pyarrow.parquet.read_schema#

pyarrow.parquet.read_schema(where, memory_map=False, decryption_properties=None, filesystem=None)[source]#

Read effective Arrow schema from Parquet file metadata.

Parameters:

wherestr (file path) or file-like object
memory_mapbool, default False: Create memory map when the source is a file path.
decryption_propertiesFileDecryptionProperties, default None: Decryption properties for reading encrypted Parquet files.
filesystemFileSystem, default None: If nothing passed, will be inferred based on path. Path will try to be found in the local on-disk filesystem otherwise it will be parsed as an URI to determine the filesystem.

Returns:

schemapyarrow.Schema: The schema of the Parquet file

Examples

>>> import pyarrow as pa
>>> import pyarrow.parquet as pq
>>> table = pa.table({'n_legs': [4, 5, 100],
...                   'animal': ["Dog", "Brittle stars", "Centipede"]})
>>> pq.write_table(table, 'example.parquet')

>>> pq.read_schema('example.parquet')
n_legs: int64
animal: string