Skip to main content

Python framework for TradingView's Lightweight Charts JavaScript library.

Project description

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

Features

  1. Streamlined for live data, with methods for updating directly from tick data.
  2. Multi-pane charts using Subcharts.
  3. The Toolbox, allowing for trendlines, rays and horizontal lines to be drawn directly onto charts.
  4. Events allowing for timeframe selectors (1min, 5min, 30min etc.), searching, hotkeys, and more.
  5. Tables for watchlists, order entry, and trade management.
  6. Direct integration of market data through Polygon.io's market data API.

Supports: Jupyter Notebooks, PyQt5, PySide6, 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 
    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 
    df2 = pd.read_csv('ticks.csv')
    
    chart = Chart()
    
    chart.set(df1)
    
    chart.show()
    
    for i, tick in df2.iterrows():
        chart.update_from_tick(tick)
            
        sleep(0.03)

tick data gif


4. Line Indicators:

import pandas as pd
from lightweight_charts import Chart


def calculate_sma(df, period: int = 50):
    return pd.DataFrame({
        'time': df['date'],
        f'SMA {period}': df['close'].rolling(window=period).mean()
    }).dropna()


if __name__ == '__main__':
    chart = Chart()
    chart.legend(visible=True)

    df = pd.read_csv('ohlcv.csv')
    chart.set(df)

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

    chart.show(block=True)

line indicators image


5. Styling:

import pandas as pd
from lightweight_charts import Chart


if __name__ == '__main__':
    
    chart = Chart()

    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 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')


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


def on_timeframe_selection(chart):  # Called when the user changes the timeframe.
    new_data = get_bar_data(chart.topbar['symbol'].value, chart.topbar['timeframe'].value)
    if new_data.empty:
        return
    chart.set(new_data, True)


def on_horizontal_line_move(chart, line):
    print(f'Horizontal line moved to: {line.price}')


if __name__ == '__main__':
    chart = Chart(toolbox=True)
    chart.legend(True)

    chart.events.search += on_search

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

    df = get_bar_data('TSLA', '5min')
    chart.set(df)

    chart.horizontal_line(200, func=on_horizontal_line_move)

    chart.show(block=True)

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.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

lightweight_charts-1.0.18.7.tar.gz (92.5 kB view details)

Uploaded Source

Built Distribution

lightweight_charts-1.0.18.7-py3-none-any.whl (94.7 kB view details)

Uploaded Python 3

File details

Details for the file lightweight_charts-1.0.18.7.tar.gz.

File metadata

  • Download URL: lightweight_charts-1.0.18.7.tar.gz
  • Upload date:
  • Size: 92.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.5

File hashes

Hashes for lightweight_charts-1.0.18.7.tar.gz
Algorithm Hash digest
SHA256 e941cf48390c89387de94e9793a38fdd370e63660a27b66704c25ff817565db2
MD5 813b358e38835c35c5c27efed0cd0095
BLAKE2b-256 1309c8cf52de9d44118e2b94efdc2126114a48e26282273affcad4e4598ca253

See more details on using hashes here.

File details

Details for the file lightweight_charts-1.0.18.7-py3-none-any.whl.

File metadata

File hashes

Hashes for lightweight_charts-1.0.18.7-py3-none-any.whl
Algorithm Hash digest
SHA256 112258a09b6f4f14be6e756b81e5142bba28b58446dafc9dfc74dd01a9190d49
MD5 7d8d4223655aaa597e0a6cd1d6b27f2e
BLAKE2b-256 5fb4cba04ab6f2c8a3ccb5e5c827104a2baa003e3660453abdc33ce4b950acda

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page