Merge branch 'develop' into feat/short

This commit is contained in:
Matthias 2022-01-29 14:19:30 +01:00
commit 463714832d
41 changed files with 347 additions and 135 deletions

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@ -20,7 +20,7 @@ jobs:
strategy: strategy:
matrix: matrix:
os: [ ubuntu-18.04, ubuntu-20.04 ] os: [ ubuntu-18.04, ubuntu-20.04 ]
python-version: ["3.7", "3.8", "3.9", "3.10"] python-version: ["3.8", "3.9", "3.10"]
steps: steps:
- uses: actions/checkout@v2 - uses: actions/checkout@v2
@ -115,7 +115,7 @@ jobs:
strategy: strategy:
matrix: matrix:
os: [ macos-latest ] os: [ macos-latest ]
python-version: ["3.7", "3.8", "3.9", "3.10"] python-version: ["3.8", "3.9", "3.10"]
steps: steps:
- uses: actions/checkout@v2 - uses: actions/checkout@v2
@ -207,7 +207,7 @@ jobs:
strategy: strategy:
matrix: matrix:
os: [ windows-latest ] os: [ windows-latest ]
python-version: ["3.7", "3.8", "3.9", "3.10"] python-version: ["3.8", "3.9", "3.10"]
steps: steps:
- uses: actions/checkout@v2 - uses: actions/checkout@v2

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@ -49,7 +49,7 @@ Please find the complete documentation on the [freqtrade website](https://www.fr
## Features ## Features
- [x] **Based on Python 3.7+**: For botting on any operating system - Windows, macOS and Linux. - [x] **Based on Python 3.8+**: For botting on any operating system - Windows, macOS and Linux.
- [x] **Persistence**: Persistence is achieved through sqlite. - [x] **Persistence**: Persistence is achieved through sqlite.
- [x] **Dry-run**: Run the bot without paying money. - [x] **Dry-run**: Run the bot without paying money.
- [x] **Backtesting**: Run a simulation of your buy/sell strategy. - [x] **Backtesting**: Run a simulation of your buy/sell strategy.
@ -197,7 +197,7 @@ To run this bot we recommend you a cloud instance with a minimum of:
### Software requirements ### Software requirements
- [Python >= 3.7](http://docs.python-guide.org/en/latest/starting/installation/) - [Python >= 3.8](http://docs.python-guide.org/en/latest/starting/installation/)
- [pip](https://pip.pypa.io/en/stable/installing/) - [pip](https://pip.pypa.io/en/stable/installing/)
- [git](https://git-scm.com/book/en/v2/Getting-Started-Installing-Git) - [git](https://git-scm.com/book/en/v2/Getting-Started-Installing-Git)
- [TA-Lib](https://mrjbq7.github.io/ta-lib/install.html) - [TA-Lib](https://mrjbq7.github.io/ta-lib/install.html)

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@ -5,9 +5,6 @@ python -m pip install --upgrade pip wheel
$pyv = python -c "import sys; print(f'{sys.version_info.major}.{sys.version_info.minor}')" $pyv = python -c "import sys; print(f'{sys.version_info.major}.{sys.version_info.minor}')"
if ($pyv -eq '3.7') {
pip install build_helpers\TA_Lib-0.4.24-cp37-cp37m-win_amd64.whl
}
if ($pyv -eq '3.8') { if ($pyv -eq '3.8') {
pip install build_helpers\TA_Lib-0.4.24-cp38-cp38-win_amd64.whl pip install build_helpers\TA_Lib-0.4.24-cp38-cp38-win_amd64.whl
} }

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@ -105,7 +105,7 @@ You can define your own estimator for Hyperopt by implementing `generate_estimat
```python ```python
class MyAwesomeStrategy(IStrategy): class MyAwesomeStrategy(IStrategy):
class HyperOpt: class HyperOpt:
def generate_estimator(): def generate_estimator(dimensions: List['Dimension'], **kwargs):
return "RF" return "RF"
``` ```
@ -119,13 +119,34 @@ Example for `ExtraTreesRegressor` ("ET") with additional parameters:
```python ```python
class MyAwesomeStrategy(IStrategy): class MyAwesomeStrategy(IStrategy):
class HyperOpt: class HyperOpt:
def generate_estimator(): def generate_estimator(dimensions: List['Dimension'], **kwargs):
from skopt.learning import ExtraTreesRegressor from skopt.learning import ExtraTreesRegressor
# Corresponds to "ET" - but allows additional parameters. # Corresponds to "ET" - but allows additional parameters.
return ExtraTreesRegressor(n_estimators=100) return ExtraTreesRegressor(n_estimators=100)
``` ```
The `dimensions` parameter is the list of `skopt.space.Dimension` objects corresponding to the parameters to be optimized. It can be used to create isotropic kernels for the `skopt.learning.GaussianProcessRegressor` estimator. Here's an example:
```python
class MyAwesomeStrategy(IStrategy):
class HyperOpt:
def generate_estimator(dimensions: List['Dimension'], **kwargs):
from skopt.utils import cook_estimator
from skopt.learning.gaussian_process.kernels import (Matern, ConstantKernel)
kernel_bounds = (0.0001, 10000)
kernel = (
ConstantKernel(1.0, kernel_bounds) *
Matern(length_scale=np.ones(len(dimensions)), length_scale_bounds=[kernel_bounds for d in dimensions], nu=2.5)
)
kernel += (
ConstantKernel(1.0, kernel_bounds) *
Matern(length_scale=np.ones(len(dimensions)), length_scale_bounds=[kernel_bounds for d in dimensions], nu=1.5)
)
return cook_estimator("GP", space=dimensions, kernel=kernel, n_restarts_optimizer=2)
```
!!! Note !!! Note
While custom estimators can be provided, it's up to you as User to do research on possible parameters and analyze / understand which ones should be used. While custom estimators can be provided, it's up to you as User to do research on possible parameters and analyze / understand which ones should be used.
If you're unsure about this, best use one of the Defaults (`"ET"` has proven to be the most versatile) without further parameters. If you're unsure about this, best use one of the Defaults (`"ET"` has proven to be the most versatile) without further parameters.

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@ -175,6 +175,7 @@ Mandatory parameters are marked as **Required**, which means that they are requi
| `dataformat_ohlcv` | Data format to use to store historical candle (OHLCV) data. <br> *Defaults to `json`*. <br> **Datatype:** String | `dataformat_ohlcv` | Data format to use to store historical candle (OHLCV) data. <br> *Defaults to `json`*. <br> **Datatype:** String
| `dataformat_trades` | Data format to use to store historical trades data. <br> *Defaults to `jsongz`*. <br> **Datatype:** String | `dataformat_trades` | Data format to use to store historical trades data. <br> *Defaults to `jsongz`*. <br> **Datatype:** String
| `position_adjustment_enable` | Enables the strategy to use position adjustments (additional buys or sells). [More information here](strategy-callbacks.md#adjust-trade-position). <br> [Strategy Override](#parameters-in-the-strategy). <br>*Defaults to `false`.*<br> **Datatype:** Boolean | `position_adjustment_enable` | Enables the strategy to use position adjustments (additional buys or sells). [More information here](strategy-callbacks.md#adjust-trade-position). <br> [Strategy Override](#parameters-in-the-strategy). <br>*Defaults to `false`.*<br> **Datatype:** Boolean
| `max_entry_position_adjustment` | Maximum additional order(s) for each open trade on top of the first entry Order. Set it to `-1` for unlimited additional orders. [More information here](strategy-callbacks.md#adjust-trade-position). <br> [Strategy Override](#parameters-in-the-strategy). <br>*Defaults to `-1`.*<br> **Datatype:** Positive Integer or -1
### Parameters in the strategy ### Parameters in the strategy
@ -200,6 +201,7 @@ Values set in the configuration file always overwrite values set in the strategy
* `ignore_roi_if_buy_signal` * `ignore_roi_if_buy_signal`
* `ignore_buying_expired_candle_after` * `ignore_buying_expired_candle_after`
* `position_adjustment_enable` * `position_adjustment_enable`
* `max_entry_position_adjustment`
### Configuring amount per trade ### Configuring amount per trade

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@ -126,6 +126,12 @@ All freqtrade arguments will be available by running `docker-compose run --rm fr
!!! Note "`docker-compose run --rm`" !!! Note "`docker-compose run --rm`"
Including `--rm` will remove the container after completion, and is highly recommended for all modes except trading mode (running with `freqtrade trade` command). Including `--rm` will remove the container after completion, and is highly recommended for all modes except trading mode (running with `freqtrade trade` command).
??? Note "Using docker without docker-compose"
"`docker-compose run --rm`" will require a compose file to be provided.
Some freqtrade commands that don't require authentication such as `list-pairs` can be run with "`docker run --rm`" instead.
For example `docker run --rm freqtradeorg/freqtrade:stable list-pairs --exchange binance --quote BTC --print-json`.
This can be useful for fetching exchange information to add to your `config.json` without affecting your running containers.
#### Example: Download data with docker-compose #### Example: Download data with docker-compose
Download backtesting data for 5 days for the pair ETH/BTC and 1h timeframe from Binance. The data will be stored in the directory `user_data/data/` on the host. Download backtesting data for 5 days for the pair ETH/BTC and 1h timeframe from Binance. The data will be stored in the directory `user_data/data/` on the host.

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@ -11,7 +11,7 @@
## Introduction ## Introduction
Freqtrade is a crypto-currency algorithmic trading software developed in python (3.7+) and supported on Windows, macOS and Linux. Freqtrade is a crypto-currency algorithmic trading software developed in python (3.8+) and supported on Windows, macOS and Linux.
!!! Danger "DISCLAIMER" !!! Danger "DISCLAIMER"
This software is for educational purposes only. Do not risk money which you are afraid to lose. USE THE SOFTWARE AT YOUR OWN RISK. THE AUTHORS AND ALL AFFILIATES ASSUME NO RESPONSIBILITY FOR YOUR TRADING RESULTS. This software is for educational purposes only. Do not risk money which you are afraid to lose. USE THE SOFTWARE AT YOUR OWN RISK. THE AUTHORS AND ALL AFFILIATES ASSUME NO RESPONSIBILITY FOR YOUR TRADING RESULTS.
@ -67,7 +67,7 @@ To run this bot we recommend you a linux cloud instance with a minimum of:
Alternatively Alternatively
- Python 3.7+ - Python 3.8+
- pip (pip3) - pip (pip3)
- git - git
- TA-Lib - TA-Lib

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@ -42,7 +42,7 @@ These requirements apply to both [Script Installation](#script-installation) and
### Install guide ### Install guide
* [Python >= 3.7.x](http://docs.python-guide.org/en/latest/starting/installation/) * [Python >= 3.8.x](http://docs.python-guide.org/en/latest/starting/installation/)
* [pip](https://pip.pypa.io/en/stable/installing/) * [pip](https://pip.pypa.io/en/stable/installing/)
* [git](https://git-scm.com/book/en/v2/Getting-Started-Installing-Git) * [git](https://git-scm.com/book/en/v2/Getting-Started-Installing-Git)
* [virtualenv](https://virtualenv.pypa.io/en/stable/installation.html) (Recommended) * [virtualenv](https://virtualenv.pypa.io/en/stable/installation.html) (Recommended)

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@ -1,4 +1,4 @@
mkdocs==1.2.3 mkdocs==1.2.3
mkdocs-material==8.1.7 mkdocs-material==8.1.8
mdx_truly_sane_lists==1.2 mdx_truly_sane_lists==1.2
pymdown-extensions==9.1 pymdown-extensions==9.1

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@ -363,8 +363,8 @@ class AwesomeStrategy(IStrategy):
# ... populate_* methods # ... populate_* methods
def custom_entry_price(self, pair: str, current_time: datetime, def custom_entry_price(self, pair: str, current_time: datetime, proposed_rate: float,
proposed_rate, **kwargs) -> float: entry_tag: Optional[str], **kwargs) -> float:
dataframe, last_updated = self.dp.get_analyzed_dataframe(pair=pair, dataframe, last_updated = self.dp.get_analyzed_dataframe(pair=pair,
timeframe=self.timeframe) timeframe=self.timeframe)
@ -414,7 +414,7 @@ It applies a tight timeout for higher priced assets, while allowing more time to
The function must return either `True` (cancel order) or `False` (keep order alive). The function must return either `True` (cancel order) or `False` (keep order alive).
``` python ``` python
from datetime import datetime, timedelta, timezone from datetime import datetime, timedelta
from freqtrade.persistence import Trade from freqtrade.persistence import Trade
class AwesomeStrategy(IStrategy): class AwesomeStrategy(IStrategy):
@ -427,22 +427,24 @@ class AwesomeStrategy(IStrategy):
'sell': 60 * 25 'sell': 60 * 25
} }
def check_buy_timeout(self, pair: str, trade: 'Trade', order: dict, **kwargs) -> bool: def check_buy_timeout(self, pair: str, trade: 'Trade', order: dict,
if trade.open_rate > 100 and trade.open_date_utc < datetime.now(timezone.utc) - timedelta(minutes=5): current_time: datetime, **kwargs) -> bool:
if trade.open_rate > 100 and trade.open_date_utc < current_time - timedelta(minutes=5):
return True return True
elif trade.open_rate > 10 and trade.open_date_utc < datetime.now(timezone.utc) - timedelta(minutes=3): elif trade.open_rate > 10 and trade.open_date_utc < current_time - timedelta(minutes=3):
return True return True
elif trade.open_rate < 1 and trade.open_date_utc < datetime.now(timezone.utc) - timedelta(hours=24): elif trade.open_rate < 1 and trade.open_date_utc < current_time - timedelta(hours=24):
return True return True
return False return False
def check_sell_timeout(self, pair: str, trade: 'Trade', order: dict, **kwargs) -> bool: def check_sell_timeout(self, pair: str, trade: Trade, order: dict,
if trade.open_rate > 100 and trade.open_date_utc < datetime.now(timezone.utc) - timedelta(minutes=5): current_time: datetime, **kwargs) -> bool:
if trade.open_rate > 100 and trade.open_date_utc < current_time - timedelta(minutes=5):
return True return True
elif trade.open_rate > 10 and trade.open_date_utc < datetime.now(timezone.utc) - timedelta(minutes=3): elif trade.open_rate > 10 and trade.open_date_utc < current_time - timedelta(minutes=3):
return True return True
elif trade.open_rate < 1 and trade.open_date_utc < datetime.now(timezone.utc) - timedelta(hours=24): elif trade.open_rate < 1 and trade.open_date_utc < current_time - timedelta(hours=24):
return True return True
return False return False
``` ```
@ -501,7 +503,7 @@ class AwesomeStrategy(IStrategy):
# ... populate_* methods # ... populate_* methods
def confirm_trade_entry(self, pair: str, order_type: str, amount: float, rate: float, def confirm_trade_entry(self, pair: str, order_type: str, amount: float, rate: float,
time_in_force: str, current_time: datetime, time_in_force: str, current_time: datetime, entry_tag: Optional[str],
side: str, **kwargs) -> bool: side: str, **kwargs) -> bool:
""" """
Called right before placing a entry order. Called right before placing a entry order.
@ -579,11 +581,13 @@ The `position_adjustment_enable` strategy property enables the usage of `adjust_
For performance reasons, it's disabled by default and freqtrade will show a warning message on startup if enabled. For performance reasons, it's disabled by default and freqtrade will show a warning message on startup if enabled.
`adjust_trade_position()` can be used to perform additional orders, for example to manage risk with DCA (Dollar Cost Averaging). `adjust_trade_position()` can be used to perform additional orders, for example to manage risk with DCA (Dollar Cost Averaging).
`max_entry_position_adjustment` property is used to limit the number of additional buys per trade (on top of the first buy) that the bot can execute. By default, the value is -1 which means the bot have no limit on number of adjustment buys.
The strategy is expected to return a stake_amount (in stake currency) between `min_stake` and `max_stake` if and when an additional buy order should be made (position is increased). The strategy is expected to return a stake_amount (in stake currency) between `min_stake` and `max_stake` if and when an additional buy order should be made (position is increased).
If there are not enough funds in the wallet (the return value is above `max_stake`) then the signal will be ignored. If there are not enough funds in the wallet (the return value is above `max_stake`) then the signal will be ignored.
Additional orders also result in additional fees and those orders don't count towards `max_open_trades`. Additional orders also result in additional fees and those orders don't count towards `max_open_trades`.
This callback is **not** called when there is an open order (either buy or sell) waiting for execution. This callback is **not** called when there is an open order (either buy or sell) waiting for execution, or when you have reached the maximum amount of extra buys that you have set on `max_entry_position_adjustment`.
`adjust_trade_position()` is called very frequently for the duration of a trade, so you must keep your implementation as performant as possible. `adjust_trade_position()` is called very frequently for the duration of a trade, so you must keep your implementation as performant as possible.
!!! Note "About stake size" !!! Note "About stake size"
@ -614,14 +618,14 @@ class DigDeeperStrategy(IStrategy):
# ... populate_* methods # ... populate_* methods
# Example specific variables # Example specific variables
max_dca_orders = 3 max_entry_position_adjustment = 3
# This number is explained a bit further down # This number is explained a bit further down
max_dca_multiplier = 5.5 max_dca_multiplier = 5.5
# This is called when placing the initial order (opening trade) # This is called when placing the initial order (opening trade)
def custom_stake_amount(self, pair: str, current_time: datetime, current_rate: float, def custom_stake_amount(self, pair: str, current_time: datetime, current_rate: float,
proposed_stake: float, min_stake: float, max_stake: float, proposed_stake: float, min_stake: float, max_stake: float,
**kwargs) -> float: entry_tag: Optional[str], **kwargs) -> float:
# We need to leave most of the funds for possible further DCA orders # We need to leave most of the funds for possible further DCA orders
# This also applies to fixed stakes # This also applies to fixed stakes
@ -656,8 +660,7 @@ class DigDeeperStrategy(IStrategy):
return None return None
filled_buys = trade.select_filled_orders('buy') filled_buys = trade.select_filled_orders('buy')
count_of_buys = len(filled_buys) count_of_buys = trade.nr_of_successful_buys
# Allow up to 3 additional increasingly larger buys (4 in total) # Allow up to 3 additional increasingly larger buys (4 in total)
# Initial buy is 1x # Initial buy is 1x
# If that falls to -5% profit, we buy 1.25x more, average profit should increase to roughly -2.2% # If that falls to -5% profit, we buy 1.25x more, average profit should increase to roughly -2.2%
@ -666,7 +669,6 @@ class DigDeeperStrategy(IStrategy):
# Total stake for this trade would be 1 + 1.25 + 1.5 + 1.75 = 5.5x of the initial allowed stake. # Total stake for this trade would be 1 + 1.25 + 1.5 + 1.75 = 5.5x of the initial allowed stake.
# That is why max_dca_multiplier is 5.5 # That is why max_dca_multiplier is 5.5
# Hope you have a deep wallet! # Hope you have a deep wallet!
if 0 < count_of_buys <= self.max_dca_orders:
try: try:
# This returns first order stake size # This returns first order stake size
stake_amount = filled_buys[0].cost stake_amount = filled_buys[0].cost

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@ -25,7 +25,7 @@ Install ta-lib according to the [ta-lib documentation](https://github.com/mrjbq7
As compiling from source on windows has heavy dependencies (requires a partial visual studio installation), there is also a repository of unofficial pre-compiled windows Wheels [here](https://www.lfd.uci.edu/~gohlke/pythonlibs/#ta-lib), which need to be downloaded and installed using `pip install TA_Lib-0.4.24-cp38-cp38-win_amd64.whl` (make sure to use the version matching your python version). As compiling from source on windows has heavy dependencies (requires a partial visual studio installation), there is also a repository of unofficial pre-compiled windows Wheels [here](https://www.lfd.uci.edu/~gohlke/pythonlibs/#ta-lib), which need to be downloaded and installed using `pip install TA_Lib-0.4.24-cp38-cp38-win_amd64.whl` (make sure to use the version matching your python version).
Freqtrade provides these dependencies for the latest 3 Python versions (3.7, 3.8, 3.9 and 3.10) and for 64bit Windows. Freqtrade provides these dependencies for the latest 3 Python versions (3.8, 3.9 and 3.10) and for 64bit Windows.
Other versions must be downloaded from the above link. Other versions must be downloaded from the above link.
``` powershell ``` powershell

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@ -4,7 +4,7 @@ channels:
# - defaults # - defaults
dependencies: dependencies:
# 1/4 req main # 1/4 req main
- python>=3.7,<3.9 - python>=3.8,<=3.10
- numpy - numpy
- pandas - pandas
- pip - pip
@ -25,10 +25,14 @@ dependencies:
- fastapi - fastapi
- uvicorn - uvicorn
- pyjwt - pyjwt
- aiofiles
- psutil
- colorama - colorama
- questionary - questionary
- prompt-toolkit - prompt-toolkit
- schedule - schedule
- python-dateutil
# ============================ # ============================
# 2/4 req dev # 2/4 req dev

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@ -3,7 +3,7 @@
__main__.py for Freqtrade __main__.py for Freqtrade
To launch Freqtrade as a module To launch Freqtrade as a module
> python -m freqtrade (with Python >= 3.7) > python -m freqtrade (with Python >= 3.8)
""" """
from freqtrade import main from freqtrade import main

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@ -377,7 +377,9 @@ CONF_SCHEMA = {
'type': 'string', 'type': 'string',
'enum': AVAILABLE_DATAHANDLERS, 'enum': AVAILABLE_DATAHANDLERS,
'default': 'jsongz' 'default': 'jsongz'
} },
'position_adjustment_enable': {'type': 'boolean'},
'max_entry_position_adjustment': {'type': ['integer', 'number'], 'minimum': -1},
}, },
'definitions': { 'definitions': {
'exchange': { 'exchange': {

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@ -1114,7 +1114,7 @@ class Exchange:
raise OperationalException(e) from e raise OperationalException(e) from e
@retrier @retrier
def get_tickers(self, cached: bool = False) -> Dict: def get_tickers(self, symbols: List[str] = None, cached: bool = False) -> Dict:
""" """
:param cached: Allow cached result :param cached: Allow cached result
:return: fetch_tickers result :return: fetch_tickers result
@ -1124,7 +1124,7 @@ class Exchange:
if tickers: if tickers:
return tickers return tickers
try: try:
tickers = self._api.fetch_tickers() tickers = self._api.fetch_tickers(symbols)
self._fetch_tickers_cache['fetch_tickers'] = tickers self._fetch_tickers_cache['fetch_tickers'] = tickers
return tickers return tickers
except ccxt.NotSupported as e: except ccxt.NotSupported as e:

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@ -43,6 +43,12 @@ class Kraken(Exchange):
return (parent_check and return (parent_check and
market.get('darkpool', False) is False) market.get('darkpool', False) is False)
def get_tickers(self, symbols: List[str] = None, cached: bool = False) -> Dict:
# Only fetch tickers for current stake currency
# Otherwise the request for kraken becomes too large.
symbols = list(self.get_markets(quote_currencies=[self._config['stake_currency']]))
return super().get_tickers(symbols=symbols, cached=cached)
@retrier @retrier
def get_balances(self) -> dict: def get_balances(self) -> dict:
if self._config['dry_run']: if self._config['dry_run']:

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@ -9,7 +9,6 @@ from math import isclose
from threading import Lock from threading import Lock
from typing import Any, Dict, List, Optional, Tuple from typing import Any, Dict, List, Optional, Tuple
import arrow
from schedule import Scheduler from schedule import Scheduler
from freqtrade import __version__, constants from freqtrade import __version__, constants
@ -521,8 +520,8 @@ class FreqtradeBot(LoggingMixin):
try: try:
self.check_and_call_adjust_trade_position(trade) self.check_and_call_adjust_trade_position(trade)
except DependencyException as exception: except DependencyException as exception:
logger.warning('Unable to adjust position of trade for %s: %s', logger.warning(
trade.pair, exception) f"Unable to adjust position of trade for {trade.pair}: {exception}")
def check_and_call_adjust_trade_position(self, trade: Trade): def check_and_call_adjust_trade_position(self, trade: Trade):
""" """
@ -531,6 +530,13 @@ class FreqtradeBot(LoggingMixin):
Once that completes, the existing trade is modified to match new data. Once that completes, the existing trade is modified to match new data.
""" """
# TODO-lev: Check what changes are necessary for DCA in relation to shorts. # TODO-lev: Check what changes are necessary for DCA in relation to shorts.
if self.strategy.max_entry_position_adjustment > -1:
count_of_buys = trade.nr_of_successful_buys
if count_of_buys > self.strategy.max_entry_position_adjustment:
logger.debug(f"Max adjustment entries for {trade.pair} has been reached.")
return
else:
logger.debug("Max adjustment entries is set to unlimited.")
current_rate = self.exchange.get_rate(trade.pair, refresh=True, side="buy") current_rate = self.exchange.get_rate(trade.pair, refresh=True, side="buy")
current_profit = trade.calc_profit_ratio(current_rate) current_profit = trade.calc_profit_ratio(current_rate)
@ -649,7 +655,7 @@ class FreqtradeBot(LoggingMixin):
pos_adjust = trade is not None pos_adjust = trade is not None
enter_limit_requested, stake_amount = self.get_valid_enter_price_and_stake( enter_limit_requested, stake_amount = self.get_valid_enter_price_and_stake(
pair, price, stake_amount, side, trade_side, trade) pair, price, stake_amount, side, trade_side, enter_tag, trade)
if not stake_amount: if not stake_amount:
return False return False
@ -680,8 +686,7 @@ class FreqtradeBot(LoggingMixin):
self.strategy.confirm_trade_entry, default_retval=True)( self.strategy.confirm_trade_entry, default_retval=True)(
pair=pair, order_type=order_type, amount=amount, rate=enter_limit_requested, pair=pair, order_type=order_type, amount=amount, rate=enter_limit_requested,
time_in_force=time_in_force, current_time=datetime.now(timezone.utc), time_in_force=time_in_force, current_time=datetime.now(timezone.utc),
side=trade_side entry_tag=enter_tag, side=trade_side):
):
logger.info(f"User requested abortion of buying {pair}") logger.info(f"User requested abortion of buying {pair}")
return False return False
amount = self.exchange.amount_to_precision(pair, amount) amount = self.exchange.amount_to_precision(pair, amount)
@ -814,6 +819,7 @@ class FreqtradeBot(LoggingMixin):
def get_valid_enter_price_and_stake( def get_valid_enter_price_and_stake(
self, pair: str, price: Optional[float], stake_amount: float, self, pair: str, price: Optional[float], stake_amount: float,
side: str, trade_side: str, side: str, trade_side: str,
entry_tag: Optional[str],
trade: Optional[Trade]) -> Tuple[float, float]: trade: Optional[Trade]) -> Tuple[float, float]:
if price: if price:
enter_limit_requested = price enter_limit_requested = price
@ -823,7 +829,7 @@ class FreqtradeBot(LoggingMixin):
custom_entry_price = strategy_safe_wrapper(self.strategy.custom_entry_price, custom_entry_price = strategy_safe_wrapper(self.strategy.custom_entry_price,
default_retval=proposed_enter_rate)( default_retval=proposed_enter_rate)(
pair=pair, current_time=datetime.now(timezone.utc), pair=pair, current_time=datetime.now(timezone.utc),
proposed_rate=proposed_enter_rate) proposed_rate=proposed_enter_rate, entry_tag=entry_tag)
enter_limit_requested = self.get_valid_price(custom_entry_price, proposed_enter_rate) enter_limit_requested = self.get_valid_price(custom_entry_price, proposed_enter_rate)
@ -844,7 +850,7 @@ class FreqtradeBot(LoggingMixin):
pair=pair, current_time=datetime.now(timezone.utc), pair=pair, current_time=datetime.now(timezone.utc),
current_rate=enter_limit_requested, proposed_stake=stake_amount, current_rate=enter_limit_requested, proposed_stake=stake_amount,
min_stake=min_stake_amount, max_stake=max_stake_amount, min_stake=min_stake_amount, max_stake=max_stake_amount,
side=trade_side entry_tag=entry_tag, side=trade_side
) )
stake_amount = self.wallets.validate_stake_amount(pair, stake_amount, min_stake_amount) stake_amount = self.wallets.validate_stake_amount(pair, stake_amount, min_stake_amount)
@ -1145,20 +1151,6 @@ class FreqtradeBot(LoggingMixin):
return True return True
return False return False
def _check_timed_out(self, side: str, order: dict) -> bool:
"""
Check if timeout is active, and if the order is still open and timed out
"""
timeout = self.config.get('unfilledtimeout', {}).get(side)
ordertime = arrow.get(order['datetime']).datetime
if timeout is not None:
timeout_unit = self.config.get('unfilledtimeout', {}).get('unit', 'minutes')
timeout_kwargs = {timeout_unit: -timeout}
timeout_threshold = arrow.utcnow().shift(**timeout_kwargs).datetime
return (order['status'] == 'open' and order['side'] == side
and ordertime < timeout_threshold)
return False
def check_handle_timedout(self) -> None: def check_handle_timedout(self) -> None:
""" """
Check if any orders are timed out and cancel if necessary Check if any orders are timed out and cancel if necessary
@ -1178,18 +1170,12 @@ class FreqtradeBot(LoggingMixin):
fully_cancelled = self.update_trade_state(trade, trade.open_order_id, order) fully_cancelled = self.update_trade_state(trade, trade.open_order_id, order)
is_entering = order['side'] == trade.enter_side is_entering = order['side'] == trade.enter_side
not_closed = order['status'] == 'open' or fully_cancelled not_closed = order['status'] == 'open' or fully_cancelled
side = trade.enter_side if is_entering else trade.exit_side time_method = 'sell' if order['side'] == 'sell' else 'buy'
timed_out = self._check_timed_out(side, order)
time_method = 'check_sell_timeout' if order['side'] == 'sell' else 'check_buy_timeout'
max_timeouts = self.config.get('unfilledtimeout', {}).get('exit_timeout_count', 0) max_timeouts = self.config.get('unfilledtimeout', {}).get('exit_timeout_count', 0)
if not_closed and (fully_cancelled or timed_out or ( if not_closed and (fully_cancelled or self.strategy.ft_check_timed_out(
strategy_safe_wrapper(getattr(self.strategy, time_method), default_retval=False)( time_method, trade, order, datetime.now(timezone.utc))
pair=trade.pair, ):
trade=trade,
order=order
)
)):
if is_entering: if is_entering:
self.handle_cancel_enter(trade, order, constants.CANCEL_REASON['TIMEOUT']) self.handle_cancel_enter(trade, order, constants.CANCEL_REASON['TIMEOUT'])
else: else:

View File

@ -9,8 +9,8 @@ from typing import Any, List
# check min. python version # check min. python version
if sys.version_info < (3, 7): # pragma: no cover if sys.version_info < (3, 8): # pragma: no cover
sys.exit("Freqtrade requires Python version >= 3.7") sys.exit("Freqtrade requires Python version >= 3.8")
from freqtrade.commands import Arguments from freqtrade.commands import Arguments
from freqtrade.exceptions import FreqtradeException, OperationalException from freqtrade.exceptions import FreqtradeException, OperationalException

View File

@ -434,6 +434,11 @@ class Backtesting:
# Check if we need to adjust our current positions # Check if we need to adjust our current positions
if self.strategy.position_adjustment_enable: if self.strategy.position_adjustment_enable:
check_adjust_buy = True
if self.strategy.max_entry_position_adjustment > -1:
count_of_buys = trade.nr_of_successful_buys
check_adjust_buy = (count_of_buys <= self.strategy.max_entry_position_adjustment)
if check_adjust_buy:
trade = self._get_adjust_trade_entry_for_candle(trade, sell_row) trade = self._get_adjust_trade_entry_for_candle(trade, sell_row)
sell_candle_time: datetime = sell_row[DATE_IDX].to_pydatetime() sell_candle_time: datetime = sell_row[DATE_IDX].to_pydatetime()
@ -533,12 +538,14 @@ class Backtesting:
def _enter_trade(self, pair: str, row: Tuple, direction: str, def _enter_trade(self, pair: str, row: Tuple, direction: str,
stake_amount: Optional[float] = None, stake_amount: Optional[float] = None,
trade: Optional[LocalTrade] = None) -> Optional[LocalTrade]: trade: Optional[LocalTrade] = None) -> Optional[LocalTrade]:
current_time = row[DATE_IDX].to_pydatetime() current_time = row[DATE_IDX].to_pydatetime()
entry_tag = row[ENTER_TAG_IDX] if len(row) >= ENTER_TAG_IDX + 1 else None
# let's call the custom entry price, using the open price as default price # let's call the custom entry price, using the open price as default price
propose_rate = strategy_safe_wrapper(self.strategy.custom_entry_price, propose_rate = strategy_safe_wrapper(self.strategy.custom_entry_price,
default_retval=row[OPEN_IDX])( default_retval=row[OPEN_IDX])(
pair=pair, current_time=current_time, pair=pair, current_time=current_time,
proposed_rate=row[OPEN_IDX]) # default value is the open rate proposed_rate=row[OPEN_IDX], entry_tag=entry_tag) # default value is the open rate
# Move rate to within the candle's low/high rate # Move rate to within the candle's low/high rate
propose_rate = min(max(propose_rate, row[LOW_IDX]), row[HIGH_IDX]) propose_rate = min(max(propose_rate, row[LOW_IDX]), row[HIGH_IDX])
@ -557,7 +564,7 @@ class Backtesting:
default_retval=stake_amount)( default_retval=stake_amount)(
pair=pair, current_time=current_time, current_rate=propose_rate, pair=pair, current_time=current_time, current_rate=propose_rate,
proposed_stake=stake_amount, min_stake=min_stake_amount, max_stake=max_stake_amount, proposed_stake=stake_amount, min_stake=min_stake_amount, max_stake=max_stake_amount,
side=direction) entry_tag=entry_tag, side=direction)
stake_amount = self.wallets.validate_stake_amount(pair, stake_amount, min_stake_amount) stake_amount = self.wallets.validate_stake_amount(pair, stake_amount, min_stake_amount)
@ -585,14 +592,13 @@ class Backtesting:
if not strategy_safe_wrapper(self.strategy.confirm_trade_entry, default_retval=True)( if not strategy_safe_wrapper(self.strategy.confirm_trade_entry, default_retval=True)(
pair=pair, order_type=order_type, amount=stake_amount, rate=propose_rate, pair=pair, order_type=order_type, amount=stake_amount, rate=propose_rate,
time_in_force=time_in_force, current_time=current_time, time_in_force=time_in_force, current_time=current_time,
side=direction): entry_tag=entry_tag, side=direction):
return None return None
if stake_amount and (not min_stake_amount or stake_amount > min_stake_amount): if stake_amount and (not min_stake_amount or stake_amount > min_stake_amount):
amount = round((stake_amount / propose_rate) * leverage, 8) amount = round((stake_amount / propose_rate) * leverage, 8)
if trade is None: if trade is None:
# Enter trade # Enter trade
has_buy_tag = len(row) >= ENTER_TAG_IDX + 1
trade = LocalTrade( trade = LocalTrade(
pair=pair, pair=pair,
open_rate=propose_rate, open_rate=propose_rate,
@ -602,7 +608,7 @@ class Backtesting:
fee_open=self.fee, fee_open=self.fee,
fee_close=self.fee, fee_close=self.fee,
is_open=True, is_open=True,
enter_tag=row[ENTER_TAG_IDX] if has_buy_tag else None, enter_tag=entry_tag,
exchange=self._exchange_name, exchange=self._exchange_name,
is_short=(direction == 'short'), is_short=(direction == 'short'),
trading_mode=self.trading_mode, trading_mode=self.trading_mode,
@ -619,6 +625,9 @@ class Backtesting:
side="buy", side="buy",
order_type="market", order_type="market",
status="closed", status="closed",
order_date=current_time,
order_filled_date=current_time,
order_update_date=current_time,
price=propose_rate, price=propose_rate,
average=propose_rate, average=propose_rate,
amount=amount, amount=amount,

View File

@ -367,7 +367,7 @@ class Hyperopt:
} }
def get_optimizer(self, dimensions: List[Dimension], cpu_count) -> Optimizer: def get_optimizer(self, dimensions: List[Dimension], cpu_count) -> Optimizer:
estimator = self.custom_hyperopt.generate_estimator() estimator = self.custom_hyperopt.generate_estimator(dimensions=dimensions)
acq_optimizer = "sampling" acq_optimizer = "sampling"
if isinstance(estimator, str): if isinstance(estimator, str):

View File

@ -91,5 +91,5 @@ class HyperOptAuto(IHyperOpt):
def trailing_space(self) -> List['Dimension']: def trailing_space(self) -> List['Dimension']:
return self._get_func('trailing_space')() return self._get_func('trailing_space')()
def generate_estimator(self) -> EstimatorType: def generate_estimator(self, dimensions: List['Dimension'], **kwargs) -> EstimatorType:
return self._get_func('generate_estimator')() return self._get_func('generate_estimator')(dimensions=dimensions, **kwargs)

View File

@ -40,7 +40,7 @@ class IHyperOpt(ABC):
IHyperOpt.ticker_interval = str(config['timeframe']) # DEPRECATED IHyperOpt.ticker_interval = str(config['timeframe']) # DEPRECATED
IHyperOpt.timeframe = str(config['timeframe']) IHyperOpt.timeframe = str(config['timeframe'])
def generate_estimator(self) -> EstimatorType: def generate_estimator(self, dimensions: List[Dimension], **kwargs) -> EstimatorType:
""" """
Return base_estimator. Return base_estimator.
Can be any of "GP", "RF", "ET", "GBRT" or an instance of a class Can be any of "GP", "RF", "ET", "GBRT" or an instance of a class

View File

@ -804,18 +804,19 @@ class LocalTrade():
total_amount = 0.0 total_amount = 0.0
total_stake = 0.0 total_stake = 0.0
for temp_order in self.orders: for o in self.orders:
if (temp_order.ft_is_open or if (o.ft_is_open or
(temp_order.ft_order_side != self.enter_side) or (o.ft_order_side != self.enter_side) or
(temp_order.status not in NON_OPEN_EXCHANGE_STATES)): (o.status not in NON_OPEN_EXCHANGE_STATES)):
continue continue
tmp_amount = temp_order.amount tmp_amount = o.amount
if temp_order.filled is not None: tmp_price = o.average or o.price
tmp_amount = temp_order.filled if o.filled is not None:
if tmp_amount > 0.0 and temp_order.average is not None: tmp_amount = o.filled
if tmp_amount > 0.0 and tmp_price is not None:
total_amount += tmp_amount total_amount += tmp_amount
total_stake += temp_order.average * tmp_amount total_stake += tmp_price * tmp_amount
if total_amount > 0: if total_amount > 0:
self.open_rate = total_stake / total_amount self.open_rate = total_stake / total_amount

View File

@ -97,7 +97,8 @@ class StrategyResolver(IResolver):
("sell_profit_offset", 0.0), ("sell_profit_offset", 0.0),
("disable_dataframe_checks", False), ("disable_dataframe_checks", False),
("ignore_buying_expired_candle_after", 0), ("ignore_buying_expired_candle_after", 0),
("position_adjustment_enable", False) ("position_adjustment_enable", False),
("max_entry_position_adjustment", -1),
] ]
for attribute, default in attributes: for attribute, default in attributes:
StrategyResolver._override_attribute_helper(strategy, config, StrategyResolver._override_attribute_helper(strategy, config,

View File

@ -175,6 +175,8 @@ class ShowConfig(BaseModel):
bot_name: str bot_name: str
state: str state: str
runmode: str runmode: str
position_adjustment_enable: bool
max_entry_position_adjustment: int
class TradeSchema(BaseModel): class TradeSchema(BaseModel):

View File

@ -77,6 +77,9 @@ class CryptoToFiatConverter:
else: else:
return None return None
found = [x for x in self._coinlistings if x['symbol'] == crypto_symbol] found = [x for x in self._coinlistings if x['symbol'] == crypto_symbol]
if crypto_symbol == 'eth':
found = [x for x in self._coinlistings if x['id'] == 'ethereum']
if len(found) == 1: if len(found) == 1:
return found[0]['id'] return found[0]['id']

View File

@ -138,7 +138,12 @@ class RPC:
'ask_strategy': config.get('ask_strategy', {}), 'ask_strategy': config.get('ask_strategy', {}),
'bid_strategy': config.get('bid_strategy', {}), 'bid_strategy': config.get('bid_strategy', {}),
'state': str(botstate), 'state': str(botstate),
'runmode': config['runmode'].value 'runmode': config['runmode'].value,
'position_adjustment_enable': config.get('position_adjustment_enable', False),
'max_entry_position_adjustment': (
config.get('max_entry_position_adjustment', -1)
if config.get('max_entry_position_adjustment') != float('inf')
else -1)
} }
return val return val
@ -252,8 +257,9 @@ class RPC:
profit_str profit_str
] ]
if self._config.get('position_adjustment_enable', False): if self._config.get('position_adjustment_enable', False):
filled_buys = trade.select_filled_orders('buy') max_buy = self._config['max_entry_position_adjustment'] + 1
detail_trade.append(str(len(filled_buys))) filled_buys = trade.nr_of_successful_buys
detail_trade.append(f"{filled_buys}/{max_buy}")
trades_list.append(detail_trade) trades_list.append(detail_trade)
profitcol = "Profit" profitcol = "Profit"
if self._fiat_converter: if self._fiat_converter:

View File

@ -1363,6 +1363,14 @@ class Telegram(RPCHandler):
else: else:
sl_info = f"*Stoploss:* `{val['stoploss']}`\n" sl_info = f"*Stoploss:* `{val['stoploss']}`\n"
if val['position_adjustment_enable']:
pa_info = (
f"*Position adjustment:* On\n"
f"*Max enter position adjustment:* `{val['max_entry_position_adjustment']}`\n"
)
else:
pa_info = "*Position adjustment:* Off\n"
self._send_msg( self._send_msg(
f"*Mode:* `{'Dry-run' if val['dry_run'] else 'Live'}`\n" f"*Mode:* `{'Dry-run' if val['dry_run'] else 'Live'}`\n"
f"*Exchange:* `{val['exchange']}`\n" f"*Exchange:* `{val['exchange']}`\n"
@ -1372,6 +1380,7 @@ class Telegram(RPCHandler):
f"*Ask strategy:* ```\n{json.dumps(val['ask_strategy'])}```\n" f"*Ask strategy:* ```\n{json.dumps(val['ask_strategy'])}```\n"
f"*Bid strategy:* ```\n{json.dumps(val['bid_strategy'])}```\n" f"*Bid strategy:* ```\n{json.dumps(val['bid_strategy'])}```\n"
f"{sl_info}" f"{sl_info}"
f"{pa_info}"
f"*Timeframe:* `{val['timeframe']}`\n" f"*Timeframe:* `{val['timeframe']}`\n"
f"*Strategy:* `{val['strategy']}`\n" f"*Strategy:* `{val['strategy']}`\n"
f"*Current state:* `{val['state']}`" f"*Current state:* `{val['state']}`"

View File

@ -108,6 +108,7 @@ class IStrategy(ABC, HyperStrategyMixin):
# Position adjustment is disabled by default # Position adjustment is disabled by default
position_adjustment_enable: bool = False position_adjustment_enable: bool = False
max_entry_position_adjustment: int = -1
# Number of seconds after which the candle will no longer result in a buy on expired candles # Number of seconds after which the candle will no longer result in a buy on expired candles
ignore_buying_expired_candle_after: int = 0 ignore_buying_expired_candle_after: int = 0
@ -188,7 +189,17 @@ class IStrategy(ABC, HyperStrategyMixin):
""" """
return dataframe return dataframe
def check_buy_timeout(self, pair: str, trade: Trade, order: dict, **kwargs) -> bool: def bot_loop_start(self, **kwargs) -> None:
"""
Called at the start of the bot iteration (one loop).
Might be used to perform pair-independent tasks
(e.g. gather some remote resource for comparison)
:param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
"""
pass
def check_buy_timeout(self, pair: str, trade: Trade, order: dict,
current_time: datetime, **kwargs) -> bool:
""" """
Check buy timeout function callback. Check buy timeout function callback.
This method can be used to override the enter-timeout. This method can be used to override the enter-timeout.
@ -201,12 +212,14 @@ class IStrategy(ABC, HyperStrategyMixin):
:param pair: Pair the trade is for :param pair: Pair the trade is for
:param trade: trade object. :param trade: trade object.
:param order: Order dictionary as returned from CCXT. :param order: Order dictionary as returned from CCXT.
:param current_time: datetime object, containing the current datetime
:param **kwargs: Ensure to keep this here so updates to this won't break your strategy. :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
:return bool: When True is returned, then the entry order is cancelled. :return bool: When True is returned, then the entry order is cancelled.
""" """
return False return False
def check_sell_timeout(self, pair: str, trade: Trade, order: dict, **kwargs) -> bool: def check_sell_timeout(self, pair: str, trade: Trade, order: dict,
current_time: datetime, **kwargs) -> bool:
""" """
Check sell timeout function callback. Check sell timeout function callback.
This method can be used to override the exit-timeout. This method can be used to override the exit-timeout.
@ -219,22 +232,14 @@ class IStrategy(ABC, HyperStrategyMixin):
:param pair: Pair the trade is for :param pair: Pair the trade is for
:param trade: trade object. :param trade: trade object.
:param order: Order dictionary as returned from CCXT. :param order: Order dictionary as returned from CCXT.
:param current_time: datetime object, containing the current datetime
:param **kwargs: Ensure to keep this here so updates to this won't break your strategy. :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
:return bool: When True is returned, then the (long)sell/(short)buy-order is cancelled. :return bool: When True is returned, then the (long)sell/(short)buy-order is cancelled.
""" """
return False return False
def bot_loop_start(self, **kwargs) -> None:
"""
Called at the start of the bot iteration (one loop).
Might be used to perform pair-independent tasks
(e.g. gather some remote resource for comparison)
:param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
"""
pass
def confirm_trade_entry(self, pair: str, order_type: str, amount: float, rate: float, def confirm_trade_entry(self, pair: str, order_type: str, amount: float, rate: float,
time_in_force: str, current_time: datetime, time_in_force: str, current_time: datetime, entry_tag: Optional[str],
side: str, **kwargs) -> bool: side: str, **kwargs) -> bool:
""" """
Called right before placing a entry order. Called right before placing a entry order.
@ -251,6 +256,7 @@ class IStrategy(ABC, HyperStrategyMixin):
:param rate: Rate that's going to be used when using limit orders :param rate: Rate that's going to be used when using limit orders
:param time_in_force: Time in force. Defaults to GTC (Good-til-cancelled). :param time_in_force: Time in force. Defaults to GTC (Good-til-cancelled).
:param current_time: datetime object, containing the current datetime :param current_time: datetime object, containing the current datetime
:param entry_tag: Optional entry_tag (buy_tag) if provided with the buy signal.
:param side: 'long' or 'short' - indicating the direction of the proposed trade :param side: 'long' or 'short' - indicating the direction of the proposed trade
:param **kwargs: Ensure to keep this here so updates to this won't break your strategy. :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
:return bool: When True is returned, then the buy-order is placed on the exchange. :return bool: When True is returned, then the buy-order is placed on the exchange.
@ -309,7 +315,7 @@ class IStrategy(ABC, HyperStrategyMixin):
return self.stoploss return self.stoploss
def custom_entry_price(self, pair: str, current_time: datetime, proposed_rate: float, def custom_entry_price(self, pair: str, current_time: datetime, proposed_rate: float,
**kwargs) -> float: entry_tag: Optional[str], **kwargs) -> float:
""" """
Custom entry price logic, returning the new entry price. Custom entry price logic, returning the new entry price.
@ -320,6 +326,7 @@ class IStrategy(ABC, HyperStrategyMixin):
:param pair: Pair that's currently analyzed :param pair: Pair that's currently analyzed
:param current_time: datetime object, containing the current datetime :param current_time: datetime object, containing the current datetime
:param proposed_rate: Rate, calculated based on pricing settings in ask_strategy. :param proposed_rate: Rate, calculated based on pricing settings in ask_strategy.
:param entry_tag: Optional entry_tag (buy_tag) if provided with the buy signal.
:param **kwargs: Ensure to keep this here so updates to this won't break your strategy. :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
:return float: New entry price value if provided :return float: New entry price value if provided
""" """
@ -371,7 +378,7 @@ class IStrategy(ABC, HyperStrategyMixin):
def custom_stake_amount(self, pair: str, current_time: datetime, current_rate: float, def custom_stake_amount(self, pair: str, current_time: datetime, current_rate: float,
proposed_stake: float, min_stake: float, max_stake: float, proposed_stake: float, min_stake: float, max_stake: float,
side: str, **kwargs) -> float: entry_tag: Optional[str], side: str, **kwargs) -> float:
""" """
Customize stake size for each new trade. Customize stake size for each new trade.
@ -381,6 +388,7 @@ class IStrategy(ABC, HyperStrategyMixin):
:param proposed_stake: A stake amount proposed by the bot. :param proposed_stake: A stake amount proposed by the bot.
:param min_stake: Minimal stake size allowed by exchange. :param min_stake: Minimal stake size allowed by exchange.
:param max_stake: Balance available for trading. :param max_stake: Balance available for trading.
:param entry_tag: Optional entry_tag (buy_tag) if provided with the buy signal.
:param side: 'long' or 'short' - indicating the direction of the proposed trade :param side: 'long' or 'short' - indicating the direction of the proposed trade
:return: A stake size, which is between min_stake and max_stake. :return: A stake size, which is between min_stake and max_stake.
""" """
@ -392,6 +400,7 @@ class IStrategy(ABC, HyperStrategyMixin):
""" """
Custom trade adjustment logic, returning the stake amount that a trade should be increased. Custom trade adjustment logic, returning the stake amount that a trade should be increased.
This means extra buy orders with additional fees. This means extra buy orders with additional fees.
Only called when `position_adjustment_enable` is set to True.
For full documentation please go to https://www.freqtrade.io/en/latest/strategy-advanced/ For full documentation please go to https://www.freqtrade.io/en/latest/strategy-advanced/
@ -976,6 +985,29 @@ class IStrategy(ABC, HyperStrategyMixin):
else: else:
return current_profit > roi return current_profit > roi
def ft_check_timed_out(self, side: str, trade: Trade, order: Dict,
current_time: datetime) -> bool:
"""
FT Internal method.
Check if timeout is active, and if the order is still open and timed out
"""
timeout = self.config.get('unfilledtimeout', {}).get(side)
ordertime = arrow.get(order['datetime']).datetime
if timeout is not None:
timeout_unit = self.config.get('unfilledtimeout', {}).get('unit', 'minutes')
timeout_kwargs = {timeout_unit: -timeout}
timeout_threshold = current_time + timedelta(**timeout_kwargs)
timedout = (order['status'] == 'open' and order['side'] == side
and ordertime < timeout_threshold)
if timedout:
return True
time_method = self.check_sell_timeout if order['side'] == 'sell' else self.check_buy_timeout
return strategy_safe_wrapper(time_method,
default_retval=False)(
pair=trade.pair, trade=trade, order=order,
current_time=current_time)
def advise_all_indicators(self, data: Dict[str, DataFrame]) -> Dict[str, DataFrame]: def advise_all_indicators(self, data: Dict[str, DataFrame]) -> Dict[str, DataFrame]:
""" """
Populates indicators for given candle (OHLCV) data (for multiple pairs) Populates indicators for given candle (OHLCV) data (for multiple pairs)

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@ -12,9 +12,47 @@ def bot_loop_start(self, **kwargs) -> None:
""" """
pass pass
def custom_stake_amount(self, pair: str, current_time: datetime, current_rate: float, def custom_entry_price(self, pair: str, current_time: 'datetime', proposed_rate: float,
entry_tag: 'Optional[str]', **kwargs) -> float:
"""
Custom entry price logic, returning the new entry price.
For full documentation please go to https://www.freqtrade.io/en/latest/strategy-advanced/
When not implemented by a strategy, returns None, orderbook is used to set entry price
:param pair: Pair that's currently analyzed
:param current_time: datetime object, containing the current datetime
:param proposed_rate: Rate, calculated based on pricing settings in ask_strategy.
:param entry_tag: Optional entry_tag (buy_tag) if provided with the buy signal.
:param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
:return float: New entry price value if provided
"""
return proposed_rate
def custom_exit_price(self, pair: str, trade: 'Trade',
current_time: 'datetime', proposed_rate: float,
current_profit: float, **kwargs) -> float:
"""
Custom exit price logic, returning the new exit price.
For full documentation please go to https://www.freqtrade.io/en/latest/strategy-advanced/
When not implemented by a strategy, returns None, orderbook is used to set exit price
:param pair: Pair that's currently analyzed
:param trade: trade object.
:param current_time: datetime object, containing the current datetime
:param proposed_rate: Rate, calculated based on pricing settings in ask_strategy.
:param current_profit: Current profit (as ratio), calculated based on current_rate.
:param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
:return float: New exit price value if provided
"""
return proposed_rate
def custom_stake_amount(self, pair: str, current_time: 'datetime', current_rate: float,
proposed_stake: float, min_stake: float, max_stake: float, proposed_stake: float, min_stake: float, max_stake: float,
side: str, **kwargs) -> float: side: str, entry_tag: 'Optional[str]', **kwargs) -> float:
""" """
Customize stake size for each new trade. Customize stake size for each new trade.
@ -24,6 +62,7 @@ def custom_stake_amount(self, pair: str, current_time: datetime, current_rate: f
:param proposed_stake: A stake amount proposed by the bot. :param proposed_stake: A stake amount proposed by the bot.
:param min_stake: Minimal stake size allowed by exchange. :param min_stake: Minimal stake size allowed by exchange.
:param max_stake: Balance available for trading. :param max_stake: Balance available for trading.
:param entry_tag: Optional entry_tag (buy_tag) if provided with the buy signal.
:param side: 'long' or 'short' - indicating the direction of the proposed trade :param side: 'long' or 'short' - indicating the direction of the proposed trade
:return: A stake size, which is between min_stake and max_stake. :return: A stake size, which is between min_stake and max_stake.
""" """
@ -78,7 +117,7 @@ def custom_sell(self, pair: str, trade: 'Trade', current_time: 'datetime', curre
return None return None
def confirm_trade_entry(self, pair: str, order_type: str, amount: float, rate: float, def confirm_trade_entry(self, pair: str, order_type: str, amount: float, rate: float,
time_in_force: str, current_time: datetime, time_in_force: str, current_time: datetime, entry_tag: 'Optional[str]',
side: str, **kwargs) -> bool: side: str, **kwargs) -> bool:
""" """
Called right before placing a entry order. Called right before placing a entry order.
@ -95,6 +134,7 @@ def confirm_trade_entry(self, pair: str, order_type: str, amount: float, rate: f
:param rate: Rate that's going to be used when using limit orders :param rate: Rate that's going to be used when using limit orders
:param time_in_force: Time in force. Defaults to GTC (Good-til-cancelled). :param time_in_force: Time in force. Defaults to GTC (Good-til-cancelled).
:param current_time: datetime object, containing the current datetime :param current_time: datetime object, containing the current datetime
:param entry_tag: Optional entry_tag (buy_tag) if provided with the buy signal.
:param side: 'long' or 'short' - indicating the direction of the proposed trade :param side: 'long' or 'short' - indicating the direction of the proposed trade
:param **kwargs: Ensure to keep this here so updates to this won't break your strategy. :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
:return bool: When True is returned, then the buy-order is placed on the exchange. :return bool: When True is returned, then the buy-order is placed on the exchange.
@ -169,3 +209,26 @@ def check_sell_timeout(self, pair: str, trade: 'Trade', order: dict, **kwargs) -
:return bool: When True is returned, then the sell-order is cancelled. :return bool: When True is returned, then the sell-order is cancelled.
""" """
return False return False
def adjust_trade_position(self, trade: 'Trade', current_time: 'datetime',
current_rate: float, current_profit: float, min_stake: float,
max_stake: float, **kwargs) -> 'Optional[float]':
"""
Custom trade adjustment logic, returning the stake amount that a trade should be increased.
This means extra buy orders with additional fees.
Only called when `position_adjustment_enable` is set to True.
For full documentation please go to https://www.freqtrade.io/en/latest/strategy-advanced/
When not implemented by a strategy, returns None
:param trade: trade object.
:param current_time: datetime object, containing the current datetime
:param current_rate: Current buy rate.
:param current_profit: Current profit (as ratio), calculated based on current_rate.
:param min_stake: Minimal stake size allowed by exchange.
:param max_stake: Balance available for trading.
:param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
:return float: Stake amount to adjust your trade
"""
return None

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@ -8,7 +8,7 @@ flake8==4.0.1
flake8-tidy-imports==4.6.0 flake8-tidy-imports==4.6.0
mypy==0.931 mypy==0.931
pytest==6.2.5 pytest==6.2.5
pytest-asyncio==0.17.1 pytest-asyncio==0.17.2
pytest-cov==3.0.0 pytest-cov==3.0.0
pytest-mock==3.6.1 pytest-mock==3.6.1
pytest-random-order==1.0.4 pytest-random-order==1.0.4
@ -21,9 +21,9 @@ nbconvert==6.4.0
# mypy types # mypy types
types-cachetools==4.2.9 types-cachetools==4.2.9
types-filelock==3.2.4 types-filelock==3.2.5
types-requests==2.27.7 types-requests==2.27.7
types-tabulate==0.8.5 types-tabulate==0.8.5
# Extensions to datetime library # Extensions to datetime library
types-python-dateutil==2.8.7 types-python-dateutil==2.8.8

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@ -1,13 +1,12 @@
numpy==1.21.5; python_version <= '3.7' numpy==1.22.1
numpy==1.22.1; python_version > '3.7' pandas==1.4.0
pandas==1.3.5
pandas-ta==0.3.14b pandas-ta==0.3.14b
ccxt==1.68.20 ccxt==1.70.45
# Pin cryptography for now due to rust build errors with piwheels # Pin cryptography for now due to rust build errors with piwheels
cryptography==36.0.1 cryptography==36.0.1
aiohttp==3.8.1 aiohttp==3.8.1
SQLAlchemy==1.4.29 SQLAlchemy==1.4.31
python-telegram-bot==13.10 python-telegram-bot==13.10
arrow==1.2.1 arrow==1.2.1
cachetools==4.2.2 cachetools==4.2.2
@ -32,7 +31,7 @@ python-rapidjson==1.5
sdnotify==0.3.2 sdnotify==0.3.2
# API Server # API Server
fastapi==0.72.0 fastapi==0.73.0
uvicorn==0.17.0 uvicorn==0.17.0
pyjwt==2.3.0 pyjwt==2.3.0
aiofiles==0.8.0 aiofiles==0.8.0

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@ -14,7 +14,6 @@ classifiers =
Environment :: Console Environment :: Console
Intended Audience :: Science/Research Intended Audience :: Science/Research
License :: OSI Approved :: GNU General Public License v3 (GPLv3) License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Programming Language :: Python :: 3.7
Programming Language :: Python :: 3.8 Programming Language :: Python :: 3.8
Programming Language :: Python :: 3.9 Programming Language :: Python :: 3.9
Programming Language :: Python :: 3.10 Programming Language :: Python :: 3.10

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@ -25,7 +25,7 @@ function check_installed_python() {
exit 2 exit 2
fi fi
for v in 9 10 8 7 for v in 9 10 8
do do
PYTHON="python3.${v}" PYTHON="python3.${v}"
which $PYTHON which $PYTHON
@ -219,7 +219,7 @@ function install() {
install_redhat install_redhat
else else
echo "This script does not support your OS." echo "This script does not support your OS."
echo "If you have Python version 3.7 - 3.10, pip, virtualenv, ta-lib you can continue." echo "If you have Python version 3.8 - 3.10, pip, virtualenv, ta-lib you can continue."
echo "Wait 10 seconds to continue the next install steps or use ctrl+c to interrupt this shell." echo "Wait 10 seconds to continue the next install steps or use ctrl+c to interrupt this shell."
sleep 10 sleep 10
fi fi
@ -246,7 +246,7 @@ function help() {
echo " -p,--plot Install dependencies for Plotting scripts." echo " -p,--plot Install dependencies for Plotting scripts."
} }
# Verify if 3.7 or 3.8 is installed # Verify if 3.8+ is installed
check_installed_python check_installed_python
case $* in case $* in

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@ -782,6 +782,8 @@ def test_backtest_pricecontours_protections(default_conf, fee, mocker, testdatad
# While buy-signals are unrealistic, running backtesting # While buy-signals are unrealistic, running backtesting
# over and over again should not cause different results # over and over again should not cause different results
for [contour, numres] in tests: for [contour, numres] in tests:
# Debug output for random test failure
print(f"{contour}, {numres}")
assert len(simple_backtest(default_conf, contour, mocker, testdatadir)['results']) == numres assert len(simple_backtest(default_conf, contour, mocker, testdatadir)['results']) == numres

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@ -148,10 +148,13 @@ def test_fiat_multiple_coins(mocker, caplog):
{'id': 'helium', 'symbol': 'hnt', 'name': 'Helium'}, {'id': 'helium', 'symbol': 'hnt', 'name': 'Helium'},
{'id': 'hymnode', 'symbol': 'hnt', 'name': 'Hymnode'}, {'id': 'hymnode', 'symbol': 'hnt', 'name': 'Hymnode'},
{'id': 'bitcoin', 'symbol': 'btc', 'name': 'Bitcoin'}, {'id': 'bitcoin', 'symbol': 'btc', 'name': 'Bitcoin'},
{'id': 'ethereum', 'symbol': 'eth', 'name': 'Ethereum'},
{'id': 'ethereum-wormhole', 'symbol': 'eth', 'name': 'Ethereum Wormhole'},
] ]
assert fiat_convert._get_gekko_id('btc') == 'bitcoin' assert fiat_convert._get_gekko_id('btc') == 'bitcoin'
assert fiat_convert._get_gekko_id('hnt') is None assert fiat_convert._get_gekko_id('hnt') is None
assert fiat_convert._get_gekko_id('eth') == 'ethereum'
assert log_has('Found multiple mappings in goingekko for hnt.', caplog) assert log_has('Found multiple mappings in goingekko for hnt.', caplog)

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@ -44,7 +44,7 @@ def test_strategy_test_v3(result, fee, is_short, side):
assert strategy.confirm_trade_entry(pair='ETH/BTC', order_type='limit', amount=0.1, assert strategy.confirm_trade_entry(pair='ETH/BTC', order_type='limit', amount=0.1,
rate=20000, time_in_force='gtc', rate=20000, time_in_force='gtc',
current_time=datetime.utcnow(), current_time=datetime.utcnow(),
side=side) is True side=side, entry_tag=None) is True
assert strategy.confirm_trade_exit(pair='ETH/BTC', trade=trade, order_type='limit', amount=0.1, assert strategy.confirm_trade_exit(pair='ETH/BTC', trade=trade, order_type='limit', amount=0.1,
rate=20000, time_in_force='gtc', sell_reason='roi', rate=20000, time_in_force='gtc', sell_reason='roi',
current_time=datetime.utcnow(), current_time=datetime.utcnow(),

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@ -5182,3 +5182,32 @@ def test_position_adjust(mocker, default_conf_usdt, fee) -> None:
# Make sure the closed order is found as the second order. # Make sure the closed order is found as the second order.
order = trade.select_order('buy', False) order = trade.select_order('buy', False)
assert order.order_id == '652' assert order.order_id == '652'
def test_process_open_trade_positions_exception(mocker, default_conf_usdt, fee, caplog) -> None:
default_conf_usdt.update({
"position_adjustment_enable": True,
})
freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt)
mocker.patch('freqtrade.freqtradebot.FreqtradeBot.check_and_call_adjust_trade_position',
side_effect=DependencyException())
create_mock_trades(fee)
freqtrade.process_open_trade_positions()
assert log_has_re(r"Unable to adjust position of trade for .*", caplog)
def test_check_and_call_adjust_trade_position(mocker, default_conf_usdt, fee, caplog) -> None:
default_conf_usdt.update({
"position_adjustment_enable": True,
"max_entry_position_adjustment": 0,
})
freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt)
create_mock_trades(fee)
caplog.set_level(logging.DEBUG)
freqtrade.process_open_trade_positions()
assert log_has_re(r"Max adjustment entries for .* has been reached\.", caplog)

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@ -243,6 +243,8 @@ def test_dca_buying(default_conf_usdt, ticker_usdt, fee, mocker) -> None:
freqtrade.process() freqtrade.process()
trade = Trade.get_trades().first() trade = Trade.get_trades().first()
assert len(trade.orders) == 2 assert len(trade.orders) == 2
for o in trade.orders:
assert o.status == "closed"
assert trade.stake_amount == 120 assert trade.stake_amount == 120
# Open-rate averaged between 2.0 and 2.0 * 0.995 # Open-rate averaged between 2.0 and 2.0 * 0.995
@ -258,7 +260,6 @@ def test_dca_buying(default_conf_usdt, ticker_usdt, fee, mocker) -> None:
assert trade.orders[1].amount == 60 / ticker_usdt_modif['bid'] assert trade.orders[1].amount == 60 / ticker_usdt_modif['bid']
assert trade.amount == trade.orders[0].amount + trade.orders[1].amount assert trade.amount == trade.orders[0].amount + trade.orders[1].amount
assert trade.nr_of_successful_buys == 2 assert trade.nr_of_successful_buys == 2
# Sell # Sell

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@ -2464,6 +2464,33 @@ def test_recalc_trade_from_orders_ignores_bad_orders(fee):
assert trade.fee_open_cost == 2 * o1_fee_cost assert trade.fee_open_cost == 2 * o1_fee_cost
assert trade.open_trade_value == 2 * o1_trade_val assert trade.open_trade_value == 2 * o1_trade_val
assert trade.nr_of_successful_buys == 2 assert trade.nr_of_successful_buys == 2
# Check with 1 order
order_noavg = Order(
ft_order_side='buy',
ft_pair=trade.pair,
ft_is_open=False,
status="closed",
symbol=trade.pair,
order_type="market",
side="buy",
price=o1_rate,
average=None,
filled=o1_amount,
remaining=0,
cost=o1_amount,
order_date=trade.open_date,
order_filled_date=trade.open_date,
)
trade.orders.append(order_noavg)
trade.recalc_trade_from_orders()
# Calling recalc with single initial order should not change anything
assert trade.amount == 3 * o1_amount
assert trade.stake_amount == 3 * o1_amount
assert trade.open_rate == o1_rate
assert trade.fee_open_cost == 3 * o1_fee_cost
assert trade.open_trade_value == 3 * o1_trade_val
assert trade.nr_of_successful_buys == 3
@pytest.mark.usefixtures("init_persistence") @pytest.mark.usefixtures("init_persistence")