mirror of
https://github.com/freqtrade/freqtrade.git
synced 2024-11-10 10:21:59 +00:00
Merge branch 'develop' into datadir
This commit is contained in:
kryofly
commit
890083ce7f
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@ -204,19 +204,39 @@ signal. Given following result from hyperopt:
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```
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Best parameters:
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{
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"adx": 1,
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"adx-value": 15.0,
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"fastd": 1,
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"fastd-value": 40.0,
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"green_candle": 1,
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"mfi": 0,
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"over_sar": 0,
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"rsi": 1,
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"rsi-value": 37.0,
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"trigger": 0,
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"uptrend_long_ema": 1,
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"uptrend_short_ema": 0,
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"uptrend_sma": 0
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"adx": {
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"enabled": true,
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"value": 15.0
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},
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"fastd": {
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"enabled": true,
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"value": 40.0
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},
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"green_candle": {
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"enabled": true
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},
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"mfi": {
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"enabled": false
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},
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"over_sar": {
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"enabled": false
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},
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"rsi": {
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"enabled": true,
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"value": 37.0
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},
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"trigger": {
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"type": "lower_bb"
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},
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"uptrend_long_ema": {
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"enabled": true
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},
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"uptrend_short_ema": {
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"enabled": false
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},
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"uptrend_sma": {
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"enabled": false
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}
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}
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Best Result:
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@ -224,14 +244,14 @@ Best Result:
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```
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You should understand this result like:
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- You should **consider** the guard "adx" (`"adx": 1,` = `adx` is true)
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and the best value is `15.0` (`"adx-value": 15.0,`)
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- You should **consider** the guard "fastd" (`"fastd": 1,` = `fastd`
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is true) and the best value is `40.0` (`"fastd-value": 40.0,`)
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- You should **consider** the guard "adx" (`"adx"` is `"enabled": true`)
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and the best value is `15.0` (`"value": 15.0,`)
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- You should **consider** the guard "fastd" (`"fastd"` is `"enabled":
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true`) and the best value is `40.0` (`"value": 40.0,`)
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- You should **consider** to enable the guard "green_candle"
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(`"green_candle": 1,` = `candle` is true) but this guards as no
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(`"green_candle"` is `"enabled": true`) but this guards as no
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customizable value.
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- You should **ignore** the guard "mfi" (`"mfi": 0,` = `mfi` is false)
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- You should **ignore** the guard "mfi" (`"mfi"` is `"enabled": false`)
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- and so on...
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@ -239,8 +259,8 @@ You have to look from
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[freqtrade/optimize/hyperopt.py](https://github.com/gcarq/freqtrade/blob/develop/freqtrade/optimize/hyperopt.py#L170-L200)
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what those values match to.
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So for example you had `adx-value: 15.0` (and `adx: 1` was true) so we
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would look at `adx`-block from
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So for example you had `adx:` with the `value: 15.0` so we would look
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at `adx`-block from
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[freqtrade/optimize/hyperopt.py](https://github.com/gcarq/freqtrade/blob/develop/freqtrade/optimize/hyperopt.py#L178-L179).
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That translates to the following code block to
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[analyze.populate_buy_trend()](https://github.com/gcarq/freqtrade/blob/develop/freqtrade/analyze.py#L73)
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|
|
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@ -11,7 +11,7 @@ import talib.abstract as ta
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from pandas import DataFrame, to_datetime
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from freqtrade.exchange import get_ticker_history
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from freqtrade.vendor.qtpylib.indicators import awesome_oscillator, crossed_above
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from freqtrade.vendor.qtpylib.indicators import awesome_oscillator, PandasObject as qtpylib
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logger = logging.getLogger(__name__)
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@ -40,34 +40,185 @@ def parse_ticker_dataframe(ticker: list) -> DataFrame:
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def populate_indicators(dataframe: DataFrame) -> DataFrame:
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"""
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Adds several different TA indicators to the given DataFrame
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Performance Note: For the best performance be frugal on the number of indicators
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you are using. Let uncomment only the indicator you are using in your strategies
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or your hyperopt configuration, otherwise you will waste your memory and CPU usage.
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"""
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dataframe['sar'] = ta.SAR(dataframe)
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# Momentum Indicator
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# ------------------------------------
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# ADX
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dataframe['adx'] = ta.ADX(dataframe)
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stoch = ta.STOCHF(dataframe)
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dataframe['fastd'] = stoch['fastd']
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dataframe['fastk'] = stoch['fastk']
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dataframe['blower'] = ta.BBANDS(dataframe, nbdevup=2, nbdevdn=2)['lowerband']
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dataframe['sma'] = ta.SMA(dataframe, timeperiod=40)
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dataframe['tema'] = ta.TEMA(dataframe, timeperiod=9)
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dataframe['mfi'] = ta.MFI(dataframe)
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dataframe['rsi'] = ta.RSI(dataframe)
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dataframe['cci'] = ta.CCI(dataframe)
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dataframe['ema5'] = ta.EMA(dataframe, timeperiod=5)
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dataframe['ema10'] = ta.EMA(dataframe, timeperiod=10)
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dataframe['ema50'] = ta.EMA(dataframe, timeperiod=50)
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dataframe['ema100'] = ta.EMA(dataframe, timeperiod=100)
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# Awesome oscillator
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dataframe['ao'] = awesome_oscillator(dataframe)
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"""
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# Commodity Channel Index: values Oversold:<-100, Overbought:>100
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dataframe['cci'] = ta.CCI(dataframe)
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"""
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# MACD
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macd = ta.MACD(dataframe)
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dataframe['macd'] = macd['macd']
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dataframe['macdsignal'] = macd['macdsignal']
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dataframe['macdhist'] = macd['macdhist']
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# MFI
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dataframe['mfi'] = ta.MFI(dataframe)
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# Minus Directional Indicator / Movement
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dataframe['minus_dm'] = ta.MINUS_DM(dataframe)
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dataframe['minus_di'] = ta.MINUS_DI(dataframe)
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# Plus Directional Indicator / Movement
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dataframe['plus_dm'] = ta.PLUS_DM(dataframe)
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dataframe['plus_di'] = ta.PLUS_DI(dataframe)
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"""
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# ROC
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dataframe['roc'] = ta.ROC(dataframe)
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"""
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# RSI
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dataframe['rsi'] = ta.RSI(dataframe)
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"""
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# Inverse Fisher transform on RSI, values [-1.0, 1.0] (https://goo.gl/2JGGoy)
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rsi = 0.1 * (dataframe['rsi'] - 50)
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dataframe['fisher_rsi'] = (numpy.exp(2 * rsi) - 1) / (numpy.exp(2 * rsi) + 1)
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# Inverse Fisher transform on RSI normalized, value [0.0, 100.0] (https://goo.gl/2JGGoy)
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dataframe['fisher_rsi_norma'] = 50 * (dataframe['fisher_rsi'] + 1)
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# Stoch
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stoch = ta.STOCH(dataframe)
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dataframe['slowd'] = stoch['slowd']
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dataframe['slowk'] = stoch['slowk']
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"""
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# Stoch fast
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stoch_fast = ta.STOCHF(dataframe)
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dataframe['fastd'] = stoch_fast['fastd']
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dataframe['fastk'] = stoch_fast['fastk']
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"""
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# Stoch RSI
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stoch_rsi = ta.STOCHRSI(dataframe)
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dataframe['fastd_rsi'] = stoch_rsi['fastd']
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dataframe['fastk_rsi'] = stoch_rsi['fastk']
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"""
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||||
# Overlap Studies
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# ------------------------------------
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||||
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||||
# Previous Bollinger bands
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||||
# Because ta.BBANDS implementation is broken with small numbers, it actually
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# returns middle band for all the three bands. Switch to qtpylib.bollinger_bands
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# and use middle band instead.
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dataframe['blower'] = ta.BBANDS(dataframe, nbdevup=2, nbdevdn=2)['lowerband']
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"""
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# Bollinger bands
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bollinger = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=2)
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dataframe['bb_lowerband'] = bollinger['lower']
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dataframe['bb_middleband'] = bollinger['mid']
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dataframe['bb_upperband'] = bollinger['upper']
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"""
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# EMA - Exponential Moving Average
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dataframe['ema5'] = ta.EMA(dataframe, timeperiod=5)
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dataframe['ema10'] = ta.EMA(dataframe, timeperiod=10)
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dataframe['ema50'] = ta.EMA(dataframe, timeperiod=50)
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dataframe['ema100'] = ta.EMA(dataframe, timeperiod=100)
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# SAR Parabol
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dataframe['sar'] = ta.SAR(dataframe)
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# SMA - Simple Moving Average
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dataframe['sma'] = ta.SMA(dataframe, timeperiod=40)
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# TEMA - Triple Exponential Moving Average
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dataframe['tema'] = ta.TEMA(dataframe, timeperiod=9)
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# Cycle Indicator
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# ------------------------------------
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# Hilbert Transform Indicator - SineWave
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hilbert = ta.HT_SINE(dataframe)
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dataframe['htsine'] = hilbert['sine']
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dataframe['htleadsine'] = hilbert['leadsine']
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dataframe['plus_dm'] = ta.PLUS_DM(dataframe)
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dataframe['plus_di'] = ta.PLUS_DI(dataframe)
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dataframe['minus_dm'] = ta.MINUS_DM(dataframe)
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dataframe['minus_di'] = ta.MINUS_DI(dataframe)
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# Pattern Recognition - Bullish candlestick patterns
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# ------------------------------------
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"""
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# Hammer: values [0, 100]
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dataframe['CDLHAMMER'] = ta.CDLHAMMER(dataframe)
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# Inverted Hammer: values [0, 100]
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dataframe['CDLINVERTEDHAMMER'] = ta.CDLINVERTEDHAMMER(dataframe)
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# Dragonfly Doji: values [0, 100]
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dataframe['CDLDRAGONFLYDOJI'] = ta.CDLDRAGONFLYDOJI(dataframe)
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# Piercing Line: values [0, 100]
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dataframe['CDLPIERCING'] = ta.CDLPIERCING(dataframe) # values [0, 100]
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# Morningstar: values [0, 100]
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dataframe['CDLMORNINGSTAR'] = ta.CDLMORNINGSTAR(dataframe) # values [0, 100]
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# Three White Soldiers: values [0, 100]
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dataframe['CDL3WHITESOLDIERS'] = ta.CDL3WHITESOLDIERS(dataframe) # values [0, 100]
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"""
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||||
|
||||
# Pattern Recognition - Bearish candlestick patterns
|
||||
# ------------------------------------
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||||
"""
|
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# Hanging Man: values [0, 100]
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dataframe['CDLHANGINGMAN'] = ta.CDLHANGINGMAN(dataframe)
|
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|
||||
# Shooting Star: values [0, 100]
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dataframe['CDLSHOOTINGSTAR'] = ta.CDLSHOOTINGSTAR(dataframe)
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|
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# Gravestone Doji: values [0, 100]
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dataframe['CDLGRAVESTONEDOJI'] = ta.CDLGRAVESTONEDOJI(dataframe)
|
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|
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# Dark Cloud Cover: values [0, 100]
|
||||
dataframe['CDLDARKCLOUDCOVER'] = ta.CDLDARKCLOUDCOVER(dataframe)
|
||||
|
||||
# Evening Doji Star: values [0, 100]
|
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dataframe['CDLEVENINGDOJISTAR'] = ta.CDLEVENINGDOJISTAR(dataframe)
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||||
|
||||
# Evening Star: values [0, 100]
|
||||
dataframe['CDLEVENINGSTAR'] = ta.CDLEVENINGSTAR(dataframe)
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||||
"""
|
||||
|
||||
# Pattern Recognition - Bullish/Bearish candlestick patterns
|
||||
# ------------------------------------
|
||||
"""
|
||||
# Three Line Strike: values [0, -100, 100]
|
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dataframe['CDL3LINESTRIKE'] = ta.CDL3LINESTRIKE(dataframe)
|
||||
|
||||
# Spinning Top: values [0, -100, 100]
|
||||
dataframe['CDLSPINNINGTOP'] = ta.CDLSPINNINGTOP(dataframe) # values [0, -100, 100]
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|
||||
# Engulfing: values [0, -100, 100]
|
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dataframe['CDLENGULFING'] = ta.CDLENGULFING(dataframe) # values [0, -100, 100]
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|
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# Harami: values [0, -100, 100]
|
||||
dataframe['CDLHARAMI'] = ta.CDLHARAMI(dataframe) # values [0, -100, 100]
|
||||
|
||||
# Three Outside Up/Down: values [0, -100, 100]
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dataframe['CDL3OUTSIDE'] = ta.CDL3OUTSIDE(dataframe) # values [0, -100, 100]
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|
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# Three Inside Up/Down: values [0, -100, 100]
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||||
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']
|
||||
"""
|
||||
|
||||
return dataframe
|
||||
|
||||
|
||||
|
|
@ -102,8 +253,8 @@ def populate_sell_trend(dataframe: DataFrame) -> DataFrame:
|
|||
dataframe.loc[
|
||||
(
|
||||
(
|
||||
(crossed_above(dataframe['rsi'], 70)) |
|
||||
(crossed_above(dataframe['fastd'], 70))
|
||||
(qtpylib.crossed_above(dataframe['rsi'], 70)) |
|
||||
(qtpylib.crossed_above(dataframe['fastd'], 70))
|
||||
) &
|
||||
(dataframe['adx'] > 10) &
|
||||
(dataframe['minus_di'] > 0)
|
||||
|
|
|
|||
|
|
@ -57,7 +57,11 @@ class CryptoToFiatConverter():
|
|||
]
|
||||
|
||||
def __init__(self) -> None:
|
||||
self._coinmarketcap = Pymarketcap()
|
||||
try:
|
||||
self._coinmarketcap = Pymarketcap()
|
||||
except BaseException:
|
||||
self._coinmarketcap = None
|
||||
|
||||
self._pairs = []
|
||||
|
||||
def convert_amount(self, crypto_amount: float, crypto_symbol: str, fiat_symbol: str) -> float:
|
||||
|
|
@ -147,10 +151,12 @@ class CryptoToFiatConverter():
|
|||
# Check if the fiat convertion you want is supported
|
||||
if not self._is_supported_fiat(fiat=fiat_symbol):
|
||||
raise ValueError('The fiat {} is not supported.'.format(fiat_symbol))
|
||||
|
||||
return float(
|
||||
self._coinmarketcap.ticker(
|
||||
currency=crypto_symbol,
|
||||
convert=fiat_symbol
|
||||
)['price_' + fiat_symbol.lower()]
|
||||
)
|
||||
try:
|
||||
return float(
|
||||
self._coinmarketcap.ticker(
|
||||
currency=crypto_symbol,
|
||||
convert=fiat_symbol
|
||||
)['price_' + fiat_symbol.lower()]
|
||||
)
|
||||
except BaseException:
|
||||
return 0.0
|
||||
|
|
|
|||
|
|
@ -247,12 +247,6 @@ def handle_trade(trade: Trade) -> bool:
|
|||
logger.debug('Handling %s ...', trade)
|
||||
current_rate = exchange.get_ticker(trade.pair)['bid']
|
||||
|
||||
# Experimental: Check if the trade is profitable before selling it (avoid selling at loss)
|
||||
if _CONF.get('experimental', {}).get('sell_profit_only'):
|
||||
logger.debug('Checking if trade is profitable ...')
|
||||
if trade.calc_profit(rate=current_rate) <= 0:
|
||||
return False
|
||||
|
||||
# Check if minimal roi has been reached
|
||||
if min_roi_reached(trade, current_rate, datetime.utcnow()):
|
||||
logger.debug('Executing sell due to ROI ...')
|
||||
|
|
@ -261,6 +255,11 @@ def handle_trade(trade: Trade) -> bool:
|
|||
|
||||
# Experimental: Check if sell signal has been enabled and triggered
|
||||
if _CONF.get('experimental', {}).get('use_sell_signal'):
|
||||
# Experimental: Check if the trade is profitable before selling it (avoid selling at loss)
|
||||
if _CONF.get('experimental', {}).get('sell_profit_only'):
|
||||
logger.debug('Checking if trade is profitable ...')
|
||||
if trade.calc_profit(rate=current_rate) <= 0:
|
||||
return False
|
||||
logger.debug('Checking sell_signal ...')
|
||||
if get_signal(trade.pair, SignalType.SELL):
|
||||
logger.debug('Executing sell due to sell signal ...')
|
||||
|
|
@ -399,14 +398,18 @@ def cleanup() -> None:
|
|||
exit(0)
|
||||
|
||||
|
||||
def main() -> None:
|
||||
def main(sysargv=sys.argv[1:]) -> None:
|
||||
"""
|
||||
Loads and validates the config and handles the main loop
|
||||
:return: None
|
||||
"""
|
||||
global _CONF
|
||||
args = parse_args(sys.argv[1:])
|
||||
if not args:
|
||||
args = parse_args(sysargv,
|
||||
'Simple High Frequency Trading Bot for crypto currencies')
|
||||
|
||||
# A subcommand has been issued
|
||||
if hasattr(args, 'func'):
|
||||
args.func(args)
|
||||
exit(0)
|
||||
|
||||
# Initialize logger
|
||||
|
|
|
|||
|
|
@ -81,21 +81,12 @@ def throttle(func: Callable[..., Any], min_secs: float, *args, **kwargs) -> Any:
|
|||
return result
|
||||
|
||||
|
||||
def parse_args(args: List[str]):
|
||||
def parse_args_common(args: List[str], description: str):
|
||||
"""
|
||||
Parses given arguments and returns an argparse Namespace instance.
|
||||
Returns None if a sub command has been selected and executed.
|
||||
Parses given common arguments and returns them as a parsed object.
|
||||
"""
|
||||
parser = argparse.ArgumentParser(
|
||||
description='Simple High Frequency Trading Bot for crypto currencies'
|
||||
)
|
||||
parser.add_argument(
|
||||
'-c', '--config',
|
||||
help='specify configuration file (default: config.json)',
|
||||
dest='config',
|
||||
default='config.json',
|
||||
type=str,
|
||||
metavar='PATH',
|
||||
description=description
|
||||
)
|
||||
parser.add_argument(
|
||||
'-v', '--verbose',
|
||||
|
|
@ -111,14 +102,22 @@ def parse_args(args: List[str]):
|
|||
version='%(prog)s {}'.format(__version__),
|
||||
)
|
||||
parser.add_argument(
|
||||
'--dynamic-whitelist',
|
||||
help='dynamically generate and update whitelist based on 24h BaseVolume (Default 20 currencies)', # noqa
|
||||
dest='dynamic_whitelist',
|
||||
const=20,
|
||||
type=int,
|
||||
metavar='INT',
|
||||
nargs='?',
|
||||
'-c', '--config',
|
||||
help='specify configuration file (default: config.json)',
|
||||
dest='config',
|
||||
default='config.json',
|
||||
type=str,
|
||||
metavar='PATH',
|
||||
)
|
||||
return parser
|
||||
|
||||
|
||||
def parse_args(args: List[str], description: str):
|
||||
"""
|
||||
Parses given arguments and returns an argparse Namespace instance.
|
||||
Returns None if a sub command has been selected and executed.
|
||||
"""
|
||||
parser = parse_args_common(args, description)
|
||||
parser.add_argument(
|
||||
'--dry-run-db',
|
||||
help='Force dry run to use a local DB "tradesv3.dry_run.sqlite" instead of memory DB. Work only if dry_run is \
|
||||
|
|
@ -134,16 +133,18 @@ def parse_args(args: List[str]):
|
|||
type=str,
|
||||
metavar='PATH',
|
||||
)
|
||||
parser.add_argument(
|
||||
'--dynamic-whitelist',
|
||||
help='dynamically generate and update whitelist based on 24h BaseVolume (Default 20 currencies)', # noqa
|
||||
dest='dynamic_whitelist',
|
||||
const=20,
|
||||
type=int,
|
||||
metavar='INT',
|
||||
nargs='?',
|
||||
)
|
||||
|
||||
build_subcommands(parser)
|
||||
parsed_args = parser.parse_args(args)
|
||||
|
||||
# No subcommand as been selected
|
||||
if not hasattr(parsed_args, 'func'):
|
||||
return parsed_args
|
||||
|
||||
parsed_args.func(parsed_args)
|
||||
return None
|
||||
return parser.parse_args(args)
|
||||
|
||||
|
||||
def build_subcommands(parser: argparse.ArgumentParser) -> None:
|
||||
|
|
|
|||
|
|
@ -8,7 +8,7 @@ from functools import reduce
|
|||
from math import exp
|
||||
from operator import itemgetter
|
||||
|
||||
from hyperopt import fmin, tpe, hp, Trials, STATUS_OK, STATUS_FAIL
|
||||
from hyperopt import fmin, tpe, hp, Trials, STATUS_OK, STATUS_FAIL, space_eval
|
||||
from hyperopt.mongoexp import MongoTrials
|
||||
from pandas import DataFrame
|
||||
|
||||
|
|
@ -209,7 +209,7 @@ def buy_strategy_generator(params):
|
|||
|
||||
|
||||
def start(args):
|
||||
global TOTAL_TRIES, PROCESSED
|
||||
global TOTAL_TRIES, PROCESSED, SPACE
|
||||
TOTAL_TRIES = args.epochs
|
||||
|
||||
exchange._API = Bittrex({'key': '', 'secret': ''})
|
||||
|
|
@ -236,6 +236,11 @@ def start(args):
|
|||
trials = Trials()
|
||||
|
||||
best = fmin(fn=optimizer, space=SPACE, algo=tpe.suggest, max_evals=TOTAL_TRIES, trials=trials)
|
||||
|
||||
# Improve best parameter logging display
|
||||
if best:
|
||||
best = space_eval(SPACE, best)
|
||||
|
||||
logger.info('Best parameters:\n%s', json.dumps(best, indent=4))
|
||||
|
||||
results = sorted(trials.results, key=itemgetter('loss'))
|
||||
|
|
|
|||
|
|
@ -77,3 +77,40 @@ def test_no_log_if_loss_does_not_improve(mocker):
|
|||
})
|
||||
|
||||
assert not logger.called
|
||||
|
||||
|
||||
def test_fmin_best_results(mocker, caplog):
|
||||
fmin_result = {
|
||||
"adx": 1,
|
||||
"adx-value": 15.0,
|
||||
"fastd": 1,
|
||||
"fastd-value": 40.0,
|
||||
"green_candle": 1,
|
||||
"mfi": 0,
|
||||
"over_sar": 0,
|
||||
"rsi": 1,
|
||||
"rsi-value": 37.0,
|
||||
"trigger": 2,
|
||||
"uptrend_long_ema": 1,
|
||||
"uptrend_short_ema": 0,
|
||||
"uptrend_sma": 0
|
||||
}
|
||||
|
||||
mocker.patch('freqtrade.optimize.hyperopt.MongoTrials', return_value=create_trials(mocker))
|
||||
mocker.patch('freqtrade.optimize.preprocess')
|
||||
mocker.patch('freqtrade.optimize.load_data')
|
||||
mocker.patch('freqtrade.optimize.hyperopt.fmin', return_value=fmin_result)
|
||||
|
||||
args = mocker.Mock(epochs=1, config='config.json.example')
|
||||
start(args)
|
||||
|
||||
exists = [
|
||||
'Best parameters',
|
||||
'"adx": {\n "enabled": true,\n "value": 15.0\n },',
|
||||
'"green_candle": {\n "enabled": true\n },',
|
||||
'"mfi": {\n "enabled": false\n },',
|
||||
'"trigger": {\n "type": "ao_cross_zero"\n },'
|
||||
]
|
||||
|
||||
for line in exists:
|
||||
assert line in caplog.text
|
||||
|
|
|
|||
|
|
@ -167,6 +167,7 @@ def test_profit_handle(
|
|||
mocker.patch.multiple('freqtrade.fiat_convert.Pymarketcap',
|
||||
ticker=MagicMock(return_value={'price_usd': 15000.0}),
|
||||
_cache_symbols=MagicMock(return_value={'BTC': 1}))
|
||||
mocker.patch('freqtrade.fiat_convert.CryptoToFiatConverter._find_price', return_value=15000.0)
|
||||
init(default_conf, create_engine('sqlite://'))
|
||||
|
||||
_profit(bot=MagicMock(), update=update)
|
||||
|
|
@ -422,6 +423,7 @@ def test_daily_handle(
|
|||
mocker.patch.multiple('freqtrade.fiat_convert.Pymarketcap',
|
||||
ticker=MagicMock(return_value={'price_usd': 15000.0}),
|
||||
_cache_symbols=MagicMock(return_value={'BTC': 1}))
|
||||
mocker.patch('freqtrade.fiat_convert.CryptoToFiatConverter._find_price', return_value=15000.0)
|
||||
init(default_conf, create_engine('sqlite://'))
|
||||
|
||||
# Create some test data
|
||||
|
|
|
|||
|
|
@ -72,8 +72,11 @@ def test_fiat_convert_find_price(mocker):
|
|||
with pytest.raises(ValueError, match=r'The fiat ABC is not supported.'):
|
||||
fiat_convert._find_price(crypto_symbol='BTC', fiat_symbol='ABC')
|
||||
|
||||
mocker.patch('freqtrade.fiat_convert.CryptoToFiatConverter._find_price', return_value=12345.0)
|
||||
assert fiat_convert.get_price(crypto_symbol='BTC', fiat_symbol='USD') == 12345.0
|
||||
assert fiat_convert.get_price(crypto_symbol='btc', fiat_symbol='usd') == 12345.0
|
||||
|
||||
mocker.patch('freqtrade.fiat_convert.CryptoToFiatConverter._find_price', return_value=13000.2)
|
||||
assert fiat_convert.get_price(crypto_symbol='BTC', fiat_symbol='EUR') == 13000.2
|
||||
|
||||
|
||||
|
|
@ -83,6 +86,7 @@ def test_fiat_convert_get_price(mocker):
|
|||
'price_eur': 15000.0
|
||||
})
|
||||
mocker.patch('freqtrade.fiat_convert.Pymarketcap.ticker', api_mock)
|
||||
mocker.patch('freqtrade.fiat_convert.CryptoToFiatConverter._find_price', return_value=28000.0)
|
||||
|
||||
fiat_convert = CryptoToFiatConverter()
|
||||
|
||||
|
|
@ -109,3 +113,12 @@ def test_fiat_convert_get_price(mocker):
|
|||
fiat_convert._pairs[0]._expiration = expiration
|
||||
assert fiat_convert.get_price(crypto_symbol='BTC', fiat_symbol='USD') == 28000.0
|
||||
assert fiat_convert._pairs[0]._expiration is not expiration
|
||||
|
||||
|
||||
def test_fiat_convert_without_network(mocker):
|
||||
Pymarketcap = MagicMock(side_effect=ImportError('Oh boy, you have no network!'))
|
||||
mocker.patch('freqtrade.fiat_convert.Pymarketcap', Pymarketcap)
|
||||
|
||||
fiat_convert = CryptoToFiatConverter()
|
||||
assert fiat_convert._coinmarketcap is None
|
||||
assert fiat_convert._find_price(crypto_symbol='BTC', fiat_symbol='USD') == 0.0
|
||||
|
|
|
|||
|
|
@ -15,6 +15,39 @@ from freqtrade.main import create_trade, handle_trade, init, \
|
|||
get_target_bid, _process, execute_sell, check_handle_timedout
|
||||
from freqtrade.misc import get_state, State
|
||||
from freqtrade.persistence import Trade
|
||||
import freqtrade.main as main
|
||||
|
||||
|
||||
# Test that main() can start backtesting or hyperopt.
|
||||
# and also ensure we can pass some specific arguments
|
||||
# argument parsing is done in test_misc.py
|
||||
|
||||
def test_parse_args_backtesting(mocker):
|
||||
backtesting_mock = mocker.patch(
|
||||
'freqtrade.optimize.backtesting.start', MagicMock())
|
||||
with pytest.raises(SystemExit, match=r'0'):
|
||||
main.main(['backtesting'])
|
||||
assert backtesting_mock.call_count == 1
|
||||
call_args = backtesting_mock.call_args[0][0]
|
||||
assert call_args.config == 'config.json'
|
||||
assert call_args.live is False
|
||||
assert call_args.loglevel == 20
|
||||
assert call_args.subparser == 'backtesting'
|
||||
assert call_args.func is not None
|
||||
assert call_args.ticker_interval == 5
|
||||
|
||||
|
||||
def test_main_start_hyperopt(mocker):
|
||||
hyperopt_mock = mocker.patch(
|
||||
'freqtrade.optimize.hyperopt.start', MagicMock())
|
||||
with pytest.raises(SystemExit, match=r'0'):
|
||||
main.main(['hyperopt'])
|
||||
assert hyperopt_mock.call_count == 1
|
||||
call_args = hyperopt_mock.call_args[0][0]
|
||||
assert call_args.config == 'config.json'
|
||||
assert call_args.loglevel == 20
|
||||
assert call_args.subparser == 'hyperopt'
|
||||
assert call_args.func is not None
|
||||
|
||||
|
||||
def test_process_trade_creation(default_conf, ticker, limit_buy_order, health, mocker):
|
||||
|
|
@ -331,7 +364,7 @@ def test_check_handle_timedout_buy(default_conf, ticker, health, limit_buy_order
|
|||
cancel_order=cancel_order_mock)
|
||||
init(default_conf, create_engine('sqlite://'))
|
||||
|
||||
tradeBuy = Trade(
|
||||
trade_buy = Trade(
|
||||
pair='BTC_ETH',
|
||||
open_rate=0.00001099,
|
||||
exchange='BITTREX',
|
||||
|
|
@ -343,12 +376,12 @@ def test_check_handle_timedout_buy(default_conf, ticker, health, limit_buy_order
|
|||
is_open=True
|
||||
)
|
||||
|
||||
Trade.session.add(tradeBuy)
|
||||
Trade.session.add(trade_buy)
|
||||
|
||||
# check it does cancel buy orders over the time limit
|
||||
check_handle_timedout(600)
|
||||
assert cancel_order_mock.call_count == 1
|
||||
trades = Trade.query.filter(Trade.open_order_id.is_(tradeBuy.open_order_id)).all()
|
||||
trades = Trade.query.filter(Trade.open_order_id.is_(trade_buy.open_order_id)).all()
|
||||
assert len(trades) == 0
|
||||
|
||||
|
||||
|
|
@ -363,7 +396,7 @@ def test_check_handle_timedout_sell(default_conf, ticker, health, limit_sell_ord
|
|||
cancel_order=cancel_order_mock)
|
||||
init(default_conf, create_engine('sqlite://'))
|
||||
|
||||
tradeSell = Trade(
|
||||
trade_sell = Trade(
|
||||
pair='BTC_ETH',
|
||||
open_rate=0.00001099,
|
||||
exchange='BITTREX',
|
||||
|
|
@ -376,12 +409,12 @@ def test_check_handle_timedout_sell(default_conf, ticker, health, limit_sell_ord
|
|||
is_open=False
|
||||
)
|
||||
|
||||
Trade.session.add(tradeSell)
|
||||
Trade.session.add(trade_sell)
|
||||
|
||||
# check it does cancel sell orders over the time limit
|
||||
check_handle_timedout(600)
|
||||
assert cancel_order_mock.call_count == 1
|
||||
assert tradeSell.is_open is True
|
||||
assert trade_sell.is_open is True
|
||||
|
||||
|
||||
def test_check_handle_timedout_partial(default_conf, ticker, limit_buy_order_old_partial,
|
||||
|
|
@ -396,7 +429,7 @@ def test_check_handle_timedout_partial(default_conf, ticker, limit_buy_order_old
|
|||
cancel_order=cancel_order_mock)
|
||||
init(default_conf, create_engine('sqlite://'))
|
||||
|
||||
tradeBuy = Trade(
|
||||
trade_buy = Trade(
|
||||
pair='BTC_ETH',
|
||||
open_rate=0.00001099,
|
||||
exchange='BITTREX',
|
||||
|
|
@ -408,16 +441,16 @@ def test_check_handle_timedout_partial(default_conf, ticker, limit_buy_order_old
|
|||
is_open=True
|
||||
)
|
||||
|
||||
Trade.session.add(tradeBuy)
|
||||
Trade.session.add(trade_buy)
|
||||
|
||||
# check it does cancel buy orders over the time limit
|
||||
# note this is for a partially-complete buy order
|
||||
check_handle_timedout(600)
|
||||
assert cancel_order_mock.call_count == 1
|
||||
trades = Trade.query.filter(Trade.open_order_id.is_(tradeBuy.open_order_id)).all()
|
||||
trades = Trade.query.filter(Trade.open_order_id.is_(trade_buy.open_order_id)).all()
|
||||
assert len(trades) == 1
|
||||
assert trades[0].amount == 23.0
|
||||
assert trades[0].stake_amount == tradeBuy.open_rate * trades[0].amount
|
||||
assert trades[0].stake_amount == trade_buy.open_rate * trades[0].amount
|
||||
|
||||
|
||||
def test_balance_fully_ask_side(mocker):
|
||||
|
|
@ -537,10 +570,13 @@ def test_execute_sell_without_conf(default_conf, ticker, ticker_sell_up, mocker)
|
|||
|
||||
|
||||
def test_sell_profit_only_enable_profit(default_conf, limit_buy_order, mocker):
|
||||
default_conf['experimental'] = {}
|
||||
default_conf['experimental']['sell_profit_only'] = True
|
||||
default_conf['experimental'] = {
|
||||
'use_sell_signal': True,
|
||||
'sell_profit_only': True,
|
||||
}
|
||||
|
||||
mocker.patch.dict('freqtrade.main._CONF', default_conf)
|
||||
mocker.patch('freqtrade.main.min_roi_reached', return_value=False)
|
||||
mocker.patch('freqtrade.main.get_signal', side_effect=lambda s, t: True)
|
||||
mocker.patch.multiple('freqtrade.rpc', init=MagicMock(), send_msg=MagicMock())
|
||||
mocker.patch.multiple('freqtrade.main.exchange',
|
||||
|
|
@ -561,10 +597,13 @@ def test_sell_profit_only_enable_profit(default_conf, limit_buy_order, mocker):
|
|||
|
||||
|
||||
def test_sell_profit_only_disable_profit(default_conf, limit_buy_order, mocker):
|
||||
default_conf['experimental'] = {}
|
||||
default_conf['experimental']['sell_profit_only'] = False
|
||||
default_conf['experimental'] = {
|
||||
'use_sell_signal': True,
|
||||
'sell_profit_only': False,
|
||||
}
|
||||
|
||||
mocker.patch.dict('freqtrade.main._CONF', default_conf)
|
||||
mocker.patch('freqtrade.main.min_roi_reached', return_value=False)
|
||||
mocker.patch('freqtrade.main.get_signal', side_effect=lambda s, t: True)
|
||||
mocker.patch.multiple('freqtrade.rpc', init=MagicMock(), send_msg=MagicMock())
|
||||
mocker.patch.multiple('freqtrade.main.exchange',
|
||||
|
|
@ -585,10 +624,13 @@ def test_sell_profit_only_disable_profit(default_conf, limit_buy_order, mocker):
|
|||
|
||||
|
||||
def test_sell_profit_only_enable_loss(default_conf, limit_buy_order, mocker):
|
||||
default_conf['experimental'] = {}
|
||||
default_conf['experimental']['sell_profit_only'] = True
|
||||
default_conf['experimental'] = {
|
||||
'use_sell_signal': True,
|
||||
'sell_profit_only': True,
|
||||
}
|
||||
|
||||
mocker.patch.dict('freqtrade.main._CONF', default_conf)
|
||||
mocker.patch('freqtrade.main.min_roi_reached', return_value=False)
|
||||
mocker.patch('freqtrade.main.get_signal', side_effect=lambda s, t: True)
|
||||
mocker.patch.multiple('freqtrade.rpc', init=MagicMock(), send_msg=MagicMock())
|
||||
mocker.patch.multiple('freqtrade.main.exchange',
|
||||
|
|
@ -609,10 +651,13 @@ def test_sell_profit_only_enable_loss(default_conf, limit_buy_order, mocker):
|
|||
|
||||
|
||||
def test_sell_profit_only_disable_loss(default_conf, limit_buy_order, mocker):
|
||||
default_conf['experimental'] = {}
|
||||
default_conf['experimental']['sell_profit_only'] = False
|
||||
default_conf['experimental'] = {
|
||||
'use_sell_signal': True,
|
||||
'sell_profit_only': False,
|
||||
}
|
||||
|
||||
mocker.patch.dict('freqtrade.main._CONF', default_conf)
|
||||
mocker.patch('freqtrade.main.min_roi_reached', return_value=False)
|
||||
mocker.patch('freqtrade.main.get_signal', side_effect=lambda s, t: True)
|
||||
mocker.patch.multiple('freqtrade.rpc', init=MagicMock(), send_msg=MagicMock())
|
||||
mocker.patch.multiple('freqtrade.main.exchange',
|
||||
|
|
|
|||
|
|
@ -1,13 +1,14 @@
|
|||
# pragma pylint: disable=missing-docstring,C0103
|
||||
import json
|
||||
import time
|
||||
import argparse
|
||||
from copy import deepcopy
|
||||
from unittest.mock import MagicMock
|
||||
|
||||
import pytest
|
||||
from jsonschema import ValidationError
|
||||
|
||||
from freqtrade.misc import throttle, parse_args, load_config
|
||||
from freqtrade.misc import throttle, parse_args, load_config,\
|
||||
parse_args_common
|
||||
|
||||
|
||||
def test_throttle():
|
||||
|
|
@ -38,89 +39,83 @@ def test_throttle_with_assets():
|
|||
assert result == -1
|
||||
|
||||
|
||||
# Parse common command-line-arguments
|
||||
# used for all tools
|
||||
|
||||
|
||||
def test_parse_args_none():
|
||||
args = parse_args_common([], '')
|
||||
assert isinstance(args, argparse.ArgumentParser)
|
||||
|
||||
|
||||
def test_parse_args_defaults():
|
||||
args = parse_args([])
|
||||
assert args is not None
|
||||
args = parse_args([], '')
|
||||
assert args.config == 'config.json'
|
||||
assert args.dynamic_whitelist is None
|
||||
assert args.loglevel == 20
|
||||
|
||||
|
||||
def test_parse_args_invalid():
|
||||
with pytest.raises(SystemExit, match=r'2'):
|
||||
parse_args(['-c'])
|
||||
|
||||
|
||||
def test_parse_args_config():
|
||||
args = parse_args(['-c', '/dev/null'])
|
||||
assert args is not None
|
||||
args = parse_args(['-c', '/dev/null'], '')
|
||||
assert args.config == '/dev/null'
|
||||
|
||||
args = parse_args(['--config', '/dev/null'])
|
||||
assert args is not None
|
||||
args = parse_args(['--config', '/dev/null'], '')
|
||||
assert args.config == '/dev/null'
|
||||
|
||||
|
||||
def test_parse_args_verbose():
|
||||
args = parse_args(['-v'])
|
||||
assert args is not None
|
||||
args = parse_args(['-v'], '')
|
||||
assert args.loglevel == 10
|
||||
|
||||
args = parse_args(['--verbose'], '')
|
||||
assert args.loglevel == 10
|
||||
|
||||
|
||||
def test_parse_args_version():
|
||||
with pytest.raises(SystemExit, match=r'0'):
|
||||
parse_args(['--version'], '')
|
||||
|
||||
|
||||
def test_parse_args_invalid():
|
||||
with pytest.raises(SystemExit, match=r'2'):
|
||||
parse_args(['-c'], '')
|
||||
|
||||
|
||||
# Parse command-line-arguments
|
||||
# used for main, backtesting and hyperopt
|
||||
|
||||
|
||||
def test_parse_args_dynamic_whitelist():
|
||||
args = parse_args(['--dynamic-whitelist'])
|
||||
assert args is not None
|
||||
args = parse_args(['--dynamic-whitelist'], '')
|
||||
assert args.dynamic_whitelist is 20
|
||||
|
||||
|
||||
def test_parse_args_dynamic_whitelist_10():
|
||||
args = parse_args(['--dynamic-whitelist', '10'])
|
||||
assert args is not None
|
||||
args = parse_args(['--dynamic-whitelist', '10'], '')
|
||||
assert args.dynamic_whitelist is 10
|
||||
|
||||
|
||||
def test_parse_args_dynamic_whitelist_invalid_values():
|
||||
with pytest.raises(SystemExit, match=r'2'):
|
||||
parse_args(['--dynamic-whitelist', 'abc'])
|
||||
|
||||
|
||||
def test_parse_args_backtesting(mocker):
|
||||
backtesting_mock = mocker.patch(
|
||||
'freqtrade.optimize.backtesting.start', MagicMock())
|
||||
args = parse_args(['backtesting'])
|
||||
assert args is None
|
||||
assert backtesting_mock.call_count == 1
|
||||
|
||||
call_args = backtesting_mock.call_args[0][0]
|
||||
assert call_args.config == 'config.json'
|
||||
assert call_args.live is False
|
||||
assert call_args.loglevel == 20
|
||||
assert call_args.subparser == 'backtesting'
|
||||
assert call_args.func is not None
|
||||
assert call_args.ticker_interval == 5
|
||||
parse_args(['--dynamic-whitelist', 'abc'], '')
|
||||
|
||||
|
||||
def test_parse_args_backtesting_invalid():
|
||||
with pytest.raises(SystemExit, match=r'2'):
|
||||
parse_args(['backtesting --ticker-interval'])
|
||||
parse_args(['backtesting --ticker-interval'], '')
|
||||
|
||||
with pytest.raises(SystemExit, match=r'2'):
|
||||
parse_args(['backtesting --ticker-interval', 'abc'])
|
||||
parse_args(['backtesting --ticker-interval', 'abc'], '')
|
||||
|
||||
|
||||
def test_parse_args_backtesting_custom(mocker):
|
||||
backtesting_mock = mocker.patch(
|
||||
'freqtrade.optimize.backtesting.start', MagicMock())
|
||||
args = parse_args([
|
||||
def test_parse_args_backtesting_custom():
|
||||
args = [
|
||||
'-c', 'test_conf.json',
|
||||
'backtesting',
|
||||
'--live',
|
||||
'--ticker-interval', '1',
|
||||
'--refresh-pairs-cached'])
|
||||
assert args is None
|
||||
assert backtesting_mock.call_count == 1
|
||||
|
||||
call_args = backtesting_mock.call_args[0][0]
|
||||
'--refresh-pairs-cached']
|
||||
call_args = parse_args(args, '')
|
||||
assert call_args.config == 'test_conf.json'
|
||||
assert call_args.live is True
|
||||
assert call_args.loglevel == 20
|
||||
|
|
@ -130,28 +125,9 @@ def test_parse_args_backtesting_custom(mocker):
|
|||
assert call_args.refresh_pairs is True
|
||||
|
||||
|
||||
def test_parse_args_hyperopt(mocker):
|
||||
hyperopt_mock = mocker.patch(
|
||||
'freqtrade.optimize.hyperopt.start', MagicMock())
|
||||
args = parse_args(['hyperopt'])
|
||||
assert args is None
|
||||
assert hyperopt_mock.call_count == 1
|
||||
|
||||
call_args = hyperopt_mock.call_args[0][0]
|
||||
assert call_args.config == 'config.json'
|
||||
assert call_args.loglevel == 20
|
||||
assert call_args.subparser == 'hyperopt'
|
||||
assert call_args.func is not None
|
||||
|
||||
|
||||
def test_parse_args_hyperopt_custom(mocker):
|
||||
hyperopt_mock = mocker.patch(
|
||||
'freqtrade.optimize.hyperopt.start', MagicMock())
|
||||
args = parse_args(['-c', 'test_conf.json', 'hyperopt', '--epochs', '20'])
|
||||
assert args is None
|
||||
assert hyperopt_mock.call_count == 1
|
||||
|
||||
call_args = hyperopt_mock.call_args[0][0]
|
||||
args = ['-c', 'test_conf.json', 'hyperopt', '--epochs', '20']
|
||||
call_args = parse_args(args, '')
|
||||
assert call_args.config == 'test_conf.json'
|
||||
assert call_args.epochs == 20
|
||||
assert call_args.loglevel == 20
|
||||
|
|
|
|||
|
|
@ -10,7 +10,7 @@ pandas==0.22.0
|
|||
scikit-learn==0.19.1
|
||||
scipy==1.0.0
|
||||
jsonschema==2.6.0
|
||||
numpy==1.13.3
|
||||
numpy==1.14.0
|
||||
TA-Lib==0.4.10
|
||||
pytest==3.3.2
|
||||
pytest-mock==1.6.3
|
||||
|
|
|
|||
|
|
@ -1,17 +1,33 @@
|
|||
#!/usr/bin/env python3
|
||||
|
||||
import sys
|
||||
import argparse
|
||||
import matplotlib # Install PYQT5 manually if you want to test this helper function
|
||||
matplotlib.use("Qt5Agg")
|
||||
import matplotlib.pyplot as plt
|
||||
from freqtrade import exchange, analyze
|
||||
from freqtrade.misc import parse_args_common
|
||||
|
||||
|
||||
def plot_analyzed_dataframe(pair: str) -> None:
|
||||
def plot_parse_args(args ):
|
||||
parser = parse_args_common(args, 'Graph utility')
|
||||
parser.add_argument(
|
||||
'-p', '--pair',
|
||||
help = 'What currency pair',
|
||||
dest = 'pair',
|
||||
default = 'BTC_ETH',
|
||||
type = str,
|
||||
)
|
||||
return parser.parse_args(args)
|
||||
|
||||
|
||||
def plot_analyzed_dataframe(args) -> None:
|
||||
"""
|
||||
Calls analyze() and plots the returned dataframe
|
||||
:param pair: pair as str
|
||||
:return: None
|
||||
"""
|
||||
pair = args.pair
|
||||
|
||||
# Init Bittrex to use public API
|
||||
exchange._API = exchange.Bittrex({'key': '', 'secret': ''})
|
||||
|
|
@ -50,4 +66,5 @@ def plot_analyzed_dataframe(pair: str) -> None:
|
|||
|
||||
|
||||
if __name__ == '__main__':
|
||||
plot_analyzed_dataframe('BTC_ETH')
|
||||
args = plot_parse_args(sys.argv[1:])
|
||||
plot_analyzed_dataframe(args)
|
||||
|
|
|
|||
Loading…
Reference in New Issue
Block a user