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vptrade

MIT License

vptrade is a technical indicators trading tools can be used to all instruments.

Requirements

  • Python 3.9 or higher

Features

  • Trends Indicator
  • Oscillators Indicator

Installation

Instal this package with pip

  pip install vptrade

Usage/Examples

Moving Average

from vptrade.indicators.trends import Trend
import pandas as pd


data = pd.read_csv(r'YOUR PATH\TSLA.csv',
                   index_col='Date',
                   parse_dates=True)
trend = Trend(data)

#simple moving average
sma = trend.sma(period=30, volume="Close", show=True, save="sma_img.png")

#exponential moving average
ema = trend.ema(period=30, volume="Close", show=True, save="ema_img.png")

#cummulative moving average show only without save
cma = trend.cma(period=30, volume="Close", show=True)

#smoothed moving average without save and show
smma = trend.smma(period=30, volume="Close", show=False)

#lienar-weighted moving average without show and save
lwma = trend.lwma(period=30, volume="Close")

Bollinger band

from vptrade.indicators.trends import Trend
import pandas as pd

data = pd.read_csv(r'YOUR PATH\TSLA.csv',
                   index_col='Date',
                   parse_dates=True)
trend = Trend(data)
bollinger = trend.bollinger_bands(period=30, volume="Close", show=True, save="bolinger_band.png")

Support

For support, Join my discord https://discord.gg/HZJZAVAZdr

Contributing

Contributions are always welcome!

See contributing.md for ways to get started.

Please adhere to this project's code of conduct.

Release files for vptrade 0.0.2

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for vptrade 0.0.2
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Table of built distributions (wheels) for vptrade 0.0.2
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vptrade-0.0.2-py3-none-any.whl Python 3 none any Details

Total release size: 15.5 kB

Release files / vptrade-0.0.2.tar.gz

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Release files / vptrade-0.0.2-py3-none-any.whl

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