{"id":27757364,"url":"https://github.com/DanielAvdar/ml-orchestrator","last_synced_at":"2025-04-29T09:01:40.853Z","repository":{"id":226807959,"uuid":"759359328","full_name":"DanielAvdar/ml-orchestrator","owner":"DanielAvdar","description":"Software engineering approach for building kubeflow components","archived":false,"fork":false,"pushed_at":"2025-04-21T05:30:38.000Z","size":5900,"stargazers_count":3,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-04-22T16:55:50.889Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/DanielAvdar.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2024-02-18T11:28:32.000Z","updated_at":"2025-04-21T05:30:35.000Z","dependencies_parsed_at":"2024-03-23T07:35:19.171Z","dependency_job_id":"eaa0e4ed-d43a-417d-8462-6dd377e009b4","html_url":"https://github.com/DanielAvdar/ml-orchestrator","commit_stats":{"total_commits":105,"total_committers":2,"mean_commits":52.5,"dds":"0.24761904761904763","last_synced_commit":"39d822466ce16f39cc3818d95f4db5af7837d99e"},"previous_names":["danielavdar/ml-orchestrator"],"tags_count":19,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/DanielAvdar%2Fml-orchestrator","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/DanielAvdar%2Fml-orchestrator/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/DanielAvdar%2Fml-orchestrator/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/DanielAvdar%2Fml-orchestrator/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/DanielAvdar","download_url":"https://codeload.github.com/DanielAvdar/ml-orchestrator/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":251470301,"owners_count":21594525,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2025-04-29T09:01:19.017Z","updated_at":"2025-04-29T09:01:40.761Z","avatar_url":"https://github.com/DanielAvdar.png","language":"Python","funding_links":[],"categories":["Projects by main language"],"sub_categories":["python"],"readme":"# Defining Kubeflow Pipeline (KFP) Components with Python Dataclasses\n\n[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/ml-orchestrator)](https://pypi.org/project/ml-orchestrator/)\n[![version](https://img.shields.io/pypi/v/ml-orchestrator)](https://img.shields.io/pypi/v/ml-orchestrator)\n[![License](https://img.shields.io/:license-MIT-blue.svg)](https://opensource.org/licenses/MIT)\n![OS](https://img.shields.io/badge/ubuntu-blue?logo=ubuntu)\n![OS](https://img.shields.io/badge/win-blue?logo=windows)\n![OS](https://img.shields.io/badge/mac-blue?logo=apple)\n[![Tests](https://github.com/DanielAvdar/ml-orchestrator/actions/workflows/ci.yml/badge.svg)](https://github.com/DanielAvdar/ml-orchestrator/actions/workflows/ci.yml)\n[![Code Checks](https://github.com/DanielAvdar/ml-orchestrator/actions/workflows/code-checks.yml/badge.svg)](https://github.com/DanielAvdar/ml-orchestrator/actions/workflows/code-checks.yml)\n[![codecov](https://codecov.io/gh/DanielAvdar/ml-orchestrator/graph/badge.svg?token=N0V9KANTG2)](https://codecov.io/gh/DanielAvdar/ml-orchestrator)\n[![Ruff](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/ruff/main/assets/badge/v2.json)](https://github.com/astral-sh/ruff)\n![Last Commit](https://img.shields.io/github/last-commit/DanielAvdar/ml-orchestrator/main)\n## Features\n\n* **Dataclass-Driven Component Definition:** Define component logic using Python dataclasses, seamlessly translating\n  them into Kubeflow Pipelines (KFP) compatible functions and components.\n* **KFP Agnostic:** Empower developers to design and implement component logic as standard Python code, independent of\n  the KFP framework.\n\n## Installation\n\n```bash\npip install ml-orchestrator\n```\n\nNote: `ml-orchestrator` is designed to be lightweight and free of external dependencies, ensuring efficient runtime\nperformance without additional overhead.\n\nNote: `ml-orchestrator` does not require the `kfp` package to parse or create Kubeflow components.\n\nNote: To construct `kfp` pipelines and utilize the components, the `kfp` package is required.\n\n## Usage\n\nplease read the [documentation](https://ml-orchestrator.readthedocs.io/en/latest/)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FDanielAvdar%2Fml-orchestrator","html_url":"https://awesome.ecosyste.ms/projects/github.com%2FDanielAvdar%2Fml-orchestrator","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FDanielAvdar%2Fml-orchestrator/lists"}