206 lines
4.8 KiB
Markdown
206 lines
4.8 KiB
Markdown
# lightweight_charts_python
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lightweight-charts-python aims to provide a simple and pythonic way to access and implement [TradingView's Lightweight Charts](https://www.tradingview.com/lightweight-charts/).
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## Installation
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```
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pip install lightweight_charts
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```
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___
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## Features
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1. Simple and easy to use.
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2. Blocking or non-blocking GUI.
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3. Streamlined for live data, with methods for updating directly from tick data.
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4. Support for wxPython.
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___
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### 1. Display data from a csv:
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```python
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import pandas as pd
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from lightweight_charts import Chart
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if __name__ == '__main__':
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chart = Chart()
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# Columns: | time | open | high | low | close | volume (if volume is enabled) |
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df = pd.read_csv('ohlcv.csv')
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chart.set(df)
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chart.show(block=True)
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```
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___
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### 2. Updating bars in real-time:
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```python
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import pandas as pd
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from time import sleep
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from lightweight_charts import Chart
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if __name__ == '__main__':
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chart = Chart()
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df1 = pd.read_csv('ohlcv.csv')
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df2 = pd.read_csv('next_ohlcv.csv')
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chart.set(df1)
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chart.show()
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last_close = df1.iloc[-1]
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for i, series in df2.iterrows():
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chart.update(series)
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if series['close'] > 20 and last_close < 20:
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chart.marker(text='The price crossed $20!')
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last_close = series['close']
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sleep(0.1)
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```
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___
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### 3. Updating bars from tick data in real-time:
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```python
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import pandas as pd
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from time import sleep
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from lightweight_charts import Chart
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if __name__ == '__main__':
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df1 = pd.read_csv('ohlc.csv')
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# Columns: | time | price | volume (if volume is enabled) |
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df2 = pd.read_csv('ticks.csv')
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chart = Chart(volume_enabled=False)
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chart.set(df1)
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chart.show()
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for i, tick in df2.iterrows():
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chart.update_from_tick(tick)
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sleep(0.3)
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```
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___
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### 4. Line Indicators:
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```python
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import pandas as pd
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from lightweight_charts import Chart
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def calculate_sma(data: pd.DataFrame, period: int = 50):
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def avg(d: pd.DataFrame):
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return d['close'].mean()
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result = []
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for i in range(period - 1, len(data)):
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val = avg(data.iloc[i - period + 1:i])
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result.append({'time': data.iloc[i]['date'], 'value': val})
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return pd.DataFrame(result)
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if __name__ == '__main__':
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chart = Chart()
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df = pd.read_csv('ohlcv.csv')
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chart.set(df)
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line = chart.create_line()
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sma_data = calculate_sma(df)
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line.set(sma_data)
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chart.show(block=True)
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```
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___
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### 5. Styling:
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```python
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import pandas as pd
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from lightweight_charts import Chart
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if __name__ == '__main__':
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chart = Chart(debug=True)
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df = pd.read_csv('ohlcv.csv')
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chart.layout(background_color='#090008', text_color='#FFFFFF', font_size=16, font_family='Helvetica')
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chart.candle_style(up_color='#00ff55', down_color='#ed4807', border_up_color='#FFFFFF', border_down_color='#FFFFFF',
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wick_up_color='#FFFFFF', wick_down_color='#FFFFFF')
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chart.volume_config(up_color='#00ff55', down_color='#ed4807')
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chart.watermark('1D', color='rgba(180, 180, 240, 0.7)')
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chart.crosshair(mode='normal', vert_color='#FFFFFF', vert_style='dotted', horz_color='#FFFFFF', horz_style='dotted')
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chart.legend(visible=True, font_size=14)
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chart.set(df)
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chart.show(block=True)
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```
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___
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### 6. Callbacks:
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```python
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import pandas as pd
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from lightweight_charts import Chart
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def on_click(bar: dict):
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print(f"Time: {bar['time']} | Close: {bar['close']}")
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if __name__ == '__main__':
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chart = Chart()
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df = pd.read_csv('ohlcv.csv')
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chart.set(df)
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chart.subscribe_click(on_click)
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chart.show(block=True)
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```
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___
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## Wiki
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For a detailed guide of lightweight-charts-python, view the wiki [here](https://github.com/louisnw01/lightweight-charts-python/wiki).
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___
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_This package is an independent creation and has not been endorsed, sponsored, or approved by TradingView. The author of this package does not have any official relationship with TradingView, and the package does not represent the views or opinions of TradingView._
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