Help on using dataclasses.field function

I want to generate dataclass code from a nested dictionary. Below is the code supplied by one AI and it doesn’t work.
The code seems troublesome but one problem really confuse me is that
when I debug it using pdb under Python3.8 and Windows10, a breakpoint at line6 won’t be hit when the recursion call at line9
was executed by “next” command.

What causes this to happen?

from dataclasses import dataclass, field, make_dataclass
from typing import Any, Dict, List

def convert_dict_to_dataclass(name: str, d: Dict[str, Any]) -> Any:
    fields = {}
    for key, value in d.items():  # line6
        if isinstance(value, dict):
            # Recursively convert nested dictionaries
            nv = field(default_factory=lambda v=value: convert_dict_to_dataclass(key.capitalize(), v))  # line9
            fields[key] = nv
            fields[key] = value

    # Create the dataclass dynamically
    klass = make_dataclass(name, fields.items())
    return klass  # line16
# Example usage
nested_dict = {
'key1': 'value1',
    'nested': {
    'key2': 'value2', 'inner_nested': {'key3': 'value3'}

DataClass = convert_dict_to_dataclass('DynamicDataClass', nested_dict)
instance = DataClass()

According to the documentation of dataclasses.make_dataclass:

fields is an iterable whose elements are each either name , (name, type) , or (name, type, Field)

And yet your AI-generated code passes fields.items() as the fields argument to make_dataclass. Since fields.items() yields tuples of (name, Field), the Field value gets incorrectly treated as type by the make_dataclass function. You should create a sequence of 3-tuples expected by make_dataclass yourself instead:

from dataclasses import field, make_dataclass
from typing import Any, Dict

def to_dataclass(name: str, d: Dict[str, Any]) -> Any:
    fields = []
    for key, value in d.items():
        if isinstance(value, dict):
            value = field(default_factory=to_dataclass(key.capitalize(), value))
        fields.append((key, type(value), value))

    return make_dataclass(name, fields)

nested_dict = {
    'key1': 'value1',
    'nested': {
        'key2': 'value2', 'inner_nested': {'key3': 'value3'}
DataClass = to_dataclass('DynamicDataClass', nested_dict)

This outputs:

DynamicDataClass(key1='value1', nested=Nested(key2='value2', inner_nested=Inner_nested(key3='value3')))

Thank you for pointing out this veiled error which I didn’t notice that the default_factory() should return an instance, not a class, to be the default value of attribute.