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A backend-agnostic array utility library that unifies array conversion, context control, and cross-library operations across `NumPy`/`PyTorch`-style ecosystems.

Project description

🍁 cobra-array 🍁
Unified Array Utilities with Python Array API Compatibility

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About

cobra-array is a backend-agnostic array utility library that unifies array conversion, context control, and cross-library operations across NumPy/PyTorch-style ecosystems.

  • Python: 3.9+
  • Runtime deps: array-api-compat (>= 1.11.2)

Features

  • 🚀 Ackend-agnostic API: Work with different array backends through one consistent interface.
  • 🚀 Context-driven unification: Automatically align namespace, dtype, and device via context managers and decorators.
  • 🚀 Compatibility wrappers: CompatArray and CompatNamespace provide a clean, consistent layer over native backend behavior.

Installation

Install from PyPI

pip install cobra-array

Quick Start

  • Basic conversions:

    import numpy as np
    from cobra_array.convert import to_numpy, to_tensor, to_list
    
    data = [[1, 2], [3, 4]]
    
    arr_np = to_numpy(data, dtype=np.float32)
    print(type(arr_np), arr_np.dtype)  # numpy.ndarray float32
    
    arr_torch = to_tensor(data, device="cpu")
    print(type(arr_torch), arr_torch.device)
    
    back_to_list = to_list(arr_np)
    print(back_to_list)  # [[1.0, 2.0], [3.0, 4.0]]
    
  • Context-based conversion:

    import numpy as np
    from cobra_array import array_context, as_context, context_spec
    
    with array_context(xp="numpy", dtype=np.float32, device="cpu"):
        x = as_context([1, 2, 3])
        y = as_context(np.array([4, 5]))
        spec = context_spec()
        print(spec.cxp.xp_name, spec.dtype, spec.device)
        print(x, y)
    
  • Auto-unify function arguments:

    import numpy as np
    from cobra_array import unify_args
    
    @unify_args(ref=0, unify_dtype=True, unify_device=True, arraylike_only=True)
    def add_and_mean(a, b):
        c = a + b
        return c.mean()
    
    out = add_and_mean(np.array([1, 2, 3]), [4, 5, 6])
    print(out)
    
  • Default backend strategy:

    from cobra_array.default import as_default, default_spec
    
    spec = default_spec()
    print(spec.cxp.xp_name, spec.dtype, spec.device)
    
    x = as_default([1, 2, 3], unify_dtype=True, unify_device=True)
    print(x, x.dtype)
    

Requirements

  • Python >= 3.9
  • array-api-compat >= 1.11.2

License

See LICENSE in the repository.

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