search

freyastreamlit / streamlit-lightweight-charts-ntf

5 stars 4 forks source link

readme

streamlit-lightweight-charts-ntf

This streamlit component wraps lightweight-charts using the ntf fork. This fork augments the lightweight-charts with an effective and aligned multipane experience.

The ntf fork is frozen on an old version (v3.8.0), there are no further developments, and no further updates - it is an AS IT IS scenario. Although it seems very stable and very useful for financial and trading Data Science. It has an extra option pane that:

Documentation

A nice example from DeKay on how to use:

How to install:

python -m pip install streamlit-lightweight-charts-ntf

How to use:

from streamlit_lightweight_charts_ntf import renderLightweightCharts

renderLightweightCharts(charts: <List of Dicts> , key: <str>)

API

The extra option: pane

In the example below you will notice the option pane that is used to group charts

It return values from an onClick() event


Multi Pane Chart with Pandas

import streamlit as st
from streamlit_lightweight_charts_ntf import renderLightweightCharts

import json
import numpy as np
import yfinance as yf
import pandas as pd
import pandas_ta as ta

COLOR_BULL = 'rgba(38,166,154,0.9)' # #26a69a
COLOR_BEAR = 'rgba(239,83,80,0.9)'  # #ef5350

def dataToJSON(df, column, slice=0, color=None):
    data = df[['time', column, 'color']].copy()
    data = data.rename(columns={column: "value"})
    if(color == None):
        data.drop('color', axis=1)
    elif(color != 'default'):
        data['color'] = color
    if(slice > 0):
        data = data.iloc[slice:,:]
    return json.loads(data.to_json(orient = "records"))

# Request historic pricing data via finance.yahoo.com API
df = yf.Ticker('AAPL').history(period='9mo')[['Open', 'High', 'Low', 'Close', 'Volume']]

# Some data wrangling to match required format
df = df.reset_index()
df.columns = ['time','open','high','low','close','volume']                  # rename columns
df['time'] = df['time'].dt.strftime('%Y-%m-%d')                             # Date to string

# indicators
df.ta.macd(close='close', fast=6, slow=12, signal=5, append=True)           # calculate macd
df.ta.ema(close='close', length=14, offset=None, append=True)               # EMA fast
df.ta.sma(close='close', length=60, offset=None, append=True)               # SMA slow
df.ta.rsi(close='close', length=14, offset=None, append=True)               # RSI - momentum oscillator
df['VOL_BID'] = -df['volume'].sample(frac=1).values                         # shuffle and negate volume values

# export to JSON format
df['color'] = np.where(  df['open'] > df['close'], COLOR_BEAR, COLOR_BULL)  # bull or bear
candles = json.loads(df.to_json(orient = "records"))
sma_slow = dataToJSON(df,"SMA_60", 60, 'blue')
ema_fast = dataToJSON(df, "EMA_14", 14, 'orange')
vol_ASK = dataToJSON(df,'volume', 0, COLOR_BULL)
vol_BID = dataToJSON(df,'VOL_BID', 0, COLOR_BEAR)
rsi = dataToJSON(df,'RSI_14', 14, 'purple')
macd_fast = dataToJSON(df, "MACDh_6_12_5", 0, 'orange')
macd_slow = dataToJSON(df, "MACDs_6_12_5", 0, 'blue')
df['color'] = np.where(  df['MACD_6_12_5'] > 0, COLOR_BULL, COLOR_BEAR)     # MACD histogram color
macd_hist = dataToJSON(df, "MACD_6_12_5")

chartMultipaneOptions = [
    {
        "width": 600,
        "height": 600,
        "layout": {
            "background": {
                "type": "solid",
                "color": 'white'
            },
            "textColor": "black"
        },
        "grid": {
            "vertLines": {
                "color": "rgba(197, 203, 206, 0.5)"
                },
            "horzLines": {
                "color": "rgba(197, 203, 206, 0.5)"
            }
        },
        "priceScale": {
            "borderColor": "rgba(197, 203, 206, 0.8)"
        },
        "timeScale": {
            "borderColor": "rgba(197, 203, 206, 0.8)",
            "barSpacing": 10,
            "minBarSpacing": 8
        }
    }
]

seriesMultipaneChart = [
    {
        "type": 'Candlestick',
        "title": 'Main chart',
        "data": candles,
        "options": {
            "upColor": COLOR_BULL,
            "downColor": COLOR_BEAR,
            "borderVisible": False,
            "wickUpColor": COLOR_BULL,
            "wickDownColor": COLOR_BEAR,
            "pane": 0
        }
    },
    {
        "type": 'Line',
        "title": 'SMA slow',
        "data": sma_slow,
        "options": {
            "color": 'blue',
            "lineWidth": 2,
            "pane": 0
        }
    },
    {
        "type": 'Line',
        "title": 'EMA fast',
        "data": ema_fast,
        "options": {
            "color": 'green',
            "lineWidth": 2,
            "pane": 0
        }
    },
    {
        "type": 'Histogram',
        "title": 'volume ASK',
        "data": vol_ASK,
        "options": {
            "priceFormat": {
                "type": 'volume',
            },
            "pane": 1

        }
    },
    {
        "type": 'Histogram',
        "title": 'volume BID',
        "data": vol_BID,
        "options": {
            "priceFormat": {
                "type": 'volume',
            },
            "pane": 1

        }
    },
    {
        "type": 'Line',
        "title": 'RSI',
        "data": rsi,
        "options": {
            "lineWidth": 2,
            "pane": 2
        }
    },
    {
        "type": 'Line',
        "title": 'MACD fast',
        "data": macd_fast,
        "options": {
            "lineWidth": 2,
            "pane": 3
        }
    },
    {
        "type": 'Line',
        "title": 'MACD slow',
        "data": macd_slow,
        "options": {
            "lineWidth": 2,
            "pane": 3
        }
    },
    {
        "type": 'Histogram',
        "title": 'MACD histogram',
        "data": macd_hist,
        "options": {
            "lineWidth": 1,
            "pane": 3
        }
    }
]

st.subheader("Multipane Chart with Pandas")

click_events = renderLightweightCharts([
    {
        "chart": chartMultipaneOptions[0],
        "series": seriesMultipaneChart
    }
], 'multipane')

print('onClick event', click_events)