valohai-utils

library0.7.0pypypi✓ verified 86d ago

Utilities for building and running machine learning pipelines on the Valohai platform. Version 0.7.0, stable but occasional updates for Valohai API changes.

ai-ml data devops

pip install valohai-utils

package ↗homepage ↗

INSTALL

IMPORT

SIG · VALOHAI-UTILS

valohai-utils

ai-mlpythonv0.7.0

Install

3.2s avg

Import

1094ms

Disk

27MB

Pass rate

10/ 10

Env Coverage10 / 10

glibc

3.9–3.13

musl

3.9–3.13

Install & Compatibility

Where this runs

tested against v0.7.0 · 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 3.10–3.95 runs

installs and imports cleanly · install 0.0s · import 1.138s · 28.2MB

glibc

py 3.10–3.95 runs

installs and imports cleanly · install 3.2s · import 1.050s · 29MB

27MB installed

● package 27MB

Code

Verified usage

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

valohai

✓ import valohai

✗ import valohai_utils

valohai-utils is the PyPI package, but importable as valohai

task_context

✓ from valohai import task_context

✗ from valohai.utils import task_context

Renamed in older versions; always use valohai.task_context

Inputs

✓ from valohai.internals.inputs import Inputs

✗ from valohai import Inputs

Inputs helper is in internals submodule, not direct import

Minimal Valohai pipeline step using task_context for input/output management.

import valohai from valohai import task_context if __name__ == '__main__': with task_context() as ctx: # Access input files for file_path in ctx.inputs['dataset']: print(f"Processing {file_path}") # Write outputs for output_name in ctx.outputs: ctx.write_output(output_name, data=[], output_path='/some/path')

valohai --version

Debug

Known issues

breakingIn v0.5+, task_context no longer auto-uploads outputs; you must explicitly call ctx.upload_outputs() or use write_output which auto-uploads.

fix

After writing outputs, call ctx.upload_outputs() or use ctx.write_output() which handles upload.

affects: >=0.5.0

gotchaInputs are accessed via comma-separated values in the pipeline YAML. If you define an input as 'dataset', you must use ctx.inputs['dataset'] — case-sensitive and matches exactly the YAML key.

fix

Use ctx.inputs['input_name'] exactly as defined in valohai.yaml under inputs:.

affects: all

gotchaThe local execution mode does not validate Valohai API tokens; scripts that work locally may fail on Valohai due to missing environment variables.

fix

Always test on Valohai or use valohai-utils in an environment with VALOHAI_TOKEN set.

affects: all

deprecatedvalohai.prepare_execution() is deprecated. Use valohai.initialize() or task_context instead.

fix

Replace valohai.prepare_execution() with valohai.initialize() and use task_context.

affects: <=0.4

Errors

Common errors & fixes

ModuleNotFoundError: No module named 'valohai'

The import is 'valohai' not 'valohai_utils'. The package is installed as valohai-utils but import uses valohai.

fix

Install valohai-utils (pip install valohai-utils) then use 'import valohai'.

KeyError: 'dataset' when accessing ctx.inputs['dataset']

The input name in code does not match the key defined in valohai.yaml inputs section.

fix

Ensure the input key in valohai.yaml matches exactly: e.g., inputs: [name: dataset] then code uses ctx.inputs['dataset'].

Upgrade

Version history

0.7.0latest on PyPI · released Mar 21, 2025

Audit

Dependencies

valohairequiredCore client library for Valohai API interactions

clickoptionalCommand-line interface framework

Agent activity

26 hits · last 30 days

node

OpenAI (training)

Resources

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

homepagehttps://valohai.com ↗