(source, *, columns=None, use_threads=True,
schema=None, use_pandas_metadata=False, read_dictionary=None,
binary_type=None, list_type=None, memory_map=False, buffer_size=0,
partitioning="hive", filesystem=None, filters=None,
ignore_prefixes=None, pre_buffer=True,
coerce_int96_timestamp_unit=None,
decryption_properties=None, thrift_string_size_limit=None,
thrift_container_size_limit=None,
page_checksum_verification=False,
arrow_extensions_enabled=True)
| 1882 | |
| 1883 | |
| 1884 | def read_table(source, *, columns=None, use_threads=True, |
| 1885 | schema=None, use_pandas_metadata=False, read_dictionary=None, |
| 1886 | binary_type=None, list_type=None, memory_map=False, buffer_size=0, |
| 1887 | partitioning="hive", filesystem=None, filters=None, |
| 1888 | ignore_prefixes=None, pre_buffer=True, |
| 1889 | coerce_int96_timestamp_unit=None, |
| 1890 | decryption_properties=None, thrift_string_size_limit=None, |
| 1891 | thrift_container_size_limit=None, |
| 1892 | page_checksum_verification=False, |
| 1893 | arrow_extensions_enabled=True): |
| 1894 | |
| 1895 | try: |
| 1896 | dataset = ParquetDataset( |
| 1897 | source, |
| 1898 | schema=schema, |
| 1899 | filesystem=filesystem, |
| 1900 | partitioning=partitioning, |
| 1901 | memory_map=memory_map, |
| 1902 | read_dictionary=read_dictionary, |
| 1903 | binary_type=binary_type, |
| 1904 | list_type=list_type, |
| 1905 | buffer_size=buffer_size, |
| 1906 | filters=filters, |
| 1907 | ignore_prefixes=ignore_prefixes, |
| 1908 | pre_buffer=pre_buffer, |
| 1909 | coerce_int96_timestamp_unit=coerce_int96_timestamp_unit, |
| 1910 | decryption_properties=decryption_properties, |
| 1911 | thrift_string_size_limit=thrift_string_size_limit, |
| 1912 | thrift_container_size_limit=thrift_container_size_limit, |
| 1913 | page_checksum_verification=page_checksum_verification, |
| 1914 | arrow_extensions_enabled=arrow_extensions_enabled, |
| 1915 | ) |
| 1916 | except ImportError: |
| 1917 | # fall back on ParquetFile for simple cases when pyarrow.dataset |
| 1918 | # module is not available |
| 1919 | if filters is not None: |
| 1920 | raise ValueError( |
| 1921 | "the 'filters' keyword is not supported when the " |
| 1922 | "pyarrow.dataset module is not available" |
| 1923 | ) |
| 1924 | if partitioning != "hive": |
| 1925 | raise ValueError( |
| 1926 | "the 'partitioning' keyword is not supported when the " |
| 1927 | "pyarrow.dataset module is not available" |
| 1928 | ) |
| 1929 | if schema is not None: |
| 1930 | raise ValueError( |
| 1931 | "the 'schema' argument is not supported when the " |
| 1932 | "pyarrow.dataset module is not available" |
| 1933 | ) |
| 1934 | if isinstance(source, list): |
| 1935 | raise ValueError( |
| 1936 | "the 'source' argument cannot be a list of files " |
| 1937 | "when the pyarrow.dataset module is not available" |
| 1938 | ) |
| 1939 | |
| 1940 | filesystem, path = _resolve_filesystem_and_path(source, filesystem) |
| 1941 | if filesystem is not None: |
no test coverage detected