Merge pull request #11945 from freqtrade/new_release

New release 2025.6

.github/workflows/ci.yml

@@ -25,7 +25,7 @@ jobs:
     strategy:
       matrix:
         os: [ "ubuntu-22.04", "ubuntu-24.04" ]
-        python-version: ["3.10", "3.11", "3.12"]
+        python-version: ["3.10", "3.11", "3.12", "3.13"]
 
     steps:
     - uses: actions/checkout@v4
@@ -38,7 +38,7 @@ jobs:
         python-version: ${{ matrix.python-version }}
 
     - name: Install uv
-      uses: astral-sh/setup-uv@f0ec1fc3b38f5e7cd731bb6ce540c5af426746bb # v6.1.0
+      uses: astral-sh/setup-uv@bd01e18f51369d5a26f1651c3cb451d3417e3bba # v6.3.1
       with:
         activate-environment: true
         enable-cache: true
@@ -90,6 +90,7 @@ jobs:
         COVERALLS_REPO_TOKEN: 6D1m0xupS3FgutfuGao8keFf9Hc0FpIXu
       run: |
         # Allow failure for coveralls
+        uv pip install coveralls
         coveralls || true
 
     - name: Run json schema extract
@@ -103,6 +104,8 @@ jobs:
         python build_helpers/create_command_partials.py
 
     - name: Check for repository changes
+      # TODO: python 3.13 slightly changed the output of argparse.
+      if: (matrix.python-version != '3.13')
       run: |
         if [ -n "$(git status --porcelain)" ]; then
           echo "Repository is dirty, changes detected:"
@@ -145,7 +148,7 @@ jobs:
         mypy freqtrade scripts tests
 
     - name: Discord notification
-      uses: rjstone/discord-webhook-notify@1399c1b2d57cc05894d506d2cfdc33c5f012b993 #v1.1.1
+      uses: rjstone/discord-webhook-notify@c2597273488aeda841dd1e891321952b51f7996f #v2.2.1
       if: failure() && ( github.event_name != 'pull_request' || github.event.pull_request.head.repo.fork == false)
       with:
           severity: error
@@ -156,8 +159,8 @@ jobs:
     runs-on: ${{ matrix.os }}
     strategy:
       matrix:
-        os: [ "macos-13", "macos-14", "macos-15" ]
-        python-version: ["3.10", "3.11", "3.12"]
+        os: [ "macos-14", "macos-15" ]
+        python-version: ["3.10", "3.11", "3.12", "3.13"]
 
     steps:
     - uses: actions/checkout@v4
@@ -171,7 +174,7 @@ jobs:
         check-latest: true
 
     - name: Install uv
-      uses: astral-sh/setup-uv@f0ec1fc3b38f5e7cd731bb6ce540c5af426746bb # v6.1.0
+      uses: astral-sh/setup-uv@bd01e18f51369d5a26f1651c3cb451d3417e3bba # v6.3.1
       with:
         activate-environment: true
         enable-cache: true
@@ -272,7 +275,7 @@ jobs:
         mypy freqtrade scripts
 
     - name: Discord notification
-      uses: rjstone/discord-webhook-notify@1399c1b2d57cc05894d506d2cfdc33c5f012b993 #v1.1.1
+      uses: rjstone/discord-webhook-notify@c2597273488aeda841dd1e891321952b51f7996f #v2.2.1
       if: failure() && ( github.event_name != 'pull_request' || github.event.pull_request.head.repo.fork == false)
       with:
           severity: info
@@ -285,7 +288,7 @@ jobs:
     strategy:
       matrix:
         os: [ windows-latest ]
-        python-version: ["3.10", "3.11", "3.12"]
+        python-version: ["3.10", "3.11", "3.12", "3.13"]
 
     steps:
     - uses: actions/checkout@v4
@@ -298,7 +301,7 @@ jobs:
         python-version: ${{ matrix.python-version }}
 
     - name: Install uv
-      uses: astral-sh/setup-uv@f0ec1fc3b38f5e7cd731bb6ce540c5af426746bb # v6.1.0
+      uses: astral-sh/setup-uv@bd01e18f51369d5a26f1651c3cb451d3417e3bba # v6.3.1
       with:
         activate-environment: true
         enable-cache: true
@@ -366,7 +369,7 @@ jobs:
       shell: powershell
 
     - name: Discord notification
-      uses: rjstone/discord-webhook-notify@1399c1b2d57cc05894d506d2cfdc33c5f012b993 #v1.1.1
+      uses: rjstone/discord-webhook-notify@c2597273488aeda841dd1e891321952b51f7996f #v2.2.1
       if: failure() && ( github.event_name != 'pull_request' || github.event.pull_request.head.repo.fork == false)
       with:
           severity: error
@@ -424,7 +427,7 @@ jobs:
         mkdocs build
 
     - name: Discord notification
-      uses: rjstone/discord-webhook-notify@1399c1b2d57cc05894d506d2cfdc33c5f012b993 #v1.1.1
+      uses: rjstone/discord-webhook-notify@c2597273488aeda841dd1e891321952b51f7996f #v2.2.1
       if: failure() && ( github.event_name != 'pull_request' || github.event.pull_request.head.repo.fork == false)
       with:
           severity: error
@@ -446,7 +449,7 @@ jobs:
         python-version: "3.12"
 
     - name: Install uv
-      uses: astral-sh/setup-uv@f0ec1fc3b38f5e7cd731bb6ce540c5af426746bb # v6.1.0
+      uses: astral-sh/setup-uv@bd01e18f51369d5a26f1651c3cb451d3417e3bba # v6.3.1
       with:
         activate-environment: true
         enable-cache: true
@@ -512,7 +515,7 @@ jobs:
         GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
 
     - name: Discord notification
-      uses: rjstone/discord-webhook-notify@1399c1b2d57cc05894d506d2cfdc33c5f012b993 #v1.1.1
+      uses: rjstone/discord-webhook-notify@c2597273488aeda841dd1e891321952b51f7996f #v2.2.1
       if: always() && steps.check.outputs.has-permission && ( github.event_name != 'pull_request' || github.event.pull_request.head.repo.fork == false)
       with:
           severity: info
@@ -616,100 +619,15 @@ jobs:
       uses: pypa/gh-action-pypi-publish@76f52bc884231f62b9a034ebfe128415bbaabdfc # v1.12.4
 
 
-  deploy-docker:
+  docker-build:
+    name: "Docker Build and Deploy"
     needs: [ build-linux, build-macos, build-windows, docs-check, mypy-version-check, pre-commit ]
-    runs-on: ubuntu-22.04
-
     if: (github.event_name == 'push' || github.event_name == 'schedule' || github.event_name == 'release') && github.repository == 'freqtrade/freqtrade'
-
-    steps:
-    - uses: actions/checkout@v4
-      with:
-        persist-credentials: false
-
-    - name: Set up Python
-      uses: actions/setup-python@v5
-      with:
-        python-version: "3.12"
-
-    - name: Extract branch name
-      id: extract-branch
-      run: |
-        echo "GITHUB_REF='${GITHUB_REF}'"
-        echo "branch=${GITHUB_REF##*/}" >> "$GITHUB_OUTPUT"
-
-    - name: Dockerhub login
-      env:
-        DOCKER_PASSWORD: ${{ secrets.DOCKER_PASSWORD }}
-        DOCKER_USERNAME: ${{ secrets.DOCKER_USERNAME }}
-      run: |
-        echo "${DOCKER_PASSWORD}" | docker login --username ${DOCKER_USERNAME} --password-stdin
-
-    # We need docker experimental to pull the ARM image.
-    - name: Switch docker to experimental
-      run: |
-          docker version -f '{{.Server.Experimental}}'
-          echo $'{\n    "experimental": true\n}' | sudo tee /etc/docker/daemon.json
-          sudo systemctl restart docker
-          docker version -f '{{.Server.Experimental}}'
-
-    - name: Set up QEMU
-      uses: docker/setup-qemu-action@29109295f81e9208d7d86ff1c6c12d2833863392 # v3.6.0
-
-    - name: Set up Docker Buildx
-      id: buildx
-      uses: docker/setup-buildx-action@b5ca514318bd6ebac0fb2aedd5d36ec1b5c232a2 #v3.10.0
-
-    - name: Available platforms
-      run: echo ${PLATFORMS}
-      env:
-        PLATFORMS: ${{ steps.buildx.outputs.platforms }}
-
-    - name: Build and test and push docker images
-      env:
-        BRANCH_NAME: ${{ steps.extract-branch.outputs.branch }}
-      run: |
-        build_helpers/publish_docker_multi.sh
-
-  deploy-arm:
-    name: "Deploy Docker"
+    uses: ./.github/workflows/docker-build.yml
     permissions:
       packages: write
-    needs: [ deploy-docker ]
-    # Only run on 64bit machines
-    runs-on: [self-hosted, linux, ARM64]
-    if: (github.event_name == 'push' || github.event_name == 'schedule' || github.event_name == 'release') && github.repository == 'freqtrade/freqtrade'
-
-    steps:
-    - uses: actions/checkout@v4
-      with:
-        persist-credentials: false
-
-    - name: Extract branch name
-      id: extract-branch
-      run: |
-        echo "GITHUB_REF='${GITHUB_REF}'"
-        echo "branch=${GITHUB_REF##*/}" >> "$GITHUB_OUTPUT"
-
-    - name: Dockerhub login
-      env:
-        DOCKER_PASSWORD: ${{ secrets.DOCKER_PASSWORD }}
-        DOCKER_USERNAME: ${{ secrets.DOCKER_USERNAME }}
-      run: |
-        echo "${DOCKER_PASSWORD}" | docker login --username ${DOCKER_USERNAME} --password-stdin
-
-    - name: Build and test and push docker images
-      env:
-        BRANCH_NAME: ${{ steps.extract-branch.outputs.branch }}
-        GHCR_USERNAME: ${{ github.actor }}
-        GHCR_TOKEN: ${{ secrets.GITHUB_TOKEN }}
-      run: |
-        build_helpers/publish_docker_arm64.sh
-
-    - name: Discord notification
-      uses: rjstone/discord-webhook-notify@1399c1b2d57cc05894d506d2cfdc33c5f012b993 #v1.1.1
-      if: always() && ( github.event_name != 'pull_request' || github.event.pull_request.head.repo.fork == false) && (github.event_name != 'schedule')
-      with:
-          severity: info
-          details: Deploy Succeeded!
-          webhookUrl: ${{ secrets.DISCORD_WEBHOOK }}
+      contents: read
+    secrets:
+      DOCKER_PASSWORD: ${{ secrets.DOCKER_PASSWORD }}
+      DOCKER_USERNAME: ${{ secrets.DOCKER_USERNAME }}
+      DISCORD_WEBHOOK: ${{ secrets.DISCORD_WEBHOOK }}

.github/workflows/docker-build.yml

@@ -0,0 +1,132 @@
+name: Docker Build and Deploy
+
+on:
+  workflow_call:
+    secrets:
+      DOCKER_PASSWORD:
+        required: true
+      DOCKER_USERNAME:
+        required: true
+      DISCORD_WEBHOOK:
+        required: false
+  workflow_dispatch:
+    inputs:
+      branch_name:
+        description: 'Branch name to build Docker images for'
+        required: false
+        default: 'develop'
+        type: string
+
+permissions:
+  contents: read
+
+jobs:
+  deploy-docker:
+    runs-on: ubuntu-22.04
+    if: github.repository == 'freqtrade/freqtrade'
+
+    steps:
+    - uses: actions/checkout@v4
+      with:
+        persist-credentials: false
+
+    - name: Set up Python
+      uses: actions/setup-python@v5
+      with:
+        python-version: "3.12"
+
+    - name: Extract branch name
+      id: extract-branch
+      env:
+        BRANCH_NAME_INPUT: ${{ github.event.inputs.branch_name }}
+      run: |
+        if [ "${{ github.event_name }}" = "workflow_dispatch" ]; then
+          BRANCH_NAME="${BRANCH_NAME_INPUT}"
+        else
+          BRANCH_NAME="${GITHUB_REF##*/}"
+        fi
+        echo "GITHUB_REF='${GITHUB_REF}'"
+        echo "branch=${BRANCH_NAME}" >> "$GITHUB_OUTPUT"
+
+    - name: Dockerhub login
+      env:
+        DOCKER_PASSWORD: ${{ secrets.DOCKER_PASSWORD }}
+        DOCKER_USERNAME: ${{ secrets.DOCKER_USERNAME }}
+      run: |
+        echo "${DOCKER_PASSWORD}" | docker login --username ${DOCKER_USERNAME} --password-stdin
+
+    # We need docker experimental to pull the ARM image.
+    - name: Switch docker to experimental
+      run: |
+          docker version -f '{{.Server.Experimental}}'
+          echo $'{\n    "experimental": true\n}' | sudo tee /etc/docker/daemon.json
+          sudo systemctl restart docker
+          docker version -f '{{.Server.Experimental}}'
+
+    - name: Set up QEMU
+      uses: docker/setup-qemu-action@29109295f81e9208d7d86ff1c6c12d2833863392 # v3.6.0
+
+    - name: Set up Docker Buildx
+      id: buildx
+      uses: docker/setup-buildx-action@e468171a9de216ec08956ac3ada2f0791b6bd435 #v3.11.1
+
+    - name: Available platforms
+      run: echo ${PLATFORMS}
+      env:
+        PLATFORMS: ${{ steps.buildx.outputs.platforms }}
+
+    - name: Build and test and push docker images
+      env:
+        BRANCH_NAME: ${{ steps.extract-branch.outputs.branch }}
+      run: |
+        build_helpers/publish_docker_multi.sh
+
+  deploy-arm:
+    name: "Deploy Docker"
+    permissions:
+      packages: write
+    needs: [ deploy-docker ]
+    # Only run on 64bit machines
+    runs-on: [self-hosted, linux, ARM64]
+    if: github.repository == 'freqtrade/freqtrade'
+
+    steps:
+    - uses: actions/checkout@v4
+      with:
+        persist-credentials: false
+
+    - name: Extract branch name
+      id: extract-branch
+      env:
+        BRANCH_NAME_INPUT: ${{ github.event.inputs.branch_name }}
+      run: |
+        if [ "${{ github.event_name }}" = "workflow_dispatch" ]; then
+          BRANCH_NAME="${BRANCH_NAME_INPUT}"
+        else
+          BRANCH_NAME="${GITHUB_REF##*/}"
+        fi
+        echo "GITHUB_REF='${GITHUB_REF}'"
+        echo "branch=${BRANCH_NAME}" >> "$GITHUB_OUTPUT"
+
+    - name: Dockerhub login
+      env:
+        DOCKER_PASSWORD: ${{ secrets.DOCKER_PASSWORD }}
+        DOCKER_USERNAME: ${{ secrets.DOCKER_USERNAME }}
+      run: |
+        echo "${DOCKER_PASSWORD}" | docker login --username ${DOCKER_USERNAME} --password-stdin
+
+    - name: Build and test and push docker images
+      env:
+        BRANCH_NAME: ${{ steps.extract-branch.outputs.branch }}
+        GHCR_USERNAME: ${{ github.actor }}
+        GHCR_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+      run: |
+        build_helpers/publish_docker_arm64.sh
+
+    - name: Discord notification
+      uses: rjstone/discord-webhook-notify@c2597273488aeda841dd1e891321952b51f7996f #v2.2.1
+      if: always() && ( github.event_name != 'pull_request' || github.event.pull_request.head.repo.fork == false) && (github.event_name != 'schedule')
+      with:
+          severity: info
+          details: Deploy Succeeded!
+          webhookUrl: ${{ secrets.DISCORD_WEBHOOK }}

.pre-commit-config.yaml

@@ -14,21 +14,21 @@ repos:
         additional_dependencies: ["python-rapidjson", "jsonschema"]
 
   - repo: https://github.com/pycqa/flake8
-    rev: "7.2.0"
+    rev: "7.3.0"
     hooks:
       - id: flake8
         additional_dependencies: [Flake8-pyproject]
         # stages: [push]
 
   - repo: https://github.com/pre-commit/mirrors-mypy
-    rev: "v1.15.0"
+    rev: "v1.16.1"
     hooks:
       - id: mypy
         exclude: build_helpers
         additional_dependencies:
           - types-cachetools==6.0.0.20250525
           - types-filelock==3.2.7
-          - types-requests==2.32.0.20250515
+          - types-requests==2.32.4.20250611
           - types-tabulate==0.9.0.20241207
           - types-python-dateutil==2.9.0.20250516
           - SQLAlchemy==2.0.41
@@ -43,7 +43,7 @@ repos:
 
   - repo: https://github.com/charliermarsh/ruff-pre-commit
     # Ruff version.
-    rev: 'v0.11.11'
+    rev: 'v0.12.1'
     hooks:
       - id: ruff
       - id: ruff-format
@@ -69,7 +69,7 @@ repos:
             )$
 
   - repo: https://github.com/stefmolin/exif-stripper
-    rev: 0.6.2
+    rev: 1.0.0
     hooks:
       - id: strip-exif
 
@@ -82,6 +82,6 @@ repos:
 
   # Ensure github actions remain safe
   - repo: https://github.com/woodruffw/zizmor-pre-commit
-    rev: v1.8.0
+    rev: v1.11.0
     hooks:
     - id: zizmor

Dockerfile

@@ -1,4 +1,4 @@
-FROM python:3.12.10-slim-bookworm as base
+FROM python:3.13.5-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<2.0" \
+RUN  pip install --user --no-cache-dir "numpy<3.0" \
   && pip install --user --no-cache-dir -r requirements-hyperopt.txt
 
 # Copy dependencies to runtime-image

README.md

@@ -70,7 +70,6 @@ Please find the complete documentation on the [freqtrade website](https://www.fr
 - [x] **Backtesting**: Run a simulation of your buy/sell strategy.
 - [x] **Strategy Optimization by machine learning**: Use machine learning to optimize your buy/sell strategy parameters with real exchange data.
 - [X] **Adaptive prediction modeling**: Build a smart strategy with FreqAI that self-trains to the market via adaptive machine learning methods. [Learn more](https://www.freqtrade.io/en/stable/freqai/)
-- [x] **Edge position sizing** Calculate your win rate, risk reward ratio, the best stoploss and adjust your position size before taking a position for each specific market. [Learn more](https://www.freqtrade.io/en/stable/edge/).
 - [x] **Whitelist crypto-currencies**: Select which crypto-currency you want to trade or use dynamic whitelists.
 - [x] **Blacklist crypto-currencies**: Select which crypto-currency you want to avoid.
 - [x] **Builtin WebUI**: Builtin web UI to manage your bot.
@@ -112,7 +111,6 @@ positional arguments:
     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

build_helpers/install_windows.ps1

@@ -3,7 +3,7 @@
 python -m pip install --upgrade pip
 python -c "import sys; print(f'{sys.version_info.major}.{sys.version_info.minor}')"
 
-pip install -U wheel "numpy<2"
+pip install -U wheel "numpy<3.0"
 pip install --only-binary ta-lib --find-links=build_helpers\ ta-lib
 
 pip install -r requirements-dev.txt

build_helpers/schema.json

@@ -538,10 +538,6 @@
       "description": "Exchange configuration.",
       "$ref": "#/definitions/exchange"
     },
-    "edge": {
-      "description": "Edge configuration.",
-      "$ref": "#/definitions/edge"
-    },
     "log_config": {
       "description": "Logging configuration.",
       "$ref": "#/definitions/logging"
@@ -1247,7 +1243,11 @@
           "type": "object"
         },
         "ccxt_async_config": {
-          "description": "CCXT asynchronous configuration settings.",
+          "description": "CCXT asynchronous configuration settings.Usually ccxt_config should be used instead.",
+          "type": "object"
+        },
+        "ccxt_sync_config": {
+          "description": "CCXT synchronous configuration settings. Usually ccxt_config should be used instead.",
           "type": "object"
         }
       },
@@ -1255,52 +1255,6 @@
         "name"
       ]
     },
-    "edge": {
-      "type": "object",
-      "properties": {
-        "enabled": {
-          "type": "boolean"
-        },
-        "process_throttle_secs": {
-          "type": "integer",
-          "minimum": 600
-        },
-        "calculate_since_number_of_days": {
-          "type": "integer"
-        },
-        "allowed_risk": {
-          "type": "number"
-        },
-        "stoploss_range_min": {
-          "type": "number"
-        },
-        "stoploss_range_max": {
-          "type": "number"
-        },
-        "stoploss_range_step": {
-          "type": "number"
-        },
-        "minimum_winrate": {
-          "type": "number"
-        },
-        "minimum_expectancy": {
-          "type": "number"
-        },
-        "min_trade_number": {
-          "type": "number"
-        },
-        "max_trade_duration_minute": {
-          "type": "integer"
-        },
-        "remove_pumps": {
-          "type": "boolean"
-        }
-      },
-      "required": [
-        "process_throttle_secs",
-        "allowed_risk"
-      ]
-    },
     "logging": {
       "type": "object",
       "properties": {

config_examples/config_binance.example.json

@@ -2,7 +2,7 @@
     "$schema": "https://schema.freqtrade.io/schema.json",
     "max_open_trades": 3,
     "stake_currency": "USDT",
-    "stake_amount": 0.05,
+    "stake_amount": 30,
     "tradable_balance_ratio": 0.99,
     "fiat_display_currency": "USD",
     "timeframe": "5m",

config_examples/config_full.example.json

@@ -121,20 +121,6 @@
         "outdated_offset": 5,
         "markets_refresh_interval": 60
     },
-    "edge": {
-        "enabled": false,
-        "process_throttle_secs": 3600,
-        "calculate_since_number_of_days": 7,
-        "allowed_risk": 0.01,
-        "stoploss_range_min": -0.01,
-        "stoploss_range_max": -0.1,
-        "stoploss_range_step": -0.01,
-        "minimum_winrate": 0.60,
-        "minimum_expectancy": 0.20,
-        "min_trade_number": 10,
-        "max_trade_duration_minute": 1440,
-        "remove_pumps": false
-    },
     "telegram": {
         "enabled": false,
         "token": "your_telegram_token",

docker/Dockerfile.armhf

@@ -1,4 +1,4 @@
-FROM python:3.11.12-slim-bookworm as base
+FROM python:3.11.13-slim-bookworm as base
 
 # Setup env
 ENV LANG C.UTF-8
@@ -34,7 +34,7 @@ COPY build_helpers/* /tmp/
 # Install dependencies
 COPY --chown=ftuser:ftuser requirements.txt /freqtrade/
 USER ftuser
-RUN  pip install --user --no-cache-dir "numpy<2" \
+RUN  pip install --user --no-cache-dir "numpy<3.0" \
   && pip install --user --no-index --find-links /tmp/ pyarrow TA-Lib \
   && pip install --user --no-cache-dir -r requirements.txt
 

docs/backtesting.md

@@ -5,6 +5,8 @@ This page explains how to validate your strategy performance by using Backtestin
 Backtesting requires historic data to be available.
 To learn how to get data for the pairs and exchange you're interested in, head over to the [Data Downloading](data-download.md) section of the documentation.
 
+Backtesting is also available in [webserver mode](freq-ui.md#backtesting), which allows you to run backtests via the web interface.
+
 ## Backtesting command reference
 
 --8<-- "commands/backtesting.md"
@@ -435,6 +437,10 @@ To save time, by default backtest will reuse a cached result from within the las
 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.
 
+Also, you can use freqtrade in [webserver mode](freq-ui.md#backtesting) to visualize the backtest results in a web interface.
+This mode also allows you to load existing backtest results, so you can analyze them without running the backtest again.  
+For this mode - `--notes "<notes>"` can be used to add notes to the backtest results, which will be shown in the web interface.
+
 ### Backtest output file
 
 The output file freqtrade produces is a zip file containing the following files:

docs/commands/backtesting.md

@@ -17,7 +17,7 @@ usage: freqtrade backtesting [-h] [-v] [--no-color] [--logfile FILE] [-V]
                              [--export-filename PATH]
                              [--breakdown {day,week,month,year} [{day,week,month,year} ...]]
                              [--cache {none,day,week,month}]
-                             [--freqai-backtest-live-models]
+                             [--freqai-backtest-live-models] [--notes TEXT]
 
 options:
   -h, --help            show this help message and exit
@@ -73,6 +73,7 @@ options:
                         age (default: day).
   --freqai-backtest-live-models
                         Run backtest with ready models.
+  --notes TEXT          Add notes to the backtest results.
 
 Common arguments:
   -v, --verbose         Verbose mode (-vv for more, -vvv to get all messages).

docs/commands/edge.md

@@ -7,7 +7,6 @@ usage: freqtrade edge [-h] [-v] [--no-color] [--logfile FILE] [-V] [-c PATH]
                       [--data-format-ohlcv {json,jsongz,feather,parquet}]
                       [--max-open-trades INT] [--stake-amount STAKE_AMOUNT]
                       [--fee FLOAT] [-p PAIRS [PAIRS ...]]
-                      [--stoplosses STOPLOSS_RANGE]
 
 options:
   -h, --help            show this help message and exit
@@ -29,11 +28,6 @@ options:
   -p PAIRS [PAIRS ...], --pairs PAIRS [PAIRS ...]
                         Limit command to these pairs. Pairs are space-
                         separated.
-  --stoplosses STOPLOSS_RANGE
-                        Defines a range of stoploss values against which edge
-                        will assess the strategy. The format is "min,max,step"
-                        (without any space). Example:
-                        `--stoplosses=-0.01,-0.1,-0.001`
 
 Common arguments:
   -v, --verbose         Verbose mode (-vv for more, -vvv to get all messages).

docs/commands/main.md

@@ -22,7 +22,7 @@ positional arguments:
     backtesting-show    Show past Backtest results
     backtesting-analysis
                         Backtest Analysis module.
-    edge                Edge module.
+    edge                Edge module. No longer part of Freqtrade
     hyperopt            Hyperopt module.
     hyperopt-list       List Hyperopt results
     hyperopt-show       Show details of Hyperopt results

docs/configuration.md

@@ -234,7 +234,6 @@ Mandatory parameters are marked as **Required**, which means that they are requi
 | `exchange.only_from_ccxt` | Prevent data-download from data.binance.vision. Leaving this as false can greatly speed up downloads, but may be problematic if the site is not available.<br>*Defaults to `false`*<br> **Datatype:** Boolean
 | `experimental.block_bad_exchanges` | Block exchanges known to not work with freqtrade. Leave on default unless you want to test if that exchange works now. <br>*Defaults to `true`.* <br> **Datatype:** Boolean
 | | **Plugins**
-| `edge.*` | Please refer to [edge configuration document](edge.md) for detailed explanation of all possible configuration options.
 | `pairlists` | Define one or more pairlists to be used. [More information](plugins.md#pairlists-and-pairlist-handlers). <br>*Defaults to `StaticPairList`.*  <br> **Datatype:** List of Dicts
 | | **Telegram**
 | `telegram.enabled` | Enable the usage of Telegram. <br> **Datatype:** Boolean

docs/deprecated.md

@@ -93,3 +93,8 @@ Please use the [`convert-data` subcommand](data-download.md#sub-command-convert-
 
 Configuring syslog and journald via `--logfile systemd` and `--logfile journald` respectively has been deprecated in 2025.3.
 Please use configuration based [log setup](advanced-setup.md#advanced-logging) instead.
+
+## Removal of the edge module
+
+The edge module has been deprecated in 2023.9 and removed in 2025.6.
+All functionalities of edge have been removed, and having edge configured will result in an error.

docs/developer.md

@@ -304,6 +304,13 @@ The `IProtection` parent class provides a helper method for this in `calculate_l
 
 Most exchanges supported by CCXT should work out of the box.
 
+If you need to implement a specific exchange class, these are found in the `freqtrade/exchange` source folder. You'll also need to add the import to `freqtrade/exchange/__init__.py` to make the loading logic aware of the new exchange.  
+We recommend looking at existing exchange implementations to get an idea of what might be required.
+
+!!! Warning
+    Implementing and testing an exchange can be a lot of trial and error, so please bear this in mind.
+    You should also have some development experience, as this is not a beginner task.
+
 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).
 

docs/edge.md

@@ -1,300 +0,0 @@
-# Edge positioning
-
-The `Edge Positioning` module uses probability to calculate your win rate and risk reward ratio. It will use these statistics to control your strategy trade entry points, position size and, stoploss.
-
-!!! Danger "Deprecated functionality"
-    `Edge positioning` (or short Edge) is currently in maintenance mode only (we keep existing functionality alive) and should be considered as deprecated.
-    It will currently not receive new features until either someone stepped forward to take up ownership of that module - or we'll decide to remove edge from freqtrade.
-
-!!! Warning
-    When using `Edge positioning` with a dynamic whitelist (VolumePairList), make sure to also use `AgeFilter` and set it to at least `calculate_since_number_of_days` to avoid problems with missing data.
-
-!!! Note
-    `Edge Positioning` only considers *its own* buy/sell/stoploss signals. It ignores the stoploss, trailing stoploss, and ROI settings in the strategy configuration file.
-    `Edge Positioning` improves the performance of some trading strategies and *decreases* the performance of others.
-
-
-## Introduction
-
-Trading strategies are not perfect. They are frameworks that are susceptible to the market and its indicators. Because the market is not at all predictable, sometimes a strategy will win and sometimes the same strategy will lose.
-
-To obtain an edge in the market, a strategy has to make more money than it loses. Making money in trading is not only about *how often* the strategy makes or loses money.
-
-!!! tip "It doesn't matter how often, but how much!"
-    A bad strategy might make 1 penny in *ten* transactions but lose 1 dollar in *one* transaction. If one only checks the number of winning trades, it would be misleading to think that the strategy is actually making a profit.
-
-The Edge Positioning module seeks to improve a strategy's winning probability and the money that the strategy will make *on the long run*. 
-
-We raise the following question[^1]:
-
-!!! Question "Which trade is a better option?"
-    a) A trade with 80% of chance of losing 100\$ and 20% chance of winning 200\$<br/>
-    b) A trade with 100% of chance of losing 30\$
-
-???+ Info "Answer"
-    The expected value of *a)* is smaller than the expected value of *b)*.<br/>
-    Hence, *b*) represents a smaller loss in the long run.<br/>
-    However, the answer is: *it depends*
-
-Another way to look at it is to ask a similar question:
-
-!!! Question "Which trade is a better option?"
-    a) A trade with 80% of chance of winning 100\$ and 20% chance of losing 200\$<br/>
-    b) A trade with 100% of chance of winning 30\$
-
-Edge positioning tries to answer the hard questions about risk/reward and position size automatically, seeking to minimizes the chances of losing of a given strategy.
-
-### Trading, winning and losing
-
-Let's call $o$ the return of a single transaction $o$ where $o \in \mathbb{R}$. The collection $O = \{o_1, o_2, ..., o_N\}$ is the set of all returns of transactions made during a trading session. We say that $N$ is the cardinality of $O$, or, in lay terms, it is the number of transactions made in a trading session.
-
-!!! Example
-    In a session where a strategy made three transactions we can say that $O = \{3.5, -1, 15\}$. That means that $N = 3$ and $o_1 = 3.5$, $o_2 = -1$, $o_3 = 15$.
-
-A winning trade is a trade where a strategy *made* money. Making money means that the strategy closed the position in a value that returned a profit, after all deducted fees. Formally, a winning trade will have a return $o_i > 0$. Similarly, a losing trade will have a return $o_j \leq 0$. With that, we can discover the set of all winning trades, $T_{win}$, as follows:
-
-$$ T_{win} = \{ o \in O | o > 0 \} $$
-
-Similarly, we can discover the set of losing trades $T_{lose}$ as follows:
-
-$$ T_{lose} = \{o \in O | o \leq 0\} $$
-
-!!! Example
-    In a section where a strategy made four transactions $O = \{3.5, -1, 15, 0\}$:<br>
-    $T_{win} = \{3.5, 15\}$<br>
-    $T_{lose} = \{-1, 0\}$<br>
-
-### Win Rate and Lose Rate
-
-The win rate $W$ is the proportion of winning trades with respect to all the trades made by a strategy. We use the following function to compute the win rate:
-
-$$W = \frac{|T_{win}|}{N}$$
-
-Where $W$ is the win rate, $N$ is the number of trades and, $T_{win}$ is the set of all trades where the strategy made money.
-
-Similarly, we can compute the rate of losing trades:
-
-$$ 
-    L = \frac{|T_{lose}|}{N} 
-$$
-
-Where $L$ is the lose rate, $N$ is the amount of trades made and, $T_{lose}$ is the set of all trades where the strategy lost money. Note that the above formula is the same as calculating $L = 1 – W$ or $W = 1 – L$
-
-### Risk Reward Ratio
-
-Risk Reward Ratio ($R$) is a formula used to measure the expected gains of a given investment against the risk of loss. It is basically what you potentially win divided by what you potentially lose. Formally:
-
-$$ R = \frac{\text{potential_profit}}{\text{potential_loss}} $$
-
-???+ Example "Worked example of $R$ calculation"
-    Let's say that you think that the price of *stonecoin* today is 10.0\$. You believe that, because they will start mining stonecoin, it will go up to 15.0\$ tomorrow. There is the risk that the stone is too hard, and the GPUs can't mine it, so the price might go to 0\$ tomorrow. You are planning to invest 100\$, which will give you 10 shares (100 / 10).
-
-    Your potential profit is calculated as:
-
-    $\begin{aligned} 
-        \text{potential_profit} &= (\text{potential_price} - \text{entry_price}) * \frac{\text{investment}}{\text{entry_price}} \\
-                                &= (15 - 10) * (100 / 10) \\
-                                &= 50
-    \end{aligned}$
-
-    Since the price might go to 0\$, the 100\$ dollars invested could turn into 0.
-
-    We do however use a stoploss of 15% - so in the worst case, we'll sell 15% below entry price (or at 8.5$\).
-
-    $\begin{aligned}
-        \text{potential_loss} &= (\text{entry_price} - \text{stoploss}) * \frac{\text{investment}}{\text{entry_price}} \\
-                                &= (10 - 8.5) * (100 / 10)\\
-                                &= 15
-    \end{aligned}$
-
-    We can compute the Risk Reward Ratio as follows:
-
-    $\begin{aligned}
-        R   &= \frac{\text{potential_profit}}{\text{potential_loss}}\\
-            &= \frac{50}{15}\\
-            &= 3.33
-    \end{aligned}$<br>
-    What it effectively means is that the strategy have the potential to make 3.33\$ for each 1\$ invested.
-
-On a long horizon, that is, on many trades, we can calculate the risk reward by dividing the strategy' average profit on winning trades by the strategy' average loss on losing trades. We can calculate the average profit, $\mu_{win}$, as follows:
-
-$$ \text{average_profit} = \mu_{win} = \frac{\text{sum_of_profits}}{\text{count_winning_trades}} = \frac{\sum^{o \in T_{win}} o}{|T_{win}|} $$
-
-Similarly, we can calculate the average loss, $\mu_{lose}$, as follows:
-
-$$ \text{average_loss} = \mu_{lose} = \frac{\text{sum_of_losses}}{\text{count_losing_trades}} = \frac{\sum^{o \in T_{lose}} o}{|T_{lose}|} $$
-
-Finally, we can calculate the Risk Reward ratio, $R$, as follows:
-
-$$ R = \frac{\text{average_profit}}{\text{average_loss}} = \frac{\mu_{win}}{\mu_{lose}}\\ $$
-
-
-???+ Example "Worked example of $R$ calculation using mean profit/loss"
-    Let's say the strategy that we are using makes an average win $\mu_{win} = 2.06$ and an average loss $\mu_{loss} = 4.11$.<br>
-    We calculate the risk reward ratio as follows:<br>
-    $R = \frac{\mu_{win}}{\mu_{loss}} = \frac{2.06}{4.11} = 0.5012...$
-    
-
-### Expectancy
-
-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:
-
-$$E = R * W - L$$
-
-!!! Example "Calculating $E$"
-    Let's say that a strategy has a win rate $W = 0.28$ and a risk reward ratio $R = 5$. What this means is that the strategy is expected to make 5 times the investment around on 28% of the trades it makes. Working out the example:<br>
-    $E = R * W - L = 5 * 0.28 - 0.72 = 0.68$
-    <br>
-
-The expectancy worked out in the example above means that, on average, this strategy' trades will return 1.68 times the size of its losses. Said another way, the strategy makes 1.68\$ for every 1\$ it loses, on average. 
-
-This is important for two reasons: First, it may seem obvious, but you know right away that you have a positive return. Second, you now have a number you can compare to other candidate systems to make decisions about which ones you employ.
-
-It is important to remember that any system with an expectancy greater than 0 is profitable using past data. The key is finding one that will be profitable in the future.
-
-You can also use this value to evaluate the effectiveness of modifications to this system.
-
-!!! Note
-    It's important to keep in mind that Edge is testing your expectancy using historical data, there's no guarantee that you will have a similar edge in the future. It's still vital to do this testing in order to build confidence in your methodology but be wary of "curve-fitting" your approach to the historical data as things are unlikely to play out the exact same way for future trades.
-
-## How does it work?
-
-Edge combines dynamic stoploss, dynamic positions, and whitelist generation into one isolated module which is then applied to the trading strategy. If enabled in config, Edge will go through historical data with a range of stoplosses in order to find buy and sell/stoploss signals. It then calculates win rate and expectancy over *N* trades for each stoploss. Here is an example:
-
-| Pair   |      Stoploss      |  Win Rate | Risk Reward Ratio | Expectancy |
-|----------|:-------------:|-------------:|------------------:|-----------:|
-| XZC/ETH  |  -0.01        |   0.50       |1.176384           | 0.088      |
-| XZC/ETH  |  -0.02        |   0.51       |1.115941           | 0.079      |
-| XZC/ETH  |  -0.03        |   0.52       |1.359670           | 0.228      |
-| XZC/ETH  |  -0.04        |   0.51       |1.234539           | 0.117      |
-
-The goal here is to find the best stoploss for the strategy in order to have the maximum expectancy. In the above example stoploss at $3%$ leads to the maximum expectancy according to historical data.
-
-Edge module then forces stoploss value it evaluated to your strategy dynamically.
-
-### Position size
-
-Edge dictates the amount at stake for each trade to the bot according to the following factors:
-
-- Allowed capital at risk
-- Stoploss
-
-Allowed capital at risk is calculated as follows:
-
-```
-Allowed capital at risk = (Capital available_percentage) X (Allowed risk per trade)
-```
-
-Stoploss is calculated as described above with respect to historical data.
-
-The position size is calculated as follows:
-
-```
-Position size = (Allowed capital at risk) / Stoploss
-```
-
-Example:
-
-Let's say the stake currency is **ETH** and there is $10$ **ETH** on the wallet. The capital available percentage is $50%$ and the allowed risk per trade is $1\%$. Thus, the available capital for trading is $10 * 0.5 = 5$ **ETH** and the allowed capital at risk would be $5 * 0.01 = 0.05$ **ETH**.
-
--   **Trade 1:** The strategy detects a new buy signal in the **XLM/ETH** market. `Edge Positioning` calculates a stoploss of $2\%$ and a position of $0.05 / 0.02 = 2.5$ **ETH**. The bot takes a position of $2.5$ **ETH** in the **XLM/ETH** market.
-
--   **Trade 2:** The strategy detects a buy signal on the **BTC/ETH** market while **Trade 1** is still open. `Edge Positioning` calculates the stoploss of $4\%$ on this market. Thus, **Trade 2** position size is $0.05 / 0.04 = 1.25$ **ETH**.
-
-!!! Tip "Available Capital $\neq$ Available in wallet"
-    The available capital for trading didn't change in **Trade 2** even with **Trade 1** still open. The available capital **is not** the free amount in the wallet.
-
--   **Trade 3:** The strategy detects a buy signal in the **ADA/ETH** market. `Edge Positioning` calculates a stoploss of $1\%$ and a position of $0.05 / 0.01 = 5$ **ETH**. Since **Trade 1** has $2.5$ **ETH** blocked and **Trade 2** has $1.25$ **ETH** blocked, there is only $5 - 1.25 - 2.5 = 1.25$ **ETH** available. Hence, the position size of **Trade 3** is $1.25$ **ETH**. 
-
-!!! Tip "Available Capital Updates"
-    The available capital does not change before a position is sold. After a trade is closed the Available Capital goes up if the trade was profitable or goes down if the trade was a loss.
-
--   The strategy detects a sell signal in the **XLM/ETH** market. The bot exits **Trade 1** for a profit of $1$ **ETH**. The total capital in the wallet becomes $11$ **ETH** and the available capital for trading becomes $5.5$ **ETH**.
-
--   **Trade 4** The strategy detects a new buy signal int the **XLM/ETH** market. `Edge Positioning` calculates the stoploss of $2\%$, and the position size of $0.055 / 0.02 = 2.75$ **ETH**.
-
-## Edge command reference
-
---8<-- "commands/edge.md"
-
-## Configurations
-
-Edge module has following configuration options:
-
-|  Parameter | Description |
-|------------|-------------|
-| `enabled` | If true, then Edge will run periodically. <br>*Defaults to `false`.* <br> **Datatype:** Boolean
-| `process_throttle_secs` | How often should Edge run in seconds. <br>*Defaults to `3600` (once per hour).* <br> **Datatype:** Integer
-| `calculate_since_number_of_days` | Number of days of data against which Edge calculates Win Rate, Risk Reward and Expectancy. <br> **Note** that it downloads historical data so increasing this number would lead to slowing down the bot. <br>*Defaults to `7`.* <br> **Datatype:** Integer
-| `allowed_risk` | Ratio of allowed risk per trade. <br>*Defaults to `0.01` (1%)).* <br> **Datatype:** Float
-| `stoploss_range_min` | Minimum stoploss. <br>*Defaults to `-0.01`.* <br> **Datatype:** Float
-| `stoploss_range_max` | Maximum stoploss. <br>*Defaults to `-0.10`.* <br> **Datatype:** Float
-| `stoploss_range_step` | As an example if this is set to -0.01 then Edge will test the strategy for `[-0.01, -0,02, -0,03 ..., -0.09, -0.10]` ranges. <br> **Note** than having a smaller step means having a bigger range which could lead to slow calculation. <br> If you set this parameter to -0.001, you then slow down the Edge calculation by a factor of 10. <br>*Defaults to `-0.001`.* <br> **Datatype:** Float
-| `minimum_winrate` | It filters out pairs which don't have at least minimum_winrate. <br>This comes handy if you want to be conservative and don't comprise win rate in favour of risk reward ratio. <br>*Defaults to `0.60`.* <br> **Datatype:** Float
-| `minimum_expectancy` | It filters out pairs which have the expectancy lower than this number. <br>Having an expectancy of 0.20 means if you put 10\$ on a trade you expect a 12\$ return. <br>*Defaults to `0.20`.* <br> **Datatype:** Float
-| `min_trade_number` | When calculating *W*, *R* and *E* (expectancy) against historical data, you always want to have a minimum number of trades. The more this number is the more Edge is reliable. <br>Having a win rate of 100% on a single trade doesn't mean anything at all. But having a win rate of 70% over past 100 trades means clearly something. <br>*Defaults to `10` (it is highly recommended not to decrease this number).* <br> **Datatype:** Integer
-| `max_trade_duration_minute` | Edge will filter out trades with long duration. If a trade is profitable after 1 month, it is hard to evaluate the strategy based on it. But if most of trades are profitable and they have maximum duration of 30 minutes, then it is clearly a good sign.<br>**NOTICE:** While configuring this value, you should take into consideration your timeframe. As an example filtering out trades having duration less than one day for a strategy which has 4h interval does not make sense. Default value is set assuming your strategy interval is relatively small (1m or 5m, etc.).<br>*Defaults to `1440` (one day).* <br> **Datatype:** Integer
-| `remove_pumps` | Edge will remove sudden pumps in a given market while going through historical data. However, given that pumps happen very often in crypto markets, we recommend you keep this off.<br>*Defaults to `false`.* <br> **Datatype:** Boolean
-
-## Running Edge independently
-
-You can run Edge independently in order to see in details the result. Here is an example:
-
-``` bash
-freqtrade edge
-```
-
-An example of its output:
-
-| **pair**     |   **stoploss** |   **win rate** |   **risk reward ratio** |   **required risk reward** |   **expectancy** |   **total number of trades** |   **average duration (min)** |
-|:----------|-----------:|-----------:|--------------------:|-----------------------:|-------------:|-----------------:|---------------:|
-| **AGI/BTC**   |      -0.02 |       0.64 |                5.86 |                   0.56 |         3.41 |                       14 |                       54 |
-| **NXS/BTC**   |      -0.03 |       0.64 |                2.99 |                   0.57 |         1.54 |                       11 |                       26 |
-| **LEND/BTC**  |      -0.02 |       0.82 |                2.05 |                   0.22 |         1.50 |                       11 |                       36 |
-| **VIA/BTC**   |      -0.01 |       0.55 |                3.01 |                   0.83 |         1.19 |                       11 |                       48 |
-| **MTH/BTC**   |      -0.09 |       0.56 |                2.82 |                   0.80 |         1.12 |                       18 |                       52 |
-| **ARDR/BTC**  |      -0.04 |       0.42 |                3.14 |                   1.40 |         0.73 |                       12 |                       42 |
-| **BCPT/BTC**  |      -0.01 |       0.71 |                1.34 |                   0.40 |         0.67 |                       14 |                       30 |
-| **WINGS/BTC** |      -0.02 |       0.56 |                1.97 |                   0.80 |         0.65 |                       27 |                       42 |
-| **VIBE/BTC**  |      -0.02 |       0.83 |                0.91 |                   0.20 |         0.59 |                       12 |                       35 |
-| **MCO/BTC**   |      -0.02 |       0.79 |                0.97 |                   0.27 |         0.55 |                       14 |                       31 |
-| **GNT/BTC**   |      -0.02 |       0.50 |                2.06 |                   1.00 |         0.53 |                       18 |                       24 |
-| **HOT/BTC**   |      -0.01 |       0.17 |                7.72 |                   4.81 |         0.50 |                      209 |                        7 |
-| **SNM/BTC**   |      -0.03 |       0.71 |                1.06 |                   0.42 |         0.45 |                       17 |                       38 |
-| **APPC/BTC**  |      -0.02 |       0.44 |                2.28 |                   1.27 |         0.44 |                       25 |                       43 |
-| **NEBL/BTC**  |      -0.03 |       0.63 |                1.29 |                   0.58 |         0.44 |                       19 |                       59 |
-
-Edge produced the above table by comparing `calculate_since_number_of_days` to `minimum_expectancy` to find `min_trade_number` historical information based on the config file. The timerange Edge uses for its comparisons can be further limited by using the `--timerange` switch.
-
-In live and dry-run modes, after the `process_throttle_secs` has passed, Edge will again process `calculate_since_number_of_days` against `minimum_expectancy` to find `min_trade_number`. If no `min_trade_number` is found, the bot will return "whitelist empty". Depending on the trade strategy being deployed, "whitelist empty" may be return much of the time - or *all* of the time. The use of Edge may also cause trading to occur in bursts, though this is rare.
-
-If you encounter "whitelist empty" a lot, condsider tuning `calculate_since_number_of_days`, `minimum_expectancy`  and `min_trade_number` to align to the trading frequency of your strategy.
-
-### Update cached pairs with the latest data
-
-Edge requires historic data the same way as backtesting does.
-Please refer to the [Data Downloading](data-download.md) section of the documentation for details.
-
-### Precising stoploss range
-
-```bash
-freqtrade edge --stoplosses=-0.01,-0.1,-0.001 #min,max,step
-```
-
-### Advanced use of timerange
-
-```bash
-freqtrade edge --timerange=20181110-20181113
-```
-
-Doing `--timerange=-20190901` will get all available data until September 1st (excluding September 1st 2019).
-
-The full timerange specification:
-
-* Use tickframes till 2018/01/31: `--timerange=-20180131`
-* Use tickframes since 2018/01/31: `--timerange=20180131-`
-* Use tickframes since 2018/01/31 till 2018/03/01 : `--timerange=20180131-20180301`
-* Use tickframes between POSIX timestamps 1527595200 1527618600: `--timerange=1527595200-1527618600`
-
-
-[^1]: Question extracted from MIT Opencourseware S096 - Mathematics with applications in Finance: https://ocw.mit.edu/courses/mathematics/18-s096-topics-in-mathematics-with-applications-in-finance-fall-2013/

docs/faq.md

@@ -276,20 +276,6 @@ Example: 4% profit 650 times vs 0,3% profit a trade 10000 times in a year. If we
 Example:
 `freqtrade --config config.json --strategy SampleStrategy --hyperopt SampleHyperopt -e 1000 --timerange 20190601-20200601`
 
-## Edge module
-
-### Edge implements interesting approach for controlling position size, is there any theory behind it?
-
-The Edge module is mostly a result of brainstorming of [@mishaker](https://github.com/mishaker) and [@creslinux](https://github.com/creslinux) freqtrade team members.
-
-You can find further info on expectancy, win rate, risk management and position size in the following sources:
-
-- https://www.tradeciety.com/ultimate-math-guide-for-traders/
-- https://samuraitradingacademy.com/trading-expectancy/
-- https://www.learningmarkets.com/determining-expectancy-in-your-trading/
-- https://www.lonestocktrader.com/make-money-trading-positive-expectancy/
-- https://www.babypips.com/trading/trade-expectancy-matter
-
 ## Official channels
 
 Freqtrade is using exclusively the following official channels:

docs/index.md

@@ -5,10 +5,10 @@
 [![Coverage Status](https://coveralls.io/repos/github/freqtrade/freqtrade/badge.svg?branch=develop&service=github)](https://coveralls.io/github/freqtrade/freqtrade?branch=develop)
 [![Maintainability](https://api.codeclimate.com/v1/badges/5737e6d668200b7518ff/maintainability)](https://codeclimate.com/github/freqtrade/freqtrade/maintainability)
 
-<!-- Place this tag where you want the button to render. -->
-<a class="github-button" href="https://github.com/freqtrade/freqtrade" data-icon="octicon-star" data-size="large" aria-label="Star freqtrade/freqtrade on GitHub">Star</a>
-<a class="github-button" href="https://github.com/freqtrade/freqtrade/fork" data-icon="octicon-repo-forked" data-size="large" aria-label="Fork freqtrade/freqtrade on GitHub">Fork</a>
-<a class="github-button" href="https://github.com/freqtrade/freqtrade/archive/stable.zip" data-icon="octicon-cloud-download" data-size="large" aria-label="Download freqtrade/freqtrade on GitHub">Download</a>
+<!-- GitHub action buttons -->
+[:octicons-star-16: Star](https://github.com/freqtrade/freqtrade){ .md-button .md-button--sm }
+[:octicons-repo-forked-16: Fork](https://github.com/freqtrade/freqtrade/fork){ .md-button .md-button--sm }
+[:octicons-download-16: Download](https://github.com/freqtrade/freqtrade/archive/stable.zip){ .md-button .md-button--sm }
 
 ## Introduction
 
@@ -31,7 +31,6 @@ Freqtrade is a free and open source crypto trading bot written in Python. It is
 - Optimize: Find the best parameters for your strategy using hyperoptimization which employs machine learning methods. You can optimize buy, sell, take profit (ROI), stop-loss and trailing stop-loss parameters for your strategy.
 - Select markets: Create your static list or use an automatic one based on top traded volumes and/or prices (not available during backtesting). You can also explicitly blacklist markets you don't want to trade.
 - Run: Test your strategy with simulated money (Dry-Run mode) or deploy it with real money (Live-Trade mode).
-- Run using Edge (optional module): The concept is to find the best historical [trade expectancy](edge.md#expectancy) by markets based on variation of the stop-loss and then allow/reject markets to trade. The sizing of the trade is based on a risk of a percentage of your capital.
 - Control/Monitor: Use Telegram or a WebUI (start/stop the bot, show profit/loss, daily summary, current open trades results, etc.).
 - Analyze: Further analysis can be performed on either Backtesting data or Freqtrade trading history (SQL database), including automated standard plots, and methods to load the data into [interactive environments](data-analysis.md).
 

docs/overrides/main.html

@@ -37,7 +37,6 @@
     {{ super() }}
 
     <!-- Place this tag in your head or just before your close body tag. -->
-    <script async defer src="https://buttons.github.io/buttons.js"></script>
     <script src="https://code.jquery.com/jquery-3.4.1.min.js"
       integrity="sha256-CSXorXvZcTkaix6Yvo6HppcZGetbYMGWSFlBw8HfCJo=" crossorigin="anonymous"></script>
 

docs/requirements-docs.txt

@@ -1,7 +1,7 @@
-markdown==3.8
+markdown==3.8.2
 mkdocs==1.6.1
 mkdocs-material==9.6.14
 mdx_truly_sane_lists==1.3
-pymdown-extensions==10.15
+pymdown-extensions==10.16
 jinja2==3.1.6
 mike==2.1.3

docs/rest-api.md

@@ -190,9 +190,6 @@ delete_trade
 
         :param trade_id: Deletes the trade with this ID from the database.
 
-edge
-	Return information about edge.
-
 forcebuy
 	Buy an asset.
 
@@ -368,7 +365,6 @@ All endpoints in the below table need to be prefixed with the base URL of the AP
 | `/blacklist` | GET | Show the current blacklist.
 | `/blacklist` | POST | Adds the specified pair to the blacklist.<br/>*Params:*<br/>- `pair` (`str`)
 | `/blacklist` | DELETE | Deletes the specified list of pairs from the blacklist.<br/>*Params:*<br/>- `[pair,pair]` (`list[str]`) 
-| `/edge` | GET | Show validated pairs by Edge if it is enabled.
 | `/pair_candles` | GET | Returns dataframe for a pair / timeframe combination while the bot is running. **Alpha**
 | `/pair_candles` | POST | Returns dataframe for a pair / timeframe combination while the bot is running, filtered by a provided list of columns to return. **Alpha**<br/>*Params:*<br/>- `<column_list>` (`list[str]`)
 | `/pair_history` | GET | Returns an analyzed dataframe for a given timerange, analyzed by a given strategy. **Alpha**

docs/stoploss.md

@@ -256,4 +256,4 @@ The new stoploss value will be applied to open trades (and corresponding log-mes
 
 ### Limitations
 
-Stoploss values cannot be changed if `trailing_stop` is enabled and the stoploss has already been adjusted, or if [Edge](edge.md) is enabled (since Edge would recalculate stoploss based on the current market situation).
+Stoploss values cannot be changed if `trailing_stop` is enabled and the stoploss has already been adjusted.

docs/strategy-customization.md

@@ -1068,7 +1068,7 @@ To verify if a pair is currently locked, use `self.is_pair_locked(pair)`.
 ``` python
 from freqtrade.persistence import Trade
 from datetime import timedelta, datetime, timezone
-# Put the above lines a the top of the strategy file, next to all the other imports
+# Put the above lines at the top of the strategy file, next to all the other imports
 # --------
 
 # Within populate indicators (or populate_entry_trend):

docs/stylesheets/ft.extra.css

@@ -19,3 +19,31 @@
 #available-endpoints ~ .md-typeset__scrollwrap .md-typeset__table th:first-of-type {
     width: 35% !important;
 }
+
+
+.md-typeset .md-button--sm {
+    padding: 0.2em 1em;
+    font-size: 12px;
+    font-weight: 600;
+    background-color: #f6f8fa;
+    color: #24292f;
+    border: 1px solid #d0d7de;
+    border-radius: 0.25em;
+    text-decoration: none;
+    display: inline-block;
+    transition: all 0.2s ease;
+    cursor: pointer;
+}
+
+.md-typeset .md-button--sm:hover {
+    background-color: #e5eaee;
+    border-color: #d1d9e0;
+    text-decoration: none;
+    color: #24292f;
+}
+
+.md-typeset .md-button--sm:active {
+    background-color: #ebecf0;
+    border-color: #afb8c1;
+    box-shadow: inset 0 1px 0 rgba(175, 184, 193, 0.2);
+}

docs/telegram-usage.md

@@ -188,7 +188,7 @@ You can create your own keyboard in `config.json`:
 !!! Note "Supported Commands"
     Only the following commands are allowed. Command arguments are not supported!
 
-    `/start`, `/pause`, `/stop`, `/status`, `/status table`, `/trades`, `/profit`, `/performance`, `/daily`, `/stats`, `/count`, `/locks`, `/balance`, `/stopentry`, `/reload_config`, `/show_config`, `/logs`, `/whitelist`, `/blacklist`, `/edge`, `/help`, `/version`, `/marketdir`
+    `/start`, `/pause`, `/stop`, `/status`, `/status table`, `/trades`, `/profit`, `/performance`, `/daily`, `/stats`, `/count`, `/locks`, `/balance`, `/stopentry`, `/reload_config`, `/show_config`, `/logs`, `/whitelist`, `/blacklist`, `/help`, `/version`, `/marketdir`
 
 ## Telegram commands
 
@@ -240,7 +240,6 @@ official commands. You can ask at any moment for help with `/help`.
 | `/entries` | Shows Wins / losses by Exit reason as well as Avg. holding durations for buys and sells
 | `/whitelist [sorted] [baseonly]` | Show the current whitelist. Optionally display in alphabetical order and/or with just the base currency of each pairing.
 | `/blacklist [pair]` | Show the current blacklist, or adds a pair to the blacklist.
-| `/edge` | Show validated pairs by Edge if it is enabled.
 
 ## Telegram commands in action
 
@@ -451,21 +450,6 @@ Use `/reload_config` to reset the blacklist.
 > Using blacklist `StaticPairList` with 2 pairs  
 >`DODGE/BTC`, `HOT/BTC`.  
 
-### /edge
-
-Shows pairs validated by Edge along with their corresponding win-rate, expectancy and stoploss values.
-
-> **Edge only validated following pairs:**
-```
-Pair        Winrate    Expectancy    Stoploss
---------  ---------  ------------  ----------
-DOCK/ETH   0.522727      0.881821       -0.03
-PHX/ETH    0.677419      0.560488       -0.03
-HOT/ETH    0.733333      0.490492       -0.03
-HC/ETH     0.588235      0.280988       -0.02
-ARDR/ETH   0.366667      0.143059       -0.01
-```
-
 ### /version
 
 > **Version:** `0.14.3`

docs/utils.md

@@ -1,6 +1,6 @@
 # Utility Subcommands
 
-Besides the Live-Trade and Dry-Run run modes, the `backtesting`, `edge` and `hyperopt` optimization subcommands, and the `download-data` subcommand which prepares historical data, the bot contains a number of utility subcommands. They are described in this section.
+Besides the Live-Trade and Dry-Run run modes, the `backtesting` and `hyperopt` optimization subcommands, and the `download-data` subcommand which prepares historical data, the bot contains a number of utility subcommands. They are described in this section.
 
 ## Create userdir
 

docs/windows_installation.md

@@ -42,7 +42,7 @@ cd freqtrade
 
 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 (3.10, 3.11 and 3.12) 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 (3.10, 3.11, 3.12 and 3.13) and for 64bit Windows.
 These Wheels are also used by CI running on windows, and are therefore tested together with freqtrade.
 
 Other versions must be downloaded from the above link.

freqtrade/__init__.py

@@ -1,6 +1,6 @@
 """Freqtrade bot"""
 
-__version__ = "2025.5"
+__version__ = "2025.6"
 
 if "dev" in __version__:
     from pathlib import Path

freqtrade/commands/arguments.py

@@ -57,6 +57,7 @@ ARGS_BACKTEST = [
     "backtest_breakdown",
     "backtest_cache",
     "freqai_backtest_live_models",
+    "backtest_notes",
 ]
 
 ARGS_HYPEROPT = [
@@ -81,7 +82,7 @@ ARGS_HYPEROPT = [
     "early_stop",
 ]
 
-ARGS_EDGE = [*ARGS_COMMON_OPTIMIZE, "stoploss_range"]
+ARGS_EDGE = [*ARGS_COMMON_OPTIMIZE]
 
 ARGS_LIST_STRATEGIES = [
     "strategy_path",
@@ -250,7 +251,7 @@ ARGS_STRATEGY_UPDATER = ["strategy_list", "strategy_path", "recursive_strategy_s
 ARGS_LOOKAHEAD_ANALYSIS = [
     a
     for a in ARGS_BACKTEST
-    if a not in ("position_stacking", "backtest_cache", "backtest_breakdown")
+    if a not in ("position_stacking", "backtest_cache", "backtest_breakdown", "backtest_notes")
 ] + ["minimum_trade_amount", "targeted_trade_amount", "lookahead_analysis_exportfilename"]
 
 ARGS_RECURSIVE_ANALYSIS = ["timeframe", "timerange", "dataformat_ohlcv", "pairs", "startup_candle"]
@@ -505,7 +506,9 @@ class Arguments:
 
         # Add edge subcommand
         edge_cmd = subparsers.add_parser(
-            "edge", help="Edge module.", parents=[_common_parser, _strategy_parser]
+            "edge",
+            help="Edge module. No longer part of Freqtrade",
+            parents=[_common_parser, _strategy_parser],
         )
         edge_cmd.set_defaults(func=start_edge)
         self._build_args(optionlist=ARGS_EDGE, parser=edge_cmd)

freqtrade/commands/cli_options.py

@@ -204,6 +204,11 @@ AVAILABLE_CLI_OPTIONS = {
         help="Export backtest results (default: trades).",
         choices=constants.EXPORT_OPTIONS,
     ),
+    "backtest_notes": Arg(
+        "--notes",
+        help="Add notes to the backtest results.",
+        metavar="TEXT",
+    ),
     "exportfilename": Arg(
         "--export-filename",
         "--backtest-filename",
@@ -235,13 +240,6 @@ AVAILABLE_CLI_OPTIONS = {
         default=constants.BACKTEST_CACHE_DEFAULT,
         choices=constants.BACKTEST_CACHE_AGE,
     ),
-    # Edge
-    "stoploss_range": Arg(
-        "--stoplosses",
-        help="Defines a range of stoploss values against which edge will assess the strategy. "
-        'The format is "min,max,step" (without any space). '
-        "Example: `--stoplosses=-0.01,-0.1,-0.001`",
-    ),
     # Hyperopt
     "hyperopt": Arg(
         "--hyperopt",

freqtrade/commands/optimize_commands.py

@@ -129,15 +129,10 @@ def start_edge(args: dict[str, Any]) -> None:
     :param args: Cli args from Arguments()
     :return: None
     """
-    from freqtrade.optimize.edge_cli import EdgeCli
-
-    # Initialize configuration
-    config = setup_optimize_configuration(args, RunMode.EDGE)
-    logger.info("Starting freqtrade in Edge mode")
-
-    # Initialize Edge object
-    edge_cli = EdgeCli(config)
-    edge_cli.start()
+    raise ConfigurationError(
+        "The Edge module has been deprecated in 2023.9 and removed in 2025.6. "
+        "All functionalities of edge have been removed."
+    )
 
 
 def start_lookahead_analysis(args: dict[str, Any]) -> None:

freqtrade/config_schema/config_schema.py

@@ -423,10 +423,6 @@ CONF_SCHEMA = {
             "description": "Exchange configuration.",
             "$ref": "#/definitions/exchange",
         },
-        "edge": {
-            "description": "Edge configuration.",
-            "$ref": "#/definitions/edge",
-        },
         "log_config": {
             "description": "Logging configuration.",
             "$ref": "#/definitions/logging",
@@ -913,30 +909,22 @@ CONF_SCHEMA = {
                 },
                 "ccxt_config": {"description": "CCXT configuration settings.", "type": "object"},
                 "ccxt_async_config": {
-                    "description": "CCXT asynchronous configuration settings.",
+                    "description": (
+                        "CCXT asynchronous configuration settings."
+                        "Usually ccxt_config should be used instead."
+                    ),
+                    "type": "object",
+                },
+                "ccxt_sync_config": {
+                    "description": (
+                        "CCXT synchronous configuration settings. "
+                        "Usually ccxt_config should be used instead."
+                    ),
                     "type": "object",
                 },
             },
             "required": ["name"],
         },
-        "edge": {
-            "type": "object",
-            "properties": {
-                "enabled": {"type": "boolean"},
-                "process_throttle_secs": {"type": "integer", "minimum": 600},
-                "calculate_since_number_of_days": {"type": "integer"},
-                "allowed_risk": {"type": "number"},
-                "stoploss_range_min": {"type": "number"},
-                "stoploss_range_max": {"type": "number"},
-                "stoploss_range_step": {"type": "number"},
-                "minimum_winrate": {"type": "number"},
-                "minimum_expectancy": {"type": "number"},
-                "min_trade_number": {"type": "number"},
-                "max_trade_duration_minute": {"type": "integer"},
-                "remove_pumps": {"type": "boolean"},
-            },
-            "required": ["process_throttle_secs", "allowed_risk"],
-        },
         "logging": {
             "type": "object",
             "properties": {

freqtrade/configuration/__init__.py

@@ -1,6 +1,6 @@
 # flake8: noqa: F401
 
-from freqtrade.configuration.config_secrets import sanitize_config
+from freqtrade.configuration.config_secrets import remove_exchange_credentials, sanitize_config
 from freqtrade.configuration.config_setup import setup_utils_configuration
 from freqtrade.configuration.config_validation import validate_config_consistency
 from freqtrade.configuration.configuration import Configuration

freqtrade/configuration/config_secrets.py

@@ -1,6 +1,27 @@
 from copy import deepcopy
 
-from freqtrade.constants import Config
+from freqtrade.constants import Config, ExchangeConfig
+
+
+_SENSITIVE_KEYS = [
+    "exchange.key",
+    "exchange.api_key",
+    "exchange.apiKey",
+    "exchange.secret",
+    "exchange.password",
+    "exchange.uid",
+    "exchange.account_id",
+    "exchange.accountId",
+    "exchange.wallet_address",
+    "exchange.walletAddress",
+    "exchange.private_key",
+    "exchange.privateKey",
+    "telegram.token",
+    "telegram.chat_id",
+    "discord.webhook_url",
+    "api_server.password",
+    "webhook.url",
+]
 
 
 def sanitize_config(config: Config, *, show_sensitive: bool = False) -> Config:
@@ -12,27 +33,8 @@ def sanitize_config(config: Config, *, show_sensitive: bool = False) -> Config:
     """
     if show_sensitive:
         return config
-    keys_to_remove = [
-        "exchange.key",
-        "exchange.api_key",
-        "exchange.apiKey",
-        "exchange.secret",
-        "exchange.password",
-        "exchange.uid",
-        "exchange.account_id",
-        "exchange.accountId",
-        "exchange.wallet_address",
-        "exchange.walletAddress",
-        "exchange.private_key",
-        "exchange.privateKey",
-        "telegram.token",
-        "telegram.chat_id",
-        "discord.webhook_url",
-        "api_server.password",
-        "webhook.url",
-    ]
     config = deepcopy(config)
-    for key in keys_to_remove:
+    for key in _SENSITIVE_KEYS:
         if "." in key:
             nested_keys = key.split(".")
             nested_config = config
@@ -45,3 +47,21 @@ def sanitize_config(config: Config, *, show_sensitive: bool = False) -> Config:
                 config[key] = "REDACTED"
 
     return config
+
+
+def remove_exchange_credentials(exchange_config: ExchangeConfig, dry_run: bool) -> None:
+    """
+    Removes exchange keys from the configuration and specifies dry-run
+    Used for backtesting / hyperopt and utils.
+    Modifies the input dict!
+    :param exchange_config: Exchange configuration
+    :param dry_run: If True, remove sensitive keys from the exchange configuration
+    """
+    if not dry_run:
+        return
+
+    for key in [k for k in _SENSITIVE_KEYS if k.startswith("exchange.")]:
+        if "." in key:
+            key1 = key.removeprefix("exchange.")
+            if key1 in exchange_config:
+                exchange_config[key1] = ""

freqtrade/configuration/config_validation.py

@@ -99,14 +99,12 @@ def validate_config_consistency(conf: dict[str, Any], *, preliminary: bool = Fal
 
 def _validate_unlimited_amount(conf: dict[str, Any]) -> None:
     """
-    If edge is disabled, either max_open_trades or stake_amount need to be set.
+    Either max_open_trades or stake_amount need to be set.
     :raise: ConfigurationError if config validation failed
     """
     if (
-        not conf.get("edge", {}).get("enabled")
-        and (conf.get("max_open_trades") == float("inf") or conf.get("max_open_trades") == -1)
-        and conf.get("stake_amount") == UNLIMITED_STAKE_AMOUNT
-    ):
+        conf.get("max_open_trades") == float("inf") or conf.get("max_open_trades") == -1
+    ) and conf.get("stake_amount") == UNLIMITED_STAKE_AMOUNT:
         raise ConfigurationError("`max_open_trades` and `stake_amount` cannot both be unlimited.")
 
 
@@ -164,12 +162,9 @@ def _validate_edge(conf: dict[str, Any]) -> None:
     Edge and Dynamic whitelist should not both be enabled, since edge overrides dynamic whitelists.
     """
 
-    if not conf.get("edge", {}).get("enabled"):
-        return
-
-    if not conf.get("use_exit_signal", True):
+    if conf.get("edge", {}).get("enabled"):
         raise ConfigurationError(
-            "Edge requires `use_exit_signal` to be True, otherwise no sells will happen."
+            "Edge is no longer supported and has been removed from Freqtrade with 2025.6."
         )
 
 

freqtrade/configuration/configuration.py

@@ -2,7 +2,6 @@
 This module contains the configuration class
 """
 
-import ast
 import logging
 import warnings
 from collections.abc import Callable
@@ -310,17 +309,10 @@ class Configuration:
             ("backtest_cache", "Parameter --cache={} detected ..."),
             ("disableparamexport", "Parameter --disableparamexport detected: {} ..."),
             ("freqai_backtest_live_models", "Parameter --freqai-backtest-live-models detected ..."),
+            ("backtest_notes", "Parameter --notes detected: {} ..."),
         ]
         self._args_to_config_loop(config, configurations)
 
-        # Edge section:
-        if self.args.get("stoploss_range"):
-            txt_range = ast.literal_eval(self.args["stoploss_range"])
-            config["edge"].update({"stoploss_range_min": txt_range[0]})
-            config["edge"].update({"stoploss_range_max": txt_range[1]})
-            config["edge"].update({"stoploss_range_step": txt_range[2]})
-            logger.info("Parameter --stoplosses detected: %s ...", self.args["stoploss_range"])
-
         # Hyperopt section
 
         configurations = [

freqtrade/configuration/deprecated_settings.py

@@ -159,16 +159,6 @@ def process_temporary_deprecated_settings(config: Config) -> None:
     process_removed_setting(
         config, "ask_strategy", "ignore_roi_if_buy_signal", None, "ignore_roi_if_entry_signal"
     )
-    if config.get("edge", {}).get(
-        "enabled", False
-    ) and "capital_available_percentage" in config.get("edge", {}):
-        raise ConfigurationError(
-            "DEPRECATED: "
-            "Using 'edge.capital_available_percentage' has been deprecated in favor of "
-            "'tradable_balance_ratio'. Please migrate your configuration to "
-            "'tradable_balance_ratio' and remove 'capital_available_percentage' "
-            "from the edge configuration."
-        )
     if "ticker_interval" in config:
         raise ConfigurationError(
             "DEPRECATED: 'ticker_interval' detected. "

freqtrade/configuration/environment_vars.py

@@ -43,15 +43,27 @@ def _flat_vars_to_nested_dict(env_dict: dict[str, Any], prefix: str) -> dict[str
     :return: Nested dict based on available and relevant variables.
     """
     no_convert = ["CHAT_ID", "PASSWORD"]
+    ccxt_config_keys = ["ccxt_config", "ccxt_sync_config", "ccxt_async_config"]
     relevant_vars: dict[str, Any] = {}
 
     for env_var, val in sorted(env_dict.items()):
         if env_var.startswith(prefix):
             logger.info(f"Loading variable '{env_var}'")
             key = env_var.replace(prefix, "")
-            for k in reversed(key.split("__")):
+            key_parts = key.split("__")
+            logger.info("Key parts: %s", key_parts)
+
+            # Check if any ccxt config key is in the key parts
+            preserve_case = key_parts[0].lower() == "exchange" and any(
+                ccxt_key in [part.lower() for part in key_parts] for ccxt_key in ccxt_config_keys
+            )
+
+            for i, k in enumerate(reversed(key_parts)):
+                # Preserve case for the final key if ccxt config is involved
+                key_name = k if preserve_case and i == 0 else k.lower()
+
                 val = {
-                    k.lower(): (
+                    key_name: (
                         _get_var_typed(val)
                         if not isinstance(val, dict) and k not in no_convert
                         else val

freqtrade/data/converter/trade_converter_kraken.py

@@ -69,6 +69,10 @@ def import_kraken_trades_from_csv(config: Config, convert_to: str):
         trades = pd.concat(dfs, ignore_index=True)
         del dfs
 
+        # drop any row not having a number in the column timestamp
+        timestamp_numeric = pd.to_numeric(trades["timestamp"], errors="coerce")
+        trades = trades[timestamp_numeric.notna()]
+
         trades.loc[:, "timestamp"] = trades["timestamp"] * 1e3
         trades.loc[:, "cost"] = trades["price"] * trades["amount"]
         for col in DEFAULT_TRADES_COLUMNS:

freqtrade/data/dataprovider.py

@@ -405,7 +405,7 @@ class DataProvider:
     def runmode(self) -> RunMode:
         """
         Get runmode of the bot
-        can be "live", "dry-run", "backtest", "edgecli", "hyperopt" or "other".
+        can be "live", "dry-run", "backtest", "hyperopt" or "other".
         """
         return RunMode(self._config.get("runmode", RunMode.OTHER))
 

freqtrade/data/entryexitanalysis.py

@@ -331,7 +331,9 @@ def process_entry_exit_reasons(config: Config):
         exit_only = config.get("exit_only", False)
         do_rejected = config.get("analysis_rejected", False)
         to_csv = config.get("analysis_to_csv", False)
-        csv_path = Path(config.get("analysis_csv_path", config["exportfilename"]))
+        csv_path = Path(
+            config.get("analysis_csv_path", config["exportfilename"]),  # type: ignore[arg-type]
+        )
 
         if entry_only is True and exit_only is True:
             raise OperationalException(

freqtrade/edge/__init__.py

@@ -1 +0,0 @@
-from .edge_positioning import Edge, PairInfo  # noqa: F401

freqtrade/edge/edge_positioning.py

@@ -1,524 +0,0 @@
-# pragma pylint: disable=W0603
-"""Edge positioning package"""
-
-import logging
-from collections import defaultdict
-from copy import deepcopy
-from datetime import timedelta
-from typing import Any, NamedTuple
-
-import numpy as np
-import utils_find_1st as utf1st
-from pandas import DataFrame
-
-from freqtrade.configuration import TimeRange
-from freqtrade.constants import DATETIME_PRINT_FORMAT, UNLIMITED_STAKE_AMOUNT, Config
-from freqtrade.data.history import get_timerange, load_data, refresh_data
-from freqtrade.enums import CandleType, ExitType, RunMode
-from freqtrade.exceptions import OperationalException
-from freqtrade.exchange import timeframe_to_seconds
-from freqtrade.plugins.pairlist.pairlist_helpers import expand_pairlist
-from freqtrade.strategy.interface import IStrategy
-from freqtrade.util import dt_now
-
-
-logger = logging.getLogger(__name__)
-
-
-class PairInfo(NamedTuple):
-    stoploss: float
-    winrate: float
-    risk_reward_ratio: float
-    required_risk_reward: float
-    expectancy: float
-    nb_trades: int
-    avg_trade_duration: float
-
-
-class Edge:
-    """
-    Calculates Win Rate, Risk Reward Ratio, Expectancy
-    against historical data for a give set of markets and a strategy
-    it then adjusts stoploss and position size accordingly
-    and force it into the strategy
-    Author: https://github.com/mishaker
-    """
-
-    _cached_pairs: dict[str, Any] = {}  # Keeps a list of pairs
-
-    def __init__(self, config: Config, exchange, strategy) -> None:
-        self.config = config
-        self.exchange = exchange
-        self.strategy: IStrategy = strategy
-
-        self.edge_config = self.config.get("edge", {})
-        self._cached_pairs: dict[str, Any] = {}  # Keeps a list of pairs
-        self._final_pairs: list = []
-
-        # checking max_open_trades. it should be -1 as with Edge
-        # the number of trades is determined by position size
-        if self.config["max_open_trades"] != float("inf"):
-            logger.critical("max_open_trades should be -1 in config !")
-
-        if self.config["stake_amount"] != UNLIMITED_STAKE_AMOUNT:
-            raise OperationalException("Edge works only with unlimited stake amount")
-
-        self._capital_ratio: float = self.config["tradable_balance_ratio"]
-        self._allowed_risk: float = self.edge_config.get("allowed_risk")
-        self._since_number_of_days: int = self.edge_config.get("calculate_since_number_of_days", 14)
-        self._last_updated: int = 0  # Timestamp of pairs last updated time
-        self._refresh_pairs = True
-
-        self._stoploss_range_min = float(self.edge_config.get("stoploss_range_min", -0.01))
-        self._stoploss_range_max = float(self.edge_config.get("stoploss_range_max", -0.05))
-        self._stoploss_range_step = float(self.edge_config.get("stoploss_range_step", -0.001))
-
-        # calculating stoploss range
-        self._stoploss_range = np.arange(
-            self._stoploss_range_min, self._stoploss_range_max, self._stoploss_range_step
-        )
-
-        self._timerange: TimeRange = TimeRange.parse_timerange(
-            f"{(dt_now() - timedelta(days=self._since_number_of_days)).strftime('%Y%m%d')}-"
-        )
-        if config.get("fee"):
-            self.fee = config["fee"]
-        else:
-            try:
-                self.fee = self.exchange.get_fee(
-                    symbol=expand_pairlist(
-                        self.config["exchange"]["pair_whitelist"], list(self.exchange.markets)
-                    )[0]
-                )
-            except IndexError:
-                self.fee = None
-
-    def calculate(self, pairs: list[str]) -> bool:
-        if self.fee is None and pairs:
-            self.fee = self.exchange.get_fee(pairs[0])
-
-        heartbeat = self.edge_config.get("process_throttle_secs")
-
-        if (self._last_updated > 0) and (
-            self._last_updated + heartbeat > int(dt_now().timestamp())
-        ):
-            return False
-
-        data: dict[str, Any] = {}
-        logger.info("Using stake_currency: %s ...", self.config["stake_currency"])
-        logger.info("Using local backtesting data (using whitelist in given config) ...")
-
-        if self._refresh_pairs:
-            timerange_startup = deepcopy(self._timerange)
-            timerange_startup.subtract_start(
-                timeframe_to_seconds(self.strategy.timeframe) * self.strategy.startup_candle_count
-            )
-            refresh_data(
-                datadir=self.config["datadir"],
-                pairs=pairs,
-                exchange=self.exchange,
-                timeframe=self.strategy.timeframe,
-                timerange=timerange_startup,
-                data_format=self.config["dataformat_ohlcv"],
-                candle_type=self.config.get("candle_type_def", CandleType.SPOT),
-            )
-            # Download informative pairs too
-            res = defaultdict(list)
-            for pair, timeframe, _ in self.strategy.gather_informative_pairs():
-                res[timeframe].append(pair)
-            for timeframe, inf_pairs in res.items():
-                timerange_startup = deepcopy(self._timerange)
-                timerange_startup.subtract_start(
-                    timeframe_to_seconds(timeframe) * self.strategy.startup_candle_count
-                )
-                refresh_data(
-                    datadir=self.config["datadir"],
-                    pairs=inf_pairs,
-                    exchange=self.exchange,
-                    timeframe=timeframe,
-                    timerange=timerange_startup,
-                    data_format=self.config["dataformat_ohlcv"],
-                    candle_type=self.config.get("candle_type_def", CandleType.SPOT),
-                )
-
-        data = load_data(
-            datadir=self.config["datadir"],
-            pairs=pairs,
-            timeframe=self.strategy.timeframe,
-            timerange=self._timerange,
-            startup_candles=self.strategy.startup_candle_count,
-            data_format=self.config["dataformat_ohlcv"],
-            candle_type=self.config.get("candle_type_def", CandleType.SPOT),
-        )
-
-        if not data:
-            # Reinitializing cached pairs
-            self._cached_pairs = {}
-            logger.critical("No data found. Edge is stopped ...")
-            return False
-        # Fake run-mode to Edge
-        prior_rm = self.config["runmode"]
-        self.config["runmode"] = RunMode.EDGE
-        preprocessed = self.strategy.advise_all_indicators(data)
-        self.config["runmode"] = prior_rm
-
-        # Print timeframe
-        min_date, max_date = get_timerange(preprocessed)
-        logger.info(
-            f"Measuring data from {min_date.strftime(DATETIME_PRINT_FORMAT)} "
-            f"up to {max_date.strftime(DATETIME_PRINT_FORMAT)} "
-            f"({(max_date - min_date).days} days).."
-        )
-        # TODO: Should edge support shorts? needs to be investigated further
-        # * (add enter_short exit_short)
-        headers = ["date", "open", "high", "low", "close", "enter_long", "exit_long"]
-
-        trades: list = []
-        for pair, pair_data in preprocessed.items():
-            # Sorting dataframe by date and reset index
-            pair_data = pair_data.sort_values(by=["date"])
-            pair_data = pair_data.reset_index(drop=True)
-
-            df_analyzed = self.strategy.ft_advise_signals(pair_data, {"pair": pair})[headers].copy()
-
-            trades += self._find_trades_for_stoploss_range(df_analyzed, pair, self._stoploss_range)
-
-        # If no trade found then exit
-        if len(trades) == 0:
-            logger.info("No trades found.")
-            return False
-
-        # Fill missing, calculable columns, profit, duration , abs etc.
-        trades_df = self._fill_calculable_fields(DataFrame(trades))
-        self._cached_pairs = self._process_expectancy(trades_df)
-        self._last_updated = int(dt_now().timestamp())
-
-        return True
-
-    def stake_amount(
-        self, pair: str, free_capital: float, total_capital: float, capital_in_trade: float
-    ) -> float:
-        stoploss = self.get_stoploss(pair)
-        available_capital = (total_capital + capital_in_trade) * self._capital_ratio
-        allowed_capital_at_risk = available_capital * self._allowed_risk
-        max_position_size = abs(allowed_capital_at_risk / stoploss)
-        # Position size must be below available capital.
-        position_size = min(min(max_position_size, free_capital), available_capital)
-        if pair in self._cached_pairs:
-            logger.info(
-                "winrate: %s, expectancy: %s, position size: %s, pair: %s,"
-                " capital in trade: %s, free capital: %s, total capital: %s,"
-                " stoploss: %s, available capital: %s.",
-                self._cached_pairs[pair].winrate,
-                self._cached_pairs[pair].expectancy,
-                position_size,
-                pair,
-                capital_in_trade,
-                free_capital,
-                total_capital,
-                stoploss,
-                available_capital,
-            )
-        return round(position_size, 15)
-
-    def get_stoploss(self, pair: str) -> float:
-        if pair in self._cached_pairs:
-            return self._cached_pairs[pair].stoploss
-        else:
-            logger.warning(
-                f"Tried to access stoploss of non-existing pair {pair}, "
-                "strategy stoploss is returned instead."
-            )
-            return self.strategy.stoploss
-
-    def adjust(self, pairs: list[str]) -> list:
-        """
-        Filters out and sorts "pairs" according to Edge calculated pairs
-        """
-        final = []
-        for pair, info in self._cached_pairs.items():
-            if (
-                info.expectancy > float(self.edge_config.get("minimum_expectancy", 0.2))
-                and info.winrate > float(self.edge_config.get("minimum_winrate", 0.60))
-                and pair in pairs
-            ):
-                final.append(pair)
-
-        if self._final_pairs != final:
-            self._final_pairs = final
-            if self._final_pairs:
-                logger.info(
-                    "Minimum expectancy and minimum winrate are met only for %s,"
-                    " so other pairs are filtered out.",
-                    self._final_pairs,
-                )
-            else:
-                logger.info(
-                    "Edge removed all pairs as no pair with minimum expectancy "
-                    "and minimum winrate was found !"
-                )
-
-        return self._final_pairs
-
-    def accepted_pairs(self) -> list[dict[str, Any]]:
-        """
-        return a list of accepted pairs along with their winrate, expectancy and stoploss
-        """
-        final = []
-        for pair, info in self._cached_pairs.items():
-            if info.expectancy > float(
-                self.edge_config.get("minimum_expectancy", 0.2)
-            ) and info.winrate > float(self.edge_config.get("minimum_winrate", 0.60)):
-                final.append(
-                    {
-                        "Pair": pair,
-                        "Winrate": info.winrate,
-                        "Expectancy": info.expectancy,
-                        "Stoploss": info.stoploss,
-                    }
-                )
-        return final
-
-    def _fill_calculable_fields(self, result: DataFrame) -> DataFrame:
-        """
-        The result frame contains a number of columns that are calculable
-        from other columns. These are left blank till all rows are added,
-        to be populated in single vector calls.
-
-        Columns to be populated are:
-        - Profit
-        - trade duration
-        - profit abs
-        :param result Dataframe
-        :return: result Dataframe
-        """
-        # We set stake amount to an arbitrary amount, as it doesn't change the calculation.
-        # All returned values are relative, they are defined as ratios.
-        stake = 0.015
-
-        result["trade_duration"] = result["close_date"] - result["open_date"]
-
-        result["trade_duration"] = result["trade_duration"].map(
-            lambda x: int(x.total_seconds() / 60)
-        )
-
-        # Spends, Takes, Profit, Absolute Profit
-
-        # Buy Price
-        result["buy_vol"] = stake / result["open_rate"]  # How many target are we buying
-        result["buy_fee"] = stake * self.fee
-        result["buy_spend"] = stake + result["buy_fee"]  # How much we're spending
-
-        # Sell price
-        result["sell_sum"] = result["buy_vol"] * result["close_rate"]
-        result["sell_fee"] = result["sell_sum"] * self.fee
-        result["sell_take"] = result["sell_sum"] - result["sell_fee"]
-
-        # profit_ratio
-        result["profit_ratio"] = (result["sell_take"] - result["buy_spend"]) / result["buy_spend"]
-
-        # Absolute profit
-        result["profit_abs"] = result["sell_take"] - result["buy_spend"]
-
-        return result
-
-    def _process_expectancy(self, results: DataFrame) -> dict[str, Any]:
-        """
-        This calculates WinRate, Required Risk Reward, Risk Reward and Expectancy of all pairs
-        The calculation will be done per pair and per strategy.
-        """
-        # Removing pairs having less than min_trades_number
-        min_trades_number = self.edge_config.get("min_trade_number", 10)
-        results = results.groupby(["pair", "stoploss"]).filter(lambda x: len(x) > min_trades_number)
-        ###################################
-
-        # Removing outliers (Only Pumps) from the dataset
-        # The method to detect outliers is to calculate standard deviation
-        # Then every value more than (standard deviation + 2*average) is out (pump)
-        #
-        # Removing Pumps
-        if self.edge_config.get("remove_pumps", False):
-            results = results[
-                results["profit_abs"]
-                < 2 * results["profit_abs"].std() + results["profit_abs"].mean()
-            ]
-        ##########################################################################
-
-        # Removing trades having a duration more than X minutes (set in config)
-        max_trade_duration = self.edge_config.get("max_trade_duration_minute", 1440)
-        results = results[results.trade_duration < max_trade_duration]
-        #######################################################################
-
-        if results.empty:
-            return {}
-
-        groupby_aggregator = {
-            "profit_abs": [
-                ("nb_trades", "count"),  # number of all trades
-                ("profit_sum", lambda x: x[x > 0].sum()),  # cumulative profit of all winning trades
-                ("loss_sum", lambda x: abs(x[x < 0].sum())),  # cumulative loss of all losing trades
-                ("nb_win_trades", lambda x: x[x > 0].count()),  # number of winning trades
-            ],
-            "trade_duration": [("avg_trade_duration", "mean")],
-        }
-
-        # Group by (pair and stoploss) by applying above aggregator
-        df = (
-            results.groupby(["pair", "stoploss"])[["profit_abs", "trade_duration"]]
-            .agg(groupby_aggregator)
-            .reset_index(col_level=1)
-        )
-
-        # Dropping level 0 as we don't need it
-        df.columns = df.columns.droplevel(0)
-
-        # Calculating number of losing trades, average win and average loss
-        df["nb_loss_trades"] = df["nb_trades"] - df["nb_win_trades"]
-        df["average_win"] = np.where(
-            df["nb_win_trades"] == 0, 0.0, df["profit_sum"] / df["nb_win_trades"]
-        )
-        df["average_loss"] = np.where(
-            df["nb_loss_trades"] == 0, 0.0, df["loss_sum"] / df["nb_loss_trades"]
-        )
-
-        # Win rate = number of profitable trades / number of trades
-        df["winrate"] = df["nb_win_trades"] / df["nb_trades"]
-
-        # risk_reward_ratio = average win / average loss
-        df["risk_reward_ratio"] = df["average_win"] / df["average_loss"]
-
-        # required_risk_reward = (1 / winrate) - 1
-        df["required_risk_reward"] = (1 / df["winrate"]) - 1
-
-        # expectancy = (risk_reward_ratio * winrate) - (lossrate)
-        df["expectancy"] = (df["risk_reward_ratio"] * df["winrate"]) - (1 - df["winrate"])
-
-        # sort by expectancy and stoploss
-        df = (
-            df.sort_values(by=["expectancy", "stoploss"], ascending=False)
-            .groupby("pair")
-            .first()
-            .sort_values(by=["expectancy"], ascending=False)
-            .reset_index()
-        )
-
-        final = {}
-        for x in df.itertuples():
-            final[x.pair] = PairInfo(
-                x.stoploss,
-                x.winrate,
-                x.risk_reward_ratio,
-                x.required_risk_reward,
-                x.expectancy,
-                x.nb_trades,
-                x.avg_trade_duration,
-            )
-
-        # Returning a list of pairs in order of "expectancy"
-        return final
-
-    def _find_trades_for_stoploss_range(self, df, pair: str, stoploss_range) -> list:
-        buy_column = df["enter_long"].values
-        sell_column = df["exit_long"].values
-        date_column = df["date"].values
-        ohlc_columns = df[["open", "high", "low", "close"]].values
-
-        result: list = []
-        for stoploss in stoploss_range:
-            result += self._detect_next_stop_or_sell_point(
-                buy_column, sell_column, date_column, ohlc_columns, round(stoploss, 6), pair
-            )
-
-        return result
-
-    def _detect_next_stop_or_sell_point(
-        self, buy_column, sell_column, date_column, ohlc_columns, stoploss, pair: str
-    ):
-        """
-        Iterate through ohlc_columns in order to find the next trade
-        Next trade opens from the first buy signal noticed to
-        The sell or stoploss signal after it.
-        It then cuts OHLC, buy_column, sell_column and date_column.
-        Cut from (the exit trade index) + 1.
-
-        Author: https://github.com/mishaker
-        """
-
-        result: list = []
-        start_point = 0
-
-        while True:
-            open_trade_index = utf1st.find_1st(buy_column, 1, utf1st.cmp_equal)
-
-            # Return empty if we don't find trade entry (i.e. buy==1) or
-            # we find a buy but at the end of array
-            if open_trade_index == -1 or open_trade_index == len(buy_column) - 1:
-                break
-            else:
-                # When a buy signal is seen,
-                # trade opens in reality on the next candle
-                open_trade_index += 1
-
-            open_price = ohlc_columns[open_trade_index, 0]
-            stop_price = open_price * (stoploss + 1)
-
-            # Searching for the index where stoploss is hit
-            stop_index = utf1st.find_1st(
-                ohlc_columns[open_trade_index:, 2], stop_price, utf1st.cmp_smaller
-            )
-
-            # If we don't find it then we assume stop_index will be far in future (infinite number)
-            if stop_index == -1:
-                stop_index = float("inf")
-
-            # Searching for the index where sell is hit
-            sell_index = utf1st.find_1st(sell_column[open_trade_index:], 1, utf1st.cmp_equal)
-
-            # If we don't find it then we assume sell_index will be far in future (infinite number)
-            if sell_index == -1:
-                sell_index = float("inf")
-
-            # Check if we don't find any stop or sell point (in that case trade remains open)
-            # It is not interesting for Edge to consider it so we simply ignore the trade
-            # And stop iterating there is no more entry
-            if stop_index == sell_index == float("inf"):
-                break
-
-            if stop_index <= sell_index:
-                exit_index = open_trade_index + stop_index
-                exit_type = ExitType.STOP_LOSS
-                exit_price = stop_price
-            elif stop_index > sell_index:
-                # If exit is SELL then we exit at the next candle
-                exit_index = open_trade_index + sell_index + 1
-
-                # Check if we have the next candle
-                if len(ohlc_columns) - 1 < exit_index:
-                    break
-
-                exit_type = ExitType.EXIT_SIGNAL
-                exit_price = ohlc_columns[exit_index, 0]
-
-            trade = {
-                "pair": pair,
-                "stoploss": stoploss,
-                "profit_ratio": "",
-                "profit_abs": "",
-                "open_date": date_column[open_trade_index],
-                "close_date": date_column[exit_index],
-                "trade_duration": "",
-                "open_rate": round(open_price, 15),
-                "close_rate": round(exit_price, 15),
-                "exit_type": exit_type,
-            }
-
-            result.append(trade)
-
-            # Giving a view of exit_index till the end of array
-            buy_column = buy_column[exit_index:]
-            sell_column = sell_column[exit_index:]
-            date_column = date_column[exit_index:]
-            ohlc_columns = ohlc_columns[exit_index:]
-            start_point += exit_index
-
-        return result

freqtrade/enums/marginmode.py

@@ -13,4 +13,4 @@ class MarginMode(str, Enum):
     NONE = ""
 
     def __str__(self):
-        return f"{self.name.lower()}"
+        return f"{self.value.lower()}"

freqtrade/enums/runmode.py

@@ -4,13 +4,12 @@ from enum import Enum
 class RunMode(str, Enum):
     """
     Bot running mode (backtest, hyperopt, ...)
-    can be "live", "dry-run", "backtest", "edge", "hyperopt".
+    can be "live", "dry-run", "backtest", "hyperopt".
     """
 
     LIVE = "live"
     DRY_RUN = "dry_run"
     BACKTEST = "backtest"
-    EDGE = "edge"
     HYPEROPT = "hyperopt"
     UTIL_EXCHANGE = "util_exchange"
     UTIL_NO_EXCHANGE = "util_no_exchange"
@@ -20,5 +19,5 @@ class RunMode(str, Enum):
 
 
 TRADE_MODES = [RunMode.LIVE, RunMode.DRY_RUN]
-OPTIMIZE_MODES = [RunMode.BACKTEST, RunMode.EDGE, RunMode.HYPEROPT]
+OPTIMIZE_MODES = [RunMode.BACKTEST, RunMode.HYPEROPT]
 NON_UTIL_MODES = TRADE_MODES + OPTIMIZE_MODES

freqtrade/exchange/__init__.py

@@ -1,6 +1,6 @@
 # flake8: noqa: F401
 # isort: off
-from freqtrade.exchange.common import remove_exchange_credentials, MAP_EXCHANGE_CHILDCLASS
+from freqtrade.exchange.common import MAP_EXCHANGE_CHILDCLASS
 from freqtrade.exchange.exchange import Exchange
 
 # isort: on

freqtrade/exchange/binance.py

@@ -76,7 +76,10 @@ class Binance(Exchange):
         :return: Proxy coin or stake currency
         """
         if self.margin_mode == MarginMode.CROSS:
-            return self._config.get("proxy_coin", self._config["stake_currency"])
+            return self._config.get(
+                "proxy_coin",
+                self._config["stake_currency"],
+            )  # type: ignore[return-value]
         return self._config["stake_currency"]
 
     def get_tickers(

freqtrade/exchange/common.py

@@ -5,7 +5,6 @@ from collections.abc import Callable
 from functools import wraps
 from typing import Any, TypeVar, cast, overload
 
-from freqtrade.constants import ExchangeConfig
 from freqtrade.exceptions import DDosProtection, RetryableOrderError, TemporaryError
 from freqtrade.mixins import LoggingMixin
 
@@ -104,20 +103,6 @@ EXCHANGE_HAS_OPTIONAL = [
 ]
 
 
-def remove_exchange_credentials(exchange_config: ExchangeConfig, dry_run: bool) -> None:
-    """
-    Removes exchange keys from the configuration and specifies dry-run
-    Used for backtesting / hyperopt / edge and utils.
-    Modifies the input dict!
-    """
-    if dry_run:
-        exchange_config["key"] = ""
-        exchange_config["apiKey"] = ""
-        exchange_config["secret"] = ""
-        exchange_config["password"] = ""
-        exchange_config["uid"] = ""
-
-
 def calculate_backoff(retrycount, max_retries):
     """
     Calculate backoff

freqtrade/exchange/exchange.py

@@ -21,6 +21,7 @@ from ccxt import TICK_SIZE
 from dateutil import parser
 from pandas import DataFrame, concat
 
+from freqtrade.configuration import remove_exchange_credentials
 from freqtrade.constants import (
     DEFAULT_AMOUNT_RESERVE_PERCENT,
     DEFAULT_TRADES_COLUMNS,
@@ -64,7 +65,6 @@ from freqtrade.exceptions import (
 )
 from freqtrade.exchange.common import (
     API_FETCH_ORDER_RETRY_COUNT,
-    remove_exchange_credentials,
     retrier,
     retrier_async,
 )
@@ -637,9 +637,9 @@ class Exchange:
         if self._exchange_ws:
             self._exchange_ws.reset_connections()
 
-    async def _api_reload_markets(self, reload: bool = False) -> dict[str, Any]:
+    async def _api_reload_markets(self, reload: bool = False) -> None:
         try:
-            return await self._api_async.load_markets(reload=reload, params={})
+            await self._api_async.load_markets(reload=reload, params={})
         except ccxt.DDoSProtection as e:
             raise DDosProtection(e) from e
         except (ccxt.OperationFailed, ccxt.ExchangeError) as e:
@@ -649,14 +649,14 @@ class Exchange:
         except ccxt.BaseError as e:
             raise TemporaryError(e) from e
 
-    def _load_async_markets(self, reload: bool = False) -> dict[str, Any]:
+    def _load_async_markets(self, reload: bool = False) -> None:
         try:
             with self._loop_lock:
                 markets = self.loop.run_until_complete(self._api_reload_markets(reload=reload))
 
             if isinstance(markets, Exception):
                 raise markets
-            return markets
+            return None
         except asyncio.TimeoutError as e:
             logger.warning("Could not load markets. Reason: %s", e)
             raise TemporaryError from e
@@ -679,7 +679,8 @@ class Exchange:
             # on initial load, we retry 3 times to ensure we get the markets
             retries: int = 3 if force else 0
             # Reload async markets, then assign them to sync api
-            self._markets = retrier(self._load_async_markets, retries=retries)(reload=True)
+            retrier(self._load_async_markets, retries=retries)(reload=True)
+            self._markets = self._api_async.markets
             self._api.set_markets(self._api_async.markets, self._api_async.currencies)
             # Assign options array, as it contains some temporary information from the exchange.
             self._api.options = self._api_async.options
@@ -876,8 +877,8 @@ class Exchange:
             (trading_mode, margin_mode) not in self._supported_trading_mode_margin_pairs
         ):
             mm_value = margin_mode and margin_mode.value
-            raise OperationalException(
-                f"Freqtrade does not support {mm_value} {trading_mode} on {self.name}"
+            raise ConfigurationError(
+                f"Freqtrade does not support '{mm_value}' '{trading_mode}' on {self.name}."
             )
 
     def get_option(self, param: str, default: Any | None = None) -> Any:
@@ -3428,7 +3429,8 @@ class Exchange:
                 raise InvalidOrderException(f"Amount {stake_amount} too high for {pair}")
 
             raise OperationalException(
-                "Looped through all tiers without finding a max leverage. Should never be reached"
+                f"Looped through all tiers without finding a max leverage for {pair}. "
+                "Should never be reached."
             )
 
         elif self.trading_mode == TradingMode.MARGIN:  # Search markets.limits for max lev

freqtrade/exchange/gate.py

@@ -70,7 +70,6 @@ class Gate(Exchange):
         """
         try:
             if not self._config["dry_run"]:
-                # TODO: This should work with 4.4.34 and later.
                 self._api.load_unified_status()
                 is_unified = self._api.options.get("unifiedAccount")
 

freqtrade/freqai/prediction_models/ReinforcementLearner.py

@@ -101,7 +101,7 @@ class ReinforcementLearner(BaseReinforcementLearningModel):
 
         return model
 
-    MyRLEnv: type[BaseEnvironment]
+    MyRLEnv: type[BaseEnvironment]  # type: ignore[assignment, unused-ignore]
 
     class MyRLEnv(Base5ActionRLEnv):  # type: ignore[no-redef]
         """

freqtrade/freqtradebot.py

@@ -14,11 +14,10 @@ from typing import Any
 from schedule import Scheduler
 
 from freqtrade import constants
-from freqtrade.configuration import validate_config_consistency
+from freqtrade.configuration import remove_exchange_credentials, validate_config_consistency
 from freqtrade.constants import BuySell, Config, EntryExecuteMode, ExchangeConfig, LongShort
 from freqtrade.data.converter import order_book_to_dataframe
 from freqtrade.data.dataprovider import DataProvider
-from freqtrade.edge import Edge
 from freqtrade.enums import (
     ExitCheckTuple,
     ExitType,
@@ -38,7 +37,6 @@ from freqtrade.exceptions import (
 from freqtrade.exchange import (
     ROUND_DOWN,
     ROUND_UP,
-    remove_exchange_credentials,
     timeframe_to_minutes,
     timeframe_to_next_date,
     timeframe_to_seconds,
@@ -131,13 +129,6 @@ class FreqtradeBot(LoggingMixin):
         # Attach Wallets to strategy instance
         self.strategy.wallets = self.wallets
 
-        # Initializing Edge only if enabled
-        self.edge = (
-            Edge(self.config, self.exchange, self.strategy)
-            if self.config.get("edge", {}).get("enabled", False)
-            else None
-        )
-
         # Init ExternalMessageConsumer if enabled
         self.emc = (
             ExternalMessageConsumer(self.config, self.dataprovider)
@@ -242,9 +233,8 @@ class FreqtradeBot(LoggingMixin):
         self.rpc.startup_messages(self.config, self.pairlists, self.protections)
         # Update older trades with precision and precision mode
         self.startup_backpopulate_precision()
-        if not self.edge:
-            # Adjust stoploss if it was changed
-            Trade.stoploss_reinitialization(self.strategy.stoploss)
+        # Adjust stoploss if it was changed
+        Trade.stoploss_reinitialization(self.strategy.stoploss)
 
         # Only update open orders on startup
         # This will update the database after the initial migration
@@ -335,7 +325,7 @@ class FreqtradeBot(LoggingMixin):
 
     def _refresh_active_whitelist(self, trades: list[Trade] | None = None) -> list[str]:
         """
-        Refresh active whitelist from pairlist or edge and extend it with
+        Refresh active whitelist from pairlist and extend it with
         pairs that have open trades.
         """
         # Refresh whitelist
@@ -343,11 +333,6 @@ class FreqtradeBot(LoggingMixin):
         self.pairlists.refresh_pairlist()
         _whitelist = self.pairlists.whitelist
 
-        # Calculating Edge positioning
-        if self.edge:
-            self.edge.calculate(_whitelist)
-            _whitelist = self.edge.adjust(_whitelist)
-
         if trades:
             # Extend active-pair whitelist with pairs of open trades
             # It ensures that candle (OHLCV) data are downloaded for open trades as well
@@ -701,9 +686,7 @@ class FreqtradeBot(LoggingMixin):
                 else:
                     self.log_once(f"Pair {pair} is currently locked.", logger.info)
                 return False
-            stake_amount = self.wallets.get_trade_stake_amount(
-                pair, self.config["max_open_trades"], self.edge
-            )
+            stake_amount = self.wallets.get_trade_stake_amount(pair, self.config["max_open_trades"])
 
             bid_check_dom = self.config.get("entry_pricing", {}).get("check_depth_of_market", {})
             if (bid_check_dom.get("enabled", False)) and (
@@ -1042,13 +1025,11 @@ class FreqtradeBot(LoggingMixin):
                 precision_mode_price=self.exchange.precision_mode_price,
                 contract_size=self.exchange.get_contract_size(pair),
             )
-            stoploss = self.strategy.stoploss if not self.edge else self.edge.get_stoploss(pair)
+            stoploss = self.strategy.stoploss
             trade.adjust_stop_loss(trade.open_rate, stoploss, initial=True)
 
         else:
-            # This is additional entry, we reset fee_open_currency so timeout checking can work
             trade.is_open = True
-            trade.fee_open_currency = None
             trade.set_funding_fees(funding_fees)
 
         trade.orders.append(order_obj)
@@ -1170,7 +1151,7 @@ class FreqtradeBot(LoggingMixin):
             pair, enter_limit_requested, leverage
         )
 
-        if not self.edge and trade is None:
+        if trade is None:
             stake_available = self.wallets.get_available_stake_amount()
             stake_amount = strategy_safe_wrapper(
                 self.strategy.custom_stake_amount, default_retval=stake_amount
@@ -1299,6 +1280,7 @@ class FreqtradeBot(LoggingMixin):
             if (
                 not trade.has_open_orders
                 and not trade.has_open_sl_orders
+                and trade.fee_open_currency is not None
                 and not self.wallets.check_exit_amount(trade)
             ):
                 logger.warning(
@@ -1382,7 +1364,7 @@ class FreqtradeBot(LoggingMixin):
             datetime.now(timezone.utc),
             enter=enter,
             exit_=exit_,
-            force_stoploss=self.edge.get_stoploss(trade.pair) if self.edge else 0,
+            force_stoploss=0,
         )
         for should_exit in exits:
             if should_exit.exit_flag:
@@ -1487,13 +1469,6 @@ class FreqtradeBot(LoggingMixin):
         # If enter order is fulfilled but there is no stoploss, we add a stoploss on exchange
         if len(stoploss_orders) == 0:
             stop_price = trade.stoploss_or_liquidation
-            if self.edge:
-                stoploss = self.edge.get_stoploss(pair=trade.pair)
-                stop_price = (
-                    trade.open_rate * (1 - stoploss)
-                    if trade.is_short
-                    else trade.open_rate * (1 + stoploss)
-                )
 
             if self.create_stoploss_order(trade=trade, stop_price=stop_price):
                 # The above will return False if the placement failed and the trade was force-sold.
@@ -2368,12 +2343,13 @@ class FreqtradeBot(LoggingMixin):
             # If a entry order was closed, force update on stoploss on exchange
             if order.ft_order_side == trade.entry_side:
                 if send_msg:
+                    if trade.nr_of_successful_entries > 1:
+                        # Reset fee_open_currency so fee checking can work
+                        # Only necessary for additional entries
+                        trade.fee_open_currency = None
                     # Don't cancel stoploss in recovery modes immediately
                     trade = self.cancel_stoploss_on_exchange(trade)
-                if not self.edge:
-                    # TODO: should shorting/leverage be supported by Edge,
-                    # then this will need to be fixed.
-                    trade.adjust_stop_loss(trade.open_rate, self.strategy.stoploss, initial=True)
+                trade.adjust_stop_loss(trade.open_rate, self.strategy.stoploss, initial=True)
             if (
                 order.ft_order_side == trade.entry_side
                 or (trade.amount > 0 and trade.is_open)
@@ -2476,10 +2452,9 @@ class FreqtradeBot(LoggingMixin):
         return None
 
     def handle_order_fee(self, trade: Trade, order_obj: Order, order: CcxtOrder) -> None:
-        # Try update amount (binance-fix)
+        # Try update amount (binance-fix - but also applies to different exchanges)
         try:
-            fee_abs = self.get_real_amount(trade, order, order_obj)
-            if fee_abs is not None:
+            if (fee_abs := self.get_real_amount(trade, order, order_obj)) is not None:
                 order_obj.ft_fee_base = fee_abs
         except DependencyException as exception:
             logger.warning("Could not update trade amount: %s", exception)
@@ -2496,9 +2471,8 @@ class FreqtradeBot(LoggingMixin):
         order_amount = safe_value_fallback(order, "filled", "amount")
         # Only run for closed orders
         if (
-            trade.fee_updated(order.get("side", ""))
-            or order["status"] == "open"
-            or order_obj.ft_fee_base
+            trade.fee_updated(order.get("side", "")) or order["status"] == "open"
+            # or order_obj.ft_fee_base
         ):
             return None
 

freqtrade/loggers/ft_rich_handler.py

@@ -21,7 +21,9 @@ class FtRichHandler(Handler):
             msg = self.format(record)
             # Format log message
             log_time = Text(
-                datetime.fromtimestamp(record.created).strftime("%Y-%m-%d %H:%M:%S,%f")[:-3],
+                datetime.fromtimestamp(record.created).strftime("%Y-%m-%d %H:%M:%S,%f")[:-3]
+                if record.created
+                else "N/A",
             )
             name = Text(record.name, style="violet")
             log_level = Text(record.levelname, style=f"logging.level.{record.levelname.lower()}")
@@ -40,5 +42,8 @@ class FtRichHandler(Handler):
 
         except RecursionError:
             raise
+        except ImportError:
+            # Error when shutting down the console...
+            pass
         except Exception:
             self.handleError(record)

freqtrade/optimize/backtesting.py

@@ -1822,7 +1822,11 @@ class Backtesting:
         # Update old results with new ones.
         if len(self.all_bt_content) > 0:
             results = generate_backtest_stats(
-                data, self.all_bt_content, min_date=min_date, max_date=max_date
+                data,
+                self.all_bt_content,
+                min_date=min_date,
+                max_date=max_date,
+                notes=self.config.get("backtest_notes"),
             )
             if self.results:
                 self.results["metadata"].update(results["metadata"])

freqtrade/optimize/edge_cli.py

@@ -1,55 +0,0 @@
-# pragma pylint: disable=missing-docstring, W0212, too-many-arguments
-
-"""
-This module contains the edge backtesting interface
-"""
-
-import logging
-
-from freqtrade import constants
-from freqtrade.configuration import TimeRange, validate_config_consistency
-from freqtrade.constants import Config
-from freqtrade.data.dataprovider import DataProvider
-from freqtrade.edge import Edge
-from freqtrade.optimize.optimize_reports import generate_edge_table
-from freqtrade.resolvers import ExchangeResolver, StrategyResolver
-
-
-logger = logging.getLogger(__name__)
-
-
-class EdgeCli:
-    """
-    EdgeCli class, this class contains all the logic to run edge backtesting
-
-    To run a edge backtest:
-    edge = EdgeCli(config)
-    edge.start()
-    """
-
-    def __init__(self, config: Config) -> None:
-        self.config = config
-
-        # Ensure using dry-run
-        self.config["dry_run"] = True
-        self.config["stake_amount"] = constants.UNLIMITED_STAKE_AMOUNT
-        self.exchange = ExchangeResolver.load_exchange(self.config)
-        self.strategy = StrategyResolver.load_strategy(self.config)
-        self.strategy.dp = DataProvider(config, self.exchange)
-
-        validate_config_consistency(self.config)
-
-        self.edge = Edge(config, self.exchange, self.strategy)
-        # Set refresh_pairs to false for edge-cli (it must be true for edge)
-        self.edge._refresh_pairs = False
-
-        self.edge._timerange = TimeRange.parse_timerange(
-            None if self.config.get("timerange") is None else str(self.config.get("timerange"))
-        )
-        self.strategy.ft_bot_start()
-
-    def start(self) -> None:
-        result = self.edge.calculate(self.config["exchange"]["pair_whitelist"])
-        if result:
-            print("")  # blank line for readability
-            generate_edge_table(self.edge._cached_pairs)

freqtrade/optimize/optimize_reports/__init__.py

@@ -1,6 +1,5 @@
 # flake8: noqa: F401
 from freqtrade.optimize.optimize_reports.bt_output import (
-    generate_edge_table,
     generate_wins_draws_losses,
     show_backtest_result,
     show_backtest_results,

freqtrade/optimize/optimize_reports/bt_output.py

@@ -499,33 +499,3 @@ def show_sorted_pairlist(config: Config, backtest_stats: BacktestResultType):
                 if result["key"] != "TOTAL":
                     print(f'"{result["key"]}",  // {result["profit_mean"]:.2%}')
             print("]")
-
-
-def generate_edge_table(results: dict) -> None:
-    tabular_data = []
-    headers = [
-        "Pair",
-        "Stoploss",
-        "Win Rate",
-        "Risk Reward Ratio",
-        "Required Risk Reward",
-        "Expectancy",
-        "Total Number of Trades",
-        "Average Duration (min)",
-    ]
-
-    for result in results.items():
-        if result[1].nb_trades > 0:
-            tabular_data.append(
-                [
-                    result[0],
-                    f"{result[1].stoploss:.10g}",
-                    f"{result[1].winrate:.2f}",
-                    f"{result[1].risk_reward_ratio:.2f}",
-                    f"{result[1].required_risk_reward:.2f}",
-                    f"{result[1].expectancy:.2f}",
-                    result[1].nb_trades,
-                    round(result[1].avg_trade_duration),
-                ]
-            )
-    print_rich_table(tabular_data, headers, summary="EDGE TABLE")

freqtrade/optimize/optimize_reports/optimize_reports.py

@@ -347,7 +347,7 @@ def generate_trading_stats(results: DataFrame) -> dict[str, Any]:
         else timedelta()
     )
     winner_holding_min = (
-        timedelta(minutes=round(winning_duration[winning_duration > 0].min()))
+        timedelta(minutes=round(winning_duration.min()))
         if not winning_duration.empty
         else timedelta()
     )
@@ -362,7 +362,7 @@ def generate_trading_stats(results: DataFrame) -> dict[str, Any]:
         else timedelta()
     )
     loser_holding_min = (
-        timedelta(minutes=round(losing_duration[losing_duration > 0].min()))
+        timedelta(minutes=round(losing_duration.min()))
         if not losing_duration.empty
         else timedelta()
     )
@@ -669,6 +669,7 @@ def generate_backtest_stats(
     all_results: dict[str, BacktestContentType],
     min_date: datetime,
     max_date: datetime,
+    notes: str | None = None,
 ) -> BacktestResultType:
     """
     :param btdata: Backtest data
@@ -694,6 +695,8 @@ def generate_backtest_stats(
             "backtest_start_ts": int(min_date.timestamp()),
             "backtest_end_ts": int(max_date.timestamp()),
         }
+        if notes:
+            metadata[strategy]["notes"] = notes
         result["strategy"][strategy] = strat_stats
 
     strategy_results = generate_strategy_comparison(bt_stats=result["strategy"])

freqtrade/persistence/models.py

@@ -2,6 +2,7 @@
 This module contains the class to persist trades into SQLite
 """
 
+import functools
 import logging
 import threading
 from contextvars import ContextVar
@@ -94,3 +95,22 @@ def init_db(db_url: str) -> None:
     previous_tables = inspect(engine).get_table_names()
     ModelBase.metadata.create_all(engine)
     check_migrate(engine, decl_base=ModelBase, previous_tables=previous_tables)
+
+
+def custom_data_rpc_wrapper(func):
+    """
+    Wrapper for RPC methods when using custom_data
+    Similar behavior to deps.get_rpc() - but limited to custom_data.
+    """
+
+    @functools.wraps(func)
+    def wrapper(*args, **kwargs):
+        try:
+            _CustomData.session.rollback()
+            return func(*args, **kwargs)
+        finally:
+            _CustomData.session.rollback()
+            # Ensure the session is removed after use
+            _CustomData.session.remove()
+
+    return wrapper

freqtrade/persistence/trade_model.py

@@ -114,6 +114,7 @@ class Order(ModelBase):
     order_update_date: Mapped[datetime | None] = mapped_column(nullable=True)
     funding_fee: Mapped[float | None] = mapped_column(Float(), nullable=True)
 
+    # Fee if paid in base currency
     ft_fee_base: Mapped[float | None] = mapped_column(Float(), nullable=True)
     ft_order_tag: Mapped[str | None] = mapped_column(String(CUSTOM_TAG_MAX_LENGTH), nullable=True)
 
@@ -957,6 +958,10 @@ class LocalTrade:
     ) -> None:
         """
         Update Fee parameters. Only acts once per side
+        :param fee_cost: Cost of the fee in stake currency
+        :param fee_currency: Currency the fee was paid in
+        :param fee_rate: Rate of the fee (e.g. 0.001 for 0.1%)
+        :param side: Side of the fee (buy / sell)
         """
         if self.entry_side == side and self.fee_open_currency is None:
             self.fee_open_cost = fee_cost
@@ -1627,6 +1632,7 @@ class LocalTrade:
                 remaining=order.get("remaining", 0.0),
                 funding_fee=order.get("funding_fee", None),
                 ft_order_tag=order.get("ft_order_tag", None),
+                ft_fee_base=order.get("ft_fee_base", None),
             )
             trade.orders.append(order_obj)
 
@@ -1646,120 +1652,88 @@ class Trade(ModelBase, LocalTrade):
 
     use_db: bool = True
 
-    id: Mapped[int] = mapped_column(Integer, primary_key=True)  # type: ignore
+    id: Mapped[int] = mapped_column(Integer, primary_key=True)
 
     orders: Mapped[list[Order]] = relationship(
-        "Order", order_by="Order.id", cascade="all, delete-orphan", lazy="selectin", innerjoin=True
-    )  # type: ignore
+        "Order",
+        order_by="Order.id",
+        cascade="all, delete-orphan",
+        lazy="selectin",
+        innerjoin=True,
+        back_populates="_trade_live",
+    )
     custom_data: Mapped[list[_CustomData]] = relationship(
         "_CustomData", cascade="all, delete-orphan", lazy="raise"
     )
 
-    exchange: Mapped[str] = mapped_column(String(25), nullable=False)  # type: ignore
-    pair: Mapped[str] = mapped_column(String(25), nullable=False, index=True)  # type: ignore
-    base_currency: Mapped[str | None] = mapped_column(String(25), nullable=True)  # type: ignore
-    stake_currency: Mapped[str | None] = mapped_column(String(25), nullable=True)  # type: ignore
-    is_open: Mapped[bool] = mapped_column(nullable=False, default=True, index=True)  # type: ignore
-    fee_open: Mapped[float] = mapped_column(Float(), nullable=False, default=0.0)  # type: ignore
-    fee_open_cost: Mapped[float | None] = mapped_column(Float(), nullable=True)  # type: ignore
-    fee_open_currency: Mapped[str | None] = mapped_column(  # type: ignore
-        String(25), nullable=True
-    )
-    fee_close: Mapped[float | None] = mapped_column(  # type: ignore
-        Float(), nullable=False, default=0.0
-    )
-    fee_close_cost: Mapped[float | None] = mapped_column(Float(), nullable=True)  # type: ignore
-    fee_close_currency: Mapped[str | None] = mapped_column(  # type: ignore
-        String(25), nullable=True
-    )
-    open_rate: Mapped[float] = mapped_column(Float())  # type: ignore
-    open_rate_requested: Mapped[float | None] = mapped_column(  # type: ignore
-        Float(), nullable=True
-    )
+    exchange: Mapped[str] = mapped_column(String(25), nullable=False)
+    pair: Mapped[str] = mapped_column(String(25), nullable=False, index=True)
+    base_currency: Mapped[str | None] = mapped_column(String(25), nullable=True)
+    stake_currency: Mapped[str | None] = mapped_column(String(25), nullable=True)
+    is_open: Mapped[bool] = mapped_column(nullable=False, default=True, index=True)
+    fee_open: Mapped[float] = mapped_column(Float(), nullable=False, default=0.0)
+    # Fee cost in quote currency for entry the trade
+    fee_open_cost: Mapped[float | None] = mapped_column(Float(), nullable=True)
+    # Currency the fee was paid in. Has no relation to fee_open_cost.
+    fee_open_currency: Mapped[str | None] = mapped_column(String(25), nullable=True)
+    fee_close: Mapped[float | None] = mapped_column(Float(), nullable=False, default=0.0)
+    # Fee cost in quote currency for exit orders
+    fee_close_cost: Mapped[float | None] = mapped_column(Float(), nullable=True)
+    fee_close_currency: Mapped[str | None] = mapped_column(String(25), nullable=True)
+    open_rate: Mapped[float] = mapped_column(Float())
+    open_rate_requested: Mapped[float | None] = mapped_column(Float(), nullable=True)
     # open_trade_value - calculated via _calc_open_trade_value
-    open_trade_value: Mapped[float] = mapped_column(Float(), nullable=True)  # type: ignore
-    close_rate: Mapped[float | None] = mapped_column(Float())  # type: ignore
-    close_rate_requested: Mapped[float | None] = mapped_column(Float())  # type: ignore
-    realized_profit: Mapped[float] = mapped_column(  # type: ignore
-        Float(), default=0.0, nullable=True
-    )
-    close_profit: Mapped[float | None] = mapped_column(Float())  # type: ignore
-    close_profit_abs: Mapped[float | None] = mapped_column(Float())  # type: ignore
-    stake_amount: Mapped[float] = mapped_column(Float(), nullable=False)  # type: ignore
-    max_stake_amount: Mapped[float | None] = mapped_column(Float())  # type: ignore
-    amount: Mapped[float] = mapped_column(Float())  # type: ignore
-    amount_requested: Mapped[float | None] = mapped_column(Float())  # type: ignore
-    open_date: Mapped[datetime] = mapped_column(  # type: ignore
-        nullable=False, default=datetime.now
-    )
-    close_date: Mapped[datetime | None] = mapped_column()  # type: ignore
+    open_trade_value: Mapped[float] = mapped_column(Float(), nullable=True)
+    close_rate: Mapped[float | None] = mapped_column(Float())
+    close_rate_requested: Mapped[float | None] = mapped_column(Float())
+    realized_profit: Mapped[float] = mapped_column(Float(), default=0.0, nullable=True)
+    close_profit: Mapped[float | None] = mapped_column(Float())
+    close_profit_abs: Mapped[float | None] = mapped_column(Float())
+    stake_amount: Mapped[float] = mapped_column(Float(), nullable=False)
+    max_stake_amount: Mapped[float | None] = mapped_column(Float())
+    amount: Mapped[float] = mapped_column(Float())
+    amount_requested: Mapped[float | None] = mapped_column(Float())
+    open_date: Mapped[datetime] = mapped_column(nullable=False, default=datetime.now)
+    close_date: Mapped[datetime | None] = mapped_column()
     # absolute value of the stop loss
-    stop_loss: Mapped[float] = mapped_column(Float(), nullable=True, default=0.0)  # type: ignore
+    stop_loss: Mapped[float] = mapped_column(Float(), nullable=True, default=0.0)
     # percentage value of the stop loss
-    stop_loss_pct: Mapped[float | None] = mapped_column(Float(), nullable=True)  # type: ignore
+    stop_loss_pct: Mapped[float | None] = mapped_column(Float(), nullable=True)
     # absolute value of the initial stop loss
-    initial_stop_loss: Mapped[float | None] = mapped_column(  # type: ignore
-        Float(), nullable=True, default=0.0
-    )
+    initial_stop_loss: Mapped[float | None] = mapped_column(Float(), nullable=True, default=0.0)
     # percentage value of the initial stop loss
-    initial_stop_loss_pct: Mapped[float | None] = mapped_column(  # type: ignore
-        Float(), nullable=True
-    )
-    is_stop_loss_trailing: Mapped[bool] = mapped_column(  # type: ignore
-        nullable=False, default=False
-    )
+    initial_stop_loss_pct: Mapped[float | None] = mapped_column(Float(), nullable=True)
+    is_stop_loss_trailing: Mapped[bool] = mapped_column(nullable=False, default=False)
     # absolute value of the highest reached price
-    max_rate: Mapped[float | None] = mapped_column(  # type: ignore
-        Float(), nullable=True, default=0.0
-    )
+    max_rate: Mapped[float | None] = mapped_column(Float(), nullable=True, default=0.0)
     # Lowest price reached
-    min_rate: Mapped[float | None] = mapped_column(Float(), nullable=True)  # type: ignore
-    exit_reason: Mapped[str | None] = mapped_column(  # type: ignore
-        String(CUSTOM_TAG_MAX_LENGTH), nullable=True
-    )
-    exit_order_status: Mapped[str | None] = mapped_column(  # type: ignore
-        String(100), nullable=True
-    )
-    strategy: Mapped[str | None] = mapped_column(String(100), nullable=True)  # type: ignore
-    enter_tag: Mapped[str | None] = mapped_column(  # type: ignore
-        String(CUSTOM_TAG_MAX_LENGTH), nullable=True
-    )
-    timeframe: Mapped[int | None] = mapped_column(Integer, nullable=True)  # type: ignore
+    min_rate: Mapped[float | None] = mapped_column(Float(), nullable=True)
+    exit_reason: Mapped[str | None] = mapped_column(String(CUSTOM_TAG_MAX_LENGTH), nullable=True)
+    exit_order_status: Mapped[str | None] = mapped_column(String(100), nullable=True)
+    strategy: Mapped[str | None] = mapped_column(String(100), nullable=True)
+    enter_tag: Mapped[str | None] = mapped_column(String(CUSTOM_TAG_MAX_LENGTH), nullable=True)
+    timeframe: Mapped[int | None] = mapped_column(Integer, nullable=True)
 
-    trading_mode: Mapped[TradingMode] = mapped_column(  # type: ignore
-        Enum(TradingMode), nullable=True
-    )
-    amount_precision: Mapped[float | None] = mapped_column(  # type: ignore
-        Float(), nullable=True
-    )
-    price_precision: Mapped[float | None] = mapped_column(Float(), nullable=True)  # type: ignore
-    precision_mode: Mapped[int | None] = mapped_column(Integer, nullable=True)  # type: ignore
-    precision_mode_price: Mapped[int | None] = mapped_column(  # type: ignore
-        Integer, nullable=True
-    )
-    contract_size: Mapped[float | None] = mapped_column(Float(), nullable=True)  # type: ignore
+    trading_mode: Mapped[TradingMode] = mapped_column(Enum(TradingMode), nullable=True)
+    amount_precision: Mapped[float | None] = mapped_column(Float(), nullable=True)
+    price_precision: Mapped[float | None] = mapped_column(Float(), nullable=True)
+    precision_mode: Mapped[int | None] = mapped_column(Integer, nullable=True)
+    precision_mode_price: Mapped[int | None] = mapped_column(Integer, nullable=True)
+    contract_size: Mapped[float | None] = mapped_column(Float(), nullable=True)
 
     # Leverage trading properties
-    leverage: Mapped[float] = mapped_column(Float(), nullable=True, default=1.0)  # type: ignore
-    is_short: Mapped[bool] = mapped_column(nullable=False, default=False)  # type: ignore
-    liquidation_price: Mapped[float | None] = mapped_column(  # type: ignore
-        Float(), nullable=True
-    )
+    leverage: Mapped[float] = mapped_column(Float(), nullable=True, default=1.0)
+    is_short: Mapped[bool] = mapped_column(nullable=False, default=False)
+    liquidation_price: Mapped[float | None] = mapped_column(Float(), nullable=True)
 
     # Margin Trading Properties
-    interest_rate: Mapped[float] = mapped_column(  # type: ignore
-        Float(), nullable=False, default=0.0
-    )
+    interest_rate: Mapped[float] = mapped_column(Float(), nullable=False, default=0.0)
 
     # Futures properties
-    funding_fees: Mapped[float | None] = mapped_column(  # type: ignore
-        Float(), nullable=True, default=None
-    )
-    funding_fee_running: Mapped[float | None] = mapped_column(  # type: ignore
-        Float(), nullable=True, default=None
-    )
+    funding_fees: Mapped[float | None] = mapped_column(Float(), nullable=True, default=None)
+    funding_fee_running: Mapped[float | None] = mapped_column(Float(), nullable=True, default=None)
 
-    record_version: Mapped[int] = mapped_column(Integer, nullable=False, default=2)  # type: ignore
+    record_version: Mapped[int] = mapped_column(Integer, nullable=False, default=2)
 
     def __init__(self, **kwargs):
         from_json = kwargs.pop("__FROM_JSON", None)

freqtrade/plugins/pairlistmanager.py

@@ -61,7 +61,7 @@ class PairListManager(LoggingMixin):
         LoggingMixin.__init__(self, logger, refresh_period)
 
     def _check_backtest(self) -> None:
-        if self._config["runmode"] not in (RunMode.BACKTEST, RunMode.EDGE, RunMode.HYPEROPT):
+        if self._config["runmode"] not in (RunMode.BACKTEST, RunMode.HYPEROPT):
             return
 
         pairlist_errors: list[str] = []

freqtrade/rpc/api_server/api_backtest.py

@@ -8,6 +8,7 @@ from typing import Any
 from fastapi import APIRouter, BackgroundTasks, Depends
 from fastapi.exceptions import HTTPException
 
+from freqtrade.configuration import remove_exchange_credentials
 from freqtrade.configuration.config_validation import validate_config_consistency
 from freqtrade.constants import Config
 from freqtrade.data.btanalysis import (
@@ -20,7 +21,6 @@ from freqtrade.data.btanalysis import (
 )
 from freqtrade.enums import BacktestState
 from freqtrade.exceptions import ConfigurationError, DependencyException, OperationalException
-from freqtrade.exchange.common import remove_exchange_credentials
 from freqtrade.ft_types import get_BacktestResultType_default
 from freqtrade.misc import deep_merge_dicts, is_file_in_dir
 from freqtrade.rpc.api_server.api_schemas import (

freqtrade/rpc/api_server/api_v1.py

@@ -263,12 +263,6 @@ def list_custom_data(trade_id: int, key: str | None = Query(None), rpc: RPC = De
         raise HTTPException(status_code=404, detail=str(e))
 
 
-# TODO: Missing response model
-@router.get("/edge", tags=["info"])
-def edge(rpc: RPC = Depends(get_rpc)):
-    return rpc._rpc_edge()
-
-
 @router.get("/show_config", response_model=ShowConfig, tags=["info"])
 def show_config(rpc: RPC | None = Depends(get_rpc_optional), config=Depends(get_config)):
     state: State | str = ""

freqtrade/rpc/rpc.py

@@ -35,7 +35,7 @@ from freqtrade.exchange.exchange_utils import price_to_precision
 from freqtrade.ft_types import AnnotationType
 from freqtrade.loggers import bufferHandler
 from freqtrade.persistence import CustomDataWrapper, KeyValueStore, PairLocks, Trade
-from freqtrade.persistence.models import PairLock
+from freqtrade.persistence.models import PairLock, custom_data_rpc_wrapper
 from freqtrade.plugins.pairlist.pairlist_helpers import expand_pairlist
 from freqtrade.rpc.fiat_convert import CryptoToFiatConverter
 from freqtrade.rpc.rpc_types import RPCSendMsg
@@ -1125,6 +1125,7 @@ class RPC:
                 "cancel_order_count": c_count,
             }
 
+    @custom_data_rpc_wrapper
     def _rpc_list_custom_data(
         self, trade_id: int | None = None, key: str | None = None, limit: int = 100, offset: int = 0
     ) -> list[dict[str, Any]]:
@@ -1137,6 +1138,7 @@ class RPC:
         - "custom_data": a list of custom data dicts, each with the fields:
                 "id", "key", "type", "value", "created_at", "updated_at"
         """
+
         trades: Sequence[Trade]
         if trade_id is None:
             # Get all open trades
@@ -1343,12 +1345,6 @@ class RPC:
 
         return {"log_count": len(records), "logs": records}
 
-    def _rpc_edge(self) -> list[dict[str, Any]]:
-        """Returns information related to Edge"""
-        if not self._freqtrade.edge:
-            raise RPCException("Edge is not enabled.")
-        return self._freqtrade.edge.accepted_pairs()
-
     @staticmethod
     def _convert_dataframe_to_dict(
         strategy: str,

freqtrade/rpc/telegram.py

@@ -215,7 +215,6 @@ class Telegram(RPCHandler):
             r"/forceshort$",
             r"/forcesell$",
             r"/forceexit$",
-            r"/edge$",
             r"/health$",
             r"/help$",
             r"/version$",
@@ -299,7 +298,6 @@ class Telegram(RPCHandler):
             CommandHandler("blacklist", self._blacklist),
             CommandHandler(["blacklist_delete", "bl_delete"], self._blacklist_delete),
             CommandHandler("logs", self._logs),
-            CommandHandler("edge", self._edge),
             CommandHandler("health", self._health),
             CommandHandler("help", self._help),
             CommandHandler("version", self._version),
@@ -1044,12 +1042,15 @@ class Telegram(RPCHandler):
         else:
             # Message to display
             if stats["closed_trade_count"] > 0:
+                fiat_closed_trades = (
+                    f"∙ `{fmt_coin(profit_closed_fiat, fiat_disp_cur)}`\n" if fiat_disp_cur else ""
+                )
                 markdown_msg = (
                     "*ROI:* Closed trades\n"
                     f"∙ `{fmt_coin(profit_closed_coin, stake_cur)} "
                     f"({profit_closed_ratio_mean:.2%}) "
                     f"({profit_closed_percent} \N{GREEK CAPITAL LETTER SIGMA}%)`\n"
-                    f"∙ `{fmt_coin(profit_closed_fiat, fiat_disp_cur)}`\n"
+                    f"{fiat_closed_trades}"
                 )
             else:
                 markdown_msg = "`No closed trade` \n"
@@ -1224,10 +1225,13 @@ class Telegram(RPCHandler):
         total_stake = fmt_coin(
             result["total" if full_result else "total_bot"], result["stake"], False
         )
+        fiat_estimated_value = (
+            f"\t`{result['symbol']}: {value}`{fiat_val}\n" if result["symbol"] else ""
+        )
         output += (
             f"\n*Estimated Value{' (Bot managed assets only)' if not full_result else ''}*:\n"
             f"\t`{result['stake']}: {total_stake}`{stake_improve}\n"
-            f"\t`{result['symbol']}: {value}`{fiat_val}\n"
+            f"{fiat_estimated_value}"
         )
         await self._send_msg(
             output, reload_able=True, callback_path="update_balance", query=update.callback_query
@@ -1789,23 +1793,6 @@ class Telegram(RPCHandler):
         if msgs:
             await self._send_msg(msgs, parse_mode=ParseMode.MARKDOWN_V2)
 
-    @authorized_only
-    async def _edge(self, update: Update, context: CallbackContext) -> None:
-        """
-        Handler for /edge
-        Shows information related to Edge
-        """
-        edge_pairs = self._rpc._rpc_edge()
-        if not edge_pairs:
-            message = "<b>Edge only validated following pairs:</b>"
-            await self._send_msg(message, parse_mode=ParseMode.HTML)
-
-        for chunk in chunks(edge_pairs, 25):
-            edge_pairs_tab = tabulate(chunk, headers="keys", tablefmt="simple")
-            message = f"<b>Edge only validated following pairs:</b>\n<pre>{edge_pairs_tab}</pre>"
-
-            await self._send_msg(message, parse_mode=ParseMode.HTML)
-
     @authorized_only
     async def _help(self, update: Update, context: CallbackContext) -> None:
         """
@@ -1858,7 +1845,6 @@ class Telegram(RPCHandler):
             "*/balance total:* `Show account balance per currency`\n"
             "*/logs [limit]:* `Show latest logs - defaults to 10` \n"
             "*/count:* `Show number of active trades compared to allowed number of trades`\n"
-            "*/edge:* `Shows validated pairs by Edge if it is enabled` \n"
             "*/health* `Show latest process timestamp - defaults to 1970-01-01 00:00:00` \n"
             "*/marketdir [long | short | even | none]:* `Updates the user managed variable "
             "that represents the current market direction. If no direction is provided `"

freqtrade/wallets.py

@@ -352,7 +352,7 @@ class Wallets:
         return max(stake_amount, 0)
 
     def get_trade_stake_amount(
-        self, pair: str, max_open_trades: IntOrInf, edge=None, update: bool = True
+        self, pair: str, max_open_trades: IntOrInf, update: bool = True
     ) -> float:
         """
         Calculate stake amount for the trade
@@ -366,19 +366,11 @@ class Wallets:
         val_tied_up = Trade.total_open_trades_stakes()
         available_amount = self.get_available_stake_amount()
 
-        if edge:
-            stake_amount = edge.stake_amount(
-                pair,
-                self.get_free(self._stake_currency),
-                self.get_total(self._stake_currency),
-                val_tied_up,
+        stake_amount = self._config["stake_amount"]
+        if stake_amount == UNLIMITED_STAKE_AMOUNT:
+            stake_amount = self._calculate_unlimited_stake_amount(
+                available_amount, val_tied_up, max_open_trades
             )
-        else:
-            stake_amount = self._config["stake_amount"]
-            if stake_amount == UNLIMITED_STAKE_AMOUNT:
-                stake_amount = self._calculate_unlimited_stake_amount(
-                    available_amount, val_tied_up, max_open_trades
-                )
 
         return self._check_available_stake_amount(stake_amount, available_amount)
 

ft_client/freqtrade_client/__init__.py

@@ -1,7 +1,7 @@
 from freqtrade_client.ft_rest_client import FtRestClient
 
 
-__version__ = "2025.5"
+__version__ = "2025.6"
 
 if "dev" in __version__:
     from pathlib import Path

ft_client/freqtrade_client/ft_rest_client.py

@@ -189,13 +189,6 @@ class FtRestClient:
         """
         return self._get("monthly", params={"timescale": months} if months else None)
 
-    def edge(self):
-        """Return information about edge.
-
-        :return: json object
-        """
-        return self._get("edge")
-
     def profit(self):
         """Return the profit summary.
 
@@ -268,8 +261,8 @@ class FtRestClient:
             params["limit"] = limit
         if offset:
             params["offset"] = offset
-        if order_by_id:
-            params["order_by_id"] = True
+        if not order_by_id:
+            params["order_by_id"] = False
         return self._get("trades", params)
 
     def list_open_trades_custom_data(self, key=None, limit=100, offset=0):

ft_client/pyproject.toml

@@ -23,6 +23,7 @@ classifiers = [
     "Programming Language :: Python :: 3.10",
     "Programming Language :: Python :: 3.11",
     "Programming Language :: Python :: 3.12",
+    "Programming Language :: Python :: 3.13",
     "Operating System :: MacOS",
     "Operating System :: Unix",
     "Topic :: Office/Business :: Financial :: Investment",

ft_client/requirements.txt

@@ -1,3 +1,3 @@
 # Requirements for freqtrade client library
-requests==2.32.3
+requests==2.32.4
 python-rapidjson==1.20

ft_client/test_client/test_rest_client.py

@@ -72,7 +72,6 @@ def test_FtRestClient_call_invalid(caplog):
         ("weekly", [15], {}),
         ("monthly", [], {}),
         ("monthly", [12], {}),
-        ("edge", [], {}),
         ("profit", [], {}),
         ("stats", [], {}),
         ("performance", [], {}),

mkdocs.yml

@@ -52,7 +52,6 @@ nav:
         - Orderflow: advanced-orderflow.md
         - Producer/Consumer mode: producer-consumer.md
         - SQL Cheat-sheet: sql_cheatsheet.md
-        - Edge Positioning: edge.md
     - FAQ: faq.md
     - Strategy migration: strategy_migration.md
     - Updating Freqtrade: updating.md
@@ -62,11 +61,14 @@ theme:
   name: material
   logo: "images/logo.png"
   favicon: "images/logo.png"
+  icon:
+    repo: fontawesome/brands/github
   custom_dir: "docs/overrides"
   features:
     - content.code.annotate
     - search.share
     - content.code.copy
+    - content.action.edit
     - navigation.top
     - navigation.footer
   palette:
@@ -115,6 +117,9 @@ markdown_extensions:
       custom_checkbox: true
   - pymdownx.tilde
   - mdx_truly_sane_lists
+  - pymdownx.emoji:
+      emoji_index: !!python/name:material.extensions.emoji.twemoji
+      emoji_generator: !!python/name:material.extensions.emoji.to_svg
 extra:
   version:
     provider: mike

pyproject.toml

@@ -22,6 +22,7 @@ classifiers = [
     "Programming Language :: Python :: 3.10",
     "Programming Language :: Python :: 3.11",
     "Programming Language :: Python :: 3.12",
+    "Programming Language :: Python :: 3.13",
     "Operating System :: MacOS",
     "Operating System :: Unix",
     "Topic :: Office/Business :: Financial :: Investment",
@@ -29,7 +30,7 @@ classifiers = [
 
 dependencies = [
   # from requirements.txt
-  "ccxt>=4.4.60",
+  "ccxt>=4.4.87",
   "SQLAlchemy>=2.0.6",
   "python-telegram-bot>=20.1",
   "humanize>=4.0.0",
@@ -38,14 +39,13 @@ dependencies = [
   "httpx>=0.24.1",
   "urllib3",
   "jsonschema",
-  "numpy<2.0",
+  "numpy>2.0,<3.0",
   "pandas>=2.2.0,<3.0",
-  "TA-Lib",
-  "pandas-ta",
+  "TA-Lib<0.6",
+  "ft-pandas-ta",
   "technical",
   "tabulate",
   "pycoingecko>=3.2.0",
-  "py_find_1st",
   "python-rapidjson",
   "orjson",
   "jinja2",
@@ -100,7 +100,6 @@ freqai_rl = [
   "tqdm",
 ]
 develop = [
-  "coveralls",
   "isort",
   "mypy",
   "pre-commit",
@@ -207,6 +206,14 @@ plugins = [
 module = "tests.*"
 ignore_errors = true
 
+[[tool.mypy.overrides]]
+module = [
+  "freqtrade.templates.*",
+  "tests.strategy.strats"
+]
+# Disable attr-defined check due to ta-lib not having type stubs
+disable_error_code = "attr-defined"
+
 [tool.pyright]
 include = ["freqtrade", "ft_client"]
 exclude = [
@@ -283,6 +290,7 @@ extend-ignore = [
   "RUF010",  # Use explicit conversion flag
   "RUF012",  # mutable-class-default
   "RUF022",  # unsorted-dunder-all
+  "RUF005",  # list concatenation
 ]
 
 [tool.ruff.lint.mccabe]

requirements-dev.txt

@@ -6,17 +6,16 @@
 -r requirements-freqai-rl.txt
 -r docs/requirements-docs.txt
 
-coveralls==4.0.1
-ruff==0.11.11
-mypy==1.15.0
+ruff==0.12.1
+mypy==1.16.1
 pre-commit==4.2.0
-pytest==8.3.5
-pytest-asyncio==0.26.0
-pytest-cov==6.1.1
-pytest-mock==3.14.0
-pytest-random-order==1.1.1
+pytest==8.4.1
+pytest-asyncio==1.0.0
+pytest-cov==6.2.1
+pytest-mock==3.14.1
+pytest-random-order==1.2.0
 pytest-timeout==2.4.0
-pytest-xdist==3.6.1
+pytest-xdist==3.7.0
 isort==6.0.1
 # For datetime mocking
 time-machine==2.16.0
@@ -27,6 +26,6 @@ nbconvert==7.16.6
 # mypy types
 types-cachetools==6.0.0.20250525
 types-filelock==3.2.7
-types-requests==2.32.0.20250515
+types-requests==2.32.4.20250611
 types-tabulate==0.9.0.20241207
 types-python-dateutil==2.9.0.20250516

requirements-freqai-rl.txt

@@ -2,11 +2,10 @@
 -r requirements-freqai.txt
 
 # Required for freqai-rl
-torch==2.7.0; sys_platform != 'darwin' or platform_machine != 'x86_64'
+torch==2.7.1; sys_platform != 'darwin' or platform_machine != 'x86_64'
 gymnasium==0.29.1
 # SB3 >=2.5.0 depends on torch 2.3.0 - which implies it dropped support x86 macos
-stable_baselines3==2.4.1; sys_platform == 'darwin' and platform_machine == 'x86_64'
-stable_baselines3==2.5.0; sys_platform != 'darwin' or platform_machine != 'x86_64'
+stable_baselines3==2.6.0; sys_platform != 'darwin' or platform_machine != 'x86_64'
 sb3_contrib>=2.2.1
 # Progress bar for stable-baselines3 and sb3-contrib
 tqdm==4.67.1

requirements-freqai.txt

@@ -3,7 +3,7 @@
 -r requirements-plot.txt
 
 # Required for freqai
-scikit-learn==1.6.1
+scikit-learn==1.7.0
 joblib==1.5.1
 catboost==1.2.8; 'arm' not in platform_machine
 lightgbm==4.6.0

requirements-hyperopt.txt

@@ -3,7 +3,7 @@
 
 # Required for hyperopt
 scipy==1.15.3
-scikit-learn==1.6.1
+scikit-learn==1.7.0
 filelock==3.18.0
-optuna==4.3.0
+optuna==4.4.0
 cmaes==0.11.1

requirements-plot.txt

@@ -1,4 +1,4 @@
 # Include all requirements to run the bot.
 -r requirements.txt
 
-plotly==6.1.1
+plotly==6.2.0

requirements.txt

@@ -1,24 +1,25 @@
-numpy==1.26.4
-pandas==2.2.3
-bottleneck==1.4.2
-numexpr==2.10.2
-pandas-ta==0.3.14b
+numpy==2.2.6
+pandas==2.3.0
+bottleneck==1.5.0
+numexpr==2.11.0
+# Indicator libraries
+ft-pandas-ta==0.3.15
+ta-lib==0.5.5
+technical==1.5.1
 
-ccxt==4.4.82
-cryptography==45.0.3
-aiohttp==3.9.5
+ccxt==4.4.91
+cryptography==45.0.4
+aiohttp==3.12.13
 SQLAlchemy==2.0.41
-python-telegram-bot==22.1
+python-telegram-bot==22.2
 # can't be hard-pinned due to telegram-bot pinning httpx with ~
 httpx>=0.24.1
 humanize==4.12.3
-cachetools==6.0.0
-requests==2.32.3
-urllib3==2.4.0
-certifi==2025.4.26
-jsonschema==4.23.0
-TA-Lib==0.4.38
-technical==1.5.0
+cachetools==6.1.0
+requests==2.32.4
+urllib3==2.5.0
+certifi==2025.6.15
+jsonschema==4.24.0
 tabulate==0.9.0
 pycoingecko==3.2.0
 jinja2==3.1.6
@@ -26,9 +27,6 @@ joblib==1.5.1
 rich==14.0.0
 pyarrow==20.0.0; platform_machine != 'armv7l'
 
-# find first, C search in arrays
-py_find_1st==1.1.7
-
 # Load ticker files 30% faster
 python-rapidjson==1.20
 # Properly format api responses
@@ -38,9 +36,9 @@ orjson==3.10.18
 sdnotify==0.3.2
 
 # API Server
-fastapi==0.115.12
-pydantic==2.11.5
-uvicorn==0.34.2
+fastapi==0.115.14
+pydantic==2.11.7
+uvicorn==0.35.0
 pyjwt==2.10.1
 aiofiles==24.1.0
 psutil==7.0.0
@@ -59,5 +57,5 @@ schedule==1.2.2
 websockets==15.0.1
 janus==2.0.0
 
-ast-comments==1.2.2
+ast-comments==1.2.3
 packaging==25.0

setup.ps1

@@ -150,13 +150,16 @@ function Test-PythonExecutable {
 function Find-PythonExecutable {
   $PythonExecutables = @(
     "python",
+    "python3.13",
     "python3.12",
     "python3.11",
     "python3.10",
     "python3",
+    "C:\Users\$env:USERNAME\AppData\Local\Programs\Python\Python313\python.exe",
     "C:\Users\$env:USERNAME\AppData\Local\Programs\Python\Python312\python.exe",
     "C:\Users\$env:USERNAME\AppData\Local\Programs\Python\Python311\python.exe",
     "C:\Users\$env:USERNAME\AppData\Local\Programs\Python\Python310\python.exe",
+    "C:\Python313\python.exe",
     "C:\Python312\python.exe",
     "C:\Python311\python.exe",
     "C:\Python310\python.exe"

setup.sh

@@ -25,7 +25,7 @@ function check_installed_python() {
         exit 2
     fi
 
-    for v in 12 11 10
+    for v in 13 12 11 10
     do
         PYTHON="python3.${v}"
         which $PYTHON
@@ -257,7 +257,7 @@ function install() {
         install_redhat
     else
         echo "This script does not support your OS."
-        echo "If you have Python version 3.10 - 3.12, pip, virtualenv, ta-lib you can continue."
+        echo "If you have Python version 3.10 - 3.13, pip, virtualenv, ta-lib you can continue."
         echo "Wait 10 seconds to continue the next install steps or use ctrl+c to interrupt this shell."
         sleep 10
     fi

tests/commands/test_commands.py

@@ -16,6 +16,7 @@ from freqtrade.commands import (
     start_convert_trades,
     start_create_userdir,
     start_download_data,
+    start_edge,
     start_hyperopt_list,
     start_hyperopt_show,
     start_install_ui,
@@ -1937,3 +1938,15 @@ def test_start_show_config(capsys, caplog):
     assert '"max_open_trades":' in captured.out
     assert '"secret": "REDACTED"' not in captured.out
     assert log_has_re(r"Sensitive information will be shown in the upcoming output.*", caplog)
+
+
+def test_start_edge():
+    args = [
+        "edge",
+        "--config",
+        "tests/testdata/testconfigs/main_test_config.json",
+    ]
+
+    pargs = get_args(args)
+    with pytest.raises(OperationalException, match="The Edge module has been deprecated in 2023.9"):
+        start_edge(pargs)

tests/conftest.py

@@ -16,8 +16,7 @@ from xdist.scheduler.loadscope import LoadScopeScheduling
 from freqtrade import constants
 from freqtrade.commands import Arguments
 from freqtrade.data.converter import ohlcv_to_dataframe, trades_list_to_df
-from freqtrade.edge import PairInfo
-from freqtrade.enums import CandleType, MarginMode, RunMode, SignalDirection, TradingMode
+from freqtrade.enums import CandleType, MarginMode, SignalDirection, TradingMode
 from freqtrade.exchange import Exchange, timeframe_to_minutes, timeframe_to_seconds
 from freqtrade.freqtradebot import FreqtradeBot
 from freqtrade.persistence import LocalTrade, Order, Trade, init_db
@@ -298,24 +297,6 @@ def patch_whitelist(mocker, conf) -> None:
     )
 
 
-def patch_edge(mocker) -> None:
-    # "ETH/BTC",
-    # "LTC/BTC",
-    # "XRP/BTC",
-    # "NEO/BTC"
-
-    mocker.patch(
-        "freqtrade.edge.Edge._cached_pairs",
-        mocker.PropertyMock(
-            return_value={
-                "NEO/BTC": PairInfo(-0.20, 0.66, 3.71, 0.50, 1.71, 10, 25),
-                "LTC/BTC": PairInfo(-0.21, 0.66, 3.71, 0.50, 1.71, 11, 20),
-            }
-        ),
-    )
-    mocker.patch("freqtrade.edge.Edge.calculate", MagicMock(return_value=True))
-
-
 # Functions for recurrent object patching
 
 
@@ -2603,31 +2584,6 @@ def buy_order_fee():
     }
 
 
-@pytest.fixture(scope="function")
-def edge_conf(default_conf):
-    conf = deepcopy(default_conf)
-    conf["runmode"] = RunMode.DRY_RUN
-    conf["max_open_trades"] = -1
-    conf["tradable_balance_ratio"] = 0.5
-    conf["stake_amount"] = constants.UNLIMITED_STAKE_AMOUNT
-    conf["edge"] = {
-        "enabled": True,
-        "process_throttle_secs": 1800,
-        "calculate_since_number_of_days": 14,
-        "allowed_risk": 0.01,
-        "stoploss_range_min": -0.01,
-        "stoploss_range_max": -0.1,
-        "stoploss_range_step": -0.01,
-        "maximum_winrate": 0.80,
-        "minimum_expectancy": 0.20,
-        "min_trade_number": 15,
-        "max_trade_duration_minute": 1440,
-        "remove_pumps": False,
-    }
-
-    return conf
-
-
 @pytest.fixture
 def rpc_balance():
     return {

tests/edge/test_edge.py

@@ -1,606 +0,0 @@
-# pragma pylint: disable=missing-docstring, C0103, C0330
-# pragma pylint: disable=protected-access, too-many-lines, invalid-name, too-many-arguments
-
-import logging
-import math
-from datetime import timedelta
-from unittest.mock import MagicMock
-
-import numpy as np
-import pytest
-from pandas import DataFrame
-
-from freqtrade.data.converter import ohlcv_to_dataframe
-from freqtrade.edge import Edge, PairInfo
-from freqtrade.enums import ExitType
-from freqtrade.exceptions import OperationalException
-from freqtrade.util.datetime_helpers import dt_ts, dt_utc
-from tests.conftest import EXMS, get_patched_freqtradebot, log_has
-from tests.optimize import (
-    BTContainer,
-    BTrade,
-    _build_backtest_dataframe,
-    _get_frame_time_from_offset,
-)
-
-
-# Cases to be tested:
-# 1) Open trade should be removed from the end
-# 2) Two complete trades within dataframe (with sell hit for all)
-# 3) Entered, sl 1%, candle drops 8% => Trade closed, 1% loss
-# 4) Entered, sl 3%, candle drops 4%, recovers to 1% => Trade closed, 3% loss
-# 5) Stoploss and sell are hit. should sell on stoploss
-####################################################################
-
-tests_start_time = dt_utc(2018, 10, 3)
-timeframe_in_minute = 60
-
-# End helper functions
-# Open trade should be removed from the end
-tc0 = BTContainer(
-    data=[
-        # D  O     H     L     C     V    B  S
-        [0, 5000, 5025, 4975, 4987, 6172, 1, 0],
-        [1, 5000, 5025, 4975, 4987, 6172, 0, 1],
-    ],  # enter trade (signal on last candle)
-    stop_loss=-0.99,
-    roi={"0": float("inf")},
-    profit_perc=0.00,
-    trades=[],
-)
-
-# Two complete trades within dataframe(with sell hit for all)
-tc1 = BTContainer(
-    data=[
-        # D  O     H     L     C     V    B  S
-        [0, 5000, 5025, 4975, 4987, 6172, 1, 0],
-        [1, 5000, 5025, 4975, 4987, 6172, 0, 1],  # enter trade (signal on last candle)
-        [2, 5000, 5025, 4975, 4987, 6172, 0, 0],  # exit at open
-        [3, 5000, 5025, 4975, 4987, 6172, 1, 0],  # no action
-        [4, 5000, 5025, 4975, 4987, 6172, 0, 0],  # should enter the trade
-        [5, 5000, 5025, 4975, 4987, 6172, 0, 1],  # no action
-        [6, 5000, 5025, 4975, 4987, 6172, 0, 0],  # should sell
-    ],
-    stop_loss=-0.99,
-    roi={"0": float("inf")},
-    profit_perc=0.00,
-    trades=[
-        BTrade(exit_reason=ExitType.EXIT_SIGNAL, open_tick=1, close_tick=2),
-        BTrade(exit_reason=ExitType.EXIT_SIGNAL, open_tick=4, close_tick=6),
-    ],
-)
-
-# 3) Entered, sl 1%, candle drops 8% => Trade closed, 1% loss
-tc2 = BTContainer(
-    data=[
-        # D  O     H     L     C     V    B  S
-        [0, 5000, 5025, 4975, 4987, 6172, 1, 0],
-        [1, 5000, 5025, 4600, 4987, 6172, 0, 0],  # enter trade, stoploss hit
-        [2, 5000, 5025, 4975, 4987, 6172, 0, 0],
-    ],
-    stop_loss=-0.01,
-    roi={"0": float("inf")},
-    profit_perc=-0.01,
-    trades=[BTrade(exit_reason=ExitType.STOP_LOSS, open_tick=1, close_tick=1)],
-)
-
-# 4) Entered, sl 3 %, candle drops 4%, recovers to 1 % = > Trade closed, 3 % loss
-tc3 = BTContainer(
-    data=[
-        # D  O     H     L     C     V    B  S
-        [0, 5000, 5025, 4975, 4987, 6172, 1, 0],
-        [1, 5000, 5025, 4800, 4987, 6172, 0, 0],  # enter trade, stoploss hit
-        [2, 5000, 5025, 4975, 4987, 6172, 0, 0],
-    ],
-    stop_loss=-0.03,
-    roi={"0": float("inf")},
-    profit_perc=-0.03,
-    trades=[BTrade(exit_reason=ExitType.STOP_LOSS, open_tick=1, close_tick=1)],
-)
-
-# 5) Stoploss and sell are hit. should sell on stoploss
-tc4 = BTContainer(
-    data=[
-        # D  O     H     L     C     V    B  S
-        [0, 5000, 5025, 4975, 4987, 6172, 1, 0],
-        [1, 5000, 5025, 4800, 4987, 6172, 0, 1],  # enter trade, stoploss hit, sell signal
-        [2, 5000, 5025, 4975, 4987, 6172, 0, 0],
-    ],
-    stop_loss=-0.03,
-    roi={"0": float("inf")},
-    profit_perc=-0.03,
-    trades=[BTrade(exit_reason=ExitType.STOP_LOSS, open_tick=1, close_tick=1)],
-)
-
-TESTS = [tc0, tc1, tc2, tc3, tc4]
-
-
-@pytest.mark.parametrize("data", TESTS)
-def test_edge_results(edge_conf, mocker, caplog, data) -> None:
-    """
-    run functional tests
-    """
-    freqtrade = get_patched_freqtradebot(mocker, edge_conf)
-    edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy)
-    frame = _build_backtest_dataframe(data.data)
-    caplog.set_level(logging.DEBUG)
-    edge.fee = 0
-
-    trades = edge._find_trades_for_stoploss_range(frame, "TEST/BTC", [data.stop_loss])
-    results = edge._fill_calculable_fields(DataFrame(trades)) if trades else DataFrame()
-
-    assert len(trades) == len(data.trades)
-
-    if not results.empty:
-        assert round(results["profit_ratio"].sum(), 3) == round(data.profit_perc, 3)
-
-    for c, trade in enumerate(data.trades):
-        res = results.iloc[c]
-        assert res.exit_type == trade.exit_reason
-        assert res.open_date == _get_frame_time_from_offset(trade.open_tick).replace(tzinfo=None)
-        assert res.close_date == _get_frame_time_from_offset(trade.close_tick).replace(tzinfo=None)
-
-
-def test_adjust(mocker, edge_conf):
-    freqtrade = get_patched_freqtradebot(mocker, edge_conf)
-    edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy)
-    mocker.patch(
-        "freqtrade.edge.Edge._cached_pairs",
-        mocker.PropertyMock(
-            return_value={
-                "E/F": PairInfo(-0.01, 0.66, 3.71, 0.50, 1.71, 10, 60),
-                "C/D": PairInfo(-0.01, 0.66, 3.71, 0.50, 1.71, 10, 60),
-                "N/O": PairInfo(-0.01, 0.66, 3.71, 0.50, 1.71, 10, 60),
-            }
-        ),
-    )
-
-    pairs = ["A/B", "C/D", "E/F", "G/H"]
-    assert edge.adjust(pairs) == ["E/F", "C/D"]
-
-
-def test_edge_get_stoploss(mocker, edge_conf):
-    freqtrade = get_patched_freqtradebot(mocker, edge_conf)
-    edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy)
-    mocker.patch(
-        "freqtrade.edge.Edge._cached_pairs",
-        mocker.PropertyMock(
-            return_value={
-                "E/F": PairInfo(-0.01, 0.66, 3.71, 0.50, 1.71, 10, 60),
-                "C/D": PairInfo(-0.01, 0.66, 3.71, 0.50, 1.71, 10, 60),
-                "N/O": PairInfo(-0.01, 0.66, 3.71, 0.50, 1.71, 10, 60),
-            }
-        ),
-    )
-
-    assert edge.get_stoploss("E/F") == -0.01
-
-
-def test_nonexisting_get_stoploss(mocker, edge_conf):
-    freqtrade = get_patched_freqtradebot(mocker, edge_conf)
-    edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy)
-    mocker.patch(
-        "freqtrade.edge.Edge._cached_pairs",
-        mocker.PropertyMock(
-            return_value={
-                "E/F": PairInfo(-0.01, 0.66, 3.71, 0.50, 1.71, 10, 60),
-            }
-        ),
-    )
-
-    assert edge.get_stoploss("N/O") == -0.1
-
-
-def test_edge_stake_amount(mocker, edge_conf):
-    freqtrade = get_patched_freqtradebot(mocker, edge_conf)
-    edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy)
-    mocker.patch(
-        "freqtrade.edge.Edge._cached_pairs",
-        mocker.PropertyMock(
-            return_value={
-                "E/F": PairInfo(-0.02, 0.66, 3.71, 0.50, 1.71, 10, 60),
-            }
-        ),
-    )
-    assert edge._capital_ratio == 0.5
-    assert (
-        edge.stake_amount("E/F", free_capital=100, total_capital=100, capital_in_trade=25) == 31.25
-    )
-
-    assert edge.stake_amount("E/F", free_capital=20, total_capital=100, capital_in_trade=25) == 20
-
-    assert edge.stake_amount("E/F", free_capital=0, total_capital=100, capital_in_trade=25) == 0
-
-    # Test with increased allowed_risk
-    # Result should be no more than allowed capital
-    edge._allowed_risk = 0.4
-    edge._capital_ratio = 0.5
-    assert (
-        edge.stake_amount("E/F", free_capital=100, total_capital=100, capital_in_trade=25) == 62.5
-    )
-
-    assert edge.stake_amount("E/F", free_capital=100, total_capital=100, capital_in_trade=0) == 50
-
-    edge._capital_ratio = 1
-    # Full capital is available
-    assert edge.stake_amount("E/F", free_capital=100, total_capital=100, capital_in_trade=0) == 100
-    # Full capital is available
-    assert edge.stake_amount("E/F", free_capital=0, total_capital=100, capital_in_trade=0) == 0
-
-
-def test_nonexisting_stake_amount(mocker, edge_conf):
-    freqtrade = get_patched_freqtradebot(mocker, edge_conf)
-    edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy)
-    mocker.patch(
-        "freqtrade.edge.Edge._cached_pairs",
-        mocker.PropertyMock(
-            return_value={
-                "E/F": PairInfo(-0.11, 0.66, 3.71, 0.50, 1.71, 10, 60),
-            }
-        ),
-    )
-    # should use strategy stoploss
-    assert edge.stake_amount("N/O", 1, 2, 1) == 0.15
-
-
-def test_edge_heartbeat_calculate(mocker, edge_conf):
-    freqtrade = get_patched_freqtradebot(mocker, edge_conf)
-    edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy)
-    heartbeat = edge_conf["edge"]["process_throttle_secs"]
-
-    # should not recalculate if heartbeat not reached
-    edge._last_updated = dt_ts() - heartbeat + 1
-
-    assert edge.calculate(edge_conf["exchange"]["pair_whitelist"]) is False
-
-
-def mocked_load_data(datadir, pairs=None, timeframe="0m", timerange=None, *args, **kwargs):
-    if pairs is None:
-        pairs = []
-    hz = 0.1
-    base = 0.001
-
-    NEOBTC = [
-        [
-            dt_ts(tests_start_time + timedelta(minutes=(x * timeframe_in_minute))),
-            math.sin(x * hz) / 1000 + base,
-            math.sin(x * hz) / 1000 + base + 0.0001,
-            math.sin(x * hz) / 1000 + base - 0.0001,
-            math.sin(x * hz) / 1000 + base,
-            123.45,
-        ]
-        for x in range(0, 500)
-    ]
-
-    hz = 0.2
-    base = 0.002
-    LTCBTC = [
-        [
-            dt_ts(tests_start_time + timedelta(minutes=(x * timeframe_in_minute))),
-            math.sin(x * hz) / 1000 + base,
-            math.sin(x * hz) / 1000 + base + 0.0001,
-            math.sin(x * hz) / 1000 + base - 0.0001,
-            math.sin(x * hz) / 1000 + base,
-            123.45,
-        ]
-        for x in range(0, 500)
-    ]
-
-    pairdata = {
-        "NEO/BTC": ohlcv_to_dataframe(NEOBTC, "1h", pair="NEO/BTC", fill_missing=True),
-        "LTC/BTC": ohlcv_to_dataframe(LTCBTC, "1h", pair="LTC/BTC", fill_missing=True),
-    }
-    return pairdata
-
-
-def test_edge_process_downloaded_data(mocker, edge_conf):
-    freqtrade = get_patched_freqtradebot(mocker, edge_conf)
-    mocker.patch(f"{EXMS}.get_fee", MagicMock(return_value=0.001))
-    mocker.patch("freqtrade.edge.edge_positioning.refresh_data", MagicMock())
-    mocker.patch("freqtrade.edge.edge_positioning.load_data", mocked_load_data)
-    edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy)
-
-    assert edge.calculate(edge_conf["exchange"]["pair_whitelist"])
-    assert len(edge._cached_pairs) == 2
-    assert edge._last_updated <= dt_ts() + 2
-
-
-def test_edge_process_no_data(mocker, edge_conf, caplog):
-    freqtrade = get_patched_freqtradebot(mocker, edge_conf)
-    mocker.patch(f"{EXMS}.get_fee", MagicMock(return_value=0.001))
-    mocker.patch("freqtrade.edge.edge_positioning.refresh_data", MagicMock())
-    mocker.patch("freqtrade.edge.edge_positioning.load_data", MagicMock(return_value={}))
-    edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy)
-
-    assert not edge.calculate(edge_conf["exchange"]["pair_whitelist"])
-    assert len(edge._cached_pairs) == 0
-    assert log_has("No data found. Edge is stopped ...", caplog)
-    assert edge._last_updated == 0
-
-
-def test_edge_process_no_trades(mocker, edge_conf, caplog):
-    freqtrade = get_patched_freqtradebot(mocker, edge_conf)
-    mocker.patch(f"{EXMS}.get_fee", return_value=0.001)
-    mocker.patch(
-        "freqtrade.edge.edge_positioning.refresh_data",
-    )
-    mocker.patch("freqtrade.edge.edge_positioning.load_data", mocked_load_data)
-    # Return empty
-    mocker.patch("freqtrade.edge.Edge._find_trades_for_stoploss_range", return_value=[])
-    edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy)
-
-    assert not edge.calculate(edge_conf["exchange"]["pair_whitelist"])
-    assert len(edge._cached_pairs) == 0
-    assert log_has("No trades found.", caplog)
-
-
-def test_edge_process_no_pairs(mocker, edge_conf, caplog):
-    edge_conf["exchange"]["pair_whitelist"] = []
-    mocker.patch("freqtrade.freqtradebot.validate_config_consistency")
-
-    freqtrade = get_patched_freqtradebot(mocker, edge_conf)
-    fee_mock = mocker.patch(f"{EXMS}.get_fee", return_value=0.001)
-    mocker.patch("freqtrade.edge.edge_positioning.refresh_data")
-    mocker.patch("freqtrade.edge.edge_positioning.load_data", mocked_load_data)
-    # Return empty
-    mocker.patch("freqtrade.edge.Edge._find_trades_for_stoploss_range", return_value=[])
-    edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy)
-    assert fee_mock.call_count == 0
-    assert edge.fee is None
-
-    assert not edge.calculate(["XRP/USDT"])
-    assert fee_mock.call_count == 1
-    assert edge.fee == 0.001
-
-
-def test_edge_init_error(mocker, edge_conf):
-    edge_conf["stake_amount"] = 0.5
-    mocker.patch(f"{EXMS}.get_fee", MagicMock(return_value=0.001))
-    with pytest.raises(OperationalException, match="Edge works only with unlimited stake amount"):
-        get_patched_freqtradebot(mocker, edge_conf)
-
-
-@pytest.mark.parametrize(
-    "fee,risk_reward_ratio,expectancy",
-    [
-        (0.0005, 306.5384615384, 101.5128205128),
-        (0.001, 152.6923076923, 50.2307692308),
-    ],
-)
-def test_process_expectancy(mocker, edge_conf, fee, risk_reward_ratio, expectancy):
-    edge_conf["edge"]["min_trade_number"] = 2
-    freqtrade = get_patched_freqtradebot(mocker, edge_conf)
-
-    def get_fee(*args, **kwargs):
-        return fee
-
-    freqtrade.exchange.get_fee = get_fee
-    edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy)
-
-    trades = [
-        {
-            "pair": "TEST/BTC",
-            "stoploss": -0.9,
-            "profit_percent": "",
-            "profit_abs": "",
-            "open_date": np.datetime64("2018-10-03T00:05:00.000000000"),
-            "close_date": np.datetime64("2018-10-03T00:10:00.000000000"),
-            "trade_duration": "",
-            "open_rate": 17,
-            "close_rate": 17,
-            "exit_type": "exit_signal",
-        },
-        {
-            "pair": "TEST/BTC",
-            "stoploss": -0.9,
-            "profit_percent": "",
-            "profit_abs": "",
-            "open_date": np.datetime64("2018-10-03T00:20:00.000000000"),
-            "close_date": np.datetime64("2018-10-03T00:25:00.000000000"),
-            "trade_duration": "",
-            "open_rate": 20,
-            "close_rate": 20,
-            "exit_type": "exit_signal",
-        },
-        {
-            "pair": "TEST/BTC",
-            "stoploss": -0.9,
-            "profit_percent": "",
-            "profit_abs": "",
-            "open_date": np.datetime64("2018-10-03T00:30:00.000000000"),
-            "close_date": np.datetime64("2018-10-03T00:40:00.000000000"),
-            "trade_duration": "",
-            "open_rate": 26,
-            "close_rate": 34,
-            "exit_type": "exit_signal",
-        },
-    ]
-
-    trades_df = DataFrame(trades)
-    trades_df = edge._fill_calculable_fields(trades_df)
-    final = edge._process_expectancy(trades_df)
-    assert len(final) == 1
-
-    assert "TEST/BTC" in final
-    assert final["TEST/BTC"].stoploss == -0.9
-    assert round(final["TEST/BTC"].winrate, 10) == 0.3333333333
-    assert round(final["TEST/BTC"].risk_reward_ratio, 10) == risk_reward_ratio
-    assert round(final["TEST/BTC"].required_risk_reward, 10) == 2.0
-    assert round(final["TEST/BTC"].expectancy, 10) == expectancy
-
-    # Pop last item so no trade is profitable
-    trades.pop()
-    trades_df = DataFrame(trades)
-    trades_df = edge._fill_calculable_fields(trades_df)
-    final = edge._process_expectancy(trades_df)
-    assert len(final) == 0
-    assert isinstance(final, dict)
-
-
-def test_process_expectancy_remove_pumps(mocker, edge_conf, fee):
-    edge_conf["edge"]["min_trade_number"] = 2
-    edge_conf["edge"]["remove_pumps"] = True
-    freqtrade = get_patched_freqtradebot(mocker, edge_conf)
-
-    freqtrade.exchange.get_fee = fee
-    edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy)
-
-    trades = [
-        {
-            "pair": "TEST/BTC",
-            "stoploss": -0.9,
-            "profit_percent": "",
-            "profit_abs": "",
-            "open_date": np.datetime64("2018-10-03T00:05:00.000000000"),
-            "close_date": np.datetime64("2018-10-03T00:10:00.000000000"),
-            "open_index": 1,
-            "close_index": 1,
-            "trade_duration": "",
-            "open_rate": 17,
-            "close_rate": 15,
-            "exit_type": "sell_signal",
-        },
-        {
-            "pair": "TEST/BTC",
-            "stoploss": -0.9,
-            "profit_percent": "",
-            "profit_abs": "",
-            "open_date": np.datetime64("2018-10-03T00:20:00.000000000"),
-            "close_date": np.datetime64("2018-10-03T00:25:00.000000000"),
-            "open_index": 4,
-            "close_index": 4,
-            "trade_duration": "",
-            "open_rate": 20,
-            "close_rate": 10,
-            "exit_type": "sell_signal",
-        },
-        {
-            "pair": "TEST/BTC",
-            "stoploss": -0.9,
-            "profit_percent": "",
-            "profit_abs": "",
-            "open_date": np.datetime64("2018-10-03T00:20:00.000000000"),
-            "close_date": np.datetime64("2018-10-03T00:25:00.000000000"),
-            "open_index": 4,
-            "close_index": 4,
-            "trade_duration": "",
-            "open_rate": 20,
-            "close_rate": 10,
-            "exit_type": "sell_signal",
-        },
-        {
-            "pair": "TEST/BTC",
-            "stoploss": -0.9,
-            "profit_percent": "",
-            "profit_abs": "",
-            "open_date": np.datetime64("2018-10-03T00:20:00.000000000"),
-            "close_date": np.datetime64("2018-10-03T00:25:00.000000000"),
-            "open_index": 4,
-            "close_index": 4,
-            "trade_duration": "",
-            "open_rate": 20,
-            "close_rate": 10,
-            "exit_type": "sell_signal",
-        },
-        {
-            "pair": "TEST/BTC",
-            "stoploss": -0.9,
-            "profit_percent": "",
-            "profit_abs": "",
-            "open_date": np.datetime64("2018-10-03T00:20:00.000000000"),
-            "close_date": np.datetime64("2018-10-03T00:25:00.000000000"),
-            "open_index": 4,
-            "close_index": 4,
-            "trade_duration": "",
-            "open_rate": 20,
-            "close_rate": 10,
-            "exit_type": "sell_signal",
-        },
-        {
-            "pair": "TEST/BTC",
-            "stoploss": -0.9,
-            "profit_percent": "",
-            "profit_abs": "",
-            "open_date": np.datetime64("2018-10-03T00:30:00.000000000"),
-            "close_date": np.datetime64("2018-10-03T00:40:00.000000000"),
-            "open_index": 6,
-            "close_index": 7,
-            "trade_duration": "",
-            "open_rate": 26,
-            "close_rate": 134,
-            "exit_type": "sell_signal",
-        },
-    ]
-
-    trades_df = DataFrame(trades)
-    trades_df = edge._fill_calculable_fields(trades_df)
-    final = edge._process_expectancy(trades_df)
-
-    assert "TEST/BTC" in final
-    assert final["TEST/BTC"].stoploss == -0.9
-    assert final["TEST/BTC"].nb_trades == len(trades_df) - 1
-    assert round(final["TEST/BTC"].winrate, 10) == 0.0
-
-
-def test_process_expectancy_only_wins(mocker, edge_conf, fee):
-    edge_conf["edge"]["min_trade_number"] = 2
-    freqtrade = get_patched_freqtradebot(mocker, edge_conf)
-
-    freqtrade.exchange.get_fee = fee
-    edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy)
-
-    trades = [
-        {
-            "pair": "TEST/BTC",
-            "stoploss": -0.9,
-            "profit_percent": "",
-            "profit_abs": "",
-            "open_date": np.datetime64("2018-10-03T00:05:00.000000000"),
-            "close_date": np.datetime64("2018-10-03T00:10:00.000000000"),
-            "open_index": 1,
-            "close_index": 1,
-            "trade_duration": "",
-            "open_rate": 15,
-            "close_rate": 17,
-            "exit_type": "sell_signal",
-        },
-        {
-            "pair": "TEST/BTC",
-            "stoploss": -0.9,
-            "profit_percent": "",
-            "profit_abs": "",
-            "open_date": np.datetime64("2018-10-03T00:20:00.000000000"),
-            "close_date": np.datetime64("2018-10-03T00:25:00.000000000"),
-            "open_index": 4,
-            "close_index": 4,
-            "trade_duration": "",
-            "open_rate": 10,
-            "close_rate": 20,
-            "exit_type": "sell_signal",
-        },
-        {
-            "pair": "TEST/BTC",
-            "stoploss": -0.9,
-            "profit_percent": "",
-            "profit_abs": "",
-            "open_date": np.datetime64("2018-10-03T00:30:00.000000000"),
-            "close_date": np.datetime64("2018-10-03T00:40:00.000000000"),
-            "open_index": 6,
-            "close_index": 7,
-            "trade_duration": "",
-            "open_rate": 26,
-            "close_rate": 134,
-            "exit_type": "sell_signal",
-        },
-    ]
-
-    trades_df = DataFrame(trades)
-    trades_df = edge._fill_calculable_fields(trades_df)
-    final = edge._process_expectancy(trades_df)
-
-    assert "TEST/BTC" in final
-    assert final["TEST/BTC"].stoploss == -0.9
-    assert final["TEST/BTC"].nb_trades == len(trades_df)
-    assert round(final["TEST/BTC"].winrate, 10) == 1.0
-    assert round(final["TEST/BTC"].risk_reward_ratio, 10) == float("inf")
-    assert round(final["TEST/BTC"].expectancy, 10) == float("inf")

tests/exchange/test_exchange.py

@@ -35,7 +35,6 @@ from freqtrade.exchange.common import (
     API_FETCH_ORDER_RETRY_COUNT,
     API_RETRY_COUNT,
     calculate_backoff,
-    remove_exchange_credentials,
 )
 from freqtrade.resolvers.exchange_resolver import ExchangeResolver
 from freqtrade.util import dt_now, dt_ts
@@ -167,20 +166,6 @@ def test_init(default_conf, mocker, caplog):
     assert log_has("Instance is running with dry_run enabled", caplog)
 
 
-def test_remove_exchange_credentials(default_conf) -> None:
-    conf = deepcopy(default_conf)
-    remove_exchange_credentials(conf["exchange"], False)
-
-    assert conf["exchange"]["key"] != ""
-    assert conf["exchange"]["secret"] != ""
-
-    remove_exchange_credentials(conf["exchange"], True)
-    assert conf["exchange"]["key"] == ""
-    assert conf["exchange"]["secret"] == ""
-    assert conf["exchange"]["password"] == ""
-    assert conf["exchange"]["uid"] == ""
-
-
 def test_init_ccxt_kwargs(default_conf, mocker, caplog):
     mocker.patch(f"{EXMS}.reload_markets")
     mocker.patch(f"{EXMS}.validate_stakecurrency")
@@ -590,7 +575,8 @@ def test__load_markets(default_conf, mocker, caplog):
 
     expected_return = {"ETH/BTC": "available"}
     api_mock = MagicMock()
-    api_mock.load_markets = get_mock_coro(return_value=expected_return)
+    api_mock.load_markets = get_mock_coro()
+    api_mock.markets = expected_return
     mocker.patch(f"{EXMS}._init_ccxt", MagicMock(return_value=api_mock))
     default_conf["exchange"]["pair_whitelist"] = ["ETH/BTC"]
     ex = Exchange(default_conf)
@@ -606,6 +592,7 @@ def test_reload_markets(default_conf, mocker, caplog, time_machine):
     time_machine.move_to(start_dt, tick=False)
     api_mock = MagicMock()
     api_mock.load_markets = get_mock_coro(return_value=initial_markets)
+    api_mock.markets = initial_markets
     default_conf["exchange"]["markets_refresh_interval"] = 10
     exchange = get_patched_exchange(
         mocker, default_conf, api_mock, exchange="binance", mock_markets=False
@@ -624,6 +611,7 @@ def test_reload_markets(default_conf, mocker, caplog, time_machine):
     api_mock.load_markets = get_mock_coro(return_value=updated_markets)
     # more than 10 minutes have passed, reload is executed
     time_machine.move_to(start_dt + timedelta(minutes=11), tick=False)
+    api_mock.markets = updated_markets
     exchange.reload_markets()
     assert exchange.markets == updated_markets
     assert lam_spy.call_count == 1
@@ -669,34 +657,33 @@ def test_reload_markets_exception(default_conf, mocker, caplog):
 
 
 @pytest.mark.parametrize("stake_currency", ["ETH", "BTC", "USDT"])
-def test_validate_stakecurrency(default_conf, stake_currency, mocker, caplog):
+def test_validate_stakecurrency(default_conf, stake_currency, mocker):
     default_conf["stake_currency"] = stake_currency
     api_mock = MagicMock()
-    type(api_mock).load_markets = get_mock_coro(
-        return_value={
-            "ETH/BTC": {"quote": "BTC"},
-            "LTC/BTC": {"quote": "BTC"},
-            "XRP/ETH": {"quote": "ETH"},
-            "NEO/USDT": {"quote": "USDT"},
-        }
-    )
+    api_mock.load_markets = get_mock_coro()
+    api_mock.markets = {
+        "ETH/BTC": {"quote": "BTC"},
+        "LTC/BTC": {"quote": "BTC"},
+        "XRP/ETH": {"quote": "ETH"},
+        "NEO/USDT": {"quote": "USDT"},
+    }
     mocker.patch(f"{EXMS}._init_ccxt", MagicMock(return_value=api_mock))
     mocker.patch(f"{EXMS}.validate_timeframes")
     mocker.patch(f"{EXMS}.validate_pricing")
     Exchange(default_conf)
 
 
-def test_validate_stakecurrency_error(default_conf, mocker, caplog):
+def test_validate_stakecurrency_error(default_conf, mocker):
     default_conf["stake_currency"] = "XRP"
     api_mock = MagicMock()
-    type(api_mock).load_markets = get_mock_coro(
-        return_value={
-            "ETH/BTC": {"quote": "BTC"},
-            "LTC/BTC": {"quote": "BTC"},
-            "XRP/ETH": {"quote": "ETH"},
-            "NEO/USDT": {"quote": "USDT"},
-        }
-    )
+    api_mock.load_markets = get_mock_coro()
+    api_mock.markets = {
+        "ETH/BTC": {"quote": "BTC"},
+        "LTC/BTC": {"quote": "BTC"},
+        "XRP/ETH": {"quote": "ETH"},
+        "NEO/USDT": {"quote": "USDT"},
+    }
+
     mocker.patch(f"{EXMS}._init_ccxt", MagicMock(return_value=api_mock))
     mocker.patch(f"{EXMS}.validate_timeframes")
     with pytest.raises(
@@ -705,7 +692,7 @@ def test_validate_stakecurrency_error(default_conf, mocker, caplog):
     ):
         Exchange(default_conf)
 
-    type(api_mock).load_markets = get_mock_coro(side_effect=ccxt.NetworkError("No connection."))
+    api_mock.load_markets = get_mock_coro(side_effect=ccxt.NetworkError("No connection."))
     mocker.patch(f"{EXMS}._init_ccxt", MagicMock(return_value=api_mock))
 
     with pytest.raises(

tests/exchange/test_exchange_utils.py

@@ -66,7 +66,7 @@ def test_check_exchange(default_conf, caplog) -> None:
     )
     caplog.clear()
     # Test an available exchange, supported by ccxt
-    default_conf.get("exchange").update({"name": "huobijp"})
+    default_conf.get("exchange").update({"name": "bittrade"})
     assert check_exchange(default_conf)
     assert log_has_re(
         r"Exchange .* is known to the ccxt library, available for the bot, "

tests/exchange/test_hyperliquid.py

@@ -283,7 +283,8 @@ def test_hyperliquid_dry_run_liquidation_price(default_conf, mocker):
     default_conf["trading_mode"] = "futures"
     default_conf["margin_mode"] = "isolated"
     default_conf["stake_currency"] = "USDC"
-    api_mock.load_markets = get_mock_coro(return_value=markets)
+    api_mock.load_markets = get_mock_coro()
+    api_mock.markets = markets
     exchange = get_patched_exchange(
         mocker, default_conf, api_mock, exchange="hyperliquid", mock_markets=False
     )