Merge pull request #10725 from freqtrade/new_release

New release 2024.9

.devcontainer/Dockerfile

@@ -1,22 +0,0 @@
-FROM freqtradeorg/freqtrade:develop_freqairl
-
-USER root
-# Install dependencies
-COPY requirements-dev.txt /freqtrade/
-
-RUN apt-get update \
-    && apt-get -y install --no-install-recommends apt-utils dialog \
-    && apt-get -y install --no-install-recommends git sudo vim build-essential \
-    && apt-get clean \
-    && mkdir -p /home/ftuser/.vscode-server /home/ftuser/.vscode-server-insiders /home/ftuser/commandhistory \
-    && echo "export PROMPT_COMMAND='history -a'" >> /home/ftuser/.bashrc \
-    && echo "export HISTFILE=~/commandhistory/.bash_history" >> /home/ftuser/.bashrc \
-    && chown ftuser:ftuser -R /home/ftuser/.local/ \
-    && chown ftuser: -R /home/ftuser/
-
-USER ftuser
-
-RUN pip install --user autopep8 -r docs/requirements-docs.txt -r requirements-dev.txt --no-cache-dir
-
-# Empty the ENTRYPOINT to allow all commands
-ENTRYPOINT []

.devcontainer/devcontainer.json

@@ -1,42 +1,44 @@
 {
     "name": "freqtrade Develop",
-    "build": {
-        "dockerfile": "Dockerfile",
-        "context": ".."
-    },
+    "image": "ghcr.io/freqtrade/freqtrade-devcontainer:latest",
     // Use 'forwardPorts' to make a list of ports inside the container available locally.
     "forwardPorts": [
         8080
     ],
-    "mounts": [
-        "source=freqtrade-bashhistory,target=/home/ftuser/commandhistory,type=volume"
-    ],
     "workspaceMount": "source=${localWorkspaceFolder},target=/workspaces/freqtrade,type=bind,consistency=cached",
     // Uncomment to connect as a non-root user if you've added one. See https://aka.ms/vscode-remote/containers/non-root.
     "remoteUser": "ftuser",
-
     "onCreateCommand": "pip install --user -e .",
     "postCreateCommand": "freqtrade create-userdir --userdir user_data/",
-
     "workspaceFolder": "/workspaces/freqtrade",
     "customizations": {
-        "settings": {
-            "terminal.integrated.shell.linux": "/bin/bash",
-            "editor.insertSpaces": true,
-            "files.trimTrailingWhitespace": true,
-            "[markdown]": {
-                "files.trimTrailingWhitespace": false,
+        "vscode": {
+            "settings": {
+                "terminal.integrated.shell.linux": "/bin/bash",
+                "editor.insertSpaces": true,
+                "files.trimTrailingWhitespace": true,
+                "[markdown]": {
+                    "files.trimTrailingWhitespace": false
+                },
+                "python.pythonPath": "/usr/local/bin/python",
+                "[python]": {
+                    "editor.codeActionsOnSave": {
+                        "source.organizeImports": "explicit"
+                    },
+                    "editor.formatOnSave": true,
+                    "editor.defaultFormatter": "charliermarsh.ruff"
+                }
             },
-            "python.pythonPath": "/usr/local/bin/python",
-        },
-
-        // Add the IDs of extensions you want installed when the container is created.
-        "extensions": [
-            "ms-python.python",
-            "ms-python.vscode-pylance",
-            "davidanson.vscode-markdownlint",
-            "ms-azuretools.vscode-docker",
-            "vscode-icons-team.vscode-icons",
-        ],
+            // Add the IDs of extensions you want installed when the container is created.
+            "extensions": [
+                "ms-python.python",
+                "ms-python.vscode-pylance",
+                "charliermarsh.ruff",
+                "davidanson.vscode-markdownlint",
+                "ms-azuretools.vscode-docker",
+                "vscode-icons-team.vscode-icons",
+                "github.vscode-github-actions",
+            ],
+        }
     }
 }

.github/.devcontainer/Dockerfile

@@ -0,0 +1,21 @@
+FROM freqtradeorg/freqtrade:develop_freqairl
+
+USER root
+# Install dependencies
+COPY requirements-dev.txt /freqtrade/
+
+ARG USERNAME=ftuser
+
+RUN apt-get update \
+    && apt-get -y install --no-install-recommends apt-utils dialog git ssh vim build-essential zsh \
+    && apt-get clean \
+    && mkdir -p /home/${USERNAME}/.vscode-server /home/${USERNAME}/.vscode-server-insiders /home/${USERNAME}/commandhistory \
+    && chown ${USERNAME}:${USERNAME} -R /home/${USERNAME}/.local/ \
+    && chown ${USERNAME}: -R /home/${USERNAME}/
+
+USER ftuser
+
+RUN pip install --user autopep8 -r docs/requirements-docs.txt -r requirements-dev.txt --no-cache-dir
+
+# Empty the ENTRYPOINT to allow all commands
+ENTRYPOINT []

.github/.devcontainer/devcontainer.json

@@ -0,0 +1,12 @@
+{
+    "name": "freqtrade Dev container image builder",
+    "build": {
+        "dockerfile": "Dockerfile",
+        "context": "../../"
+    },
+    "features": {
+        "ghcr.io/devcontainers/features/common-utils:2": {
+        },
+        "ghcr.io/stuartleeks/dev-container-features/shell-history:0.0.3": {}
+    }
+}

.github/dependabot.yml

@@ -1,9 +1,14 @@
 version: 2
 updates:
 - package-ecosystem: docker
-  directory: "/"
+  directories:
+    - "/"
+    - "/docker"
   schedule:
     interval: daily
+  ignore:
+  - dependency-name: "*"
+    update-types: ["version-update:semver-major"]
   open-pull-requests-limit: 10
 
 - package-ecosystem: pip
@@ -21,6 +26,9 @@ updates:
     pytest:
       patterns:
         - "pytest*"
+    mkdocs:
+      patterns:
+        - "mkdocs*"
 
 - package-ecosystem: "github-actions"
   directory: "/"

.github/workflows/binance-lev-tier-update.yml

@@ -19,7 +19,7 @@ jobs:
 
     - uses: actions/setup-python@v5
       with:
-        python-version: "3.11"
+        python-version: "3.12"
 
     - name: Install ccxt
       run: pip install ccxt
@@ -32,7 +32,7 @@ jobs:
       run: python build_helpers/binance_update_lev_tiers.py
 
 
-    - uses: peter-evans/create-pull-request@v6
+    - uses: peter-evans/create-pull-request@v7
       with:
         token: ${{ secrets.REPO_SCOPED_TOKEN }}
         add-paths: freqtrade/exchange/binance_leverage_tiers.json

.github/workflows/ci.yml

@@ -24,7 +24,7 @@ jobs:
     runs-on: ${{ matrix.os }}
     strategy:
       matrix:
-        os: [ ubuntu-20.04, ubuntu-22.04 ]
+        os: [ "ubuntu-20.04", "ubuntu-22.04", "ubuntu-24.04" ]
         python-version: ["3.9", "3.10", "3.11", "3.12"]
 
     steps:
@@ -80,6 +80,11 @@ jobs:
         # Allow failure for coveralls
         coveralls || true
 
+    - name: Run json schema extract
+      # This should be kept before the repository check to ensure that the schema is up-to-date
+      run: |
+        python build_helpers/extract_config_json_schema.py
+
     - name: Check for repository changes
       run: |
         if [ -n "$(git status --porcelain)" ]; then
@@ -111,7 +116,11 @@ jobs:
 
     - name: Run Ruff
       run: |
-        ruff check --output-format=github .
+        ruff check --output-format=github
+
+    - name: Run Ruff format check
+      run: |
+        ruff format --check
 
     - name: Mypy
       run: |
@@ -129,7 +138,7 @@ jobs:
     runs-on: ${{ matrix.os }}
     strategy:
       matrix:
-        os: [ "macos-latest", "macos-13", "macos-14" ]
+        os: [ "macos-12", "macos-13", "macos-14" ]
         python-version: ["3.9", "3.10", "3.11", "3.12"]
         exclude:
           - os: "macos-14"
@@ -230,7 +239,11 @@ jobs:
 
     - name: Run Ruff
       run: |
-        ruff check --output-format=github .
+        ruff check --output-format=github
+
+    - name: Run Ruff format check
+      run: |
+        ruff format --check
 
     - name: Mypy
       run: |
@@ -300,12 +313,27 @@ jobs:
 
     - name: Run Ruff
       run: |
-        ruff check --output-format=github .
+        ruff check --output-format=github
+
+    - name: Run Ruff format check
+      run: |
+        ruff format --check
 
     - name: Mypy
       run: |
         mypy freqtrade scripts tests
 
+    - name: Run Pester tests (PowerShell)
+      run: |
+        $PSVersionTable
+        Set-PSRepository psgallery -InstallationPolicy trusted
+        Install-Module -Name Pester -RequiredVersion 5.3.1 -Confirm:$false -Force -SkipPublisherCheck
+        $Error.clear()
+        Invoke-Pester -Path "tests" -CI
+        if ($Error.Length -gt 0) {exit 1}
+
+      shell: powershell
+
     - name: Discord notification
       uses: rjstone/discord-webhook-notify@v1
       if: failure() && ( github.event_name != 'pull_request' || github.event.pull_request.head.repo.fork == false)
@@ -322,7 +350,7 @@ jobs:
     - name: Set up Python
       uses: actions/setup-python@v5
       with:
-        python-version: "3.10"
+        python-version: "3.12"
 
     - name: pre-commit dependencies
       run: |
@@ -336,7 +364,7 @@ jobs:
 
     - uses: actions/setup-python@v5
       with:
-        python-version: "3.10"
+        python-version: "3.12"
     - uses: pre-commit/action@v3.0.1
 
   docs-check:
@@ -351,12 +379,11 @@ jobs:
     - name: Set up Python
       uses: actions/setup-python@v5
       with:
-        python-version: "3.11"
+        python-version: "3.12"
 
     - name: Documentation build
       run: |
         pip install -r docs/requirements-docs.txt
-        pip install mkdocs
         mkdocs build
 
     - name: Discord notification
@@ -377,7 +404,7 @@ jobs:
     - name: Set up Python
       uses: actions/setup-python@v5
       with:
-        python-version: "3.11"
+        python-version: "3.12"
 
     - name: Cache_dependencies
       uses: actions/cache@v4
@@ -414,7 +441,7 @@ jobs:
         pytest --random-order --longrun --durations 20 -n auto
 
 
-  # Notify only once - when CI completes (and after deploy) in case it's successfull
+  # Notify only once - when CI completes (and after deploy) in case it's successful
   notify-complete:
     needs: [
       build-linux,
@@ -459,7 +486,7 @@ jobs:
     - name: Set up Python
       uses: actions/setup-python@v5
       with:
-        python-version: "3.11"
+        python-version: "3.12"
 
     - name: Build distribution
       run: |
@@ -510,12 +537,12 @@ jobs:
 
 
     - name: Publish to PyPI (Test)
-      uses: pypa/gh-action-pypi-publish@v1.8.14
+      uses: pypa/gh-action-pypi-publish@v1.10.2
       with:
         repository-url: https://test.pypi.org/legacy/
 
     - name: Publish to PyPI
-      uses: pypa/gh-action-pypi-publish@v1.8.14
+      uses: pypa/gh-action-pypi-publish@v1.10.2
 
 
   deploy-docker:
@@ -530,7 +557,7 @@ jobs:
     - name: Set up Python
       uses: actions/setup-python@v5
       with:
-        python-version: "3.11"
+        python-version: "3.12"
 
     - name: Extract branch name
       id: extract-branch
@@ -553,12 +580,12 @@ jobs:
           sudo systemctl restart docker
           docker version -f '{{.Server.Experimental}}'
 
+    - name: Set up QEMU
+      uses: docker/setup-qemu-action@v3
+
     - name: Set up Docker Buildx
       id: buildx
-      uses: crazy-max/ghaction-docker-buildx@v3.3.1
-      with:
-        buildx-version: latest
-        qemu-version: latest
+      uses: docker/setup-buildx-action@v3
 
     - name: Available platforms
       run: echo ${{ steps.buildx.outputs.platforms }}

.github/workflows/deploy-docs.yml

@@ -0,0 +1,55 @@
+name: Build Documentation
+
+on:
+  push:
+    branches:
+      - develop
+  release:
+    types: [published]
+
+
+# disable permissions for all of the available permissions
+permissions: {}
+
+
+jobs:
+  build-docs:
+    permissions:
+      contents: write  #  for mike to push
+    name: Deploy Docs through mike
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+
+      - name: Set up Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: '3.12'
+
+      - name: Install dependencies
+        run: |
+          python -m pip install --upgrade pip
+          pip install -r docs/requirements-docs.txt
+
+      - name: Fetch gh-pages branch
+        run: |
+          git fetch origin gh-pages --depth=1
+
+      - name: Configure Git user
+        run: |
+          git config --local user.email "github-actions[bot]@users.noreply.github.com"
+          git config --local user.name "github-actions[bot]"
+
+      - name: Build and push Mike
+        if: ${{ github.event_name == 'push' }}
+        run: |
+          mike deploy ${{ github.ref_name }} latest --push --update-aliases
+
+      - name: Build and push Mike - Release
+        if: ${{ github.event_name == 'release' }}
+        run: |
+          mike deploy ${{ github.ref_name }} stable --push --update-aliases
+
+      - name: Show mike versions
+        run: |
+          mike list

.github/workflows/devcontainer-build.yml

@@ -0,0 +1,45 @@
+name: Devcontainer Pre-Build
+
+on:
+  workflow_dispatch:
+  schedule:
+    - cron: "0 3 * * 0"
+  # push:
+  #   branches:
+  #     - "master"
+  #   tags:
+  #     - "v*.*.*"
+  #   pull_requests:
+  #     branches:
+  #       - "master"
+
+concurrency:
+  group: "${{ github.workflow }}"
+  cancel-in-progress: true
+
+permissions:
+  packages: write
+
+jobs:
+  build-and-push:
+    runs-on: ubuntu-latest
+    steps:
+    -
+      name: Checkout
+      id: checkout
+      uses: actions/checkout@v4
+    -
+        name: Login to GitHub Container Registry
+        uses: docker/login-action@v3
+        with:
+          registry: ghcr.io
+          username: ${{ github.actor }}
+          password: ${{ secrets.GITHUB_TOKEN }}
+    -
+        name: Pre-build dev container image
+        uses: devcontainers/ci@v0.3
+        with:
+          subFolder: .github
+          imageName: ghcr.io/${{ github.repository }}-devcontainer
+          cacheFrom: ghcr.io/${{ github.repository }}-devcontainer
+          push: always

.github/workflows/pre-commit-update.yml

@@ -17,7 +17,7 @@ jobs:
 
     - uses: actions/setup-python@v5
       with:
-        python-version: "3.11"
+        python-version: "3.12"
 
 
     - name: Install pre-commit
@@ -26,10 +26,7 @@ jobs:
     - name: Run auto-update
       run: pre-commit autoupdate
 
-    - name: Run pre-commit
-      run: pre-commit run --all-files
-
-    - uses: peter-evans/create-pull-request@v6
+    - uses: peter-evans/create-pull-request@v7
       with:
         token: ${{ secrets.REPO_SCOPED_TOKEN }}
         add-paths: .pre-commit-config.yaml

.gitignore

@@ -114,3 +114,5 @@ target/
 !config_examples/config_full.example.json
 !config_examples/config_kraken.example.json
 !config_examples/config_freqai.example.json
+
+docker-compose-*.yml

.pre-commit-config.yaml

@@ -2,24 +2,24 @@
 # See https://pre-commit.com/hooks.html for more hooks
 repos:
   - repo: https://github.com/pycqa/flake8
-    rev: "7.0.0"
+    rev: "7.1.1"
     hooks:
       - id: flake8
         additional_dependencies: [Flake8-pyproject]
         # stages: [push]
 
   - repo: https://github.com/pre-commit/mirrors-mypy
-    rev: "v1.9.0"
+    rev: "v1.11.2"
     hooks:
       - id: mypy
         exclude: build_helpers
         additional_dependencies:
-          - types-cachetools==5.3.0.7
+          - types-cachetools==5.5.0.20240820
           - types-filelock==3.2.7
-          - types-requests==2.31.0.20240311
+          - types-requests==2.32.0.20240914
           - types-tabulate==0.9.0.20240106
-          - types-python-dateutil==2.9.0.20240316
-          - SQLAlchemy==2.0.29
+          - types-python-dateutil==2.9.0.20240906
+          - SQLAlchemy==2.0.35
         # stages: [push]
 
   - repo: https://github.com/pycqa/isort
@@ -31,12 +31,13 @@ repos:
 
   - repo: https://github.com/charliermarsh/ruff-pre-commit
     # Ruff version.
-    rev: 'v0.3.4'
+    rev: 'v0.6.7'
     hooks:
       - id: ruff
+      - id: ruff-format
 
   - repo: https://github.com/pre-commit/pre-commit-hooks
-    rev: v4.5.0
+    rev: v4.6.0
     hooks:
       - id: end-of-file-fixer
         exclude: |
@@ -54,3 +55,10 @@ repos:
           (?x)^(
                 .*\.md
             )$
+
+  - repo: https://github.com/codespell-project/codespell
+    rev: v2.3.0
+    hooks:
+    - id: codespell
+      additional_dependencies:
+        - tomli

.vscode/extensions.json

@@ -0,0 +1,11 @@
+{
+    "recommendations": [
+        "ms-python.python",
+        "ms-python.vscode-pylance",
+        "charliermarsh.ruff",
+        "davidanson.vscode-markdownlint",
+        "ms-azuretools.vscode-docker",
+        "vscode-icons-team.vscode-icons",
+        "github.vscode-github-actions",
+    ]
+}

CONTRIBUTING.md

@@ -72,12 +72,12 @@ you can manually run pre-commit with `pre-commit run -a`.
 mypy freqtrade
 ```
 
-### 4. Ensure all imports are correct
+### 4. Ensure formatting is correct
 
-#### Run isort
+#### Run ruff
 
 ``` bash
-isort .
+ruff format .
 ```
 
 ## (Core)-Committer Guide

Dockerfile

@@ -1,4 +1,4 @@
-FROM python:3.12.2-slim-bookworm as base
+FROM python:3.12.6-slim-bookworm as base
 
 # Setup env
 ENV LANG C.UTF-8
@@ -35,7 +35,7 @@ ENV LD_LIBRARY_PATH /usr/local/lib
 # Install dependencies
 COPY --chown=ftuser:ftuser requirements.txt requirements-hyperopt.txt /freqtrade/
 USER ftuser
-RUN  pip install --user --no-cache-dir numpy \
+RUN  pip install --user --no-cache-dir "numpy<2.0" \
   && pip install --user --no-cache-dir -r requirements-hyperopt.txt
 
 # Copy dependencies to runtime-image

README.md

@@ -29,6 +29,8 @@ Please read the [exchange specific notes](docs/exchanges.md) to learn about even
 
 - [X] [Binance](https://www.binance.com/)
 - [X] [Bitmart](https://bitmart.com/)
+- [X] [BingX](https://bingx.com/invite/0EM9RX)
+- [X] [Bybit](https://bybit.com/)
 - [X] [Gate.io](https://www.gate.io/ref/6266643)
 - [X] [HTX](https://www.htx.com/) (Former Huobi)
 - [X] [Kraken](https://kraken.com/)
@@ -85,41 +87,50 @@ For further (native) installation methods, please refer to the [Installation doc
 
 ```
 usage: freqtrade [-h] [-V]
-                 {trade,create-userdir,new-config,new-strategy,download-data,convert-data,convert-trade-data,list-data,backtesting,edge,hyperopt,hyperopt-list,hyperopt-show,list-exchanges,list-hyperopts,list-markets,list-pairs,list-strategies,list-timeframes,show-trades,test-pairlist,install-ui,plot-dataframe,plot-profit,webserver}
+                 {trade,create-userdir,new-config,show-config,new-strategy,download-data,convert-data,convert-trade-data,trades-to-ohlcv,list-data,backtesting,backtesting-show,backtesting-analysis,edge,hyperopt,hyperopt-list,hyperopt-show,list-exchanges,list-markets,list-pairs,list-strategies,list-freqaimodels,list-timeframes,show-trades,test-pairlist,convert-db,install-ui,plot-dataframe,plot-profit,webserver,strategy-updater,lookahead-analysis,recursive-analysis}
                  ...
 
 Free, open source crypto trading bot
 
 positional arguments:
-  {trade,create-userdir,new-config,new-strategy,download-data,convert-data,convert-trade-data,list-data,backtesting,edge,hyperopt,hyperopt-list,hyperopt-show,list-exchanges,list-hyperopts,list-markets,list-pairs,list-strategies,list-timeframes,show-trades,test-pairlist,install-ui,plot-dataframe,plot-profit,webserver}
+  {trade,create-userdir,new-config,show-config,new-strategy,download-data,convert-data,convert-trade-data,trades-to-ohlcv,list-data,backtesting,backtesting-show,backtesting-analysis,edge,hyperopt,hyperopt-list,hyperopt-show,list-exchanges,list-markets,list-pairs,list-strategies,list-freqaimodels,list-timeframes,show-trades,test-pairlist,convert-db,install-ui,plot-dataframe,plot-profit,webserver,strategy-updater,lookahead-analysis,recursive-analysis}
     trade               Trade module.
     create-userdir      Create user-data directory.
     new-config          Create new config
+    show-config         Show resolved config
     new-strategy        Create new strategy
     download-data       Download backtesting data.
     convert-data        Convert candle (OHLCV) data from one format to
                         another.
     convert-trade-data  Convert trade data from one format to another.
+    trades-to-ohlcv     Convert trade data to OHLCV data.
     list-data           List downloaded data.
     backtesting         Backtesting module.
+    backtesting-show    Show past Backtest results
+    backtesting-analysis
+                        Backtest Analysis module.
     edge                Edge module.
     hyperopt            Hyperopt module.
     hyperopt-list       List Hyperopt results
     hyperopt-show       Show details of Hyperopt results
     list-exchanges      Print available exchanges.
-    list-hyperopts      Print available hyperopt classes.
     list-markets        Print markets on exchange.
     list-pairs          Print pairs on exchange.
     list-strategies     Print available strategies.
+    list-freqaimodels   Print available freqAI models.
     list-timeframes     Print available timeframes for the exchange.
     show-trades         Show trades.
     test-pairlist       Test your pairlist configuration.
+    convert-db          Migrate database to different system
     install-ui          Install FreqUI
     plot-dataframe      Plot candles with indicators.
     plot-profit         Generate plot showing profits.
     webserver           Webserver module.
+    strategy-updater    updates outdated strategy files to the current version
+    lookahead-analysis  Check for potential look ahead bias.
+    recursive-analysis  Check for potential recursive formula issue.
 
-optional arguments:
+options:
   -h, --help            show this help message and exit
   -V, --version         show program's version number and exit
 

build_helpers/binance_update_lev_tiers.py

@@ -6,21 +6,18 @@ from pathlib import Path
 import ccxt
 
 
-key = os.environ.get('FREQTRADE__EXCHANGE__KEY')
-secret = os.environ.get('FREQTRADE__EXCHANGE__SECRET')
+key = os.environ.get("FREQTRADE__EXCHANGE__KEY")
+secret = os.environ.get("FREQTRADE__EXCHANGE__SECRET")
 
-proxy = os.environ.get('CI_WEB_PROXY')
+proxy = os.environ.get("CI_WEB_PROXY")
 
-exchange = ccxt.binance({
-    'apiKey': key,
-    'secret': secret,
-    'httpsProxy': proxy,
-    'options': {'defaultType': 'swap'}
-    })
+exchange = ccxt.binance(
+    {"apiKey": key, "secret": secret, "httpsProxy": proxy, "options": {"defaultType": "swap"}}
+)
 _ = exchange.load_markets()
 
 lev_tiers = exchange.fetch_leverage_tiers()
 
 # Assumes this is running in the root of the repository.
-file = Path('freqtrade/exchange/binance_leverage_tiers.json')
-json.dump(dict(sorted(lev_tiers.items())), file.open('w'), indent=2)
+file = Path("freqtrade/exchange/binance_leverage_tiers.json")
+json.dump(dict(sorted(lev_tiers.items())), file.open("w"), indent=2)

build_helpers/extract_config_json_schema.py

@@ -0,0 +1,17 @@
+"""Script to extract the configuration json schema from config_schema.py file."""
+
+from pathlib import Path
+
+import rapidjson
+
+from freqtrade.configuration.config_schema import CONF_SCHEMA
+
+
+def extract_config_json_schema():
+    schema_filename = Path(__file__).parent / "schema.json"
+    with schema_filename.open("w") as f:
+        rapidjson.dump(CONF_SCHEMA, f, indent=2)
+
+
+if __name__ == "__main__":
+    extract_config_json_schema()

build_helpers/freqtrade_client_version_align.py

@@ -1,18 +1,15 @@
 #!/usr/bin/env python3
-from freqtrade_client import __version__ as client_version
-
 from freqtrade import __version__ as ft_version
+from freqtrade_client import __version__ as client_version
 
 
 def main():
     if ft_version != client_version:
-        print(f"Versions do not match: \n"
-              f"ft: {ft_version} \n"
-              f"client: {client_version}")
+        print(f"Versions do not match: \nft: {ft_version} \nclient: {client_version}")
         exit(1)
     print(f"Versions match: ft: {ft_version}, client: {client_version}")
     exit(0)
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     main()

build_helpers/pre_commit_update.py

@@ -1,4 +1,4 @@
-# File used in CI to ensure pre-commit dependencies are kept uptodate.
+# File used in CI to ensure pre-commit dependencies are kept up-to-date.
 
 import sys
 from pathlib import Path
@@ -6,28 +6,30 @@ from pathlib import Path
 import yaml
 
 
-pre_commit_file = Path('.pre-commit-config.yaml')
-require_dev = Path('requirements-dev.txt')
-require = Path('requirements.txt')
+pre_commit_file = Path(".pre-commit-config.yaml")
+require_dev = Path("requirements-dev.txt")
+require = Path("requirements.txt")
 
-with require_dev.open('r') as rfile:
+with require_dev.open("r") as rfile:
     requirements = rfile.readlines()
 
-with require.open('r') as rfile:
+with require.open("r") as rfile:
     requirements.extend(rfile.readlines())
 
 # Extract types only
-type_reqs = [r.strip('\n') for r in requirements if r.startswith(
-    'types-') or r.startswith('SQLAlchemy')]
+type_reqs = [
+    r.strip("\n") for r in requirements if r.startswith("types-") or r.startswith("SQLAlchemy")
+]
 
-with pre_commit_file.open('r') as file:
-    f = yaml.load(file, Loader=yaml.FullLoader)
+with pre_commit_file.open("r") as file:
+    f = yaml.load(file, Loader=yaml.SafeLoader)
 
 
-mypy_repo = [repo for repo in f['repos'] if repo['repo']
-             == 'https://github.com/pre-commit/mirrors-mypy']
+mypy_repo = [
+    repo for repo in f["repos"] if repo["repo"] == "https://github.com/pre-commit/mirrors-mypy"
+]
 
-hooks = mypy_repo[0]['hooks'][0]['additional_dependencies']
+hooks = mypy_repo[0]["hooks"][0]["additional_dependencies"]
 
 errors = []
 for hook in hooks:

config_examples/config_binance.example.json

@@ -1,4 +1,5 @@
 {
+    "$schema": "https://schema.freqtrade.io/schema.json",
     "max_open_trades": 3,
     "stake_currency": "USDT",
     "stake_amount": 0.05,

config_examples/config_freqai.example.json

@@ -1,4 +1,5 @@
 {
+    "$schema": "https://schema.freqtrade.io/schema.json",
     "trading_mode": "futures",
     "margin_mode": "isolated",
     "max_open_trades": 5,

config_examples/config_full.example.json

@@ -1,4 +1,5 @@
 {
+    "$schema": "https://schema.freqtrade.io/schema.json",
     "max_open_trades": 3,
     "stake_currency": "BTC",
     "stake_amount": 0.05,

config_examples/config_kraken.example.json

@@ -1,4 +1,5 @@
 {
+    "$schema": "https://schema.freqtrade.io/schema.json",
     "max_open_trades": 5,
     "stake_currency": "EUR",
     "stake_amount": 10,

docker-compose.yml

@@ -1,5 +1,4 @@
 ---
-version: '3'
 services:
   freqtrade:
     image: freqtradeorg/freqtrade:stable

docker/Dockerfile.armhf

@@ -1,4 +1,4 @@
-FROM python:3.11.8-slim-bookworm as base
+FROM python:3.11.10-slim-bookworm as base
 
 # Setup env
 ENV LANG C.UTF-8
@@ -35,7 +35,7 @@ COPY build_helpers/* /tmp/
 COPY --chown=ftuser:ftuser requirements.txt /freqtrade/
 USER ftuser
 RUN  pip install --user --no-cache-dir numpy \
-  && pip install --user --no-index --find-links /tmp/ pyarrow TA-Lib==0.4.28 \
+  && pip install --user --no-index --find-links /tmp/ pyarrow TA-Lib \
   && pip install --user --no-cache-dir -r requirements.txt
 
 # Copy dependencies to runtime-image

docker/docker-compose-freqai.yml

@@ -1,5 +1,4 @@
 ---
-version: '3'
 services:
   freqtrade:
     image: freqtradeorg/freqtrade:stable_freqaitorch

docker/docker-compose-jupyter.yml

@@ -1,5 +1,4 @@
 ---
-version: '3'
 services:
   ft_jupyterlab:
     build:

docs/advanced-backtesting.md

@@ -18,15 +18,13 @@ freqtrade backtesting -c <config.json> --timeframe <tf> --strategy <strategy_nam
 ```
 
 This will tell freqtrade to output a pickled dictionary of strategy, pairs and corresponding
-DataFrame of the candles that resulted in buy signals. Depending on how many buys your strategy
-makes, this file may get quite large, so periodically check your `user_data/backtest_results`
-folder to delete old exports.
+DataFrame of the candles that resulted in entry and exit signals.
+Depending on how many entries your strategy makes, this file may get quite large, so periodically check your `user_data/backtest_results` folder to delete old exports.
 
 Before running your next backtest, make sure you either delete your old backtest results or run
 backtesting with the `--cache none` option to make sure no cached results are used.
 
-If all goes well, you should now see a `backtest-result-{timestamp}_signals.pkl` file in the
-`user_data/backtest_results` folder.
+If all goes well, you should now see a `backtest-result-{timestamp}_signals.pkl` and `backtest-result-{timestamp}_exited.pkl` files in the `user_data/backtest_results` folder.
 
 To analyze the entry/exit tags, we now need to use the `freqtrade backtesting-analysis` command
 with `--analysis-groups` option provided with space-separated arguments:
@@ -36,7 +34,7 @@ freqtrade backtesting-analysis -c <config.json> --analysis-groups 0 1 2 3 4 5
 ```
 
 This command will read from the last backtesting results. The `--analysis-groups` option is
-used to specify the various tabular outputs showing the profit fo each group or trade,
+used to specify the various tabular outputs showing the profit of each group or trade,
 ranging from the simplest (0) to the most detailed per pair, per buy and per sell tag (4):
 
 * 0: overall winrate and profit summary by enter_tag
@@ -103,6 +101,10 @@ The indicators have to be present in your strategy's main DataFrame (either for
 timeframe or for informative timeframes) otherwise they will simply be ignored in the script
 output.
 
+!!! Note "Indicator List"
+    The indicator values will be displayed for both entry and exit points. If `--indicator-list all` is specified, 
+    only the indicators at the entry point will be shown to avoid excessively large lists, which could occur depending on the strategy.
+
 There are a range of candle and trade-related fields that are included in the analysis so are 
 automatically accessible by including them on the indicator-list, and these include:
 
@@ -118,6 +120,53 @@ automatically accessible by including them on the indicator-list, and these incl
 - **profit_ratio  :** trade profit ratio
 - **profit_abs    :** absolute profit return of the trade 
 
+#### Sample Output for Indicator Values
+
+```bash
+freqtrade backtesting-analysis -c user_data/config.json --analysis-groups 0 --indicator-list chikou_span tenkan_sen 
+```
+
+In this example,
+we aim to display the `chikou_span` and `tenkan_sen` indicator values at both the entry and exit points of trades.
+
+A sample output for indicators might look like this:
+
+| pair      | open_date                 | enter_reason | exit_reason | chikou_span (entry) | tenkan_sen (entry) | chikou_span (exit) | tenkan_sen (exit) |
+|-----------|---------------------------|--------------|-------------|---------------------|--------------------|--------------------|-------------------|
+| DOGE/USDT | 2024-07-06 00:35:00+00:00 |              | exit_signal | 0.105               | 0.106              | 0.105              | 0.107             |
+| BTC/USDT  | 2024-08-05 14:20:00+00:00 |              | roi         | 54643.440           | 51696.400          | 54386.000          | 52072.010         |
+
+As shown in the table, `chikou_span (entry)` represents the indicator value at the time of trade entry, 
+while `chikou_span (exit)` reflects its value at the time of exit. 
+This detailed view of indicator values enhances the analysis.
+
+The `(entry)` and `(exit)` suffixes are added to indicators
+to distinguish the values at the entry and exit points of the trade.
+
+!!! Note "Trade-wide Indicators"
+    Certain trade-wide indicators do not have the `(entry)` or `(exit)` suffix. These indicators include: `pair`, `stake_amount`, 
+    `max_stake_amount`, `amount`, `open_date`, `close_date`, `open_rate`, `close_rate`, `fee_open`, `fee_close`, `trade_duration`, 
+    `profit_ratio`, `profit_abs`, `exit_reason`,`initial_stop_loss_abs`, `initial_stop_loss_ratio`, `stop_loss_abs`, `stop_loss_ratio`, 
+    `min_rate`, `max_rate`, `is_open`, `enter_tag`, `leverage`, `is_short`, `open_timestamp`, `close_timestamp` and `orders`
+
+#### Filtering Indicators Based on Entry or Exit Signals
+
+The `--indicator-list` option, by default, displays indicator values for both entry and exit signals. To filter the indicator values exclusively for entry signals, you can use the `--entry-only` argument. Similarly, to display indicator values only at exit signals, use the `--exit-only` argument.
+
+Example: Display indicator values at entry signals:
+
+```bash
+freqtrade backtesting-analysis -c user_data/config.json --analysis-groups 0 --indicator-list chikou_span tenkan_sen --entry-only
+```
+
+Example: Display indicator values at exit signals:
+
+```bash
+freqtrade backtesting-analysis -c user_data/config.json --analysis-groups 0 --indicator-list chikou_span tenkan_sen --exit-only
+```
+
+!!! note 
+    When using these filters, the indicator names will not be suffixed with `(entry)` or `(exit)`.
 
 ### Filtering the trade output by date
 

docs/advanced-hyperopt.md

@@ -30,11 +30,17 @@ class SuperDuperHyperOptLoss(IHyperOptLoss):
     """
 
     @staticmethod
-    def hyperopt_loss_function(results: DataFrame, trade_count: int,
-                               min_date: datetime, max_date: datetime,
-                               config: Config, processed: Dict[str, DataFrame],
-                               backtest_stats: Dict[str, Any],
-                               *args, **kwargs) -> float:
+    def hyperopt_loss_function(
+        *,
+        results: DataFrame,
+        trade_count: int,
+        min_date: datetime,
+        max_date: datetime,
+        config: Config,
+        processed: Dict[str, DataFrame],
+        backtest_stats: Dict[str, Any],
+        **kwargs,
+    ) -> float:
         """
         Objective function, returns smaller number for better results
         This is the legacy algorithm (used until now in freqtrade).

docs/advanced-orderflow.md

@@ -0,0 +1,152 @@
+# Orderflow data
+
+This guide walks you through utilizing public trade data for advanced orderflow analysis in Freqtrade.
+
+!!! Warning "Experimental Feature"
+    The orderflow feature is currently in beta and may be subject to changes in future releases. Please report any issues or feedback on the [Freqtrade GitHub repository](https://github.com/freqtrade/freqtrade/issues).
+
+!!! Warning "Performance"
+    Orderflow requires raw trades data. This data is rather large, and can cause a slow initial startup, when freqtrade needs to download the trades data for the last X candles. Additionally, enabling this feature will cause increased memory usage. Please ensure to have sufficient resources available.
+
+## Getting Started
+
+### Enable Public Trades
+
+In your `config.json` file, set the `use_public_trades` option to true under the `exchange` section.
+
+```json
+"exchange": {
+   ...
+   "use_public_trades": true,
+}
+```
+
+### Configure Orderflow Processing
+
+Define your desired settings for orderflow processing within the orderflow section of config.json. Here, you can adjust factors like:
+
+- `cache_size`: How many previous orderflow candles are saved into cache instead of calculated every new candle
+- `max_candles`: Filter how many candles would you like to get trades data for.
+- `scale`: This controls the price bin size for the footprint chart.
+- `stacked_imbalance_range`: Defines the minimum consecutive imbalanced price levels required for consideration.
+- `imbalance_volume`: Filters out imbalances with volume below this threshold.
+- `imbalance_ratio`: Filters out imbalances with a ratio (difference between ask and bid volume) lower than this value.
+
+```json
+"orderflow": {
+    "cache_size": 1000, 
+    "max_candles": 1500, 
+    "scale": 0.5, 
+    "stacked_imbalance_range": 3, //  needs at least this amount of imbalance next to each other
+    "imbalance_volume": 1, //  filters out below
+    "imbalance_ratio": 3 //  filters out ratio lower than
+  },
+```
+
+## Downloading Trade Data for Backtesting
+
+To download historical trade data for backtesting, use the --dl-trades flag with the freqtrade download-data command.
+
+```bash
+freqtrade download-data -p BTC/USDT:USDT --timerange 20230101- --trading-mode futures --timeframes 5m --dl-trades
+```
+
+!!! Warning "Data availability"
+    Not all exchanges provide public trade data. For supported exchanges, freqtrade will warn you if public trade data is not available if you start downloading data with the `--dl-trades` flag.
+
+## Accessing Orderflow Data
+
+Once activated, several new columns become available in your dataframe:
+
+``` python
+
+dataframe["trades"] # Contains information about each individual trade.
+dataframe["orderflow"] # Represents a footprint chart dict (see below)
+dataframe["imbalances"] # Contains information about imbalances in the order flow.
+dataframe["bid"] # Total bid volume 
+dataframe["ask"] # Total ask volume
+dataframe["delta"] # Difference between ask and bid volume.
+dataframe["min_delta"] # Minimum delta within the candle
+dataframe["max_delta"] # Maximum delta within the candle
+dataframe["total_trades"] # Total number of trades
+dataframe["stacked_imbalances_bid"] # Price level of stacked bid imbalance 
+dataframe["stacked_imbalances_ask"] # Price level of stacked ask imbalance  
+```
+
+You can access these columns in your strategy code for further analysis. Here's an example:
+
+``` python
+def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+    # Calculating cumulative delta
+    dataframe["cum_delta"] = cumulative_delta(dataframe["delta"])
+    # Accessing total trades
+    total_trades = dataframe["total_trades"]
+    ...
+
+def cumulative_delta(delta: Series):
+    cumdelta = delta.cumsum()
+    return cumdelta
+
+```
+
+### Footprint chart (`dataframe["orderflow"]`)
+
+This column provides a detailed breakdown of buy and sell orders at different price levels, offering valuable insights into order flow dynamics. The `scale` parameter in your configuration determines the price bin size for this representation
+
+The `orderflow` column contains a dict with the following structure:
+
+``` output
+{
+    "price": {
+        "bid_amount": 0.0,
+        "ask_amount": 0.0,
+        "bid": 0,
+        "ask": 0,
+        "delta": 0.0,
+        "total_volume": 0.0,
+        "total_trades": 0
+    }
+}
+```
+
+#### Orderflow column explanation
+
+- key: Price bin - binned at `scale` intervals
+- `bid_amount`: Total volume bought at each price level.
+- `ask_amount`: Total volume sold at each price level.
+- `bid`: Number of buy orders at each price level.
+- `ask`: Number of sell orders at each price level.
+- `delta`: Difference between ask and bid volume at each price level.
+- `total_volume`: Total volume (ask amount + bid amount) at each price level.
+- `total_trades`: Total number of trades (ask + bid) at each price level.
+
+By leveraging these features, you can gain valuable insights into market sentiment and potential trading opportunities based on order flow analysis.
+
+### Raw trades data (`dataframe["trades"]`)
+
+List with the individual trades that occurred during the candle. This data can be used for more granular analysis of order flow dynamics.
+
+Each individual entry contains a dict with the following keys:
+
+- `timestamp`: Timestamp of the trade.
+- `date`: Date of the trade.
+- `price`: Price of the trade.
+- `amount`: Volume of the trade.
+- `side`: Buy or sell.
+- `id`: Unique identifier for the trade.
+- `cost`: Total cost of the trade (price * amount).
+
+### Imbalances (`dataframe["imbalances"]`)
+
+This column provides a dict with information about imbalances in the order flow. An imbalance occurs when there is a significant difference between the ask and bid volume at a given price level.
+
+Each row looks as follows - with price as index, and the corresponding bid and ask imbalance values as columns
+
+``` output
+{
+    "price": {
+        "bid_imbalance": False,
+        "ask_imbalance": False
+    }
+}
+```

docs/advanced-setup.md

@@ -114,8 +114,46 @@ services:
       --strategy SampleStrategy
 
 ```
+
 You can use whatever naming convention you want, freqtrade1 and 2 are arbitrary. Note, that you will need to use different database files, port mappings and telegram configurations for each instance, as mentioned above. 
 
+## Use a different database system
+
+Freqtrade is using SQLAlchemy, which supports multiple different database systems. As such, a multitude of database systems should be supported.
+Freqtrade does not depend or install any additional database driver. Please refer to the [SQLAlchemy docs](https://docs.sqlalchemy.org/en/14/core/engines.html#database-urls) on installation instructions for the respective database systems.
+
+The following systems have been tested and are known to work with freqtrade:
+
+* sqlite (default)
+* PostgreSQL
+* MariaDB
+
+!!! Warning
+    By using one of the below database systems, you acknowledge that you know how to manage such a system. The freqtrade team will not provide any support with setup or maintenance (or backups) of the below database systems.
+
+### PostgreSQL
+
+Installation:
+`pip install psycopg2-binary`
+
+Usage:
+`... --db-url postgresql+psycopg2://<username>:<password>@localhost:5432/<database>`
+
+Freqtrade will automatically create the tables necessary upon startup.
+
+If you're running different instances of Freqtrade, you must either setup one database per Instance or use different users / schemas for your connections.
+
+### MariaDB / MySQL
+
+Freqtrade supports MariaDB by using SQLAlchemy, which supports multiple different database systems.
+
+Installation:
+`pip install pymysql`
+
+Usage:
+`... --db-url mysql+pymysql://<username>:<password>@localhost:3306/<database>`
+
+
 
 ## Configure the bot running as a systemd service
 

docs/backtesting.md

@@ -253,36 +253,36 @@ A backtesting result will look like that:
 
 ```
 ================================================ BACKTESTING REPORT =================================================
-| Pair     | Entries |   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 |
+| 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     |  Entries |   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 |
+| 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 |
@@ -293,6 +293,7 @@ A backtesting result will look like that:
 |-----------------------------+---------------------|
 | 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         |
@@ -398,6 +399,7 @@ It contains some useful key metrics about performance of your strategy on backte
 |-----------------------------+---------------------|
 | 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         |
@@ -452,6 +454,7 @@ It contains some useful key metrics about performance of your strategy on backte
 
 - `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.
 - `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.
@@ -522,21 +525,22 @@ To save time, by default backtest will reuse a cached result from within the las
 
 ### Further backtest-result analysis
 
-To further analyze your backtest results, you can [export the trades](#exporting-trades-to-file).
-You can then load the trades to perform further analysis as shown in the [data analysis](data-analysis.md#backtesting) backtesting section.
+To further analyze your backtest results, freqtrade will export the trades to file by default.
+You can then load the trades to perform further analysis as shown in the [data analysis](strategy_analysis_example.md#load-backtest-results-to-pandas-dataframe) backtesting section.
 
 ## Assumptions made by backtesting
 
 Since backtesting lacks some detailed information about what happens within a candle, it needs to take a few assumptions:
 
 - Exchange [trading limits](#trading-limits-in-backtesting) are respected
-- Entries happen at open-price
-- All orders are filled at the requested price (no slippage, no unfilled orders)
+- Entries happen at open-price unless a custom price logic has been specified
+- All orders are filled at the requested price (no slippage) as long as the price is within the candle's high/low range
 - Exit-signal exits happen at open-price of the consecutive candle
+- Exits free their trade slot for a new trade with a different pair
 - 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 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
   - 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
@@ -587,7 +591,7 @@ These precision values are based on current exchange limits (as described in the
 
 ## Improved backtest accuracy
 
-One big limitation of backtesting is it's inability to know how prices moved intra-candle (was high before close, or viceversa?).
+One big limitation of backtesting is it's inability to know how prices moved intra-candle (was high before close, or vice-versa?).
 So assuming you run backtesting with a 1h timeframe, there will be 4 prices for that candle (Open, High, Low, Close).
 
 While backtesting does take some assumptions (read above) about this - this can never be perfect, and will always be biased in one way or the other.
@@ -630,10 +634,10 @@ Detailed output for all strategies one after the other will be available, so mak
 
 ```
 ================================================== STRATEGY SUMMARY ===================================================================
-| Strategy    |  Entries |   Avg Profit % |   Tot Profit BTC |   Tot Profit % | Avg Duration   |  Wins |  Draws | Losses | Drawdown % |
-|:------------|---------:|---------------:|-----------------:|---------------:|:---------------|------:|-------:|-------:|-----------:|
-| Strategy1   |      429 |           0.36 |       0.00762792 |          76.20 | 4:12:00        |   186 |      0 |    243 |       45.2 |
-| Strategy2   |     1487 |          -0.13 |      -0.00988917 |         -98.79 | 4:43:00        |   662 |      0 |    825 |     241.68 |
+| Strategy    |  Trades |   Avg Profit % |   Tot Profit BTC |   Tot Profit % | Avg Duration   |  Wins |  Draws | Losses | Drawdown % |
+|-------------+---------+----------------+------------------+----------------+----------------+-------+--------+--------+------------|
+| Strategy1   |     429 |           0.36 |       0.00762792 |          76.20 | 4:12:00        |   186 |      0 |    243 |       45.2 |
+| Strategy2   |    1487 |          -0.13 |      -0.00988917 |         -98.79 | 4:43:00        |   662 |      0 |    825 |     241.68 |
 ```
 
 ## Next step

docs/bot-usage.md

@@ -12,41 +12,50 @@ This page explains the different parameters of the bot and how to run it.
 
 ```
 usage: freqtrade [-h] [-V]
-                 {trade,create-userdir,new-config,new-strategy,download-data,convert-data,convert-trade-data,list-data,backtesting,edge,hyperopt,hyperopt-list,hyperopt-show,list-exchanges,list-hyperopts,list-markets,list-pairs,list-strategies,list-timeframes,show-trades,test-pairlist,install-ui,plot-dataframe,plot-profit,webserver}
+                 {trade,create-userdir,new-config,show-config,new-strategy,download-data,convert-data,convert-trade-data,trades-to-ohlcv,list-data,backtesting,backtesting-show,backtesting-analysis,edge,hyperopt,hyperopt-list,hyperopt-show,list-exchanges,list-markets,list-pairs,list-strategies,list-freqaimodels,list-timeframes,show-trades,test-pairlist,convert-db,install-ui,plot-dataframe,plot-profit,webserver,strategy-updater,lookahead-analysis,recursive-analysis}
                  ...
 
 Free, open source crypto trading bot
 
 positional arguments:
-  {trade,create-userdir,new-config,new-strategy,download-data,convert-data,convert-trade-data,list-data,backtesting,edge,hyperopt,hyperopt-list,hyperopt-show,list-exchanges,list-hyperopts,list-markets,list-pairs,list-strategies,list-timeframes,show-trades,test-pairlist,install-ui,plot-dataframe,plot-profit,webserver}
+  {trade,create-userdir,new-config,show-config,new-strategy,download-data,convert-data,convert-trade-data,trades-to-ohlcv,list-data,backtesting,backtesting-show,backtesting-analysis,edge,hyperopt,hyperopt-list,hyperopt-show,list-exchanges,list-markets,list-pairs,list-strategies,list-freqaimodels,list-timeframes,show-trades,test-pairlist,convert-db,install-ui,plot-dataframe,plot-profit,webserver,strategy-updater,lookahead-analysis,recursive-analysis}
     trade               Trade module.
     create-userdir      Create user-data directory.
     new-config          Create new config
+    show-config         Show resolved config
     new-strategy        Create new strategy
     download-data       Download backtesting data.
     convert-data        Convert candle (OHLCV) data from one format to
                         another.
     convert-trade-data  Convert trade data from one format to another.
+    trades-to-ohlcv     Convert trade data to OHLCV data.
     list-data           List downloaded data.
     backtesting         Backtesting module.
+    backtesting-show    Show past Backtest results
+    backtesting-analysis
+                        Backtest Analysis module.
     edge                Edge module.
     hyperopt            Hyperopt module.
     hyperopt-list       List Hyperopt results
     hyperopt-show       Show details of Hyperopt results
     list-exchanges      Print available exchanges.
-    list-hyperopts      Print available hyperopt classes.
     list-markets        Print markets on exchange.
     list-pairs          Print pairs on exchange.
     list-strategies     Print available strategies.
+    list-freqaimodels   Print available freqAI models.
     list-timeframes     Print available timeframes for the exchange.
     show-trades         Show trades.
     test-pairlist       Test your pairlist configuration.
+    convert-db          Migrate database to different system
     install-ui          Install FreqUI
     plot-dataframe      Plot candles with indicators.
     plot-profit         Generate plot showing profits.
     webserver           Webserver module.
+    strategy-updater    updates outdated strategy files to the current version
+    lookahead-analysis  Check for potential look ahead bias.
+    recursive-analysis  Check for potential recursive formula issue.
 
-optional arguments:
+options:
   -h, --help            show this help message and exit
   -V, --version         show program's version number and exit
 

docs/configuration.md

@@ -123,6 +123,19 @@ This is similar to using multiple `--config` parameters, but simpler in usage as
 
     If multiple files are in the `add_config_files` section, then they will be assumed to be at identical levels, having the last occurrence override the earlier config (unless a parent already defined such a key).
 
+## Editor autocomplete and validation
+
+If you are using an editor that supports JSON schema, you can use the schema provided by Freqtrade to get autocompletion and validation of your configuration file by adding the following line to the top of your configuration file:
+
+``` json
+{
+    "$schema": "https://schema.freqtrade.io/schema.json",
+}
+```
+
+??? Note "Develop version"
+    The develop schema is available as `https://schema.freqtrade.io/schema_dev.json` - though we recommend to stick to the stable version for the best experience.
+
 ## Configuration parameters
 
 The table below will list all configuration parameters available.
@@ -197,18 +210,18 @@ Mandatory parameters are marked as **Required**, which means that they are requi
 | `position_adjustment_enable` | Enables the strategy to use position adjustments (additional buys or sells). [More information here](strategy-callbacks.md#adjust-trade-position). <br> [Strategy Override](#parameters-in-the-strategy). <br>*Defaults to `false`.*<br> **Datatype:** Boolean
 | `max_entry_position_adjustment` | Maximum additional order(s) for each open trade on top of the first entry Order. Set it to `-1` for unlimited additional orders. [More information here](strategy-callbacks.md#adjust-trade-position). <br> [Strategy Override](#parameters-in-the-strategy). <br>*Defaults to `-1`.*<br> **Datatype:** Positive Integer or -1
 | | **Exchange**
-| `exchange.name` | **Required.** Name of the exchange class to use. [List below](#user-content-what-values-for-exchangename). <br> **Datatype:** String
+| `exchange.name` | **Required.** Name of the exchange class to use. <br> **Datatype:** String
 | `exchange.key` | API key to use for the exchange. Only required when you are in production mode.<br>**Keep it in secret, do not disclose publicly.** <br> **Datatype:** String
 | `exchange.secret` | API secret to use for the exchange. Only required when you are in production mode.<br>**Keep it in secret, do not disclose publicly.** <br> **Datatype:** String
 | `exchange.password` | API password to use for the exchange. Only required when you are in production mode and for exchanges that use password for API requests.<br>**Keep it in secret, do not disclose publicly.** <br> **Datatype:** String
 | `exchange.uid` | API uid to use for the exchange. Only required when you are in production mode and for exchanges that use uid for API requests.<br>**Keep it in secret, do not disclose publicly.** <br> **Datatype:** String
 | `exchange.pair_whitelist` | List of pairs to use by the bot for trading and to check for potential trades during backtesting. Supports regex pairs as `.*/BTC`. Not used by VolumePairList. [More information](plugins.md#pairlists-and-pairlist-handlers). <br> **Datatype:** List
 | `exchange.pair_blacklist` | List of pairs the bot must absolutely avoid for trading and backtesting. [More information](plugins.md#pairlists-and-pairlist-handlers). <br> **Datatype:** List
-| `exchange.ccxt_config` | Additional CCXT parameters passed to both ccxt instances (sync and async). This is usually the correct place for additional ccxt configurations. Parameters may differ from exchange to exchange and are documented in the [ccxt documentation](https://ccxt.readthedocs.io/en/latest/manual.html#instantiation). Please avoid adding exchange secrets here (use the dedicated fields instead), as they may be contained in logs. <br> **Datatype:** Dict
-| `exchange.ccxt_sync_config` | Additional CCXT parameters passed to the regular (sync) ccxt instance. Parameters may differ from exchange to exchange and are documented in the [ccxt documentation](https://ccxt.readthedocs.io/en/latest/manual.html#instantiation) <br> **Datatype:** Dict
-| `exchange.ccxt_async_config` | Additional CCXT parameters passed to the async ccxt instance. Parameters may differ from exchange to exchange  and are documented in the [ccxt documentation](https://ccxt.readthedocs.io/en/latest/manual.html#instantiation) <br> **Datatype:** Dict
+| `exchange.ccxt_config` | Additional CCXT parameters passed to both ccxt instances (sync and async). This is usually the correct place for additional ccxt configurations. Parameters may differ from exchange to exchange and are documented in the [ccxt documentation](https://docs.ccxt.com/#/README?id=overriding-exchange-properties-upon-instantiation). Please avoid adding exchange secrets here (use the dedicated fields instead), as they may be contained in logs. <br> **Datatype:** Dict
+| `exchange.ccxt_sync_config` | Additional CCXT parameters passed to the regular (sync) ccxt instance. Parameters may differ from exchange to exchange and are documented in the [ccxt documentation](https://docs.ccxt.com/#/README?id=overriding-exchange-properties-upon-instantiation) <br> **Datatype:** Dict
+| `exchange.ccxt_async_config` | Additional CCXT parameters passed to the async ccxt instance. Parameters may differ from exchange to exchange  and are documented in the [ccxt documentation](https://docs.ccxt.com/#/README?id=overriding-exchange-properties-upon-instantiation) <br> **Datatype:** Dict
+| `exchange.enable_ws` | Enable the usage of Websockets for the exchange. <br>[More information](#consuming-exchange-websockets).<br>*Defaults to `true`.* <br> **Datatype:** Boolean
 | `exchange.markets_refresh_interval` | The interval in minutes in which markets are reloaded. <br>*Defaults to `60` minutes.* <br> **Datatype:** Positive Integer
-| `exchange.skip_pair_validation` | Skip pairlist validation on startup.<br>*Defaults to `false`*<br> **Datatype:** Boolean
 | `exchange.skip_open_order_update` | Skips open order updates on startup should the exchange cause problems. Only relevant in live conditions.<br>*Defaults to `false`*<br> **Datatype:** Boolean
 | `exchange.unknown_fee_rate` | Fallback value to use when calculating trading fees. This can be useful for exchanges which have fees in non-tradable currencies. The value provided here will be multiplied with the "fee cost".<br>*Defaults to `None`<br> **Datatype:** float
 | `exchange.log_responses` | Log relevant exchange responses. For debug mode only - use with care.<br>*Defaults to `false`*<br> **Datatype:** Boolean
@@ -252,7 +265,7 @@ Mandatory parameters are marked as **Required**, which means that they are requi
 | `disable_dataframe_checks` | Disable checking the OHLCV dataframe returned from the strategy methods for correctness. Only use when intentionally changing the dataframe and understand what you are doing. [Strategy Override](#parameters-in-the-strategy).<br> *Defaults to `False`*. <br> **Datatype:** Boolean
 | `internals.process_throttle_secs` | Set the process throttle, or minimum loop duration for one bot iteration loop. Value in second. <br>*Defaults to `5` seconds.* <br> **Datatype:** Positive Integer
 | `internals.heartbeat_interval` | Print heartbeat message every N seconds. Set to 0 to disable heartbeat messages. <br>*Defaults to `60` seconds.* <br> **Datatype:** Positive Integer or 0
-| `internals.sd_notify` | Enables use of the sd_notify protocol to tell systemd service manager about changes in the bot state and issue keep-alive pings. See [here](installation.md#7-optional-configure-freqtrade-as-a-systemd-service) for more details. <br> **Datatype:** Boolean
+| `internals.sd_notify` | Enables use of the sd_notify protocol to tell systemd service manager about changes in the bot state and issue keep-alive pings. See [here](advanced-setup.md#configure-the-bot-running-as-a-systemd-service) for more details. <br> **Datatype:** Boolean
 | `strategy` | **Required** Defines Strategy class to use. Recommended to be set via `--strategy NAME`. <br> **Datatype:** ClassName
 | `strategy_path` | Adds an additional strategy lookup path (must be a directory). <br> **Datatype:** String
 | `recursive_strategy_search` | Set to `true` to recursively search sub-directories inside `user_data/strategies` for a strategy. <br> **Datatype:** Boolean
@@ -370,7 +383,7 @@ This setting works in combination with `max_open_trades`. The maximum capital en
 For example, the bot will at most use (0.05 BTC x 3) = 0.15 BTC, assuming a configuration of `max_open_trades=3` and `stake_amount=0.05`.
 
 !!! Note
-    This setting respects the [available balance configuration](#available-balance).
+    This setting respects the [available balance configuration](#tradable-balance).
 
 #### Dynamic stake amount
 
@@ -409,6 +422,8 @@ Or another example if your position adjustment assumes it can do 1 additional bu
 
 --8<-- "includes/pricing.md"
 
+## Further Configuration details
+
 ### Understand minimal_roi
 
 The `minimal_roi` configuration parameter is a JSON object where the key is a duration
@@ -547,7 +562,7 @@ is automatically cancelled by the exchange.
 **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 at least time in an unfilled state.
+This means the order must be placed on orderbook for at least time in an unfilled state.
 
 #### time_in_force config
 
@@ -568,7 +583,14 @@ The possible values are: `GTC` (default), `FOK` or `IOC`.
     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.
 
-### What values can be used for fiat_display_currency?
+### Fiat conversion
+
+Freqtrade uses the Coingecko API to convert the coin value to it's corresponding fiat value for the Telegram reports.
+The FIAT currency can be set in the configuration file as `fiat_display_currency`.
+
+Removing `fiat_display_currency` completely from the configuration will skip initializing coingecko, and will not show any FIAT currency conversion. This has no importance for the correct functioning of the bot.
+
+#### What values can be used for fiat_display_currency?
 
 The `fiat_display_currency` configuration parameter sets the base currency to use for the
 conversion from coin to fiat in the bot Telegram reports.
@@ -587,7 +609,49 @@ The valid values are:
 "BTC", "ETH", "XRP", "LTC", "BCH", "BNB"
 ```
 
-Removing `fiat_display_currency` completely from the configuration will skip initializing coingecko, and will not show any FIAT currency conversion. This has no importance for the correct functioning of the bot.
+#### Coingecko Rate limit problems
+
+On some IP ranges, coingecko is heavily rate-limiting.
+In such cases, you may want to add your coingecko API key to the configuration.
+
+``` json
+{
+    "fiat_display_currency": "USD",
+    "coingecko": {
+        "api_key": "your-api",
+        "is_demo": true
+    }
+}
+```
+
+Freqtrade supports both Demo and Pro coingecko API keys.
+
+The Coingecko API key is NOT required for the bot to function correctly.
+It is only used for the conversion of coin to fiat in the Telegram reports, which usually also work without API key.
+
+## Consuming exchange Websockets
+
+Freqtrade can consume websockets through ccxt.pro.
+
+Freqtrade aims ensure data is available at all times.
+Should the websocket connection fail (or be disabled), the bot will fall back to REST API calls.
+
+Should you experience problems you suspect are caused by websockets, you can disable these via the setting `exchange.enable_ws`, which defaults to true.
+
+```jsonc
+"exchange": {
+    // ...
+    "enable_ws": false,
+    // ...
+}
+```
+
+Should you be required to use a proxy, please refer to the [proxy section](#using-proxy-with-freqtrade) for more information.
+
+!!! Info "Rollout"
+    We're implementing this out slowly, ensuring stability of your bots.
+    Currently, usage is limited to ohlcv data streams.
+    It's also limited to a few exchanges, with new exchanges being added on an ongoing basis.
 
 ## Using Dry-run mode
 
@@ -625,9 +689,9 @@ Once you will be happy with your bot performance running in the Dry-run mode, yo
 * API-keys may or may not be provided. Only Read-Only operations (i.e. operations that do not alter account state) on the exchange are performed in dry-run mode.
 * Wallets (`/balance`) are simulated based on `dry_run_wallet`.
 * Orders are simulated, and will not be posted to the exchange.
-* Market orders fill based on orderbook volume the moment the order is placed.
+* Market orders fill based on orderbook volume the moment the order is placed, with a maximum slippage of 5%.
 * Limit orders fill once the price reaches the defined level - or time out based on `unfilledtimeout` settings.
-* Limit orders will be converted to market orders if they cross the price by more than 1%.
+* Limit orders will be converted to market orders if they cross the price by more than 1%, and will be filled immediately based regular market order rules (see point about Market orders above).
 * In combination with `stoploss_on_exchange`, the stop_loss price is assumed to be filled.
 * Open orders (not trades, which are stored in the database) are kept open after bot restarts, with the assumption that they were not filled while being offline.
 
@@ -677,7 +741,7 @@ You should also make sure to read the [Exchanges](exchanges.md) section of the d
 
     **NEVER** share your private configuration file or your exchange keys with anyone!
 
-### Using proxy with Freqtrade
+## Using a proxy with Freqtrade
 
 To use a proxy with freqtrade, export your proxy settings using the variables `"HTTP_PROXY"` and `"HTTPS_PROXY"` set to the appropriate values.
 This will have the proxy settings applied to everything (telegram, coingecko, ...) **except** for exchange requests.
@@ -688,7 +752,7 @@ export HTTPS_PROXY="http://addr:port"
 freqtrade
 ```
 
-#### Proxy exchange requests
+### Proxy exchange requests
 
 To use a proxy for exchange connections - you will have to define the proxies as part of the ccxt configuration.
 
@@ -697,6 +761,7 @@ To use a proxy for exchange connections - you will have to define the proxies as
   "exchange": {
     "ccxt_config": {
       "httpsProxy": "http://addr:port",
+      "wsProxy": "http://addr:port",
     }
   }
 }

docs/data-download.md

@@ -24,10 +24,10 @@ usage: freqtrade download-data [-h] [-v] [--logfile FILE] [-V] [-c PATH]
                                [--days INT] [--new-pairs-days INT]
                                [--include-inactive-pairs]
                                [--timerange TIMERANGE] [--dl-trades]
-                               [--exchange EXCHANGE]
+                               [--convert] [--exchange EXCHANGE]
                                [-t TIMEFRAMES [TIMEFRAMES ...]] [--erase]
                                [--data-format-ohlcv {json,jsongz,hdf5,feather,parquet}]
-                               [--data-format-trades {json,jsongz,hdf5,feather}]
+                               [--data-format-trades {json,jsongz,hdf5,feather,parquet}]
                                [--trading-mode {spot,margin,futures}]
                                [--prepend]
 
@@ -48,6 +48,11 @@ options:
   --dl-trades           Download trades instead of OHLCV data. The bot will
                         resample trades to the desired timeframe as specified
                         as --timeframes/-t.
+  --convert             Convert downloaded trades to OHLCV data. Only
+                        applicable in combination with `--dl-trades`. Will be
+                        automatic for exchanges which don't have historic
+                        OHLCV (e.g. Kraken). If not provided, use `trades-to-
+                        ohlcv` to convert trades data to OHLCV data.
   --exchange EXCHANGE   Exchange name. Only valid if no config is provided.
   -t TIMEFRAMES [TIMEFRAMES ...], --timeframes TIMEFRAMES [TIMEFRAMES ...]
                         Specify which tickers to download. Space-separated
@@ -57,7 +62,7 @@ options:
   --data-format-ohlcv {json,jsongz,hdf5,feather,parquet}
                         Storage format for downloaded candle (OHLCV) data.
                         (default: `feather`).
-  --data-format-trades {json,jsongz,hdf5,feather}
+  --data-format-trades {json,jsongz,hdf5,feather,parquet}
                         Storage format for downloaded trades data. (default:
                         `feather`).
   --trading-mode {spot,margin,futures}, --tradingmode {spot,margin,futures}
@@ -418,7 +423,8 @@ You can get a list of downloaded data using the `list-data` sub-command.
 usage: freqtrade list-data [-h] [-v] [--logfile FILE] [-V] [-c PATH] [-d PATH]
                            [--userdir PATH] [--exchange EXCHANGE]
                            [--data-format-ohlcv {json,jsongz,hdf5,feather,parquet}]
-                           [-p PAIRS [PAIRS ...]]
+                           [--data-format-trades {json,jsongz,hdf5,feather,parquet}]
+                           [--trades] [-p PAIRS [PAIRS ...]]
                            [--trading-mode {spot,margin,futures}]
                            [--show-timerange]
 
@@ -428,6 +434,10 @@ options:
   --data-format-ohlcv {json,jsongz,hdf5,feather,parquet}
                         Storage format for downloaded candle (OHLCV) data.
                         (default: `feather`).
+  --data-format-trades {json,jsongz,hdf5,feather,parquet}
+                        Storage format for downloaded trades data. (default:
+                        `feather`).
+  --trades              Work on trades data instead of OHLCV data.
   -p PAIRS [PAIRS ...], --pairs PAIRS [PAIRS ...]
                         Limit command to these pairs. Pairs are space-
                         separated.
@@ -460,26 +470,47 @@ Common arguments:
 ```bash
 > freqtrade list-data --userdir ~/.freqtrade/user_data/
 
-Found 33 pair / timeframe combinations.
-pairs       timeframe
-----------  -----------------------------------------
-ADA/BTC     5m, 15m, 30m, 1h, 2h, 4h, 6h, 12h, 1d
-ADA/ETH     5m, 15m, 30m, 1h, 2h, 4h, 6h, 12h, 1d
-ETH/BTC     5m, 15m, 30m, 1h, 2h, 4h, 6h, 12h, 1d
-ETH/USDT    5m, 15m, 30m, 1h, 2h, 4h
+              Found 33 pair / timeframe combinations.
+┏━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━┓
+┃          Pair ┃                                 Timeframe ┃ Type ┃
+┡━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━┩
+│       ADA/BTC │     5m, 15m, 30m, 1h, 2h, 4h, 6h, 12h, 1d │ spot │
+│       ADA/ETH │     5m, 15m, 30m, 1h, 2h, 4h, 6h, 12h, 1d │ spot │
+│       ETH/BTC │     5m, 15m, 30m, 1h, 2h, 4h, 6h, 12h, 1d │ spot │
+│      ETH/USDT │                  5m, 15m, 30m, 1h, 2h, 4h │ spot │
+└───────────────┴───────────────────────────────────────────┴──────┘
+
+```
+
+Show all trades data including from/to timerange
+
+``` bash
+> freqtrade list-data --show --trades
+                     Found trades data for 1 pair.                     
+┏━━━━━━━━━┳━━━━━━┳━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━┓
+┃    Pair ┃ Type ┃                From ┃                  To ┃ Trades ┃
+┡━━━━━━━━━╇━━━━━━╇━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━┩
+│ XRP/ETH │ spot │ 2019-10-11 00:00:11 │ 2019-10-13 11:19:28 │  12477 │
+└─────────┴──────┴─────────────────────┴─────────────────────┴────────┘
+
 ```
 
 ## Trades (tick) data
 
-By default, `download-data` sub-command downloads Candles (OHLCV) data. Some exchanges also provide historic trade-data via their API.
+By default, `download-data` sub-command downloads Candles (OHLCV) data. Most exchanges also provide historic trade-data via their API.
 This data can be useful if you need many different timeframes, since it is only downloaded once, and then resampled locally to the desired timeframes.
 
-Since this data is large by default, the files use the feather fileformat by default. They are stored in your data-directory with the naming convention of `<pair>-trades.feather` (`ETH_BTC-trades.feather`). Incremental mode is also supported, as for historic OHLCV data, so downloading the data once per week with `--days 8` will create an incremental data-repository.
+Since this data is large by default, the files use the feather file format by default. They are stored in your data-directory with the naming convention of `<pair>-trades.feather` (`ETH_BTC-trades.feather`). Incremental mode is also supported, as for historic OHLCV data, so downloading the data once per week with `--days 8` will create an incremental data-repository.
 
-To use this mode, simply add `--dl-trades` to your call. This will swap the download method to download trades, and resamples the data locally.
+To use this mode, simply add `--dl-trades` to your call. This will swap the download method to download trades.
+If `--convert` is also provided, the resample step will happen automatically and overwrite eventually existing OHLCV data for the given pair/timeframe combinations.
 
-!!! Warning "do not use"
-    You should not use this unless you're a kraken user. Most other exchanges provide OHLCV data with sufficient history.
+!!! Warning "Do not use"
+    You should not use this unless you're a kraken user (Kraken does not provide historic OHLCV data).  
+    Most other exchanges provide OHLCV data with sufficient history, so downloading multiple timeframes through that method will still proof to be a lot faster than downloading trades data.
+
+!!! Note "Kraken user"
+    Kraken users should read [this](exchanges.md#historic-kraken-data) before starting to download data.
 
 Example call:
 
@@ -490,12 +521,6 @@ freqtrade download-data --exchange kraken --pairs XRP/EUR ETH/EUR --days 20 --dl
 !!! Note
     While this method uses async calls, it will be slow, since it requires the result of the previous call to generate the next request to the exchange.
 
-!!! Warning
-    The historic trades are not available during Freqtrade dry-run and live trade modes because all exchanges tested provide this data with a delay of few 100 candles, so it's not suitable for real-time trading.
-
-!!! Note "Kraken user"
-    Kraken users should read [this](exchanges.md#historic-kraken-data) before starting to download data.
-
 ## Next step
 
-Great, you now have backtest data downloaded, so you can now start [backtesting](backtesting.md) your strategy.
+Great, you now have some data downloaded, so you can now start [backtesting](backtesting.md) your strategy.

docs/developer.md

@@ -22,7 +22,7 @@ This will spin up a local server (usually on port 8000) so you can see if everyt
 ## Developer setup
 
 To configure a development environment, you can either use the provided [DevContainer](#devcontainer-setup), or use the `setup.sh` script and answer "y" when asked "Do you want to install dependencies for dev [y/N]? ".
-Alternatively (e.g. if your system is not supported by the setup.sh script), follow the manual installation process and run `pip3 install -e .[all]`.
+Alternatively (e.g. if your system is not supported by the setup.sh script), follow the manual installation process and run `pip3 install -r requirements-dev.txt` - followed by `pip3 install -e .[all]`.
 
 This will install all required tools for development, including `pytest`, `ruff`, `mypy`, and `coveralls`.
 
@@ -83,7 +83,7 @@ Details will obviously vary between setups - but this should work to get you sta
 ``` json
 {
     "name": "freqtrade trade",
-    "type": "python",
+    "type": "debugpy",
     "request": "launch",
     "module": "freqtrade",
     "console": "integratedTerminal",
@@ -205,7 +205,7 @@ This is called with each iteration of the bot (only if the Pairlist Handler is a
 
 It must return the resulting pairlist (which may then be passed into the chain of Pairlist Handlers).
 
-Validations are optional, the parent class exposes a `_verify_blacklist(pairlist)` and `_whitelist_for_active_markets(pairlist)` to do default filtering. Use this if you limit your result to a certain number of pairs - so the end-result is not shorter than expected.
+Validations are optional, the parent class exposes a `verify_blacklist(pairlist)` and `_whitelist_for_active_markets(pairlist)` to do default filtering. Use this if you limit your result to a certain number of pairs - so the end-result is not shorter than expected.
 
 #### filter_pairlist
 
@@ -219,7 +219,7 @@ The default implementation in the base class simply calls the `_validate_pair()`
 
 If overridden, it must return the resulting pairlist (which may then be passed into the next Pairlist Handler in the chain).
 
-Validations are optional, the parent class exposes a `_verify_blacklist(pairlist)` and `_whitelist_for_active_markets(pairlist)` to do default filters. Use this if you limit your result to a certain number of pairs - so the end result is not shorter than expected.
+Validations are optional, the parent class exposes a `verify_blacklist(pairlist)` and `_whitelist_for_active_markets(pairlist)` to do default filters. Use this if you limit your result to a certain number of pairs - so the end result is not shorter than expected.
 
 In `VolumePairList`, this implements different methods of sorting, does early validation so only the expected number of pairs is returned.
 
@@ -261,7 +261,7 @@ For that reason, they must implement the following methods:
 
 The `until` portion should be calculated using the provided `calculate_lock_end()` method.
 
-All Protections should use `"stop_duration"` / `"stop_duration_candles"` to define how long a a pair (or all pairs) should be locked.
+All Protections should use `"stop_duration"` / `"stop_duration_candles"` to define how long a pair (or all pairs) should be locked.
 The content of this is made available as `self._stop_duration` to the each Protection.
 
 If your protection requires a look-back period, please use `"lookback_period"` / `"lockback_period_candles"` to keep all protections aligned.
@@ -305,7 +305,7 @@ The `IProtection` parent class provides a helper method for this in `calculate_l
 
 Most exchanges supported by CCXT should work out of the box.
 
-To quickly test the public endpoints of an exchange, add a configuration for your exchange to `test_ccxt_compat.py` and run these tests with `pytest --longrun tests/exchange/test_ccxt_compat.py`.
+To quickly test the public endpoints of an exchange, add a configuration for your exchange to `tests/exchange_online/conftest.py` and run these tests with `pytest --longrun tests/exchange_online/test_ccxt_compat.py`.
 Completing these tests successfully a good basis point (it's a requirement, actually), however these won't guarantee correct exchange functioning, as this only tests public endpoints, but no private endpoint (like generate order or similar).
 
 Also try to use `freqtrade download-data` for an extended timerange (multiple months) and verify that the data downloaded correctly (no holes, the specified timerange was actually downloaded).
@@ -481,21 +481,24 @@ Once the PR against stable is merged (best right after merging):
 
 ### pypi
 
-!!! Note
-    This process is now automated as part of Github Actions.
+!!! Warning "Manual Releases"
+    This process is automated as part of Github Actions.  
+    Manual pypi pushes should not be necessary.
 
-To create a pypi release, please run the following commands:
+??? example "Manual release"
+    To manually create a pypi release, please run the following commands:
 
-Additional requirement: `wheel`, `twine` (for uploading), account on pypi with proper permissions.
+    Additional requirement: `wheel`, `twine` (for uploading), account on pypi with proper permissions.
 
-``` bash
-python setup.py sdist bdist_wheel
+    ``` bash
+    pip install -U build
+    python -m build --sdist --wheel
 
-# For pypi test (to check if some change to the installation did work)
-twine upload --repository-url https://test.pypi.org/legacy/ dist/*
+    # For pypi test (to check if some change to the installation did work)
+    twine upload --repository-url https://test.pypi.org/legacy/ dist/*
 
-# For production:
-twine upload dist/*
-```
+    # For production:
+    twine upload dist/*
+    ```
 
-Please don't push non-releases to the productive / real pypi instance.
+    Please don't push non-releases to the productive / real pypi instance.

docs/edge.md

@@ -137,7 +137,7 @@ $$ R = \frac{\text{average_profit}}{\text{average_loss}} = \frac{\mu_{win}}{\mu_
 
 ### Expectancy
 
-By combining the Win Rate $W$ and and the Risk Reward ratio $R$ to create an expectancy ratio $E$. A expectance ratio is the expected return of the investment made in a trade. We can compute the value of $E$ as follows:
+By combining the Win Rate $W$ and the Risk Reward ratio $R$ to create an expectancy ratio $E$. A expectance ratio is the expected return of the investment made in a trade. We can compute the value of $E$ as follows:
 
 $$E = R * W - L$$
 

docs/exchanges.md

@@ -127,6 +127,13 @@ These settings will be checked on startup, and freqtrade will show an error if t
 
 Freqtrade will not attempt to change these settings.
 
+## Bingx
+
+BingX supports [time_in_force](configuration.md#understand-order_time_in_force) with settings "GTC" (good till cancelled), "IOC" (immediate-or-cancel) and "PO" (Post only) settings.
+
+!!! Tip "Stoploss on Exchange"
+    Bingx supports `stoploss_on_exchange` and can use both stop-limit and stop-market orders. It provides great advantages, so we recommend to benefit from it by enabling stoploss on exchange.
+
 ## Kraken
 
 Kraken supports [time_in_force](configuration.md#understand-order_time_in_force) with settings "GTC" (good till cancelled), "IOC" (immediate-or-cancel) and "PO" (Post only) settings.
@@ -248,18 +255,24 @@ The configuration parameter `exchange.unknown_fee_rate` can be used to specify t
 ## Bybit
 
 Futures trading on bybit is currently supported for USDT markets, and will use isolated futures mode.
-Users with unified accounts (there's no way back) can create a Sub-account which will start as "non-unified", and can therefore use isolated futures.
-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
+
+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.
 
 As bybit doesn't provide funding rate history, the dry-run calculation is used for live trades as well.
 
-API Keys for live futures trading (Subaccount on non-unified) must have the following permissions:
+API Keys for live futures trading must have the following permissions:
 * Read-write
 * Contract - Orders
 * Contract - Positions
 
 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.
@@ -299,7 +312,7 @@ $ pip3 install web3
 Most exchanges return current incomplete candle via their OHLCV/klines API interface.
 By default, Freqtrade assumes that incomplete candle is fetched from the exchange and removes the last candle assuming it's the incomplete candle.
 
-Whether your exchange returns incomplete candles or not can be checked using [the helper script](developer.md#Incomplete-candles) from the Contributor documentation.
+Whether your exchange returns incomplete candles or not can be checked using [the helper script](developer.md#incomplete-candles) from the Contributor documentation.
 
 Due to the danger of repainting, Freqtrade does not allow you to use this incomplete candle.
 

docs/faq.md

@@ -2,7 +2,7 @@
 
 ## Supported Markets
 
-Freqtrade supports spot trading, as well as (isolated) futures trading for some selected exchanges. Please refer to the [documentation start page](index.md#supported-futures-exchanges-experimental) for an uptodate list of supported exchanges.
+Freqtrade supports spot trading, as well as (isolated) futures trading for some selected exchanges. Please refer to the [documentation start page](index.md#supported-futures-exchanges-experimental) for an up-to-date list of supported exchanges.
 
 ### Can my bot open short positions?
 
@@ -14,7 +14,7 @@ In spot markets, you can in some cases use leveraged spot tokens, which reflect
 
 ### Can my bot trade options or futures?
 
-Futures trading is supported for selected exchanges. Please refer to the [documentation start page](index.md#supported-futures-exchanges-experimental) for an uptodate list of supported exchanges.
+Futures trading is supported for selected exchanges. Please refer to the [documentation start page](index.md#supported-futures-exchanges-experimental) for an up-to-date list of supported exchanges.
 
 ## Beginner Tips & Tricks
 

docs/freq-ui.md

@@ -0,0 +1,84 @@
+# FreqUI
+
+Freqtrade provides a builtin webserver, which can serve [FreqUI](https://github.com/freqtrade/frequi), the freqtrade frontend.
+
+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.
+
+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`).
+
+??? Note "Looking to contribute to freqUI?"
+    Developers should not use this method, but instead clone the corresponding use the method described in the [freqUI repository](https://github.com/freqtrade/frequi) to get the source-code of freqUI. A working installation of node will be required to build the frontend.
+
+!!! tip "freqUI is not required to run freqtrade"
+    freqUI is an optional component of freqtrade, and is not required to run the bot.
+    It is a frontend that can be used to monitor the bot and to interact with it - but freqtrade itself will work perfectly fine without it.
+
+## Configuration
+
+FreqUI does not have it's own configuration file - but assumes a working setup for the [rest-api](rest-api.md) is available.
+Please refer to the corresponding documentation page to get setup with freqUI
+
+## UI
+
+FreqUI is a modern, responsive web application that can be used to monitor and interact with your bot.
+
+FreqUI provides a light, as well as a dark theme.
+Themes can be easily switched via a prominent button at the top of the page.
+The theme of the screenshots on this page will adapt to the selected documentation Theme, so to see the dark (or light) version, please switch the theme of the Documentation.
+
+### Login
+
+The below screenshot shows the login screen of freqUI.
+
+![FreqUI - login](assets/frequi-login-CORS.png#only-dark)
+![FreqUI - login](assets/frequi-login-CORS-light.png#only-light)
+
+!!! Hint "CORS"
+    The Cors error shown in this screenshot is due to the fact that the UI is running on a different port than the API, and [CORS](#cors) has not been setup correctly yet.
+
+### Trade view
+
+The trade view allows you to visualize the trades that the bot is making and to interact with the bot.
+On this page, you can also interact with the bot by starting and stopping it and - if configured - force trade entries and exits.
+
+![FreqUI - trade view](assets/freqUI-trade-pane-dark.png#only-dark)
+![FreqUI - trade view](assets/freqUI-trade-pane-light.png#only-light)
+
+### Plot Configurator
+
+FreqUI Plots can be configured either via a `plot_config` configuration object in the strategy (which can be loaded via "from strategy" button) or via the UI.
+Multiple plot configurations can be created and switched at will - allowing for flexible, different views into your charts.
+
+The plot configuration can be accessed via the "Plot Configurator" (Cog icon) button in the top right corner of the trade view.
+
+![FreqUI - plot configuration](assets/freqUI-plot-configurator-dark.png#only-dark)
+![FreqUI - plot configuration](assets/freqUI-plot-configurator-light.png#only-light)
+
+### Settings
+
+Several UI related settings can be changed by accessing the settings page.
+
+Things you can change (among others):
+
+* Timezone of the UI
+* Visualization of open trades as part of the favicon (browser tab)
+* Candle colors (up/down -> red/green)
+* Enable / disable in-app notification types
+
+![FreqUI - Settings view](assets/frequi-settings-dark.png#only-dark)
+![FreqUI - Settings view](assets/frequi-settings-light.png#only-light)
+
+## 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.
+
+You can also load and visualize previous backtest results, as well as compare the results with each other.
+
+![FreqUI - Backtesting](assets/freqUI-backtesting-dark.png#only-dark)
+![FreqUI - Backtesting](assets/freqUI-backtesting-light.png#only-light)
+
+
+--8<-- "includes/cors.md"

docs/freqai-feature-engineering.md

@@ -224,7 +224,7 @@ where $W_i$ is the weight of data point $i$ in a total set of $n$ data points. B
 
 ## Building the data pipeline
 
-By default, FreqAI builds a dynamic pipeline based on user congfiguration settings. The default settings are robust and designed to work with a variety of methods. These two steps are a `MinMaxScaler(-1,1)` and a `VarianceThreshold` which removes any column that has 0 variance. Users can activate other steps with more configuration parameters. For example if users add `use_SVM_to_remove_outliers: true` to the `freqai` config, then FreqAI will automatically add the [`SVMOutlierExtractor`](#identifying-outliers-using-a-support-vector-machine-svm) to the pipeline. Likewise, users can add `principal_component_analysis: true` to the `freqai` config to activate PCA. The [DissimilarityIndex](#identifying-outliers-with-the-dissimilarity-index-di) is activated with `DI_threshold: 1`. Finally, noise can also be added to the data with `noise_standard_deviation: 0.1`. Finally, users can add [DBSCAN](#identifying-outliers-with-dbscan) outlier removal with `use_DBSCAN_to_remove_outliers: true`.
+By default, FreqAI builds a dynamic pipeline based on user configuration settings. The default settings are robust and designed to work with a variety of methods. These two steps are a `MinMaxScaler(-1,1)` and a `VarianceThreshold` which removes any column that has 0 variance. Users can activate other steps with more configuration parameters. For example if users add `use_SVM_to_remove_outliers: true` to the `freqai` config, then FreqAI will automatically add the [`SVMOutlierExtractor`](#identifying-outliers-using-a-support-vector-machine-svm) to the pipeline. Likewise, users can add `principal_component_analysis: true` to the `freqai` config to activate PCA. The [DissimilarityIndex](#identifying-outliers-with-the-dissimilarity-index-di) is activated with `DI_threshold: 1`. Finally, noise can also be added to the data with `noise_standard_deviation: 0.1`. Finally, users can add [DBSCAN](#identifying-outliers-with-dbscan) outlier removal with `use_DBSCAN_to_remove_outliers: true`.
 
 !!! note "More information available"
     Please review the [parameter table](freqai-parameter-table.md) for more information on these parameters.
@@ -235,7 +235,7 @@ By default, FreqAI builds a dynamic pipeline based on user congfiguration settin
 Users are encouraged to customize the data pipeline to their needs by building their own data pipeline. This can be done by simply setting `dk.feature_pipeline` to their desired `Pipeline` object inside their `IFreqaiModel` `train()` function, or if they prefer not to touch the `train()` function, they can override `define_data_pipeline`/`define_label_pipeline` functions in their `IFreqaiModel`:
 
 !!! note "More information available"
-    FreqAI uses the the [`DataSieve`](https://github.com/emergentmethods/datasieve) pipeline, which follows the SKlearn pipeline API, but adds, among other features, coherence between the X, y, and sample_weight vector point removals, feature removal, feature name following. 
+    FreqAI uses the [`DataSieve`](https://github.com/emergentmethods/datasieve) pipeline, which follows the SKlearn pipeline API, but adds, among other features, coherence between the X, y, and sample_weight vector point removals, feature removal, feature name following. 
 
 ```python
 from datasieve.transforms import SKLearnWrapper, DissimilarityIndex
@@ -391,3 +391,18 @@ Given a number of data points $N$, and a distance $\varepsilon$, DBSCAN clusters
 ![dbscan](assets/freqai_dbscan.jpg)
 
 FreqAI uses `sklearn.cluster.DBSCAN` (details are available on scikit-learn's webpage [here](https://scikit-learn.org/stable/modules/generated/sklearn.cluster.DBSCAN.html) (external website)) with `min_samples` ($N$) taken as 1/4 of the no. of time points (candles) in the feature set. `eps` ($\varepsilon$) is computed automatically as the elbow point in the *k-distance graph* computed from the nearest neighbors in the pairwise distances of all data points in the feature set.
+
+
+### Data dimensionality reduction with Principal Component Analysis
+
+You can reduce the dimensionality of your features by activating the principal_component_analysis in the config:
+
+```json
+    "freqai": {
+        "feature_parameters" : {
+            "principal_component_analysis": true
+        }
+    }
+```
+
+This will perform PCA on the features and reduce their dimensionality so that the explained variance of the data set is >= 0.999. Reducing data dimensionality makes training the model faster and hence allows for more up-to-date models.

docs/freqai-parameter-table.md

@@ -31,12 +31,12 @@ Mandatory parameters are marked as **Required** and have to be set in one of the
 | `feature_parameters` | A dictionary containing the parameters used to engineer the feature set. Details and examples are shown [here](freqai-feature-engineering.md). <br> **Datatype:** Dictionary.
 | `include_timeframes` | A list of timeframes that all indicators in `feature_engineering_expand_*()` will be created for. The list is added as features to the base indicators dataset. <br> **Datatype:** List of timeframes (strings).
 | `include_corr_pairlist` | A list of correlated coins that FreqAI will add as additional features to all `pair_whitelist` coins. All indicators set in `feature_engineering_expand_*()` during feature engineering (see details [here](freqai-feature-engineering.md)) will be created for each correlated coin. The correlated coins features are added to the base indicators dataset. <br> **Datatype:** List of assets (strings).
-| `label_period_candles` | Number of candles into the future that the labels are created for. This is used in `feature_engineering_expand_all()` (see `templates/FreqaiExampleStrategy.py` for detailed usage). You can create custom labels and choose whether to make use of this parameter or not. <br> **Datatype:** Positive integer.
+| `label_period_candles` | Number of candles into the future that the labels are created for. This can be used in `set_freqai_targets()` (see `templates/FreqaiExampleStrategy.py` for detailed usage). This parameter is not necessarily required, you can create custom labels and choose whether to make use of this parameter or not. Please see `templates/FreqaiExampleStrategy.py` to see the example usage. <br> **Datatype:** Positive integer.
 | `include_shifted_candles` | Add features from previous candles to subsequent candles with the intent of adding historical information. If used, FreqAI will duplicate and shift all features from the `include_shifted_candles` previous candles so that the information is available for the subsequent candle. <br> **Datatype:** Positive integer.
 | `weight_factor` | Weight training data points according to their recency (see details [here](freqai-feature-engineering.md#weighting-features-for-temporal-importance)). <br> **Datatype:** Positive float (typically < 1).
 | `indicator_max_period_candles` | **No longer used (#7325)**. Replaced by `startup_candle_count` which is set in the [strategy](freqai-configuration.md#building-a-freqai-strategy). `startup_candle_count` is timeframe independent and defines the maximum *period* used in `feature_engineering_*()` for indicator creation. FreqAI uses this parameter together with the maximum timeframe in `include_time_frames` to calculate how many data points to download such that the first data point does not include a NaN. <br> **Datatype:** Positive integer.
 | `indicator_periods_candles` | Time periods to calculate indicators for. The indicators are added to the base indicator dataset. <br> **Datatype:** List of positive integers.
-| `principal_component_analysis` | Automatically reduce the dimensionality of the data set using Principal Component Analysis. See details about how it works [here](#reducing-data-dimensionality-with-principal-component-analysis) <br> **Datatype:** Boolean. <br> Default: `False`.
+| `principal_component_analysis` | Automatically reduce the dimensionality of the data set using Principal Component Analysis. See details about how it works [here](freqai-feature-engineering.md#data-dimensionality-reduction-with-principal-component-analysis) <br> **Datatype:** Boolean. <br> Default: `False`.
 | `plot_feature_importances` | Create a feature importance plot for each model for the top/bottom `plot_feature_importances` number of features. Plot is stored in `user_data/models/<identifier>/sub-train-<COIN>_<timestamp>.html`. <br> **Datatype:** Integer. <br> Default: `0`.
 | `DI_threshold` | Activates the use of the Dissimilarity Index for outlier detection when set to > 0. See details about how it works [here](freqai-feature-engineering.md#identifying-outliers-with-the-dissimilarity-index-di). <br> **Datatype:** Positive float (typically < 1).
 | `use_SVM_to_remove_outliers` | Train a support vector machine to detect and remove outliers from the training dataset, as well as from incoming data points. See details about how it works [here](freqai-feature-engineering.md#identifying-outliers-using-a-support-vector-machine-svm). <br> **Datatype:** Boolean.
@@ -55,7 +55,7 @@ Mandatory parameters are marked as **Required** and have to be set in one of the
 |  |  **Data split parameters within the `freqai.data_split_parameters` sub dictionary**
 | `data_split_parameters` | Include any additional parameters available from scikit-learn `test_train_split()`, which are shown [here](https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.train_test_split.html) (external website). <br> **Datatype:** Dictionary.
 | `test_size` | The fraction of data that should be used for testing instead of training. <br> **Datatype:** Positive float < 1.
-| `shuffle` | Shuffle the training data points during training. Typically, to not remove the chronological order of data in time-series forecasting, this is set to `False`. <br> **Datatype:** Boolean. <br> Defaut: `False`.
+| `shuffle` | Shuffle the training data points during training. Typically, to not remove the chronological order of data in time-series forecasting, this is set to `False`. <br> **Datatype:** Boolean. <br> Default: `False`.
 
 ### Model training parameters
 

docs/freqai-running.md

@@ -73,23 +73,26 @@ Backtesting mode requires [downloading the necessary data](#downloading-data-to-
 
 ---
 
-### Saving prediction data
+### Saving backtesting prediction data
 
 To allow for tweaking your strategy (**not** the features!), FreqAI will automatically save the predictions during backtesting so that they can be reused for future backtests and live runs using the same `identifier` model. This provides a performance enhancement geared towards enabling **high-level hyperopting** of entry/exit criteria.
 
-An additional directory called `backtesting_predictions`, which contains all the predictions stored in `hdf` format, will be created in the `unique-id` folder.
+An additional directory called `backtesting_predictions`, which contains all the predictions stored in `feather` format, will be created in the `unique-id` folder.
 
 To change your **features**, you **must** set a new `identifier` in the config to signal to FreqAI to train new models.
 
 To save the models generated during a particular backtest so that you can start a live deployment from one of them instead of training a new model, you must set `save_backtest_models` to `True` in the config.
 
+!!! Note
+    To ensure that the model can be reused, freqAI will call your strategy with a dataframe of length 1. 
+    If your strategy requires more data than this to generate the same features, you can't reuse backtest predictions for live deployment and need to update your `identifier` for each new backtest.
+
 ### Backtest live collected predictions
 
 FreqAI allow you to reuse live historic predictions through the backtest parameter `--freqai-backtest-live-models`. This can be useful when you want to reuse predictions generated in dry/run for comparison or other study.
 
 The `--timerange` parameter must not be informed, as it will be automatically calculated through the data in the historic predictions file.
 
-
 ### Downloading data to cover the full backtest period
 
 For live/dry deployments, FreqAI will download the necessary data automatically. However, to use backtesting functionality, you need to download the necessary data using `download-data` (details [here](data-download.md#data-downloading)). You need to pay careful attention to understanding how much *additional* data needs to be downloaded to ensure that there is a sufficient amount of training data *before* the start of the backtesting time range. The amount of additional data can be roughly estimated by moving the start date of the time range backwards by `train_period_days` and the `startup_candle_count` (see the [parameter table](freqai-parameter-table.md) for detailed descriptions of these parameters) from the beginning of the desired backtesting time range. 

docs/hyperopt.md

@@ -14,8 +14,7 @@ To learn how to get data for the pairs and exchange you're interested in, head o
 
 !!! Note
     Since 2021.4 release you no longer have to write a separate hyperopt class, but can configure the parameters directly in the strategy.
-    The legacy method is still supported, but it is no longer the recommended way of setting up hyperopt. 
-    The legacy documentation is available at [Legacy Hyperopt](advanced-hyperopt.md#legacy-hyperopt).
+    The legacy method was supported up to 2021.8 and has been removed in 2021.9.
 
 ## Install hyperopt dependencies
 
@@ -765,7 +764,7 @@ Override the `roi_space()` method if you need components of the ROI tables to va
 A sample for these methods can be found in the [overriding pre-defined spaces section](advanced-hyperopt.md#overriding-pre-defined-spaces).
 
 !!! Note "Reduced search space"
-    To limit the search space further, Decimals are limited to 3 decimal places (a precision of 0.001). This is usually sufficient, every value more precise than this will usually result in overfitted results. You can however [overriding pre-defined spaces](advanced-hyperopt.md#pverriding-pre-defined-spaces) to change this to your needs.
+    To limit the search space further, Decimals are limited to 3 decimal places (a precision of 0.001). This is usually sufficient, every value more precise than this will usually result in overfitted results. You can however [overriding pre-defined spaces](advanced-hyperopt.md#overriding-pre-defined-spaces) to change this to your needs.
 
 ### Understand Hyperopt Stoploss results
 
@@ -807,7 +806,7 @@ If you have the `stoploss_space()` method in your custom hyperopt file, remove i
 Override the `stoploss_space()` method and define the desired range in it if you need stoploss values to vary in other range during hyperoptimization. A sample for this method can be found in the [overriding pre-defined spaces section](advanced-hyperopt.md#overriding-pre-defined-spaces).
 
 !!! Note "Reduced search space"
-    To limit the search space further, Decimals are limited to 3 decimal places (a precision of 0.001). This is usually sufficient, every value more precise than this will usually result in overfitted results. You can however [overriding pre-defined spaces](advanced-hyperopt.md#pverriding-pre-defined-spaces) to change this to your needs.
+    To limit the search space further, Decimals are limited to 3 decimal places (a precision of 0.001). This is usually sufficient, every value more precise than this will usually result in overfitted results. You can however [overriding pre-defined spaces](advanced-hyperopt.md#overriding-pre-defined-spaces) to change this to your needs.
 
 ### Understand Hyperopt Trailing Stop results
 

docs/includes/cors.md

@@ -0,0 +1,43 @@
+## CORS
+
+This whole section is only necessary in cross-origin cases (where you multiple bot API's running on `localhost:8081`, `localhost:8082`, ...), and want to combine them into one FreqUI instance.
+
+??? info "Technical explanation"
+    All web-based front-ends are subject to [CORS](https://developer.mozilla.org/en-US/docs/Web/HTTP/CORS) - Cross-Origin Resource Sharing.
+    Since most of the requests to the Freqtrade API must be authenticated, a proper CORS policy is key to avoid security problems.
+    Also, the standard disallows `*` CORS policies for requests with credentials, so this setting must be set appropriately.
+
+Users can allow access from different origin URL's to the bot API via the `CORS_origins` configuration setting.
+It consists of a list of allowed URL's that are allowed to consume resources from the bot's API.
+
+Assuming your application is deployed as `https://frequi.freqtrade.io/home/` - this would mean that the following configuration becomes necessary:
+
+```jsonc
+{
+    //...
+    "jwt_secret_key": "somethingrandom",
+    "CORS_origins": ["https://frequi.freqtrade.io"],
+    //...
+}
+```
+
+In the following (pretty common) case, FreqUI is accessible on `http://localhost:8080/trade` (this is what you see in your navbar when navigating to freqUI).
+![freqUI url](assets/frequi_url.png)
+
+The correct configuration for this case is `http://localhost:8080` - the main part of the URL including the port.
+
+```jsonc
+{
+    //...
+    "jwt_secret_key": "somethingrandom",
+    "CORS_origins": ["http://localhost:8080"],
+    //...
+}
+```
+
+!!! Tip "trailing Slash"
+    The trailing slash is not allowed in the `CORS_origins` configuration (e.g. `"http://localhots:8080/"`).
+    Such a configuration will not take effect, and the cors errors will remain.
+
+!!! Note
+    We strongly recommend to also set `jwt_secret_key` to something random and known only to yourself to avoid unauthorized access to your bot.

docs/includes/pairlists.md

@@ -2,11 +2,11 @@
 
 Pairlist Handlers define the list of pairs (pairlist) that the bot should trade. They are configured in the `pairlists` section of the configuration settings.
 
-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) Pairlist Handler).
+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.
 
-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` or `MarketCapPairList` as the starting Pairlist Handler.
+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.
 
 Inactive markets are always removed from the resulting pairlist. Explicitly blacklisted pairs (those in the `pair_blacklist` configuration setting) are also always removed from the resulting pairlist.
 
@@ -22,6 +22,7 @@ You may also use something like `.*DOWN/BTC` or `.*UP/BTC` to exclude leveraged
 
 * [`StaticPairList`](#static-pair-list) (default, if not configured differently)
 * [`VolumePairList`](#volume-pair-list)
+* [`PercentChangePairList`](#percent-change-pair-list)
 * [`ProducerPairList`](#producerpairlist)
 * [`RemotePairList`](#remotepairlist)
 * [`MarketCapPairList`](#marketcappairlist)
@@ -54,7 +55,6 @@ It uses configuration from `exchange.pair_whitelist` and `exchange.pair_blacklis
 By default, only currently enabled pairs are allowed.
 To skip pair validation against active markets, set `"allow_inactive": true` within the `StaticPairList` configuration.
 This can be useful for backtesting expired pairs (like quarterly spot-markets).
-This option must be configured along with `exchange.skip_pair_validation` in the exchange configuration.
 
 When used in a "follow-up" position (e.g. after VolumePairlist), all pairs in `'pair_whitelist'` will be added to the end of the pairlist.
 
@@ -152,6 +152,89 @@ More sophisticated approach can be used, by using `lookback_timeframe` for candl
 !!! Note
     `VolumePairList` does not support backtesting mode.
 
+#### Percent Change Pair List
+
+`PercentChangePairList` filters and sorts pairs based on the percentage change in their price over the last 24 hours or any defined timeframe as part of advanced options. This allows traders to focus on assets that have experienced significant price movements, either positive or negative.
+
+**Configuration Options**
+
+* `number_assets`: Specifies the number of top pairs to select based on the 24-hour percentage change.
+* `min_value`: Sets a minimum percentage change threshold. Pairs with a percentage change below this value will be filtered out.
+* `max_value`: Sets a maximum percentage change threshold. Pairs with a percentage change above this value will be filtered out.
+* `sort_direction`: Specifies the order in which pairs are sorted based on their percentage change. Accepts two values: `asc` for ascending order and `desc` for descending order.
+* `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. 
+
+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.
+
+`PercentChangePairList` uses ticker data from the exchange, provided via the ccxt library:
+The percentage change is calculated as the change in price over the last 24 hours.
+
+??? Note "Unsupported exchanges"
+    On some exchanges (like HTX), regular PercentChangePairList does not work as the api does not natively provide 24h percent change in price. This can be worked around by using candle data to calculate the percentage change. To roughly simulate 24h percent change, you can use the following configuration. Please note that these pairlists will only refresh once per day.
+    ```json
+    "pairlists": [
+        {
+            "method": "PercentChangePairList",
+            "number_assets": 20,
+            "min_value": 0,
+            "refresh_period": 86400,
+            "lookback_days": 1
+        }
+    ],
+    ```
+
+**Example Configuration to Read from Ticker**
+
+```json
+"pairlists": [
+    {
+        "method": "PercentChangePairList",
+        "number_assets": 15,
+        "min_value": -10,
+        "max_value": 50
+    }
+],
+```
+
+In this configuration:
+
+1. The top 15 pairs are selected based on the highest percentage change in price over the last 24 hours.
+2. Only pairs with a percentage change between -10% and 50% are considered.
+
+**Example Configuration to Read from Candles**
+
+```json
+"pairlists": [
+    {
+        "method": "PercentChangePairList",
+        "number_assets": 15,
+        "sort_key": "percentage",
+        "min_value": 0,
+        "refresh_period": 3600,
+        "lookback_timeframe": "1h",
+        "lookback_period": 72
+    }
+],
+```
+
+This example builds the percent change pairs based on a rolling period of 3 days of 1-hour candles by using `lookback_timeframe` for candle size and `lookback_period` which specifies the number of candles.
+
+The percent change in price is calculated using the following formula, which expresses the percentage difference between the current candle's close price and the previous candle's close price, as defined by the specified timeframe and lookback period:
+
+$$ Percent Change = (\frac{Current Close - Previous Close}{Previous Close}) * 100 $$
+
+!!! Warning "Range look back and refresh period"
+    When used in conjunction with `lookback_days` and `lookback_timeframe` the `refresh_period` can not be smaller than the candle size in seconds. As this will result in unnecessary requests to the exchanges API.
+
+!!! Warning "Performance implications when using lookback range"
+    If used in first position in combination with lookback, the computation of the range-based percent change can be time and resource consuming, as it downloads candles for all tradable pairs. Hence it's highly advised to use the standard approach with `PercentChangePairList` to narrow the pairlist down for further percent-change calculation.
+
+!!! Note "Backtesting"
+    `PercentChangePairList` does not support backtesting mode.
+
 #### ProducerPairList
 
 With `ProducerPairList`, you can reuse the pairlist from a [Producer](producer-consumer.md) without explicitly defining the pairlist on each consumer.
@@ -277,14 +360,21 @@ The optional `bearer_token` will be included in the requests Authorization Heade
         "method": "MarketCapPairList",
         "number_assets": 20,
         "max_rank": 50,
-        "refresh_period": 86400
+        "refresh_period": 86400,
+        "categories": ["layer-1"]
     }
 ]
 ```
 
 `number_assets` defines the maximum number of pairs returned by the pairlist. `max_rank` will determine the maximum rank used in creating/filtering the pairlist. It's expected that some coins within the top `max_rank` marketcap will not be included in the resulting pairlist since not all pairs will have active trading pairs in your preferred market/stake/exchange combination.
 
-`refresh_period` setting defines the period (in seconds) at which the marketcap rank data will be refreshed. Defaults to 86,400s (1 day). The pairlist cache (`refresh_period`) is applicable on both generating pairlists (first position in the list) and filtering instances (not the first position in the list).
+The `refresh_period` setting defines the interval (in seconds) at which the marketcap rank data will be refreshed. The default is 86,400 seconds (1 day). The pairlist cache (`refresh_period`) applies to both generating pairlists (when in the first position in the list) and filtering instances (when not in the first position in the list).
+
+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.
+
+!!! 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.
 
 #### AgeFilter
 
@@ -373,7 +463,7 @@ Filters low-value coins which would not allow setting stoplosses.
 
 Namely, pairs are blacklisted if a variance of one percent or more in the stop price would be caused by precision rounding on the exchange, i.e. `rounded(stop_price) <= rounded(stop_price * 0.99)`. The idea is to avoid coins with a value VERY close to their lower trading boundary, not allowing setting of proper stoploss.
 
-!!! Tip "PerformanceFilter is pointless for futures trading"
+!!! Tip "PrecisionFilter is pointless for futures trading"
     The above does not apply to shorts. And for longs, in theory the trade will be liquidated first.
 
 !!! Warning "Backtesting"

docs/includes/protections.md

@@ -36,6 +36,7 @@ All protection end times are rounded up to the next candle to avoid sudden, unex
 | `lookback_period_candles` | Only trades that completed within the last `lookback_period_candles` candles will be considered. This setting may be ignored by some Protections. <br> **Datatype:** Positive integer (in candles).
 | `lookback_period` | Only trades that completed after `current_time - lookback_period` will be considered. <br>Cannot be used together with `lookback_period_candles`. <br>This setting may be ignored by some Protections. <br> **Datatype:**  Float (in minutes)
 | `trade_limit` | Number of trades required at minimum (not used by all Protections). <br> **Datatype:** Positive integer
+| `unlock_at` | Time when trading will be unlocked regularly (not used by all Protections). <br> **Datatype:** string <br>**Input Format:** "HH:MM" (24-hours)
 
 !!! Note "Durations"
     Durations (`stop_duration*` and `lookback_period*` can be defined in either minutes or candles).
@@ -44,7 +45,7 @@ All protection end times are rounded up to the next candle to avoid sudden, unex
 #### Stoploss Guard
 
 `StoplossGuard` selects all trades within `lookback_period` in minutes (or in candles when using `lookback_period_candles`).
-If `trade_limit` or more trades resulted in stoploss, trading will stop for `stop_duration` in minutes (or in candles when using `stop_duration_candles`).
+If `trade_limit` or more trades resulted in stoploss, trading will stop for `stop_duration` in minutes (or in candles when using `stop_duration_candles`, or until the set time when using `unlock_at`).
 
 This applies across all pairs, unless `only_per_pair` is set to true, which will then only look at one pair at a time.
 
@@ -97,7 +98,7 @@ def protections(self):
 #### Low Profit Pairs
 
 `LowProfitPairs` uses all trades for a pair within `lookback_period` in minutes (or in candles when using `lookback_period_candles`) to determine the overall profit ratio.
-If that ratio is below `required_profit`, that pair will be locked for `stop_duration` in minutes (or in candles when using `stop_duration_candles`).
+If that ratio is below `required_profit`, that pair will be locked for `stop_duration` in minutes (or in candles when using `stop_duration_candles`, or until the set time when using `unlock_at`).
 
 For futures bots, setting `only_per_side` will make the bot only consider one side, and will then only lock this one side, allowing for example shorts to continue after a series of long losses.
 
@@ -120,7 +121,7 @@ def protections(self):
 
 #### Cooldown Period
 
-`CooldownPeriod` locks a pair for `stop_duration` in minutes (or in candles when using `stop_duration_candles`) after selling, avoiding a re-entry for this pair for `stop_duration` minutes.
+`CooldownPeriod` locks a pair for `stop_duration` in minutes (or in candles when using `stop_duration_candles`, or until the set time when using `unlock_at`) after exiting, avoiding a re-entry for this pair for `stop_duration` minutes.
 
 The below example will stop trading a pair for 2 candles after closing a trade, allowing this pair to "cool down".
 

docs/includes/strategy-imports.md

@@ -0,0 +1,45 @@
+## Imports necessary for a strategy
+
+When creating a strategy, you will need to import the necessary modules and classes. The following imports are required for a strategy:
+
+By default, we recommend the following imports as a base line for your strategy:
+This will cover all imports necessary for freqtrade functions to work.
+Obviously you can add more imports as needed for your strategy.
+
+``` python
+# flake8: noqa: F401
+# isort: skip_file
+# --- Do not remove these imports ---
+import numpy as np
+import pandas as pd
+from datetime import datetime, timedelta, timezone
+from pandas import DataFrame
+from typing import Dict, Optional, Union, Tuple
+
+from freqtrade.strategy import (
+    IStrategy,
+    Trade, 
+    Order,
+    PairLocks,
+    informative,  # @informative decorator
+    # Hyperopt Parameters
+    BooleanParameter,
+    CategoricalParameter,
+    DecimalParameter,
+    IntParameter,
+    RealParameter,
+    # timeframe helpers
+    timeframe_to_minutes,
+    timeframe_to_next_date,
+    timeframe_to_prev_date,
+    # Strategy helper functions
+    merge_informative_pair,
+    stoploss_from_absolute,
+    stoploss_from_open,
+)
+
+# --------------------------------
+# Add your lib to import here
+import talib.abstract as ta
+from technical import qtpylib
+```

docs/index.md

@@ -41,6 +41,8 @@ Please read the [exchange specific notes](exchanges.md) to learn about eventual,
 
 - [X] [Binance](https://www.binance.com/)
 - [X] [Bitmart](https://bitmart.com/)
+- [X] [BingX](https://bingx.com/invite/0EM9RX)
+- [X] [Bybit](https://bybit.com/)
 - [X] [Gate.io](https://www.gate.io/ref/6266643)
 - [X] [HTX](https://www.htx.com/) (Former Huobi)
 - [X] [Kraken](https://kraken.com/)

docs/installation.md

@@ -51,7 +51,7 @@ These requirements apply to both [Script Installation](#script-installation) and
 ### Install code
 
 We've included/collected install instructions for Ubuntu, MacOS, and Windows. These are guidelines and your success may vary with other distros.
-OS Specific steps are listed first, the [Common](#common) section below is necessary for all systems.
+OS Specific steps are listed first, the common section below is necessary for all systems.
 
 !!! Note
     Python3.9 or higher and the corresponding pip are assumed to be available.
@@ -286,7 +286,7 @@ cd freqtrade
 #### Freqtrade install: Conda Environment
 
 ```bash
-conda create --name freqtrade python=3.11
+conda create --name freqtrade python=3.12
 ```
 
 !!! Note "Creating Conda Environment"

docs/leverage.md

@@ -17,7 +17,7 @@ If you already have an existing strategy, please read the [strategy migration gu
 
 ## Shorting
 
-Shorting is not possible when trading with [`trading_mode`](#understand-tradingmode) set to `spot`. To short trade, `trading_mode` must be set to `margin`(currently unavailable) or [`futures`](#futures), with [`margin_mode`](#margin-mode) set to `cross`(currently unavailable) or [`isolated`](#isolated-margin-mode)
+Shorting is not possible when trading with [`trading_mode`](#leverage-trading-modes) set to `spot`. To short trade, `trading_mode` must be set to `margin`(currently unavailable) or [`futures`](#futures), with [`margin_mode`](#margin-mode) set to `cross`(currently unavailable) or [`isolated`](#isolated-margin-mode)
 
 For a strategy to short, the strategy class must set the class variable `can_short = True`
 

docs/lookahead-analysis.md

@@ -101,3 +101,4 @@ This could lead to a false-negative (the strategy will then be reported as non-b
 - `lookahead-analysis` has access to everything that backtesting has too.
 Please don't provoke any configs like enabling position stacking.
 If you decide to do so, then make doubly sure that you won't ever run out of `max_open_trades` amount and neither leftover money in your wallet.
+- 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.

docs/plotting.md

@@ -2,6 +2,14 @@
 
 This page explains how to plot prices, indicators and profits.
 
+!!! Warning "Deprecated"
+    The commands described in this page (`plot-dataframe`, `plot-profit`) should be considered deprecated and are in maintenance mode.
+    This is mostly for the performance problems even medium sized plots can cause, but also because "store a file and open it in a browser" isn't very intuitive from a UI perspective.
+
+    While there are no immediate plans to remove them, they are not actively maintained - and may be removed short-term should major changes be required to keep them working.
+    
+    Please use [FreqUI](freq-ui.md) for plotting needs, which doesn't struggle with the same performance problems.
+
 ## Installation / Setup
 
 Plotting modules use the Plotly library. You can install / upgrade this by running the following command:

docs/requirements-docs.txt

@@ -1,6 +1,7 @@
-markdown==3.6
-mkdocs==1.5.3
-mkdocs-material==9.5.15
+markdown==3.7
+mkdocs==1.6.1
+mkdocs-material==9.5.36
 mdx_truly_sane_lists==1.3
-pymdown-extensions==10.7.1
-jinja2==3.1.3
+pymdown-extensions==10.10.1
+jinja2==3.1.4
+mike==2.1.3

docs/rest-api.md

@@ -1,16 +1,8 @@
-# REST API & FreqUI
+# REST API
 
 ## FreqUI
 
-Freqtrade provides a builtin webserver, which can serve [FreqUI](https://github.com/freqtrade/frequi), the freqtrade UI.
-
-By default, the UI is not included in the installation (except for docker images), and must be installed explicitly with `freqtrade install-ui`.
-This same command can also be used to update freqUI, should there be a new release.
-
-Once the bot is started in trade / dry-run mode (with `freqtrade trade`) - the UI will be available under the configured port below (usually `http://127.0.0.1:8080`).
-
-!!! Note "developers"
-    Developers should not use this method, but instead use the method described in the [freqUI repository](https://github.com/freqtrade/frequi) to get the source-code of freqUI.
+FreqUI now has it's own dedicated [documentation section](freq-ui.md) - please refer to that section for all information regarding the FreqUI.
 
 ## Configuration
 
@@ -89,7 +81,8 @@ Make sure that the following 2 lines are available in your docker-compose file:
 ```
 
 !!! Danger "Security warning"
-    By using `8080:8080` in the docker port mapping, the API will be available to everyone connecting to the server under the correct port, so others may be able to control your bot.
+    By using `"8080:8080"` (or `"0.0.0.0:8080:8080"`) in the docker port mapping, the API will be available to everyone connecting to the server under the correct port, so others may be able to control your bot.
+    This **may** be safe if you're running the bot in a secure environment (like your home network), but it's not recommended to expose the API to the internet.
 
 ## Rest API
 
@@ -125,6 +118,14 @@ By default, the script assumes `127.0.0.1` (localhost) and port `8080` to be use
 freqtrade-client --config rest_config.json <command> [optional parameters]
 ```
 
+Commands with many arguments may require keyword arguments (for clarity) - which can be provided as follows:
+
+``` bash
+freqtrade-client --config rest_config.json forceenter BTC/USDT long enter_tag=GutFeeling
+```
+
+This method will work for all arguments - check the "show" command for a list of available parameters.
+
 ??? Note "Programmatic use"
     The `freqtrade-client` package (installable independent of freqtrade) can be used in your own scripts to interact with the freqtrade API.
     to do so, please use the following:
@@ -166,8 +167,9 @@ freqtrade-client --config rest_config.json <command> [optional parameters]
 | `mix_tags [pair]` | 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.
 | `locks` | Displays currently locked pairs.
 | `delete_lock <lock_id>` | Deletes (disables) the lock by id.
+| `locks add <pair>, <until>, [side], [reason]` | Locks a pair until "until". (Until will be rounded up to the nearest timeframe).
 | `profit` | Display a summary of your profit/loss from close trades and some stats about your performance.
-| `forceexit <trade_id>` | Instantly exits the given trade  (Ignoring `minimum_roi`).
+| `forceexit <trade_id> [order_type] [amount]` | 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).
 | `forceexit all` | Instantly exits all open trades (Ignoring `minimum_roi`).
 | `forceenter <pair> [rate]` | Instantly enters the given pair. Rate is optional. (`force_entry_enable` must be set to True)
 | `forceenter <pair> <side> [rate]` | Instantly longs or shorts the given pair. Rate is optional. (`force_entry_enable` must be set to True)
@@ -453,7 +455,7 @@ To properly configure your reverse proxy (securely), please consult it's documen
 - **Caddy**: Caddy v2 supports websockets out of the box, see the [documentation](https://caddyserver.com/docs/v2-upgrade#proxy)
 
 !!! Tip "SSL certificates"
-    You can use tools like certbot to setup ssl certificates to access your bot's UI through encrypted connection by using any fo the above reverse proxies.
+    You can use tools like certbot to setup ssl certificates to access your bot's UI through encrypted connection by using any of the above reverse proxies.
     While this will protect your data in transit, we do not recommend to run the freqtrade API outside of your private network (VPN, SSH tunnel).
 
 ### OpenAPI interface
@@ -486,42 +488,4 @@ Since the access token has a short timeout (15 min) - the `token/refresh` reques
 {"access_token":"eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJpYXQiOjE1ODkxMTk5NzQsIm5iZiI6MTU4OTExOTk3NCwianRpIjoiMDBjNTlhMWUtMjBmYS00ZTk0LTliZjAtNWQwNTg2MTdiZDIyIiwiZXhwIjoxNTg5MTIwODc0LCJpZGVudGl0eSI6eyJ1IjoiRnJlcXRyYWRlciJ9LCJmcmVzaCI6ZmFsc2UsInR5cGUiOiJhY2Nlc3MifQ.1seHlII3WprjjclY6DpRhen0rqdF4j6jbvxIhUFaSbs"}
 ```
 
-### CORS
-
-This whole section is only necessary in cross-origin cases (where you multiple bot API's running on `localhost:8081`, `localhost:8082`, ...), and want to combine them into one FreqUI instance.
-
-??? info "Technical explanation"
-    All web-based front-ends are subject to [CORS](https://developer.mozilla.org/en-US/docs/Web/HTTP/CORS) - Cross-Origin Resource Sharing.
-    Since most of the requests to the Freqtrade API must be authenticated, a proper CORS policy is key to avoid security problems.
-    Also, the standard disallows `*` CORS policies for requests with credentials, so this setting must be set appropriately.
-
-Users can allow access from different origin URL's to the bot API via the `CORS_origins` configuration setting.
-It consists of a list of allowed URL's that are allowed to consume resources from the bot's API.
-
-Assuming your application is deployed as `https://frequi.freqtrade.io/home/` - this would mean that the following configuration becomes necessary:
-
-```jsonc
-{
-    //...
-    "jwt_secret_key": "somethingrandom",
-    "CORS_origins": ["https://frequi.freqtrade.io"],
-    //...
-}
-```
-
-In the following (pretty common) case, FreqUI is accessible on `http://localhost:8080/trade` (this is what you see in your navbar when navigating to freqUI).
-![freqUI url](assets/frequi_url.png)
-
-The correct configuration for this case is `http://localhost:8080` - the main part of the URL including the port.
-
-```jsonc
-{
-    //...
-    "jwt_secret_key": "somethingrandom",
-    "CORS_origins": ["http://localhost:8080"],
-    //...
-}
-```
-
-!!! Note
-    We strongly recommend to also set `jwt_secret_key` to something random and known only to yourself to avoid unauthorized access to your bot.
+--8<-- "includes/cors.md"

docs/sql_cheatsheet.md

@@ -1,6 +1,13 @@
 # SQL Helper
 
-This page contains some help if you want to edit your sqlite db.
+This page contains some help if you want to query your sqlite db.
+
+!!! Tip "Other Database systems"
+    To use other Database Systems like PostgreSQL or MariaDB, you can use the same queries, but you need to use the respective client for the database system. [Click here](advanced-setup.md#use-a-different-database-system) to learn how to setup a different database system with freqtrade.
+
+!!! Warning
+    If you are not familiar with SQL, you should be very careful when running queries on your database.  
+    Always make sure to have a backup of your database before running any queries.
 
 ## Install sqlite3
 
@@ -43,13 +50,25 @@ sqlite3
 .schema <table_name>
 ```
 
-## Get all trades in the table
+### Get all trades in the table
 
 ```sql
 SELECT * FROM trades;
 ```
 
-## Fix trade still open after a manual exit on the exchange
+## Destructive queries
+
+Queries that write to the database.
+These queries should usually not be necessary as freqtrade tries to handle all database operations itself - or exposes them via API or telegram commands.
+
+!!! Warning
+    Please make sure you have a backup of your database before running any of the below queries.
+
+!!! Danger
+    You should also **never** run any writing query (`update`, `insert`, `delete`) while a bot is connected to the database.
+    This can and will lead to data corruption - most likely, without the possibility of recovery.
+
+### Fix trade still open after a manual exit on the exchange
 
 !!! Warning
     Manually selling a pair on the exchange will not be detected by the bot and it will try to sell anyway. Whenever possible, /forceexit <tradeid> should be used to accomplish the same thing.  
@@ -69,7 +88,7 @@ SET is_open=0,
 WHERE id=<trade_ID_to_update>;
 ```
 
-### Example
+#### Example
 
 ```sql
 UPDATE trades
@@ -82,7 +101,7 @@ SET is_open=0,
 WHERE id=31;
 ```
 
-## Remove trade from the database
+### Remove trade from the database
 
 !!! Tip "Use RPC Methods to delete trades"
     Consider using `/delete <tradeid>` via telegram or rest API. That's the recommended way to deleting trades.
@@ -100,39 +119,3 @@ DELETE FROM trades WHERE id = 31;
 
 !!! Warning
     This will remove this trade from the database. Please make sure you got the correct id and **NEVER** run this query without the `where` clause.
-
-## Use a different database system
-
-Freqtrade is using SQLAlchemy, which supports multiple different database systems. As such, a multitude of database systems should be supported.
-Freqtrade does not depend or install any additional database driver. Please refer to the [SQLAlchemy docs](https://docs.sqlalchemy.org/en/14/core/engines.html#database-urls) on installation instructions for the respective database systems.
-
-The following systems have been tested and are known to work with freqtrade:
-
-* sqlite (default)
-* PostgreSQL
-* MariaDB
-
-!!! Warning
-    By using one of the below database systems, you acknowledge that you know how to manage such a system. The freqtrade team will not provide any support with setup or maintenance (or backups) of the below database systems.
-
-### PostgreSQL
-
-Installation:
-`pip install psycopg2-binary`
-
-Usage:
-`... --db-url postgresql+psycopg2://<username>:<password>@localhost:5432/<database>`
-
-Freqtrade will automatically create the tables necessary upon startup.
-
-If you're running different instances of Freqtrade, you must either setup one database per Instance or use different users / schemas for your connections.
-
-### MariaDB / MySQL
-
-Freqtrade supports MariaDB by using SQLAlchemy, which supports multiple different database systems.
-
-Installation:
-`pip install pymysql`
-
-Usage:
-`... --db-url mysql+pymysql://<username>:<password>@localhost:3306/<database>`

docs/stoploss.md

@@ -30,6 +30,7 @@ The Order-type will be ignored if only one mode is available.
 |----------|-------------|
 | Binance  | limit |
 | Binance Futures  | market, limit |
+| Bingx  | market, limit |
 | HTX (former Huobi)    | limit |
 | kraken   | market, limit |
 | Gate     | limit |
@@ -158,7 +159,7 @@ You could also have a default stop loss when you are in the red with your buy (b
 For example, your default stop loss is -10%, but once you have more than 0% profit (example 0.1%) a different trailing stoploss will be used.
 
 !!! Note
-    If you want the stoploss to only be changed when you break even of making a profit (what most users want) please refer to next section with [offset enabled](#Trailing-stop-loss-only-once-the-trade-has-reached-a-certain-offset).
+    If you want the stoploss to only be changed when you break even of making a profit (what most users want) please refer to next section with [offset enabled](#trailing-stop-loss-only-once-the-trade-has-reached-a-certain-offset).
 
 Both values require `trailing_stop` to be set to true and `trailing_stop_positive` with a value.
 
@@ -240,7 +241,7 @@ When using leverage, the same principle is applied - with stoploss defining the
 
 Therefore, a stoploss of 10% on a 10x trade would trigger on a 1% price move.
 If your stake amount (own capital) was 100$ - this trade would be 1000$ at 10x (after leverage).
-If price moves 1% - you've lost 10$ of your own capital - therfore stoploss will trigger in this case.
+If price moves 1% - you've lost 10$ of your own capital - therefore stoploss will trigger in this case.
 
 Make sure to be aware of this, and avoid using too tight stoploss (at 10x leverage, 10% risk may be too little to allow the trade to "breath" a little).
 

docs/strategy-advanced.md

@@ -209,7 +209,7 @@ def custom_exit(self, pair: str, trade: Trade, current_time: datetime, current_r
 
 ## Exit tag
 
-Similar to [Buy Tagging](#buy-tag), you can also specify a sell tag.
+Similar to [Entry Tagging](#enter-tag), you can also specify an exit tag.
 
 ``` python
 def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
@@ -326,4 +326,4 @@ for val in self.buy_ema_short.range:
 dataframe = pd.concat(frames, axis=1)
 ```
 
-Freqtrade does however also counter this by running `dataframe.copy()` on the dataframe right after the `populate_indicators()` method - so performance implications of this should be low to non-existant.
+Freqtrade does however also counter this by running `dataframe.copy()` on the dataframe right after the `populate_indicators()` method - so performance implications of this should be low to non-existent.

docs/strategy-callbacks.md

@@ -24,6 +24,8 @@ Currently available callbacks:
 !!! Tip "Callback calling sequence"
     You can find the callback calling sequence in [bot-basics](bot-basics.md#bot-execution-logic)
 
+--8<-- "includes/strategy-imports.md"
+
 ## Bot start
 
 A simple callback which is called once when the strategy is loaded.
@@ -41,10 +43,10 @@ class AwesomeStrategy(IStrategy):
         Called only once after bot instantiation.
         :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
         """
-        if self.config['runmode'].value in ('live', 'dry_run'):
+        if self.config["runmode"].value in ("live", "dry_run"):
             # Assign this to the class by using self.*
             # can then be used by populate_* methods
-            self.custom_remote_data = requests.get('https://some_remote_source.example.com')
+            self.custom_remote_data = requests.get("https://some_remote_source.example.com")
 
 ```
 
@@ -57,6 +59,7 @@ seconds, unless configured differently) or once per candle in backtest/hyperopt
 This can be used to perform calculations which are pair independent (apply to all pairs), loading of external data, etc.
 
 ``` python
+# Default imports
 import requests
 
 class AwesomeStrategy(IStrategy):
@@ -71,10 +74,10 @@ class AwesomeStrategy(IStrategy):
         :param current_time: datetime object, containing the current datetime
         :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
         """
-        if self.config['runmode'].value in ('live', 'dry_run'):
+        if self.config["runmode"].value in ("live", "dry_run"):
             # Assign this to the class by using self.*
             # can then be used by populate_* methods
-            self.remote_data = requests.get('https://some_remote_source.example.com')
+            self.remote_data = requests.get("https://some_remote_source.example.com")
 
 ```
 
@@ -83,6 +86,8 @@ class AwesomeStrategy(IStrategy):
 Called before entering a trade, makes it possible to manage your position size when placing a new trade.
 
 ```python
+# Default imports
+
 class AwesomeStrategy(IStrategy):
     def custom_stake_amount(self, pair: str, current_time: datetime, current_rate: float,
                             proposed_stake: float, min_stake: Optional[float], max_stake: float,
@@ -92,13 +97,13 @@ class AwesomeStrategy(IStrategy):
         dataframe, _ = self.dp.get_analyzed_dataframe(pair=pair, timeframe=self.timeframe)
         current_candle = dataframe.iloc[-1].squeeze()
 
-        if current_candle['fastk_rsi_1h'] > current_candle['fastd_rsi_1h']:
-            if self.config['stake_amount'] == 'unlimited':
+        if current_candle["fastk_rsi_1h"] > current_candle["fastd_rsi_1h"]:
+            if self.config["stake_amount"] == "unlimited":
                 # Use entire available wallet during favorable conditions when in compounding mode.
                 return max_stake
             else:
                 # Compound profits during favorable conditions instead of using a static stake.
-                return self.wallets.get_total_stake_amount() / self.config['max_open_trades']
+                return self.wallets.get_total_stake_amount() / self.config["max_open_trades"]
 
         # Use default stake amount.
         return proposed_stake
@@ -129,25 +134,27 @@ Using `custom_exit()` signals in place of stoploss though *is not recommended*.
 An example of how we can use different indicators depending on the current profit and also exit trades that were open longer than one day:
 
 ``` python
+# Default imports
+
 class AwesomeStrategy(IStrategy):
-    def custom_exit(self, pair: str, trade: 'Trade', current_time: 'datetime', current_rate: float,
+    def custom_exit(self, pair: str, trade: Trade, current_time: datetime, current_rate: float,
                     current_profit: float, **kwargs):
         dataframe, _ = self.dp.get_analyzed_dataframe(pair, self.timeframe)
         last_candle = dataframe.iloc[-1].squeeze()
 
         # Above 20% profit, sell when rsi < 80
         if current_profit > 0.2:
-            if last_candle['rsi'] < 80:
-                return 'rsi_below_80'
+            if last_candle["rsi"] < 80:
+                return "rsi_below_80"
 
         # Between 2% and 10%, sell if EMA-long above EMA-short
         if 0.02 < current_profit < 0.1:
-            if last_candle['emalong'] > last_candle['emashort']:
-                return 'ema_long_below_80'
+            if last_candle["emalong"] > last_candle["emashort"]:
+                return "ema_long_below_80"
 
         # Sell any positions at a loss if they are held for more than one day.
         if current_profit < 0.0 and (current_time - trade.open_date_utc).days >= 1:
-            return 'unclog'
+            return "unclog"
 ```
 
 See [Dataframe access](strategy-advanced.md#dataframe-access) for more information about dataframe use in strategy callbacks.
@@ -165,9 +172,10 @@ E.g. If the `current_rate` is 200 USD, then returning `0.02` will set the stoplo
 During backtesting, `current_rate` (and `current_profit`) are provided against the candle's high (or low for short trades) - while the resulting stoploss is evaluated against the candle's low (or high for short trades).
 
 The absolute value of the return value is used (the sign is ignored), so returning `0.05` or `-0.05` have the same result, a stoploss 5% below the current price.
-Returning None will be interpreted as "no desire to change", and is the only safe way to return when you'd like to not modify the stoploss.
+Returning `None` will be interpreted as "no desire to change", and is the only safe way to return when you'd like to not modify the stoploss.
+`NaN` and `inf` values are considered invalid and will be ignored (identical to `None`).
 
-Stoploss on exchange works similar to `trailing_stop`, and the stoploss on exchange is updated as configured in `stoploss_on_exchange_interval` ([More details about stoploss on exchange](stoploss.md#stop-loss-on-exchange-freqtrade)).
+Stoploss on exchange works similar to `trailing_stop`, and the stoploss on exchange is updated as configured in `stoploss_on_exchange_interval` ([More details about stoploss on exchange](stoploss.md#stop-loss-on-exchangefreqtrade)).
 
 !!! Note "Use of dates"
     All time-based calculations should be done based on `current_time` - using `datetime.now()` or `datetime.utcnow()` is discouraged, as this will break backtesting support.
@@ -194,9 +202,7 @@ Of course, many more things are possible, and all examples can be combined at wi
 To simulate a regular trailing stoploss of 4% (trailing 4% behind the maximum reached price) you would use the following very simple method:
 
 ``` python
-# additional imports required
-from datetime import datetime
-from freqtrade.persistence import Trade
+# Default imports
 
 class AwesomeStrategy(IStrategy):
 
@@ -204,7 +210,7 @@ class AwesomeStrategy(IStrategy):
 
     use_custom_stoploss = True
 
-    def custom_stoploss(self, pair: str, trade: 'Trade', current_time: datetime,
+    def custom_stoploss(self, pair: str, trade: Trade, current_time: datetime,
                         current_rate: float, current_profit: float, after_fill: bool, 
                         **kwargs) -> Optional[float]:
         """
@@ -234,8 +240,7 @@ class AwesomeStrategy(IStrategy):
 Use the initial stoploss for the first 60 minutes, after this change to 10% trailing stoploss, and after 2 hours (120 minutes) we use a 5% trailing stoploss.
 
 ``` python
-from datetime import datetime, timedelta
-from freqtrade.persistence import Trade
+# Default imports
 
 class AwesomeStrategy(IStrategy):
 
@@ -243,7 +248,7 @@ class AwesomeStrategy(IStrategy):
 
     use_custom_stoploss = True
 
-    def custom_stoploss(self, pair: str, trade: 'Trade', current_time: datetime,
+    def custom_stoploss(self, pair: str, trade: Trade, current_time: datetime,
                         current_rate: float, current_profit: float, after_fill: bool, 
                         **kwargs) -> Optional[float]:
 
@@ -261,8 +266,7 @@ Use the initial stoploss for the first 60 minutes, after this change to 10% trai
 If an additional order fills, set stoploss to -10% below the new `open_rate` ([Averaged across all entries](#position-adjust-calculations)).
 
 ``` python
-from datetime import datetime, timedelta
-from freqtrade.persistence import Trade
+# Default imports
 
 class AwesomeStrategy(IStrategy):
 
@@ -270,7 +274,7 @@ class AwesomeStrategy(IStrategy):
 
     use_custom_stoploss = True
 
-    def custom_stoploss(self, pair: str, trade: 'Trade', current_time: datetime,
+    def custom_stoploss(self, pair: str, trade: Trade, current_time: datetime,
                         current_rate: float, current_profit: float, after_fill: bool, 
                         **kwargs) -> Optional[float]:
 
@@ -291,8 +295,7 @@ Use a different stoploss depending on the pair.
 In this example, we'll trail the highest price with 10% trailing stoploss for `ETH/BTC` and `XRP/BTC`, with 5% trailing stoploss for `LTC/BTC` and with 15% for all other pairs.
 
 ``` python
-from datetime import datetime
-from freqtrade.persistence import Trade
+# Default imports
 
 class AwesomeStrategy(IStrategy):
 
@@ -300,13 +303,13 @@ class AwesomeStrategy(IStrategy):
 
     use_custom_stoploss = True
 
-    def custom_stoploss(self, pair: str, trade: 'Trade', current_time: datetime,
+    def custom_stoploss(self, pair: str, trade: Trade, current_time: datetime,
                         current_rate: float, current_profit: float, after_fill: bool,
                         **kwargs) -> Optional[float]:
 
-        if pair in ('ETH/BTC', 'XRP/BTC'):
+        if pair in ("ETH/BTC", "XRP/BTC"):
             return -0.10
-        elif pair in ('LTC/BTC'):
+        elif pair in ("LTC/BTC"):
             return -0.05
         return -0.15
 ```
@@ -318,8 +321,7 @@ Use the initial stoploss until the profit is above 4%, then use a trailing stopl
 Please note that the stoploss can only increase, values lower than the current stoploss are ignored.
 
 ``` python
-from datetime import datetime, timedelta
-from freqtrade.persistence import Trade
+# Default imports
 
 class AwesomeStrategy(IStrategy):
 
@@ -327,12 +329,12 @@ class AwesomeStrategy(IStrategy):
 
     use_custom_stoploss = True
 
-    def custom_stoploss(self, pair: str, trade: 'Trade', current_time: datetime,
+    def custom_stoploss(self, pair: str, trade: Trade, current_time: datetime,
                         current_rate: float, current_profit: float, after_fill: bool,
                         **kwargs) -> Optional[float]:
 
         if current_profit < 0.04:
-            return -1 # return a value bigger than the initial stoploss to keep using the initial stoploss
+            return None # return None to keep using the initial stoploss
 
         # After reaching the desired offset, allow the stoploss to trail by half the profit
         desired_stoploss = current_profit / 2
@@ -351,9 +353,7 @@ Instead of continuously trailing behind the current price, this example sets fix
 * Once profit is > 40% - set stoploss to 25% above open price.
 
 ``` python
-from datetime import datetime
-from freqtrade.persistence import Trade
-from freqtrade.strategy import stoploss_from_open
+# Default imports
 
 class AwesomeStrategy(IStrategy):
 
@@ -361,7 +361,7 @@ class AwesomeStrategy(IStrategy):
 
     use_custom_stoploss = True
 
-    def custom_stoploss(self, pair: str, trade: 'Trade', current_time: datetime,
+    def custom_stoploss(self, pair: str, trade: Trade, current_time: datetime,
                         current_rate: float, current_profit: float, after_fill: bool,
                         **kwargs) -> Optional[float]:
 
@@ -382,15 +382,17 @@ class AwesomeStrategy(IStrategy):
 Absolute stoploss value may be derived from indicators stored in dataframe. Example uses parabolic SAR below the price as stoploss.
 
 ``` python
+# Default imports
+
 class AwesomeStrategy(IStrategy):
 
     def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
         # <...>
-        dataframe['sar'] = ta.SAR(dataframe)
+        dataframe["sar"] = ta.SAR(dataframe)
 
     use_custom_stoploss = True
 
-    def custom_stoploss(self, pair: str, trade: 'Trade', current_time: datetime,
+    def custom_stoploss(self, pair: str, trade: Trade, current_time: datetime,
                         current_rate: float, current_profit: float, after_fill: bool,
                         **kwargs) -> Optional[float]:
 
@@ -398,7 +400,7 @@ class AwesomeStrategy(IStrategy):
         last_candle = dataframe.iloc[-1].squeeze()
 
         # Use parabolic sar as absolute stoploss price
-        stoploss_price = last_candle['sar']
+        stoploss_price = last_candle["sar"]
 
         # Convert absolute price to percentage relative to current_rate
         if stoploss_price < current_rate:
@@ -427,10 +429,7 @@ Stoploss values returned from `custom_stoploss()` must specify a percentage rela
 
 
     ``` python
-
-    from datetime import datetime
-    from freqtrade.persistence import Trade
-    from freqtrade.strategy import IStrategy, stoploss_from_open
+    # Default imports
 
     class AwesomeStrategy(IStrategy):
 
@@ -438,7 +437,7 @@ Stoploss values returned from `custom_stoploss()` must specify a percentage rela
 
         use_custom_stoploss = True
 
-        def custom_stoploss(self, pair: str, trade: 'Trade', current_time: datetime,
+        def custom_stoploss(self, pair: str, trade: Trade, current_time: datetime,
                             current_rate: float, current_profit: float, after_fill: bool,
                             **kwargs) -> Optional[float]:
 
@@ -450,7 +449,7 @@ Stoploss values returned from `custom_stoploss()` must specify a percentage rela
 
     ```
 
-    Full examples can be found in the [Custom stoploss](strategy-advanced.md#custom-stoploss) section of the Documentation.
+    Full examples can be found in the [Custom stoploss](strategy-callbacks.md#custom-stoploss) section of the Documentation.
 
 !!! Note
     Providing invalid input to `stoploss_from_open()` may produce "CustomStoploss function did not return valid stoploss" warnings.
@@ -467,37 +466,34 @@ The helper function `stoploss_from_absolute()` can be used to convert from an ab
 
 ??? Example "Returning a stoploss using absolute price from the custom stoploss function"
 
-    If we want to trail a stop price at 2xATR below current price we can call `stoploss_from_absolute(current_rate + (side * candle['atr'] * 2), current_rate, is_short=trade.is_short, leverage=trade.leverage)`.
+    If we want to trail a stop price at 2xATR below current price we can call `stoploss_from_absolute(current_rate + (side * candle["atr"] * 2), current_rate=current_rate, is_short=trade.is_short, leverage=trade.leverage)`.
     For futures, we need to adjust the direction (up or down), as well as adjust for leverage, since the [`custom_stoploss`](strategy-callbacks.md#custom-stoploss) callback  returns the ["risk for this trade"](stoploss.md#stoploss-and-leverage) - not the relative price movement.
 
     ``` python
-
-    from datetime import datetime
-    from freqtrade.persistence import Trade
-    from freqtrade.strategy import IStrategy, stoploss_from_absolute, timeframe_to_prev_date
+    # Default imports
 
     class AwesomeStrategy(IStrategy):
 
         use_custom_stoploss = True
 
-        def populate_indicators_1h(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
-            dataframe['atr'] = ta.ATR(dataframe, timeperiod=14)
+        def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+            dataframe["atr"] = ta.ATR(dataframe, timeperiod=14)
             return dataframe
 
-        def custom_stoploss(self, pair: str, trade: 'Trade', current_time: datetime,
+        def custom_stoploss(self, pair: str, trade: Trade, current_time: datetime,
                             current_rate: float, current_profit: float, after_fill: bool,
                             **kwargs) -> Optional[float]:
             dataframe, _ = self.dp.get_analyzed_dataframe(pair, self.timeframe)
             trade_date = timeframe_to_prev_date(self.timeframe, trade.open_date_utc)
             candle = dataframe.iloc[-1].squeeze()
             side = 1 if trade.is_short else -1
-            return stoploss_from_absolute(current_rate + (side * candle['atr'] * 2), 
-                                          current_rate, is_short=trade.is_short,
+            return stoploss_from_absolute(current_rate + (side * candle["atr"] * 2), 
+                                          current_rate=current_rate, 
+                                          is_short=trade.is_short,
                                           leverage=trade.leverage)
 
     ```
 
-
 ---
 
 ## Custom order price rules
@@ -517,19 +513,18 @@ Each of these methods are called right before placing an order on the exchange.
 ### Custom order entry and exit price example
 
 ``` python
-from datetime import datetime, timedelta, timezone
-from freqtrade.persistence import Trade
+# Default imports
 
 class AwesomeStrategy(IStrategy):
 
     # ... populate_* methods
 
-    def custom_entry_price(self, pair: str, trade: Optional['Trade'], current_time: datetime, proposed_rate: float,
+    def custom_entry_price(self, pair: str, trade: Optional[Trade], current_time: datetime, proposed_rate: float,
                            entry_tag: Optional[str], side: str, **kwargs) -> float:
 
         dataframe, last_updated = self.dp.get_analyzed_dataframe(pair=pair,
                                                                 timeframe=self.timeframe)
-        new_entryprice = dataframe['bollinger_10_lowerband'].iat[-1]
+        new_entryprice = dataframe["bollinger_10_lowerband"].iat[-1]
 
         return new_entryprice
 
@@ -539,7 +534,7 @@ class AwesomeStrategy(IStrategy):
 
         dataframe, last_updated = self.dp.get_analyzed_dataframe(pair=pair,
                                                                 timeframe=self.timeframe)
-        new_exitprice = dataframe['bollinger_10_upperband'].iat[-1]
+        new_exitprice = dataframe["bollinger_10_upperband"].iat[-1]
 
         return new_exitprice
 
@@ -576,8 +571,7 @@ It applies a tight timeout for higher priced assets, while allowing more time to
 The function must return either `True` (cancel order) or `False` (keep order alive).
 
 ``` python
-from datetime import datetime, timedelta
-from freqtrade.persistence import Trade, Order
+    # Default imports
 
 class AwesomeStrategy(IStrategy):
 
@@ -585,11 +579,11 @@ class AwesomeStrategy(IStrategy):
 
     # Set unfilledtimeout to 25 hours, since the maximum timeout from below is 24 hours.
     unfilledtimeout = {
-        'entry': 60 * 25,
-        'exit': 60 * 25
+        "entry": 60 * 25,
+        "exit": 60 * 25
     }
 
-    def check_entry_timeout(self, pair: str, trade: 'Trade', order: 'Order',
+    def check_entry_timeout(self, pair: str, trade: Trade, order: Order,
                             current_time: datetime, **kwargs) -> bool:
         if trade.open_rate > 100 and trade.open_date_utc < current_time - timedelta(minutes=5):
             return True
@@ -600,7 +594,7 @@ class AwesomeStrategy(IStrategy):
         return False
 
 
-    def check_exit_timeout(self, pair: str, trade: Trade, order: 'Order',
+    def check_exit_timeout(self, pair: str, trade: Trade, order: Order,
                            current_time: datetime, **kwargs) -> bool:
         if trade.open_rate > 100 and trade.open_date_utc < current_time - timedelta(minutes=5):
             return True
@@ -617,8 +611,7 @@ class AwesomeStrategy(IStrategy):
 ### Custom order timeout example (using additional data)
 
 ``` python
-from datetime import datetime
-from freqtrade.persistence import Trade, Order
+    # Default imports
 
 class AwesomeStrategy(IStrategy):
 
@@ -626,24 +619,24 @@ class AwesomeStrategy(IStrategy):
 
     # Set unfilledtimeout to 25 hours, since the maximum timeout from below is 24 hours.
     unfilledtimeout = {
-        'entry': 60 * 25,
-        'exit': 60 * 25
+        "entry": 60 * 25,
+        "exit": 60 * 25
     }
 
-    def check_entry_timeout(self, pair: str, trade: 'Trade', order: 'Order',
+    def check_entry_timeout(self, pair: str, trade: Trade, order: Order,
                             current_time: datetime, **kwargs) -> bool:
         ob = self.dp.orderbook(pair, 1)
-        current_price = ob['bids'][0][0]
+        current_price = ob["bids"][0][0]
         # Cancel buy order if price is more than 2% above the order.
         if current_price > order.price * 1.02:
             return True
         return False
 
 
-    def check_exit_timeout(self, pair: str, trade: 'Trade', order: 'Order',
+    def check_exit_timeout(self, pair: str, trade: Trade, order: Order,
                            current_time: datetime, **kwargs) -> bool:
         ob = self.dp.orderbook(pair, 1)
-        current_price = ob['asks'][0][0]
+        current_price = ob["asks"][0][0]
         # Cancel sell order if price is more than 2% below the order.
         if current_price < order.price * 0.98:
             return True
@@ -662,6 +655,8 @@ This are the last methods that will be called before an order is placed.
 `confirm_trade_entry()` can be used to abort a trade entry at the latest second (maybe because the price is not what we expect).
 
 ``` python
+# Default imports
+
 class AwesomeStrategy(IStrategy):
 
     # ... populate_* methods
@@ -686,7 +681,7 @@ class AwesomeStrategy(IStrategy):
         :param time_in_force: Time in force. Defaults to GTC (Good-til-cancelled).
         :param current_time: datetime object, containing the current datetime
         :param entry_tag: Optional entry_tag (buy_tag) if provided with the buy signal.
-        :param side: 'long' or 'short' - indicating the direction of the proposed trade
+        :param side: "long" or "short" - indicating the direction of the proposed trade
         :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
         :return bool: When True is returned, then the buy-order is placed on the exchange.
             False aborts the process
@@ -708,8 +703,7 @@ The exit-reasons (if applicable) will be in the following sequence:
 * `trailing_stop_loss`
 
 ``` python
-from freqtrade.persistence import Trade
-
+# Default imports
 
 class AwesomeStrategy(IStrategy):
 
@@ -735,14 +729,14 @@ class AwesomeStrategy(IStrategy):
                      or current rate for market orders.
         :param time_in_force: Time in force. Defaults to GTC (Good-til-cancelled).
         :param exit_reason: Exit reason.
-            Can be any of ['roi', 'stop_loss', 'stoploss_on_exchange', 'trailing_stop_loss',
-                           'exit_signal', 'force_exit', 'emergency_exit']
+            Can be any of ["roi", "stop_loss", "stoploss_on_exchange", "trailing_stop_loss",
+                           "exit_signal", "force_exit", "emergency_exit"]
         :param current_time: datetime object, containing the current datetime
         :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
         :return bool: When True, then the exit-order is placed on the exchange.
             False aborts the process
         """
-        if exit_reason == 'force_exit' and trade.calc_profit_ratio(rate) < 0:
+        if exit_reason == "force_exit" and trade.calc_profit_ratio(rate) < 0:
             # Reject force-sells with negative profit
             # This is just a sample, please adjust to your needs
             # (this does not necessarily make sense, assuming you know when you're force-selling)
@@ -768,7 +762,7 @@ This callback is **not** called when there is an open order (either buy or sell)
 `adjust_trade_position()` is called very frequently for the duration of a trade, so you must keep your implementation as performant as possible.
 
 Position adjustments will always be applied in the direction of the trade, so a positive value will always increase your position (negative values will decrease your position), no matter if it's a long or short trade.
-Adjustment orders can be assigned with a tag by returning a 2 element Tuple, with the first element being the adjustment amount, and the 2nd element the tag (e.g. `return 250, 'increase_favorable_conditions'`).
+Adjustment orders can be assigned with a tag by returning a 2 element Tuple, with the first element being the adjustment amount, and the 2nd element the tag (e.g. `return 250, "increase_favorable_conditions"`).
 
 Modifications to leverage are not possible, and the stake-amount returned is assumed to be before applying leverage.
 
@@ -790,7 +784,7 @@ Returning a value more than the above (so remaining stake_amount would become ne
 !!! Note "About stake size"
     Using fixed stake size means it will be the amount used for the first order, just like without position adjustment.
     If you wish to buy additional orders with DCA, then make sure to leave enough funds in the wallet for that.
-    Using 'unlimited' stake amount with DCA orders requires you to also implement the `custom_stake_amount()` callback to avoid allocating all funds to the initial order.
+    Using `"unlimited"` stake amount with DCA orders requires you to also implement the `custom_stake_amount()` callback to avoid allocating all funds to the initial order.
 
 !!! Warning "Stoploss calculation"
     Stoploss is still calculated from the initial opening price, not averaged price.
@@ -808,8 +802,7 @@ Returning a value more than the above (so remaining stake_amount would become ne
     Trades with long duration and 10s or even 100ds of position adjustments are therefore not recommended, and should be closed at regular intervals to not affect performance.
 
 ``` python
-from freqtrade.persistence import Trade
-
+# Default imports
 
 class DigDeeperStrategy(IStrategy):
 
@@ -872,7 +865,7 @@ class DigDeeperStrategy(IStrategy):
 
         if current_profit > 0.05 and trade.nr_of_successful_exits == 0:
             # Take half of the profit at +5%
-            return -(trade.stake_amount / 2), 'half_profit_5%'
+            return -(trade.stake_amount / 2), "half_profit_5%"
 
         if current_profit > -0.05:
             return None
@@ -882,7 +875,7 @@ class DigDeeperStrategy(IStrategy):
         # Only buy when not actively falling price.
         last_candle = dataframe.iloc[-1].squeeze()
         previous_candle = dataframe.iloc[-2].squeeze()
-        if last_candle['close'] < previous_candle['close']:
+        if last_candle["close"] < previous_candle["close"]:
             return None
 
         filled_entries = trade.select_filled_orders(trade.entry_side)
@@ -900,7 +893,7 @@ class DigDeeperStrategy(IStrategy):
             stake_amount = filled_entries[0].stake_amount
             # This then calculates current safety order size
             stake_amount = stake_amount * (1 + (count_of_entries * 0.25))
-            return stake_amount, '1/3rd_increase'
+            return stake_amount, "1/3rd_increase"
         except Exception as exception:
             return None
 
@@ -947,8 +940,7 @@ If the cancellation of the original order fails, then the order will not be repl
     Entry Orders that are cancelled via the above methods will not have this callback called. Be sure to update timeout values to match your expectations.
 
 ```python
-from freqtrade.persistence import Trade
-from datetime import timedelta
+# Default imports
 
 class AwesomeStrategy(IStrategy):
 
@@ -973,13 +965,18 @@ class AwesomeStrategy(IStrategy):
         :param proposed_rate: Rate, calculated based on pricing settings in entry_pricing.
         :param current_order_rate: Rate of the existing order in place.
         :param entry_tag: Optional entry_tag (buy_tag) if provided with the buy signal.
-        :param side: 'long' or 'short' - indicating the direction of the proposed trade
+        :param side: "long" or "short" - indicating the direction of the proposed trade
         :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
         :return float: New entry price value if provided
 
         """
         # Limit orders to use and follow SMA200 as price target for the first 10 minutes since entry trigger for BTC/USDT pair.
-        if pair == 'BTC/USDT' and entry_tag == 'long_sma200' and side == 'long' and (current_time - timedelta(minutes=10)) > trade.open_date_utc:
+        if (
+            pair == "BTC/USDT" 
+            and entry_tag == "long_sma200" 
+            and side == "long" 
+            and (current_time - timedelta(minutes=10)) > trade.open_date_utc
+        ):
             # just cancel the order if it has been filled more than half of the amount
             if order.filled > order.remaining:
                 return None
@@ -987,7 +984,7 @@ class AwesomeStrategy(IStrategy):
                 dataframe, _ = self.dp.get_analyzed_dataframe(pair=pair, timeframe=self.timeframe)
                 current_candle = dataframe.iloc[-1].squeeze()
                 # desired price
-                return current_candle['sma_200']
+                return current_candle["sma_200"]
         # default: maintain existing order
         return current_order_rate
 ```
@@ -1002,6 +999,8 @@ Values that are above `max_leverage` will be adjusted to `max_leverage`.
 For markets / exchanges that don't support leverage, this method is ignored.
 
 ``` python
+# Default imports
+
 class AwesomeStrategy(IStrategy):
     def leverage(self, pair: str, current_time: datetime, current_rate: float,
                  proposed_leverage: float, max_leverage: float, entry_tag: Optional[str], side: str,
@@ -1015,7 +1014,7 @@ class AwesomeStrategy(IStrategy):
         :param proposed_leverage: A leverage proposed by the bot.
         :param max_leverage: Max leverage allowed on this pair
         :param entry_tag: Optional entry_tag (buy_tag) if provided with the buy signal.
-        :param side: 'long' or 'short' - indicating the direction of the proposed trade
+        :param side: "long" or "short" - indicating the direction of the proposed trade
         :return: A leverage amount, which is between 1.0 and max_leverage.
         """
         return 1.0
@@ -1032,6 +1031,8 @@ It will be called independent of the order type (entry, exit, stoploss or positi
 Assuming that your strategy needs to store the high value of the candle at trade entry, this is possible with this callback as the following example show.
 
 ``` python
+# Default imports
+
 class AwesomeStrategy(IStrategy):
     def order_filled(self, pair: str, trade: Trade, order: Order, current_time: datetime, **kwargs) -> None:
         """
@@ -1048,7 +1049,7 @@ class AwesomeStrategy(IStrategy):
         last_candle = dataframe.iloc[-1].squeeze()
         
         if (trade.nr_of_successful_entries == 1) and (order.ft_order_side == trade.entry_side):
-            trade.set_custom_data(key='entry_candle_high', value=last_candle['high'])
+            trade.set_custom_data(key="entry_candle_high", value=last_candle["high"])
 
         return None
 

docs/strategy-customization.md

@@ -158,7 +158,7 @@ Out of the box, freqtrade installs the following technical libraries:
 
 - [ta-lib](https://ta-lib.github.io/ta-lib-python/)
 - [pandas-ta](https://twopirllc.github.io/pandas-ta/)
-- [technical](https://github.com/freqtrade/technical/)
+- [technical](https://technical.freqtrade.io)
 
 Additional technical libraries can be installed as necessary, or custom indicators may be written / invented by the strategy author.
 
@@ -405,7 +405,9 @@ The metadata-dict (available for `populate_entry_trend`, `populate_exit_trend`,
 Currently this is `pair`, which can be accessed using `metadata['pair']` - and will return a pair in the format `XRP/BTC`.
 
 The Metadata-dict should not be modified and does not persist information across multiple calls.
-Instead, have a look at the [Storing information](strategy-advanced.md#Storing-information) section.
+Instead, have a look at the [Storing information](strategy-advanced.md#storing-information-persistent) section.
+
+--8<-- "includes/strategy-imports.md"
 
 ## Strategy file loading
 
@@ -551,8 +553,8 @@ for more information.
     
         # Define BTC/STAKE informative pair. A custom formatter may be specified for formatting
         # column names. A callable `fmt(**kwargs) -> str` may be specified, to implement custom
-        # formatting. Available in populate_indicators and other methods as 'rsi_upper'.
-        @informative('1h', 'BTC/{stake}', '{column}')
+        # formatting. Available in populate_indicators and other methods as 'rsi_upper_1h'.
+        @informative('1h', 'BTC/{stake}', '{column}_{timeframe}')
         def populate_indicators_btc_1h_2(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
             dataframe['rsi_upper'] = ta.RSI(dataframe, timeperiod=14)
             return dataframe
@@ -715,6 +717,7 @@ This is where calling `self.dp.current_whitelist()` comes in handy.
 
 ??? Note "Plotting with current_whitelist"
     Current whitelist is not supported for `plot-dataframe`, as this command is usually used by providing an explicit pairlist - and would therefore make the return values of this method misleading.
+    It's also not supported for freqUI visualization in [webserver mode](utils.md#webserver-mode) - as the configuration for webserver mode doesn't require a pairlist to be set.
 
 ### *get_pair_dataframe(pair, timeframe)*
 
@@ -776,7 +779,7 @@ The orderbook structure is aligned with the order structure from [ccxt](https://
 Therefore, using `ob['bids'][0][0]` as demonstrated above will result in using the best bid price. `ob['bids'][0][1]` would look at the amount at this orderbook position.
 
 !!! Warning "Warning about backtesting"
-    The order book 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 uptodate values.
+    The order book 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.
 
 ### *ticker(pair)*
 

docs/strategy_analysis_example.md

@@ -13,19 +13,22 @@ Please follow the [documentation](https://www.freqtrade.io/en/stable/data-downlo
 import os
 from pathlib import Path
 
+
 # Change directory
 # Modify this cell to insure that the output shows the correct path.
 # Define all paths relative to the project root shown in the cell output
 project_root = "somedir/freqtrade"
-i=0
+i = 0
 try:
     os.chdir(project_root)
-    assert Path('LICENSE').is_file()
-except:
-    while i<4 and (not Path('LICENSE').is_file()):
-        os.chdir(Path(Path.cwd(), '../'))
-        i+=1
-    project_root = Path.cwd()
+    if not Path("LICENSE").is_file():
+        i = 0
+        while i < 4 and (not Path("LICENSE").is_file()):
+            os.chdir(Path(Path.cwd(), "../"))
+            i += 1
+        project_root = Path.cwd()
+except FileNotFoundError:
+    print("Please define the project root relative to the current directory")
 print(Path.cwd())
 ```
 
@@ -35,6 +38,7 @@ print(Path.cwd())
 ```python
 from freqtrade.configuration import Configuration
 
+
 # Customize these according to your needs.
 
 # Initialize empty configuration object
@@ -58,12 +62,14 @@ pair = "BTC/USDT"
 from freqtrade.data.history import load_pair_history
 from freqtrade.enums import CandleType
 
-candles = load_pair_history(datadir=data_location,
-                            timeframe=config["timeframe"],
-                            pair=pair,
-                            data_format = "json",  # Make sure to update this to your data
-                            candle_type=CandleType.SPOT,
-                            )
+
+candles = load_pair_history(
+    datadir=data_location,
+    timeframe=config["timeframe"],
+    pair=pair,
+    data_format="json",  # Make sure to update this to your data
+    candle_type=CandleType.SPOT,
+)
 
 # Confirm success
 print(f"Loaded {len(candles)} rows of data for {pair} from {data_location}")
@@ -76,14 +82,16 @@ candles.head()
 
 ```python
 # Load strategy using values set above
-from freqtrade.resolvers import StrategyResolver
 from freqtrade.data.dataprovider import DataProvider
+from freqtrade.resolvers import StrategyResolver
+
+
 strategy = StrategyResolver.load_strategy(config)
 strategy.dp = DataProvider(config, None, None)
 strategy.ft_bot_start()
 
 # Generate buy/sell signals using strategy
-df = strategy.analyze_ticker(candles, {'pair': pair})
+df = strategy.analyze_ticker(candles, {"pair": pair})
 df.tail()
 ```
 
@@ -102,7 +110,7 @@ df.tail()
 ```python
 # Report results
 print(f"Generated {df['enter_long'].sum()} entry signals")
-data = df.set_index('date', drop=False)
+data = df.set_index("date", drop=False)
 data.tail()
 ```
 
@@ -119,10 +127,13 @@ Analyze a trades dataframe (also used below for plotting)
 ```python
 from freqtrade.data.btanalysis import load_backtest_data, load_backtest_stats
 
+
 # if backtest_dir points to a directory, it'll automatically load the last backtest file.
 backtest_dir = config["user_data_dir"] / "backtest_results"
-# backtest_dir can also point to a specific file 
-# backtest_dir = config["user_data_dir"] / "backtest_results/backtest-result-2020-07-01_20-04-22.json"
+# backtest_dir can also point to a specific file
+# backtest_dir = (
+#   config["user_data_dir"] / "backtest_results/backtest-result-2020-07-01_20-04-22.json"
+# )
 ```
 
 
@@ -131,24 +142,24 @@ backtest_dir = config["user_data_dir"] / "backtest_results"
 # This contains all information used to generate the backtest result.
 stats = load_backtest_stats(backtest_dir)
 
-strategy = 'SampleStrategy'
-# All statistics are available per strategy, so if `--strategy-list` was used during backtest, this will be reflected here as well.
+strategy = "SampleStrategy"
+# All statistics are available per strategy, so if `--strategy-list` was used during backtest,
+# this will be reflected here as well.
 # Example usages:
-print(stats['strategy'][strategy]['results_per_pair'])
+print(stats["strategy"][strategy]["results_per_pair"])
 # Get pairlist used for this backtest
-print(stats['strategy'][strategy]['pairlist'])
+print(stats["strategy"][strategy]["pairlist"])
 # Get market change (average change of all pairs from start to end of the backtest period)
-print(stats['strategy'][strategy]['market_change'])
+print(stats["strategy"][strategy]["market_change"])
 # Maximum drawdown ()
-print(stats['strategy'][strategy]['max_drawdown'])
+print(stats["strategy"][strategy]["max_drawdown"])
 # Maximum drawdown start and end
-print(stats['strategy'][strategy]['drawdown_start'])
-print(stats['strategy'][strategy]['drawdown_end'])
+print(stats["strategy"][strategy]["drawdown_start"])
+print(stats["strategy"][strategy]["drawdown_end"])
 
 
 # Get strategy comparison (only relevant if multiple strategies were compared)
-print(stats['strategy_comparison'])
-
+print(stats["strategy_comparison"])
 ```
 
 
@@ -166,24 +177,25 @@ trades.groupby("pair")["exit_reason"].value_counts()
 ```python
 # Plotting equity line (starting with 0 on day 1 and adding daily profit for each backtested day)
 
+import pandas as pd
+import plotly.express as px
+
 from freqtrade.configuration import Configuration
 from freqtrade.data.btanalysis import load_backtest_stats
-import plotly.express as px
-import pandas as pd
+
 
 # strategy = 'SampleStrategy'
 # config = Configuration.from_files(["user_data/config.json"])
 # backtest_dir = config["user_data_dir"] / "backtest_results"
 
 stats = load_backtest_stats(backtest_dir)
-strategy_stats = stats['strategy'][strategy]
+strategy_stats = stats["strategy"][strategy]
 
-df = pd.DataFrame(columns=['dates','equity'], data=strategy_stats['daily_profit'])
-df['equity_daily'] = df['equity'].cumsum()
+df = pd.DataFrame(columns=["dates", "equity"], data=strategy_stats["daily_profit"])
+df["equity_daily"] = df["equity"].cumsum()
 
 fig = px.line(df, x="dates", y="equity_daily")
 fig.show()
-
 ```
 
 ### Load live trading results into a pandas dataframe
@@ -194,6 +206,7 @@ In case you did already some trading and want to analyze your performance
 ```python
 from freqtrade.data.btanalysis import load_trades_from_db
 
+
 # Fetch trades from database
 trades = load_trades_from_db("sqlite:///tradesv3.sqlite")
 
@@ -210,8 +223,9 @@ This can be useful to find the best `max_open_trades` parameter, when used with
 ```python
 from freqtrade.data.btanalysis import analyze_trade_parallelism
 
+
 # Analyze the above
-parallel_trades = analyze_trade_parallelism(trades, '5m')
+parallel_trades = analyze_trade_parallelism(trades, "5m")
 
 parallel_trades.plot()
 ```
@@ -222,23 +236,23 @@ Freqtrade offers interactive plotting capabilities based on plotly.
 
 
 ```python
-from freqtrade.plot.plotting import  generate_candlestick_graph
+from freqtrade.plot.plotting import generate_candlestick_graph
+
+
 # Limit graph period to keep plotly quick and reactive
 
 # Filter trades to one pair
-trades_red = trades.loc[trades['pair'] == pair]
+trades_red = trades.loc[trades["pair"] == pair]
 
-data_red = data['2019-06-01':'2019-06-10']
+data_red = data["2019-06-01":"2019-06-10"]
 # Generate candlestick graph
-graph = generate_candlestick_graph(pair=pair,
-                                   data=data_red,
-                                   trades=trades_red,
-                                   indicators1=['sma20', 'ema50', 'ema55'],
-                                   indicators2=['rsi', 'macd', 'macdsignal', 'macdhist']
-                                  )
-
-
-
+graph = generate_candlestick_graph(
+    pair=pair,
+    data=data_red,
+    trades=trades_red,
+    indicators1=["sma20", "ema50", "ema55"],
+    indicators2=["rsi", "macd", "macdsignal", "macdhist"],
+)
 ```
 
 
@@ -248,7 +262,6 @@ graph = generate_candlestick_graph(pair=pair,
 
 # Render graph in a separate window
 graph.show(renderer="browser")
-
 ```
 
 ## Plot average profit per trade as distribution graph
@@ -257,12 +270,12 @@ graph.show(renderer="browser")
 ```python
 import plotly.figure_factory as ff
 
+
 hist_data = [trades.profit_ratio]
-group_labels = ['profit_ratio']  # name of the dataset
+group_labels = ["profit_ratio"]  # name of the dataset
 
 fig = ff.create_distplot(hist_data, group_labels, bin_size=0.01)
 fig.show()
-
 ```
 
 Feel free to submit an issue or Pull Request enhancing this document if you would like to share ideas on how to best analyze the data.

docs/stylesheets/ft.extra.css

@@ -11,3 +11,7 @@
 .rst-versions .rst-other-versions {
     color: white;
 }
+
+.md-version__list {
+    font-weight: 500 !important;
+}

docs/telegram-usage.md

@@ -53,7 +53,7 @@ You can use bots in telegram groups by just adding them to the group. You can fi
 }
 ```
 
-For the Freqtrade configuration, you can then use the the full value (including `-` if it's there) as string:
+For the Freqtrade configuration, you can then use the full value (including `-` if it's there) as string:
 
 ```json
    "chat_id": "-1001332619709"

docs/trade-object.md

@@ -13,28 +13,28 @@ The following attributes / properties are available for each individual trade -
 
 |  Attribute | DataType | Description |
 |------------|-------------|-------------|
-`pair`| string | Pair of this trade
-`is_open`| boolean | Is the trade currently open, or has it been concluded
-`open_rate`| float | Rate this trade was entered at (Avg. entry rate in case of trade-adjustments)
-`close_rate`| float | Close rate - only set when is_open = False
-`stake_amount`| float | Amount in Stake (or Quote) currency.
-`amount`| float | Amount in Asset / Base currency that is currently owned.
-`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**
-`close_date_utc`| datetime | Timestamp when trade was closed - in UTC
-`close_profit`| float | Relative profit at the time of trade closure. `0.01` == 1%
-`close_profit_abs`| float | Absolute profit (in stake currency) at the time of trade closure.
-`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
-`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
-`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.
-`nr_of_successful_entries` | int | Number of successful (filled) entry orders
-`nr_of_successful_exits` | int | Number of successful (filled) exit orders
+| `pair` | string | Pair of this trade. |
+| `is_open` | boolean | Is the trade currently open, or has it been concluded. |
+| `open_rate` | float | Rate this trade was entered at (Avg. entry rate in case of trade-adjustments). |
+| `close_rate` | float | Close rate - only set when is_open = False. |
+| `stake_amount` | float | Amount in Stake (or Quote) currency. |
+| `amount` | float | Amount in Asset / Base currency that is currently owned. Will be 0.0 until the initial order fills. |
+| `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** |
+| `close_date_utc` | datetime | Timestamp when trade was closed - in UTC. |
+| `close_profit` | float | Relative profit at the time of trade closure. `0.01` == 1% |
+| `close_profit_abs` | float | Absolute profit (in stake currency) at the time of trade closure. |
+| `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. |
+| `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. |
+| `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. |
+| `nr_of_successful_entries` | int | Number of successful (filled) entry orders. |
+| `nr_of_successful_exits` | int | Number of successful (filled) exit orders. |
 
 ## Class methods
 
@@ -126,24 +126,24 @@ An `Order` object will always be tied to it's corresponding [`Trade`](#trade-obj
 ### Order - Available attributes
 
 an Order object is typically attached to a trade.
-Most properties here can be None as they are dependant on the exchange response.
+Most properties here can be None as they are dependent on the exchange response.
 
 |  Attribute | DataType | Description |
 |------------|-------------|-------------|
-`trade` | Trade | Trade object this order is attached to
-`ft_pair` | string | Pair this order is for
-`ft_is_open` | boolean | is the order filled?
-`order_type` | string | Order type as defined on the exchange - usually market, limit or stoploss
-`status` | string | Status as defined by ccxt. Usually open, closed, expired or canceled
-`side` | string | Buy or Sell
-`price` | float | Price the order was placed at
-`average` | float | Average price the order filled at
-`amount` | float | Amount in base currency
-`filled` | float | Filled amount (in base currency)
-`remaining` | float | Remaining amount
-`cost` | float | Cost of the order - usually average * filled (*Exchange dependant 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.*
-`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
+| `trade` | Trade | Trade object this order is attached to |
+| `ft_pair` | string | Pair this order is for |
+| `ft_is_open` | boolean | is the order filled? |
+| `order_type` | string | Order type as defined on the exchange - usually market, limit or stoploss |
+| `status` | string | Status as defined by ccxt. Usually open, closed, expired or canceled |
+| `side` | string | Buy or Sell |
+| `price` | float | Price the order was placed at |
+| `average` | float | Average price the order filled at |
+| `amount` | float | Amount in base currency |
+| `filled` | float | Filled amount (in base currency) |
+| `remaining` | float | Remaining amount |
+| `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.* |
+| `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 |

docs/utils.md

@@ -418,8 +418,9 @@ Common arguments:
 
 ```
 
-By default, only active pairs/markets are shown. Active pairs/markets are those that can currently be traded
-on the exchange. The see the list of all pairs/markets (not only the active ones), use the `-a`/`-all` option.
+By default, only active pairs/markets are shown. Active pairs/markets are those that can currently be traded on the exchange.
+You can use the `-a`/`-all` option to see the list of all pairs/markets, including the inactive ones.
+Pairs may be listed as untradeable if the smallest tradeable price for the market is very small, i.e. less than `1e-11` (`0.00000000001`)
 
 Pairs/markets are sorted by its symbol string in the printed output.
 
@@ -488,7 +489,7 @@ freqtrade test-pairlist --config config.json --quote USDT BTC
 
 `freqtrade convert-db` can be used to convert your database from one system to another (sqlite -> postgres, postgres -> other postgres), migrating all trades, orders and Pairlocks.
 
-Please refer to the [SQL cheatsheet](sql_cheatsheet.md#use-a-different-database-system) to learn about requirements for different database systems.
+Please refer to the [corresponding documentation](advanced-setup.md#use-a-different-database-system) to learn about requirements for different database systems.
 
 ```
 usage: freqtrade convert-db [-h] [--db-url PATH] [--db-url-from PATH]

docs/windows_installation.md

@@ -5,6 +5,30 @@ We **strongly** recommend that Windows users use [Docker](docker_quickstart.md)
 If that is not possible, try using the Windows Linux subsystem (WSL) - for which the Ubuntu instructions should work.
 Otherwise, please follow the instructions below.
 
+All instructions assume that python 3.9+ is installed and available.
+
+## Clone the git repository
+
+First of all clone the repository by running:
+
+``` powershell
+git clone https://github.com/freqtrade/freqtrade.git
+```
+
+Now, choose your installation method, either automatically via script (recommended) or manually following the corresponding instructions.
+
+## Install freqtrade automatically
+
+### Run the installation script
+
+The script will ask you a few questions to determine which parts should be installed.
+
+```powershell
+Set-ExecutionPolicy -ExecutionPolicy Bypass
+cd freqtrade
+. .\setup.ps1
+```
+
 ## Install freqtrade manually
 
 !!! Note "64bit Python version"
@@ -14,17 +38,11 @@ Otherwise, please follow the instructions below.
 !!! 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.
 
-### 1. Clone the git repository
-
-```bash
-git clone https://github.com/freqtrade/freqtrade.git
-```
-
-### 2. Install ta-lib
+### 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 (3.9, 3.10 and 3.11) and for 64bit 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 (3.9, 3.10, 3.11 and 3.12) 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.

freqtrade/__init__.py

@@ -1,22 +1,34 @@
-""" Freqtrade bot """
-__version__ = '2024.3'
+"""Freqtrade bot"""
 
-if 'dev' in __version__:
+__version__ = "2024.9"
+
+if "dev" in __version__:
     from pathlib import Path
+
     try:
-        import subprocess
+        import subprocess  # noqa: S404
+
         freqtrade_basedir = Path(__file__).parent
 
-        __version__ = __version__ + '-' + subprocess.check_output(
-            ['git', 'log', '--format="%h"', '-n 1'],
-            stderr=subprocess.DEVNULL, cwd=freqtrade_basedir).decode("utf-8").rstrip().strip('"')
+        __version__ = (
+            __version__
+            + "-"
+            + subprocess.check_output(
+                ["git", "log", '--format="%h"', "-n 1"],
+                stderr=subprocess.DEVNULL,
+                cwd=freqtrade_basedir,
+            )
+            .decode("utf-8")
+            .rstrip()
+            .strip('"')
+        )
 
     except Exception:  # pragma: no cover
         # git not available, ignore
         try:
             # Try Fallback to freqtrade_commit file (created by CI while building docker image)
-            versionfile = Path('./freqtrade_commit')
+            versionfile = Path("./freqtrade_commit")
             if versionfile.is_file():
                 __version__ = f"docker-{__version__}-{versionfile.read_text()[:8]}"
-        except Exception:
+        except Exception:  # noqa: S110
             pass

freqtrade/__main__.py

@@ -9,5 +9,5 @@ To launch Freqtrade as a module
 from freqtrade import main
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     main.main()

freqtrade/commands/__init__.py

@@ -6,22 +6,40 @@ Contains all start-commands, subcommands and CLI Interface creation.
 Note: Be careful with file-scoped imports in these subfiles.
     as they are parsed on startup, nothing containing optional modules should be loaded.
 """
+
 from freqtrade.commands.analyze_commands import start_analysis_entries_exits
 from freqtrade.commands.arguments import Arguments
 from freqtrade.commands.build_config_commands import start_new_config, start_show_config
-from freqtrade.commands.data_commands import (start_convert_data, start_convert_trades,
-                                              start_download_data, start_list_data)
+from freqtrade.commands.data_commands import (
+    start_convert_data,
+    start_convert_trades,
+    start_download_data,
+    start_list_data,
+    start_list_trades_data,
+)
 from freqtrade.commands.db_commands import start_convert_db
-from freqtrade.commands.deploy_commands import (start_create_userdir, start_install_ui,
-                                                start_new_strategy)
+from freqtrade.commands.deploy_commands import (
+    start_create_userdir,
+    start_install_ui,
+    start_new_strategy,
+)
 from freqtrade.commands.hyperopt_commands import start_hyperopt_list, start_hyperopt_show
-from freqtrade.commands.list_commands import (start_list_exchanges, start_list_freqAI_models,
-                                              start_list_markets, start_list_strategies,
-                                              start_list_timeframes, start_show_trades)
-from freqtrade.commands.optimize_commands import (start_backtesting, start_backtesting_show,
-                                                  start_edge, start_hyperopt,
-                                                  start_lookahead_analysis,
-                                                  start_recursive_analysis)
+from freqtrade.commands.list_commands import (
+    start_list_exchanges,
+    start_list_freqAI_models,
+    start_list_markets,
+    start_list_strategies,
+    start_list_timeframes,
+    start_show_trades,
+)
+from freqtrade.commands.optimize_commands import (
+    start_backtesting,
+    start_backtesting_show,
+    start_edge,
+    start_hyperopt,
+    start_lookahead_analysis,
+    start_recursive_analysis,
+)
 from freqtrade.commands.pairlist_commands import start_test_pairlist
 from freqtrade.commands.plot_commands import start_plot_dataframe, start_plot_profit
 from freqtrade.commands.strategy_utils_commands import start_strategy_update

freqtrade/commands/analyze_commands.py

@@ -20,25 +20,25 @@ def setup_analyze_configuration(args: Dict[str, Any], method: RunMode) -> Dict[s
     config = setup_utils_configuration(args, method)
 
     no_unlimited_runmodes = {
-        RunMode.BACKTEST: 'backtesting',
+        RunMode.BACKTEST: "backtesting",
     }
     if method in no_unlimited_runmodes.keys():
         from freqtrade.data.btanalysis import get_latest_backtest_filename
 
-        if 'exportfilename' in config:
-            if config['exportfilename'].is_dir():
-                btfile = Path(get_latest_backtest_filename(config['exportfilename']))
+        if "exportfilename" in config:
+            if config["exportfilename"].is_dir():
+                btfile = Path(get_latest_backtest_filename(config["exportfilename"]))
                 signals_file = f"{config['exportfilename']}/{btfile.stem}_signals.pkl"
             else:
-                if config['exportfilename'].exists():
-                    btfile = Path(config['exportfilename'])
+                if config["exportfilename"].exists():
+                    btfile = Path(config["exportfilename"])
                     signals_file = f"{btfile.parent}/{btfile.stem}_signals.pkl"
                 else:
                     raise ConfigurationError(f"{config['exportfilename']} does not exist.")
         else:
-            raise ConfigurationError('exportfilename not in config.')
+            raise ConfigurationError("exportfilename not in config.")
 
-        if (not Path(signals_file).exists()):
+        if not Path(signals_file).exists():
             raise OperationalException(
                 f"Cannot find latest backtest signals file: {signals_file}."
                 "Run backtesting with `--export signals`."
@@ -58,6 +58,6 @@ def start_analysis_entries_exits(args: Dict[str, Any]) -> None:
     # Initialize configuration
     config = setup_analyze_configuration(args, RunMode.BACKTEST)
 
-    logger.info('Starting freqtrade in analysis mode')
+    logger.info("Starting freqtrade in analysis mode")
 
     process_entry_exit_reasons(config)

freqtrade/commands/arguments.py

@@ -1,10 +1,11 @@
 """
 This module contains the argument manager class
 """
-import argparse
+
+from argparse import ArgumentParser, Namespace, _ArgumentGroup
 from functools import partial
 from pathlib import Path
-from typing import Any, Dict, List, Optional
+from typing import Any, Dict, List, Optional, Union
 
 from freqtrade.commands.cli_options import AVAILABLE_CLI_OPTIONS
 from freqtrade.constants import DEFAULT_CONFIG
@@ -12,35 +13,72 @@ from freqtrade.constants import DEFAULT_CONFIG
 
 ARGS_COMMON = ["verbosity", "logfile", "version", "config", "datadir", "user_data_dir"]
 
-ARGS_STRATEGY = ["strategy", "strategy_path", "recursive_strategy_search", "freqaimodel",
-                 "freqaimodel_path"]
+ARGS_STRATEGY = [
+    "strategy",
+    "strategy_path",
+    "recursive_strategy_search",
+    "freqaimodel",
+    "freqaimodel_path",
+]
 
 ARGS_TRADE = ["db_url", "sd_notify", "dry_run", "dry_run_wallet", "fee"]
 
 ARGS_WEBSERVER: List[str] = []
 
-ARGS_COMMON_OPTIMIZE = ["timeframe", "timerange", "dataformat_ohlcv",
-                        "max_open_trades", "stake_amount", "fee", "pairs"]
+ARGS_COMMON_OPTIMIZE = [
+    "timeframe",
+    "timerange",
+    "dataformat_ohlcv",
+    "max_open_trades",
+    "stake_amount",
+    "fee",
+    "pairs",
+]
 
-ARGS_BACKTEST = ARGS_COMMON_OPTIMIZE + ["position_stacking", "use_max_market_positions",
-                                        "enable_protections", "dry_run_wallet", "timeframe_detail",
-                                        "strategy_list", "export", "exportfilename",
-                                        "backtest_breakdown", "backtest_cache",
-                                        "freqai_backtest_live_models"]
+ARGS_BACKTEST = ARGS_COMMON_OPTIMIZE + [
+    "position_stacking",
+    "use_max_market_positions",
+    "enable_protections",
+    "dry_run_wallet",
+    "timeframe_detail",
+    "strategy_list",
+    "export",
+    "exportfilename",
+    "backtest_breakdown",
+    "backtest_cache",
+    "freqai_backtest_live_models",
+]
 
-ARGS_HYPEROPT = ARGS_COMMON_OPTIMIZE + ["hyperopt", "hyperopt_path",
-                                        "position_stacking", "use_max_market_positions",
-                                        "enable_protections", "dry_run_wallet", "timeframe_detail",
-                                        "epochs", "spaces", "print_all",
-                                        "print_colorized", "print_json", "hyperopt_jobs",
-                                        "hyperopt_random_state", "hyperopt_min_trades",
-                                        "hyperopt_loss", "disableparamexport",
-                                        "hyperopt_ignore_missing_space", "analyze_per_epoch"]
+ARGS_HYPEROPT = ARGS_COMMON_OPTIMIZE + [
+    "hyperopt",
+    "hyperopt_path",
+    "position_stacking",
+    "use_max_market_positions",
+    "enable_protections",
+    "dry_run_wallet",
+    "timeframe_detail",
+    "epochs",
+    "spaces",
+    "print_all",
+    "print_colorized",
+    "print_json",
+    "hyperopt_jobs",
+    "hyperopt_random_state",
+    "hyperopt_min_trades",
+    "hyperopt_loss",
+    "disableparamexport",
+    "hyperopt_ignore_missing_space",
+    "analyze_per_epoch",
+]
 
 ARGS_EDGE = ARGS_COMMON_OPTIMIZE + ["stoploss_range"]
 
-ARGS_LIST_STRATEGIES = ["strategy_path", "print_one_column", "print_colorized",
-                        "recursive_strategy_search"]
+ARGS_LIST_STRATEGIES = [
+    "strategy_path",
+    "print_one_column",
+    "print_colorized",
+    "recursive_strategy_search",
+]
 
 ARGS_LIST_FREQAIMODELS = ["freqaimodel_path", "print_one_column", "print_colorized"]
 
@@ -52,12 +90,27 @@ ARGS_LIST_EXCHANGES = ["print_one_column", "list_exchanges_all"]
 
 ARGS_LIST_TIMEFRAMES = ["exchange", "print_one_column"]
 
-ARGS_LIST_PAIRS = ["exchange", "print_list", "list_pairs_print_json", "print_one_column",
-                   "print_csv", "base_currencies", "quote_currencies", "list_pairs_all",
-                   "trading_mode"]
+ARGS_LIST_PAIRS = [
+    "exchange",
+    "print_list",
+    "list_pairs_print_json",
+    "print_one_column",
+    "print_csv",
+    "base_currencies",
+    "quote_currencies",
+    "list_pairs_all",
+    "trading_mode",
+]
 
-ARGS_TEST_PAIRLIST = ["user_data_dir", "verbosity", "config", "quote_currencies",
-                      "print_one_column", "list_pairs_print_json", "exchange"]
+ARGS_TEST_PAIRLIST = [
+    "user_data_dir",
+    "verbosity",
+    "config",
+    "quote_currencies",
+    "print_one_column",
+    "list_pairs_print_json",
+    "exchange",
+]
 
 ARGS_CREATE_USERDIR = ["user_data_dir", "reset"]
 
@@ -70,22 +123,67 @@ ARGS_CONVERT_DATA_TRADES = ["pairs", "format_from_trades", "format_to", "erase",
 ARGS_CONVERT_DATA = ["pairs", "format_from", "format_to", "erase", "exchange"]
 ARGS_CONVERT_DATA_OHLCV = ARGS_CONVERT_DATA + ["timeframes", "trading_mode", "candle_types"]
 
-ARGS_CONVERT_TRADES = ["pairs", "timeframes", "exchange", "dataformat_ohlcv", "dataformat_trades",
-                       "trading_mode"]
+ARGS_CONVERT_TRADES = [
+    "pairs",
+    "timeframes",
+    "exchange",
+    "dataformat_ohlcv",
+    "dataformat_trades",
+    "trading_mode",
+]
 
-ARGS_LIST_DATA = ["exchange", "dataformat_ohlcv", "pairs", "trading_mode", "show_timerange"]
+ARGS_LIST_DATA = [
+    "exchange",
+    "dataformat_ohlcv",
+    "dataformat_trades",
+    "trades",
+    "pairs",
+    "trading_mode",
+    "show_timerange",
+]
 
-ARGS_DOWNLOAD_DATA = ["pairs", "pairs_file", "days", "new_pairs_days", "include_inactive",
-                      "timerange", "download_trades", "exchange", "timeframes",
-                      "erase", "dataformat_ohlcv", "dataformat_trades", "trading_mode",
-                      "prepend_data"]
+ARGS_DOWNLOAD_DATA = [
+    "pairs",
+    "pairs_file",
+    "days",
+    "new_pairs_days",
+    "include_inactive",
+    "timerange",
+    "download_trades",
+    "convert_trades",
+    "exchange",
+    "timeframes",
+    "erase",
+    "dataformat_ohlcv",
+    "dataformat_trades",
+    "trading_mode",
+    "prepend_data",
+]
 
-ARGS_PLOT_DATAFRAME = ["pairs", "indicators1", "indicators2", "plot_limit",
-                       "db_url", "trade_source", "export", "exportfilename",
-                       "timerange", "timeframe", "no_trades"]
+ARGS_PLOT_DATAFRAME = [
+    "pairs",
+    "indicators1",
+    "indicators2",
+    "plot_limit",
+    "db_url",
+    "trade_source",
+    "export",
+    "exportfilename",
+    "timerange",
+    "timeframe",
+    "no_trades",
+]
 
-ARGS_PLOT_PROFIT = ["pairs", "timerange", "export", "exportfilename", "db_url",
-                    "trade_source", "timeframe", "plot_auto_open", ]
+ARGS_PLOT_PROFIT = [
+    "pairs",
+    "timerange",
+    "export",
+    "exportfilename",
+    "db_url",
+    "trade_source",
+    "timeframe",
+    "plot_auto_open",
+]
 
 ARGS_CONVERT_DB = ["db_url", "db_url_from"]
 
@@ -93,39 +191,86 @@ ARGS_INSTALL_UI = ["erase_ui_only", "ui_version"]
 
 ARGS_SHOW_TRADES = ["db_url", "trade_ids", "print_json"]
 
-ARGS_HYPEROPT_LIST = ["hyperopt_list_best", "hyperopt_list_profitable",
-                      "hyperopt_list_min_trades", "hyperopt_list_max_trades",
-                      "hyperopt_list_min_avg_time", "hyperopt_list_max_avg_time",
-                      "hyperopt_list_min_avg_profit", "hyperopt_list_max_avg_profit",
-                      "hyperopt_list_min_total_profit", "hyperopt_list_max_total_profit",
-                      "hyperopt_list_min_objective", "hyperopt_list_max_objective",
-                      "print_colorized", "print_json", "hyperopt_list_no_details",
-                      "hyperoptexportfilename", "export_csv"]
+ARGS_HYPEROPT_LIST = [
+    "hyperopt_list_best",
+    "hyperopt_list_profitable",
+    "hyperopt_list_min_trades",
+    "hyperopt_list_max_trades",
+    "hyperopt_list_min_avg_time",
+    "hyperopt_list_max_avg_time",
+    "hyperopt_list_min_avg_profit",
+    "hyperopt_list_max_avg_profit",
+    "hyperopt_list_min_total_profit",
+    "hyperopt_list_max_total_profit",
+    "hyperopt_list_min_objective",
+    "hyperopt_list_max_objective",
+    "print_colorized",
+    "print_json",
+    "hyperopt_list_no_details",
+    "hyperoptexportfilename",
+    "export_csv",
+]
 
-ARGS_HYPEROPT_SHOW = ["hyperopt_list_best", "hyperopt_list_profitable", "hyperopt_show_index",
-                      "print_json", "hyperoptexportfilename", "hyperopt_show_no_header",
-                      "disableparamexport", "backtest_breakdown"]
+ARGS_HYPEROPT_SHOW = [
+    "hyperopt_list_best",
+    "hyperopt_list_profitable",
+    "hyperopt_show_index",
+    "print_json",
+    "hyperoptexportfilename",
+    "hyperopt_show_no_header",
+    "disableparamexport",
+    "backtest_breakdown",
+]
 
-ARGS_ANALYZE_ENTRIES_EXITS = ["exportfilename", "analysis_groups", "enter_reason_list",
-                              "exit_reason_list", "indicator_list", "timerange",
-                              "analysis_rejected", "analysis_to_csv", "analysis_csv_path"]
+ARGS_ANALYZE_ENTRIES_EXITS = [
+    "exportfilename",
+    "analysis_groups",
+    "enter_reason_list",
+    "exit_reason_list",
+    "indicator_list",
+    "entry_only",
+    "exit_only",
+    "timerange",
+    "analysis_rejected",
+    "analysis_to_csv",
+    "analysis_csv_path",
+]
 
-NO_CONF_REQURIED = ["convert-data", "convert-trade-data", "download-data", "list-timeframes",
-                    "list-markets", "list-pairs", "list-strategies", "list-freqaimodels",
-                    "list-data", "hyperopt-list", "hyperopt-show", "backtest-filter",
-                    "plot-dataframe", "plot-profit", "show-trades", "trades-to-ohlcv",
-                    "strategy-updater"]
-
-NO_CONF_ALLOWED = ["create-userdir", "list-exchanges", "new-strategy"]
 
 ARGS_STRATEGY_UPDATER = ["strategy_list", "strategy_path", "recursive_strategy_search"]
 
 ARGS_LOOKAHEAD_ANALYSIS = [
-    a for a in ARGS_BACKTEST if a not in ("position_stacking", "use_max_market_positions", 'cache')
-    ] + ["minimum_trade_amount", "targeted_trade_amount", "lookahead_analysis_exportfilename"]
+    a
+    for a in ARGS_BACKTEST
+    if a
+    not in ("position_stacking", "use_max_market_positions", "backtest_cache", "backtest_breakdown")
+] + ["minimum_trade_amount", "targeted_trade_amount", "lookahead_analysis_exportfilename"]
 
 ARGS_RECURSIVE_ANALYSIS = ["timeframe", "timerange", "dataformat_ohlcv", "pairs", "startup_candle"]
 
+# Command level configs - keep at the bottom of the above definitions
+NO_CONF_REQURIED = [
+    "convert-data",
+    "convert-trade-data",
+    "download-data",
+    "list-timeframes",
+    "list-markets",
+    "list-pairs",
+    "list-strategies",
+    "list-freqaimodels",
+    "list-data",
+    "hyperopt-list",
+    "hyperopt-show",
+    "backtest-filter",
+    "plot-dataframe",
+    "plot-profit",
+    "show-trades",
+    "trades-to-ohlcv",
+    "strategy-updater",
+]
+
+NO_CONF_ALLOWED = ["create-userdir", "list-exchanges", "new-strategy"]
+
 
 class Arguments:
     """
@@ -134,7 +279,7 @@ class Arguments:
 
     def __init__(self, args: Optional[List[str]]) -> None:
         self.args = args
-        self._parsed_arg: Optional[argparse.Namespace] = None
+        self._parsed_arg: Optional[Namespace] = None
 
     def get_parsed_arg(self) -> Dict[str, Any]:
         """
@@ -147,7 +292,7 @@ class Arguments:
 
         return vars(self._parsed_arg)
 
-    def _parse_args(self) -> argparse.Namespace:
+    def _parse_args(self) -> Namespace:
         """
         Parses given arguments and returns an argparse Namespace instance.
         """
@@ -156,14 +301,14 @@ class Arguments:
         # Workaround issue in argparse with action='append' and default value
         # (see https://bugs.python.org/issue16399)
         # Allow no-config for certain commands (like downloading / plotting)
-        if ('config' in parsed_arg and parsed_arg.config is None):
-            conf_required = ('command' in parsed_arg and parsed_arg.command in NO_CONF_REQURIED)
+        if "config" in parsed_arg and parsed_arg.config is None:
+            conf_required = "command" in parsed_arg and parsed_arg.command in NO_CONF_REQURIED
 
-            if 'user_data_dir' in parsed_arg and parsed_arg.user_data_dir is not None:
+            if "user_data_dir" in parsed_arg and parsed_arg.user_data_dir is not None:
                 user_dir = parsed_arg.user_data_dir
             else:
                 # Default case
-                user_dir = 'user_data'
+                user_dir = "user_data"
                 # Try loading from "user_data/config.json"
             cfgfile = Path(user_dir) / DEFAULT_CONFIG
             if cfgfile.is_file():
@@ -176,8 +321,9 @@ class Arguments:
 
         return parsed_arg
 
-    def _build_args(self, optionlist, parser):
-
+    def _build_args(
+        self, optionlist: List[str], parser: Union[ArgumentParser, _ArgumentGroup]
+    ) -> None:
         for val in optionlist:
             opt = AVAILABLE_CLI_OPTIONS[val]
             parser.add_argument(*opt.cli, dest=val, **opt.kwargs)
@@ -188,50 +334,71 @@ class Arguments:
         :return: None
         """
         # Build shared arguments (as group Common Options)
-        _common_parser = argparse.ArgumentParser(add_help=False)
+        _common_parser = ArgumentParser(add_help=False)
         group = _common_parser.add_argument_group("Common arguments")
         self._build_args(optionlist=ARGS_COMMON, parser=group)
 
-        _strategy_parser = argparse.ArgumentParser(add_help=False)
+        _strategy_parser = ArgumentParser(add_help=False)
         strategy_group = _strategy_parser.add_argument_group("Strategy arguments")
         self._build_args(optionlist=ARGS_STRATEGY, parser=strategy_group)
 
         # Build main command
-        self.parser = argparse.ArgumentParser(description='Free, open source crypto trading bot')
-        self._build_args(optionlist=['version'], parser=self.parser)
+        self.parser = ArgumentParser(
+            prog="freqtrade", description="Free, open source crypto trading bot"
+        )
+        self._build_args(optionlist=["version"], parser=self.parser)
 
-        from freqtrade.commands import (start_analysis_entries_exits, start_backtesting,
-                                        start_backtesting_show, start_convert_data,
-                                        start_convert_db, start_convert_trades,
-                                        start_create_userdir, start_download_data, start_edge,
-                                        start_hyperopt, start_hyperopt_list, start_hyperopt_show,
-                                        start_install_ui, start_list_data, start_list_exchanges,
-                                        start_list_freqAI_models, start_list_markets,
-                                        start_list_strategies, start_list_timeframes,
-                                        start_lookahead_analysis, start_new_config,
-                                        start_new_strategy, start_plot_dataframe, start_plot_profit,
-                                        start_recursive_analysis, start_show_config,
-                                        start_show_trades, start_strategy_update,
-                                        start_test_pairlist, start_trading, start_webserver)
+        from freqtrade.commands import (
+            start_analysis_entries_exits,
+            start_backtesting,
+            start_backtesting_show,
+            start_convert_data,
+            start_convert_db,
+            start_convert_trades,
+            start_create_userdir,
+            start_download_data,
+            start_edge,
+            start_hyperopt,
+            start_hyperopt_list,
+            start_hyperopt_show,
+            start_install_ui,
+            start_list_data,
+            start_list_exchanges,
+            start_list_freqAI_models,
+            start_list_markets,
+            start_list_strategies,
+            start_list_timeframes,
+            start_lookahead_analysis,
+            start_new_config,
+            start_new_strategy,
+            start_plot_dataframe,
+            start_plot_profit,
+            start_recursive_analysis,
+            start_show_config,
+            start_show_trades,
+            start_strategy_update,
+            start_test_pairlist,
+            start_trading,
+            start_webserver,
+        )
 
-        subparsers = self.parser.add_subparsers(dest='command',
-                                                # Use custom message when no subhandler is added
-                                                # shown from `main.py`
-                                                # required=True
-                                                )
+        subparsers = self.parser.add_subparsers(
+            dest="command",
+            # Use custom message when no subhandler is added
+            # shown from `main.py`
+            # required=True
+        )
 
         # Add trade subcommand
         trade_cmd = subparsers.add_parser(
-            'trade',
-            help='Trade module.',
-            parents=[_common_parser, _strategy_parser]
+            "trade", help="Trade module.", parents=[_common_parser, _strategy_parser]
         )
         trade_cmd.set_defaults(func=start_trading)
         self._build_args(optionlist=ARGS_TRADE, parser=trade_cmd)
 
         # add create-userdir subcommand
         create_userdir_cmd = subparsers.add_parser(
-            'create-userdir',
+            "create-userdir",
             help="Create user-data directory.",
         )
         create_userdir_cmd.set_defaults(func=start_create_userdir)
@@ -239,7 +406,7 @@ class Arguments:
 
         # add new-config subcommand
         build_config_cmd = subparsers.add_parser(
-            'new-config',
+            "new-config",
             help="Create new config",
         )
         build_config_cmd.set_defaults(func=start_new_config)
@@ -247,7 +414,7 @@ class Arguments:
 
         # add show-config subcommand
         show_config_cmd = subparsers.add_parser(
-            'show-config',
+            "show-config",
             help="Show resolved config",
         )
         show_config_cmd.set_defaults(func=start_show_config)
@@ -255,7 +422,7 @@ class Arguments:
 
         # add new-strategy subcommand
         build_strategy_cmd = subparsers.add_parser(
-            'new-strategy',
+            "new-strategy",
             help="Create new strategy",
         )
         build_strategy_cmd.set_defaults(func=start_new_strategy)
@@ -263,8 +430,8 @@ class Arguments:
 
         # Add download-data subcommand
         download_data_cmd = subparsers.add_parser(
-            'download-data',
-            help='Download backtesting data.',
+            "download-data",
+            help="Download backtesting data.",
             parents=[_common_parser],
         )
         download_data_cmd.set_defaults(func=start_download_data)
@@ -272,8 +439,8 @@ class Arguments:
 
         # Add convert-data subcommand
         convert_data_cmd = subparsers.add_parser(
-            'convert-data',
-            help='Convert candle (OHLCV) data from one format to another.',
+            "convert-data",
+            help="Convert candle (OHLCV) data from one format to another.",
             parents=[_common_parser],
         )
         convert_data_cmd.set_defaults(func=partial(start_convert_data, ohlcv=True))
@@ -281,8 +448,8 @@ class Arguments:
 
         # Add convert-trade-data subcommand
         convert_trade_data_cmd = subparsers.add_parser(
-            'convert-trade-data',
-            help='Convert trade data from one format to another.',
+            "convert-trade-data",
+            help="Convert trade data from one format to another.",
             parents=[_common_parser],
         )
         convert_trade_data_cmd.set_defaults(func=partial(start_convert_data, ohlcv=False))
@@ -290,8 +457,8 @@ class Arguments:
 
         # Add trades-to-ohlcv subcommand
         convert_trade_data_cmd = subparsers.add_parser(
-            'trades-to-ohlcv',
-            help='Convert trade data to OHLCV data.',
+            "trades-to-ohlcv",
+            help="Convert trade data to OHLCV data.",
             parents=[_common_parser],
         )
         convert_trade_data_cmd.set_defaults(func=start_convert_trades)
@@ -299,8 +466,8 @@ class Arguments:
 
         # Add list-data subcommand
         list_data_cmd = subparsers.add_parser(
-            'list-data',
-            help='List downloaded data.',
+            "list-data",
+            help="List downloaded data.",
             parents=[_common_parser],
         )
         list_data_cmd.set_defaults(func=start_list_data)
@@ -308,17 +475,15 @@ class Arguments:
 
         # Add backtesting subcommand
         backtesting_cmd = subparsers.add_parser(
-            'backtesting',
-            help='Backtesting module.',
-            parents=[_common_parser, _strategy_parser]
+            "backtesting", help="Backtesting module.", parents=[_common_parser, _strategy_parser]
         )
         backtesting_cmd.set_defaults(func=start_backtesting)
         self._build_args(optionlist=ARGS_BACKTEST, parser=backtesting_cmd)
 
         # Add backtesting-show subcommand
         backtesting_show_cmd = subparsers.add_parser(
-            'backtesting-show',
-            help='Show past Backtest results',
+            "backtesting-show",
+            help="Show past Backtest results",
             parents=[_common_parser],
         )
         backtesting_show_cmd.set_defaults(func=start_backtesting_show)
@@ -326,26 +491,22 @@ class Arguments:
 
         # Add backtesting analysis subcommand
         analysis_cmd = subparsers.add_parser(
-            'backtesting-analysis',
-            help='Backtest Analysis module.',
-            parents=[_common_parser]
+            "backtesting-analysis", help="Backtest Analysis module.", parents=[_common_parser]
         )
         analysis_cmd.set_defaults(func=start_analysis_entries_exits)
         self._build_args(optionlist=ARGS_ANALYZE_ENTRIES_EXITS, parser=analysis_cmd)
 
         # Add edge subcommand
         edge_cmd = subparsers.add_parser(
-            'edge',
-            help='Edge module.',
-            parents=[_common_parser, _strategy_parser]
+            "edge", help="Edge module.", parents=[_common_parser, _strategy_parser]
         )
         edge_cmd.set_defaults(func=start_edge)
         self._build_args(optionlist=ARGS_EDGE, parser=edge_cmd)
 
         # Add hyperopt subcommand
         hyperopt_cmd = subparsers.add_parser(
-            'hyperopt',
-            help='Hyperopt module.',
+            "hyperopt",
+            help="Hyperopt module.",
             parents=[_common_parser, _strategy_parser],
         )
         hyperopt_cmd.set_defaults(func=start_hyperopt)
@@ -353,8 +514,8 @@ class Arguments:
 
         # Add hyperopt-list subcommand
         hyperopt_list_cmd = subparsers.add_parser(
-            'hyperopt-list',
-            help='List Hyperopt results',
+            "hyperopt-list",
+            help="List Hyperopt results",
             parents=[_common_parser],
         )
         hyperopt_list_cmd.set_defaults(func=start_hyperopt_list)
@@ -362,8 +523,8 @@ class Arguments:
 
         # Add hyperopt-show subcommand
         hyperopt_show_cmd = subparsers.add_parser(
-            'hyperopt-show',
-            help='Show details of Hyperopt results',
+            "hyperopt-show",
+            help="Show details of Hyperopt results",
             parents=[_common_parser],
         )
         hyperopt_show_cmd.set_defaults(func=start_hyperopt_show)
@@ -371,8 +532,8 @@ class Arguments:
 
         # Add list-exchanges subcommand
         list_exchanges_cmd = subparsers.add_parser(
-            'list-exchanges',
-            help='Print available exchanges.',
+            "list-exchanges",
+            help="Print available exchanges.",
             parents=[_common_parser],
         )
         list_exchanges_cmd.set_defaults(func=start_list_exchanges)
@@ -380,8 +541,8 @@ class Arguments:
 
         # Add list-markets subcommand
         list_markets_cmd = subparsers.add_parser(
-            'list-markets',
-            help='Print markets on exchange.',
+            "list-markets",
+            help="Print markets on exchange.",
             parents=[_common_parser],
         )
         list_markets_cmd.set_defaults(func=partial(start_list_markets, pairs_only=False))
@@ -389,8 +550,8 @@ class Arguments:
 
         # Add list-pairs subcommand
         list_pairs_cmd = subparsers.add_parser(
-            'list-pairs',
-            help='Print pairs on exchange.',
+            "list-pairs",
+            help="Print pairs on exchange.",
             parents=[_common_parser],
         )
         list_pairs_cmd.set_defaults(func=partial(start_list_markets, pairs_only=True))
@@ -398,8 +559,8 @@ class Arguments:
 
         # Add list-strategies subcommand
         list_strategies_cmd = subparsers.add_parser(
-            'list-strategies',
-            help='Print available strategies.',
+            "list-strategies",
+            help="Print available strategies.",
             parents=[_common_parser],
         )
         list_strategies_cmd.set_defaults(func=start_list_strategies)
@@ -407,8 +568,8 @@ class Arguments:
 
         # Add list-freqAI Models subcommand
         list_freqaimodels_cmd = subparsers.add_parser(
-            'list-freqaimodels',
-            help='Print available freqAI models.',
+            "list-freqaimodels",
+            help="Print available freqAI models.",
             parents=[_common_parser],
         )
         list_freqaimodels_cmd.set_defaults(func=start_list_freqAI_models)
@@ -416,8 +577,8 @@ class Arguments:
 
         # Add list-timeframes subcommand
         list_timeframes_cmd = subparsers.add_parser(
-            'list-timeframes',
-            help='Print available timeframes for the exchange.',
+            "list-timeframes",
+            help="Print available timeframes for the exchange.",
             parents=[_common_parser],
         )
         list_timeframes_cmd.set_defaults(func=start_list_timeframes)
@@ -425,8 +586,8 @@ class Arguments:
 
         # Add show-trades subcommand
         show_trades = subparsers.add_parser(
-            'show-trades',
-            help='Show trades.',
+            "show-trades",
+            help="Show trades.",
             parents=[_common_parser],
         )
         show_trades.set_defaults(func=start_show_trades)
@@ -434,8 +595,8 @@ class Arguments:
 
         # Add test-pairlist subcommand
         test_pairlist_cmd = subparsers.add_parser(
-            'test-pairlist',
-            help='Test your pairlist configuration.',
+            "test-pairlist",
+            help="Test your pairlist configuration.",
         )
         test_pairlist_cmd.set_defaults(func=start_test_pairlist)
         self._build_args(optionlist=ARGS_TEST_PAIRLIST, parser=test_pairlist_cmd)
@@ -450,16 +611,16 @@ class Arguments:
 
         # Add install-ui subcommand
         install_ui_cmd = subparsers.add_parser(
-            'install-ui',
-            help='Install FreqUI',
+            "install-ui",
+            help="Install FreqUI",
         )
         install_ui_cmd.set_defaults(func=start_install_ui)
         self._build_args(optionlist=ARGS_INSTALL_UI, parser=install_ui_cmd)
 
         # Add Plotting subcommand
         plot_dataframe_cmd = subparsers.add_parser(
-            'plot-dataframe',
-            help='Plot candles with indicators.',
+            "plot-dataframe",
+            help="Plot candles with indicators.",
             parents=[_common_parser, _strategy_parser],
         )
         plot_dataframe_cmd.set_defaults(func=start_plot_dataframe)
@@ -467,8 +628,8 @@ class Arguments:
 
         # Plot profit
         plot_profit_cmd = subparsers.add_parser(
-            'plot-profit',
-            help='Generate plot showing profits.',
+            "plot-profit",
+            help="Generate plot showing profits.",
             parents=[_common_parser, _strategy_parser],
         )
         plot_profit_cmd.set_defaults(func=start_plot_profit)
@@ -476,40 +637,36 @@ class Arguments:
 
         # Add webserver subcommand
         webserver_cmd = subparsers.add_parser(
-            'webserver',
-            help='Webserver module.',
-            parents=[_common_parser]
+            "webserver", help="Webserver module.", parents=[_common_parser]
         )
         webserver_cmd.set_defaults(func=start_webserver)
         self._build_args(optionlist=ARGS_WEBSERVER, parser=webserver_cmd)
 
         # Add strategy_updater subcommand
         strategy_updater_cmd = subparsers.add_parser(
-            'strategy-updater',
-            help='updates outdated strategy files to the current version',
-            parents=[_common_parser]
+            "strategy-updater",
+            help="updates outdated strategy files to the current version",
+            parents=[_common_parser],
         )
         strategy_updater_cmd.set_defaults(func=start_strategy_update)
         self._build_args(optionlist=ARGS_STRATEGY_UPDATER, parser=strategy_updater_cmd)
 
         # Add lookahead_analysis subcommand
         lookahead_analayis_cmd = subparsers.add_parser(
-            'lookahead-analysis',
+            "lookahead-analysis",
             help="Check for potential look ahead bias.",
-            parents=[_common_parser, _strategy_parser]
+            parents=[_common_parser, _strategy_parser],
         )
         lookahead_analayis_cmd.set_defaults(func=start_lookahead_analysis)
 
-        self._build_args(optionlist=ARGS_LOOKAHEAD_ANALYSIS,
-                         parser=lookahead_analayis_cmd)
+        self._build_args(optionlist=ARGS_LOOKAHEAD_ANALYSIS, parser=lookahead_analayis_cmd)
 
         # Add recursive_analysis subcommand
         recursive_analayis_cmd = subparsers.add_parser(
-            'recursive-analysis',
+            "recursive-analysis",
             help="Check for potential recursive formula issue.",
-            parents=[_common_parser, _strategy_parser]
+            parents=[_common_parser, _strategy_parser],
         )
         recursive_analayis_cmd.set_defaults(func=start_recursive_analysis)
 
-        self._build_args(optionlist=ARGS_RECURSIVE_ANALYSIS,
-                         parser=recursive_analayis_cmd)
+        self._build_args(optionlist=ARGS_RECURSIVE_ANALYSIS, parser=recursive_analayis_cmd)

freqtrade/commands/build_config_commands.py

@@ -45,7 +45,7 @@ def ask_user_overwrite(config_path: Path) -> bool:
         },
     ]
     answers = prompt(questions)
-    return answers['overwrite']
+    return answers["overwrite"]
 
 
 def ask_user_config() -> Dict[str, Any]:
@@ -65,7 +65,7 @@ def ask_user_config() -> Dict[str, Any]:
             "type": "text",
             "name": "stake_currency",
             "message": "Please insert your stake currency:",
-            "default": 'USDT',
+            "default": "USDT",
         },
         {
             "type": "text",
@@ -73,36 +73,38 @@ def ask_user_config() -> Dict[str, Any]:
             "message": f"Please insert your stake amount (Number or '{UNLIMITED_STAKE_AMOUNT}'):",
             "default": "unlimited",
             "validate": lambda val: val == UNLIMITED_STAKE_AMOUNT or validate_is_float(val),
-            "filter": lambda val: '"' + UNLIMITED_STAKE_AMOUNT + '"'
-            if val == UNLIMITED_STAKE_AMOUNT
-            else val
+            "filter": lambda val: (
+                '"' + UNLIMITED_STAKE_AMOUNT + '"' if val == UNLIMITED_STAKE_AMOUNT else val
+            ),
         },
         {
             "type": "text",
             "name": "max_open_trades",
             "message": "Please insert max_open_trades (Integer or -1 for unlimited open trades):",
             "default": "3",
-            "validate": lambda val: validate_is_int(val)
+            "validate": lambda val: validate_is_int(val),
         },
         {
             "type": "select",
             "name": "timeframe_in_config",
             "message": "Time",
-            "choices": ["Have the strategy define timeframe.", "Override in configuration."]
+            "choices": ["Have the strategy define timeframe.", "Override in configuration."],
         },
         {
             "type": "text",
             "name": "timeframe",
             "message": "Please insert your desired timeframe (e.g. 5m):",
             "default": "5m",
-            "when": lambda x: x["timeframe_in_config"] == 'Override in configuration.'
-
+            "when": lambda x: x["timeframe_in_config"] == "Override in configuration.",
         },
         {
             "type": "text",
             "name": "fiat_display_currency",
-            "message": "Please insert your display Currency (for reporting):",
-            "default": 'USD',
+            "message": (
+                "Please insert your display Currency for reporting "
+                "(leave empty to disable FIAT conversion):"
+            ),
+            "default": "USD",
         },
         {
             "type": "select",
@@ -111,6 +113,7 @@ def ask_user_config() -> Dict[str, Any]:
             "choices": [
                 "binance",
                 "binanceus",
+                "bingx",
                 "gate",
                 "htx",
                 "kraken",
@@ -125,33 +128,33 @@ def ask_user_config() -> Dict[str, Any]:
             "name": "trading_mode",
             "message": "Do you want to trade Perpetual Swaps (perpetual futures)?",
             "default": False,
-            "filter": lambda val: 'futures' if val else 'spot',
-            "when": lambda x: x["exchange_name"] in ['binance', 'gate', 'okx'],
+            "filter": lambda val: "futures" if val else "spot",
+            "when": lambda x: x["exchange_name"] in ["binance", "gate", "okx", "bybit"],
         },
         {
             "type": "autocomplete",
             "name": "exchange_name",
             "message": "Type your exchange name (Must be supported by ccxt)",
             "choices": available_exchanges(),
-            "when": lambda x: x["exchange_name"] == 'other'
+            "when": lambda x: x["exchange_name"] == "other",
         },
         {
             "type": "password",
             "name": "exchange_key",
             "message": "Insert Exchange Key",
-            "when": lambda x: not x['dry_run']
+            "when": lambda x: not x["dry_run"],
         },
         {
             "type": "password",
             "name": "exchange_secret",
             "message": "Insert Exchange Secret",
-            "when": lambda x: not x['dry_run']
+            "when": lambda x: not x["dry_run"],
         },
         {
             "type": "password",
             "name": "exchange_key_password",
             "message": "Insert Exchange API Key password",
-            "when": lambda x: not x['dry_run'] and x['exchange_name'] in ('kucoin', 'okx')
+            "when": lambda x: not x["dry_run"] and x["exchange_name"] in ("kucoin", "okx"),
         },
         {
             "type": "confirm",
@@ -163,13 +166,13 @@ def ask_user_config() -> Dict[str, Any]:
             "type": "password",
             "name": "telegram_token",
             "message": "Insert Telegram token",
-            "when": lambda x: x['telegram']
+            "when": lambda x: x["telegram"],
         },
         {
             "type": "password",
             "name": "telegram_chat_id",
             "message": "Insert Telegram chat id",
-            "when": lambda x: x['telegram']
+            "when": lambda x: x["telegram"],
         },
         {
             "type": "confirm",
@@ -180,23 +183,25 @@ def ask_user_config() -> Dict[str, Any]:
         {
             "type": "text",
             "name": "api_server_listen_addr",
-            "message": ("Insert Api server Listen Address (0.0.0.0 for docker, "
-                        "otherwise best left untouched)"),
-            "default": "127.0.0.1" if not running_in_docker() else "0.0.0.0",
-            "when": lambda x: x['api_server']
+            "message": (
+                "Insert Api server Listen Address (0.0.0.0 for docker, "
+                "otherwise best left untouched)"
+            ),
+            "default": "127.0.0.1" if not running_in_docker() else "0.0.0.0",  # noqa: S104
+            "when": lambda x: x["api_server"],
         },
         {
             "type": "text",
             "name": "api_server_username",
             "message": "Insert api-server username",
             "default": "freqtrader",
-            "when": lambda x: x['api_server']
+            "when": lambda x: x["api_server"],
         },
         {
             "type": "password",
             "name": "api_server_password",
             "message": "Insert api-server password",
-            "when": lambda x: x['api_server']
+            "when": lambda x: x["api_server"],
         },
     ]
     answers = prompt(questions)
@@ -205,15 +210,11 @@ def ask_user_config() -> Dict[str, Any]:
         # Interrupted questionary sessions return an empty dict.
         raise OperationalException("User interrupted interactive questions.")
     # Ensure default is set for non-futures exchanges
-    answers['trading_mode'] = answers.get('trading_mode', "spot")
-    answers['margin_mode'] = (
-        'isolated'
-        if answers.get('trading_mode') == 'futures'
-        else ''
-    )
+    answers["trading_mode"] = answers.get("trading_mode", "spot")
+    answers["margin_mode"] = "isolated" if answers.get("trading_mode") == "futures" else ""
     # Force JWT token to be a random string
-    answers['api_server_jwt_key'] = secrets.token_hex()
-    answers['api_server_ws_token'] = secrets.token_urlsafe(25)
+    answers["api_server_jwt_key"] = secrets.token_hex()
+    answers["api_server_ws_token"] = secrets.token_urlsafe(25)
 
     return answers
 
@@ -225,26 +226,26 @@ def deploy_new_config(config_path: Path, selections: Dict[str, Any]) -> None:
     :param selections: Dict containing selections taken by the user.
     """
     from jinja2.exceptions import TemplateNotFound
+
     try:
         exchange_template = MAP_EXCHANGE_CHILDCLASS.get(
-            selections['exchange_name'], selections['exchange_name'])
+            selections["exchange_name"], selections["exchange_name"]
+        )
 
-        selections['exchange'] = render_template(
-            templatefile=f"subtemplates/exchange_{exchange_template}.j2",
-            arguments=selections
+        selections["exchange"] = render_template(
+            templatefile=f"subtemplates/exchange_{exchange_template}.j2", arguments=selections
         )
     except TemplateNotFound:
-        selections['exchange'] = render_template(
-            templatefile="subtemplates/exchange_generic.j2",
-            arguments=selections
+        selections["exchange"] = render_template(
+            templatefile="subtemplates/exchange_generic.j2", arguments=selections
         )
 
-    config_text = render_template(templatefile='base_config.json.j2',
-                                  arguments=selections)
+    config_text = render_template(templatefile="base_config.json.j2", arguments=selections)
 
     logger.info(f"Writing config to `{config_path}`.")
     logger.info(
-        "Please make sure to check the configuration contents and adjust settings to your needs.")
+        "Please make sure to check the configuration contents and adjust settings to your needs."
+    )
 
     config_path.write_text(config_text)
 
@@ -255,7 +256,7 @@ def start_new_config(args: Dict[str, Any]) -> None:
     Asking the user questions to fill out the template accordingly.
     """
 
-    config_path = Path(args['config'][0])
+    config_path = Path(args["config"][0])
     chown_user_directory(config_path.parent)
     if config_path.exists():
         overwrite = ask_user_overwrite(config_path)
@@ -264,22 +265,20 @@ def start_new_config(args: Dict[str, Any]) -> None:
         else:
             raise OperationalException(
                 f"Configuration file `{config_path}` already exists. "
-                "Please delete it or use a different configuration file name.")
+                "Please delete it or use a different configuration file name."
+            )
     selections = ask_user_config()
     deploy_new_config(config_path, selections)
 
 
 def start_show_config(args: Dict[str, Any]) -> None:
-
     config = setup_utils_configuration(args, RunMode.UTIL_EXCHANGE, set_dry=False)
 
-    # TODO: Sanitize from sensitive info before printing
-
     print("Your combined configuration is:")
     config_sanitized = sanitize_config(
-        config['original_config'],
-        show_sensitive=args.get('show_sensitive', False)
+        config["original_config"], show_sensitive=args.get("show_sensitive", False)
     )
 
     from rich import print_json
+
     print_json(data=config_sanitized)