maxframe.dataframe.read_parquet#

maxframe.dataframe.read_parquet(path, engine: str = 'auto', columns: list = None, groups_as_chunks: bool = False, dtype_backend: str = <no_default>, default_index_type: DefaultIndexType | str = None, storage_options: dict = None, use_nullable_dtypes: bool = <no_default>, *, dtypes: Series = None, index_dtypes: Series = None, memory_scale: int = None, merge_small_files: bool = True, merge_small_file_options: dict = None, gpu: bool = None, session=None, run_kwargs: dict = None, **kwargs)[source]#

Load a parquet object from the file path, returning a DataFrame.

Parameters:

  • path (str, path object or file-like object) – Any valid string path is acceptable. The string could be a URL. For file URLs, a host is expected. A local file could be: file://localhost/path/to/table.parquet. A file URL can also be a path to a directory that contains multiple partitioned parquet files. Both pyarrow and fastparquet support paths to directories as well as file URLs. A directory path could be: file://localhost/path/to/tables. By file-like object, we refer to objects with a read() method, such as a file handler (e.g. via builtin open function) or StringIO.

  • engine ({'auto', 'pyarrow'}, default 'auto') – Parquet library to use. The default behavior is to try ‘pyarrow’,

  • storage_options (dict, optional) – Options for storage connection.

  • columns (list, default=None) – If not None, only these columns will be read from the file.

  • groups_as_chunks (bool, default False) – if True, each row group correspond to a chunk. if False, each file correspond to a chunk. Only available for ‘pyarrow’ engine.

  • default_index_type ({None, 'range', 'incremental'}, default None) – If index_col not specified, specify type of index to generate. If not specified, options.dataframe.default_index_type will be used.

  • dtype_backend ({'numpy', 'pyarrow'}, default 'numpy') – Back-end data type applied to the resultant DataFrame (still experimental).

  • storage_options – Options for storage connection.

  • memory_scale (int, optional) – Scale that real memory occupation divided with raw file size.

  • merge_small_files (bool, default True) – Merge small files whose size is small.

  • **kwargs – Any additional kwargs are passed to the engine.

Return type:

MaxFrame DataFrame