sdks/python/apache_beam/examples/complete/tfidf_test.py

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#    http://www.apache.org/licenses/LICENSE-2.0
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"""Test for the TF-IDF example."""

# pytype: skip-file

import logging
import unittest

import apache_beam as beam
from apache_beam.examples.complete import tfidf
from apache_beam.testing.test_pipeline import TestPipeline
from apache_beam.testing.util import assert_that
from apache_beam.testing.util import equal_to

EXPECTED_RESULTS = set([
    ('ghi', '1.txt', 0.3662040962227032), ('abc', '1.txt', 0.0),
    ('abc', '3.txt', 0.0), ('abc', '2.txt', 0.0),
    ('def', '1.txt', 0.13515503603605478), ('def', '2.txt', 0.2027325540540822)
])


class TfIdfTest(unittest.TestCase):
  def test_tfidf_transform(self):
    with TestPipeline() as p:

      def re_key(word_uri_tfidf):
        (word, (uri, tfidf)) = word_uri_tfidf
        return (word, uri, tfidf)

      uri_to_line = p | 'create sample' >> beam.Create(
          [('1.txt', 'abc def ghi'), ('2.txt', 'abc def'), ('3.txt', 'abc')])
      result = (uri_to_line | tfidf.TfIdf() | beam.Map(re_key))
      assert_that(result, equal_to(EXPECTED_RESULTS))
      # Run the pipeline. Note that the assert_that above adds to the pipeline
      # a check that the result PCollection contains expected values.
      # To actually trigger the check the pipeline must be run (e.g. by
      # exiting the with context).


if __name__ == '__main__':
  logging.getLogger().setLevel(logging.INFO)
  unittest.main()