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Merge branch 'develop' of https://github.com/simwai/freqtrade into develop

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simwai
2024-01-08 13:40:34 +01:00
parent 5110c14d35 e28b2f44d3
commit 44856eedb2
115 changed files with 4651 additions and 1489 deletions
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.github/workflows/ci.yml
+87 -52
View File
@@ -31,7 +31,7 @@ jobs:
- uses: actions/checkout@v4
- name: Set up Python
uses: actions/setup-python@v4
uses: actions/setup-python@v5
with:
python-version: ${{ matrix.python-version }}
@@ -44,7 +44,6 @@ jobs:
- name: pip cache (linux)
uses: actions/cache@v3
if: runner.os == 'Linux'
with:
path: ~/.cache/pip
key: test-${{ matrix.os }}-${{ matrix.python-version }}-pip
@@ -55,7 +54,6 @@ jobs:
cd build_helpers && ./install_ta-lib.sh ${HOME}/dependencies/; cd ..
- name: Installation - *nix
if: runner.os == 'Linux'
run: |
python -m pip install --upgrade pip wheel
export LD_LIBRARY_PATH=${HOME}/dependencies/lib:$LD_LIBRARY_PATH
@@ -122,18 +120,18 @@ jobs:
details: Freqtrade CI failed on ${{ matrix.os }}
webhookUrl: ${{ secrets.DISCORD_WEBHOOK }}
build_macos:
build-macos:
runs-on: ${{ matrix.os }}
strategy:
matrix:
os: [ macos-latest ]
os: [ "macos-latest", "macos-13" ]
python-version: ["3.9", "3.10", "3.11"]
steps:
- uses: actions/checkout@v4
- name: Set up Python
uses: actions/setup-python@v4
uses: actions/setup-python@v5
with:
python-version: ${{ matrix.python-version }}
check-latest: true
@@ -143,14 +141,13 @@ jobs:
id: cache
with:
path: ~/dependencies/
key: ${{ runner.os }}-dependencies
key: ${{ matrix.os }}-dependencies
- name: pip cache (macOS)
uses: actions/cache@v3
if: runner.os == 'macOS'
with:
path: ~/Library/Caches/pip
key: test-${{ matrix.os }}-${{ matrix.python-version }}-pip
key: ${{ matrix.os }}-${{ matrix.python-version }}-pip
- name: TA binary *nix
if: steps.cache.outputs.cache-hit != 'true'
@@ -158,7 +155,6 @@ jobs:
cd build_helpers && ./install_ta-lib.sh ${HOME}/dependencies/; cd ..
- name: Installation - macOS
if: runner.os == 'macOS'
run: |
# brew update
# TODO: Should be the brew upgrade
@@ -166,16 +162,21 @@ jobs:
# https://github.com/actions/runner-images/issues/6817
rm /usr/local/bin/2to3 || true
rm /usr/local/bin/2to3-3.11 || true
rm /usr/local/bin/2to3-3.12 || true
rm /usr/local/bin/idle3 || true
rm /usr/local/bin/idle3.11 || true
rm /usr/local/bin/idle3.12 || true
rm /usr/local/bin/pydoc3 || true
rm /usr/local/bin/pydoc3.11 || true
rm /usr/local/bin/pydoc3.12 || true
rm /usr/local/bin/python3 || true
rm /usr/local/bin/python3.11 || true
rm /usr/local/bin/python3.12 || true
rm /usr/local/bin/python3-config || true
rm /usr/local/bin/python3.11-config || true
rm /usr/local/bin/python3.12-config || true
brew install hdf5 c-blosc
brew install hdf5 c-blosc libomp
python -m pip install --upgrade pip wheel
export LD_LIBRARY_PATH=${HOME}/dependencies/lib:$LD_LIBRARY_PATH
export TA_LIBRARY_PATH=${HOME}/dependencies/lib
@@ -231,7 +232,7 @@ jobs:
details: Test Succeeded!
webhookUrl: ${{ secrets.DISCORD_WEBHOOK }}
build_windows:
build-windows:
runs-on: ${{ matrix.os }}
strategy:
@@ -243,7 +244,7 @@ jobs:
- uses: actions/checkout@v4
- name: Set up Python
uses: actions/setup-python@v4
uses: actions/setup-python@v5
with:
python-version: ${{ matrix.python-version }}
@@ -301,13 +302,13 @@ jobs:
details: Test Failed
webhookUrl: ${{ secrets.DISCORD_WEBHOOK }}
mypy_version_check:
mypy-version-check:
runs-on: ubuntu-22.04
steps:
- uses: actions/checkout@v4
- name: Set up Python
uses: actions/setup-python@v4
uses: actions/setup-python@v5
with:
python-version: "3.10"
@@ -321,12 +322,12 @@ jobs:
steps:
- uses: actions/checkout@v4
- uses: actions/setup-python@v4
- uses: actions/setup-python@v5
with:
python-version: "3.10"
- uses: pre-commit/action@v3.0.0
docs_check:
docs-check:
runs-on: ubuntu-22.04
steps:
- uses: actions/checkout@v4
@@ -336,7 +337,7 @@ jobs:
./tests/test_docs.sh
- name: Set up Python
uses: actions/setup-python@v4
uses: actions/setup-python@v5
with:
python-version: "3.11"
@@ -362,9 +363,9 @@ jobs:
- uses: actions/checkout@v4
- name: Set up Python
uses: actions/setup-python@v4
uses: actions/setup-python@v5
with:
python-version: "3.9"
python-version: "3.11"
- name: Cache_dependencies
uses: actions/cache@v3
@@ -375,7 +376,6 @@ jobs:
- name: pip cache (linux)
uses: actions/cache@v3
if: runner.os == 'Linux'
with:
path: ~/.cache/pip
key: test-${{ matrix.os }}-${{ matrix.python-version }}-pip
@@ -386,7 +386,6 @@ jobs:
cd build_helpers && ./install_ta-lib.sh ${HOME}/dependencies/; cd ..
- name: Installation - *nix
if: runner.os == 'Linux'
run: |
python -m pip install --upgrade pip wheel
export LD_LIBRARY_PATH=${HOME}/dependencies/lib:$LD_LIBRARY_PATH
@@ -399,17 +398,17 @@ jobs:
env:
CI_WEB_PROXY: http://152.67.78.211:13128
run: |
pytest --random-order --cov=freqtrade --cov-config=.coveragerc --longrun
pytest --random-order --longrun --durations 20 -n auto --dist loadscope
# Notify only once - when CI completes (and after deploy) in case it's successfull
notify-complete:
needs: [
build_linux,
build_macos,
build_windows,
docs_check,
mypy_version_check,
build-macos,
build-windows,
docs-check,
mypy-version-check,
pre-commit,
build_linux_online
]
@@ -436,8 +435,63 @@ jobs:
details: Test Completed!
webhookUrl: ${{ secrets.DISCORD_WEBHOOK }}
deploy:
needs: [ build_linux, build_macos, build_windows, docs_check, mypy_version_check, pre-commit ]
build:
name: "Build"
needs: [ build_linux, build-macos, build-windows, docs-check, mypy-version-check, pre-commit ]
runs-on: ubuntu-22.04
steps:
- uses: actions/checkout@v4
- name: Set up Python
uses: actions/setup-python@v5
with:
python-version: "3.11"
- name: Build distribution
run: |
pip install -U build
python -m build --sdist --wheel
- name: Upload artifacts 📦
uses: actions/upload-artifact@v4
with:
name: freqtrade-build
path: |
dist
retention-days: 10
deploy-pypi:
name: "Deploy to PyPI"
needs: [ build ]
runs-on: ubuntu-22.04
if: (github.event_name == 'release')
environment:
name: release
url: https://pypi.org/p/freqtrade
permissions:
id-token: write
steps:
- uses: actions/checkout@v4
- name: Download artifact 📦
uses: actions/download-artifact@v4
with:
name: freqtrade-build
path: dist
- name: Publish to PyPI (Test)
uses: pypa/gh-action-pypi-publish@v1.8.11
with:
repository-url: https://test.pypi.org/legacy/
- name: Publish to PyPI
uses: pypa/gh-action-pypi-publish@v1.8.11
deploy-docker:
needs: [ build_linux, build-macos, build-windows, docs-check, mypy-version-check, pre-commit ]
runs-on: ubuntu-22.04
if: (github.event_name == 'push' || github.event_name == 'schedule' || github.event_name == 'release') && github.repository == 'freqtrade/freqtrade'
@@ -446,7 +500,7 @@ jobs:
- uses: actions/checkout@v4
- name: Set up Python
uses: actions/setup-python@v4
uses: actions/setup-python@v5
with:
python-version: "3.11"
@@ -455,26 +509,6 @@ jobs:
run: echo "##[set-output name=branch;]$(echo ${GITHUB_REF##*/})"
id: extract_branch
- name: Build distribution
run: |
pip install -U setuptools wheel
python setup.py sdist bdist_wheel
- name: Publish to PyPI (Test)
uses: pypa/gh-action-pypi-publish@v1.8.10
if: (github.event_name == 'release')
with:
user: __token__
password: ${{ secrets.pypi_test_password }}
repository_url: https://test.pypi.org/legacy/
- name: Publish to PyPI
uses: pypa/gh-action-pypi-publish@v1.8.10
if: (github.event_name == 'release')
with:
user: __token__
password: ${{ secrets.pypi_password }}
- name: Dockerhub login
env:
DOCKER_PASSWORD: ${{ secrets.DOCKER_PASSWORD }}
@@ -506,10 +540,11 @@ jobs:
run: |
build_helpers/publish_docker_multi.sh
deploy_arm:
deploy-arm:
name: "Deploy Docker"
permissions:
packages: write
needs: [ deploy ]
needs: [ deploy-docker ]
# Only run on 64bit machines
runs-on: [self-hosted, linux, ARM64]
if: (github.event_name == 'push' || github.event_name == 'schedule' || github.event_name == 'release') && github.repository == 'freqtrade/freqtrade'
.github/workflows/pre-commit-update.yml
+44
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@@ -0,0 +1,44 @@
name: Pre-commit auto-update
on:
# every day at midnight
schedule:
- cron: "0 3 * * 2"
# on demand
workflow_dispatch:
permissions:
contents: read
jobs:
auto-update:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: actions/setup-python@v5
with:
python-version: "3.11"
- name: Install pre-commit
run: pip install pre-commit
- name: Run auto-update
run: pre-commit autoupdate
- name: Run pre-commit
run: pre-commit run --all-files
- uses: peter-evans/create-pull-request@v5
with:
token: ${{ secrets.REPO_SCOPED_TOKEN }}
add-paths: .pre-commit-config.yaml
labels: |
Tech maintenance
branch: update/pre-commit-hooks
title: Update pre-commit hooks
commit-message: "chore: update pre-commit hooks"
committer: Freqtrade Bot <noreply@github.com>
body: Update versions of pre-commit hooks to latest version.
delete-branch: true
.gitignore
-1
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@@ -111,7 +111,6 @@ target/
#exceptions
!*.gitkeep
!config_examples/config_binance.example.json
!config_examples/config_bittrex.example.json
!config_examples/config_full.example.json
!config_examples/config_kraken.example.json
!config_examples/config_freqai.example.json
.pre-commit-config.yaml
+9 -8
View File
@@ -2,27 +2,28 @@
# See https://pre-commit.com/hooks.html for more hooks
repos:
- repo: https://github.com/pycqa/flake8
rev: "6.0.0"
rev: "6.1.0"
hooks:
- id: flake8
additional_dependencies: [Flake8-pyproject]
# stages: [push]
- repo: https://github.com/pre-commit/mirrors-mypy
rev: "v1.7.0"
rev: "v1.8.0"
hooks:
- id: mypy
exclude: build_helpers
additional_dependencies:
- types-cachetools==5.3.0.7
- types-filelock==3.2.7
- types-requests==2.31.0.10
- types-tabulate==0.9.0.3
- types-python-dateutil==2.8.19.14
- types-requests==2.31.0.20240106
- types-tabulate==0.9.0.20240106
- types-python-dateutil==2.8.19.20240106
- SQLAlchemy==2.0.23
# stages: [push]
- repo: https://github.com/pycqa/isort
rev: "5.12.0"
rev: "5.13.2"
hooks:
- id: isort
name: isort (python)
@@ -30,12 +31,12 @@ repos:
- repo: https://github.com/charliermarsh/ruff-pre-commit
# Ruff version.
rev: 'v0.1.1'
rev: 'v0.1.9'
hooks:
- id: ruff
- repo: https://github.com/pre-commit/pre-commit-hooks
rev: v4.4.0
rev: v4.5.0
hooks:
- id: end-of-file-fixer
exclude: |
MANIFEST.in
+2
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@@ -5,3 +5,5 @@ recursive-include freqtrade/templates/ *.j2 *.ipynb
include freqtrade/exchange/binance_leverage_tiers.json
include freqtrade/rpc/api_server/ui/fallback_file.html
include freqtrade/rpc/api_server/ui/favicon.ico
prune tests
build_helpers/TA_Lib-0.4.28-cp312-cp312-win_amd64.whl
BIN
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build_helpers/pyarrow-14.0.1-cp311-cp311-linux_armv7l.whl → build_helpers/pyarrow-14.0.2-cp311-cp311-linux_armv7l.whl
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Binary file not shown.
build_helpers/pyarrow-14.0.1-cp39-cp39-linux_armv7l.whl → build_helpers/pyarrow-14.0.2-cp39-cp39-linux_armv7l.whl
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config_examples/config_freqai.example.json
+1 -1
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@@ -52,7 +52,7 @@
"train_period_days": 15,
"backtest_period_days": 7,
"live_retrain_hours": 0,
"identifier": "uniqe-id",
"identifier": "unique-id",
"feature_parameters": {
"include_timeframes": [
"3m",
docs/backtesting.md
+2 -2
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@@ -618,13 +618,13 @@ To compare multiple strategies, a list of Strategies can be provided to backtest
This is limited to 1 timeframe value per run. However, data is only loaded once from disk so if you have multiple
strategies you'd like to compare, this will give a nice runtime boost.
All listed Strategies need to be in the same directory.
All listed Strategies need to be in the same directory, unless also `--recursive-strategy-search` is specified, where sub-directories within the strategy directory are also considered.
``` bash
freqtrade backtesting --timerange 20180401-20180410 --timeframe 5m --strategy-list Strategy001 Strategy002 --export trades
```
This will save the results to `user_data/backtest_results/backtest-result-<strategy>.json`, injecting the strategy-name into the target filename.
This will save the results to `user_data/backtest_results/backtest-result-<datetime>.json`, including results for both `Strategy001` and `Strategy002`.
There will be an additional table comparing win/losses of the different strategies (identical to the "Total" row in the first table).
Detailed output for all strategies one after the other will be available, so make sure to scroll up to see the details per strategy.
docs/configuration.md
+4 -2
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@@ -321,7 +321,7 @@ For example, if you have 10 ETH available in your wallet on the exchange and `tr
To fully utilize compounding profits when using multiple bots on the same exchange account, you'll want to limit each bot to a certain starting balance.
This can be accomplished by setting `available_capital` to the desired starting balance.
Assuming your account has 10.000 USDT and you want to run 2 different strategies on this exchange.
Assuming your account has 10000 USDT and you want to run 2 different strategies on this exchange.
You'd set `available_capital=5000` - granting each bot an initial capital of 5000 USDT.
The bot will then split this starting balance equally into `max_open_trades` buckets.
Profitable trades will result in increased stake-sizes for this bot - without affecting the stake-sizes of the other bot.
@@ -572,9 +572,11 @@ In addition to fiat currencies, a range of crypto currencies is supported.
The valid values are:
```json
"BTC", "ETH", "XRP", "LTC", "BCH", "USDT"
"BTC", "ETH", "XRP", "LTC", "BCH", "BNB"
```
Removing `fiat_display_currency` completely from the configuration will skip initializing coingecko, and will not show any FIAT currency conversion. This has no importance for the correct functioning of the bot.
## Using Dry-run mode
We recommend starting the bot in the Dry-run mode to see how your bot will
docs/exchanges.md
+2 -42
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@@ -127,6 +127,8 @@ Freqtrade will not attempt to change these settings.
## Kraken
Kraken supports [time_in_force](configuration.md#understand-order_time_in_force) with settings "GTC" (good till cancelled), "IOC" (immediate-or-cancel) and "PO" (Post only) settings.
!!! Tip "Stoploss on Exchange"
Kraken supports `stoploss_on_exchange` and can use both stop-loss-market and stop-loss-limit orders. It provides great advantages, so we recommend to benefit from it.
You can use either `"limit"` or `"market"` in the `order_types.stoploss` configuration setting to decide which type to use.
@@ -181,48 +183,6 @@ freqtrade download-data --exchange kraken --dl-trades -p BTC/EUR BCH/EUR
Please pay attention that rateLimit configuration entry holds delay in milliseconds between requests, NOT requests\sec rate.
So, in order to mitigate Kraken API "Rate limit exceeded" exception, this configuration should be increased, NOT decreased.
## Bittrex
### Order types
Bittrex does not support market orders. If you have a message at the bot startup about this, you should change order type values set in your configuration and/or in the strategy from `"market"` to `"limit"`. See some more details on this [here in the FAQ](faq.md#im-getting-the-exchange-bittrex-does-not-support-market-orders-message-and-cannot-run-my-strategy).
Bittrex also does not support `VolumePairlist` due to limited / split API constellation at the moment.
Please use `StaticPairlist`. Other pairlists (other than `VolumePairlist`) should not be affected.
### Volume pairlist
Bittrex does not support the direct usage of VolumePairList. This can however be worked around by using the advanced mode with `lookback_days: 1` (or more), which will emulate 24h volume.
Read more in the [pairlist documentation](plugins.md#volumepairlist-advanced-mode).
### Restricted markets
Bittrex split its exchange into US and International versions.
The International version has more pairs available, however the API always returns all pairs, so there is currently no automated way to detect if you're affected by the restriction.
If you have restricted pairs in your whitelist, you'll get a warning message in the log on Freqtrade startup for each restricted pair.
The warning message will look similar to the following:
``` output
[...] Message: bittrex {"success":false,"message":"RESTRICTED_MARKET","result":null,"explanation":null}"
```
If you're an "International" customer on the Bittrex exchange, then this warning will probably not impact you.
If you're a US customer, the bot will fail to create orders for these pairs, and you should remove them from your whitelist.
You can get a list of restricted markets by using the following snippet:
``` python
import ccxt
ct = ccxt.bittrex()
lm = ct.load_markets()
res = [p for p, x in lm.items() if 'US' in x['info']['prohibitedIn']]
print(res)
```
## Kucoin
Kucoin requires a passphrase for each api key, you will therefore need to add this key into the configuration so your exchange section looks as follows:
docs/faq.md
+1 -7
View File
@@ -128,15 +128,9 @@ This warning can point to one of the below problems:
* Barely traded pair -> Check the pair on the exchange webpage, look at the timeframe your strategy uses. If the pair does not have any volume in some candles (usually visualized with a "volume 0" bar, and a "_" as candle), this pair did not have any trades in this timeframe. These pairs should ideally be avoided, as they can cause problems with order-filling.
* API problem -> API returns wrong data (this only here for completeness, and should not happen with supported exchanges).
### I'm getting the "RESTRICTED_MARKET" message in the log
Currently known to happen for US Bittrex users.
Read [the Bittrex section about restricted markets](exchanges.md#restricted-markets) for more information.
### I'm getting the "Exchange XXX does not support market orders." message and cannot run my strategy
As the message says, your exchange does not support market orders and you have one of the [order types](configuration.md/#understand-order_types) set to "market". Your strategy was probably written with other exchanges in mind and sets "market" orders for "stoploss" orders, which is correct and preferable for most of the exchanges supporting market orders (but not for Bittrex and Gate.io).
As the message says, your exchange does not support market orders and you have one of the [order types](configuration.md/#understand-order_types) set to "market". Your strategy was probably written with other exchanges in mind and sets "market" orders for "stoploss" orders, which is correct and preferable for most of the exchanges supporting market orders (but not for Gate.io).
To fix this, redefine order types in the strategy to use "limit" instead of "market":
docs/freqai-running.md
+3 -3
View File
@@ -41,11 +41,11 @@ FreqAI stores new model files after each successful training. These files become
```json
"freqai": {
"purge_old_models": true,
"purge_old_models": 4,
}
```
This will automatically purge all models older than the two most recently trained ones to save disk space.
This will automatically purge all models older than the four most recently trained ones to save disk space. Inputing "0" will never purge any models.
## Backtesting
@@ -68,7 +68,7 @@ Backtesting mode requires [downloading the necessary data](#downloading-data-to-
This way, you can return to using any model you wish by simply specifying the `identifier`.
!!! Note
Backtesting calls `set_freqai_targets()` one time for each backtest window (where the number of windows is the full backtest timerange divided by the `backtest_period_days` parameter). Doing this means that the targets simulate dry/live behavior without look ahead bias. However, the definition of the features in `feature_engineering_*()` is performed once on the entire backtest timerange. This means that you should be sure that features do look-ahead into the future.
Backtesting calls `set_freqai_targets()` one time for each backtest window (where the number of windows is the full backtest timerange divided by the `backtest_period_days` parameter). Doing this means that the targets simulate dry/live behavior without look ahead bias. However, the definition of the features in `feature_engineering_*()` is performed once on the entire training timerange. This means that you should be sure that features do not look-ahead into the future.
More details about look-ahead bias can be found in [Common Mistakes](strategy-customization.md#common-mistakes-when-developing-strategies).
---
docs/freqai.md
+5
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@@ -114,6 +114,11 @@ Here we compile some external materials that provide deeper looks into various c
- [Real-time head-to-head: Adaptive modeling of financial market data using XGBoost and CatBoost](https://emergentmethods.medium.com/real-time-head-to-head-adaptive-modeling-of-financial-market-data-using-xgboost-and-catboost-995a115a7495)
- [FreqAI - from price to prediction](https://emergentmethods.medium.com/freqai-from-price-to-prediction-6fadac18b665)
## Support
You can find support for FreqAI in a variety of places, including the [Freqtrade discord](https://discord.gg/Jd8JYeWHc4), the dedicated [FreqAI discord](https://discord.gg/7AMWACmbjT), and in [github issues](https://github.com/freqtrade/freqtrade/issues).
## Credits
FreqAI is developed by a group of individuals who all contribute specific skillsets to the project.
docs/includes/pairlists.md
+2 -2
View File
@@ -112,8 +112,8 @@ For convenience `lookback_days` can be specified, which will imply that 1d candl
!!! Warning "Performance implications when using lookback range"
If used in first position in combination with lookback, the computation of the range based volume can be time and resource consuming, as it downloads candles for all tradable pairs. Hence it's highly advised to use the standard approach with `VolumeFilter` to narrow the pairlist down for further range volume calculation.
??? Tip "Unsupported exchanges (Bittrex, Gemini)"
On some exchanges (like Bittrex and Gemini), regular VolumePairList does not work as the api does not natively provide 24h volume. This can be worked around by using candle data to build the volume.
??? Tip "Unsupported exchanges"
On some exchanges (like Gemini), regular VolumePairList does not work as the api does not natively provide 24h volume. This can be worked around by using candle data to build the volume.
To roughly simulate 24h volume, you can use the following configuration.
Please note that These pairlists will only refresh once per day.
docs/requirements-docs.txt
+2 -2
View File
@@ -1,6 +1,6 @@
markdown==3.5.1
mkdocs==1.5.3
mkdocs-material==9.4.14
mkdocs-material==9.5.3
mdx_truly_sane_lists==1.3
pymdown-extensions==10.5
pymdown-extensions==10.7
jinja2==3.1.2
docs/strategy-callbacks.md
+16 -7
View File
@@ -489,7 +489,7 @@ The helper function `stoploss_from_absolute()` can be used to convert from an ab
dataframe, _ = self.dp.get_analyzed_dataframe(pair, self.timeframe)
trade_date = timeframe_to_prev_date(self.timeframe, trade.open_date_utc)
candle = dataframe.iloc[-1].squeeze()
sign = 1 if trade.is_short else -1
side = 1 if trade.is_short else -1
return stoploss_from_absolute(current_rate + (side * candle['atr'] * 2),
current_rate, is_short=trade.is_short,
leverage=trade.leverage)
@@ -760,22 +760,31 @@ 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.
`adjust_trade_position()` can be used to perform additional orders, for example to manage risk with DCA (Dollar Cost Averaging) or to increase or decrease positions.
`max_entry_position_adjustment` property is used to limit the number of additional entries per trade (on top of the first entry order) that the bot can execute. By default, the value is -1 which means the bot have no limit on number of adjustment entries.
The strategy is expected to return a stake_amount (in stake currency) between `min_stake` and `max_stake` if and when an additional entry order should be made (position is increased -> buy order for long trades, sell order for short trades).
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`.
This callback is **not** called when there is an open order (either buy or sell) waiting for execution.
`adjust_trade_position()` is called very frequently for the duration of a trade, so you must keep your implementation as performant as possible.
Additional entries are ignored once you have reached the maximum amount of extra entries that you have set on `max_entry_position_adjustment`, but the callback is called anyway looking for partial exits.
Position adjustments will always be applied in the direction of the trade, so a positive value will always increase your position (negative values will decrease your position), no matter if it's a long or short trade.
Modifications to leverage are not possible, and the stake-amount returned is assumed to be before applying leverage.
### Increase position
The strategy is expected to return a positive **stake_amount** (in stake currency) between `min_stake` and `max_stake` if and when an additional entry order should be made (position is increased -> buy order for long trades, sell order for short trades).
If there are not enough funds in the wallet (the return value is above `max_stake`) then the signal will be ignored.
`max_entry_position_adjustment` property is used to limit the number of additional entries per trade (on top of the first entry order) that the bot can execute. By default, the value is -1 which means the bot have no limit on number of adjustment entries.
Additional entries are ignored once you have reached the maximum amount of extra entries that you have set on `max_entry_position_adjustment`, but the callback is called anyway looking for partial exits.
### Decrease position
The strategy is expected to return a negative stake_amount (in stake currency) for a partial exit.
Returning the full owned stake at that point (based on the current price) (`-(trade.amount / trade.leverage) * current_exit_rate`) results in a full exit.
Returning a value more than the above (so remaining stake_amount would become negative) will result in the bot ignoring the signal.
!!! Note "About stake size"
Using fixed stake size means it will be the amount used for the first order, just like without position adjustment.
If you wish to buy additional orders with DCA, then make sure to leave enough funds in the wallet for that.
docs/strategy-customization.md
+5
View File
@@ -367,6 +367,11 @@ class AwesomeStrategy(IStrategy):
}
```
??? info "Orders that don't fill immediately"
`minimal_roi` will take the `trade.open_date` as reference, which is the time the trade was initialized / the first order for this trade was placed.
This will also hold true for limit orders that don't fill immediately (usually in combination with "off-spot" prices through `custom_entry_price()`), as well as for cases where the initial order is replaced through `adjust_entry_price()`.
The time used will still be from the initial `trade.open_date` (when the initial order was first placed), not from the newly placed order date.
### Stoploss
Setting a stoploss is highly recommended to protect your capital from strong moves against you.
docs/utils.md
-2
View File
@@ -242,7 +242,6 @@ bitkk True missing opt: fetchMyTrades
bitmart True
bitmax True missing opt: fetchMyTrades
bitpanda True
bittrex True
bitvavo True
bitz True missing opt: fetchMyTrades
btcalpha True missing opt: fetchTicker, fetchTickers
@@ -324,7 +323,6 @@ bitpanda True
bitso False missing: fetchOHLCV
bitstamp True missing opt: fetchTickers
bitstamp1 False missing: fetchOrder, fetchOHLCV
bittrex True
bitvavo True
bitz True missing opt: fetchMyTrades
bl3p False missing: fetchOrder, fetchOHLCV
docs/webhook-config.md
+6
View File
@@ -134,6 +134,7 @@ Possible parameters are:
* `stake_amount`
* `stake_currency`
* `base_currency`
* `quote_currency`
* `fiat_currency`
* `order_type`
* `current_rate`
@@ -155,6 +156,7 @@ Possible parameters are:
* `stake_amount`
* `stake_currency`
* `base_currency`
* `quote_currency`
* `fiat_currency`
* `order_type`
* `current_rate`
@@ -176,6 +178,7 @@ Possible parameters are:
* `stake_amount`
* `stake_currency`
* `base_currency`
* `quote_currency`
* `fiat_currency`
* `order_type`
* `current_rate`
@@ -199,6 +202,7 @@ Possible parameters are:
* `profit_ratio`
* `stake_currency`
* `base_currency`
* `quote_currency`
* `fiat_currency`
* `exit_reason`
* `order_type`
@@ -224,6 +228,7 @@ Possible parameters are:
* `profit_ratio`
* `stake_currency`
* `base_currency`
* `quote_currency`
* `fiat_currency`
* `exit_reason`
* `order_type`
@@ -249,6 +254,7 @@ Possible parameters are:
* `profit_ratio`
* `stake_currency`
* `base_currency`
* `quote_currency`
* `fiat_currency`
* `exit_reason`
* `order_type`
freqtrade/__init__.py
+1 -1
View File
@@ -1,5 +1,5 @@
""" Freqtrade bot """
__version__ = '2023.12-dev'
__version__ = '2024.1-dev'
if 'dev' in __version__:
from pathlib import Path
freqtrade/commands/data_commands.py
+2 -2
View File
@@ -12,7 +12,7 @@ from freqtrade.enums import RunMode, TradingMode
from freqtrade.exceptions import OperationalException
from freqtrade.exchange import timeframe_to_minutes
from freqtrade.resolvers import ExchangeResolver
from freqtrade.util.binance_mig import migrate_binance_futures_data
from freqtrade.util.migrations import migrate_data
logger = logging.getLogger(__name__)
@@ -78,7 +78,7 @@ def start_convert_data(args: Dict[str, Any], ohlcv: bool = True) -> None:
"""
config = setup_utils_configuration(args, RunMode.UTIL_NO_EXCHANGE)
if ohlcv:
migrate_binance_futures_data(config)
migrate_data(config)
convert_ohlcv_format(config,
convert_from=args['format_from'],
convert_to=args['format_to'],
freqtrade/commands/optimize_commands.py
+3 -3
View File
@@ -5,7 +5,7 @@ from freqtrade import constants
from freqtrade.configuration import setup_utils_configuration
from freqtrade.enums import RunMode
from freqtrade.exceptions import OperationalException
from freqtrade.misc import round_coin_value
from freqtrade.util import fmt_coin
logger = logging.getLogger(__name__)
@@ -29,8 +29,8 @@ def setup_optimize_configuration(args: Dict[str, Any], method: RunMode) -> Dict[
# tradable_balance_ratio
if (config['stake_amount'] != constants.UNLIMITED_STAKE_AMOUNT
and config['stake_amount'] > wallet_size):
wallet = round_coin_value(wallet_size, config['stake_currency'])
stake = round_coin_value(config['stake_amount'], config['stake_currency'])
wallet = fmt_coin(wallet_size, config['stake_currency'])
stake = fmt_coin(config['stake_amount'], config['stake_currency'])
raise OperationalException(
f"Starting balance ({wallet}) is smaller than stake_amount {stake}. "
f"Wallet is calculated as `dry_run_wallet * tradable_balance_ratio`."
freqtrade/configuration/config_validation.py
+4 -4
View File
@@ -67,7 +67,7 @@ def validate_config_schema(conf: Dict[str, Any], preliminary: bool = False) -> D
)
def validate_config_consistency(conf: Dict[str, Any], preliminary: bool = False) -> None:
def validate_config_consistency(conf: Dict[str, Any], *, preliminary: bool = False) -> None:
"""
Validate the configuration consistency.
Should be ran after loading both configuration and strategy,
@@ -86,7 +86,7 @@ def validate_config_consistency(conf: Dict[str, Any], preliminary: bool = False)
_validate_ask_orderbook(conf)
_validate_freqai_hyperopt(conf)
_validate_freqai_backtest(conf)
_validate_freqai_include_timeframes(conf)
_validate_freqai_include_timeframes(conf, preliminary=preliminary)
_validate_consumers(conf)
validate_migrated_strategy_settings(conf)
@@ -335,7 +335,7 @@ def _validate_freqai_hyperopt(conf: Dict[str, Any]) -> None:
'Using analyze-per-epoch parameter is not supported with a FreqAI strategy.')
def _validate_freqai_include_timeframes(conf: Dict[str, Any]) -> None:
def _validate_freqai_include_timeframes(conf: Dict[str, Any], preliminary: bool) -> None:
freqai_enabled = conf.get('freqai', {}).get('enabled', False)
if freqai_enabled:
main_tf = conf.get('timeframe', '5m')
@@ -355,7 +355,7 @@ def _validate_freqai_include_timeframes(conf: Dict[str, Any]) -> None:
f"`include_timeframes`.Offending include-timeframes: {', '.join(offending_lines)}")
# Ensure that the base timeframe is included in the include_timeframes list
if main_tf not in freqai_include_timeframes:
if not preliminary and main_tf not in freqai_include_timeframes:
feature_parameters = conf.get('freqai', {}).get('feature_parameters', {})
include_timeframes = [main_tf] + freqai_include_timeframes
conf.get('freqai', {}).get('feature_parameters', {}) \
freqtrade/constants.py
+1 -1
View File
@@ -105,7 +105,7 @@ SUPPORTED_FIAT = [
"EUR", "GBP", "HKD", "HUF", "IDR", "ILS", "INR", "JPY",
"KRW", "MXN", "MYR", "NOK", "NZD", "PHP", "PKR", "PLN",
"RUB", "UAH", "SEK", "SGD", "THB", "TRY", "TWD", "ZAR",
"USD", "BTC", "ETH", "XRP", "LTC", "BCH"
"USD", "BTC", "ETH", "XRP", "LTC", "BCH", "BNB"
]
MINIMAL_CONFIG = {
freqtrade/data/btanalysis.py
+23 -16
View File
@@ -175,36 +175,40 @@ def _get_backtest_files(dirname: Path) -> List[Path]:
return list(reversed(sorted(dirname.glob('backtest-result-*-[0-9][0-9].json'))))
def get_backtest_result(filename: Path) -> List[BacktestHistoryEntryType]:
"""
Get backtest result read from metadata file
"""
def _extract_backtest_result(filename: Path) -> List[BacktestHistoryEntryType]:
metadata = load_backtest_metadata(filename)
return [
{
'filename': filename.stem,
'strategy': s,
'notes': v.get('notes', ''),
'run_id': v['run_id'],
'notes': v.get('notes', ''),
# Backtest "run" time
'backtest_start_time': v['backtest_start_time'],
} for s, v in load_backtest_metadata(filename).items()
# Backtest timerange
'backtest_start_ts': v.get('backtest_start_ts', None),
'backtest_end_ts': v.get('backtest_end_ts', None),
'timeframe': v.get('timeframe', None),
'timeframe_detail': v.get('timeframe_detail', None),
} for s, v in metadata.items()
]
def get_backtest_result(filename: Path) -> List[BacktestHistoryEntryType]:
"""
Get backtest result read from metadata file
"""
return _extract_backtest_result(filename)
def get_backtest_resultlist(dirname: Path) -> List[BacktestHistoryEntryType]:
"""
Get list of backtest results read from metadata files
"""
return [
{
'filename': filename.stem,
'strategy': s,
'run_id': v['run_id'],
'notes': v.get('notes', ''),
'backtest_start_time': v['backtest_start_time'],
}
result
for filename in _get_backtest_files(dirname)
for s, v in load_backtest_metadata(filename).items()
if v
for result in _extract_backtest_result(filename)
]
@@ -326,7 +330,10 @@ def load_backtest_data(filename: Union[Path, str], strategy: Optional[str] = Non
"Please specify a strategy.")
if strategy not in data['strategy']:
raise ValueError(f"Strategy {strategy} not available in the backtest result.")
raise ValueError(
f"Strategy {strategy} not available in the backtest result. "
f"Available strategies are '{','.join(data['strategy'].keys())}'"
)
data = data['strategy'][strategy]['trades']
df = pd.DataFrame(data)
freqtrade/data/converter/converter.py
+2 -2
View File
@@ -116,8 +116,8 @@ def ohlcv_fill_up_missing_data(dataframe: DataFrame, timeframe: str, pair: str)
len_after = len(df)
pct_missing = (len_after - len_before) / len_before if len_before > 0 else 0
if len_before != len_after:
message = (f"Missing data fillup for {pair}: before: {len_before} - after: {len_after}"
f" - {pct_missing:.2%}")
message = (f"Missing data fillup for {pair}, {timeframe}: "
f"before: {len_before} - after: {len_after} - {pct_missing:.2%}")
if pct_missing > 0.01:
logger.info(message)
else:
freqtrade/data/dataprovider.py
+10 -9
View File
@@ -311,11 +311,13 @@ class DataProvider:
timerange = TimeRange.parse_timerange(None if self._config.get(
'timerange') is None else str(self._config.get('timerange')))
# It is not necessary to add the training candles, as they
# were already added at the beginning of the backtest.
startup_candles = self.get_required_startup(str(timeframe), False)
startup_candles = self.get_required_startup(str(timeframe))
tf_seconds = timeframe_to_seconds(str(timeframe))
timerange.subtract_start(tf_seconds * startup_candles)
logger.info(f"Loading data for {pair} {timeframe} "
f"from {timerange.start_fmt} to {timerange.stop_fmt}")
self.__cached_pairs_backtesting[saved_pair] = load_pair_history(
pair=pair,
timeframe=timeframe,
@@ -327,7 +329,7 @@ class DataProvider:
)
return self.__cached_pairs_backtesting[saved_pair].copy()
def get_required_startup(self, timeframe: str, add_train_candles: bool = True) -> int:
def get_required_startup(self, timeframe: str) -> int:
freqai_config = self._config.get('freqai', {})
if not freqai_config.get('enabled', False):
return self._config.get('startup_candle_count', 0)
@@ -337,12 +339,11 @@ class DataProvider:
# make sure the startupcandles is at least the set maximum indicator periods
self._config['startup_candle_count'] = max(startup_candles, max(indicator_periods))
tf_seconds = timeframe_to_seconds(timeframe)
train_candles = 0
if add_train_candles:
train_candles = freqai_config['train_period_days'] * 86400 / tf_seconds
train_candles = freqai_config['train_period_days'] * 86400 / tf_seconds
total_candles = int(self._config['startup_candle_count'] + train_candles)
logger.info(f'Increasing startup_candle_count for freqai to {total_candles}')
return total_candles
logger.info(
f'Increasing startup_candle_count for freqai on {timeframe} to {total_candles}')
return total_candles
def get_pair_dataframe(
self,
freqtrade/data/history/history_utils.py
+16 -6
View File
@@ -8,7 +8,7 @@ from pandas import DataFrame, concat
from freqtrade.configuration import TimeRange
from freqtrade.constants import (DATETIME_PRINT_FORMAT, DEFAULT_DATAFRAME_COLUMNS,
DL_DATA_TIMEFRAMES, Config)
DL_DATA_TIMEFRAMES, DOCS_LINK, Config)
from freqtrade.data.converter import (clean_ohlcv_dataframe, convert_trades_to_ohlcv,
ohlcv_to_dataframe, trades_df_remove_duplicates,
trades_list_to_df)
@@ -18,8 +18,8 @@ from freqtrade.exceptions import OperationalException
from freqtrade.exchange import Exchange
from freqtrade.plugins.pairlist.pairlist_helpers import dynamic_expand_pairlist
from freqtrade.util import dt_ts, format_ms_time
from freqtrade.util.binance_mig import migrate_binance_futures_data
from freqtrade.util.datetime_helpers import dt_now
from freqtrade.util.migrations import migrate_data
logger = logging.getLogger(__name__)
@@ -311,15 +311,19 @@ def refresh_backtest_ohlcv_data(exchange: Exchange, pairs: List[str], timeframes
# Predefined candletype (and timeframe) depending on exchange
# Downloads what is necessary to backtest based on futures data.
tf_mark = exchange.get_option('mark_ohlcv_timeframe')
tf_funding_rate = exchange.get_option('funding_fee_timeframe')
fr_candle_type = CandleType.from_string(exchange.get_option('mark_ohlcv_price'))
# All exchanges need FundingRate for futures trading.
# The timeframe is aligned to the mark-price timeframe.
for funding_candle_type in (CandleType.FUNDING_RATE, fr_candle_type):
combs = ((CandleType.FUNDING_RATE, tf_funding_rate), (fr_candle_type, tf_mark))
for candle_type_f, tf in combs:
logger.debug(f'Downloading pair {pair}, {candle_type_f}, interval {tf}.')
_download_pair_history(pair=pair, process=process,
datadir=datadir, exchange=exchange,
timerange=timerange, data_handler=data_handler,
timeframe=str(tf_mark), new_pairs_days=new_pairs_days,
candle_type=funding_candle_type,
timeframe=str(tf), new_pairs_days=new_pairs_days,
candle_type=candle_type_f,
erase=erase, prepend=prepend)
return pairs_not_available
@@ -500,6 +504,12 @@ def download_data_main(config: Config) -> None:
logger.info(f"About to download pairs: {expanded_pairs}, "
f"intervals: {config['timeframes']} to {config['datadir']}")
if len(expanded_pairs) == 0:
logger.warning(
"No pairs available for download. "
"Please make sure you're using the correct Pair naming for your selected trade mode. \n"
f"More info: {DOCS_LINK}/bot-basics/#pair-naming")
for timeframe in config['timeframes']:
exchange.validate_timeframes(timeframe)
@@ -527,7 +537,7 @@ def download_data_main(config: Config) -> None:
"Please use `--dl-trades` instead for this exchange "
"(will unfortunately take a long time)."
)
migrate_binance_futures_data(config)
migrate_data(config, exchange)
pairs_not_available = refresh_backtest_ohlcv_data(
exchange, pairs=expanded_pairs, timeframes=config['timeframes'],
datadir=config['datadir'], timerange=timerange,
freqtrade/data/history/idatahandler.py
+28
View File
@@ -403,6 +403,34 @@ class IDataHandler(ABC):
return
file_old.rename(file_new)
def fix_funding_fee_timeframe(self, ff_timeframe: str):
"""
Temporary method to migrate data from old funding fee timeframe to the correct timeframe
Applies to bybit and okx, where funding-fee and mark candles have different timeframes.
"""
paircombs = self.ohlcv_get_available_data(self._datadir, TradingMode.FUTURES)
funding_rate_combs = [
f for f in paircombs if f[2] == CandleType.FUNDING_RATE and f[1] != ff_timeframe
]
if funding_rate_combs:
logger.warning(
f'Migrating {len(funding_rate_combs)} funding fees to correct timeframe.')
for pair, timeframe, candletype in funding_rate_combs:
old_name = self._pair_data_filename(self._datadir, pair, timeframe, candletype)
new_name = self._pair_data_filename(self._datadir, pair, ff_timeframe, candletype)
if not Path(old_name).exists():
logger.warning(f'{old_name} does not exist, skipping.')
continue
if Path(new_name).exists():
logger.warning(f'{new_name} already exists, Removing.')
Path(new_name).unlink()
Path(old_name).rename(new_name)
def get_datahandlerclass(datatype: str) -> Type[IDataHandler]:
"""
freqtrade/exchange/__init__.py
-1
View File
@@ -6,7 +6,6 @@ from freqtrade.exchange.exchange import Exchange
from freqtrade.exchange.binance import Binance
from freqtrade.exchange.bitmart import Bitmart
from freqtrade.exchange.bitpanda import Bitpanda
from freqtrade.exchange.bittrex import Bittrex
from freqtrade.exchange.bitvavo import Bitvavo
from freqtrade.exchange.bybit import Bybit
from freqtrade.exchange.coinbasepro import Coinbasepro
freqtrade/exchange/binance_leverage_tiers.json
+2838 -444
View File
File diff suppressed because it is too large Load Diff
freqtrade/exchange/bittrex.py
-25
View File
@@ -1,25 +0,0 @@
""" Bittrex exchange subclass """
import logging
from typing import Dict
from freqtrade.exchange import Exchange
logger = logging.getLogger(__name__)
class Bittrex(Exchange):
"""
Bittrex exchange class. Contains adjustments needed for Freqtrade to work
with this exchange.
"""
_ft_has: Dict = {
"ohlcv_candle_limit_per_timeframe": {
'1m': 1440,
'5m': 288,
'1h': 744,
'1d': 365,
},
"l2_limit_range": [1, 25, 500],
}
freqtrade/exchange/bybit.py
+1
View File
@@ -29,6 +29,7 @@ class Bybit(Exchange):
_ft_has: Dict = {
"ohlcv_candle_limit": 1000,
"ohlcv_has_history": True,
"order_time_in_force": ["GTC", "FOK", "IOC", "PO"],
}
_ft_has_futures: Dict = {
"ohlcv_has_history": True,
freqtrade/exchange/exchange.py
+16 -11
View File
@@ -80,6 +80,7 @@ class Exchange:
"l2_limit_range_required": True, # Allow Empty L2 limit (kucoin)
"mark_ohlcv_price": "mark",
"mark_ohlcv_timeframe": "8h",
"funding_fee_timeframe": "8h",
"ccxt_futures_name": "swap",
"needs_trading_fees": False, # use fetch_trading_fees to cache fees
"order_props_in_contracts": ['amount', 'filled', 'remaining'],
@@ -121,11 +122,12 @@ class Exchange:
# Cache for 10 minutes ...
self._cache_lock = Lock()
self._fetch_tickers_cache: TTLCache = TTLCache(maxsize=2, ttl=60 * 10)
# Cache values for 1800 to avoid frequent polling of the exchange for prices
# Cache values for 300 to avoid frequent polling of the exchange for prices
# Caching only applies to RPC methods, so prices for open trades are still
# refreshed once every iteration.
self._exit_rate_cache: TTLCache = TTLCache(maxsize=100, ttl=1800)
self._entry_rate_cache: TTLCache = TTLCache(maxsize=100, ttl=1800)
# Shouldn't be too high either, as it'll freeze UI updates in case of open orders.
self._exit_rate_cache: TTLCache = TTLCache(maxsize=100, ttl=300)
self._entry_rate_cache: TTLCache = TTLCache(maxsize=100, ttl=300)
# Holds candles
self._klines: Dict[PairWithTimeframe, DataFrame] = {}
@@ -319,10 +321,11 @@ class Exchange:
"""
pass
def _log_exchange_response(self, endpoint, response) -> None:
def _log_exchange_response(self, endpoint: str, response, *, add_info=None) -> None:
""" Log exchange responses """
if self.log_responses:
logger.info(f"API {endpoint}: {response}")
add_info_str = "" if add_info is None else f" {add_info}: "
logger.info(f"API {endpoint}: {add_info_str}{response}")
def ohlcv_candle_limit(
self, timeframe: str, candle_type: CandleType, since_ms: Optional[int] = None) -> int:
@@ -330,6 +333,7 @@ class Exchange:
Exchange ohlcv candle limit
Uses ohlcv_candle_limit_per_timeframe if the exchange has different limits
per timeframe (e.g. bittrex), otherwise falls back to ohlcv_candle_limit
TODO: this is most likely no longer needed since only bittrex needed this.
:param timeframe: Timeframe to check
:param candle_type: Candle-type
:param since_ms: Starting timestamp
@@ -1383,7 +1387,7 @@ class Exchange:
order = self.fetch_stoploss_order(order_id, pair)
except InvalidOrderException:
logger.warning(f"Could not fetch cancelled stoploss order {order_id}.")
order = {'fee': {}, 'status': 'canceled', 'amount': amount, 'info': {}}
order = {'id': order_id, 'fee': {}, 'status': 'canceled', 'amount': amount, 'info': {}}
return order
@@ -2413,6 +2417,8 @@ class Exchange:
symbol=pair,
since=since
)
self._log_exchange_response('funding_history', funding_history,
add_info=f"pair: {pair}, since: {since}")
return sum(fee['amount'] for fee in funding_history)
except ccxt.DDoSProtection as e:
raise DDosProtection(e) from e
@@ -2729,17 +2735,16 @@ class Exchange:
# Only really relevant for trades very close to the full hour
open_date = timeframe_to_prev_date('1h', open_date)
timeframe = self._ft_has['mark_ohlcv_timeframe']
timeframe_ff = self._ft_has.get('funding_fee_timeframe',
self._ft_has['mark_ohlcv_timeframe'])
timeframe_ff = self._ft_has['funding_fee_timeframe']
mark_price_type = CandleType.from_string(self._ft_has["mark_ohlcv_price"])
if not close_date:
close_date = datetime.now(timezone.utc)
since_ms = int(timeframe_to_prev_date(timeframe, open_date).timestamp()) * 1000
mark_comb: PairWithTimeframe = (
pair, timeframe, CandleType.from_string(self._ft_has["mark_ohlcv_price"]))
mark_comb: PairWithTimeframe = (pair, timeframe, mark_price_type)
funding_comb: PairWithTimeframe = (pair, timeframe_ff, CandleType.FUNDING_RATE)
candle_histories = self.refresh_latest_ohlcv(
[mark_comb, funding_comb],
since_ms=since_ms,
freqtrade/exchange/kraken.py
+4
View File
@@ -26,6 +26,7 @@ class Kraken(Exchange):
"stoploss_on_exchange": True,
"stop_price_param": "stopPrice",
"stop_price_prop": "stopPrice",
"order_time_in_force": ["GTC", "IOC", "PO"],
"ohlcv_candle_limit": 720,
"ohlcv_has_history": False,
"trades_pagination": "id",
@@ -187,6 +188,9 @@ class Kraken(Exchange):
)
if leverage > 1.0:
params['leverage'] = round(leverage)
if time_in_force == 'PO':
params.pop('timeInForce', None)
params['postOnly'] = True
return params
def calculate_funding_fees(
freqtrade/exchange/okx.py
+1 -1
View File
@@ -228,7 +228,7 @@ class Okx(Exchange):
f'StoplossOrder not found (pair: {pair} id: {order_id}).')
def get_order_id_conditional(self, order: Dict[str, Any]) -> str:
if order['type'] == 'stop':
if order.get('type', '') == 'stop':
return safe_value_fallback2(order, order, 'id_stop', 'id')
return order['id']
freqtrade/freqai/base_models/FreqaiMultiOutputClassifier.py
+1 -2
View File
@@ -1,9 +1,8 @@
import numpy as np
from joblib import Parallel
from sklearn.base import is_classifier
from sklearn.multioutput import MultiOutputClassifier, _fit_estimator
from sklearn.utils.fixes import delayed
from sklearn.utils.multiclass import check_classification_targets
from sklearn.utils.parallel import Parallel, delayed
from sklearn.utils.validation import has_fit_parameter
from freqtrade.exceptions import OperationalException
freqtrade/freqai/base_models/FreqaiMultiOutputRegressor.py
+1 -2
View File
@@ -1,6 +1,5 @@
from joblib import Parallel
from sklearn.multioutput import MultiOutputRegressor, _fit_estimator
from sklearn.utils.fixes import delayed
from sklearn.utils.parallel import Parallel, delayed
from sklearn.utils.validation import has_fit_parameter
freqtrade/freqai/data_drawer.py
+13 -6
View File
@@ -12,7 +12,6 @@ import numpy as np
import pandas as pd
import psutil
import rapidjson
from joblib import dump, load
from joblib.externals import cloudpickle
from numpy.typing import NDArray
from pandas import DataFrame
@@ -285,6 +284,10 @@ class FreqaiDataDrawer:
new_pred["date_pred"] = dataframe["date"]
hist_preds = self.historic_predictions[pair].copy()
# ensure both dataframes have the same date format so they can be merged
new_pred["date_pred"] = pd.to_datetime(new_pred["date_pred"])
hist_preds["date_pred"] = pd.to_datetime(hist_preds["date_pred"])
# find the closest common date between new_pred and historic predictions
# and cut off the new_pred dataframe at that date
common_dates = pd.merge(new_pred, hist_preds, on="date_pred", how="inner")
@@ -295,7 +298,9 @@ class FreqaiDataDrawer:
"predictions. You likely left your FreqAI instance offline "
f"for more than {len(dataframe.index)} candles.")
df_concat = pd.concat([hist_preds, new_pred], ignore_index=True, keys=hist_preds.keys())
# reindex new_pred columns to match the historic predictions dataframe
new_pred_reindexed = new_pred.reindex(columns=hist_preds.columns)
df_concat = pd.concat([hist_preds, new_pred_reindexed], ignore_index=True)
# any missing values will get zeroed out so users can see the exact
# downtime in FreqUI
@@ -318,9 +323,9 @@ class FreqaiDataDrawer:
index = self.historic_predictions[pair].index[-1:]
columns = self.historic_predictions[pair].columns
nan_df = pd.DataFrame(np.nan, index=index, columns=columns)
zeros_df = pd.DataFrame(np.zeros((1, len(columns))), index=index, columns=columns)
self.historic_predictions[pair] = pd.concat(
[self.historic_predictions[pair], nan_df], ignore_index=True, axis=0)
[self.historic_predictions[pair], zeros_df], ignore_index=True, axis=0)
df = self.historic_predictions[pair]
# model outputs and associated statistics
@@ -471,7 +476,8 @@ class FreqaiDataDrawer:
# Save the trained model
if self.model_type == 'joblib':
dump(model, save_path / f"{dk.model_filename}_model.joblib")
with (save_path / f"{dk.model_filename}_model.joblib").open("wb") as fp:
cloudpickle.dump(model, fp)
elif self.model_type == 'keras':
model.save(save_path / f"{dk.model_filename}_model.h5")
elif self.model_type in ["stable_baselines3", "sb3_contrib", "pytorch"]:
@@ -558,7 +564,8 @@ class FreqaiDataDrawer:
if dk.live and coin in self.model_dictionary:
model = self.model_dictionary[coin]
elif self.model_type == 'joblib':
model = load(dk.data_path / f"{dk.model_filename}_model.joblib")
with (dk.data_path / f"{dk.model_filename}_model.joblib").open("rb") as fp:
model = cloudpickle.load(fp)
elif 'stable_baselines' in self.model_type or 'sb3_contrib' == self.model_type:
mod = importlib.import_module(
self.model_type, self.freqai_info['rl_config']['model_type'])
freqtrade/freqai/data_kitchen.py
+4 -1
View File
@@ -244,7 +244,7 @@ class FreqaiDataKitchen:
f"{self.pair}: dropped {len(unfiltered_df) - len(filtered_df)} training points"
f" due to NaNs in populated dataset {len(unfiltered_df)}."
)
if len(unfiltered_df) == 0 and not self.live:
if len(filtered_df) == 0 and not self.live:
raise OperationalException(
f"{self.pair}: all training data dropped due to NaNs. "
"You likely did not download enough training data prior "
@@ -709,6 +709,8 @@ class FreqaiDataKitchen:
pair, tf, strategy, corr_dataframes, base_dataframes, is_corr_pairs)
informative_copy = informative_df.copy()
logger.debug(f"Populating features for {pair} {tf}")
for t in self.freqai_config["feature_parameters"]["indicator_periods_candles"]:
df_features = strategy.feature_engineering_expand_all(
informative_copy.copy(), t, metadata=metadata)
@@ -788,6 +790,7 @@ class FreqaiDataKitchen:
if not prediction_dataframe.empty:
dataframe = prediction_dataframe.copy()
base_dataframes[self.config["timeframe"]] = dataframe.copy()
else:
dataframe = base_dataframes[self.config["timeframe"]].copy()
freqtrade/freqai/prediction_models/SKLearnRandomForestClassifier.py
+82
View File
@@ -0,0 +1,82 @@
import logging
from typing import Any, Dict, Tuple
import numpy as np
import numpy.typing as npt
from pandas import DataFrame
from sklearn.ensemble import RandomForestClassifier
from sklearn.preprocessing import LabelEncoder
from freqtrade.freqai.base_models.BaseClassifierModel import BaseClassifierModel
from freqtrade.freqai.data_kitchen import FreqaiDataKitchen
logger = logging.getLogger(__name__)
class SKLearnRandomForestClassifier(BaseClassifierModel):
"""
User created prediction model. The class inherits IFreqaiModel, which
means it has full access to all Frequency AI functionality. Typically,
users would use this to override the common `fit()`, `train()`, or
`predict()` methods to add their custom data handling tools or change
various aspects of the training that cannot be configured via the
top level config.json file.
"""
def fit(self, data_dictionary: Dict, dk: FreqaiDataKitchen, **kwargs) -> Any:
"""
User sets up the training and test data to fit their desired model here
:param data_dictionary: the dictionary holding all data for train, test,
labels, weights
:param dk: The datakitchen object for the current coin/model
"""
X = data_dictionary["train_features"].to_numpy()
y = data_dictionary["train_labels"].to_numpy()[:, 0]
if self.freqai_info.get('data_split_parameters', {}).get('test_size', 0.1) == 0:
eval_set = None
else:
test_features = data_dictionary["test_features"].to_numpy()
test_labels = data_dictionary["test_labels"].to_numpy()[:, 0]
eval_set = (test_features, test_labels)
if self.freqai_info.get("continual_learning", False):
logger.warning("Continual learning is not supported for "
"SKLearnRandomForestClassifier, ignoring.")
train_weights = data_dictionary["train_weights"]
model = RandomForestClassifier(**self.model_training_parameters)
model.fit(X=X, y=y, sample_weight=train_weights)
if eval_set:
logger.info("Score: %s", model.score(eval_set[0], eval_set[1]))
return model
def predict(
self, unfiltered_df: DataFrame, dk: FreqaiDataKitchen, **kwargs
) -> Tuple[DataFrame, npt.NDArray[np.int_]]:
"""
Filter the prediction features data and predict with it.
:param unfiltered_df: Full dataframe for the current backtest period.
:return:
:pred_df: dataframe containing the predictions
:do_predict: np.array of 1s and 0s to indicate places where freqai needed to remove
data (NaNs) or felt uncertain about data (PCA and DI index)
"""
(pred_df, dk.do_predict) = super().predict(unfiltered_df, dk, **kwargs)
le = LabelEncoder()
label = dk.label_list[0]
labels_before = list(dk.data['labels_std'].keys())
labels_after = le.fit_transform(labels_before).tolist()
pred_df[label] = le.inverse_transform(pred_df[label])
pred_df = pred_df.rename(
columns={labels_after[i]: labels_before[i] for i in range(len(labels_before))})
return (pred_df, dk.do_predict)
freqtrade/freqai/prediction_models/XGBoostRFRegressor.py
+1 -1
View File
@@ -45,7 +45,7 @@ class XGBoostRFRegressor(BaseRegressionModel):
model = XGBRFRegressor(**self.model_training_parameters)
model.set_params(callbacks=[TBCallback(dk.data_path)], activate=self.activate_tensorboard)
model.set_params(callbacks=[TBCallback(dk.data_path)])
model.fit(X=X, y=y, sample_weight=sample_weight, eval_set=eval_set,
sample_weight_eval_set=eval_weights, xgb_model=xgb_model)
# set the callbacks to empty so that we can serialize to disk later
freqtrade/freqai/prediction_models/XGBoostRegressor.py
+1 -1
View File
@@ -45,7 +45,7 @@ class XGBoostRegressor(BaseRegressionModel):
model = XGBRegressor(**self.model_training_parameters)
model.set_params(callbacks=[TBCallback(dk.data_path)], activate=self.activate_tensorboard)
model.set_params(callbacks=[TBCallback(dk.data_path)])
model.fit(X=X, y=y, sample_weight=sample_weight, eval_set=eval_set,
sample_weight_eval_set=eval_weights, xgb_model=xgb_model)
# set the callbacks to empty so that we can serialize to disk later
freqtrade/freqtradebot.py
+34 -36
View File
@@ -18,8 +18,8 @@ from freqtrade.constants import BuySell, Config, EntryExecuteMode, ExchangeConfi
from freqtrade.data.converter import order_book_to_dataframe
from freqtrade.data.dataprovider import DataProvider
from freqtrade.edge import Edge
from freqtrade.enums import (ExitCheckTuple, ExitType, RPCMessageType, RunMode, SignalDirection,
State, TradingMode)
from freqtrade.enums import (ExitCheckTuple, ExitType, RPCMessageType, SignalDirection, State,
TradingMode)
from freqtrade.exceptions import (DependencyException, ExchangeError, InsufficientFundsError,
InvalidOrderException, PricingError)
from freqtrade.exchange import (ROUND_DOWN, ROUND_UP, remove_exchange_credentials,
@@ -33,12 +33,12 @@ from freqtrade.plugins.protectionmanager import ProtectionManager
from freqtrade.resolvers import ExchangeResolver, StrategyResolver
from freqtrade.rpc import RPCManager
from freqtrade.rpc.external_message_consumer import ExternalMessageConsumer
from freqtrade.rpc.rpc_types import (RPCBuyMsg, RPCCancelMsg, RPCProtectionMsg, RPCSellCancelMsg,
RPCSellMsg)
from freqtrade.rpc.rpc_types import (ProfitLossStr, RPCCancelMsg, RPCEntryMsg, RPCExitCancelMsg,
RPCExitMsg, RPCProtectionMsg)
from freqtrade.strategy.interface import IStrategy
from freqtrade.strategy.strategy_wrapper import strategy_safe_wrapper
from freqtrade.util import FtPrecise
from freqtrade.util.binance_mig import migrate_binance_futures_names
from freqtrade.util.migrations import migrate_binance_futures_names
from freqtrade.wallets import Wallets
@@ -83,6 +83,8 @@ class FreqtradeBot(LoggingMixin):
PairLocks.timeframe = self.config['timeframe']
self.pairlists = PairListManager(self.exchange, self.config)
self.trading_mode: TradingMode = self.config.get('trading_mode', TradingMode.SPOT)
self.last_process: Optional[datetime] = None
# RPC runs in separate threads, can start handling external commands just after
# initialization, even before Freqtradebot has a chance to start its throttling,
@@ -119,8 +121,6 @@ class FreqtradeBot(LoggingMixin):
self._exit_lock = Lock()
LoggingMixin.__init__(self, logger, timeframe_to_seconds(self.strategy.timeframe))
self.trading_mode: TradingMode = self.config.get('trading_mode', TradingMode.SPOT)
self._schedule = Scheduler()
if self.trading_mode == TradingMode.FUTURES:
@@ -135,7 +135,6 @@ class FreqtradeBot(LoggingMixin):
for minutes in [1, 31]:
t = str(time(time_slot, minutes, 2))
self._schedule.every().day.at(t).do(update)
self.last_process: Optional[datetime] = None
self.strategy.ft_bot_start()
# Initialize protections AFTER bot start - otherwise parameters are not loaded.
@@ -580,7 +579,8 @@ class FreqtradeBot(LoggingMixin):
else:
self.log_once(f"Pair {pair} is currently locked.", logger.info)
return False
stake_amount = self.wallets.get_trade_stake_amount(pair, self.edge)
stake_amount = self.wallets.get_trade_stake_amount(
pair, self.config['max_open_trades'], self.edge)
bid_check_dom = self.config.get('entry_pricing', {}).get('check_depth_of_market', {})
if ((bid_check_dom.get('enabled', False)) and
@@ -672,20 +672,13 @@ class FreqtradeBot(LoggingMixin):
amount = self.exchange.amount_to_contract_precision(
trade.pair,
abs(float(FtPrecise(stake_amount * trade.leverage) / FtPrecise(current_exit_rate))))
if amount > trade.amount:
# This is currently ineffective as remaining would become < min tradable
# Fixing this would require checking for 0.0 there -
# if we decide that this callback is allowed to "fully exit"
logger.info(
f"Adjusting amount to trade.amount as it is higher. {amount} > {trade.amount}")
amount = trade.amount
if amount == 0.0:
logger.info("Amount to exit is 0.0 due to exchange limits - not exiting.")
return
remaining = (trade.amount - amount) * current_exit_rate
if min_exit_stake and remaining < min_exit_stake:
if min_exit_stake and remaining != 0 and remaining < min_exit_stake:
logger.info(f"Remaining amount of {remaining} would be smaller "
f"than the minimum of {min_exit_stake}.")
return
@@ -903,7 +896,7 @@ class FreqtradeBot(LoggingMixin):
# First cancelling stoploss on exchange ...
if trade.stoploss_order_id:
try:
logger.info(f"Canceling stoploss on exchange for {trade}")
logger.info(f"Cancelling stoploss on exchange for {trade}")
co = self.exchange.cancel_stoploss_order_with_result(
trade.stoploss_order_id, trade.pair, trade.amount)
self.update_trade_state(trade, trade.stoploss_order_id, co, stoploss_order=True)
@@ -1009,12 +1002,10 @@ class FreqtradeBot(LoggingMixin):
if open_rate is None:
open_rate = trade.open_rate
current_rate = trade.open_rate_requested
if self.dataprovider.runmode in (RunMode.DRY_RUN, RunMode.LIVE):
current_rate = self.exchange.get_rate(
trade.pair, side='entry', is_short=trade.is_short, refresh=False)
current_rate = self.exchange.get_rate(
trade.pair, side='entry', is_short=trade.is_short, refresh=False)
msg: RPCBuyMsg = {
msg: RPCEntryMsg = {
'trade_id': trade.id,
'type': RPCMessageType.ENTRY_FILL if fill else RPCMessageType.ENTRY,
'buy_tag': trade.enter_tag,
@@ -1029,6 +1020,7 @@ class FreqtradeBot(LoggingMixin):
'stake_amount': trade.stake_amount,
'stake_currency': self.config['stake_currency'],
'base_currency': self.exchange.get_pair_base_currency(trade.pair),
'quote_currency': self.exchange.get_pair_quote_currency(trade.pair),
'fiat_currency': self.config.get('fiat_display_currency', None),
'amount': order.safe_amount_after_fee if fill else (order.amount or trade.amount),
'open_date': trade.open_date_utc or datetime.now(timezone.utc),
@@ -1062,6 +1054,7 @@ class FreqtradeBot(LoggingMixin):
'open_rate': trade.open_rate,
'stake_currency': self.config['stake_currency'],
'base_currency': self.exchange.get_pair_base_currency(trade.pair),
'quote_currency': self.exchange.get_pair_quote_currency(trade.pair),
'fiat_currency': self.config.get('fiat_display_currency', None),
'amount': trade.amount,
'open_date': trade.open_date,
@@ -1347,9 +1340,11 @@ class FreqtradeBot(LoggingMixin):
not_closed = order['status'] == 'open' or fully_cancelled
if not_closed:
if fully_cancelled or (
open_order and self.strategy.ft_check_timed_out(
trade, open_order, datetime.now(timezone.utc)
if (
fully_cancelled or (
open_order and self.strategy.ft_check_timed_out(
trade, open_order, datetime.now(timezone.utc)
)
)
):
self.handle_cancel_order(
@@ -1791,9 +1786,9 @@ class FreqtradeBot(LoggingMixin):
order_rate = trade.safe_close_rate
profit = trade.calculate_profit(rate=order_rate)
amount = trade.amount
gain = "profit" if profit.profit_ratio > 0 else "loss"
gain: ProfitLossStr = "profit" if profit.profit_ratio > 0 else "loss"
msg: RPCSellMsg = {
msg: RPCExitMsg = {
'type': (RPCMessageType.EXIT_FILL if fill
else RPCMessageType.EXIT),
'trade_id': trade.id,
@@ -1809,20 +1804,22 @@ class FreqtradeBot(LoggingMixin):
'open_rate': trade.open_rate,
'close_rate': order_rate,
'current_rate': current_rate,
'profit_amount': profit.profit_abs if fill else profit.total_profit,
'profit_amount': profit.profit_abs,
'profit_ratio': profit.profit_ratio,
'buy_tag': trade.enter_tag,
'enter_tag': trade.enter_tag,
'sell_reason': trade.exit_reason, # Deprecated
'exit_reason': trade.exit_reason,
'open_date': trade.open_date_utc,
'close_date': trade.close_date_utc or datetime.now(timezone.utc),
'stake_amount': trade.stake_amount,
'stake_currency': self.config['stake_currency'],
'base_currency': self.exchange.get_pair_base_currency(trade.pair),
'quote_currency': self.exchange.get_pair_quote_currency(trade.pair),
'fiat_currency': self.config.get('fiat_display_currency'),
'sub_trade': sub_trade,
'cumulative_profit': trade.realized_profit,
'final_profit_ratio': trade.close_profit if not trade.is_open else None,
'is_final_exit': trade.is_open is False,
}
# Send the message
@@ -1845,9 +1842,9 @@ class FreqtradeBot(LoggingMixin):
profit = trade.calculate_profit(rate=profit_rate)
current_rate = self.exchange.get_rate(
trade.pair, side='exit', is_short=trade.is_short, refresh=False)
gain = "profit" if profit.profit_ratio > 0 else "loss"
gain: ProfitLossStr = "profit" if profit.profit_ratio > 0 else "loss"
msg: RPCSellCancelMsg = {
msg: RPCExitCancelMsg = {
'type': RPCMessageType.EXIT_CANCEL,
'trade_id': trade.id,
'exchange': trade.exchange.capitalize(),
@@ -1864,12 +1861,12 @@ class FreqtradeBot(LoggingMixin):
'profit_ratio': profit.profit_ratio,
'buy_tag': trade.enter_tag,
'enter_tag': trade.enter_tag,
'sell_reason': trade.exit_reason, # Deprecated
'exit_reason': trade.exit_reason,
'open_date': trade.open_date,
'close_date': trade.close_date or datetime.now(timezone.utc),
'stake_currency': self.config['stake_currency'],
'base_currency': self.exchange.get_pair_base_currency(trade.pair),
'quote_currency': self.exchange.get_pair_quote_currency(trade.pair),
'fiat_currency': self.config.get('fiat_display_currency', None),
'reason': reason,
'sub_trade': sub_trade,
@@ -1977,15 +1974,16 @@ class FreqtradeBot(LoggingMixin):
self, trade: Trade, order: Order, stoploss_order: bool, send_msg: bool):
"""send "fill" notifications"""
sub_trade = not isclose(order.safe_amount_after_fee,
trade.amount, abs_tol=constants.MATH_CLOSE_PREC)
if order.ft_order_side == trade.exit_side:
# Exit notification
if send_msg and not stoploss_order and order.order_id not in trade.open_orders_ids:
self._notify_exit(trade, '', fill=True, sub_trade=sub_trade, order=order)
self._notify_exit(trade, order.order_type, fill=True,
sub_trade=trade.is_open, order=order)
if not trade.is_open:
self.handle_protections(trade.pair, trade.trade_direction)
elif send_msg and order.order_id not in trade.open_orders_ids and not stoploss_order:
sub_trade = not isclose(order.safe_amount_after_fee,
trade.amount, abs_tol=constants.MATH_CLOSE_PREC)
# Enter fill
self._notify_enter(trade, order, order.order_type, fill=True, sub_trade=sub_trade)
freqtrade/misc.py
-29
View File
@@ -11,41 +11,12 @@ from urllib.parse import urlparse
import pandas as pd
import rapidjson
from freqtrade.constants import DECIMAL_PER_COIN_FALLBACK, DECIMALS_PER_COIN
from freqtrade.enums import SignalTagType, SignalType
logger = logging.getLogger(__name__)
def decimals_per_coin(coin: str):
"""
Helper method getting decimal amount for this coin
example usage: f".{decimals_per_coin('USD')}f"
:param coin: Which coin are we printing the price / value for
"""
return DECIMALS_PER_COIN.get(coin, DECIMAL_PER_COIN_FALLBACK)
def round_coin_value(
value: float, coin: str, show_coin_name=True, keep_trailing_zeros=False) -> str:
"""
Get price value for this coin
:param value: Value to be printed
:param coin: Which coin are we printing the price / value for
:param show_coin_name: Return string in format: "222.22 USDT" or "222.22"
:param keep_trailing_zeros: Keep trailing zeros "222.200" vs. "222.2"
:return: Formatted / rounded value (with or without coin name)
"""
val = f"{value:.{decimals_per_coin(coin)}f}"
if not keep_trailing_zeros:
val = val.rstrip('0').rstrip('.')
if show_coin_name:
val = f"{val} {coin}"
return val
def file_dump_json(filename: Path, data: Any, is_zip: bool = False, log: bool = True) -> None:
"""
Dump JSON data into a file
freqtrade/optimize/backtesting.py
+43 -26
View File
@@ -40,7 +40,7 @@ from freqtrade.resolvers import ExchangeResolver, StrategyResolver
from freqtrade.strategy.interface import IStrategy
from freqtrade.strategy.strategy_wrapper import strategy_safe_wrapper
from freqtrade.types import BacktestResultType, get_BacktestResultType_default
from freqtrade.util.binance_mig import migrate_binance_futures_data
from freqtrade.util.migrations import migrate_data
from freqtrade.wallets import Wallets
@@ -145,19 +145,20 @@ class Backtesting:
self.required_startup = max([strat.startup_candle_count for strat in self.strategylist])
self.exchange.validate_required_startup_candles(self.required_startup, self.timeframe)
if self.config.get('freqai', {}).get('enabled', False):
# For FreqAI, increase the required_startup to includes the training data
self.required_startup = self.dataprovider.get_required_startup(self.timeframe)
# Add maximum startup candle count to configuration for informative pairs support
self.config['startup_candle_count'] = self.required_startup
if self.config.get('freqai', {}).get('enabled', False):
# For FreqAI, increase the required_startup to includes the training data
# This value should NOT be written to startup_candle_count
self.required_startup = self.dataprovider.get_required_startup(self.timeframe)
self.trading_mode: TradingMode = config.get('trading_mode', TradingMode.SPOT)
# strategies which define "can_short=True" will fail to load in Spot mode.
self._can_short = self.trading_mode != TradingMode.SPOT
self._position_stacking: bool = self.config.get('position_stacking', False)
self.enable_protections: bool = self.config.get('enable_protections', False)
migrate_binance_futures_data(config)
migrate_data(config, self.exchange)
self.init_backtest()
@@ -239,7 +240,7 @@ class Backtesting:
pairs=self.pairlists.whitelist,
timeframe=self.timeframe,
timerange=self.timerange,
startup_candles=self.config['startup_candle_count'],
startup_candles=self.required_startup,
fail_without_data=True,
data_format=self.config['dataformat_ohlcv'],
candle_type=self.config.get('candle_type_def', CandleType.SPOT)
@@ -276,11 +277,15 @@ class Backtesting:
else:
self.detail_data = {}
if self.trading_mode == TradingMode.FUTURES:
self.funding_fee_timeframe: str = self.exchange.get_option('funding_fee_timeframe')
self.funding_fee_timeframe_secs: int = timeframe_to_seconds(self.funding_fee_timeframe)
mark_timeframe: str = self.exchange.get_option('mark_ohlcv_timeframe')
# Load additional futures data.
funding_rates_dict = history.load_data(
datadir=self.config['datadir'],
pairs=self.pairlists.whitelist,
timeframe=self.exchange.get_option('mark_ohlcv_timeframe'),
timeframe=self.funding_fee_timeframe,
timerange=self.timerange,
startup_candles=0,
fail_without_data=True,
@@ -292,7 +297,7 @@ class Backtesting:
mark_rates_dict = history.load_data(
datadir=self.config['datadir'],
pairs=self.pairlists.whitelist,
timeframe=self.exchange.get_option('mark_ohlcv_timeframe'),
timeframe=mark_timeframe,
timerange=self.timerange,
startup_candles=0,
fail_without_data=True,
@@ -528,7 +533,7 @@ class Backtesting:
def _get_adjust_trade_entry_for_candle(
self, trade: LocalTrade, row: Tuple, current_time: datetime
) -> LocalTrade:
current_rate = row[OPEN_IDX]
current_rate: float = row[OPEN_IDX]
current_profit = trade.calc_profit_ratio(current_rate)
min_stake = self.exchange.get_min_pair_stake_amount(trade.pair, current_rate, -0.1)
max_stake = self.exchange.get_max_pair_stake_amount(trade.pair, current_rate)
@@ -561,11 +566,8 @@ class Backtesting:
self.precision_mode, trade.contract_size)
if amount == 0.0:
return trade
if amount > trade.amount:
# This is currently ineffective as remaining would become < min tradable
amount = trade.amount
remaining = (trade.amount - amount) * current_rate
if remaining < min_stake:
if min_stake and remaining != 0 and remaining < min_stake:
# Remaining stake is too low to be sold.
return trade
exit_ = ExitCheckTuple(ExitType.PARTIAL_EXIT)
@@ -597,6 +599,8 @@ class Backtesting:
"""
if order and self._get_order_filled(order.ft_price, row):
order.close_bt_order(current_date, trade)
self._run_funding_fees(trade, current_date, force=True)
if not (order.ft_order_side == trade.exit_side and order.safe_amount == trade.amount):
# trade is still open
trade.set_liquidation_price(self.exchange.get_liquidation_price(
@@ -718,16 +722,7 @@ class Backtesting:
self, trade: LocalTrade, row: Tuple, current_time: datetime
) -> Optional[LocalTrade]:
if self.trading_mode == TradingMode.FUTURES:
trade.set_funding_fees(
self.exchange.calculate_funding_fees(
self.futures_data[trade.pair],
amount=trade.amount,
is_short=trade.is_short,
open_date=trade.date_last_filled_utc,
close_date=current_time
)
)
self._run_funding_fees(trade, current_time)
# Check if we need to adjust our current positions
if self.strategy.position_adjustment_enable:
@@ -746,6 +741,27 @@ class Backtesting:
return t
return None
def _run_funding_fees(self, trade: LocalTrade, current_time: datetime, force: bool = False):
"""
Calculate funding fees if necessary and add them to the trade.
"""
if self.trading_mode == TradingMode.FUTURES:
if (
force
or (current_time.timestamp() % self.funding_fee_timeframe_secs) == 0
):
# Funding fee interval.
trade.set_funding_fees(
self.exchange.calculate_funding_fees(
self.futures_data[trade.pair],
amount=trade.amount,
is_short=trade.is_short,
open_date=trade.date_last_filled_utc,
close_date=current_time
)
)
def get_valid_price_and_stake(
self, pair: str, row: Tuple, propose_rate: float, stake_amount: float,
direction: LongShort, current_time: datetime, entry_tag: Optional[str],
@@ -775,7 +791,8 @@ class Backtesting:
leverage = trade.leverage if trade else 1.0
if not pos_adjust:
try:
stake_amount = self.wallets.get_trade_stake_amount(pair, None, update=False)
stake_amount = self.wallets.get_trade_stake_amount(
pair, self.strategy.max_open_trades, update=False)
except DependencyException:
return 0, 0, 0, 0
@@ -957,7 +974,7 @@ class Backtesting:
def trade_slot_available(self, open_trade_count: int) -> bool:
# Always allow trades when max_open_trades is enabled.
max_open_trades: IntOrInf = self.config['max_open_trades']
max_open_trades: IntOrInf = self.strategy.max_open_trades
if max_open_trades <= 0 or open_trade_count < max_open_trades:
return True
# Rejected trade
freqtrade/optimize/hyperopt.py
+5 -1
View File
@@ -500,7 +500,7 @@ class Hyperopt:
while i < 5 and len(asked_non_tried) < n_points:
if i < 3:
self.opt.cache_ = {}
asked = unique_list(self.opt.ask(n_points=n_points * 5))
asked = unique_list(self.opt.ask(n_points=n_points * 5 if i > 0 else n_points))
is_random = [False for _ in range(len(asked))]
else:
asked = unique_list(self.opt.space.rvs(n_samples=n_points * 5))
@@ -637,6 +637,10 @@ class Hyperopt:
HyperoptTools.show_epoch_details(self.current_best_epoch, self.total_epochs,
self.print_json)
elif self.num_epochs_saved > 0:
print(
f"No good result found for given optimization function in {self.num_epochs_saved} "
f"{plural(self.num_epochs_saved, 'epoch')}.")
else:
# This is printed when Ctrl+C is pressed quickly, before first epochs have
# a chance to be evaluated.
freqtrade/optimize/hyperopt_tools.py
+4 -3
View File
@@ -14,9 +14,10 @@ from pandas import isna, json_normalize
from freqtrade.constants import FTHYPT_FILEVERSION, Config
from freqtrade.enums import HyperoptState
from freqtrade.exceptions import OperationalException
from freqtrade.misc import deep_merge_dicts, round_coin_value, round_dict, safe_value_fallback2
from freqtrade.misc import deep_merge_dicts, round_dict, safe_value_fallback2
from freqtrade.optimize.hyperopt_epoch_filters import hyperopt_filter_epochs
from freqtrade.optimize.optimize_reports import generate_wins_draws_losses
from freqtrade.util import fmt_coin
logger = logging.getLogger(__name__)
@@ -405,7 +406,7 @@ class HyperoptTools:
trials[f"Max Drawdown{' (Acct)' if has_account_drawdown else ''}"] = trials.apply(
lambda x: "{} {}".format(
round_coin_value(x['max_drawdown_abs'], stake_currency, keep_trailing_zeros=True),
fmt_coin(x['max_drawdown_abs'], stake_currency, keep_trailing_zeros=True),
(f"({x['max_drawdown_account']:,.2%})"
if has_account_drawdown
else f"({x['max_drawdown']:,.2%})"
@@ -420,7 +421,7 @@ class HyperoptTools:
trials['Profit'] = trials.apply(
lambda x: '{} {}'.format(
round_coin_value(x['Total profit'], stake_currency, keep_trailing_zeros=True),
fmt_coin(x['Total profit'], stake_currency, keep_trailing_zeros=True),
f"({x['Profit']:,.2%})".rjust(10, ' ')
).rjust(25 + len(stake_currency))
if x['Total profit'] != 0.0 else '--'.rjust(25 + len(stake_currency)),
freqtrade/optimize/optimize_reports/bt_output.py
+41 -48
View File
@@ -4,9 +4,9 @@ from typing import Any, Dict, List
from tabulate import tabulate
from freqtrade.constants import UNLIMITED_STAKE_AMOUNT, Config
from freqtrade.misc import decimals_per_coin, round_coin_value
from freqtrade.optimize.optimize_reports.optimize_reports import generate_periodic_breakdown_stats
from freqtrade.types import BacktestResultType
from freqtrade.util import decimals_per_coin, fmt_coin
logger = logging.getLogger(__name__)
@@ -63,7 +63,7 @@ def text_table_bt_results(pair_results: List[Dict[str, Any]], stake_currency: st
def text_table_exit_reason(exit_reason_stats: List[Dict[str, Any]], stake_currency: str) -> str:
"""
Generate small table outlining Backtest results
:param sell_reason_stats: Exit reason metrics
:param exit_reason_stats: Exit reason metrics
:param stake_currency: Stakecurrency used
:return: pretty printed table with tabulate as string
"""
@@ -81,7 +81,7 @@ def text_table_exit_reason(exit_reason_stats: List[Dict[str, Any]], stake_curren
t.get('exit_reason', t.get('sell_reason')), t['trades'],
generate_wins_draws_losses(t['wins'], t['draws'], t['losses']),
t['profit_mean_pct'], t['profit_sum_pct'],
round_coin_value(t['profit_total_abs'], stake_currency, False),
fmt_coin(t['profit_total_abs'], stake_currency, False),
t['profit_total_pct'],
] for t in exit_reason_stats]
return tabulate(output, headers=headers, tablefmt="orgtbl", stralign="right")
@@ -134,7 +134,7 @@ def text_table_periodic_breakdown(days_breakdown_stats: List[Dict[str, Any]],
'Losses',
]
output = [[
d['date'], round_coin_value(d['profit_abs'], stake_currency, False),
d['date'], fmt_coin(d['profit_abs'], stake_currency, False),
d['wins'], d['draws'], d['loses'],
] for d in days_breakdown_stats]
return tabulate(output, headers=headers, tablefmt="orgtbl", stralign="right")
@@ -187,10 +187,10 @@ def text_table_add_metrics(strat_results: Dict) -> str:
f"{strat_results.get('trade_count_short', 0)}"),
('Total profit Long %', f"{strat_results['profit_total_long']:.2%}"),
('Total profit Short %', f"{strat_results['profit_total_short']:.2%}"),
('Absolute profit Long', round_coin_value(strat_results['profit_total_long_abs'],
strat_results['stake_currency'])),
('Absolute profit Short', round_coin_value(strat_results['profit_total_short_abs'],
strat_results['stake_currency'])),
('Absolute profit Long', fmt_coin(strat_results['profit_total_long_abs'],
strat_results['stake_currency'])),
('Absolute profit Short', fmt_coin(strat_results['profit_total_short_abs'],
strat_results['stake_currency'])),
] if strat_results.get('trade_count_short', 0) > 0 else []
drawdown_metrics = []
@@ -203,12 +203,12 @@ def text_table_add_metrics(strat_results: Dict) -> str:
('Absolute Drawdown (Account)', f"{strat_results['max_drawdown_account']:.2%}")
if 'max_drawdown_account' in strat_results else (
'Drawdown', f"{strat_results['max_drawdown']:.2%}"),
('Absolute Drawdown', round_coin_value(strat_results['max_drawdown_abs'],
strat_results['stake_currency'])),
('Drawdown high', round_coin_value(strat_results['max_drawdown_high'],
strat_results['stake_currency'])),
('Drawdown low', round_coin_value(strat_results['max_drawdown_low'],
strat_results['stake_currency'])),
('Absolute Drawdown', fmt_coin(strat_results['max_drawdown_abs'],
strat_results['stake_currency'])),
('Drawdown high', fmt_coin(strat_results['max_drawdown_high'],
strat_results['stake_currency'])),
('Drawdown low', fmt_coin(strat_results['max_drawdown_low'],
strat_results['stake_currency'])),
('Drawdown Start', strat_results['drawdown_start']),
('Drawdown End', strat_results['drawdown_end']),
])
@@ -230,12 +230,12 @@ def text_table_add_metrics(strat_results: Dict) -> str:
('Total/Daily Avg Trades',
f"{strat_results['total_trades']} / {strat_results['trades_per_day']}"),
('Starting balance', round_coin_value(strat_results['starting_balance'],
strat_results['stake_currency'])),
('Final balance', round_coin_value(strat_results['final_balance'],
strat_results['stake_currency'])),
('Absolute profit ', round_coin_value(strat_results['profit_total_abs'],
strat_results['stake_currency'])),
('Starting balance', fmt_coin(strat_results['starting_balance'],
strat_results['stake_currency'])),
('Final balance', fmt_coin(strat_results['final_balance'],
strat_results['stake_currency'])),
('Absolute profit ', fmt_coin(strat_results['profit_total_abs'],
strat_results['stake_currency'])),
('Total profit %', f"{strat_results['profit_total']:.2%}"),
('CAGR %', f"{strat_results['cagr']:.2%}" if 'cagr' in strat_results else 'N/A'),
('Sortino', f"{strat_results['sortino']:.2f}" if 'sortino' in strat_results else 'N/A'),
@@ -249,10 +249,10 @@ def text_table_add_metrics(strat_results: Dict) -> str:
('Trades per day', strat_results['trades_per_day']),
('Avg. daily profit %',
f"{(strat_results['profit_total'] / strat_results['backtest_days']):.2%}"),
('Avg. stake amount', round_coin_value(strat_results['avg_stake_amount'],
strat_results['stake_currency'])),
('Total trade volume', round_coin_value(strat_results['total_volume'],
strat_results['stake_currency'])),
('Avg. stake amount', fmt_coin(strat_results['avg_stake_amount'],
strat_results['stake_currency'])),
('Total trade volume', fmt_coin(strat_results['total_volume'],
strat_results['stake_currency'])),
*short_metrics,
('', ''), # Empty line to improve readability
('Best Pair', f"{strat_results['best_pair']['key']} "
@@ -263,10 +263,10 @@ def text_table_add_metrics(strat_results: Dict) -> str:
('Worst trade', f"{worst_trade['pair']} "
f"{worst_trade['profit_ratio']:.2%}"),
('Best day', round_coin_value(strat_results['backtest_best_day_abs'],
strat_results['stake_currency'])),
('Worst day', round_coin_value(strat_results['backtest_worst_day_abs'],
strat_results['stake_currency'])),
('Best day', fmt_coin(strat_results['backtest_best_day_abs'],
strat_results['stake_currency'])),
('Worst day', fmt_coin(strat_results['backtest_worst_day_abs'],
strat_results['stake_currency'])),
('Days win/draw/lose', f"{strat_results['winning_days']} / "
f"{strat_results['draw_days']} / {strat_results['losing_days']}"),
('Avg. Duration Winners', f"{strat_results['winner_holding_avg']}"),
@@ -281,10 +281,8 @@ def text_table_add_metrics(strat_results: Dict) -> str:
*entry_adjustment_metrics,
('', ''), # Empty line to improve readability
('Min balance', round_coin_value(strat_results['csum_min'],
strat_results['stake_currency'])),
('Max balance', round_coin_value(strat_results['csum_max'],
strat_results['stake_currency'])),
('Min balance', fmt_coin(strat_results['csum_min'], strat_results['stake_currency'])),
('Max balance', fmt_coin(strat_results['csum_max'], strat_results['stake_currency'])),
*drawdown_metrics,
('Market change', f"{strat_results['market_change']:.2%}"),
@@ -292,9 +290,8 @@ def text_table_add_metrics(strat_results: Dict) -> str:
return tabulate(metrics, headers=["Metric", "Value"], tablefmt="orgtbl")
else:
start_balance = round_coin_value(strat_results['starting_balance'],
strat_results['stake_currency'])
stake_amount = round_coin_value(
start_balance = fmt_coin(strat_results['starting_balance'], strat_results['stake_currency'])
stake_amount = fmt_coin(
strat_results['stake_amount'], strat_results['stake_currency']
) if strat_results['stake_amount'] != UNLIMITED_STAKE_AMOUNT else 'unlimited'
@@ -322,24 +319,20 @@ def show_backtest_result(strategy: str, results: Dict[str, Any], stake_currency:
print(' LEFT OPEN TRADES REPORT '.center(len(table.splitlines()[0]), '='))
print(table)
if (results.get('results_per_enter_tag') is not None
or results.get('results_per_buy_tag') is not None):
# results_per_buy_tag is deprecated and should be removed 2 versions after short golive.
table = text_table_tags(
"enter_tag",
results.get('results_per_enter_tag', results.get('results_per_buy_tag')),
stake_currency=stake_currency)
if (results.get('results_per_enter_tag') is not None):
table = text_table_tags("enter_tag", results['results_per_enter_tag'], stake_currency)
if isinstance(table, str) and len(table) > 0:
print(' ENTER TAG STATS '.center(len(table.splitlines()[0]), '='))
print(table)
exit_reasons = results.get('exit_reason_summary', results.get('sell_reason_summary'))
table = text_table_exit_reason(exit_reason_stats=exit_reasons,
stake_currency=stake_currency)
if isinstance(table, str) and len(table) > 0:
print(' EXIT REASON STATS '.center(len(table.splitlines()[0]), '='))
print(table)
exit_reasons = results.get('exit_reason_summary')
if exit_reasons:
table = text_table_exit_reason(exit_reason_stats=exit_reasons,
stake_currency=stake_currency)
if isinstance(table, str) and len(table) > 0:
print(' EXIT REASON STATS '.center(len(table.splitlines()[0]), '='))
print(table)
for period in backtest_breakdown:
if period in results.get('periodic_breakdown', {}):
freqtrade/optimize/optimize_reports/optimize_reports.py
+6 -2
View File
@@ -10,8 +10,8 @@ from freqtrade.constants import BACKTEST_BREAKDOWNS, DATETIME_PRINT_FORMAT, IntO
from freqtrade.data.metrics import (calculate_cagr, calculate_calmar, calculate_csum,
calculate_expectancy, calculate_market_change,
calculate_max_drawdown, calculate_sharpe, calculate_sortino)
from freqtrade.misc import decimals_per_coin, round_coin_value
from freqtrade.types import BacktestResultType
from freqtrade.util import decimals_per_coin, fmt_coin
logger = logging.getLogger(__name__)
@@ -203,7 +203,7 @@ def generate_strategy_comparison(bt_stats: Dict) -> List[Dict]:
# Update "key" to strategy (results_per_pair has it as "Total").
tabular_data[-1]['key'] = strategy
tabular_data[-1]['max_drawdown_account'] = result['max_drawdown_account']
tabular_data[-1]['max_drawdown_abs'] = round_coin_value(
tabular_data[-1]['max_drawdown_abs'] = fmt_coin(
result['max_drawdown_abs'], result['stake_currency'], False)
return tabular_data
@@ -561,6 +561,10 @@ def generate_backtest_stats(btdata: Dict[str, DataFrame],
metadata[strategy] = {
'run_id': content['run_id'],
'backtest_start_time': content['backtest_start_time'],
'timeframe': content['config']['timeframe'],
'timeframe_detail': content['config'].get('timeframe_detail', None),
'backtest_start_ts': int(min_date.timestamp()),
'backtest_end_ts': int(max_date.timestamp()),
}
result['strategy'][strategy] = strat_stats
freqtrade/persistence/trade_model.py
+19 -17
View File
@@ -146,7 +146,7 @@ class Order(ModelBase):
return (f"Order(id={self.id}, trade={self.ft_trade_id}, order_id={self.order_id}, "
f"side={self.side}, filled={self.safe_filled}, price={self.safe_price}, "
f"status={self.status}, date={self.order_date:{DATETIME_PRINT_FORMAT}})")
f"status={self.status}, date={self.order_date_utc:{DATETIME_PRINT_FORMAT}})")
def update_from_ccxt_object(self, order):
"""
@@ -156,20 +156,20 @@ class Order(ModelBase):
if self.order_id != str(order['id']):
raise DependencyException("Order-id's don't match")
self.status = order.get('status', self.status)
self.symbol = order.get('symbol', self.symbol)
self.order_type = order.get('type', self.order_type)
self.side = order.get('side', self.side)
self.price = order.get('price', self.price)
self.amount = order.get('amount', self.amount)
self.filled = order.get('filled', self.filled)
self.average = order.get('average', self.average)
self.remaining = order.get('remaining', self.remaining)
self.cost = order.get('cost', self.cost)
self.stop_price = order.get('stopPrice', self.stop_price)
if 'timestamp' in order and order['timestamp'] is not None:
self.order_date = datetime.fromtimestamp(order['timestamp'] / 1000, tz=timezone.utc)
self.status = safe_value_fallback(order, 'status', default_value=self.status)
self.symbol = safe_value_fallback(order, 'symbol', default_value=self.symbol)
self.order_type = safe_value_fallback(order, 'type', default_value=self.order_type)
self.side = safe_value_fallback(order, 'side', default_value=self.side)
self.price = safe_value_fallback(order, 'price', default_value=self.price)
self.amount = safe_value_fallback(order, 'amount', default_value=self.amount)
self.filled = safe_value_fallback(order, 'filled', default_value=self.filled)
self.average = safe_value_fallback(order, 'average', default_value=self.average)
self.remaining = safe_value_fallback(order, 'remaining', default_value=self.remaining)
self.cost = safe_value_fallback(order, 'cost', default_value=self.cost)
self.stop_price = safe_value_fallback(order, 'stopPrice', default_value=self.stop_price)
order_date = safe_value_fallback(order, 'timestamp')
if order_date:
self.order_date = datetime.fromtimestamp(order_date / 1000, tz=timezone.utc)
self.ft_is_open = True
if self.status in NON_OPEN_EXCHANGE_STATES:
@@ -542,7 +542,9 @@ class LocalTrade:
f"{self.trading_mode.value} trading requires param interest_rate on trades")
def __repr__(self):
open_since = self.open_date.strftime(DATETIME_PRINT_FORMAT) if self.is_open else 'closed'
open_since = (
self.open_date_utc.strftime(DATETIME_PRINT_FORMAT) if self.is_open else 'closed'
)
return (
f'Trade(id={self.id}, pair={self.pair}, amount={self.amount:.8f}, '
@@ -1603,7 +1605,7 @@ class Trade(ModelBase, LocalTrade):
:return: unsorted query object
"""
query = Trade.get_trades_query(trade_filter, include_orders)
# this sholud remain split. if use_db is False, session is not available and the above will
# this should remain split. if use_db is False, session is not available and the above will
# raise an exception.
return Trade.session.scalars(query)
freqtrade/rpc/api_server/api_schemas.py
+5
View File
@@ -471,6 +471,7 @@ class FreqAIModelListResponse(BaseModel):
class StrategyResponse(BaseModel):
strategy: str
code: str
timeframe: Optional[str]
class AvailablePairs(BaseModel):
@@ -537,6 +538,10 @@ class BacktestHistoryEntry(BaseModel):
run_id: str
backtest_start_time: int
notes: Optional[str] = ''
backtest_start_ts: Optional[int] = None
backtest_end_ts: Optional[int] = None
timeframe: Optional[str] = None
timeframe_detail: Optional[str] = None
class BacktestMetadataUpdate(BaseModel):
freqtrade/rpc/api_server/api_v1.py
+1
View File
@@ -350,6 +350,7 @@ def get_strategy(strategy: str, config=Depends(get_config)):
return {
'strategy': strategy_obj.get_strategy_name(),
'code': strategy_obj.__source__,
'timeframe': getattr(strategy_obj, 'timeframe', None),
}
freqtrade/rpc/discord.py
+2
View File
@@ -15,6 +15,7 @@ class Discord(Webhook):
self.rpc = rpc
self.strategy = config.get('strategy', '')
self.timeframe = config.get('timeframe', '')
self.bot_name = config.get('bot_name', '')
self._url = config['discord']['webhook_url']
self._format = 'json'
@@ -36,6 +37,7 @@ class Discord(Webhook):
msg['strategy'] = self.strategy
msg['timeframe'] = self.timeframe
msg['bot_name'] = self.bot_name
color = 0x0000FF
if msg['type'] in (RPCMessageType.EXIT, RPCMessageType.EXIT_FILL):
profit_ratio = msg.get('profit_ratio')
freqtrade/rpc/fiat_convert.py
+1
View File
@@ -28,6 +28,7 @@ coingecko_mapping = {
'busd': 'binance-usd',
'tusd': 'true-usd',
'usdc': 'usd-coin',
'btc': 'bitcoin'
}
freqtrade/rpc/rpc.py
+6 -5
View File
@@ -25,13 +25,13 @@ from freqtrade.exceptions import ExchangeError, PricingError
from freqtrade.exchange import timeframe_to_minutes, timeframe_to_msecs
from freqtrade.exchange.types import Tickers
from freqtrade.loggers import bufferHandler
from freqtrade.misc import decimals_per_coin
from freqtrade.persistence import KeyStoreKeys, KeyValueStore, PairLocks, Trade
from freqtrade.persistence.models import PairLock
from freqtrade.plugins.pairlist.pairlist_helpers import expand_pairlist
from freqtrade.rpc.fiat_convert import CryptoToFiatConverter
from freqtrade.rpc.rpc_types import RPCSendMsg
from freqtrade.util import dt_humanize, dt_now, dt_ts_def, format_date, shorten_date
from freqtrade.util import (decimals_per_coin, dt_humanize, dt_now, dt_ts_def, format_date,
shorten_date)
from freqtrade.wallets import PositionWallet, Wallet
@@ -121,8 +121,8 @@ class RPC:
'stake_currency_decimals': decimals_per_coin(config['stake_currency']),
'stake_amount': str(config['stake_amount']),
'available_capital': config.get('available_capital'),
'max_open_trades': (config['max_open_trades']
if config['max_open_trades'] != float('inf') else -1),
'max_open_trades': (config.get('max_open_trades', 0)
if config.get('max_open_trades', 0) != float('inf') else -1),
'minimal_roi': config['minimal_roi'].copy() if 'minimal_roi' in config else {},
'stoploss': config.get('stoploss'),
'stoploss_on_exchange': config.get('order_types',
@@ -914,7 +914,8 @@ class RPC:
if not stake_amount:
# gen stake amount
stake_amount = self._freqtrade.wallets.get_trade_stake_amount(pair)
stake_amount = self._freqtrade.wallets.get_trade_stake_amount(
pair, self._config['max_open_trades'])
# execute buy
if not order_type:
freqtrade/rpc/rpc_types.py
+19 -12
View File
@@ -5,6 +5,9 @@ from freqtrade.constants import PairWithTimeframe
from freqtrade.enums import RPCMessageType
ProfitLossStr = Literal["profit", "loss"]
class RPCSendMsgBase(TypedDict):
pass
# ty1pe: Literal[RPCMessageType]
@@ -41,13 +44,14 @@ class RPCWhitelistMsg(RPCSendMsgBase):
data: List[str]
class __RPCBuyMsgBase(RPCSendMsgBase):
class __RPCEntryExitMsgBase(RPCSendMsgBase):
trade_id: int
buy_tag: Optional[str]
enter_tag: Optional[str]
exchange: str
pair: str
base_currency: str
quote_currency: str
leverage: Optional[float]
direction: str
limit: float
@@ -62,36 +66,36 @@ class __RPCBuyMsgBase(RPCSendMsgBase):
sub_trade: bool
class RPCBuyMsg(__RPCBuyMsgBase):
class RPCEntryMsg(__RPCEntryExitMsgBase):
type: Literal[RPCMessageType.ENTRY, RPCMessageType.ENTRY_FILL]
class RPCCancelMsg(__RPCBuyMsgBase):
class RPCCancelMsg(__RPCEntryExitMsgBase):
type: Literal[RPCMessageType.ENTRY_CANCEL]
reason: str
class RPCSellMsg(__RPCBuyMsgBase):
class RPCExitMsg(__RPCEntryExitMsgBase):
type: Literal[RPCMessageType.EXIT, RPCMessageType.EXIT_FILL]
cumulative_profit: float
gain: str # Literal["profit", "loss"]
gain: ProfitLossStr
close_rate: float
profit_amount: float
profit_ratio: float
sell_reason: Optional[str]
exit_reason: Optional[str]
close_date: datetime
# current_rate: Optional[float]
order_rate: Optional[float]
final_profit_ratio: Optional[float]
is_final_exit: bool
class RPCSellCancelMsg(__RPCBuyMsgBase):
class RPCExitCancelMsg(__RPCEntryExitMsgBase):
type: Literal[RPCMessageType.EXIT_CANCEL]
reason: str
gain: str # Literal["profit", "loss"]
gain: ProfitLossStr
profit_amount: float
profit_ratio: float
sell_reason: Optional[str]
exit_reason: Optional[str]
close_date: datetime
@@ -114,15 +118,18 @@ class RPCNewCandleMsg(RPCSendMsgBase):
data: PairWithTimeframe
RPCOrderMsg = Union[RPCEntryMsg, RPCExitMsg, RPCExitCancelMsg, RPCCancelMsg]
RPCSendMsg = Union[
RPCStatusMsg,
RPCStrategyMsg,
RPCProtectionMsg,
RPCWhitelistMsg,
RPCBuyMsg,
RPCEntryMsg,
RPCCancelMsg,
RPCSellMsg,
RPCSellCancelMsg,
RPCExitMsg,
RPCExitCancelMsg,
RPCAnalyzedDFMsg,
RPCNewCandleMsg
]
freqtrade/rpc/telegram.py
+159 -132
View File
@@ -10,12 +10,12 @@ import re
from copy import deepcopy
from dataclasses import dataclass
from datetime import date, datetime, timedelta
from functools import partial
from functools import partial, wraps
from html import escape
from itertools import chain
from math import isnan
from threading import Thread
from typing import Any, Callable, Coroutine, Dict, List, Optional, Union
from typing import Any, Callable, Coroutine, Dict, List, Literal, Optional, Union
from tabulate import tabulate
from telegram import (CallbackQuery, InlineKeyboardButton, InlineKeyboardMarkup, KeyboardButton,
@@ -29,11 +29,11 @@ from freqtrade.__init__ import __version__
from freqtrade.constants import DUST_PER_COIN, Config
from freqtrade.enums import MarketDirection, RPCMessageType, SignalDirection, TradingMode
from freqtrade.exceptions import OperationalException
from freqtrade.misc import chunks, plural, round_coin_value
from freqtrade.misc import chunks, plural
from freqtrade.persistence import Trade
from freqtrade.rpc import RPC, RPCException, RPCHandler
from freqtrade.rpc.rpc_types import RPCSendMsg
from freqtrade.util import dt_humanize
from freqtrade.rpc.rpc_types import RPCEntryMsg, RPCExitMsg, RPCOrderMsg, RPCSendMsg
from freqtrade.util import dt_humanize, fmt_coin, round_value
MAX_MESSAGE_LENGTH = MessageLimit.MAX_TEXT_LENGTH
@@ -44,6 +44,23 @@ logger = logging.getLogger(__name__)
logger.debug('Included module rpc.telegram ...')
def safe_async_db(func: Callable[..., Any]):
"""
Decorator to safely handle sessions when switching async context
:param func: function to decorate
:return: decorated function
"""
@wraps(func)
def wrapper(*args, **kwargs):
""" Decorator logic """
try:
return func(*args, **kwargs)
finally:
Trade.session.remove()
return wrapper
@dataclass
class TimeunitMappings:
header: str
@@ -61,6 +78,7 @@ def authorized_only(command_handler: Callable[..., Coroutine[Any, Any, None]]):
:return: decorated function
"""
@wraps(command_handler)
async def wrapper(self, *args, **kwargs):
""" Decorator logic """
update = kwargs.get('update') or args[0]
@@ -286,7 +304,7 @@ class Telegram(RPCHandler):
asyncio.run_coroutine_threadsafe(self._cleanup_telegram(), self._loop)
self._thread.join()
def _exchange_from_msg(self, msg: Dict[str, Any]) -> str:
def _exchange_from_msg(self, msg: RPCOrderMsg) -> str:
"""
Extracts the exchange name from the given message.
:param msg: The message to extract the exchange name from.
@@ -310,164 +328,172 @@ class Telegram(RPCHandler):
return ''
def _format_entry_msg(self, msg: Dict[str, Any]) -> str:
if self._rpc._fiat_converter:
msg['stake_amount_fiat'] = self._rpc._fiat_converter.convert_amount(
msg['stake_amount'], msg['stake_currency'], msg['fiat_currency'])
else:
msg['stake_amount_fiat'] = 0
def _format_entry_msg(self, msg: RPCEntryMsg) -> str:
is_fill = msg['type'] in [RPCMessageType.ENTRY_FILL]
emoji = '\N{CHECK MARK}' if is_fill else '\N{LARGE BLUE CIRCLE}'
entry_side = ({'enter': 'Long', 'entered': 'Longed'} if msg['direction'] == 'Long'
else {'enter': 'Short', 'entered': 'Shorted'})
terminology = {
'1_enter': 'New Trade',
'1_entered': 'New Trade filled',
'x_enter': 'Increasing position',
'x_entered': 'Position increase filled',
}
key = f"{'x' if msg['sub_trade'] else '1'}_{'entered' if is_fill else 'enter'}"
wording = terminology[key]
message = (
f"{emoji} *{self._exchange_from_msg(msg)}:*"
f" {entry_side['entered'] if is_fill else entry_side['enter']} {msg['pair']}"
f" (#{msg['trade_id']})\n"
f" {wording} (#{msg['trade_id']})\n"
f"*Pair:* `{msg['pair']}`\n"
)
message += self._add_analyzed_candle(msg['pair'])
message += f"*Enter Tag:* `{msg['enter_tag']}`\n" if msg.get('enter_tag') else ""
message += f"*Amount:* `{msg['amount']:.8f}`\n"
message += f"*Amount:* `{round_value(msg['amount'], 8)}`\n"
message += f"*Direction:* `{msg['direction']}"
if msg.get('leverage') and msg.get('leverage', 1.0) != 1.0:
message += f"*Leverage:* `{msg['leverage']}`\n"
message += f" ({msg['leverage']:.1g}x)"
message += "`\n"
message += f"*Open Rate:* `{fmt_coin(msg['open_rate'], msg['quote_currency'])}`\n"
if msg['type'] == RPCMessageType.ENTRY and msg['current_rate']:
message += f"*Current Rate:* `{fmt_coin(msg['current_rate'], msg['quote_currency'])}`\n"
if msg['type'] in [RPCMessageType.ENTRY_FILL]:
message += f"*Open Rate:* `{msg['open_rate']:.8f}`\n"
elif msg['type'] in [RPCMessageType.ENTRY]:
message += f"*Open Rate:* `{msg['open_rate']:.8f}`\n"\
f"*Current Rate:* `{msg['current_rate']:.8f}`\n"
profit_fiat_extra = self.__format_profit_fiat(msg, 'stake_amount') # type: ignore
total = fmt_coin(msg['stake_amount'], msg['quote_currency'])
message += f"*Total:* `({round_coin_value(msg['stake_amount'], msg['stake_currency'])}"
message += f"*{'New ' if msg['sub_trade'] else ''}Total:* `{total}{profit_fiat_extra}`"
if msg.get('fiat_currency'):
message += f", {round_coin_value(msg['stake_amount_fiat'], msg['fiat_currency'])}"
message += ")`"
return message
def _format_exit_msg(self, msg: Dict[str, Any]) -> str:
msg['amount'] = round(msg['amount'], 8)
msg['profit_percent'] = round(msg['profit_ratio'] * 100, 2)
msg['duration'] = msg['close_date'].replace(
def _format_exit_msg(self, msg: RPCExitMsg) -> str:
duration = msg['close_date'].replace(
microsecond=0) - msg['open_date'].replace(microsecond=0)
msg['duration_min'] = msg['duration'].total_seconds() / 60
duration_min = duration.total_seconds() / 60
msg['enter_tag'] = msg['enter_tag'] if "enter_tag" in msg.keys() else None
msg['emoji'] = self._get_sell_emoji(msg)
msg['leverage_text'] = (f"*Leverage:* `{msg['leverage']:.1f}`\n"
if msg.get('leverage') and msg.get('leverage', 1.0) != 1.0
else "")
leverage_text = (f" ({msg['leverage']:.1g}x)"
if msg.get('leverage') and msg.get('leverage', 1.0) != 1.0
else "")
# Check if all sell properties are available.
# This might not be the case if the message origin is triggered by /forceexit
if (all(prop in msg for prop in ['gain', 'fiat_currency', 'stake_currency'])
and self._rpc._fiat_converter):
msg['profit_fiat'] = self._rpc._fiat_converter.convert_amount(
msg['profit_amount'], msg['stake_currency'], msg['fiat_currency'])
msg['profit_extra'] = f" / {msg['profit_fiat']:.3f} {msg['fiat_currency']}"
else:
msg['profit_extra'] = ''
msg['profit_extra'] = (
f" ({msg['gain']}: {msg['profit_amount']:.8f} {msg['stake_currency']}"
f"{msg['profit_extra']})")
profit_fiat_extra = self.__format_profit_fiat(msg, 'profit_amount')
profit_extra = (
f" ({msg['gain']}: {fmt_coin(msg['profit_amount'], msg['quote_currency'])}"
f"{profit_fiat_extra})")
is_fill = msg['type'] == RPCMessageType.EXIT_FILL
is_sub_trade = msg.get('sub_trade')
is_sub_profit = msg['profit_amount'] != msg.get('cumulative_profit')
profit_prefix = ('Sub ' if is_sub_profit else 'Cumulative ') if is_sub_trade else ''
is_final_exit = msg.get('is_final_exit', False) and is_sub_profit
profit_prefix = 'Sub ' if is_sub_trade else ''
cp_extra = ''
exit_wording = 'Exited' if is_fill else 'Exiting'
if is_sub_profit and is_sub_trade:
if self._rpc._fiat_converter:
cp_fiat = self._rpc._fiat_converter.convert_amount(
msg['cumulative_profit'], msg['stake_currency'], msg['fiat_currency'])
cp_extra = f" / {cp_fiat:.3f} {msg['fiat_currency']}"
exit_wording = f"Partially {exit_wording.lower()}"
cp_extra = (
f"*Cumulative Profit:* (`{msg['cumulative_profit']:.8f} "
f"{msg['stake_currency']}{cp_extra}`)\n"
)
if is_sub_trade or is_final_exit:
cp_fiat = self.__format_profit_fiat(msg, 'cumulative_profit')
if is_final_exit:
profit_prefix = 'Sub '
cp_extra = (
f"*Final Profit:* `{msg['final_profit_ratio']:.2%} "
f"({msg['cumulative_profit']:.8f} {msg['quote_currency']}{cp_fiat})`\n"
)
else:
exit_wording = f"Partially {exit_wording.lower()}"
if msg['cumulative_profit']:
cp_extra = (
f"*Cumulative Profit:* `"
f"{fmt_coin(msg['cumulative_profit'], msg['stake_currency'])}{cp_fiat}`\n"
)
enter_tag = f"*Enter Tag:* `{msg['enter_tag']}`\n" if msg.get('enter_tag') else ""
message = (
f"{msg['emoji']} *{self._exchange_from_msg(msg)}:* "
f"{self._get_exit_emoji(msg)} *{self._exchange_from_msg(msg)}:* "
f"{exit_wording} {msg['pair']} (#{msg['trade_id']})\n"
f"{self._add_analyzed_candle(msg['pair'])}"
f"*{f'{profit_prefix}Profit' if is_fill else f'Unrealized {profit_prefix}Profit'}:* "
f"`{msg['profit_ratio']:.2%}{msg['profit_extra']}`\n"
f"`{msg['profit_ratio']:.2%}{profit_extra}`\n"
f"{cp_extra}"
f"*Enter Tag:* `{msg['enter_tag']}`\n"
f"{enter_tag}"
f"*Exit Reason:* `{msg['exit_reason']}`\n"
f"*Direction:* `{msg['direction']}`\n"
f"{msg['leverage_text']}"
f"*Amount:* `{msg['amount']:.8f}`\n"
f"*Open Rate:* `{msg['open_rate']:.8f}`\n"
f"*Direction:* `{msg['direction']}"
f"{leverage_text}`\n"
f"*Amount:* `{round_value(msg['amount'], 8)}`\n"
f"*Open Rate:* `{fmt_coin(msg['open_rate'], msg['quote_currency'])}`\n"
)
if msg['type'] == RPCMessageType.EXIT:
message += f"*Current Rate:* `{msg['current_rate']:.8f}`\n"
if msg['type'] == RPCMessageType.EXIT and msg['current_rate']:
message += f"*Current Rate:* `{fmt_coin(msg['current_rate'], msg['quote_currency'])}`\n"
if msg['order_rate']:
message += f"*Exit Rate:* `{msg['order_rate']:.8f}`"
message += f"*Exit Rate:* `{fmt_coin(msg['order_rate'], msg['quote_currency'])}`"
elif msg['type'] == RPCMessageType.EXIT_FILL:
message += f"*Exit Rate:* `{msg['close_rate']:.8f}`"
message += f"*Exit Rate:* `{fmt_coin(msg['close_rate'], msg['quote_currency'])}`"
if is_sub_trade:
if self._rpc._fiat_converter:
msg['stake_amount_fiat'] = self._rpc._fiat_converter.convert_amount(
msg['stake_amount'], msg['stake_currency'], msg['fiat_currency'])
else:
msg['stake_amount_fiat'] = 0
rem = round_coin_value(msg['stake_amount'], msg['stake_currency'])
message += f"\n*Remaining:* `({rem}"
stake_amount_fiat = self.__format_profit_fiat(msg, 'stake_amount')
if msg.get('fiat_currency', None):
message += f", {round_coin_value(msg['stake_amount_fiat'], msg['fiat_currency'])}"
message += ")`"
rem = fmt_coin(msg['stake_amount'], msg['quote_currency'])
message += f"\n*Remaining:* `{rem}{stake_amount_fiat}`"
else:
message += f"\n*Duration:* `{msg['duration']} ({msg['duration_min']:.1f} min)`"
message += f"\n*Duration:* `{duration} ({duration_min:.1f} min)`"
return message
def compose_message(self, msg: Dict[str, Any], msg_type: RPCMessageType) -> Optional[str]:
if msg_type in [RPCMessageType.ENTRY, RPCMessageType.ENTRY_FILL]:
def __format_profit_fiat(
self,
msg: RPCExitMsg,
key: Literal['stake_amount', 'profit_amount', 'cumulative_profit']
) -> str:
"""
Format Fiat currency to append to regular profit output
"""
profit_fiat_extra = ''
if self._rpc._fiat_converter and (fiat_currency := msg.get('fiat_currency')):
profit_fiat = self._rpc._fiat_converter.convert_amount(
msg[key], msg['stake_currency'], fiat_currency)
profit_fiat_extra = f" / {profit_fiat:.3f} {fiat_currency}"
return profit_fiat_extra
def compose_message(self, msg: RPCSendMsg) -> Optional[str]:
if msg['type'] == RPCMessageType.ENTRY or msg['type'] == RPCMessageType.ENTRY_FILL:
message = self._format_entry_msg(msg)
elif msg_type in [RPCMessageType.EXIT, RPCMessageType.EXIT_FILL]:
elif msg['type'] == RPCMessageType.EXIT or msg['type'] == RPCMessageType.EXIT_FILL:
message = self._format_exit_msg(msg)
elif msg_type in (RPCMessageType.ENTRY_CANCEL, RPCMessageType.EXIT_CANCEL):
msg['message_side'] = 'enter' if msg_type in [RPCMessageType.ENTRY_CANCEL] else 'exit'
elif (
msg['type'] == RPCMessageType.ENTRY_CANCEL
or msg['type'] == RPCMessageType.EXIT_CANCEL
):
message_side = 'enter' if msg['type'] == RPCMessageType.ENTRY_CANCEL else 'exit'
message = (f"\N{WARNING SIGN} *{self._exchange_from_msg(msg)}:* "
f"Cancelling {'partial ' if msg.get('sub_trade') else ''}"
f"{msg['message_side']} Order for {msg['pair']} "
f"{message_side} Order for {msg['pair']} "
f"(#{msg['trade_id']}). Reason: {msg['reason']}.")
elif msg_type == RPCMessageType.PROTECTION_TRIGGER:
elif msg['type'] == RPCMessageType.PROTECTION_TRIGGER:
message = (
f"*Protection* triggered due to {msg['reason']}. "
f"`{msg['pair']}` will be locked until `{msg['lock_end_time']}`."
)
elif msg_type == RPCMessageType.PROTECTION_TRIGGER_GLOBAL:
elif msg['type'] == RPCMessageType.PROTECTION_TRIGGER_GLOBAL:
message = (
f"*Protection* triggered due to {msg['reason']}. "
f"*All pairs* will be locked until `{msg['lock_end_time']}`."
)
elif msg_type == RPCMessageType.STATUS:
elif msg['type'] == RPCMessageType.STATUS:
message = f"*Status:* `{msg['status']}`"
elif msg_type == RPCMessageType.WARNING:
elif msg['type'] == RPCMessageType.WARNING:
message = f"\N{WARNING SIGN} *Warning:* `{msg['status']}`"
elif msg_type == RPCMessageType.EXCEPTION:
elif msg['type'] == RPCMessageType.EXCEPTION:
# Errors will contain exceptions, which are wrapped in tripple ticks.
message = f"\N{WARNING SIGN} *ERROR:* \n {msg['status']}"
elif msg_type == RPCMessageType.STARTUP:
elif msg['type'] == RPCMessageType.STARTUP:
message = f"{msg['status']}"
elif msg_type == RPCMessageType.STRATEGY_MSG:
elif msg['type'] == RPCMessageType.STRATEGY_MSG:
message = f"{msg['msg']}"
else:
logger.debug("Unknown message type: %s", msg_type)
logger.debug("Unknown message type: %s", msg['type'])
return None
return message
@@ -495,20 +521,20 @@ class Telegram(RPCHandler):
# Notification disabled
return
message = self.compose_message(deepcopy(msg), msg_type) # type: ignore
message = self.compose_message(deepcopy(msg))
if message:
asyncio.run_coroutine_threadsafe(
self._send_msg(message, disable_notification=(noti == 'silent')),
self._loop)
def _get_sell_emoji(self, msg):
def _get_exit_emoji(self, msg):
"""
Get emoji for sell-side
Get emoji for exit-messages
"""
if float(msg['profit_percent']) >= 5.0:
if float(msg['profit_ratio']) >= 0.05:
return "\N{ROCKET}"
elif float(msg['profit_percent']) >= 0.0:
elif float(msg['profit_ratio']) >= 0.0:
return "\N{EIGHT SPOKED ASTERISK}"
elif msg['exit_reason'] == "stop_loss":
return "\N{WARNING SIGN}"
@@ -537,7 +563,7 @@ class Telegram(RPCHandler):
if order_nr == 1:
lines.append(
f"*Amount:* {cur_entry_amount:.8g} "
f"({round_coin_value(order['cost'], quote_currency)})"
f"({fmt_coin(order['cost'], quote_currency)})"
)
lines.append(f"*Average Price:* {cur_entry_average:.8g}")
else:
@@ -547,7 +573,7 @@ class Telegram(RPCHandler):
lines.append("({})".format(dt_humanize(order["order_filled_date"],
granularity=["day", "hour", "minute"])))
lines.append(f"*Amount:* {cur_entry_amount:.8g} "
f"({round_coin_value(order['cost'], quote_currency)})")
f"({fmt_coin(order['cost'], quote_currency)})")
lines.append(f"*Average {wording} Price:* {cur_entry_average:.8g} "
f"({price_to_1st_entry:.2%} from 1st entry rate)")
lines.append(f"*Order Filled:* {order['order_filled_date']}")
@@ -633,12 +659,12 @@ class Telegram(RPCHandler):
r['num_exits'] = len([o for o in r['orders'] if not o['ft_is_entry']
and not o['ft_order_side'] == 'stoploss'])
r['exit_reason'] = r.get('exit_reason', "")
r['stake_amount_r'] = round_coin_value(r['stake_amount'], r['quote_currency'])
r['max_stake_amount_r'] = round_coin_value(
r['stake_amount_r'] = fmt_coin(r['stake_amount'], r['quote_currency'])
r['max_stake_amount_r'] = fmt_coin(
r['max_stake_amount'] or r['stake_amount'], r['quote_currency'])
r['profit_abs_r'] = round_coin_value(r['profit_abs'], r['quote_currency'])
r['realized_profit_r'] = round_coin_value(r['realized_profit'], r['quote_currency'])
r['total_profit_abs_r'] = round_coin_value(
r['profit_abs_r'] = fmt_coin(r['profit_abs'], r['quote_currency'])
r['realized_profit_r'] = fmt_coin(r['realized_profit'], r['quote_currency'])
r['total_profit_abs_r'] = fmt_coin(
r['total_profit_abs'], r['quote_currency'])
lines = [
"*Trade ID:* `{trade_id}`" +
@@ -781,7 +807,7 @@ class Telegram(RPCHandler):
)
stats_tab = tabulate(
[[f"{period['date']:{val.dateformat}} ({period['trade_count']})",
f"{round_coin_value(period['abs_profit'], stats['stake_currency'])}",
f"{fmt_coin(period['abs_profit'], stats['stake_currency'])}",
f"{period['fiat_value']:.2f} {stats['fiat_display_currency']}",
f"{period['rel_profit']:.2%}",
] for period in stats['data']],
@@ -883,19 +909,19 @@ class Telegram(RPCHandler):
# Message to display
if stats['closed_trade_count'] > 0:
markdown_msg = ("*ROI:* Closed trades\n"
f"∙ `{round_coin_value(profit_closed_coin, stake_cur)} "
f"∙ `{fmt_coin(profit_closed_coin, stake_cur)} "
f"({profit_closed_ratio_mean:.2%}) "
f"({profit_closed_percent} \N{GREEK CAPITAL LETTER SIGMA}%)`\n"
f"∙ `{round_coin_value(profit_closed_fiat, fiat_disp_cur)}`\n")
f"∙ `{fmt_coin(profit_closed_fiat, fiat_disp_cur)}`\n")
else:
markdown_msg = "`No closed trade` \n"
markdown_msg += (
f"*ROI:* All trades\n"
f"∙ `{round_coin_value(profit_all_coin, stake_cur)} "
f"∙ `{fmt_coin(profit_all_coin, stake_cur)} "
f"({profit_all_ratio_mean:.2%}) "
f"({profit_all_percent} \N{GREEK CAPITAL LETTER SIGMA}%)`\n"
f"∙ `{round_coin_value(profit_all_fiat, fiat_disp_cur)}`\n"
f"∙ `{fmt_coin(profit_all_fiat, fiat_disp_cur)}`\n"
f"*Total Trade Count:* `{trade_count}`\n"
f"*Bot started:* `{stats['bot_start_date']}`\n"
f"*{'First Trade opened' if not timescale else 'Showing Profit since'}:* "
@@ -909,14 +935,14 @@ class Telegram(RPCHandler):
markdown_msg += (
f"\n*Avg. Duration:* `{avg_duration}`\n"
f"*Best Performing:* `{best_pair}: {best_pair_profit_ratio:.2%}`\n"
f"*Trading volume:* `{round_coin_value(stats['trading_volume'], stake_cur)}`\n"
f"*Trading volume:* `{fmt_coin(stats['trading_volume'], stake_cur)}`\n"
f"*Profit factor:* `{stats['profit_factor']:.2f}`\n"
f"*Max Drawdown:* `{stats['max_drawdown']:.2%} "
f"({round_coin_value(stats['max_drawdown_abs'], stake_cur)})`\n"
f"({fmt_coin(stats['max_drawdown_abs'], stake_cur)})`\n"
f" from `{stats['max_drawdown_start']} "
f"({round_coin_value(stats['drawdown_high'], stake_cur)})`\n"
f"({fmt_coin(stats['drawdown_high'], stake_cur)})`\n"
f" to `{stats['max_drawdown_end']} "
f"({round_coin_value(stats['drawdown_low'], stake_cur)})`\n"
f"({fmt_coin(stats['drawdown_low'], stake_cur)})`\n"
)
await self._send_msg(markdown_msg, reload_able=True, callback_path="update_profit",
query=update.callback_query)
@@ -984,9 +1010,9 @@ class Telegram(RPCHandler):
output = ''
if self._config['dry_run']:
output += "*Warning:* Simulated balances in Dry Mode.\n"
starting_cap = round_coin_value(result['starting_capital'], self._config['stake_currency'])
starting_cap = fmt_coin(result['starting_capital'], self._config['stake_currency'])
output += f"Starting capital: `{starting_cap}`"
starting_cap_fiat = round_coin_value(
starting_cap_fiat = fmt_coin(
result['starting_capital_fiat'], self._config['fiat_display_currency']
) if result['starting_capital_fiat'] > 0 else ''
output += (f" `, {starting_cap_fiat}`.\n"
@@ -1006,9 +1032,9 @@ class Telegram(RPCHandler):
f"\t`{curr['side']}: {curr['position']:.8f}`\n"
f"\t`Leverage: {curr['leverage']:.1f}`\n"
f"\t`Est. {curr['stake']}: "
f"{round_coin_value(curr['est_stake'], curr['stake'], False)}`\n")
f"{fmt_coin(curr['est_stake'], curr['stake'], False)}`\n")
else:
est_stake = round_coin_value(
est_stake = fmt_coin(
curr['est_stake' if full_result else 'est_stake_bot'], curr['stake'], False)
curr_output = (
@@ -1036,13 +1062,13 @@ class Telegram(RPCHandler):
f"{plural(total_dust_currencies, 'Currency', 'Currencies')} "
f"(< {balance_dust_level} {result['stake']}):*\n"
f"\t`Est. {result['stake']}: "
f"{round_coin_value(total_dust_balance, result['stake'], False)}`\n")
f"{fmt_coin(total_dust_balance, result['stake'], False)}`\n")
tc = result['trade_count'] > 0
stake_improve = f" `({result['starting_capital_ratio']:.2%})`" if tc else ''
fiat_val = f" `({result['starting_capital_fiat_ratio']:.2%})`" if tc else ''
value = round_coin_value(
value = fmt_coin(
result['value' if full_result else 'value_bot'], result['symbol'], False)
total_stake = round_coin_value(
total_stake = fmt_coin(
result['total' if full_result else 'total_bot'], result['stake'], False)
output += (
f"\n*Estimated Value{' (Bot managed assets only)' if not full_result else ''}*:\n"
@@ -1150,7 +1176,7 @@ class Telegram(RPCHandler):
try:
loop = asyncio.get_running_loop()
# Workaround to avoid nested loops
await loop.run_in_executor(None, self._rpc._rpc_force_exit, trade_id)
await loop.run_in_executor(None, safe_async_db(self._rpc._rpc_force_exit), trade_id)
except RPCException as e:
await self._send_msg(str(e))
@@ -1176,6 +1202,7 @@ class Telegram(RPCHandler):
async def _force_enter_action(self, pair, price: Optional[float], order_side: SignalDirection):
if pair != 'cancel':
try:
@safe_async_db
def _force_enter():
self._rpc._rpc_force_entry(pair, price, order_side=order_side)
loop = asyncio.get_running_loop()
@@ -1320,7 +1347,7 @@ class Telegram(RPCHandler):
for i, trade in enumerate(trades):
stat_line = (
f"{i+1}.\t <code>{trade['pair']}\t"
f"{round_coin_value(trade['profit_abs'], self._config['stake_currency'])} "
f"{fmt_coin(trade['profit_abs'], self._config['stake_currency'])} "
f"({trade['profit_ratio']:.2%}) "
f"({trade['count']})</code>\n")
@@ -1352,7 +1379,7 @@ class Telegram(RPCHandler):
for i, trade in enumerate(trades):
stat_line = (
f"{i+1}.\t <code>{trade['enter_tag']}\t"
f"{round_coin_value(trade['profit_abs'], self._config['stake_currency'])} "
f"{fmt_coin(trade['profit_abs'], self._config['stake_currency'])} "
f"({trade['profit_ratio']:.2%}) "
f"({trade['count']})</code>\n")
@@ -1384,7 +1411,7 @@ class Telegram(RPCHandler):
for i, trade in enumerate(trades):
stat_line = (
f"{i+1}.\t <code>{trade['exit_reason']}\t"
f"{round_coin_value(trade['profit_abs'], self._config['stake_currency'])} "
f"{fmt_coin(trade['profit_abs'], self._config['stake_currency'])} "
f"({trade['profit_ratio']:.2%}) "
f"({trade['count']})</code>\n")
@@ -1416,7 +1443,7 @@ class Telegram(RPCHandler):
for i, trade in enumerate(trades):
stat_line = (
f"{i+1}.\t <code>{trade['mix_tag']}\t"
f"{round_coin_value(trade['profit_abs'], self._config['stake_currency'])} "
f"{fmt_coin(trade['profit_abs'], self._config['stake_currency'])} "
f"({trade['profit_ratio']:.2%}) "
f"({trade['count']})</code>\n")
freqtrade/rpc/webhook.py
+1 -1
View File
@@ -84,7 +84,7 @@ class Webhook(RPCHandler):
valuedict = self._get_value_dict(msg)
if not valuedict:
logger.info("Message type '%s' not configured for webhooks", msg['type'])
logger.debug("Message type '%s' not configured for webhooks", msg['type'])
return
payload = {key: value.format(**msg) for (key, value) in valuedict.items()}
freqtrade/strategy/strategy_helper.py
+11 -8
View File
@@ -36,7 +36,7 @@ def merge_informative_pair(dataframe: pd.DataFrame, informative: pd.DataFrame,
:return: Merged dataframe
:raise: ValueError if the secondary timeframe is shorter than the dataframe timeframe
"""
informative = informative.copy()
minutes_inf = timeframe_to_minutes(timeframe_inf)
minutes = timeframe_to_minutes(timeframe)
if minutes == minutes_inf:
@@ -46,10 +46,16 @@ def merge_informative_pair(dataframe: pd.DataFrame, informative: pd.DataFrame,
# Subtract "small" timeframe so merging is not delayed by 1 small candle
# Detailed explanation in https://github.com/freqtrade/freqtrade/issues/4073
if not informative.empty:
informative['date_merge'] = (
informative[date_column] + pd.to_timedelta(minutes_inf, 'm') -
pd.to_timedelta(minutes, 'm')
)
if timeframe_inf == '1M':
informative['date_merge'] = (
(informative[date_column] + pd.offsets.MonthBegin(1))
- pd.to_timedelta(minutes, 'm')
)
else:
informative['date_merge'] = (
informative[date_column] + pd.to_timedelta(minutes_inf, 'm') -
pd.to_timedelta(minutes, 'm')
)
else:
informative['date_merge'] = informative[date_column]
else:
@@ -80,9 +86,6 @@ def merge_informative_pair(dataframe: pd.DataFrame, informative: pd.DataFrame,
right_on=date_merge, how='left')
dataframe = dataframe.drop(date_merge, axis=1)
# if ffill:
# dataframe = dataframe.ffill()
return dataframe
freqtrade/templates/FreqaiExampleHybridStrategy.py
+1 -1
View File
@@ -29,7 +29,7 @@ class FreqaiExampleHybridStrategy(IStrategy):
"enabled": true,
"purge_old_models": 2,
"train_period_days": 15,
"identifier": "uniqe-id",
"identifier": "unique-id",
"feature_parameters": {
"include_timeframes": [
"3m",
freqtrade/templates/FreqaiExampleStrategy.py
+5 -18
View File
@@ -6,7 +6,7 @@ import talib.abstract as ta
from pandas import DataFrame
from technical import qtpylib
from freqtrade.strategy import CategoricalParameter, IStrategy
from freqtrade.strategy import IStrategy
logger = logging.getLogger(__name__)
@@ -45,11 +45,6 @@ class FreqaiExampleStrategy(IStrategy):
startup_candle_count: int = 40
can_short = True
std_dev_multiplier_buy = CategoricalParameter(
[0.75, 1, 1.25, 1.5, 1.75], default=1.25, space="buy", optimize=True)
std_dev_multiplier_sell = CategoricalParameter(
[0.75, 1, 1.25, 1.5, 1.75], space="sell", default=1.25, optimize=True)
def feature_engineering_expand_all(self, dataframe: DataFrame, period: int,
metadata: Dict, **kwargs) -> DataFrame:
"""
@@ -239,21 +234,13 @@ class FreqaiExampleStrategy(IStrategy):
dataframe = self.freqai.start(dataframe, metadata, self)
for val in self.std_dev_multiplier_buy.range:
dataframe[f'target_roi_{val}'] = (
dataframe["&-s_close_mean"] + dataframe["&-s_close_std"] * val
)
for val in self.std_dev_multiplier_sell.range:
dataframe[f'sell_roi_{val}'] = (
dataframe["&-s_close_mean"] - dataframe["&-s_close_std"] * val
)
return dataframe
def populate_entry_trend(self, df: DataFrame, metadata: dict) -> DataFrame:
enter_long_conditions = [
df["do_predict"] == 1,
df["&-s_close"] > df[f"target_roi_{self.std_dev_multiplier_buy.value}"],
df["&-s_close"] > 0.01,
]
if enter_long_conditions:
@@ -263,7 +250,7 @@ class FreqaiExampleStrategy(IStrategy):
enter_short_conditions = [
df["do_predict"] == 1,
df["&-s_close"] < df[f"sell_roi_{self.std_dev_multiplier_sell.value}"],
df["&-s_close"] < -0.01,
]
if enter_short_conditions:
@@ -276,14 +263,14 @@ class FreqaiExampleStrategy(IStrategy):
def populate_exit_trend(self, df: DataFrame, metadata: dict) -> DataFrame:
exit_long_conditions = [
df["do_predict"] == 1,
df["&-s_close"] < df[f"sell_roi_{self.std_dev_multiplier_sell.value}"] * 0.25,
df["&-s_close"] < 0
]
if exit_long_conditions:
df.loc[reduce(lambda x, y: x & y, exit_long_conditions), "exit_long"] = 1
exit_short_conditions = [
df["do_predict"] == 1,
df["&-s_close"] > df[f"target_roi_{self.std_dev_multiplier_buy.value}"] * 0.25,
df["&-s_close"] > 0
]
if exit_short_conditions:
df.loc[reduce(lambda x, y: x & y, exit_short_conditions), "exit_short"] = 1
freqtrade/templates/base_config.json.j2
+1 -1
View File
@@ -39,7 +39,7 @@
},
{{ exchange | indent(4) }},
"pairlists": [
{{ '{"method": "StaticPairList"}' if exchange_name == 'bittrex' else volume_pairlist }}
{{ volume_pairlist }}
],
"telegram": {
"enabled": {{ telegram | lower }},
freqtrade/types/backtest_result_type.py
+5 -1
View File
@@ -1,4 +1,4 @@
from typing import Any, Dict, List
from typing import Any, Dict, List, Optional
from typing_extensions import TypedDict
@@ -26,3 +26,7 @@ class BacktestHistoryEntryType(BacktestMetadataType):
filename: str
strategy: str
notes: str
backtest_start_ts: Optional[int]
backtest_end_ts: Optional[int]
timeframe: Optional[str]
timeframe_detail: Optional[str]
freqtrade/util/__init__.py
+4
View File
@@ -1,6 +1,7 @@
from freqtrade.util.datetime_helpers import (dt_floor_day, dt_from_ts, dt_humanize, dt_now, dt_ts,
dt_ts_def, dt_utc, format_date, format_ms_time,
shorten_date)
from freqtrade.util.formatters import decimals_per_coin, fmt_coin, round_value
from freqtrade.util.ft_precise import FtPrecise
from freqtrade.util.periodic_cache import PeriodicCache
from freqtrade.util.template_renderer import render_template, render_template_with_fallback # noqa
@@ -19,4 +20,7 @@ __all__ = [
'FtPrecise',
'PeriodicCache',
'shorten_date',
'decimals_per_coin',
'round_value',
'fmt_coin',
]
freqtrade/util/formatters.py
+42
View File
@@ -0,0 +1,42 @@
from freqtrade.constants import DECIMAL_PER_COIN_FALLBACK, DECIMALS_PER_COIN
def decimals_per_coin(coin: str):
"""
Helper method getting decimal amount for this coin
example usage: f".{decimals_per_coin('USD')}f"
:param coin: Which coin are we printing the price / value for
"""
return DECIMALS_PER_COIN.get(coin, DECIMAL_PER_COIN_FALLBACK)
def round_value(value: float, decimals: int, keep_trailing_zeros=False) -> str:
"""
Round value to given decimals
:param value: Value to be rounded
:param decimals: Number of decimals to round to
:param keep_trailing_zeros: Keep trailing zeros "222.200" vs. "222.2"
:return: Rounded value as string
"""
val = f"{value:.{decimals}f}"
if not keep_trailing_zeros:
val = val.rstrip('0').rstrip('.')
return val
def fmt_coin(
value: float, coin: str, show_coin_name=True, keep_trailing_zeros=False) -> str:
"""
Format price value for this coin
:param value: Value to be printed
:param coin: Which coin are we printing the price / value for
:param show_coin_name: Return string in format: "222.22 USDT" or "222.22"
:param keep_trailing_zeros: Keep trailing zeros "222.200" vs. "222.2"
:return: Formatted / rounded value (with or without coin name)
"""
val = f"{value:.{decimals_per_coin(coin)}f}"
val = round_value(value, decimals_per_coin(coin), keep_trailing_zeros)
if show_coin_name:
val = f"{val} {coin}"
return val
freqtrade/util/migrations/__init__.py
+12
View File
@@ -0,0 +1,12 @@
from typing import Optional
from freqtrade.exchange import Exchange
from freqtrade.util.migrations.binance_mig import migrate_binance_futures_names # noqa F401
from freqtrade.util.migrations.binance_mig import migrate_binance_futures_data
from freqtrade.util.migrations.funding_rate_mig import migrate_funding_fee_timeframe
def migrate_data(config, exchange: Optional[Exchange] = None):
migrate_binance_futures_data(config)
migrate_funding_fee_timeframe(config, exchange)
freqtrade/util/binance_mig.py → freqtrade/util/migrations/binance_mig.py
View File
freqtrade/util/migrations/funding_rate_mig.py
+27
View File
@@ -0,0 +1,27 @@
import logging
from typing import Optional
from freqtrade.constants import Config
from freqtrade.data.history.idatahandler import get_datahandler
from freqtrade.enums import TradingMode
from freqtrade.exchange import Exchange
logger = logging.getLogger(__name__)
def migrate_funding_fee_timeframe(config: Config, exchange: Optional[Exchange]):
if (
config.get('trading_mode', TradingMode.SPOT) != TradingMode.FUTURES
):
# only act on futures
return
if not exchange:
from freqtrade.resolvers import ExchangeResolver
exchange = ExchangeResolver.load_exchange(config, validate=False)
ff_timeframe = exchange.get_option('funding_fee_timeframe')
dhc = get_datahandler(config['datadir'], config['dataformat_ohlcv'])
dhc.fix_funding_fee_timeframe(ff_timeframe)
freqtrade/wallets.py
+7 -6
View File
@@ -6,7 +6,7 @@ from copy import deepcopy
from datetime import datetime, timedelta
from typing import Dict, NamedTuple, Optional
from freqtrade.constants import UNLIMITED_STAKE_AMOUNT, Config
from freqtrade.constants import UNLIMITED_STAKE_AMOUNT, Config, IntOrInf
from freqtrade.enums import RunMode, TradingMode
from freqtrade.exceptions import DependencyException
from freqtrade.exchange import Exchange
@@ -262,15 +262,15 @@ class Wallets:
return min(self.get_total_stake_amount() - Trade.total_open_trades_stakes(), free)
def _calculate_unlimited_stake_amount(self, available_amount: float,
val_tied_up: float) -> float:
val_tied_up: float, max_open_trades: IntOrInf) -> float:
"""
Calculate stake amount for "unlimited" stake amount
:return: 0 if max number of trades reached, else stake_amount to use.
"""
if self._config['max_open_trades'] == 0:
if max_open_trades == 0:
return 0
possible_stake = (available_amount + val_tied_up) / self._config['max_open_trades']
possible_stake = (available_amount + val_tied_up) / max_open_trades
# Theoretical amount can be above available amount - therefore limit to available amount!
return min(possible_stake, available_amount)
@@ -298,7 +298,8 @@ class Wallets:
return stake_amount
def get_trade_stake_amount(self, pair: str, edge=None, update: bool = True) -> float:
def get_trade_stake_amount(
self, pair: str, max_open_trades: IntOrInf, edge=None, update: bool = True) -> float:
"""
Calculate stake amount for the trade
:return: float: Stake amount
@@ -322,7 +323,7 @@ class Wallets:
stake_amount = self._config['stake_amount']
if stake_amount == UNLIMITED_STAKE_AMOUNT:
stake_amount = self._calculate_unlimited_stake_amount(
available_amount, val_tied_up)
available_amount, val_tied_up, max_open_trades)
return self._check_available_stake_amount(stake_amount, available_amount)
pyproject.toml
+65
View File
@@ -2,6 +2,55 @@
requires = ["setuptools >= 64.0.0", "wheel"]
build-backend = "setuptools.build_meta"
[project]
name = "freqtrade"
dynamic = ["version", "dependencies", "optional-dependencies"]
authors = [
{name = "Freqtrade Team"},
{name = "Freqtrade Team", email = "freqtrade@protonmail.com"},
]
description = "Freqtrade - Crypto Trading Bot"
readme = "README.md"
requires-python = ">=3.9"
license = {text = "GPLv3"}
# license = "GPLv3"
classifiers = [
"Environment :: Console",
"Intended Audience :: Science/Research",
"License :: OSI Approved :: GNU General Public License v3 (GPLv3)",
"Programming Language :: Python :: 3.9",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"Operating System :: MacOS",
"Operating System :: Unix",
"Topic :: Office/Business :: Financial :: Investment",
]
[project.urls]
Homepage = "https://github.com/freqtrade/freqtrade"
Documentation = "https://freqtrade.io"
"Bug Tracker" = "https://github.com/freqtrade/freqtrade/issues"
[project.scripts]
freqtrade = "freqtrade.main:main"
[tool.setuptools]
include-package-data = true
zip-safe = false
[tool.setuptools.packages.find]
where = ["."]
include = ["freqtrade*"]
exclude = ["tests", "tests.*"]
namespaces = true
[tool.setuptools.dynamic]
version = {attr = "freqtrade.__version__"}
[tool.black]
line-length = 100
exclude = '''
@@ -31,6 +80,7 @@ skip_glob = ["**/.env*", "**/env/*", "**/.venv/*", "**/docs/*", "**/user_data/*"
[tool.pytest.ini_options]
asyncio_mode = "auto"
addopts = "--dist loadscope"
[tool.mypy]
ignore_missing_imports = true
@@ -93,3 +143,18 @@ max-complexity = 12
[tool.ruff.per-file-ignores]
"tests/*" = ["S"]
[tool.flake8]
# Default from https://flake8.pycqa.org/en/latest/user/options.html#cmdoption-flake8-ignore
# minus E226
ignore = ["E121","E123","E126","E24","E704","W503","W504"]
max-line-length = 100
max-complexity = 12
exclude = [
".git",
"__pycache__",
".eggs",
"user_data",
".venv",
".env",
]
requirements-dev.txt
+10 -9
View File
@@ -7,24 +7,25 @@
-r docs/requirements-docs.txt
coveralls==3.3.1
ruff==0.1.6
mypy==1.7.1
pre-commit==3.5.0
pytest==7.4.3
ruff==0.1.11
mypy==1.8.0
pre-commit==3.6.0
pytest==7.4.4
pytest-asyncio==0.21.1
pytest-cov==4.1.0
pytest-mock==3.12.0
pytest-random-order==1.1.0
isort==5.12.0
pytest-xdist==3.5.0
isort==5.13.2
# For datetime mocking
time-machine==2.13.0
# Convert jupyter notebooks to markdown documents
nbconvert==7.11.0
nbconvert==7.14.0
# mypy types
types-cachetools==5.3.0.7
types-filelock==3.2.7
types-requests==2.31.0.10
types-tabulate==0.9.0.3
types-python-dateutil==2.8.19.14
types-requests==2.31.0.20240106
types-tabulate==0.9.0.20240106
types-python-dateutil==2.8.19.20240106
requirements-freqai-rl.txt
+1 -1
View File
@@ -2,7 +2,7 @@
-r requirements-freqai.txt
# Required for freqai-rl
torch==2.0.1
torch==2.1.2
#until these branches will be released we can use this
gymnasium==0.29.1
stable_baselines3==2.2.1
requirements-freqai.txt
+3 -3
View File
@@ -3,10 +3,10 @@
-r requirements-plot.txt
# Required for freqai
scikit-learn==1.1.3
scikit-learn==1.3.2
joblib==1.3.2
catboost==1.2.2; 'arm' not in platform_machine
lightgbm==4.1.0
xgboost==2.0.2
lightgbm==4.2.0
xgboost==2.0.3
tensorboard==2.15.1
datasieve==0.1.7
requirements-hyperopt.txt
+2 -2
View File
@@ -3,6 +3,6 @@
# Required for hyperopt
scipy==1.11.4
scikit-learn==1.1.3
scikit-optimize==0.9.0
scikit-learn==1.3.2
ft-scikit-optimize==0.9.2
filelock==3.13.1
requirements.txt
+12 -12
View File
@@ -1,12 +1,12 @@
numpy==1.26.2
pandas==2.1.3
numpy==1.26.3
pandas==2.1.4
pandas-ta==0.3.14b
ccxt==4.1.66
ccxt==4.2.9
cryptography==41.0.7
aiohttp==3.9.1
SQLAlchemy==2.0.23
python-telegram-bot==20.6
python-telegram-bot==20.7
# can't be hard-pinned due to telegram-bot pinning httpx with ~
httpx>=0.24.1
arrow==1.3.0
@@ -15,20 +15,20 @@ requests==2.31.0
urllib3==2.1.0
jsonschema==4.20.0
TA-Lib==0.4.28
technical==1.4.0
technical==1.4.2
tabulate==0.9.0
pycoingecko==3.1.0
jinja2==3.1.2
tables==3.9.1
joblib==1.3.2
rich==13.7.0
pyarrow==14.0.1; platform_machine != 'armv7l'
pyarrow==14.0.2; platform_machine != 'armv7l'
# find first, C search in arrays
py_find_1st==1.1.6
# Load ticker files 30% faster
python-rapidjson==1.13
python-rapidjson==1.14
# Properly format api responses
orjson==3.9.10
@@ -36,12 +36,12 @@ orjson==3.9.10
sdnotify==0.3.2
# API Server
fastapi==0.104.1
pydantic==2.5.2
uvicorn==0.24.0.post1
fastapi==0.108.0
pydantic==2.5.3
uvicorn==0.25.0
pyjwt==2.8.0
aiofiles==23.2.1
psutil==5.9.6
psutil==5.9.7
# Support for colorized terminal output
colorama==0.4.6
@@ -58,5 +58,5 @@ schedule==1.2.1
websockets==12.0
janus==1.0.0
ast-comments==1.2.0
ast-comments==1.2.1
packaging==23.2
setup.cfg
-53
View File
@@ -1,53 +0,0 @@
[metadata]
name = freqtrade
version = attr: freqtrade.__version__
author = Freqtrade Team
author_email = freqtrade@protonmail.com
description = Freqtrade - Crypto Trading Bot
long_description = file: README.md
long_description_content_type = text/markdown
url = https://github.com/freqtrade/freqtrade
project_urls =
Bug Tracker = https://github.com/freqtrade/freqtrade/issues
license = GPLv3
classifiers =
Environment :: Console
Intended Audience :: Science/Research
License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Programming Language :: Python :: 3.9
Programming Language :: Python :: 3.10
Programming Language :: Python :: 3.11
Operating System :: MacOS
Operating System :: Unix
Topic :: Office/Business :: Financial :: Investment
[options]
zip_safe = False
include_package_data = True
tests_require =
pytest
pytest-asyncio
pytest-cov
pytest-mock
packages = find:
python_requires = >=3.9
[options.entry_points]
console_scripts =
freqtrade = freqtrade.main:main
[flake8]
# Default from https://flake8.pycqa.org/en/latest/user/options.html#cmdoption-flake8-ignore
# minus E226
ignore = E121,E123,E126,E24,E704,W503,W504
max-line-length = 100
max-complexity = 12
exclude =
.git,
__pycache__,
.eggs,
user_data,
.venv
.env
setup.py
+3 -2
View File
@@ -5,8 +5,8 @@ from setuptools import setup
plot = ['plotly>=4.0']
hyperopt = [
'scipy',
'scikit-learn<=1.1.3',
'scikit-optimize>=0.7.0',
'scikit-learn',
'ft-scikit-optimize>=0.9.2',
'filelock',
]
@@ -122,4 +122,5 @@ setup(
'freqai_rl': freqai_rl,
'all': all_extra,
},
url="https://github.com/freqtrade/freqtrade",
)
tests/commands/test_build_config.py
+1 -1
View File
@@ -30,7 +30,7 @@ def test_validate_is_int():
assert not validate_is_int('-ee')
@pytest.mark.parametrize('exchange', ['bittrex', 'binance', 'kraken'])
@pytest.mark.parametrize('exchange', ['bybit', 'binance', 'kraken'])
def test_start_new_config(mocker, caplog, exchange):
wt_mock = mocker.patch.object(Path, "write_text", MagicMock())
mocker.patch.object(Path, "exists", MagicMock(return_value=True))
tests/commands/test_commands.py
+53 -53
View File
@@ -32,7 +32,7 @@ from tests.conftest_trades import MOCK_TRADE_COUNT
def test_setup_utils_configuration():
args = [
'list-exchanges', '--config', 'config_examples/config_bittrex.example.json',
'list-exchanges', '--config', 'tests/testdata/testconfigs/main_test_config.json',
]
config = setup_utils_configuration(get_args(args), RunMode.OTHER)
@@ -49,7 +49,7 @@ def test_start_trading_fail(mocker, caplog):
exitmock = mocker.patch("freqtrade.worker.Worker.exit", MagicMock())
args = [
'trade',
'-c', 'config_examples/config_bittrex.example.json'
'-c', 'tests/testdata/testconfigs/main_test_config.json'
]
start_trading(get_args(args))
assert exitmock.call_count == 1
@@ -68,7 +68,7 @@ def test_start_webserver(mocker, caplog):
args = [
'webserver',
'-c', 'config_examples/config_bittrex.example.json'
'-c', 'tests/testdata/testconfigs/main_test_config.json'
]
start_webserver(get_args(args))
assert api_server_mock.call_count == 1
@@ -84,7 +84,7 @@ def test_list_exchanges(capsys):
captured = capsys.readouterr()
assert re.match(r"Exchanges available for Freqtrade.*", captured.out)
assert re.search(r".*binance.*", captured.out)
assert re.search(r".*bittrex.*", captured.out)
assert re.search(r".*bybit.*", captured.out)
# Test with --one-column
args = [
@@ -95,7 +95,7 @@ def test_list_exchanges(capsys):
start_list_exchanges(get_args(args))
captured = capsys.readouterr()
assert re.search(r"^binance$", captured.out, re.MULTILINE)
assert re.search(r"^bittrex$", captured.out, re.MULTILINE)
assert re.search(r"^bybit$", captured.out, re.MULTILINE)
# Test with --all
args = [
@@ -107,7 +107,7 @@ def test_list_exchanges(capsys):
captured = capsys.readouterr()
assert re.match(r"All exchanges supported by the ccxt library.*", captured.out)
assert re.search(r".*binance.*", captured.out)
assert re.search(r".*bittrex.*", captured.out)
assert re.search(r".*bingx.*", captured.out)
assert re.search(r".*bitmex.*", captured.out)
# Test with --one-column --all
@@ -120,7 +120,7 @@ def test_list_exchanges(capsys):
start_list_exchanges(get_args(args))
captured = capsys.readouterr()
assert re.search(r"^binance$", captured.out, re.MULTILINE)
assert re.search(r"^bittrex$", captured.out, re.MULTILINE)
assert re.search(r"^bingx$", captured.out, re.MULTILINE)
assert re.search(r"^bitmex$", captured.out, re.MULTILINE)
@@ -133,7 +133,7 @@ def test_list_timeframes(mocker, capsys):
'1h': 'hour',
'1d': 'day',
}
patch_exchange(mocker, api_mock=api_mock, id='bittrex')
patch_exchange(mocker, api_mock=api_mock, id='bybit')
args = [
"list-timeframes",
]
@@ -143,25 +143,25 @@ def test_list_timeframes(mocker, capsys):
match=r"This command requires a configured exchange.*"):
start_list_timeframes(pargs)
# Test with --config config_examples/config_bittrex.example.json
# Test with --config tests/testdata/testconfigs/main_test_config.json
args = [
"list-timeframes",
'--config', 'config_examples/config_bittrex.example.json',
'--config', 'tests/testdata/testconfigs/main_test_config.json',
]
start_list_timeframes(get_args(args))
captured = capsys.readouterr()
assert re.match("Timeframes available for the exchange `Bittrex`: "
assert re.match("Timeframes available for the exchange `Bybit`: "
"1m, 5m, 30m, 1h, 1d",
captured.out)
# Test with --exchange bittrex
# Test with --exchange bybit
args = [
"list-timeframes",
"--exchange", "bittrex",
"--exchange", "bybit",
]
start_list_timeframes(get_args(args))
captured = capsys.readouterr()
assert re.match("Timeframes available for the exchange `Bittrex`: "
assert re.match("Timeframes available for the exchange `Bybit`: "
"1m, 5m, 30m, 1h, 1d",
captured.out)
@@ -190,7 +190,7 @@ def test_list_timeframes(mocker, capsys):
# Test with --one-column
args = [
"list-timeframes",
'--config', 'config_examples/config_bittrex.example.json',
'--config', 'tests/testdata/testconfigs/main_test_config.json',
"--one-column",
]
start_list_timeframes(get_args(args))
@@ -217,7 +217,7 @@ def test_list_timeframes(mocker, capsys):
def test_list_markets(mocker, markets_static, capsys):
api_mock = MagicMock()
patch_exchange(mocker, api_mock=api_mock, id='bittrex', mock_markets=markets_static)
patch_exchange(mocker, api_mock=api_mock, id='binance', mock_markets=markets_static)
# Test with no --config
args = [
@@ -229,15 +229,15 @@ def test_list_markets(mocker, markets_static, capsys):
match=r"This command requires a configured exchange.*"):
start_list_markets(pargs, False)
# Test with --config config_examples/config_bittrex.example.json
# Test with --config tests/testdata/testconfigs/main_test_config.json
args = [
"list-markets",
'--config', 'config_examples/config_bittrex.example.json',
'--config', 'tests/testdata/testconfigs/main_test_config.json',
"--print-list",
]
start_list_markets(get_args(args), False)
captured = capsys.readouterr()
assert ("Exchange Bittrex has 12 active markets: "
assert ("Exchange Binance has 12 active markets: "
"ADA/USDT:USDT, BLK/BTC, ETH/BTC, ETH/USDT, ETH/USDT:USDT, LTC/BTC, "
"LTC/ETH, LTC/USD, NEO/BTC, TKN/BTC, XLTCUSDT, XRP/BTC.\n"
in captured.out)
@@ -255,16 +255,16 @@ def test_list_markets(mocker, markets_static, capsys):
assert re.match("\nExchange Binance has 12 active markets:\n",
captured.out)
patch_exchange(mocker, api_mock=api_mock, id="bittrex", mock_markets=markets_static)
patch_exchange(mocker, api_mock=api_mock, id="binance", mock_markets=markets_static)
# Test with --all: all markets
args = [
"list-markets", "--all",
'--config', 'config_examples/config_bittrex.example.json',
'--config', 'tests/testdata/testconfigs/main_test_config.json',
"--print-list",
]
start_list_markets(get_args(args), False)
captured = capsys.readouterr()
assert ("Exchange Bittrex has 14 markets: "
assert ("Exchange Binance has 14 markets: "
"ADA/USDT:USDT, BLK/BTC, BTT/BTC, ETH/BTC, ETH/USDT, ETH/USDT:USDT, "
"LTC/BTC, LTC/ETH, LTC/USD, LTC/USDT, NEO/BTC, TKN/BTC, XLTCUSDT, XRP/BTC.\n"
in captured.out)
@@ -272,24 +272,24 @@ def test_list_markets(mocker, markets_static, capsys):
# Test list-pairs subcommand: active pairs
args = [
"list-pairs",
'--config', 'config_examples/config_bittrex.example.json',
'--config', 'tests/testdata/testconfigs/main_test_config.json',
"--print-list",
]
start_list_markets(get_args(args), True)
captured = capsys.readouterr()
assert ("Exchange Bittrex has 9 active pairs: "
assert ("Exchange Binance has 9 active pairs: "
"BLK/BTC, ETH/BTC, ETH/USDT, LTC/BTC, LTC/ETH, LTC/USD, NEO/BTC, TKN/BTC, XRP/BTC.\n"
in captured.out)
# Test list-pairs subcommand with --all: all pairs
args = [
"list-pairs", "--all",
'--config', 'config_examples/config_bittrex.example.json',
'--config', 'tests/testdata/testconfigs/main_test_config.json',
"--print-list",
]
start_list_markets(get_args(args), True)
captured = capsys.readouterr()
assert ("Exchange Bittrex has 11 pairs: "
assert ("Exchange Binance has 11 pairs: "
"BLK/BTC, BTT/BTC, ETH/BTC, ETH/USDT, LTC/BTC, LTC/ETH, LTC/USD, LTC/USDT, NEO/BTC, "
"TKN/BTC, XRP/BTC.\n"
in captured.out)
@@ -297,133 +297,133 @@ def test_list_markets(mocker, markets_static, capsys):
# active markets, base=ETH, LTC
args = [
"list-markets",
'--config', 'config_examples/config_bittrex.example.json',
'--config', 'tests/testdata/testconfigs/main_test_config.json',
"--base", "ETH", "LTC",
"--print-list",
]
start_list_markets(get_args(args), False)
captured = capsys.readouterr()
assert ("Exchange Bittrex has 7 active markets with ETH, LTC as base currencies: "
assert ("Exchange Binance has 7 active markets with ETH, LTC as base currencies: "
"ETH/BTC, ETH/USDT, ETH/USDT:USDT, LTC/BTC, LTC/ETH, LTC/USD, XLTCUSDT.\n"
in captured.out)
# active markets, base=LTC
args = [
"list-markets",
'--config', 'config_examples/config_bittrex.example.json',
'--config', 'tests/testdata/testconfigs/main_test_config.json',
"--base", "LTC",
"--print-list",
]
start_list_markets(get_args(args), False)
captured = capsys.readouterr()
assert ("Exchange Bittrex has 4 active markets with LTC as base currency: "
assert ("Exchange Binance has 4 active markets with LTC as base currency: "
"LTC/BTC, LTC/ETH, LTC/USD, XLTCUSDT.\n"
in captured.out)
# active markets, quote=USDT, USD
args = [
"list-markets",
'--config', 'config_examples/config_bittrex.example.json',
'--config', 'tests/testdata/testconfigs/main_test_config.json',
"--quote", "USDT", "USD",
"--print-list",
]
start_list_markets(get_args(args), False)
captured = capsys.readouterr()
assert ("Exchange Bittrex has 5 active markets with USDT, USD as quote currencies: "
assert ("Exchange Binance has 5 active markets with USDT, USD as quote currencies: "
"ADA/USDT:USDT, ETH/USDT, ETH/USDT:USDT, LTC/USD, XLTCUSDT.\n"
in captured.out)
# active markets, quote=USDT
args = [
"list-markets",
'--config', 'config_examples/config_bittrex.example.json',
'--config', 'tests/testdata/testconfigs/main_test_config.json',
"--quote", "USDT",
"--print-list",
]
start_list_markets(get_args(args), False)
captured = capsys.readouterr()
assert ("Exchange Bittrex has 4 active markets with USDT as quote currency: "
assert ("Exchange Binance has 4 active markets with USDT as quote currency: "
"ADA/USDT:USDT, ETH/USDT, ETH/USDT:USDT, XLTCUSDT.\n"
in captured.out)
# active markets, base=LTC, quote=USDT
args = [
"list-markets",
'--config', 'config_examples/config_bittrex.example.json',
'--config', 'tests/testdata/testconfigs/main_test_config.json',
"--base", "LTC", "--quote", "USDT",
"--print-list",
]
start_list_markets(get_args(args), False)
captured = capsys.readouterr()
assert ("Exchange Bittrex has 1 active market with LTC as base currency and "
assert ("Exchange Binance has 1 active market with LTC as base currency and "
"with USDT as quote currency: XLTCUSDT.\n"
in captured.out)
# active pairs, base=LTC, quote=USDT
args = [
"list-pairs",
'--config', 'config_examples/config_bittrex.example.json',
'--config', 'tests/testdata/testconfigs/main_test_config.json',
"--base", "LTC", "--quote", "USD",
"--print-list",
]
start_list_markets(get_args(args), True)
captured = capsys.readouterr()
assert ("Exchange Bittrex has 1 active pair with LTC as base currency and "
assert ("Exchange Binance has 1 active pair with LTC as base currency and "
"with USD as quote currency: LTC/USD.\n"
in captured.out)
# active markets, base=LTC, quote=USDT, NONEXISTENT
args = [
"list-markets",
'--config', 'config_examples/config_bittrex.example.json',
'--config', 'tests/testdata/testconfigs/main_test_config.json',
"--base", "LTC", "--quote", "USDT", "NONEXISTENT",
"--print-list",
]
start_list_markets(get_args(args), False)
captured = capsys.readouterr()
assert ("Exchange Bittrex has 1 active market with LTC as base currency and "
assert ("Exchange Binance has 1 active market with LTC as base currency and "
"with USDT, NONEXISTENT as quote currencies: XLTCUSDT.\n"
in captured.out)
# active markets, base=LTC, quote=NONEXISTENT
args = [
"list-markets",
'--config', 'config_examples/config_bittrex.example.json',
'--config', 'tests/testdata/testconfigs/main_test_config.json',
"--base", "LTC", "--quote", "NONEXISTENT",
"--print-list",
]
start_list_markets(get_args(args), False)
captured = capsys.readouterr()
assert ("Exchange Bittrex has 0 active markets with LTC as base currency and "
assert ("Exchange Binance has 0 active markets with LTC as base currency and "
"with NONEXISTENT as quote currency.\n"
in captured.out)
# Test tabular output
args = [
"list-markets",
'--config', 'config_examples/config_bittrex.example.json',
'--config', 'tests/testdata/testconfigs/main_test_config.json',
]
start_list_markets(get_args(args), False)
captured = capsys.readouterr()
assert ("Exchange Bittrex has 12 active markets:\n"
assert ("Exchange Binance has 12 active markets:\n"
in captured.out)
# Test tabular output, no markets found
args = [
"list-markets",
'--config', 'config_examples/config_bittrex.example.json',
'--config', 'tests/testdata/testconfigs/main_test_config.json',
"--base", "LTC", "--quote", "NONEXISTENT",
]
start_list_markets(get_args(args), False)
captured = capsys.readouterr()
assert ("Exchange Bittrex has 0 active markets with LTC as base currency and "
assert ("Exchange Binance has 0 active markets with LTC as base currency and "
"with NONEXISTENT as quote currency.\n"
in captured.out)
# Test --print-json
args = [
"list-markets",
'--config', 'config_examples/config_bittrex.example.json',
'--config', 'tests/testdata/testconfigs/main_test_config.json',
"--print-json"
]
start_list_markets(get_args(args), False)
@@ -435,7 +435,7 @@ def test_list_markets(mocker, markets_static, capsys):
# Test --print-csv
args = [
"list-markets",
'--config', 'config_examples/config_bittrex.example.json',
'--config', 'tests/testdata/testconfigs/main_test_config.json',
"--print-csv"
]
start_list_markets(get_args(args), False)
@@ -447,7 +447,7 @@ def test_list_markets(mocker, markets_static, capsys):
# Test --one-column
args = [
"list-markets",
'--config', 'config_examples/config_bittrex.example.json',
'--config', 'tests/testdata/testconfigs/main_test_config.json',
"--one-column"
]
start_list_markets(get_args(args), False)
@@ -459,7 +459,7 @@ def test_list_markets(mocker, markets_static, capsys):
# Test --one-column
args = [
"list-markets",
'--config', 'config_examples/config_bittrex.example.json',
'--config', 'tests/testdata/testconfigs/main_test_config.json',
"--one-column"
]
with pytest.raises(OperationalException, match=r"Cannot get markets.*"):
@@ -971,7 +971,7 @@ def test_start_test_pairlist(mocker, caplog, tickers, default_conf, capsys):
patched_configuration_load_config_file(mocker, default_conf)
args = [
'test-pairlist',
'-c', 'config_examples/config_bittrex.example.json'
'-c', 'tests/testdata/testconfigs/main_test_config.json'
]
start_test_pairlist(get_args(args))
@@ -985,7 +985,7 @@ def test_start_test_pairlist(mocker, caplog, tickers, default_conf, capsys):
args = [
'test-pairlist',
'-c', 'config_examples/config_bittrex.example.json',
'-c', 'tests/testdata/testconfigs/main_test_config.json',
'--one-column',
]
start_test_pairlist(get_args(args))
@@ -994,7 +994,7 @@ def test_start_test_pairlist(mocker, caplog, tickers, default_conf, capsys):
args = [
'test-pairlist',
'-c', 'config_examples/config_bittrex.example.json',
'-c', 'tests/testdata/testconfigs/main_test_config.json',
'--print-json',
]
start_test_pairlist(get_args(args))
tests/conftest.py
+30 -3
View File
@@ -11,6 +11,7 @@ from unittest.mock import MagicMock, Mock, PropertyMock
import numpy as np
import pandas as pd
import pytest
from xdist.scheduler.loadscope import LoadScopeScheduling
from freqtrade import constants
from freqtrade.commands import Arguments
@@ -56,6 +57,27 @@ def pytest_configure(config):
setattr(config.option, 'markexpr', 'not longrun')
class FixtureScheduler(LoadScopeScheduling):
# Based on the suggestion in
# https://github.com/pytest-dev/pytest-xdist/issues/18
def _split_scope(self, nodeid):
if 'exchange_online' in nodeid:
try:
# Extract exchange ID from nodeid
exchange_id = nodeid.split('[')[1].split('-')[0].rstrip(']')
return exchange_id
except Exception as e:
print(e)
pass
return nodeid
def pytest_xdist_make_scheduler(config, log):
return FixtureScheduler(config, log)
def log_has(line, logs):
"""Check if line is found on some caplog's message."""
return any(line == message for message in logs.messages)
@@ -87,11 +109,15 @@ def get_args(args):
def generate_test_data(timeframe: str, size: int, start: str = '2020-07-05'):
np.random.seed(42)
tf_mins = timeframe_to_minutes(timeframe)
base = np.random.normal(20, 2, size=size)
date = pd.date_range(start, periods=size, freq=f'{tf_mins}min', tz='UTC')
if timeframe == '1M':
date = pd.date_range(start, periods=size, freq='1MS', tz='UTC')
elif timeframe == '1w':
date = pd.date_range(start, periods=size, freq='1W-MON', tz='UTC')
else:
tf_mins = timeframe_to_minutes(timeframe)
date = pd.date_range(start, periods=size, freq=f'{tf_mins}min', tz='UTC')
df = pd.DataFrame({
'date': date,
'open': base,
@@ -527,6 +553,7 @@ def get_default_conf(testdatadir):
"internals": {},
"export": "none",
"dataformat_ohlcv": "feather",
"runmode": "dry_run",
"candle_type_def": CandleType.SPOT,
}
return configuration
tests/data/test_converter.py
+2 -2
View File
@@ -64,7 +64,7 @@ def test_ohlcv_fill_up_missing_data(testdatadir, caplog):
# Column names should not change
assert (data.columns == data2.columns).all()
assert log_has_re(f"Missing data fillup for UNITTEST/BTC: before: "
assert log_has_re(f"Missing data fillup for UNITTEST/BTC, 1m: before: "
f"{len(data)} - after: {len(data2)}.*", caplog)
# Test fillup actually fixes invalid backtest data
@@ -128,7 +128,7 @@ def test_ohlcv_fill_up_missing_data2(caplog):
# Column names should not change
assert (data.columns == data2.columns).all()
assert log_has_re(f"Missing data fillup for UNITTEST/BTC: before: "
assert log_has_re(f"Missing data fillup for UNITTEST/BTC, {timeframe}: before: "
f"{len(data)} - after: {len(data2)}.*", caplog)
tests/data/test_datahandler.py
+3 -3
View File
@@ -513,11 +513,11 @@ def test_gethandlerclass():
def test_get_datahandler(testdatadir):
dh = get_datahandler(testdatadir, 'json')
assert type(dh) == JsonDataHandler
assert isinstance(dh, JsonDataHandler)
dh = get_datahandler(testdatadir, 'jsongz')
assert type(dh) == JsonGzDataHandler
assert isinstance(dh, JsonGzDataHandler)
dh1 = get_datahandler(testdatadir, 'jsongz', dh)
assert id(dh1) == id(dh)
dh = get_datahandler(testdatadir, 'hdf5')
assert type(dh) == HDF5DataHandler
assert isinstance(dh, HDF5DataHandler)
tests/data/test_dataprovider.py
+59
View File
@@ -500,3 +500,62 @@ def test_dp__add_external_df(default_conf_usdt):
# 36 hours - from 2022-01-03 12:00:00+00:00 to 2022-01-05 00:00:00+00:00
assert isinstance(res[1], int)
assert res[1] == 0
def test_dp_get_required_startup(default_conf_usdt):
timeframe = '1h'
default_conf_usdt["timeframe"] = timeframe
dp = DataProvider(default_conf_usdt, None)
# No FreqAI config
assert dp.get_required_startup('5m') == 0
assert dp.get_required_startup('1h') == 0
assert dp.get_required_startup('1d') == 0
dp._config['startup_candle_count'] = 20
assert dp.get_required_startup('5m') == 20
assert dp.get_required_startup('1h') == 20
assert dp.get_required_startup('1h') == 20
# With freqAI config
dp._config['freqai'] = {
'enabled': True,
'train_period_days': 20,
'feature_parameters': {
'indicator_periods_candles': [
5,
20,
]
}
}
assert dp.get_required_startup('5m') == 5780
assert dp.get_required_startup('1h') == 500
assert dp.get_required_startup('1d') == 40
# FreqAI kindof ignores startup_candle_count if it's below indicator_periods_candles
dp._config['startup_candle_count'] = 0
assert dp.get_required_startup('5m') == 5780
assert dp.get_required_startup('1h') == 500
assert dp.get_required_startup('1d') == 40
dp._config['freqai']['feature_parameters']['indicator_periods_candles'][1] = 50
assert dp.get_required_startup('5m') == 5810
assert dp.get_required_startup('1h') == 530
assert dp.get_required_startup('1d') == 70
# scenario from issue https://github.com/freqtrade/freqtrade/issues/9432
dp._config['freqai'] = {
'enabled': True,
'train_period_days': 180,
'feature_parameters': {
'indicator_periods_candles': [
10,
20,
]
}
}
dp._config['startup_candle_count'] = 40
assert dp.get_required_startup('5m') == 51880
assert dp.get_required_startup('1h') == 4360
assert dp.get_required_startup('1d') == 220
tests/data/test_history.py
+5 -1
View File
@@ -508,8 +508,9 @@ def test_refresh_backtest_ohlcv_data(
mocker.patch.object(Path, "exists", MagicMock(return_value=True))
mocker.patch.object(Path, "unlink", MagicMock())
default_conf['trading_mode'] = trademode
ex = get_patched_exchange(mocker, default_conf)
ex = get_patched_exchange(mocker, default_conf, id='bybit')
timerange = TimeRange.parse_timerange("20190101-20190102")
refresh_backtest_ohlcv_data(exchange=ex, pairs=["ETH/BTC", "XRP/BTC"],
timeframes=["1m", "5m"], datadir=testdatadir,
@@ -521,6 +522,9 @@ def test_refresh_backtest_ohlcv_data(
assert dl_mock.call_args[1]['timerange'].starttype == 'date'
assert log_has_re(r"Downloading pair ETH/BTC, .* interval 1m\.", caplog)
if trademode == 'futures':
assert log_has_re(r"Downloading pair ETH/BTC, funding_rate, interval 8h\.", caplog)
assert log_has_re(r"Downloading pair ETH/BTC, mark, interval 4h\.", caplog)
def test_download_data_no_markets(mocker, default_conf, caplog, testdatadir):
tests/exchange/test_exchange.py
+99 -42
View File
@@ -13,7 +13,7 @@ from freqtrade.enums import CandleType, MarginMode, TradingMode
from freqtrade.exceptions import (DDosProtection, DependencyException, ExchangeError,
InsufficientFundsError, InvalidOrderException,
OperationalException, PricingError, TemporaryError)
from freqtrade.exchange import (Binance, Bittrex, Exchange, Kraken, market_is_active,
from freqtrade.exchange import (Binance, Bybit, Exchange, Kraken, market_is_active,
timeframe_to_prev_date)
from freqtrade.exchange.common import (API_FETCH_ORDER_RETRY_COUNT, API_RETRY_COUNT,
calculate_backoff, remove_exchange_credentials)
@@ -24,7 +24,7 @@ from tests.conftest import (EXMS, generate_test_data_raw, get_mock_coro, get_pat
# Make sure to always keep one exchange here which is NOT subclassed!!
EXCHANGES = ['bittrex', 'binance', 'kraken', 'gate', 'kucoin', 'bybit', 'okx']
EXCHANGES = ['binance', 'kraken', 'gate', 'kucoin', 'bybit', 'okx']
get_entry_rate_data = [
('other', 20, 19, 10, 0.0, 20), # Full ask side
@@ -55,7 +55,7 @@ get_entry_rate_data = [
('bid', 6, 5, None, 0, 5), # last not available - uses bid
]
get_sell_rate_data = [
get_exit_rate_data = [
('bid', 12.0, 11.0, 11.5, 0.0, 11.0), # full bid side
('bid', 12.0, 11.0, 11.5, 1.0, 11.5), # full last side
('bid', 12.0, 11.0, 11.5, 0.5, 11.25), # between bid and lat
@@ -228,10 +228,10 @@ def test_exchange_resolver(default_conf, mocker, caplog):
assert log_has_re(r"No .* specific subclass found. Using the generic class instead.", caplog)
caplog.clear()
default_conf['exchange']['name'] = 'Bittrex'
default_conf['exchange']['name'] = 'Bybit'
exchange = ExchangeResolver.load_exchange(default_conf)
assert isinstance(exchange, Exchange)
assert isinstance(exchange, Bittrex)
assert isinstance(exchange, Bybit)
assert not log_has_re(r"No .* specific subclass found. Using the generic class instead.",
caplog)
caplog.clear()
@@ -263,8 +263,8 @@ def test_exchange_resolver(default_conf, mocker, caplog):
def test_validate_order_time_in_force(default_conf, mocker, caplog):
caplog.set_level(logging.INFO)
# explicitly test bittrex, exchanges implementing other policies need separate tests
ex = get_patched_exchange(mocker, default_conf, id="bittrex")
# explicitly test bybit, exchanges implementing other policies need separate tests
ex = get_patched_exchange(mocker, default_conf, id="bybit")
tif = {
"buy": "gtc",
"sell": "gtc",
@@ -273,11 +273,14 @@ def test_validate_order_time_in_force(default_conf, mocker, caplog):
ex.validate_order_time_in_force(tif)
tif2 = {
"buy": "fok",
"sell": "ioc",
"sell": "ioc22",
}
with pytest.raises(OperationalException, match=r"Time in force.*not supported for .*"):
ex.validate_order_time_in_force(tif2)
tif2 = {
"buy": "fok",
"sell": "ioc",
}
# Patch to see if this will pass if the values are in the ft dict
ex._ft_has.update({"order_time_in_force": ["GTC", "FOK", "IOC"]})
ex.validate_order_time_in_force(tif2)
@@ -915,7 +918,6 @@ def test_validate_ordertypes(default_conf, mocker):
mocker.patch(f'{EXMS}.validate_timeframes')
mocker.patch(f'{EXMS}.validate_stakecurrency')
mocker.patch(f'{EXMS}.validate_pricing')
mocker.patch(f'{EXMS}.name', 'Bittrex')
default_conf['order_types'] = {
'entry': 'limit',
@@ -1977,6 +1979,34 @@ def test_fetch_ticker(default_conf, mocker, exchange_name):
exchange.fetch_ticker(pair='XRP/ETH')
@pytest.mark.parametrize("exchange_name", EXCHANGES)
def test___now_is_time_to_refresh(default_conf, mocker, exchange_name, time_machine):
exchange = get_patched_exchange(mocker, default_conf, id=exchange_name)
pair = 'BTC/USDT'
candle_type = CandleType.SPOT
start_dt = datetime(2023, 12, 1, 0, 10, 0, tzinfo=timezone.utc)
time_machine.move_to(start_dt, tick=False)
assert (pair, '5m', candle_type) not in exchange._pairs_last_refresh_time
# not refreshed yet
assert exchange._now_is_time_to_refresh(pair, '5m', candle_type) is True
last_closed_candle = (start_dt - timedelta(minutes=5)).timestamp()
exchange._pairs_last_refresh_time[(pair, '5m', candle_type)] = last_closed_candle
# next candle not closed yet
time_machine.move_to(start_dt + timedelta(minutes=4, seconds=59), tick=False)
assert exchange._now_is_time_to_refresh(pair, '5m', candle_type) is False
# next candle closed
time_machine.move_to(start_dt + timedelta(minutes=5, seconds=0), tick=False)
assert exchange._now_is_time_to_refresh(pair, '5m', candle_type) is True
# 1 second later (last_refresh_time didn't change)
time_machine.move_to(start_dt + timedelta(minutes=5, seconds=1), tick=False)
assert exchange._now_is_time_to_refresh(pair, '5m', candle_type) is True
@pytest.mark.parametrize("exchange_name", EXCHANGES)
@pytest.mark.parametrize('candle_type', ['mark', ''])
def test_get_historic_ohlcv(default_conf, mocker, caplog, exchange_name, candle_type):
@@ -2482,8 +2512,10 @@ def test_fetch_l2_order_book_exception(default_conf, mocker, exchange_name):
@pytest.mark.parametrize("side,ask,bid,last,last_ab,expected", get_entry_rate_data)
def test_get_entry_rate(mocker, default_conf, caplog, side, ask, bid,
last, last_ab, expected) -> None:
last, last_ab, expected, time_machine) -> None:
caplog.set_level(logging.DEBUG)
start_dt = datetime(2023, 12, 1, 0, 10, 0, tzinfo=timezone.utc)
time_machine.move_to(start_dt, tick=False)
if last_ab is None:
del default_conf['entry_pricing']['price_last_balance']
else:
@@ -2491,39 +2523,65 @@ def test_get_entry_rate(mocker, default_conf, caplog, side, ask, bid,
default_conf['entry_pricing']['price_side'] = side
exchange = get_patched_exchange(mocker, default_conf)
mocker.patch(f'{EXMS}.fetch_ticker', return_value={'ask': ask, 'last': last, 'bid': bid})
log_msg = "Using cached entry rate for ETH/BTC."
assert exchange.get_rate('ETH/BTC', side="entry", is_short=False, refresh=True) == expected
assert not log_has("Using cached entry rate for ETH/BTC.", caplog)
assert not log_has(log_msg, caplog)
time_machine.move_to(start_dt + timedelta(minutes=4), tick=False)
# Running a 2nd time without Refresh!
caplog.clear()
assert exchange.get_rate('ETH/BTC', side="entry", is_short=False, refresh=False) == expected
assert log_has("Using cached entry rate for ETH/BTC.", caplog)
assert log_has(log_msg, caplog)
time_machine.move_to(start_dt + timedelta(minutes=6), tick=False)
# Running a 2nd time - forces refresh due to ttl timeout
caplog.clear()
assert exchange.get_rate('ETH/BTC', side="entry", is_short=False, refresh=False) == expected
assert not log_has(log_msg, caplog)
# Running a 2nd time with Refresh on!
caplog.clear()
assert exchange.get_rate('ETH/BTC', side="entry", is_short=False, refresh=True) == expected
assert not log_has("Using cached entry rate for ETH/BTC.", caplog)
assert not log_has(log_msg, caplog)
@pytest.mark.parametrize('side,ask,bid,last,last_ab,expected', get_sell_rate_data)
@pytest.mark.parametrize('side,ask,bid,last,last_ab,expected', get_exit_rate_data)
def test_get_exit_rate(default_conf, mocker, caplog, side, bid, ask,
last, last_ab, expected) -> None:
last, last_ab, expected, time_machine) -> None:
caplog.set_level(logging.DEBUG)
start_dt = datetime(2023, 12, 1, 0, 10, 0, tzinfo=timezone.utc)
time_machine.move_to(start_dt, tick=False)
default_conf['exit_pricing']['price_side'] = side
if last_ab is not None:
default_conf['exit_pricing']['price_last_balance'] = last_ab
mocker.patch(f'{EXMS}.fetch_ticker', return_value={'ask': ask, 'bid': bid, 'last': last})
pair = "ETH/BTC"
log_msg = "Using cached exit rate for ETH/BTC."
# Test regular mode
exchange = get_patched_exchange(mocker, default_conf)
rate = exchange.get_rate(pair, side="exit", is_short=False, refresh=True)
assert not log_has("Using cached exit rate for ETH/BTC.", caplog)
assert not log_has(log_msg, caplog)
assert isinstance(rate, float)
assert rate == expected
# Use caching
rate = exchange.get_rate(pair, side="exit", is_short=False, refresh=False)
assert rate == expected
assert log_has("Using cached exit rate for ETH/BTC.", caplog)
caplog.clear()
assert exchange.get_rate(pair, side="exit", is_short=False, refresh=False) == expected
assert log_has(log_msg, caplog)
time_machine.move_to(start_dt + timedelta(minutes=4), tick=False)
# Caching still active - TTL didn't expire
caplog.clear()
assert exchange.get_rate(pair, side="exit", is_short=False, refresh=False) == expected
assert log_has(log_msg, caplog)
time_machine.move_to(start_dt + timedelta(minutes=6), tick=False)
# Caching expired - refresh forced
caplog.clear()
assert exchange.get_rate(pair, side="exit", is_short=False, refresh=False) == expected
assert not log_has(log_msg, caplog)
@pytest.mark.parametrize("entry,is_short,side,ask,bid,last,last_ab,expected", [
@@ -2619,9 +2677,9 @@ def test_get_exit_rate_exception(default_conf, mocker, is_short):
@pytest.mark.parametrize("side,ask,bid,last,last_ab,expected", get_entry_rate_data)
@pytest.mark.parametrize("side2", ['bid', 'ask'])
@pytest.mark.parametrize("use_order_book", [True, False])
def test_get_rates_testing_buy(mocker, default_conf, caplog, side, ask, bid,
last, last_ab, expected,
side2, use_order_book, order_book_l2) -> None:
def test_get_rates_testing_entry(mocker, default_conf, caplog, side, ask, bid,
last, last_ab, expected,
side2, use_order_book, order_book_l2) -> None:
caplog.set_level(logging.DEBUG)
if last_ab is None:
del default_conf['entry_pricing']['price_last_balance']
@@ -2655,10 +2713,10 @@ def test_get_rates_testing_buy(mocker, default_conf, caplog, side, ask, bid,
assert api_mock.fetch_ticker.call_count == 1
@pytest.mark.parametrize('side,ask,bid,last,last_ab,expected', get_sell_rate_data)
@pytest.mark.parametrize('side,ask,bid,last,last_ab,expected', get_exit_rate_data)
@pytest.mark.parametrize("side2", ['bid', 'ask'])
@pytest.mark.parametrize("use_order_book", [True, False])
def test_get_rates_testing_sell(default_conf, mocker, caplog, side, bid, ask,
def test_get_rates_testing_exit(default_conf, mocker, caplog, side, bid, ask,
last, last_ab, expected,
side2, use_order_book, order_book_l2) -> None:
caplog.set_level(logging.DEBUG)
@@ -2738,7 +2796,6 @@ async def test___async_get_candle_history_sort(default_conf, mocker, exchange_na
assert res_ohlcv[9][4] == 0.07668
assert res_ohlcv[9][5] == 16.65244264
# Bittrex use-case (real data from Bittrex)
# This OHLCV data is ordered ASC (oldest first, newest last)
ohlcv = [
[1527827700000, 0.07659999, 0.0766, 0.07627, 0.07657998, 1.85216924],
@@ -3165,7 +3222,7 @@ def test_cancel_stoploss_order_with_result(default_conf, mocker, exchange_name):
mocker.patch(f'{mock_prefix}.fetch_stoploss_order', side_effect=exc)
co = exchange.cancel_stoploss_order_with_result(order_id='_', pair='TKN/BTC', amount=555)
assert co['amount'] == 555
assert co == {'fee': {}, 'status': 'canceled', 'amount': 555, 'info': {}}
assert co == {'id': '_', 'fee': {}, 'status': 'canceled', 'amount': 555, 'info': {}}
with pytest.raises(InvalidOrderException):
exc = InvalidOrderException("Did not find order")
@@ -3382,7 +3439,7 @@ def test_get_fee(default_conf, mocker, exchange_name):
def test_stoploss_order_unsupported_exchange(default_conf, mocker):
exchange = get_patched_exchange(mocker, default_conf, id='bittrex')
exchange = get_patched_exchange(mocker, default_conf, id='bitpanda')
with pytest.raises(OperationalException, match=r"stoploss is not implemented .*"):
exchange.create_stoploss(
pair='ETH/BTC',
@@ -3578,10 +3635,10 @@ def test_ohlcv_candle_limit(default_conf, mocker, exchange_name):
timeframes = ('1m', '5m', '1h')
expected = exchange._ft_has['ohlcv_candle_limit']
for timeframe in timeframes:
if 'ohlcv_candle_limit_per_timeframe' in exchange._ft_has:
expected = exchange._ft_has['ohlcv_candle_limit_per_timeframe'][timeframe]
# This should only run for bittrex
assert exchange_name == 'bittrex'
# if 'ohlcv_candle_limit_per_timeframe' in exchange._ft_has:
# expected = exchange._ft_has['ohlcv_candle_limit_per_timeframe'][timeframe]
# This should only run for bittrex
# assert exchange_name == 'bittrex'
assert exchange.ohlcv_candle_limit(timeframe, CandleType.SPOT) == expected
@@ -3873,11 +3930,11 @@ def test_set_margin_mode(mocker, default_conf, margin_mode):
("kraken", TradingMode.SPOT, None, False),
("kraken", TradingMode.MARGIN, MarginMode.ISOLATED, True),
("kraken", TradingMode.FUTURES, MarginMode.ISOLATED, True),
("bittrex", TradingMode.SPOT, None, False),
("bittrex", TradingMode.MARGIN, MarginMode.CROSS, True),
("bittrex", TradingMode.MARGIN, MarginMode.ISOLATED, True),
("bittrex", TradingMode.FUTURES, MarginMode.CROSS, True),
("bittrex", TradingMode.FUTURES, MarginMode.ISOLATED, True),
("bitmart", TradingMode.SPOT, None, False),
("bitmart", TradingMode.MARGIN, MarginMode.CROSS, True),
("bitmart", TradingMode.MARGIN, MarginMode.ISOLATED, True),
("bitmart", TradingMode.FUTURES, MarginMode.CROSS, True),
("bitmart", TradingMode.FUTURES, MarginMode.ISOLATED, True),
("gate", TradingMode.MARGIN, MarginMode.ISOLATED, True),
("okx", TradingMode.SPOT, None, False),
("okx", TradingMode.MARGIN, MarginMode.CROSS, True),
@@ -4494,10 +4551,10 @@ def test_amount_to_contract_precision(
@pytest.mark.parametrize('exchange_name,open_rate,is_short,trading_mode,margin_mode', [
# Bittrex
('bittrex', 2.0, False, 'spot', None),
('bittrex', 2.0, False, 'spot', 'cross'),
('bittrex', 2.0, True, 'spot', 'isolated'),
# Bybit
('bybit', 2.0, False, 'spot', None),
('bybit', 2.0, False, 'spot', 'cross'),
('bybit', 2.0, True, 'spot', 'isolated'),
# Binance
('binance', 2.0, False, 'spot', None),
('binance', 2.0, False, 'spot', 'cross'),
@@ -4919,7 +4976,7 @@ def test_get_max_leverage_futures(default_conf, mocker, leverage_tiers):
exchange.get_max_leverage("BTC/USDT:USDT", 1000000000.01)
@pytest.mark.parametrize("exchange_name", ['bittrex', 'binance', 'kraken', 'gate', 'okx', 'bybit'])
@pytest.mark.parametrize("exchange_name", ['binance', 'kraken', 'gate', 'okx', 'bybit'])
def test__get_params(mocker, default_conf, exchange_name):
api_mock = MagicMock()
mocker.patch(f'{EXMS}.exchange_has', return_value=True)
tests/exchange/test_kraken.py
+9 -38
View File
@@ -13,11 +13,14 @@ STOPLOSS_ORDERTYPE = 'stop-loss'
STOPLOSS_LIMIT_ORDERTYPE = 'stop-loss-limit'
def test_buy_kraken_trading_agreement(default_conf, mocker):
@pytest.mark.parametrize("order_type,time_in_force,expected_params", [
('limit', 'ioc', {'timeInForce': 'IOC', 'trading_agreement': 'agree'}),
('limit', 'PO', {'postOnly': True, 'trading_agreement': 'agree'}),
('market', None, {'trading_agreement': 'agree'})
])
def test_kraken_trading_agreement(default_conf, mocker, order_type, time_in_force, expected_params):
api_mock = MagicMock()
order_id = f'test_prod_buy_{randint(0, 10 ** 6)}'
order_type = 'limit'
time_in_force = 'ioc'
order_id = f'test_prod_{order_type}_{randint(0, 10 ** 6)}'
api_mock.options = {}
api_mock.create_order = MagicMock(return_value={
'id': order_id,
@@ -49,41 +52,9 @@ def test_buy_kraken_trading_agreement(default_conf, mocker):
assert api_mock.create_order.call_args[0][1] == order_type
assert api_mock.create_order.call_args[0][2] == 'buy'
assert api_mock.create_order.call_args[0][3] == 1
assert api_mock.create_order.call_args[0][4] == 200
assert api_mock.create_order.call_args[0][5] == {'timeInForce': 'IOC',
'trading_agreement': 'agree'}
assert api_mock.create_order.call_args[0][4] == (200 if order_type == 'limit' else None)
def test_sell_kraken_trading_agreement(default_conf, mocker):
api_mock = MagicMock()
order_id = f'test_prod_sell_{randint(0, 10 ** 6)}'
order_type = 'market'
api_mock.options = {}
api_mock.create_order = MagicMock(return_value={
'id': order_id,
'symbol': 'ETH/BTC',
'info': {
'foo': 'bar'
}
})
default_conf['dry_run'] = False
mocker.patch(f'{EXMS}.amount_to_precision', lambda s, x, y: y)
mocker.patch(f'{EXMS}.price_to_precision', lambda s, x, y: y)
exchange = get_patched_exchange(mocker, default_conf, api_mock, id="kraken")
order = exchange.create_order(pair='ETH/BTC', ordertype=order_type,
side="sell", amount=1, rate=200, leverage=1.0)
assert 'id' in order
assert 'info' in order
assert order['id'] == order_id
assert api_mock.create_order.call_args[0][0] == 'ETH/BTC'
assert api_mock.create_order.call_args[0][1] == order_type
assert api_mock.create_order.call_args[0][2] == 'sell'
assert api_mock.create_order.call_args[0][3] == 1
assert api_mock.create_order.call_args[0][4] is None
assert api_mock.create_order.call_args[0][5] == {'trading_agreement': 'agree'}
assert api_mock.create_order.call_args[0][5] == expected_params
def test_get_balances_prod(default_conf, mocker):
tests/exchange_online/conftest.py
-8
View File
@@ -14,14 +14,6 @@ EXCHANGE_FIXTURE_TYPE = Tuple[Exchange, str]
# Exchanges that should be tested online
EXCHANGES = {
'bittrex': {
'pair': 'BTC/USDT',
'stake_currency': 'USDT',
'hasQuoteVolume': False,
'timeframe': '1h',
'leverage_tiers_public': False,
'leverage_in_spot_market': False,
},
'binance': {
'pair': 'BTC/USDT',
'stake_currency': 'USDT',
tests/exchange_online/test_ccxt_compat.py
-3
View File
@@ -218,9 +218,6 @@ class TestCCXTExchange:
def test_ccxt__async_get_candle_history(self, exchange: EXCHANGE_FIXTURE_TYPE):
exc, exchangename = exchange
if exchangename in ('bittrex'):
# For some weired reason, this test returns random lengths for bittrex.
pytest.skip("Exchange doesn't provide stable ohlcv history")
if not exc._ft_has['ohlcv_has_history']:
pytest.skip("Exchange does not support candle history")
tests/freqai/conftest.py
+16 -1
View File
@@ -20,6 +20,21 @@ def is_mac() -> bool:
return "Darwin" in machine
@pytest.fixture(autouse=True)
def patch_torch_initlogs(mocker) -> None:
if is_mac():
# Mock torch import completely
import sys
import types
module_name = 'torch'
mocked_module = types.ModuleType(module_name)
sys.modules[module_name] = mocked_module
else:
mocker.patch("torch._logging._init_logs")
@pytest.fixture(scope="function")
def freqai_conf(default_conf, tmp_path):
freqaiconf = deepcopy(default_conf)
@@ -39,7 +54,7 @@ def freqai_conf(default_conf, tmp_path):
"backtest_period_days": 10,
"live_retrain_hours": 0,
"expiration_hours": 1,
"identifier": "uniqe-id100",
"identifier": "unique-id100",
"live_trained_timestamp": 0,
"data_kitchen_thread_count": 2,
"activate_tensorboard": False,
tests/freqai/test_freqai_backtesting.py
+55 -4
View File
@@ -6,11 +6,17 @@ from unittest.mock import PropertyMock
import pytest
from freqtrade.commands.optimize_commands import setup_optimize_configuration
from freqtrade.configuration.timerange import TimeRange
from freqtrade.data import history
from freqtrade.data.dataprovider import DataProvider
from freqtrade.enums import RunMode
from freqtrade.enums.candletype import CandleType
from freqtrade.exceptions import OperationalException
from freqtrade.freqai.data_kitchen import FreqaiDataKitchen
from freqtrade.optimize.backtesting import Backtesting
from tests.conftest import (CURRENT_TEST_STRATEGY, get_args, log_has_re, patch_exchange,
patched_configuration_load_config_file)
from tests.conftest import (CURRENT_TEST_STRATEGY, get_args, get_patched_exchange, log_has_re,
patch_exchange, patched_configuration_load_config_file)
from tests.freqai.conftest import get_patched_freqai_strategy
def test_freqai_backtest_start_backtest_list(freqai_conf, mocker, testdatadir, caplog):
@@ -40,7 +46,16 @@ def test_freqai_backtest_start_backtest_list(freqai_conf, mocker, testdatadir, c
Backtesting.cleanup()
def test_freqai_backtest_load_data(freqai_conf, mocker, caplog):
@pytest.mark.parametrize(
"timeframe, expected_startup_candle_count",
[
("5m", 876),
("15m", 492),
("1d", 302),
],
)
def test_freqai_backtest_load_data(freqai_conf, mocker, caplog,
timeframe, expected_startup_candle_count):
patch_exchange(mocker)
now = datetime.now(timezone.utc)
@@ -48,10 +63,14 @@ def test_freqai_backtest_load_data(freqai_conf, mocker, caplog):
PropertyMock(return_value=['HULUMULU/USDT', 'XRP/USDT']))
mocker.patch('freqtrade.optimize.backtesting.history.load_data')
mocker.patch('freqtrade.optimize.backtesting.history.get_timerange', return_value=(now, now))
freqai_conf['timeframe'] = timeframe
freqai_conf.get('freqai', {}).get('feature_parameters', {}).update({'include_timeframes': []})
backtesting = Backtesting(deepcopy(freqai_conf))
backtesting.load_bt_data()
assert log_has_re('Increasing startup_candle_count for freqai to.*', caplog)
assert log_has_re(f'Increasing startup_candle_count for freqai on {timeframe} '
f'to {expected_startup_candle_count}', caplog)
assert history.load_data.call_args[1]['startup_candles'] == expected_startup_candle_count
Backtesting.cleanup()
@@ -85,3 +104,35 @@ def test_freqai_backtest_live_models_model_not_found(freqai_conf, mocker, testda
Backtesting(bt_config)
Backtesting.cleanup()
def test_freqai_backtest_consistent_timerange(mocker, freqai_conf):
freqai_conf['runmode'] = 'backtest'
mocker.patch('freqtrade.plugins.pairlistmanager.PairListManager.whitelist',
PropertyMock(return_value=['XRP/USDT:USDT']))
gbs = mocker.patch('freqtrade.optimize.backtesting.generate_backtest_stats')
freqai_conf['candle_type_def'] = CandleType.FUTURES
freqai_conf.get('exchange', {}).update({'pair_whitelist': ['XRP/USDT:USDT']})
freqai_conf.get('freqai', {}).get('feature_parameters', {}).update(
{'include_timeframes': ['5m', '1h'], 'include_corr_pairlist': []})
freqai_conf['timerange'] = '20211120-20211121'
strategy = get_patched_freqai_strategy(mocker, freqai_conf)
exchange = get_patched_exchange(mocker, freqai_conf)
strategy.dp = DataProvider(freqai_conf, exchange)
strategy.freqai_info = freqai_conf.get("freqai", {})
freqai = strategy.freqai
freqai.dk = FreqaiDataKitchen(freqai_conf)
timerange = TimeRange.parse_timerange("20211115-20211122")
freqai.dd.load_all_pair_histories(timerange, freqai.dk)
backtesting = Backtesting(deepcopy(freqai_conf))
backtesting.start()
gbs.call_args[1]['min_date'] == datetime(2021, 11, 20, 0, 0, tzinfo=timezone.utc)
gbs.call_args[1]['max_date'] == datetime(2021, 11, 21, 0, 0, tzinfo=timezone.utc)
Backtesting.cleanup()
tests/freqai/test_freqai_datadrawer.py
+1
View File
@@ -15,6 +15,7 @@ from tests.freqai.conftest import get_patched_freqai_strategy
def test_update_historic_data(mocker, freqai_conf):
freqai_conf['runmode'] = 'backtest'
strategy = get_patched_freqai_strategy(mocker, freqai_conf)
exchange = get_patched_exchange(mocker, freqai_conf)
strategy.dp = DataProvider(freqai_conf, exchange)
tests/freqai/test_freqai_datakitchen.py
+63 -2
View File
@@ -3,6 +3,7 @@ from datetime import datetime, timedelta, timezone
from pathlib import Path
from unittest.mock import MagicMock
import pandas as pd
import pytest
from freqtrade.configuration import TimeRange
@@ -10,9 +11,8 @@ from freqtrade.data.dataprovider import DataProvider
from freqtrade.exceptions import OperationalException
from freqtrade.freqai.data_kitchen import FreqaiDataKitchen
from tests.conftest import get_patched_exchange
from tests.freqai.conftest import (get_patched_data_kitchen, get_patched_freqai_strategy,
from tests.freqai.conftest import (get_patched_data_kitchen, get_patched_freqai_strategy, is_mac,
make_unfiltered_dataframe)
from tests.freqai.test_freqai_interface import is_mac
@pytest.mark.parametrize(
@@ -136,3 +136,64 @@ def test_get_full_model_path(mocker, freqai_conf, model):
model_path = freqai.dk.get_full_models_path(freqai_conf)
assert model_path.is_dir() is True
def test_get_pair_data_for_features_with_prealoaded_data(mocker, freqai_conf):
strategy = get_patched_freqai_strategy(mocker, freqai_conf)
exchange = get_patched_exchange(mocker, freqai_conf)
strategy.dp = DataProvider(freqai_conf, exchange)
strategy.freqai_info = freqai_conf.get("freqai", {})
freqai = strategy.freqai
freqai.dk = FreqaiDataKitchen(freqai_conf)
timerange = TimeRange.parse_timerange("20180110-20180130")
freqai.dd.load_all_pair_histories(timerange, freqai.dk)
_, base_df = freqai.dd.get_base_and_corr_dataframes(timerange, "LTC/BTC", freqai.dk)
df = freqai.dk.get_pair_data_for_features("LTC/BTC", "5m", strategy, base_dataframes=base_df)
assert df is base_df["5m"]
assert not df.empty
def test_get_pair_data_for_features_without_preloaded_data(mocker, freqai_conf):
freqai_conf.update({"timerange": "20180115-20180130"})
freqai_conf['runmode'] = 'backtest'
strategy = get_patched_freqai_strategy(mocker, freqai_conf)
exchange = get_patched_exchange(mocker, freqai_conf)
strategy.dp = DataProvider(freqai_conf, exchange)
strategy.freqai_info = freqai_conf.get("freqai", {})
freqai = strategy.freqai
freqai.dk = FreqaiDataKitchen(freqai_conf)
timerange = TimeRange.parse_timerange("20180110-20180130")
freqai.dd.load_all_pair_histories(timerange, freqai.dk)
base_df = {'5m': pd.DataFrame()}
df = freqai.dk.get_pair_data_for_features("LTC/BTC", "5m", strategy, base_dataframes=base_df)
assert df is not base_df["5m"]
assert not df.empty
assert df.iloc[0]['date'].strftime("%Y-%m-%d %H:%M:%S") == "2018-01-11 23:00:00"
assert df.iloc[-1]['date'].strftime("%Y-%m-%d %H:%M:%S") == "2018-01-30 00:00:00"
def test_populate_features(mocker, freqai_conf):
strategy = get_patched_freqai_strategy(mocker, freqai_conf)
exchange = get_patched_exchange(mocker, freqai_conf)
strategy.dp = DataProvider(freqai_conf, exchange)
strategy.freqai_info = freqai_conf.get("freqai", {})
freqai = strategy.freqai
freqai.dk = FreqaiDataKitchen(freqai_conf)
timerange = TimeRange.parse_timerange("20180115-20180130")
freqai.dd.load_all_pair_histories(timerange, freqai.dk)
corr_df, base_df = freqai.dd.get_base_and_corr_dataframes(timerange, "LTC/BTC", freqai.dk)
mocker.patch.object(strategy, 'feature_engineering_expand_all', return_value=base_df["5m"])
df = freqai.dk.populate_features(base_df["5m"], "LTC/BTC", strategy,
base_dataframes=base_df, corr_dataframes=corr_df)
strategy.feature_engineering_expand_all.assert_called_once()
pd.testing.assert_frame_equal(base_df["5m"],
strategy.feature_engineering_expand_all.call_args[0][0])
assert df.iloc[0]['date'].strftime("%Y-%m-%d %H:%M:%S") == "2018-01-15 00:00:00"
tests/freqai/test_freqai_interface.py
+12 -6
View File
@@ -20,8 +20,8 @@ from tests.freqai.conftest import (get_patched_freqai_strategy, is_mac, make_rl_
mock_pytorch_mlp_model_training_parameters)
def is_py11() -> bool:
return sys.version_info >= (3, 11)
def is_py12() -> bool:
return sys.version_info >= (3, 12)
def is_arm() -> bool:
@@ -176,6 +176,7 @@ def test_extract_data_and_train_model_MultiTargets(mocker, freqai_conf, model, s
'CatboostClassifier',
'XGBoostClassifier',
'XGBoostRFClassifier',
'SKLearnRandomForestClassifier',
'PyTorchMLPClassifier',
])
def test_extract_data_and_train_model_Classifiers(mocker, freqai_conf, model):
@@ -298,8 +299,11 @@ def test_start_backtesting(mocker, freqai_conf, model, num_files, strat, caplog)
def test_start_backtesting_subdaily_backtest_period(mocker, freqai_conf):
freqai_conf.update({"timerange": "20180120-20180124"})
freqai_conf.get("freqai", {}).update({"backtest_period_days": 0.5})
freqai_conf.get("freqai", {}).update({"save_backtest_models": True})
freqai_conf['runmode'] = 'backtest'
freqai_conf.get("freqai", {}).update({
"backtest_period_days": 0.5,
"save_backtest_models": True,
})
freqai_conf.get("freqai", {}).get("feature_parameters", {}).update(
{"indicator_periods_candles": [2]})
strategy = get_patched_freqai_strategy(mocker, freqai_conf)
@@ -326,6 +330,7 @@ def test_start_backtesting_subdaily_backtest_period(mocker, freqai_conf):
def test_start_backtesting_from_existing_folder(mocker, freqai_conf, caplog):
freqai_conf.update({"timerange": "20180120-20180130"})
freqai_conf['runmode'] = 'backtest'
freqai_conf.get("freqai", {}).update({"save_backtest_models": True})
freqai_conf.get("freqai", {}).get("feature_parameters", {}).update(
{"indicator_periods_candles": [2]})
@@ -389,6 +394,7 @@ def test_start_backtesting_from_existing_folder(mocker, freqai_conf, caplog):
def test_backtesting_fit_live_predictions(mocker, freqai_conf, caplog):
freqai_conf['runmode'] = 'backtest'
freqai_conf.get("freqai", {}).update({"fit_live_predictions_candles": 10})
strategy = get_patched_freqai_strategy(mocker, freqai_conf)
exchange = get_patched_exchange(mocker, freqai_conf)
@@ -522,8 +528,8 @@ def test_get_state_info(mocker, freqai_conf, dp_exists, caplog, tickers):
if is_mac():
pytest.skip("Reinforcement learning module not available on intel based Mac OS")
if is_py11():
pytest.skip("Reinforcement learning currently not available on python 3.11.")
if is_py12():
pytest.skip("Reinforcement learning currently not available on python 3.12.")
freqai_conf.update({"freqaimodel": "ReinforcementLearner"})
freqai_conf.update({"timerange": "20180110-20180130"})
tests/optimize/test_backtesting.py
+33 -8
View File
@@ -549,6 +549,7 @@ def test_backtest__enter_trade_futures(default_conf_usdt, fee, mocker) -> None:
default_conf_usdt['exchange']['pair_whitelist'] = ['.*']
backtesting = Backtesting(default_conf_usdt)
backtesting._set_strategy(backtesting.strategylist[0])
mocker.patch('freqtrade.optimize.backtesting.Backtesting._run_funding_fees')
pair = 'ETH/USDT:USDT'
row = [
pd.Timestamp(year=2020, month=1, day=1, hour=5, minute=0),
@@ -851,9 +852,13 @@ def test_backtest_one_detail(default_conf_usdt, fee, mocker, testdatadir, use_de
assert late_entry > 0
@pytest.mark.parametrize('use_detail', [True, False])
@pytest.mark.parametrize('use_detail,exp_funding_fee, exp_ff_updates', [
(True, -0.018054162, 11),
(False, -0.01780296, 5),
])
def test_backtest_one_detail_futures(
default_conf_usdt, fee, mocker, testdatadir, use_detail) -> None:
default_conf_usdt, fee, mocker, testdatadir, use_detail, exp_funding_fee,
exp_ff_updates) -> None:
default_conf_usdt['use_exit_signal'] = False
default_conf_usdt['trading_mode'] = 'futures'
default_conf_usdt['margin_mode'] = 'isolated'
@@ -882,6 +887,8 @@ def test_backtest_one_detail_futures(
default_conf_usdt['max_open_trades'] = 10
backtesting = Backtesting(default_conf_usdt)
ff_spy = mocker.spy(backtesting.exchange, 'calculate_funding_fees')
backtesting._set_strategy(backtesting.strategylist[0])
backtesting.strategy.populate_entry_trend = advise_entry
backtesting.strategy.custom_entry_price = custom_entry_price
@@ -936,13 +943,22 @@ def test_backtest_one_detail_futures(
assert (round(ln2.iloc[0]["low"], 6) <= round(
t["close_rate"], 6) <= round(ln2.iloc[0]["high"], 6))
assert -0.0181 < Trade.trades[1].funding_fees < -0.01
assert pytest.approx(Trade.trades[1].funding_fees) == exp_funding_fee
assert ff_spy.call_count == exp_ff_updates
# assert late_entry > 0
@pytest.mark.parametrize('use_detail', [True, False])
@pytest.mark.parametrize('use_detail,entries,max_stake,ff_updates,expected_ff', [
(True, 50, 3000, 54, -1.18038144),
(False, 6, 360, 10, -0.14679994),
])
def test_backtest_one_detail_futures_funding_fees(
default_conf_usdt, fee, mocker, testdatadir, use_detail) -> None:
default_conf_usdt, fee, mocker, testdatadir, use_detail, entries, max_stake,
ff_updates, expected_ff,
) -> None:
"""
Funding fees are expected to differ, as the maximum position size differs.
"""
default_conf_usdt['use_exit_signal'] = False
default_conf_usdt['trading_mode'] = 'futures'
default_conf_usdt['margin_mode'] = 'isolated'
@@ -975,6 +991,7 @@ def test_backtest_one_detail_futures_funding_fees(
default_conf_usdt['max_open_trades'] = 1
backtesting = Backtesting(default_conf_usdt)
ff_spy = mocker.spy(backtesting.exchange, 'calculate_funding_fees')
backtesting._set_strategy(backtesting.strategylist[0])
backtesting.strategy.populate_entry_trend = advise_entry
backtesting.strategy.adjust_trade_position = adjust_trade_position
@@ -1000,13 +1017,18 @@ def test_backtest_one_detail_futures_funding_fees(
assert len(results) == 1
assert 'orders' in results.columns
# funding_fees have been calculated for each funding-fee candle
# the trade is open for 26 hours - hence we expect the 8h fee to apply 4 times.
# Additional counts will happen due each successful entry, which needs to call this, too.
assert ff_spy.call_count == ff_updates
for t in Trade.trades:
# At least 4 adjustment orders
assert t.nr_of_successful_entries >= 6
# At least 6 adjustment orders
assert t.nr_of_successful_entries == entries
# Funding fees will vary depending on the number of adjustment orders
# That number is a lot higher with detail data.
assert -1.81 < t.funding_fees < -0.1
assert t.max_stake_amount == max_stake
assert pytest.approx(t.funding_fees) == expected_ff
def test_backtest_timedout_entry_orders(default_conf, fee, mocker, testdatadir) -> None:
@@ -1110,6 +1132,7 @@ def test_processed(default_conf, mocker, testdatadir) -> None:
def test_backtest_dataprovider_analyzed_df(default_conf, fee, mocker, testdatadir) -> None:
default_conf['use_exit_signal'] = False
default_conf['max_open_trades'] = 10
default_conf['runmode'] = 'backtest'
mocker.patch(f'{EXMS}.get_fee', fee)
mocker.patch(f"{EXMS}.get_min_pair_stake_amount", return_value=0.00001)
mocker.patch(f"{EXMS}.get_max_pair_stake_amount", return_value=100000)
@@ -1276,6 +1299,7 @@ def test_backtest_alternate_buy_sell(default_conf, fee, mocker, testdatadir):
mocker.patch(f"{EXMS}.get_max_pair_stake_amount", return_value=float('inf'))
mocker.patch(f'{EXMS}.get_fee', fee)
default_conf['max_open_trades'] = 10
default_conf['runmode'] = 'backtest'
backtest_conf = _make_backtest_conf(mocker, conf=default_conf,
pair='UNITTEST/BTC', datadir=testdatadir)
default_conf['timeframe'] = '1m'
@@ -1320,6 +1344,7 @@ def test_backtest_multi_pair(default_conf, fee, mocker, tres, pair, testdatadir)
dataframe['exit_short'] = 0
return dataframe
default_conf['runmode'] = 'backtest'
mocker.patch(f"{EXMS}.get_min_pair_stake_amount", return_value=0.00001)
mocker.patch(f"{EXMS}.get_max_pair_stake_amount", return_value=float('inf'))
mocker.patch(f'{EXMS}.get_fee', fee)
tests/optimize/test_backtesting_adjust_position.py
+1
View File
@@ -104,6 +104,7 @@ def test_backtest_position_adjustment_detailed(default_conf, fee, mocker, levera
mocker.patch(f"{EXMS}.get_max_pair_stake_amount", return_value=float('inf'))
mocker.patch(f"{EXMS}.get_max_leverage", return_value=10)
mocker.patch(f"{EXMS}.get_maintenance_ratio_and_amt", return_value=(0.1, 0.1))
mocker.patch('freqtrade.optimize.backtesting.Backtesting._run_funding_fees')
patch_exchange(mocker)
default_conf.update({
tests/rpc/test_rpc.py
+14 -4
View File
@@ -9,7 +9,7 @@ from sqlalchemy import select
from freqtrade.edge import PairInfo
from freqtrade.enums import SignalDirection, State, TradingMode
from freqtrade.exceptions import ExchangeError, InvalidOrderException, TemporaryError
from freqtrade.persistence import Trade
from freqtrade.persistence import Order, Trade
from freqtrade.persistence.pairlock_middleware import PairLocks
from freqtrade.rpc import RPC, RPCException
from freqtrade.rpc.fiat_convert import CryptoToFiatConverter
@@ -355,8 +355,18 @@ def test_rpc_delete_trade(mocker, default_conf, fee, markets, caplog, is_short):
rpc._rpc_delete('200')
trades = Trade.session.scalars(select(Trade)).all()
trades[1].stoploss_order_id = '1234'
trades[2].stoploss_order_id = '1234'
trades[2].stoploss_order_id = '102'
trades[2].orders.append(
Order(
ft_order_side='stoploss',
ft_pair=trades[2].pair,
ft_is_open=True,
ft_amount=trades[2].amount,
ft_price=trades[2].stop_loss,
order_id='102',
status='open',
)
)
assert len(trades) > 2
res = rpc._rpc_delete('1')
@@ -369,7 +379,7 @@ def test_rpc_delete_trade(mocker, default_conf, fee, markets, caplog, is_short):
cancel_mock.reset_mock()
stoploss_mock.reset_mock()
res = rpc._rpc_delete('2')
res = rpc._rpc_delete('5')
assert isinstance(res, dict)
assert stoploss_mock.call_count == 1
assert res['cancel_order_count'] == 1
tests/rpc/test_rpc_apiserver.py
+4 -3
View File
@@ -728,7 +728,6 @@ def test_api_delete_trade(botclient, mocker, fee, markets, is_short):
ftbot.strategy.order_types['stoploss_on_exchange'] = True
trades = Trade.session.scalars(select(Trade)).all()
trades[1].stoploss_order_id = '1234'
Trade.commit()
assert len(trades) > 2
@@ -745,9 +744,9 @@ def test_api_delete_trade(botclient, mocker, fee, markets, is_short):
assert cancel_mock.call_count == 0
assert len(trades) - 1 == len(Trade.session.scalars(select(Trade)).all())
rc = client_delete(client, f"{BASE_URI}/trades/2")
rc = client_delete(client, f"{BASE_URI}/trades/5")
assert_response(rc)
assert rc.json()['result_msg'] == 'Deleted trade 2. Closed 1 open orders.'
assert rc.json()['result_msg'] == 'Deleted trade 5. Closed 1 open orders.'
assert len(trades) - 2 == len(Trade.session.scalars(select(Trade)).all())
assert stoploss_mock.call_count == 1
@@ -1770,6 +1769,7 @@ def test_api_freqaimodels(botclient, tmp_path, mocker):
{'name': 'LightGBMRegressorMultiTarget'},
{'name': 'ReinforcementLearner'},
{'name': 'ReinforcementLearner_multiproc'},
{'name': 'SKlearnRandomForestClassifier'},
{'name': 'XGBoostClassifier'},
{'name': 'XGBoostRFClassifier'},
{'name': 'XGBoostRFRegressor'},
@@ -1788,6 +1788,7 @@ def test_api_freqaimodels(botclient, tmp_path, mocker):
'LightGBMRegressorMultiTarget',
'ReinforcementLearner',
'ReinforcementLearner_multiproc',
'SKlearnRandomForestClassifier',
'XGBoostClassifier',
'XGBoostRFClassifier',
'XGBoostRFRegressor',

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