151 lines
4.5 KiB
Markdown
151 lines
4.5 KiB
Markdown
1. install parallel:
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```unzip pp-1.6.4.4.zip```
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```cd pp-1.6.4.4```
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```python3.6 setup.py install```
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2. Move Generator.py into the parent folder, or your "main freqtrade folder."
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```mv Generator.py ../```
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3. Move the default strategy over the default strategy in freqtrade/strategies folder.
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4. Move backtesting.py over the backtesting.py in freqtrade/optimize folder.
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5. Optinlally install modded bittrex.py
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6. Install dependencies:
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```
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sudo add-apt-repository ppa:jonathonf/python-3.6
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sudo apt-get update
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sudo apt-get install python3.6 python3.6-venv python3.6-dev build-essential autoconf libtool pkg-config make wget git
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```
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7. Install ta-lib:
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```
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wget http://prdownloads.sourceforge.net/ta-lib/ta-lib-0.4.0-src.tar.gz
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tar xvzf ta-lib-0.4.0-src.tar.gz
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cd ta-lib
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./configure --prefix=/usr
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make
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make install
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cd ..
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rm -rf ./ta-lib*
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```
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8. Install freqtrade:
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```
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cd ~/freqtrade && pip3.6 install -r requirements.txt && python3.6 setup.py install && pip3.6 install -e .
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```
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9. Run generator.py:
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```python3.6 generator.py```
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10. Wait for results.
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11. Implement these results into your default_strategy:
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***
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You will need to read the if statements and populate_buy_signal and populate_sell_signal in this file carefully.
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Once implemented, remove the if statements in the populate_buy_trend.
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***
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For ease of use, here is an example:
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The if statements that run the random generator are:
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```
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def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
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conditions = []
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# GUARDS AND TRENDS
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if 'uptrend_long_ema' in str(self.params):
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conditions.append(dataframe['ema50'] > dataframe['ema100'])
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if 'macd_below_zero' in str(self.params):
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conditions.append(dataframe['macd'] < 0)
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if 'uptrend_short_ema' in str(self.params):
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conditions.append(dataframe['ema5'] > dataframe['ema10'])
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if 'mfi' in str(self.params):
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conditions.append(dataframe['mfi'] < self.valm)
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if 'fastd' in str(self.params):
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conditions.append(dataframe['fastd'] < self.valfast)
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if 'adx' in str(self.params):
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conditions.append(dataframe['adx'] > self.valadx)
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if 'rsi' in str(self.params):
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conditions.append(dataframe['rsi'] < self.valrsi)
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if 'over_sar' in str(self.params):
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conditions.append(dataframe['close'] > dataframe['sar'])
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if 'green_candle' in str(self.params):
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conditions.append(dataframe['close'] > dataframe['open'])
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if 'uptrend_sma' in str(self.params):
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prevsma = dataframe['sma'].shift(1)
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conditions.append(dataframe['sma'] > prevsma)
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if 'closebb' in str(self.params):
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conditions.append(dataframe['close'] < dataframe['bb_lowerband'])
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if 'temabb' in str(self.params):
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conditions.append(dataframe['tema'] < dataframe['bb_lowerband'])
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if 'fastdt' in str(self.params):
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conditions.append(qtpylib.crossed_above(dataframe['fastd'], 10.0))
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if 'ao' in str(self.params):
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conditions.append(qtpylib.crossed_above(dataframe['ao'], 0.0))
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if 'ema3' in str(self.params):
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conditions.append(qtpylib.crossed_above(dataframe['ema3'], dataframe['ema10']))
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if 'macd' in str(self.params):
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conditions.append(qtpylib.crossed_above(dataframe['macd'], dataframe['macdsignal']))
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if 'closesar' in str(self.params):
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conditions.append(qtpylib.crossed_above(dataframe['close'], dataframe['sar']))
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if 'htsine' in str(self.params):
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conditions.append(qtpylib.crossed_above(dataframe['htleadsine'], dataframe['htsine']))
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if 'has' in str(self.params):
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conditions.append((qtpylib.crossed_above(dataframe['ha_close'], dataframe['ha_open'])) & (dataframe['ha_low'] == dataframe['ha_open']))
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if 'plusdi' in str(self.params):
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conditions.append(qtpylib.crossed_above(dataframe['plus_di'], dataframe['minus_di']))
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dataframe.loc[
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reduce(lambda x, y: x & y, conditions),
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'buy'] = 1
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return dataframe
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```
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So of you get MFI as a option runnning generator.py, and it's option in output is 91, look at the if statements above at mfi, the populate_buy_trend will now look like this:
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```
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def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
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dataframe.loc[
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(
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(dataframe['mfi'] < 91)
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),
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'buy'] = 1
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return dataframe
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```
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It's as simple as that.
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