lychiyu/freqtrade_origin
1
0
Fork 0
mirror of https://github.com/freqtrade/freqtrade.git synced 2024-11-10 10:21:59 +00:00
Code Issues Actions 2 Packages Projects Releases Wiki Activity

Merge branch 'feat/short' into pr/samgermain/5378

Browse Source
This commit is contained in:
Matthias 2021-09-17 19:24:47 +02:00
commit 4d558879e9
99 changed files with 1075 additions and 2863 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

6
.github/PULL_REQUEST_TEMPLATE.md vendored
View File

@ -2,14 +2,16 @@ Thank you for sending your pull request. But first, have you included
unit tests, and is your code PEP8 conformant? [More details](https://github.com/freqtrade/freqtrade/blob/develop/CONTRIBUTING.md)
## Summary
Explain in one sentence the goal of this PR
Solve the issue: #___
## Quick changelog
- <change log #1>
- <change log #2>
- <change log 1>
- <change log 1>
## What's new?
*Explain in details what this PR solve or improve. You can include visuals.*

6
.github/workflows/ci.yml vendored
View File

@ -87,7 +87,7 @@ jobs:
run: |
cp config_examples/config_bittrex.example.json config.json
freqtrade create-userdir --userdir user_data
freqtrade hyperopt --datadir tests/testdata -e 5 --strategy SampleStrategy --hyperopt SampleHyperOpt --hyperopt-loss SharpeHyperOptLossDaily --print-all
freqtrade hyperopt --datadir tests/testdata -e 5 --strategy SampleStrategy --hyperopt-loss SharpeHyperOptLossDaily --print-all
- name: Flake8
run: |
@ -180,7 +180,7 @@ jobs:
run: |
cp config_examples/config_bittrex.example.json config.json
freqtrade create-userdir --userdir user_data
freqtrade hyperopt --datadir tests/testdata -e 5 --strategy SampleStrategy --hyperopt SampleHyperOpt --hyperopt-loss SharpeHyperOptLossDaily --print-all
freqtrade hyperopt --datadir tests/testdata -e 5 --strategy SampleStrategy --hyperopt-loss SharpeHyperOptLossDaily --print-all
- name: Flake8
run: |
@ -247,7 +247,7 @@ jobs:
run: |
cp config_examples/config_bittrex.example.json config.json
freqtrade create-userdir --userdir user_data
freqtrade hyperopt --datadir tests/testdata -e 5 --strategy SampleStrategy --hyperopt SampleHyperOpt --hyperopt-loss SharpeHyperOptLossDaily --print-all
freqtrade hyperopt --datadir tests/testdata -e 5 --strategy SampleStrategy --hyperopt-loss SharpeHyperOptLossDaily --print-all
- name: Flake8
run: |

2
.travis.yml
View File

@ -33,7 +33,7 @@ jobs:
- script:
- cp config_examples/config_bittrex.example.json config.json
- freqtrade create-userdir --userdir user_data
- freqtrade hyperopt --datadir tests/testdata -e 5 --strategy SampleStrategy --hyperopt SampleHyperOpt --hyperopt-loss SharpeHyperOptLossDaily
- freqtrade hyperopt --datadir tests/testdata -e 5 --strategy SampleStrategy --hyperopt-loss SharpeHyperOptLossDaily
name: hyperopt
- script: flake8
name: flake8

2
Dockerfile
View File

@ -13,7 +13,7 @@ RUN mkdir /freqtrade \
&& apt-get update \
&& apt-get -y install sudo libatlas3-base curl sqlite3 libhdf5-serial-dev \
&& apt-get clean \
&& useradd -u 1000 -G sudo -U -m ftuser \
&& useradd -u 1000 -G sudo -U -m -s /bin/bash ftuser \
&& chown ftuser:ftuser /freqtrade \
# Allow sudoers
&& echo "ftuser ALL=(ALL) NOPASSWD: /bin/chown" >> /etc/sudoers

9
README.md
View File

@ -30,6 +30,7 @@ Please read the [exchange specific notes](docs/exchanges.md) to learn about even
- [X] [Bittrex](https://bittrex.com/)
- [X] [Kraken](https://kraken.com/)
- [X] [FTX](https://ftx.com)
- [X] [Gate.io](https://www.gate.io/ref/6266643)
- [ ] [potentially many others](https://github.com/ccxt/ccxt/). _(We cannot guarantee they will work)_
### Community tested
@ -78,22 +79,22 @@ For any other type of installation please refer to [Installation doc](https://ww
```
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.
@ -107,8 +108,10 @@ 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

9
build_helpers/install_ta-lib.sh
View File

@ -12,9 +12,12 @@ if [ ! -f "${INSTALL_LOC}/lib/libta_lib.a" ]; then
&& curl 'http://git.savannah.gnu.org/gitweb/?p=config.git;a=blob_plain;f=config.sub;hb=HEAD' -o config.sub \
&& ./configure --prefix=${INSTALL_LOC}/ \
&& make -j$(nproc) \
&& which sudo && sudo make install || make install \
&& cd ..
&& which sudo && sudo make install || make install
if [ -x "$(command -v apt-get)" ]; then
echo "Updating library path using ldconfig"
sudo ldconfig
fi
cd .. && rm -rf ./ta-lib/
else
echo "TA-lib already installed, skipping installation"
fi
# && sed -i.bak "s|0.00000001|0.000000000000000001 |g" src/ta_func/ta_utility.h \

332
docs/advanced-hyperopt.md
View File

@ -67,10 +67,10 @@ Currently, the arguments are:
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.
!!! Note
This function is called once per iteration - so please make sure to have this as optimized as possible to not slow hyperopt down unnecessarily.
This function is called once per epoch - so please make sure to have this as optimized as possible to not slow hyperopt down unnecessarily.
!!! Note
Please keep the arguments `*args` and `**kwargs` in the interface to allow us to extend this interface later.
!!! Note "`*args` and `**kwargs`"
Please keep the arguments `*args` and `**kwargs` in the interface to allow us to extend this interface in the future.
## Overriding pre-defined spaces
@ -80,10 +80,56 @@ To override a pre-defined space (`roi_space`, `generate_roi_table`, `stoploss_sp
class MyAwesomeStrategy(IStrategy):
class HyperOpt:
# Define a custom stoploss space.
def stoploss_space(self):
def stoploss_space():
return [SKDecimal(-0.05, -0.01, decimals=3, name='stoploss')]
# Define custom ROI space
def roi_space() -> List[Dimension]:
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'),
]
```
!!! Note
All overrides are optional and can be mixed/matched as necessary.
### Overriding Base estimator
You can define your own estimator for Hyperopt by implementing `generate_estimator()` in the Hyperopt subclass.
```python
class MyAwesomeStrategy(IStrategy):
class HyperOpt:
def generate_estimator():
return "RF"
```
Possible values are either one of "GP", "RF", "ET", "GBRT" (Details can be found in the [scikit-optimize documentation](https://scikit-optimize.github.io/)), or "an instance of a class that inherits from `RegressorMixin` (from sklearn) and where the `predict` method has an optional `return_std` argument, which returns `std(Y | x)` along with `E[Y | x]`".
Some research will be necessary to find additional Regressors.
Example for `ExtraTreesRegressor` ("ET") with additional parameters:
```python
class MyAwesomeStrategy(IStrategy):
class HyperOpt:
def generate_estimator():
from skopt.learning import ExtraTreesRegressor
# Corresponds to "ET" - but allows additional parameters.
return ExtraTreesRegressor(n_estimators=100)
```
!!! Note
While custom estimators can be provided, it's up to you as User to do research on possible parameters and analyze / understand which ones should be used.
If you're unsure about this, best use one of the Defaults (`"ET"` has proven to be the most versatile) without further parameters.
## Space options
For the additional spaces, scikit-optimize (in combination with Freqtrade) provides the following space types:
@ -105,281 +151,3 @@ from freqtrade.optimize.space import Categorical, Dimension, Integer, SKDecimal,
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]`).
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]`).
---
## Legacy Hyperopt
This Section explains the configuration of an explicit Hyperopt file (separate to the strategy).
!!! Warning "Deprecated / legacy mode"
Since the 2021.4 release you no longer have to write a separate hyperopt class, but all strategies can be hyperopted.
Please read the [main hyperopt page](hyperopt.md) for more details.
### Prepare hyperopt file
Configuring an explicit hyperopt file is similar to writing your own strategy, and many tasks will be similar.
!!! Tip "About this page"
For this page, we will be using a fictional strategy called `AwesomeStrategy` - which will be optimized using the `AwesomeHyperopt` class.
#### Create a Custom Hyperopt File
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`.
Let assume you want a hyperopt file `AwesomeHyperopt.py`:
``` bash
freqtrade new-hyperopt --hyperopt AwesomeHyperopt
```
#### Legacy Hyperopt checklist
Checklist on all tasks / possibilities in hyperopt
Depending on the space you want to optimize, only some of the below are required:
* fill `buy_strategy_generator` - for buy signal optimization
* fill `indicator_space` - for buy signal optimization
* fill `sell_strategy_generator` - for sell signal optimization
* fill `sell_indicator_space` - for sell signal optimization
!!! Note
`populate_indicators` needs to create all indicators any of thee spaces may use, otherwise hyperopt will not work.
Optional in hyperopt - can also be loaded from a strategy (recommended):
* `populate_indicators` - fallback to create indicators
* `populate_buy_trend` - fallback if not optimizing for buy space. should come from strategy
* `populate_sell_trend` - fallback if not optimizing for sell space. should come from strategy
!!! Note
You always have to provide a strategy to Hyperopt, even if your custom Hyperopt class contains all methods.
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.
Rarely you may also need to override:
* `roi_space` - for custom ROI optimization (if you need the ranges for the ROI parameters in the optimization hyperspace that differ from default)
* `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)
* `stoploss_space` - for custom stoploss optimization (if you need the range for the stoploss parameter in the optimization hyperspace that differs from default)
* `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)
#### Defining a buy signal optimization
Let's say you are curious: should you use MACD crossings or lower Bollinger
Bands to trigger your buys. And you also wonder should you use RSI or ADX to
help with those buy decisions. If you decide to use RSI or ADX, which values
should I use for them? So let's use hyperparameter optimization to solve this
mystery.
We will start by defining a search space:
```python
def indicator_space() -> List[Dimension]:
"""
Define your Hyperopt space for searching strategy parameters
"""
return [
Integer(20, 40, name='adx-value'),
Integer(20, 40, name='rsi-value'),
Categorical([True, False], name='adx-enabled'),
Categorical([True, False], name='rsi-enabled'),
Categorical(['bb_lower', 'macd_cross_signal'], name='trigger')
]
```
Above definition says: I have five parameters I want you to randomly combine
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.
Then we have three category variables. First two are either `True` or `False`.
We use these to either enable or disable the ADX and RSI guards.
The last one we call `trigger` and use it to decide which buy trigger we want to use.
So let's write the buy strategy generator using these values:
```python
@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:
conditions = []
# GUARDS AND TRENDS
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']
))
# 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
```
Hyperopt will now call `populate_buy_trend()` many times (`epochs`) with different value combinations.
It will use the given historical data and make buys based on the buy signals generated with the above function.
Based on the results, hyperopt will tell you which parameter combination produced the best results (based on the configured [loss function](#loss-functions)).
!!! Note
The above setup expects to find ADX, RSI and Bollinger Bands in the populated indicators.
When you want to test an indicator that isn't used by the bot currently, remember to
add it to the `populate_indicators()` method in your strategy or hyperopt file.
#### Sell optimization
Similar to the buy-signal above, sell-signals can also be optimized.
Place the corresponding settings into the following methods
* Inside `sell_indicator_space()` - the parameters hyperopt shall be optimizing.
* Within `sell_strategy_generator()` - populate the nested method `populate_sell_trend()` to apply the parameters.
The configuration and rules are the same than for buy signals.
To avoid naming collisions in the search-space, please prefix all sell-spaces with `sell-`.
### Execute Hyperopt
Once you have updated your hyperopt configuration you can run it.
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.
We strongly recommend to use `screen` or `tmux` to prevent any connection loss.
```bash
freqtrade hyperopt --config config.json --hyperopt <hyperoptname> --hyperopt-loss <hyperoptlossname> --strategy <strategyname> -e 500 --spaces all
```
Use `<hyperoptname>` as the name of the custom hyperopt used.
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.
Doing multiple runs (executions) with a few 1000 epochs and different random state will most likely produce different results.
The `--spaces all` option determines that all possible parameters should be optimized. Possibilities are listed below.
!!! Note
Hyperopt will store hyperopt results with the timestamp of the hyperopt start time.
Reading commands (`hyperopt-list`, `hyperopt-show`) can use `--hyperopt-filename <filename>` to read and display older hyperopt results.
You can find a list of filenames with `ls -l user_data/hyperopt_results/`.
#### Running Hyperopt using methods from a strategy
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.
```bash
freqtrade hyperopt --hyperopt AwesomeHyperopt --hyperopt-loss SharpeHyperOptLossDaily --strategy AwesomeStrategy
```
### Understand the Hyperopt Result
Once Hyperopt is completed you can use the result to create a new strategy.
Given the following result from hyperopt:
```
Best result:
44/100: 135 trades. Avg profit 0.57%. Total profit 0.03871918 BTC (0.7722%). Avg duration 180.4 mins. Objective: 1.94367
Buy hyperspace params:
{ 'adx-value': 44,
'rsi-value': 29,
'adx-enabled': False,
'rsi-enabled': True,
'trigger': 'bb_lower'}
```
You should understand this result like:
* The buy trigger that worked best was `bb_lower`.
* You should not use ADX because `adx-enabled: False`)
* You should **consider** using the RSI indicator (`rsi-enabled: True` and the best value is `29.0` (`rsi-value: 29.0`)
You have to look inside your strategy file into `buy_strategy_generator()`
method, what those values match to.
So for example you had `rsi-value: 29.0` so we would look at `rsi`-block, that translates to the following code block:
```python
(dataframe['rsi'] < 29.0)
```
Translating your whole hyperopt result as the new buy-signal would then look like:
```python
def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
dataframe.loc[
(
(dataframe['rsi'] < 29.0) & # rsi-value
dataframe['close'] < dataframe['bb_lowerband'] # trigger
),
'buy'] = 1
return dataframe
```
### Validate backtesting results
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.
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.
Should results not match, please double-check to make sure you transferred all conditions correctly.
Pay special care to the stoploss (and trailing stoploss) parameters, as these are often set in configuration files, which override changes to the strategy.
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`).
### Sharing methods with your strategy
Hyperopt classes provide access to the Strategy via the `strategy` class attribute.
This can be a great way to reduce code duplication if used correctly, but will also complicate usage for inexperienced users.
``` python
from pandas import DataFrame
from freqtrade.strategy.interface import IStrategy
import freqtrade.vendor.qtpylib.indicators as qtpylib
class MyAwesomeStrategy(IStrategy):
buy_params = {
'rsi-value': 30,
'adx-value': 35,
}
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
return self.buy_strategy_generator(self.buy_params, dataframe, metadata)
@staticmethod
def buy_strategy_generator(params, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
qtpylib.crossed_above(dataframe['rsi'], params['rsi-value']) &
dataframe['adx'] > params['adx-value']) &
dataframe['volume'] > 0
)
, 'buy'] = 1
return dataframe
class MyAwesomeHyperOpt(IHyperOpt):
...
@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:
# Call strategy's buy strategy generator
return self.StrategyClass.buy_strategy_generator(params, dataframe, metadata)
return populate_buy_trend
```

8
docs/bot-usage.md
View File

@ -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

4
docs/configuration.md
View File

@ -444,8 +444,8 @@ The possible values are: `gtc` (default), `fok` or `ioc`.
```
!!! Warning
This is ongoing work. For now, it is supported only for binance.
Please don't change the default value unless you know what you are doing and have researched the impact of using different values.
This is ongoing work. For now, it is supported only for binance and kucoin.
Please don't change the default value unless you know what you are doing and have researched the impact of using different values for your particular exchange.
### Exchange configuration

5
docs/deprecated.md
View File

@ -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.

2
docs/edge.md
View File

@ -3,7 +3,7 @@
The `Edge Positioning` module uses probability to calculate your win rate and risk reward ratio. It will use these statistics to control your strategy trade entry points, position size and, stoploss.
!!! Warning
WHen using `Edge positioning` with a dynamic whitelist (VolumePairList), make sure to also use `AgeFilter` and set it to at least `calculate_since_number_of_days` to avoid problems with missing data.
When using `Edge positioning` with a dynamic whitelist (VolumePairList), make sure to also use `AgeFilter` and set it to at least `calculate_since_number_of_days` to avoid problems with missing data.
!!! Note
`Edge Positioning` only considers *its own* buy/sell/stoploss signals. It ignores the stoploss, trailing stoploss, and ROI settings in the strategy configuration file.

14
docs/exchanges.md
View File

@ -4,6 +4,8 @@ This page combines common gotchas and informations which are exchange-specific a
## Binance
Binance supports [time_in_force](configuration.md#understand-order_time_in_force).
!!! Tip "Stoploss on Exchange"
Binance supports `stoploss_on_exchange` and uses stop-loss-limit orders. It provides great advantages, so we recommend to benefit from it.
@ -56,6 +58,12 @@ Bittrex does not support market orders. If you have a message at the bot startup
Bittrex also does not support `VolumePairlist` due to limited / split API constellation at the moment.
Please use `StaticPairlist`. Other pairlists (other than `VolumePairlist`) should not be affected.
### Volume pairlist
Bittrex does not support the direct usage of VolumePairList. This can however be worked around by using the advanced mode with `lookback_days: 1` (or more), which will emulate 24h volume.
Read more in the [pairlist documentation](plugins.md#volumepairlist-advanced-mode).
### Restricted markets
Bittrex split its exchange into US and International versions.
@ -113,8 +121,12 @@ Kucoin requires a passphrase for each api key, you will therefore need to add th
"key": "your_exchange_key",
"secret": "your_exchange_secret",
"password": "your_exchange_api_key_password",
// ...
}
```
Kucoin supports [time_in_force](configuration.md#understand-order_time_in_force).
### Kucoin Blacklists
For Kucoin, please add `"KCS/<STAKE>"` to your blacklist to avoid issues.
@ -158,6 +170,8 @@ For example, to test the order type `FOK` with Kraken, and modify candle limit t
"order_time_in_force": ["gtc", "fok"],
"ohlcv_candle_limit": 200
}
//...
}
```
!!! Warning

2
docs/faq.md
View File

@ -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?

23
docs/hyperopt.md
View File

@ -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
@ -680,11 +677,11 @@ If you are optimizing ROI, Freqtrade creates the 'roi' optimization hyperspace f
These ranges should be sufficient in most cases. The minutes in the steps (ROI dict keys) are scaled linearly depending on the timeframe used. The ROI values in the steps (ROI dict values) are scaled logarithmically depending on the timeframe used.
If you have the `generate_roi_table()` and `roi_space()` methods in your custom hyperopt file, remove them in order to utilize these adaptive ROI tables and the ROI hyperoptimization space generated by Freqtrade by default.
If you have the `generate_roi_table()` and `roi_space()` methods in your custom hyperopt, remove them in order to utilize these adaptive ROI tables and the ROI hyperoptimization space generated by Freqtrade by default.
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

20
docs/includes/pairlists.md
View File

@ -82,6 +82,8 @@ Filtering instances (not the first position in the list) will not apply any cach
You can define a minimum volume with `min_value` - which will filter out pairs with a volume lower than the specified value in the specified timerange.
### VolumePairList Advanced mode
`VolumePairList` can also operate in an advanced mode to build volume over a given timerange of specified candle size. It utilizes exchange historical candle data, builds a typical price (calculated by (open+high+low)/3) and multiplies the typical price with every candle's volume. The sum is the `quoteVolume` over the given range. This allows different scenarios, for a more smoothened volume, when using longer ranges with larger candle sizes, or the opposite when using a short range with small candles.
For convenience `lookback_days` can be specified, which will imply that 1d candles will be used for the lookback. In the example below the pairlist would be created based on the last 7 days:
@ -105,6 +107,24 @@ For convenience `lookback_days` can be specified, which will imply that 1d candl
!!! Warning "Performance implications when using lookback range"
If used in first position in combination with lookback, the computation of the range based volume can be time and resource consuming, as it downloads candles for all tradable pairs. Hence it's highly advised to use the standard approach with `VolumeFilter` to narrow the pairlist down for further range volume calculation.
??? Tip "Unsupported exchanges (Bittrex, Gemini)"
On some exchanges (like Bittrex and Gemini), regular VolumePairList does not work as the api does not natively provide 24h volume. This can be worked around by using candle data to build the volume.
To roughly simulate 24h volume, you can use the following configuration.
Please note that These pairlists will only refresh once per day.
```json
"pairlists": [
{
"method": "VolumePairList",
"number_assets": 20,
"sort_key": "quoteVolume",
"min_value": 0,
"refresh_period": 86400,
"lookback_days": 1
}
],
```
More sophisticated approach can be used, by using `lookback_timeframe` for candle size and `lookback_period` which specifies the amount of candles. This example will build the volume pairs based on a rolling period of 3 days of 1h candles:
```json

1
docs/index.md
View File

@ -40,6 +40,7 @@ Please read the [exchange specific notes](exchanges.md) to learn about eventual,
- [X] [Bittrex](https://bittrex.com/)
- [X] [FTX](https://ftx.com)
- [X] [Kraken](https://kraken.com/)
- [X] [Gate.io](https://www.gate.io/ref/6266643)
- [ ] [potentially many others through <img alt="ccxt" width="30px" src="assets/ccxt-logo.svg" />](https://github.com/ccxt/ccxt/). _(We cannot guarantee they will work)_
### Community tested

2
docs/requirements-docs.txt
View File

@ -1,4 +1,4 @@
mkdocs==1.2.2
mkdocs-material==7.2.5
mkdocs-material==7.2.6
mdx_truly_sane_lists==1.2
pymdown-extensions==8.2

83
docs/utils.md
View File

@ -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.

2
freqtrade/__init__.py
View File

@ -22,7 +22,7 @@ if __version__ == 'develop':
# subprocess.check_output(
# ['git', 'log', '--format="%h"', '-n 1'],
# stderr=subprocess.DEVNULL).decode("utf-8").rstrip().strip('"')
except Exception:
except Exception: # pragma: no cover
# git not available, ignore
try:
# Try Fallback to freqtrade_commit file (created by CI while building docker image)

8
freqtrade/commands/__init__.py
View File

@ -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

32
freqtrade/commands/arguments.py
View File

@ -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',

12
freqtrade/commands/build_config_commands.py
View File

@ -61,13 +61,13 @@ def ask_user_config() -> Dict[str, Any]:
"type": "text",
"name": "stake_currency",
"message": "Please insert your stake currency:",
"default": 'BTC',
"default": 'USDT',
},
{
"type": "text",
"name": "stake_amount",
"message": f"Please insert your stake amount (Number or '{UNLIMITED_STAKE_AMOUNT}'):",
"default": "0.01",
"default": "100",
"validate": lambda val: val == UNLIMITED_STAKE_AMOUNT or validate_is_float(val),
"filter": lambda val: '"' + UNLIMITED_STAKE_AMOUNT + '"'
if val == UNLIMITED_STAKE_AMOUNT
@ -105,6 +105,8 @@ def ask_user_config() -> Dict[str, Any]:
"bittrex",
"kraken",
"ftx",
"kucoin",
"gateio",
Separator(),
"other",
],
@ -128,6 +130,12 @@ def ask_user_config() -> Dict[str, Any]:
"message": "Insert Exchange Secret",
"when": lambda x: not x['dry_run']
},
{
"type": "password",
"name": "exchange_key_password",
"message": "Insert Exchange API Key password",
"when": lambda x: not x['dry_run'] and x['exchange_name'] == 'kucoin'
},
{
"type": "confirm",
"name": "telegram",

6
freqtrade/commands/cli_options.py
View File

@ -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(

52
freqtrade/commands/deploy_commands.py
View File

@ -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.")

1
freqtrade/commands/hyperopt_commands.py
View File

@ -102,3 +102,4 @@ def start_hyperopt_show(args: Dict[str, Any]) -> None:
HyperoptTools.show_epoch_details(val, total_epochs, print_json, no_header,
header_str="Epoch details")
# TODO-lev: Hyperopt optimal leverage

22
freqtrade/commands/list_commands.py
View File

@ -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
@ -148,6 +129,7 @@ def start_list_markets(args: Dict[str, Any], pairs_only: bool = False) -> None:
quote_currencies = args.get('quote_currencies', [])
try:
# TODO-lev: Add leverage amount to get markets that support a certain leverage
pairs = exchange.get_markets(base_currencies=base_currencies,
quote_currencies=quote_currencies,
pairs_only=pairs_only,

19
freqtrade/configuration/PeriodicCache.py Normal file
View File

@ -0,0 +1,19 @@
from datetime import datetime, timezone
from cachetools.ttl import TTLCache
class PeriodicCache(TTLCache):
"""
Special cache that expires at "straight" times
A timer with ttl of 3600 (1h) will expire at every full hour (:00).
"""
def __init__(self, maxsize, ttl, getsizeof=None):
def local_timer():
ts = datetime.now(timezone.utc).timestamp()
offset = (ts % ttl)
return ts - offset
# Init with smlight offset
super().__init__(maxsize=maxsize, ttl=ttl-1e-5, timer=local_timer, getsizeof=getsizeof)

3
freqtrade/configuration/__init__.py
View File

@ -1,7 +1,8 @@
# flake8: noqa: F401
from freqtrade.configuration.check_exchange import check_exchange, remove_credentials
from freqtrade.configuration.check_exchange import check_exchange
from freqtrade.configuration.config_setup import setup_utils_configuration
from freqtrade.configuration.config_validation import validate_config_consistency
from freqtrade.configuration.configuration import Configuration
from freqtrade.configuration.PeriodicCache import PeriodicCache
from freqtrade.configuration.timerange import TimeRange

13
freqtrade/configuration/check_exchange.py
View File

@ -10,19 +10,6 @@ from freqtrade.exchange import (available_exchanges, is_exchange_known_ccxt,
logger = logging.getLogger(__name__)
def remove_credentials(config: Dict[str, Any]) -> None:
"""
Removes exchange keys from the configuration and specifies dry-run
Used for backtesting / hyperopt / edge and utils.
Modifies the input dict!
"""
config['exchange']['key'] = ''
config['exchange']['secret'] = ''
config['exchange']['password'] = ''
config['exchange']['uid'] = ''
config['dry_run'] = True
def check_exchange(config: Dict[str, Any], check_for_bad: bool = True) -> bool:
"""
Check if the exchange name in the config file is supported by Freqtrade

5
freqtrade/configuration/config_setup.py
View File

@ -3,7 +3,6 @@ from typing import Any, Dict
from freqtrade.enums import RunMode
from .check_exchange import remove_credentials
from .config_validation import validate_config_consistency
from .configuration import Configuration
@ -21,8 +20,8 @@ def setup_utils_configuration(args: Dict[str, Any], method: RunMode) -> Dict[str
configuration = Configuration(args, method)
config = configuration.get_config()
# Ensure we do not use Exchange credentials
remove_credentials(config)
# Ensure these modes are using Dry-run
config['dry_run'] = True
validate_config_consistency(config)
return config

2
freqtrade/constants.py
View File

@ -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,
}

3
freqtrade/data/history/history_utils.py
View File

@ -197,7 +197,8 @@ def _download_pair_history(pair: str, *,
timeframe=timeframe,
since_ms=since_ms if since_ms else
arrow.utcnow().shift(
days=-new_pairs_days).int_timestamp * 1000
days=-new_pairs_days).int_timestamp * 1000,
is_new_pair=data.empty
)
# TODO: Maybe move parsing to exchange class (?)
new_dataframe = ohlcv_to_dataframe(new_data, timeframe, pair,

2
freqtrade/enums/signaltype.py
View File

@ -3,7 +3,7 @@ from enum import Enum
class SignalType(Enum):
"""
Enum to distinguish between buy and sell signals
Enum to distinguish between enter and exit signals
"""
ENTER_LONG = "enter_long"
EXIT_LONG = "exit_long"

2
freqtrade/exchange/__init__.py
View File

@ -1,6 +1,6 @@
# flake8: noqa: F401
# isort: off
from freqtrade.exchange.common import MAP_EXCHANGE_CHILDCLASS
from freqtrade.exchange.common import remove_credentials, MAP_EXCHANGE_CHILDCLASS
from freqtrade.exchange.exchange import Exchange
# isort: on
from freqtrade.exchange.bibox import Bibox

21
freqtrade/exchange/binance.py
View File

@ -1,7 +1,8 @@
""" Binance exchange subclass """
import logging
from typing import Dict
from typing import Dict, List
import arrow
import ccxt
from freqtrade.exceptions import (DDosProtection, InsufficientFundsError, InvalidOrderException,
@ -18,6 +19,7 @@ class Binance(Exchange):
_ft_has: Dict = {
"stoploss_on_exchange": True,
"order_time_in_force": ['gtc', 'fok', 'ioc'],
"time_in_force_parameter": "timeInForce",
"ohlcv_candle_limit": 1000,
"trades_pagination": "id",
"trades_pagination_arg": "fromId",
@ -89,3 +91,20 @@ class Binance(Exchange):
f'Could not place sell order due to {e.__class__.__name__}. Message: {e}') from e
except ccxt.BaseError as e:
raise OperationalException(e) from e
async def _async_get_historic_ohlcv(self, pair: str, timeframe: str,
since_ms: int, is_new_pair: bool
) -> List:
"""
Overwrite to introduce "fast new pair" functionality by detecting the pair's listing date
Does not work for other exchanges, which don't return the earliest data when called with "0"
"""
if is_new_pair:
x = await self._async_get_candle_history(pair, timeframe, 0)
if x and x[2] and x[2][0] and x[2][0][0] > since_ms:
# Set starting date to first available candle.
since_ms = x[2][0][0]
logger.info(f"Candle-data for {pair} available starting with "
f"{arrow.get(since_ms // 1000).isoformat()}.")
return await super()._async_get_historic_ohlcv(
pair=pair, timeframe=timeframe, since_ms=since_ms, is_new_pair=is_new_pair)

13
freqtrade/exchange/common.py
View File

@ -51,6 +51,19 @@ EXCHANGE_HAS_OPTIONAL = [
]
def remove_credentials(config) -> None:
"""
Removes exchange keys from the configuration and specifies dry-run
Used for backtesting / hyperopt / edge and utils.
Modifies the input dict!
"""
if config.get('dry_run', False):
config['exchange']['key'] = ''
config['exchange']['secret'] = ''
config['exchange']['password'] = ''
config['exchange']['uid'] = ''
def calculate_backoff(retrycount, max_retries):
"""
Calculate backoff

56
freqtrade/exchange/exchange.py
View File

@ -26,9 +26,9 @@ from freqtrade.exceptions import (DDosProtection, ExchangeError, InsufficientFun
InvalidOrderException, OperationalException, PricingError,
RetryableOrderError, TemporaryError)
from freqtrade.exchange.common import (API_FETCH_ORDER_RETRY_COUNT, BAD_EXCHANGES,
EXCHANGE_HAS_OPTIONAL, EXCHANGE_HAS_REQUIRED, retrier,
retrier_async)
from freqtrade.misc import deep_merge_dicts, safe_value_fallback2
EXCHANGE_HAS_OPTIONAL, EXCHANGE_HAS_REQUIRED,
remove_credentials, retrier, retrier_async)
from freqtrade.misc import chunks, deep_merge_dicts, safe_value_fallback2
from freqtrade.plugins.pairlist.pairlist_helpers import expand_pairlist
@ -54,12 +54,16 @@ class Exchange:
# Parameters to add directly to buy/sell calls (like agreeing to trading agreement)
_params: Dict = {}
# Additional headers - added to the ccxt object
_headers: Dict = {}
# Dict to specify which options each exchange implements
# This defines defaults, which can be selectively overridden by subclasses using _ft_has
# or by specifying them in the configuration.
_ft_has_default: Dict = {
"stoploss_on_exchange": False,
"order_time_in_force": ["gtc"],
"time_in_force_parameter": "timeInForce",
"ohlcv_params": {},
"ohlcv_candle_limit": 500,
"ohlcv_partial_candle": True,
@ -100,6 +104,7 @@ class Exchange:
# Holds all open sell orders for dry_run
self._dry_run_open_orders: Dict[str, Any] = {}
remove_credentials(config)
if config['dry_run']:
logger.info('Instance is running with dry_run enabled')
@ -169,7 +174,7 @@ class Exchange:
asyncio.get_event_loop().run_until_complete(self._api_async.close())
def _init_ccxt(self, exchange_config: Dict[str, Any], ccxt_module: CcxtModuleType = ccxt,
ccxt_kwargs: dict = None) -> ccxt.Exchange:
ccxt_kwargs: Dict = {}) -> ccxt.Exchange:
"""
Initialize ccxt with given config and return valid
ccxt instance.
@ -188,6 +193,10 @@ class Exchange:
}
if ccxt_kwargs:
logger.info('Applying additional ccxt config: %s', ccxt_kwargs)
if self._headers:
# Inject static headers after the above output to not confuse users.
ccxt_kwargs = deep_merge_dicts({'headers': self._headers}, ccxt_kwargs)
if ccxt_kwargs:
ex_config.update(ccxt_kwargs)
try:
@ -716,7 +725,8 @@ class Exchange:
params = self._params.copy()
if time_in_force != 'gtc' and ordertype != 'market':
params.update({'timeInForce': time_in_force})
param = self._ft_has.get('time_in_force_parameter', '')
params.update({param: time_in_force})
try:
# Set the precision for amount and price(rate) as accepted by the exchange
@ -1185,7 +1195,7 @@ class Exchange:
# Historic data
def get_historic_ohlcv(self, pair: str, timeframe: str,
since_ms: int) -> List:
since_ms: int, is_new_pair: bool = False) -> List:
"""
Get candle history using asyncio and returns the list of candles.
Handles all async work for this.
@ -1197,7 +1207,7 @@ class Exchange:
"""
return asyncio.get_event_loop().run_until_complete(
self._async_get_historic_ohlcv(pair=pair, timeframe=timeframe,
since_ms=since_ms))
since_ms=since_ms, is_new_pair=is_new_pair))
def get_historic_ohlcv_as_df(self, pair: str, timeframe: str,
since_ms: int) -> DataFrame:
@ -1212,11 +1222,12 @@ class Exchange:
return ohlcv_to_dataframe(ticks, timeframe, pair=pair, fill_missing=True,
drop_incomplete=self._ohlcv_partial_candle)
async def _async_get_historic_ohlcv(self, pair: str,
timeframe: str,
since_ms: int) -> List:
async def _async_get_historic_ohlcv(self, pair: str, timeframe: str,
since_ms: int, is_new_pair: bool
) -> List:
"""
Download historic ohlcv
:param is_new_pair: used by binance subclass to allow "fast" new pair downloading
"""
one_call = timeframe_to_msecs(timeframe) * self.ohlcv_candle_limit(timeframe)
@ -1229,21 +1240,22 @@ class Exchange:
pair, timeframe, since) for since in
range(since_ms, arrow.utcnow().int_timestamp * 1000, one_call)]
results = await asyncio.gather(*input_coroutines, return_exceptions=True)
# Combine gathered results
data: List = []
for res in results:
if isinstance(res, Exception):
logger.warning("Async code raised an exception: %s", res.__class__.__name__)
continue
# Deconstruct tuple if it's not an exception
p, _, new_data = res
if p == pair:
data.extend(new_data)
# Chunk requests into batches of 100 to avoid overwelming ccxt Throttling
for input_coro in chunks(input_coroutines, 100):
results = await asyncio.gather(*input_coro, return_exceptions=True)
for res in results:
if isinstance(res, Exception):
logger.warning("Async code raised an exception: %s", res.__class__.__name__)
continue
# Deconstruct tuple if it's not an exception
p, _, new_data = res
if p == pair:
data.extend(new_data)
# Sort data again after extending the result - above calls return in "async order"
data = sorted(data, key=lambda x: x[0])
logger.info("Downloaded data for %s with length %s.", pair, len(data))
logger.info(f"Downloaded data for {pair} with length {len(data)}.")
return data
def refresh_latest_ohlcv(self, pair_list: ListPairsWithTimeframes, *,

2
freqtrade/exchange/gateio.py
View File

@ -21,3 +21,5 @@ class Gateio(Exchange):
_ft_has: Dict = {
"ohlcv_candle_limit": 1000,
}
_headers = {'X-Gate-Channel-Id': 'freqtrade'}

2
freqtrade/exchange/kucoin.py
View File

@ -21,4 +21,6 @@ class Kucoin(Exchange):
_ft_has: Dict = {
"l2_limit_range": [20, 100],
"l2_limit_range_required": False,
"order_time_in_force": ['gtc', 'fok', 'ioc'],
"time_in_force_parameter": "timeInForce",
}

165
freqtrade/freqtradebot.py
View File

@ -66,6 +66,7 @@ class FreqtradeBot(LoggingMixin):
init_db(self.config.get('db_url', None), clean_open_orders=self.config['dry_run'])
# TODO-lev: Do anything with this?
self.wallets = Wallets(self.config, self.exchange)
PairLocks.timeframe = self.config['timeframe']
@ -77,6 +78,7 @@ class FreqtradeBot(LoggingMixin):
# so anything in the Freqtradebot instance should be ready (initialized), including
# the initial state of the bot.
# Keep this at the end of this initialization method.
# TODO-lev: Do I need to consider the rpc, pairlists or dataprovider?
self.rpc: RPCManager = RPCManager(self)
self.pairlists = PairListManager(self.exchange, self.config)
@ -99,7 +101,7 @@ class FreqtradeBot(LoggingMixin):
self.state = State[initial_state.upper()] if initial_state else State.STOPPED
# Protect sell-logic from forcesell and vice versa
self._sell_lock = Lock()
self._exit_lock = Lock()
LoggingMixin.__init__(self, logger, timeframe_to_seconds(self.strategy.timeframe))
def notify_status(self, msg: str) -> None:
@ -166,14 +168,14 @@ class FreqtradeBot(LoggingMixin):
self.strategy.analyze(self.active_pair_whitelist)
with self._sell_lock:
with self._exit_lock:
# Check and handle any timed out open orders
self.check_handle_timedout()
# Protect from collisions with forcesell.
# Protect from collisions with forceexit.
# Without this, freqtrade my try to recreate stoploss_on_exchange orders
# while selling is in process, since telegram messages arrive in an different thread.
with self._sell_lock:
with self._exit_lock:
trades = Trade.get_open_trades()
# First process current opened trades (positions)
self.exit_positions(trades)
@ -289,16 +291,16 @@ class FreqtradeBot(LoggingMixin):
def handle_insufficient_funds(self, trade: Trade):
"""
Determine if we ever opened a sell order for this trade.
If not, try update buy fees - otherwise "refind" the open order we obviously lost.
Determine if we ever opened a exiting order for this trade.
If not, try update entering fees - otherwise "refind" the open order we obviously lost.
"""
sell_order = trade.select_order('sell', None)
if sell_order:
self.refind_lost_order(trade)
else:
self.reupdate_buy_order_fees(trade)
self.reupdate_enter_order_fees(trade)
def reupdate_buy_order_fees(self, trade: Trade):
def reupdate_enter_order_fees(self, trade: Trade):
"""
Get buy order from database, and try to reupdate.
Handles trades where the initial fee-update did not work.
@ -312,7 +314,7 @@ class FreqtradeBot(LoggingMixin):
def refind_lost_order(self, trade):
"""
Try refinding a lost trade.
Only used when InsufficientFunds appears on sell orders (stoploss or sell).
Only used when InsufficientFunds appears on exit orders (stoploss or long sell/short buy).
Tries to walk the stored orders and sell them off eventually.
"""
logger.info(f"Trying to refind lost order for {trade}")
@ -323,7 +325,7 @@ class FreqtradeBot(LoggingMixin):
logger.debug(f"Order {order} is no longer open.")
continue
if order.ft_order_side == 'buy':
# Skip buy side - this is handled by reupdate_buy_order_fees
# Skip buy side - this is handled by reupdate_enter_order_fees
continue
try:
fo = self.exchange.fetch_order_or_stoploss_order(order.order_id, order.ft_pair,
@ -350,7 +352,7 @@ class FreqtradeBot(LoggingMixin):
def enter_positions(self) -> int:
"""
Tries to execute buy orders for new trades (positions)
Tries to execute entry orders for new trades (positions)
"""
trades_created = 0
@ -366,7 +368,7 @@ class FreqtradeBot(LoggingMixin):
if not whitelist:
logger.info("No currency pair in active pair whitelist, "
"but checking to sell open trades.")
"but checking to exit open trades.")
return trades_created
if PairLocks.is_global_lock():
lock = PairLocks.get_pair_longest_lock('*')
@ -385,7 +387,7 @@ class FreqtradeBot(LoggingMixin):
logger.warning('Unable to create trade for %s: %s', pair, exception)
if not trades_created:
logger.debug("Found no buy signals for whitelisted currencies. Trying again...")
logger.debug("Found no enter signals for whitelisted currencies. Trying again...")
return trades_created
@ -477,21 +479,21 @@ class FreqtradeBot(LoggingMixin):
time_in_force = self.strategy.order_time_in_force['buy']
if price:
buy_limit_requested = price
enter_limit_requested = price
else:
# Calculate price
proposed_buy_rate = self.exchange.get_rate(pair, refresh=True, side="buy")
proposed_enter_rate = self.exchange.get_rate(pair, refresh=True, side="buy")
custom_entry_price = strategy_safe_wrapper(self.strategy.custom_entry_price,
default_retval=proposed_buy_rate)(
default_retval=proposed_enter_rate)(
pair=pair, current_time=datetime.now(timezone.utc),
proposed_rate=proposed_buy_rate)
proposed_rate=proposed_enter_rate)
buy_limit_requested = self.get_valid_price(custom_entry_price, proposed_buy_rate)
enter_limit_requested = self.get_valid_price(custom_entry_price, proposed_enter_rate)
if not buy_limit_requested:
if not enter_limit_requested:
raise PricingError('Could not determine buy price.')
min_stake_amount = self.exchange.get_min_pair_stake_amount(pair, buy_limit_requested,
min_stake_amount = self.exchange.get_min_pair_stake_amount(pair, enter_limit_requested,
self.strategy.stoploss)
if not self.edge:
@ -499,7 +501,7 @@ class FreqtradeBot(LoggingMixin):
stake_amount = strategy_safe_wrapper(self.strategy.custom_stake_amount,
default_retval=stake_amount)(
pair=pair, current_time=datetime.now(timezone.utc),
current_rate=buy_limit_requested, proposed_stake=stake_amount,
current_rate=enter_limit_requested, proposed_stake=stake_amount,
min_stake=min_stake_amount, max_stake=max_stake_amount)
stake_amount = self.wallets._validate_stake_amount(pair, stake_amount, min_stake_amount)
@ -509,27 +511,29 @@ class FreqtradeBot(LoggingMixin):
logger.info(f"Buy signal found: about create a new trade for {pair} with stake_amount: "
f"{stake_amount} ...")
amount = stake_amount / buy_limit_requested
amount = stake_amount / enter_limit_requested
order_type = self.strategy.order_types['buy']
if forcebuy:
# Forcebuy can define a different ordertype
# TODO-lev: get a forceshort? What is this
order_type = self.strategy.order_types.get('forcebuy', order_type)
# TODO-lev: Will this work for shorting?
if not strategy_safe_wrapper(self.strategy.confirm_trade_entry, default_retval=True)(
pair=pair, order_type=order_type, amount=amount, rate=buy_limit_requested,
pair=pair, order_type=order_type, amount=amount, rate=enter_limit_requested,
time_in_force=time_in_force, current_time=datetime.now(timezone.utc)):
logger.info(f"User requested abortion of buying {pair}")
return False
amount = self.exchange.amount_to_precision(pair, amount)
order = self.exchange.create_order(pair=pair, ordertype=order_type, side="buy",
amount=amount, rate=buy_limit_requested,
amount=amount, rate=enter_limit_requested,
time_in_force=time_in_force)
order_obj = Order.parse_from_ccxt_object(order, pair, 'buy')
order_id = order['id']
order_status = order.get('status', None)
# we assume the order is executed at the price requested
buy_limit_filled_price = buy_limit_requested
enter_limit_filled_price = enter_limit_requested
amount_requested = amount
if order_status == 'expired' or order_status == 'rejected':
@ -552,13 +556,13 @@ class FreqtradeBot(LoggingMixin):
)
stake_amount = order['cost']
amount = safe_value_fallback(order, 'filled', 'amount')
buy_limit_filled_price = safe_value_fallback(order, 'average', 'price')
enter_limit_filled_price = safe_value_fallback(order, 'average', 'price')
# in case of FOK the order may be filled immediately and fully
elif order_status == 'closed':
stake_amount = order['cost']
amount = safe_value_fallback(order, 'filled', 'amount')
buy_limit_filled_price = safe_value_fallback(order, 'average', 'price')
enter_limit_filled_price = safe_value_fallback(order, 'average', 'price')
# Fee is applied twice because we make a LIMIT_BUY and LIMIT_SELL
fee = self.exchange.get_fee(symbol=pair, taker_or_maker='maker')
@ -570,8 +574,8 @@ class FreqtradeBot(LoggingMixin):
amount_requested=amount_requested,
fee_open=fee,
fee_close=fee,
open_rate=buy_limit_filled_price,
open_rate_requested=buy_limit_requested,
open_rate=enter_limit_filled_price,
open_rate_requested=enter_limit_requested,
open_date=datetime.utcnow(),
exchange=self.exchange.id,
open_order_id=order_id,
@ -592,13 +596,13 @@ class FreqtradeBot(LoggingMixin):
# Updating wallets
self.wallets.update()
self._notify_buy(trade, order_type)
self._notify_enter(trade, order_type)
return True
def _notify_buy(self, trade: Trade, order_type: str) -> None:
def _notify_enter(self, trade: Trade, order_type: str) -> None:
"""
Sends rpc notification when a buy occurred.
Sends rpc notification when a entry order occurred.
"""
msg = {
'trade_id': trade.id,
@ -619,9 +623,9 @@ class FreqtradeBot(LoggingMixin):
# Send the message
self.rpc.send_msg(msg)
def _notify_buy_cancel(self, trade: Trade, order_type: str, reason: str) -> None:
def _notify_enter_cancel(self, trade: Trade, order_type: str, reason: str) -> None:
"""
Sends rpc notification when a buy cancel occurred.
Sends rpc notification when a entry order cancel occurred.
"""
current_rate = self.exchange.get_rate(trade.pair, refresh=False, side="buy")
@ -645,7 +649,7 @@ class FreqtradeBot(LoggingMixin):
# Send the message
self.rpc.send_msg(msg)
def _notify_buy_fill(self, trade: Trade) -> None:
def _notify_enter_fill(self, trade: Trade) -> None:
msg = {
'trade_id': trade.id,
'type': RPCMessageType.BUY_FILL,
@ -667,7 +671,7 @@ class FreqtradeBot(LoggingMixin):
def exit_positions(self, trades: List[Any]) -> int:
"""
Tries to execute sell orders for open trades (positions)
Tries to execute exit orders for open trades (positions)
"""
trades_closed = 0
for trade in trades:
@ -683,7 +687,7 @@ class FreqtradeBot(LoggingMixin):
trades_closed += 1
except DependencyException as exception:
logger.warning('Unable to sell trade %s: %s', trade.pair, exception)
logger.warning('Unable to exit trade %s: %s', trade.pair, exception)
# Updating wallets if any trade occurred
if trades_closed:
@ -693,8 +697,8 @@ class FreqtradeBot(LoggingMixin):
def handle_trade(self, trade: Trade) -> bool:
"""
Sells the current pair if the threshold is reached and updates the trade record.
:return: True if trade has been sold, False otherwise
Sells/exits_short the current pair if the threshold is reached and updates the trade record.
:return: True if trade has been sold/exited_short, False otherwise
"""
if not trade.is_open:
raise DependencyException(f'Attempt to handle closed trade: {trade}')
@ -703,6 +707,7 @@ class FreqtradeBot(LoggingMixin):
(enter, exit_) = (False, False)
# TODO-lev: change to use_exit_signal, ignore_roi_if_enter_signal
if (self.config.get('use_sell_signal', True) or
self.config.get('ignore_roi_if_buy_signal', False)):
analyzed_df, _ = self.dataprovider.get_analyzed_dataframe(trade.pair,
@ -715,8 +720,8 @@ class FreqtradeBot(LoggingMixin):
)
# TODO-lev: side should depend on trade side.
sell_rate = self.exchange.get_rate(trade.pair, refresh=True, side="sell")
if self._check_and_execute_exit(trade, sell_rate, enter, exit_):
exit_rate = self.exchange.get_rate(trade.pair, refresh=True, side="sell")
if self._check_and_execute_exit(trade, exit_rate, enter, exit_):
return True
logger.debug('Found no sell signal for %s.', trade)
@ -746,7 +751,7 @@ class FreqtradeBot(LoggingMixin):
except InvalidOrderException as e:
trade.stoploss_order_id = None
logger.error(f'Unable to place a stoploss order on exchange. {e}')
logger.warning('Selling the trade forcefully')
logger.warning('Exiting the trade forcefully')
self.execute_trade_exit(trade, trade.stop_loss, sell_reason=SellCheckTuple(
sell_type=SellType.EMERGENCY_SELL))
@ -760,6 +765,8 @@ class FreqtradeBot(LoggingMixin):
Check if trade is fulfilled in which case the stoploss
on exchange should be added immediately if stoploss on exchange
is enabled.
# TODO-lev: liquidation price will always be on exchange, even though
# TODO-lev: stoploss_on_exchange might not be enabled
"""
logger.debug('Handling stoploss on exchange %s ...', trade)
@ -778,13 +785,14 @@ class FreqtradeBot(LoggingMixin):
# We check if stoploss order is fulfilled
if stoploss_order and stoploss_order['status'] in ('closed', 'triggered'):
# TODO-lev: Update to exit reason
trade.sell_reason = SellType.STOPLOSS_ON_EXCHANGE.value
self.update_trade_state(trade, trade.stoploss_order_id, stoploss_order,
stoploss_order=True)
# Lock pair for one candle to prevent immediate rebuys
self.strategy.lock_pair(trade.pair, datetime.now(timezone.utc),
reason='Auto lock')
self._notify_sell(trade, "stoploss")
self._notify_exit(trade, "stoploss")
return True
if trade.open_order_id or not trade.is_open:
@ -793,7 +801,7 @@ class FreqtradeBot(LoggingMixin):
# The trade can be closed already (sell-order fill confirmation came in this iteration)
return False
# If buy order is fulfilled but there is no stoploss, we add a stoploss on exchange
# If enter order is fulfilled but there is no stoploss, we add a stoploss on exchange
if not stoploss_order:
stoploss = self.edge.stoploss(pair=trade.pair) if self.edge else self.strategy.stoploss
stop_price = trade.open_rate * (1 + stoploss)
@ -853,19 +861,19 @@ class FreqtradeBot(LoggingMixin):
logger.warning(f"Could not create trailing stoploss order "
f"for pair {trade.pair}.")
def _check_and_execute_exit(self, trade: Trade, sell_rate: float,
def _check_and_execute_exit(self, trade: Trade, exit_rate: float,
enter: bool, exit_: bool) -> bool:
"""
Check and execute trade exit
"""
should_exit: SellCheckTuple = self.strategy.should_exit(
trade, sell_rate, datetime.now(timezone.utc), enter=enter, exit_=exit_,
trade, exit_rate, datetime.now(timezone.utc), enter=enter, exit_=exit_,
force_stoploss=self.edge.stoploss(trade.pair) if self.edge else 0
)
if should_exit.sell_flag:
logger.info(f'Exit for {trade.pair} detected. Reason: {should_exit.sell_type}')
self.execute_trade_exit(trade, sell_rate, should_exit)
self.execute_trade_exit(trade, exit_rate, should_exit)
return True
return False
@ -908,7 +916,7 @@ class FreqtradeBot(LoggingMixin):
default_retval=False)(pair=trade.pair,
trade=trade,
order=order))):
self.handle_cancel_buy(trade, order, constants.CANCEL_REASON['TIMEOUT'])
self.handle_cancel_enter(trade, order, constants.CANCEL_REASON['TIMEOUT'])
elif (order['side'] == 'sell' and (order['status'] == 'open' or fully_cancelled) and (
fully_cancelled
@ -917,7 +925,7 @@ class FreqtradeBot(LoggingMixin):
default_retval=False)(pair=trade.pair,
trade=trade,
order=order))):
self.handle_cancel_sell(trade, order, constants.CANCEL_REASON['TIMEOUT'])
self.handle_cancel_exit(trade, order, constants.CANCEL_REASON['TIMEOUT'])
def cancel_all_open_orders(self) -> None:
"""
@ -933,17 +941,18 @@ class FreqtradeBot(LoggingMixin):
continue
if order['side'] == 'buy':
self.handle_cancel_buy(trade, order, constants.CANCEL_REASON['ALL_CANCELLED'])
self.handle_cancel_enter(trade, order, constants.CANCEL_REASON['ALL_CANCELLED'])
elif order['side'] == 'sell':
self.handle_cancel_sell(trade, order, constants.CANCEL_REASON['ALL_CANCELLED'])
self.handle_cancel_exit(trade, order, constants.CANCEL_REASON['ALL_CANCELLED'])
Trade.commit()
def handle_cancel_buy(self, trade: Trade, order: Dict, reason: str) -> bool:
def handle_cancel_enter(self, trade: Trade, order: Dict, reason: str) -> bool:
"""
Buy cancel - cancel order
:return: True if order was fully cancelled
"""
# TODO-lev: Pay back borrowed/interest and transfer back on leveraged trades
was_trade_fully_canceled = False
# Cancelled orders may have the status of 'canceled' or 'closed'
@ -988,6 +997,8 @@ class FreqtradeBot(LoggingMixin):
# to the order dict acquired before cancelling.
# we need to fall back to the values from order if corder does not contain these keys.
trade.amount = filled_amount
# TODO-lev: Check edge cases, we don't want to make leverage > 1.0 if we don't have to
trade.stake_amount = trade.amount * trade.open_rate
self.update_trade_state(trade, trade.open_order_id, corder)
@ -996,13 +1007,13 @@ class FreqtradeBot(LoggingMixin):
reason += f", {constants.CANCEL_REASON['PARTIALLY_FILLED']}"
self.wallets.update()
self._notify_buy_cancel(trade, order_type=self.strategy.order_types['buy'],
reason=reason)
self._notify_enter_cancel(trade, order_type=self.strategy.order_types['buy'],
reason=reason)
return was_trade_fully_canceled
def handle_cancel_sell(self, trade: Trade, order: Dict, reason: str) -> str:
def handle_cancel_exit(self, trade: Trade, order: Dict, reason: str) -> str:
"""
Sell cancel - cancel order and update trade
exit order cancel - cancel order and update trade
:return: Reason for cancel
"""
# if trade is not partially completed, just cancel the order
@ -1034,14 +1045,14 @@ class FreqtradeBot(LoggingMixin):
reason = constants.CANCEL_REASON['PARTIALLY_FILLED_KEEP_OPEN']
self.wallets.update()
self._notify_sell_cancel(
self._notify_exit_cancel(
trade,
order_type=self.strategy.order_types['sell'],
reason=reason
)
return reason
def _safe_sell_amount(self, pair: str, amount: float) -> float:
def _safe_exit_amount(self, pair: str, amount: float) -> float:
"""
Get sellable amount.
Should be trade.amount - but will fall back to the available amount if necessary.
@ -1052,6 +1063,7 @@ class FreqtradeBot(LoggingMixin):
:return: amount to sell
:raise: DependencyException: if available balance is not within 2% of the available amount.
"""
# TODO-lev Maybe update?
# Update wallets to ensure amounts tied up in a stoploss is now free!
self.wallets.update()
trade_base_currency = self.exchange.get_pair_base_currency(pair)
@ -1064,7 +1076,7 @@ class FreqtradeBot(LoggingMixin):
return wallet_amount
else:
raise DependencyException(
f"Not enough amount to sell. Trade-amount: {amount}, Wallet: {wallet_amount}")
f"Not enough amount to exit trade. Trade-amount: {amount}, Wallet: {wallet_amount}")
def execute_trade_exit(self, trade: Trade, limit: float, sell_reason: SellCheckTuple) -> bool:
"""
@ -1074,7 +1086,7 @@ class FreqtradeBot(LoggingMixin):
:param sell_reason: Reason the sell was triggered
:return: True if it succeeds (supported) False (not supported)
"""
sell_type = 'sell'
sell_type = 'sell' # TODO-lev: Update to exit
if sell_reason.sell_type in (SellType.STOP_LOSS, SellType.TRAILING_STOP_LOSS):
sell_type = 'stoploss'
@ -1113,23 +1125,26 @@ class FreqtradeBot(LoggingMixin):
# but we allow this value to be changed)
order_type = self.strategy.order_types.get("forcesell", order_type)
amount = self._safe_sell_amount(trade.pair, trade.amount)
amount = self._safe_exit_amount(trade.pair, trade.amount)
time_in_force = self.strategy.order_time_in_force['sell']
if not strategy_safe_wrapper(self.strategy.confirm_trade_exit, default_retval=True)(
pair=trade.pair, trade=trade, order_type=order_type, amount=amount, rate=limit,
time_in_force=time_in_force, sell_reason=sell_reason.sell_reason,
current_time=datetime.now(timezone.utc)):
logger.info(f"User requested abortion of selling {trade.pair}")
current_time=datetime.now(timezone.utc)): # TODO-lev: Update to exit
logger.info(f"User requested abortion of exiting {trade.pair}")
return False
try:
# Execute sell and update trade record
order = self.exchange.create_order(pair=trade.pair,
ordertype=order_type, side="sell",
amount=amount, rate=limit,
time_in_force=time_in_force
)
order = self.exchange.create_order(
pair=trade.pair,
ordertype=order_type,
side="sell",
amount=amount,
rate=limit,
time_in_force=time_in_force
)
except InsufficientFundsError as e:
logger.warning(f"Unable to place order {e}.")
# Try to figure out what went wrong
@ -1148,15 +1163,15 @@ class FreqtradeBot(LoggingMixin):
self.update_trade_state(trade, trade.open_order_id, order)
Trade.commit()
# Lock pair for one candle to prevent immediate re-buys
# Lock pair for one candle to prevent immediate re-trading
self.strategy.lock_pair(trade.pair, datetime.now(timezone.utc),
reason='Auto lock')
self._notify_sell(trade, order_type)
self._notify_exit(trade, order_type)
return True
def _notify_sell(self, trade: Trade, order_type: str, fill: bool = False) -> None:
def _notify_exit(self, trade: Trade, order_type: str, fill: bool = False) -> None:
"""
Sends rpc notification when a sell occurred.
"""
@ -1198,7 +1213,7 @@ class FreqtradeBot(LoggingMixin):
# Send the message
self.rpc.send_msg(msg)
def _notify_sell_cancel(self, trade: Trade, order_type: str, reason: str) -> None:
def _notify_exit_cancel(self, trade: Trade, order_type: str, reason: str) -> None:
"""
Sends rpc notification when a sell cancel occurred.
"""
@ -1293,13 +1308,13 @@ class FreqtradeBot(LoggingMixin):
# Updating wallets when order is closed
if not trade.is_open:
if not stoploss_order and not trade.open_order_id:
self._notify_sell(trade, '', True)
self._notify_exit(trade, '', True)
self.protections.stop_per_pair(trade.pair)
self.protections.global_stop()
self.wallets.update()
elif not trade.open_order_id:
# Buy fill
self._notify_buy_fill(trade)
self._notify_enter_fill(trade)
return False
@ -1312,6 +1327,7 @@ class FreqtradeBot(LoggingMixin):
self.wallets.update()
if fee_abs != 0 and self.wallets.get_free(trade_base_currency) >= amount:
# Eat into dust if we own more than base currency
# TODO-lev: won't be in "base"(quote) currency for shorts
logger.info(f"Fee amount for {trade} was in base currency - "
f"Eating Fee {fee_abs} into dust.")
elif fee_abs != 0:
@ -1388,6 +1404,7 @@ class FreqtradeBot(LoggingMixin):
trade.update_fee(fee_cost, fee_currency, fee_rate, order.get('side', ''))
if not isclose(amount, order_amount, abs_tol=constants.MATH_CLOSE_PREC):
# TODO-lev: leverage?
logger.warning(f"Amount {amount} does not match amount {trade.amount}")
raise DependencyException("Half bought? Amounts don't match")

2
freqtrade/loggers.py
View File

@ -87,7 +87,7 @@ def setup_logging(config: Dict[str, Any]) -> None:
# syslog config. The messages should be equal for this.
handler_sl.setFormatter(Formatter('%(name)s - %(levelname)s - %(message)s'))
logging.root.addHandler(handler_sl)
elif s[0] == 'journald':
elif s[0] == 'journald': # pragma: no cover
try:
from systemd.journal import JournaldLogHandler
except ImportError:

6
freqtrade/main.py
View File

@ -9,7 +9,7 @@ from typing import Any, List
# check min. python version
if sys.version_info < (3, 7):
if sys.version_info < (3, 7): # pragma: no cover
sys.exit("Freqtrade requires Python version >= 3.7")
from freqtrade.commands import Arguments
@ -46,7 +46,7 @@ def main(sysargv: List[str] = None) -> None:
"`freqtrade --help` or `freqtrade <command> --help`."
)
except SystemExit as e:
except SystemExit as e: # pragma: no cover
return_code = e
except KeyboardInterrupt:
logger.info('SIGINT received, aborting ...')
@ -60,5 +60,5 @@ def main(sysargv: List[str] = None) -> None:
sys.exit(return_code)
if __name__ == '__main__':
if __name__ == '__main__': # pragma: no cover
main()

7
freqtrade/optimize/backtesting.py
View File

@ -11,7 +11,7 @@ from typing import Any, Dict, List, Optional, Tuple
from pandas import DataFrame
from freqtrade.configuration import TimeRange, remove_credentials, validate_config_consistency
from freqtrade.configuration import TimeRange, validate_config_consistency
from freqtrade.constants import DATETIME_PRINT_FORMAT
from freqtrade.data import history
from freqtrade.data.btanalysis import trade_list_to_dataframe
@ -64,8 +64,7 @@ class Backtesting:
self.config = config
self.results: Optional[Dict[str, Any]] = None
# Reset keys for backtesting
remove_credentials(self.config)
config['dry_run'] = True
self.strategylist: List[IStrategy] = []
self.all_results: Dict[str, Dict] = {}
self._exchange_name = self.config['exchange']['name']
@ -403,7 +402,7 @@ class Backtesting:
detail_data = detail_data.loc[
(detail_data['date'] >= sell_candle_time) &
(detail_data['date'] < sell_candle_end)
]
]
if len(detail_data) == 0:
# Fall back to "regular" data if no detail data was found for this candle
return self._get_sell_trade_entry_for_candle(trade, sell_row)

6
freqtrade/optimize/edge_cli.py
View File

@ -7,7 +7,7 @@ import logging
from typing import Any, Dict
from freqtrade import constants
from freqtrade.configuration import TimeRange, remove_credentials, validate_config_consistency
from freqtrade.configuration import TimeRange, validate_config_consistency
from freqtrade.edge import Edge
from freqtrade.optimize.optimize_reports import generate_edge_table
from freqtrade.resolvers import ExchangeResolver, StrategyResolver
@ -28,8 +28,8 @@ class EdgeCli:
def __init__(self, config: Dict[str, Any]) -> None:
self.config = config
# Reset keys for edge
remove_credentials(self.config)
# Ensure using dry-run
self.config['dry_run'] = True
self.config['stake_amount'] = constants.UNLIMITED_STAKE_AMOUNT
self.exchange = ExchangeResolver.load_exchange(self.config['exchange']['name'], self.config)
self.strategy = StrategyResolver.load_strategy(self.config)

83
freqtrade/optimize/hyperopt.py
View File

@ -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
@ -44,7 +45,7 @@ progressbar.streams.wrap_stdout()
logger = logging.getLogger(__name__)
INITIAL_POINTS = 30
INITIAL_POINTS = 5
# Keep no more than SKOPT_MODEL_QUEUE_SIZE models
# in the skopt model queue, to optimize memory consumption
@ -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.
@ -265,7 +241,7 @@ class Hyperopt:
if HyperoptTools.has_space(self.config, 'buy'):
logger.debug("Hyperopt has 'buy' space")
self.buy_space = self.custom_hyperopt.indicator_space()
self.buy_space = self.custom_hyperopt.buy_indicator_space()
if HyperoptTools.has_space(self.config, 'sell'):
logger.debug("Hyperopt has 'sell' space")
@ -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
@ -385,10 +365,20 @@ class Hyperopt:
}
def get_optimizer(self, dimensions: List[Dimension], cpu_count) -> Optimizer:
estimator = self.custom_hyperopt.generate_estimator()
acq_optimizer = "sampling"
if isinstance(estimator, str):
if estimator not in ("GP", "RF", "ET", "GBRT"):
raise OperationalException(f"Estimator {estimator} not supported.")
else:
acq_optimizer = "auto"
logger.info(f"Using estimator {estimator}.")
return Optimizer(
dimensions,
base_estimator="ET",
acq_optimizer="auto",
base_estimator=estimator,
acq_optimizer=acq_optimizer,
n_initial_points=INITIAL_POINTS,
acq_optimizer_kwargs={'n_jobs': cpu_count},
random_state=self.random_state,
@ -517,11 +507,10 @@ class Hyperopt:
f"saved to '{self.results_file}'.")
if self.current_best_epoch:
if self.auto_hyperopt:
HyperoptTools.try_export_params(
self.config,
self.backtesting.strategy.get_strategy_name(),
self.current_best_epoch)
HyperoptTools.try_export_params(
self.config,
self.backtesting.strategy.get_strategy_name(),
self.current_best_epoch)
HyperoptTools.show_epoch_details(self.current_best_epoch, self.total_epochs,
self.print_json)

50
freqtrade/optimize/hyperopt_auto.py
View File

@ -4,15 +4,23 @@ 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):
from skopt.space import Dimension
from freqtrade.optimize.hyperopt_interface import IHyperOpt
from freqtrade.optimize.hyperopt_interface import EstimatorType, 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):
@ -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')
def buy_indicator_space(self) -> List['Dimension']:
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)
@ -90,3 +79,6 @@ class HyperOptAuto(IHyperOpt):
def trailing_space(self) -> List['Dimension']:
return self._get_func('trailing_space')()
def generate_estimator(self) -> EstimatorType:
return self._get_func('generate_estimator')()

44
freqtrade/optimize/hyperopt_interface.py
View File

@ -5,11 +5,11 @@ 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, Union
from sklearn.base import RegressorMixin
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
@ -18,12 +18,7 @@ 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.")
EstimatorType = Union[RegressorMixin, str]
class IHyperOpt(ABC):
@ -45,36 +40,13 @@ 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:
def generate_estimator(self) -> EstimatorType:
"""
Create a buy strategy generator.
Return base_estimator.
Can be any of "GP", "RF", "ET", "GBRT" or an instance of a class
inheriting from RegressorMixin (from sklearn).
"""
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'))
return 'ET'
def generate_roi_table(self, params: Dict) -> Dict[int, float]:
"""

3
freqtrade/persistence/models.py
View File

@ -320,6 +320,7 @@ class LocalTrade():
if self.isolated_liq:
self.set_isolated_liq(self.isolated_liq)
self.recalc_open_trade_value()
# TODO-lev: Throw exception if on margin and interest_rate is none
def _set_stop_loss(self, stop_loss: float, percent: float):
"""
@ -549,7 +550,7 @@ class LocalTrade():
if self.is_open:
payment = "BUY" if self.is_short else "SELL"
# TODO-lev: On shorts, you buy a little bit more than the amount (amount + interest)
# This wll only print the original amount
# TODO-lev: This wll only print the original amount
logger.info(f'{order_type.upper()}_{payment} has been fulfilled for {self}.')
# TODO-lev: Double check this
self.close(safe_value_fallback(order, 'average', 'price'))

16
freqtrade/plugins/pairlist/AgeFilter.py
View File

@ -8,6 +8,7 @@ from typing import Any, Dict, List, Optional
import arrow
from pandas import DataFrame
from freqtrade.configuration import PeriodicCache
from freqtrade.exceptions import OperationalException
from freqtrade.misc import plural
from freqtrade.plugins.pairlist.IPairList import IPairList
@ -18,14 +19,15 @@ logger = logging.getLogger(__name__)
class AgeFilter(IPairList):
# Checked symbols cache (dictionary of ticker symbol => timestamp)
_symbolsChecked: Dict[str, int] = {}
def __init__(self, exchange, pairlistmanager,
config: Dict[str, Any], pairlistconfig: Dict[str, Any],
pairlist_pos: int) -> None:
super().__init__(exchange, pairlistmanager, config, pairlistconfig, pairlist_pos)
# Checked symbols cache (dictionary of ticker symbol => timestamp)
self._symbolsChecked: Dict[str, int] = {}
self._symbolsCheckFailed = PeriodicCache(maxsize=1000, ttl=86_400)
self._min_days_listed = pairlistconfig.get('min_days_listed', 10)
self._max_days_listed = pairlistconfig.get('max_days_listed', None)
@ -69,9 +71,12 @@ class AgeFilter(IPairList):
:param tickers: Tickers (from exchange.get_tickers()). May be cached.
:return: new allowlist
"""
needed_pairs = [(p, '1d') for p in pairlist if p not in self._symbolsChecked]
needed_pairs = [
(p, '1d') for p in pairlist
if p not in self._symbolsChecked and p not in self._symbolsCheckFailed]
if not needed_pairs:
return pairlist
# Remove pairs that have been removed before
return [p for p in pairlist if p not in self._symbolsCheckFailed]
since_days = -(
self._max_days_listed if self._max_days_listed else self._min_days_listed
@ -118,5 +123,6 @@ class AgeFilter(IPairList):
" or more than "
f"{self._max_days_listed} {plural(self._max_days_listed, 'day')}"
) if self._max_days_listed else ''), logger.info)
self._symbolsCheckFailed[pair] = arrow.utcnow().int_timestamp * 1000
return False
return False

1
freqtrade/plugins/pairlist/PrecisionFilter.py
View File

@ -18,6 +18,7 @@ class PrecisionFilter(IPairList):
pairlist_pos: int) -> None:
super().__init__(exchange, pairlistmanager, config, pairlistconfig, pairlist_pos)
# TODO-lev: Liquidation price?
if 'stoploss' not in self._config:
raise OperationalException(
'PrecisionFilter can only work with stoploss defined. Please add the '

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

@ -123,7 +123,7 @@ class VolumePairList(IPairList):
filtered_tickers = [
v for k, v in tickers.items()
if (self._exchange.get_pair_quote_currency(k) == self._stake_currency
and v[self._sort_key] is not None)]
and (self._use_range or v[self._sort_key] is not None))]
pairlist = [s['symbol'] for s in filtered_tickers]
pairlist = self.filter_pairlist(pairlist, tickers)

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

@ -17,7 +17,7 @@ def expand_pairlist(wildcardpl: List[str], available_pairs: List[str],
if keep_invalid:
for pair_wc in wildcardpl:
try:
comp = re.compile(pair_wc)
comp = re.compile(pair_wc, re.IGNORECASE)
result_partial = [
pair for pair in available_pairs if re.fullmatch(comp, pair)
]
@ -33,7 +33,7 @@ def expand_pairlist(wildcardpl: List[str], available_pairs: List[str],
else:
for pair_wc in wildcardpl:
try:
comp = re.compile(pair_wc)
comp = re.compile(pair_wc, re.IGNORECASE)
result += [
pair for pair in available_pairs if re.fullmatch(comp, pair)
]

2
freqtrade/plugins/pairlistmanager.py
View File

@ -127,7 +127,7 @@ class PairListManager():
:return: pairlist - whitelisted pairs
"""
try:
# TODO-lev: filter for pairlists that are able to trade at the desired leverage
whitelist = expand_pairlist(pairlist, self._exchange.get_markets().keys(), keep_invalid)
except ValueError as err:
logger.error(f"Pair whitelist contains an invalid Wildcard: {err}")

1
freqtrade/plugins/protections/max_drawdown_protection.py
View File

@ -36,6 +36,7 @@ class MaxDrawdown(IProtection):
"""
LockReason to use
"""
# TODO-lev: < for shorts?
return (f'{drawdown} > {self._max_allowed_drawdown} in {self.lookback_period_str}, '
f'locking for {self.stop_duration_str}.')

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

@ -32,6 +32,7 @@ class StoplossGuard(IProtection):
def _reason(self) -> str:
"""
LockReason to use
#TODO-lev: check if min is the right word for shorts
"""
return (f'{self._trade_limit} stoplosses in {self._lookback_period} min, '
f'locking for {self._stop_duration} min.')
@ -51,6 +52,7 @@ class StoplossGuard(IProtection):
# if pair:
# filters.append(Trade.pair == pair)
# trades = Trade.get_trades(filters).all()
# TODO-lev: Liquidation price?
trades1 = Trade.get_trades_proxy(pair=pair, is_open=False, close_date=look_back_until)
trades = [trade for trade in trades1 if (str(trade.sell_reason) in (

39
freqtrade/resolvers/hyperopt_resolver.py
View File

@ -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
@ -17,44 +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.")
# TODO-lev: Short equivelents?
return hyperopt
class HyperOptLossResolver(IResolver):
"""
This class contains all the logic to load custom hyperopt loss class

16
freqtrade/rpc/api_server/uvicorn_threaded.py
View File

@ -5,6 +5,20 @@ import time
import uvicorn
def asyncio_setup() -> None: # pragma: no cover
# Set eventloop for win32 setups
# Reverts a change done in uvicorn 0.15.0 - which now sets the eventloop
# via policy.
import sys
if sys.version_info >= (3, 8) and sys.platform == "win32":
import asyncio
import selectors
selector = selectors.SelectSelector()
loop = asyncio.SelectorEventLoop(selector)
asyncio.set_event_loop(loop)
class UvicornServer(uvicorn.Server):
"""
Multithreaded server - as found in https://github.com/encode/uvicorn/issues/742
@ -28,7 +42,7 @@ class UvicornServer(uvicorn.Server):
try:
import uvloop # noqa
except ImportError: # pragma: no cover
from uvicorn.loops.asyncio import asyncio_setup
asyncio_setup()
else:
asyncio.set_event_loop(uvloop.new_event_loop())

16
freqtrade/rpc/rpc.py
View File

@ -36,6 +36,7 @@ class RPCException(Exception):
raise RPCException('*Status:* `no active trade`')
"""
# TODO-lev: Add new configuration options introduced with leveraged/short trading
def __init__(self, message: str) -> None:
super().__init__(self)
@ -403,8 +404,11 @@ class RPC:
# Doing the sum is not right - overall profit needs to be based on initial capital
profit_all_ratio_sum = sum(profit_all_ratio) if profit_all_ratio else 0.0
starting_balance = self._freqtrade.wallets.get_starting_balance()
profit_closed_ratio_fromstart = profit_closed_coin_sum / starting_balance
profit_all_ratio_fromstart = profit_all_coin_sum / starting_balance
profit_closed_ratio_fromstart = 0
profit_all_ratio_fromstart = 0
if starting_balance:
profit_closed_ratio_fromstart = profit_closed_coin_sum / starting_balance
profit_all_ratio_fromstart = profit_all_coin_sum / starting_balance
profit_all_fiat = self._fiat_converter.convert_amount(
profit_all_coin_sum,
@ -545,12 +549,12 @@ class RPC:
order = self._freqtrade.exchange.fetch_order(trade.open_order_id, trade.pair)
if order['side'] == 'buy':
fully_canceled = self._freqtrade.handle_cancel_buy(
fully_canceled = self._freqtrade.handle_cancel_enter(
trade, order, CANCEL_REASON['FORCE_SELL'])
if order['side'] == 'sell':
# Cancel order - so it is placed anew with a fresh price.
self._freqtrade.handle_cancel_sell(trade, order, CANCEL_REASON['FORCE_SELL'])
self._freqtrade.handle_cancel_exit(trade, order, CANCEL_REASON['FORCE_SELL'])
if not fully_canceled:
# Get current rate and execute sell
@ -563,7 +567,7 @@ class RPC:
if self._freqtrade.state != State.RUNNING:
raise RPCException('trader is not running')
with self._freqtrade._sell_lock:
with self._freqtrade._exit_lock:
if trade_id == 'all':
# Execute sell for all open orders
for trade in Trade.get_open_trades():
@ -625,7 +629,7 @@ class RPC:
Handler for delete <id>.
Delete the given trade and close eventually existing open orders.
"""
with self._freqtrade._sell_lock:
with self._freqtrade._exit_lock:
c_count = 0
trade = Trade.get_trades(trade_filter=[Trade.id == trade_id]).first()
if not trade:

25
freqtrade/strategy/interface.py
View File

@ -168,7 +168,7 @@ class IStrategy(ABC, HyperStrategyMixin):
"""
Check buy timeout function callback.
This method can be used to override the enter-timeout.
It is called whenever a limit buy/short order has been created,
It is called whenever a limit entry order has been created,
and is not yet fully filled.
Configuration options in `unfilledtimeout` will be verified before this,
so ensure to set these timeouts high enough.
@ -178,7 +178,7 @@ class IStrategy(ABC, HyperStrategyMixin):
:param trade: trade object.
:param order: Order dictionary as returned from CCXT.
:param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
:return bool: When True is returned, then the buy/short-order is cancelled.
:return bool: When True is returned, then the entry order is cancelled.
"""
return False
@ -213,7 +213,7 @@ class IStrategy(ABC, HyperStrategyMixin):
def confirm_trade_entry(self, pair: str, order_type: str, amount: float, rate: float,
time_in_force: str, current_time: datetime, **kwargs) -> bool:
"""
Called right before placing a buy/short order.
Called right before placing a entry order.
Timing for this function is critical, so avoid doing heavy computations or
network requests in this method.
@ -237,7 +237,7 @@ class IStrategy(ABC, HyperStrategyMixin):
rate: float, time_in_force: str, sell_reason: str,
current_time: datetime, **kwargs) -> bool:
"""
Called right before placing a regular sell/exit_short order.
Called right before placing a regular exit order.
Timing for this function is critical, so avoid doing heavy computations or
network requests in this method.
@ -412,7 +412,7 @@ class IStrategy(ABC, HyperStrategyMixin):
Checks if a pair is currently locked
The 2nd, optional parameter ensures that locks are applied until the new candle arrives,
and not stop at 14:00:00 - while the next candle arrives at 14:00:02 leaving a gap
of 2 seconds for a buy/short to happen on an old signal.
of 2 seconds for an entry order to happen on an old signal.
:param pair: "Pair to check"
:param candle_date: Date of the last candle. Optional, defaults to current date
:returns: locking state of the pair in question.
@ -428,7 +428,7 @@ class IStrategy(ABC, HyperStrategyMixin):
def analyze_ticker(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Parses the given candle (OHLCV) data and returns a populated DataFrame
add several TA indicators and buy/short signal to it
add several TA indicators and entry order signal to it
:param dataframe: Dataframe containing data from exchange
:param metadata: Metadata dictionary with additional data (e.g. 'pair')
:return: DataFrame of candle (OHLCV) data with indicator data and signals added
@ -547,7 +547,9 @@ class IStrategy(ABC, HyperStrategyMixin):
dataframe: DataFrame,
) -> Tuple[Optional[DataFrame], Optional[arrow.Arrow]]:
"""
Get the latest candle. Used only during real mode
Calculates current signal based based on the entry order or exit order
columns of the dataframe.
Used by Bot to get the signal to buy, sell, short, or exit_short
:param pair: pair in format ANT/BTC
:param timeframe: timeframe to use
:param dataframe: Analyzed dataframe to get signal from.
@ -672,7 +674,7 @@ class IStrategy(ABC, HyperStrategyMixin):
low: float = None, high: float = None,
force_stoploss: float = 0) -> SellCheckTuple:
"""
This function evaluates if one of the conditions required to trigger a sell/exit_short
This function evaluates if one of the conditions required to trigger an exit order
has been reached, which can either be a stop-loss, ROI or exit-signal.
:param low: Only used during backtesting to simulate (long)stoploss/(short)ROI
:param high: Only used during backtesting, to simulate (short)stoploss/(long)ROI
@ -860,10 +862,11 @@ class IStrategy(ABC, HyperStrategyMixin):
Does not run advise_buy or advise_sell!
Used by optimize operations only, not during dry / live runs.
Using .copy() to get a fresh copy of the dataframe for every strategy run.
Also copy on output to avoid PerformanceWarnings pandas 1.3.0 started to show.
Has positive effects on memory usage for whatever reason - also when
using only one strategy.
"""
return {pair: self.advise_indicators(pair_data.copy(), {'pair': pair})
return {pair: self.advise_indicators(pair_data.copy(), {'pair': pair}).copy()
for pair, pair_data in data.items()}
def advise_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
@ -884,7 +887,7 @@ class IStrategy(ABC, HyperStrategyMixin):
def advise_buy(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Based on TA indicators, populates the buy/short signal for the given dataframe
Based on TA indicators, populates the entry order signal for the given dataframe
This method should not be overridden.
:param dataframe: DataFrame
:param metadata: Additional information dictionary, with details like the
@ -907,7 +910,7 @@ class IStrategy(ABC, HyperStrategyMixin):
def advise_sell(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Based on TA indicators, populates the sell/exit_short signal for the given dataframe
Based on TA indicators, populates the exit order signal for the given dataframe
This method should not be overridden.
:param dataframe: DataFrame
:param metadata: Additional information dictionary, with details like the

9
freqtrade/templates/base_config.json.j2
View File

@ -1,3 +1,10 @@
{%set volume_pairlist = '{
"method": "VolumePairList",
"number_assets": 20,
"sort_key": "quoteVolume",
"min_value": 0,
"refresh_period": 1800
}' %}
{
"max_open_trades": {{ max_open_trades }},
"stake_currency": "{{ stake_currency }}",
@ -29,7 +36,7 @@
},
{{ exchange | indent(4) }},
"pairlists": [
{"method": "StaticPairList"}
{{ '{"method": "StaticPairList"}' if exchange_name == 'bittrex' else volume_pairlist }}
],
"edge": {
"enabled": false,

137
freqtrade/templates/base_hyperopt.py.j2
View File

@ -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

180
freqtrade/templates/sample_hyperopt.py
View File

@ -1,180 +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(['boll', '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.
"""
long_conditions = []
# GUARDS AND TRENDS
if 'mfi-enabled' in params and params['mfi-enabled']:
long_conditions.append(dataframe['mfi'] < params['mfi-value'])
if 'fastd-enabled' in params and params['fastd-enabled']:
long_conditions.append(dataframe['fastd'] < params['fastd-value'])
if 'adx-enabled' in params and params['adx-enabled']:
long_conditions.append(dataframe['adx'] > params['adx-value'])
if 'rsi-enabled' in params and params['rsi-enabled']:
long_conditions.append(dataframe['rsi'] < params['rsi-value'])
# TRIGGERS
if 'trigger' in params:
if params['trigger'] == 'boll':
long_conditions.append(dataframe['close'] < dataframe['bb_lowerband'])
if params['trigger'] == 'macd_cross_signal':
long_conditions.append(qtpylib.crossed_above(
dataframe['macd'],
dataframe['macdsignal']
))
if params['trigger'] == 'sar_reversal':
long_conditions.append(qtpylib.crossed_above(
dataframe['close'],
dataframe['sar']
))
# Check that volume is not 0
long_conditions.append(dataframe['volume'] > 0)
if long_conditions:
dataframe.loc[
reduce(lambda x, y: x & y, long_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-boll',
'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.
"""
exit_long_conditions = []
# GUARDS AND TRENDS
if 'sell-mfi-enabled' in params and params['sell-mfi-enabled']:
exit_long_conditions.append(dataframe['mfi'] > params['sell-mfi-value'])
if 'sell-fastd-enabled' in params and params['sell-fastd-enabled']:
exit_long_conditions.append(dataframe['fastd'] > params['sell-fastd-value'])
if 'sell-adx-enabled' in params and params['sell-adx-enabled']:
exit_long_conditions.append(dataframe['adx'] < params['sell-adx-value'])
if 'sell-rsi-enabled' in params and params['sell-rsi-enabled']:
exit_long_conditions.append(dataframe['rsi'] > params['sell-rsi-value'])
# TRIGGERS
if 'sell-trigger' in params:
if params['sell-trigger'] == 'sell-boll':
exit_long_conditions.append(dataframe['close'] > dataframe['bb_upperband'])
if params['sell-trigger'] == 'sell-macd_cross_signal':
exit_long_conditions.append(qtpylib.crossed_above(
dataframe['macdsignal'],
dataframe['macd']
))
if params['sell-trigger'] == 'sell-sar_reversal':
exit_long_conditions.append(qtpylib.crossed_above(
dataframe['sar'],
dataframe['close']
))
# Check that volume is not 0
exit_long_conditions.append(dataframe['volume'] > 0)
if exit_long_conditions:
dataframe.loc[
reduce(lambda x, y: x & y, exit_long_conditions),
'sell'] = 1
return dataframe
return populate_sell_trend

272
freqtrade/templates/sample_hyperopt_advanced.py
View File

@ -1,272 +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(['boll', '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
"""
long_conditions = []
# GUARDS AND TRENDS
if 'mfi-enabled' in params and params['mfi-enabled']:
long_conditions.append(dataframe['mfi'] < params['mfi-value'])
if 'fastd-enabled' in params and params['fastd-enabled']:
long_conditions.append(dataframe['fastd'] < params['fastd-value'])
if 'adx-enabled' in params and params['adx-enabled']:
long_conditions.append(dataframe['adx'] > params['adx-value'])
if 'rsi-enabled' in params and params['rsi-enabled']:
long_conditions.append(dataframe['rsi'] < params['rsi-value'])
# TRIGGERS
if 'trigger' in params:
if params['trigger'] == 'boll':
long_conditions.append(dataframe['close'] < dataframe['bb_lowerband'])
if params['trigger'] == 'macd_cross_signal':
long_conditions.append(qtpylib.crossed_above(
dataframe['macd'], dataframe['macdsignal']
))
if params['trigger'] == 'sar_reversal':
long_conditions.append(qtpylib.crossed_above(
dataframe['close'], dataframe['sar']
))
# Check that volume is not 0
long_conditions.append(dataframe['volume'] > 0)
if long_conditions:
dataframe.loc[
reduce(lambda x, y: x & y, long_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-boll',
'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)
exit_long_conditions = []
# GUARDS AND TRENDS
if 'sell-mfi-enabled' in params and params['sell-mfi-enabled']:
exit_long_conditions.append(dataframe['mfi'] > params['sell-mfi-value'])
if 'sell-fastd-enabled' in params and params['sell-fastd-enabled']:
exit_long_conditions.append(dataframe['fastd'] > params['sell-fastd-value'])
if 'sell-adx-enabled' in params and params['sell-adx-enabled']:
exit_long_conditions.append(dataframe['adx'] < params['sell-adx-value'])
if 'sell-rsi-enabled' in params and params['sell-rsi-enabled']:
exit_long_conditions.append(dataframe['rsi'] > params['sell-rsi-value'])
# TRIGGERS
if 'sell-trigger' in params:
if params['sell-trigger'] == 'sell-boll':
exit_long_conditions.append(dataframe['close'] > dataframe['bb_upperband'])
if params['sell-trigger'] == 'sell-macd_cross_signal':
exit_long_conditions.append(qtpylib.crossed_above(
dataframe['macdsignal'],
dataframe['macd']
))
if params['sell-trigger'] == 'sell-sar_reversal':
exit_long_conditions.append(qtpylib.crossed_above(
dataframe['sar'],
dataframe['close']
))
# Check that volume is not 0
exit_long_conditions.append(dataframe['volume'] > 0)
if exit_long_conditions:
dataframe.loc[
reduce(lambda x, y: x & y, exit_long_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'),
]

28
freqtrade/templates/subtemplates/exchange_binance.j2
View File

@ -8,34 +8,8 @@
"rateLimit": 200
},
"pair_whitelist": [
"ALGO/BTC",
"ATOM/BTC",
"BAT/BTC",
"BCH/BTC",
"BRD/BTC",
"EOS/BTC",
"ETH/BTC",
"IOTA/BTC",
"LINK/BTC",
"LTC/BTC",
"NEO/BTC",
"NXS/BTC",
"XMR/BTC",
"XRP/BTC",
"XTZ/BTC"
],
"pair_blacklist": [
"BNB/BTC",
"BNB/BUSD",
"BNB/ETH",
"BNB/EUR",
"BNB/NGN",
"BNB/PAX",
"BNB/RUB",
"BNB/TRY",
"BNB/TUSD",
"BNB/USDC",
"BNB/USDS",
"BNB/USDT"
"BNB/.*"
]
}

10
freqtrade/templates/subtemplates/exchange_bittrex.j2
View File

@ -15,16 +15,6 @@
"rateLimit": 500
},
"pair_whitelist": [
"ETH/BTC",
"LTC/BTC",
"ETC/BTC",
"DASH/BTC",
"ZEC/BTC",
"XLM/BTC",
"XRP/BTC",
"TRX/BTC",
"ADA/BTC",
"XMR/BTC"
],
"pair_blacklist": [
]

22
freqtrade/templates/subtemplates/exchange_kraken.j2
View File

@ -7,28 +7,10 @@
"ccxt_async_config": {
"enableRateLimit": true,
"rateLimit": 1000
// Enable the below for downoading data.
//"rateLimit": 3100
},
"pair_whitelist": [
"ADA/EUR",
"ATOM/EUR",
"BAT/EUR",
"BCH/EUR",
"BTC/EUR",
"DAI/EUR",
"DASH/EUR",
"EOS/EUR",
"ETC/EUR",
"ETH/EUR",
"LINK/EUR",
"LTC/EUR",
"QTUM/EUR",
"REP/EUR",
"WAVES/EUR",
"XLM/EUR",
"XMR/EUR",
"XRP/EUR",
"XTZ/EUR",
"ZEC/EUR"
],
"pair_blacklist": [

18
freqtrade/templates/subtemplates/exchange_kucoin.j2 Normal file
View File

@ -0,0 +1,18 @@
"exchange": {
"name": "{{ exchange_name | lower }}",
"key": "{{ exchange_key }}",
"secret": "{{ exchange_secret }}",
"password": "{{ exchange_key_password }}",
"ccxt_config": {
"enableRateLimit": true
"rateLimit": 200
},
"ccxt_async_config": {
"enableRateLimit": true,
"rateLimit": 200
},
"pair_whitelist": [
],
"pair_blacklist": [
]
}

8
freqtrade/templates/subtemplates/hyperopt_buy_guards_full.j2
View File

@ -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'])

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

@ -1,2 +0,0 @@
if params.get('rsi-enabled'):
conditions.append(dataframe['rsi'] < params['rsi-value'])

9
freqtrade/templates/subtemplates/hyperopt_buy_space_full.j2
View File

@ -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')

3
freqtrade/templates/subtemplates/hyperopt_buy_space_minimal.j2
View File

@ -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')

8
freqtrade/templates/subtemplates/hyperopt_sell_guards_full.j2
View File

@ -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'])

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

@ -1,2 +0,0 @@
if params.get('sell-rsi-enabled'):
conditions.append(dataframe['rsi'] > params['sell-rsi-value'])

11
freqtrade/templates/subtemplates/hyperopt_sell_space_full.j2
View File

@ -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')

5
freqtrade/templates/subtemplates/hyperopt_sell_space_minimal.j2
View File

@ -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')

72
mkdocs.yml
View File

@ -3,42 +3,42 @@ site_url: https://www.freqtrade.io/
repo_url: https://github.com/freqtrade/freqtrade
use_directory_urls: True
nav:
- Home: index.md
- Quickstart with Docker: docker_quickstart.md
- Installation:
- Linux/MacOS/Raspberry: installation.md
- Windows: windows_installation.md
- Freqtrade Basics: bot-basics.md
- Configuration: configuration.md
- Strategy Customization: strategy-customization.md
- Plugins: plugins.md
- Stoploss: stoploss.md
- Start the bot: bot-usage.md
- Control the bot:
- Telegram: telegram-usage.md
- REST API & FreqUI: rest-api.md
- Web Hook: webhook-config.md
- Data Downloading: data-download.md
- Backtesting: backtesting.md
- Leverage: leverage.md
- Hyperopt: hyperopt.md
- Utility Sub-commands: utils.md
- Plotting: plotting.md
- Data Analysis:
- Jupyter Notebooks: data-analysis.md
- Strategy analysis: strategy_analysis_example.md
- Exchange-specific Notes: exchanges.md
- Advanced Topics:
- Advanced Post-installation Tasks: advanced-setup.md
- Edge Positioning: edge.md
- Advanced Strategy: strategy-advanced.md
- Advanced Hyperopt: advanced-hyperopt.md
- Sandbox Testing: sandbox-testing.md
- FAQ: faq.md
- SQL Cheat-sheet: sql_cheatsheet.md
- Updating Freqtrade: updating.md
- Deprecated Features: deprecated.md
- Contributors Guide: developer.md
- Home: index.md
- Quickstart with Docker: docker_quickstart.md
- Installation:
- Linux/MacOS/Raspberry: installation.md
- Windows: windows_installation.md
- Freqtrade Basics: bot-basics.md
- Configuration: configuration.md
- Strategy Customization: strategy-customization.md
- Plugins: plugins.md
- Stoploss: stoploss.md
- Start the bot: bot-usage.md
- Control the bot:
- Telegram: telegram-usage.md
- REST API & FreqUI: rest-api.md
- Web Hook: webhook-config.md
- Data Downloading: data-download.md
- Backtesting: backtesting.md
- Hyperopt: hyperopt.md
- Leverage: leverage.md
- Utility Sub-commands: utils.md
- Plotting: plotting.md
- Exchange-specific Notes: exchanges.md
- Data Analysis:
- Jupyter Notebooks: data-analysis.md
- Strategy analysis: strategy_analysis_example.md
- Advanced Topics:
- Advanced Post-installation Tasks: advanced-setup.md
- Edge Positioning: edge.md
- Advanced Strategy: strategy-advanced.md
- Advanced Hyperopt: advanced-hyperopt.md
- Sandbox Testing: sandbox-testing.md
- FAQ: faq.md
- SQL Cheat-sheet: sql_cheatsheet.md
- Updating Freqtrade: updating.md
- Deprecated Features: deprecated.md
- Contributors Guide: developer.md
theme:
name: material
logo: "images/logo.png"

4
requirements-dev.txt
View File

@ -8,12 +8,14 @@ flake8==3.9.2
flake8-type-annotations==0.1.0
flake8-tidy-imports==4.4.1
mypy==0.910
pytest==6.2.4
pytest==6.2.5
pytest-asyncio==0.15.1
pytest-cov==2.12.1
pytest-mock==3.6.1
pytest-random-order==1.0.4
isort==5.9.3
# For datetime mocking
time-machine==2.4.0
# Convert jupyter notebooks to markdown documents
nbconvert==6.1.0

2
requirements-hyperopt.txt
View File

@ -8,4 +8,4 @@ scikit-optimize==0.8.1
filelock==3.0.12
joblib==1.0.1
psutil==5.8.0
progressbar2==3.53.1
progressbar2==3.53.2

2
requirements-plot.txt
View File

@ -1,5 +1,5 @@
# Include all requirements to run the bot.
-r requirements.txt
plotly==5.3.0
plotly==5.3.1

4
requirements.txt
View File

@ -1,7 +1,7 @@
numpy==1.21.2
pandas==1.3.2
pandas==1.3.3
ccxt==1.55.56
ccxt==1.56.30
# Pin cryptography for now due to rust build errors with piwheels
cryptography==3.4.8
aiohttp==3.7.4.post0

14
setup.sh
View File

@ -95,19 +95,7 @@ function install_talib() {
return
fi
cd build_helpers
tar zxvf ta-lib-0.4.0-src.tar.gz
cd ta-lib
sed -i.bak "s|0.00000001|0.000000000000000001 |g" src/ta_func/ta_utility.h
./configure --prefix=/usr/local
make
sudo make install
if [ -x "$(command -v apt-get)" ]; then
echo "Updating library path using ldconfig"
sudo ldconfig
fi
cd .. && rm -rf ./ta-lib/
cd ..
cd build_helpers && ./install_ta-lib.sh && cd ..
}
function install_mac_newer_python_dependencies() {

76
tests/commands/test_commands.py
View File

@ -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
@ -32,8 +32,6 @@ def test_setup_utils_configuration():
config = setup_utils_configuration(get_args(args), RunMode.OTHER)
assert "exchange" in config
assert config['dry_run'] is True
assert config['exchange']['key'] == ''
assert config['exchange']['secret'] == ''
def test_start_trading_fail(mocker, caplog):
@ -519,37 +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',
@ -824,37 +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):

6
tests/conftest.py
View File

@ -6,7 +6,7 @@ from copy import deepcopy
from datetime import datetime, timedelta
from functools import reduce
from pathlib import Path
from typing import Optional
from typing import Optional, Tuple
from unittest.mock import MagicMock, Mock, PropertyMock
import arrow
@ -286,6 +286,10 @@ def create_mock_trades_with_leverage(fee, use_db: bool = True):
Trade.query.session.flush()
def get_sides(is_short: bool) -> Tuple[str, str]:
return ("sell", "buy") if is_short else ("buy", "sell")
@pytest.fixture(autouse=True)
def patch_coingekko(mocker) -> None:
"""

35
tests/exchange/test_binance.py
View File

@ -1,3 +1,4 @@
from datetime import datetime, timezone
from random import randint
from unittest.mock import MagicMock
@ -5,7 +6,7 @@ import ccxt
import pytest
from freqtrade.exceptions import DependencyException, InvalidOrderException, OperationalException
from tests.conftest import get_patched_exchange
from tests.conftest import get_mock_coro, get_patched_exchange, log_has_re
from tests.exchange.test_exchange import ccxt_exceptionhandlers
@ -105,3 +106,35 @@ def test_stoploss_adjust_binance(mocker, default_conf):
# Test with invalid order case
order['type'] = 'stop_loss'
assert not exchange.stoploss_adjust(1501, order)
@pytest.mark.asyncio
async def test__async_get_historic_ohlcv_binance(default_conf, mocker, caplog):
ohlcv = [
[
int((datetime.now(timezone.utc).timestamp() - 1000) * 1000),
1, # open
2, # high
3, # low
4, # close
5, # volume (in quote currency)
]
]
exchange = get_patched_exchange(mocker, default_conf, id='binance')
# Monkey-patch async function
exchange._api_async.fetch_ohlcv = get_mock_coro(ohlcv)
pair = 'ETH/BTC'
res = await exchange._async_get_historic_ohlcv(pair, "5m",
1500000000000, is_new_pair=False)
# Call with very old timestamp - causes tons of requests
assert exchange._api_async.fetch_ohlcv.call_count > 400
# assert res == ohlcv
exchange._api_async.fetch_ohlcv.reset_mock()
res = await exchange._async_get_historic_ohlcv(pair, "5m", 1500000000000, is_new_pair=True)
# Called twice - one "init" call - and one to get the actual data.
assert exchange._api_async.fetch_ohlcv.call_count == 2
assert res == ohlcv
assert log_has_re(r"Candle-data for ETH/BTC available starting with .*", caplog)

2
tests/exchange/test_ccxt_compat.py
View File

@ -54,6 +54,8 @@ EXCHANGES = {
def exchange_conf():
config = get_default_conf((Path(__file__).parent / "testdata").resolve())
config['exchange']['pair_whitelist'] = []
config['exchange']['key'] = ''
config['exchange']['secret'] = ''
config['dry_run'] = False
return config

56
tests/exchange/test_exchange.py
View File

@ -1,5 +1,6 @@
import copy
import logging
from copy import deepcopy
from datetime import datetime, timedelta, timezone
from math import isclose
from random import randint
@ -14,7 +15,7 @@ from freqtrade.exceptions import (DDosProtection, DependencyException, InvalidOr
OperationalException, PricingError, TemporaryError)
from freqtrade.exchange import Binance, Bittrex, Exchange, Kraken
from freqtrade.exchange.common import (API_FETCH_ORDER_RETRY_COUNT, API_RETRY_COUNT,
calculate_backoff)
calculate_backoff, remove_credentials)
from freqtrade.exchange.exchange import (market_is_active, timeframe_to_minutes, timeframe_to_msecs,
timeframe_to_next_date, timeframe_to_prev_date,
timeframe_to_seconds)
@ -78,6 +79,22 @@ def test_init(default_conf, mocker, caplog):
assert log_has('Instance is running with dry_run enabled', caplog)
def test_remove_credentials(default_conf, caplog) -> None:
conf = deepcopy(default_conf)
conf['dry_run'] = False
remove_credentials(conf)
assert conf['exchange']['key'] != ''
assert conf['exchange']['secret'] != ''
conf['dry_run'] = True
remove_credentials(conf)
assert conf['exchange']['key'] == ''
assert conf['exchange']['secret'] == ''
assert conf['exchange']['password'] == ''
assert conf['exchange']['uid'] == ''
def test_init_ccxt_kwargs(default_conf, mocker, caplog):
mocker.patch('freqtrade.exchange.Exchange._load_markets', MagicMock(return_value={}))
mocker.patch('freqtrade.exchange.Exchange.validate_stakecurrency')
@ -108,6 +125,13 @@ def test_init_ccxt_kwargs(default_conf, mocker, caplog):
assert hasattr(ex._api_async, 'TestKWARG')
assert log_has("Applying additional ccxt config: {'TestKWARG': 11, 'TestKWARG44': 11}", caplog)
assert log_has(asynclogmsg, caplog)
# Test additional headers case
Exchange._headers = {'hello': 'world'}
ex = Exchange(conf)
assert log_has("Applying additional ccxt config: {'TestKWARG': 11, 'TestKWARG44': 11}", caplog)
assert ex._api.headers == {'hello': 'world'}
Exchange._headers = {}
def test_destroy(default_conf, mocker, caplog):
@ -178,7 +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",
@ -1544,6 +1568,32 @@ def test_get_historic_ohlcv_as_df(default_conf, mocker, exchange_name):
assert 'high' in ret.columns
@pytest.mark.asyncio
@pytest.mark.parametrize("exchange_name", EXCHANGES)
async def test__async_get_historic_ohlcv(default_conf, mocker, caplog, exchange_name):
ohlcv = [
[
int((datetime.now(timezone.utc).timestamp() - 1000) * 1000),
1, # open
2, # high
3, # low
4, # close
5, # volume (in quote currency)
]
]
exchange = get_patched_exchange(mocker, default_conf, id=exchange_name)
# Monkey-patch async function
exchange._api_async.fetch_ohlcv = get_mock_coro(ohlcv)
pair = 'ETH/USDT'
res = await exchange._async_get_historic_ohlcv(pair, "5m",
1500000000000, is_new_pair=False)
# Call with very old timestamp - causes tons of requests
assert exchange._api_async.fetch_ohlcv.call_count > 200
assert res[0] == ohlcv[0]
assert log_has_re(r'Downloaded data for .* with length .*\.', caplog)
def test_refresh_latest_ohlcv(mocker, default_conf, caplog) -> None:
ohlcv = [
[
@ -2431,7 +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

2
tests/optimize/conftest.py
View File

@ -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,

207
tests/optimize/hyperopts/hyperopt_test_sep_file.py
View File

@ -1,207 +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'] == 'boll':
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(['boll', '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-boll':
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-boll',
'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

271
tests/optimize/hyperopts/short_hyperopt.py
View File

@ -1,271 +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 DefaultHyperOpt(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.
"""
long_conditions = []
short_conditions = []
# GUARDS AND TRENDS
if 'mfi-enabled' in params and params['mfi-enabled']:
long_conditions.append(dataframe['mfi'] < params['mfi-value'])
short_conditions.append(dataframe['mfi'] > params['short-mfi-value'])
if 'fastd-enabled' in params and params['fastd-enabled']:
long_conditions.append(dataframe['fastd'] < params['fastd-value'])
short_conditions.append(dataframe['fastd'] > params['short-fastd-value'])
if 'adx-enabled' in params and params['adx-enabled']:
long_conditions.append(dataframe['adx'] > params['adx-value'])
short_conditions.append(dataframe['adx'] < params['short-adx-value'])
if 'rsi-enabled' in params and params['rsi-enabled']:
long_conditions.append(dataframe['rsi'] < params['rsi-value'])
short_conditions.append(dataframe['rsi'] > params['short-rsi-value'])
# TRIGGERS
if 'trigger' in params:
if params['trigger'] == 'boll':
long_conditions.append(dataframe['close'] < dataframe['bb_lowerband'])
short_conditions.append(dataframe['close'] > dataframe['bb_upperband'])
if params['trigger'] == 'macd_cross_signal':
long_conditions.append(qtpylib.crossed_above(
dataframe['macd'],
dataframe['macdsignal']
))
short_conditions.append(qtpylib.crossed_below(
dataframe['macd'],
dataframe['macdsignal']
))
if params['trigger'] == 'sar_reversal':
long_conditions.append(qtpylib.crossed_above(
dataframe['close'],
dataframe['sar']
))
short_conditions.append(qtpylib.crossed_below(
dataframe['close'],
dataframe['sar']
))
if long_conditions:
dataframe.loc[
reduce(lambda x, y: x & y, long_conditions),
'buy'] = 1
if short_conditions:
dataframe.loc[
reduce(lambda x, y: x & y, short_conditions),
'enter_short'] = 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'),
Integer(75, 90, name='short-mfi-value'),
Integer(55, 85, name='short-fastd-value'),
Integer(50, 80, name='short-adx-value'),
Integer(60, 80, name='short-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(['boll', '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.
"""
exit_long_conditions = []
exit_short_conditions = []
# GUARDS AND TRENDS
if 'sell-mfi-enabled' in params and params['sell-mfi-enabled']:
exit_long_conditions.append(dataframe['mfi'] > params['sell-mfi-value'])
exit_short_conditions.append(dataframe['mfi'] < params['exit-short-mfi-value'])
if 'sell-fastd-enabled' in params and params['sell-fastd-enabled']:
exit_long_conditions.append(dataframe['fastd'] > params['sell-fastd-value'])
exit_short_conditions.append(dataframe['fastd'] < params['exit-short-fastd-value'])
if 'sell-adx-enabled' in params and params['sell-adx-enabled']:
exit_long_conditions.append(dataframe['adx'] < params['sell-adx-value'])
exit_short_conditions.append(dataframe['adx'] > params['exit-short-adx-value'])
if 'sell-rsi-enabled' in params and params['sell-rsi-enabled']:
exit_long_conditions.append(dataframe['rsi'] > params['sell-rsi-value'])
exit_short_conditions.append(dataframe['rsi'] < params['exit-short-rsi-value'])
# TRIGGERS
if 'sell-trigger' in params:
if params['sell-trigger'] == 'sell-boll':
exit_long_conditions.append(dataframe['close'] > dataframe['bb_upperband'])
exit_short_conditions.append(dataframe['close'] < dataframe['bb_lowerband'])
if params['sell-trigger'] == 'sell-macd_cross_signal':
exit_long_conditions.append(qtpylib.crossed_above(
dataframe['macdsignal'],
dataframe['macd']
))
exit_short_conditions.append(qtpylib.crossed_below(
dataframe['macdsignal'],
dataframe['macd']
))
if params['sell-trigger'] == 'sell-sar_reversal':
exit_long_conditions.append(qtpylib.crossed_above(
dataframe['sar'],
dataframe['close']
))
exit_short_conditions.append(qtpylib.crossed_below(
dataframe['sar'],
dataframe['close']
))
if exit_long_conditions:
dataframe.loc[
reduce(lambda x, y: x & y, exit_long_conditions),
'sell'] = 1
if exit_short_conditions:
dataframe.loc[
reduce(lambda x, y: x & y, exit_short_conditions),
'exit-short'] = 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'),
Integer(1, 25, name='exit-short-mfi-value'),
Integer(1, 50, name='exit-short-fastd-value'),
Integer(1, 50, name='exit-short-adx-value'),
Integer(1, 40, name='exit-short-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-boll',
'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
dataframe.loc[
(
(dataframe['close'] > dataframe['bb_upperband']) &
(dataframe['mfi'] < 84) &
(dataframe['adx'] > 75) &
(dataframe['rsi'] < 79)
),
'enter_short'] = 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
dataframe.loc[
(
(qtpylib.crossed_below(
dataframe['macdsignal'], dataframe['macd']
)) &
(dataframe['fastd'] < 46)
),
'exit_short'] = 1
return dataframe

229
tests/optimize/test_hyperopt.py
View File

@ -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
# TODO-lev: This file
@ -34,7 +31,7 @@ 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)
@ -66,7 +63,7 @@ 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',
@ -118,7 +115,7 @@ 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'
]
@ -136,47 +133,6 @@ 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)
@ -187,9 +143,7 @@ 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',
]
@ -199,7 +153,7 @@ 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)
@ -213,10 +167,8 @@ def test_start(mocker, hyperopt_conf, caplog) -> None:
'--epochs', '5'
]
pargs = get_args(args)
start_hyperopt(pargs)
assert log_has('Starting freqtrade in Hyperopt mode', caplog)
assert start_mock.call_count == 1
with pytest.raises(OperationalException, match=r"Using separate Hyperopt files has been.*"):
start_hyperopt(pargs)
def test_start_no_data(mocker, hyperopt_conf) -> None:
@ -228,11 +180,11 @@ 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'
]
@ -250,7 +202,7 @@ def test_start_filelock(mocker, hyperopt_conf, caplog) -> None:
args = [
'hyperopt',
'--config', 'config.json',
'--hyperopt', 'HyperoptTestSepFile',
'--strategy', 'HyperoptableStrategy',
'--hyperopt-loss', 'SharpeHyperOptLossDaily',
'--epochs', '5'
]
@ -430,74 +382,14 @@ 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,
'short-adx-value': 80,
'short-fastd-value': 80,
'short-mfi-value': 80,
'short-rsi-value': 80,
'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,
'exit-short-adx-value': 80,
'exit-short-fastd-value': 25,
'exit-short-mfi-value': 20,
'exit-short-rsi-value': 80,
'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,
@ -538,24 +430,12 @@ 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,
@ -575,29 +455,19 @@ 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,
@ -819,11 +689,6 @@ 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()
@ -854,16 +719,14 @@ 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()
@ -900,11 +763,6 @@ def test_simplified_interface_buy(mocker, hyperopt_conf, capsys) -> None:
hyperopt.backtesting.strategy.advise_all_indicators = MagicMock()
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
del hyperopt.custom_hyperopt.__class__.sell_indicator_space
hyperopt.start()
parallel.assert_called_once()
@ -954,11 +812,6 @@ def test_simplified_interface_sell(mocker, hyperopt_conf, capsys) -> None:
hyperopt.backtesting.strategy.advise_all_indicators = MagicMock()
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()
@ -975,13 +828,12 @@ 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',
@ -990,6 +842,8 @@ 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)
@ -999,8 +853,6 @@ 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()
@ -1010,7 +862,6 @@ 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),
@ -1036,6 +887,10 @@ def test_in_strategy_auto_hyperopt(mocker, hyperopt_conf, tmpdir, fee) -> None:
assert hyperopt.backtesting.strategy.buy_rsi.value != 35
assert hyperopt.backtesting.strategy.sell_rsi.value != 74
hyperopt.custom_hyperopt.generate_estimator = lambda *args, **kwargs: 'ET1'
with pytest.raises(OperationalException, match="Estimator ET1 not supported."):
hyperopt.get_optimizer([], 2)
def test_SKDecimal():
space = SKDecimal(1, 2, decimals=2)

80
tests/plugins/test_pairlist.py
View File

@ -4,6 +4,7 @@ import time
from unittest.mock import MagicMock, PropertyMock
import pytest
import time_machine
from freqtrade.constants import AVAILABLE_PAIRLISTS
from freqtrade.exceptions import OperationalException
@ -815,32 +816,63 @@ def test_agefilter_min_days_listed_too_large(mocker, default_conf, markets, tick
def test_agefilter_caching(mocker, markets, whitelist_conf_agefilter, tickers, ohlcv_history):
ohlcv_data = {
('ETH/BTC', '1d'): ohlcv_history,
('TKN/BTC', '1d'): ohlcv_history,
('LTC/BTC', '1d'): ohlcv_history,
}
mocker.patch.multiple('freqtrade.exchange.Exchange',
markets=PropertyMock(return_value=markets),
exchange_has=MagicMock(return_value=True),
get_tickers=tickers
)
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
refresh_latest_ohlcv=MagicMock(return_value=ohlcv_data),
)
with time_machine.travel("2021-09-01 05:00:00 +00:00") as t:
ohlcv_data = {
('ETH/BTC', '1d'): ohlcv_history,
('TKN/BTC', '1d'): ohlcv_history,
('LTC/BTC', '1d'): ohlcv_history,
}
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
markets=PropertyMock(return_value=markets),
exchange_has=MagicMock(return_value=True),
get_tickers=tickers,
refresh_latest_ohlcv=MagicMock(return_value=ohlcv_data),
)
freqtrade = get_patched_freqtradebot(mocker, whitelist_conf_agefilter)
assert freqtrade.exchange.refresh_latest_ohlcv.call_count == 0
freqtrade.pairlists.refresh_pairlist()
assert len(freqtrade.pairlists.whitelist) == 3
assert freqtrade.exchange.refresh_latest_ohlcv.call_count > 0
freqtrade = get_patched_freqtradebot(mocker, whitelist_conf_agefilter)
assert freqtrade.exchange.refresh_latest_ohlcv.call_count == 0
freqtrade.pairlists.refresh_pairlist()
assert len(freqtrade.pairlists.whitelist) == 3
assert freqtrade.exchange.refresh_latest_ohlcv.call_count > 0
previous_call_count = freqtrade.exchange.refresh_latest_ohlcv.call_count
freqtrade.pairlists.refresh_pairlist()
assert len(freqtrade.pairlists.whitelist) == 3
# Called once for XRP/BTC
assert freqtrade.exchange.refresh_latest_ohlcv.call_count == previous_call_count + 1
freqtrade.pairlists.refresh_pairlist()
assert len(freqtrade.pairlists.whitelist) == 3
# Call to XRP/BTC cached
assert freqtrade.exchange.refresh_latest_ohlcv.call_count == 2
ohlcv_data = {
('ETH/BTC', '1d'): ohlcv_history,
('TKN/BTC', '1d'): ohlcv_history,
('LTC/BTC', '1d'): ohlcv_history,
('XRP/BTC', '1d'): ohlcv_history.iloc[[0]],
}
mocker.patch('freqtrade.exchange.Exchange.refresh_latest_ohlcv', return_value=ohlcv_data)
freqtrade.pairlists.refresh_pairlist()
assert len(freqtrade.pairlists.whitelist) == 3
assert freqtrade.exchange.refresh_latest_ohlcv.call_count == 1
# Move to next day
t.move_to("2021-09-02 01:00:00 +00:00")
mocker.patch('freqtrade.exchange.Exchange.refresh_latest_ohlcv', return_value=ohlcv_data)
freqtrade.pairlists.refresh_pairlist()
assert len(freqtrade.pairlists.whitelist) == 3
assert freqtrade.exchange.refresh_latest_ohlcv.call_count == 1
# Move another day with fresh mocks (now the pair is old enough)
t.move_to("2021-09-03 01:00:00 +00:00")
# Called once for XRP/BTC
ohlcv_data = {
('ETH/BTC', '1d'): ohlcv_history,
('TKN/BTC', '1d'): ohlcv_history,
('LTC/BTC', '1d'): ohlcv_history,
('XRP/BTC', '1d'): ohlcv_history,
}
mocker.patch('freqtrade.exchange.Exchange.refresh_latest_ohlcv', return_value=ohlcv_data)
freqtrade.pairlists.refresh_pairlist()
assert len(freqtrade.pairlists.whitelist) == 4
# Called once (only for XRP/BTC)
assert freqtrade.exchange.refresh_latest_ohlcv.call_count == 1
def test_OffsetFilter_error(mocker, whitelist_conf) -> None:

2
tests/plugins/test_pairlocks.py
View File

@ -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))

9
tests/strategy/test_interface.py
View File

@ -1,5 +1,4 @@
# pragma pylint: disable=missing-docstring, C0103
from freqtrade.enums.signaltype import SignalDirection
import logging
from datetime import datetime, timedelta, timezone
from pathlib import Path
@ -13,6 +12,7 @@ from freqtrade.configuration import TimeRange
from freqtrade.data.dataprovider import DataProvider
from freqtrade.data.history import load_data
from freqtrade.enums import SellType
from freqtrade.enums.signaltype import SignalDirection
from freqtrade.exceptions import OperationalException, StrategyError
from freqtrade.optimize.space import SKDecimal
from freqtrade.persistence import PairLocks, Trade
@ -48,7 +48,7 @@ def test_returns_latest_signal(ohlcv_history):
mocked_history.loc[1, 'enter_long'] = 1
assert _STRATEGY.get_entry_signal('ETH/BTC', '5m', mocked_history
) == (SignalDirection.LONG, None)
) == (SignalDirection.LONG, None)
assert _STRATEGY.get_exit_signal('ETH/BTC', '5m', mocked_history) == (True, False)
assert _STRATEGY.get_exit_signal('ETH/BTC', '5m', mocked_history, True) == (False, False)
mocked_history.loc[1, 'exit_long'] = 0
@ -776,11 +776,16 @@ def test_auto_hyperopt_interface(default_conf):
PairLocks.timeframe = default_conf['timeframe']
strategy = StrategyResolver.load_strategy(default_conf)
with pytest.raises(OperationalException):
next(strategy.enumerate_parameters('deadBeef'))
assert strategy.buy_rsi.value == strategy.buy_params['buy_rsi']
# PlusDI is NOT in the buy-params, so default should be used
assert strategy.buy_plusdi.value == 0.5
assert strategy.sell_rsi.value == strategy.sell_params['sell_rsi']
assert repr(strategy.sell_rsi) == 'IntParameter(74)'
# Parameter is disabled - so value from sell_param dict will NOT be used.
assert strategy.sell_minusdi.value == 0.5
all_params = strategy.detect_all_parameters()

15
tests/test_configuration.py
View File

@ -11,8 +11,7 @@ import pytest
from jsonschema import ValidationError
from freqtrade.commands import Arguments
from freqtrade.configuration import (Configuration, check_exchange, remove_credentials,
validate_config_consistency)
from freqtrade.configuration import Configuration, check_exchange, validate_config_consistency
from freqtrade.configuration.config_validation import validate_config_schema
from freqtrade.configuration.deprecated_settings import (check_conflicting_settings,
process_deprecated_setting,
@ -617,18 +616,6 @@ def test_check_exchange(default_conf, caplog) -> None:
check_exchange(default_conf)
def test_remove_credentials(default_conf, caplog) -> None:
conf = deepcopy(default_conf)
conf['dry_run'] = False
remove_credentials(conf)
assert conf['dry_run'] is True
assert conf['exchange']['key'] == ''
assert conf['exchange']['secret'] == ''
assert conf['exchange']['password'] == ''
assert conf['exchange']['uid'] == ''
def test_cli_verbose_with_params(default_conf, mocker, caplog) -> None:
patched_configuration_load_config_file(mocker, default_conf)

8
tests/test_directory_operations.py
View File

@ -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')

84
tests/test_freqtradebot.py
View File

@ -518,6 +518,7 @@ def test_enter_positions_global_pairlock(default_conf, ticker, limit_buy_order,
# 0 trades, but it's not because of pairlock.
assert n == 0
assert not log_has_re(message, caplog)
caplog.clear()
PairLocks.lock_pair('*', arrow.utcnow().shift(minutes=20).datetime, 'Just because')
n = freqtrade.enter_positions()
@ -1087,6 +1088,7 @@ def test_handle_stoploss_on_exchange(mocker, default_conf, fee, caplog,
assert log_has_re(r'STOP_LOSS_LIMIT is hit for Trade\(id=1, .*\)\.', caplog)
assert trade.stoploss_order_id is None
assert trade.is_open is False
caplog.clear()
mocker.patch(
'freqtrade.exchange.Binance.stoploss',
@ -1191,7 +1193,7 @@ def test_create_stoploss_order_invalid_order(mocker, default_conf, caplog, fee,
assert trade.stoploss_order_id is None
assert trade.sell_reason == SellType.EMERGENCY_SELL.value
assert log_has("Unable to place a stoploss order on exchange. ", caplog)
assert log_has("Selling the trade forcefully", caplog)
assert log_has("Exiting the trade forcefully", caplog)
# Should call a market sell
assert create_order_mock.call_count == 2
@ -1660,7 +1662,7 @@ def test_enter_positions(mocker, default_conf, caplog) -> None:
MagicMock(return_value=False))
n = freqtrade.enter_positions()
assert n == 0
assert log_has('Found no buy signals for whitelisted currencies. Trying again...', caplog)
assert log_has('Found no enter signals for whitelisted currencies. Trying again...', caplog)
# create_trade should be called once for every pair in the whitelist.
assert mock_ct.call_count == len(default_conf['exchange']['pair_whitelist'])
@ -1721,7 +1723,7 @@ def test_exit_positions_exception(mocker, default_conf, limit_buy_order, caplog)
)
n = freqtrade.exit_positions(trades)
assert n == 0
assert log_has('Unable to sell trade ETH/BTC: ', caplog)
assert log_has('Unable to exit trade ETH/BTC: ', caplog)
def test_update_trade_state(mocker, default_conf, limit_buy_order, caplog) -> None:
@ -1744,10 +1746,12 @@ def test_update_trade_state(mocker, default_conf, limit_buy_order, caplog) -> No
)
assert not freqtrade.update_trade_state(trade, None)
assert log_has_re(r'Orderid for trade .* is empty.', caplog)
caplog.clear()
# Add datetime explicitly since sqlalchemy defaults apply only once written to database
freqtrade.update_trade_state(trade, '123')
# Test amount not modified by fee-logic
assert not log_has_re(r'Applying fee to .*', caplog)
caplog.clear()
assert trade.open_order_id is None
assert trade.amount == limit_buy_order['amount']
@ -2454,8 +2458,8 @@ def test_check_handle_timedout_exception(default_conf, ticker, open_trade, mocke
mocker.patch.multiple(
'freqtrade.freqtradebot.FreqtradeBot',
handle_cancel_buy=MagicMock(),
handle_cancel_sell=MagicMock(),
handle_cancel_enter=MagicMock(),
handle_cancel_exit=MagicMock(),
)
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
@ -2476,7 +2480,7 @@ def test_check_handle_timedout_exception(default_conf, ticker, open_trade, mocke
caplog)
def test_handle_cancel_buy(mocker, caplog, default_conf, limit_buy_order) -> None:
def test_handle_cancel_enter(mocker, caplog, default_conf, limit_buy_order) -> None:
patch_RPCManager(mocker)
patch_exchange(mocker)
cancel_buy_order = deepcopy(limit_buy_order)
@ -2487,7 +2491,7 @@ def test_handle_cancel_buy(mocker, caplog, default_conf, limit_buy_order) -> Non
mocker.patch('freqtrade.exchange.Exchange.cancel_order_with_result', cancel_order_mock)
freqtrade = FreqtradeBot(default_conf)
freqtrade._notify_buy_cancel = MagicMock()
freqtrade._notify_enter_cancel = MagicMock()
trade = MagicMock()
trade.pair = 'LTC/USDT'
@ -2495,46 +2499,46 @@ def test_handle_cancel_buy(mocker, caplog, default_conf, limit_buy_order) -> Non
limit_buy_order['filled'] = 0.0
limit_buy_order['status'] = 'open'
reason = CANCEL_REASON['TIMEOUT']
assert freqtrade.handle_cancel_buy(trade, limit_buy_order, reason)
assert freqtrade.handle_cancel_enter(trade, limit_buy_order, reason)
assert cancel_order_mock.call_count == 1
cancel_order_mock.reset_mock()
caplog.clear()
limit_buy_order['filled'] = 0.01
assert not freqtrade.handle_cancel_buy(trade, limit_buy_order, reason)
assert not freqtrade.handle_cancel_enter(trade, limit_buy_order, reason)
assert cancel_order_mock.call_count == 0
assert log_has_re("Order .* for .* not cancelled, as the filled amount.* unsellable.*", caplog)
caplog.clear()
cancel_order_mock.reset_mock()
limit_buy_order['filled'] = 2
assert not freqtrade.handle_cancel_buy(trade, limit_buy_order, reason)
assert not freqtrade.handle_cancel_enter(trade, limit_buy_order, reason)
assert cancel_order_mock.call_count == 1
# Order remained open for some reason (cancel failed)
cancel_buy_order['status'] = 'open'
cancel_order_mock = MagicMock(return_value=cancel_buy_order)
mocker.patch('freqtrade.exchange.Exchange.cancel_order_with_result', cancel_order_mock)
assert not freqtrade.handle_cancel_buy(trade, limit_buy_order, reason)
assert not freqtrade.handle_cancel_enter(trade, limit_buy_order, reason)
assert log_has_re(r"Order .* for .* not cancelled.", caplog)
@pytest.mark.parametrize("limit_buy_order_canceled_empty", ['binance', 'ftx', 'kraken', 'bittrex'],
indirect=['limit_buy_order_canceled_empty'])
def test_handle_cancel_buy_exchanges(mocker, caplog, default_conf,
limit_buy_order_canceled_empty) -> None:
def test_handle_cancel_enter_exchanges(mocker, caplog, default_conf,
limit_buy_order_canceled_empty) -> None:
patch_RPCManager(mocker)
patch_exchange(mocker)
cancel_order_mock = mocker.patch(
'freqtrade.exchange.Exchange.cancel_order_with_result',
return_value=limit_buy_order_canceled_empty)
nofiy_mock = mocker.patch('freqtrade.freqtradebot.FreqtradeBot._notify_buy_cancel')
nofiy_mock = mocker.patch('freqtrade.freqtradebot.FreqtradeBot._notify_enter_cancel')
freqtrade = FreqtradeBot(default_conf)
reason = CANCEL_REASON['TIMEOUT']
trade = MagicMock()
trade.pair = 'LTC/ETH'
assert freqtrade.handle_cancel_buy(trade, limit_buy_order_canceled_empty, reason)
assert freqtrade.handle_cancel_enter(trade, limit_buy_order_canceled_empty, reason)
assert cancel_order_mock.call_count == 0
assert log_has_re(r'Buy order fully cancelled. Removing .* from database\.', caplog)
assert nofiy_mock.call_count == 1
@ -2546,8 +2550,8 @@ def test_handle_cancel_buy_exchanges(mocker, caplog, default_conf,
'String Return value',
123
])
def test_handle_cancel_buy_corder_empty(mocker, default_conf, limit_buy_order,
cancelorder) -> None:
def test_handle_cancel_enter_corder_empty(mocker, default_conf, limit_buy_order,
cancelorder) -> None:
patch_RPCManager(mocker)
patch_exchange(mocker)
cancel_order_mock = MagicMock(return_value=cancelorder)
@ -2557,7 +2561,7 @@ def test_handle_cancel_buy_corder_empty(mocker, default_conf, limit_buy_order,
)
freqtrade = FreqtradeBot(default_conf)
freqtrade._notify_buy_cancel = MagicMock()
freqtrade._notify_enter_cancel = MagicMock()
trade = MagicMock()
trade.pair = 'LTC/USDT'
@ -2565,16 +2569,16 @@ def test_handle_cancel_buy_corder_empty(mocker, default_conf, limit_buy_order,
limit_buy_order['filled'] = 0.0
limit_buy_order['status'] = 'open'
reason = CANCEL_REASON['TIMEOUT']
assert freqtrade.handle_cancel_buy(trade, limit_buy_order, reason)
assert freqtrade.handle_cancel_enter(trade, limit_buy_order, reason)
assert cancel_order_mock.call_count == 1
cancel_order_mock.reset_mock()
limit_buy_order['filled'] = 1.0
assert not freqtrade.handle_cancel_buy(trade, limit_buy_order, reason)
assert not freqtrade.handle_cancel_enter(trade, limit_buy_order, reason)
assert cancel_order_mock.call_count == 1
def test_handle_cancel_sell_limit(mocker, default_conf, fee) -> None:
def test_handle_cancel_exit_limit(mocker, default_conf, fee) -> None:
send_msg_mock = patch_RPCManager(mocker)
patch_exchange(mocker)
cancel_order_mock = MagicMock()
@ -2600,26 +2604,26 @@ def test_handle_cancel_sell_limit(mocker, default_conf, fee) -> None:
'amount': 1,
'status': "open"}
reason = CANCEL_REASON['TIMEOUT']
assert freqtrade.handle_cancel_sell(trade, order, reason)
assert freqtrade.handle_cancel_exit(trade, order, reason)
assert cancel_order_mock.call_count == 1
assert send_msg_mock.call_count == 1
send_msg_mock.reset_mock()
order['amount'] = 2
assert freqtrade.handle_cancel_sell(trade, order, reason
assert freqtrade.handle_cancel_exit(trade, order, reason
) == CANCEL_REASON['PARTIALLY_FILLED_KEEP_OPEN']
# Assert cancel_order was not called (callcount remains unchanged)
assert cancel_order_mock.call_count == 1
assert send_msg_mock.call_count == 1
assert freqtrade.handle_cancel_sell(trade, order, reason
assert freqtrade.handle_cancel_exit(trade, order, reason
) == CANCEL_REASON['PARTIALLY_FILLED_KEEP_OPEN']
# Message should not be iterated again
assert trade.sell_order_status == CANCEL_REASON['PARTIALLY_FILLED_KEEP_OPEN']
assert send_msg_mock.call_count == 1
def test_handle_cancel_sell_cancel_exception(mocker, default_conf) -> None:
def test_handle_cancel_exit_cancel_exception(mocker, default_conf) -> None:
patch_RPCManager(mocker)
patch_exchange(mocker)
mocker.patch(
@ -2632,7 +2636,7 @@ def test_handle_cancel_sell_cancel_exception(mocker, default_conf) -> None:
order = {'remaining': 1,
'amount': 1,
'status': "open"}
assert freqtrade.handle_cancel_sell(trade, order, reason) == 'error cancelling order'
assert freqtrade.handle_cancel_exit(trade, order, reason) == 'error cancelling order'
def test_execute_trade_exit_up(default_conf, ticker, fee, ticker_sell_up, mocker) -> None:
@ -3304,7 +3308,7 @@ def test_sell_not_enough_balance(default_conf, limit_buy_order, limit_buy_order_
assert trade.amount != amnt
def test__safe_sell_amount(default_conf, fee, caplog, mocker):
def test__safe_exit_amount(default_conf, fee, caplog, mocker):
patch_RPCManager(mocker)
patch_exchange(mocker)
amount = 95.33
@ -3324,17 +3328,17 @@ def test__safe_sell_amount(default_conf, fee, caplog, mocker):
patch_get_signal(freqtrade)
wallet_update.reset_mock()
assert freqtrade._safe_sell_amount(trade.pair, trade.amount) == amount_wallet
assert freqtrade._safe_exit_amount(trade.pair, trade.amount) == amount_wallet
assert log_has_re(r'.*Falling back to wallet-amount.', caplog)
assert wallet_update.call_count == 1
caplog.clear()
wallet_update.reset_mock()
assert freqtrade._safe_sell_amount(trade.pair, amount_wallet) == amount_wallet
assert freqtrade._safe_exit_amount(trade.pair, amount_wallet) == amount_wallet
assert not log_has_re(r'.*Falling back to wallet-amount.', caplog)
assert wallet_update.call_count == 1
def test__safe_sell_amount_error(default_conf, fee, caplog, mocker):
def test__safe_exit_amount_error(default_conf, fee, caplog, mocker):
patch_RPCManager(mocker)
patch_exchange(mocker)
amount = 95.33
@ -3351,8 +3355,8 @@ def test__safe_sell_amount_error(default_conf, fee, caplog, mocker):
)
freqtrade = FreqtradeBot(default_conf)
patch_get_signal(freqtrade)
with pytest.raises(DependencyException, match=r"Not enough amount to sell."):
assert freqtrade._safe_sell_amount(trade.pair, trade.amount)
with pytest.raises(DependencyException, match=r"Not enough amount to exit."):
assert freqtrade._safe_exit_amount(trade.pair, trade.amount)
def test_locked_pairs(default_conf, ticker, fee, ticker_sell_down, mocker, caplog) -> None:
@ -3526,6 +3530,7 @@ def test_trailing_stop_loss_positive(default_conf, limit_buy_order, limit_buy_or
assert log_has("ETH/BTC - Using positive stoploss: 0.01 offset: 0 profit: 0.2666%", caplog)
assert log_has("ETH/BTC - Adjusting stoploss...", caplog)
assert trade.stop_loss == 0.0000138501
caplog.clear()
mocker.patch('freqtrade.exchange.Exchange.fetch_ticker',
MagicMock(return_value={
@ -3586,6 +3591,7 @@ def test_trailing_stop_loss_offset(default_conf, limit_buy_order, limit_buy_orde
assert log_has("ETH/BTC - Using positive stoploss: 0.01 offset: 0.011 profit: 0.2666%", caplog)
assert log_has("ETH/BTC - Adjusting stoploss...", caplog)
assert trade.stop_loss == 0.0000138501
caplog.clear()
mocker.patch('freqtrade.exchange.Exchange.fetch_ticker',
MagicMock(return_value={
@ -3650,6 +3656,7 @@ def test_tsl_only_offset_reached(default_conf, limit_buy_order, limit_buy_order_
assert not log_has("ETH/BTC - Adjusting stoploss...", caplog)
assert trade.stop_loss == 0.0000098910
caplog.clear()
# price rises above the offset (rises 12% when the offset is 5.5%)
mocker.patch('freqtrade.exchange.Exchange.fetch_ticker',
@ -4317,8 +4324,8 @@ def test_cancel_all_open_orders(mocker, default_conf, fee, limit_buy_order, limi
mocker.patch('freqtrade.exchange.Exchange.fetch_order',
side_effect=[
ExchangeError(), limit_sell_order, limit_buy_order, limit_sell_order])
buy_mock = mocker.patch('freqtrade.freqtradebot.FreqtradeBot.handle_cancel_buy')
sell_mock = mocker.patch('freqtrade.freqtradebot.FreqtradeBot.handle_cancel_sell')
buy_mock = mocker.patch('freqtrade.freqtradebot.FreqtradeBot.handle_cancel_enter')
sell_mock = mocker.patch('freqtrade.freqtradebot.FreqtradeBot.handle_cancel_exit')
freqtrade = get_patched_freqtradebot(mocker, default_conf)
create_mock_trades(fee)
@ -4352,6 +4359,7 @@ def test_update_open_orders(mocker, default_conf, fee, caplog):
freqtrade.update_open_orders()
assert not log_has_re(r"Error updating Order .*", caplog)
caplog.clear()
freqtrade.config['dry_run'] = False
freqtrade.update_open_orders()
@ -4433,14 +4441,14 @@ def test_update_closed_trades_without_assigned_fees(mocker, default_conf, fee):
@pytest.mark.usefixtures("init_persistence")
def test_reupdate_buy_order_fees(mocker, default_conf, fee, caplog):
def test_reupdate_enter_order_fees(mocker, default_conf, fee, caplog):
freqtrade = get_patched_freqtradebot(mocker, default_conf)
mock_uts = mocker.patch('freqtrade.freqtradebot.FreqtradeBot.update_trade_state')
create_mock_trades(fee)
trades = Trade.get_trades().all()
freqtrade.reupdate_buy_order_fees(trades[0])
freqtrade.reupdate_enter_order_fees(trades[0])
assert log_has_re(r"Trying to reupdate buy fees for .*", caplog)
assert mock_uts.call_count == 1
assert mock_uts.call_args_list[0][0][0] == trades[0]
@ -4463,7 +4471,7 @@ def test_reupdate_buy_order_fees(mocker, default_conf, fee, caplog):
)
Trade.query.session.add(trade)
freqtrade.reupdate_buy_order_fees(trade)
freqtrade.reupdate_enter_order_fees(trade)
assert log_has_re(r"Trying to reupdate buy fees for .*", caplog)
assert mock_uts.call_count == 0
assert not log_has_re(r"Updating buy-fee on trade .* for order .*\.", caplog)
@ -4473,7 +4481,7 @@ def test_reupdate_buy_order_fees(mocker, default_conf, fee, caplog):
def test_handle_insufficient_funds(mocker, default_conf, fee):
freqtrade = get_patched_freqtradebot(mocker, default_conf)
mock_rlo = mocker.patch('freqtrade.freqtradebot.FreqtradeBot.refind_lost_order')
mock_bof = mocker.patch('freqtrade.freqtradebot.FreqtradeBot.reupdate_buy_order_fees')
mock_bof = mocker.patch('freqtrade.freqtradebot.FreqtradeBot.reupdate_enter_order_fees')
create_mock_trades(fee)
trades = Trade.get_trades().all()

4
tests/test_integration.py
View File

@ -70,7 +70,7 @@ def test_may_execute_exit_stoploss_on_exchange_multi(default_conf, ticker, fee,
mocker.patch.multiple(
'freqtrade.freqtradebot.FreqtradeBot',
create_stoploss_order=MagicMock(return_value=True),
_notify_sell=MagicMock(),
_notify_exit=MagicMock(),
)
mocker.patch("freqtrade.strategy.interface.IStrategy.should_exit", should_sell_mock)
wallets_mock = mocker.patch("freqtrade.wallets.Wallets.update", MagicMock())
@ -154,7 +154,7 @@ def test_forcebuy_last_unlimited(default_conf, ticker, fee, limit_buy_order, moc
mocker.patch.multiple(
'freqtrade.freqtradebot.FreqtradeBot',
create_stoploss_order=MagicMock(return_value=True),
_notify_sell=MagicMock(),
_notify_exit=MagicMock(),
)
should_sell_mock = MagicMock(side_effect=[
SellCheckTuple(sell_type=SellType.NONE),

32
tests/test_periodiccache.py Normal file
View File

@ -0,0 +1,32 @@
import time_machine
from freqtrade.configuration import PeriodicCache
def test_ttl_cache():
with time_machine.travel("2021-09-01 05:00:00 +00:00") as t:
cache = PeriodicCache(5, ttl=60)
cache1h = PeriodicCache(5, ttl=3600)
assert cache.timer() == 1630472400.0
cache['a'] = 1235
cache1h['a'] = 555123
assert 'a' in cache
assert 'a' in cache1h
t.move_to("2021-09-01 05:00:59 +00:00")
assert 'a' in cache
assert 'a' in cache1h
# Cache expired
t.move_to("2021-09-01 05:01:00 +00:00")
assert 'a' not in cache
assert 'a' in cache1h
t.move_to("2021-09-01 05:59:59 +00:00")
assert 'a' in cache1h
t.move_to("2021-09-01 06:00:00 +00:00")
assert 'a' not in cache1h

700
tests/test_persistence.py
View File

@ -13,7 +13,8 @@ from sqlalchemy import create_engine, inspect, text
from freqtrade import constants
from freqtrade.exceptions import DependencyException, OperationalException
from freqtrade.persistence import LocalTrade, Order, Trade, clean_dry_run_db, init_db
from tests.conftest import create_mock_trades, create_mock_trades_with_leverage, log_has, log_has_re
from tests.conftest import (create_mock_trades, create_mock_trades_with_leverage, get_sides,
log_has, log_has_re)
def test_init_create_session(default_conf):
@ -64,8 +65,10 @@ def test_init_dryrun_db(default_conf, tmpdir):
assert Path(filename).is_file()
@pytest.mark.parametrize('is_short', [False, True])
@pytest.mark.usefixtures("init_persistence")
def test_enter_exit_side(fee):
def test_enter_exit_side(fee, is_short):
enter_side, exit_side = get_sides(is_short)
trade = Trade(
id=2,
pair='ADA/USDT',
@ -77,20 +80,15 @@ def test_enter_exit_side(fee):
fee_open=fee.return_value,
fee_close=fee.return_value,
exchange='binance',
is_short=False,
is_short=is_short,
leverage=2.0
)
assert trade.enter_side == 'buy'
assert trade.exit_side == 'sell'
trade.is_short = True
assert trade.enter_side == 'sell'
assert trade.exit_side == 'buy'
assert trade.enter_side == enter_side
assert trade.exit_side == exit_side
@pytest.mark.usefixtures("init_persistence")
def test__set_stop_loss_isolated_liq(fee):
def test_set_stop_loss_isolated_liq(fee):
trade = Trade(
id=2,
pair='ADA/USDT',
@ -170,8 +168,32 @@ def test__set_stop_loss_isolated_liq(fee):
assert trade.initial_stop_loss == 0.09
@pytest.mark.parametrize('exchange,is_short,lev,minutes,rate,interest', [
("binance", False, 3, 10, 0.0005, round(0.0008333333333333334, 8)),
("binance", True, 3, 10, 0.0005, 0.000625),
("binance", False, 3, 295, 0.0005, round(0.004166666666666667, 8)),
("binance", True, 3, 295, 0.0005, round(0.0031249999999999997, 8)),
("binance", False, 3, 295, 0.00025, round(0.0020833333333333333, 8)),
("binance", True, 3, 295, 0.00025, round(0.0015624999999999999, 8)),
("binance", False, 5, 295, 0.0005, 0.005),
("binance", True, 5, 295, 0.0005, round(0.0031249999999999997, 8)),
("binance", False, 1, 295, 0.0005, 0.0),
("binance", True, 1, 295, 0.0005, 0.003125),
("kraken", False, 3, 10, 0.0005, 0.040),
("kraken", True, 3, 10, 0.0005, 0.030),
("kraken", False, 3, 295, 0.0005, 0.06),
("kraken", True, 3, 295, 0.0005, 0.045),
("kraken", False, 3, 295, 0.00025, 0.03),
("kraken", True, 3, 295, 0.00025, 0.0225),
("kraken", False, 5, 295, 0.0005, round(0.07200000000000001, 8)),
("kraken", True, 5, 295, 0.0005, 0.045),
("kraken", False, 1, 295, 0.0005, 0.0),
("kraken", True, 1, 295, 0.0005, 0.045),
])
@pytest.mark.usefixtures("init_persistence")
def test_interest(market_buy_order_usdt, fee):
def test_interest(market_buy_order_usdt, fee, exchange, is_short, lev, minutes, rate, interest):
"""
10min, 5hr limit trade on Binance/Kraken at 3x,5x leverage
fee: 0.25 % quote
@ -230,114 +252,27 @@ def test_interest(market_buy_order_usdt, fee):
stake_amount=20.0,
amount=30.0,
open_rate=2.0,
open_date=datetime.utcnow() - timedelta(hours=0, minutes=10),
open_date=datetime.utcnow() - timedelta(minutes=minutes),
fee_open=fee.return_value,
fee_close=fee.return_value,
exchange='binance',
leverage=3.0,
interest_rate=0.0005,
exchange=exchange,
leverage=lev,
interest_rate=rate,
is_short=is_short
)
# 10min, 3x leverage
# binance
assert round(float(trade.calculate_interest()), 8) == round(0.0008333333333333334, 8)
# kraken
trade.exchange = "kraken"
assert float(trade.calculate_interest()) == 0.040
# Short
trade.is_short = True
trade.recalc_open_trade_value()
# binace
trade.exchange = "binance"
assert float(trade.calculate_interest()) == 0.000625
# kraken
trade.exchange = "kraken"
assert isclose(float(trade.calculate_interest()), 0.030)
# 5hr, long
trade.open_date = datetime.utcnow() - timedelta(hours=4, minutes=55)
trade.is_short = False
trade.recalc_open_trade_value()
# binance
trade.exchange = "binance"
assert round(float(trade.calculate_interest()), 8) == round(0.004166666666666667, 8)
# kraken
trade.exchange = "kraken"
assert float(trade.calculate_interest()) == 0.06
# short
trade.is_short = True
trade.recalc_open_trade_value()
# binace
trade.exchange = "binance"
assert round(float(trade.calculate_interest()), 8) == round(0.0031249999999999997, 8)
# kraken
trade.exchange = "kraken"
assert float(trade.calculate_interest()) == 0.045
# 0.00025 interest, 5hr, long
trade.is_short = False
trade.recalc_open_trade_value()
# binance
trade.exchange = "binance"
assert round(float(trade.calculate_interest(interest_rate=0.00025)),
8) == round(0.0020833333333333333, 8)
# kraken
trade.exchange = "kraken"
assert isclose(float(trade.calculate_interest(interest_rate=0.00025)), 0.03)
# short
trade.is_short = True
trade.recalc_open_trade_value()
# binace
trade.exchange = "binance"
assert round(float(trade.calculate_interest(interest_rate=0.00025)),
8) == round(0.0015624999999999999, 8)
# kraken
trade.exchange = "kraken"
assert float(trade.calculate_interest(interest_rate=0.00025)) == 0.0225
# 5x leverage, 0.0005 interest, 5hr, long
trade.is_short = False
trade.recalc_open_trade_value()
trade.leverage = 5.0
# binance
trade.exchange = "binance"
assert round(float(trade.calculate_interest()), 8) == 0.005
# kraken
trade.exchange = "kraken"
assert float(trade.calculate_interest()) == round(0.07200000000000001, 8)
# short
trade.is_short = True
trade.recalc_open_trade_value()
# binace
trade.exchange = "binance"
assert round(float(trade.calculate_interest()), 8) == round(0.0031249999999999997, 8)
# kraken
trade.exchange = "kraken"
assert float(trade.calculate_interest()) == 0.045
# 1x leverage, 0.0005 interest, 5hr
trade.is_short = False
trade.recalc_open_trade_value()
trade.leverage = 1.0
# binance
trade.exchange = "binance"
assert float(trade.calculate_interest()) == 0.0
# kraken
trade.exchange = "kraken"
assert float(trade.calculate_interest()) == 0.0
# short
trade.is_short = True
trade.recalc_open_trade_value()
# binace
trade.exchange = "binance"
assert float(trade.calculate_interest()) == 0.003125
# kraken
trade.exchange = "kraken"
assert float(trade.calculate_interest()) == 0.045
assert round(float(trade.calculate_interest()), 8) == interest
@pytest.mark.parametrize('is_short,lev,borrowed', [
(False, 1.0, 0.0),
(True, 1.0, 30.0),
(False, 3.0, 40.0),
(True, 3.0, 30.0),
])
@pytest.mark.usefixtures("init_persistence")
def test_borrowed(limit_buy_order_usdt, limit_sell_order_usdt, fee, caplog):
def test_borrowed(limit_buy_order_usdt, limit_sell_order_usdt, fee,
caplog, is_short, lev, borrowed):
"""
10 minute limit trade on Binance/Kraken at 1x, 3x leverage
fee: 0.25% quote
@ -411,20 +346,19 @@ def test_borrowed(limit_buy_order_usdt, limit_sell_order_usdt, fee, caplog):
fee_open=fee.return_value,
fee_close=fee.return_value,
exchange='binance',
is_short=is_short,
leverage=lev
)
assert trade.borrowed == 0
trade.is_short = True
trade.recalc_open_trade_value()
assert trade.borrowed == 30.0
trade.leverage = 3.0
assert trade.borrowed == 30.0
trade.is_short = False
trade.recalc_open_trade_value()
assert trade.borrowed == 40.0
assert trade.borrowed == borrowed
@pytest.mark.parametrize('is_short,open_rate,close_rate,lev,profit', [
(False, 2.0, 2.2, 1.0, round(0.0945137157107232, 8)),
(True, 2.2, 2.0, 3.0, round(0.2589996297562085, 8))
])
@pytest.mark.usefixtures("init_persistence")
def test_update_limit_order(limit_buy_order_usdt, limit_sell_order_usdt, fee, caplog):
def test_update_limit_order(fee, caplog, limit_buy_order_usdt, limit_sell_order_usdt,
is_short, open_rate, close_rate, lev, profit):
"""
10 minute limit trade on Binance/Kraken at 1x, 3x leverage
fee: 0.25% quote
@ -494,84 +428,52 @@ def test_update_limit_order(limit_buy_order_usdt, limit_sell_order_usdt, fee, ca
"""
enter_order = limit_sell_order_usdt if is_short else limit_buy_order_usdt
exit_order = limit_buy_order_usdt if is_short else limit_sell_order_usdt
enter_side, exit_side = get_sides(is_short)
trade = Trade(
id=2,
pair='ADA/USDT',
stake_amount=60.0,
open_rate=2.0,
amount=30.0,
is_open=True,
open_date=arrow.utcnow().datetime,
fee_open=fee.return_value,
fee_close=fee.return_value,
exchange='binance'
)
assert trade.open_order_id is None
assert trade.close_profit is None
assert trade.close_date is None
trade.open_order_id = 'something'
trade.update(limit_buy_order_usdt)
assert trade.open_order_id is None
assert trade.open_rate == 2.00
assert trade.close_profit is None
assert trade.close_date is None
assert log_has_re(r"LIMIT_BUY has been fulfilled for Trade\(id=2, "
r'pair=ADA/USDT, amount=30.00000000, '
r"is_short=False, leverage=1.0, open_rate=2.00000000, open_since=.*\).",
caplog)
caplog.clear()
trade.open_order_id = 'something'
trade.update(limit_sell_order_usdt)
assert trade.open_order_id is None
assert trade.close_rate == 2.20
assert trade.close_profit == round(0.0945137157107232, 8)
assert trade.close_date is not None
assert log_has_re(r"LIMIT_SELL has been fulfilled for Trade\(id=2, "
r"pair=ADA/USDT, amount=30.00000000, "
r"is_short=False, leverage=1.0, open_rate=2.00000000, open_since=.*\).",
caplog)
caplog.clear()
trade = Trade(
id=226531,
pair='ADA/USDT',
stake_amount=20.0,
open_rate=2.0,
open_rate=open_rate,
amount=30.0,
is_open=True,
open_date=arrow.utcnow().datetime,
fee_open=fee.return_value,
fee_close=fee.return_value,
exchange='binance',
is_short=True,
leverage=3.0,
is_short=is_short,
interest_rate=0.0005,
leverage=lev
)
trade.open_order_id = 'something'
trade.update(limit_sell_order_usdt)
assert trade.open_order_id is None
assert trade.open_rate == 2.20
assert trade.close_profit is None
assert trade.close_date is None
assert log_has_re(r"LIMIT_SELL has been fulfilled for Trade\(id=226531, "
r"pair=ADA/USDT, amount=30.00000000, "
r"is_short=True, leverage=3.0, open_rate=2.20000000, open_since=.*\).",
caplog)
caplog.clear()
trade.open_order_id = 'something'
trade.update(limit_buy_order_usdt)
trade.update(enter_order)
assert trade.open_order_id is None
assert trade.close_rate == 2.00
assert trade.close_profit == round(0.2589996297562085, 8)
assert trade.open_rate == open_rate
assert trade.close_profit is None
assert trade.close_date is None
assert log_has_re(f"LIMIT_{enter_side.upper()} has been fulfilled for "
r"Trade\(id=2, pair=ADA/USDT, amount=30.00000000, "
f"is_short={is_short}, leverage={lev}, open_rate={open_rate}0000000, "
r"open_since=.*\).",
caplog)
caplog.clear()
trade.open_order_id = 'something'
trade.update(exit_order)
assert trade.open_order_id is None
assert trade.close_rate == close_rate
assert trade.close_profit == profit
assert trade.close_date is not None
assert log_has_re(r"LIMIT_BUY has been fulfilled for Trade\(id=226531, "
r"pair=ADA/USDT, amount=30.00000000, "
r"is_short=True, leverage=3.0, open_rate=2.20000000, open_since=.*\).",
assert log_has_re(f"LIMIT_{exit_side.upper()} has been fulfilled for "
r"Trade\(id=2, pair=ADA/USDT, amount=30.00000000, "
f"is_short={is_short}, leverage={lev}, open_rate={open_rate}0000000, "
r"open_since=.*\).",
caplog)
caplog.clear()
@ -616,9 +518,21 @@ def test_update_market_order(market_buy_order_usdt, market_sell_order_usdt, fee,
caplog)
@pytest.mark.parametrize('exchange,is_short,lev,open_value,close_value,profit,profit_ratio', [
("binance", False, 1, 60.15, 65.835, 5.685, 0.0945137157107232),
("binance", True, 1, 59.850, 66.1663784375, -6.316378437500013, -0.1055368159983292),
("binance", False, 3, 60.15, 65.83416667, 5.684166670000003, 0.2834995845386534),
("binance", True, 3, 59.85, 66.1663784375, -6.316378437500013, -0.3166104479949876),
("kraken", False, 1, 60.15, 65.835, 5.685, 0.0945137157107232),
("kraken", True, 1, 59.850, 66.231165, -6.381165, -0.106619298245614),
("kraken", False, 3, 60.15, 65.795, 5.645, 0.2815461346633419),
("kraken", True, 3, 59.850, 66.231165, -6.381165000000003, -0.319857894736842),
])
@pytest.mark.usefixtures("init_persistence")
def test_calc_open_close_trade_price(limit_buy_order_usdt, limit_sell_order_usdt, fee):
trade = Trade(
def test_calc_open_close_trade_price(limit_buy_order_usdt, limit_sell_order_usdt, fee, exchange,
is_short, lev, open_value, close_value, profit, profit_ratio):
trade: Trade = Trade(
pair='ADA/USDT',
stake_amount=60.0,
open_rate=2.0,
@ -627,55 +541,22 @@ def test_calc_open_close_trade_price(limit_buy_order_usdt, limit_sell_order_usdt
interest_rate=0.0005,
fee_open=fee.return_value,
fee_close=fee.return_value,
exchange='binance',
exchange=exchange,
is_short=is_short,
leverage=lev
)
trade.open_order_id = 'something'
trade.open_order_id = f'something-{is_short}-{lev}-{exchange}'
trade.update(limit_buy_order_usdt)
trade.update(limit_sell_order_usdt)
# 1x leverage, binance
assert trade._calc_open_trade_value() == 60.15
assert isclose(trade.calc_close_trade_value(), 65.835)
assert trade.calc_profit() == 5.685
assert trade.calc_profit_ratio() == round(0.0945137157107232, 8)
# 3x leverage, binance
trade.leverage = 3
trade.exchange = "binance"
assert trade._calc_open_trade_value() == 60.15
assert round(trade.calc_close_trade_value(), 8) == 65.83416667
assert trade.calc_profit() == round(5.684166670000003, 8)
assert trade.calc_profit_ratio() == round(0.2834995845386534, 8)
trade.exchange = "kraken"
# 3x leverage, kraken
assert trade._calc_open_trade_value() == 60.15
assert trade.calc_close_trade_value() == 65.795
assert trade.calc_profit() == 5.645
assert trade.calc_profit_ratio() == round(0.2815461346633419, 8)
trade.is_short = True
trade.open_rate = 2.0
trade.close_rate = 2.2
trade.recalc_open_trade_value()
# 3x leverage, short, kraken
assert trade._calc_open_trade_value() == 59.850
assert trade.calc_close_trade_value() == 66.231165
assert trade.calc_profit() == round(-6.381165000000003, 8)
assert trade.calc_profit_ratio() == round(-0.319857894736842, 8)
trade.exchange = "binance"
# 3x leverage, short, binance
assert trade._calc_open_trade_value() == 59.85
assert trade.calc_close_trade_value() == 66.1663784375
assert trade.calc_profit() == round(-6.316378437500013, 8)
assert trade.calc_profit_ratio() == round(-0.3166104479949876, 8)
# 1x leverage, short, binance
trade.leverage = 1.0
assert trade._calc_open_trade_value() == 59.850
assert trade.calc_close_trade_value() == 66.1663784375
assert trade.calc_profit() == round(-6.316378437500013, 8)
assert trade.calc_profit_ratio() == round(-0.1055368159983292, 8)
# 1x leverage, short, kraken
trade.exchange = "kraken"
assert trade._calc_open_trade_value() == 59.850
assert trade.calc_close_trade_value() == 66.231165
assert trade.calc_profit() == -6.381165
assert trade.calc_profit_ratio() == round(-0.106619298245614, 8)
assert isclose(trade._calc_open_trade_value(), open_value)
assert isclose(trade.calc_close_trade_value(), close_value)
assert isclose(trade.calc_profit(), round(profit, 8))
assert isclose(trade.calc_profit_ratio(), round(profit_ratio, 8))
@pytest.mark.usefixtures("init_persistence")
@ -766,8 +647,27 @@ def test_update_invalid_order(limit_buy_order_usdt):
trade.update(limit_buy_order_usdt)
@pytest.mark.parametrize('exchange', ['binance', 'kraken'])
@pytest.mark.parametrize('lev', [1, 3])
@pytest.mark.parametrize('is_short,fee_rate,result', [
(False, 0.003, 60.18),
(False, 0.0025, 60.15),
(False, 0.003, 60.18),
(False, 0.0025, 60.15),
(True, 0.003, 59.82),
(True, 0.0025, 59.85),
(True, 0.003, 59.82),
(True, 0.0025, 59.85)
])
@pytest.mark.usefixtures("init_persistence")
def test_calc_open_trade_value(limit_buy_order_usdt, fee):
def test_calc_open_trade_value(
limit_buy_order_usdt,
exchange,
lev,
is_short,
fee_rate,
result
):
# 10 minute limit trade on Binance/Kraken at 1x, 3x leverage
# fee: 0.25 %, 0.3% quote
# open_rate: 2.00 quote
@ -787,90 +687,104 @@ def test_calc_open_trade_value(limit_buy_order_usdt, fee):
stake_amount=60.0,
amount=30.0,
open_rate=2.0,
fee_open=fee.return_value,
fee_close=fee.return_value,
exchange='binance',
open_date=datetime.now(tz=timezone.utc) - timedelta(minutes=10),
fee_open=fee_rate,
fee_close=fee_rate,
exchange=exchange,
leverage=lev,
is_short=is_short
)
trade.open_order_id = 'open_trade'
trade.update(limit_buy_order_usdt)
# Get the open rate price with the standard fee rate
assert trade._calc_open_trade_value() == 60.15
trade.is_short = True
trade.recalc_open_trade_value()
assert trade._calc_open_trade_value() == 59.85
trade.leverage = 3
trade.exchange = "binance"
assert trade._calc_open_trade_value() == 59.85
trade.is_short = False
trade.recalc_open_trade_value()
assert trade._calc_open_trade_value() == 60.15
# Get the open rate price with a custom fee rate
trade.fee_open = 0.003
assert trade._calc_open_trade_value() == 60.18
trade.is_short = True
trade.recalc_open_trade_value()
assert trade._calc_open_trade_value() == 59.82
assert trade._calc_open_trade_value() == result
@pytest.mark.parametrize('exchange,is_short,lev,open_rate,close_rate,fee_rate,result', [
('binance', False, 1, 2.0, 2.5, 0.0025, 74.8125),
('binance', False, 1, 2.0, 2.5, 0.003, 74.775),
('binance', False, 1, 2.0, 2.2, 0.005, 65.67),
('binance', False, 3, 2.0, 2.5, 0.0025, 74.81166667),
('binance', False, 3, 2.0, 2.5, 0.003, 74.77416667),
('kraken', False, 3, 2.0, 2.5, 0.0025, 74.7725),
('kraken', False, 3, 2.0, 2.5, 0.003, 74.735),
('kraken', True, 3, 2.2, 2.5, 0.0025, 75.2626875),
('kraken', True, 3, 2.2, 2.5, 0.003, 75.300225),
('binance', True, 3, 2.2, 2.5, 0.0025, 75.18906641),
('binance', True, 3, 2.2, 2.5, 0.003, 75.22656719),
('binance', True, 1, 2.2, 2.5, 0.0025, 75.18906641),
('binance', True, 1, 2.2, 2.5, 0.003, 75.22656719),
('kraken', True, 1, 2.2, 2.5, 0.0025, 75.2626875),
('kraken', True, 1, 2.2, 2.5, 0.003, 75.300225),
])
@pytest.mark.usefixtures("init_persistence")
def test_calc_close_trade_price(limit_buy_order_usdt, limit_sell_order_usdt, fee):
def test_calc_close_trade_price(limit_buy_order_usdt, limit_sell_order_usdt, open_rate,
exchange, is_short, lev, close_rate, fee_rate, result):
trade = Trade(
pair='ADA/USDT',
stake_amount=60.0,
amount=30.0,
open_rate=2.0,
open_rate=open_rate,
open_date=datetime.now(tz=timezone.utc) - timedelta(minutes=10),
fee_open=fee.return_value,
fee_close=fee.return_value,
exchange='binance',
fee_open=fee_rate,
fee_close=fee_rate,
exchange=exchange,
interest_rate=0.0005,
is_short=is_short,
leverage=lev
)
trade.open_order_id = 'close_trade'
trade.update(limit_buy_order_usdt)
# 1x leverage binance
assert trade.calc_close_trade_value(rate=2.5) == 74.8125
assert trade.calc_close_trade_value(rate=2.5, fee=0.003) == 74.775
trade.update(limit_sell_order_usdt)
assert trade.calc_close_trade_value(fee=0.005) == 65.67
# 3x leverage binance
trade.leverage = 3.0
assert round(trade.calc_close_trade_value(rate=2.5), 8) == 74.81166667
assert round(trade.calc_close_trade_value(rate=2.5, fee=0.003), 8) == 74.77416667
# 3x leverage kraken
trade.exchange = "kraken"
assert trade.calc_close_trade_value(rate=2.5) == 74.7725
assert trade.calc_close_trade_value(rate=2.5, fee=0.003) == 74.735
# 3x leverage kraken, short
trade.is_short = True
trade.recalc_open_trade_value()
assert round(trade.calc_close_trade_value(rate=2.5), 8) == 75.2626875
assert trade.calc_close_trade_value(rate=2.5, fee=0.003) == 75.300225
# 3x leverage binance, short
trade.exchange = "binance"
assert round(trade.calc_close_trade_value(rate=2.5), 8) == 75.18906641
assert round(trade.calc_close_trade_value(rate=2.5, fee=0.003), 8) == 75.22656719
trade.leverage = 1.0
# 1x leverage binance, short
assert round(trade.calc_close_trade_value(rate=2.5), 8) == 75.18906641
assert round(trade.calc_close_trade_value(rate=2.5, fee=0.003), 8) == 75.22656719
# 1x leverage kraken, short
trade.exchange = "kraken"
assert round(trade.calc_close_trade_value(rate=2.5), 8) == 75.2626875
assert trade.calc_close_trade_value(rate=2.5, fee=0.003) == 75.300225
assert round(trade.calc_close_trade_value(rate=close_rate, fee=fee_rate), 8) == result
@pytest.mark.parametrize('exchange,is_short,lev,close_rate,fee_close,profit,profit_ratio', [
('binance', False, 1, 2.1, 0.0025, 2.6925, 0.04476309226932673),
('binance', False, 3, 2.1, 0.0025, 2.69166667, 0.13424771421446402),
('binance', True, 1, 2.1, 0.0025, -3.308815781249997, -0.05528514254385963),
('binance', True, 3, 2.1, 0.0025, -3.308815781249997, -0.1658554276315789),
('binance', False, 1, 1.9, 0.0025, -3.2925, -0.05473815461346632),
('binance', False, 3, 1.9, 0.0025, -3.29333333, -0.16425602643391513),
('binance', True, 1, 1.9, 0.0025, 2.7063095312499996, 0.045218204365079395),
('binance', True, 3, 1.9, 0.0025, 2.7063095312499996, 0.13565461309523819),
('binance', False, 1, 2.2, 0.0025, 5.685, 0.0945137157107232),
('binance', False, 3, 2.2, 0.0025, 5.68416667, 0.2834995845386534),
('binance', True, 1, 2.2, 0.0025, -6.316378437499999, -0.1055368159983292),
('binance', True, 3, 2.2, 0.0025, -6.316378437499999, -0.3166104479949876),
('kraken', False, 1, 2.1, 0.0025, 2.6925, 0.04476309226932673),
('kraken', False, 3, 2.1, 0.0025, 2.6525, 0.13229426433915248),
('kraken', True, 1, 2.1, 0.0025, -3.3706575, -0.05631842105263152),
('kraken', True, 3, 2.1, 0.0025, -3.3706575, -0.16895526315789455),
('kraken', False, 1, 1.9, 0.0025, -3.2925, -0.05473815461346632),
('kraken', False, 3, 1.9, 0.0025, -3.3325, -0.16620947630922667),
('kraken', True, 1, 1.9, 0.0025, 2.6503575, 0.04428333333333334),
('kraken', True, 3, 1.9, 0.0025, 2.6503575, 0.13285000000000002),
('kraken', False, 1, 2.2, 0.0025, 5.685, 0.0945137157107232),
('kraken', False, 3, 2.2, 0.0025, 5.645, 0.2815461346633419),
('kraken', True, 1, 2.2, 0.0025, -6.381165, -0.106619298245614),
('kraken', True, 3, 2.2, 0.0025, -6.381165, -0.319857894736842),
('binance', False, 1, 2.1, 0.003, 2.6610000000000014, 0.04423940149625927),
('binance', False, 1, 1.9, 0.003, -3.320999999999998, -0.05521197007481293),
('binance', False, 1, 2.2, 0.003, 5.652000000000008, 0.09396508728179565),
])
@pytest.mark.usefixtures("init_persistence")
def test_calc_profit(limit_buy_order_usdt, limit_sell_order_usdt, fee):
def test_calc_profit(
limit_buy_order_usdt,
limit_sell_order_usdt,
fee,
exchange,
is_short,
lev,
close_rate,
fee_close,
profit,
profit_ratio
):
"""
10 minute limit trade on Binance/Kraken at 1x, 3x leverage
arguments:
@ -1007,198 +921,16 @@ def test_calc_profit(limit_buy_order_usdt, limit_sell_order_usdt, fee):
open_rate=2.0,
open_date=datetime.now(tz=timezone.utc) - timedelta(minutes=10),
interest_rate=0.0005,
fee_open=fee.return_value,
fee_close=fee.return_value,
exchange='binance'
exchange=exchange,
is_short=is_short,
leverage=lev,
fee_open=0.0025,
fee_close=fee_close
)
trade.open_order_id = 'something'
trade.update(limit_buy_order_usdt) # Buy @ 2.0
# 1x Leverage, long
# Custom closing rate and regular fee rate
# Higher than open rate - 2.1 quote
assert trade.calc_profit(rate=2.1) == 2.6925
# Lower than open rate - 1.9 quote
assert trade.calc_profit(rate=1.9) == round(-3.292499999999997, 8)
# fee 0.003
# Higher than open rate - 2.1 quote
assert trade.calc_profit(rate=2.1, fee=0.003) == 2.661
# Lower than open rate - 1.9 quote
assert trade.calc_profit(rate=1.9, fee=0.003) == round(-3.320999999999998, 8)
# Test when we apply a Sell order. Sell higher than open rate @ 2.2
trade.update(limit_sell_order_usdt)
assert trade.calc_profit() == round(5.684999999999995, 8)
# Test with a custom fee rate on the close trade
assert trade.calc_profit(fee=0.003) == round(5.652000000000008, 8)
trade.open_trade_value = 0.0
trade.open_trade_value = trade._calc_open_trade_value()
# 3x leverage, long ###################################################
trade.leverage = 3.0
# Higher than open rate - 2.1 quote
trade.exchange = "binance" # binance
assert trade.calc_profit(rate=2.1, fee=0.0025) == 2.69166667
trade.exchange = "kraken"
assert trade.calc_profit(rate=2.1, fee=0.0025) == 2.6525
# 1.9 quote
trade.exchange = "binance" # binance
assert trade.calc_profit(rate=1.9, fee=0.0025) == -3.29333333
trade.exchange = "kraken"
assert trade.calc_profit(rate=1.9, fee=0.0025) == -3.3325
# 2.2 quote
trade.exchange = "binance" # binance
assert trade.calc_profit(fee=0.0025) == 5.68416667
trade.exchange = "kraken"
assert trade.calc_profit(fee=0.0025) == 5.645
# 3x leverage, short ###################################################
trade.is_short = True
trade.recalc_open_trade_value()
# 2.1 quote - Higher than open rate
trade.exchange = "binance" # binance
assert trade.calc_profit(rate=2.1, fee=0.0025) == round(-3.308815781249997, 8)
trade.exchange = "kraken"
assert trade.calc_profit(rate=2.1, fee=0.0025) == -3.3706575
# 1.9 quote - Lower than open rate
trade.exchange = "binance" # binance
assert trade.calc_profit(rate=1.9, fee=0.0025) == round(2.7063095312499996, 8)
trade.exchange = "kraken"
assert trade.calc_profit(rate=1.9, fee=0.0025) == 2.6503575
# Test when we apply a Sell order. Uses sell order used above
trade.exchange = "binance" # binance
assert trade.calc_profit(fee=0.0025) == round(-6.316378437499999, 8)
trade.exchange = "kraken"
assert trade.calc_profit(fee=0.0025) == -6.381165
# 1x leverage, short ###################################################
trade.leverage = 1.0
# 2.1 quote - Higher than open rate
trade.exchange = "binance" # binance
assert trade.calc_profit(rate=2.1, fee=0.0025) == round(-3.308815781249997, 8)
trade.exchange = "kraken"
assert trade.calc_profit(rate=2.1, fee=0.0025) == -3.3706575
# 1.9 quote - Lower than open rate
trade.exchange = "binance" # binance
assert trade.calc_profit(rate=1.9, fee=0.0025) == round(2.7063095312499996, 8)
trade.exchange = "kraken"
assert trade.calc_profit(rate=1.9, fee=0.0025) == 2.6503575
# Test when we apply a Sell order. Uses sell order used above
trade.exchange = "binance" # binance
assert trade.calc_profit(fee=0.0025) == round(-6.316378437499999, 8)
trade.exchange = "kraken"
assert trade.calc_profit(fee=0.0025) == -6.381165
@pytest.mark.usefixtures("init_persistence")
def test_calc_profit_ratio(limit_buy_order_usdt, limit_sell_order_usdt, fee):
trade = Trade(
pair='ADA/USDT',
stake_amount=60.0,
amount=30.0,
open_rate=2.0,
open_date=datetime.now(tz=timezone.utc) - timedelta(minutes=10),
interest_rate=0.0005,
fee_open=fee.return_value,
fee_close=fee.return_value,
exchange='binance'
)
trade.open_order_id = 'something'
trade.update(limit_buy_order_usdt) # Buy @ 2.0
# 1x Leverage, long
# Custom closing rate and regular fee rate
# Higher than open rate - 2.1 quote
assert trade.calc_profit_ratio(rate=2.1) == round(0.04476309226932673, 8)
# Lower than open rate - 1.9 quote
assert trade.calc_profit_ratio(rate=1.9) == round(-0.05473815461346632, 8)
# fee 0.003
# Higher than open rate - 2.1 quote
assert trade.calc_profit_ratio(rate=2.1, fee=0.003) == round(0.04423940149625927, 8)
# Lower than open rate - 1.9 quote
assert trade.calc_profit_ratio(rate=1.9, fee=0.003) == round(-0.05521197007481293, 8)
# Test when we apply a Sell order. Sell higher than open rate @ 2.2
trade.update(limit_sell_order_usdt)
assert trade.calc_profit_ratio() == round(0.0945137157107232, 8)
# Test with a custom fee rate on the close trade
assert trade.calc_profit_ratio(fee=0.003) == round(0.09396508728179565, 8)
trade.open_trade_value = 0.0
assert trade.calc_profit_ratio(fee=0.003) == 0.0
trade.open_trade_value = trade._calc_open_trade_value()
# 3x leverage, long ###################################################
trade.leverage = 3.0
# 2.1 quote - Higher than open rate
trade.exchange = "binance" # binance
assert trade.calc_profit_ratio(rate=2.1) == round(0.13424771421446402, 8)
trade.exchange = "kraken"
assert trade.calc_profit_ratio(rate=2.1) == round(0.13229426433915248, 8)
# 1.9 quote - Lower than open rate
trade.exchange = "binance" # binance
assert trade.calc_profit_ratio(rate=1.9) == round(-0.16425602643391513, 8)
trade.exchange = "kraken"
assert trade.calc_profit_ratio(rate=1.9) == round(-0.16620947630922667, 8)
# Test when we apply a Sell order. Uses sell order used above
trade.exchange = "binance" # binance
assert trade.calc_profit_ratio() == round(0.2834995845386534, 8)
trade.exchange = "kraken"
assert trade.calc_profit_ratio() == round(0.2815461346633419, 8)
# 3x leverage, short ###################################################
trade.is_short = True
trade.recalc_open_trade_value()
# 2.1 quote - Higher than open rate
trade.exchange = "binance" # binance
assert trade.calc_profit_ratio(rate=2.1) == round(-0.1658554276315789, 8)
trade.exchange = "kraken"
assert trade.calc_profit_ratio(rate=2.1) == round(-0.16895526315789455, 8)
# 1.9 quote - Lower than open rate
trade.exchange = "binance" # binance
assert trade.calc_profit_ratio(rate=1.9) == round(0.13565461309523819, 8)
trade.exchange = "kraken"
assert trade.calc_profit_ratio(rate=1.9) == round(0.13285000000000002, 8)
# Test when we apply a Sell order. Uses sell order used above
trade.exchange = "binance" # binance
assert trade.calc_profit_ratio() == round(-0.3166104479949876, 8)
trade.exchange = "kraken"
assert trade.calc_profit_ratio() == round(-0.319857894736842, 8)
# 1x leverage, short ###################################################
trade.leverage = 1.0
# 2.1 quote - Higher than open rate
trade.exchange = "binance" # binance
assert trade.calc_profit_ratio(rate=2.1) == round(-0.05528514254385963, 8)
trade.exchange = "kraken"
assert trade.calc_profit_ratio(rate=2.1) == round(-0.05631842105263152, 8)
# 1.9 quote - Lower than open rate
trade.exchange = "binance"
assert trade.calc_profit_ratio(rate=1.9) == round(0.045218204365079395, 8)
trade.exchange = "kraken"
assert trade.calc_profit_ratio(rate=1.9) == round(0.04428333333333334, 8)
# Test when we apply a Sell order. Uses sell order used above
trade.exchange = "binance"
assert trade.calc_profit_ratio() == round(-0.1055368159983292, 8)
trade.exchange = "kraken"
assert trade.calc_profit_ratio() == round(-0.106619298245614, 8)
assert trade.calc_profit(rate=close_rate) == round(profit, 8)
assert trade.calc_profit_ratio(rate=close_rate) == round(profit_ratio, 8)
@pytest.mark.usefixtures("init_persistence")