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valohai-yaml

Valohai.yaml validation and parsing

valohai-yaml v0.58.0 137.2K downloads/30d#11,375 on PyPI6
Permissive license MIT Active released

What it is and what it does

valohai-yaml is a parser and validator for valohai.yaml files, the configuration format used to define machine learning workloads and pipelines in the Valohai ecosystem. It provides both programmatic and command-line interfaces to validate YAML structure and parse it into Python objects that expose pipeline steps, parameters, and other configuration details.

The package depends on jsonschema, leval, and pyyaml to perform schema validation and YAML parsing. It is actively maintained, supports Python 3.9 through 3.13, and carries no known security vulnerabilities. Use it when you need to validate or programmatically inspect valohai.yaml files as part of a Valohai-integrated ML workflow.

Use it for:

  • Validate valohai.yaml files in CI/CD pipelines before submitting workloads to Valohai
  • Programmatically inspect pipeline steps and commands from valohai.yaml in custom tooling
  • Parse and extract configuration metadata from ML project definitions for automation or reporting
  • Integrate valohai.yaml validation into local development workflows via the command-line tool

Worth the install?

AI-flagged interpretation of the facts on this page — verify before relying

Parses and validates valohai.yaml configuration files used to define machine learning workloads and pipelines on the Valohai platform.

Yes. If you use Valohai for ML workload orchestration, this package is essential for validating and parsing your configuration files. Low install friction, active maintenance, MIT license, no known vulnerabilities, and a straightforward API make it a reliable choice for both CI/CD integration and programmatic configuration inspection.

Install

valohai-yaml on PyPI

pip

pip install valohai-yaml

uv

uv add valohai-yaml

poetry

poetry add valohai-yaml

Installing valohai-yaml

Before you install

Low install friction with three lightweight runtime dependencies (jsonschema, leval, pyyaml). Active maintenance with a release 1 day old and commits current as of 2026-08-13.

License in practice

MIT license permits free use, modification, and distribution with minimal restrictions—suitable for both commercial and open-source projects.

Quickstart

pip install valohai-yaml

from valohai_yaml import validate, parse

with open('valohai.yaml') as f:
    validate(f)

with open('valohai.yaml') as f:
    config = parse(f)
    print(config.steps['step_name'].command)

Verify before relying

  • Whether the package handles all Valohai YAML schema versions or only current versions
  • Performance characteristics when parsing large or complex pipeline definitions

Package facts

License MIT (permissive)
Python support supports the current Python release (>=3.9)
Install friction low — pure-Python wheel
Runtime dependencies 3 — jsonschema, leval, pyyaml
Maintenance actively maintained — 1 days since the last release
Last repo commit
First released
Downloads 137,192/month — #11,375 on PyPI (30-day window, as of 2026-08-14)
Known vulnerabilities none known (OSV.dev, checked 2026-08-14)

Evidence: valohai_yaml-0.58.0-py3-none-any.whl

Keywords: strings, utility

Development Status :: 5 - Production/StableLicense :: OSI Approved :: MIT LicenseNatural Language :: EnglishProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.9Topic :: Software Development :: Libraries

Tags

valohai yaml validationml pipeline configuration parservalohai config parsingyaml validation for ml workflowsvalohai workload definition
ml-workflowyaml-validationvalohai-ecosystem

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