# BSD 3-Clause License; see https://github.com/scikit-hep/awkward-1.0/blob/main/LICENSE

# Ideally, you want to collaborate with NumExpr to get this without a nested module.
# Barring that, though, just reimplement in v2.

# from __future__ import absolute_import

# import warnings
# import sys
# import distutils.version
# import types

# import awkward as ak

# checked_version = False


# def import_numexpr():
#     global checked_version
#     try:
#         import numexpr
#     except ImportError:
#         raise ImportError(
#             """install the 'numexpr' package with:

#     pip install numexpr --upgrade

# or

#     conda install numexpr"""
#         )
#     else:
#         if not checked_version and distutils.version.LooseVersion(
#             numexpr.__version__
#         ) < distutils.version.LooseVersion("2.7.1"):
#             warnings.warn(
#                 "Awkward Array is only known to work with numexpr 2.7.1 or later"
#                 "(you have version {0})".format(numexpr.__version__),
#                 RuntimeWarning,
#             )
#         checked_version = True
#         return numexpr


# def getArguments(names, local_dict=None, global_dict=None):
#     call_frame = sys._getframe(2)

#     clear_local_dict = False
#     if local_dict is None:
#         local_dict = call_frame.f_locals
#         clear_local_dict = True
#     try:
#         frame_globals = call_frame.f_globals
#         if global_dict is None:
#             global_dict = frame_globals

#         clear_local_dict = clear_local_dict and frame_globals is not local_dict

#         arguments = []
#         for name in names:
#             try:
#                 a = local_dict[name]
#             except KeyError:
#                 a = global_dict[name]
#             arguments.append(a)  # <--- different from NumExpr
#     finally:
#         if clear_local_dict:
#             local_dict.clear()

#     return arguments


# def evaluate(
#     expression, local_dict=None, global_dict=None, order="K", casting="safe", **kwargs
# ):
#     numexpr = import_numexpr()

#     context = numexpr.necompiler.getContext(kwargs, frame_depth=1)
#     expr_key = (expression, tuple(sorted(context.items())))
#     if expr_key not in numexpr.necompiler._names_cache:
#         numexpr.necompiler._names_cache[expr_key] = numexpr.necompiler.getExprNames(
#             expression, context
#         )
#     names, ex_uses_vml = numexpr.necompiler._names_cache[expr_key]
#     arguments = getArguments(names, local_dict, global_dict)

#     arrays = [
#         ak._v2.operations.convert.to_layout(x, allow_record=True, allow_other=True)
#         for x in arguments
#     ]

#     def getfunction(inputs):
#         if all(
#             isinstance(x, ak._v2.contents.NumpyArray) or not isinstance(x, ak._v2.contents.Content)
#             for x in inputs
#         ):
#             return lambda: (
#                 ak._v2.contents.NumpyArray(
#                     numexpr.evaluate(
#                         expression,
#                         dict(zip(names, inputs)),
#                         {},
#                         order=order,
#                         casting=casting,
#                         **kwargs
#                     )
#                 ),
#             )
#         else:
#             return None

#     behavior = ak._v2._util.behaviorof(*arrays)
#     out = ak._v2._util.broadcast_and_apply(
#         arrays, getfunction, behavior, allow_records=False, pass_depth=False
#     )
#     assert isinstance(out, tuple) and len(out) == 1
#     return ak._v2._util.wrap(out[0], behavior)


# evaluate.evaluate = evaluate


# def re_evaluate(local_dict=None):
#     numexpr = import_numexpr()

#     try:
#         compiled_ex = numexpr.necompiler._numexpr_last["ex"]  # noqa: F841
#     except KeyError:
#         raise RuntimeError(
#             "not a previous evaluate() execution found"
#
#         )
#     names = numexpr.necompiler._numexpr_last["argnames"]
#     arguments = getArguments(names, local_dict)

#     arrays = [
#         ak._v2.operations.convert.to_layout(x, allow_record=True, allow_other=True)
#         for x in arguments
#     ]

#     def getfunction(inputs):
#         if all(
#             isinstance(x, ak._v2.contents.NumpyArray) or not isinstance(x, ak._v2.contents.Content)
#             for x in inputs
#         ):
#             return lambda: (
#                 ak._v2.contents.NumpyArray(numexpr.re_evaluate(dict(zip(names, inputs)))),
#             )
#         else:
#             return None

#     behavior = ak._v2._util.behaviorof(*arrays)
#     out = ak._v2._util.broadcast_and_apply(
#         arrays, getfunction, behavior, allow_records=False, pass_depth=False
#     )
#     assert isinstance(out, tuple) and len(out) == 1
#     return ak._v2._util.wrap(out[0], behavior)


# ak.numexpr = types.ModuleType("numexpr")
# ak.numexpr.evaluate = evaluate
# ak.numexpr.re_evaluate = re_evaluate
