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src=\"https://raw.githubusercontent.com/pepkit/pipestat/master/docs/img/pipestat_logo.svg?sanitize=true\" alt=\"pipestat\" height=\"70\"/\u003e\u003cbr\u003e\n\nPipestat is a Python package for managing pipeline results. It provides a standard API for reporting, storing, and retrieving outputs from any computational pipeline. Results are validated against a JSON Schema and stored in either a YAML file or a PostgreSQL database. A pipeline author defines outputs in a schema, then uses pipestat to report results as the pipeline runs. Downstream tools retrieve those results through the same API.\n\nSee [Pipestat documentation](https://pep.databio.org/pipestat/) for complete details.\n\n## Quick Start\n\n```python\nimport pipestat\n\npsm = pipestat.PipestatManager(\n    schema_path=\"output_schema.yaml\",\n    results_file_path=\"results.yaml\",\n    record_identifier=\"sample1\",\n)\npsm.report(values={\"accuracy\": 0.95, \"processing_time\": 12.3})\npsm.report(values={\"output_file\": {\"path\": \"results/output.csv\", \"title\": \"Output CSV\"}})\n```\n\n## Schema\n\nPipestat requires a schema that defines the results your pipeline reports. Here is a minimal example:\n\n```yaml\npipeline_name: my_pipeline\nsamples:\n  accuracy:\n    type: number\n    description: \"Model accuracy score\"\n  processing_time:\n    type: number\n    description: \"Processing time in seconds\"\n  output_file:\n    type: object\n    object_type: file\n    properties:\n      path: {type: string}\n      title: {type: string}\n    required: [\"path\", \"title\"]\n```\n\nEvery result needs `type` and `description`. See `sample_output_schema_generic.yaml` in this repo for a fuller example with both sample and project result types.\n\n### Generating a schema from existing results\n\nIf you already have a pipestat results file, you can auto-generate a schema:\n\n```bash\npipestat infer-schema -f results.yaml -o schema.yaml\n```\n\nThis inspects your results and produces a schema with the correct types. See `pipestat infer-schema --help` for options.\n\n## Developer tests\n\n###  Optional Dependencies\n\nNote: to run the pytest suite locally, you will need to install the related requirements:\n\n```bash\ncd pipestat\n\npip install -r requirements/requirements-test.txt\n\n```\n\n### Database Backend Configuration for Tests\n\nMany of the tests require a postgres database to be set up otherwise many of the tests will skip.\n\nWe recommend using docker:\n```bash\ndocker run --rm -it --name pipestat_test_db \\\n    -e POSTGRES_USER=postgres \\\n    -e POSTGRES_PASSWORD=pipestat-password \\\n    -e POSTGRES_DB=pipestat-test \\\n    -p 5432:5432 \\\n    postgres\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpepkit%2Fpipestat","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fpepkit%2Fpipestat","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpepkit%2Fpipestat/lists"}