Pandas BUG: Calling dict(df.groupby(...)) raises TypeError: 'str' object is not callable despite valid inputs

Pandas version checks

[x] I have checked that this issue has not already been reported.
[x] 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

import pandas as pd

df = pd.DataFrame({
    'security': ['A', 'B'],
    'price': [1, 2]
})

print(dict(df.groupby('security')))  # ❌ Raises TypeError


Using a comprehension works fine:

res = {k: v for k, v in df.groupby('security')}  # ✅ Succeeds

Verifying the iteration:

for k, v in df.groupby('security'):
    print(type(k), type(v))  # <class 'str'>, <class 'DataFrame'>

Issue Description

When using the built-in dict() constructor on a DataFrameGroupBy object returned by pandas.DataFrame.groupby(...), I get:

TypeError: 'str' object is not callable

This occurs even though the iterable yields valid (str, DataFrame) pairs, and built-in dict is not shadowed.

Environment Info

Item	Value
pandas version	2.3.0
Python version	3.12.3
Install method	poetry
OS	Ubuntu 22.04
Reproducible in venv	✅ Yes
Reproducible in clean script	✅ Yes

Additional Notes

dict is and matches builtins.dict
Removing pycache and .pyc files does not help
The error only occurs when using dict(df.groupby(...)), not in other contexts
inspect.getmodule(dict) returns the expected built-in location

This could potentially be a pandas bug, interpreter-edge case, or a low-level compatibility glitch with Python 3.12+. Please let me know if you'd like a deeper trace or full traceback logs!

Expected Behavior

{ 'A': pd.DataFrame(...), 'B': pd.DataFrame(...) }

Installed Versions