Merge pull request #8421 from freqtrade/new_release

New release 2023.3
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Matthias 2023-03-31 07:09:11 +02:00 committed by GitHub
commit 038a111b45
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152 changed files with 8486 additions and 4689 deletions

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@ -16,7 +16,8 @@ on:
concurrency: concurrency:
group: ${{ github.workflow }}-${{ github.ref }} group: ${{ github.workflow }}-${{ github.ref }}
cancel-in-progress: true cancel-in-progress: true
permissions:
repository-projects: read
jobs: jobs:
build_linux: build_linux:
@ -24,7 +25,7 @@ jobs:
strategy: strategy:
matrix: matrix:
os: [ ubuntu-20.04, ubuntu-22.04 ] os: [ ubuntu-20.04, ubuntu-22.04 ]
python-version: ["3.8", "3.9", "3.10"] python-version: ["3.8", "3.9", "3.10", "3.11"]
steps: steps:
- uses: actions/checkout@v3 - uses: actions/checkout@v3
@ -90,14 +91,14 @@ jobs:
freqtrade create-userdir --userdir user_data freqtrade create-userdir --userdir user_data
freqtrade hyperopt --datadir tests/testdata -e 6 --strategy SampleStrategy --hyperopt-loss SharpeHyperOptLossDaily --print-all freqtrade hyperopt --datadir tests/testdata -e 6 --strategy SampleStrategy --hyperopt-loss SharpeHyperOptLossDaily --print-all
- name: Flake8
run: |
flake8
- name: Sort imports (isort) - name: Sort imports (isort)
run: | run: |
isort --check . isort --check .
- name: Run Ruff
run: |
ruff check --format=github .
- name: Mypy - name: Mypy
run: | run: |
mypy freqtrade scripts tests mypy freqtrade scripts tests
@ -115,7 +116,7 @@ jobs:
strategy: strategy:
matrix: matrix:
os: [ macos-latest ] os: [ macos-latest ]
python-version: ["3.8", "3.9", "3.10"] python-version: ["3.8", "3.9", "3.10", "3.11"]
steps: steps:
- uses: actions/checkout@v3 - uses: actions/checkout@v3
@ -186,14 +187,14 @@ jobs:
freqtrade create-userdir --userdir user_data freqtrade create-userdir --userdir user_data
freqtrade hyperopt --datadir tests/testdata -e 5 --strategy SampleStrategy --hyperopt-loss SharpeHyperOptLossDaily --print-all freqtrade hyperopt --datadir tests/testdata -e 5 --strategy SampleStrategy --hyperopt-loss SharpeHyperOptLossDaily --print-all
- name: Flake8
run: |
flake8
- name: Sort imports (isort) - name: Sort imports (isort)
run: | run: |
isort --check . isort --check .
- name: Run Ruff
run: |
ruff check --format=github .
- name: Mypy - name: Mypy
run: | run: |
mypy freqtrade scripts mypy freqtrade scripts
@ -212,7 +213,7 @@ jobs:
strategy: strategy:
matrix: matrix:
os: [ windows-latest ] os: [ windows-latest ]
python-version: ["3.8", "3.9", "3.10"] python-version: ["3.8", "3.9", "3.10", "3.11"]
steps: steps:
- uses: actions/checkout@v3 - uses: actions/checkout@v3
@ -248,9 +249,9 @@ jobs:
freqtrade create-userdir --userdir user_data freqtrade create-userdir --userdir user_data
freqtrade hyperopt --datadir tests/testdata -e 5 --strategy SampleStrategy --hyperopt-loss SharpeHyperOptLossDaily --print-all freqtrade hyperopt --datadir tests/testdata -e 5 --strategy SampleStrategy --hyperopt-loss SharpeHyperOptLossDaily --print-all
- name: Flake8 - name: Run Ruff
run: | run: |
flake8 ruff check --format=github .
- name: Mypy - name: Mypy
run: | run: |
@ -321,7 +322,6 @@ jobs:
build_linux_online: build_linux_online:
# Run pytest with "live" checks # Run pytest with "live" checks
runs-on: ubuntu-22.04 runs-on: ubuntu-22.04
# permissions:
steps: steps:
- uses: actions/checkout@v3 - uses: actions/checkout@v3
@ -425,7 +425,7 @@ jobs:
python setup.py sdist bdist_wheel python setup.py sdist bdist_wheel
- name: Publish to PyPI (Test) - name: Publish to PyPI (Test)
uses: pypa/gh-action-pypi-publish@v1.6.4 uses: pypa/gh-action-pypi-publish@v1.8.3
if: (github.event_name == 'release') if: (github.event_name == 'release')
with: with:
user: __token__ user: __token__
@ -433,7 +433,7 @@ jobs:
repository_url: https://test.pypi.org/legacy/ repository_url: https://test.pypi.org/legacy/
- name: Publish to PyPI - name: Publish to PyPI
uses: pypa/gh-action-pypi-publish@v1.6.4 uses: pypa/gh-action-pypi-publish@v1.8.3
if: (github.event_name == 'release') if: (github.event_name == 'release')
with: with:
user: __token__ user: __token__
@ -466,12 +466,13 @@ jobs:
- name: Build and test and push docker images - name: Build and test and push docker images
env: env:
IMAGE_NAME: freqtradeorg/freqtrade
BRANCH_NAME: ${{ steps.extract_branch.outputs.branch }} BRANCH_NAME: ${{ steps.extract_branch.outputs.branch }}
run: | run: |
build_helpers/publish_docker_multi.sh build_helpers/publish_docker_multi.sh
deploy_arm: deploy_arm:
permissions:
packages: write
needs: [ deploy ] needs: [ deploy ]
# Only run on 64bit machines # Only run on 64bit machines
runs-on: [self-hosted, linux, ARM64] runs-on: [self-hosted, linux, ARM64]
@ -494,8 +495,9 @@ jobs:
- name: Build and test and push docker images - name: Build and test and push docker images
env: env:
IMAGE_NAME: freqtradeorg/freqtrade
BRANCH_NAME: ${{ steps.extract_branch.outputs.branch }} BRANCH_NAME: ${{ steps.extract_branch.outputs.branch }}
GHCR_USERNAME: ${{ github.actor }}
GHCR_TOKEN: ${{ secrets.GITHUB_TOKEN }}
run: | run: |
build_helpers/publish_docker_arm64.sh build_helpers/publish_docker_arm64.sh

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@ -8,16 +8,17 @@ repos:
# stages: [push] # stages: [push]
- repo: https://github.com/pre-commit/mirrors-mypy - repo: https://github.com/pre-commit/mirrors-mypy
rev: "v0.991" rev: "v1.0.1"
hooks: hooks:
- id: mypy - id: mypy
exclude: build_helpers exclude: build_helpers
additional_dependencies: additional_dependencies:
- types-cachetools==5.3.0.0 - types-cachetools==5.3.0.4
- types-filelock==3.2.7 - types-filelock==3.2.7
- types-requests==2.28.11.13 - types-requests==2.28.11.16
- types-tabulate==0.9.0.0 - types-tabulate==0.9.0.1
- types-python-dateutil==2.8.19.6 - types-python-dateutil==2.8.19.10
- SQLAlchemy==2.0.7
# stages: [push] # stages: [push]
- repo: https://github.com/pycqa/isort - repo: https://github.com/pycqa/isort
@ -27,6 +28,12 @@ repos:
name: isort (python) name: isort (python)
# stages: [push] # stages: [push]
- repo: https://github.com/charliermarsh/ruff-pre-commit
# Ruff version.
rev: 'v0.0.255'
hooks:
- id: ruff
- repo: https://github.com/pre-commit/pre-commit-hooks - repo: https://github.com/pre-commit/pre-commit-hooks
rev: v4.4.0 rev: v4.4.0
hooks: hooks:

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@ -45,16 +45,17 @@ pytest tests/test_<file_name>.py::test_<method_name>
### 2. Test if your code is PEP8 compliant ### 2. Test if your code is PEP8 compliant
#### Run Flake8 #### Run Ruff
```bash ```bash
flake8 freqtrade tests scripts ruff .
``` ```
We receive a lot of code that fails the `flake8` checks. We receive a lot of code that fails the `ruff` checks.
To help with that, we encourage you to install the git pre-commit To help with that, we encourage you to install the git pre-commit
hook that will warn you when you try to commit code that fails these checks. hook that will warn you when you try to commit code that fails these checks.
Guide for installing them is [here](http://flake8.pycqa.org/en/latest/user/using-hooks.html).
you can manually run pre-commit with `pre-commit run -a`.
##### Additional styles applied ##### Additional styles applied

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@ -8,8 +8,8 @@ if [ -n "$2" ] || [ ! -f "${INSTALL_LOC}/lib/libta_lib.a" ]; then
tar zxvf ta-lib-0.4.0-src.tar.gz tar zxvf ta-lib-0.4.0-src.tar.gz
cd ta-lib \ cd ta-lib \
&& sed -i.bak "s|0.00000001|0.000000000000000001 |g" src/ta_func/ta_utility.h \ && sed -i.bak "s|0.00000001|0.000000000000000001 |g" src/ta_func/ta_utility.h \
&& curl 'http://git.savannah.gnu.org/gitweb/?p=config.git;a=blob_plain;f=config.guess;hb=HEAD' -o config.guess \ && curl 'https://raw.githubusercontent.com/gcc-mirror/gcc/master/config.guess' -o config.guess \
&& curl 'http://git.savannah.gnu.org/gitweb/?p=config.git;a=blob_plain;f=config.sub;hb=HEAD' -o config.sub \ && curl 'https://raw.githubusercontent.com/gcc-mirror/gcc/master/config.sub' -o config.sub \
&& ./configure --prefix=${INSTALL_LOC}/ \ && ./configure --prefix=${INSTALL_LOC}/ \
&& make && make
if [ $? -ne 0 ]; then if [ $? -ne 0 ]; then

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@ -8,12 +8,17 @@ import yaml
pre_commit_file = Path('.pre-commit-config.yaml') pre_commit_file = Path('.pre-commit-config.yaml')
require_dev = Path('requirements-dev.txt') require_dev = Path('requirements-dev.txt')
require = Path('requirements.txt')
with require_dev.open('r') as rfile: with require_dev.open('r') as rfile:
requirements = rfile.readlines() requirements = rfile.readlines()
with require.open('r') as rfile:
requirements.extend(rfile.readlines())
# Extract types only # Extract types only
type_reqs = [r.strip('\n') for r in requirements if r.startswith('types-')] 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: with pre_commit_file.open('r') as file:
f = yaml.load(file, Loader=yaml.FullLoader) f = yaml.load(file, Loader=yaml.FullLoader)

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@ -3,6 +3,10 @@
# Use BuildKit, otherwise building on ARM fails # Use BuildKit, otherwise building on ARM fails
export DOCKER_BUILDKIT=1 export DOCKER_BUILDKIT=1
IMAGE_NAME=freqtradeorg/freqtrade
CACHE_IMAGE=freqtradeorg/freqtrade_cache
GHCR_IMAGE_NAME=ghcr.io/freqtrade/freqtrade
# Replace / with _ to create a valid tag # Replace / with _ to create a valid tag
TAG=$(echo "${BRANCH_NAME}" | sed -e "s/\//_/g") TAG=$(echo "${BRANCH_NAME}" | sed -e "s/\//_/g")
TAG_PLOT=${TAG}_plot TAG_PLOT=${TAG}_plot
@ -14,7 +18,6 @@ TAG_ARM=${TAG}_arm
TAG_PLOT_ARM=${TAG_PLOT}_arm TAG_PLOT_ARM=${TAG_PLOT}_arm
TAG_FREQAI_ARM=${TAG_FREQAI}_arm TAG_FREQAI_ARM=${TAG_FREQAI}_arm
TAG_FREQAI_RL_ARM=${TAG_FREQAI_RL}_arm TAG_FREQAI_RL_ARM=${TAG_FREQAI_RL}_arm
CACHE_IMAGE=freqtradeorg/freqtrade_cache
echo "Running for ${TAG}" echo "Running for ${TAG}"
@ -38,13 +41,13 @@ if [ $? -ne 0 ]; then
echo "failed building multiarch images" echo "failed building multiarch images"
return 1 return 1
fi fi
# Tag image for upload and next build step
docker tag freqtrade:$TAG_ARM ${CACHE_IMAGE}:$TAG_ARM
docker build --cache-from freqtrade:${TAG_ARM} --build-arg sourceimage=${CACHE_IMAGE} --build-arg sourcetag=${TAG_ARM} -t freqtrade:${TAG_PLOT_ARM} -f docker/Dockerfile.plot . docker build --cache-from freqtrade:${TAG_ARM} --build-arg sourceimage=${CACHE_IMAGE} --build-arg sourcetag=${TAG_ARM} -t freqtrade:${TAG_PLOT_ARM} -f docker/Dockerfile.plot .
docker build --cache-from freqtrade:${TAG_ARM} --build-arg sourceimage=${CACHE_IMAGE} --build-arg sourcetag=${TAG_ARM} -t freqtrade:${TAG_FREQAI_ARM} -f docker/Dockerfile.freqai . docker build --cache-from freqtrade:${TAG_ARM} --build-arg sourceimage=${CACHE_IMAGE} --build-arg sourcetag=${TAG_ARM} -t freqtrade:${TAG_FREQAI_ARM} -f docker/Dockerfile.freqai .
docker build --cache-from freqtrade:${TAG_ARM} --build-arg sourceimage=${CACHE_IMAGE} --build-arg sourcetag=${TAG_ARM} -t freqtrade:${TAG_FREQAI_RL_ARM} -f docker/Dockerfile.freqai_rl . docker build --cache-from freqtrade:${TAG_ARM} --build-arg sourceimage=${CACHE_IMAGE} --build-arg sourcetag=${TAG_ARM} -t freqtrade:${TAG_FREQAI_RL_ARM} -f docker/Dockerfile.freqai_rl .
# Tag image for upload and next build step
docker tag freqtrade:$TAG_ARM ${CACHE_IMAGE}:$TAG_ARM
docker tag freqtrade:$TAG_PLOT_ARM ${CACHE_IMAGE}:$TAG_PLOT_ARM docker tag freqtrade:$TAG_PLOT_ARM ${CACHE_IMAGE}:$TAG_PLOT_ARM
docker tag freqtrade:$TAG_FREQAI_ARM ${CACHE_IMAGE}:$TAG_FREQAI_ARM docker tag freqtrade:$TAG_FREQAI_ARM ${CACHE_IMAGE}:$TAG_FREQAI_ARM
docker tag freqtrade:$TAG_FREQAI_RL_ARM ${CACHE_IMAGE}:$TAG_FREQAI_RL_ARM docker tag freqtrade:$TAG_FREQAI_RL_ARM ${CACHE_IMAGE}:$TAG_FREQAI_RL_ARM
@ -59,7 +62,6 @@ fi
docker images docker images
# docker push ${IMAGE_NAME}
docker push ${CACHE_IMAGE}:$TAG_PLOT_ARM docker push ${CACHE_IMAGE}:$TAG_PLOT_ARM
docker push ${CACHE_IMAGE}:$TAG_FREQAI_ARM docker push ${CACHE_IMAGE}:$TAG_FREQAI_ARM
docker push ${CACHE_IMAGE}:$TAG_FREQAI_RL_ARM docker push ${CACHE_IMAGE}:$TAG_FREQAI_RL_ARM
@ -82,14 +84,30 @@ docker manifest push -p ${IMAGE_NAME}:${TAG_FREQAI}
docker manifest create ${IMAGE_NAME}:${TAG_FREQAI_RL} ${CACHE_IMAGE}:${TAG_FREQAI_RL} ${CACHE_IMAGE}:${TAG_FREQAI_RL_ARM} docker manifest create ${IMAGE_NAME}:${TAG_FREQAI_RL} ${CACHE_IMAGE}:${TAG_FREQAI_RL} ${CACHE_IMAGE}:${TAG_FREQAI_RL_ARM}
docker manifest push -p ${IMAGE_NAME}:${TAG_FREQAI_RL} docker manifest push -p ${IMAGE_NAME}:${TAG_FREQAI_RL}
# copy images to ghcr.io
alias crane="docker run --rm -i -v $(pwd)/.crane:/home/nonroot/.docker/ gcr.io/go-containerregistry/crane"
mkdir .crane
chmod a+rwx .crane
echo "${GHCR_TOKEN}" | crane auth login ghcr.io -u "${GHCR_USERNAME}" --password-stdin
crane copy ${IMAGE_NAME}:${TAG_FREQAI_RL} ${GHCR_IMAGE_NAME}:${TAG_FREQAI_RL}
crane copy ${IMAGE_NAME}:${TAG_FREQAI} ${GHCR_IMAGE_NAME}:${TAG_FREQAI}
crane copy ${IMAGE_NAME}:${TAG_PLOT} ${GHCR_IMAGE_NAME}:${TAG_PLOT}
crane copy ${IMAGE_NAME}:${TAG} ${GHCR_IMAGE_NAME}:${TAG}
# Tag as latest for develop builds # Tag as latest for develop builds
if [ "${TAG}" = "develop" ]; then if [ "${TAG}" = "develop" ]; then
echo 'Tagging image as latest' echo 'Tagging image as latest'
docker manifest create ${IMAGE_NAME}:latest ${CACHE_IMAGE}:${TAG_ARM} ${IMAGE_NAME}:${TAG_PI} ${CACHE_IMAGE}:${TAG} docker manifest create ${IMAGE_NAME}:latest ${CACHE_IMAGE}:${TAG_ARM} ${IMAGE_NAME}:${TAG_PI} ${CACHE_IMAGE}:${TAG}
docker manifest push -p ${IMAGE_NAME}:latest docker manifest push -p ${IMAGE_NAME}:latest
crane copy ${IMAGE_NAME}:latest ${GHCR_IMAGE_NAME}:latest
fi fi
docker images docker images
rm -rf .crane
# Cleanup old images from arm64 node. # Cleanup old images from arm64 node.
docker image prune -a --force --filter "until=24h" docker image prune -a --force --filter "until=24h"

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@ -2,6 +2,8 @@
# The below assumes a correctly setup docker buildx environment # The below assumes a correctly setup docker buildx environment
IMAGE_NAME=freqtradeorg/freqtrade
CACHE_IMAGE=freqtradeorg/freqtrade_cache
# Replace / with _ to create a valid tag # Replace / with _ to create a valid tag
TAG=$(echo "${BRANCH_NAME}" | sed -e "s/\//_/g") TAG=$(echo "${BRANCH_NAME}" | sed -e "s/\//_/g")
TAG_PLOT=${TAG}_plot TAG_PLOT=${TAG}_plot
@ -11,7 +13,6 @@ TAG_PI="${TAG}_pi"
PI_PLATFORM="linux/arm/v7" PI_PLATFORM="linux/arm/v7"
echo "Running for ${TAG}" echo "Running for ${TAG}"
CACHE_IMAGE=freqtradeorg/freqtrade_cache
CACHE_TAG=${CACHE_IMAGE}:${TAG_PI}_cache CACHE_TAG=${CACHE_IMAGE}:${TAG_PI}_cache
# Add commit and commit_message to docker container # Add commit and commit_message to docker container

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@ -12,6 +12,9 @@ This page provides you some basic concepts on how Freqtrade works and operates.
* **Indicators**: Technical indicators (SMA, EMA, RSI, ...). * **Indicators**: Technical indicators (SMA, EMA, RSI, ...).
* **Limit order**: Limit orders which execute at the defined limit price or better. * **Limit order**: Limit orders which execute at the defined limit price or better.
* **Market order**: Guaranteed to fill, may move price depending on the order size. * **Market order**: Guaranteed to fill, may move price depending on the order size.
* **Current Profit**: Currently pending (unrealized) profit for this trade. This is mainly used throughout the bot and UI.
* **Realized Profit**: Already realized profit. Only relevant in combination with [partial exits](strategy-callbacks.md#adjust-trade-position) - which also explains the calculation logic for this.
* **Total Profit**: Combined realized and unrealized profit. The relative number (%) is calculated against the total investment in this trade.
## Fee handling ## Fee handling
@ -57,10 +60,10 @@ This loop will be repeated again and again until the bot is stopped.
* Load historic data for configured pairlist. * Load historic data for configured pairlist.
* Calls `bot_start()` once. * Calls `bot_start()` once.
* Calls `bot_loop_start()` once.
* Calculate indicators (calls `populate_indicators()` once per pair). * Calculate indicators (calls `populate_indicators()` once per pair).
* Calculate entry / exit signals (calls `populate_entry_trend()` and `populate_exit_trend()` once per pair). * Calculate entry / exit signals (calls `populate_entry_trend()` and `populate_exit_trend()` once per pair).
* Loops per candle simulating entry and exit points. * Loops per candle simulating entry and exit points.
* Calls `bot_loop_start()` strategy callback.
* Check for Order timeouts, either via the `unfilledtimeout` configuration, or via `check_entry_timeout()` / `check_exit_timeout()` strategy callbacks. * Check for Order timeouts, either via the `unfilledtimeout` configuration, or via `check_entry_timeout()` / `check_exit_timeout()` strategy callbacks.
* Calls `adjust_entry_price()` strategy callback for open entry orders. * Calls `adjust_entry_price()` strategy callback for open entry orders.
* Check for trade entry signals (`enter_long` / `enter_short` columns). * Check for trade entry signals (`enter_long` / `enter_short` columns).

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@ -74,3 +74,8 @@ Webhook terminology changed from "sell" to "exit", and from "buy" to "entry", re
* `webhooksell`, `webhookexit` -> `exit` * `webhooksell`, `webhookexit` -> `exit`
* `webhooksellfill`, `webhookexitfill` -> `exit_fill` * `webhooksellfill`, `webhookexitfill` -> `exit_fill`
* `webhooksellcancel`, `webhookexitcancel` -> `exit_cancel` * `webhooksellcancel`, `webhookexitcancel` -> `exit_cancel`
## Removal of `populate_any_indicators`
version 2023.3 saw the removal of `populate_any_indicators` in favor of split methods for feature engineering and targets. Please read the [migration document](strategy_migration.md#freqai-strategy) for full details.

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@ -24,7 +24,7 @@ This will spin up a local server (usually on port 8000) so you can see if everyt
To configure a development environment, you can either use the provided [DevContainer](#devcontainer-setup), or use the `setup.sh` script and answer "y" when asked "Do you want to install dependencies for dev [y/N]? ". To configure a development environment, you can either use the provided [DevContainer](#devcontainer-setup), or use the `setup.sh` script and answer "y" when asked "Do you want to install dependencies for dev [y/N]? ".
Alternatively (e.g. if your system is not supported by the setup.sh script), follow the manual installation process and run `pip3 install -e .[all]`. Alternatively (e.g. if your system is not supported by the setup.sh script), follow the manual installation process and run `pip3 install -e .[all]`.
This will install all required tools for development, including `pytest`, `flake8`, `mypy`, and `coveralls`. This will install all required tools for development, including `pytest`, `ruff`, `mypy`, and `coveralls`.
Then install the git hook scripts by running `pre-commit install`, so your changes will be verified locally before committing. Then install the git hook scripts by running `pre-commit install`, so your changes will be verified locally before committing.
This avoids a lot of waiting for CI already, as some basic formatting checks are done locally on your machine. This avoids a lot of waiting for CI already, as some basic formatting checks are done locally on your machine.

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@ -46,7 +46,7 @@ Mandatory parameters are marked as **Required** and have to be set in one of the
| `outlier_protection_percentage` | Enable to prevent outlier detection methods from discarding too much data. If more than `outlier_protection_percentage` % of points are detected as outliers by the SVM or DBSCAN, FreqAI will log a warning message and ignore outlier detection, i.e., the original dataset will be kept intact. If the outlier protection is triggered, no predictions will be made based on the training dataset. <br> **Datatype:** Float. <br> Default: `30`. | `outlier_protection_percentage` | Enable to prevent outlier detection methods from discarding too much data. If more than `outlier_protection_percentage` % of points are detected as outliers by the SVM or DBSCAN, FreqAI will log a warning message and ignore outlier detection, i.e., the original dataset will be kept intact. If the outlier protection is triggered, no predictions will be made based on the training dataset. <br> **Datatype:** Float. <br> Default: `30`.
| `reverse_train_test_order` | Split the feature dataset (see below) and use the latest data split for training and test on historical split of the data. This allows the model to be trained up to the most recent data point, while avoiding overfitting. However, you should be careful to understand the unorthodox nature of this parameter before employing it. <br> **Datatype:** Boolean. <br> Default: `False` (no reversal). | `reverse_train_test_order` | Split the feature dataset (see below) and use the latest data split for training and test on historical split of the data. This allows the model to be trained up to the most recent data point, while avoiding overfitting. However, you should be careful to understand the unorthodox nature of this parameter before employing it. <br> **Datatype:** Boolean. <br> Default: `False` (no reversal).
| `shuffle_after_split` | Split the data into train and test sets, and then shuffle both sets individually. <br> **Datatype:** Boolean. <br> Default: `False`. | `shuffle_after_split` | Split the data into train and test sets, and then shuffle both sets individually. <br> **Datatype:** Boolean. <br> Default: `False`.
| `buffer_train_data_candles` | Cut `buffer_train_data_candles` off the beginning and end of the training data *after* the indicators were populated. The main example use is when predicting maxima and minima, the argrelextrema function cannot know the maxima/minima at the edges of the timerange. To improve model accuracy, it is best to compute argrelextrema on the full timerange and then use this function to cut off the edges (buffer) by the kernel. In another case, if the targets are set to a shifted price movement, this buffer is unnecessary because the shifted candles at the end of the timerange will be NaN and FreqAI will automatically cut those off of the training dataset.<br> **Datatype:** Boolean. <br> Default: `False`. | `buffer_train_data_candles` | Cut `buffer_train_data_candles` off the beginning and end of the training data *after* the indicators were populated. The main example use is when predicting maxima and minima, the argrelextrema function cannot know the maxima/minima at the edges of the timerange. To improve model accuracy, it is best to compute argrelextrema on the full timerange and then use this function to cut off the edges (buffer) by the kernel. In another case, if the targets are set to a shifted price movement, this buffer is unnecessary because the shifted candles at the end of the timerange will be NaN and FreqAI will automatically cut those off of the training dataset.<br> **Datatype:** Integer. <br> Default: `0`.
### Data split parameters ### Data split parameters
@ -84,6 +84,7 @@ Mandatory parameters are marked as **Required** and have to be set in one of the
| `add_state_info` | Tell FreqAI to include state information in the feature set for training and inferencing. The current state variables include trade duration, current profit, trade position. This is only available in dry/live runs, and is automatically switched to false for backtesting. <br> **Datatype:** bool. <br> Default: `False`. | `add_state_info` | Tell FreqAI to include state information in the feature set for training and inferencing. The current state variables include trade duration, current profit, trade position. This is only available in dry/live runs, and is automatically switched to false for backtesting. <br> **Datatype:** bool. <br> Default: `False`.
| `net_arch` | Network architecture which is well described in [`stable_baselines3` doc](https://stable-baselines3.readthedocs.io/en/master/guide/custom_policy.html#examples). In summary: `[<shared layers>, dict(vf=[<non-shared value network layers>], pi=[<non-shared policy network layers>])]`. By default this is set to `[128, 128]`, which defines 2 shared hidden layers with 128 units each. | `net_arch` | Network architecture which is well described in [`stable_baselines3` doc](https://stable-baselines3.readthedocs.io/en/master/guide/custom_policy.html#examples). In summary: `[<shared layers>, dict(vf=[<non-shared value network layers>], pi=[<non-shared policy network layers>])]`. By default this is set to `[128, 128]`, which defines 2 shared hidden layers with 128 units each.
| `randomize_starting_position` | Randomize the starting point of each episode to avoid overfitting. <br> **Datatype:** bool. <br> Default: `False`. | `randomize_starting_position` | Randomize the starting point of each episode to avoid overfitting. <br> **Datatype:** bool. <br> Default: `False`.
| `drop_ohlc_from_features` | Do not include the normalized ohlc data in the feature set passed to the agent during training (ohlc will still be used for driving the environment in all cases) <br> **Datatype:** Boolean. <br> **Default:** `False`
### Additional parameters ### Additional parameters

View File

@ -55,7 +55,7 @@ where `ReinforcementLearner` will use the templated `ReinforcementLearner` from
dataframe["&-action"] = 0 dataframe["&-action"] = 0
``` ```
Most of the function remains the same as for typical Regressors, however, the function above shows how the strategy must pass the raw price data to the agent so that it has access to raw OHLCV in the training environment: Most of the function remains the same as for typical Regressors, however, the function below shows how the strategy must pass the raw price data to the agent so that it has access to raw OHLCV in the training environment:
```python ```python
def feature_engineering_standard(self, dataframe, **kwargs): def feature_engineering_standard(self, dataframe, **kwargs):
@ -176,9 +176,11 @@ As you begin to modify the strategy and the prediction model, you will quickly r
factor = 100 factor = 100
pair = self.pair.replace(':', '')
# you can use feature values from dataframe # you can use feature values from dataframe
# Assumes the shifted RSI indicator has been generated in the strategy. # Assumes the shifted RSI indicator has been generated in the strategy.
rsi_now = self.raw_features[f"%-rsi-period-10_shift-1_{self.pair}_" rsi_now = self.raw_features[f"%-rsi-period-10_shift-1_{pair}_"
f"{self.config['timeframe']}"].iloc[self._current_tick] f"{self.config['timeframe']}"].iloc[self._current_tick]
# reward agent for entering trades # reward agent for entering trades
@ -246,13 +248,13 @@ FreqAI also provides a built in episodic summary logger called `self.tensorboard
""" """
def calculate_reward(self, action: int) -> float: def calculate_reward(self, action: int) -> float:
if not self._is_valid(action): if not self._is_valid(action):
self.tensorboard_log("is_valid") self.tensorboard_log("invalid")
return -2 return -2
``` ```
!!! Note !!! Note
The `self.tensorboard_log()` function is designed for tracking incremented objects only i.e. events, actions inside the training environment. If the event of interest is a float, the float can be passed as the second argument e.g. `self.tensorboard_log("float_metric1", 0.23)` would add 0.23 to `float_metric`. In this case you can also disable incrementing using `inc=False` parameter. The `self.tensorboard_log()` function is designed for tracking incremented objects only i.e. events, actions inside the training environment. If the event of interest is a float, the float can be passed as the second argument e.g. `self.tensorboard_log("float_metric1", 0.23)`. In this case the metric values are not incremented.
### Choosing a base environment ### Choosing a base environment

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@ -128,6 +128,9 @@ The FreqAI specific parameter `label_period_candles` defines the offset (number
You can choose to adopt a continual learning scheme by setting `"continual_learning": true` in the config. By enabling `continual_learning`, after training an initial model from scratch, subsequent trainings will start from the final model state of the preceding training. This gives the new model a "memory" of the previous state. By default, this is set to `False` which means that all new models are trained from scratch, without input from previous models. You can choose to adopt a continual learning scheme by setting `"continual_learning": true` in the config. By enabling `continual_learning`, after training an initial model from scratch, subsequent trainings will start from the final model state of the preceding training. This gives the new model a "memory" of the previous state. By default, this is set to `False` which means that all new models are trained from scratch, without input from previous models.
???+ danger "Continual learning enforces a constant parameter space"
Since `continual_learning` means that the model parameter space *cannot* change between trainings, `principal_component_analysis` is automatically disabled when `continual_learning` is enabled. Hint: PCA changes the parameter space and the number of features, learn more about PCA [here](freqai-feature-engineering.md#data-dimensionality-reduction-with-principal-component-analysis).
## Hyperopt ## Hyperopt
You can hyperopt using the same command as for [typical Freqtrade hyperopt](hyperopt.md): You can hyperopt using the same command as for [typical Freqtrade hyperopt](hyperopt.md):

View File

@ -71,6 +71,10 @@ pip install -r requirements-freqai.txt
!!! Note !!! Note
Catboost will not be installed on arm devices (raspberry, Mac M1, ARM based VPS, ...), since it does not provide wheels for this platform. Catboost will not be installed on arm devices (raspberry, Mac M1, ARM based VPS, ...), since it does not provide wheels for this platform.
!!! Note "python 3.11"
Some dependencies (Catboost, Torch) currently don't support python 3.11. Freqtrade therefore only supports python 3.10 for these models/dependencies.
Tests involving these dependencies are skipped on 3.11.
### Usage with docker ### Usage with docker
If you are using docker, a dedicated tag with FreqAI dependencies is available as `:freqai`. As such - you can replace the image line in your docker compose file with `image: freqtradeorg/freqtrade:develop_freqai`. This image contains the regular FreqAI dependencies. Similar to native installs, Catboost will not be available on ARM based devices. If you are using docker, a dedicated tag with FreqAI dependencies is available as `:freqai`. As such - you can replace the image line in your docker compose file with `image: freqtradeorg/freqtrade:develop_freqai`. This image contains the regular FreqAI dependencies. Similar to native installs, Catboost will not be available on ARM based devices.

View File

@ -149,7 +149,7 @@ The below example assumes a timeframe of 1 hour:
* Locks each pair after selling for an additional 5 candles (`CooldownPeriod`), giving other pairs a chance to get filled. * Locks each pair after selling for an additional 5 candles (`CooldownPeriod`), giving other pairs a chance to get filled.
* Stops trading for 4 hours (`4 * 1h candles`) if the last 2 days (`48 * 1h candles`) had 20 trades, which caused a max-drawdown of more than 20%. (`MaxDrawdown`). * Stops trading for 4 hours (`4 * 1h candles`) if the last 2 days (`48 * 1h candles`) had 20 trades, which caused a max-drawdown of more than 20%. (`MaxDrawdown`).
* Stops trading if more than 4 stoploss occur for all pairs within a 1 day (`24 * 1h candles`) limit (`StoplossGuard`). * Stops trading if more than 4 stoploss occur for all pairs within a 1 day (`24 * 1h candles`) limit (`StoplossGuard`).
* Locks all pairs that had 4 Trades within the last 6 hours (`6 * 1h candles`) with a combined profit ratio of below 0.02 (<2%) (`LowProfitPairs`). * Locks all pairs that had 2 Trades within the last 6 hours (`6 * 1h candles`) with a combined profit ratio of below 0.02 (<2%) (`LowProfitPairs`).
* Locks all pairs for 2 candles that had a profit of below 0.01 (<1%) within the last 24h (`24 * 1h candles`), a minimum of 4 trades. * Locks all pairs for 2 candles that had a profit of below 0.01 (<1%) within the last 24h (`24 * 1h candles`), a minimum of 4 trades.
``` python ``` python

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@ -290,10 +290,8 @@ cd freqtrade
#### Freqtrade install: Conda Environment #### Freqtrade install: Conda Environment
Prepare conda-freqtrade environment, using file `environment.yml`, which exist in main freqtrade directory
```bash ```bash
conda env create -n freqtrade-conda -f environment.yml conda create --name freqtrade python=3.10
``` ```
!!! Note "Creating Conda Environment" !!! Note "Creating Conda Environment"
@ -302,12 +300,9 @@ conda env create -n freqtrade-conda -f environment.yml
```bash ```bash
# choose your own packages # choose your own packages
conda env create -n [name of the environment] [python version] [packages] conda env create -n [name of the environment] [python version] [packages]
# point to file with packages
conda env create -n [name of the environment] -f [file]
``` ```
#### Enter/exit freqtrade-conda environment #### Enter/exit freqtrade environment
To check available environments, type To check available environments, type
@ -319,7 +314,7 @@ Enter installed environment
```bash ```bash
# enter conda environment # enter conda environment
conda activate freqtrade-conda conda activate freqtrade
# exit conda environment - don't do it now # exit conda environment - don't do it now
conda deactivate conda deactivate
@ -329,6 +324,7 @@ Install last python dependencies with pip
```bash ```bash
python3 -m pip install --upgrade pip python3 -m pip install --upgrade pip
python3 -m pip install -r requirements.txt
python3 -m pip install -e . python3 -m pip install -e .
``` ```
@ -336,7 +332,7 @@ Patch conda libta-lib (Linux only)
```bash ```bash
# Ensure that the environment is active! # Ensure that the environment is active!
conda activate freqtrade-conda conda activate freqtrade
cd build_helpers cd build_helpers
bash install_ta-lib.sh ${CONDA_PREFIX} nosudo bash install_ta-lib.sh ${CONDA_PREFIX} nosudo
@ -355,8 +351,8 @@ conda env list
# activate base environment # activate base environment
conda activate conda activate
# activate freqtrade-conda environment # activate freqtrade environment
conda activate freqtrade-conda conda activate freqtrade
#deactivate any conda environments #deactivate any conda environments
conda deactivate conda deactivate

View File

@ -42,14 +42,14 @@ Enable subscribing to an instance by adding the `external_message_consumer` sect
| `producers` | **Required.** List of producers <br> **Datatype:** Array. | `producers` | **Required.** List of producers <br> **Datatype:** Array.
| `producers.name` | **Required.** Name of this producer. This name must be used in calls to `get_producer_pairs()` and `get_producer_df()` if more than one producer is used.<br> **Datatype:** string | `producers.name` | **Required.** Name of this producer. This name must be used in calls to `get_producer_pairs()` and `get_producer_df()` if more than one producer is used.<br> **Datatype:** string
| `producers.host` | **Required.** The hostname or IP address from your producer.<br> **Datatype:** string | `producers.host` | **Required.** The hostname or IP address from your producer.<br> **Datatype:** string
| `producers.port` | **Required.** The port matching the above host.<br> **Datatype:** string | `producers.port` | **Required.** The port matching the above host.<br>*Defaults to `8080`.*<br> **Datatype:** Integer
| `producers.secure` | **Optional.** Use ssl in websockets connection. Default False.<br> **Datatype:** string | `producers.secure` | **Optional.** Use ssl in websockets connection. Default False.<br> **Datatype:** string
| `producers.ws_token` | **Required.** `ws_token` as configured on the producer.<br> **Datatype:** string | `producers.ws_token` | **Required.** `ws_token` as configured on the producer.<br> **Datatype:** string
| | **Optional settings** | | **Optional settings**
| `wait_timeout` | Timeout until we ping again if no message is received. <br>*Defaults to `300`.*<br> **Datatype:** Integer - in seconds. | `wait_timeout` | Timeout until we ping again if no message is received. <br>*Defaults to `300`.*<br> **Datatype:** Integer - in seconds.
| `wait_timeout` | Ping timeout <br>*Defaults to `10`.*<br> **Datatype:** Integer - in seconds. | `ping_timeout` | Ping timeout <br>*Defaults to `10`.*<br> **Datatype:** Integer - in seconds.
| `sleep_time` | Sleep time before retrying to connect.<br>*Defaults to `10`.*<br> **Datatype:** Integer - in seconds. | `sleep_time` | Sleep time before retrying to connect.<br>*Defaults to `10`.*<br> **Datatype:** Integer - in seconds.
| `remove_entry_exit_signals` | Remove signal columns from the dataframe (set them to 0) on dataframe receipt.<br>*Defaults to `10`.*<br> **Datatype:** Integer - in seconds. | `remove_entry_exit_signals` | Remove signal columns from the dataframe (set them to 0) on dataframe receipt.<br>*Defaults to `False`.*<br> **Datatype:** Boolean.
| `message_size_limit` | Size limit per message<br>*Defaults to `8`.*<br> **Datatype:** Integer - Megabytes. | `message_size_limit` | Size limit per message<br>*Defaults to `8`.*<br> **Datatype:** Integer - Megabytes.
Instead of (or as well as) calculating indicators in `populate_indicators()` the follower instance listens on the connection to a producer instance's messages (or multiple producer instances in advanced configurations) and requests the producer's most recently analyzed dataframes for each pair in the active whitelist. Instead of (or as well as) calculating indicators in `populate_indicators()` the follower instance listens on the connection to a producer instance's messages (or multiple producer instances in advanced configurations) and requests the producer's most recently analyzed dataframes for each pair in the active whitelist.

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@ -1,6 +1,6 @@
markdown==3.3.7 markdown==3.3.7
mkdocs==1.4.2 mkdocs==1.4.2
mkdocs-material==9.0.13 mkdocs-material==9.1.4
mdx_truly_sane_lists==1.3 mdx_truly_sane_lists==1.3
pymdown-extensions==9.9.2 pymdown-extensions==9.10
jinja2==3.1.2 jinja2==3.1.2

View File

@ -51,7 +51,8 @@ During hyperopt, this runs only once at startup.
## Bot loop start ## Bot loop start
A simple callback which is called once at the start of every bot throttling iteration (roughly every 5 seconds, unless configured differently). A simple callback which is called once at the start of every bot throttling iteration in dry/live mode (roughly every 5
seconds, unless configured differently) or once per candle in backtest/hyperopt mode.
This can be used to perform calculations which are pair independent (apply to all pairs), loading of external data, etc. This can be used to perform calculations which are pair independent (apply to all pairs), loading of external data, etc.
``` python ``` python
@ -61,11 +62,12 @@ class AwesomeStrategy(IStrategy):
# ... populate_* methods # ... populate_* methods
def bot_loop_start(self, **kwargs) -> None: def bot_loop_start(self, current_time: datetime, **kwargs) -> None:
""" """
Called at the start of the bot iteration (one loop). Called at the start of the bot iteration (one loop).
Might be used to perform pair-independent tasks Might be used to perform pair-independent tasks
(e.g. gather some remote resource for comparison) (e.g. gather some remote resource for comparison)
: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. :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
""" """
if self.config['runmode'].value in ('live', 'dry_run'): if self.config['runmode'].value in ('live', 'dry_run'):
@ -316,11 +318,11 @@ class AwesomeStrategy(IStrategy):
# evaluate highest to lowest, so that highest possible stop is used # evaluate highest to lowest, so that highest possible stop is used
if current_profit > 0.40: if current_profit > 0.40:
return stoploss_from_open(0.25, current_profit, is_short=trade.is_short) return stoploss_from_open(0.25, current_profit, is_short=trade.is_short, leverage=trade.leverage)
elif current_profit > 0.25: elif current_profit > 0.25:
return stoploss_from_open(0.15, current_profit, is_short=trade.is_short) return stoploss_from_open(0.15, current_profit, is_short=trade.is_short, leverage=trade.leverage)
elif current_profit > 0.20: elif current_profit > 0.20:
return stoploss_from_open(0.07, current_profit, is_short=trade.is_short) return stoploss_from_open(0.07, current_profit, is_short=trade.is_short, leverage=trade.leverage)
# return maximum stoploss value, keeping current stoploss price unchanged # return maximum stoploss value, keeping current stoploss price unchanged
return 1 return 1

View File

@ -881,7 +881,7 @@ All columns of the informative dataframe will be available on the returning data
### *stoploss_from_open()* ### *stoploss_from_open()*
Stoploss values returned from `custom_stoploss` must specify a percentage relative to `current_rate`, but sometimes you may want to specify a stoploss relative to the open price instead. `stoploss_from_open()` is a helper function to calculate a stoploss value that can be returned from `custom_stoploss` which will be equivalent to the desired percentage above the open price. Stoploss values returned from `custom_stoploss` must specify a percentage relative to `current_rate`, but sometimes you may want to specify a stoploss relative to the entry point instead. `stoploss_from_open()` is a helper function to calculate a stoploss value that can be returned from `custom_stoploss` which will be equivalent to the desired trade profit above the entry point.
??? Example "Returning a stoploss relative to the open price from the custom stoploss function" ??? Example "Returning a stoploss relative to the open price from the custom stoploss function"
@ -889,6 +889,8 @@ Stoploss values returned from `custom_stoploss` must specify a percentage relati
If we want a stop price at 7% above the open price we can call `stoploss_from_open(0.07, current_profit, False)` which will return `0.1157024793`. 11.57% below $121 is $107, which is the same as 7% above $100. If we want a stop price at 7% above the open price we can call `stoploss_from_open(0.07, current_profit, False)` which will return `0.1157024793`. 11.57% below $121 is $107, which is the same as 7% above $100.
This function will consider leverage - so at 10x leverage, the actual stoploss would be 0.7% above $100 (0.7% * 10x = 7%).
``` python ``` python
@ -907,7 +909,7 @@ Stoploss values returned from `custom_stoploss` must specify a percentage relati
# once the profit has risen above 10%, keep the stoploss at 7% above the open price # once the profit has risen above 10%, keep the stoploss at 7% above the open price
if current_profit > 0.10: if current_profit > 0.10:
return stoploss_from_open(0.07, current_profit, is_short=trade.is_short) return stoploss_from_open(0.07, current_profit, is_short=trade.is_short, leverage=trade.leverage)
return 1 return 1
@ -954,12 +956,14 @@ In some situations it may be confusing to deal with stops relative to current ra
## Additional data (Wallets) ## Additional data (Wallets)
The strategy provides access to the `Wallets` object. This contains the current balances on the exchange. The strategy provides access to the `wallets` object. This contains the current balances on the exchange.
!!! Note !!! Note "Backtesting / Hyperopt"
Wallets is not available during backtesting / hyperopt. Wallets behaves differently depending on the function it's called.
Within `populate_*()` methods, it'll return the full wallet as configured.
Within [callbacks](strategy-callbacks.md), you'll get the wallet state corresponding to the actual simulated wallet at that point in the simulation process.
Please always check if `Wallets` is available to avoid failures during backtesting. Please always check if `wallets` is available to avoid failures during backtesting.
``` python ``` python
if self.wallets: if self.wallets:
@ -1037,10 +1041,9 @@ from datetime import timedelta, datetime, timezone
# Within populate indicators (or populate_buy): # Within populate indicators (or populate_buy):
if self.config['runmode'].value in ('live', 'dry_run'): if self.config['runmode'].value in ('live', 'dry_run'):
# fetch closed trades for the last 2 days # fetch closed trades for the last 2 days
trades = Trade.get_trades([Trade.pair == metadata['pair'], trades = Trade.get_trades_proxy(
Trade.open_date > datetime.utcnow() - timedelta(days=2), pair=metadata['pair'], is_open=False,
Trade.is_open.is_(False), open_date=datetime.now(timezone.utc) - timedelta(days=2))
]).all()
# Analyze the conditions you'd like to lock the pair .... will probably be different for every strategy # Analyze the conditions you'd like to lock the pair .... will probably be different for every strategy
sumprofit = sum(trade.close_profit for trade in trades) sumprofit = sum(trade.close_profit for trade in trades)
if sumprofit < 0: if sumprofit < 0:

View File

@ -152,7 +152,7 @@ You can create your own keyboard in `config.json`:
!!! Note "Supported Commands" !!! Note "Supported Commands"
Only the following commands are allowed. Command arguments are not supported! Only the following commands are allowed. Command arguments are not supported!
`/start`, `/stop`, `/status`, `/status table`, `/trades`, `/profit`, `/performance`, `/daily`, `/stats`, `/count`, `/locks`, `/balance`, `/stopentry`, `/reload_config`, `/show_config`, `/logs`, `/whitelist`, `/blacklist`, `/edge`, `/help`, `/version` `/start`, `/stop`, `/status`, `/status table`, `/trades`, `/profit`, `/performance`, `/daily`, `/stats`, `/count`, `/locks`, `/balance`, `/stopentry`, `/reload_config`, `/show_config`, `/logs`, `/whitelist`, `/blacklist`, `/edge`, `/help`, `/version`, `/marketdir`
## Telegram commands ## Telegram commands
@ -179,6 +179,7 @@ official commands. You can ask at any moment for help with `/help`.
| `/count` | Displays number of trades used and available | `/count` | Displays number of trades used and available
| `/locks` | Show currently locked pairs. | `/locks` | Show currently locked pairs.
| `/unlock <pair or lock_id>` | Remove the lock for this pair (or for this lock id). | `/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.
| **Modify Trade states** | | **Modify Trade states** |
| `/forceexit <trade_id> | /fx <tradeid>` | Instantly exits the given trade (Ignoring `minimum_roi`). | `/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`). | `/forceexit all | /fx all` | Instantly exits all open trades (Ignoring `minimum_roi`).
@ -242,7 +243,7 @@ Enter Tag is configurable via Strategy.
> **Enter Tag:** Awesome Long Signal > **Enter Tag:** Awesome Long Signal
> **Open Rate:** `0.00007489` > **Open Rate:** `0.00007489`
> **Current Rate:** `0.00007489` > **Current Rate:** `0.00007489`
> **Current Profit:** `12.95%` > **Unrealized Profit:** `12.95%`
> **Stoploss:** `0.00007389 (-0.02%)` > **Stoploss:** `0.00007389 (-0.02%)`
### /status table ### /status table
@ -416,3 +417,27 @@ ARDR/ETH 0.366667 0.143059 -0.01
### /version ### /version
> **Version:** `0.14.3` > **Version:** `0.14.3`
### /marketdir
If a market direction is provided the command updates the user managed variable that represents the current market direction.
This variable is not set to any valid market direction on bot startup and must be set by the user. The example below is for `/marketdir long`:
```
Successfully updated marketdirection from none to long.
```
If no market direction is provided the command outputs the currently set market directions. The example below is for `/marketdir`:
```
Currently set marketdirection: even
```
You can use the market direction in your strategy via `self.market_direction`.
!!! Warning "Bot restarts"
Please note that the market direction is not persisted, and will be reset after a bot restart/reload.
!!! Danger "Backtesting"
As this value/variable is intended to be changed manually in dry/live trading.
Strategies using `market_direction` will probably not produce reliable, reproducible results (changes to this variable will not be reflected for backtesting). Use at your own risk.

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@ -955,3 +955,47 @@ Print trades with id 2 and 3 as json
``` bash ``` bash
freqtrade show-trades --db-url sqlite:///tradesv3.sqlite --trade-ids 2 3 --print-json freqtrade show-trades --db-url sqlite:///tradesv3.sqlite --trade-ids 2 3 --print-json
``` ```
### Strategy-Updater
Updates listed strategies or all strategies within the strategies folder to be v3 compliant.
If the command runs without --strategy-list then all strategies inside the strategies folder will be converted.
Your original strategy will remain available in the `user_data/strategies_orig_updater/` directory.
!!! Warning "Conversion results"
Strategy updater will work on a "best effort" approach. Please do your due diligence and verify the results of the conversion.
We also recommend to run a python formatter (e.g. `black`) to format results in a sane manner.
```
usage: freqtrade strategy-updater [-h] [-v] [--logfile FILE] [-V] [-c PATH]
[-d PATH] [--userdir PATH]
[--strategy-list STRATEGY_LIST [STRATEGY_LIST ...]]
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`
Common arguments:
-v, --verbose Verbose mode (-vv for more, -vvv to get all messages).
--logfile FILE, --log-file FILE
Log to the file specified. Special values are:
'syslog', 'journald'. See the documentation for more
details.
-V, --version show program's version number and exit
-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.
-d PATH, --datadir PATH, --data-dir PATH
Path to directory with historical backtesting data.
--userdir PATH, --user-data-dir PATH
Path to userdata directory.
```

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@ -26,7 +26,7 @@ Install ta-lib according to the [ta-lib documentation](https://github.com/mrjbq7
As compiling from source on windows has heavy dependencies (requires a partial visual studio installation), there is also a repository of unofficial pre-compiled windows Wheels [here](https://www.lfd.uci.edu/~gohlke/pythonlibs/#ta-lib), which need to be downloaded and installed using `pip install TA_Lib-0.4.25-cp38-cp38-win_amd64.whl` (make sure to use the version matching your python version). As compiling from source on windows has heavy dependencies (requires a partial visual studio installation), there is also a repository of unofficial pre-compiled windows Wheels [here](https://www.lfd.uci.edu/~gohlke/pythonlibs/#ta-lib), which need to be downloaded and installed using `pip install TA_Lib-0.4.25-cp38-cp38-win_amd64.whl` (make sure to use the version matching your python version).
Freqtrade provides these dependencies for the latest 3 Python versions (3.8, 3.9 and 3.10) and for 64bit Windows. Freqtrade provides these dependencies for the latest 3 Python versions (3.8, 3.9, 3.10 and 3.11) and for 64bit Windows.
Other versions must be downloaded from the above link. Other versions must be downloaded from the above link.
``` powershell ``` powershell

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@ -1,75 +0,0 @@
name: freqtrade
channels:
- conda-forge
# - defaults
dependencies:
# 1/4 req main
- python>=3.8,<=3.10
- numpy
- pandas
- pip
- py-find-1st
- aiohttp
- SQLAlchemy
- python-telegram-bot<20.0.0
- arrow
- cachetools
- requests
- urllib3
- jsonschema
- TA-Lib
- tabulate
- jinja2
- blosc
- sdnotify
- fastapi
- uvicorn
- pyjwt
- aiofiles
- psutil
- colorama
- questionary
- prompt-toolkit
- schedule
- python-dateutil
- joblib
- pyarrow
# ============================
# 2/4 req dev
- coveralls
- flake8
- mypy
- pytest
- pytest-asyncio
- pytest-cov
- pytest-mock
- isort
- nbconvert
# ============================
# 3/4 req hyperopt
- scipy
- scikit-learn<1.2.0
- filelock
- scikit-optimize
- progressbar2
# ============================
# 4/4 req plot
- plotly
- jupyter
- pip:
- pycoingecko
# - py_find_1st
- tables
- pytest-random-order
- ccxt
- flake8-tidy-imports
- -e .
# - python-rapidjso

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@ -1,5 +1,5 @@
""" Freqtrade bot """ """ Freqtrade bot """
__version__ = '2023.2' __version__ = '2023.3'
if 'dev' in __version__: if 'dev' in __version__:
from pathlib import Path from pathlib import Path

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@ -22,5 +22,6 @@ from freqtrade.commands.optimize_commands import (start_backtesting, start_backt
start_edge, start_hyperopt) start_edge, start_hyperopt)
from freqtrade.commands.pairlist_commands import start_test_pairlist from freqtrade.commands.pairlist_commands import start_test_pairlist
from freqtrade.commands.plot_commands import start_plot_dataframe, start_plot_profit from freqtrade.commands.plot_commands import start_plot_dataframe, start_plot_profit
from freqtrade.commands.strategy_utils_commands import start_strategy_update
from freqtrade.commands.trade_commands import start_trading from freqtrade.commands.trade_commands import start_trading
from freqtrade.commands.webserver_commands import start_webserver from freqtrade.commands.webserver_commands import start_webserver

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@ -40,8 +40,8 @@ def setup_analyze_configuration(args: Dict[str, Any], method: RunMode) -> Dict[s
if (not Path(signals_file).exists()): if (not Path(signals_file).exists()):
raise OperationalException( raise OperationalException(
(f"Cannot find latest backtest signals file: {signals_file}." f"Cannot find latest backtest signals file: {signals_file}."
"Run backtesting with `--export signals`.") "Run backtesting with `--export signals`."
) )
return config return config

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@ -111,10 +111,13 @@ ARGS_ANALYZE_ENTRIES_EXITS = ["exportfilename", "analysis_groups", "enter_reason
NO_CONF_REQURIED = ["convert-data", "convert-trade-data", "download-data", "list-timeframes", NO_CONF_REQURIED = ["convert-data", "convert-trade-data", "download-data", "list-timeframes",
"list-markets", "list-pairs", "list-strategies", "list-freqaimodels", "list-markets", "list-pairs", "list-strategies", "list-freqaimodels",
"list-data", "hyperopt-list", "hyperopt-show", "backtest-filter", "list-data", "hyperopt-list", "hyperopt-show", "backtest-filter",
"plot-dataframe", "plot-profit", "show-trades", "trades-to-ohlcv"] "plot-dataframe", "plot-profit", "show-trades", "trades-to-ohlcv",
"strategy-updater"]
NO_CONF_ALLOWED = ["create-userdir", "list-exchanges", "new-strategy"] NO_CONF_ALLOWED = ["create-userdir", "list-exchanges", "new-strategy"]
ARGS_STRATEGY_UTILS = ["strategy_list", "strategy_path", "recursive_strategy_search"]
class Arguments: class Arguments:
""" """
@ -198,8 +201,8 @@ class Arguments:
start_list_freqAI_models, start_list_markets, start_list_freqAI_models, start_list_markets,
start_list_strategies, start_list_timeframes, start_list_strategies, start_list_timeframes,
start_new_config, start_new_strategy, start_plot_dataframe, start_new_config, start_new_strategy, start_plot_dataframe,
start_plot_profit, start_show_trades, start_test_pairlist, start_plot_profit, start_show_trades, start_strategy_update,
start_trading, start_webserver) start_test_pairlist, start_trading, start_webserver)
subparsers = self.parser.add_subparsers(dest='command', subparsers = self.parser.add_subparsers(dest='command',
# Use custom message when no subhandler is added # Use custom message when no subhandler is added
@ -440,3 +443,11 @@ class Arguments:
parents=[_common_parser]) parents=[_common_parser])
webserver_cmd.set_defaults(func=start_webserver) webserver_cmd.set_defaults(func=start_webserver)
self._build_args(optionlist=ARGS_WEBSERVER, parser=webserver_cmd) self._build_args(optionlist=ARGS_WEBSERVER, parser=webserver_cmd)
# Add strategy_updater subcommand
strategy_updater_cmd = subparsers.add_parser('strategy-updater',
help='updates outdated strategy'
'files to the current version',
parents=[_common_parser])
strategy_updater_cmd.set_defaults(func=start_strategy_update)
self._build_args(optionlist=ARGS_STRATEGY_UTILS, parser=strategy_updater_cmd)

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@ -5,7 +5,7 @@ from datetime import datetime, timedelta
from typing import Any, Dict, List from typing import Any, Dict, List
from freqtrade.configuration import TimeRange, setup_utils_configuration from freqtrade.configuration import TimeRange, setup_utils_configuration
from freqtrade.constants import DATETIME_PRINT_FORMAT from freqtrade.constants import DATETIME_PRINT_FORMAT, Config
from freqtrade.data.converter import convert_ohlcv_format, convert_trades_format from freqtrade.data.converter import convert_ohlcv_format, convert_trades_format
from freqtrade.data.history import (convert_trades_to_ohlcv, refresh_backtest_ohlcv_data, from freqtrade.data.history import (convert_trades_to_ohlcv, refresh_backtest_ohlcv_data,
refresh_backtest_trades_data) refresh_backtest_trades_data)
@ -20,15 +20,24 @@ from freqtrade.util.binance_mig import migrate_binance_futures_data
logger = logging.getLogger(__name__) logger = logging.getLogger(__name__)
def _data_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.")
if 'pairs' not in config:
raise OperationalException(
"Downloading data requires a list of pairs. "
"Please check the documentation on how to configure this.")
def start_download_data(args: Dict[str, Any]) -> None: def start_download_data(args: Dict[str, Any]) -> None:
""" """
Download data (former download_backtest_data.py script) Download data (former download_backtest_data.py script)
""" """
config = setup_utils_configuration(args, RunMode.UTIL_EXCHANGE) config = setup_utils_configuration(args, RunMode.UTIL_EXCHANGE)
if 'days' in config and 'timerange' in config: _data_download_sanity(config)
raise OperationalException("--days and --timerange are mutually exclusive. "
"You can only specify one or the other.")
timerange = TimeRange() timerange = TimeRange()
if 'days' in config: if 'days' in config:
time_since = (datetime.now() - timedelta(days=config['days'])).strftime("%Y%m%d") time_since = (datetime.now() - timedelta(days=config['days'])).strftime("%Y%m%d")
@ -40,11 +49,6 @@ def start_download_data(args: Dict[str, Any]) -> None:
# Remove stake-currency to skip checks which are not relevant for datadownload # Remove stake-currency to skip checks which are not relevant for datadownload
config['stake_currency'] = '' config['stake_currency'] = ''
if 'pairs' not in config:
raise OperationalException(
"Downloading data requires a list of pairs. "
"Please check the documentation on how to configure this.")
pairs_not_available: List[str] = [] pairs_not_available: List[str] = []
# Init exchange # Init exchange
@ -200,11 +204,14 @@ def start_list_data(args: Dict[str, Any]) -> None:
pair, timeframe, candle_type, pair, timeframe, candle_type,
*dhc.ohlcv_data_min_max(pair, timeframe, candle_type) *dhc.ohlcv_data_min_max(pair, timeframe, candle_type)
) for pair, timeframe, candle_type in paircombs] ) for pair, timeframe, candle_type in paircombs]
print(tabulate([ print(tabulate([
(pair, timeframe, candle_type, (pair, timeframe, candle_type,
start.strftime(DATETIME_PRINT_FORMAT), start.strftime(DATETIME_PRINT_FORMAT),
end.strftime(DATETIME_PRINT_FORMAT)) end.strftime(DATETIME_PRINT_FORMAT))
for pair, timeframe, candle_type, start, end in paircombs1 for pair, timeframe, candle_type, start, end in sorted(
paircombs1,
key=lambda x: (x[0], timeframe_to_minutes(x[1]), x[2]))
], ],
headers=("Pair", "Timeframe", "Type", 'From', 'To'), headers=("Pair", "Timeframe", "Type", 'From', 'To'),
tablefmt='psql', stralign='right')) tablefmt='psql', stralign='right'))

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@ -1,7 +1,7 @@
import logging import logging
from typing import Any, Dict from typing import Any, Dict
from sqlalchemy import func from sqlalchemy import func, select
from freqtrade.configuration.config_setup import setup_utils_configuration from freqtrade.configuration.config_setup import setup_utils_configuration
from freqtrade.enums import RunMode from freqtrade.enums import RunMode
@ -20,7 +20,7 @@ def start_convert_db(args: Dict[str, Any]) -> None:
config = setup_utils_configuration(args, RunMode.UTIL_NO_EXCHANGE) config = setup_utils_configuration(args, RunMode.UTIL_NO_EXCHANGE)
init_db(config['db_url']) init_db(config['db_url'])
session_target = Trade._session session_target = Trade.session
init_db(config['db_url_from']) init_db(config['db_url_from'])
logger.info("Starting db migration.") logger.info("Starting db migration.")
@ -36,16 +36,16 @@ def start_convert_db(args: Dict[str, Any]) -> None:
session_target.commit() session_target.commit()
for pairlock in PairLock.query: for pairlock in PairLock.get_all_locks():
pairlock_count += 1 pairlock_count += 1
make_transient(pairlock) make_transient(pairlock)
session_target.add(pairlock) session_target.add(pairlock)
session_target.commit() session_target.commit()
# Update sequences # Update sequences
max_trade_id = session_target.query(func.max(Trade.id)).scalar() max_trade_id = session_target.scalar(select(func.max(Trade.id)))
max_order_id = session_target.query(func.max(Order.id)).scalar() max_order_id = session_target.scalar(select(func.max(Order.id)))
max_pairlock_id = session_target.query(func.max(PairLock.id)).scalar() max_pairlock_id = session_target.scalar(select(func.max(PairLock.id)))
set_sequence_ids(session_target.get_bind(), set_sequence_ids(session_target.get_bind(),
trade_id=max_trade_id, trade_id=max_trade_id,

View File

@ -0,0 +1,55 @@
import logging
import sys
import time
from pathlib import Path
from typing import Any, Dict
from freqtrade.configuration import setup_utils_configuration
from freqtrade.enums import RunMode
from freqtrade.resolvers import StrategyResolver
from freqtrade.strategy.strategyupdater import StrategyUpdater
logger = logging.getLogger(__name__)
def start_strategy_update(args: Dict[str, Any]) -> None:
"""
Start the strategy updating script
:param args: Cli args from Arguments()
:return: None
"""
if sys.version_info == (3, 8): # pragma: no cover
sys.exit("Freqtrade strategy updater requires Python version >= 3.9")
config = setup_utils_configuration(args, RunMode.UTIL_NO_EXCHANGE)
strategy_objs = StrategyResolver.search_all_objects(
config, enum_failed=False, recursive=config.get('recursive_strategy_search', False))
filtered_strategy_objs = []
if args['strategy_list']:
filtered_strategy_objs = [
strategy_obj for strategy_obj in strategy_objs
if strategy_obj['name'] in args['strategy_list']
]
else:
# Use all available entries.
filtered_strategy_objs = strategy_objs
processed_locations = set()
for strategy_obj in filtered_strategy_objs:
if strategy_obj['location'] not in processed_locations:
processed_locations.add(strategy_obj['location'])
start_conversion(strategy_obj, config)
def start_conversion(strategy_obj, config):
print(f"Conversion of {Path(strategy_obj['location']).name} started.")
instance_strategy_updater = StrategyUpdater()
start = time.perf_counter()
instance_strategy_updater.start(config, strategy_obj)
elapsed = time.perf_counter() - start
print(f"Conversion of {Path(strategy_obj['location']).name} took {elapsed:.1f} seconds.")

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@ -27,10 +27,7 @@ def _extend_validator(validator_class):
if 'default' in subschema: if 'default' in subschema:
instance.setdefault(prop, subschema['default']) instance.setdefault(prop, subschema['default'])
for error in validate_properties( yield from validate_properties(validator, properties, instance, schema)
validator, properties, instance, schema,
):
yield error
return validators.extend( return validators.extend(
validator_class, {'properties': set_defaults} validator_class, {'properties': set_defaults}

View File

@ -58,7 +58,7 @@ def load_config_file(path: str) -> Dict[str, Any]:
""" """
try: try:
# Read config from stdin if requested in the options # Read config from stdin if requested in the options
with open(path) if path != '-' else sys.stdin as file: with Path(path).open() if path != '-' else sys.stdin as file:
config = rapidjson.load(file, parse_mode=CONFIG_PARSE_MODE) config = rapidjson.load(file, parse_mode=CONFIG_PARSE_MODE)
except FileNotFoundError: except FileNotFoundError:
raise OperationalException( raise OperationalException(

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@ -36,9 +36,10 @@ AVAILABLE_PAIRLISTS = ['StaticPairList', 'VolumePairList', 'ProducerPairList', '
'AgeFilter', 'OffsetFilter', 'PerformanceFilter', 'AgeFilter', 'OffsetFilter', 'PerformanceFilter',
'PrecisionFilter', 'PriceFilter', 'RangeStabilityFilter', 'PrecisionFilter', 'PriceFilter', 'RangeStabilityFilter',
'ShuffleFilter', 'SpreadFilter', 'VolatilityFilter'] 'ShuffleFilter', 'SpreadFilter', 'VolatilityFilter']
AVAILABLE_PROTECTIONS = ['CooldownPeriod', 'LowProfitPairs', 'MaxDrawdown', 'StoplossGuard'] AVAILABLE_PROTECTIONS = ['CooldownPeriod',
AVAILABLE_DATAHANDLERS_TRADES = ['json', 'jsongz', 'hdf5'] 'LowProfitPairs', 'MaxDrawdown', 'StoplossGuard']
AVAILABLE_DATAHANDLERS = AVAILABLE_DATAHANDLERS_TRADES + ['feather', 'parquet'] AVAILABLE_DATAHANDLERS_TRADES = ['json', 'jsongz', 'hdf5', 'feather']
AVAILABLE_DATAHANDLERS = AVAILABLE_DATAHANDLERS_TRADES + ['parquet']
BACKTEST_BREAKDOWNS = ['day', 'week', 'month'] BACKTEST_BREAKDOWNS = ['day', 'week', 'month']
BACKTEST_CACHE_AGE = ['none', 'day', 'week', 'month'] BACKTEST_CACHE_AGE = ['none', 'day', 'week', 'month']
BACKTEST_CACHE_DEFAULT = 'day' BACKTEST_CACHE_DEFAULT = 'day'
@ -588,6 +589,7 @@ CONF_SCHEMA = {
"rl_config": { "rl_config": {
"type": "object", "type": "object",
"properties": { "properties": {
"drop_ohlc_from_features": {"type": "boolean", "default": False},
"train_cycles": {"type": "integer"}, "train_cycles": {"type": "integer"},
"max_trade_duration_candles": {"type": "integer"}, "max_trade_duration_candles": {"type": "integer"},
"add_state_info": {"type": "boolean", "default": False}, "add_state_info": {"type": "boolean", "default": False},

View File

@ -346,7 +346,7 @@ def evaluate_result_multi(results: pd.DataFrame, timeframe: str,
return df_final[df_final['open_trades'] > max_open_trades] return df_final[df_final['open_trades'] > max_open_trades]
def trade_list_to_dataframe(trades: List[LocalTrade]) -> pd.DataFrame: def trade_list_to_dataframe(trades: Union[List[Trade], List[LocalTrade]]) -> pd.DataFrame:
""" """
Convert list of Trade objects to pandas Dataframe Convert list of Trade objects to pandas Dataframe
:param trades: List of trade objects :param trades: List of trade objects
@ -373,7 +373,7 @@ def load_trades_from_db(db_url: str, strategy: Optional[str] = None) -> pd.DataF
filters = [] filters = []
if strategy: if strategy:
filters.append(Trade.strategy == strategy) filters.append(Trade.strategy == strategy)
trades = trade_list_to_dataframe(Trade.get_trades(filters).all()) trades = trade_list_to_dataframe(list(Trade.get_trades(filters).all()))
return trades return trades

View File

@ -21,6 +21,7 @@ from freqtrade.exchange import Exchange, timeframe_to_seconds
from freqtrade.exchange.types import OrderBook from freqtrade.exchange.types import OrderBook
from freqtrade.misc import append_candles_to_dataframe from freqtrade.misc import append_candles_to_dataframe
from freqtrade.rpc import RPCManager from freqtrade.rpc import RPCManager
from freqtrade.rpc.rpc_types import RPCAnalyzedDFMsg
from freqtrade.util import PeriodicCache from freqtrade.util import PeriodicCache
@ -118,8 +119,7 @@ class DataProvider:
:param new_candle: This is a new candle :param new_candle: This is a new candle
""" """
if self.__rpc: if self.__rpc:
self.__rpc.send_msg( msg: RPCAnalyzedDFMsg = {
{
'type': RPCMessageType.ANALYZED_DF, 'type': RPCMessageType.ANALYZED_DF,
'data': { 'data': {
'key': pair_key, 'key': pair_key,
@ -127,7 +127,7 @@ class DataProvider:
'la': datetime.now(timezone.utc) 'la': datetime.now(timezone.utc)
} }
} }
) self.__rpc.send_msg(msg)
if new_candle: if new_candle:
self.__rpc.send_msg({ self.__rpc.send_msg({
'type': RPCMessageType.NEW_CANDLE, 'type': RPCMessageType.NEW_CANDLE,

View File

@ -24,7 +24,7 @@ def _load_signal_candles(backtest_dir: Path):
scpf = Path(backtest_dir.parent / f"{backtest_dir.stem}_signals.pkl") scpf = Path(backtest_dir.parent / f"{backtest_dir.stem}_signals.pkl")
try: try:
scp = open(scpf, "rb") with scpf.open("rb") as scp:
signal_candles = joblib.load(scp) signal_candles = joblib.load(scp)
logger.info(f"Loaded signal candles: {str(scpf)}") logger.info(f"Loaded signal candles: {str(scpf)}")
except Exception as e: except Exception as e:

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@ -4,7 +4,7 @@ from typing import Optional
from pandas import DataFrame, read_feather, to_datetime from pandas import DataFrame, read_feather, to_datetime
from freqtrade.configuration import TimeRange from freqtrade.configuration import TimeRange
from freqtrade.constants import DEFAULT_DATAFRAME_COLUMNS, TradeList from freqtrade.constants import DEFAULT_DATAFRAME_COLUMNS, DEFAULT_TRADES_COLUMNS, TradeList
from freqtrade.enums import CandleType from freqtrade.enums import CandleType
from .idatahandler import IDataHandler from .idatahandler import IDataHandler
@ -92,12 +92,11 @@ class FeatherDataHandler(IDataHandler):
:param data: List of Lists containing trade data, :param data: List of Lists containing trade data,
column sequence as in DEFAULT_TRADES_COLUMNS column sequence as in DEFAULT_TRADES_COLUMNS
""" """
# filename = self._pair_trades_filename(self._datadir, pair) filename = self._pair_trades_filename(self._datadir, pair)
self.create_dir_if_needed(filename)
raise NotImplementedError() tradesdata = DataFrame(data, columns=DEFAULT_TRADES_COLUMNS)
# array = pa.array(data) tradesdata.to_feather(filename, compression_level=9, compression='lz4')
# array
# feather.write_feather(data, filename)
def trades_append(self, pair: str, data: TradeList): def trades_append(self, pair: str, data: TradeList):
""" """
@ -116,14 +115,13 @@ class FeatherDataHandler(IDataHandler):
:param timerange: Timerange to load trades for - currently not implemented :param timerange: Timerange to load trades for - currently not implemented
:return: List of trades :return: List of trades
""" """
raise NotImplementedError() filename = self._pair_trades_filename(self._datadir, pair)
# filename = self._pair_trades_filename(self._datadir, pair) if not filename.exists():
# tradesdata = misc.file_load_json(filename) return []
# if not tradesdata: tradesdata = read_feather(filename)
# return []
# return tradesdata return tradesdata.values.tolist()
@classmethod @classmethod
def _get_file_extension(cls): def _get_file_extension(cls):

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@ -5,6 +5,7 @@ from freqtrade.enums.exitchecktuple import ExitCheckTuple
from freqtrade.enums.exittype import ExitType from freqtrade.enums.exittype import ExitType
from freqtrade.enums.hyperoptstate import HyperoptState from freqtrade.enums.hyperoptstate import HyperoptState
from freqtrade.enums.marginmode import MarginMode from freqtrade.enums.marginmode import MarginMode
from freqtrade.enums.marketstatetype import MarketDirection
from freqtrade.enums.ordertypevalue import OrderTypeValues from freqtrade.enums.ordertypevalue import OrderTypeValues
from freqtrade.enums.pricetype import PriceType from freqtrade.enums.pricetype import PriceType
from freqtrade.enums.rpcmessagetype import NO_ECHO_MESSAGES, RPCMessageType, RPCRequestType from freqtrade.enums.rpcmessagetype import NO_ECHO_MESSAGES, RPCMessageType, RPCRequestType

View File

@ -13,6 +13,9 @@ class CandleType(str, Enum):
FUNDING_RATE = "funding_rate" FUNDING_RATE = "funding_rate"
# BORROW_RATE = "borrow_rate" # * unimplemented # BORROW_RATE = "borrow_rate" # * unimplemented
def __str__(self):
return f"{self.name.lower()}"
@staticmethod @staticmethod
def from_string(value: str) -> 'CandleType': def from_string(value: str) -> 'CandleType':
if not value: if not value:

View File

@ -0,0 +1,15 @@
from enum import Enum
class MarketDirection(Enum):
"""
Enum for various market directions.
"""
LONG = "long"
SHORT = "short"
EVEN = "even"
NONE = "none"
def __str__(self):
# convert to string
return self.value

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@ -4,6 +4,7 @@ from enum import Enum
class RPCMessageType(str, Enum): class RPCMessageType(str, Enum):
STATUS = 'status' STATUS = 'status'
WARNING = 'warning' WARNING = 'warning'
EXCEPTION = 'exception'
STARTUP = 'startup' STARTUP = 'startup'
ENTRY = 'entry' ENTRY = 'entry'
@ -37,5 +38,8 @@ class RPCRequestType(str, Enum):
WHITELIST = 'whitelist' WHITELIST = 'whitelist'
ANALYZED_DF = 'analyzed_df' ANALYZED_DF = 'analyzed_df'
def __str__(self):
return self.value
NO_ECHO_MESSAGES = (RPCMessageType.ANALYZED_DF, RPCMessageType.WHITELIST, RPCMessageType.NEW_CANDLE) NO_ECHO_MESSAGES = (RPCMessageType.ANALYZED_DF, RPCMessageType.WHITELIST, RPCMessageType.NEW_CANDLE)

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@ -10,6 +10,9 @@ class SignalType(Enum):
ENTER_SHORT = "enter_short" ENTER_SHORT = "enter_short"
EXIT_SHORT = "exit_short" EXIT_SHORT = "exit_short"
def __str__(self):
return f"{self.name.lower()}"
class SignalTagType(Enum): class SignalTagType(Enum):
""" """
@ -18,7 +21,13 @@ class SignalTagType(Enum):
ENTER_TAG = "enter_tag" ENTER_TAG = "enter_tag"
EXIT_TAG = "exit_tag" EXIT_TAG = "exit_tag"
def __str__(self):
return f"{self.name.lower()}"
class SignalDirection(str, Enum): class SignalDirection(str, Enum):
LONG = 'long' LONG = 'long'
SHORT = 'short' SHORT = 'short'
def __str__(self):
return f"{self.name.lower()}"

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@ -23,7 +23,7 @@ class Binance(Exchange):
_ft_has: Dict = { _ft_has: Dict = {
"stoploss_on_exchange": True, "stoploss_on_exchange": True,
"stoploss_order_types": {"limit": "stop_loss_limit"}, "stoploss_order_types": {"limit": "stop_loss_limit"},
"order_time_in_force": ['GTC', 'FOK', 'IOC'], "order_time_in_force": ["GTC", "FOK", "IOC", "PO"],
"ohlcv_candle_limit": 1000, "ohlcv_candle_limit": 1000,
"trades_pagination": "id", "trades_pagination": "id",
"trades_pagination_arg": "fromId", "trades_pagination_arg": "fromId",
@ -31,6 +31,7 @@ class Binance(Exchange):
} }
_ft_has_futures: Dict = { _ft_has_futures: Dict = {
"stoploss_order_types": {"limit": "stop", "market": "stop_market"}, "stoploss_order_types": {"limit": "stop", "market": "stop_market"},
"order_time_in_force": ["GTC", "FOK", "IOC"],
"tickers_have_price": False, "tickers_have_price": False,
"floor_leverage": True, "floor_leverage": True,
"stop_price_type_field": "workingType", "stop_price_type_field": "workingType",
@ -195,7 +196,7 @@ class Binance(Exchange):
leverage_tiers_path = ( leverage_tiers_path = (
Path(__file__).parent / 'binance_leverage_tiers.json' Path(__file__).parent / 'binance_leverage_tiers.json'
) )
with open(leverage_tiers_path) as json_file: with leverage_tiers_path.open() as json_file:
return json_load(json_file) return json_load(json_file)
else: else:
try: try:

File diff suppressed because it is too large Load Diff

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@ -27,11 +27,10 @@ class Bybit(Exchange):
""" """
_ft_has: Dict = { _ft_has: Dict = {
"ohlcv_candle_limit": 1000, "ohlcv_candle_limit": 200,
"ohlcv_has_history": False, "ohlcv_has_history": False,
} }
_ft_has_futures: Dict = { _ft_has_futures: Dict = {
"ohlcv_candle_limit": 200,
"ohlcv_has_history": True, "ohlcv_has_history": True,
"mark_ohlcv_timeframe": "4h", "mark_ohlcv_timeframe": "4h",
"funding_fee_timeframe": "8h", "funding_fee_timeframe": "8h",
@ -115,7 +114,7 @@ class Bybit(Exchange):
data = [[x['timestamp'], x['fundingRate'], 0, 0, 0, 0] for x in data] data = [[x['timestamp'], x['fundingRate'], 0, 0, 0, 0] for x in data]
return data return data
def _lev_prep(self, pair: str, leverage: float, side: BuySell): def _lev_prep(self, pair: str, leverage: float, side: BuySell, accept_fail: bool = False):
if self.trading_mode != TradingMode.SPOT: if self.trading_mode != TradingMode.SPOT:
params = {'leverage': leverage} params = {'leverage': leverage}
self.set_margin_mode(pair, self.margin_mode, accept_fail=True, params=params) self.set_margin_mode(pair, self.margin_mode, accept_fail=True, params=params)

View File

@ -60,7 +60,6 @@ class Exchange:
_ft_has_default: Dict = { _ft_has_default: Dict = {
"stoploss_on_exchange": False, "stoploss_on_exchange": False,
"order_time_in_force": ["GTC"], "order_time_in_force": ["GTC"],
"time_in_force_parameter": "timeInForce",
"ohlcv_params": {}, "ohlcv_params": {},
"ohlcv_candle_limit": 500, "ohlcv_candle_limit": 500,
"ohlcv_has_history": True, # Some exchanges (Kraken) don't provide history via ohlcv "ohlcv_has_history": True, # Some exchanges (Kraken) don't provide history via ohlcv
@ -69,6 +68,7 @@ class Exchange:
# Check https://github.com/ccxt/ccxt/issues/10767 for removal of ohlcv_volume_currency # Check https://github.com/ccxt/ccxt/issues/10767 for removal of ohlcv_volume_currency
"ohlcv_volume_currency": "base", # "base" or "quote" "ohlcv_volume_currency": "base", # "base" or "quote"
"tickers_have_quoteVolume": True, "tickers_have_quoteVolume": True,
"tickers_have_bid_ask": True, # bid / ask empty for fetch_tickers
"tickers_have_price": True, "tickers_have_price": True,
"trades_pagination": "time", # Possible are "time" or "id" "trades_pagination": "time", # Possible are "time" or "id"
"trades_pagination_arg": "since", "trades_pagination_arg": "since",
@ -80,6 +80,8 @@ class Exchange:
"fee_cost_in_contracts": False, # Fee cost needs contract conversion "fee_cost_in_contracts": False, # Fee cost needs contract conversion
"needs_trading_fees": False, # use fetch_trading_fees to cache fees "needs_trading_fees": False, # use fetch_trading_fees to cache fees
"order_props_in_contracts": ['amount', 'cost', 'filled', 'remaining'], "order_props_in_contracts": ['amount', 'cost', 'filled', 'remaining'],
# Override createMarketBuyOrderRequiresPrice where ccxt has it wrong
"marketOrderRequiresPrice": False,
} }
_ft_has: Dict = {} _ft_has: Dict = {}
_ft_has_futures: Dict = {} _ft_has_futures: Dict = {}
@ -205,6 +207,8 @@ class Exchange:
and self._api_async.session): and self._api_async.session):
logger.debug("Closing async ccxt session.") logger.debug("Closing async ccxt session.")
self.loop.run_until_complete(self._api_async.close()) self.loop.run_until_complete(self._api_async.close())
if self.loop and not self.loop.is_closed():
self.loop.close()
def validate_config(self, config): def validate_config(self, config):
# Check if timeframe is available # Check if timeframe is available
@ -1018,10 +1022,10 @@ class Exchange:
# Order handling # Order handling
def _lev_prep(self, pair: str, leverage: float, side: BuySell): def _lev_prep(self, pair: str, leverage: float, side: BuySell, accept_fail: bool = False):
if self.trading_mode != TradingMode.SPOT: if self.trading_mode != TradingMode.SPOT:
self.set_margin_mode(pair, self.margin_mode) self.set_margin_mode(pair, self.margin_mode, accept_fail)
self._set_leverage(leverage, pair) self._set_leverage(leverage, pair, accept_fail)
def _get_params( def _get_params(
self, self,
@ -1033,12 +1037,18 @@ class Exchange:
) -> Dict: ) -> Dict:
params = self._params.copy() params = self._params.copy()
if time_in_force != 'GTC' and ordertype != 'market': if time_in_force != 'GTC' and ordertype != 'market':
param = self._ft_has.get('time_in_force_parameter', '') params.update({'timeInForce': time_in_force.upper()})
params.update({param: time_in_force.upper()})
if reduceOnly: if reduceOnly:
params.update({'reduceOnly': True}) params.update({'reduceOnly': True})
return params return params
def _order_needs_price(self, ordertype: str) -> bool:
return (
ordertype != 'market'
or self._api.options.get("createMarketBuyOrderRequiresPrice", False)
or self._ft_has.get('marketOrderRequiresPrice', False)
)
def create_order( def create_order(
self, self,
*, *,
@ -1061,8 +1071,7 @@ class Exchange:
try: try:
# Set the precision for amount and price(rate) as accepted by the exchange # Set the precision for amount and price(rate) as accepted by the exchange
amount = self.amount_to_precision(pair, self._amount_to_contracts(pair, amount)) amount = self.amount_to_precision(pair, self._amount_to_contracts(pair, amount))
needs_price = (ordertype != 'market' needs_price = self._order_needs_price(ordertype)
or self._api.options.get("createMarketBuyOrderRequiresPrice", False))
rate_for_order = self.price_to_precision(pair, rate) if needs_price else None rate_for_order = self.price_to_precision(pair, rate) if needs_price else None
if not reduceOnly: if not reduceOnly:
@ -1086,7 +1095,7 @@ class Exchange:
f'Tried to {side} amount {amount} at rate {rate}.' f'Tried to {side} amount {amount} at rate {rate}.'
f'Message: {e}') from e f'Message: {e}') from e
except ccxt.InvalidOrder as e: except ccxt.InvalidOrder as e:
raise ExchangeError( raise InvalidOrderException(
f'Could not create {ordertype} {side} order on market {pair}. ' f'Could not create {ordertype} {side} order on market {pair}. '
f'Tried to {side} amount {amount} at rate {rate}. ' f'Tried to {side} amount {amount} at rate {rate}. '
f'Message: {e}') from e f'Message: {e}') from e
@ -1136,8 +1145,15 @@ class Exchange:
"sell" else (stop_price >= limit_rate)) "sell" else (stop_price >= limit_rate))
# Ensure rate is less than stop price # Ensure rate is less than stop price
if bad_stop_price: if bad_stop_price:
raise OperationalException( # This can for example happen if the stop / liquidation price is set to 0
'In stoploss limit order, stop price should be more than limit price') # Which is possible if a market-order closes right away.
# The InvalidOrderException will bubble up to exit_positions, where it will be
# handled gracefully.
raise InvalidOrderException(
"In stoploss limit order, stop price should be more than limit price. "
f"Stop price: {stop_price}, Limit price: {limit_rate}, "
f"Limit Price pct: {limit_price_pct}"
)
return limit_rate return limit_rate
def _get_stop_params(self, side: BuySell, ordertype: str, stop_price: float) -> Dict: def _get_stop_params(self, side: BuySell, ordertype: str, stop_price: float) -> Dict:
@ -1200,7 +1216,7 @@ class Exchange:
amount = self.amount_to_precision(pair, self._amount_to_contracts(pair, amount)) amount = self.amount_to_precision(pair, self._amount_to_contracts(pair, amount))
self._lev_prep(pair, leverage, side) self._lev_prep(pair, leverage, side, accept_fail=True)
order = self._api.create_order(symbol=pair, type=ordertype, side=side, order = self._api.create_order(symbol=pair, type=ordertype, side=side,
amount=amount, price=limit_rate, params=params) amount=amount, price=limit_rate, params=params)
self._log_exchange_response('create_stoploss_order', order) self._log_exchange_response('create_stoploss_order', order)
@ -1961,7 +1977,8 @@ class Exchange:
cache: bool, drop_incomplete: bool) -> DataFrame: cache: bool, drop_incomplete: bool) -> DataFrame:
# keeping last candle time as last refreshed time of the pair # keeping last candle time as last refreshed time of the pair
if ticks and cache: if ticks and cache:
self._pairs_last_refresh_time[(pair, timeframe, c_type)] = ticks[-1][0] // 1000 idx = -2 if drop_incomplete and len(ticks) > 1 else -1
self._pairs_last_refresh_time[(pair, timeframe, c_type)] = ticks[idx][0] // 1000
# keeping parsed dataframe in cache # keeping parsed dataframe in cache
ohlcv_df = ohlcv_to_dataframe(ticks, timeframe, pair=pair, fill_missing=True, ohlcv_df = ohlcv_to_dataframe(ticks, timeframe, pair=pair, fill_missing=True,
drop_incomplete=drop_incomplete) drop_incomplete=drop_incomplete)
@ -2034,7 +2051,9 @@ class Exchange:
# Timeframe in seconds # Timeframe in seconds
interval_in_sec = timeframe_to_seconds(timeframe) interval_in_sec = timeframe_to_seconds(timeframe)
plr = self._pairs_last_refresh_time.get((pair, timeframe, candle_type), 0) + interval_in_sec plr = self._pairs_last_refresh_time.get((pair, timeframe, candle_type), 0) + interval_in_sec
return plr < arrow.utcnow().int_timestamp # current,active candle open date
now = int(timeframe_to_prev_date(timeframe).timestamp())
return plr < now
@retrier_async @retrier_async
async def _async_get_candle_history( async def _async_get_candle_history(
@ -2522,7 +2541,6 @@ class Exchange:
self, self,
leverage: float, leverage: float,
pair: Optional[str] = None, pair: Optional[str] = None,
trading_mode: Optional[TradingMode] = None,
accept_fail: bool = False, accept_fail: bool = False,
): ):
""" """
@ -2540,7 +2558,7 @@ class Exchange:
self._log_exchange_response('set_leverage', res) self._log_exchange_response('set_leverage', res)
except ccxt.DDoSProtection as e: except ccxt.DDoSProtection as e:
raise DDosProtection(e) from e raise DDosProtection(e) from e
except ccxt.BadRequest as e: except (ccxt.BadRequest, ccxt.InsufficientFunds) as e:
if not accept_fail: if not accept_fail:
raise TemporaryError( raise TemporaryError(
f'Could not set leverage due to {e.__class__.__name__}. Message: {e}') from e f'Could not set leverage due to {e.__class__.__name__}. Message: {e}') from e
@ -2751,10 +2769,10 @@ class Exchange:
raise OperationalException( raise OperationalException(
f"{self.name} does not support {self.margin_mode} {self.trading_mode}") f"{self.name} does not support {self.margin_mode} {self.trading_mode}")
isolated_liq = None liquidation_price = None
if self._config['dry_run'] or not self.exchange_has("fetchPositions"): if self._config['dry_run'] or not self.exchange_has("fetchPositions"):
isolated_liq = self.dry_run_liquidation_price( liquidation_price = self.dry_run_liquidation_price(
pair=pair, pair=pair,
open_rate=open_rate, open_rate=open_rate,
is_short=is_short, is_short=is_short,
@ -2769,16 +2787,16 @@ class Exchange:
positions = self.fetch_positions(pair) positions = self.fetch_positions(pair)
if len(positions) > 0: if len(positions) > 0:
pos = positions[0] pos = positions[0]
isolated_liq = pos['liquidationPrice'] liquidation_price = pos['liquidationPrice']
if isolated_liq is not None: if liquidation_price is not None:
buffer_amount = abs(open_rate - isolated_liq) * self.liquidation_buffer buffer_amount = abs(open_rate - liquidation_price) * self.liquidation_buffer
isolated_liq = ( liquidation_price_buffer = (
isolated_liq - buffer_amount liquidation_price - buffer_amount
if is_short else if is_short else
isolated_liq + buffer_amount liquidation_price + buffer_amount
) )
return isolated_liq return max(liquidation_price_buffer, 0.0)
else: else:
return None return None

View File

@ -5,7 +5,6 @@ from typing import Any, Dict, List, Optional, Tuple
from freqtrade.constants import BuySell from freqtrade.constants import BuySell
from freqtrade.enums import MarginMode, PriceType, TradingMode from freqtrade.enums import MarginMode, PriceType, TradingMode
from freqtrade.exceptions import OperationalException
from freqtrade.exchange import Exchange from freqtrade.exchange import Exchange
from freqtrade.misc import safe_value_fallback2 from freqtrade.misc import safe_value_fallback2
@ -28,10 +27,13 @@ class Gate(Exchange):
"order_time_in_force": ['GTC', 'IOC'], "order_time_in_force": ['GTC', 'IOC'],
"stoploss_order_types": {"limit": "limit"}, "stoploss_order_types": {"limit": "limit"},
"stoploss_on_exchange": True, "stoploss_on_exchange": True,
"marketOrderRequiresPrice": True,
} }
_ft_has_futures: Dict = { _ft_has_futures: Dict = {
"needs_trading_fees": True, "needs_trading_fees": True,
"marketOrderRequiresPrice": False,
"tickers_have_bid_ask": False,
"fee_cost_in_contracts": False, # Set explicitly to false for clarity "fee_cost_in_contracts": False, # Set explicitly to false for clarity
"order_props_in_contracts": ['amount', 'filled', 'remaining'], "order_props_in_contracts": ['amount', 'filled', 'remaining'],
"stop_price_type_field": "price_type", "stop_price_type_field": "price_type",
@ -49,14 +51,6 @@ class Gate(Exchange):
(TradingMode.FUTURES, MarginMode.ISOLATED) (TradingMode.FUTURES, MarginMode.ISOLATED)
] ]
def validate_ordertypes(self, order_types: Dict) -> None:
if self.trading_mode != TradingMode.FUTURES:
if any(v == 'market' for k, v in order_types.items()):
raise OperationalException(
f'Exchange {self.name} does not support market orders.')
super().validate_stop_ordertypes(order_types)
def _get_params( def _get_params(
self, self,
side: BuySell, side: BuySell,
@ -74,8 +68,7 @@ class Gate(Exchange):
) )
if ordertype == 'market' and self.trading_mode == TradingMode.FUTURES: if ordertype == 'market' and self.trading_mode == TradingMode.FUTURES:
params['type'] = 'market' params['type'] = 'market'
param = self._ft_has.get('time_in_force_parameter', '') params.update({'timeInForce': 'IOC'})
params.update({param: 'IOC'})
return params return params
def get_trades_for_order(self, order_id: str, pair: str, since: datetime, def get_trades_for_order(self, order_id: str, pair: str, since: datetime,

View File

@ -158,7 +158,6 @@ class Kraken(Exchange):
self, self,
leverage: float, leverage: float,
pair: Optional[str] = None, pair: Optional[str] = None,
trading_mode: Optional[TradingMode] = None,
accept_fail: bool = False, accept_fail: bool = False,
): ):
""" """

View File

@ -64,6 +64,7 @@ class Kucoin(Exchange):
# ccxt returns status = 'closed' at the moment - which is information ccxt invented. # ccxt returns status = 'closed' at the moment - which is information ccxt invented.
# Since we rely on status heavily, we must set it to 'open' here. # Since we rely on status heavily, we must set it to 'open' here.
# ref: https://github.com/ccxt/ccxt/pull/16674, (https://github.com/ccxt/ccxt/pull/16553) # ref: https://github.com/ccxt/ccxt/pull/16674, (https://github.com/ccxt/ccxt/pull/16553)
if not self._config['dry_run']:
res['type'] = ordertype res['type'] = ordertype
res['status'] = 'open' res['status'] = 'open'
return res return res

View File

@ -1,14 +1,16 @@
import logging import logging
from typing import Dict, List, Optional, Tuple from typing import Any, Dict, List, Optional, Tuple
import ccxt import ccxt
from freqtrade.constants import BuySell from freqtrade.constants import BuySell
from freqtrade.enums import CandleType, MarginMode, TradingMode from freqtrade.enums import CandleType, MarginMode, TradingMode
from freqtrade.enums.pricetype import PriceType from freqtrade.enums.pricetype import PriceType
from freqtrade.exceptions import DDosProtection, OperationalException, TemporaryError from freqtrade.exceptions import (DDosProtection, OperationalException, RetryableOrderError,
TemporaryError)
from freqtrade.exchange import Exchange, date_minus_candles from freqtrade.exchange import Exchange, date_minus_candles
from freqtrade.exchange.common import retrier from freqtrade.exchange.common import retrier
from freqtrade.misc import safe_value_fallback2
logger = logging.getLogger(__name__) logger = logging.getLogger(__name__)
@ -24,11 +26,13 @@ class Okx(Exchange):
"ohlcv_candle_limit": 100, # Warning, special case with data prior to X months "ohlcv_candle_limit": 100, # Warning, special case with data prior to X months
"mark_ohlcv_timeframe": "4h", "mark_ohlcv_timeframe": "4h",
"funding_fee_timeframe": "8h", "funding_fee_timeframe": "8h",
"stoploss_order_types": {"limit": "limit"},
"stoploss_on_exchange": True,
} }
_ft_has_futures: Dict = { _ft_has_futures: Dict = {
"tickers_have_quoteVolume": False, "tickers_have_quoteVolume": False,
"fee_cost_in_contracts": True, "fee_cost_in_contracts": True,
"stop_price_type_field": "tpTriggerPxType", "stop_price_type_field": "slTriggerPxType",
"stop_price_type_value_mapping": { "stop_price_type_value_mapping": {
PriceType.LAST: "last", PriceType.LAST: "last",
PriceType.MARK: "index", PriceType.MARK: "index",
@ -121,10 +125,9 @@ class Okx(Exchange):
return params return params
@retrier @retrier
def _lev_prep(self, pair: str, leverage: float, side: BuySell): def _lev_prep(self, pair: str, leverage: float, side: BuySell, accept_fail: bool = False):
if self.trading_mode != TradingMode.SPOT and self.margin_mode is not None: if self.trading_mode != TradingMode.SPOT and self.margin_mode is not None:
try: try:
# TODO-lev: Test me properly (check mgnMode passed)
res = self._api.set_leverage( res = self._api.set_leverage(
leverage=leverage, leverage=leverage,
symbol=pair, symbol=pair,
@ -157,3 +160,78 @@ class Okx(Exchange):
pair_tiers = self._leverage_tiers[pair] pair_tiers = self._leverage_tiers[pair]
return pair_tiers[-1]['maxNotional'] / leverage return pair_tiers[-1]['maxNotional'] / leverage
def _get_stop_params(self, side: BuySell, ordertype: str, stop_price: float) -> Dict:
params = self._params.copy()
# Verify if stopPrice works for your exchange!
params.update({'stopLossPrice': stop_price})
if self.trading_mode == TradingMode.FUTURES and self.margin_mode:
params['tdMode'] = self.margin_mode.value
params['posSide'] = self._get_posSide(side, True)
return params
def stoploss_adjust(self, stop_loss: float, order: Dict, side: str) -> bool:
"""
OKX uses non-default stoploss price naming.
"""
if not self._ft_has.get('stoploss_on_exchange'):
raise OperationalException(f"stoploss is not implemented for {self.name}.")
return (
order.get('stopLossPrice', None) is None
or ((side == "sell" and stop_loss > float(order['stopLossPrice'])) or
(side == "buy" and stop_loss < float(order['stopLossPrice'])))
)
def fetch_stoploss_order(self, order_id: str, pair: str, params: Dict = {}) -> Dict:
if self._config['dry_run']:
return self.fetch_dry_run_order(order_id)
try:
params1 = {'stop': True}
order_reg = self._api.fetch_order(order_id, pair, params=params1)
self._log_exchange_response('fetch_stoploss_order', order_reg)
return order_reg
except ccxt.OrderNotFound:
pass
params2 = {'stop': True, 'ordType': 'conditional'}
for method in (self._api.fetch_open_orders, self._api.fetch_closed_orders,
self._api.fetch_canceled_orders):
try:
orders = method(pair, params=params2)
orders_f = [order for order in orders if order['id'] == order_id]
if orders_f:
order = orders_f[0]
if (order['status'] == 'closed'
and (real_order_id := order.get('info', {}).get('ordId')) is not None):
# Once a order triggered, we fetch the regular followup order.
order_reg = self.fetch_order(real_order_id, pair)
self._log_exchange_response('fetch_stoploss_order1', order_reg)
order_reg['id_stop'] = order_reg['id']
order_reg['id'] = order_id
order_reg['type'] = 'stoploss'
order_reg['status_stop'] = 'triggered'
return order_reg
order['type'] = 'stoploss'
return order
except ccxt.BaseError:
pass
raise RetryableOrderError(
f'StoplossOrder not found (pair: {pair} id: {order_id}).')
def get_order_id_conditional(self, order: Dict[str, Any]) -> str:
if order['type'] == 'stop':
return safe_value_fallback2(order, order, 'id_stop', 'id')
return order['id']
def cancel_stoploss_order(self, order_id: str, pair: str, params: Dict = {}) -> Dict:
params1 = {'stop': True}
# 'ordType': 'conditional'
#
return self.cancel_order(
order_id=order_id,
pair=pair,
params=params1,
)

View File

@ -47,7 +47,7 @@ class Base3ActionRLEnv(BaseEnvironment):
self._update_unrealized_total_profit() self._update_unrealized_total_profit()
step_reward = self.calculate_reward(action) step_reward = self.calculate_reward(action)
self.total_reward += step_reward self.total_reward += step_reward
self.tensorboard_log(self.actions._member_names_[action]) self.tensorboard_log(self.actions._member_names_[action], category="actions")
trade_type = None trade_type = None
if self.is_tradesignal(action): if self.is_tradesignal(action):

View File

@ -48,7 +48,7 @@ class Base4ActionRLEnv(BaseEnvironment):
self._update_unrealized_total_profit() self._update_unrealized_total_profit()
step_reward = self.calculate_reward(action) step_reward = self.calculate_reward(action)
self.total_reward += step_reward self.total_reward += step_reward
self.tensorboard_log(self.actions._member_names_[action]) self.tensorboard_log(self.actions._member_names_[action], category="actions")
trade_type = None trade_type = None
if self.is_tradesignal(action): if self.is_tradesignal(action):

View File

@ -49,7 +49,7 @@ class Base5ActionRLEnv(BaseEnvironment):
self._update_unrealized_total_profit() self._update_unrealized_total_profit()
step_reward = self.calculate_reward(action) step_reward = self.calculate_reward(action)
self.total_reward += step_reward self.total_reward += step_reward
self.tensorboard_log(self.actions._member_names_[action]) self.tensorboard_log(self.actions._member_names_[action], category="actions")
trade_type = None trade_type = None
if self.is_tradesignal(action): if self.is_tradesignal(action):

View File

@ -137,7 +137,8 @@ class BaseEnvironment(gym.Env):
self.np_random, seed = seeding.np_random(seed) self.np_random, seed = seeding.np_random(seed)
return [seed] return [seed]
def tensorboard_log(self, metric: str, value: Union[int, float] = 1, inc: bool = True): def tensorboard_log(self, metric: str, value: Optional[Union[int, float]] = None,
inc: Optional[bool] = None, category: str = "custom"):
""" """
Function builds the tensorboard_metrics dictionary Function builds the tensorboard_metrics dictionary
to be parsed by the TensorboardCallback. This to be parsed by the TensorboardCallback. This
@ -149,17 +150,24 @@ class BaseEnvironment(gym.Env):
def calculate_reward(self, action: int) -> float: def calculate_reward(self, action: int) -> float:
if not self._is_valid(action): if not self._is_valid(action):
self.tensorboard_log("is_valid") self.tensorboard_log("invalid")
return -2 return -2
:param metric: metric to be tracked and incremented :param metric: metric to be tracked and incremented
:param value: value to increment `metric` by :param value: `metric` value
:param inc: sets whether the `value` is incremented or not :param inc: (deprecated) sets whether the `value` is incremented or not
:param category: `metric` category
""" """
if not inc or metric not in self.tensorboard_metrics: increment = True if value is None else False
self.tensorboard_metrics[metric] = value value = 1 if increment else value
if category not in self.tensorboard_metrics:
self.tensorboard_metrics[category] = {}
if not increment or metric not in self.tensorboard_metrics[category]:
self.tensorboard_metrics[category][metric] = value
else: else:
self.tensorboard_metrics[metric] += value self.tensorboard_metrics[category][metric] += value
def reset_tensorboard_log(self): def reset_tensorboard_log(self):
self.tensorboard_metrics = {} self.tensorboard_metrics = {}

View File

@ -114,6 +114,7 @@ class BaseReinforcementLearningModel(IFreqaiModel):
# normalize all data based on train_dataset only # normalize all data based on train_dataset only
prices_train, prices_test = self.build_ohlc_price_dataframes(dk.data_dictionary, pair, dk) prices_train, prices_test = self.build_ohlc_price_dataframes(dk.data_dictionary, pair, dk)
data_dictionary = dk.normalize_data(data_dictionary) data_dictionary = dk.normalize_data(data_dictionary)
# data cleaning/analysis # data cleaning/analysis
@ -148,12 +149,8 @@ class BaseReinforcementLearningModel(IFreqaiModel):
env_info = self.pack_env_dict(dk.pair) env_info = self.pack_env_dict(dk.pair)
self.train_env = self.MyRLEnv(df=train_df, self.train_env = self.MyRLEnv(df=train_df, prices=prices_train, **env_info)
prices=prices_train, self.eval_env = Monitor(self.MyRLEnv(df=test_df, prices=prices_test, **env_info))
**env_info)
self.eval_env = Monitor(self.MyRLEnv(df=test_df,
prices=prices_test,
**env_info))
self.eval_callback = EvalCallback(self.eval_env, deterministic=True, self.eval_callback = EvalCallback(self.eval_env, deterministic=True,
render=False, eval_freq=len(train_df), render=False, eval_freq=len(train_df),
best_model_save_path=str(dk.data_path)) best_model_save_path=str(dk.data_path))
@ -238,6 +235,9 @@ class BaseReinforcementLearningModel(IFreqaiModel):
filtered_dataframe, _ = dk.filter_features( filtered_dataframe, _ = dk.filter_features(
unfiltered_df, dk.training_features_list, training_filter=False unfiltered_df, dk.training_features_list, training_filter=False
) )
filtered_dataframe = self.drop_ohlc_from_df(filtered_dataframe, dk)
filtered_dataframe = dk.normalize_data_from_metadata(filtered_dataframe) filtered_dataframe = dk.normalize_data_from_metadata(filtered_dataframe)
dk.data_dictionary["prediction_features"] = filtered_dataframe dk.data_dictionary["prediction_features"] = filtered_dataframe
@ -285,7 +285,6 @@ class BaseReinforcementLearningModel(IFreqaiModel):
train_df = data_dictionary["train_features"] train_df = data_dictionary["train_features"]
test_df = data_dictionary["test_features"] test_df = data_dictionary["test_features"]
# %-raw_volume_gen_shift-2_ETH/USDT_1h
# price data for model training and evaluation # price data for model training and evaluation
tf = self.config['timeframe'] tf = self.config['timeframe']
rename_dict = {'%-raw_open': 'open', '%-raw_low': 'low', rename_dict = {'%-raw_open': 'open', '%-raw_low': 'low',
@ -318,8 +317,24 @@ class BaseReinforcementLearningModel(IFreqaiModel):
prices_test.rename(columns=rename_dict, inplace=True) prices_test.rename(columns=rename_dict, inplace=True)
prices_test.reset_index(drop=True) prices_test.reset_index(drop=True)
train_df = self.drop_ohlc_from_df(train_df, dk)
test_df = self.drop_ohlc_from_df(test_df, dk)
return prices_train, prices_test return prices_train, prices_test
def drop_ohlc_from_df(self, df: DataFrame, dk: FreqaiDataKitchen):
"""
Given a dataframe, drop the ohlc data
"""
drop_list = ['%-raw_open', '%-raw_low', '%-raw_high', '%-raw_close']
if self.rl_config["drop_ohlc_from_features"]:
df.drop(drop_list, axis=1, inplace=True)
feature_list = dk.training_features_list
dk.training_features_list = [e for e in feature_list if e not in drop_list]
return df
def load_model_from_disk(self, dk: FreqaiDataKitchen) -> Any: def load_model_from_disk(self, dk: FreqaiDataKitchen) -> Any:
""" """
Can be used by user if they are trying to limit_ram_usage *and* Can be used by user if they are trying to limit_ram_usage *and*

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@ -13,7 +13,7 @@ class TensorboardCallback(BaseCallback):
episodic summary reports. episodic summary reports.
""" """
def __init__(self, verbose=1, actions: Type[Enum] = BaseActions): def __init__(self, verbose=1, actions: Type[Enum] = BaseActions):
super(TensorboardCallback, self).__init__(verbose) super().__init__(verbose)
self.model: Any = None self.model: Any = None
self.logger = None # type: Any self.logger = None # type: Any
self.training_env: BaseEnvironment = None # type: ignore self.training_env: BaseEnvironment = None # type: ignore
@ -46,14 +46,12 @@ class TensorboardCallback(BaseCallback):
local_info = self.locals["infos"][0] local_info = self.locals["infos"][0]
tensorboard_metrics = self.training_env.get_attr("tensorboard_metrics")[0] tensorboard_metrics = self.training_env.get_attr("tensorboard_metrics")[0]
for info in local_info: for metric in local_info:
if info not in ["episode", "terminal_observation"]: if metric not in ["episode", "terminal_observation"]:
self.logger.record(f"_info/{info}", local_info[info]) self.logger.record(f"info/{metric}", local_info[metric])
for info in tensorboard_metrics: for category in tensorboard_metrics:
if info in [action.name for action in self.actions]: for metric in tensorboard_metrics[category]:
self.logger.record(f"_actions/{info}", tensorboard_metrics[info]) self.logger.record(f"{category}/{metric}", tensorboard_metrics[category][metric])
else:
self.logger.record(f"_custom/{info}", tensorboard_metrics[info])
return True return True

View File

@ -126,7 +126,7 @@ class FreqaiDataDrawer:
""" """
exists = self.global_metadata_path.is_file() exists = self.global_metadata_path.is_file()
if exists: if exists:
with open(self.global_metadata_path, "r") as fp: with self.global_metadata_path.open("r") as fp:
metatada_dict = rapidjson.load(fp, number_mode=rapidjson.NM_NATIVE) metatada_dict = rapidjson.load(fp, number_mode=rapidjson.NM_NATIVE)
return metatada_dict return metatada_dict
return {} return {}
@ -139,7 +139,7 @@ class FreqaiDataDrawer:
""" """
exists = self.pair_dictionary_path.is_file() exists = self.pair_dictionary_path.is_file()
if exists: if exists:
with open(self.pair_dictionary_path, "r") as fp: with self.pair_dictionary_path.open("r") as fp:
self.pair_dict = rapidjson.load(fp, number_mode=rapidjson.NM_NATIVE) self.pair_dict = rapidjson.load(fp, number_mode=rapidjson.NM_NATIVE)
else: else:
logger.info("Could not find existing datadrawer, starting from scratch") logger.info("Could not find existing datadrawer, starting from scratch")
@ -152,7 +152,7 @@ class FreqaiDataDrawer:
if self.freqai_info.get('write_metrics_to_disk', False): if self.freqai_info.get('write_metrics_to_disk', False):
exists = self.metric_tracker_path.is_file() exists = self.metric_tracker_path.is_file()
if exists: if exists:
with open(self.metric_tracker_path, "r") as fp: with self.metric_tracker_path.open("r") as fp:
self.metric_tracker = rapidjson.load(fp, number_mode=rapidjson.NM_NATIVE) self.metric_tracker = rapidjson.load(fp, number_mode=rapidjson.NM_NATIVE)
logger.info("Loading existing metric tracker from disk.") logger.info("Loading existing metric tracker from disk.")
else: else:
@ -166,7 +166,7 @@ class FreqaiDataDrawer:
exists = self.historic_predictions_path.is_file() exists = self.historic_predictions_path.is_file()
if exists: if exists:
try: try:
with open(self.historic_predictions_path, "rb") as fp: with self.historic_predictions_path.open("rb") as fp:
self.historic_predictions = cloudpickle.load(fp) self.historic_predictions = cloudpickle.load(fp)
logger.info( logger.info(
f"Found existing historic predictions at {self.full_path}, but beware " f"Found existing historic predictions at {self.full_path}, but beware "
@ -176,7 +176,7 @@ class FreqaiDataDrawer:
except EOFError: except EOFError:
logger.warning( logger.warning(
'Historical prediction file was corrupted. Trying to load backup file.') 'Historical prediction file was corrupted. Trying to load backup file.')
with open(self.historic_predictions_bkp_path, "rb") as fp: with self.historic_predictions_bkp_path.open("rb") as fp:
self.historic_predictions = cloudpickle.load(fp) self.historic_predictions = cloudpickle.load(fp)
logger.warning('FreqAI successfully loaded the backup historical predictions file.') logger.warning('FreqAI successfully loaded the backup historical predictions file.')
@ -189,7 +189,7 @@ class FreqaiDataDrawer:
""" """
Save historic predictions pickle to disk Save historic predictions pickle to disk
""" """
with open(self.historic_predictions_path, "wb") as fp: with self.historic_predictions_path.open("wb") as fp:
cloudpickle.dump(self.historic_predictions, fp, protocol=cloudpickle.DEFAULT_PROTOCOL) cloudpickle.dump(self.historic_predictions, fp, protocol=cloudpickle.DEFAULT_PROTOCOL)
# create a backup # create a backup
@ -200,16 +200,16 @@ class FreqaiDataDrawer:
Save metric tracker of all pair metrics collected. Save metric tracker of all pair metrics collected.
""" """
with self.save_lock: with self.save_lock:
with open(self.metric_tracker_path, 'w') as fp: with self.metric_tracker_path.open('w') as fp:
rapidjson.dump(self.metric_tracker, fp, default=self.np_encoder, rapidjson.dump(self.metric_tracker, fp, default=self.np_encoder,
number_mode=rapidjson.NM_NATIVE) number_mode=rapidjson.NM_NATIVE)
def save_drawer_to_disk(self): def save_drawer_to_disk(self) -> None:
""" """
Save data drawer full of all pair model metadata in present model folder. Save data drawer full of all pair model metadata in present model folder.
""" """
with self.save_lock: with self.save_lock:
with open(self.pair_dictionary_path, 'w') as fp: with self.pair_dictionary_path.open('w') as fp:
rapidjson.dump(self.pair_dict, fp, default=self.np_encoder, rapidjson.dump(self.pair_dict, fp, default=self.np_encoder,
number_mode=rapidjson.NM_NATIVE) number_mode=rapidjson.NM_NATIVE)
@ -218,7 +218,7 @@ class FreqaiDataDrawer:
Save global metadata json to disk Save global metadata json to disk
""" """
with self.save_lock: with self.save_lock:
with open(self.global_metadata_path, 'w') as fp: with self.global_metadata_path.open('w') as fp:
rapidjson.dump(metadata, fp, default=self.np_encoder, rapidjson.dump(metadata, fp, default=self.np_encoder,
number_mode=rapidjson.NM_NATIVE) number_mode=rapidjson.NM_NATIVE)
@ -424,7 +424,7 @@ class FreqaiDataDrawer:
dk.data["training_features_list"] = list(dk.data_dictionary["train_features"].columns) dk.data["training_features_list"] = list(dk.data_dictionary["train_features"].columns)
dk.data["label_list"] = dk.label_list dk.data["label_list"] = dk.label_list
with open(save_path / f"{dk.model_filename}_metadata.json", "w") as fp: with (save_path / f"{dk.model_filename}_metadata.json").open("w") as fp:
rapidjson.dump(dk.data, fp, default=self.np_encoder, number_mode=rapidjson.NM_NATIVE) rapidjson.dump(dk.data, fp, default=self.np_encoder, number_mode=rapidjson.NM_NATIVE)
return return
@ -457,7 +457,7 @@ class FreqaiDataDrawer:
dk.data["training_features_list"] = dk.training_features_list dk.data["training_features_list"] = dk.training_features_list
dk.data["label_list"] = dk.label_list dk.data["label_list"] = dk.label_list
# store the metadata # store the metadata
with open(save_path / f"{dk.model_filename}_metadata.json", "w") as fp: with (save_path / f"{dk.model_filename}_metadata.json").open("w") as fp:
rapidjson.dump(dk.data, fp, default=self.np_encoder, number_mode=rapidjson.NM_NATIVE) rapidjson.dump(dk.data, fp, default=self.np_encoder, number_mode=rapidjson.NM_NATIVE)
# save the train data to file so we can check preds for area of applicability later # save the train data to file so we can check preds for area of applicability later
@ -471,7 +471,7 @@ class FreqaiDataDrawer:
if self.freqai_info["feature_parameters"].get("principal_component_analysis"): if self.freqai_info["feature_parameters"].get("principal_component_analysis"):
cloudpickle.dump( cloudpickle.dump(
dk.pca, open(dk.data_path / f"{dk.model_filename}_pca_object.pkl", "wb") dk.pca, (dk.data_path / f"{dk.model_filename}_pca_object.pkl").open("wb")
) )
self.model_dictionary[coin] = model self.model_dictionary[coin] = model
@ -491,7 +491,7 @@ class FreqaiDataDrawer:
Load only metadata into datakitchen to increase performance during Load only metadata into datakitchen to increase performance during
presaved backtesting (prediction file loading). presaved backtesting (prediction file loading).
""" """
with open(dk.data_path / f"{dk.model_filename}_metadata.json", "r") as fp: with (dk.data_path / f"{dk.model_filename}_metadata.json").open("r") as fp:
dk.data = rapidjson.load(fp, number_mode=rapidjson.NM_NATIVE) dk.data = rapidjson.load(fp, number_mode=rapidjson.NM_NATIVE)
dk.training_features_list = dk.data["training_features_list"] dk.training_features_list = dk.data["training_features_list"]
dk.label_list = dk.data["label_list"] dk.label_list = dk.data["label_list"]
@ -514,7 +514,7 @@ class FreqaiDataDrawer:
dk.data = self.meta_data_dictionary[coin]["meta_data"] dk.data = self.meta_data_dictionary[coin]["meta_data"]
dk.data_dictionary["train_features"] = self.meta_data_dictionary[coin]["train_df"] dk.data_dictionary["train_features"] = self.meta_data_dictionary[coin]["train_df"]
else: else:
with open(dk.data_path / f"{dk.model_filename}_metadata.json", "r") as fp: with (dk.data_path / f"{dk.model_filename}_metadata.json").open("r") as fp:
dk.data = rapidjson.load(fp, number_mode=rapidjson.NM_NATIVE) dk.data = rapidjson.load(fp, number_mode=rapidjson.NM_NATIVE)
dk.data_dictionary["train_features"] = pd.read_pickle( dk.data_dictionary["train_features"] = pd.read_pickle(
@ -552,7 +552,7 @@ class FreqaiDataDrawer:
if self.config["freqai"]["feature_parameters"]["principal_component_analysis"]: if self.config["freqai"]["feature_parameters"]["principal_component_analysis"]:
dk.pca = cloudpickle.load( dk.pca = cloudpickle.load(
open(dk.data_path / f"{dk.model_filename}_pca_object.pkl", "rb") (dk.data_path / f"{dk.model_filename}_pca_object.pkl").open("rb")
) )
return model return model
@ -570,12 +570,12 @@ class FreqaiDataDrawer:
for pair in dk.all_pairs: for pair in dk.all_pairs:
for tf in feat_params.get("include_timeframes"): for tf in feat_params.get("include_timeframes"):
hist_df = history_data[pair][tf]
# check if newest candle is already appended # check if newest candle is already appended
df_dp = strategy.dp.get_pair_dataframe(pair, tf) df_dp = strategy.dp.get_pair_dataframe(pair, tf)
if len(df_dp.index) == 0: if len(df_dp.index) == 0:
continue continue
if str(history_data[pair][tf].iloc[-1]["date"]) == str( if str(hist_df.iloc[-1]["date"]) == str(
df_dp.iloc[-1:]["date"].iloc[-1] df_dp.iloc[-1:]["date"].iloc[-1]
): ):
continue continue
@ -583,21 +583,30 @@ class FreqaiDataDrawer:
try: try:
index = ( index = (
df_dp.loc[ df_dp.loc[
df_dp["date"] == history_data[pair][tf].iloc[-1]["date"] df_dp["date"] == hist_df.iloc[-1]["date"]
].index[0] ].index[0]
+ 1 + 1
) )
except IndexError: except IndexError:
if hist_df.iloc[-1]['date'] < df_dp['date'].iloc[0]:
raise OperationalException("In memory historical data is older than "
f"oldest DataProvider candle for {pair} on "
f"timeframe {tf}")
else:
index = -1
logger.warning( logger.warning(
f"Unable to update pair history for {pair}. " f"No common dates in historical data and dataprovider for {pair}. "
"If this does not resolve itself after 1 additional candle, " f"Appending latest dataprovider candle to historical data "
"please report the error to #freqai discord channel" "but please be aware that there is likely a gap in the historical "
"data. \n"
f"Historical data ends at {hist_df.iloc[-1]['date']} "
f"while dataprovider starts at {df_dp['date'].iloc[0]} and"
f"ends at {df_dp['date'].iloc[0]}."
) )
return
history_data[pair][tf] = pd.concat( history_data[pair][tf] = pd.concat(
[ [
history_data[pair][tf], hist_df,
df_dp.iloc[index:], df_dp.iloc[index:],
], ],
ignore_index=True, ignore_index=True,

View File

@ -251,7 +251,7 @@ class FreqaiDataKitchen:
(drop_index == 0) & (drop_index_labels == 0) (drop_index == 0) & (drop_index_labels == 0)
] ]
logger.info( logger.info(
f"dropped {len(unfiltered_df) - len(filtered_df)} training points" f"{self.pair}: dropped {len(unfiltered_df) - len(filtered_df)} training points"
f" due to NaNs in populated dataset {len(unfiltered_df)}." f" due to NaNs in populated dataset {len(unfiltered_df)}."
) )
if (1 - len(filtered_df) / len(unfiltered_df)) > 0.1 and self.live: if (1 - len(filtered_df) / len(unfiltered_df)) > 0.1 and self.live:
@ -675,7 +675,7 @@ class FreqaiDataKitchen:
] ]
logger.info( logger.info(
f"SVM tossed {len(y_pred) - kept_points.sum()}" f"{self.pair}: SVM tossed {len(y_pred) - kept_points.sum()}"
f" test points from {len(y_pred)} total points." f" test points from {len(y_pred)} total points."
) )
@ -949,7 +949,7 @@ class FreqaiDataKitchen:
if (len(do_predict) - do_predict.sum()) > 0: if (len(do_predict) - do_predict.sum()) > 0:
logger.info( logger.info(
f"DI tossed {len(do_predict) - do_predict.sum()} predictions for " f"{self.pair}: DI tossed {len(do_predict) - do_predict.sum()} predictions for "
"being too far from training data." "being too far from training data."
) )
@ -1315,11 +1315,21 @@ class FreqaiDataKitchen:
dataframe: DataFrame = dataframe containing populated indicators dataframe: DataFrame = dataframe containing populated indicators
""" """
# this is a hack to check if the user is using the populate_any_indicators function # check if the user is using the deprecated populate_any_indicators function
new_version = inspect.getsource(strategy.populate_any_indicators) == ( new_version = inspect.getsource(strategy.populate_any_indicators) == (
inspect.getsource(IStrategy.populate_any_indicators)) inspect.getsource(IStrategy.populate_any_indicators))
if new_version: if not new_version:
raise OperationalException(
"You are using the `populate_any_indicators()` function"
" which was deprecated on March 1, 2023. Please refer "
"to the strategy migration guide to use the new "
"feature_engineering_* methods: \n"
"https://www.freqtrade.io/en/stable/strategy_migration/#freqai-strategy \n"
"And the feature_engineering_* documentation: \n"
"https://www.freqtrade.io/en/latest/freqai-feature-engineering/"
)
tfs: List[str] = self.freqai_config["feature_parameters"].get("include_timeframes") tfs: List[str] = self.freqai_config["feature_parameters"].get("include_timeframes")
pairs: List[str] = self.freqai_config["feature_parameters"].get( pairs: List[str] = self.freqai_config["feature_parameters"].get(
"include_corr_pairlist", []) "include_corr_pairlist", [])
@ -1363,85 +1373,6 @@ class FreqaiDataKitchen:
return dataframe return dataframe
else:
# the user is using the populate_any_indicators functions which is deprecated
df = self.use_strategy_to_populate_indicators_old_version(
strategy, corr_dataframes, base_dataframes, pair,
prediction_dataframe, do_corr_pairs)
return df
def use_strategy_to_populate_indicators_old_version(
self,
strategy: IStrategy,
corr_dataframes: dict = {},
base_dataframes: dict = {},
pair: str = "",
prediction_dataframe: DataFrame = pd.DataFrame(),
do_corr_pairs: bool = True,
) -> DataFrame:
"""
Use the user defined strategy for populating indicators during retrain
:param strategy: IStrategy = user defined strategy object
:param corr_dataframes: dict = dict containing the df pair dataframes
(for user defined timeframes)
:param base_dataframes: dict = dict containing the current pair dataframes
(for user defined timeframes)
:param metadata: dict = strategy furnished pair metadata
:return:
dataframe: DataFrame = dataframe containing populated indicators
"""
# for prediction dataframe creation, we let dataprovider handle everything in the strategy
# so we create empty dictionaries, which allows us to pass None to
# `populate_any_indicators()`. Signaling we want the dp to give us the live dataframe.
tfs: List[str] = self.freqai_config["feature_parameters"].get("include_timeframes")
pairs: List[str] = self.freqai_config["feature_parameters"].get("include_corr_pairlist", [])
if not prediction_dataframe.empty:
dataframe = prediction_dataframe.copy()
for tf in tfs:
base_dataframes[tf] = None
for p in pairs:
if p not in corr_dataframes:
corr_dataframes[p] = {}
corr_dataframes[p][tf] = None
else:
dataframe = base_dataframes[self.config["timeframe"]].copy()
sgi = False
for tf in tfs:
if tf == tfs[-1]:
sgi = True # doing this last allows user to use all tf raw prices in labels
dataframe = strategy.populate_any_indicators(
pair,
dataframe.copy(),
tf,
informative=base_dataframes[tf],
set_generalized_indicators=sgi
)
# ensure corr pairs are always last
for corr_pair in pairs:
if pair == corr_pair:
continue # dont repeat anything from whitelist
for tf in tfs:
if pairs and do_corr_pairs:
dataframe = strategy.populate_any_indicators(
corr_pair,
dataframe.copy(),
tf,
informative=corr_dataframes[corr_pair][tf]
)
self.get_unique_classes_from_labels(dataframe)
dataframe = self.remove_special_chars_from_feature_names(dataframe)
if self.config.get('reduce_df_footprint', False):
dataframe = reduce_dataframe_footprint(dataframe)
return dataframe
def fit_labels(self) -> None: def fit_labels(self) -> None:
""" """
Fit the labels with a gaussian distribution Fit the labels with a gaussian distribution

View File

@ -1,4 +1,3 @@
import inspect
import logging import logging
import threading import threading
import time import time
@ -105,8 +104,10 @@ class IFreqaiModel(ABC):
self.data_provider: Optional[DataProvider] = None self.data_provider: Optional[DataProvider] = None
self.max_system_threads = max(int(psutil.cpu_count() * 2 - 2), 1) self.max_system_threads = max(int(psutil.cpu_count() * 2 - 2), 1)
self.can_short = True # overridden in start() with strategy.can_short self.can_short = True # overridden in start() with strategy.can_short
self.model: Any = None
self.warned_deprecated_populate_any_indicators = False if self.ft_params.get('principal_component_analysis', False) and self.continual_learning:
self.ft_params.update({'principal_component_analysis': False})
logger.warning('User tried to use PCA with continual learning. Deactivating PCA.')
record_params(config, self.full_path) record_params(config, self.full_path)
@ -138,9 +139,6 @@ class IFreqaiModel(ABC):
self.data_provider = strategy.dp self.data_provider = strategy.dp
self.can_short = strategy.can_short self.can_short = strategy.can_short
# check if the strategy has deprecated populate_any_indicators function
self.check_deprecated_populate_any_indicators(strategy)
if self.live: if self.live:
self.inference_timer('start') self.inference_timer('start')
self.dk = FreqaiDataKitchen(self.config, self.live, metadata["pair"]) self.dk = FreqaiDataKitchen(self.config, self.live, metadata["pair"])
@ -159,8 +157,7 @@ class IFreqaiModel(ABC):
dk = self.start_backtesting(dataframe, metadata, self.dk, strategy) dk = self.start_backtesting(dataframe, metadata, self.dk, strategy)
dataframe = dk.remove_features_from_df(dk.return_dataframe) dataframe = dk.remove_features_from_df(dk.return_dataframe)
else: else:
logger.info( logger.info("Backtesting using historic predictions (live models)")
"Backtesting using historic predictions (live models)")
dk = self.start_backtesting_from_historic_predictions( dk = self.start_backtesting_from_historic_predictions(
dataframe, metadata, self.dk) dataframe, metadata, self.dk)
dataframe = dk.return_dataframe dataframe = dk.return_dataframe
@ -344,13 +341,14 @@ class IFreqaiModel(ABC):
except Exception as msg: except Exception as msg:
logger.warning( logger.warning(
f"Training {pair} raised exception {msg.__class__.__name__}. " f"Training {pair} raised exception {msg.__class__.__name__}. "
f"Message: {msg}, skipping.") f"Message: {msg}, skipping.", exc_info=True)
self.model = None
self.dd.pair_dict[pair]["trained_timestamp"] = int( self.dd.pair_dict[pair]["trained_timestamp"] = int(
tr_train.stopts) tr_train.stopts)
if self.plot_features: if self.plot_features and self.model is not None:
plot_feature_importance(self.model, pair, dk, self.plot_features) plot_feature_importance(self.model, pair, dk, self.plot_features)
if self.save_backtest_models: if self.save_backtest_models and self.model is not None:
logger.info('Saving backtest model to disk.') logger.info('Saving backtest model to disk.')
self.dd.save_data(self.model, pair, dk) self.dd.save_data(self.model, pair, dk)
else: else:
@ -491,7 +489,7 @@ class IFreqaiModel(ABC):
"strategy is furnishing the same features as the pretrained" "strategy is furnishing the same features as the pretrained"
"model. In case of --strategy-list, please be aware that FreqAI " "model. In case of --strategy-list, please be aware that FreqAI "
"requires all strategies to maintain identical " "requires all strategies to maintain identical "
"populate_any_indicator() functions" "feature_engineering_* functions"
) )
def data_cleaning_train(self, dk: FreqaiDataKitchen) -> None: def data_cleaning_train(self, dk: FreqaiDataKitchen) -> None:
@ -603,7 +601,7 @@ class IFreqaiModel(ABC):
:param strategy: IStrategy = user defined strategy object :param strategy: IStrategy = user defined strategy object
:param dk: FreqaiDataKitchen = non-persistent data container for current coin/loop :param dk: FreqaiDataKitchen = non-persistent data container for current coin/loop
:param data_load_timerange: TimeRange = the amount of data to be loaded :param data_load_timerange: TimeRange = the amount of data to be loaded
for populate_any_indicators for populating indicators
(larger than new_trained_timerange so that (larger than new_trained_timerange so that
new_trained_timerange does not contain any NaNs) new_trained_timerange does not contain any NaNs)
""" """
@ -809,7 +807,7 @@ class IFreqaiModel(ABC):
logger.warning("Couldn't cache corr_pair dataframes for improved performance. " logger.warning("Couldn't cache corr_pair dataframes for improved performance. "
"Consider ensuring that the full coin/stake, e.g. XYZ/USD, " "Consider ensuring that the full coin/stake, e.g. XYZ/USD, "
"is included in the column names when you are creating features " "is included in the column names when you are creating features "
"in `populate_any_indicators()`.") "in `feature_engineering_*` functions.")
self.get_corr_dataframes = not bool(self.corr_dataframes) self.get_corr_dataframes = not bool(self.corr_dataframes)
elif self.corr_dataframes: elif self.corr_dataframes:
dataframe = dk.attach_corr_pair_columns( dataframe = dk.attach_corr_pair_columns(
@ -936,26 +934,6 @@ class IFreqaiModel(ABC):
dk.return_dataframe, saved_dataframe, how='left', left_on='date', right_on="date_pred") dk.return_dataframe, saved_dataframe, how='left', left_on='date', right_on="date_pred")
return dk return dk
def check_deprecated_populate_any_indicators(self, strategy: IStrategy):
"""
Check and warn if the deprecated populate_any_indicators function is used.
:param strategy: strategy object
"""
if not self.warned_deprecated_populate_any_indicators:
self.warned_deprecated_populate_any_indicators = True
old_version = inspect.getsource(strategy.populate_any_indicators) != (
inspect.getsource(IStrategy.populate_any_indicators))
if old_version:
logger.warning("DEPRECATION WARNING: "
"You are using the deprecated populate_any_indicators function. "
"This function will raise an error on March 1 2023. "
"Please update your strategy by using "
"the new feature_engineering functions. See \n"
"https://www.freqtrade.io/en/latest/freqai-feature-engineering/"
"for details.")
# Following methods which are overridden by user made prediction models. # Following methods which are overridden by user made prediction models.
# See freqai/prediction_models/CatboostPredictionModel.py for an example. # See freqai/prediction_models/CatboostPredictionModel.py for an example.

View File

@ -100,7 +100,7 @@ class ReinforcementLearner(BaseReinforcementLearningModel):
""" """
# first, penalize if the action is not valid # first, penalize if the action is not valid
if not self._is_valid(action): if not self._is_valid(action):
self.tensorboard_log("is_valid") self.tensorboard_log("invalid", category="actions")
return -2 return -2
pnl = self.get_unrealized_profit() pnl = self.get_unrealized_profit()

View File

@ -34,6 +34,11 @@ class ReinforcementLearner_multiproc(ReinforcementLearner):
train_df = data_dictionary["train_features"] train_df = data_dictionary["train_features"]
test_df = data_dictionary["test_features"] test_df = data_dictionary["test_features"]
if self.train_env:
self.train_env.close()
if self.eval_env:
self.eval_env.close()
env_info = self.pack_env_dict(dk.pair) env_info = self.pack_env_dict(dk.pair)
env_id = "train_env" env_id = "train_env"

View File

@ -211,7 +211,7 @@ def record_params(config: Dict[str, Any], full_path: Path) -> None:
"pairs": config.get('exchange', {}).get('pair_whitelist') "pairs": config.get('exchange', {}).get('pair_whitelist')
} }
with open(params_record_path, "w") as handle: with params_record_path.open("w") as handle:
rapidjson.dump( rapidjson.dump(
run_params, run_params,
handle, handle,

View File

@ -30,6 +30,8 @@ from freqtrade.plugins.protectionmanager import ProtectionManager
from freqtrade.resolvers import ExchangeResolver, StrategyResolver from freqtrade.resolvers import ExchangeResolver, StrategyResolver
from freqtrade.rpc import RPCManager from freqtrade.rpc import RPCManager
from freqtrade.rpc.external_message_consumer import ExternalMessageConsumer from freqtrade.rpc.external_message_consumer import ExternalMessageConsumer
from freqtrade.rpc.rpc_types import (RPCBuyMsg, RPCCancelMsg, RPCProtectionMsg, RPCSellCancelMsg,
RPCSellMsg)
from freqtrade.strategy.interface import IStrategy from freqtrade.strategy.interface import IStrategy
from freqtrade.strategy.strategy_wrapper import strategy_safe_wrapper from freqtrade.strategy.strategy_wrapper import strategy_safe_wrapper
from freqtrade.util import FtPrecise from freqtrade.util import FtPrecise
@ -127,19 +129,19 @@ class FreqtradeBot(LoggingMixin):
for minutes in [0, 15, 30, 45]: for minutes in [0, 15, 30, 45]:
t = str(time(time_slot, minutes, 2)) t = str(time(time_slot, minutes, 2))
self._schedule.every().day.at(t).do(update) self._schedule.every().day.at(t).do(update)
self.last_process = datetime(1970, 1, 1, tzinfo=timezone.utc) self.last_process: Optional[datetime] = None
self.strategy.ft_bot_start() self.strategy.ft_bot_start()
# Initialize protections AFTER bot start - otherwise parameters are not loaded. # Initialize protections AFTER bot start - otherwise parameters are not loaded.
self.protections = ProtectionManager(self.config, self.strategy.protections) self.protections = ProtectionManager(self.config, self.strategy.protections)
def notify_status(self, msg: str) -> None: def notify_status(self, msg: str, msg_type=RPCMessageType.STATUS) -> None:
""" """
Public method for users of this class (worker, etc.) to send notifications Public method for users of this class (worker, etc.) to send notifications
via RPC about changes in the bot status. via RPC about changes in the bot status.
""" """
self.rpc.send_msg({ self.rpc.send_msg({
'type': RPCMessageType.STATUS, 'type': msg_type,
'status': msg 'status': msg
}) })
@ -212,7 +214,8 @@ class FreqtradeBot(LoggingMixin):
self.dataprovider.refresh(self.pairlists.create_pair_list(self.active_pair_whitelist), self.dataprovider.refresh(self.pairlists.create_pair_list(self.active_pair_whitelist),
self.strategy.gather_informative_pairs()) self.strategy.gather_informative_pairs())
strategy_safe_wrapper(self.strategy.bot_loop_start, supress_error=True)() strategy_safe_wrapper(self.strategy.bot_loop_start, supress_error=True)(
current_time=datetime.now(timezone.utc))
self.strategy.analyze(self.active_pair_whitelist) self.strategy.analyze(self.active_pair_whitelist)
@ -586,7 +589,7 @@ class FreqtradeBot(LoggingMixin):
min_entry_stake = self.exchange.get_min_pair_stake_amount(trade.pair, min_entry_stake = self.exchange.get_min_pair_stake_amount(trade.pair,
current_entry_rate, current_entry_rate,
self.strategy.stoploss) 0.0)
min_exit_stake = self.exchange.get_min_pair_stake_amount(trade.pair, min_exit_stake = self.exchange.get_min_pair_stake_amount(trade.pair,
current_exit_rate, current_exit_rate,
self.strategy.stoploss) self.strategy.stoploss)
@ -594,7 +597,7 @@ class FreqtradeBot(LoggingMixin):
stake_available = self.wallets.get_available_stake_amount() stake_available = self.wallets.get_available_stake_amount()
logger.debug(f"Calling adjust_trade_position for pair {trade.pair}") logger.debug(f"Calling adjust_trade_position for pair {trade.pair}")
stake_amount = strategy_safe_wrapper(self.strategy.adjust_trade_position, stake_amount = strategy_safe_wrapper(self.strategy.adjust_trade_position,
default_retval=None)( default_retval=None, supress_error=True)(
trade=trade, trade=trade,
current_time=datetime.now(timezone.utc), current_rate=current_entry_rate, current_time=datetime.now(timezone.utc), current_rate=current_entry_rate,
current_profit=current_entry_profit, min_stake=min_entry_stake, current_profit=current_entry_profit, min_stake=min_entry_stake,
@ -633,7 +636,7 @@ class FreqtradeBot(LoggingMixin):
return return
remaining = (trade.amount - amount) * current_exit_rate remaining = (trade.amount - amount) * current_exit_rate
if remaining < min_exit_stake: if min_exit_stake and remaining < min_exit_stake:
logger.info(f"Remaining amount of {remaining} would be smaller " logger.info(f"Remaining amount of {remaining} would be smaller "
f"than the minimum of {min_exit_stake}.") f"than the minimum of {min_exit_stake}.")
return return
@ -700,7 +703,8 @@ class FreqtradeBot(LoggingMixin):
pos_adjust = trade is not None pos_adjust = trade is not None
enter_limit_requested, stake_amount, leverage = self.get_valid_enter_price_and_stake( enter_limit_requested, stake_amount, leverage = self.get_valid_enter_price_and_stake(
pair, price, stake_amount, trade_side, enter_tag, trade, order_adjust, leverage_) pair, price, stake_amount, trade_side, enter_tag, trade, order_adjust, leverage_,
pos_adjust)
if not stake_amount: if not stake_amount:
return False return False
@ -809,6 +813,9 @@ class FreqtradeBot(LoggingMixin):
precision_mode=self.exchange.precisionMode, precision_mode=self.exchange.precisionMode,
contract_size=self.exchange.get_contract_size(pair), contract_size=self.exchange.get_contract_size(pair),
) )
stoploss = self.strategy.stoploss if not self.edge else self.edge.get_stoploss(pair)
trade.adjust_stop_loss(trade.open_rate, stoploss, initial=True)
else: else:
# This is additional buy, we reset fee_open_currency so timeout checking can work # This is additional buy, we reset fee_open_currency so timeout checking can work
trade.is_open = True trade.is_open = True
@ -818,7 +825,7 @@ class FreqtradeBot(LoggingMixin):
trade.orders.append(order_obj) trade.orders.append(order_obj)
trade.recalc_trade_from_orders() trade.recalc_trade_from_orders()
Trade.query.session.add(trade) Trade.session.add(trade)
Trade.commit() Trade.commit()
# Updating wallets # Updating wallets
@ -841,7 +848,7 @@ class FreqtradeBot(LoggingMixin):
def cancel_stoploss_on_exchange(self, trade: Trade) -> Trade: def cancel_stoploss_on_exchange(self, trade: Trade) -> Trade:
# First cancelling stoploss on exchange ... # First cancelling stoploss on exchange ...
if self.strategy.order_types.get('stoploss_on_exchange') and trade.stoploss_order_id: if trade.stoploss_order_id:
try: try:
logger.info(f"Canceling stoploss on exchange for {trade}") logger.info(f"Canceling stoploss on exchange for {trade}")
co = self.exchange.cancel_stoploss_order_with_result( co = self.exchange.cancel_stoploss_order_with_result(
@ -850,7 +857,8 @@ class FreqtradeBot(LoggingMixin):
# Reset stoploss order id. # Reset stoploss order id.
trade.stoploss_order_id = None trade.stoploss_order_id = None
except InvalidOrderException: except InvalidOrderException:
logger.exception(f"Could not cancel stoploss order {trade.stoploss_order_id}") logger.exception(f"Could not cancel stoploss order {trade.stoploss_order_id} "
f"for pair {trade.pair}")
return trade return trade
def get_valid_enter_price_and_stake( def get_valid_enter_price_and_stake(
@ -860,7 +868,12 @@ class FreqtradeBot(LoggingMixin):
trade: Optional[Trade], trade: Optional[Trade],
order_adjust: bool, order_adjust: bool,
leverage_: Optional[float], leverage_: Optional[float],
pos_adjust: bool,
) -> Tuple[float, float, float]: ) -> Tuple[float, float, float]:
"""
Validate and eventually adjust (within limits) limit, amount and leverage
:return: Tuple with (price, amount, leverage)
"""
if price: if price:
enter_limit_requested = price enter_limit_requested = price
@ -906,7 +919,9 @@ class FreqtradeBot(LoggingMixin):
# We do however also need min-stake to determine leverage, therefore this is ignored as # We do however also need min-stake to determine leverage, therefore this is ignored as
# edge-case for now. # edge-case for now.
min_stake_amount = self.exchange.get_min_pair_stake_amount( min_stake_amount = self.exchange.get_min_pair_stake_amount(
pair, enter_limit_requested, self.strategy.stoploss, leverage) pair, enter_limit_requested,
self.strategy.stoploss if not pos_adjust else 0.0,
leverage)
max_stake_amount = self.exchange.get_max_pair_stake_amount( max_stake_amount = self.exchange.get_max_pair_stake_amount(
pair, enter_limit_requested, leverage) pair, enter_limit_requested, leverage)
@ -935,7 +950,6 @@ class FreqtradeBot(LoggingMixin):
""" """
Sends rpc notification when a entry order occurred. Sends rpc notification when a entry order occurred.
""" """
msg_type = RPCMessageType.ENTRY_FILL if fill else RPCMessageType.ENTRY
open_rate = order.safe_price open_rate = order.safe_price
if open_rate is None: if open_rate is None:
@ -946,9 +960,9 @@ class FreqtradeBot(LoggingMixin):
current_rate = self.exchange.get_rate( current_rate = self.exchange.get_rate(
trade.pair, side='entry', is_short=trade.is_short, refresh=False) trade.pair, side='entry', is_short=trade.is_short, refresh=False)
msg = { msg: RPCBuyMsg = {
'trade_id': trade.id, 'trade_id': trade.id,
'type': msg_type, 'type': RPCMessageType.ENTRY_FILL if fill else RPCMessageType.ENTRY,
'buy_tag': trade.enter_tag, 'buy_tag': trade.enter_tag,
'enter_tag': trade.enter_tag, 'enter_tag': trade.enter_tag,
'exchange': trade.exchange.capitalize(), 'exchange': trade.exchange.capitalize(),
@ -960,6 +974,7 @@ class FreqtradeBot(LoggingMixin):
'order_type': order_type, 'order_type': order_type,
'stake_amount': trade.stake_amount, 'stake_amount': trade.stake_amount,
'stake_currency': self.config['stake_currency'], 'stake_currency': self.config['stake_currency'],
'base_currency': self.exchange.get_pair_base_currency(trade.pair),
'fiat_currency': self.config.get('fiat_display_currency', None), 'fiat_currency': self.config.get('fiat_display_currency', None),
'amount': order.safe_amount_after_fee if fill else (order.amount or trade.amount), 'amount': order.safe_amount_after_fee if fill else (order.amount or trade.amount),
'open_date': trade.open_date or datetime.utcnow(), 'open_date': trade.open_date or datetime.utcnow(),
@ -978,7 +993,7 @@ class FreqtradeBot(LoggingMixin):
current_rate = self.exchange.get_rate( current_rate = self.exchange.get_rate(
trade.pair, side='entry', is_short=trade.is_short, refresh=False) trade.pair, side='entry', is_short=trade.is_short, refresh=False)
msg = { msg: RPCCancelMsg = {
'trade_id': trade.id, 'trade_id': trade.id,
'type': RPCMessageType.ENTRY_CANCEL, 'type': RPCMessageType.ENTRY_CANCEL,
'buy_tag': trade.enter_tag, 'buy_tag': trade.enter_tag,
@ -990,7 +1005,9 @@ class FreqtradeBot(LoggingMixin):
'limit': trade.open_rate, 'limit': trade.open_rate,
'order_type': order_type, 'order_type': order_type,
'stake_amount': trade.stake_amount, 'stake_amount': trade.stake_amount,
'open_rate': trade.open_rate,
'stake_currency': self.config['stake_currency'], 'stake_currency': self.config['stake_currency'],
'base_currency': self.exchange.get_pair_base_currency(trade.pair),
'fiat_currency': self.config.get('fiat_display_currency', None), 'fiat_currency': self.config.get('fiat_display_currency', None),
'amount': trade.amount, 'amount': trade.amount,
'open_date': trade.open_date, 'open_date': trade.open_date,
@ -1013,12 +1030,16 @@ class FreqtradeBot(LoggingMixin):
trades_closed = 0 trades_closed = 0
for trade in trades: for trade in trades:
try: try:
try:
if (self.strategy.order_types.get('stoploss_on_exchange') and if (self.strategy.order_types.get('stoploss_on_exchange') and
self.handle_stoploss_on_exchange(trade)): self.handle_stoploss_on_exchange(trade)):
trades_closed += 1 trades_closed += 1
Trade.commit() Trade.commit()
continue continue
except InvalidOrderException as exception:
logger.warning(
f'Unable to handle stoploss on exchange for {trade.pair}: {exception}')
# Check if we can sell our current pair # Check if we can sell our current pair
if trade.open_order_id is None and trade.is_open and self.handle_trade(trade): if trade.open_order_id is None and trade.is_open and self.handle_trade(trade):
trades_closed += 1 trades_closed += 1
@ -1122,8 +1143,7 @@ class FreqtradeBot(LoggingMixin):
trade.stoploss_order_id = None trade.stoploss_order_id = None
logger.error(f'Unable to place a stoploss order on exchange. {e}') logger.error(f'Unable to place a stoploss order on exchange. {e}')
logger.warning('Exiting the trade forcefully') logger.warning('Exiting the trade forcefully')
self.execute_trade_exit(trade, stop_price, exit_check=ExitCheckTuple( self.emergency_exit(trade, stop_price)
exit_type=ExitType.EMERGENCY_EXIT))
except ExchangeError: except ExchangeError:
trade.stoploss_order_id = None trade.stoploss_order_id = None
@ -1225,13 +1245,8 @@ class FreqtradeBot(LoggingMixin):
# cancelling the current stoploss on exchange first # cancelling the current stoploss on exchange first
logger.info(f"Cancelling current stoploss on exchange for pair {trade.pair} " logger.info(f"Cancelling current stoploss on exchange for pair {trade.pair} "
f"(orderid:{order['id']}) in order to add another one ...") f"(orderid:{order['id']}) in order to add another one ...")
try:
co = self.exchange.cancel_stoploss_order_with_result(order['id'], trade.pair, self.cancel_stoploss_on_exchange(trade)
trade.amount)
trade.update_order(co)
except InvalidOrderException:
logger.exception(f"Could not cancel stoploss order {order['id']} "
f"for pair {trade.pair}")
# Create new stoploss order # Create new stoploss order
if not self.create_stoploss_order(trade=trade, stop_price=stoploss_norm): if not self.create_stoploss_order(trade=trade, stop_price=stoploss_norm):
@ -1275,20 +1290,22 @@ class FreqtradeBot(LoggingMixin):
if order['side'] == trade.entry_side: if order['side'] == trade.entry_side:
self.handle_cancel_enter(trade, order, reason) self.handle_cancel_enter(trade, order, reason)
else: else:
canceled = self.handle_cancel_exit( canceled = self.handle_cancel_exit(trade, order, reason)
trade, order, reason)
canceled_count = trade.get_exit_order_count() canceled_count = trade.get_exit_order_count()
max_timeouts = self.config.get('unfilledtimeout', {}).get('exit_timeout_count', 0) max_timeouts = self.config.get('unfilledtimeout', {}).get('exit_timeout_count', 0)
if canceled and max_timeouts > 0 and canceled_count >= max_timeouts: if canceled and max_timeouts > 0 and canceled_count >= max_timeouts:
logger.warning(f'Emergency exiting trade {trade}, as the exit order ' logger.warning(f'Emergency exiting trade {trade}, as the exit order '
f'timed out {max_timeouts} times.') f'timed out {max_timeouts} times.')
self.emergency_exit(trade, order['price'])
def emergency_exit(self, trade: Trade, price: float) -> None:
try: try:
self.execute_trade_exit( self.execute_trade_exit(
trade, order['price'], trade, price,
exit_check=ExitCheckTuple(exit_type=ExitType.EMERGENCY_EXIT)) exit_check=ExitCheckTuple(exit_type=ExitType.EMERGENCY_EXIT))
except DependencyException as exception: except DependencyException as exception:
logger.warning( logger.warning(
f'Unable to emergency sell trade {trade.pair}: {exception}') f'Unable to emergency exit trade {trade.pair}: {exception}')
def replace_order(self, order: Dict, order_obj: Optional[Order], trade: Trade) -> None: def replace_order(self, order: Dict, order_obj: Optional[Order], trade: Trade) -> None:
""" """
@ -1315,7 +1332,7 @@ class FreqtradeBot(LoggingMixin):
default_retval=order_obj.price)( default_retval=order_obj.price)(
trade=trade, order=order_obj, pair=trade.pair, trade=trade, order=order_obj, pair=trade.pair,
current_time=datetime.now(timezone.utc), proposed_rate=proposed_rate, current_time=datetime.now(timezone.utc), proposed_rate=proposed_rate,
current_order_rate=order_obj.price, entry_tag=trade.enter_tag, current_order_rate=order_obj.safe_price, entry_tag=trade.enter_tag,
side=trade.entry_side) side=trade.entry_side)
replacing = True replacing = True
@ -1331,7 +1348,8 @@ class FreqtradeBot(LoggingMixin):
# place new order only if new price is supplied # place new order only if new price is supplied
self.execute_entry( self.execute_entry(
pair=trade.pair, pair=trade.pair,
stake_amount=(order_obj.remaining * order_obj.price / trade.leverage), stake_amount=(
order_obj.safe_remaining * order_obj.safe_price / trade.leverage),
price=adjusted_entry_price, price=adjusted_entry_price,
trade=trade, trade=trade,
is_short=trade.is_short, is_short=trade.is_short,
@ -1345,6 +1363,8 @@ class FreqtradeBot(LoggingMixin):
""" """
for trade in Trade.get_open_order_trades(): for trade in Trade.get_open_order_trades():
if not trade.open_order_id:
continue
try: try:
order = self.exchange.fetch_order(trade.open_order_id, trade.pair) order = self.exchange.fetch_order(trade.open_order_id, trade.pair)
except (ExchangeError): except (ExchangeError):
@ -1369,6 +1389,9 @@ class FreqtradeBot(LoggingMixin):
""" """
was_trade_fully_canceled = False was_trade_fully_canceled = False
side = trade.entry_side.capitalize() side = trade.entry_side.capitalize()
if not trade.open_order_id:
logger.warning(f"No open order for {trade}.")
return False
# Cancelled orders may have the status of 'canceled' or 'closed' # Cancelled orders may have the status of 'canceled' or 'closed'
if order['status'] not in constants.NON_OPEN_EXCHANGE_STATES: if order['status'] not in constants.NON_OPEN_EXCHANGE_STATES:
@ -1455,34 +1478,32 @@ class FreqtradeBot(LoggingMixin):
return False return False
try: try:
co = self.exchange.cancel_order_with_result(trade.open_order_id, trade.pair, order = self.exchange.cancel_order_with_result(order['id'], trade.pair,
trade.amount) trade.amount)
except InvalidOrderException: except InvalidOrderException:
logger.exception( logger.exception(
f"Could not cancel {trade.exit_side} order {trade.open_order_id}") f"Could not cancel {trade.exit_side} order {trade.open_order_id}")
return False return False
trade.close_rate = None
trade.close_rate_requested = None
trade.close_profit = None
trade.close_profit_abs = None
# Set exit_reason for fill message # Set exit_reason for fill message
exit_reason_prev = trade.exit_reason exit_reason_prev = trade.exit_reason
trade.exit_reason = trade.exit_reason + f", {reason}" if trade.exit_reason else reason trade.exit_reason = trade.exit_reason + f", {reason}" if trade.exit_reason else reason
self.update_trade_state(trade, trade.open_order_id, co)
# Order might be filled above in odd timing issues. # Order might be filled above in odd timing issues.
if co.get('status') in ('canceled', 'cancelled'): if order.get('status') in ('canceled', 'cancelled'):
trade.exit_reason = None trade.exit_reason = None
trade.open_order_id = None
else: else:
trade.exit_reason = exit_reason_prev trade.exit_reason = exit_reason_prev
logger.info(f'{trade.exit_side.capitalize()} order {reason} for {trade}.')
cancelled = True cancelled = True
else: else:
reason = constants.CANCEL_REASON['CANCELLED_ON_EXCHANGE'] reason = constants.CANCEL_REASON['CANCELLED_ON_EXCHANGE']
logger.info(f'{trade.exit_side.capitalize()} order {reason} for {trade}.') trade.exit_reason = None
self.update_trade_state(trade, trade.open_order_id, order) self.update_trade_state(trade, trade.open_order_id, order)
logger.info(f'{trade.exit_side.capitalize()} order {reason} for {trade}.')
trade.open_order_id = None trade.open_order_id = None
trade.close_rate = None
trade.close_rate_requested = None
self._notify_exit_cancel( self._notify_exit_cancel(
trade, trade,
@ -1640,13 +1661,13 @@ class FreqtradeBot(LoggingMixin):
profit = trade.calc_profit(rate=order_rate, amount=amount, open_rate=trade.open_rate) profit = trade.calc_profit(rate=order_rate, amount=amount, open_rate=trade.open_rate)
profit_ratio = trade.calc_profit_ratio(order_rate, amount, trade.open_rate) profit_ratio = trade.calc_profit_ratio(order_rate, amount, trade.open_rate)
else: else:
order_rate = trade.close_rate if trade.close_rate else trade.close_rate_requested order_rate = trade.safe_close_rate
profit = trade.calc_profit(rate=order_rate) + (0.0 if fill else trade.realized_profit) profit = trade.calc_profit(rate=order_rate) + (0.0 if fill else trade.realized_profit)
profit_ratio = trade.calc_profit_ratio(order_rate) profit_ratio = trade.calc_profit_ratio(order_rate)
amount = trade.amount amount = trade.amount
gain = "profit" if profit_ratio > 0 else "loss" gain = "profit" if profit_ratio > 0 else "loss"
msg = { msg: RPCSellMsg = {
'type': (RPCMessageType.EXIT_FILL if fill 'type': (RPCMessageType.EXIT_FILL if fill
else RPCMessageType.EXIT), else RPCMessageType.EXIT),
'trade_id': trade.id, 'trade_id': trade.id,
@ -1672,6 +1693,7 @@ class FreqtradeBot(LoggingMixin):
'close_date': trade.close_date or datetime.utcnow(), 'close_date': trade.close_date or datetime.utcnow(),
'stake_amount': trade.stake_amount, 'stake_amount': trade.stake_amount,
'stake_currency': self.config['stake_currency'], 'stake_currency': self.config['stake_currency'],
'base_currency': self.exchange.get_pair_base_currency(trade.pair),
'fiat_currency': self.config.get('fiat_display_currency'), 'fiat_currency': self.config.get('fiat_display_currency'),
'sub_trade': sub_trade, 'sub_trade': sub_trade,
'cumulative_profit': trade.realized_profit, 'cumulative_profit': trade.realized_profit,
@ -1695,14 +1717,14 @@ class FreqtradeBot(LoggingMixin):
raise DependencyException( raise DependencyException(
f"Order_obj not found for {order_id}. This should not have happened.") f"Order_obj not found for {order_id}. This should not have happened.")
profit_rate = trade.close_rate if trade.close_rate else trade.close_rate_requested profit_rate: float = trade.safe_close_rate
profit_trade = trade.calc_profit(rate=profit_rate) profit_trade = trade.calc_profit(rate=profit_rate)
current_rate = self.exchange.get_rate( current_rate = self.exchange.get_rate(
trade.pair, side='exit', is_short=trade.is_short, refresh=False) trade.pair, side='exit', is_short=trade.is_short, refresh=False)
profit_ratio = trade.calc_profit_ratio(profit_rate) profit_ratio = trade.calc_profit_ratio(profit_rate)
gain = "profit" if profit_ratio > 0 else "loss" gain = "profit" if profit_ratio > 0 else "loss"
msg = { msg: RPCSellCancelMsg = {
'type': RPCMessageType.EXIT_CANCEL, 'type': RPCMessageType.EXIT_CANCEL,
'trade_id': trade.id, 'trade_id': trade.id,
'exchange': trade.exchange.capitalize(), 'exchange': trade.exchange.capitalize(),
@ -1724,6 +1746,7 @@ class FreqtradeBot(LoggingMixin):
'open_date': trade.open_date, 'open_date': trade.open_date,
'close_date': trade.close_date or datetime.now(timezone.utc), 'close_date': trade.close_date or datetime.now(timezone.utc),
'stake_currency': self.config['stake_currency'], 'stake_currency': self.config['stake_currency'],
'base_currency': self.exchange.get_pair_base_currency(trade.pair),
'fiat_currency': self.config.get('fiat_display_currency', None), 'fiat_currency': self.config.get('fiat_display_currency', None),
'reason': reason, 'reason': reason,
'sub_trade': sub_trade, 'sub_trade': sub_trade,
@ -1738,7 +1761,8 @@ class FreqtradeBot(LoggingMixin):
# #
def update_trade_state( def update_trade_state(
self, trade: Trade, order_id: str, action_order: Optional[Dict[str, Any]] = None, self, trade: Trade, order_id: Optional[str],
action_order: Optional[Dict[str, Any]] = None,
stoploss_order: bool = False, send_msg: bool = True) -> bool: stoploss_order: bool = False, send_msg: bool = True) -> bool:
""" """
Checks trades with open orders and updates the amount if necessary Checks trades with open orders and updates the amount if necessary
@ -1787,7 +1811,7 @@ class FreqtradeBot(LoggingMixin):
# TODO: should shorting/leverage be supported by Edge, # TODO: should shorting/leverage be supported by Edge,
# then this will need to be fixed. # then this will need to be fixed.
trade.adjust_stop_loss(trade.open_rate, self.strategy.stoploss, initial=True) trade.adjust_stop_loss(trade.open_rate, self.strategy.stoploss, initial=True)
if order.get('side') == trade.entry_side or trade.amount > 0: if order.get('side') == trade.entry_side or (trade.amount > 0 and trade.is_open):
# Must also run for partial exits # Must also run for partial exits
# TODO: Margin will need to use interest_rate as well. # TODO: Margin will need to use interest_rate as well.
# interest_rate = self.exchange.get_interest_rate() # interest_rate = self.exchange.get_interest_rate()
@ -1830,14 +1854,20 @@ class FreqtradeBot(LoggingMixin):
self.strategy.lock_pair(pair, datetime.now(timezone.utc), reason='Auto lock') self.strategy.lock_pair(pair, datetime.now(timezone.utc), reason='Auto lock')
prot_trig = self.protections.stop_per_pair(pair, side=side) prot_trig = self.protections.stop_per_pair(pair, side=side)
if prot_trig: if prot_trig:
msg = {'type': RPCMessageType.PROTECTION_TRIGGER, } msg: RPCProtectionMsg = {
msg.update(prot_trig.to_json()) 'type': RPCMessageType.PROTECTION_TRIGGER,
'base_currency': self.exchange.get_pair_base_currency(prot_trig.pair),
**prot_trig.to_json() # type: ignore
}
self.rpc.send_msg(msg) self.rpc.send_msg(msg)
prot_trig_glb = self.protections.global_stop(side=side) prot_trig_glb = self.protections.global_stop(side=side)
if prot_trig_glb: if prot_trig_glb:
msg = {'type': RPCMessageType.PROTECTION_TRIGGER_GLOBAL, } msg = {
msg.update(prot_trig_glb.to_json()) 'type': RPCMessageType.PROTECTION_TRIGGER_GLOBAL,
'base_currency': self.exchange.get_pair_base_currency(prot_trig_glb.pair),
**prot_trig_glb.to_json() # type: ignore
}
self.rpc.send_msg(msg) self.rpc.send_msg(msg)
def apply_fee_conditional(self, trade: Trade, trade_base_currency: str, def apply_fee_conditional(self, trade: Trade, trade_base_currency: str,

View File

@ -6,8 +6,7 @@ import logging
import re import re
from datetime import datetime from datetime import datetime
from pathlib import Path from pathlib import Path
from typing import Any, Dict, Iterator, List, Mapping, Optional, Union from typing import Any, Dict, Iterator, List, Mapping, Optional, TextIO, Union
from typing.io import IO
from urllib.parse import urlparse from urllib.parse import urlparse
import orjson import orjson
@ -81,7 +80,7 @@ def file_dump_json(filename: Path, data: Any, is_zip: bool = False, log: bool =
else: else:
if log: if log:
logger.info(f'dumping json to "{filename}"') logger.info(f'dumping json to "{filename}"')
with open(filename, 'w') as fp: with filename.open('w') as fp:
rapidjson.dump(data, fp, default=str, number_mode=rapidjson.NM_NATIVE) rapidjson.dump(data, fp, default=str, number_mode=rapidjson.NM_NATIVE)
logger.debug(f'done json to "{filename}"') logger.debug(f'done json to "{filename}"')
@ -98,12 +97,12 @@ def file_dump_joblib(filename: Path, data: Any, log: bool = True) -> None:
if log: if log:
logger.info(f'dumping joblib to "{filename}"') logger.info(f'dumping joblib to "{filename}"')
with open(filename, 'wb') as fp: with filename.open('wb') as fp:
joblib.dump(data, fp) joblib.dump(data, fp)
logger.debug(f'done joblib dump to "{filename}"') logger.debug(f'done joblib dump to "{filename}"')
def json_load(datafile: IO) -> Any: def json_load(datafile: Union[gzip.GzipFile, TextIO]) -> Any:
""" """
load data with rapidjson load data with rapidjson
Use this to have a consistent experience, Use this to have a consistent experience,
@ -112,7 +111,7 @@ def json_load(datafile: IO) -> Any:
return rapidjson.load(datafile, number_mode=rapidjson.NM_NATIVE) return rapidjson.load(datafile, number_mode=rapidjson.NM_NATIVE)
def file_load_json(file): def file_load_json(file: Path):
if file.suffix != ".gz": if file.suffix != ".gz":
gzipfile = file.with_suffix(file.suffix + '.gz') gzipfile = file.with_suffix(file.suffix + '.gz')
@ -125,7 +124,7 @@ def file_load_json(file):
pairdata = json_load(datafile) pairdata = json_load(datafile)
elif file.is_file(): elif file.is_file():
logger.debug(f"Loading historical data from file {file}") logger.debug(f"Loading historical data from file {file}")
with open(file) as datafile: with file.open() as datafile:
pairdata = json_load(datafile) pairdata = json_load(datafile)
else: else:
return None return None

View File

@ -29,7 +29,7 @@ def get_strategy_run_id(strategy) -> str:
# Include _ft_params_from_file - so changing parameter files cause cache eviction # Include _ft_params_from_file - so changing parameter files cause cache eviction
digest.update(rapidjson.dumps( digest.update(rapidjson.dumps(
strategy._ft_params_from_file, default=str, number_mode=rapidjson.NM_NAN).encode('utf-8')) strategy._ft_params_from_file, default=str, number_mode=rapidjson.NM_NAN).encode('utf-8'))
with open(strategy.__file__, 'rb') as fp: with Path(strategy.__file__).open('rb') as fp:
digest.update(fp.read()) digest.update(fp.read())
return digest.hexdigest().lower() return digest.hexdigest().lower()

View File

@ -93,7 +93,7 @@ class Backtesting:
if self.config.get('strategy_list'): if self.config.get('strategy_list'):
if self.config.get('freqai', {}).get('enabled', False): if self.config.get('freqai', {}).get('enabled', False):
logger.warning("Using --strategy-list with FreqAI REQUIRES all strategies " logger.warning("Using --strategy-list with FreqAI REQUIRES all strategies "
"to have identical populate_any_indicators.") "to have identical feature_engineering_* functions.")
for strat in list(self.config['strategy_list']): for strat in list(self.config['strategy_list']):
stratconf = deepcopy(self.config) stratconf = deepcopy(self.config)
stratconf['strategy'] = strat stratconf['strategy'] = strat
@ -203,9 +203,10 @@ class Backtesting:
# since a "perfect" stoploss-exit is assumed anyway # since a "perfect" stoploss-exit is assumed anyway
# And the regular "stoploss" function would not apply to that case # And the regular "stoploss" function would not apply to that case
self.strategy.order_types['stoploss_on_exchange'] = False self.strategy.order_types['stoploss_on_exchange'] = False
# Update can_short flag
self._can_short = self.trading_mode != TradingMode.SPOT and strategy.can_short
self.strategy.ft_bot_start() self.strategy.ft_bot_start()
strategy_safe_wrapper(self.strategy.bot_loop_start, supress_error=True)()
def _load_protections(self, strategy: IStrategy): def _load_protections(self, strategy: IStrategy):
if self.config.get('enable_protections', False): if self.config.get('enable_protections', False):
@ -440,11 +441,8 @@ class Backtesting:
side_1 * abs(self.strategy.trailing_stop_positive / leverage))) side_1 * abs(self.strategy.trailing_stop_positive / leverage)))
else: else:
# Worst case: price ticks tiny bit above open and dives down. # Worst case: price ticks tiny bit above open and dives down.
stop_rate = row[OPEN_IDX] * (1 - side_1 * abs(trade.stop_loss_pct / leverage)) stop_rate = row[OPEN_IDX] * (1 - side_1 * abs(
if is_short: (trade.stop_loss_pct or 0.0) / leverage))
assert stop_rate > row[LOW_IDX]
else:
assert stop_rate < row[HIGH_IDX]
# Limit lower-end to candle low to avoid exits below the low. # Limit lower-end to candle low to avoid exits below the low.
# This still remains "worst case" - but "worst realistic case". # This still remains "worst case" - but "worst realistic case".
@ -472,7 +470,7 @@ class Backtesting:
# - (Expected abs profit - open_rate - open_fee) / (fee_close -1) # - (Expected abs profit - open_rate - open_fee) / (fee_close -1)
roi_rate = trade.open_rate * roi / leverage roi_rate = trade.open_rate * roi / leverage
open_fee_rate = side_1 * trade.open_rate * (1 + side_1 * trade.fee_open) open_fee_rate = side_1 * trade.open_rate * (1 + side_1 * trade.fee_open)
close_rate = -(roi_rate + open_fee_rate) / (trade.fee_close - side_1 * 1) close_rate = -(roi_rate + open_fee_rate) / ((trade.fee_close or 0.0) - side_1 * 1)
if is_short: if is_short:
is_new_roi = row[OPEN_IDX] < close_rate is_new_roi = row[OPEN_IDX] < close_rate
else: else:
@ -525,7 +523,7 @@ class Backtesting:
max_stake = self.exchange.get_max_pair_stake_amount(trade.pair, current_rate) max_stake = self.exchange.get_max_pair_stake_amount(trade.pair, current_rate)
stake_available = self.wallets.get_available_stake_amount() stake_available = self.wallets.get_available_stake_amount()
stake_amount = strategy_safe_wrapper(self.strategy.adjust_trade_position, stake_amount = strategy_safe_wrapper(self.strategy.adjust_trade_position,
default_retval=None)( default_retval=None, supress_error=True)(
trade=trade, # type: ignore[arg-type] trade=trade, # type: ignore[arg-type]
current_time=current_date, current_rate=current_rate, current_time=current_date, current_rate=current_rate,
current_profit=current_profit, min_stake=min_stake, current_profit=current_profit, min_stake=min_stake,
@ -563,7 +561,7 @@ class Backtesting:
pos_trade = self._get_exit_for_signal(trade, row, exit_, amount) pos_trade = self._get_exit_for_signal(trade, row, exit_, amount)
if pos_trade is not None: if pos_trade is not None:
order = pos_trade.orders[-1] order = pos_trade.orders[-1]
if self._get_order_filled(order.price, row): if self._get_order_filled(order.ft_price, row):
order.close_bt_order(current_date, trade) order.close_bt_order(current_date, trade)
trade.recalc_trade_from_orders() trade.recalc_trade_from_orders()
self.wallets.update() self.wallets.update()
@ -664,6 +662,7 @@ class Backtesting:
side=trade.exit_side, side=trade.exit_side,
order_type=order_type, order_type=order_type,
status="open", status="open",
ft_price=close_rate,
price=close_rate, price=close_rate,
average=close_rate, average=close_rate,
amount=amount, amount=amount,
@ -742,12 +741,12 @@ class Backtesting:
proposed_leverage=1.0, proposed_leverage=1.0,
max_leverage=max_leverage, max_leverage=max_leverage,
side=direction, entry_tag=entry_tag, side=direction, entry_tag=entry_tag,
) if self._can_short else 1.0 ) if self.trading_mode != TradingMode.SPOT else 1.0
# Cap leverage between 1.0 and max_leverage. # Cap leverage between 1.0 and max_leverage.
leverage = min(max(leverage, 1.0), max_leverage) leverage = min(max(leverage, 1.0), max_leverage)
min_stake_amount = self.exchange.get_min_pair_stake_amount( min_stake_amount = self.exchange.get_min_pair_stake_amount(
pair, propose_rate, -0.05, leverage=leverage) or 0 pair, propose_rate, -0.05 if not pos_adjust else 0.0, leverage=leverage) or 0
max_stake_amount = self.exchange.get_max_pair_stake_amount( max_stake_amount = self.exchange.get_max_pair_stake_amount(
pair, propose_rate, leverage=leverage) pair, propose_rate, leverage=leverage)
stake_available = self.wallets.get_available_stake_amount() stake_available = self.wallets.get_available_stake_amount()
@ -887,6 +886,7 @@ class Backtesting:
order_date=current_time, order_date=current_time,
order_filled_date=current_time, order_filled_date=current_time,
order_update_date=current_time, order_update_date=current_time,
ft_price=propose_rate,
price=propose_rate, price=propose_rate,
average=propose_rate, average=propose_rate,
amount=amount, amount=amount,
@ -895,7 +895,7 @@ class Backtesting:
cost=stake_amount + trade.fee_open, cost=stake_amount + trade.fee_open,
) )
trade.orders.append(order) trade.orders.append(order)
if pos_adjust and self._get_order_filled(order.price, row): if pos_adjust and self._get_order_filled(order.ft_price, row):
order.close_bt_order(current_time, trade) order.close_bt_order(current_time, trade)
else: else:
trade.open_order_id = str(self.order_id_counter) trade.open_order_id = str(self.order_id_counter)
@ -1008,15 +1008,15 @@ class Backtesting:
# only check on new candles for open entry orders # only check on new candles for open entry orders
if order.side == trade.entry_side and current_time > order.order_date_utc: if order.side == trade.entry_side and current_time > order.order_date_utc:
requested_rate = strategy_safe_wrapper(self.strategy.adjust_entry_price, requested_rate = strategy_safe_wrapper(self.strategy.adjust_entry_price,
default_retval=order.price)( default_retval=order.ft_price)(
trade=trade, # type: ignore[arg-type] trade=trade, # type: ignore[arg-type]
order=order, pair=trade.pair, current_time=current_time, order=order, pair=trade.pair, current_time=current_time,
proposed_rate=row[OPEN_IDX], current_order_rate=order.price, proposed_rate=row[OPEN_IDX], current_order_rate=order.ft_price,
entry_tag=trade.enter_tag, side=trade.trade_direction entry_tag=trade.enter_tag, side=trade.trade_direction
) # default value is current order price ) # default value is current order price
# cancel existing order whenever a new rate is requested (or None) # cancel existing order whenever a new rate is requested (or None)
if requested_rate == order.price: if requested_rate == order.ft_price:
# assumption: there can't be multiple open entry orders at any given time # assumption: there can't be multiple open entry orders at any given time
return False return False
else: else:
@ -1028,8 +1028,12 @@ class Backtesting:
if requested_rate: if requested_rate:
self._enter_trade(pair=trade.pair, row=row, trade=trade, self._enter_trade(pair=trade.pair, row=row, trade=trade,
requested_rate=requested_rate, requested_rate=requested_rate,
requested_stake=(order.remaining * order.price / trade.leverage), requested_stake=(
order.safe_remaining * order.ft_price / trade.leverage),
direction='short' if trade.is_short else 'long') direction='short' if trade.is_short else 'long')
# Delete trade if no successful entries happened (if placing the new order failed)
if trade.open_order_id is None and trade.nr_of_successful_entries == 0:
return True
self.replaced_entry_orders += 1 self.replaced_entry_orders += 1
else: else:
# assumption: there can't be multiple open entry orders at any given time # assumption: there can't be multiple open entry orders at any given time
@ -1095,7 +1099,7 @@ class Backtesting:
for trade in list(LocalTrade.bt_trades_open_pp[pair]): for trade in list(LocalTrade.bt_trades_open_pp[pair]):
# 3. Process entry orders. # 3. Process entry orders.
order = trade.select_order(trade.entry_side, is_open=True) order = trade.select_order(trade.entry_side, is_open=True)
if order and self._get_order_filled(order.price, row): if order and self._get_order_filled(order.ft_price, row):
order.close_bt_order(current_time, trade) order.close_bt_order(current_time, trade)
trade.open_order_id = None trade.open_order_id = None
self.wallets.update() self.wallets.update()
@ -1106,7 +1110,7 @@ class Backtesting:
# 5. Process exit orders. # 5. Process exit orders.
order = trade.select_order(trade.exit_side, is_open=True) order = trade.select_order(trade.exit_side, is_open=True)
if order and self._get_order_filled(order.price, row): if order and self._get_order_filled(order.ft_price, row):
order.close_bt_order(current_time, trade) order.close_bt_order(current_time, trade)
trade.open_order_id = None trade.open_order_id = None
sub_trade = order.safe_amount_after_fee != trade.amount sub_trade = order.safe_amount_after_fee != trade.amount
@ -1115,7 +1119,7 @@ class Backtesting:
trade.recalc_trade_from_orders() trade.recalc_trade_from_orders()
else: else:
trade.close_date = current_time trade.close_date = current_time
trade.close(order.price, show_msg=False) trade.close(order.ft_price, show_msg=False)
# logger.debug(f"{pair} - Backtesting exit {trade}") # logger.debug(f"{pair} - Backtesting exit {trade}")
LocalTrade.close_bt_trade(trade) LocalTrade.close_bt_trade(trade)
@ -1155,6 +1159,8 @@ class Backtesting:
while current_time <= end_date: while current_time <= end_date:
open_trade_count_start = LocalTrade.bt_open_open_trade_count open_trade_count_start = LocalTrade.bt_open_open_trade_count
self.check_abort() self.check_abort()
strategy_safe_wrapper(self.strategy.bot_loop_start, supress_error=True)(
current_time=current_time)
for i, pair in enumerate(data): for i, pair in enumerate(data):
row_index = indexes[pair] row_index = indexes[pair]
row = self.validate_row(data, pair, row_index, current_time) row = self.validate_row(data, pair, row_index, current_time)

View File

@ -1,4 +1,3 @@
import io
import logging import logging
from copy import deepcopy from copy import deepcopy
from datetime import datetime, timezone from datetime import datetime, timezone
@ -464,8 +463,8 @@ class HyperoptTools():
return return
try: try:
io.open(csv_file, 'w+').close() Path(csv_file).open('w+').close()
except IOError: except OSError:
logger.error(f"Failed to create CSV file: {csv_file}") logger.error(f"Failed to create CSV file: {csv_file}")
return return

View File

@ -1,7 +1,9 @@
from typing import Any from sqlalchemy.orm import DeclarativeBase, Session, scoped_session
from sqlalchemy.orm import declarative_base
_DECL_BASE: Any = declarative_base() SessionType = scoped_session[Session]
class ModelBase(DeclarativeBase):
pass

View File

@ -2,6 +2,9 @@
This module contains the class to persist trades into SQLite This module contains the class to persist trades into SQLite
""" """
import logging import logging
import threading
from contextvars import ContextVar
from typing import Any, Dict, Final, Optional
from sqlalchemy import create_engine, inspect from sqlalchemy import create_engine, inspect
from sqlalchemy.exc import NoSuchModuleError from sqlalchemy.exc import NoSuchModuleError
@ -9,7 +12,7 @@ from sqlalchemy.orm import scoped_session, sessionmaker
from sqlalchemy.pool import StaticPool from sqlalchemy.pool import StaticPool
from freqtrade.exceptions import OperationalException from freqtrade.exceptions import OperationalException
from freqtrade.persistence.base import _DECL_BASE from freqtrade.persistence.base import ModelBase
from freqtrade.persistence.migrations import check_migrate from freqtrade.persistence.migrations import check_migrate
from freqtrade.persistence.pairlock import PairLock from freqtrade.persistence.pairlock import PairLock
from freqtrade.persistence.trade_model import Order, Trade from freqtrade.persistence.trade_model import Order, Trade
@ -18,6 +21,22 @@ from freqtrade.persistence.trade_model import Order, Trade
logger = logging.getLogger(__name__) logger = logging.getLogger(__name__)
REQUEST_ID_CTX_KEY: Final[str] = 'request_id'
_request_id_ctx_var: ContextVar[Optional[str]] = ContextVar(REQUEST_ID_CTX_KEY, default=None)
def get_request_or_thread_id() -> Optional[str]:
"""
Helper method to get either async context (for fastapi requests), or thread id
"""
id = _request_id_ctx_var.get()
if id is None:
# when not in request context - use thread id
id = str(threading.current_thread().ident)
return id
_SQL_DOCS_URL = 'http://docs.sqlalchemy.org/en/latest/core/engines.html#database-urls' _SQL_DOCS_URL = 'http://docs.sqlalchemy.org/en/latest/core/engines.html#database-urls'
@ -29,7 +48,7 @@ def init_db(db_url: str) -> None:
:param db_url: Database to use :param db_url: Database to use
:return: None :return: None
""" """
kwargs = {} kwargs: Dict[str, Any] = {}
if db_url == 'sqlite:///': if db_url == 'sqlite:///':
raise OperationalException( raise OperationalException(
@ -52,12 +71,12 @@ def init_db(db_url: str) -> None:
# https://docs.sqlalchemy.org/en/13/orm/contextual.html#thread-local-scope # https://docs.sqlalchemy.org/en/13/orm/contextual.html#thread-local-scope
# Scoped sessions proxy requests to the appropriate thread-local session. # Scoped sessions proxy requests to the appropriate thread-local session.
# We should use the scoped_session object - not a seperately initialized version # Since we also use fastAPI, we need to make it aware of the request id, too
Trade._session = scoped_session(sessionmaker(bind=engine, autoflush=False)) Trade.session = scoped_session(sessionmaker(
Trade.query = Trade._session.query_property() bind=engine, autoflush=False), scopefunc=get_request_or_thread_id)
Order.query = Trade._session.query_property() Order.session = Trade.session
PairLock.query = Trade._session.query_property() PairLock.session = Trade.session
previous_tables = inspect(engine).get_table_names() previous_tables = inspect(engine).get_table_names()
_DECL_BASE.metadata.create_all(engine) ModelBase.metadata.create_all(engine)
check_migrate(engine, decl_base=_DECL_BASE, previous_tables=previous_tables) check_migrate(engine, decl_base=ModelBase, previous_tables=previous_tables)

View File

@ -1,33 +1,34 @@
from datetime import datetime, timezone from datetime import datetime, timezone
from typing import Any, Dict, Optional from typing import Any, ClassVar, Dict, Optional
from sqlalchemy import Boolean, Column, DateTime, Integer, String, or_ from sqlalchemy import ScalarResult, String, or_, select
from sqlalchemy.orm import Query from sqlalchemy.orm import Mapped, mapped_column
from freqtrade.constants import DATETIME_PRINT_FORMAT from freqtrade.constants import DATETIME_PRINT_FORMAT
from freqtrade.persistence.base import _DECL_BASE from freqtrade.persistence.base import ModelBase, SessionType
class PairLock(_DECL_BASE): class PairLock(ModelBase):
""" """
Pair Locks database model. Pair Locks database model.
""" """
__tablename__ = 'pairlocks' __tablename__ = 'pairlocks'
session: ClassVar[SessionType]
id = Column(Integer, primary_key=True) id: Mapped[int] = mapped_column(primary_key=True)
pair = Column(String(25), nullable=False, index=True) pair: Mapped[str] = mapped_column(String(25), nullable=False, index=True)
# lock direction - long, short or * (for both) # lock direction - long, short or * (for both)
side = Column(String(25), nullable=False, default="*") side: Mapped[str] = mapped_column(String(25), nullable=False, default="*")
reason = Column(String(255), nullable=True) reason: Mapped[Optional[str]] = mapped_column(String(255), nullable=True)
# Time the pair was locked (start time) # Time the pair was locked (start time)
lock_time = Column(DateTime(), nullable=False) lock_time: Mapped[datetime] = mapped_column(nullable=False)
# Time until the pair is locked (end time) # Time until the pair is locked (end time)
lock_end_time = Column(DateTime(), nullable=False, index=True) lock_end_time: Mapped[datetime] = mapped_column(nullable=False, index=True)
active = Column(Boolean, nullable=False, default=True, index=True) active: Mapped[bool] = mapped_column(nullable=False, default=True, index=True)
def __repr__(self): def __repr__(self) -> str:
lock_time = self.lock_time.strftime(DATETIME_PRINT_FORMAT) lock_time = self.lock_time.strftime(DATETIME_PRINT_FORMAT)
lock_end_time = self.lock_end_time.strftime(DATETIME_PRINT_FORMAT) lock_end_time = self.lock_end_time.strftime(DATETIME_PRINT_FORMAT)
return ( return (
@ -35,7 +36,8 @@ class PairLock(_DECL_BASE):
f'lock_end_time={lock_end_time}, reason={self.reason}, active={self.active})') f'lock_end_time={lock_end_time}, reason={self.reason}, active={self.active})')
@staticmethod @staticmethod
def query_pair_locks(pair: Optional[str], now: datetime, side: str = '*') -> Query: def query_pair_locks(
pair: Optional[str], now: datetime, side: str = '*') -> ScalarResult['PairLock']:
""" """
Get all currently active locks for this pair Get all currently active locks for this pair
:param pair: Pair to check for. Returns all current locks if pair is empty :param pair: Pair to check for. Returns all current locks if pair is empty
@ -51,9 +53,11 @@ class PairLock(_DECL_BASE):
else: else:
filters.append(PairLock.side == '*') filters.append(PairLock.side == '*')
return PairLock.query.filter( return PairLock.session.scalars(select(PairLock).filter(*filters))
*filters
) @staticmethod
def get_all_locks() -> ScalarResult['PairLock']:
return PairLock.session.scalars(select(PairLock))
def to_json(self) -> Dict[str, Any]: def to_json(self) -> Dict[str, Any]:
return { return {

View File

@ -1,6 +1,8 @@
import logging import logging
from datetime import datetime, timezone from datetime import datetime, timezone
from typing import List, Optional from typing import List, Optional, Sequence
from sqlalchemy import select
from freqtrade.exchange import timeframe_to_next_date from freqtrade.exchange import timeframe_to_next_date
from freqtrade.persistence.models import PairLock from freqtrade.persistence.models import PairLock
@ -51,15 +53,15 @@ class PairLocks():
active=True active=True
) )
if PairLocks.use_db: if PairLocks.use_db:
PairLock.query.session.add(lock) PairLock.session.add(lock)
PairLock.query.session.commit() PairLock.session.commit()
else: else:
PairLocks.locks.append(lock) PairLocks.locks.append(lock)
return lock return lock
@staticmethod @staticmethod
def get_pair_locks( def get_pair_locks(pair: Optional[str], now: Optional[datetime] = None,
pair: Optional[str], now: Optional[datetime] = None, side: str = '*') -> List[PairLock]: side: str = '*') -> Sequence[PairLock]:
""" """
Get all currently active locks for this pair Get all currently active locks for this pair
:param pair: Pair to check for. Returns all current locks if pair is empty :param pair: Pair to check for. Returns all current locks if pair is empty
@ -106,7 +108,7 @@ class PairLocks():
for lock in locks: for lock in locks:
lock.active = False lock.active = False
if PairLocks.use_db: if PairLocks.use_db:
PairLock.query.session.commit() PairLock.session.commit()
@staticmethod @staticmethod
def unlock_reason(reason: str, now: Optional[datetime] = None) -> None: def unlock_reason(reason: str, now: Optional[datetime] = None) -> None:
@ -126,15 +128,15 @@ class PairLocks():
PairLock.active.is_(True), PairLock.active.is_(True),
PairLock.reason == reason PairLock.reason == reason
] ]
locks = PairLock.query.filter(*filters) locks = PairLock.session.scalars(select(PairLock).filter(*filters)).all()
for lock in locks: for lock in locks:
logger.info(f"Releasing lock for {lock.pair} with reason '{reason}'.") logger.info(f"Releasing lock for {lock.pair} with reason '{reason}'.")
lock.active = False lock.active = False
PairLock.query.session.commit() PairLock.session.commit()
else: else:
# used in backtesting mode; don't show log messages for speed # used in backtesting mode; don't show log messages for speed
locks = PairLocks.get_pair_locks(None) locksb = PairLocks.get_pair_locks(None)
for lock in locks: for lock in locksb:
if lock.reason == reason: if lock.reason == reason:
lock.active = False lock.active = False
@ -165,11 +167,11 @@ class PairLocks():
) )
@staticmethod @staticmethod
def get_all_locks() -> List[PairLock]: def get_all_locks() -> Sequence[PairLock]:
""" """
Return all locks, also locks with expired end date Return all locks, also locks with expired end date
""" """
if PairLocks.use_db: if PairLocks.use_db:
return PairLock.query.all() return PairLock.get_all_locks().all()
else: else:
return PairLocks.locks return PairLocks.locks

View File

@ -5,11 +5,11 @@ import logging
from collections import defaultdict from collections import defaultdict
from datetime import datetime, timedelta, timezone from datetime import datetime, timedelta, timezone
from math import isclose from math import isclose
from typing import Any, Dict, List, Optional from typing import Any, ClassVar, Dict, List, Optional, Sequence, cast
from sqlalchemy import (Boolean, Column, DateTime, Enum, Float, ForeignKey, Integer, String, from sqlalchemy import (Enum, Float, ForeignKey, Integer, ScalarResult, Select, String,
UniqueConstraint, desc, func) UniqueConstraint, desc, func, select)
from sqlalchemy.orm import Query, lazyload, relationship from sqlalchemy.orm import Mapped, lazyload, mapped_column, relationship
from freqtrade.constants import (DATETIME_PRINT_FORMAT, MATH_CLOSE_PREC, NON_OPEN_EXCHANGE_STATES, from freqtrade.constants import (DATETIME_PRINT_FORMAT, MATH_CLOSE_PREC, NON_OPEN_EXCHANGE_STATES,
BuySell, LongShort) BuySell, LongShort)
@ -17,14 +17,14 @@ from freqtrade.enums import ExitType, TradingMode
from freqtrade.exceptions import DependencyException, OperationalException from freqtrade.exceptions import DependencyException, OperationalException
from freqtrade.exchange import amount_to_contract_precision, price_to_precision from freqtrade.exchange import amount_to_contract_precision, price_to_precision
from freqtrade.leverage import interest from freqtrade.leverage import interest
from freqtrade.persistence.base import _DECL_BASE from freqtrade.persistence.base import ModelBase, SessionType
from freqtrade.util import FtPrecise from freqtrade.util import FtPrecise
logger = logging.getLogger(__name__) logger = logging.getLogger(__name__)
class Order(_DECL_BASE): class Order(ModelBase):
""" """
Order database model Order database model
Keeps a record of all orders placed on the exchange Keeps a record of all orders placed on the exchange
@ -36,41 +36,43 @@ class Order(_DECL_BASE):
Mirrors CCXT Order structure Mirrors CCXT Order structure
""" """
__tablename__ = 'orders' __tablename__ = 'orders'
session: ClassVar[SessionType]
# Uniqueness should be ensured over pair, order_id # Uniqueness should be ensured over pair, order_id
# its likely that order_id is unique per Pair on some exchanges. # its likely that order_id is unique per Pair on some exchanges.
__table_args__ = (UniqueConstraint('ft_pair', 'order_id', name="_order_pair_order_id"),) __table_args__ = (UniqueConstraint('ft_pair', 'order_id', name="_order_pair_order_id"),)
id = Column(Integer, primary_key=True) id: Mapped[int] = mapped_column(Integer, primary_key=True)
ft_trade_id = Column(Integer, ForeignKey('trades.id'), index=True) ft_trade_id: Mapped[int] = mapped_column(Integer, ForeignKey('trades.id'), index=True)
trade = relationship("Trade", back_populates="orders") trade: Mapped[List["Trade"]] = relationship("Trade", back_populates="orders")
# order_side can only be 'buy', 'sell' or 'stoploss' # order_side can only be 'buy', 'sell' or 'stoploss'
ft_order_side = Column(String(25), nullable=False) ft_order_side: Mapped[str] = mapped_column(String(25), nullable=False)
ft_pair = Column(String(25), nullable=False) ft_pair: Mapped[str] = mapped_column(String(25), nullable=False)
ft_is_open = Column(Boolean, nullable=False, default=True, index=True) ft_is_open: Mapped[bool] = mapped_column(nullable=False, default=True, index=True)
ft_amount = Column(Float(), nullable=False) ft_amount: Mapped[float] = mapped_column(Float(), nullable=False)
ft_price = Column(Float(), nullable=False) ft_price: Mapped[float] = mapped_column(Float(), nullable=False)
order_id = Column(String(255), nullable=False, index=True) order_id: Mapped[str] = mapped_column(String(255), nullable=False, index=True)
status = Column(String(255), nullable=True) status: Mapped[Optional[str]] = mapped_column(String(255), nullable=True)
symbol = Column(String(25), nullable=True) symbol: Mapped[Optional[str]] = mapped_column(String(25), nullable=True)
order_type = Column(String(50), nullable=True) # TODO: type: order_type type is Optional[str]
side = Column(String(25), nullable=True) order_type: Mapped[str] = mapped_column(String(50), nullable=True)
price = Column(Float(), nullable=True) side: Mapped[str] = mapped_column(String(25), nullable=True)
average = Column(Float(), nullable=True) price: Mapped[Optional[float]] = mapped_column(Float(), nullable=True)
amount = Column(Float(), nullable=True) average: Mapped[Optional[float]] = mapped_column(Float(), nullable=True)
filled = Column(Float(), nullable=True) amount: Mapped[Optional[float]] = mapped_column(Float(), nullable=True)
remaining = Column(Float(), nullable=True) filled: Mapped[Optional[float]] = mapped_column(Float(), nullable=True)
cost = Column(Float(), nullable=True) remaining: Mapped[Optional[float]] = mapped_column(Float(), nullable=True)
stop_price = Column(Float(), nullable=True) cost: Mapped[Optional[float]] = mapped_column(Float(), nullable=True)
order_date = Column(DateTime(), nullable=True, default=datetime.utcnow) stop_price: Mapped[Optional[float]] = mapped_column(Float(), nullable=True)
order_filled_date = Column(DateTime(), nullable=True) order_date: Mapped[datetime] = mapped_column(nullable=True, default=datetime.utcnow)
order_update_date = Column(DateTime(), nullable=True) order_filled_date: Mapped[Optional[datetime]] = mapped_column(nullable=True)
order_update_date: Mapped[Optional[datetime]] = mapped_column(nullable=True)
funding_fee: Mapped[Optional[float]] = mapped_column(Float(), nullable=True)
funding_fee = Column(Float(), nullable=True) ft_fee_base: Mapped[Optional[float]] = mapped_column(Float(), nullable=True)
ft_fee_base = Column(Float(), nullable=True)
@property @property
def order_date_utc(self) -> datetime: def order_date_utc(self) -> datetime:
@ -96,6 +98,10 @@ class Order(_DECL_BASE):
def safe_filled(self) -> float: def safe_filled(self) -> float:
return self.filled if self.filled is not None else self.amount or 0.0 return self.filled if self.filled is not None else self.amount or 0.0
@property
def safe_cost(self) -> float:
return self.cost or 0.0
@property @property
def safe_remaining(self) -> float: def safe_remaining(self) -> float:
return ( return (
@ -113,8 +119,9 @@ class Order(_DECL_BASE):
def __repr__(self): def __repr__(self):
return (f'Order(id={self.id}, order_id={self.order_id}, trade_id={self.ft_trade_id}, ' return (f"Order(id={self.id}, order_id={self.order_id}, trade_id={self.ft_trade_id}, "
f'side={self.side}, order_type={self.order_type}, status={self.status})') f"side={self.side}, filled={self.safe_filled}, price={self.safe_price}, "
f"order_type={self.order_type}, status={self.status})")
def update_from_ccxt_object(self, order): def update_from_ccxt_object(self, order):
""" """
@ -151,7 +158,7 @@ class Order(_DECL_BASE):
self.order_update_date = datetime.now(timezone.utc) self.order_update_date = datetime.now(timezone.utc)
def to_ccxt_object(self) -> Dict[str, Any]: def to_ccxt_object(self) -> Dict[str, Any]:
order = { order: Dict[str, Any] = {
'id': self.order_id, 'id': self.order_id,
'symbol': self.ft_pair, 'symbol': self.ft_pair,
'price': self.price, 'price': self.price,
@ -213,7 +220,7 @@ class Order(_DECL_BASE):
# Assumes backtesting will use date_last_filled_utc to calculate future funding fees. # Assumes backtesting will use date_last_filled_utc to calculate future funding fees.
self.funding_fee = trade.funding_fees self.funding_fee = trade.funding_fees
if (self.ft_order_side == trade.entry_side): if (self.ft_order_side == trade.entry_side and self.price):
trade.open_rate = self.price trade.open_rate = self.price
trade.recalc_trade_from_orders() trade.recalc_trade_from_orders()
trade.adjust_stop_loss(trade.open_rate, trade.stop_loss_pct, refresh=True) trade.adjust_stop_loss(trade.open_rate, trade.stop_loss_pct, refresh=True)
@ -255,12 +262,12 @@ class Order(_DECL_BASE):
return o return o
@staticmethod @staticmethod
def get_open_orders() -> List['Order']: def get_open_orders() -> Sequence['Order']:
""" """
Retrieve open orders from the database Retrieve open orders from the database
:return: List of open orders :return: List of open orders
""" """
return Order.query.filter(Order.ft_is_open.is_(True)).all() return Order.session.scalars(select(Order).filter(Order.ft_is_open.is_(True))).all()
@staticmethod @staticmethod
def order_by_id(order_id: str) -> Optional['Order']: def order_by_id(order_id: str) -> Optional['Order']:
@ -268,7 +275,7 @@ class Order(_DECL_BASE):
Retrieve order based on order_id Retrieve order based on order_id
:return: Order or None :return: Order or None
""" """
return Order.query.filter(Order.order_id == order_id).first() return Order.session.scalars(select(Order).filter(Order.order_id == order_id)).first()
class LocalTrade(): class LocalTrade():
@ -293,15 +300,15 @@ class LocalTrade():
exchange: str = '' exchange: str = ''
pair: str = '' pair: str = ''
base_currency: str = '' base_currency: Optional[str] = ''
stake_currency: str = '' stake_currency: Optional[str] = ''
is_open: bool = True is_open: bool = True
fee_open: float = 0.0 fee_open: float = 0.0
fee_open_cost: Optional[float] = None fee_open_cost: Optional[float] = None
fee_open_currency: str = '' fee_open_currency: Optional[str] = ''
fee_close: float = 0.0 fee_close: Optional[float] = 0.0
fee_close_cost: Optional[float] = None fee_close_cost: Optional[float] = None
fee_close_currency: str = '' fee_close_currency: Optional[str] = ''
open_rate: float = 0.0 open_rate: float = 0.0
open_rate_requested: Optional[float] = None open_rate_requested: Optional[float] = None
# open_trade_value - calculated via _calc_open_trade_value # open_trade_value - calculated via _calc_open_trade_value
@ -311,7 +318,7 @@ class LocalTrade():
close_profit: Optional[float] = None close_profit: Optional[float] = None
close_profit_abs: Optional[float] = None close_profit_abs: Optional[float] = None
stake_amount: float = 0.0 stake_amount: float = 0.0
max_stake_amount: float = 0.0 max_stake_amount: Optional[float] = 0.0
amount: float = 0.0 amount: float = 0.0
amount_requested: Optional[float] = None amount_requested: Optional[float] = None
open_date: datetime open_date: datetime
@ -320,9 +327,9 @@ class LocalTrade():
# absolute value of the stop loss # absolute value of the stop loss
stop_loss: float = 0.0 stop_loss: float = 0.0
# percentage value of the stop loss # percentage value of the stop loss
stop_loss_pct: float = 0.0 stop_loss_pct: Optional[float] = 0.0
# absolute value of the initial stop loss # absolute value of the initial stop loss
initial_stop_loss: float = 0.0 initial_stop_loss: Optional[float] = 0.0
# percentage value of the initial stop loss # percentage value of the initial stop loss
initial_stop_loss_pct: Optional[float] = None initial_stop_loss_pct: Optional[float] = None
# stoploss order id which is on exchange # stoploss order id which is on exchange
@ -330,12 +337,12 @@ class LocalTrade():
# last update time of the stoploss order on exchange # last update time of the stoploss order on exchange
stoploss_last_update: Optional[datetime] = None stoploss_last_update: Optional[datetime] = None
# absolute value of the highest reached price # absolute value of the highest reached price
max_rate: float = 0.0 max_rate: Optional[float] = None
# Lowest price reached # Lowest price reached
min_rate: float = 0.0 min_rate: Optional[float] = None
exit_reason: str = '' exit_reason: Optional[str] = ''
exit_order_status: str = '' exit_order_status: Optional[str] = ''
strategy: str = '' strategy: Optional[str] = ''
enter_tag: Optional[str] = None enter_tag: Optional[str] = None
timeframe: Optional[int] = None timeframe: Optional[int] = None
@ -511,6 +518,8 @@ class LocalTrade():
'close_timestamp': int(self.close_date.replace( 'close_timestamp': int(self.close_date.replace(
tzinfo=timezone.utc).timestamp() * 1000) if self.close_date else None, tzinfo=timezone.utc).timestamp() * 1000) if self.close_date else None,
'realized_profit': self.realized_profit or 0.0, 'realized_profit': self.realized_profit or 0.0,
# Close-profit corresponds to relative realized_profit ratio
'realized_profit_ratio': self.close_profit or None,
'close_rate': self.close_rate, 'close_rate': self.close_rate,
'close_rate_requested': self.close_rate_requested, 'close_rate_requested': self.close_rate_requested,
'close_profit': self.close_profit, # Deprecated 'close_profit': self.close_profit, # Deprecated
@ -551,6 +560,9 @@ class LocalTrade():
'trading_mode': self.trading_mode, 'trading_mode': self.trading_mode,
'funding_fees': self.funding_fees, 'funding_fees': self.funding_fees,
'open_order_id': self.open_order_id, 'open_order_id': self.open_order_id,
'amount_precision': self.amount_precision,
'price_precision': self.price_precision,
'precision_mode': self.precision_mode,
'orders': orders, 'orders': orders,
} }
@ -592,7 +604,7 @@ class LocalTrade():
self.stop_loss_pct = -1 * abs(percent) self.stop_loss_pct = -1 * abs(percent)
def adjust_stop_loss(self, current_price: float, stoploss: float, def adjust_stop_loss(self, current_price: float, stoploss: Optional[float],
initial: bool = False, refresh: bool = False) -> None: initial: bool = False, refresh: bool = False) -> None:
""" """
This adjusts the stop loss to it's most recently observed setting This adjusts the stop loss to it's most recently observed setting
@ -601,7 +613,7 @@ class LocalTrade():
:param initial: Called to initiate stop_loss. :param initial: Called to initiate stop_loss.
Skips everything if self.stop_loss is already set. Skips everything if self.stop_loss is already set.
""" """
if initial and not (self.stop_loss is None or self.stop_loss == 0): if stoploss is None or (initial and not (self.stop_loss is None or self.stop_loss == 0)):
# Don't modify if called with initial and nothing to do # Don't modify if called with initial and nothing to do
return return
refresh = True if refresh and self.nr_of_successful_entries == 1 else False refresh = True if refresh and self.nr_of_successful_entries == 1 else False
@ -640,7 +652,7 @@ class LocalTrade():
f"initial_stop_loss={self.initial_stop_loss:.8f}, " f"initial_stop_loss={self.initial_stop_loss:.8f}, "
f"stop_loss={self.stop_loss:.8f}. " f"stop_loss={self.stop_loss:.8f}. "
f"Trailing stoploss saved us: " f"Trailing stoploss saved us: "
f"{float(self.stop_loss) - float(self.initial_stop_loss):.8f}.") f"{float(self.stop_loss) - float(self.initial_stop_loss or 0.0):.8f}.")
def update_trade(self, order: Order) -> None: def update_trade(self, order: Order) -> None:
""" """
@ -792,10 +804,10 @@ class LocalTrade():
return interest(exchange_name=self.exchange, borrowed=borrowed, rate=rate, hours=hours) return interest(exchange_name=self.exchange, borrowed=borrowed, rate=rate, hours=hours)
def _calc_base_close(self, amount: FtPrecise, rate: float, fee: float) -> FtPrecise: def _calc_base_close(self, amount: FtPrecise, rate: float, fee: Optional[float]) -> FtPrecise:
close_trade = amount * FtPrecise(rate) close_trade = amount * FtPrecise(rate)
fees = close_trade * FtPrecise(fee) fees = close_trade * FtPrecise(fee or 0.0)
if self.is_short: if self.is_short:
return close_trade + fees return close_trade + fees
@ -1059,10 +1071,14 @@ class LocalTrade():
return len(self.select_filled_orders('sell')) return len(self.select_filled_orders('sell'))
@property @property
def sell_reason(self) -> str: def sell_reason(self) -> Optional[str]:
""" DEPRECATED! Please use exit_reason instead.""" """ DEPRECATED! Please use exit_reason instead."""
return self.exit_reason return self.exit_reason
@property
def safe_close_rate(self) -> float:
return self.close_rate or self.close_rate_requested or 0.0
@staticmethod @staticmethod
def get_trades_proxy(*, pair: Optional[str] = None, is_open: Optional[bool] = None, def get_trades_proxy(*, pair: Optional[str] = None, is_open: Optional[bool] = None,
open_date: Optional[datetime] = None, open_date: Optional[datetime] = None,
@ -1074,6 +1090,11 @@ class LocalTrade():
In live mode, converts the filter to a database query and returns all rows In live mode, converts the filter to a database query and returns all rows
In Backtest mode, uses filters on Trade.trades to get the result. In Backtest mode, uses filters on Trade.trades to get the result.
:param pair: Filter by pair
:param is_open: Filter by open/closed status
:param open_date: Filter by open_date (filters via trade.open_date > input)
:param close_date: Filter by close_date (filters via trade.close_date > input)
Will implicitly only return closed trades.
:return: unsorted List[Trade] :return: unsorted List[Trade]
""" """
@ -1124,7 +1145,7 @@ class LocalTrade():
@staticmethod @staticmethod
def get_open_trades() -> List[Any]: def get_open_trades() -> List[Any]:
""" """
Query trades from persistence layer Retrieve open trades
""" """
return Trade.get_trades_proxy(is_open=True) return Trade.get_trades_proxy(is_open=True)
@ -1134,7 +1155,9 @@ class LocalTrade():
get open trade count get open trade count
""" """
if Trade.use_db: if Trade.use_db:
return Trade.query.filter(Trade.is_open.is_(True)).count() return Trade.session.execute(
select(func.count(Trade.id)).filter(Trade.is_open.is_(True))
).scalar_one()
else: else:
return LocalTrade.bt_open_open_trade_count return LocalTrade.bt_open_open_trade_count
@ -1159,7 +1182,7 @@ class LocalTrade():
logger.info(f"New stoploss: {trade.stop_loss}.") logger.info(f"New stoploss: {trade.stop_loss}.")
class Trade(_DECL_BASE, LocalTrade): class Trade(ModelBase, LocalTrade):
""" """
Trade database model. Trade database model.
Also handles updating and querying trades Also handles updating and querying trades
@ -1167,79 +1190,97 @@ class Trade(_DECL_BASE, LocalTrade):
Note: Fields must be aligned with LocalTrade class Note: Fields must be aligned with LocalTrade class
""" """
__tablename__ = 'trades' __tablename__ = 'trades'
session: ClassVar[SessionType]
use_db: bool = True use_db: bool = True
id = Column(Integer, primary_key=True) id: Mapped[int] = mapped_column(Integer, primary_key=True) # type: ignore
orders = relationship("Order", order_by="Order.id", cascade="all, delete-orphan", orders: Mapped[List[Order]] = relationship(
lazy="selectin", innerjoin=True) "Order", order_by="Order.id", cascade="all, delete-orphan", lazy="selectin",
innerjoin=True) # type: ignore
exchange = Column(String(25), nullable=False) exchange: Mapped[str] = mapped_column(String(25), nullable=False) # type: ignore
pair = Column(String(25), nullable=False, index=True) pair: Mapped[str] = mapped_column(String(25), nullable=False, index=True) # type: ignore
base_currency = Column(String(25), nullable=True) base_currency: Mapped[Optional[str]] = mapped_column(String(25), nullable=True) # type: ignore
stake_currency = Column(String(25), nullable=True) stake_currency: Mapped[Optional[str]] = mapped_column(String(25), nullable=True) # type: ignore
is_open = Column(Boolean, nullable=False, default=True, index=True) is_open: Mapped[bool] = mapped_column(nullable=False, default=True, index=True) # type: ignore
fee_open = Column(Float(), nullable=False, default=0.0) fee_open: Mapped[float] = mapped_column(Float(), nullable=False, default=0.0) # type: ignore
fee_open_cost = Column(Float(), nullable=True) fee_open_cost: Mapped[Optional[float]] = mapped_column(Float(), nullable=True) # type: ignore
fee_open_currency = Column(String(25), nullable=True) fee_open_currency: Mapped[Optional[str]] = mapped_column(
fee_close = Column(Float(), nullable=False, default=0.0) String(25), nullable=True) # type: ignore
fee_close_cost = Column(Float(), nullable=True) fee_close: Mapped[Optional[float]] = mapped_column(
fee_close_currency = Column(String(25), nullable=True) Float(), nullable=False, default=0.0) # type: ignore
open_rate: float = Column(Float()) fee_close_cost: Mapped[Optional[float]] = mapped_column(Float(), nullable=True) # type: ignore
open_rate_requested = Column(Float()) fee_close_currency: Mapped[Optional[str]] = mapped_column(
String(25), nullable=True) # type: ignore
open_rate: Mapped[float] = mapped_column(Float()) # type: ignore
open_rate_requested: Mapped[Optional[float]] = mapped_column(
Float(), nullable=True) # type: ignore
# open_trade_value - calculated via _calc_open_trade_value # open_trade_value - calculated via _calc_open_trade_value
open_trade_value = Column(Float()) open_trade_value: Mapped[float] = mapped_column(Float(), nullable=True) # type: ignore
close_rate: Optional[float] = Column(Float()) close_rate: Mapped[Optional[float]] = mapped_column(Float()) # type: ignore
close_rate_requested = Column(Float()) close_rate_requested: Mapped[Optional[float]] = mapped_column(Float()) # type: ignore
realized_profit = Column(Float(), default=0.0) realized_profit: Mapped[float] = mapped_column(
close_profit = Column(Float()) Float(), default=0.0, nullable=True) # type: ignore
close_profit_abs = Column(Float()) close_profit: Mapped[Optional[float]] = mapped_column(Float()) # type: ignore
stake_amount = Column(Float(), nullable=False) close_profit_abs: Mapped[Optional[float]] = mapped_column(Float()) # type: ignore
max_stake_amount = Column(Float()) stake_amount: Mapped[float] = mapped_column(Float(), nullable=False) # type: ignore
amount = Column(Float()) max_stake_amount: Mapped[Optional[float]] = mapped_column(Float()) # type: ignore
amount_requested = Column(Float()) amount: Mapped[float] = mapped_column(Float()) # type: ignore
open_date = Column(DateTime(), nullable=False, default=datetime.utcnow) amount_requested: Mapped[Optional[float]] = mapped_column(Float()) # type: ignore
close_date = Column(DateTime()) open_date: Mapped[datetime] = mapped_column(
open_order_id = Column(String(255)) nullable=False, default=datetime.utcnow) # type: ignore
close_date: Mapped[Optional[datetime]] = mapped_column() # type: ignore
open_order_id: Mapped[Optional[str]] = mapped_column(String(255), nullable=True) # type: ignore
# absolute value of the stop loss # absolute value of the stop loss
stop_loss = Column(Float(), nullable=True, default=0.0) stop_loss: Mapped[float] = mapped_column(Float(), nullable=True, default=0.0) # type: ignore
# percentage value of the stop loss # percentage value of the stop loss
stop_loss_pct = Column(Float(), nullable=True) stop_loss_pct: Mapped[Optional[float]] = mapped_column(Float(), nullable=True) # type: ignore
# absolute value of the initial stop loss # absolute value of the initial stop loss
initial_stop_loss = Column(Float(), nullable=True, default=0.0) initial_stop_loss: Mapped[Optional[float]] = mapped_column(
Float(), nullable=True, default=0.0) # type: ignore
# percentage value of the initial stop loss # percentage value of the initial stop loss
initial_stop_loss_pct = Column(Float(), nullable=True) initial_stop_loss_pct: Mapped[Optional[float]] = mapped_column(
Float(), nullable=True) # type: ignore
# stoploss order id which is on exchange # stoploss order id which is on exchange
stoploss_order_id = Column(String(255), nullable=True, index=True) stoploss_order_id: Mapped[Optional[str]] = mapped_column(
String(255), nullable=True, index=True) # type: ignore
# last update time of the stoploss order on exchange # last update time of the stoploss order on exchange
stoploss_last_update = Column(DateTime(), nullable=True) stoploss_last_update: Mapped[Optional[datetime]] = mapped_column(nullable=True) # type: ignore
# absolute value of the highest reached price # absolute value of the highest reached price
max_rate = Column(Float(), nullable=True, default=0.0) max_rate: Mapped[Optional[float]] = mapped_column(
Float(), nullable=True, default=0.0) # type: ignore
# Lowest price reached # Lowest price reached
min_rate = Column(Float(), nullable=True) min_rate: Mapped[Optional[float]] = mapped_column(Float(), nullable=True) # type: ignore
exit_reason = Column(String(100), nullable=True) exit_reason: Mapped[Optional[str]] = mapped_column(String(100), nullable=True) # type: ignore
exit_order_status = Column(String(100), nullable=True) exit_order_status: Mapped[Optional[str]] = mapped_column(
strategy = Column(String(100), nullable=True) String(100), nullable=True) # type: ignore
enter_tag = Column(String(100), nullable=True) strategy: Mapped[Optional[str]] = mapped_column(String(100), nullable=True) # type: ignore
timeframe = Column(Integer, nullable=True) enter_tag: Mapped[Optional[str]] = mapped_column(String(100), nullable=True) # type: ignore
timeframe: Mapped[Optional[int]] = mapped_column(Integer, nullable=True) # type: ignore
trading_mode = Column(Enum(TradingMode), nullable=True) trading_mode: Mapped[TradingMode] = mapped_column(
amount_precision = Column(Float(), nullable=True) Enum(TradingMode), nullable=True) # type: ignore
price_precision = Column(Float(), nullable=True) amount_precision: Mapped[Optional[float]] = mapped_column(
precision_mode = Column(Integer, nullable=True) Float(), nullable=True) # type: ignore
contract_size = Column(Float(), nullable=True) price_precision: Mapped[Optional[float]] = mapped_column(Float(), nullable=True) # type: ignore
precision_mode: Mapped[Optional[int]] = mapped_column(Integer, nullable=True) # type: ignore
contract_size: Mapped[Optional[float]] = mapped_column(Float(), nullable=True) # type: ignore
# Leverage trading properties # Leverage trading properties
leverage = Column(Float(), nullable=True, default=1.0) leverage: Mapped[float] = mapped_column(Float(), nullable=True, default=1.0) # type: ignore
is_short = Column(Boolean, nullable=False, default=False) is_short: Mapped[bool] = mapped_column(nullable=False, default=False) # type: ignore
liquidation_price = Column(Float(), nullable=True) liquidation_price: Mapped[Optional[float]] = mapped_column(
Float(), nullable=True) # type: ignore
# Margin Trading Properties # Margin Trading Properties
interest_rate = Column(Float(), nullable=False, default=0.0) interest_rate: Mapped[float] = mapped_column(
Float(), nullable=False, default=0.0) # type: ignore
# Futures properties # Futures properties
funding_fees = Column(Float(), nullable=True, default=None) funding_fees: Mapped[Optional[float]] = mapped_column(
Float(), nullable=True, default=None) # type: ignore
def __init__(self, **kwargs): def __init__(self, **kwargs):
super().__init__(**kwargs) super().__init__(**kwargs)
@ -1249,18 +1290,18 @@ class Trade(_DECL_BASE, LocalTrade):
def delete(self) -> None: def delete(self) -> None:
for order in self.orders: for order in self.orders:
Order.query.session.delete(order) Order.session.delete(order)
Trade.query.session.delete(self) Trade.session.delete(self)
Trade.commit() Trade.commit()
@staticmethod @staticmethod
def commit(): def commit():
Trade.query.session.commit() Trade.session.commit()
@staticmethod @staticmethod
def rollback(): def rollback():
Trade.query.session.rollback() Trade.session.rollback()
@staticmethod @staticmethod
def get_trades_proxy(*, pair: Optional[str] = None, is_open: Optional[bool] = None, def get_trades_proxy(*, pair: Optional[str] = None, is_open: Optional[bool] = None,
@ -1285,7 +1326,7 @@ class Trade(_DECL_BASE, LocalTrade):
trade_filter.append(Trade.close_date > close_date) trade_filter.append(Trade.close_date > close_date)
if is_open is not None: if is_open is not None:
trade_filter.append(Trade.is_open.is_(is_open)) trade_filter.append(Trade.is_open.is_(is_open))
return Trade.get_trades(trade_filter).all() return cast(List[LocalTrade], Trade.get_trades(trade_filter).all())
else: else:
return LocalTrade.get_trades_proxy( return LocalTrade.get_trades_proxy(
pair=pair, is_open=is_open, pair=pair, is_open=is_open,
@ -1294,7 +1335,7 @@ class Trade(_DECL_BASE, LocalTrade):
) )
@staticmethod @staticmethod
def get_trades(trade_filter=None, include_orders: bool = True) -> Query: def get_trades_query(trade_filter=None, include_orders: bool = True) -> Select:
""" """
Helper function to query Trades using filters. Helper function to query Trades using filters.
NOTE: Not supported in Backtesting. NOTE: Not supported in Backtesting.
@ -1309,22 +1350,35 @@ class Trade(_DECL_BASE, LocalTrade):
if trade_filter is not None: if trade_filter is not None:
if not isinstance(trade_filter, list): if not isinstance(trade_filter, list):
trade_filter = [trade_filter] trade_filter = [trade_filter]
this_query = Trade.query.filter(*trade_filter) this_query = select(Trade).filter(*trade_filter)
else: else:
this_query = Trade.query this_query = select(Trade)
if not include_orders: if not include_orders:
# Don't load order relations # Don't load order relations
# Consider using noload or raiseload instead of lazyload # Consider using noload or raiseload instead of lazyload
this_query = this_query.options(lazyload(Trade.orders)) this_query = this_query.options(lazyload(Trade.orders))
return this_query return this_query
@staticmethod
def get_trades(trade_filter=None, include_orders: bool = True) -> ScalarResult['Trade']:
"""
Helper function to query Trades using filters.
NOTE: Not supported in Backtesting.
:param trade_filter: Optional filter to apply to trades
Can be either a Filter object, or a List of filters
e.g. `(trade_filter=[Trade.id == trade_id, Trade.is_open.is_(True),])`
e.g. `(trade_filter=Trade.id == trade_id)`
:return: unsorted query object
"""
return Trade.session.scalars(Trade.get_trades_query(trade_filter, include_orders))
@staticmethod @staticmethod
def get_open_order_trades() -> List['Trade']: def get_open_order_trades() -> List['Trade']:
""" """
Returns all open trades Returns all open trades
NOTE: Not supported in Backtesting. NOTE: Not supported in Backtesting.
""" """
return Trade.get_trades(Trade.open_order_id.isnot(None)).all() return cast(List[Trade], Trade.get_trades(Trade.open_order_id.isnot(None)).all())
@staticmethod @staticmethod
def get_open_trades_without_assigned_fees(): def get_open_trades_without_assigned_fees():
@ -1354,11 +1408,12 @@ class Trade(_DECL_BASE, LocalTrade):
Retrieves total realized profit Retrieves total realized profit
""" """
if Trade.use_db: if Trade.use_db:
total_profit = Trade.query.with_entities( total_profit: float = Trade.session.execute(
func.sum(Trade.close_profit_abs)).filter(Trade.is_open.is_(False)).scalar() select(func.sum(Trade.close_profit_abs)).filter(Trade.is_open.is_(False))
).scalar_one()
else: else:
total_profit = sum( total_profit = sum(t.close_profit_abs # type: ignore
t.close_profit_abs for t in LocalTrade.get_trades_proxy(is_open=False)) for t in LocalTrade.get_trades_proxy(is_open=False))
return total_profit or 0 return total_profit or 0
@staticmethod @staticmethod
@ -1368,8 +1423,9 @@ class Trade(_DECL_BASE, LocalTrade):
in stake currency in stake currency
""" """
if Trade.use_db: if Trade.use_db:
total_open_stake_amount = Trade.query.with_entities( total_open_stake_amount = Trade.session.scalar(
func.sum(Trade.stake_amount)).filter(Trade.is_open.is_(True)).scalar() select(func.sum(Trade.stake_amount)).filter(Trade.is_open.is_(True))
)
else: else:
total_open_stake_amount = sum( total_open_stake_amount = sum(
t.stake_amount for t in LocalTrade.get_trades_proxy(is_open=True)) t.stake_amount for t in LocalTrade.get_trades_proxy(is_open=True))
@ -1381,19 +1437,22 @@ class Trade(_DECL_BASE, LocalTrade):
Returns List of dicts containing all Trades, including profit and trade count Returns List of dicts containing all Trades, including profit and trade count
NOTE: Not supported in Backtesting. NOTE: Not supported in Backtesting.
""" """
filters = [Trade.is_open.is_(False)] filters: List = [Trade.is_open.is_(False)]
if minutes: if minutes:
start_date = datetime.now(timezone.utc) - timedelta(minutes=minutes) start_date = datetime.now(timezone.utc) - timedelta(minutes=minutes)
filters.append(Trade.close_date >= start_date) filters.append(Trade.close_date >= start_date)
pair_rates = Trade.query.with_entities(
pair_rates = Trade.session.execute(
select(
Trade.pair, Trade.pair,
func.sum(Trade.close_profit).label('profit_sum'), func.sum(Trade.close_profit).label('profit_sum'),
func.sum(Trade.close_profit_abs).label('profit_sum_abs'), func.sum(Trade.close_profit_abs).label('profit_sum_abs'),
func.count(Trade.pair).label('count') func.count(Trade.pair).label('count')
).filter(*filters)\ ).filter(*filters)
.group_by(Trade.pair) \ .group_by(Trade.pair)
.order_by(desc('profit_sum_abs')) \ .order_by(desc('profit_sum_abs'))
.all() ).all()
return [ return [
{ {
'pair': pair, 'pair': pair,
@ -1414,19 +1473,20 @@ class Trade(_DECL_BASE, LocalTrade):
NOTE: Not supported in Backtesting. NOTE: Not supported in Backtesting.
""" """
filters = [Trade.is_open.is_(False)] filters: List = [Trade.is_open.is_(False)]
if (pair is not None): if (pair is not None):
filters.append(Trade.pair == pair) filters.append(Trade.pair == pair)
enter_tag_perf = Trade.query.with_entities( enter_tag_perf = Trade.session.execute(
select(
Trade.enter_tag, Trade.enter_tag,
func.sum(Trade.close_profit).label('profit_sum'), func.sum(Trade.close_profit).label('profit_sum'),
func.sum(Trade.close_profit_abs).label('profit_sum_abs'), func.sum(Trade.close_profit_abs).label('profit_sum_abs'),
func.count(Trade.pair).label('count') func.count(Trade.pair).label('count')
).filter(*filters)\ ).filter(*filters)
.group_by(Trade.enter_tag) \ .group_by(Trade.enter_tag)
.order_by(desc('profit_sum_abs')) \ .order_by(desc('profit_sum_abs'))
.all() ).all()
return [ return [
{ {
@ -1447,19 +1507,19 @@ class Trade(_DECL_BASE, LocalTrade):
NOTE: Not supported in Backtesting. NOTE: Not supported in Backtesting.
""" """
filters = [Trade.is_open.is_(False)] filters: List = [Trade.is_open.is_(False)]
if (pair is not None): if (pair is not None):
filters.append(Trade.pair == pair) filters.append(Trade.pair == pair)
sell_tag_perf = Trade.session.execute(
sell_tag_perf = Trade.query.with_entities( select(
Trade.exit_reason, Trade.exit_reason,
func.sum(Trade.close_profit).label('profit_sum'), func.sum(Trade.close_profit).label('profit_sum'),
func.sum(Trade.close_profit_abs).label('profit_sum_abs'), func.sum(Trade.close_profit_abs).label('profit_sum_abs'),
func.count(Trade.pair).label('count') func.count(Trade.pair).label('count')
).filter(*filters)\ ).filter(*filters)
.group_by(Trade.exit_reason) \ .group_by(Trade.exit_reason)
.order_by(desc('profit_sum_abs')) \ .order_by(desc('profit_sum_abs'))
.all() ).all()
return [ return [
{ {
@ -1480,21 +1540,21 @@ class Trade(_DECL_BASE, LocalTrade):
NOTE: Not supported in Backtesting. NOTE: Not supported in Backtesting.
""" """
filters = [Trade.is_open.is_(False)] filters: List = [Trade.is_open.is_(False)]
if (pair is not None): if (pair is not None):
filters.append(Trade.pair == pair) filters.append(Trade.pair == pair)
mix_tag_perf = Trade.session.execute(
mix_tag_perf = Trade.query.with_entities( select(
Trade.id, Trade.id,
Trade.enter_tag, Trade.enter_tag,
Trade.exit_reason, Trade.exit_reason,
func.sum(Trade.close_profit).label('profit_sum'), func.sum(Trade.close_profit).label('profit_sum'),
func.sum(Trade.close_profit_abs).label('profit_sum_abs'), func.sum(Trade.close_profit_abs).label('profit_sum_abs'),
func.count(Trade.pair).label('count') func.count(Trade.pair).label('count')
).filter(*filters)\ ).filter(*filters)
.group_by(Trade.id) \ .group_by(Trade.id)
.order_by(desc('profit_sum_abs')) \ .order_by(desc('profit_sum_abs'))
.all() ).all()
return_list: List[Dict] = [] return_list: List[Dict] = []
for id, enter_tag, exit_reason, profit, profit_abs, count in mix_tag_perf: for id, enter_tag, exit_reason, profit, profit_abs, count in mix_tag_perf:
@ -1530,11 +1590,15 @@ class Trade(_DECL_BASE, LocalTrade):
NOTE: Not supported in Backtesting. NOTE: Not supported in Backtesting.
:returns: Tuple containing (pair, profit_sum) :returns: Tuple containing (pair, profit_sum)
""" """
best_pair = Trade.query.with_entities( best_pair = Trade.session.execute(
Trade.pair, func.sum(Trade.close_profit).label('profit_sum') select(
).filter(Trade.is_open.is_(False) & (Trade.close_date >= start_date)) \ Trade.pair,
.group_by(Trade.pair) \ func.sum(Trade.close_profit).label('profit_sum')
.order_by(desc('profit_sum')).first() ).filter(Trade.is_open.is_(False) & (Trade.close_date >= start_date))
.group_by(Trade.pair)
.order_by(desc('profit_sum'))
).first()
return best_pair return best_pair
@staticmethod @staticmethod
@ -1544,12 +1608,13 @@ class Trade(_DECL_BASE, LocalTrade):
NOTE: Not supported in Backtesting. NOTE: Not supported in Backtesting.
:returns: Tuple containing (pair, profit_sum) :returns: Tuple containing (pair, profit_sum)
""" """
trading_volume = Order.query.with_entities( trading_volume = Trade.session.execute(
select(
func.sum(Order.cost).label('volume') func.sum(Order.cost).label('volume')
).filter( ).filter(
Order.order_filled_date >= start_date, Order.order_filled_date >= start_date,
Order.status == 'closed' Order.status == 'closed'
).scalar() )).scalar_one()
return trading_volume return trading_volume
@staticmethod @staticmethod
@ -1598,8 +1663,10 @@ class Trade(_DECL_BASE, LocalTrade):
stop_loss=data["stop_loss_abs"], stop_loss=data["stop_loss_abs"],
stop_loss_pct=data["stop_loss_ratio"], stop_loss_pct=data["stop_loss_ratio"],
stoploss_order_id=data["stoploss_order_id"], stoploss_order_id=data["stoploss_order_id"],
stoploss_last_update=(datetime.fromtimestamp(data["stoploss_last_update"] // 1000, stoploss_last_update=(
tz=timezone.utc) if data["stoploss_last_update"] else None), datetime.fromtimestamp(data["stoploss_last_update_timestamp"] // 1000,
tz=timezone.utc)
if data["stoploss_last_update_timestamp"] else None),
initial_stop_loss=data["initial_stop_loss_abs"], initial_stop_loss=data["initial_stop_loss_abs"],
initial_stop_loss_pct=data["initial_stop_loss_ratio"], initial_stop_loss_pct=data["initial_stop_loss_ratio"],
min_rate=data["min_rate"], min_rate=data["min_rate"],

View File

@ -1,4 +1,5 @@
import logging import logging
from datetime import datetime, timezone
from pathlib import Path from pathlib import Path
from typing import Dict, List, Optional from typing import Dict, List, Optional
@ -635,7 +636,7 @@ def load_and_plot_trades(config: Config):
exchange = ExchangeResolver.load_exchange(config['exchange']['name'], config) exchange = ExchangeResolver.load_exchange(config['exchange']['name'], config)
IStrategy.dp = DataProvider(config, exchange) IStrategy.dp = DataProvider(config, exchange)
strategy.ft_bot_start() strategy.ft_bot_start()
strategy.bot_loop_start() strategy.bot_loop_start(datetime.now(timezone.utc))
plot_elements = init_plotscript(config, list(exchange.markets), strategy.startup_candle_count) plot_elements = init_plotscript(config, list(exchange.markets), strategy.startup_candle_count)
timerange = plot_elements['timerange'] timerange = plot_elements['timerange']
trades = plot_elements['trades'] trades = plot_elements['trades']

View File

@ -157,7 +157,7 @@ class RemotePairList(IPairList):
file_path = Path(filename) file_path = Path(filename)
if file_path.exists(): if file_path.exists():
with open(filename) as json_file: with file_path.open() as json_file:
# Load the JSON data into a dictionary # Load the JSON data into a dictionary
jsonparse = json.load(json_file) jsonparse = json.load(json_file)

View File

@ -5,6 +5,7 @@ import logging
from typing import Any, Dict, Optional from typing import Any, Dict, Optional
from freqtrade.constants import Config from freqtrade.constants import Config
from freqtrade.exceptions import OperationalException
from freqtrade.exchange.types import Ticker from freqtrade.exchange.types import Ticker
from freqtrade.plugins.pairlist.IPairList import IPairList from freqtrade.plugins.pairlist.IPairList import IPairList
@ -22,6 +23,12 @@ class SpreadFilter(IPairList):
self._max_spread_ratio = pairlistconfig.get('max_spread_ratio', 0.005) self._max_spread_ratio = pairlistconfig.get('max_spread_ratio', 0.005)
self._enabled = self._max_spread_ratio != 0 self._enabled = self._max_spread_ratio != 0
if not self._exchange.get_option('tickers_have_bid_ask'):
raise OperationalException(
f"{self.name} requires exchange to have bid/ask data for tickers, "
"which is not available for the selected exchange / trading mode."
)
@property @property
def needstickers(self) -> bool: def needstickers(self) -> bool:
""" """

View File

@ -228,24 +228,33 @@ class TradeSchema(BaseModel):
fee_close: Optional[float] fee_close: Optional[float]
fee_close_cost: Optional[float] fee_close_cost: Optional[float]
fee_close_currency: Optional[str] fee_close_currency: Optional[str]
open_date: str open_date: str
open_timestamp: int open_timestamp: int
open_rate: float open_rate: float
open_rate_requested: Optional[float] open_rate_requested: Optional[float]
open_trade_value: float open_trade_value: float
close_date: Optional[str] close_date: Optional[str]
close_timestamp: Optional[int] close_timestamp: Optional[int]
close_rate: Optional[float] close_rate: Optional[float]
close_rate_requested: Optional[float] close_rate_requested: Optional[float]
close_profit: Optional[float] close_profit: Optional[float]
close_profit_pct: Optional[float] close_profit_pct: Optional[float]
close_profit_abs: Optional[float] close_profit_abs: Optional[float]
profit_ratio: Optional[float] profit_ratio: Optional[float]
profit_pct: Optional[float] profit_pct: Optional[float]
profit_abs: Optional[float] profit_abs: Optional[float]
profit_fiat: Optional[float] profit_fiat: Optional[float]
realized_profit: float
realized_profit_ratio: Optional[float]
exit_reason: Optional[str] exit_reason: Optional[str]
exit_order_status: Optional[str] exit_order_status: Optional[str]
stop_loss_abs: Optional[float] stop_loss_abs: Optional[float]
stop_loss_ratio: Optional[float] stop_loss_ratio: Optional[float]
stop_loss_pct: Optional[float] stop_loss_pct: Optional[float]
@ -255,6 +264,7 @@ class TradeSchema(BaseModel):
initial_stop_loss_abs: Optional[float] initial_stop_loss_abs: Optional[float]
initial_stop_loss_ratio: Optional[float] initial_stop_loss_ratio: Optional[float]
initial_stop_loss_pct: Optional[float] initial_stop_loss_pct: Optional[float]
min_rate: Optional[float] min_rate: Optional[float]
max_rate: Optional[float] max_rate: Optional[float]
open_order_id: Optional[str] open_order_id: Optional[str]
@ -266,6 +276,10 @@ class TradeSchema(BaseModel):
funding_fees: Optional[float] funding_fees: Optional[float]
trading_mode: Optional[TradingMode] trading_mode: Optional[TradingMode]
amount_precision: Optional[float]
price_precision: Optional[float]
precision_mode: Optional[int]
class OpenTradeSchema(TradeSchema): class OpenTradeSchema(TradeSchema):
stoploss_current_dist: Optional[float] stoploss_current_dist: Optional[float]
@ -273,10 +287,11 @@ class OpenTradeSchema(TradeSchema):
stoploss_current_dist_ratio: Optional[float] stoploss_current_dist_ratio: Optional[float]
stoploss_entry_dist: Optional[float] stoploss_entry_dist: Optional[float]
stoploss_entry_dist_ratio: Optional[float] stoploss_entry_dist_ratio: Optional[float]
current_profit: float
current_profit_abs: float
current_profit_pct: float
current_rate: float current_rate: float
total_profit_abs: float
total_profit_fiat: Optional[float]
total_profit_ratio: Optional[float]
open_order: Optional[str] open_order: Optional[str]
@ -300,7 +315,7 @@ class LockModel(BaseModel):
lock_timestamp: int lock_timestamp: int
pair: str pair: str
side: str side: str
reason: str reason: Optional[str]
class Locks(BaseModel): class Locks(BaseModel):
@ -456,5 +471,5 @@ class SysInfo(BaseModel):
class Health(BaseModel): class Health(BaseModel):
last_process: datetime last_process: Optional[datetime]
last_process_ts: int last_process_ts: Optional[int]

View File

@ -42,7 +42,8 @@ logger = logging.getLogger(__name__)
# 2.22: Add FreqAI to backtesting # 2.22: Add FreqAI to backtesting
# 2.23: Allow plot config request in webserver mode # 2.23: Allow plot config request in webserver mode
# 2.24: Add cancel_open_order endpoint # 2.24: Add cancel_open_order endpoint
API_VERSION = 2.24 # 2.25: Add several profit values to /status endpoint
API_VERSION = 2.25
# Public API, requires no auth. # Public API, requires no auth.
router_public = APIRouter() router_public = APIRouter()
@ -346,4 +347,4 @@ def sysinfo():
@router.get('/health', response_model=Health, tags=['info']) @router.get('/health', response_model=Health, tags=['info'])
def health(rpc: RPC = Depends(get_rpc)): def health(rpc: RPC = Depends(get_rpc)):
return rpc._health() return rpc.health()

View File

@ -1,9 +1,11 @@
from typing import Any, Dict, Iterator, Optional from typing import Any, AsyncIterator, Dict, Optional
from uuid import uuid4
from fastapi import Depends from fastapi import Depends
from freqtrade.enums import RunMode from freqtrade.enums import RunMode
from freqtrade.persistence import Trade from freqtrade.persistence import Trade
from freqtrade.persistence.models import _request_id_ctx_var
from freqtrade.rpc.rpc import RPC, RPCException from freqtrade.rpc.rpc import RPC, RPCException
from .webserver import ApiServer from .webserver import ApiServer
@ -15,12 +17,19 @@ def get_rpc_optional() -> Optional[RPC]:
return None return None
def get_rpc() -> Optional[Iterator[RPC]]: async def get_rpc() -> Optional[AsyncIterator[RPC]]:
_rpc = get_rpc_optional() _rpc = get_rpc_optional()
if _rpc: if _rpc:
request_id = str(uuid4())
ctx_token = _request_id_ctx_var.set(request_id)
Trade.rollback() Trade.rollback()
try:
yield _rpc yield _rpc
Trade.rollback() finally:
Trade.session.remove()
_request_id_ctx_var.reset(ctx_token)
else: else:
raise RPCException('Bot is not in the correct state') raise RPCException('Bot is not in the correct state')

View File

@ -13,6 +13,7 @@ from freqtrade.exceptions import OperationalException
from freqtrade.rpc.api_server.uvicorn_threaded import UvicornServer from freqtrade.rpc.api_server.uvicorn_threaded import UvicornServer
from freqtrade.rpc.api_server.ws.message_stream import MessageStream from freqtrade.rpc.api_server.ws.message_stream import MessageStream
from freqtrade.rpc.rpc import RPC, RPCException, RPCHandler from freqtrade.rpc.rpc import RPC, RPCException, RPCHandler
from freqtrade.rpc.rpc_types import RPCSendMsg
logger = logging.getLogger(__name__) logger = logging.getLogger(__name__)
@ -108,7 +109,7 @@ class ApiServer(RPCHandler):
cls._has_rpc = False cls._has_rpc = False
cls._rpc = None cls._rpc = None
def send_msg(self, msg: Dict[str, Any]) -> None: def send_msg(self, msg: RPCSendMsg) -> None:
""" """
Publish the message to the message stream Publish the message to the message stream
""" """

View File

@ -5,7 +5,7 @@ import logging
from abc import abstractmethod from abc import abstractmethod
from datetime import date, datetime, timedelta, timezone from datetime import date, datetime, timedelta, timezone
from math import isnan from math import isnan
from typing import Any, Dict, Generator, List, Optional, Tuple, Union from typing import Any, Dict, Generator, List, Optional, Sequence, Tuple, Union
import arrow import arrow
import psutil import psutil
@ -13,14 +13,15 @@ from dateutil.relativedelta import relativedelta
from dateutil.tz import tzlocal from dateutil.tz import tzlocal
from numpy import NAN, inf, int64, mean from numpy import NAN, inf, int64, mean
from pandas import DataFrame, NaT from pandas import DataFrame, NaT
from sqlalchemy import func, select
from freqtrade import __version__ from freqtrade import __version__
from freqtrade.configuration.timerange import TimeRange from freqtrade.configuration.timerange import TimeRange
from freqtrade.constants import CANCEL_REASON, DATETIME_PRINT_FORMAT, Config from freqtrade.constants import CANCEL_REASON, DATETIME_PRINT_FORMAT, Config
from freqtrade.data.history import load_data from freqtrade.data.history import load_data
from freqtrade.data.metrics import calculate_max_drawdown from freqtrade.data.metrics import calculate_max_drawdown
from freqtrade.enums import (CandleType, ExitCheckTuple, ExitType, SignalDirection, State, from freqtrade.enums import (CandleType, ExitCheckTuple, ExitType, MarketDirection, SignalDirection,
TradingMode) State, TradingMode)
from freqtrade.exceptions import ExchangeError, PricingError from freqtrade.exceptions import ExchangeError, PricingError
from freqtrade.exchange import timeframe_to_minutes, timeframe_to_msecs from freqtrade.exchange import timeframe_to_minutes, timeframe_to_msecs
from freqtrade.loggers import bufferHandler from freqtrade.loggers import bufferHandler
@ -29,6 +30,7 @@ from freqtrade.persistence import Order, PairLocks, Trade
from freqtrade.persistence.models import PairLock from freqtrade.persistence.models import PairLock
from freqtrade.plugins.pairlist.pairlist_helpers import expand_pairlist from freqtrade.plugins.pairlist.pairlist_helpers import expand_pairlist
from freqtrade.rpc.fiat_convert import CryptoToFiatConverter from freqtrade.rpc.fiat_convert import CryptoToFiatConverter
from freqtrade.rpc.rpc_types import RPCSendMsg
from freqtrade.wallets import PositionWallet, Wallet from freqtrade.wallets import PositionWallet, Wallet
@ -78,7 +80,7 @@ class RPCHandler:
""" Cleanup pending module resources """ """ Cleanup pending module resources """
@abstractmethod @abstractmethod
def send_msg(self, msg: Dict[str, str]) -> None: def send_msg(self, msg: RPCSendMsg) -> None:
""" Sends a message to all registered rpc modules """ """ Sends a message to all registered rpc modules """
@ -122,7 +124,8 @@ class RPC:
if config['max_open_trades'] != float('inf') else -1), if config['max_open_trades'] != float('inf') else -1),
'minimal_roi': config['minimal_roi'].copy() if 'minimal_roi' in config else {}, 'minimal_roi': config['minimal_roi'].copy() if 'minimal_roi' in config else {},
'stoploss': config.get('stoploss'), 'stoploss': config.get('stoploss'),
'stoploss_on_exchange': config.get('stoploss_on_exchange', False), 'stoploss_on_exchange': config.get('order_types',
{}).get('stoploss_on_exchange', False),
'trailing_stop': config.get('trailing_stop'), 'trailing_stop': config.get('trailing_stop'),
'trailing_stop_positive': config.get('trailing_stop_positive'), 'trailing_stop_positive': config.get('trailing_stop_positive'),
'trailing_stop_positive_offset': config.get('trailing_stop_positive_offset'), 'trailing_stop_positive_offset': config.get('trailing_stop_positive_offset'),
@ -158,7 +161,7 @@ class RPC:
""" """
# Fetch open trades # Fetch open trades
if trade_ids: if trade_ids:
trades: List[Trade] = Trade.get_trades(trade_filter=Trade.id.in_(trade_ids)).all() trades: Sequence[Trade] = Trade.get_trades(trade_filter=Trade.id.in_(trade_ids)).all()
else: else:
trades = Trade.get_open_trades() trades = Trade.get_open_trades()
@ -169,6 +172,7 @@ class RPC:
for trade in trades: for trade in trades:
order: Optional[Order] = None order: Optional[Order] = None
current_profit_fiat: Optional[float] = None current_profit_fiat: Optional[float] = None
total_profit_fiat: Optional[float] = None
if trade.open_order_id: if trade.open_order_id:
order = trade.select_order_by_order_id(trade.open_order_id) order = trade.select_order_by_order_id(trade.open_order_id)
# calculate profit and send message to user # calculate profit and send message to user
@ -188,8 +192,14 @@ class RPC:
else: else:
# Closed trade ... # Closed trade ...
current_rate = trade.close_rate current_rate = trade.close_rate
current_profit = trade.close_profit current_profit = trade.close_profit or 0.0
current_profit_abs = trade.close_profit_abs current_profit_abs = trade.close_profit_abs or 0.0
total_profit_abs = trade.realized_profit + current_profit_abs
total_profit_ratio: Optional[float] = None
if trade.max_stake_amount:
total_profit_ratio = (
(total_profit_abs / trade.max_stake_amount) * trade.leverage
)
# Calculate fiat profit # Calculate fiat profit
if not isnan(current_profit_abs) and self._fiat_converter: if not isnan(current_profit_abs) and self._fiat_converter:
@ -198,6 +208,11 @@ class RPC:
self._freqtrade.config['stake_currency'], self._freqtrade.config['stake_currency'],
self._freqtrade.config['fiat_display_currency'] self._freqtrade.config['fiat_display_currency']
) )
total_profit_fiat = self._fiat_converter.convert_amount(
total_profit_abs,
self._freqtrade.config['stake_currency'],
self._freqtrade.config['fiat_display_currency']
)
# Calculate guaranteed profit (in case of trailing stop) # Calculate guaranteed profit (in case of trailing stop)
stoploss_entry_dist = trade.calc_profit(trade.stop_loss) stoploss_entry_dist = trade.calc_profit(trade.stop_loss)
@ -210,14 +225,14 @@ class RPC:
trade_dict.update(dict( trade_dict.update(dict(
close_profit=trade.close_profit if not trade.is_open else None, close_profit=trade.close_profit if not trade.is_open else None,
current_rate=current_rate, current_rate=current_rate,
current_profit=current_profit, # Deprecated
current_profit_pct=round(current_profit * 100, 2), # Deprecated
current_profit_abs=current_profit_abs, # Deprecated
profit_ratio=current_profit, profit_ratio=current_profit,
profit_pct=round(current_profit * 100, 2), profit_pct=round(current_profit * 100, 2),
profit_abs=current_profit_abs, profit_abs=current_profit_abs,
profit_fiat=current_profit_fiat, profit_fiat=current_profit_fiat,
total_profit_abs=total_profit_abs,
total_profit_fiat=total_profit_fiat,
total_profit_ratio=total_profit_ratio,
stoploss_current_dist=stoploss_current_dist, stoploss_current_dist=stoploss_current_dist,
stoploss_current_dist_ratio=round(stoploss_current_dist_ratio, 8), stoploss_current_dist_ratio=round(stoploss_current_dist_ratio, 8),
stoploss_current_dist_pct=round(stoploss_current_dist_ratio * 100, 2), stoploss_current_dist_pct=round(stoploss_current_dist_ratio * 100, 2),
@ -327,11 +342,13 @@ class RPC:
for day in range(0, timescale): for day in range(0, timescale):
profitday = start_date - time_offset(day) profitday = start_date - time_offset(day)
# Only query for necessary columns for performance reasons. # Only query for necessary columns for performance reasons.
trades = Trade.query.session.query(Trade.close_profit_abs).filter( trades = Trade.session.execute(
Trade.is_open.is_(False), select(Trade.close_profit_abs)
.filter(Trade.is_open.is_(False),
Trade.close_date >= profitday, Trade.close_date >= profitday,
Trade.close_date < (profitday + time_offset(1)) Trade.close_date < (profitday + time_offset(1)))
).order_by(Trade.close_date).all() .order_by(Trade.close_date)
).all()
curdayprofit = sum( curdayprofit = sum(
trade.close_profit_abs for trade in trades if trade.close_profit_abs is not None) trade.close_profit_abs for trade in trades if trade.close_profit_abs is not None)
@ -367,21 +384,27 @@ class RPC:
def _rpc_trade_history(self, limit: int, offset: int = 0, order_by_id: bool = False) -> Dict: def _rpc_trade_history(self, limit: int, offset: int = 0, order_by_id: bool = False) -> Dict:
""" Returns the X last trades """ """ Returns the X last trades """
order_by = Trade.id if order_by_id else Trade.close_date.desc() order_by: Any = Trade.id if order_by_id else Trade.close_date.desc()
if limit: if limit:
trades = Trade.get_trades([Trade.is_open.is_(False)]).order_by( trades = Trade.session.scalars(
order_by).limit(limit).offset(offset) Trade.get_trades_query([Trade.is_open.is_(False)])
.order_by(order_by)
.limit(limit)
.offset(offset))
else: else:
trades = Trade.get_trades([Trade.is_open.is_(False)]).order_by( trades = Trade.session.scalars(
Trade.close_date.desc()).all() Trade.get_trades_query([Trade.is_open.is_(False)])
.order_by(Trade.close_date.desc()))
output = [trade.to_json() for trade in trades] output = [trade.to_json() for trade in trades]
total_trades = Trade.session.scalar(
select(func.count(Trade.id)).filter(Trade.is_open.is_(False)))
return { return {
"trades": output, "trades": output,
"trades_count": len(output), "trades_count": len(output),
"offset": offset, "offset": offset,
"total_trades": Trade.get_trades([Trade.is_open.is_(False)]).count(), "total_trades": total_trades,
} }
def _rpc_stats(self) -> Dict[str, Any]: def _rpc_stats(self) -> Dict[str, Any]:
@ -395,7 +418,7 @@ class RPC:
return 'losses' return 'losses'
else: else:
return 'draws' return 'draws'
trades: List[Trade] = Trade.get_trades([Trade.is_open.is_(False)], include_orders=False) trades = Trade.get_trades([Trade.is_open.is_(False)], include_orders=False)
# Sell reason # Sell reason
exit_reasons = {} exit_reasons = {}
for trade in trades: for trade in trades:
@ -404,7 +427,7 @@ class RPC:
exit_reasons[trade.exit_reason][trade_win_loss(trade)] += 1 exit_reasons[trade.exit_reason][trade_win_loss(trade)] += 1
# Duration # Duration
dur: Dict[str, List[int]] = {'wins': [], 'draws': [], 'losses': []} dur: Dict[str, List[float]] = {'wins': [], 'draws': [], 'losses': []}
for trade in trades: for trade in trades:
if trade.close_date is not None and trade.open_date is not None: if trade.close_date is not None and trade.open_date is not None:
trade_dur = (trade.close_date - trade.open_date).total_seconds() trade_dur = (trade.close_date - trade.open_date).total_seconds()
@ -423,8 +446,8 @@ class RPC:
""" Returns cumulative profit statistics """ """ Returns cumulative profit statistics """
trade_filter = ((Trade.is_open.is_(False) & (Trade.close_date >= start_date)) | trade_filter = ((Trade.is_open.is_(False) & (Trade.close_date >= start_date)) |
Trade.is_open.is_(True)) Trade.is_open.is_(True))
trades: List[Trade] = Trade.get_trades( trades: Sequence[Trade] = Trade.session.scalars(Trade.get_trades_query(
trade_filter, include_orders=False).order_by(Trade.id).all() trade_filter, include_orders=False).order_by(Trade.id)).all()
profit_all_coin = [] profit_all_coin = []
profit_all_ratio = [] profit_all_ratio = []
@ -443,11 +466,11 @@ class RPC:
durations.append((trade.close_date - trade.open_date).total_seconds()) durations.append((trade.close_date - trade.open_date).total_seconds())
if not trade.is_open: if not trade.is_open:
profit_ratio = trade.close_profit profit_ratio = trade.close_profit or 0.0
profit_abs = trade.close_profit_abs profit_abs = trade.close_profit_abs or 0.0
profit_closed_coin.append(profit_abs) profit_closed_coin.append(profit_abs)
profit_closed_ratio.append(profit_ratio) profit_closed_ratio.append(profit_ratio)
if trade.close_profit >= 0: if profit_ratio >= 0:
winning_trades += 1 winning_trades += 1
winning_profit += profit_abs winning_profit += profit_abs
else: else:
@ -500,7 +523,7 @@ class RPC:
trades_df = DataFrame([{'close_date': trade.close_date.strftime(DATETIME_PRINT_FORMAT), trades_df = DataFrame([{'close_date': trade.close_date.strftime(DATETIME_PRINT_FORMAT),
'profit_abs': trade.close_profit_abs} 'profit_abs': trade.close_profit_abs}
for trade in trades if not trade.is_open]) for trade in trades if not trade.is_open and trade.close_date])
max_drawdown_abs = 0.0 max_drawdown_abs = 0.0
max_drawdown = 0.0 max_drawdown = 0.0
if len(trades_df) > 0: if len(trades_df) > 0:
@ -779,7 +802,8 @@ class RPC:
# check if valid pair # check if valid pair
# check if pair already has an open pair # check if pair already has an open pair
trade: Trade = Trade.get_trades([Trade.is_open.is_(True), Trade.pair == pair]).first() trade: Optional[Trade] = Trade.get_trades(
[Trade.is_open.is_(True), Trade.pair == pair]).first()
is_short = (order_side == SignalDirection.SHORT) is_short = (order_side == SignalDirection.SHORT)
if trade: if trade:
is_short = trade.is_short is_short = trade.is_short
@ -932,12 +956,12 @@ class RPC:
def _rpc_delete_lock(self, lockid: Optional[int] = None, def _rpc_delete_lock(self, lockid: Optional[int] = None,
pair: Optional[str] = None) -> Dict[str, Any]: pair: Optional[str] = None) -> Dict[str, Any]:
""" Delete specific lock(s) """ """ Delete specific lock(s) """
locks = [] locks: Sequence[PairLock] = []
if pair: if pair:
locks = PairLocks.get_pair_locks(pair) locks = PairLocks.get_pair_locks(pair)
if lockid: if lockid:
locks = PairLock.query.filter(PairLock.id == lockid).all() locks = PairLock.session.scalars(select(PairLock).filter(PairLock.id == lockid)).all()
for lock in locks: for lock in locks:
lock.active = False lock.active = False
@ -1198,10 +1222,23 @@ class RPC:
"ram_pct": psutil.virtual_memory().percent "ram_pct": psutil.virtual_memory().percent
} }
def _health(self) -> Dict[str, Union[str, int]]: def health(self) -> Dict[str, Optional[Union[str, int]]]:
last_p = self._freqtrade.last_process last_p = self._freqtrade.last_process
if last_p is None:
return { return {
'last_process': str(last_p), "last_process": None,
'last_process_loc': last_p.astimezone(tzlocal()).strftime(DATETIME_PRINT_FORMAT), "last_process_loc": None,
'last_process_ts': int(last_p.timestamp()), "last_process_ts": None,
} }
return {
"last_process": str(last_p),
"last_process_loc": last_p.astimezone(tzlocal()).strftime(DATETIME_PRINT_FORMAT),
"last_process_ts": int(last_p.timestamp()),
}
def _update_market_direction(self, direction: MarketDirection) -> None:
self._freqtrade.strategy.market_direction = direction
def _get_market_direction(self) -> MarketDirection:
return self._freqtrade.strategy.market_direction

View File

@ -3,11 +3,12 @@ This module contains class to manage RPC communications (Telegram, API, ...)
""" """
import logging import logging
from collections import deque from collections import deque
from typing import Any, Dict, List from typing import List
from freqtrade.constants import Config from freqtrade.constants import Config
from freqtrade.enums import NO_ECHO_MESSAGES, RPCMessageType from freqtrade.enums import NO_ECHO_MESSAGES, RPCMessageType
from freqtrade.rpc import RPC, RPCHandler from freqtrade.rpc import RPC, RPCHandler
from freqtrade.rpc.rpc_types import RPCSendMsg
logger = logging.getLogger(__name__) logger = logging.getLogger(__name__)
@ -58,7 +59,7 @@ class RPCManager:
mod.cleanup() mod.cleanup()
del mod del mod
def send_msg(self, msg: Dict[str, Any]) -> None: def send_msg(self, msg: RPCSendMsg) -> None:
""" """
Send given message to all registered rpc modules. Send given message to all registered rpc modules.
A message consists of one or more key value pairs of strings. A message consists of one or more key value pairs of strings.
@ -69,10 +70,6 @@ class RPCManager:
""" """
if msg.get('type') not in NO_ECHO_MESSAGES: if msg.get('type') not in NO_ECHO_MESSAGES:
logger.info('Sending rpc message: %s', msg) logger.info('Sending rpc message: %s', msg)
if 'pair' in msg:
msg.update({
'base_currency': self._rpc._freqtrade.exchange.get_pair_base_currency(msg['pair'])
})
for mod in self.registered_modules: for mod in self.registered_modules:
logger.debug('Forwarding message to rpc.%s', mod.name) logger.debug('Forwarding message to rpc.%s', mod.name)
try: try:

128
freqtrade/rpc/rpc_types.py Normal file
View File

@ -0,0 +1,128 @@
from datetime import datetime
from typing import Any, List, Literal, Optional, TypedDict, Union
from freqtrade.constants import PairWithTimeframe
from freqtrade.enums import RPCMessageType
class RPCSendMsgBase(TypedDict):
pass
# ty1pe: Literal[RPCMessageType]
class RPCStatusMsg(RPCSendMsgBase):
"""Used for Status, Startup and Warning messages"""
type: Literal[RPCMessageType.STATUS, RPCMessageType.STARTUP, RPCMessageType.WARNING]
status: str
class RPCStrategyMsg(RPCSendMsgBase):
"""Used for Status, Startup and Warning messages"""
type: Literal[RPCMessageType.STRATEGY_MSG]
msg: str
class RPCProtectionMsg(RPCSendMsgBase):
type: Literal[RPCMessageType.PROTECTION_TRIGGER, RPCMessageType.PROTECTION_TRIGGER_GLOBAL]
id: int
pair: str
base_currency: Optional[str]
lock_time: str
lock_timestamp: int
lock_end_time: str
lock_end_timestamp: int
reason: str
side: str
active: bool
class RPCWhitelistMsg(RPCSendMsgBase):
type: Literal[RPCMessageType.WHITELIST]
data: List[str]
class __RPCBuyMsgBase(RPCSendMsgBase):
trade_id: int
buy_tag: Optional[str]
enter_tag: Optional[str]
exchange: str
pair: str
base_currency: str
leverage: Optional[float]
direction: str
limit: float
open_rate: float
order_type: Optional[str] # TODO: why optional??
stake_amount: float
stake_currency: str
fiat_currency: Optional[str]
amount: float
open_date: datetime
current_rate: Optional[float]
sub_trade: bool
class RPCBuyMsg(__RPCBuyMsgBase):
type: Literal[RPCMessageType.ENTRY, RPCMessageType.ENTRY_FILL]
class RPCCancelMsg(__RPCBuyMsgBase):
type: Literal[RPCMessageType.ENTRY_CANCEL]
reason: str
class RPCSellMsg(__RPCBuyMsgBase):
type: Literal[RPCMessageType.EXIT, RPCMessageType.EXIT_FILL]
cumulative_profit: float
gain: str # Literal["profit", "loss"]
close_rate: float
profit_amount: float
profit_ratio: float
sell_reason: Optional[str]
exit_reason: Optional[str]
close_date: datetime
# current_rate: Optional[float]
order_rate: Optional[float]
class RPCSellCancelMsg(__RPCBuyMsgBase):
type: Literal[RPCMessageType.EXIT_CANCEL]
reason: str
gain: str # Literal["profit", "loss"]
profit_amount: float
profit_ratio: float
sell_reason: Optional[str]
exit_reason: Optional[str]
close_date: datetime
class _AnalyzedDFData(TypedDict):
key: PairWithTimeframe
df: Any
la: datetime
class RPCAnalyzedDFMsg(RPCSendMsgBase):
"""New Analyzed dataframe message"""
type: Literal[RPCMessageType.ANALYZED_DF]
data: _AnalyzedDFData
class RPCNewCandleMsg(RPCSendMsgBase):
"""New candle ping message, issued once per new candle/pair"""
type: Literal[RPCMessageType.NEW_CANDLE]
data: PairWithTimeframe
RPCSendMsg = Union[
RPCStatusMsg,
RPCStrategyMsg,
RPCProtectionMsg,
RPCWhitelistMsg,
RPCBuyMsg,
RPCCancelMsg,
RPCSellMsg,
RPCSellCancelMsg,
RPCAnalyzedDFMsg,
RPCNewCandleMsg
]

View File

@ -25,11 +25,12 @@ from telegram.utils.helpers import escape_markdown
from freqtrade.__init__ import __version__ from freqtrade.__init__ import __version__
from freqtrade.constants import DUST_PER_COIN, Config from freqtrade.constants import DUST_PER_COIN, Config
from freqtrade.enums import RPCMessageType, SignalDirection, TradingMode from freqtrade.enums import MarketDirection, RPCMessageType, SignalDirection, TradingMode
from freqtrade.exceptions import OperationalException from freqtrade.exceptions import OperationalException
from freqtrade.misc import chunks, plural, round_coin_value from freqtrade.misc import chunks, plural, round_coin_value
from freqtrade.persistence import Trade from freqtrade.persistence import Trade
from freqtrade.rpc import RPC, RPCException, RPCHandler from freqtrade.rpc import RPC, RPCException, RPCHandler
from freqtrade.rpc.rpc_types import RPCSendMsg
logger = logging.getLogger(__name__) logger = logging.getLogger(__name__)
@ -83,6 +84,8 @@ def authorized_only(command_handler: Callable[..., None]) -> Callable[..., Any]:
self._send_msg(str(e)) self._send_msg(str(e))
except BaseException: except BaseException:
logger.exception('Exception occurred within Telegram module') logger.exception('Exception occurred within Telegram module')
finally:
Trade.session.remove()
return wrapper return wrapper
@ -129,7 +132,8 @@ class Telegram(RPCHandler):
r'/weekly$', r'/weekly \d+$', r'/monthly$', r'/monthly \d+$', r'/weekly$', r'/weekly \d+$', r'/monthly$', r'/monthly \d+$',
r'/forcebuy$', r'/forcelong$', r'/forceshort$', r'/forcebuy$', r'/forcelong$', r'/forceshort$',
r'/forcesell$', r'/forceexit$', r'/forcesell$', r'/forceexit$',
r'/edge$', r'/health$', r'/help$', r'/version$' r'/edge$', r'/health$', r'/help$', r'/version$', r'/marketdir (long|short|even|none)$',
r'/marketdir$'
] ]
# Create keys for generation # Create keys for generation
valid_keys_print = [k.replace('$', '') for k in valid_keys] valid_keys_print = [k.replace('$', '') for k in valid_keys]
@ -197,6 +201,7 @@ class Telegram(RPCHandler):
CommandHandler('health', self._health), CommandHandler('health', self._health),
CommandHandler('help', self._help), CommandHandler('help', self._help),
CommandHandler('version', self._version), CommandHandler('version', self._version),
CommandHandler('marketdir', self._changemarketdir)
] ]
callbacks = [ callbacks = [
CallbackQueryHandler(self._status_table, pattern='update_status_table'), CallbackQueryHandler(self._status_table, pattern='update_status_table'),
@ -319,31 +324,33 @@ class Telegram(RPCHandler):
and self._rpc._fiat_converter): and self._rpc._fiat_converter):
msg['profit_fiat'] = self._rpc._fiat_converter.convert_amount( msg['profit_fiat'] = self._rpc._fiat_converter.convert_amount(
msg['profit_amount'], msg['stake_currency'], msg['fiat_currency']) msg['profit_amount'], msg['stake_currency'], msg['fiat_currency'])
msg['profit_extra'] = ( msg['profit_extra'] = f" / {msg['profit_fiat']:.3f} {msg['fiat_currency']}"
f" / {msg['profit_fiat']:.3f} {msg['fiat_currency']}")
else: else:
msg['profit_extra'] = '' msg['profit_extra'] = ''
msg['profit_extra'] = ( msg['profit_extra'] = (
f" ({msg['gain']}: {msg['profit_amount']:.8f} {msg['stake_currency']}" f" ({msg['gain']}: {msg['profit_amount']:.8f} {msg['stake_currency']}"
f"{msg['profit_extra']})") f"{msg['profit_extra']})")
is_fill = msg['type'] == RPCMessageType.EXIT_FILL is_fill = msg['type'] == RPCMessageType.EXIT_FILL
is_sub_trade = msg.get('sub_trade') is_sub_trade = msg.get('sub_trade')
is_sub_profit = msg['profit_amount'] != msg.get('cumulative_profit') is_sub_profit = msg['profit_amount'] != msg.get('cumulative_profit')
profit_prefix = ('Sub ' if is_sub_profit profit_prefix = ('Sub ' if is_sub_profit else 'Cumulative ') if is_sub_trade else ''
else 'Cumulative ') if is_sub_trade else ''
cp_extra = '' cp_extra = ''
exit_wording = 'Exited' if is_fill else 'Exiting'
if is_sub_profit and is_sub_trade: if is_sub_profit and is_sub_trade:
if self._rpc._fiat_converter: if self._rpc._fiat_converter:
cp_fiat = self._rpc._fiat_converter.convert_amount( cp_fiat = self._rpc._fiat_converter.convert_amount(
msg['cumulative_profit'], msg['stake_currency'], msg['fiat_currency']) msg['cumulative_profit'], msg['stake_currency'], msg['fiat_currency'])
cp_extra = f" / {cp_fiat:.3f} {msg['fiat_currency']}" cp_extra = f" / {cp_fiat:.3f} {msg['fiat_currency']}"
else: exit_wording = f"Partially {exit_wording.lower()}"
cp_extra = '' cp_extra = (
cp_extra = f"*Cumulative Profit:* (`{msg['cumulative_profit']:.8f} " \ f"*Cumulative Profit:* (`{msg['cumulative_profit']:.8f} "
f"{msg['stake_currency']}{cp_extra}`)\n" f"{msg['stake_currency']}{cp_extra}`)\n"
)
message = ( message = (
f"{msg['emoji']} *{self._exchange_from_msg(msg)}:* " f"{msg['emoji']} *{self._exchange_from_msg(msg)}:* "
f"{'Exited' if is_fill else 'Exiting'} {msg['pair']} (#{msg['trade_id']})\n" f"{exit_wording} {msg['pair']} (#{msg['trade_id']})\n"
f"{self._add_analyzed_candle(msg['pair'])}" f"{self._add_analyzed_candle(msg['pair'])}"
f"*{f'{profit_prefix}Profit' if is_fill else f'Unrealized {profit_prefix}Profit'}:* " f"*{f'{profit_prefix}Profit' if is_fill else f'Unrealized {profit_prefix}Profit'}:* "
f"`{msg['profit_ratio']:.2%}{msg['profit_extra']}`\n" f"`{msg['profit_ratio']:.2%}{msg['profit_extra']}`\n"
@ -362,7 +369,7 @@ class Telegram(RPCHandler):
elif msg['type'] == RPCMessageType.EXIT_FILL: elif msg['type'] == RPCMessageType.EXIT_FILL:
message += f"*Exit Rate:* `{msg['close_rate']:.8f}`" message += f"*Exit Rate:* `{msg['close_rate']:.8f}`"
if msg.get('sub_trade'): if is_sub_trade:
if self._rpc._fiat_converter: if self._rpc._fiat_converter:
msg['stake_amount_fiat'] = self._rpc._fiat_converter.convert_amount( msg['stake_amount_fiat'] = self._rpc._fiat_converter.convert_amount(
msg['stake_amount'], msg['stake_currency'], msg['fiat_currency']) msg['stake_amount'], msg['stake_currency'], msg['fiat_currency'])
@ -410,6 +417,9 @@ class Telegram(RPCHandler):
elif msg_type == RPCMessageType.WARNING: elif msg_type == RPCMessageType.WARNING:
message = f"\N{WARNING SIGN} *Warning:* `{msg['status']}`" message = f"\N{WARNING SIGN} *Warning:* `{msg['status']}`"
elif msg_type == RPCMessageType.EXCEPTION:
# Errors will contain exceptions, which are wrapped in tripple ticks.
message = f"\N{WARNING SIGN} *ERROR:* \n {msg['status']}"
elif msg_type == RPCMessageType.STARTUP: elif msg_type == RPCMessageType.STARTUP:
message = f"{msg['status']}" message = f"{msg['status']}"
@ -420,14 +430,14 @@ class Telegram(RPCHandler):
return None return None
return message return message
def send_msg(self, msg: Dict[str, Any]) -> None: def send_msg(self, msg: RPCSendMsg) -> None:
""" Send a message to telegram channel """ """ Send a message to telegram channel """
default_noti = 'on' default_noti = 'on'
msg_type = msg['type'] msg_type = msg['type']
noti = '' noti = ''
if msg_type == RPCMessageType.EXIT: if msg['type'] == RPCMessageType.EXIT:
sell_noti = self._config['telegram'] \ sell_noti = self._config['telegram'] \
.get('notification_settings', {}).get(str(msg_type), {}) .get('notification_settings', {}).get(str(msg_type), {})
# For backward compatibility sell still can be string # For backward compatibility sell still can be string
@ -444,7 +454,7 @@ class Telegram(RPCHandler):
# Notification disabled # Notification disabled
return return
message = self.compose_message(deepcopy(msg), msg_type) message = self.compose_message(deepcopy(msg), msg_type) # type: ignore
if message: if message:
self._send_msg(message, disable_notification=(noti == 'silent')) self._send_msg(message, disable_notification=(noti == 'silent'))
@ -469,44 +479,51 @@ class Telegram(RPCHandler):
lines_detail: List[str] = [] lines_detail: List[str] = []
if len(filled_orders) > 0: if len(filled_orders) > 0:
first_avg = filled_orders[0]["safe_price"] first_avg = filled_orders[0]["safe_price"]
order_nr = 0
for x, order in enumerate(filled_orders): for order in filled_orders:
lines: List[str] = [] lines: List[str] = []
if order['is_open'] is True: if order['is_open'] is True:
continue continue
order_nr += 1
wording = 'Entry' if order['ft_is_entry'] else 'Exit' wording = 'Entry' if order['ft_is_entry'] else 'Exit'
cur_entry_datetime = arrow.get(order["order_filled_date"]) cur_entry_datetime = arrow.get(order["order_filled_date"])
cur_entry_amount = order["filled"] or order["amount"] cur_entry_amount = order["filled"] or order["amount"]
cur_entry_average = order["safe_price"] cur_entry_average = order["safe_price"]
lines.append(" ") lines.append(" ")
if x == 0: if order_nr == 1:
lines.append(f"*{wording} #{x+1}:*") lines.append(f"*{wording} #{order_nr}:*")
lines.append( lines.append(
f"*Amount:* {cur_entry_amount} ({order['cost']:.8f} {quote_currency})") f"*Amount:* {cur_entry_amount} "
f"({round_coin_value(order['cost'], quote_currency)})"
)
lines.append(f"*Average Price:* {cur_entry_average}") lines.append(f"*Average Price:* {cur_entry_average}")
else: else:
sumA = 0 sum_stake = 0
sumB = 0 sum_amount = 0
for y in range(x): for y in range(order_nr):
amount = filled_orders[y]["filled"] or filled_orders[y]["amount"] loc_order = filled_orders[y]
sumA += amount * filled_orders[y]["safe_price"] if loc_order['is_open'] is True:
sumB += amount # Skip open orders (e.g. stop orders)
prev_avg_price = sumA / sumB continue
amount = loc_order["filled"] or loc_order["amount"]
sum_stake += amount * loc_order["safe_price"]
sum_amount += amount
prev_avg_price = sum_stake / sum_amount
# TODO: This calculation ignores fees. # TODO: This calculation ignores fees.
price_to_1st_entry = ((cur_entry_average - first_avg) / first_avg) price_to_1st_entry = ((cur_entry_average - first_avg) / first_avg)
minus_on_entry = 0 minus_on_entry = 0
if prev_avg_price: if prev_avg_price:
minus_on_entry = (cur_entry_average - prev_avg_price) / prev_avg_price minus_on_entry = (cur_entry_average - prev_avg_price) / prev_avg_price
lines.append(f"*{wording} #{x+1}:* at {minus_on_entry:.2%} avg profit") lines.append(f"*{wording} #{order_nr}:* at {minus_on_entry:.2%} avg Profit")
if is_open: if is_open:
lines.append("({})".format(cur_entry_datetime lines.append("({})".format(cur_entry_datetime
.humanize(granularity=["day", "hour", "minute"]))) .humanize(granularity=["day", "hour", "minute"])))
lines.append( lines.append(f"*Amount:* {cur_entry_amount} "
f"*Amount:* {cur_entry_amount} ({order['cost']:.8f} {quote_currency})") f"({round_coin_value(order['cost'], quote_currency)})")
lines.append(f"*Average {wording} Price:* {cur_entry_average} " lines.append(f"*Average {wording} Price:* {cur_entry_average} "
f"({price_to_1st_entry:.2%} from 1st entry rate)") f"({price_to_1st_entry:.2%} from 1st entry Rate)")
lines.append(f"*Order filled:* {order['order_filled_date']}") lines.append(f"*Order filled:* {order['order_filled_date']}")
# TODO: is this really useful? # TODO: is this really useful?
@ -518,6 +535,7 @@ class Telegram(RPCHandler):
# lines.append( # lines.append(
# f"({days}d {hours}h {minutes}m {seconds}s from previous {wording.lower()})") # f"({days}d {hours}h {minutes}m {seconds}s from previous {wording.lower()})")
lines_detail.append("\n".join(lines)) lines_detail.append("\n".join(lines))
return lines_detail return lines_detail
@authorized_only @authorized_only
@ -553,35 +571,54 @@ class Telegram(RPCHandler):
for r in results: for r in results:
r['open_date_hum'] = arrow.get(r['open_date']).humanize() r['open_date_hum'] = arrow.get(r['open_date']).humanize()
r['num_entries'] = len([o for o in r['orders'] if o['ft_is_entry']]) r['num_entries'] = len([o for o in r['orders'] if o['ft_is_entry']])
r['num_exits'] = len([o for o in r['orders'] if not o['ft_is_entry']
and not o['ft_order_side'] == 'stoploss'])
r['exit_reason'] = r.get('exit_reason', "") r['exit_reason'] = r.get('exit_reason', "")
r['stake_amount_r'] = round_coin_value(r['stake_amount'], r['quote_currency'])
r['max_stake_amount_r'] = round_coin_value(
r['max_stake_amount'] or r['stake_amount'], r['quote_currency'])
r['profit_abs_r'] = round_coin_value(r['profit_abs'], r['quote_currency'])
r['realized_profit_r'] = round_coin_value(r['realized_profit'], r['quote_currency'])
r['total_profit_abs_r'] = round_coin_value(
r['total_profit_abs'], r['quote_currency'])
lines = [ lines = [
"*Trade ID:* `{trade_id}`" + "*Trade ID:* `{trade_id}`" +
(" `(since {open_date_hum})`" if r['is_open'] else ""), (" `(since {open_date_hum})`" if r['is_open'] else ""),
"*Current Pair:* {pair}", "*Current Pair:* {pair}",
"*Direction:* " + ("`Short`" if r.get('is_short') else "`Long`"), f"*Direction:* {'`Short`' if r.get('is_short') else '`Long`'}"
"*Leverage:* `{leverage}`" if r.get('leverage') else "", + " ` ({leverage}x)`" if r.get('leverage') else "",
"*Amount:* `{amount} ({stake_amount} {quote_currency})`", "*Amount:* `{amount} ({stake_amount_r})`",
"*Total invested:* `{max_stake_amount_r}`" if position_adjust else "",
"*Enter Tag:* `{enter_tag}`" if r['enter_tag'] else "", "*Enter Tag:* `{enter_tag}`" if r['enter_tag'] else "",
"*Exit Reason:* `{exit_reason}`" if r['exit_reason'] else "", "*Exit Reason:* `{exit_reason}`" if r['exit_reason'] else "",
] ]
if position_adjust: if position_adjust:
max_buy_str = (f"/{max_entries + 1}" if (max_entries > 0) else "") max_buy_str = (f"/{max_entries + 1}" if (max_entries > 0) else "")
lines.append("*Number of Entries:* `{num_entries}`" + max_buy_str) lines.extend([
"*Number of Entries:* `{num_entries}" + max_buy_str + "`",
"*Number of Exits:* `{num_exits}`"
])
lines.extend([ lines.extend([
"*Open Rate:* `{open_rate:.8f}`", "*Open Rate:* `{open_rate:.8f}`",
"*Close Rate:* `{close_rate:.8f}`" if r['close_rate'] else "", "*Close Rate:* `{close_rate:.8f}`" if r['close_rate'] else "",
"*Open Date:* `{open_date}`", "*Open Date:* `{open_date}`",
"*Close Date:* `{close_date}`" if r['close_date'] else "", "*Close Date:* `{close_date}`" if r['close_date'] else "",
"*Current Rate:* `{current_rate:.8f}`" if r['is_open'] else "", " \n*Current Rate:* `{current_rate:.8f}`" if r['is_open'] else "",
("*Current Profit:* " if r['is_open'] else "*Close Profit: *") ("*Unrealized Profit:* " if r['is_open'] else "*Close Profit: *")
+ "`{profit_ratio:.2%}`", + "`{profit_ratio:.2%}` `({profit_abs_r})`",
]) ])
if r['is_open']: if r['is_open']:
if r.get('realized_profit'): if r.get('realized_profit'):
lines.append("*Realized Profit:* `{realized_profit:.8f}`") lines.extend([
"*Realized Profit:* `{realized_profit_ratio:.2%} ({realized_profit_r})`",
"*Total Profit:* `{total_profit_ratio:.2%} ({total_profit_abs_r})`"
])
# Append empty line to improve readability
lines.append(" ")
if (r['stop_loss_abs'] != r['initial_stop_loss_abs'] if (r['stop_loss_abs'] != r['initial_stop_loss_abs']
and r['initial_stop_loss_ratio'] is not None): and r['initial_stop_loss_ratio'] is not None):
# Adding initial stoploss only if it is different from stoploss # Adding initial stoploss only if it is different from stoploss
@ -1040,10 +1077,14 @@ class Telegram(RPCHandler):
query.answer() query.answer()
query.edit_message_text(text="Force exit canceled.") query.edit_message_text(text="Force exit canceled.")
return return
trade: Trade = Trade.get_trades(trade_filter=Trade.id == trade_id).first() trade: Optional[Trade] = Trade.get_trades(trade_filter=Trade.id == trade_id).first()
query.answer() query.answer()
query.edit_message_text(text=f"Manually exiting Trade #{trade_id}, {trade.pair}") if trade:
query.edit_message_text(
text=f"Manually exiting Trade #{trade_id}, {trade.pair}")
self._force_exit_action(trade_id) self._force_exit_action(trade_id)
else:
query.edit_message_text(text=f"Trade {trade_id} not found.")
def _force_enter_action(self, pair, price: Optional[float], order_side: SignalDirection): def _force_enter_action(self, pair, price: Optional[float], order_side: SignalDirection):
if pair != 'cancel': if pair != 'cancel':
@ -1302,7 +1343,7 @@ class Telegram(RPCHandler):
message = tabulate({k: [v] for k, v in counts.items()}, message = tabulate({k: [v] for k, v in counts.items()},
headers=['current', 'max', 'total stake'], headers=['current', 'max', 'total stake'],
tablefmt='simple') tablefmt='simple')
message = "<pre>{}</pre>".format(message) message = f"<pre>{message}</pre>"
logger.debug(message) logger.debug(message)
self._send_msg(message, parse_mode=ParseMode.HTML, self._send_msg(message, parse_mode=ParseMode.HTML,
reload_able=True, callback_path="update_count", reload_able=True, callback_path="update_count",
@ -1494,6 +1535,9 @@ class Telegram(RPCHandler):
"*/count:* `Show number of active trades compared to allowed number of trades`\n" "*/count:* `Show number of active trades compared to allowed number of trades`\n"
"*/edge:* `Shows validated pairs by Edge if it is enabled` \n" "*/edge:* `Shows validated pairs by Edge if it is enabled` \n"
"*/health* `Show latest process timestamp - defaults to 1970-01-01 00:00:00` \n" "*/health* `Show latest process timestamp - defaults to 1970-01-01 00:00:00` \n"
"*/marketdir [long | short | even | none]:* `Updates the user managed variable "
"that represents the current market direction. If no direction is provided `"
"`the currently set market direction will be output.` \n"
"_Statistics_\n" "_Statistics_\n"
"------------\n" "------------\n"
@ -1527,7 +1571,7 @@ class Telegram(RPCHandler):
Handler for /health Handler for /health
Shows the last process timestamp Shows the last process timestamp
""" """
health = self._rpc._health() health = self._rpc.health()
message = f"Last process: `{health['last_process_loc']}`" message = f"Last process: `{health['last_process_loc']}`"
self._send_msg(message) self._send_msg(message)
@ -1601,7 +1645,7 @@ class Telegram(RPCHandler):
]) ])
else: else:
reply_markup = InlineKeyboardMarkup([[]]) reply_markup = InlineKeyboardMarkup([[]])
msg += "\nUpdated: {}".format(datetime.now().ctime()) msg += f"\nUpdated: {datetime.now().ctime()}"
if not query.message: if not query.message:
return return
chat_id = query.message.chat_id chat_id = query.message.chat_id
@ -1677,3 +1721,39 @@ class Telegram(RPCHandler):
'TelegramError: %s! Giving up on that message.', 'TelegramError: %s! Giving up on that message.',
telegram_err.message telegram_err.message
) )
@authorized_only
def _changemarketdir(self, update: Update, context: CallbackContext) -> None:
"""
Handler for /marketdir.
Updates the bot's market_direction
:param bot: telegram bot
:param update: message update
:return: None
"""
if context.args and len(context.args) == 1:
new_market_dir_arg = context.args[0]
old_market_dir = self._rpc._get_market_direction()
new_market_dir = None
if new_market_dir_arg == "long":
new_market_dir = MarketDirection.LONG
elif new_market_dir_arg == "short":
new_market_dir = MarketDirection.SHORT
elif new_market_dir_arg == "even":
new_market_dir = MarketDirection.EVEN
elif new_market_dir_arg == "none":
new_market_dir = MarketDirection.NONE
if new_market_dir is not None:
self._rpc._update_market_direction(new_market_dir)
self._send_msg("Successfully updated market direction"
f" from *{old_market_dir}* to *{new_market_dir}*.")
else:
raise RPCException("Invalid market direction provided. \n"
"Valid market directions: *long, short, even, none*")
elif context.args is not None and len(context.args) == 0:
old_market_dir = self._rpc._get_market_direction()
self._send_msg(f"Currently set market direction: *{old_market_dir}*")
else:
raise RPCException("Invalid usage of command /marketdir. \n"
"Usage: */marketdir [short | long | even | none]*")

View File

@ -10,6 +10,7 @@ from requests import RequestException, post
from freqtrade.constants import Config from freqtrade.constants import Config
from freqtrade.enums import RPCMessageType from freqtrade.enums import RPCMessageType
from freqtrade.rpc import RPC, RPCHandler from freqtrade.rpc import RPC, RPCHandler
from freqtrade.rpc.rpc_types import RPCSendMsg
logger = logging.getLogger(__name__) logger = logging.getLogger(__name__)
@ -41,7 +42,7 @@ class Webhook(RPCHandler):
""" """
pass pass
def _get_value_dict(self, msg: Dict[str, Any]) -> Optional[Dict[str, Any]]: def _get_value_dict(self, msg: RPCSendMsg) -> Optional[Dict[str, Any]]:
whconfig = self._config['webhook'] whconfig = self._config['webhook']
# Deprecated 2022.10 - only keep generic method. # Deprecated 2022.10 - only keep generic method.
if msg['type'] in [RPCMessageType.ENTRY]: if msg['type'] in [RPCMessageType.ENTRY]:
@ -58,6 +59,7 @@ class Webhook(RPCHandler):
valuedict = whconfig.get('webhookexitcancel') valuedict = whconfig.get('webhookexitcancel')
elif msg['type'] in (RPCMessageType.STATUS, elif msg['type'] in (RPCMessageType.STATUS,
RPCMessageType.STARTUP, RPCMessageType.STARTUP,
RPCMessageType.EXCEPTION,
RPCMessageType.WARNING): RPCMessageType.WARNING):
valuedict = whconfig.get('webhookstatus') valuedict = whconfig.get('webhookstatus')
elif msg['type'].value in whconfig: elif msg['type'].value in whconfig:
@ -74,7 +76,7 @@ class Webhook(RPCHandler):
return None return None
return valuedict return valuedict
def send_msg(self, msg: Dict[str, Any]) -> None: def send_msg(self, msg: RPCSendMsg) -> None:
""" Send a message to telegram channel """ """ Send a message to telegram channel """
try: try:
@ -112,7 +114,7 @@ class Webhook(RPCHandler):
response = post(self._url, data=payload['data'], response = post(self._url, data=payload['data'],
headers={'Content-Type': 'text/plain'}) headers={'Content-Type': 'text/plain'})
else: else:
raise NotImplementedError('Unknown format: {}'.format(self._format)) raise NotImplementedError(f'Unknown format: {self._format}')
# Throw a RequestException if the post was not successful # Throw a RequestException if the post was not successful
response.raise_for_status() response.raise_for_status()

View File

@ -12,8 +12,8 @@ from pandas import DataFrame
from freqtrade.constants import Config, IntOrInf, ListPairsWithTimeframes from freqtrade.constants import Config, IntOrInf, ListPairsWithTimeframes
from freqtrade.data.dataprovider import DataProvider from freqtrade.data.dataprovider import DataProvider
from freqtrade.enums import (CandleType, ExitCheckTuple, ExitType, RunMode, SignalDirection, from freqtrade.enums import (CandleType, ExitCheckTuple, ExitType, MarketDirection, RunMode,
SignalTagType, SignalType, TradingMode) SignalDirection, SignalTagType, SignalType, TradingMode)
from freqtrade.exceptions import OperationalException, StrategyError from freqtrade.exceptions import OperationalException, StrategyError
from freqtrade.exchange import timeframe_to_minutes, timeframe_to_next_date, timeframe_to_seconds from freqtrade.exchange import timeframe_to_minutes, timeframe_to_next_date, timeframe_to_seconds
from freqtrade.misc import remove_entry_exit_signals from freqtrade.misc import remove_entry_exit_signals
@ -122,6 +122,9 @@ class IStrategy(ABC, HyperStrategyMixin):
# Definition of plot_config. See plotting documentation for more details. # Definition of plot_config. See plotting documentation for more details.
plot_config: Dict = {} plot_config: Dict = {}
# A self set parameter that represents the market direction. filled from configuration
market_direction: MarketDirection = MarketDirection.NONE
def __init__(self, config: Config) -> None: def __init__(self, config: Config) -> None:
self.config = config self.config = config
# Dict to determine if analysis is necessary # Dict to determine if analysis is necessary
@ -248,11 +251,12 @@ class IStrategy(ABC, HyperStrategyMixin):
""" """
pass pass
def bot_loop_start(self, **kwargs) -> None: def bot_loop_start(self, current_time: datetime, **kwargs) -> None:
""" """
Called at the start of the bot iteration (one loop). Called at the start of the bot iteration (one loop).
Might be used to perform pair-independent tasks Might be used to perform pair-independent tasks
(e.g. gather some remote resource for comparison) (e.g. gather some remote resource for comparison)
: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. :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
""" """
pass pass

View File

@ -86,37 +86,41 @@ def merge_informative_pair(dataframe: pd.DataFrame, informative: pd.DataFrame,
def stoploss_from_open( def stoploss_from_open(
open_relative_stop: float, open_relative_stop: float,
current_profit: float, current_profit: float,
is_short: bool = False is_short: bool = False,
leverage: float = 1.0
) -> float: ) -> float:
""" """
Given the current profit, and a desired stop loss value relative to the trade entry price,
Given the current profit, and a desired stop loss value relative to the open price,
return a stop loss value that is relative to the current price, and which can be return a stop loss value that is relative to the current price, and which can be
returned from `custom_stoploss`. returned from `custom_stoploss`.
The requested stop can be positive for a stop above the open price, or negative for The requested stop can be positive for a stop above the open price, or negative for
a stop below the open price. The return value is always >= 0. a stop below the open price. The return value is always >= 0.
`open_relative_stop` will be considered as adjusted for leverage if leverage is provided..
Returns 0 if the resulting stop price would be above/below (longs/shorts) the current price Returns 0 if the resulting stop price would be above/below (longs/shorts) the current price
:param open_relative_stop: Desired stop loss percentage relative to open price :param open_relative_stop: Desired stop loss percentage, relative to the open price,
adjusted for leverage
:param current_profit: The current profit percentage :param current_profit: The current profit percentage
:param is_short: When true, perform the calculation for short instead of long :param is_short: When true, perform the calculation for short instead of long
:param leverage: Leverage to use for the calculation
:return: Stop loss value relative to current price :return: Stop loss value relative to current price
""" """
# formula is undefined for current_profit -1 (longs) or 1 (shorts), return maximum value # formula is undefined for current_profit -1 (longs) or 1 (shorts), return maximum value
if (current_profit == -1 and not is_short) or (is_short and current_profit == 1): _current_profit = current_profit / leverage
if (_current_profit == -1 and not is_short) or (is_short and _current_profit == 1):
return 1 return 1
if is_short is True: if is_short is True:
stoploss = -1 + ((1 - open_relative_stop) / (1 - current_profit)) stoploss = -1 + ((1 - open_relative_stop / leverage) / (1 - _current_profit))
else: else:
stoploss = 1 - ((1 + open_relative_stop) / (1 + current_profit)) stoploss = 1 - ((1 + open_relative_stop / leverage) / (1 + _current_profit))
# negative stoploss values indicate the requested stop price is higher/lower # negative stoploss values indicate the requested stop price is higher/lower
# (long/short) than the current price # (long/short) than the current price
return max(stoploss, 0.0) return max(stoploss * leverage, 0.0)
def stoploss_from_absolute(stop_rate: float, current_rate: float, is_short: bool = False) -> float: def stoploss_from_absolute(stop_rate: float, current_rate: float, is_short: bool = False) -> float:

View File

@ -0,0 +1,255 @@
import shutil
from pathlib import Path
import ast_comments
from freqtrade.constants import Config
class StrategyUpdater:
name_mapping = {
'ticker_interval': 'timeframe',
'buy': 'enter_long',
'sell': 'exit_long',
'buy_tag': 'enter_tag',
'sell_reason': 'exit_reason',
'sell_signal': 'exit_signal',
'custom_sell': 'custom_exit',
'force_sell': 'force_exit',
'emergency_sell': 'emergency_exit',
# Strategy/config settings:
'use_sell_signal': 'use_exit_signal',
'sell_profit_only': 'exit_profit_only',
'sell_profit_offset': 'exit_profit_offset',
'ignore_roi_if_buy_signal': 'ignore_roi_if_entry_signal',
'forcebuy_enable': 'force_entry_enable',
}
function_mapping = {
'populate_buy_trend': 'populate_entry_trend',
'populate_sell_trend': 'populate_exit_trend',
'custom_sell': 'custom_exit',
'check_buy_timeout': 'check_entry_timeout',
'check_sell_timeout': 'check_exit_timeout',
# '': '',
}
# order_time_in_force, order_types, unfilledtimeout
otif_ot_unfilledtimeout = {
'buy': 'entry',
'sell': 'exit',
}
# create a dictionary that maps the old column names to the new ones
rename_dict = {'buy': 'enter_long', 'sell': 'exit_long', 'buy_tag': 'enter_tag'}
def start(self, config: Config, strategy_obj: dict) -> None:
"""
Run strategy updater
It updates a strategy to v3 with the help of the ast-module
:return: None
"""
source_file = strategy_obj['location']
strategies_backup_folder = Path.joinpath(config['user_data_dir'], "strategies_orig_updater")
target_file = Path.joinpath(strategies_backup_folder, strategy_obj['location_rel'])
# read the file
with Path(source_file).open('r') as f:
old_code = f.read()
if not strategies_backup_folder.is_dir():
Path(strategies_backup_folder).mkdir(parents=True, exist_ok=True)
# backup original
# => currently no date after the filename,
# could get overridden pretty fast if this is fired twice!
# The folder is always the same and the file name too (currently).
shutil.copy(source_file, target_file)
# update the code
new_code = self.update_code(old_code)
# write the modified code to the destination folder
with Path(source_file).open('w') as f:
f.write(new_code)
# define the function to update the code
def update_code(self, code):
# parse the code into an AST
tree = ast_comments.parse(code)
# use the AST to update the code
updated_code = self.modify_ast(tree)
# return the modified code without executing it
return updated_code
# function that uses the ast module to update the code
def modify_ast(self, tree): # noqa
# use the visitor to update the names and functions in the AST
NameUpdater().visit(tree)
# first fix the comments, so it understands "\n" properly inside multi line comments.
ast_comments.fix_missing_locations(tree)
ast_comments.increment_lineno(tree, n=1)
# generate the new code from the updated AST
# without indent {} parameters would just be written straight one after the other.
# ast_comments would be amazing since this is the only solution that carries over comments,
# but it does currently not have an unparse function, hopefully in the future ... !
# return ast_comments.unparse(tree)
return ast_comments.unparse(tree)
# Here we go through each respective node, slice, elt, key ... to replace outdated entries.
class NameUpdater(ast_comments.NodeTransformer):
def generic_visit(self, node):
# space is not yet transferred from buy/sell to entry/exit and thereby has to be skipped.
if isinstance(node, ast_comments.keyword):
if node.arg == "space":
return node
# from here on this is the original function.
for field, old_value in ast_comments.iter_fields(node):
if isinstance(old_value, list):
new_values = []
for value in old_value:
if isinstance(value, ast_comments.AST):
value = self.visit(value)
if value is None:
continue
elif not isinstance(value, ast_comments.AST):
new_values.extend(value)
continue
new_values.append(value)
old_value[:] = new_values
elif isinstance(old_value, ast_comments.AST):
new_node = self.visit(old_value)
if new_node is None:
delattr(node, field)
else:
setattr(node, field, new_node)
return node
def visit_Expr(self, node):
if hasattr(node.value, "left") and hasattr(node.value.left, "id"):
node.value.left.id = self.check_dict(StrategyUpdater.name_mapping, node.value.left.id)
self.visit(node.value)
return node
# Renames an element if contained inside a dictionary.
@staticmethod
def check_dict(current_dict: dict, element: str):
if element in current_dict:
element = current_dict[element]
return element
def visit_arguments(self, node):
if isinstance(node.args, list):
for arg in node.args:
arg.arg = self.check_dict(StrategyUpdater.name_mapping, arg.arg)
return node
def visit_Name(self, node):
# if the name is in the mapping, update it
node.id = self.check_dict(StrategyUpdater.name_mapping, node.id)
return node
def visit_Import(self, node):
# do not update the names in import statements
return node
def visit_ImportFrom(self, node):
# if hasattr(node, "module"):
# if node.module == "freqtrade.strategy.hyper":
# node.module = "freqtrade.strategy"
return node
def visit_If(self, node: ast_comments.If):
for child in ast_comments.iter_child_nodes(node):
self.visit(child)
return node
def visit_FunctionDef(self, node):
node.name = self.check_dict(StrategyUpdater.function_mapping, node.name)
self.generic_visit(node)
return node
def visit_Attribute(self, node):
if (
isinstance(node.value, ast_comments.Name)
and node.value.id == 'trade'
and node.attr == 'nr_of_successful_buys'
):
node.attr = 'nr_of_successful_entries'
return node
def visit_ClassDef(self, node):
# check if the class is derived from IStrategy
if any(isinstance(base, ast_comments.Name) and
base.id == 'IStrategy' for base in node.bases):
# check if the INTERFACE_VERSION variable exists
has_interface_version = any(
isinstance(child, ast_comments.Assign) and
isinstance(child.targets[0], ast_comments.Name) and
child.targets[0].id == 'INTERFACE_VERSION'
for child in node.body
)
# if the INTERFACE_VERSION variable does not exist, add it as the first child
if not has_interface_version:
node.body.insert(0, ast_comments.parse('INTERFACE_VERSION = 3').body[0])
# otherwise, update its value to 3
else:
for child in node.body:
if (
isinstance(child, ast_comments.Assign)
and isinstance(child.targets[0], ast_comments.Name)
and child.targets[0].id == 'INTERFACE_VERSION'
):
child.value = ast_comments.parse('3').body[0].value
self.generic_visit(node)
return node
def visit_Subscript(self, node):
if isinstance(node.slice, ast_comments.Constant):
if node.slice.value in StrategyUpdater.rename_dict:
# Replace the slice attributes with the values from rename_dict
node.slice.value = StrategyUpdater.rename_dict[node.slice.value]
if hasattr(node.slice, "elts"):
self.visit_elts(node.slice.elts)
if hasattr(node.slice, "value"):
if hasattr(node.slice.value, "elts"):
self.visit_elts(node.slice.value.elts)
return node
# elts can have elts (technically recursively)
def visit_elts(self, elts):
if isinstance(elts, list):
for elt in elts:
self.visit_elt(elt)
else:
self.visit_elt(elts)
return elts
# sub function again needed since the structure itself is highly flexible ...
def visit_elt(self, elt):
if isinstance(elt, ast_comments.Constant) and elt.value in StrategyUpdater.rename_dict:
elt.value = StrategyUpdater.rename_dict[elt.value]
if hasattr(elt, "elts"):
self.visit_elts(elt.elts)
if hasattr(elt, "args"):
if isinstance(elt.args, ast_comments.arguments):
self.visit_elts(elt.args)
else:
for arg in elt.args:
self.visit_elts(arg)
return elt
def visit_Constant(self, node):
node.value = self.check_dict(StrategyUpdater.otif_ot_unfilledtimeout, node.value)
node.value = self.check_dict(StrategyUpdater.name_mapping, node.value)
return node

View File

@ -1,5 +1,5 @@
def bot_loop_start(self, **kwargs) -> None: def bot_loop_start(self, current_time: datetime, **kwargs) -> None:
""" """
Called at the start of the bot iteration (one loop). Called at the start of the bot iteration (one loop).
Might be used to perform pair-independent tasks Might be used to perform pair-independent tasks
@ -8,6 +8,7 @@ def bot_loop_start(self, **kwargs) -> None:
For full documentation please go to https://www.freqtrade.io/en/latest/strategy-advanced/ For full documentation please go to https://www.freqtrade.io/en/latest/strategy-advanced/
When not implemented by a strategy, this simply does nothing. When not implemented by a strategy, this simply does nothing.
: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. :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
""" """
pass pass

View File

@ -1,6 +1,7 @@
import logging import logging
from packaging import version from packaging import version
from sqlalchemy import select
from freqtrade.constants import Config from freqtrade.constants import Config
from freqtrade.enums.tradingmode import TradingMode from freqtrade.enums.tradingmode import TradingMode
@ -44,7 +45,7 @@ def _migrate_binance_futures_db(config: Config):
# Should symbol be migrated too? # Should symbol be migrated too?
# order.symbol = new_pair # order.symbol = new_pair
Trade.commit() Trade.commit()
pls = PairLock.query.filter(PairLock.pair.notlike('%:%')) pls = PairLock.session.scalars(select(PairLock).filter(PairLock.pair.notlike('%:%'))).all()
for pl in pls: for pl in pls:
pl.pair = f"{pl.pair}:{config['stake_currency']}" pl.pair = f"{pl.pair}:{config['stake_currency']}"
# print(pls) # print(pls)

View File

@ -1,5 +1,3 @@
# -*- coding: utf-8 -*-
#
# QTPyLib: Quantitative Trading Python Library # QTPyLib: Quantitative Trading Python Library
# https://github.com/ranaroussi/qtpylib # https://github.com/ranaroussi/qtpylib
# #
@ -18,7 +16,6 @@
# limitations under the License. # limitations under the License.
# #
import sys
import warnings import warnings
from datetime import datetime, timedelta from datetime import datetime, timedelta
@ -27,11 +24,6 @@ import pandas as pd
from pandas.core.base import PandasObject from pandas.core.base import PandasObject
# =============================================
# check min, python version
if sys.version_info < (3, 4):
raise SystemError("QTPyLib requires Python version >= 3.4")
# ============================================= # =============================================
warnings.simplefilter(action="ignore", category=RuntimeWarning) warnings.simplefilter(action="ignore", category=RuntimeWarning)

View File

@ -12,7 +12,7 @@ import sdnotify
from freqtrade import __version__ from freqtrade import __version__
from freqtrade.configuration import Configuration from freqtrade.configuration import Configuration
from freqtrade.constants import PROCESS_THROTTLE_SECS, RETRY_TIMEOUT, Config from freqtrade.constants import PROCESS_THROTTLE_SECS, RETRY_TIMEOUT, Config
from freqtrade.enums import State from freqtrade.enums import RPCMessageType, State
from freqtrade.exceptions import OperationalException, TemporaryError from freqtrade.exceptions import OperationalException, TemporaryError
from freqtrade.exchange import timeframe_to_next_date from freqtrade.exchange import timeframe_to_next_date
from freqtrade.freqtradebot import FreqtradeBot from freqtrade.freqtradebot import FreqtradeBot
@ -185,7 +185,10 @@ class Worker:
tb = traceback.format_exc() tb = traceback.format_exc()
hint = 'Issue `/start` if you think it is safe to restart.' hint = 'Issue `/start` if you think it is safe to restart.'
self.freqtrade.notify_status(f'OperationalException:\n```\n{tb}```{hint}') self.freqtrade.notify_status(
f'*OperationalException:*\n```\n{tb}```\n {hint}',
msg_type=RPCMessageType.EXCEPTION
)
logger.exception('OperationalException. Stopping trader ...') logger.exception('OperationalException. Stopping trader ...')
self.freqtrade.state = State.STOPPED self.freqtrade.state = State.STOPPED

View File

@ -1,3 +1,7 @@
[build-system]
requires = ["setuptools >= 46.4.0", "wheel"]
build-backend = "setuptools.build_meta"
[tool.black] [tool.black]
line-length = 100 line-length = 100
exclude = ''' exclude = '''
@ -35,6 +39,9 @@ warn_unused_ignores = true
exclude = [ exclude = [
'^build_helpers\.py$' '^build_helpers\.py$'
] ]
plugins = [
"sqlalchemy.ext.mypy.plugin"
]
[[tool.mypy.overrides]] [[tool.mypy.overrides]]
module = "tests.*" module = "tests.*"
@ -45,10 +52,6 @@ ignore_errors = true
module = "telegram.*" module = "telegram.*"
implicit_optional = true implicit_optional = true
[build-system]
requires = ["setuptools >= 46.4.0", "wheel"]
build-backend = "setuptools.build_meta"
[tool.pyright] [tool.pyright]
include = ["freqtrade"] include = ["freqtrade"]
exclude = [ exclude = [
@ -56,3 +59,28 @@ exclude = [
"build_helpers/*.py", "build_helpers/*.py",
] ]
ignore = ["freqtrade/vendor/**"] ignore = ["freqtrade/vendor/**"]
[tool.ruff]
line-length = 100
extend-exclude = [".env"]
target-version = "py38"
extend-select = [
"C90", # mccabe
# "N", # pep8-naming
"UP", # pyupgrade
"TID", # flake8-tidy-imports
# "EXE", # flake8-executable
"YTT", # flake8-2020
# "S", # flake8-bandit
# "DTZ", # flake8-datetimez
# "RSE", # flake8-raise
# "TCH", # flake8-type-checking
"PTH", # flake8-use-pathlib
]
[tool.ruff.mccabe]
max-complexity = 12
[tool.ruff.per-file-ignores]
"tests/*" = ["S"]

View File

@ -7,12 +7,11 @@
-r docs/requirements-docs.txt -r docs/requirements-docs.txt
coveralls==3.3.1 coveralls==3.3.1
flake8==6.0.0 ruff==0.0.259
flake8-tidy-imports==4.8.0 mypy==1.1.1
mypy==1.0.1 pre-commit==3.2.1
pre-commit==3.0.4 pytest==7.2.2
pytest==7.2.1 pytest-asyncio==0.21.0
pytest-asyncio==0.20.3
pytest-cov==4.0.0 pytest-cov==4.0.0
pytest-mock==3.10.0 pytest-mock==3.10.0
pytest-random-order==1.1.0 pytest-random-order==1.1.0
@ -23,11 +22,11 @@ time-machine==2.9.0
httpx==0.23.3 httpx==0.23.3
# Convert jupyter notebooks to markdown documents # Convert jupyter notebooks to markdown documents
nbconvert==7.2.9 nbconvert==7.2.10
# mypy types # mypy types
types-cachetools==5.3.0.0 types-cachetools==5.3.0.4
types-filelock==3.2.7 types-filelock==3.2.7
types-requests==2.28.11.13 types-requests==2.28.11.16
types-tabulate==0.9.0.0 types-tabulate==0.9.0.1
types-python-dateutil==2.8.19.6 types-python-dateutil==2.8.19.10

View File

@ -2,9 +2,9 @@
-r requirements-freqai.txt -r requirements-freqai.txt
# Required for freqai-rl # Required for freqai-rl
torch==1.13.1 torch==1.13.1; python_version < '3.11'
stable-baselines3==1.7.0 stable-baselines3==1.7.0; python_version < '3.11'
sb3-contrib==1.7.0 sb3-contrib==1.7.0; python_version < '3.11'
# Gym is forced to this version by stable-baselines3. # Gym is forced to this version by stable-baselines3.
setuptools==65.5.1 # Should be removed when gym is fixed. setuptools==65.5.1 # Should be removed when gym is fixed.
gym==0.21 gym==0.21; python_version < '3.11'

View File

@ -5,7 +5,7 @@
# Required for freqai # Required for freqai
scikit-learn==1.1.3 scikit-learn==1.1.3
joblib==1.2.0 joblib==1.2.0
catboost==1.1.1; platform_machine != 'aarch64' catboost==1.1.1; platform_machine != 'aarch64' and 'arm' not in platform_machine and python_version < '3.11'
lightgbm==3.3.5 lightgbm==3.3.5
xgboost==1.7.3 xgboost==1.7.4
tensorboard==2.12.0 tensorboard==2.12.0

View File

@ -5,5 +5,5 @@
scipy==1.10.1 scipy==1.10.1
scikit-learn==1.1.3 scikit-learn==1.1.3
scikit-optimize==0.9.0 scikit-optimize==0.9.0
filelock==3.9.0 filelock==3.10.6
progressbar2==4.2.0 progressbar2==4.2.0

View File

@ -1,4 +1,4 @@
# Include all requirements to run the bot. # Include all requirements to run the bot.
-r requirements.txt -r requirements.txt
plotly==5.13.0 plotly==5.13.1

View File

@ -2,15 +2,15 @@ numpy==1.24.2
pandas==1.5.3 pandas==1.5.3
pandas-ta==0.3.14b pandas-ta==0.3.14b
ccxt==2.8.17 ccxt==3.0.37
cryptography==39.0.1 cryptography==40.0.1
aiohttp==3.8.4 aiohttp==3.8.4
SQLAlchemy==1.4.46 SQLAlchemy==2.0.7
python-telegram-bot==13.15 python-telegram-bot==13.15
arrow==1.2.3 arrow==1.2.3
cachetools==4.2.2 cachetools==4.2.2
requests==2.28.2 requests==2.28.2
urllib3==1.26.14 urllib3==1.26.15
jsonschema==4.17.3 jsonschema==4.17.3
TA-Lib==0.4.25 TA-Lib==0.4.25
technical==1.4.0 technical==1.4.0
@ -26,17 +26,17 @@ pyarrow==11.0.0; platform_machine != 'armv7l'
py_find_1st==1.1.5 py_find_1st==1.1.5
# Load ticker files 30% faster # Load ticker files 30% faster
python-rapidjson==1.9 python-rapidjson==1.10
# Properly format api responses # Properly format api responses
orjson==3.8.6 orjson==3.8.8
# Notify systemd # Notify systemd
sdnotify==0.3.2 sdnotify==0.3.2
# API Server # API Server
fastapi==0.92.0 fastapi==0.95.0
pydantic==1.10.4 pydantic==1.10.7
uvicorn==0.20.0 uvicorn==0.21.1
pyjwt==2.6.0 pyjwt==2.6.0
aiofiles==23.1.0 aiofiles==23.1.0
psutil==5.9.4 psutil==5.9.4
@ -45,7 +45,7 @@ psutil==5.9.4
colorama==0.4.6 colorama==0.4.6
# Building config files interactively # Building config files interactively
questionary==1.10.0 questionary==1.10.0
prompt-toolkit==3.0.36 prompt-toolkit==3.0.38
# Extensions to datetime library # Extensions to datetime library
python-dateutil==2.8.2 python-dateutil==2.8.2
@ -55,3 +55,5 @@ schedule==1.1.0
#WS Messages #WS Messages
websockets==10.4 websockets==10.4
janus==1.0.0 janus==1.0.0
ast-comments==1.0.1

View File

@ -340,11 +340,13 @@ class FtRestClient():
:param limit: Limit result to the last n candles. :param limit: Limit result to the last n candles.
:return: json object :return: json object
""" """
return self._get("pair_candles", params={ params = {
"pair": pair, "pair": pair,
"timeframe": timeframe, "timeframe": timeframe,
"limit": limit, }
}) if limit:
params['limit'] = limit
return self._get("pair_candles", params=params)
def pair_history(self, pair, timeframe, strategy, timerange=None): def pair_history(self, pair, timeframe, strategy, timerange=None):
"""Return historic, analyzed dataframe """Return historic, analyzed dataframe

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