BUG: pd.json_normalize has inconsistent validation for non-string keys - accepts integers in some parameter combinations but rejects in others

[nocoding03]

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

import pandas as pd
data = [{"a": 1, 12: "meta_value", "nested": [{"b": 2}]}]
# This works - integer as meta  
pd.json_normalize(data, meta=[12])
# But this fails - integer as meta (with record_path)
pd.json_normalize(data, record_path=["nested"], meta=[12])

Issue Description

pd.json_normalize exhibits inconsistent behavior when using integer keys in the meta parameter:
meta=[12] (without record_path) - WORKS
record_path=["nested"], meta=[12] - FAILS with TypeError: sequence item 0: expected str instance, int found

Expected Behavior

This should either be consistently supported or consistently rejected.

Installed Versions

Replace this line with the output of pd.show_versions()

[nocoding03]

reference: #62264

[nocoding03]

@rhshadrach Could you please take a look at this issue when you have time? I‘m a little confused about this.

[Lonercode]

Pretty weird that the docs mention record_path should be a str or list of strs and this works... Maybe some internal conversion? I'd like to check it out if that's okay.

[nocoding03]

Pretty weird that the docs mention record_path should be a str or list of strs and this works... Maybe some internal conversion? I'd like to check it out if that's okay.

import pandas as pd
data1 = [{"a": 1, 13: [{"x": 1}], "nested": [{"b": 2}]}]
print(pd.json_normalize(data1, record_path=[13])) # this works
I tested this on pandas 2.3.3.