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"""

Introspection helper functions.

"""
import re

__all__ = ['opt_func_info']


def opt_func_info(func_name=None, signature=None):
    """

    Returns a dictionary containing the currently supported CPU dispatched

    features for all optimized functions.



    Parameters

    ----------

    func_name : str (optional)

        Regular expression to filter by function name.



    signature : str (optional)

        Regular expression to filter by data type.



    Returns

    -------

    dict

        A dictionary where keys are optimized function names and values are

        nested dictionaries indicating supported targets based on data types.



    Examples

    --------

    Retrieve dispatch information for functions named 'add' or 'sub' and

    data types 'float64' or 'float32':



    >>> dict = np.lib.introspect.opt_func_info(

    ...     func_name="add|abs", signature="float64|complex64"

    ... )

    >>> import json

    >>> print(json.dumps(dict, indent=2))

        {

          "absolute": {

            "dd": {

              "current": "SSE41",

              "available": "SSE41 baseline(SSE SSE2 SSE3)"

            },

            "Ff": {

              "current": "FMA3__AVX2",

              "available": "AVX512F FMA3__AVX2 baseline(SSE SSE2 SSE3)"

            },

            "Dd": {

              "current": "FMA3__AVX2",

              "available": "AVX512F FMA3__AVX2 baseline(SSE SSE2 SSE3)"

            }

          },

          "add": {

            "ddd": {

              "current": "FMA3__AVX2",

              "available": "FMA3__AVX2 baseline(SSE SSE2 SSE3)"

            },

            "FFF": {

              "current": "FMA3__AVX2",

              "available": "FMA3__AVX2 baseline(SSE SSE2 SSE3)"

            }

          }

        }



    """
    from numpy._core._multiarray_umath import (
        __cpu_targets_info__ as targets, dtype
    )

    if func_name is not None:
        func_pattern = re.compile(func_name)
        matching_funcs = {
            k: v for k, v in targets.items()
            if func_pattern.search(k)
        }
    else:
        matching_funcs = targets

    if signature is not None:
        sig_pattern = re.compile(signature)
        matching_sigs = {}
        for k, v in matching_funcs.items():
            matching_chars = {}
            for chars, targets in v.items():
                if any([
                    sig_pattern.search(c) or
                    sig_pattern.search(dtype(c).name)
                    for c in chars
                ]):
                    matching_chars[chars] = targets
            if matching_chars:
                matching_sigs[k] = matching_chars
    else:
        matching_sigs = matching_funcs
    return matching_sigs