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#
# 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.
#
"""Tests for apache_beam.runners.interactive.interactive_beam."""
# pytype: skip-file
import importlib
import sys
import time
import unittest
from typing import NamedTuple
from unittest.mock import patch
import apache_beam as beam
from apache_beam import dataframe as frames
from apache_beam.options.pipeline_options import PipelineOptions
from apache_beam.runners.interactive import interactive_beam as ib
from apache_beam.runners.interactive import interactive_environment as ie
from apache_beam.runners.interactive import interactive_runner as ir
from apache_beam.runners.interactive.options.capture_limiters import Limiter
from apache_beam.runners.runner import PipelineState
from apache_beam.testing.test_stream import TestStream
class Record(NamedTuple):
order_id: int
product_id: int
quantity: int
# The module name is also a variable in module.
_module_name = 'apache_beam.runners.interactive.interactive_beam_test'
def _get_watched_pcollections_with_variable_names():
watched_pcollections = {}
for watching in ie.current_env().watching():
for key, val in watching:
if hasattr(val, '__class__') and isinstance(val, beam.pvalue.PCollection):
watched_pcollections[val] = key
return watched_pcollections
class InteractiveBeamTest(unittest.TestCase):
def setUp(self):
self._var_in_class_instance = 'a var in class instance, not directly used'
ie.new_env()
def tearDown(self):
ib.options.capture_control.set_limiters_for_test([])
def test_watch_main_by_default(self):
test_env = ie.InteractiveEnvironment()
# Current Interactive Beam env fetched and the test env are 2 instances.
self.assertNotEqual(id(ie.current_env()), id(test_env))
self.assertEqual(ie.current_env().watching(), test_env.watching())
def test_watch_a_module_by_name(self):
test_env = ie.InteractiveEnvironment()
ib.watch(_module_name)
test_env.watch(_module_name)
self.assertEqual(ie.current_env().watching(), test_env.watching())
def test_watch_a_module_by_module_object(self):
test_env = ie.InteractiveEnvironment()
module = importlib.import_module(_module_name)
ib.watch(module)
test_env.watch(module)
self.assertEqual(ie.current_env().watching(), test_env.watching())
def test_watch_locals(self):
# test_env serves as local var too.
test_env = ie.InteractiveEnvironment()
ib.watch(locals())
test_env.watch(locals())
self.assertEqual(ie.current_env().watching(), test_env.watching())
def test_watch_class_instance(self):
test_env = ie.InteractiveEnvironment()
ib.watch(self)
test_env.watch(self)
self.assertEqual(ie.current_env().watching(), test_env.watching())
@unittest.skipIf(sys.platform == "win32", "[BEAM-10627]")
def test_show_always_watch_given_pcolls(self):
p = beam.Pipeline(ir.InteractiveRunner())
# pylint: disable=range-builtin-not-iterating
pcoll = p | 'Create' >> beam.Create(range(10))
# The pcoll is not watched since watch(locals()) is not explicitly called.
self.assertFalse(pcoll in _get_watched_pcollections_with_variable_names())
# The call of show watches pcoll.
ib.watch({'p': p})
ie.current_env().track_user_pipelines()
ib.show(pcoll)
self.assertTrue(pcoll in _get_watched_pcollections_with_variable_names())
@unittest.skipIf(sys.platform == "win32", "[BEAM-10627]")
def test_show_mark_pcolls_computed_when_done(self):
p = beam.Pipeline(ir.InteractiveRunner())
# pylint: disable=range-builtin-not-iterating
pcoll = p | 'Create' >> beam.Create(range(10))
self.assertFalse(pcoll in ie.current_env().computed_pcollections)
# The call of show marks pcoll computed.
ib.watch(locals())
ie.current_env().track_user_pipelines()
ib.show(pcoll)
self.assertTrue(pcoll in ie.current_env().computed_pcollections)
@patch((
'apache_beam.runners.interactive.interactive_beam.'
'visualize_computed_pcoll'))
def test_show_handles_dict_of_pcolls(self, mocked_visualize):
p = beam.Pipeline(ir.InteractiveRunner())
# pylint: disable=range-builtin-not-iterating
pcoll = p | 'Create' >> beam.Create(range(10))
ib.watch(locals())
ie.current_env().track_user_pipelines()
ie.current_env().mark_pcollection_computed([pcoll])
ie.current_env()._is_in_ipython = True
ie.current_env()._is_in_notebook = True
ib.show({'pcoll': pcoll})
mocked_visualize.assert_called_once()
@patch((
'apache_beam.runners.interactive.interactive_beam.'
'visualize_computed_pcoll'))
def test_show_handles_iterable_of_pcolls(self, mocked_visualize):
p = beam.Pipeline(ir.InteractiveRunner())
# pylint: disable=range-builtin-not-iterating
pcoll = p | 'Create' >> beam.Create(range(10))
ib.watch(locals())
ie.current_env().track_user_pipelines()
ie.current_env().mark_pcollection_computed([pcoll])
ie.current_env()._is_in_ipython = True
ie.current_env()._is_in_notebook = True
ib.show([pcoll])
mocked_visualize.assert_called_once()
@patch('apache_beam.runners.interactive.interactive_beam.visualize')
def test_show_handles_deferred_dataframes(self, mocked_visualize):
p = beam.Pipeline(ir.InteractiveRunner())
deferred = frames.convert.to_dataframe(p | beam.Create([Record(0, 0, 0)]))
ib.watch(locals())
ie.current_env().track_user_pipelines()
ie.current_env()._is_in_ipython = True
ie.current_env()._is_in_notebook = True
ib.show(deferred)
mocked_visualize.assert_called_once()
@patch((
'apache_beam.runners.interactive.interactive_beam.'
'visualize_computed_pcoll'))
def test_show_noop_when_pcoll_container_is_invalid(self, mocked_visualize):
class SomeRandomClass:
def __init__(self, pcoll):
self._pcoll = pcoll
p = beam.Pipeline(ir.InteractiveRunner())
# pylint: disable=range-builtin-not-iterating
pcoll = p | 'Create' >> beam.Create(range(10))
ie.current_env().mark_pcollection_computed([pcoll])
ie.current_env()._is_in_ipython = True
ie.current_env()._is_in_notebook = True
self.assertRaises(ValueError, ib.show, SomeRandomClass(pcoll))
mocked_visualize.assert_not_called()
def test_recordings_describe(self):
"""Tests that getting the description works."""
# Create the pipelines to test.
p1 = beam.Pipeline(ir.InteractiveRunner())
p2 = beam.Pipeline(ir.InteractiveRunner())
ib.watch(locals())
# Get the descriptions. This test is simple as there isn't much logic in the
# method.
self.assertEqual(ib.recordings.describe(p1)['size'], 0)
self.assertEqual(ib.recordings.describe(p2)['size'], 0)
all_descriptions = ib.recordings.describe()
self.assertEqual(all_descriptions[p1]['size'], 0)
self.assertEqual(all_descriptions[p2]['size'], 0)
# Ensure that the variable name for the pipeline is set correctly.
self.assertEqual(all_descriptions[p1]['pipeline_var'], 'p1')
self.assertEqual(all_descriptions[p2]['pipeline_var'], 'p2')
def test_recordings_clear(self):
"""Tests that clearing the pipeline is correctly forwarded."""
# Create a basic pipeline to store something in the cache.
p = beam.Pipeline(ir.InteractiveRunner())
elem = p | beam.Create([1])
ib.watch(locals())
ie.current_env().track_user_pipelines()
# This records the pipeline so that the cache size is > 0.
ib.collect(elem)
self.assertGreater(ib.recordings.describe(p)['size'], 0)
# After clearing, the cache should be empty.
ib.recordings.clear(p)
self.assertEqual(ib.recordings.describe(p)['size'], 0)
def test_recordings_record(self):
"""Tests that recording pipeline succeeds."""
# Add the TestStream so that it can be cached.
ib.options.recordable_sources.add(TestStream)
# Create a pipeline with an arbitrary amonunt of elements.
p = beam.Pipeline(
ir.InteractiveRunner(), options=PipelineOptions(streaming=True))
# pylint: disable=unused-variable
_ = (p
| TestStream()
.advance_watermark_to(0)
.advance_processing_time(1)
.add_elements(list(range(10)))
.advance_processing_time(1)) # yapf: disable
ib.watch(locals())
ie.current_env().track_user_pipelines()
# Assert that the pipeline starts in a good state.
self.assertEqual(ib.recordings.describe(p)['state'], PipelineState.STOPPED)
self.assertEqual(ib.recordings.describe(p)['size'], 0)
# Create a lmiter that stops the background caching job when something is
# written to cache. This is used to make ensure that the pipeline is
# functioning properly and that there are no data races with the test.
class SizeLimiter(Limiter):
def __init__(self, pipeline):
self.pipeline = pipeline
self.should_trigger = False
def is_triggered(self):
return (
ib.recordings.describe(self.pipeline)['size'] > 0 and
self.should_trigger)
limiter = SizeLimiter(p)
ib.options.capture_control.set_limiters_for_test([limiter])
# Assert that a recording can be started only once.
self.assertTrue(ib.recordings.record(p))
self.assertFalse(ib.recordings.record(p))
self.assertEqual(ib.recordings.describe(p)['state'], PipelineState.RUNNING)
# Wait for the pipeline to start and write something to cache.
limiter.should_trigger = True
for _ in range(60):
if limiter.is_triggered():
break
time.sleep(1)
self.assertTrue(
limiter.is_triggered(),
'Test timed out waiting for limiter to be triggered. This indicates '
'that the BackgroundCachingJob did not cache anything.')
# Assert that a recording can be stopped and can't be started again until
# after the cache is cleared.
ib.recordings.stop(p)
self.assertEqual(ib.recordings.describe(p)['state'], PipelineState.STOPPED)
self.assertFalse(ib.recordings.record(p))
ib.recordings.clear(p)
self.assertTrue(ib.recordings.record(p))
ib.recordings.stop(p)
if __name__ == '__main__':
unittest.main()