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Merge branch 'develop' into fix/tz-naive-predictions

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Matthias
2025-10-24 07:04:52 +02:00
parent a4c82a95a0 bf7fc79519
commit dccd0dcb9e
194 changed files with 24097 additions and 12425 deletions
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3
.dockerignore
View File

@@ -14,10 +14,11 @@ MANIFEST.in
README.md
freqtrade.service
freqtrade.egg-info
.venv/
config.json*
*.sqlite
user_data
user_data/
*.log
.vscode

92
.github/actions/docker-tags/action.yml vendored Normal file
View File

@@ -0,0 +1,92 @@
name: 'docker-tags'
description: 'Set Docker default Tag environment variables'
# inputs:
outputs:
BRANCH_NAME:
description: 'The branch name'
value: ${{ steps.tags.outputs.BRANCH_NAME }}
TAG:
description: 'The Docker tag'
value: ${{ steps.tags.outputs.TAG }}
TAG_PLOT:
description: 'The Docker tag for the plot'
value: ${{ steps.tags.outputs.TAG_PLOT }}
TAG_FREQAI:
description: 'The Docker tag for the freqai'
value: ${{ steps.tags.outputs.TAG_FREQAI }}
TAG_FREQAI_RL:
description: 'The Docker tag for the freqai_rl'
value: ${{ steps.tags.outputs.TAG_FREQAI_RL }}
TAG_FREQAI_TORCH:
description: 'The Docker tag for the freqai_torch'
value: ${{ steps.tags.outputs.TAG_FREQAI_TORCH }}
TAG_ARM:
description: 'The Docker tag for the arm'
value: ${{ steps.tags.outputs.TAG_ARM }}
TAG_PLOT_ARM:
description: 'The Docker tag for the plot arm'
value: ${{ steps.tags.outputs.TAG_PLOT_ARM }}
TAG_FREQAI_ARM:
description: 'The Docker tag for the freqai arm'
value: ${{ steps.tags.outputs.TAG_FREQAI_ARM }}
TAG_FREQAI_RL_ARM:
description: 'The Docker tag for the freqai_rl arm'
value: ${{ steps.tags.outputs.TAG_FREQAI_RL_ARM }}
TAG_PI:
description: 'The Docker tag for the pi'
value: ${{ steps.tags.outputs.TAG_PI }}
CACHE_TAG_PI:
description: 'The Docker cache tag for the pi'
value: ${{ steps.tags.outputs.CACHE_TAG_PI }}
runs:
using: "composite"
steps:
- name: Extract branch name
shell: bash
id: tags
env:
BRANCH_NAME_INPUT: ${{ github.event.inputs.branch_name }}
run: |
if [ "${{ github.event_name }}" = "workflow_dispatch" ]; then
BRANCH_NAME="${BRANCH_NAME_INPUT}"
else
BRANCH_NAME="${GITHUB_REF##*/}"
fi
# Replace / with _ to create a valid tag
TAG=$(echo "${BRANCH_NAME}" | sed -e "s/\//_/g")
TAG_PLOT=${TAG}_plot
TAG_FREQAI=${TAG}_freqai
TAG_FREQAI_RL=${TAG_FREQAI}rl
TAG_FREQAI_TORCH=${TAG_FREQAI}torch
TAG_ARM=${TAG}_arm
TAG_PLOT_ARM=${TAG_PLOT}_arm
TAG_FREQAI_ARM=${TAG_FREQAI}_arm
TAG_FREQAI_RL_ARM=${TAG_FREQAI_RL}_arm
TAG_PI="${TAG}_pi"
CACHE_TAG_PI=${CACHE_IMAGE}:${TAG_PI}_cache
echo "BRANCH_NAME=${BRANCH_NAME}" >> "$GITHUB_OUTPUT"
echo "TAG=${TAG}" >> "$GITHUB_OUTPUT"
echo "TAG_PLOT=${TAG_PLOT}" >> "$GITHUB_OUTPUT"
echo "TAG_FREQAI=${TAG_FREQAI}" >> "$GITHUB_OUTPUT"
echo "TAG_FREQAI_RL=${TAG_FREQAI_RL}" >> "$GITHUB_OUTPUT"
echo "TAG_FREQAI_TORCH=${TAG_FREQAI_TORCH}" >> "$GITHUB_OUTPUT"
echo "TAG_ARM=${TAG_ARM}" >> "$GITHUB_OUTPUT"
echo "TAG_PLOT_ARM=${TAG_PLOT_ARM}" >> "$GITHUB_OUTPUT"
echo "TAG_FREQAI_ARM=${TAG_FREQAI_ARM}" >> "$GITHUB_OUTPUT"
echo "TAG_FREQAI_RL_ARM=${TAG_FREQAI_RL_ARM}" >> "$GITHUB_OUTPUT"
echo "TAG_PI=${TAG_PI}" >> "$GITHUB_OUTPUT"
echo "CACHE_TAG_PI=${CACHE_TAG_PI}" >> "$GITHUB_OUTPUT"
cat "$GITHUB_OUTPUT"
- name: Save commit SHA to file
shell: bash
# Add commit to docker container
run: |
echo "${GITHUB_SHA}" > freqtrade_commit

16
.github/dependabot.yml vendored
View File

@@ -1,6 +1,8 @@
version: 2
updates:
- package-ecosystem: docker
cooldown:
default-days: 4
directories:
- "/"
- "/docker"
@@ -11,8 +13,20 @@ updates:
update-types: ["version-update:semver-major"]
open-pull-requests-limit: 10
- package-ecosystem: devcontainers
directory: "/"
cooldown:
default-days: 4
schedule:
interval: daily
open-pull-requests-limit: 10
- package-ecosystem: pip
directory: "/"
cooldown:
default-days: 4
exclude:
- ccxt
schedule:
interval: weekly
time: "03:00"
@@ -36,6 +50,8 @@ updates:
- package-ecosystem: "github-actions"
directory: "/"
cooldown:
default-days: 4
schedule:
interval: "weekly"
open-pull-requests-limit: 10

4
.github/workflows/binance-lev-tier-update.yml vendored
View File

@@ -15,11 +15,11 @@ jobs:
environment:
name: develop
steps:
- uses: actions/checkout@v4
- uses: actions/checkout@v5
with:
persist-credentials: false
- uses: actions/setup-python@v5
- uses: actions/setup-python@v6
with:
python-version: "3.12"

367
.github/workflows/ci.yml vendored
View File

@@ -19,52 +19,43 @@ concurrency:
permissions:
repository-projects: read
jobs:
build-linux:
tests:
name: "Tests and Linting"
runs-on: ${{ matrix.os }}
strategy:
matrix:
os: [ "ubuntu-22.04", "ubuntu-24.04" ]
os: [ "ubuntu-22.04", "ubuntu-24.04", "macos-14", "macos-15" , "windows-2022", "windows-2025" ]
python-version: ["3.11", "3.12", "3.13"]
steps:
- uses: actions/checkout@v4
- uses: actions/checkout@v5
with:
persist-credentials: false
- name: Set up Python
uses: actions/setup-python@v5
uses: actions/setup-python@v6
with:
python-version: ${{ matrix.python-version }}
- name: Install uv
uses: astral-sh/setup-uv@e92bafb6253dcd438e0484186d7669ea7a8ca1cc # v6.4.3
uses: astral-sh/setup-uv@3259c6206f993105e3a61b142c2d97bf4b9ef83d # v7.1.0
with:
activate-environment: true
enable-cache: true
python-version: ${{ matrix.python-version }}
cache-dependency-glob: "requirements**.txt"
cache-suffix: "${{ matrix.python-version }}"
prune-cache: false
- name: Cache_dependencies
uses: actions/cache@v4
id: cache
with:
path: ~/dependencies/
key: ${{ runner.os }}-dependencies
- name: TA binary *nix
if: steps.cache.outputs.cache-hit != 'true'
- name: Installation - macOS (Brew)
if: ${{ runner.os == 'macOS' }}
run: |
cd build_helpers && ./install_ta-lib.sh ${HOME}/dependencies/; cd ..
# brew update
# TODO: Should be the brew upgrade
brew install libomp
- name: Installation - *nix
- name: Installation (python)
run: |
uv pip install --upgrade wheel
export LD_LIBRARY_PATH=${HOME}/dependencies/lib:$LD_LIBRARY_PATH
export TA_LIBRARY_PATH=${HOME}/dependencies/lib
export TA_INCLUDE_PATH=${HOME}/dependencies/include
uv pip install -r requirements-dev.txt
uv pip install -e ft_client/
uv pip install -e .
@@ -76,7 +67,7 @@ jobs:
- name: Tests
if: (!(runner.os == 'Linux' && matrix.python-version == '3.12' && matrix.os == 'ubuntu-24.04'))
run: |
pytest --random-order
pytest --random-order --durations 20 -n auto
- name: Tests with Coveralls
if: (runner.os == 'Linux' && matrix.python-version == '3.12' && matrix.os == 'ubuntu-24.04')
@@ -103,9 +94,9 @@ jobs:
run: |
python build_helpers/create_command_partials.py
- name: Check for repository changes
- name: Check for repository changes - *nix
# TODO: python 3.13 slightly changed the output of argparse.
if: (matrix.python-version != '3.13')
if: ${{ (matrix.python-version != '3.13') && (runner.os != 'Windows') }}
run: |
if [ -n "$(git status --porcelain)" ]; then
echo "Repository is dirty, changes detected:"
@@ -116,13 +107,27 @@ jobs:
echo "Repository is clean, no changes detected."
fi
- name: Check for repository changes - Windows
if: ${{ runner.os == 'Windows' && (matrix.python-version != '3.13') }}
run: |
if (git status --porcelain) {
Write-Host "Repository is dirty, changes detected:"
git status
git diff
exit 1
}
else {
Write-Host "Repository is clean, no changes detected."
}
- name: Backtesting (multi)
run: |
cp tests/testdata/config.tests.json config.json
freqtrade create-userdir --userdir user_data
cp tests/testdata/config.tests.json user_data/config.json
freqtrade new-strategy -s AwesomeStrategy
freqtrade new-strategy -s AwesomeStrategyMin --template minimal
freqtrade backtesting --datadir tests/testdata --strategy-list AwesomeStrategy AwesomeStrategyMin -i 5m
freqtrade new-strategy -s AwesomeStrategyAdv --template advanced
freqtrade backtesting --datadir tests/testdata --strategy-list AwesomeStrategy AwesomeStrategyMin AwesomeStrategyAdv -i 5m
- name: Hyperopt
run: |
@@ -143,221 +148,13 @@ jobs:
ruff format --check
- name: Mypy
if: matrix.os == 'ubuntu-24.04'
run: |
mypy freqtrade scripts tests
- name: Discord notification
uses: rjstone/discord-webhook-notify@c2597273488aeda841dd1e891321952b51f7996f #v2.2.1
if: failure() && ( github.event_name != 'pull_request' || github.event.pull_request.head.repo.fork == false)
with:
severity: error
details: Freqtrade CI failed on ${{ matrix.os }}
webhookUrl: ${{ secrets.DISCORD_WEBHOOK }}
build-macos:
runs-on: ${{ matrix.os }}
strategy:
matrix:
os: [ "macos-14", "macos-15" ]
python-version: ["3.11", "3.12", "3.13"]
steps:
- uses: actions/checkout@v4
with:
persist-credentials: false
- name: Set up Python
uses: actions/setup-python@v5
with:
python-version: ${{ matrix.python-version }}
check-latest: true
- name: Install uv
uses: astral-sh/setup-uv@e92bafb6253dcd438e0484186d7669ea7a8ca1cc # v6.4.3
with:
activate-environment: true
enable-cache: true
python-version: ${{ matrix.python-version }}
cache-dependency-glob: "requirements**.txt"
cache-suffix: "${{ matrix.python-version }}"
prune-cache: false
- name: Cache_dependencies
uses: actions/cache@v4
id: cache
with:
path: ~/dependencies/
key: ${{ matrix.os }}-dependencies
- name: TA binary *nix
if: steps.cache.outputs.cache-hit != 'true'
run: |
cd build_helpers && ./install_ta-lib.sh ${HOME}/dependencies/; cd ..
- name: Installation - macOS (Brew)
run: |
# brew update
# TODO: Should be the brew upgrade
# homebrew fails to update python due to unlinking failures
# https://github.com/actions/runner-images/issues/6817
rm /usr/local/bin/2to3 || true
rm /usr/local/bin/2to3-3.11 || true
rm /usr/local/bin/2to3-3.12 || true
rm /usr/local/bin/idle3 || true
rm /usr/local/bin/idle3.11 || true
rm /usr/local/bin/idle3.12 || true
rm /usr/local/bin/pydoc3 || true
rm /usr/local/bin/pydoc3.11 || true
rm /usr/local/bin/pydoc3.12 || true
rm /usr/local/bin/python3 || true
rm /usr/local/bin/python3.11 || true
rm /usr/local/bin/python3.12 || true
rm /usr/local/bin/python3-config || true
rm /usr/local/bin/python3.11-config || true
rm /usr/local/bin/python3.12-config || true
brew install libomp
- name: Installation (python)
run: |
uv pip install wheel
export LD_LIBRARY_PATH=${HOME}/dependencies/lib:$LD_LIBRARY_PATH
export TA_LIBRARY_PATH=${HOME}/dependencies/lib
export TA_INCLUDE_PATH=${HOME}/dependencies/include
uv pip install -r requirements-dev.txt
uv pip install -e ft_client/
uv pip install -e .
- name: Tests
run: |
pytest --random-order
- name: Check for repository changes
run: |
if [ -n "$(git status --porcelain)" ]; then
echo "Repository is dirty, changes detected:"
git status
git diff
exit 1
else
echo "Repository is clean, no changes detected."
fi
- name: Backtesting
run: |
cp tests/testdata/config.tests.json config.json
freqtrade create-userdir --userdir user_data
freqtrade new-strategy -s AwesomeStrategyAdv --template advanced
freqtrade backtesting --datadir tests/testdata --strategy AwesomeStrategyAdv
- name: Hyperopt
run: |
cp tests/testdata/config.tests.json config.json
freqtrade create-userdir --userdir user_data
freqtrade hyperopt --datadir tests/testdata -e 5 --strategy SampleStrategy --hyperopt-loss SharpeHyperOptLossDaily --print-all
- name: Sort imports (isort)
run: |
isort --check .
- name: Run Ruff
run: |
ruff check --output-format=github
- name: Run Ruff format check
run: |
ruff format --check
- name: Mypy
if: matrix.os == 'macos-15'
run: |
mypy freqtrade scripts
- name: Discord notification
uses: rjstone/discord-webhook-notify@c2597273488aeda841dd1e891321952b51f7996f #v2.2.1
if: failure() && ( github.event_name != 'pull_request' || github.event.pull_request.head.repo.fork == false)
with:
severity: info
details: Test Succeeded!
webhookUrl: ${{ secrets.DISCORD_WEBHOOK }}
build-windows:
runs-on: ${{ matrix.os }}
strategy:
matrix:
os: [ windows-latest ]
python-version: ["3.11", "3.12", "3.13"]
steps:
- uses: actions/checkout@v4
with:
persist-credentials: false
- name: Set up Python
uses: actions/setup-python@v5
with:
python-version: ${{ matrix.python-version }}
- name: Install uv
uses: astral-sh/setup-uv@e92bafb6253dcd438e0484186d7669ea7a8ca1cc # v6.4.3
with:
activate-environment: true
enable-cache: true
python-version: ${{ matrix.python-version }}
cache-dependency-glob: "requirements**.txt"
cache-suffix: "${{ matrix.python-version }}"
prune-cache: false
- name: Installation
run: |
function uvpipFunction { uv pip $args }
Set-Alias -name pip -value uvpipFunction
./build_helpers/install_windows.ps1
- name: Tests
run: |
pytest --random-order --durations 20 -n auto
- name: Check for repository changes
run: |
if (git status --porcelain) {
Write-Host "Repository is dirty, changes detected:"
git status
git diff
exit 1
}
else {
Write-Host "Repository is clean, no changes detected."
}
- name: Backtesting
run: |
cp tests/testdata/config.tests.json config.json
freqtrade create-userdir --userdir user_data
freqtrade backtesting --datadir tests/testdata --strategy SampleStrategy
- name: Hyperopt
run: |
cp tests/testdata/config.tests.json config.json
freqtrade create-userdir --userdir user_data
freqtrade hyperopt --datadir tests/testdata -e 5 --strategy SampleStrategy --hyperopt-loss SharpeHyperOptLossDaily --print-all
- name: Run Ruff
run: |
ruff check --output-format=github
- name: Run Ruff format check
run: |
ruff format --check
- name: Mypy
if: ${{ matrix.os == 'ubuntu-24.04' || matrix.os == 'macos-15' }}
run: |
mypy freqtrade scripts tests
- name: Run Pester tests (PowerShell)
if: ${{ runner.os == 'Windows' }}
shell: powershell
run: |
$PSVersionTable
Set-PSRepository psgallery -InstallationPolicy trusted
@@ -366,25 +163,24 @@ jobs:
Invoke-Pester -Path "tests" -CI
if ($Error.Length -gt 0) {exit 1}
shell: powershell
- name: Discord notification
uses: rjstone/discord-webhook-notify@c2597273488aeda841dd1e891321952b51f7996f #v2.2.1
if: failure() && ( github.event_name != 'pull_request' || github.event.pull_request.head.repo.fork == false)
if: ${{ failure() && ( github.event_name != 'pull_request' || github.event.pull_request.head.repo.fork == false) }}
with:
severity: error
details: Test Failed
details: Freqtrade CI failed on ${{ matrix.os }} with Python ${{ matrix.python-version }}!
webhookUrl: ${{ secrets.DISCORD_WEBHOOK }}
mypy-version-check:
runs-on: ubuntu-22.04
name: "Mypy Version Check"
runs-on: ubuntu-24.04
steps:
- uses: actions/checkout@v4
- uses: actions/checkout@v5
with:
persist-credentials: false
- name: Set up Python
uses: actions/setup-python@v5
uses: actions/setup-python@v6
with:
python-version: "3.12"
@@ -394,21 +190,23 @@ jobs:
python build_helpers/pre_commit_update.py
pre-commit:
name: "Pre-commit checks"
runs-on: ubuntu-22.04
steps:
- uses: actions/checkout@v4
- uses: actions/checkout@v5
with:
persist-credentials: false
- uses: actions/setup-python@v5
- uses: actions/setup-python@v6
with:
python-version: "3.12"
- uses: pre-commit/action@2c7b3805fd2a0fd8c1884dcaebf91fc102a13ecd # v3.0.1
docs-check:
name: "Documentation build"
runs-on: ubuntu-22.04
steps:
- uses: actions/checkout@v4
- uses: actions/checkout@v5
with:
persist-credentials: false
@@ -417,7 +215,7 @@ jobs:
./tests/test_docs.sh
- name: Set up Python
uses: actions/setup-python@v5
uses: actions/setup-python@v6
with:
python-version: "3.12"
@@ -437,53 +235,37 @@ jobs:
build-linux-online:
# Run pytest with "live" checks
name: "Tests and Linting - Online tests"
runs-on: ubuntu-24.04
steps:
- uses: actions/checkout@v4
- uses: actions/checkout@v5
with:
persist-credentials: false
- name: Set up Python
uses: actions/setup-python@v5
uses: actions/setup-python@v6
with:
python-version: "3.12"
- name: Install uv
uses: astral-sh/setup-uv@e92bafb6253dcd438e0484186d7669ea7a8ca1cc # v6.4.3
uses: astral-sh/setup-uv@3259c6206f993105e3a61b142c2d97bf4b9ef83d # v7.1.0
with:
activate-environment: true
enable-cache: true
python-version: "3.12"
cache-dependency-glob: "requirements**.txt"
cache-suffix: "3.12"
prune-cache: false
- name: Cache_dependencies
uses: actions/cache@v4
id: cache
with:
path: ~/dependencies/
key: ${{ runner.os }}-dependencies
- name: TA binary *nix
if: steps.cache.outputs.cache-hit != 'true'
run: |
cd build_helpers && ./install_ta-lib.sh ${HOME}/dependencies/; cd ..
- name: Installation - *nix
run: |
uv pip install --upgrade wheel
export LD_LIBRARY_PATH=${HOME}/dependencies/lib:$LD_LIBRARY_PATH
export TA_LIBRARY_PATH=${HOME}/dependencies/lib
export TA_INCLUDE_PATH=${HOME}/dependencies/include
uv pip install -r requirements-dev.txt
uv pip install -e ft_client/
uv pip install -e .
- name: Tests incl. ccxt compatibility tests
env:
CI_WEB_PROXY: http://152.67.78.211:13128
CI_WEB_PROXY: http://152.67.66.8:13128
run: |
pytest --random-order --longrun --durations 20 -n auto
@@ -491,9 +273,7 @@ jobs:
# Notify only once - when CI completes (and after deploy) in case it's successful
notify-complete:
needs: [
build-linux,
build-macos,
build-windows,
tests,
docs-check,
mypy-version-check,
pre-commit,
@@ -508,15 +288,16 @@ jobs:
- name: Check user permission
id: check
uses: scherermichael-oss/action-has-permission@136e061bfe093832d87f090dd768e14e27a740d3 # 1.0.6
continue-on-error: true
uses: prince-chrismc/check-actor-permissions-action@d504e74ba31658f4cdf4fcfeb509d4c09736d88e # v3.0.2
with:
required-permission: write
permission: "write"
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
- name: Discord notification
uses: rjstone/discord-webhook-notify@c2597273488aeda841dd1e891321952b51f7996f #v2.2.1
if: always() && steps.check.outputs.has-permission && ( github.event_name != 'pull_request' || github.event.pull_request.head.repo.fork == false)
if: steps.check.outputs.permitted == 'true' && ( github.event_name != 'pull_request' || github.event.pull_request.head.repo.fork == false)
with:
severity: info
details: Test Completed!
@@ -524,16 +305,16 @@ jobs:
build:
name: "Build"
needs: [ build-linux, build-macos, build-windows, docs-check, mypy-version-check, pre-commit ]
needs: [ tests, docs-check, mypy-version-check, pre-commit ]
runs-on: ubuntu-22.04
steps:
- uses: actions/checkout@v4
- uses: actions/checkout@v5
with:
persist-credentials: false
- name: Set up Python
uses: actions/setup-python@v5
uses: actions/setup-python@v6
with:
python-version: "3.12"
@@ -575,19 +356,19 @@ jobs:
id-token: write
steps:
- uses: actions/checkout@v4
- uses: actions/checkout@v5
with:
persist-credentials: false
- name: Download artifact 📦
uses: actions/download-artifact@v4
uses: actions/download-artifact@v5
with:
pattern: freqtrade*-build
path: dist
merge-multiple: true
- name: Publish to PyPI (Test)
uses: pypa/gh-action-pypi-publish@76f52bc884231f62b9a034ebfe128415bbaabdfc # v1.12.4
uses: pypa/gh-action-pypi-publish@ed0c53931b1dc9bd32cbe73a98c7f6766f8a527e # v1.13.0
with:
repository-url: https://test.pypi.org/legacy/
@@ -604,24 +385,29 @@ jobs:
id-token: write
steps:
- uses: actions/checkout@v4
- uses: actions/checkout@v5
with:
persist-credentials: false
- name: Download artifact 📦
uses: actions/download-artifact@v4
uses: actions/download-artifact@v5
with:
pattern: freqtrade*-build
path: dist
merge-multiple: true
- name: Publish to PyPI
uses: pypa/gh-action-pypi-publish@76f52bc884231f62b9a034ebfe128415bbaabdfc # v1.12.4
uses: pypa/gh-action-pypi-publish@ed0c53931b1dc9bd32cbe73a98c7f6766f8a527e # v1.13.0
docker-build:
name: "Docker Build and Deploy"
needs: [ build-linux, build-macos, build-windows, docs-check, mypy-version-check, pre-commit ]
needs: [
tests,
docs-check,
mypy-version-check,
pre-commit
]
if: (github.event_name == 'push' || github.event_name == 'schedule' || github.event_name == 'release') && github.repository == 'freqtrade/freqtrade'
uses: ./.github/workflows/docker-build.yml
permissions:
@@ -631,3 +417,14 @@ jobs:
DOCKER_PASSWORD: ${{ secrets.DOCKER_PASSWORD }}
DOCKER_USERNAME: ${{ secrets.DOCKER_USERNAME }}
DISCORD_WEBHOOK: ${{ secrets.DISCORD_WEBHOOK }}
packages-cleanup:
name: "Docker Package Cleanup"
uses: ./.github/workflows/packages-cleanup.yml
# Only run on push, schedule, or release events
if: (github.event_name == 'push' || github.event_name == 'schedule') && github.repository == 'freqtrade/freqtrade'
permissions:
packages: write
with:
package_name: 'freqtrade'

4
.github/workflows/deploy-docs.yml vendored
View File

@@ -19,12 +19,12 @@ jobs:
name: Deploy Docs through mike
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: actions/checkout@v5
with:
persist-credentials: true
- name: Set up Python
uses: actions/setup-python@v5
uses: actions/setup-python@v6
with:
python-version: '3.12'

4
.github/workflows/devcontainer-build.yml vendored
View File

@@ -24,11 +24,11 @@ jobs:
packages: write
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: actions/checkout@v5
with:
persist-credentials: false
- name: Login to GitHub Container Registry
uses: docker/login-action@184bdaa0721073962dff0199f1fb9940f07167d1 # v3.5.0
uses: docker/login-action@5e57cd118135c172c3672efd75eb46360885c0ef # v3.6.0
with:
registry: ghcr.io
username: ${{ github.actor }}

275
.github/workflows/docker-build.yml vendored
View File

@@ -20,43 +20,37 @@ on:
permissions:
contents: read
env:
IMAGE_NAME: "freqtradeorg/freqtrade"
CACHE_IMAGE: "freqtradeorg/freqtrade_cache"
GHCR_IMAGE_NAME: "ghcr.io/freqtrade/freqtrade"
PI_PLATFORM: "linux/arm/v7"
jobs:
deploy-docker:
name: "Deploy Docker x64 and armv7l"
runs-on: ubuntu-22.04
if: github.repository == 'freqtrade/freqtrade'
steps:
- uses: actions/checkout@v4
- uses: actions/checkout@v5
with:
persist-credentials: false
- name: Set up Python
uses: actions/setup-python@v5
- name: Set docker tag names
id: tags
uses: ./.github/actions/docker-tags
- name: Login to Docker Hub
uses: docker/login-action@5e57cd118135c172c3672efd75eb46360885c0ef # v3.6.0
with:
python-version: "3.12"
- name: Extract branch name
id: extract-branch
env:
BRANCH_NAME_INPUT: ${{ github.event.inputs.branch_name }}
run: |
if [ "${{ github.event_name }}" = "workflow_dispatch" ]; then
BRANCH_NAME="${BRANCH_NAME_INPUT}"
else
BRANCH_NAME="${GITHUB_REF##*/}"
fi
echo "GITHUB_REF='${GITHUB_REF}'"
echo "branch=${BRANCH_NAME}" >> "$GITHUB_OUTPUT"
- name: Dockerhub login
env:
DOCKER_PASSWORD: ${{ secrets.DOCKER_PASSWORD }}
DOCKER_USERNAME: ${{ secrets.DOCKER_USERNAME }}
run: |
echo "${DOCKER_PASSWORD}" | docker login --username ${DOCKER_USERNAME} --password-stdin
username: ${{ secrets.DOCKER_USERNAME }}
password: ${{ secrets.DOCKER_PASSWORD }}
- name: Set up QEMU
uses: docker/setup-qemu-action@29109295f81e9208d7d86ff1c6c12d2833863392 # v3.6.0
with:
cache-image: false
- name: Set up Docker Buildx
id: buildx
@@ -67,14 +61,89 @@ jobs:
env:
PLATFORMS: ${{ steps.buildx.outputs.platforms }}
- name: Build and test and push docker images
- name: Build image without cache
if: github.event_name == 'schedule'
env:
BRANCH_NAME: ${{ steps.extract-branch.outputs.branch }}
TAG: ${{ steps.tags.outputs.TAG }}
run: |
build_helpers/publish_docker_multi.sh
docker build -t ${CACHE_IMAGE}:${TAG} .
- name: Build ARMHF image without cache
if: github.event_name == 'schedule'
env:
TAG_PI: ${{ steps.tags.outputs.TAG_PI }}
CACHE_TAG_PI: ${{ steps.tags.outputs.CACHE_TAG_PI }}
run: |
docker buildx build \
--cache-to=type=registry,ref=${CACHE_TAG_PI} \
-f docker/Dockerfile.armhf \
--platform ${PI_PLATFORM} \
-t ${IMAGE_NAME}:${TAG_PI} \
--push \
--provenance=false \
.
- name: Build image with cache
if: github.event_name != 'schedule'
env:
TAG: ${{ steps.tags.outputs.TAG }}
run: |
docker pull ${IMAGE_NAME}:${TAG} || true
docker build --cache-from ${IMAGE_NAME}:${TAG} -t ${CACHE_IMAGE}:${TAG} .
- name: Build ARMHF image with cache
if: github.event_name != 'schedule'
# disable provenance due to https://github.com/docker/buildx/issues/1509
env:
TAG_PI: ${{ steps.tags.outputs.TAG_PI }}
CACHE_TAG_PI: ${{ steps.tags.outputs.CACHE_TAG_PI }}
run: |
docker buildx build \
--cache-from=type=registry,ref=${CACHE_TAG_PI} \
--cache-to=type=registry,ref=${CACHE_TAG_PI} \
-f docker/Dockerfile.armhf \
--platform ${PI_PLATFORM} \
-t ${IMAGE_NAME}:${TAG_PI} \
--push \
--provenance=false \
.
- name: Run build for AI images
env:
TAG: ${{ steps.tags.outputs.TAG }}
TAG_PLOT: ${{ steps.tags.outputs.TAG_PLOT }}
TAG_FREQAI: ${{ steps.tags.outputs.TAG_FREQAI }}
TAG_FREQAI_RL: ${{ steps.tags.outputs.TAG_FREQAI_RL }}
run: |
docker build --build-arg sourceimage=${CACHE_IMAGE} --build-arg sourcetag=${TAG} -t ${CACHE_IMAGE}:${TAG_PLOT} -f docker/Dockerfile.plot .
docker build --build-arg sourceimage=${CACHE_IMAGE} --build-arg sourcetag=${TAG} -t ${CACHE_IMAGE}:${TAG_FREQAI} -f docker/Dockerfile.freqai .
docker build --build-arg sourceimage=${CACHE_IMAGE} --build-arg sourcetag=${TAG_FREQAI} -t ${CACHE_IMAGE}:${TAG_FREQAI_RL} -f docker/Dockerfile.freqai_rl .
- name: Run backtest in Docker
env:
TAG: ${{ steps.tags.outputs.TAG }}
run: |
docker run --rm -v $(pwd)/tests/testdata/config.tests.json:/freqtrade/config.json:ro -v $(pwd)/tests:/tests ${CACHE_IMAGE}:${TAG} backtesting --datadir /tests/testdata --strategy-path /tests/strategy/strats/ --strategy StrategyTestV3
- name: Push cache images
env:
TAG: ${{ steps.tags.outputs.TAG }}
TAG_PLOT: ${{ steps.tags.outputs.TAG_PLOT }}
TAG_FREQAI: ${{ steps.tags.outputs.TAG_FREQAI }}
TAG_FREQAI_RL: ${{ steps.tags.outputs.TAG_FREQAI_RL }}
run: |
docker push ${CACHE_IMAGE}:$TAG
docker push ${CACHE_IMAGE}:$TAG_PLOT
docker push ${CACHE_IMAGE}:$TAG_FREQAI
docker push ${CACHE_IMAGE}:$TAG_FREQAI_RL
- name: list Images
run: |
docker images
deploy-arm:
name: "Deploy Docker"
name: "Deploy Docker ARM64"
permissions:
packages: write
needs: [ deploy-docker ]
@@ -83,37 +152,139 @@ jobs:
if: github.repository == 'freqtrade/freqtrade'
steps:
- uses: actions/checkout@v4
- uses: actions/checkout@v5
with:
persist-credentials: false
- name: Extract branch name
id: extract-branch
env:
BRANCH_NAME_INPUT: ${{ github.event.inputs.branch_name }}
run: |
if [ "${{ github.event_name }}" = "workflow_dispatch" ]; then
BRANCH_NAME="${BRANCH_NAME_INPUT}"
else
BRANCH_NAME="${GITHUB_REF##*/}"
fi
echo "GITHUB_REF='${GITHUB_REF}'"
echo "branch=${BRANCH_NAME}" >> "$GITHUB_OUTPUT"
- name: Set docker tag names
id: tags
uses: ./.github/actions/docker-tags
- name: Dockerhub login
env:
DOCKER_PASSWORD: ${{ secrets.DOCKER_PASSWORD }}
DOCKER_USERNAME: ${{ secrets.DOCKER_USERNAME }}
run: |
echo "${DOCKER_PASSWORD}" | docker login --username ${DOCKER_USERNAME} --password-stdin
- name: Login to Docker Hub
uses: docker/login-action@5e57cd118135c172c3672efd75eb46360885c0ef # v3.6.0
with:
username: ${{ secrets.DOCKER_USERNAME }}
password: ${{ secrets.DOCKER_PASSWORD }}
- name: Build and test and push docker images
- name: Login to github
uses: docker/login-action@5e57cd118135c172c3672efd75eb46360885c0ef # v3.6.0
with:
registry: ghcr.io
username: ${{ github.actor }}
password: ${{ secrets.GITHUB_TOKEN }}
- name: Build image without cache
if: github.event_name == 'schedule'
env:
BRANCH_NAME: ${{ steps.extract-branch.outputs.branch }}
GHCR_USERNAME: ${{ github.actor }}
GHCR_TOKEN: ${{ secrets.GITHUB_TOKEN }}
TAG_ARM: ${{ steps.tags.outputs.TAG_ARM }}
run: |
build_helpers/publish_docker_arm64.sh
docker build -t ${IMAGE_NAME}:${TAG_ARM} .
- name: Build image with cache
if: github.event_name != 'schedule'
env:
TAG_ARM: ${{ steps.tags.outputs.TAG_ARM }}
run: |
docker pull ${IMAGE_NAME}:${TAG_ARM} || true
docker build --cache-from ${IMAGE_NAME}:${TAG_ARM} -t ${CACHE_IMAGE}:${TAG_ARM} .
- name: Run build for AI images
env:
TAG_ARM: ${{ steps.tags.outputs.TAG_ARM }}
TAG_PLOT_ARM: ${{ steps.tags.outputs.TAG_PLOT_ARM }}
TAG_FREQAI_ARM: ${{ steps.tags.outputs.TAG_FREQAI_ARM }}
TAG_FREQAI_RL_ARM: ${{ steps.tags.outputs.TAG_FREQAI_RL_ARM }}
run: |
docker build --build-arg sourceimage=${CACHE_IMAGE} --build-arg sourcetag=${TAG_ARM} -t ${CACHE_IMAGE}:${TAG_PLOT_ARM} -f docker/Dockerfile.plot .
docker build --build-arg sourceimage=${CACHE_IMAGE} --build-arg sourcetag=${TAG_ARM} -t ${CACHE_IMAGE}:${TAG_FREQAI_ARM} -f docker/Dockerfile.freqai .
docker build --build-arg sourceimage=${CACHE_IMAGE} --build-arg sourcetag=${TAG_FREQAI_ARM} -t ${CACHE_IMAGE}:${TAG_FREQAI_RL_ARM} -f docker/Dockerfile.freqai_rl .
- name: Run backtest in Docker
env:
TAG_ARM: ${{ steps.tags.outputs.TAG_ARM }}
run: |
docker run --rm -v $(pwd)/tests/testdata/config.tests.json:/freqtrade/config.json:ro -v $(pwd)/tests:/tests ${CACHE_IMAGE}:${TAG_ARM} backtesting --datadir /tests/testdata --strategy-path /tests/strategy/strats/ --strategy StrategyTestV3
- name: Docker images
run: |
docker images
- name: Push cache images
env:
TAG_ARM: ${{ steps.tags.outputs.TAG_ARM }}
TAG_PLOT_ARM: ${{ steps.tags.outputs.TAG_PLOT_ARM }}
TAG_FREQAI_ARM: ${{ steps.tags.outputs.TAG_FREQAI_ARM }}
TAG_FREQAI_RL_ARM: ${{ steps.tags.outputs.TAG_FREQAI_RL_ARM }}
run: |
docker push ${CACHE_IMAGE}:$TAG_PLOT_ARM
docker push ${CACHE_IMAGE}:$TAG_FREQAI_ARM
docker push ${CACHE_IMAGE}:$TAG_FREQAI_RL_ARM
docker push ${CACHE_IMAGE}:$TAG_ARM
- name: Create manifests
env:
TAG_ARM: ${{ steps.tags.outputs.TAG_ARM }}
TAG: ${{ steps.tags.outputs.TAG }}
TAG_PI: ${{ steps.tags.outputs.TAG_PI }}
run: |
docker buildx imagetools create \
--tag ${IMAGE_NAME}:${TAG} \
--tag ${GHCR_IMAGE_NAME}:${TAG} \
${CACHE_IMAGE}:${TAG} ${CACHE_IMAGE}:${TAG_ARM} ${IMAGE_NAME}:${TAG_PI}
- name: Create multiarch image - Plot
env:
TAG_PLOT: ${{ steps.tags.outputs.TAG_PLOT }}
TAG_PLOT_ARM: ${{ steps.tags.outputs.TAG_PLOT_ARM }}
run: |
docker buildx imagetools create \
--tag ${IMAGE_NAME}:${TAG_PLOT} \
--tag ${GHCR_IMAGE_NAME}:${TAG_PLOT} \
${CACHE_IMAGE}:${TAG_PLOT} ${CACHE_IMAGE}:${TAG_PLOT_ARM}
- name: Create multiarch image - FreqAI
env:
TAG_FREQAI: ${{ steps.tags.outputs.TAG_FREQAI }}
TAG_FREQAI_ARM: ${{ steps.tags.outputs.TAG_FREQAI_ARM }}
run: |
docker buildx imagetools create \
--tag ${IMAGE_NAME}:${TAG_FREQAI} \
--tag ${GHCR_IMAGE_NAME}:${TAG_FREQAI} \
${CACHE_IMAGE}:${TAG_FREQAI} ${CACHE_IMAGE}:${TAG_FREQAI_ARM}
- name: Create multiarch image - FreqAI RL
env:
TAG_FREQAI_RL: ${{ steps.tags.outputs.TAG_FREQAI_RL }}
TAG_FREQAI_RL_ARM: ${{ steps.tags.outputs.TAG_FREQAI_RL_ARM }}
TAG_FREQAI_TORCH: ${{ steps.tags.outputs.TAG_FREQAI_TORCH }}
run: |
# Create special Torch tag - which is identical to the RL tag.
docker buildx imagetools create \
--tag ${IMAGE_NAME}:${TAG_FREQAI_RL} \
--tag ${GHCR_IMAGE_NAME}:${TAG_FREQAI_RL} \
--tag ${IMAGE_NAME}:${TAG_FREQAI_TORCH} \
--tag ${GHCR_IMAGE_NAME}:${TAG_FREQAI_TORCH} \
${CACHE_IMAGE}:${TAG_FREQAI_RL} ${CACHE_IMAGE}:${TAG_FREQAI_RL_ARM}
- name: Tag latest
if: env.TAG == 'develop'
env:
TAG: ${{ steps.tags.outputs.TAG }}
run: |
# Tag image as latest
docker buildx imagetools create \
--tag ${GHCR_IMAGE_NAME}:${TAG} \
--tag ${GHCR_IMAGE_NAME}:latest \
${IMAGE_NAME}:${TAG}
- name: Docker images
run: |
docker images
- name: Image cleanup
run: |
docker image prune -a --force --filter "until=24h"
- name: Discord notification
uses: rjstone/discord-webhook-notify@c2597273488aeda841dd1e891321952b51f7996f #v2.2.1

4
.github/workflows/docker-update-readme.yml vendored
View File

@@ -11,12 +11,12 @@ jobs:
dockerHubDescription:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: actions/checkout@v5
with:
persist-credentials: false
- name: Docker Hub Description
uses: peter-evans/dockerhub-description@432a30c9e07499fd01da9f8a49f0faf9e0ca5b77 # v4.0.2
uses: peter-evans/dockerhub-description@1b9a80c056b620d92cedb9d9b5a223409c68ddfa # v5.0.0
with:
username: ${{ secrets.DOCKER_USERNAME }}
password: ${{ secrets.DOCKER_PASSWORD }}

46
.github/workflows/packages-cleanup.yml vendored Normal file
View File

@@ -0,0 +1,46 @@
name: Cleanup Packages
on:
workflow_call:
inputs:
package_name:
description: 'Package name to clean up'
required: false
default: 'freqtrade'
type: string
workflow_dispatch:
inputs:
package_name:
description: 'Package name to clean up'
required: false
default: 'freqtrade'
type: choice
options:
- 'freqtrade'
- 'freqtrade-devcontainer'
delete-untagged:
description: 'Whether to delete only untagged images'
required: false
default: true
type: boolean
env:
PACKAGE_NAME: "freqtrade"
jobs:
deploy-docker:
name: "Delete Packages"
runs-on: ubuntu-24.04
if: github.repository == 'freqtrade/freqtrade'
permissions:
packages: write
steps:
- name: "Delete untagged Package Versions"
uses: actions/delete-package-versions@v5
with:
package-name: ${{ inputs.package_name || env.PACKAGE_NAME }}
package-type: 'container'
min-versions-to-keep: 10
delete-only-untagged-versions: ${{ inputs.delete-untagged || 'true' }}

4
.github/workflows/pre-commit-update.yml vendored
View File

@@ -13,11 +13,11 @@ jobs:
auto-update:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: actions/checkout@v5
with:
persist-credentials: false
- uses: actions/setup-python@v5
- uses: actions/setup-python@v6
with:
python-version: "3.12"

4
.github/workflows/zizmor.yml vendored
View File

@@ -21,9 +21,9 @@ jobs:
# actions: read # only needed for private repos
steps:
- name: Checkout repository
uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0
with:
persist-credentials: false
- name: Run zizmor 🌈
uses: zizmorcore/zizmor-action@f52a838cfabf134edcbaa7c8b3677dde20045018 # v0.1.1
uses: zizmorcore/zizmor-action@e673c3917a1aef3c65c972347ed84ccd013ecda4 # v0.2.0

20
.pre-commit-config.yaml
View File

@@ -21,22 +21,22 @@ repos:
# stages: [push]
- repo: https://github.com/pre-commit/mirrors-mypy
rev: "v1.17.1"
rev: "v1.18.2"
hooks:
- id: mypy
exclude: build_helpers
additional_dependencies:
- types-cachetools==6.1.0.20250717
- types-cachetools==6.2.0.20250827
- types-filelock==3.2.7
- types-requests==2.32.4.20250611
- types-requests==2.32.4.20250913
- types-tabulate==0.9.0.20241207
- types-python-dateutil==2.9.0.20250708
- scipy-stubs==1.16.1.0
- SQLAlchemy==2.0.42
- types-python-dateutil==2.9.0.20251008
- scipy-stubs==1.16.2.3
- SQLAlchemy==2.0.44
# stages: [push]
- repo: https://github.com/pycqa/isort
rev: "6.0.1"
rev: "7.0.0"
hooks:
- id: isort
name: isort (python)
@@ -44,13 +44,13 @@ repos:
- repo: https://github.com/charliermarsh/ruff-pre-commit
# Ruff version.
rev: 'v0.12.7'
rev: 'v0.14.1'
hooks:
- id: ruff
- id: ruff-format
- repo: https://github.com/pre-commit/pre-commit-hooks
rev: v5.0.0
rev: v6.0.0
hooks:
- id: end-of-file-fixer
exclude: |
@@ -83,6 +83,6 @@ repos:
# Ensure github actions remain safe
- repo: https://github.com/woodruffw/zizmor-pre-commit
rev: v1.11.0
rev: v1.15.2
hooks:
- id: zizmor

62
CONTRIBUTING.md
View File

@@ -9,8 +9,10 @@ Issues labeled [good first issue](https://github.com/freqtrade/freqtrade/labels/
Few pointers for contributions:
- Create your PR against the `develop` branch, not `stable`.
- New features need to contain unit tests, must conform to PEP8 (max-line-length = 100) and should be documented with the introduction PR.
- PR's can be declared as `[WIP]` - which signify Work in Progress Pull Requests (which are not finished).
- Stick to english in both commit messages, PR descriptions and code comments and variable names.
- New features need to contain unit tests, must pass CI (run pre-commit and pytest to get an early feedback) and should be documented with the introduction PR.
- PR's can be declared as draft - signaling Work in Progress for Pull Requests (which are not finished). We'll still aim to provide feedback on draft PR's in a timely manner.
- If you're using AI for your PR, please both mention it in the PR description and do a thorough review of the generated code. The final responsibility for the code with the PR author, not with the AI.
If you are unsure, discuss the feature on our [discord server](https://discord.gg/p7nuUNVfP7) or in a [issue](https://github.com/freqtrade/freqtrade/issues) before a Pull Request.
@@ -43,43 +45,43 @@ pytest tests/test_<file_name>.py
pytest tests/test_<file_name>.py::test_<method_name>
```
### 2. Test if your code is PEP8 compliant
### 2. Test if your code corresponds to our style guide
#### Run Ruff
We receive a lot of code that fails preliminary CI checks.
To help with that, we encourage contributors to install the git pre-commit hook that will let you know immediately when you try to commit code that fails these checks.
You can manually run pre-commit with `pre-commit run -a` - or install the git hook with `pre-commit install` to have it run automatically on each commit.
Running `pre-commit run -a` will run all checks, including `ruff`, `mypy` and `codespell` (among others).
#### Additional styles applied
- Have docstrings on all public methods
- Use double-quotes for docstrings
- Multiline docstrings should be indented to the level of the first quote
- Doc-strings should follow the reST format (`:param xxx: ...`, `:return: ...`, `:raises KeyError: ...`)
#### Manually run the individual checks
The following sections describe how to run the individual checks that are running as part of the pre-commit hook.
##### Run ruff
Check your code with ruff to ensure that it follows the style guide.
```bash
ruff check .
ruff format .
```
We receive a lot of code that fails the `ruff` checks.
To help with that, we encourage you to install the git pre-commit
hook that will warn you when you try to commit code that fails these checks.
##### Run mypy
you can manually run pre-commit with `pre-commit run -a`.
##### Additional styles applied
* Have docstrings on all public methods
* Use double-quotes for docstrings
* Multiline docstrings should be indented to the level of the first quote
* Doc-strings should follow the reST format (`:param xxx: ...`, `:return: ...`, `:raises KeyError: ... `)
### 3. Test if all type-hints are correct
#### Run mypy
Check your code with mypy to ensure that it follows the type-hinting rules.
``` bash
mypy freqtrade
```
### 4. Ensure formatting is correct
#### Run ruff
``` bash
ruff format .
```
## (Core)-Committer Guide
### Process: Pull Requests
@@ -118,18 +120,18 @@ Exceptions:
- Ensure cross-platform compatibility for every change that's accepted. Windows, Mac & Linux.
- Ensure no malicious code is introduced into the core code.
- Create issues for any major changes and enhancements that you wish to make. Discuss things transparently and get community feedback.
- Keep feature versions as small as possible, preferably one new feature per version.
- Keep feature PR's as small as possible, preferably one new feature per PR.
- Be welcoming to newcomers and encourage diverse new contributors from all backgrounds. See the Python Community Code of Conduct (https://www.python.org/psf/codeofconduct/).
### Becoming a Committer
Contributors may be given commit privileges. Preference will be given to those with:
1. Past contributions to Freqtrade and other related open-source projects. Contributions to Freqtrade include both code (both accepted and pending) and friendly participation in the issue tracker and Pull request reviews. Both quantity and quality are considered.
1. Past contributions to Freqtrade and other related open source projects. Contributions to Freqtrade include both code (both accepted and pending) and friendly participation in the issue tracker and Pull request reviews. Both quantity and quality are considered.
1. A coding style that the other core committers find simple, minimal, and clean.
1. Access to resources for cross-platform development and testing.
1. Time to devote to the project regularly.
Being a Committer does not grant write permission on `develop` or `stable` for security reasons (Users trust Freqtrade with their Exchange API keys).
Being a Committer does not automatically grant write permission on `develop` or `stable` for security reasons (Users trust Freqtrade with their Exchange API keys).
After being Committer for some time, a Committer may be named Core Committer and given full repository access.

9
Dockerfile
View File

@@ -1,4 +1,4 @@
FROM python:3.13.5-slim-bookworm AS base
FROM python:3.13.8-slim-bookworm AS base
# Setup env
ENV LANG=C.UTF-8
@@ -27,11 +27,6 @@ RUN apt-get update \
&& apt-get clean \
&& pip install --upgrade pip wheel
# Install TA-lib
COPY build_helpers/* /tmp/
RUN cd /tmp && /tmp/install_ta-lib.sh && rm -r /tmp/*ta-lib*
ENV LD_LIBRARY_PATH=/usr/local/lib
# Install dependencies
COPY --chown=ftuser:ftuser requirements.txt requirements-hyperopt.txt /freqtrade/
USER ftuser
@@ -49,7 +44,7 @@ USER ftuser
# Install and execute
COPY --chown=ftuser:ftuser . /freqtrade/
RUN pip install -e . --user --no-cache-dir --no-build-isolation \
RUN pip install -e . --user --no-cache-dir \
&& mkdir /freqtrade/user_data/ \
&& freqtrade install-ui

5
README.md
View File

@@ -4,7 +4,6 @@
[![DOI](https://joss.theoj.org/papers/10.21105/joss.04864/status.svg)](https://doi.org/10.21105/joss.04864)
[![Coverage Status](https://coveralls.io/repos/github/freqtrade/freqtrade/badge.svg?branch=develop&service=github)](https://coveralls.io/github/freqtrade/freqtrade?branch=develop)
[![Documentation](https://readthedocs.org/projects/freqtrade/badge/)](https://www.freqtrade.io)
[![Maintainability](https://api.codeclimate.com/v1/badges/5737e6d668200b7518ff/maintainability)](https://codeclimate.com/github/freqtrade/freqtrade/maintainability)
Freqtrade is a free and open source crypto trading bot written in Python. It is designed to support all major exchanges and be controlled via Telegram or webUI. It contains backtesting, plotting and money management tools as well as strategy optimization by machine learning.
@@ -28,8 +27,9 @@ hesitate to read the source code and understand the mechanism of this bot.
Please read the [exchange specific notes](docs/exchanges.md) to learn about eventual, special configurations needed for each exchange.
- [X] [Binance](https://www.binance.com/)
- [X] [Bitmart](https://bitmart.com/)
- [X] [BingX](https://bingx.com/invite/0EM9RX)
- [X] [Bitget](https://www.bitget.com/)
- [X] [Bitmart](https://bitmart.com/)
- [X] [Bybit](https://bybit.com/)
- [X] [Gate.io](https://www.gate.io/ref/6266643)
- [X] [HTX](https://www.htx.com/)
@@ -42,6 +42,7 @@ Please read the [exchange specific notes](docs/exchanges.md) to learn about even
### Supported Futures Exchanges (experimental)
- [X] [Binance](https://www.binance.com/)
- [X] [Bitget](https://www.bitget.com/)
- [X] [Gate.io](https://www.gate.io/ref/6266643)
- [X] [Hyperliquid](https://hyperliquid.xyz/) (A decentralized exchange, or DEX)
- [X] [OKX](https://okx.com/)

35
build_helpers/install_ta-lib.sh
View File

@@ -1,35 +0,0 @@
if [ -z "$1" ]; then
INSTALL_LOC=/usr/local
else
INSTALL_LOC=${1}
fi
echo "Installing to ${INSTALL_LOC}"
if [ -n "$2" ] || [ ! -f "${INSTALL_LOC}/lib/libta_lib.a" ]; then
tar zxvf ta-lib-0.4.0-src.tar.gz
cd ta-lib \
&& sed -i.bak "s|0.00000001|0.000000000000000001 |g" src/ta_func/ta_utility.h \
&& echo "Downloading gcc config.guess and config.sub" \
&& curl -s 'https://raw.githubusercontent.com/gcc-mirror/gcc/master/config.guess' -o config.guess \
&& curl -s 'https://raw.githubusercontent.com/gcc-mirror/gcc/master/config.sub' -o config.sub \
&& ./configure --prefix=${INSTALL_LOC}/ \
&& make
if [ $? -ne 0 ]; then
echo "Failed building ta-lib."
cd .. && rm -rf ./ta-lib/
exit 1
fi
if [ -z "$2" ]; then
which sudo && sudo make install || make install
if [ -x "$(command -v apt-get)" ]; then
echo "Updating library path using ldconfig"
sudo ldconfig
fi
else
# Don't install with sudo
make install
fi
cd .. && rm -rf ./ta-lib/
else
echo "TA-lib already installed, skipping installation"
fi

10
build_helpers/install_windows.ps1
View File

@@ -1,10 +0,0 @@
# vendored Wheels compiled via https://github.com/xmatthias/ta-lib-python/tree/ta_bundled_040
python -m pip install --upgrade pip
python -c "import sys; print(f'{sys.version_info.major}.{sys.version_info.minor}')"
pip install -U wheel "numpy<3.0"
pip install --only-binary ta-lib --find-links=build_helpers\ ta-lib
pip install -r requirements-dev.txt
pip install -e .

119
build_helpers/publish_docker_arm64.sh
View File

@@ -1,119 +0,0 @@
#!/bin/sh
# Use BuildKit, otherwise building on ARM fails
export DOCKER_BUILDKIT=1
IMAGE_NAME=freqtradeorg/freqtrade
CACHE_IMAGE=freqtradeorg/freqtrade_cache
GHCR_IMAGE_NAME=ghcr.io/freqtrade/freqtrade
# Replace / with _ to create a valid tag
TAG=$(echo "${BRANCH_NAME}" | sed -e "s/\//_/g")
TAG_PLOT=${TAG}_plot
TAG_FREQAI=${TAG}_freqai
TAG_FREQAI_RL=${TAG_FREQAI}rl
TAG_FREQAI_TORCH=${TAG_FREQAI}torch
TAG_PI="${TAG}_pi"
TAG_ARM=${TAG}_arm
TAG_PLOT_ARM=${TAG_PLOT}_arm
TAG_FREQAI_ARM=${TAG_FREQAI}_arm
TAG_FREQAI_RL_ARM=${TAG_FREQAI_RL}_arm
echo "Running for ${TAG}"
# Add commit and commit_message to docker container
echo "${GITHUB_SHA}" > freqtrade_commit
if [ "${GITHUB_EVENT_NAME}" = "schedule" ]; then
echo "event ${GITHUB_EVENT_NAME}: full rebuild - skipping cache"
# Build regular image
docker build -t freqtrade:${TAG_ARM} .
else
echo "event ${GITHUB_EVENT_NAME}: building with cache"
# Build regular image
docker pull ${IMAGE_NAME}:${TAG_ARM}
docker build --cache-from ${IMAGE_NAME}:${TAG_ARM} -t freqtrade:${TAG_ARM} .
fi
if [ $? -ne 0 ]; then
echo "failed building multiarch images"
return 1
fi
docker build --build-arg sourceimage=freqtrade --build-arg sourcetag=${TAG_ARM} -t freqtrade:${TAG_PLOT_ARM} -f docker/Dockerfile.plot .
docker build --build-arg sourceimage=freqtrade --build-arg sourcetag=${TAG_ARM} -t freqtrade:${TAG_FREQAI_ARM} -f docker/Dockerfile.freqai .
docker build --build-arg sourceimage=freqtrade --build-arg sourcetag=${TAG_FREQAI_ARM} -t freqtrade:${TAG_FREQAI_RL_ARM} -f docker/Dockerfile.freqai_rl .
# Tag image for upload and next build step
docker tag freqtrade:$TAG_ARM ${CACHE_IMAGE}:$TAG_ARM
docker tag freqtrade:$TAG_PLOT_ARM ${CACHE_IMAGE}:$TAG_PLOT_ARM
docker tag freqtrade:$TAG_FREQAI_ARM ${CACHE_IMAGE}:$TAG_FREQAI_ARM
docker tag freqtrade:$TAG_FREQAI_RL_ARM ${CACHE_IMAGE}:$TAG_FREQAI_RL_ARM
# Run backtest
docker run --rm -v $(pwd)/tests/testdata/config.tests.json:/freqtrade/config.json:ro -v $(pwd)/tests:/tests freqtrade:${TAG_ARM} backtesting --datadir /tests/testdata --strategy-path /tests/strategy/strats/ --strategy StrategyTestV3
if [ $? -ne 0 ]; then
echo "failed running backtest"
return 1
fi
docker images
docker push ${CACHE_IMAGE}:$TAG_PLOT_ARM
docker push ${CACHE_IMAGE}:$TAG_FREQAI_ARM
docker push ${CACHE_IMAGE}:$TAG_FREQAI_RL_ARM
docker push ${CACHE_IMAGE}:$TAG_ARM
# Create multi-arch image
# Make sure that all images contained here are pushed to github first.
# Otherwise installation might fail.
echo "create manifests"
docker manifest create ${IMAGE_NAME}:${TAG} ${CACHE_IMAGE}:${TAG} ${CACHE_IMAGE}:${TAG_ARM} ${IMAGE_NAME}:${TAG_PI}
docker manifest push -p ${IMAGE_NAME}:${TAG}
docker manifest create ${IMAGE_NAME}:${TAG_PLOT} ${CACHE_IMAGE}:${TAG_PLOT} ${CACHE_IMAGE}:${TAG_PLOT_ARM}
docker manifest push -p ${IMAGE_NAME}:${TAG_PLOT}
docker manifest create ${IMAGE_NAME}:${TAG_FREQAI} ${CACHE_IMAGE}:${TAG_FREQAI} ${CACHE_IMAGE}:${TAG_FREQAI_ARM}
docker manifest push -p ${IMAGE_NAME}:${TAG_FREQAI}
docker manifest create ${IMAGE_NAME}:${TAG_FREQAI_RL} ${CACHE_IMAGE}:${TAG_FREQAI_RL} ${CACHE_IMAGE}:${TAG_FREQAI_RL_ARM}
docker manifest push -p ${IMAGE_NAME}:${TAG_FREQAI_RL}
# Create special Torch tag - which is identical to the RL tag.
docker manifest create ${IMAGE_NAME}:${TAG_FREQAI_TORCH} ${CACHE_IMAGE}:${TAG_FREQAI_RL} ${CACHE_IMAGE}:${TAG_FREQAI_RL_ARM}
docker manifest push -p ${IMAGE_NAME}:${TAG_FREQAI_TORCH}
# copy images to ghcr.io
alias crane="docker run --rm -i -v $(pwd)/.crane:/home/nonroot/.docker/ gcr.io/go-containerregistry/crane"
mkdir .crane
chmod a+rwx .crane
echo "${GHCR_TOKEN}" | crane auth login ghcr.io -u "${GHCR_USERNAME}" --password-stdin
crane copy ${IMAGE_NAME}:${TAG_FREQAI_RL} ${GHCR_IMAGE_NAME}:${TAG_FREQAI_RL}
crane copy ${IMAGE_NAME}:${TAG_FREQAI_RL} ${GHCR_IMAGE_NAME}:${TAG_FREQAI_TORCH}
crane copy ${IMAGE_NAME}:${TAG_FREQAI} ${GHCR_IMAGE_NAME}:${TAG_FREQAI}
crane copy ${IMAGE_NAME}:${TAG_PLOT} ${GHCR_IMAGE_NAME}:${TAG_PLOT}
crane copy ${IMAGE_NAME}:${TAG} ${GHCR_IMAGE_NAME}:${TAG}
# Tag as latest for develop builds
if [ "${TAG}" = "develop" ]; then
echo 'Tagging image as latest'
docker manifest create ${IMAGE_NAME}:latest ${CACHE_IMAGE}:${TAG_ARM} ${IMAGE_NAME}:${TAG_PI} ${CACHE_IMAGE}:${TAG}
docker manifest push -p ${IMAGE_NAME}:latest
crane copy ${IMAGE_NAME}:latest ${GHCR_IMAGE_NAME}:latest
fi
docker images
rm -rf .crane
# Cleanup old images from arm64 node.
docker image prune -a --force --filter "until=24h"

89
build_helpers/publish_docker_multi.sh
View File

@@ -1,89 +0,0 @@
#!/bin/sh
# The below assumes a correctly setup docker buildx environment
IMAGE_NAME=freqtradeorg/freqtrade
CACHE_IMAGE=freqtradeorg/freqtrade_cache
# Replace / with _ to create a valid tag
TAG=$(echo "${BRANCH_NAME}" | sed -e "s/\//_/g")
TAG_PLOT=${TAG}_plot
TAG_FREQAI=${TAG}_freqai
TAG_FREQAI_RL=${TAG_FREQAI}rl
TAG_PI="${TAG}_pi"
PI_PLATFORM="linux/arm/v7"
echo "Running for ${TAG}"
CACHE_TAG=${CACHE_IMAGE}:${TAG_PI}_cache
# Add commit and commit_message to docker container
echo "${GITHUB_SHA}" > freqtrade_commit
if [ "${GITHUB_EVENT_NAME}" = "schedule" ]; then
echo "event ${GITHUB_EVENT_NAME}: full rebuild - skipping cache"
# Build regular image
docker build -t freqtrade:${TAG} .
# Build PI image
docker buildx build \
--cache-to=type=registry,ref=${CACHE_TAG} \
-f docker/Dockerfile.armhf \
--platform ${PI_PLATFORM} \
-t ${IMAGE_NAME}:${TAG_PI} \
--push \
--provenance=false \
.
else
echo "event ${GITHUB_EVENT_NAME}: building with cache"
# Build regular image
docker pull ${IMAGE_NAME}:${TAG}
docker build --cache-from ${IMAGE_NAME}:${TAG} -t freqtrade:${TAG} .
# Pull last build to avoid rebuilding the whole image
# docker pull --platform ${PI_PLATFORM} ${IMAGE_NAME}:${TAG}
# disable provenance due to https://github.com/docker/buildx/issues/1509
docker buildx build \
--cache-from=type=registry,ref=${CACHE_TAG} \
--cache-to=type=registry,ref=${CACHE_TAG} \
-f docker/Dockerfile.armhf \
--platform ${PI_PLATFORM} \
-t ${IMAGE_NAME}:${TAG_PI} \
--push \
--provenance=false \
.
fi
if [ $? -ne 0 ]; then
echo "failed building multiarch images"
return 1
fi
# Tag image for upload and next build step
docker tag freqtrade:$TAG ${CACHE_IMAGE}:$TAG
docker build --build-arg sourceimage=freqtrade --build-arg sourcetag=${TAG} -t freqtrade:${TAG_PLOT} -f docker/Dockerfile.plot .
docker build --build-arg sourceimage=freqtrade --build-arg sourcetag=${TAG} -t freqtrade:${TAG_FREQAI} -f docker/Dockerfile.freqai .
docker build --build-arg sourceimage=freqtrade --build-arg sourcetag=${TAG_FREQAI} -t freqtrade:${TAG_FREQAI_RL} -f docker/Dockerfile.freqai_rl .
docker tag freqtrade:$TAG_PLOT ${CACHE_IMAGE}:$TAG_PLOT
docker tag freqtrade:$TAG_FREQAI ${CACHE_IMAGE}:$TAG_FREQAI
docker tag freqtrade:$TAG_FREQAI_RL ${CACHE_IMAGE}:$TAG_FREQAI_RL
# Run backtest
docker run --rm -v $(pwd)/tests/testdata/config.tests.json:/freqtrade/config.json:ro -v $(pwd)/tests:/tests freqtrade:${TAG} backtesting --datadir /tests/testdata --strategy-path /tests/strategy/strats/ --strategy StrategyTestV3
if [ $? -ne 0 ]; then
echo "failed running backtest"
return 1
fi
docker images
docker push ${CACHE_IMAGE}:$TAG
docker push ${CACHE_IMAGE}:$TAG_PLOT
docker push ${CACHE_IMAGE}:$TAG_FREQAI
docker push ${CACHE_IMAGE}:$TAG_FREQAI_RL
docker images
if [ $? -ne 0 ]; then
echo "failed building image"
return 1
fi

10
build_helpers/schema.json
View File

@@ -268,7 +268,8 @@
"day",
"week",
"month",
"year"
"year",
"weekday"
]
}
},
@@ -572,6 +573,7 @@
"pairlists": {
"description": "Configuration for pairlists.",
"type": "array",
"minItems": 1,
"items": {
"type": "object",
"properties": {
@@ -586,6 +588,7 @@
"RemotePairList",
"MarketCapPairList",
"AgeFilter",
"DelistFilter",
"FullTradesFilter",
"OffsetFilter",
"PerformanceFilter",
@@ -1459,6 +1462,11 @@
"type": "boolean",
"default": false
},
"override_exchange_check": {
"description": "Override the exchange check to force FreqAI to use exchanges that may not have enough historic data. Turn this to True if you know your FreqAI model and strategy do not require historical data.",
"type": "boolean",
"default": false
},
"feature_parameters": {
"description": "The parameters used to engineer the feature set",
"type": "object",

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56
config_examples/config_full.example.json
View File

@@ -25,10 +25,10 @@
"trading_mode": "spot",
"margin_mode": "",
"minimal_roi": {
"40": 0.0,
"30": 0.01,
"20": 0.02,
"0": 0.04
"40": 0.0,
"30": 0.01,
"20": 0.02,
"0": 0.04
},
"stoploss": -0.10,
"unfilledtimeout": {
@@ -47,7 +47,7 @@
"bids_to_ask_delta": 1
}
},
"exit_pricing":{
"exit_pricing": {
"price_side": "same",
"use_order_book": true,
"order_book_top": 1,
@@ -70,18 +70,38 @@
"exit": "GTC"
},
"pairlists": [
{"method": "StaticPairList"},
{"method": "FullTradesFilter"},
{
"method": "StaticPairList"
},
{
"method": "DelistFilter",
"max_days_from_now": 0,
},
{
"method": "FullTradesFilter"
},
{
"method": "VolumePairList",
"number_assets": 20,
"sort_key": "quoteVolume",
"refresh_period": 1800
},
{"method": "AgeFilter", "min_days_listed": 10},
{"method": "PrecisionFilter"},
{"method": "PriceFilter", "low_price_ratio": 0.01, "min_price": 0.00000010},
{"method": "SpreadFilter", "max_spread_ratio": 0.005},
{
"method": "AgeFilter",
"min_days_listed": 10
},
{
"method": "PrecisionFilter"
},
{
"method": "PriceFilter",
"low_price_ratio": 0.01,
"min_price": 0.00000010
},
{
"method": "SpreadFilter",
"max_spread_ratio": 0.005
},
{
"method": "RangeStabilityFilter",
"lookback_days": 10,
@@ -166,12 +186,12 @@
"external_message_consumer": {
"enabled": false,
"producers": [
{
"name": "default",
"host": "127.0.0.2",
"port": 8080,
"ws_token": "secret_ws_t0ken."
}
{
"name": "default",
"host": "127.0.0.2",
"port": 8080,
"ws_token": "secret_ws_t0ken."
}
],
"wait_timeout": 300,
"ping_timeout": 10,
@@ -195,4 +215,4 @@
"reduce_df_footprint": false,
"dataformat_ohlcv": "feather",
"dataformat_trades": "feather"
}
}

5
docker/Dockerfile.armhf
View File

@@ -34,8 +34,7 @@ COPY build_helpers/* /tmp/
# Install dependencies
COPY --chown=ftuser:ftuser requirements.txt /freqtrade/
USER ftuser
RUN pip install --user --no-cache-dir "numpy<3.0" \
&& pip install --user --no-index --find-links /tmp/ pyarrow TA-Lib \
RUN pip install --user --only-binary=:all: --find-links /tmp/ pyarrow TA-Lib \
&& pip install --user --no-cache-dir -r requirements.txt
# Copy dependencies to runtime-image
@@ -49,7 +48,7 @@ USER ftuser
# Install and execute
COPY --chown=ftuser:ftuser . /freqtrade/
RUN pip install -e . --user --no-cache-dir --no-build-isolation\
RUN pip install -e . --user --no-cache-dir \
&& mkdir /freqtrade/user_data/ \
&& freqtrade install-ui

21
docs/advanced-backtesting.md
View File

@@ -46,29 +46,32 @@ ranging from the simplest (0) to the most detailed per pair, per buy and per sel
More options are available by running with the `-h` option.
### Using export-filename
### Using backtest-filename
Normally, `backtesting-analysis` uses the latest backtest results, but if you wanted to go
back to a previous backtest output, you need to supply the `--export-filename` option.
You can supply the same parameter to `backtest-analysis` with the name of the final backtest
output file. This allows you to keep historical versions of backtest results and re-analyse
them at a later date:
By default, `backtesting-analysis` processes the most recent backtest results in the `user_data/backtest_results` directory.
If you want to analyze results from an earlier backtest, use the `--backtest-filename` option to specify the desired file. This lets you revisit and re-analyze historical backtest outputs at any time by providing the filename of the relevant backtest result:
``` bash
freqtrade backtesting -c <config.json> --timeframe <tf> --strategy <strategy_name> --timerange=<timerange> --export=signals --export-filename=/tmp/mystrat_backtest.json
freqtrade backtesting-analysis -c <config.json> --timeframe <tf> --strategy <strategy_name> --timerange <timerange> --export signals --backtest-filename backtest-result-2025-03-05_20-38-34.zip
```
You should see some output similar to below in the logs with the name of the timestamped
filename that was exported:
```
2022-06-14 16:28:32,698 - freqtrade.misc - INFO - dumping json to "/tmp/mystrat_backtest-2022-06-14_16-28-32.json"
2022-06-14 16:28:32,698 - freqtrade.misc - INFO - dumping json to "mystrat_backtest-2022-06-14_16-28-32.json"
```
You can then use that filename in `backtesting-analysis`:
```
freqtrade backtesting-analysis -c <config.json> --export-filename=/tmp/mystrat_backtest-2022-06-14_16-28-32.json
freqtrade backtesting-analysis -c <config.json> --backtest-filename=mystrat_backtest-2022-06-14_16-28-32.json
```
To use a result from a different results directory, you can use `--backtest-directory` to specify the directory
``` bash
freqtrade backtesting-analysis -c <config.json> --backtest-directory custom_results/ --backtest-filename mystrat_backtest-2022-06-14_16-28-32.json
```
### Tuning the buy tags and sell tags to display

4
docs/advanced-setup.md
View File

@@ -134,10 +134,10 @@ The following systems have been tested and are known to work with freqtrade:
### PostgreSQL
Installation:
`pip install psycopg2-binary`
`pip install "psycopg[binary]"`
Usage:
`... --db-url postgresql+psycopg2://<username>:<password>@localhost:5432/<database>`
`... --db-url postgresql+psycopg://<username>:<password>@localhost:5432/<database>`
Freqtrade will automatically create the tables necessary upon startup.

439
docs/backtesting.md
View File

@@ -105,12 +105,14 @@ Only use this if you're sure you'll not want to plot or analyze your results fur
---
Exporting trades to file specifying a custom filename
Exporting trades to file specifying a custom directory
```bash
freqtrade backtesting --strategy backtesting --export trades --export-filename=backtest_samplestrategy.json
freqtrade backtesting --strategy backtesting --export trades --backtest-directory=user_data/custom-backtest-results
```
---
Please also read about the [strategy startup period](strategy-customization.md#strategy-startup-period).
---
@@ -158,117 +160,136 @@ The most important in the backtesting is to understand the result.
A backtesting result will look like that:
```
================================================ BACKTESTING REPORT =================================================
| Pair | Trades | Avg Profit % | Tot Profit BTC | Tot Profit % | Avg Duration | Wins Draws Loss Win% |
|----------+--------+----------------+------------------+----------------+--------------+--------------------------|
| ADA/BTC | 35 | -0.11 | -0.00019428 | -1.94 | 4:35:00 | 14 0 21 40.0 |
| ARK/BTC | 11 | -0.41 | -0.00022647 | -2.26 | 2:03:00 | 3 0 8 27.3 |
| BTS/BTC | 32 | 0.31 | 0.00048938 | 4.89 | 5:05:00 | 18 0 14 56.2 |
| DASH/BTC | 13 | -0.08 | -0.00005343 | -0.53 | 4:39:00 | 6 0 7 46.2 |
| ENG/BTC | 18 | 1.36 | 0.00122807 | 12.27 | 2:50:00 | 8 0 10 44.4 |
| EOS/BTC | 36 | 0.08 | 0.00015304 | 1.53 | 3:34:00 | 16 0 20 44.4 |
| ETC/BTC | 26 | 0.37 | 0.00047576 | 4.75 | 6:14:00 | 11 0 15 42.3 |
| ETH/BTC | 33 | 0.30 | 0.00049856 | 4.98 | 7:31:00 | 16 0 17 48.5 |
| IOTA/BTC | 32 | 0.03 | 0.00005444 | 0.54 | 3:12:00 | 14 0 18 43.8 |
| LSK/BTC | 15 | 1.75 | 0.00131413 | 13.13 | 2:58:00 | 6 0 9 40.0 |
| LTC/BTC | 32 | -0.04 | -0.00006886 | -0.69 | 4:49:00 | 11 0 21 34.4 |
| NANO/BTC | 17 | 1.26 | 0.00107058 | 10.70 | 1:55:00 | 10 0 7 58.5 |
| NEO/BTC | 23 | 0.82 | 0.00094936 | 9.48 | 2:59:00 | 10 0 13 43.5 |
| REQ/BTC | 9 | 1.17 | 0.00052734 | 5.27 | 3:47:00 | 4 0 5 44.4 |
| XLM/BTC | 16 | 1.22 | 0.00097800 | 9.77 | 3:15:00 | 7 0 9 43.8 |
| XMR/BTC | 23 | -0.18 | -0.00020696 | -2.07 | 5:30:00 | 12 0 11 52.2 |
| XRP/BTC | 35 | 0.66 | 0.00114897 | 11.48 | 3:49:00 | 12 0 23 34.3 |
| ZEC/BTC | 22 | -0.46 | -0.00050971 | -5.09 | 2:22:00 | 7 0 15 31.8 |
| TOTAL | 429 | 0.36 | 0.00762792 | 76.20 | 4:12:00 | 186 0 243 43.4 |
============================================= LEFT OPEN TRADES REPORT =============================================
| Pair | Trades | Avg Profit % | Tot Profit BTC | Tot Profit % | Avg Duration | Win Draw Loss Win% |
|----------+---------+----------------+------------------+----------------+----------------+---------------------|
| ADA/BTC | 1 | 0.89 | 0.00004434 | 0.44 | 6:00:00 | 1 0 0 100 |
| LTC/BTC | 1 | 0.68 | 0.00003421 | 0.34 | 2:00:00 | 1 0 0 100 |
| TOTAL | 2 | 0.78 | 0.00007855 | 0.78 | 4:00:00 | 2 0 0 100 |
==================== EXIT REASON STATS ====================
| Exit Reason | Exits | Wins | Draws | Losses |
|--------------------+---------+-------+--------+---------|
| trailing_stop_loss | 205 | 150 | 0 | 55 |
| stop_loss | 166 | 0 | 0 | 166 |
| exit_signal | 56 | 36 | 0 | 20 |
| force_exit | 2 | 0 | 0 | 2 |
BACKTESTING REPORT
┏━━━━━━━━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┓
┃ Pair ┃ Trades ┃ Avg Profit % ┃ Tot Profit USDT ┃ Tot Profit % ┃ Avg Duration ┃ Win Draw Loss Win% ┃
┡━━━━━━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━┩
│ LTC/USDT:USDT │ 16 │ 1.0 │ 56.176 │ 5.62 │ 16:16:00 │ 16 0 0 100 │
│ ETC/USDT:USDT │ 12 │ 0.72 │ 30.936 │ 3.09 │ 9:55:00 │ 11 0 1 91.7 │
│ ETH/USDT:USDT │ 8 │ 0.66 │ 17.864 │ 1.79 │ 1 day, 13:55:00 │ 7 0 1 87.5 │
│ XLM/USDT:USDT │ 10 │ 0.31 │ 11.054 │ 1.11 │ 12:08:00 │ 9 0 1 90.0 │
│ BTC/USDT:USDT │ 8 │ 0.21 │ 7.289 │ 0.73 │ 3 days, 1:24:00 │ 6 0 2 75.0 │
│ XRP/USDT:USDT │ 9 │ -0.14 │ -7.261 │ -0.73 │ 21:18:00 │ 8 0 1 88.9 │
│ DOT/USDT:USDT │ 6 │ -0.4 │ -9.187 │ -0.92 │ 5:35:00 │ 4 0 2 66.7 │
│ ADA/USDT:USDT │ 8 │ -1.76 │ -52.098 │ -5.21 │ 11:38:00 │ 6 0 2 75.0 │
│ TOTAL │ 77 │ 0.22 │ 54.774 │ 5.48 │ 22:12:00 │ 67 0 10 87.0 │
└───────────────┴────────┴──────────────┴─────────────────┴──────────────┴─────────────────┴────────────────────────┘
LEFT OPEN TRADES REPORT
┏━━━━━━━━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┓
┃ Pair ┃ Trades ┃ Avg Profit % ┃ Tot Profit USDT ┃ Tot Profit % ┃ Avg Duration ┃ Win Draw Loss Win% ┃
┡━━━━━━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━┩
│ BTC/USDT:USDT │ 1 │ -4.14 │ -9.930 │ -0.99 │ 17 days, 8:00:00 │ 0 0 1 0 │
│ ETC/USDT:USDT │ 1 │ -4.24 │ -15.365 │ -1.54 │ 10:40:00 │ 0 0 1 0 │
│ DOT/USDT:USDT │ 1 │ -5.29 │ -19.125 │ -1.91 │ 11:30:00 │ 0 0 1 0 │
│ TOTAL │ 3 │ -4.56 │ -44.420 │ -4.44 │ 6 days, 2:03:00 │ 0 0 3 0 │
└───────────────┴────────┴──────────────┴─────────────────┴──────────────┴──────────────────┴────────────────────────┘
ENTER TAG STATS
┏━━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┓
┃ Enter Tag ┃ Entries ┃ Avg Profit % ┃ Tot Profit USDT ┃ Tot Profit % ┃ Avg Duration ┃ Win Draw Loss Win% ┃
┡━━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━┩
│ OTHER │ 77 │ 0.22 │ 54.774 │ 5.48 │ 22:12:00 │ 67 0 10 87.0 │
│ TOTAL │ 77 │ 0.22 │ 54.774 │ 5.48 │ 22:12:00 │ 67 0 10 87.0 │
└───────────┴─────────┴──────────────┴─────────────────┴──────────────┴──────────────┴────────────────────────┘
EXIT REASON STATS
┏━━━━━━━━━━━━━┳━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┓
┃ Exit Reason ┃ Exits ┃ Avg Profit % ┃ Tot Profit USDT ┃ Tot Profit % ┃ Avg Duration ┃ Win Draw Loss Win% ┃
┡━━━━━━━━━━━━━╇━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━┩
│ roi │ 67 │ 1.05 │ 242.179 │ 24.22 │ 15:49:00 │ 67 0 0 100 │
│ exit_signal │ 4 │ -2.23 │ -31.217 │ -3.12 │ 1 day, 8:38:00 │ 0 0 4 0 │
│ force_exit │ 3 │ -4.56 │ -44.420 │ -4.44 │ 6 days, 2:03:00 │ 0 0 3 0 │
│ stop_loss │ 3 │ -10.14 │ -111.768 │ -11.18 │ 1 day, 3:05:00 │ 0 0 3 0 │
│ TOTAL │ 77 │ 0.22 │ 54.774 │ 5.48 │ 22:12:00 │ 67 0 10 87.0 │
└─────────────┴───────┴──────────────┴─────────────────┴──────────────┴─────────────────┴────────────────────────┘
MIXED TAG STATS
┏━━━━━━━━━━━┳━━━━━━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┓
┃ Enter Tag ┃ Exit Reason ┃ Trades ┃ Avg Profit % ┃ Tot Profit USDT ┃ Tot Profit % ┃ Avg Duration ┃ Win Draw Loss Win% ┃
┡━━━━━━━━━━━╇━━━━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━┩
│ │ roi │ 67 │ 1.05 │ 242.179 │ 24.22 │ 15:49:00 │ 67 0 0 100 │
│ │ exit_signal │ 4 │ -2.23 │ -31.217 │ -3.12 │ 1 day, 8:38:00 │ 0 0 4 0 │
│ │ force_exit │ 3 │ -4.56 │ -44.420 │ -4.44 │ 6 days, 2:03:00 │ 0 0 3 0 │
│ │ stop_loss │ 3 │ -10.14 │ -111.768 │ -11.18 │ 1 day, 3:05:00 │ 0 0 3 0 │
│ TOTAL │ │ 77 │ 0.22 │ 54.774 │ 5.48 │ 22:12:00 │ 67 0 10 87.0 │
└───────────┴─────────────┴────────┴──────────────┴─────────────────┴──────────────┴─────────────────┴────────────────────────┘
SUMMARY METRICS
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
┃ Metric ┃ Value ┃
┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┩
│ Backtesting from │ 2025-07-01 00:00:00 │
│ Backtesting to │ 2025-08-01 00:00:00 │
│ Trading Mode │ Isolated Futures │
│ Max open trades │ 3 │
│ │ │
│ Total/Daily Avg Trades │ 77 / 2.48 │
│ Starting balance │ 1000 USDT │
│ Final balance │ 1054.774 USDT │
│ Absolute profit │ 54.774 USDT │
│ Total profit % │ 5.48% │
│ CAGR % │ 87.36% │
│ Sortino │ 2.48 │
│ Sharpe │ 3.75 │
│ Calmar │ 40.99 │
│ SQN │ 0.69 │
│ Profit factor │ 1.29 │
│ Expectancy (Ratio) │ 0.71 (0.04) │
│ Avg. daily profit │ 1.767 USDT │
│ Avg. stake amount │ 345.016 USDT │
│ Total trade volume │ 53316.954 USDT │
│ │ │
│ Long / Short trades │ 67 / 10 │
│ Long / Short profit % │ 8.94% / -3.47% │
│ Long / Short profit USDT │ 89.425 / -34.651 │
│ │ │
│ Best Pair │ LTC/USDT:USDT 5.62% │
│ Worst Pair │ ADA/USDT:USDT -5.21% │
│ Best trade │ ETC/USDT:USDT 2.00% │
│ Worst trade │ ADA/USDT:USDT -10.17% │
│ Best day │ 26.91 USDT │
│ Worst day │ -47.741 USDT │
│ Days win/draw/lose │ 20 / 6 / 5 │
│ Min/Max/Avg. Duration Winners │ 0d 00:35 / 5d 18:15 / 0d 15:49 │
│ Min/Max/Avg. Duration Losers │ 0d 10:40 / 17d 08:00 / 2d 17:00 │
│ Max Consecutive Wins / Loss │ 36 / 3 │
│ Rejected Entry signals │ 258 │
│ Entry/Exit Timeouts │ 0 / 0 │
│ │ │
│ Min balance │ 1003.168 USDT │
│ Max balance │ 1149.421 USDT │
│ Max % of account underwater │ 8.23% │
│ Absolute drawdown │ 94.647 USDT (8.23%) │
│ Drawdown duration │ 9 days 08:50:00 │
│ Profit at drawdown start │ 149.421 USDT │
│ Profit at drawdown end │ 54.774 USDT │
│ Drawdown start │ 2025-07-22 15:10:00 │
│ Drawdown end │ 2025-08-01 00:00:00 │
│ Market change │ 30.51% │
└───────────────────────────────┴─────────────────────────────────┘
================== SUMMARY METRICS ==================
| Metric | Value |
|-----------------------------+---------------------|
| Backtesting from | 2019-01-01 00:00:00 |
| Backtesting to | 2019-05-01 00:00:00 |
| Trading Mode | Spot |
| Max open trades | 3 |
| | |
| Total/Daily Avg Trades | 429 / 3.575 |
| Starting balance | 0.01000000 BTC |
| Final balance | 0.01762792 BTC |
| Absolute profit | 0.00762792 BTC |
| Total profit % | 76.2% |
| CAGR % | 460.87% |
| Sortino | 1.88 |
| Sharpe | 2.97 |
| Calmar | 6.29 |
| SQN | 2.45 |
| Profit factor | 1.11 |
| Expectancy (Ratio) | -0.15 (-0.05) |
| Avg. stake amount | 0.001 BTC |
| Total trade volume | 0.429 BTC |
| | |
| Long / Short | 352 / 77 |
| Total profit Long % | 1250.58% |
| Total profit Short % | -15.02% |
| Absolute profit Long | 0.00838792 BTC |
| Absolute profit Short | -0.00076 BTC |
| | |
| Best Pair | LSK/BTC 26.26% |
| Worst Pair | ZEC/BTC -10.18% |
| Best Trade | LSK/BTC 4.25% |
| Worst Trade | ZEC/BTC -10.25% |
| Best day | 0.00076 BTC |
| Worst day | -0.00036 BTC |
| Days win/draw/lose | 12 / 82 / 25 |
| Avg. Duration Winners | 4:23:00 |
| Avg. Duration Loser | 6:55:00 |
| Max Consecutive Wins / Loss | 3 / 4 |
| Rejected Entry signals | 3089 |
| Entry/Exit Timeouts | 0 / 0 |
| Canceled Trade Entries | 34 |
| Canceled Entry Orders | 123 |
| Replaced Entry Orders | 89 |
| | |
| Min balance | 0.00945123 BTC |
| Max balance | 0.01846651 BTC |
| Max % of account underwater | 25.19% |
| Absolute Drawdown (Account) | 13.33% |
| Drawdown | 0.0015 BTC |
| Drawdown high | 0.0013 BTC |
| Drawdown low | -0.0002 BTC |
| Drawdown Start | 2019-02-15 14:10:00 |
| Drawdown End | 2019-04-11 18:15:00 |
| Market change | -5.88% |
=====================================================
Backtested 2025-07-01 00:00:00 -> 2025-08-01 00:00:00 | Max open trades : 3
STRATEGY SUMMARY
┏━━━━━━━━━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━┓
┃ Strategy ┃ Trades ┃ Avg Profit % ┃ Tot Profit USDT ┃ Tot Profit % ┃ Avg Duration ┃ Win Draw Loss Win% ┃ Drawdown ┃
┡━━━━━━━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━┩
│ SampleStrategy │ 77 │ 0.22 │ 54.774 │ 5.48 │ 22:12:00 │ 67 0 10 87.0 │ 94.647 USDT 8.23% │
└────────────────┴────────┴──────────────┴─────────────────┴──────────────┴──────────────┴────────────────────────┴────────────────────┘
```
### Backtesting report table
The 1st table contains all trades the bot made, including "left open trades".
The first table contains all trades the bot made, including "left open trades".
The last line will give you the overall performance of your strategy,
here:
```
| TOTAL | 429 | 0.36 | 152.41 | 0.00762792 | 76.20 | 4:12:00 | 186 0 243 43.4 |
│ TOTAL │ 77 │ 0.22 │ 54.774 │ 5.48 │ 22:12:00 │ 67 0 10 87.0 │
```
The bot has made `429` trades for an average duration of `4:12:00`, with a performance of `76.20%` (profit), that means it has
earned a total of `0.00762792 BTC` starting with a capital of 0.01 BTC.
The bot has made `77` trades for an average duration of `22:12:00`, with a performance of `5.48%` (profit), that means it has earned a total of `54.774 USDT` starting with a capital of 1000 USDT.
The column `Avg Profit %` shows the average profit for all trades made.
The column `Tot Profit %` shows instead the total profit % in relation to the starting balance.
In the above results, we have a starting balance of 0.01 BTC and an absolute profit of 0.00762792 BTC - so the `Tot Profit %` will be `(0.00762792 / 0.01) * 100 ~= 76.2%`.
In the above results, we have a starting balance of 1000 USDT and an absolute profit of 54.774 USDT - so the `Tot Profit %` will be `(54.774 / 1000) * 100 ~= 5.48%`.
Your strategy performance is influenced by your entry strategy, your exit strategy, and also by the `minimal_roi` and `stop_loss` you have set.
@@ -284,86 +305,83 @@ On the other hand, if you set a too high `minimal_roi` like `"0": 0.55`
(55%), there is almost no chance that the bot will ever reach this profit.
Hence, keep in mind that your performance is an integral mix of all different elements of the strategy, your configuration, and the crypto-currency pairs you have set up.
### Exit reasons table
The 2nd table contains a recap of exit reasons.
This table can tell you which area needs some additional work (e.g. all or many of the `exit_signal` trades are losses, so you should work on improving the exit signal, or consider disabling it).
### Left open trades table
The 3rd table contains all trades the bot had to `force_exit` at the end of the backtesting period to present you the full picture.
The second table contains all trades the bot had to `force_exit` at the end of the backtesting period to present you the full picture.
This is necessary to simulate realistic behavior, since the backtest period has to end at some point, while realistically, you could leave the bot running forever.
These trades are also included in the first table, but are also shown separately in this table for clarity.
### Enter tag stats table
The third table provides a breakdown of trades by their entry tags (e.g., `enter_long`, `enter_short`), showing the number of entries, average profit percentage, total profit in the stake currency, total profit percentage, average duration, and the number of wins, draws, and losses for each tag.
### Exit reason stats table
The fourth table contains a recap of exit reasons (e.g., `exit_signal`, `roi`, `stop_loss`, `force_exit`). This table can tell you which area needs additional work (e.g., if many `exit_signal` trades are losses, you should work on improving the exit signal or consider disabling it).
### Mixed tag stats table
The fifth table combines entry tags and exit reasons, providing a detailed view of how different entry tags performed with specific exit reasons. This can help identify which combinations of entry and exit strategies are most effective.
### Summary metrics
The last element of the backtest report is the summary metrics table.
It contains some useful key metrics about performance of your strategy on backtesting data.
It contains key metrics about the performance of your strategy on backtesting data.
```
================== SUMMARY METRICS ==================
| Metric | Value |
|-----------------------------+---------------------|
| Backtesting from | 2019-01-01 00:00:00 |
| Backtesting to | 2019-05-01 00:00:00 |
| Trading Mode | Spot |
| Max open trades | 3 |
| | |
| Total/Daily Avg Trades | 429 / 3.575 |
| Starting balance | 0.01000000 BTC |
| Final balance | 0.01762792 BTC |
| Absolute profit | 0.00762792 BTC |
| Total profit % | 76.2% |
| CAGR % | 460.87% |
| Sortino | 1.88 |
| Sharpe | 2.97 |
| Calmar | 6.29 |
| SQN | 2.45 |
| Profit factor | 1.11 |
| Expectancy (Ratio) | -0.15 (-0.05) |
| Avg. daily profit | 0.0001 BTC |
| Avg. stake amount | 0.001 BTC |
| Total trade volume | 0.429 BTC |
| | |
| Long / Short | 352 / 77 |
| Total profit Long % | 1250.58% |
| Total profit Short % | -15.02% |
| Absolute profit Long | 0.00838792 BTC |
| Absolute profit Short | -0.00076 BTC |
| | |
| Best Pair | LSK/BTC 26.26% |
| Worst Pair | ZEC/BTC -10.18% |
| Best Trade | LSK/BTC 4.25% |
| Worst Trade | ZEC/BTC -10.25% |
| Best day | 0.00076 BTC |
| Worst day | -0.00036 BTC |
| Days win/draw/lose | 12 / 82 / 25 |
| Avg. Duration Winners | 4:23:00 |
| Avg. Duration Loser | 6:55:00 |
| Max Consecutive Wins / Loss | 3 / 4 |
| Rejected Entry signals | 3089 |
| Entry/Exit Timeouts | 0 / 0 |
| Canceled Trade Entries | 34 |
| Canceled Entry Orders | 123 |
| Replaced Entry Orders | 89 |
| | |
| Min balance | 0.00945123 BTC |
| Max balance | 0.01846651 BTC |
| Max % of account underwater | 25.19% |
| Absolute Drawdown (Account) | 13.33% |
| Drawdown | 0.0015 BTC |
| Drawdown high | 0.0013 BTC |
| Drawdown low | -0.0002 BTC |
| Drawdown Start | 2019-02-15 14:10:00 |
| Drawdown End | 2019-04-11 18:15:00 |
| Market change | -5.88% |
=====================================================
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
┃ Metric ┃ Value ┃
┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┩
│ Backtesting from │ 2025-07-01 00:00:00 │
│ Backtesting to │ 2025-08-01 00:00:00 │
│ Trading Mode │ Isolated Futures │
│ Max open trades │ 3 │
│ │ │
│ Total/Daily Avg Trades │ 72 / 2.32 │
│ Starting balance │ 1000 USDT │
│ Final balance │ 1106.734 USDT │
│ Absolute profit │ 106.734 USDT │
│ Total profit % │ 10.67% │
│ CAGR % │ 230.04% │
│ Sortino │ 4.99 │
│ Sharpe │ 8.00 │
│ Calmar │ 77.76 │
│ SQN │ 1.52 │
│ Profit factor │ 1.79 │
│ Expectancy (Ratio) │ 1.48 (0.07) │
│ Avg. daily profit │ 3.443 USDT │
│ Avg. stake amount │ 363.133 USDT │
│ Total trade volume │ 52466.174 USDT │
│ │ │
│ Best Pair │ LTC/USDT:USDT 4.48% │
│ Worst Pair │ ADA/USDT:USDT -1.78% │
│ Best trade │ ETC/USDT:USDT 2.00% │
│ Worst trade │ ADA/USDT:USDT -10.17% │
│ Best day │ 23.535 USDT │
│ Worst day │ -49.813 USDT │
│ Days win/draw/lose │ 21 / 6 / 4 │
│ Min/Max/Avg. Duration Winners │ 0d 00:35 / 5d 18:15 / 0d 15:30 │
│ Min/Max/Avg. Duration Losers │ 0d 12:00 / 17d 08:00 / 3d 23:28 │
│ Max Consecutive Wins / Loss │ 58 / 4 │
│ Rejected Entry signals │ 254 │
│ Entry/Exit Timeouts │ 0 / 0 │
│ │ │
│ Min balance │ 1003.168 USDT │
│ Max balance │ 1209 USDT │
│ Max % of account underwater │ 8.46% │
│ Absolute drawdown │ 102.266 USDT (8.46%) │
│ Drawdown duration │ 9 days 08:50:00 │
│ Profit at drawdown start │ 209 USDT │
│ Profit at drawdown end │ 106.734 USDT │
│ Drawdown start │ 2025-07-22 15:10:00 │
│ Drawdown end │ 2025-08-01 00:00:00 │
│ Market change │ 30.51% │
└───────────────────────────────┴─────────────────────────────────┘
```
- `Backtesting from` / `Backtesting to`: Backtesting range (usually defined with the `--timerange` option).
- `Max open trades`: Setting of `max_open_trades` (or `--max-open-trades`) - or number of pairs in the pairlist (whatever is lower).
- `Trading Mode`: Spot or Futures trading.
- `Max open trades`: Setting of `max_open_trades` (or `--max-open-trades`) - or number of pairs in the pairlist (whatever is lower).
- `Total/Daily Avg Trades`: Identical to the total trades of the backtest output table / Total trades divided by the backtesting duration in days (this will give you information about how many trades to expect from the strategy).
- `Starting balance`: Start balance - as given by dry-run-wallet (config or command line).
- `Final balance`: Final balance - starting balance + absolute profit.
@@ -374,58 +392,71 @@ It contains some useful key metrics about performance of your strategy on backte
- `Sharpe`: Annualized Sharpe ratio.
- `Calmar`: Annualized Calmar ratio.
- `SQN`: System Quality Number (SQN) - by Van Tharp.
- `Profit factor`: profit / loss.
- `Profit factor`: Sum of the profits of all winning trades divided by the sum of the losses of all losing trades.
- `Expectancy (Ratio)`: Expectancy ratio, which is the average profit or loss per trade. A negative expectancy ratio means that your strategy is not profitable.
- `Avg. daily profit`: Average profit per day, calculated as `(Total Profit / Backtest Days)`.
- `Avg. stake amount`: Average stake amount, either `stake_amount` or the average when using dynamic stake amount.
- `Total trade volume`: Volume generated on the exchange to reach the above profit.
- `Best Pair` / `Worst Pair`: Best and worst performing pair (based on absolute profit), and it's corresponding `Tot Profit %`.
- `Best Trade` / `Worst Trade`: Biggest single winning trade and biggest single losing trade.
- `Long / Short trades`: Split long/short trade counts (only shown when short trades were made).
- `Long / Short profit %`: Profit percentage for long and short trades (only shown when short trades were made).
- `Long / Short profit USDT`: Profit in stake currency for long and short trades (only shown when short trades were made).
- `Best Pair` / `Worst Pair`: Best and worst performing pair (based on total profit percentage), and its corresponding `Tot Profit %`.
- `Best trade` / `Worst trade`: Biggest single winning trade and biggest single losing trade.
- `Best day` / `Worst day`: Best and worst day based on daily profit.
- `Days win/draw/lose`: Winning / Losing days (draws are usually days without closed trade).
- `Avg. Duration Winners` / `Avg. Duration Loser`: Average durations for winning and losing trades.
- `Days win/draw/lose`: Winning / Losing days (draws are usually days without closed trades).
- `Min/Max/Avg. Duration Winners`: Minimum, maximum, and average durations for winning trades.
- `Min/Max/Avg. Duration Losers`: Minimum, maximum, and average durations for losing trades.
- `Max Consecutive Wins / Loss`: Maximum consecutive wins/losses in a row.
- `Rejected Entry signals`: Trade entry signals that could not be acted upon due to `max_open_trades` being reached.
- `Entry/Exit Timeouts`: Entry/exit orders which did not fill (only applicable if custom pricing is used).
- `Canceled Trade Entries`: Number of trades that have been canceled by user request via `adjust_entry_price`.
- `Canceled Entry Orders`: Number of entry orders that have been canceled by user request via `adjust_entry_price`.
- `Replaced Entry Orders`: Number of entry orders that have been replaced by user request via `adjust_entry_price`.
- `Min balance` / `Max balance`: Lowest and Highest Wallet balance during the backtest period.
- `Max % of account underwater`: Maximum percentage your account has decreased from the top since the simulation started.
Calculated as the maximum of `(Max Balance - Current Balance) / (Max Balance)`.
- `Absolute Drawdown (Account)`: Maximum Account Drawdown experienced. Calculated as `(Absolute Drawdown) / (DrawdownHigh + startingBalance)`.
- `Drawdown`: Maximum, absolute drawdown experienced. Difference between Drawdown High and Subsequent Low point.
- `Drawdown high` / `Drawdown low`: Profit at the beginning and end of the largest drawdown period. A negative low value means initial capital lost.
- `Drawdown Start` / `Drawdown End`: Start and end datetime for this largest drawdown (can also be visualized via the `plot-dataframe` sub-command).
- `Market change`: Change of the market during the backtest period. Calculated as average of all pairs changes from the first to the last candle using the "close" column.
- `Long / Short`: Split long/short values (Only shown when short trades were made).
- `Total profit Long %` / `Absolute profit Long`: Profit long trades only (Only shown when short trades were made).
- `Total profit Short %` / `Absolute profit Short`: Profit short trades only (Only shown when short trades were made).
- `Max % of account underwater`: Maximum percentage your account has decreased from the top since the simulation started. Calculated as the maximum of `(Max Balance - Current Balance) / (Max Balance)`.
- `Absolute drawdown`: Maximum absolute drawdown experienced, including percentage relative to the account calculated as `(Absolute Drawdown) / (DrawdownHigh + startingBalance)`..
- `Drawdown duration`: Duration of the largest drawdown period.
- `Profit at drawdown start` / `Profit at drawdown end`: Profit at the beginning and end of the largest drawdown period.
- `Drawdown start` / `Drawdown end`: Start and end datetime for the largest drawdown (can also be visualized via the `plot-dataframe` sub-command).
- `Market change`: Change of the market during the backtest period. Calculated as the average of all pairs' changes from the first to the last candle using the "close" column.
### Daily / Weekly / Monthly breakdown
### Daily / Weekly / Monthly / Yearly breakdown
You can get an overview over daily / weekly or monthly results by using the `--breakdown <>` switch.
You can get an overview over daily, weekly, monthly, or yearly results by using the `--breakdown <>` switch.
To visualize daily and weekly breakdowns, you can use the following:
To visualize monthly and yearly breakdowns, you can use the following:
``` bash
freqtrade backtesting --strategy MyAwesomeStrategy --breakdown day week
freqtrade backtesting --strategy MyAwesomeStrategy --breakdown month year
```
``` output
======================== DAY BREAKDOWN =========================
| Day | Tot Profit USDT | Wins | Draws | Losses |
|------------+-------------------+--------+---------+----------|
| 03/07/2021 | 200.0 | 2 | 0 | 0 |
| 04/07/2021 | -50.31 | 0 | 0 | 2 |
| 05/07/2021 | 220.611 | 3 | 2 | 0 |
| 06/07/2021 | 150.974 | 3 | 0 | 2 |
| 07/07/2021 | -70.193 | 1 | 0 | 2 |
| 08/07/2021 | 212.413 | 2 | 0 | 3 |
MONTH BREAKDOWN
┏━━━━━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┓
┃ Month ┃ Trades ┃ Tot Profit USDT ┃ Profit Factor ┃ Win Draw Loss Win% ┃
┡━━━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━┩
│ 31/01/2020 │ 12 │ 44.451 │ 7.28 │ 10 0 2 83.3 │
│ 29/02/2020 │ 30 │ 45.41 │ 2.36 │ 17 0 13 56.7 │
│ 31/03/2020 │ 35 │ 142.024 │ 2.42 │ 14 0 21 40.0 │
│ 30/04/2020 │ 67 │ -23.692 │ 0.81 │ 24 0 43 35.8 │
...
...
│ 30/04/2025 │ 203 │ -63.43 │ 0.81 │ 73 0 130 36.0 │
│ 31/05/2025 │ 142 │ 104.675 │ 1.28 │ 59 0 83 41.5 │
│ 30/06/2025 │ 177 │ -1.014 │ 1.0 │ 85 0 92 48.0 │
│ 31/07/2025 │ 155 │ 232.762 │ 1.6 │ 63 0 92 40.6 │
└────────────┴────────┴─────────────────┴───────────────┴────────────────────────┘
YEAR BREAKDOWN
┏━━━━━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┓
┃ Year ┃ Trades ┃ Tot Profit USDT ┃ Profit Factor ┃ Win Draw Loss Win% ┃
┡━━━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━┩
│ 31/12/2020 │ 896 │ 868.889 │ 1.46 │ 351 0 545 39.2 │
│ 31/12/2021 │ 1778 │ 4487.163 │ 1.93 │ 745 0 1033 41.9 │
│ 31/12/2022 │ 1736 │ 938.27 │ 1.27 │ 698 0 1038 40.2 │
│ 31/12/2023 │ 1712 │ 1677.126 │ 1.68 │ 670 0 1042 39.1 │
│ 31/12/2024 │ 1609 │ 3198.424 │ 2.22 │ 773 0 836 48.0 │
│ 31/12/2025 │ 1042 │ 716.174 │ 1.33 │ 420 0 622 40.3 │
└────────────┴────────┴─────────────────┴───────────────┴────────────────────────┘
```
The output will show a table containing the realized absolute Profit (in stake currency) for the given timeperiod, as well as wins, draws and losses that materialized (closed) on this day. Below that there will be a second table for the summarized values of weeks indicated by the date of the closing Sunday. The same would apply to a monthly breakdown indicated by the last day of the month.
The output will display tables containing the realized absolute profit (in stake currency) for the selected period, along with additional statistics such as number of trades, profit factor, and distribution of wins, draws, and losses that materialized (closed) on this period.
### Backtest result caching
@@ -449,10 +480,10 @@ For this mode - `--notes "<notes>"` can be used to add notes to the backtest res
The output file freqtrade produces is a zip file containing the following files:
- The backtest report in json format
- the market change data in feather format
- a copy of the strategy file
- a copy of the strategy parameters (if a parameter file was used)
- a sanitized copy of the config file
- The market change data in feather format
- A copy of the strategy file
- A copy of the strategy parameters (if a parameter file was used)
- A sanitized copy of the config file
This will ensure results are reproducible - under the assumption that the same data is available.
@@ -470,7 +501,7 @@ Since backtesting lacks some detailed information about what happens within a ca
- Exit-signal is favored over Stoploss, because exit-signals are assumed to trigger on candle's open
- ROI
- Exits are compared to high - but the ROI value is used (e.g. ROI = 2%, high=5% - so the exit will be at 2%)
- Exits are never "below the candle", so a ROI of 2% may result in a exit at 2.4% if low was at 2.4% profit
- Exits are never "below the candle", so a ROI of 2% may result in an exit at 2.4% if low was at 2.4% profit
- ROI entries which came into effect on the triggering candle (e.g. `120: 0.02` for 1h candles, from `60: 0.05`) will use the candle's open as exit rate
- Force-exits caused by `<N>=-1` ROI entries use low as exit value, unless N falls on the candle open (e.g. `120: -1` for 1h candles)
- Stoploss exits happen exactly at stoploss price, even if low was lower, but the loss will be `2 * fees` higher than the stoploss price
@@ -536,7 +567,7 @@ freqtrade backtesting --strategy AwesomeStrategy --timeframe 1h --timeframe-deta
This will load 1h data (the main timeframe) as well as 5m data (detail timeframe) for the selected timerange.
The strategy will be analyzed with the 1h timeframe.
Candles where activity may take place (there's an active signal, the pair is in a trade) are evaluated at the 5m timeframe.
Candles where activity may take place (there's an active signal, the pair is in a trade) are evaluated at the 5m timeframe.
This will allow for a more accurate simulation of intra-candle movements - and can lead to different results, especially on higher timeframes.
Entries will generally still happen at the main candle's open, however freed trade slots may be freed earlier (if the exit signal is triggered on the 5m candle), which can then be used for a new trade of a different pair.
@@ -599,5 +630,5 @@ Detailed output for all strategies one after the other will be available, so mak
## Next step
Great, your strategy is profitable. What if the bot can give your the optimal parameters to use for your strategy?
Great, your strategy is profitable. What if the bot can give you the optimal parameters to use for your strategy?
Your next step is to learn [how to find optimal parameters with Hyperopt](hyperopt.md)

16
docs/commands/backtesting-analysis.md
View File

@@ -2,7 +2,8 @@
usage: freqtrade backtesting-analysis [-h] [-v] [--no-color] [--logfile FILE]
[-V] [-c PATH] [-d PATH]
[--userdir PATH]
[--export-filename PATH]
[--backtest-filename PATH]
[--backtest-directory PATH]
[--analysis-groups {0,1,2,3,4,5} [{0,1,2,3,4,5} ...]]
[--enter-reason-list ENTER_REASON_LIST [ENTER_REASON_LIST ...]]
[--exit-reason-list EXIT_REASON_LIST [EXIT_REASON_LIST ...]]
@@ -14,10 +15,15 @@ usage: freqtrade backtesting-analysis [-h] [-v] [--no-color] [--logfile FILE]
options:
-h, --help show this help message and exit
--export-filename PATH, --backtest-filename PATH
Use this filename for backtest results.Requires
`--export` to be set as well. Example: `--export-filen
ame=user_data/backtest_results/backtest_today.json`
--backtest-filename PATH, --export-filename PATH
Use this filename for backtest results.Example:
`--backtest-
filename=backtest_results_2020-09-27_16-20-48.json`.
Assumes either `user_data/backtest_results/` or
`--export-directory` as base directory.
--backtest-directory PATH, --export-directory PATH
Directory to use for backtest results. Example:
`--export-directory=user_data/backtest_results/`.
--analysis-groups {0,1,2,3,4,5} [{0,1,2,3,4,5} ...]
grouping output - 0: simple wins/losses by enter tag,
1: by enter_tag, 2: by enter_tag and exit_tag, 3: by

23
docs/commands/backtesting-show.md
View File

@@ -1,19 +1,26 @@
```
usage: freqtrade backtesting-show [-h] [-v] [--no-color] [--logfile FILE] [-V]
[-c PATH] [-d PATH] [--userdir PATH]
[--export-filename PATH] [--show-pair-list]
[--breakdown {day,week,month,year} [{day,week,month,year} ...]]
[--backtest-filename PATH]
[--backtest-directory PATH]
[--show-pair-list]
[--breakdown {day,week,month,year,weekday} [{day,week,month,year,weekday} ...]]
options:
-h, --help show this help message and exit
--export-filename PATH, --backtest-filename PATH
Use this filename for backtest results.Requires
`--export` to be set as well. Example: `--export-filen
ame=user_data/backtest_results/backtest_today.json`
--backtest-filename PATH, --export-filename PATH
Use this filename for backtest results.Example:
`--backtest-
filename=backtest_results_2020-09-27_16-20-48.json`.
Assumes either `user_data/backtest_results/` or
`--export-directory` as base directory.
--backtest-directory PATH, --export-directory PATH
Directory to use for backtest results. Example:
`--export-directory=user_data/backtest_results/`.
--show-pair-list Show backtesting pairlist sorted by profit.
--breakdown {day,week,month,year} [{day,week,month,year} ...]
--breakdown {day,week,month,year,weekday} [{day,week,month,year,weekday} ...]
Show backtesting breakdown per [day, week, month,
year].
year, weekday].
Common arguments:
-v, --verbose Verbose mode (-vv for more, -vvv to get all messages).

30
docs/commands/backtesting.md
View File

@@ -10,12 +10,14 @@ usage: freqtrade backtesting [-h] [-v] [--no-color] [--logfile FILE] [-V]
[--stake-amount STAKE_AMOUNT] [--fee FLOAT]
[-p PAIRS [PAIRS ...]] [--eps]
[--enable-protections]
[--enable-dynamic-pairlist]
[--dry-run-wallet DRY_RUN_WALLET]
[--timeframe-detail TIMEFRAME_DETAIL]
[--strategy-list STRATEGY_LIST [STRATEGY_LIST ...]]
[--export {none,trades,signals}]
[--export-filename PATH]
[--breakdown {day,week,month,year} [{day,week,month,year} ...]]
[--backtest-filename PATH]
[--backtest-directory PATH]
[--breakdown {day,week,month,year,weekday} [{day,week,month,year,weekday} ...]]
[--cache {none,day,week,month}]
[--freqai-backtest-live-models] [--notes TEXT]
@@ -43,9 +45,14 @@ options:
Allow buying the same pair multiple times (position
stacking).
--enable-protections, --enableprotections
Enable protections for backtesting.Will slow
Enable protections for backtesting. Will slow
backtesting down by a considerable amount, but will
include configured protections
--enable-dynamic-pairlist
Enables dynamic pairlist refreshes in backtesting. The
pairlist will be generated for each new candle if
you're using a pairlist handler that supports this
feature, for example, ShuffleFilter.
--dry-run-wallet DRY_RUN_WALLET, --starting-balance DRY_RUN_WALLET
Starting balance, used for backtesting / hyperopt and
dry-runs.
@@ -61,13 +68,18 @@ options:
becomes `backtest-data-SampleStrategy.json`
--export {none,trades,signals}
Export backtest results (default: trades).
--export-filename PATH, --backtest-filename PATH
Use this filename for backtest results.Requires
`--export` to be set as well. Example: `--export-filen
ame=user_data/backtest_results/backtest_today.json`
--breakdown {day,week,month,year} [{day,week,month,year} ...]
--backtest-filename PATH, --export-filename PATH
Use this filename for backtest results.Example:
`--backtest-
filename=backtest_results_2020-09-27_16-20-48.json`.
Assumes either `user_data/backtest_results/` or
`--export-directory` as base directory.
--backtest-directory PATH, --export-directory PATH
Directory to use for backtest results. Example:
`--export-directory=user_data/backtest_results/`.
--breakdown {day,week,month,year,weekday} [{day,week,month,year,weekday} ...]
Show backtesting breakdown per [day, week, month,
year].
year, weekday].
--cache {none,day,week,month}
Load a cached backtest result no older than specified
age (default: day).

4
docs/commands/download-data.md
View File

@@ -4,6 +4,7 @@ usage: freqtrade download-data [-h] [-v] [--no-color] [--logfile FILE] [-V]
[-p PAIRS [PAIRS ...]] [--pairs-file FILE]
[--days INT] [--new-pairs-days INT]
[--include-inactive-pairs]
[--no-parallel-download]
[--timerange TIMERANGE] [--dl-trades]
[--convert] [--exchange EXCHANGE]
[-t TIMEFRAMES [TIMEFRAMES ...]] [--erase]
@@ -24,6 +25,9 @@ options:
Default: `None`.
--include-inactive-pairs
Also download data from inactive pairs.
--no-parallel-download
Disable parallel startup download. Only use this if
you experience issues.
--timerange TIMERANGE
Specify what timerange of data to use.
--dl-trades Download trades instead of OHLCV data.

6
docs/commands/hyperopt-show.md
View File

@@ -4,7 +4,7 @@ usage: freqtrade hyperopt-show [-h] [-v] [--no-color] [--logfile FILE] [-V]
[--profitable] [-n INT] [--print-json]
[--hyperopt-filename FILENAME] [--no-header]
[--disable-param-export]
[--breakdown {day,week,month,year} [{day,week,month,year} ...]]
[--breakdown {day,week,month,year,weekday} [{day,week,month,year,weekday} ...]]
options:
-h, --help show this help message and exit
@@ -18,9 +18,9 @@ options:
--no-header Do not print epoch details header.
--disable-param-export
Disable automatic hyperopt parameter export.
--breakdown {day,week,month,year} [{day,week,month,year} ...]
--breakdown {day,week,month,year,weekday} [{day,week,month,year,weekday} ...]
Show backtesting breakdown per [day, week, month,
year].
year, weekday].
Common arguments:
-v, --verbose Verbose mode (-vv for more, -vvv to get all messages).

2
docs/commands/hyperopt.md
View File

@@ -44,7 +44,7 @@ options:
Allow buying the same pair multiple times (position
stacking).
--enable-protections, --enableprotections
Enable protections for backtesting.Will slow
Enable protections for backtesting. Will slow
backtesting down by a considerable amount, but will
include configured protections
--dry-run-wallet DRY_RUN_WALLET, --starting-balance DRY_RUN_WALLET

27
docs/commands/lookahead-analysis.md
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@@ -11,15 +11,18 @@ usage: freqtrade lookahead-analysis [-h] [-v] [--no-color] [--logfile FILE]
[--stake-amount STAKE_AMOUNT]
[--fee FLOAT] [-p PAIRS [PAIRS ...]]
[--enable-protections]
[--enable-dynamic-pairlist]
[--dry-run-wallet DRY_RUN_WALLET]
[--timeframe-detail TIMEFRAME_DETAIL]
[--strategy-list STRATEGY_LIST [STRATEGY_LIST ...]]
[--export {none,trades,signals}]
[--export-filename PATH]
[--backtest-filename PATH]
[--backtest-directory PATH]
[--freqai-backtest-live-models]
[--minimum-trade-amount INT]
[--targeted-trade-amount INT]
[--lookahead-analysis-exportfilename LOOKAHEAD_ANALYSIS_EXPORTFILENAME]
[--allow-limit-orders]
options:
-h, --help show this help message and exit
@@ -42,9 +45,14 @@ options:
Limit command to these pairs. Pairs are space-
separated.
--enable-protections, --enableprotections
Enable protections for backtesting.Will slow
Enable protections for backtesting. Will slow
backtesting down by a considerable amount, but will
include configured protections
--enable-dynamic-pairlist
Enables dynamic pairlist refreshes in backtesting. The
pairlist will be generated for each new candle if
you're using a pairlist handler that supports this
feature, for example, ShuffleFilter.
--dry-run-wallet DRY_RUN_WALLET, --starting-balance DRY_RUN_WALLET
Starting balance, used for backtesting / hyperopt and
dry-runs.
@@ -60,10 +68,15 @@ options:
becomes `backtest-data-SampleStrategy.json`
--export {none,trades,signals}
Export backtest results (default: trades).
--export-filename PATH, --backtest-filename PATH
Use this filename for backtest results.Requires
`--export` to be set as well. Example: `--export-filen
ame=user_data/backtest_results/backtest_today.json`
--backtest-filename PATH, --export-filename PATH
Use this filename for backtest results.Example:
`--backtest-
filename=backtest_results_2020-09-27_16-20-48.json`.
Assumes either `user_data/backtest_results/` or
`--export-directory` as base directory.
--backtest-directory PATH, --export-directory PATH
Directory to use for backtest results. Example:
`--export-directory=user_data/backtest_results/`.
--freqai-backtest-live-models
Run backtest with ready models.
--minimum-trade-amount INT
@@ -73,6 +86,8 @@ options:
--lookahead-analysis-exportfilename LOOKAHEAD_ANALYSIS_EXPORTFILENAME
Use this csv-filename to store lookahead-analysis-
results
--allow-limit-orders Allow limit orders in lookahead analysis (could cause
false positives in lookahead analysis results).
Common arguments:
-v, --verbose Verbose mode (-vv for more, -vvv to get all messages).

12
docs/commands/plot-dataframe.md
View File

@@ -10,7 +10,7 @@ usage: freqtrade plot-dataframe [-h] [-v] [--no-color] [--logfile FILE] [-V]
[--plot-limit INT] [--db-url PATH]
[--trade-source {DB,file}]
[--export {none,trades,signals}]
[--export-filename PATH]
[--backtest-filename PATH]
[--timerange TIMERANGE] [-i TIMEFRAME]
[--no-trades]
@@ -38,10 +38,12 @@ options:
(backtest file)) Default: file
--export {none,trades,signals}
Export backtest results (default: trades).
--export-filename PATH, --backtest-filename PATH
Use this filename for backtest results.Requires
`--export` to be set as well. Example: `--export-filen
ame=user_data/backtest_results/backtest_today.json`
--backtest-filename PATH, --export-filename PATH
Use this filename for backtest results.Example:
`--backtest-
filename=backtest_results_2020-09-27_16-20-48.json`.
Assumes either `user_data/backtest_results/` or
`--export-directory` as base directory.
--timerange TIMERANGE
Specify what timerange of data to use.
-i TIMEFRAME, --timeframe TIMEFRAME

12
docs/commands/plot-profit.md
View File

@@ -6,7 +6,7 @@ usage: freqtrade plot-profit [-h] [-v] [--no-color] [--logfile FILE] [-V]
[--freqaimodel NAME] [--freqaimodel-path PATH]
[-p PAIRS [PAIRS ...]] [--timerange TIMERANGE]
[--export {none,trades,signals}]
[--export-filename PATH] [--db-url PATH]
[--backtest-filename PATH] [--db-url PATH]
[--trade-source {DB,file}] [-i TIMEFRAME]
[--auto-open]
@@ -19,10 +19,12 @@ options:
Specify what timerange of data to use.
--export {none,trades,signals}
Export backtest results (default: trades).
--export-filename PATH, --backtest-filename PATH
Use this filename for backtest results.Requires
`--export` to be set as well. Example: `--export-filen
ame=user_data/backtest_results/backtest_today.json`
--backtest-filename PATH, --export-filename PATH
Use this filename for backtest results.Example:
`--backtest-
filename=backtest_results_2020-09-27_16-20-48.json`.
Assumes either `user_data/backtest_results/` or
`--export-directory` as base directory.
--db-url PATH Override trades database URL, this is useful in custom
deployments (default: `sqlite:///tradesv3.sqlite` for
Live Run mode, `sqlite:///tradesv3.dryrun.sqlite` for

19
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View File

@@ -566,14 +566,12 @@ Configuration:
### Understand order_time_in_force
The `order_time_in_force` configuration parameter defines the policy by which the order
is executed on the exchange. Three commonly used time in force are:
The `order_time_in_force` configuration parameter defines the policy by which the order is executed on the exchange.
Commonly used time in force are:
**GTC (Good Till Canceled):**
This is most of the time the default time in force. It means the order will remain
on exchange till it is cancelled by the user. It can be fully or partially fulfilled.
If partially fulfilled, the remaining will stay on the exchange till cancelled.
This is most of the time the default time in force. It means the order will remain on exchange till it is cancelled by the user. It can be fully or partially fulfilled. If partially fulfilled, the remaining will stay on the exchange till cancelled.
**FOK (Fill Or Kill):**
@@ -581,19 +579,22 @@ It means if the order is not executed immediately AND fully then it is cancelled
**IOC (Immediate Or Canceled):**
It is the same as FOK (above) except it can be partially fulfilled. The remaining part
is automatically cancelled by the exchange.
It is the same as FOK (above) except it can be partially fulfilled. The remaining part is automatically cancelled by the exchange.
Not necessarily recommended, as this can lead to partial fills below the minimum trade size.
**PO (Post only):**
Post only order. The order is either placed as a maker order, or it is canceled.
This means the order must be placed on orderbook for at least time in an unfilled state.
Please check the [Exchange documentation](exchanges.md) for supported time in force values for your exchange.
#### time_in_force config
The `order_time_in_force` parameter contains a dict with entry and exit time in force policy values.
This can be set in the configuration file or in the strategy.
Values set in the configuration file overwrites values set in the strategy.
Values set in the configuration file overwrite values from in the strategy, following the regular [precedence rules](#configuration-option-prevalence).
The possible values are: `GTC` (default), `FOK` or `IOC`.
@@ -605,9 +606,9 @@ The possible values are: `GTC` (default), `FOK` or `IOC`.
```
!!! Warning
This is ongoing work. For now, it is supported only for binance, gate and kucoin.
Please don't change the default value unless you know what you are doing and have researched the impact of using different values for your particular exchange.
### Fiat conversion
Freqtrade uses the Coingecko API to convert the coin value to it's corresponding fiat value for the Telegram reports.

17
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@@ -408,6 +408,22 @@ jupyter nbconvert --ClearOutputPreprocessor.enabled=True --inplace freqtrade/tem
jupyter nbconvert --ClearOutputPreprocessor.enabled=True --to markdown freqtrade/templates/strategy_analysis_example.ipynb --stdout > docs/strategy_analysis_example.md
```
## Backtest documentation results
To generate backtest outputs, please use the following commands:
``` bash
# Assume a dedicated user directory for this output
freqtrade create-userdir --userdir user_data_bttest/
# set can_short = True
sed -i "s/can_short: bool = False/can_short: bool = True/" user_data_bttest/strategies/sample_strategy.py
freqtrade download-data --timerange 20250625-20250801 --config tests/testdata/config.tests.usdt.json --userdir user_data_bttest/ -t 5m
freqtrade backtesting --config tests/testdata/config.tests.usdt.json -s SampleStrategy --userdir user_data_bttest/ --cache none --timerange 20250701-20250801
```
## Continuous integration
This documents some decisions taken for the CI Pipeline.
@@ -418,7 +434,6 @@ This documents some decisions taken for the CI Pipeline.
* Docker images contain a file, `/freqtrade/freqtrade_commit` containing the commit this image is based of.
* Full docker image rebuilds are run once a week via schedule.
* Deployments run on ubuntu.
* ta-lib binaries are contained in the build_helpers directory to avoid fails related to external unavailability.
* All tests must pass for a PR to be merged to `stable` or `develop`.
## Creating a release

50
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@@ -2,6 +2,10 @@
This page combines common gotchas and Information which are exchange-specific and most likely don't apply to other exchanges.
## Quick overview of supported exchange features
--8<-- "includes/exchange-features.md"
## Exchange configuration
Freqtrade is based on [CCXT library](https://github.com/ccxt/ccxt) that supports over 100 cryptocurrency
@@ -227,7 +231,7 @@ Kucoin requires a passphrase for each api key, you will therefore need to add th
}
```
Kucoin supports [time_in_force](configuration.md#understand-order_time_in_force).
Kucoin supports [time_in_force](configuration.md#understand-order_time_in_force) with settings "GTC" (good till cancelled), "FOK" (full-or-cancel) and "IOC" (immediate-or-cancel) settings.
!!! Tip "Stoploss on Exchange"
Kucoin 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.
@@ -271,7 +275,9 @@ Using the wrong exchange will result in the error "OKX Error 50119: API key does
## Gate.io
!!! Tip "Stoploss on Exchange"
Gate.io supports `stoploss_on_exchange` and uses `stop-loss-limit` orders. It provides great advantages, so we recommend to benefit from it by enabling stoploss on exchange..
Gate.io supports `stoploss_on_exchange` and uses `stop-loss-limit` orders. It provides great advantages, so we recommend to benefit from it by enabling stoploss on exchange.
Gate.io supports [time_in_force](configuration.md#understand-order_time_in_force) with settings "GTC" (good till cancelled), and "IOC" (immediate-or-cancel) settings.
Gate.io allows the use of `POINT` to pay for fees. As this is not a tradable currency (no regular market available), automatic fee calculations will fail (and default to a fee of 0).
The configuration parameter `exchange.unknown_fee_rate` can be used to specify the exchange rate between Point and the stake currency. Obviously, changing the stake-currency will also require changes to this value.
@@ -286,9 +292,22 @@ Without these permissions, the bot will not start correctly and show errors like
## Bybit
Futures trading on bybit is currently supported for USDT markets, and will use isolated futures mode.
!!! Tip "Stoploss on Exchange"
Bybit (futures only) supports `stoploss_on_exchange` and uses `stop-loss-limit` orders. It provides great advantages, so we recommend to benefit from it by enabling stoploss on exchange.
On futures, Bybit supports both `stop-limit` as well as `stop-market` orders. You can use either `"limit"` or `"market"` in the `order_types.stoploss` configuration setting to decide which type to use.
On startup, freqtrade will set the position mode to "One-way Mode" for the whole (sub)account. This avoids making this call over and over again (slowing down bot operations), but means that changes to this setting may result in exceptions and errors.
Bybit supports [time_in_force](configuration.md#understand-order_time_in_force) with settings "GTC" (good till cancelled), "FOK" (full-or-cancel), "IOC" (immediate-or-cancel) and "PO" (Post only) settings.
!!! Warning "Unified accounts"
Freqtrade assumes accounts to be dedicated to the bot.
We therefore recommend the usage of one subaccount per bot. This is especially important when using unified accounts.
Other configurations (multiple bots on one account, manual non-bot trades on the bot account) are not supported and may lead to unexpected behavior.
### Bybit Futures
Futures trading on bybit is supported for isolated futures mode.
On startup, freqtrade will set the position mode to "One-way Mode" for the whole (sub)account. This avoids making this call over and over again (slowing down bot operations), but means that manual changes to this setting may result in exceptions and errors.
As bybit doesn't provide funding rate history, the dry-run calculation is used for live trades as well.
@@ -300,15 +319,6 @@ API Keys for live futures trading must have the following permissions:
We do strongly recommend to limit all API keys to the IP you're going to use it from.
!!! Warning "Unified accounts"
Freqtrade assumes accounts to be dedicated to the bot.
We therefore recommend the usage of one subaccount per bot. This is especially important when using unified accounts.
Other configurations (multiple bots on one account, manual non-bot trades on the bot account) are not supported and may lead to unexpected behavior.
!!! Tip "Stoploss on Exchange"
Bybit (futures only) supports `stoploss_on_exchange` and uses `stop-loss-limit` orders. It provides great advantages, so we recommend to benefit from it by enabling stoploss on exchange.
On futures, Bybit supports both `stop-limit` as well as `stop-market` orders. You can use either `"limit"` or `"market"` in the `order_types.stoploss` configuration setting to decide which type to use.
## Bitmart
@@ -342,7 +352,17 @@ Bitget requires a passphrase for each api key, you will therefore need to add th
}
```
Bitget supports [time_in_force](configuration.md#understand-order_time_in_force).
Bitget supports [time_in_force](configuration.md#understand-order_time_in_force) with settings "GTC" (good till cancelled), "FOK" (full-or-cancel), "IOC" (immediate-or-cancel) and "PO" (Post only) settings.
!!! Tip "Stoploss on Exchange"
Bitget 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 of stoploss shall be used.
### Bitget Futures
Futures trading on bitget is supported for isolated futures mode.
On startup, freqtrade will set the position mode to "One-way Mode" for the whole (sub)account. This avoids making this call over and over again (slowing down bot operations), but means that manual changes to this setting may result in exceptions and errors.
## Hyperliquid
@@ -467,3 +487,5 @@ For example, to test the order type `FOK` with Kraken, and modify candle limit t
!!! Warning
Please make sure to fully understand the impacts of these settings before modifying them.
Using `_ft_has_params` overrides may lead to unexpected behavior, and may even break your bot.
We will not be able to provide support for issues caused by custom settings in `_ft_has_params`.

7
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@@ -297,6 +297,13 @@ Should you be asked to expose your exchange keys or send funds to some random wa
Failing to follow these guidelines will not be responsibility of freqtrade.
## Support policy
We provide free support for Freqtrade on our [Discord server](https://discord.gg/p7nuUNVfP7) and via GitHub issues.
We only support the most recent release (e.g. 2025.8) and the current development branch (e.g. 2025.9-dev).
If you're on an older version, please follow the [upgrade instructions](updating.md) and see if your problem has already been addressed.
## "Freqtrade token"
Freqtrade does not have a Crypto token offering.

13
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View File

@@ -4,7 +4,7 @@ Freqtrade provides a builtin webserver, which can serve [FreqUI](https://github.
By default, the UI is automatically installed as part of the installation (script, docker).
freqUI can also be manually installed by using the `freqtrade install-ui` command.
This same command can also be used to update freqUI to new new releases.
This same command can also be used to update freqUI to new releases.
Once the bot is started in trade / dry-run mode (with `freqtrade trade`) - the UI will be available under the configured API port (by default `http://127.0.0.1:8080`).
@@ -70,7 +70,16 @@ Things you can change (among others):
![FreqUI - Settings view](assets/frequi-settings-dark.png#only-dark)
![FreqUI - Settings view](assets/frequi-settings-light.png#only-light)
## Backtesting
## Webserver mode
when freqtrade is started in [webserver mode](utils.md#webserver-mode) (freqtrade started with `freqtrade webserver`), the webserver will start in a special mode allowing for additional features, for example:
* Downloading data
* Testing pairlists
* [Backtesting strategies](#backtesting)
* ... to be expanded
### Backtesting
When freqtrade is started in [webserver mode](utils.md#webserver-mode) (freqtrade started with `freqtrade webserver`), the backtesting view becomes available.
This view allows you to backtest strategies and visualize the results.

2
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View File

@@ -79,7 +79,7 @@ Mandatory parameters are marked as **Required** and have to be set in one of the
| `model_type` | Model string from stable_baselines3 or SBcontrib. Available strings include: `'TRPO', 'ARS', 'RecurrentPPO', 'MaskablePPO', 'PPO', 'A2C', 'DQN'`. User should ensure that `model_training_parameters` match those available to the corresponding stable_baselines3 model by visiting their documentation. [PPO doc](https://stable-baselines3.readthedocs.io/en/master/modules/ppo.html) (external website) <br> **Datatype:** string.
| `policy_type` | One of the available policy types from stable_baselines3 <br> **Datatype:** string.
| `max_training_drawdown_pct` | The maximum drawdown that the agent is allowed to experience during training. <br> **Datatype:** float. <br> Default: 0.8
| `cpu_count` | Number of threads/cpus to dedicate to the Reinforcement Learning training process (depending on if `ReinforcementLearning_multiproc` is selected or not). Recommended to leave this untouched, by default, this value is set to the total number of physical cores minus 1. <br> **Datatype:** int.
| `cpu_count` | Number of threads/cpus to dedicate to the Reinforcement Learning training process (depending on if `ReinforcementLearner_multiproc` is selected or not). Recommended to leave this untouched, by default, this value is set to the total number of physical cores minus 1. <br> **Datatype:** int.
| `model_reward_parameters` | Parameters used inside the customizable `calculate_reward()` function in `ReinforcementLearner.py` <br> **Datatype:** int.
| `add_state_info` | Tell FreqAI to include state information in the feature set for training and inferencing. The current state variables include trade duration, current profit, trade position. This is only available in dry/live runs, and is automatically switched to false for backtesting. <br> **Datatype:** bool. <br> Default: `False`.
| `net_arch` | Network architecture which is well described in [`stable_baselines3` doc](https://stable-baselines3.readthedocs.io/en/master/guide/custom_policy.html#examples). In summary: `[<shared layers>, dict(vf=[<non-shared value network layers>], pi=[<non-shared policy network layers>])]`. By default this is set to `[128, 128]`, which defines 2 shared hidden layers with 128 units each.

6
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View File

@@ -7,7 +7,7 @@
FreqAI is a software designed to automate a variety of tasks associated with training a predictive machine learning model to generate market forecasts given a set of input signals. In general, FreqAI aims to be a sandbox for easily deploying robust machine learning libraries on real-time data ([details](#freqai-position-in-open-source-machine-learning-landscape)).
!!! Note
FreqAI is, and always will be, a not-for-profit, open-source project. FreqAI does *not* have a crypto token, FreqAI does *not* sell signals, and FreqAI does not have a domain besides the present [freqtrade documentation](https://www.freqtrade.io/en/latest/freqai/).
FreqAI is, and always will be, a not-for-profit, open source project. FreqAI does *not* have a crypto token, FreqAI does *not* sell signals, and FreqAI does not have a domain besides the present [freqtrade documentation](https://www.freqtrade.io/en/latest/freqai/).
Features include:
@@ -81,9 +81,9 @@ If you are using docker, a dedicated tag with FreqAI dependencies is available a
!!! note "docker-compose-freqai.yml"
We do provide an explicit docker-compose file for this in `docker/docker-compose-freqai.yml` - which can be used via `docker compose -f docker/docker-compose-freqai.yml run ...` - or can be copied to replace the original docker file. This docker-compose file also contains a (disabled) section to enable GPU resources within docker containers. This obviously assumes the system has GPU resources available.
### FreqAI position in open-source machine learning landscape
### FreqAI position in open source machine learning landscape
Forecasting chaotic time-series based systems, such as equity/cryptocurrency markets, requires a broad set of tools geared toward testing a wide range of hypotheses. Fortunately, a recent maturation of robust machine learning libraries (e.g. `scikit-learn`) has opened up a wide range of research possibilities. Scientists from a diverse range of fields can now easily prototype their studies on an abundance of established machine learning algorithms. Similarly, these user-friendly libraries enable "citizen scientists" to use their basic Python skills for data exploration. However, leveraging these machine learning libraries on historical and live chaotic data sources can be logistically difficult and expensive. Additionally, robust data collection, storage, and handling presents a disparate challenge. [`FreqAI`](#freqai) aims to provide a generalized and extensible open-sourced framework geared toward live deployments of adaptive modeling for market forecasting. The `FreqAI` framework is effectively a sandbox for the rich world of open-source machine learning libraries. Inside the `FreqAI` sandbox, users find they can combine a wide variety of third-party libraries to test creative hypotheses on a free live 24/7 chaotic data source - cryptocurrency exchange data.
Forecasting chaotic time-series based systems, such as equity/cryptocurrency markets, requires a broad set of tools geared toward testing a wide range of hypotheses. Fortunately, a recent maturation of robust machine learning libraries (e.g. `scikit-learn`) has opened up a wide range of research possibilities. Scientists from a diverse range of fields can now easily prototype their studies on an abundance of established machine learning algorithms. Similarly, these user-friendly libraries enable "citizen scientists" to use their basic Python skills for data exploration. However, leveraging these machine learning libraries on historical and live chaotic data sources can be logistically difficult and expensive. Additionally, robust data collection, storage, and handling presents a disparate challenge. [`FreqAI`](#freqai) aims to provide a generalized and extensible open-sourced framework geared toward live deployments of adaptive modeling for market forecasting. The `FreqAI` framework is effectively a sandbox for the rich world of open source machine learning libraries. Inside the `FreqAI` sandbox, users find they can combine a wide variety of third-party libraries to test creative hypotheses on a free live 24/7 chaotic data source - cryptocurrency exchange data.
### Citing FreqAI

21
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View File

@@ -0,0 +1,21 @@
| Exchange | Mode | Margin mode | Stoploss type |
|---------|---------|------|------------------|
| [Binance](exchanges.md#binance) | spot | | limit |
| [Binance](exchanges.md#binance) | futures | isolated, cross | market, limit |
| [Bingx](exchanges.md#bingx) | spot | | market, limit |
| [Bitmart](exchanges.md#bitmart) | spot | | ❌ (not supported) |
| [Bitget](exchanges.md#bitget) | spot | | market, limit |
| [Bitget](exchanges.md#bitget) | futures | isolated | market, limit |
| [Bybit](exchanges.md#bybit) | spot | | ❌ (not supported) |
| [Bybit](exchanges.md#bybit) | futures | isolated | market, limit |
| [Gate.io](exchanges.md#gateio) | spot | | limit |
| [Gate.io](exchanges.md#gateio) | futures | isolated | limit |
| [HTX](exchanges.md#htx) | spot | | limit |
| [Hyperliquid](exchanges.md#hyperliquid) | spot | | ❌ (not supported) |
| [Hyperliquid](exchanges.md#hyperliquid) | futures | isolated, cross | limit |
| [Kraken](exchanges.md#kraken) | spot | | market, limit |
| [OKX](exchanges.md#okx) | spot | | limit |
| [OKX](exchanges.md#okx) | futures | isolated | limit |
| [Bitvavo](exchanges.md#bitvavo) | spot | | ❌ (not supported) |
| [Kucoin](exchanges.md#kucoin) | spot | | market, limit |

30
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@@ -4,7 +4,7 @@ Pairlist Handlers define the list of pairs (pairlist) that the bot should trade.
In your configuration, you can use Static Pairlist (defined by the [`StaticPairList`](#static-pair-list) Pairlist Handler) and Dynamic Pairlist (defined by the [`VolumePairList`](#volume-pair-list) and [`PercentChangePairList`](#percent-change-pair-list) Pairlist Handlers).
Additionally, [`AgeFilter`](#agefilter), [`PrecisionFilter`](#precisionfilter), [`PriceFilter`](#pricefilter), [`ShuffleFilter`](#shufflefilter), [`SpreadFilter`](#spreadfilter) and [`VolatilityFilter`](#volatilityfilter) act as Pairlist Filters, removing certain pairs and/or moving their positions in the pairlist.
Additionally, [`AgeFilter`](#agefilter), [`DelistFilter`](#delistfilter), [`PrecisionFilter`](#precisionfilter), [`PriceFilter`](#pricefilter), [`ShuffleFilter`](#shufflefilter), [`SpreadFilter`](#spreadfilter) and [`VolatilityFilter`](#volatilityfilter) act as Pairlist Filters, removing certain pairs and/or moving their positions in the pairlist.
If multiple Pairlist Handlers are used, they are chained and a combination of all Pairlist Handlers forms the resulting pairlist the bot uses for trading and backtesting. Pairlist Handlers are executed in the sequence they are configured. You can define either `StaticPairList`, `VolumePairList`, `ProducerPairList`, `RemotePairList`, `MarketCapPairList` or `PercentChangePairList` as the starting Pairlist Handler.
@@ -27,6 +27,7 @@ You may also use something like `.*DOWN/BTC` or `.*UP/BTC` to exclude leveraged
* [`RemotePairList`](#remotepairlist)
* [`MarketCapPairList`](#marketcappairlist)
* [`AgeFilter`](#agefilter)
* [`DelistFilter`](#delistfilter)
* [`FullTradesFilter`](#fulltradesfilter)
* [`OffsetFilter`](#offsetfilter)
* [`PerformanceFilter`](#performancefilter)
@@ -38,7 +39,7 @@ You may also use something like `.*DOWN/BTC` or `.*UP/BTC` to exclude leveraged
* [`VolatilityFilter`](#volatilityfilter)
!!! Tip "Testing pairlists"
Pairlist configurations can be quite tricky to get right. Best use the [`test-pairlist`](utils.md#test-pairlist) utility sub-command to test your configuration quickly.
Pairlist configurations can be quite tricky to get right. Best use freqUI in [webserver mode](freq-ui.md#webserver-mode) or the [`test-pairlist`](utils.md#test-pairlist) utility sub-command to test your Pairlist configuration quickly.
#### Static Pair List
@@ -180,7 +181,7 @@ More sophisticated approach can be used, by using `lookback_timeframe` for candl
* `refresh_period`: Defines the interval (in seconds) at which the pairlist will be refreshed. The default is 1800 seconds (30 minutes).
* `lookback_days`: Number of days to look back. When `lookback_days` is selected, the `lookback_timeframe` is defaulted to 1 day.
* `lookback_timeframe`: Timeframe to use for the lookback period.
* `lookback_period`: Number of periods to look back at.
* `lookback_period`: Number of periods to look back at.
When PercentChangePairList is used after other Pairlist Handlers, it will operate on the outputs of those handlers. If it is the leading Pairlist Handler, it will select pairs from all available markets with the specified stake currency.
@@ -270,7 +271,6 @@ You can limit the length of the pairlist with the optional parameter `number_ass
],
```
!!! Tip "Combining pairlists"
This pairlist can be combined with all other pairlists and filters for further pairlist reduction, and can also act as an "additional" pairlist, on top of already defined pairs.
`ProducerPairList` can also be used multiple times in sequence, combining the pairs from multiple producers.
@@ -312,7 +312,7 @@ The `pairlist_url` option specifies the URL of the remote server where the pairl
The `save_to_file` option, when provided with a valid filename, saves the processed pairlist to that file in JSON format. This option is optional, and by default, the pairlist is not saved to a file.
??? Example "Multi bot with shared pairlist example"
`save_to_file` can be used to save the pairlist to a file with Bot1:
```json
@@ -389,6 +389,8 @@ The `refresh_period` setting defines the interval (in seconds) at which the mark
The `categories` setting specifies the [coingecko categories](https://www.coingecko.com/en/categories) from which to select coins from. The default is an empty list `[]`, meaning no category filtering is applied.
If an incorrect category string is chosen, the plugin will print the available categories from CoinGecko and fail. The category should be the ID of the category, for example, for `https://www.coingecko.com/en/categories/layer-1`, the category ID would be `layer-1`. You can pass multiple categories such as `["layer-1", "meme-token"]` to select from several categories.
Coins like 1000PEPE/USDT or KPEPE/USDT:USDT are detected on a best effort basis, with the prefixes `1000` and `K` being used to identify them.
!!! Warning "Many categories"
Each added category corresponds to one API call to CoinGecko. The more categories you add, the longer the pairlist generation will take, potentially causing rate limit issues.
@@ -405,6 +407,16 @@ be caught out buying before the pair has finished dropping in price.
This filter allows freqtrade to ignore pairs until they have been listed for at least `min_days_listed` days and listed before `max_days_listed`.
#### DelistFilter
Removes pairs that will be delisted on the exchange maximum `max_days_from_now` days from now (defaults to `0` which remove all future delisted pairs no matter how far from now). Currently this filter only supports following exchanges:
!!! Note "Available exchanges"
Delist filter is only available on Binance, where Binance Futures will work for both dry and live modes, while Binance Spot is limited to live mode (for technical reasons).
!!! Warning "Backtesting"
`DelistFilter` does not support backtesting mode.
#### FullTradesFilter
Shrink whitelist to consist only in-trade pairs when the trade slots are full (when `max_open_trades` isn't being set to `-1` in the config).
@@ -436,7 +448,7 @@ Example to remove the first 10 pairs from the pairlist, and takes the next 20 (t
```
!!! Warning
When `OffsetFilter` is used to split a larger pairlist among multiple bots in combination with `VolumeFilter`
When `OffsetFilter` is used to split a larger pairlist among multiple bots in combination with `VolumeFilter`
it can not be guaranteed that pairs won't overlap due to slightly different refresh intervals for the
`VolumeFilter`.
@@ -599,7 +611,7 @@ Adding `"sort_direction": "asc"` or `"sort_direction": "desc"` enables sorting m
### Full example of Pairlist Handlers
The below example blacklists `BNB/BTC`, uses `VolumePairList` with `20` assets, sorting pairs by `quoteVolume` and applies [`PrecisionFilter`](#precisionfilter) and [`PriceFilter`](#pricefilter), filtering all assets where 1 price unit is > 1%. Then the [`SpreadFilter`](#spreadfilter) and [`VolatilityFilter`](#volatilityfilter) is applied and pairs are finally shuffled with the random seed set to some predefined value.
The below example blacklists `BNB/BTC`, uses `VolumePairList` with `20` assets, sorting pairs by `quoteVolume`, then filter future delisted pairs using [`DelistFilter`](#delistfilter) and [`AgeFilter`](#agefilter) to remove pairs that are listed less than 10 days ago. After that [`PrecisionFilter`](#precisionfilter) and [`PriceFilter`](#pricefilter) are applied, filtering all assets where 1 price unit is > 1%. Then the [`SpreadFilter`](#spreadfilter) and [`VolatilityFilter`](#volatilityfilter) are applied and pairs are finally shuffled with the random seed set to some predefined value.
```json
"exchange": {
@@ -612,6 +624,10 @@ The below example blacklists `BNB/BTC`, uses `VolumePairList` with `20` assets,
"number_assets": 20,
"sort_key": "quoteVolume"
},
{
"method": "DelistFilter",
"max_days_from_now": 0,
},
{"method": "AgeFilter", "min_days_listed": 10},
{"method": "PrecisionFilter"},
{"method": "PriceFilter", "low_price_ratio": 0.01},

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View File

@@ -1,11 +1,11 @@
This section will highlight a few projects from members of the community.
!!! Note
The projects below are for the most part not maintained by the freqtrade , therefore use your own caution before using them.
The projects below are for the most part not maintained by the freqtrade team, therefore use your own caution before using them.
- [Example freqtrade strategies](https://github.com/freqtrade/freqtrade-strategies/)
- [FrequentHippo - Statistics of dry/live runs and backtests](http://frequenthippo.ddns.net) (by hippocritical).
- [Online pairlist generator](https://remotepairlist.com/) (by Blood4rc).
- [Freqtrade Backtesting Project](https://strat.ninja/) (by Blood4rc).
- [Freqtrade analysis notebook](https://github.com/froggleston/freqtrade_analysis_notebook) (by Froggleston).
- [TUI for freqtrade](https://github.com/froggleston/freqtrade-frogtrade9000) (by Froggleston).
- [FTUI - Terminal UI for freqtrade](https://github.com/freqtrade/ftui) (by Froggleston).
- [Bot Academy](https://botacademy.ddns.net/) (by stash86) - Blog about crypto bot projects.

3
docs/index.md
View File

@@ -3,7 +3,6 @@
[![Freqtrade CI](https://github.com/freqtrade/freqtrade/actions/workflows/ci.yml/badge.svg?branch=develop)](https://github.com/freqtrade/freqtrade/actions/)
[![DOI](https://joss.theoj.org/papers/10.21105/joss.04864/status.svg)](https://doi.org/10.21105/joss.04864)
[![Coverage Status](https://coveralls.io/repos/github/freqtrade/freqtrade/badge.svg?branch=develop&service=github)](https://coveralls.io/github/freqtrade/freqtrade?branch=develop)
[![Maintainability](https://api.codeclimate.com/v1/badges/5737e6d668200b7518ff/maintainability)](https://codeclimate.com/github/freqtrade/freqtrade/maintainability)
<!-- GitHub action buttons -->
[:octicons-star-16: Star](https://github.com/freqtrade/freqtrade){ .md-button .md-button--sm }
@@ -40,6 +39,7 @@ Please read the [exchange specific notes](exchanges.md) to learn about eventual,
- [X] [Binance](https://www.binance.com/)
- [X] [BingX](https://bingx.com/invite/0EM9RX)
- [X] [Bitget](https://www.bitget.com/)
- [X] [Bitmart](https://bitmart.com/)
- [X] [Bybit](https://bybit.com/)
- [X] [Gate.io](https://www.gate.io/ref/6266643)
@@ -53,6 +53,7 @@ Please read the [exchange specific notes](exchanges.md) to learn about eventual,
### Supported Futures Exchanges (experimental)
- [X] [Binance](https://www.binance.com/)
- [X] [Bitget](https://www.bitget.com/)
- [X] [Bybit](https://bybit.com/)
- [X] [Gate.io](https://www.gate.io/ref/6266643)
- [X] [Hyperliquid](https://hyperliquid.xyz/) (A decentralized exchange, or DEX)

40
docs/installation.md
View File

@@ -46,7 +46,6 @@ These requirements apply to both [Script Installation](#script-installation) and
* [pip](https://pip.pypa.io/en/stable/installing/)
* [git](https://git-scm.com/book/en/v2/Getting-Started-Installing-Git)
* [virtualenv](https://virtualenv.pypa.io/en/stable/installation.html) (Recommended)
* [TA-Lib](https://ta-lib.github.io/ta-lib-python/) (install instructions [below](#install-ta-lib))
### Install code
@@ -201,35 +200,6 @@ This option will hard reset your branch (only if you are on either `stable` or `
Make sure you fulfill the [Requirements](#requirements) and have downloaded the [Freqtrade repository](#freqtrade-repository).
### Install TA-Lib
#### TA-Lib script installation
```bash
sudo ./build_helpers/install_ta-lib.sh
```
!!! Note
This will use the ta-lib tar.gz included in this repository.
##### TA-Lib manual installation
[Official installation guide](https://ta-lib.github.io/ta-lib-python/install.html)
```bash
wget http://prdownloads.sourceforge.net/ta-lib/ta-lib-0.4.0-src.tar.gz
tar xvzf ta-lib-0.4.0-src.tar.gz
cd ta-lib
sed -i.bak "s|0.00000001|0.000000000000000001 |g" src/ta_func/ta_utility.h
./configure --prefix=/usr/local
make
sudo make install
# On debian based systems (debian, ubuntu, ...) - updating ldconfig might be necessary.
sudo ldconfig
cd ..
rm -rf ./ta-lib*
```
### Setup Python virtual environment (virtualenv)
You will run freqtrade in separated `virtual environment`
@@ -332,16 +302,6 @@ python3 -m pip install -r requirements.txt
python3 -m pip install -e .
```
Patch conda libta-lib (Linux only)
```bash
# Ensure that the environment is active!
conda activate freqtrade
cd build_helpers
bash install_ta-lib.sh ${CONDA_PREFIX} nosudo
```
[You are now ready](#you-are-ready) to run the bot.
### Important shortcuts

5
docs/leverage.md
View File

@@ -92,6 +92,11 @@ One account is used to share collateral between markets (trading pairs). Margin
Please read the [exchange specific notes](exchanges.md) for exchanges that support this mode and how they differ.
!!! Warning "Increased risk of liquidation"
Cross margin mode increases the risk of full account liquidation, as all trades share the same collateral.
A loss on one trade can affect the liquidation price of other trades.
Also, cross-position influence may not be fully simulated in dry-run or backtesting mode.
## Set leverage to use
Different strategies and risk profiles will require different levels of leverage.

13
docs/lookahead-analysis.md
View File

@@ -22,6 +22,7 @@ This is done by not looking at the strategy code itself, but at changed indicato
- `--dry-run-wallet` is forced to be basically infinite (1 billion).
- `--stake-amount` is forced to be a static 10000 (10k).
- `--enable-protections` is forced to be off.
- `order_types` are forced to be "market" (late entries) unless `--lookahead-allow-limit-orders` is set.
These are set to avoid users accidentally generating false positives.
@@ -38,7 +39,7 @@ Many strategies, without the programmer knowing, have fallen prey to lookahead b
This typically makes the strategy backtest look profitable, sometimes to extremes, but this is not realistic as the strategy is "cheating" by looking at data it would not have in dry or live modes.
The reason why strategies can "cheat" is because the freqtrade backtesting process populates the full dataframe including all candle timestamps at the outset.
If the programmer is not careful or oblivious how things work internally
If the programmer is not careful or oblivious how things work internally
(which sometimes can be really hard to find out) then the strategy will look into the future.
This command is made to try to verify the validity in the form of the aforementioned lookahead bias.
@@ -50,8 +51,7 @@ After this initial backtest runs, it will look if the `minimum-trade-amount` is
If this happens, use a wider timerange to get more trades for the analysis, or use a timerange where more trades occur.
After setting the baseline it will then do additional backtest runs for every entry and exit separately.
When these verification backtests complete, it will compare the indicators at the signal candles (both entry or exit)
and report the bias.
When these verification backtests complete, it will compare both dataframes (baseline and sliced) for any difference in columns' value and report the bias.
After all signals have been verified or falsified a result table will be generated for the user to see.
### How to find and remove bias? How can I salvage a biased strategy?
@@ -98,8 +98,11 @@ If the strategy has many different signals / signal types, it's up to you to sel
This would lead to a false-negative, i.e. the strategy will be reported as non-biased.
- `lookahead-analysis` has access to the same backtesting options and this can introduce problems.
Please don't use any options like enabling position stacking as this will distort the number of checked signals.
If you decide to do so, then make doubly sure that you won't ever run out of `max_open_trades` slots,
If you decide to do so, then make doubly sure that you won't ever run out of `max_open_trades` slots,
and that you have enough capital in the backtest wallet configuration.
- In the results table, the `biased_indicators` column
- limit orders in combination with `custom_entry_price()` and `custom_exit_price()` callbacks can cause late / delayed entries and exists, causing false positives.
To avoid this - market orders are forced for this command. This implicitly means that `custom_entry_price()` and `custom_exit_price()` callbacks are not called.
Using `--lookahead-allow-limit-orders` will skip the override and use your configured order types - however has shown to eventually produce false positives.
- In the results table, the `biased_indicators` column
will falsely flag FreqAI target indicators defined in `set_freqai_targets()` as biased.
**These are not biased and can safely be ignored.**

4
docs/requirements-docs.txt
View File

@@ -1,6 +1,6 @@
markdown==3.8.2
markdown==3.9
mkdocs==1.6.1
mkdocs-material==9.6.16
mkdocs-material==9.6.22
mdx_truly_sane_lists==1.3
pymdown-extensions==10.16.1
jinja2==3.1.6

103
docs/rest-api.md
View File

@@ -140,6 +140,11 @@ This method will work for all arguments - check the "show" command for a list of
# Get the status of the bot
ping = client.ping()
print(ping)
# Add pairs to blacklist
client.blacklist("BTC/USDT", "ETH/USDT")
# Add pairs to blacklist by supplying a list
client.blacklist(*listPairs)
# ...
```
@@ -155,63 +160,63 @@ freqtrade-client help
Possible commands:
available_pairs
Return available pair (backtest data) based on timeframe / stake_currency selection
Return available pair (backtest data) based on timeframe / stake_currency selection
:param timeframe: Only pairs with this timeframe available.
:param stake_currency: Only pairs that include this timeframe
balance
Get the account balance.
Get the account balance.
blacklist
Show the current blacklist.
Show the current blacklist.
:param add: List of coins to add (example: "BNB/BTC")
cancel_open_order
Cancel open order for trade.
Cancel open order for trade.
:param trade_id: Cancels open orders for this trade.
count
Return the amount of open trades.
Return the amount of open trades.
daily
Return the profits for each day, and amount of trades.
Return the profits for each day, and amount of trades.
delete_lock
Delete (disable) lock from the database.
Delete (disable) lock from the database.
:param lock_id: ID for the lock to delete
delete_trade
Delete trade from the database.
Delete trade from the database.
Tries to close open orders. Requires manual handling of this asset on the exchange.
:param trade_id: Deletes the trade with this ID from the database.
forcebuy
Buy an asset.
Buy an asset.
:param pair: Pair to buy (ETH/BTC)
:param price: Optional - price to buy
forceenter
Force entering a trade
Force entering a trade
:param pair: Pair to buy (ETH/BTC)
:param side: 'long' or 'short'
:param price: Optional - price to buy
forceexit
Force-exit a trade.
Force-exit a trade.
:param tradeid: Id of the trade (can be received via status command)
:param ordertype: Order type to use (must be market or limit)
:param amount: Amount to sell. Full sell if not given
health
Provides a quick health check of the running bot.
Provides a quick health check of the running bot.
lock_add
Manually lock a specific pair
@@ -222,22 +227,22 @@ lock_add
:param reason: Reason for the lock
locks
Return current locks
Return current locks
logs
Show latest logs.
Show latest logs.
:param limit: Limits log messages to the last <limit> logs. No limit to get the entire log.
pair_candles
Return live dataframe for <pair><timeframe>.
Return live dataframe for <pair><timeframe>.
:param pair: Pair to get data for
:param timeframe: Only pairs with this timeframe available.
:param limit: Limit result to the last n candles.
pair_history
Return historic, analyzed dataframe
Return historic, analyzed dataframe
:param pair: Pair to get data for
:param timeframe: Only pairs with this timeframe available.
@@ -245,59 +250,59 @@ pair_history
:param timerange: Timerange to get data for (same format than --timerange endpoints)
performance
Return the performance of the different coins.
Return the performance of the different coins.
ping
simple ping
simple ping
plot_config
Return plot configuration if the strategy defines one.
Return plot configuration if the strategy defines one.
profit
Return the profit summary.
Return the profit summary.
reload_config
Reload configuration.
Reload configuration.
show_config
Returns part of the configuration, relevant for trading operations.
Returns part of the configuration, relevant for trading operations.
start
Start the bot if it's in the stopped state.
Start the bot if it's in the stopped state.
pause
Pause the bot if it's in the running state. If triggered on stopped state will handle open positions.
Pause the bot if it's in the running state. If triggered on stopped state will handle open positions.
stats
Return the stats report (durations, sell-reasons).
Return the stats report (durations, sell-reasons).
status
Get the status of open trades.
Get the status of open trades.
stop
Stop the bot. Use `start` to restart.
Stop the bot. Use `start` to restart.
stopbuy
Stop buying (but handle sells gracefully). Use `reload_config` to reset.
Stop buying (but handle sells gracefully). Use `reload_config` to reset.
strategies
Lists available strategies
Lists available strategies
strategy
Get strategy details
Get strategy details
:param strategy: Strategy class name
sysinfo
Provides system information (CPU, RAM usage)
Provides system information (CPU, RAM usage)
trade
Return specific trade
Return specific trade
:param trade_id: Specify which trade to get.
trades
Return trades history, sorted by id
Return trades history, sorted by id
:param limit: Limits trades to the X last trades. Max 500 trades.
:param offset: Offset by this amount of trades.
@@ -316,10 +321,10 @@ list_custom_data
:param key: str, optional - Key of the custom-data
version
Return the version of the bot.
Return the version of the bot.
whitelist
Show the current whitelist.
Show the current whitelist.
```
@@ -339,32 +344,32 @@ All endpoints in the below table need to be prefixed with the base URL of the AP
| `/reload_config` | POST | Reloads the configuration file.
| `/trades` | GET | List last trades. Limited to 500 trades per call.
| `/trade/<tradeid>` | GET | Get specific trade.<br/>*Params:*<br/>- `tradeid` (`int`)
| `/trades/<tradeid>` | DELETE | Remove trade from the database. Tries to close open orders. Requires manual handling of this trade on the exchange.<br/>*Params:*<br/>- `tradeid` (`int`)
| `/trades/<tradeid>/open-order` | DELETE | Cancel open order for this trade.<br/>*Params:*<br/>- `tradeid` (`int`)
| `/trades/<tradeid>/reload` | POST | Reload a trade from the Exchange. Only works in live, and can potentially help recover a trade that was manually sold on the exchange.<br/>*Params:*<br/>- `tradeid` (`int`)
| `/trades/<tradeid>` | DELETE | Remove trade from the database. Tries to close open orders. Requires manual handling of this trade on the exchange.<br/>*Params:*<br/>- `tradeid` (`int`)
| `/trades/<tradeid>/open-order` | DELETE | Cancel open order for this trade.<br/>*Params:*<br/>- `tradeid` (`int`)
| `/trades/<tradeid>/reload` | POST | Reload a trade from the Exchange. Only works in live, and can potentially help recover a trade that was manually sold on the exchange.<br/>*Params:*<br/>- `tradeid` (`int`)
| `/show_config` | GET | Shows part of the current configuration with relevant settings to operation.
| `/logs` | GET | Shows last log messages.
| `/status` | GET | Lists all open trades.
| `/count` | GET | Displays number of trades used and available.
| `/entries` | GET | Shows profit statistics for each enter tags for given pair (or all pairs if pair isn't given). Pair is optional.<br/>*Params:*<br/>- `pair` (`str`)
| `/exits` | GET | Shows profit statistics for each exit reasons for given pair (or all pairs if pair isn't given). Pair is optional.<br/>*Params:*<br/>- `pair` (`str`)
| `/mix_tags` | GET | Shows profit statistics for each combinations of enter tag + exit reasons for given pair (or all pairs if pair isn't given). Pair is optional.<br/>*Params:*<br/>- `pair` (`str`)
| `/entries` | GET | Shows profit statistics for each enter tags for given pair (or all pairs if pair isn't given). Pair is optional.<br/>*Params:*<br/>- `pair` (`str`)
| `/exits` | GET | Shows profit statistics for each exit reasons for given pair (or all pairs if pair isn't given). Pair is optional.<br/>*Params:*<br/>- `pair` (`str`)
| `/mix_tags` | GET | Shows profit statistics for each combinations of enter tag + exit reasons for given pair (or all pairs if pair isn't given). Pair is optional.<br/>*Params:*<br/>- `pair` (`str`)
| `/locks` | GET | Displays currently locked pairs.
| `/locks` | POST | Locks a pair until "until". (Until will be rounded up to the nearest timeframe). Side is optional and is either `long` or `short` (default is `long`). Reason is optional.<br/>*Params:*<br/>- `<pair>` (`str`)<br/>- `<until>` (`datetime`)<br/>- `[side]` (`str`)<br/>- `[reason]` (`str`)
| `/locks/<lockid>` | DELETE | Deletes (disables) the lock by id.<br/>*Params:*<br/>- `lockid` (`int`)
| `/locks` | POST | Locks a pair until "until". (Until will be rounded up to the nearest timeframe). Side is optional and is either `long` or `short` (default is `long`). Reason is optional.<br/>*Params:*<br/>- `<pair>` (`str`)<br/>- `<until>` (`datetime`)<br/>- `[side]` (`str`)<br/>- `[reason]` (`str`)
| `/locks/<lockid>` | DELETE | Deletes (disables) the lock by id.<br/>*Params:*<br/>- `lockid` (`int`)
| `/profit` | GET | Display a summary of your profit/loss from close trades and some stats about your performance.
| `/forceexit` | POST | Instantly exits the given trade (ignoring `minimum_roi`), using the given order type ("market" or "limit", uses your config setting if not specified), and the chosen amount (full sell if not specified). If `all` is supplied as the `tradeid`, then all currently open trades will be forced to exit.<br/>*Params:*<br/>- `<tradeid>` (`int` or `str`)<br/>- `<ordertype>` (`str`)<br/>- `[amount]` (`float`)
| `/forceenter` | POST | Instantly enters the given pair. Side is optional and is either `long` or `short` (default is `long`). Rate is optional. (`force_entry_enable` must be set to True)<br/>*Params:*<br/>- `<pair>` (`str`)<br/>- `<side>` (`str`)<br/>- `[rate]` (`float`)
| `/performance` | GET | Show performance of each finished trade grouped by pair.
| `/balance` | GET | Show account balance per currency.
| `/daily` | GET | Shows profit or loss per day, over the last n days (n defaults to 7).<br/>*Params:*<br/>- `<n>` (`int`)
| `/weekly` | GET | Shows profit or loss per week, over the last n days (n defaults to 4).<br/>*Params:*<br/>- `<n>` (`int`)
| `/monthly` | GET | Shows profit or loss per month, over the last n days (n defaults to 3).<br/>*Params:*<br/>- `<n>` (`int`)
| `/daily` | GET | Shows profit or loss per day, over the last n days (n defaults to 7).<br/>*Params:*<br/>- `timescale` (`int`)
| `/weekly` | GET | Shows profit or loss per week, over the last n days (n defaults to 4).<br/>*Params:*<br/>- `timescale` (`int`)
| `/monthly` | GET | Shows profit or loss per month, over the last n days (n defaults to 3).<br/>*Params:*<br/>- `timescale` (`int`)
| `/stats` | GET | Display a summary of profit / loss reasons as well as average holding times.
| `/whitelist` | GET | Show the current whitelist.
| `/blacklist` | GET | Show the current blacklist.
| `/blacklist` | POST | Adds the specified pair to the blacklist.<br/>*Params:*<br/>- `pair` (`str`)
| `/blacklist` | DELETE | Deletes the specified list of pairs from the blacklist.<br/>*Params:*<br/>- `[pair,pair]` (`list[str]`)
| `/blacklist` | POST | Adds the specified pair to the blacklist.<br/>*Params:*<br/>- `blacklist` (`str`)
| `/blacklist` | DELETE | Deletes the specified list of pairs from the blacklist.<br/>*Params:*<br/>- `[pair,pair]` (`list[str]`)
| `/pair_candles` | GET | Returns dataframe for a pair / timeframe combination while the bot is running. **Alpha**
| `/pair_candles` | POST | Returns dataframe for a pair / timeframe combination while the bot is running, filtered by a provided list of columns to return. **Alpha**<br/>*Params:*<br/>- `<column_list>` (`list[str]`)
| `/pair_history` | GET | Returns an analyzed dataframe for a given timerange, analyzed by a given strategy. **Alpha**
@@ -488,7 +493,7 @@ To properly configure your reverse proxy (securely), please consult it's documen
### OpenAPI interface
To enable the builtin openAPI interface (Swagger UI), specify `"enable_openapi": true` in the api_server configuration.
This will enable the Swagger UI at the `/docs` endpoint. By default, that's running at http://localhost:8080/docs - but it'll depend on your settings.
This will enable the Swagger UI at the `/docs` endpoint. By default, that's running at <http://localhost:8080/docs> - but it'll depend on your settings.
### Advanced API usage using JWT tokens

14
docs/stoploss.md
View File

@@ -26,17 +26,9 @@ These modes can be configured with these values:
Stoploss on exchange is only supported for the following exchanges, and not all exchanges support both stop-limit and stop-market.
The Order-type will be ignored if only one mode is available.
| Exchange | stop-loss type |
|----------|-------------|
| Binance | limit |
| Binance Futures | market, limit |
| Bingx | market, limit |
| HTX | limit |
| kraken | market, limit |
| Gate | limit |
| Okx | limit |
| Kucoin | stop-limit, stop-market|
| Hyperliquid (futures only) | limit |
??? info "Supported exchanges and stoploss types"
--8<-- "includes/exchange-features.md"
!!! Note "Tight stoploss"
<ins>Do not set too low/tight stoploss value when using stop loss on exchange!</ins>

36
docs/strategy-callbacks.md
View File

@@ -1243,15 +1243,23 @@ class AwesomeStrategy(IStrategy):
```
!!! Tip "Learn more about storing data"
You can learn more about storing data on the [Storing custom trade data](strategy-advanced.md#storing-information-persistent) section.
Please keep in mind that this is considered advanced usage, and should be used with care.
## Plot annotations callback
The plot annotations callback is called whenever freqUI requests data to display a chart.
This callback has no meaning in the trade cycle context and is only used for charting purposes.
The strategy can then return a list of `AnnotationType` objects to be displayed on the chart.
Depending on the content returned - the chart can display horizontal areas, vertical areas, or boxes.
Depending on the content returned - the chart can display horizontal areas, vertical areas, boxes or lines.
The full object looks like this:
### Annotation types
Currently two types of annotations are supported, `area` and `line`.
#### Area
``` json
{
@@ -1261,10 +1269,29 @@ The full object looks like this:
"y_start": 94000.2, // Price / y axis value
"y_end": 98000, // Price / y axis value
"color": "",
"z_level": 5, // z-level, higher values are drawn on top of lower values. Positions relative to the Chart elements need to be set in freqUI.
"label": "some label"
}
```
#### Line
``` json
{
"type": "line", // Type of the annotation, currently only "line" is supported
"start": "2024-01-01 15:00:00", // Start date of the line
"end": "2024-01-01 16:00:00", // End date of the line
"y_start": 94000.2, // Price / y axis value
"y_end": 98000, // Price / y axis value
"color": "",
"z_level": 5, // z-level, higher values are drawn on top of lower values. Positions relative to the Chart elements need to be set in freqUI.
"label": "some label",
"width": 2, // Optional, line width in pixels. Defaults to 1
"line_style": "dashed", // Optional, can be "solid", "dashed" or "dotted". Defaults to "solid"
}
```
The below example will mark the chart with areas for the hours 8 and 15, with a grey color, highlighting the market open and close hours.
This is obviously a very basic example.
@@ -1332,7 +1359,7 @@ Entries will be validated, and won't be passed to the UI if they don't correspon
while start_dt < end_date:
start_dt += timedelta(hours=1)
if (start_dt.hour % 4) == 0:
mark_areas.append(
annotations.append(
{
"type": "area",
"label": "4h",
@@ -1343,7 +1370,7 @@ Entries will be validated, and won't be passed to the UI if they don't correspon
)
elif (start_dt.hour % 2) == 0:
price = dataframe.loc[dataframe["date"] == start_dt, ["close"]].mean()
mark_areas.append(
annotations.append(
{
"type": "area",
"label": "2h",
@@ -1352,6 +1379,7 @@ Entries will be validated, and won't be passed to the UI if they don't correspon
"y_end": price * 1.01,
"y_start": price * 0.99,
"color": "rgba(0, 255, 0, 0.4)",
"z_level": 5,
}
)

80
docs/strategy-customization.md
View File

@@ -84,6 +84,7 @@ Check the [configuration documentation](configuration.md) about how to set the b
**Always use dry mode when testing as this gives you an idea of how your strategy will work in reality without risking capital.**
## Diving in deeper
**For the following section we will use the [user_data/strategies/sample_strategy.py](https://github.com/freqtrade/freqtrade/blob/develop/freqtrade/templates/sample_strategy.py)
file as reference.**
@@ -99,9 +100,9 @@ file as reference.**
Some common patterns for this are listed in the [Common Mistakes](#common-mistakes-when-developing-strategies) section of this document.
??? Hint "Lookahead and recursive analysis"
Freqtrade includes two helpful commands to help assess common lookahead (using future data) and
recursive bias (variance in indicator values) issues. Before running a strategy in dry or live more,
you should always use these commands first. Please check the relevant documentation for
Freqtrade includes two helpful commands to help assess common lookahead (using future data) and
recursive bias (variance in indicator values) issues. Before running a strategy in dry or live more,
you should always use these commands first. Please check the relevant documentation for
[lookahead](lookahead-analysis.md) and [recursive](recursive-analysis.md) analysis.
### Dataframe
@@ -154,7 +155,7 @@ Vectorized operations perform calculations across the whole range of data and ar
!!! Warning "Trade order assumptions"
In backtesting, signals are generated on candle close. Trades are then initiated immeditely on next candle open.
In dry and live, this may be delayed due to all pair dataframes needing to be analysed first, then trade processing
for each of those pairs happens. This means that in dry/live you need to be mindful of having as low a computation
delay as possible, usually by running a low number of pairs and having a CPU with a good clock speed.
@@ -284,7 +285,7 @@ It's important to always return the dataframe without removing/modifying the col
This method will also define a new column, `"enter_long"` (`"enter_short"` for shorts), which needs to contain `1` for entries, and `0` for "no action". `enter_long` is a mandatory column that must be set even if the strategy is shorting only.
You can name your entry signals by using the `"enter_tag"` column, which can help debug and assess your strategy later.
You can name your entry signals by using the `"enter_tag"` column, which can help debug and assess your strategy later.
Sample from `user_data/strategies/sample_strategy.py`:
@@ -555,7 +556,7 @@ A full sample can be found [in the DataProvider section](#complete-dataprovider-
??? Note "Alternative candle types"
Informative_pairs can also provide a 3rd tuple element defining the candle type explicitly.
Availability of alternative candle-types will depend on the trading-mode and the exchange.
Availability of alternative candle-types will depend on the trading-mode and the exchange.
In general, spot pairs cannot be used in futures markets, and futures candles can't be used as informative pairs for spot bots.
Details about this may vary, if they do, this can be found in the exchange documentation.
@@ -783,6 +784,8 @@ Please always check the mode of operation to select the correct method to get da
- `ohlcv(pair, timeframe)` - Currently cached candle (OHLCV) data for the pair, returns DataFrame or empty DataFrame.
- [`orderbook(pair, maximum)`](#orderbookpair-maximum) - Returns latest orderbook data for the pair, a dict with bids/asks with a total of `maximum` entries.
- [`ticker(pair)`](#tickerpair) - Returns current ticker data for the pair. See [ccxt documentation](https://github.com/ccxt/ccxt/wiki/Manual#price-tickers) for more details on the Ticker data structure.
- [`check_delisting(pair)`](#check_delistingpair) - Return Datetime of the pair delisting schedule if any, otherwise return None
- [`funding_rate(pair)`](#funding_ratepair) - Returns current funding rate data for the pair.
- `runmode` - Property containing the current runmode.
### Example Usages
@@ -854,6 +857,8 @@ dataframe, last_updated = self.dp.get_analyzed_dataframe(pair=metadata['pair'],
### *orderbook(pair, maximum)*
Retrieve the current order book for a pair.
``` python
if self.dp.runmode.value in ('live', 'dry_run'):
ob = self.dp.orderbook(metadata['pair'], 1)
@@ -903,6 +908,69 @@ if self.dp.runmode.value in ('live', 'dry_run'):
!!! Warning "Warning about backtesting"
This method will always return up-to-date / real-time values. As such, usage during backtesting / hyperopt without runmode checks will lead to wrong results, e.g. your whole dataframe will contain the same single value in all rows.
### *check_delisting(pair)*
```python
def custom_exit(self, pair: str, trade: Trade, current_time: datetime, current_rate: float, current_profit: float, **kwargs):
if self.dp.runmode.value in ('live', 'dry_run'):
delisting_dt = self.dp.check_delisting(pair)
if delisting_dt is not None:
return "delist"
```
!!! Note "Availabiity of delisting information"
This method is only available for certain exchanges and will return `None` in cases this is not available or if the pair is not scheduled for delisting.
!!! Warning "Warning about backtesting"
This method will always return up-to-date / real-time values. As such, usage during backtesting / hyperopt without runmode checks will lead to wrong results, e.g. your whole dataframe will contain the same single value in all rows.
### *funding_rate(pair)*
Retrieves the current funding rate for the pair and only works for futures pairs in the format of `base/quote:settle` (e.g. `ETH/USDT:USDT`).
``` python
if self.dp.runmode.value in ('live', 'dry_run'):
funding_rate = self.dp.funding_rate(metadata['pair'])
dataframe['current_funding_rate'] = funding_rate['fundingRate']
dataframe['next_funding_timestamp'] = funding_rate['fundingTimestamp']
dataframe['next_funding_datetime'] = funding_rate['fundingDatetime']
```
The funding rate structure is aligned with the funding rate structure from [ccxt](https://github.com/ccxt/ccxt/wiki/Manual#funding-rate-structure), so the result will be formatted as follows:
``` python
{
"info": {
# ...
},
"symbol": "BTC/USDT:USDT",
"markPrice": 110730.7,
"indexPrice": 110782.52,
"interestRate": 0.0001,
"estimatedSettlePrice": 110822.67200153,
"timestamp": 1757146321001,
"datetime": "2025-09-06T08:12:01.001Z",
"fundingRate": 5.609e-05,
"fundingTimestamp": 1757174400000,
"fundingDatetime": "2025-09-06T16:00:00.000Z",
"nextFundingRate": None,
"nextFundingTimestamp": None,
"nextFundingDatetime": None,
"previousFundingRate": None,
"previousFundingTimestamp": None,
"previousFundingDatetime": None,
"interval": None,
}
```
Therefore, using `funding_rate['fundingRate']` as demonstrated above will use the current funding rate.
Actually available data will vary between exchanges, so this code may not work as expected across exchanges.
!!! Warning "Warning about backtesting"
Current funding-rate is not part of the historic data which means backtesting and hyperopt will not work correctly if this method is used, as the method will return up-to-date values.
We recommend to use the historically available funding rate for backtesting (which is automatically downloaded, and is at the frequency of what the exchange provides, usually 4h or 8h).
`self.dp.get_pair_dataframe(pair=metadata['pair'], timeframe='8h', candle_type="funding_rate")`
### Send Notification
The dataprovider `.send_msg()` function allows you to send custom notifications from your strategy.

5
docs/stylesheets/ft.extra.css
View File

@@ -47,3 +47,8 @@
border-color: #afb8c1;
box-shadow: inset 0 1px 0 rgba(175, 184, 193, 0.2);
}
.md-grid {
/* default is max-width: 61rem; */
max-width: 75rem;
}

78
docs/trade-object.md
View File

@@ -14,11 +14,20 @@ The following attributes / properties are available for each individual trade -
| Attribute | DataType | Description |
|------------|-------------|-------------|
| `pair` | string | Pair of this trade. |
| `safe_base_currency` | string | Compatibility layer for base currency . |
| `safe_quote_currency` | string | Compatibility layer for quote currency. |
| `is_open` | boolean | Is the trade currently open, or has it been concluded. |
| `exchange` | string | Exchange where this trade was executed. |
| `open_rate` | float | Rate this trade was entered at (Avg. entry rate in case of trade-adjustments). |
| `open_rate_requested` | float | The rate that was requested when the trade was opened. |
| `open_trade_value` | float | Value of the open trade including fees. |
| `close_rate` | float | Close rate - only set when is_open = False. |
| `close_rate_requested` | float | The close rate that was requested. |
| `safe_close_rate` | float | Close rate or `close_rate_requested` or 0.0 if neither is available. Only makes sense once the trade is closed. |
| `stake_amount` | float | Amount in Stake (or Quote) currency. |
| `max_stake_amount` | float | Maximum stake amount that was used in this trade (sum of all filled Entry orders). |
| `amount` | float | Amount in Asset / Base currency that is currently owned. Will be 0.0 until the initial order fills. |
| `amount_requested` | float | Amount that was originally requested for this trade as part of the first entry order. |
| `open_date` | datetime | Timestamp when trade was opened **use `open_date_utc` instead** |
| `open_date_utc` | datetime | Timestamp when trade was opened - in UTC. |
| `close_date` | datetime | Timestamp when trade was closed **use `close_date_utc` instead** |
@@ -28,15 +37,47 @@ The following attributes / properties are available for each individual trade -
| `realized_profit` | float | Absolute already realized profit (in stake currency) while the trade is still open. |
| `leverage` | float | Leverage used for this trade - defaults to 1.0 in spot markets. |
| `enter_tag` | string | Tag provided on entry via the `enter_tag` column in the dataframe. |
| `exit_reason` | string | Reason why the trade was exited. |
| `exit_order_status` | string | Status of the exit order. |
| `strategy` | string | Strategy name that was used for this trade. |
| `timeframe` | int | Timeframe used for this trade. |
| `is_short` | boolean | True for short trades, False otherwise. |
| `orders` | Order[] | List of order objects attached to this trade (includes both filled and cancelled orders). |
| `date_last_filled_utc` | datetime | Time of the last filled order. |
| `date_entry_fill_utc` | datetime | Date of the first filled entry order. |
| `entry_side` | "buy" / "sell" | Order Side the trade was entered. |
| `exit_side` | "buy" / "sell" | Order Side that will result in a trade exit / position reduction. |
| `trade_direction` | "long" / "short" | Trade direction in text - long or short. |
| `max_rate` | float | Highest price reached during this trade. Not 100% accurate. |
| `min_rate` | float | Lowest price reached during this trade. Not 100% accurate. |
| `nr_of_successful_entries` | int | Number of successful (filled) entry orders. |
| `nr_of_successful_exits` | int | Number of successful (filled) exit orders. |
| `has_open_position` | boolean | True if there is an open position (amount > 0) for this trade. Only false while the initial entry order is unfilled. |
| `has_open_orders` | boolean | Has the trade open orders (excluding stoploss orders). |
| `has_open_sl_orders` | boolean | True if there are open stoploss orders for this trade. |
| `open_orders` | Order[] | All open orders for this trade excluding stoploss orders. |
| `open_sl_orders` | Order[] | All open stoploss orders for this trade. |
| `fully_canceled_entry_order_count` | int | Number of fully canceled entry orders. |
| `canceled_exit_order_count` | int | Number of canceled exit orders. |
### Stop Loss related attributes
| Attribute | DataType | Description |
|------------|-------------|-------------|
| `stop_loss` | float | Absolute value of the stop loss. |
| `stop_loss_pct` | float | Relative value of the stop loss. |
| `initial_stop_loss` | float | Absolute value of the initial stop loss. |
| `initial_stop_loss_pct` | float | Relative value of the initial stop loss. |
| `stoploss_last_update_utc` | datetime | Timestamp of the last stoploss on exchange order update. |
| `stoploss_or_liquidation` | float | Returns the more restrictive of stoploss or liquidation price and corresponds to the price a stoploss would trigger at. |
### Futures/Margin trading attributes
| Attribute | DataType | Description |
|------------|-------------|-------------|
| `liquidation_price` | float | Liquidation price for leveraged trades. |
| `interest_rate` | float | Interest rate for margin trades. |
| `funding_fees` | float | Total funding fees for futures trades. |
## Class methods
@@ -102,6 +143,10 @@ from freqtrade.persistence import Trade
profit = Trade.total_open_trades_stakes()
```
## Class methods not supported in backtesting/hyperopt
The following class methods are not supported in backtesting/hyperopt mode.
### get_overall_performance
Retrieve the overall performance - similar to the `/performance` telegram command.
@@ -120,6 +165,17 @@ Sample return value: ETH/BTC had 5 trades, with a total profit of 1.5% (ratio of
{"pair": "ETH/BTC", "profit": 0.015, "count": 5}
```
### get_trading_volume
Get total trading volume based on orders.
``` python
from freqtrade.persistence import Trade
# ...
volume = Trade.get_trading_volume()
```
## Order Object
An `Order` object represents an order on the exchange (or a simulated order in dry-run mode).
@@ -135,6 +191,10 @@ Most properties here can be None as they are dependent on the exchange response.
| `trade` | Trade | Trade object this order is attached to |
| `ft_pair` | string | Pair this order is for |
| `ft_is_open` | boolean | is the order still open? |
| `ft_order_side` | string | Order side ('buy', 'sell', or 'stoploss') |
| `ft_cancel_reason` | string | Reason why the order was canceled |
| `ft_order_tag` | string | Custom order tag |
| `order_id` | string | Exchange order ID |
| `order_type` | string | Order type as defined on the exchange - usually market, limit or stoploss |
| `status` | string | Status as defined by [ccxt's order structure](https://docs.ccxt.com/#/README?id=order-structure). Usually open, closed, expired, canceled or rejected |
| `side` | string | buy or sell |
@@ -143,12 +203,20 @@ Most properties here can be None as they are dependent on the exchange response.
| `amount` | float | Amount in base currency |
| `filled` | float | Filled amount (in base currency) (use `safe_filled` instead) |
| `safe_filled` | float | Filled amount (in base currency) - guaranteed to not be None |
| `safe_amount` | float | Amount - falls back to ft_amount if None |
| `safe_price` | float | Price - falls back through average, price, stop_price, ft_price |
| `safe_placement_price` | float | Price at which the order was placed |
| `remaining` | float | Remaining amount (use `safe_remaining` instead) |
| `safe_remaining` | float | Remaining amount - either taken from the exchange or calculated. |
| `cost` | float | Cost of the order - usually average * filled (*Exchange dependent on futures, may contain the cost with or without leverage and may be in contracts.*) |
| `stake_amount` | float | Stake amount used for this order. *Added in 2023.7.* |
| `stake_amount_filled` | float | Filled Stake amount used for this order. *Added in 2024.11.* |
| `safe_cost` | float | Cost of the order - guaranteed to not be None |
| `safe_fee_base` | float | Fee in base currency - guaranteed to not be None |
| `safe_amount_after_fee` | float | Amount after deducting fees |
| `cost` | float | Cost of the order - usually average * filled (*Exchange dependent on futures trading, may contain the cost with or without leverage and may be in contracts.*) |
| `stop_price` | float | Stop price for stop orders. Empty for non-stoploss orders. |
| `stake_amount` | float | Stake amount used for this order. |
| `stake_amount_filled` | float | Filled Stake amount used for this order. |
| `order_date` | datetime | Order creation date **use `order_date_utc` instead** |
| `order_date_utc` | datetime | Order creation date (in UTC) |
| `order_fill_date` | datetime | Order fill date **use `order_fill_utc` instead** |
| `order_fill_date_utc` | datetime | Order fill date |
| `order_filled_date` | datetime | Order fill date **use `order_filled_utc` instead** |
| `order_filled_utc` | datetime | Order fill date |
| `order_update_date` | datetime | Last order update date |

4
docs/updating.md
View File

@@ -42,7 +42,3 @@ freqtrade install-ui
Update-problems usually come missing dependencies (you didn't follow the above instructions) - or from updated dependencies, which fail to install (for example TA-lib).
Please refer to the corresponding installation sections (common problems linked below)
Common problems and their solutions:
* [ta-lib update on windows](windows_installation.md#install-ta-lib)

23
docs/webhook-config.md
View File

@@ -80,6 +80,29 @@ When using the Form-Encoded or JSON-Encoded configuration you can configure any
The result would be a POST request with e.g. `Status: running` body and `Content-Type: text/plain` header.
### Nested Webhook Configuration
Some webhook targets require a nested structure.
This can be accomplished by setting the content as dictionary or list instead of as text directly.
This is only supported for the JSON format.
```json
"webhook": {
"enabled": true,
"url": "https://<yourhookurl>",
"format": "json",
"status": {
"msgtype": "text",
"text": {
"content": "Status update: {status}"
}
}
}
```
The result would be a POST request with e.g. `{"msgtype":"text","text":{"content":"Status update: running"}}` body and `Content-Type: application/json` header.
## Additional configurations
The `webhook.retries` parameter can be set for the maximum number of retries the webhook request should attempt if it is unsuccessful (i.e. HTTP response status is not 200). By default this is set to `0` which is disabled. An additional `webhook.retry_delay` parameter can be set to specify the time in seconds between retry attempts. By default this is set to `0.1` (i.e. 100ms). Note that increasing the number of retries or retry delay may slow down the trader if there are connectivity issues with the webhook.

24
docs/windows_installation.md
View File

@@ -38,30 +38,6 @@ cd freqtrade
!!! Hint
Using the [Anaconda Distribution](https://www.anaconda.com/distribution/) under Windows can greatly help with installation problems. Check out the [Anaconda installation section](installation.md#installation-with-conda) in the documentation for more information.
### Install ta-lib
Install ta-lib according to the [ta-lib documentation](https://github.com/TA-Lib/ta-lib-python#windows).
As compiling from source on windows has heavy dependencies (requires a partial visual studio installation), Freqtrade provides these dependencies (in the binary wheel format) for the latest 3 Python versions (3.11, 3.12 and 3.13) and for 64bit Windows.
These Wheels are also used by CI running on windows, and are therefore tested together with freqtrade.
Other versions must be downloaded from the above link.
``` powershell
cd \path\freqtrade
python -m venv .venv
.venv\Scripts\activate.ps1
# optionally install ta-lib from wheel
# Eventually adjust the below filename to match the downloaded wheel
pip install --find-links build_helpers\ TA-Lib -U
pip install -r requirements.txt
pip install -e .
freqtrade
```
!!! Note "Use Powershell"
The above installation script assumes you're using powershell on a 64bit windows.
Commands for the legacy CMD windows console may differ.
### Error during installation on Windows

2
freqtrade/__init__.py
View File

@@ -1,6 +1,6 @@
"""Freqtrade bot"""
__version__ = "2025.8-dev"
__version__ = "2025.10-dev"
if "dev" in __version__:
from pathlib import Path

2
freqtrade/commands/analyze_commands.py
View File

@@ -17,7 +17,7 @@ def start_analysis_entries_exits(args: dict[str, Any]) -> None:
from freqtrade.data.entryexitanalysis import process_entry_exit_reasons
# Initialize configuration
config = setup_utils_configuration(args, RunMode.BACKTEST)
config = setup_utils_configuration(args, RunMode.UTIL_NO_EXCHANGE)
logger.info("Starting freqtrade in analysis mode")

18
freqtrade/commands/arguments.py
View File

@@ -49,11 +49,13 @@ ARGS_BACKTEST = [
*ARGS_COMMON_OPTIMIZE,
"position_stacking",
"enable_protections",
"enable_dynamic_pairlist",
"dry_run_wallet",
"timeframe_detail",
"strategy_list",
"export",
"exportfilename",
"exportdirectory",
"backtest_breakdown",
"backtest_cache",
"freqai_backtest_live_models",
@@ -94,7 +96,12 @@ ARGS_LIST_FREQAIMODELS = ["freqaimodel_path", "print_one_column"]
ARGS_LIST_HYPEROPTS = ["hyperopt_path", "print_one_column"]
ARGS_BACKTEST_SHOW = ["exportfilename", "backtest_show_pair_list", "backtest_breakdown"]
ARGS_BACKTEST_SHOW = [
"exportfilename",
"exportdirectory",
"backtest_show_pair_list",
"backtest_breakdown",
]
ARGS_LIST_EXCHANGES = ["print_one_column", "list_exchanges_all", "trading_mode", "dex_exchanges"]
@@ -158,6 +165,7 @@ ARGS_DOWNLOAD_DATA = [
"days",
"new_pairs_days",
"include_inactive",
"no_parallel_download",
"timerange",
"download_trades",
"convert_trades",
@@ -233,6 +241,7 @@ ARGS_HYPEROPT_SHOW = [
ARGS_ANALYZE_ENTRIES_EXITS = [
"exportfilename",
"exportdirectory",
"analysis_groups",
"enter_reason_list",
"exit_reason_list",
@@ -252,7 +261,12 @@ ARGS_LOOKAHEAD_ANALYSIS = [
a
for a in ARGS_BACKTEST
if a not in ("position_stacking", "backtest_cache", "backtest_breakdown", "backtest_notes")
] + ["minimum_trade_amount", "targeted_trade_amount", "lookahead_analysis_exportfilename"]
] + [
"minimum_trade_amount",
"targeted_trade_amount",
"lookahead_analysis_exportfilename",
"lookahead_allow_limit_orders",
]
ARGS_RECURSIVE_ANALYSIS = ["timeframe", "timerange", "dataformat_ohlcv", "pairs", "startup_candle"]

48
freqtrade/commands/cli_options.py
View File

@@ -184,12 +184,20 @@ AVAILABLE_CLI_OPTIONS = {
"enable_protections": Arg(
"--enable-protections",
"--enableprotections",
help="Enable protections for backtesting."
help="Enable protections for backtesting. "
"Will slow backtesting down by a considerable amount, but will include "
"configured protections",
action="store_true",
default=False,
),
"enable_dynamic_pairlist": Arg(
"--enable-dynamic-pairlist",
help="Enables dynamic pairlist refreshes in backtesting. "
"The pairlist will be generated for each new candle if you're using a "
"pairlist handler that supports this feature, for example, ShuffleFilter.",
action="store_true",
default=False,
),
"strategy_list": Arg(
"--strategy-list",
help="Provide a space-separated list of strategies to backtest. "
@@ -199,22 +207,29 @@ AVAILABLE_CLI_OPTIONS = {
"(so `backtest-data.json` becomes `backtest-data-SampleStrategy.json`",
nargs="+",
),
"export": Arg(
"--export",
help="Export backtest results (default: trades).",
choices=constants.EXPORT_OPTIONS,
),
"backtest_notes": Arg(
"--notes",
help="Add notes to the backtest results.",
metavar="TEXT",
),
"export": Arg(
"--export",
help="Export backtest results (default: trades).",
choices=constants.EXPORT_OPTIONS,
),
"exportdirectory": Arg(
"--backtest-directory",
"--export-directory",
help="Directory to use for backtest results. "
"Example: `--export-directory=user_data/backtest_results/`. ",
metavar="PATH",
),
"exportfilename": Arg(
"--export-filename",
"--backtest-filename",
"--export-filename",
help="Use this filename for backtest results."
"Requires `--export` to be set as well. "
"Example: `--export-filename=user_data/backtest_results/backtest_today.json`",
"Example: `--backtest-filename=backtest_results_2020-09-27_16-20-48.json`. "
"Assumes either `user_data/backtest_results/` or `--export-directory` as base directory.",
metavar="PATH",
),
"disableparamexport": Arg(
@@ -230,7 +245,7 @@ AVAILABLE_CLI_OPTIONS = {
),
"backtest_breakdown": Arg(
"--breakdown",
help="Show backtesting breakdown per [day, week, month, year].",
help="Show backtesting breakdown per [day, week, month, year, weekday].",
nargs="+",
choices=constants.BACKTEST_BREAKDOWNS,
),
@@ -447,6 +462,11 @@ AVAILABLE_CLI_OPTIONS = {
help="Also download data from inactive pairs.",
action="store_true",
),
"no_parallel_download": Arg(
"--no-parallel-download",
help="Disable parallel startup download. Only use this if you experience issues.",
action="store_true",
),
"new_pairs_days": Arg(
"--new-pairs-days",
help="Download data of new pairs for given number of days. Default: `%(default)s`.",
@@ -794,6 +814,14 @@ AVAILABLE_CLI_OPTIONS = {
help="Specify startup candles to be checked (`199`, `499`, `999`, `1999`).",
nargs="+",
),
"lookahead_allow_limit_orders": Arg(
"--allow-limit-orders",
help=(
"Allow limit orders in lookahead analysis (could cause false positives "
"in lookahead analysis results)."
),
action="store_true",
),
"show_sensitive": Arg(
"--show-sensitive",
help="Show secrets in the output.",

8
freqtrade/commands/data_commands.py
View File

@@ -6,7 +6,7 @@ from typing import Any
from freqtrade.constants import DATETIME_PRINT_FORMAT, DL_DATA_TIMEFRAMES, Config
from freqtrade.enums import CandleType, RunMode, TradingMode
from freqtrade.exceptions import ConfigurationError
from freqtrade.plugins.pairlist.pairlist_helpers import dynamic_expand_pairlist
from freqtrade.plugins.pairlist.pairlist_helpers import dynamic_expand_pairlist, expand_pairlist
logger = logging.getLogger(__name__)
@@ -134,7 +134,8 @@ def start_list_data(args: dict[str, Any]) -> None:
config["datadir"], config.get("trading_mode", TradingMode.SPOT)
)
if args["pairs"]:
paircombs = [comb for comb in paircombs if comb[0] in args["pairs"]]
pl = expand_pairlist(args["pairs"], [p[0] for p in paircombs], keep_invalid=True)
paircombs = [comb for comb in paircombs if comb[0] in pl]
title = f"Found {len(paircombs)} pair / timeframe combinations."
if not config.get("show_timerange"):
groupedpair = defaultdict(list)
@@ -197,7 +198,8 @@ def start_list_trades_data(args: dict[str, Any]) -> None:
)
if args["pairs"]:
paircombs = [comb for comb in paircombs if comb in args["pairs"]]
pl = expand_pairlist(args["pairs"], [p for p in paircombs], keep_invalid=True)
paircombs = [comb for comb in paircombs if comb in pl]
title = f"Found trades data for {len(paircombs)} {plural(len(paircombs), 'pair')}."
if not config.get("show_timerange"):

5
freqtrade/commands/list_commands.py
View File

@@ -66,7 +66,7 @@ def start_list_exchanges(args: dict[str, Any]) -> None:
if exchange["is_alias"]:
name.stylize("strike")
classname.stylize("strike")
classname.append(f" (use {exchange['alias_for']})", style="italic")
classname.append(f"\n -> use {exchange['alias_for']}", style="italic")
trade_modes = Text(
", ".join(
@@ -146,6 +146,9 @@ def start_list_strategies(args: dict[str, Any]) -> None:
strategy_objs = StrategyResolver.search_all_objects(
config, not args["print_one_column"], config.get("recursive_strategy_search", False)
)
if not strategy_objs:
logger.warning("No strategies found.")
return
# Sort alphabetically
strategy_objs = sorted(strategy_objs, key=lambda x: x["name"])
for obj in strategy_objs:

2
freqtrade/commands/optimize_commands.py
View File

@@ -72,7 +72,7 @@ def start_backtesting_show(args: dict[str, Any]) -> None:
from freqtrade.data.btanalysis import load_backtest_stats
from freqtrade.optimize.optimize_reports import show_backtest_results, show_sorted_pairlist
results = load_backtest_stats(config["exportfilename"])
results = load_backtest_stats(config["exportdirectory"], config["exportfilename"])
show_backtest_results(config, results)
show_sorted_pairlist(config, results)

12
freqtrade/config_schema/config_schema.py
View File

@@ -453,6 +453,7 @@ CONF_SCHEMA = {
"pairlists": {
"description": "Configuration for pairlists.",
"type": "array",
"minItems": 1,
"items": {
"type": "object",
"properties": {
@@ -1141,6 +1142,15 @@ CONF_SCHEMA = {
"type": "boolean",
"default": False,
},
"override_exchange_check": {
"description": (
"Override the exchange check to force FreqAI to use exchanges "
"that may not have enough historic data. Turn this to True if "
"you know your FreqAI model and strategy do not require historical data."
),
"type": "boolean",
"default": False,
},
"feature_parameters": {
"description": "The parameters used to engineer the feature set",
"type": "object",
@@ -1381,6 +1391,7 @@ SCHEMA_TRADE_REQUIRED = [
"entry_pricing",
"stoploss",
"minimal_roi",
"pairlists",
"internals",
"dataformat_ohlcv",
"dataformat_trades",
@@ -1390,6 +1401,7 @@ SCHEMA_BACKTEST_REQUIRED = [
"exchange",
"stake_currency",
"stake_amount",
"pairlists",
"dry_run_wallet",
"dataformat_ohlcv",
"dataformat_trades",

4
freqtrade/configuration/config_validation.py
View File

@@ -66,7 +66,8 @@ def validate_config_schema(conf: dict[str, Any], preliminary: bool = False) -> d
return conf
except ValidationError as e:
logger.critical(f"Invalid configuration. Reason: {e}")
raise ValidationError(best_match(Draft4Validator(conf_schema).iter_errors(conf)).message)
result = best_match(FreqtradeValidator(conf_schema).iter_errors(conf))
raise ConfigurationError(result.message)
def validate_config_consistency(conf: dict[str, Any], *, preliminary: bool = False) -> None:
@@ -112,7 +113,6 @@ def _validate_price_config(conf: dict[str, Any]) -> None:
"""
When using market orders, price sides must be using the "other" side of the price
"""
# TODO: The below could be an enforced setting when using market orders
if conf.get("order_types", {}).get("entry") == "market" and conf.get("entry_pricing", {}).get(
"price_side"
) not in ("ask", "other"):

50
freqtrade/configuration/configuration.py
View File

@@ -12,13 +12,16 @@ from typing import Any
from freqtrade import constants
from freqtrade.configuration.deprecated_settings import process_temporary_deprecated_settings
from freqtrade.configuration.directory_operations import create_datadir, create_userdata_dir
from freqtrade.configuration.environment_vars import enironment_vars_to_dict
from freqtrade.configuration.environment_vars import environment_vars_to_dict
from freqtrade.configuration.load_config import load_file, load_from_files
from freqtrade.constants import Config
from freqtrade.enums import (
NON_UTIL_MODES,
TRADE_MODES,
CandleType,
MarginMode,
RunMode,
TradingMode,
)
from freqtrade.exceptions import OperationalException
from freqtrade.loggers import setup_logging
@@ -77,16 +80,13 @@ class Configuration:
from freqtrade.commands.arguments import NO_CONF_ALLOWED
if self.args.get("command") not in NO_CONF_ALLOWED:
env_data = enironment_vars_to_dict()
env_data = environment_vars_to_dict()
config = deep_merge_dicts(env_data, config)
# Normalize config
if "internals" not in config:
config["internals"] = {}
if "pairlists" not in config:
config["pairlists"] = []
# Keep a copy of the original configuration file
config["original_config"] = deepcopy(config)
@@ -212,13 +212,31 @@ class Configuration:
config.update({"datadir": create_datadir(config, self.args.get("datadir"))})
logger.info("Using data directory: %s ...", config.get("datadir"))
self._args_to_config(
config, argname="exportdirectory", logstring="Using {} as backtest directory ..."
)
if self.args.get("exportfilename"):
self._args_to_config(
config, argname="exportfilename", logstring="Storing backtest results to {} ..."
)
config["exportfilename"] = Path(config["exportfilename"])
else:
config["exportfilename"] = config["user_data_dir"] / "backtest_results"
if config.get("exportdirectory") and Path(config["exportdirectory"]).is_dir():
logger.warning(
"DEPRECATED: Using `--export-filename` with directories is deprecated, "
"use `--backtest-directory` instead."
)
if config.get("exportdirectory") is None:
# Fallback - assign export-directory directly.
config["exportdirectory"] = config["exportfilename"]
if not config.get("exportdirectory"):
config["exportdirectory"] = config["user_data_dir"] / "backtest_results"
if not config.get("exportfilename"):
config["exportfilename"] = None
if config.get("exportfilename"):
# ensure exportfilename is a Path object
config["exportfilename"] = Path(config["exportfilename"])
config["exportdirectory"] = Path(config["exportdirectory"])
if self.args.get("show_sensitive"):
logger.warning(
@@ -244,7 +262,13 @@ class Configuration:
self._args_to_config(
config,
argname="enable_protections",
logstring="Parameter --enable-protections detected, enabling Protections. ...",
logstring="Parameter --enable-protections detected, enabling Protections ...",
)
self._args_to_config(
config,
argname="enable_dynamic_pairlist",
logstring="Parameter --enable-dynamic-pairlist detected, enabling dynamic pairlist ...",
)
if self.args.get("max_open_trades"):
@@ -300,7 +324,6 @@ class Configuration:
"recursive_strategy_search",
"Recursively searching for a strategy in the strategies folder.",
),
("timeframe", "Overriding timeframe with Command line argument"),
("export", "Parameter --export detected: {} ..."),
("backtest_breakdown", "Parameter --breakdown detected ..."),
("backtest_cache", "Parameter --cache={} detected ..."),
@@ -379,6 +402,7 @@ class Configuration:
("timeframes", "timeframes --timeframes: {}"),
("days", "Detected --days: {}"),
("include_inactive", "Detected --include-inactive-pairs: {}"),
("no_parallel_download", "Detected --no-parallel-download: {}"),
("download_trades", "Detected --dl-trades: {}"),
("convert_trades", "Detected --convert: {} - Converting Trade data to OHCV {}"),
("dataformat_ohlcv", 'Using "{}" to store OHLCV data.'),
@@ -394,6 +418,14 @@ class Configuration:
self._args_to_config(
config, argname="trading_mode", logstring="Detected --trading-mode: {}"
)
# TODO: The following 3 lines (candle_type_def, trading_mode, margin_mode) are actually
# set in the exchange class. They're however necessary as fallback to avoid
# random errors in commands that don't initialize an exchange.
config["candle_type_def"] = CandleType.get_default(
config.get("trading_mode", "spot") or "spot"
)
config["trading_mode"] = TradingMode(config.get("trading_mode", "spot") or "spot")
config["margin_mode"] = MarginMode(config.get("margin_mode", "") or "")
self._args_to_config(
config, argname="candle_types", logstring="Detected --candle-types: {}"
)

2
freqtrade/configuration/environment_vars.py
View File

@@ -73,7 +73,7 @@ def _flat_vars_to_nested_dict(env_dict: dict[str, Any], prefix: str) -> dict[str
return relevant_vars
def enironment_vars_to_dict() -> dict[str, Any]:
def environment_vars_to_dict() -> dict[str, Any]:
"""
Read environment variables and return a nested dict for relevant variables
Relevant variables must follow the FREQTRADE__{section}__{key} pattern

3
freqtrade/configuration/timerange.py
View File

@@ -80,6 +80,9 @@ class TimeRange:
val = stopdt.strftime(DATETIME_PRINT_FORMAT)
return val
def __repr__(self) -> str:
return f"TimeRange({self.timerange_str})"
def __eq__(self, other):
"""Override the default Equals behavior"""
return (

3
freqtrade/constants.py
View File

@@ -49,6 +49,7 @@ AVAILABLE_PAIRLISTS = [
"RemotePairList",
"MarketCapPairList",
"AgeFilter",
"DelistFilter",
"FullTradesFilter",
"OffsetFilter",
"PerformanceFilter",
@@ -60,7 +61,7 @@ AVAILABLE_PAIRLISTS = [
"VolatilityFilter",
]
AVAILABLE_DATAHANDLERS = ["json", "jsongz", "feather", "parquet"]
BACKTEST_BREAKDOWNS = ["day", "week", "month", "year"]
BACKTEST_BREAKDOWNS = ["day", "week", "month", "year", "weekday"]
BACKTEST_CACHE_AGE = ["none", "day", "week", "month"]
BACKTEST_CACHE_DEFAULT = "day"
DRY_RUN_WALLET = 1000

3
freqtrade/data/btanalysis/__init__.py
View File

@@ -16,10 +16,7 @@ from .bt_fileutils import (
load_backtest_data,
load_backtest_metadata,
load_backtest_stats,
load_exit_signal_candles,
load_file_from_zip,
load_rejected_signals,
load_signal_candles,
load_trades,
load_trades_from_db,
trade_list_to_dataframe,

113
freqtrade/data/btanalysis/bt_fileutils.py
View File

@@ -155,33 +155,55 @@ def load_backtest_metadata(filename: Path | str) -> dict[str, Any]:
raise OperationalException("Unexpected error while loading backtest metadata.") from e
def load_backtest_stats(filename: Path | str) -> BacktestResultType:
def _normalize_filename(file_or_directory: Path | str, filename: Path | str | None) -> Path:
"""
Normalize the filename by ensuring it is a Path object.
:param file_or_directory: The directory or file to normalize.
:param filename: The filename to normalize.
:return: A Path object representing the normalized filename.
"""
if isinstance(file_or_directory, str):
file_or_directory = Path(file_or_directory)
if file_or_directory.is_dir():
if not filename:
filename = get_latest_backtest_filename(file_or_directory)
if Path(filename).is_file():
fn = Path(filename)
else:
fn = file_or_directory / filename
else:
fn = file_or_directory
return fn
def load_backtest_stats(
file_or_directory: Path | str, filename: Path | str | None = None
) -> BacktestResultType:
"""
Load backtest statistics file.
:param filename: pathlib.Path object, or string pointing to the file.
:param file_or_directory: pathlib.Path object, or string pointing to the directory,
or absolute/relative path to the backtest results file.
:param filename: Optional filename to load from (if different from the main filename).
Only valid when loading from a directory.
:return: a dictionary containing the resulting file.
"""
if isinstance(filename, str):
filename = Path(filename)
if filename.is_dir():
filename = filename / get_latest_backtest_filename(filename)
if not filename.is_file():
raise ValueError(f"File {filename} does not exist.")
logger.info(f"Loading backtest result from {filename}")
fn = _normalize_filename(file_or_directory, filename)
if filename.suffix == ".zip":
if not fn.is_file():
raise ValueError(f"File or directory {fn} does not exist.")
logger.info(f"Loading backtest result from {fn}")
if fn.suffix == ".zip":
data = json_load(
StringIO(
load_file_from_zip(filename, filename.with_suffix(".json").name).decode("utf-8")
)
StringIO(load_file_from_zip(fn, fn.with_suffix(".json").name).decode("utf-8"))
)
else:
with filename.open() as file:
with fn.open() as file:
data = json_load(file)
# Legacy list format does not contain metadata.
if isinstance(data, dict):
data["metadata"] = load_backtest_metadata(filename)
data["metadata"] = load_backtest_metadata(fn)
return data
@@ -362,16 +384,21 @@ def _load_backtest_data_df_compatibility(df: pd.DataFrame) -> pd.DataFrame:
return df
def load_backtest_data(filename: Path | str, strategy: str | None = None) -> pd.DataFrame:
def load_backtest_data(
file_or_directory: Path | str, strategy: str | None = None, filename: Path | str | None = None
) -> pd.DataFrame:
"""
Load backtest data file.
:param filename: pathlib.Path object, or string pointing to a file or directory
Load backtest data file, returns a dataframe with the individual trades.
:param file_or_directory: pathlib.Path object, or string pointing to the directory,
or absolute/relative path to the backtest results file.
:param strategy: Strategy to load - mainly relevant for multi-strategy backtests
Can also serve as protection to load the correct result.
:param filename: Optional filename to load from (if different from the main filename).
Only valid when loading from a directory.
:return: a dataframe with the analysis results
:raise: ValueError if loading goes wrong.
"""
data = load_backtest_stats(filename)
data = load_backtest_stats(file_or_directory, filename)
if not isinstance(data, list):
# new, nested format
if "strategy" not in data:
@@ -430,20 +457,23 @@ def load_file_from_zip(zip_path: Path, filename: str) -> bytes:
raise ValueError(f"Bad zip file: {zip_path}.") from None
def load_backtest_analysis_data(backtest_dir: Path, name: str):
def load_backtest_analysis_data(
file_or_directory: Path,
name: Literal["signals", "rejected", "exited"],
filename: Path | str | None = None,
):
"""
Load backtest analysis data either from a pickle file or from within a zip file
:param backtest_dir: Directory containing backtest results
:param file_or_directory: pathlib.Path object, or string pointing to the directory,
or absolute/relative path to the backtest results file.
:param name: Name of the analysis data to load (signals, rejected, exited)
:param filename: Optional filename to load from (if different from the main filename).
Only valid when loading from a directory.
:return: Analysis data
"""
import joblib
if backtest_dir.is_dir():
lbf = Path(get_latest_backtest_filename(backtest_dir))
zip_path = backtest_dir / lbf
else:
zip_path = backtest_dir
zip_path = _normalize_filename(file_or_directory, filename)
if zip_path.suffix == ".zip":
# Load from zip file
@@ -458,10 +488,10 @@ def load_backtest_analysis_data(backtest_dir: Path, name: str):
else:
# Load from separate pickle file
if backtest_dir.is_dir():
scpf = Path(backtest_dir, f"{zip_path.stem}_{name}.pkl")
if file_or_directory.is_dir():
scpf = Path(file_or_directory, f"{zip_path.stem}_{name}.pkl")
else:
scpf = Path(backtest_dir.parent / f"{backtest_dir.stem}_{name}.pkl")
scpf = Path(file_or_directory.parent / f"{file_or_directory.stem}_{name}.pkl")
try:
with scpf.open("rb") as scp:
@@ -473,27 +503,6 @@ def load_backtest_analysis_data(backtest_dir: Path, name: str):
return None
def load_rejected_signals(backtest_dir: Path):
"""
Load rejected signals from backtest directory
"""
return load_backtest_analysis_data(backtest_dir, "rejected")
def load_signal_candles(backtest_dir: Path):
"""
Load signal candles from backtest directory
"""
return load_backtest_analysis_data(backtest_dir, "signals")
def load_exit_signal_candles(backtest_dir: Path) -> dict[str, dict[str, pd.DataFrame]]:
"""
Load exit signal candles from backtest directory
"""
return load_backtest_analysis_data(backtest_dir, "exited")
def trade_list_to_dataframe(trades: list[Trade] | list[LocalTrade]) -> pd.DataFrame:
"""
Convert list of Trade objects to pandas Dataframe
@@ -502,8 +511,8 @@ def trade_list_to_dataframe(trades: list[Trade] | list[LocalTrade]) -> pd.DataFr
"""
df = pd.DataFrame.from_records([t.to_json(True) for t in trades], columns=BT_DATA_COLUMNS)
if len(df) > 0:
df["close_date"] = pd.to_datetime(df["close_date"], utc=True)
df["open_date"] = pd.to_datetime(df["open_date"], utc=True)
df["close_date"] = pd.to_datetime(df["close_timestamp"], unit="ms", utc=True)
df["open_date"] = pd.to_datetime(df["open_timestamp"], unit="ms", utc=True)
df["close_rate"] = df["close_rate"].astype("float64")
return df

1
freqtrade/data/converter/converter.py
View File

@@ -181,7 +181,6 @@ def trim_dataframes(
def order_book_to_dataframe(bids: list, asks: list) -> DataFrame:
"""
TODO: This should get a dedicated test
Gets order book list, returns dataframe with below format per suggested by creslin
-------------------------------------------------------------------
b_sum b_size bids asks a_size a_sum

47
freqtrade/data/dataprovider.py
View File

@@ -23,7 +23,7 @@ from freqtrade.data.history import get_datahandler, load_pair_history
from freqtrade.enums import CandleType, RPCMessageType, RunMode, TradingMode
from freqtrade.exceptions import ExchangeError, OperationalException
from freqtrade.exchange import Exchange, timeframe_to_prev_date, timeframe_to_seconds
from freqtrade.exchange.exchange_types import OrderBook
from freqtrade.exchange.exchange_types import FundingRate, OrderBook
from freqtrade.misc import append_candles_to_dataframe
from freqtrade.rpc import RPCManager
from freqtrade.rpc.rpc_types import RPCAnalyzedDFMsg
@@ -498,7 +498,12 @@ class DataProvider:
return DataFrame()
def trades(
self, pair: str, timeframe: str | None = None, copy: bool = True, candle_type: str = ""
self,
pair: str,
timeframe: str | None = None,
copy: bool = True,
candle_type: str = "",
timerange: TimeRange | None = None,
) -> DataFrame:
"""
Get candle (TRADES) data for the given pair as DataFrame
@@ -526,7 +531,7 @@ class DataProvider:
self._config["datadir"], data_format=self._config["dataformat_trades"]
)
trades_df = data_handler.trades_load(
pair, self._config.get("trading_mode", TradingMode.SPOT)
pair, self._config.get("trading_mode", TradingMode.SPOT), timerange=timerange
)
return trades_df
@@ -543,6 +548,7 @@ class DataProvider:
def ticker(self, pair: str):
"""
Return last ticker data from exchange
Warning: Performs a network request - so use with common sense.
:param pair: Pair to get the data for
:return: Ticker dict from exchange or empty dict if ticker is not available for the pair
"""
@@ -556,7 +562,7 @@ class DataProvider:
def orderbook(self, pair: str, maximum: int) -> OrderBook:
"""
Fetch latest l2 orderbook data
Warning: Does a network request - so use with common sense.
Warning: Performs a network request - so use with common sense.
:param pair: pair to get the data for
:param maximum: Maximum number of orderbook entries to query
:return: dict including bids/asks with a total of `maximum` entries.
@@ -565,6 +571,23 @@ class DataProvider:
raise OperationalException(NO_EXCHANGE_EXCEPTION)
return self._exchange.fetch_l2_order_book(pair, maximum)
def funding_rate(self, pair: str) -> FundingRate:
"""
Return Funding rate from the exchange
Warning: Performs a network request - so use with common sense.
:param pair: Pair to get the data for
:return: Funding rate dict from exchange or empty dict if funding rate is not available
If available, the "fundingRate" field will contain the funding rate.
"fundingTimestamp" and "fundingDatetime" will contain the next funding times.
Actually filled fields may vary between exchanges.
"""
if self._exchange is None:
raise OperationalException(NO_EXCHANGE_EXCEPTION)
try:
return self._exchange.fetch_funding_rate(pair)
except ExchangeError:
return {}
def send_msg(self, message: str, *, always_send: bool = False) -> None:
"""
Send custom RPC Notifications from your bot.
@@ -581,3 +604,19 @@ class DataProvider:
if always_send or message not in self.__msg_cache:
self._msg_queue.append(message)
self.__msg_cache[message] = True
def check_delisting(self, pair: str) -> datetime | None:
"""
Check if a pair gonna be delisted on the exchange.
Will only return datetime if the pair is gonna be delisted.
:param pair: Pair to check
:return: Datetime of the pair's delisting, None otherwise
"""
if self._exchange is None:
raise OperationalException(NO_EXCHANGE_EXCEPTION)
try:
return self._exchange.check_delisting_time(pair)
except ExchangeError:
logger.warning(f"Could not fetch market data for {pair}. Assuming no delisting.")
return None

26
freqtrade/data/entryexitanalysis.py
View File

@@ -7,11 +7,9 @@ from freqtrade.configuration import TimeRange
from freqtrade.constants import Config
from freqtrade.data.btanalysis import (
BT_DATA_COLUMNS,
load_backtest_analysis_data,
load_backtest_data,
load_backtest_stats,
load_exit_signal_candles,
load_rejected_signals,
load_signal_candles,
)
from freqtrade.exceptions import ConfigurationError, OperationalException
from freqtrade.util import print_df_rich_table
@@ -332,7 +330,7 @@ def process_entry_exit_reasons(config: Config):
do_rejected = config.get("analysis_rejected", False)
to_csv = config.get("analysis_to_csv", False)
csv_path = Path(
config.get("analysis_csv_path", config["exportfilename"]), # type: ignore[arg-type]
config.get("analysis_csv_path", config["exportdirectory"]), # type: ignore[arg-type]
)
if entry_only is True and exit_only is True:
@@ -346,20 +344,30 @@ def process_entry_exit_reasons(config: Config):
None if config.get("timerange") is None else str(config.get("timerange"))
)
try:
backtest_stats = load_backtest_stats(config["exportfilename"])
backtest_stats = load_backtest_stats(
config["exportdirectory"], config["exportfilename"]
)
except ValueError as e:
raise ConfigurationError(e) from e
for strategy_name, results in backtest_stats["strategy"].items():
trades = load_backtest_data(config["exportfilename"], strategy_name)
trades = load_backtest_data(
config["exportdirectory"], strategy_name, config["exportfilename"]
)
if trades is not None and not trades.empty:
signal_candles = load_signal_candles(config["exportfilename"])
exit_signals = load_exit_signal_candles(config["exportfilename"])
signal_candles = load_backtest_analysis_data(
config["exportdirectory"], "signals", config["exportfilename"]
)
exit_signals = load_backtest_analysis_data(
config["exportdirectory"], "exited", config["exportfilename"]
)
rej_df = None
if do_rejected:
rejected_signals_dict = load_rejected_signals(config["exportfilename"])
rejected_signals_dict = load_backtest_analysis_data(
config["exportdirectory"], "rejected", config["exportfilename"]
)
rej_df = prepare_results(
rejected_signals_dict,
strategy_name,

56
freqtrade/data/history/datahandlers/featherdatahandler.py
View File

@@ -1,6 +1,7 @@
import logging
from pandas import DataFrame, read_feather, to_datetime
from pyarrow import dataset
from freqtrade.configuration import TimeRange
from freqtrade.constants import DEFAULT_DATAFRAME_COLUMNS, DEFAULT_TRADES_COLUMNS
@@ -111,22 +112,71 @@ class FeatherDataHandler(IDataHandler):
"""
raise NotImplementedError()
def _build_arrow_time_filter(self, timerange: TimeRange | None):
"""
Build Arrow predicate filter for timerange filtering.
Treats 0 as unbounded (no filter on that side).
:param timerange: TimeRange object with start/stop timestamps
:return: Arrow filter expression or None if fully unbounded
"""
if not timerange:
return None
# Treat 0 as unbounded
start_set = bool(timerange.startts and timerange.startts > 0)
stop_set = bool(timerange.stopts and timerange.stopts > 0)
if not (start_set or stop_set):
return None
ts_field = dataset.field("timestamp")
exprs = []
if start_set:
exprs.append(ts_field >= timerange.startts)
if stop_set:
exprs.append(ts_field <= timerange.stopts)
if len(exprs) == 1:
return exprs[0]
else:
return exprs[0] & exprs[1]
def _trades_load(
self, pair: str, trading_mode: TradingMode, timerange: TimeRange | None = None
) -> DataFrame:
"""
Load a pair from file, either .json.gz or .json
# TODO: respect timerange ...
:param pair: Load trades for this pair
:param trading_mode: Trading mode to use (used to determine the filename)
:param timerange: Timerange to load trades for - currently not implemented
:param timerange: Timerange to load trades for - filters data to this range if provided
:return: Dataframe containing trades
"""
filename = self._pair_trades_filename(self._datadir, pair, trading_mode)
if not filename.exists():
return DataFrame(columns=DEFAULT_TRADES_COLUMNS)
tradesdata = read_feather(filename)
# Use Arrow dataset with optional timerange filtering, fallback to read_feather
try:
dataset_reader = dataset.dataset(filename, format="feather")
time_filter = self._build_arrow_time_filter(timerange)
if time_filter is not None and timerange is not None:
tradesdata = dataset_reader.to_table(filter=time_filter).to_pandas()
start_desc = timerange.startts if timerange.startts > 0 else "unbounded"
stop_desc = timerange.stopts if timerange.stopts > 0 else "unbounded"
logger.debug(
f"Loaded {len(tradesdata)} trades for {pair} "
f"(filtered start={start_desc}, stop={stop_desc})"
)
else:
tradesdata = dataset_reader.to_table().to_pandas()
logger.debug(f"Loaded {len(tradesdata)} trades for {pair} (unfiltered)")
except (ImportError, AttributeError, ValueError) as e:
# Fallback: load entire file
logger.warning(f"Unable to use Arrow filtering, loading entire trades file: {e}")
tradesdata = read_feather(filename)
return tradesdata

124
freqtrade/data/history/history_utils.py
View File

@@ -6,7 +6,14 @@ from pathlib import Path
from pandas import DataFrame, concat
from freqtrade.configuration import TimeRange
from freqtrade.constants import DATETIME_PRINT_FORMAT, DL_DATA_TIMEFRAMES, DOCS_LINK, Config
from freqtrade.constants import (
DATETIME_PRINT_FORMAT,
DL_DATA_TIMEFRAMES,
DOCS_LINK,
Config,
ListPairsWithTimeframes,
PairWithTimeframe,
)
from freqtrade.data.converter import (
clean_ohlcv_dataframe,
convert_trades_to_ohlcv,
@@ -17,6 +24,7 @@ from freqtrade.data.history.datahandlers import IDataHandler, get_datahandler
from freqtrade.enums import CandleType, TradingMode
from freqtrade.exceptions import OperationalException
from freqtrade.exchange import Exchange
from freqtrade.exchange.exchange_utils import date_minus_candles
from freqtrade.plugins.pairlist.pairlist_helpers import dynamic_expand_pairlist
from freqtrade.util import dt_now, dt_ts, format_ms_time, format_ms_time_det
from freqtrade.util.migrations import migrate_data
@@ -97,7 +105,7 @@ def load_data(
"""
result: dict[str, DataFrame] = {}
if startup_candles > 0 and timerange:
logger.info(f"Using indicator startup period: {startup_candles} ...")
logger.debug(f"Using indicator startup period: {startup_candles} ...")
data_handler = get_datahandler(datadir, data_format)
@@ -226,6 +234,7 @@ def _download_pair_history(
candle_type: CandleType,
erase: bool = False,
prepend: bool = False,
pair_candles: DataFrame | None = None,
) -> bool:
"""
Download latest candles from the exchange for the pair and timeframe passed in parameters
@@ -238,6 +247,7 @@ def _download_pair_history(
:param timerange: range of time to download
:param candle_type: Any of the enum CandleType (must match trading mode!)
:param erase: Erase existing data
:param pair_candles: Optional with "1 call" pair candles.
:return: bool with success state
"""
data_handler = get_datahandler(datadir, data_handler=data_handler)
@@ -271,21 +281,40 @@ def _download_pair_history(
"Current End: %s",
f"{data.iloc[-1]['date']:{DATETIME_PRINT_FORMAT}}" if not data.empty else "None",
)
# Default since_ms to 30 days if nothing is given
new_dataframe = exchange.get_historic_ohlcv(
pair=pair,
timeframe=timeframe,
since_ms=(
since_ms
if since_ms
else int((datetime.now() - timedelta(days=new_pairs_days)).timestamp()) * 1000
),
is_new_pair=data.empty,
candle_type=candle_type,
until_ms=until_ms if until_ms else None,
# used to check if the passed in pair_candles (parallel downloaded) covers since_ms.
# If we need more data, we have to fall back to the standard method.
pair_candles_since_ms = (
dt_ts(pair_candles.iloc[0]["date"])
if pair_candles is not None and len(pair_candles.index) > 0
else 0
)
logger.info(f"Downloaded data for {pair} with length {len(new_dataframe)}.")
if (
pair_candles is None
or len(pair_candles.index) == 0
or data.empty
or prepend is True
or erase is True
or pair_candles_since_ms > (since_ms if since_ms else 0)
):
new_dataframe = exchange.get_historic_ohlcv(
pair=pair,
timeframe=timeframe,
since_ms=(
since_ms
if since_ms
else int((datetime.now() - timedelta(days=new_pairs_days)).timestamp()) * 1000
),
is_new_pair=data.empty,
candle_type=candle_type,
until_ms=until_ms if until_ms else None,
)
logger.info(f"Downloaded data for {pair} with length {len(new_dataframe)}.")
else:
new_dataframe = pair_candles
logger.info(
f"Downloaded data for {pair} with length {len(new_dataframe)}. Parallel Method."
)
if data.empty:
data = new_dataframe
else:
@@ -330,6 +359,7 @@ def refresh_backtest_ohlcv_data(
data_format: str | None = None,
prepend: bool = False,
progress_tracker: CustomProgress | None = None,
no_parallel_download: bool = False,
) -> list[str]:
"""
Refresh stored ohlcv data for backtesting and hyperopt operations.
@@ -339,6 +369,7 @@ def refresh_backtest_ohlcv_data(
progress_tracker = retrieve_progress_tracker(progress_tracker)
pairs_not_available = []
fast_candles: dict[PairWithTimeframe, DataFrame] = {}
data_handler = get_datahandler(datadir, data_format)
candle_type = CandleType.get_default(trading_mode)
with progress_tracker as progress:
@@ -355,6 +386,30 @@ def refresh_backtest_ohlcv_data(
logger.info(f"Skipping pair {pair}...")
continue
for timeframe in timeframes:
# Get fast candles via parallel method on first loop through per timeframe
# and candle type. Downloads all the pairs in the list and stores them.
if (
not no_parallel_download
and exchange.get_option("download_data_parallel_quick", True)
and (
((pair, timeframe, candle_type) not in fast_candles)
and (erase is False)
and (prepend is False)
)
):
fast_candles.update(
_download_all_pairs_history_parallel(
exchange=exchange,
pairs=pairs,
timeframe=timeframe,
candle_type=candle_type,
timerange=timerange,
)
)
# get the already downloaded pair candles if they exist
pair_candles = fast_candles.pop((pair, timeframe, candle_type), None)
progress.update(timeframe_task, description=f"Timeframe {timeframe}")
logger.debug(f"Downloading pair {pair}, {candle_type}, interval {timeframe}.")
_download_pair_history(
@@ -368,6 +423,7 @@ def refresh_backtest_ohlcv_data(
candle_type=candle_type,
erase=erase,
prepend=prepend,
pair_candles=pair_candles, # optional pass of dataframe of parallel candles
)
progress.update(timeframe_task, advance=1)
if trading_mode == "futures":
@@ -404,6 +460,41 @@ def refresh_backtest_ohlcv_data(
return pairs_not_available
def _download_all_pairs_history_parallel(
exchange: Exchange,
pairs: list[str],
timeframe: str,
candle_type: CandleType,
timerange: TimeRange | None = None,
) -> dict[PairWithTimeframe, DataFrame]:
"""
Allows to use the faster parallel async download method for many coins
but only if the data is short enough to be retrieved in one call.
Used by freqtrade download-data subcommand.
:return: Candle pairs with timeframes
"""
candles: dict[PairWithTimeframe, DataFrame] = {}
since = 0
if timerange:
if timerange.starttype == "date":
since = timerange.startts * 1000
candle_limit = exchange.ohlcv_candle_limit(timeframe, candle_type)
one_call_min_time_dt = dt_ts(date_minus_candles(timeframe, candle_limit))
# check if we can get all candles in one go, if so then we can download them in parallel
if since > one_call_min_time_dt:
logger.info(
f"Downloading parallel candles for {timeframe} for all pairs "
f"since {format_ms_time(since)}"
)
needed_pairs: ListPairsWithTimeframes = [
(p, timeframe, candle_type) for p in [p for p in pairs]
]
candles = exchange.refresh_latest_ohlcv(needed_pairs, since_ms=since, cache=False)
return candles
def _download_trades_history(
exchange: Exchange,
pair: str,
@@ -702,6 +793,7 @@ def download_data(
trading_mode=config.get("trading_mode", "spot"),
prepend=config.get("prepend_data", False),
progress_tracker=progress_tracker,
no_parallel_download=config.get("no_parallel_download", False),
)
finally:
if pairs_not_available:

3
freqtrade/exchange/__init__.py
View File

@@ -11,6 +11,7 @@ from freqtrade.exchange.bitmart import Bitmart
from freqtrade.exchange.bitpanda import Bitpanda
from freqtrade.exchange.bitvavo import Bitvavo
from freqtrade.exchange.bybit import Bybit
from freqtrade.exchange.coinex import Coinex
from freqtrade.exchange.cryptocom import Cryptocom
from freqtrade.exchange.exchange_utils import (
ROUND_DOWN,
@@ -46,4 +47,4 @@ from freqtrade.exchange.kucoin import Kucoin
from freqtrade.exchange.lbank import Lbank
from freqtrade.exchange.luno import Luno
from freqtrade.exchange.modetrade import Modetrade
from freqtrade.exchange.okx import MyOkx, Okx
from freqtrade.exchange.okx import Myokx, Okx, Okxus

117
freqtrade/exchange/binance.py
View File

@@ -5,10 +5,11 @@ from datetime import UTC, datetime
from pathlib import Path
import ccxt
from cachetools import TTLCache
from pandas import DataFrame
from freqtrade.constants import DEFAULT_DATAFRAME_COLUMNS
from freqtrade.enums import CandleType, MarginMode, PriceType, TradingMode
from freqtrade.enums import TRADE_MODES, CandleType, MarginMode, PriceType, RunMode, TradingMode
from freqtrade.exceptions import DDosProtection, OperationalException, TemporaryError
from freqtrade.exchange import Exchange
from freqtrade.exchange.binance_public_data import (
@@ -27,6 +28,10 @@ logger = logging.getLogger(__name__)
class Binance(Exchange):
"""Binance exchange class.
Contains adjustments needed for Freqtrade to work with this exchange.
"""
_ft_has: FtHas = {
"stoploss_on_exchange": True,
"stop_price_param": "stopPrice",
@@ -40,12 +45,12 @@ class Binance(Exchange):
"fetch_orders_limit_minutes": None,
"l2_limit_range": [5, 10, 20, 50, 100, 500, 1000],
"ws_enabled": True,
"has_delisting": True,
}
_ft_has_futures: FtHas = {
"funding_fee_candle_limit": 1000,
"stoploss_order_types": {"limit": "stop", "market": "stop_market"},
"stoploss_blocks_assets": False, # Stoploss orders do not block assets
"order_time_in_force": ["GTC", "FOK", "IOC"],
"tickers_have_price": False,
"floor_leverage": True,
"fetch_orders_limit_minutes": 7 * 1440, # "fetch_orders" is limited to 7 days
@@ -69,6 +74,10 @@ class Binance(Exchange):
(TradingMode.FUTURES, MarginMode.ISOLATED),
]
def __init__(self, *args, **kwargs) -> None:
super().__init__(*args, **kwargs)
self._spot_delist_schedule_cache: TTLCache = TTLCache(maxsize=100, ttl=300)
def get_proxy_coin(self) -> str:
"""
Get the proxy coin for the given coin
@@ -392,7 +401,7 @@ class Binance(Exchange):
async def _async_get_trade_history_id(
self, pair: str, until: int, since: int, from_id: str | None = None
) -> tuple[str, list[list]]:
logger.info(f"Fetching trades from Binance, {from_id=}, {since=}, {until=}")
logger.info(f"Fetching trades for {pair} from Binance, {from_id=}, {since=}, {until=}")
if not self._config["exchange"].get("only_from_ccxt", False):
if from_id is None or not since:
@@ -433,3 +442,105 @@ class Binance(Exchange):
return await super()._async_get_trade_history_id(
pair, until=until, since=since, from_id=from_id
)
def _check_delisting_futures(self, pair: str) -> datetime | None:
delivery_time = self.markets.get(pair, {}).get("info", {}).get("deliveryDate", None)
if delivery_time:
if isinstance(delivery_time, str) and (delivery_time != ""):
delivery_time = int(delivery_time)
# Binance set a very high delivery time for all perpetuals.
# We compare with delivery time of BTC/USDT:USDT which assumed to never be delisted
btc_delivery_time = (
self.markets.get("BTC/USDT:USDT", {}).get("info", {}).get("deliveryDate", None)
)
if delivery_time == btc_delivery_time:
return None
delivery_time = dt_from_ts(delivery_time)
return delivery_time
def check_delisting_time(self, pair: str) -> datetime | None:
"""
Check if the pair gonna be delisted.
By default, it returns None.
:param pair: Market symbol
:return: Datetime if the pair gonna be delisted, None otherwise
"""
if self._config["runmode"] not in TRADE_MODES:
return None
if self.trading_mode == TradingMode.FUTURES:
return self._check_delisting_futures(pair)
return self._get_spot_pair_delist_time(pair, refresh=False)
def _get_spot_delist_schedule(self):
"""
Get the delisting schedule for spot pairs
Only works in live mode as it requires API keys,
Return sample:
[{
"delistTime": "1759114800000",
"symbols": [
"OMNIBTC",
"OMNIFDUSD",
"OMNITRY",
"OMNIUSDC",
"OMNIUSDT"
]
}]
"""
try:
delist_schedule = self._api.sapi_get_spot_delist_schedule()
return delist_schedule
except ccxt.DDoSProtection as e:
raise DDosProtection(e) from e
except (ccxt.NetworkError, ccxt.OperationFailed, ccxt.ExchangeError) as e:
raise TemporaryError(
f"Could not get delist schedule {e.__class__.__name__}. Message: {e}"
) from e
except ccxt.BaseError as e:
raise OperationalException(e) from e
def _get_spot_pair_delist_time(self, pair: str, refresh: bool = False) -> datetime | None:
"""
Get the delisting time for a pair if it will be delisted
:param pair: Pair to get the delisting time for
:param refresh: true if you need fresh data
:return: int: delisting time None if not delisting
"""
if not pair or not self._config["runmode"] == RunMode.LIVE:
# Endpoint only works in live mode as it requires API keys
return None
cache = self._spot_delist_schedule_cache
if not refresh:
if delist_time := cache.get(pair, None):
return delist_time
delist_schedule = self._get_spot_delist_schedule()
if delist_schedule is None:
return None
for schedule in delist_schedule:
delist_dt = dt_from_ts(int(schedule["delistTime"]))
for symbol in schedule["symbols"]:
ft_symbol = next(
(
pair
for pair, market in self.markets.items()
if market.get("id", None) == symbol
),
None,
)
if ft_symbol is None:
continue
cache[ft_symbol] = delist_dt
return cache.get(pair, None)

29739
freqtrade/exchange/binance_leverage_tiers.json
View File

File diff suppressed because it is too large Load Diff

206
freqtrade/exchange/bitget.py
View File

@@ -1,9 +1,19 @@
import logging
from datetime import timedelta
from freqtrade.enums import CandleType
import ccxt
from freqtrade.constants import BuySell
from freqtrade.enums import CandleType, MarginMode, TradingMode
from freqtrade.exceptions import (
DDosProtection,
OperationalException,
RetryableOrderError,
TemporaryError,
)
from freqtrade.exchange import Exchange
from freqtrade.exchange.exchange_types import FtHas
from freqtrade.exchange.common import API_RETRY_COUNT, retrier
from freqtrade.exchange.exchange_types import CcxtOrder, FtHas
from freqtrade.util.datetime_helpers import dt_now, dt_ts
@@ -11,23 +21,30 @@ logger = logging.getLogger(__name__)
class Bitget(Exchange):
"""
Bitget exchange class. Contains adjustments needed for Freqtrade to work
with this exchange.
Please note that this exchange is not included in the list of exchanges
officially supported by the Freqtrade development team. So some features
may still not work as expected.
"""Bitget exchange class.
Contains adjustments needed for Freqtrade to work with this exchange.
"""
_ft_has: FtHas = {
"stoploss_on_exchange": True,
"stop_price_param": "stopPrice",
"stop_price_prop": "stopPrice",
"stoploss_blocks_assets": False, # Stoploss orders do not block assets
"stoploss_order_types": {"limit": "limit", "market": "market"},
"ohlcv_candle_limit": 200, # 200 for historical candles, 1000 for recent ones.
"order_time_in_force": ["GTC", "FOK", "IOC", "PO"],
}
_ft_has_futures: FtHas = {
"mark_ohlcv_timeframe": "4h",
"funding_fee_candle_limit": 100,
}
_supported_trading_mode_margin_pairs: list[tuple[TradingMode, MarginMode]] = [
(TradingMode.SPOT, MarginMode.NONE),
(TradingMode.FUTURES, MarginMode.ISOLATED),
# (TradingMode.FUTURES, MarginMode.CROSS),
]
def ohlcv_candle_limit(
self, timeframe: str, candle_type: CandleType, since_ms: int | None = None
) -> int:
@@ -44,9 +61,178 @@ class Bitget(Exchange):
timeframe_map = self._api.options["fetchOHLCV"]["maxRecentDaysPerTimeframe"]
days = timeframe_map.get(timeframe, 30)
if candle_type in (CandleType.FUTURES, CandleType.SPOT) and (
if candle_type in (CandleType.FUTURES, CandleType.SPOT, CandleType.MARK) and (
not since_ms or dt_ts(dt_now() - timedelta(days=days)) < since_ms
):
return 1000
return super().ohlcv_candle_limit(timeframe, candle_type, since_ms)
def _convert_stop_order(self, pair: str, order_id: str, order: CcxtOrder) -> CcxtOrder:
if order.get("status", "open") == "closed":
# Use orderID as cliendOrderId filter to fetch the regular followup order.
# Could be done with "fetch_order" - but clientOid as filter doesn't seem to work
# https://www.bitget.com/api-doc/spot/trade/Get-Order-Info
for method in (
self._api.fetch_canceled_and_closed_orders,
self._api.fetch_open_orders,
):
orders = method(pair)
orders_f = [order for order in orders if order["clientOrderId"] == order_id]
if orders_f:
order_reg = orders_f[0]
self._log_exchange_response("fetch_stoploss_order1", order_reg)
order_reg["id_stop"] = order_reg["id"]
order_reg["id"] = order_id
order_reg["type"] = "stoploss"
order_reg["status_stop"] = "triggered"
return order_reg
order = self._order_contracts_to_amount(order)
order["type"] = "stoploss"
return order
def _fetch_stop_order_fallback(self, order_id: str, pair: str) -> CcxtOrder:
params2 = {
"stop": True,
}
for method in (
self._api.fetch_open_orders,
self._api.fetch_canceled_and_closed_orders,
):
try:
orders = method(pair, params=params2)
orders_f = [order for order in orders if order["id"] == order_id]
if orders_f:
order = orders_f[0]
self._log_exchange_response("get_stop_order_fallback", order)
return self._convert_stop_order(pair, order_id, order)
except (ccxt.OrderNotFound, ccxt.InvalidOrder):
pass
except ccxt.DDoSProtection as e:
raise DDosProtection(e) from e
except (ccxt.OperationFailed, ccxt.ExchangeError) as e:
raise TemporaryError(
f"Could not get order due to {e.__class__.__name__}. Message: {e}"
) from e
except ccxt.BaseError as e:
raise OperationalException(e) from e
raise RetryableOrderError(f"StoplossOrder not found (pair: {pair} id: {order_id}).")
@retrier(retries=API_RETRY_COUNT)
def fetch_stoploss_order(
self, order_id: str, pair: str, params: dict | None = None
) -> CcxtOrder:
if self._config["dry_run"]:
return self.fetch_dry_run_order(order_id)
return self._fetch_stop_order_fallback(order_id, pair)
def cancel_stoploss_order(self, order_id: str, pair: str, params: dict | None = None) -> dict:
return self.cancel_order(order_id=order_id, pair=pair, params={"stop": True})
@retrier
def additional_exchange_init(self) -> None:
"""
Additional exchange initialization logic.
.api will be available at this point.
Must be overridden in child methods if required.
"""
try:
if not self._config["dry_run"]:
if self.trading_mode == TradingMode.FUTURES:
position_mode = self._api.set_position_mode(False)
self._log_exchange_response("set_position_mode", position_mode)
except ccxt.DDoSProtection as e:
raise DDosProtection(e) from e
except (ccxt.OperationFailed, ccxt.ExchangeError) as e:
raise TemporaryError(
f"Error in additional_exchange_init due to {e.__class__.__name__}. Message: {e}"
) from e
except ccxt.BaseError as e:
raise OperationalException(e) from e
def _lev_prep(self, pair: str, leverage: float, side: BuySell, accept_fail: bool = False):
if self.trading_mode != TradingMode.SPOT:
# Explicitly setting margin_mode is not necessary as marginMode can be set per order.
# self.set_margin_mode(pair, self.margin_mode, accept_fail)
self._set_leverage(leverage, pair, accept_fail)
def _get_params(
self,
side: BuySell,
ordertype: str,
leverage: float,
reduceOnly: bool,
time_in_force: str = "GTC",
) -> dict:
params = super()._get_params(
side=side,
ordertype=ordertype,
leverage=leverage,
reduceOnly=reduceOnly,
time_in_force=time_in_force,
)
if self.trading_mode == TradingMode.FUTURES and self.margin_mode:
params["marginMode"] = self.margin_mode.value.lower()
return params
def dry_run_liquidation_price(
self,
pair: str,
open_rate: float,
is_short: bool,
amount: float,
stake_amount: float,
leverage: float,
wallet_balance: float,
open_trades: list,
) -> float | None:
"""
Important: Must be fetching data from cached values as this is used by backtesting!
https://www.bitget.com/support/articles/12560603808759
MMR: Maintenance margin rate of the trading pair.
CoinMainIndexPrice: The index price for Coin-M futures. For USDT-M futures,
the index price is: 1.
TakerFeeRatio: The fee rate applied when placing taker orders.
Position direction: The current position direction of the trading pair.
1 indicates a long position, and -1 indicates a short position.
Formula:
Estimated liquidation price = [
position margin - position size x average entry price x position direction
] ÷ [position size x (MMR + TakerFeeRatio - position direction)]
:param pair: Pair to calculate liquidation price for
:param open_rate: Entry price of position
:param is_short: True if the trade is a short, false otherwise
:param amount: Absolute value of position size incl. leverage (in base currency)
:param stake_amount: Stake amount - Collateral in settle currency.
:param leverage: Leverage used for this position.
:param wallet_balance: Amount of margin_mode in the wallet being used to trade
Cross-Margin Mode: crossWalletBalance
Isolated-Margin Mode: isolatedWalletBalance
:param open_trades: List of other open trades in the same wallet
"""
market = self.markets[pair]
taker_fee_rate = market["taker"] or self._api.describe().get("fees", {}).get(
"trading", {}
).get("taker", 0.001)
mm_ratio, _ = self.get_maintenance_ratio_and_amt(pair, stake_amount)
if self.trading_mode == TradingMode.FUTURES and self.margin_mode == MarginMode.ISOLATED:
position_direction = -1 if is_short else 1
return (wallet_balance - (amount * open_rate * position_direction)) / (
amount * (mm_ratio + taker_fee_rate - position_direction)
)
else:
raise OperationalException(
"Freqtrade currently only supports isolated futures for bitget"
)

10
freqtrade/exchange/bitvavo.py
View File

@@ -2,8 +2,6 @@
import logging
from ccxt import DECIMAL_PLACES
from freqtrade.exchange import Exchange
from freqtrade.exchange.exchange_types import FtHas
@@ -24,11 +22,3 @@ class Bitvavo(Exchange):
_ft_has: FtHas = {
"ohlcv_candle_limit": 1440,
}
@property
def precisionMode(self) -> int:
"""
Exchange ccxt precisionMode
Override due to https://github.com/ccxt/ccxt/issues/20408
"""
return DECIMAL_PLACES

9
freqtrade/exchange/bybit.py
View File

@@ -16,13 +16,8 @@ logger = logging.getLogger(__name__)
class Bybit(Exchange):
"""
Bybit exchange class. Contains adjustments needed for Freqtrade to work
with this exchange.
Please note that this exchange is not included in the list of exchanges
officially supported by the Freqtrade development team. So some features
may still not work as expected.
"""Bybit exchange class.
Contains adjustments needed for Freqtrade to work with this exchange.
"""
unified_account = False

24
freqtrade/exchange/coinex.py Normal file
View File

@@ -0,0 +1,24 @@
import logging
from freqtrade.exchange import Exchange
from freqtrade.exchange.exchange_types import FtHas
logger = logging.getLogger(__name__)
class Coinex(Exchange):
"""
CoinEx exchange class. Contains adjustments needed for Freqtrade to work
with this exchange.
Please note that this exchange is not included in the list of exchanges
officially supported by the Freqtrade development team. So some features
may still not work as expected.
"""
_ft_has: FtHas = {
"l2_limit_range": [5, 10, 20, 50],
"tickers_have_bid_ask": False,
"tickers_have_quoteVolume": False,
}

3
freqtrade/exchange/common.py
View File

@@ -48,7 +48,6 @@ MAP_EXCHANGE_CHILDCLASS = {
"binanceus": "binance",
"binanceusdm": "binance",
"okex": "okx",
"okxus": "okx",
"gateio": "gate",
"huboi": "htx",
}
@@ -57,6 +56,7 @@ SUPPORTED_EXCHANGES = [
"binance",
"bingx",
"bitmart",
"bitget",
"bybit",
"gate",
"htx",
@@ -96,7 +96,6 @@ EXCHANGE_HAS_OPTIONAL = [
# 'fetchPositions', # Futures trading
# 'fetchLeverageTiers', # Futures initialization
# 'fetchMarketLeverageTiers', # Futures initialization
# 'fetchOpenOrder', 'fetchClosedOrder', # replacement for fetchOrder
# 'fetchOpenOrders', 'fetchClosedOrders', # 'fetchOrders', # Refinding balance...
# ccxt.pro
"watchOHLCV",

126
freqtrade/exchange/exchange.py
View File

@@ -73,6 +73,7 @@ from freqtrade.exchange.exchange_types import (
CcxtOrder,
CcxtPosition,
FtHas,
FundingRate,
OHLCVResponse,
OrderBook,
Ticker,
@@ -137,6 +138,7 @@ class Exchange:
"ohlcv_has_history": True, # Some exchanges (Kraken) don't provide history via ohlcv
"ohlcv_partial_candle": True,
"ohlcv_require_since": False,
"download_data_parallel_quick": True,
"always_require_api_keys": False, # purge API keys for Dry-run. Must default to false.
# Check https://github.com/ccxt/ccxt/issues/10767 for removal of ohlcv_volume_currency
"ohlcv_volume_currency": "base", # "base" or "quote"
@@ -164,6 +166,7 @@ class Exchange:
"proxy_coin_mapping": {}, # Mapping for proxy coins
# Expected to be in the format {"fetchOHLCV": True} or {"fetchOHLCV": False}
"ws_enabled": False, # Set to true for exchanges with tested websocket support
"has_delisting": False, # Set to true for exchanges that have delisting pair checks
}
_ft_has: FtHas = {}
_ft_has_futures: FtHas = {}
@@ -297,7 +300,7 @@ class Exchange:
if self.trading_mode != TradingMode.SPOT and load_leverage_tiers:
self.fill_leverage_tiers()
self.additional_exchange_init()
self.ft_additional_exchange_init()
def __del__(self):
"""
@@ -452,6 +455,12 @@ class Exchange:
"""
return self._api.precisionMode
def ft_additional_exchange_init(self) -> None:
"""
Wrapper around additional_exchange_init to simplify testing
"""
self.additional_exchange_init()
def additional_exchange_init(self) -> None:
"""
Additional exchange initialization logic.
@@ -690,12 +699,13 @@ class Exchange:
# Reload async markets, then assign them to sync api
retrier(self._load_async_markets, retries=retries)(reload=True)
self._markets = self._api_async.markets
self._api.set_markets(self._api_async.markets, self._api_async.currencies)
self._api.set_markets_from_exchange(self._api_async)
# Assign options array, as it contains some temporary information from the exchange.
# TODO: investigate with ccxt if it's safe to remove `.options`
self._api.options = self._api_async.options
if self._exchange_ws:
# Set markets to avoid reloading on websocket api
self._ws_async.set_markets(self._api.markets, self._api.currencies)
self._ws_async.set_markets_from_exchange(self._api_async)
self._ws_async.options = self._api.options
self._last_markets_refresh = dt_ts()
@@ -828,10 +838,16 @@ class Exchange:
def validate_freqai(self, config: Config) -> None:
freqai_enabled = config.get("freqai", {}).get("enabled", False)
if freqai_enabled and not self._ft_has["ohlcv_has_history"]:
override = config.get("freqai", {}).get("override_exchange_checks", False)
if not override and freqai_enabled and not self._ft_has["ohlcv_has_history"]:
raise ConfigurationError(
f"Historic OHLCV data not available for {self.name}. Can't use freqAI."
)
elif override and freqai_enabled and not self._ft_has["ohlcv_has_history"]:
logger.warning(
"Overriding exchange checks for freqAI. Make sure that your exchange supports "
"fetching historic OHLCV data, otherwise freqAI will not work."
)
def validate_required_startup_candles(self, startup_candles: int, timeframe: str) -> int:
"""
@@ -890,6 +906,19 @@ class Exchange:
f"Freqtrade does not support '{mm_value}' '{trading_mode}' on {self.name}."
)
@classmethod
def combine_ft_has(cls, include_futures: bool) -> FtHas:
"""
Combine all ft_has options from the class hierarchy.
Child classes override parent classes.
Doesn't apply overrides from the configuration.
"""
_ft_has = deep_merge_dicts(cls._ft_has, deepcopy(cls._ft_has_default))
if include_futures:
_ft_has = deep_merge_dicts(cls._ft_has_futures, _ft_has)
return _ft_has
def build_ft_has(self, exchange_conf: ExchangeConfig) -> None:
"""
Deep merge ft_has with default ft_has options
@@ -897,9 +926,8 @@ class Exchange:
This is called on initialization of the exchange object.
It must be called before ft_has is used.
"""
self._ft_has = deep_merge_dicts(self._ft_has, deepcopy(self._ft_has_default))
if self.trading_mode == TradingMode.FUTURES:
self._ft_has = deep_merge_dicts(self._ft_has_futures, self._ft_has)
self._ft_has = self.combine_ft_has(include_futures=self.trading_mode == TradingMode.FUTURES)
if exchange_conf.get("_ft_has_params"):
self._ft_has = deep_merge_dicts(exchange_conf.get("_ft_has_params"), self._ft_has)
logger.info("Overriding exchange._ft_has with config params, result: %s", self._ft_has)
@@ -2001,6 +2029,30 @@ class Exchange:
except ccxt.BaseError as e:
raise OperationalException(e) from e
@retrier
def fetch_funding_rate(self, pair: str) -> FundingRate:
"""
Get current Funding rate from exchange.
On Futures markets, this is the interest rate for holding a position.
Won't work for non-futures markets
"""
try:
if pair not in self.markets or self.markets[pair].get("active", False) is False:
raise ExchangeError(f"Pair {pair} not available")
return self._api.fetch_funding_rate(pair)
except ccxt.NotSupported as e:
raise OperationalException(
f"Exchange {self._api.name} does not support fetching funding rate. Message: {e}"
) from e
except ccxt.DDoSProtection as e:
raise DDosProtection(e) from e
except (ccxt.OperationFailed, ccxt.ExchangeError) as e:
raise TemporaryError(
f"Could not get funding rate due to {e.__class__.__name__}. Message: {e}"
) from e
except ccxt.BaseError as e:
raise OperationalException(e) from e
@staticmethod
def get_next_limit_in_list(
limit: int,
@@ -2456,7 +2508,14 @@ class Exchange:
data.extend(new_data)
# Sort data again after extending the result - above calls return in "async order"
data = sorted(data, key=lambda x: x[0])
return pair, timeframe, candle_type, data, self._ohlcv_partial_candle
return (
pair,
timeframe,
candle_type,
data,
# funding_rates are always complete, so never need to be dropped.
self._ohlcv_partial_candle if candle_type != CandleType.FUNDING_RATE else False,
)
def _try_build_from_websocket(
self, pair: str, timeframe: str, candle_type: CandleType
@@ -2566,14 +2625,24 @@ class Exchange:
input_coroutines: list[Coroutine[Any, Any, OHLCVResponse]] = []
cached_pairs = []
for pair, timeframe, candle_type in set(pair_list):
if timeframe not in self.timeframes and candle_type in (
invalid_funding = (
candle_type == CandleType.FUNDING_RATE
and timeframe != self.get_option("funding_fee_timeframe")
)
invalid_timeframe = timeframe not in self.timeframes and candle_type in (
CandleType.SPOT,
CandleType.FUTURES,
):
)
if invalid_timeframe or invalid_funding:
timeframes_ = (
", ".join(self.timeframes)
if candle_type != CandleType.FUNDING_RATE
else self.get_option("funding_fee_timeframe")
)
logger.warning(
f"Cannot download ({pair}, {timeframe}) combination as this timeframe is "
f"not available on {self.name}. Available timeframes are "
f"{', '.join(self.timeframes)}."
f"Cannot download ({pair}, {timeframe}, {candle_type}) combination as this "
f"timeframe is not available on {self.name}. Available timeframes are "
f"{timeframes_}."
)
continue
@@ -2756,7 +2825,7 @@ class Exchange:
timeframe, candle_type=candle_type, since_ms=since_ms
)
if candle_type and candle_type != CandleType.SPOT:
if candle_type and candle_type not in (CandleType.SPOT, CandleType.FUTURES):
params.update({"price": candle_type.value})
if candle_type != CandleType.FUNDING_RATE:
data = await self._api_async.fetch_ohlcv(
@@ -2771,8 +2840,6 @@ class Exchange:
since_ms=since_ms,
)
# Some exchanges sort OHLCV in ASC order and others in DESC.
# Ex: Bittrex returns the list of OHLCV in ASC order (oldest first, newest last)
# while GDAX returns the list of OHLCV in DESC order (newest first, oldest last)
# Only sort if necessary to save computing time
try:
if data and data[0][0] > data[-1][0]:
@@ -2781,7 +2848,14 @@ class Exchange:
logger.exception("Error loading %s. Result was %s.", pair, data)
return pair, timeframe, candle_type, [], self._ohlcv_partial_candle
logger.debug("Done fetching pair %s, %s interval %s...", pair, candle_type, timeframe)
return pair, timeframe, candle_type, data, self._ohlcv_partial_candle
return (
pair,
timeframe,
candle_type,
data,
# funding_rates are always complete, so never need to be dropped.
self._ohlcv_partial_candle if candle_type != CandleType.FUNDING_RATE else False,
)
except ccxt.NotSupported as e:
raise OperationalException(
@@ -3229,7 +3303,7 @@ class Exchange:
for sig in [signal.SIGINT, signal.SIGTERM]:
try:
self.loop.add_signal_handler(sig, task.cancel)
except NotImplementedError:
except (NotImplementedError, RuntimeError):
# Not all platforms implement signals (e.g. windows)
pass
return self.loop.run_until_complete(task)
@@ -3811,7 +3885,10 @@ class Exchange:
"""
market = self.markets[pair]
taker_fee_rate = market["taker"]
# default to some default fee if not available from exchange
taker_fee_rate = market["taker"] or self._api.describe().get("fees", {}).get(
"trading", {}
).get("taker", 0.001)
mm_ratio, _ = self.get_maintenance_ratio_and_amt(pair, stake_amount)
if self.trading_mode == TradingMode.FUTURES and self.margin_mode == MarginMode.ISOLATED:
@@ -3863,3 +3940,14 @@ class Exchange:
# describes the min amt for a tier, and the lowest tier will always go down to 0
else:
raise ExchangeError(f"Cannot get maintenance ratio using {self.name}")
def check_delisting_time(self, pair: str) -> datetime | None:
"""
Check if the pair gonna be delisted.
This function should be overridden by the exchange class if the exchange
provides such information.
By default, it returns None.
:param pair: Market symbol
:return: Datetime if the pair gonna be delisted, None otherwise
"""
return None

8
freqtrade/exchange/exchange_types.py
View File

@@ -1,5 +1,8 @@
from typing import Any, Literal, TypedDict
# Re-export for easier use
from ccxt.base.types import FundingRate # noqa: F401
from freqtrade.enums import CandleType
@@ -25,6 +28,8 @@ class FtHas(TypedDict, total=False):
ohlcv_volume_currency: str
ohlcv_candle_limit_per_timeframe: dict[str, int]
always_require_api_keys: bool
# allow disabling of parallel download-data for specific exchanges
download_data_parallel_quick: bool
# Tickers
tickers_have_quoteVolume: bool
tickers_have_percentage: bool
@@ -58,6 +63,9 @@ class FtHas(TypedDict, total=False):
# Websocket control
ws_enabled: bool
# Delisting check
has_delisting: bool
class Ticker(TypedDict):
symbol: str

9
freqtrade/exchange/gate.py
View File

@@ -18,13 +18,8 @@ logger = logging.getLogger(__name__)
class Gate(Exchange):
"""
Gate.io exchange class. Contains adjustments needed for Freqtrade to work
with this exchange.
Please note that this exchange is not included in the list of exchanges
officially supported by the Freqtrade development team. So some features
may still not work as expected.
"""Gate.io exchange class.
Contains adjustments needed for Freqtrade to work with this exchange.
"""
unified_account = False

5
freqtrade/exchange/htx.py
View File

@@ -11,9 +11,8 @@ logger = logging.getLogger(__name__)
class Htx(Exchange):
"""
HTX exchange class. Contains adjustments needed for Freqtrade to work
with this exchange.
"""HTX exchange class.
Contains adjustments needed for Freqtrade to work with this exchange.
"""
_ft_has: FtHas = {

13
freqtrade/exchange/hyperliquid.py
View File

@@ -28,6 +28,7 @@ class Hyperliquid(Exchange):
"stoploss_on_exchange": False,
"exchange_has_overrides": {"fetchTrades": False},
"marketOrderRequiresPrice": True,
"download_data_parallel_quick": False,
"ws_enabled": True,
}
_ft_has_futures: FtHas = {
@@ -43,6 +44,7 @@ class Hyperliquid(Exchange):
_supported_trading_mode_margin_pairs: list[tuple[TradingMode, MarginMode]] = [
(TradingMode.SPOT, MarginMode.NONE),
(TradingMode.FUTURES, MarginMode.ISOLATED),
(TradingMode.FUTURES, MarginMode.CROSS),
]
@property
@@ -98,7 +100,6 @@ class Hyperliquid(Exchange):
'SOL/USDC:USDC': 43}}
"""
# Defining/renaming variables to match the documentation
isolated_margin = wallet_balance
position_size = amount
price = open_rate
position_value = price * position_size
@@ -116,8 +117,14 @@ class Hyperliquid(Exchange):
# 3. Divide this by 2
maintenance_margin_required = position_value / max_leverage / 2
# Docs: margin_available (isolated) = isolated_margin - maintenance_margin_required
margin_available = isolated_margin - maintenance_margin_required
if self.margin_mode == MarginMode.ISOLATED:
# Docs: margin_available (isolated) = isolated_margin - maintenance_margin_required
margin_available = stake_amount - maintenance_margin_required
elif self.margin_mode == MarginMode.CROSS:
# Docs: margin_available (cross) = account_value - maintenance_margin_required
margin_available = wallet_balance - maintenance_margin_required
else:
raise OperationalException("Unsupported margin mode for liquidation price calculation")
# Docs: The maintenance margin is half of the initial margin at max leverage
# The docs don't explicitly specify maintenance leverage, but this works.

4
freqtrade/exchange/kraken.py
View File

@@ -19,6 +19,10 @@ logger = logging.getLogger(__name__)
class Kraken(Exchange):
"""Kraken exchange class.
Contains adjustments needed for Freqtrade to work with this exchange.
"""
_params: dict = {"trading_agreement": "agree"}
_ft_has: FtHas = {
"stoploss_on_exchange": True,

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