ta VS pandas-ta

If you know python, you’ll be able to see for yourself. Bukosabino took the time to make dozens of indicators easy to calculate from historical data. Try and find any predictive power from any of these on any remotely liquid ticker

Use the technical analysis python library to compute the technical indicators for that SPX data

The documentation can be found here: https://technical-analysis-library-in-python.readthedocs.io/en/latest/

I also use python binance but with bubosabino‘s ta library: https://github.com/bukosabino/ta

There's a Python Technical Analysis module located here: https://github.com/bukosabino/ta

If you are using python, check out https://github.com/bukosabino/ta

I'd recommend you to use TA. I used it to generate lany indicators in the past months. No issues to mention, and it's documentation is rich and kept updated. Repo: https://github.com/bukosabino/ta

I use https://technical-analysis-library-in-python.readthedocs.io/en/latest/ for my proprietary bot.

Python with a library that gives you tons of indicators to test (personally, I use this one: https://github.com/bukosabino/ta). Pandas is used but just to set the data, nothing fancy. I don't use Jupyter, I go with the simple IDLE that comes with Python installation but this point doesn't really matter, just go with the most comfortable for you. In the end, this is what I get after a backtest: https://i.ibb.co/pjbZvhv/backtest-sample.png

I'm using this one - https://github.com/bukosabino/ta

I do not know what is the difference between MACD and MACDFIX but maybe you can take a look how MACD is implemented in pandas_ta library and modify it a bit to achive a behavior you want.

I use https://github.com/twopirllc/pandas-ta found some indicators that are in the pandas_ta but not in the tulip library though tulip also has thing pandas doesn't have.

Having a look at ta.rsi it looks like it is calculating the value for rsi and returns it.

I feel like this is more of a devops issue but its all local, the `local_cron_job` runs at 11pm each night to update `mcvaluations` which then activates 'PandasTA_Strategy_Examples.ipynb' then `VectorBT_Backtest_with_Pandas_TA.ipynb' then 'backorder.py` and finally `strategy`

Pandas T.A: Biblioteca Pandas para análise técnica.