Merge pull request #10163 from freqtrade/new_release

New release 2024.4

.devcontainer/Dockerfile

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

.devcontainer/devcontainer.json

@@ -1,42 +1,37 @@
 {
     "name": "freqtrade Develop",
-    "build": {
-        "dockerfile": "Dockerfile",
-        "context": ".."
-    },
+    "image": "ghcr.io/freqtrade/freqtrade-devcontainer:latest",
     // Use 'forwardPorts' to make a list of ports inside the container available locally.
     "forwardPorts": [
         8080
     ],
-    "mounts": [
-        "source=freqtrade-bashhistory,target=/home/ftuser/commandhistory,type=volume"
-    ],
     "workspaceMount": "source=${localWorkspaceFolder},target=/workspaces/freqtrade,type=bind,consistency=cached",
     // Uncomment to connect as a non-root user if you've added one. See https://aka.ms/vscode-remote/containers/non-root.
     "remoteUser": "ftuser",
-
     "onCreateCommand": "pip install --user -e .",
     "postCreateCommand": "freqtrade create-userdir --userdir user_data/",
-
     "workspaceFolder": "/workspaces/freqtrade",
     "customizations": {
-        "settings": {
-            "terminal.integrated.shell.linux": "/bin/bash",
-            "editor.insertSpaces": true,
-            "files.trimTrailingWhitespace": true,
-            "[markdown]": {
-                "files.trimTrailingWhitespace": false,
+        "vscode": {
+            "settings": {
+                "terminal.integrated.shell.linux": "/bin/bash",
+                "editor.insertSpaces": true,
+                "files.trimTrailingWhitespace": true,
+                "[markdown]": {
+                    "files.trimTrailingWhitespace": false,
+                },
+                "python.pythonPath": "/usr/local/bin/python",
             },
-            "python.pythonPath": "/usr/local/bin/python",
-        },
-
-        // Add the IDs of extensions you want installed when the container is created.
-        "extensions": [
-            "ms-python.python",
-            "ms-python.vscode-pylance",
-            "davidanson.vscode-markdownlint",
-            "ms-azuretools.vscode-docker",
-            "vscode-icons-team.vscode-icons",
-        ],
+            // Add the IDs of extensions you want installed when the container is created.
+            "extensions": [
+                "ms-python.python",
+                "ms-python.vscode-pylance",
+                "ms-python.isort",
+                "davidanson.vscode-markdownlint",
+                "ms-azuretools.vscode-docker",
+                "vscode-icons-team.vscode-icons",
+                "github.vscode-github-actions",
+            ],
+        }
     }
 }

.github/.devcontainer/Dockerfile

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

.github/.devcontainer/devcontainer.json

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

.github/dependabot.yml

@@ -10,8 +10,20 @@ updates:
   directory: "/"
   schedule:
     interval: weekly
+    time: "03:00"
+    timezone: "Etc/UTC"
   open-pull-requests-limit: 15
   target-branch: develop
+  groups:
+    types:
+      patterns:
+        - "types-*"
+    pytest:
+      patterns:
+        - "pytest*"
+    mkdocs:
+      patterns:
+        - "mkdocs*"
 
 - package-ecosystem: "github-actions"
   directory: "/"

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

@@ -0,0 +1,47 @@
+name: Binance Leverage tiers update
+
+on:
+  schedule:
+    - cron: "0 3 * * 4"
+  # on demand
+  workflow_dispatch:
+
+permissions:
+  contents: read
+
+jobs:
+  auto-update:
+    runs-on: ubuntu-latest
+    environment:
+      name: develop
+    steps:
+    - uses: actions/checkout@v4
+
+    - uses: actions/setup-python@v5
+      with:
+        python-version: "3.11"
+
+    - name: Install ccxt
+      run: pip install ccxt
+
+    - name: Run leverage tier update
+      env:
+        CI_WEB_PROXY: ${{ secrets.CI_WEB_PROXY }}
+        FREQTRADE__EXCHANGE__KEY: ${{ secrets.BINANCE_EXCHANGE_KEY }}
+        FREQTRADE__EXCHANGE__SECRET: ${{ secrets.BINANCE_EXCHANGE_SECRET }}
+      run: python build_helpers/binance_update_lev_tiers.py
+
+
+    - uses: peter-evans/create-pull-request@v6
+      with:
+        token: ${{ secrets.REPO_SCOPED_TOKEN }}
+        add-paths: freqtrade/exchange/binance_leverage_tiers.json
+        labels: |
+          Tech maintenance
+          Dependencies
+        branch: update/binance-leverage-tiers
+        title: Update Binance Leverage Tiers
+        commit-message: "chore: update pre-commit hooks"
+        committer: Freqtrade Bot <noreply@github.com>
+        body: Update binance leverage tiers.
+        delete-branch: true

.github/workflows/ci.yml

@@ -11,7 +11,7 @@ on:
     types: [published]
   pull_request:
   schedule:
-    - cron:  '0 5 * * 4'
+    - cron:  '0 3 * * 4'
 
 concurrency:
   group: "${{ github.workflow }}-${{ github.ref }}-${{ github.event_name }}"
@@ -19,7 +19,7 @@ concurrency:
 permissions:
   repository-projects: read
 jobs:
-  build_linux:
+  build-linux:
 
     runs-on: ${{ matrix.os }}
     strategy:
@@ -60,11 +60,16 @@ jobs:
         export TA_LIBRARY_PATH=${HOME}/dependencies/lib
         export TA_INCLUDE_PATH=${HOME}/dependencies/include
         pip install -r requirements-dev.txt
+        pip install -e ft_client/
         pip install -e .
 
+    - name: Check for version alignment
+      run: |
+        python build_helpers/freqtrade_client_version_align.py
+
     - name: Tests
       run: |
-        pytest --random-order --cov=freqtrade --cov-config=.coveragerc
+        pytest --random-order --cov=freqtrade --cov=freqtrade_client --cov-config=.coveragerc
 
     - name: Coveralls
       if: (runner.os == 'Linux' && matrix.python-version == '3.10' && matrix.os == 'ubuntu-22.04')
@@ -124,8 +129,11 @@ jobs:
     runs-on: ${{ matrix.os }}
     strategy:
       matrix:
-        os: [ "macos-latest", "macos-13" ]
+        os: [ "macos-12", "macos-13", "macos-14" ]
         python-version: ["3.9", "3.10", "3.11", "3.12"]
+        exclude:
+          - os: "macos-14"
+            python-version: "3.9"
 
     steps:
     - uses: actions/checkout@v4
@@ -154,7 +162,7 @@ jobs:
       run: |
         cd build_helpers && ./install_ta-lib.sh ${HOME}/dependencies/; cd ..
 
-    - name: Installation - macOS
+    - name: Installation - macOS (Brew)
       run: |
         # brew update
         # TODO: Should be the brew upgrade
@@ -177,11 +185,15 @@ jobs:
         rm /usr/local/bin/python3.12-config || true
 
         brew install hdf5 c-blosc libomp
+
+    - name: Installation (python)
+      run: |
         python -m pip install --upgrade pip wheel
         export LD_LIBRARY_PATH=${HOME}/dependencies/lib:$LD_LIBRARY_PATH
         export TA_LIBRARY_PATH=${HOME}/dependencies/lib
         export TA_INCLUDE_PATH=${HOME}/dependencies/include
         pip install -r requirements-dev.txt
+        pip install -e ft_client/
         pip install -e .
 
     - name: Tests
@@ -325,7 +337,7 @@ jobs:
     - uses: actions/setup-python@v5
       with:
         python-version: "3.10"
-    - uses: pre-commit/action@v3.0.0
+    - uses: pre-commit/action@v3.0.1
 
   docs-check:
     runs-on: ubuntu-22.04
@@ -356,7 +368,7 @@ jobs:
           webhookUrl: ${{ secrets.DISCORD_WEBHOOK }}
 
 
-  build_linux_online:
+  build-linux-online:
     # Run pytest with "live" checks
     runs-on: ubuntu-22.04
     steps:
@@ -392,29 +404,30 @@ jobs:
         export TA_LIBRARY_PATH=${HOME}/dependencies/lib
         export TA_INCLUDE_PATH=${HOME}/dependencies/include
         pip install -r requirements-dev.txt
+        pip install -e ft_client/
         pip install -e .
 
     - name: Tests incl. ccxt compatibility tests
       env:
         CI_WEB_PROXY: http://152.67.78.211:13128
       run: |
-        pytest --random-order --longrun --durations 20 -n auto --dist loadscope
+        pytest --random-order --longrun --durations 20 -n auto
 
 
-  # Notify only once - when CI completes (and after deploy) in case it's successfull
+  # Notify only once - when CI completes (and after deploy) in case it's successful
   notify-complete:
     needs: [
-      build_linux,
+      build-linux,
       build-macos,
       build-windows,
       docs-check,
       mypy-version-check,
       pre-commit,
-      build_linux_online
+      build-linux-online
     ]
     runs-on: ubuntu-22.04
     # Discord notification can't handle schedule events
-    if: (github.event_name != 'schedule')
+    if: github.event_name != 'schedule' && github.repository == 'freqtrade/freqtrade'
     permissions:
       repository-projects: read
     steps:
@@ -437,7 +450,7 @@ jobs:
 
   build:
     name: "Build"
-    needs: [ build_linux, build-macos, build-windows, docs-check, mypy-version-check, pre-commit ]
+    needs: [ build-linux, build-macos, build-windows, docs-check, mypy-version-check, pre-commit ]
     runs-on: ubuntu-22.04
 
     steps:
@@ -461,6 +474,19 @@ jobs:
           dist
         retention-days: 10
 
+    - name: Build Client distribution
+      run: |
+        pip install -U build
+        python -m build --sdist --wheel ft_client
+
+    - name: Upload artifacts 📦
+      uses: actions/upload-artifact@v4
+      with:
+        name: freqtrade-client-build
+        path: |
+          ft_client/dist
+        retention-days: 10
+
   deploy-pypi:
     name: "Deploy to PyPI"
     needs: [ build ]
@@ -478,20 +504,22 @@ jobs:
     - name: Download artifact  📦
       uses: actions/download-artifact@v4
       with:
-        name: freqtrade-build
+        pattern: freqtrade*-build
         path: dist
+        merge-multiple: true
+
 
     - name: Publish to PyPI (Test)
-      uses: pypa/gh-action-pypi-publish@v1.8.11
+      uses: pypa/gh-action-pypi-publish@v1.8.14
       with:
         repository-url: https://test.pypi.org/legacy/
 
     - name: Publish to PyPI
-      uses: pypa/gh-action-pypi-publish@v1.8.11
+      uses: pypa/gh-action-pypi-publish@v1.8.14
 
 
   deploy-docker:
-    needs: [ build_linux, build-macos, build-windows, docs-check, mypy-version-check, pre-commit ]
+    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'

.github/workflows/devcontainer-build.yml

@@ -0,0 +1,43 @@
+name: Devcontainer Pre-Build
+
+on:
+  workflow_dispatch:
+  # push:
+  #   branches:
+  #     - "master"
+  #   tags:
+  #     - "v*.*.*"
+  #   pull_requests:
+  #     branches:
+  #       - "master"
+
+concurrency:
+  group: "${{ github.workflow }}"
+  cancel-in-progress: true
+
+permissions:
+  packages: write
+
+jobs:
+  build-and-push:
+    runs-on: ubuntu-latest
+    steps:
+    -
+      name: Checkout
+      id: checkout
+      uses: actions/checkout@v4
+    -
+        name: Login to GitHub Container Registry
+        uses: docker/login-action@v3
+        with:
+          registry: ghcr.io
+          username: ${{ github.actor }}
+          password: ${{ secrets.GITHUB_TOKEN }}
+    -
+        name: Pre-build dev container image
+        uses: devcontainers/ci@v0.3
+        with:
+          subFolder: .github
+          imageName: ghcr.io/${{ github.repository }}-devcontainer
+          cacheFrom: ghcr.io/${{ github.repository }}-devcontainer
+          push: always

.github/workflows/docker-update-readme.yml

@@ -9,9 +9,10 @@ jobs:
     runs-on: ubuntu-latest
     steps:
     - uses: actions/checkout@v4
+
     - name: Docker Hub Description
       uses: peter-evans/dockerhub-description@v4
-      env:
-        DOCKERHUB_USERNAME: ${{ secrets.DOCKER_USERNAME }}
-        DOCKERHUB_PASSWORD: ${{ secrets.DOCKER_PASSWORD }}
-        DOCKERHUB_REPOSITORY: freqtradeorg/freqtrade
+      with:
+        username: ${{ secrets.DOCKER_USERNAME }}
+        password: ${{ secrets.DOCKER_PASSWORD }}
+        repository: freqtradeorg/freqtrade

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

@@ -1,7 +1,6 @@
 name: Pre-commit auto-update
 
 on:
-  # every day at midnight
   schedule:
     - cron: "0 3 * * 2"
   # on demand
@@ -14,31 +13,32 @@ jobs:
   auto-update:
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/checkout@v4
+    - uses: actions/checkout@v4
 
-      - uses: actions/setup-python@v5
-        with:
-          python-version: "3.11"
+    - uses: actions/setup-python@v5
+      with:
+        python-version: "3.11"
 
 
-      - name: Install pre-commit
-        run: pip install pre-commit
+    - name: Install pre-commit
+      run: pip install pre-commit
 
-      - name: Run auto-update
-        run: pre-commit autoupdate
+    - name: Run auto-update
+      run: pre-commit autoupdate
 
-      - name: Run pre-commit
-        run: pre-commit run --all-files
+    - name: Run pre-commit
+      run: pre-commit run --all-files
 
-      - uses: peter-evans/create-pull-request@v5
-        with:
-          token: ${{ secrets.REPO_SCOPED_TOKEN }}
-          add-paths: .pre-commit-config.yaml
-          labels: |
-            Tech maintenance
-          branch: update/pre-commit-hooks
-          title: Update pre-commit hooks
-          commit-message: "chore: update pre-commit hooks"
-          committer: Freqtrade Bot <noreply@github.com>
-          body: Update versions of pre-commit hooks to latest version.
-          delete-branch: true
+    - uses: peter-evans/create-pull-request@v6
+      with:
+        token: ${{ secrets.REPO_SCOPED_TOKEN }}
+        add-paths: .pre-commit-config.yaml
+        labels: |
+          Tech maintenance
+          Dependencies
+        branch: update/pre-commit-hooks
+        title: Update pre-commit hooks
+        commit-message: "chore: update pre-commit hooks"
+        committer: Freqtrade Bot <noreply@github.com>
+        body: Update versions of pre-commit hooks to latest version.
+        delete-branch: true

.pre-commit-config.yaml

@@ -9,17 +9,17 @@ repos:
         # stages: [push]
 
   - repo: https://github.com/pre-commit/mirrors-mypy
-    rev: "v1.8.0"
+    rev: "v1.10.0"
     hooks:
       - id: mypy
         exclude: build_helpers
         additional_dependencies:
           - types-cachetools==5.3.0.7
           - types-filelock==3.2.7
-          - types-requests==2.31.0.20240125
+          - types-requests==2.31.0.20240406
           - types-tabulate==0.9.0.20240106
-          - types-python-dateutil==2.8.19.20240106
-          - SQLAlchemy==2.0.25
+          - types-python-dateutil==2.9.0.20240316
+          - SQLAlchemy==2.0.29
         # stages: [push]
 
   - repo: https://github.com/pycqa/isort
@@ -31,12 +31,12 @@ repos:
 
   - repo: https://github.com/charliermarsh/ruff-pre-commit
     # Ruff version.
-    rev: 'v0.1.14'
+    rev: 'v0.4.2'
     hooks:
       - id: ruff
 
   - repo: https://github.com/pre-commit/pre-commit-hooks
-    rev: v4.5.0
+    rev: v4.6.0
     hooks:
       - id: end-of-file-fixer
         exclude: |
@@ -54,3 +54,10 @@ repos:
           (?x)^(
                 .*\.md
             )$
+
+  - repo: https://github.com/codespell-project/codespell
+    rev: v2.2.6
+    hooks:
+    - id: codespell
+      additional_dependencies:
+        - tomli

CONTRIBUTING.md

@@ -48,7 +48,7 @@ pytest tests/test_<file_name>.py::test_<method_name>
 #### Run Ruff
 
 ```bash
-ruff .
+ruff check .
 ```
 
 We receive a lot of code that fails the `ruff` checks.

Dockerfile

@@ -1,4 +1,4 @@
-FROM python:3.11.7-slim-bookworm as base
+FROM python:3.12.3-slim-bookworm as base
 
 # Setup env
 ENV LANG C.UTF-8

build_helpers/binance_update_lev_tiers.py

@@ -0,0 +1,26 @@
+#!/usr/bin/env python3
+import json
+import os
+from pathlib import Path
+
+import ccxt
+
+
+key = os.environ.get('FREQTRADE__EXCHANGE__KEY')
+secret = os.environ.get('FREQTRADE__EXCHANGE__SECRET')
+
+proxy = os.environ.get('CI_WEB_PROXY')
+
+exchange = ccxt.binance({
+    'apiKey': key,
+    'secret': secret,
+    'httpsProxy': proxy,
+    'options': {'defaultType': 'swap'}
+    })
+_ = exchange.load_markets()
+
+lev_tiers = exchange.fetch_leverage_tiers()
+
+# Assumes this is running in the root of the repository.
+file = Path('freqtrade/exchange/binance_leverage_tiers.json')
+json.dump(dict(sorted(lev_tiers.items())), file.open('w'), indent=2)

build_helpers/freqtrade_client_version_align.py

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

build_helpers/pre_commit_update.py

@@ -1,4 +1,4 @@
-# File used in CI to ensure pre-commit dependencies are kept uptodate.
+# File used in CI to ensure pre-commit dependencies are kept up-to-date.
 
 import sys
 from pathlib import Path
@@ -21,7 +21,7 @@ type_reqs = [r.strip('\n') for r in requirements if r.startswith(
     'types-') or r.startswith('SQLAlchemy')]
 
 with pre_commit_file.open('r') as file:
-    f = yaml.load(file, Loader=yaml.FullLoader)
+    f = yaml.load(file, Loader=yaml.SafeLoader)
 
 
 mypy_repo = [repo for repo in f['repos'] if repo['repo']

docker/Dockerfile.armhf

@@ -1,4 +1,4 @@
-FROM python:3.11.7-slim-bookworm as base
+FROM python:3.11.8-slim-bookworm as base
 
 # Setup env
 ENV LANG C.UTF-8

docs/advanced-backtesting.md

@@ -36,7 +36,7 @@ freqtrade backtesting-analysis -c <config.json> --analysis-groups 0 1 2 3 4 5
 ```
 
 This command will read from the last backtesting results. The `--analysis-groups` option is
-used to specify the various tabular outputs showing the profit fo each group or trade,
+used to specify the various tabular outputs showing the profit of each group or trade,
 ranging from the simplest (0) to the most detailed per pair, per buy and per sell tag (4):
 
 * 0: overall winrate and profit summary by enter_tag
@@ -109,12 +109,12 @@ automatically accessible by including them on the indicator-list, and these incl
 - **open_date     :** trade open datetime
 - **close_date    :** trade close datetime
 - **min_rate      :** minimum price seen throughout the position
-- **max_rate      :** maxiumum price seen throughout the position
+- **max_rate      :** maximum price seen throughout the position
 - **open          :** signal candle open price
 - **close         :** signal candle close price
 - **high          :** signal candle high price
 - **low           :** signal candle low price
-- **volume        :** signal candle volumne
+- **volume        :** signal candle volume
 - **profit_ratio  :** trade profit ratio
 - **profit_abs    :** absolute profit return of the trade 
 

docs/backtesting.md

@@ -252,34 +252,34 @@ The most important in the backtesting is to understand the result.
 A backtesting result will look like that:
 
 ```
-========================================================= BACKTESTING REPORT =========================================================
-| Pair     | Entries |   Avg Profit % |   Cum Profit % |   Tot Profit BTC |   Tot Profit % | Avg Duration |  Wins Draws Loss   Win%  |
-|:---------|--------:|---------------:|---------------:|-----------------:|---------------:|:-------------|-------------------------:|
-| ADA/BTC  |      35 |          -0.11 |          -3.88 |      -0.00019428 |          -1.94 | 4:35:00      |    14     0    21   40.0 |
-| ARK/BTC  |      11 |          -0.41 |          -4.52 |      -0.00022647 |          -2.26 | 2:03:00      |     3     0     8   27.3 |
-| BTS/BTC  |      32 |           0.31 |           9.78 |       0.00048938 |           4.89 | 5:05:00      |    18     0    14   56.2 |
-| DASH/BTC |      13 |          -0.08 |          -1.07 |      -0.00005343 |          -0.53 | 4:39:00      |     6     0     7   46.2 |
-| ENG/BTC  |      18 |           1.36 |          24.54 |       0.00122807 |          12.27 | 2:50:00      |     8     0    10   44.4 |
-| EOS/BTC  |      36 |           0.08 |           3.06 |       0.00015304 |           1.53 | 3:34:00      |    16     0    20   44.4 |
-| ETC/BTC  |      26 |           0.37 |           9.51 |       0.00047576 |           4.75 | 6:14:00      |    11     0    15   42.3 |
-| ETH/BTC  |      33 |           0.30 |           9.96 |       0.00049856 |           4.98 | 7:31:00      |    16     0    17   48.5 |
-| IOTA/BTC |      32 |           0.03 |           1.09 |       0.00005444 |           0.54 | 3:12:00      |    14     0    18   43.8 |
-| LSK/BTC  |      15 |           1.75 |          26.26 |       0.00131413 |          13.13 | 2:58:00      |     6     0     9   40.0 |
-| LTC/BTC  |      32 |          -0.04 |          -1.38 |      -0.00006886 |          -0.69 | 4:49:00      |    11     0    21   34.4 |
-| NANO/BTC |      17 |           1.26 |          21.39 |       0.00107058 |          10.70 | 1:55:00      |    10     0     7   58.5 |
-| NEO/BTC  |      23 |           0.82 |          18.97 |       0.00094936 |           9.48 | 2:59:00      |    10     0    13   43.5 |
-| REQ/BTC  |       9 |           1.17 |          10.54 |       0.00052734 |           5.27 | 3:47:00      |     4     0     5   44.4 |
-| XLM/BTC  |      16 |           1.22 |          19.54 |       0.00097800 |           9.77 | 3:15:00      |     7     0     9   43.8 |
-| XMR/BTC  |      23 |          -0.18 |          -4.13 |      -0.00020696 |          -2.07 | 5:30:00      |    12     0    11   52.2 |
-| XRP/BTC  |      35 |           0.66 |          22.96 |       0.00114897 |          11.48 | 3:49:00      |    12     0    23   34.3 |
-| ZEC/BTC  |      22 |          -0.46 |         -10.18 |      -0.00050971 |          -5.09 | 2:22:00      |     7     0    15   31.8 |
-| TOTAL    |     429 |           0.36 |         152.41 |       0.00762792 |          76.20 | 4:12:00      |   186     0   243   43.4 |
-====================================================== LEFT OPEN TRADES REPORT ======================================================
-| Pair     |  Entries |   Avg Profit % |   Cum Profit % |   Tot Profit BTC |   Tot Profit % | Avg Duration   |  Win Draw Loss Win% |
-|:---------|---------:|---------------:|---------------:|-----------------:|---------------:|:---------------|--------------------:|
-| ADA/BTC  |        1 |           0.89 |           0.89 |       0.00004434 |           0.44 | 6:00:00        |    1    0    0  100 |
-| LTC/BTC  |        1 |           0.68 |           0.68 |       0.00003421 |           0.34 | 2:00:00        |    1    0    0  100 |
-| TOTAL    |        2 |           0.78 |           1.57 |       0.00007855 |           0.78 | 4:00:00        |    2    0    0  100 |
+================================================ BACKTESTING REPORT =================================================
+| Pair     | Entries |   Avg Profit % |   Tot Profit BTC |   Tot Profit % | Avg Duration |  Wins Draws Loss   Win%  |
+|:---------|--------:|---------------:|-----------------:|---------------:|:-------------|-------------------------:|
+| ADA/BTC  |      35 |          -0.11 |      -0.00019428 |          -1.94 | 4:35:00      |    14     0    21   40.0 |
+| ARK/BTC  |      11 |          -0.41 |      -0.00022647 |          -2.26 | 2:03:00      |     3     0     8   27.3 |
+| BTS/BTC  |      32 |           0.31 |       0.00048938 |           4.89 | 5:05:00      |    18     0    14   56.2 |
+| DASH/BTC |      13 |          -0.08 |      -0.00005343 |          -0.53 | 4:39:00      |     6     0     7   46.2 |
+| ENG/BTC  |      18 |           1.36 |       0.00122807 |          12.27 | 2:50:00      |     8     0    10   44.4 |
+| EOS/BTC  |      36 |           0.08 |       0.00015304 |           1.53 | 3:34:00      |    16     0    20   44.4 |
+| ETC/BTC  |      26 |           0.37 |       0.00047576 |           4.75 | 6:14:00      |    11     0    15   42.3 |
+| ETH/BTC  |      33 |           0.30 |       0.00049856 |           4.98 | 7:31:00      |    16     0    17   48.5 |
+| IOTA/BTC |      32 |           0.03 |       0.00005444 |           0.54 | 3:12:00      |    14     0    18   43.8 |
+| LSK/BTC  |      15 |           1.75 |       0.00131413 |          13.13 | 2:58:00      |     6     0     9   40.0 |
+| LTC/BTC  |      32 |          -0.04 |      -0.00006886 |          -0.69 | 4:49:00      |    11     0    21   34.4 |
+| NANO/BTC |      17 |           1.26 |       0.00107058 |          10.70 | 1:55:00      |    10     0     7   58.5 |
+| NEO/BTC  |      23 |           0.82 |       0.00094936 |           9.48 | 2:59:00      |    10     0    13   43.5 |
+| REQ/BTC  |       9 |           1.17 |       0.00052734 |           5.27 | 3:47:00      |     4     0     5   44.4 |
+| XLM/BTC  |      16 |           1.22 |       0.00097800 |           9.77 | 3:15:00      |     7     0     9   43.8 |
+| XMR/BTC  |      23 |          -0.18 |      -0.00020696 |          -2.07 | 5:30:00      |    12     0    11   52.2 |
+| XRP/BTC  |      35 |           0.66 |       0.00114897 |          11.48 | 3:49:00      |    12     0    23   34.3 |
+| ZEC/BTC  |      22 |          -0.46 |      -0.00050971 |          -5.09 | 2:22:00      |     7     0    15   31.8 |
+| TOTAL    |     429 |           0.36 |       0.00762792 |          76.20 | 4:12:00      |   186     0   243   43.4 |
+============================================= LEFT OPEN TRADES REPORT =============================================
+| Pair     |  Entries |   Avg Profit % |   Tot Profit BTC |   Tot Profit % | Avg Duration   |  Win Draw Loss Win% |
+|:---------|---------:|---------------:|-----------------:|---------------:|:---------------|--------------------:|
+| ADA/BTC  |        1 |           0.89 |       0.00004434 |           0.44 | 6:00:00        |    1    0    0  100 |
+| LTC/BTC  |        1 |           0.68 |       0.00003421 |           0.34 | 2:00:00        |    1    0    0  100 |
+| TOTAL    |        2 |           0.78 |       0.00007855 |           0.78 | 4:00:00        |    2    0    0  100 |
 ==================== EXIT REASON STATS ====================
 | Exit Reason        |   Exits |  Wins |  Draws |  Losses |
 |:-------------------|--------:|------:|-------:|--------:|
@@ -358,7 +358,7 @@ here:
 The bot has made `429` trades for an average duration of `4:12:00`, with a performance of `76.20%` (profit), that means it has
 earned a total of `0.00762792 BTC` starting with a capital of 0.01 BTC.
 
-The column `Avg Profit %` shows the average profit for all trades made while the column `Cum Profit %` sums up all the profits/losses.
+The column `Avg Profit %` shows the average profit for all trades made.
 The column `Tot Profit %` shows instead the total profit % in relation to the starting balance.
 In the above results, we have a starting balance of 0.01 BTC and an absolute profit of 0.00762792 BTC - so the `Tot Profit %` will be `(0.00762792 / 0.01) * 100 ~= 76.2%`.
 
@@ -464,7 +464,7 @@ It contains some useful key metrics about performance of your strategy on backte
 - `Profit factor`: profit / loss.
 - `Avg. stake amount`: Average stake amount, either `stake_amount` or the average when using dynamic stake amount.
 - `Total trade volume`: Volume generated on the exchange to reach the above profit.
-- `Best Pair` / `Worst Pair`: Best and worst performing pair, and it's corresponding `Cum Profit %`.
+- `Best Pair` / `Worst Pair`: Best and worst performing pair, and it's corresponding `Tot Profit %`.
 - `Best Trade` / `Worst Trade`: Biggest single winning trade and biggest single losing trade.
 - `Best day` / `Worst day`: Best and worst day based on daily profit.
 - `Days win/draw/lose`: Winning / Losing days (draws are usually days without closed trade).
@@ -522,8 +522,8 @@ To save time, by default backtest will reuse a cached result from within the las
 
 ### Further backtest-result analysis
 
-To further analyze your backtest results, you can [export the trades](#exporting-trades-to-file).
-You can then load the trades to perform further analysis as shown in the [data analysis](data-analysis.md#backtesting) backtesting section.
+To further analyze your backtest results, freqtrade will export the trades to file by default.
+You can then load the trades to perform further analysis as shown in the [data analysis](strategy_analysis_example.md#load-backtest-results-to-pandas-dataframe) backtesting section.
 
 ## Assumptions made by backtesting
 
@@ -531,12 +531,13 @@ Since backtesting lacks some detailed information about what happens within a ca
 
 - Exchange [trading limits](#trading-limits-in-backtesting) are respected
 - Entries happen at open-price
-- All orders are filled at the requested price (no slippage, no unfilled orders)
+- All orders are filled at the requested price (no slippage) as long as the price is within the candle's high/low range
 - Exit-signal exits happen at open-price of the consecutive candle
+- Exits don't free their trade slot for a new trade until the next candle
 - Exit-signal is favored over Stoploss, because exit-signals are assumed to trigger on candle's open
 - ROI
-  - exits are compared to high - but the ROI value is used (e.g. ROI = 2%, high=5% - so the exit will be at 2%)
-  - exits are never "below the candle", so a ROI of 2% may result in a exit at 2.4% if low was at 2.4% profit
+  - Exits are compared to high - but the ROI value is used (e.g. ROI = 2%, high=5% - so the exit will be at 2%)
+  - Exits are never "below the candle", so a ROI of 2% may result in a exit at 2.4% if low was at 2.4% profit
   - ROI entries which came into effect on the triggering candle (e.g. `120: 0.02` for 1h candles, from `60: 0.05`) will use the candle's open as exit rate
   - Force-exits caused by `<N>=-1` ROI entries use low as exit value, unless N falls on the candle open (e.g. `120: -1` for 1h candles)
 - Stoploss exits happen exactly at stoploss price, even if low was lower, but the loss will be `2 * fees` higher than the stoploss price
@@ -587,7 +588,7 @@ These precision values are based on current exchange limits (as described in the
 
 ## Improved backtest accuracy
 
-One big limitation of backtesting is it's inability to know how prices moved intra-candle (was high before close, or viceversa?).
+One big limitation of backtesting is it's inability to know how prices moved intra-candle (was high before close, or vice-versa?).
 So assuming you run backtesting with a 1h timeframe, there will be 4 prices for that candle (Open, High, Low, Close).
 
 While backtesting does take some assumptions (read above) about this - this can never be perfect, and will always be biased in one way or the other.
@@ -629,11 +630,11 @@ There will be an additional table comparing win/losses of the different strategi
 Detailed output for all strategies one after the other will be available, so make sure to scroll up to see the details per strategy.
 
 ```
-=========================================================== STRATEGY SUMMARY ===========================================================================
-| Strategy    |  Entries |   Avg Profit % |   Cum Profit % |   Tot Profit BTC |   Tot Profit % | Avg Duration   |  Wins |  Draws | Losses | Drawdown % |
-|:------------|---------:|---------------:|---------------:|-----------------:|---------------:|:---------------|------:|-------:|-------:|-----------:|
-| Strategy1   |      429 |           0.36 |         152.41 |       0.00762792 |          76.20 | 4:12:00        |   186 |      0 |    243 |       45.2 |
-| Strategy2   |     1487 |          -0.13 |        -197.58 |      -0.00988917 |         -98.79 | 4:43:00        |   662 |      0 |    825 |     241.68 |
+================================================== STRATEGY SUMMARY ===================================================================
+| Strategy    |  Entries |   Avg Profit % |   Tot Profit BTC |   Tot Profit % | Avg Duration   |  Wins |  Draws | Losses | Drawdown % |
+|:------------|---------:|---------------:|-----------------:|---------------:|:---------------|------:|-------:|-------:|-----------:|
+| Strategy1   |      429 |           0.36 |       0.00762792 |          76.20 | 4:12:00        |   186 |      0 |    243 |       45.2 |
+| Strategy2   |     1487 |          -0.13 |      -0.00988917 |         -98.79 | 4:43:00        |   662 |      0 |    825 |     241.68 |
 ```
 
 ## Next step

docs/bot-basics.md

@@ -33,7 +33,6 @@ For spot pairs, naming will be `base/quote` (e.g. `ETH/USDT`).
 
 For futures pairs, naming will be `base/quote:settle` (e.g. `ETH/USDT:USDT`).
 
-
 ## Bot execution logic
 
 Starting freqtrade in dry-run or live mode (using `freqtrade trade`) will start the bot and start the bot iteration loop.
@@ -50,10 +49,12 @@ By default, the bot loop runs every few seconds (`internals.process_throttle_sec
   * Call `populate_indicators()`
   * Call `populate_entry_trend()`
   * Call `populate_exit_trend()`
-* Check timeouts for open orders.
-  * Calls `check_entry_timeout()` strategy callback for open entry orders.
-  * Calls `check_exit_timeout()` strategy callback for open exit orders.
-  * Calls `adjust_entry_price()` strategy callback for open entry orders.
+* Update trades open order state from exchange.
+  * Call `order_filled()` strategy callback for filled orders.
+  * Check timeouts for open orders.
+    * Calls `check_entry_timeout()` strategy callback for open entry orders.
+    * Calls `check_exit_timeout()` strategy callback for open exit orders.
+    * Calls `adjust_entry_price()` strategy callback for open entry orders.
 * Verifies existing positions and eventually places exit orders.
   * Considers stoploss, ROI and exit-signal, `custom_exit()` and `custom_stoploss()`.
   * Determine exit-price based on `exit_pricing` configuration setting or by using the `custom_exit_price()` callback.
@@ -86,8 +87,10 @@ This loop will be repeated again and again until the bot is stopped.
   * In Margin and Futures mode, `leverage()` strategy callback is called to determine the desired leverage.
   * Determine stake size by calling the `custom_stake_amount()` callback.
   * Check position adjustments for open trades if enabled and call `adjust_trade_position()` to determine if an additional order is requested.
+  * Call `order_filled()` strategy callback for filled entry orders.
   * Call `custom_stoploss()` and `custom_exit()` to find custom exit points.
   * For exits based on exit-signal, custom-exit and partial exits: Call `custom_exit_price()` to determine exit price (Prices are moved to be within the closing candle).
+  * Call `order_filled()` strategy callback for filled exit orders.
 * Generate backtest report output
 
 !!! Note

docs/configuration.md

@@ -14,7 +14,7 @@ You can specify a different configuration file used by the bot with the `-c/--co
 If you used the [Quick start](docker_quickstart.md#docker-quick-start) method for installing
 the bot, the installation script should have already created the default configuration file (`config.json`) for you.
 
-If the default configuration file is not created we recommend to use `freqtrade new-config --config config.json` to generate a basic configuration file.
+If the default configuration file is not created we recommend to use `freqtrade new-config --config user_data/config.json` to generate a basic configuration file.
 
 The Freqtrade configuration file is to be written in JSON format.
 
@@ -49,6 +49,13 @@ FREQTRADE__EXCHANGE__SECRET=<yourExchangeSecret>
 !!! Note
     Environment variables detected are logged at startup - so if you can't find why a value is not what you think it should be based on the configuration, make sure it's not loaded from an environment variable.
 
+!!! Tip "Validate combined result"
+    You can use the [show-config subcommand](utils.md#show-config) to see the final, combined configuration.
+
+??? Warning "Loading sequence"
+    Environment variables are loaded after the initial configuration. As such, you cannot provide the path to the configuration through environment variables. Please use `--config path/to/config.json` for that.
+    This also applies to user_dir to some degree. while the user directory can be set through environment variables - the configuration will **not** be loaded from that location.
+
 ### Multiple configuration files
 
 Multiple configuration files can be specified and used by the bot or the bot can read its configuration parameters from the process standard input stream.
@@ -56,6 +63,9 @@ Multiple configuration files can be specified and used by the bot or the bot can
 You can specify additional configuration files in `add_config_files`. Files specified in this parameter will be loaded and merged with the initial config file. The files are resolved relative to the initial configuration file.
 This is similar to using multiple `--config` parameters, but simpler in usage as you don't have to specify all files for all commands.
 
+!!! Tip "Validate combined result"
+    You can use the [show-config subcommand](utils.md#show-config) to see the final, combined configuration.
+
 !!! Tip "Use multiple configuration files to keep secrets secret"
     You can use a 2nd configuration file containing your secrets. That way you can share your "primary" configuration file, while still keeping your API keys for yourself.
     The 2nd file should only specify what you intend to override.
@@ -187,7 +197,7 @@ Mandatory parameters are marked as **Required**, which means that they are requi
 | `position_adjustment_enable` | Enables the strategy to use position adjustments (additional buys or sells). [More information here](strategy-callbacks.md#adjust-trade-position). <br> [Strategy Override](#parameters-in-the-strategy). <br>*Defaults to `false`.*<br> **Datatype:** Boolean
 | `max_entry_position_adjustment` | Maximum additional order(s) for each open trade on top of the first entry Order. Set it to `-1` for unlimited additional orders. [More information here](strategy-callbacks.md#adjust-trade-position). <br> [Strategy Override](#parameters-in-the-strategy). <br>*Defaults to `-1`.*<br> **Datatype:** Positive Integer or -1
 | | **Exchange**
-| `exchange.name` | **Required.** Name of the exchange class to use. [List below](#user-content-what-values-for-exchangename). <br> **Datatype:** String
+| `exchange.name` | **Required.** Name of the exchange class to use. <br> **Datatype:** String
 | `exchange.key` | API key to use for the exchange. Only required when you are in production mode.<br>**Keep it in secret, do not disclose publicly.** <br> **Datatype:** String
 | `exchange.secret` | API secret to use for the exchange. Only required when you are in production mode.<br>**Keep it in secret, do not disclose publicly.** <br> **Datatype:** String
 | `exchange.password` | API password to use for the exchange. Only required when you are in production mode and for exchanges that use password for API requests.<br>**Keep it in secret, do not disclose publicly.** <br> **Datatype:** String
@@ -242,7 +252,7 @@ Mandatory parameters are marked as **Required**, which means that they are requi
 | `disable_dataframe_checks` | Disable checking the OHLCV dataframe returned from the strategy methods for correctness. Only use when intentionally changing the dataframe and understand what you are doing. [Strategy Override](#parameters-in-the-strategy).<br> *Defaults to `False`*. <br> **Datatype:** Boolean
 | `internals.process_throttle_secs` | Set the process throttle, or minimum loop duration for one bot iteration loop. Value in second. <br>*Defaults to `5` seconds.* <br> **Datatype:** Positive Integer
 | `internals.heartbeat_interval` | Print heartbeat message every N seconds. Set to 0 to disable heartbeat messages. <br>*Defaults to `60` seconds.* <br> **Datatype:** Positive Integer or 0
-| `internals.sd_notify` | Enables use of the sd_notify protocol to tell systemd service manager about changes in the bot state and issue keep-alive pings. See [here](installation.md#7-optional-configure-freqtrade-as-a-systemd-service) for more details. <br> **Datatype:** Boolean
+| `internals.sd_notify` | Enables use of the sd_notify protocol to tell systemd service manager about changes in the bot state and issue keep-alive pings. See [here](advanced-setup.md#configure-the-bot-running-as-a-systemd-service) for more details. <br> **Datatype:** Boolean
 | `strategy` | **Required** Defines Strategy class to use. Recommended to be set via `--strategy NAME`. <br> **Datatype:** ClassName
 | `strategy_path` | Adds an additional strategy lookup path (must be a directory). <br> **Datatype:** String
 | `recursive_strategy_search` | Set to `true` to recursively search sub-directories inside `user_data/strategies` for a strategy. <br> **Datatype:** Boolean
@@ -326,6 +336,8 @@ You'd set `available_capital=5000` - granting each bot an initial capital of 500
 The bot will then split this starting balance equally into `max_open_trades` buckets.
 Profitable trades will result in increased stake-sizes for this bot - without affecting the stake-sizes of the other bot.
 
+Adjusting `available_capital` requires reloading the configuration to take effect. Adjusting the `available_capital` adds the difference between the previous `available_capital` and the new `available_capital`. Decreasing the available capital when trades are open doesn't exit the trades. The difference is returned to the wallet when the trades conclude. The outcome of this differs depending on the price movement between the adjustment and exiting the trades.
+
 !!! Warning "Incompatible with `tradable_balance_ratio`"
     Setting this option will replace any configuration of `tradable_balance_ratio`.
 
@@ -358,7 +370,7 @@ This setting works in combination with `max_open_trades`. The maximum capital en
 For example, the bot will at most use (0.05 BTC x 3) = 0.15 BTC, assuming a configuration of `max_open_trades=3` and `stake_amount=0.05`.
 
 !!! Note
-    This setting respects the [available balance configuration](#available-balance).
+    This setting respects the [available balance configuration](#tradable-balance).
 
 #### Dynamic stake amount
 
@@ -503,13 +515,13 @@ Configuration:
     Please carefully read the section [Market order pricing](#market-order-pricing) section when using market orders.
 
 !!! Note "Stoploss on exchange"
-    `stoploss_on_exchange_interval` is not mandatory. Do not change its value if you are
+    `order_types.stoploss_on_exchange_interval` is not mandatory. Do not change its value if you are
     unsure of what you are doing. For more information about how stoploss works please
     refer to [the stoploss documentation](stoploss.md).
 
-    If `stoploss_on_exchange` is enabled and the stoploss is cancelled manually on the exchange, then the bot will create a new stoploss order.
+    If `order_types.stoploss_on_exchange` is enabled and the stoploss is cancelled manually on the exchange, then the bot will create a new stoploss order.
 
-!!! Warning "Warning: stoploss_on_exchange failures"
+!!! Warning "Warning: order_types.stoploss_on_exchange failures"
     If stoploss on exchange creation fails for some reason, then an "emergency exit" is initiated. By default, this will exit the trade using a market order. The order-type for the emergency-exit can be changed by setting the `emergency_exit` value in the `order_types` dictionary - however, this is not advised.
 
 ### Understand order_time_in_force
@@ -535,7 +547,7 @@ is automatically cancelled by the exchange.
 **PO (Post only):**
 
 Post only order. The order is either placed as a maker order, or it is canceled.
-This means the order must be placed on orderbook for at at least time in an unfilled state.
+This means the order must be placed on orderbook for at least time in an unfilled state.
 
 #### time_in_force config
 

docs/developer.md

@@ -83,7 +83,7 @@ Details will obviously vary between setups - but this should work to get you sta
 ``` json
 {
     "name": "freqtrade trade",
-    "type": "python",
+    "type": "debugpy",
     "request": "launch",
     "module": "freqtrade",
     "console": "integratedTerminal",
@@ -129,6 +129,8 @@ Below is an outline of exception inheritance hierarchy:
 + FreqtradeException
 |
 +---+ OperationalException
+|   |
+|   +---+ ConfigurationError
 |
 +---+ DependencyException
 |   |
@@ -259,7 +261,7 @@ For that reason, they must implement the following methods:
 
 The `until` portion should be calculated using the provided `calculate_lock_end()` method.
 
-All Protections should use `"stop_duration"` / `"stop_duration_candles"` to define how long a a pair (or all pairs) should be locked.
+All Protections should use `"stop_duration"` / `"stop_duration_candles"` to define how long a pair (or all pairs) should be locked.
 The content of this is made available as `self._stop_duration` to the each Protection.
 
 If your protection requires a look-back period, please use `"lookback_period"` / `"lockback_period_candles"` to keep all protections aligned.
@@ -303,7 +305,7 @@ The `IProtection` parent class provides a helper method for this in `calculate_l
 
 Most exchanges supported by CCXT should work out of the box.
 
-To quickly test the public endpoints of an exchange, add a configuration for your exchange to `test_ccxt_compat.py` and run these tests with `pytest --longrun tests/exchange/test_ccxt_compat.py`.
+To quickly test the public endpoints of an exchange, add a configuration for your exchange to `tests/exchange_online/conftest.py` and run these tests with `pytest --longrun tests/exchange_online/test_ccxt_compat.py`.
 Completing these tests successfully a good basis point (it's a requirement, actually), however these won't guarantee correct exchange functioning, as this only tests public endpoints, but no private endpoint (like generate order or similar).
 
 Also try to use `freqtrade download-data` for an extended timerange (multiple months) and verify that the data downloaded correctly (no holes, the specified timerange was actually downloaded).
@@ -376,7 +378,7 @@ from pathlib import Path
 
 exchange = ccxt.binance({
     'apiKey': '<apikey>',
-    'secret': '<secret>'
+    'secret': '<secret>',
     'options': {'defaultType': 'swap'}
     })
 _ = exchange.load_markets()

docs/edge.md

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

docs/exchanges.md

@@ -68,6 +68,8 @@ Binance supports [time_in_force](configuration.md#understand-order_time_in_force
 For Binance, it is suggested to add `"BNB/<STAKE>"` to your blacklist to avoid issues, unless you are willing to maintain enough extra `BNB` on the account or unless you're willing to disable using `BNB` for fees.
 Binance accounts may use `BNB` for fees, and if a trade happens to be on `BNB`, further trades may consume this position and make the initial BNB trade unsellable as the expected amount is not there anymore.
 
+If not enough `BNB` is available to cover transaction fees, then fees will not be covered by `BNB` and no fee reduction will occur. Freqtrade will never buy BNB to cover for fees. BNB needs to be bought and monitored manually to this end.
+
 ### Binance sites
 
 Binance has been split into 2, and users must use the correct ccxt exchange ID for their exchange, otherwise API keys are not recognized.
@@ -297,7 +299,7 @@ $ pip3 install web3
 Most exchanges return current incomplete candle via their OHLCV/klines API interface.
 By default, Freqtrade assumes that incomplete candle is fetched from the exchange and removes the last candle assuming it's the incomplete candle.
 
-Whether your exchange returns incomplete candles or not can be checked using [the helper script](developer.md#Incomplete-candles) from the Contributor documentation.
+Whether your exchange returns incomplete candles or not can be checked using [the helper script](developer.md#incomplete-candles) from the Contributor documentation.
 
 Due to the danger of repainting, Freqtrade does not allow you to use this incomplete candle.
 

docs/faq.md

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

docs/freqai-configuration.md

@@ -32,6 +32,9 @@ FreqAI is configured through the typical [Freqtrade config file](configuration.m
 
 A full example config is available in `config_examples/config_freqai.example.json`.
 
+!!! Note
+    The `identifier` is commonly overlooked by newcomers, however, this value plays an important role in your configuration. This value is a unique ID that you choose to describe one of your runs. Keeping it the same allows you to maintain crash resilience as well as faster backtesting. As soon as you want to try a new run (new features, new model, etc.), you should change this value (or delete the `user_data/models/unique-id` folder. More details available in the [parameter table](freqai-parameter-table.md#feature-parameters).
+
 ## Building a FreqAI strategy
 
 The FreqAI strategy requires including the following lines of code in the standard [Freqtrade strategy](strategy-customization.md):

docs/freqai-feature-engineering.md

@@ -235,7 +235,7 @@ By default, FreqAI builds a dynamic pipeline based on user congfiguration settin
 Users are encouraged to customize the data pipeline to their needs by building their own data pipeline. This can be done by simply setting `dk.feature_pipeline` to their desired `Pipeline` object inside their `IFreqaiModel` `train()` function, or if they prefer not to touch the `train()` function, they can override `define_data_pipeline`/`define_label_pipeline` functions in their `IFreqaiModel`:
 
 !!! note "More information available"
-    FreqAI uses the the [`DataSieve`](https://github.com/emergentmethods/datasieve) pipeline, which follows the SKlearn pipeline API, but adds, among other features, coherence between the X, y, and sample_weight vector point removals, feature removal, feature name following. 
+    FreqAI uses the [`DataSieve`](https://github.com/emergentmethods/datasieve) pipeline, which follows the SKlearn pipeline API, but adds, among other features, coherence between the X, y, and sample_weight vector point removals, feature removal, feature name following. 
 
 ```python
 from datasieve.transforms import SKLearnWrapper, DissimilarityIndex

docs/freqai-parameter-table.md

@@ -31,7 +31,7 @@ Mandatory parameters are marked as **Required** and have to be set in one of the
 | `feature_parameters` | A dictionary containing the parameters used to engineer the feature set. Details and examples are shown [here](freqai-feature-engineering.md). <br> **Datatype:** Dictionary.
 | `include_timeframes` | A list of timeframes that all indicators in `feature_engineering_expand_*()` will be created for. The list is added as features to the base indicators dataset. <br> **Datatype:** List of timeframes (strings).
 | `include_corr_pairlist` | A list of correlated coins that FreqAI will add as additional features to all `pair_whitelist` coins. All indicators set in `feature_engineering_expand_*()` during feature engineering (see details [here](freqai-feature-engineering.md)) will be created for each correlated coin. The correlated coins features are added to the base indicators dataset. <br> **Datatype:** List of assets (strings).
-| `label_period_candles` | Number of candles into the future that the labels are created for. This is used in `feature_engineering_expand_all()` (see `templates/FreqaiExampleStrategy.py` for detailed usage). You can create custom labels and choose whether to make use of this parameter or not. <br> **Datatype:** Positive integer.
+| `label_period_candles` | Number of candles into the future that the labels are created for. This can be used in `set_freqai_targets()` (see `templates/FreqaiExampleStrategy.py` for detailed usage). This parameter is not necessarily required, you can create custom labels and choose whether to make use of this parameter or not. Please see `templates/FreqaiExampleStrategy.py` to see the example usage. <br> **Datatype:** Positive integer.
 | `include_shifted_candles` | Add features from previous candles to subsequent candles with the intent of adding historical information. If used, FreqAI will duplicate and shift all features from the `include_shifted_candles` previous candles so that the information is available for the subsequent candle. <br> **Datatype:** Positive integer.
 | `weight_factor` | Weight training data points according to their recency (see details [here](freqai-feature-engineering.md#weighting-features-for-temporal-importance)). <br> **Datatype:** Positive float (typically < 1).
 | `indicator_max_period_candles` | **No longer used (#7325)**. Replaced by `startup_candle_count` which is set in the [strategy](freqai-configuration.md#building-a-freqai-strategy). `startup_candle_count` is timeframe independent and defines the maximum *period* used in `feature_engineering_*()` for indicator creation. FreqAI uses this parameter together with the maximum timeframe in `include_time_frames` to calculate how many data points to download such that the first data point does not include a NaN. <br> **Datatype:** Positive integer.
@@ -55,7 +55,7 @@ Mandatory parameters are marked as **Required** and have to be set in one of the
 |  |  **Data split parameters within the `freqai.data_split_parameters` sub dictionary**
 | `data_split_parameters` | Include any additional parameters available from scikit-learn `test_train_split()`, which are shown [here](https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.train_test_split.html) (external website). <br> **Datatype:** Dictionary.
 | `test_size` | The fraction of data that should be used for testing instead of training. <br> **Datatype:** Positive float < 1.
-| `shuffle` | Shuffle the training data points during training. Typically, to not remove the chronological order of data in time-series forecasting, this is set to `False`. <br> **Datatype:** Boolean. <br> Defaut: `False`.
+| `shuffle` | Shuffle the training data points during training. Typically, to not remove the chronological order of data in time-series forecasting, this is set to `False`. <br> **Datatype:** Boolean. <br> Default: `False`.
 
 ### Model training parameters
 
@@ -75,7 +75,7 @@ Mandatory parameters are marked as **Required** and have to be set in one of the
 | `rl_config` | A dictionary containing the control parameters for a Reinforcement Learning model. <br> **Datatype:** Dictionary.
 | `train_cycles` | Training time steps will be set based on the `train_cycles * number of training data points. <br> **Datatype:** Integer.
 | `max_trade_duration_candles`| Guides the agent training to keep trades below desired length. Example usage shown in `prediction_models/ReinforcementLearner.py` within the customizable `calculate_reward()` function. <br> **Datatype:** int.
-| `model_type` | Model string from stable_baselines3 or SBcontrib. Available strings include: `'TRPO', 'ARS', 'RecurrentPPO', 'MaskablePPO', 'PPO', 'A2C', 'DQN'`. User should ensure that `model_training_parameters` match those available to the corresponding stable_baselines3 model by visiting their documentaiton. [PPO doc](https://stable-baselines3.readthedocs.io/en/master/modules/ppo.html) (external website) <br> **Datatype:** string.
+| `model_type` | Model string from stable_baselines3 or SBcontrib. Available strings include: `'TRPO', 'ARS', 'RecurrentPPO', 'MaskablePPO', 'PPO', 'A2C', 'DQN'`. User should ensure that `model_training_parameters` match those available to the corresponding stable_baselines3 model by visiting their documentation. [PPO doc](https://stable-baselines3.readthedocs.io/en/master/modules/ppo.html) (external website) <br> **Datatype:** string.
 | `policy_type` | One of the available policy types from stable_baselines3 <br> **Datatype:** string.
 | `max_training_drawdown_pct` | The maximum drawdown that the agent is allowed to experience during training. <br> **Datatype:** float. <br> Default: 0.8
 | `cpu_count` | Number of threads/cpus to dedicate to the Reinforcement Learning training process (depending on if `ReinforcementLearning_multiproc` is selected or not). Recommended to leave this untouched, by default, this value is set to the total number of physical cores minus 1. <br> **Datatype:** int. 

docs/freqai-reinforcement-learning.md

@@ -142,7 +142,7 @@ Parameter details can be found [here](freqai-parameter-table.md), but in general
 As you begin to modify the strategy and the prediction model, you will quickly realize some important differences between the Reinforcement Learner and the Regressors/Classifiers. Firstly, the strategy does not set a target value (no labels!). Instead, you set the `calculate_reward()` function inside the `MyRLEnv` class (see below). A default `calculate_reward()` is provided inside `prediction_models/ReinforcementLearner.py` to demonstrate the necessary building blocks for creating rewards, but this is *not* designed for production. Users *must* create their own custom reinforcement learning model class or use a pre-built one from outside the Freqtrade source code and save it to `user_data/freqaimodels`. It is inside the `calculate_reward()` where creative theories about the market can be expressed. For example, you can reward your agent when it makes a winning trade, and penalize the agent when it makes a losing trade. Or perhaps, you wish to reward the agent for entering trades, and penalize the agent for sitting in trades too long. Below we show examples of how these rewards are all calculated:
 
 !!! note "Hint"
-    The best reward functions are ones that are continuously differentiable, and well scaled. In other words, adding a single large negative penalty to a rare event is not a good idea, and the neural net will not be able to learn that function. Instead, it is better to add a small negative penalty to a common event. This will help the agent learn faster. Not only this, but you can help improve the continuity of your rewards/penalties by having them scale with severity according to some linear/exponential functions. In other words, you'd slowly scale the penalty as the duration of the trade increases. This is better than a single large penalty occuring at a single point in time.
+    The best reward functions are ones that are continuously differentiable, and well scaled. In other words, adding a single large negative penalty to a rare event is not a good idea, and the neural net will not be able to learn that function. Instead, it is better to add a small negative penalty to a common event. This will help the agent learn faster. Not only this, but you can help improve the continuity of your rewards/penalties by having them scale with severity according to some linear/exponential functions. In other words, you'd slowly scale the penalty as the duration of the trade increases. This is better than a single large penalty occurring at a single point in time.
 
 ```python
 from freqtrade.freqai.prediction_models.ReinforcementLearner import ReinforcementLearner

docs/hyperopt.md

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

docs/includes/pairlists.md

@@ -6,7 +6,7 @@ In your configuration, you can use Static Pairlist (defined by the [`StaticPairL
 
 Additionally, [`AgeFilter`](#agefilter), [`PrecisionFilter`](#precisionfilter), [`PriceFilter`](#pricefilter), [`ShuffleFilter`](#shufflefilter), [`SpreadFilter`](#spreadfilter) and [`VolatilityFilter`](#volatilityfilter) act as Pairlist Filters, removing certain pairs and/or moving their positions in the pairlist.
 
-If multiple Pairlist Handlers are used, they are chained and a combination of all Pairlist Handlers forms the resulting pairlist the bot uses for trading and backtesting. Pairlist Handlers are executed in the sequence they are configured. You should always configure either `StaticPairList` or `VolumePairList` as the starting Pairlist Handler.
+If multiple Pairlist Handlers are used, they are chained and a combination of all Pairlist Handlers forms the resulting pairlist the bot uses for trading and backtesting. Pairlist Handlers are executed in the sequence they are configured. You can define either `StaticPairList`, `VolumePairList`, `ProducerPairList`, `RemotePairList` or `MarketCapPairList` as the starting Pairlist Handler.
 
 Inactive markets are always removed from the resulting pairlist. Explicitly blacklisted pairs (those in the `pair_blacklist` configuration setting) are also always removed from the resulting pairlist.
 
@@ -24,6 +24,7 @@ You may also use something like `.*DOWN/BTC` or `.*UP/BTC` to exclude leveraged
 * [`VolumePairList`](#volume-pair-list)
 * [`ProducerPairList`](#producerpairlist)
 * [`RemotePairList`](#remotepairlist)
+* [`MarketCapPairList`](#marketcappairlist)
 * [`AgeFilter`](#agefilter)
 * [`FullTradesFilter`](#fulltradesfilter)
 * [`OffsetFilter`](#offsetfilter)
@@ -67,7 +68,7 @@ When used in the leading position of the chain of Pairlist Handlers, the `pair_w
 
 The `refresh_period` setting allows to define the period (in seconds), at which the pairlist will be refreshed. Defaults to 1800s (30 minutes).
 The pairlist cache (`refresh_period`) on `VolumePairList` is only applicable to generating pairlists.
-Filtering instances (not the first position in the list) will not apply any cache and will always use up-to-date data.
+Filtering instances (not the first position in the list) will not apply any cache (beyond caching candles for the duration of the candle in advanced mode) and will always use up-to-date data.
 
 `VolumePairList` is per default based on the ticker data from exchange, as reported by the ccxt library:
 
@@ -80,12 +81,14 @@ Filtering instances (not the first position in the list) will not apply any cach
         "number_assets": 20,
         "sort_key": "quoteVolume",
         "min_value": 0,
+        "max_value": 8000000,
         "refresh_period": 1800
     }
 ],
 ```
 
 You can define a minimum volume with `min_value` - which will filter out pairs with a volume lower than the specified value in the specified timerange.
+In addition to that, you can also define a maximum volume with `max_value` - which will filter out pairs with a volume higher than the specified value in the specified timerange.
 
 ##### VolumePairList Advanced mode
 
@@ -200,7 +203,7 @@ The RemotePairList is defined in the pairlists section of the configuration sett
 
 The optional `mode` option specifies if the pairlist should be used as a `blacklist` or as a `whitelist`. The default value is "whitelist".
 
-The optional `processing_mode` option in the RemotePairList configuration determines how the retrieved pairlist is processed. It can have two values: "filter" or "append".
+The optional `processing_mode` option in the RemotePairList configuration determines how the retrieved pairlist is processed. It can have two values: "filter" or "append". The default value is "filter".
 
 In "filter" mode, the retrieved pairlist is used as a filter. Only the pairs present in both the original pairlist and the retrieved pairlist are included in the final pairlist. Other pairs are filtered out.
 
@@ -264,6 +267,25 @@ The optional `bearer_token` will be included in the requests Authorization Heade
 !!! Note
     In case of a server error the last received pairlist will be kept if `keep_pairlist_on_failure` is set to true, when set to false a empty pairlist is returned.
 
+#### MarketCapPairList
+
+`MarketCapPairList` employs sorting/filtering of pairs by their marketcap rank based of CoinGecko. It will only recognize coins up to the coin placed at rank 250. The returned pairlist will be sorted based of their marketcap ranks.
+
+```json
+"pairlists": [
+    {
+        "method": "MarketCapPairList",
+        "number_assets": 20,
+        "max_rank": 50,
+        "refresh_period": 86400
+    }
+]
+```
+
+`number_assets` defines the maximum number of pairs returned by the pairlist. `max_rank` will determine the maximum rank used in creating/filtering the pairlist. It's expected that some coins within the top `max_rank` marketcap will not be included in the resulting pairlist since not all pairs will have active trading pairs in your preferred market/stake/exchange combination.
+
+`refresh_period` setting defines the period (in seconds) at which the marketcap rank data will be refreshed. Defaults to 86,400s (1 day). The pairlist cache (`refresh_period`) is applicable on both generating pairlists (first position in the list) and filtering instances (not the first position in the list).
+
 #### AgeFilter
 
 Removes pairs that have been listed on the exchange for less than `min_days_listed` days (defaults to `10`) or more than `max_days_listed` days (defaults `None` mean infinity).
@@ -349,6 +371,11 @@ As this Filter uses past performance of the bot, it'll have some startup-period
 
 Filters low-value coins which would not allow setting stoplosses.
 
+Namely, pairs are blacklisted if a variance of one percent or more in the stop price would be caused by precision rounding on the exchange, i.e. `rounded(stop_price) <= rounded(stop_price * 0.99)`. The idea is to avoid coins with a value VERY close to their lower trading boundary, not allowing setting of proper stoploss.
+
+!!! Tip "PerformanceFilter is pointless for futures trading"
+    The above does not apply to shorts. And for longs, in theory the trade will be liquidated first.
+
 !!! Warning "Backtesting"
     `PrecisionFilter` does not support backtesting mode using multiple strategies.
 
@@ -430,6 +457,8 @@ If the trading range over the last 10 days is <1% or >99%, remove the pair from
 ]
 ```
 
+Adding `"sort_direction": "asc"` or `"sort_direction": "desc"` enables sorting for this pairlist.
+
 !!! Tip
     This Filter can be used to automatically remove stable coin pairs, which have a very low trading range, and are therefore extremely difficult to trade with profit.
     Additionally, it can also be used to automatically remove pairs with extreme high/low variance over a given amount of time.
@@ -440,7 +469,7 @@ Volatility is the degree of historical variation of a pairs over time, it is mea
 
 This filter removes pairs if the average volatility over a `lookback_days` days is below `min_volatility` or above `max_volatility`. Since this is a filter that requires additional data, the results are cached for `refresh_period`.
 
-This filter can be used to narrow down your pairs to a certain volatility or avoid very volatile pairs. 
+This filter can be used to narrow down your pairs to a certain volatility or avoid very volatile pairs.
 
 In the below example:
 If the volatility over the last 10 days is not in the range of 0.05-0.50, remove the pair from the whitelist. The filter is applied every 24h.
@@ -457,6 +486,8 @@ If the volatility over the last 10 days is not in the range of 0.05-0.50, remove
 ]
 ```
 
+Adding `"sort_direction": "asc"` or `"sort_direction": "desc"` enables sorting mode for this pairlist.
+
 ### Full example of Pairlist Handlers
 
 The below example blacklists `BNB/BTC`, uses `VolumePairList` with `20` assets, sorting pairs by `quoteVolume` and applies [`PrecisionFilter`](#precisionfilter) and [`PriceFilter`](#pricefilter), filtering all assets where 1 price unit is > 1%. Then the [`SpreadFilter`](#spreadfilter) and [`VolatilityFilter`](#volatilityfilter) is applied and pairs are finally shuffled with the random seed set to some predefined value.

docs/installation.md

@@ -51,7 +51,7 @@ These requirements apply to both [Script Installation](#script-installation) and
 ### Install code
 
 We've included/collected install instructions for Ubuntu, MacOS, and Windows. These are guidelines and your success may vary with other distros.
-OS Specific steps are listed first, the [Common](#common) section below is necessary for all systems.
+OS Specific steps are listed first, the common section below is necessary for all systems.
 
 !!! Note
     Python3.9 or higher and the corresponding pip are assumed to be available.

docs/leverage.md

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

docs/lookahead-analysis.md

@@ -23,6 +23,7 @@ It also supports the lookahead-analysis of freqai strategies.
 - `--max-open-trades` is forced to be at least equal to the number of pairs.
 - `--dry-run-wallet` is forced to be basically infinite (1 billion).
 - `--stake-amount` is forced to be a static 10000 (10k).
+- `--enable-protections` is forced to be off.
 
 Those are set to avoid users accidentally generating false positives.
 
@@ -40,7 +41,6 @@ usage: freqtrade lookahead-analysis [-h] [-v] [--logfile FILE] [-V] [-c PATH]
                                     [--max-open-trades INT]
                                     [--stake-amount STAKE_AMOUNT]
                                     [--fee FLOAT] [-p PAIRS [PAIRS ...]]
-                                    [--enable-protections]
                                     [--dry-run-wallet DRY_RUN_WALLET]
                                     [--timeframe-detail TIMEFRAME_DETAIL]
                                     [--strategy-list STRATEGY_LIST [STRATEGY_LIST ...]]

docs/requirements-docs.txt

@@ -1,6 +1,6 @@
-markdown==3.5.2
-mkdocs==1.5.3
-mkdocs-material==9.5.6
+markdown==3.6
+mkdocs==1.6.0
+mkdocs-material==9.5.19
 mdx_truly_sane_lists==1.3
-pymdown-extensions==10.7
+pymdown-extensions==10.8.1
 jinja2==3.1.3

docs/rest-api.md

@@ -89,17 +89,20 @@ Make sure that the following 2 lines are available in your docker-compose file:
 ```
 
 !!! Danger "Security warning"
-    By using `8080:8080` in the docker port mapping, the API will be available to everyone connecting to the server under the correct port, so others may be able to control your bot.
+    By using `"8080:8080"` (or `"0.0.0.0:8080:8080"`) in the docker port mapping, the API will be available to everyone connecting to the server under the correct port, so others may be able to control your bot.
+    This **may** be safe if you're running the bot in a secure environment (like your home network), but it's not recommended to expose the API to the internet.
 
 ## Rest API
 
 ### Consuming the API
 
-You can consume the API by using the script `scripts/rest_client.py`.
-The client script only requires the `requests` module, so Freqtrade does not need to be installed on the system.
+You can consume the API by using `freqtrade-client` (also available as `scripts/rest_client.py`).
+This command can be installed independent of the bot by using `pip install freqtrade-client`.
+
+This module is designed to be lightweight, and only depends on the `requests` and `python-rapidjson` modules, skipping all heavy dependencies freqtrade otherwise needs.
 
 ``` bash
-python3 scripts/rest_client.py <command> [optional parameters]
+freqtrade-client <command> [optional parameters]
 ```
 
 By default, the script assumes `127.0.0.1` (localhost) and port `8080` to be used, however you can specify a configuration file to override this behaviour.
@@ -120,9 +123,27 @@ By default, the script assumes `127.0.0.1` (localhost) and port `8080` to be use
 ```
 
 ``` bash
-python3 scripts/rest_client.py --config rest_config.json <command> [optional parameters]
+freqtrade-client --config rest_config.json <command> [optional parameters]
 ```
 
+??? Note "Programmatic use"
+    The `freqtrade-client` package (installable independent of freqtrade) can be used in your own scripts to interact with the freqtrade API.
+    to do so, please use the following:
+
+    ``` python
+    from freqtrade_client import FtRestClient
+    
+
+    client = FtRestClient(server_url, username, password)
+
+    # Get the status of the bot
+    ping = client.ping()
+    print(ping)
+    # ... 
+    ```
+
+    For a full list of available commands, please refer to the list below.
+
 ### Available endpoints
 
 |  Command | Description |
@@ -146,6 +167,7 @@ python3 scripts/rest_client.py --config rest_config.json <command> [optional par
 | `mix_tags [pair]` | Shows profit statistics for each combinations of enter tag + exit reasons for given pair (or all pairs if pair isn't given). Pair is optional.
 | `locks` | Displays currently locked pairs.
 | `delete_lock <lock_id>` | Deletes (disables) the lock by id.
+| `locks add <pair>, <until>, [side], [reason]` | Locks a pair until "until". (Until will be rounded up to the nearest timeframe).
 | `profit` | Display a summary of your profit/loss from close trades and some stats about your performance.
 | `forceexit <trade_id>` | Instantly exits the given trade  (Ignoring `minimum_roi`).
 | `forceexit all` | Instantly exits all open trades (Ignoring `minimum_roi`).
@@ -176,7 +198,7 @@ python3 scripts/rest_client.py --config rest_config.json <command> [optional par
 Possible commands can be listed from the rest-client script using the `help` command.
 
 ``` bash
-python3 scripts/rest_client.py help
+freqtrade-client help
 ```
 
 ``` output
@@ -433,7 +455,7 @@ To properly configure your reverse proxy (securely), please consult it's documen
 - **Caddy**: Caddy v2 supports websockets out of the box, see the [documentation](https://caddyserver.com/docs/v2-upgrade#proxy)
 
 !!! Tip "SSL certificates"
-    You can use tools like certbot to setup ssl certificates to access your bot's UI through encrypted connection by using any fo the above reverse proxies.
+    You can use tools like certbot to setup ssl certificates to access your bot's UI through encrypted connection by using any of the above reverse proxies.
     While this will protect your data in transit, we do not recommend to run the freqtrade API outside of your private network (VPN, SSH tunnel).
 
 ### OpenAPI interface

docs/sql_cheatsheet.md

@@ -109,7 +109,7 @@ Freqtrade does not depend or install any additional database driver. Please refe
 The following systems have been tested and are known to work with freqtrade:
 
 * sqlite (default)
-* PostgreSQL)
+* PostgreSQL
 * MariaDB
 
 !!! Warning

docs/stoploss.md

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

docs/strategy-advanced.md

@@ -11,34 +11,129 @@ The call sequence of the methods described here is covered under [bot execution
 !!! Tip
     Start off with a strategy template containing all available callback methods by running `freqtrade new-strategy --strategy MyAwesomeStrategy --template advanced`
 
-## Storing information
+## Storing information (Persistent)
 
-Storing information can be accomplished by creating a new dictionary within the strategy class.
+Freqtrade allows storing/retrieving user custom information associated with a specific trade in the database.
 
-The name of the variable can be chosen at will, but should be prefixed with `custom_` to avoid naming collisions with predefined strategy variables.
+Using a trade object, information can be stored using `trade.set_custom_data(key='my_key', value=my_value)` and retrieved using `trade.get_custom_data(key='my_key')`. Each data entry is associated with a trade and a user supplied key (of type `string`). This means that this can only be used in callbacks that also provide a trade object.
+
+For the data to be able to be stored within the database, freqtrade must serialized the data. This is done by converting the data to a JSON formatted string.
+Freqtrade will attempt to reverse this action on retrieval, so from a strategy perspective, this should not be relevant.
 
 ```python
+from freqtrade.persistence import Trade
+from datetime import timedelta
+
 class AwesomeStrategy(IStrategy):
-    # Create custom dictionary
-    custom_info = {}
 
-    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
-        # Check if the entry already exists
-        if not metadata["pair"] in self.custom_info:
-            # Create empty entry for this pair
-            self.custom_info[metadata["pair"]] = {}
+    def bot_loop_start(self, **kwargs) -> None:
+        for trade in Trade.get_open_order_trades():
+            fills = trade.select_filled_orders(trade.entry_side)
+            if trade.pair == 'ETH/USDT':
+                trade_entry_type = trade.get_custom_data(key='entry_type')
+                if trade_entry_type is None:
+                    trade_entry_type = 'breakout' if 'entry_1' in trade.enter_tag else 'dip'
+                elif fills > 1:
+                    trade_entry_type = 'buy_up'
+                trade.set_custom_data(key='entry_type', value=trade_entry_type)
+        return super().bot_loop_start(**kwargs)
 
-        if "crosstime" in self.custom_info[metadata["pair"]]:
-            self.custom_info[metadata["pair"]]["crosstime"] += 1
-        else:
-            self.custom_info[metadata["pair"]]["crosstime"] = 1
+    def adjust_entry_price(self, trade: Trade, order: Optional[Order], pair: str,
+                           current_time: datetime, proposed_rate: float, current_order_rate: float,
+                           entry_tag: Optional[str], side: str, **kwargs) -> float:
+        # Limit orders to use and follow SMA200 as price target for the first 10 minutes since entry trigger for BTC/USDT pair.
+        if (
+            pair == 'BTC/USDT' 
+            and entry_tag == 'long_sma200' 
+            and side == 'long' 
+            and (current_time - timedelta(minutes=10)) > trade.open_date_utc 
+            and order.filled == 0.0
+        ):
+            dataframe, _ = self.dp.get_analyzed_dataframe(pair=pair, timeframe=self.timeframe)
+            current_candle = dataframe.iloc[-1].squeeze()
+            # store information about entry adjustment
+            existing_count = trade.get_custom_data('num_entry_adjustments', default=0)
+            if not existing_count:
+                existing_count = 1
+            else:
+                existing_count += 1
+            trade.set_custom_data(key='num_entry_adjustments', value=existing_count)
+
+            # adjust order price
+            return current_candle['sma_200']
+
+        # default: maintain existing order
+        return current_order_rate
+
+    def custom_exit(self, pair: str, trade: Trade, current_time: datetime, current_rate: float, current_profit: float, **kwargs):
+
+        entry_adjustment_count = trade.get_custom_data(key='num_entry_adjustments')
+        trade_entry_type = trade.get_custom_data(key='entry_type')
+        if entry_adjustment_count is None:
+            if current_profit > 0.01 and (current_time - timedelta(minutes=100) > trade.open_date_utc):
+                return True, 'exit_1'
+        else
+            if entry_adjustment_count > 0 and if current_profit > 0.05:
+                return True, 'exit_2'
+            if trade_entry_type == 'breakout' and current_profit > 0.1:
+                return True, 'exit_3
+
+        return False, None
 ```
 
-!!! Warning
-    The data is not persisted after a bot-restart (or config-reload). Also, the amount of data should be kept smallish (no DataFrames and such), otherwise the bot will start to consume a lot of memory and eventually run out of memory and crash.
+The above is a simple example - there are simpler ways to retrieve trade data like entry-adjustments.
 
 !!! Note
-    If the data is pair-specific, make sure to use pair as one of the keys in the dictionary.
+    It is recommended that simple data types are used `[bool, int, float, str]` to ensure no issues when serializing the data that needs to be stored.
+    Storing big junks of data may lead to unintended side-effects, like a database becoming big (and as a consequence, also slow).
+
+!!! Warning "Non-serializable data"
+    If supplied data cannot be serialized a warning is logged and the entry for the specified `key` will contain `None` as data.
+
+??? Note "All attributes"
+    custom-data has the following accessors through the Trade object (assumed as `trade` below):
+
+    * `trade.get_custom_data(key='something', default=0)` - Returns the actual value given in the type provided.
+    * `trade.get_custom_data_entry(key='something')` - Returns the entry - including metadata. The value is accessible via `.value` property.
+    * `trade.set_custom_data(key='something', value={'some': 'value'})` - set or update the corresponding key for this trade. Value must be serializable - and we recommend to keep the stored data relatively small.
+
+    "value" can be any type (both in setting and receiving) - but must be json serializable.
+
+## Storing information (Non-Persistent)
+
+!!! Warning "Deprecated"
+    This method of storing information is deprecated and we do advise against using non-persistent storage.  
+    Please use [Persistent Storage](#storing-information-persistent) instead.
+
+    It's content has therefore been collapsed.
+
+??? Abstract "Storing information"
+    Storing information can be accomplished by creating a new dictionary within the strategy class.
+
+    The name of the variable can be chosen at will, but should be prefixed with `custom_` to avoid naming collisions with predefined strategy variables.
+
+    ```python
+    class AwesomeStrategy(IStrategy):
+        # Create custom dictionary
+        custom_info = {}
+
+        def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+            # Check if the entry already exists
+            if not metadata["pair"] in self.custom_info:
+                # Create empty entry for this pair
+                self.custom_info[metadata["pair"]] = {}
+
+            if "crosstime" in self.custom_info[metadata["pair"]]:
+                self.custom_info[metadata["pair"]]["crosstime"] += 1
+            else:
+                self.custom_info[metadata["pair"]]["crosstime"] = 1
+    ```
+
+    !!! Warning
+        The data is not persisted after a bot-restart (or config-reload). Also, the amount of data should be kept smallish (no DataFrames and such), otherwise the bot will start to consume a lot of memory and eventually run out of memory and crash.
+
+    !!! Note
+        If the data is pair-specific, make sure to use pair as one of the keys in the dictionary.
 
 ## Dataframe access
 
@@ -114,7 +209,7 @@ def custom_exit(self, pair: str, trade: Trade, current_time: datetime, current_r
 
 ## Exit tag
 
-Similar to [Buy Tagging](#buy-tag), you can also specify a sell tag.
+Similar to [Entry Tagging](#enter-tag), you can also specify an exit tag.
 
 ``` python
 def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
@@ -231,4 +326,4 @@ for val in self.buy_ema_short.range:
 dataframe = pd.concat(frames, axis=1)
 ```
 
-Freqtrade does however also counter this by running `dataframe.copy()` on the dataframe right after the `populate_indicators()` method - so performance implications of this should be low to non-existant.
+Freqtrade does however also counter this by running `dataframe.copy()` on the dataframe right after the `populate_indicators()` method - so performance implications of this should be low to non-existent.

docs/strategy-callbacks.md

@@ -19,6 +19,7 @@ Currently available callbacks:
 * [`adjust_trade_position()`](#adjust-trade-position)
 * [`adjust_entry_price()`](#adjust-entry-price)
 * [`leverage()`](#leverage-callback)
+* [`order_filled()`](#order-filled-callback)
 
 !!! Tip "Callback calling sequence"
     You can find the callback calling sequence in [bot-basics](bot-basics.md#bot-execution-logic)
@@ -166,7 +167,7 @@ During backtesting, `current_rate` (and `current_profit`) are provided against t
 The absolute value of the return value is used (the sign is ignored), so returning `0.05` or `-0.05` have the same result, a stoploss 5% below the current price.
 Returning None will be interpreted as "no desire to change", and is the only safe way to return when you'd like to not modify the stoploss.
 
-Stoploss on exchange works similar to `trailing_stop`, and the stoploss on exchange is updated as configured in `stoploss_on_exchange_interval` ([More details about stoploss on exchange](stoploss.md#stop-loss-on-exchange-freqtrade)).
+Stoploss on exchange works similar to `trailing_stop`, and the stoploss on exchange is updated as configured in `stoploss_on_exchange_interval` ([More details about stoploss on exchange](stoploss.md#stop-loss-on-exchangefreqtrade)).
 
 !!! Note "Use of dates"
     All time-based calculations should be done based on `current_time` - using `datetime.now()` or `datetime.utcnow()` is discouraged, as this will break backtesting support.
@@ -331,7 +332,7 @@ class AwesomeStrategy(IStrategy):
                         **kwargs) -> Optional[float]:
 
         if current_profit < 0.04:
-            return -1 # return a value bigger than the initial stoploss to keep using the initial stoploss
+            return None # return None to keep using the initial stoploss
 
         # After reaching the desired offset, allow the stoploss to trail by half the profit
         desired_stoploss = current_profit / 2
@@ -449,7 +450,7 @@ Stoploss values returned from `custom_stoploss()` must specify a percentage rela
 
     ```
 
-    Full examples can be found in the [Custom stoploss](strategy-advanced.md#custom-stoploss) section of the Documentation.
+    Full examples can be found in the [Custom stoploss](strategy-callbacks.md#custom-stoploss) section of the Documentation.
 
 !!! Note
     Providing invalid input to `stoploss_from_open()` may produce "CustomStoploss function did not return valid stoploss" warnings.
@@ -767,6 +768,7 @@ This callback is **not** called when there is an open order (either buy or sell)
 `adjust_trade_position()` is called very frequently for the duration of a trade, so you must keep your implementation as performant as possible.
 
 Position adjustments will always be applied in the direction of the trade, so a positive value will always increase your position (negative values will decrease your position), no matter if it's a long or short trade.
+Adjustment orders can be assigned with a tag by returning a 2 element Tuple, with the first element being the adjustment amount, and the 2nd element the tag (e.g. `return 250, 'increase_favorable_conditions'`).
 
 Modifications to leverage are not possible, and the stake-amount returned is assumed to be before applying leverage.
 
@@ -782,7 +784,7 @@ Additional entries are ignored once you have reached the maximum amount of extra
 ### Decrease position
 
 The strategy is expected to return a negative stake_amount (in stake currency) for a partial exit.
-Returning the full owned stake at that point (based on the current price) (`-(trade.amount / trade.leverage) * current_exit_rate`) results in a full exit.  
+Returning the full owned stake at that point (`-trade.stake_amount`) results in a full exit.  
 Returning a value more than the above (so remaining stake_amount would become negative) will result in the bot ignoring the signal.
 
 !!! Note "About stake size"
@@ -790,7 +792,7 @@ Returning a value more than the above (so remaining stake_amount would become ne
     If you wish to buy additional orders with DCA, then make sure to leave enough funds in the wallet for that.
     Using 'unlimited' stake amount with DCA orders requires you to also implement the `custom_stake_amount()` callback to avoid allocating all funds to the initial order.
 
-!!! Warning
+!!! Warning "Stoploss calculation"
     Stoploss is still calculated from the initial opening price, not averaged price.
     Regular stoploss rules still apply (cannot move down).
 
@@ -800,8 +802,14 @@ Returning a value more than the above (so remaining stake_amount would become ne
     During backtesting this callback is called for each candle in `timeframe` or `timeframe_detail`, so run-time performance will be affected.
     This can also cause deviating results between live and backtesting, since backtesting can adjust the trade only once per candle, whereas live could adjust the trade multiple times per candle.
 
+!!! Warning "Performance with many position adjustments"
+    Position adjustments can be a good approach to increase a strategy's output - but it can also have drawbacks if using this feature extensively.  
+    Each of the orders will be attached to the trade object for the duration of the trade - hence increasing memory usage.
+    Trades with long duration and 10s or even 100ds of position adjustments are therefore not recommended, and should be closed at regular intervals to not affect performance.
+
 ``` python
 from freqtrade.persistence import Trade
+from typing import Optional, Tuple, Union
 
 
 class DigDeeperStrategy(IStrategy):
@@ -833,7 +841,8 @@ class DigDeeperStrategy(IStrategy):
                               min_stake: Optional[float], max_stake: float,
                               current_entry_rate: float, current_exit_rate: float,
                               current_entry_profit: float, current_exit_profit: float,
-                              **kwargs) -> Optional[float]:
+                              **kwargs
+                              ) -> Union[Optional[float], Tuple[Optional[float], Optional[str]]]:
         """
         Custom trade adjustment logic, returning the stake amount that a trade should be
         increased or decreased.
@@ -859,11 +868,12 @@ class DigDeeperStrategy(IStrategy):
         :return float: Stake amount to adjust your trade,
                        Positive values to increase position, Negative values to decrease position.
                        Return None for no action.
+                       Optionally, return a tuple with a 2nd element with an order reason
         """
 
         if current_profit > 0.05 and trade.nr_of_successful_exits == 0:
             # Take half of the profit at +5%
-            return -(trade.stake_amount / 2)
+            return -(trade.stake_amount / 2), 'half_profit_5%'
 
         if current_profit > -0.05:
             return None
@@ -891,7 +901,7 @@ class DigDeeperStrategy(IStrategy):
             stake_amount = filled_entries[0].stake_amount
             # This then calculates current safety order size
             stake_amount = stake_amount * (1 + (count_of_entries * 0.25))
-            return stake_amount
+            return stake_amount, '1/3rd_increase'
         except Exception as exception:
             return None
 
@@ -939,7 +949,7 @@ If the cancellation of the original order fails, then the order will not be repl
 
 ```python
 from freqtrade.persistence import Trade
-from datetime import timedelta
+from datetime import timedelta, datetime
 
 class AwesomeStrategy(IStrategy):
 
@@ -1014,3 +1024,33 @@ class AwesomeStrategy(IStrategy):
 
 All profit calculations include leverage. Stoploss / ROI also include leverage in their calculation.
 Defining a stoploss of 10% at 10x leverage would trigger the stoploss with a 1% move to the downside.
+
+## Order filled Callback
+
+The `order_filled()` callback may be used to perform specific actions based on the current trade state after an order is filled.
+It will be called independent of the order type (entry, exit, stoploss or position adjustment).
+
+Assuming that your strategy needs to store the high value of the candle at trade entry, this is possible with this callback as the following example show.
+
+``` python
+class AwesomeStrategy(IStrategy):
+    def order_filled(self, pair: str, trade: Trade, order: Order, current_time: datetime, **kwargs) -> None:
+        """
+        Called right after an order fills. 
+        Will be called for all order types (entry, exit, stoploss, position adjustment).
+        :param pair: Pair for trade
+        :param trade: trade object.
+        :param order: Order object.
+        :param current_time: datetime object, containing the current datetime
+        :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
+        """
+        # Obtain pair dataframe (just to show how to access it)
+        dataframe, _ = self.dp.get_analyzed_dataframe(trade.pair, self.timeframe)
+        last_candle = dataframe.iloc[-1].squeeze()
+        
+        if (trade.nr_of_successful_entries == 1) and (order.ft_order_side == trade.entry_side):
+            trade.set_custom_data(key='entry_candle_high', value=last_candle['high'])
+
+        return None
+
+```

docs/strategy-customization.md

@@ -405,7 +405,7 @@ The metadata-dict (available for `populate_entry_trend`, `populate_exit_trend`,
 Currently this is `pair`, which can be accessed using `metadata['pair']` - and will return a pair in the format `XRP/BTC`.
 
 The Metadata-dict should not be modified and does not persist information across multiple calls.
-Instead, have a look at the [Storing information](strategy-advanced.md#Storing-information) section.
+Instead, have a look at the [Storing information](strategy-advanced.md#storing-information-persistent) section.
 
 ## Strategy file loading
 
@@ -551,8 +551,8 @@ for more information.
     
         # Define BTC/STAKE informative pair. A custom formatter may be specified for formatting
         # column names. A callable `fmt(**kwargs) -> str` may be specified, to implement custom
-        # formatting. Available in populate_indicators and other methods as 'rsi_upper'.
-        @informative('1h', 'BTC/{stake}', '{column}')
+        # formatting. Available in populate_indicators and other methods as 'rsi_upper_1h'.
+        @informative('1h', 'BTC/{stake}', '{column}_{timeframe}')
         def populate_indicators_btc_1h_2(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
             dataframe['rsi_upper'] = ta.RSI(dataframe, timeperiod=14)
             return dataframe
@@ -776,7 +776,7 @@ The orderbook structure is aligned with the order structure from [ccxt](https://
 Therefore, using `ob['bids'][0][0]` as demonstrated above will result in using the best bid price. `ob['bids'][0][1]` would look at the amount at this orderbook position.
 
 !!! Warning "Warning about backtesting"
-    The order book is not part of the historic data which means backtesting and hyperopt will not work correctly if this method is used, as the method will return uptodate values.
+    The order book is not part of the historic data which means backtesting and hyperopt will not work correctly if this method is used, as the method will return up-to-date values.
 
 ### *ticker(pair)*
 

docs/strategy_analysis_example.md

@@ -19,7 +19,7 @@ from pathlib import Path
 project_root = "somedir/freqtrade"
 i=0
 try:
-    os.chdirdir(project_root)
+    os.chdir(project_root)
     assert Path('LICENSE').is_file()
 except:
     while i<4 and (not Path('LICENSE').is_file()):

docs/telegram-usage.md

@@ -53,13 +53,13 @@ You can use bots in telegram groups by just adding them to the group. You can fi
 }
 ```
 
-For the Freqtrade configuration, you can then use the the full value (including `-` if it's there) as string:
+For the Freqtrade configuration, you can then use the full value (including `-` if it's there) as string:
 
 ```json
    "chat_id": "-1001332619709"
 ```
 !!! Warning "Using telegram groups"
-    When using telegram groups, you're giving every member of the telegram group access to your freqtrade bot and to all commands possible via telegram. Please make sure that you can trust everyone in the telegram group to avoid unpleasent surprises.
+    When using telegram groups, you're giving every member of the telegram group access to your freqtrade bot and to all commands possible via telegram. Please make sure that you can trust everyone in the telegram group to avoid unpleasant surprises.
 
 ## Control telegram noise
 
@@ -181,6 +181,7 @@ official commands. You can ask at any moment for help with `/help`.
 | `/locks` | Show currently locked pairs.
 | `/unlock <pair or lock_id>` | Remove the lock for this pair (or for this lock id).
 | `/marketdir [long | short | even | none]` | Updates the user managed variable that represents the current market direction. If no direction is provided, the currently set direction will be displayed.
+| `/list_custom_data <trade_id> [key]` | List custom_data for Trade ID & Key combination. If no Key is supplied it will list all key-value pairs found for that Trade ID.
 | **Modify Trade states** |
 | `/forceexit <trade_id> | /fx <tradeid>` | Instantly exits the given trade  (Ignoring `minimum_roi`).
 | `/forceexit all | /fx all` | Instantly exits all open trades (Ignoring `minimum_roi`).

docs/trade-object.md

@@ -126,7 +126,7 @@ An `Order` object will always be tied to it's corresponding [`Trade`](#trade-obj
 ### Order - Available attributes
 
 an Order object is typically attached to a trade.
-Most properties here can be None as they are dependant on the exchange response.
+Most properties here can be None as they are dependent on the exchange response.
 
 |  Attribute | DataType | Description |
 |------------|-------------|-------------|
@@ -141,7 +141,7 @@ Most properties here can be None as they are dependant on the exchange response.
 `amount` | float | Amount in base currency
 `filled` | float | Filled amount (in base currency)
 `remaining` | float | Remaining amount
-`cost` | float | Cost of the order - usually average * filled (*Exchange dependant on futures, may contain the cost with or without leverage and may be in contracts.*)
+`cost` | float | Cost of the order - usually average * filled (*Exchange dependent on futures, may contain the cost with or without leverage and may be in contracts.*)
 `stake_amount` | float | Stake amount used for this order. *Added in 2023.7.*
 `order_date` | datetime | Order creation date **use `order_date_utc` instead**
 `order_date_utc` | datetime | Order creation date (in UTC)

docs/updating.md

@@ -6,7 +6,7 @@ To update your freqtrade installation, please use one of the below methods, corr
     Breaking changes / changed behavior will be documented in the changelog that is posted alongside every release.
     For the develop branch, please follow PR's to avoid being surprised by changes.
 
-## docker
+## Docker
 
 !!! Note "Legacy installations using the `master` image"
     We're switching from master to stable for the release Images - please adjust your docker-file and replace `freqtradeorg/freqtrade:master` with `freqtradeorg/freqtrade:stable`

docs/utils.md

@@ -54,7 +54,7 @@ optional arguments:
 ### Create config examples
 
 ```
-$ freqtrade new-config --config config_binance.json
+$ freqtrade new-config --config user_data/config_binance.json
 
 ? Do you want to enable Dry-run (simulated trades)?  Yes
 ? Please insert your stake currency: BTC
@@ -66,6 +66,53 @@ $ freqtrade new-config --config config_binance.json
 ? Do you want to enable Telegram?  No
 ```
 
+## Show config
+
+Show configuration file (with sensitive values redacted by default).
+Especially useful with [split configuration files](configuration.md#multiple-configuration-files) or [environment variables](configuration.md#environment-variables), where this command will show the merged configuration.
+
+![Show config output](assets/show-config-output.png)
+
+```
+usage: freqtrade show-config [-h] [--userdir PATH] [-c PATH]
+                             [--show-sensitive]
+
+options:
+  -h, --help            show this help message and exit
+  --userdir PATH, --user-data-dir PATH
+                        Path to userdata directory.
+  -c PATH, --config PATH
+                        Specify configuration file (default:
+                        `userdir/config.json` or `config.json` whichever
+                        exists). Multiple --config options may be used. Can be
+                        set to `-` to read config from stdin.
+  --show-sensitive      Show secrets in the output.
+```
+
+``` output
+Your combined configuration is:
+{
+  "exit_pricing": {
+    "price_side": "other",
+    "use_order_book": true,
+    "order_book_top": 1
+  },
+  "stake_currency": "USDT",
+  "exchange": {
+    "name": "binance",
+    "key": "REDACTED",
+    "secret": "REDACTED",
+    "ccxt_config": {},
+    "ccxt_async_config": {},
+  }
+  // ...
+}
+```
+
+!!! Warning "Sharing information provided by this command"
+    We try to remove all known sensitive information from the default output (without `--show-sensitive`). 
+    Yet, please do double-check for sensitive values in your output to make sure you're not accidentally exposing some private info.
+
 ## Create new strategy
 
 Creates a new strategy from a template similar to SampleStrategy.
@@ -219,207 +266,49 @@ optional arguments:
   -a, --all         Print all exchanges known to the ccxt library.
 ```
 
-* Example: see exchanges available for the bot:
+Example: see exchanges available for the bot:
+
 ```
 $ freqtrade list-exchanges
 Exchanges available for Freqtrade:
-Exchange name    Valid    reason
----------------  -------  --------------------------------------------
-aax              True
-ascendex         True     missing opt: fetchMyTrades
-bequant          True
-bibox            True
-bigone           True
-binance          True
-binanceus        True
-bitbank          True     missing opt: fetchTickers
-bitcoincom       True
-bitfinex         True
-bitforex         True     missing opt: fetchMyTrades, fetchTickers
-bitget           True
-bithumb          True     missing opt: fetchMyTrades
-bitkk            True     missing opt: fetchMyTrades
-bitmart          True
-bitmax           True     missing opt: fetchMyTrades
-bitpanda         True
-bitvavo          True
-bitz             True     missing opt: fetchMyTrades
-btcalpha         True     missing opt: fetchTicker, fetchTickers
-btcmarkets       True     missing opt: fetchTickers
-buda             True     missing opt: fetchMyTrades, fetchTickers
-bw               True     missing opt: fetchMyTrades, fetchL2OrderBook
-bybit            True
-bytetrade        True
-cdax             True
-cex              True     missing opt: fetchMyTrades
-coinbaseprime    True     missing opt: fetchTickers
-coinbasepro      True     missing opt: fetchTickers
-coinex           True
-crex24           True
-deribit          True
-digifinex        True
-equos            True     missing opt: fetchTicker, fetchTickers
-eterbase         True
-fcoin            True     missing opt: fetchMyTrades, fetchTickers
-fcoinjp          True     missing opt: fetchMyTrades, fetchTickers
-gateio           True
-gemini           True
-gopax            True
-hbtc             True
-hitbtc           True
-huobijp          True
-huobipro         True
-idex             True
-kraken           True
-kucoin           True
-lbank            True     missing opt: fetchMyTrades
-mercado          True     missing opt: fetchTickers
-ndax             True     missing opt: fetchTickers
-novadax          True
-okcoin           True
-okex             True
-probit           True
-qtrade           True
-stex             True
-timex            True
-upbit            True     missing opt: fetchMyTrades
-vcc              True
-zb               True     missing opt: fetchMyTrades
-
+Exchange name       Supported    Markets                 Reason
+------------------  -----------  ----------------------  ------------------------------------------------------------------------
+binance             Official     spot, isolated futures
+bitmart             Official     spot
+bybit                            spot, isolated futures
+gate                Official     spot, isolated futures
+htx                 Official     spot
+huobi                            spot
+kraken              Official     spot
+okx                 Official     spot, isolated futures
 ```
 
+!!! info ""
+    Output reduced for clarity - supported and available exchanges may change over time.
+
 !!! Note "missing opt exchanges"
     Values with "missing opt:" might need special configuration (e.g. using orderbook if `fetchTickers` is missing) - but should in theory work (although we cannot guarantee they will).
 
-* Example: see all exchanges supported by the ccxt library (including 'bad' ones, i.e. those that are known to not work with Freqtrade):
+Example: see all exchanges supported by the ccxt library (including 'bad' ones, i.e. those that are known to not work with Freqtrade)
+
 ```
 $ freqtrade list-exchanges -a
 All exchanges supported by the ccxt library:
-Exchange name       Valid    reason
-------------------  -------  ---------------------------------------------------------------------------------------
-aax                 True
-aofex               False    missing: fetchOrder
-ascendex            True     missing opt: fetchMyTrades
-bequant             True
-bibox               True
-bigone              True
-binance             True
-binanceus           True
-bit2c               False    missing: fetchOrder, fetchOHLCV
-bitbank             True     missing opt: fetchTickers
-bitbay              False    missing: fetchOrder
-bitcoincom          True
-bitfinex            True
-bitfinex2           False    missing: fetchOrder
-bitflyer            False    missing: fetchOrder, fetchOHLCV
-bitforex            True     missing opt: fetchMyTrades, fetchTickers
-bitget              True
-bithumb             True     missing opt: fetchMyTrades
-bitkk               True     missing opt: fetchMyTrades
-bitmart             True
-bitmax              True     missing opt: fetchMyTrades
-bitmex              False    Various reasons.
-bitpanda            True
-bitso               False    missing: fetchOHLCV
-bitstamp            True     missing opt: fetchTickers
-bitstamp1           False    missing: fetchOrder, fetchOHLCV
-bitvavo             True
-bitz                True     missing opt: fetchMyTrades
-bl3p                False    missing: fetchOrder, fetchOHLCV
-bleutrade           False    missing: fetchOrder
-braziliex           False    missing: fetchOHLCV
-btcalpha            True     missing opt: fetchTicker, fetchTickers
-btcbox              False    missing: fetchOHLCV
-btcmarkets          True     missing opt: fetchTickers
-btctradeua          False    missing: fetchOrder, fetchOHLCV
-btcturk             False    missing: fetchOrder
-buda                True     missing opt: fetchMyTrades, fetchTickers
-bw                  True     missing opt: fetchMyTrades, fetchL2OrderBook
-bybit               True
-bytetrade           True
-cdax                True
-cex                 True     missing opt: fetchMyTrades
-chilebit            False    missing: fetchOrder, fetchOHLCV
-coinbase            False    missing: fetchOrder, cancelOrder, createOrder, fetchOHLCV
-coinbaseprime       True     missing opt: fetchTickers
-coinbasepro         True     missing opt: fetchTickers
-coincheck           False    missing: fetchOrder, fetchOHLCV
-coinegg             False    missing: fetchOHLCV
-coinex              True
-coinfalcon          False    missing: fetchOHLCV
-coinfloor           False    missing: fetchOrder, fetchOHLCV
-coingi              False    missing: fetchOrder, fetchOHLCV
-coinmarketcap       False    missing: fetchOrder, cancelOrder, createOrder, fetchBalance, fetchOHLCV
-coinmate            False    missing: fetchOHLCV
-coinone             False    missing: fetchOHLCV
-coinspot            False    missing: fetchOrder, cancelOrder, fetchOHLCV
-crex24              True
-currencycom         False    missing: fetchOrder
-delta               False    missing: fetchOrder
-deribit             True
-digifinex           True
-equos               True     missing opt: fetchTicker, fetchTickers
-eterbase            True
-exmo                False    missing: fetchOrder
-exx                 False    missing: fetchOHLCV
-fcoin               True     missing opt: fetchMyTrades, fetchTickers
-fcoinjp             True     missing opt: fetchMyTrades, fetchTickers
-flowbtc             False    missing: fetchOrder, fetchOHLCV
-foxbit              False    missing: fetchOrder, fetchOHLCV
-gateio              True
-gemini              True
-gopax               True
-hbtc                True
-hitbtc              True
-hollaex             False    missing: fetchOrder
-huobijp             True
-huobipro            True
-idex                True
-independentreserve  False    missing: fetchOHLCV
-indodax             False    missing: fetchOHLCV
-itbit               False    missing: fetchOHLCV
-kraken              True
-kucoin              True
-kuna                False    missing: fetchOHLCV
-lakebtc             False    missing: fetchOrder, fetchOHLCV
-latoken             False    missing: fetchOrder, fetchOHLCV
-lbank               True     missing opt: fetchMyTrades
-liquid              False    missing: fetchOHLCV
-luno                False    missing: fetchOHLCV
-lykke               False    missing: fetchOHLCV
-mercado             True     missing opt: fetchTickers
-mixcoins            False    missing: fetchOrder, fetchOHLCV
-ndax                True     missing opt: fetchTickers
-novadax             True
-oceanex             False    missing: fetchOHLCV
-okcoin              True
-okex                True
-paymium             False    missing: fetchOrder, fetchOHLCV
-phemex              False    Does not provide history.
-poloniex            False    missing: fetchOrder
-probit              True
-qtrade              True
-rightbtc            False    missing: fetchOrder
-ripio               False    missing: fetchOHLCV
-southxchange        False    missing: fetchOrder, fetchOHLCV
-stex                True
-surbitcoin          False    missing: fetchOrder, fetchOHLCV
-therock             False    missing: fetchOHLCV
-tidebit             False    missing: fetchOrder
-tidex               False    missing: fetchOHLCV
-timex               True
-upbit               True     missing opt: fetchMyTrades
-vbtc                False    missing: fetchOrder, fetchOHLCV
-vcc                 True
-wavesexchange       False    missing: fetchOrder
-whitebit            False    missing: fetchOrder, cancelOrder, createOrder, fetchBalance
-xbtce               False    missing: fetchOrder, fetchOHLCV
-xena                False    missing: fetchOrder
-yobit               False    missing: fetchOHLCV
-zaif                False    missing: fetchOrder, fetchOHLCV
-zb                  True     missing opt: fetchMyTrades
+Exchange name       Valid    Supported    Markets                 Reason
+------------------  -------  -----------  ----------------------  ---------------------------------------------------------------------------------
+binance             True     Official     spot, isolated futures
+bitflyer            False                 spot                    missing: fetchOrder. missing opt: fetchTickers.
+bitmart             True     Official     spot
+bybit               True                  spot, isolated futures
+gate                True     Official     spot, isolated futures
+htx                 True     Official     spot
+kraken              True     Official     spot
+okx                 True     Official     spot, isolated futures
 ```
 
+!!! info ""
+    Reduced output - supported and available exchanges may change over time.
+
 ## List Timeframes
 
 Use the `list-timeframes` subcommand to see the list of timeframes available for the exchange.
@@ -990,11 +879,7 @@ options:
   -h, --help            show this help message and exit
   --strategy-list STRATEGY_LIST [STRATEGY_LIST ...]
                         Provide a space-separated list of strategies to
-                        backtest. Please note that timeframe needs to be set
-                        either in config or via command line. When using this
-                        together with `--export trades`, the strategy-name is
-                        injected into the filename (so `backtest-data.json`
-                        becomes `backtest-data-SampleStrategy.json`
+                        be converted.
 
 Common arguments:
   -v, --verbose         Verbose mode (-vv for more, -vvv to get all messages).

docs/webhook-config.md

@@ -65,7 +65,7 @@ You can set the POST body format to Form-Encoded (default), JSON-Encoded, or raw
 
 The result would be a POST request with e.g. `{"text":"Status: running"}` body and `Content-Type: application/json` header which results `Status: running` message in the Mattermost channel.
 
-When using the Form-Encoded or JSON-Encoded configuration you can configure any number of payload values, and both the key and value will be ouput in the POST request. However, when using the raw data format you can only configure one value and it **must** be named `"data"`. In this instance the data key will not be output in the POST request, only the value. For example:
+When using the Form-Encoded or JSON-Encoded configuration you can configure any number of payload values, and both the key and value will be output in the POST request. However, when using the raw data format you can only configure one value and it **must** be named `"data"`. In this instance the data key will not be output in the POST request, only the value. For example:
 
 ```json
   "webhook": {

freqtrade/__init__.py

@@ -1,5 +1,5 @@
 """ Freqtrade bot """
-__version__ = '2024.1'
+__version__ = '2024.4'
 
 if 'dev' in __version__:
     from pathlib import Path

freqtrade/commands/__init__.py

@@ -8,7 +8,7 @@ Note: Be careful with file-scoped imports in these subfiles.
 """
 from freqtrade.commands.analyze_commands import start_analysis_entries_exits
 from freqtrade.commands.arguments import Arguments
-from freqtrade.commands.build_config_commands import start_new_config
+from freqtrade.commands.build_config_commands import start_new_config, start_show_config
 from freqtrade.commands.data_commands import (start_convert_data, start_convert_trades,
                                               start_download_data, start_list_data)
 from freqtrade.commands.db_commands import start_convert_db

freqtrade/commands/analyze_commands.py

@@ -4,7 +4,7 @@ from typing import Any, Dict
 
 from freqtrade.configuration import setup_utils_configuration
 from freqtrade.enums import RunMode
-from freqtrade.exceptions import OperationalException
+from freqtrade.exceptions import ConfigurationError, OperationalException
 
 
 logger = logging.getLogger(__name__)
@@ -34,9 +34,9 @@ def setup_analyze_configuration(args: Dict[str, Any], method: RunMode) -> Dict[s
                     btfile = Path(config['exportfilename'])
                     signals_file = f"{btfile.parent}/{btfile.stem}_signals.pkl"
                 else:
-                    raise OperationalException(f"{config['exportfilename']} does not exist.")
+                    raise ConfigurationError(f"{config['exportfilename']} does not exist.")
         else:
-            raise OperationalException('exportfilename not in config.')
+            raise ConfigurationError('exportfilename not in config.')
 
         if (not Path(signals_file).exists()):
             raise OperationalException(

freqtrade/commands/arguments.py

@@ -62,6 +62,7 @@ ARGS_TEST_PAIRLIST = ["user_data_dir", "verbosity", "config", "quote_currencies"
 ARGS_CREATE_USERDIR = ["user_data_dir", "reset"]
 
 ARGS_BUILD_CONFIG = ["config"]
+ARGS_SHOW_CONFIG = ["user_data_dir", "config", "show_sensitive"]
 
 ARGS_BUILD_STRATEGY = ["user_data_dir", "strategy", "template"]
 
@@ -69,7 +70,8 @@ ARGS_CONVERT_DATA_TRADES = ["pairs", "format_from_trades", "format_to", "erase",
 ARGS_CONVERT_DATA = ["pairs", "format_from", "format_to", "erase", "exchange"]
 ARGS_CONVERT_DATA_OHLCV = ARGS_CONVERT_DATA + ["timeframes", "trading_mode", "candle_types"]
 
-ARGS_CONVERT_TRADES = ["pairs", "timeframes", "exchange", "dataformat_ohlcv", "dataformat_trades"]
+ARGS_CONVERT_TRADES = ["pairs", "timeframes", "exchange", "dataformat_ohlcv", "dataformat_trades",
+                       "trading_mode"]
 
 ARGS_LIST_DATA = ["exchange", "dataformat_ohlcv", "pairs", "trading_mode", "show_timerange"]
 
@@ -195,7 +197,10 @@ class Arguments:
         self._build_args(optionlist=ARGS_STRATEGY, parser=strategy_group)
 
         # Build main command
-        self.parser = argparse.ArgumentParser(description='Free, open source crypto trading bot')
+        self.parser = argparse.ArgumentParser(
+            prog="freqtrade",
+            description='Free, open source crypto trading bot'
+        )
         self._build_args(optionlist=['version'], parser=self.parser)
 
         from freqtrade.commands import (start_analysis_entries_exits, start_backtesting,
@@ -208,9 +213,9 @@ class Arguments:
                                         start_list_strategies, start_list_timeframes,
                                         start_lookahead_analysis, start_new_config,
                                         start_new_strategy, start_plot_dataframe, start_plot_profit,
-                                        start_recursive_analysis, start_show_trades,
-                                        start_strategy_update, start_test_pairlist, start_trading,
-                                        start_webserver)
+                                        start_recursive_analysis, start_show_config,
+                                        start_show_trades, start_strategy_update,
+                                        start_test_pairlist, start_trading, start_webserver)
 
         subparsers = self.parser.add_subparsers(dest='command',
                                                 # Use custom message when no subhandler is added
@@ -243,6 +248,14 @@ class Arguments:
         build_config_cmd.set_defaults(func=start_new_config)
         self._build_args(optionlist=ARGS_BUILD_CONFIG, parser=build_config_cmd)
 
+        # add show-config subcommand
+        show_config_cmd = subparsers.add_parser(
+            'show-config',
+            help="Show resolved config",
+        )
+        show_config_cmd.set_defaults(func=start_show_config)
+        self._build_args(optionlist=ARGS_SHOW_CONFIG, parser=show_config_cmd)
+
         # add new-strategy subcommand
         build_strategy_cmd = subparsers.add_parser(
             'new-strategy',

freqtrade/commands/build_config_commands.py

@@ -5,9 +5,12 @@ from typing import Any, Dict, List
 
 from questionary import Separator, prompt
 
+from freqtrade.configuration import sanitize_config
+from freqtrade.configuration.config_setup import setup_utils_configuration
 from freqtrade.configuration.detect_environment import running_in_docker
 from freqtrade.configuration.directory_operations import chown_user_directory
 from freqtrade.constants import UNLIMITED_STAKE_AMOUNT
+from freqtrade.enums import RunMode
 from freqtrade.exceptions import OperationalException
 from freqtrade.exchange import MAP_EXCHANGE_CHILDCLASS, available_exchanges
 from freqtrade.util import render_template
@@ -264,3 +267,19 @@ def start_new_config(args: Dict[str, Any]) -> None:
                 "Please delete it or use a different configuration file name.")
     selections = ask_user_config()
     deploy_new_config(config_path, selections)
+
+
+def start_show_config(args: Dict[str, Any]) -> None:
+
+    config = setup_utils_configuration(args, RunMode.UTIL_EXCHANGE, set_dry=False)
+
+    # TODO: Sanitize from sensitive info before printing
+
+    print("Your combined configuration is:")
+    config_sanitized = sanitize_config(
+        config['original_config'],
+        show_sensitive=args.get('show_sensitive', False)
+    )
+
+    from rich import print_json
+    print_json(data=config_sanitized)

freqtrade/commands/cli_options.py

@@ -716,4 +716,10 @@ AVAILABLE_CLI_OPTIONS = {
         help='Specify startup candles to be checked (`199`, `499`, `999`, `1999`).',
         nargs='+',
     ),
+    "show_sensitive": Arg(
+        '--show-sensitive',
+        help='Show secrets in the output.',
+        action='store_true',
+        default=False,
+    ),
 }

freqtrade/commands/data_commands.py

@@ -8,9 +8,10 @@ from freqtrade.constants import DATETIME_PRINT_FORMAT, DL_DATA_TIMEFRAMES, Confi
 from freqtrade.data.converter import (convert_ohlcv_format, convert_trades_format,
                                       convert_trades_to_ohlcv)
 from freqtrade.data.history import download_data_main
-from freqtrade.enums import RunMode, TradingMode
-from freqtrade.exceptions import OperationalException
+from freqtrade.enums import CandleType, RunMode, TradingMode
+from freqtrade.exceptions import ConfigurationError
 from freqtrade.exchange import timeframe_to_minutes
+from freqtrade.plugins.pairlist.pairlist_helpers import dynamic_expand_pairlist
 from freqtrade.resolvers import ExchangeResolver
 from freqtrade.util.migrations import migrate_data
 
@@ -20,11 +21,11 @@ logger = logging.getLogger(__name__)
 
 def _check_data_config_download_sanity(config: Config) -> None:
     if 'days' in config and 'timerange' in config:
-        raise OperationalException("--days and --timerange are mutually exclusive. "
-                                   "You can only specify one or the other.")
+        raise ConfigurationError("--days and --timerange are mutually exclusive. "
+                                 "You can only specify one or the other.")
 
     if 'pairs' not in config:
-        raise OperationalException(
+        raise ConfigurationError(
             "Downloading data requires a list of pairs. "
             "Please check the documentation on how to configure this.")
 
@@ -62,13 +63,21 @@ def start_convert_trades(args: Dict[str, Any]) -> None:
 
     for timeframe in config['timeframes']:
         exchange.validate_timeframes(timeframe)
+    available_pairs = [
+        p for p in exchange.get_markets(
+            tradable_only=True, active_only=not config.get('include_inactive')
+            ).keys()
+    ]
+
+    expanded_pairs = dynamic_expand_pairlist(config, available_pairs)
 
     # Convert downloaded trade data to different timeframes
     convert_trades_to_ohlcv(
-        pairs=config.get('pairs', []), timeframes=config['timeframes'],
+        pairs=expanded_pairs, timeframes=config['timeframes'],
         datadir=config['datadir'], timerange=timerange, erase=bool(config.get('erase')),
         data_format_ohlcv=config['dataformat_ohlcv'],
         data_format_trades=config['dataformat_trades'],
+        candle_type=config.get('candle_type_def', CandleType.SPOT)
     )
 
 
@@ -98,7 +107,7 @@ def start_list_data(args: Dict[str, Any]) -> None:
 
     from tabulate import tabulate
 
-    from freqtrade.data.history.idatahandler import get_datahandler
+    from freqtrade.data.history import get_datahandler
     dhc = get_datahandler(config['datadir'], config['dataformat_ohlcv'])
 
     paircombs = dhc.ohlcv_get_available_data(

freqtrade/commands/deploy_commands.py

@@ -9,13 +9,17 @@ from freqtrade.configuration import setup_utils_configuration
 from freqtrade.configuration.directory_operations import copy_sample_files, create_userdata_dir
 from freqtrade.constants import USERPATH_STRATEGIES
 from freqtrade.enums import RunMode
-from freqtrade.exceptions import OperationalException
+from freqtrade.exceptions import ConfigurationError, OperationalException
 from freqtrade.util import render_template, render_template_with_fallback
 
 
 logger = logging.getLogger(__name__)
 
 
+# Timeout for requests
+req_timeout = 30
+
+
 def start_create_userdir(args: Dict[str, Any]) -> None:
     """
     Create "user_data" directory to contain user data strategies, hyperopt, ...)
@@ -89,7 +93,7 @@ def start_new_strategy(args: Dict[str, Any]) -> None:
         deploy_new_strategy(args['strategy'], new_path, args['template'])
 
     else:
-        raise OperationalException("`new-strategy` requires --strategy to be set.")
+        raise ConfigurationError("`new-strategy` requires --strategy to be set.")
 
 
 def clean_ui_subdir(directory: Path):
@@ -119,7 +123,7 @@ def download_and_install_ui(dest_folder: Path, dl_url: str, version: str):
     from zipfile import ZipFile
 
     logger.info(f"Downloading {dl_url}")
-    resp = requests.get(dl_url).content
+    resp = requests.get(dl_url, timeout=req_timeout).content
     dest_folder.mkdir(parents=True, exist_ok=True)
     with ZipFile(BytesIO(resp)) as zf:
         for fn in zf.filelist:
@@ -137,7 +141,7 @@ def get_ui_download_url(version: Optional[str] = None) -> Tuple[str, str]:
     base_url = 'https://api.github.com/repos/freqtrade/frequi/'
     # Get base UI Repo path
 
-    resp = requests.get(f"{base_url}releases")
+    resp = requests.get(f"{base_url}releases", timeout=req_timeout)
     resp.raise_for_status()
     r = resp.json()
 
@@ -158,7 +162,7 @@ def get_ui_download_url(version: Optional[str] = None) -> Tuple[str, str]:
     # URL not found - try assets url
     if not dl_url:
         assets = r[0]['assets_url']
-        resp = requests.get(assets)
+        resp = requests.get(assets, timeout=req_timeout)
         r = resp.json()
         dl_url = r[0]['browser_download_url']
 

freqtrade/commands/list_commands.py

@@ -10,7 +10,7 @@ from tabulate import tabulate
 
 from freqtrade.configuration import setup_utils_configuration
 from freqtrade.enums import RunMode
-from freqtrade.exceptions import OperationalException
+from freqtrade.exceptions import ConfigurationError, OperationalException
 from freqtrade.exchange import list_available_exchanges, market_is_active
 from freqtrade.misc import parse_db_uri_for_logging, plural
 from freqtrade.resolvers import ExchangeResolver, StrategyResolver
@@ -246,7 +246,7 @@ def start_show_trades(args: Dict[str, Any]) -> None:
     config = setup_utils_configuration(args, RunMode.UTIL_NO_EXCHANGE)
 
     if 'db_url' not in config:
-        raise OperationalException("--db-url is required for this command.")
+        raise ConfigurationError("--db-url is required for this command.")
 
     logger.info(f'Using DB: "{parse_db_uri_for_logging(config["db_url"])}"')
     init_db(config['db_url'])

freqtrade/commands/optimize_commands.py

@@ -4,7 +4,7 @@ from typing import Any, Dict
 from freqtrade import constants
 from freqtrade.configuration import setup_utils_configuration
 from freqtrade.enums import RunMode
-from freqtrade.exceptions import OperationalException
+from freqtrade.exceptions import ConfigurationError, OperationalException
 from freqtrade.util import fmt_coin
 
 
@@ -31,7 +31,7 @@ def setup_optimize_configuration(args: Dict[str, Any], method: RunMode) -> Dict[
                 and config['stake_amount'] > wallet_size):
             wallet = fmt_coin(wallet_size, config['stake_currency'])
             stake = fmt_coin(config['stake_amount'], config['stake_currency'])
-            raise OperationalException(
+            raise ConfigurationError(
                 f"Starting balance ({wallet}) is smaller than stake_amount {stake}. "
                 f"Wallet is calculated as `dry_run_wallet * tradable_balance_ratio`."
                 )

freqtrade/commands/plot_commands.py

@@ -2,12 +2,12 @@ from typing import Any, Dict
 
 from freqtrade.configuration import setup_utils_configuration
 from freqtrade.enums import RunMode
-from freqtrade.exceptions import OperationalException
+from freqtrade.exceptions import ConfigurationError
 
 
 def validate_plot_args(args: Dict[str, Any]) -> None:
     if not args.get('datadir') and not args.get('config'):
-        raise OperationalException(
+        raise ConfigurationError(
             "You need to specify either `--datadir` or `--config` "
             "for plot-profit and plot-dataframe.")
 

freqtrade/commands/trade_commands.py

@@ -23,11 +23,6 @@ def start_trading(args: Dict[str, Any]) -> int:
         signal.signal(signal.SIGTERM, term_handler)
         worker = Worker(args)
         worker.run()
-    except Exception as e:
-        logger.error(str(e))
-        logger.exception("Fatal exception!")
-    except (KeyboardInterrupt):
-        logger.info('SIGINT received, aborting ...')
     finally:
         if worker:
             logger.info("worker found ... calling exit")

freqtrade/configuration/__init__.py

@@ -1,5 +1,6 @@
 # flake8: noqa: F401
 
+from freqtrade.configuration.config_secrets import 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

@@ -0,0 +1,36 @@
+from copy import deepcopy
+
+from freqtrade.constants import Config
+
+
+def sanitize_config(config: Config, *, show_sensitive: bool = False) -> Config:
+    """
+    Remove sensitive information from the config.
+    :param config: Configuration
+    :param show_sensitive: Show sensitive information
+    :return: Configuration
+    """
+    if show_sensitive:
+        return config
+    keys_to_remove = [
+        "exchange.key",
+        "exchange.secret",
+        "exchange.password",
+        "exchange.uid",
+        "telegram.token",
+        "telegram.chat_id",
+        "discord.webhook_url",
+        "api_server.password",
+    ]
+    config = deepcopy(config)
+    for key in keys_to_remove:
+        if '.' in key:
+            nested_keys = key.split('.')
+            nested_config = config
+            for nested_key in nested_keys[:-1]:
+                nested_config = nested_config.get(nested_key, {})
+            nested_config[nested_keys[-1]] = 'REDACTED'
+        else:
+            config[key] = 'REDACTED'
+
+    return config

freqtrade/configuration/config_setup.py

@@ -10,7 +10,8 @@ from .configuration import Configuration
 logger = logging.getLogger(__name__)
 
 
-def setup_utils_configuration(args: Dict[str, Any], method: RunMode) -> Dict[str, Any]:
+def setup_utils_configuration(
+        args: Dict[str, Any], method: RunMode, *, set_dry: bool = True) -> Dict[str, Any]:
     """
     Prepare the configuration for utils subcommands
     :param args: Cli args from Arguments()
@@ -21,7 +22,8 @@ def setup_utils_configuration(args: Dict[str, Any], method: RunMode) -> Dict[str
     config = configuration.get_config()
 
     # Ensure these modes are using Dry-run
-    config['dry_run'] = True
+    if set_dry:
+        config['dry_run'] = True
     validate_config_consistency(config, preliminary=True)
 
     return config

freqtrade/configuration/config_validation.py

@@ -9,7 +9,7 @@ from jsonschema.exceptions import ValidationError, best_match
 from freqtrade import constants
 from freqtrade.configuration.deprecated_settings import process_deprecated_setting
 from freqtrade.enums import RunMode, TradingMode
-from freqtrade.exceptions import OperationalException
+from freqtrade.exceptions import ConfigurationError
 
 
 logger = logging.getLogger(__name__)
@@ -73,7 +73,7 @@ def validate_config_consistency(conf: Dict[str, Any], *, preliminary: bool = Fal
     Should be ran after loading both configuration and strategy,
     since strategies can set certain configuration settings too.
     :param conf: Config in JSON format
-    :return: Returns None if everything is ok, otherwise throw an OperationalException
+    :return: Returns None if everything is ok, otherwise throw an ConfigurationError
     """
 
     # validating trailing stoploss
@@ -98,12 +98,12 @@ 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.
-    :raise: OperationalException if config validation failed
+    :raise: ConfigurationError if config validation failed
     """
     if (not conf.get('edge', {}).get('enabled')
         and conf.get('max_open_trades') == float('inf')
             and conf.get('stake_amount') == constants.UNLIMITED_STAKE_AMOUNT):
-        raise OperationalException("`max_open_trades` and `stake_amount` cannot both be unlimited.")
+        raise ConfigurationError("`max_open_trades` and `stake_amount` cannot both be unlimited.")
 
 
 def _validate_price_config(conf: Dict[str, Any]) -> None:
@@ -113,18 +113,18 @@ def _validate_price_config(conf: Dict[str, Any]) -> None:
     # TODO: The below could be an enforced setting when using market orders
     if (conf.get('order_types', {}).get('entry') == 'market'
             and conf.get('entry_pricing', {}).get('price_side') not in ('ask', 'other')):
-        raise OperationalException(
+        raise ConfigurationError(
             'Market entry orders require entry_pricing.price_side = "other".')
 
     if (conf.get('order_types', {}).get('exit') == 'market'
             and conf.get('exit_pricing', {}).get('price_side') not in ('bid', 'other')):
-        raise OperationalException('Market exit orders require exit_pricing.price_side = "other".')
+        raise ConfigurationError('Market exit orders require exit_pricing.price_side = "other".')
 
 
 def _validate_trailing_stoploss(conf: Dict[str, Any]) -> None:
 
     if conf.get('stoploss') == 0.0:
-        raise OperationalException(
+        raise ConfigurationError(
             'The config stoploss needs to be different from 0 to avoid problems with sell orders.'
         )
     # Skip if trailing stoploss is not activated
@@ -137,17 +137,17 @@ def _validate_trailing_stoploss(conf: Dict[str, Any]) -> None:
 
     if tsl_only_offset:
         if tsl_positive == 0.0:
-            raise OperationalException(
+            raise ConfigurationError(
                 'The config trailing_only_offset_is_reached needs '
                 'trailing_stop_positive_offset to be more than 0 in your config.')
     if tsl_positive > 0 and 0 < tsl_offset <= tsl_positive:
-        raise OperationalException(
+        raise ConfigurationError(
             'The config trailing_stop_positive_offset needs '
             'to be greater than trailing_stop_positive in your config.')
 
     # Fetch again without default
     if 'trailing_stop_positive' in conf and float(conf['trailing_stop_positive']) == 0.0:
-        raise OperationalException(
+        raise ConfigurationError(
             'The config trailing_stop_positive needs to be different from 0 '
             'to avoid problems with sell orders.'
         )
@@ -162,7 +162,7 @@ def _validate_edge(conf: Dict[str, Any]) -> None:
         return
 
     if not conf.get('use_exit_signal', True):
-        raise OperationalException(
+        raise ConfigurationError(
             "Edge requires `use_exit_signal` to be True, otherwise no sells will happen."
         )
 
@@ -178,7 +178,7 @@ def _validate_whitelist(conf: Dict[str, Any]) -> None:
     for pl in conf.get('pairlists', [{'method': 'StaticPairList'}]):
         if (isinstance(pl, dict) and pl.get('method') == 'StaticPairList'
                 and not conf.get('exchange', {}).get('pair_whitelist')):
-            raise OperationalException("StaticPairList requires pair_whitelist to be set.")
+            raise ConfigurationError("StaticPairList requires pair_whitelist to be set.")
 
 
 def _validate_protections(conf: Dict[str, Any]) -> None:
@@ -188,13 +188,13 @@ def _validate_protections(conf: Dict[str, Any]) -> None:
 
     for prot in conf.get('protections', []):
         if ('stop_duration' in prot and 'stop_duration_candles' in prot):
-            raise OperationalException(
+            raise ConfigurationError(
                 "Protections must specify either `stop_duration` or `stop_duration_candles`.\n"
                 f"Please fix the protection {prot.get('method')}"
             )
 
         if ('lookback_period' in prot and 'lookback_period_candles' in prot):
-            raise OperationalException(
+            raise ConfigurationError(
                 "Protections must specify either `lookback_period` or `lookback_period_candles`.\n"
                 f"Please fix the protection {prot.get('method')}"
             )
@@ -206,7 +206,7 @@ def _validate_ask_orderbook(conf: Dict[str, Any]) -> None:
     ob_max = ask_strategy.get('order_book_max')
     if ob_min is not None and ob_max is not None and ask_strategy.get('use_order_book'):
         if ob_min != ob_max:
-            raise OperationalException(
+            raise ConfigurationError(
                 "Using order_book_max != order_book_min in exit_pricing is no longer supported."
                 "Please pick one value and use `order_book_top` in the future."
             )
@@ -234,7 +234,7 @@ def _validate_time_in_force(conf: Dict[str, Any]) -> None:
     time_in_force = conf.get('order_time_in_force', {})
     if 'buy' in time_in_force or 'sell' in time_in_force:
         if conf.get('trading_mode', TradingMode.SPOT) != TradingMode.SPOT:
-            raise OperationalException(
+            raise ConfigurationError(
                 "Please migrate your time_in_force settings to use 'entry' and 'exit'.")
         else:
             logger.warning(
@@ -255,7 +255,7 @@ def _validate_order_types(conf: Dict[str, Any]) -> None:
                        'forcesell', 'emergencyexit', 'forceexit', 'forceentry']
     if any(x in order_types for x in old_order_types):
         if conf.get('trading_mode', TradingMode.SPOT) != TradingMode.SPOT:
-            raise OperationalException(
+            raise ConfigurationError(
                 "Please migrate your order_types settings to use the new wording.")
         else:
             logger.warning(
@@ -280,7 +280,7 @@ def _validate_unfilledtimeout(conf: Dict[str, Any]) -> None:
     unfilledtimeout = conf.get('unfilledtimeout', {})
     if any(x in unfilledtimeout for x in ['buy', 'sell']):
         if conf.get('trading_mode', TradingMode.SPOT) != TradingMode.SPOT:
-            raise OperationalException(
+            raise ConfigurationError(
                 "Please migrate your unfilledtimeout settings to use the new wording.")
         else:
 
@@ -300,7 +300,7 @@ def _validate_pricing_rules(conf: Dict[str, Any]) -> None:
 
     if conf.get('ask_strategy') or conf.get('bid_strategy'):
         if conf.get('trading_mode', TradingMode.SPOT) != TradingMode.SPOT:
-            raise OperationalException(
+            raise ConfigurationError(
                 "Please migrate your pricing settings to use the new wording.")
         else:
 
@@ -331,7 +331,7 @@ def _validate_freqai_hyperopt(conf: Dict[str, Any]) -> None:
     freqai_enabled = conf.get('freqai', {}).get('enabled', False)
     analyze_per_epoch = conf.get('analyze_per_epoch', False)
     if analyze_per_epoch and freqai_enabled:
-        raise OperationalException(
+        raise ConfigurationError(
             'Using analyze-per-epoch parameter is not supported with a FreqAI strategy.')
 
 
@@ -350,7 +350,7 @@ def _validate_freqai_include_timeframes(conf: Dict[str, Any], preliminary: bool)
             if tf_s < main_tf_s:
                 offending_lines.append(tf)
         if offending_lines:
-            raise OperationalException(
+            raise ConfigurationError(
                 f"Main timeframe of {main_tf} must be smaller or equal to FreqAI "
                 f"`include_timeframes`.Offending include-timeframes: {', '.join(offending_lines)}")
 
@@ -368,17 +368,17 @@ def _validate_freqai_backtest(conf: Dict[str, Any]) -> None:
         timerange = conf.get('timerange')
         freqai_backtest_live_models = conf.get('freqai_backtest_live_models', False)
         if freqai_backtest_live_models and freqai_enabled and timerange:
-            raise OperationalException(
+            raise ConfigurationError(
                 'Using timerange parameter is not supported with '
                 '--freqai-backtest-live-models parameter.')
 
         if freqai_backtest_live_models and not freqai_enabled:
-            raise OperationalException(
+            raise ConfigurationError(
                 'Using --freqai-backtest-live-models parameter is only '
                 'supported with a FreqAI strategy.')
 
         if freqai_enabled and not freqai_backtest_live_models and not timerange:
-            raise OperationalException(
+            raise ConfigurationError(
                 'Please pass --timerange if you intend to use FreqAI for backtesting.')
 
 
@@ -386,12 +386,12 @@ def _validate_consumers(conf: Dict[str, Any]) -> None:
     emc_conf = conf.get('external_message_consumer', {})
     if emc_conf.get('enabled', False):
         if len(emc_conf.get('producers', [])) < 1:
-            raise OperationalException("You must specify at least 1 Producer to connect to.")
+            raise ConfigurationError("You must specify at least 1 Producer to connect to.")
 
         producer_names = [p['name'] for p in emc_conf.get('producers', [])]
         duplicates = [item for item, count in Counter(producer_names).items() if count > 1]
         if duplicates:
-            raise OperationalException(
+            raise ConfigurationError(
                 f"Producer names must be unique. Duplicate: {', '.join(duplicates)}")
         if conf.get('process_only_new_candles', True):
             # Warning here or require it?

freqtrade/configuration/configuration.py

@@ -13,7 +13,7 @@ from freqtrade.configuration.directory_operations import create_datadir, create_
 from freqtrade.configuration.environment_vars import enironment_vars_to_dict
 from freqtrade.configuration.load_config import load_file, load_from_files
 from freqtrade.constants import Config
-from freqtrade.enums import NON_UTIL_MODES, TRADING_MODES, CandleType, RunMode, TradingMode
+from freqtrade.enums import NON_UTIL_MODES, TRADE_MODES, CandleType, RunMode, TradingMode
 from freqtrade.exceptions import OperationalException
 from freqtrade.loggers import setup_logging
 from freqtrade.misc import deep_merge_dicts, parse_db_uri_for_logging
@@ -127,7 +127,7 @@ class Configuration:
         setup_logging(config)
 
     def _process_trading_options(self, config: Config) -> None:
-        if config['runmode'] not in TRADING_MODES:
+        if config['runmode'] not in TRADE_MODES:
             return
 
         if config.get('dry_run', False):
@@ -200,6 +200,12 @@ class Configuration:
             config['exportfilename'] = (config['user_data_dir']
                                         / 'backtest_results')
 
+        if self.args.get('show_sensitive'):
+            logger.warning(
+                "Sensitive information will be shown in the upcoming output. "
+                "Please make sure to never share this output without redacting "
+                "the information yourself.")
+
     def _process_optimize_options(self, config: Config) -> None:
 
         # This will override the strategy configuration

freqtrade/configuration/deprecated_settings.py

@@ -6,7 +6,7 @@ import logging
 from typing import Optional
 
 from freqtrade.constants import Config
-from freqtrade.exceptions import OperationalException
+from freqtrade.exceptions import ConfigurationError, OperationalException
 
 
 logger = logging.getLogger(__name__)
@@ -41,7 +41,7 @@ def process_removed_setting(config: Config,
     section1_config = config.get(section1, {})
     if name1 in section1_config:
         section_2 = f"{section2}.{name2}" if section2 else f"{name2}"
-        raise OperationalException(
+        raise ConfigurationError(
             f"Setting `{section1}.{name1}` has been moved to `{section_2}. "
             f"Please delete it from your configuration and use the `{section_2}` "
             "setting instead."
@@ -122,7 +122,7 @@ def process_temporary_deprecated_settings(config: Config) -> None:
                             None, 'ignore_roi_if_entry_signal')
     if (config.get('edge', {}).get('enabled', False)
        and 'capital_available_percentage' in config.get('edge', {})):
-        raise OperationalException(
+        raise ConfigurationError(
             "DEPRECATED: "
             "Using 'edge.capital_available_percentage' has been deprecated in favor of "
             "'tradable_balance_ratio'. Please migrate your configuration to "
@@ -131,7 +131,7 @@ def process_temporary_deprecated_settings(config: Config) -> None:
         )
     if 'ticker_interval' in config:
 
-        raise OperationalException(
+        raise ConfigurationError(
             "DEPRECATED: 'ticker_interval' detected. "
             "Please use 'timeframe' instead of 'ticker_interval."
         )

freqtrade/configuration/load_config.py

@@ -11,7 +11,7 @@ from typing import Any, Dict, List, Optional
 import rapidjson
 
 from freqtrade.constants import MINIMAL_CONFIG, Config
-from freqtrade.exceptions import OperationalException
+from freqtrade.exceptions import ConfigurationError, OperationalException
 from freqtrade.misc import deep_merge_dicts
 
 
@@ -46,7 +46,7 @@ def load_file(path: Path) -> Dict[str, Any]:
         with path.open('r') as file:
             config = rapidjson.load(file, parse_mode=CONFIG_PARSE_MODE)
     except FileNotFoundError:
-        raise OperationalException(f'File "{path}" not found!')
+        raise OperationalException(f'File "{path}" not found!') from None
     return config
 
 
@@ -63,10 +63,10 @@ def load_config_file(path: str) -> Dict[str, Any]:
     except FileNotFoundError:
         raise OperationalException(
             f'Config file "{path}" not found!'
-            ' Please create a config file or check whether it exists.')
+            ' Please create a config file or check whether it exists.') from None
     except rapidjson.JSONDecodeError as e:
         err_range = log_config_error_range(path, str(e))
-        raise OperationalException(
+        raise ConfigurationError(
             f'{e}\n'
             f'Please verify the following segment of your configuration:\n{err_range}'
             if err_range else 'Please verify your configuration file for syntax errors.'
@@ -83,7 +83,7 @@ def load_from_files(
     """
     config: Config = {}
     if level > 5:
-        raise OperationalException("Config loop detected.")
+        raise ConfigurationError("Config loop detected.")
 
     if not files:
         return deepcopy(MINIMAL_CONFIG)

freqtrade/configuration/timerange.py

@@ -9,7 +9,7 @@ from typing import Optional
 from typing_extensions import Self
 
 from freqtrade.constants import DATETIME_PRINT_FORMAT
-from freqtrade.exceptions import OperationalException
+from freqtrade.exceptions import ConfigurationError
 
 
 logger = logging.getLogger(__name__)
@@ -156,7 +156,7 @@ class TimeRange:
                     else:
                         stop = int(stops)
                 if start > stop > 0:
-                    raise OperationalException(
+                    raise ConfigurationError(
                         f'Start date is after stop date for timerange "{text}"')
                 return cls(stype[0], stype[1], start, stop)
-        raise OperationalException(f'Incorrect syntax for timerange "{text}"')
+        raise ConfigurationError(f'Incorrect syntax for timerange "{text}"')

freqtrade/constants.py

@@ -33,9 +33,10 @@ HYPEROPT_LOSS_BUILTIN = ['ShortTradeDurHyperOptLoss', 'OnlyProfitHyperOptLoss',
                          'MaxDrawDownHyperOptLoss', 'MaxDrawDownRelativeHyperOptLoss',
                          'ProfitDrawDownHyperOptLoss']
 AVAILABLE_PAIRLISTS = ['StaticPairList', 'VolumePairList', 'ProducerPairList', 'RemotePairList',
-                       'AgeFilter', "FullTradesFilter", 'OffsetFilter', 'PerformanceFilter',
-                       'PrecisionFilter', 'PriceFilter', 'RangeStabilityFilter',
-                       'ShuffleFilter', 'SpreadFilter', 'VolatilityFilter']
+                       'MarketCapPairList', 'AgeFilter', "FullTradesFilter", 'OffsetFilter',
+                       'PerformanceFilter', 'PrecisionFilter', 'PriceFilter',
+                       'RangeStabilityFilter', 'ShuffleFilter', 'SpreadFilter',
+                       'VolatilityFilter']
 AVAILABLE_PROTECTIONS = ['CooldownPeriod',
                          'LowProfitPairs', 'MaxDrawdown', 'StoplossGuard']
 AVAILABLE_DATAHANDLERS = ['json', 'jsongz', 'hdf5', 'feather', 'parquet']

freqtrade/data/btanalysis.py

@@ -11,7 +11,7 @@ import numpy as np
 import pandas as pd
 
 from freqtrade.constants import LAST_BT_RESULT_FN, IntOrInf
-from freqtrade.exceptions import OperationalException
+from freqtrade.exceptions import ConfigurationError, OperationalException
 from freqtrade.misc import file_dump_json, json_load
 from freqtrade.optimize.backtest_caching import get_backtest_metadata_filename
 from freqtrade.persistence import LocalTrade, Trade, init_db
@@ -106,7 +106,7 @@ def get_latest_hyperopt_file(
         directory = Path(directory)
     if predef_filename:
         if Path(predef_filename).is_absolute():
-            raise OperationalException(
+            raise ConfigurationError(
                 "--hyperopt-filename expects only the filename, not an absolute path.")
         return directory / predef_filename
     return directory / get_latest_hyperopt_filename(directory)
@@ -238,6 +238,16 @@ def update_backtest_metadata(filename: Path, strategy: str, content: Dict[str, A
     file_dump_json(get_backtest_metadata_filename(filename), metadata)
 
 
+def get_backtest_market_change(filename: Path, include_ts: bool = True) -> pd.DataFrame:
+    """
+    Read backtest market change file.
+    """
+    df = pd.read_feather(filename)
+    if include_ts:
+        df.loc[:, '__date_ts'] = df.loc[:, 'date'].astype(np.int64) // 1000 // 1000
+    return df
+
+
 def find_existing_backtest_stats(dirname: Union[Path, str], run_ids: Dict[str, str],
                                  min_backtest_date: Optional[datetime] = None) -> Dict[str, Any]:
     """

freqtrade/data/converter/converter.py

@@ -200,7 +200,7 @@ def convert_ohlcv_format(
     :param convert_to: Target format
     :param erase: Erase source data (does not apply if source and target format are identical)
     """
-    from freqtrade.data.history.idatahandler import get_datahandler
+    from freqtrade.data.history import get_datahandler
     src = get_datahandler(config['datadir'], convert_from)
     trg = get_datahandler(config['datadir'], convert_to)
     timeframes = config.get('timeframes', [config.get('timeframe')])

freqtrade/data/converter/trade_converter.py

@@ -11,7 +11,7 @@ from pandas import DataFrame, to_datetime
 from freqtrade.configuration import TimeRange
 from freqtrade.constants import (DEFAULT_DATAFRAME_COLUMNS, DEFAULT_TRADES_COLUMNS, TRADES_DTYPES,
                                  Config, TradeList)
-from freqtrade.enums import CandleType
+from freqtrade.enums import CandleType, TradingMode
 from freqtrade.exceptions import OperationalException
 
 
@@ -88,25 +88,23 @@ def convert_trades_to_ohlcv(
     timeframes: List[str],
     datadir: Path,
     timerange: TimeRange,
-    erase: bool = False,
-    data_format_ohlcv: str = 'feather',
-    data_format_trades: str = 'feather',
-    candle_type: CandleType = CandleType.SPOT
+    erase: bool,
+    data_format_ohlcv: str,
+    data_format_trades: str,
+    candle_type: CandleType,
 ) -> None:
     """
     Convert stored trades data to ohlcv data
     """
-    from freqtrade.data.history.idatahandler import get_datahandler
+    from freqtrade.data.history import get_datahandler
     data_handler_trades = get_datahandler(datadir, data_format=data_format_trades)
     data_handler_ohlcv = get_datahandler(datadir, data_format=data_format_ohlcv)
-    if not pairs:
-        pairs = data_handler_trades.trades_get_pairs(datadir)
 
     logger.info(f"About to convert pairs: '{', '.join(pairs)}', "
                 f"intervals: '{', '.join(timeframes)}' to {datadir}")
-
+    trading_mode = TradingMode.FUTURES if candle_type != CandleType.SPOT else TradingMode.SPOT
     for pair in pairs:
-        trades = data_handler_trades.trades_load(pair)
+        trades = data_handler_trades.trades_load(pair, trading_mode)
         for timeframe in timeframes:
             if erase:
                 if data_handler_ohlcv.ohlcv_purge(pair, timeframe, candle_type=candle_type):
@@ -116,7 +114,7 @@ def convert_trades_to_ohlcv(
                 # Store ohlcv
                 data_handler_ohlcv.ohlcv_store(pair, timeframe, data=ohlcv, candle_type=candle_type)
             except ValueError:
-                logger.exception(f'Could not convert {pair} to OHLCV.')
+                logger.warning(f'Could not convert {pair} to OHLCV.')
 
 
 def convert_trades_format(config: Config, convert_from: str, convert_to: str, erase: bool):
@@ -137,18 +135,19 @@ def convert_trades_format(config: Config, convert_from: str, convert_to: str, er
         import_kraken_trades_from_csv(config, convert_to)
         return
 
-    from freqtrade.data.history.idatahandler import get_datahandler
+    from freqtrade.data.history import get_datahandler
     src = get_datahandler(config['datadir'], convert_from)
     trg = get_datahandler(config['datadir'], convert_to)
 
     if 'pairs' not in config:
         config['pairs'] = src.trades_get_pairs(config['datadir'])
     logger.info(f"Converting trades for {config['pairs']}")
-
+    trading_mode: TradingMode = config.get('trading_mode', TradingMode.SPOT)
     for pair in config['pairs']:
-        data = src.trades_load(pair=pair)
+        data = src.trades_load(pair, trading_mode)
         logger.info(f"Converting {len(data)} trades for {pair}")
-        trg.trades_store(pair, data)
+        trg.trades_store(pair, data, trading_mode)
+
         if erase and convert_from != convert_to:
             logger.info(f"Deleting source Trade data for {pair}.")
-            src.trades_purge(pair=pair)
+            src.trades_purge(pair, trading_mode)

freqtrade/data/converter/trade_converter_kraken.py

@@ -6,8 +6,10 @@ import pandas as pd
 from freqtrade.constants import DATETIME_PRINT_FORMAT, DEFAULT_TRADES_COLUMNS, Config
 from freqtrade.data.converter.trade_converter import (trades_convert_types,
                                                       trades_df_remove_duplicates)
-from freqtrade.data.history.idatahandler import get_datahandler
+from freqtrade.data.history import get_datahandler
+from freqtrade.enums import TradingMode
 from freqtrade.exceptions import OperationalException
+from freqtrade.plugins.pairlist.pairlist_helpers import expand_pairlist
 from freqtrade.resolvers import ExchangeResolver
 
 
@@ -38,12 +40,22 @@ def import_kraken_trades_from_csv(config: Config, convert_to: str):
     }
     logger.info(f"Found csv files for {', '.join(data_symbols)}.")
 
+    if pairs_raw := config.get('pairs'):
+        pairs = expand_pairlist(pairs_raw, [m[0] for m in markets])
+        markets = {m for m in markets if m[0] in pairs}
+        if not markets:
+            logger.info(f"No data found for pairs {', '.join(pairs_raw)}.")
+            return
+    logger.info(f"Converting pairs: {', '.join(m[0] for m in markets)}.")
+
     for pair, name in markets:
+        logger.debug(f"Converting pair {pair}, files */{name}.csv")
         dfs = []
         # Load and combine all csv files for this pair
         for f in tradesdir.rglob(f"{name}.csv"):
             df = pd.read_csv(f, names=KRAKEN_CSV_TRADE_COLUMNS)
-            dfs.append(df)
+            if not df.empty:
+                dfs.append(df)
 
         # Load existing trades data
         if not dfs:
@@ -52,19 +64,20 @@ def import_kraken_trades_from_csv(config: Config, convert_to: str):
             continue
 
         trades = pd.concat(dfs, ignore_index=True)
+        del dfs
 
         trades.loc[:, 'timestamp'] = trades['timestamp'] * 1e3
         trades.loc[:, 'cost'] = trades['price'] * trades['amount']
         for col in DEFAULT_TRADES_COLUMNS:
             if col not in trades.columns:
-                trades[col] = ''
-
+                trades.loc[:, col] = ''
         trades = trades[DEFAULT_TRADES_COLUMNS]
         trades = trades_convert_types(trades)
 
         trades_df = trades_df_remove_duplicates(trades)
+        del trades
         logger.info(f"{pair}: {len(trades_df)} trades, from "
                     f"{trades_df['date'].min():{DATETIME_PRINT_FORMAT}} to "
                     f"{trades_df['date'].max():{DATETIME_PRINT_FORMAT}}")
 
-        data_handler.trades_store(pair, trades_df)
+        data_handler.trades_store(pair, trades_df, TradingMode.SPOT)

freqtrade/data/dataprovider.py

@@ -523,7 +523,7 @@ class DataProvider:
         Send custom RPC Notifications from your bot.
         Will not send any bot in modes other than Dry-run or Live.
         :param message: Message to be sent. Must be below 4096.
-        :param always_send: If False, will send the message only once per candle, and surpress
+        :param always_send: If False, will send the message only once per candle, and suppress
                             identical messages.
                             Careful as this can end up spaming your chat.
                             Defaults to False

freqtrade/data/history/__init__.py

@@ -6,7 +6,7 @@ Includes:
 * download data from exchange and store to disk
 """
 # flake8: noqa: F401
+from .datahandlers import get_datahandler
 from .history_utils import (convert_trades_to_ohlcv, download_data_main, get_timerange, load_data,
                             load_pair_history, refresh_backtest_ohlcv_data,
                             refresh_backtest_trades_data, refresh_data, validate_backtest_data)
-from .idatahandler import get_datahandler

freqtrade/data/history/datahandlers/__init__.py

@@ -0,0 +1,2 @@
+# flake8: noqa: F401
+from .idatahandler import IDataHandler, get_datahandler

freqtrade/data/history/datahandlers/featherdatahandler.py

@@ -5,7 +5,7 @@ from pandas import DataFrame, read_feather, to_datetime
 
 from freqtrade.configuration import TimeRange
 from freqtrade.constants import DEFAULT_DATAFRAME_COLUMNS, DEFAULT_TRADES_COLUMNS
-from freqtrade.enums import CandleType
+from freqtrade.enums import CandleType, TradingMode
 
 from .idatahandler import IDataHandler
 
@@ -82,14 +82,15 @@ class FeatherDataHandler(IDataHandler):
         """
         raise NotImplementedError()
 
-    def _trades_store(self, pair: str, data: DataFrame) -> None:
+    def _trades_store(self, pair: str, data: DataFrame, trading_mode: TradingMode) -> None:
         """
         Store trades data (list of Dicts) to file
         :param pair: Pair - used for filename
         :param data: Dataframe containing trades
                      column sequence as in DEFAULT_TRADES_COLUMNS
+        :param trading_mode: Trading mode to use (used to determine the filename)
         """
-        filename = self._pair_trades_filename(self._datadir, pair)
+        filename = self._pair_trades_filename(self._datadir, pair, trading_mode)
         self.create_dir_if_needed(filename)
         data.reset_index(drop=True).to_feather(filename, compression_level=9, compression='lz4')
 
@@ -102,15 +103,18 @@ class FeatherDataHandler(IDataHandler):
         """
         raise NotImplementedError()
 
-    def _trades_load(self, pair: str, timerange: Optional[TimeRange] = None) -> DataFrame:
+    def _trades_load(
+            self, pair: str, trading_mode: TradingMode, timerange: Optional[TimeRange] = None
+    ) -> DataFrame:
         """
         Load a pair from file, either .json.gz or .json
         # TODO: respect timerange ...
         :param pair: Load trades for this pair
+        :param trading_mode: Trading mode to use (used to determine the filename)
         :param timerange: Timerange to load trades for - currently not implemented
         :return: Dataframe containing trades
         """
-        filename = self._pair_trades_filename(self._datadir, pair)
+        filename = self._pair_trades_filename(self._datadir, pair, trading_mode)
         if not filename.exists():
             return DataFrame(columns=DEFAULT_TRADES_COLUMNS)
 

freqtrade/data/history/datahandlers/hdf5datahandler.py

@@ -6,7 +6,7 @@ import pandas as pd
 
 from freqtrade.configuration import TimeRange
 from freqtrade.constants import DEFAULT_DATAFRAME_COLUMNS, DEFAULT_TRADES_COLUMNS
-from freqtrade.enums import CandleType
+from freqtrade.enums import CandleType, TradingMode
 
 from .idatahandler import IDataHandler
 
@@ -35,7 +35,7 @@ class HDF5DataHandler(IDataHandler):
         self.create_dir_if_needed(filename)
 
         _data.loc[:, self._columns].to_hdf(
-            filename, key, mode='a', complevel=9, complib='blosc',
+            filename, key=key, mode='a', complevel=9, complib='blosc',
             format='table', data_columns=['date']
         )
 
@@ -100,17 +100,18 @@ class HDF5DataHandler(IDataHandler):
         """
         raise NotImplementedError()
 
-    def _trades_store(self, pair: str, data: pd.DataFrame) -> None:
+    def _trades_store(self, pair: str, data: pd.DataFrame, trading_mode: TradingMode) -> None:
         """
         Store trades data (list of Dicts) to file
         :param pair: Pair - used for filename
         :param data: Dataframe containing trades
                      column sequence as in DEFAULT_TRADES_COLUMNS
+        :param trading_mode: Trading mode to use (used to determine the filename)
         """
         key = self._pair_trades_key(pair)
 
         data.to_hdf(
-            self._pair_trades_filename(self._datadir, pair), key,
+            self._pair_trades_filename(self._datadir, pair, trading_mode), key=key,
             mode='a', complevel=9, complib='blosc',
             format='table', data_columns=['timestamp']
         )
@@ -124,15 +125,18 @@ class HDF5DataHandler(IDataHandler):
         """
         raise NotImplementedError()
 
-    def _trades_load(self, pair: str, timerange: Optional[TimeRange] = None) -> pd.DataFrame:
+    def _trades_load(
+        self, pair: str, trading_mode: TradingMode, timerange: Optional[TimeRange] = None
+    ) -> pd.DataFrame:
         """
         Load a pair from h5 file.
         :param pair: Load trades for this pair
+        :param trading_mode: Trading mode to use (used to determine the filename)
         :param timerange: Timerange to load trades for - currently not implemented
         :return: Dataframe containing trades
         """
         key = self._pair_trades_key(pair)
-        filename = self._pair_trades_filename(self._datadir, pair)
+        filename = self._pair_trades_filename(self._datadir, pair, trading_mode)
 
         if not filename.exists():
             return pd.DataFrame(columns=DEFAULT_TRADES_COLUMNS)

freqtrade/data/history/datahandlers/idatahandler.py

@@ -172,12 +172,13 @@ class IDataHandler(ABC):
         return [cls.rebuild_pair_from_filename(match[0]) for match in _tmp if match]
 
     @abstractmethod
-    def _trades_store(self, pair: str, data: DataFrame) -> None:
+    def _trades_store(self, pair: str, data: DataFrame, trading_mode: TradingMode) -> None:
         """
         Store trades data (list of Dicts) to file
         :param pair: Pair - used for filename
         :param data: Dataframe containing trades
                      column sequence as in DEFAULT_TRADES_COLUMNS
+        :param trading_mode: Trading mode to use (used to determine the filename)
         """
 
     @abstractmethod
@@ -190,45 +191,55 @@ class IDataHandler(ABC):
         """
 
     @abstractmethod
-    def _trades_load(self, pair: str, timerange: Optional[TimeRange] = None) -> DataFrame:
+    def _trades_load(
+        self, pair: str, trading_mode: TradingMode, timerange: Optional[TimeRange] = None
+    ) -> DataFrame:
         """
         Load a pair from file, either .json.gz or .json
         :param pair: Load trades for this pair
+        :param trading_mode: Trading mode to use (used to determine the filename)
         :param timerange: Timerange to load trades for - currently not implemented
         :return: Dataframe containing trades
         """
 
-    def trades_store(self, pair: str, data: DataFrame) -> None:
+    def trades_store(self, pair: str, data: DataFrame, trading_mode: TradingMode) -> None:
         """
         Store trades data (list of Dicts) to file
         :param pair: Pair - used for filename
         :param data: Dataframe containing trades
                      column sequence as in DEFAULT_TRADES_COLUMNS
+        :param trading_mode: Trading mode to use (used to determine the filename)
         """
         # Filter on expected columns (will remove the actual date column).
-        self._trades_store(pair, data[DEFAULT_TRADES_COLUMNS])
+        self._trades_store(pair, data[DEFAULT_TRADES_COLUMNS], trading_mode)
 
-    def trades_purge(self, pair: str) -> bool:
+    def trades_purge(self, pair: str, trading_mode: TradingMode) -> bool:
         """
         Remove data for this pair
         :param pair: Delete data for this pair.
+        :param trading_mode: Trading mode to use (used to determine the filename)
         :return: True when deleted, false if file did not exist.
         """
-        filename = self._pair_trades_filename(self._datadir, pair)
+        filename = self._pair_trades_filename(self._datadir, pair, trading_mode)
         if filename.exists():
             filename.unlink()
             return True
         return False
 
-    def trades_load(self, pair: str, timerange: Optional[TimeRange] = None) -> DataFrame:
+    def trades_load(
+            self, pair: str, trading_mode: TradingMode, timerange: Optional[TimeRange] = None
+    ) -> DataFrame:
         """
         Load a pair from file, either .json.gz or .json
         Removes duplicates in the process.
         :param pair: Load trades for this pair
+        :param trading_mode: Trading mode to use (used to determine the filename)
         :param timerange: Timerange to load trades for - currently not implemented
         :return: List of trades
         """
-        trades = trades_df_remove_duplicates(self._trades_load(pair, timerange=timerange))
+        trades = trades_df_remove_duplicates(
+            self._trades_load(pair, trading_mode, timerange=timerange)
+        )
 
         trades = trades_convert_types(trades)
         return trades
@@ -264,8 +275,12 @@ class IDataHandler(ABC):
         return filename
 
     @classmethod
-    def _pair_trades_filename(cls, datadir: Path, pair: str) -> Path:
+    def _pair_trades_filename(cls, datadir: Path, pair: str, trading_mode: TradingMode) -> Path:
         pair_s = misc.pair_to_filename(pair)
+        if trading_mode == TradingMode.FUTURES:
+            # Futures pair ...
+            datadir = datadir.joinpath('futures')
+
         filename = datadir.joinpath(f'{pair_s}-trades.{cls._get_file_extension()}')
         return filename
 
@@ -287,8 +302,8 @@ class IDataHandler(ABC):
         Rebuild pair name from filename
         Assumes a asset name of max. 7 length to also support BTC-PERP and BTC-PERP:USD names.
         """
-        res = re.sub(r'^(([A-Za-z\d]{1,10})|^([A-Za-z\-]{1,6}))(_)', r'\g<1>/', pair, 1)
-        res = re.sub('_', ':', res, 1)
+        res = re.sub(r'^(([A-Za-z\d]{1,10})|^([A-Za-z\-]{1,6}))(_)', r'\g<1>/', pair, count=1)
+        res = re.sub('_', ':', res, count=1)
         return res
 
     def ohlcv_load(self, pair, timeframe: str,

freqtrade/data/history/datahandlers/jsondatahandler.py

@@ -8,7 +8,7 @@ from freqtrade import misc
 from freqtrade.configuration import TimeRange
 from freqtrade.constants import DEFAULT_DATAFRAME_COLUMNS, DEFAULT_TRADES_COLUMNS
 from freqtrade.data.converter import trades_dict_to_list, trades_list_to_df
-from freqtrade.enums import CandleType
+from freqtrade.enums import CandleType, TradingMode
 
 from .idatahandler import IDataHandler
 
@@ -37,7 +37,7 @@ class JsonDataHandler(IDataHandler):
         self.create_dir_if_needed(filename)
         _data = data.copy()
         # Convert date to int
-        _data['date'] = _data['date'].view(np.int64) // 1000 // 1000
+        _data['date'] = _data['date'].astype(np.int64) // 1000 // 1000
 
         # Reset index, select only appropriate columns and save as json
         _data.reset_index(drop=True).loc[:, self._columns].to_json(
@@ -94,14 +94,15 @@ class JsonDataHandler(IDataHandler):
         """
         raise NotImplementedError()
 
-    def _trades_store(self, pair: str, data: DataFrame) -> None:
+    def _trades_store(self, pair: str, data: DataFrame, trading_mode: TradingMode) -> None:
         """
         Store trades data (list of Dicts) to file
         :param pair: Pair - used for filename
         :param data: Dataframe containing trades
                      column sequence as in DEFAULT_TRADES_COLUMNS
+        :param trading_mode: Trading mode to use (used to determine the filename)
         """
-        filename = self._pair_trades_filename(self._datadir, pair)
+        filename = self._pair_trades_filename(self._datadir, pair, trading_mode)
         trades = data.values.tolist()
         misc.file_dump_json(filename, trades, is_zip=self._use_zip)
 
@@ -114,15 +115,18 @@ class JsonDataHandler(IDataHandler):
         """
         raise NotImplementedError()
 
-    def _trades_load(self, pair: str, timerange: Optional[TimeRange] = None) -> DataFrame:
+    def _trades_load(
+        self, pair: str, trading_mode: TradingMode, timerange: Optional[TimeRange] = None
+    ) -> DataFrame:
         """
         Load a pair from file, either .json.gz or .json
         # TODO: respect timerange ...
         :param pair: Load trades for this pair
+        :param trading_mode: Trading mode to use (used to determine the filename)
         :param timerange: Timerange to load trades for - currently not implemented
         :return: Dataframe containing trades
         """
-        filename = self._pair_trades_filename(self._datadir, pair)
+        filename = self._pair_trades_filename(self._datadir, pair, trading_mode)
         tradesdata = misc.file_load_json(filename)
 
         if not tradesdata:

freqtrade/data/history/datahandlers/parquetdatahandler.py

@@ -4,8 +4,8 @@ from typing import Optional
 from pandas import DataFrame, read_parquet, to_datetime
 
 from freqtrade.configuration import TimeRange
-from freqtrade.constants import DEFAULT_DATAFRAME_COLUMNS, DEFAULT_TRADES_COLUMNS, TradeList
-from freqtrade.enums import CandleType
+from freqtrade.constants import DEFAULT_DATAFRAME_COLUMNS, DEFAULT_TRADES_COLUMNS
+from freqtrade.enums import CandleType, TradingMode
 
 from .idatahandler import IDataHandler
 
@@ -81,14 +81,15 @@ class ParquetDataHandler(IDataHandler):
         """
         raise NotImplementedError()
 
-    def _trades_store(self, pair: str, data: DataFrame) -> None:
+    def _trades_store(self, pair: str, data: DataFrame, trading_mode: TradingMode) -> None:
         """
         Store trades data (list of Dicts) to file
         :param pair: Pair - used for filename
         :param data: Dataframe containing trades
                      column sequence as in DEFAULT_TRADES_COLUMNS
+        :param trading_mode: Trading mode to use (used to determine the filename)
         """
-        filename = self._pair_trades_filename(self._datadir, pair)
+        filename = self._pair_trades_filename(self._datadir, pair, trading_mode)
         self.create_dir_if_needed(filename)
         data.reset_index(drop=True).to_parquet(filename)
 
@@ -101,15 +102,18 @@ class ParquetDataHandler(IDataHandler):
         """
         raise NotImplementedError()
 
-    def _trades_load(self, pair: str, timerange: Optional[TimeRange] = None) -> TradeList:
+    def _trades_load(
+        self, pair: str, trading_mode: TradingMode, timerange: Optional[TimeRange] = None
+    ) -> DataFrame:
         """
         Load a pair from file, either .json.gz or .json
         # TODO: respect timerange ...
         :param pair: Load trades for this pair
+        :param trading_mode: Trading mode to use (used to determine the filename)
         :param timerange: Timerange to load trades for - currently not implemented
         :return: List of trades
         """
-        filename = self._pair_trades_filename(self._datadir, pair)
+        filename = self._pair_trades_filename(self._datadir, pair, trading_mode)
         if not filename.exists():
             return DataFrame(columns=DEFAULT_TRADES_COLUMNS)
 

freqtrade/data/history/history_utils.py

@@ -12,8 +12,8 @@ from freqtrade.constants import (DATETIME_PRINT_FORMAT, DEFAULT_DATAFRAME_COLUMN
 from freqtrade.data.converter import (clean_ohlcv_dataframe, convert_trades_to_ohlcv,
                                       ohlcv_to_dataframe, trades_df_remove_duplicates,
                                       trades_list_to_df)
-from freqtrade.data.history.idatahandler import IDataHandler, get_datahandler
-from freqtrade.enums import CandleType
+from freqtrade.data.history.datahandlers import IDataHandler, get_datahandler
+from freqtrade.enums import CandleType, TradingMode
 from freqtrade.exceptions import OperationalException
 from freqtrade.exchange import Exchange
 from freqtrade.plugins.pairlist.pairlist_helpers import dynamic_expand_pairlist
@@ -333,7 +333,8 @@ def _download_trades_history(exchange: Exchange,
                              pair: str, *,
                              new_pairs_days: int = 30,
                              timerange: Optional[TimeRange] = None,
-                             data_handler: IDataHandler
+                             data_handler: IDataHandler,
+                             trading_mode: TradingMode,
                              ) -> bool:
     """
     Download trade history from the exchange.
@@ -349,7 +350,7 @@ def _download_trades_history(exchange: Exchange,
             if timerange.stoptype == 'date':
                 until = timerange.stopts * 1000
 
-        trades = data_handler.trades_load(pair)
+        trades = data_handler.trades_load(pair, trading_mode)
 
         # TradesList columns are defined in constants.DEFAULT_TRADES_COLUMNS
         # DEFAULT_TRADES_COLUMNS: 0 -> timestamp
@@ -388,7 +389,7 @@ def _download_trades_history(exchange: Exchange,
         trades = concat([trades, new_trades_df], axis=0)
         # Remove duplicates to make sure we're not storing data we don't need
         trades = trades_df_remove_duplicates(trades)
-        data_handler.trades_store(pair, data=trades)
+        data_handler.trades_store(pair, trades, trading_mode)
 
         logger.debug("New Start: %s", 'None' if trades.empty else
                      f"{trades.iloc[0]['date']:{DATETIME_PRINT_FORMAT}}")
@@ -405,8 +406,10 @@ def _download_trades_history(exchange: Exchange,
 
 
 def refresh_backtest_trades_data(exchange: Exchange, pairs: List[str], datadir: Path,
-                                 timerange: TimeRange, new_pairs_days: int = 30,
-                                 erase: bool = False, data_format: str = 'feather') -> List[str]:
+                                 timerange: TimeRange, trading_mode: TradingMode,
+                                 new_pairs_days: int = 30,
+                                 erase: bool = False, data_format: str = 'feather',
+                                 ) -> List[str]:
     """
     Refresh stored trades data for backtesting and hyperopt operations.
     Used by freqtrade download-data subcommand.
@@ -421,7 +424,7 @@ def refresh_backtest_trades_data(exchange: Exchange, pairs: List[str], datadir:
             continue
 
         if erase:
-            if data_handler.trades_purge(pair):
+            if data_handler.trades_purge(pair, trading_mode):
                 logger.info(f'Deleting existing data for pair {pair}.')
 
         logger.info(f'Downloading trades for pair {pair}.')
@@ -429,7 +432,8 @@ def refresh_backtest_trades_data(exchange: Exchange, pairs: List[str], datadir:
                                  pair=pair,
                                  new_pairs_days=new_pairs_days,
                                  timerange=timerange,
-                                 data_handler=data_handler)
+                                 data_handler=data_handler,
+                                 trading_mode=trading_mode)
     return pairs_not_available
 
 
@@ -516,12 +520,12 @@ def download_data_main(config: Config) -> None:
     # Start downloading
     try:
         if config.get('download_trades'):
-            if config.get('trading_mode') == 'futures':
-                raise OperationalException("Trade download not supported for futures.")
             pairs_not_available = refresh_backtest_trades_data(
                 exchange, pairs=expanded_pairs, datadir=config['datadir'],
                 timerange=timerange, new_pairs_days=config['new_pairs_days'],
-                erase=bool(config.get('erase')), data_format=config['dataformat_trades'])
+                erase=bool(config.get('erase')), data_format=config['dataformat_trades'],
+                trading_mode=config.get('trading_mode', TradingMode.SPOT),
+                )
 
             # Convert downloaded trade data to different timeframes
             convert_trades_to_ohlcv(
@@ -529,6 +533,7 @@ def download_data_main(config: Config) -> None:
                 datadir=config['datadir'], timerange=timerange, erase=bool(config.get('erase')),
                 data_format_ohlcv=config['dataformat_ohlcv'],
                 data_format_trades=config['dataformat_trades'],
+                candle_type=config.get('candle_type_def', CandleType.SPOT),
             )
         else:
             if not exchange.get_option('ohlcv_has_history', True):

freqtrade/data/metrics.py

@@ -30,8 +30,25 @@ def calculate_market_change(data: Dict[str, pd.DataFrame], column: str = "close"
     return float(np.mean(tmp_means))
 
 
-def combine_dataframes_with_mean(data: Dict[str, pd.DataFrame],
-                                 column: str = "close") -> pd.DataFrame:
+def combine_dataframes_by_column(
+        data: Dict[str, pd.DataFrame], column: str = "close") -> pd.DataFrame:
+    """
+    Combine multiple dataframes "column"
+    :param data: Dict of Dataframes, dict key should be pair.
+    :param column: Column in the original dataframes to use
+    :return: DataFrame with the column renamed to the dict key.
+    :raise: ValueError if no data is provided.
+    """
+    if not data:
+        raise ValueError("No data provided.")
+    df_comb = pd.concat([data[pair].set_index('date').rename(
+        {column: pair}, axis=1)[pair] for pair in data], axis=1)
+    return df_comb
+
+
+def combined_dataframes_with_rel_mean(
+        data: Dict[str, pd.DataFrame], fromdt: datetime, todt: datetime,
+        column: str = "close") -> pd.DataFrame:
     """
     Combine multiple dataframes "column"
     :param data: Dict of Dataframes, dict key should be pair.
@@ -40,8 +57,26 @@ def combine_dataframes_with_mean(data: Dict[str, pd.DataFrame],
         named mean, containing the mean of all pairs.
     :raise: ValueError if no data is provided.
     """
-    df_comb = pd.concat([data[pair].set_index('date').rename(
-        {column: pair}, axis=1)[pair] for pair in data], axis=1)
+    df_comb = combine_dataframes_by_column(data, column)
+    # Trim dataframes to the given timeframe
+    df_comb = df_comb.iloc[(df_comb.index >= fromdt) & (df_comb.index < todt)]
+    df_comb['count'] = df_comb.count(axis=1)
+    df_comb['mean'] = df_comb.mean(axis=1)
+    df_comb['rel_mean'] = df_comb['mean'].pct_change().fillna(0).cumsum()
+    return df_comb[['mean', 'rel_mean', 'count']]
+
+
+def combine_dataframes_with_mean(
+        data: Dict[str, pd.DataFrame], column: str = "close") -> pd.DataFrame:
+    """
+    Combine multiple dataframes "column"
+    :param data: Dict of Dataframes, dict key should be pair.
+    :param column: Column in the original dataframes to use
+    :return: DataFrame with the column renamed to the dict key, and a column
+        named mean, containing the mean of all pairs.
+    :raise: ValueError if no data is provided.
+    """
+    df_comb = combine_dataframes_by_column(data, column)
 
     df_comb['mean'] = df_comb.mean(axis=1)
 
@@ -143,8 +178,10 @@ def calculate_max_drawdown(trades: pd.DataFrame, *, date_col: str = 'close_date'
         starting_balance=starting_balance
     )
 
-    idxmin = max_drawdown_df['drawdown_relative'].idxmax() if relative \
-        else max_drawdown_df['drawdown'].idxmin()
+    idxmin = (
+        max_drawdown_df['drawdown_relative'].idxmax()
+        if relative else max_drawdown_df['drawdown'].idxmin()
+    )
     if idxmin == 0:
         raise ValueError("No losing trade, therefore no drawdown.")
     high_date = profit_results.loc[max_drawdown_df.iloc[:idxmin]['high_value'].idxmax(), date_col]
@@ -191,6 +228,9 @@ def calculate_cagr(days_passed: int, starting_balance: float, final_balance: flo
     :param final_balance: Final balance to calculate CAGR against
     :return: CAGR
     """
+    if final_balance < 0:
+        # With leveraged trades, final_balance can become negative.
+        return 0
     return (final_balance / starting_balance) ** (1 / (days_passed / 365)) - 1
 
 

freqtrade/enums/__init__.py

@@ -9,7 +9,7 @@ from freqtrade.enums.marketstatetype import MarketDirection
 from freqtrade.enums.ordertypevalue import OrderTypeValues
 from freqtrade.enums.pricetype import PriceType
 from freqtrade.enums.rpcmessagetype import NO_ECHO_MESSAGES, RPCMessageType, RPCRequestType
-from freqtrade.enums.runmode import NON_UTIL_MODES, OPTIMIZE_MODES, TRADING_MODES, RunMode
+from freqtrade.enums.runmode import NON_UTIL_MODES, OPTIMIZE_MODES, TRADE_MODES, RunMode
 from freqtrade.enums.signaltype import SignalDirection, SignalTagType, SignalType
 from freqtrade.enums.state import State
 from freqtrade.enums.tradingmode import TradingMode

freqtrade/enums/runmode.py

@@ -18,6 +18,6 @@ class RunMode(Enum):
     OTHER = "other"
 
 
-TRADING_MODES = [RunMode.LIVE, RunMode.DRY_RUN]
+TRADE_MODES = [RunMode.LIVE, RunMode.DRY_RUN]
 OPTIMIZE_MODES = [RunMode.BACKTEST, RunMode.EDGE, RunMode.HYPEROPT]
-NON_UTIL_MODES = TRADING_MODES + OPTIMIZE_MODES
+NON_UTIL_MODES = TRADE_MODES + OPTIMIZE_MODES

freqtrade/exceptions.py

@@ -12,6 +12,12 @@ class OperationalException(FreqtradeException):
     """
 
 
+class ConfigurationError(OperationalException):
+    """
+    Configuration error. Usually caused by invalid configuration.
+    """
+
+
 class DependencyException(FreqtradeException):
     """
     Indicates that an assumed dependency is not met.

freqtrade/exchange/__init__.py

@@ -4,6 +4,7 @@ from freqtrade.exchange.common import remove_exchange_credentials, MAP_EXCHANGE_
 from freqtrade.exchange.exchange import Exchange
 # isort: on
 from freqtrade.exchange.binance import Binance
+from freqtrade.exchange.bingx import Bingx
 from freqtrade.exchange.bitmart import Bitmart
 from freqtrade.exchange.bitpanda import Bitpanda
 from freqtrade.exchange.bitvavo import Bitvavo
@@ -15,13 +16,16 @@ from freqtrade.exchange.exchange_utils import (ROUND_DOWN, ROUND_UP, amount_to_c
                                                contracts_to_amount, date_minus_candles,
                                                is_exchange_known_ccxt, list_available_exchanges,
                                                market_is_active, price_to_precision,
-                                               timeframe_to_minutes, timeframe_to_msecs,
-                                               timeframe_to_next_date, timeframe_to_prev_date,
-                                               timeframe_to_resample_freq, timeframe_to_seconds,
                                                validate_exchange)
+from freqtrade.exchange.exchange_utils_timeframe import (timeframe_to_minutes, timeframe_to_msecs,
+                                                         timeframe_to_next_date,
+                                                         timeframe_to_prev_date,
+                                                         timeframe_to_resample_freq,
+                                                         timeframe_to_seconds)
 from freqtrade.exchange.gate import Gate
 from freqtrade.exchange.hitbtc import Hitbtc
 from freqtrade.exchange.htx import Htx
+from freqtrade.exchange.idex import Idex
 from freqtrade.exchange.kraken import Kraken
 from freqtrade.exchange.kucoin import Kucoin
 from freqtrade.exchange.okx import Okx

freqtrade/exchange/binance.py

@@ -84,7 +84,7 @@ class Binance(Exchange):
                     raise OperationalException(msg)
         except ccxt.DDoSProtection as e:
             raise DDosProtection(e) from e
-        except (ccxt.NetworkError, ccxt.ExchangeError) as e:
+        except (ccxt.OperationFailed, ccxt.ExchangeError) as e:
             raise TemporaryError(
                 f'Error in additional_exchange_init due to {e.__class__.__name__}. Message: {e}'
                 ) from e
@@ -210,7 +210,7 @@ class Binance(Exchange):
                     return self._api.fetch_leverage_tiers()
                 except ccxt.DDoSProtection as e:
                     raise DDosProtection(e) from e
-                except (ccxt.NetworkError, ccxt.ExchangeError) as e:
+                except (ccxt.OperationFailed, ccxt.ExchangeError) as e:
                     raise TemporaryError(f'Could not fetch leverage amounts due to'
                                          f'{e.__class__.__name__}. Message: {e}') from e
                 except ccxt.BaseError as e:

freqtrade/exchange/bingx.py

@@ -0,0 +1,19 @@
+""" Bingx exchange subclass """
+import logging
+from typing import Dict
+
+from freqtrade.exchange import Exchange
+
+
+logger = logging.getLogger(__name__)
+
+
+class Bingx(Exchange):
+    """
+    Bingx exchange class. Contains adjustments needed for Freqtrade to work
+    with this exchange.
+    """
+
+    _ft_has: Dict = {
+        "ohlcv_candle_limit": 1000,
+    }

freqtrade/exchange/bybit.py

@@ -25,6 +25,7 @@ class Bybit(Exchange):
     officially supported by the Freqtrade development team. So some features
     may still not work as expected.
     """
+    unified_account = False
 
     _ft_has: Dict = {
         "ohlcv_candle_limit": 1000,
@@ -82,12 +83,23 @@ class Bybit(Exchange):
         Must be overridden in child methods if required.
         """
         try:
-            if self.trading_mode == TradingMode.FUTURES and not self._config['dry_run']:
-                position_mode = self._api.set_position_mode(False)
-                self._log_exchange_response('set_position_mode', position_mode)
+            if not self._config['dry_run']:
+                if self.trading_mode == TradingMode.FUTURES:
+                    position_mode = self._api.set_position_mode(False)
+                    self._log_exchange_response('set_position_mode', position_mode)
+                is_unified = self._api.is_unified_enabled()
+                # Returns a tuple of bools, first for margin, second for Account
+                if is_unified and len(is_unified) > 1 and is_unified[1]:
+                    self.unified_account = True
+                    logger.info("Bybit: Unified account.")
+                    raise OperationalException("Bybit: Unified account is not supported. "
+                                               "Please use a standard (sub)account.")
+                else:
+                    self.unified_account = False
+                    logger.info("Bybit: Standard account.")
         except ccxt.DDoSProtection as e:
             raise DDosProtection(e) from e
-        except (ccxt.NetworkError, ccxt.ExchangeError) as e:
+        except (ccxt.OperationFailed, ccxt.ExchangeError) as e:
             raise TemporaryError(
                 f'Error in additional_exchange_init due to {e.__class__.__name__}. Message: {e}'
                 ) from e
@@ -227,7 +239,7 @@ class Bybit(Exchange):
 
         return orders
 
-    def fetch_order(self, order_id: str, pair: str, params: Dict = {}) -> Dict:
+    def fetch_order(self, order_id: str, pair: str, params: Optional[Dict] = None) -> Dict:
         order = super().fetch_order(order_id, pair, params)
         if (
             order.get('status') == 'canceled'

freqtrade/exchange/check_exchange.py

@@ -56,7 +56,7 @@ def check_exchange(config: Config, check_for_bad: bool = True) -> bool:
         logger.info(f'Exchange "{exchange}" is officially supported '
                     f'by the Freqtrade development team.')
     else:
-        logger.warning(f'Exchange "{exchange}" is known to the the ccxt library, '
+        logger.warning(f'Exchange "{exchange}" is known to the ccxt library, '
                        f'available for the bot, but not officially supported '
                        f'by the Freqtrade development team. '
                        f'It may work flawlessly (please report back) or have serious issues. '

freqtrade/exchange/common.py

@@ -2,7 +2,7 @@ import asyncio
 import logging
 import time
 from functools import wraps
-from typing import Any, Callable, Optional, TypeVar, cast, overload
+from typing import Any, Callable, Dict, List, Optional, TypeVar, cast, overload
 
 from freqtrade.constants import ExchangeConfig
 from freqtrade.exceptions import DDosProtection, RetryableOrderError, TemporaryError
@@ -60,16 +60,17 @@ SUPPORTED_EXCHANGES = [
     'okx',
 ]
 
-EXCHANGE_HAS_REQUIRED = [
+# either the main, or replacement methods (array) is required
+EXCHANGE_HAS_REQUIRED: Dict[str, List[str]] = {
     # Required / private
-    'fetchOrder',
-    'cancelOrder',
-    'createOrder',
-    'fetchBalance',
+    'fetchOrder': ['fetchOpenOrder', 'fetchClosedOrder'],
+    'cancelOrder': [],
+    'createOrder': [],
+    'fetchBalance': [],
 
     # Public endpoints
-    'fetchOHLCV',
-]
+    'fetchOHLCV': [],
+}
 
 EXCHANGE_HAS_OPTIONAL = [
     # Private
@@ -86,6 +87,7 @@ EXCHANGE_HAS_OPTIONAL = [
     # 'fetchPositions',  # Futures trading
     # 'fetchLeverageTiers',  # Futures initialization
     # 'fetchMarketLeverageTiers',  # Futures initialization
+    # 'fetchOpenOrder', 'fetchClosedOrder',  # replacement for fetchOrder
     # 'fetchOpenOrders', 'fetchClosedOrders',  # 'fetchOrders',  # Refinding balance...
 ]
 

freqtrade/exchange/exchange.py

@@ -8,7 +8,7 @@ import logging
 import signal
 from copy import deepcopy
 from datetime import datetime, timedelta, timezone
-from math import floor
+from math import floor, isnan
 from threading import Lock
 from typing import Any, Coroutine, Dict, List, Literal, Optional, Tuple, Union
 
@@ -23,26 +23,29 @@ from freqtrade.constants import (DEFAULT_AMOUNT_RESERVE_PERCENT, NON_OPEN_EXCHAN
                                  BuySell, Config, EntryExit, ExchangeConfig,
                                  ListPairsWithTimeframes, MakerTaker, OBLiteral, PairWithTimeframe)
 from freqtrade.data.converter import clean_ohlcv_dataframe, ohlcv_to_dataframe, trades_dict_to_list
-from freqtrade.enums import OPTIMIZE_MODES, CandleType, MarginMode, PriceType, TradingMode
-from freqtrade.exceptions import (DDosProtection, ExchangeError, InsufficientFundsError,
-                                  InvalidOrderException, OperationalException, PricingError,
-                                  RetryableOrderError, TemporaryError)
+from freqtrade.enums import OPTIMIZE_MODES, CandleType, MarginMode, PriceType, RunMode, TradingMode
+from freqtrade.exceptions import (ConfigurationError, DDosProtection, ExchangeError,
+                                  InsufficientFundsError, InvalidOrderException,
+                                  OperationalException, PricingError, RetryableOrderError,
+                                  TemporaryError)
 from freqtrade.exchange.common import (API_FETCH_ORDER_RETRY_COUNT, remove_exchange_credentials,
                                        retrier, retrier_async)
 from freqtrade.exchange.exchange_utils import (ROUND, ROUND_DOWN, ROUND_UP, CcxtModuleType,
                                                amount_to_contract_precision, amount_to_contracts,
                                                amount_to_precision, contracts_to_amount,
                                                date_minus_candles, is_exchange_known_ccxt,
-                                               market_is_active, price_to_precision,
-                                               timeframe_to_minutes, timeframe_to_msecs,
-                                               timeframe_to_next_date, timeframe_to_prev_date,
-                                               timeframe_to_seconds)
+                                               market_is_active, price_to_precision)
+from freqtrade.exchange.exchange_utils_timeframe import (timeframe_to_minutes, timeframe_to_msecs,
+                                                         timeframe_to_next_date,
+                                                         timeframe_to_prev_date,
+                                                         timeframe_to_seconds)
 from freqtrade.exchange.types import OHLCVResponse, OrderBook, Ticker, Tickers
 from freqtrade.misc import (chunks, deep_merge_dicts, file_dump_json, file_load_json,
                             safe_value_fallback2)
 from freqtrade.plugins.pairlist.pairlist_helpers import expand_pairlist
 from freqtrade.util import dt_from_ts, dt_now
-from freqtrade.util.datetime_helpers import dt_humanize, dt_ts
+from freqtrade.util.datetime_helpers import dt_humanize_delta, dt_ts
+from freqtrade.util.periodic_cache import PeriodicCache
 
 
 logger = logging.getLogger(__name__)
@@ -86,6 +89,8 @@ class Exchange:
         "order_props_in_contracts": ['amount', 'filled', 'remaining'],
         # Override createMarketBuyOrderRequiresPrice where ccxt has it wrong
         "marketOrderRequiresPrice": False,
+        "exchange_has_overrides": {},  # Dictionary overriding ccxt's "has".
+        # Expected to be in the format {"fetchOHLCV": True} or {"fetchOHLCV": False}
     }
     _ft_has: Dict = {}
     _ft_has_futures: Dict = {}
@@ -131,6 +136,7 @@ class Exchange:
 
         # Holds candles
         self._klines: Dict[PairWithTimeframe, DataFrame] = {}
+        self._expiring_candle_cache: Dict[Tuple[str, int], PeriodicCache] = {}
 
         # Holds all open sell orders for dry_run
         self._dry_run_open_orders: Dict[str, Any] = {}
@@ -233,8 +239,8 @@ class Exchange:
         self.validate_pricing(config['exit_pricing'])
         self.validate_pricing(config['entry_pricing'])
 
-    def _init_ccxt(self, exchange_config: Dict[str, Any], ccxt_module: CcxtModuleType = ccxt,
-                   ccxt_kwargs: Dict = {}) -> ccxt.Exchange:
+    def _init_ccxt(self, exchange_config: Dict[str, Any], ccxt_module: CcxtModuleType = ccxt, *,
+                   ccxt_kwargs: Dict) -> ccxt.Exchange:
         """
         Initialize ccxt with given config and return valid
         ccxt instance.
@@ -342,10 +348,13 @@ class Exchange:
         return int(self._ft_has.get('ohlcv_candle_limit_per_timeframe', {}).get(
             timeframe, self._ft_has.get('ohlcv_candle_limit')))
 
-    def get_markets(self, base_currencies: List[str] = [], quote_currencies: List[str] = [],
-                    spot_only: bool = False, margin_only: bool = False, futures_only: bool = False,
-                    tradable_only: bool = True,
-                    active_only: bool = False) -> Dict[str, Any]:
+    def get_markets(
+            self,
+            base_currencies: Optional[List[str]] = None,
+            quote_currencies: Optional[List[str]] = None,
+            spot_only: bool = False, margin_only: bool = False, futures_only: bool = False,
+            tradable_only: bool = True,
+            active_only: bool = False) -> Dict[str, Any]:
         """
         Return exchange ccxt markets, filtered out by base currency and quote currency
         if this was requested in parameters.
@@ -524,7 +533,7 @@ class Exchange:
             )
         quote_currencies = self.get_quote_currencies()
         if stake_currency not in quote_currencies:
-            raise OperationalException(
+            raise ConfigurationError(
                 f"{stake_currency} is not available as stake on {self.name}. "
                 f"Available currencies are: {', '.join(quote_currencies)}")
 
@@ -592,11 +601,15 @@ class Exchange:
                 f"is therefore not supported. ccxt fetchOHLCV: {self.exchange_has('fetchOHLCV')}")
 
         if timeframe and (timeframe not in self.timeframes):
-            raise OperationalException(
+            raise ConfigurationError(
                 f"Invalid timeframe '{timeframe}'. This exchange supports: {self.timeframes}")
 
-        if timeframe and timeframe_to_minutes(timeframe) < 1:
-            raise OperationalException("Timeframes < 1m are currently not supported by Freqtrade.")
+        if (
+            timeframe
+            and self._config['runmode'] != RunMode.UTIL_EXCHANGE
+            and timeframe_to_minutes(timeframe) < 1
+        ):
+            raise ConfigurationError("Timeframes < 1m are currently not supported by Freqtrade.")
 
     def validate_ordertypes(self, order_types: Dict) -> None:
         """
@@ -604,7 +617,7 @@ class Exchange:
         """
         if any(v == 'market' for k, v in order_types.items()):
             if not self.exchange_has('createMarketOrder'):
-                raise OperationalException(
+                raise ConfigurationError(
                     f'Exchange {self.name} does not support market orders.')
         self.validate_stop_ordertypes(order_types)
 
@@ -614,7 +627,7 @@ class Exchange:
         """
         if (order_types.get("stoploss_on_exchange")
                 and not self._ft_has.get("stoploss_on_exchange", False)):
-            raise OperationalException(
+            raise ConfigurationError(
                 f'On exchange stoploss is not supported for {self.name}.'
             )
         if self.trading_mode == TradingMode.FUTURES:
@@ -624,17 +637,17 @@ class Exchange:
                 and 'stoploss_price_type' in order_types
                 and order_types['stoploss_price_type'] not in price_mapping
             ):
-                raise OperationalException(
+                raise ConfigurationError(
                     f'On exchange stoploss price type is not supported for {self.name}.'
                 )
 
     def validate_pricing(self, pricing: Dict) -> None:
         if pricing.get('use_order_book', False) and not self.exchange_has('fetchL2OrderBook'):
-            raise OperationalException(f'Orderbook not available for {self.name}.')
+            raise ConfigurationError(f'Orderbook not available for {self.name}.')
         if (not pricing.get('use_order_book', False) and (
                 not self.exchange_has('fetchTicker')
                 or not self._ft_has['tickers_have_price'])):
-            raise OperationalException(f'Ticker pricing not available for {self.name}.')
+            raise ConfigurationError(f'Ticker pricing not available for {self.name}.')
 
     def validate_order_time_in_force(self, order_time_in_force: Dict) -> None:
         """
@@ -642,7 +655,7 @@ class Exchange:
         """
         if any(v.upper() not in self._ft_has["order_time_in_force"]
                for k, v in order_time_in_force.items()):
-            raise OperationalException(
+            raise ConfigurationError(
                 f'Time in force policies are not supported for {self.name} yet.')
 
     def validate_required_startup_candles(self, startup_candles: int, timeframe: str) -> int:
@@ -653,7 +666,7 @@ class Exchange:
 
         candle_limit = self.ohlcv_candle_limit(
             timeframe, self._config['candle_type_def'],
-            int(date_minus_candles(timeframe, startup_candles).timestamp() * 1000)
+            dt_ts(date_minus_candles(timeframe, startup_candles))
             if timeframe else None)
         # Require one more candle - to account for the still open candle.
         candle_count = startup_candles + 1
@@ -664,12 +677,12 @@ class Exchange:
 
             if required_candle_call_count > 5:
                 # Only allow 5 calls per pair to somewhat limit the impact
-                raise OperationalException(
+                raise ConfigurationError(
                     f"This strategy requires {startup_candles} candles to start, "
                     "which is more than 5x "
                     f"the amount of candles {self.name} provides for {timeframe}.")
         elif required_candle_call_count > 1:
-            raise OperationalException(
+            raise ConfigurationError(
                 f"This strategy requires {startup_candles} candles to start, which is more than "
                 f"the amount of candles {self.name} provides for {timeframe}.")
         if required_candle_call_count > 1:
@@ -710,6 +723,8 @@ class Exchange:
         :param endpoint: Name of endpoint (e.g. 'fetchOHLCV', 'fetchTickers')
         :return: bool
         """
+        if endpoint in self._ft_has.get('exchange_has_overrides', {}):
+            return self._ft_has['exchange_has_overrides'][endpoint]
         return endpoint in self._api.has and self._api.has[endpoint]
 
     def get_precision_amount(self, pair: str) -> Optional[float]:
@@ -746,7 +761,7 @@ class Exchange:
 
     def price_get_one_pip(self, pair: str, price: float) -> float:
         """
-        Get's the "1 pip" value for this pair.
+        Gets the "1 pip" value for this pair.
         Used in PriceFilter to calculate the 1pip movements.
         """
         precision = self.markets[pair]['precision']['price']
@@ -836,7 +851,7 @@ class Exchange:
     # Dry-run methods
 
     def create_dry_run_order(self, pair: str, ordertype: str, side: str, amount: float,
-                             rate: float, leverage: float, params: Dict = {},
+                             rate: float, leverage: float, params: Optional[Dict] = None,
                              stop_loss: bool = False) -> Dict[str, Any]:
         now = dt_now()
         order_id = f'dry_run_{side}_{pair}_{now.timestamp()}'
@@ -1110,7 +1125,7 @@ class Exchange:
                 f'Message: {e}') from e
         except ccxt.DDoSProtection as e:
             raise DDosProtection(e) from e
-        except (ccxt.NetworkError, ccxt.ExchangeError) as e:
+        except (ccxt.OperationFailed, ccxt.ExchangeError) as e:
             raise TemporaryError(
                 f'Could not place {side} order due to {e.__class__.__name__}. Message: {e}') from e
         except ccxt.BaseError as e:
@@ -1238,7 +1253,7 @@ class Exchange:
                 f'Insufficient funds to create {ordertype} {side} order on market {pair}. '
                 f'Tried to {side} amount {amount} at rate {limit_rate} with '
                 f'stop-price {stop_price_norm}. Message: {e}') from e
-        except (ccxt.InvalidOrder, ccxt.BadRequest) as e:
+        except (ccxt.InvalidOrder, ccxt.BadRequest, ccxt.OperationRejected) as e:
             # Errors:
             # `Order would trigger immediately.`
             raise InvalidOrderException(
@@ -1247,18 +1262,52 @@ class Exchange:
                 f'stop-price {stop_price_norm}. Message: {e}') from e
         except ccxt.DDoSProtection as e:
             raise DDosProtection(e) from e
-        except (ccxt.NetworkError, ccxt.ExchangeError) as e:
+        except (ccxt.OperationFailed, ccxt.ExchangeError) as e:
             raise TemporaryError(
                 f"Could not place stoploss order due to {e.__class__.__name__}. "
                 f"Message: {e}") from e
         except ccxt.BaseError as e:
             raise OperationalException(e) from e
 
+    def fetch_order_emulated(self, order_id: str, pair: str, params: Dict) -> Dict:
+        """
+        Emulated fetch_order if the exchange doesn't support fetch_order, but requires separate
+        calls for open and closed orders.
+        """
+        try:
+            order = self._api.fetch_open_order(order_id, pair, params=params)
+            self._log_exchange_response('fetch_open_order', order)
+            order = self._order_contracts_to_amount(order)
+            return order
+        except ccxt.OrderNotFound:
+            try:
+                order = self._api.fetch_closed_order(order_id, pair, params=params)
+                self._log_exchange_response('fetch_closed_order', order)
+                order = self._order_contracts_to_amount(order)
+                return order
+            except ccxt.OrderNotFound as e:
+                raise RetryableOrderError(
+                    f'Order not found (pair: {pair} id: {order_id}). Message: {e}') from e
+        except ccxt.InvalidOrder as e:
+            raise InvalidOrderException(
+                f'Tried to get an invalid order (pair: {pair} id: {order_id}). Message: {e}') from e
+        except ccxt.DDoSProtection as e:
+            raise DDosProtection(e) from e
+        except (ccxt.OperationFailed, ccxt.ExchangeError) as e:
+            raise TemporaryError(
+                f'Could not get order due to {e.__class__.__name__}. Message: {e}') from e
+        except ccxt.BaseError as e:
+            raise OperationalException(e) from e
+
     @retrier(retries=API_FETCH_ORDER_RETRY_COUNT)
-    def fetch_order(self, order_id: str, pair: str, params: Dict = {}) -> Dict:
+    def fetch_order(self, order_id: str, pair: str, params: Optional[Dict] = None) -> Dict:
         if self._config['dry_run']:
             return self.fetch_dry_run_order(order_id)
+        if params is None:
+            params = {}
         try:
+            if not self.exchange_has('fetchOrder'):
+                return self.fetch_order_emulated(order_id, pair, params)
             order = self._api.fetch_order(order_id, pair, params=params)
             self._log_exchange_response('fetch_order', order)
             order = self._order_contracts_to_amount(order)
@@ -1271,13 +1320,13 @@ class Exchange:
                 f'Tried to get an invalid order (pair: {pair} id: {order_id}). Message: {e}') from e
         except ccxt.DDoSProtection as e:
             raise DDosProtection(e) from e
-        except (ccxt.NetworkError, ccxt.ExchangeError) as e:
+        except (ccxt.OperationFailed, ccxt.ExchangeError) as e:
             raise TemporaryError(
                 f'Could not get order due to {e.__class__.__name__}. Message: {e}') from e
         except ccxt.BaseError as e:
             raise OperationalException(e) from e
 
-    def fetch_stoploss_order(self, order_id: str, pair: str, params: Dict = {}) -> Dict:
+    def fetch_stoploss_order(self, order_id: str, pair: str, params: Optional[Dict] = None) -> Dict:
         return self.fetch_order(order_id, pair, params)
 
     def fetch_order_or_stoploss_order(self, order_id: str, pair: str,
@@ -1303,7 +1352,7 @@ class Exchange:
                 and order.get('filled') == 0.0)
 
     @retrier
-    def cancel_order(self, order_id: str, pair: str, params: Dict = {}) -> Dict:
+    def cancel_order(self, order_id: str, pair: str, params: Optional[Dict] = None) -> Dict:
         if self._config['dry_run']:
             try:
                 order = self.fetch_dry_run_order(order_id)
@@ -1313,6 +1362,8 @@ class Exchange:
             except InvalidOrderException:
                 return {}
 
+        if params is None:
+            params = {}
         try:
             order = self._api.cancel_order(order_id, pair, params=params)
             self._log_exchange_response('cancel_order', order)
@@ -1323,13 +1374,14 @@ class Exchange:
                 f'Could not cancel order. Message: {e}') from e
         except ccxt.DDoSProtection as e:
             raise DDosProtection(e) from e
-        except (ccxt.NetworkError, ccxt.ExchangeError) as e:
+        except (ccxt.OperationFailed, ccxt.ExchangeError) as e:
             raise TemporaryError(
                 f'Could not cancel order due to {e.__class__.__name__}. Message: {e}') from e
         except ccxt.BaseError as e:
             raise OperationalException(e) from e
 
-    def cancel_stoploss_order(self, order_id: str, pair: str, params: Dict = {}) -> Dict:
+    def cancel_stoploss_order(
+            self, order_id: str, pair: str, params: Optional[Dict] = None) -> Dict:
         return self.cancel_order(order_id, pair, params)
 
     def is_cancel_order_result_suitable(self, corder) -> bool:
@@ -1405,7 +1457,7 @@ class Exchange:
             return balances
         except ccxt.DDoSProtection as e:
             raise DDosProtection(e) from e
-        except (ccxt.NetworkError, ccxt.ExchangeError) as e:
+        except (ccxt.OperationFailed, ccxt.ExchangeError) as e:
             raise TemporaryError(
                 f'Could not get balance due to {e.__class__.__name__}. Message: {e}') from e
         except ccxt.BaseError as e:
@@ -1429,7 +1481,7 @@ class Exchange:
             return positions
         except ccxt.DDoSProtection as e:
             raise DDosProtection(e) from e
-        except (ccxt.NetworkError, ccxt.ExchangeError) as e:
+        except (ccxt.OperationFailed, ccxt.ExchangeError) as e:
             raise TemporaryError(
                 f'Could not get positions due to {e.__class__.__name__}. Message: {e}') from e
         except ccxt.BaseError as e:
@@ -1473,7 +1525,7 @@ class Exchange:
             return orders
         except ccxt.DDoSProtection as e:
             raise DDosProtection(e) from e
-        except (ccxt.NetworkError, ccxt.ExchangeError) as e:
+        except (ccxt.OperationFailed, ccxt.ExchangeError) as e:
             raise TemporaryError(
                 f'Could not fetch positions due to {e.__class__.__name__}. Message: {e}') from e
         except ccxt.BaseError as e:
@@ -1494,7 +1546,7 @@ class Exchange:
             return trading_fees
         except ccxt.DDoSProtection as e:
             raise DDosProtection(e) from e
-        except (ccxt.NetworkError, ccxt.ExchangeError) as e:
+        except (ccxt.OperationFailed, ccxt.ExchangeError) as e:
             raise TemporaryError(
                 f'Could not fetch trading fees due to {e.__class__.__name__}. Message: {e}') from e
         except ccxt.BaseError as e:
@@ -1525,7 +1577,7 @@ class Exchange:
                 f'Message: {e}') from e
         except ccxt.DDoSProtection as e:
             raise DDosProtection(e) from e
-        except (ccxt.NetworkError, ccxt.ExchangeError) as e:
+        except (ccxt.OperationFailed, ccxt.ExchangeError) as e:
             raise TemporaryError(
                 f'Could not load bids/asks due to {e.__class__.__name__}. Message: {e}') from e
         except ccxt.BaseError as e:
@@ -1562,7 +1614,7 @@ class Exchange:
             raise TemporaryError from e
         except ccxt.DDoSProtection as e:
             raise DDosProtection(e) from e
-        except (ccxt.NetworkError, ccxt.ExchangeError) as e:
+        except (ccxt.OperationFailed, ccxt.ExchangeError) as e:
             raise TemporaryError(
                 f'Could not load tickers due to {e.__class__.__name__}. Message: {e}') from e
         except ccxt.BaseError as e:
@@ -1580,7 +1632,7 @@ class Exchange:
             return data
         except ccxt.DDoSProtection as e:
             raise DDosProtection(e) from e
-        except (ccxt.NetworkError, ccxt.ExchangeError) as e:
+        except (ccxt.OperationFailed, ccxt.ExchangeError) as e:
             raise TemporaryError(
                 f'Could not load ticker due to {e.__class__.__name__}. Message: {e}') from e
         except ccxt.BaseError as e:
@@ -1621,7 +1673,7 @@ class Exchange:
                 f'Message: {e}') from e
         except ccxt.DDoSProtection as e:
             raise DDosProtection(e) from e
-        except (ccxt.NetworkError, ccxt.ExchangeError) as e:
+        except (ccxt.OperationFailed, ccxt.ExchangeError) as e:
             raise TemporaryError(
                 f'Could not get order book due to {e.__class__.__name__}. Message: {e}') from e
         except ccxt.BaseError as e:
@@ -1800,7 +1852,7 @@ class Exchange:
             return matched_trades
         except ccxt.DDoSProtection as e:
             raise DDosProtection(e) from e
-        except (ccxt.NetworkError, ccxt.ExchangeError) as e:
+        except (ccxt.OperationFailed, ccxt.ExchangeError) as e:
             raise TemporaryError(
                 f'Could not get trades due to {e.__class__.__name__}. Message: {e}') from e
         except ccxt.BaseError as e:
@@ -1834,7 +1886,7 @@ class Exchange:
                                            price=price, takerOrMaker=taker_or_maker)['rate']
         except ccxt.DDoSProtection as e:
             raise DDosProtection(e) from e
-        except (ccxt.NetworkError, ccxt.ExchangeError) as e:
+        except (ccxt.OperationFailed, ccxt.ExchangeError) as e:
             raise TemporaryError(
                 f'Could not get fee info due to {e.__class__.__name__}. Message: {e}') from e
         except ccxt.BaseError as e:
@@ -1956,14 +2008,14 @@ class Exchange:
         logger.debug(
             "one_call: %s msecs (%s)",
             one_call,
-            dt_humanize(dt_now() - timedelta(milliseconds=one_call), only_distance=True)
+            dt_humanize_delta(dt_now() - timedelta(milliseconds=one_call))
         )
         input_coroutines = [self._async_get_candle_history(
             pair, timeframe, candle_type, since) for since in
             range(since_ms, until_ms or dt_ts(), one_call)]
 
         data: List = []
-        # Chunk requests into batches of 100 to avoid overwelming ccxt Throttling
+        # Chunk requests into batches of 100 to avoid overwhelming ccxt Throttling
         for input_coro in chunks(input_coroutines, 100):
 
             results = await asyncio.gather(*input_coro, return_exceptions=True)
@@ -2005,7 +2057,7 @@ class Exchange:
                 timeframe, candle_type, since_ms)
             move_to = one_call * self.required_candle_call_count
             now = timeframe_to_next_date(timeframe)
-            since_ms = int((now - timedelta(seconds=move_to // 1000)).timestamp() * 1000)
+            since_ms = dt_ts(now - timedelta(seconds=move_to // 1000))
 
         if since_ms:
             return self._async_get_historic_ohlcv(
@@ -2080,7 +2132,7 @@ class Exchange:
         Only used in the dataprovider.refresh() method.
         :param pair_list: List of 2 element tuples containing pair, interval to refresh
         :param since_ms: time since when to download, in milliseconds
-        :param cache: Assign result to _klines. Usefull for one-off downloads like for pairlists
+        :param cache: Assign result to _klines. Useful for one-off downloads like for pairlists
         :param drop_incomplete: Control candle dropping.
             Specifying None defaults to _ohlcv_partial_candle
         :return: Dict of [{(pair, timeframe): Dataframe}]
@@ -2091,7 +2143,7 @@ class Exchange:
         input_coroutines, cached_pairs = self._build_ohlcv_dl_jobs(pair_list, since_ms, cache)
 
         results_df = {}
-        # Chunk requests into batches of 100 to avoid overwelming ccxt Throttling
+        # Chunk requests into batches of 100 to avoid overwhelming ccxt Throttling
         for input_coro in chunks(input_coroutines, 100):
             async def gather_stuff():
                 return await asyncio.gather(*input_coro, return_exceptions=True)
@@ -2120,6 +2172,39 @@ class Exchange:
 
         return results_df
 
+    def refresh_ohlcv_with_cache(
+        self,
+        pairs: List[PairWithTimeframe],
+        since_ms: int
+    ) -> Dict[PairWithTimeframe, DataFrame]:
+        """
+        Refresh ohlcv data for all pairs in needed_pairs if necessary.
+        Caches data with expiring per timeframe.
+        Should only be used for pairlists which need "on time" expirarion, and no longer cache.
+        """
+
+        timeframes = {p[1] for p in pairs}
+        for timeframe in timeframes:
+            if (timeframe, since_ms) not in self._expiring_candle_cache:
+                timeframe_in_sec = timeframe_to_seconds(timeframe)
+                # Initialise cache
+                self._expiring_candle_cache[(timeframe, since_ms)] = PeriodicCache(
+                    ttl=timeframe_in_sec, maxsize=1000)
+
+        # Get candles from cache
+        candles = {
+            c: self._expiring_candle_cache[(c[1], since_ms)].get(c, None) for c in pairs
+            if c in self._expiring_candle_cache[(c[1], since_ms)]
+        }
+        pairs_to_download = [p for p in pairs if p not in candles]
+        if pairs_to_download:
+            candles = self.refresh_latest_ohlcv(
+                pairs_to_download, since_ms=since_ms, cache=False
+            )
+            for c, val in candles.items():
+                self._expiring_candle_cache[(c[1], since_ms)][c] = val
+        return candles
+
     def _now_is_time_to_refresh(self, pair: str, timeframe: str, candle_type: CandleType) -> bool:
         # Timeframe in seconds
         interval_in_sec = timeframe_to_seconds(timeframe)
@@ -2185,7 +2270,7 @@ class Exchange:
                 f'candle (OHLCV) data. Message: {e}') from e
         except ccxt.DDoSProtection as e:
             raise DDosProtection(e) from e
-        except (ccxt.NetworkError, ccxt.ExchangeError) as e:
+        except (ccxt.OperationFailed, ccxt.ExchangeError) as e:
             raise TemporaryError(f'Could not fetch historical candle (OHLCV) data '
                                  f'for pair {pair} due to {e.__class__.__name__}. '
                                  f'Message: {e}') from e
@@ -2218,7 +2303,7 @@ class Exchange:
                                   since: Optional[int] = None,
                                   params: Optional[dict] = None) -> Tuple[List[List], Any]:
         """
-        Asyncronously gets trade history using fetch_trades.
+        Asynchronously gets trade history using fetch_trades.
         Handles exchange errors, does one call to the exchange.
         :param pair: Pair to fetch trade data for
         :param since: Since as integer timestamp in milliseconds
@@ -2245,7 +2330,7 @@ class Exchange:
                 f'Message: {e}') from e
         except ccxt.DDoSProtection as e:
             raise DDosProtection(e) from e
-        except (ccxt.NetworkError, ccxt.ExchangeError) as e:
+        except (ccxt.OperationFailed, ccxt.ExchangeError) as e:
             raise TemporaryError(f'Could not load trade history due to {e.__class__.__name__}. '
                                  f'Message: {e}') from e
         except ccxt.BaseError as e:
@@ -2275,7 +2360,7 @@ class Exchange:
                                           since: Optional[int] = None,
                                           from_id: Optional[str] = None) -> Tuple[str, List[List]]:
         """
-        Asyncronously gets trade history using fetch_trades
+        Asynchronously gets trade history using fetch_trades
         use this when exchange uses id-based iteration (check `self._trades_pagination`)
         :param pair: Pair to fetch trade data for
         :param since: Since as integer timestamp in milliseconds
@@ -2326,7 +2411,7 @@ class Exchange:
     async def _async_get_trade_history_time(self, pair: str, until: int,
                                             since: Optional[int] = None) -> Tuple[str, List[List]]:
         """
-        Asyncronously gets trade history using fetch_trades,
+        Asynchronously gets trade history using fetch_trades,
         when the exchange uses time-based iteration (check `self._trades_pagination`)
         :param pair: Pair to fetch trade data for
         :param since: Since as integer timestamp in milliseconds
@@ -2432,7 +2517,7 @@ class Exchange:
             )
 
         if type(since) is datetime:
-            since = int(since.timestamp()) * 1000   # * 1000 for ms
+            since = dt_ts(since)
 
         try:
             funding_history = self._api.fetch_funding_history(
@@ -2444,7 +2529,7 @@ class Exchange:
             return sum(fee['amount'] for fee in funding_history)
         except ccxt.DDoSProtection as e:
             raise DDosProtection(e) from e
-        except (ccxt.NetworkError, ccxt.ExchangeError) as e:
+        except (ccxt.OperationFailed, ccxt.ExchangeError) as e:
             raise TemporaryError(
                 f'Could not get funding fees due to {e.__class__.__name__}. Message: {e}') from e
         except ccxt.BaseError as e:
@@ -2456,7 +2541,7 @@ class Exchange:
             return self._api.fetch_leverage_tiers()
         except ccxt.DDoSProtection as e:
             raise DDosProtection(e) from e
-        except (ccxt.NetworkError, ccxt.ExchangeError) as e:
+        except (ccxt.OperationFailed, ccxt.ExchangeError) as e:
             raise TemporaryError(
                 f'Could not load leverage tiers due to {e.__class__.__name__}. Message: {e}'
             ) from e
@@ -2471,7 +2556,7 @@ class Exchange:
             return symbol, tier
         except ccxt.DDoSProtection as e:
             raise DDosProtection(e) from e
-        except (ccxt.NetworkError, ccxt.ExchangeError) as e:
+        except (ccxt.OperationFailed, ccxt.ExchangeError) as e:
             raise TemporaryError(
                 f'Could not load leverage tiers for {symbol}'
                 f' due to {e.__class__.__name__}. Message: {e}'
@@ -2681,11 +2766,11 @@ class Exchange:
             self._log_exchange_response('set_leverage', res)
         except ccxt.DDoSProtection as e:
             raise DDosProtection(e) from e
-        except (ccxt.BadRequest, ccxt.InsufficientFunds) as e:
+        except (ccxt.BadRequest, ccxt.OperationRejected, ccxt.InsufficientFunds) as e:
             if not accept_fail:
                 raise TemporaryError(
                     f'Could not set leverage due to {e.__class__.__name__}. Message: {e}') from e
-        except (ccxt.NetworkError, ccxt.ExchangeError) as e:
+        except (ccxt.OperationFailed, ccxt.ExchangeError) as e:
             raise TemporaryError(
                 f'Could not set leverage due to {e.__class__.__name__}. Message: {e}') from e
         except ccxt.BaseError as e:
@@ -2709,7 +2794,7 @@ class Exchange:
 
     @retrier
     def set_margin_mode(self, pair: str, margin_mode: MarginMode, accept_fail: bool = False,
-                        params: dict = {}):
+                        params: Optional[Dict] = None):
         """
         Set's the margin mode on the exchange to cross or isolated for a specific pair
         :param pair: base/quote currency pair (e.g. "ADA/USDT")
@@ -2718,16 +2803,18 @@ class Exchange:
             # Some exchanges only support one margin_mode type
             return
 
+        if params is None:
+            params = {}
         try:
             res = self._api.set_margin_mode(margin_mode.value, pair, params)
             self._log_exchange_response('set_margin_mode', res)
         except ccxt.DDoSProtection as e:
             raise DDosProtection(e) from e
-        except ccxt.BadRequest as e:
+        except (ccxt.BadRequest, ccxt.OperationRejected) as e:
             if not accept_fail:
                 raise TemporaryError(
                     f'Could not set margin mode due to {e.__class__.__name__}. Message: {e}') from e
-        except (ccxt.NetworkError, ccxt.ExchangeError) as e:
+        except (ccxt.OperationFailed, ccxt.ExchangeError) as e:
             raise TemporaryError(
                 f'Could not set margin mode due to {e.__class__.__name__}. Message: {e}') from e
         except ccxt.BaseError as e:
@@ -2762,7 +2849,7 @@ class Exchange:
 
         if not close_date:
             close_date = datetime.now(timezone.utc)
-        since_ms = int(timeframe_to_prev_date(timeframe, open_date).timestamp()) * 1000
+        since_ms = dt_ts(timeframe_to_prev_date(timeframe, open_date))
 
         mark_comb: PairWithTimeframe = (pair, timeframe, mark_price_type)
         funding_comb: PairWithTimeframe = (pair, timeframe_ff, CandleType.FUNDING_RATE)
@@ -2816,7 +2903,7 @@ class Exchange:
             else:
                 # Fill up missing funding_rate candles with fallback value
                 combined = mark_rates.merge(
-                    funding_rates, on='date', how="outer", suffixes=["_mark", "_fund"]
+                    funding_rates, on='date', how="left", suffixes=["_mark", "_fund"]
                     )
                 combined['open_fund'] = combined['open_fund'].fillna(futures_funding_rate)
                 return combined
@@ -2845,7 +2932,8 @@ class Exchange:
         if not df.empty:
             df1 = df[(df['date'] >= open_date) & (df['date'] <= close_date)]
             fees = sum(df1['open_fund'] * df1['open_mark'] * amount)
-
+        if isnan(fees):
+            fees = 0.0
         # Negate fees for longs as funding_fees expects it this way based on live endpoints.
         return fees if is_short else -fees
 
@@ -3021,3 +3109,4 @@ class Exchange:
             # describes the min amt for a tier, and the lowest tier will always go down to 0
         else:
             raise ExchangeError(f"Cannot get maintenance ratio using {self.name}")
+            raise ExchangeError(f"Cannot get maintenance ratio using {self.name}")

freqtrade/exchange/exchange_utils.py

@@ -11,9 +11,9 @@ from ccxt import (DECIMAL_PLACES, ROUND, ROUND_DOWN, ROUND_UP, SIGNIFICANT_DIGIT
 
 from freqtrade.exchange.common import (BAD_EXCHANGES, EXCHANGE_HAS_OPTIONAL, EXCHANGE_HAS_REQUIRED,
                                        SUPPORTED_EXCHANGES)
+from freqtrade.exchange.exchange_utils_timeframe import timeframe_to_minutes, timeframe_to_prev_date
 from freqtrade.types import ValidExchangesType
 from freqtrade.util import FtPrecise
-from freqtrade.util.datetime_helpers import dt_from_ts, dt_ts
 
 
 CcxtModuleType = Any
@@ -40,21 +40,34 @@ def available_exchanges(ccxt_module: Optional[CcxtModuleType] = None) -> List[st
 
 
 def validate_exchange(exchange: str) -> Tuple[bool, str]:
+    """
+    returns: can_use, reason
+        with Reason including both missing and missing_opt
+    """
     ex_mod = getattr(ccxt, exchange.lower())()
+    result = True
+    reason = ''
     if not ex_mod or not ex_mod.has:
         return False, ''
-    missing = [k for k in EXCHANGE_HAS_REQUIRED if ex_mod.has.get(k) is not True]
+    missing = [
+        k for k, v in EXCHANGE_HAS_REQUIRED.items()
+        if ex_mod.has.get(k) is not True
+        and not (all(ex_mod.has.get(x) for x in v))
+    ]
     if missing:
-        return False, f"missing: {', '.join(missing)}"
+        result = False
+        reason += f"missing: {', '.join(missing)}"
 
     missing_opt = [k for k in EXCHANGE_HAS_OPTIONAL if not ex_mod.has.get(k)]
 
     if exchange.lower() in BAD_EXCHANGES:
-        return False, BAD_EXCHANGES.get(exchange.lower(), '')
-    if missing_opt:
-        return True, f"missing opt: {', '.join(missing_opt)}"
+        result = False
+        reason = BAD_EXCHANGES.get(exchange.lower(), '')
 
-    return True, ''
+    if missing_opt:
+        reason += f"{'. ' if reason else ''}missing opt: {', '.join(missing_opt)}. "
+
+    return result, reason
 
 
 def _build_exchange_list_entry(
@@ -95,78 +108,6 @@ def list_available_exchanges(all_exchanges: bool) -> List[ValidExchangesType]:
     return exchanges_valid
 
 
-def timeframe_to_seconds(timeframe: str) -> int:
-    """
-    Translates the timeframe interval value written in the human readable
-    form ('1m', '5m', '1h', '1d', '1w', etc.) to the number
-    of seconds for one timeframe interval.
-    """
-    return ccxt.Exchange.parse_timeframe(timeframe)
-
-
-def timeframe_to_minutes(timeframe: str) -> int:
-    """
-    Same as timeframe_to_seconds, but returns minutes.
-    """
-    return ccxt.Exchange.parse_timeframe(timeframe) // 60
-
-
-def timeframe_to_msecs(timeframe: str) -> int:
-    """
-    Same as timeframe_to_seconds, but returns milliseconds.
-    """
-    return ccxt.Exchange.parse_timeframe(timeframe) * 1000
-
-
-def timeframe_to_resample_freq(timeframe: str) -> str:
-    """
-    Translates the timeframe interval value written in the human readable
-    form ('1m', '5m', '1h', '1d', '1w', etc.) to the resample frequency
-    used by pandas ('1T', '5T', '1H', '1D', '1W', etc.)
-    """
-    if timeframe == '1y':
-        return '1YS'
-    timeframe_seconds = timeframe_to_seconds(timeframe)
-    timeframe_minutes = timeframe_seconds // 60
-    resample_interval = f'{timeframe_seconds}s'
-    if 10000 < timeframe_minutes < 43200:
-        resample_interval = '1W-MON'
-    elif timeframe_minutes >= 43200 and timeframe_minutes < 525600:
-        # Monthly candles need special treatment to stick to the 1st of the month
-        resample_interval = f'{timeframe}S'
-    elif timeframe_minutes > 43200:
-        resample_interval = timeframe
-    return resample_interval
-
-
-def timeframe_to_prev_date(timeframe: str, date: Optional[datetime] = None) -> datetime:
-    """
-    Use Timeframe and determine the candle start date for this date.
-    Does not round when given a candle start date.
-    :param timeframe: timeframe in string format (e.g. "5m")
-    :param date: date to use. Defaults to now(utc)
-    :returns: date of previous candle (with utc timezone)
-    """
-    if not date:
-        date = datetime.now(timezone.utc)
-
-    new_timestamp = ccxt.Exchange.round_timeframe(timeframe, dt_ts(date), ROUND_DOWN) // 1000
-    return dt_from_ts(new_timestamp)
-
-
-def timeframe_to_next_date(timeframe: str, date: Optional[datetime] = None) -> datetime:
-    """
-    Use Timeframe and determine next candle.
-    :param timeframe: timeframe in string format (e.g. "5m")
-    :param date: date to use. Defaults to now(utc)
-    :returns: date of next candle (with utc timezone)
-    """
-    if not date:
-        date = datetime.now(timezone.utc)
-    new_timestamp = ccxt.Exchange.round_timeframe(timeframe, dt_ts(date), ROUND_UP) // 1000
-    return dt_from_ts(new_timestamp)
-
-
 def date_minus_candles(
         timeframe: str, candle_count: int, date: Optional[datetime] = None) -> datetime:
     """

freqtrade/exchange/exchange_utils_timeframe.py

@@ -0,0 +1,81 @@
+from datetime import datetime, timezone
+from typing import Optional
+
+import ccxt
+from ccxt import ROUND_DOWN, ROUND_UP
+
+from freqtrade.util.datetime_helpers import dt_from_ts, dt_ts
+
+
+def timeframe_to_seconds(timeframe: str) -> int:
+    """
+    Translates the timeframe interval value written in the human readable
+    form ('1m', '5m', '1h', '1d', '1w', etc.) to the number
+    of seconds for one timeframe interval.
+    """
+    return ccxt.Exchange.parse_timeframe(timeframe)
+
+
+def timeframe_to_minutes(timeframe: str) -> int:
+    """
+    Same as timeframe_to_seconds, but returns minutes.
+    """
+    return ccxt.Exchange.parse_timeframe(timeframe) // 60
+
+
+def timeframe_to_msecs(timeframe: str) -> int:
+    """
+    Same as timeframe_to_seconds, but returns milliseconds.
+    """
+    return ccxt.Exchange.parse_timeframe(timeframe) * 1000
+
+
+def timeframe_to_resample_freq(timeframe: str) -> str:
+    """
+    Translates the timeframe interval value written in the human readable
+    form ('1m', '5m', '1h', '1d', '1w', etc.) to the resample frequency
+    used by pandas ('1T', '5T', '1H', '1D', '1W', etc.)
+    """
+    if timeframe == '1y':
+        return '1YS'
+    timeframe_seconds = timeframe_to_seconds(timeframe)
+    timeframe_minutes = timeframe_seconds // 60
+    resample_interval = f'{timeframe_seconds}s'
+    if 10000 < timeframe_minutes < 43200:
+        resample_interval = '1W-MON'
+    elif timeframe_minutes >= 43200 and timeframe_minutes < 525600:
+        # Monthly candles need special treatment to stick to the 1st of the month
+        resample_interval = f'{timeframe}S'
+    elif timeframe_minutes > 43200:
+        resample_interval = timeframe
+    return resample_interval
+
+
+def timeframe_to_prev_date(timeframe: str, date: Optional[datetime] = None) -> datetime:
+    """
+    Use Timeframe and determine the candle start date for this date.
+    Does not round when given a candle start date.
+    :param timeframe: timeframe in string format (e.g. "5m")
+    :param date: date to use. Defaults to now(utc)
+    :returns: date of previous candle (with utc timezone)
+    """
+    if not date:
+        date = datetime.now(timezone.utc)
+
+    new_timestamp = ccxt.Exchange.round_timeframe(
+        timeframe, dt_ts(date), ROUND_DOWN) // 1000
+    return dt_from_ts(new_timestamp)
+
+
+def timeframe_to_next_date(timeframe: str, date: Optional[datetime] = None) -> datetime:
+    """
+    Use Timeframe and determine next candle.
+    :param timeframe: timeframe in string format (e.g. "5m")
+    :param date: date to use. Defaults to now(utc)
+    :returns: date of next candle (with utc timezone)
+    """
+    if not date:
+        date = datetime.now(timezone.utc)
+    new_timestamp = ccxt.Exchange.round_timeframe(
+        timeframe, dt_ts(date), ROUND_UP) // 1000
+    return dt_from_ts(new_timestamp)

freqtrade/exchange/gate.py

@@ -79,7 +79,7 @@ class Gate(Exchange):
             # As such, futures orders on gate will not contain a fee, which causes
             # a repeated "update fee" cycle and wrong calculations.
             # Therefore we patch the response with fees if it's not available.
-            # An alternative also contianing fees would be
+            # An alternative also containing fees would be
             # privateFuturesGetSettleAccountBook({"settle": "usdt"})
             pair_fees = self._trading_fees.get(pair, {})
             if pair_fees:
@@ -96,30 +96,31 @@ class Gate(Exchange):
         return trades
 
     def get_order_id_conditional(self, order: Dict[str, Any]) -> str:
-        if self.trading_mode == TradingMode.FUTURES:
-            return safe_value_fallback2(order, order, 'id_stop', 'id')
-        return order['id']
+        return safe_value_fallback2(order, order, 'id_stop', 'id')
 
-    def fetch_stoploss_order(self, order_id: str, pair: str, params: Dict = {}) -> Dict:
+    def fetch_stoploss_order(self, order_id: str, pair: str, params: Optional[Dict] = None) -> Dict:
         order = self.fetch_order(
             order_id=order_id,
             pair=pair,
             params={'stop': True}
         )
-        if self.trading_mode == TradingMode.FUTURES:
-            if order['status'] == 'closed':
-                # Places a real order - which we need to fetch explicitly.
-                new_orderid = order.get('info', {}).get('trade_id')
-                if new_orderid:
-                    order1 = self.fetch_order(order_id=new_orderid, pair=pair, params=params)
-                    order1['id_stop'] = order1['id']
-                    order1['id'] = order_id
-                    order1['stopPrice'] = order.get('stopPrice')
+        if order.get('status', 'open') == 'closed':
+            # Places a real order - which we need to fetch explicitly.
+            val = 'trade_id' if self.trading_mode == TradingMode.FUTURES else 'fired_order_id'
 
-                    return order1
+            if new_orderid := order.get('info', {}).get(val):
+                order1 = self.fetch_order(order_id=new_orderid, pair=pair, params=params)
+                order1['id_stop'] = order1['id']
+                order1['id'] = order_id
+                order1['type'] = 'stoploss'
+                order1['stopPrice'] = order.get('stopPrice')
+                order1['status_stop'] = 'triggered'
+
+                return order1
         return order
 
-    def cancel_stoploss_order(self, order_id: str, pair: str, params: Dict = {}) -> Dict:
+    def cancel_stoploss_order(
+            self, order_id: str, pair: str, params: Optional[Dict] = None) -> Dict:
         return self.cancel_order(
             order_id=order_id,
             pair=pair,

freqtrade/exchange/idex.py

@@ -0,0 +1,19 @@
+""" Idex exchange subclass """
+import logging
+from typing import Dict
+
+from freqtrade.exchange import Exchange
+
+
+logger = logging.getLogger(__name__)
+
+
+class Idex(Exchange):
+    """
+    Idex exchange class. Contains adjustments needed for Freqtrade to work
+    with this exchange.
+    """
+
+    _ft_has: Dict = {
+        "ohlcv_candle_limit": 1000,
+    }