Python framework for TradingView's Lightweight Charts JavaScript library.
Project description
lightweight-charts-python
lightweight-charts-python aims to provide a simple and pythonic way to access and implement TradingView's Lightweight Charts.
Installation
pip install lightweight-charts
Features
- Simple and easy to use.
- Blocking or non-blocking GUI.
- Streamlined for live data, with methods for updating directly from tick data.
- Supports:
- PyQt
- wxPython
- Streamlit
- asyncio
- Callbacks allowing for timeframe (1min, 5min, 30min etc.) selectors, searching, and more.
- Multi-Pane Charts using the
SubChart
(examples).
1. Display data from a csv:
import pandas as pd
from lightweight_charts import Chart
if __name__ == '__main__':
chart = Chart()
# Columns: | time | open | high | low | close | volume (if volume is enabled) |
df = pd.read_csv('ohlcv.csv')
chart.set(df)
chart.show(block=True)
2. Updating bars in real-time:
import pandas as pd
from time import sleep
from lightweight_charts import Chart
if __name__ == '__main__':
chart = Chart()
df1 = pd.read_csv('ohlcv.csv')
df2 = pd.read_csv('next_ohlcv.csv')
chart.set(df1)
chart.show()
last_close = df1.iloc[-1]
for i, series in df2.iterrows():
chart.update(series)
if series['close'] > 20 and last_close < 20:
chart.marker(text='The price crossed $20!')
last_close = series['close']
sleep(0.1)
3. Updating bars from tick data in real-time:
import pandas as pd
from time import sleep
from lightweight_charts import Chart
if __name__ == '__main__':
df1 = pd.read_csv('ohlc.csv')
# Columns: | time | price | volume (if volume is enabled) |
df2 = pd.read_csv('ticks.csv')
chart = Chart(volume_enabled=False)
chart.set(df1)
chart.show()
for i, tick in df2.iterrows():
chart.update_from_tick(tick)
sleep(0.3)
4. Line Indicators:
import pandas as pd
from lightweight_charts import Chart
def calculate_sma(data: pd.DataFrame, period: int = 50):
def avg(d: pd.DataFrame):
return d['close'].mean()
result = []
for i in range(period - 1, len(data)):
val = avg(data.iloc[i - period + 1:i])
result.append({'time': data.iloc[i]['date'], 'value': val})
return pd.DataFrame(result)
if __name__ == '__main__':
chart = Chart()
df = pd.read_csv('ohlcv.csv')
chart.set(df)
line = chart.create_line()
sma_data = calculate_sma(df)
line.set(sma_data)
chart.show(block=True)
5. Styling:
import pandas as pd
from lightweight_charts import Chart
if __name__ == '__main__':
chart = Chart(debug=True)
df = pd.read_csv('ohlcv.csv')
chart.layout(background_color='#090008', text_color='#FFFFFF', font_size=16,
font_family='Helvetica')
chart.candle_style(up_color='#00ff55', down_color='#ed4807',
border_up_color='#FFFFFF', border_down_color='#FFFFFF',
wick_up_color='#FFFFFF', wick_down_color='#FFFFFF')
chart.volume_config(up_color='#00ff55', down_color='#ed4807')
chart.watermark('1D', color='rgba(180, 180, 240, 0.7)')
chart.crosshair(mode='normal', vert_color='#FFFFFF', vert_style='dotted',
horz_color='#FFFFFF', horz_style='dotted')
chart.legend(visible=True, font_size=14)
chart.set(df)
chart.show(block=True)
6. ChartAsync:
import asyncio
import pandas as pd
from lightweight_charts import ChartAsync
def get_bar_data(symbol, timeframe):
return pd.read_csv(f'bar_data/{symbol}_{timeframe}.csv')
class API:
def __init__(self):
self.chart = None # Changes after each callback.
self.symbol = 'TSLA'
self.timeframe = '5min'
async def on_search(self, searched_string): # Called when the user searches.
self.symbol = searched_string
new_data = await self.get_data()
if new_data.empty:
return
self.chart.set(new_data)
self.chart.corner_text(searched_string)
async def on_timeframe_selection(self, timeframe): # Called when the user changes the timeframe.
self.timeframe = timeframe
new_data = await self.get_data()
if new_data.empty:
return
self.chart.set(new_data)
async def get_data(self):
if self.symbol not in ('AAPL', 'GOOGL', 'TSLA'):
print(f'No data for "{self.symbol}"')
return pd.DataFrame()
data = get_bar_data(self.symbol, self.timeframe)
return data
async def main():
api = API()
chart = ChartAsync(api=api, debug=True)
chart.legend(True)
chart.create_switcher(api.on_timeframe_selection, '1min', '5min', '30min', default='5min')
chart.corner_text(api.symbol)
df = get_bar_data(api.symbol, api.timeframe)
chart.set(df)
await chart.show(block=True)
if __name__ == '__main__':
asyncio.run(main())
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