Skip to main content

CLI tool for managing ML projects on Vertex AI

Project description

WANNA-ML


Complete MLOps framework for Vertex-AI


Build Release Coverage Package version

About WANNA-ML

WANNA-ML is a CLI tool that helps researchers, data scientists, and ML Engineers quickly adapt to Google Cloud Platform (GCP) and get started on the cloud in almost no time.

It makes it easy to start a Jupyter notebook, run training jobs and pipelines, build a Docker container, export logs to Tensorboards, and much more.

We build on top of Vertex-AI managed services and integrate with other GCP services like Cloud Build and Artifact Registry to provide you with a standardized structure for managing ML assets on GCP.

Help

See the documentation for more details.

Get started

Installation

Install using pip install -U wanna-ml.

For more information on the installation process and requirements, visit out installation page in documentation

Authentication

WANNA-ML relies on gcloud for user authentication.

  1. Install the gcloud CLI - follow official guide
  2. Authenticate with the gcloud init
  3. Set you Google Application Credentials gcloud auth application-default login

Docker Build

You can use a local Docker daemon to build Docker images, but it is not required. You are free to choose between local building on GCP Cloud Build. If you prefer local Docker image building, install Docker Desktop.

GCP IAM Roles and Permissions

Different WANNA-ML calls require different GCP permissions to create given resources on GCP. Our documentation page lists recommended GCP IAM roles for each wanna command.

Examples

Jump to the samples to see a complete solution for various use cases.

Issues

Please report issues to GitHub.

Contributing

Your contributions are always welcome, see CONTRIBUTING.md for more information. If you like WANNA-ML, don't forget to give our project a star!

Licence

Distributed under the MIT License - see LICENSE.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

wanna_ml-0.3.0.tar.gz (67.6 kB view details)

Uploaded Source

Built Distribution

wanna_ml-0.3.0-py3-none-any.whl (99.2 kB view details)

Uploaded Python 3

File details

Details for the file wanna_ml-0.3.0.tar.gz.

File metadata

  • Download URL: wanna_ml-0.3.0.tar.gz
  • Upload date:
  • Size: 67.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.8.2 CPython/3.8.18 Linux/6.5.0-1015-azure

File hashes

Hashes for wanna_ml-0.3.0.tar.gz
Algorithm Hash digest
SHA256 336cc182bc10b2a82ce364073586f10e5f12c0b577c87dcfee9f20eca0331b1a
MD5 fad5fd7d583b05b4ca6dfea68eed3f16
BLAKE2b-256 a9d3c1fe1b3696cc4eaf44174076d38d220df3f2990da4680b1f697f8bdc9bd9

See more details on using hashes here.

File details

Details for the file wanna_ml-0.3.0-py3-none-any.whl.

File metadata

  • Download URL: wanna_ml-0.3.0-py3-none-any.whl
  • Upload date:
  • Size: 99.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.8.2 CPython/3.8.18 Linux/6.5.0-1015-azure

File hashes

Hashes for wanna_ml-0.3.0-py3-none-any.whl
Algorithm Hash digest
SHA256 5102c35cf31ec2b9ffc89f7fa4c65d7eb572f3e0a8bc0b5851fcd9744597398e
MD5 09d83b3835d8f623ced98bed634477eb
BLAKE2b-256 cb9377a77a48234504119f60f2004fc057a8f939eca8b40383a9c80239a8846c

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page