_ohlcv_mock(tick))
mocker.patch('freqtrade.exchange._API', api_mock)
exchange = get_patched_exchange(mocker, default_conf, api_mock)
# retrieve original ticker
ticks = get_ticker_history('ETH/BTC', default_conf['ticker_interval'])
ticks = exchange.get_ticker_history('ETH/BTC', default_conf['ticker_interval'])
assert ticks[0][0] == 1511686200000
assert ticks[0][1] == 1
assert ticks[0][2] == 2
@ -384,9 +426,9 @@ def test_get_ticker_history(default_conf, mocker):
]
]
api_mock.fetch_ohlcv = MagicMock(side_effect=make_fetch_ohlcv_mock(new_tick))
mocker.patch('freqtrade.exchange._API', api_mock)
exchange = get_patched_exchange(mocker, default_conf, api_mock)
ticks = get_ticker_history('ETH/BTC', default_conf['ticker_interval'])
ticks = exchange.get_ticker_history('ETH/BTC', default_conf['ticker_interval'])
assert ticks[0][0] == 1511686210000
assert ticks[0][1] == 6
assert ticks[0][2] == 7
@ -394,17 +436,14 @@ def test_get_ticker_history(default_conf, mocker):
assert ticks[0][4] == 9
assert ticks[0][5] == 10
with pytest.raises(TemporaryError): # test retrier
api_mock.fetch_ohlcv = MagicMock(side_effect=ccxt.NetworkError)
mocker.patch('freqtrade.exchange._API', api_mock)
# new symbol to get around cache
get_ticker_history('ABCD/BTC', default_conf['ticker_interval'])
ccxt_exceptionhandlers(mocker, default_conf, api_mock,
"get_ticker_history", "fetch_ohlcv",
pair='ABCD/BTC', tick_interval=default_conf['ticker_interval'])
with pytest.raises(OperationalException):
api_mock.fetch_ohlcv = MagicMock(side_effect=ccxt.BaseError)
mocker.patch('freqtrade.exchange._API', api_mock)
# new symbol to get around cache
get_ticker_history('EFGH/BTC', default_conf['ticker_interval'])
with pytest.raises(OperationalException, match=r'Exchange .* does not support.*'):
api_mock.fetch_ohlcv = MagicMock(side_effect=ccxt.NotSupported)
exchange = get_patched_exchange(mocker, default_conf, api_mock)
exchange.get_ticker_history(pair='ABCD/BTC', tick_interval=default_conf['ticker_interval'])
def test_get_ticker_history_sort(default_conf, mocker):
@ -426,10 +465,11 @@ def test_get_ticker_history_sort(default_conf, mocker):
]
type(api_mock).has = PropertyMock(return_value={'fetchOHLCV': True})
api_mock.fetch_ohlcv = MagicMock(side_effect=make_fetch_ohlcv_mock(tick))
mocker.patch('freqtrade.exchange._API', api_mock)
exchange = get_patched_exchange(mocker, default_conf, api_mock)
# Test the ticker history sort
ticks = get_ticker_history('ETH/BTC', default_conf['ticker_interval'])
ticks = exchange.get_ticker_history('ETH/BTC', default_conf['ticker_interval'])
assert ticks[0][0] == 1527830400000
assert ticks[0][1] == 0.07649
assert ticks[0][2] == 0.07651
@ -460,10 +500,9 @@ def test_get_ticker_history_sort(default_conf, mocker):
]
type(api_mock).has = PropertyMock(return_value={'fetchOHLCV': True})
api_mock.fetch_ohlcv = MagicMock(side_effect=make_fetch_ohlcv_mock(tick))
mocker.patch('freqtrade.exchange._API', api_mock)
exchange = get_patched_exchange(mocker, default_conf, api_mock)
# Test the ticker history sort
ticks = get_ticker_history('ETH/BTC', default_conf['ticker_interval'])
ticks = exchange.get_ticker_history('ETH/BTC', default_conf['ticker_interval'])
assert ticks[0][0] == 1527827700000
assert ticks[0][1] == 0.07659999
assert ticks[0][2] == 0.0766
@ -481,117 +520,159 @@ def test_get_ticker_history_sort(default_conf, mocker):
def test_cancel_order_dry_run(default_conf, mocker):
default_conf['dry_run'] = True
mocker.patch.dict('freqtrade.exchange._CONF', default_conf)
assert cancel_order(order_id='123', pair='TKN/BTC') is None
exchange = get_patched_exchange(mocker, default_conf)
assert exchange.cancel_order(order_id='123', pair='TKN/BTC') is None
# Ensure that if not dry_run, we should call API
def test_cancel_order(default_conf, mocker):
default_conf['dry_run'] = False
mocker.patch.dict('freqtrade.exchange._CONF', default_conf)
api_mock = MagicMock()
api_mock.cancel_order = MagicMock(return_value=123)
mocker.patch('freqtrade.exchange._API', api_mock)
assert cancel_order(order_id='_', pair='TKN/BTC') == 123
with pytest.raises(TemporaryError):
api_mock.cancel_order = MagicMock(side_effect=ccxt.NetworkError)
mocker.patch('freqtrade.exchange._API', api_mock)
cancel_order(order_id='_', pair='TKN/BTC')
assert api_mock.cancel_order.call_count == exchange.API_RETRY_COUNT + 1
exchange = get_patched_exchange(mocker, default_conf, api_mock)
assert exchange.cancel_order(order_id='_', pair='TKN/BTC') == 123
with pytest.raises(DependencyException):
api_mock.cancel_order = MagicMock(side_effect=ccxt.InvalidOrder)
mocker.patch('freqtrade.exchange._API', api_mock)
cancel_order(order_id='_', pair='TKN/BTC')
assert api_mock.cancel_order.call_count == exchange.API_RETRY_COUNT + 1
exchange = get_patched_exchange(mocker, default_conf, api_mock)
exchange.cancel_order(order_id='_', pair='TKN/BTC')
assert api_mock.cancel_order.call_count == API_RETRY_COUNT + 1
with pytest.raises(OperationalException):
api_mock.cancel_order = MagicMock(side_effect=ccxt.BaseError)
mocker.patch('freqtrade.exchange._API', api_mock)
cancel_order(order_id='_', pair='TKN/BTC')
assert api_mock.cancel_order.call_count == 1
ccxt_exceptionhandlers(mocker, default_conf, api_mock,
"cancel_order", "cancel_order",
order_id='_', pair='TKN/BTC')
def test_get_order(default_conf, mocker):
default_conf['dry_run'] = True
mocker.patch.dict('freqtrade.exchange._CONF', default_conf)
order = MagicMock()
order.myid = 123
exchange._DRY_RUN_OPEN_ORDERS['X'] = order
exchange = get_patched_exchange(mocker, default_conf)
exchange._dry_run_open_orders['X'] = order
print(exchange.get_order('X', 'TKN/BTC'))
assert exchange.get_order('X', 'TKN/BTC').myid == 123
default_conf['dry_run'] = False
mocker.patch.dict('freqtrade.exchange._CONF', default_conf)
api_mock = MagicMock()
api_mock.fetch_order = MagicMock(return_value=456)
mocker.patch('freqtrade.exchange._API', api_mock)
exchange = get_patched_exchange(mocker, default_conf, api_mock)
assert exchange.get_order('X', 'TKN/BTC') == 456
with pytest.raises(TemporaryError):
api_mock.fetch_order = MagicMock(side_effect=ccxt.NetworkError)
mocker.patch('freqtrade.exchange._API', api_mock)
exchange.get_order(order_id='_', pair='TKN/BTC')
assert api_mock.fetch_order.call_count == exchange.API_RETRY_COUNT + 1
with pytest.raises(DependencyException):
api_mock.fetch_order = MagicMock(side_effect=ccxt.InvalidOrder)
mocker.patch('freqtrade.exchange._API', api_mock)
exchange = get_patched_exchange(mocker, default_conf, api_mock)
exchange.get_order(order_id='_', pair='TKN/BTC')
assert api_mock.fetch_order.call_count == exchange.API_RETRY_COUNT + 1
assert api_mock.fetch_order.call_count == API_RETRY_COUNT + 1
with pytest.raises(OperationalException):
api_mock.fetch_order = MagicMock(side_effect=ccxt.BaseError)
mocker.patch('freqtrade.exchange._API', api_mock)
exchange.get_order(order_id='_', pair='TKN/BTC')
assert api_mock.fetch_order.call_count == 1
ccxt_exceptionhandlers(mocker, default_conf, api_mock,
'get_order', 'fetch_order',
order_id='_', pair='TKN/BTC')
def test_get_name(default_conf, mocker):
mocker.patch('freqtrade.exchange.validate_pairs',
def test_name(default_conf, mocker):
mocker.patch('freqtrade.exchange.Exchange.validate_pairs',
side_effect=lambda s: True)
default_conf['exchange']['name'] = 'binance'
init(default_conf)
exchange = Exchange(default_conf)
assert get_name() == 'Binance'
assert exchange.name == 'Binance'
def test_get_id(default_conf, mocker):
mocker.patch('freqtrade.exchange.validate_pairs',
def test_id(default_conf, mocker):
mocker.patch('freqtrade.exchange.Exchange.validate_pairs',
side_effect=lambda s: True)
default_conf['exchange']['name'] = 'binance'
init(default_conf)
assert get_id() == 'binance'
exchange = Exchange(default_conf)
assert exchange.id == 'binance'
def test_get_pair_detail_url(default_conf, mocker):
mocker.patch('freqtrade.exchange.validate_pairs',
def test_get_pair_detail_url(default_conf, mocker, caplog):
mocker.patch('freqtrade.exchange.Exchange.validate_pairs',
side_effect=lambda s: True)
default_conf['exchange']['name'] = 'binance'
init(default_conf)
exchange = Exchange(default_conf)
url = get_pair_detail_url('TKN/ETH')
url = exchange.get_pair_detail_url('TKN/ETH')
assert 'TKN' in url
assert 'ETH' in url
url = get_pair_detail_url('LOOONG/BTC')
url = exchange.get_pair_detail_url('LOOONG/BTC')
assert 'LOOONG' in url
assert 'BTC' in url
default_conf['exchange']['name'] = 'bittrex'
init(default_conf)
exchange = Exchange(default_conf)
url = get_pair_detail_url('TKN/ETH')
url = exchange.get_pair_detail_url('TKN/ETH')
assert 'TKN' in url
assert 'ETH' in url
url = get_pair_detail_url('LOOONG/BTC')
url = exchange.get_pair_detail_url('LOOONG/BTC')
assert 'LOOONG' in url
assert 'BTC' in url
default_conf['exchange']['name'] = 'poloniex'
exchange = Exchange(default_conf)
url = exchange.get_pair_detail_url('LOOONG/BTC')
assert '' == url
assert log_has('Could not get exchange url for Poloniex', caplog.record_tuples)
def test_get_trades_for_order(default_conf, mocker):
order_id = 'ABCD-ABCD'
since = datetime(2018, 5, 5)
default_conf["dry_run"] = False
mocker.patch('freqtrade.exchange.Exchange.exchange_has', return_value=True)
api_mock = MagicMock()
api_mock.fetch_my_trades = MagicMock(return_value=[{'id': 'TTR67E-3PFBD-76IISV',
'order': 'ABCD-ABCD',
'info': {'pair': 'XLTCZBTC',
'time': 1519860024.4388,
'type': 'buy',
'ordertype': 'limit',
'price': '20.00000',
'cost': '38.62000',
'fee': '0.06179',
'vol': '5',
'id': 'ABCD-ABCD'},
'timestamp': 1519860024438,
'datetime': '2018-02-28T23:20:24.438Z',
'symbol': 'LTC/BTC',
'type': 'limit',
'side': 'buy',
'price': 165.0,
'amount': 0.2340606,
'fee': {'cost': 0.06179, 'currency': 'BTC'}
}])
exchange = get_patched_exchange(mocker, default_conf, api_mock)
orders = exchange.get_trades_for_order(order_id, 'LTC/BTC', since)
assert len(orders) == 1
assert orders[0]['price'] == 165
ccxt_exceptionhandlers(mocker, default_conf, api_mock,
'get_trades_for_order', 'fetch_my_trades',
order_id=order_id, pair='LTC/BTC', since=since)
mocker.patch('freqtrade.exchange.Exchange.exchange_has', MagicMock(return_value=False))
assert exchange.get_trades_for_order(order_id, 'LTC/BTC', since) == []
def test_get_markets(default_conf, mocker, markets):
api_mock = MagicMock()
api_mock.fetch_markets = markets
exchange = get_patched_exchange(mocker, default_conf, api_mock)
ret = exchange.get_markets()
assert isinstance(ret, list)
assert len(ret) == 6
assert ret[0]["id"] == "ethbtc"
assert ret[0]["symbol"] == "ETH/BTC"
ccxt_exceptionhandlers(mocker, default_conf, api_mock,
'get_markets', 'fetch_markets')
def test_get_fee(default_conf, mocker):
api_mock = MagicMock()
@ -601,12 +682,21 @@ def test_get_fee(default_conf, mocker):
'rate': 0.025,
'cost': 0.05
})
mocker.patch('freqtrade.exchange._API', api_mock)
assert get_fee() == 0.025
exchange = get_patched_exchange(mocker, default_conf, api_mock)
assert exchange.get_fee() == 0.025
ccxt_exceptionhandlers(mocker, default_conf, api_mock,
'get_fee', 'calculate_fee')
def test_get_amount_lots(default_conf, mocker):
api_mock = MagicMock()
api_mock.amount_to_lots = MagicMock(return_value=1.0)
mocker.patch('freqtrade.exchange._API', api_mock)
assert get_amount_lots('LTC/BTC', 1.54) == 1
api_mock.markets = None
marketmock = MagicMock()
api_mock.load_markets = marketmock
exchange = get_patched_exchange(mocker, default_conf, api_mock)
assert exchange.get_amount_lots('LTC/BTC', 1.54) == 1
assert marketmock.call_count == 1

152
freqtrade/tests/optimize/test_backtesting.py
View File

@ -9,13 +9,15 @@ from unittest.mock import MagicMock
import numpy as np
import pandas as pd
import pytest
from arrow import Arrow
from freqtrade import optimize
from freqtrade import DependencyException, constants, optimize
from freqtrade.analyze import Analyze
from freqtrade.arguments import Arguments, TimeRange
from freqtrade.optimize.backtesting import Backtesting, start, setup_configuration
from freqtrade.tests.conftest import log_has
from freqtrade.optimize.backtesting import (Backtesting, setup_configuration,
start)
from freqtrade.tests.conftest import log_has, patch_exchange
def get_args(args) -> List[str]:
@ -83,7 +85,7 @@ def load_data_test(what):
def simple_backtest(config, contour, num_results, mocker) -> None:
mocker.patch('freqtrade.exchange.validate_pairs', MagicMock(return_value=True))
patch_exchange(mocker)
backtesting = Backtesting(config)
data = load_data_test(contour)
@ -101,7 +103,8 @@ def simple_backtest(config, contour, num_results, mocker) -> None:
assert len(results) == num_results
def mocked_load_data(datadir, pairs=[], ticker_interval='0m', refresh_pairs=False, timerange=None):
def mocked_load_data(datadir, pairs=[], ticker_interval='0m', refresh_pairs=False,
timerange=None, exchange=None):
tickerdata = optimize.load_tickerdata_file(datadir, 'UNITTEST/BTC', '1m', timerange=timerange)
pairdata = {'UNITTEST/BTC': tickerdata}
return pairdata
@ -118,7 +121,7 @@ def _load_pair_as_ticks(pair, tickfreq):
def _make_backtest_conf(mocker, conf=None, pair='UNITTEST/BTC', record=None):
data = optimize.load_data(None, ticker_interval='8m', pairs=[pair])
data = trim_dictlist(data, -201)
mocker.patch('freqtrade.exchange.validate_pairs', MagicMock(return_value=True))
patch_exchange(mocker)
backtesting = Backtesting(conf)
return {
'stake_amount': conf['stake_amount'],
@ -267,13 +270,35 @@ def test_setup_configuration_with_arguments(mocker, default_conf, caplog) -> Non
)
def test_setup_configuration_unlimited_stake_amount(mocker, default_conf, caplog) -> None:
"""
Test setup_configuration() function
"""
conf = deepcopy(default_conf)
conf['stake_amount'] = constants.UNLIMITED_STAKE_AMOUNT
mocker.patch('freqtrade.configuration.open', mocker.mock_open(
read_data=json.dumps(conf)
))
args = [
'--config', 'config.json',
'--strategy', 'DefaultStrategy',
'backtesting'
]
with pytest.raises(DependencyException, match=r'.*stake amount.*'):
setup_configuration(get_args(args))
def test_start(mocker, fee, default_conf, caplog) -> None:
"""
Test start() function
"""
start_mock = MagicMock()
mocker.patch('freqtrade.exchange.get_fee', fee)
mocker.patch('freqtrade.exchange.validate_pairs', MagicMock(return_value=True))
mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
patch_exchange(mocker)
mocker.patch('freqtrade.optimize.backtesting.Backtesting.start', start_mock)
mocker.patch('freqtrade.configuration.open', mocker.mock_open(
read_data=json.dumps(default_conf)
@ -296,7 +321,8 @@ def test_backtesting_init(mocker, default_conf) -> None:
"""
Test Backtesting._init() method
"""
mocker.patch('freqtrade.exchange.validate_pairs', MagicMock(return_value=True))
patch_exchange(mocker)
get_fee = mocker.patch('freqtrade.exchange.Exchange.get_fee', MagicMock(return_value=0.5))
backtesting = Backtesting(default_conf)
assert backtesting.config == default_conf
assert isinstance(backtesting.analyze, Analyze)
@ -304,13 +330,15 @@ def test_backtesting_init(mocker, default_conf) -> None:
assert callable(backtesting.tickerdata_to_dataframe)
assert callable(backtesting.populate_buy_trend)
assert callable(backtesting.populate_sell_trend)
get_fee.assert_called()
assert backtesting.fee == 0.5
def test_tickerdata_to_dataframe(default_conf, mocker) -> None:
"""
Test Backtesting.tickerdata_to_dataframe() method
"""
mocker.patch('freqtrade.exchange.validate_pairs', MagicMock(return_value=True))
patch_exchange(mocker)
timerange = TimeRange(None, 'line', 0, -100)
tick = optimize.load_tickerdata_file(None, 'UNITTEST/BTC', '1m', timerange=timerange)
tickerlist = {'UNITTEST/BTC': tick}
@ -329,7 +357,7 @@ def test_get_timeframe(default_conf, mocker) -> None:
"""
Test Backtesting.get_timeframe() method
"""
mocker.patch('freqtrade.exchange.validate_pairs', MagicMock(return_value=True))
patch_exchange(mocker)
backtesting = Backtesting(default_conf)
data = backtesting.tickerdata_to_dataframe(
@ -348,15 +376,15 @@ def test_generate_text_table(default_conf, mocker):
"""
Test Backtesting.generate_text_table() method
"""
mocker.patch('freqtrade.exchange.validate_pairs', MagicMock(return_value=True))
patch_exchange(mocker)
backtesting = Backtesting(default_conf)
results = pd.DataFrame(
{
'currency': ['ETH/BTC', 'ETH/BTC'],
'pair': ['ETH/BTC', 'ETH/BTC'],
'profit_percent': [0.1, 0.2],
'profit_BTC': [0.2, 0.4],
'duration': [10, 30],
'profit_abs': [0.2, 0.4],
'trade_duration': [10, 30],
'profit': [2, 0],
'loss': [0, 0]
}
@ -385,8 +413,8 @@ def test_backtesting_start(default_conf, mocker, caplog) -> None:
mocker.patch('freqtrade.freqtradebot.Analyze', MagicMock())
mocker.patch('freqtrade.optimize.load_data', mocked_load_data)
mocker.patch('freqtrade.exchange.get_ticker_history')
mocker.patch('freqtrade.exchange.validate_pairs', MagicMock(return_value=True))
mocker.patch('freqtrade.exchange.Exchange.get_ticker_history')
patch_exchange(mocker)
mocker.patch.multiple(
'freqtrade.optimize.backtesting.Backtesting',
backtest=MagicMock(),
@ -426,8 +454,8 @@ def test_backtesting_start_no_data(default_conf, mocker, caplog) -> None:
mocker.patch('freqtrade.freqtradebot.Analyze', MagicMock())
mocker.patch('freqtrade.optimize.load_data', MagicMock(return_value={}))
mocker.patch('freqtrade.exchange.get_ticker_history')
mocker.patch('freqtrade.exchange.validate_pairs', MagicMock(return_value=True))
mocker.patch('freqtrade.exchange.Exchange.get_ticker_history')
patch_exchange(mocker)
mocker.patch.multiple(
'freqtrade.optimize.backtesting.Backtesting',
backtest=MagicMock(),
@ -454,8 +482,8 @@ def test_backtest(default_conf, fee, mocker) -> None:
"""
Test Backtesting.backtest() method
"""
mocker.patch('freqtrade.exchange.get_fee', fee)
mocker.patch('freqtrade.exchange.validate_pairs', MagicMock(return_value=True))
mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
patch_exchange(mocker)
backtesting = Backtesting(default_conf)
data = optimize.load_data(None, ticker_interval='5m', pairs=['UNITTEST/BTC'])
@ -469,14 +497,15 @@ def test_backtest(default_conf, fee, mocker) -> None:
}
)
assert not results.empty
assert len(results) == 2
def test_backtest_1min_ticker_interval(default_conf, fee, mocker) -> None:
"""
Test Backtesting.backtest() method with 1 min ticker
"""
mocker.patch('freqtrade.exchange.get_fee', fee)
mocker.patch('freqtrade.exchange.validate_pairs', MagicMock(return_value=True))
mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
patch_exchange(mocker)
backtesting = Backtesting(default_conf)
# Run a backtesting for an exiting 5min ticker_interval
@ -491,13 +520,14 @@ def test_backtest_1min_ticker_interval(default_conf, fee, mocker) -> None:
}
)
assert not results.empty
assert len(results) == 1
def test_processed(default_conf, mocker) -> None:
"""
Test Backtesting.backtest() method with offline data
"""
mocker.patch('freqtrade.exchange.validate_pairs', MagicMock(return_value=True))
patch_exchange(mocker)
backtesting = Backtesting(default_conf)
dict_of_tickerrows = load_data_test('raise')
@ -511,16 +541,16 @@ def test_processed(default_conf, mocker) -> None:
def test_backtest_pricecontours(default_conf, fee, mocker) -> None:
mocker.patch('freqtrade.optimize.backtesting.exchange.get_fee', fee)
tests = [['raise', 17], ['lower', 0], ['sine', 16]]
mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
tests = [['raise', 18], ['lower', 0], ['sine', 16]]
for [contour, numres] in tests:
simple_backtest(default_conf, contour, numres, mocker)
# Test backtest using offline data (testdata directory)
def test_backtest_ticks(default_conf, fee, mocker):
mocker.patch('freqtrade.exchange.get_fee', fee)
mocker.patch('freqtrade.exchange.validate_pairs', MagicMock(return_value=True))
mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
patch_exchange(mocker)
ticks = [1, 5]
fun = Backtesting(default_conf).populate_buy_trend
for _ in ticks:
@ -539,7 +569,6 @@ def test_backtest_clash_buy_sell(mocker, default_conf):
sell_value = 1
return _trend(dataframe, buy_value, sell_value)
mocker.patch('freqtrade.exchange.validate_pairs', MagicMock(return_value=True))
backtest_conf = _make_backtest_conf(mocker, conf=default_conf)
backtesting = Backtesting(default_conf)
backtesting.populate_buy_trend = fun # Override
@ -555,7 +584,6 @@ def test_backtest_only_sell(mocker, default_conf):
sell_value = 1
return _trend(dataframe, buy_value, sell_value)
mocker.patch('freqtrade.exchange.validate_pairs', MagicMock(return_value=True))
backtest_conf = _make_backtest_conf(mocker, conf=default_conf)
backtesting = Backtesting(default_conf)
backtesting.populate_buy_trend = fun # Override
@ -565,50 +593,68 @@ def test_backtest_only_sell(mocker, default_conf):
def test_backtest_alternate_buy_sell(default_conf, fee, mocker):
mocker.patch('freqtrade.optimize.backtesting.exchange.get_fee', fee)
mocker.patch('freqtrade.exchange.validate_pairs', MagicMock(return_value=True))
mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
backtest_conf = _make_backtest_conf(mocker, conf=default_conf, pair='UNITTEST/BTC')
backtesting = Backtesting(default_conf)
backtesting.populate_buy_trend = _trend_alternate # Override
backtesting.populate_sell_trend = _trend_alternate # Override
results = backtesting.backtest(backtest_conf)
assert len(results) == 3
backtesting._store_backtest_result("test_.json", results)
assert len(results) == 4
# One trade was force-closed at the end
assert len(results.loc[results.open_at_end]) == 1
def test_backtest_record(default_conf, fee, mocker):
names = []
records = []
mocker.patch('freqtrade.exchange.validate_pairs', MagicMock(return_value=True))
mocker.patch('freqtrade.optimize.backtesting.exchange.get_fee', fee)
patch_exchange(mocker)
mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
mocker.patch(
'freqtrade.optimize.backtesting.file_dump_json',
new=lambda n, r: (names.append(n), records.append(r))
)
backtest_conf = _make_backtest_conf(
mocker,
conf=default_conf,
pair='UNITTEST/BTC',
record="trades"
)
backtesting = Backtesting(default_conf)
backtesting.populate_buy_trend = _trend_alternate # Override
backtesting.populate_sell_trend = _trend_alternate # Override
results = backtesting.backtest(backtest_conf)
assert len(results) == 3
results = pd.DataFrame({"pair": ["UNITTEST/BTC", "UNITTEST/BTC",
"UNITTEST/BTC", "UNITTEST/BTC"],
"profit_percent": [0.003312, 0.010801, 0.013803, 0.002780],
"profit_abs": [0.000003, 0.000011, 0.000014, 0.000003],
"open_time": [Arrow(2017, 11, 14, 19, 32, 00).datetime,
Arrow(2017, 11, 14, 21, 36, 00).datetime,
Arrow(2017, 11, 14, 22, 12, 00).datetime,
Arrow(2017, 11, 14, 22, 44, 00).datetime],
"close_time": [Arrow(2017, 11, 14, 21, 35, 00).datetime,
Arrow(2017, 11, 14, 22, 10, 00).datetime,
Arrow(2017, 11, 14, 22, 43, 00).datetime,
Arrow(2017, 11, 14, 22, 58, 00).datetime],
"open_rate": [0.002543, 0.003003, 0.003089, 0.003214],
"close_rate": [0.002546, 0.003014, 0.003103, 0.003217],
"open_index": [1, 119, 153, 185],
"close_index": [118, 151, 184, 199],
"trade_duration": [123, 34, 31, 14],
"open_at_end": [False, False, False, True]
})
backtesting._store_backtest_result("backtest-result.json", results)
assert len(results) == 4
# Assert file_dump_json was only called once
assert names == ['backtest-result.json']
records = records[0]
# Ensure records are of correct type
assert len(records) == 3
assert len(records) == 4
# ('UNITTEST/BTC', 0.00331158, '1510684320', '1510691700', 0, 117)
# Below follows just a typecheck of the schema/type of trade-records
oix = None
for (pair, profit, date_buy, date_sell, buy_index, dur) in records:
for (pair, profit, date_buy, date_sell, buy_index, dur,
openr, closer, open_at_end) in records:
assert pair == 'UNITTEST/BTC'
isinstance(profit, float)
assert isinstance(profit, float)
# FIX: buy/sell should be converted to ints
isinstance(date_buy, str)
isinstance(date_sell, str)
assert isinstance(date_buy, float)
assert isinstance(date_sell, float)
assert isinstance(openr, float)
assert isinstance(closer, float)
assert isinstance(open_at_end, bool)
isinstance(buy_index, pd._libs.tslib.Timestamp)
if oix:
assert buy_index > oix
@ -619,9 +665,9 @@ def test_backtest_record(default_conf, fee, mocker):
def test_backtest_start_live(default_conf, mocker, caplog):
conf = deepcopy(default_conf)
conf['exchange']['pair_whitelist'] = ['UNITTEST/BTC']
mocker.patch('freqtrade.exchange.get_ticker_history',
new=lambda n, i: _load_pair_as_ticks(n, i))
mocker.patch('freqtrade.exchange.validate_pairs', MagicMock())
mocker.patch('freqtrade.exchange.Exchange.get_ticker_history',
new=lambda s, n, i: _load_pair_as_ticks(n, i))
patch_exchange(mocker)
mocker.patch('freqtrade.optimize.backtesting.Backtesting.backtest', MagicMock())
mocker.patch('freqtrade.optimize.backtesting.Backtesting._generate_text_table', MagicMock())
mocker.patch('freqtrade.configuration.open', mocker.mock_open(

330
freqtrade/tests/optimize/test_hyperopt.py
View File

@ -1,6 +1,5 @@
# pragma pylint: disable=missing-docstring,W0212,C0103
import os
import signal
from copy import deepcopy
from unittest.mock import MagicMock
@ -10,7 +9,7 @@ import pytest
from freqtrade.optimize.__init__ import load_tickerdata_file
from freqtrade.optimize.hyperopt import Hyperopt, start
from freqtrade.strategy.resolver import StrategyResolver
from freqtrade.tests.conftest import log_has
from freqtrade.tests.conftest import log_has, patch_exchange
from freqtrade.tests.optimize.test_backtesting import get_args
# Avoid to reinit the same object again and again
@ -22,10 +21,7 @@ _HYPEROPT = None
def init_hyperopt(default_conf, mocker):
global _HYPEROPT_INITIALIZED, _HYPEROPT
if not _HYPEROPT_INITIALIZED:
mocker.patch('freqtrade.exchange.validate_pairs', MagicMock(return_value=True))
mocker.patch('freqtrade.optimize.hyperopt.hyperopt_optimize_conf',
MagicMock(return_value=default_conf))
mocker.patch('freqtrade.exchange.validate_pairs', MagicMock())
patch_exchange(mocker)
_HYPEROPT = Hyperopt(default_conf)
_HYPEROPT_INITIALIZED = True
@ -43,30 +39,22 @@ def create_trials(mocker) -> None:
mocker.patch('freqtrade.optimize.hyperopt.os.path.exists', return_value=False)
mocker.patch('freqtrade.optimize.hyperopt.os.path.getsize', return_value=1)
mocker.patch('freqtrade.optimize.hyperopt.os.remove', return_value=True)
mocker.patch('freqtrade.optimize.hyperopt.pickle.dump', return_value=None)
mocker.patch('freqtrade.optimize.hyperopt.dump', return_value=None)
return mocker.Mock(
results=[
{
'loss': 1,
'result': 'foo',
'status': 'ok'
}
],
best_trial={'misc': {'vals': {'adx': 999}}}
)
return [{'loss': 1, 'result': 'foo', 'params': {}}]
# Unit tests
def test_start(mocker, default_conf, caplog) -> None:
"""
Test start() function
"""
start_mock = MagicMock()
mocker.patch(
'freqtrade.configuration.Configuration._load_config_file',
lambda *args, **kwargs: default_conf
)
mocker.patch('freqtrade.optimize.hyperopt.Hyperopt.start', start_mock)
mocker.patch('freqtrade.optimize.hyperopt.hyperopt_optimize_conf',
MagicMock(return_value=default_conf))
mocker.patch('freqtrade.freqtradebot.exchange.validate_pairs', MagicMock())
patch_exchange(mocker)
args = [
'--config', 'config.json',
@ -149,159 +137,18 @@ def test_no_log_if_loss_does_not_improve(init_hyperopt, caplog) -> None:
assert caplog.record_tuples == []
def test_fmin_best_results(mocker, init_hyperopt, default_conf, caplog) -> None:
fmin_result = {
"macd_below_zero": 0,
"adx": 1,
"adx-value": 15.0,
"fastd": 1,
"fastd-value": 40.0,
"green_candle": 1,
"mfi": 0,
"over_sar": 0,
"rsi": 1,
"rsi-value": 37.0,
"trigger": 2,
"uptrend_long_ema": 1,
"uptrend_short_ema": 0,
"uptrend_sma": 0,
"stoploss": -0.1,
"roi_t1": 1,
"roi_t2": 2,
"roi_t3": 3,
"roi_p1": 1,
"roi_p2": 2,
"roi_p3": 3,
}
conf = deepcopy(default_conf)
conf.update({'config': 'config.json.example'})
conf.update({'epochs': 1})
conf.update({'timerange': None})
conf.update({'spaces': 'all'})
mocker.patch('freqtrade.optimize.hyperopt.load_data', MagicMock())
mocker.patch('freqtrade.optimize.hyperopt.fmin', return_value=fmin_result)
mocker.patch('freqtrade.optimize.hyperopt.hyperopt_optimize_conf', return_value=conf)
mocker.patch('freqtrade.freqtradebot.exchange.validate_pairs', MagicMock())
StrategyResolver({'strategy': 'DefaultStrategy'})
hyperopt = Hyperopt(conf)
hyperopt.trials = create_trials(mocker)
hyperopt.tickerdata_to_dataframe = MagicMock()
hyperopt.start()
exists = [
'Best parameters:',
'"adx": {\n "enabled": true,\n "value": 15.0\n },',
'"fastd": {\n "enabled": true,\n "value": 40.0\n },',
'"green_candle": {\n "enabled": true\n },',
'"macd_below_zero": {\n "enabled": false\n },',
'"mfi": {\n "enabled": false\n },',
'"over_sar": {\n "enabled": false\n },',
'"roi_p1": 1.0,',
'"roi_p2": 2.0,',
'"roi_p3": 3.0,',
'"roi_t1": 1.0,',
'"roi_t2": 2.0,',
'"roi_t3": 3.0,',
'"rsi": {\n "enabled": true,\n "value": 37.0\n },',
'"stoploss": -0.1,',
'"trigger": {\n "type": "faststoch10"\n },',
'"uptrend_long_ema": {\n "enabled": true\n },',
'"uptrend_short_ema": {\n "enabled": false\n },',
'"uptrend_sma": {\n "enabled": false\n }',
'ROI table:\n{0: 6.0, 3.0: 3.0, 5.0: 1.0, 6.0: 0}',
'Best Result:\nfoo'
]
for line in exists:
assert line in caplog.text
def test_fmin_throw_value_error(mocker, init_hyperopt, default_conf, caplog) -> None:
mocker.patch('freqtrade.optimize.hyperopt.load_data', MagicMock())
mocker.patch('freqtrade.optimize.hyperopt.fmin', side_effect=ValueError())
conf = deepcopy(default_conf)
conf.update({'config': 'config.json.example'})
conf.update({'epochs': 1})
conf.update({'timerange': None})
conf.update({'spaces': 'all'})
mocker.patch('freqtrade.optimize.hyperopt.hyperopt_optimize_conf', return_value=conf)
mocker.patch('freqtrade.freqtradebot.exchange.validate_pairs', MagicMock())
StrategyResolver({'strategy': 'DefaultStrategy'})
hyperopt = Hyperopt(conf)
hyperopt.trials = create_trials(mocker)
hyperopt.tickerdata_to_dataframe = MagicMock()
hyperopt.start()
exists = [
'Best Result:',
'Sorry, Hyperopt was not able to find good parameters. Please try with more epochs '
'(param: -e).',
]
for line in exists:
assert line in caplog.text
def test_resuming_previous_hyperopt_results_succeeds(mocker, init_hyperopt, default_conf) -> None:
trials = create_trials(mocker)
conf = deepcopy(default_conf)
conf.update({'config': 'config.json.example'})
conf.update({'epochs': 1})
conf.update({'mongodb': False})
conf.update({'timerange': None})
conf.update({'spaces': 'all'})
mocker.patch('freqtrade.optimize.hyperopt.os.path.exists', return_value=True)
mocker.patch('freqtrade.optimize.hyperopt.len', return_value=len(trials.results))
mock_read = mocker.patch(
'freqtrade.optimize.hyperopt.Hyperopt.read_trials',
return_value=trials
)
mock_save = mocker.patch(
'freqtrade.optimize.hyperopt.Hyperopt.save_trials',
return_value=None
)
mocker.patch('freqtrade.optimize.hyperopt.sorted', return_value=trials.results)
mocker.patch('freqtrade.optimize.hyperopt.load_data', MagicMock())
mocker.patch('freqtrade.optimize.hyperopt.fmin', return_value={})
mocker.patch('freqtrade.optimize.hyperopt.hyperopt_optimize_conf', return_value=conf)
mocker.patch('freqtrade.exchange.validate_pairs', MagicMock())
StrategyResolver({'strategy': 'DefaultStrategy'})
hyperopt = Hyperopt(conf)
hyperopt.trials = trials
hyperopt.tickerdata_to_dataframe = MagicMock()
hyperopt.start()
mock_read.assert_called_once()
mock_save.assert_called_once()
current_tries = hyperopt.current_tries
total_tries = hyperopt.total_tries
assert current_tries == len(trials.results)
assert total_tries == (current_tries + len(trials.results))
def test_save_trials_saves_trials(mocker, init_hyperopt, caplog) -> None:
create_trials(mocker)
mock_dump = mocker.patch('freqtrade.optimize.hyperopt.pickle.dump', return_value=None)
trials = create_trials(mocker)
mock_dump = mocker.patch('freqtrade.optimize.hyperopt.dump', return_value=None)
hyperopt = _HYPEROPT
mocker.patch('freqtrade.optimize.hyperopt.open', return_value=hyperopt.trials_file)
_HYPEROPT.trials = trials
hyperopt.save_trials()
trials_file = os.path.join('freqtrade', 'tests', 'optimize', 'ut_trials.pickle')
assert log_has(
'Saving Trials to \'{}\''.format(trials_file),
'Saving 1 evaluations to \'{}\''.format(trials_file),
caplog.record_tuples
)
mock_dump.assert_called_once()
@ -309,8 +156,7 @@ def test_save_trials_saves_trials(mocker, init_hyperopt, caplog) -> None:
def test_read_trials_returns_trials_file(mocker, init_hyperopt, caplog) -> None:
trials = create_trials(mocker)
mock_load = mocker.patch('freqtrade.optimize.hyperopt.pickle.load', return_value=trials)
mock_open = mocker.patch('freqtrade.optimize.hyperopt.open', return_value=mock_load)
mock_load = mocker.patch('freqtrade.optimize.hyperopt.load', return_value=trials)
hyperopt = _HYPEROPT
hyperopt_trial = hyperopt.read_trials()
@ -320,7 +166,6 @@ def test_read_trials_returns_trials_file(mocker, init_hyperopt, caplog) -> None:
caplog.record_tuples
)
assert hyperopt_trial == trials
mock_open.assert_called_once()
mock_load.assert_called_once()
@ -338,56 +183,31 @@ def test_roi_table_generation(init_hyperopt) -> None:
assert hyperopt.generate_roi_table(params) == {0: 6, 15: 3, 25: 1, 30: 0}
def test_start_calls_fmin(mocker, init_hyperopt, default_conf) -> None:
trials = create_trials(mocker)
mocker.patch('freqtrade.optimize.hyperopt.sorted', return_value=trials.results)
def test_start_calls_optimizer(mocker, init_hyperopt, default_conf, caplog) -> None:
dumper = mocker.patch('freqtrade.optimize.hyperopt.dump', MagicMock())
mocker.patch('freqtrade.optimize.hyperopt.load_data', MagicMock())
mocker.patch('freqtrade.exchange.validate_pairs', MagicMock())
mock_fmin = mocker.patch('freqtrade.optimize.hyperopt.fmin', return_value={})
conf = deepcopy(default_conf)
conf.update({'config': 'config.json.example'})
conf.update({'epochs': 1})
conf.update({'mongodb': False})
conf.update({'timerange': None})
conf.update({'spaces': 'all'})
hyperopt = Hyperopt(conf)
hyperopt.trials = trials
hyperopt.tickerdata_to_dataframe = MagicMock()
hyperopt.start()
mock_fmin.assert_called_once()
def test_start_uses_mongotrials(mocker, init_hyperopt, default_conf) -> None:
mocker.patch('freqtrade.optimize.hyperopt.load_data', MagicMock())
mock_fmin = mocker.patch('freqtrade.optimize.hyperopt.fmin', return_value={})
mock_mongotrials = mocker.patch(
'freqtrade.optimize.hyperopt.MongoTrials',
return_value=create_trials(mocker)
mocker.patch('freqtrade.optimize.hyperopt.multiprocessing.cpu_count', MagicMock(return_value=1))
parallel = mocker.patch(
'freqtrade.optimize.hyperopt.Hyperopt.run_optimizer_parallel',
MagicMock(return_value=[{'loss': 1, 'result': 'foo result', 'params': {}}])
)
patch_exchange(mocker)
conf = deepcopy(default_conf)
conf.update({'config': 'config.json.example'})
conf.update({'epochs': 1})
conf.update({'mongodb': True})
conf.update({'timerange': None})
conf.update({'spaces': 'all'})
mocker.patch('freqtrade.optimize.hyperopt.hyperopt_optimize_conf', return_value=conf)
mocker.patch('freqtrade.freqtradebot.exchange.validate_pairs', MagicMock())
hyperopt = Hyperopt(conf)
hyperopt.tickerdata_to_dataframe = MagicMock()
hyperopt.start()
mock_mongotrials.assert_called_once()
mock_fmin.assert_called_once()
parallel.assert_called_once()
assert 'Best result:\nfoo result\nwith values:\n{}' in caplog.text
assert dumper.called
# test log_trials_result
# test buy_strategy_generator def populate_buy_trend
# test optimizer if 'ro_t1' in params
def test_format_results(init_hyperopt):
"""
@ -400,7 +220,7 @@ def test_format_results(init_hyperopt):
('LTC/BTC', 1, 1, 123),
('XPR/BTC', -1, -2, -246)
]
labels = ['currency', 'profit_percent', 'profit_BTC', 'duration']
labels = ['currency', 'profit_percent', 'profit_abs', 'trade_duration']
df = pd.DataFrame.from_records(trades, columns=labels)
result = _HYPEROPT.format_results(df)
@ -419,20 +239,6 @@ def test_format_results(init_hyperopt):
assert result.find('Total profit 1.00000000 EUR')
def test_signal_handler(mocker, init_hyperopt):
"""
Test Hyperopt.signal_handler()
"""
m = MagicMock()
mocker.patch('sys.exit', m)
mocker.patch('freqtrade.optimize.hyperopt.Hyperopt.save_trials', m)
mocker.patch('freqtrade.optimize.hyperopt.Hyperopt.log_trials_result', m)
hyperopt = _HYPEROPT
hyperopt.signal_handler(signal.SIGTERM, None)
assert m.call_count == 3
def test_has_space(init_hyperopt):
"""
Test Hyperopt.has_space() method
@ -457,8 +263,8 @@ def test_populate_indicators(init_hyperopt) -> None:
# Check if some indicators are generated. We will not test all of them
assert 'adx' in dataframe
assert 'ao' in dataframe
assert 'cci' in dataframe
assert 'mfi' in dataframe
assert 'rsi' in dataframe
def test_buy_strategy_generator(init_hyperopt) -> None:
@ -472,44 +278,15 @@ def test_buy_strategy_generator(init_hyperopt) -> None:
populate_buy_trend = _HYPEROPT.buy_strategy_generator(
{
'uptrend_long_ema': {
'enabled': True
},
'macd_below_zero': {
'enabled': True
},
'uptrend_short_ema': {
'enabled': True
},
'mfi': {
'enabled': True,
'value': 20
},
'fastd': {
'enabled': True,
'value': 20
},
'adx': {
'enabled': True,
'value': 20
},
'rsi': {
'enabled': True,
'value': 20
},
'over_sar': {
'enabled': True,
},
'green_candle': {
'enabled': True,
},
'uptrend_sma': {
'enabled': True,
},
'trigger': {
'type': 'lower_bb'
}
'adx-value': 20,
'fastd-value': 20,
'mfi-value': 20,
'rsi-value': 20,
'adx-enabled': True,
'fastd-enabled': True,
'mfi-enabled': True,
'rsi-enabled': True,
'trigger': 'bb_lower'
}
)
result = populate_buy_trend(dataframe)
@ -530,43 +307,42 @@ def test_generate_optimizer(mocker, init_hyperopt, default_conf) -> None:
trades = [
('POWR/BTC', 0.023117, 0.000233, 100)
]
labels = ['currency', 'profit_percent', 'profit_BTC', 'duration']
labels = ['currency', 'profit_percent', 'profit_abs', 'trade_duration']
backtest_result = pd.DataFrame.from_records(trades, columns=labels)
mocker.patch(
'freqtrade.optimize.hyperopt.Hyperopt.backtest',
MagicMock(return_value=backtest_result)
)
mocker.patch('freqtrade.exchange.validate_pairs', MagicMock())
patch_exchange(mocker)
mocker.patch('freqtrade.optimize.hyperopt.load', MagicMock())
optimizer_param = {
'adx': {'enabled': False},
'fastd': {'enabled': True, 'value': 35.0},
'green_candle': {'enabled': True},
'macd_below_zero': {'enabled': True},
'mfi': {'enabled': False},
'over_sar': {'enabled': False},
'roi_p1': 0.01,
'roi_p2': 0.01,
'roi_p3': 0.1,
'adx-value': 0,
'fastd-value': 35,
'mfi-value': 0,
'rsi-value': 0,
'adx-enabled': False,
'fastd-enabled': True,
'mfi-enabled': False,
'rsi-enabled': False,
'trigger': 'macd_cross_signal',
'roi_t1': 60.0,
'roi_t2': 30.0,
'roi_t3': 20.0,
'rsi': {'enabled': False},
'roi_p1': 0.01,
'roi_p2': 0.01,
'roi_p3': 0.1,
'stoploss': -0.4,
'trigger': {'type': 'macd_cross_signal'},
'uptrend_long_ema': {'enabled': False},
'uptrend_short_ema': {'enabled': True},
'uptrend_sma': {'enabled': True}
}
response_expected = {
'loss': 1.9840569076926293,
'result': ' 1 trades. Avg profit 2.31%. Total profit 0.00023300 BTC '
'(0.0231Σ%). Avg duration 100.0 mins.',
'status': 'ok'
'params': optimizer_param
}
hyperopt = Hyperopt(conf)
generate_optimizer_value = hyperopt.generate_optimizer(optimizer_param)
generate_optimizer_value = hyperopt.generate_optimizer(list(optimizer_param.values()))
assert generate_optimizer_value == response_expected

16
freqtrade/tests/optimize/test_hyperopt_config.py
View File

@ -1,16 +0,0 @@
# pragma pylint: disable=missing-docstring,W0212
from user_data.hyperopt_conf import hyperopt_optimize_conf
def test_hyperopt_optimize_conf():
hyperopt_conf = hyperopt_optimize_conf()
assert "max_open_trades" in hyperopt_conf
assert "stake_currency" in hyperopt_conf
assert "stake_amount" in hyperopt_conf
assert "minimal_roi" in hyperopt_conf
assert "stoploss" in hyperopt_conf
assert "bid_strategy" in hyperopt_conf
assert "exchange" in hyperopt_conf
assert "pair_whitelist" in hyperopt_conf['exchange']

75
freqtrade/tests/optimize/test_optimize.py
View File

@ -3,16 +3,19 @@
import json
import os
import uuid
import arrow
from shutil import copyfile
import arrow
from freqtrade import optimize
from freqtrade.misc import file_dump_json
from freqtrade.optimize.__init__ import make_testdata_path, download_pairs, \
download_backtesting_testdata, load_tickerdata_file, trim_tickerlist, \
load_cached_data_for_updating
from freqtrade.arguments import TimeRange
from freqtrade.tests.conftest import log_has
from freqtrade.misc import file_dump_json
from freqtrade.optimize.__init__ import (download_backtesting_testdata,
download_pairs,
load_cached_data_for_updating,
load_tickerdata_file,
make_testdata_path, trim_tickerlist)
from freqtrade.tests.conftest import get_patched_exchange, log_has
# Change this if modifying UNITTEST/BTC testdatafile
_BTC_UNITTEST_LENGTH = 13681
@ -49,12 +52,11 @@ def _clean_test_file(file: str) -> None:
os.rename(file_swp, file)
def test_load_data_30min_ticker(ticker_history, mocker, caplog) -> None:
def test_load_data_30min_ticker(ticker_history, mocker, caplog, default_conf) -> None:
"""
Test load_data() with 30 min ticker
"""
mocker.patch('freqtrade.optimize.get_ticker_history', return_value=ticker_history)
mocker.patch('freqtrade.exchange.Exchange.get_ticker_history', return_value=ticker_history)
file = os.path.join(os.path.dirname(__file__), '..', 'testdata', 'UNITTEST_BTC-30m.json')
_backup_file(file, copy_file=True)
optimize.load_data(None, pairs=['UNITTEST/BTC'], ticker_interval='30m')
@ -63,11 +65,11 @@ def test_load_data_30min_ticker(ticker_history, mocker, caplog) -> None:
_clean_test_file(file)
def test_load_data_5min_ticker(ticker_history, mocker, caplog) -> None:
def test_load_data_5min_ticker(ticker_history, mocker, caplog, default_conf) -> None:
"""
Test load_data() with 5 min ticker
"""
mocker.patch('freqtrade.optimize.get_ticker_history', return_value=ticker_history)
mocker.patch('freqtrade.exchange.Exchange.get_ticker_history', return_value=ticker_history)
file = os.path.join(os.path.dirname(__file__), '..', 'testdata', 'UNITTEST_BTC-5m.json')
_backup_file(file, copy_file=True)
@ -81,7 +83,7 @@ def test_load_data_1min_ticker(ticker_history, mocker, caplog) -> None:
"""
Test load_data() with 1 min ticker
"""
mocker.patch('freqtrade.optimize.get_ticker_history', return_value=ticker_history)
mocker.patch('freqtrade.exchange.Exchange.get_ticker_history', return_value=ticker_history)
file = os.path.join(os.path.dirname(__file__), '..', 'testdata', 'UNITTEST_BTC-1m.json')
_backup_file(file, copy_file=True)
@ -91,12 +93,12 @@ def test_load_data_1min_ticker(ticker_history, mocker, caplog) -> None:
_clean_test_file(file)
def test_load_data_with_new_pair_1min(ticker_history, mocker, caplog) -> None:
def test_load_data_with_new_pair_1min(ticker_history, mocker, caplog, default_conf) -> None:
"""
Test load_data() with 1 min ticker
"""
mocker.patch('freqtrade.optimize.get_ticker_history', return_value=ticker_history)
mocker.patch('freqtrade.exchange.Exchange.get_ticker_history', return_value=ticker_history)
exchange = get_patched_exchange(mocker, default_conf)
file = os.path.join(os.path.dirname(__file__), '..', 'testdata', 'MEME_BTC-1m.json')
_backup_file(file)
@ -114,6 +116,7 @@ def test_load_data_with_new_pair_1min(ticker_history, mocker, caplog) -> None:
optimize.load_data(None,
ticker_interval='1m',
refresh_pairs=True,
exchange=exchange,
pairs=['MEME/BTC'])
assert os.path.isfile(file) is True
assert log_has('Download the pair: "MEME/BTC", Interval: 1m', caplog.record_tuples)
@ -124,9 +127,9 @@ def test_testdata_path() -> None:
assert os.path.join('freqtrade', 'tests', 'testdata') in make_testdata_path(None)
def test_download_pairs(ticker_history, mocker) -> None:
mocker.patch('freqtrade.optimize.__init__.get_ticker_history', return_value=ticker_history)
def test_download_pairs(ticker_history, mocker, default_conf) -> None:
mocker.patch('freqtrade.exchange.Exchange.get_ticker_history', return_value=ticker_history)
exchange = get_patched_exchange(mocker, default_conf)
file1_1 = os.path.join(os.path.dirname(__file__), '..', 'testdata', 'MEME_BTC-1m.json')
file1_5 = os.path.join(os.path.dirname(__file__), '..', 'testdata', 'MEME_BTC-5m.json')
file2_1 = os.path.join(os.path.dirname(__file__), '..', 'testdata', 'CFI_BTC-1m.json')
@ -140,7 +143,8 @@ def test_download_pairs(ticker_history, mocker) -> None:
assert os.path.isfile(file1_1) is False
assert os.path.isfile(file2_1) is False
assert download_pairs(None, pairs=['MEME/BTC', 'CFI/BTC'], ticker_interval='1m') is True
assert download_pairs(None, exchange,
pairs=['MEME/BTC', 'CFI/BTC'], ticker_interval='1m') is True
assert os.path.isfile(file1_1) is True
assert os.path.isfile(file2_1) is True
@ -152,7 +156,8 @@ def test_download_pairs(ticker_history, mocker) -> None:
assert os.path.isfile(file1_5) is False
assert os.path.isfile(file2_5) is False
assert download_pairs(None, pairs=['MEME/BTC', 'CFI/BTC'], ticker_interval='5m') is True
assert download_pairs(None, exchange,
pairs=['MEME/BTC', 'CFI/BTC'], ticker_interval='5m') is True
assert os.path.isfile(file1_5) is True
assert os.path.isfile(file2_5) is True
@ -265,30 +270,32 @@ def test_load_cached_data_for_updating(mocker) -> None:
assert start_ts is None
def test_download_pairs_exception(ticker_history, mocker, caplog) -> None:
mocker.patch('freqtrade.optimize.__init__.get_ticker_history', return_value=ticker_history)
def test_download_pairs_exception(ticker_history, mocker, caplog, default_conf) -> None:
mocker.patch('freqtrade.exchange.Exchange.get_ticker_history', return_value=ticker_history)
mocker.patch('freqtrade.optimize.__init__.download_backtesting_testdata',
side_effect=BaseException('File Error'))
exchange = get_patched_exchange(mocker, default_conf)
file1_1 = os.path.join(os.path.dirname(__file__), '..', 'testdata', 'MEME_BTC-1m.json')
file1_5 = os.path.join(os.path.dirname(__file__), '..', 'testdata', 'MEME_BTC-5m.json')
_backup_file(file1_1)
_backup_file(file1_5)
download_pairs(None, pairs=['MEME/BTC'], ticker_interval='1m')
download_pairs(None, exchange, pairs=['MEME/BTC'], ticker_interval='1m')
# clean files freshly downloaded
_clean_test_file(file1_1)
_clean_test_file(file1_5)
assert log_has('Failed to download the pair: "MEME/BTC", Interval: 1m', caplog.record_tuples)
def test_download_backtesting_testdata(ticker_history, mocker) -> None:
mocker.patch('freqtrade.optimize.__init__.get_ticker_history', return_value=ticker_history)
def test_download_backtesting_testdata(ticker_history, mocker, default_conf) -> None:
mocker.patch('freqtrade.exchange.Exchange.get_ticker_history', return_value=ticker_history)
exchange = get_patched_exchange(mocker, default_conf)
# Download a 1 min ticker file
file1 = os.path.join(os.path.dirname(__file__), '..', 'testdata', 'XEL_BTC-1m.json')
_backup_file(file1)
download_backtesting_testdata(None, pair="XEL/BTC", tick_interval='1m')
download_backtesting_testdata(None, exchange, pair="XEL/BTC", tick_interval='1m')
assert os.path.isfile(file1) is True
_clean_test_file(file1)
@ -296,21 +303,21 @@ def test_download_backtesting_testdata(ticker_history, mocker) -> None:
file2 = os.path.join(os.path.dirname(__file__), '..', 'testdata', 'STORJ_BTC-5m.json')
_backup_file(file2)
download_backtesting_testdata(None, pair="STORJ/BTC", tick_interval='5m')
download_backtesting_testdata(None, exchange, pair="STORJ/BTC", tick_interval='5m')
assert os.path.isfile(file2) is True
_clean_test_file(file2)
def test_download_backtesting_testdata2(mocker) -> None:
def test_download_backtesting_testdata2(mocker, default_conf) -> None:
tick = [
[1509836520000, 0.00162008, 0.00162008, 0.00162008, 0.00162008, 108.14853839],
[1509836580000, 0.00161, 0.00161, 0.00161, 0.00161, 82.390199]
]
json_dump_mock = mocker.patch('freqtrade.misc.file_dump_json', return_value=None)
mocker.patch('freqtrade.optimize.__init__.get_ticker_history', return_value=tick)
download_backtesting_testdata(None, pair="UNITTEST/BTC", tick_interval='1m')
download_backtesting_testdata(None, pair="UNITTEST/BTC", tick_interval='3m')
mocker.patch('freqtrade.exchange.Exchange.get_ticker_history', return_value=tick)
exchange = get_patched_exchange(mocker, default_conf)
download_backtesting_testdata(None, exchange, pair="UNITTEST/BTC", tick_interval='1m')
download_backtesting_testdata(None, exchange, pair="UNITTEST/BTC", tick_interval='3m')
assert json_dump_mock.call_count == 2
@ -326,10 +333,10 @@ def test_load_tickerdata_file() -> None:
def test_init(default_conf, mocker) -> None:
conf = {'exchange': {'pair_whitelist': []}}
mocker.patch('freqtrade.optimize.hyperopt_optimize_conf', return_value=conf)
exchange = get_patched_exchange(mocker, default_conf)
assert {} == optimize.load_data(
'',
exchange=exchange,
pairs=[],
refresh_pairs=True,
ticker_interval=default_conf['ticker_interval']

234
freqtrade/tests/rpc/test_rpc.py
View File

@ -7,11 +7,14 @@ Unit test file for rpc/rpc.py
from datetime import datetime
from unittest.mock import MagicMock
import pytest
from freqtrade.freqtradebot import FreqtradeBot
from freqtrade.persistence import Trade
from freqtrade.rpc.rpc import RPC
from freqtrade.rpc.rpc import RPC, RPCException
from freqtrade.state import State
from freqtrade.tests.test_freqtradebot import patch_get_signal, patch_coinmarketcap
from freqtrade.tests.test_freqtradebot import (patch_coinmarketcap,
patch_get_signal)
# Functions for recurrent object patching
@ -23,37 +26,35 @@ def prec_satoshi(a, b) -> float:
# Unit tests
def test_rpc_trade_status(default_conf, ticker, fee, mocker) -> None:
def test_rpc_trade_status(default_conf, ticker, fee, markets, mocker) -> None:
"""
Test rpc_trade_status() method
"""
patch_get_signal(mocker, (True, False))
patch_coinmarketcap(mocker)
mocker.patch('freqtrade.rpc.rpc_manager.Telegram', MagicMock())
mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
mocker.patch.multiple(
'freqtrade.freqtradebot.exchange',
'freqtrade.exchange.Exchange',
validate_pairs=MagicMock(),
get_ticker=ticker,
get_fee=fee
get_fee=fee,
get_markets=markets
)
freqtradebot = FreqtradeBot(default_conf)
rpc = RPC(freqtradebot)
freqtradebot.state = State.STOPPED
(error, result) = rpc.rpc_trade_status()
assert error
assert 'trader is not running' in result
with pytest.raises(RPCException, match=r'.*trader is not running*'):
rpc._rpc_trade_status()
freqtradebot.state = State.RUNNING
(error, result) = rpc.rpc_trade_status()
assert error
assert 'no active trade' in result
with pytest.raises(RPCException, match=r'.*no active trade*'):
rpc._rpc_trade_status()
freqtradebot.create_trade()
(error, result) = rpc.rpc_trade_status()
assert not error
trade = result[0]
trades = rpc._rpc_trade_status()
trade = trades[0]
result_message = [
'*Trade ID:* `1`\n'
@ -68,57 +69,57 @@ def test_rpc_trade_status(default_conf, ticker, fee, mocker) -> None:
'*Current Profit:* `-0.59%`\n'
'*Open Order:* `(limit buy rem=0.00000000)`'
]
assert result == result_message
assert trades == result_message
assert trade.find('[ETH/BTC]') >= 0
def test_rpc_status_table(default_conf, ticker, fee, mocker) -> None:
def test_rpc_status_table(default_conf, ticker, fee, markets, mocker) -> None:
"""
Test rpc_status_table() method
"""
patch_get_signal(mocker, (True, False))
patch_coinmarketcap(mocker)
mocker.patch('freqtrade.rpc.rpc_manager.Telegram', MagicMock())
mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
mocker.patch.multiple(
'freqtrade.freqtradebot.exchange',
'freqtrade.exchange.Exchange',
validate_pairs=MagicMock(),
get_ticker=ticker,
get_fee=fee
get_fee=fee,
get_markets=markets
)
freqtradebot = FreqtradeBot(default_conf)
rpc = RPC(freqtradebot)
freqtradebot.state = State.STOPPED
(error, result) = rpc.rpc_status_table()
assert error
assert '*Status:* `trader is not running`' in result
with pytest.raises(RPCException, match=r'.*\*Status:\* `trader is not running``*'):
rpc._rpc_status_table()
freqtradebot.state = State.RUNNING
(error, result) = rpc.rpc_status_table()
assert error
assert '*Status:* `no active order`' in result
with pytest.raises(RPCException, match=r'.*\*Status:\* `no active order`*'):
rpc._rpc_status_table()
freqtradebot.create_trade()
(error, result) = rpc.rpc_status_table()
result = rpc._rpc_status_table()
assert 'just now' in result['Since'].all()
assert 'ETH/BTC' in result['Pair'].all()
assert '-0.59%' in result['Profit'].all()
def test_rpc_daily_profit(default_conf, update, ticker, fee,
limit_buy_order, limit_sell_order, mocker) -> None:
limit_buy_order, limit_sell_order, markets, mocker) -> None:
"""
Test rpc_daily_profit() method
"""
patch_get_signal(mocker, (True, False))
patch_coinmarketcap(mocker, value={'price_usd': 15000.0})
mocker.patch('freqtrade.rpc.rpc_manager.Telegram', MagicMock())
mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
mocker.patch.multiple(
'freqtrade.freqtradebot.exchange',
'freqtrade.exchange.Exchange',
validate_pairs=MagicMock(),
get_ticker=ticker,
get_fee=fee
get_fee=fee,
get_markets=markets
)
freqtradebot = FreqtradeBot(default_conf)
@ -140,8 +141,7 @@ def test_rpc_daily_profit(default_conf, update, ticker, fee,
# Try valid data
update.message.text = '/daily 2'
(error, days) = rpc.rpc_daily_profit(7, stake_currency, fiat_display_currency)
assert not error
days = rpc._rpc_daily_profit(7, stake_currency, fiat_display_currency)
assert len(days) == 7
for day in days:
# [datetime.date(2018, 1, 11), '0.00000000 BTC', '0.000 USD']
@ -154,13 +154,12 @@ def test_rpc_daily_profit(default_conf, update, ticker, fee,
assert str(days[0][0]) == str(datetime.utcnow().date())
# Try invalid data
(error, days) = rpc.rpc_daily_profit(0, stake_currency, fiat_display_currency)
assert error
assert days.find('must be an integer greater than 0') >= 0
with pytest.raises(RPCException, match=r'.*must be an integer greater than 0*'):
rpc._rpc_daily_profit(0, stake_currency, fiat_display_currency)
def test_rpc_trade_statistics(default_conf, ticker, ticker_sell_up, fee,
limit_buy_order, limit_sell_order, mocker) -> None:
limit_buy_order, limit_sell_order, markets, mocker) -> None:
"""
Test rpc_trade_statistics() method
"""
@ -170,12 +169,13 @@ def test_rpc_trade_statistics(default_conf, ticker, ticker_sell_up, fee,
ticker=MagicMock(return_value={'price_usd': 15000.0}),
)
mocker.patch('freqtrade.fiat_convert.CryptoToFiatConverter._find_price', return_value=15000.0)
mocker.patch('freqtrade.rpc.rpc_manager.Telegram', MagicMock())
mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
mocker.patch.multiple(
'freqtrade.freqtradebot.exchange',
'freqtrade.exchange.Exchange',
validate_pairs=MagicMock(),
get_ticker=ticker,
get_fee=fee
get_fee=fee,
get_markets=markets
)
freqtradebot = FreqtradeBot(default_conf)
@ -184,9 +184,8 @@ def test_rpc_trade_statistics(default_conf, ticker, ticker_sell_up, fee,
rpc = RPC(freqtradebot)
(error, stats) = rpc.rpc_trade_statistics(stake_currency, fiat_display_currency)
assert error
assert stats.find('no closed trade') >= 0
with pytest.raises(RPCException, match=r'.*no closed trade*'):
rpc._rpc_trade_statistics(stake_currency, fiat_display_currency)
# Create some test data
freqtradebot.create_trade()
@ -196,7 +195,7 @@ def test_rpc_trade_statistics(default_conf, ticker, ticker_sell_up, fee,
# Update the ticker with a market going up
mocker.patch.multiple(
'freqtrade.freqtradebot.exchange',
'freqtrade.exchange.Exchange',
validate_pairs=MagicMock(),
get_ticker=ticker_sell_up
)
@ -211,7 +210,7 @@ def test_rpc_trade_statistics(default_conf, ticker, ticker_sell_up, fee,
# Update the ticker with a market going up
mocker.patch.multiple(
'freqtrade.freqtradebot.exchange',
'freqtrade.exchange.Exchange',
validate_pairs=MagicMock(),
get_ticker=ticker_sell_up
)
@ -219,8 +218,7 @@ def test_rpc_trade_statistics(default_conf, ticker, ticker_sell_up, fee,
trade.close_date = datetime.utcnow()
trade.is_open = False
(error, stats) = rpc.rpc_trade_statistics(stake_currency, fiat_display_currency)
assert not error
stats = rpc._rpc_trade_statistics(stake_currency, fiat_display_currency)
assert prec_satoshi(stats['profit_closed_coin'], 6.217e-05)
assert prec_satoshi(stats['profit_closed_percent'], 6.2)
assert prec_satoshi(stats['profit_closed_fiat'], 0.93255)
@ -237,7 +235,7 @@ def test_rpc_trade_statistics(default_conf, ticker, ticker_sell_up, fee,
# Test that rpc_trade_statistics can handle trades that lacks
# trade.open_rate (it is set to None)
def test_rpc_trade_statistics_closed(mocker, default_conf, ticker, fee,
def test_rpc_trade_statistics_closed(mocker, default_conf, ticker, fee, markets,
ticker_sell_up, limit_buy_order, limit_sell_order):
"""
Test rpc_trade_statistics() method
@ -248,12 +246,13 @@ def test_rpc_trade_statistics_closed(mocker, default_conf, ticker, fee,
ticker=MagicMock(return_value={'price_usd': 15000.0}),
)
mocker.patch('freqtrade.fiat_convert.CryptoToFiatConverter._find_price', return_value=15000.0)
mocker.patch('freqtrade.rpc.rpc_manager.Telegram', MagicMock())
mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
mocker.patch.multiple(
'freqtrade.freqtradebot.exchange',
'freqtrade.exchange.Exchange',
validate_pairs=MagicMock(),
get_ticker=ticker,
get_fee=fee
get_fee=fee,
get_markets=markets
)
freqtradebot = FreqtradeBot(default_conf)
@ -269,7 +268,7 @@ def test_rpc_trade_statistics_closed(mocker, default_conf, ticker, fee,
trade.update(limit_buy_order)
# Update the ticker with a market going up
mocker.patch.multiple(
'freqtrade.freqtradebot.exchange',
'freqtrade.exchange.Exchange',
validate_pairs=MagicMock(),
get_ticker=ticker_sell_up,
get_fee=fee
@ -281,8 +280,7 @@ def test_rpc_trade_statistics_closed(mocker, default_conf, ticker, fee,
for trade in Trade.query.order_by(Trade.id).all():
trade.open_rate = None
(error, stats) = rpc.rpc_trade_statistics(stake_currency, fiat_display_currency)
assert not error
stats = rpc._rpc_trade_statistics(stake_currency, fiat_display_currency)
assert prec_satoshi(stats['profit_closed_coin'], 0)
assert prec_satoshi(stats['profit_closed_percent'], 0)
assert prec_satoshi(stats['profit_closed_fiat'], 0)
@ -320,9 +318,9 @@ def test_rpc_balance_handle(default_conf, mocker):
ticker=MagicMock(return_value={'price_usd': 15000.0}),
)
mocker.patch('freqtrade.fiat_convert.CryptoToFiatConverter._find_price', return_value=15000.0)
mocker.patch('freqtrade.rpc.rpc_manager.Telegram', MagicMock())
mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
mocker.patch.multiple(
'freqtrade.freqtradebot.exchange',
'freqtrade.exchange.Exchange',
validate_pairs=MagicMock(),
get_balances=MagicMock(return_value=mock_balance)
)
@ -330,18 +328,16 @@ def test_rpc_balance_handle(default_conf, mocker):
freqtradebot = FreqtradeBot(default_conf)
rpc = RPC(freqtradebot)
(error, res) = rpc.rpc_balance(default_conf['fiat_display_currency'])
assert not error
(trade, x, y, z) = res
assert prec_satoshi(x, 12)
assert prec_satoshi(z, 180000)
assert 'USD' in y
assert len(trade) == 1
assert 'BTC' in trade[0]['currency']
assert prec_satoshi(trade[0]['available'], 10)
assert prec_satoshi(trade[0]['balance'], 12)
assert prec_satoshi(trade[0]['pending'], 2)
assert prec_satoshi(trade[0]['est_btc'], 12)
output, total, symbol, value = rpc._rpc_balance(default_conf['fiat_display_currency'])
assert prec_satoshi(total, 12)
assert prec_satoshi(value, 180000)
assert 'USD' in symbol
assert len(output) == 1
assert 'BTC' in output[0]['currency']
assert prec_satoshi(output[0]['available'], 10)
assert prec_satoshi(output[0]['balance'], 12)
assert prec_satoshi(output[0]['pending'], 2)
assert prec_satoshi(output[0]['est_btc'], 12)
def test_rpc_start(mocker, default_conf) -> None:
@ -350,9 +346,9 @@ def test_rpc_start(mocker, default_conf) -> None:
"""
patch_get_signal(mocker, (True, False))
patch_coinmarketcap(mocker)
mocker.patch('freqtrade.rpc.rpc_manager.Telegram', MagicMock())
mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
mocker.patch.multiple(
'freqtrade.freqtradebot.exchange',
'freqtrade.exchange.Exchange',
validate_pairs=MagicMock(),
get_ticker=MagicMock()
)
@ -361,13 +357,11 @@ def test_rpc_start(mocker, default_conf) -> None:
rpc = RPC(freqtradebot)
freqtradebot.state = State.STOPPED
(error, result) = rpc.rpc_start()
assert not error
result = rpc._rpc_start()
assert '`Starting trader ...`' in result
assert freqtradebot.state == State.RUNNING
(error, result) = rpc.rpc_start()
assert error
result = rpc._rpc_start()
assert '*Status:* `already running`' in result
assert freqtradebot.state == State.RUNNING
@ -378,9 +372,9 @@ def test_rpc_stop(mocker, default_conf) -> None:
"""
patch_get_signal(mocker, (True, False))
patch_coinmarketcap(mocker)
mocker.patch('freqtrade.rpc.rpc_manager.Telegram', MagicMock())
mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
mocker.patch.multiple(
'freqtrade.freqtradebot.exchange',
'freqtrade.exchange.Exchange',
validate_pairs=MagicMock(),
get_ticker=MagicMock()
)
@ -389,28 +383,26 @@ def test_rpc_stop(mocker, default_conf) -> None:
rpc = RPC(freqtradebot)
freqtradebot.state = State.RUNNING
(error, result) = rpc.rpc_stop()
assert not error
result = rpc._rpc_stop()
assert '`Stopping trader ...`' in result
assert freqtradebot.state == State.STOPPED
(error, result) = rpc.rpc_stop()
assert error
result = rpc._rpc_stop()
assert '*Status:* `already stopped`' in result
assert freqtradebot.state == State.STOPPED
def test_rpc_forcesell(default_conf, ticker, fee, mocker) -> None:
def test_rpc_forcesell(default_conf, ticker, fee, mocker, markets) -> None:
"""
Test rpc_forcesell() method
"""
patch_get_signal(mocker, (True, False))
patch_coinmarketcap(mocker)
mocker.patch('freqtrade.rpc.rpc_manager.Telegram', MagicMock())
mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
cancel_order_mock = MagicMock()
mocker.patch.multiple(
'freqtrade.freqtradebot.exchange',
'freqtrade.exchange.Exchange',
validate_pairs=MagicMock(),
get_ticker=ticker,
cancel_order=cancel_order_mock,
@ -422,42 +414,33 @@ def test_rpc_forcesell(default_conf, ticker, fee, mocker) -> None:
}
),
get_fee=fee,
get_markets=markets
)
freqtradebot = FreqtradeBot(default_conf)
rpc = RPC(freqtradebot)
freqtradebot.state = State.STOPPED
(error, res) = rpc.rpc_forcesell(None)
assert error
assert res == '`trader is not running`'
with pytest.raises(RPCException, match=r'.*`trader is not running`*'):
rpc._rpc_forcesell(None)
freqtradebot.state = State.RUNNING
(error, res) = rpc.rpc_forcesell(None)
assert error
assert res == 'Invalid argument.'
with pytest.raises(RPCException, match=r'.*Invalid argument.*'):
rpc._rpc_forcesell(None)
(error, res) = rpc.rpc_forcesell('all')
assert not error
assert res == ''
rpc._rpc_forcesell('all')
freqtradebot.create_trade()
(error, res) = rpc.rpc_forcesell('all')
assert not error
assert res == ''
rpc._rpc_forcesell('all')
(error, res) = rpc.rpc_forcesell('1')
assert not error
assert res == ''
rpc._rpc_forcesell('1')
freqtradebot.state = State.STOPPED
(error, res) = rpc.rpc_forcesell(None)
assert error
assert res == '`trader is not running`'
with pytest.raises(RPCException, match=r'.*`trader is not running`*'):
rpc._rpc_forcesell(None)
(error, res) = rpc.rpc_forcesell('all')
assert error
assert res == '`trader is not running`'
with pytest.raises(RPCException, match=r'.*`trader is not running`*'):
rpc._rpc_forcesell('all')
freqtradebot.state = State.RUNNING
assert cancel_order_mock.call_count == 0
@ -465,7 +448,7 @@ def test_rpc_forcesell(default_conf, ticker, fee, mocker) -> None:
trade = Trade.query.filter(Trade.id == '1').first()
filled_amount = trade.amount / 2
mocker.patch(
'freqtrade.freqtradebot.exchange.get_order',
'freqtrade.exchange.Exchange.get_order',
return_value={
'status': 'open',
'type': 'limit',
@ -475,9 +458,7 @@ def test_rpc_forcesell(default_conf, ticker, fee, mocker) -> None:
)
# check that the trade is called, which is done by ensuring exchange.cancel_order is called
# and trade amount is updated
(error, res) = rpc.rpc_forcesell('1')
assert not error
assert res == ''
rpc._rpc_forcesell('1')
assert cancel_order_mock.call_count == 1
assert trade.amount == filled_amount
@ -486,7 +467,7 @@ def test_rpc_forcesell(default_conf, ticker, fee, mocker) -> None:
amount = trade.amount
# make an limit-buy open trade, if there is no 'filled', don't sell it
mocker.patch(
'freqtrade.freqtradebot.exchange.get_order',
'freqtrade.exchange.Exchange.get_order',
return_value={
'status': 'open',
'type': 'limit',
@ -495,43 +476,40 @@ def test_rpc_forcesell(default_conf, ticker, fee, mocker) -> None:
}
)
# check that the trade is called, which is done by ensuring exchange.cancel_order is called
(error, res) = rpc.rpc_forcesell('2')
assert not error
assert res == ''
rpc._rpc_forcesell('2')
assert cancel_order_mock.call_count == 2
assert trade.amount == amount
freqtradebot.create_trade()
# make an limit-sell open trade
mocker.patch(
'freqtrade.freqtradebot.exchange.get_order',
'freqtrade.exchange.Exchange.get_order',
return_value={
'status': 'open',
'type': 'limit',
'side': 'sell'
}
)
(error, res) = rpc.rpc_forcesell('3')
assert not error
assert res == ''
rpc._rpc_forcesell('3')
# status quo, no exchange calls
assert cancel_order_mock.call_count == 2
def test_performance_handle(default_conf, ticker, limit_buy_order, fee,
limit_sell_order, mocker) -> None:
limit_sell_order, markets, mocker) -> None:
"""
Test rpc_performance() method
"""
patch_get_signal(mocker, (True, False))
patch_coinmarketcap(mocker)
mocker.patch('freqtrade.rpc.rpc_manager.Telegram', MagicMock())
mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
mocker.patch.multiple(
'freqtrade.freqtradebot.exchange',
'freqtrade.exchange.Exchange',
validate_pairs=MagicMock(),
get_balances=MagicMock(return_value=ticker),
get_ticker=ticker,
get_fee=fee
get_fee=fee,
get_markets=markets
)
freqtradebot = FreqtradeBot(default_conf)
@ -550,40 +528,38 @@ def test_performance_handle(default_conf, ticker, limit_buy_order, fee,
trade.close_date = datetime.utcnow()
trade.is_open = False
(error, res) = rpc.rpc_performance()
assert not error
res = rpc._rpc_performance()
assert len(res) == 1
assert res[0]['pair'] == 'ETH/BTC'
assert res[0]['count'] == 1
assert prec_satoshi(res[0]['profit'], 6.2)
def test_rpc_count(mocker, default_conf, ticker, fee) -> None:
def test_rpc_count(mocker, default_conf, ticker, fee, markets) -> None:
"""
Test rpc_count() method
"""
patch_get_signal(mocker, (True, False))
patch_coinmarketcap(mocker)
mocker.patch('freqtrade.rpc.rpc_manager.Telegram', MagicMock())
mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
mocker.patch.multiple(
'freqtrade.freqtradebot.exchange',
'freqtrade.exchange.Exchange',
validate_pairs=MagicMock(),
get_balances=MagicMock(return_value=ticker),
get_ticker=ticker,
get_fee=fee,
get_markets=markets
)
freqtradebot = FreqtradeBot(default_conf)
rpc = RPC(freqtradebot)
(error, trades) = rpc.rpc_count()
trades = rpc._rpc_count()
nb_trades = len(trades)
assert not error
assert nb_trades == 0
# Create some test data
freqtradebot.create_trade()
(error, trades) = rpc.rpc_count()
trades = rpc._rpc_count()
nb_trades = len(trades)
assert not error
assert nb_trades == 1

44
freqtrade/tests/rpc/test_rpc_manager.py
View File

@ -7,49 +7,35 @@ from copy import deepcopy
from unittest.mock import MagicMock
from freqtrade.rpc.rpc_manager import RPCManager
from freqtrade.rpc.telegram import Telegram
from freqtrade.tests.conftest import log_has, get_patched_freqtradebot
from freqtrade.tests.conftest import get_patched_freqtradebot, log_has
def test_rpc_manager_object() -> None:
"""
Test the Arguments object has the mandatory methods
:return: None
"""
assert hasattr(RPCManager, '_init')
""" Test the Arguments object has the mandatory methods """
assert hasattr(RPCManager, 'send_msg')
assert hasattr(RPCManager, 'cleanup')
def test__init__(mocker, default_conf) -> None:
"""
Test __init__() method
"""
init_mock = mocker.patch('freqtrade.rpc.rpc_manager.RPCManager._init', MagicMock())
freqtradebot = get_patched_freqtradebot(mocker, default_conf)
""" Test __init__() method """
conf = deepcopy(default_conf)
conf['telegram']['enabled'] = False
rpc_manager = RPCManager(freqtradebot)
assert rpc_manager.freqtrade == freqtradebot
rpc_manager = RPCManager(get_patched_freqtradebot(mocker, conf))
assert rpc_manager.registered_modules == []
assert rpc_manager.telegram is None
assert init_mock.call_count == 1
def test_init_telegram_disabled(mocker, default_conf, caplog) -> None:
"""
Test _init() method with Telegram disabled
"""
""" Test _init() method with Telegram disabled """
caplog.set_level(logging.DEBUG)
conf = deepcopy(default_conf)
conf['telegram']['enabled'] = False
freqtradebot = get_patched_freqtradebot(mocker, conf)
rpc_manager = RPCManager(freqtradebot)
rpc_manager = RPCManager(get_patched_freqtradebot(mocker, conf))
assert not log_has('Enabling rpc.telegram ...', caplog.record_tuples)
assert rpc_manager.registered_modules == []
assert rpc_manager.telegram is None
def test_init_telegram_enabled(mocker, default_conf, caplog) -> None:
@ -59,14 +45,12 @@ def test_init_telegram_enabled(mocker, default_conf, caplog) -> None:
caplog.set_level(logging.DEBUG)
mocker.patch('freqtrade.rpc.telegram.Telegram._init', MagicMock())
freqtradebot = get_patched_freqtradebot(mocker, default_conf)
rpc_manager = RPCManager(freqtradebot)
rpc_manager = RPCManager(get_patched_freqtradebot(mocker, default_conf))
assert log_has('Enabling rpc.telegram ...', caplog.record_tuples)
len_modules = len(rpc_manager.registered_modules)
assert len_modules == 1
assert 'telegram' in rpc_manager.registered_modules
assert isinstance(rpc_manager.telegram, Telegram)
assert 'telegram' in [mod.name for mod in rpc_manager.registered_modules]
def test_cleanup_telegram_disabled(mocker, default_conf, caplog) -> None:
@ -99,11 +83,11 @@ def test_cleanup_telegram_enabled(mocker, default_conf, caplog) -> None:
rpc_manager = RPCManager(freqtradebot)
# Check we have Telegram as a registered modules
assert 'telegram' in rpc_manager.registered_modules
assert 'telegram' in [mod.name for mod in rpc_manager.registered_modules]
rpc_manager.cleanup()
assert log_has('Cleaning up rpc.telegram ...', caplog.record_tuples)
assert 'telegram' not in rpc_manager.registered_modules
assert 'telegram' not in [mod.name for mod in rpc_manager.registered_modules]
assert telegram_mock.call_count == 1
@ -120,7 +104,7 @@ def test_send_msg_telegram_disabled(mocker, default_conf, caplog) -> None:
rpc_manager = RPCManager(freqtradebot)
rpc_manager.send_msg('test')
assert log_has('test', caplog.record_tuples)
assert log_has('Sending rpc message: test', caplog.record_tuples)
assert telegram_mock.call_count == 0
@ -135,5 +119,5 @@ def test_send_msg_telegram_enabled(mocker, default_conf, caplog) -> None:
rpc_manager = RPCManager(freqtradebot)
rpc_manager.send_msg('test')
assert log_has('test', caplog.record_tuples)
assert log_has('Sending rpc message: test', caplog.record_tuples)
assert telegram_mock.call_count == 1

256
freqtrade/tests/rpc/test_rpc_telegram.py
View File

@ -11,17 +11,18 @@ from datetime import datetime
from random import randint
from unittest.mock import MagicMock
from telegram import Update, Message, Chat
from telegram import Chat, Message, Update
from telegram.error import NetworkError
from freqtrade import __version__
from freqtrade.freqtradebot import FreqtradeBot
from freqtrade.persistence import Trade
from freqtrade.rpc.telegram import Telegram
from freqtrade.rpc.telegram import authorized_only
from freqtrade.rpc.telegram import Telegram, authorized_only
from freqtrade.state import State
from freqtrade.tests.conftest import get_patched_freqtradebot, log_has
from freqtrade.tests.test_freqtradebot import patch_get_signal, patch_coinmarketcap
from freqtrade.tests.conftest import (get_patched_freqtradebot, log_has,
patch_exchange)
from freqtrade.tests.test_freqtradebot import (patch_coinmarketcap,
patch_get_signal)
class DummyCls(Telegram):
@ -32,6 +33,9 @@ class DummyCls(Telegram):
super().__init__(freqtrade)
self.state = {'called': False}
def _init(self):
pass
@authorized_only
def dummy_handler(self, *args, **kwargs) -> None:
"""
@ -60,9 +64,7 @@ def test__init__(default_conf, mocker) -> None:
def test_init(default_conf, mocker, caplog) -> None:
"""
Test _init() method
"""
""" Test _init() method """
start_polling = MagicMock()
mocker.patch('freqtrade.rpc.telegram.Updater', MagicMock(return_value=start_polling))
@ -80,21 +82,6 @@ def test_init(default_conf, mocker, caplog) -> None:
assert log_has(message_str, caplog.record_tuples)
def test_init_disabled(default_conf, mocker, caplog) -> None:
"""
Test _init() method when Telegram is disabled
"""
conf = deepcopy(default_conf)
conf['telegram']['enabled'] = False
Telegram(get_patched_freqtradebot(mocker, conf))
message_str = "rpc.telegram is listening for following commands: [['status'], ['profit'], " \
"['balance'], ['start'], ['stop'], ['forcesell'], ['performance'], ['daily'], " \
"['count'], ['help'], ['version']]"
assert not log_has(message_str, caplog.record_tuples)
def test_cleanup(default_conf, mocker) -> None:
"""
Test cleanup() method
@ -103,51 +90,18 @@ def test_cleanup(default_conf, mocker) -> None:
updater_mock.stop = MagicMock()
mocker.patch('freqtrade.rpc.telegram.Updater', updater_mock)
# not enabled
conf = deepcopy(default_conf)
conf['telegram']['enabled'] = False
telegram = Telegram(get_patched_freqtradebot(mocker, conf))
telegram.cleanup()
assert telegram._updater is None
assert updater_mock.call_count == 0
assert not hasattr(telegram._updater, 'stop')
assert updater_mock.stop.call_count == 0
# enabled
conf['telegram']['enabled'] = True
telegram = Telegram(get_patched_freqtradebot(mocker, conf))
telegram = Telegram(get_patched_freqtradebot(mocker, default_conf))
telegram.cleanup()
assert telegram._updater.stop.call_count == 1
def test_is_enabled(default_conf, mocker) -> None:
"""
Test is_enabled() method
"""
mocker.patch('freqtrade.rpc.telegram.Updater', MagicMock())
telegram = Telegram(get_patched_freqtradebot(mocker, default_conf))
assert telegram.is_enabled()
def test_is_not_enabled(default_conf, mocker) -> None:
"""
Test is_enabled() method
"""
conf = deepcopy(default_conf)
conf['telegram']['enabled'] = False
telegram = Telegram(get_patched_freqtradebot(mocker, conf))
assert not telegram.is_enabled()
def test_authorized_only(default_conf, mocker, caplog) -> None:
"""
Test authorized_only() method when we are authorized
"""
patch_get_signal(mocker, (True, False))
patch_coinmarketcap(mocker)
mocker.patch('freqtrade.freqtradebot.exchange.init', MagicMock())
patch_exchange(mocker, None)
chat = Chat(0, 0)
update = Update(randint(1, 100))
@ -178,8 +132,7 @@ def test_authorized_only_unauthorized(default_conf, mocker, caplog) -> None:
"""
patch_get_signal(mocker, (True, False))
patch_coinmarketcap(mocker)
mocker.patch('freqtrade.freqtradebot.exchange.init', MagicMock())
patch_exchange(mocker, None)
chat = Chat(0xdeadbeef, 0)
update = Update(randint(1, 100))
update.message = Message(randint(1, 100), 0, datetime.utcnow(), chat)
@ -209,7 +162,7 @@ def test_authorized_only_exception(default_conf, mocker, caplog) -> None:
"""
patch_get_signal(mocker, (True, False))
patch_coinmarketcap(mocker)
mocker.patch('freqtrade.freqtradebot.exchange.init', MagicMock())
patch_exchange(mocker)
update = Update(randint(1, 100))
update.message = Message(randint(1, 100), 0, datetime.utcnow(), Chat(0, 0))
@ -233,7 +186,7 @@ def test_authorized_only_exception(default_conf, mocker, caplog) -> None:
)
def test_status(default_conf, update, mocker, fee, ticker) -> None:
def test_status(default_conf, update, mocker, fee, ticker, markets) -> None:
"""
Test _status() method
"""
@ -245,20 +198,21 @@ def test_status(default_conf, update, mocker, fee, ticker) -> None:
patch_get_signal(mocker, (True, False))
patch_coinmarketcap(mocker)
mocker.patch.multiple(
'freqtrade.freqtradebot.exchange',
'freqtrade.exchange.Exchange',
validate_pairs=MagicMock(),
get_ticker=ticker,
get_pair_detail_url=MagicMock(),
get_fee=fee,
get_markets=markets
)
msg_mock = MagicMock()
status_table = MagicMock()
mocker.patch.multiple(
'freqtrade.rpc.telegram.Telegram',
_init=MagicMock(),
rpc_trade_status=MagicMock(return_value=(False, [1, 2, 3])),
_rpc_trade_status=MagicMock(return_value=[1, 2, 3]),
_status_table=status_table,
send_msg=msg_mock
_send_msg=msg_mock
)
mocker.patch('freqtrade.freqtradebot.RPCManager', MagicMock())
@ -278,17 +232,18 @@ def test_status(default_conf, update, mocker, fee, ticker) -> None:
assert status_table.call_count == 1
def test_status_handle(default_conf, update, ticker, fee, mocker) -> None:
def test_status_handle(default_conf, update, ticker, fee, markets, mocker) -> None:
"""
Test _status() method
"""
patch_get_signal(mocker, (True, False))
patch_coinmarketcap(mocker)
mocker.patch.multiple(
'freqtrade.freqtradebot.exchange',
'freqtrade.exchange.Exchange',
validate_pairs=MagicMock(),
get_ticker=ticker,
get_fee=fee,
get_markets=markets
)
msg_mock = MagicMock()
status_table = MagicMock()
@ -296,7 +251,7 @@ def test_status_handle(default_conf, update, ticker, fee, mocker) -> None:
'freqtrade.rpc.telegram.Telegram',
_init=MagicMock(),
_status_table=status_table,
send_msg=msg_mock
_send_msg=msg_mock
)
mocker.patch('freqtrade.freqtradebot.RPCManager', MagicMock())
@ -324,24 +279,25 @@ def test_status_handle(default_conf, update, ticker, fee, mocker) -> None:
assert '[ETH/BTC]' in msg_mock.call_args_list[0][0][0]
def test_status_table_handle(default_conf, update, ticker, fee, mocker) -> None:
def test_status_table_handle(default_conf, update, ticker, fee, markets, mocker) -> None:
"""
Test _status_table() method
"""
patch_get_signal(mocker, (True, False))
patch_coinmarketcap(mocker)
mocker.patch.multiple(
'freqtrade.freqtradebot.exchange',
'freqtrade.exchange.Exchange',
validate_pairs=MagicMock(),
get_ticker=ticker,
buy=MagicMock(return_value={'id': 'mocked_order_id'}),
get_fee=fee,
get_markets=markets
)
msg_mock = MagicMock()
mocker.patch.multiple(
'freqtrade.rpc.telegram.Telegram',
_init=MagicMock(),
send_msg=msg_mock
_send_msg=msg_mock
)
mocker.patch('freqtrade.freqtradebot.RPCManager', MagicMock())
@ -377,7 +333,7 @@ def test_status_table_handle(default_conf, update, ticker, fee, mocker) -> None:
def test_daily_handle(default_conf, update, ticker, limit_buy_order, fee,
limit_sell_order, mocker) -> None:
limit_sell_order, markets, mocker) -> None:
"""
Test _daily() method
"""
@ -388,16 +344,17 @@ def test_daily_handle(default_conf, update, ticker, limit_buy_order, fee,
return_value=15000.0
)
mocker.patch.multiple(
'freqtrade.freqtradebot.exchange',
'freqtrade.exchange.Exchange',
validate_pairs=MagicMock(),
get_ticker=ticker,
get_fee=fee
get_fee=fee,
get_markets=markets
)
msg_mock = MagicMock()
mocker.patch.multiple(
'freqtrade.rpc.telegram.Telegram',
_init=MagicMock(),
send_msg=msg_mock
_send_msg=msg_mock
)
mocker.patch('freqtrade.freqtradebot.RPCManager', MagicMock())
@ -457,7 +414,7 @@ def test_daily_wrong_input(default_conf, update, ticker, mocker) -> None:
patch_get_signal(mocker, (True, False))
patch_coinmarketcap(mocker, value={'price_usd': 15000.0})
mocker.patch.multiple(
'freqtrade.freqtradebot.exchange',
'freqtrade.exchange.Exchange',
validate_pairs=MagicMock(),
get_ticker=ticker
)
@ -465,7 +422,7 @@ def test_daily_wrong_input(default_conf, update, ticker, mocker) -> None:
mocker.patch.multiple(
'freqtrade.rpc.telegram.Telegram',
_init=MagicMock(),
send_msg=msg_mock
_send_msg=msg_mock
)
mocker.patch('freqtrade.freqtradebot.RPCManager', MagicMock())
@ -489,7 +446,7 @@ def test_daily_wrong_input(default_conf, update, ticker, mocker) -> None:
def test_profit_handle(default_conf, update, ticker, ticker_sell_up, fee,
limit_buy_order, limit_sell_order, mocker) -> None:
limit_buy_order, limit_sell_order, markets, mocker) -> None:
"""
Test _profit() method
"""
@ -497,16 +454,17 @@ def test_profit_handle(default_conf, update, ticker, ticker_sell_up, fee,
patch_coinmarketcap(mocker, value={'price_usd': 15000.0})
mocker.patch('freqtrade.fiat_convert.CryptoToFiatConverter._find_price', return_value=15000.0)
mocker.patch.multiple(
'freqtrade.freqtradebot.exchange',
'freqtrade.exchange.Exchange',
validate_pairs=MagicMock(),
get_ticker=ticker,
get_fee=fee
get_fee=fee,
get_markets=markets
)
msg_mock = MagicMock()
mocker.patch.multiple(
'freqtrade.rpc.telegram.Telegram',
_init=MagicMock(),
send_msg=msg_mock
_send_msg=msg_mock
)
mocker.patch('freqtrade.freqtradebot.RPCManager', MagicMock())
@ -531,7 +489,7 @@ def test_profit_handle(default_conf, update, ticker, ticker_sell_up, fee,
msg_mock.reset_mock()
# Update the ticker with a market going up
mocker.patch('freqtrade.freqtradebot.exchange.get_ticker', ticker_sell_up)
mocker.patch('freqtrade.exchange.Exchange.get_ticker', ticker_sell_up)
trade.update(limit_sell_order)
trade.close_date = datetime.utcnow()
@ -596,18 +554,17 @@ def test_telegram_balance_handle(default_conf, update, mocker) -> None:
patch_get_signal(mocker, (True, False))
patch_coinmarketcap(mocker, value={'price_usd': 15000.0})
mocker.patch('freqtrade.freqtradebot.exchange.init', MagicMock())
mocker.patch('freqtrade.freqtradebot.exchange.get_balances', return_value=mock_balance)
mocker.patch('freqtrade.freqtradebot.exchange.get_ticker', side_effect=mock_ticker)
mocker.patch('freqtrade.exchange.Exchange.get_balances', return_value=mock_balance)
mocker.patch('freqtrade.exchange.Exchange.get_ticker', side_effect=mock_ticker)
msg_mock = MagicMock()
mocker.patch.multiple(
'freqtrade.rpc.telegram.Telegram',
_init=MagicMock(),
send_msg=msg_mock
_send_msg=msg_mock
)
freqtradebot = FreqtradeBot(default_conf)
freqtradebot = get_patched_freqtradebot(mocker, default_conf)
telegram = Telegram(freqtradebot)
telegram._balance(bot=MagicMock(), update=update)
@ -626,18 +583,16 @@ def test_zero_balance_handle(default_conf, update, mocker) -> None:
Test _balance() method when the Exchange platform returns nothing
"""
patch_get_signal(mocker, (True, False))
patch_coinmarketcap(mocker, value={'price_usd': 15000.0})
mocker.patch('freqtrade.freqtradebot.exchange.init', MagicMock())
mocker.patch('freqtrade.freqtradebot.exchange.get_balances', return_value={})
mocker.patch('freqtrade.exchange.Exchange.get_balances', return_value={})
msg_mock = MagicMock()
mocker.patch.multiple(
'freqtrade.rpc.telegram.Telegram',
_init=MagicMock(),
send_msg=msg_mock
_send_msg=msg_mock
)
freqtradebot = FreqtradeBot(default_conf)
freqtradebot = get_patched_freqtradebot(mocker, default_conf)
telegram = Telegram(freqtradebot)
telegram._balance(bot=MagicMock(), update=update)
@ -650,41 +605,35 @@ def test_start_handle(default_conf, update, mocker) -> None:
"""
Test _start() method
"""
patch_coinmarketcap(mocker)
mocker.patch('freqtrade.freqtradebot.exchange.init', MagicMock())
msg_mock = MagicMock()
mocker.patch.multiple(
'freqtrade.rpc.telegram.Telegram',
_init=MagicMock(),
send_msg=msg_mock
_send_msg=msg_mock
)
mocker.patch('freqtrade.freqtradebot.RPCManager', MagicMock())
freqtradebot = FreqtradeBot(default_conf)
freqtradebot = get_patched_freqtradebot(mocker, default_conf)
telegram = Telegram(freqtradebot)
freqtradebot.state = State.STOPPED
assert freqtradebot.state == State.STOPPED
telegram._start(bot=MagicMock(), update=update)
assert freqtradebot.state == State.RUNNING
assert msg_mock.call_count == 0
assert msg_mock.call_count == 1
def test_start_handle_already_running(default_conf, update, mocker) -> None:
"""
Test _start() method
"""
patch_coinmarketcap(mocker)
mocker.patch('freqtrade.freqtradebot.exchange.init', MagicMock())
msg_mock = MagicMock()
mocker.patch.multiple(
'freqtrade.rpc.telegram.Telegram',
_init=MagicMock(),
send_msg=msg_mock
_send_msg=msg_mock
)
mocker.patch('freqtrade.freqtradebot.RPCManager', MagicMock())
freqtradebot = FreqtradeBot(default_conf)
freqtradebot = get_patched_freqtradebot(mocker, default_conf)
telegram = Telegram(freqtradebot)
freqtradebot.state = State.RUNNING
@ -700,16 +649,14 @@ def test_stop_handle(default_conf, update, mocker) -> None:
Test _stop() method
"""
patch_coinmarketcap(mocker)
mocker.patch('freqtrade.freqtradebot.exchange.init', MagicMock())
msg_mock = MagicMock()
mocker.patch.multiple(
'freqtrade.rpc.telegram.Telegram',
_init=MagicMock(),
send_msg=msg_mock
_send_msg=msg_mock
)
mocker.patch('freqtrade.freqtradebot.RPCManager', MagicMock())
freqtradebot = FreqtradeBot(default_conf)
freqtradebot = get_patched_freqtradebot(mocker, default_conf)
telegram = Telegram(freqtradebot)
freqtradebot.state = State.RUNNING
@ -725,16 +672,14 @@ def test_stop_handle_already_stopped(default_conf, update, mocker) -> None:
Test _stop() method
"""
patch_coinmarketcap(mocker)
mocker.patch('freqtrade.freqtradebot.exchange.init', MagicMock())
msg_mock = MagicMock()
mocker.patch.multiple(
'freqtrade.rpc.telegram.Telegram',
_init=MagicMock(),
send_msg=msg_mock
_send_msg=msg_mock
)
mocker.patch('freqtrade.freqtradebot.RPCManager', MagicMock())
freqtradebot = FreqtradeBot(default_conf)
freqtradebot = get_patched_freqtradebot(mocker, default_conf)
telegram = Telegram(freqtradebot)
freqtradebot.state = State.STOPPED
@ -748,16 +693,14 @@ def test_stop_handle_already_stopped(default_conf, update, mocker) -> None:
def test_reload_conf_handle(default_conf, update, mocker) -> None:
""" Test _reload_conf() method """
patch_coinmarketcap(mocker)
mocker.patch('freqtrade.freqtradebot.exchange.init', MagicMock())
msg_mock = MagicMock()
mocker.patch.multiple(
'freqtrade.rpc.telegram.Telegram',
_init=MagicMock(),
send_msg=msg_mock
_send_msg=msg_mock
)
mocker.patch('freqtrade.freqtradebot.RPCManager', MagicMock())
freqtradebot = FreqtradeBot(default_conf)
freqtradebot = get_patched_freqtradebot(mocker, default_conf)
telegram = Telegram(freqtradebot)
freqtradebot.state = State.RUNNING
@ -768,7 +711,8 @@ def test_reload_conf_handle(default_conf, update, mocker) -> None:
assert 'Reloading config' in msg_mock.call_args_list[0][0][0]
def test_forcesell_handle(default_conf, update, ticker, fee, ticker_sell_up, mocker) -> None:
def test_forcesell_handle(default_conf, update, ticker, fee,
ticker_sell_up, markets, mocker) -> None:
"""
Test _forcesell() method
"""
@ -778,10 +722,11 @@ def test_forcesell_handle(default_conf, update, ticker, fee, ticker_sell_up, moc
rpc_mock = mocker.patch('freqtrade.rpc.telegram.Telegram.send_msg', MagicMock())
mocker.patch('freqtrade.rpc.telegram.Telegram._init', MagicMock())
mocker.patch.multiple(
'freqtrade.freqtradebot.exchange',
'freqtrade.exchange.Exchange',
validate_pairs=MagicMock(),
get_ticker=ticker,
get_fee=fee
get_fee=fee,
get_markets=markets
)
freqtradebot = FreqtradeBot(default_conf)
@ -794,7 +739,7 @@ def test_forcesell_handle(default_conf, update, ticker, fee, ticker_sell_up, moc
assert trade
# Increase the price and sell it
mocker.patch('freqtrade.freqtradebot.exchange.get_ticker', ticker_sell_up)
mocker.patch('freqtrade.exchange.Exchange.get_ticker', ticker_sell_up)
update.message.text = '/forcesell 1'
telegram._forcesell(bot=MagicMock(), update=update)
@ -808,7 +753,8 @@ def test_forcesell_handle(default_conf, update, ticker, fee, ticker_sell_up, moc
assert '0.919 USD' in rpc_mock.call_args_list[-1][0][0]
def test_forcesell_down_handle(default_conf, update, ticker, fee, ticker_sell_down, mocker) -> None:
def test_forcesell_down_handle(default_conf, update, ticker, fee,
ticker_sell_down, markets, mocker) -> None:
"""
Test _forcesell() method
"""
@ -818,10 +764,11 @@ def test_forcesell_down_handle(default_conf, update, ticker, fee, ticker_sell_do
rpc_mock = mocker.patch('freqtrade.rpc.telegram.Telegram.send_msg', MagicMock())
mocker.patch('freqtrade.rpc.telegram.Telegram._init', MagicMock())
mocker.patch.multiple(
'freqtrade.freqtradebot.exchange',
'freqtrade.exchange.Exchange',
validate_pairs=MagicMock(),
get_ticker=ticker,
get_fee=fee
get_fee=fee,
get_markets=markets
)
freqtradebot = FreqtradeBot(default_conf)
@ -832,7 +779,7 @@ def test_forcesell_down_handle(default_conf, update, ticker, fee, ticker_sell_do
# Decrease the price and sell it
mocker.patch.multiple(
'freqtrade.freqtradebot.exchange',
'freqtrade.exchange.Exchange',
validate_pairs=MagicMock(),
get_ticker=ticker_sell_down
)
@ -852,7 +799,7 @@ def test_forcesell_down_handle(default_conf, update, ticker, fee, ticker_sell_do
assert '-0.824 USD' in rpc_mock.call_args_list[-1][0][0]
def test_forcesell_all_handle(default_conf, update, ticker, fee, mocker) -> None:
def test_forcesell_all_handle(default_conf, update, ticker, fee, markets, mocker) -> None:
"""
Test _forcesell() method
"""
@ -861,12 +808,13 @@ def test_forcesell_all_handle(default_conf, update, ticker, fee, mocker) -> None
mocker.patch('freqtrade.fiat_convert.CryptoToFiatConverter._find_price', return_value=15000.0)
rpc_mock = mocker.patch('freqtrade.rpc.telegram.Telegram.send_msg', MagicMock())
mocker.patch('freqtrade.rpc.telegram.Telegram._init', MagicMock())
mocker.patch('freqtrade.exchange.get_pair_detail_url', MagicMock())
mocker.patch('freqtrade.exchange.Exchange.get_pair_detail_url', MagicMock())
mocker.patch.multiple(
'freqtrade.freqtradebot.exchange',
'freqtrade.exchange.Exchange',
validate_pairs=MagicMock(),
get_ticker=ticker,
get_fee=fee
get_fee=fee,
get_markets=markets
)
freqtradebot = FreqtradeBot(default_conf)
@ -898,9 +846,9 @@ def test_forcesell_handle_invalid(default_conf, update, mocker) -> None:
mocker.patch.multiple(
'freqtrade.rpc.telegram.Telegram',
_init=MagicMock(),
send_msg=msg_mock
_send_msg=msg_mock
)
mocker.patch('freqtrade.freqtradebot.exchange.validate_pairs', MagicMock())
mocker.patch('freqtrade.exchange.Exchange.validate_pairs', MagicMock())
freqtradebot = FreqtradeBot(default_conf)
telegram = Telegram(freqtradebot)
@ -930,7 +878,7 @@ def test_forcesell_handle_invalid(default_conf, update, mocker) -> None:
def test_performance_handle(default_conf, update, ticker, fee,
limit_buy_order, limit_sell_order, mocker) -> None:
limit_buy_order, limit_sell_order, markets, mocker) -> None:
"""
Test _performance() method
"""
@ -940,13 +888,14 @@ def test_performance_handle(default_conf, update, ticker, fee,
mocker.patch.multiple(
'freqtrade.rpc.telegram.Telegram',
_init=MagicMock(),
send_msg=msg_mock
_send_msg=msg_mock
)
mocker.patch.multiple(
'freqtrade.freqtradebot.exchange',
'freqtrade.exchange.Exchange',
validate_pairs=MagicMock(),
get_ticker=ticker,
get_fee=fee
get_fee=fee,
get_markets=markets
)
mocker.patch('freqtrade.freqtradebot.RPCManager', MagicMock())
freqtradebot = FreqtradeBot(default_conf)
@ -981,9 +930,9 @@ def test_performance_handle_invalid(default_conf, update, mocker) -> None:
mocker.patch.multiple(
'freqtrade.rpc.telegram.Telegram',
_init=MagicMock(),
send_msg=msg_mock
_send_msg=msg_mock
)
mocker.patch('freqtrade.freqtradebot.exchange.validate_pairs', MagicMock())
mocker.patch('freqtrade.exchange.Exchange.validate_pairs', MagicMock())
freqtradebot = FreqtradeBot(default_conf)
telegram = Telegram(freqtradebot)
@ -994,7 +943,7 @@ def test_performance_handle_invalid(default_conf, update, mocker) -> None:
assert 'not running' in msg_mock.call_args_list[0][0][0]
def test_count_handle(default_conf, update, ticker, fee, mocker) -> None:
def test_count_handle(default_conf, update, ticker, fee, markets, mocker) -> None:
"""
Test _count() method
"""
@ -1004,15 +953,16 @@ def test_count_handle(default_conf, update, ticker, fee, mocker) -> None:
mocker.patch.multiple(
'freqtrade.rpc.telegram.Telegram',
_init=MagicMock(),
send_msg=msg_mock
_send_msg=msg_mock
)
mocker.patch.multiple(
'freqtrade.freqtradebot.exchange',
'freqtrade.exchange.Exchange',
validate_pairs=MagicMock(),
get_ticker=ticker,
buy=MagicMock(return_value={'id': 'mocked_order_id'})
buy=MagicMock(return_value={'id': 'mocked_order_id'}),
get_markets=markets
)
mocker.patch('freqtrade.optimize.backtesting.exchange.get_fee', fee)
mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
freqtradebot = FreqtradeBot(default_conf)
telegram = Telegram(freqtradebot)
@ -1042,14 +992,14 @@ def test_help_handle(default_conf, update, mocker) -> None:
Test _help() method
"""
patch_coinmarketcap(mocker)
mocker.patch('freqtrade.freqtradebot.exchange.init', MagicMock())
msg_mock = MagicMock()
mocker.patch.multiple(
'freqtrade.rpc.telegram.Telegram',
_init=MagicMock(),
send_msg=msg_mock
_send_msg=msg_mock
)
freqtradebot = FreqtradeBot(default_conf)
freqtradebot = get_patched_freqtradebot(mocker, default_conf)
telegram = Telegram(freqtradebot)
telegram._help(bot=MagicMock(), update=update)
@ -1062,14 +1012,13 @@ def test_version_handle(default_conf, update, mocker) -> None:
Test _version() method
"""
patch_coinmarketcap(mocker)
mocker.patch('freqtrade.freqtradebot.exchange.init', MagicMock())
msg_mock = MagicMock()
mocker.patch.multiple(
'freqtrade.rpc.telegram.Telegram',
_init=MagicMock(),
send_msg=msg_mock
_send_msg=msg_mock
)
freqtradebot = FreqtradeBot(default_conf)
freqtradebot = get_patched_freqtradebot(mocker, default_conf)
telegram = Telegram(freqtradebot)
telegram._version(bot=MagicMock(), update=update)
@ -1082,20 +1031,14 @@ def test_send_msg(default_conf, mocker) -> None:
Test send_msg() method
"""
patch_coinmarketcap(mocker)
mocker.patch('freqtrade.freqtradebot.exchange.init', MagicMock())
mocker.patch('freqtrade.rpc.telegram.Telegram._init', MagicMock())
conf = deepcopy(default_conf)
bot = MagicMock()
freqtradebot = FreqtradeBot(conf)
freqtradebot = get_patched_freqtradebot(mocker, conf)
telegram = Telegram(freqtradebot)
telegram._config['telegram']['enabled'] = False
telegram.send_msg('test', bot)
assert not bot.method_calls
bot.reset_mock()
telegram._config['telegram']['enabled'] = True
telegram.send_msg('test', bot)
telegram._send_msg('test', bot)
assert len(bot.method_calls) == 1
@ -1104,16 +1047,15 @@ def test_send_msg_network_error(default_conf, mocker, caplog) -> None:
Test send_msg() method
"""
patch_coinmarketcap(mocker)
mocker.patch('freqtrade.freqtradebot.exchange.init', MagicMock())
mocker.patch('freqtrade.rpc.telegram.Telegram._init', MagicMock())
conf = deepcopy(default_conf)
bot = MagicMock()
bot.send_message = MagicMock(side_effect=NetworkError('Oh snap'))
freqtradebot = FreqtradeBot(conf)
freqtradebot = get_patched_freqtradebot(mocker, conf)
telegram = Telegram(freqtradebot)
telegram._config['telegram']['enabled'] = True
telegram.send_msg('test', bot)
telegram._send_msg('test', bot)
# Bot should've tried to send it twice
assert len(bot.method_calls) == 2

41
freqtrade/tests/strategy/test_strategy.py
View File

@ -1,14 +1,39 @@
# pragma pylint: disable=missing-docstring, protected-access, C0103
import logging
import os
import pytest
from freqtrade.strategy import import_strategy
from freqtrade.strategy.default_strategy import DefaultStrategy
from freqtrade.strategy.interface import IStrategy
from freqtrade.strategy.resolver import StrategyResolver
def test_import_strategy(caplog):
caplog.set_level(logging.DEBUG)
strategy = DefaultStrategy()
strategy.some_method = lambda *args, **kwargs: 42
assert strategy.__module__ == 'freqtrade.strategy.default_strategy'
assert strategy.some_method() == 42
imported_strategy = import_strategy(strategy)
assert dir(strategy) == dir(imported_strategy)
assert imported_strategy.__module__ == 'freqtrade.strategy'
assert imported_strategy.some_method() == 42
assert (
'freqtrade.strategy',
logging.DEBUG,
'Imported strategy freqtrade.strategy.default_strategy.DefaultStrategy '
'as freqtrade.strategy.DefaultStrategy',
) in caplog.record_tuples
def test_search_strategy():
default_location = os.path.join(os.path.dirname(
os.path.realpath(__file__)), '..', '..', 'strategy'
@ -20,20 +45,22 @@ def test_search_strategy():
def test_load_strategy(result):
resolver = StrategyResolver()
resolver._load_strategy('TestStrategy')
resolver = StrategyResolver({'strategy': 'TestStrategy'})
assert hasattr(resolver.strategy, 'populate_indicators')
assert 'adx' in resolver.strategy.populate_indicators(result)
def test_load_strategy_custom_directory(result):
def test_load_strategy_invalid_directory(result, caplog):
resolver = StrategyResolver()
extra_dir = os.path.join('some', 'path')
with pytest.raises(
FileNotFoundError,
match=r".*No such file or directory: '{}'".format(extra_dir)):
resolver._load_strategy('TestStrategy', extra_dir)
assert (
'freqtrade.strategy.resolver',
logging.WARNING,
'Path "{}" does not exist'.format(extra_dir),
) in caplog.record_tuples
assert hasattr(resolver.strategy, 'populate_indicators')
assert 'adx' in resolver.strategy.populate_indicators(result)

11
freqtrade/tests/test_acl_pair.py
View File

@ -1,8 +1,9 @@
# pragma pylint: disable=missing-docstring,C0103,protected-access
import freqtrade.tests.conftest as tt # test tools
from unittest.mock import MagicMock
import freqtrade.tests.conftest as tt # test tools
# whitelist, blacklist, filtering, all of that will
# eventually become some rules to run on a generic ACL engine
# perhaps try to anticipate that by using some python package
@ -32,7 +33,7 @@ def test_refresh_market_pair_not_in_whitelist(mocker, markets):
freqtradebot = tt.get_patched_freqtradebot(mocker, conf)
mocker.patch('freqtrade.freqtradebot.exchange.get_markets', markets)
mocker.patch('freqtrade.exchange.Exchange.get_markets', markets)
refreshedwhitelist = freqtradebot._refresh_whitelist(
conf['exchange']['pair_whitelist'] + ['XXX/BTC']
)
@ -46,7 +47,7 @@ def test_refresh_whitelist(mocker, markets):
conf = whitelist_conf()
freqtradebot = tt.get_patched_freqtradebot(mocker, conf)
mocker.patch('freqtrade.freqtradebot.exchange.get_markets', markets)
mocker.patch('freqtrade.exchange.Exchange.get_markets', markets)
refreshedwhitelist = freqtradebot._refresh_whitelist(conf['exchange']['pair_whitelist'])
# List ordered by BaseVolume
@ -59,7 +60,7 @@ def test_refresh_whitelist_dynamic(mocker, markets, tickers):
conf = whitelist_conf()
freqtradebot = tt.get_patched_freqtradebot(mocker, conf)
mocker.patch.multiple(
'freqtrade.freqtradebot.exchange',
'freqtrade.exchange.Exchange',
get_markets=markets,
get_tickers=tickers,
exchange_has=MagicMock(return_value=True)
@ -78,7 +79,7 @@ def test_refresh_whitelist_dynamic(mocker, markets, tickers):
def test_refresh_whitelist_dynamic_empty(mocker, markets_empty):
conf = whitelist_conf()
freqtradebot = tt.get_patched_freqtradebot(mocker, conf)
mocker.patch('freqtrade.freqtradebot.exchange.get_markets', markets_empty)
mocker.patch('freqtrade.exchange.Exchange.get_markets', markets_empty)
# argument: use the whitelist dynamically by exchange-volume
whitelist = []

51
freqtrade/tests/test_analyze.py
View File

@ -12,9 +12,9 @@ import arrow
from pandas import DataFrame
from freqtrade.analyze import Analyze, SignalType
from freqtrade.optimize.__init__ import load_tickerdata_file
from freqtrade.arguments import TimeRange
from freqtrade.tests.conftest import log_has
from freqtrade.optimize.__init__ import load_tickerdata_file
from freqtrade.tests.conftest import get_patched_exchange, log_has
# Avoid to reinit the same object again and again
_ANALYZE = Analyze({'strategy': 'DefaultStrategy'})
@ -42,6 +42,7 @@ def test_analyze_object() -> None:
assert hasattr(Analyze, 'get_signal')
assert hasattr(Analyze, 'should_sell')
assert hasattr(Analyze, 'min_roi_reached')
assert hasattr(Analyze, 'stop_loss_reached')
def test_dataframe_correct_length(result):
@ -68,16 +69,16 @@ def test_populates_sell_trend(result):
assert 'sell' in dataframe.columns
def test_returns_latest_buy_signal(mocker):
mocker.patch('freqtrade.analyze.get_ticker_history', return_value=MagicMock())
def test_returns_latest_buy_signal(mocker, default_conf):
mocker.patch('freqtrade.exchange.Exchange.get_ticker_history', return_value=MagicMock())
exchange = get_patched_exchange(mocker, default_conf)
mocker.patch.multiple(
'freqtrade.analyze.Analyze',
analyze_ticker=MagicMock(
return_value=DataFrame([{'buy': 1, 'sell': 0, 'date': arrow.utcnow()}])
)
)
assert _ANALYZE.get_signal('ETH/BTC', '5m') == (True, False)
assert _ANALYZE.get_signal(exchange, 'ETH/BTC', '5m') == (True, False)
mocker.patch.multiple(
'freqtrade.analyze.Analyze',
@ -85,11 +86,12 @@ def test_returns_latest_buy_signal(mocker):
return_value=DataFrame([{'buy': 0, 'sell': 1, 'date': arrow.utcnow()}])
)
)
assert _ANALYZE.get_signal('ETH/BTC', '5m') == (False, True)
assert _ANALYZE.get_signal(exchange, 'ETH/BTC', '5m') == (False, True)
def test_returns_latest_sell_signal(mocker):
mocker.patch('freqtrade.analyze.get_ticker_history', return_value=MagicMock())
def test_returns_latest_sell_signal(mocker, default_conf):
mocker.patch('freqtrade.exchange.Exchange.get_ticker_history', return_value=MagicMock())
exchange = get_patched_exchange(mocker, default_conf)
mocker.patch.multiple(
'freqtrade.analyze.Analyze',
analyze_ticker=MagicMock(
@ -97,7 +99,7 @@ def test_returns_latest_sell_signal(mocker):
)
)
assert _ANALYZE.get_signal('ETH/BTC', '5m') == (False, True)
assert _ANALYZE.get_signal(exchange, 'ETH/BTC', '5m') == (False, True)
mocker.patch.multiple(
'freqtrade.analyze.Analyze',
@ -105,45 +107,49 @@ def test_returns_latest_sell_signal(mocker):
return_value=DataFrame([{'sell': 0, 'buy': 1, 'date': arrow.utcnow()}])
)
)
assert _ANALYZE.get_signal('ETH/BTC', '5m') == (True, False)
assert _ANALYZE.get_signal(exchange, 'ETH/BTC', '5m') == (True, False)
def test_get_signal_empty(default_conf, mocker, caplog):
caplog.set_level(logging.INFO)
mocker.patch('freqtrade.analyze.get_ticker_history', return_value=None)
assert (False, False) == _ANALYZE.get_signal('foo', default_conf['ticker_interval'])
mocker.patch('freqtrade.exchange.Exchange.get_ticker_history', return_value=None)
exchange = get_patched_exchange(mocker, default_conf)
assert (False, False) == _ANALYZE.get_signal(exchange, 'foo', default_conf['ticker_interval'])
assert log_has('Empty ticker history for pair foo', caplog.record_tuples)
def test_get_signal_exception_valueerror(default_conf, mocker, caplog):
caplog.set_level(logging.INFO)
mocker.patch('freqtrade.analyze.get_ticker_history', return_value=1)
mocker.patch('freqtrade.exchange.Exchange.get_ticker_history', return_value=1)
exchange = get_patched_exchange(mocker, default_conf)
mocker.patch.multiple(
'freqtrade.analyze.Analyze',
analyze_ticker=MagicMock(
side_effect=ValueError('xyz')
)
)
assert (False, False) == _ANALYZE.get_signal('foo', default_conf['ticker_interval'])
assert (False, False) == _ANALYZE.get_signal(exchange, 'foo', default_conf['ticker_interval'])
assert log_has('Unable to analyze ticker for pair foo: xyz', caplog.record_tuples)
def test_get_signal_empty_dataframe(default_conf, mocker, caplog):
caplog.set_level(logging.INFO)
mocker.patch('freqtrade.analyze.get_ticker_history', return_value=1)
mocker.patch('freqtrade.exchange.Exchange.get_ticker_history', return_value=1)
exchange = get_patched_exchange(mocker, default_conf)
mocker.patch.multiple(
'freqtrade.analyze.Analyze',
analyze_ticker=MagicMock(
return_value=DataFrame([])
)
)
assert (False, False) == _ANALYZE.get_signal('xyz', default_conf['ticker_interval'])
assert (False, False) == _ANALYZE.get_signal(exchange, 'xyz', default_conf['ticker_interval'])
assert log_has('Empty dataframe for pair xyz', caplog.record_tuples)
def test_get_signal_old_dataframe(default_conf, mocker, caplog):
caplog.set_level(logging.INFO)
mocker.patch('freqtrade.analyze.get_ticker_history', return_value=1)
mocker.patch('freqtrade.exchange.Exchange.get_ticker_history', return_value=1)
exchange = get_patched_exchange(mocker, default_conf)
# FIX: The get_signal function has hardcoded 10, which we must inturn hardcode
oldtime = arrow.utcnow() - datetime.timedelta(minutes=11)
ticks = DataFrame([{'buy': 1, 'date': oldtime}])
@ -153,15 +159,16 @@ def test_get_signal_old_dataframe(default_conf, mocker, caplog):
return_value=DataFrame(ticks)
)
)
assert (False, False) == _ANALYZE.get_signal('xyz', default_conf['ticker_interval'])
assert (False, False) == _ANALYZE.get_signal(exchange, 'xyz', default_conf['ticker_interval'])
assert log_has(
'Outdated history for pair xyz. Last tick is 11 minutes old',
caplog.record_tuples
)
def test_get_signal_handles_exceptions(mocker):
mocker.patch('freqtrade.analyze.get_ticker_history', return_value=MagicMock())
def test_get_signal_handles_exceptions(mocker, default_conf):
mocker.patch('freqtrade.exchange.Exchange.get_ticker_history', return_value=MagicMock())
exchange = get_patched_exchange(mocker, default_conf)
mocker.patch.multiple(
'freqtrade.analyze.Analyze',
analyze_ticker=MagicMock(
@ -169,7 +176,7 @@ def test_get_signal_handles_exceptions(mocker):
)
)
assert _ANALYZE.get_signal('ETH/BTC', '5m') == (False, False)
assert _ANALYZE.get_signal(exchange, 'ETH/BTC', '5m') == (False, False)
def test_parse_ticker_dataframe(ticker_history):

59
freqtrade/tests/test_configuration.py
View File

@ -4,17 +4,18 @@
Unit test file for configuration.py
"""
import json
from argparse import Namespace
from copy import deepcopy
from unittest.mock import MagicMock
from argparse import Namespace
import pytest
from jsonschema import ValidationError
from freqtrade import OperationalException
from freqtrade.arguments import Arguments
from freqtrade.configuration import Configuration
from freqtrade.constants import DEFAULT_DB_DRYRUN_URL, DEFAULT_DB_PROD_URL
from freqtrade.tests.conftest import log_has
from freqtrade import OperationalException
def test_configuration_object() -> None:
@ -54,6 +55,18 @@ def test_load_config_missing_attributes(default_conf) -> None:
configuration._validate_config(conf)
def test_load_config_incorrect_stake_amount(default_conf) -> None:
"""
Test the configuration validator with a missing attribute
"""
conf = deepcopy(default_conf)
conf['stake_amount'] = 'fake'
with pytest.raises(ValidationError, match=r'.*\'fake\' does not match \'unlimited\'.*'):
configuration = Configuration(Namespace())
configuration._validate_config(conf)
def test_load_config_file(default_conf, mocker, caplog) -> None:
"""
Test Configuration._load_config_file() method
@ -140,6 +153,43 @@ def test_load_config_with_params(default_conf, mocker) -> None:
assert validated_conf.get('strategy_path') == '/some/path'
assert validated_conf.get('db_url') == 'sqlite:///someurl'
conf = default_conf.copy()
conf["dry_run"] = False
del conf["db_url"]
mocker.patch('freqtrade.configuration.open', mocker.mock_open(
read_data=json.dumps(conf)
))
arglist = [
'--dynamic-whitelist', '10',
'--strategy', 'TestStrategy',
'--strategy-path', '/some/path'
]
args = Arguments(arglist, '').get_parsed_arg()
configuration = Configuration(args)
validated_conf = configuration.load_config()
assert validated_conf.get('db_url') == DEFAULT_DB_PROD_URL
# Test dry=run with ProdURL
conf = default_conf.copy()
conf["dry_run"] = True
conf["db_url"] = DEFAULT_DB_PROD_URL
mocker.patch('freqtrade.configuration.open', mocker.mock_open(
read_data=json.dumps(conf)
))
arglist = [
'--dynamic-whitelist', '10',
'--strategy', 'TestStrategy',
'--strategy-path', '/some/path'
]
args = Arguments(arglist, '').get_parsed_arg()
configuration = Configuration(args)
validated_conf = configuration.load_config()
assert validated_conf.get('db_url') == DEFAULT_DB_DRYRUN_URL
def test_load_custom_strategy(default_conf, mocker) -> None:
"""
@ -310,7 +360,6 @@ def test_hyperopt_with_arguments(mocker, default_conf, caplog) -> None:
arglist = [
'hyperopt',
'--epochs', '10',
'--use-mongodb',
'--spaces', 'all',
]
@ -324,10 +373,6 @@ def test_hyperopt_with_arguments(mocker, default_conf, caplog) -> None:
assert log_has('Parameter --epochs detected ...', caplog.record_tuples)
assert log_has('Will run Hyperopt with for 10 epochs ...', caplog.record_tuples)
assert 'mongodb' in config
assert config['mongodb'] is True
assert log_has('Parameter --use-mongodb detected ...', caplog.record_tuples)
assert 'spaces' in config
assert config['spaces'] == ['all']
assert log_has('Parameter -s/--spaces detected: [\'all\']', caplog.record_tuples)

27
freqtrade/tests/test_fiat_convert.py
View File

@ -5,7 +5,6 @@ import time
from unittest.mock import MagicMock
import pytest
from requests.exceptions import RequestException
from freqtrade.fiat_convert import CryptoFiat, CryptoToFiatConverter
@ -40,7 +39,8 @@ def test_pair_convertion_object():
assert pair_convertion.price == 30000.123
def test_fiat_convert_is_supported():
def test_fiat_convert_is_supported(mocker):
patch_coinmarketcap(mocker)
fiat_convert = CryptoToFiatConverter()
assert fiat_convert._is_supported_fiat(fiat='USD') is True
assert fiat_convert._is_supported_fiat(fiat='usd') is True
@ -48,7 +48,9 @@ def test_fiat_convert_is_supported():
assert fiat_convert._is_supported_fiat(fiat='ABC') is False
def test_fiat_convert_add_pair():
def test_fiat_convert_add_pair(mocker):
patch_coinmarketcap(mocker)
fiat_convert = CryptoToFiatConverter()
pair_len = len(fiat_convert._pairs)
@ -70,11 +72,8 @@ def test_fiat_convert_add_pair():
def test_fiat_convert_find_price(mocker):
api_mock = MagicMock(return_value={
'price_usd': 12345.0,
'price_eur': 13000.2
})
mocker.patch('freqtrade.fiat_convert.Market.ticker', api_mock)
patch_coinmarketcap(mocker)
fiat_convert = CryptoToFiatConverter()
with pytest.raises(ValueError, match=r'The fiat ABC is not supported.'):
@ -92,17 +91,15 @@ def test_fiat_convert_find_price(mocker):
def test_fiat_convert_unsupported_crypto(mocker, caplog):
mocker.patch('freqtrade.fiat_convert.CryptoToFiatConverter._cryptomap', return_value=[])
patch_coinmarketcap(mocker)
fiat_convert = CryptoToFiatConverter()
assert fiat_convert._find_price(crypto_symbol='CRYPTO_123', fiat_symbol='EUR') == 0.0
assert log_has('unsupported crypto-symbol CRYPTO_123 - returning 0.0', caplog.record_tuples)
def test_fiat_convert_get_price(mocker):
api_mock = MagicMock(return_value={
'price_usd': 28000.0,
'price_eur': 15000.0
})
mocker.patch('freqtrade.fiat_convert.Market.ticker', api_mock)
patch_coinmarketcap(mocker)
mocker.patch('freqtrade.fiat_convert.CryptoToFiatConverter._find_price', return_value=28000.0)
fiat_convert = CryptoToFiatConverter()
@ -172,8 +169,9 @@ def test_fiat_init_network_exception(mocker):
assert length_cryptomap == 0
def test_fiat_convert_without_network():
def test_fiat_convert_without_network(mocker):
# Because CryptoToFiatConverter is a Singleton we reset the value of _coinmarketcap
patch_coinmarketcap(mocker)
fiat_convert = CryptoToFiatConverter()
@ -186,6 +184,7 @@ def test_fiat_convert_without_network():
def test_convert_amount(mocker):
patch_coinmarketcap(mocker)
mocker.patch('freqtrade.fiat_convert.CryptoToFiatConverter.get_price', return_value=12345.0)
fiat_convert = CryptoToFiatConverter()

699
freqtrade/tests/test_freqtradebot.py
View File

File diff suppressed because it is too large Load Diff

2
freqtrade/tests/test_indicator_helpers.py
View File

@ -1,6 +1,6 @@
import pandas as pd
from freqtrade.indicator_helpers import went_up, went_down
from freqtrade.indicator_helpers import went_down, went_up
def test_went_up():

9
freqtrade/tests/test_main.py
View File

@ -11,9 +11,9 @@ import pytest
from freqtrade import OperationalException
from freqtrade.arguments import Arguments
from freqtrade.freqtradebot import FreqtradeBot
from freqtrade.main import main, set_loggers, reconfigure
from freqtrade.main import main, reconfigure, set_loggers
from freqtrade.state import State
from freqtrade.tests.conftest import log_has
from freqtrade.tests.conftest import log_has, patch_exchange
def test_parse_args_backtesting(mocker) -> None:
@ -70,6 +70,7 @@ def test_main_fatal_exception(mocker, default_conf, caplog) -> None:
Test main() function
In this test we are skipping the while True loop by throwing an exception.
"""
patch_exchange(mocker)
mocker.patch.multiple(
'freqtrade.freqtradebot.FreqtradeBot',
_init_modules=MagicMock(),
@ -97,6 +98,7 @@ def test_main_keyboard_interrupt(mocker, default_conf, caplog) -> None:
Test main() function
In this test we are skipping the while True loop by throwing an exception.
"""
patch_exchange(mocker)
mocker.patch.multiple(
'freqtrade.freqtradebot.FreqtradeBot',
_init_modules=MagicMock(),
@ -124,6 +126,7 @@ def test_main_operational_exception(mocker, default_conf, caplog) -> None:
Test main() function
In this test we are skipping the while True loop by throwing an exception.
"""
patch_exchange(mocker)
mocker.patch.multiple(
'freqtrade.freqtradebot.FreqtradeBot',
_init_modules=MagicMock(),
@ -151,6 +154,7 @@ def test_main_reload_conf(mocker, default_conf, caplog) -> None:
Test main() function
In this test we are skipping the while True loop by throwing an exception.
"""
patch_exchange(mocker)
mocker.patch.multiple(
'freqtrade.freqtradebot.FreqtradeBot',
_init_modules=MagicMock(),
@ -178,6 +182,7 @@ def test_main_reload_conf(mocker, default_conf, caplog) -> None:
def test_reconfigure(mocker, default_conf) -> None:
""" Test recreate() function """
patch_exchange(mocker)
mocker.patch.multiple(
'freqtrade.freqtradebot.FreqtradeBot',
_init_modules=MagicMock(),

4
freqtrade/tests/test_misc.py
View File

@ -8,8 +8,8 @@ import datetime
from unittest.mock import MagicMock
from freqtrade.analyze import Analyze
from freqtrade.misc import (shorten_date, datesarray_to_datetimearray,
common_datearray, file_dump_json, format_ms_time)
from freqtrade.misc import (common_datearray, datesarray_to_datetimearray,
file_dump_json, format_ms_time, shorten_date)
from freqtrade.optimize.__init__ import load_tickerdata_file

77
freqtrade/tests/test_persistence.py
View File

@ -5,8 +5,9 @@ from unittest.mock import MagicMock
import pytest
from sqlalchemy import create_engine
from freqtrade import constants, OperationalException
from freqtrade.persistence import Trade, init, clean_dry_run_db
from freqtrade import OperationalException, constants
from freqtrade.persistence import Trade, clean_dry_run_db, init
from freqtrade.tests.conftest import log_has
@pytest.fixture(scope='function')
@ -14,9 +15,7 @@ def init_persistence(default_conf):
init(default_conf)
def test_init_create_session(default_conf, mocker):
mocker.patch.dict('freqtrade.persistence._CONF', default_conf)
def test_init_create_session(default_conf):
# Check if init create a session
init(default_conf)
assert hasattr(Trade, 'session')
@ -29,20 +28,17 @@ def test_init_custom_db_url(default_conf, mocker):
# Update path to a value other than default, but still in-memory
conf.update({'db_url': 'sqlite:///tmp/freqtrade2_test.sqlite'})
create_engine_mock = mocker.patch('freqtrade.persistence.create_engine', MagicMock())
mocker.patch.dict('freqtrade.persistence._CONF', conf)
init(conf)
assert create_engine_mock.call_count == 1
assert create_engine_mock.mock_calls[0][1][0] == 'sqlite:///tmp/freqtrade2_test.sqlite'
def test_init_invalid_db_url(default_conf, mocker):
def test_init_invalid_db_url(default_conf):
conf = deepcopy(default_conf)
# Update path to a value other than default, but still in-memory
conf.update({'db_url': 'unknown:///some.url'})
mocker.patch.dict('freqtrade.persistence._CONF', conf)
with pytest.raises(OperationalException, match=r'.*no valid database URL*'):
init(conf)
@ -53,7 +49,6 @@ def test_init_prod_db(default_conf, mocker):
conf.update({'db_url': constants.DEFAULT_DB_PROD_URL})
create_engine_mock = mocker.patch('freqtrade.persistence.create_engine', MagicMock())
mocker.patch.dict('freqtrade.persistence._CONF', conf)
init(conf)
assert create_engine_mock.call_count == 1
@ -66,7 +61,6 @@ def test_init_dryrun_db(default_conf, mocker):
conf.update({'db_url': constants.DEFAULT_DB_DRYRUN_URL})
create_engine_mock = mocker.patch('freqtrade.persistence.create_engine', MagicMock())
mocker.patch.dict('freqtrade.persistence._CONF', conf)
init(conf)
assert create_engine_mock.call_count == 1
@ -407,9 +401,12 @@ def test_migrate_old(mocker, default_conf, fee):
assert trade.stake_amount == default_conf.get("stake_amount")
assert trade.pair == "ETC/BTC"
assert trade.exchange == "bittrex"
assert trade.max_rate == 0.0
assert trade.stop_loss == 0.0
assert trade.initial_stop_loss == 0.0
def test_migrate_new(mocker, default_conf, fee):
def test_migrate_new(mocker, default_conf, fee, caplog):
"""
Test Database migration (starting with new pairformat)
"""
@ -446,6 +443,11 @@ def test_migrate_new(mocker, default_conf, fee):
# Create table using the old format
engine.execute(create_table_old)
engine.execute(insert_table_old)
# fake previous backup
engine.execute("create table trades_bak as select * from trades")
engine.execute("create table trades_bak1 as select * from trades")
# Run init to test migration
init(default_conf)
@ -460,3 +462,54 @@ def test_migrate_new(mocker, default_conf, fee):
assert trade.stake_amount == default_conf.get("stake_amount")
assert trade.pair == "ETC/BTC"
assert trade.exchange == "binance"
assert trade.max_rate == 0.0
assert trade.stop_loss == 0.0
assert trade.initial_stop_loss == 0.0
assert log_has("trying trades_bak1", caplog.record_tuples)
assert log_has("trying trades_bak2", caplog.record_tuples)
def test_adjust_stop_loss(limit_buy_order, limit_sell_order, fee):
trade = Trade(
pair='ETH/BTC',
stake_amount=0.001,
fee_open=fee.return_value,
fee_close=fee.return_value,
exchange='bittrex',
open_rate=1,
)
trade.adjust_stop_loss(trade.open_rate, 0.05, True)
assert trade.stop_loss == 0.95
assert trade.max_rate == 1
assert trade.initial_stop_loss == 0.95
# Get percent of profit with a lowre rate
trade.adjust_stop_loss(0.96, 0.05)
assert trade.stop_loss == 0.95
assert trade.max_rate == 1
assert trade.initial_stop_loss == 0.95
# Get percent of profit with a custom rate (Higher than open rate)
trade.adjust_stop_loss(1.3, -0.1)
assert round(trade.stop_loss, 8) == 1.17
assert trade.max_rate == 1.3
assert trade.initial_stop_loss == 0.95
# current rate lower again ... should not change
trade.adjust_stop_loss(1.2, 0.1)
assert round(trade.stop_loss, 8) == 1.17
assert trade.max_rate == 1.3
assert trade.initial_stop_loss == 0.95
# current rate higher... should raise stoploss
trade.adjust_stop_loss(1.4, 0.1)
assert round(trade.stop_loss, 8) == 1.26
assert trade.max_rate == 1.4
assert trade.initial_stop_loss == 0.95
# Initial is true but stop_loss set - so doesn't do anything
trade.adjust_stop_loss(1.7, 0.1, True)
assert round(trade.stop_loss, 8) == 1.26
assert trade.max_rate == 1.4
assert trade.initial_stop_loss == 0.95

25
freqtrade/vendor/qtpylib/indicators.py vendored
View File

@ -110,10 +110,13 @@ def heikinashi(bars):
bars = bars.copy()
bars['ha_close'] = (bars['open'] + bars['high'] +
bars['low'] + bars['close']) / 4
bars['ha_open'] = (bars['open'].shift(1) + bars['close'].shift(1)) / 2
bars.loc[:1, 'ha_open'] = bars['open'].values[0]
for x in range(2):
bars.loc[1:, 'ha_open'] = (
(bars['ha_open'].shift(1) + bars['ha_close'].shift(1)) / 2)[1:]
bars['ha_high'] = bars.loc[:, ['high', 'ha_open', 'ha_close']].max(axis=1)
bars['ha_low'] = bars.loc[:, ['low', 'ha_open', 'ha_close']].min(axis=1)
@ -248,58 +251,46 @@ def crossed_below(series1, series2):
def rolling_std(series, window=200, min_periods=None):
min_periods = window if min_periods is None else min_periods
try:
if min_periods == window:
if min_periods == window and len(series) > window:
return numpy_rolling_std(series, window, True)
else:
try:
return series.rolling(window=window, min_periods=min_periods).std()
except BaseException:
return pd.Series(series).rolling(window=window, min_periods=min_periods).std()
except BaseException:
return pd.rolling_std(series, window=window, min_periods=min_periods)
# ---------------------------------------------
def rolling_mean(series, window=200, min_periods=None):
min_periods = window if min_periods is None else min_periods
try:
if min_periods == window:
if min_periods == window and len(series) > window:
return numpy_rolling_mean(series, window, True)
else:
try:
return series.rolling(window=window, min_periods=min_periods).mean()
except BaseException:
return pd.Series(series).rolling(window=window, min_periods=min_periods).mean()
except BaseException:
return pd.rolling_mean(series, window=window, min_periods=min_periods)
# ---------------------------------------------
def rolling_min(series, window=14, min_periods=None):
min_periods = window if min_periods is None else min_periods
try:
try:
return series.rolling(window=window, min_periods=min_periods).min()
except BaseException:
return pd.Series(series).rolling(window=window, min_periods=min_periods).min()
except BaseException:
return pd.rolling_min(series, window=window, min_periods=min_periods)
# ---------------------------------------------
def rolling_max(series, window=14, min_periods=None):
min_periods = window if min_periods is None else min_periods
try:
try:
return series.rolling(window=window, min_periods=min_periods).min()
except BaseException:
return pd.Series(series).rolling(window=window, min_periods=min_periods).min()
except BaseException:
return pd.rolling_min(series, window=window, min_periods=min_periods)
# ---------------------------------------------
@ -566,9 +557,9 @@ def stoch(df, window=14, d=3, k=3, fast=False):
return pd.DataFrame(index=df.index, data=data)
# ---------------------------------------------
def zscore(bars, window=20, stds=1, col='close'):
""" get zscore of price """
std = numpy_rolling_std(bars[col], window)

20
requirements.txt
View File

@ -1,25 +1,25 @@
ccxt==1.14.177
SQLAlchemy==1.2.8
ccxt==1.15.13
SQLAlchemy==1.2.9
python-telegram-bot==10.1.0
arrow==0.12.1
cachetools==2.1.0
requests==2.18.4
requests==2.19.1
urllib3==1.22
wrapt==1.10.11
pandas==0.23.0
pandas==0.23.1
scikit-learn==0.19.1
scipy==1.1.0
jsonschema==2.6.0
numpy==1.14.4
numpy==1.14.5
TA-Lib==0.4.17
pytest==3.6.1
pytest==3.6.3
pytest-mock==1.10.0
pytest-cov==2.5.1
hyperopt==0.1
# do not upgrade networkx before this is fixed https://github.com/hyperopt/hyperopt/issues/325
networkx==1.11 # pyup: ignore
tabulate==0.8.2
coinmarketcap==5.0.3
# Required for hyperopt
scikit-optimize==0.5.2
# Required for plotting data
#plotly==2.3.0
#plotly==2.7.0

7
scripts/convert_backtestdata.py
View File

@ -143,15 +143,14 @@ def convert_main(args: Namespace) -> None:
interval = str_interval
break
# change order on pairs if old ticker interval found
filename_new = path.join(path.dirname(filename),
"{}_{}-{}.json".format(currencies[1],
currencies[0], interval))
f"{currencies[1]}_{currencies[0]}-{interval}.json")
elif ret_string:
interval = ret_string.group(0)
filename_new = path.join(path.dirname(filename),
"{}_{}-{}.json".format(currencies[0],
currencies[1], interval))
f"{currencies[0]}_{currencies[1]}-{interval}.json")
else:
logger.warning("file %s could not be converted, interval not found", filename)

64
scripts/download_backtest_data.py
View File

@ -3,10 +3,14 @@
"""This script generate json data from bittrex"""
import json
import sys
import os
from pathlib import Path
import arrow
from freqtrade import (exchange, arguments, misc)
from freqtrade import arguments
from freqtrade.arguments import TimeRange
from freqtrade.exchange import Exchange
from freqtrade.optimize import download_backtesting_testdata
DEFAULT_DL_PATH = 'user_data/data'
@ -16,58 +20,62 @@ args = arguments.parse_args()
timeframes = args.timeframes
dl_path = os.path.join(DEFAULT_DL_PATH, args.exchange)
dl_path = Path(DEFAULT_DL_PATH).joinpath(args.exchange)
if args.export:
dl_path = args.export
dl_path = Path(args.export)
if not os.path.isdir(dl_path):
if not dl_path.is_dir():
sys.exit(f'Directory {dl_path} does not exist.')
pairs_file = args.pairs_file if args.pairs_file else os.path.join(dl_path, 'pairs.json')
if not os.path.isfile(pairs_file):
pairs_file = Path(args.pairs_file) if args.pairs_file else dl_path.joinpath('pairs.json')
if not pairs_file.exists():
sys.exit(f'No pairs file found with path {pairs_file}.')
with open(pairs_file) as file:
with pairs_file.open() as file:
PAIRS = list(set(json.load(file)))
PAIRS.sort()
since_time = None
timerange = TimeRange()
if args.days:
since_time = arrow.utcnow().shift(days=-args.days).timestamp * 1000
time_since = arrow.utcnow().shift(days=-args.days).strftime("%Y%m%d")
timerange = arguments.parse_timerange(f'{time_since}-')
print(f'About to download pairs: {PAIRS} to {dl_path}')
# Init exchange
exchange._API = exchange.init_ccxt({'key': '',
exchange = Exchange({'key': '',
'secret': '',
'name': args.exchange})
'stake_currency': '',
'dry_run': True,
'exchange': {
'name': args.exchange,
'pair_whitelist': []
}
})
pairs_not_available = []
# Make sure API markets is initialized
exchange._API.load_markets()
for pair in PAIRS:
if pair not in exchange._API.markets:
if pair not in exchange._api.markets:
pairs_not_available.append(pair)
print(f"skipping pair {pair}")
continue
for tick_interval in timeframes:
print(f'downloading pair {pair}, interval {tick_interval}')
data = exchange.get_ticker_history(pair, tick_interval, since_ms=since_time)
if not data:
print('\tNo data was downloaded')
break
print('\tData was downloaded for period %s - %s' % (
arrow.get(data[0][0] / 1000).format(),
arrow.get(data[-1][0] / 1000).format()))
# save data
pair_print = pair.replace('/', '_')
filename = f'{pair_print}-{tick_interval}.json'
misc.file_dump_json(os.path.join(dl_path, filename), data)
dl_file = dl_path.joinpath(filename)
if args.erase and dl_file.exists():
print(f'Deleting existing data for pair {pair}, interval {tick_interval}')
dl_file.unlink()
print(f'downloading pair {pair}, interval {tick_interval}')
download_backtesting_testdata(str(dl_path), exchange=exchange,
pair=pair,
tick_interval=tick_interval,
timerange=timerange)
if pairs_not_available:

90
scripts/plot_dataframe.py
View File

@ -25,20 +25,22 @@ Example of usage:
--indicators2 fastk,fastd
"""
import logging
import os
import sys
import json
from pathlib import Path
from argparse import Namespace
from typing import Dict, List, Any
import pandas as pd
import plotly.graph_objs as go
from plotly import tools
from plotly.offline import plot
import freqtrade.optimize as optimize
from freqtrade import exchange
from freqtrade import persistence
from freqtrade.analyze import Analyze
from freqtrade.arguments import Arguments
from freqtrade.arguments import Arguments, TimeRange
from freqtrade.exchange import Exchange
from freqtrade.optimize.backtesting import setup_configuration
from freqtrade.persistence import Trade
@ -46,6 +48,45 @@ logger = logging.getLogger(__name__)
_CONF: Dict[str, Any] = {}
def load_trades(args: Namespace, pair: str, timerange: TimeRange) -> pd.DataFrame:
trades: pd.DataFrame = pd.DataFrame()
if args.db_url:
persistence.init(_CONF)
columns = ["pair", "profit", "opents", "closets", "open_rate", "close_rate", "duration"]
trades = pd.DataFrame([(t.pair, t.calc_profit(),
t.open_date, t.close_date,
t.open_rate, t.close_rate,
t.close_date.timestamp() - t.open_date.timestamp())
for t in Trade.query.filter(Trade.pair.is_(pair)).all()],
columns=columns)
if args.exportfilename:
file = Path(args.exportfilename)
# must align with columns in backtest.py
columns = ["pair", "profit", "opents", "closets", "index", "duration",
"open_rate", "close_rate", "open_at_end"]
with file.open() as f:
data = json.load(f)
trades = pd.DataFrame(data, columns=columns)
trades = trades.loc[trades["pair"] == pair]
if timerange:
if timerange.starttype == 'date':
trades = trades.loc[trades["opents"] >= timerange.startts]
if timerange.stoptype == 'date':
trades = trades.loc[trades["opents"] <= timerange.stopts]
trades['opents'] = pd.to_datetime(trades['opents'],
unit='s',
utc=True,
infer_datetime_format=True)
trades['closets'] = pd.to_datetime(trades['closets'],
unit='s',
utc=True,
infer_datetime_format=True)
return trades
def plot_analyzed_dataframe(args: Namespace) -> None:
"""
Calls analyze() and plots the returned dataframe
@ -73,7 +114,7 @@ def plot_analyzed_dataframe(args: Namespace) -> None:
# Load the strategy
try:
analyze = Analyze(_CONF)
exchange.init(_CONF)
exchange = Exchange(_CONF)
except AttributeError:
logger.critical(
'Impossible to load the strategy. Please check the file "user_data/strategies/%s.py"',
@ -91,7 +132,7 @@ def plot_analyzed_dataframe(args: Namespace) -> None:
tickers[pair] = exchange.get_ticker_history(pair, tick_interval)
else:
tickers = optimize.load_data(
datadir=args.datadir,
datadir=_CONF.get("datadir"),
pairs=[pair],
ticker_interval=tick_interval,
refresh_pairs=_CONF.get('refresh_pairs', False),
@ -102,31 +143,32 @@ def plot_analyzed_dataframe(args: Namespace) -> None:
if tickers == {}:
exit()
if args.db_url and args.exportfilename:
logger.critical("Can only specify --db-url or --export-filename")
# Get trades already made from the DB
trades: List[Trade] = []
if args.db_url:
persistence.init(_CONF)
trades = Trade.query.filter(Trade.pair.is_(pair)).all()
trades = load_trades(args, pair, timerange)
dataframes = analyze.tickerdata_to_dataframe(tickers)
dataframe = dataframes[pair]
dataframe = analyze.populate_buy_trend(dataframe)
dataframe = analyze.populate_sell_trend(dataframe)
if len(dataframe.index) > 750:
logger.warning('Ticker contained more than 750 candles, clipping.')
if len(dataframe.index) > args.plot_limit:
logger.warning('Ticker contained more than %s candles as defined '
'with --plot-limit, clipping.', args.plot_limit)
dataframe = dataframe.tail(args.plot_limit)
trades = trades.loc[trades['opents'] >= dataframe.iloc[0]['date']]
fig = generate_graph(
pair=pair,
trades=trades,
data=dataframe.tail(750),
data=dataframe,
args=args
)
plot(fig, filename=os.path.join('user_data', 'freqtrade-plot.html'))
plot(fig, filename=str(Path('user_data').joinpath('freqtrade-plot.html')))
def generate_graph(pair, trades, data, args) -> tools.make_subplots:
def generate_graph(pair, trades: pd.DataFrame, data: pd.DataFrame, args) -> tools.make_subplots:
"""
Generate the graph from the data generated by Backtesting or from DB
:param pair: Pair to Display on the graph
@ -187,8 +229,8 @@ def generate_graph(pair, trades, data, args) -> tools.make_subplots:
)
trade_buys = go.Scattergl(
x=[t.open_date.isoformat() for t in trades],
y=[t.open_rate for t in trades],
x=trades["opents"],
y=trades["open_rate"],
mode='markers',
name='trade_buy',
marker=dict(
@ -199,8 +241,8 @@ def generate_graph(pair, trades, data, args) -> tools.make_subplots:
)
)
trade_sells = go.Scattergl(
x=[t.close_date.isoformat() for t in trades],
y=[t.close_rate for t in trades],
x=trades["closets"],
y=trades["close_rate"],
mode='markers',
name='trade_sell',
marker=dict(
@ -299,11 +341,17 @@ def plot_parse_args(args: List[str]) -> Namespace:
default='macd',
dest='indicators2',
)
arguments.parser.add_argument(
'--plot-limit',
help='Specify tick limit for plotting - too high values cause huge files - '
'Default: %(default)s',
dest='plot_limit',
default=750,
type=int,
)
arguments.common_args_parser()
arguments.optimizer_shared_options(arguments.parser)
arguments.backtesting_options(arguments.parser)
return arguments.parse_args()

2
scripts/plot_profit.py
View File

@ -121,7 +121,7 @@ def plot_profit(args: Namespace) -> None:
logger.info('Filter, keep pairs %s' % pairs)
tickers = optimize.load_data(
datadir=args.datadir,
datadir=config.get('datadir'),
pairs=pairs,
ticker_interval=tick_interval,
refresh_pairs=False,

27
scripts/start-hyperopt-worker.py
View File

@ -1,27 +0,0 @@
#!/usr/bin/env python3
import multiprocessing
import os
import subprocess
PROC_COUNT = multiprocessing.cpu_count() - 1
DB_NAME = 'freqtrade_hyperopt'
WORK_DIR = os.path.join(
os.path.sep,
os.path.abspath(os.path.dirname(__file__)),
'..', '.hyperopt', 'worker'
)
if not os.path.exists(WORK_DIR):
os.makedirs(WORK_DIR)
# Spawn workers
command = [
'hyperopt-mongo-worker',
'--mongo=127.0.0.1:1234/{}'.format(DB_NAME),
'--poll-interval=0.1',
'--workdir={}'.format(WORK_DIR),
]
processes = [subprocess.Popen(command) for i in range(PROC_COUNT)]
# Join all workers
for proc in processes:
proc.wait()

21
scripts/start-mongodb.py
View File

@ -1,21 +0,0 @@
#!/usr/bin/env python3
import os
import subprocess
DB_PATH = os.path.join(
os.path.sep,
os.path.abspath(os.path.dirname(__file__)),
'..', '.hyperopt', 'mongodb'
)
if not os.path.exists(DB_PATH):
os.makedirs(DB_PATH)
subprocess.Popen([
'mongod',
'--bind_ip=127.0.0.1',
'--port=1234',
'--nohttpinterface',
'--dbpath={}'.format(DB_PATH),
]).wait()

1
setup.py
View File

@ -36,6 +36,7 @@ setup(name='freqtrade',
'tabulate',
'cachetools',
'coinmarketcap',
'scikit-optimize',
],
include_package_data=True,
zip_safe=False,

42
user_data/hyperopt_conf.py
View File

@ -1,42 +0,0 @@
"""
File that contains the configuration for Hyperopt
"""
def hyperopt_optimize_conf() -> dict:
"""
This function is used to define which parameters Hyperopt must used.
The "pair_whitelist" is only used is your are using Hyperopt with MongoDB,
without MongoDB, Hyperopt will use the pair your have set in your config file.
:return:
"""
return {
'max_open_trades': 3,
'stake_currency': 'BTC',
'stake_amount': 0.01,
"minimal_roi": {
'40': 0.0,
'30': 0.01,
'20': 0.02,
'0': 0.04,
},
'stoploss': -0.10,
"bid_strategy": {
"ask_last_balance": 0.0
},
"exchange": {
"name": "bittrex",
"pair_whitelist": [
"ETH/BTC",
"LTC/BTC",
"ETC/BTC",
"DASH/BTC",
"ZEC/BTC",
"XLM/BTC",
"NXT/BTC",
"POWR/BTC",
"ADA/BTC",
"XMR/BTC"
]
}
}