ta-lib-python
finta
ta-lib-python | finta | |
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23 | 5 | |
9,009 | 1,728 | |
1.2% | - | |
7.3 | 2.7 | |
about 2 months ago | almost 2 years ago | |
Cython | Python | |
GNU General Public License v3.0 or later | GNU Lesser General Public License v3.0 only |
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ta-lib-python
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Why is my RSI coming up incorrect?
One such excellent Python library is TA-Lib. (https://github.com/TA-Lib/ta-lib-python)
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Technical Analysis libraries
Have you looked TA-Lib?
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Crypto Data Bot using Python, Binance WebSockets and PostgreSQL DB
TA-Lib
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Why Economists should embrace Data Science
Dev here. I've wanted to get into doing this for as long as I can remember. Back in 2018 I got a half start at it, pulling in Binance candle data for all intervals with python and then running them all through every TA function of ta-lib to generate corresponding indicators. I intended to take it that next step further into picking up ML, and wanted to write a script that would pair every permutation of indicator looking for combinations that improve certainty for price direction changes (the certainty of BOLL + RSI was going to be used as my baseline for a known semi-reliable combo). I would really love to circle back someday to finishing that up, and then start sucking in candle data from as many markets as I could afford the AWS services for lol. That's my dream dashboard.
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How are these guys doing automated trend analysis like finding falling wedges, bullish pennants or bull flag?
Not sure what they are using specifically, but ta-lib has candle pattern matching.
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Relative Strength in Python; am I coding it right?
Just use TA-Lib https://mrjbq7.github.io/ta-lib/
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looking for a python lib
Doesn't seem like an official mirror but if you're curious what the code looks like, including the python/C bindings, here it is: https://github.com/mrjbq7/ta-lib
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Calculating EMA200 from Binance API?
I use talib https://mrjbq7.github.io/ta-lib/ and it accurately mirrors binance
- Baby python advice
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How to install TA-lib in a linux machine w/o root?
This from a closed issue.
finta
- looking for a python lib
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How It's Made! // Building A Crypto Trading Bot Network - A Tutorial (Part 1) // Whew, this was a tough one guys. It took 10x longer to put this together than I imagined. This is an in-depth review of my Bots and their parent system. Please let me know what you think and if I should continue.
Have you thought about using the FinTA package for trading signals and also ratelimit to help with some of those weird things that can pop up with dealing with external APIs
- Yesterday I came across Awesome-Quant repository and it was great. I went ahead and dig through all the backtesting & AI repos from Python and created a list of repo which are most updated & maintained. Let me know if I missed your favorite.
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Important python libraries?
I'm also going to shamelessly plug fast-trade, which is a backtesting library where you write strategies as objects instead of actual code. It's also built on a couple of pretty wonderful libraries including pandas and FinTa, which has a lot of indicators and it's really simple to use.
- Why use ta_lib when you can use FinTA?
What are some alternatives?
pandas-ta - Technical Analysis Indicators - Pandas TA is an easy to use Python 3 Pandas Extension with 150+ Indicators
ta - Technical Analysis Library using Pandas and Numpy
quantstats - Portfolio analytics for quants, written in Python
Apache Arrow - Apache Arrow is a multi-language toolbox for accelerated data interchange and in-memory processing
fast-trade - low code backtesting library utilizing pandas and technical analysis indicators
tf-quant-finance - High-performance TensorFlow library for quantitative finance.
trading-ig - A lightweight Python wrapper for the IG Markets API
trading-utils - Collection of scripts and utilities for stock market analysis, strategies etc
Lean - Lean Algorithmic Trading Engine by QuantConnect (Python, C#)
Alpaca-API - The Alpaca API is a developer interface for trading operations and market data reception through the Alpaca platform.
documentation - This repository contains the documentation for the current Quantiacs project. Check it out at: https://quantiacs.com/documentation/en/