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Merge branch 'develop' into hyperopt-list

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1
.coveragerc
View File

@ -1,6 +1,7 @@
[run]
omit =
scripts/*
freqtrade/templates/*
freqtrade/vendor/*
freqtrade/__main__.py
tests/*

12
.github/workflows/ci.yml vendored
View File

@ -73,19 +73,21 @@ jobs:
# Allow failure for coveralls
# Fake travis environment to get coveralls working correctly
export TRAVIS_PULL_REQUEST="https://github.com/${GITHUB_REPOSITORY}/pull/$(cat $GITHUB_EVENT_PATH | jq -r .number)"
export TRAVIS_BRANCH=${GITHUB_REF#"ref/heads"}
export CI_BRANCH=${GITHUB_REF#"ref/heads"}
export CI_BRANCH=${HEAD_REF}
echo "${CI_BRANCH}"
echo "${TRAVIS_BRANCH}"
coveralls || true
- name: Backtesting
run: |
cp config.json.example config.json
freqtrade backtesting --datadir tests/testdata --strategy DefaultStrategy
freqtrade create-userdir --userdir user_data
freqtrade backtesting --datadir tests/testdata --strategy SampleStrategy
- name: Hyperopt
run: |
cp config.json.example config.json
freqtrade create-userdir --userdir user_data
freqtrade hyperopt --datadir tests/testdata -e 5 --strategy SampleStrategy --hyperopt SampleHyperOpt
- name: Flake8
@ -142,11 +144,13 @@ jobs:
- name: Backtesting
run: |
cp config.json.example config.json
freqtrade backtesting --datadir tests/testdata --strategy DefaultStrategy
freqtrade create-userdir --userdir user_data
freqtrade backtesting --datadir tests/testdata --strategy SampleStrategy
- name: Hyperopt
run: |
cp config.json.example config.json
freqtrade create-userdir --userdir user_data
freqtrade hyperopt --datadir tests/testdata -e 5 --strategy SampleStrategy --hyperopt SampleHyperOpt
- name: Flake8

4
.travis.yml
View File

@ -28,10 +28,12 @@ jobs:
name: pytest
- script:
- cp config.json.example config.json
- freqtrade backtesting --datadir tests/testdata --strategy DefaultStrategy
- freqtrade create-userdir --userdir user_data
- freqtrade backtesting --datadir tests/testdata --strategy SampleStrategy
name: backtest
- script:
- cp config.json.example config.json
- freqtrade create-userdir --userdir user_data
- freqtrade hyperopt --datadir tests/testdata -e 5 --strategy SampleStrategy --hyperopt SampleHyperOpt
name: hyperopt
- script: flake8

4
docs/developer.md
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@ -200,8 +200,8 @@ If the day shows the same day, then the last candle can be assumed as incomplete
To keep the jupyter notebooks aligned with the documentation, the following should be ran after updating a example notebook.
``` bash
jupyter nbconvert --ClearOutputPreprocessor.enabled=True --inplace user_data/notebooks/strategy_analysis_example.ipynb
jupyter nbconvert --ClearOutputPreprocessor.enabled=True --to markdown user_data/notebooks/strategy_analysis_example.ipynb --stdout > docs/strategy_analysis_example.md
jupyter nbconvert --ClearOutputPreprocessor.enabled=True --inplace freqtrade/templates/strategy_analysis_example.ipynb
jupyter nbconvert --ClearOutputPreprocessor.enabled=True --to markdown freqtrade/templates/strategy_analysis_example.ipynb --stdout > docs/strategy_analysis_example.md
```
## Continuous integration

9
docs/hyperopt.md
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@ -15,10 +15,13 @@ To learn how to get data for the pairs and exchange you're interrested in, head
## Prepare Hyperopting
Before we start digging into Hyperopt, we recommend you to take a look at
the sample hyperopt file located in [user_data/hyperopts/](https://github.com/freqtrade/freqtrade/blob/develop/user_data/hyperopts/sample_hyperopt.py).
the sample hyperopt file located in [user_data/hyperopts/](https://github.com/freqtrade/freqtrade/blob/develop/freqtrade/templates/sample_hyperopt.py).
Configuring hyperopt is similar to writing your own strategy, and many tasks will be similar and a lot of code can be copied across from the strategy.
The simplest way to get started is to use `freqtrade new-hyperopt --hyperopt AwesomeHyperopt`.
This will create a new hyperopt file from a template, which will be located under `user_data/hyperopts/AwesomeHyperopt.py`.
### Checklist on all tasks / possibilities in hyperopt
Depending on the space you want to optimize, only some of the below are required:
@ -423,7 +426,7 @@ These ranges should be sufficient in most cases. The minutes in the steps (ROI d
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.
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 [user_data/hyperopts/sample_hyperopt_advanced.py](https://github.com/freqtrade/freqtrade/blob/develop/user_data/hyperopts/sample_hyperopt_advanced.py).
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 [user_data/hyperopts/sample_hyperopt_advanced.py](https://github.com/freqtrade/freqtrade/blob/develop/freqtrade/templates/sample_hyperopt_advanced.py).
### Understand Hyperopt Stoploss results
@ -458,7 +461,7 @@ 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/user_data/hyperopts/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 [user_data/hyperopts/sample_hyperopt_advanced.py](https://github.com/freqtrade/freqtrade/blob/develop/freqtrade/templates/sample_hyperopt_advanced.py).
### Validate backtesting results

26
docs/installation.md
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@ -162,7 +162,7 @@ Clone the git repository:
```bash
git clone https://github.com/freqtrade/freqtrade.git
cd freqtrade
```
Optionally checkout the master branch to get the latest stable release:
@ -171,22 +171,24 @@ Optionally checkout the master branch to get the latest stable release:
git checkout master
```
#### 4. Initialize the configuration
```bash
cd freqtrade
cp config.json.example config.json
```
> *To edit the config please refer to [Bot Configuration](configuration.md).*
#### 5. Install python dependencies
#### 4. Install python dependencies
``` bash
python3 -m pip install --upgrade pip
python3 -m pip install -e .
```
#### 5. Initialize the configuration
```bash
# Initialize the user_directory
freqtrade create-userdir --userdir user_data/
cp config.json.example config.json
```
> *To edit the config please refer to [Bot Configuration](configuration.md).*
#### 6. Run the Bot
If this is the first time you run the bot, ensure you are running it in Dry-run `"dry_run": true,` otherwise it will start to buy and sell coins.
@ -227,7 +229,7 @@ If that is not available on your system, feel free to try the instructions below
Make sure to use 64bit Windows and 64bit Python to avoid problems with backtesting or hyperopt due to the memory constraints 32bit applications have under Windows.
!!! Hint
Using the [Anaconda Distribution](https://www.anaconda.com/distribution/) under Windows can greatly help with installation problems. Check out the [Conda section](#using-conda) in this document.
Using the [Anaconda Distribution](https://www.anaconda.com/distribution/) under Windows can greatly help with installation problems. Check out the [Conda section](#using-conda) in this document for more information.
#### Clone the git repository

28
docs/strategy-customization.md
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@ -7,24 +7,28 @@ indicators.
This is very simple. Copy paste your strategy file into the directory `user_data/strategies`.
Let assume you have a class called `AwesomeStrategy` in the file `awesome-strategy.py`:
Let assume you have a class called `AwesomeStrategy` in the file `AwesomeStrategy.py`:
1. Move your file into `user_data/strategies` (you should have `user_data/strategies/awesome-strategy.py`
1. Move your file into `user_data/strategies` (you should have `user_data/strategies/AwesomeStrategy.py`
2. Start the bot with the param `--strategy AwesomeStrategy` (the parameter is the class name)
```bash
freqtrade trade --strategy AwesomeStrategy
```
## Change your strategy
## Develop your own strategy
The bot includes a default strategy file. However, we recommend you to
use your own file to not have to lose your parameters every time the default
strategy file will be updated on Github. Put your custom strategy file
into the directory `user_data/strategies`.
The bot includes a default strategy file.
Also, several other strategies are available in the [strategy repository](https://github.com/freqtrade/freqtrade-strategies).
Best copy the test-strategy and modify this copy to avoid having bot-updates override your changes.
`cp user_data/strategies/sample_strategy.py user_data/strategies/awesome-strategy.py`
You will however most likely have your own idea for a strategy.
This document intends to help you develop one for yourself.
To get started, use `freqtrade new-strategy --strategy AwesomeStrategy`.
This will create a new strategy file from a template, which will be located under `user_data/strategies/AwesomeStrategy.py`.
!!! Note
This is just a template file, which will most likely not be profitable out of the box.
### Anatomy of a strategy
@ -48,7 +52,7 @@ Future versions will require this to be set.
freqtrade trade --strategy AwesomeStrategy
```
**For the following section we will use the [user_data/strategies/sample_strategy.py](https://github.com/freqtrade/freqtrade/blob/develop/user_data/strategies/sample_strategy.py)
**For the following section we will use the [user_data/strategies/sample_strategy.py](https://github.com/freqtrade/freqtrade/blob/develop/freqtrade/templates/sample_strategy.py)
file as reference.**
!!! Note "Strategies and Backtesting"
@ -114,7 +118,7 @@ def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame
```
!!! Note "Want more indicator examples?"
Look into the [user_data/strategies/sample_strategy.py](https://github.com/freqtrade/freqtrade/blob/develop/user_data/strategies/sample_strategy.py).
Look into the [user_data/strategies/sample_strategy.py](https://github.com/freqtrade/freqtrade/blob/develop/freqtrade/templates/sample_strategy.py).
Then uncomment indicators you need.
### Strategy startup period
@ -478,7 +482,7 @@ Printing more than a few rows is also possible (simply use `print(dataframe)` i
### Where can i find a strategy template?
The strategy template is located in the file
[user_data/strategies/sample_strategy.py](https://github.com/freqtrade/freqtrade/blob/develop/user_data/strategies/sample_strategy.py).
[user_data/strategies/sample_strategy.py](https://github.com/freqtrade/freqtrade/blob/develop/freqtrade/templates/sample_strategy.py).
### Specify custom strategy location

110
docs/utils.md
View File

@ -2,6 +2,116 @@
Besides the Live-Trade and Dry-Run run modes, the `backtesting`, `edge` and `hyperopt` optimization subcommands, and the `download-data` subcommand which prepares historical data, the bot contains a number of utility subcommands. They are described in this section.
## Create userdir
Creates the directory structure to hold your files for freqtrade.
Will also create strategy and hyperopt examples for you to get started.
Can be used multiple times - using `--reset` will reset the sample strategy and hyperopt files to their default state.
```
usage: freqtrade create-userdir [-h] [--userdir PATH] [--reset]
optional arguments:
-h, --help show this help message and exit
--userdir PATH, --user-data-dir PATH
Path to userdata directory.
--reset Reset sample files to their original state.
```
!!! Warning
Using `--reset` may result in loss of data, since this will overwrite all sample files without asking again.
```
├── backtest_results
├── data
├── hyperopt_results
├── hyperopts
│   ├── sample_hyperopt_advanced.py
│   ├── sample_hyperopt_loss.py
│   └── sample_hyperopt.py
├── notebooks
│   └── strategy_analysis_example.ipynb
├── plot
└── strategies
└── sample_strategy.py
```
## Create new strategy
Creates a new strategy from a template similar to SampleStrategy.
The file will be named inline with your class name, and will not overwrite existing files.
Results will be located in `user_data/strategies/<strategyclassname>.py`.
### Sample usage of new-strategy
```bash
freqtrade new-strategy --strategy AwesomeStrategy
```
With custom user directory
```bash
freqtrade new-strategy --userdir ~/.freqtrade/ --strategy AwesomeStrategy
```
### new-strategy complete options
``` output
usage: freqtrade new-strategy [-h] [--userdir PATH] [-s NAME]
[--template {full,minimal}]
optional arguments:
-h, --help show this help message and exit
--userdir PATH, --user-data-dir PATH
Path to userdata directory.
-s NAME, --strategy NAME
Specify strategy class name which will be used by the
bot.
--template {full,minimal}
Use a template which is either `minimal` or `full`
(containing multiple sample indicators). Default:
`full`.
```
## Create new hyperopt
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.
Results will be located in `user_data/hyperopts/<classname>.py`.
### Sample usage of new-hyperopt
```bash
freqtrade new-hyperopt --hyperopt AwesomeHyperopt
```
With custom user directory
```bash
freqtrade new-hyperopt --userdir ~/.freqtrade/ --hyperopt AwesomeHyperopt
```
### new-hyperopt complete options
``` output
usage: freqtrade new-hyperopt [-h] [--userdir PATH] [--hyperopt NAME]
[--template {full,minimal}]
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}
Use a template which is either `minimal` or `full`
(containing multiple sample indicators). Default:
`full`.
```
## List Exchanges
Use the `list-exchanges` subcommand to see the exchanges available for the bot.

21
freqtrade/configuration/arguments.py
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@ -37,7 +37,11 @@ ARGS_LIST_TIMEFRAMES = ["exchange", "print_one_column"]
ARGS_LIST_PAIRS = ["exchange", "print_list", "list_pairs_print_json", "print_one_column",
"print_csv", "base_currencies", "quote_currencies", "list_pairs_all"]
ARGS_CREATE_USERDIR = ["user_data_dir"]
ARGS_CREATE_USERDIR = ["user_data_dir", "reset"]
ARGS_BUILD_STRATEGY = ["user_data_dir", "strategy", "template"]
ARGS_BUILD_HYPEROPT = ["user_data_dir", "hyperopt", "template"]
ARGS_DOWNLOAD_DATA = ["pairs", "pairs_file", "days", "download_trades", "exchange",
"timeframes", "erase"]
@ -58,7 +62,7 @@ ARGS_HYPEROPT_SHOW = ["hyperopt_list_best", "hyperopt_list_profitable", "hyperop
NO_CONF_REQURIED = ["download-data", "list-timeframes", "list-markets", "list-pairs",
"hyperopt_list", "hyperopt_show", "plot-dataframe", "plot-profit"]
NO_CONF_ALLOWED = ["create-userdir", "list-exchanges"]
NO_CONF_ALLOWED = ["create-userdir", "list-exchanges", "new-hyperopt", "new-strategy"]
class Arguments:
@ -124,6 +128,7 @@ class Arguments:
from freqtrade.utils import (start_create_userdir, start_download_data,
start_hyperopt_list, start_hyperopt_show,
start_list_exchanges, start_list_markets,
start_new_hyperopt, start_new_strategy,
start_list_timeframes, start_trading)
from freqtrade.plot.plot_utils import start_plot_dataframe, start_plot_profit
@ -165,6 +170,18 @@ class Arguments:
create_userdir_cmd.set_defaults(func=start_create_userdir)
self._build_args(optionlist=ARGS_CREATE_USERDIR, parser=create_userdir_cmd)
# add new-strategy subcommand
build_strategy_cmd = subparsers.add_parser('new-strategy',
help="Create new strategy")
build_strategy_cmd.set_defaults(func=start_new_strategy)
self._build_args(optionlist=ARGS_BUILD_STRATEGY, parser=build_strategy_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 list-exchanges subcommand
list_exchanges_cmd = subparsers.add_parser(
'list-exchanges',

13
freqtrade/configuration/cli_options.py
View File

@ -74,6 +74,11 @@ AVAILABLE_CLI_OPTIONS = {
help='Path to userdata directory.',
metavar='PATH',
),
"reset": Arg(
'--reset',
help='Reset sample files to their original state.',
action='store_true',
),
# Main options
"strategy": Arg(
'-s', '--strategy',
@ -346,6 +351,14 @@ AVAILABLE_CLI_OPTIONS = {
help='Clean all existing data for the selected exchange/pairs/timeframes.',
action='store_true',
),
# Templating options
"template": Arg(
'--template',
help='Use a template which is either `minimal` or '
'`full` (containing multiple sample indicators). Default: `%(default)s`.',
choices=['full', 'minimal'],
default='full',
),
# Plot dataframe
"indicators1": Arg(
'--indicators1',

7
freqtrade/configuration/deprecated_settings.py
View File

@ -58,6 +58,13 @@ def process_temporary_deprecated_settings(config: Dict[str, Any]) -> None:
process_deprecated_setting(config, 'ask_strategy', 'ignore_roi_if_buy_signal',
'experimental', 'ignore_roi_if_buy_signal')
if not config.get('pairlists') and not config.get('pairlists'):
config['pairlists'] = [{'method': 'StaticPairList'}]
logger.warning(
"DEPRECATED: "
"Pairlists must be defined explicitly in the future."
"Defaulting to StaticPairList for now.")
if config.get('pairlist', {}).get("method") == 'VolumePairList':
logger.warning(
"DEPRECATED: "

30
freqtrade/configuration/directory_operations.py
View File

@ -1,8 +1,10 @@
import logging
from typing import Any, Dict, Optional
import shutil
from pathlib import Path
from typing import Any, Dict, Optional
from freqtrade import OperationalException
from freqtrade.constants import USER_DATA_FILES
logger = logging.getLogger(__name__)
@ -31,7 +33,8 @@ def create_userdata_dir(directory: str, create_dir=False) -> Path:
:param create_dir: Create directory if it does not exist.
:return: Path object containing the directory
"""
sub_dirs = ["backtest_results", "data", "hyperopts", "hyperopt_results", "plot", "strategies", ]
sub_dirs = ["backtest_results", "data", "hyperopts", "hyperopt_results", "notebooks",
"plot", "strategies", ]
folder = Path(directory)
if not folder.is_dir():
if create_dir:
@ -48,3 +51,26 @@ def create_userdata_dir(directory: str, create_dir=False) -> Path:
if not subfolder.is_dir():
subfolder.mkdir(parents=False)
return folder
def copy_sample_files(directory: Path, overwrite: bool = False) -> None:
"""
Copy files from templates to User data directory.
:param directory: Directory to copy data to
:param overwrite: Overwrite existing sample files
"""
if not directory.is_dir():
raise OperationalException(f"Directory `{directory}` does not exist.")
sourcedir = Path(__file__).parents[1] / "templates"
for source, target in USER_DATA_FILES.items():
targetdir = directory / target
if not targetdir.is_dir():
raise OperationalException(f"Directory `{targetdir}` does not exist.")
targetfile = targetdir / source
if targetfile.exists():
if not overwrite:
logger.warning(f"File `{targetfile}` exists already, not deploying sample file.")
continue
else:
logger.warning(f"File `{targetfile}` exists already, overwriting.")
shutil.copy(str(sourcedir / source), str(targetfile))

12
freqtrade/constants.py
View File

@ -22,6 +22,18 @@ AVAILABLE_PAIRLISTS = ['StaticPairList', 'VolumePairList', 'PrecisionFilter', 'P
DRY_RUN_WALLET = 999.9
MATH_CLOSE_PREC = 1e-14 # Precision used for float comparisons
USERPATH_HYPEROPTS = 'hyperopts'
USERPATH_STRATEGY = 'strategies'
# Soure files with destination directories within user-directory
USER_DATA_FILES = {
'sample_strategy.py': USERPATH_STRATEGY,
'sample_hyperopt_advanced.py': USERPATH_HYPEROPTS,
'sample_hyperopt_loss.py': USERPATH_HYPEROPTS,
'sample_hyperopt.py': USERPATH_HYPEROPTS,
'strategy_analysis_example.ipynb': 'notebooks',
}
TIMEFRAMES = [
'1m', '3m', '5m', '15m', '30m',
'1h', '2h', '4h', '6h', '8h', '12h',

13
freqtrade/misc.py
View File

@ -127,3 +127,16 @@ def round_dict(d, n):
def plural(num, singular: str, plural: str = None) -> str:
return singular if (num == 1 or num == -1) else plural or singular + 's'
def render_template(templatefile: str, arguments: dict = {}):
from jinja2 import Environment, PackageLoader, select_autoescape
env = Environment(
loader=PackageLoader('freqtrade', 'templates'),
autoescape=select_autoescape(['html', 'xml'])
)
template = env.get_template(templatefile)
return template.render(**arguments)

6
freqtrade/resolvers/hyperopt_resolver.py
View File

@ -8,7 +8,7 @@ from pathlib import Path
from typing import Optional, Dict
from freqtrade import OperationalException
from freqtrade.constants import DEFAULT_HYPEROPT_LOSS
from freqtrade.constants import DEFAULT_HYPEROPT_LOSS, USERPATH_HYPEROPTS
from freqtrade.optimize.hyperopt_interface import IHyperOpt
from freqtrade.optimize.hyperopt_loss_interface import IHyperOptLoss
from freqtrade.resolvers import IResolver
@ -58,7 +58,7 @@ class HyperOptResolver(IResolver):
current_path = Path(__file__).parent.parent.joinpath('optimize').resolve()
abs_paths = self.build_search_paths(config, current_path=current_path,
user_subdir='hyperopts', extra_dir=extra_dir)
user_subdir=USERPATH_HYPEROPTS, extra_dir=extra_dir)
hyperopt = self._load_object(paths=abs_paths, object_type=IHyperOpt,
object_name=hyperopt_name, kwargs={'config': config})
@ -110,7 +110,7 @@ class HyperOptLossResolver(IResolver):
current_path = Path(__file__).parent.parent.joinpath('optimize').resolve()
abs_paths = self.build_search_paths(config, current_path=current_path,
user_subdir='hyperopts', extra_dir=extra_dir)
user_subdir=USERPATH_HYPEROPTS, extra_dir=extra_dir)
hyperoptloss = self._load_object(paths=abs_paths, object_type=IHyperOptLoss,
object_name=hyper_loss_name)

3
freqtrade/resolvers/strategy_resolver.py
View File

@ -129,7 +129,8 @@ class StrategyResolver(IResolver):
current_path = Path(__file__).parent.parent.joinpath('strategy').resolve()
abs_paths = self.build_search_paths(config, current_path=current_path,
user_subdir='strategies', extra_dir=extra_dir)
user_subdir=constants.USERPATH_STRATEGY,
extra_dir=extra_dir)
if ":" in strategy_name:
logger.info("loading base64 encoded strategy")

127
freqtrade/templates/base_hyperopt.py.j2 Normal file
View File

@ -0,0 +1,127 @@
# 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 https://github.com/freqtrade/freqtrade/blob/develop/docs/hyperopt.md
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 roi_space, generate_roi_table, stoploss_space methods are no longer required to be
copied in every custom hyperopt. However, you may override them if you need the
'roi' and the 'stoploss' spaces that differ from the defaults offered by Freqtrade.
Sample implementation of these methods can be found in
https://github.com/freqtrade/freqtrade/blob/develop/user_data/hyperopts/sample_hyperopt_advanced.py
"""
@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']
))
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 [
{{ buy_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']
))
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 [
{{ sell_space | indent(12) }}
]

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@ -0,0 +1,138 @@
# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement
# --- Do not remove these libs ---
import numpy as np # noqa
import pandas as pd # noqa
from pandas import DataFrame
from freqtrade.strategy.interface import IStrategy
# --------------------------------
# Add your lib to import here
import talib.abstract as ta
import freqtrade.vendor.qtpylib.indicators as qtpylib
class {{ strategy }}(IStrategy):
"""
This is a strategy template to get you started.
More information in https://github.com/freqtrade/freqtrade/blob/develop/docs/bot-optimization.md
You can:
:return: a Dataframe with all mandatory indicators for the strategies
- Rename the class name (Do not forget to update class_name)
- Add any methods you want to build your strategy
- Add any lib you need to build your strategy
You must keep:
- the lib in the section "Do not remove these libs"
- the prototype for the methods: minimal_roi, stoploss, populate_indicators, populate_buy_trend,
populate_sell_trend, hyperopt_space, buy_strategy_generator
"""
# Strategy interface version - allow new iterations of the strategy interface.
# Check the documentation or the Sample strategy to get the latest version.
INTERFACE_VERSION = 2
# Minimal ROI designed for the strategy.
# This attribute will be overridden if the config file contains "minimal_roi".
minimal_roi = {
"60": 0.01,
"30": 0.02,
"0": 0.04
}
# Optimal stoploss designed for the strategy.
# This attribute will be overridden if the config file contains "stoploss".
stoploss = -0.10
# Trailing stoploss
trailing_stop = False
# trailing_stop_positive = 0.01
# trailing_stop_positive_offset = 0.0 # Disabled / not configured
# Optimal ticker interval for the strategy.
ticker_interval = '5m'
# Run "populate_indicators()" only for new candle.
process_only_new_candles = False
# These values can be overridden in the "ask_strategy" section in the config.
use_sell_signal = True
sell_profit_only = False
ignore_roi_if_buy_signal = False
# Number of candles the strategy requires before producing valid signals
startup_candle_count: int = 20
# Optional order type mapping.
order_types = {
'buy': 'limit',
'sell': 'limit',
'stoploss': 'market',
'stoploss_on_exchange': False
}
# Optional order time in force.
order_time_in_force = {
'buy': 'gtc',
'sell': 'gtc'
}
def informative_pairs(self):
"""
Define additional, informative pair/interval combinations to be cached from the exchange.
These pair/interval combinations are non-tradeable, unless they are part
of the whitelist as well.
For more information, please consult the documentation
:return: List of tuples in the format (pair, interval)
Sample: return [("ETH/USDT", "5m"),
("BTC/USDT", "15m"),
]
"""
return []
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Adds several different TA indicators to the given DataFrame
Performance Note: For the best performance be frugal on the number of indicators
you are using. Let uncomment only the indicator you are using in your strategies
or your hyperopt configuration, otherwise you will waste your memory and CPU usage.
:param dataframe: Raw data from the exchange and parsed by parse_ticker_dataframe()
:param metadata: Additional information, like the currently traded pair
:return: a Dataframe with all mandatory indicators for the strategies
"""
{{ indicators | indent(8) }}
return dataframe
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Based on TA indicators, populates the buy signal for the given dataframe
:param dataframe: DataFrame populated with indicators
:param metadata: Additional information, like the currently traded pair
:return: DataFrame with buy column
"""
dataframe.loc[
(
{{ buy_trend | indent(16) }}
(dataframe['volume'] > 0) # Make sure Volume is not 0
),
'buy'] = 1
return dataframe
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Based on TA indicators, populates the sell signal for the given dataframe
:param dataframe: DataFrame populated with indicators
:param metadata: Additional information, like the currently traded pair
:return: DataFrame with buy column
"""
dataframe.loc[
(
{{ sell_trend | indent(16) }}
(dataframe['volume'] > 0) # Make sure Volume is not 0
),
'sell'] = 1
return dataframe

9
user_data/hyperopts/sample_hyperopt.py → freqtrade/templates/sample_hyperopt.py
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@ -1,16 +1,21 @@
# 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 talib.abstract as ta
import pandas as pd # noqa
from pandas import DataFrame
from skopt.space import Categorical, Dimension, Integer, Real # noqa
import freqtrade.vendor.qtpylib.indicators as qtpylib
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):
"""

15
user_data/hyperopts/sample_hyperopt_advanced.py → freqtrade/templates/sample_hyperopt_advanced.py
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@ -1,18 +1,21 @@
# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement
# --- Do not remove these libs ---
from functools import reduce
from math import exp
from typing import Any, Callable, Dict, List
from datetime import datetime
import numpy as np# noqa F401
import talib.abstract as ta
import numpy as np # noqa
import pandas as pd # noqa
from pandas import DataFrame
from skopt.space import Categorical, Dimension, Integer, Real
from skopt.space import Categorical, Dimension, Integer, Real # noqa
import freqtrade.vendor.qtpylib.indicators as qtpylib
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):
"""

0
user_data/hyperopts/sample_hyperopt_loss.py → freqtrade/templates/sample_hyperopt_loss.py
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194
user_data/strategies/sample_strategy.py → freqtrade/templates/sample_strategy.py
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@ -1,13 +1,16 @@
# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement
# --- Do not remove these libs ---
from freqtrade.strategy.interface import IStrategy
import numpy as np # noqa
import pandas as pd # noqa
from pandas import DataFrame
# --------------------------------
from freqtrade.strategy.interface import IStrategy
# --------------------------------
# Add your lib to import here
import talib.abstract as ta
import freqtrade.vendor.qtpylib.indicators as qtpylib
import numpy # noqa
# This class is a sample. Feel free to customize it.
@ -110,19 +113,18 @@ class SampleStrategy(IStrategy):
# ADX
dataframe['adx'] = ta.ADX(dataframe)
"""
# Aroon, Aroon Oscillator
aroon = ta.AROON(dataframe)
dataframe['aroonup'] = aroon['aroonup']
dataframe['aroondown'] = aroon['aroondown']
dataframe['aroonosc'] = ta.AROONOSC(dataframe)
# # Aroon, Aroon Oscillator
# aroon = ta.AROON(dataframe)
# dataframe['aroonup'] = aroon['aroonup']
# dataframe['aroondown'] = aroon['aroondown']
# dataframe['aroonosc'] = ta.AROONOSC(dataframe)
# Awesome oscillator
dataframe['ao'] = qtpylib.awesome_oscillator(dataframe)
# # Awesome oscillator
# dataframe['ao'] = qtpylib.awesome_oscillator(dataframe)
# # Commodity Channel Index: values Oversold:<-100, Overbought:>100
# dataframe['cci'] = ta.CCI(dataframe)
# Commodity Channel Index: values Oversold:<-100, Overbought:>100
dataframe['cci'] = ta.CCI(dataframe)
"""
# MACD
macd = ta.MACD(dataframe)
dataframe['macd'] = macd['macd']
@ -132,42 +134,39 @@ class SampleStrategy(IStrategy):
# MFI
dataframe['mfi'] = ta.MFI(dataframe)
"""
# Minus Directional Indicator / Movement
dataframe['minus_dm'] = ta.MINUS_DM(dataframe)
dataframe['minus_di'] = ta.MINUS_DI(dataframe)
# # Minus Directional Indicator / Movement
# dataframe['minus_dm'] = ta.MINUS_DM(dataframe)
# dataframe['minus_di'] = ta.MINUS_DI(dataframe)
# Plus Directional Indicator / Movement
dataframe['plus_dm'] = ta.PLUS_DM(dataframe)
dataframe['plus_di'] = ta.PLUS_DI(dataframe)
dataframe['minus_di'] = ta.MINUS_DI(dataframe)
# # Plus Directional Indicator / Movement
# dataframe['plus_dm'] = ta.PLUS_DM(dataframe)
# dataframe['plus_di'] = ta.PLUS_DI(dataframe)
# dataframe['minus_di'] = ta.MINUS_DI(dataframe)
# ROC
dataframe['roc'] = ta.ROC(dataframe)
# # ROC
# dataframe['roc'] = ta.ROC(dataframe)
# Inverse Fisher transform on RSI, values [-1.0, 1.0] (https://goo.gl/2JGGoy)
rsi = 0.1 * (dataframe['rsi'] - 50)
dataframe['fisher_rsi'] = (numpy.exp(2 * rsi) - 1) / (numpy.exp(2 * rsi) + 1)
# # Inverse Fisher transform on RSI, values [-1.0, 1.0] (https://goo.gl/2JGGoy)
# rsi = 0.1 * (dataframe['rsi'] - 50)
# dataframe['fisher_rsi'] = (np.exp(2 * rsi) - 1) / (np.exp(2 * rsi) + 1)
# Inverse Fisher transform on RSI normalized, value [0.0, 100.0] (https://goo.gl/2JGGoy)
dataframe['fisher_rsi_norma'] = 50 * (dataframe['fisher_rsi'] + 1)
# # Inverse Fisher transform on RSI normalized, value [0.0, 100.0] (https://goo.gl/2JGGoy)
# dataframe['fisher_rsi_norma'] = 50 * (dataframe['fisher_rsi'] + 1)
# # Stoch
# stoch = ta.STOCH(dataframe)
# dataframe['slowd'] = stoch['slowd']
# dataframe['slowk'] = stoch['slowk']
# Stoch
stoch = ta.STOCH(dataframe)
dataframe['slowd'] = stoch['slowd']
dataframe['slowk'] = stoch['slowk']
"""
# Stoch fast
stoch_fast = ta.STOCHF(dataframe)
dataframe['fastd'] = stoch_fast['fastd']
dataframe['fastk'] = stoch_fast['fastk']
"""
# Stoch RSI
stoch_rsi = ta.STOCHRSI(dataframe)
dataframe['fastd_rsi'] = stoch_rsi['fastd']
dataframe['fastk_rsi'] = stoch_rsi['fastk']
"""
# # Stoch RSI
# stoch_rsi = ta.STOCHRSI(dataframe)
# dataframe['fastd_rsi'] = stoch_rsi['fastd']
# dataframe['fastk_rsi'] = stoch_rsi['fastk']
# Overlap Studies
# ------------------------------------
@ -178,17 +177,16 @@ class SampleStrategy(IStrategy):
dataframe['bb_middleband'] = bollinger['mid']
dataframe['bb_upperband'] = bollinger['upper']
"""
# EMA - Exponential Moving Average
dataframe['ema3'] = ta.EMA(dataframe, timeperiod=3)
dataframe['ema5'] = ta.EMA(dataframe, timeperiod=5)
dataframe['ema10'] = ta.EMA(dataframe, timeperiod=10)
dataframe['ema50'] = ta.EMA(dataframe, timeperiod=50)
dataframe['ema100'] = ta.EMA(dataframe, timeperiod=100)
# # EMA - Exponential Moving Average
# dataframe['ema3'] = ta.EMA(dataframe, timeperiod=3)
# dataframe['ema5'] = ta.EMA(dataframe, timeperiod=5)
# dataframe['ema10'] = ta.EMA(dataframe, timeperiod=10)
# dataframe['ema50'] = ta.EMA(dataframe, timeperiod=50)
# dataframe['ema100'] = ta.EMA(dataframe, timeperiod=100)
# # SMA - Simple Moving Average
# dataframe['sma'] = ta.SMA(dataframe, timeperiod=40)
# SMA - Simple Moving Average
dataframe['sma'] = ta.SMA(dataframe, timeperiod=40)
"""
# SAR Parabol
dataframe['sar'] = ta.SAR(dataframe)
@ -204,65 +202,57 @@ class SampleStrategy(IStrategy):
# Pattern Recognition - Bullish candlestick patterns
# ------------------------------------
"""
# Hammer: values [0, 100]
dataframe['CDLHAMMER'] = ta.CDLHAMMER(dataframe)
# Inverted Hammer: values [0, 100]
dataframe['CDLINVERTEDHAMMER'] = ta.CDLINVERTEDHAMMER(dataframe)
# Dragonfly Doji: values [0, 100]
dataframe['CDLDRAGONFLYDOJI'] = ta.CDLDRAGONFLYDOJI(dataframe)
# Piercing Line: values [0, 100]
dataframe['CDLPIERCING'] = ta.CDLPIERCING(dataframe) # values [0, 100]
# Morningstar: values [0, 100]
dataframe['CDLMORNINGSTAR'] = ta.CDLMORNINGSTAR(dataframe) # values [0, 100]
# Three White Soldiers: values [0, 100]
dataframe['CDL3WHITESOLDIERS'] = ta.CDL3WHITESOLDIERS(dataframe) # values [0, 100]
"""
# # Hammer: values [0, 100]
# dataframe['CDLHAMMER'] = ta.CDLHAMMER(dataframe)
# # Inverted Hammer: values [0, 100]
# dataframe['CDLINVERTEDHAMMER'] = ta.CDLINVERTEDHAMMER(dataframe)
# # Dragonfly Doji: values [0, 100]
# dataframe['CDLDRAGONFLYDOJI'] = ta.CDLDRAGONFLYDOJI(dataframe)
# # Piercing Line: values [0, 100]
# dataframe['CDLPIERCING'] = ta.CDLPIERCING(dataframe) # values [0, 100]
# # Morningstar: values [0, 100]
# dataframe['CDLMORNINGSTAR'] = ta.CDLMORNINGSTAR(dataframe) # values [0, 100]
# # Three White Soldiers: values [0, 100]
# dataframe['CDL3WHITESOLDIERS'] = ta.CDL3WHITESOLDIERS(dataframe) # values [0, 100]
# Pattern Recognition - Bearish candlestick patterns
# ------------------------------------
"""
# Hanging Man: values [0, 100]
dataframe['CDLHANGINGMAN'] = ta.CDLHANGINGMAN(dataframe)
# Shooting Star: values [0, 100]
dataframe['CDLSHOOTINGSTAR'] = ta.CDLSHOOTINGSTAR(dataframe)
# Gravestone Doji: values [0, 100]
dataframe['CDLGRAVESTONEDOJI'] = ta.CDLGRAVESTONEDOJI(dataframe)
# Dark Cloud Cover: values [0, 100]
dataframe['CDLDARKCLOUDCOVER'] = ta.CDLDARKCLOUDCOVER(dataframe)
# Evening Doji Star: values [0, 100]
dataframe['CDLEVENINGDOJISTAR'] = ta.CDLEVENINGDOJISTAR(dataframe)
# Evening Star: values [0, 100]
dataframe['CDLEVENINGSTAR'] = ta.CDLEVENINGSTAR(dataframe)
"""
# # Hanging Man: values [0, 100]
# dataframe['CDLHANGINGMAN'] = ta.CDLHANGINGMAN(dataframe)
# # Shooting Star: values [0, 100]
# dataframe['CDLSHOOTINGSTAR'] = ta.CDLSHOOTINGSTAR(dataframe)
# # Gravestone Doji: values [0, 100]
# dataframe['CDLGRAVESTONEDOJI'] = ta.CDLGRAVESTONEDOJI(dataframe)
# # Dark Cloud Cover: values [0, 100]
# dataframe['CDLDARKCLOUDCOVER'] = ta.CDLDARKCLOUDCOVER(dataframe)
# # Evening Doji Star: values [0, 100]
# dataframe['CDLEVENINGDOJISTAR'] = ta.CDLEVENINGDOJISTAR(dataframe)
# # Evening Star: values [0, 100]
# dataframe['CDLEVENINGSTAR'] = ta.CDLEVENINGSTAR(dataframe)
# Pattern Recognition - Bullish/Bearish candlestick patterns
# ------------------------------------
"""
# Three Line Strike: values [0, -100, 100]
dataframe['CDL3LINESTRIKE'] = ta.CDL3LINESTRIKE(dataframe)
# Spinning Top: values [0, -100, 100]
dataframe['CDLSPINNINGTOP'] = ta.CDLSPINNINGTOP(dataframe) # values [0, -100, 100]
# Engulfing: values [0, -100, 100]
dataframe['CDLENGULFING'] = ta.CDLENGULFING(dataframe) # values [0, -100, 100]
# Harami: values [0, -100, 100]
dataframe['CDLHARAMI'] = ta.CDLHARAMI(dataframe) # values [0, -100, 100]
# Three Outside Up/Down: values [0, -100, 100]
dataframe['CDL3OUTSIDE'] = ta.CDL3OUTSIDE(dataframe) # values [0, -100, 100]
# Three Inside Up/Down: values [0, -100, 100]
dataframe['CDL3INSIDE'] = ta.CDL3INSIDE(dataframe) # values [0, -100, 100]
"""
# # Three Line Strike: values [0, -100, 100]
# dataframe['CDL3LINESTRIKE'] = ta.CDL3LINESTRIKE(dataframe)
# # Spinning Top: values [0, -100, 100]
# dataframe['CDLSPINNINGTOP'] = ta.CDLSPINNINGTOP(dataframe) # values [0, -100, 100]
# # Engulfing: values [0, -100, 100]
# dataframe['CDLENGULFING'] = ta.CDLENGULFING(dataframe) # values [0, -100, 100]
# # Harami: values [0, -100, 100]
# dataframe['CDLHARAMI'] = ta.CDLHARAMI(dataframe) # values [0, -100, 100]
# # Three Outside Up/Down: values [0, -100, 100]
# dataframe['CDL3OUTSIDE'] = ta.CDL3OUTSIDE(dataframe) # values [0, -100, 100]
# # Three Inside Up/Down: values [0, -100, 100]
# dataframe['CDL3INSIDE'] = ta.CDL3INSIDE(dataframe) # values [0, -100, 100]
# Chart type
# ------------------------------------
"""
# Heikinashi stategy
heikinashi = qtpylib.heikinashi(dataframe)
dataframe['ha_open'] = heikinashi['open']
dataframe['ha_close'] = heikinashi['close']
dataframe['ha_high'] = heikinashi['high']
dataframe['ha_low'] = heikinashi['low']
"""
# # Chart type
# # ------------------------------------
# # Heikinashi stategy
# heikinashi = qtpylib.heikinashi(dataframe)
# dataframe['ha_open'] = heikinashi['open']
# dataframe['ha_close'] = heikinashi['close']
# dataframe['ha_high'] = heikinashi['high']
# dataframe['ha_low'] = heikinashi['low']
# Retrieve best bid and best ask from the orderbook
# ------------------------------------

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3
freqtrade/templates/subtemplates/buy_trend_full.j2 Normal file
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@ -0,0 +1,3 @@
(qtpylib.crossed_above(dataframe['rsi'], 30)) & # Signal: RSI crosses above 30
(dataframe['tema'] <= dataframe['bb_middleband']) & # Guard: tema below BB middle
(dataframe['tema'] > dataframe['tema'].shift(1)) & # Guard: tema is raising

1
freqtrade/templates/subtemplates/buy_trend_minimal.j2 Normal file
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@ -0,0 +1 @@
(qtpylib.crossed_above(dataframe['rsi'], 30)) & # Signal: RSI crosses above 30

8
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@ -0,0 +1,8 @@
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
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@ -0,0 +1,2 @@
if params.get('rsi-enabled'):
conditions.append(dataframe['rsi'] < params['rsi-value'])

9
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@ -0,0 +1,9 @@
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
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@ -0,0 +1,3 @@
Integer(20, 40, name='rsi-value'),
Categorical([True, False], name='rsi-enabled'),
Categorical(['bb_lower', 'macd_cross_signal', 'sar_reversal'], name='trigger')

8
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@ -0,0 +1,8 @@
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'])

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

11
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@ -0,0 +1,11 @@
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
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@ -0,0 +1,5 @@
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')

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@ -0,0 +1,161 @@
# Momentum Indicators
# ------------------------------------
# RSI
dataframe['rsi'] = ta.RSI(dataframe)
# ADX
dataframe['adx'] = ta.ADX(dataframe)
# # Aroon, Aroon Oscillator
# aroon = ta.AROON(dataframe)
# dataframe['aroonup'] = aroon['aroonup']
# dataframe['aroondown'] = aroon['aroondown']
# dataframe['aroonosc'] = ta.AROONOSC(dataframe)
# # Awesome oscillator
# dataframe['ao'] = qtpylib.awesome_oscillator(dataframe)
# # Commodity Channel Index: values Oversold:<-100, Overbought:>100
# dataframe['cci'] = ta.CCI(dataframe)
# MACD
macd = ta.MACD(dataframe)
dataframe['macd'] = macd['macd']
dataframe['macdsignal'] = macd['macdsignal']
dataframe['macdhist'] = macd['macdhist']
# MFI
dataframe['mfi'] = ta.MFI(dataframe)
# # Minus Directional Indicator / Movement
# dataframe['minus_dm'] = ta.MINUS_DM(dataframe)
# dataframe['minus_di'] = ta.MINUS_DI(dataframe)
# # Plus Directional Indicator / Movement
# dataframe['plus_dm'] = ta.PLUS_DM(dataframe)
# dataframe['plus_di'] = ta.PLUS_DI(dataframe)
# dataframe['minus_di'] = ta.MINUS_DI(dataframe)
# # ROC
# dataframe['roc'] = ta.ROC(dataframe)
# # Inverse Fisher transform on RSI, values [-1.0, 1.0] (https://goo.gl/2JGGoy)
# rsi = 0.1 * (dataframe['rsi'] - 50)
# dataframe['fisher_rsi'] = (np.exp(2 * rsi) - 1) / (np.exp(2 * rsi) + 1)
# # Inverse Fisher transform on RSI normalized, value [0.0, 100.0] (https://goo.gl/2JGGoy)
# dataframe['fisher_rsi_norma'] = 50 * (dataframe['fisher_rsi'] + 1)
# # Stoch
# stoch = ta.STOCH(dataframe)
# dataframe['slowd'] = stoch['slowd']
# dataframe['slowk'] = stoch['slowk']
# Stoch fast
stoch_fast = ta.STOCHF(dataframe)
dataframe['fastd'] = stoch_fast['fastd']
dataframe['fastk'] = stoch_fast['fastk']
# # Stoch RSI
# stoch_rsi = ta.STOCHRSI(dataframe)
# dataframe['fastd_rsi'] = stoch_rsi['fastd']
# dataframe['fastk_rsi'] = stoch_rsi['fastk']
# Overlap Studies
# ------------------------------------
# Bollinger bands
bollinger = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=2)
dataframe['bb_lowerband'] = bollinger['lower']
dataframe['bb_middleband'] = bollinger['mid']
dataframe['bb_upperband'] = bollinger['upper']
# # EMA - Exponential Moving Average
# dataframe['ema3'] = ta.EMA(dataframe, timeperiod=3)
# dataframe['ema5'] = ta.EMA(dataframe, timeperiod=5)
# dataframe['ema10'] = ta.EMA(dataframe, timeperiod=10)
# dataframe['ema50'] = ta.EMA(dataframe, timeperiod=50)
# dataframe['ema100'] = ta.EMA(dataframe, timeperiod=100)
# # SMA - Simple Moving Average
# dataframe['sma'] = ta.SMA(dataframe, timeperiod=40)
# SAR Parabol
dataframe['sar'] = ta.SAR(dataframe)
# TEMA - Triple Exponential Moving Average
dataframe['tema'] = ta.TEMA(dataframe, timeperiod=9)
# Cycle Indicator
# ------------------------------------
# Hilbert Transform Indicator - SineWave
hilbert = ta.HT_SINE(dataframe)
dataframe['htsine'] = hilbert['sine']
dataframe['htleadsine'] = hilbert['leadsine']
# Pattern Recognition - Bullish candlestick patterns
# ------------------------------------
# # Hammer: values [0, 100]
# dataframe['CDLHAMMER'] = ta.CDLHAMMER(dataframe)
# # Inverted Hammer: values [0, 100]
# dataframe['CDLINVERTEDHAMMER'] = ta.CDLINVERTEDHAMMER(dataframe)
# # Dragonfly Doji: values [0, 100]
# dataframe['CDLDRAGONFLYDOJI'] = ta.CDLDRAGONFLYDOJI(dataframe)
# # Piercing Line: values [0, 100]
# dataframe['CDLPIERCING'] = ta.CDLPIERCING(dataframe) # values [0, 100]
# # Morningstar: values [0, 100]
# dataframe['CDLMORNINGSTAR'] = ta.CDLMORNINGSTAR(dataframe) # values [0, 100]
# # Three White Soldiers: values [0, 100]
# dataframe['CDL3WHITESOLDIERS'] = ta.CDL3WHITESOLDIERS(dataframe) # values [0, 100]
# Pattern Recognition - Bearish candlestick patterns
# ------------------------------------
# # Hanging Man: values [0, 100]
# dataframe['CDLHANGINGMAN'] = ta.CDLHANGINGMAN(dataframe)
# # Shooting Star: values [0, 100]
# dataframe['CDLSHOOTINGSTAR'] = ta.CDLSHOOTINGSTAR(dataframe)
# # Gravestone Doji: values [0, 100]
# dataframe['CDLGRAVESTONEDOJI'] = ta.CDLGRAVESTONEDOJI(dataframe)
# # Dark Cloud Cover: values [0, 100]
# dataframe['CDLDARKCLOUDCOVER'] = ta.CDLDARKCLOUDCOVER(dataframe)
# # Evening Doji Star: values [0, 100]
# dataframe['CDLEVENINGDOJISTAR'] = ta.CDLEVENINGDOJISTAR(dataframe)
# # Evening Star: values [0, 100]
# dataframe['CDLEVENINGSTAR'] = ta.CDLEVENINGSTAR(dataframe)
# Pattern Recognition - Bullish/Bearish candlestick patterns
# ------------------------------------
# # Three Line Strike: values [0, -100, 100]
# dataframe['CDL3LINESTRIKE'] = ta.CDL3LINESTRIKE(dataframe)
# # Spinning Top: values [0, -100, 100]
# dataframe['CDLSPINNINGTOP'] = ta.CDLSPINNINGTOP(dataframe) # values [0, -100, 100]
# # Engulfing: values [0, -100, 100]
# dataframe['CDLENGULFING'] = ta.CDLENGULFING(dataframe) # values [0, -100, 100]
# # Harami: values [0, -100, 100]
# dataframe['CDLHARAMI'] = ta.CDLHARAMI(dataframe) # values [0, -100, 100]
# # Three Outside Up/Down: values [0, -100, 100]
# dataframe['CDL3OUTSIDE'] = ta.CDL3OUTSIDE(dataframe) # values [0, -100, 100]
# # Three Inside Up/Down: values [0, -100, 100]
# dataframe['CDL3INSIDE'] = ta.CDL3INSIDE(dataframe) # values [0, -100, 100]
# # Chart type
# # ------------------------------------
# # Heikinashi stategy
# heikinashi = qtpylib.heikinashi(dataframe)
# dataframe['ha_open'] = heikinashi['open']
# dataframe['ha_close'] = heikinashi['close']
# dataframe['ha_high'] = heikinashi['high']
# dataframe['ha_low'] = heikinashi['low']
# Retrieve best bid and best ask from the orderbook
# ------------------------------------
"""
# first check if dataprovider is available
if self.dp:
if self.dp.runmode in ('live', 'dry_run'):
ob = self.dp.orderbook(metadata['pair'], 1)
dataframe['best_bid'] = ob['bids'][0][0]
dataframe['best_ask'] = ob['asks'][0][0]
"""

17
freqtrade/templates/subtemplates/indicators_minimal.j2 Normal file
View File

@ -0,0 +1,17 @@
# Momentum Indicators
# ------------------------------------
# RSI
dataframe['rsi'] = ta.RSI(dataframe)
# Retrieve best bid and best ask from the orderbook
# ------------------------------------
"""
# first check if dataprovider is available
if self.dp:
if self.dp.runmode in ('live', 'dry_run'):
ob = self.dp.orderbook(metadata['pair'], 1)
dataframe['best_bid'] = ob['bids'][0][0]
dataframe['best_ask'] = ob['asks'][0][0]
"""

3
freqtrade/templates/subtemplates/sell_trend_full.j2 Normal file
View File

@ -0,0 +1,3 @@
(qtpylib.crossed_above(dataframe['rsi'], 70)) & # Signal: RSI crosses above 70
(dataframe['tema'] > dataframe['bb_middleband']) & # Guard: tema above BB middle
(dataframe['tema'] < dataframe['tema'].shift(1)) & # Guard: tema is falling

1
freqtrade/templates/subtemplates/sell_trend_minimal.j2 Normal file
View File

@ -0,0 +1 @@
(qtpylib.crossed_above(dataframe['rsi'], 70)) & # Signal: RSI crosses above 70

100
freqtrade/utils.py
View File

@ -1,3 +1,4 @@
import csv
import logging
import sys
from collections import OrderedDict
@ -6,20 +7,22 @@ from pathlib import Path
from typing import Any, Dict, List
import arrow
import csv
import rapidjson
from colorama import init as colorama_init
from tabulate import tabulate
from freqtrade import OperationalException
from freqtrade.configuration import Configuration, TimeRange, remove_credentials
from freqtrade.configuration.directory_operations import create_userdata_dir
from freqtrade.configuration import (Configuration, TimeRange,
remove_credentials)
from freqtrade.configuration.directory_operations import (copy_sample_files,
create_userdata_dir)
from freqtrade.constants import USERPATH_HYPEROPTS, USERPATH_STRATEGY
from freqtrade.data.history import (convert_trades_to_ohlcv,
refresh_backtest_ohlcv_data,
refresh_backtest_trades_data)
from freqtrade.exchange import (available_exchanges, ccxt_exchanges, market_is_active,
symbol_is_pair)
from freqtrade.misc import plural
from freqtrade.exchange import (available_exchanges, ccxt_exchanges,
market_is_active, symbol_is_pair)
from freqtrade.misc import plural, render_template
from freqtrade.optimize.hyperopt import Hyperopt
from freqtrade.resolvers import ExchangeResolver
from freqtrade.state import RunMode
@ -84,12 +87,95 @@ def start_create_userdir(args: Dict[str, Any]) -> None:
:return: None
"""
if "user_data_dir" in args and args["user_data_dir"]:
create_userdata_dir(args["user_data_dir"], create_dir=True)
userdir = create_userdata_dir(args["user_data_dir"], create_dir=True)
copy_sample_files(userdir, overwrite=args["reset"])
else:
logger.warning("`create-userdir` requires --userdir to be set.")
sys.exit(1)
def deploy_new_strategy(strategy_name, strategy_path: Path, subtemplate: str):
"""
Deploy new strategy from template to strategy_path
"""
indicators = render_template(templatefile=f"subtemplates/indicators_{subtemplate}.j2",)
buy_trend = render_template(templatefile=f"subtemplates/buy_trend_{subtemplate}.j2",)
sell_trend = render_template(templatefile=f"subtemplates/sell_trend_{subtemplate}.j2",)
strategy_text = render_template(templatefile='base_strategy.py.j2',
arguments={"strategy": strategy_name,
"indicators": indicators,
"buy_trend": buy_trend,
"sell_trend": sell_trend,
})
logger.info(f"Writing strategy to `{strategy_path}`.")
strategy_path.write_text(strategy_text)
def start_new_strategy(args: Dict[str, Any]) -> None:
config = setup_utils_configuration(args, RunMode.UTIL_NO_EXCHANGE)
if "strategy" in args and args["strategy"]:
if args["strategy"] == "DefaultStrategy":
raise OperationalException("DefaultStrategy is not allowed as name.")
new_path = config['user_data_dir'] / USERPATH_STRATEGY / (args["strategy"] + ".py")
if new_path.exists():
raise OperationalException(f"`{new_path}` already exists. "
"Please choose another Strategy Name.")
deploy_new_strategy(args['strategy'], new_path, args['template'])
else:
raise OperationalException("`new-strategy` requires --strategy to be set.")
def deploy_new_hyperopt(hyperopt_name, hyperopt_path: Path, subtemplate: str):
"""
Deploys a new hyperopt template to hyperopt_path
"""
buy_guards = render_template(
templatefile=f"subtemplates/hyperopt_buy_guards_{subtemplate}.j2",)
sell_guards = render_template(
templatefile=f"subtemplates/hyperopt_sell_guards_{subtemplate}.j2",)
buy_space = render_template(
templatefile=f"subtemplates/hyperopt_buy_space_{subtemplate}.j2",)
sell_space = render_template(
templatefile=f"subtemplates/hyperopt_sell_space_{subtemplate}.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"]:
if args["hyperopt"] == "DefaultHyperopt":
raise OperationalException("DefaultHyperopt is not allowed as name.")
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 Strategy Name.")
deploy_new_hyperopt(args['hyperopt'], new_path, args['template'])
else:
raise OperationalException("`new-hyperopt` requires --hyperopt to be set.")
def start_download_data(args: Dict[str, Any]) -> None:
"""
Download data (former download_backtest_data.py script)

5
requirements-common.txt
View File

@ -1,6 +1,6 @@
# requirements without requirements installable via conda
# mainly used for Raspberry pi installs
ccxt==1.19.54
ccxt==1.19.86
SQLAlchemy==1.3.11
python-telegram-bot==12.2.0
arrow==0.15.4
@ -8,10 +8,11 @@ cachetools==3.1.1
requests==2.22.0
urllib3==1.25.7
wrapt==1.11.2
jsonschema==3.1.1
jsonschema==3.2.0
TA-Lib==0.4.17
tabulate==0.8.6
coinmarketcap==5.0.3
jinja2==2.10.3
# find first, C search in arrays
py_find_1st==1.1.4

4
requirements-dev.txt
View File

@ -8,10 +8,10 @@ flake8==3.7.9
flake8-type-annotations==0.1.0
flake8-tidy-imports==3.1.0
mypy==0.740
pytest==5.2.4
pytest==5.3.0
pytest-asyncio==0.10.0
pytest-cov==2.8.1
pytest-mock==1.11.2
pytest-mock==1.12.1
pytest-random-order==1.0.4
# Convert jupyter notebooks to markdown documents

2
requirements-hyperopt.txt
View File

@ -2,7 +2,7 @@
-r requirements.txt
# Required for hyperopt
scipy==1.3.2
scipy==1.3.3
scikit-learn==0.21.3
scikit-optimize==0.5.2
filelock==3.0.12

1
setup.py
View File

@ -78,6 +78,7 @@ setup(name='freqtrade',
'python-rapidjson',
'sdnotify',
'colorama',
'jinja2',
# from requirements.txt
'numpy',
'pandas',

1
tests/optimize/test_backtesting.py
View File

@ -869,6 +869,7 @@ def test_backtest_start_multi_strat(default_conf, mocker, caplog, testdatadir):
'backtesting',
'--config', 'config.json',
'--datadir', str(testdatadir),
'--strategy-path', str(Path(__file__).parents[2] / 'freqtrade/templates'),
'--ticker-interval', '1m',
'--timerange', '1510694220-1510700340',
'--enable-position-stacking',

10
tests/strategy/test_strategy.py
View File

@ -36,13 +36,15 @@ def test_search_strategy():
def test_load_strategy(default_conf, result):
default_conf.update({'strategy': 'SampleStrategy'})
default_conf.update({'strategy': 'SampleStrategy',
'strategy_path': str(Path(__file__).parents[2] / 'freqtrade/templates')
})
resolver = StrategyResolver(default_conf)
assert 'rsi' in resolver.strategy.advise_indicators(result, {'pair': 'ETH/BTC'})
def test_load_strategy_base64(result, caplog, default_conf):
with open("user_data/strategies/sample_strategy.py", "rb") as file:
with (Path(__file__).parents[2] / 'freqtrade/templates/sample_strategy.py').open("rb") as file:
encoded_string = urlsafe_b64encode(file.read()).decode("utf-8")
default_conf.update({'strategy': 'SampleStrategy:{}'.format(encoded_string)})
@ -54,10 +56,10 @@ def test_load_strategy_base64(result, caplog, default_conf):
def test_load_strategy_invalid_directory(result, caplog, default_conf):
default_conf['strategy'] = 'SampleStrategy'
default_conf['strategy'] = 'DefaultStrategy'
resolver = StrategyResolver(default_conf)
extra_dir = Path.cwd() / 'some/path'
resolver._load_strategy('SampleStrategy', config=default_conf, extra_dir=extra_dir)
resolver._load_strategy('DefaultStrategy', config=default_conf, extra_dir=extra_dir)
assert log_has_re(r'Path .*' + r'some.*path.*' + r'.* does not exist', caplog)

41
tests/test_configuration.py
View File

@ -17,8 +17,6 @@ from freqtrade.configuration.config_validation import validate_config_schema
from freqtrade.configuration.deprecated_settings import (
check_conflicting_settings, process_deprecated_setting,
process_temporary_deprecated_settings)
from freqtrade.configuration.directory_operations import (create_datadir,
create_userdata_dir)
from freqtrade.configuration.load_config import load_config_file
from freqtrade.constants import DEFAULT_DB_DRYRUN_URL, DEFAULT_DB_PROD_URL
from freqtrade.loggers import _set_loggers
@ -670,45 +668,6 @@ def test_validate_default_conf(default_conf) -> None:
validate(default_conf, constants.CONF_SCHEMA, Draft4Validator)
def test_create_datadir(mocker, default_conf, caplog) -> None:
mocker.patch.object(Path, "is_dir", MagicMock(return_value=False))
md = mocker.patch.object(Path, 'mkdir', MagicMock())
create_datadir(default_conf, '/foo/bar')
assert md.call_args[1]['parents'] is True
assert log_has('Created data directory: /foo/bar', caplog)
def test_create_userdata_dir(mocker, default_conf, caplog) -> None:
mocker.patch.object(Path, "is_dir", MagicMock(return_value=False))
md = mocker.patch.object(Path, 'mkdir', MagicMock())
x = create_userdata_dir('/tmp/bar', create_dir=True)
assert md.call_count == 7
assert md.call_args[1]['parents'] is False
assert log_has(f'Created user-data directory: {Path("/tmp/bar")}', caplog)
assert isinstance(x, Path)
assert str(x) == str(Path("/tmp/bar"))
def test_create_userdata_dir_exists(mocker, default_conf, caplog) -> None:
mocker.patch.object(Path, "is_dir", MagicMock(return_value=True))
md = mocker.patch.object(Path, 'mkdir', MagicMock())
create_userdata_dir('/tmp/bar')
assert md.call_count == 0
def test_create_userdata_dir_exists_exception(mocker, default_conf, caplog) -> None:
mocker.patch.object(Path, "is_dir", MagicMock(return_value=False))
md = mocker.patch.object(Path, 'mkdir', MagicMock())
with pytest.raises(OperationalException,
match=r'Directory `.{1,2}tmp.{1,2}bar` does not exist.*'):
create_userdata_dir('/tmp/bar', create_dir=False)
assert md.call_count == 0
def test_validate_tsl(default_conf):
default_conf['stoploss'] = 0.0
with pytest.raises(OperationalException, match='The config stoploss needs to be different '

91
tests/test_directory_operations.py Normal file
View File

@ -0,0 +1,91 @@
# pragma pylint: disable=missing-docstring, protected-access, invalid-name
from pathlib import Path
from unittest.mock import MagicMock
import pytest
from freqtrade import OperationalException
from freqtrade.configuration.directory_operations import (copy_sample_files,
create_datadir,
create_userdata_dir)
from tests.conftest import log_has, log_has_re
def test_create_datadir(mocker, default_conf, caplog) -> None:
mocker.patch.object(Path, "is_dir", MagicMock(return_value=False))
md = mocker.patch.object(Path, 'mkdir', MagicMock())
create_datadir(default_conf, '/foo/bar')
assert md.call_args[1]['parents'] is True
assert log_has('Created data directory: /foo/bar', caplog)
def test_create_userdata_dir(mocker, default_conf, caplog) -> None:
mocker.patch.object(Path, "is_dir", MagicMock(return_value=False))
md = mocker.patch.object(Path, 'mkdir', MagicMock())
x = create_userdata_dir('/tmp/bar', create_dir=True)
assert md.call_count == 8
assert md.call_args[1]['parents'] is False
assert log_has(f'Created user-data directory: {Path("/tmp/bar")}', caplog)
assert isinstance(x, Path)
assert str(x) == str(Path("/tmp/bar"))
def test_create_userdata_dir_exists(mocker, default_conf, caplog) -> None:
mocker.patch.object(Path, "is_dir", MagicMock(return_value=True))
md = mocker.patch.object(Path, 'mkdir', MagicMock())
create_userdata_dir('/tmp/bar')
assert md.call_count == 0
def test_create_userdata_dir_exists_exception(mocker, default_conf, caplog) -> None:
mocker.patch.object(Path, "is_dir", MagicMock(return_value=False))
md = mocker.patch.object(Path, 'mkdir', MagicMock())
with pytest.raises(OperationalException,
match=r'Directory `.{1,2}tmp.{1,2}bar` does not exist.*'):
create_userdata_dir('/tmp/bar', create_dir=False)
assert md.call_count == 0
def test_copy_sample_files(mocker, default_conf, caplog) -> None:
mocker.patch.object(Path, "is_dir", MagicMock(return_value=True))
mocker.patch.object(Path, "exists", MagicMock(return_value=False))
copymock = mocker.patch('shutil.copy', MagicMock())
copy_sample_files(Path('/tmp/bar'))
assert copymock.call_count == 5
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(
Path('/tmp/bar') / 'notebooks/strategy_analysis_example.ipynb')
def test_copy_sample_files_errors(mocker, default_conf, caplog) -> None:
mocker.patch.object(Path, "is_dir", MagicMock(return_value=False))
mocker.patch.object(Path, "exists", MagicMock(return_value=False))
mocker.patch('shutil.copy', MagicMock())
with pytest.raises(OperationalException,
match=r"Directory `.{1,2}tmp.{1,2}bar` does not exist\."):
copy_sample_files(Path('/tmp/bar'))
mocker.patch.object(Path, "is_dir", MagicMock(side_effect=[True, False]))
with pytest.raises(OperationalException,
match=r"Directory `.{1,2}tmp.{1,2}bar.{1,2}strategies` does not exist\."):
copy_sample_files(Path('/tmp/bar'))
mocker.patch.object(Path, "is_dir", MagicMock(return_value=True))
mocker.patch.object(Path, "exists", MagicMock(return_value=True))
copy_sample_files(Path('/tmp/bar'))
assert log_has_re(r"File `.*` exists already, not deploying sample file\.", caplog)
caplog.clear()
copy_sample_files(Path('/tmp/bar'), overwrite=True)
assert log_has_re(r"File `.*` exists already, overwriting\.", caplog)

77
tests/test_utils.py
View File

@ -9,8 +9,9 @@ from freqtrade.state import RunMode
from freqtrade.utils import (setup_utils_configuration, start_create_userdir,
start_download_data, start_list_exchanges,
start_list_markets, start_list_timeframes,
start_new_hyperopt, start_new_strategy,
start_trading)
from tests.conftest import get_args, log_has, patch_exchange
from tests.conftest import get_args, log_has, log_has_re, patch_exchange
def test_setup_utils_configuration():
@ -442,6 +443,7 @@ def test_create_datadir_failed(caplog):
def test_create_datadir(caplog, mocker):
cud = mocker.patch("freqtrade.utils.create_userdata_dir", MagicMock())
csf = mocker.patch("freqtrade.utils.copy_sample_files", MagicMock())
args = [
"create-userdir",
"--userdir",
@ -450,9 +452,82 @@ def test_create_datadir(caplog, mocker):
start_create_userdir(get_args(args))
assert cud.call_count == 1
assert csf.call_count == 1
assert len(caplog.record_tuples) == 0
def test_start_new_strategy(mocker, caplog):
wt_mock = mocker.patch.object(Path, "write_text", MagicMock())
mocker.patch.object(Path, "exists", MagicMock(return_value=False))
args = [
"new-strategy",
"--strategy",
"CoolNewStrategy"
]
start_new_strategy(get_args(args))
assert wt_mock.call_count == 1
assert "CoolNewStrategy" in wt_mock.call_args_list[0][0][0]
assert log_has_re("Writing strategy to .*", caplog)
def test_start_new_strategy_DefaultStrat(mocker, caplog):
args = [
"new-strategy",
"--strategy",
"DefaultStrategy"
]
with pytest.raises(OperationalException,
match=r"DefaultStrategy is not allowed as name\."):
start_new_strategy(get_args(args))
def test_start_new_strategy_no_arg(mocker, caplog):
args = [
"new-strategy",
]
with pytest.raises(OperationalException,
match="`new-strategy` requires --strategy to be set."):
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)
def test_start_new_hyperopt_DefaultHyperopt(mocker, caplog):
args = [
"new-hyperopt",
"--hyperopt",
"DefaultHyperopt"
]
with pytest.raises(OperationalException,
match=r"DefaultHyperopt is not allowed as name\."):
start_new_hyperopt(get_args(args))
def test_start_new_hyperopt_no_arg(mocker, caplog):
args = [
"new-hyperopt",
]
with pytest.raises(OperationalException,
match="`new-hyperopt` requires --hyperopt to be set."):
start_new_hyperopt(get_args(args))
def test_download_data_keyboardInterrupt(mocker, caplog, markets):
dl_mock = mocker.patch('freqtrade.utils.refresh_backtest_ohlcv_data',
MagicMock(side_effect=KeyboardInterrupt))

0
user_data/hyperopts/__init__.py → user_data/hyperopts/.gitkeep
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user_data/strategies/__init__.py → user_data/strategies/.gitkeep
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