def _examples()

in spotify_tensorflow/dataset.py [0:0]

• 35 lines of code
• 2 McCabe index (conditional complexity)

        def _examples(cls,
                      file_pattern,  # type: str
                      schema_path=None,  # type: str
                      feature_spec=None,  # type: Dict[str, Union[tf.FixedLenFeature, tf.VarLenFeature, tf.SparseFeature]]  # noqa: E501
                      default_value=0,  # type: float
                      compression_type=None,  # type: str
                      batch_size=128,  # type: int
                      shuffle=True,  # type: bool
                      num_epochs=1,  # type: int
                      shuffle_buffer_size=10000,  # type: int
                      shuffle_seed=None,  # type: int
                      prefetch_buffer_size=1,  # type: int
                      reader_num_threads=1,  # type: int
                      parser_num_threads=2,  # type: int
                      sloppy_ordering=False,  # type: bool
                      drop_final_batch=False  # type: bool
                      ):
            # type: (...) -> Iterator[pd.DataFrame]
            Datasets._assert_eager("DataFrame")
            dataset = Datasets.dict._examples(file_pattern=file_pattern,
                                              schema_path=schema_path,
                                              default_value=default_value,
                                              feature_spec=feature_spec,
                                              compression_type=compression_type,
                                              batch_size=batch_size,
                                              shuffle=shuffle,
                                              num_epochs=num_epochs,
                                              shuffle_buffer_size=shuffle_buffer_size,
                                              shuffle_seed=shuffle_seed,
                                              prefetch_buffer_size=prefetch_buffer_size,
                                              reader_num_threads=reader_num_threads,
                                              parser_num_threads=parser_num_threads,
                                              sloppy_ordering=sloppy_ordering,
                                              drop_final_batch=drop_final_batch)
            for d in dataset:
                yield pd.DataFrame(data=d)