Source code for mixle.utils.optional_deps

"""Optional-dependency shims so the base install works without the heavy extras.

numba: when installed, the real module is re-exported. When missing, a no-op
stand-in is provided whose jit/njit decorators return the function unchanged
and whose prange is range - the jitted code paths then run as pure Python
(correct, but slow). Install the accelerated paths with:

    pip install mixle[numba]

pyspark: `pyspark` is None when missing and RDD_TYPES is an empty tuple, so
`isinstance(data, RDD_TYPES)` is simply False and the estimation helpers fall
through to their local implementations. Install with:

    pip install mixle[spark]
"""

__all__ = ["numba", "HAS_NUMBA", "pyspark", "HAS_PYSPARK", "RDD_TYPES", "gmpy2", "HAS_GMPY2", "require"]




def require(name: str, extra: str):
    """Raise a helpful error for a feature that needs an uninstalled extra."""
    raise ImportError("%s is required for this feature; install it with pip install mixle[%s]" % (name, extra))



# gmpy2: when installed, the structural count-DP routes its large histogram convolutions through GMP's
# FFT-based big-integer multiply (Schoenhage-Strassen), ~100x faster than CPython's Karatsuba on the
# multi-megabyte operands that wide deep-sequence convolutions produce. When missing, gmpy2 is None and
# the convolution falls back to the exact CPython big-int path. Install with: pip install mixle[gmpy2]
try:
    import gmpy2

    HAS_GMPY2 = True
except ImportError:
    gmpy2 = None
    HAS_GMPY2 = False


try:
    import numba

    HAS_NUMBA = True
except ImportError:
    HAS_NUMBA = False

    class _NumbaShim:
        prange = staticmethod(range)

        @staticmethod
        def _decorate(*args, **kwargs):
            if args and callable(args[0]):
                return args[0]

            def deco(f):
                return f

            return deco

        njit = _decorate
        jit = _decorate

    numba = _NumbaShim()


try:
    import pyspark
    import pyspark.rdd

    HAS_PYSPARK = True
    RDD_TYPES = (pyspark.rdd.RDD,)
except ImportError:
    pyspark = None
    HAS_PYSPARK = False
    RDD_TYPES = ()