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import re | |
from typing import Any, Optional, Type, TypeVar | |
from dataclasses import is_dataclass | |
import attr | |
from attr import NOTHING, resolve_types | |
from ._compat import get_args, get_origin, is_generic, adapted_fields | |
class AttributeOverride(object): | |
omit_if_default: Optional[bool] = attr.ib(default=None) | |
rename: Optional[str] = attr.ib(default=None) | |
def override(omit_if_default=None, rename=None): | |
return AttributeOverride(omit_if_default=omit_if_default, rename=rename) | |
_neutral = AttributeOverride() | |
def make_dict_unstructure_fn(cl, converter, omit_if_default=False, **kwargs): | |
"""Generate a specialized dict unstructuring function for an attrs class.""" | |
cl_name = cl.__name__ | |
fn_name = "unstructure_" + cl_name | |
globs = {} | |
lines = [] | |
post_lines = [] | |
attrs = adapted_fields(cl) # type: ignore | |
lines.append(f"def {fn_name}(i):") | |
lines.append(" res = {") | |
for a in attrs: | |
attr_name = a.name | |
override = kwargs.pop(attr_name, _neutral) | |
kn = attr_name if override.rename is None else override.rename | |
d = a.default | |
# For each attribute, we try resolving the type here and now. | |
# If a type is manually overwritten, this function should be | |
# regenerated. | |
if a.type is not None: | |
handler = converter._unstructure_func.dispatch(a.type) | |
else: | |
handler = converter.unstructure | |
is_identity = handler == converter._unstructure_identity | |
if not is_identity: | |
unstruct_handler_name = f"__cattr_unstruct_handler_{attr_name}" | |
globs[unstruct_handler_name] = handler | |
invoke = f"{unstruct_handler_name}(i.{attr_name})" | |
else: | |
invoke = f"i.{attr_name}" | |
if d is not attr.NOTHING and ( | |
(omit_if_default and override.omit_if_default is not False) | |
or override.omit_if_default | |
): | |
def_name = f"__cattr_def_{attr_name}" | |
if isinstance(d, attr.Factory): | |
globs[def_name] = d.factory | |
if d.takes_self: | |
post_lines.append( | |
f" if i.{attr_name} != {def_name}(i):" | |
) | |
else: | |
post_lines.append(f" if i.{attr_name} != {def_name}():") | |
post_lines.append(f" res['{kn}'] = {invoke}") | |
else: | |
globs[def_name] = d | |
post_lines.append(f" if i.{attr_name} != {def_name}:") | |
post_lines.append(f" res['{kn}'] = {invoke}") | |
else: | |
# No default or no override. | |
lines.append(f" '{kn}': {invoke},") | |
lines.append(" }") | |
total_lines = lines + post_lines + [" return res"] | |
eval(compile("\n".join(total_lines), "", "exec"), globs) | |
fn = globs[fn_name] | |
return fn | |
def generate_mapping(cl: Type, old_mapping): | |
mapping = {} | |
for p, t in zip(get_origin(cl).__parameters__, get_args(cl)): | |
if isinstance(t, TypeVar): | |
continue | |
mapping[p.__name__] = t | |
if not mapping: | |
return old_mapping | |
cls = attr.make_class( | |
"GenericMapping", | |
{x: attr.attrib() for x in mapping.keys()}, | |
frozen=True, | |
) | |
return cls(**mapping) | |
def make_dict_structure_fn( | |
cl: Type, converter, _cattrs_forbid_extra_keys: bool = False, **kwargs | |
): | |
"""Generate a specialized dict structuring function for an attrs class.""" | |
mapping = None | |
if is_generic(cl): | |
base = get_origin(cl) | |
mapping = generate_mapping(cl, mapping) | |
cl = base | |
for base in getattr(cl, "__orig_bases__", ()): | |
if is_generic(base) and not str(base).startswith("typing.Generic"): | |
mapping = generate_mapping(base, mapping) | |
break | |
if isinstance(cl, TypeVar): | |
cl = getattr(mapping, cl.__name__, cl) | |
cl_name = cl.__name__ | |
fn_name = "structure_" + cl_name | |
# We have generic parameters and need to generate a unique name for the function | |
for p in getattr(cl, "__parameters__", ()): | |
# This is nasty, I am not sure how best to handle `typing.List[str]` or `TClass[int, int]` as a parameter type here | |
name_base = getattr(mapping, p.__name__) | |
name = getattr(name_base, "__name__", str(name_base)) | |
name = re.sub(r"[\[\.\] ,]", "_", name) | |
fn_name += f"_{name}" | |
globs = {"__c_s": converter.structure, "__cl": cl, "__m": mapping} | |
lines = [] | |
post_lines = [] | |
attrs = adapted_fields(cl) | |
is_dc = is_dataclass(cl) | |
if any(isinstance(a.type, str) for a in attrs): | |
# PEP 563 annotations - need to be resolved. | |
resolve_types(cl) | |
lines.append(f"def {fn_name}(o, *_):") | |
lines.append(" res = {") | |
for a in attrs: | |
an = a.name | |
override = kwargs.pop(an, _neutral) | |
type = a.type | |
if isinstance(type, TypeVar): | |
type = getattr(mapping, type.__name__, type) | |
# For each attribute, we try resolving the type here and now. | |
# If a type is manually overwritten, this function should be | |
# regenerated. | |
if type is not None: | |
handler = converter._structure_func.dispatch(type) | |
else: | |
handler = converter.structure | |
struct_handler_name = f"__cattr_struct_handler_{an}" | |
globs[struct_handler_name] = handler | |
ian = an if (is_dc or an[0] != "_") else an[1:] | |
kn = an if override.rename is None else override.rename | |
globs[f"__c_t_{an}"] = type | |
if a.default is NOTHING: | |
lines.append( | |
f" '{ian}': {struct_handler_name}(o['{kn}'], __c_t_{an})," | |
) | |
else: | |
post_lines.append(f" if '{kn}' in o:") | |
post_lines.append( | |
f" res['{ian}'] = {struct_handler_name}(o['{kn}'], __c_t_{an})" | |
) | |
lines.append(" }") | |
if _cattrs_forbid_extra_keys: | |
allowed_fields = {a.name for a in attrs} | |
globs["__c_a"] = allowed_fields | |
post_lines += [ | |
" unknown_fields = set(o.keys()) - __c_a", | |
" if unknown_fields:", | |
" raise Exception(", | |
f" 'Extra fields in constructor for {cl_name}: ' + ', '.join(unknown_fields)" | |
" )", | |
] | |
total_lines = lines + post_lines + [" return __cl(**res)"] | |
eval(compile("\n".join(total_lines), "", "exec"), globs) | |
return globs[fn_name] | |
def make_iterable_unstructure_fn(cl: Any, converter, unstructure_to=None): | |
"""Generate a specialized unstructure function for an iterable.""" | |
handler = converter.unstructure | |
fn_name = "unstructure_iterable" | |
# Let's try fishing out the type args. | |
if getattr(cl, "__args__", None) is not None: | |
type_arg = get_args(cl)[0] | |
# We can do the dispatch here and now. | |
handler = converter._unstructure_func.dispatch(type_arg) | |
globs = {"__cattr_seq_cl": unstructure_to or cl, "__cattr_u": handler} | |
lines = [] | |
lines.append(f"def {fn_name}(iterable):") | |
lines.append(" res = __cattr_seq_cl(__cattr_u(i) for i in iterable)") | |
total_lines = lines + [" return res"] | |
eval(compile("\n".join(total_lines), "", "exec"), globs) | |
fn = globs[fn_name] | |
return fn | |
def make_mapping_unstructure_fn(cl: Any, converter, unstructure_to=None): | |
"""Generate a specialized unstructure function for a mapping.""" | |
key_handler = converter.unstructure | |
val_handler = converter.unstructure | |
fn_name = "unstructure_mapping" | |
# Let's try fishing out the type args. | |
if getattr(cl, "__args__", None) is not None: | |
args = get_args(cl) | |
if len(args) == 2: | |
key_arg, val_arg = args | |
else: | |
# Probably a Counter | |
key_arg, val_arg = args, Any | |
# We can do the dispatch here and now. | |
key_handler = converter._unstructure_func.dispatch(key_arg) | |
if key_handler == converter._unstructure_identity: | |
key_handler = None | |
val_handler = converter._unstructure_func.dispatch(val_arg) | |
if val_handler == converter._unstructure_identity: | |
val_handler = None | |
globs = { | |
"__cattr_mapping_cl": unstructure_to or cl, | |
"__cattr_k_u": key_handler, | |
"__cattr_v_u": val_handler, | |
} | |
if key_handler is not None: | |
globs["__cattr_k_u"] | |
if val_handler is not None: | |
globs["__cattr_v_u"] | |
k_u = "__cattr_k_u(k)" if key_handler is not None else "k" | |
v_u = "__cattr_v_u(v)" if val_handler is not None else "v" | |
lines = [] | |
lines.append(f"def {fn_name}(mapping):") | |
lines.append( | |
f" res = __cattr_mapping_cl(({k_u}, {v_u}) for k, v in mapping.items())" | |
) | |
total_lines = lines + [" return res"] | |
eval(compile("\n".join(total_lines), "", "exec"), globs) | |
fn = globs[fn_name] | |
return fn | |