BUG: read_json silently ignores the dtype when engine=pyarrow #59516
Labels
Bug
Dtype Conversions
Unexpected or buggy dtype conversions
IO JSON
read_json, to_json, json_normalize
Pandas version checks
I have checked that this issue has not already been reported.
I have confirmed this bug exists on the latest version of pandas.
I have confirmed this bug exists on the main branch of pandas.
Reproducible Example
Issue Description
The call to
pyarrow_json.read_json
doesn't pass anyParseOptions
. This means that determining the dtype is always left up to the pyarrow json parser's dtype inference system, even when we explicitly passed a requested dtype intopd.read_json
.Expected Behavior
read_json
's pyarrow parser should respect the requesteddtype
.Installed Versions
INSTALLED VERSIONS
commit : d9cdd2e
python : 3.12.3.final.0
python-bits : 64
OS : Windows
OS-release : 11
Version : 10.0.22631
machine : AMD64
processor : Intel64 Family 6 Model 165 Stepping 5, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : English_United Kingdom.1252
pandas : 2.2.2
numpy : 2.0.1
pytz : 2024.1
dateutil : 2.9.0.post0
setuptools : 72.1.0
pip : None
Cython : None
pytest : 8.3.2
hypothesis : None
sphinx : 7.4.7
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.1.4
IPython : 8.26.0
pandas_datareader : None
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : 4.12.3
bottleneck : None
dataframe-api-compat : None
fastparquet : None
fsspec : 2024.6.1
gcsfs : None
matplotlib : 3.9.1
numba : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 17.0.0
pyreadstat : None
python-calamine : None
pyxlsb : None
s3fs : None
scipy : 1.14.0
sqlalchemy : None
tables : None
tabulate : 0.9.0
xarray : None
xlrd : None
zstandard : None
tzdata : 2024.1
qtpy : None
pyqt5 : None
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