Name | valohai-yaml JSON |
Version |
0.39.0
JSON |
| download |
home_page | |
Summary | Valohai.yaml validation and parsing |
upload_time | 2024-03-13 12:37:03 |
maintainer | |
docs_url | None |
author | |
requires_python | >=3.8 |
license | |
keywords |
strings
utility
|
VCS |
|
bugtrack_url |
|
requirements |
No requirements were recorded.
|
Travis-CI |
No Travis.
|
coveralls test coverage |
|
# valohai-yaml
[![Build Status](https://github.com/valohai/valohai-yaml/actions/workflows/ci.yml/badge.svg)](https://github.com/valohai/valohai-yaml/actions/workflows/ci.yml)
[![Codecov](https://codecov.io/gh/valohai/valohai-yaml/branch/master/graph/badge.svg)](https://codecov.io/gh/valohai/valohai-yaml)
[![License: MIT](https://img.shields.io/badge/License-MIT-green.svg)](https://opensource.org/licenses/MIT)
Parses and validates `valohai.yaml` files.
Valohai YAML files are used to define how your machine learning project workloads and pipelines are ran on the [Valohai](https://valohai.com/) ecosystem. Refer to [Valohai Documentation](https://docs.valohai.com/) to learn how to write the actual YAML files and for more in-depth usage examples.
## Installation
```bash
pip install valohai-yaml
```
## Usage
### Validation
Programmatic usage:
```python
from valohai_yaml import validate, ValidationErrors
try:
with open('path/to/valohai.yaml') as f:
validate(f)
except ValidationErrors as errors:
print('oh no!')
for err in errors:
print(err)
```
Command-line usage:
```bash
valohai-yaml my_yaml.yaml
echo $? # 1 if errors, 0 if ok
```
### Parsing
```python
from valohai_yaml import parse
with open('path/to/valohai.yaml') as f:
config = parse(f)
print(config.steps['cool step'].command)
```
# Development
```bash
# setup development dependencies
make dev
# run linting and type checks
make lint
# run tests
make test
```
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