mozmlops 0.1.3

A package for getting your models into production

mozmlops

A package for getting your models into production!

For the Model Orchestration/Experiment Evaluation Flow Template

You'll find a README in the src/mozmlops/templates directory!

Installation for use

You can install the library with pip install mozmlops.

Installation for local testing and contributing

Steps:

1. Clone this repository
2. cd into the repository
3. Start up a virtual environment:

python -m venv env
source env/bin/activate

3. python -m pip install poetry
4. poetry install

Running tests

Linting:

Run ruff check to find style issues and ruff check --fix to fix many automatically.

Unit tests:

Run pytest from the top-level directory.

Integration tests:

You need to be logged into GCP to run the integration tests; you can use the gcloud CLI command gcloud auth login.

Run the integration tests with pytest -m integration.

Usage

An example import line (in fact, the only one currently implemented) would be:

from mozmlops.storage_client import CloudStorageAPIClient

at the top of your favorite Python file, or in a python console.

From there, you can try running this line:

store = CloudStorageAPIClient('some-project-name', 'some-bucket-name')

To make sure the import worked.

Contributing

Interested in contributing? Check out the contributing guidelines. Please note that this project is released with a Code of Conduct. By contributing to this project, you agree to abide by its terms.

License

mozmlops was created by Mozilla MLOps. It is licensed under the terms of the Mozilla Public License.

Credits

mozmlops was created with cookiecutter and the py-pkgs-cookiecutter template.