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a model lifecycle tracker

Project description

model-tracker

A simple data store keeping track of models and things

Running locally

  • 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

Database dict

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

Project details


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