valohai-yaml
Valohai.yaml validation and parsing
Decision gist · record as of 2026-08-14
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.AI-flagged interpretation of the facts on this page — verify before relying
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 · maintenance · safety
MIT (permissive) — MIT license permits free use, modification, and distribution with minimal restrictions—suitable for both commercial and open-source projects.
last release 2026-08-13 (1 days) · last repo commit 2026-08-13 · 6 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 137,192 downloads/mo, #11,375 on PyPI
Alternatives
Verify before relying
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)- Whether the package handles all Valohai YAML schema versions or only current versions
- Performance characteristics when parsing large or complex pipeline definitions
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 on it.
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
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 packagesjsonschemalevalpyyaml |
| 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 |
| Classifiers | 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 |
Evidence: valohai_yaml-0.58.0-py3-none-any.whl
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See also valohai-papi · valohai-utils · annotatedyaml · azureml-pipeline-core · yamale · azureml-pipeline · azureml-pipeline-steps · zenml · kfp-pipeline-spec · clearml