louisnw 527130e618 Ability to save drawings
- Added `toolbox` to the common methods.
- `toolbox.save_drawings_under` can save drawings under a specific `topbar` widget. eg `chart.toolbox.save_drawings_under(chart.topbar[’symbol’]`)
- `toolbox.load_drawings` will load and display drawings stored under the tag/string given.
- `toolbox.export_drawings` will export all currently saved drawings to the given file path.
- `toolbox.import_drawings` will import the drawings stored at the given file path.

Fixes/Enhancements:
- `update` methods are no longer case sensitive.
- HorizontalLines no longer throw cyclic structure errors in the web console.
- `API` methods can now be normal methods or coroutines.
2023-07-20 21:52:17 +01:00
2023-07-20 21:52:17 +01:00
2023-07-20 21:52:17 +01:00
2023-05-10 20:45:23 +01:00
2023-07-20 21:52:17 +01:00
2023-07-20 21:52:17 +01:00

lightweight-charts-python

PyPi Release Made with Python License Documentation

cover

lightweight-charts-python aims to provide a simple and pythonic way to access and implement TradingView's Lightweight Charts.

Installation

pip install lightweight-charts
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Features

  1. Simple and easy to use.
  2. Blocking or non-blocking GUI.
  3. Streamlined for live data, with methods for updating directly from tick data.
  4. Multi-Pane Charts using the SubChart.
  5. The Toolbox, allowing for trendlines, rays and horizontal lines to be drawn directly onto charts.
  6. Callbacks allowing for timeframe (1min, 5min, 30min etc.) selectors, searching, and more.
  7. Direct integration of market data through Polygon.io's market data API.

Supports: Jupyter Notebooks, PyQt, wxPython, Streamlit, and asyncio.

PartTimeLarry: Interactive Brokers API and TradingView Charts in Python


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)

setting_data image


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)

live data gif


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)

tick data gif


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'], f'SMA {period}': val})
   return pd.DataFrame(result)


if __name__ == '__main__':
   chart = Chart()
   chart.legend(visible=True)
   
   df = pd.read_csv('ohlcv.csv')
   chart.set(df)

   line = chart.create_line()
   sma_data = calculate_sma(df, period=50)
   line.set(sma_data, name='SMA 50')

   chart.show(block=True)

line indicators image


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)

styling image


6. Callbacks:

import asyncio
import pandas as pd

from lightweight_charts import Chart


def get_bar_data(symbol, timeframe):
    if symbol not in ('AAPL', 'GOOGL', 'TSLA'):
        print(f'No data for "{symbol}"')
        return pd.DataFrame()
    return pd.read_csv(f'bar_data/{symbol}_{timeframe}.csv')


class API:
    def __init__(self):
        self.chart = None  # Changes after each callback.

    async def on_search(self, searched_string):  # Called when the user searches.
        new_data = get_bar_data(searched_string, self.chart.topbar['timeframe'].value)
        if new_data.empty:
            return
        self.chart.topbar['corner'].set(searched_string)
        self.chart.set(new_data)

    async def on_timeframe_selection(self):  # Called when the user changes the timeframe.
        new_data = get_bar_data(self.chart.topbar['corner'].value, self.chart.topbar['timeframe'].value)
        if new_data.empty:
            return
        self.chart.set(new_data)
            
    async def on_horizontal_line_move(self, line_id, price):
        print(f'Horizontal line moved to: {price}')


async def main():
    api = API()

    chart = Chart(api=api, topbar=True, searchbox=True, toolbox=True)
    chart.legend(True)

    chart.topbar.textbox('corner', 'TSLA')
    chart.topbar.switcher('timeframe', api.on_timeframe_selection, '1min', '5min', '30min', default='5min')

    df = get_bar_data('TSLA', '5min')
    chart.set(df)
    
    chart.horizontal_line(200, interactive=True)

    await chart.show_async(block=True)


if __name__ == '__main__':
    asyncio.run(main())

callbacks gif


Documentation

Inquiries: shaders_worker_0e@icloud.com


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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