Artisan is a lightweight experiment-management library with support for gradual typing. It allows you to write code like this:

class SineWave(artisan.Artifact):
    'sin(2πf⋅t + φ) for t ∈ [0, 1sec), sampled at 44.1kHz.'

    class Spec(Protocol):
        f: float; 'Frequency.'
        φ: float = 0.0; 'Phase shift.'

    def __init__(self, spec: Spec) -> None:
        self.t = np.linspace(0, 1, 44100)
        self.x = np.sin(2 * np.pi * spec.f * self.t + spec.φ)

to generate file trees like this:

├── SineWave_0000/
│   ├── _meta_.json
│   ├── t.cbor
│   └── x.cbor
└── SineWave_0001/
    ├── _meta_.json
    ├── t.cbor
    └── x.cbor

that can be viewed as customizable, live-updated, interactive documents like this:

– artisan-ui screenshot coming soon! –

to facilitate an explorable, explainable, composable-component-based approach to scientific, analytical, and artistic programming.


> pip install artisan-builder

Artisan works with CPython and PyPy 3.6+.

Guide contents

  • Working with targets describes how to define types that can be exposed via a command-line interface, REST API, or web UI.

  • Working with artifacts describes how to define new types of artifacts—persistent, immutable targets corresponding to directory trees—and how artifacts can be created and inspected.

  • Working with contexts describes how to use the context API to customize target instantiation, and how to generate JSON Schemas describing the space of valid artifact specifications within a given context.

  • Generating a CLI describes how to make a command-line interface for creating artifacts.

  • Generating a REST API describes how to make artifacts and artifact types accessible over HTTP.

  • Generating a web UI describes how to create and inspect artifacts using a web browser, and how to define custom artifact views.

  • The API reference contains comprehensive class and function documentation.