# Source code for dataclass_wizard.environ.dumpers

    from typing import List, Any, Optional, Callable, Dict, Type, TYPE_CHECKING
    if TYPE_CHECKING:
        from collections.abc import Collection

    from .loaders import EnvLoader
    from .. import EnvMeta
    from ..bases import AbstractEnvMeta, META
    from ..class_helper import (
        dataclass_field_to_default,
        dataclass_field_to_json_field,
        CLASS_TO_DUMP_FUNC, _META, dataclass_field_to_load_parser, dataclass_field_to_json_path, dataclass_field_names,
        dataclass_field_to_skip_if, is_builtin, setup_dump_config_for_cls_if_needed, get_meta,
    )
    from ..constants import CATCH_ALL, TAG
    # TODO
    #from ..dumpers import get_dumper, _asdict_inner
    from ..dumpers import _asdict_inner
    from ..loader_selection import get_dumper
    from ..enums import LetterCase
    from ..errors import show_deprecation_warning
    from ..models import Condition, get_skip_if_condition, finalize_skip_if
    from ..type_def import ExplicitNull, JSONObject, T
    from ..utils.dataclass_compat import _set_new_attribute
    from ..utils.dict_helper import NestedDict
    from ..utils.function_builder import FunctionBuilder

    def asdict(o: T,
               *, cls=None,
               dict_factory=dict,
               exclude: 'Collection[str] | None' = None,
               **kwargs) -> JSONObject:
        # noinspection PyUnresolvedReferences
        """Return the fields of an instance of a `EnvWizard` subclass as a new
        dictionary mapping field names to field values.

        Example usage::

          class MyEnv(EnvWizard):
              x: int
              y: str

          env = MyEnv()
          serialized = asdict(env)

        When directly invoking this function, an optional Meta configuration for
        the `EnvWizard` subclass can be specified via ``EnvMeta``; by default,
        this will apply recursively to any nested subclasses. Here's a sample
        usage of this below::

            >>> EnvMeta(key_transform_with_dump='CAMEL').bind_to(MyClass)
            >>> asdict(MyClass(my_str="value"))

        If given, 'dict_factory' will be used instead of built-in dict.
        The function applies recursively to field values that are
        `EnvWizard` subclasses. This will also look into built-in containers:
        tuples, lists, and dicts.
        """
        # This likely won't be needed, as ``dataclasses.fields`` already has this
        # check.
        # if not _is_dataclass_instance(obj):
        #     raise TypeError("asdict() should be called on dataclass instances")

        cls = cls or type(o)

        try:
            dump = CLASS_TO_DUMP_FUNC[cls]
        except KeyError:
            dump = dump_func_for_dataclass(cls)

        return dump(o, dict_factory, exclude, **kwargs)

    def dump_func_for_dataclass(cls: Type['E'],
                                config: Optional[META] = None,
                                nested_cls_to_dump_func: Optional[Dict[Type, Any]] = None,
                                ) -> Callable[['E', Any, Any, Any], JSONObject]:

        # TODO dynamically generate for multiple nested classes at once

        # Get the dumper for the class, or create a new one as needed.
        cls_dumper = get_dumper(cls)

        # Get the meta config for the class, or the default config otherwise.
        meta = get_meta(cls, AbstractEnvMeta)

        # Check if we're being run for the main dataclass or for a nested one.
        is_main_class = nested_cls_to_dump_func is None

        if is_main_class:  # we are being run for the main dataclass
            nested_cls_to_dump_func = {}
            # If the `recursive` flag is enabled and a Meta config is provided,
            # apply the Meta recursively to any nested classes.
            if meta.recursive and meta is not AbstractEnvMeta:
                config = meta

        # we are being run for a nested dataclass
        elif config:
            # we want to apply the meta config from the main dataclass
            # recursively.
            meta = meta | config
            meta.bind_to(cls, is_default=False)

        # This contains the dump hooks for the dataclass. If the class
        # sub-classes from `DumpMixIn`, these hooks could be customized.
        hooks = cls_dumper.__DUMP_HOOKS__

        # Set up the initial dump config for the dataclass.
        setup_dump_config_for_cls_if_needed(cls)

        # A cached mapping of each dataclass field to the resolved key name in a
        # JSON or dictionary object; useful so we don't need to do a case
        # transformation (via regex) each time.
        dataclass_to_json_field = dataclass_field_to_json_field(cls)

        # A cached mapping of dataclass field name to its default value, either
        # via a `default` or `default_factory` argument.
        field_to_default = dataclass_field_to_default(cls)

        # A cached mapping of dataclass field name to its SkipIf condition.
        field_to_skip_if = dataclass_field_to_skip_if(cls)

        # A collection of field names in the dataclass.
        field_names = dataclass_field_names(cls)

        # TODO: Check if we need to auto-assign tags for dataclasses in `Union` types.
        # if meta.auto_assign_tags:
        #     # Unfortunately, we can't handle this as part of the dump process, as
        #     # we don't process the class annotations here. So instead, generate
        #     # the load parser for each field  (if needed), but don't cache the
        #     # result, as it's conceivable we might yet call `LoadMeta` later.
        #     from ..loaders import get_loader
        #     cls_loader = get_loader(cls, base_cls=EnvLoader)
        #     # Use the cached result if it exists, but don't cache it ourselves.
        #     _ = dataclass_field_to_load_parser(
        #         cls_loader, cls, config, save=False)

        # Tag key to populate when a dataclass is in a `Union` with other types.
        # tag_key = meta.tag_key or TAG

        catch_all_field = dataclass_to_json_field.get(CATCH_ALL)
        has_catch_all = catch_all_field is not None

        field_to_path = dataclass_field_to_json_path(cls)
        num_paths = len(field_to_path)
        has_json_paths = True if num_paths else False

        skip_defaults = True if meta.skip_defaults or meta.skip_defaults_if else False

        _locals = {
            'config': config,
            'asdict': _asdict_inner,
            'hooks': hooks,
            'cls_to_asdict': nested_cls_to_dump_func,
            'cls_dump_fn': dump_func_for_dataclass,
        }

        _globals = {
            'T': T,
        }

        skip_if_condition = get_skip_if_condition(
            meta.skip_if, _locals, '_skip_value')

        skip_defaults_if_condition = get_skip_if_condition(
            meta.skip_defaults_if, _locals, '_skip_defaults_value')

        # Initialize FuncBuilder
        fn_gen = FunctionBuilder()

        # Code for `cls_asdict`
        with fn_gen.function('cls_asdict',
                             ['o:T',
                              'dict_factory=dict',
                              "exclude:'list[str]|None'=None",
                              f'skip_defaults:bool={skip_defaults}'],
                             'JSONObject',
                             _locals):

            if (
                _pre_dict := getattr(cls, '_pre_dict', None)
            ) is not None:
                # class defines a `_pre_dict()`
                _locals['__pre_dict__'] = _pre_dict
                fn_gen.add_line('__pre_dict__(o)')
            elif (
                _pre_dict := getattr(cls_dumper, '__pre_as_dict__', None)
            ) is not None:
                # deprecated since v0.28.0
                # subclass of `DumpMixin` defines a `__pre_as_dict__()`
                reason = "use `_pre_dict` instead - no need to subclass from DumpMixin"
                show_deprecation_warning(_pre_dict, reason)

                _locals['__pre_dict__'] = _pre_dict

                # Call the optional hook that runs before we process the dataclass
                fn_gen.add_line('__pre_dict__(o)')

            # Initialize result list to hold field mappings
            fn_gen.add_line("result = []")

            if has_json_paths:
                _locals['NestedDict'] = NestedDict
                fn_gen.add_line('paths = NestedDict()')

            if field_names:

                skip_field_assignments = []
                exclude_assignments = []
                skip_default_assignments = []
                field_assignments = []

                # Loop over the dataclass fields
                for i, field in enumerate(field_names):
                    skip_field = f'_skip_{i}'
                    skip_if_field = f'_skip_if_{i}'
                    default_value = f'_default_{i}'

                    skip_field_assignments.append(skip_field)
                    exclude_assignments.append(
                        f'{skip_field}={field!r} in exclude'
                    )
                    if field in field_to_default:
                        if skip_defaults_if_condition:
                            _final_skip_if = finalize_skip_if(
                                meta.skip_defaults_if, f'o.{field}', skip_defaults_if_condition)
                            skip_default_assignments.append(
                                f"{skip_field} = {skip_field} or {_final_skip_if}"
                            )
                        else:
                            _locals[default_value] = field_to_default[field]
                            skip_default_assignments.append(
                                f"{skip_field} = {skip_field} or o.{field} == {default_value}"
                            )

                    # Get the resolved JSON field name
                    try:
                        json_field = dataclass_to_json_field[field]
                    except KeyError:
                        # Normalize the dataclass field name (by default to camel
                        # case)
                        json_field = cls_dumper.transform_dataclass_field(field)
                        dataclass_to_json_field[field] = json_field

                    # Exclude any dataclass fields that are explicitly ignored.
                    if json_field is not ExplicitNull:
                        # If field has an explicit `SkipIf` condition
                        if field in field_to_skip_if:
                            _skip_condition = field_to_skip_if[field]
                            _skip_if = get_skip_if_condition(
                                _skip_condition, _locals, skip_if_field)
                            _final_skip_if = finalize_skip_if(
                                _skip_condition, f'o.{field}', _skip_if)
                            field_assignments.append(f'if not ({skip_field} or {_final_skip_if}):')
                        # If Meta `skip_if` has a value
                        elif skip_if_condition:
                            _final_skip_if = finalize_skip_if(
                                meta.skip_if, f'o.{field}', skip_if_condition)
                            field_assignments.append(f'if not ({skip_field} or {_final_skip_if}):')
                        # Else, proceed as normal
                        else:
                            field_assignments.append(f"if not {skip_field}:")

                        if json_field:
                            field_assignments.append(f"  result.append(('{json_field}',"
                                                     f"asdict(o.{field},dict_factory,hooks,config,cls_to_asdict,cls_dump_fn)))")
                        # Empty string, will be the case for a dataclass
                        # field which specifies a "JSON Path".
                        else:
                            path = field_to_path[field]
                            key_part = ''.join(f'[{p!r}]' for p in path)
                            field_assignments.append(
                                f'  paths{key_part} = asdict(o.{field},dict_factory,hooks,config,cls_to_asdict,cls_dump_fn)')

                    elif has_catch_all and catch_all_field == field:
                        if field in field_to_default:
                            field_assignments.append(f"if o.{field} != {default_value} and not {skip_field}:")
                        else:
                            field_assignments.append(f"if not {skip_field}:")
                        field_assignments.append(f"  for k, v in o.{field}.items():")
                        field_assignments.append("    result.append((k,"
                                                 "asdict(v,dict_factory,hooks,config,cls_to_asdict,cls_dump_fn)))")

                with fn_gen.if_('exclude is None'):
                    fn_gen.add_line('='.join(skip_field_assignments) + '=False')
                with fn_gen.else_():
                    fn_gen.add_line(';'.join(exclude_assignments))

                if skip_default_assignments:
                    with fn_gen.if_('skip_defaults'):
                        fn_gen.add_lines(*skip_default_assignments)

                fn_gen.add_lines(*field_assignments)

            if has_json_paths:
                fn_gen.add_line("result and paths.update(result); result = paths")

            # Return the final dictionary result
            # if meta.tag:
            #     fn_gen.add_line("result = dict_factory(result)")
            #     fn_gen.add_line(f"result[{tag_key!r}] = {meta.tag!r}")
            #     # Return the result with the tag added
            #     fn_gen.add_line("return result")
            # else:
            fn_gen.add_line("return dict_factory(result)")

        # Compile the code into a dynamic string
        functions = fn_gen.create_functions(_globals)

        cls_asdict = functions['cls_asdict']

        asdict_func = cls_asdict

        # In any case, save the dump function for the class, so we don't need to
        # run this logic each time.
        if is_main_class:
            # Check if the class has a `to_dict`, and it's
            # equivalent to `asdict`.
            if getattr(cls, 'to_dict', None) is asdict:
                _set_new_attribute(cls, 'to_dict', asdict_func)
            CLASS_TO_DUMP_FUNC[cls] = asdict_func
        else:
            nested_cls_to_dump_func[cls] = asdict_func

        return asdict_func