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Merge pull request #5185 from freqtrade/new_release

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New release 2021.6
This commit is contained in:
Matthias 2021-06-26 14:41:13 +02:00 committed by GitHub
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1
.dockerignore
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@ -3,6 +3,7 @@
Dockerfile
Dockerfile.armhf
.dockerignore
docker/
.coveragerc
.eggs
.github

6
.gitattributes vendored
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@ -1,3 +1,3 @@
*.py eol=lf
*.sh eol=lf
*.ps1 eol=crlf
*.py eol=lf
*.sh eol=lf
*.ps1 eol=crlf

2
.github/ISSUE_TEMPLATE/config.yml vendored
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@ -2,5 +2,5 @@
blank_issues_enabled: false
contact_links:
- name: Discord Server
url: https://discord.gg/MA9v74M
url: https://discord.gg/p7nuUNVfP7
about: Ask a question or get community support from our Discord server

15
.github/workflows/ci.yml vendored
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@ -75,7 +75,7 @@ jobs:
COVERALLS_REPO_TOKEN: 6D1m0xupS3FgutfuGao8keFf9Hc0FpIXu
run: |
# Allow failure for coveralls
coveralls -v || true
coveralls || true
- name: Backtesting
run: |
@ -374,13 +374,6 @@ jobs:
run: |
echo "${DOCKER_PASSWORD}" | docker login --username ${DOCKER_USERNAME} --password-stdin
- name: Build and test and push docker image
env:
IMAGE_NAME: freqtradeorg/freqtrade
BRANCH_NAME: ${{ steps.extract_branch.outputs.branch }}
run: |
build_helpers/publish_docker.sh
# We need docker experimental to pull the ARM image.
- name: Switch docker to experimental
run: |
@ -399,12 +392,12 @@ jobs:
- name: Available platforms
run: echo ${{ steps.buildx.outputs.platforms }}
- name: Build Raspberry docker image
- name: Build and test and push docker images
env:
IMAGE_NAME: freqtradeorg/freqtrade
BRANCH_NAME: ${{ steps.extract_branch.outputs.branch }}_pi
BRANCH_NAME: ${{ steps.extract_branch.outputs.branch }}
run: |
build_helpers/publish_docker_pi.sh
build_helpers/publish_docker_multi.sh
- name: Slack Notification

6
.travis.yml
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@ -46,12 +46,6 @@ jobs:
- script: mypy freqtrade scripts
name: mypy
# - stage: docker
# if: branch in (master, develop, feat/improve_travis) AND (type in (push, cron))
# script:
# - build_helpers/publish_docker.sh
# name: "Build and test and push docker image"
notifications:
slack:
secure: 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

2
CONTRIBUTING.md
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@ -12,7 +12,7 @@ Few pointers for contributions:
- New features need to contain unit tests, must conform to PEP8 (max-line-length = 100) and should be documented with the introduction PR.
- PR's can be declared as `[WIP]` - which signify Work in Progress Pull Requests (which are not finished).
If you are unsure, discuss the feature on our [discord server](https://discord.gg/MA9v74M), on [Slack](https://join.slack.com/t/highfrequencybot/shared_invite/zt-mm786y93-Fxo37glxMY9g8OQC5AoOIw) or in a [issue](https://github.com/freqtrade/freqtrade/issues) before a PR.
If you are unsure, discuss the feature on our [discord server](https://discord.gg/p7nuUNVfP7), on [Slack](https://join.slack.com/t/highfrequencybot/shared_invite/zt-mm786y93-Fxo37glxMY9g8OQC5AoOIw) or in a [issue](https://github.com/freqtrade/freqtrade/issues) before a PR.
## Getting started

14
Dockerfile
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@ -10,8 +10,8 @@ ENV FT_APP_ENV="docker"
# Prepare environment
RUN mkdir /freqtrade \
&& apt update \
&& apt install -y sudo \
&& apt-get update \
&& apt-get -y install sudo libatlas3-base curl sqlite3 libhdf5-serial-dev \
&& apt-get clean \
&& useradd -u 1000 -G sudo -U -m ftuser \
&& chown ftuser:ftuser /freqtrade \
@ -22,10 +22,10 @@ WORKDIR /freqtrade
# Install dependencies
FROM base as python-deps
RUN apt-get update \
&& apt-get -y install curl build-essential libssl-dev git \
&& apt-get clean \
&& pip install --upgrade pip
RUN apt-get update \
&& apt-get -y install build-essential libssl-dev git libffi-dev libgfortran5 pkg-config cmake gcc \
&& apt-get clean \
&& pip install --upgrade pip
# Install TA-lib
COPY build_helpers/* /tmp/
@ -49,7 +49,7 @@ USER ftuser
# Install and execute
COPY --chown=ftuser:ftuser . /freqtrade/
RUN pip install -e . --user --no-cache-dir \
RUN pip install -e . --user --no-cache-dir --no-build-isolation \
&& mkdir /freqtrade/user_data/ \
&& freqtrade install-ui

6
README.md
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@ -123,7 +123,7 @@ Telegram is not mandatory. However, this is a great way to control your bot. Mor
- `/stop`: Stops the trader.
- `/stopbuy`: Stop entering new trades.
- `/status <trade_id>|[table]`: Lists all or specific open trades.
- `/profit`: Lists cumulative profit from all finished trades
- `/profit [<n>]`: Lists cumulative profit from all finished trades, over the last n days.
- `/forcesell <trade_id>|all`: Instantly sells the given trade (Ignoring `minimum_roi`).
- `/performance`: Show performance of each finished trade grouped by pair
- `/balance`: Show account balance per currency.
@ -145,7 +145,7 @@ The project is currently setup in two main branches:
For any questions not covered by the documentation or for further information about the bot, or to simply engage with like-minded individuals, we encourage you to join our slack channel.
Please check out our [discord server](https://discord.gg/MA9v74M).
Please check out our [discord server](https://discord.gg/p7nuUNVfP7).
You can also join our [Slack channel](https://join.slack.com/t/highfrequencybot/shared_invite/zt-mm786y93-Fxo37glxMY9g8OQC5AoOIw).
@ -178,7 +178,7 @@ to understand the requirements before sending your pull-requests.
Coding is not a necessity to contribute - maybe start with improving our documentation?
Issues labeled [good first issue](https://github.com/freqtrade/freqtrade/labels/good%20first%20issue) can be good first contributions, and will help get you familiar with the codebase.
**Note** before starting any major new feature work, *please open an issue describing what you are planning to do* or talk to us on [discord](https://discord.gg/MA9v74M) or [Slack](https://join.slack.com/t/highfrequencybot/shared_invite/zt-mm786y93-Fxo37glxMY9g8OQC5AoOIw). This will ensure that interested parties can give valuable feedback on the feature, and let others know that you are working on it.
**Note** before starting any major new feature work, *please open an issue describing what you are planning to do* or talk to us on [discord](https://discord.gg/p7nuUNVfP7) or [Slack](https://join.slack.com/t/highfrequencybot/shared_invite/zt-mm786y93-Fxo37glxMY9g8OQC5AoOIw). This will ensure that interested parties can give valuable feedback on the feature, and let others know that you are working on it.
**Important:** Always create your PR against the `develop` branch, not `stable`.

64
build_helpers/publish_docker.sh → build_helpers/publish_docker_multi.sh
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@ -1,21 +1,48 @@
#!/bin/sh
# The below assumes a correctly setup docker buildx environment
# Replace / with _ to create a valid tag
TAG=$(echo "${BRANCH_NAME}" | sed -e "s/\//_/g")
TAG_PLOT=${TAG}_plot
TAG_PI="${TAG}_pi"
PI_PLATFORM="linux/arm/v7"
echo "Running for ${TAG}"
CACHE_TAG=freqtradeorg/freqtrade_cache:${TAG}_cache
# Add commit and commit_message to docker container
echo "${GITHUB_SHA}" > freqtrade_commit
if [ "${GITHUB_EVENT_NAME}" = "schedule" ]; then
echo "event ${GITHUB_EVENT_NAME}: full rebuild - skipping cache"
# Build regular image
docker build -t freqtrade:${TAG} .
# Build PI image
docker buildx build \
--cache-to=type=registry,ref=${CACHE_TAG} \
-f docker/Dockerfile.armhf \
--platform ${PI_PLATFORM} \
-t ${IMAGE_NAME}:${TAG_PI} --push .
else
echo "event ${GITHUB_EVENT_NAME}: building with cache"
# Pull last build to avoid rebuilding the whole image
# Build regular image
docker pull ${IMAGE_NAME}:${TAG}
docker build --cache-from ${IMAGE_NAME}:${TAG} -t freqtrade:${TAG} .
# Pull last build to avoid rebuilding the whole image
# docker pull --platform ${PI_PLATFORM} ${IMAGE_NAME}:${TAG}
docker buildx build \
--cache-from=type=registry,ref=${CACHE_TAG} \
--cache-to=type=registry,ref=${CACHE_TAG} \
-f docker/Dockerfile.armhf \
--platform ${PI_PLATFORM} \
-t ${IMAGE_NAME}:${TAG_PI} --push .
fi
if [ $? -ne 0 ]; then
echo "failed building multiarch images"
return 1
fi
# Tag image for upload and next build step
docker tag freqtrade:$TAG ${IMAGE_NAME}:$TAG
@ -24,11 +51,6 @@ docker build --cache-from freqtrade:${TAG} --build-arg sourceimage=${TAG} -t fre
docker tag freqtrade:$TAG_PLOT ${IMAGE_NAME}:$TAG_PLOT
if [ $? -ne 0 ]; then
echo "failed building image"
return 1
fi
# Run backtest
docker run --rm -v $(pwd)/config_bittrex.json.example:/freqtrade/config.json:ro -v $(pwd)/tests:/tests freqtrade:${TAG} backtesting --datadir /tests/testdata --strategy-path /tests/strategy/strats/ --strategy DefaultStrategy
@ -37,23 +59,29 @@ if [ $? -ne 0 ]; then
return 1
fi
if [ $? -ne 0 ]; then
echo "failed tagging image"
return 1
fi
# Tag as latest for develop builds
if [ "${TAG}" = "develop" ]; then
docker tag freqtrade:$TAG ${IMAGE_NAME}:latest
fi
# Show all available images
docker images
docker push ${IMAGE_NAME}
docker push ${IMAGE_NAME}:$TAG_PLOT
docker push ${IMAGE_NAME}:$TAG
# Create multiarch image
# Make sure that all images contained here are pushed to github first.
# Otherwise installation might fail.
docker manifest create freqtradeorg/freqtrade:${TAG} ${IMAGE_NAME}:${TAG} ${IMAGE_NAME}:${TAG_PI}
docker manifest push freqtradeorg/freqtrade:${TAG}
# Tag as latest for develop builds
if [ "${TAG}" = "develop" ]; then
docker manifest create freqtradeorg/freqtrade:latest ${IMAGE_NAME}:${TAG} ${IMAGE_NAME}:${TAG_PI}
docker manifest push freqtradeorg/freqtrade:latest
fi
docker images
if [ $? -ne 0 ]; then
echo "failed pushing repo"
echo "failed building image"
return 1
fi

36
build_helpers/publish_docker_pi.sh
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@ -1,36 +0,0 @@
#!/bin/sh
# The below assumes a correctly setup docker buildx environment
# Replace / with _ to create a valid tag
TAG=$(echo "${BRANCH_NAME}" | sed -e "s/\//_/g")
PI_PLATFORM="linux/arm/v7"
echo "Running for ${TAG}"
CACHE_TAG=freqtradeorg/freqtrade_cache:${TAG}_cache
# Add commit and commit_message to docker container
echo "${GITHUB_SHA}" > freqtrade_commit
if [ "${GITHUB_EVENT_NAME}" = "schedule" ]; then
echo "event ${GITHUB_EVENT_NAME}: full rebuild - skipping cache"
docker buildx build \
--cache-to=type=registry,ref=${CACHE_TAG} \
-f Dockerfile.armhf \
--platform ${PI_PLATFORM} \
-t ${IMAGE_NAME}:${TAG} --push .
else
echo "event ${GITHUB_EVENT_NAME}: building with cache"
# Pull last build to avoid rebuilding the whole image
# docker pull --platform ${PI_PLATFORM} ${IMAGE_NAME}:${TAG}
docker buildx build \
--cache-from=type=registry,ref=${CACHE_TAG} \
--cache-to=type=registry,ref=${CACHE_TAG} \
-f Dockerfile.armhf \
--platform ${PI_PLATFORM} \
-t ${IMAGE_NAME}:${TAG} --push .
fi
if [ $? -ne 0 ]; then
echo "failed building image"
return 1
fi

15
config_full.json.example
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@ -165,11 +165,22 @@
"startup": "on",
"buy": "on",
"buy_fill": "on",
"sell": "on",
"sell": {
"roi": "off",
"emergency_sell": "off",
"force_sell": "off",
"sell_signal": "off",
"trailing_stop_loss": "off",
"stop_loss": "off",
"stoploss_on_exchange": "off",
"custom_sell": "off"
},
"sell_fill": "on",
"buy_cancel": "on",
"sell_cancel": "on"
}
},
"reload": true,
"balance_dust_level": 0.01
},
"api_server": {
"enabled": false,

58
docker/Dockerfile.aarch64
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@ -1,58 +0,0 @@
FROM --platform=linux/arm64/v8 python:3.9.4-slim-buster as base
# Setup env
ENV LANG C.UTF-8
ENV LC_ALL C.UTF-8
ENV PYTHONDONTWRITEBYTECODE 1
ENV PYTHONFAULTHANDLER 1
ENV PATH=/home/ftuser/.local/bin:$PATH
ENV FT_APP_ENV="docker"
# Prepare environment
RUN mkdir /freqtrade \
&& apt-get update \
&& apt-get -y install libatlas3-base curl sqlite3 libhdf5-serial-dev sudo \
&& apt-get clean \
&& useradd -u 1000 -G sudo -U -m ftuser \
&& chown ftuser:ftuser /freqtrade \
# Allow sudoers
&& echo "ftuser ALL=(ALL) NOPASSWD: /bin/chown" >> /etc/sudoers
WORKDIR /freqtrade
# Install dependencies
FROM base as python-deps
RUN apt-get update \
&& apt-get -y install curl build-essential libssl-dev git libffi-dev libgfortran5 pkg-config cmake gcc \
&& apt-get clean \
&& pip install --upgrade pip
# Install TA-lib
COPY build_helpers/* /tmp/
RUN cd /tmp && /tmp/install_ta-lib.sh && rm -r /tmp/*ta-lib*
ENV LD_LIBRARY_PATH /usr/local/lib
# Install dependencies
COPY --chown=ftuser:ftuser requirements.txt requirements-hyperopt.txt /freqtrade/
USER ftuser
RUN pip install --user --no-cache-dir numpy \
&& pip install --user --no-cache-dir -r requirements-hyperopt.txt
# Copy dependencies to runtime-image
FROM base as runtime-image
COPY --from=python-deps /usr/local/lib /usr/local/lib
ENV LD_LIBRARY_PATH /usr/local/lib
COPY --from=python-deps --chown=ftuser:ftuser /home/ftuser/.local /home/ftuser/.local
USER ftuser
# Install and execute
COPY --chown=ftuser:ftuser . /freqtrade/
RUN pip install -e . --user --no-cache-dir \
&& mkdir /freqtrade/user_data/ \
&& freqtrade install-ui
ENTRYPOINT ["freqtrade"]
# Default to trade mode
CMD [ "trade" ]

9
Dockerfile.armhf → docker/Dockerfile.armhf
View File

@ -1,4 +1,4 @@
FROM --platform=linux/arm/v7 python:3.7.10-slim-buster as base
FROM python:3.7.10-slim-buster as base
# Setup env
ENV LANG C.UTF-8
@ -11,7 +11,7 @@ ENV FT_APP_ENV="docker"
# Prepare environment
RUN mkdir /freqtrade \
&& apt-get update \
&& apt-get -y install libatlas3-base curl sqlite3 libhdf5-serial-dev sudo \
&& apt-get -y install sudo libatlas3-base curl sqlite3 libhdf5-dev \
&& apt-get clean \
&& useradd -u 1000 -G sudo -U -m ftuser \
&& chown ftuser:ftuser /freqtrade \
@ -22,7 +22,8 @@ WORKDIR /freqtrade
# Install dependencies
FROM base as python-deps
RUN apt-get -y install build-essential libssl-dev libffi-dev libgfortran5 \
RUN apt-get update \
&& apt-get -y install build-essential libssl-dev libffi-dev libgfortran5 pkg-config cmake gcc \
&& apt-get clean \
&& pip install --upgrade pip \
&& echo "[global]\nextra-index-url=https://www.piwheels.org/simple" > /etc/pip.conf
@ -49,7 +50,7 @@ USER ftuser
# Install and execute
COPY --chown=ftuser:ftuser . /freqtrade/
RUN pip install -e . --user --no-cache-dir \
RUN pip install -e . --user --no-cache-dir --no-build-isolation\
&& mkdir /freqtrade/user_data/ \
&& freqtrade install-ui

2
docs/advanced-hyperopt.md
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@ -289,7 +289,7 @@ Given the following result from hyperopt:
```
Best result:
44/100: 135 trades. Avg profit 0.57%. Total profit 0.03871918 BTC (0.7722Σ%). Avg duration 180.4 mins. Objective: 1.94367
44/100: 135 trades. Avg profit 0.57%. Total profit 0.03871918 BTC (0.7722%). Avg duration 180.4 mins. Objective: 1.94367
Buy hyperspace params:
{ 'adx-value': 44,

30
docs/backtesting.md
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@ -19,7 +19,7 @@ usage: freqtrade backtesting [-h] [-v] [--logfile FILE] [-V] [-c PATH]
[--enable-protections]
[--dry-run-wallet DRY_RUN_WALLET]
[--strategy-list STRATEGY_LIST [STRATEGY_LIST ...]]
[--export EXPORT] [--export-filename PATH]
[--export {none,trades}] [--export-filename PATH]
optional arguments:
-h, --help show this help message and exit
@ -63,8 +63,8 @@ optional arguments:
name is injected into the filename (so `backtest-
data.json` becomes `backtest-data-
DefaultStrategy.json`
--export EXPORT Export backtest results, argument are: trades.
Example: `--export=trades`
--export {none,trades}
Export backtest results (default: trades).
--export-filename PATH
Save backtest results to the file with this filename.
Requires `--export` to be set as well. Example:
@ -100,7 +100,7 @@ Strategy arguments:
Now you have good Buy and Sell strategies and some historic data, you want to test it against
real data. This is what we call [backtesting](https://en.wikipedia.org/wiki/Backtesting).
Backtesting will use the crypto-currencies (pairs) from your config file and load historical candle (OHCLV) data from `user_data/data/<exchange>` by default.
Backtesting will use the crypto-currencies (pairs) from your config file and load historical candle (OHLCV) data from `user_data/data/<exchange>` by default.
If no data is available for the exchange / pair / timeframe combination, backtesting will ask you to download them first using `freqtrade download-data`.
For details on downloading, please refer to the [Data Downloading](data-download.md) section in the documentation.
@ -110,11 +110,16 @@ All profit calculations include fees, and freqtrade will use the exchange's defa
!!! Warning "Using dynamic pairlists for backtesting"
Using dynamic pairlists is possible, however it relies on the current market conditions - which will not reflect the historic status of the pairlist.
Also, when using pairlists other than StaticPairlist, reproducability of backtesting-results cannot be guaranteed.
Also, when using pairlists other than StaticPairlist, reproducibility of backtesting-results cannot be guaranteed.
Please read the [pairlists documentation](plugins.md#pairlists) for more information.
To achieve reproducible results, best generate a pairlist via the [`test-pairlist`](utils.md#test-pairlist) command and use that as static pairlist.
!!! Note
By default, Freqtrade will export backtesting results to `user_data/backtest_results`.
The exported trades can be used for [further analysis](#further-backtest-result-analysis) or can be used by the [plotting sub-command](plotting.md#plot-price-and-indicators) (`freqtrade plot-dataframe`) in the scripts directory.
### Starting balance
Backtesting will require a starting balance, which can be provided as `--dry-run-wallet <balance>` or `--starting-balance <balance>` command line argument, or via `dry_run_wallet` configuration setting.
@ -174,13 +179,13 @@ Where `SampleStrategy1` and `AwesomeStrategy` refer to class names of strategies
---
Exporting trades to file
Prevent exporting trades to file
```bash
freqtrade backtesting --strategy backtesting --export trades --config config.json
freqtrade backtesting --strategy backtesting --export none --config config.json
```
The exported trades can be used for [further analysis](#further-backtest-result-analysis), or can be used by the plotting script `plot_dataframe.py` in the scripts directory.
Only use this if you're sure you'll not want to plot or analyze your results further.
---
@ -279,7 +284,7 @@ A backtesting result will look like that:
| Backtesting to | 2019-05-01 00:00:00 |
| Max open trades | 3 |
| | |
| Total trades | 429 |
| Total/Daily Avg Trades| 429 / 3.575 |
| Starting balance | 0.01000000 BTC |
| Final balance | 0.01762792 BTC |
| Absolute profit | 0.00762792 BTC |
@ -368,12 +373,11 @@ It contains some useful key metrics about performance of your strategy on backte
| Backtesting to | 2019-05-01 00:00:00 |
| Max open trades | 3 |
| | |
| Total trades | 429 |
| Total/Daily Avg Trades| 429 / 3.575 |
| Starting balance | 0.01000000 BTC |
| Final balance | 0.01762792 BTC |
| Absolute profit | 0.00762792 BTC |
| Total profit % | 76.2% |
| Trades per day | 3.575 |
| Avg. stake amount | 0.001 BTC |
| Total trade volume | 0.429 BTC |
| | |
@ -404,12 +408,11 @@ It contains some useful key metrics about performance of your strategy on backte
- `Backtesting from` / `Backtesting to`: Backtesting range (usually defined with the `--timerange` option).
- `Max open trades`: Setting of `max_open_trades` (or `--max-open-trades`) - or number of pairs in the pairlist (whatever is lower).
- `Total trades`: Identical to the total trades of the backtest output table.
- `Total/Daily Avg Trades`: Identical to the total trades of the backtest output table / Total trades divided by the backtesting duration in days (this will give you information about how many trades to expect from the strategy).
- `Starting balance`: Start balance - as given by dry-run-wallet (config or command line).
- `Final balance`: Final balance - starting balance + absolute profit.
- `Absolute profit`: Profit made in stake currency.
- `Total profit %`: Total profit. Aligned to the `TOTAL` row's `Tot Profit %` from the first table. Calculated as `(End capital − Starting capital) / Starting capital`.
- `Trades per day`: Total trades divided by the backtesting duration in days (this will give you information about how many trades to expect from the strategy).
- `Avg. stake amount`: Average stake amount, either `stake_amount` or the average when using dynamic stake amount.
- `Total trade volume`: Volume generated on the exchange to reach the above profit.
- `Best Pair` / `Worst Pair`: Best and worst performing pair, and it's corresponding `Cum Profit %`.
@ -441,6 +444,7 @@ Since backtesting lacks some detailed information about what happens within a ca
- Stoploss is evaluated before ROI within one candle. So you can often see more trades with the `stoploss` sell reason comparing to the results obtained with the same strategy in the Dry Run/Live Trade modes
- Low happens before high for stoploss, protecting capital first
- Trailing stoploss
- Trailing Stoploss is only adjusted if it's below the candle's low (otherwise it would be triggered)
- High happens first - adjusting stoploss
- Low uses the adjusted stoploss (so sells with large high-low difference are backtested correctly)
- ROI applies before trailing-stop, ensuring profits are "top-capped" at ROI if both ROI and trailing stop applies

18
docs/configuration.md
View File

@ -102,10 +102,11 @@ Mandatory parameters are marked as **Required**, which means that they are requi
| `exchange.markets_refresh_interval` | The interval in minutes in which markets are reloaded. <br>*Defaults to `60` minutes.* <br> **Datatype:** Positive Integer
| `exchange.skip_pair_validation` | Skip pairlist validation on startup.<br>*Defaults to `false`<br> **Datatype:** Boolean
| `exchange.skip_open_order_update` | Skips open order updates on startup should the exchange cause problems. Only relevant in live conditions.<br>*Defaults to `false`<br> **Datatype:** Boolean
| `exchange.log_responses` | Log relevant exchange responses. For debug mode only - use with care.<br>*Defaults to `false`<br> **Datatype:** Boolean
| `edge.*` | Please refer to [edge configuration document](edge.md) for detailed explanation.
| `experimental.block_bad_exchanges` | Block exchanges known to not work with freqtrade. Leave on default unless you want to test if that exchange works now. <br>*Defaults to `true`.* <br> **Datatype:** Boolean
| `pairlists` | Define one or more pairlists to be used. [More information](plugins.md#pairlists-and-pairlist-handlers). <br>*Defaults to `StaticPairList`.* <br> **Datatype:** List of Dicts
| `protections` | Define one or more protections to be used. [More information](plugins.md#protections). [Strategy Override](#parameters-in-the-strategy). <br> **Datatype:** List of Dicts
| `protections` | Define one or more protections to be used. [More information](plugins.md#protections). <br> **Datatype:** List of Dicts
| `telegram.enabled` | Enable the usage of Telegram. <br> **Datatype:** Boolean
| `telegram.token` | Your Telegram bot token. Only required if `telegram.enabled` is `true`. <br>**Keep it in secret, do not disclose publicly.** <br> **Datatype:** String
| `telegram.chat_id` | Your personal Telegram account id. Only required if `telegram.enabled` is `true`. <br>**Keep it in secret, do not disclose publicly.** <br> **Datatype:** String
@ -140,7 +141,7 @@ Mandatory parameters are marked as **Required**, which means that they are requi
### Parameters in the strategy
The following parameters can be set in either configuration file or strategy.
The following parameters can be set in configuration file or strategy.
Values set in the configuration file always overwrite values set in the strategy.
* `minimal_roi`
@ -156,7 +157,6 @@ Values set in the configuration file always overwrite values set in the strategy
* `order_time_in_force`
* `unfilledtimeout`
* `disable_dataframe_checks`
* `protections`
* `use_sell_signal` (ask_strategy)
* `sell_profit_only` (ask_strategy)
* `sell_profit_offset` (ask_strategy)
@ -170,7 +170,7 @@ There are several methods to configure how much of the stake currency the bot wi
#### Minimum trade stake
The minimum stake amount will depend by exchange and pair, and is usually listed in the exchange support pages.
Assuming the minimum tradable amount for XRP/USD is 20 XRP (given by the exchange), and the price is 0.4$.
Assuming the minimum tradable amount for XRP/USD is 20 XRP (given by the exchange), and the price is 0.6$.
The minimum stake amount to buy this pair is therefore `20 * 0.6 ~= 12`.
This exchange has also a limit on USD - where all orders must be > 10$ - which however does not apply in this case.
@ -304,6 +304,9 @@ For example, if your strategy is using a 1h timeframe, and you only want to buy
},
```
!!! Note
This setting resets with each new candle, so it will not prevent sticking-signals from executing on the 2nd or 3rd candle they're active. Best use a "trigger" selector for buy signals, which are only active for one candle.
### Understand order_types
The `order_types` configuration parameter maps actions (`buy`, `sell`, `stoploss`, `emergencysell`, `forcesell`, `forcebuy`) to order-types (`market`, `limit`, ...) as well as configures stoploss to be on the exchange and defines stoploss on exchange update interval in seconds.
@ -403,8 +406,8 @@ The possible values are: `gtc` (default), `fok` or `ioc`.
```
!!! Warning
This is an ongoing work. For now it is supported only for binance and only for buy orders.
Please don't change the default value unless you know what you are doing.
This is an ongoing work. For now it is supported only for binance.
Please don't change the default value unless you know what you are doing and have researched the impact of using different values.
### Exchange configuration
@ -500,7 +503,8 @@ Once you will be happy with your bot performance running in the Dry-run mode, yo
* API-keys may or may not be provided. Only Read-Only operations (i.e. operations that do not alter account state) on the exchange are performed in dry-run mode.
* Wallets (`/balance`) are simulated based on `dry_run_wallet`.
* Orders are simulated, and will not be posted to the exchange.
* Orders are assumed to fill immediately, and will never time out.
* Market orders fill based on orderbook volume the moment the order is placed.
* Limit orders fill once price reaches the defined level - or time out based on `unfilledtimeout` settings.
* In combination with `stoploss_on_exchange`, the stop_loss price is assumed to be filled.
* Open orders (not trades, which are stored in the database) are reset on bot restart.

2
docs/developer.md
View File

@ -2,7 +2,7 @@
This page is intended for developers of Freqtrade, people who want to contribute to the Freqtrade codebase or documentation, or people who want to understand the source code of the application they're running.
All contributions, bug reports, bug fixes, documentation improvements, enhancements and ideas are welcome. We [track issues](https://github.com/freqtrade/freqtrade/issues) on [GitHub](https://github.com) and also have a dev channel on [discord](https://discord.gg/MA9v74M) or [slack](https://join.slack.com/t/highfrequencybot/shared_invite/zt-mm786y93-Fxo37glxMY9g8OQC5AoOIw) where you can ask questions.
All contributions, bug reports, bug fixes, documentation improvements, enhancements and ideas are welcome. We [track issues](https://github.com/freqtrade/freqtrade/issues) on [GitHub](https://github.com) and also have a dev channel on [discord](https://discord.gg/p7nuUNVfP7) or [slack](https://join.slack.com/t/highfrequencybot/shared_invite/zt-mm786y93-Fxo37glxMY9g8OQC5AoOIw) where you can ask questions.
## Documentation

2
docs/docker_quickstart.md
View File

@ -98,7 +98,7 @@ Create a new directory and place the [docker-compose file](https://raw.githubuse
image: freqtradeorg/freqtrade:custom_arm64
build:
context: .
dockerfile: "./docker/Dockerfile.aarch64"
dockerfile: "Dockerfile"
```
The above snippet creates a new directory called `ft_userdata`, downloads the latest compose file and pulls the freqtrade image.

6
docs/exchanges.md
View File

@ -14,11 +14,10 @@ Accounts having BNB accounts use this to pay for fees - if your first trade happ
### Binance sites
Binance has been split into 3, and users must use the correct ccxt exchange ID for their exchange, otherwise API keys are not recognized.
Binance has been split into 2, and users must use the correct ccxt exchange ID for their exchange, otherwise API keys are not recognized.
* [binance.com](https://www.binance.com/) - International users. Use exchange id: `binance`.
* [binance.us](https://www.binance.us/) - US based users. Use exchange id: `binanceus`.
* [binance.je](https://www.binance.je/) - Binance Jersey, trading fiat currencies. Use exchange id: `binanceje`.
## Kraken
@ -54,6 +53,9 @@ Due to the heavy rate-limiting applied by Kraken, the following configuration se
Bittrex does not support market orders. If you have a message at the bot startup about this, you should change order type values set in your configuration and/or in the strategy from `"market"` to `"limit"`. See some more details on this [here in the FAQ](faq.md#im-getting-the-exchange-bittrex-does-not-support-market-orders-message-and-cannot-run-my-strategy).
Bittrex also does not support `VolumePairlist` due to limited / split API constellation at the moment.
Please use `StaticPairlist`. Other pairlists (other than `VolumePairlist`) should not be affected.
### Restricted markets
Bittrex split its exchange into US and International versions.

18
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@ -136,6 +136,22 @@ On Windows, the `--logfile` option is also supported by Freqtrade and you can us
> type \path\to\mylogfile.log | findstr "something"
```
### Why does freqtrade not have GPU support?
First of all, most indicator libraries don't have GPU support - as such, there would be little benefit for indicator calculations.
The GPU improvements would only apply to pandas-native calculations - or ones written by yourself.
For hyperopt, freqtrade is using scikit-optimize, which is built on top of scikit-learn.
Their statement about GPU support is [pretty clear](https://scikit-learn.org/stable/faq.html#will-you-add-gpu-support).
GPU's also are only good at crunching numbers (floating point operations).
For hyperopt, we need both number-crunching (find next parameters) and running python code (running backtesting).
As such, GPU's are not too well suited for most parts of hyperopt.
The benefit of using GPU would therefore be pretty slim - and will not justify the complexity introduced by trying to add GPU support.
There is however nothing preventing you from using GPU-enabled indicators within your strategy if you think you must have this - you will however probably be disappointed by the slim gain that will give you (compared to the complexity).
## Hyperopt module
### How many epochs do I need to get a good Hyperopt result?
@ -156,7 +172,7 @@ freqtrade hyperopt --hyperopt SampleHyperopt --hyperopt-loss SharpeHyperOptLossD
### Why does it take a long time to run hyperopt?
* Discovering a great strategy with Hyperopt takes time. Study www.freqtrade.io, the Freqtrade Documentation page, join the Freqtrade [Slack community](https://join.slack.com/t/highfrequencybot/shared_invite/zt-mm786y93-Fxo37glxMY9g8OQC5AoOIw) - or the Freqtrade [discord community](https://discord.gg/MA9v74M). While you patiently wait for the most advanced, free crypto bot in the world, to hand you a possible golden strategy specially designed just for you.
* Discovering a great strategy with Hyperopt takes time. Study www.freqtrade.io, the Freqtrade Documentation page, join the Freqtrade [Slack community](https://join.slack.com/t/highfrequencybot/shared_invite/zt-mm786y93-Fxo37glxMY9g8OQC5AoOIw) - or the Freqtrade [discord community](https://discord.gg/p7nuUNVfP7). While you patiently wait for the most advanced, free crypto bot in the world, to hand you a possible golden strategy specially designed just for you.
* If you wonder why it can take from 20 minutes to days to do 1000 epochs here are some answers:

14
docs/hyperopt.md
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@ -237,9 +237,9 @@ class MyAwesomeStrategy(IStrategy):
dataframe['macdhist'] = macd['macdhist']
bollinger = ta.BBANDS(dataframe, timeperiod=20, nbdevup=2.0, nbdevdn=2.0)
dataframe['bb_lowerband'] = boll['lowerband']
dataframe['bb_middleband'] = boll['middleband']
dataframe['bb_upperband'] = boll['upperband']
dataframe['bb_lowerband'] = bollinger['lowerband']
dataframe['bb_middleband'] = bollinger['middleband']
dataframe['bb_upperband'] = bollinger['upperband']
return dataframe
```
@ -491,7 +491,7 @@ Given the following result from hyperopt:
```
Best result:
44/100: 135 trades. Avg profit 0.57%. Total profit 0.03871918 BTC (0.7722Σ%). Avg duration 180.4 mins. Objective: 1.94367
44/100: 135 trades. Avg profit 0.57%. Total profit 0.03871918 BTC (0.7722%). Avg duration 180.4 mins. Objective: 1.94367
# Buy hyperspace params:
buy_params = {
@ -532,7 +532,7 @@ If you are optimizing ROI (i.e. if optimization search-space contains 'all', 'de
```
Best result:
44/100: 135 trades. Avg profit 0.57%. Total profit 0.03871918 BTC (0.7722Σ%). Avg duration 180.4 mins. Objective: 1.94367
44/100: 135 trades. Avg profit 0.57%. Total profit 0.03871918 BTC (0.7722%). Avg duration 180.4 mins. Objective: 1.94367
# ROI table:
minimal_roi = {
@ -587,7 +587,7 @@ If you are optimizing stoploss values (i.e. if optimization search-space contain
```
Best result:
44/100: 135 trades. Avg profit 0.57%. Total profit 0.03871918 BTC (0.7722Σ%). Avg duration 180.4 mins. Objective: 1.94367
44/100: 135 trades. Avg profit 0.57%. Total profit 0.03871918 BTC (0.7722%). Avg duration 180.4 mins. Objective: 1.94367
# Buy hyperspace params:
buy_params = {
@ -629,7 +629,7 @@ If you are optimizing trailing stop values (i.e. if optimization search-space co
```
Best result:
45/100: 606 trades. Avg profit 1.04%. Total profit 0.31555614 BTC ( 630.48Σ%). Avg duration 150.3 mins. Objective: -1.10161
45/100: 606 trades. Avg profit 1.04%. Total profit 0.31555614 BTC ( 630.48%). Avg duration 150.3 mins. Objective: -1.10161
# Trailing stop:
trailing_stop = True

4
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@ -122,8 +122,8 @@ The `max_price` setting removes pairs where the price is above the specified pri
This option is disabled by default, and will only apply if set to > 0.
The `max_value` setting removes pairs where the minimum value change is above a specified value.
This is useful when an exchange has unbalanced limits. For example, if step-size = 1 (so you can only buy 1, or 2, or 3, but not 1.1 Coins) - and the price is pretty high (like 20$) as the coin has risen sharply since the last limit adaption.
As a result of the above, you can only buy for 20$, or 40$ - but not for 25$.
This is useful when an exchange has unbalanced limits. For example, if step-size = 1 (so you can only buy 1, or 2, or 3, but not 1.1 Coins) - and the price is pretty high (like 20\$) as the coin has risen sharply since the last limit adaption.
As a result of the above, you can only buy for 20\$, or 40\$ - but not for 25\$.
On exchanges that deduct fees from the receiving currency (e.g. FTX) - this can result in high value coins / amounts that are unsellable as the amount is slightly below the limit.
The `low_price_ratio` setting removes pairs where a raise of 1 price unit (pip) is above the `low_price_ratio` ratio.

67
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@ -8,7 +8,6 @@ All protection end times are rounded up to the next candle to avoid sudden, unex
!!! Note
Not all Protections will work for all strategies, and parameters will need to be tuned for your strategy to improve performance.
To align your protection with your strategy, you can define protections in the strategy.
!!! Tip
Each Protection can be configured multiple times with different parameters, to allow different levels of protection (short-term / long-term).
@ -47,16 +46,16 @@ This applies across all pairs, unless `only_per_pair` is set to true, which will
The below example stops trading for all pairs for 4 candles after the last trade if the bot hit stoploss 4 times within the last 24 candles.
```json
"protections": [
``` python
protections = [
{
"method": "StoplossGuard",
"lookback_period_candles": 24,
"trade_limit": 4,
"stop_duration_candles": 4,
"only_per_pair": false
"only_per_pair": False
}
],
]
```
!!! Note
@ -69,8 +68,8 @@ The below example stops trading for all pairs for 4 candles after the last trade
The below sample stops trading for 12 candles if max-drawdown is > 20% considering all pairs - with a minimum of `trade_limit` trades - within the last 48 candles. If desired, `lookback_period` and/or `stop_duration` can be used.
```json
"protections": [
``` python
protections = [
{
"method": "MaxDrawdown",
"lookback_period_candles": 48,
@ -78,7 +77,7 @@ The below sample stops trading for 12 candles if max-drawdown is > 20% consideri
"stop_duration_candles": 12,
"max_allowed_drawdown": 0.2
},
],
]
```
#### Low Profit Pairs
@ -88,8 +87,8 @@ If that ratio is below `required_profit`, that pair will be locked for `stop_dur
The below example will stop trading a pair for 60 minutes if the pair does not have a required profit of 2% (and a minimum of 2 trades) within the last 6 candles.
```json
"protections": [
``` python
protections = [
{
"method": "LowProfitPairs",
"lookback_period_candles": 6,
@ -97,7 +96,7 @@ The below example will stop trading a pair for 60 minutes if the pair does not h
"stop_duration": 60,
"required_profit": 0.02
}
],
]
```
#### Cooldown Period
@ -106,13 +105,13 @@ The below example will stop trading a pair for 60 minutes if the pair does not h
The below example will stop trading a pair for 2 candles after closing a trade, allowing this pair to "cool down".
```json
"protections": [
``` python
protections = [
{
"method": "CooldownPeriod",
"stop_duration_candles": 2
}
],
]
```
!!! Note
@ -132,46 +131,6 @@ The below example assumes a timeframe of 1 hour:
* 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 for 2 candles that had a profit of below 0.01 (<1%) within the last 24h (`24 * 1h candles`), a minimum of 4 trades.
```json
"timeframe": "1h",
"protections": [
{
"method": "CooldownPeriod",
"stop_duration_candles": 5
},
{
"method": "MaxDrawdown",
"lookback_period_candles": 48,
"trade_limit": 20,
"stop_duration_candles": 4,
"max_allowed_drawdown": 0.2
},
{
"method": "StoplossGuard",
"lookback_period_candles": 24,
"trade_limit": 4,
"stop_duration_candles": 2,
"only_per_pair": false
},
{
"method": "LowProfitPairs",
"lookback_period_candles": 6,
"trade_limit": 2,
"stop_duration_candles": 60,
"required_profit": 0.02
},
{
"method": "LowProfitPairs",
"lookback_period_candles": 24,
"trade_limit": 4,
"stop_duration_candles": 2,
"required_profit": 0.01
}
],
```
You can use the same in your strategy, the syntax is only slightly different:
``` python
from freqtrade.strategy import IStrategy

2
docs/index.md
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@ -76,7 +76,7 @@ Alternatively
For any questions not covered by the documentation or for further information about the bot, or to simply engage with like-minded individuals, we encourage you to join our slack channel.
Please check out our [discord server](https://discord.gg/MA9v74M).
Please check out our [discord server](https://discord.gg/p7nuUNVfP7).
You can also join our [Slack channel](https://join.slack.com/t/highfrequencybot/shared_invite/zt-mm786y93-Fxo37glxMY9g8OQC5AoOIw).

2
docs/installation.md
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@ -60,7 +60,7 @@ OS Specific steps are listed first, the [Common](#common) section below is neces
sudo apt-get update
# install packages
sudo apt install -y python3-pip python3-venv python3-pandas git
sudo apt install -y python3-pip python3-venv python3-dev python3-pandas git
```
=== "RaspberryPi/Raspbian"

68
docs/overrides/main.html Normal file
View File

@ -0,0 +1,68 @@
{% extends "base.html" %}
<!-- Navigation -->
{% block site_nav %}
<!-- Main navigation -->
{% if nav %}
{% if page and page.meta and page.meta.hide %}
{% set hidden = "hidden" if "navigation" in page.meta.hide %}
{% endif %}
<div class="md-sidebar md-sidebar--primary" data-md-component="sidebar" data-md-type="navigation" {{ hidden }}>
<div class="md-sidebar__scrollwrap">
<div id="widget-wrapper">
</div>
<div class="md-sidebar__inner">
{% include "partials/nav.html" %}
</div>
</div>
</div>
{% endif %}
<!-- Table of contents -->
{% if page.toc and not "toc.integrate" in features %}
{% if page and page.meta and page.meta.hide %}
{% set hidden = "hidden" if "toc" in page.meta.hide %}
{% endif %}
<div class="md-sidebar md-sidebar--secondary" data-md-component="sidebar" data-md-type="toc" {{ hidden }}>
<div class="md-sidebar__scrollwrap">
<div class="md-sidebar__inner">
{% include "partials/toc.html" %}
</div>
</div>
</div>
{% endif %}
{% endblock %}
{% block footer %}
{{ super() }}
<!-- Place this tag in your head or just before your close body tag. -->
<script async defer src="https://buttons.github.io/buttons.js"></script>
<script src="https://code.jquery.com/jquery-3.4.1.min.js"
integrity="sha256-CSXorXvZcTkaix6Yvo6HppcZGetbYMGWSFlBw8HfCJo=" crossorigin="anonymous"></script>
<!-- Load binance SDK -->
<script async defer src="https://public.bnbstatic.com/static/js/broker-sdk/broker-sdk@1.0.0.min.js"></script>
<script>
window.onload = function () {
var sidebar = document.getElementById('widget-wrapper')
var newDiv = document.createElement("div");
newDiv.id = "widget";
try {
sidebar.prepend(newDiv);
window.binanceBrokerPortalSdk.initBrokerSDK('#widget', {
apiHost: 'https://www.binance.com',
brokerId: 'R4BD3S82',
slideTime: 4e4,
});
} catch(err) {
console.log(err)
}
}
</script>
{% endblock %}

72
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@ -1,72 +0,0 @@
{#-
This file was automatically generated - do not edit
-#}
{% set site_url = config.site_url | d(nav.homepage.url, true) | url %}
{% if not config.use_directory_urls and site_url[0] == site_url[-1] == "." %}
{% set site_url = site_url ~ "/index.html" %}
{% endif %}
<header class="md-header" data-md-component="header">
<nav class="md-header__inner md-grid" aria-label="{{ lang.t('header.title') }}">
<a href="{{ site_url }}" title="{{ config.site_name | e }}" class="md-header__button md-logo"
aria-label="{{ config.site_name }}">
{% include "partials/logo.html" %}
</a>
<label class="md-header__button md-icon" for="__drawer">
{% include ".icons/material/menu" ~ ".svg" %}
</label>
<div class="md-header__title" data-md-component="header-title">
<div class="md-header__ellipsis">
<div class="md-header__topic">
<span class="md-ellipsis">
{{ config.site_name }}
</span>
</div>
<div class="md-header__topic" data-md-component="header-topic">
<span class="md-ellipsis">
{% if page and page.meta and page.meta.title %}
{{ page.meta.title }}
{% else %}
{{ page.title }}
{% endif %}
</span>
</div>
</div>
</div>
<div class="md-header__options">
{% if config.extra.alternate %}
<div class="md-select">
{% set icon = config.theme.icon.alternate or "material/translate" %}
<span class="md-header__button md-icon">
{% include ".icons/" ~ icon ~ ".svg" %}
</span>
<div class="md-select__inner">
<ul class="md-select__list">
{% for alt in config.extra.alternate %}
<li class="md-select__item">
<a href="{{ alt.link | url }}" class="md-select__link">
{{ alt.name }}
</a>
</li>
{% endfor %}
</ul>
</div>
</div>
{% endif %}
</div>
{% if "search" in config["plugins"] %}
<label class="md-header__button md-icon" for="__search">
{% include ".icons/material/magnify.svg" %}
</label>
{% include "partials/search.html" %}
{% endif %}
{% if config.repo_url %}
<div class="md-header__source">
{% include "partials/source.html" %}
</div>
{% endif %}
</nav>
<!-- Place this tag in your head or just before your close body tag. -->
<script async defer src="https://buttons.github.io/buttons.js"></script>
<script src="https://code.jquery.com/jquery-3.4.1.min.js"
integrity="sha256-CSXorXvZcTkaix6Yvo6HppcZGetbYMGWSFlBw8HfCJo=" crossorigin="anonymous"></script>
</header>

15
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@ -170,9 +170,15 @@ Additional features when using plot_config include:
* Specify additional subplots
* Specify indicator pairs to fill area in between
The sample plot configuration below specifies fixed colors for the indicators. Otherwise consecutive plots may produce different colorschemes each time, making comparisons difficult.
The sample plot configuration below specifies fixed colors for the indicators. Otherwise, consecutive plots may produce different color schemes each time, making comparisons difficult.
It also allows multiple subplots to display both MACD and RSI at the same time.
Plot type can be configured using `type` key. Possible types are:
* `scatter` corresponding to `plotly.graph_objects.Scatter` class (default).
* `bar` corresponding to `plotly.graph_objects.Bar` class.
Extra parameters to `plotly.graph_objects.*` constructor can be specified in `plotly` dict.
Sample configuration with inline comments explaining the process:
``` python
@ -198,7 +204,8 @@ Sample configuration with inline comments explaining the process:
# Create subplot MACD
"MACD": {
'macd': {'color': 'blue', 'fill_to': 'macdhist'},
'macdsignal': {'color': 'orange'}
'macdsignal': {'color': 'orange'},
'macdhist': {'type': 'bar', 'plotly': {'opacity': 0.9}}
},
# Additional subplot RSI
"RSI": {
@ -213,6 +220,9 @@ Sample configuration with inline comments explaining the process:
The above configuration assumes that `ema10`, `ema50`, `senkou_a`, `senkou_b`,
`macd`, `macdsignal`, `macdhist` and `rsi` are columns in the DataFrame created by the strategy.
!!! Warning
`plotly` arguments are only supported with plotly library and will not work with freq-ui.
## Plot profit
![plot-profit](assets/plot-profit.png)
@ -265,6 +275,7 @@ optional arguments:
(backtest file)) Default: file
-i TIMEFRAME, --timeframe TIMEFRAME, --ticker-interval TIMEFRAME
Specify timeframe (`1m`, `5m`, `30m`, `1h`, `1d`).
--auto-open Automatically open generated plot.
Common arguments:
-v, --verbose Verbose mode (-vv for more, -vvv to get all messages).

3
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@ -1,3 +1,4 @@
mkdocs-material==7.1.5
mkdocs==1.2.1
mkdocs-material==7.1.8
mdx_truly_sane_lists==1.2
pymdown-extensions==8.2

15
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@ -11,3 +11,18 @@
.rst-versions .rst-other-versions {
color: white;
}
#widget-wrapper {
height: calc(220px * 0.5625 + 18px);
width: 220px;
margin: 0 auto 16px auto;
border-style: solid;
border-color: var(--md-code-bg-color);
border-width: 1px;
border-radius: 5px;
}
@media screen and (max-width: calc(76.25em - 1px)) {
#widget-wrapper { display: none; }
}

45
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@ -72,22 +72,32 @@ Example configuration showing the different settings:
``` json
"telegram": {
"enabled": true,
"token": "your_telegram_token",
"chat_id": "your_telegram_chat_id",
"notification_settings": {
"status": "silent",
"warning": "on",
"startup": "off",
"buy": "silent",
"sell": "on",
"buy_cancel": "silent",
"sell_cancel": "on",
"buy_fill": "off",
"sell_fill": "off"
},
"balance_dust_level": 0.01
},
"enabled": true,
"token": "your_telegram_token",
"chat_id": "your_telegram_chat_id",
"notification_settings": {
"status": "silent",
"warning": "on",
"startup": "off",
"buy": "silent",
"sell": {
"roi": "silent",
"emergency_sell": "on",
"force_sell": "on",
"sell_signal": "silent",
"trailing_stop_loss": "on",
"stop_loss": "on",
"stoploss_on_exchange": "on",
"custom_sell": "silent"
},
"buy_cancel": "silent",
"sell_cancel": "on",
"buy_fill": "off",
"sell_fill": "off"
},
"reload": true,
"balance_dust_level": 0.01
},
```
`buy` notifications are sent when the order is placed, while `buy_fill` notifications are sent when the order is filled on the exchange.
@ -96,6 +106,7 @@ Example configuration showing the different settings:
`balance_dust_level` will define what the `/balance` command takes as "dust" - Currencies with a balance below this will be shown.
`reload` allows you to disable reload-buttons on selected messages.
## Create a custom keyboard (command shortcut buttons)
@ -154,7 +165,7 @@ official commands. You can ask at any moment for help with `/help`.
| `/count` | Displays number of trades used and available
| `/locks` | Show currently locked pairs.
| `/unlock <pair or lock_id>` | Remove the lock for this pair (or for this lock id).
| `/profit` | Display a summary of your profit/loss from close trades and some stats about your performance
| `/profit [<n>]` | Display a summary of your profit/loss from close trades and some stats about your performance, over the last n days (all trades by default)
| `/forcesell <trade_id>` | Instantly sells the given trade (Ignoring `minimum_roi`).
| `/forcesell all` | Instantly sells all open trades (Ignoring `minimum_roi`).
| `/forcebuy <pair> [rate]` | Instantly buys the given pair. Rate is optional. (`forcebuy_enable` must be set to True)

2
freqtrade/__init__.py
View File

@ -1,5 +1,5 @@
""" Freqtrade bot """
__version__ = '2021.5'
__version__ = '2021.6'
if __version__ == 'develop':

2
freqtrade/commands/arguments.py
View File

@ -69,7 +69,7 @@ ARGS_PLOT_DATAFRAME = ["pairs", "indicators1", "indicators2", "plot_limit",
"timerange", "timeframe", "no_trades"]
ARGS_PLOT_PROFIT = ["pairs", "timerange", "export", "exportfilename", "db_url",
"trade_source", "timeframe"]
"trade_source", "timeframe", "plot_auto_open"]
ARGS_INSTALL_UI = ["erase_ui_only"]

4
freqtrade/commands/build_config_commands.py
View File

@ -183,7 +183,7 @@ def deploy_new_config(config_path: Path, selections: Dict[str, Any]) -> None:
"""
Applies selections to the template and writes the result to config_path
:param config_path: Path object for new config file. Should not exist yet
:param selecions: Dict containing selections taken by the user.
:param selections: Dict containing selections taken by the user.
"""
from jinja2.exceptions import TemplateNotFound
try:
@ -213,7 +213,7 @@ def deploy_new_config(config_path: Path, selections: Dict[str, Any]) -> None:
def start_new_config(args: Dict[str, Any]) -> None:
"""
Create a new strategy from a template
Asking the user questions to fill out the templateaccordingly.
Asking the user questions to fill out the template accordingly.
"""
config_path = Path(args['config'][0])

10
freqtrade/commands/cli_options.py
View File

@ -167,8 +167,9 @@ AVAILABLE_CLI_OPTIONS = {
),
"export": Arg(
'--export',
help='Export backtest results, argument are: trades. '
'Example: `--export=trades`',
help='Export backtest results (default: trades).',
choices=constants.EXPORT_OPTIONS,
),
"exportfilename": Arg(
'--export-filename',
@ -433,6 +434,11 @@ AVAILABLE_CLI_OPTIONS = {
metavar='INT',
default=750,
),
"plot_auto_open": Arg(
'--auto-open',
help='Automatically open generated plot.',
action='store_true',
),
"no_trades": Arg(
'--no-trades',
help='Skip using trades from backtesting file and DB.',

2
freqtrade/commands/data_commands.py
View File

@ -8,11 +8,11 @@ from freqtrade.configuration import TimeRange, setup_utils_configuration
from freqtrade.data.converter import convert_ohlcv_format, convert_trades_format
from freqtrade.data.history import (convert_trades_to_ohlcv, refresh_backtest_ohlcv_data,
refresh_backtest_trades_data)
from freqtrade.enums import RunMode
from freqtrade.exceptions import OperationalException
from freqtrade.exchange import timeframe_to_minutes
from freqtrade.plugins.pairlist.pairlist_helpers import expand_pairlist
from freqtrade.resolvers import ExchangeResolver
from freqtrade.state import RunMode
logger = logging.getLogger(__name__)

2
freqtrade/commands/deploy_commands.py
View File

@ -8,9 +8,9 @@ import requests
from freqtrade.configuration import setup_utils_configuration
from freqtrade.configuration.directory_operations import copy_sample_files, create_userdata_dir
from freqtrade.constants import USERPATH_HYPEROPTS, USERPATH_STRATEGIES
from freqtrade.enums import RunMode
from freqtrade.exceptions import OperationalException
from freqtrade.misc import render_template, render_template_with_fallback
from freqtrade.state import RunMode
logger = logging.getLogger(__name__)

16
freqtrade/commands/hyperopt_commands.py
View File

@ -6,9 +6,9 @@ from colorama import init as colorama_init
from freqtrade.configuration import setup_utils_configuration
from freqtrade.data.btanalysis import get_latest_hyperopt_file
from freqtrade.enums import RunMode
from freqtrade.exceptions import OperationalException
from freqtrade.optimize.optimize_reports import show_backtest_result
from freqtrade.state import RunMode
logger = logging.getLogger(__name__)
@ -67,7 +67,7 @@ def start_hyperopt_list(args: Dict[str, Any]) -> None:
if epochs and not no_details:
sorted_epochs = sorted(epochs, key=itemgetter('loss'))
results = sorted_epochs[0]
HyperoptTools.print_epoch_details(results, total_epochs, print_json, no_header)
HyperoptTools.show_epoch_details(results, total_epochs, print_json, no_header)
if epochs and export_csv:
HyperoptTools.export_csv_file(
@ -132,8 +132,8 @@ def start_hyperopt_show(args: Dict[str, Any]) -> None:
show_backtest_result(metrics['strategy_name'], metrics,
metrics['stake_currency'])
HyperoptTools.print_epoch_details(val, total_epochs, print_json, no_header,
header_str="Epoch details")
HyperoptTools.show_epoch_details(val, total_epochs, print_json, no_header,
header_str="Epoch details")
def hyperopt_filter_epochs(epochs: List, filteroptions: dict) -> List:
@ -197,8 +197,12 @@ def _hyperopt_filter_epochs_duration(epochs: List, filteroptions: dict) -> List:
return x['results_metrics']['duration']
else:
# New mode
avg = x['results_metrics']['holding_avg']
return avg.total_seconds() // 60
if 'holding_avg_s' in x['results_metrics']:
avg = x['results_metrics']['holding_avg_s']
return avg // 60
raise OperationalException(
"Holding-average not available. Please omit the filter on average time, "
"or rerun hyperopt with this version")
if filteroptions['filter_min_avg_time'] is not None:
epochs = _hyperopt_filter_epochs_trade(epochs, 0)

22
freqtrade/commands/list_commands.py
View File

@ -1,7 +1,6 @@
import csv
import logging
import sys
from collections import OrderedDict
from pathlib import Path
from typing import Any, Dict, List
@ -12,11 +11,11 @@ from tabulate import tabulate
from freqtrade.configuration import setup_utils_configuration
from freqtrade.constants import USERPATH_HYPEROPTS, USERPATH_STRATEGIES
from freqtrade.enums import RunMode
from freqtrade.exceptions import OperationalException
from freqtrade.exchange import market_is_active, validate_exchanges
from freqtrade.misc import plural
from freqtrade.resolvers import ExchangeResolver, StrategyResolver
from freqtrade.state import RunMode
logger = logging.getLogger(__name__)
@ -54,15 +53,21 @@ def _print_objs_tabular(objs: List, print_colorized: bool) -> None:
reset = ''
names = [s['name'] for s in objs]
objss_to_print = [{
objs_to_print = [{
'name': s['name'] if s['name'] else "--",
'location': s['location'].name,
'status': (red + "LOAD FAILED" + reset if s['class'] is None
else "OK" if names.count(s['name']) == 1
else yellow + "DUPLICATE NAME" + reset)
} for s in objs]
print(tabulate(objss_to_print, headers='keys', tablefmt='psql', stralign='right'))
for idx, s in enumerate(objs):
if 'hyperoptable' in s:
objs_to_print[idx].update({
'hyperoptable': "Yes" if s['hyperoptable']['count'] > 0 else "No",
'buy-Params': len(s['hyperoptable'].get('buy', [])),
'sell-Params': len(s['hyperoptable'].get('sell', [])),
})
print(tabulate(objs_to_print, headers='keys', tablefmt='psql', stralign='right'))
def start_list_strategies(args: Dict[str, Any]) -> None:
@ -75,6 +80,11 @@ def start_list_strategies(args: Dict[str, Any]) -> None:
strategy_objs = StrategyResolver.search_all_objects(directory, not args['print_one_column'])
# Sort alphabetically
strategy_objs = sorted(strategy_objs, key=lambda x: x['name'])
for obj in strategy_objs:
if obj['class']:
obj['hyperoptable'] = obj['class'].detect_all_parameters()
else:
obj['hyperoptable'] = {'count': 0}
if args['print_one_column']:
print('\n'.join([s['name'] for s in strategy_objs]))
@ -143,7 +153,7 @@ def start_list_markets(args: Dict[str, Any], pairs_only: bool = False) -> None:
pairs_only=pairs_only,
active_only=active_only)
# Sort the pairs/markets by symbol
pairs = OrderedDict(sorted(pairs.items()))
pairs = dict(sorted(pairs.items()))
except Exception as e:
raise OperationalException(f"Cannot get markets. Reason: {e}") from e

3
freqtrade/commands/optimize_commands.py
View File

@ -3,9 +3,9 @@ from typing import Any, Dict
from freqtrade import constants
from freqtrade.configuration import setup_utils_configuration
from freqtrade.enums import RunMode
from freqtrade.exceptions import OperationalException
from freqtrade.misc import round_coin_value
from freqtrade.state import RunMode
logger = logging.getLogger(__name__)
@ -15,6 +15,7 @@ def setup_optimize_configuration(args: Dict[str, Any], method: RunMode) -> Dict[
"""
Prepare the configuration for the Hyperopt module
:param args: Cli args from Arguments()
:param method: Bot running mode
:return: Configuration
"""
config = setup_utils_configuration(args, method)

4
freqtrade/commands/pairlist_commands.py
View File

@ -4,8 +4,8 @@ from typing import Any, Dict
import rapidjson
from freqtrade.configuration import setup_utils_configuration
from freqtrade.enums import RunMode
from freqtrade.resolvers import ExchangeResolver
from freqtrade.state import RunMode
logger = logging.getLogger(__name__)
@ -31,7 +31,7 @@ def start_test_pairlist(args: Dict[str, Any]) -> None:
results[curr] = pairlists.whitelist
for curr, pairlist in results.items():
if not args.get('print_one_column', False):
if not args.get('print_one_column', False) and not args.get('list_pairs_print_json', False):
print(f"Pairs for {curr}: ")
if args.get('print_one_column', False):

2
freqtrade/commands/plot_commands.py
View File

@ -1,8 +1,8 @@
from typing import Any, Dict
from freqtrade.configuration import setup_utils_configuration
from freqtrade.enums import RunMode
from freqtrade.exceptions import OperationalException
from freqtrade.state import RunMode
def validate_plot_args(args: Dict[str, Any]) -> None:

2
freqtrade/configuration/check_exchange.py
View File

@ -1,10 +1,10 @@
import logging
from typing import Any, Dict
from freqtrade.enums import RunMode
from freqtrade.exceptions import OperationalException
from freqtrade.exchange import (available_exchanges, is_exchange_known_ccxt,
is_exchange_officially_supported, validate_exchange)
from freqtrade.state import RunMode
logger = logging.getLogger(__name__)

3
freqtrade/configuration/config_setup.py
View File

@ -1,7 +1,7 @@
import logging
from typing import Any, Dict
from freqtrade.state import RunMode
from freqtrade.enums import RunMode
from .check_exchange import remove_credentials
from .config_validation import validate_config_consistency
@ -15,6 +15,7 @@ def setup_utils_configuration(args: Dict[str, Any], method: RunMode) -> Dict[str
"""
Prepare the configuration for utils subcommands
:param args: Cli args from Arguments()
:param method: Bot running mode
:return: Configuration
"""
configuration = Configuration(args, method)

2
freqtrade/configuration/config_validation.py
View File

@ -6,8 +6,8 @@ from jsonschema import Draft4Validator, validators
from jsonschema.exceptions import ValidationError, best_match
from freqtrade import constants
from freqtrade.enums import RunMode
from freqtrade.exceptions import OperationalException
from freqtrade.state import RunMode
logger = logging.getLogger(__name__)

7
freqtrade/configuration/configuration.py
View File

@ -12,10 +12,10 @@ from freqtrade.configuration.check_exchange import check_exchange
from freqtrade.configuration.deprecated_settings import process_temporary_deprecated_settings
from freqtrade.configuration.directory_operations import create_datadir, create_userdata_dir
from freqtrade.configuration.load_config import load_config_file, load_file
from freqtrade.enums import NON_UTIL_MODES, TRADING_MODES, RunMode
from freqtrade.exceptions import OperationalException
from freqtrade.loggers import setup_logging
from freqtrade.misc import deep_merge_dicts
from freqtrade.state import NON_UTIL_MODES, TRADING_MODES, RunMode
logger = logging.getLogger(__name__)
@ -375,6 +375,9 @@ class Configuration:
self._args_to_config(config, argname='plot_limit',
logstring='Limiting plot to: {}')
self._args_to_config(config, argname='plot_auto_open',
logstring='Parameter --auto-open detected.')
self._args_to_config(config, argname='trade_source',
logstring='Using trades from: {}')
@ -457,7 +460,7 @@ class Configuration:
pairs_file = Path(self.args["pairs_file"])
logger.info(f'Reading pairs file "{pairs_file}".')
# Download pairs from the pairs file if no config is specified
# or if pairs file is specified explicitely
# or if pairs file is specified explicitly
if not pairs_file.exists():
raise OperationalException(f'No pairs file found with path "{pairs_file}".')
config['pairs'] = load_file(pairs_file)

2
freqtrade/configuration/load_config.py
View File

@ -43,7 +43,7 @@ def load_file(path: Path) -> Dict[str, Any]:
with path.open('r') as file:
config = rapidjson.load(file, parse_mode=CONFIG_PARSE_MODE)
except FileNotFoundError:
raise OperationalException(f'File file "{path}" not found!')
raise OperationalException(f'File "{path}" not found!')
return config

15
freqtrade/constants.py
View File

@ -12,6 +12,7 @@ PROCESS_THROTTLE_SECS = 5 # sec
HYPEROPT_EPOCH = 100 # epochs
RETRY_TIMEOUT = 30 # sec
TIMEOUT_UNITS = ['minutes', 'seconds']
EXPORT_OPTIONS = ['none', 'trades']
DEFAULT_DB_PROD_URL = 'sqlite:///tradesv3.sqlite'
DEFAULT_DB_DRYRUN_URL = 'sqlite:///tradesv3.dryrun.sqlite'
UNLIMITED_STAKE_AMOUNT = 'unlimited'
@ -61,7 +62,7 @@ DUST_PER_COIN = {
}
# Soure files with destination directories within user-directory
# Source files with destination directories within user-directory
USER_DATA_FILES = {
'sample_strategy.py': USERPATH_STRATEGIES,
'sample_hyperopt_advanced.py': USERPATH_HYPEROPTS,
@ -260,7 +261,13 @@ CONF_SCHEMA = {
'enum': TELEGRAM_SETTING_OPTIONS,
'default': 'off'
},
'sell': {'type': 'string', 'enum': TELEGRAM_SETTING_OPTIONS},
'sell': {
'type': ['string', 'object'],
'additionalProperties': {
'type': 'string',
'enum': TELEGRAM_SETTING_OPTIONS
}
},
'sell_cancel': {'type': 'string', 'enum': TELEGRAM_SETTING_OPTIONS},
'sell_fill': {
'type': 'string',
@ -268,7 +275,8 @@ CONF_SCHEMA = {
'default': 'off'
},
}
}
},
'reload': {'type': 'boolean'},
},
'required': ['enabled', 'token', 'chat_id'],
},
@ -302,6 +310,7 @@ CONF_SCHEMA = {
'required': ['enabled', 'listen_ip_address', 'listen_port', 'username', 'password']
},
'db_url': {'type': 'string'},
'export': {'type': 'string', 'enum': EXPORT_OPTIONS, 'default': 'trades'},
'initial_state': {'type': 'string', 'enum': ['running', 'stopped']},
'forcebuy_enable': {'type': 'boolean'},
'disable_dataframe_checks': {'type': 'boolean'},

2
freqtrade/data/converter.py
View File

@ -49,7 +49,7 @@ def clean_ohlcv_dataframe(data: DataFrame, timeframe: str, pair: str, *,
fill_missing: bool = True,
drop_incomplete: bool = True) -> DataFrame:
"""
Clense a OHLCV dataframe by
Cleanse a OHLCV dataframe by
* Grouping it by date (removes duplicate tics)
* dropping last candles if requested
* Filling up missing data (if requested)

2
freqtrade/data/dataprovider.py
View File

@ -12,9 +12,9 @@ from pandas import DataFrame
from freqtrade.constants import ListPairsWithTimeframes, PairWithTimeframe
from freqtrade.data.history import load_pair_history
from freqtrade.enums import RunMode
from freqtrade.exceptions import ExchangeError, OperationalException
from freqtrade.exchange import Exchange
from freqtrade.state import RunMode
logger = logging.getLogger(__name__)

4
freqtrade/data/history/hdf5datahandler.py
View File

@ -52,8 +52,8 @@ class HDF5DataHandler(IDataHandler):
"""
Store data in hdf5 file.
:param pair: Pair - used to generate filename
:timeframe: Timeframe - used to generate filename
:data: Dataframe containing OHLCV data
:param timeframe: Timeframe - used to generate filename
:param data: Dataframe containing OHLCV data
:return: None
"""
key = self._pair_ohlcv_key(pair, timeframe)

1
freqtrade/data/history/history_utils.py
View File

@ -113,6 +113,7 @@ def refresh_data(datadir: Path,
:param timeframe: Timeframe (e.g. "5m")
:param pairs: List of pairs to load
:param exchange: Exchange object
:param data_format: dataformat to use
:param timerange: Limit data to be loaded to this timerange
"""
data_handler = get_datahandler(datadir, data_format)

8
freqtrade/data/history/idatahandler.py
View File

@ -49,8 +49,8 @@ class IDataHandler(ABC):
"""
Store ohlcv data.
:param pair: Pair - used to generate filename
:timeframe: Timeframe - used to generate filename
:data: Dataframe containing OHLCV data
:param timeframe: Timeframe - used to generate filename
:param data: Dataframe containing OHLCV data
:return: None
"""
@ -245,8 +245,8 @@ def get_datahandler(datadir: Path, data_format: str = None,
data_handler: IDataHandler = None) -> IDataHandler:
"""
:param datadir: Folder to save data
:data_format: dataformat to use
:data_handler: returns this datahandler if it exists or initializes a new one
:param data_format: dataformat to use
:param data_handler: returns this datahandler if it exists or initializes a new one
"""
if not data_handler:

4
freqtrade/data/history/jsondatahandler.py
View File

@ -55,8 +55,8 @@ class JsonDataHandler(IDataHandler):
format looks as follows:
[[<date>,<open>,<high>,<low>,<close>]]
:param pair: Pair - used to generate filename
:timeframe: Timeframe - used to generate filename
:data: Dataframe containing OHLCV data
:param timeframe: Timeframe - used to generate filename
:param data: Dataframe containing OHLCV data
:return: None
"""
filename = self._pair_data_filename(self._datadir, pair, timeframe)

6
freqtrade/edge/edge_positioning.py
View File

@ -13,11 +13,11 @@ from pandas import DataFrame
from freqtrade.configuration import TimeRange
from freqtrade.constants import DATETIME_PRINT_FORMAT, UNLIMITED_STAKE_AMOUNT
from freqtrade.data.history import get_timerange, load_data, refresh_data
from freqtrade.enums import RunMode, SellType
from freqtrade.exceptions import OperationalException
from freqtrade.exchange.exchange import timeframe_to_seconds
from freqtrade.plugins.pairlist.pairlist_helpers import expand_pairlist
from freqtrade.state import RunMode
from freqtrade.strategy.interface import IStrategy, SellType
from freqtrade.strategy.interface import IStrategy
logger = logging.getLogger(__name__)
@ -301,7 +301,7 @@ class Edge:
def _process_expectancy(self, results: DataFrame) -> Dict[str, Any]:
"""
This calculates WinRate, Required Risk Reward, Risk Reward and Expectancy of all pairs
The calulation will be done per pair and per strategy.
The calculation will be done per pair and per strategy.
"""
# Removing pairs having less than min_trades_number
min_trades_number = self.edge_config.get('min_trade_number', 10)

6
freqtrade/enums/__init__.py Normal file
View File

@ -0,0 +1,6 @@
# flake8: noqa: F401
from freqtrade.enums.rpcmessagetype import RPCMessageType
from freqtrade.enums.runmode import NON_UTIL_MODES, OPTIMIZE_MODES, TRADING_MODES, RunMode
from freqtrade.enums.selltype import SellType
from freqtrade.enums.signaltype import SignalType
from freqtrade.enums.state import State

19
freqtrade/enums/rpcmessagetype.py Normal file
View File

@ -0,0 +1,19 @@
from enum import Enum
class RPCMessageType(Enum):
STATUS = 'status'
WARNING = 'warning'
STARTUP = 'startup'
BUY = 'buy'
BUY_FILL = 'buy_fill'
BUY_CANCEL = 'buy_cancel'
SELL = 'sell'
SELL_FILL = 'sell_fill'
SELL_CANCEL = 'sell_cancel'
def __repr__(self):
return self.value
def __str__(self):
return self.value

17
freqtrade/state.py → freqtrade/enums/runmode.py
View File

@ -1,23 +1,6 @@
# pragma pylint: disable=too-few-public-methods
"""
Bot state constant
"""
from enum import Enum
class State(Enum):
"""
Bot application states
"""
RUNNING = 1
STOPPED = 2
RELOAD_CONFIG = 3
def __str__(self):
return f"{self.name.lower()}"
class RunMode(Enum):
"""
Bot running mode (backtest, hyperopt, ...)

20
freqtrade/enums/selltype.py Normal file
View File

@ -0,0 +1,20 @@
from enum import Enum
class SellType(Enum):
"""
Enum to distinguish between sell reasons
"""
ROI = "roi"
STOP_LOSS = "stop_loss"
STOPLOSS_ON_EXCHANGE = "stoploss_on_exchange"
TRAILING_STOP_LOSS = "trailing_stop_loss"
SELL_SIGNAL = "sell_signal"
FORCE_SELL = "force_sell"
EMERGENCY_SELL = "emergency_sell"
CUSTOM_SELL = "custom_sell"
NONE = ""
def __str__(self):
# explicitly convert to String to help with exporting data.
return self.value

9
freqtrade/enums/signaltype.py Normal file
View File

@ -0,0 +1,9 @@
from enum import Enum
class SignalType(Enum):
"""
Enum to distinguish between buy and sell signals
"""
BUY = "buy"
SELL = "sell"

13
freqtrade/enums/state.py Normal file
View File

@ -0,0 +1,13 @@
from enum import Enum
class State(Enum):
"""
Bot application states
"""
RUNNING = 1
STOPPED = 2
RELOAD_CONFIG = 3
def __str__(self):
return f"{self.name.lower()}"

4
freqtrade/exceptions.py
View File

@ -47,7 +47,7 @@ class InvalidOrderException(ExchangeError):
class RetryableOrderError(InvalidOrderException):
"""
This is returned when the order is not found.
This Error will be repeated with increasing backof (in line with DDosError).
This Error will be repeated with increasing backoff (in line with DDosError).
"""
@ -75,6 +75,6 @@ class DDosProtection(TemporaryError):
class StrategyError(FreqtradeException):
"""
Errors with custom user-code deteced.
Errors with custom user-code detected.
Usually caused by errors in the strategy.
"""

1
freqtrade/exchange/binance.py
View File

@ -68,6 +68,7 @@ class Binance(Exchange):
amount=amount, price=rate, params=params)
logger.info('stoploss limit order added for %s. '
'stop price: %s. limit: %s', pair, stop_price, rate)
self._log_exchange_response('create_stoploss_order', order)
return order
except ccxt.InsufficientFunds as e:
raise InsufficientFundsError(

830
freqtrade/exchange/exchange.py
View File

@ -22,8 +22,8 @@ from pandas import DataFrame
from freqtrade.constants import DEFAULT_AMOUNT_RESERVE_PERCENT, ListPairsWithTimeframes
from freqtrade.data.converter import ohlcv_to_dataframe, trades_dict_to_list
from freqtrade.exceptions import (DDosProtection, ExchangeError, InsufficientFundsError,
InvalidOrderException, OperationalException, RetryableOrderError,
TemporaryError)
InvalidOrderException, OperationalException, PricingError,
RetryableOrderError, TemporaryError)
from freqtrade.exchange.common import (API_FETCH_ORDER_RETRY_COUNT, BAD_EXCHANGES,
EXCHANGE_HAS_OPTIONAL, EXCHANGE_HAS_REQUIRED, retrier,
retrier_async)
@ -88,6 +88,11 @@ class Exchange:
# Cache for 10 minutes ...
self._fetch_tickers_cache: TTLCache = TTLCache(maxsize=1, ttl=60 * 10)
# Cache values for 1800 to avoid frequent polling of the exchange for prices
# Caching only applies to RPC methods, so prices for open trades are still
# refreshed once every iteration.
self._sell_rate_cache: TTLCache = TTLCache(maxsize=100, ttl=1800)
self._buy_rate_cache: TTLCache = TTLCache(maxsize=100, ttl=1800)
# Holds candles
self._klines: Dict[Tuple[str, str], DataFrame] = {}
@ -99,6 +104,7 @@ class Exchange:
logger.info('Instance is running with dry_run enabled')
logger.info(f"Using CCXT {ccxt.__version__}")
exchange_config = config['exchange']
self.log_responses = exchange_config.get('log_responses', False)
# Deep merge ft_has with default ft_has options
self._ft_has = deep_merge_dicts(self._ft_has, deepcopy(self._ft_has_default))
@ -221,10 +227,15 @@ class Exchange:
"""exchange ccxt precisionMode"""
return self._api.precisionMode
def _log_exchange_response(self, endpoint, response) -> None:
""" Log exchange responses """
if self.log_responses:
logger.info(f"API {endpoint}: {response}")
def ohlcv_candle_limit(self, timeframe: str) -> int:
"""
Exchange ohlcv candle limit
Uses ohlcv_candle_limit_per_timeframe if the exchange has different limts
Uses ohlcv_candle_limit_per_timeframe if the exchange has different limits
per timeframe (e.g. bittrex), otherwise falls back to ohlcv_candle_limit
:param timeframe: Timeframe to check
:return: Candle limit as integer
@ -464,11 +475,11 @@ class Exchange:
return endpoint in self._api.has and self._api.has[endpoint]
def amount_to_precision(self, pair: str, amount: float) -> float:
'''
"""
Returns the amount to buy or sell to a precision the Exchange accepts
Re-implementation of ccxt internal methods - ensuring we can test the result is correct
based on our definitions.
'''
"""
if self.markets[pair]['precision']['amount']:
amount = float(decimal_to_precision(amount, rounding_mode=TRUNCATE,
precision=self.markets[pair]['precision']['amount'],
@ -478,14 +489,14 @@ class Exchange:
return amount
def price_to_precision(self, pair: str, price: float) -> float:
'''
"""
Returns the price rounded up to the precision the Exchange accepts.
Partial Re-implementation of ccxt internal method decimal_to_precision(),
which does not support rounding up
TODO: If ccxt supports ROUND_UP for decimal_to_precision(), we could remove this and
align with amount_to_precision().
Rounds up
'''
"""
if self.markets[pair]['precision']['price']:
# price = float(decimal_to_precision(price, rounding_mode=ROUND,
# precision=self.markets[pair]['precision']['price'],
@ -550,11 +561,13 @@ class Exchange:
# See also #2575 at github.
return max(min_stake_amounts) * amount_reserve_percent
# Dry-run methods
def create_dry_run_order(self, pair: str, ordertype: str, side: str, amount: float,
rate: float, params: Dict = {}) -> Dict[str, Any]:
order_id = f'dry_run_{side}_{datetime.now().timestamp()}'
_amount = self.amount_to_precision(pair, amount)
dry_order = {
dry_order: Dict[str, Any] = {
'id': order_id,
'symbol': pair,
'price': rate,
@ -570,26 +583,110 @@ class Exchange:
'fee': None,
'info': {}
}
self._store_dry_order(dry_order, pair)
if dry_order["type"] in ["stop_loss_limit", "stop-loss-limit"]:
dry_order["info"] = {"stopPrice": dry_order["price"]}
if dry_order["type"] == "market":
# Update market order pricing
average = self.get_dry_market_fill_price(pair, side, amount, rate)
dry_order.update({
'average': average,
'cost': dry_order['amount'] * average,
})
dry_order = self.add_dry_order_fee(pair, dry_order)
dry_order = self.check_dry_limit_order_filled(dry_order)
self._dry_run_open_orders[dry_order["id"]] = dry_order
# Copy order and close it - so the returned order is open unless it's a market order
return dry_order
def _store_dry_order(self, dry_order: Dict, pair: str) -> None:
closed_order = dry_order.copy()
if closed_order['type'] in ["market", "limit"]:
closed_order.update({
'status': 'closed',
'filled': closed_order['amount'],
'remaining': 0,
'fee': {
'currency': self.get_pair_quote_currency(pair),
'cost': dry_order['cost'] * self.get_fee(pair),
'rate': self.get_fee(pair)
}
})
if closed_order["type"] in ["stop_loss_limit", "stop-loss-limit"]:
closed_order["info"].update({"stopPrice": closed_order["price"]})
self._dry_run_open_orders[closed_order["id"]] = closed_order
def add_dry_order_fee(self, pair: str, dry_order: Dict[str, Any]) -> Dict[str, Any]:
dry_order.update({
'fee': {
'currency': self.get_pair_quote_currency(pair),
'cost': dry_order['cost'] * self.get_fee(pair),
'rate': self.get_fee(pair)
}
})
return dry_order
def get_dry_market_fill_price(self, pair: str, side: str, amount: float, rate: float) -> float:
"""
Get the market order fill price based on orderbook interpolation
"""
if self.exchange_has('fetchL2OrderBook'):
ob = self.fetch_l2_order_book(pair, 20)
ob_type = 'asks' if side == 'buy' else 'bids'
remaining_amount = amount
filled_amount = 0
for book_entry in ob[ob_type]:
book_entry_price = book_entry[0]
book_entry_coin_volume = book_entry[1]
if remaining_amount > 0:
if remaining_amount < book_entry_coin_volume:
filled_amount += remaining_amount * book_entry_price
else:
filled_amount += book_entry_coin_volume * book_entry_price
remaining_amount -= book_entry_coin_volume
else:
break
else:
# If remaining_amount wasn't consumed completely (break was not called)
filled_amount += remaining_amount * book_entry_price
forecast_avg_filled_price = filled_amount / amount
return self.price_to_precision(pair, forecast_avg_filled_price)
return rate
def _is_dry_limit_order_filled(self, pair: str, side: str, limit: float) -> bool:
if not self.exchange_has('fetchL2OrderBook'):
return True
ob = self.fetch_l2_order_book(pair, 1)
if side == 'buy':
price = ob['asks'][0][0]
logger.debug(f"{pair} checking dry buy-order: price={price}, limit={limit}")
if limit >= price:
return True
else:
price = ob['bids'][0][0]
logger.debug(f"{pair} checking dry sell-order: price={price}, limit={limit}")
if limit <= price:
return True
return False
def check_dry_limit_order_filled(self, order: Dict[str, Any]) -> Dict[str, Any]:
"""
Check dry-run limit order fill and update fee (if it filled).
"""
if order['status'] != "closed" and order['type'] in ["limit"]:
pair = order['symbol']
if self._is_dry_limit_order_filled(pair, order['side'], order['price']):
order.update({
'status': 'closed',
'filled': order['amount'],
'remaining': 0,
})
self.add_dry_order_fee(pair, order)
return order
def fetch_dry_run_order(self, order_id) -> Dict[str, Any]:
"""
Return dry-run order
Only call if running in dry-run mode.
"""
try:
order = self._dry_run_open_orders[order_id]
order = self.check_dry_limit_order_filled(order)
return order
except KeyError as e:
# Gracefully handle errors with dry-run orders.
raise InvalidOrderException(
f'Tried to get an invalid dry-run-order (id: {order_id}). Message: {e}') from e
# Order handling
def create_order(self, pair: str, ordertype: str, side: str, amount: float,
rate: float, params: Dict = {}) -> Dict:
@ -600,8 +697,10 @@ class Exchange:
or self._api.options.get("createMarketBuyOrderRequiresPrice", False))
rate_for_order = self.price_to_precision(pair, rate) if needs_price else None
return self._api.create_order(pair, ordertype, side,
amount, rate_for_order, params)
order = self._api.create_order(pair, ordertype, side,
amount, rate_for_order, params)
self._log_exchange_response('create_order', order)
return order
except ccxt.InsufficientFunds as e:
raise InsufficientFundsError(
@ -667,6 +766,134 @@ class Exchange:
raise OperationalException(f"stoploss is not implemented for {self.name}.")
@retrier(retries=API_FETCH_ORDER_RETRY_COUNT)
def fetch_order(self, order_id: str, pair: str) -> Dict:
if self._config['dry_run']:
return self.fetch_dry_run_order(order_id)
try:
order = self._api.fetch_order(order_id, pair)
self._log_exchange_response('fetch_order', order)
return order
except ccxt.OrderNotFound as e:
raise RetryableOrderError(
f'Order not found (pair: {pair} id: {order_id}). Message: {e}') from e
except ccxt.InvalidOrder as e:
raise InvalidOrderException(
f'Tried to get an invalid order (pair: {pair} id: {order_id}). Message: {e}') from e
except ccxt.DDoSProtection as e:
raise DDosProtection(e) from e
except (ccxt.NetworkError, ccxt.ExchangeError) as e:
raise TemporaryError(
f'Could not get order due to {e.__class__.__name__}. Message: {e}') from e
except ccxt.BaseError as e:
raise OperationalException(e) from e
# Assign method to fetch_stoploss_order to allow easy overriding in other classes
fetch_stoploss_order = fetch_order
def fetch_order_or_stoploss_order(self, order_id: str, pair: str,
stoploss_order: bool = False) -> Dict:
"""
Simple wrapper calling either fetch_order or fetch_stoploss_order depending on
the stoploss_order parameter
:param order_id: OrderId to fetch order
:param pair: Pair corresponding to order_id
:param stoploss_order: If true, uses fetch_stoploss_order, otherwise fetch_order.
"""
if stoploss_order:
return self.fetch_stoploss_order(order_id, pair)
return self.fetch_order(order_id, pair)
def check_order_canceled_empty(self, order: Dict) -> bool:
"""
Verify if an order has been cancelled without being partially filled
:param order: Order dict as returned from fetch_order()
:return: True if order has been cancelled without being filled, False otherwise.
"""
return (order.get('status') in ('closed', 'canceled', 'cancelled')
and order.get('filled') == 0.0)
@retrier
def cancel_order(self, order_id: str, pair: str) -> Dict:
if self._config['dry_run']:
try:
order = self.fetch_dry_run_order(order_id)
order.update({'status': 'canceled', 'filled': 0.0, 'remaining': order['amount']})
return order
except InvalidOrderException:
return {}
try:
order = self._api.cancel_order(order_id, pair)
self._log_exchange_response('cancel_order', order)
return order
except ccxt.InvalidOrder as e:
raise InvalidOrderException(
f'Could not cancel order. Message: {e}') from e
except ccxt.DDoSProtection as e:
raise DDosProtection(e) from e
except (ccxt.NetworkError, ccxt.ExchangeError) as e:
raise TemporaryError(
f'Could not cancel order due to {e.__class__.__name__}. Message: {e}') from e
except ccxt.BaseError as e:
raise OperationalException(e) from e
# Assign method to cancel_stoploss_order to allow easy overriding in other classes
cancel_stoploss_order = cancel_order
def is_cancel_order_result_suitable(self, corder) -> bool:
if not isinstance(corder, dict):
return False
required = ('fee', 'status', 'amount')
return all(k in corder for k in required)
def cancel_order_with_result(self, order_id: str, pair: str, amount: float) -> Dict:
"""
Cancel order returning a result.
Creates a fake result if cancel order returns a non-usable result
and fetch_order does not work (certain exchanges don't return cancelled orders)
:param order_id: Orderid to cancel
:param pair: Pair corresponding to order_id
:param amount: Amount to use for fake response
:return: Result from either cancel_order if usable, or fetch_order
"""
try:
corder = self.cancel_order(order_id, pair)
if self.is_cancel_order_result_suitable(corder):
return corder
except InvalidOrderException:
logger.warning(f"Could not cancel order {order_id} for {pair}.")
try:
order = self.fetch_order(order_id, pair)
except InvalidOrderException:
logger.warning(f"Could not fetch cancelled order {order_id}.")
order = {'fee': {}, 'status': 'canceled', 'amount': amount, 'info': {}}
return order
def cancel_stoploss_order_with_result(self, order_id: str, pair: str, amount: float) -> Dict:
"""
Cancel stoploss order returning a result.
Creates a fake result if cancel order returns a non-usable result
and fetch_order does not work (certain exchanges don't return cancelled orders)
:param order_id: stoploss-order-id to cancel
:param pair: Pair corresponding to order_id
:param amount: Amount to use for fake response
:return: Result from either cancel_order if usable, or fetch_order
"""
corder = self.cancel_stoploss_order(order_id, pair)
if self.is_cancel_order_result_suitable(corder):
return corder
try:
order = self.fetch_stoploss_order(order_id, pair)
except InvalidOrderException:
logger.warning(f"Could not fetch cancelled stoploss order {order_id}.")
order = {'fee': {}, 'status': 'canceled', 'amount': amount, 'info': {}}
return order
@retrier
def get_balances(self) -> dict:
@ -713,6 +940,8 @@ class Exchange:
except ccxt.BaseError as e:
raise OperationalException(e) from e
# Pricing info
@retrier
def fetch_ticker(self, pair: str) -> dict:
try:
@ -729,6 +958,265 @@ class Exchange:
except ccxt.BaseError as e:
raise OperationalException(e) from e
@staticmethod
def get_next_limit_in_list(limit: int, limit_range: Optional[List[int]],
range_required: bool = True):
"""
Get next greater value in the list.
Used by fetch_l2_order_book if the api only supports a limited range
"""
if not limit_range:
return limit
result = min([x for x in limit_range if limit <= x] + [max(limit_range)])
if not range_required and limit > result:
# Range is not required - we can use None as parameter.
return None
return result
@retrier
def fetch_l2_order_book(self, pair: str, limit: int = 100) -> dict:
"""
Get L2 order book from exchange.
Can be limited to a certain amount (if supported).
Returns a dict in the format
{'asks': [price, volume], 'bids': [price, volume]}
"""
limit1 = self.get_next_limit_in_list(limit, self._ft_has['l2_limit_range'],
self._ft_has['l2_limit_range_required'])
try:
return self._api.fetch_l2_order_book(pair, limit1)
except ccxt.NotSupported as e:
raise OperationalException(
f'Exchange {self._api.name} does not support fetching order book.'
f'Message: {e}') from e
except ccxt.DDoSProtection as e:
raise DDosProtection(e) from e
except (ccxt.NetworkError, ccxt.ExchangeError) as e:
raise TemporaryError(
f'Could not get order book due to {e.__class__.__name__}. Message: {e}') from e
except ccxt.BaseError as e:
raise OperationalException(e) from e
def _order_book_gen(self, pair: str, side: str, order_book_max: int = 1,
order_book_min: int = 1):
"""
Helper generator to query orderbook in loop (used for early sell-order placing)
"""
order_book = self.fetch_l2_order_book(pair, order_book_max)
for i in range(order_book_min, order_book_max + 1):
yield order_book[side][i - 1][0]
def get_buy_rate(self, pair: str, refresh: bool) -> float:
"""
Calculates bid target between current ask price and last price
:param pair: Pair to get rate for
:param refresh: allow cached data
:return: float: Price
:raises PricingError if orderbook price could not be determined.
"""
if not refresh:
rate = self._buy_rate_cache.get(pair)
# Check if cache has been invalidated
if rate:
logger.debug(f"Using cached buy rate for {pair}.")
return rate
bid_strategy = self._config.get('bid_strategy', {})
if 'use_order_book' in bid_strategy and bid_strategy.get('use_order_book', False):
order_book_top = bid_strategy.get('order_book_top', 1)
order_book = self.fetch_l2_order_book(pair, order_book_top)
logger.debug('order_book %s', order_book)
# top 1 = index 0
try:
rate_from_l2 = order_book[f"{bid_strategy['price_side']}s"][order_book_top - 1][0]
except (IndexError, KeyError) as e:
logger.warning(
"Buy Price from orderbook could not be determined."
f"Orderbook: {order_book}"
)
raise PricingError from e
logger.info(f"Buy price from orderbook {bid_strategy['price_side'].capitalize()} side "
f"- top {order_book_top} order book buy rate {rate_from_l2:.8f}")
used_rate = rate_from_l2
else:
logger.info(f"Using Last {bid_strategy['price_side'].capitalize()} / Last Price")
ticker = self.fetch_ticker(pair)
ticker_rate = ticker[bid_strategy['price_side']]
if ticker['last'] and ticker_rate > ticker['last']:
balance = bid_strategy['ask_last_balance']
ticker_rate = ticker_rate + balance * (ticker['last'] - ticker_rate)
used_rate = ticker_rate
self._buy_rate_cache[pair] = used_rate
return used_rate
def get_sell_rate(self, pair: str, refresh: bool) -> float:
"""
Get sell rate - either using ticker bid or first bid based on orderbook
or remain static in any other case since it's not updating.
:param pair: Pair to get rate for
:param refresh: allow cached data
:return: Bid rate
:raises PricingError if price could not be determined.
"""
if not refresh:
rate = self._sell_rate_cache.get(pair)
# Check if cache has been invalidated
if rate:
logger.debug(f"Using cached sell rate for {pair}.")
return rate
ask_strategy = self._config.get('ask_strategy', {})
if ask_strategy.get('use_order_book', False):
# This code is only used for notifications, selling uses the generator directly
logger.info(
f"Getting price from order book {ask_strategy['price_side'].capitalize()} side."
)
try:
rate = next(self._order_book_gen(pair, f"{ask_strategy['price_side']}s"))
except (IndexError, KeyError) as e:
logger.warning("Sell Price at location from orderbook could not be determined.")
raise PricingError from e
else:
ticker = self.fetch_ticker(pair)
ticker_rate = ticker[ask_strategy['price_side']]
if ticker['last'] and ticker_rate < ticker['last']:
balance = ask_strategy.get('bid_last_balance', 0.0)
ticker_rate = ticker_rate - balance * (ticker_rate - ticker['last'])
rate = ticker_rate
if rate is None:
raise PricingError(f"Sell-Rate for {pair} was empty.")
self._sell_rate_cache[pair] = rate
return rate
# Fee handling
@retrier
def get_trades_for_order(self, order_id: str, pair: str, since: datetime) -> List:
"""
Fetch Orders using the "fetch_my_trades" endpoint and filter them by order-id.
The "since" argument passed in is coming from the database and is in UTC,
as timezone-native datetime object.
From the python documentation:
> Naive datetime instances are assumed to represent local time
Therefore, calling "since.timestamp()" will get the UTC timestamp, after applying the
transformation from local timezone to UTC.
This works for timezones UTC+ since then the result will contain trades from a few hours
instead of from the last 5 seconds, however fails for UTC- timezones,
since we're then asking for trades with a "since" argument in the future.
:param order_id order_id: Order-id as given when creating the order
:param pair: Pair the order is for
:param since: datetime object of the order creation time. Assumes object is in UTC.
"""
if self._config['dry_run']:
return []
if not self.exchange_has('fetchMyTrades'):
return []
try:
# Allow 5s offset to catch slight time offsets (discovered in #1185)
# since needs to be int in milliseconds
my_trades = self._api.fetch_my_trades(
pair, int((since.replace(tzinfo=timezone.utc).timestamp() - 5) * 1000))
matched_trades = [trade for trade in my_trades if trade['order'] == order_id]
self._log_exchange_response('get_trades_for_order', matched_trades)
return matched_trades
except ccxt.DDoSProtection as e:
raise DDosProtection(e) from e
except (ccxt.NetworkError, ccxt.ExchangeError) as e:
raise TemporaryError(
f'Could not get trades due to {e.__class__.__name__}. Message: {e}') from e
except ccxt.BaseError as e:
raise OperationalException(e) from e
def get_order_id_conditional(self, order: Dict[str, Any]) -> str:
return order['id']
@retrier
def get_fee(self, symbol: str, type: str = '', side: str = '', amount: float = 1,
price: float = 1, taker_or_maker: str = 'maker') -> float:
try:
if self._config['dry_run'] and self._config.get('fee', None) is not None:
return self._config['fee']
# validate that markets are loaded before trying to get fee
if self._api.markets is None or len(self._api.markets) == 0:
self._api.load_markets()
return self._api.calculate_fee(symbol=symbol, type=type, side=side, amount=amount,
price=price, takerOrMaker=taker_or_maker)['rate']
except ccxt.DDoSProtection as e:
raise DDosProtection(e) from e
except (ccxt.NetworkError, ccxt.ExchangeError) as e:
raise TemporaryError(
f'Could not get fee info due to {e.__class__.__name__}. Message: {e}') from e
except ccxt.BaseError as e:
raise OperationalException(e) from e
@staticmethod
def order_has_fee(order: Dict) -> bool:
"""
Verifies if the passed in order dict has the needed keys to extract fees,
and that these keys (currency, cost) are not empty.
:param order: Order or trade (one trade) dict
:return: True if the fee substructure contains currency and cost, false otherwise
"""
if not isinstance(order, dict):
return False
return ('fee' in order and order['fee'] is not None
and (order['fee'].keys() >= {'currency', 'cost'})
and order['fee']['currency'] is not None
and order['fee']['cost'] is not None
)
def calculate_fee_rate(self, order: Dict) -> Optional[float]:
"""
Calculate fee rate if it's not given by the exchange.
:param order: Order or trade (one trade) dict
"""
if order['fee'].get('rate') is not None:
return order['fee'].get('rate')
fee_curr = order['fee']['currency']
# Calculate fee based on order details
if fee_curr in self.get_pair_base_currency(order['symbol']):
# Base currency - divide by amount
return round(
order['fee']['cost'] / safe_value_fallback2(order, order, 'filled', 'amount'), 8)
elif fee_curr in self.get_pair_quote_currency(order['symbol']):
# Quote currency - divide by cost
return round(order['fee']['cost'] / order['cost'], 8) if order['cost'] else None
else:
# If Fee currency is a different currency
if not order['cost']:
# If cost is None or 0.0 -> falsy, return None
return None
try:
comb = self.get_valid_pair_combination(fee_curr, self._config['stake_currency'])
tick = self.fetch_ticker(comb)
fee_to_quote_rate = safe_value_fallback2(tick, tick, 'last', 'ask')
return round((order['fee']['cost'] * fee_to_quote_rate) / order['cost'], 8)
except ExchangeError:
return None
def extract_cost_curr_rate(self, order: Dict) -> Tuple[float, str, Optional[float]]:
"""
Extract tuple of cost, currency, rate.
Requires order_has_fee to run first!
:param order: Order or trade (one trade) dict
:return: Tuple with cost, currency, rate of the given fee dict
"""
return (order['fee']['cost'],
order['fee']['currency'],
self.calculate_fee_rate(order))
# Historic data
def get_historic_ohlcv(self, pair: str, timeframe: str,
since_ms: int) -> List:
"""
@ -896,6 +1384,8 @@ class Exchange:
raise OperationalException(f'Could not fetch historical candle (OHLCV) data '
f'for pair {pair}. Message: {e}') from e
# Fetch historic trades
@retrier_async
async def _async_fetch_trades(self, pair: str,
since: Optional[int] = None,
@ -1054,292 +1544,6 @@ class Exchange:
self._async_get_trade_history(pair=pair, since=since,
until=until, from_id=from_id))
def check_order_canceled_empty(self, order: Dict) -> bool:
"""
Verify if an order has been cancelled without being partially filled
:param order: Order dict as returned from fetch_order()
:return: True if order has been cancelled without being filled, False otherwise.
"""
return (order.get('status') in ('closed', 'canceled', 'cancelled')
and order.get('filled') == 0.0)
@retrier
def cancel_order(self, order_id: str, pair: str) -> Dict:
if self._config['dry_run']:
order = self._dry_run_open_orders.get(order_id)
if order:
order.update({'status': 'canceled', 'filled': 0.0, 'remaining': order['amount']})
return order
else:
return {}
try:
return self._api.cancel_order(order_id, pair)
except ccxt.InvalidOrder as e:
raise InvalidOrderException(
f'Could not cancel order. Message: {e}') from e
except ccxt.DDoSProtection as e:
raise DDosProtection(e) from e
except (ccxt.NetworkError, ccxt.ExchangeError) as e:
raise TemporaryError(
f'Could not cancel order due to {e.__class__.__name__}. Message: {e}') from e
except ccxt.BaseError as e:
raise OperationalException(e) from e
# Assign method to cancel_stoploss_order to allow easy overriding in other classes
cancel_stoploss_order = cancel_order
def is_cancel_order_result_suitable(self, corder) -> bool:
if not isinstance(corder, dict):
return False
required = ('fee', 'status', 'amount')
return all(k in corder for k in required)
def cancel_order_with_result(self, order_id: str, pair: str, amount: float) -> Dict:
"""
Cancel order returning a result.
Creates a fake result if cancel order returns a non-usable result
and fetch_order does not work (certain exchanges don't return cancelled orders)
:param order_id: Orderid to cancel
:param pair: Pair corresponding to order_id
:param amount: Amount to use for fake response
:return: Result from either cancel_order if usable, or fetch_order
"""
try:
corder = self.cancel_order(order_id, pair)
if self.is_cancel_order_result_suitable(corder):
return corder
except InvalidOrderException:
logger.warning(f"Could not cancel order {order_id} for {pair}.")
try:
order = self.fetch_order(order_id, pair)
except InvalidOrderException:
logger.warning(f"Could not fetch cancelled order {order_id}.")
order = {'fee': {}, 'status': 'canceled', 'amount': amount, 'info': {}}
return order
def cancel_stoploss_order_with_result(self, order_id: str, pair: str, amount: float) -> Dict:
"""
Cancel stoploss order returning a result.
Creates a fake result if cancel order returns a non-usable result
and fetch_order does not work (certain exchanges don't return cancelled orders)
:param order_id: stoploss-order-id to cancel
:param pair: Pair corresponding to order_id
:param amount: Amount to use for fake response
:return: Result from either cancel_order if usable, or fetch_order
"""
corder = self.cancel_stoploss_order(order_id, pair)
if self.is_cancel_order_result_suitable(corder):
return corder
try:
order = self.fetch_stoploss_order(order_id, pair)
except InvalidOrderException:
logger.warning(f"Could not fetch cancelled stoploss order {order_id}.")
order = {'fee': {}, 'status': 'canceled', 'amount': amount, 'info': {}}
return order
@retrier(retries=API_FETCH_ORDER_RETRY_COUNT)
def fetch_order(self, order_id: str, pair: str) -> Dict:
if self._config['dry_run']:
try:
order = self._dry_run_open_orders[order_id]
return order
except KeyError as e:
# Gracefully handle errors with dry-run orders.
raise InvalidOrderException(
f'Tried to get an invalid dry-run-order (id: {order_id}). Message: {e}') from e
try:
return self._api.fetch_order(order_id, pair)
except ccxt.OrderNotFound as e:
raise RetryableOrderError(
f'Order not found (pair: {pair} id: {order_id}). Message: {e}') from e
except ccxt.InvalidOrder as e:
raise InvalidOrderException(
f'Tried to get an invalid order (pair: {pair} id: {order_id}). Message: {e}') from e
except ccxt.DDoSProtection as e:
raise DDosProtection(e) from e
except (ccxt.NetworkError, ccxt.ExchangeError) as e:
raise TemporaryError(
f'Could not get order due to {e.__class__.__name__}. Message: {e}') from e
except ccxt.BaseError as e:
raise OperationalException(e) from e
# Assign method to fetch_stoploss_order to allow easy overriding in other classes
fetch_stoploss_order = fetch_order
def fetch_order_or_stoploss_order(self, order_id: str, pair: str,
stoploss_order: bool = False) -> Dict:
"""
Simple wrapper calling either fetch_order or fetch_stoploss_order depending on
the stoploss_order parameter
:param stoploss_order: If true, uses fetch_stoploss_order, otherwise fetch_order.
"""
if stoploss_order:
return self.fetch_stoploss_order(order_id, pair)
return self.fetch_order(order_id, pair)
@staticmethod
def get_next_limit_in_list(limit: int, limit_range: Optional[List[int]],
range_required: bool = True):
"""
Get next greater value in the list.
Used by fetch_l2_order_book if the api only supports a limited range
"""
if not limit_range:
return limit
result = min([x for x in limit_range if limit <= x] + [max(limit_range)])
if not range_required and limit > result:
# Range is not required - we can use None as parameter.
return None
return result
@retrier
def fetch_l2_order_book(self, pair: str, limit: int = 100) -> dict:
"""
Get L2 order book from exchange.
Can be limited to a certain amount (if supported).
Returns a dict in the format
{'asks': [price, volume], 'bids': [price, volume]}
"""
limit1 = self.get_next_limit_in_list(limit, self._ft_has['l2_limit_range'],
self._ft_has['l2_limit_range_required'])
try:
return self._api.fetch_l2_order_book(pair, limit1)
except ccxt.NotSupported as e:
raise OperationalException(
f'Exchange {self._api.name} does not support fetching order book.'
f'Message: {e}') from e
except ccxt.DDoSProtection as e:
raise DDosProtection(e) from e
except (ccxt.NetworkError, ccxt.ExchangeError) as e:
raise TemporaryError(
f'Could not get order book due to {e.__class__.__name__}. Message: {e}') from e
except ccxt.BaseError as e:
raise OperationalException(e) from e
@retrier
def get_trades_for_order(self, order_id: str, pair: str, since: datetime) -> List:
"""
Fetch Orders using the "fetch_my_trades" endpoint and filter them by order-id.
The "since" argument passed in is coming from the database and is in UTC,
as timezone-native datetime object.
From the python documentation:
> Naive datetime instances are assumed to represent local time
Therefore, calling "since.timestamp()" will get the UTC timestamp, after applying the
transformation from local timezone to UTC.
This works for timezones UTC+ since then the result will contain trades from a few hours
instead of from the last 5 seconds, however fails for UTC- timezones,
since we're then asking for trades with a "since" argument in the future.
:param order_id order_id: Order-id as given when creating the order
:param pair: Pair the order is for
:param since: datetime object of the order creation time. Assumes object is in UTC.
"""
if self._config['dry_run']:
return []
if not self.exchange_has('fetchMyTrades'):
return []
try:
# Allow 5s offset to catch slight time offsets (discovered in #1185)
# since needs to be int in milliseconds
my_trades = self._api.fetch_my_trades(
pair, int((since.replace(tzinfo=timezone.utc).timestamp() - 5) * 1000))
matched_trades = [trade for trade in my_trades if trade['order'] == order_id]
return matched_trades
except ccxt.DDoSProtection as e:
raise DDosProtection(e) from e
except (ccxt.NetworkError, ccxt.ExchangeError) as e:
raise TemporaryError(
f'Could not get trades due to {e.__class__.__name__}. Message: {e}') from e
except ccxt.BaseError as e:
raise OperationalException(e) from e
def get_order_id_conditional(self, order: Dict[str, Any]) -> str:
return order['id']
@retrier
def get_fee(self, symbol: str, type: str = '', side: str = '', amount: float = 1,
price: float = 1, taker_or_maker: str = 'maker') -> float:
try:
if self._config['dry_run'] and self._config.get('fee', None) is not None:
return self._config['fee']
# validate that markets are loaded before trying to get fee
if self._api.markets is None or len(self._api.markets) == 0:
self._api.load_markets()
return self._api.calculate_fee(symbol=symbol, type=type, side=side, amount=amount,
price=price, takerOrMaker=taker_or_maker)['rate']
except ccxt.DDoSProtection as e:
raise DDosProtection(e) from e
except (ccxt.NetworkError, ccxt.ExchangeError) as e:
raise TemporaryError(
f'Could not get fee info due to {e.__class__.__name__}. Message: {e}') from e
except ccxt.BaseError as e:
raise OperationalException(e) from e
@staticmethod
def order_has_fee(order: Dict) -> bool:
"""
Verifies if the passed in order dict has the needed keys to extract fees,
and that these keys (currency, cost) are not empty.
:param order: Order or trade (one trade) dict
:return: True if the fee substructure contains currency and cost, false otherwise
"""
if not isinstance(order, dict):
return False
return ('fee' in order and order['fee'] is not None
and (order['fee'].keys() >= {'currency', 'cost'})
and order['fee']['currency'] is not None
and order['fee']['cost'] is not None
)
def calculate_fee_rate(self, order: Dict) -> Optional[float]:
"""
Calculate fee rate if it's not given by the exchange.
:param order: Order or trade (one trade) dict
"""
if order['fee'].get('rate') is not None:
return order['fee'].get('rate')
fee_curr = order['fee']['currency']
# Calculate fee based on order details
if fee_curr in self.get_pair_base_currency(order['symbol']):
# Base currency - divide by amount
return round(
order['fee']['cost'] / safe_value_fallback2(order, order, 'filled', 'amount'), 8)
elif fee_curr in self.get_pair_quote_currency(order['symbol']):
# Quote currency - divide by cost
return round(order['fee']['cost'] / order['cost'], 8) if order['cost'] else None
else:
# If Fee currency is a different currency
if not order['cost']:
# If cost is None or 0.0 -> falsy, return None
return None
try:
comb = self.get_valid_pair_combination(fee_curr, self._config['stake_currency'])
tick = self.fetch_ticker(comb)
fee_to_quote_rate = safe_value_fallback2(tick, tick, 'last', 'ask')
return round((order['fee']['cost'] * fee_to_quote_rate) / order['cost'], 8)
except ExchangeError:
return None
def extract_cost_curr_rate(self, order: Dict) -> Tuple[float, str, Optional[float]]:
"""
Extract tuple of cost, currency, rate.
Requires order_has_fee to run first!
:param order: Order or trade (one trade) dict
:return: Tuple with cost, currency, rate of the given fee dict
"""
return (order['fee']['cost'],
order['fee']['currency'],
self.calculate_fee_rate(order))
def is_exchange_known_ccxt(exchange_name: str, ccxt_module: CcxtModuleType = None) -> bool:
return exchange_name in ccxt_exchanges(ccxt_module)

29
freqtrade/exchange/ftx.py
View File

@ -69,6 +69,7 @@ class Ftx(Exchange):
order = self._api.create_order(symbol=pair, type=ordertype, side='sell',
amount=amount, params=params)
self._log_exchange_response('create_stoploss_order', order)
logger.info('stoploss order added for %s. '
'stop price: %s.', pair, stop_price)
return order
@ -93,18 +94,26 @@ class Ftx(Exchange):
@retrier(retries=API_FETCH_ORDER_RETRY_COUNT)
def fetch_stoploss_order(self, order_id: str, pair: str) -> Dict:
if self._config['dry_run']:
try:
order = self._dry_run_open_orders[order_id]
return order
except KeyError as e:
# Gracefully handle errors with dry-run orders.
raise InvalidOrderException(
f'Tried to get an invalid dry-run-order (id: {order_id}). Message: {e}') from e
return self.fetch_dry_run_order(order_id)
try:
orders = self._api.fetch_orders(pair, None, params={'type': 'stop'})
order = [order for order in orders if order['id'] == order_id]
self._log_exchange_response('fetch_stoploss_order', order)
if len(order) == 1:
if order[0].get('status') == 'closed':
# Trigger order was triggered ...
real_order_id = order[0].get('info', {}).get('orderId')
order1 = self._api.fetch_order(real_order_id, pair)
self._log_exchange_response('fetch_stoploss_order1', order1)
# Fake type to stop - as this was really a stop order.
order1['id_stop'] = order1['id']
order1['id'] = order_id
order1['type'] = 'stop'
order1['status_stop'] = 'triggered'
return order1
return order[0]
else:
raise InvalidOrderException(f"Could not get stoploss order for id {order_id}")
@ -125,7 +134,9 @@ class Ftx(Exchange):
if self._config['dry_run']:
return {}
try:
return self._api.cancel_order(order_id, pair, params={'type': 'stop'})
order = self._api.cancel_order(order_id, pair, params={'type': 'stop'})
self._log_exchange_response('cancel_stoploss_order', order)
return order
except ccxt.InvalidOrder as e:
raise InvalidOrderException(
f'Could not cancel order. Message: {e}') from e
@ -139,5 +150,5 @@ class Ftx(Exchange):
def get_order_id_conditional(self, order: Dict[str, Any]) -> str:
if order['type'] == 'stop':
return safe_value_fallback2(order['info'], order, 'orderId', 'id')
return safe_value_fallback2(order, order, 'id_stop', 'id')
return order['id']

3
freqtrade/exchange/kraken.py
View File

@ -49,7 +49,7 @@ class Kraken(Exchange):
orders = self._api.fetch_open_orders()
order_list = [(x["symbol"].split("/")[0 if x["side"] == "sell" else 1],
x["remaining"] if x["side"] == "sell" else x["remaining"] * x["price"],
# Don't remove the below comment, this can be important for debuggung
# Don't remove the below comment, this can be important for debugging
# x["side"], x["amount"],
) for x in orders]
for bal in balances:
@ -103,6 +103,7 @@ class Kraken(Exchange):
order = self._api.create_order(symbol=pair, type=ordertype, side='sell',
amount=amount, price=stop_price, params=params)
self._log_exchange_response('create_stoploss_order', order)
logger.info('stoploss order added for %s. '
'stop price: %s.', pair, stop_price)
return order

169
freqtrade/freqtradebot.py
View File

@ -10,13 +10,13 @@ from threading import Lock
from typing import Any, Dict, List, Optional
import arrow
from cachetools import TTLCache
from freqtrade import __version__, constants
from freqtrade.configuration import validate_config_consistency
from freqtrade.data.converter import order_book_to_dataframe
from freqtrade.data.dataprovider import DataProvider
from freqtrade.edge import Edge
from freqtrade.enums import RPCMessageType, SellType, State
from freqtrade.exceptions import (DependencyException, ExchangeError, InsufficientFundsError,
InvalidOrderException, PricingError)
from freqtrade.exchange import timeframe_to_minutes, timeframe_to_seconds
@ -26,9 +26,8 @@ from freqtrade.persistence import Order, PairLocks, Trade, cleanup_db, init_db
from freqtrade.plugins.pairlistmanager import PairListManager
from freqtrade.plugins.protectionmanager import ProtectionManager
from freqtrade.resolvers import ExchangeResolver, StrategyResolver
from freqtrade.rpc import RPCManager, RPCMessageType
from freqtrade.state import State
from freqtrade.strategy.interface import IStrategy, SellCheckTuple, SellType
from freqtrade.rpc import RPCManager
from freqtrade.strategy.interface import IStrategy, SellCheckTuple
from freqtrade.strategy.strategy_wrapper import strategy_safe_wrapper
from freqtrade.wallets import Wallets
@ -48,6 +47,7 @@ class FreqtradeBot(LoggingMixin):
:param config: configuration dict, you can use Configuration.get_config()
to get the config dict.
"""
self.active_pair_whitelist: List[str] = []
logger.info('Starting freqtrade %s', __version__)
@ -57,12 +57,6 @@ class FreqtradeBot(LoggingMixin):
# Init objects
self.config = config
# Cache values for 1800 to avoid frequent polling of the exchange for prices
# Caching only applies to RPC methods, so prices for open trades are still
# refreshed once every iteration.
self._sell_rate_cache: TTLCache = TTLCache(maxsize=100, ttl=1800)
self._buy_rate_cache: TTLCache = TTLCache(maxsize=100, ttl=1800)
self.strategy: IStrategy = StrategyResolver.load_strategy(self.config)
# Check config consistency here since strategies can set certain options
@ -76,12 +70,19 @@ class FreqtradeBot(LoggingMixin):
PairLocks.timeframe = self.config['timeframe']
self.protections = ProtectionManager(self.config, self.strategy.protections)
# RPC runs in separate threads, can start handling external commands just after
# initialization, even before Freqtradebot has a chance to start its throttling,
# so anything in the Freqtradebot instance should be ready (initialized), including
# the initial state of the bot.
# Keep this at the end of this initialization method.
self.rpc: RPCManager = RPCManager(self)
self.pairlists = PairListManager(self.exchange, self.config)
self.dataprovider = DataProvider(self.config, self.exchange, self.pairlists)
self.protections = ProtectionManager(self.config)
# Attach Dataprovider to Strategy baseclass
IStrategy.dp = self.dataprovider
# Attach Wallets to Strategy baseclass
@ -97,13 +98,7 @@ class FreqtradeBot(LoggingMixin):
initial_state = self.config.get('initial_state')
self.state = State[initial_state.upper()] if initial_state else State.STOPPED
# RPC runs in separate threads, can start handling external commands just after
# initialization, even before Freqtradebot has a chance to start its throttling,
# so anything in the Freqtradebot instance should be ready (initialized), including
# the initial state of the bot.
# Keep this at the end of this initialization method.
self.rpc: RPCManager = RPCManager(self)
# Protect sell-logic from forcesell and viceversa
# Protect sell-logic from forcesell and vice versa
self._sell_lock = Lock()
LoggingMixin.__init__(self, logger, timeframe_to_seconds(self.strategy.timeframe))
@ -187,7 +182,7 @@ class FreqtradeBot(LoggingMixin):
if self.get_free_open_trades():
self.enter_positions()
Trade.query.session.flush()
Trade.commit()
def process_stopped(self) -> None:
"""
@ -342,7 +337,7 @@ class FreqtradeBot(LoggingMixin):
# Assume this as the open order
trade.open_order_id = order.order_id
if fo:
logger.info(f"Found {order} for trade {trade}.jj")
logger.info(f"Found {order} for trade {trade}.")
self.update_trade_state(trade, order.order_id, fo,
stoploss_order=order.ft_order_side == 'stoploss')
@ -394,51 +389,6 @@ class FreqtradeBot(LoggingMixin):
return trades_created
def get_buy_rate(self, pair: str, refresh: bool) -> float:
"""
Calculates bid target between current ask price and last price
:param pair: Pair to get rate for
:param refresh: allow cached data
:return: float: Price
"""
if not refresh:
rate = self._buy_rate_cache.get(pair)
# Check if cache has been invalidated
if rate:
logger.debug(f"Using cached buy rate for {pair}.")
return rate
bid_strategy = self.config.get('bid_strategy', {})
if 'use_order_book' in bid_strategy and bid_strategy.get('use_order_book', False):
order_book_top = bid_strategy.get('order_book_top', 1)
order_book = self.exchange.fetch_l2_order_book(pair, order_book_top)
logger.debug('order_book %s', order_book)
# top 1 = index 0
try:
rate_from_l2 = order_book[f"{bid_strategy['price_side']}s"][order_book_top - 1][0]
except (IndexError, KeyError) as e:
logger.warning(
"Buy Price from orderbook could not be determined."
f"Orderbook: {order_book}"
)
raise PricingError from e
logger.info(f"Buy price from orderbook {bid_strategy['price_side'].capitalize()} side "
f"- top {order_book_top} order book buy rate {rate_from_l2:.8f}")
used_rate = rate_from_l2
else:
logger.info(f"Using Last {bid_strategy['price_side'].capitalize()} / Last Price")
ticker = self.exchange.fetch_ticker(pair)
ticker_rate = ticker[bid_strategy['price_side']]
if ticker['last'] and ticker_rate > ticker['last']:
balance = bid_strategy['ask_last_balance']
ticker_rate = ticker_rate + balance * (ticker['last'] - ticker_rate)
used_rate = ticker_rate
self._buy_rate_cache[pair] = used_rate
return used_rate
def create_trade(self, pair: str) -> bool:
"""
Check the implemented trading strategy for buy signals.
@ -522,6 +472,7 @@ class FreqtradeBot(LoggingMixin):
"""
Executes a limit buy for the given pair
:param pair: pair for which we want to create a LIMIT_BUY
:param stake_amount: amount of stake-currency for the pair
:return: True if a buy order is created, false if it fails.
"""
time_in_force = self.strategy.order_time_in_force['buy']
@ -530,7 +481,7 @@ class FreqtradeBot(LoggingMixin):
buy_limit_requested = price
else:
# Calculate price
buy_limit_requested = self.get_buy_rate(pair, True)
buy_limit_requested = self.exchange.get_buy_rate(pair, True)
if not buy_limit_requested:
raise PricingError('Could not determine buy price.')
@ -620,7 +571,7 @@ class FreqtradeBot(LoggingMixin):
self.update_trade_state(trade, order_id, order)
Trade.query.session.add(trade)
Trade.query.session.flush()
Trade.commit()
# Updating wallets
self.wallets.update()
@ -655,7 +606,7 @@ class FreqtradeBot(LoggingMixin):
"""
Sends rpc notification when a buy cancel occurred.
"""
current_rate = self.get_buy_rate(trade.pair, False)
current_rate = self.exchange.get_buy_rate(trade.pair, False)
msg = {
'trade_id': trade.id,
@ -706,6 +657,7 @@ class FreqtradeBot(LoggingMixin):
if (self.strategy.order_types.get('stoploss_on_exchange') and
self.handle_stoploss_on_exchange(trade)):
trades_closed += 1
Trade.commit()
continue
# Check if we can sell our current pair
if trade.open_order_id is None and trade.is_open and self.handle_trade(trade):
@ -720,56 +672,6 @@ class FreqtradeBot(LoggingMixin):
return trades_closed
def _order_book_gen(self, pair: str, side: str, order_book_max: int = 1,
order_book_min: int = 1):
"""
Helper generator to query orderbook in loop (used for early sell-order placing)
"""
order_book = self.exchange.fetch_l2_order_book(pair, order_book_max)
for i in range(order_book_min, order_book_max + 1):
yield order_book[side][i - 1][0]
def get_sell_rate(self, pair: str, refresh: bool) -> float:
"""
Get sell rate - either using ticker bid or first bid based on orderbook
The orderbook portion is only used for rpc messaging, which would otherwise fail
for BitMex (has no bid/ask in fetch_ticker)
or remain static in any other case since it's not updating.
:param pair: Pair to get rate for
:param refresh: allow cached data
:return: Bid rate
"""
if not refresh:
rate = self._sell_rate_cache.get(pair)
# Check if cache has been invalidated
if rate:
logger.debug(f"Using cached sell rate for {pair}.")
return rate
ask_strategy = self.config.get('ask_strategy', {})
if ask_strategy.get('use_order_book', False):
# This code is only used for notifications, selling uses the generator directly
logger.info(
f"Getting price from order book {ask_strategy['price_side'].capitalize()} side."
)
try:
rate = next(self._order_book_gen(pair, f"{ask_strategy['price_side']}s"))
except (IndexError, KeyError) as e:
logger.warning("Sell Price at location from orderbook could not be determined.")
raise PricingError from e
else:
ticker = self.exchange.fetch_ticker(pair)
ticker_rate = ticker[ask_strategy['price_side']]
if ticker['last'] and ticker_rate < ticker['last']:
balance = ask_strategy.get('bid_last_balance', 0.0)
ticker_rate = ticker_rate - balance * (ticker_rate - ticker['last'])
rate = ticker_rate
if rate is None:
raise PricingError(f"Sell-Rate for {pair} was empty.")
self._sell_rate_cache[pair] = rate
return rate
def handle_trade(self, trade: Trade) -> bool:
"""
Sells the current pair if the threshold is reached and updates the trade record.
@ -797,9 +699,9 @@ class FreqtradeBot(LoggingMixin):
logger.debug(f'Using order book between {order_book_min} and {order_book_max} '
f'for selling {trade.pair}...')
order_book = self._order_book_gen(trade.pair, f"{config_ask_strategy['price_side']}s",
order_book_min=order_book_min,
order_book_max=order_book_max)
order_book = self.exchange._order_book_gen(
trade.pair, f"{config_ask_strategy['price_side']}s",
order_book_min=order_book_min, order_book_max=order_book_max)
for i in range(order_book_min, order_book_max + 1):
try:
sell_rate = next(order_book)
@ -812,14 +714,14 @@ class FreqtradeBot(LoggingMixin):
f"{sell_rate:0.8f}")
# Assign sell-rate to cache - otherwise sell-rate is never updated in the cache,
# resulting in outdated RPC messages
self._sell_rate_cache[trade.pair] = sell_rate
self.exchange._sell_rate_cache[trade.pair] = sell_rate
if self._check_and_execute_sell(trade, sell_rate, buy, sell):
return True
else:
logger.debug('checking sell')
sell_rate = self.get_sell_rate(trade.pair, True)
sell_rate = self.exchange.get_sell_rate(trade.pair, True)
if self._check_and_execute_sell(trade, sell_rate, buy, sell):
return True
@ -915,8 +817,13 @@ class FreqtradeBot(LoggingMixin):
logger.warning('Stoploss order was cancelled, but unable to recreate one.')
# Finally we check if stoploss on exchange should be moved up because of trailing.
if stoploss_order and (self.config.get('trailing_stop', False)
or self.config.get('use_custom_stoploss', False)):
# Triggered Orders are now real orders - so don't replace stoploss anymore
if (
stoploss_order
and stoploss_order.get('status_stop') != 'triggered'
and (self.config.get('trailing_stop', False)
or self.config.get('use_custom_stoploss', False))
):
# if trailing stoploss is enabled we check if stoploss value has changed
# in which case we cancel stoploss order and put another one with new
# value immediately
@ -928,7 +835,7 @@ class FreqtradeBot(LoggingMixin):
"""
Check to see if stoploss on exchange should be updated
in case of trailing stoploss on exchange
:param Trade: Corresponding Trade
:param trade: Corresponding Trade
:param order: Current on exchange stoploss order
:return: None
"""
@ -1036,6 +943,7 @@ class FreqtradeBot(LoggingMixin):
elif order['side'] == 'sell':
self.handle_cancel_sell(trade, order, constants.CANCEL_REASON['ALL_CANCELLED'])
Trade.commit()
def handle_cancel_buy(self, trade: Trade, order: Dict, reason: str) -> bool:
"""
@ -1233,7 +1141,7 @@ class FreqtradeBot(LoggingMixin):
# In case of market sell orders the order can be closed immediately
if order.get('status', 'unknown') == 'closed':
self.update_trade_state(trade, trade.open_order_id, order)
Trade.query.session.flush()
Trade.commit()
# Lock pair for one candle to prevent immediate re-buys
self.strategy.lock_pair(trade.pair, datetime.now(timezone.utc),
@ -1250,7 +1158,7 @@ class FreqtradeBot(LoggingMixin):
profit_rate = trade.close_rate if trade.close_rate else trade.close_rate_requested
profit_trade = trade.calc_profit(rate=profit_rate)
# Use cached rates here - it was updated seconds ago.
current_rate = self.get_sell_rate(trade.pair, False) if not fill else None
current_rate = self.exchange.get_sell_rate(trade.pair, False) if not fill else None
profit_ratio = trade.calc_profit_ratio(profit_rate)
gain = "profit" if profit_ratio > 0 else "loss"
@ -1295,7 +1203,7 @@ class FreqtradeBot(LoggingMixin):
profit_rate = trade.close_rate if trade.close_rate else trade.close_rate_requested
profit_trade = trade.calc_profit(rate=profit_rate)
current_rate = self.get_sell_rate(trade.pair, False)
current_rate = self.exchange.get_sell_rate(trade.pair, False)
profit_ratio = trade.calc_profit_ratio(profit_rate)
gain = "profit" if profit_ratio > 0 else "loss"
@ -1374,6 +1282,7 @@ class FreqtradeBot(LoggingMixin):
# Handling of this will happen in check_handle_timeout.
return True
trade.update(order)
Trade.commit()
# Updating wallets when order is closed
if not trade.is_open:

1
freqtrade/misc.py
View File

@ -56,6 +56,7 @@ def file_dump_json(filename: Path, data: Any, is_zip: bool = False, log: bool =
"""
Dump JSON data into a file
:param filename: file to create
:param is_zip: if file should be zip
:param data: JSON Data to save
:return:
"""

25
freqtrade/optimize/backtesting.py
View File

@ -17,6 +17,7 @@ from freqtrade.data import history
from freqtrade.data.btanalysis import trade_list_to_dataframe
from freqtrade.data.converter import trim_dataframes
from freqtrade.data.dataprovider import DataProvider
from freqtrade.enums import SellType
from freqtrade.exceptions import DependencyException, OperationalException
from freqtrade.exchange import timeframe_to_minutes, timeframe_to_seconds
from freqtrade.mixins import LoggingMixin
@ -26,7 +27,7 @@ from freqtrade.persistence import LocalTrade, PairLocks, Trade
from freqtrade.plugins.pairlistmanager import PairListManager
from freqtrade.plugins.protectionmanager import ProtectionManager
from freqtrade.resolvers import ExchangeResolver, StrategyResolver
from freqtrade.strategy.interface import IStrategy, SellCheckTuple, SellType
from freqtrade.strategy.interface import IStrategy, SellCheckTuple
from freqtrade.strategy.strategy_wrapper import strategy_safe_wrapper
from freqtrade.wallets import Wallets
@ -136,7 +137,7 @@ class Backtesting:
if hasattr(strategy, 'protections'):
conf = deepcopy(conf)
conf['protections'] = strategy.protections
self.protections = ProtectionManager(conf)
self.protections = ProtectionManager(self.config, strategy.protections)
def load_bt_data(self) -> Tuple[Dict[str, DataFrame], TimeRange]:
"""
@ -224,6 +225,22 @@ class Backtesting:
# sell at open price.
return sell_row[OPEN_IDX]
# Special case: trailing triggers within same candle as trade opened. Assume most
# pessimistic price movement, which is moving just enough to arm stoploss and
# immediately going down to stop price.
if (sell.sell_type == SellType.TRAILING_STOP_LOSS and trade_dur == 0
and self.strategy.trailing_stop_positive):
if self.strategy.trailing_only_offset_is_reached:
# Worst case: price reaches stop_positive_offset and dives down.
stop_rate = (sell_row[OPEN_IDX] *
(1 + abs(self.strategy.trailing_stop_positive_offset) -
abs(self.strategy.trailing_stop_positive)))
else:
# Worst case: price ticks tiny bit above open and dives down.
stop_rate = sell_row[OPEN_IDX] * (1 - abs(self.strategy.trailing_stop_positive))
assert stop_rate < sell_row[HIGH_IDX]
return stop_rate
# Set close_rate to stoploss
return trade.stop_loss
elif sell.sell_type == (SellType.ROI):
@ -428,7 +445,7 @@ class Backtesting:
for trade in open_trades[pair]:
# also check the buying candle for sell conditions.
trade_entry = self._get_sell_trade_entry(trade, row)
# Sell occured
# Sell occurred
if trade_entry:
# logger.debug(f"{pair} - Backtesting sell {trade}")
open_trade_count -= 1
@ -519,7 +536,7 @@ class Backtesting:
stats = generate_backtest_stats(data, self.all_results,
min_date=min_date, max_date=max_date)
if self.config.get('export', False):
if self.config.get('export', 'none') == 'trades':
store_backtest_stats(self.config['exportfilename'], stats)
# Show backtest results

4
freqtrade/optimize/hyperopt.py
View File

@ -469,8 +469,8 @@ class Hyperopt:
f"saved to '{self.results_file}'.")
if self.current_best_epoch:
HyperoptTools.print_epoch_details(self.current_best_epoch, self.total_epochs,
self.print_json)
HyperoptTools.show_epoch_details(self.current_best_epoch, self.total_epochs,
self.print_json)
else:
# This is printed when Ctrl+C is pressed quickly, before first epochs have
# a chance to be evaluated.

18
freqtrade/optimize/hyperopt_loss_onlyprofit.py
View File

@ -9,23 +9,11 @@ from pandas import DataFrame
from freqtrade.optimize.hyperopt import IHyperOptLoss
# This is assumed to be expected avg profit * expected trade count.
# For example, for 0.35% avg per trade (or 0.0035 as ratio) and 1100 trades,
# expected max profit = 3.85
#
# Note, this is ratio. 3.85 stated above means 385Σ%, 3.0 means 300Σ%.
#
# In this implementation it's only used in calculation of the resulting value
# of the objective function as a normalization coefficient and does not
# represent any limit for profits as in the Freqtrade legacy default loss function.
EXPECTED_MAX_PROFIT = 3.0
class OnlyProfitHyperOptLoss(IHyperOptLoss):
"""
Defines the loss function for hyperopt.
This implementation takes only profit into account.
This implementation takes only absolute profit into account, not looking at any other indicator.
"""
@staticmethod
@ -34,5 +22,5 @@ class OnlyProfitHyperOptLoss(IHyperOptLoss):
"""
Objective function, returns smaller number for better results.
"""
total_profit = results['profit_ratio'].sum()
return 1 - total_profit / EXPECTED_MAX_PROFIT
total_profit = results['profit_abs'].sum()
return -1 * total_profit

135
freqtrade/optimize/hyperopt_tools.py Normal file → Executable file
View File

@ -1,8 +1,6 @@
import io
import locale
import logging
from collections import OrderedDict
from pathlib import Path
from typing import Any, Dict, List
@ -74,8 +72,8 @@ class HyperoptTools():
return epochs
@staticmethod
def print_epoch_details(results, total_epochs: int, print_json: bool,
no_header: bool = False, header_str: str = None) -> None:
def show_epoch_details(results, total_epochs: int, print_json: bool,
no_header: bool = False, header_str: str = None) -> None:
"""
Display details of the hyperopt result
"""
@ -93,7 +91,7 @@ class HyperoptTools():
if print_json:
result_dict: Dict = {}
for s in ['buy', 'sell', 'roi', 'stoploss', 'trailing']:
HyperoptTools._params_update_for_json(result_dict, params, s)
HyperoptTools._params_update_for_json(result_dict, params, non_optimized, s)
print(rapidjson.dumps(result_dict, default=str, number_mode=rapidjson.NM_NATIVE))
else:
@ -106,24 +104,24 @@ class HyperoptTools():
HyperoptTools._params_pretty_print(params, 'trailing', "Trailing stop:")
@staticmethod
def _params_update_for_json(result_dict, params, space: str) -> None:
if space in params:
def _params_update_for_json(result_dict, params, non_optimized, space: str) -> None:
if (space in params) or (space in non_optimized):
space_params = HyperoptTools._space_params(params, space)
if space in ['buy', 'sell']:
result_dict.setdefault('params', {}).update(space_params)
elif space == 'roi':
# TODO: get rid of OrderedDict when support for python 3.6 will be
# dropped (dicts keep the order as the language feature)
space_non_optimized = HyperoptTools._space_params(non_optimized, space)
all_space_params = space_params
# Merge non optimized params if there are any
if len(space_non_optimized) > 0:
all_space_params = {**space_params, **space_non_optimized}
if space in ['buy', 'sell']:
result_dict.setdefault('params', {}).update(all_space_params)
elif space == 'roi':
# Convert keys in min_roi dict to strings because
# rapidjson cannot dump dicts with integer keys...
# OrderedDict is used to keep the numeric order of the items
# in the dict.
result_dict['minimal_roi'] = OrderedDict(
(str(k), v) for k, v in space_params.items()
)
result_dict['minimal_roi'] = {str(k): v for k, v in all_space_params.items()}
else: # 'stoploss', 'trailing'
result_dict.update(space_params)
result_dict.update(all_space_params)
@staticmethod
def _params_pretty_print(params, space: str, header: str, non_optimized={}) -> None:
@ -133,13 +131,9 @@ class HyperoptTools():
if space == 'stoploss':
result += f"stoploss = {space_params.get('stoploss')}"
elif space == 'roi':
# TODO: get rid of OrderedDict when support for python 3.6 will be
# dropped (dicts keep the order as the language feature)
minimal_roi_result = rapidjson.dumps(
OrderedDict(
(str(k), v) for k, v in space_params.items()
),
default=str, indent=4, number_mode=rapidjson.NM_NATIVE)
minimal_roi_result = rapidjson.dumps({
str(k): v for k, v in space_params.items()
}, default=str, indent=4, number_mode=rapidjson.NM_NATIVE)
result += f"minimal_roi = {minimal_roi_result}"
elif space == 'trailing':
@ -195,9 +189,9 @@ class HyperoptTools():
f"Avg profit {results_metrics['profit_mean'] * 100: 6.2f}%. "
f"Median profit {results_metrics['profit_median'] * 100: 6.2f}%. "
f"Total profit {results_metrics['profit_total_abs']: 11.8f} {stake_currency} "
f"({results_metrics['profit_total'] * 100: 7.2f}\N{GREEK CAPITAL LETTER SIGMA}%). "
f"({results_metrics['profit_total'] * 100: 7.2f}%). "
f"Avg duration {results_metrics['holding_avg']} min."
).encode(locale.getpreferredencoding(), 'replace').decode('utf-8')
)
@staticmethod
def _format_explanation_string(results, total_epochs) -> str:
@ -206,6 +200,47 @@ class HyperoptTools():
f"{results['results_explanation']} " +
f"Objective: {results['loss']:.5f}")
@staticmethod
def prepare_trials_columns(trials, legacy_mode: bool, has_drawdown: bool) -> str:
trials['Best'] = ''
if 'results_metrics.winsdrawslosses' not in trials.columns:
# Ensure compatibility with older versions of hyperopt results
trials['results_metrics.winsdrawslosses'] = 'N/A'
if not has_drawdown:
# Ensure compatibility with older versions of hyperopt results
trials['results_metrics.max_drawdown_abs'] = None
trials['results_metrics.max_drawdown'] = None
if not legacy_mode:
# New mode, using backtest result for metrics
trials['results_metrics.winsdrawslosses'] = trials.apply(
lambda x: f"{x['results_metrics.wins']} {x['results_metrics.draws']:>4} "
f"{x['results_metrics.losses']:>4}", axis=1)
trials = trials[['Best', 'current_epoch', 'results_metrics.total_trades',
'results_metrics.winsdrawslosses',
'results_metrics.profit_mean', 'results_metrics.profit_total_abs',
'results_metrics.profit_total', 'results_metrics.holding_avg',
'results_metrics.max_drawdown', 'results_metrics.max_drawdown_abs',
'loss', 'is_initial_point', 'is_best']]
else:
# Legacy mode
trials = trials[['Best', 'current_epoch', 'results_metrics.trade_count',
'results_metrics.winsdrawslosses', 'results_metrics.avg_profit',
'results_metrics.total_profit', 'results_metrics.profit',
'results_metrics.duration', 'results_metrics.max_drawdown',
'results_metrics.max_drawdown_abs', 'loss', 'is_initial_point',
'is_best']]
trials.columns = ['Best', 'Epoch', 'Trades', ' Win Draw Loss', 'Avg profit',
'Total profit', 'Profit', 'Avg duration', 'Max Drawdown',
'max_drawdown_abs', 'Objective', 'is_initial_point', 'is_best']
return trials
@staticmethod
def get_result_table(config: dict, results: list, total_epochs: int, highlight_best: bool,
print_colorized: bool, remove_header: int) -> str:
@ -216,36 +251,13 @@ class HyperoptTools():
return ''
tabulate.PRESERVE_WHITESPACE = True
trials = json_normalize(results, max_level=1)
trials['Best'] = ''
if 'results_metrics.winsdrawslosses' not in trials.columns:
# Ensure compatibility with older versions of hyperopt results
trials['results_metrics.winsdrawslosses'] = 'N/A'
legacy_mode = True
if 'results_metrics.total_trades' in trials:
legacy_mode = False
# New mode, using backtest result for metrics
trials['results_metrics.winsdrawslosses'] = trials.apply(
lambda x: f"{x['results_metrics.wins']} {x['results_metrics.draws']:>4} "
f"{x['results_metrics.losses']:>4}", axis=1)
trials = trials[['Best', 'current_epoch', 'results_metrics.total_trades',
'results_metrics.winsdrawslosses',
'results_metrics.profit_mean', 'results_metrics.profit_total_abs',
'results_metrics.profit_total', 'results_metrics.holding_avg',
'loss', 'is_initial_point', 'is_best']]
else:
# Legacy mode
trials = trials[['Best', 'current_epoch', 'results_metrics.trade_count',
'results_metrics.winsdrawslosses',
'results_metrics.avg_profit', 'results_metrics.total_profit',
'results_metrics.profit', 'results_metrics.duration',
'loss', 'is_initial_point', 'is_best']]
legacy_mode = 'results_metrics.total_trades' not in trials
has_drawdown = 'results_metrics.max_drawdown_abs' in trials.columns
trials = HyperoptTools.prepare_trials_columns(trials, legacy_mode, has_drawdown)
trials.columns = ['Best', 'Epoch', 'Trades', ' Win Draw Loss', 'Avg profit',
'Total profit', 'Profit', 'Avg duration', 'Objective',
'is_initial_point', 'is_best']
trials['is_profit'] = False
trials.loc[trials['is_initial_point'], 'Best'] = '* '
trials.loc[trials['is_best'], 'Best'] = 'Best'
@ -268,6 +280,21 @@ class HyperoptTools():
)
stake_currency = config['stake_currency']
if has_drawdown:
trials['Max Drawdown'] = trials.apply(
lambda x: '{} {}'.format(
round_coin_value(x['max_drawdown_abs'], stake_currency),
'({:,.2f}%)'.format(x['Max Drawdown'] * perc_multi).rjust(10, ' ')
).rjust(25 + len(stake_currency))
if x['Max Drawdown'] != 0.0 else '--'.rjust(25 + len(stake_currency)),
axis=1
)
else:
trials = trials.drop(columns=['Max Drawdown'])
trials = trials.drop(columns=['max_drawdown_abs'])
trials['Profit'] = trials.apply(
lambda x: '{} {}'.format(
round_coin_value(x['Total profit'], stake_currency),

32
freqtrade/optimize/optimize_reports.py
View File

@ -21,7 +21,7 @@ def store_backtest_stats(recordfilename: Path, stats: Dict[str, DataFrame]) -> N
Stores backtest results
:param recordfilename: Path object, which can either be a filename or a directory.
Filenames will be appended with a timestamp right before the suffix
while for diectories, <directory>/backtest-result-<datetime>.json will be used as filename
while for directories, <directory>/backtest-result-<datetime>.json will be used as filename
:param stats: Dataframe containing the backtesting statistics
"""
if recordfilename.is_dir():
@ -232,16 +232,23 @@ def generate_trading_stats(results: DataFrame) -> Dict[str, Any]:
zero_duration_trades = len(results.loc[(results['trade_duration'] == 0) &
(results['sell_reason'] == 'trailing_stop_loss')])
holding_avg = (timedelta(minutes=round(results['trade_duration'].mean()))
if not results.empty else timedelta())
winner_holding_avg = (timedelta(minutes=round(winning_trades['trade_duration'].mean()))
if not winning_trades.empty else timedelta())
loser_holding_avg = (timedelta(minutes=round(losing_trades['trade_duration'].mean()))
if not losing_trades.empty else timedelta())
return {
'wins': len(winning_trades),
'losses': len(losing_trades),
'draws': len(draw_trades),
'holding_avg': (timedelta(minutes=round(results['trade_duration'].mean()))
if not results.empty else timedelta()),
'winner_holding_avg': (timedelta(minutes=round(winning_trades['trade_duration'].mean()))
if not winning_trades.empty else timedelta()),
'loser_holding_avg': (timedelta(minutes=round(losing_trades['trade_duration'].mean()))
if not losing_trades.empty else timedelta()),
'holding_avg': holding_avg,
'holding_avg_s': holding_avg.total_seconds(),
'winner_holding_avg': winner_holding_avg,
'winner_holding_avg_s': winner_holding_avg.total_seconds(),
'loser_holding_avg': loser_holding_avg,
'loser_holding_avg_s': loser_holding_avg.total_seconds(),
'zero_duration_trades': zero_duration_trades,
}
@ -293,7 +300,7 @@ def generate_strategy_stats(btdata: Dict[str, DataFrame],
:param min_date: Backtest start date
:param max_date: Backtest end date
:param market_change: float indicating the market change
:return: Dictionary containing results per strategy and a stratgy summary.
:return: Dictionary containing results per strategy and a strategy summary.
"""
results: Dict[str, DataFrame] = content['results']
if not isinstance(results, DataFrame):
@ -429,7 +436,7 @@ def generate_backtest_stats(btdata: Dict[str, DataFrame],
{ Strategy: {'results: results, 'config: config}}.
:param min_date: Backtest start date
:param max_date: Backtest end date
:return: Dictionary containing results per strategy and a stratgy summary.
:return: Dictionary containing results per strategy and a strategy summary.
"""
result: Dict[str, Any] = {'strategy': {}}
market_change = calculate_market_change(btdata, 'close')
@ -500,9 +507,8 @@ def text_table_sell_reason(sell_reason_stats: List[Dict[str, Any]], stake_curren
def text_table_strategy(strategy_results, stake_currency: str) -> str:
"""
Generate summary table per strategy
:param strategy_results: Dict of <Strategyname: DataFrame> containing results for all strategies
:param stake_currency: stake-currency - used to correctly name headers
:param max_open_trades: Maximum allowed open trades used for backtest
:param all_results: Dict of <Strategyname: DataFrame> containing results for all strategies
:return: pretty printed table with tabulate as string
"""
floatfmt = _get_line_floatfmt(stake_currency)
@ -549,7 +555,8 @@ def text_table_add_metrics(strat_results: Dict) -> str:
('Backtesting to', strat_results['backtest_end']),
('Max open trades', strat_results['max_open_trades']),
('', ''), # Empty line to improve readability
('Total trades', strat_results['total_trades']),
('Total/Daily Avg Trades',
f"{strat_results['total_trades']} / {strat_results['trades_per_day']}"),
('Starting balance', round_coin_value(strat_results['starting_balance'],
strat_results['stake_currency'])),
('Final balance', round_coin_value(strat_results['final_balance'],
@ -557,7 +564,6 @@ def text_table_add_metrics(strat_results: Dict) -> str:
('Absolute profit ', round_coin_value(strat_results['profit_total_abs'],
strat_results['stake_currency'])),
('Total profit %', f"{round(strat_results['profit_total'] * 100, 2):}%"),
('Trades per day', strat_results['trades_per_day']),
('Avg. stake amount', round_coin_value(strat_results['avg_stake_amount'],
strat_results['stake_currency'])),
('Total trade volume', round_coin_value(strat_results['total_volume'],

51
freqtrade/persistence/migrations.py
View File

@ -1,7 +1,7 @@
import logging
from typing import List
from sqlalchemy import inspect
from sqlalchemy import inspect, text
logger = logging.getLogger(__name__)
@ -62,15 +62,17 @@ def migrate_trades_table(decl_base, inspector, engine, table_back_name: str, col
amount_requested = get_column_def(cols, 'amount_requested', 'amount')
# Schema migration necessary
engine.execute(f"alter table trades rename to {table_back_name}")
# drop indexes on backup table
for index in inspector.get_indexes(table_back_name):
engine.execute(f"drop index {index['name']}")
with engine.begin() as connection:
connection.execute(text(f"alter table trades rename to {table_back_name}"))
# drop indexes on backup table
for index in inspector.get_indexes(table_back_name):
connection.execute(text(f"drop index {index['name']}"))
# let SQLAlchemy create the schema as required
decl_base.metadata.create_all(engine)
# Copy data back - following the correct schema
engine.execute(f"""insert into trades
with engine.begin() as connection:
connection.execute(text(f"""insert into trades
(id, exchange, pair, is_open,
fee_open, fee_open_cost, fee_open_currency,
fee_close, fee_close_cost, fee_open_currency, open_rate,
@ -104,11 +106,12 @@ def migrate_trades_table(decl_base, inspector, engine, table_back_name: str, col
{strategy} strategy, {timeframe} timeframe,
{open_trade_value} open_trade_value, {close_profit_abs} close_profit_abs
from {table_back_name}
""")
"""))
def migrate_open_orders_to_trades(engine):
engine.execute("""
with engine.begin() as connection:
connection.execute(text("""
insert into orders (ft_trade_id, ft_pair, order_id, ft_order_side, ft_is_open)
select id ft_trade_id, pair ft_pair, open_order_id,
case when close_rate_requested is null then 'buy'
@ -120,28 +123,30 @@ def migrate_open_orders_to_trades(engine):
'stoploss' ft_order_side, 1 ft_is_open
from trades
where stoploss_order_id is not null
""")
"""))
def migrate_orders_table(decl_base, inspector, engine, table_back_name: str, cols: List):
# Schema migration necessary
engine.execute(f"alter table orders rename to {table_back_name}")
# drop indexes on backup table
for index in inspector.get_indexes(table_back_name):
engine.execute(f"drop index {index['name']}")
with engine.begin() as connection:
connection.execute(text(f"alter table orders rename to {table_back_name}"))
# drop indexes on backup table
for index in inspector.get_indexes(table_back_name):
connection.execute(text(f"drop index {index['name']}"))
# let SQLAlchemy create the schema as required
decl_base.metadata.create_all(engine)
engine.execute(f"""
insert into orders ( id, ft_trade_id, ft_order_side, ft_pair, ft_is_open, order_id, status,
symbol, order_type, side, price, amount, filled, average, remaining, cost, order_date,
order_filled_date, order_update_date)
select id, ft_trade_id, ft_order_side, ft_pair, ft_is_open, order_id, status,
symbol, order_type, side, price, amount, filled, null average, remaining, cost, order_date,
order_filled_date, order_update_date
from {table_back_name}
""")
with engine.begin() as connection:
connection.execute(text(f"""
insert into orders ( id, ft_trade_id, ft_order_side, ft_pair, ft_is_open, order_id,
status, symbol, order_type, side, price, amount, filled, average, remaining, cost,
order_date, order_filled_date, order_update_date)
select id, ft_trade_id, ft_order_side, ft_pair, ft_is_open, order_id,
status, symbol, order_type, side, price, amount, filled, null average, remaining, cost,
order_date, order_filled_date, order_update_date
from {table_back_name}
"""))
def check_migrate(engine, decl_base, previous_tables) -> None:

31
freqtrade/persistence/models.py
View File

@ -9,14 +9,12 @@ from typing import Any, Dict, List, Optional
from sqlalchemy import (Boolean, Column, DateTime, Float, ForeignKey, Integer, String,
create_engine, desc, func, inspect)
from sqlalchemy.exc import NoSuchModuleError
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.orm import Query, relationship
from sqlalchemy.orm.scoping import scoped_session
from sqlalchemy.orm.session import sessionmaker
from sqlalchemy.orm import Query, declarative_base, relationship, scoped_session, sessionmaker
from sqlalchemy.pool import StaticPool
from sqlalchemy.sql.schema import UniqueConstraint
from freqtrade.constants import DATETIME_PRINT_FORMAT
from freqtrade.enums import SellType
from freqtrade.exceptions import DependencyException, OperationalException
from freqtrade.misc import safe_value_fallback
from freqtrade.persistence.migrations import check_migrate
@ -41,16 +39,18 @@ def init_db(db_url: str, clean_open_orders: bool = False) -> None:
"""
kwargs = {}
# Take care of thread ownership if in-memory db
if db_url == 'sqlite://':
kwargs.update({
'connect_args': {'check_same_thread': False},
'poolclass': StaticPool,
'echo': False,
})
# Take care of thread ownership
if db_url.startswith('sqlite://'):
kwargs.update({
'connect_args': {'check_same_thread': False},
})
try:
engine = create_engine(db_url, **kwargs)
engine = create_engine(db_url, future=True, **kwargs)
except NoSuchModuleError:
raise OperationalException(f"Given value for db_url: '{db_url}' "
f"is no valid database URL! (See {_SQL_DOCS_URL})")
@ -58,7 +58,7 @@ def init_db(db_url: str, clean_open_orders: bool = False) -> None:
# https://docs.sqlalchemy.org/en/13/orm/contextual.html#thread-local-scope
# Scoped sessions proxy requests to the appropriate thread-local session.
# We should use the scoped_session object - not a seperately initialized version
Trade._session = scoped_session(sessionmaker(bind=engine, autoflush=True, autocommit=True))
Trade._session = scoped_session(sessionmaker(bind=engine, autoflush=True))
Trade.query = Trade._session.query_property()
Order.query = Trade._session.query_property()
PairLock.query = Trade._session.query_property()
@ -77,7 +77,7 @@ def cleanup_db() -> None:
Flushes all pending operations to disk.
:return: None
"""
Trade.query.session.flush()
Trade.commit()
def clean_dry_run_db() -> None:
@ -89,6 +89,7 @@ def clean_dry_run_db() -> None:
# Check we are updating only a dry_run order not a prod one
if 'dry_run' in trade.open_order_id:
trade.open_order_id = None
Trade.commit()
class Order(_DECL_BASE):
@ -177,6 +178,7 @@ class Order(_DECL_BASE):
if filtered_orders:
oobj = filtered_orders[0]
oobj.update_from_ccxt_object(order)
Order.query.session.commit()
else:
logger.warning(f"Did not find order for {order}.")
@ -429,12 +431,13 @@ class LocalTrade():
elif order_type in ('stop_loss_limit', 'stop-loss', 'stop-loss-limit', 'stop'):
self.stoploss_order_id = None
self.close_rate_requested = self.stop_loss
self.sell_reason = SellType.STOPLOSS_ON_EXCHANGE.value
if self.is_open:
logger.info(f'{order_type.upper()} is hit for {self}.')
self.close(safe_value_fallback(order, 'average', 'price'))
else:
raise ValueError(f'Unknown order type: {order_type}')
cleanup_db()
Trade.commit()
def close(self, rate: float, *, show_msg: bool = True) -> None:
"""
@ -712,7 +715,11 @@ class Trade(_DECL_BASE, LocalTrade):
Order.query.session.delete(order)
Trade.query.session.delete(self)
Trade.query.session.flush()
Trade.commit()
@staticmethod
def commit():
Trade.query.session.commit()
@staticmethod
def get_trades_proxy(*, pair: str = None, is_open: bool = None,

4
freqtrade/persistence/pairlock_middleware.py
View File

@ -49,7 +49,7 @@ class PairLocks():
)
if PairLocks.use_db:
PairLock.query.session.add(lock)
PairLock.query.session.flush()
PairLock.query.session.commit()
else:
PairLocks.locks.append(lock)
@ -99,7 +99,7 @@ class PairLocks():
for lock in locks:
lock.active = False
if PairLocks.use_db:
PairLock.query.session.flush()
PairLock.query.session.commit()
@staticmethod
def is_global_lock(now: Optional[datetime] = None) -> bool:

44
freqtrade/plot/plotting.py
View File

@ -47,7 +47,7 @@ def init_plotscript(config, markets: List, startup_candles: int = 0):
data = load_data(
datadir=config.get('datadir'),
pairs=pairs,
timeframe=config.get('timeframe', '5m'),
timeframe=config['timeframe'],
timerange=timerange,
startup_candles=startup_candles,
data_format=config.get('dataformat_ohlcv', 'json'),
@ -56,7 +56,7 @@ def init_plotscript(config, markets: List, startup_candles: int = 0):
if startup_candles and data:
min_date, max_date = get_timerange(data)
logger.info(f"Loading data from {min_date} to {max_date}")
timerange.adjust_start_if_necessary(timeframe_to_seconds(config.get('timeframe', '5m')),
timerange.adjust_start_if_necessary(timeframe_to_seconds(config['timeframe']),
startup_candles, min_date)
no_trades = False
@ -96,20 +96,34 @@ def add_indicators(fig, row, indicators: Dict[str, Dict], data: pd.DataFrame) ->
Dict key must correspond to dataframe column.
:param data: candlestick DataFrame
"""
plot_kinds = {
'scatter': go.Scatter,
'bar': go.Bar,
}
for indicator, conf in indicators.items():
logger.debug(f"indicator {indicator} with config {conf}")
if indicator in data:
kwargs = {'x': data['date'],
'y': data[indicator].values,
'mode': 'lines',
'name': indicator
}
if 'color' in conf:
kwargs.update({'line': {'color': conf['color']}})
scatter = go.Scatter(
**kwargs
)
fig.add_trace(scatter, row, 1)
plot_type = conf.get('type', 'scatter')
color = conf.get('color')
if plot_type == 'bar':
kwargs.update({'marker_color': color or 'DarkSlateGrey',
'marker_line_color': color or 'DarkSlateGrey'})
else:
if color:
kwargs.update({'line': {'color': color}})
kwargs['mode'] = 'lines'
if plot_type != 'scatter':
logger.warning(f'Indicator {indicator} has unknown plot trace kind {plot_type}'
f', assuming "scatter".')
kwargs.update(conf.get('plotly', {}))
trace = plot_kinds[plot_type](**kwargs)
fig.add_trace(trace, row, 1)
else:
logger.info(
'Indicator "%s" ignored. Reason: This indicator is not found '
@ -274,8 +288,8 @@ def plot_area(fig, row: int, data: pd.DataFrame, indicator_a: str,
:param fig: Plot figure to append to
:param row: row number for this plot
:param data: candlestick DataFrame
:param indicator_a: indicator name as populated in stragetie
:param indicator_b: indicator name as populated in stragetie
:param indicator_a: indicator name as populated in strategy
:param indicator_b: indicator name as populated in strategy
:param label: label for the filled area
:param fill_color: color to be used for the filled area
:return: fig with added filled_traces plot
@ -569,6 +583,9 @@ def plot_profit(config: Dict[str, Any]) -> None:
But should be somewhat proportional, and therefor useful
in helping out to find a good algorithm.
"""
if 'timeframe' not in config:
raise OperationalException('Timeframe must be set in either config or via --timeframe.')
exchange = ExchangeResolver.load_exchange(config['exchange']['name'], config)
plot_elements = init_plotscript(config, list(exchange.markets))
trades = plot_elements['trades']
@ -585,7 +602,8 @@ def plot_profit(config: Dict[str, Any]) -> None:
# Create an average close price of all the pairs that were involved.
# this could be useful to gauge the overall market trend
fig = generate_profit_graph(plot_elements['pairs'], plot_elements['ohlcv'],
trades, config.get('timeframe', '5m'),
trades, config['timeframe'],
config.get('stake_currency', ''))
store_plot_file(fig, filename='freqtrade-profit-plot.html',
directory=config['user_data_dir'] / 'plot', auto_open=True)
directory=config['user_data_dir'] / 'plot',
auto_open=config.get('plot_auto_open', False))

2
freqtrade/plugins/pairlist/PerformanceFilter.py
View File

@ -19,7 +19,7 @@ class PerformanceFilter(IPairList):
def needstickers(self) -> bool:
"""
Boolean property defining if tickers are necessary.
If no Pairlist requries tickers, an empty List is passed
If no Pairlist requires tickers, an empty List is passed
as tickers argument to filter_pairlist
"""
return False

4
freqtrade/plugins/pairlist/VolatilityFilter.py
View File

@ -20,9 +20,9 @@ logger = logging.getLogger(__name__)
class VolatilityFilter(IPairList):
'''
"""
Filters pairs by volatility
'''
"""
def __init__(self, exchange, pairlistmanager,
config: Dict[str, Any], pairlistconfig: Dict[str, Any],

3
freqtrade/plugins/pairlistmanager.py
View File

@ -83,7 +83,8 @@ class PairListManager():
pairlist = self._pairlist_handlers[0].gen_pairlist(tickers)
# Process all Pairlist Handlers in the chain
for pairlist_handler in self._pairlist_handlers:
# except for the first one, which is the generator.
for pairlist_handler in self._pairlist_handlers[1:]:
pairlist = pairlist_handler.filter_pairlist(pairlist, tickers)
# Validation against blacklist happens after the chain of Pairlist Handlers

4
freqtrade/plugins/protectionmanager.py
View File

@ -15,11 +15,11 @@ logger = logging.getLogger(__name__)
class ProtectionManager():
def __init__(self, config: dict) -> None:
def __init__(self, config: Dict, protections: List) -> None:
self._config = config
self._protection_handlers: List[IProtection] = []
for protection_handler_config in self._config.get('protections', []):
for protection_handler_config in protections:
protection_handler = ProtectionResolver.load_protection(
protection_handler_config['method'],
config=config,

2
freqtrade/plugins/protections/stoploss_guard.py
View File

@ -3,9 +3,9 @@ import logging
from datetime import datetime, timedelta
from typing import Any, Dict
from freqtrade.enums import SellType
from freqtrade.persistence import Trade
from freqtrade.plugins.protections import IProtection, ProtectionReturn
from freqtrade.strategy.interface import SellType
logger = logging.getLogger(__name__)

1
freqtrade/resolvers/exchange_resolver.py
View File

@ -21,6 +21,7 @@ class ExchangeResolver(IResolver):
def load_exchange(exchange_name: str, config: dict, validate: bool = True) -> Exchange:
"""
Load the custom class from config parameter
:param exchange_name: name of the Exchange to load
:param config: configuration dictionary
"""
# Map exchange name to avoid duplicate classes for identical exchanges

10
freqtrade/resolvers/iresolver.py
View File

@ -58,6 +58,9 @@ class IResolver:
# Generate spec based on absolute path
# Pass object_name as first argument to have logging print a reasonable name.
spec = importlib.util.spec_from_file_location(object_name or "", str(module_path))
if not spec:
return iter([None])
module = importlib.util.module_from_spec(spec)
try:
spec.loader.exec_module(module) # type: ignore # importlib does not use typehints
@ -91,6 +94,9 @@ class IResolver:
if not str(entry).endswith('.py'):
logger.debug('Ignoring %s', entry)
continue
if entry.is_symlink() and not entry.is_file():
logger.debug('Ignoring broken symlink %s', entry)
continue
module_path = entry.resolve()
obj = next(cls._get_valid_object(module_path, object_name), None)
@ -129,7 +135,7 @@ class IResolver:
extra_dir: Optional[str] = None) -> Any:
"""
Search and loads the specified object as configured in hte child class.
:param objectname: name of the module to import
:param object_name: name of the module to import
:param config: configuration dictionary
:param extra_dir: additional directory to search for the given pairlist
:raises: OperationalException if the class is invalid or does not exist.
@ -157,7 +163,7 @@ class IResolver:
:param directory: Path to search
:param enum_failed: If True, will return None for modules which fail.
Otherwise, failing modules are skipped.
:return: List of dicts containing 'name', 'class' and 'location' entires
:return: List of dicts containing 'name', 'class' and 'location' entries
"""
logger.debug(f"Searching for {cls.object_type.__name__} '{directory}'")
objects = []

7
freqtrade/resolvers/strategy_resolver.py
View File

@ -6,7 +6,6 @@ This module load custom strategies
import logging
import tempfile
from base64 import urlsafe_b64decode
from collections import OrderedDict
from inspect import getfullargspec
from pathlib import Path
from typing import Any, Dict, Optional
@ -114,7 +113,9 @@ class StrategyResolver(IResolver):
- Strategy
- default (if not None)
"""
if attribute in config:
if (attribute in config
and not isinstance(getattr(type(strategy), 'my_property', None), property)):
# Ensure Properties are not overwritten
setattr(strategy, attribute, config[attribute])
logger.info("Override strategy '%s' with value in config file: %s.",
attribute, config[attribute])
@ -139,7 +140,7 @@ class StrategyResolver(IResolver):
# Sort and apply type conversions
if hasattr(strategy, 'minimal_roi'):
strategy.minimal_roi = OrderedDict(sorted(
strategy.minimal_roi = dict(sorted(
{int(key): value for (key, value) in strategy.minimal_roi.items()}.items(),
key=lambda t: t[0]))
if hasattr(strategy, 'stoploss'):

2
freqtrade/rpc/__init__.py
View File

@ -1,3 +1,3 @@
# flake8: noqa: F401
from .rpc import RPC, RPCException, RPCHandler, RPCMessageType
from .rpc import RPC, RPCException, RPCHandler
from .rpc_manager import RPCManager

4
freqtrade/rpc/api_server/api_v1.py
View File

@ -162,8 +162,8 @@ def delete_lock_pair(payload: DeleteLockRequest, rpc: RPC = Depends(get_rpc)):
@router.get('/logs', response_model=Logs, tags=['info'])
def logs(limit: Optional[int] = None, rpc: RPC = Depends(get_rpc)):
return rpc._rpc_get_logs(limit)
def logs(limit: Optional[int] = None):
return RPC._rpc_get_logs(limit)
@router.post('/start', response_model=StatusMsg, tags=['botcontrol'])

6
freqtrade/rpc/api_server/webserver.py
View File

@ -115,14 +115,12 @@ class ApiServer(RPCHandler):
logger.info('Starting Local Rest Server.')
verbosity = self._config['api_server'].get('verbosity', 'error')
log_config = uvicorn.config.LOGGING_CONFIG
# Change logging of access logs to stderr
log_config["handlers"]["access"]["stream"] = log_config["handlers"]["default"]["stream"]
uvconfig = uvicorn.Config(self.app,
port=rest_port,
host=rest_ip,
use_colors=False,
log_config=log_config,
log_config=None,
access_log=True if verbosity != 'error' else False,
)
try:

6
freqtrade/rpc/fiat_convert.py
View File

@ -102,7 +102,7 @@ class CryptoToFiatConverter:
inverse = True
symbol = f"{crypto_symbol}/{fiat_symbol}"
# Check if the fiat convertion you want is supported
# Check if the fiat conversion you want is supported
if not self._is_supported_fiat(fiat=fiat_symbol):
raise ValueError(f'The fiat {fiat_symbol} is not supported.')
@ -135,7 +135,7 @@ class CryptoToFiatConverter:
:param fiat_symbol: FIAT currency you want to convert to (e.g usd)
:return: float, price of the crypto-currency in Fiat
"""
# Check if the fiat convertion you want is supported
# Check if the fiat conversion you want is supported
if not self._is_supported_fiat(fiat=fiat_symbol):
raise ValueError(f'The fiat {fiat_symbol} is not supported.')
@ -146,7 +146,7 @@ class CryptoToFiatConverter:
if self._cryptomap == {}:
if self._backoff <= datetime.datetime.now().timestamp():
self._load_cryptomap()
# return 0.0 if we still dont have data to check, no reason to proceed
# return 0.0 if we still don't have data to check, no reason to proceed
if self._cryptomap == {}:
return 0.0
else:

55
freqtrade/rpc/rpc.py
View File

@ -4,7 +4,6 @@ This module contains class to define a RPC communications
import logging
from abc import abstractmethod
from datetime import date, datetime, timedelta, timezone
from enum import Enum
from math import isnan
from typing import Any, Dict, List, Optional, Tuple, Union
@ -15,6 +14,7 @@ from pandas import DataFrame
from freqtrade.configuration.timerange import TimeRange
from freqtrade.constants import CANCEL_REASON, DATETIME_PRINT_FORMAT
from freqtrade.data.history import load_data
from freqtrade.enums import SellType, State
from freqtrade.exceptions import ExchangeError, PricingError
from freqtrade.exchange import timeframe_to_minutes, timeframe_to_msecs
from freqtrade.loggers import bufferHandler
@ -23,31 +23,12 @@ from freqtrade.persistence import PairLocks, Trade
from freqtrade.persistence.models import PairLock
from freqtrade.plugins.pairlist.pairlist_helpers import expand_pairlist
from freqtrade.rpc.fiat_convert import CryptoToFiatConverter
from freqtrade.state import State
from freqtrade.strategy.interface import SellCheckTuple, SellType
from freqtrade.strategy.interface import SellCheckTuple
logger = logging.getLogger(__name__)
class RPCMessageType(Enum):
STATUS = 'status'
WARNING = 'warning'
STARTUP = 'startup'
BUY = 'buy'
BUY_FILL = 'buy_fill'
BUY_CANCEL = 'buy_cancel'
SELL = 'sell'
SELL_FILL = 'sell_fill'
SELL_CANCEL = 'sell_cancel'
def __repr__(self):
return self.value
def __str__(self):
return self.value
class RPCException(Exception):
"""
Should be raised with a rpc-formatted message in an _rpc_* method
@ -171,7 +152,7 @@ class RPC:
# calculate profit and send message to user
if trade.is_open:
try:
current_rate = self._freqtrade.get_sell_rate(trade.pair, False)
current_rate = self._freqtrade.exchange.get_sell_rate(trade.pair, False)
except (ExchangeError, PricingError):
current_rate = NAN
else:
@ -199,9 +180,9 @@ class RPC:
base_currency=self._freqtrade.config['stake_currency'],
close_profit=trade.close_profit if trade.close_profit is not None else None,
current_rate=current_rate,
current_profit=current_profit, # Deprectated
current_profit_pct=round(current_profit * 100, 2), # Deprectated
current_profit_abs=current_profit_abs, # Deprectated
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_pct=round(current_profit * 100, 2),
profit_abs=current_profit_abs,
@ -230,7 +211,7 @@ class RPC:
for trade in trades:
# calculate profit and send message to user
try:
current_rate = self._freqtrade.get_sell_rate(trade.pair, False)
current_rate = self._freqtrade.exchange.get_sell_rate(trade.pair, False)
except (PricingError, ExchangeError):
current_rate = NAN
trade_percent = (100 * trade.calc_profit_ratio(current_rate))
@ -355,9 +336,12 @@ class RPC:
return {'sell_reasons': sell_reasons, 'durations': durations}
def _rpc_trade_statistics(
self, stake_currency: str, fiat_display_currency: str) -> Dict[str, Any]:
self, stake_currency: str, fiat_display_currency: str,
start_date: datetime = datetime.fromtimestamp(0)) -> Dict[str, Any]:
""" Returns cumulative profit statistics """
trades = Trade.get_trades().order_by(Trade.id).all()
trade_filter = ((Trade.is_open.is_(False) & (Trade.close_date >= start_date)) |
Trade.is_open.is_(True))
trades = Trade.get_trades(trade_filter).order_by(Trade.id).all()
profit_all_coin = []
profit_all_ratio = []
@ -386,7 +370,7 @@ class RPC:
else:
# Get current rate
try:
current_rate = self._freqtrade.get_sell_rate(trade.pair, False)
current_rate = self._freqtrade.exchange.get_sell_rate(trade.pair, False)
except (PricingError, ExchangeError):
current_rate = NAN
profit_ratio = trade.calc_profit_ratio(rate=current_rate)
@ -556,7 +540,7 @@ class RPC:
if not fully_canceled:
# Get current rate and execute sell
current_rate = self._freqtrade.get_sell_rate(trade.pair, False)
current_rate = self._freqtrade.exchange.get_sell_rate(trade.pair, False)
sell_reason = SellCheckTuple(sell_type=SellType.FORCE_SELL)
self._freqtrade.execute_sell(trade, current_rate, sell_reason)
# ---- EOF def _exec_forcesell ----
@ -569,7 +553,7 @@ class RPC:
# Execute sell for all open orders
for trade in Trade.get_open_trades():
_exec_forcesell(trade)
Trade.query.session.flush()
Trade.commit()
self._freqtrade.wallets.update()
return {'result': 'Created sell orders for all open trades.'}
@ -582,7 +566,7 @@ class RPC:
raise RPCException('invalid argument')
_exec_forcesell(trade)
Trade.query.session.flush()
Trade.commit()
self._freqtrade.wallets.update()
return {'result': f'Created sell order for trade {trade_id}.'}
@ -615,6 +599,7 @@ class RPC:
# execute buy
if self._freqtrade.execute_buy(pair, stakeamount, price, forcebuy=True):
Trade.commit()
trade = Trade.get_trades([Trade.is_open.is_(True), Trade.pair == pair]).first()
return trade
else:
@ -705,8 +690,7 @@ class RPC:
lock.active = False
lock.lock_end_time = datetime.now(timezone.utc)
# session is always the same
PairLock.query.session.flush()
PairLock.query.session.commit()
return self._rpc_locks()
@ -840,8 +824,11 @@ class RPC:
)
if pair not in _data:
raise RPCException(f"No data for {pair}, {timeframe} in {timerange} found.")
from freqtrade.data.dataprovider import DataProvider
from freqtrade.resolvers.strategy_resolver import StrategyResolver
strategy = StrategyResolver.load_strategy(config)
strategy.dp = DataProvider(config, exchange=None, pairlists=None)
df_analyzed = strategy.analyze_ticker(_data[pair], {'pair': pair})
return RPC._convert_dataframe_to_dict(strategy.get_strategy_name(), pair, timeframe,

3
freqtrade/rpc/rpc_manager.py
View File

@ -4,7 +4,8 @@ This module contains class to manage RPC communications (Telegram, Slack, ...)
import logging
from typing import Any, Dict, List
from freqtrade.rpc import RPC, RPCHandler, RPCMessageType
from freqtrade.enums import RPCMessageType
from freqtrade.rpc import RPC, RPCHandler
logger = logging.getLogger(__name__)

267
freqtrade/rpc/telegram.py
View File

@ -5,25 +5,27 @@ This module manage Telegram communication
"""
import json
import logging
from datetime import timedelta
import re
from datetime import date, datetime, timedelta
from html import escape
from itertools import chain
from math import isnan
from typing import Any, Callable, Dict, List, Optional, Union, cast
from typing import Any, Callable, Dict, List, Optional, Union
import arrow
from tabulate import tabulate
from telegram import (InlineKeyboardButton, InlineKeyboardMarkup, KeyboardButton, ParseMode,
ReplyKeyboardMarkup, Update)
from telegram.error import NetworkError, TelegramError
from telegram import (CallbackQuery, InlineKeyboardButton, InlineKeyboardMarkup, KeyboardButton,
ParseMode, ReplyKeyboardMarkup, Update)
from telegram.error import BadRequest, NetworkError, TelegramError
from telegram.ext import CallbackContext, CallbackQueryHandler, CommandHandler, Updater
from telegram.utils.helpers import escape_markdown
from freqtrade.__init__ import __version__
from freqtrade.constants import DUST_PER_COIN
from freqtrade.enums import RPCMessageType
from freqtrade.exceptions import OperationalException
from freqtrade.misc import chunks, round_coin_value
from freqtrade.rpc import RPC, RPCException, RPCHandler, RPCMessageType
from freqtrade.rpc import RPC, RPCException, RPCHandler
logger = logging.getLogger(__name__)
@ -45,16 +47,20 @@ def authorized_only(command_handler: Callable[..., None]) -> Callable[..., Any]:
update = kwargs.get('update') or args[0]
# Reject unauthorized messages
chat_id = int(self._config['telegram']['chat_id'])
if update.callback_query:
cchat_id = int(update.callback_query.message.chat.id)
else:
cchat_id = int(update.message.chat_id)
if int(update.message.chat_id) != chat_id:
chat_id = int(self._config['telegram']['chat_id'])
if cchat_id != chat_id:
logger.info(
'Rejected unauthorized message from: %s',
update.message.chat_id
)
return wrapper
logger.info(
logger.debug(
'Executing handler: %s for chat_id: %s',
command_handler.__name__,
chat_id
@ -89,7 +95,7 @@ class Telegram(RPCHandler):
Validates the keyboard configuration from telegram config
section.
"""
self._keyboard: List[List[Union[str, KeyboardButton, InlineKeyboardButton]]] = [
self._keyboard: List[List[Union[str, KeyboardButton]]] = [
['/daily', '/profit', '/balance'],
['/status', '/status table', '/performance'],
['/count', '/start', '/stop', '/help']
@ -97,25 +103,29 @@ class Telegram(RPCHandler):
# do not allow commands with mandatory arguments and critical cmds
# like /forcesell and /forcebuy
# TODO: DRY! - its not good to list all valid cmds here. But otherwise
# this needs refacoring of the whole telegram module (same
# this needs refactoring of the whole telegram module (same
# problem in _help()).
valid_keys: List[str] = ['/start', '/stop', '/status', '/status table',
'/trades', '/profit', '/performance', '/daily',
'/stats', '/count', '/locks', '/balance',
'/stopbuy', '/reload_config', '/show_config',
'/logs', '/whitelist', '/blacklist', '/edge',
'/help', '/version']
valid_keys: List[str] = [r'/start$', r'/stop$', r'/status$', r'/status table$',
r'/trades$', r'/performance$', r'/daily$', r'/daily \d+$',
r'/profit$', r'/profit \d+',
r'/stats$', r'/count$', r'/locks$', r'/balance$',
r'/stopbuy$', r'/reload_config$', r'/show_config$',
r'/logs$', r'/whitelist$', r'/blacklist$', r'/edge$',
r'/forcebuy$', r'/help$', r'/version$']
# Create keys for generation
valid_keys_print = [k.replace('$', '') for k in valid_keys]
# custom keyboard specified in config.json
cust_keyboard = self._config['telegram'].get('keyboard', [])
if cust_keyboard:
combined = "(" + ")|(".join(valid_keys) + ")"
# check for valid shortcuts
invalid_keys = [b for b in chain.from_iterable(cust_keyboard)
if b not in valid_keys]
if not re.match(combined, b)]
if len(invalid_keys):
err_msg = ('config.telegram.keyboard: Invalid commands for '
f'custom Telegram keyboard: {invalid_keys}'
f'\nvalid commands are: {valid_keys}')
f'\nvalid commands are: {valid_keys_print}')
raise OperationalException(err_msg)
else:
self._keyboard = cust_keyboard
@ -158,8 +168,21 @@ class Telegram(RPCHandler):
CommandHandler('help', self._help),
CommandHandler('version', self._version),
]
callbacks = [
CallbackQueryHandler(self._status_table, pattern='update_status_table'),
CallbackQueryHandler(self._daily, pattern='update_daily'),
CallbackQueryHandler(self._profit, pattern='update_profit'),
CallbackQueryHandler(self._balance, pattern='update_balance'),
CallbackQueryHandler(self._performance, pattern='update_performance'),
CallbackQueryHandler(self._count, pattern='update_count'),
CallbackQueryHandler(self._forcebuy_inline),
]
for handle in handles:
self._updater.dispatcher.add_handler(handle)
for callback in callbacks:
self._updater.dispatcher.add_handler(callback)
self._updater.start_polling(
bootstrap_retries=-1,
timeout=30,
@ -171,11 +194,6 @@ class Telegram(RPCHandler):
[h.command for h in handles]
)
self._current_callback_query_handler: Optional[CallbackQueryHandler] = None
self._callback_query_handlers = {
'forcebuy': CallbackQueryHandler(self._forcebuy_inline)
}
def cleanup(self) -> None:
"""
Stops all running telegram threads.
@ -211,66 +229,83 @@ class Telegram(RPCHandler):
msg['emoji'] = self._get_sell_emoji(msg)
message = ("{emoji} *{exchange}:* Selling {pair} (#{trade_id})\n"
"*Amount:* `{amount:.8f}`\n"
"*Open Rate:* `{open_rate:.8f}`\n"
"*Current Rate:* `{current_rate:.8f}`\n"
"*Close Rate:* `{limit:.8f}`\n"
"*Sell Reason:* `{sell_reason}`\n"
"*Duration:* `{duration} ({duration_min:.1f} min)`\n"
"*Profit:* `{profit_percent:.2f}%`").format(**msg)
# Check if all sell properties are available.
# This might not be the case if the message origin is triggered by /forcesell
if (all(prop in msg for prop in ['gain', 'fiat_currency', 'stake_currency'])
and self._rpc._fiat_converter):
msg['profit_fiat'] = self._rpc._fiat_converter.convert_amount(
msg['profit_amount'], msg['stake_currency'], msg['fiat_currency'])
message += (' `({gain}: {profit_amount:.8f} {stake_currency}'
' / {profit_fiat:.3f} {fiat_currency})`').format(**msg)
msg['profit_extra'] = (' ({gain}: {profit_amount:.8f} {stake_currency}'
' / {profit_fiat:.3f} {fiat_currency})').format(**msg)
else:
msg['profit_extra'] = ''
message = ("{emoji} *{exchange}:* Selling {pair} (#{trade_id})\n"
"*Profit:* `{profit_percent:.2f}%{profit_extra}`\n"
"*Sell Reason:* `{sell_reason}`\n"
"*Duration:* `{duration} ({duration_min:.1f} min)`\n"
"*Amount:* `{amount:.8f}`\n"
"*Open Rate:* `{open_rate:.8f}`\n"
"*Current Rate:* `{current_rate:.8f}`\n"
"*Close Rate:* `{limit:.8f}`").format(**msg)
return message
def send_msg(self, msg: Dict[str, Any]) -> None:
""" Send a message to telegram channel """
noti = self._config['telegram'].get('notification_settings', {}
).get(str(msg['type']), 'on')
default_noti = 'on'
msg_type = msg['type']
noti = ''
if msg_type == RPCMessageType.SELL:
sell_noti = self._config['telegram'] \
.get('notification_settings', {}).get(str(msg_type), {})
# For backward compatibility sell still can be string
if isinstance(sell_noti, str):
noti = sell_noti
else:
noti = sell_noti.get(str(msg['sell_reason']), default_noti)
else:
noti = self._config['telegram'] \
.get('notification_settings', {}).get(str(msg_type), default_noti)
if noti == 'off':
logger.info(f"Notification '{msg['type']}' not sent.")
logger.info(f"Notification '{msg_type}' not sent.")
# Notification disabled
return
if msg['type'] == RPCMessageType.BUY:
if msg_type == RPCMessageType.BUY:
message = self._format_buy_msg(msg)
elif msg['type'] in (RPCMessageType.BUY_CANCEL, RPCMessageType.SELL_CANCEL):
msg['message_side'] = 'buy' if msg['type'] == RPCMessageType.BUY_CANCEL else 'sell'
elif msg_type in (RPCMessageType.BUY_CANCEL, RPCMessageType.SELL_CANCEL):
msg['message_side'] = 'buy' if msg_type == RPCMessageType.BUY_CANCEL else 'sell'
message = ("\N{WARNING SIGN} *{exchange}:* "
"Cancelling open {message_side} Order for {pair} (#{trade_id}). "
"Reason: {reason}.".format(**msg))
elif msg['type'] == RPCMessageType.BUY_FILL:
elif msg_type == RPCMessageType.BUY_FILL:
message = ("\N{LARGE CIRCLE} *{exchange}:* "
"Buy order for {pair} (#{trade_id}) filled "
"for {open_rate}.".format(**msg))
elif msg['type'] == RPCMessageType.SELL_FILL:
elif msg_type == RPCMessageType.SELL_FILL:
message = ("\N{LARGE CIRCLE} *{exchange}:* "
"Sell order for {pair} (#{trade_id}) filled "
"for {close_rate}.".format(**msg))
elif msg['type'] == RPCMessageType.SELL:
elif msg_type == RPCMessageType.SELL:
message = self._format_sell_msg(msg)
elif msg['type'] == RPCMessageType.STATUS:
elif msg_type == RPCMessageType.STATUS:
message = '*Status:* `{status}`'.format(**msg)
elif msg['type'] == RPCMessageType.WARNING:
elif msg_type == RPCMessageType.WARNING:
message = '\N{WARNING SIGN} *Warning:* `{status}`'.format(**msg)
elif msg['type'] == RPCMessageType.STARTUP:
elif msg_type == RPCMessageType.STARTUP:
message = '{status}'.format(**msg)
else:
raise NotImplementedError('Unknown message type: {}'.format(msg['type']))
raise NotImplementedError('Unknown message type: {}'.format(msg_type))
self._send_msg(message, disable_notification=(noti == 'silent'))
@ -386,7 +421,9 @@ class Telegram(RPCHandler):
# insert separators line between Total
lines = message.split("\n")
message = "\n".join(lines[:-1] + [lines[1]] + [lines[-1]])
self._send_msg(f"<pre>{message}</pre>", parse_mode=ParseMode.HTML)
self._send_msg(f"<pre>{message}</pre>", parse_mode=ParseMode.HTML,
reload_able=True, callback_path="update_status_table",
query=update.callback_query)
except RPCException as e:
self._send_msg(str(e))
@ -424,7 +461,8 @@ class Telegram(RPCHandler):
],
tablefmt='simple')
message = f'<b>Daily Profit over the last {timescale} days</b>:\n<pre>{stats_tab}</pre>'
self._send_msg(message, parse_mode=ParseMode.HTML)
self._send_msg(message, parse_mode=ParseMode.HTML, reload_able=True,
callback_path="update_daily", query=update.callback_query)
except RPCException as e:
self._send_msg(str(e))
@ -440,9 +478,20 @@ class Telegram(RPCHandler):
stake_cur = self._config['stake_currency']
fiat_disp_cur = self._config.get('fiat_display_currency', '')
start_date = datetime.fromtimestamp(0)
timescale = None
try:
if context.args:
timescale = int(context.args[0]) - 1
today_start = datetime.combine(date.today(), datetime.min.time())
start_date = today_start - timedelta(days=timescale)
except (TypeError, ValueError, IndexError):
pass
stats = self._rpc._rpc_trade_statistics(
stake_cur,
fiat_disp_cur)
fiat_disp_cur,
start_date)
profit_closed_coin = stats['profit_closed_coin']
profit_closed_percent_mean = stats['profit_closed_percent_mean']
profit_closed_percent_sum = stats['profit_closed_percent_sum']
@ -470,20 +519,23 @@ class Telegram(RPCHandler):
else:
markdown_msg = "`No closed trade` \n"
markdown_msg += (f"*ROI:* All trades\n"
f"∙ `{round_coin_value(profit_all_coin, stake_cur)} "
f"({profit_all_percent_mean:.2f}%) "
f"({profit_all_percent_sum} \N{GREEK CAPITAL LETTER SIGMA}%)`\n"
f"∙ `{round_coin_value(profit_all_fiat, fiat_disp_cur)}`\n"
f"*Total Trade Count:* `{trade_count}`\n"
f"*First Trade opened:* `{first_trade_date}`\n"
f"*Latest Trade opened:* `{latest_trade_date}\n`"
f"*Win / Loss:* `{stats['winning_trades']} / {stats['losing_trades']}`"
)
markdown_msg += (
f"*ROI:* All trades\n"
f"∙ `{round_coin_value(profit_all_coin, stake_cur)} "
f"({profit_all_percent_mean:.2f}%) "
f"({profit_all_percent_sum} \N{GREEK CAPITAL LETTER SIGMA}%)`\n"
f"∙ `{round_coin_value(profit_all_fiat, fiat_disp_cur)}`\n"
f"*Total Trade Count:* `{trade_count}`\n"
f"*{'First Trade opened' if not timescale else 'Showing Profit since'}:* "
f"`{first_trade_date}`\n"
f"*Latest Trade opened:* `{latest_trade_date}\n`"
f"*Win / Loss:* `{stats['winning_trades']} / {stats['losing_trades']}`"
)
if stats['closed_trade_count'] > 0:
markdown_msg += (f"\n*Avg. Duration:* `{avg_duration}`\n"
f"*Best Performing:* `{best_pair}: {best_rate:.2f}%`")
self._send_msg(markdown_msg)
self._send_msg(markdown_msg, reload_able=True, callback_path="update_profit",
query=update.callback_query)
@authorized_only
def _stats(self, update: Update, context: CallbackContext) -> None:
@ -559,7 +611,7 @@ class Telegram(RPCHandler):
curr_output = (f"*{curr['currency']}:* not showing <{balance_dust_level} "
f"{curr['stake']} amount \n")
# Handle overflowing messsage length
# Handle overflowing message length
if len(output + curr_output) >= MAX_TELEGRAM_MESSAGE_LENGTH:
self._send_msg(output)
output = curr_output
@ -570,7 +622,8 @@ class Telegram(RPCHandler):
f"\t`{result['stake']}: {result['total']: .8f}`\n"
f"\t`{result['symbol']}: "
f"{round_coin_value(result['value'], result['symbol'], False)}`\n")
self._send_msg(output)
self._send_msg(output, reload_able=True, callback_path="update_balance",
query=update.callback_query)
except RPCException as e:
self._send_msg(str(e))
@ -677,10 +730,10 @@ class Telegram(RPCHandler):
self._forcebuy_action(pair, price)
else:
whitelist = self._rpc._rpc_whitelist()['whitelist']
pairs = [InlineKeyboardButton(pair, callback_data=pair) for pair in whitelist]
self._send_inline_msg("Which pair?",
keyboard=self._layout_inline_keyboard(pairs),
callback_query_handler='forcebuy')
pairs = [InlineKeyboardButton(text=pair, callback_data=pair) for pair in whitelist]
self._send_msg(msg="Which pair?",
keyboard=self._layout_inline_keyboard(pairs))
@authorized_only
def _trades(self, update: Update, context: CallbackContext) -> None:
@ -764,7 +817,9 @@ class Telegram(RPCHandler):
else:
output += stat_line
self._send_msg(output, parse_mode=ParseMode.HTML)
self._send_msg(output, parse_mode=ParseMode.HTML,
reload_able=True, callback_path="update_performance",
query=update.callback_query)
except RPCException as e:
self._send_msg(str(e))
@ -784,7 +839,9 @@ class Telegram(RPCHandler):
tablefmt='simple')
message = "<pre>{}</pre>".format(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",
query=update.callback_query)
except RPCException as e:
self._send_msg(str(e))
@ -942,7 +999,8 @@ class Telegram(RPCHandler):
" `pending buy orders are marked with an asterisk (*)`\n"
" `pending sell orders are marked with a double asterisk (**)`\n"
"*/trades [limit]:* `Lists last closed trades (limited to 10 by default)`\n"
"*/profit:* `Lists cumulative profit from all finished trades`\n"
"*/profit [<n>]:* `Lists cumulative profit from all finished trades, "
"over the last n days`\n"
"*/forcesell <trade_id>|all:* `Instantly sells the given trade or all trades, "
"regardless of profit`\n"
f"{forcebuy_text if self._config.get('forcebuy_enable', False) else ''}"
@ -1015,29 +1073,42 @@ class Telegram(RPCHandler):
f"*Current state:* `{val['state']}`"
)
def _send_inline_msg(self, msg: str, callback_query_handler,
parse_mode: str = ParseMode.MARKDOWN, disable_notification: bool = False,
keyboard: List[List[InlineKeyboardButton]] = None, ) -> None:
"""
Send given markdown message
:param msg: message
:param bot: alternative bot
:param parse_mode: telegram parse mode
:return: None
"""
if self._current_callback_query_handler:
self._updater.dispatcher.remove_handler(self._current_callback_query_handler)
self._current_callback_query_handler = self._callback_query_handlers[callback_query_handler]
self._updater.dispatcher.add_handler(self._current_callback_query_handler)
def _update_msg(self, query: CallbackQuery, msg: str, callback_path: str = "",
reload_able: bool = False, parse_mode: str = ParseMode.MARKDOWN) -> None:
if reload_able:
reply_markup = InlineKeyboardMarkup([
[InlineKeyboardButton("Refresh", callback_data=callback_path)],
])
else:
reply_markup = InlineKeyboardMarkup([[]])
msg += "\nUpdated: {}".format(datetime.now().ctime())
if not query.message:
return
chat_id = query.message.chat_id
message_id = query.message.message_id
self._send_msg(msg, parse_mode, disable_notification,
cast(List[List[Union[str, KeyboardButton, InlineKeyboardButton]]], keyboard),
reply_markup=InlineKeyboardMarkup)
try:
self._updater.bot.edit_message_text(
chat_id=chat_id,
message_id=message_id,
text=msg,
parse_mode=parse_mode,
reply_markup=reply_markup
)
except BadRequest as e:
if 'not modified' in e.message.lower():
pass
else:
logger.warning('TelegramError: %s', e.message)
except TelegramError as telegram_err:
logger.warning('TelegramError: %s! Giving up on that message.', telegram_err.message)
def _send_msg(self, msg: str, parse_mode: str = ParseMode.MARKDOWN,
disable_notification: bool = False,
keyboard: List[List[Union[str, KeyboardButton, InlineKeyboardButton]]] = None,
reply_markup=ReplyKeyboardMarkup) -> None:
keyboard: List[List[InlineKeyboardButton]] = None,
callback_path: str = "",
reload_able: bool = False,
query: Optional[CallbackQuery] = None) -> None:
"""
Send given markdown message
:param msg: message
@ -1045,9 +1116,19 @@ class Telegram(RPCHandler):
:param parse_mode: telegram parse mode
:return: None
"""
if keyboard is None:
keyboard = self._keyboard
reply_markup = reply_markup(keyboard, resize_keyboard=True)
reply_markup: Union[InlineKeyboardMarkup, ReplyKeyboardMarkup]
if query:
self._update_msg(query=query, msg=msg, parse_mode=parse_mode,
callback_path=callback_path, reload_able=reload_able)
return
if reload_able and self._config['telegram'].get('reload', True):
reply_markup = InlineKeyboardMarkup([
[InlineKeyboardButton("Refresh", callback_data=callback_path)]])
else:
if keyboard is not None:
reply_markup = InlineKeyboardMarkup(keyboard, resize_keyboard=True)
else:
reply_markup = ReplyKeyboardMarkup(self._keyboard, resize_keyboard=True)
try:
try:
self._updater.bot.send_message(

18
freqtrade/rpc/webhook.py
View File

@ -6,7 +6,8 @@ from typing import Any, Dict
from requests import RequestException, post
from freqtrade.rpc import RPC, RPCHandler, RPCMessageType
from freqtrade.enums import RPCMessageType
from freqtrade.rpc import RPC, RPCHandler
logger = logging.getLogger(__name__)
@ -76,14 +77,13 @@ class Webhook(RPCHandler):
def _send_msg(self, payload: dict) -> None:
"""do the actual call to the webhook"""
if self._format == 'form':
kwargs = {'data': payload}
elif self._format == 'json':
kwargs = {'json': payload}
else:
raise NotImplementedError('Unknown format: {}'.format(self._format))
try:
post(self._url, **kwargs)
if self._format == 'form':
post(self._url, data=payload)
elif self._format == 'json':
post(self._url, json=payload)
else:
raise NotImplementedError('Unknown format: {}'.format(self._format))
except RequestException as exc:
logger.warning("Could not call webhook url. Exception: %s", exc)

30
freqtrade/strategy/hyper.py
View File

@ -14,8 +14,8 @@ with suppress(ImportError):
from skopt.space import Integer, Real, Categorical
from freqtrade.optimize.space import SKDecimal
from freqtrade.enums import RunMode
from freqtrade.exceptions import OperationalException
from freqtrade.state import RunMode
logger = logging.getLogger(__name__)
@ -242,7 +242,7 @@ class CategoricalParameter(BaseParameter):
class HyperStrategyMixin(object):
"""
A helper base class which allows HyperOptAuto class to reuse implementations of of buy/sell
A helper base class which allows HyperOptAuto class to reuse implementations of buy/sell
strategy logic.
"""
@ -258,7 +258,7 @@ class HyperStrategyMixin(object):
def enumerate_parameters(self, category: str = None) -> Iterator[Tuple[str, BaseParameter]]:
"""
Find all optimizeable parameters and return (name, attr) iterator.
Find all optimizable parameters and return (name, attr) iterator.
:param category:
:return:
"""
@ -273,11 +273,12 @@ class HyperStrategyMixin(object):
for par in params:
yield par.name, par
def _detect_parameters(self, category: str) -> Iterator[Tuple[str, BaseParameter]]:
@classmethod
def detect_parameters(cls, category: str) -> Iterator[Tuple[str, BaseParameter]]:
""" Detect all parameters for 'category' """
for attr_name in dir(self):
for attr_name in dir(cls):
if not attr_name.startswith('__'): # Ignore internals, not strictly necessary.
attr = getattr(self, attr_name)
attr = getattr(cls, attr_name)
if issubclass(attr.__class__, BaseParameter):
if (attr_name.startswith(category + '_')
and attr.category is not None and attr.category != category):
@ -287,6 +288,19 @@ class HyperStrategyMixin(object):
(attr_name.startswith(category + '_') and attr.category is None)):
yield attr_name, attr
@classmethod
def detect_all_parameters(cls) -> Dict:
""" Detect all parameters and return them as a list"""
params: Dict = {
'buy': list(cls.detect_parameters('buy')),
'sell': list(cls.detect_parameters('sell')),
}
params.update({
'count': len(params['buy'] + params['sell'])
})
return params
def _load_hyper_params(self, hyperopt: bool = False) -> None:
"""
Load Hyperoptable parameters
@ -296,14 +310,14 @@ class HyperStrategyMixin(object):
def _load_params(self, params: dict, space: str, hyperopt: bool = False) -> None:
"""
Set optimizeable parameter values.
Set optimizable parameter values.
:param params: Dictionary with new parameter values.
"""
if not params:
logger.info(f"No params for {space} found, using default values.")
param_container: List[BaseParameter] = getattr(self, f"ft_{space}_params")
for attr_name, attr in self._detect_parameters(space):
for attr_name, attr in self.detect_parameters(space):
attr.name = attr_name
attr.in_space = hyperopt and HyperoptTools.has_space(self.config, space)
if not attr.category:

80
freqtrade/strategy/interface.py
View File

@ -6,7 +6,6 @@ import logging
import warnings
from abc import ABC, abstractmethod
from datetime import datetime, timedelta, timezone
from enum import Enum
from typing import Dict, List, Optional, Tuple, Union
import arrow
@ -14,6 +13,7 @@ from pandas import DataFrame
from freqtrade.constants import ListPairsWithTimeframes
from freqtrade.data.dataprovider import DataProvider
from freqtrade.enums import SellType, SignalType
from freqtrade.exceptions import OperationalException, StrategyError
from freqtrade.exchange import timeframe_to_minutes, timeframe_to_seconds
from freqtrade.exchange.exchange import timeframe_to_next_date
@ -27,33 +27,6 @@ logger = logging.getLogger(__name__)
CUSTOM_SELL_MAX_LENGTH = 64
class SignalType(Enum):
"""
Enum to distinguish between buy and sell signals
"""
BUY = "buy"
SELL = "sell"
class SellType(Enum):
"""
Enum to distinguish between sell reasons
"""
ROI = "roi"
STOP_LOSS = "stop_loss"
STOPLOSS_ON_EXCHANGE = "stoploss_on_exchange"
TRAILING_STOP_LOSS = "trailing_stop_loss"
SELL_SIGNAL = "sell_signal"
FORCE_SELL = "force_sell"
EMERGENCY_SELL = "emergency_sell"
CUSTOM_SELL = "custom_sell"
NONE = ""
def __str__(self):
# explicitly convert to String to help with exporting data.
return self.value
class SellCheckTuple(object):
"""
NamedTuple for Sell type + reason
@ -134,7 +107,7 @@ class IStrategy(ABC, HyperStrategyMixin):
startup_candle_count: int = 0
# Protections
protections: List
protections: List = []
# Class level variables (intentional) containing
# the dataprovider (dp) (access to other candles, historic data, ...)
@ -297,7 +270,7 @@ class IStrategy(ABC, HyperStrategyMixin):
:param current_rate: Rate, calculated based on pricing settings in ask_strategy.
:param current_profit: Current profit (as ratio), calculated based on current_rate.
:param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
:return float: New stoploss value, relative to the currentrate
:return float: New stoploss value, relative to the current_rate
"""
return self.stoploss
@ -328,7 +301,7 @@ class IStrategy(ABC, HyperStrategyMixin):
def informative_pairs(self) -> ListPairsWithTimeframes:
"""
Define additional, informative pair/interval combinations to be cached from the exchange.
These pair/interval combinations are non-tradeable, unless they are part
These pair/interval combinations are non-tradable, unless they are part
of the whitelist as well.
For more information, please consult the documentation
:return: List of tuples in the format (pair, interval)
@ -376,7 +349,7 @@ class IStrategy(ABC, HyperStrategyMixin):
The 2nd, optional parameter ensures that locks are applied until the new candle arrives,
and not stop at 14:00:00 - while the next candle arrives at 14:00:02 leaving a gap
of 2 seconds for a buy to happen on an old signal.
:param: pair: "Pair to check"
:param pair: "Pair to check"
:param candle_date: Date of the last candle. Optional, defaults to current date
:returns: locking state of the pair in question.
"""
@ -480,18 +453,25 @@ class IStrategy(ABC, HyperStrategyMixin):
"""
Ensure dataframe (length, last candle) was not modified, and has all elements we need.
"""
message_template = "Dataframe returned from strategy has mismatching {}."
message = ""
if df_len != len(dataframe):
message = "length"
if dataframe is None:
message = "No dataframe returned (return statement missing?)."
elif 'buy' not in dataframe:
message = "Buy column not set."
elif 'sell' not in dataframe:
message = "Sell column not set."
elif df_len != len(dataframe):
message = message_template.format("length")
elif df_close != dataframe["close"].iloc[-1]:
message = "last close price"
message = message_template.format("last close price")
elif df_date != dataframe["date"].iloc[-1]:
message = "last date"
message = message_template.format("last date")
if message:
if self.disable_dataframe_checks:
logger.warning(f"Dataframe returned from strategy has mismatching {message}.")
logger.warning(message)
else:
raise StrategyError(f"Dataframe returned from strategy has mismatching {message}.")
raise StrategyError(message)
def get_signal(self, pair: str, timeframe: str, dataframe: DataFrame) -> Tuple[bool, bool]:
"""
@ -551,15 +531,14 @@ class IStrategy(ABC, HyperStrategyMixin):
:param force_stoploss: Externally provided stoploss
:return: True if trade should be sold, False otherwise
"""
# Set current rate to low for backtesting sell
current_rate = low or rate
current_rate = rate
current_profit = trade.calc_profit_ratio(current_rate)
trade.adjust_min_max_rates(high or current_rate)
stoplossflag = self.stop_loss_reached(current_rate=current_rate, trade=trade,
current_time=date, current_profit=current_profit,
force_stoploss=force_stoploss, high=high)
force_stoploss=force_stoploss, low=low, high=high)
# Set current rate to high for backtesting sell
current_rate = high or rate
@ -626,18 +605,21 @@ class IStrategy(ABC, HyperStrategyMixin):
def stop_loss_reached(self, current_rate: float, trade: Trade,
current_time: datetime, current_profit: float,
force_stoploss: float, high: float = None) -> SellCheckTuple:
force_stoploss: float, low: float = None,
high: float = None) -> SellCheckTuple:
"""
Based on current profit of the trade and configured (trailing) stoploss,
decides to sell or not
:param current_profit: current profit as ratio
:param low: Low value of this candle, only set in backtesting
:param high: High value of this candle, only set in backtesting
"""
stop_loss_value = force_stoploss if force_stoploss else self.stoploss
# Initiate stoploss with open_rate. Does nothing if stoploss is already set.
trade.adjust_stop_loss(trade.open_rate, stop_loss_value, initial=True)
if self.use_custom_stoploss:
if self.use_custom_stoploss and trade.stop_loss < (low or current_rate):
stop_loss_value = strategy_safe_wrapper(self.custom_stoploss, default_retval=None
)(pair=trade.pair, trade=trade,
current_time=current_time,
@ -650,7 +632,7 @@ class IStrategy(ABC, HyperStrategyMixin):
else:
logger.warning("CustomStoploss function did not return valid stoploss")
if self.trailing_stop:
if self.trailing_stop and trade.stop_loss < (low or current_rate):
# trailing stoploss handling
sl_offset = self.trailing_stop_positive_offset
@ -670,7 +652,7 @@ class IStrategy(ABC, HyperStrategyMixin):
# evaluate if the stoploss was hit if stoploss is not on exchange
# in Dry-Run, this handles stoploss logic as well, as the logic will not be different to
# regular stoploss handling.
if ((trade.stop_loss >= current_rate) and
if ((trade.stop_loss >= (low or current_rate)) and
(not self.order_types.get('stoploss_on_exchange') or self.config['dry_run'])):
sell_type = SellType.STOP_LOSS
@ -679,7 +661,7 @@ class IStrategy(ABC, HyperStrategyMixin):
if trade.initial_stop_loss != trade.stop_loss:
sell_type = SellType.TRAILING_STOP_LOSS
logger.debug(
f"{trade.pair} - HIT STOP: current price at {current_rate:.6f}, "
f"{trade.pair} - HIT STOP: current price at {(low or current_rate):.6f}, "
f"stoploss is {trade.stop_loss:.6f}, "
f"initial stoploss was at {trade.initial_stop_loss:.6f}, "
f"trade opened at {trade.open_rate:.6f}")
@ -751,7 +733,8 @@ class IStrategy(ABC, HyperStrategyMixin):
Based on TA indicators, populates the buy signal for the given dataframe
This method should not be overridden.
:param dataframe: DataFrame
:param pair: Additional information, like the currently traded pair
:param metadata: Additional information dictionary, with details like the
currently traded pair
:return: DataFrame with buy column
"""
logger.debug(f"Populating buy signals for pair {metadata.get('pair')}.")
@ -768,7 +751,8 @@ class IStrategy(ABC, HyperStrategyMixin):
Based on TA indicators, populates the sell signal for the given dataframe
This method should not be overridden.
:param dataframe: DataFrame
:param pair: Additional information, like the currently traded pair
:param metadata: Additional information dictionary, with details like the
currently traded pair
:return: DataFrame with sell column
"""
logger.debug(f"Populating sell signals for pair {metadata.get('pair')}.")

2
freqtrade/templates/sample_strategy.py
View File

@ -329,7 +329,7 @@ class SampleStrategy(IStrategy):
"""
# first check if dataprovider is available
if self.dp:
if self.dp.runmode in ('live', 'dry_run'):
if self.dp.runmode.value in ('live', 'dry_run'):
ob = self.dp.orderbook(metadata['pair'], 1)
dataframe['best_bid'] = ob['bids'][0][0]
dataframe['best_ask'] = ob['asks'][0][0]

2
freqtrade/templates/subtemplates/indicators_full.j2
View File

@ -199,7 +199,7 @@ dataframe['htleadsine'] = hilbert['leadsine']
"""
# first check if dataprovider is available
if self.dp:
if self.dp.runmode in ('live', 'dry_run'):
if self.dp.runmode.value in ('live', 'dry_run'):
ob = self.dp.orderbook(metadata['pair'], 1)
dataframe['best_bid'] = ob['bids'][0][0]
dataframe['best_ask'] = ob['asks'][0][0]

2
freqtrade/templates/subtemplates/indicators_minimal.j2
View File

@ -10,7 +10,7 @@ dataframe['rsi'] = ta.RSI(dataframe)
"""
# first check if dataprovider is available
if self.dp:
if self.dp.runmode in ('live', 'dry_run'):
if self.dp.runmode.value in ('live', 'dry_run'):
ob = self.dp.orderbook(metadata['pair'], 1)
dataframe['best_bid'] = ob['bids'][0][0]
dataframe['best_ask'] = ob['asks'][0][0]

2
freqtrade/wallets.py
View File

@ -8,10 +8,10 @@ from typing import Any, Dict, NamedTuple
import arrow
from freqtrade.constants import UNLIMITED_STAKE_AMOUNT
from freqtrade.enums import RunMode
from freqtrade.exceptions import DependencyException
from freqtrade.exchange import Exchange
from freqtrade.persistence import LocalTrade, Trade
from freqtrade.state import RunMode
logger = logging.getLogger(__name__)

4
freqtrade/worker.py
View File

@ -11,9 +11,9 @@ import sdnotify
from freqtrade import __version__, constants
from freqtrade.configuration import Configuration
from freqtrade.enums import State
from freqtrade.exceptions import OperationalException, TemporaryError
from freqtrade.freqtradebot import FreqtradeBot
from freqtrade.state import State
logger = logging.getLogger(__name__)
@ -61,7 +61,7 @@ class Worker:
def _notify(self, message: str) -> None:
"""
Removes the need to verify in all occurances if sd_notify is enabled
Removes the need to verify in all occurrences if sd_notify is enabled
:param message: Message to send to systemd if it's enabled.
"""
if self._sd_notify:

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