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merging develop into money_mgt (updated to async)

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This commit is contained in:
misagh 2018-09-14 19:20:49 +02:00
commit 5f68834ccc
25 changed files with 1125 additions and 180 deletions
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2
.travis.yml
View File

@ -13,7 +13,7 @@ addons:
install:
- ./install_ta-lib.sh
- export LD_LIBRARY_PATH=/usr/local/lib:$LD_LIBRARY_PATH
- pip install --upgrade flake8 coveralls pytest-random-order mypy
- pip install --upgrade flake8 coveralls pytest-random-order pytest-asyncio mypy
- pip install -r requirements.txt
- pip install -e .
jobs:

13
config.json.example
View File

@ -11,7 +11,18 @@
"sell": 30
},
"bid_strategy": {
"ask_last_balance": 0.0
"ask_last_balance": 0.0,
"use_order_book": false,
"order_book_top": 1,
"check_depth_of_market": {
"enabled": false,
"bids_to_ask_delta": 1
}
},
"ask_strategy":{
"use_order_book": false,
"order_book_min": 1,
"order_book_max": 9
},
"exchange": {
"name": "bittrex",

13
config_full.json.example
View File

@ -20,7 +20,18 @@
"sell": 30
},
"bid_strategy": {
"ask_last_balance": 0.0
"ask_last_balance": 0.0,
"use_order_book": false,
"order_book_top": 1,
"check_depth_of_market": {
"enabled": false,
"bids_to_ask_delta": 1
}
},
"ask_strategy":{
"use_order_book": false,
"order_book_min": 1,
"order_book_max": 9
},
"exchange": {
"name": "bittrex",

15
docs/configuration.md
View File

@ -23,19 +23,28 @@ The table below will list all configuration parameters.
| `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.
| `process_only_new_candles` | false | No | If set to true indicators are processed only once a new candle arrives. If false each loop populates the indicators, this will mean the same candle is processed many times creating system load but can be useful of your strategy depends on tick data not only candle. Can be set either in Configuration or in the strategy.
| `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.
| `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.
| `trailing_stoploss_positve_offset` | 0 | No | Offset on when to apply `trailing_stoploss_positive`. Percentage value which should be positive.
| `trailing_stop` | false | No | Enables trailing stop-loss (based on `stoploss` in either configuration or strategy file).
| `trailing_stop_positve` | 0 | No | Changes stop-loss once profit has been reached.
| `trailing_stop_positve_offset` | 0 | No | Offset on when to apply `trailing_stop_positive`. Percentage value which should be positive.
| `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.
| `bid_strategy.use_order_book` | false | No | Allows buying of pair using the rates in Order Book Bids.
| `bid_strategy.order_book_top` | 0 | No | Bot will use the top N rate in Order Book Bids. Ie. a value of 2 will allow the bot to pick the 2nd bid rate in Order Book Bids.
| `bid_strategy.check_depth_of_market.enabled` | false | No | Does not buy if the % difference of buy orders and sell orders is met in Order Book.
| `bid_strategy.check_depth_of_market.bids_to_ask_delta` | 0 | No | The % difference of buy orders and sell orders found in Order Book. A value lesser than 1 means sell orders is greater, while value greater than 1 means buy orders is higher.
| `ask_strategy.use_order_book` | false | No | Allows selling of open traded pair using the rates in Order Book Asks.
| `ask_strategy.order_book_min` | 0 | No | Bot will scan from the top min to max Order Book Asks searching for a profitable rate.
| `ask_strategy.order_book_max` | 0 | No | Bot will scan from the top min to max Order Book Asks searching for a profitable rate.
| `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.
| `exchange.secret` | secret | No | API secret to use for the exchange. Only required when you are in production mode.
| `exchange.pair_whitelist` | [] | No | List of currency to use by the bot. Can be overrided with `--dynamic-whitelist` param.
| `exchange.pair_blacklist` | [] | No | List of currency the bot must avoid. Useful when using `--dynamic-whitelist` param.
| `exchange.ccxt_rate_limit` | True | No | Have CCXT handle Exchange rate limits. Depending on the exchange, having this to false can lead to temporary bans from the exchange.
| `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`

2
docs/hyperopt.md
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@ -5,6 +5,8 @@ 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.
*Note:* Hyperopt will crash when used with only 1 CPU Core as found out in [Issue #1133](https://github.com/freqtrade/freqtrade/issues/1133)
## Table of Contents
- [Prepare your Hyperopt](#prepare-hyperopt)
- [Configure your Guards and Triggers](#configure-your-guards-and-triggers)

182
docs/installation.md
View File

@ -8,7 +8,6 @@ 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)
@ -56,34 +55,6 @@ 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
@ -196,7 +167,7 @@ docker run -d \
freqtrade --db-url sqlite:///tradesv3.sqlite
```
NOTE: db-url defaults to `sqlite:///tradesv3.sqlite` but it defaults to `sqlite://` if `dry_run=True` is being used.
*Note*: db-url defaults to `sqlite:///tradesv3.sqlite` but it defaults to `sqlite://` if `dry_run=True` is being used.
To override this behaviour use a custom db-url value: i.e.: `--db-url sqlite:///tradesv3.dryrun.sqlite`
### 6. Monitor your Docker instance
@ -211,14 +182,15 @@ docker stop freqtrade
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.
For more information on how to operate Docker, please refer to the [official Docker documentation](https://docs.docker.com/).
*Note*: 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 \
@ -238,12 +210,13 @@ Head over to the [Backtesting Documentation](https://github.com/freqtrade/freqtr
## Custom Installation
We've included/collected install instructions for Ubuntu 16.04, MacOS, and Windows. These are guidelines and your success may vary with other distros.
OS Specific steps are listed first, the [common](#common) section below is necessary for all systems.
### Requirements
Click each one for install guide:
* [Python 3.6.x](http://docs.python-guide.org/en/latest/starting/installation/), note the bot was not tested on Python >= 3.7.x
* [Python >= 3.6.x](http://docs.python-guide.org/en/latest/starting/installation/)
* [pip](https://pip.pypa.io/en/stable/installing/)
* [git](https://git-scm.com/book/en/v2/Getting-Started-Installing-Git)
* [virtualenv](https://virtualenv.pypa.io/en/stable/installation/) (Recommended)
@ -251,7 +224,7 @@ Click each one for install guide:
### Linux - Ubuntu 16.04
#### 1. Install Python 3.6, Git, and wget
#### Install Python 3.6, Git, and wget
```bash
sudo add-apt-repository ppa:jonathonf/python-3.6
@ -259,7 +232,34 @@ sudo apt-get update
sudo apt-get install python3.6 python3.6-venv python3.6-dev build-essential autoconf libtool pkg-config make wget git
```
#### 2. Install TA-Lib
#### Raspberry Pi / Raspbian
Before installing FreqTrade on a Raspberry Pi running the official Raspbian Image, make sure you have at least Python 3.6 installed. The default image only provides Python 3.5. Probably the easiest way to get a recent version of python is [miniconda](https://repo.continuum.io/miniconda/).
The following assumes that miniconda3 is installed and available in your environment, and is installed.
It's recommended to use (mini)conda for this as installation/compilation of `scipy` and `pandas` takes a long time.
``` bash
conda config --add channels rpi
conda install python=3.6
conda create -n freqtrade python=3.6
conda install scipy pandas
pip install -r requirements.txt
pip install -e .
```
### MacOS
#### Install Python 3.6, git, wget and ta-lib
```bash
brew install python3 git wget
```
### common
#### 1. Install TA-Lib
Official webpage: https://mrjbq7.github.io/ta-lib/install.html
@ -275,15 +275,60 @@ cd ..
rm -rf ./ta-lib*
```
*Note*: An already downloaded version of ta-lib is included in the repository, as the sourceforge.net source seems to have problems frequently.
#### 2. Setup your Python virtual environment (virtualenv)
*Note*: This step is optional but strongly recommended to keep your system organized
```bash
python3 -m venv .env
source .env/bin/activate
```
#### 3. Install FreqTrade
Clone the git repository:
```bash
git clone https://github.com/freqtrade/freqtrade.git
```
#### 4. Configure `freqtrade` as a `systemd` service
Optionally checkout the stable/master branch:
```bash
git checkout master
```
#### 4. Initialize the configuration
```bash
cd freqtrade
cp config.json.example config.json
```
> *To edit the config please refer to [Bot Configuration](https://github.com/freqtrade/freqtrade/blob/develop/docs/configuration.md).*
#### 5. Install python dependencies
``` bash
pip3 install --upgrade pip
pip3 install -r requirements.txt
pip3 install -e .
```
#### 6. Run the Bot
If this is the first time you run the bot, ensure you are running it in Dry-run `"dry_run": true,` otherwise it will start to buy and sell coins.
```bash
python3.6 ./freqtrade/main.py -c config.json
```
*Note*: If you run the bot on a server, you should consider using [Docker](#automatic-installation---docker) a terminal multiplexer like `screen` or [`tmux`](https://en.wikipedia.org/wiki/Tmux) to avoid that the bot is stopped on logout.
#### 7. [Optional] 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.
@ -299,57 +344,6 @@ For this to be persistent (run when user is logged out) you'll need to enable `l
sudo loginctl enable-linger "$USER"
```
### MacOS
#### 1. Install Python 3.6, git, wget and ta-lib
```bash
brew install python3 git wget ta-lib
```
#### 2. Install FreqTrade
Clone the git repository:
```bash
git clone https://github.com/freqtrade/freqtrade.git
```
Optionally checkout the develop branch:
```bash
git checkout develop
```
### Setup Config and virtual env
#### 1. Initialize the configuration
```bash
cd freqtrade
cp config.json.example config.json
```
> *To edit the config please refer to [Bot Configuration](https://github.com/freqtrade/freqtrade/blob/develop/docs/configuration.md).*
#### 2. Setup your Python virtual environment (virtualenv)
```bash
python3.6 -m venv .env
source .env/bin/activate
pip3.6 install --upgrade pip
pip3.6 install -r requirements.txt
pip3.6 install -e .
```
#### 3. Run the Bot
If this is the first time you run the bot, ensure you are running it in Dry-run `"dry_run": true,` otherwise it will start to buy and sell coins.
```bash
python3.6 ./freqtrade/main.py -c config.json
```
------
## Windows
@ -369,7 +363,7 @@ git clone https://github.com/freqtrade/freqtrade.git
copy paste `config.json` to ``\path\freqtrade-develop\freqtrade`
#### install ta-lib
#### Install ta-lib
Install ta-lib according to the [ta-lib documentation](https://github.com/mrjbq7/ta-lib#windows).
@ -390,5 +384,17 @@ REM >pip install TA_Lib‑0.4.17‑cp36‑cp36m‑win32.whl
> Thanks [Owdr](https://github.com/Owdr) for the commands. Source: [Issue #222](https://github.com/freqtrade/freqtrade/issues/222)
#### Error during installation under Windows
``` bash
error: Microsoft Visual C++ 14.0 is required. Get it with "Microsoft Visual C++ Build Tools": http://landinghub.visualstudio.com/visual-cpp-build-tools
```
Unfortunately, many packages requiring compilation don't provide a pre-build wheel. It is therefore mandatory to have a C/C++ compiler installed and available for your python environment to use.
The easiest way is to download install Microsoft Visual Studio Community [here](https://visualstudio.microsoft.com/downloads/) and make sure to install "Common Tools for Visual C++" to enable building c code on Windows. Unfortunately, this is a heavy download / dependency (~4Gb) so you might want to consider WSL or docker first.
---
Now you have an environment ready, the next step is
[Bot Configuration](https://github.com/freqtrade/freqtrade/blob/develop/docs/configuration.md)...

22
freqtrade/constants.py
View File

@ -53,6 +53,7 @@ CONF_SCHEMA = {
},
'fiat_display_currency': {'type': 'string', 'enum': SUPPORTED_FIAT},
'dry_run': {'type': 'boolean'},
'process_only_new_candles': {'type': 'boolean'},
'minimal_roi': {
'type': 'object',
'patternProperties': {
@ -78,18 +79,35 @@ CONF_SCHEMA = {
'type': 'number',
'minimum': 0,
'maximum': 1,
'exclusiveMaximum': False
'exclusiveMaximum': False,
'use_order_book': {'type': 'boolean'},
'order_book_top': {'type': 'number', 'maximum': 20, 'minimum': 1},
'check_depth_of_market': {
'type': 'object',
'properties': {
'enabled': {'type': 'boolean'},
'bids_to_ask_delta': {'type': 'number', 'minimum': 0},
}
},
},
},
'required': ['ask_last_balance']
},
'ask_strategy': {
'type': 'object',
'properties': {
'use_order_book': {'type': 'boolean'},
'order_book_min': {'type': 'number', 'minimum': 1},
'order_book_max': {'type': 'number', 'minimum': 1, 'maximum': 50}
}
},
'exchange': {'$ref': '#/definitions/exchange'},
'experimental': {
'type': 'object',
'properties': {
'use_sell_signal': {'type': 'boolean'},
'sell_profit_only': {'type': 'boolean'},
"ignore_roi_if_buy_signal_true": {'type': 'boolean'}
'ignore_roi_if_buy_signal_true': {'type': 'boolean'}
}
},
'telegram': {

191
freqtrade/exchange/__init__.py
View File

@ -1,12 +1,15 @@
# pragma pylint: disable=W0603
""" Cryptocurrency Exchanges support """
import logging
import inspect
from random import randint
from typing import List, Dict, Any, Optional
from typing import List, Dict, Tuple, Any, Optional
from datetime import datetime
from math import floor, ceil
import asyncio
import ccxt
import ccxt.async_support as ccxt_async
import arrow
from freqtrade import constants, OperationalException, DependencyException, TemporaryError
@ -23,6 +26,24 @@ _EXCHANGE_URLS = {
}
def retrier_async(f):
async def wrapper(*args, **kwargs):
count = kwargs.pop('count', API_RETRY_COUNT)
try:
return await f(*args, **kwargs)
except (TemporaryError, DependencyException) as ex:
logger.warning('%s() returned exception: "%s"', f.__name__, ex)
if count > 0:
count -= 1
kwargs.update({'count': count})
logger.warning('retrying %s() still for %s times', f.__name__, count)
return await wrapper(*args, **kwargs)
else:
logger.warning('Giving up retrying: %s()', f.__name__)
raise ex
return wrapper
def retrier(f):
def wrapper(*args, **kwargs):
count = kwargs.pop('count', API_RETRY_COUNT)
@ -45,8 +66,8 @@ class Exchange(object):
# Current selected exchange
_api: ccxt.Exchange = None
_api_async: ccxt_async.Exchange = None
_conf: Dict = {}
_cached_ticker: Dict[str, Any] = {}
# Holds all open sell orders for dry_run
_dry_run_open_orders: Dict[str, Any] = {}
@ -60,11 +81,20 @@ class Exchange(object):
"""
self._conf.update(config)
self._cached_ticker: Dict[str, Any] = {}
# Holds last candle refreshed time of each pair
self._pairs_last_refresh_time: Dict[str, int] = {}
# Holds candles
self.klines: Dict[str, Any] = {}
if config['dry_run']:
logger.info('Instance is running with dry_run enabled')
exchange_config = config['exchange']
self._api = self._init_ccxt(exchange_config)
self._api_async = self._init_ccxt(exchange_config, ccxt_async)
logger.info('Using Exchange "%s"', self.name)
@ -75,7 +105,15 @@ class Exchange(object):
# Check if timeframe is available
self.validate_timeframes(config['ticker_interval'])
def _init_ccxt(self, exchange_config: dict) -> ccxt.Exchange:
def __del__(self):
"""
Destructor - clean up async stuff
"""
logger.debug("Exchange object destroyed, closing async loop")
if self._api_async and inspect.iscoroutinefunction(self._api_async.close):
asyncio.get_event_loop().run_until_complete(self._api_async.close())
def _init_ccxt(self, exchange_config: dict, ccxt_module=ccxt) -> ccxt.Exchange:
"""
Initialize ccxt with given config and return valid
ccxt instance.
@ -83,15 +121,15 @@ class Exchange(object):
# Find matching class for the given exchange name
name = exchange_config['name']
if name not in ccxt.exchanges:
if name not in ccxt_module.exchanges:
raise OperationalException(f'Exchange {name} is not supported')
try:
api = getattr(ccxt, name.lower())({
api = getattr(ccxt_module, name.lower())({
'apiKey': exchange_config.get('key'),
'secret': exchange_config.get('secret'),
'password': exchange_config.get('password'),
'uid': exchange_config.get('uid', ''),
'enableRateLimit': exchange_config.get('ccxt_rate_limit', True),
'enableRateLimit': exchange_config.get('ccxt_rate_limit', True)
})
except (KeyError, AttributeError):
raise OperationalException(f'Exchange {name} is not supported')
@ -116,10 +154,19 @@ class Exchange(object):
api.urls['api'] = api.urls['test']
logger.info("Enabled Sandbox API on %s", name)
else:
logger.warning(self._api.name, "No Sandbox URL in CCXT, exiting. "
"Please check your config.json")
logger.warning(name, "No Sandbox URL in CCXT, exiting. "
"Please check your config.json")
raise OperationalException(f'Exchange {name} does not provide a sandbox api')
def _load_async_markets(self) -> None:
try:
if self._api_async:
asyncio.get_event_loop().run_until_complete(self._api_async.load_markets())
except ccxt.BaseError as e:
logger.warning('Could not load async markets. Reason: %s', e)
return
def validate_pairs(self, pairs: List[str]) -> None:
"""
Checks if all given pairs are tradable on the current exchange.
@ -130,6 +177,7 @@ class Exchange(object):
try:
markets = self._api.load_markets()
self._load_async_markets()
except ccxt.BaseError as e:
logger.warning('Unable to validate pairs (assuming they are correct). Reason: %s', e)
return
@ -329,6 +377,102 @@ class Exchange(object):
logger.info("returning cached ticker-data for %s", pair)
return self._cached_ticker[pair]
def get_history(self, pair: str, tick_interval: str,
since_ms: int) -> List:
"""
Gets candle history using asyncio and returns the list of candles.
Handles all async doing.
"""
return asyncio.get_event_loop().run_until_complete(
self._async_get_history(pair=pair, tick_interval=tick_interval,
since_ms=since_ms))
async def _async_get_history(self, pair: str,
tick_interval: str,
since_ms: int) -> List:
# Assume exchange returns 500 candles
_LIMIT = 500
one_call = constants.TICKER_INTERVAL_MINUTES[tick_interval] * 60 * _LIMIT * 1000
logger.debug("one_call: %s", one_call)
input_coroutines = [self._async_get_candle_history(
pair, tick_interval, since) for since in
range(since_ms, arrow.utcnow().timestamp * 1000, one_call)]
tickers = await asyncio.gather(*input_coroutines, return_exceptions=True)
# Combine tickers
data: List = []
for tick in tickers:
if tick[0] == pair:
data.extend(tick[1])
# Sort data again after extending the result - above calls return in "async order" order
data = sorted(data, key=lambda x: x[0])
logger.info("downloaded %s with length %s.", pair, len(data))
return data
def refresh_tickers(self, pair_list: List[str], ticker_interval: str) -> None:
"""
Refresh tickers asyncronously and return the result.
"""
logger.debug("Refreshing klines for %d pairs", len(pair_list))
asyncio.get_event_loop().run_until_complete(
self.async_get_candles_history(pair_list, ticker_interval))
async def async_get_candles_history(self, pairs: List[str],
tick_interval: str) -> List[Tuple[str, List]]:
"""Download ohlcv history for pair-list asyncronously """
input_coroutines = [self._async_get_candle_history(
symbol, tick_interval) for symbol in pairs]
tickers = await asyncio.gather(*input_coroutines, return_exceptions=True)
return tickers
@retrier_async
async def _async_get_candle_history(self, pair: str, tick_interval: str,
since_ms: Optional[int] = None) -> Tuple[str, List]:
try:
# fetch ohlcv asynchronously
logger.debug("fetching %s since %s ...", pair, since_ms)
# Calculating ticker interval in second
interval_in_sec = constants.TICKER_INTERVAL_MINUTES[tick_interval] * 60
# If (last update time) + (interval in second) is greater or equal than now
# that means we don't have to hit the API as there is no new candle
# so we fetch it from local cache
if (not since_ms and
self._pairs_last_refresh_time.get(pair, 0) + interval_in_sec >=
arrow.utcnow().timestamp):
data = self.klines[pair]
logger.debug("Using cached klines data for %s ...", pair)
else:
data = await self._api_async.fetch_ohlcv(pair, timeframe=tick_interval,
since=since_ms)
# Because some exchange sort Tickers ASC and other DESC.
# Ex: Bittrex returns a list of tickers ASC (oldest first, newest last)
# when GDAX returns a list of tickers DESC (newest first, oldest last)
data = sorted(data, key=lambda x: x[0])
# keeping last candle time as last refreshed time of the pair
if data:
self._pairs_last_refresh_time[pair] = data[-1][0] // 1000
# keeping candles in cache
self.klines[pair] = data
logger.debug("done fetching %s ...", pair)
return pair, data
except ccxt.NotSupported as e:
raise OperationalException(
f'Exchange {self._api.name} does not support fetching historical candlestick data.'
f'Message: {e}')
except (ccxt.NetworkError, ccxt.ExchangeError) as e:
raise TemporaryError(
f'Could not load ticker history due to {e.__class__.__name__}. Message: {e}')
except ccxt.BaseError as e:
raise OperationalException(f'Could not fetch ticker data. Msg: {e}')
@retrier
def get_candle_history(self, pair: str, tick_interval: str,
since_ms: Optional[int] = None) -> List[Dict]:
@ -409,6 +553,37 @@ class Exchange(object):
except ccxt.BaseError as e:
raise OperationalException(e)
@retrier
def get_order_book(self, pair: str, limit: int = 100) -> dict:
"""
get order book level 2 from exchange
Notes:
20180619: bittrex doesnt support limits -.-
20180619: binance support limits but only on specific range
"""
try:
if self._api.name == 'Binance':
limit_range = [5, 10, 20, 50, 100, 500, 1000]
# get next-higher step in the limit_range list
limit = min(list(filter(lambda x: limit <= x, limit_range)))
# above script works like loop below (but with slightly better performance):
# for limitx in limit_range:
# if limit <= limitx:
# limit = limitx
# break
return self._api.fetch_l2_order_book(pair, limit)
except ccxt.NotSupported as e:
raise OperationalException(
f'Exchange {self._api.name} does not support fetching order book.'
f'Message: {e}')
except (ccxt.NetworkError, ccxt.ExchangeError) as e:
raise TemporaryError(
f'Could not get order book due to {e.__class__.__name__}. Message: {e}')
except ccxt.BaseError as e:
raise OperationalException(e)
@retrier
def get_trades_for_order(self, order_id: str, pair: str, since: datetime) -> List:
if self._conf['dry_run']:

25
freqtrade/exchange/exchange_helpers.py
View File

@ -2,6 +2,7 @@
Functions to analyze ticker data with indicators and produce buy and sell signals
"""
import logging
import pandas as pd
from pandas import DataFrame, to_datetime
logger = logging.getLogger(__name__)
@ -31,3 +32,27 @@ def parse_ticker_dataframe(ticker: list) -> DataFrame:
})
frame.drop(frame.tail(1).index, inplace=True) # eliminate partial candle
return frame
def order_book_to_dataframe(bids: list, asks: list) -> DataFrame:
"""
Gets order book list, returns dataframe with below format per suggested by creslin
-------------------------------------------------------------------
b_sum b_size bids asks a_size a_sum
-------------------------------------------------------------------
"""
cols = ['bids', 'b_size']
bids_frame = DataFrame(bids, columns=cols)
# add cumulative sum column
bids_frame['b_sum'] = bids_frame['b_size'].cumsum()
cols2 = ['asks', 'a_size']
asks_frame = DataFrame(asks, columns=cols2)
# add cumulative sum column
asks_frame['a_sum'] = asks_frame['a_size'].cumsum()
frame = pd.concat([bids_frame['b_sum'], bids_frame['b_size'], bids_frame['bids'],
asks_frame['asks'], asks_frame['a_size'], asks_frame['a_sum']], axis=1,
keys=['b_sum', 'b_size', 'bids', 'asks', 'a_size', 'a_sum'])
# logger.info('order book %s', frame )
return frame

126
freqtrade/freqtradebot.py
View File

@ -11,6 +11,7 @@ from typing import Any, Callable, Dict, List, Optional
import arrow
import requests
from cachetools import TTLCache, cached
from freqtrade import (DependencyException, OperationalException,
@ -21,6 +22,7 @@ from freqtrade.rpc import RPCManager, RPCMessageType
from freqtrade.state import State
from freqtrade.strategy.interface import SellType
from freqtrade.strategy.resolver import IStrategy, StrategyResolver
from freqtrade.exchange.exchange_helpers import order_book_to_dataframe
logger = logging.getLogger(__name__)
@ -180,6 +182,9 @@ class FreqtradeBot(object):
final_list = sanitized_list[:nb_assets] if nb_assets else sanitized_list
self.config['exchange']['pair_whitelist'] = final_list
# Refreshing candles
self.exchange.refresh_tickers(final_list, self.strategy.ticker_interval)
# Query trades from persistence layer
trades = Trade.query.filter(Trade.is_open.is_(True)).all()
@ -267,16 +272,40 @@ class FreqtradeBot(object):
return final_list
def get_target_bid(self, ticker: Dict[str, float]) -> float:
def get_target_bid(self, pair: str, ticker: Dict[str, float]) -> float:
"""
Calculates bid target between current ask price and last price
:param ticker: Ticker to use for getting Ask and Last Price
:return: float: Price
"""
if ticker['ask'] < ticker['last']:
return ticker['ask']
balance = self.config['bid_strategy']['ask_last_balance']
return ticker['ask'] + balance * (ticker['last'] - ticker['ask'])
ticker_rate = ticker['ask']
else:
balance = self.config['bid_strategy']['ask_last_balance']
ticker_rate = ticker['ask'] + balance * (ticker['last'] - ticker['ask'])
used_rate = ticker_rate
config_bid_strategy = self.config.get('bid_strategy', {})
if 'use_order_book' in config_bid_strategy and\
config_bid_strategy.get('use_order_book', False):
logger.info('Getting price from order book')
order_book_top = config_bid_strategy.get('order_book_top', 1)
order_book = self.exchange.get_order_book(pair, order_book_top)
logger.debug('order_book %s', order_book)
# top 1 = index 0
order_book_rate = order_book['bids'][order_book_top - 1][0]
# if ticker has lower rate, then use ticker ( usefull if down trending )
logger.info('...top %s order book buy rate %0.8f', order_book_top, order_book_rate)
if ticker_rate < order_book_rate:
logger.info('...using ticker rate instead %0.8f', ticker_rate)
used_rate = ticker_rate
else:
used_rate = order_book_rate
else:
logger.info('Using Last Ask / Last Price')
used_rate = ticker_rate
return used_rate
def _get_trade_stake_amount(self) -> Optional[float]:
"""
@ -333,7 +362,7 @@ class FreqtradeBot(object):
amount_reserve_percent += self.strategy.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
return min(min_stake_amounts) / amount_reserve_percent
def create_trade(self) -> bool:
"""
@ -365,23 +394,38 @@ class FreqtradeBot(object):
if not whitelist:
raise DependencyException('No currency pairs in whitelist')
# EDGE
# WinRate and Expected Risk Reward should be calculated for all whitelisted pairs
# ASYNC: For each pair call backslap
# Save WR and ERR in Edge Dict
# Save last time updated for each pair in edge_last_update_time
# Calulate expectancy and position size and stop loss
# whitelist = Edge.filter(whitelist)
# Pick pair based on buy signals
# running get_signal on historical data fetched
# to find buy signals
for _pair in whitelist:
thistory = self.exchange.get_candle_history(_pair, interval)
(buy, sell) = self.strategy.get_signal(_pair, interval, thistory)
(buy, sell) = self.strategy.get_signal(_pair, interval, self.exchange.klines.get(_pair))
if buy and not sell:
bidstrat_check_depth_of_market = self.config.get('bid_strategy', {}).\
get('check_depth_of_market', {})
if (bidstrat_check_depth_of_market.get('enabled', False)) and\
(bidstrat_check_depth_of_market.get('bids_to_ask_delta', 0) > 0):
if self._check_depth_of_market_buy(_pair, bidstrat_check_depth_of_market):
return self.execute_buy(_pair, stake_amount)
else:
return False
return self.execute_buy(_pair, stake_amount)
return False
def _check_depth_of_market_buy(self, pair: str, conf: Dict) -> bool:
"""
Checks depth of market before executing a buy
"""
conf_bids_to_ask_delta = conf.get('bids_to_ask_delta', 0)
logger.info('checking depth of market for %s', pair)
order_book = self.exchange.get_order_book(pair, 1000)
order_book_data_frame = order_book_to_dataframe(order_book['bids'], order_book['asks'])
order_book_bids = order_book_data_frame['b_size'].sum()
order_book_asks = order_book_data_frame['a_size'].sum()
bids_ask_delta = order_book_bids / order_book_asks
logger.info('bids: %s, asks: %s, delta: %s', order_book_bids,
order_book_asks, bids_ask_delta)
if bids_ask_delta >= conf_bids_to_ask_delta:
return True
return False
def execute_buy(self, pair: str, stake_amount: float) -> bool:
@ -396,7 +440,7 @@ class FreqtradeBot(object):
fiat_currency = self.config.get('fiat_display_currency', None)
# Calculate amount
buy_limit = self.get_target_bid(self.exchange.get_ticker(pair))
buy_limit = self.get_target_bid(pair, 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:
@ -539,22 +583,52 @@ class FreqtradeBot(object):
raise ValueError(f'attempt to handle closed trade: {trade}')
logger.debug('Handling %s ...', trade)
current_rate = self.exchange.get_ticker(trade.pair)['bid']
sell_rate = self.exchange.get_ticker(trade.pair)['bid']
(buy, sell) = (False, False)
experimental = self.config.get('experimental', {})
if experimental.get('use_sell_signal') or experimental.get('ignore_roi_if_buy_signal'):
ticker = self.exchange.get_candle_history(trade.pair, self.strategy.ticker_interval)
ticker = self.exchange.klines.get(trade.pair)
(buy, sell) = self.strategy.get_signal(trade.pair, self.strategy.ticker_interval,
ticker)
should_sell = self.strategy.should_sell(trade, current_rate, datetime.utcnow(), buy, sell)
if should_sell.sell_flag:
self.execute_sell(trade, current_rate, should_sell.sell_type)
return True
config_ask_strategy = self.config.get('ask_strategy', {})
if config_ask_strategy.get('use_order_book', False):
logger.info('Using order book for selling...')
# logger.debug('Order book %s',orderBook)
order_book_min = config_ask_strategy.get('order_book_min', 1)
order_book_max = config_ask_strategy.get('order_book_max', 1)
order_book = self.exchange.get_order_book(trade.pair, order_book_max)
for i in range(order_book_min, order_book_max + 1):
order_book_rate = order_book['asks'][i - 1][0]
# if orderbook has higher rate (high profit),
# use orderbook, otherwise just use bids rate
logger.info(' order book asks top %s: %0.8f', i, order_book_rate)
if sell_rate < order_book_rate:
sell_rate = order_book_rate
if self.check_sell(trade, sell_rate, buy, sell):
return True
break
else:
logger.info('checking sell')
if self.check_sell(trade, sell_rate, buy, sell):
return True
logger.info('Found no sell signals for whitelisted currencies. Trying again..')
return False
def check_sell(self, trade: Trade, sell_rate: float, buy: bool, sell: bool) -> bool:
should_sell = self.strategy.should_sell(trade, sell_rate, datetime.utcnow(), buy, sell)
if should_sell.sell_flag:
self.execute_sell(trade, sell_rate, should_sell.sell_type)
logger.info('excuted sell')
return True
return False
def check_handle_timedout(self) -> None:
"""
Check if any orders are timed out and cancel if neccessary

14
freqtrade/optimize/__init__.py
View File

@ -221,19 +221,18 @@ def download_backtesting_testdata(datadir: str,
timerange: Optional[TimeRange] = None) -> None:
"""
Download the latest ticker intervals from the exchange for the pairs passed in parameters
Download the latest ticker intervals from the exchange for the pair passed in parameters
The data is downloaded starting from the last correct ticker interval data that
esists in a cache. If timerange starts earlier than the data in the cache,
exists in a cache. If timerange starts earlier than the data in the cache,
the full data will be redownloaded
Based on @Rybolov work: https://github.com/rybolov/freqtrade-data
:param pairs: list of pairs to download
:param pair: pair to download
:param tick_interval: ticker interval
:param timerange: range of time to download
:return: None
"""
path = make_testdata_path(datadir)
filepair = pair.replace("/", "_")
filename = os.path.join(path, f'{filepair}-{tick_interval}.json')
@ -249,8 +248,11 @@ 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 = exchange.get_candle_history(pair=pair, tick_interval=tick_interval,
since_ms=since_ms)
# Default since_ms to 30 days if nothing is given
new_data = exchange.get_history(pair=pair, tick_interval=tick_interval,
since_ms=since_ms if since_ms
else
int(arrow.utcnow().shift(days=-30).float_timestamp) * 1000)
data.extend(new_data)
logger.debug("New Start: %s", misc.format_ms_time(data[0][0]))

6
freqtrade/optimize/backtesting.py
View File

@ -434,15 +434,15 @@ class Backtesting(object):
Run a backtesting end-to-end
:return: None
"""
data = {}
data: Dict[str, Any] = {}
pairs = self.config['exchange']['pair_whitelist']
logger.info('Using stake_currency: %s ...', self.config['stake_currency'])
logger.info('Using stake_amount: %s ...', self.config['stake_amount'])
if self.config.get('live'):
logger.info('Downloading data for all pairs in whitelist ...')
for pair in pairs:
data[pair] = self.exchange.get_ticker_history(pair, self.ticker_interval)
self.exchange.refresh_tickers(pairs, self.ticker_interval)
data = self.exchange.klines
else:
logger.info('Using local backtesting data (using whitelist in given config) ...')

38
freqtrade/strategy/interface.py
View File

@ -6,7 +6,7 @@ import logging
from abc import ABC, abstractmethod
from datetime import datetime
from enum import Enum
from typing import Dict, List, NamedTuple, Tuple
from typing import Dict, List, NamedTuple, Optional, Tuple
import warnings
import arrow
@ -70,8 +70,15 @@ class IStrategy(ABC):
# associated ticker interval
ticker_interval: str
# run "populate_indicators" only for new candle
process_only_new_candles: bool = False
# Dict to determine if analysis is necessary
_last_candle_seen_per_pair: Dict[str, datetime] = {}
def __init__(self, config: dict) -> None:
self.config = config
self._last_candle_seen_per_pair = {}
@abstractmethod
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
@ -112,13 +119,34 @@ class IStrategy(ABC):
add several TA indicators and buy signal to it
:return DataFrame with ticker data and indicator data
"""
dataframe = parse_ticker_dataframe(ticker_history)
dataframe = self.advise_indicators(dataframe, metadata)
dataframe = self.advise_buy(dataframe, metadata)
dataframe = self.advise_sell(dataframe, metadata)
pair = str(metadata.get('pair'))
# Test if seen this pair and last candle before.
# always run if process_only_new_candles is set to true
if (not self.process_only_new_candles or
self._last_candle_seen_per_pair.get(pair, None) != dataframe.iloc[-1]['date']):
# Defs that only make change on new candle data.
logging.debug("TA Analysis Launched")
dataframe = self.advise_indicators(dataframe, metadata)
dataframe = self.advise_buy(dataframe, metadata)
dataframe = self.advise_sell(dataframe, metadata)
self._last_candle_seen_per_pair[pair] = dataframe.iloc[-1]['date']
else:
logging.debug("Skippinig TA Analysis for already analyzed candle")
dataframe['buy'] = 0
dataframe['sell'] = 0
# Other Defs in strategy that want to be called every loop here
# twitter_sell = self.watch_twitter_feed(dataframe, metadata)
logging.debug("Loop Analysis Launched")
return dataframe
def get_signal(self, pair: str, interval: str, ticker_hist: List[Dict]) -> Tuple[bool, bool]:
def get_signal(self, pair: str, interval: str,
ticker_hist: Optional[List[Dict]]) -> Tuple[bool, bool]:
"""
Calculates current signal based several technical analysis indicators
:param pair: pair in format ANT/BTC

9
freqtrade/strategy/resolver.py
View File

@ -66,6 +66,15 @@ class StrategyResolver(object):
else:
config['ticker_interval'] = self.strategy.ticker_interval
if 'process_only_new_candles' in config:
self.strategy.process_only_new_candles = config['process_only_new_candles']
logger.info(
"Override process_only_new_candles 'process_only_new_candles' "
"with value in config file: %s.", config['process_only_new_candles']
)
else:
config['process_only_new_candles'] = self.strategy.process_only_new_candles
# Sort and apply type conversions
self.strategy.minimal_roi = OrderedDict(sorted(
{int(key): value for (key, value) in self.strategy.minimal_roi.items()}.items(),

46
freqtrade/tests/conftest.py
View File

@ -102,7 +102,18 @@ def default_conf():
"sell": 30
},
"bid_strategy": {
"ask_last_balance": 0.0
"ask_last_balance": 0.0,
"use_order_book": False,
"order_book_top": 1,
"check_depth_of_market": {
"enabled": False,
"bids_to_ask_delta": 1
}
},
"ask_strategy": {
"use_order_book": False,
"order_book_min": 1,
"order_book_max": 1
},
"exchange": {
"name": "bittrex",
@ -403,6 +414,39 @@ def limit_sell_order():
}
@pytest.fixture
def order_book_l2():
return MagicMock(return_value={
'bids': [
[0.043936, 10.442],
[0.043935, 31.865],
[0.043933, 11.212],
[0.043928, 0.088],
[0.043925, 10.0],
[0.043921, 10.0],
[0.04392, 37.64],
[0.043899, 0.066],
[0.043885, 0.676],
[0.04387, 22.758]
],
'asks': [
[0.043949, 0.346],
[0.04395, 0.608],
[0.043951, 3.948],
[0.043954, 0.288],
[0.043958, 9.277],
[0.043995, 1.566],
[0.044, 0.588],
[0.044002, 0.992],
[0.044003, 0.095],
[0.04402, 37.64]
],
'timestamp': None,
'datetime': None,
'nonce': 288004540
})
@pytest.fixture
def ticker_history():
return [

237
freqtrade/tests/exchange/test_exchange.py
View File

@ -3,8 +3,9 @@
import logging
from datetime import datetime
from random import randint
from unittest.mock import MagicMock, PropertyMock
from unittest.mock import Mock, MagicMock, PropertyMock
import arrow
import ccxt
import pytest
@ -13,6 +14,14 @@ from freqtrade.exchange import API_RETRY_COUNT, Exchange
from freqtrade.tests.conftest import get_patched_exchange, log_has
# Source: https://stackoverflow.com/questions/29881236/how-to-mock-asyncio-coroutines
def get_mock_coro(return_value):
async def mock_coro(*args, **kwargs):
return return_value
return Mock(wraps=mock_coro)
def ccxt_exceptionhandlers(mocker, default_conf, api_mock, fun, mock_ccxt_fun, **kwargs):
with pytest.raises(TemporaryError):
api_mock.__dict__[mock_ccxt_fun] = MagicMock(side_effect=ccxt.NetworkError)
@ -27,12 +36,32 @@ def ccxt_exceptionhandlers(mocker, default_conf, api_mock, fun, mock_ccxt_fun, *
assert api_mock.__dict__[mock_ccxt_fun].call_count == 1
async def async_ccxt_exception(mocker, default_conf, api_mock, fun, mock_ccxt_fun, **kwargs):
with pytest.raises(TemporaryError):
api_mock.__dict__[mock_ccxt_fun] = MagicMock(side_effect=ccxt.NetworkError)
exchange = get_patched_exchange(mocker, default_conf, api_mock)
await 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)
await 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)
get_patched_exchange(mocker, default_conf)
assert log_has('Instance is running with dry_run enabled', caplog.record_tuples)
def test_destroy(default_conf, mocker, caplog):
caplog.set_level(logging.DEBUG)
get_patched_exchange(mocker, default_conf)
assert log_has('Exchange object destroyed, closing async loop', caplog.record_tuples)
def test_init_exception(default_conf, mocker):
default_conf['exchange']['name'] = 'wrong_exchange_name'
@ -64,6 +93,7 @@ def test_symbol_amount_prec(default_conf, mocker):
mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=api_mock))
mocker.patch('freqtrade.exchange.Exchange.validate_timeframes', MagicMock())
mocker.patch('freqtrade.exchange.Exchange._load_async_markets', MagicMock())
exchange = Exchange(default_conf)
amount = 2.34559
@ -87,6 +117,7 @@ def test_symbol_price_prec(default_conf, mocker):
mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=api_mock))
mocker.patch('freqtrade.exchange.Exchange.validate_timeframes', MagicMock())
mocker.patch('freqtrade.exchange.Exchange._load_async_markets', MagicMock())
exchange = Exchange(default_conf)
price = 2.34559
@ -108,6 +139,7 @@ def test_set_sandbox(default_conf, mocker):
type(api_mock).urls = url_mock
mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=api_mock))
mocker.patch('freqtrade.exchange.Exchange.validate_timeframes', MagicMock())
mocker.patch('freqtrade.exchange.Exchange._load_async_markets', MagicMock())
exchange = Exchange(default_conf)
liveurl = exchange._api.urls['api']
@ -129,6 +161,7 @@ def test_set_sandbox_exception(default_conf, mocker):
mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=api_mock))
mocker.patch('freqtrade.exchange.Exchange.validate_timeframes', MagicMock())
mocker.patch('freqtrade.exchange.Exchange._load_async_markets', MagicMock())
with pytest.raises(OperationalException, match=r'does not provide a sandbox api'):
exchange = Exchange(default_conf)
@ -136,6 +169,20 @@ def test_set_sandbox_exception(default_conf, mocker):
exchange.set_sandbox(exchange._api, default_conf['exchange'], 'Logname')
def test__load_async_markets(default_conf, mocker, caplog):
exchange = get_patched_exchange(mocker, default_conf)
exchange._api_async.load_markets = get_mock_coro(None)
exchange._load_async_markets()
assert exchange._api_async.load_markets.call_count == 1
caplog.set_level(logging.DEBUG)
exchange._api_async.load_markets = Mock(side_effect=ccxt.BaseError("deadbeef"))
exchange._load_async_markets()
assert log_has('Could not load async markets. Reason: deadbeef',
caplog.record_tuples)
def test_validate_pairs(default_conf, mocker):
api_mock = MagicMock()
api_mock.load_markets = MagicMock(return_value={
@ -146,6 +193,7 @@ def test_validate_pairs(default_conf, mocker):
mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=api_mock))
mocker.patch('freqtrade.exchange.Exchange.validate_timeframes', MagicMock())
mocker.patch('freqtrade.exchange.Exchange._load_async_markets', MagicMock())
Exchange(default_conf)
@ -154,6 +202,7 @@ def test_validate_pairs_not_available(default_conf, mocker):
api_mock.load_markets = MagicMock(return_value={})
mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=api_mock))
mocker.patch('freqtrade.exchange.Exchange.validate_timeframes', MagicMock())
mocker.patch('freqtrade.exchange.Exchange._load_async_markets', MagicMock())
with pytest.raises(OperationalException, match=r'not available'):
Exchange(default_conf)
@ -167,6 +216,7 @@ def test_validate_pairs_not_compatible(default_conf, mocker):
default_conf['stake_currency'] = 'ETH'
mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=api_mock))
mocker.patch('freqtrade.exchange.Exchange.validate_timeframes', MagicMock())
mocker.patch('freqtrade.exchange.Exchange._load_async_markets', MagicMock())
with pytest.raises(OperationalException, match=r'not compatible'):
Exchange(default_conf)
@ -179,6 +229,7 @@ def test_validate_pairs_exception(default_conf, mocker, caplog):
api_mock.load_markets = MagicMock(return_value={})
mocker.patch('freqtrade.exchange.Exchange._init_ccxt', api_mock)
mocker.patch('freqtrade.exchange.Exchange.validate_timeframes', MagicMock())
mocker.patch('freqtrade.exchange.Exchange._load_async_markets', MagicMock())
with pytest.raises(OperationalException, match=r'Pair ETH/BTC is not available at Binance'):
Exchange(default_conf)
@ -198,6 +249,7 @@ def test_validate_pairs_stake_exception(default_conf, mocker, caplog):
api_mock.name = MagicMock(return_value='binance')
mocker.patch('freqtrade.exchange.Exchange._init_ccxt', api_mock)
mocker.patch('freqtrade.exchange.Exchange.validate_timeframes', MagicMock())
mocker.patch('freqtrade.exchange.Exchange._load_async_markets', MagicMock())
with pytest.raises(
OperationalException,
@ -515,6 +567,189 @@ def test_get_ticker(default_conf, mocker):
exchange.get_ticker(pair='ETH/BTC', refresh=True)
def test_get_history(default_conf, mocker, caplog):
exchange = get_patched_exchange(mocker, default_conf)
tick = [
[
arrow.utcnow().timestamp * 1000, # unix timestamp ms
1, # open
2, # high
3, # low
4, # close
5, # volume (in quote currency)
]
]
pair = 'ETH/BTC'
async def mock_candle_hist(pair, tick_interval, since_ms):
return pair, tick
exchange._async_get_candle_history = Mock(wraps=mock_candle_hist)
# one_call calculation * 1.8 should do 2 calls
since = 5 * 60 * 500 * 1.8
print(f"since = {since}")
ret = exchange.get_history(pair, "5m", int((arrow.utcnow().timestamp - since) * 1000))
assert exchange._async_get_candle_history.call_count == 2
# Returns twice the above tick
assert len(ret) == 2
def test_refresh_tickers(mocker, default_conf, caplog) -> None:
tick = [
[
1511686200000, # unix timestamp ms
1, # open
2, # high
3, # low
4, # close
5, # volume (in quote currency)
]
]
caplog.set_level(logging.DEBUG)
exchange = get_patched_exchange(mocker, default_conf)
exchange._api_async.fetch_ohlcv = get_mock_coro(tick)
pairs = ['IOTA/ETH', 'XRP/ETH']
# empty dicts
assert not exchange.klines
exchange.refresh_tickers(['IOTA/ETH', 'XRP/ETH'], '5m')
assert log_has(f'Refreshing klines for {len(pairs)} pairs', caplog.record_tuples)
assert exchange.klines
for pair in pairs:
assert exchange.klines[pair]
@pytest.mark.asyncio
async def test__async_get_candle_history(default_conf, mocker, caplog):
tick = [
[
arrow.utcnow().timestamp * 1000, # unix timestamp ms
1, # open
2, # high
3, # low
4, # close
5, # volume (in quote currency)
]
]
caplog.set_level(logging.DEBUG)
exchange = get_patched_exchange(mocker, default_conf)
# Monkey-patch async function
exchange._api_async.fetch_ohlcv = get_mock_coro(tick)
exchange = Exchange(default_conf)
pair = 'ETH/BTC'
res = await exchange._async_get_candle_history(pair, "5m")
assert type(res) is tuple
assert len(res) == 2
assert res[0] == pair
assert res[1] == tick
assert exchange._api_async.fetch_ohlcv.call_count == 1
assert not log_has(f"Using cached klines data for {pair} ...", caplog.record_tuples)
# test caching
res = await exchange._async_get_candle_history(pair, "5m")
assert exchange._api_async.fetch_ohlcv.call_count == 1
assert log_has(f"Using cached klines data for {pair} ...", caplog.record_tuples)
# exchange = Exchange(default_conf)
await async_ccxt_exception(mocker, default_conf, MagicMock(),
"_async_get_candle_history", "fetch_ohlcv",
pair='ABCD/BTC', tick_interval=default_conf['ticker_interval'])
api_mock = MagicMock()
with pytest.raises(OperationalException, match=r'Could not fetch ticker data*'):
api_mock.fetch_ohlcv = MagicMock(side_effect=ccxt.BaseError)
exchange = get_patched_exchange(mocker, default_conf, api_mock)
await exchange._async_get_candle_history(pair, "5m",
(arrow.utcnow().timestamp - 2000) * 1000)
@pytest.mark.asyncio
async def test__async_get_candle_history_empty(default_conf, mocker, caplog):
""" Test empty exchange result """
tick = []
caplog.set_level(logging.DEBUG)
exchange = get_patched_exchange(mocker, default_conf)
# Monkey-patch async function
exchange._api_async.fetch_ohlcv = get_mock_coro([])
exchange = Exchange(default_conf)
pair = 'ETH/BTC'
res = await exchange._async_get_candle_history(pair, "5m")
assert type(res) is tuple
assert len(res) == 2
assert res[0] == pair
assert res[1] == tick
assert exchange._api_async.fetch_ohlcv.call_count == 1
@pytest.mark.asyncio
async def test_async_get_candles_history(default_conf, mocker):
tick = [
[
1511686200000, # unix timestamp ms
1, # open
2, # high
3, # low
4, # close
5, # volume (in quote currency)
]
]
async def mock_get_candle_hist(pair, tick_interval, since_ms=None):
return (pair, tick)
exchange = get_patched_exchange(mocker, default_conf)
# Monkey-patch async function
exchange._api_async.fetch_ohlcv = get_mock_coro(tick)
exchange._async_get_candle_history = Mock(wraps=mock_get_candle_hist)
pairs = ['ETH/BTC', 'XRP/BTC']
res = await exchange.async_get_candles_history(pairs, "5m")
assert type(res) is list
assert len(res) == 2
assert type(res[0]) is tuple
assert res[0][0] == pairs[0]
assert res[0][1] == tick
assert res[1][0] == pairs[1]
assert res[1][1] == tick
assert exchange._async_get_candle_history.call_count == 2
def test_get_order_book(default_conf, mocker, order_book_l2):
default_conf['exchange']['name'] = 'binance'
api_mock = MagicMock()
api_mock.fetch_l2_order_book = order_book_l2
exchange = get_patched_exchange(mocker, default_conf, api_mock)
order_book = exchange.get_order_book(pair='ETH/BTC', limit=10)
assert 'bids' in order_book
assert 'asks' in order_book
assert len(order_book['bids']) == 10
assert len(order_book['asks']) == 10
def test_get_order_book_exception(default_conf, mocker):
api_mock = MagicMock()
with pytest.raises(OperationalException):
api_mock.fetch_l2_order_book = MagicMock(side_effect=ccxt.NotSupported)
exchange = get_patched_exchange(mocker, default_conf, api_mock)
exchange.get_order_book(pair='ETH/BTC', limit=50)
with pytest.raises(TemporaryError):
api_mock.fetch_l2_order_book = MagicMock(side_effect=ccxt.NetworkError)
exchange = get_patched_exchange(mocker, default_conf, api_mock)
exchange.get_order_book(pair='ETH/BTC', limit=50)
with pytest.raises(OperationalException):
api_mock.fetch_l2_order_book = MagicMock(side_effect=ccxt.BaseError)
exchange = get_patched_exchange(mocker, default_conf, api_mock)
exchange.get_order_book(pair='ETH/BTC', limit=50)
def make_fetch_ohlcv_mock(data):
def fetch_ohlcv_mock(pair, timeframe, since):
if since:

27
freqtrade/tests/optimize/test_backtesting.py
View File

@ -110,7 +110,7 @@ def mocked_load_data(datadir, pairs=[], ticker_interval='0m', refresh_pairs=Fals
return pairdata
# use for mock freqtrade.exchange.get_candle_history'
# use for mock ccxt.fetch_ohlvc'
def _load_pair_as_ticks(pair, tickfreq):
ticks = optimize.load_data(None, ticker_interval=tickfreq, pairs=[pair])
ticks = trim_dictlist(ticks, -201)
@ -455,7 +455,7 @@ def test_backtesting_start(default_conf, mocker, caplog) -> None:
return Arrow(2017, 11, 14, 21, 17), Arrow(2017, 11, 14, 22, 59)
mocker.patch('freqtrade.optimize.load_data', mocked_load_data)
mocker.patch('freqtrade.exchange.Exchange.get_candle_history')
mocker.patch('freqtrade.exchange.Exchange.refresh_tickers', MagicMock())
patch_exchange(mocker)
mocker.patch.multiple(
'freqtrade.optimize.backtesting.Backtesting',
@ -490,7 +490,7 @@ def test_backtesting_start_no_data(default_conf, mocker, caplog) -> None:
return Arrow(2017, 11, 14, 21, 17), Arrow(2017, 11, 14, 22, 59)
mocker.patch('freqtrade.optimize.load_data', MagicMock(return_value={}))
mocker.patch('freqtrade.exchange.Exchange.get_candle_history')
mocker.patch('freqtrade.exchange.Exchange.refresh_tickers', MagicMock())
patch_exchange(mocker)
mocker.patch.multiple(
'freqtrade.optimize.backtesting.Backtesting',
@ -733,9 +733,14 @@ def test_backtest_record(default_conf, fee, mocker):
def test_backtest_start_live(default_conf, mocker, caplog):
default_conf['exchange']['pair_whitelist'] = ['UNITTEST/BTC']
mocker.patch('freqtrade.exchange.Exchange.get_candle_history',
new=lambda s, n, i: _load_pair_as_ticks(n, i))
patch_exchange(mocker)
async def load_pairs(pair, timeframe, since):
return _load_pair_as_ticks(pair, timeframe)
api_mock = MagicMock()
api_mock.fetch_ohlcv = load_pairs
patch_exchange(mocker, api_mock)
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(
@ -776,9 +781,13 @@ def test_backtest_start_live(default_conf, mocker, caplog):
def test_backtest_start_multi_strat(default_conf, mocker, caplog):
default_conf['exchange']['pair_whitelist'] = ['UNITTEST/BTC']
mocker.patch('freqtrade.exchange.Exchange.get_candle_history',
new=lambda s, n, i: _load_pair_as_ticks(n, i))
patch_exchange(mocker)
async def load_pairs(pair, timeframe, since):
return _load_pair_as_ticks(pair, timeframe)
api_mock = MagicMock()
api_mock.fetch_ohlcv = load_pairs
patch_exchange(mocker, api_mock)
backtestmock = MagicMock()
mocker.patch('freqtrade.optimize.backtesting.Backtesting.backtest', backtestmock)
gen_table_mock = MagicMock()

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

@ -53,7 +53,7 @@ def _clean_test_file(file: str) -> None:
def test_load_data_30min_ticker(ticker_history, mocker, caplog, default_conf) -> None:
mocker.patch('freqtrade.exchange.Exchange.get_candle_history', return_value=ticker_history)
mocker.patch('freqtrade.exchange.Exchange.get_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')
@ -63,7 +63,7 @@ def test_load_data_30min_ticker(ticker_history, mocker, caplog, default_conf) ->
def test_load_data_5min_ticker(ticker_history, mocker, caplog, default_conf) -> None:
mocker.patch('freqtrade.exchange.Exchange.get_candle_history', return_value=ticker_history)
mocker.patch('freqtrade.exchange.Exchange.get_history', return_value=ticker_history)
file = os.path.join(os.path.dirname(__file__), '..', 'testdata', 'UNITTEST_BTC-5m.json')
_backup_file(file, copy_file=True)
@ -74,7 +74,7 @@ def test_load_data_5min_ticker(ticker_history, mocker, caplog, default_conf) ->
def test_load_data_1min_ticker(ticker_history, mocker, caplog) -> None:
mocker.patch('freqtrade.exchange.Exchange.get_candle_history', return_value=ticker_history)
mocker.patch('freqtrade.exchange.Exchange.get_history', return_value=ticker_history)
file = os.path.join(os.path.dirname(__file__), '..', 'testdata', 'UNITTEST_BTC-1m.json')
_backup_file(file, copy_file=True)
optimize.load_data(None, ticker_interval='1m', pairs=['UNITTEST/BTC'])
@ -87,7 +87,7 @@ def test_load_data_with_new_pair_1min(ticker_history, mocker, caplog, default_co
"""
Test load_data() with 1 min ticker
"""
mocker.patch('freqtrade.exchange.Exchange.get_candle_history', return_value=ticker_history)
mocker.patch('freqtrade.exchange.Exchange.get_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')
@ -118,7 +118,7 @@ def test_testdata_path() -> None:
def test_download_pairs(ticker_history, mocker, default_conf) -> None:
mocker.patch('freqtrade.exchange.Exchange.get_candle_history', return_value=ticker_history)
mocker.patch('freqtrade.exchange.Exchange.get_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')
@ -261,7 +261,7 @@ def test_load_cached_data_for_updating(mocker) -> None:
def test_download_pairs_exception(ticker_history, mocker, caplog, default_conf) -> None:
mocker.patch('freqtrade.exchange.Exchange.get_candle_history', return_value=ticker_history)
mocker.patch('freqtrade.exchange.Exchange.get_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)
@ -279,7 +279,7 @@ def test_download_pairs_exception(ticker_history, mocker, caplog, default_conf)
def test_download_backtesting_testdata(ticker_history, mocker, default_conf) -> None:
mocker.patch('freqtrade.exchange.Exchange.get_candle_history', return_value=ticker_history)
mocker.patch('freqtrade.exchange.Exchange.get_history', return_value=ticker_history)
exchange = get_patched_exchange(mocker, default_conf)
# Download a 1 min ticker file
@ -304,7 +304,7 @@ def test_download_backtesting_testdata2(mocker, default_conf) -> None:
[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.exchange.Exchange.get_candle_history', return_value=tick)
mocker.patch('freqtrade.exchange.Exchange.get_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')

73
freqtrade/tests/strategy/test_interface.py
View File

@ -89,7 +89,6 @@ def test_get_signal_old_dataframe(default_conf, mocker, caplog):
def test_get_signal_handles_exceptions(mocker, default_conf):
mocker.patch('freqtrade.exchange.Exchange.get_candle_history', return_value=MagicMock())
exchange = get_patched_exchange(mocker, default_conf)
mocker.patch.object(
_STRATEGY, 'analyze_ticker',
@ -129,3 +128,75 @@ def test_min_roi_reached(default_conf, fee) -> None:
assert not strategy.min_roi_reached(trade, -0.01, arrow.utcnow().shift(minutes=-1).datetime)
assert strategy.min_roi_reached(trade, 0.02, arrow.utcnow().shift(minutes=-1).datetime)
def test_analyze_ticker_default(ticker_history, mocker, caplog) -> None:
caplog.set_level(logging.DEBUG)
ind_mock = MagicMock(side_effect=lambda x, meta: x)
buy_mock = MagicMock(side_effect=lambda x, meta: x)
sell_mock = MagicMock(side_effect=lambda x, meta: x)
mocker.patch.multiple(
'freqtrade.strategy.interface.IStrategy',
advise_indicators=ind_mock,
advise_buy=buy_mock,
advise_sell=sell_mock,
)
strategy = DefaultStrategy({})
strategy.analyze_ticker(ticker_history, {'pair': 'ETH/BTC'})
assert ind_mock.call_count == 1
assert buy_mock.call_count == 1
assert buy_mock.call_count == 1
assert log_has('TA Analysis Launched', caplog.record_tuples)
assert not log_has('Skippinig TA Analysis for already analyzed candle',
caplog.record_tuples)
caplog.clear()
strategy.analyze_ticker(ticker_history, {'pair': 'ETH/BTC'})
# No analysis happens as process_only_new_candles is true
assert ind_mock.call_count == 2
assert buy_mock.call_count == 2
assert buy_mock.call_count == 2
assert log_has('TA Analysis Launched', caplog.record_tuples)
assert not log_has('Skippinig TA Analysis for already analyzed candle',
caplog.record_tuples)
def test_analyze_ticker_skip_analyze(ticker_history, mocker, caplog) -> None:
caplog.set_level(logging.DEBUG)
ind_mock = MagicMock(side_effect=lambda x, meta: x)
buy_mock = MagicMock(side_effect=lambda x, meta: x)
sell_mock = MagicMock(side_effect=lambda x, meta: x)
mocker.patch.multiple(
'freqtrade.strategy.interface.IStrategy',
advise_indicators=ind_mock,
advise_buy=buy_mock,
advise_sell=sell_mock,
)
strategy = DefaultStrategy({})
strategy.process_only_new_candles = True
ret = strategy.analyze_ticker(ticker_history, {'pair': 'ETH/BTC'})
assert ind_mock.call_count == 1
assert buy_mock.call_count == 1
assert buy_mock.call_count == 1
assert log_has('TA Analysis Launched', caplog.record_tuples)
assert not log_has('Skippinig TA Analysis for already analyzed candle',
caplog.record_tuples)
caplog.clear()
ret = strategy.analyze_ticker(ticker_history, {'pair': 'ETH/BTC'})
# No analysis happens as process_only_new_candles is true
assert ind_mock.call_count == 1
assert buy_mock.call_count == 1
assert buy_mock.call_count == 1
# only skipped analyze adds buy and sell columns, otherwise it's all mocked
assert 'buy' in ret
assert 'sell' in ret
assert ret['buy'].sum() == 0
assert ret['sell'].sum() == 0
assert not log_has('TA Analysis Launched', caplog.record_tuples)
assert log_has('Skippinig TA Analysis for already analyzed candle',
caplog.record_tuples)

17
freqtrade/tests/strategy/test_strategy.py
View File

@ -165,6 +165,23 @@ def test_strategy_override_ticker_interval(caplog):
) in caplog.record_tuples
def test_strategy_override_process_only_new_candles(caplog):
caplog.set_level(logging.INFO)
config = {
'strategy': 'DefaultStrategy',
'process_only_new_candles': True
}
resolver = StrategyResolver(config)
assert resolver.strategy.process_only_new_candles
assert ('freqtrade.strategy.resolver',
logging.INFO,
"Override process_only_new_candles 'process_only_new_candles' "
"with value in config file: True."
) in caplog.record_tuples
def test_deprecate_populate_indicators(result):
default_location = path.join(path.dirname(path.realpath(__file__)))
resolver = StrategyResolver({'strategy': 'TestStrategyLegacy',

203
freqtrade/tests/test_freqtradebot.py
View File

@ -43,7 +43,7 @@ def patch_get_signal(freqtrade: FreqtradeBot, value=(True, False)) -> None:
:return: None
"""
freqtrade.strategy.get_signal = lambda e, s, t: value
freqtrade.exchange.get_candle_history = lambda p, i: None
freqtrade.exchange.refresh_tickers = lambda p, i: None
def patch_RPCManager(mocker) -> MagicMock:
@ -159,6 +159,15 @@ def test_gen_pair_whitelist(mocker, default_conf, tickers) -> None:
assert whitelist == []
def test_gen_pair_whitelist_not_supported(mocker, default_conf, tickers) -> None:
freqtrade = get_patched_freqtradebot(mocker, default_conf)
mocker.patch('freqtrade.exchange.Exchange.get_tickers', tickers)
mocker.patch('freqtrade.exchange.Exchange.exchange_has', MagicMock(return_value=False))
with pytest.raises(OperationalException):
freqtrade._gen_pair_whitelist(base_currency='BTC')
@pytest.mark.skip(reason="Test not implemented")
def test_refresh_whitelist() -> None:
pass
@ -544,7 +553,6 @@ def test_create_trade_no_signal(default_conf, fee, mocker) -> None:
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
validate_pairs=MagicMock(),
get_candle_history=MagicMock(return_value=20),
get_balance=MagicMock(return_value=20),
get_fee=fee,
)
@ -664,21 +672,21 @@ def test_balance_fully_ask_side(mocker, default_conf) -> None:
default_conf['bid_strategy']['ask_last_balance'] = 0.0
freqtrade = get_patched_freqtradebot(mocker, default_conf)
assert freqtrade.get_target_bid({'ask': 20, 'last': 10}) == 20
assert freqtrade.get_target_bid('ETH/BTC', {'ask': 20, 'last': 10}) == 20
def test_balance_fully_last_side(mocker, default_conf) -> None:
default_conf['bid_strategy']['ask_last_balance'] = 1.0
freqtrade = get_patched_freqtradebot(mocker, default_conf)
assert freqtrade.get_target_bid({'ask': 20, 'last': 10}) == 10
assert freqtrade.get_target_bid('ETH/BTC', {'ask': 20, 'last': 10}) == 10
def test_balance_bigger_last_ask(mocker, default_conf) -> None:
default_conf['bid_strategy']['ask_last_balance'] = 1.0
freqtrade = get_patched_freqtradebot(mocker, default_conf)
assert freqtrade.get_target_bid({'ask': 5, 'last': 10}) == 5
assert freqtrade.get_target_bid('ETH/BTC', {'ask': 5, 'last': 10}) == 5
def test_process_maybe_execute_buy(mocker, default_conf) -> None:
@ -1878,6 +1886,191 @@ def test_get_real_amount_open_trade(default_conf, mocker):
assert freqtrade.get_real_amount(trade, order) == amount
def test_order_book_depth_of_market(default_conf, ticker, limit_buy_order, fee, markets, mocker,
order_book_l2):
default_conf['bid_strategy']['check_depth_of_market']['enabled'] = True
default_conf['bid_strategy']['check_depth_of_market']['bids_to_ask_delta'] = 0.1
patch_RPCManager(mocker)
mocker.patch('freqtrade.exchange.Exchange.get_order_book', order_book_l2)
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
validate_pairs=MagicMock(),
get_ticker=ticker,
buy=MagicMock(return_value={'id': limit_buy_order['id']}),
get_fee=fee,
get_markets=markets
)
# Save state of current whitelist
whitelist = deepcopy(default_conf['exchange']['pair_whitelist'])
freqtrade = FreqtradeBot(default_conf)
patch_get_signal(freqtrade)
freqtrade.create_trade()
trade = Trade.query.first()
assert trade is not None
assert trade.stake_amount == 0.001
assert trade.is_open
assert trade.open_date is not None
assert trade.exchange == 'bittrex'
# Simulate fulfilled LIMIT_BUY order for trade
trade.update(limit_buy_order)
assert trade.open_rate == 0.00001099
assert whitelist == default_conf['exchange']['pair_whitelist']
def test_order_book_depth_of_market_high_delta(default_conf, ticker, limit_buy_order,
fee, markets, mocker, order_book_l2):
default_conf['bid_strategy']['check_depth_of_market']['enabled'] = True
# delta is 100 which is impossible to reach. hence check_depth_of_market will return false
default_conf['bid_strategy']['check_depth_of_market']['bids_to_ask_delta'] = 100
patch_RPCManager(mocker)
mocker.patch('freqtrade.exchange.Exchange.get_order_book', order_book_l2)
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
validate_pairs=MagicMock(),
get_ticker=ticker,
buy=MagicMock(return_value={'id': limit_buy_order['id']}),
get_fee=fee,
get_markets=markets
)
# Save state of current whitelist
freqtrade = FreqtradeBot(default_conf)
patch_get_signal(freqtrade)
freqtrade.create_trade()
trade = Trade.query.first()
assert trade is None
def test_order_book_bid_strategy1(mocker, default_conf, order_book_l2, markets) -> None:
"""
test if function get_target_bid will return the order book price
instead of the ask rate
"""
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
validate_pairs=MagicMock(),
get_markets=markets,
get_order_book=order_book_l2
)
default_conf['exchange']['name'] = 'binance'
default_conf['bid_strategy']['use_order_book'] = True
default_conf['bid_strategy']['order_book_top'] = 2
default_conf['bid_strategy']['ask_last_balance'] = 0
default_conf['telegram']['enabled'] = False
freqtrade = FreqtradeBot(default_conf)
assert freqtrade.get_target_bid('ETH/BTC', {'ask': 0.045, 'last': 0.046}) == 0.043935
def test_order_book_bid_strategy2(mocker, default_conf, order_book_l2, markets) -> None:
"""
test if function get_target_bid will return the ask rate (since its value is lower)
instead of the order book rate (even if enabled)
"""
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
validate_pairs=MagicMock(),
get_markets=markets,
get_order_book=order_book_l2
)
default_conf['exchange']['name'] = 'binance'
default_conf['bid_strategy']['use_order_book'] = True
default_conf['bid_strategy']['order_book_top'] = 2
default_conf['bid_strategy']['ask_last_balance'] = 0
default_conf['telegram']['enabled'] = False
freqtrade = FreqtradeBot(default_conf)
assert freqtrade.get_target_bid('ETH/BTC', {'ask': 0.042, 'last': 0.046}) == 0.042
def test_order_book_bid_strategy3(default_conf, mocker, order_book_l2, markets) -> None:
"""
test if function get_target_bid will return ask rate instead
of the order book rate
"""
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
validate_pairs=MagicMock(),
get_markets=markets,
get_order_book=order_book_l2
)
default_conf['exchange']['name'] = 'binance'
default_conf['bid_strategy']['use_order_book'] = True
default_conf['bid_strategy']['order_book_top'] = 1
default_conf['bid_strategy']['ask_last_balance'] = 0
default_conf['telegram']['enabled'] = False
freqtrade = FreqtradeBot(default_conf)
assert freqtrade.get_target_bid('ETH/BTC', {'ask': 0.03, 'last': 0.029}) == 0.03
def test_check_depth_of_market_buy(default_conf, mocker, order_book_l2, markets) -> None:
"""
test check depth of market
"""
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
validate_pairs=MagicMock(),
get_markets=markets,
get_order_book=order_book_l2
)
default_conf['telegram']['enabled'] = False
default_conf['exchange']['name'] = 'binance'
default_conf['bid_strategy']['check_depth_of_market']['enabled'] = True
# delta is 100 which is impossible to reach. hence function will return false
default_conf['bid_strategy']['check_depth_of_market']['bids_to_ask_delta'] = 100
freqtrade = FreqtradeBot(default_conf)
conf = default_conf['bid_strategy']['check_depth_of_market']
assert freqtrade._check_depth_of_market_buy('ETH/BTC', conf) is False
def test_order_book_ask_strategy(default_conf, limit_buy_order, limit_sell_order,
fee, markets, mocker, order_book_l2) -> None:
"""
test order book ask strategy
"""
mocker.patch('freqtrade.exchange.Exchange.get_order_book', order_book_l2)
default_conf['exchange']['name'] = 'binance'
default_conf['ask_strategy']['use_order_book'] = True
default_conf['ask_strategy']['order_book_min'] = 1
default_conf['ask_strategy']['order_book_max'] = 2
default_conf['telegram']['enabled'] = False
patch_RPCManager(mocker)
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
validate_pairs=MagicMock(),
get_ticker=MagicMock(return_value={
'bid': 0.00001172,
'ask': 0.00001173,
'last': 0.00001172
}),
buy=MagicMock(return_value={'id': limit_buy_order['id']}),
sell=MagicMock(return_value={'id': limit_sell_order['id']}),
get_fee=fee,
get_markets=markets
)
freqtrade = FreqtradeBot(default_conf)
patch_get_signal(freqtrade)
freqtrade.create_trade()
trade = Trade.query.first()
assert trade
time.sleep(0.01) # Race condition fix
trade.update(limit_buy_order)
assert trade.is_open is True
patch_get_signal(freqtrade, value=(False, True))
assert freqtrade.handle_trade(trade) is True
def test_startup_messages(default_conf, mocker):
default_conf['dynamic_whitelist'] = 20
freqtrade = get_patched_freqtradebot(mocker, default_conf)

9
requirements.txt
View File

@ -1,6 +1,6 @@
ccxt==1.17.170
ccxt==1.17.283
SQLAlchemy==1.2.11
python-telegram-bot==10.1.0
python-telegram-bot==11.1.0
arrow==0.12.1
cachetools==2.1.0
requests==2.19.1
@ -12,9 +12,10 @@ scipy==1.1.0
jsonschema==2.6.0
numpy==1.15.1
TA-Lib==0.4.17
pytest==3.7.2
pytest==3.8.0
pytest-mock==1.10.0
pytest-cov==2.5.1
pytest-asyncio==0.9.0
pytest-cov==2.6.0
tabulate==0.8.2
coinmarketcap==5.0.3

9
scripts/download_backtest_data.py
View File

@ -1,6 +1,6 @@
#!/usr/bin/env python3
"""This script generate json data from bittrex"""
"""This script generate json data"""
import json
import sys
from pathlib import Path
@ -52,9 +52,10 @@ exchange = Exchange({'key': '',
'stake_currency': '',
'dry_run': True,
'exchange': {
'name': args.exchange,
'pair_whitelist': []
}
'name': args.exchange,
'pair_whitelist': [],
'ccxt_rate_limit': False
}
})
pairs_not_available = []

3
scripts/plot_dataframe.py
View File

@ -138,7 +138,8 @@ def plot_analyzed_dataframe(args: Namespace) -> None:
tickers = {}
if args.live:
logger.info('Downloading pair.')
tickers[pair] = exchange.get_candle_history(pair, tick_interval)
exchange.refresh_tickers([pair], tick_interval)
tickers[pair] = exchange.klines[pair]
else:
tickers = optimize.load_data(
datadir=_CONF.get("datadir"),

3
user_data/strategies/test_strategy.py
View File

@ -45,6 +45,9 @@ class TestStrategy(IStrategy):
# Optimal ticker interval for the strategy
ticker_interval = '5m'
# run "populate_indicators" only for new candle
ta_on_candle = False
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Adds several different TA indicators to the given DataFrame