Merge pull request #5566 from freqtrade/remove_hyperopt
Remove legacy hyperopt
This commit is contained in:
Matthias
GitHub
commit
315ea1e116
6
.github/workflows/ci.yml
vendored
6
.github/workflows/ci.yml
vendored
@ -87,7 +87,7 @@ jobs:
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run: |
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cp config_examples/config_bittrex.example.json config.json
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freqtrade create-userdir --userdir user_data
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freqtrade hyperopt --datadir tests/testdata -e 5 --strategy SampleStrategy --hyperopt SampleHyperOpt --hyperopt-loss SharpeHyperOptLossDaily --print-all
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freqtrade hyperopt --datadir tests/testdata -e 5 --strategy SampleStrategy --hyperopt-loss SharpeHyperOptLossDaily --print-all
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- name: Flake8
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run: |
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@ -180,7 +180,7 @@ jobs:
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run: |
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cp config_examples/config_bittrex.example.json config.json
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freqtrade create-userdir --userdir user_data
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freqtrade hyperopt --datadir tests/testdata -e 5 --strategy SampleStrategy --hyperopt SampleHyperOpt --hyperopt-loss SharpeHyperOptLossDaily --print-all
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freqtrade hyperopt --datadir tests/testdata -e 5 --strategy SampleStrategy --hyperopt-loss SharpeHyperOptLossDaily --print-all
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- name: Flake8
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run: |
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@ -247,7 +247,7 @@ jobs:
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run: |
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cp config_examples/config_bittrex.example.json config.json
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freqtrade create-userdir --userdir user_data
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freqtrade hyperopt --datadir tests/testdata -e 5 --strategy SampleStrategy --hyperopt SampleHyperOpt --hyperopt-loss SharpeHyperOptLossDaily --print-all
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freqtrade hyperopt --datadir tests/testdata -e 5 --strategy SampleStrategy --hyperopt-loss SharpeHyperOptLossDaily --print-all
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- name: Flake8
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run: |
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@ -33,7 +33,7 @@ jobs:
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- script:
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- cp config_examples/config_bittrex.example.json config.json
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- freqtrade create-userdir --userdir user_data
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- freqtrade hyperopt --datadir tests/testdata -e 5 --strategy SampleStrategy --hyperopt SampleHyperOpt --hyperopt-loss SharpeHyperOptLossDaily
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- freqtrade hyperopt --datadir tests/testdata -e 5 --strategy SampleStrategy --hyperopt-loss SharpeHyperOptLossDaily
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name: hyperopt
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- script: flake8
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name: flake8
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@ -79,22 +79,22 @@ For any other type of installation please refer to [Installation doc](https://ww
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```
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usage: freqtrade [-h] [-V]
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{trade,create-userdir,new-config,new-hyperopt,new-strategy,download-data,convert-data,convert-trade-data,backtesting,edge,hyperopt,hyperopt-list,hyperopt-show,list-exchanges,list-hyperopts,list-markets,list-pairs,list-strategies,list-timeframes,show-trades,test-pairlist,plot-dataframe,plot-profit}
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{trade,create-userdir,new-config,new-strategy,download-data,convert-data,convert-trade-data,list-data,backtesting,edge,hyperopt,hyperopt-list,hyperopt-show,list-exchanges,list-hyperopts,list-markets,list-pairs,list-strategies,list-timeframes,show-trades,test-pairlist,install-ui,plot-dataframe,plot-profit,webserver}
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...
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Free, open source crypto trading bot
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positional arguments:
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{trade,create-userdir,new-config,new-hyperopt,new-strategy,download-data,convert-data,convert-trade-data,backtesting,edge,hyperopt,hyperopt-list,hyperopt-show,list-exchanges,list-hyperopts,list-markets,list-pairs,list-strategies,list-timeframes,show-trades,test-pairlist,plot-dataframe,plot-profit}
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{trade,create-userdir,new-config,new-strategy,download-data,convert-data,convert-trade-data,list-data,backtesting,edge,hyperopt,hyperopt-list,hyperopt-show,list-exchanges,list-hyperopts,list-markets,list-pairs,list-strategies,list-timeframes,show-trades,test-pairlist,install-ui,plot-dataframe,plot-profit,webserver}
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trade Trade module.
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create-userdir Create user-data directory.
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new-config Create new config
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new-hyperopt Create new hyperopt
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new-strategy Create new strategy
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download-data Download backtesting data.
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convert-data Convert candle (OHLCV) data from one format to
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another.
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convert-trade-data Convert trade data from one format to another.
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list-data List downloaded data.
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backtesting Backtesting module.
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edge Edge module.
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hyperopt Hyperopt module.
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@ -108,8 +108,10 @@ positional arguments:
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list-timeframes Print available timeframes for the exchange.
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show-trades Show trades.
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test-pairlist Test your pairlist configuration.
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install-ui Install FreqUI
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plot-dataframe Plot candles with indicators.
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plot-profit Generate plot showing profits.
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webserver Webserver module.
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optional arguments:
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-h, --help show this help message and exit
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@ -67,10 +67,10 @@ Currently, the arguments are:
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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.
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!!! Note
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This function is called once per iteration - so please make sure to have this as optimized as possible to not slow hyperopt down unnecessarily.
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This function is called once per epoch - so please make sure to have this as optimized as possible to not slow hyperopt down unnecessarily.
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!!! Note
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Please keep the arguments `*args` and `**kwargs` in the interface to allow us to extend this interface later.
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!!! Note "`*args` and `**kwargs`"
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Please keep the arguments `*args` and `**kwargs` in the interface to allow us to extend this interface in the future.
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## Overriding pre-defined spaces
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@ -82,8 +82,22 @@ class MyAwesomeStrategy(IStrategy):
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# Define a custom stoploss space.
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def stoploss_space():
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return [SKDecimal(-0.05, -0.01, decimals=3, name='stoploss')]
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# Define custom ROI space
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def roi_space() -> List[Dimension]:
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return [
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Integer(10, 120, name='roi_t1'),
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Integer(10, 60, name='roi_t2'),
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Integer(10, 40, name='roi_t3'),
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SKDecimal(0.01, 0.04, decimals=3, name='roi_p1'),
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SKDecimal(0.01, 0.07, decimals=3, name='roi_p2'),
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SKDecimal(0.01, 0.20, decimals=3, name='roi_p3'),
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]
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```
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!!! Note
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All overrides are optional and can be mixed/matched as necessary.
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## Space options
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For the additional spaces, scikit-optimize (in combination with Freqtrade) provides the following space types:
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@ -105,281 +119,3 @@ from freqtrade.optimize.space import Categorical, Dimension, Integer, SKDecimal,
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Assuming the definition of a rather small space (`SKDecimal(0.10, 0.15, decimals=2, name='xxx')`) - SKDecimal will have 5 possibilities (`[0.10, 0.11, 0.12, 0.13, 0.14, 0.15]`).
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A corresponding real space `Real(0.10, 0.15 name='xxx')` on the other hand has an almost unlimited number of possibilities (`[0.10, 0.010000000001, 0.010000000002, ... 0.014999999999, 0.01500000000]`).
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---
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## Legacy Hyperopt
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This Section explains the configuration of an explicit Hyperopt file (separate to the strategy).
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!!! Warning "Deprecated / legacy mode"
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Since the 2021.4 release you no longer have to write a separate hyperopt class, but all strategies can be hyperopted.
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Please read the [main hyperopt page](hyperopt.md) for more details.
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### Prepare hyperopt file
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Configuring an explicit hyperopt file is similar to writing your own strategy, and many tasks will be similar.
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!!! Tip "About this page"
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For this page, we will be using a fictional strategy called `AwesomeStrategy` - which will be optimized using the `AwesomeHyperopt` class.
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#### Create a Custom Hyperopt File
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The simplest way to get started is to use the following command, which will create a new hyperopt file from a template, which will be located under `user_data/hyperopts/AwesomeHyperopt.py`.
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Let assume you want a hyperopt file `AwesomeHyperopt.py`:
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``` bash
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freqtrade new-hyperopt --hyperopt AwesomeHyperopt
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```
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#### Legacy Hyperopt checklist
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Checklist on all tasks / possibilities in hyperopt
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Depending on the space you want to optimize, only some of the below are required:
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* fill `buy_strategy_generator` - for buy signal optimization
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* fill `indicator_space` - for buy signal optimization
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* fill `sell_strategy_generator` - for sell signal optimization
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* fill `sell_indicator_space` - for sell signal optimization
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!!! Note
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`populate_indicators` needs to create all indicators any of thee spaces may use, otherwise hyperopt will not work.
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Optional in hyperopt - can also be loaded from a strategy (recommended):
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* `populate_indicators` - fallback to create indicators
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* `populate_buy_trend` - fallback if not optimizing for buy space. should come from strategy
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* `populate_sell_trend` - fallback if not optimizing for sell space. should come from strategy
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!!! Note
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You always have to provide a strategy to Hyperopt, even if your custom Hyperopt class contains all methods.
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Assuming the optional methods are not in your hyperopt file, please use `--strategy AweSomeStrategy` which contains these methods so hyperopt can use these methods instead.
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Rarely you may also need to override:
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* `roi_space` - for custom ROI optimization (if you need the ranges for the ROI parameters in the optimization hyperspace that differ from default)
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* `generate_roi_table` - for custom ROI optimization (if you need the ranges for the values in the ROI table that differ from default or the number of entries (steps) in the ROI table which differs from the default 4 steps)
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* `stoploss_space` - for custom stoploss optimization (if you need the range for the stoploss parameter in the optimization hyperspace that differs from default)
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* `trailing_space` - for custom trailing stop optimization (if you need the ranges for the trailing stop parameters in the optimization hyperspace that differ from default)
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#### Defining a buy signal optimization
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Let's say you are curious: should you use MACD crossings or lower Bollinger
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Bands to trigger your buys. And you also wonder should you use RSI or ADX to
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help with those buy decisions. If you decide to use RSI or ADX, which values
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should I use for them? So let's use hyperparameter optimization to solve this
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mystery.
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We will start by defining a search space:
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```python
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def indicator_space() -> List[Dimension]:
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"""
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Define your Hyperopt space for searching strategy parameters
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"""
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return [
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Integer(20, 40, name='adx-value'),
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Integer(20, 40, name='rsi-value'),
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Categorical([True, False], name='adx-enabled'),
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Categorical([True, False], name='rsi-enabled'),
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Categorical(['bb_lower', 'macd_cross_signal'], name='trigger')
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]
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```
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Above definition says: I have five parameters I want you to randomly combine
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to find the best combination. Two of them are integer values (`adx-value` and `rsi-value`) and I want you test in the range of values 20 to 40.
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Then we have three category variables. First two are either `True` or `False`.
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We use these to either enable or disable the ADX and RSI guards.
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The last one we call `trigger` and use it to decide which buy trigger we want to use.
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So let's write the buy strategy generator using these values:
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```python
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@staticmethod
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def buy_strategy_generator(params: Dict[str, Any]) -> Callable:
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"""
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Define the buy strategy parameters to be used by Hyperopt.
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"""
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def populate_buy_trend(dataframe: DataFrame, metadata: dict) -> DataFrame:
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conditions = []
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# GUARDS AND TRENDS
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if 'adx-enabled' in params and params['adx-enabled']:
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conditions.append(dataframe['adx'] > params['adx-value'])
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if 'rsi-enabled' in params and params['rsi-enabled']:
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conditions.append(dataframe['rsi'] < params['rsi-value'])
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# TRIGGERS
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if 'trigger' in params:
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if params['trigger'] == 'bb_lower':
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conditions.append(dataframe['close'] < dataframe['bb_lowerband'])
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if params['trigger'] == 'macd_cross_signal':
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conditions.append(qtpylib.crossed_above(
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dataframe['macd'], dataframe['macdsignal']
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))
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# Check that volume is not 0
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conditions.append(dataframe['volume'] > 0)
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if conditions:
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dataframe.loc[
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reduce(lambda x, y: x & y, conditions),
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'buy'] = 1
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return dataframe
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return populate_buy_trend
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```
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Hyperopt will now call `populate_buy_trend()` many times (`epochs`) with different value combinations.
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It will use the given historical data and make buys based on the buy signals generated with the above function.
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Based on the results, hyperopt will tell you which parameter combination produced the best results (based on the configured [loss function](#loss-functions)).
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!!! Note
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The above setup expects to find ADX, RSI and Bollinger Bands in the populated indicators.
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When you want to test an indicator that isn't used by the bot currently, remember to
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add it to the `populate_indicators()` method in your strategy or hyperopt file.
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#### Sell optimization
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Similar to the buy-signal above, sell-signals can also be optimized.
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Place the corresponding settings into the following methods
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* Inside `sell_indicator_space()` - the parameters hyperopt shall be optimizing.
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* Within `sell_strategy_generator()` - populate the nested method `populate_sell_trend()` to apply the parameters.
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The configuration and rules are the same than for buy signals.
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To avoid naming collisions in the search-space, please prefix all sell-spaces with `sell-`.
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### Execute Hyperopt
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Once you have updated your hyperopt configuration you can run it.
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Because hyperopt tries a lot of combinations to find the best parameters it will take time to get a good result. More time usually results in better results.
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We strongly recommend to use `screen` or `tmux` to prevent any connection loss.
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```bash
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freqtrade hyperopt --config config.json --hyperopt <hyperoptname> --hyperopt-loss <hyperoptlossname> --strategy <strategyname> -e 500 --spaces all
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```
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Use `<hyperoptname>` as the name of the custom hyperopt used.
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The `-e` option will set how many evaluations hyperopt will do. Since hyperopt uses Bayesian search, running too many epochs at once may not produce greater results. Experience has shown that best results are usually not improving much after 500-1000 epochs.
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Doing multiple runs (executions) with a few 1000 epochs and different random state will most likely produce different results.
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The `--spaces all` option determines that all possible parameters should be optimized. Possibilities are listed below.
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!!! Note
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Hyperopt will store hyperopt results with the timestamp of the hyperopt start time.
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Reading commands (`hyperopt-list`, `hyperopt-show`) can use `--hyperopt-filename <filename>` to read and display older hyperopt results.
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You can find a list of filenames with `ls -l user_data/hyperopt_results/`.
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#### Running Hyperopt using methods from a strategy
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Hyperopt can reuse `populate_indicators`, `populate_buy_trend`, `populate_sell_trend` from your strategy, assuming these methods are **not** in your custom hyperopt file, and a strategy is provided.
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```bash
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freqtrade hyperopt --hyperopt AwesomeHyperopt --hyperopt-loss SharpeHyperOptLossDaily --strategy AwesomeStrategy
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```
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### Understand the Hyperopt Result
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Once Hyperopt is completed you can use the result to create a new strategy.
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Given the following result from hyperopt:
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```
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Best result:
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44/100: 135 trades. Avg profit 0.57%. Total profit 0.03871918 BTC (0.7722%). Avg duration 180.4 mins. Objective: 1.94367
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Buy hyperspace params:
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{ 'adx-value': 44,
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'rsi-value': 29,
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'adx-enabled': False,
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'rsi-enabled': True,
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'trigger': 'bb_lower'}
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```
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You should understand this result like:
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* The buy trigger that worked best was `bb_lower`.
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* You should not use ADX because `adx-enabled: False`)
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* You should **consider** using the RSI indicator (`rsi-enabled: True` and the best value is `29.0` (`rsi-value: 29.0`)
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You have to look inside your strategy file into `buy_strategy_generator()`
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method, what those values match to.
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So for example you had `rsi-value: 29.0` so we would look at `rsi`-block, that translates to the following code block:
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```python
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(dataframe['rsi'] < 29.0)
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```
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Translating your whole hyperopt result as the new buy-signal would then look like:
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```python
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def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
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dataframe.loc[
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(
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(dataframe['rsi'] < 29.0) & # rsi-value
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dataframe['close'] < dataframe['bb_lowerband'] # trigger
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),
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'buy'] = 1
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return dataframe
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```
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### Validate backtesting results
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Once the optimized parameters and conditions have been implemented into your strategy, you should backtest the strategy to make sure everything is working as expected.
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To achieve same results (number of trades, their durations, profit, etc.) than during Hyperopt, please use same configuration and parameters (timerange, timeframe, ...) used for hyperopt `--dmmp`/`--disable-max-market-positions` and `--eps`/`--enable-position-stacking` for Backtesting.
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Should results not match, please double-check to make sure you transferred all conditions correctly.
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Pay special care to the stoploss (and trailing stoploss) parameters, as these are often set in configuration files, which override changes to the strategy.
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You should also carefully review the log of your backtest to ensure that there were no parameters inadvertently set by the configuration (like `stoploss` or `trailing_stop`).
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### Sharing methods with your strategy
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Hyperopt classes provide access to the Strategy via the `strategy` class attribute.
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This can be a great way to reduce code duplication if used correctly, but will also complicate usage for inexperienced users.
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``` python
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from pandas import DataFrame
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from freqtrade.strategy.interface import IStrategy
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import freqtrade.vendor.qtpylib.indicators as qtpylib
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class MyAwesomeStrategy(IStrategy):
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buy_params = {
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'rsi-value': 30,
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'adx-value': 35,
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}
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def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
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return self.buy_strategy_generator(self.buy_params, dataframe, metadata)
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@staticmethod
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def buy_strategy_generator(params, dataframe: DataFrame, metadata: dict) -> DataFrame:
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dataframe.loc[
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(
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qtpylib.crossed_above(dataframe['rsi'], params['rsi-value']) &
|
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dataframe['adx'] > params['adx-value']) &
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dataframe['volume'] > 0
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)
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, 'buy'] = 1
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return dataframe
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class MyAwesomeHyperOpt(IHyperOpt):
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...
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@staticmethod
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def buy_strategy_generator(params: Dict[str, Any]) -> Callable:
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"""
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Define the buy strategy parameters to be used by Hyperopt.
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"""
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def populate_buy_trend(dataframe: DataFrame, metadata: dict) -> DataFrame:
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# Call strategy's buy strategy generator
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return self.StrategyClass.buy_strategy_generator(params, dataframe, metadata)
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return populate_buy_trend
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```
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|
||||
@ -12,22 +12,22 @@ This page explains the different parameters of the bot and how to run it.
|
||||
|
||||
```
|
||||
usage: freqtrade [-h] [-V]
|
||||
{trade,create-userdir,new-config,new-hyperopt,new-strategy,download-data,convert-data,convert-trade-data,backtesting,edge,hyperopt,hyperopt-list,hyperopt-show,list-exchanges,list-hyperopts,list-markets,list-pairs,list-strategies,list-timeframes,show-trades,test-pairlist,plot-dataframe,plot-profit}
|
||||
{trade,create-userdir,new-config,new-strategy,download-data,convert-data,convert-trade-data,list-data,backtesting,edge,hyperopt,hyperopt-list,hyperopt-show,list-exchanges,list-hyperopts,list-markets,list-pairs,list-strategies,list-timeframes,show-trades,test-pairlist,install-ui,plot-dataframe,plot-profit,webserver}
|
||||
...
|
||||
|
||||
Free, open source crypto trading bot
|
||||
|
||||
positional arguments:
|
||||
{trade,create-userdir,new-config,new-hyperopt,new-strategy,download-data,convert-data,convert-trade-data,backtesting,edge,hyperopt,hyperopt-list,hyperopt-show,list-exchanges,list-hyperopts,list-markets,list-pairs,list-strategies,list-timeframes,show-trades,test-pairlist,plot-dataframe,plot-profit}
|
||||
{trade,create-userdir,new-config,new-strategy,download-data,convert-data,convert-trade-data,list-data,backtesting,edge,hyperopt,hyperopt-list,hyperopt-show,list-exchanges,list-hyperopts,list-markets,list-pairs,list-strategies,list-timeframes,show-trades,test-pairlist,install-ui,plot-dataframe,plot-profit,webserver}
|
||||
trade Trade module.
|
||||
create-userdir Create user-data directory.
|
||||
new-config Create new config
|
||||
new-hyperopt Create new hyperopt
|
||||
new-strategy Create new strategy
|
||||
download-data Download backtesting data.
|
||||
convert-data Convert candle (OHLCV) data from one format to
|
||||
another.
|
||||
convert-trade-data Convert trade data from one format to another.
|
||||
list-data List downloaded data.
|
||||
backtesting Backtesting module.
|
||||
edge Edge module.
|
||||
hyperopt Hyperopt module.
|
||||
@ -41,8 +41,10 @@ positional arguments:
|
||||
list-timeframes Print available timeframes for the exchange.
|
||||
show-trades Show trades.
|
||||
test-pairlist Test your pairlist configuration.
|
||||
install-ui Install FreqUI
|
||||
plot-dataframe Plot candles with indicators.
|
||||
plot-profit Generate plot showing profits.
|
||||
webserver Webserver module.
|
||||
|
||||
optional arguments:
|
||||
-h, --help show this help message and exit
|
||||
|
||||
@ -38,3 +38,8 @@ Since only quoteVolume can be compared between assets, the other options (bidVol
|
||||
|
||||
Using `order_book_min` and `order_book_max` used to allow stepping the orderbook and trying to find the next ROI slot - trying to place sell-orders early.
|
||||
As this does however increase risk and provides no benefit, it's been removed for maintainability purposes in 2021.7.
|
||||
|
||||
### Legacy Hyperopt mode
|
||||
|
||||
Using separate hyperopt files was deprecated in 2021.4 and was removed in 2021.9.
|
||||
Please switch to the new [Parametrized Strategies](hyperopt.md) to benefit from the new hyperopt interface.
|
||||
|
||||
@ -167,7 +167,7 @@ Since hyperopt uses Bayesian search, running for too many epochs may not produce
|
||||
It's therefore recommended to run between 500-1000 epochs over and over until you hit at least 10.000 epochs in total (or are satisfied with the result). You can best judge by looking at the results - if the bot keeps discovering better strategies, it's best to keep on going.
|
||||
|
||||
```bash
|
||||
freqtrade hyperopt --hyperopt SampleHyperopt --hyperopt-loss SharpeHyperOptLossDaily --strategy SampleStrategy -e 1000
|
||||
freqtrade hyperopt --hyperopt-loss SharpeHyperOptLossDaily --strategy SampleStrategy -e 1000
|
||||
```
|
||||
|
||||
### Why does it take a long time to run hyperopt?
|
||||
|
||||
@ -44,9 +44,8 @@ usage: freqtrade hyperopt [-h] [-v] [--logfile FILE] [-V] [-c PATH] [-d PATH]
|
||||
[--data-format-ohlcv {json,jsongz,hdf5}]
|
||||
[--max-open-trades INT]
|
||||
[--stake-amount STAKE_AMOUNT] [--fee FLOAT]
|
||||
[-p PAIRS [PAIRS ...]] [--hyperopt NAME]
|
||||
[--hyperopt-path PATH] [--eps] [--dmmp]
|
||||
[--enable-protections]
|
||||
[-p PAIRS [PAIRS ...]] [--hyperopt-path PATH]
|
||||
[--eps] [--dmmp] [--enable-protections]
|
||||
[--dry-run-wallet DRY_RUN_WALLET] [-e INT]
|
||||
[--spaces {all,buy,sell,roi,stoploss,trailing,protection,default} [{all,buy,sell,roi,stoploss,trailing,protection,default} ...]]
|
||||
[--print-all] [--no-color] [--print-json] [-j JOBS]
|
||||
@ -73,10 +72,8 @@ optional arguments:
|
||||
-p PAIRS [PAIRS ...], --pairs PAIRS [PAIRS ...]
|
||||
Limit command to these pairs. Pairs are space-
|
||||
separated.
|
||||
--hyperopt NAME Specify hyperopt class name which will be used by the
|
||||
bot.
|
||||
--hyperopt-path PATH Specify additional lookup path for Hyperopt and
|
||||
Hyperopt Loss functions.
|
||||
--hyperopt-path PATH Specify additional lookup path for Hyperopt Loss
|
||||
functions.
|
||||
--eps, --enable-position-stacking
|
||||
Allow buying the same pair multiple times (position
|
||||
stacking).
|
||||
@ -558,7 +555,7 @@ For example, to use one month of data, pass `--timerange 20210101-20210201` (fro
|
||||
Full command:
|
||||
|
||||
```bash
|
||||
freqtrade hyperopt --hyperopt <hyperoptname> --strategy <strategyname> --timerange 20210101-20210201
|
||||
freqtrade hyperopt --strategy <strategyname> --timerange 20210101-20210201
|
||||
```
|
||||
|
||||
### Running Hyperopt with Smaller Search Space
|
||||
@ -684,7 +681,7 @@ If you have the `generate_roi_table()` and `roi_space()` methods in your custom
|
||||
|
||||
Override the `roi_space()` method if you need components of the ROI tables to vary in other ranges. Override the `generate_roi_table()` and `roi_space()` methods and implement your own custom approach for generation of the ROI tables during hyperoptimization if you need a different structure of the ROI tables or other amount of rows (steps).
|
||||
|
||||
A sample for these methods can be found in [sample_hyperopt_advanced.py](https://github.com/freqtrade/freqtrade/blob/develop/freqtrade/templates/sample_hyperopt_advanced.py).
|
||||
A sample for these methods can be found in the [overriding pre-defined spaces section](advanced-hyperopt.md#overriding-pre-defined-spaces).
|
||||
|
||||
!!! Note "Reduced search space"
|
||||
To limit the search space further, Decimals are limited to 3 decimal places (a precision of 0.001). This is usually sufficient, every value more precise than this will usually result in overfitted results. You can however [overriding pre-defined spaces](advanced-hyperopt.md#pverriding-pre-defined-spaces) to change this to your needs.
|
||||
@ -726,7 +723,7 @@ If you are optimizing stoploss values, Freqtrade creates the 'stoploss' optimiza
|
||||
|
||||
If you have the `stoploss_space()` method in your custom hyperopt file, remove it in order to utilize Stoploss hyperoptimization space generated by Freqtrade by default.
|
||||
|
||||
Override the `stoploss_space()` method and define the desired range in it if you need stoploss values to vary in other range during hyperoptimization. A sample for this method can be found in [user_data/hyperopts/sample_hyperopt_advanced.py](https://github.com/freqtrade/freqtrade/blob/develop/freqtrade/templates/sample_hyperopt_advanced.py).
|
||||
Override the `stoploss_space()` method and define the desired range in it if you need stoploss values to vary in other range during hyperoptimization. A sample for this method can be found in the [overriding pre-defined spaces section](advanced-hyperopt.md#overriding-pre-defined-spaces).
|
||||
|
||||
!!! Note "Reduced search space"
|
||||
To limit the search space further, Decimals are limited to 3 decimal places (a precision of 0.001). This is usually sufficient, every value more precise than this will usually result in overfitted results. You can however [overriding pre-defined spaces](advanced-hyperopt.md#pverriding-pre-defined-spaces) to change this to your needs.
|
||||
@ -764,10 +761,10 @@ As stated in the comment, you can also use it as the values of the corresponding
|
||||
|
||||
If you are optimizing trailing stop values, Freqtrade creates the 'trailing' optimization hyperspace for you. By default, the `trailing_stop` parameter is always set to True in that hyperspace, the value of the `trailing_only_offset_is_reached` vary between True and False, the values of the `trailing_stop_positive` and `trailing_stop_positive_offset` parameters vary in the ranges 0.02...0.35 and 0.01...0.1 correspondingly, which is sufficient in most cases.
|
||||
|
||||
Override the `trailing_space()` method and define the desired range in it if you need values of the trailing stop parameters to vary in other ranges during hyperoptimization. A sample for this method can be found in [user_data/hyperopts/sample_hyperopt_advanced.py](https://github.com/freqtrade/freqtrade/blob/develop/freqtrade/templates/sample_hyperopt_advanced.py).
|
||||
Override the `trailing_space()` method and define the desired range in it if you need values of the trailing stop parameters to vary in other ranges during hyperoptimization. A sample for this method can be found in the [overriding pre-defined spaces section](advanced-hyperopt.md#overriding-pre-defined-spaces).
|
||||
|
||||
!!! Note "Reduced search space"
|
||||
To limit the search space further, Decimals are limited to 3 decimal places (a precision of 0.001). This is usually sufficient, every value more precise than this will usually result in overfitted results. You can however [overriding pre-defined spaces](advanced-hyperopt.md#pverriding-pre-defined-spaces) to change this to your needs.
|
||||
To limit the search space further, Decimals are limited to 3 decimal places (a precision of 0.001). This is usually sufficient, every value more precise than this will usually result in overfitted results. You can however [overriding pre-defined spaces](advanced-hyperopt.md#overriding-pre-defined-spaces) to change this to your needs.
|
||||
|
||||
### Reproducible results
|
||||
|
||||
|
||||
@ -26,9 +26,7 @@ optional arguments:
|
||||
├── data
|
||||
├── hyperopt_results
|
||||
├── hyperopts
|
||||
│ ├── sample_hyperopt_advanced.py
|
||||
│ ├── sample_hyperopt_loss.py
|
||||
│ └── sample_hyperopt.py
|
||||
├── notebooks
|
||||
│ └── strategy_analysis_example.ipynb
|
||||
├── plot
|
||||
@ -111,46 +109,11 @@ Using the advanced template (populates all optional functions and methods)
|
||||
freqtrade new-strategy --strategy AwesomeStrategy --template advanced
|
||||
```
|
||||
|
||||
## Create new hyperopt
|
||||
## List Strategies
|
||||
|
||||
Creates a new hyperopt from a template similar to SampleHyperopt.
|
||||
The file will be named inline with your class name, and will not overwrite existing files.
|
||||
Use the `list-strategies` subcommand to see all strategies in one particular directory.
|
||||
|
||||
Results will be located in `user_data/hyperopts/<classname>.py`.
|
||||
|
||||
``` output
|
||||
usage: freqtrade new-hyperopt [-h] [--userdir PATH] [--hyperopt NAME]
|
||||
[--template {full,minimal,advanced}]
|
||||
|
||||
optional arguments:
|
||||
-h, --help show this help message and exit
|
||||
--userdir PATH, --user-data-dir PATH
|
||||
Path to userdata directory.
|
||||
--hyperopt NAME Specify hyperopt class name which will be used by the
|
||||
bot.
|
||||
--template {full,minimal,advanced}
|
||||
Use a template which is either `minimal`, `full`
|
||||
(containing multiple sample indicators) or `advanced`.
|
||||
Default: `full`.
|
||||
```
|
||||
|
||||
### Sample usage of new-hyperopt
|
||||
|
||||
```bash
|
||||
freqtrade new-hyperopt --hyperopt AwesomeHyperopt
|
||||
```
|
||||
|
||||
With custom user directory
|
||||
|
||||
```bash
|
||||
freqtrade new-hyperopt --userdir ~/.freqtrade/ --hyperopt AwesomeHyperopt
|
||||
```
|
||||
|
||||
## List Strategies and List Hyperopts
|
||||
|
||||
Use the `list-strategies` subcommand to see all strategies in one particular directory and the `list-hyperopts` subcommand to list custom Hyperopts.
|
||||
|
||||
These subcommands are useful for finding problems in your environment with loading strategies or hyperopt classes: modules with strategies or hyperopt classes that contain errors and failed to load are printed in red (LOAD FAILED), while strategies or hyperopt classes with duplicate names are printed in yellow (DUPLICATE NAME).
|
||||
This subcommand is useful for finding problems in your environment with loading strategies: modules with strategies that contain errors and failed to load are printed in red (LOAD FAILED), while strategies with duplicate names are printed in yellow (DUPLICATE NAME).
|
||||
|
||||
```
|
||||
usage: freqtrade list-strategies [-h] [-v] [--logfile FILE] [-V] [-c PATH]
|
||||
@ -164,34 +127,6 @@ optional arguments:
|
||||
--no-color Disable colorization of hyperopt results. May be
|
||||
useful if you are redirecting output to a file.
|
||||
|
||||
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: `config.json`).
|
||||
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.
|
||||
```
|
||||
```
|
||||
usage: freqtrade list-hyperopts [-h] [-v] [--logfile FILE] [-V] [-c PATH]
|
||||
[-d PATH] [--userdir PATH]
|
||||
[--hyperopt-path PATH] [-1] [--no-color]
|
||||
|
||||
optional arguments:
|
||||
-h, --help show this help message and exit
|
||||
--hyperopt-path PATH Specify additional lookup path for Hyperopt and
|
||||
Hyperopt Loss functions.
|
||||
-1, --one-column Print output in one column.
|
||||
--no-color Disable colorization of hyperopt results. May be
|
||||
useful if you are redirecting output to a file.
|
||||
|
||||
Common arguments:
|
||||
-v, --verbose Verbose mode (-vv for more, -vvv to get all messages).
|
||||
--logfile FILE Log to the file specified. Special values are:
|
||||
@ -211,18 +146,16 @@ Common arguments:
|
||||
!!! Warning
|
||||
Using these commands will try to load all python files from a directory. This can be a security risk if untrusted files reside in this directory, since all module-level code is executed.
|
||||
|
||||
Example: Search default strategies and hyperopts directories (within the default userdir).
|
||||
Example: Search default strategies directories (within the default userdir).
|
||||
|
||||
``` bash
|
||||
freqtrade list-strategies
|
||||
freqtrade list-hyperopts
|
||||
```
|
||||
|
||||
Example: Search strategies and hyperopts directory within the userdir.
|
||||
Example: Search strategies directory within the userdir.
|
||||
|
||||
``` bash
|
||||
freqtrade list-strategies --userdir ~/.freqtrade/
|
||||
freqtrade list-hyperopts --userdir ~/.freqtrade/
|
||||
```
|
||||
|
||||
Example: Search dedicated strategy path.
|
||||
@ -231,12 +164,6 @@ Example: Search dedicated strategy path.
|
||||
freqtrade list-strategies --strategy-path ~/.freqtrade/strategies/
|
||||
```
|
||||
|
||||
Example: Search dedicated hyperopt path.
|
||||
|
||||
``` bash
|
||||
freqtrade list-hyperopt --hyperopt-path ~/.freqtrade/hyperopts/
|
||||
```
|
||||
|
||||
## List Exchanges
|
||||
|
||||
Use the `list-exchanges` subcommand to see the exchanges available for the bot.
|
||||
|
||||
@ -11,11 +11,11 @@ from freqtrade.commands.build_config_commands import start_new_config
|
||||
from freqtrade.commands.data_commands import (start_convert_data, start_download_data,
|
||||
start_list_data)
|
||||
from freqtrade.commands.deploy_commands import (start_create_userdir, start_install_ui,
|
||||
start_new_hyperopt, start_new_strategy)
|
||||
start_new_strategy)
|
||||
from freqtrade.commands.hyperopt_commands import start_hyperopt_list, start_hyperopt_show
|
||||
from freqtrade.commands.list_commands import (start_list_exchanges, start_list_hyperopts,
|
||||
start_list_markets, start_list_strategies,
|
||||
start_list_timeframes, start_show_trades)
|
||||
from freqtrade.commands.list_commands import (start_list_exchanges, start_list_markets,
|
||||
start_list_strategies, start_list_timeframes,
|
||||
start_show_trades)
|
||||
from freqtrade.commands.optimize_commands import start_backtesting, start_edge, start_hyperopt
|
||||
from freqtrade.commands.pairlist_commands import start_test_pairlist
|
||||
from freqtrade.commands.plot_commands import start_plot_dataframe, start_plot_profit
|
||||
|
||||
@ -55,8 +55,6 @@ ARGS_BUILD_CONFIG = ["config"]
|
||||
|
||||
ARGS_BUILD_STRATEGY = ["user_data_dir", "strategy", "template"]
|
||||
|
||||
ARGS_BUILD_HYPEROPT = ["user_data_dir", "hyperopt", "template"]
|
||||
|
||||
ARGS_CONVERT_DATA = ["pairs", "format_from", "format_to", "erase"]
|
||||
ARGS_CONVERT_DATA_OHLCV = ARGS_CONVERT_DATA + ["timeframes"]
|
||||
|
||||
@ -92,10 +90,10 @@ ARGS_HYPEROPT_SHOW = ["hyperopt_list_best", "hyperopt_list_profitable", "hyperop
|
||||
|
||||
NO_CONF_REQURIED = ["convert-data", "convert-trade-data", "download-data", "list-timeframes",
|
||||
"list-markets", "list-pairs", "list-strategies", "list-data",
|
||||
"list-hyperopts", "hyperopt-list", "hyperopt-show",
|
||||
"hyperopt-list", "hyperopt-show",
|
||||
"plot-dataframe", "plot-profit", "show-trades"]
|
||||
|
||||
NO_CONF_ALLOWED = ["create-userdir", "list-exchanges", "new-hyperopt", "new-strategy"]
|
||||
NO_CONF_ALLOWED = ["create-userdir", "list-exchanges", "new-strategy"]
|
||||
|
||||
|
||||
class Arguments:
|
||||
@ -174,12 +172,11 @@ class Arguments:
|
||||
from freqtrade.commands import (start_backtesting, start_convert_data, start_create_userdir,
|
||||
start_download_data, start_edge, start_hyperopt,
|
||||
start_hyperopt_list, start_hyperopt_show, start_install_ui,
|
||||
start_list_data, start_list_exchanges, start_list_hyperopts,
|
||||
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_webserver)
|
||||
start_list_data, start_list_exchanges, start_list_markets,
|
||||
start_list_strategies, start_list_timeframes,
|
||||
start_new_config, start_new_strategy, start_plot_dataframe,
|
||||
start_plot_profit, 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
|
||||
@ -206,12 +203,6 @@ class Arguments:
|
||||
build_config_cmd.set_defaults(func=start_new_config)
|
||||
self._build_args(optionlist=ARGS_BUILD_CONFIG, parser=build_config_cmd)
|
||||
|
||||
# add new-hyperopt subcommand
|
||||
build_hyperopt_cmd = subparsers.add_parser('new-hyperopt',
|
||||
help="Create new hyperopt")
|
||||
build_hyperopt_cmd.set_defaults(func=start_new_hyperopt)
|
||||
self._build_args(optionlist=ARGS_BUILD_HYPEROPT, parser=build_hyperopt_cmd)
|
||||
|
||||
# add new-strategy subcommand
|
||||
build_strategy_cmd = subparsers.add_parser('new-strategy',
|
||||
help="Create new strategy")
|
||||
@ -300,15 +291,6 @@ class Arguments:
|
||||
list_exchanges_cmd.set_defaults(func=start_list_exchanges)
|
||||
self._build_args(optionlist=ARGS_LIST_EXCHANGES, parser=list_exchanges_cmd)
|
||||
|
||||
# Add list-hyperopts subcommand
|
||||
list_hyperopts_cmd = subparsers.add_parser(
|
||||
'list-hyperopts',
|
||||
help='Print available hyperopt classes.',
|
||||
parents=[_common_parser],
|
||||
)
|
||||
list_hyperopts_cmd.set_defaults(func=start_list_hyperopts)
|
||||
self._build_args(optionlist=ARGS_LIST_HYPEROPTS, parser=list_hyperopts_cmd)
|
||||
|
||||
# Add list-markets subcommand
|
||||
list_markets_cmd = subparsers.add_parser(
|
||||
'list-markets',
|
||||
|
||||
@ -1,7 +1,7 @@
|
||||
"""
|
||||
Definition of cli arguments used in arguments.py
|
||||
"""
|
||||
from argparse import ArgumentTypeError
|
||||
from argparse import SUPPRESS, ArgumentTypeError
|
||||
|
||||
from freqtrade import __version__, constants
|
||||
from freqtrade.constants import HYPEROPT_LOSS_BUILTIN
|
||||
@ -203,13 +203,13 @@ AVAILABLE_CLI_OPTIONS = {
|
||||
# Hyperopt
|
||||
"hyperopt": Arg(
|
||||
'--hyperopt',
|
||||
help='Specify hyperopt class name which will be used by the bot.',
|
||||
help=SUPPRESS,
|
||||
metavar='NAME',
|
||||
required=False,
|
||||
),
|
||||
"hyperopt_path": Arg(
|
||||
'--hyperopt-path',
|
||||
help='Specify additional lookup path for Hyperopt and Hyperopt Loss functions.',
|
||||
help='Specify additional lookup path for Hyperopt Loss functions.',
|
||||
metavar='PATH',
|
||||
),
|
||||
"epochs": Arg(
|
||||
|
||||
@ -7,7 +7,7 @@ import requests
|
||||
|
||||
from freqtrade.configuration import setup_utils_configuration
|
||||
from freqtrade.configuration.directory_operations import copy_sample_files, create_userdata_dir
|
||||
from freqtrade.constants import USERPATH_HYPEROPTS, USERPATH_STRATEGIES
|
||||
from freqtrade.constants import USERPATH_STRATEGIES
|
||||
from freqtrade.enums import RunMode
|
||||
from freqtrade.exceptions import OperationalException
|
||||
from freqtrade.misc import render_template, render_template_with_fallback
|
||||
@ -87,56 +87,6 @@ def start_new_strategy(args: Dict[str, Any]) -> None:
|
||||
raise OperationalException("`new-strategy` requires --strategy to be set.")
|
||||
|
||||
|
||||
def deploy_new_hyperopt(hyperopt_name: str, hyperopt_path: Path, subtemplate: str) -> None:
|
||||
"""
|
||||
Deploys a new hyperopt template to hyperopt_path
|
||||
"""
|
||||
fallback = 'full'
|
||||
buy_guards = render_template_with_fallback(
|
||||
templatefile=f"subtemplates/hyperopt_buy_guards_{subtemplate}.j2",
|
||||
templatefallbackfile=f"subtemplates/hyperopt_buy_guards_{fallback}.j2",
|
||||
)
|
||||
sell_guards = render_template_with_fallback(
|
||||
templatefile=f"subtemplates/hyperopt_sell_guards_{subtemplate}.j2",
|
||||
templatefallbackfile=f"subtemplates/hyperopt_sell_guards_{fallback}.j2",
|
||||
)
|
||||
buy_space = render_template_with_fallback(
|
||||
templatefile=f"subtemplates/hyperopt_buy_space_{subtemplate}.j2",
|
||||
templatefallbackfile=f"subtemplates/hyperopt_buy_space_{fallback}.j2",
|
||||
)
|
||||
sell_space = render_template_with_fallback(
|
||||
templatefile=f"subtemplates/hyperopt_sell_space_{subtemplate}.j2",
|
||||
templatefallbackfile=f"subtemplates/hyperopt_sell_space_{fallback}.j2",
|
||||
)
|
||||
|
||||
strategy_text = render_template(templatefile='base_hyperopt.py.j2',
|
||||
arguments={"hyperopt": hyperopt_name,
|
||||
"buy_guards": buy_guards,
|
||||
"sell_guards": sell_guards,
|
||||
"buy_space": buy_space,
|
||||
"sell_space": sell_space,
|
||||
})
|
||||
|
||||
logger.info(f"Writing hyperopt to `{hyperopt_path}`.")
|
||||
hyperopt_path.write_text(strategy_text)
|
||||
|
||||
|
||||
def start_new_hyperopt(args: Dict[str, Any]) -> None:
|
||||
|
||||
config = setup_utils_configuration(args, RunMode.UTIL_NO_EXCHANGE)
|
||||
|
||||
if 'hyperopt' in args and args['hyperopt']:
|
||||
|
||||
new_path = config['user_data_dir'] / USERPATH_HYPEROPTS / (args['hyperopt'] + '.py')
|
||||
|
||||
if new_path.exists():
|
||||
raise OperationalException(f"`{new_path}` already exists. "
|
||||
"Please choose another Hyperopt Name.")
|
||||
deploy_new_hyperopt(args['hyperopt'], new_path, args['template'])
|
||||
else:
|
||||
raise OperationalException("`new-hyperopt` requires --hyperopt to be set.")
|
||||
|
||||
|
||||
def clean_ui_subdir(directory: Path):
|
||||
if directory.is_dir():
|
||||
logger.info("Removing UI directory content.")
|
||||
|
||||
@ -10,7 +10,7 @@ from colorama import init as colorama_init
|
||||
from tabulate import tabulate
|
||||
|
||||
from freqtrade.configuration import setup_utils_configuration
|
||||
from freqtrade.constants import USERPATH_HYPEROPTS, USERPATH_STRATEGIES
|
||||
from freqtrade.constants import USERPATH_STRATEGIES
|
||||
from freqtrade.enums import RunMode
|
||||
from freqtrade.exceptions import OperationalException
|
||||
from freqtrade.exchange import market_is_active, validate_exchanges
|
||||
@ -92,25 +92,6 @@ def start_list_strategies(args: Dict[str, Any]) -> None:
|
||||
_print_objs_tabular(strategy_objs, config.get('print_colorized', False))
|
||||
|
||||
|
||||
def start_list_hyperopts(args: Dict[str, Any]) -> None:
|
||||
"""
|
||||
Print files with HyperOpt custom classes available in the directory
|
||||
"""
|
||||
from freqtrade.resolvers.hyperopt_resolver import HyperOptResolver
|
||||
|
||||
config = setup_utils_configuration(args, RunMode.UTIL_NO_EXCHANGE)
|
||||
|
||||
directory = Path(config.get('hyperopt_path', config['user_data_dir'] / USERPATH_HYPEROPTS))
|
||||
hyperopt_objs = HyperOptResolver.search_all_objects(directory, not args['print_one_column'])
|
||||
# Sort alphabetically
|
||||
hyperopt_objs = sorted(hyperopt_objs, key=lambda x: x['name'])
|
||||
|
||||
if args['print_one_column']:
|
||||
print('\n'.join([s['name'] for s in hyperopt_objs]))
|
||||
else:
|
||||
_print_objs_tabular(hyperopt_objs, config.get('print_colorized', False))
|
||||
|
||||
|
||||
def start_list_timeframes(args: Dict[str, Any]) -> None:
|
||||
"""
|
||||
Print timeframes available on Exchange
|
||||
|
||||
@ -69,9 +69,7 @@ DUST_PER_COIN = {
|
||||
# Source files with destination directories within user-directory
|
||||
USER_DATA_FILES = {
|
||||
'sample_strategy.py': USERPATH_STRATEGIES,
|
||||
'sample_hyperopt_advanced.py': USERPATH_HYPEROPTS,
|
||||
'sample_hyperopt_loss.py': USERPATH_HYPEROPTS,
|
||||
'sample_hyperopt.py': USERPATH_HYPEROPTS,
|
||||
'strategy_analysis_example.ipynb': USERPATH_NOTEBOOKS,
|
||||
}
|
||||
|
||||
|
||||
@ -22,6 +22,7 @@ from pandas import DataFrame
|
||||
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.exceptions import OperationalException
|
||||
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
|
||||
@ -30,7 +31,7 @@ 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, hyperopt_serializer
|
||||
from freqtrade.optimize.optimize_reports import generate_strategy_stats
|
||||
from freqtrade.resolvers.hyperopt_resolver import HyperOptLossResolver, HyperOptResolver
|
||||
from freqtrade.resolvers.hyperopt_resolver import HyperOptLossResolver
|
||||
|
||||
|
||||
# Suppress scikit-learn FutureWarnings from skopt
|
||||
@ -78,10 +79,10 @@ 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
|
||||
raise OperationalException(
|
||||
"Using separate Hyperopt files has been removed in 2021.9. Please convert "
|
||||
"your existing Hyperopt file to the new Hyperoptable strategy interface")
|
||||
|
||||
self.backtesting._set_strategy(self.backtesting.strategylist[0])
|
||||
self.custom_hyperopt.strategy = self.backtesting.strategy
|
||||
@ -103,31 +104,6 @@ class Hyperopt:
|
||||
self.num_epochs_saved = 0
|
||||
self.current_best_epoch: Optional[Dict[str, Any]] = None
|
||||
|
||||
if not self.auto_hyperopt:
|
||||
# Populate "fallback" functions here
|
||||
# (hasattr is slow so should not be run during "regular" operations)
|
||||
if hasattr(self.custom_hyperopt, 'populate_indicators'):
|
||||
logger.warning(
|
||||
"DEPRECATED: Using `populate_indicators()` in the hyperopt file is deprecated. "
|
||||
"Please move these methods to your strategy."
|
||||
)
|
||||
self.backtesting.strategy.populate_indicators = ( # type: ignore
|
||||
self.custom_hyperopt.populate_indicators) # type: ignore
|
||||
if hasattr(self.custom_hyperopt, 'populate_buy_trend'):
|
||||
logger.warning(
|
||||
"DEPRECATED: Using `populate_buy_trend()` in the hyperopt file is deprecated. "
|
||||
"Please move these methods to your strategy."
|
||||
)
|
||||
self.backtesting.strategy.populate_buy_trend = ( # type: ignore
|
||||
self.custom_hyperopt.populate_buy_trend) # type: ignore
|
||||
if hasattr(self.custom_hyperopt, 'populate_sell_trend'):
|
||||
logger.warning(
|
||||
"DEPRECATED: Using `populate_sell_trend()` in the hyperopt file is deprecated. "
|
||||
"Please move these methods to your strategy."
|
||||
)
|
||||
self.backtesting.strategy.populate_sell_trend = ( # type: ignore
|
||||
self.custom_hyperopt.populate_sell_trend) # type: ignore
|
||||
|
||||
# Use max_open_trades for hyperopt as well, except --disable-max-market-positions is set
|
||||
if self.config.get('use_max_market_positions', True):
|
||||
self.max_open_trades = self.config['max_open_trades']
|
||||
@ -256,7 +232,7 @@ class Hyperopt:
|
||||
"""
|
||||
Assign the dimensions in the hyperoptimization space.
|
||||
"""
|
||||
if self.auto_hyperopt and HyperoptTools.has_space(self.config, 'protection'):
|
||||
if HyperoptTools.has_space(self.config, 'protection'):
|
||||
# Protections can only be optimized when using the Parameter interface
|
||||
logger.debug("Hyperopt has 'protection' space")
|
||||
# Enable Protections if protection space is selected.
|
||||
@ -285,6 +261,15 @@ class Hyperopt:
|
||||
self.dimensions = (self.buy_space + self.sell_space + self.protection_space
|
||||
+ self.roi_space + self.stoploss_space + self.trailing_space)
|
||||
|
||||
def assign_params(self, params_dict: Dict, category: str) -> None:
|
||||
"""
|
||||
Assign hyperoptable parameters
|
||||
"""
|
||||
for attr_name, attr in self.backtesting.strategy.enumerate_parameters(category):
|
||||
if attr.optimize:
|
||||
# noinspection PyProtectedMember
|
||||
attr.value = params_dict[attr_name]
|
||||
|
||||
def generate_optimizer(self, raw_params: List[Any], iteration=None) -> Dict:
|
||||
"""
|
||||
Used Optimize function.
|
||||
@ -296,18 +281,13 @@ class Hyperopt:
|
||||
|
||||
# Apply parameters
|
||||
if HyperoptTools.has_space(self.config, 'buy'):
|
||||
self.backtesting.strategy.advise_buy = ( # type: ignore
|
||||
self.custom_hyperopt.buy_strategy_generator(params_dict))
|
||||
self.assign_params(params_dict, 'buy')
|
||||
|
||||
if HyperoptTools.has_space(self.config, 'sell'):
|
||||
self.backtesting.strategy.advise_sell = ( # type: ignore
|
||||
self.custom_hyperopt.sell_strategy_generator(params_dict))
|
||||
self.assign_params(params_dict, 'sell')
|
||||
|
||||
if HyperoptTools.has_space(self.config, 'protection'):
|
||||
for attr_name, attr in self.backtesting.strategy.enumerate_parameters('protection'):
|
||||
if attr.optimize:
|
||||
# noinspection PyProtectedMember
|
||||
attr.value = params_dict[attr_name]
|
||||
self.assign_params(params_dict, 'protection')
|
||||
|
||||
if HyperoptTools.has_space(self.config, 'roi'):
|
||||
self.backtesting.strategy.minimal_roi = ( # type: ignore
|
||||
@ -517,7 +497,6 @@ 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(),
|
||||
|
||||
@ -4,9 +4,9 @@ This module implements a convenience auto-hyperopt class, which can be used toge
|
||||
that implement IHyperStrategy interface.
|
||||
"""
|
||||
from contextlib import suppress
|
||||
from typing import Any, Callable, Dict, List
|
||||
from typing import Callable, Dict, List
|
||||
|
||||
from pandas import DataFrame
|
||||
from freqtrade.exceptions import OperationalException
|
||||
|
||||
|
||||
with suppress(ImportError):
|
||||
@ -15,6 +15,14 @@ with suppress(ImportError):
|
||||
from freqtrade.optimize.hyperopt_interface import IHyperOpt
|
||||
|
||||
|
||||
def _format_exception_message(space: str) -> str:
|
||||
raise OperationalException(
|
||||
f"The '{space}' space is included into the hyperoptimization "
|
||||
f"but no parameter for this space was not found in your Strategy. "
|
||||
f"Please make sure to have parameters for this space enabled for optimization "
|
||||
f"or remove the '{space}' space from hyperoptimization.")
|
||||
|
||||
|
||||
class HyperOptAuto(IHyperOpt):
|
||||
"""
|
||||
This class delegates functionality to Strategy(IHyperStrategy) and Strategy.HyperOpt classes.
|
||||
@ -22,26 +30,6 @@ class HyperOptAuto(IHyperOpt):
|
||||
sell_indicator_space methods, but other hyperopt methods can be overridden as well.
|
||||
"""
|
||||
|
||||
def buy_strategy_generator(self, params: Dict[str, Any]) -> Callable:
|
||||
def populate_buy_trend(dataframe: DataFrame, metadata: dict):
|
||||
for attr_name, attr in self.strategy.enumerate_parameters('buy'):
|
||||
if attr.optimize:
|
||||
# noinspection PyProtectedMember
|
||||
attr.value = params[attr_name]
|
||||
return self.strategy.populate_buy_trend(dataframe, metadata)
|
||||
|
||||
return populate_buy_trend
|
||||
|
||||
def sell_strategy_generator(self, params: Dict[str, Any]) -> Callable:
|
||||
def populate_sell_trend(dataframe: DataFrame, metadata: dict):
|
||||
for attr_name, attr in self.strategy.enumerate_parameters('sell'):
|
||||
if attr.optimize:
|
||||
# noinspection PyProtectedMember
|
||||
attr.value = params[attr_name]
|
||||
return self.strategy.populate_sell_trend(dataframe, metadata)
|
||||
|
||||
return populate_sell_trend
|
||||
|
||||
def _get_func(self, name) -> Callable:
|
||||
"""
|
||||
Return a function defined in Strategy.HyperOpt class, or one defined in super() class.
|
||||
@ -60,21 +48,22 @@ class HyperOptAuto(IHyperOpt):
|
||||
if attr.optimize:
|
||||
yield attr.get_space(attr_name)
|
||||
|
||||
def _get_indicator_space(self, category, fallback_method_name):
|
||||
def _get_indicator_space(self, category):
|
||||
# TODO: is this necessary, or can we call "generate_space" directly?
|
||||
indicator_space = list(self._generate_indicator_space(category))
|
||||
if len(indicator_space) > 0:
|
||||
return indicator_space
|
||||
else:
|
||||
return self._get_func(fallback_method_name)()
|
||||
_format_exception_message(category)
|
||||
|
||||
def indicator_space(self) -> List['Dimension']:
|
||||
return self._get_indicator_space('buy', 'indicator_space')
|
||||
return self._get_indicator_space('buy')
|
||||
|
||||
def sell_indicator_space(self) -> List['Dimension']:
|
||||
return self._get_indicator_space('sell', 'sell_indicator_space')
|
||||
return self._get_indicator_space('sell')
|
||||
|
||||
def protection_space(self) -> List['Dimension']:
|
||||
return self._get_indicator_space('protection', 'protection_space')
|
||||
return self._get_indicator_space('protection')
|
||||
|
||||
def generate_roi_table(self, params: Dict) -> Dict[int, float]:
|
||||
return self._get_func('generate_roi_table')(params)
|
||||
|
||||
@ -5,11 +5,10 @@ This module defines the interface to apply for hyperopt
|
||||
import logging
|
||||
import math
|
||||
from abc import ABC
|
||||
from typing import Any, Callable, Dict, List
|
||||
from typing import Dict, List
|
||||
|
||||
from skopt.space import Categorical, Dimension, Integer
|
||||
|
||||
from freqtrade.exceptions import OperationalException
|
||||
from freqtrade.exchange import timeframe_to_minutes
|
||||
from freqtrade.misc import round_dict
|
||||
from freqtrade.optimize.space import SKDecimal
|
||||
@ -19,13 +18,6 @@ from freqtrade.strategy import IStrategy
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
def _format_exception_message(method: str, space: str) -> str:
|
||||
return (f"The '{space}' space is included into the hyperoptimization "
|
||||
f"but {method}() method is not found in your "
|
||||
f"custom Hyperopt class. You should either implement this "
|
||||
f"method or remove the '{space}' space from hyperoptimization.")
|
||||
|
||||
|
||||
class IHyperOpt(ABC):
|
||||
"""
|
||||
Interface for freqtrade hyperopt
|
||||
@ -45,37 +37,6 @@ class IHyperOpt(ABC):
|
||||
IHyperOpt.ticker_interval = str(config['timeframe']) # DEPRECATED
|
||||
IHyperOpt.timeframe = str(config['timeframe'])
|
||||
|
||||
def buy_strategy_generator(self, params: Dict[str, Any]) -> Callable:
|
||||
"""
|
||||
Create a buy strategy generator.
|
||||
"""
|
||||
raise OperationalException(_format_exception_message('buy_strategy_generator', 'buy'))
|
||||
|
||||
def sell_strategy_generator(self, params: Dict[str, Any]) -> Callable:
|
||||
"""
|
||||
Create a sell strategy generator.
|
||||
"""
|
||||
raise OperationalException(_format_exception_message('sell_strategy_generator', 'sell'))
|
||||
|
||||
def protection_space(self) -> List[Dimension]:
|
||||
"""
|
||||
Create a protection space.
|
||||
Only supported by the Parameter interface.
|
||||
"""
|
||||
raise OperationalException(_format_exception_message('indicator_space', 'protection'))
|
||||
|
||||
def indicator_space(self) -> List[Dimension]:
|
||||
"""
|
||||
Create an indicator space.
|
||||
"""
|
||||
raise OperationalException(_format_exception_message('indicator_space', 'buy'))
|
||||
|
||||
def sell_indicator_space(self) -> List[Dimension]:
|
||||
"""
|
||||
Create a sell indicator space.
|
||||
"""
|
||||
raise OperationalException(_format_exception_message('sell_indicator_space', 'sell'))
|
||||
|
||||
def generate_roi_table(self, params: Dict) -> Dict[int, float]:
|
||||
"""
|
||||
Create a ROI table.
|
||||
|
||||
@ -9,7 +9,6 @@ from typing import Dict
|
||||
|
||||
from freqtrade.constants import HYPEROPT_LOSS_BUILTIN, USERPATH_HYPEROPTS
|
||||
from freqtrade.exceptions import OperationalException
|
||||
from freqtrade.optimize.hyperopt_interface import IHyperOpt
|
||||
from freqtrade.optimize.hyperopt_loss_interface import IHyperOptLoss
|
||||
from freqtrade.resolvers import IResolver
|
||||
|
||||
@ -17,43 +16,6 @@ from freqtrade.resolvers import IResolver
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
class HyperOptResolver(IResolver):
|
||||
"""
|
||||
This class contains all the logic to load custom hyperopt class
|
||||
"""
|
||||
object_type = IHyperOpt
|
||||
object_type_str = "Hyperopt"
|
||||
user_subdir = USERPATH_HYPEROPTS
|
||||
initial_search_path = None
|
||||
|
||||
@staticmethod
|
||||
def load_hyperopt(config: Dict) -> IHyperOpt:
|
||||
"""
|
||||
Load the custom hyperopt class from config parameter
|
||||
:param config: configuration dictionary
|
||||
"""
|
||||
if not config.get('hyperopt'):
|
||||
raise OperationalException("No Hyperopt set. Please use `--hyperopt` to specify "
|
||||
"the Hyperopt class to use.")
|
||||
|
||||
hyperopt_name = config['hyperopt']
|
||||
|
||||
hyperopt = HyperOptResolver.load_object(hyperopt_name, config,
|
||||
kwargs={'config': config},
|
||||
extra_dir=config.get('hyperopt_path'))
|
||||
|
||||
if not hasattr(hyperopt, 'populate_indicators'):
|
||||
logger.info("Hyperopt class does not provide populate_indicators() method. "
|
||||
"Using populate_indicators from the strategy.")
|
||||
if not hasattr(hyperopt, 'populate_buy_trend'):
|
||||
logger.info("Hyperopt class does not provide populate_buy_trend() method. "
|
||||
"Using populate_buy_trend from the strategy.")
|
||||
if not hasattr(hyperopt, 'populate_sell_trend'):
|
||||
logger.info("Hyperopt class does not provide populate_sell_trend() method. "
|
||||
"Using populate_sell_trend from the strategy.")
|
||||
return hyperopt
|
||||
|
||||
|
||||
class HyperOptLossResolver(IResolver):
|
||||
"""
|
||||
This class contains all the logic to load custom hyperopt loss class
|
||||
|
||||
@ -1,137 +0,0 @@
|
||||
# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement
|
||||
|
||||
# --- Do not remove these libs ---
|
||||
from functools import reduce
|
||||
from typing import Any, Callable, Dict, List
|
||||
|
||||
import numpy as np # noqa
|
||||
import pandas as pd # noqa
|
||||
from pandas import DataFrame
|
||||
from skopt.space import Categorical, Dimension, Integer, Real # noqa
|
||||
|
||||
from freqtrade.optimize.hyperopt_interface import IHyperOpt
|
||||
|
||||
# --------------------------------
|
||||
# Add your lib to import here
|
||||
import talib.abstract as ta # noqa
|
||||
import freqtrade.vendor.qtpylib.indicators as qtpylib
|
||||
|
||||
|
||||
class {{ hyperopt }}(IHyperOpt):
|
||||
"""
|
||||
This is a Hyperopt template to get you started.
|
||||
|
||||
More information in the documentation: https://www.freqtrade.io/en/latest/hyperopt/
|
||||
|
||||
You should:
|
||||
- Add any lib you need to build your hyperopt.
|
||||
|
||||
You must keep:
|
||||
- The prototypes for the methods: populate_indicators, indicator_space, buy_strategy_generator.
|
||||
|
||||
The methods roi_space, generate_roi_table and stoploss_space are not required
|
||||
and are provided by default.
|
||||
However, you may override them if you need 'roi' and 'stoploss' spaces that
|
||||
differ from the defaults offered by Freqtrade.
|
||||
Sample implementation of these methods will be copied to `user_data/hyperopts` when
|
||||
creating the user-data directory using `freqtrade create-userdir --userdir user_data`,
|
||||
or is available online under the following URL:
|
||||
https://github.com/freqtrade/freqtrade/blob/develop/freqtrade/templates/sample_hyperopt_advanced.py.
|
||||
"""
|
||||
|
||||
@staticmethod
|
||||
def indicator_space() -> List[Dimension]:
|
||||
"""
|
||||
Define your Hyperopt space for searching buy strategy parameters.
|
||||
"""
|
||||
return [
|
||||
{{ buy_space | indent(12) }}
|
||||
]
|
||||
|
||||
@staticmethod
|
||||
def buy_strategy_generator(params: Dict[str, Any]) -> Callable:
|
||||
"""
|
||||
Define the buy strategy parameters to be used by Hyperopt.
|
||||
"""
|
||||
def populate_buy_trend(dataframe: DataFrame, metadata: dict) -> DataFrame:
|
||||
"""
|
||||
Buy strategy Hyperopt will build and use.
|
||||
"""
|
||||
conditions = []
|
||||
|
||||
# GUARDS AND TRENDS
|
||||
{{ buy_guards | indent(12) }}
|
||||
|
||||
# TRIGGERS
|
||||
if 'trigger' in params:
|
||||
if params['trigger'] == 'bb_lower':
|
||||
conditions.append(dataframe['close'] < dataframe['bb_lowerband'])
|
||||
if params['trigger'] == 'macd_cross_signal':
|
||||
conditions.append(qtpylib.crossed_above(
|
||||
dataframe['macd'], dataframe['macdsignal']
|
||||
))
|
||||
if params['trigger'] == 'sar_reversal':
|
||||
conditions.append(qtpylib.crossed_above(
|
||||
dataframe['close'], dataframe['sar']
|
||||
))
|
||||
|
||||
# Check that the candle had volume
|
||||
conditions.append(dataframe['volume'] > 0)
|
||||
|
||||
if conditions:
|
||||
dataframe.loc[
|
||||
reduce(lambda x, y: x & y, conditions),
|
||||
'buy'] = 1
|
||||
|
||||
return dataframe
|
||||
|
||||
return populate_buy_trend
|
||||
|
||||
@staticmethod
|
||||
def sell_indicator_space() -> List[Dimension]:
|
||||
"""
|
||||
Define your Hyperopt space for searching sell strategy parameters.
|
||||
"""
|
||||
return [
|
||||
{{ sell_space | indent(12) }}
|
||||
]
|
||||
|
||||
@staticmethod
|
||||
def sell_strategy_generator(params: Dict[str, Any]) -> Callable:
|
||||
"""
|
||||
Define the sell strategy parameters to be used by Hyperopt.
|
||||
"""
|
||||
def populate_sell_trend(dataframe: DataFrame, metadata: dict) -> DataFrame:
|
||||
"""
|
||||
Sell strategy Hyperopt will build and use.
|
||||
"""
|
||||
conditions = []
|
||||
|
||||
# GUARDS AND TRENDS
|
||||
{{ sell_guards | indent(12) }}
|
||||
|
||||
# TRIGGERS
|
||||
if 'sell-trigger' in params:
|
||||
if params['sell-trigger'] == 'sell-bb_upper':
|
||||
conditions.append(dataframe['close'] > dataframe['bb_upperband'])
|
||||
if params['sell-trigger'] == 'sell-macd_cross_signal':
|
||||
conditions.append(qtpylib.crossed_above(
|
||||
dataframe['macdsignal'], dataframe['macd']
|
||||
))
|
||||
if params['sell-trigger'] == 'sell-sar_reversal':
|
||||
conditions.append(qtpylib.crossed_above(
|
||||
dataframe['sar'], dataframe['close']
|
||||
))
|
||||
|
||||
# Check that the candle had volume
|
||||
conditions.append(dataframe['volume'] > 0)
|
||||
|
||||
if conditions:
|
||||
dataframe.loc[
|
||||
reduce(lambda x, y: x & y, conditions),
|
||||
'sell'] = 1
|
||||
|
||||
return dataframe
|
||||
|
||||
return populate_sell_trend
|
||||
|
||||
@ -1,174 +0,0 @@
|
||||
# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement
|
||||
# isort: skip_file
|
||||
|
||||
# --- Do not remove these libs ---
|
||||
from functools import reduce
|
||||
from typing import Any, Callable, Dict, List
|
||||
|
||||
import numpy as np # noqa
|
||||
import pandas as pd # noqa
|
||||
from pandas import DataFrame
|
||||
from skopt.space import Categorical, Dimension, Integer, Real # noqa
|
||||
|
||||
from freqtrade.optimize.hyperopt_interface import IHyperOpt
|
||||
|
||||
# --------------------------------
|
||||
# Add your lib to import here
|
||||
import talib.abstract as ta # noqa
|
||||
import freqtrade.vendor.qtpylib.indicators as qtpylib
|
||||
|
||||
|
||||
class SampleHyperOpt(IHyperOpt):
|
||||
"""
|
||||
This is a sample Hyperopt to inspire you.
|
||||
|
||||
More information in the documentation: https://www.freqtrade.io/en/latest/hyperopt/
|
||||
|
||||
You should:
|
||||
- Rename the class name to some unique name.
|
||||
- Add any methods you want to build your hyperopt.
|
||||
- Add any lib you need to build your hyperopt.
|
||||
|
||||
An easier way to get a new hyperopt file is by using
|
||||
`freqtrade new-hyperopt --hyperopt MyCoolHyperopt`.
|
||||
|
||||
You must keep:
|
||||
- The prototypes for the methods: populate_indicators, indicator_space, buy_strategy_generator.
|
||||
|
||||
The methods roi_space, generate_roi_table and stoploss_space are not required
|
||||
and are provided by default.
|
||||
However, you may override them if you need 'roi' and 'stoploss' spaces that
|
||||
differ from the defaults offered by Freqtrade.
|
||||
Sample implementation of these methods will be copied to `user_data/hyperopts` when
|
||||
creating the user-data directory using `freqtrade create-userdir --userdir user_data`,
|
||||
or is available online under the following URL:
|
||||
https://github.com/freqtrade/freqtrade/blob/develop/freqtrade/templates/sample_hyperopt_advanced.py.
|
||||
"""
|
||||
|
||||
@staticmethod
|
||||
def indicator_space() -> List[Dimension]:
|
||||
"""
|
||||
Define your Hyperopt space for searching buy strategy parameters.
|
||||
"""
|
||||
return [
|
||||
Integer(10, 25, name='mfi-value'),
|
||||
Integer(15, 45, name='fastd-value'),
|
||||
Integer(20, 50, name='adx-value'),
|
||||
Integer(20, 40, name='rsi-value'),
|
||||
Categorical([True, False], name='mfi-enabled'),
|
||||
Categorical([True, False], name='fastd-enabled'),
|
||||
Categorical([True, False], name='adx-enabled'),
|
||||
Categorical([True, False], name='rsi-enabled'),
|
||||
Categorical(['bb_lower', 'macd_cross_signal', 'sar_reversal'], name='trigger')
|
||||
]
|
||||
|
||||
@staticmethod
|
||||
def buy_strategy_generator(params: Dict[str, Any]) -> Callable:
|
||||
"""
|
||||
Define the buy strategy parameters to be used by Hyperopt.
|
||||
"""
|
||||
def populate_buy_trend(dataframe: DataFrame, metadata: dict) -> DataFrame:
|
||||
"""
|
||||
Buy strategy Hyperopt will build and use.
|
||||
"""
|
||||
conditions = []
|
||||
|
||||
# GUARDS AND TRENDS
|
||||
if 'mfi-enabled' in params and params['mfi-enabled']:
|
||||
conditions.append(dataframe['mfi'] < params['mfi-value'])
|
||||
if 'fastd-enabled' in params and params['fastd-enabled']:
|
||||
conditions.append(dataframe['fastd'] < params['fastd-value'])
|
||||
if 'adx-enabled' in params and params['adx-enabled']:
|
||||
conditions.append(dataframe['adx'] > params['adx-value'])
|
||||
if 'rsi-enabled' in params and params['rsi-enabled']:
|
||||
conditions.append(dataframe['rsi'] < params['rsi-value'])
|
||||
|
||||
# TRIGGERS
|
||||
if 'trigger' in params:
|
||||
if params['trigger'] == 'bb_lower':
|
||||
conditions.append(dataframe['close'] < dataframe['bb_lowerband'])
|
||||
if params['trigger'] == 'macd_cross_signal':
|
||||
conditions.append(qtpylib.crossed_above(
|
||||
dataframe['macd'], dataframe['macdsignal']
|
||||
))
|
||||
if params['trigger'] == 'sar_reversal':
|
||||
conditions.append(qtpylib.crossed_above(
|
||||
dataframe['close'], dataframe['sar']
|
||||
))
|
||||
|
||||
# Check that volume is not 0
|
||||
conditions.append(dataframe['volume'] > 0)
|
||||
|
||||
if conditions:
|
||||
dataframe.loc[
|
||||
reduce(lambda x, y: x & y, conditions),
|
||||
'buy'] = 1
|
||||
|
||||
return dataframe
|
||||
|
||||
return populate_buy_trend
|
||||
|
||||
@staticmethod
|
||||
def sell_indicator_space() -> List[Dimension]:
|
||||
"""
|
||||
Define your Hyperopt space for searching sell strategy parameters.
|
||||
"""
|
||||
return [
|
||||
Integer(75, 100, name='sell-mfi-value'),
|
||||
Integer(50, 100, name='sell-fastd-value'),
|
||||
Integer(50, 100, name='sell-adx-value'),
|
||||
Integer(60, 100, name='sell-rsi-value'),
|
||||
Categorical([True, False], name='sell-mfi-enabled'),
|
||||
Categorical([True, False], name='sell-fastd-enabled'),
|
||||
Categorical([True, False], name='sell-adx-enabled'),
|
||||
Categorical([True, False], name='sell-rsi-enabled'),
|
||||
Categorical(['sell-bb_upper',
|
||||
'sell-macd_cross_signal',
|
||||
'sell-sar_reversal'], name='sell-trigger')
|
||||
]
|
||||
|
||||
@staticmethod
|
||||
def sell_strategy_generator(params: Dict[str, Any]) -> Callable:
|
||||
"""
|
||||
Define the sell strategy parameters to be used by Hyperopt.
|
||||
"""
|
||||
def populate_sell_trend(dataframe: DataFrame, metadata: dict) -> DataFrame:
|
||||
"""
|
||||
Sell strategy Hyperopt will build and use.
|
||||
"""
|
||||
conditions = []
|
||||
|
||||
# GUARDS AND TRENDS
|
||||
if 'sell-mfi-enabled' in params and params['sell-mfi-enabled']:
|
||||
conditions.append(dataframe['mfi'] > params['sell-mfi-value'])
|
||||
if 'sell-fastd-enabled' in params and params['sell-fastd-enabled']:
|
||||
conditions.append(dataframe['fastd'] > params['sell-fastd-value'])
|
||||
if 'sell-adx-enabled' in params and params['sell-adx-enabled']:
|
||||
conditions.append(dataframe['adx'] < params['sell-adx-value'])
|
||||
if 'sell-rsi-enabled' in params and params['sell-rsi-enabled']:
|
||||
conditions.append(dataframe['rsi'] > params['sell-rsi-value'])
|
||||
|
||||
# TRIGGERS
|
||||
if 'sell-trigger' in params:
|
||||
if params['sell-trigger'] == 'sell-bb_upper':
|
||||
conditions.append(dataframe['close'] > dataframe['bb_upperband'])
|
||||
if params['sell-trigger'] == 'sell-macd_cross_signal':
|
||||
conditions.append(qtpylib.crossed_above(
|
||||
dataframe['macdsignal'], dataframe['macd']
|
||||
))
|
||||
if params['sell-trigger'] == 'sell-sar_reversal':
|
||||
conditions.append(qtpylib.crossed_above(
|
||||
dataframe['sar'], dataframe['close']
|
||||
))
|
||||
|
||||
# Check that volume is not 0
|
||||
conditions.append(dataframe['volume'] > 0)
|
||||
|
||||
if conditions:
|
||||
dataframe.loc[
|
||||
reduce(lambda x, y: x & y, conditions),
|
||||
'sell'] = 1
|
||||
|
||||
return dataframe
|
||||
|
||||
return populate_sell_trend
|
||||
@ -1,269 +0,0 @@
|
||||
# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement
|
||||
# isort: skip_file
|
||||
# --- Do not remove these libs ---
|
||||
from functools import reduce
|
||||
from typing import Any, Callable, Dict, List
|
||||
|
||||
import numpy as np # noqa
|
||||
import pandas as pd # noqa
|
||||
from pandas import DataFrame
|
||||
from freqtrade.optimize.space import Categorical, Dimension, Integer, SKDecimal, Real # noqa
|
||||
|
||||
from freqtrade.optimize.hyperopt_interface import IHyperOpt
|
||||
|
||||
# --------------------------------
|
||||
# Add your lib to import here
|
||||
import talib.abstract as ta # noqa
|
||||
import freqtrade.vendor.qtpylib.indicators as qtpylib
|
||||
|
||||
|
||||
class AdvancedSampleHyperOpt(IHyperOpt):
|
||||
"""
|
||||
This is a sample hyperopt to inspire you.
|
||||
Feel free to customize it.
|
||||
|
||||
More information in the documentation: https://www.freqtrade.io/en/latest/hyperopt/
|
||||
|
||||
You should:
|
||||
- Rename the class name to some unique name.
|
||||
- Add any methods you want to build your hyperopt.
|
||||
- Add any lib you need to build your hyperopt.
|
||||
|
||||
You must keep:
|
||||
- The prototypes for the methods: populate_indicators, indicator_space, buy_strategy_generator.
|
||||
|
||||
The methods roi_space, generate_roi_table and stoploss_space are not required
|
||||
and are provided by default.
|
||||
However, you may override them if you need the
|
||||
'roi' and the 'stoploss' spaces that differ from the defaults offered by Freqtrade.
|
||||
|
||||
This sample illustrates how to override these methods.
|
||||
"""
|
||||
@staticmethod
|
||||
def populate_indicators(dataframe: DataFrame, metadata: dict) -> DataFrame:
|
||||
"""
|
||||
This method can also be loaded from the strategy, if it doesn't exist in the hyperopt class.
|
||||
"""
|
||||
dataframe['adx'] = ta.ADX(dataframe)
|
||||
macd = ta.MACD(dataframe)
|
||||
dataframe['macd'] = macd['macd']
|
||||
dataframe['macdsignal'] = macd['macdsignal']
|
||||
dataframe['mfi'] = ta.MFI(dataframe)
|
||||
dataframe['rsi'] = ta.RSI(dataframe)
|
||||
stoch_fast = ta.STOCHF(dataframe)
|
||||
dataframe['fastd'] = stoch_fast['fastd']
|
||||
dataframe['minus_di'] = ta.MINUS_DI(dataframe)
|
||||
# Bollinger bands
|
||||
bollinger = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=2)
|
||||
dataframe['bb_lowerband'] = bollinger['lower']
|
||||
dataframe['bb_upperband'] = bollinger['upper']
|
||||
dataframe['sar'] = ta.SAR(dataframe)
|
||||
return dataframe
|
||||
|
||||
@staticmethod
|
||||
def indicator_space() -> List[Dimension]:
|
||||
"""
|
||||
Define your Hyperopt space for searching buy strategy parameters.
|
||||
"""
|
||||
return [
|
||||
Integer(10, 25, name='mfi-value'),
|
||||
Integer(15, 45, name='fastd-value'),
|
||||
Integer(20, 50, name='adx-value'),
|
||||
Integer(20, 40, name='rsi-value'),
|
||||
Categorical([True, False], name='mfi-enabled'),
|
||||
Categorical([True, False], name='fastd-enabled'),
|
||||
Categorical([True, False], name='adx-enabled'),
|
||||
Categorical([True, False], name='rsi-enabled'),
|
||||
Categorical(['bb_lower', 'macd_cross_signal', 'sar_reversal'], name='trigger')
|
||||
]
|
||||
|
||||
@staticmethod
|
||||
def buy_strategy_generator(params: Dict[str, Any]) -> Callable:
|
||||
"""
|
||||
Define the buy strategy parameters to be used by hyperopt
|
||||
"""
|
||||
def populate_buy_trend(dataframe: DataFrame, metadata: dict) -> DataFrame:
|
||||
"""
|
||||
Buy strategy Hyperopt will build and use
|
||||
"""
|
||||
conditions = []
|
||||
# GUARDS AND TRENDS
|
||||
if 'mfi-enabled' in params and params['mfi-enabled']:
|
||||
conditions.append(dataframe['mfi'] < params['mfi-value'])
|
||||
if 'fastd-enabled' in params and params['fastd-enabled']:
|
||||
conditions.append(dataframe['fastd'] < params['fastd-value'])
|
||||
if 'adx-enabled' in params and params['adx-enabled']:
|
||||
conditions.append(dataframe['adx'] > params['adx-value'])
|
||||
if 'rsi-enabled' in params and params['rsi-enabled']:
|
||||
conditions.append(dataframe['rsi'] < params['rsi-value'])
|
||||
|
||||
# TRIGGERS
|
||||
if 'trigger' in params:
|
||||
if params['trigger'] == 'bb_lower':
|
||||
conditions.append(dataframe['close'] < dataframe['bb_lowerband'])
|
||||
if params['trigger'] == 'macd_cross_signal':
|
||||
conditions.append(qtpylib.crossed_above(
|
||||
dataframe['macd'], dataframe['macdsignal']
|
||||
))
|
||||
if params['trigger'] == 'sar_reversal':
|
||||
conditions.append(qtpylib.crossed_above(
|
||||
dataframe['close'], dataframe['sar']
|
||||
))
|
||||
|
||||
# Check that volume is not 0
|
||||
conditions.append(dataframe['volume'] > 0)
|
||||
|
||||
if conditions:
|
||||
dataframe.loc[
|
||||
reduce(lambda x, y: x & y, conditions),
|
||||
'buy'] = 1
|
||||
|
||||
return dataframe
|
||||
|
||||
return populate_buy_trend
|
||||
|
||||
@staticmethod
|
||||
def sell_indicator_space() -> List[Dimension]:
|
||||
"""
|
||||
Define your Hyperopt space for searching sell strategy parameters.
|
||||
"""
|
||||
return [
|
||||
Integer(75, 100, name='sell-mfi-value'),
|
||||
Integer(50, 100, name='sell-fastd-value'),
|
||||
Integer(50, 100, name='sell-adx-value'),
|
||||
Integer(60, 100, name='sell-rsi-value'),
|
||||
Categorical([True, False], name='sell-mfi-enabled'),
|
||||
Categorical([True, False], name='sell-fastd-enabled'),
|
||||
Categorical([True, False], name='sell-adx-enabled'),
|
||||
Categorical([True, False], name='sell-rsi-enabled'),
|
||||
Categorical(['sell-bb_upper',
|
||||
'sell-macd_cross_signal',
|
||||
'sell-sar_reversal'], name='sell-trigger')
|
||||
]
|
||||
|
||||
@staticmethod
|
||||
def sell_strategy_generator(params: Dict[str, Any]) -> Callable:
|
||||
"""
|
||||
Define the sell strategy parameters to be used by hyperopt
|
||||
"""
|
||||
def populate_sell_trend(dataframe: DataFrame, metadata: dict) -> DataFrame:
|
||||
"""
|
||||
Sell strategy Hyperopt will build and use
|
||||
"""
|
||||
# print(params)
|
||||
conditions = []
|
||||
# GUARDS AND TRENDS
|
||||
if 'sell-mfi-enabled' in params and params['sell-mfi-enabled']:
|
||||
conditions.append(dataframe['mfi'] > params['sell-mfi-value'])
|
||||
if 'sell-fastd-enabled' in params and params['sell-fastd-enabled']:
|
||||
conditions.append(dataframe['fastd'] > params['sell-fastd-value'])
|
||||
if 'sell-adx-enabled' in params and params['sell-adx-enabled']:
|
||||
conditions.append(dataframe['adx'] < params['sell-adx-value'])
|
||||
if 'sell-rsi-enabled' in params and params['sell-rsi-enabled']:
|
||||
conditions.append(dataframe['rsi'] > params['sell-rsi-value'])
|
||||
|
||||
# TRIGGERS
|
||||
if 'sell-trigger' in params:
|
||||
if params['sell-trigger'] == 'sell-bb_upper':
|
||||
conditions.append(dataframe['close'] > dataframe['bb_upperband'])
|
||||
if params['sell-trigger'] == 'sell-macd_cross_signal':
|
||||
conditions.append(qtpylib.crossed_above(
|
||||
dataframe['macdsignal'], dataframe['macd']
|
||||
))
|
||||
if params['sell-trigger'] == 'sell-sar_reversal':
|
||||
conditions.append(qtpylib.crossed_above(
|
||||
dataframe['sar'], dataframe['close']
|
||||
))
|
||||
|
||||
# Check that volume is not 0
|
||||
conditions.append(dataframe['volume'] > 0)
|
||||
|
||||
if conditions:
|
||||
dataframe.loc[
|
||||
reduce(lambda x, y: x & y, conditions),
|
||||
'sell'] = 1
|
||||
|
||||
return dataframe
|
||||
|
||||
return populate_sell_trend
|
||||
|
||||
@staticmethod
|
||||
def generate_roi_table(params: Dict) -> Dict[int, float]:
|
||||
"""
|
||||
Generate the ROI table that will be used by Hyperopt
|
||||
|
||||
This implementation generates the default legacy Freqtrade ROI tables.
|
||||
|
||||
Change it if you need different number of steps in the generated
|
||||
ROI tables or other structure of the ROI tables.
|
||||
|
||||
Please keep it aligned with parameters in the 'roi' optimization
|
||||
hyperspace defined by the roi_space method.
|
||||
"""
|
||||
roi_table = {}
|
||||
roi_table[0] = params['roi_p1'] + params['roi_p2'] + params['roi_p3']
|
||||
roi_table[params['roi_t3']] = params['roi_p1'] + params['roi_p2']
|
||||
roi_table[params['roi_t3'] + params['roi_t2']] = params['roi_p1']
|
||||
roi_table[params['roi_t3'] + params['roi_t2'] + params['roi_t1']] = 0
|
||||
|
||||
return roi_table
|
||||
|
||||
@staticmethod
|
||||
def roi_space() -> List[Dimension]:
|
||||
"""
|
||||
Values to search for each ROI steps
|
||||
|
||||
Override it if you need some different ranges for the parameters in the
|
||||
'roi' optimization hyperspace.
|
||||
|
||||
Please keep it aligned with the implementation of the
|
||||
generate_roi_table method.
|
||||
"""
|
||||
return [
|
||||
Integer(10, 120, name='roi_t1'),
|
||||
Integer(10, 60, name='roi_t2'),
|
||||
Integer(10, 40, name='roi_t3'),
|
||||
SKDecimal(0.01, 0.04, decimals=3, name='roi_p1'),
|
||||
SKDecimal(0.01, 0.07, decimals=3, name='roi_p2'),
|
||||
SKDecimal(0.01, 0.20, decimals=3, name='roi_p3'),
|
||||
]
|
||||
|
||||
@staticmethod
|
||||
def stoploss_space() -> List[Dimension]:
|
||||
"""
|
||||
Stoploss Value to search
|
||||
|
||||
Override it if you need some different range for the parameter in the
|
||||
'stoploss' optimization hyperspace.
|
||||
"""
|
||||
return [
|
||||
SKDecimal(-0.35, -0.02, decimals=3, name='stoploss'),
|
||||
]
|
||||
|
||||
@staticmethod
|
||||
def trailing_space() -> List[Dimension]:
|
||||
"""
|
||||
Create a trailing stoploss space.
|
||||
|
||||
You may override it in your custom Hyperopt class.
|
||||
"""
|
||||
return [
|
||||
# It was decided to always set trailing_stop is to True if the 'trailing' hyperspace
|
||||
# is used. Otherwise hyperopt will vary other parameters that won't have effect if
|
||||
# trailing_stop is set False.
|
||||
# This parameter is included into the hyperspace dimensions rather than assigning
|
||||
# it explicitly in the code in order to have it printed in the results along with
|
||||
# other 'trailing' hyperspace parameters.
|
||||
Categorical([True], name='trailing_stop'),
|
||||
|
||||
SKDecimal(0.01, 0.35, decimals=3, name='trailing_stop_positive'),
|
||||
|
||||
# 'trailing_stop_positive_offset' should be greater than 'trailing_stop_positive',
|
||||
# so this intermediate parameter is used as the value of the difference between
|
||||
# them. The value of the 'trailing_stop_positive_offset' is constructed in the
|
||||
# generate_trailing_params() method.
|
||||
# This is similar to the hyperspace dimensions used for constructing the ROI tables.
|
||||
SKDecimal(0.001, 0.1, decimals=3, name='trailing_stop_positive_offset_p1'),
|
||||
|
||||
Categorical([True, False], name='trailing_only_offset_is_reached'),
|
||||
]
|
||||
@ -1,8 +0,0 @@
|
||||
if params.get('mfi-enabled'):
|
||||
conditions.append(dataframe['mfi'] < params['mfi-value'])
|
||||
if params.get('fastd-enabled'):
|
||||
conditions.append(dataframe['fastd'] < params['fastd-value'])
|
||||
if params.get('adx-enabled'):
|
||||
conditions.append(dataframe['adx'] > params['adx-value'])
|
||||
if params.get('rsi-enabled'):
|
||||
conditions.append(dataframe['rsi'] < params['rsi-value'])
|
||||
@ -1,2 +0,0 @@
|
||||
if params.get('rsi-enabled'):
|
||||
conditions.append(dataframe['rsi'] < params['rsi-value'])
|
||||
@ -1,9 +0,0 @@
|
||||
Integer(10, 25, name='mfi-value'),
|
||||
Integer(15, 45, name='fastd-value'),
|
||||
Integer(20, 50, name='adx-value'),
|
||||
Integer(20, 40, name='rsi-value'),
|
||||
Categorical([True, False], name='mfi-enabled'),
|
||||
Categorical([True, False], name='fastd-enabled'),
|
||||
Categorical([True, False], name='adx-enabled'),
|
||||
Categorical([True, False], name='rsi-enabled'),
|
||||
Categorical(['bb_lower', 'macd_cross_signal', 'sar_reversal'], name='trigger')
|
||||
@ -1,3 +0,0 @@
|
||||
Integer(20, 40, name='rsi-value'),
|
||||
Categorical([True, False], name='rsi-enabled'),
|
||||
Categorical(['bb_lower', 'macd_cross_signal', 'sar_reversal'], name='trigger')
|
||||
@ -1,8 +0,0 @@
|
||||
if params.get('sell-mfi-enabled'):
|
||||
conditions.append(dataframe['mfi'] > params['sell-mfi-value'])
|
||||
if params.get('sell-fastd-enabled'):
|
||||
conditions.append(dataframe['fastd'] > params['sell-fastd-value'])
|
||||
if params.get('sell-adx-enabled'):
|
||||
conditions.append(dataframe['adx'] < params['sell-adx-value'])
|
||||
if params.get('sell-rsi-enabled'):
|
||||
conditions.append(dataframe['rsi'] > params['sell-rsi-value'])
|
||||
@ -1,2 +0,0 @@
|
||||
if params.get('sell-rsi-enabled'):
|
||||
conditions.append(dataframe['rsi'] > params['sell-rsi-value'])
|
||||
@ -1,11 +0,0 @@
|
||||
Integer(75, 100, name='sell-mfi-value'),
|
||||
Integer(50, 100, name='sell-fastd-value'),
|
||||
Integer(50, 100, name='sell-adx-value'),
|
||||
Integer(60, 100, name='sell-rsi-value'),
|
||||
Categorical([True, False], name='sell-mfi-enabled'),
|
||||
Categorical([True, False], name='sell-fastd-enabled'),
|
||||
Categorical([True, False], name='sell-adx-enabled'),
|
||||
Categorical([True, False], name='sell-rsi-enabled'),
|
||||
Categorical(['sell-bb_upper',
|
||||
'sell-macd_cross_signal',
|
||||
'sell-sar_reversal'], name='sell-trigger')
|
||||
@ -1,5 +0,0 @@
|
||||
Integer(60, 100, name='sell-rsi-value'),
|
||||
Categorical([True, False], name='sell-rsi-enabled'),
|
||||
Categorical(['sell-bb_upper',
|
||||
'sell-macd_cross_signal',
|
||||
'sell-sar_reversal'], name='sell-trigger')
|
||||
@ -10,10 +10,10 @@ import pytest
|
||||
|
||||
from freqtrade.commands import (start_convert_data, start_create_userdir, start_download_data,
|
||||
start_hyperopt_list, start_hyperopt_show, start_install_ui,
|
||||
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_webserver)
|
||||
start_list_data, start_list_exchanges, start_list_markets,
|
||||
start_list_strategies, start_list_timeframes, start_new_strategy,
|
||||
start_show_trades, 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
|
||||
@ -517,37 +517,6 @@ def test_start_new_strategy_no_arg(mocker, caplog):
|
||||
start_new_strategy(get_args(args))
|
||||
|
||||
|
||||
def test_start_new_hyperopt(mocker, caplog):
|
||||
wt_mock = mocker.patch.object(Path, "write_text", MagicMock())
|
||||
mocker.patch.object(Path, "exists", MagicMock(return_value=False))
|
||||
|
||||
args = [
|
||||
"new-hyperopt",
|
||||
"--hyperopt",
|
||||
"CoolNewhyperopt"
|
||||
]
|
||||
start_new_hyperopt(get_args(args))
|
||||
|
||||
assert wt_mock.call_count == 1
|
||||
assert "CoolNewhyperopt" in wt_mock.call_args_list[0][0][0]
|
||||
assert log_has_re("Writing hyperopt to .*", caplog)
|
||||
|
||||
mocker.patch('freqtrade.commands.deploy_commands.setup_utils_configuration')
|
||||
mocker.patch.object(Path, "exists", MagicMock(return_value=True))
|
||||
with pytest.raises(OperationalException,
|
||||
match=r".* already exists. Please choose another Hyperopt Name\."):
|
||||
start_new_hyperopt(get_args(args))
|
||||
|
||||
|
||||
def test_start_new_hyperopt_no_arg(mocker):
|
||||
args = [
|
||||
"new-hyperopt",
|
||||
]
|
||||
with pytest.raises(OperationalException,
|
||||
match="`new-hyperopt` requires --hyperopt to be set."):
|
||||
start_new_hyperopt(get_args(args))
|
||||
|
||||
|
||||
def test_start_install_ui(mocker):
|
||||
clean_mock = mocker.patch('freqtrade.commands.deploy_commands.clean_ui_subdir')
|
||||
get_url_mock = mocker.patch('freqtrade.commands.deploy_commands.get_ui_download_url',
|
||||
@ -822,37 +791,20 @@ def test_start_list_strategies(mocker, caplog, capsys):
|
||||
assert "legacy_strategy_v1.py" in captured.out
|
||||
assert "StrategyTestV2" in captured.out
|
||||
|
||||
|
||||
def test_start_list_hyperopts(mocker, caplog, capsys):
|
||||
|
||||
# Test color output
|
||||
args = [
|
||||
"list-hyperopts",
|
||||
"--hyperopt-path",
|
||||
str(Path(__file__).parent.parent / "optimize" / "hyperopts"),
|
||||
"-1"
|
||||
"list-strategies",
|
||||
"--strategy-path",
|
||||
str(Path(__file__).parent.parent / "strategy" / "strats"),
|
||||
]
|
||||
pargs = get_args(args)
|
||||
# pargs['config'] = None
|
||||
start_list_hyperopts(pargs)
|
||||
start_list_strategies(pargs)
|
||||
captured = capsys.readouterr()
|
||||
assert "TestHyperoptLegacy" not in captured.out
|
||||
assert "legacy_hyperopt.py" not in captured.out
|
||||
assert "HyperoptTestSepFile" in captured.out
|
||||
assert "test_hyperopt.py" not in captured.out
|
||||
|
||||
# Test regular output
|
||||
args = [
|
||||
"list-hyperopts",
|
||||
"--hyperopt-path",
|
||||
str(Path(__file__).parent.parent / "optimize" / "hyperopts"),
|
||||
]
|
||||
pargs = get_args(args)
|
||||
# pargs['config'] = None
|
||||
start_list_hyperopts(pargs)
|
||||
captured = capsys.readouterr()
|
||||
assert "TestHyperoptLegacy" not in captured.out
|
||||
assert "legacy_hyperopt.py" not in captured.out
|
||||
assert "HyperoptTestSepFile" in captured.out
|
||||
assert "TestStrategyLegacyV1" in captured.out
|
||||
assert "legacy_strategy_v1.py" in captured.out
|
||||
assert "StrategyTestV2" in captured.out
|
||||
assert "LOAD FAILED" in captured.out
|
||||
|
||||
|
||||
def test_start_test_pairlist(mocker, caplog, tickers, default_conf, capsys):
|
||||
|
||||
@ -202,7 +202,7 @@ def test_exchange_resolver(default_conf, mocker, caplog):
|
||||
|
||||
def test_validate_order_time_in_force(default_conf, mocker, caplog):
|
||||
caplog.set_level(logging.INFO)
|
||||
# explicitly test bittrex, exchanges implementing other policies need seperate tests
|
||||
# explicitly test bittrex, exchanges implementing other policies need separate tests
|
||||
ex = get_patched_exchange(mocker, default_conf, id="bittrex")
|
||||
tif = {
|
||||
"buy": "gtc",
|
||||
@ -2481,7 +2481,7 @@ def test_fetch_order(default_conf, mocker, exchange_name, caplog):
|
||||
|
||||
@pytest.mark.parametrize("exchange_name", EXCHANGES)
|
||||
def test_fetch_stoploss_order(default_conf, mocker, exchange_name):
|
||||
# Don't test FTX here - that needs a seperate test
|
||||
# Don't test FTX here - that needs a separate test
|
||||
if exchange_name == 'ftx':
|
||||
return
|
||||
default_conf['dry_run'] = True
|
||||
|
||||
@ -16,7 +16,7 @@ def hyperopt_conf(default_conf):
|
||||
hyperconf.update({
|
||||
'datadir': Path(default_conf['datadir']),
|
||||
'runmode': RunMode.HYPEROPT,
|
||||
'hyperopt': 'HyperoptTestSepFile',
|
||||
'strategy': 'HyperoptableStrategy',
|
||||
'hyperopt_loss': 'ShortTradeDurHyperOptLoss',
|
||||
'hyperopt_path': str(Path(__file__).parent / 'hyperopts'),
|
||||
'epochs': 1,
|
||||
|
||||
@ -1,202 +0,0 @@
|
||||
# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement
|
||||
|
||||
from functools import reduce
|
||||
from typing import Any, Callable, Dict, List
|
||||
|
||||
import talib.abstract as ta
|
||||
from pandas import DataFrame
|
||||
from skopt.space import Categorical, Dimension, Integer
|
||||
|
||||
import freqtrade.vendor.qtpylib.indicators as qtpylib
|
||||
from freqtrade.optimize.hyperopt_interface import IHyperOpt
|
||||
|
||||
|
||||
class HyperoptTestSepFile(IHyperOpt):
|
||||
"""
|
||||
Default hyperopt provided by the Freqtrade bot.
|
||||
You can override it with your own Hyperopt
|
||||
"""
|
||||
@staticmethod
|
||||
def populate_indicators(dataframe: DataFrame, metadata: dict) -> DataFrame:
|
||||
"""
|
||||
Add several indicators needed for buy and sell strategies defined below.
|
||||
"""
|
||||
# ADX
|
||||
dataframe['adx'] = ta.ADX(dataframe)
|
||||
# MACD
|
||||
macd = ta.MACD(dataframe)
|
||||
dataframe['macd'] = macd['macd']
|
||||
dataframe['macdsignal'] = macd['macdsignal']
|
||||
# MFI
|
||||
dataframe['mfi'] = ta.MFI(dataframe)
|
||||
# RSI
|
||||
dataframe['rsi'] = ta.RSI(dataframe)
|
||||
# Stochastic Fast
|
||||
stoch_fast = ta.STOCHF(dataframe)
|
||||
dataframe['fastd'] = stoch_fast['fastd']
|
||||
# Minus-DI
|
||||
dataframe['minus_di'] = ta.MINUS_DI(dataframe)
|
||||
# Bollinger bands
|
||||
bollinger = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=2)
|
||||
dataframe['bb_lowerband'] = bollinger['lower']
|
||||
dataframe['bb_upperband'] = bollinger['upper']
|
||||
# SAR
|
||||
dataframe['sar'] = ta.SAR(dataframe)
|
||||
|
||||
return dataframe
|
||||
|
||||
@staticmethod
|
||||
def buy_strategy_generator(params: Dict[str, Any]) -> Callable:
|
||||
"""
|
||||
Define the buy strategy parameters to be used by Hyperopt.
|
||||
"""
|
||||
def populate_buy_trend(dataframe: DataFrame, metadata: dict) -> DataFrame:
|
||||
"""
|
||||
Buy strategy Hyperopt will build and use.
|
||||
"""
|
||||
conditions = []
|
||||
|
||||
# GUARDS AND TRENDS
|
||||
if 'mfi-enabled' in params and params['mfi-enabled']:
|
||||
conditions.append(dataframe['mfi'] < params['mfi-value'])
|
||||
if 'fastd-enabled' in params and params['fastd-enabled']:
|
||||
conditions.append(dataframe['fastd'] < params['fastd-value'])
|
||||
if 'adx-enabled' in params and params['adx-enabled']:
|
||||
conditions.append(dataframe['adx'] > params['adx-value'])
|
||||
if 'rsi-enabled' in params and params['rsi-enabled']:
|
||||
conditions.append(dataframe['rsi'] < params['rsi-value'])
|
||||
|
||||
# TRIGGERS
|
||||
if 'trigger' in params:
|
||||
if params['trigger'] == 'bb_lower':
|
||||
conditions.append(dataframe['close'] < dataframe['bb_lowerband'])
|
||||
if params['trigger'] == 'macd_cross_signal':
|
||||
conditions.append(qtpylib.crossed_above(
|
||||
dataframe['macd'], dataframe['macdsignal']
|
||||
))
|
||||
if params['trigger'] == 'sar_reversal':
|
||||
conditions.append(qtpylib.crossed_above(
|
||||
dataframe['close'], dataframe['sar']
|
||||
))
|
||||
|
||||
if conditions:
|
||||
dataframe.loc[
|
||||
reduce(lambda x, y: x & y, conditions),
|
||||
'buy'] = 1
|
||||
|
||||
return dataframe
|
||||
|
||||
return populate_buy_trend
|
||||
|
||||
@staticmethod
|
||||
def indicator_space() -> List[Dimension]:
|
||||
"""
|
||||
Define your Hyperopt space for searching buy strategy parameters.
|
||||
"""
|
||||
return [
|
||||
Integer(10, 25, name='mfi-value'),
|
||||
Integer(15, 45, name='fastd-value'),
|
||||
Integer(20, 50, name='adx-value'),
|
||||
Integer(20, 40, name='rsi-value'),
|
||||
Categorical([True, False], name='mfi-enabled'),
|
||||
Categorical([True, False], name='fastd-enabled'),
|
||||
Categorical([True, False], name='adx-enabled'),
|
||||
Categorical([True, False], name='rsi-enabled'),
|
||||
Categorical(['bb_lower', 'macd_cross_signal', 'sar_reversal'], name='trigger')
|
||||
]
|
||||
|
||||
@staticmethod
|
||||
def sell_strategy_generator(params: Dict[str, Any]) -> Callable:
|
||||
"""
|
||||
Define the sell strategy parameters to be used by Hyperopt.
|
||||
"""
|
||||
def populate_sell_trend(dataframe: DataFrame, metadata: dict) -> DataFrame:
|
||||
"""
|
||||
Sell strategy Hyperopt will build and use.
|
||||
"""
|
||||
conditions = []
|
||||
|
||||
# GUARDS AND TRENDS
|
||||
if 'sell-mfi-enabled' in params and params['sell-mfi-enabled']:
|
||||
conditions.append(dataframe['mfi'] > params['sell-mfi-value'])
|
||||
if 'sell-fastd-enabled' in params and params['sell-fastd-enabled']:
|
||||
conditions.append(dataframe['fastd'] > params['sell-fastd-value'])
|
||||
if 'sell-adx-enabled' in params and params['sell-adx-enabled']:
|
||||
conditions.append(dataframe['adx'] < params['sell-adx-value'])
|
||||
if 'sell-rsi-enabled' in params and params['sell-rsi-enabled']:
|
||||
conditions.append(dataframe['rsi'] > params['sell-rsi-value'])
|
||||
|
||||
# TRIGGERS
|
||||
if 'sell-trigger' in params:
|
||||
if params['sell-trigger'] == 'sell-bb_upper':
|
||||
conditions.append(dataframe['close'] > dataframe['bb_upperband'])
|
||||
if params['sell-trigger'] == 'sell-macd_cross_signal':
|
||||
conditions.append(qtpylib.crossed_above(
|
||||
dataframe['macdsignal'], dataframe['macd']
|
||||
))
|
||||
if params['sell-trigger'] == 'sell-sar_reversal':
|
||||
conditions.append(qtpylib.crossed_above(
|
||||
dataframe['sar'], dataframe['close']
|
||||
))
|
||||
|
||||
if conditions:
|
||||
dataframe.loc[
|
||||
reduce(lambda x, y: x & y, conditions),
|
||||
'sell'] = 1
|
||||
|
||||
return dataframe
|
||||
|
||||
return populate_sell_trend
|
||||
|
||||
@staticmethod
|
||||
def sell_indicator_space() -> List[Dimension]:
|
||||
"""
|
||||
Define your Hyperopt space for searching sell strategy parameters.
|
||||
"""
|
||||
return [
|
||||
Integer(75, 100, name='sell-mfi-value'),
|
||||
Integer(50, 100, name='sell-fastd-value'),
|
||||
Integer(50, 100, name='sell-adx-value'),
|
||||
Integer(60, 100, name='sell-rsi-value'),
|
||||
Categorical([True, False], name='sell-mfi-enabled'),
|
||||
Categorical([True, False], name='sell-fastd-enabled'),
|
||||
Categorical([True, False], name='sell-adx-enabled'),
|
||||
Categorical([True, False], name='sell-rsi-enabled'),
|
||||
Categorical(['sell-bb_upper',
|
||||
'sell-macd_cross_signal',
|
||||
'sell-sar_reversal'], name='sell-trigger')
|
||||
]
|
||||
|
||||
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
|
||||
"""
|
||||
Based on TA indicators. Should be a copy of same method from strategy.
|
||||
Must align to populate_indicators in this file.
|
||||
Only used when --spaces does not include buy space.
|
||||
"""
|
||||
dataframe.loc[
|
||||
(
|
||||
(dataframe['close'] < dataframe['bb_lowerband']) &
|
||||
(dataframe['mfi'] < 16) &
|
||||
(dataframe['adx'] > 25) &
|
||||
(dataframe['rsi'] < 21)
|
||||
),
|
||||
'buy'] = 1
|
||||
|
||||
return dataframe
|
||||
|
||||
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
|
||||
"""
|
||||
Based on TA indicators. Should be a copy of same method from strategy.
|
||||
Must align to populate_indicators in this file.
|
||||
Only used when --spaces does not include sell space.
|
||||
"""
|
||||
dataframe.loc[
|
||||
(
|
||||
(qtpylib.crossed_above(
|
||||
dataframe['macdsignal'], dataframe['macd']
|
||||
)) &
|
||||
(dataframe['fastd'] > 54)
|
||||
),
|
||||
'sell'] = 1
|
||||
|
||||
return dataframe
|
||||
@ -17,13 +17,10 @@ from freqtrade.optimize.hyperopt_auto import HyperOptAuto
|
||||
from freqtrade.optimize.hyperopt_tools import HyperoptTools
|
||||
from freqtrade.optimize.optimize_reports import generate_strategy_stats
|
||||
from freqtrade.optimize.space import SKDecimal
|
||||
from freqtrade.resolvers.hyperopt_resolver import HyperOptResolver
|
||||
from freqtrade.strategy.hyper import IntParameter
|
||||
from tests.conftest import (get_args, log_has, log_has_re, patch_exchange,
|
||||
patched_configuration_load_config_file)
|
||||
|
||||
from .hyperopts.hyperopt_test_sep_file import HyperoptTestSepFile
|
||||
|
||||
|
||||
def test_setup_hyperopt_configuration_without_arguments(mocker, default_conf, caplog) -> None:
|
||||
patched_configuration_load_config_file(mocker, default_conf)
|
||||
@ -31,7 +28,7 @@ def test_setup_hyperopt_configuration_without_arguments(mocker, default_conf, ca
|
||||
args = [
|
||||
'hyperopt',
|
||||
'--config', 'config.json',
|
||||
'--hyperopt', 'HyperoptTestSepFile',
|
||||
'--strategy', 'HyperoptableStrategy',
|
||||
]
|
||||
|
||||
config = setup_optimize_configuration(get_args(args), RunMode.HYPEROPT)
|
||||
@ -63,7 +60,7 @@ def test_setup_hyperopt_configuration_with_arguments(mocker, default_conf, caplo
|
||||
args = [
|
||||
'hyperopt',
|
||||
'--config', 'config.json',
|
||||
'--hyperopt', 'HyperoptTestSepFile',
|
||||
'--strategy', 'HyperoptableStrategy',
|
||||
'--datadir', '/foo/bar',
|
||||
'--timeframe', '1m',
|
||||
'--timerange', ':100',
|
||||
@ -115,7 +112,7 @@ def test_setup_hyperopt_configuration_stake_amount(mocker, default_conf) -> None
|
||||
args = [
|
||||
'hyperopt',
|
||||
'--config', 'config.json',
|
||||
'--hyperopt', 'HyperoptTestSepFile',
|
||||
'--strategy', 'HyperoptableStrategy',
|
||||
'--stake-amount', '1',
|
||||
'--starting-balance', '2'
|
||||
]
|
||||
@ -133,47 +130,6 @@ def test_setup_hyperopt_configuration_stake_amount(mocker, default_conf) -> None
|
||||
setup_optimize_configuration(get_args(args), RunMode.HYPEROPT)
|
||||
|
||||
|
||||
def test_hyperoptresolver(mocker, default_conf, caplog) -> None:
|
||||
patched_configuration_load_config_file(mocker, default_conf)
|
||||
|
||||
hyperopt = HyperoptTestSepFile
|
||||
delattr(hyperopt, 'populate_indicators')
|
||||
delattr(hyperopt, 'populate_buy_trend')
|
||||
delattr(hyperopt, 'populate_sell_trend')
|
||||
mocker.patch(
|
||||
'freqtrade.resolvers.hyperopt_resolver.HyperOptResolver.load_object',
|
||||
MagicMock(return_value=hyperopt(default_conf))
|
||||
)
|
||||
default_conf.update({'hyperopt': 'HyperoptTestSepFile'})
|
||||
x = HyperOptResolver.load_hyperopt(default_conf)
|
||||
assert not hasattr(x, 'populate_indicators')
|
||||
assert not hasattr(x, 'populate_buy_trend')
|
||||
assert not hasattr(x, 'populate_sell_trend')
|
||||
assert log_has("Hyperopt class does not provide populate_indicators() method. "
|
||||
"Using populate_indicators from the strategy.", caplog)
|
||||
assert log_has("Hyperopt class does not provide populate_sell_trend() method. "
|
||||
"Using populate_sell_trend from the strategy.", caplog)
|
||||
assert log_has("Hyperopt class does not provide populate_buy_trend() method. "
|
||||
"Using populate_buy_trend from the strategy.", caplog)
|
||||
assert hasattr(x, "ticker_interval") # DEPRECATED
|
||||
assert hasattr(x, "timeframe")
|
||||
|
||||
|
||||
def test_hyperoptresolver_wrongname(default_conf) -> None:
|
||||
default_conf.update({'hyperopt': "NonExistingHyperoptClass"})
|
||||
|
||||
with pytest.raises(OperationalException, match=r'Impossible to load Hyperopt.*'):
|
||||
HyperOptResolver.load_hyperopt(default_conf)
|
||||
|
||||
|
||||
def test_hyperoptresolver_noname(default_conf):
|
||||
default_conf['hyperopt'] = ''
|
||||
with pytest.raises(OperationalException,
|
||||
match="No Hyperopt set. Please use `--hyperopt` to specify "
|
||||
"the Hyperopt class to use."):
|
||||
HyperOptResolver.load_hyperopt(default_conf)
|
||||
|
||||
|
||||
def test_start_not_installed(mocker, default_conf, import_fails) -> None:
|
||||
start_mock = MagicMock()
|
||||
patched_configuration_load_config_file(mocker, default_conf)
|
||||
@ -184,9 +140,7 @@ def test_start_not_installed(mocker, default_conf, import_fails) -> None:
|
||||
args = [
|
||||
'hyperopt',
|
||||
'--config', 'config.json',
|
||||
'--hyperopt', 'HyperoptTestSepFile',
|
||||
'--hyperopt-path',
|
||||
str(Path(__file__).parent / "hyperopts"),
|
||||
'--strategy', 'HyperoptableStrategy',
|
||||
'--epochs', '5',
|
||||
'--hyperopt-loss', 'SharpeHyperOptLossDaily',
|
||||
]
|
||||
@ -196,7 +150,7 @@ def test_start_not_installed(mocker, default_conf, import_fails) -> None:
|
||||
start_hyperopt(pargs)
|
||||
|
||||
|
||||
def test_start(mocker, hyperopt_conf, caplog) -> None:
|
||||
def test_start_no_hyperopt_allowed(mocker, hyperopt_conf, caplog) -> None:
|
||||
start_mock = MagicMock()
|
||||
patched_configuration_load_config_file(mocker, hyperopt_conf)
|
||||
mocker.patch('freqtrade.optimize.hyperopt.Hyperopt.start', start_mock)
|
||||
@ -210,11 +164,9 @@ def test_start(mocker, hyperopt_conf, caplog) -> None:
|
||||
'--epochs', '5'
|
||||
]
|
||||
pargs = get_args(args)
|
||||
with pytest.raises(OperationalException, match=r"Using separate Hyperopt files has been.*"):
|
||||
start_hyperopt(pargs)
|
||||
|
||||
assert log_has('Starting freqtrade in Hyperopt mode', caplog)
|
||||
assert start_mock.call_count == 1
|
||||
|
||||
|
||||
def test_start_no_data(mocker, hyperopt_conf) -> None:
|
||||
patched_configuration_load_config_file(mocker, hyperopt_conf)
|
||||
@ -225,11 +177,11 @@ def test_start_no_data(mocker, hyperopt_conf) -> None:
|
||||
)
|
||||
|
||||
patch_exchange(mocker)
|
||||
|
||||
# TODO: migrate to strategy-based hyperopt
|
||||
args = [
|
||||
'hyperopt',
|
||||
'--config', 'config.json',
|
||||
'--hyperopt', 'HyperoptTestSepFile',
|
||||
'--strategy', 'HyperoptableStrategy',
|
||||
'--hyperopt-loss', 'SharpeHyperOptLossDaily',
|
||||
'--epochs', '5'
|
||||
]
|
||||
@ -247,7 +199,7 @@ def test_start_filelock(mocker, hyperopt_conf, caplog) -> None:
|
||||
args = [
|
||||
'hyperopt',
|
||||
'--config', 'config.json',
|
||||
'--hyperopt', 'HyperoptTestSepFile',
|
||||
'--strategy', 'HyperoptableStrategy',
|
||||
'--hyperopt-loss', 'SharpeHyperOptLossDaily',
|
||||
'--epochs', '5'
|
||||
]
|
||||
@ -427,66 +379,14 @@ def test_hyperopt_format_results(hyperopt):
|
||||
def test_populate_indicators(hyperopt, testdatadir) -> None:
|
||||
data = load_data(testdatadir, '1m', ['UNITTEST/BTC'], fill_up_missing=True)
|
||||
dataframes = hyperopt.backtesting.strategy.advise_all_indicators(data)
|
||||
dataframe = hyperopt.custom_hyperopt.populate_indicators(dataframes['UNITTEST/BTC'],
|
||||
{'pair': 'UNITTEST/BTC'})
|
||||
dataframe = dataframes['UNITTEST/BTC']
|
||||
|
||||
# Check if some indicators are generated. We will not test all of them
|
||||
assert 'adx' in dataframe
|
||||
assert 'mfi' in dataframe
|
||||
assert 'macd' in dataframe
|
||||
assert 'rsi' in dataframe
|
||||
|
||||
|
||||
def test_buy_strategy_generator(hyperopt, testdatadir) -> None:
|
||||
data = load_data(testdatadir, '1m', ['UNITTEST/BTC'], fill_up_missing=True)
|
||||
dataframes = hyperopt.backtesting.strategy.advise_all_indicators(data)
|
||||
dataframe = hyperopt.custom_hyperopt.populate_indicators(dataframes['UNITTEST/BTC'],
|
||||
{'pair': 'UNITTEST/BTC'})
|
||||
|
||||
populate_buy_trend = hyperopt.custom_hyperopt.buy_strategy_generator(
|
||||
{
|
||||
'adx-value': 20,
|
||||
'fastd-value': 20,
|
||||
'mfi-value': 20,
|
||||
'rsi-value': 20,
|
||||
'adx-enabled': True,
|
||||
'fastd-enabled': True,
|
||||
'mfi-enabled': True,
|
||||
'rsi-enabled': True,
|
||||
'trigger': 'bb_lower'
|
||||
}
|
||||
)
|
||||
result = populate_buy_trend(dataframe, {'pair': 'UNITTEST/BTC'})
|
||||
# Check if some indicators are generated. We will not test all of them
|
||||
assert 'buy' in result
|
||||
assert 1 in result['buy']
|
||||
|
||||
|
||||
def test_sell_strategy_generator(hyperopt, testdatadir) -> None:
|
||||
data = load_data(testdatadir, '1m', ['UNITTEST/BTC'], fill_up_missing=True)
|
||||
dataframes = hyperopt.backtesting.strategy.advise_all_indicators(data)
|
||||
dataframe = hyperopt.custom_hyperopt.populate_indicators(dataframes['UNITTEST/BTC'],
|
||||
{'pair': 'UNITTEST/BTC'})
|
||||
|
||||
populate_sell_trend = hyperopt.custom_hyperopt.sell_strategy_generator(
|
||||
{
|
||||
'sell-adx-value': 20,
|
||||
'sell-fastd-value': 75,
|
||||
'sell-mfi-value': 80,
|
||||
'sell-rsi-value': 20,
|
||||
'sell-adx-enabled': True,
|
||||
'sell-fastd-enabled': True,
|
||||
'sell-mfi-enabled': True,
|
||||
'sell-rsi-enabled': True,
|
||||
'sell-trigger': 'sell-bb_upper'
|
||||
}
|
||||
)
|
||||
result = populate_sell_trend(dataframe, {'pair': 'UNITTEST/BTC'})
|
||||
# Check if some indicators are generated. We will not test all of them
|
||||
print(result)
|
||||
assert 'sell' in result
|
||||
assert 1 in result['sell']
|
||||
|
||||
|
||||
def test_generate_optimizer(mocker, hyperopt_conf) -> None:
|
||||
hyperopt_conf.update({'spaces': 'all',
|
||||
'hyperopt_min_trades': 1,
|
||||
@ -527,24 +427,12 @@ def test_generate_optimizer(mocker, hyperopt_conf) -> None:
|
||||
mocker.patch('freqtrade.optimize.hyperopt.load', return_value={'XRP/BTC': None})
|
||||
|
||||
optimizer_param = {
|
||||
'adx-value': 0,
|
||||
'fastd-value': 35,
|
||||
'mfi-value': 0,
|
||||
'rsi-value': 0,
|
||||
'adx-enabled': False,
|
||||
'fastd-enabled': True,
|
||||
'mfi-enabled': False,
|
||||
'rsi-enabled': False,
|
||||
'trigger': 'macd_cross_signal',
|
||||
'sell-adx-value': 0,
|
||||
'sell-fastd-value': 75,
|
||||
'sell-mfi-value': 0,
|
||||
'sell-rsi-value': 0,
|
||||
'sell-adx-enabled': False,
|
||||
'sell-fastd-enabled': True,
|
||||
'sell-mfi-enabled': False,
|
||||
'sell-rsi-enabled': False,
|
||||
'sell-trigger': 'macd_cross_signal',
|
||||
'buy_plusdi': 0.02,
|
||||
'buy_rsi': 35,
|
||||
'sell_minusdi': 0.02,
|
||||
'sell_rsi': 75,
|
||||
'protection_cooldown_lookback': 20,
|
||||
'protection_enabled': True,
|
||||
'roi_t1': 60.0,
|
||||
'roi_t2': 30.0,
|
||||
'roi_t3': 20.0,
|
||||
@ -564,29 +452,19 @@ def test_generate_optimizer(mocker, hyperopt_conf) -> None:
|
||||
'0.00003100 BTC ( 0.00%). '
|
||||
'Avg duration 0:50:00 min.'
|
||||
),
|
||||
'params_details': {'buy': {'adx-enabled': False,
|
||||
'adx-value': 0,
|
||||
'fastd-enabled': True,
|
||||
'fastd-value': 35,
|
||||
'mfi-enabled': False,
|
||||
'mfi-value': 0,
|
||||
'rsi-enabled': False,
|
||||
'rsi-value': 0,
|
||||
'trigger': 'macd_cross_signal'},
|
||||
'params_details': {'buy': {'buy_plusdi': 0.02,
|
||||
'buy_rsi': 35,
|
||||
},
|
||||
'roi': {"0": 0.12000000000000001,
|
||||
"20.0": 0.02,
|
||||
"50.0": 0.01,
|
||||
"110.0": 0},
|
||||
'protection': {},
|
||||
'sell': {'sell-adx-enabled': False,
|
||||
'sell-adx-value': 0,
|
||||
'sell-fastd-enabled': True,
|
||||
'sell-fastd-value': 75,
|
||||
'sell-mfi-enabled': False,
|
||||
'sell-mfi-value': 0,
|
||||
'sell-rsi-enabled': False,
|
||||
'sell-rsi-value': 0,
|
||||
'sell-trigger': 'macd_cross_signal'},
|
||||
'protection': {'protection_cooldown_lookback': 20,
|
||||
'protection_enabled': True,
|
||||
},
|
||||
'sell': {'sell_minusdi': 0.02,
|
||||
'sell_rsi': 75,
|
||||
},
|
||||
'stoploss': {'stoploss': -0.4},
|
||||
'trailing': {'trailing_only_offset_is_reached': False,
|
||||
'trailing_stop': True,
|
||||
@ -808,11 +686,6 @@ def test_simplified_interface_roi_stoploss(mocker, hyperopt_conf, capsys) -> Non
|
||||
hyperopt.backtesting.strategy.advise_all_indicators = MagicMock()
|
||||
hyperopt.custom_hyperopt.generate_roi_table = MagicMock(return_value={})
|
||||
|
||||
del hyperopt.custom_hyperopt.__class__.buy_strategy_generator
|
||||
del hyperopt.custom_hyperopt.__class__.sell_strategy_generator
|
||||
del hyperopt.custom_hyperopt.__class__.indicator_space
|
||||
del hyperopt.custom_hyperopt.__class__.sell_indicator_space
|
||||
|
||||
hyperopt.start()
|
||||
|
||||
parallel.assert_called_once()
|
||||
@ -843,16 +716,14 @@ def test_simplified_interface_all_failed(mocker, hyperopt_conf) -> None:
|
||||
|
||||
hyperopt_conf.update({'spaces': 'all', })
|
||||
|
||||
mocker.patch('freqtrade.optimize.hyperopt_auto.HyperOptAuto._generate_indicator_space',
|
||||
return_value=[])
|
||||
|
||||
hyperopt = Hyperopt(hyperopt_conf)
|
||||
hyperopt.backtesting.strategy.advise_all_indicators = MagicMock()
|
||||
hyperopt.custom_hyperopt.generate_roi_table = MagicMock(return_value={})
|
||||
|
||||
del hyperopt.custom_hyperopt.__class__.buy_strategy_generator
|
||||
del hyperopt.custom_hyperopt.__class__.sell_strategy_generator
|
||||
del hyperopt.custom_hyperopt.__class__.indicator_space
|
||||
del hyperopt.custom_hyperopt.__class__.sell_indicator_space
|
||||
|
||||
with pytest.raises(OperationalException, match=r"The 'buy' space is included into *"):
|
||||
with pytest.raises(OperationalException, match=r"The 'protection' space is included into *"):
|
||||
hyperopt.start()
|
||||
|
||||
|
||||
@ -889,11 +760,6 @@ def test_simplified_interface_buy(mocker, hyperopt_conf, capsys) -> None:
|
||||
hyperopt.backtesting.strategy.advise_all_indicators = MagicMock()
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||||
hyperopt.custom_hyperopt.generate_roi_table = MagicMock(return_value={})
|
||||
|
||||
# TODO: sell_strategy_generator() is actually not called because
|
||||
# run_optimizer_parallel() is mocked
|
||||
del hyperopt.custom_hyperopt.__class__.sell_strategy_generator
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del hyperopt.custom_hyperopt.__class__.sell_indicator_space
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||||
|
||||
hyperopt.start()
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||||
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parallel.assert_called_once()
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||||
@ -943,11 +809,6 @@ def test_simplified_interface_sell(mocker, hyperopt_conf, capsys) -> None:
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hyperopt.backtesting.strategy.advise_all_indicators = MagicMock()
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||||
hyperopt.custom_hyperopt.generate_roi_table = MagicMock(return_value={})
|
||||
|
||||
# TODO: buy_strategy_generator() is actually not called because
|
||||
# run_optimizer_parallel() is mocked
|
||||
del hyperopt.custom_hyperopt.__class__.buy_strategy_generator
|
||||
del hyperopt.custom_hyperopt.__class__.indicator_space
|
||||
|
||||
hyperopt.start()
|
||||
|
||||
parallel.assert_called_once()
|
||||
@ -964,13 +825,12 @@ def test_simplified_interface_sell(mocker, hyperopt_conf, capsys) -> None:
|
||||
assert hasattr(hyperopt, "position_stacking")
|
||||
|
||||
|
||||
@pytest.mark.parametrize("method,space", [
|
||||
('buy_strategy_generator', 'buy'),
|
||||
('indicator_space', 'buy'),
|
||||
('sell_strategy_generator', 'sell'),
|
||||
('sell_indicator_space', 'sell'),
|
||||
@pytest.mark.parametrize("space", [
|
||||
('buy'),
|
||||
('sell'),
|
||||
('protection'),
|
||||
])
|
||||
def test_simplified_interface_failed(mocker, hyperopt_conf, method, space) -> None:
|
||||
def test_simplified_interface_failed(mocker, hyperopt_conf, space) -> None:
|
||||
mocker.patch('freqtrade.optimize.hyperopt.dump', MagicMock())
|
||||
mocker.patch('freqtrade.optimize.hyperopt.file_dump_json')
|
||||
mocker.patch('freqtrade.optimize.backtesting.Backtesting.load_bt_data',
|
||||
@ -979,6 +839,8 @@ def test_simplified_interface_failed(mocker, hyperopt_conf, method, space) -> No
|
||||
'freqtrade.optimize.hyperopt.get_timerange',
|
||||
MagicMock(return_value=(datetime(2017, 12, 10), datetime(2017, 12, 13)))
|
||||
)
|
||||
mocker.patch('freqtrade.optimize.hyperopt_auto.HyperOptAuto._generate_indicator_space',
|
||||
return_value=[])
|
||||
|
||||
patch_exchange(mocker)
|
||||
|
||||
@ -988,8 +850,6 @@ def test_simplified_interface_failed(mocker, hyperopt_conf, method, space) -> No
|
||||
hyperopt.backtesting.strategy.advise_all_indicators = MagicMock()
|
||||
hyperopt.custom_hyperopt.generate_roi_table = MagicMock(return_value={})
|
||||
|
||||
delattr(hyperopt.custom_hyperopt.__class__, method)
|
||||
|
||||
with pytest.raises(OperationalException, match=f"The '{space}' space is included into *"):
|
||||
hyperopt.start()
|
||||
|
||||
@ -999,7 +859,6 @@ def test_in_strategy_auto_hyperopt(mocker, hyperopt_conf, tmpdir, fee) -> None:
|
||||
mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
|
||||
(Path(tmpdir) / 'hyperopt_results').mkdir(parents=True)
|
||||
# No hyperopt needed
|
||||
del hyperopt_conf['hyperopt']
|
||||
hyperopt_conf.update({
|
||||
'strategy': 'HyperoptableStrategy',
|
||||
'user_data_dir': Path(tmpdir),
|
||||
|
||||
@ -68,7 +68,7 @@ def test_PairLocks(use_db):
|
||||
# Global lock
|
||||
PairLocks.lock_pair('*', lock_time)
|
||||
assert PairLocks.is_global_lock(lock_time + timedelta(minutes=-50))
|
||||
# Global lock also locks every pair seperately
|
||||
# Global lock also locks every pair separately
|
||||
assert PairLocks.is_pair_locked(pair, lock_time + timedelta(minutes=-50))
|
||||
assert PairLocks.is_pair_locked('XRP/USDT', lock_time + timedelta(minutes=-50))
|
||||
|
||||
|
||||
@ -74,16 +74,12 @@ def test_copy_sample_files(mocker, default_conf, caplog) -> None:
|
||||
copymock = mocker.patch('shutil.copy', MagicMock())
|
||||
|
||||
copy_sample_files(Path('/tmp/bar'))
|
||||
assert copymock.call_count == 5
|
||||
assert copymock.call_count == 3
|
||||
assert copymock.call_args_list[0][0][1] == str(
|
||||
Path('/tmp/bar') / 'strategies/sample_strategy.py')
|
||||
assert copymock.call_args_list[1][0][1] == str(
|
||||
Path('/tmp/bar') / 'hyperopts/sample_hyperopt_advanced.py')
|
||||
assert copymock.call_args_list[2][0][1] == str(
|
||||
Path('/tmp/bar') / 'hyperopts/sample_hyperopt_loss.py')
|
||||
assert copymock.call_args_list[3][0][1] == str(
|
||||
Path('/tmp/bar') / 'hyperopts/sample_hyperopt.py')
|
||||
assert copymock.call_args_list[4][0][1] == str(
|
||||
assert copymock.call_args_list[2][0][1] == str(
|
||||
Path('/tmp/bar') / 'notebooks/strategy_analysis_example.ipynb')
|
||||
|
||||
|
||||
|
||||
Loading…
Reference in New Issue
Block a user