colt

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Introduction

colt is a configuration utility for Python objects. colt constructs Python objects from a configuration dict which is convertable into JSON. (Inspired by AllenNLP)

Installation

pip install colt

Examples

Basic Usage

import typing as tp
import colt

@colt.register("foo")
class Foo:
    def __init__(self, message: str) -> None:
        self.message = message

@colt.register("bar")
class Bar:
    def __init__(self, foos: tp.List[Foo]) -> None:
        self.foos = foos

if __name__ == "__main__":
    config = {
        "@type": "bar",  # specify type name with `@type`
        "foos": [
            {"message": "hello"},  # type of this is inferred from type-hint
            {"message": "world"},
        ]
    }

    bar = colt.build(config)

    assert isinstance(bar, Bar)

    print(" ".join(foo.message for foo in bar.foos))
        # => "hello world"

`scikit-learn` Configuration

import colt

from sklearn.datasets import load_iris
from sklearn.model_selection import train_test_split

if __name__ == "__main__":
    config = {
        # import types automatically if type name is not registerd
        "@type": "sklearn.ensemble.VotingClassifier",
        "estimators": [
            ("rfc", { "@type": "sklearn.ensemble.RandomForestClassifier",
                      "n_estimators": 10 }),
            ("svc", { "@type": "sklearn.svm.SVC",
                      "gamma": "scale" }),
        ]
    }

    X, y = load_iris(return_X_y=True)
    X_train, X_valid, y_train, y_valid = train_test_split(X, y)

    model = colt.build(config)
    model.fit(X_train, y_train)

    valid_accuracy = model.score(X_valid, y_valid)
    print(f"valid_accuracy: {valid_accuracy}")

`Registrable` Class

By using the Registrable class, you can devide namespace into each class. In a following example, Foo and Bar have different namespaces.

import colt

class Foo(colt.Registrable):
    pass

class Bar(colt.Registrable):
    pass

@Foo.register("baz")
class FooBaz(Foo):
    pass

@Bar.register("baz")
class BarBaz(Bar):
    pass

@colt.register("my_class")
class MyClass:
    def __init__(self, foo: Foo, bar: Bar):
        self.foo = foo
        self.bar = bar

if __name__ == "__main__":
    config = {
        "@type": "my_class",
        "foo": {"@type": "baz"},
        "bar": {"@type": "baz"}
    }

    obj = colt.build(config)

    assert isinstance(obj.foo, FooBaz)
    assert isinstance(obj.bar, BarBaz)

Release files for colt 0.9.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for colt 0.9.0
File	Size	Uploaded
colt-0.9.0.tar.gz	8.7 kB	Oct 9, 2022	Details

Built distribution (wheel)

Table of built distributions (wheels) for colt 0.9.0
File	Interpreter	ABI	Platform	Reset
colt-0.9.0-py3-none-any.whl 8.6 kB Oct 9, 2022	Python 3	none	any	Details

Total release size: 17.3 kB

Release files / colt-0.9.0.tar.gz

Download URL	colt-0.9.0.tar.gz
Size	8.7 kB
Tags	Source
SHA-256 checksum How to use checksums	`e9532719831486ae8e87365c298f2ccad8193e61d497f2b48464cde11a3e4600`
BLAKE2b-256 checksum How to use checksums	`363c030597fc49c22d5c909c7106d18529b78bb01405d9068558316f123aadad`
Upload date	Oct 9, 2022
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`poetry/1.2.1 CPython/3.8.2 Linux/5.15.0-1020-azure`

Release files / colt-0.9.0-py3-none-any.whl

Download URL	colt-0.9.0-py3-none-any.whl
Size	8.6 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`3af7a32c700e97afbf34d648094aae47b0c6d5e5645cfa3e5f5dc14f8d9543d3`
BLAKE2b-256 checksum How to use checksums	`bcc6b6fff8f9d9ec4577b5458cf0ba9496941dc7d30c225e0203e9d27c055c86`
Upload date	Oct 9, 2022
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`poetry/1.2.1 CPython/3.8.2 Linux/5.15.0-1020-azure`