1from __future__ import annotations
2
3import functools
4from collections import namedtuple
5from collections.abc import Generator
6from typing import Any
7
8
9def make_model_tuple(model: Any) -> tuple[str, str]:
10 """
11 Take a model or a string of the form "package_label.ModelName" and return a
12 corresponding ("package_label", "modelname") tuple. If a tuple is passed in,
13 assume it's a valid model tuple already and return it unchanged.
14 """
15 try:
16 if isinstance(model, tuple):
17 model_tuple = model
18 elif isinstance(model, str):
19 package_label, model_name = model.split(".")
20 model_tuple = package_label, model_name.lower()
21 else:
22 model_tuple = (
23 model.model_options.package_label,
24 model.model_options.model_name,
25 )
26 assert len(model_tuple) == 2
27 return model_tuple
28 except (ValueError, AssertionError):
29 raise ValueError(
30 f"Invalid model reference '{model}'. String model references "
31 "must be of the form 'package_label.ModelName'."
32 )
33
34
35def resolve_callables(
36 mapping: dict[str, Any],
37) -> Generator[tuple[str, Any], None, None]:
38 """
39 Generate key/value pairs for the given mapping where the values are
40 evaluated if they're callable.
41 """
42 for k, v in mapping.items():
43 yield k, v() if callable(v) else v
44
45
46def unpickle_named_row(
47 names: tuple[str, ...], values: tuple[Any, ...]
48) -> tuple[Any, ...]:
49 return create_namedtuple_class(*names)(*values)
50
51
52@functools.lru_cache
53def create_namedtuple_class(*names: str) -> type[tuple[Any, ...]]:
54 # Cache type() with @lru_cache since it's too slow to be called for every
55 # QuerySet evaluation.
56 def __reduce__(self: Any) -> tuple[Any, tuple[tuple[str, ...], tuple[Any, ...]]]:
57 return unpickle_named_row, (names, tuple(self))
58
59 return type(
60 "Row",
61 (namedtuple("Row", names),),
62 {"__reduce__": __reduce__, "__slots__": ()},
63 )