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

Read effective Arrow schema from Parquet file metadata.

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.


The schema of the Parquet file


>>> 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