#
# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements. See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the "License"); you may not use this file except in compliance with
# the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
"""Internal side input transforms and implementations.
For internal use only; no backwards-compatibility guarantees.
Important: this module is an implementation detail and should not be used
directly by pipeline writers. Instead, users should use the helper methods
AsSingleton, AsIter, AsList and AsDict in apache_beam.pvalue.
"""
# pytype: skip-file
from __future__ import absolute_import
import re
from builtins import object
from typing import TYPE_CHECKING
from typing import Any
from typing import Callable
from typing import Dict
from apache_beam.transforms import window
if TYPE_CHECKING:
from apache_beam import pvalue
WindowMappingFn = Callable[[window.BoundedWindow], window.BoundedWindow]
# Top-level function so we can identify it later.
def _global_window_mapping_fn(w, global_window=window.GlobalWindow()):
# type: (...) -> window.GlobalWindow
return global_window
[docs]def default_window_mapping_fn(target_window_fn):
# type: (window.WindowFn) -> WindowMappingFn
if target_window_fn == window.GlobalWindows():
return _global_window_mapping_fn
def map_via_end(source_window):
# type: (window.BoundedWindow) -> window.BoundedWindow
return list(
target_window_fn.assign(
window.WindowFn.AssignContext(source_window.max_timestamp())))[-1]
return map_via_end
class _FilteringIterable(object):
"""An iterable containing only those values in the given window.
"""
def __init__(self, iterable, target_window):
self._iterable = iterable
self._target_window = target_window
def __iter__(self):
for wv in self._iterable:
if self._target_window in wv.windows:
yield wv.value
def __reduce__(self):
# Pickle self as an already filtered list.
return list, (list(self), )