[ARROW-8987] [C++][Python] Make reading functions to return consistent exceptions

• Type: Bug
• Status: Open
• Priority: Minor
• Resolution: Unresolved
• Affects Version/s: 0.17.1
• Component/s: C++, Python
• External issue URL: https://github.com/apache/arrow/issues/25109
• Assignee: Unassigned
• Reporter: German I. Ramirez-Espinoza
• Created: 31/May/20 11:22
• Updated: 11/Jan/23 08:03

Description

Reading functions like dataset.dataset and read_table functions in feather, parquet, and csv modules return different exceptions when reading an "empty file" or "missing file", respectively. See table below.

It would be idea if all the reading functions return FileNotFound error when the file is missing and return ArrowInvalid when the file's empty.

Most interesting is the case of dataset.dataset since the format parameter modifies the exception behaviour when reading an empty file.

 

Function	Missing file	Empty File
feather.read_table	FileNotFoundError	ArrowInvalid
parquet.read_table	OSError	ArrowInvalid
csv.read_csv	FileNotFoundError	ArrowInvalid
dataset.dataset "feather"	FileNotFoundError	ArrowInvalid
dataset.dataset "parquet"	FileNotFoundError	OSError
dataset.dataset "csv"	FileNotFoundError	ArrowInvalid

 

Code to reproduce issue:

import pathlib
import sys
import tempfile

import pyarrow as pa

import pyarrow.csv as csv
import pyarrow.dataset as dataset
import pyarrow.feather as feather
import pyarrow.parquet as parquet

tempdir = pathlib.Path(tempfile.mkdtemp())

with open(str(tempdir / "empty_feather.feather"), 'wb') as f:
    pass

with open(str(tempdir / "empty_parquet.parquet"), 'wb') as f:
    pass

with open(str(tempdir / "empty_csv.csv"), 'wb') as f:
    pass

# Empty File
feather.read_table(str(tempdir / "empty_feather.feather"))
parquet.read_table(str(tempdir / "empty_parquet.parquet"))
csv.read_csv(str(tempdir / "empty_csv.csv"))
dataset.dataset(str(tempdir / "empty_feather.feather"), format="feather")
dataset.dataset(str(tempdir / "empty_parquet.parquet"), format="parquet")
dataset.dataset(str(tempdir / "empty_csv.csv"), format="csv")

# Missing File
feather.read_table(str(tempdir / "non_existent.feather"))
parquet.read_table(str(tempdir / "non_existent.parquet"))
csv.read_csv(str(tempdir / "non_existent.csv"))
dataset.dataset(str(tempdir / "non_existent.feather"), format="feather")
dataset.dataset(str(tempdir / "non_existent.parquet"), format="parquet")
dataset.dataset(str(tempdir / "non_existent.csv"), format="csv")