Description
Pandas version checks
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I have checked that this issue has not already been reported.
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I have confirmed this bug exists on the latest version of pandas.
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I have confirmed this bug exists on the main branch of pandas.
Reproducible Example
from pathlib import Path
import pandas
out_path = Path('tmp.xml')
def generate_xml(N):
record ='''
<outer>
<inner1>1</inner1>
<inner2>b</inner2>
</outer>
'''
with open(out_path, 'w') as f:
f.write('<?xml version="1.0" encoding="UTF-8"?>\n<root_elem>')
for i in range(1, N):
f.write(record)
f.write('</root_elem>')
## bigger files take a long time to load, but for me, the 'magic number' is between 10M and 20M:
## 20M always fails to read, 10M always succeeds
## I think more accurate predictor is file size, which needs to be over 1.2GB roughly.
## Small sanity check:
generate_xml(1000)
pandas.read_xml(out_path)
## The bug:
generate_xml(20000000)
from xml.etree import ElementTree as ET
## File is obviously valid XML, and ET can parse it
tmp = ET.parse(out_path)
## The following fails
pandas.read_xml(out_path)Issue Description
Reading big XML files, on Windows 11 (not reproduced on Linux), causes an XMLSyntaxError: switching encoding: encoder error, line 1, column 1.
Trigger size is between 1.2 - 1.6 GB.
Expected Behavior
To either parse the file or give an accurate error about running out of memory, etc. The misleading error is very frustrating when working with 3rd party XMLs where it's not inconceivable they're in the wrong encoding, causing a futile search for a problem in the file.
Installed Versions
pandas : 2.2.2
numpy : 1.26.4
pytz : 2024.1
dateutil : 2.9.0.post0
setuptools : None
pip : 24.1.1
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 5.2.2
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : None
IPython : 8.26.0
pandas_datareader : None
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : None
bottleneck : None
dataframe-api-compat : None
fastparquet : None
fsspec : None
gcsfs : None
matplotlib : None
numba : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 16.1.0
pyreadstat : None
python-calamine : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
zstandard : None
tzdata : 2024.1
qtpy : None
pyqt5 : None