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Merge branch 'develop' into feat/kevinjulian/add-buy-signal-name

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33
.devcontainer/devcontainer.json
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@ -1,11 +1,20 @@
{
"name": "freqtrade Develop",
"dockerComposeFile": [
"docker-compose.yml"
"build": {
"dockerfile": "Dockerfile",
"context": ".."
},
// Use 'forwardPorts' to make a list of ports inside the container available locally.
"forwardPorts": [
8080
],
"mounts": [
"source=freqtrade-bashhistory,target=/home/ftuser/commandhistory,type=volume"
],
// Uncomment to connect as a non-root user if you've added one. See https://aka.ms/vscode-remote/containers/non-root.
"remoteUser": "ftuser",
"service": "ft_vscode",
"postCreateCommand": "freqtrade create-userdir --userdir user_data/",
"workspaceFolder": "/freqtrade/",
@ -25,20 +34,6 @@
"ms-python.vscode-pylance",
"davidanson.vscode-markdownlint",
"ms-azuretools.vscode-docker",
"vscode-icons-team.vscode-icons",
],
// Use 'forwardPorts' to make a list of ports inside the container available locally.
// "forwardPorts": [],
// Uncomment the next line if you want start specific services in your Docker Compose config.
// "runServices": [],
// Uncomment the next line if you want to keep your containers running after VS Code shuts down.
// "shutdownAction": "none",
// Uncomment the next line to run commands after the container is created - for example installing curl.
// "postCreateCommand": "sudo apt-get update && apt-get install -y git",
// Uncomment to connect as a non-root user if you've added one. See https://aka.ms/vscode-remote/containers/non-root.
"remoteUser": "ftuser"
}

24
.devcontainer/docker-compose.yml
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@ -1,24 +0,0 @@
---
version: '3'
services:
ft_vscode:
build:
context: ..
dockerfile: ".devcontainer/Dockerfile"
volumes:
# Allow git usage within container
- "${HOME}/.ssh:/home/ftuser/.ssh:ro"
- "${HOME}/.gitconfig:/home/ftuser/.gitconfig:ro"
- ..:/freqtrade:cached
# Persist bash-history
- freqtrade-vscode-server:/home/ftuser/.vscode-server
- freqtrade-bashhistory:/home/ftuser/commandhistory
# Expose API port
ports:
- "127.0.0.1:8080:8080"
command: /bin/sh -c "while sleep 1000; do :; done"
volumes:
freqtrade-vscode-server:
freqtrade-bashhistory:

41
.github/workflows/ci.yml vendored
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@ -79,13 +79,13 @@ jobs:
- name: Backtesting
run: |
cp config_bittrex.json.example config.json
cp config_examples/config_bittrex.example.json config.json
freqtrade create-userdir --userdir user_data
freqtrade backtesting --datadir tests/testdata --strategy SampleStrategy
- name: Hyperopt
run: |
cp config_bittrex.json.example config.json
cp config_examples/config_bittrex.example.json config.json
freqtrade create-userdir --userdir user_data
freqtrade hyperopt --datadir tests/testdata -e 5 --strategy SampleStrategy --hyperopt SampleHyperOpt --hyperopt-loss SharpeHyperOptLossDaily --print-all
@ -172,13 +172,13 @@ jobs:
- name: Backtesting
run: |
cp config_bittrex.json.example config.json
cp config_examples/config_bittrex.example.json config.json
freqtrade create-userdir --userdir user_data
freqtrade backtesting --datadir tests/testdata --strategy SampleStrategy
- name: Hyperopt
run: |
cp config_bittrex.json.example config.json
cp config_examples/config_bittrex.example.json config.json
freqtrade create-userdir --userdir user_data
freqtrade hyperopt --datadir tests/testdata -e 5 --strategy SampleStrategy --hyperopt SampleHyperOpt --hyperopt-loss SharpeHyperOptLossDaily --print-all
@ -239,13 +239,13 @@ jobs:
- name: Backtesting
run: |
cp config_bittrex.json.example config.json
cp config_examples/config_bittrex.example.json config.json
freqtrade create-userdir --userdir user_data
freqtrade backtesting --datadir tests/testdata --strategy SampleStrategy
- name: Hyperopt
run: |
cp config_bittrex.json.example config.json
cp config_examples/config_bittrex.example.json config.json
freqtrade create-userdir --userdir user_data
freqtrade hyperopt --datadir tests/testdata -e 5 --strategy SampleStrategy --hyperopt SampleHyperOpt --hyperopt-loss SharpeHyperOptLossDaily --print-all
@ -334,6 +334,7 @@ jobs:
runs-on: ubuntu-20.04
if: (github.event_name == 'push' || github.event_name == 'schedule' || github.event_name == 'release') && github.repository == 'freqtrade/freqtrade'
steps:
- uses: actions/checkout@v2
@ -411,3 +412,31 @@ jobs:
channel: '#notifications'
url: ${{ secrets.SLACK_WEBHOOK }}
deploy_arm:
needs: [ deploy ]
# Only run on 64bit machines
runs-on: [self-hosted, linux, ARM64]
if: (github.event_name == 'push' || github.event_name == 'schedule' || github.event_name == 'release') && github.repository == 'freqtrade/freqtrade'
steps:
- uses: actions/checkout@v2
- name: Extract branch name
shell: bash
run: echo "##[set-output name=branch;]$(echo ${GITHUB_REF##*/})"
id: extract_branch
- name: Dockerhub login
env:
DOCKER_PASSWORD: ${{ secrets.DOCKER_PASSWORD }}
DOCKER_USERNAME: ${{ secrets.DOCKER_USERNAME }}
run: |
echo "${DOCKER_PASSWORD}" | docker login --username ${DOCKER_USERNAME} --password-stdin
- name: Build and test and push docker images
env:
IMAGE_NAME: freqtradeorg/freqtrade
BRANCH_NAME: ${{ steps.extract_branch.outputs.branch }}
run: |
build_helpers/publish_docker_arm64.sh

5
.gitignore vendored
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@ -95,3 +95,8 @@ target/
#exceptions
!*.gitkeep
!config_examples/config_binance.example.json
!config_examples/config_bittrex.example.json
!config_examples/config_ftx.example.json
!config_examples/config_full.example.json
!config_examples/config_kraken.example.json

4
.travis.yml
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@ -26,12 +26,12 @@ jobs:
# - coveralls || true
name: pytest
- script:
- cp config_bittrex.json.example config.json
- cp config_examples/config_bittrex.example.json config.json
- freqtrade create-userdir --userdir user_data
- freqtrade backtesting --datadir tests/testdata --strategy SampleStrategy
name: backtest
- script:
- cp config_bittrex.json.example config.json
- cp config_examples/config_bittrex.example.json config.json
- freqtrade create-userdir --userdir user_data
- freqtrade hyperopt --datadir tests/testdata -e 5 --strategy SampleStrategy --hyperopt SampleHyperOpt --hyperopt-loss SharpeHyperOptLossDaily
name: hyperopt

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/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.
If you are unsure, discuss the feature on our [discord server](https://discord.gg/p7nuUNVfP7) or in a [issue](https://github.com/freqtrade/freqtrade/issues) before a Pull Request.
## Getting started

10
README.md
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@ -142,13 +142,9 @@ The project is currently setup in two main branches:
## Support
### Help / Discord / Slack
### Help / Discord
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/p7nuUNVfP7).
You can also join our [Slack channel](https://join.slack.com/t/highfrequencybot/shared_invite/zt-mm786y93-Fxo37glxMY9g8OQC5AoOIw).
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 the Freqtrade [discord server](https://discord.gg/p7nuUNVfP7).
### [Bugs / Issues](https://github.com/freqtrade/freqtrade/issues?q=is%3Aissue)
@ -179,7 +175,7 @@ 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/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.
**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) (please use the #dev channel for this). 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`.

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7
build_helpers/install_windows.ps1
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@ -6,10 +6,13 @@ python -m pip install --upgrade pip
$pyv = python -c "import sys; print(f'{sys.version_info.major}.{sys.version_info.minor}')"
if ($pyv -eq '3.7') {
pip install build_helpers\TA_Lib-0.4.20-cp37-cp37m-win_amd64.whl
pip install build_helpers\TA_Lib-0.4.21-cp37-cp37m-win_amd64.whl
}
if ($pyv -eq '3.8') {
pip install build_helpers\TA_Lib-0.4.20-cp38-cp38-win_amd64.whl
pip install build_helpers\TA_Lib-0.4.21-cp38-cp38-win_amd64.whl
}
if ($pyv -eq '3.9') {
pip install build_helpers\TA_Lib-0.4.21-cp39-cp39-win_amd64.whl
}
pip install -r requirements-dev.txt

80
build_helpers/publish_docker_arm64.sh Executable file
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@ -0,0 +1,80 @@
#!/bin/sh
# Use BuildKit, otherwise building on ARM fails
export DOCKER_BUILDKIT=1
# Replace / with _ to create a valid tag
TAG=$(echo "${BRANCH_NAME}" | sed -e "s/\//_/g")
TAG_PLOT=${TAG}_plot
TAG_PI="${TAG}_pi"
TAG_ARM=${TAG}_arm
TAG_PLOT_ARM=${TAG_PLOT}_arm
CACHE_IMAGE=freqtradeorg/freqtrade_cache
echo "Running for ${TAG}"
# Add commit and commit_message to docker container
echo "${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_ARM} .
else
echo "event ${GITHUB_EVENT_NAME}: building with cache"
# Build regular image
docker pull ${IMAGE_NAME}:${TAG_ARM}
docker build --cache-from ${IMAGE_NAME}:${TAG_ARM} -t freqtrade:${TAG_ARM} .
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_ARM ${CACHE_IMAGE}:$TAG_ARM
docker build --cache-from freqtrade:${TAG_ARM} --build-arg sourceimage=${TAG_ARM} -t freqtrade:${TAG_PLOT_ARM} -f docker/Dockerfile.plot .
docker tag freqtrade:$TAG_PLOT_ARM ${CACHE_IMAGE}:$TAG_PLOT_ARM
# Run backtest
docker run --rm -v $(pwd)/config_examples/config_bittrex.example.json:/freqtrade/config.json:ro -v $(pwd)/tests:/tests freqtrade:${TAG_ARM} backtesting --datadir /tests/testdata --strategy-path /tests/strategy/strats/ --strategy DefaultStrategy
if [ $? -ne 0 ]; then
echo "failed running backtest"
return 1
fi
docker images
# docker push ${IMAGE_NAME}
docker push ${CACHE_IMAGE}:$TAG_PLOT_ARM
docker push ${CACHE_IMAGE}:$TAG_ARM
# Create multi-arch image
# Make sure that all images contained here are pushed to github first.
# Otherwise installation might fail.
echo "create manifests"
docker manifest create --amend ${IMAGE_NAME}:${TAG} ${CACHE_IMAGE}:${TAG_ARM} ${IMAGE_NAME}:${TAG_PI} ${CACHE_IMAGE}:${TAG}
docker manifest push -p ${IMAGE_NAME}:${TAG}
docker manifest create --amend ${IMAGE_NAME}:${TAG_PLOT} ${CACHE_IMAGE}:${TAG_PLOT_ARM} ${CACHE_IMAGE}:${TAG_PLOT}
docker manifest push -p ${IMAGE_NAME}:${TAG_PLOT}
Tag as latest for develop builds
if [ "${TAG}" = "develop" ]; then
docker tag ${IMAGE_NAME}:develop ${IMAGE_NAME}:latest
docker push ${IMAGE_NAME}:latest
fi
docker images
if [ $? -ne 0 ]; then
echo "failed building image"
return 1
fi

28
build_helpers/publish_docker_multi.sh
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@ -9,7 +9,8 @@ TAG_PI="${TAG}_pi"
PI_PLATFORM="linux/arm/v7"
echo "Running for ${TAG}"
CACHE_TAG=freqtradeorg/freqtrade_cache:${TAG}_cache
CACHE_IMAGE=freqtradeorg/freqtrade_cache
CACHE_TAG=${CACHE_IMAGE}:${TAG_PI}_cache
# Add commit and commit_message to docker container
echo "${GITHUB_SHA}" > freqtrade_commit
@ -45,14 +46,14 @@ if [ $? -ne 0 ]; then
return 1
fi
# Tag image for upload and next build step
docker tag freqtrade:$TAG ${IMAGE_NAME}:$TAG
docker tag freqtrade:$TAG ${CACHE_IMAGE}:$TAG
docker build --cache-from freqtrade:${TAG} --build-arg sourceimage=${TAG} -t freqtrade:${TAG_PLOT} -f docker/Dockerfile.plot .
docker tag freqtrade:$TAG_PLOT ${IMAGE_NAME}:$TAG_PLOT
docker tag freqtrade:$TAG_PLOT ${CACHE_IMAGE}:$TAG_PLOT
# 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
docker run --rm -v $(pwd)/config_examples/config_bittrex.example.json:/freqtrade/config.json:ro -v $(pwd)/tests:/tests freqtrade:${TAG} backtesting --datadir /tests/testdata --strategy-path /tests/strategy/strats/ --strategy DefaultStrategy
if [ $? -ne 0 ]; then
echo "failed running backtest"
@ -61,22 +62,9 @@ fi
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 push ${CACHE_IMAGE}
docker push ${CACHE_IMAGE}:$TAG_PLOT
docker push ${CACHE_IMAGE}:$TAG
docker images

0
config_binance.json.example → config_examples/config_binance.example.json
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0
config_bittrex.json.example → config_examples/config_bittrex.example.json
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0
config_ftx.json.example → config_examples/config_ftx.example.json
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0
config_full.json.example → config_examples/config_full.example.json
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0
config_kraken.json.example → config_examples/config_kraken.example.json
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4
docs/advanced-hyperopt.md
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@ -32,6 +32,7 @@ class SuperDuperHyperOptLoss(IHyperOptLoss):
def hyperopt_loss_function(results: DataFrame, trade_count: int,
min_date: datetime, max_date: datetime,
config: Dict, processed: Dict[str, DataFrame],
backtest_stats: Dict[str, Any],
*args, **kwargs) -> float:
"""
Objective function, returns smaller number for better results
@ -53,7 +54,7 @@ class SuperDuperHyperOptLoss(IHyperOptLoss):
Currently, the arguments are:
* `results`: DataFrame containing the result
* `results`: DataFrame containing the resulting trades.
The following columns are available in results (corresponds to the output-file of backtesting when used with `--export trades`):
`pair, profit_ratio, profit_abs, open_date, open_rate, fee_open, close_date, close_rate, fee_close, amount, trade_duration, is_open, sell_reason, stake_amount, min_rate, max_rate, stop_loss_ratio, stop_loss_abs`
* `trade_count`: Amount of trades (identical to `len(results)`)
@ -61,6 +62,7 @@ Currently, the arguments are:
* `min_date`: End date of the timerange used
* `config`: Config object used (Note: Not all strategy-related parameters will be updated here if they are part of a hyperopt space).
* `processed`: Dict of Dataframes with the pair as keys containing the data used for backtesting.
* `backtest_stats`: Backtesting statistics using the same format as the backtesting file "strategy" substructure. Available fields can be seen in `generate_strategy_stats()` in `optimize_reports.py`.
This function needs to return a floating point number (`float`). Smaller numbers will be interpreted as better results. The parameters and balancing for this is up to you.

3
docs/backtesting.md
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@ -302,7 +302,6 @@ A backtesting result will look like that:
| Days win/draw/lose | 12 / 82 / 25 |
| Avg. Duration Winners | 4:23:00 |
| Avg. Duration Loser | 6:55:00 |
| Zero Duration Trades | 4.6% (20) |
| Rejected Buy signals | 3089 |
| | |
| Min balance | 0.00945123 BTC |
@ -390,7 +389,6 @@ It contains some useful key metrics about performance of your strategy on backte
| Days win/draw/lose | 12 / 82 / 25 |
| Avg. Duration Winners | 4:23:00 |
| Avg. Duration Loser | 6:55:00 |
| Zero Duration Trades | 4.6% (20) |
| Rejected Buy signals | 3089 |
| | |
| Min balance | 0.00945123 BTC |
@ -420,7 +418,6 @@ It contains some useful key metrics about performance of your strategy on backte
- `Best day` / `Worst day`: Best and worst day based on daily profit.
- `Days win/draw/lose`: Winning / Losing days (draws are usually days without closed trade).
- `Avg. Duration Winners` / `Avg. Duration Loser`: Average durations for winning and losing trades.
- `Zero Duration Trades`: A number of trades that completed within same candle as they opened and had `trailing_stop_loss` sell reason. A significant amount of such trades may indicate that strategy is exploiting trailing stoploss behavior in backtesting and produces unrealistic results.
- `Rejected Buy signals`: Buy signals that could not be acted upon due to max_open_trades being reached.
- `Min balance` / `Max balance`: Lowest and Highest Wallet balance during the backtest period.
- `Drawdown`: Maximum drawdown experienced. For example, the value of 50% means that from highest to subsequent lowest point, a 50% drop was experienced).

23
docs/configuration.md
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@ -52,6 +52,7 @@ Mandatory parameters are marked as **Required**, which means that they are requi
| `stake_currency` | **Required.** Crypto-currency used for trading. <br> **Datatype:** String
| `stake_amount` | **Required.** Amount of crypto-currency your bot will use for each trade. Set it to `"unlimited"` to allow the bot to use all available balance. [More information below](#configuring-amount-per-trade). <br> **Datatype:** Positive float or `"unlimited"`.
| `tradable_balance_ratio` | Ratio of the total account balance the bot is allowed to trade. [More information below](#configuring-amount-per-trade). <br>*Defaults to `0.99` 99%).*<br> **Datatype:** Positive float between `0.1` and `1.0`.
| `available_capital` | Available starting capital for the bot. Useful when running multiple bots on the same exchange account.[More information below](#configuring-amount-per-trade). <br> **Datatype:** Positive float.
| `amend_last_stake_amount` | Use reduced last stake amount if necessary. [More information below](#configuring-amount-per-trade). <br>*Defaults to `false`.* <br> **Datatype:** Boolean
| `last_stake_amount_min_ratio` | Defines minimum stake amount that has to be left and executed. Applies only to the last stake amount when it's amended to a reduced value (i.e. if `amend_last_stake_amount` is set to `true`). [More information below](#configuring-amount-per-trade). <br>*Defaults to `0.5`.* <br> **Datatype:** Float (as ratio)
| `amount_reserve_percent` | Reserve some amount in min pair stake amount. The bot will reserve `amount_reserve_percent` + stoploss value when calculating min pair stake amount in order to avoid possible trade refusals. <br>*Defaults to `0.05` (5%).* <br> **Datatype:** Positive Float as ratio.
@ -164,7 +165,7 @@ Values set in the configuration file always overwrite values set in the strategy
### Configuring amount per trade
There are several methods to configure how much of the stake currency the bot will use to enter a trade. All methods respect the [available balance configuration](#available-balance) as explained below.
There are several methods to configure how much of the stake currency the bot will use to enter a trade. All methods respect the [available balance configuration](#tradable-balance) as explained below.
#### Minimum trade stake
@ -183,7 +184,7 @@ To limit this calculation in case of large stoploss values, the calculated minim
!!! Warning
Since the limits on exchanges are usually stable and are not updated often, some pairs can show pretty high minimum limits, simply because the price increased a lot since the last limit adjustment by the exchange.
#### Available balance
#### Tradable balance
By default, the bot assumes that the `complete amount - 1%` is at it's disposal, and when using [dynamic stake amount](#dynamic-stake-amount), it will split the complete balance into `max_open_trades` buckets per trade.
Freqtrade will reserve 1% for eventual fees when entering a trade and will therefore not touch that by default.
@ -192,9 +193,25 @@ You can configure the "untouched" amount by using the `tradable_balance_ratio` s
For example, if you have 10 ETH available in your wallet on the exchange and `tradable_balance_ratio=0.5` (which is 50%), then the bot will use a maximum amount of 5 ETH for trading and considers this as available balance. The rest of the wallet is untouched by the trades.
!!! Danger
This setting should **not** be used when running multiple bots on the same account. Please look at [Available Capital to the bot](#assign-available-capital) instead.
!!! Warning
The `tradable_balance_ratio` setting applies to the current balance (free balance + tied up in trades). Therefore, assuming the starting balance of 1000, a configuration with `tradable_balance_ratio=0.99` will not guarantee that 10 currency units will always remain available on the exchange. For example, the free amount may reduce to 5 units if the total balance is reduced to 500 (either by a losing streak, or by withdrawing balance).
#### Assign available Capital
To fully utilize compounding profits when using multiple bots on the same exchange account, you'll want to limit each bot to a certain starting balance.
This can be accomplished by setting `available_capital` to the desired starting balance.
Assuming your account has 10.000 USDT and you want to run 2 different strategies on this exchange.
You'd set `available_capital=5000` - granting each bot an initial capital of 5000 USDT.
The bot will then split this starting balance equally into `max_open_trades` buckets.
Profitable trades will result in increased stake-sizes for this bot - without affecting stake-sizes of the other bot.
!!! Warning "Incompatible with `tradable_balance_ratio`"
Setting this option will replace any configuration of `tradable_balance_ratio`.
#### Amend last stake amount
Assuming we have the tradable balance of 1000 USDT, `stake_amount=400`, and `max_open_trades=3`.
@ -556,7 +573,7 @@ You should also make sure to read the [Exchanges](exchanges.md) section of the d
To use a proxy with freqtrade, add the kwarg `"aiohttp_trust_env"=true` to the `"ccxt_async_kwargs"` dict in the exchange section of the configuration.
An example for this can be found in `config_full.json.example`
An example for this can be found in `config_examples/config_full.example.json`
``` json
"ccxt_async_config": {

2
docs/developer.md
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@ -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/p7nuUNVfP7) 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) where you can ask questions.
## Documentation

2
docs/faq.md
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@ -172,7 +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/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.
* Discovering a great strategy with Hyperopt takes time. Study www.freqtrade.io, the Freqtrade Documentation page, join 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:

16
docs/hyperopt.md
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@ -51,7 +51,7 @@ usage: freqtrade hyperopt [-h] [-v] [--logfile FILE] [-V] [-c PATH] [-d PATH]
[--spaces {all,buy,sell,roi,stoploss,trailing,default} [{all,buy,sell,roi,stoploss,trailing,default} ...]]
[--print-all] [--no-color] [--print-json] [-j JOBS]
[--random-state INT] [--min-trades INT]
[--hyperopt-loss NAME]
[--hyperopt-loss NAME] [--disable-param-export]
optional arguments:
-h, --help show this help message and exit
@ -118,6 +118,8 @@ optional arguments:
ShortTradeDurHyperOptLoss, OnlyProfitHyperOptLoss,
SharpeHyperOptLoss, SharpeHyperOptLossDaily,
SortinoHyperOptLoss, SortinoHyperOptLossDaily
--disable-param-export
Disable automatic hyperopt parameter export.
Common arguments:
-v, --verbose Verbose mode (-vv for more, -vvv to get all messages).
@ -512,7 +514,13 @@ You should understand this result like:
* You should not use ADX because `'buy_adx_enabled': False`.
* You should **consider** using the RSI indicator (`'buy_rsi_enabled': True`) and the best value is `29.0` (`'buy_rsi': 29.0`)
Your strategy class can immediately take advantage of these results. Simply copy hyperopt results block and paste them at class level, replacing old parameters (if any). New parameters will automatically be loaded next time strategy is executed.
### Automatic parameter application to the strategy
When using Hyperoptable parameters, the result of your hyperopt-run will be written to a json file next to your strategy (so for `MyAwesomeStrategy.py`, the file would be `MyAwesomeStrategy.json`).
This file is also updated when using the `hyperopt-show` sub-command, unless `--disable-param-export` is provided to either of the 2 commands.
Your strategy class can also contain these results explicitly. Simply copy hyperopt results block and paste them at class level, replacing old parameters (if any). New parameters will automatically be loaded next time strategy is executed.
Transferring your whole hyperopt result to your strategy would then look like:
@ -528,6 +536,10 @@ class MyAwesomeStrategy(IStrategy):
}
```
!!! Note
Values in the configuration file will overwrite Parameter-file level parameters - and both will overwrite parameters within the strategy.
The prevalence is therefore: config > parameter file > strategy
### Understand Hyperopt ROI results
If you are optimizing ROI (i.e. if optimization search-space contains 'all', 'default' or 'roi'), your result will look as follows and include a ROI table:

76
docs/includes/pairlists.md
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@ -23,6 +23,7 @@ You may also use something like `.*DOWN/BTC` or `.*UP/BTC` to exclude leveraged
* [`StaticPairList`](#static-pair-list) (default, if not configured differently)
* [`VolumePairList`](#volume-pair-list)
* [`AgeFilter`](#agefilter)
* [`OffsetFilter`](#offsetfilter)
* [`PerformanceFilter`](#performancefilter)
* [`PrecisionFilter`](#precisionfilter)
* [`PriceFilter`](#pricefilter)
@ -63,17 +64,56 @@ The `refresh_period` setting allows to define the period (in seconds), at which
The pairlist cache (`refresh_period`) on `VolumePairList` is only applicable to generating pairlists.
Filtering instances (not the first position in the list) will not apply any cache and will always use up-to-date data.
`VolumePairList` is based on the ticker data from exchange, as reported by the ccxt library:
`VolumePairList` is per default based on the ticker data from exchange, as reported by the ccxt library:
* The `quoteVolume` is the amount of quote (stake) currency traded (bought or sold) in last 24 hours.
```json
"pairlists": [{
"pairlists": [
{
"method": "VolumePairList",
"number_assets": 20,
"sort_key": "quoteVolume",
"refresh_period": 1800
}],
}
],
```
`VolumePairList` can also operate in an advanced mode to build volume over a given timerange of specified candle size. It utilizes exchange historical candle data, builds a typical price (calculated by (open+high+low)/3) and multiplies the typical price with every candle's volume. The sum is the `quoteVolume` over the given range. This allows different scenarios, for a more smoothened volume, when using longer ranges with larger candle sizes, or the opposite when using a short range with small candles.
For convenience `lookback_days` can be specified, which will imply that 1d candles will be used for the lookback. In the example below the pairlist would be created based on the last 7 days:
```json
"pairlists": [
{
"method": "VolumePairList",
"number_assets": 20,
"sort_key": "quoteVolume",
"refresh_period": 86400,
"lookback_days": 7
}
],
```
!!! Warning "Range look back and refresh period"
When used in conjunction with `lookback_days` and `lookback_timeframe` the `refresh_period` can not be smaller than the candle size in seconds. As this will result in unnecessary requests to the exchanges API.
!!! Warning "Performance implications when using lookback range"
If used in first position in combination with lookback, the computation of the range based volume can be time and resource consuming, as it downloads candles for all tradable pairs. Hence it's highly advised to use the standard approach with `VolumeFilter` to narrow the pairlist down for further range volume calculation.
More sophisticated approach can be used, by using `lookback_timeframe` for candle size and `lookback_period` which specifies the amount of candles. This example will build the volume pairs based on a rolling period of 3 days of 1h candles:
```json
"pairlists": [
{
"method": "VolumePairList",
"number_assets": 20,
"sort_key": "quoteVolume",
"refresh_period": 3600,
"lookback_timeframe": "1h",
"lookback_period": 72
}
],
```
!!! Note
@ -81,13 +121,39 @@ Filtering instances (not the first position in the list) will not apply any cach
#### AgeFilter
Removes pairs that have been listed on the exchange for less than `min_days_listed` days (defaults to `10`).
Removes pairs that have been listed on the exchange for less than `min_days_listed` days (defaults to `10`) or more than `max_days_listed` days (defaults `None` mean infinity).
When pairs are first listed on an exchange they can suffer huge price drops and volatility
in the first few days while the pair goes through its price-discovery period. Bots can often
be caught out buying before the pair has finished dropping in price.
This filter allows freqtrade to ignore pairs until they have been listed for at least `min_days_listed` days.
This filter allows freqtrade to ignore pairs until they have been listed for at least `min_days_listed` days and listed before `max_days_listed`.
#### OffsetFilter
Offsets an incoming pairlist by a given `offset` value.
As an example it can be used in conjunction with `VolumeFilter` to remove the top X volume pairs. Or to split
a larger pairlist on two bot instances.
Example to remove the first 10 pairs from the pairlist:
```json
"pairlists": [
{
"method": "OffsetFilter",
"offset": 10
}
],
```
!!! Warning
When `OffsetFilter` is used to split a larger pairlist among multiple bots in combination with `VolumeFilter`
it can not be guaranteed that pairs won't overlap due to slightly different refresh intervals for the
`VolumeFilter`.
!!! Note
An offset larger then the total length of the incoming pairlist will result in an empty pairlist.
#### PerformanceFilter

2
docs/includes/protections.md
View File

@ -1,7 +1,7 @@
## Protections
!!! Warning "Beta feature"
This feature is still in it's testing phase. Should you notice something you think is wrong please let us know via Discord, Slack or via Github Issue.
This feature is still in it's testing phase. Should you notice something you think is wrong please let us know via Discord or via Github Issue.
Protections will protect your strategy from unexpected events and market conditions by temporarily stop trading for either one pair, or for all pairs.
All protection end times are rounded up to the next candle to avoid sudden, unexpected intra-candle buys.

8
docs/index.md
View File

@ -73,13 +73,9 @@ Alternatively
## Support
### Help / Discord / Slack
### Help / Discord
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/p7nuUNVfP7).
You can also join our [Slack channel](https://join.slack.com/t/highfrequencybot/shared_invite/zt-mm786y93-Fxo37glxMY9g8OQC5AoOIw).
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 the Freqtrade [discord server](https://discord.gg/p7nuUNVfP7).
## Ready to try?

4
docs/requirements-docs.txt
View File

@ -1,4 +1,4 @@
mkdocs==1.2.1
mkdocs-material==7.1.9
mkdocs==1.2.2
mkdocs-material==7.1.11
mdx_truly_sane_lists==1.2
pymdown-extensions==8.2

39
docs/strategy-advanced.md
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@ -55,7 +55,7 @@ class AwesomeStrategy(IStrategy):
dataframe, _ = self.dp.get_analyzed_dataframe(pair, self.timeframe)
# Obtain last available candle. Do not use current_time to look up latest candle, because
# current_time points to curret incomplete candle whose data is not available.
# current_time points to current incomplete candle whose data is not available.
last_candle = dataframe.iloc[-1].squeeze()
# <...>
@ -83,7 +83,7 @@ It is possible to define custom sell signals, indicating that specified position
For example you could implement a 1:2 risk-reward ROI with `custom_sell()`.
Using custom_sell() signals in place of stoplosses though *is not recommended*. It is a inferior method to using `custom_stoploss()` in this regard - which also allows you to keep the stoploss on exchange.
Using custom_sell() signals in place of stoploss though *is not recommended*. It is a inferior method to using `custom_stoploss()` in this regard - which also allows you to keep the stoploss on exchange.
!!! Note
Returning a `string` or `True` from this method is equal to setting sell signal on a candle at specified time. This method is not called when sell signal is set already, or if sell signals are disabled (`use_sell_signal=False` or `sell_profit_only=True` while profit is below `sell_profit_offset`). `string` max length is 64 characters. Exceeding this limit will cause the message to be truncated to 64 characters.
@ -269,7 +269,7 @@ class AwesomeStrategy(IStrategy):
current_rate: float, current_profit: float, **kwargs) -> float:
if current_profit < 0.04:
return -1 # return a value bigger than the inital stoploss to keep using the inital stoploss
return -1 # return a value bigger than the initial stoploss to keep using the initial stoploss
# After reaching the desired offset, allow the stoploss to trail by half the profit
desired_stoploss = current_profit / 2
@ -547,6 +547,39 @@ class AwesomeStrategy(IStrategy):
```
### Stake size management
It is possible to manage your risk by reducing or increasing stake amount when placing a new trade.
```python
class AwesomeStrategy(IStrategy):
def custom_stake_amount(self, pair: str, current_time: datetime, current_rate: float,
proposed_stake: float, min_stake: float, max_stake: float,
**kwargs) -> float:
dataframe, _ = self.dp.get_analyzed_dataframe(pair=pair, timeframe=self.timeframe)
current_candle = dataframe.iloc[-1].squeeze()
if current_candle['fastk_rsi_1h'] > current_candle['fastd_rsi_1h']:
if self.config['stake_amount'] == 'unlimited':
# Use entire available wallet during favorable conditions when in compounding mode.
return max_stake
else:
# Compound profits during favorable conditions instead of using a static stake.
return self.wallets.get_total_stake_amount() / self.config['max_open_trades']
# Use default stake amount.
return proposed_stake
```
Freqtrade will fall back to the `proposed_stake` value should your code raise an exception. The exception itself will be logged.
!!! Tip
You do not _have_ to ensure that `min_stake <= returned_value <= max_stake`. Trades will succeed as the returned value will be clamped to supported range and this acton will be logged.
!!! Tip
Returning `0` or `None` will prevent trades from being placed.
---
## Derived strategies

38
docs/strategy_analysis_example.md
View File

@ -130,6 +130,44 @@ trades = load_backtest_data(backtest_dir)
trades.groupby("pair")["sell_reason"].value_counts()
```
## Plotting daily profit / equity line
```python
# Plotting equity line (starting with 0 on day 1 and adding daily profit for each backtested day)
from freqtrade.configuration import Configuration
from freqtrade.data.btanalysis import load_backtest_data, load_backtest_stats
import plotly.express as px
import pandas as pd
# strategy = 'SampleStrategy'
# config = Configuration.from_files(["user_data/config.json"])
# backtest_dir = config["user_data_dir"] / "backtest_results"
stats = load_backtest_stats(backtest_dir)
strategy_stats = stats['strategy'][strategy]
dates = []
profits = []
for date_profit in strategy_stats['daily_profit']:
dates.append(date_profit[0])
profits.append(date_profit[1])
equity = 0
equity_daily = []
for daily_profit in profits:
equity_daily.append(equity)
equity += float(daily_profit)
df = pd.DataFrame({'dates': dates,'equity_daily': equity_daily})
fig = px.line(df, x="dates", y="equity_daily")
fig.show()
```
### Load live trading results into a pandas dataframe
In case you did already some trading and want to analyze your performance

8
docs/telegram-usage.md
View File

@ -245,10 +245,10 @@ current max
Return a summary of your profit/loss and performance.
> **ROI:** Close trades
> ∙ `0.00485701 BTC (258.45%)`
> ∙ `0.00485701 BTC (2.2%) (15.2 Σ%)`
> ∙ `62.968 USD`
> **ROI:** All trades
> ∙ `0.00255280 BTC (143.43%)`
> ∙ `0.00255280 BTC (1.5%) (6.43 Σ%)`
> ∙ `33.095 EUR`
>
> **Total Trade Count:** `138`
@ -257,6 +257,10 @@ Return a summary of your profit/loss and performance.
> **Avg. Duration:** `2:33:45`
> **Best Performing:** `PAY/BTC: 50.23%`
The relative profit of `1.2%` is the average profit per trade.
The relative profit of `15.2 Σ%` is be based on the starting capital - so in this case, the starting capital was `0.00485701 * 1.152 = 0.00738 BTC`.
Starting capital is either taken from the `available_capital` setting, or calculated by using current wallet size - profits.
### /forcesell <trade_id>
> **BITTREX:** Selling BTC/LTC with limit `0.01650000 (profit: ~-4.07%, -0.00008168)`

47
docs/utils.md
View File

@ -614,6 +614,48 @@ Show whitelist when using a [dynamic pairlist](plugins.md#pairlists).
freqtrade test-pairlist --config config.json --quote USDT BTC
```
## Webserver mode
!!! Warning "Experimental"
Webserver mode is an experimental mode to increase backesting and strategy development productivity.
There may still be bugs - so if you happen to stumble across these, please report them as github issues, thanks.
Run freqtrade in webserver mode.
Freqtrade will start the webserver and allow FreqUI to start and control backtesting processes.
This has the advantage that data will not be reloaded between backtesting runs (as long as timeframe and timerange remain identical).
FreqUI will also show the backtesting results.
```
usage: freqtrade webserver [-h] [-v] [--logfile FILE] [-V] [-c PATH] [-d PATH]
[--userdir PATH] [-s NAME] [--strategy-path PATH]
optional arguments:
-h, --help show this help message and exit
Common arguments:
-v, --verbose Verbose mode (-vv for more, -vvv to get all messages).
--logfile FILE Log to the file specified. Special values are:
'syslog', 'journald'. See the documentation for more
details.
-V, --version show program's version number and exit
-c PATH, --config PATH
Specify configuration file (default:
`userdir/config.json` or `config.json` whichever
exists). Multiple --config options may be used. Can be
set to `-` to read config from stdin.
-d PATH, --datadir PATH
Path to directory with historical backtesting data.
--userdir PATH, --user-data-dir PATH
Path to userdata directory.
Strategy arguments:
-s NAME, --strategy NAME
Specify strategy class name which will be used by the
bot.
--strategy-path PATH Specify additional strategy lookup path.
```
## List Hyperopt results
You can list the hyperoptimization epochs the Hyperopt module evaluated previously with the `hyperopt-list` sub-command.
@ -702,7 +744,8 @@ You can show the details of any hyperoptimization epoch previously evaluated by
usage: freqtrade hyperopt-show [-h] [-v] [--logfile FILE] [-V] [-c PATH]
[-d PATH] [--userdir PATH] [--best]
[--profitable] [-n INT] [--print-json]
[--hyperopt-filename PATH] [--no-header]
[--hyperopt-filename FILENAME] [--no-header]
[--disable-param-export]
optional arguments:
-h, --help show this help message and exit
@ -714,6 +757,8 @@ optional arguments:
Hyperopt result filename.Example: `--hyperopt-
filename=hyperopt_results_2020-09-27_16-20-48.pickle`
--no-header Do not print epoch details header.
--disable-param-export
Disable automatic hyperopt parameter export.
Common arguments:
-v, --verbose Verbose mode (-vv for more, -vvv to get all messages).

2
docs/windows_installation.md
View File

@ -23,7 +23,7 @@ git clone https://github.com/freqtrade/freqtrade.git
Install ta-lib according to the [ta-lib documentation](https://github.com/mrjbq7/ta-lib#windows).
As compiling from source on windows has heavy dependencies (requires a partial visual studio installation), there is also a repository of unofficial pre-compiled windows Wheels [here](https://www.lfd.uci.edu/~gohlke/pythonlibs/#ta-lib), which needs to be downloaded and installed using `pip install TA_Lib‑0.4.20‑cp38‑cp38‑win_amd64.whl` (make sure to use the version matching your python version).
As compiling from source on windows has heavy dependencies (requires a partial visual studio installation), there is also a repository of unofficial pre-compiled windows Wheels [here](https://www.lfd.uci.edu/~gohlke/pythonlibs/#ta-lib), which need to be downloaded and installed using `pip install TA_Lib-0.4.21-cp38-cp38-win_amd64.whl` (make sure to use the version matching your python version).
Freqtrade provides these dependencies for the latest 2 Python versions (3.7 and 3.8) and for 64bit Windows.
Other versions must be downloaded from the above link.

1
freqtrade/commands/__init__.py
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@ -20,3 +20,4 @@ from freqtrade.commands.optimize_commands import start_backtesting, start_edge,
from freqtrade.commands.pairlist_commands import start_test_pairlist
from freqtrade.commands.plot_commands import start_plot_dataframe, start_plot_profit
from freqtrade.commands.trade_commands import start_trading
from freqtrade.commands.webserver_commands import start_webserver

16
freqtrade/commands/arguments.py
View File

@ -16,6 +16,8 @@ ARGS_STRATEGY = ["strategy", "strategy_path"]
ARGS_TRADE = ["db_url", "sd_notify", "dry_run", "dry_run_wallet", "fee"]
ARGS_WEBSERVER: List[str] = []
ARGS_COMMON_OPTIMIZE = ["timeframe", "timerange", "dataformat_ohlcv",
"max_open_trades", "stake_amount", "fee", "pairs"]
@ -29,7 +31,7 @@ ARGS_HYPEROPT = ARGS_COMMON_OPTIMIZE + ["hyperopt", "hyperopt_path",
"epochs", "spaces", "print_all",
"print_colorized", "print_json", "hyperopt_jobs",
"hyperopt_random_state", "hyperopt_min_trades",
"hyperopt_loss"]
"hyperopt_loss", "disableparamexport"]
ARGS_EDGE = ARGS_COMMON_OPTIMIZE + ["stoploss_range"]
@ -85,7 +87,8 @@ ARGS_HYPEROPT_LIST = ["hyperopt_list_best", "hyperopt_list_profitable",
"hyperoptexportfilename", "export_csv"]
ARGS_HYPEROPT_SHOW = ["hyperopt_list_best", "hyperopt_list_profitable", "hyperopt_show_index",
"print_json", "hyperoptexportfilename", "hyperopt_show_no_header"]
"print_json", "hyperoptexportfilename", "hyperopt_show_no_header",
"disableparamexport"]
NO_CONF_REQURIED = ["convert-data", "convert-trade-data", "download-data", "list-timeframes",
"list-markets", "list-pairs", "list-strategies", "list-data",
@ -175,7 +178,8 @@ class Arguments:
start_list_markets, start_list_strategies,
start_list_timeframes, start_new_config, start_new_hyperopt,
start_new_strategy, start_plot_dataframe, start_plot_profit,
start_show_trades, start_test_pairlist, start_trading)
start_show_trades, start_test_pairlist, start_trading,
start_webserver)
subparsers = self.parser.add_subparsers(dest='command',
# Use custom message when no subhandler is added
@ -383,3 +387,9 @@ class Arguments:
)
plot_profit_cmd.set_defaults(func=start_plot_profit)
self._build_args(optionlist=ARGS_PLOT_PROFIT, parser=plot_profit_cmd)
# Add webserver subcommand
webserver_cmd = subparsers.add_parser('webserver', help='Webserver module.',
parents=[_common_parser])
webserver_cmd.set_defaults(func=start_webserver)
self._build_args(optionlist=ARGS_WEBSERVER, parser=webserver_cmd)

5
freqtrade/commands/cli_options.py
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@ -178,6 +178,11 @@ AVAILABLE_CLI_OPTIONS = {
'Example: `--export-filename=user_data/backtest_results/backtest_today.json`',
metavar='PATH',
),
"disableparamexport": Arg(
'--disable-param-export',
help="Disable automatic hyperopt parameter export.",
action='store_true',
),
"fee": Arg(
'--fee',
help='Specify fee ratio. Will be applied twice (on trade entry and exit).',

3
freqtrade/commands/data_commands.py
View File

@ -48,7 +48,8 @@ def start_download_data(args: Dict[str, Any]) -> None:
# Init exchange
exchange = ExchangeResolver.load_exchange(config['exchange']['name'], config, validate=False)
# Manual validations of relevant settings
exchange.validate_pairs(config['pairs'])
if not config['exchange'].get('skip_pair_validation', False):
exchange.validate_pairs(config['pairs'])
expanded_pairs = expand_pairlist(config['pairs'], list(exchange.markets))
logger.info(f"About to download pairs: {expanded_pairs}, "

5
freqtrade/commands/hyperopt_commands.py
View File

@ -129,9 +129,12 @@ def start_hyperopt_show(args: Dict[str, Any]) -> None:
metrics = val['results_metrics']
if 'strategy_name' in metrics:
show_backtest_result(metrics['strategy_name'], metrics,
strategy_name = metrics['strategy_name']
show_backtest_result(strategy_name, metrics,
metrics['stake_currency'])
HyperoptTools.try_export_params(config, strategy_name, val)
HyperoptTools.show_epoch_details(val, total_epochs, print_json, no_header,
header_str="Epoch details")

4
freqtrade/commands/list_commands.py
View File

@ -14,7 +14,7 @@ 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.misc import parse_db_uri_for_logging, plural
from freqtrade.resolvers import ExchangeResolver, StrategyResolver
@ -225,7 +225,7 @@ def start_show_trades(args: Dict[str, Any]) -> None:
if 'db_url' not in config:
raise OperationalException("--db-url is required for this command.")
logger.info(f'Using DB: "{config["db_url"]}"')
logger.info(f'Using DB: "{parse_db_uri_for_logging(config["db_url"])}"')
init_db(config['db_url'], clean_open_orders=False)
tfilter = []

15
freqtrade/commands/webserver_commands.py Normal file
View File

@ -0,0 +1,15 @@
from typing import Any, Dict
from freqtrade.enums import RunMode
def start_webserver(args: Dict[str, Any]) -> None:
"""
Main entry point for webserver mode
"""
from freqtrade.configuration import Configuration
from freqtrade.rpc.api_server import ApiServer
# Initialize configuration
config = Configuration(args, RunMode.WEBSERVER).get_config()
ApiServer(config, standalone=True)

8
freqtrade/configuration/configuration.py
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@ -15,7 +15,7 @@ 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.misc import deep_merge_dicts, parse_db_uri_for_logging
logger = logging.getLogger(__name__)
@ -71,7 +71,7 @@ class Configuration:
# Merge config options, overwriting old values
config = deep_merge_dicts(load_config_file(path), config)
config['config_files'] = files
# Normalize config
if 'internals' not in config:
config['internals'] = {}
@ -144,7 +144,7 @@ class Configuration:
config['db_url'] = constants.DEFAULT_DB_PROD_URL
logger.info('Dry run is disabled')
logger.info(f'Using DB: "{config["db_url"]}"')
logger.info(f'Using DB: "{parse_db_uri_for_logging(config["db_url"])}"')
def _process_common_options(self, config: Dict[str, Any]) -> None:
@ -260,6 +260,8 @@ class Configuration:
self._args_to_config(config, argname='export',
logstring='Parameter --export detected: {} ...')
self._args_to_config(config, argname='disableparamexport',
logstring='Parameter --disableparamexport detected: {} ...')
# Edge section:
if 'stoploss_range' in self.args and self.args["stoploss_range"]:
txt_range = eval(self.args["stoploss_range"])

12
freqtrade/constants.py
View File

@ -26,9 +26,9 @@ HYPEROPT_LOSS_BUILTIN = ['ShortTradeDurHyperOptLoss', 'OnlyProfitHyperOptLoss',
'SharpeHyperOptLoss', 'SharpeHyperOptLossDaily',
'SortinoHyperOptLoss', 'SortinoHyperOptLossDaily']
AVAILABLE_PAIRLISTS = ['StaticPairList', 'VolumePairList',
'AgeFilter', 'PerformanceFilter', 'PrecisionFilter',
'PriceFilter', 'RangeStabilityFilter', 'ShuffleFilter',
'SpreadFilter', 'VolatilityFilter']
'AgeFilter', 'OffsetFilter', 'PerformanceFilter',
'PrecisionFilter', 'PriceFilter', 'RangeStabilityFilter',
'ShuffleFilter', 'SpreadFilter', 'VolatilityFilter']
AVAILABLE_PROTECTIONS = ['CooldownPeriod', 'LowProfitPairs', 'MaxDrawdown', 'StoplossGuard']
AVAILABLE_DATAHANDLERS = ['json', 'jsongz', 'hdf5']
DRY_RUN_WALLET = 1000
@ -40,6 +40,7 @@ DEFAULT_DATAFRAME_COLUMNS = ['date', 'open', 'high', 'low', 'close', 'volume']
DEFAULT_TRADES_COLUMNS = ['timestamp', 'id', 'type', 'side', 'price', 'amount', 'cost']
LAST_BT_RESULT_FN = '.last_result.json'
FTHYPT_FILEVERSION = 'fthypt_fileversion'
USERPATH_HYPEROPTS = 'hyperopts'
USERPATH_STRATEGIES = 'strategies'
@ -112,6 +113,10 @@ CONF_SCHEMA = {
'maximum': 1,
'default': 0.99
},
'available_capital': {
'type': 'number',
'minimum': 0,
},
'amend_last_stake_amount': {'type': 'boolean', 'default': False},
'last_stake_amount_min_ratio': {
'type': 'number', 'minimum': 0.0, 'maximum': 1.0, 'default': 0.5
@ -312,6 +317,7 @@ CONF_SCHEMA = {
},
'db_url': {'type': 'string'},
'export': {'type': 'string', 'enum': EXPORT_OPTIONS, 'default': 'trades'},
'disableparamexport': {'type': 'boolean'},
'initial_state': {'type': 'string', 'enum': ['running', 'stopped']},
'forcebuy_enable': {'type': 'boolean'},
'disable_dataframe_checks': {'type': 'boolean'},

6
freqtrade/data/history/history_utils.py
View File

@ -194,8 +194,8 @@ def _download_pair_history(datadir: Path,
new_data = exchange.get_historic_ohlcv(pair=pair,
timeframe=timeframe,
since_ms=since_ms if since_ms else
int(arrow.utcnow().shift(
days=-new_pairs_days).float_timestamp) * 1000
arrow.utcnow().shift(
days=-new_pairs_days).int_timestamp * 1000
)
# TODO: Maybe move parsing to exchange class (?)
new_dataframe = ohlcv_to_dataframe(new_data, timeframe, pair,
@ -272,7 +272,7 @@ def _download_trades_history(exchange: Exchange,
if timerange.stoptype == 'date':
until = timerange.stopts * 1000
else:
since = int(arrow.utcnow().shift(days=-new_pairs_days).float_timestamp) * 1000
since = arrow.utcnow().shift(days=-new_pairs_days).int_timestamp * 1000
trades = data_handler.trades_load(pair)

1
freqtrade/enums/__init__.py
View File

@ -1,4 +1,5 @@
# flake8: noqa: F401
from freqtrade.enums.backteststate import BacktestState
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

15
freqtrade/enums/backteststate.py Normal file
View File

@ -0,0 +1,15 @@
from enum import Enum
class BacktestState(Enum):
"""
Bot application states
"""
STARTUP = 1
DATALOAD = 2
ANALYZE = 3
CONVERT = 4
BACKTEST = 5
def __str__(self):
return f"{self.name.lower()}"

1
freqtrade/enums/runmode.py
View File

@ -14,6 +14,7 @@ class RunMode(Enum):
UTIL_EXCHANGE = "util_exchange"
UTIL_NO_EXCHANGE = "util_no_exchange"
PLOT = "plot"
WEBSERVER = "webserver"
OTHER = "other"

102
freqtrade/exchange/exchange.py
View File

@ -551,7 +551,7 @@ class Exchange:
amount_reserve_percent = 1.0 + self._config.get('amount_reserve_percent',
DEFAULT_AMOUNT_RESERVE_PERCENT)
amount_reserve_percent = (
amount_reserve_percent / (1 - abs(stoploss)) if abs(stoploss) != 1 else 1.5
amount_reserve_percent / (1 - abs(stoploss)) if abs(stoploss) != 1 else 1.5
)
# it should not be more than 50%
amount_reserve_percent = max(min(amount_reserve_percent, 1.5), 1)
@ -578,7 +578,7 @@ class Exchange:
'side': side,
'remaining': _amount,
'datetime': arrow.utcnow().isoformat(),
'timestamp': int(arrow.utcnow().int_timestamp * 1000),
'timestamp': arrow.utcnow().int_timestamp * 1000,
'status': "closed" if ordertype == "market" else "open",
'fee': None,
'info': {}
@ -999,94 +999,64 @@ class Exchange:
except ccxt.BaseError as e:
raise OperationalException(e) from e
def get_buy_rate(self, pair: str, refresh: bool) -> float:
def get_rate(self, pair: str, refresh: bool, side: str) -> float:
"""
Calculates bid target between current ask price and last price
Calculates bid/ask target
bid rate - between current ask price and last price
ask 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
:param side: "buy" or "sell"
:return: float: Price
:raises PricingError if orderbook price could not be determined.
"""
cache_rate: TTLCache = self._buy_rate_cache if side == "buy" else self._sell_rate_cache
[strat_name, name] = ['bid_strategy', 'Buy'] if side == "buy" else ['ask_strategy', 'Sell']
if not refresh:
rate = self._buy_rate_cache.get(pair)
rate = cache_rate.get(pair)
# Check if cache has been invalidated
if rate:
logger.debug(f"Using cached buy rate for {pair}.")
logger.debug(f"Using cached {side} 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):
conf_strategy = self._config.get(strat_name, {})
order_book_top = bid_strategy.get('order_book_top', 1)
if conf_strategy.get('use_order_book', False) and ('use_order_book' in conf_strategy):
order_book_top = conf_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]
rate = order_book[f"{conf_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):
logger.debug(
f"Getting price from order book {ask_strategy['price_side'].capitalize()} side."
)
order_book_top = ask_strategy.get('order_book_top', 1)
order_book = self.fetch_l2_order_book(pair, order_book_top)
try:
rate = order_book[f"{ask_strategy['price_side']}s"][order_book_top - 1][0]
except (IndexError, KeyError) as e:
logger.warning(
f"Sell Price at location {order_book_top} from orderbook could not be "
f"{name} Price at location {order_book_top} from orderbook could not be "
f"determined. Orderbook: {order_book}"
)
raise PricingError from e
logger.info(f"{name} price from orderbook {conf_strategy['price_side'].capitalize()}"
f"side - top {order_book_top} order book {side} rate {rate:.8f}")
else:
logger.info(f"Using Last {conf_strategy['price_side'].capitalize()} / Last Price")
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'])
ticker_rate = ticker[conf_strategy['price_side']]
if ticker['last']:
if side == 'buy' and ticker_rate > ticker['last']:
balance = conf_strategy['ask_last_balance']
ticker_rate = ticker_rate + balance * (ticker['last'] - ticker_rate)
elif side == 'sell' and ticker_rate < ticker['last']:
balance = conf_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
raise PricingError(f"{name}-Rate for {pair} was empty.")
cache_rate[pair] = rate
return rate
# Fee handling
@ -1318,8 +1288,8 @@ class Exchange:
self._pairs_last_refresh_time[(pair, timeframe)] = ticks[-1][0] // 1000
# keeping parsed dataframe in cache
ohlcv_df = ohlcv_to_dataframe(
ticks, timeframe, pair=pair, fill_missing=True,
drop_incomplete=self._ohlcv_partial_candle)
ticks, timeframe, pair=pair, fill_missing=True,
drop_incomplete=self._ohlcv_partial_candle)
results_df[(pair, timeframe)] = ohlcv_df
if cache:
self._klines[(pair, timeframe)] = ohlcv_df

38
freqtrade/freqtradebot.py
View File

@ -424,16 +424,10 @@ class FreqtradeBot(LoggingMixin):
if buy and not sell:
stake_amount = self.wallets.get_trade_stake_amount(pair, self.edge)
if not stake_amount:
logger.debug(f"Stake amount is 0, ignoring possible trade for {pair}.")
return False
logger.info(f"Buy signal found: about create a new trade for {pair} with stake_amount: "
f"{stake_amount} ...")
bid_check_dom = self.config.get('bid_strategy', {}).get('check_depth_of_market', {})
if ((bid_check_dom.get('enabled', False)) and
(bid_check_dom.get('bids_to_ask_delta', 0) > 0)):
(bid_check_dom.get('bids_to_ask_delta', 0) > 0)):
if self._check_depth_of_market_buy(pair, bid_check_dom):
return self.execute_buy(pair, stake_amount, buy_signal_name=buy_signal_name)
else:
@ -481,20 +475,29 @@ class FreqtradeBot(LoggingMixin):
buy_limit_requested = price
else:
# Calculate price
buy_limit_requested = self.exchange.get_buy_rate(pair, True)
buy_limit_requested = self.exchange.get_rate(pair, refresh=True, side="buy")
if not buy_limit_requested:
raise PricingError('Could not determine buy price.')
min_stake_amount = self.exchange.get_min_pair_stake_amount(pair, buy_limit_requested,
self.strategy.stoploss)
if min_stake_amount is not None and min_stake_amount > stake_amount:
logger.warning(
f"Can't open a new trade for {pair}: stake amount "
f"is too small ({stake_amount} < {min_stake_amount})"
)
if not self.edge:
max_stake_amount = self.wallets.get_available_stake_amount()
stake_amount = strategy_safe_wrapper(self.strategy.custom_stake_amount,
default_retval=stake_amount)(
pair=pair, current_time=datetime.now(timezone.utc),
current_rate=buy_limit_requested, proposed_stake=stake_amount,
min_stake=min_stake_amount, max_stake=max_stake_amount)
stake_amount = self.wallets._validate_stake_amount(pair, stake_amount, min_stake_amount)
if not stake_amount:
return False
logger.info(f"Buy signal found: about create a new trade for {pair} with stake_amount: "
f"{stake_amount} ...")
amount = stake_amount / buy_limit_requested
order_type = self.strategy.order_types['buy']
if forcebuy:
@ -607,7 +610,7 @@ class FreqtradeBot(LoggingMixin):
"""
Sends rpc notification when a buy cancel occurred.
"""
current_rate = self.exchange.get_buy_rate(trade.pair, False)
current_rate = self.exchange.get_rate(trade.pair, refresh=False, side="buy")
msg = {
'trade_id': trade.id,
@ -693,7 +696,7 @@ class FreqtradeBot(LoggingMixin):
(buy, sell, _) = self.strategy.get_signal(trade.pair, self.strategy.timeframe, analyzed_df)
logger.debug('checking sell')
sell_rate = self.exchange.get_sell_rate(trade.pair, True)
sell_rate = self.exchange.get_rate(trade.pair, refresh=True, side="sell")
if self._check_and_execute_sell(trade, sell_rate, buy, sell):
return True
@ -1130,7 +1133,8 @@ 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.exchange.get_sell_rate(trade.pair, False) if not fill else None
current_rate = self.exchange.get_rate(
trade.pair, refresh=False, side="sell") if not fill else None
profit_ratio = trade.calc_profit_ratio(profit_rate)
gain = "profit" if profit_ratio > 0 else "loss"
@ -1175,7 +1179,7 @@ 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.exchange.get_sell_rate(trade.pair, False)
current_rate = self.exchange.get_rate(trade.pair, refresh=False, side="sell")
profit_ratio = trade.calc_profit_ratio(profit_rate)
gain = "profit" if profit_ratio > 0 else "loss"

14
freqtrade/misc.py
View File

@ -8,6 +8,7 @@ from datetime import datetime
from pathlib import Path
from typing import Any, Iterator, List
from typing.io import IO
from urllib.parse import urlparse
import rapidjson
@ -214,3 +215,16 @@ def chunks(lst: List[Any], n: int) -> Iterator[List[Any]]:
"""
for chunk in range(0, len(lst), n):
yield (lst[chunk:chunk + n])
def parse_db_uri_for_logging(uri: str):
"""
Helper method to parse the DB URI and return the same DB URI with the password censored
if it contains it. Otherwise, return the DB URI unchanged
:param uri: DB URI to parse for logging
"""
parsed_db_uri = urlparse(uri)
if not parsed_db_uri.netloc: # No need for censoring as no password was provided
return uri
pwd = parsed_db_uri.netloc.split(':')[1].split('@')[0]
return parsed_db_uri.geturl().replace(f':{pwd}@', ':*****@')

57
freqtrade/optimize/backtesting.py
View File

@ -17,10 +17,11 @@ 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.enums import BacktestState, SellType
from freqtrade.exceptions import DependencyException, OperationalException
from freqtrade.exchange import timeframe_to_minutes, timeframe_to_seconds
from freqtrade.mixins import LoggingMixin
from freqtrade.optimize.bt_progress import BTProgress
from freqtrade.optimize.optimize_reports import (generate_backtest_stats, show_backtest_results,
store_backtest_stats)
from freqtrade.persistence import LocalTrade, PairLocks, Trade
@ -58,6 +59,7 @@ class Backtesting:
LoggingMixin.show_output = False
self.config = config
self.results: Optional[Dict[str, Any]] = None
# Reset keys for backtesting
remove_credentials(self.config)
@ -117,6 +119,10 @@ class Backtesting:
# Get maximum required startup period
self.required_startup = max([strat.startup_candle_count for strat in self.strategylist])
self.exchange.validate_required_startup_candles(self.required_startup, self.timeframe)
self.progress = BTProgress()
self.abort = False
def __del__(self):
LoggingMixin.show_output = True
@ -129,6 +135,8 @@ class Backtesting:
"""
self.strategy: IStrategy = strategy
strategy.dp = self.dataprovider
# Attach Wallets to Strategy baseclass
IStrategy.wallets = self.wallets
# Set stoploss_on_exchange to false for backtesting,
# since a "perfect" stoploss-sell is assumed anyway
# And the regular "stoploss" function would not apply to that case
@ -145,6 +153,8 @@ class Backtesting:
Loads backtest data and returns the data combined with the timerange
as tuple.
"""
self.progress.init_step(BacktestState.DATALOAD, 1)
timerange = TimeRange.parse_timerange(None if self.config.get(
'timerange') is None else str(self.config.get('timerange')))
@ -168,6 +178,7 @@ class Backtesting:
timerange.adjust_start_if_necessary(timeframe_to_seconds(self.timeframe),
self.required_startup, min_date)
self.progress.set_new_value(1)
return data, timerange
def prepare_backtest(self, enable_protections):
@ -182,6 +193,15 @@ class Backtesting:
self.rejected_trades = 0
self.dataprovider.clear_cache()
def check_abort(self):
"""
Check if abort was requested, raise DependencyException if that's the case
Only applies to Interactive backtest mode (webserver mode)
"""
if self.abort:
self.abort = False
raise DependencyException("Stop requested")
def _get_ohlcv_as_lists(self, processed: Dict[str, DataFrame]) -> Dict[str, Tuple]:
"""
Helper function to convert a processed dataframes into lists for performance reasons.
@ -192,8 +212,12 @@ class Backtesting:
# and eventually change the constants for indexes at the top
headers = ['date', 'buy', 'open', 'close', 'sell', 'low', 'high', 'buy_signal_name']
data: Dict = {}
self.progress.init_step(BacktestState.CONVERT, len(processed))
# Create dict with data
for pair, pair_data in processed.items():
self.check_abort()
self.progress.increment()
if not pair_data.empty:
pair_data.loc[:, 'buy'] = 0 # cleanup if buy_signal is exist
pair_data.loc[:, 'sell'] = 0 # cleanup if sell_signal is exist
@ -314,7 +338,18 @@ class Backtesting:
stake_amount = self.wallets.get_trade_stake_amount(pair, None)
except DependencyException:
return None
min_stake_amount = self.exchange.get_min_pair_stake_amount(pair, row[OPEN_IDX], -0.05)
min_stake_amount = self.exchange.get_min_pair_stake_amount(pair, row[OPEN_IDX], -0.05) or 0
max_stake_amount = self.wallets.get_available_stake_amount()
stake_amount = strategy_safe_wrapper(self.strategy.custom_stake_amount,
default_retval=stake_amount)(
pair=pair, current_time=row[DATE_IDX].to_pydatetime(), current_rate=row[OPEN_IDX],
proposed_stake=stake_amount, min_stake=min_stake_amount, max_stake=max_stake_amount)
stake_amount = self.wallets._validate_stake_amount(pair, stake_amount, min_stake_amount)
if not stake_amount:
return None
order_type = self.strategy.order_types['buy']
time_in_force = self.strategy.order_time_in_force['sell']
@ -407,10 +442,13 @@ class Backtesting:
open_trades: Dict[str, List[LocalTrade]] = defaultdict(list)
open_trade_count = 0
self.progress.init_step(BacktestState.BACKTEST, int(
(end_date - start_date) / timedelta(minutes=self.timeframe_min)))
# Loop timerange and get candle for each pair at that point in time
while tmp <= end_date:
open_trade_count_start = open_trade_count
self.check_abort()
for i, pair in enumerate(data):
row_index = indexes[pair]
try:
@ -466,6 +504,7 @@ class Backtesting:
self.protections.global_stop(tmp)
# Move time one configured time_interval ahead.
self.progress.increment()
tmp += timedelta(minutes=self.timeframe_min)
trades += self.handle_left_open(open_trades, data=data)
@ -481,6 +520,8 @@ class Backtesting:
}
def backtest_one_strategy(self, strat: IStrategy, data: Dict[str, Any], timerange: TimeRange):
self.progress.init_step(BacktestState.ANALYZE, 0)
logger.info("Running backtesting for Strategy %s", strat.get_strategy_name())
backtest_start_time = datetime.now(timezone.utc)
self._set_strategy(strat)
@ -507,6 +548,7 @@ class Backtesting:
"No data left after adjusting for startup candles.")
min_date, max_date = history.get_timerange(preprocessed)
logger.info(f'Backtesting with data from {min_date.strftime(DATETIME_PRINT_FORMAT)} '
f'up to {max_date.strftime(DATETIME_PRINT_FORMAT)} '
f'({(max_date - min_date).days} days).')
@ -541,11 +583,12 @@ class Backtesting:
for strat in self.strategylist:
min_date, max_date = self.backtest_one_strategy(strat, data, timerange)
if len(self.strategylist) > 0:
stats = generate_backtest_stats(data, self.all_results,
min_date=min_date, max_date=max_date)
self.results = generate_backtest_stats(data, self.all_results,
min_date=min_date, max_date=max_date)
if self.config.get('export', 'none') == 'trades':
store_backtest_stats(self.config['exportfilename'], stats)
store_backtest_stats(self.config['exportfilename'], self.results)
# Show backtest results
show_backtest_results(self.config, stats)
show_backtest_results(self.config, self.results)

33
freqtrade/optimize/bt_progress.py Normal file
View File

@ -0,0 +1,33 @@
from freqtrade.enums import BacktestState
class BTProgress:
_action: BacktestState = BacktestState.STARTUP
_progress: float = 0
_max_steps: float = 0
def __init__(self):
pass
def init_step(self, action: BacktestState, max_steps: float):
self._action = action
self._max_steps = max_steps
self._proress = 0
def set_new_value(self, new_value: float):
self._progress = new_value
def increment(self):
self._progress += 1
@property
def progress(self):
"""
Get progress as ratio, capped to be between 0 and 1 (to avoid small calculation errors).
"""
return max(min(round(self._progress / self._max_steps, 5)
if self._max_steps > 0 else 0, 1), 0)
@property
def action(self):
return str(self._action)

49
freqtrade/optimize/hyperopt.py
View File

@ -12,7 +12,6 @@ from math import ceil
from pathlib import Path
from typing import Any, Dict, List, Optional
import numpy as np
import progressbar
import rapidjson
from colorama import Fore, Style
@ -20,16 +19,16 @@ from colorama import init as colorama_init
from joblib import Parallel, cpu_count, delayed, dump, load, wrap_non_picklable_objects
from pandas import DataFrame
from freqtrade.constants import DATETIME_PRINT_FORMAT, LAST_BT_RESULT_FN
from freqtrade.constants import DATETIME_PRINT_FORMAT, FTHYPT_FILEVERSION, LAST_BT_RESULT_FN
from freqtrade.data.converter import trim_dataframes
from freqtrade.data.history import get_timerange
from freqtrade.misc import file_dump_json, plural
from freqtrade.misc import deep_merge_dicts, file_dump_json, plural
from freqtrade.optimize.backtesting import Backtesting
# Import IHyperOpt and IHyperOptLoss to allow unpickling classes from these modules
from freqtrade.optimize.hyperopt_auto import HyperOptAuto
from freqtrade.optimize.hyperopt_interface import IHyperOpt # noqa: F401
from freqtrade.optimize.hyperopt_loss_interface import IHyperOptLoss # noqa: F401
from freqtrade.optimize.hyperopt_tools import HyperoptTools
from freqtrade.optimize.hyperopt_tools import HyperoptTools, hyperopt_serializer
from freqtrade.optimize.optimize_reports import generate_strategy_stats
from freqtrade.resolvers.hyperopt_resolver import HyperOptLossResolver, HyperOptResolver
@ -78,8 +77,11 @@ class Hyperopt:
if not self.config.get('hyperopt'):
self.custom_hyperopt = HyperOptAuto(self.config)
self.auto_hyperopt = True
else:
self.custom_hyperopt = HyperOptResolver.load_hyperopt(self.config)
self.auto_hyperopt = False
self.backtesting._set_strategy(self.backtesting.strategylist[0])
self.custom_hyperopt.strategy = self.backtesting.strategy
@ -163,13 +165,9 @@ class Hyperopt:
While not a valid json object - this allows appending easily.
:param epoch: result dictionary for this epoch.
"""
def default_parser(x):
if isinstance(x, np.integer):
return int(x)
return str(x)
epoch[FTHYPT_FILEVERSION] = 2
with self.results_file.open('a') as f:
rapidjson.dump(epoch, f, default=default_parser,
rapidjson.dump(epoch, f, default=hyperopt_serializer,
number_mode=rapidjson.NM_NATIVE | rapidjson.NM_NAN)
f.write("\n")
@ -201,6 +199,25 @@ class Hyperopt:
return result
def _get_no_optimize_details(self) -> Dict[str, Any]:
"""
Get non-optimized parameters
"""
result: Dict[str, Any] = {}
strategy = self.backtesting.strategy
if not HyperoptTools.has_space(self.config, 'roi'):
result['roi'] = {str(k): v for k, v in strategy.minimal_roi.items()}
if not HyperoptTools.has_space(self.config, 'stoploss'):
result['stoploss'] = {'stoploss': strategy.stoploss}
if not HyperoptTools.has_space(self.config, 'trailing'):
result['trailing'] = {
'trailing_stop': strategy.trailing_stop,
'trailing_stop_positive': strategy.trailing_stop_positive,
'trailing_stop_positive_offset': strategy.trailing_stop_positive_offset,
'trailing_only_offset_is_reached': strategy.trailing_only_offset_is_reached,
}
return result
def print_results(self, results) -> None:
"""
Log results if it is better than any previous evaluation
@ -310,7 +327,8 @@ class Hyperopt:
results_explanation = HyperoptTools.format_results_explanation_string(
strat_stats, self.config['stake_currency'])
not_optimized = self.backtesting.strategy.get_params_dict()
not_optimized = self.backtesting.strategy.get_no_optimize_params()
not_optimized = deep_merge_dicts(not_optimized, self._get_no_optimize_details())
trade_count = strat_stats['total_trades']
total_profit = strat_stats['profit_total']
@ -324,7 +342,8 @@ class Hyperopt:
loss = self.calculate_loss(results=backtesting_results['results'],
trade_count=trade_count,
min_date=min_date, max_date=max_date,
config=self.config, processed=processed)
config=self.config, processed=processed,
backtest_stats=strat_stats)
return {
'loss': loss,
'params_dict': params_dict,
@ -469,6 +488,12 @@ class Hyperopt:
f"saved to '{self.results_file}'.")
if self.current_best_epoch:
if self.auto_hyperopt:
HyperoptTools.try_export_params(
self.config,
self.backtesting.strategy.get_strategy_name(),
self.current_best_epoch)
HyperoptTools.show_epoch_details(self.current_best_epoch, self.total_epochs,
self.print_json)
else:

3
freqtrade/optimize/hyperopt_loss_interface.py
View File

@ -5,7 +5,7 @@ This module defines the interface for the loss-function for hyperopt
from abc import ABC, abstractmethod
from datetime import datetime
from typing import Dict
from typing import Any, Dict
from pandas import DataFrame
@ -22,6 +22,7 @@ class IHyperOptLoss(ABC):
def hyperopt_loss_function(results: DataFrame, trade_count: int,
min_date: datetime, max_date: datetime,
config: Dict, processed: Dict[str, DataFrame],
backtest_stats: Dict[str, Any],
*args, **kwargs) -> float:
"""
Objective function, returns smaller number for better results

104
freqtrade/optimize/hyperopt_tools.py
View File

@ -1,23 +1,82 @@
import io
import logging
from copy import deepcopy
from datetime import datetime, timezone
from pathlib import Path
from typing import Any, Dict, List
from typing import Any, Dict, List, Optional
import numpy as np
import rapidjson
import tabulate
from colorama import Fore, Style
from pandas import isna, json_normalize
from freqtrade.constants import FTHYPT_FILEVERSION, USERPATH_STRATEGIES
from freqtrade.exceptions import OperationalException
from freqtrade.misc import round_coin_value, round_dict
from freqtrade.misc import deep_merge_dicts, round_coin_value, round_dict, safe_value_fallback2
logger = logging.getLogger(__name__)
NON_OPT_PARAM_APPENDIX = " # value loaded from strategy"
def hyperopt_serializer(x):
if isinstance(x, np.integer):
return int(x)
if isinstance(x, np.bool_):
return bool(x)
return str(x)
class HyperoptTools():
@staticmethod
def get_strategy_filename(config: Dict, strategy_name: str) -> Optional[Path]:
"""
Get Strategy-location (filename) from strategy_name
"""
from freqtrade.resolvers.strategy_resolver import StrategyResolver
directory = Path(config.get('strategy_path', config['user_data_dir'] / USERPATH_STRATEGIES))
strategy_objs = StrategyResolver.search_all_objects(directory, False)
strategies = [s for s in strategy_objs if s['name'] == strategy_name]
if strategies:
strategy = strategies[0]
return Path(strategy['location'])
return None
@staticmethod
def export_params(params, strategy_name: str, filename: Path):
"""
Generate files
"""
final_params = deepcopy(params['params_not_optimized'])
final_params = deep_merge_dicts(params['params_details'], final_params)
final_params = {
'strategy_name': strategy_name,
'params': final_params,
'ft_stratparam_v': 1,
'export_time': datetime.now(timezone.utc),
}
logger.info(f"Dumping parameters to {filename}")
rapidjson.dump(final_params, filename.open('w'), indent=2,
default=hyperopt_serializer,
number_mode=rapidjson.NM_NATIVE | rapidjson.NM_NAN
)
@staticmethod
def try_export_params(config: Dict[str, Any], strategy_name: str, params: Dict):
if params.get(FTHYPT_FILEVERSION, 1) >= 2 and not config.get('disableparamexport', False):
# Export parameters ...
fn = HyperoptTools.get_strategy_filename(config, strategy_name)
if fn:
HyperoptTools.export_params(params, strategy_name, fn.with_suffix('.json'))
else:
logger.warning("Strategy not found, not exporting parameter file.")
@staticmethod
def has_space(config: Dict[str, Any], space: str) -> bool:
"""
@ -99,9 +158,9 @@ class HyperoptTools():
non_optimized)
HyperoptTools._params_pretty_print(params, 'sell', "Sell hyperspace params:",
non_optimized)
HyperoptTools._params_pretty_print(params, 'roi', "ROI table:")
HyperoptTools._params_pretty_print(params, 'stoploss', "Stoploss:")
HyperoptTools._params_pretty_print(params, 'trailing', "Trailing stop:")
HyperoptTools._params_pretty_print(params, 'roi', "ROI table:", non_optimized)
HyperoptTools._params_pretty_print(params, 'stoploss', "Stoploss:", non_optimized)
HyperoptTools._params_pretty_print(params, 'trailing', "Trailing stop:", non_optimized)
@staticmethod
def _params_update_for_json(result_dict, params, non_optimized, space: str) -> None:
@ -127,23 +186,34 @@ class HyperoptTools():
def _params_pretty_print(params, space: str, header: str, non_optimized={}) -> None:
if space in params or space in non_optimized:
space_params = HyperoptTools._space_params(params, space, 5)
no_params = HyperoptTools._space_params(non_optimized, space, 5)
appendix = ''
if not space_params and not no_params:
# No parameters - don't print
return
if not space_params:
# Not optimized parameters - append string
appendix = NON_OPT_PARAM_APPENDIX
result = f"\n# {header}\n"
if space == 'stoploss':
result += f"stoploss = {space_params.get('stoploss')}"
elif space == 'roi':
if space == "stoploss":
stoploss = safe_value_fallback2(space_params, no_params, space, space)
result += (f"stoploss = {stoploss}{appendix}")
elif space == "roi":
result = result[:-1] + f'{appendix}\n'
minimal_roi_result = rapidjson.dumps({
str(k): v for k, v in space_params.items()
str(k): v for k, v in (space_params or no_params).items()
}, default=str, indent=4, number_mode=rapidjson.NM_NATIVE)
result += f"minimal_roi = {minimal_roi_result}"
elif space == 'trailing':
for k, v in space_params.items():
result += f'{k} = {v}\n'
elif space == "trailing":
for k, v in (space_params or no_params).items():
result += f"{k} = {v}{appendix}\n"
else:
no_params = HyperoptTools._space_params(non_optimized, space, 5)
# Buy / sell parameters
result += f"{space}_params = {HyperoptTools._pprint(space_params, no_params)}"
result += f"{space}_params = {HyperoptTools._pprint_dict(space_params, no_params)}"
result = result.replace("\n", "\n ")
print(result)
@ -157,7 +227,7 @@ class HyperoptTools():
return {}
@staticmethod
def _pprint(params, non_optimized, indent: int = 4):
def _pprint_dict(params, non_optimized, indent: int = 4):
"""
Pretty-print hyperopt results (based on 2 dicts - with add. comment)
"""
@ -169,7 +239,7 @@ class HyperoptTools():
result += " " * indent + f'"{k}": '
result += f'"{param}",' if isinstance(param, str) else f'{param},'
if k in non_optimized:
result += " # value loaded from strategy"
result += NON_OPT_PARAM_APPENDIX
result += "\n"
result += '}'
return result

20
freqtrade/optimize/optimize_reports.py
View File

@ -229,8 +229,6 @@ def generate_trading_stats(results: DataFrame) -> Dict[str, Any]:
winning_trades = results.loc[results['profit_ratio'] > 0]
draw_trades = results.loc[results['profit_ratio'] == 0]
losing_trades = results.loc[results['profit_ratio'] < 0]
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())
@ -249,7 +247,6 @@ def generate_trading_stats(results: DataFrame) -> Dict[str, Any]:
'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,
}
@ -264,6 +261,7 @@ def generate_daily_stats(results: DataFrame) -> Dict[str, Any]:
'winning_days': 0,
'draw_days': 0,
'losing_days': 0,
'daily_profit_list': [],
}
daily_profit_rel = results.resample('1d', on='close_date')['profit_ratio'].sum()
daily_profit = results.resample('1d', on='close_date')['profit_abs'].sum().round(10)
@ -274,6 +272,7 @@ def generate_daily_stats(results: DataFrame) -> Dict[str, Any]:
winning_days = sum(daily_profit > 0)
draw_days = sum(daily_profit == 0)
losing_days = sum(daily_profit < 0)
daily_profit_list = [(str(idx.date()), val) for idx, val in daily_profit.iteritems()]
return {
'backtest_best_day': best_rel,
@ -283,6 +282,7 @@ def generate_daily_stats(results: DataFrame) -> Dict[str, Any]:
'winning_days': winning_days,
'draw_days': draw_days,
'losing_days': losing_days,
'daily_profit': daily_profit_list,
}
@ -325,8 +325,9 @@ def generate_strategy_stats(btdata: Dict[str, DataFrame],
key=lambda x: x['profit_sum']) if len(pair_results) > 1 else None
worst_pair = min([pair for pair in pair_results if pair['key'] != 'TOTAL'],
key=lambda x: x['profit_sum']) if len(pair_results) > 1 else None
results['open_timestamp'] = results['open_date'].astype(int64) // 1e6
results['close_timestamp'] = results['close_date'].astype(int64) // 1e6
if not results.empty:
results['open_timestamp'] = results['open_date'].view(int64) // 1e6
results['close_timestamp'] = results['close_date'].view(int64) // 1e6
backtest_days = (max_date - min_date).days
strat_stats = {
@ -542,14 +543,6 @@ def text_table_add_metrics(strat_results: Dict) -> str:
# Newly added fields should be ignored if they are missing in strat_results. hyperopt-show
# command stores these results and newer version of freqtrade must be able to handle old
# results with missing new fields.
zero_duration_trades = '--'
if 'zero_duration_trades' in strat_results:
zero_duration_trades_per = \
100.0 / strat_results['total_trades'] * strat_results['zero_duration_trades']
zero_duration_trades = f'{zero_duration_trades_per:.2f}% ' \
f'({strat_results["zero_duration_trades"]})'
metrics = [
('Backtesting from', strat_results['backtest_start']),
('Backtesting to', strat_results['backtest_end']),
@ -585,7 +578,6 @@ def text_table_add_metrics(strat_results: Dict) -> str:
f"{strat_results['draw_days']} / {strat_results['losing_days']}"),
('Avg. Duration Winners', f"{strat_results['winner_holding_avg']}"),
('Avg. Duration Loser', f"{strat_results['loser_holding_avg']}"),
('Zero Duration Trades', zero_duration_trades),
('Rejected Buy signals', strat_results.get('rejected_signals', 'N/A')),
('', ''), # Empty line to improve readability

13
freqtrade/persistence/models.py
View File

@ -804,6 +804,19 @@ class Trade(_DECL_BASE, LocalTrade):
Trade.is_open.is_(False),
]).all()
@staticmethod
def get_total_closed_profit() -> float:
"""
Retrieves total realized profit
"""
if Trade.use_db:
total_profit = Trade.query.with_entities(
func.sum(Trade.close_profit_abs)).filter(Trade.is_open.is_(False)).scalar()
else:
total_profit = sum(
t.close_profit_abs for t in LocalTrade.get_trades_proxy(is_open=False))
return total_profit or 0
@staticmethod
def total_open_trades_stakes() -> float:
"""

39
freqtrade/plugins/pairlist/AgeFilter.py
View File

@ -27,6 +27,7 @@ class AgeFilter(IPairList):
super().__init__(exchange, pairlistmanager, config, pairlistconfig, pairlist_pos)
self._min_days_listed = pairlistconfig.get('min_days_listed', 10)
self._max_days_listed = pairlistconfig.get('max_days_listed', None)
if self._min_days_listed < 1:
raise OperationalException("AgeFilter requires min_days_listed to be >= 1")
@ -34,6 +35,12 @@ class AgeFilter(IPairList):
raise OperationalException("AgeFilter requires min_days_listed to not exceed "
"exchange max request size "
f"({exchange.ohlcv_candle_limit('1d')})")
if self._max_days_listed and self._max_days_listed <= self._min_days_listed:
raise OperationalException("AgeFilter max_days_listed <= min_days_listed not permitted")
if self._max_days_listed and self._max_days_listed > exchange.ohlcv_candle_limit('1d'):
raise OperationalException("AgeFilter requires max_days_listed to not exceed "
"exchange max request size "
f"({exchange.ohlcv_candle_limit('1d')})")
@property
def needstickers(self) -> bool:
@ -48,8 +55,13 @@ class AgeFilter(IPairList):
"""
Short whitelist method description - used for startup-messages
"""
return (f"{self.name} - Filtering pairs with age less than "
f"{self._min_days_listed} {plural(self._min_days_listed, 'day')}.")
return (
f"{self.name} - Filtering pairs with age less than "
f"{self._min_days_listed} {plural(self._min_days_listed, 'day')}"
) + ((
" or more than "
f"{self._max_days_listed} {plural(self._max_days_listed, 'day')}"
) if self._max_days_listed else '')
def filter_pairlist(self, pairlist: List[str], tickers: Dict) -> List[str]:
"""
@ -61,9 +73,12 @@ class AgeFilter(IPairList):
if not needed_pairs:
return pairlist
since_days = -(
self._max_days_listed if self._max_days_listed else self._min_days_listed
) - 1
since_ms = int(arrow.utcnow()
.floor('day')
.shift(days=-self._min_days_listed - 1)
.shift(days=since_days)
.float_timestamp) * 1000
candles = self._exchange.refresh_latest_ohlcv(needed_pairs, since_ms=since_ms, cache=False)
if self._enabled:
@ -86,14 +101,22 @@ class AgeFilter(IPairList):
return True
if daily_candles is not None:
if len(daily_candles) >= self._min_days_listed:
if (
len(daily_candles) >= self._min_days_listed
and (not self._max_days_listed or len(daily_candles) <= self._max_days_listed)
):
# We have fetched at least the minimum required number of daily candles
# Add to cache, store the time we last checked this symbol
self._symbolsChecked[pair] = int(arrow.utcnow().float_timestamp) * 1000
self._symbolsChecked[pair] = arrow.utcnow().int_timestamp * 1000
return True
else:
self.log_once(f"Removed {pair} from whitelist, because age "
f"{len(daily_candles)} is less than {self._min_days_listed} "
f"{plural(self._min_days_listed, 'day')}", logger.info)
self.log_once((
f"Removed {pair} from whitelist, because age "
f"{len(daily_candles)} is less than {self._min_days_listed} "
f"{plural(self._min_days_listed, 'day')}"
) + ((
" or more than "
f"{self._max_days_listed} {plural(self._max_days_listed, 'day')}"
) if self._max_days_listed else ''), logger.info)
return False
return False

54
freqtrade/plugins/pairlist/OffsetFilter.py Normal file
View File

@ -0,0 +1,54 @@
"""
Offset pair list filter
"""
import logging
from typing import Any, Dict, List
from freqtrade.exceptions import OperationalException
from freqtrade.plugins.pairlist.IPairList import IPairList
logger = logging.getLogger(__name__)
class OffsetFilter(IPairList):
def __init__(self, exchange, pairlistmanager,
config: Dict[str, Any], pairlistconfig: Dict[str, Any],
pairlist_pos: int) -> None:
super().__init__(exchange, pairlistmanager, config, pairlistconfig, pairlist_pos)
self._offset = pairlistconfig.get('offset', 0)
if self._offset < 0:
raise OperationalException("OffsetFilter requires offset to be >= 0")
@property
def needstickers(self) -> bool:
"""
Boolean property defining if tickers are necessary.
If no Pairlist requires tickers, an empty Dict is passed
as tickers argument to filter_pairlist
"""
return False
def short_desc(self) -> str:
"""
Short whitelist method description - used for startup-messages
"""
return f"{self.name} - Offseting pairs by {self._offset}."
def filter_pairlist(self, pairlist: List[str], tickers: Dict) -> List[str]:
"""
Filters and sorts pairlist and returns the whitelist again.
Called on each bot iteration - please use internal caching if necessary
:param pairlist: pairlist to filter or sort
:param tickers: Tickers (from exchange.get_tickers()). May be cached.
:return: new whitelist
"""
if self._offset > len(pairlist):
self.log_once(f"Offset of {self._offset} is larger than " +
f"pair count of {len(pairlist)}", logger.warning)
pairs = pairlist[self._offset:]
self.log_once(f"Searching {len(pairs)} pairs: {pairs}", logger.info)
return pairs

8
freqtrade/plugins/pairlist/VolatilityFilter.py
View File

@ -69,10 +69,10 @@ class VolatilityFilter(IPairList):
"""
needed_pairs = [(p, '1d') for p in pairlist if p not in self._pair_cache]
since_ms = int(arrow.utcnow()
.floor('day')
.shift(days=-self._days - 1)
.float_timestamp) * 1000
since_ms = (arrow.utcnow()
.floor('day')
.shift(days=-self._days - 1)
.int_timestamp) * 1000
# Get all candles
candles = {}
if needed_pairs:

94
freqtrade/plugins/pairlist/VolumePairList.py
View File

@ -6,9 +6,12 @@ Provides dynamic pair list based on trade volumes
import logging
from typing import Any, Dict, List
import arrow
from cachetools.ttl import TTLCache
from freqtrade.exceptions import OperationalException
from freqtrade.exchange import timeframe_to_minutes
from freqtrade.misc import format_ms_time
from freqtrade.plugins.pairlist.IPairList import IPairList
@ -36,6 +39,35 @@ class VolumePairList(IPairList):
self._min_value = self._pairlistconfig.get('min_value', 0)
self._refresh_period = self._pairlistconfig.get('refresh_period', 1800)
self._pair_cache: TTLCache = TTLCache(maxsize=1, ttl=self._refresh_period)
self._lookback_days = self._pairlistconfig.get('lookback_days', 0)
self._lookback_timeframe = self._pairlistconfig.get('lookback_timeframe', '1d')
self._lookback_period = self._pairlistconfig.get('lookback_period', 0)
if (self._lookback_days > 0) & (self._lookback_period > 0):
raise OperationalException(
'Ambigous configuration: lookback_days and lookback_period both set in pairlist '
'config. Please set lookback_days only or lookback_period and lookback_timeframe '
'and restart the bot.'
)
# overwrite lookback timeframe and days when lookback_days is set
if self._lookback_days > 0:
self._lookback_timeframe = '1d'
self._lookback_period = self._lookback_days
# get timeframe in minutes and seconds
self._tf_in_min = timeframe_to_minutes(self._lookback_timeframe)
self._tf_in_sec = self._tf_in_min * 60
# wether to use range lookback or not
self._use_range = (self._tf_in_min > 0) & (self._lookback_period > 0)
if self._use_range & (self._refresh_period < self._tf_in_sec):
raise OperationalException(
f'Refresh period of {self._refresh_period} seconds is smaller than one '
f'timeframe of {self._lookback_timeframe}. Please adjust refresh_period '
f'to at least {self._tf_in_sec} and restart the bot.'
)
if not self._exchange.exchange_has('fetchTickers'):
raise OperationalException(
@ -47,6 +79,13 @@ class VolumePairList(IPairList):
raise OperationalException(
f'key {self._sort_key} not in {SORT_VALUES}')
if self._lookback_period < 0:
raise OperationalException("VolumeFilter requires lookback_period to be >= 0")
if self._lookback_period > exchange.ohlcv_candle_limit(self._lookback_timeframe):
raise OperationalException("VolumeFilter requires lookback_period to not "
"exceed exchange max request size "
f"({exchange.ohlcv_candle_limit(self._lookback_timeframe)})")
@property
def needstickers(self) -> bool:
"""
@ -78,7 +117,6 @@ class VolumePairList(IPairList):
# Item found - no refresh necessary
return pairlist
else:
# Use fresh pairlist
# Check if pair quote currency equals to the stake currency.
filtered_tickers = [
@ -103,6 +141,60 @@ class VolumePairList(IPairList):
# Use the incoming pairlist.
filtered_tickers = [v for k, v in tickers.items() if k in pairlist]
# get lookback period in ms, for exchange ohlcv fetch
if self._use_range:
since_ms = int(arrow.utcnow()
.floor('minute')
.shift(minutes=-(self._lookback_period * self._tf_in_min)
- self._tf_in_min)
.int_timestamp) * 1000
to_ms = int(arrow.utcnow()
.floor('minute')
.shift(minutes=-self._tf_in_min)
.int_timestamp) * 1000
# todo: utc date output for starting date
self.log_once(f"Using volume range of {self._lookback_period} candles, timeframe: "
f"{self._lookback_timeframe}, starting from {format_ms_time(since_ms)} "
f"till {format_ms_time(to_ms)}", logger.info)
needed_pairs = [
(p, self._lookback_timeframe) for p in
[
s['symbol'] for s in filtered_tickers
] if p not in self._pair_cache
]
# Get all candles
candles = {}
if needed_pairs:
candles = self._exchange.refresh_latest_ohlcv(
needed_pairs, since_ms=since_ms, cache=False
)
for i, p in enumerate(filtered_tickers):
pair_candles = candles[
(p['symbol'], self._lookback_timeframe)
] if (p['symbol'], self._lookback_timeframe) in candles else None
# in case of candle data calculate typical price and quoteVolume for candle
if pair_candles is not None and not pair_candles.empty:
pair_candles['typical_price'] = (pair_candles['high'] + pair_candles['low']
+ pair_candles['close']) / 3
pair_candles['quoteVolume'] = (
pair_candles['volume'] * pair_candles['typical_price']
)
# ensure that a rolling sum over the lookback_period is built
# if pair_candles contains more candles than lookback_period
quoteVolume = (pair_candles['quoteVolume']
.rolling(self._lookback_period)
.sum()
.iloc[-1])
# replace quoteVolume with range quoteVolume sum calculated above
filtered_tickers[i]['quoteVolume'] = quoteVolume
else:
filtered_tickers[i]['quoteVolume'] = 0
if self._min_value > 0:
filtered_tickers = [
v for v in filtered_tickers if v[self._sort_key] > self._min_value]

8
freqtrade/plugins/pairlist/rangestabilityfilter.py
View File

@ -62,10 +62,10 @@ class RangeStabilityFilter(IPairList):
"""
needed_pairs = [(p, '1d') for p in pairlist if p not in self._pair_cache]
since_ms = int(arrow.utcnow()
.floor('day')
.shift(days=-self._days - 1)
.float_timestamp) * 1000
since_ms = (arrow.utcnow()
.floor('day')
.shift(days=-self._days - 1)
.int_timestamp) * 1000
# Get all candles
candles = {}
if needed_pairs:

15
freqtrade/resolvers/strategy_resolver.py
View File

@ -53,6 +53,21 @@ class StrategyResolver(IResolver):
)
strategy.timeframe = strategy.ticker_interval
if strategy._ft_params_from_file:
# Set parameters from Hyperopt results file
params = strategy._ft_params_from_file
strategy.minimal_roi = params.get('roi', strategy.minimal_roi)
strategy.stoploss = params.get('stoploss', {}).get('stoploss', strategy.stoploss)
trailing = params.get('trailing', {})
strategy.trailing_stop = trailing.get('trailing_stop', strategy.trailing_stop)
strategy.trailing_stop_positive = trailing.get('trailing_stop_positive',
strategy.trailing_stop_positive)
strategy.trailing_stop_positive_offset = trailing.get(
'trailing_stop_positive_offset', strategy.trailing_stop_positive_offset)
strategy.trailing_only_offset_is_reached = trailing.get(
'trailing_only_offset_is_reached', strategy.trailing_only_offset_is_reached)
# Set attributes
# Check if we need to override configuration
# (Attribute name, default, subkey)

176
freqtrade/rpc/api_server/api_backtest.py Normal file
View File

@ -0,0 +1,176 @@
import asyncio
import logging
from copy import deepcopy
from fastapi import APIRouter, BackgroundTasks, Depends
from freqtrade.enums import BacktestState
from freqtrade.exceptions import DependencyException
from freqtrade.rpc.api_server.api_schemas import BacktestRequest, BacktestResponse
from freqtrade.rpc.api_server.deps import get_config
from freqtrade.rpc.api_server.webserver import ApiServer
from freqtrade.rpc.rpc import RPCException
logger = logging.getLogger(__name__)
# Private API, protected by authentication
router = APIRouter()
@router.post('/backtest', response_model=BacktestResponse, tags=['webserver', 'backtest'])
async def api_start_backtest(bt_settings: BacktestRequest, background_tasks: BackgroundTasks,
config=Depends(get_config)):
"""Start backtesting if not done so already"""
if ApiServer._bgtask_running:
raise RPCException('Bot Background task already running')
btconfig = deepcopy(config)
settings = dict(bt_settings)
# Pydantic models will contain all keys, but non-provided ones are None
for setting in settings.keys():
if settings[setting] is not None:
btconfig[setting] = settings[setting]
# Start backtesting
# Initialize backtesting object
def run_backtest():
from freqtrade.optimize.optimize_reports import generate_backtest_stats
from freqtrade.resolvers import StrategyResolver
asyncio.set_event_loop(asyncio.new_event_loop())
try:
# Reload strategy
lastconfig = ApiServer._bt_last_config
strat = StrategyResolver.load_strategy(btconfig)
if (
not ApiServer._bt
or lastconfig.get('timeframe') != strat.timeframe
or lastconfig.get('dry_run_wallet') != btconfig.get('dry_run_wallet', 0)
):
from freqtrade.optimize.backtesting import Backtesting
ApiServer._bt = Backtesting(btconfig)
# Only reload data if timeframe or timerange changed.
if (
not ApiServer._bt_data
or not ApiServer._bt_timerange
or lastconfig.get('timerange') != btconfig['timerange']
or lastconfig.get('stake_amount') != btconfig.get('stake_amount')
or lastconfig.get('enable_protections') != btconfig.get('enable_protections')
or lastconfig.get('protections') != btconfig.get('protections', [])
or lastconfig.get('timeframe') != strat.timeframe
):
lastconfig['timerange'] = btconfig['timerange']
lastconfig['protections'] = btconfig.get('protections', [])
lastconfig['enable_protections'] = btconfig.get('enable_protections')
lastconfig['dry_run_wallet'] = btconfig.get('dry_run_wallet')
lastconfig['timeframe'] = strat.timeframe
ApiServer._bt_data, ApiServer._bt_timerange = ApiServer._bt.load_bt_data()
ApiServer._bt.abort = False
min_date, max_date = ApiServer._bt.backtest_one_strategy(
strat, ApiServer._bt_data, ApiServer._bt_timerange)
ApiServer._bt.results = generate_backtest_stats(
ApiServer._bt_data, ApiServer._bt.all_results,
min_date=min_date, max_date=max_date)
logger.info("Backtest finished.")
except DependencyException as e:
logger.info(f"Backtesting caused an error: {e}")
pass
finally:
ApiServer._bgtask_running = False
background_tasks.add_task(run_backtest)
ApiServer._bgtask_running = True
return {
"status": "running",
"running": True,
"progress": 0,
"step": str(BacktestState.STARTUP),
"status_msg": "Backtest started",
}
@router.get('/backtest', response_model=BacktestResponse, tags=['webserver', 'backtest'])
def api_get_backtest():
"""
Get backtesting result.
Returns Result after backtesting has been ran.
"""
from freqtrade.persistence import LocalTrade
if ApiServer._bgtask_running:
return {
"status": "running",
"running": True,
"step": ApiServer._bt.progress.action if ApiServer._bt else str(BacktestState.STARTUP),
"progress": ApiServer._bt.progress.progress if ApiServer._bt else 0,
"trade_count": len(LocalTrade.trades),
"status_msg": "Backtest running",
}
if not ApiServer._bt:
return {
"status": "not_started",
"running": False,
"step": "",
"progress": 0,
"status_msg": "Backtest not yet executed"
}
return {
"status": "ended",
"running": False,
"status_msg": "Backtest ended",
"step": "finished",
"progress": 1,
"backtest_result": ApiServer._bt.results,
}
@router.delete('/backtest', response_model=BacktestResponse, tags=['webserver', 'backtest'])
def api_delete_backtest():
"""Reset backtesting"""
if ApiServer._bgtask_running:
return {
"status": "running",
"running": True,
"step": "",
"progress": 0,
"status_msg": "Backtest running",
}
if ApiServer._bt:
del ApiServer._bt
ApiServer._bt = None
del ApiServer._bt_data
ApiServer._bt_data = None
logger.info("Backtesting reset")
return {
"status": "reset",
"running": False,
"step": "",
"progress": 0,
"status_msg": "Backtest reset",
}
@router.get('/backtest/abort', response_model=BacktestResponse, tags=['webserver', 'backtest'])
def api_backtest_abort():
if not ApiServer._bgtask_running:
return {
"status": "not_running",
"running": False,
"step": "",
"progress": 0,
"status_msg": "Backtest ended",
}
ApiServer._bt.abort = True
return {
"status": "stopping",
"running": False,
"step": "",
"progress": 0,
"status_msg": "Backtest ended",
}

34
freqtrade/rpc/api_server/api_schemas.py
View File

@ -67,12 +67,16 @@ class Profit(BaseModel):
profit_closed_ratio_mean: float
profit_closed_percent_sum: float
profit_closed_ratio_sum: float
profit_closed_percent: float
profit_closed_ratio: float
profit_closed_fiat: float
profit_all_coin: float
profit_all_percent_mean: float
profit_all_ratio_mean: float
profit_all_percent_sum: float
profit_all_ratio_sum: float
profit_all_percent: float
profit_all_ratio: float
profit_all_fiat: float
trade_count: int
closed_trade_count: int
@ -115,20 +119,21 @@ class ShowConfig(BaseModel):
dry_run: bool
stake_currency: str
stake_amount: Union[float, str]
available_capital: Optional[float]
stake_currency_decimals: int
max_open_trades: int
minimal_roi: Dict[str, Any]
stoploss: float
trailing_stop: bool
stoploss: Optional[float]
trailing_stop: Optional[bool]
trailing_stop_positive: Optional[float]
trailing_stop_positive_offset: Optional[float]
trailing_only_offset_is_reached: Optional[bool]
use_custom_stoploss: Optional[bool]
timeframe: str
timeframe: Optional[str]
timeframe_ms: int
timeframe_min: int
exchange: str
strategy: str
strategy: Optional[str]
forcebuy_enabled: bool
ask_strategy: Dict[str, Any]
bid_strategy: Dict[str, Any]
@ -313,3 +318,24 @@ class PairHistory(BaseModel):
json_encoders = {
datetime: lambda v: v.strftime(DATETIME_PRINT_FORMAT),
}
class BacktestRequest(BaseModel):
strategy: str
timeframe: Optional[str]
timerange: Optional[str]
max_open_trades: Optional[int]
stake_amount: Optional[Union[float, str]]
enable_protections: bool
dry_run_wallet: Optional[float]
class BacktestResponse(BaseModel):
status: str
running: bool
status_msg: str
step: str
progress: float
trade_count: Optional[float]
# TODO: Properly type backtestresult...
backtest_result: Optional[Dict[str, Any]]

5
freqtrade/rpc/api_server/api_v1.py
View File

@ -1,3 +1,4 @@
import logging
from copy import deepcopy
from pathlib import Path
from typing import List, Optional
@ -22,6 +23,8 @@ from freqtrade.rpc.api_server.deps import get_config, get_rpc, get_rpc_optional
from freqtrade.rpc.rpc import RPCException
logger = logging.getLogger(__name__)
# Public API, requires no auth.
router_public = APIRouter()
# Private API, protected by authentication
@ -249,7 +252,7 @@ def list_available_pairs(timeframe: Optional[str] = None, stake_currency: Option
pair_interval = sorted(pair_interval, key=lambda x: x[0])
pairs = list({x[0] for x in pair_interval})
pairs.sort()
result = {
'length': len(pairs),
'pairs': pairs,

11
freqtrade/rpc/api_server/web_ui.py
View File

@ -18,6 +18,17 @@ async def fallback():
return FileResponse(str(Path(__file__).parent / 'ui/fallback_file.html'))
@router_ui.get('/ui_version', include_in_schema=False)
async def ui_version():
from freqtrade.commands.deploy_commands import read_ui_version
uibase = Path(__file__).parent / 'ui/installed/'
version = read_ui_version(uibase)
return {
"version": version if version else "not_installed",
}
@router_ui.get('/{rest_of_path:path}', include_in_schema=False)
async def index_html(rest_of_path: str):
"""

63
freqtrade/rpc/api_server/webserver.py
View File

@ -8,6 +8,7 @@ from fastapi import Depends, FastAPI
from fastapi.middleware.cors import CORSMiddleware
from starlette.responses import JSONResponse
from freqtrade.exceptions import OperationalException
from freqtrade.rpc.api_server.uvicorn_threaded import UvicornServer
from freqtrade.rpc.rpc import RPC, RPCException, RPCHandler
@ -28,17 +29,37 @@ class FTJSONResponse(JSONResponse):
class ApiServer(RPCHandler):
__instance = None
__initialized = False
_rpc: RPC
# Backtesting type: Backtesting
_bt = None
_bt_data = None
_bt_timerange = None
_bt_last_config: Dict[str, Any] = {}
_has_rpc: bool = False
_bgtask_running: bool = False
_config: Dict[str, Any] = {}
def __init__(self, rpc: RPC, config: Dict[str, Any]) -> None:
super().__init__(rpc, config)
self._server = None
def __new__(cls, *args, **kwargs):
"""
This class is a singleton.
We'll only have one instance of it around.
"""
if ApiServer.__instance is None:
ApiServer.__instance = object.__new__(cls)
ApiServer.__initialized = False
return ApiServer.__instance
ApiServer._rpc = rpc
ApiServer._has_rpc = True
def __init__(self, config: Dict[str, Any], standalone: bool = False) -> None:
ApiServer._config = config
if self.__initialized and (standalone or self._standalone):
return
self._standalone: bool = standalone
self._server = None
ApiServer.__initialized = True
api_config = self._config['api_server']
self.app = FastAPI(title="Freqtrade API",
@ -50,12 +71,33 @@ class ApiServer(RPCHandler):
self.start_api()
def add_rpc_handler(self, rpc: RPC):
"""
Attach rpc handler
"""
if not self._has_rpc:
ApiServer._rpc = rpc
ApiServer._has_rpc = True
else:
# This should not happen assuming we didn't mess up.
raise OperationalException('RPC Handler already attached.')
def cleanup(self) -> None:
""" Cleanup pending module resources """
if self._server:
ApiServer._has_rpc = False
del ApiServer._rpc
if self._server and not self._standalone:
logger.info("Stopping API Server")
self._server.cleanup()
@classmethod
def shutdown(cls):
cls.__initialized = False
del cls.__instance
cls.__instance = None
cls._has_rpc = False
cls._rpc = None
def send_msg(self, msg: Dict[str, str]) -> None:
pass
@ -68,6 +110,7 @@ class ApiServer(RPCHandler):
def configure_app(self, app: FastAPI, config):
from freqtrade.rpc.api_server.api_auth import http_basic_or_jwt_token, router_login
from freqtrade.rpc.api_server.api_backtest import router as api_backtest
from freqtrade.rpc.api_server.api_v1 import router as api_v1
from freqtrade.rpc.api_server.api_v1 import router_public as api_v1_public
from freqtrade.rpc.api_server.web_ui import router_ui
@ -77,6 +120,9 @@ class ApiServer(RPCHandler):
app.include_router(api_v1, prefix="/api/v1",
dependencies=[Depends(http_basic_or_jwt_token)],
)
app.include_router(api_backtest, prefix="/api/v1",
dependencies=[Depends(http_basic_or_jwt_token)],
)
app.include_router(router_login, prefix="/api/v1", tags=["auth"])
# UI Router MUST be last!
app.include_router(router_ui, prefix='')
@ -125,6 +171,9 @@ class ApiServer(RPCHandler):
)
try:
self._server = UvicornServer(uvconfig)
self._server.run_in_thread()
if self._standalone:
self._server.run()
else:
self._server.run_in_thread()
except Exception:
logger.exception("Api server failed to start.")

36
freqtrade/rpc/rpc.py
View File

@ -106,6 +106,7 @@ class RPC:
'stake_currency': config['stake_currency'],
'stake_currency_decimals': decimals_per_coin(config['stake_currency']),
'stake_amount': config['stake_amount'],
'available_capital': config.get('available_capital'),
'max_open_trades': (config['max_open_trades']
if config['max_open_trades'] != float('inf') else -1),
'minimal_roi': config['minimal_roi'].copy() if 'minimal_roi' in config else {},
@ -118,9 +119,9 @@ class RPC:
'bot_name': config.get('bot_name', 'freqtrade'),
'timeframe': config.get('timeframe'),
'timeframe_ms': timeframe_to_msecs(config['timeframe']
) if 'timeframe' in config else '',
) if 'timeframe' in config else 0,
'timeframe_min': timeframe_to_minutes(config['timeframe']
) if 'timeframe' in config else '',
) if 'timeframe' in config else 0,
'exchange': config['exchange']['name'],
'strategy': config['strategy'],
'forcebuy_enabled': config.get('forcebuy_enable', False),
@ -153,7 +154,8 @@ class RPC:
# calculate profit and send message to user
if trade.is_open:
try:
current_rate = self._freqtrade.exchange.get_sell_rate(trade.pair, False)
current_rate = self._freqtrade.exchange.get_rate(
trade.pair, refresh=False, side="sell")
except (ExchangeError, PricingError):
current_rate = NAN
else:
@ -212,7 +214,8 @@ class RPC:
for trade in trades:
# calculate profit and send message to user
try:
current_rate = self._freqtrade.exchange.get_sell_rate(trade.pair, False)
current_rate = self._freqtrade.exchange.get_rate(
trade.pair, refresh=False, side="sell")
except (PricingError, ExchangeError):
current_rate = NAN
trade_percent = (100 * trade.calc_profit_ratio(current_rate))
@ -271,10 +274,10 @@ class RPC:
'date': key,
'abs_profit': value["amount"],
'fiat_value': self._fiat_converter.convert_amount(
value['amount'],
stake_currency,
fiat_display_currency
) if self._fiat_converter else 0,
value['amount'],
stake_currency,
fiat_display_currency
) if self._fiat_converter else 0,
'trade_count': value["trades"],
}
for key, value in profit_days.items()
@ -371,7 +374,8 @@ class RPC:
else:
# Get current rate
try:
current_rate = self._freqtrade.exchange.get_sell_rate(trade.pair, False)
current_rate = self._freqtrade.exchange.get_rate(
trade.pair, refresh=False, side="sell")
except (PricingError, ExchangeError):
current_rate = NAN
profit_ratio = trade.calc_profit_ratio(rate=current_rate)
@ -396,7 +400,12 @@ class RPC:
profit_all_coin_sum = round(sum(profit_all_coin), 8)
profit_all_ratio_mean = float(mean(profit_all_ratio) if profit_all_ratio else 0.0)
# Doing the sum is not right - overall profit needs to be based on initial capital
profit_all_ratio_sum = sum(profit_all_ratio) if profit_all_ratio else 0.0
starting_balance = self._freqtrade.wallets.get_starting_balance()
profit_closed_ratio_fromstart = profit_closed_coin_sum / starting_balance
profit_all_ratio_fromstart = profit_all_coin_sum / starting_balance
profit_all_fiat = self._fiat_converter.convert_amount(
profit_all_coin_sum,
stake_currency,
@ -412,12 +421,16 @@ class RPC:
'profit_closed_ratio_mean': profit_closed_ratio_mean,
'profit_closed_percent_sum': round(profit_closed_ratio_sum * 100, 2),
'profit_closed_ratio_sum': profit_closed_ratio_sum,
'profit_closed_ratio': profit_closed_ratio_fromstart,
'profit_closed_percent': round(profit_closed_ratio_fromstart * 100, 2),
'profit_closed_fiat': profit_closed_fiat,
'profit_all_coin': profit_all_coin_sum,
'profit_all_percent_mean': round(profit_all_ratio_mean * 100, 2),
'profit_all_ratio_mean': profit_all_ratio_mean,
'profit_all_percent_sum': round(profit_all_ratio_sum * 100, 2),
'profit_all_ratio_sum': profit_all_ratio_sum,
'profit_all_ratio': profit_all_ratio_fromstart,
'profit_all_percent': round(profit_all_ratio_fromstart * 100, 2),
'profit_all_fiat': profit_all_fiat,
'trade_count': len(trades),
'closed_trade_count': len([t for t in trades if not t.is_open]),
@ -541,7 +554,8 @@ class RPC:
if not fully_canceled:
# Get current rate and execute sell
current_rate = self._freqtrade.exchange.get_sell_rate(trade.pair, False)
current_rate = self._freqtrade.exchange.get_rate(
trade.pair, refresh=False, side="sell")
sell_reason = SellCheckTuple(sell_type=SellType.FORCE_SELL)
self._freqtrade.execute_sell(trade, current_rate, sell_reason)
# ---- EOF def _exec_forcesell ----
@ -761,7 +775,7 @@ class RPC:
sell_signals = 0
if has_content:
dataframe.loc[:, '__date_ts'] = dataframe.loc[:, 'date'].astype(int64) // 1000 // 1000
dataframe.loc[:, '__date_ts'] = dataframe.loc[:, 'date'].view(int64) // 1000 // 1000
# Move open to seperate column when signal for easy plotting
if 'buy' in dataframe.columns:
buy_mask = (dataframe['buy'] == 1)

11
freqtrade/rpc/rpc_manager.py
View File

@ -1,5 +1,5 @@
"""
This module contains class to manage RPC communications (Telegram, Slack, ...)
This module contains class to manage RPC communications (Telegram, API, ...)
"""
import logging
from typing import Any, Dict, List
@ -13,7 +13,7 @@ logger = logging.getLogger(__name__)
class RPCManager:
"""
Class to manage RPC objects (Telegram, Slack, ...)
Class to manage RPC objects (Telegram, API, ...)
"""
def __init__(self, freqtrade) -> None:
""" Initializes all enabled rpc modules """
@ -36,15 +36,16 @@ class RPCManager:
if config.get('api_server', {}).get('enabled', False):
logger.info('Enabling rpc.api_server')
from freqtrade.rpc.api_server import ApiServer
self.registered_modules.append(ApiServer(self._rpc, config))
apiserver = ApiServer(config)
apiserver.add_rpc_handler(self._rpc)
self.registered_modules.append(apiserver)
def cleanup(self) -> None:
""" Stops all enabled rpc modules """
logger.info('Cleaning up rpc modules ...')
while self.registered_modules:
mod = self.registered_modules.pop()
logger.debug('Cleaning up rpc.%s ...', mod.name)
logger.info('Cleaning up rpc.%s ...', mod.name)
mod.cleanup()
del mod

27
freqtrade/rpc/telegram.py
View File

@ -24,7 +24,7 @@ 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.misc import chunks, plural, round_coin_value
from freqtrade.rpc import RPC, RPCException, RPCHandler
@ -494,11 +494,11 @@ class Telegram(RPCHandler):
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']
profit_closed_percent = stats['profit_closed_percent']
profit_closed_fiat = stats['profit_closed_fiat']
profit_all_coin = stats['profit_all_coin']
profit_all_percent_mean = stats['profit_all_percent_mean']
profit_all_percent_sum = stats['profit_all_percent_sum']
profit_all_percent = stats['profit_all_percent']
profit_all_fiat = stats['profit_all_fiat']
trade_count = stats['trade_count']
first_trade_date = stats['first_trade_date']
@ -514,7 +514,7 @@ class Telegram(RPCHandler):
markdown_msg = ("*ROI:* Closed trades\n"
f"∙ `{round_coin_value(profit_closed_coin, stake_cur)} "
f"({profit_closed_percent_mean:.2f}%) "
f"({profit_closed_percent_sum} \N{GREEK CAPITAL LETTER SIGMA}%)`\n"
f"({profit_closed_percent} \N{GREEK CAPITAL LETTER SIGMA}%)`\n"
f"∙ `{round_coin_value(profit_closed_fiat, fiat_disp_cur)}`\n")
else:
markdown_msg = "`No closed trade` \n"
@ -523,7 +523,7 @@ class Telegram(RPCHandler):
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"({profit_all_percent} \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'}:* "
@ -598,7 +598,10 @@ class Telegram(RPCHandler):
"Starting capital: "
f"`{self._config['dry_run_wallet']}` {self._config['stake_currency']}.\n"
)
total_dust_balance = 0
total_dust_currencies = 0
for curr in result['currencies']:
curr_output = ''
if curr['est_stake'] > balance_dust_level:
curr_output = (
f"*{curr['currency']}:*\n"
@ -607,9 +610,9 @@ class Telegram(RPCHandler):
f"\t`Pending: {curr['used']:.8f}`\n"
f"\t`Est. {curr['stake']}: "
f"{round_coin_value(curr['est_stake'], curr['stake'], False)}`\n")
else:
curr_output = (f"*{curr['currency']}:* not showing <{balance_dust_level} "
f"{curr['stake']} amount \n")
elif curr['est_stake'] <= balance_dust_level:
total_dust_balance += curr['est_stake']
total_dust_currencies += 1
# Handle overflowing message length
if len(output + curr_output) >= MAX_TELEGRAM_MESSAGE_LENGTH:
@ -618,6 +621,14 @@ class Telegram(RPCHandler):
else:
output += curr_output
if total_dust_balance > 0:
output += (
f"*{total_dust_currencies} Other "
f"{plural(total_dust_currencies, 'Currency', 'Currencies')} "
f"(< {balance_dust_level} {result['stake']}):*\n"
f"\t`Est. {result['stake']}: "
f"{round_coin_value(total_dust_balance, result['stake'], False)}`\n")
output += ("\n*Estimated Value*:\n"
f"\t`{result['stake']}: {result['total']: .8f}`\n"
f"\t`{result['symbol']}: "

36
freqtrade/strategy/hyper.py
View File

@ -5,8 +5,10 @@ This module defines a base class for auto-hyperoptable strategies.
import logging
from abc import ABC, abstractmethod
from contextlib import suppress
from pathlib import Path
from typing import Any, Dict, Iterator, List, Optional, Sequence, Tuple, Union
from freqtrade.misc import deep_merge_dicts, json_load
from freqtrade.optimize.hyperopt_tools import HyperoptTools
@ -333,10 +335,36 @@ class HyperStrategyMixin(object):
"""
Load Hyperoptable parameters
"""
self._load_params(getattr(self, 'buy_params', None), 'buy', hyperopt)
self._load_params(getattr(self, 'sell_params', None), 'sell', hyperopt)
params = self.load_params_from_file()
params = params.get('params', {})
self._ft_params_from_file = params
buy_params = deep_merge_dicts(params.get('buy', {}), getattr(self, 'buy_params', None))
sell_params = deep_merge_dicts(params.get('sell', {}), getattr(self, 'sell_params', None))
def _load_params(self, params: dict, space: str, hyperopt: bool = False) -> None:
self._load_params(buy_params, 'buy', hyperopt)
self._load_params(sell_params, 'sell', hyperopt)
def load_params_from_file(self) -> Dict:
filename_str = getattr(self, '__file__', '')
if not filename_str:
return {}
filename = Path(filename_str).with_suffix('.json')
if filename.is_file():
logger.info(f"Loading parameters from file {filename}")
try:
params = json_load(filename.open('r'))
if params.get('strategy_name') != self.__class__.__name__:
raise OperationalException('Invalid parameter file provided.')
return params
except ValueError:
logger.warning("Invalid parameter file format.")
return {}
logger.info("Found no parameter file.")
return {}
def _load_params(self, params: Dict, space: str, hyperopt: bool = False) -> None:
"""
Set optimizable parameter values.
:param params: Dictionary with new parameter values.
@ -363,7 +391,7 @@ class HyperStrategyMixin(object):
else:
logger.info(f'Strategy Parameter(default): {attr_name} = {attr.value}')
def get_params_dict(self):
def get_no_optimize_params(self):
"""
Returns list of Parameters that are not part of the current optimize job
"""

18
freqtrade/strategy/interface.py
View File

@ -62,6 +62,7 @@ class IStrategy(ABC, HyperStrategyMixin):
_populate_fun_len: int = 0
_buy_fun_len: int = 0
_sell_fun_len: int = 0
_ft_params_from_file: Dict = {}
# associated minimal roi
minimal_roi: Dict
@ -303,6 +304,23 @@ class IStrategy(ABC, HyperStrategyMixin):
"""
return None
def custom_stake_amount(self, pair: str, current_time: datetime, current_rate: float,
proposed_stake: float, min_stake: float, max_stake: float,
**kwargs) -> float:
"""
Customize stake size for each new trade. This method is not called when edge module is
enabled.
:param pair: Pair that's currently analyzed
:param current_time: datetime object, containing the current datetime
:param current_rate: Rate, calculated based on pricing settings in ask_strategy.
:param proposed_stake: A stake amount proposed by the bot.
:param min_stake: Minimal stake size allowed by exchange.
:param max_stake: Balance available for trading.
:return: A stake size, which is between min_stake and max_stake.
"""
return proposed_stake
def informative_pairs(self) -> ListPairsWithTimeframes:
"""
Define additional, informative pair/interval combinations to be cached from the exchange.

48
freqtrade/templates/strategy_analysis_example.ipynb
View File

@ -188,6 +188,52 @@
"trades.groupby(\"pair\")[\"sell_reason\"].value_counts()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Plotting daily profit / equity line"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Plotting equity line (starting with 0 on day 1 and adding daily profit for each backtested day)\n",
"\n",
"from freqtrade.configuration import Configuration\n",
"from freqtrade.data.btanalysis import load_backtest_data, load_backtest_stats\n",
"import plotly.express as px\n",
"import pandas as pd\n",
"\n",
"# strategy = 'SampleStrategy'\n",
"# config = Configuration.from_files([\"user_data/config.json\"])\n",
"# backtest_dir = config[\"user_data_dir\"] / \"backtest_results\"\n",
"\n",
"stats = load_backtest_stats(backtest_dir)\n",
"strategy_stats = stats['strategy'][strategy]\n",
"\n",
"dates = []\n",
"profits = []\n",
"for date_profit in strategy_stats['daily_profit']:\n",
" dates.append(date_profit[0])\n",
" profits.append(date_profit[1])\n",
"\n",
"equity = 0\n",
"equity_daily = []\n",
"for daily_profit in profits:\n",
" equity_daily.append(equity)\n",
" equity += float(daily_profit)\n",
"\n",
"\n",
"df = pd.DataFrame({'dates': dates,'equity_daily': equity_daily})\n",
"\n",
"fig = px.line(df, x=\"dates\", y=\"equity_daily\")\n",
"fig.show()\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
@ -329,7 +375,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.4"
"version": "3.8.5"
},
"mimetype": "text/x-python",
"name": "python",

77
freqtrade/wallets.py
View File

@ -70,9 +70,7 @@ class Wallets:
# If not backtesting...
# TODO: potentially remove the ._log workaround to determine backtest mode.
if self._log:
closed_trades = Trade.get_trades_proxy(is_open=False)
tot_profit = sum(
[trade.close_profit_abs for trade in closed_trades if trade.close_profit_abs])
tot_profit = Trade.get_total_closed_profit()
else:
tot_profit = LocalTrade.total_profit
tot_in_trades = sum([trade.stake_amount for trade in open_trades])
@ -131,7 +129,41 @@ class Wallets:
def get_all_balances(self) -> Dict[str, Any]:
return self._wallets
def _get_available_stake_amount(self, val_tied_up: float) -> float:
def get_starting_balance(self) -> float:
"""
Retrieves starting balance - based on either available capital,
or by using current balance subtracting
"""
if "available_capital" in self._config:
return self._config['available_capital']
else:
tot_profit = Trade.get_total_closed_profit()
open_stakes = Trade.total_open_trades_stakes()
available_balance = self.get_free(self._config['stake_currency'])
return available_balance - tot_profit + open_stakes
def get_total_stake_amount(self):
"""
Return the total currently available balance in stake currency, including tied up stake and
respecting tradable_balance_ratio.
Calculated as
(<open_trade stakes> + free amount) * tradable_balance_ratio
"""
val_tied_up = Trade.total_open_trades_stakes()
if "available_capital" in self._config:
starting_balance = self._config['available_capital']
tot_profit = Trade.get_total_closed_profit()
available_amount = starting_balance + tot_profit
else:
# Ensure <tradable_balance_ratio>% is used from the overall balance
# Otherwise we'd risk lowering stakes with each open trade.
# (tied up + current free) * ratio) - tied up
available_amount = ((val_tied_up + self.get_free(self._config['stake_currency'])) *
self._config['tradable_balance_ratio'])
return available_amount
def get_available_stake_amount(self) -> float:
"""
Return the total currently available balance in stake currency,
respecting tradable_balance_ratio.
@ -139,12 +171,8 @@ class Wallets:
(<open_trade stakes> + free amount) * tradable_balance_ratio - <open_trade stakes>
"""
# Ensure <tradable_balance_ratio>% is used from the overall balance
# Otherwise we'd risk lowering stakes with each open trade.
# (tied up + current free) * ratio) - tied up
available_amount = ((val_tied_up + self.get_free(self._config['stake_currency'])) *
self._config['tradable_balance_ratio']) - val_tied_up
return available_amount
free = self.get_free(self._config['stake_currency'])
return min(self.get_total_stake_amount() - Trade.total_open_trades_stakes(), free)
def _calculate_unlimited_stake_amount(self, available_amount: float,
val_tied_up: float) -> float:
@ -193,7 +221,7 @@ class Wallets:
# Ensure wallets are uptodate.
self.update()
val_tied_up = Trade.total_open_trades_stakes()
available_amount = self._get_available_stake_amount(val_tied_up)
available_amount = self.get_available_stake_amount()
if edge:
stake_amount = edge.stake_amount(
@ -209,3 +237,30 @@ class Wallets:
available_amount, val_tied_up)
return self._check_available_stake_amount(stake_amount, available_amount)
def _validate_stake_amount(self, pair, stake_amount, min_stake_amount):
if not stake_amount:
logger.debug(f"Stake amount is {stake_amount}, ignoring possible trade for {pair}.")
return 0
max_stake_amount = self.get_available_stake_amount()
if min_stake_amount > max_stake_amount:
if self._log:
logger.warning("Minimum stake amount > available balance.")
return 0
if min_stake_amount is not None and stake_amount < min_stake_amount:
stake_amount = min_stake_amount
if self._log:
logger.info(
f"Stake amount for pair {pair} is too small "
f"({stake_amount} < {min_stake_amount}), adjusting to {min_stake_amount}."
)
if stake_amount > max_stake_amount:
stake_amount = max_stake_amount
if self._log:
logger.info(
f"Stake amount for pair {pair} is too big "
f"({stake_amount} > {max_stake_amount}), adjusting to {max_stake_amount}."
)
return stake_amount

2
requirements-dev.txt
View File

@ -13,7 +13,7 @@ pytest-asyncio==0.15.1
pytest-cov==2.12.1
pytest-mock==3.6.1
pytest-random-order==1.0.4
isort==5.9.1
isort==5.9.2
# Convert jupyter notebooks to markdown documents
nbconvert==6.1.0

2
requirements-plot.txt
View File

@ -1,5 +1,5 @@
# Include all requirements to run the bot.
-r requirements.txt
plotly==5.0.0
plotly==5.1.0

18
requirements.txt
View File

@ -1,19 +1,19 @@
numpy==1.21.0
pandas==1.2.5
numpy==1.21.1
pandas==1.3.0
ccxt==1.52.4
ccxt==1.53.25
# Pin cryptography for now due to rust build errors with piwheels
cryptography==3.4.7
aiohttp==3.7.4.post0
SQLAlchemy==1.4.19
python-telegram-bot==13.6
SQLAlchemy==1.4.21
python-telegram-bot==13.7
arrow==1.1.1
cachetools==4.2.2
requests==2.25.1
requests==2.26.0
urllib3==1.26.6
wrapt==1.12.1
jsonschema==3.2.0
TA-Lib==0.4.20
TA-Lib==0.4.21
technical==1.3.0
tabulate==0.8.9
pycoingecko==2.2.0
@ -31,7 +31,7 @@ python-rapidjson==1.4
sdnotify==0.3.2
# API Server
fastapi==0.65.2
fastapi==0.66.0
uvicorn==0.14.0
pyjwt==2.1.0
aiofiles==0.7.0
@ -39,5 +39,5 @@ aiofiles==0.7.0
# Support for colorized terminal output
colorama==0.4.4
# Building config files interactively
questionary==1.9.0
questionary==1.10.0
prompt-toolkit==3.0.19

101
setup.sh
View File

@ -4,8 +4,12 @@
function check_installed_pip() {
${PYTHON} -m pip > /dev/null
if [ $? -ne 0 ]; then
echo "pip not found (called as '${PYTHON} -m pip'). Please make sure that pip is available for ${PYTHON}."
exit 1
echo "-----------------------------"
echo "Installing Pip for ${PYTHON}"
echo "-----------------------------"
curl https://bootstrap.pypa.io/get-pip.py -o get-pip.py
${PYTHON} get-pip.py
rm get-pip.py
fi
}
@ -17,35 +21,19 @@ function check_installed_python() {
exit 2
fi
which python3.8
if [ $? -eq 0 ]; then
echo "using Python 3.8"
PYTHON=python3.8
check_installed_pip
return
fi
for v in 9 8 7
do
PYTHON="python3.${v}"
which $PYTHON
if [ $? -eq 0 ]; then
echo "using ${PYTHON}"
check_installed_pip
return
fi
done
which python3.9
if [ $? -eq 0 ]; then
echo "using Python 3.9"
PYTHON=python3.9
check_installed_pip
return
fi
which python3.7
if [ $? -eq 0 ]; then
echo "using Python 3.7"
PYTHON=python3.7
check_installed_pip
return
fi
if [ -z ${PYTHON} ]; then
echo "No usable python found. Please make sure to have python3.7 or newer installed"
exit 1
fi
echo "No usable python found. Please make sure to have python3.7 or newer installed"
exit 1
}
function updateenv() {
@ -122,6 +110,25 @@ function install_talib() {
cd ..
}
function install_mac_newer_python_dependencies() {
if [ ! $(brew --prefix --installed hdf5 2>/dev/null) ]
then
echo "-------------------------"
echo "Installing hdf5"
echo "-------------------------"
brew install hdf5
fi
if [ ! $(brew --prefix --installed c-blosc 2>/dev/null) ]
then
echo "-------------------------"
echo "Installing c-blosc"
echo "-------------------------"
brew install c-blosc
fi
}
# Install bot MacOS
function install_macos() {
if [ ! -x "$(command -v brew)" ]
@ -131,14 +138,19 @@ function install_macos() {
echo "-------------------------"
/usr/bin/ruby -e "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install)"
fi
#Gets number after decimal in python version
version=$(egrep -o 3.\[0-9\]+ <<< $PYTHON | sed 's/3.//g')
if [[ $version -ge 9 ]]; then #Checks if python version >= 3.9
install_mac_newer_python_dependencies
fi
install_talib
test_and_fix_python_on_mac
}
# Install bot Debian_ubuntu
function install_debian() {
sudo apt-get update
sudo apt-get install -y build-essential autoconf libtool pkg-config make wget git libpython3-dev
sudo apt-get install -y build-essential autoconf libtool pkg-config make wget git $(echo lib${PYTHON}-dev ${PYTHON}-venv)
install_talib
}
@ -189,19 +201,6 @@ function reset() {
updateenv
}
function test_and_fix_python_on_mac() {
if ! [ -x "$(command -v python3.6)" ]
then
echo "-------------------------"
echo "Fixing Python"
echo "-------------------------"
echo "Python 3.6 is not linked in your system. Fixing it..."
brew link --overwrite python
echo
fi
}
function config() {
echo "-------------------------"
@ -240,12 +239,12 @@ function install() {
}
function plot() {
echo "
-----------------------------------------
Installing dependencies for Plotting scripts
-----------------------------------------
"
${PYTHON} -m pip install plotly --upgrade
echo "
-----------------------------------------
Installing dependencies for Plotting scripts
-----------------------------------------
"
${PYTHON} -m pip install plotly --upgrade
}
function help() {

69
tests/commands/test_commands.py
View File

@ -13,7 +13,7 @@ from freqtrade.commands import (start_convert_data, start_create_userdir, start_
start_list_data, start_list_exchanges, start_list_hyperopts,
start_list_markets, start_list_strategies, start_list_timeframes,
start_new_hyperopt, start_new_strategy, start_show_trades,
start_test_pairlist, start_trading)
start_test_pairlist, start_trading, start_webserver)
from freqtrade.commands.deploy_commands import (clean_ui_subdir, download_and_install_ui,
get_ui_download_url, read_ui_version)
from freqtrade.configuration import setup_utils_configuration
@ -26,7 +26,7 @@ from tests.conftest_trades import MOCK_TRADE_COUNT
def test_setup_utils_configuration():
args = [
'list-exchanges', '--config', 'config_bittrex.json.example',
'list-exchanges', '--config', 'config_examples/config_bittrex.example.json',
]
config = setup_utils_configuration(get_args(args), RunMode.OTHER)
@ -45,7 +45,7 @@ def test_start_trading_fail(mocker, caplog):
exitmock = mocker.patch("freqtrade.worker.Worker.exit", MagicMock())
args = [
'trade',
'-c', 'config_bittrex.json.example'
'-c', 'config_examples/config_bittrex.example.json'
]
start_trading(get_args(args))
assert exitmock.call_count == 1
@ -58,6 +58,18 @@ def test_start_trading_fail(mocker, caplog):
assert log_has('Fatal exception!', caplog)
def test_start_webserver(mocker, caplog):
api_server_mock = mocker.patch("freqtrade.rpc.api_server.ApiServer", )
args = [
'webserver',
'-c', 'config_examples/config_bittrex.example.json'
]
start_webserver(get_args(args))
assert api_server_mock.call_count == 1
def test_list_exchanges(capsys):
args = [
@ -127,10 +139,10 @@ def test_list_timeframes(mocker, capsys):
match=r"This command requires a configured exchange.*"):
start_list_timeframes(pargs)
# Test with --config config_bittrex.json.example
# Test with --config config_examples/config_bittrex.example.json
args = [
"list-timeframes",
'--config', 'config_bittrex.json.example',
'--config', 'config_examples/config_bittrex.example.json',
]
start_list_timeframes(get_args(args))
captured = capsys.readouterr()
@ -174,7 +186,7 @@ def test_list_timeframes(mocker, capsys):
# Test with --one-column
args = [
"list-timeframes",
'--config', 'config_bittrex.json.example',
'--config', 'config_examples/config_bittrex.example.json',
"--one-column",
]
start_list_timeframes(get_args(args))
@ -214,10 +226,10 @@ def test_list_markets(mocker, markets, capsys):
match=r"This command requires a configured exchange.*"):
start_list_markets(pargs, False)
# Test with --config config_bittrex.json.example
# Test with --config config_examples/config_bittrex.example.json
args = [
"list-markets",
'--config', 'config_bittrex.json.example',
'--config', 'config_examples/config_bittrex.example.json',
"--print-list",
]
start_list_markets(get_args(args), False)
@ -244,7 +256,7 @@ def test_list_markets(mocker, markets, capsys):
# Test with --all: all markets
args = [
"list-markets", "--all",
'--config', 'config_bittrex.json.example',
'--config', 'config_examples/config_bittrex.example.json',
"--print-list",
]
start_list_markets(get_args(args), False)
@ -257,7 +269,7 @@ def test_list_markets(mocker, markets, capsys):
# Test list-pairs subcommand: active pairs
args = [
"list-pairs",
'--config', 'config_bittrex.json.example',
'--config', 'config_examples/config_bittrex.example.json',
"--print-list",
]
start_list_markets(get_args(args), True)
@ -269,7 +281,7 @@ def test_list_markets(mocker, markets, capsys):
# Test list-pairs subcommand with --all: all pairs
args = [
"list-pairs", "--all",
'--config', 'config_bittrex.json.example',
'--config', 'config_examples/config_bittrex.example.json',
"--print-list",
]
start_list_markets(get_args(args), True)
@ -282,7 +294,7 @@ def test_list_markets(mocker, markets, capsys):
# active markets, base=ETH, LTC
args = [
"list-markets",
'--config', 'config_bittrex.json.example',
'--config', 'config_examples/config_bittrex.example.json',
"--base", "ETH", "LTC",
"--print-list",
]
@ -295,7 +307,7 @@ def test_list_markets(mocker, markets, capsys):
# active markets, base=LTC
args = [
"list-markets",
'--config', 'config_bittrex.json.example',
'--config', 'config_examples/config_bittrex.example.json',
"--base", "LTC",
"--print-list",
]
@ -308,7 +320,7 @@ def test_list_markets(mocker, markets, capsys):
# active markets, quote=USDT, USD
args = [
"list-markets",
'--config', 'config_bittrex.json.example',
'--config', 'config_examples/config_bittrex.example.json',
"--quote", "USDT", "USD",
"--print-list",
]
@ -321,7 +333,7 @@ def test_list_markets(mocker, markets, capsys):
# active markets, quote=USDT
args = [
"list-markets",
'--config', 'config_bittrex.json.example',
'--config', 'config_examples/config_bittrex.example.json',
"--quote", "USDT",
"--print-list",
]
@ -334,7 +346,7 @@ def test_list_markets(mocker, markets, capsys):
# active markets, base=LTC, quote=USDT
args = [
"list-markets",
'--config', 'config_bittrex.json.example',
'--config', 'config_examples/config_bittrex.example.json',
"--base", "LTC", "--quote", "USDT",
"--print-list",
]
@ -347,7 +359,7 @@ def test_list_markets(mocker, markets, capsys):
# active pairs, base=LTC, quote=USDT
args = [
"list-pairs",
'--config', 'config_bittrex.json.example',
'--config', 'config_examples/config_bittrex.example.json',
"--base", "LTC", "--quote", "USD",
"--print-list",
]
@ -360,7 +372,7 @@ def test_list_markets(mocker, markets, capsys):
# active markets, base=LTC, quote=USDT, NONEXISTENT
args = [
"list-markets",
'--config', 'config_bittrex.json.example',
'--config', 'config_examples/config_bittrex.example.json',
"--base", "LTC", "--quote", "USDT", "NONEXISTENT",
"--print-list",
]
@ -373,7 +385,7 @@ def test_list_markets(mocker, markets, capsys):
# active markets, base=LTC, quote=NONEXISTENT
args = [
"list-markets",
'--config', 'config_bittrex.json.example',
'--config', 'config_examples/config_bittrex.example.json',
"--base", "LTC", "--quote", "NONEXISTENT",
"--print-list",
]
@ -386,7 +398,7 @@ def test_list_markets(mocker, markets, capsys):
# Test tabular output
args = [
"list-markets",
'--config', 'config_bittrex.json.example',
'--config', 'config_examples/config_bittrex.example.json',
]
start_list_markets(get_args(args), False)
captured = capsys.readouterr()
@ -396,7 +408,7 @@ def test_list_markets(mocker, markets, capsys):
# Test tabular output, no markets found
args = [
"list-markets",
'--config', 'config_bittrex.json.example',
'--config', 'config_examples/config_bittrex.example.json',
"--base", "LTC", "--quote", "NONEXISTENT",
]
start_list_markets(get_args(args), False)
@ -408,7 +420,7 @@ def test_list_markets(mocker, markets, capsys):
# Test --print-json
args = [
"list-markets",
'--config', 'config_bittrex.json.example',
'--config', 'config_examples/config_bittrex.example.json',
"--print-json"
]
start_list_markets(get_args(args), False)
@ -420,7 +432,7 @@ def test_list_markets(mocker, markets, capsys):
# Test --print-csv
args = [
"list-markets",
'--config', 'config_bittrex.json.example',
'--config', 'config_examples/config_bittrex.example.json',
"--print-csv"
]
start_list_markets(get_args(args), False)
@ -432,7 +444,7 @@ def test_list_markets(mocker, markets, capsys):
# Test --one-column
args = [
"list-markets",
'--config', 'config_bittrex.json.example',
'--config', 'config_examples/config_bittrex.example.json',
"--one-column"
]
start_list_markets(get_args(args), False)
@ -444,7 +456,7 @@ def test_list_markets(mocker, markets, capsys):
# Test --one-column
args = [
"list-markets",
'--config', 'config_bittrex.json.example',
'--config', 'config_examples/config_bittrex.example.json',
"--one-column"
]
with pytest.raises(OperationalException, match=r"Cannot get markets.*"):
@ -887,7 +899,7 @@ def test_start_test_pairlist(mocker, caplog, tickers, default_conf, capsys):
patched_configuration_load_config_file(mocker, default_conf)
args = [
'test-pairlist',
'-c', 'config_bittrex.json.example'
'-c', 'config_examples/config_bittrex.example.json'
]
start_test_pairlist(get_args(args))
@ -901,7 +913,7 @@ def test_start_test_pairlist(mocker, caplog, tickers, default_conf, capsys):
args = [
'test-pairlist',
'-c', 'config_bittrex.json.example',
'-c', 'config_examples/config_bittrex.example.json',
'--one-column',
]
start_test_pairlist(get_args(args))
@ -910,7 +922,7 @@ def test_start_test_pairlist(mocker, caplog, tickers, default_conf, capsys):
args = [
'test-pairlist',
'-c', 'config_bittrex.json.example',
'-c', 'config_examples/config_bittrex.example.json',
'--print-json',
]
start_test_pairlist(get_args(args))
@ -1168,6 +1180,7 @@ def test_hyperopt_show(mocker, capsys, saved_hyperopt_results):
'freqtrade.optimize.hyperopt_tools.HyperoptTools.load_previous_results',
MagicMock(return_value=saved_hyperopt_results)
)
mocker.patch('freqtrade.commands.hyperopt_commands.show_backtest_result')
args = [
"hyperopt-show",

8
tests/conftest.py
View File

@ -324,6 +324,7 @@ def get_default_conf(testdatadir):
"verbosity": 3,
"strategy_path": str(Path(__file__).parent / "strategy" / "strats"),
"strategy": "DefaultStrategy",
"disableparamexport": True,
"internals": {},
"export": "none",
}
@ -1761,7 +1762,7 @@ def rpc_balance():
'total': 0.1,
'free': 0.01,
'used': 0.0
},
},
'EUR': {
'total': 10.0,
'free': 10.0,
@ -1953,12 +1954,13 @@ def saved_hyperopt_results():
'params_dict': {
'mfi-value': 15, 'fastd-value': 20, 'adx-value': 25, 'rsi-value': 28, 'mfi-enabled': False, 'fastd-enabled': True, 'adx-enabled': True, 'rsi-enabled': True, 'trigger': 'macd_cross_signal', 'sell-mfi-value': 88, 'sell-fastd-value': 97, 'sell-adx-value': 51, 'sell-rsi-value': 67, 'sell-mfi-enabled': False, 'sell-fastd-enabled': False, 'sell-adx-enabled': True, 'sell-rsi-enabled': True, 'sell-trigger': 'sell-bb_upper', 'roi_t1': 1190, 'roi_t2': 541, 'roi_t3': 408, 'roi_p1': 0.026035863879169705, 'roi_p2': 0.12508730043628782, 'roi_p3': 0.27766427921605896, 'stoploss': -0.2562930402099556}, # noqa: E501
'params_details': {'buy': {'mfi-value': 15, 'fastd-value': 20, 'adx-value': 25, 'rsi-value': 28, 'mfi-enabled': False, 'fastd-enabled': True, 'adx-enabled': True, 'rsi-enabled': True, 'trigger': 'macd_cross_signal'}, 'sell': {'sell-mfi-value': 88, 'sell-fastd-value': 97, 'sell-adx-value': 51, 'sell-rsi-value': 67, 'sell-mfi-enabled': False, 'sell-fastd-enabled': False, 'sell-adx-enabled': True, 'sell-rsi-enabled': True, 'sell-trigger': 'sell-bb_upper'}, 'roi': {0: 0.4287874435315165, 408: 0.15112316431545753, 949: 0.026035863879169705, 2139: 0}, 'stoploss': {'stoploss': -0.2562930402099556}}, # noqa: E501
'results_metrics': {'total_trades': 2, 'wins': 0, 'draws': 0, 'losses': 2, 'profit_mean': -0.01254995, 'profit_median': -0.012222, 'profit_total': -0.00125625, 'profit_total_abs': -2.50999, 'holding_avg': timedelta(minutes=3930.0)}, # noqa: E501
'results_metrics': {'total_trades': 2, 'wins': 0, 'draws': 0, 'losses': 2, 'profit_mean': -0.01254995, 'profit_median': -0.012222, 'profit_total': -0.00125625, 'profit_total_abs': -2.50999, 'holding_avg': timedelta(minutes=3930.0), 'stake_currency': 'BTC', 'strategy_name': 'SampleStrategy'}, # noqa: E501
'results_explanation': ' 2 trades. Avg profit -1.25%. Total profit -0.00125625 BTC ( -2.51Σ%). Avg duration 3930.0 min.', # noqa: E501
'total_profit': -0.00125625,
'current_epoch': 1,
'is_initial_point': True,
'is_best': True
'is_best': True,
}, {
'loss': 20.0,
'params_dict': {

26
tests/exchange/test_exchange.py
View File

@ -1783,14 +1783,14 @@ def test_get_buy_rate(mocker, default_conf, caplog, side, ask, bid,
mocker.patch('freqtrade.exchange.Exchange.fetch_ticker',
return_value={'ask': ask, 'last': last, 'bid': bid})
assert exchange.get_buy_rate('ETH/BTC', True) == expected
assert exchange.get_rate('ETH/BTC', refresh=True, side="buy") == expected
assert not log_has("Using cached buy rate for ETH/BTC.", caplog)
assert exchange.get_buy_rate('ETH/BTC', False) == expected
assert exchange.get_rate('ETH/BTC', refresh=False, side="buy") == expected
assert log_has("Using cached buy rate for ETH/BTC.", caplog)
# Running a 2nd time with Refresh on!
caplog.clear()
assert exchange.get_buy_rate('ETH/BTC', True) == expected
assert exchange.get_rate('ETH/BTC', refresh=True, side="buy") == expected
assert not log_has("Using cached buy rate for ETH/BTC.", caplog)
@ -1825,12 +1825,12 @@ def test_get_sell_rate(default_conf, mocker, caplog, side, bid, ask,
# Test regular mode
exchange = get_patched_exchange(mocker, default_conf)
rate = exchange.get_sell_rate(pair, True)
rate = exchange.get_rate(pair, refresh=True, side="sell")
assert not log_has("Using cached sell rate for ETH/BTC.", caplog)
assert isinstance(rate, float)
assert rate == expected
# Use caching
rate = exchange.get_sell_rate(pair, False)
rate = exchange.get_rate(pair, refresh=False, side="sell")
assert rate == expected
assert log_has("Using cached sell rate for ETH/BTC.", caplog)
@ -1848,11 +1848,11 @@ def test_get_sell_rate_orderbook(default_conf, mocker, caplog, side, expected, o
pair = "ETH/BTC"
mocker.patch('freqtrade.exchange.Exchange.fetch_l2_order_book', order_book_l2)
exchange = get_patched_exchange(mocker, default_conf)
rate = exchange.get_sell_rate(pair, True)
rate = exchange.get_rate(pair, refresh=True, side="sell")
assert not log_has("Using cached sell rate for ETH/BTC.", caplog)
assert isinstance(rate, float)
assert rate == expected
rate = exchange.get_sell_rate(pair, False)
rate = exchange.get_rate(pair, refresh=False, side="sell")
assert rate == expected
assert log_has("Using cached sell rate for ETH/BTC.", caplog)
@ -1868,7 +1868,7 @@ def test_get_sell_rate_orderbook_exception(default_conf, mocker, caplog):
return_value={'bids': [[]], 'asks': [[]]})
exchange = get_patched_exchange(mocker, default_conf)
with pytest.raises(PricingError):
exchange.get_sell_rate(pair, True)
exchange.get_rate(pair, refresh=True, side="sell")
assert log_has_re(r"Sell Price at location 1 from orderbook could not be determined\..*",
caplog)
@ -1881,18 +1881,18 @@ def test_get_sell_rate_exception(default_conf, mocker, caplog):
return_value={'ask': None, 'bid': 0.12, 'last': None})
exchange = get_patched_exchange(mocker, default_conf)
with pytest.raises(PricingError, match=r"Sell-Rate for ETH/BTC was empty."):
exchange.get_sell_rate(pair, True)
exchange.get_rate(pair, refresh=True, side="sell")
exchange._config['ask_strategy']['price_side'] = 'bid'
assert exchange.get_sell_rate(pair, True) == 0.12
assert exchange.get_rate(pair, refresh=True, side="sell") == 0.12
# Reverse sides
mocker.patch('freqtrade.exchange.Exchange.fetch_ticker',
return_value={'ask': 0.13, 'bid': None, 'last': None})
with pytest.raises(PricingError, match=r"Sell-Rate for ETH/BTC was empty."):
exchange.get_sell_rate(pair, True)
exchange.get_rate(pair, refresh=True, side="sell")
exchange._config['ask_strategy']['price_side'] = 'ask'
assert exchange.get_sell_rate(pair, True) == 0.13
assert exchange.get_rate(pair, refresh=True, side="sell") == 0.13
def make_fetch_ohlcv_mock(data):
@ -2203,7 +2203,7 @@ def test_cancel_order_dry_run(default_conf, mocker, exchange_name):
({'status': 'canceled', 'filled': 10.0}, False),
({'status': 'unknown', 'filled': 10.0}, False),
({'result': 'testest123'}, False),
])
])
def test_check_order_canceled_empty(mocker, default_conf, exchange_name, order, result):
exchange = get_patched_exchange(mocker, default_conf, id=exchange_name)
assert exchange.check_order_canceled_empty(order) == result

25
tests/optimize/test_backtesting.py
View File

@ -346,6 +346,20 @@ def test_data_to_dataframe_bt(default_conf, mocker, testdatadir) -> None:
assert processed['UNITTEST/BTC'].equals(processed2['UNITTEST/BTC'])
def test_backtest_abort(default_conf, mocker, testdatadir) -> None:
patch_exchange(mocker)
backtesting = Backtesting(default_conf)
backtesting.check_abort()
backtesting.abort = True
with pytest.raises(DependencyException, match="Stop requested"):
backtesting.check_abort()
# abort flag resets
assert backtesting.abort is False
assert backtesting.progress.progress == 0
def test_backtesting_start(default_conf, mocker, testdatadir, caplog) -> None:
def get_timerange(input1):
return Arrow(2017, 11, 14, 21, 17), Arrow(2017, 11, 14, 22, 59)
@ -497,6 +511,17 @@ def test_backtest__enter_trade(default_conf, fee, mocker) -> None:
trade = backtesting._enter_trade(pair, row=row)
assert trade is not None
backtesting.strategy.custom_stake_amount = lambda **kwargs: 123.5
trade = backtesting._enter_trade(pair, row=row)
assert trade
assert trade.stake_amount == 123.5
# In case of error - use proposed stake
backtesting.strategy.custom_stake_amount = lambda **kwargs: 20 / 0
trade = backtesting._enter_trade(pair, row=row)
assert trade
assert trade.stake_amount == 495
# Stake-amount too high!
mocker.patch("freqtrade.exchange.Exchange.get_min_pair_stake_amount", return_value=600.0)

153
tests/optimize/test_hyperopt.py
View File

@ -1,9 +1,6 @@
# pragma pylint: disable=missing-docstring,W0212,C0103
import logging
import re
from datetime import datetime
from pathlib import Path
from typing import Dict, List
from unittest.mock import ANY, MagicMock
import pandas as pd
@ -28,12 +25,6 @@ from tests.conftest import (get_args, log_has, log_has_re, patch_exchange,
from .hyperopts.default_hyperopt import DefaultHyperOpt
# Functions for recurrent object patching
def create_results() -> List[Dict]:
return [{'loss': 1, 'result': 'foo', 'params': {}, 'is_best': True}]
def test_setup_hyperopt_configuration_without_arguments(mocker, default_conf, caplog) -> None:
patched_configuration_load_config_file(mocker, default_conf)
@ -303,52 +294,6 @@ def test_no_log_if_loss_does_not_improve(hyperopt, caplog) -> None:
assert caplog.record_tuples == []
def test_save_results_saves_epochs(mocker, hyperopt, tmpdir, caplog) -> None:
# Test writing to temp dir and reading again
epochs = create_results()
hyperopt.results_file = Path(tmpdir / 'ut_results.fthypt')
caplog.set_level(logging.DEBUG)
for epoch in epochs:
hyperopt._save_result(epoch)
assert log_has(f"1 epoch saved to '{hyperopt.results_file}'.", caplog)
hyperopt._save_result(epochs[0])
assert log_has(f"2 epochs saved to '{hyperopt.results_file}'.", caplog)
hyperopt_epochs = HyperoptTools.load_previous_results(hyperopt.results_file)
assert len(hyperopt_epochs) == 2
def test_load_previous_results(testdatadir, caplog) -> None:
results_file = testdatadir / 'hyperopt_results_SampleStrategy.pickle'
hyperopt_epochs = HyperoptTools.load_previous_results(results_file)
assert len(hyperopt_epochs) == 5
assert log_has_re(r"Reading pickled epochs from .*", caplog)
caplog.clear()
# Modern version
results_file = testdatadir / 'strategy_SampleStrategy.fthypt'
hyperopt_epochs = HyperoptTools.load_previous_results(results_file)
assert len(hyperopt_epochs) == 5
assert log_has_re(r"Reading epochs from .*", caplog)
def test_load_previous_results2(mocker, testdatadir, caplog) -> None:
mocker.patch('freqtrade.optimize.hyperopt_tools.HyperoptTools._read_results_pickle',
return_value=[{'asdf': '222'}])
results_file = testdatadir / 'hyperopt_results_SampleStrategy.pickle'
with pytest.raises(OperationalException, match=r"The file .* incompatible.*"):
HyperoptTools.load_previous_results(results_file)
def test_roi_table_generation(hyperopt) -> None:
params = {
'roi_t1': 5,
@ -362,6 +307,18 @@ def test_roi_table_generation(hyperopt) -> None:
assert hyperopt.custom_hyperopt.generate_roi_table(params) == {0: 6, 15: 3, 25: 1, 30: 0}
def test_params_no_optimize_details(hyperopt) -> None:
hyperopt.config['spaces'] = ['buy']
res = hyperopt._get_no_optimize_details()
assert isinstance(res, dict)
assert "trailing" in res
assert res["trailing"]['trailing_stop'] is False
assert "roi" in res
assert res['roi']['0'] == 0.04
assert "stoploss" in res
assert res['stoploss']['stoploss'] == -0.1
def test_start_calls_optimizer(mocker, hyperopt_conf, capsys) -> None:
dumper = mocker.patch('freqtrade.optimize.hyperopt.dump')
dumper2 = mocker.patch('freqtrade.optimize.hyperopt.Hyperopt._save_result')
@ -467,40 +424,6 @@ def test_hyperopt_format_results(hyperopt):
assert '0:50:00 min' in result
@pytest.mark.parametrize("spaces, expected_results", [
(['buy'],
{'buy': True, 'sell': False, 'roi': False, 'stoploss': False, 'trailing': False}),
(['sell'],
{'buy': False, 'sell': True, 'roi': False, 'stoploss': False, 'trailing': False}),
(['roi'],
{'buy': False, 'sell': False, 'roi': True, 'stoploss': False, 'trailing': False}),
(['stoploss'],
{'buy': False, 'sell': False, 'roi': False, 'stoploss': True, 'trailing': False}),
(['trailing'],
{'buy': False, 'sell': False, 'roi': False, 'stoploss': False, 'trailing': True}),
(['buy', 'sell', 'roi', 'stoploss'],
{'buy': True, 'sell': True, 'roi': True, 'stoploss': True, 'trailing': False}),
(['buy', 'sell', 'roi', 'stoploss', 'trailing'],
{'buy': True, 'sell': True, 'roi': True, 'stoploss': True, 'trailing': True}),
(['buy', 'roi'],
{'buy': True, 'sell': False, 'roi': True, 'stoploss': False, 'trailing': False}),
(['all'],
{'buy': True, 'sell': True, 'roi': True, 'stoploss': True, 'trailing': True}),
(['default'],
{'buy': True, 'sell': True, 'roi': True, 'stoploss': True, 'trailing': False}),
(['default', 'trailing'],
{'buy': True, 'sell': True, 'roi': True, 'stoploss': True, 'trailing': True}),
(['all', 'buy'],
{'buy': True, 'sell': True, 'roi': True, 'stoploss': True, 'trailing': True}),
(['default', 'buy'],
{'buy': True, 'sell': True, 'roi': True, 'stoploss': True, 'trailing': False}),
])
def test_has_space(hyperopt_conf, spaces, expected_results):
for s in ['buy', 'sell', 'roi', 'stoploss', 'trailing']:
hyperopt_conf.update({'spaces': spaces})
assert HyperoptTools.has_space(hyperopt_conf, s) == expected_results[s]
def test_populate_indicators(hyperopt, testdatadir) -> None:
data = load_data(testdatadir, '1m', ['UNITTEST/BTC'], fill_up_missing=True)
dataframes = hyperopt.backtesting.strategy.ohlcvdata_to_dataframe(data)
@ -686,6 +609,8 @@ def test_generate_optimizer(mocker, hyperopt_conf) -> None:
def test_clean_hyperopt(mocker, hyperopt_conf, caplog):
patch_exchange(mocker)
mocker.patch("freqtrade.strategy.hyper.HyperStrategyMixin.load_params_from_file",
MagicMock(return_value={}))
mocker.patch("freqtrade.optimize.hyperopt.Path.is_file", MagicMock(return_value=True))
unlinkmock = mocker.patch("freqtrade.optimize.hyperopt.Path.unlink", MagicMock())
h = Hyperopt(hyperopt_conf)
@ -1068,42 +993,6 @@ def test_simplified_interface_failed(mocker, hyperopt_conf, method, space) -> No
hyperopt.start()
def test_show_epoch_details(capsys):
test_result = {
'params_details': {
'trailing': {
'trailing_stop': True,
'trailing_stop_positive': 0.02,
'trailing_stop_positive_offset': 0.04,
'trailing_only_offset_is_reached': True
},
'roi': {
0: 0.18,
90: 0.14,
225: 0.05,
430: 0},
},
'results_explanation': 'foo result',
'is_initial_point': False,
'total_profit': 0,
'current_epoch': 2, # This starts from 1 (in a human-friendly manner)
'is_best': True
}
HyperoptTools.show_epoch_details(test_result, 5, False, no_header=True)
captured = capsys.readouterr()
assert '# Trailing stop:' in captured.out
# re.match(r"Pairs for .*", captured.out)
assert re.search(r'^\s+trailing_stop = True$', captured.out, re.MULTILINE)
assert re.search(r'^\s+trailing_stop_positive = 0.02$', captured.out, re.MULTILINE)
assert re.search(r'^\s+trailing_stop_positive_offset = 0.04$', captured.out, re.MULTILINE)
assert re.search(r'^\s+trailing_only_offset_is_reached = True$', captured.out, re.MULTILINE)
assert '# ROI table:' in captured.out
assert re.search(r'^\s+minimal_roi = \{$', captured.out, re.MULTILINE)
assert re.search(r'^\s+\"90\"\:\s0.14,\s*$', captured.out, re.MULTILINE)
def test_in_strategy_auto_hyperopt(mocker, hyperopt_conf, tmpdir, fee) -> None:
patch_exchange(mocker)
mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
@ -1143,17 +1032,3 @@ def test_SKDecimal():
assert space.transform([2.0]) == [200]
assert space.transform([1.0]) == [100]
assert space.transform([1.5, 1.6]) == [150, 160]
def test___pprint():
params = {'buy_std': 1.2, 'buy_rsi': 31, 'buy_enable': True, 'buy_what': 'asdf'}
non_params = {'buy_notoptimied': 55}
x = HyperoptTools._pprint(params, non_params)
assert x == """{
"buy_std": 1.2,
"buy_rsi": 31,
"buy_enable": True,
"buy_what": "asdf",
"buy_notoptimied": 55, # value loaded from strategy
}"""

317
tests/optimize/test_hyperopt_tools.py Normal file
View File

@ -0,0 +1,317 @@
import logging
import re
from pathlib import Path
from typing import Dict, List
import numpy as np
import pytest
import rapidjson
from freqtrade.constants import FTHYPT_FILEVERSION
from freqtrade.exceptions import OperationalException
from freqtrade.optimize.hyperopt_tools import HyperoptTools, hyperopt_serializer
from tests.conftest import log_has, log_has_re
# Functions for recurrent object patching
def create_results() -> List[Dict]:
return [{'loss': 1, 'result': 'foo', 'params': {}, 'is_best': True}]
def test_save_results_saves_epochs(hyperopt, tmpdir, caplog) -> None:
# Test writing to temp dir and reading again
epochs = create_results()
hyperopt.results_file = Path(tmpdir / 'ut_results.fthypt')
caplog.set_level(logging.DEBUG)
for epoch in epochs:
hyperopt._save_result(epoch)
assert log_has(f"1 epoch saved to '{hyperopt.results_file}'.", caplog)
hyperopt._save_result(epochs[0])
assert log_has(f"2 epochs saved to '{hyperopt.results_file}'.", caplog)
hyperopt_epochs = HyperoptTools.load_previous_results(hyperopt.results_file)
assert len(hyperopt_epochs) == 2
def test_load_previous_results(testdatadir, caplog) -> None:
results_file = testdatadir / 'hyperopt_results_SampleStrategy.pickle'
hyperopt_epochs = HyperoptTools.load_previous_results(results_file)
assert len(hyperopt_epochs) == 5
assert log_has_re(r"Reading pickled epochs from .*", caplog)
caplog.clear()
# Modern version
results_file = testdatadir / 'strategy_SampleStrategy.fthypt'
hyperopt_epochs = HyperoptTools.load_previous_results(results_file)
assert len(hyperopt_epochs) == 5
assert log_has_re(r"Reading epochs from .*", caplog)
def test_load_previous_results2(mocker, testdatadir, caplog) -> None:
mocker.patch('freqtrade.optimize.hyperopt_tools.HyperoptTools._read_results_pickle',
return_value=[{'asdf': '222'}])
results_file = testdatadir / 'hyperopt_results_SampleStrategy.pickle'
with pytest.raises(OperationalException, match=r"The file .* incompatible.*"):
HyperoptTools.load_previous_results(results_file)
@pytest.mark.parametrize("spaces, expected_results", [
(['buy'],
{'buy': True, 'sell': False, 'roi': False, 'stoploss': False, 'trailing': False}),
(['sell'],
{'buy': False, 'sell': True, 'roi': False, 'stoploss': False, 'trailing': False}),
(['roi'],
{'buy': False, 'sell': False, 'roi': True, 'stoploss': False, 'trailing': False}),
(['stoploss'],
{'buy': False, 'sell': False, 'roi': False, 'stoploss': True, 'trailing': False}),
(['trailing'],
{'buy': False, 'sell': False, 'roi': False, 'stoploss': False, 'trailing': True}),
(['buy', 'sell', 'roi', 'stoploss'],
{'buy': True, 'sell': True, 'roi': True, 'stoploss': True, 'trailing': False}),
(['buy', 'sell', 'roi', 'stoploss', 'trailing'],
{'buy': True, 'sell': True, 'roi': True, 'stoploss': True, 'trailing': True}),
(['buy', 'roi'],
{'buy': True, 'sell': False, 'roi': True, 'stoploss': False, 'trailing': False}),
(['all'],
{'buy': True, 'sell': True, 'roi': True, 'stoploss': True, 'trailing': True}),
(['default'],
{'buy': True, 'sell': True, 'roi': True, 'stoploss': True, 'trailing': False}),
(['default', 'trailing'],
{'buy': True, 'sell': True, 'roi': True, 'stoploss': True, 'trailing': True}),
(['all', 'buy'],
{'buy': True, 'sell': True, 'roi': True, 'stoploss': True, 'trailing': True}),
(['default', 'buy'],
{'buy': True, 'sell': True, 'roi': True, 'stoploss': True, 'trailing': False}),
])
def test_has_space(hyperopt_conf, spaces, expected_results):
for s in ['buy', 'sell', 'roi', 'stoploss', 'trailing']:
hyperopt_conf.update({'spaces': spaces})
assert HyperoptTools.has_space(hyperopt_conf, s) == expected_results[s]
def test_show_epoch_details(capsys):
test_result = {
'params_details': {
'trailing': {
'trailing_stop': True,
'trailing_stop_positive': 0.02,
'trailing_stop_positive_offset': 0.04,
'trailing_only_offset_is_reached': True
},
'roi': {
0: 0.18,
90: 0.14,
225: 0.05,
430: 0},
},
'results_explanation': 'foo result',
'is_initial_point': False,
'total_profit': 0,
'current_epoch': 2, # This starts from 1 (in a human-friendly manner)
'is_best': True
}
HyperoptTools.show_epoch_details(test_result, 5, False, no_header=True)
captured = capsys.readouterr()
assert '# Trailing stop:' in captured.out
# re.match(r"Pairs for .*", captured.out)
assert re.search(r'^\s+trailing_stop = True$', captured.out, re.MULTILINE)
assert re.search(r'^\s+trailing_stop_positive = 0.02$', captured.out, re.MULTILINE)
assert re.search(r'^\s+trailing_stop_positive_offset = 0.04$', captured.out, re.MULTILINE)
assert re.search(r'^\s+trailing_only_offset_is_reached = True$', captured.out, re.MULTILINE)
assert '# ROI table:' in captured.out
assert re.search(r'^\s+minimal_roi = \{$', captured.out, re.MULTILINE)
assert re.search(r'^\s+\"90\"\:\s0.14,\s*$', captured.out, re.MULTILINE)
def test__pprint_dict():
params = {'buy_std': 1.2, 'buy_rsi': 31, 'buy_enable': True, 'buy_what': 'asdf'}
non_params = {'buy_notoptimied': 55}
x = HyperoptTools._pprint_dict(params, non_params)
assert x == """{
"buy_std": 1.2,
"buy_rsi": 31,
"buy_enable": True,
"buy_what": "asdf",
"buy_notoptimied": 55, # value loaded from strategy
}"""
def test_get_strategy_filename(default_conf):
x = HyperoptTools.get_strategy_filename(default_conf, 'DefaultStrategy')
assert isinstance(x, Path)
assert x == Path(__file__).parents[1] / 'strategy/strats/default_strategy.py'
x = HyperoptTools.get_strategy_filename(default_conf, 'NonExistingStrategy')
assert x is None
def test_export_params(tmpdir):
filename = Path(tmpdir) / "DefaultStrategy.json"
assert not filename.is_file()
params = {
"params_details": {
"buy": {
"buy_rsi": 30
},
"sell": {
"sell_rsi": 70
},
"roi": {
"0": 0.528,
"346": 0.08499,
"507": 0.049,
"1595": 0
}
},
"params_not_optimized": {
"stoploss": -0.05,
"trailing": {
"trailing_stop": False,
"trailing_stop_positive": 0.05,
"trailing_stop_positive_offset": 0.1,
"trailing_only_offset_is_reached": True
},
}
}
HyperoptTools.export_params(params, "DefaultStrategy", filename)
assert filename.is_file()
content = rapidjson.load(filename.open('r'))
assert content['strategy_name'] == 'DefaultStrategy'
assert 'params' in content
assert "buy" in content["params"]
assert "sell" in content["params"]
assert "roi" in content["params"]
assert "stoploss" in content["params"]
assert "trailing" in content["params"]
def test_try_export_params(default_conf, tmpdir, caplog, mocker):
default_conf['disableparamexport'] = False
export_mock = mocker.patch("freqtrade.optimize.hyperopt_tools.HyperoptTools.export_params")
filename = Path(tmpdir) / "DefaultStrategy.json"
assert not filename.is_file()
params = {
"params_details": {
"buy": {
"buy_rsi": 30
},
"sell": {
"sell_rsi": 70
},
"roi": {
"0": 0.528,
"346": 0.08499,
"507": 0.049,
"1595": 0
}
},
"params_not_optimized": {
"stoploss": -0.05,
"trailing": {
"trailing_stop": False,
"trailing_stop_positive": 0.05,
"trailing_stop_positive_offset": 0.1,
"trailing_only_offset_is_reached": True
},
},
FTHYPT_FILEVERSION: 2,
}
HyperoptTools.try_export_params(default_conf, "DefaultStrategy22", params)
assert log_has("Strategy not found, not exporting parameter file.", caplog)
assert export_mock.call_count == 0
caplog.clear()
HyperoptTools.try_export_params(default_conf, "DefaultStrategy", params)
assert export_mock.call_count == 1
assert export_mock.call_args_list[0][0][1] == 'DefaultStrategy'
assert export_mock.call_args_list[0][0][2].name == 'default_strategy.json'
def test_params_print(capsys):
params = {
"buy": {
"buy_rsi": 30
},
"sell": {
"sell_rsi": 70
},
}
non_optimized = {
"buy": {
"buy_adx": 44
},
"sell": {
"sell_adx": 65
},
"stoploss": {
"stoploss": -0.05,
},
"roi": {
"0": 0.05,
"20": 0.01,
},
"trailing": {
"trailing_stop": False,
"trailing_stop_positive": 0.05,
"trailing_stop_positive_offset": 0.1,
"trailing_only_offset_is_reached": True
},
}
HyperoptTools._params_pretty_print(params, 'buy', 'No header', non_optimized)
captured = capsys.readouterr()
assert re.search("# No header", captured.out)
assert re.search('"buy_rsi": 30,\n', captured.out)
assert re.search('"buy_adx": 44, # value loaded.*\n', captured.out)
assert not re.search("sell", captured.out)
HyperoptTools._params_pretty_print(params, 'sell', 'Sell Header', non_optimized)
captured = capsys.readouterr()
assert re.search("# Sell Header", captured.out)
assert re.search('"sell_rsi": 70,\n', captured.out)
assert re.search('"sell_adx": 65, # value loaded.*\n', captured.out)
HyperoptTools._params_pretty_print(params, 'roi', 'ROI Table:', non_optimized)
captured = capsys.readouterr()
assert re.search("# ROI Table: # value loaded.*\n", captured.out)
assert re.search('minimal_roi = {\n', captured.out)
assert re.search('"20": 0.01\n', captured.out)
HyperoptTools._params_pretty_print(params, 'trailing', 'Trailing stop:', non_optimized)
captured = capsys.readouterr()
assert re.search("# Trailing stop:", captured.out)
assert re.search('trailing_stop = False # value loaded.*\n', captured.out)
assert re.search('trailing_stop_positive = 0.05 # value loaded.*\n', captured.out)
assert re.search('trailing_stop_positive_offset = 0.1 # value loaded.*\n', captured.out)
assert re.search('trailing_only_offset_is_reached = True # value loaded.*\n', captured.out)
def test_hyperopt_serializer():
assert isinstance(hyperopt_serializer(np.int_(5)), int)
assert isinstance(hyperopt_serializer(np.bool_(True)), bool)
assert isinstance(hyperopt_serializer(np.bool_(False)), bool)

170
tests/plugins/test_pairlist.py
View File

@ -79,7 +79,8 @@ def whitelist_conf_agefilter(default_conf):
},
{
"method": "AgeFilter",
"min_days_listed": 2
"min_days_listed": 2,
"max_days_listed": 100
}
]
return default_conf
@ -302,7 +303,7 @@ def test_VolumePairList_refresh_empty(mocker, markets_empty, whitelist_conf):
# No pair for ETH, all handlers
([{"method": "StaticPairList"},
{"method": "VolumePairList", "number_assets": 5, "sort_key": "quoteVolume"},
{"method": "AgeFilter", "min_days_listed": 2},
{"method": "AgeFilter", "min_days_listed": 2, "max_days_listed": None},
{"method": "PrecisionFilter"},
{"method": "PriceFilter", "low_price_ratio": 0.03},
{"method": "SpreadFilter", "max_spread_ratio": 0.005},
@ -310,12 +311,24 @@ def test_VolumePairList_refresh_empty(mocker, markets_empty, whitelist_conf):
"ETH", []),
# AgeFilter and VolumePairList (require 2 days only, all should pass age test)
([{"method": "VolumePairList", "number_assets": 5, "sort_key": "quoteVolume"},
{"method": "AgeFilter", "min_days_listed": 2}],
{"method": "AgeFilter", "min_days_listed": 2, "max_days_listed": 100}],
"BTC", ['ETH/BTC', 'TKN/BTC', 'LTC/BTC', 'XRP/BTC', 'HOT/BTC']),
# AgeFilter and VolumePairList (require 10 days, all should fail age test)
([{"method": "VolumePairList", "number_assets": 5, "sort_key": "quoteVolume"},
{"method": "AgeFilter", "min_days_listed": 10}],
{"method": "AgeFilter", "min_days_listed": 10, "max_days_listed": None}],
"BTC", []),
# AgeFilter and VolumePairList (all pair listed > 2, all should fail age test)
([{"method": "VolumePairList", "number_assets": 5, "sort_key": "quoteVolume"},
{"method": "AgeFilter", "min_days_listed": 1, "max_days_listed": 2}],
"BTC", []),
# AgeFilter and VolumePairList LTC/BTC has 6 candles - removes all
([{"method": "VolumePairList", "number_assets": 5, "sort_key": "quoteVolume"},
{"method": "AgeFilter", "min_days_listed": 4, "max_days_listed": 5}],
"BTC", []),
# AgeFilter and VolumePairList LTC/BTC has 6 candles - passes
([{"method": "VolumePairList", "number_assets": 5, "sort_key": "quoteVolume"},
{"method": "AgeFilter", "min_days_listed": 4, "max_days_listed": 10}],
"BTC", ["LTC/BTC"]),
# Precisionfilter and quote volume
([{"method": "VolumePairList", "number_assets": 5, "sort_key": "quoteVolume"},
{"method": "PrecisionFilter"}],
@ -417,7 +430,19 @@ def test_VolumePairList_refresh_empty(mocker, markets_empty, whitelist_conf):
([{"method": "StaticPairList"},
{"method": "VolatilityFilter", "lookback_days": 3,
"min_volatility": 0.002, "max_volatility": 0.004, "refresh_period": 1440}],
"BTC", ['ETH/BTC', 'TKN/BTC'])
"BTC", ['ETH/BTC', 'TKN/BTC']),
# VolumePairList with no offset = unchanged pairlist
([{"method": "VolumePairList", "number_assets": 20, "sort_key": "quoteVolume"},
{"method": "OffsetFilter", "offset": 0}],
"USDT", ['ETH/USDT', 'NANO/USDT', 'ADAHALF/USDT', 'ADADOUBLE/USDT']),
# VolumePairList with offset = 2
([{"method": "VolumePairList", "number_assets": 20, "sort_key": "quoteVolume"},
{"method": "OffsetFilter", "offset": 2}],
"USDT", ['ADAHALF/USDT', 'ADADOUBLE/USDT']),
# VolumePairList with higher offset, than total pairlist
([{"method": "VolumePairList", "number_assets": 20, "sort_key": "quoteVolume"},
{"method": "OffsetFilter", "offset": 100}],
"USDT", [])
])
def test_VolumePairList_whitelist_gen(mocker, whitelist_conf, shitcoinmarkets, tickers,
ohlcv_history, pairlists, base_currency,
@ -431,7 +456,7 @@ def test_VolumePairList_whitelist_gen(mocker, whitelist_conf, shitcoinmarkets, t
ohlcv_data = {
('ETH/BTC', '1d'): ohlcv_history,
('TKN/BTC', '1d'): ohlcv_history,
('LTC/BTC', '1d'): ohlcv_history,
('LTC/BTC', '1d'): ohlcv_history.append(ohlcv_history),
('XRP/BTC', '1d'): ohlcv_history,
('HOT/BTC', '1d'): ohlcv_history_high_vola,
}
@ -480,9 +505,13 @@ def test_VolumePairList_whitelist_gen(mocker, whitelist_conf, shitcoinmarkets, t
for pairlist in pairlists:
if pairlist['method'] == 'AgeFilter' and pairlist['min_days_listed'] and \
len(ohlcv_history) <= pairlist['min_days_listed']:
len(ohlcv_history) < pairlist['min_days_listed']:
assert log_has_re(r'^Removed .* from whitelist, because age .* is less than '
r'.* day.*', caplog)
if pairlist['method'] == 'AgeFilter' and pairlist['max_days_listed'] and \
len(ohlcv_history) > pairlist['max_days_listed']:
assert log_has_re(r'^Removed .* from whitelist, because age .* is less than '
r'.* day.* or more than .* day', caplog)
if pairlist['method'] == 'PrecisionFilter' and whitelist_result:
assert log_has_re(r'^Removed .* from whitelist, because stop price .* '
r'would be <= stop limit.*', caplog)
@ -507,6 +536,105 @@ def test_VolumePairList_whitelist_gen(mocker, whitelist_conf, shitcoinmarkets, t
assert log_has_re(r'^Removed .* from whitelist, because volatility.*$', caplog)
@pytest.mark.parametrize("pairlists,base_currency,volumefilter_result", [
# default refresh of 1800 to small for daily candle lookback
([{"method": "VolumePairList", "number_assets": 5, "sort_key": "quoteVolume",
"lookback_days": 1}],
"BTC", "default_refresh_too_short"), # OperationalException expected
# ambigous configuration with lookback days and period
([{"method": "VolumePairList", "number_assets": 5, "sort_key": "quoteVolume",
"lookback_days": 1, "lookback_period": 1}],
"BTC", "lookback_days_and_period"), # OperationalException expected
# negative lookback period
([{"method": "VolumePairList", "number_assets": 5, "sort_key": "quoteVolume",
"lookback_timeframe": "1d", "lookback_period": -1}],
"BTC", "lookback_period_negative"), # OperationalException expected
# lookback range exceedes exchange limit
([{"method": "VolumePairList", "number_assets": 5, "sort_key": "quoteVolume",
"lookback_timeframe": "1m", "lookback_period": 2000, "refresh_period": 3600}],
"BTC", 'lookback_exceeds_exchange_request_size'), # OperationalException expected
# expecing pairs as given
([{"method": "VolumePairList", "number_assets": 5, "sort_key": "quoteVolume",
"lookback_timeframe": "1d", "lookback_period": 1, "refresh_period": 86400}],
"BTC", ['HOT/BTC', 'LTC/BTC', 'ETH/BTC', 'TKN/BTC', 'XRP/BTC']),
# expecting pairs from default tickers, because 1h candles are not available
([{"method": "VolumePairList", "number_assets": 5, "sort_key": "quoteVolume",
"lookback_timeframe": "1h", "lookback_period": 2, "refresh_period": 3600}],
"BTC", ['ETH/BTC', 'TKN/BTC', 'LTC/BTC', 'HOT/BTC', 'FUEL/BTC']),
])
def test_VolumePairList_range(mocker, whitelist_conf, shitcoinmarkets, tickers, ohlcv_history,
pairlists, base_currency, volumefilter_result, caplog) -> None:
whitelist_conf['pairlists'] = pairlists
whitelist_conf['stake_currency'] = base_currency
ohlcv_history_high_vola = ohlcv_history.copy()
ohlcv_history_high_vola.loc[ohlcv_history_high_vola.index == 1, 'close'] = 0.00090
# create candles for medium overall volume with last candle high volume
ohlcv_history_medium_volume = ohlcv_history.copy()
ohlcv_history_medium_volume.loc[ohlcv_history_medium_volume.index == 2, 'volume'] = 5
# create candles for high volume with all candles high volume
ohlcv_history_high_volume = ohlcv_history.copy()
ohlcv_history_high_volume.loc[:, 'volume'] = 10
ohlcv_data = {
('ETH/BTC', '1d'): ohlcv_history,
('TKN/BTC', '1d'): ohlcv_history,
('LTC/BTC', '1d'): ohlcv_history_medium_volume,
('XRP/BTC', '1d'): ohlcv_history_high_vola,
('HOT/BTC', '1d'): ohlcv_history_high_volume,
}
mocker.patch('freqtrade.exchange.Exchange.exchange_has', MagicMock(return_value=True))
if volumefilter_result == 'default_refresh_too_short':
with pytest.raises(OperationalException,
match=r'Refresh period of [0-9]+ seconds is smaller than one timeframe '
r'of [0-9]+.*\. Please adjust refresh_period to at least [0-9]+ '
r'and restart the bot\.'):
freqtrade = get_patched_freqtradebot(mocker, whitelist_conf)
return
elif volumefilter_result == 'lookback_days_and_period':
with pytest.raises(OperationalException,
match=r'Ambigous configuration: lookback_days and lookback_period both '
r'set in pairlist config\..*'):
freqtrade = get_patched_freqtradebot(mocker, whitelist_conf)
elif volumefilter_result == 'lookback_period_negative':
with pytest.raises(OperationalException,
match=r'VolumeFilter requires lookback_period to be >= 0'):
freqtrade = get_patched_freqtradebot(mocker, whitelist_conf)
elif volumefilter_result == 'lookback_exceeds_exchange_request_size':
with pytest.raises(OperationalException,
match=r'VolumeFilter requires lookback_period to not exceed '
r'exchange max request size \([0-9]+\)'):
freqtrade = get_patched_freqtradebot(mocker, whitelist_conf)
else:
freqtrade = get_patched_freqtradebot(mocker, whitelist_conf)
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
get_tickers=tickers,
markets=PropertyMock(return_value=shitcoinmarkets)
)
# remove ohlcv when looback_timeframe != 1d
# to enforce fallback to ticker data
if 'lookback_timeframe' in pairlists[0]:
if pairlists[0]['lookback_timeframe'] != '1d':
ohlcv_data = []
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
refresh_latest_ohlcv=MagicMock(return_value=ohlcv_data),
)
freqtrade.pairlists.refresh_pairlist()
whitelist = freqtrade.pairlists.whitelist
assert isinstance(whitelist, list)
assert whitelist == volumefilter_result
def test_PrecisionFilter_error(mocker, whitelist_conf) -> None:
whitelist_conf['pairlists'] = [{"method": "StaticPairList"}, {"method": "PrecisionFilter"}]
del whitelist_conf['stoploss']
@ -650,6 +778,22 @@ def test_agefilter_min_days_listed_too_small(mocker, default_conf, markets, tick
get_patched_freqtradebot(mocker, default_conf)
def test_agefilter_max_days_lower_than_min_days(mocker, default_conf, markets, tickers):
default_conf['pairlists'] = [{'method': 'VolumePairList', 'number_assets': 10},
{'method': 'AgeFilter', 'min_days_listed': 3,
"max_days_listed": 2}]
mocker.patch.multiple('freqtrade.exchange.Exchange',
markets=PropertyMock(return_value=markets),
exchange_has=MagicMock(return_value=True),
get_tickers=tickers
)
with pytest.raises(OperationalException,
match=r'AgeFilter max_days_listed <= min_days_listed not permitted'):
get_patched_freqtradebot(mocker, default_conf)
def test_agefilter_min_days_listed_too_large(mocker, default_conf, markets, tickers):
default_conf['pairlists'] = [{'method': 'VolumePairList', 'number_assets': 10},
{'method': 'AgeFilter', 'min_days_listed': 99999}]
@ -695,6 +839,18 @@ def test_agefilter_caching(mocker, markets, whitelist_conf_agefilter, tickers, o
assert freqtrade.exchange.refresh_latest_ohlcv.call_count == previous_call_count + 1
def test_OffsetFilter_error(mocker, whitelist_conf) -> None:
whitelist_conf['pairlists'] = (
[{"method": "StaticPairList"}, {"method": "OffsetFilter", "offset": -1}]
)
mocker.patch('freqtrade.exchange.Exchange.exchange_has', MagicMock(return_value=True))
with pytest.raises(OperationalException,
match=r'OffsetFilter requires offset to be >= 0'):
PairListManager(MagicMock, whitelist_conf)
def test_rangestabilityfilter_checks(mocker, default_conf, markets, tickers):
default_conf['pairlists'] = [{'method': 'VolumePairList', 'number_assets': 10},
{'method': 'RangeStabilityFilter', 'lookback_days': 99999}]

8
tests/rpc/test_rpc.py
View File

@ -110,7 +110,7 @@ def test_rpc_trade_status(default_conf, ticker, fee, mocker) -> None:
'exchange': 'binance',
}
mocker.patch('freqtrade.exchange.Exchange.get_sell_rate',
mocker.patch('freqtrade.exchange.Exchange.get_rate',
MagicMock(side_effect=ExchangeError("Pair 'ETH/BTC' not available")))
results = rpc._rpc_trade_status()
assert isnan(results[0]['current_profit'])
@ -219,7 +219,7 @@ def test_rpc_status_table(default_conf, ticker, fee, mocker) -> None:
assert '-0.41% (-0.06)' == result[0][3]
assert '-0.06' == f'{fiat_profit_sum:.2f}'
mocker.patch('freqtrade.exchange.Exchange.get_sell_rate',
mocker.patch('freqtrade.exchange.Exchange.get_rate',
MagicMock(side_effect=ExchangeError("Pair 'ETH/BTC' not available")))
result, headers, fiat_profit_sum = rpc._rpc_status_table(default_conf['stake_currency'], 'USD')
assert 'instantly' == result[0][2]
@ -429,7 +429,7 @@ def test_rpc_trade_statistics(default_conf, ticker, ticker_sell_up, fee,
assert prec_satoshi(stats['best_rate'], 6.2)
# Test non-available pair
mocker.patch('freqtrade.exchange.Exchange.get_sell_rate',
mocker.patch('freqtrade.exchange.Exchange.get_rate',
MagicMock(side_effect=ExchangeError("Pair 'ETH/BTC' not available")))
stats = rpc._rpc_trade_statistics(stake_currency, fiat_display_currency)
assert stats['trade_count'] == 2
@ -888,7 +888,7 @@ def test_rpcforcebuy(mocker, default_conf, ticker, fee, limit_buy_order_open) ->
# Test not buying
freqtradebot = get_patched_freqtradebot(mocker, default_conf)
freqtradebot.config['stake_amount'] = 0.0000001
freqtradebot.config['stake_amount'] = 0
patch_get_signal(freqtradebot, (True, False, ''))
rpc = RPC(freqtradebot)
pair = 'TKN/BTC'

168
tests/rpc/test_rpc_apiserver.py
View File

@ -2,6 +2,7 @@
Unit test file for rpc/api_server.py
"""
import json
from datetime import datetime, timedelta, timezone
from pathlib import Path
from unittest.mock import ANY, MagicMock, PropertyMock
@ -16,7 +17,7 @@ from requests.auth import _basic_auth_str
from freqtrade.__init__ import __version__
from freqtrade.enums import RunMode, State
from freqtrade.exceptions import ExchangeError
from freqtrade.exceptions import DependencyException, ExchangeError, OperationalException
from freqtrade.loggers import setup_logging, setup_logging_pre
from freqtrade.persistence import PairLocks, Trade
from freqtrade.rpc import RPC
@ -48,9 +49,13 @@ def botclient(default_conf, mocker):
freqtrade = get_patched_freqtradebot(mocker, default_conf)
rpc = RPC(freqtrade)
mocker.patch('freqtrade.rpc.api_server.ApiServer.start_api', MagicMock())
apiserver = ApiServer(rpc, default_conf)
yield freqtrade, TestClient(apiserver.app)
# Cleanup ... ?
try:
apiserver = ApiServer(default_conf)
apiserver.add_rpc_handler(rpc)
yield freqtrade, TestClient(apiserver.app)
# Cleanup ... ?
finally:
ApiServer.shutdown()
def client_post(client, url, data={}):
@ -105,6 +110,15 @@ def test_api_ui_fallback(botclient):
assert rc.status_code == 200
def test_api_ui_version(botclient, mocker):
ftbot, client = botclient
mocker.patch('freqtrade.commands.deploy_commands.read_ui_version', return_value='0.1.2')
rc = client_get(client, "/ui_version")
assert rc.status_code == 200
assert rc.json()['version'] == '0.1.2'
def test_api_auth():
with pytest.raises(ValueError):
create_token({'identity': {'u': 'Freqtrade'}}, 'secret1234', token_type="NotATokenType")
@ -226,8 +240,13 @@ def test_api__init__(default_conf, mocker):
}})
mocker.patch('freqtrade.rpc.telegram.Updater', MagicMock())
mocker.patch('freqtrade.rpc.api_server.webserver.ApiServer.start_api', MagicMock())
apiserver = ApiServer(RPC(get_patched_freqtradebot(mocker, default_conf)), default_conf)
apiserver = ApiServer(default_conf)
apiserver.add_rpc_handler(RPC(get_patched_freqtradebot(mocker, default_conf)))
assert apiserver._config == default_conf
with pytest.raises(OperationalException, match="RPC Handler already attached."):
apiserver.add_rpc_handler(RPC(get_patched_freqtradebot(mocker, default_conf)))
ApiServer.shutdown()
def test_api_UvicornServer(mocker):
@ -289,15 +308,21 @@ def test_api_run(default_conf, mocker, caplog):
}})
mocker.patch('freqtrade.rpc.telegram.Updater', MagicMock())
server_mock = MagicMock()
server_inst_mock = MagicMock()
server_inst_mock.run_in_thread = MagicMock()
server_inst_mock.run = MagicMock()
server_mock = MagicMock(return_value=server_inst_mock)
mocker.patch('freqtrade.rpc.api_server.webserver.UvicornServer', server_mock)
apiserver = ApiServer(RPC(get_patched_freqtradebot(mocker, default_conf)), default_conf)
apiserver = ApiServer(default_conf)
apiserver.add_rpc_handler(RPC(get_patched_freqtradebot(mocker, default_conf)))
assert server_mock.call_count == 1
assert apiserver._config == default_conf
apiserver.start_api()
assert server_mock.call_count == 2
assert server_inst_mock.run_in_thread.call_count == 2
assert server_inst_mock.run.call_count == 0
assert server_mock.call_args_list[0][0][0].host == "127.0.0.1"
assert server_mock.call_args_list[0][0][0].port == 8080
assert isinstance(server_mock.call_args_list[0][0][0].app, FastAPI)
@ -316,6 +341,8 @@ def test_api_run(default_conf, mocker, caplog):
apiserver.start_api()
assert server_mock.call_count == 1
assert server_inst_mock.run_in_thread.call_count == 1
assert server_inst_mock.run.call_count == 0
assert server_mock.call_args_list[0][0][0].host == "0.0.0.0"
assert server_mock.call_args_list[0][0][0].port == 8089
assert isinstance(server_mock.call_args_list[0][0][0].app, FastAPI)
@ -329,12 +356,24 @@ def test_api_run(default_conf, mocker, caplog):
"Please make sure that this is intentional!", caplog)
assert log_has_re("SECURITY WARNING - `jwt_secret_key` seems to be default.*", caplog)
server_mock.reset_mock()
apiserver._standalone = True
apiserver.start_api()
assert server_inst_mock.run_in_thread.call_count == 0
assert server_inst_mock.run.call_count == 1
apiserver1 = ApiServer(default_conf)
assert id(apiserver1) == id(apiserver)
apiserver._standalone = False
# Test crashing API server
caplog.clear()
mocker.patch('freqtrade.rpc.api_server.webserver.UvicornServer',
MagicMock(side_effect=Exception))
apiserver.start_api()
assert log_has("Api server failed to start.", caplog)
ApiServer.shutdown()
def test_api_cleanup(default_conf, mocker, caplog):
@ -350,11 +389,13 @@ def test_api_cleanup(default_conf, mocker, caplog):
server_mock.cleanup = MagicMock()
mocker.patch('freqtrade.rpc.api_server.webserver.UvicornServer', server_mock)
apiserver = ApiServer(RPC(get_patched_freqtradebot(mocker, default_conf)), default_conf)
apiserver = ApiServer(default_conf)
apiserver.add_rpc_handler(RPC(get_patched_freqtradebot(mocker, default_conf)))
apiserver.cleanup()
assert apiserver._server.cleanup.call_count == 1
assert log_has("Stopping API Server", caplog)
ApiServer.shutdown()
def test_api_reloadconf(botclient):
@ -668,12 +709,16 @@ def test_api_profit(botclient, mocker, ticker, fee, markets):
'profit_all_ratio_mean': -0.6641100666666667,
'profit_all_percent_sum': -398.47,
'profit_all_ratio_sum': -3.9846604,
'profit_all_percent': -4.41,
'profit_all_ratio': -0.044063014216106644,
'profit_closed_coin': 0.00073913,
'profit_closed_fiat': 9.124559849999999,
'profit_closed_ratio_mean': 0.0075,
'profit_closed_percent_mean': 0.75,
'profit_closed_ratio_sum': 0.015,
'profit_closed_percent_sum': 1.5,
'profit_closed_ratio': 7.391275897987988e-07,
'profit_closed_percent': 0.0,
'trade_count': 6,
'closed_trade_count': 2,
'winning_trades': 2,
@ -834,7 +879,7 @@ def test_api_status(botclient, mocker, ticker, fee, markets):
'exchange': 'binance',
}
mocker.patch('freqtrade.exchange.Exchange.get_sell_rate',
mocker.patch('freqtrade.exchange.Exchange.get_rate',
MagicMock(side_effect=ExchangeError("Pair 'ETH/BTC' not available")))
rc = client_get(client, f"{BASE_URI}/status")
@ -1208,3 +1253,108 @@ def test_list_available_pairs(botclient):
assert rc.json()['length'] == 1
assert rc.json()['pairs'] == ['XRP/ETH']
assert len(rc.json()['pair_interval']) == 1
def test_api_backtesting(botclient, mocker, fee, caplog):
ftbot, client = botclient
mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
# Backtesting not started yet
rc = client_get(client, f"{BASE_URI}/backtest")
assert_response(rc)
result = rc.json()
assert result['status'] == 'not_started'
assert not result['running']
assert result['status_msg'] == 'Backtest not yet executed'
assert result['progress'] == 0
# Reset backtesting
rc = client_delete(client, f"{BASE_URI}/backtest")
assert_response(rc)
result = rc.json()
assert result['status'] == 'reset'
assert not result['running']
assert result['status_msg'] == 'Backtest reset'
# start backtesting
data = {
"strategy": "DefaultStrategy",
"timeframe": "5m",
"timerange": "20180110-20180111",
"max_open_trades": 3,
"stake_amount": 100,
"dry_run_wallet": 1000,
"enable_protections": False
}
rc = client_post(client, f"{BASE_URI}/backtest", data=json.dumps(data))
assert_response(rc)
result = rc.json()
assert result['status'] == 'running'
assert result['progress'] == 0
assert result['running']
assert result['status_msg'] == 'Backtest started'
rc = client_get(client, f"{BASE_URI}/backtest")
assert_response(rc)
result = rc.json()
assert result['status'] == 'ended'
assert not result['running']
assert result['status_msg'] == 'Backtest ended'
assert result['progress'] == 1
assert result['backtest_result']
rc = client_get(client, f"{BASE_URI}/backtest/abort")
assert_response(rc)
result = rc.json()
assert result['status'] == 'not_running'
assert not result['running']
assert result['status_msg'] == 'Backtest ended'
# Simulate running backtest
ApiServer._bgtask_running = True
rc = client_get(client, f"{BASE_URI}/backtest/abort")
assert_response(rc)
result = rc.json()
assert result['status'] == 'stopping'
assert not result['running']
assert result['status_msg'] == 'Backtest ended'
# Get running backtest...
rc = client_get(client, f"{BASE_URI}/backtest")
assert_response(rc)
result = rc.json()
assert result['status'] == 'running'
assert result['running']
assert result['step'] == "backtest"
assert result['status_msg'] == "Backtest running"
# Try delete with task still running
rc = client_delete(client, f"{BASE_URI}/backtest")
assert_response(rc)
result = rc.json()
assert result['status'] == 'running'
# Post to backtest that's still running
rc = client_post(client, f"{BASE_URI}/backtest", data=json.dumps(data))
assert_response(rc, 502)
result = rc.json()
assert 'Bot Background task already running' in result['error']
ApiServer._bgtask_running = False
mocker.patch('freqtrade.optimize.backtesting.Backtesting.backtest_one_strategy',
side_effect=DependencyException())
rc = client_post(client, f"{BASE_URI}/backtest", data=json.dumps(data))
assert log_has("Backtesting caused an error: ", caplog)
# Delete backtesting to avoid leakage since the backtest-object may stick around.
rc = client_delete(client, f"{BASE_URI}/backtest")
assert_response(rc)
result = rc.json()
assert result['status'] == 'reset'
assert not result['running']
assert result['status_msg'] == 'Backtest reset'

2
tests/rpc/test_rpc_manager.py
View File

@ -5,6 +5,7 @@ from unittest.mock import MagicMock
from freqtrade.enums import RPCMessageType
from freqtrade.rpc import RPCManager
from freqtrade.rpc.api_server.webserver import ApiServer
from tests.conftest import get_patched_freqtradebot, log_has
@ -190,3 +191,4 @@ def test_init_apiserver_enabled(mocker, default_conf, caplog) -> None:
assert len(rpc_manager.registered_modules) == 1
assert 'apiserver' in [mod.name for mod in rpc_manager.registered_modules]
assert run_mock.call_count == 1
ApiServer.shutdown()

16
tests/rpc/test_rpc_telegram.py
View File

@ -452,7 +452,8 @@ def test_profit_handle(default_conf, update, ticker, ticker_sell_up, fee,
assert msg_mock.call_count == 1
assert 'No closed trade' in msg_mock.call_args_list[-1][0][0]
assert '*ROI:* All trades' in msg_mock.call_args_list[-1][0][0]
assert ('∙ `-0.00000500 BTC (-0.50%) (-0.5 \N{GREEK CAPITAL LETTER SIGMA}%)`'
mocker.patch('freqtrade.wallets.Wallets.get_starting_balance', return_value=0.01)
assert ('∙ `-0.00000500 BTC (-0.50%) (-0.0 \N{GREEK CAPITAL LETTER SIGMA}%)`'
in msg_mock.call_args_list[-1][0][0])
msg_mock.reset_mock()
@ -466,11 +467,11 @@ def test_profit_handle(default_conf, update, ticker, ticker_sell_up, fee,
telegram._profit(update=update, context=MagicMock())
assert msg_mock.call_count == 1
assert '*ROI:* Closed trades' in msg_mock.call_args_list[-1][0][0]
assert ('∙ `0.00006217 BTC (6.20%) (6.2 \N{GREEK CAPITAL LETTER SIGMA}%)`'
assert ('∙ `0.00006217 BTC (6.20%) (0.62 \N{GREEK CAPITAL LETTER SIGMA}%)`'
in msg_mock.call_args_list[-1][0][0])
assert '∙ `0.933 USD`' in msg_mock.call_args_list[-1][0][0]
assert '*ROI:* All trades' in msg_mock.call_args_list[-1][0][0]
assert ('∙ `0.00006217 BTC (6.20%) (6.2 \N{GREEK CAPITAL LETTER SIGMA}%)`'
assert ('∙ `0.00006217 BTC (6.20%) (0.62 \N{GREEK CAPITAL LETTER SIGMA}%)`'
in msg_mock.call_args_list[-1][0][0])
assert '∙ `0.933 USD`' in msg_mock.call_args_list[-1][0][0]
@ -519,12 +520,15 @@ def test_telegram_balance_handle(default_conf, update, mocker, rpc_balance, tick
assert msg_mock.call_count == 1
assert '*BTC:*' in result
assert '*ETH:*' not in result
assert '*USDT:*' in result
assert '*EUR:*' in result
assert '*USDT:*' not in result
assert '*EUR:*' not in result
assert '*LTC:*' in result
assert '*XRP:*' not in result
assert 'Balance:' in result
assert 'Est. BTC:' in result
assert 'BTC: 12.00000000' in result
assert '*XRP:* not showing <0.0001 BTC amount' in result
assert "*3 Other Currencies (< 0.0001 BTC):*" in result
assert 'BTC: 0.00000309' in result
def test_balance_handle_empty_response(default_conf, update, mocker) -> None:

48
tests/strategy/test_interface.py
View File

@ -1,6 +1,7 @@
# pragma pylint: disable=missing-docstring, C0103
import logging
from datetime import datetime, timedelta, timezone
from pathlib import Path
from unittest.mock import MagicMock
import arrow
@ -712,3 +713,50 @@ def test_auto_hyperopt_interface(default_conf):
with pytest.raises(OperationalException, match=r"Inconclusive parameter.*"):
[x for x in strategy.detect_parameters('sell')]
def test_auto_hyperopt_interface_loadparams(default_conf, mocker, caplog):
default_conf.update({'strategy': 'HyperoptableStrategy'})
del default_conf['stoploss']
del default_conf['minimal_roi']
mocker.patch.object(Path, 'is_file', MagicMock(return_value=True))
mocker.patch.object(Path, 'open')
expected_result = {
"strategy_name": "HyperoptableStrategy",
"params": {
"stoploss": {
"stoploss": -0.05,
},
"roi": {
"0": 0.2,
"1200": 0.01
}
}
}
mocker.patch('freqtrade.strategy.hyper.json_load', return_value=expected_result)
PairLocks.timeframe = default_conf['timeframe']
strategy = StrategyResolver.load_strategy(default_conf)
assert strategy.stoploss == -0.05
assert strategy.minimal_roi == {0: 0.2, 1200: 0.01}
expected_result = {
"strategy_name": "HyperoptableStrategy_No",
"params": {
"stoploss": {
"stoploss": -0.05,
},
"roi": {
"0": 0.2,
"1200": 0.01
}
}
}
mocker.patch('freqtrade.strategy.hyper.json_load', return_value=expected_result)
with pytest.raises(OperationalException, match="Invalid parameter file provided."):
StrategyResolver.load_strategy(default_conf)
mocker.patch('freqtrade.strategy.hyper.json_load', MagicMock(side_effect=ValueError()))
StrategyResolver.load_strategy(default_conf)
assert log_has("Invalid parameter file format.", caplog)

2
tests/test_arguments.py
View File

@ -172,7 +172,7 @@ def test_download_data_options() -> None:
def test_plot_dataframe_options() -> None:
args = [
'plot-dataframe',
'-c', 'config_bittrex.json.example',
'-c', 'config_examples/config_bittrex.example.json',
'--indicators1', 'sma10', 'sma100',
'--indicators2', 'macd', 'fastd', 'fastk',
'--plot-limit', '30',

2
tests/test_configuration.py
View File

@ -28,7 +28,7 @@ from tests.conftest import log_has, log_has_re, patched_configuration_load_confi
@pytest.fixture(scope="function")
def all_conf():
config_file = Path(__file__).parents[1] / "config_full.json.example"
config_file = Path(__file__).parents[1] / "config_examples/config_full.example.json"
conf = load_config_file(str(config_file))
return conf

61
tests/test_freqtradebot.py
View File

@ -161,7 +161,7 @@ def test_get_trade_stake_amount(default_conf, ticker, mocker) -> None:
(True, 0.0022, 3, 0.5, [0.001, 0.001, 0.0]),
(True, 0.0027, 3, 0.5, [0.001, 0.001, 0.000673]),
(True, 0.0022, 3, 1, [0.001, 0.001, 0.0]),
])
])
def test_check_available_stake_amount(default_conf, ticker, mocker, fee, limit_buy_order_open,
amend_last, wallet, max_open, lsamr, expected) -> None:
patch_RPCManager(mocker)
@ -397,7 +397,7 @@ def test_create_trade_minimal_amount(default_conf, ticker, limit_buy_order_open,
def test_create_trade_too_small_stake_amount(default_conf, ticker, limit_buy_order_open,
fee, mocker) -> None:
fee, mocker, caplog) -> None:
patch_RPCManager(mocker)
patch_exchange(mocker)
buy_mock = MagicMock(return_value=limit_buy_order_open)
@ -413,6 +413,27 @@ def test_create_trade_too_small_stake_amount(default_conf, ticker, limit_buy_ord
patch_get_signal(freqtrade)
assert freqtrade.create_trade('ETH/BTC')
assert log_has_re(r"Stake amount for pair .* is too small.*", caplog)
def test_create_trade_zero_stake_amount(default_conf, ticker, limit_buy_order_open,
fee, mocker) -> None:
patch_RPCManager(mocker)
patch_exchange(mocker)
buy_mock = MagicMock(return_value=limit_buy_order_open)
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
fetch_ticker=ticker,
buy=buy_mock,
get_fee=fee,
)
freqtrade = FreqtradeBot(default_conf)
freqtrade.config['stake_amount'] = 0
patch_get_signal(freqtrade)
assert not freqtrade.create_trade('ETH/BTC')
@ -763,7 +784,7 @@ def test_execute_buy(mocker, default_conf, fee, limit_buy_order, limit_buy_order
buy_mm = MagicMock(return_value=limit_buy_order_open)
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
get_buy_rate=buy_rate_mock,
get_rate=buy_rate_mock,
fetch_ticker=MagicMock(return_value={
'bid': 0.00001172,
'ask': 0.00001173,
@ -803,7 +824,7 @@ def test_execute_buy(mocker, default_conf, fee, limit_buy_order, limit_buy_order
limit_buy_order_open['id'] = '33'
fix_price = 0.06
assert freqtrade.execute_buy(pair, stake_amount, fix_price)
# Make sure get_buy_rate wasn't called again
# Make sure get_rate wasn't called again
assert buy_rate_mock.call_count == 0
assert buy_mm.call_count == 2
@ -842,6 +863,24 @@ def test_execute_buy(mocker, default_conf, fee, limit_buy_order, limit_buy_order
assert trade.open_rate == 0.5
assert trade.stake_amount == 40.495905365
# Test with custom stake
limit_buy_order['status'] = 'open'
limit_buy_order['id'] = '556'
freqtrade.strategy.custom_stake_amount = lambda **kwargs: 150.0
assert freqtrade.execute_buy(pair, stake_amount)
trade = Trade.query.all()[4]
assert trade
assert trade.stake_amount == 150
# Exception case
limit_buy_order['id'] = '557'
freqtrade.strategy.custom_stake_amount = lambda **kwargs: 20 / 0
assert freqtrade.execute_buy(pair, stake_amount)
trade = Trade.query.all()[5]
assert trade
assert trade.stake_amount == 2.0
# In case of the order is rejected and not filled at all
limit_buy_order['status'] = 'rejected'
limit_buy_order['amount'] = 90.99181073
@ -854,7 +893,7 @@ def test_execute_buy(mocker, default_conf, fee, limit_buy_order, limit_buy_order
assert not freqtrade.execute_buy(pair, stake_amount)
# Fail to get price...
mocker.patch('freqtrade.exchange.Exchange.get_buy_rate', MagicMock(return_value=0.0))
mocker.patch('freqtrade.exchange.Exchange.get_rate', MagicMock(return_value=0.0))
with pytest.raises(PricingError, match="Could not determine buy price."):
freqtrade.execute_buy(pair, stake_amount)
@ -870,7 +909,7 @@ def test_execute_buy_confirm_error(mocker, default_conf, fee, limit_buy_order) -
'last': 0.00001172
}),
buy=MagicMock(return_value=limit_buy_order),
get_buy_rate=MagicMock(return_value=0.11),
get_rate=MagicMock(return_value=0.11),
get_min_pair_stake_amount=MagicMock(return_value=1),
get_fee=fee,
)
@ -2474,7 +2513,7 @@ def test_handle_cancel_sell_limit(mocker, default_conf, fee) -> None:
'freqtrade.exchange.Exchange',
cancel_order=cancel_order_mock,
)
mocker.patch('freqtrade.exchange.Exchange.get_sell_rate', return_value=0.245441)
mocker.patch('freqtrade.exchange.Exchange.get_rate', return_value=0.245441)
freqtrade = FreqtradeBot(default_conf)
@ -3917,7 +3956,7 @@ def test_order_book_depth_of_market_high_delta(default_conf, ticker, limit_buy_o
def test_order_book_bid_strategy1(mocker, default_conf, order_book_l2) -> None:
"""
test if function get_buy_rate will return the order book price
test if function get_rate will return the order book price
instead of the ask rate
"""
patch_exchange(mocker)
@ -3935,7 +3974,7 @@ def test_order_book_bid_strategy1(mocker, default_conf, order_book_l2) -> None:
default_conf['telegram']['enabled'] = False
freqtrade = FreqtradeBot(default_conf)
assert freqtrade.exchange.get_buy_rate('ETH/BTC', True) == 0.043935
assert freqtrade.exchange.get_rate('ETH/BTC', refresh=True, side="buy") == 0.043935
assert ticker_mock.call_count == 0
@ -3957,8 +3996,8 @@ def test_order_book_bid_strategy_exception(mocker, default_conf, caplog) -> None
freqtrade = FreqtradeBot(default_conf)
# orderbook shall be used even if tickers would be lower.
with pytest.raises(PricingError):
freqtrade.exchange.get_buy_rate('ETH/BTC', refresh=True)
assert log_has_re(r'Buy Price from orderbook could not be determined.', caplog)
freqtrade.exchange.get_rate('ETH/BTC', refresh=True, side="buy")
assert log_has_re(r'Buy Price at location 1 from orderbook could not be determined.', caplog)
def test_check_depth_of_market_buy(default_conf, mocker, order_book_l2) -> None:

28
tests/test_main.py
View File

@ -67,12 +67,12 @@ def test_main_fatal_exception(mocker, default_conf, caplog) -> None:
mocker.patch('freqtrade.freqtradebot.RPCManager', MagicMock())
mocker.patch('freqtrade.freqtradebot.init_db', MagicMock())
args = ['trade', '-c', 'config_bittrex.json.example']
args = ['trade', '-c', 'config_examples/config_bittrex.example.json']
# Test Main + the KeyboardInterrupt exception
with pytest.raises(SystemExit):
main(args)
assert log_has('Using config: config_bittrex.json.example ...', caplog)
assert log_has('Using config: config_examples/config_bittrex.example.json ...', caplog)
assert log_has('Fatal exception!', caplog)
@ -85,12 +85,12 @@ def test_main_keyboard_interrupt(mocker, default_conf, caplog) -> None:
mocker.patch('freqtrade.wallets.Wallets.update', MagicMock())
mocker.patch('freqtrade.freqtradebot.init_db', MagicMock())
args = ['trade', '-c', 'config_bittrex.json.example']
args = ['trade', '-c', 'config_examples/config_bittrex.example.json']
# Test Main + the KeyboardInterrupt exception
with pytest.raises(SystemExit):
main(args)
assert log_has('Using config: config_bittrex.json.example ...', caplog)
assert log_has('Using config: config_examples/config_bittrex.example.json ...', caplog)
assert log_has('SIGINT received, aborting ...', caplog)
@ -106,12 +106,12 @@ def test_main_operational_exception(mocker, default_conf, caplog) -> None:
mocker.patch('freqtrade.freqtradebot.RPCManager', MagicMock())
mocker.patch('freqtrade.freqtradebot.init_db', MagicMock())
args = ['trade', '-c', 'config_bittrex.json.example']
args = ['trade', '-c', 'config_examples/config_bittrex.example.json']
# Test Main + the KeyboardInterrupt exception
with pytest.raises(SystemExit):
main(args)
assert log_has('Using config: config_bittrex.json.example ...', caplog)
assert log_has('Using config: config_examples/config_bittrex.example.json ...', caplog)
assert log_has('Oh snap!', caplog)
@ -157,12 +157,16 @@ def test_main_reload_config(mocker, default_conf, caplog) -> None:
mocker.patch('freqtrade.freqtradebot.RPCManager', MagicMock())
mocker.patch('freqtrade.freqtradebot.init_db', MagicMock())
args = Arguments(['trade', '-c', 'config_bittrex.json.example']).get_parsed_arg()
args = Arguments([
'trade',
'-c',
'config_examples/config_bittrex.example.json'
]).get_parsed_arg()
worker = Worker(args=args, config=default_conf)
with pytest.raises(SystemExit):
main(['trade', '-c', 'config_bittrex.json.example'])
main(['trade', '-c', 'config_examples/config_bittrex.example.json'])
assert log_has('Using config: config_bittrex.json.example ...', caplog)
assert log_has('Using config: config_examples/config_bittrex.example.json ...', caplog)
assert worker_mock.call_count == 4
assert reconfigure_mock.call_count == 1
assert isinstance(worker.freqtrade, FreqtradeBot)
@ -180,7 +184,11 @@ def test_reconfigure(mocker, default_conf) -> None:
mocker.patch('freqtrade.freqtradebot.RPCManager', MagicMock())
mocker.patch('freqtrade.freqtradebot.init_db', MagicMock())
args = Arguments(['trade', '-c', 'config_bittrex.json.example']).get_parsed_arg()
args = Arguments([
'trade',
'-c',
'config_examples/config_bittrex.example.json'
]).get_parsed_arg()
worker = Worker(args=args, config=default_conf)
freqtrade = worker.freqtrade

17
tests/test_misc.py
View File

@ -7,7 +7,7 @@ from unittest.mock import MagicMock
import pytest
from freqtrade.misc import (decimals_per_coin, file_dump_json, file_load_json, format_ms_time,
pair_to_filename, plural, render_template,
pair_to_filename, parse_db_uri_for_logging, plural, render_template,
render_template_with_fallback, round_coin_value, safe_value_fallback,
safe_value_fallback2, shorten_date)
@ -179,3 +179,18 @@ def test_render_template_fallback(mocker):
)
assert isinstance(val, str)
assert 'if self.dp' in val
def test_parse_db_uri_for_logging() -> None:
postgresql_conn_uri = "postgresql+psycopg2://scott123:scott123@host/dbname"
mariadb_conn_uri = "mariadb+mariadbconnector://app_user:Password123!@127.0.0.1:3306/company"
mysql_conn_uri = "mysql+pymysql://user:pass@some_mariadb/dbname?charset=utf8mb4"
sqlite_conn_uri = "sqlite:////freqtrade/user_data/tradesv3.sqlite"
censored_pwd = "*****"
def get_pwd(x): return x.split(':')[2].split('@')[0]
assert get_pwd(parse_db_uri_for_logging(postgresql_conn_uri)) == censored_pwd
assert get_pwd(parse_db_uri_for_logging(mariadb_conn_uri)) == censored_pwd
assert get_pwd(parse_db_uri_for_logging(mysql_conn_uri)) == censored_pwd
assert sqlite_conn_uri == parse_db_uri_for_logging(sqlite_conn_uri)

16
tests/test_persistence.py
View File

@ -1124,6 +1124,21 @@ def test_total_open_trades_stakes(fee, use_db):
Trade.use_db = True
@pytest.mark.usefixtures("init_persistence")
@pytest.mark.parametrize('use_db', [True, False])
def test_get_total_closed_profit(fee, use_db):
Trade.use_db = use_db
Trade.reset_trades()
res = Trade.get_total_closed_profit()
assert res == 0
create_mock_trades(fee, use_db)
res = Trade.get_total_closed_profit()
assert res == 0.000739127
Trade.use_db = True
@pytest.mark.usefixtures("init_persistence")
@pytest.mark.parametrize('use_db', [True, False])
def test_get_trades_proxy(fee, use_db):
@ -1298,6 +1313,7 @@ def test_Trade_object_idem():
'open_date',
'get_best_pair',
'get_overall_performance',
'get_total_closed_profit',
'total_open_trades_stakes',
'get_sold_trades_without_assigned_fees',
'get_open_trades_without_assigned_fees',

4
tests/test_plotting.py
View File

@ -364,7 +364,7 @@ def test_start_plot_dataframe(mocker):
aup = mocker.patch("freqtrade.plot.plotting.load_and_plot_trades", MagicMock())
args = [
"plot-dataframe",
"--config", "config_bittrex.json.example",
"--config", "config_examples/config_bittrex.example.json",
"--pairs", "ETH/BTC"
]
start_plot_dataframe(get_args(args))
@ -408,7 +408,7 @@ def test_start_plot_profit(mocker):
aup = mocker.patch("freqtrade.plot.plotting.plot_profit", MagicMock())
args = [
"plot-profit",
"--config", "config_bittrex.json.example",
"--config", "config_examples/config_bittrex.example.json",
"--pairs", "ETH/BTC"
]
start_plot_profit(get_args(args))

66
tests/test_wallets.py
View File

@ -121,13 +121,19 @@ def test_get_trade_stake_amount_no_stake_amount(default_conf, mocker) -> None:
freqtrade.wallets.get_trade_stake_amount('ETH/BTC')
@pytest.mark.parametrize("balance_ratio,result1,result2", [
(1, 50, 66.66666),
(0.99, 49.5, 66.0),
(0.50, 25, 33.3333),
@pytest.mark.parametrize("balance_ratio,capital,result1,result2", [
(1, None, 50, 66.66666),
(0.99, None, 49.5, 66.0),
(0.50, None, 25, 33.3333),
# Tests with capital ignore balance_ratio
(1, 100, 50, 0.0),
(0.99, 200, 50, 66.66666),
(0.99, 150, 50, 50),
(0.50, 50, 25, 0.0),
(0.50, 10, 5, 0.0),
])
def test_get_trade_stake_amount_unlimited_amount(default_conf, ticker, balance_ratio, result1,
result2, limit_buy_order_open,
def test_get_trade_stake_amount_unlimited_amount(default_conf, ticker, balance_ratio, capital,
result1, result2, limit_buy_order_open,
fee, mocker) -> None:
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
@ -141,6 +147,8 @@ def test_get_trade_stake_amount_unlimited_amount(default_conf, ticker, balance_r
conf['dry_run_wallet'] = 100
conf['max_open_trades'] = 2
conf['tradable_balance_ratio'] = balance_ratio
if capital is not None:
conf['available_capital'] = capital
freqtrade = get_patched_freqtradebot(mocker, conf)
@ -170,3 +178,49 @@ def test_get_trade_stake_amount_unlimited_amount(default_conf, ticker, balance_r
freqtrade.config['max_open_trades'] = 0
result = freqtrade.wallets.get_trade_stake_amount('NEO/USDT')
assert result == 0
@pytest.mark.parametrize('stake_amount,min_stake_amount,max_stake_amount,expected', [
(22, 11, 50, 22),
(100, 11, 500, 100),
(1000, 11, 500, 500), # Above max-stake
(20, 15, 10, 0), # Minimum stake > max-stake
(1, 11, 100, 11), # Below min stake
(1, 15, 10, 0), # Below min stake and min_stake > max_stake
])
def test__validate_stake_amount(mocker, default_conf,
stake_amount, min_stake_amount, max_stake_amount, expected):
freqtrade = get_patched_freqtradebot(mocker, default_conf)
mocker.patch("freqtrade.wallets.Wallets.get_available_stake_amount",
return_value=max_stake_amount)
res = freqtrade.wallets._validate_stake_amount('XRP/USDT', stake_amount, min_stake_amount)
assert res == expected
@pytest.mark.parametrize('available_capital,closed_profit,open_stakes,free,expected', [
(None, 10, 100, 910, 1000),
(None, 0, 0, 2500, 2500),
(None, 500, 0, 2500, 2000),
(None, 500, 0, 2500, 2000),
(None, -70, 0, 1930, 2000),
# Only available balance matters when it's set.
(100, 0, 0, 0, 100),
(1000, 0, 2, 5, 1000),
(1235, 2250, 2, 5, 1235),
(1235, -2250, 2, 5, 1235),
])
def test_get_starting_balance(mocker, default_conf, available_capital, closed_profit,
open_stakes, free, expected):
if available_capital:
default_conf['available_capital'] = available_capital
mocker.patch("freqtrade.persistence.models.Trade.get_total_closed_profit",
return_value=closed_profit)
mocker.patch("freqtrade.persistence.models.Trade.total_open_trades_stakes",
return_value=open_stakes)
mocker.patch("freqtrade.wallets.Wallets.get_free", return_value=free)
freqtrade = get_patched_freqtradebot(mocker, default_conf)
assert freqtrade.wallets.get_starting_balance() == expected