No OverflowError when reading int longer than C long with pd.read_json()

[MadsAdrian]

Code Sample

import pandas as pd
big_int = 2147483647 + 1
json_string = '[{"A": "' + str(big_int) + '"}]'
df = pd.read_json(json_string)

Problem description

No error when loading int longer than C long. In contrast,
df = pd.DataFrame(json.loads(json_string)).astype(int)
raises the expected error.

Expected Output

OverflowError: Python int too large to convert to C long

Output of pd.show_versions()

INSTALLED VERSIONS

commit: None
python: 3.6.5.final.0
python-bits: 32
OS: Windows
OS-release: 10
machine: AMD64
processor: Intel64 Family 6 Model 58 Stepping 9, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None

pandas: 0.23.4
pytest: None
pip: 18.0
setuptools: 39.0.1
Cython: None
numpy: 1.15.0
scipy: 1.1.0
pyarrow: None
xarray: None
IPython: None
sphinx: None
patsy: None
dateutil: 2.7.3
pytz: 2018.4
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: 2.2.2
openpyxl: 2.5.4
xlrd: 1.1.0
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: None
sqlalchemy: 1.2.10
pymysql: None
psycopg2: 2.7.5 (dt dec pq3 ext)
jinja2: None
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None

[TomAugspurger]

Dupe of #20599 I believe, if you want to take a read through that. It's a bit tricky.

[MadsAdrian]

@TomAugspurger I'm not certain it's a dupe, but certainly related. Seems to me #20599 relates to the need of raising the error in the first place, and calls for using some other datatype than a C long internally when the int in question is outside [-2³¹+1, 2³¹-1]. This doesn't seem to be solved in 0.23.4, but the error is not raised anymore (maybe related to some work done on #20599). Loading big_int = 2147483647 + 1 into an python int works, but a C long gives no guaranty of correctness. In my opinion, loading an int into a df from json that can't be represented in the used datatype should at least raise a warning, but preferably an error .