valohai-yaml

library0.57.0pypypi✓ verified 87d ago

valohai-yaml is a Python library for parsing, validating, and programmatically constructing `valohai.yaml` configuration files, which define machine learning pipelines and experiments for the Valohai platform. It ensures YAML configurations adhere to the Valohai schema. The current version is 0.56.0, and it maintains a frequent release cadence, often with minor updates and new feature support aligning with the Valohai platform.

ai-ml devops serialization data

pip install valohai-yaml

github ↗package ↗homepage ↗

INSTALL

IMPORT

SIG · VALOHAI-YAML

valohai-yaml

ai-mlpythonv0.57.0

Install

2.6s avg

Import

435ms

Disk

23MB

Pass rate

10/ 10

Env Coverage10 / 10

glibc

3.9–3.13

musl

3.9–3.13

Install & Compatibility

Where this runs

tested against v0.57.0 · pip install

no network on importno background threads

Install × environment matrix

Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux

musl

py 3.10–3.910 runs

installs and imports cleanly · install 0.0s · import 0.445s · 24.5MB

glibc

py 3.10–3.910 runs

installs and imports cleanly · install 2.6s · import 0.425s · 25MB

23MB installed

● package 23MB

Code

Verified usage

Verified import paths — ran on the pinned version, not inferred.

parse

✓ from valohai_yaml import parse

✗ from valohai_yaml.yaml import parse

Top-level `parse` is re-exported for convenience since v0.56.0. The submodule path still works but is less direct.

lint

✓ from valohai_yaml import lint

✗ from valohai_yaml.lint import lint

Top-level `lint` is re-exported for convenience since v0.56.0. The submodule path still works but is less direct.

build_config

✓ from valohai_yaml import build_config

✗ from valohai_yaml.build import build_config

Top-level `build_config` is re-exported for convenience since v0.56.0. The submodule path still works but is less direct.

This quickstart demonstrates how to parse a `valohai.yaml` string using the `parse` function. It takes a YAML string as input and returns a `Config` object, which provides programmatic access to the defined steps, pipelines, and other Valohai configuration elements. This is the fundamental way to interact with Valohai YAML files in Python.

from valohai_yaml import parse valohai_yaml_content = ''' - step: name: training-step image: python:3.9 command: python train.py inputs: - name: dataset default: s3://my-bucket/data/dataset.csv outputs: - name: model default: model.pkl ''' config = parse(valohai_yaml_content) print(f"Parsed Valohai config with {len(config.steps)} step(s).") print(f"First step name: {config.steps[0].name}") # Example of linting (requires more complex setup usually) # from valohai_yaml import lint # errors = lint(config) # if errors: print(f"Linting errors: {errors}")

Debug

Known issues

breakingSupport for Python 3.8 was dropped in version 0.47.0. Users on Python 3.8 will encounter installation or runtime errors.

fix

Upgrade your Python environment to version 3.9 or newer. `valohai-yaml` >=0.47.0 requires Python >=3.9.

affects: >=0.47.0

breakingIn version 0.47.0, the linter was updated to flag duplicate top-level entity names (e.g., two steps with the same name) as errors instead of warnings. Previously invalid configurations may now fail validation.

fix

Review your `valohai.yaml` files for any duplicate step, pipeline, or endpoint names and ensure all top-level entities have unique identifiers.

affects: >=0.47.0

gotchaVersion 0.56.0 changed serialization behavior to not serialize empty edge configs or default node error actions. If you rely on programmatic serialization to regenerate exact YAML structures, this might result in differences.

fix

If programmatically generating or comparing YAML, be aware that empty configurations or default error actions may no longer be explicitly written to the YAML output. Adjust comparison logic if necessary.

affects: >=0.56.0

gotchaThe `valohai-yaml` library exports various `Items` and `Enums` directly from the top-level package since v0.56.0 for convenience. While importing from submodules (e.g., `valohai_yaml.yaml.parse`) still works, the recommended path is direct import (`from valohai_yaml import parse`).

fix

Update your import statements to use the top-level exports, e.g., `from valohai_yaml import parse` instead of `from valohai_yaml.yaml import parse` for better future compatibility and readability.

affects: >=0.56.0

Errors

Common errors & fixes

ModuleNotFoundError: No module named 'valohai_yaml'

The `valohai-yaml` library is not installed in the current Python environment.

fix

Run `pip install valohai-yaml` to install the package.

valohai_yaml.errors.ValidationError: [YAML is not valid] ...

The provided YAML content does not conform to the Valohai YAML schema, or contains structural errors.

fix

Carefully review the YAML content against the Valohai documentation and the error messages provided by the `ValidationError` to identify and correct the invalid syntax or structure. Use `valohai_yaml.lint` for detailed validation reports.

yaml.parser.ParserError: while parsing a block mapping

The input string contains malformed YAML syntax that even the underlying PyYAML parser cannot process, typically due to incorrect indentation, missing colons, or invalid character sequences.

fix

Correct the YAML syntax. Pay close attention to indentation and standard YAML formatting rules. Tools like online YAML validators can help identify basic syntax errors.

AttributeError: 'NoneType' object has no attribute 'steps'

This usually happens when `valohai_yaml.parse()` fails due to invalid YAML, returns `None` or raises an exception, and subsequent code attempts to access attributes (like `steps`) on the non-existent or unhandled parsed object.

fix

Always wrap `parse()` calls in a `try...except valohai_yaml.errors.ValidationError` block, or check the return value to ensure it's not `None` before attempting to access its attributes. Ensure the YAML input is valid.

Upgrade

Version history

0.57.0latest on PyPI · released Apr 20, 2026

Audit

Dependencies

pythonrequiredRequires Python 3.9 or newer.

Agent activity

30 hits · last 30 days

node

OpenAI (training)

Resources

githubhttps://github.com/valohai/valohai-yaml ↗

packagehttps://pypi.org/project/valohai-yaml/ ↗

homepagehttps://valohai.com ↗