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BUG: Validate path type in read_parquet, reject non-path/file-like #62979

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BUG: Validate path type in read_parquet, reject non-path/file-like #62979

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9 changes: 9 additions & 0 deletions pandas/io/parquet.py
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Original file line number Diff line number Diff line change
Expand Up @@ -27,6 +27,8 @@
)
from pandas.util._validators import check_dtype_backend

from pandas.core.dtypes.common import is_file_like

from pandas import (
DataFrame,
get_option,
Expand Down Expand Up @@ -658,6 +660,13 @@ def read_parquet(
0 3 8
1 4 9
"""
# gh-62922: validate path type early to match documented API expectations
# and provide a consistent, clear user error immediately.
if not (isinstance(path, (str, os.PathLike)) or is_file_like(path)):
raise TypeError(
f"read_parquet expected str/os.PathLike or file-like object, "
f"got {type(path).__name__} type"
)
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@mroeschke mroeschke Nov 4, 2025

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This should probably be done using get_handle in the _get_path_or_handle function.

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@YukunR YukunR Nov 5, 2025

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Hi, thanks for the review!

I looked into _get_path_or_handle more closely.

get_handle is only invoked when we already know path_or_handle is a string and not a directory. For invalid inputs like a list, we never reach that branch as they get passed through stringify_path unchanged.

Also, _get_path_or_handle is only used in PyArrowImpl.read, not in FastParquetImpl.read. So if we only rely on _get_path_or_handle to validate input, validation coverage would be asymmetric across engines.

So, I propose to validate the path type in read_parquet before engine dispatch. Alternatively, I can factor a small _validate_parquet_path_arg(path) helper and call it at the top of both PyArrowImpl.read and FastParquetImpl.read

Let me know which placement you prefer.


impl = get_engine(engine)
check_dtype_backend(dtype_backend)
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36 changes: 36 additions & 0 deletions pandas/tests/io/test_parquet.py
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Original file line number Diff line number Diff line change
Expand Up @@ -248,6 +248,42 @@ def check_partition_names(path, expected):
assert dataset.partitioning.schema.names == expected


def test_read_parquet_invalid_path_types(tmp_path, engine):
# GH #62922
df = pd.DataFrame({"a": [1]})
path = tmp_path / "test_read_parquet.parquet"
df.to_parquet(path, engine=engine)

bad_path_types = [
[str(path)], # list
(str(path),), # tuple
b"raw-bytes", # bytes
]
Comment on lines +257 to +261
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@mroeschke mroeschke Nov 4, 2025

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Testing the list case is sufficient

for bad in bad_path_types:
match = (
f"read_parquet expected str/os.PathLike or file-like object, "
f"got {type(bad).__name__} type"
)
with pytest.raises(TypeError, match=match):
read_parquet(bad, engine=engine)


def test_read_parquet_valid_path_types(tmp_path, engine):
# GH #62922
df = pd.DataFrame({"a": [1]})
path = tmp_path / "test_read_parquet.parquet"
df.to_parquet(path, engine=engine)
# str
read_parquet(str(path), engine=engine)
# os.PathLike
read_parquet(pathlib.Path(path), engine=engine)
# file-like object
buf = BytesIO()
df.to_parquet(buf, engine=engine)
buf.seek(0)
read_parquet(buf, engine=engine)
Comment on lines +271 to +284
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@mroeschke mroeschke Nov 4, 2025

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This test is not needed



def test_invalid_engine(df_compat, temp_file):
msg = "engine must be one of 'pyarrow', 'fastparquet'"
with pytest.raises(ValueError, match=msg):
Expand Down
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