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REFACTOR-modin-project#6815: move experimental parsers into 'modin.ex…
…perimental' folder Signed-off-by: Anatoly Myachev <anatoly.myachev@intel.com>
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modin/experimental/core/storage_formats/pandas/__init__.py
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| # Licensed to Modin Development Team under one or more contributor license agreements. | ||
| # See the NOTICE file distributed with this work for additional information regarding | ||
| # copyright ownership. The Modin Development Team 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. | ||
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| """The module represents the query compiler level for the pandas storage format (experimental).""" |
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modin/experimental/core/storage_formats/pandas/parsers.py
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| # Licensed to Modin Development Team under one or more contributor license agreements. | ||
| # See the NOTICE file distributed with this work for additional information regarding | ||
| # copyright ownership. The Modin Development Team 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. | ||
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| """Module houses experimental Modin parser classes, that are used for data parsing on the workers.""" | ||
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| import warnings | ||
| from io import BytesIO | ||
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| import pandas | ||
| from pandas.util._decorators import doc | ||
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| from modin.core.io.file_dispatcher import OpenFile | ||
| from modin.core.storage_formats.pandas.parsers import ( | ||
| PandasCSVParser, | ||
| PandasParser, | ||
| _doc_pandas_parser_class, | ||
| _doc_parse_func, | ||
| _doc_parse_parameters_common, | ||
| _split_result_for_readers, | ||
| ) | ||
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| @doc(_doc_pandas_parser_class, data_type="multiple CSV files simultaneously") | ||
| class PandasCSVGlobParser(PandasCSVParser): | ||
| @staticmethod | ||
| @doc( | ||
| _doc_parse_func, | ||
| parameters="""chunks : list | ||
| List, where each element of the list is a list of tuples. The inner lists | ||
| of tuples contains the data file name of the chunk, chunk start offset, and | ||
| chunk end offsets for its corresponding file.""", | ||
| ) | ||
| def parse(chunks, **kwargs): | ||
| warnings.filterwarnings("ignore") | ||
| num_splits = kwargs.pop("num_splits", None) | ||
| index_col = kwargs.get("index_col", None) | ||
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| # `single_worker_read` just pass filename via chunks; need check | ||
| if isinstance(chunks, str): | ||
| return pandas.read_csv(chunks, **kwargs) | ||
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| # pop `compression` from kwargs because `bio` below is uncompressed | ||
| compression = kwargs.pop("compression", "infer") | ||
| storage_options = kwargs.pop("storage_options", None) or {} | ||
| pandas_dfs = [] | ||
| for fname, start, end in chunks: | ||
| if start is not None and end is not None: | ||
| with OpenFile(fname, "rb", compression, **storage_options) as bio: | ||
| if kwargs.get("encoding", None) is not None: | ||
| header = b"" + bio.readline() | ||
| else: | ||
| header = b"" | ||
| bio.seek(start) | ||
| to_read = header + bio.read(end - start) | ||
| pandas_dfs.append(pandas.read_csv(BytesIO(to_read), **kwargs)) | ||
| else: | ||
| # This only happens when we are reading with only one worker (Default) | ||
| return pandas.read_csv( | ||
| fname, | ||
| compression=compression, | ||
| storage_options=storage_options, | ||
| **kwargs, | ||
| ) | ||
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| # Combine read in data. | ||
| if len(pandas_dfs) > 1: | ||
| pandas_df = pandas.concat(pandas_dfs) | ||
| elif len(pandas_dfs) > 0: | ||
| pandas_df = pandas_dfs[0] | ||
| else: | ||
| pandas_df = pandas.DataFrame() | ||
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| # Set internal index. | ||
| if index_col is not None: | ||
| index = pandas_df.index | ||
| else: | ||
| # The lengths will become the RangeIndex | ||
| index = len(pandas_df) | ||
| return _split_result_for_readers(1, num_splits, pandas_df) + [ | ||
| index, | ||
| pandas_df.dtypes, | ||
| ] | ||
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| @doc(_doc_pandas_parser_class, data_type="pickled pandas objects") | ||
| class ExperimentalPandasPickleParser(PandasParser): | ||
| @staticmethod | ||
| @doc(_doc_parse_func, parameters=_doc_parse_parameters_common) | ||
| def parse(fname, **kwargs): | ||
| warnings.filterwarnings("ignore") | ||
| num_splits = 1 | ||
| single_worker_read = kwargs.pop("single_worker_read", None) | ||
| df = pandas.read_pickle(fname, **kwargs) | ||
| if single_worker_read: | ||
| return df | ||
| assert isinstance( | ||
| df, pandas.DataFrame | ||
| ), f"Pickled obj type: [{type(df)}] in [{fname}]; works only with pandas.DataFrame" | ||
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| length = len(df) | ||
| width = len(df.columns) | ||
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| return _split_result_for_readers(1, num_splits, df) + [length, width] | ||
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| @doc(_doc_pandas_parser_class, data_type="custom text") | ||
| class ExperimentalCustomTextParser(PandasParser): | ||
| @staticmethod | ||
| @doc(_doc_parse_func, parameters=_doc_parse_parameters_common) | ||
| def parse(fname, **kwargs): | ||
| return PandasParser.generic_parse(fname, **kwargs) |