YAML configuration meets Python
Define Python objects in YAML. Reference, compose, and instantiate them effortlessly.
Quick Start
pip install sparkwheel
# config.yaml
dataset:
num_classes: 10
batch_size: 32
model:
_target_: torch.nn.Linear
in_features: 784
out_features: "%dataset::num_classes" # Reference
training:
steps_per_epoch: "$10000 // @dataset::batch_size" # Expression
from sparkwheel import Config
config = Config()
config.update("config.yaml")
model = config.resolve("model") # Actual torch.nn.Linear(784, 10)
Features
- Declarative Objects - Instantiate any Python class with
_target_ - Smart References -
@for resolved values,%for raw YAML - Composition by Default - Dicts merge, lists extend automatically
- Explicit Control -
=to replace,~to delete - Python Expressions - Dynamic values with
$ - Schema Validation - Type-check with dataclasses
Get Started · Documentation · Quick Reference
Community
About
Sparkwheel is a hard fork of MONAI Bundle's config system, with the goal of making a more general-purpose configuration library for Python projects. It combines the best of MONAI Bundle and Hydra/OmegaConf, while introducing new features and improvements not found in either.
1 maintainer
Metadata
1 maintainer
Release files for sparkwheel 0.0.11
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| File | Size | Uploaded | Provenance | Actions |
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| sparkwheel-0.0.11.tar.gz | 50.1 kB | Without provenance | Details for sparkwheel-0.0.11.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| sparkwheel-0.0.11-py3-none-any.whl | Python 3 | none | any | Details for sparkwheel-0.0.11-py3-none-any.whl |
Total release size: 109.9 kB
Release files / sparkwheel-0.0.11.tar.gz
| Download URL | sparkwheel-0.0.11.tar.gz |
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| Size | 50.1 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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Release files / sparkwheel-0.0.11-py3-none-any.whl
| Download URL | sparkwheel-0.0.11-py3-none-any.whl |
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| Size | 59.8 kB |
| Tags | Python 3 |
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