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DEPR: deprecated nonkeyword arguments in to_json #54613

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Aug 18, 2023
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1 change: 1 addition & 0 deletions doc/source/whatsnew/v2.2.0.rst
Original file line number Diff line number Diff line change
Expand Up @@ -93,6 +93,7 @@ Other API changes
Deprecations
~~~~~~~~~~~~
- Deprecated allowing non-keyword arguments in :meth:`DataFrame.to_hdf` except ``path_or_buf``. (:issue:`54229`)
- Deprecated allowing non-keyword arguments in :meth:`DataFrame.to_json` except ``path_or_buf``. (:issue:`54229`)
- Deprecated allowing non-keyword arguments in :meth:`DataFrame.to_latex` except ``buf``. (:issue:`54229`)
- Deprecated allowing non-keyword arguments in :meth:`DataFrame.to_pickle` except ``path``. (:issue:`54229`)
- Deprecated allowing non-keyword arguments in :meth:`DataFrame.to_string` except ``buf``. (:issue:`54229`)
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3 changes: 3 additions & 0 deletions pandas/core/generic.py
Original file line number Diff line number Diff line change
Expand Up @@ -2352,6 +2352,9 @@ def to_excel(
)

@final
@deprecate_nonkeyword_arguments(
version="3.0", allowed_args=["self", "path_or_buf"], name="to_json"
)
@doc(
storage_options=_shared_docs["storage_options"],
compression_options=_shared_docs["compression_options"] % "path_or_buf",
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17 changes: 16 additions & 1 deletion pandas/tests/io/json/test_pandas.py
Original file line number Diff line number Diff line change
@@ -1,7 +1,10 @@
import datetime
from datetime import timedelta
from decimal import Decimal
from io import StringIO
from io import (
BytesIO,
StringIO,
)
import json
import os
import sys
Expand Down Expand Up @@ -2106,3 +2109,15 @@ def test_json_roundtrip_string_inference(orient):
columns=pd.Index(["col 1", "col 2"], dtype=pd.ArrowDtype(pa.string())),
)
tm.assert_frame_equal(result, expected)


def test_json_pos_args_deprecation():
# GH-54229
df = DataFrame({"a": [1, 2, 3]})
msg = (
r"Starting with pandas version 3.0 all arguments of to_json except for the "
r"argument 'path_or_buf' will be keyword-only."
)
with tm.assert_produces_warning(FutureWarning, match=msg):
buf = BytesIO()
df.to_json(buf, "split")