A model lifecycle tracker database backed by postgres
A simple data store keeping track of models and things
- Get postgres up and running for local development
docker pull postgres docker run --rm --name pg-docker -e POSTGRES_PASSWORD=docker -d -p 5432:5432
- Flash database for quick dev
PGPASSWORD='docker' psql -h localhost -U postgres -c "drop database modeltracker" && PGPASSWORD='docker' psql -h localhost -U postgres -c "create database modeltracker"
- Populate the basic type tables
python -m modeltracker.main
- Suppose you have been developing and wish to destroy all table contents:
python -m modeltracker.main -r
To keep track of what is being produced by the modeltracker
datastore_type : Describes the datastore types, BQ or GCS for instance.
feature_store_metrics : Describes the metrics relating to each model in the model_catalog_id
job : Describes tasks that have been run
model_catalog : describes models and links to state_id
model_output : describes location and datastore type of model_output
state : Catalogue of states
task_type : Tracks tasks that occurr
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