A dockerized jupyter notebooks instance for computing top 50 stocks to buy determined through 2 simple methods. The code runs with miniconda and a few accompanying packages.
The src folder contains a single notebook file along with the python files that it requires to function. The notebook contains two basic methods for determining top 50 favorable stocks to buy among SP 500 index stocks.
You can use build.sh for an opinionated image build that will be tagged with
hqm-finance. For normal use the file start.sh can be used to easily mount
the volumes, set the port, etc. The start script will expect the image to have
the taq hqm-finance.
Code for the repo is contained in the src folder. Any file that is created by
the notebook is set to be saved in the artifacts folder. Raw any raw data that
is used by the notebook can be placed in the data folder.
The notebook works with IEX cloud service for stocks data. The service requires
a key token, which shall be placed in ./src/secrets.py. Without the token, the
repo will not work as expected.