Understanding conda channels

 Conda channels are package source - locations where conda looks for software packages when you run conda install. Each channel can contain different package versions, build configurations, platform-specific binaries, etc ...

In the screenshot above, you will notice 4 different conda channels:

• defaults: the official Anaconda repository, has stable, curated with conservative updates
• microsoft: Microsoft maintains its own channel mainly for AzureML environment support or packages tuned for Windows performance.
• anaconda: similar to the defaults channel
• conda-forge: community driven, massive ecosystem with the latest versions. Receives updates within hours of upstream releases

You can add a channel using this command: conda config --add channels microsoft. Conda searches channels in order, from highest priority to lowest. So from my configuration, it first try to install from defaults. If not found, it falls back to microsoft, and so on ...

Quick tip: updating Anaconda with command prompt

 I recently started getting a popup for updating Anaconda Navigator on my Windows machine and I also received a warning when installing packages using the Anaconda prompt. I first started the update through the user interface but this update completely stalled and I had to do a hard reboot after almost 2 hours (when my patience ran out). Running the update using Anaconda prompt worked without problems - next time I will use this method first. If conda is installed on your machine, you can update it to the most recent version and patches using  conda update -n base -c defaults conda

Using the yFinance Python package to download financial data from Yahoo Finance

In a previous post I explained how you can retrieve data from Yahoo Finance using Python and Pandas Datareader - an alternative Python library for retrieving data from Yahoo Finance is yFinance maintained by Ran Aroussi. 

If you are using conda package manager, you will notice that you can not install yfinance using conda so you will need to revert to pip install yfinance. All documentation is available on yFinance  as well as on https://github.com/ranaroussi/yfinance but I also uploaded a  Jupyter notebook code sample on my Github - https://github.com/jorisp/tradingnotebooks/blob/master/yfinance_sample.ipynb