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awesome-python

A curated list of awesome Python frameworks, libraries, software and resources

blueshift-demo-strategies

darts

A python library for easy manipulation and forecasting of time series.

data-science-from-scratch

code for Data Science From Scratch book

first_app

handson-ml2

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

hello-world

This is first repository

hostifi-mvp

investpy

Financial Data Extraction from Investing.com with Python

machine-learning-for-algorithmic-trading-second-edition

Code and resources for Machine Learning for Algorithmic Trading, 2nd edition.

manufacturingontologies

A reference solution for leveraging manufacturing ontologies.

mvp

MVP.css — Minimalist stylesheet for HTML elements

nsepython

The Unofficial Python Wrapper for NSEIndia API

optopsy

A nimble options backtesting library for Python

pykiteconnect

The official Python client library for the Kite Connect trading APIs

pyrtfolio

Python package to generate stock portfolios

pysystemtrade

Systematic Trading in python

quant-trading

Python quantitative trading strategies including VIX Calculator, Pattern Recognition, Commodity Trading Advisor, Monte Carlo, Options Straddle, London Breakout, Heikin-Ashi, Pair Trading, RSI, Bollinger Bands, Parabolic SAR, Dual Thrust, Awesome, MACD

research-stock-prediction

straighthigh

Find and Learn Code Control

ta

Technical Analysis Library using Pandas and Numpy

trendet

:chart_with_upwards_trend: Python package for trend detection on stock time series data :chart_with_downwards_trend:

web-scraping

Python detailed web scraping tutorials for dummies with financial data crawlers on CME (both futures and options), US Treasury, CFTC, LME, SHFE and news data crawlers on BBC, Wall Street Journal, Al Jazeera, Reuters, Financial Times, Bloomberg, CNN, Fortune, The Economist

zerodhapythonscripts

All scripts are in python language to trade in zerodha using algorithms.