Subfolder for Yield Modelling
After cloning the repo, you will need to set up the virtual enviroment and install dependencies by running the following commands in the CLI in the folder:
- python3 -m venv .venv
- source .venv/bin/activate
- pip install -r requirements.txt
- pip install ../shared_packages/aws_helper_functions/
If run outside of lambda, applicable functions must be called with local_mode=True. Enviroment variables must be set for host
, database
, port
, username
, and password
(eg redshift password) to connect to redshift. If writting results to S3 to update tables, AWS config must be set up w/access key
and secret access key
.
yield_boosting.py
-> entry pointtrain_basetable.sql
-> query to create training data seteval_basetable.sql
-> query to create evaluation data set
requirements.txt
-> packages that are requried to run intra_year_boosting (other thanaws_helper_functions
)