a58f1e306c
- Added the ChartAsync class, allowing for more sophisticated Charts and SubCharts. - Symbol searching, timeframe selectors, and more is now possible with this varation of Chart. `QtChart` and `WxChart` have access to all the methods that `ChartAsync` has, however they utilize their own respective event loops rather than asyncio. New Feature: `StreamlitChart` - Chart window that can display static data within a Streamlit application. Removed the `subscribe_click` method.
262 lines
7.2 KiB
Markdown
262 lines
7.2 KiB
Markdown
<div align="center">
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# lightweight-charts-python
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[](https://pypi.org/project/lightweight-charts/)
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[](https://python.org "Go to Python homepage")
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[](https://github.com/louisnw01/lightweight-charts-python/blob/main/LICENSE)
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[](https://lightweight-charts-python.readthedocs.io/en/latest/docs.html)
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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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</div>
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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. Supports:
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* PyQt
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* wxPython
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* Streamlit
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* asyncio
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5. [Callbacks](https://lightweight-charts-python.readthedocs.io/en/latest/docs.html#chartasync) allowing for timeframe (1min, 5min, 30min etc.) selectors, searching, and more.
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6. Multi-Pane Charts using the `SubChart` ([examples](https://lightweight-charts-python.readthedocs.io/en/latest/docs.html#subchart)).
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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,
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font_family='Helvetica')
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chart.candle_style(up_color='#00ff55', down_color='#ed4807',
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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',
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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. ChartAsync:
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```python
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import asyncio
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import pandas as pd
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from lightweight_charts import ChartAsync
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def get_bar_data(symbol, timeframe):
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return pd.read_csv(f'bar_data/{symbol}_{timeframe}.csv')
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class API:
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def __init__(self):
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self.chart = None # Changes after each callback.
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self.symbol = 'TSLA'
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self.timeframe = '5min'
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async def on_search(self, searched_string): # Called when the user searches.
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self.symbol = searched_string
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new_data = await self.get_data()
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if new_data.empty:
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return
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self.chart.set(new_data)
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self.chart.corner_text(searched_string)
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async def on_timeframe_selection(self, timeframe): # Called when the user changes the timeframe.
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self.timeframe = timeframe
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new_data = await self.get_data()
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if new_data.empty:
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return
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self.chart.set(new_data)
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async def get_data(self):
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if self.symbol not in ('AAPL', 'GOOGL', 'TSLA'):
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print(f'No data for "{self.symbol}"')
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return pd.DataFrame()
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data = get_bar_data(self.symbol, self.timeframe)
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return data
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async def main():
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api = API()
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chart = ChartAsync(api=api, debug=True)
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chart.legend(True)
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chart.create_switcher(api.on_timeframe_selection, '1min', '5min', '30min', default='5min')
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chart.corner_text(api.symbol)
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df = get_bar_data(api.symbol, api.timeframe)
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chart.set(df)
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await chart.show(block=True)
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if __name__ == '__main__':
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asyncio.run(main())
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```
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___
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<div align="center">
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[](https://lightweight-charts-python.readthedocs.io/en/latest/docs.html)
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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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</div>
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