from typing import List, Any, Optional, Callable, Dict, Type
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
from ..dumpers import get_dumper, _asdict_inner
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
[docs]
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)
[docs]
def dump_func_for_dataclass(cls: Type['E'],
config: Optional[META] = None,
nested_cls_to_dump_func: 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