Merge pull request #3497 from freqtrade/keep_dataframe_noapi
Analyze dataframe and keep it until the next analysis
This commit is contained in:
hroff-1902
GitHub
commit
839b3340e6
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@ -0,0 +1,58 @@
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# Freqtrade basics
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This page provides you some basic concepts on how Freqtrade works and operates.
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## Freqtrade terminology
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* Trade: Open position.
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* Open Order: Order which is currently placed on the exchange, and is not yet complete.
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* Pair: Tradable pair, usually in the format of Quote/Base (e.g. XRP/USDT).
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* Timeframe: Candle length to use (e.g. `"5m"`, `"1h"`, ...).
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* Indicators: Technical indicators (SMA, EMA, RSI, ...).
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* Limit order: Limit orders which execute at the defined limit price or better.
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* Market order: Guaranteed to fill, may move price depending on the order size.
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## Fee handling
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All profit calculations of Freqtrade include fees. For Backtesting / Hyperopt / Dry-run modes, the exchange default fee is used (lowest tier on the exchange). For live operations, fees are used as applied by the exchange (this includes BNB rebates etc.).
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## Bot execution logic
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Starting freqtrade in dry-run or live mode (using `freqtrade trade`) will start the bot and start the bot iteration loop.
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By default, loop runs every few seconds (`internals.process_throttle_secs`) and does roughly the following in the following sequence:
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* Fetch open trades from persistence.
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* Calculate current list of tradable pairs.
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* Download ohlcv data for the pairlist including all [informative pairs](strategy-customization.md#get-data-for-non-tradeable-pairs)
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This step is only executed once per Candle to avoid unnecessary network traffic.
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* Call `bot_loop_start()` strategy callback.
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* Analyze strategy per pair.
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* Call `populate_indicators()`
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* Call `populate_buy_trend()`
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* Call `populate_sell_trend()`
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* Check timeouts for open orders.
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* Calls `check_buy_timeout()` strategy callback for open buy orders.
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* Calls `check_sell_timeout()` strategy callback for open sell orders.
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* Verifies existing positions and eventually places sell orders.
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* Considers stoploss, ROI and sell-signal.
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* Determine sell-price based on `ask_strategy` configuration setting.
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* Before a sell order is placed, `confirm_trade_exit()` strategy callback is called.
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* Check if trade-slots are still available (if `max_open_trades` is reached).
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* Verifies buy signal trying to enter new positions.
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* Determine buy-price based on `bid_strategy` configuration setting.
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* Before a buy order is placed, `confirm_trade_entry()` strategy callback is called.
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This loop will be repeated again and again until the bot is stopped.
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## Backtesting / Hyperopt execution logic
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[backtesting](backtesting.md) or [hyperopt](hyperopt.md) do only part of the above logic, since most of the trading operations are fully simulated.
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* Load historic data for configured pairlist.
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* Calculate indicators (calls `populate_indicators()`).
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* Calls `populate_buy_trend()` and `populate_sell_trend()`
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* Loops per candle simulating entry and exit points.
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* Generate backtest report output
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!!! Note
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Both Backtesting and Hyperopt include exchange default Fees in the calculation. Custom fees can be passed to backtesting / hyperopt by specifying the `--fee` argument.
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@ -498,8 +498,3 @@ After you run Hyperopt for the desired amount of epochs, you can later list all
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Once the optimized strategy has been implemented into your strategy, you should backtest this strategy to make sure everything is working as expected.
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To achieve same results (number of trades, their durations, profit, etc.) than during Hyperopt, please use same set of arguments `--dmmp`/`--disable-max-market-positions` and `--eps`/`--enable-position-stacking` for Backtesting.
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## Next Step
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Now you have a perfect bot and want to control it from Telegram. Your
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next step is to learn the [Telegram usage](telegram-usage.md).
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@ -1,7 +1,12 @@
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# Advanced Strategies
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This page explains some advanced concepts available for strategies.
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If you're just getting started, please be familiar with the methods described in the [Strategy Customization](strategy-customization.md) documentation first.
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If you're just getting started, please be familiar with the methods described in the [Strategy Customization](strategy-customization.md) documentation and with the [Freqtrade basics](bot-basics.md) first.
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[Freqtrade basics](bot-basics.md) describes in which sequence each method described below is called, which can be helpful to understand which method to use for your custom needs.
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!!! Note
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All callback methods described below should only be implemented in a strategy if they are actually used.
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## Custom order timeout rules
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@ -89,3 +94,108 @@ class Awesomestrategy(IStrategy):
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return True
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return False
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```
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## Bot loop start callback
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A simple callback which is called once at the start of every bot throttling iteration.
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This can be used to perform calculations which are pair independent (apply to all pairs), loading of external data, etc.
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``` python
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import requests
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class Awesomestrategy(IStrategy):
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# ... populate_* methods
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def bot_loop_start(self, **kwargs) -> None:
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"""
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Called at the start of the bot iteration (one loop).
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Might be used to perform pair-independent tasks
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(e.g. gather some remote resource for comparison)
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:param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
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"""
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if self.config['runmode'].value in ('live', 'dry_run'):
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# Assign this to the class by using self.*
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# can then be used by populate_* methods
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self.remote_data = requests.get('https://some_remote_source.example.com')
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```
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## Bot order confirmation
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### Trade entry (buy order) confirmation
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`confirm_trade_entry()` can be used to abort a trade entry at the latest second (maybe because the price is not what we expect).
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``` python
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class Awesomestrategy(IStrategy):
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# ... populate_* methods
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def confirm_trade_entry(self, pair: str, order_type: str, amount: float, rate: float,
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time_in_force: str, **kwargs) -> bool:
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"""
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Called right before placing a buy order.
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Timing for this function is critical, so avoid doing heavy computations or
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network requests in this method.
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For full documentation please go to https://www.freqtrade.io/en/latest/strategy-advanced/
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When not implemented by a strategy, returns True (always confirming).
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:param pair: Pair that's about to be bought.
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:param order_type: Order type (as configured in order_types). usually limit or market.
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:param amount: Amount in target (quote) currency that's going to be traded.
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:param rate: Rate that's going to be used when using limit orders
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:param time_in_force: Time in force. Defaults to GTC (Good-til-cancelled).
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:param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
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:return bool: When True is returned, then the buy-order is placed on the exchange.
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False aborts the process
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"""
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return True
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```
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### Trade exit (sell order) confirmation
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`confirm_trade_exit()` can be used to abort a trade exit (sell) at the latest second (maybe because the price is not what we expect).
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``` python
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from freqtrade.persistence import Trade
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class Awesomestrategy(IStrategy):
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# ... populate_* methods
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def confirm_trade_exit(self, pair: str, trade: Trade, order_type: str, amount: float,
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rate: float, time_in_force: str, sell_reason: str, **kwargs) -> bool:
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"""
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Called right before placing a regular sell order.
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Timing for this function is critical, so avoid doing heavy computations or
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network requests in this method.
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For full documentation please go to https://www.freqtrade.io/en/latest/strategy-advanced/
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When not implemented by a strategy, returns True (always confirming).
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:param pair: Pair that's about to be sold.
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:param order_type: Order type (as configured in order_types). usually limit or market.
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:param amount: Amount in quote currency.
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:param rate: Rate that's going to be used when using limit orders
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:param time_in_force: Time in force. Defaults to GTC (Good-til-cancelled).
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:param sell_reason: Sell reason.
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Can be any of ['roi', 'stop_loss', 'stoploss_on_exchange', 'trailing_stop_loss',
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'sell_signal', 'force_sell', 'emergency_sell']
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:param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
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:return bool: When True is returned, then the sell-order is placed on the exchange.
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False aborts the process
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"""
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if sell_reason == 'force_sell' and trade.calc_profit_ratio(rate) < 0:
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# Reject force-sells with negative profit
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# This is just a sample, please adjust to your needs
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# (this does not necessarily make sense, assuming you know when you're force-selling)
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return False
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return True
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```
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@ -1,6 +1,8 @@
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# Strategy Customization
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This page explains where to customize your strategies, and add new indicators.
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This page explains how to customize your strategies, add new indicators and set up trading rules.
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Please familiarize yourself with [Freqtrade basics](bot-basics.md) first, which provides overall info on how the bot operates.
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## Install a custom strategy file
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@ -366,6 +368,7 @@ Please always check the mode of operation to select the correct method to get da
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- [`available_pairs`](#available_pairs) - Property with tuples listing cached pairs with their intervals (pair, interval).
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- [`current_whitelist()`](#current_whitelist) - Returns a current list of whitelisted pairs. Useful for accessing dynamic whitelists (ie. VolumePairlist)
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- [`get_pair_dataframe(pair, timeframe)`](#get_pair_dataframepair-timeframe) - This is a universal method, which returns either historical data (for backtesting) or cached live data (for the Dry-Run and Live-Run modes).
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- [`get_analyzed_dataframe(pair, timeframe)`](#get_analyzed_dataframepair-timeframe) - Returns the analyzed dataframe (after calling `populate_indicators()`, `populate_buy()`, `populate_sell()`) and the time of the latest analysis.
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- `historic_ohlcv(pair, timeframe)` - Returns historical data stored on disk.
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- `market(pair)` - Returns market data for the pair: fees, limits, precisions, activity flag, etc. See [ccxt documentation](https://github.com/ccxt/ccxt/wiki/Manual#markets) for more details on the Market data structure.
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- `ohlcv(pair, timeframe)` - Currently cached candle (OHLCV) data for the pair, returns DataFrame or empty DataFrame.
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@ -384,6 +387,7 @@ if self.dp:
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```
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#### *current_whitelist()*
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Imagine you've developed a strategy that trades the `5m` timeframe using signals generated from a `1d` timeframe on the top 10 volume pairs by volume.
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The strategy might look something like this:
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@ -431,13 +435,32 @@ if self.dp:
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```
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!!! Warning "Warning about backtesting"
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Be carefull when using dataprovider in backtesting. `historic_ohlcv()` (and `get_pair_dataframe()`
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Be careful when using dataprovider in backtesting. `historic_ohlcv()` (and `get_pair_dataframe()`
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for the backtesting runmode) provides the full time-range in one go,
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so please be aware of it and make sure to not "look into the future" to avoid surprises when running in dry/live mode).
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!!! Warning "Warning in hyperopt"
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This option cannot currently be used during hyperopt.
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#### *get_analyzed_dataframe(pair, timeframe)*
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This method is used by freqtrade internally to determine the last signal.
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It can also be used in specific callbacks to get the signal that caused the action (see [Advanced Strategy Documentation](strategy-advanced.md) for more details on available callbacks).
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``` python
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# fetch current dataframe
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if self.dp:
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dataframe, last_updated = self.dp.get_analyzed_dataframe(pair=metadata['pair'],
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timeframe=self.ticker_interval)
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```
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!!! Note "No data available"
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Returns an empty dataframe if the requested pair was not cached.
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This should not happen when using whitelisted pairs.
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!!! Warning "Warning in hyperopt"
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This option cannot currently be used during hyperopt.
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#### *orderbook(pair, maximum)*
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``` python
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@ -339,4 +339,5 @@ CANCEL_REASON = {
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}
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# List of pairs with their timeframes
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ListPairsWithTimeframes = List[Tuple[str, str]]
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PairWithTimeframe = Tuple[str, str]
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ListPairsWithTimeframes = List[PairWithTimeframe]
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@ -5,16 +5,17 @@ including ticker and orderbook data, live and historical candle (OHLCV) data
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Common Interface for bot and strategy to access data.
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"""
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import logging
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from typing import Any, Dict, List, Optional
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from datetime import datetime, timezone
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from typing import Any, Dict, List, Optional, Tuple
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from arrow import Arrow
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from pandas import DataFrame
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from freqtrade.constants import ListPairsWithTimeframes, PairWithTimeframe
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from freqtrade.data.history import load_pair_history
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from freqtrade.exceptions import ExchangeError, OperationalException
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from freqtrade.exchange import Exchange
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from freqtrade.state import RunMode
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from freqtrade.constants import ListPairsWithTimeframes
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logger = logging.getLogger(__name__)
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@ -25,6 +26,18 @@ class DataProvider:
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self._config = config
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self._exchange = exchange
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self._pairlists = pairlists
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self.__cached_pairs: Dict[PairWithTimeframe, Tuple[DataFrame, datetime]] = {}
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def _set_cached_df(self, pair: str, timeframe: str, dataframe: DataFrame) -> None:
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"""
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Store cached Dataframe.
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Using private method as this should never be used by a user
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(but the class is exposed via `self.dp` to the strategy)
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:param pair: pair to get the data for
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:param timeframe: Timeframe to get data for
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:param dataframe: analyzed dataframe
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"""
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self.__cached_pairs[(pair, timeframe)] = (dataframe, Arrow.utcnow().datetime)
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def refresh(self,
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pairlist: ListPairsWithTimeframes,
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@ -89,6 +102,20 @@ class DataProvider:
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logger.warning(f"No data found for ({pair}, {timeframe}).")
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return data
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def get_analyzed_dataframe(self, pair: str, timeframe: str) -> Tuple[DataFrame, datetime]:
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"""
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:param pair: pair to get the data for
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:param timeframe: timeframe to get data for
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:return: Tuple of (Analyzed Dataframe, lastrefreshed) for the requested pair / timeframe
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combination.
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Returns empty dataframe and Epoch 0 (1970-01-01) if no dataframe was cached.
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"""
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if (pair, timeframe) in self.__cached_pairs:
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return self.__cached_pairs[(pair, timeframe)]
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else:
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return (DataFrame(), datetime.fromtimestamp(0, tz=timezone.utc))
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def market(self, pair: str) -> Optional[Dict[str, Any]]:
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"""
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Return market data for the pair
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@ -153,6 +153,10 @@ class FreqtradeBot:
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self.dataprovider.refresh(self.pairlists.create_pair_list(self.active_pair_whitelist),
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self.strategy.informative_pairs())
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strategy_safe_wrapper(self.strategy.bot_loop_start, supress_error=True)()
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self.strategy.analyze(self.active_pair_whitelist)
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with self._sell_lock:
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# Check and handle any timed out open orders
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self.check_handle_timedout()
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@ -440,9 +444,8 @@ class FreqtradeBot:
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return False
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# running get_signal on historical data fetched
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(buy, sell) = self.strategy.get_signal(
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pair, self.strategy.timeframe,
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self.dataprovider.ohlcv(pair, self.strategy.timeframe))
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analyzed_df, _ = self.dataprovider.get_analyzed_dataframe(pair, self.strategy.timeframe)
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(buy, sell) = self.strategy.get_signal(pair, self.strategy.timeframe, analyzed_df)
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if buy and not sell:
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stake_amount = self.get_trade_stake_amount(pair)
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@ -515,6 +518,12 @@ class FreqtradeBot:
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amount = stake_amount / buy_limit_requested
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order_type = self.strategy.order_types['buy']
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if not strategy_safe_wrapper(self.strategy.confirm_trade_entry, default_retval=True)(
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pair=pair, order_type=order_type, amount=amount, rate=buy_limit_requested,
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time_in_force=time_in_force):
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logger.info(f"User requested abortion of buying {pair}")
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return False
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order = self.exchange.buy(pair=pair, ordertype=order_type,
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amount=amount, rate=buy_limit_requested,
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time_in_force=time_in_force)
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@ -717,9 +726,10 @@ class FreqtradeBot:
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if (config_ask_strategy.get('use_sell_signal', True) or
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config_ask_strategy.get('ignore_roi_if_buy_signal', False)):
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(buy, sell) = self.strategy.get_signal(
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trade.pair, self.strategy.timeframe,
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self.dataprovider.ohlcv(trade.pair, self.strategy.timeframe))
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analyzed_df, _ = self.dataprovider.get_analyzed_dataframe(trade.pair,
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self.strategy.timeframe)
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(buy, sell) = self.strategy.get_signal(trade.pair, self.strategy.timeframe, analyzed_df)
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if config_ask_strategy.get('use_order_book', False):
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order_book_min = config_ask_strategy.get('order_book_min', 1)
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@ -1097,12 +1107,20 @@ class FreqtradeBot:
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order_type = self.strategy.order_types.get("emergencysell", "market")
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amount = self._safe_sell_amount(trade.pair, trade.amount)
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time_in_force = self.strategy.order_time_in_force['sell']
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if not strategy_safe_wrapper(self.strategy.confirm_trade_exit, default_retval=True)(
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pair=trade.pair, trade=trade, order_type=order_type, amount=amount, rate=limit,
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time_in_force=time_in_force,
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sell_reason=sell_reason.value):
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logger.info(f"User requested abortion of selling {trade.pair}")
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return False
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# Execute sell and update trade record
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order = self.exchange.sell(pair=str(trade.pair),
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ordertype=order_type,
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amount=amount, rate=limit,
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time_in_force=self.strategy.order_time_in_force['sell']
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time_in_force=time_in_force
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)
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trade.open_order_id = order['id']
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|
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@ -7,20 +7,19 @@ import warnings
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|||
from abc import ABC, abstractmethod
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||||
from datetime import datetime, timezone
|
||||
from enum import Enum
|
||||
from typing import Dict, NamedTuple, Optional, Tuple
|
||||
from typing import Dict, List, NamedTuple, Optional, Tuple
|
||||
|
||||
import arrow
|
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from pandas import DataFrame
|
||||
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||||
from freqtrade.constants import ListPairsWithTimeframes
|
||||
from freqtrade.data.dataprovider import DataProvider
|
||||
from freqtrade.exceptions import StrategyError
|
||||
from freqtrade.exceptions import StrategyError, OperationalException
|
||||
from freqtrade.exchange import timeframe_to_minutes
|
||||
from freqtrade.persistence import Trade
|
||||
from freqtrade.strategy.strategy_wrapper import strategy_safe_wrapper
|
||||
from freqtrade.constants import ListPairsWithTimeframes
|
||||
from freqtrade.wallets import Wallets
|
||||
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
|
|
@ -191,6 +190,63 @@ class IStrategy(ABC):
|
|||
"""
|
||||
return False
|
||||
|
||||
def bot_loop_start(self, **kwargs) -> None:
|
||||
"""
|
||||
Called at the start of the bot iteration (one loop).
|
||||
Might be used to perform pair-independent tasks
|
||||
(e.g. gather some remote resource for comparison)
|
||||
:param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
|
||||
"""
|
||||
pass
|
||||
|
||||
def confirm_trade_entry(self, pair: str, order_type: str, amount: float, rate: float,
|
||||
time_in_force: str, **kwargs) -> bool:
|
||||
"""
|
||||
Called right before placing a buy order.
|
||||
Timing for this function is critical, so avoid doing heavy computations or
|
||||
network requests in this method.
|
||||
|
||||
For full documentation please go to https://www.freqtrade.io/en/latest/strategy-advanced/
|
||||
|
||||
When not implemented by a strategy, returns True (always confirming).
|
||||
|
||||
:param pair: Pair that's about to be bought.
|
||||
:param order_type: Order type (as configured in order_types). usually limit or market.
|
||||
:param amount: Amount in target (quote) currency that's going to be traded.
|
||||
:param rate: Rate that's going to be used when using limit orders
|
||||
:param time_in_force: Time in force. Defaults to GTC (Good-til-cancelled).
|
||||
: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-order is placed on the exchange.
|
||||
False aborts the process
|
||||
"""
|
||||
return True
|
||||
|
||||
def confirm_trade_exit(self, pair: str, trade: Trade, order_type: str, amount: float,
|
||||
rate: float, time_in_force: str, sell_reason: str, **kwargs) -> bool:
|
||||
"""
|
||||
Called right before placing a regular sell order.
|
||||
Timing for this function is critical, so avoid doing heavy computations or
|
||||
network requests in this method.
|
||||
|
||||
For full documentation please go to https://www.freqtrade.io/en/latest/strategy-advanced/
|
||||
|
||||
When not implemented by a strategy, returns True (always confirming).
|
||||
|
||||
:param pair: Pair that's about to be sold.
|
||||
:param trade: trade object.
|
||||
:param order_type: Order type (as configured in order_types). usually limit or market.
|
||||
:param amount: Amount in quote currency.
|
||||
:param rate: Rate that's going to be used when using limit orders
|
||||
:param time_in_force: Time in force. Defaults to GTC (Good-til-cancelled).
|
||||
:param sell_reason: Sell reason.
|
||||
Can be any of ['roi', 'stop_loss', 'stoploss_on_exchange', 'trailing_stop_loss',
|
||||
'sell_signal', 'force_sell', 'emergency_sell']
|
||||
:param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
|
||||
:return bool: When True is returned, then the sell-order is placed on the exchange.
|
||||
False aborts the process
|
||||
"""
|
||||
return True
|
||||
|
||||
def informative_pairs(self) -> ListPairsWithTimeframes:
|
||||
"""
|
||||
Define additional, informative pair/interval combinations to be cached from the exchange.
|
||||
|
|
@ -204,6 +260,10 @@ class IStrategy(ABC):
|
|||
"""
|
||||
return []
|
||||
|
||||
###
|
||||
# END - Intended to be overridden by strategy
|
||||
###
|
||||
|
||||
def get_strategy_name(self) -> str:
|
||||
"""
|
||||
Returns strategy class name
|
||||
|
|
@ -273,6 +333,8 @@ class IStrategy(ABC):
|
|||
# Defs that only make change on new candle data.
|
||||
dataframe = self.analyze_ticker(dataframe, metadata)
|
||||
self._last_candle_seen_per_pair[pair] = dataframe.iloc[-1]['date']
|
||||
if self.dp:
|
||||
self.dp._set_cached_df(pair, self.timeframe, dataframe)
|
||||
else:
|
||||
logger.debug("Skipping TA Analysis for already analyzed candle")
|
||||
dataframe['buy'] = 0
|
||||
|
|
@ -284,13 +346,53 @@ class IStrategy(ABC):
|
|||
|
||||
return dataframe
|
||||
|
||||
def analyze_pair(self, pair: str) -> None:
|
||||
"""
|
||||
Fetch data for this pair from dataprovider and analyze.
|
||||
Stores the dataframe into the dataprovider.
|
||||
The analyzed dataframe is then accessible via `dp.get_analyzed_dataframe()`.
|
||||
:param pair: Pair to analyze.
|
||||
"""
|
||||
if not self.dp:
|
||||
raise OperationalException("DataProvider not found.")
|
||||
dataframe = self.dp.ohlcv(pair, self.timeframe)
|
||||
if not isinstance(dataframe, DataFrame) or dataframe.empty:
|
||||
logger.warning('Empty candle (OHLCV) data for pair %s', pair)
|
||||
return
|
||||
|
||||
try:
|
||||
df_len, df_close, df_date = self.preserve_df(dataframe)
|
||||
|
||||
dataframe = strategy_safe_wrapper(
|
||||
self._analyze_ticker_internal, message=""
|
||||
)(dataframe, {'pair': pair})
|
||||
|
||||
self.assert_df(dataframe, df_len, df_close, df_date)
|
||||
except StrategyError as error:
|
||||
logger.warning(f"Unable to analyze candle (OHLCV) data for pair {pair}: {error}")
|
||||
return
|
||||
|
||||
if dataframe.empty:
|
||||
logger.warning('Empty dataframe for pair %s', pair)
|
||||
return
|
||||
|
||||
def analyze(self, pairs: List[str]) -> None:
|
||||
"""
|
||||
Analyze all pairs using analyze_pair().
|
||||
:param pairs: List of pairs to analyze
|
||||
"""
|
||||
for pair in pairs:
|
||||
self.analyze_pair(pair)
|
||||
|
||||
@staticmethod
|
||||
def preserve_df(dataframe: DataFrame) -> Tuple[int, float, datetime]:
|
||||
""" keep some data for dataframes """
|
||||
return len(dataframe), dataframe["close"].iloc[-1], dataframe["date"].iloc[-1]
|
||||
|
||||
def assert_df(self, dataframe: DataFrame, df_len: int, df_close: float, df_date: datetime):
|
||||
""" make sure data is unmodified """
|
||||
"""
|
||||
Ensure dataframe (length, last candle) was not modified, and has all elements we need.
|
||||
"""
|
||||
message = ""
|
||||
if df_len != len(dataframe):
|
||||
message = "length"
|
||||
|
|
@ -304,31 +406,17 @@ class IStrategy(ABC):
|
|||
else:
|
||||
raise StrategyError(f"Dataframe returned from strategy has mismatching {message}.")
|
||||
|
||||
def get_signal(self, pair: str, interval: str, dataframe: DataFrame) -> Tuple[bool, bool]:
|
||||
def get_signal(self, pair: str, timeframe: str, dataframe: DataFrame) -> Tuple[bool, bool]:
|
||||
"""
|
||||
Calculates current signal based several technical analysis indicators
|
||||
Calculates current signal based based on the buy / sell columns of the dataframe.
|
||||
Used by Bot to get the signal to buy or sell
|
||||
:param pair: pair in format ANT/BTC
|
||||
:param interval: Interval to use (in min)
|
||||
:param dataframe: Dataframe to analyze
|
||||
:param timeframe: timeframe to use
|
||||
:param dataframe: Analyzed dataframe to get signal from.
|
||||
:return: (Buy, Sell) A bool-tuple indicating buy/sell signal
|
||||
"""
|
||||
if not isinstance(dataframe, DataFrame) or dataframe.empty:
|
||||
logger.warning('Empty candle (OHLCV) data for pair %s', pair)
|
||||
return False, False
|
||||
|
||||
try:
|
||||
df_len, df_close, df_date = self.preserve_df(dataframe)
|
||||
dataframe = strategy_safe_wrapper(
|
||||
self._analyze_ticker_internal, message=""
|
||||
)(dataframe, {'pair': pair})
|
||||
self.assert_df(dataframe, df_len, df_close, df_date)
|
||||
except StrategyError as error:
|
||||
logger.warning(f"Unable to analyze candle (OHLCV) data for pair {pair}: {error}")
|
||||
|
||||
return False, False
|
||||
|
||||
if dataframe.empty:
|
||||
logger.warning('Empty dataframe for pair %s', pair)
|
||||
logger.warning(f'Empty candle (OHLCV) data for pair {pair}')
|
||||
return False, False
|
||||
|
||||
latest_date = dataframe['date'].max()
|
||||
|
|
@ -337,24 +425,18 @@ class IStrategy(ABC):
|
|||
latest_date = arrow.get(latest_date)
|
||||
|
||||
# Check if dataframe is out of date
|
||||
interval_minutes = timeframe_to_minutes(interval)
|
||||
timeframe_minutes = timeframe_to_minutes(timeframe)
|
||||
offset = self.config.get('exchange', {}).get('outdated_offset', 5)
|
||||
if latest_date < (arrow.utcnow().shift(minutes=-(interval_minutes * 2 + offset))):
|
||||
if latest_date < (arrow.utcnow().shift(minutes=-(timeframe_minutes * 2 + offset))):
|
||||
logger.warning(
|
||||
'Outdated history for pair %s. Last tick is %s minutes old',
|
||||
pair,
|
||||
(arrow.utcnow() - latest_date).seconds // 60
|
||||
pair, (arrow.utcnow() - latest_date).seconds // 60
|
||||
)
|
||||
return False, False
|
||||
|
||||
(buy, sell) = latest[SignalType.BUY.value] == 1, latest[SignalType.SELL.value] == 1
|
||||
logger.debug(
|
||||
'trigger: %s (pair=%s) buy=%s sell=%s',
|
||||
latest['date'],
|
||||
pair,
|
||||
str(buy),
|
||||
str(sell)
|
||||
)
|
||||
logger.debug('trigger: %s (pair=%s) buy=%s sell=%s',
|
||||
latest['date'], pair, str(buy), str(sell))
|
||||
return buy, sell
|
||||
|
||||
def should_sell(self, trade: Trade, rate: float, date: datetime, buy: bool,
|
||||
|
|
@ -500,7 +582,8 @@ class IStrategy(ABC):
|
|||
|
||||
def ohlcvdata_to_dataframe(self, data: Dict[str, DataFrame]) -> Dict[str, DataFrame]:
|
||||
"""
|
||||
Creates a dataframe and populates indicators for given candle (OHLCV) data
|
||||
Populates indicators for given candle (OHLCV) data (for multiple pairs)
|
||||
Does not run advice_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.
|
||||
Has positive effects on memory usage for whatever reason - also when
|
||||
|
|
|
|||
|
|
@ -5,7 +5,7 @@ from freqtrade.exceptions import StrategyError
|
|||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
def strategy_safe_wrapper(f, message: str = "", default_retval=None):
|
||||
def strategy_safe_wrapper(f, message: str = "", default_retval=None, supress_error=False):
|
||||
"""
|
||||
Wrapper around user-provided methods and functions.
|
||||
Caches all exceptions and returns either the default_retval (if it's not None) or raises
|
||||
|
|
@ -20,7 +20,7 @@ def strategy_safe_wrapper(f, message: str = "", default_retval=None):
|
|||
f"Strategy caused the following exception: {error}"
|
||||
f"{f}"
|
||||
)
|
||||
if default_retval is None:
|
||||
if default_retval is None and not supress_error:
|
||||
raise StrategyError(str(error)) from error
|
||||
return default_retval
|
||||
except Exception as error:
|
||||
|
|
@ -28,7 +28,7 @@ def strategy_safe_wrapper(f, message: str = "", default_retval=None):
|
|||
f"{message}"
|
||||
f"Unexpected error {error} calling {f}"
|
||||
)
|
||||
if default_retval is None:
|
||||
if default_retval is None and not supress_error:
|
||||
raise StrategyError(str(error)) from error
|
||||
return default_retval
|
||||
|
||||
|
|
|
|||
|
|
@ -1,4 +1,65 @@
|
|||
|
||||
def bot_loop_start(self, **kwargs) -> None:
|
||||
"""
|
||||
Called at the start of the bot iteration (one loop).
|
||||
Might be used to perform pair-independent tasks
|
||||
(e.g. gather some remote ressource for comparison)
|
||||
|
||||
For full documentation please go to https://www.freqtrade.io/en/latest/strategy-advanced/
|
||||
|
||||
When not implemented by a strategy, this simply does nothing.
|
||||
:param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
|
||||
"""
|
||||
pass
|
||||
|
||||
def confirm_trade_entry(self, pair: str, order_type: str, amount: float, rate: float,
|
||||
time_in_force: str, **kwargs) -> bool:
|
||||
"""
|
||||
Called right before placing a buy order.
|
||||
Timing for this function is critical, so avoid doing heavy computations or
|
||||
network requests in this method.
|
||||
|
||||
For full documentation please go to https://www.freqtrade.io/en/latest/strategy-advanced/
|
||||
|
||||
When not implemented by a strategy, returns True (always confirming).
|
||||
|
||||
:param pair: Pair that's about to be bought.
|
||||
:param order_type: Order type (as configured in order_types). usually limit or market.
|
||||
:param amount: Amount in target (quote) currency that's going to be traded.
|
||||
:param rate: Rate that's going to be used when using limit orders
|
||||
:param time_in_force: Time in force. Defaults to GTC (Good-til-cancelled).
|
||||
: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-order is placed on the exchange.
|
||||
False aborts the process
|
||||
"""
|
||||
return True
|
||||
|
||||
def confirm_trade_exit(self, pair: str, trade: Trade, order_type: str, amount: float,
|
||||
rate: float, time_in_force: str, sell_reason: str, **kwargs) -> bool:
|
||||
"""
|
||||
Called right before placing a regular sell order.
|
||||
Timing for this function is critical, so avoid doing heavy computations or
|
||||
network requests in this method.
|
||||
|
||||
For full documentation please go to https://www.freqtrade.io/en/latest/strategy-advanced/
|
||||
|
||||
When not implemented by a strategy, returns True (always confirming).
|
||||
|
||||
:param pair: Pair that's about to be sold.
|
||||
:param trade: trade object.
|
||||
:param order_type: Order type (as configured in order_types). usually limit or market.
|
||||
:param amount: Amount in quote currency.
|
||||
:param rate: Rate that's going to be used when using limit orders
|
||||
:param time_in_force: Time in force. Defaults to GTC (Good-til-cancelled).
|
||||
:param sell_reason: Sell reason.
|
||||
Can be any of ['roi', 'stop_loss', 'stoploss_on_exchange', 'trailing_stop_loss',
|
||||
'sell_signal', 'force_sell', 'emergency_sell']
|
||||
:param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
|
||||
:return bool: When True is returned, then the sell-order is placed on the exchange.
|
||||
False aborts the process
|
||||
"""
|
||||
return True
|
||||
|
||||
def check_buy_timeout(self, pair: str, trade: 'Trade', order: dict, **kwargs) -> bool:
|
||||
"""
|
||||
Check buy timeout function callback.
|
||||
|
|
|
|||
|
|
@ -3,6 +3,7 @@ nav:
|
|||
- Home: index.md
|
||||
- Installation Docker: docker.md
|
||||
- Installation: installation.md
|
||||
- Freqtrade Basics: bot-basics.md
|
||||
- Configuration: configuration.md
|
||||
- Strategy Customization: strategy-customization.md
|
||||
- Stoploss: stoploss.md
|
||||
|
|
|
|||
|
|
@ -163,7 +163,7 @@ def patch_get_signal(freqtrade: FreqtradeBot, value=(True, False)) -> None:
|
|||
:param value: which value IStrategy.get_signal() must return
|
||||
:return: None
|
||||
"""
|
||||
freqtrade.strategy.get_signal = lambda e, s, t: value
|
||||
freqtrade.strategy.get_signal = lambda e, s, x: value
|
||||
freqtrade.exchange.refresh_latest_ohlcv = lambda p: None
|
||||
|
||||
|
||||
|
|
@ -787,6 +787,7 @@ def limit_buy_order():
|
|||
'price': 0.00001099,
|
||||
'amount': 90.99181073,
|
||||
'filled': 90.99181073,
|
||||
'cost': 0.0009999,
|
||||
'remaining': 0.0,
|
||||
'status': 'closed'
|
||||
}
|
||||
|
|
|
|||
|
|
@ -1,3 +1,4 @@
|
|||
from datetime import datetime, timezone
|
||||
from unittest.mock import MagicMock
|
||||
|
||||
import pytest
|
||||
|
|
@ -194,3 +195,29 @@ def test_current_whitelist(mocker, default_conf, tickers):
|
|||
with pytest.raises(OperationalException):
|
||||
dp = DataProvider(default_conf, exchange)
|
||||
dp.current_whitelist()
|
||||
|
||||
|
||||
def test_get_analyzed_dataframe(mocker, default_conf, ohlcv_history):
|
||||
|
||||
default_conf["runmode"] = RunMode.DRY_RUN
|
||||
|
||||
timeframe = default_conf["timeframe"]
|
||||
exchange = get_patched_exchange(mocker, default_conf)
|
||||
|
||||
dp = DataProvider(default_conf, exchange)
|
||||
dp._set_cached_df("XRP/BTC", timeframe, ohlcv_history)
|
||||
dp._set_cached_df("UNITTEST/BTC", timeframe, ohlcv_history)
|
||||
|
||||
assert dp.runmode == RunMode.DRY_RUN
|
||||
dataframe, time = dp.get_analyzed_dataframe("UNITTEST/BTC", timeframe)
|
||||
assert ohlcv_history.equals(dataframe)
|
||||
assert isinstance(time, datetime)
|
||||
|
||||
dataframe, time = dp.get_analyzed_dataframe("XRP/BTC", timeframe)
|
||||
assert ohlcv_history.equals(dataframe)
|
||||
assert isinstance(time, datetime)
|
||||
|
||||
dataframe, time = dp.get_analyzed_dataframe("NOTHING/BTC", timeframe)
|
||||
assert dataframe.empty
|
||||
assert isinstance(time, datetime)
|
||||
assert time == datetime(1970, 1, 1, tzinfo=timezone.utc)
|
||||
|
|
|
|||
|
|
@ -13,12 +13,14 @@ from freqtrade.exceptions import StrategyError
|
|||
from freqtrade.persistence import Trade
|
||||
from freqtrade.resolvers import StrategyResolver
|
||||
from freqtrade.strategy.strategy_wrapper import strategy_safe_wrapper
|
||||
from tests.conftest import get_patched_exchange, log_has, log_has_re
|
||||
from freqtrade.data.dataprovider import DataProvider
|
||||
from tests.conftest import log_has, log_has_re
|
||||
|
||||
from .strats.default_strategy import DefaultStrategy
|
||||
|
||||
# Avoid to reinit the same object again and again
|
||||
_STRATEGY = DefaultStrategy(config={})
|
||||
_STRATEGY.dp = DataProvider({}, None, None)
|
||||
|
||||
|
||||
def test_returns_latest_signal(mocker, default_conf, ohlcv_history):
|
||||
|
|
@ -29,63 +31,60 @@ def test_returns_latest_signal(mocker, default_conf, ohlcv_history):
|
|||
mocked_history['buy'] = 0
|
||||
mocked_history.loc[1, 'sell'] = 1
|
||||
|
||||
mocker.patch.object(
|
||||
_STRATEGY, '_analyze_ticker_internal',
|
||||
return_value=mocked_history
|
||||
)
|
||||
|
||||
assert _STRATEGY.get_signal('ETH/BTC', '5m', ohlcv_history) == (False, True)
|
||||
assert _STRATEGY.get_signal('ETH/BTC', '5m', mocked_history) == (False, True)
|
||||
mocked_history.loc[1, 'sell'] = 0
|
||||
mocked_history.loc[1, 'buy'] = 1
|
||||
|
||||
mocker.patch.object(
|
||||
_STRATEGY, '_analyze_ticker_internal',
|
||||
return_value=mocked_history
|
||||
)
|
||||
assert _STRATEGY.get_signal('ETH/BTC', '5m', ohlcv_history) == (True, False)
|
||||
assert _STRATEGY.get_signal('ETH/BTC', '5m', mocked_history) == (True, False)
|
||||
mocked_history.loc[1, 'sell'] = 0
|
||||
mocked_history.loc[1, 'buy'] = 0
|
||||
|
||||
mocker.patch.object(
|
||||
_STRATEGY, '_analyze_ticker_internal',
|
||||
return_value=mocked_history
|
||||
)
|
||||
assert _STRATEGY.get_signal('ETH/BTC', '5m', ohlcv_history) == (False, False)
|
||||
assert _STRATEGY.get_signal('ETH/BTC', '5m', mocked_history) == (False, False)
|
||||
|
||||
|
||||
def test_get_signal_empty(default_conf, mocker, caplog):
|
||||
assert (False, False) == _STRATEGY.get_signal('foo', default_conf['timeframe'],
|
||||
DataFrame())
|
||||
assert log_has('Empty candle (OHLCV) data for pair foo', caplog)
|
||||
caplog.clear()
|
||||
|
||||
assert (False, False) == _STRATEGY.get_signal('bar', default_conf['timeframe'],
|
||||
[])
|
||||
assert log_has('Empty candle (OHLCV) data for pair bar', caplog)
|
||||
|
||||
|
||||
def test_get_signal_exception_valueerror(default_conf, mocker, caplog, ohlcv_history):
|
||||
caplog.set_level(logging.INFO)
|
||||
mocker.patch.object(
|
||||
_STRATEGY, '_analyze_ticker_internal',
|
||||
side_effect=ValueError('xyz')
|
||||
)
|
||||
assert (False, False) == _STRATEGY.get_signal('foo', default_conf['timeframe'],
|
||||
ohlcv_history)
|
||||
assert log_has_re(r'Strategy caused the following exception: xyz.*', caplog)
|
||||
|
||||
|
||||
def test_get_signal_empty_dataframe(default_conf, mocker, caplog, ohlcv_history):
|
||||
caplog.set_level(logging.INFO)
|
||||
def test_analyze_pair_empty(default_conf, mocker, caplog, ohlcv_history):
|
||||
mocker.patch.object(_STRATEGY.dp, 'ohlcv', return_value=ohlcv_history)
|
||||
mocker.patch.object(
|
||||
_STRATEGY, '_analyze_ticker_internal',
|
||||
return_value=DataFrame([])
|
||||
)
|
||||
mocker.patch.object(_STRATEGY, 'assert_df')
|
||||
|
||||
assert (False, False) == _STRATEGY.get_signal('xyz', default_conf['timeframe'],
|
||||
ohlcv_history)
|
||||
assert log_has('Empty dataframe for pair xyz', caplog)
|
||||
_STRATEGY.analyze_pair('ETH/BTC')
|
||||
|
||||
assert log_has('Empty dataframe for pair ETH/BTC', caplog)
|
||||
|
||||
|
||||
def test_get_signal_empty(default_conf, mocker, caplog):
|
||||
assert (False, False) == _STRATEGY.get_signal('foo', default_conf['timeframe'], DataFrame())
|
||||
assert log_has('Empty candle (OHLCV) data for pair foo', caplog)
|
||||
caplog.clear()
|
||||
|
||||
assert (False, False) == _STRATEGY.get_signal('bar', default_conf['timeframe'], None)
|
||||
assert log_has('Empty candle (OHLCV) data for pair bar', caplog)
|
||||
caplog.clear()
|
||||
|
||||
assert (False, False) == _STRATEGY.get_signal('baz', default_conf['timeframe'], DataFrame([]))
|
||||
assert log_has('Empty candle (OHLCV) data for pair baz', caplog)
|
||||
|
||||
|
||||
def test_get_signal_exception_valueerror(default_conf, mocker, caplog, ohlcv_history):
|
||||
caplog.set_level(logging.INFO)
|
||||
mocker.patch.object(_STRATEGY.dp, 'ohlcv', return_value=ohlcv_history)
|
||||
mocker.patch.object(
|
||||
_STRATEGY, '_analyze_ticker_internal',
|
||||
side_effect=ValueError('xyz')
|
||||
)
|
||||
_STRATEGY.analyze_pair('foo')
|
||||
assert log_has_re(r'Strategy caused the following exception: xyz.*', caplog)
|
||||
caplog.clear()
|
||||
|
||||
mocker.patch.object(
|
||||
_STRATEGY, 'analyze_ticker',
|
||||
side_effect=Exception('invalid ticker history ')
|
||||
)
|
||||
_STRATEGY.analyze_pair('foo')
|
||||
assert log_has_re(r'Strategy caused the following exception: xyz.*', caplog)
|
||||
|
||||
|
||||
def test_get_signal_old_dataframe(default_conf, mocker, caplog, ohlcv_history):
|
||||
|
|
@ -99,13 +98,9 @@ def test_get_signal_old_dataframe(default_conf, mocker, caplog, ohlcv_history):
|
|||
mocked_history.loc[1, 'buy'] = 1
|
||||
|
||||
caplog.set_level(logging.INFO)
|
||||
mocker.patch.object(
|
||||
_STRATEGY, '_analyze_ticker_internal',
|
||||
return_value=mocked_history
|
||||
)
|
||||
mocker.patch.object(_STRATEGY, 'assert_df')
|
||||
assert (False, False) == _STRATEGY.get_signal('xyz', default_conf['timeframe'],
|
||||
ohlcv_history)
|
||||
|
||||
assert (False, False) == _STRATEGY.get_signal('xyz', default_conf['timeframe'], mocked_history)
|
||||
assert log_has('Outdated history for pair xyz. Last tick is 16 minutes old', caplog)
|
||||
|
||||
|
||||
|
|
@ -120,12 +115,13 @@ def test_assert_df_raise(default_conf, mocker, caplog, ohlcv_history):
|
|||
mocked_history.loc[1, 'buy'] = 1
|
||||
|
||||
caplog.set_level(logging.INFO)
|
||||
mocker.patch.object(_STRATEGY.dp, 'ohlcv', return_value=ohlcv_history)
|
||||
mocker.patch.object(_STRATEGY.dp, 'get_analyzed_dataframe', return_value=(mocked_history, 0))
|
||||
mocker.patch.object(
|
||||
_STRATEGY, 'assert_df',
|
||||
side_effect=StrategyError('Dataframe returned...')
|
||||
)
|
||||
assert (False, False) == _STRATEGY.get_signal('xyz', default_conf['timeframe'],
|
||||
ohlcv_history)
|
||||
_STRATEGY.analyze_pair('xyz')
|
||||
assert log_has('Unable to analyze candle (OHLCV) data for pair xyz: Dataframe returned...',
|
||||
caplog)
|
||||
|
||||
|
|
@ -157,15 +153,6 @@ def test_assert_df(default_conf, mocker, ohlcv_history, caplog):
|
|||
_STRATEGY.disable_dataframe_checks = False
|
||||
|
||||
|
||||
def test_get_signal_handles_exceptions(mocker, default_conf):
|
||||
exchange = get_patched_exchange(mocker, default_conf)
|
||||
mocker.patch.object(
|
||||
_STRATEGY, 'analyze_ticker',
|
||||
side_effect=Exception('invalid ticker history ')
|
||||
)
|
||||
assert _STRATEGY.get_signal(exchange, 'ETH/BTC', '5m') == (False, False)
|
||||
|
||||
|
||||
def test_ohlcvdata_to_dataframe(default_conf, testdatadir) -> None:
|
||||
default_conf.update({'strategy': 'DefaultStrategy'})
|
||||
strategy = StrategyResolver.load_strategy(default_conf)
|
||||
|
|
@ -342,6 +329,7 @@ def test__analyze_ticker_internal_skip_analyze(ohlcv_history, mocker, caplog) ->
|
|||
|
||||
)
|
||||
strategy = DefaultStrategy({})
|
||||
strategy.dp = DataProvider({}, None, None)
|
||||
strategy.process_only_new_candles = True
|
||||
|
||||
ret = strategy._analyze_ticker_internal(ohlcv_history, {'pair': 'ETH/BTC'})
|
||||
|
|
@ -400,6 +388,14 @@ def test_is_pair_locked(default_conf):
|
|||
assert not strategy.is_pair_locked(pair)
|
||||
|
||||
|
||||
def test_is_informative_pairs_callback(default_conf):
|
||||
default_conf.update({'strategy': 'TestStrategyLegacy'})
|
||||
strategy = StrategyResolver.load_strategy(default_conf)
|
||||
# Should return empty
|
||||
# Uses fallback to base implementation
|
||||
assert [] == strategy.informative_pairs()
|
||||
|
||||
|
||||
@pytest.mark.parametrize('error', [
|
||||
ValueError, KeyError, Exception,
|
||||
])
|
||||
|
|
@ -419,6 +415,11 @@ def test_strategy_safe_wrapper_error(caplog, error):
|
|||
assert isinstance(ret, bool)
|
||||
assert ret
|
||||
|
||||
caplog.clear()
|
||||
# Test supressing error
|
||||
ret = strategy_safe_wrapper(failing_method, message='DeadBeef', supress_error=True)()
|
||||
assert log_has_re(r'DeadBeef.*', caplog)
|
||||
|
||||
|
||||
@pytest.mark.parametrize('value', [
|
||||
1, 22, 55, True, False, {'a': 1, 'b': '112'},
|
||||
|
|
|
|||
|
|
@ -911,6 +911,7 @@ def test_process_informative_pairs_added(default_conf, ticker, mocker) -> None:
|
|||
refresh_latest_ohlcv=refresh_mock,
|
||||
)
|
||||
inf_pairs = MagicMock(return_value=[("BTC/ETH", '1m'), ("ETH/USDT", "1h")])
|
||||
mocker.patch('freqtrade.strategy.interface.IStrategy.get_signal', return_value=(False, False))
|
||||
mocker.patch('time.sleep', return_value=None)
|
||||
|
||||
freqtrade = FreqtradeBot(default_conf)
|
||||
|
|
@ -973,6 +974,7 @@ def test_execute_buy(mocker, default_conf, fee, limit_buy_order) -> None:
|
|||
patch_RPCManager(mocker)
|
||||
patch_exchange(mocker)
|
||||
freqtrade = FreqtradeBot(default_conf)
|
||||
freqtrade.strategy.confirm_trade_entry = MagicMock(return_value=False)
|
||||
stake_amount = 2
|
||||
bid = 0.11
|
||||
buy_rate_mock = MagicMock(return_value=bid)
|
||||
|
|
@ -994,6 +996,13 @@ def test_execute_buy(mocker, default_conf, fee, limit_buy_order) -> None:
|
|||
)
|
||||
pair = 'ETH/BTC'
|
||||
|
||||
assert not freqtrade.execute_buy(pair, stake_amount)
|
||||
assert buy_rate_mock.call_count == 1
|
||||
assert buy_mm.call_count == 0
|
||||
assert freqtrade.strategy.confirm_trade_entry.call_count == 1
|
||||
buy_rate_mock.reset_mock()
|
||||
|
||||
freqtrade.strategy.confirm_trade_entry = MagicMock(return_value=True)
|
||||
assert freqtrade.execute_buy(pair, stake_amount)
|
||||
assert buy_rate_mock.call_count == 1
|
||||
assert buy_mm.call_count == 1
|
||||
|
|
@ -1001,6 +1010,7 @@ def test_execute_buy(mocker, default_conf, fee, limit_buy_order) -> None:
|
|||
assert call_args['pair'] == pair
|
||||
assert call_args['rate'] == bid
|
||||
assert call_args['amount'] == stake_amount / bid
|
||||
buy_rate_mock.reset_mock()
|
||||
|
||||
# Should create an open trade with an open order id
|
||||
# As the order is not fulfilled yet
|
||||
|
|
@ -1013,7 +1023,7 @@ def test_execute_buy(mocker, default_conf, fee, limit_buy_order) -> None:
|
|||
fix_price = 0.06
|
||||
assert freqtrade.execute_buy(pair, stake_amount, fix_price)
|
||||
# Make sure get_buy_rate wasn't called again
|
||||
assert buy_rate_mock.call_count == 1
|
||||
assert buy_rate_mock.call_count == 0
|
||||
|
||||
assert buy_mm.call_count == 2
|
||||
call_args = buy_mm.call_args_list[1][1]
|
||||
|
|
@ -1059,6 +1069,39 @@ def test_execute_buy(mocker, default_conf, fee, limit_buy_order) -> None:
|
|||
assert not freqtrade.execute_buy(pair, stake_amount)
|
||||
|
||||
|
||||
def test_execute_buy_confirm_error(mocker, default_conf, fee, limit_buy_order) -> None:
|
||||
freqtrade = get_patched_freqtradebot(mocker, default_conf)
|
||||
mocker.patch.multiple(
|
||||
'freqtrade.freqtradebot.FreqtradeBot',
|
||||
get_buy_rate=MagicMock(return_value=0.11),
|
||||
_get_min_pair_stake_amount=MagicMock(return_value=1)
|
||||
)
|
||||
mocker.patch.multiple(
|
||||
'freqtrade.exchange.Exchange',
|
||||
fetch_ticker=MagicMock(return_value={
|
||||
'bid': 0.00001172,
|
||||
'ask': 0.00001173,
|
||||
'last': 0.00001172
|
||||
}),
|
||||
buy=MagicMock(return_value=limit_buy_order),
|
||||
get_fee=fee,
|
||||
)
|
||||
stake_amount = 2
|
||||
pair = 'ETH/BTC'
|
||||
|
||||
freqtrade.strategy.confirm_trade_entry = MagicMock(side_effect=ValueError)
|
||||
assert freqtrade.execute_buy(pair, stake_amount)
|
||||
|
||||
freqtrade.strategy.confirm_trade_entry = MagicMock(side_effect=Exception)
|
||||
assert freqtrade.execute_buy(pair, stake_amount)
|
||||
|
||||
freqtrade.strategy.confirm_trade_entry = MagicMock(return_value=True)
|
||||
assert freqtrade.execute_buy(pair, stake_amount)
|
||||
|
||||
freqtrade.strategy.confirm_trade_entry = MagicMock(return_value=False)
|
||||
assert not freqtrade.execute_buy(pair, stake_amount)
|
||||
|
||||
|
||||
def test_add_stoploss_on_exchange(mocker, default_conf, limit_buy_order) -> None:
|
||||
patch_RPCManager(mocker)
|
||||
patch_exchange(mocker)
|
||||
|
|
@ -1962,6 +2005,18 @@ def test_close_trade(default_conf, ticker, limit_buy_order, limit_sell_order,
|
|||
freqtrade.handle_trade(trade)
|
||||
|
||||
|
||||
def test_bot_loop_start_called_once(mocker, default_conf, caplog):
|
||||
ftbot = get_patched_freqtradebot(mocker, default_conf)
|
||||
patch_get_signal(ftbot)
|
||||
ftbot.strategy.bot_loop_start = MagicMock(side_effect=ValueError)
|
||||
ftbot.strategy.analyze = MagicMock()
|
||||
|
||||
ftbot.process()
|
||||
assert log_has_re(r'Strategy caused the following exception.*', caplog)
|
||||
assert ftbot.strategy.bot_loop_start.call_count == 1
|
||||
assert ftbot.strategy.analyze.call_count == 1
|
||||
|
||||
|
||||
def test_check_handle_timedout_buy_usercustom(default_conf, ticker, limit_buy_order_old, open_trade,
|
||||
fee, mocker) -> None:
|
||||
default_conf["unfilledtimeout"] = {"buy": 1400, "sell": 30}
|
||||
|
|
@ -2488,22 +2543,33 @@ def test_execute_sell_up(default_conf, ticker, fee, ticker_sell_up, mocker) -> N
|
|||
patch_whitelist(mocker, default_conf)
|
||||
freqtrade = FreqtradeBot(default_conf)
|
||||
patch_get_signal(freqtrade)
|
||||
freqtrade.strategy.confirm_trade_exit = MagicMock(return_value=False)
|
||||
|
||||
# Create some test data
|
||||
freqtrade.enter_positions()
|
||||
rpc_mock.reset_mock()
|
||||
|
||||
trade = Trade.query.first()
|
||||
assert trade
|
||||
assert freqtrade.strategy.confirm_trade_exit.call_count == 0
|
||||
|
||||
# Increase the price and sell it
|
||||
mocker.patch.multiple(
|
||||
'freqtrade.exchange.Exchange',
|
||||
fetch_ticker=ticker_sell_up
|
||||
)
|
||||
# Prevented sell ...
|
||||
freqtrade.execute_sell(trade=trade, limit=ticker_sell_up()['bid'], sell_reason=SellType.ROI)
|
||||
assert rpc_mock.call_count == 0
|
||||
assert freqtrade.strategy.confirm_trade_exit.call_count == 1
|
||||
|
||||
# Repatch with true
|
||||
freqtrade.strategy.confirm_trade_exit = MagicMock(return_value=True)
|
||||
|
||||
freqtrade.execute_sell(trade=trade, limit=ticker_sell_up()['bid'], sell_reason=SellType.ROI)
|
||||
assert freqtrade.strategy.confirm_trade_exit.call_count == 1
|
||||
|
||||
assert rpc_mock.call_count == 2
|
||||
assert rpc_mock.call_count == 1
|
||||
last_msg = rpc_mock.call_args_list[-1][0][0]
|
||||
assert {
|
||||
'type': RPCMessageType.SELL_NOTIFICATION,
|
||||
|
|
|
|||
|
|
@ -79,10 +79,15 @@ def test_may_execute_sell_stoploss_on_exchange_multi(default_conf, ticker, fee,
|
|||
freqtrade.strategy.order_types['stoploss_on_exchange'] = True
|
||||
# Switch ordertype to market to close trade immediately
|
||||
freqtrade.strategy.order_types['sell'] = 'market'
|
||||
freqtrade.strategy.confirm_trade_entry = MagicMock(return_value=True)
|
||||
freqtrade.strategy.confirm_trade_exit = MagicMock(return_value=True)
|
||||
patch_get_signal(freqtrade)
|
||||
|
||||
# Create some test data
|
||||
freqtrade.enter_positions()
|
||||
assert freqtrade.strategy.confirm_trade_entry.call_count == 3
|
||||
freqtrade.strategy.confirm_trade_entry.reset_mock()
|
||||
assert freqtrade.strategy.confirm_trade_exit.call_count == 0
|
||||
wallets_mock.reset_mock()
|
||||
Trade.session = MagicMock()
|
||||
|
||||
|
|
@ -95,6 +100,9 @@ def test_may_execute_sell_stoploss_on_exchange_multi(default_conf, ticker, fee,
|
|||
n = freqtrade.exit_positions(trades)
|
||||
assert n == 2
|
||||
assert should_sell_mock.call_count == 2
|
||||
assert freqtrade.strategy.confirm_trade_entry.call_count == 0
|
||||
assert freqtrade.strategy.confirm_trade_exit.call_count == 1
|
||||
freqtrade.strategy.confirm_trade_exit.reset_mock()
|
||||
|
||||
# Only order for 3rd trade needs to be cancelled
|
||||
assert cancel_order_mock.call_count == 1
|
||||
|
|
|
|||
Loading…
Reference in New Issue