Source code for apache_beam.typehints.native_type_compatibility

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# this work for additional information regarding copyright ownership.
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"""Module to convert Python's native typing types to Beam types."""

from __future__ import absolute_import

import collections
import sys
import typing
from builtins import next
from builtins import range

from apache_beam.typehints import typehints

# Describes an entry in the type map in convert_to_beam_type.
# match is a function that takes a user type and returns whether the conversion
# should trigger.
# arity is the expected arity of the user type. -1 means it's variadic.
# beam_type is the Beam type the user type should map to.
_TypeMapEntry = collections.namedtuple(
    '_TypeMapEntry', ['match', 'arity', 'beam_type'])

def _get_compatible_args(typ):
  if isinstance(typ, typing.TypeVar):
    return (typ.__name__,)
  # On Python versions < 3.5.3, the Tuple and Union type from typing do
  # not have an __args__ attribute, but a __tuple_params__, and a
  # __union_params__ argument respectively.
  if (3, 0, 0) <= sys.version_info[0:3] < (3, 5, 3):
    if getattr(typ, '__tuple_params__', None) is not None:
      return typ.__tuple_params__
    elif getattr(typ, '__union_params__', None) is not None:
      return typ.__union_params__
  return None

def _get_arg(typ, index):
  """Returns the index-th argument to the given type."""
    return typ.__args__[index]
  except AttributeError:
    compatible_args = _get_compatible_args(typ)
    if compatible_args is None:
    return compatible_args[index]

def _len_arg(typ):
  """Returns the length of the arguments to the given type."""
    return len(typ.__args__)
  except AttributeError:
    compatible_args = _get_compatible_args(typ)
    if compatible_args is None:
      return 0
    return len(compatible_args)

def _safe_issubclass(derived, parent):
  """Like issubclass, but swallows TypeErrors.

  This is useful for when either parameter might not actually be a class,
  e.g. typing.Union isn't actually a class.

    derived: As in issubclass.
    parent: As in issubclass.

    issubclass(derived, parent), or False if a TypeError was raised.
    return issubclass(derived, parent)
  except TypeError:
    if hasattr(derived, '__origin__'):
        return issubclass(derived.__origin__, parent)
      except TypeError:
    return False

def _match_issubclass(match_against):
  return lambda user_type: _safe_issubclass(user_type, match_against)

def _match_same_type(match_against):
  # For types that can't be compared with isinstance or _safe_issubclass.
  return lambda user_type: type(user_type) == type(match_against)

def _match_is_exactly_iterable(user_type):
  # Avoid unintentionally catching all subtypes (e.g. strings and mappings).
  if sys.version_info < (3, 7):
    expected_origin = typing.Iterable
    expected_origin =
  return getattr(user_type, '__origin__', None) is expected_origin

def _match_is_named_tuple(user_type):
  return (_safe_issubclass(user_type, typing.Tuple) and
          hasattr(user_type, '_field_types'))

def _match_is_union(user_type):
  # For non-subscripted unions (Python 2.7.14+ with typing 3.64)
  if user_type is typing.Union:
    return True

  try:  # Python 3.5.2
    if isinstance(user_type, typing.UnionMeta):
      return True
  except AttributeError:

  try:  # Python 3.5.4+, or Python 2.7.14+ with typing 3.64
    return user_type.__origin__ is typing.Union
  except AttributeError:

  return False

_type_var_cache = {}

[docs]def convert_to_beam_type(typ): """Convert a given typing type to a Beam type. Args: typ (type): typing type. Returns: type: The given type converted to a Beam type as far as we can do the conversion. Raises: ~exceptions.ValueError: The type was malformed. """ if isinstance(typ, typing.TypeVar): # This is a special case, as it's not parameterized by types. # Also, identity must be preserved through conversion (i.e. the same # TypeVar instance must get converted into the same TypeVariable instance). # A global cache should be OK as the number of distinct type variables # is generally small. if id(typ) not in _type_var_cache: _type_var_cache[id(typ)] = typehints.TypeVariable(typ.__name__) return _type_var_cache[id(typ)] elif getattr(typ, '__module__', None) != 'typing': # Only tranlsate types from the typing module. return typ type_map = [ _TypeMapEntry( match=_match_same_type(typing.Any), arity=0, beam_type=typehints.Any), _TypeMapEntry( match=_match_issubclass(typing.Dict), arity=2, beam_type=typehints.Dict), _TypeMapEntry( match=_match_is_exactly_iterable, arity=1, beam_type=typehints.Iterable), _TypeMapEntry( match=_match_issubclass(typing.List), arity=1, beam_type=typehints.List), _TypeMapEntry( match=_match_issubclass(typing.Set), arity=1, beam_type=typehints.Set), # NamedTuple is a subclass of Tuple, but it needs special handling. # We just convert it to Any for now. # This MUST appear before the entry for the normal Tuple. _TypeMapEntry( match=_match_is_named_tuple, arity=0, beam_type=typehints.Any), _TypeMapEntry( match=_match_issubclass(typing.Tuple), arity=-1, beam_type=typehints.Tuple), _TypeMapEntry(match=_match_is_union, arity=-1, beam_type=typehints.Union), ] # Find the first matching entry. matched_entry = next((entry for entry in type_map if entry.match(typ)), None) if not matched_entry: # No match: return original type. return typ if matched_entry.arity == -1: arity = _len_arg(typ) else: arity = matched_entry.arity if _len_arg(typ) != arity: raise ValueError('expecting type %s to have arity %d, had arity %d ' 'instead' % (str(typ), arity, _len_arg(typ))) typs = [convert_to_beam_type(_get_arg(typ, i)) for i in range(arity)] if arity == 0: # Nullary types (e.g. Any) don't accept empty tuples as arguments. return matched_entry.beam_type elif arity == 1: # Unary types (e.g. Set) don't accept 1-tuples as arguments return matched_entry.beam_type[typs[0]] else: return matched_entry.beam_type[tuple(typs)]
[docs]def convert_to_beam_types(args): """Convert the given list or dictionary of args to Beam types. Args: args: Either an iterable of types, or a dictionary where the values are types. Returns: If given an iterable, a list of converted types. If given a dictionary, a dictionary with the same keys, and values which have been converted. """ if isinstance(args, dict): return {k: convert_to_beam_type(v) for k, v in args.items()} else: return [convert_to_beam_type(v) for v in args]