BUG: maximum recursion depth in eval when using bool object

[wiso]

• I have checked that this issue has not already been reported.

• I have confirmed this bug exists on the latest version of pandas.

• (optional) I have confirmed this bug exists on the master branch of pandas.

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Code Sample, a copy-pastable example

import pandas as pd
df = pd.DataFrame({"col1": [True] * 50, "col2": [2] * 50})
df["col1"] = df["col1"].astype("object")  
df.eval("col1 & (col2!=2)")

Problem description

RecursionError: maximum recursion depth exceeded while calling a Python object

"col1" in the example is casted to object bool since in my real example I have nan.

Maybe similar to #27639

Output of pd.show_versions()

INSTALLED VERSIONS ------------------ commit : None python : 3.7.6.final.0 python-bits : 64 OS : Linux OS-release : 5.4.15-200.fc31.x86_64 machine : x86_64 processor : x86_64 byteorder : little LC_ALL : None LANG : it_IT.UTF-8 LOCALE : it_IT.UTF-8

pandas : 1.0.3
numpy : 1.18.1
pytz : 2019.2
dateutil : 2.7.5
pip : 20.1
setuptools : 41.6.0
Cython : 0.29.15
pytest : 4.0.0
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.4.0
html5lib : 1.0.1
pymysql : None
psycopg2 : None
jinja2 : 2.10
IPython : 7.3.0
pandas_datareader: 0.8.0
bs4 : 4.7.1
bottleneck : 1.2.1
fastparquet : None
gcsfs : None
lxml.etree : 4.4.0
matplotlib : 3.1.3
numexpr : 2.7.1
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pytables : None
pytest : 4.0.0
pyxlsb : None
s3fs : 0.4.2
scipy : 1.2.1
sqlalchemy : None
tables : 3.5.2
tabulate : 0.8.5
xarray : 0.12.1
xlrd : 1.2.0
xlwt : 1.1.2
xlsxwriter : None
numba : 0.48.0

[justynatrojniak]

Not sure if this helps but try increase the capacity of the stack by the following :

import sys
sys.setrecursionlimit(10000)

[CloseChoice]

Nope, that doesnt help. We are calling and recalling the same stuff here. This definitely needs a fix.

[stayfools]

I have the same problem with pandas==1.0.4, and it's about string object:

import pandas as pd
df = pd.DataFrame({'A':list('abc'), 'B':list('def')})
df.eval('A+B')

But it works well with pandas==1.0.1.

[mutricyl]

Could not reproduce the issue with pandas 2.2.0

[wiso]

@mutricyl you are correct. It works also with 2.1.3.
By the way I can reproduce with 1.5.3
I am closing this