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Merge remote-tracking branch 'origin/develop' into list-pairs2
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commit
ad5f7e1581
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@ -201,6 +201,8 @@ Since backtesting lacks some detailed information about what happens within a ca
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Taking these assumptions, backtesting tries to mirror real trading as closely as possible. However, backtesting will **never** replace running a strategy in dry-run mode.
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Also, keep in mind that past results don't guarantee future success.
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In addition to the above assumptions, strategy authors should carefully read the [Common Mistakes](strategy-customization.md#common-mistakes-when-developing-strategies) section, to avoid using data in backtesting which is not available in real market conditions.
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### Further backtest-result analysis
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To further analyze your backtest results, you can [export the trades](#exporting-trades-to-file).
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@ -60,8 +60,7 @@ file as reference.**
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!!! Warning Using future data
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Since backtesting passes the full time interval to the `populate_*()` methods, the strategy author
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needs to take care to avoid having the strategy utilize data from the future.
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Samples for usage of future data are `dataframe.shift(-1)`, `dataframe.resample("1h")` (this uses the left border of the interval, so moves data from an hour to the start of the hour).
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They all use data which is not available during regular operations, so these strategies will perform well during backtesting, but will fail / perform badly in dry-runs.
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Some common patterns for this are listed in the [Common Mistakes](#common-mistakes-when-developing-strategies) section of this document.
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### Customize Indicators
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@ -399,10 +398,10 @@ def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
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Printing more than a few rows is also possible (simply use `print(dataframe)` instead of `print(dataframe.tail())`), however not recommended, as that will be very verbose (~500 lines per pair every 5 seconds).
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### Where is the default strategy?
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### Where can i find a strategy template?
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The default buy strategy is located in the file
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[freqtrade/default_strategy.py](https://github.com/freqtrade/freqtrade/blob/develop/freqtrade/strategy/default_strategy.py).
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The strategy template is located in the file
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[user_data/strategies/sample_strategy.py](https://github.com/freqtrade/freqtrade/blob/develop/user_data/strategies/sample_strategy.py).
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### Specify custom strategy location
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@ -412,6 +411,18 @@ If you want to use a strategy from a different directory you can pass `--strateg
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freqtrade --strategy AwesomeStrategy --strategy-path /some/directory
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```
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### Common mistakes when developing strategies
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Backtesting analyzes the whole time-range at once for performance reasons. Because of this, strategy authors need to make sure that strategies do not look-ahead into the future.
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This is a common pain-point, which can cause huge differences between backtesting and dry/live run methods, since they all use data which is not available during dry/live runs, so these strategies will perform well during backtesting, but will fail / perform badly in real conditions.
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The following lists some common patterns which should be avoided to prevent frustration:
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- don't use `shift(-1)`. This uses data from the future, which is not available.
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- don't use `.iloc[-1]` or any other absolute position in the dataframe, this will be different between dry-run and backtesting.
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- don't use `dataframe['volume'].mean()`. This uses the full DataFrame for backtesting, including data from the future. Use `dataframe['volume'].rolling(<window>).mean()` instead
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- don't use `.resample('1h')`. This uses the left border of the interval, so moves data from an hour to the start of the hour. Use `.resample('1h', label='right')` instead.
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### Further strategy ideas
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To get additional Ideas for strategies, head over to our [strategy repository](https://github.com/freqtrade/freqtrade-strategies). Feel free to use them as they are - but results will depend on the current market situation, pairs used etc. - therefore please backtest the strategy for your exchange/desired pairs first, evaluate carefully, use at your own risk.
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@ -166,7 +166,7 @@ class Exchange:
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}
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_ft_has: Dict = {}
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def __init__(self, config: dict) -> None:
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def __init__(self, config: dict, validate: bool = True) -> None:
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"""
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Initializes this module with the given config,
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it does basic validation whether the specified exchange and pairs are valid.
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@ -223,13 +223,13 @@ class Exchange:
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# Converts the interval provided in minutes in config to seconds
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self.markets_refresh_interval: int = exchange_config.get(
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"markets_refresh_interval", 60) * 60
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# Initial markets load
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self._load_markets()
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# Check if all pairs are available
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self.validate_pairs(config['exchange']['pair_whitelist'])
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self.validate_ordertypes(config.get('order_types', {}))
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self.validate_order_time_in_force(config.get('order_time_in_force', {}))
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if validate:
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# Initial markets load
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self._load_markets()
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# Check if all pairs are available
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self.validate_pairs(config['exchange']['pair_whitelist'])
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self.validate_ordertypes(config.get('order_types', {}))
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self.validate_order_time_in_force(config.get('order_time_in_force', {}))
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def __del__(self):
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"""
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@ -17,7 +17,7 @@ class ExchangeResolver(IResolver):
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__slots__ = ['exchange']
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def __init__(self, exchange_name: str, config: dict) -> None:
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def __init__(self, exchange_name: str, config: dict, validate: bool = True) -> None:
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"""
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Load the custom class from config parameter
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:param config: configuration dictionary
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@ -26,7 +26,8 @@ class ExchangeResolver(IResolver):
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exchange_name = MAP_EXCHANGE_CHILDCLASS.get(exchange_name, exchange_name)
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exchange_name = exchange_name.title()
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try:
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self.exchange = self._load_exchange(exchange_name, kwargs={'config': config})
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self.exchange = self._load_exchange(exchange_name, kwargs={'config': config,
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'validate': validate})
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except ImportError:
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logger.info(
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f"No {exchange_name} specific subclass found. Using the generic class instead.")
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@ -45,7 +46,7 @@ class ExchangeResolver(IResolver):
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try:
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ex_class = getattr(exchanges, exchange_name)
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exchange = ex_class(kwargs['config'])
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exchange = ex_class(**kwargs)
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if exchange:
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logger.info(f"Using resolved exchange '{exchange_name}'...")
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return exchange
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@ -2,7 +2,7 @@ import logging
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import threading
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from datetime import date, datetime
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from ipaddress import IPv4Address
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from typing import Dict
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from typing import Dict, Callable, Any
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from arrow import Arrow
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from flask import Flask, jsonify, request
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return JSONEncoder.default(self, obj)
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# Type should really be Callable[[ApiServer, Any], Any], but that will create a circular dependency
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def require_login(func: Callable[[Any, Any], Any]):
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def func_wrapper(obj, *args, **kwargs):
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auth = request.authorization
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if auth and obj.check_auth(auth.username, auth.password):
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return func(obj, *args, **kwargs)
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else:
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return jsonify({"error": "Unauthorized"}), 401
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return func_wrapper
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# Type should really be Callable[[ApiServer], Any], but that will create a circular dependency
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def rpc_catch_errors(func: Callable[[Any], Any]):
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def func_wrapper(obj, *args, **kwargs):
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try:
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return func(obj, *args, **kwargs)
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except RPCException as e:
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logger.exception("API Error calling %s: %s", func.__name__, e)
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return obj.rest_error(f"Error querying {func.__name__}: {e}")
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return func_wrapper
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class ApiServer(RPC):
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"""
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This class runs api server and provides rpc.rpc functionality to it
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This class starts a none blocking thread the api server runs within
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This class starts a non-blocking thread the api server runs within
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"""
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def rpc_catch_errors(func):
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def func_wrapper(self, *args, **kwargs):
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try:
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return func(self, *args, **kwargs)
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except RPCException as e:
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logger.exception("API Error calling %s: %s", func.__name__, e)
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return self.rest_error(f"Error querying {func.__name__}: {e}")
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return func_wrapper
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def check_auth(self, username, password):
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return (username == self._config['api_server'].get('username') and
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password == self._config['api_server'].get('password'))
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def require_login(func):
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def func_wrapper(self, *args, **kwargs):
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auth = request.authorization
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if auth and self.check_auth(auth.username, auth.password):
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return func(self, *args, **kwargs)
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else:
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return jsonify({"error": "Unauthorized"}), 401
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return func_wrapper
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def __init__(self, freqtrade) -> None:
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"""
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Init the api server, and init the super class RPC
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@ -128,7 +128,7 @@ def start_list_timeframes(args: Dict[str, Any]) -> None:
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config['ticker_interval'] = None
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# Init exchange
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exchange = ExchangeResolver(config['exchange']['name'], config).exchange
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exchange = ExchangeResolver(config['exchange']['name'], config, validate=False).exchange
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if args['print_one_column']:
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print('\n'.join(exchange.timeframes))
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@ -1,8 +1,8 @@
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# requirements without requirements installable via conda
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# mainly used for Raspberry pi installs
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ccxt==1.18.1260
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ccxt==1.18.1306
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SQLAlchemy==1.3.10
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python-telegram-bot==12.1.1
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python-telegram-bot==12.2.0
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arrow==0.15.2
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cachetools==3.1.1
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requests==2.22.0
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@ -6,8 +6,8 @@
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coveralls==1.8.2
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flake8==3.7.8
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flake8-type-annotations==0.1.0
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flake8-tidy-imports==2.0.0
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mypy==0.730
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flake8-tidy-imports==3.0.0
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mypy==0.740
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pytest==5.2.1
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pytest-asyncio==0.10.0
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pytest-cov==2.8.1
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# Include all requirements to run the bot.
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-r requirements.txt
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plotly==4.1.1
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plotly==4.2.1
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@ -1,5 +1,5 @@
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# Load common requirements
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-r requirements-common.txt
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numpy==1.17.2
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pandas==0.25.1
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numpy==1.17.3
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pandas==0.25.2
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