5e0a761b87
(for upgrading users, please see the notes at the bottom) Bazel brought a lot of nice things to the table, such as rebuilds based on content changes instead of modification times, caching of build products, detection of incorrect build rules via a sandbox, and so on. Rewriting the build in Bazel was also an opportunity to improve on the Makefile-based build we had prior, which was pretty poor: most dependencies were external or not pinned, and the build graph was poorly defined and mostly serialized. It was not uncommon for fresh checkouts to fail due to floating dependencies, or for things to break when trying to switch to an older commit. For day-to-day development, I think Bazel served us reasonably well - we could generally switch between branches while being confident that builds would be correct and reasonably fast, and not require full rebuilds (except on Windows, where the lack of a sandbox and the TS rules would cause build breakages when TS files were renamed/removed). Bazel achieves that reliability by defining rules for each programming language that define how source files should be turned into outputs. For the rules to work with Bazel's sandboxing approach, they often have to reimplement or partially bypass the standard tools that each programming language provides. The Rust rules call Rust's compiler directly for example, instead of using Cargo, and the Python rules extract each PyPi package into a separate folder that gets added to sys.path. These separate language rules allow proper declaration of inputs and outputs, and offer some advantages such as caching of build products and fine-grained dependency installation. But they also bring some downsides: - The rules don't always support use-cases/platforms that the standard language tools do, meaning they need to be patched to be used. I've had to contribute a number of patches to the Rust, Python and JS rules to unblock various issues. - The dependencies we use with each language sometimes make assumptions that do not hold in Bazel, meaning they either need to be pinned or patched, or the language rules need to be adjusted to accommodate them. I was hopeful that after the initial setup work, things would be relatively smooth-sailing. Unfortunately, that has not proved to be the case. Things frequently broke when dependencies or the language rules were updated, and I began to get frustrated at the amount of Anki development time I was instead spending on build system upkeep. It's now about 2 years since switching to Bazel, and I think it's time to cut losses, and switch to something else that's a better fit. The new build system is based on a small build tool called Ninja, and some custom Rust code in build/. This means that to build Anki, Bazel is no longer required, but Ninja and Rust need to be installed on your system. Python and Node toolchains are automatically downloaded like in Bazel. This new build system should result in faster builds in some cases: - Because we're using cargo to build now, Rust builds are able to take advantage of pipelining and incremental debug builds, which we didn't have with Bazel. It's also easier to override the default linker on Linux/macOS, which can further improve speeds. - External Rust crates are now built with opt=1, which improves performance of debug builds. - Esbuild is now used to transpile TypeScript, instead of invoking the TypeScript compiler. This results in faster builds, by deferring typechecking to test/check time, and by allowing more work to happen in parallel. As an example of the differences, when testing with the mold linker on Linux, adding a new message to tags.proto (which triggers a recompile of the bulk of the Rust and TypeScript code) results in a compile that goes from about 22s on Bazel to about 7s in the new system. With the standard linker, it's about 9s. Some other changes of note: - Our Rust workspace now uses cargo-hakari to ensure all packages agree on available features, preventing unnecessary rebuilds. - pylib/anki is now a PEP420 implicit namespace, avoiding the need to merge source files and generated files into a single folder for running. By telling VSCode about the extra search path, code completion now works with generated files without needing to symlink them into the source folder. - qt/aqt can't use PEP420 as it's difficult to get rid of aqt/__init__.py. Instead, the generated files are now placed in a separate _aqt package that's added to the path. - ts/lib is now exposed as @tslib, so the source code and generated code can be provided under the same namespace without a merging step. - MyPy and PyLint are now invoked once for the entire codebase. - dprint will be used to format TypeScript/json files in the future instead of the slower prettier (currently turned off to avoid causing conflicts). It can automatically defer to prettier when formatting Svelte files. - svelte-check is now used for typechecking our Svelte code, which revealed a few typing issues that went undetected with the old system. - The Jest unit tests now work on Windows as well. If you're upgrading from Bazel, updated usage instructions are in docs/development.md and docs/build.md. A summary of the changes: - please remove node_modules and .bazel - install rustup (https://rustup.rs/) - install rsync if not already installed (on windows, use pacman - see docs/windows.md) - install Ninja (unzip from https://github.com/ninja-build/ninja/releases/tag/v1.11.1 and place on your path, or from your distro/homebrew if it's 1.10+) - update .vscode/settings.json from .vscode.dist
205 lines
7.2 KiB
Python
205 lines
7.2 KiB
Python
# Copyright: Ankitects Pty Ltd and contributors
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# License: GNU AGPL, version 3 or later; http://www.gnu.org/licenses/agpl.html
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from __future__ import annotations
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import functools
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import os
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import pathlib
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import sys
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import traceback
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from typing import TYPE_CHECKING, Any, Callable, Union
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from anki._vendor import stringcase # type: ignore
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sys.modules["stringcase"] = stringcase
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VariableTarget = tuple[Any, str]
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DeprecatedAliasTarget = Union[Callable, VariableTarget]
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def _target_to_string(target: DeprecatedAliasTarget | None) -> str:
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if target is None:
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return ""
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if name := getattr(target, "__name__", None):
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return name
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return target[1] # type: ignore
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def partial_path(full_path: str, components: int) -> str:
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path = pathlib.Path(full_path)
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return os.path.join(*path.parts[-components:])
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def print_deprecation_warning(msg: str, frame: int = 1) -> None:
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# skip one frame to get to caller
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# then by default, skip one more frame as caller themself usually wants to
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# print their own caller
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path, linenum, _, _ = traceback.extract_stack(limit=frame + 2)[0]
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path = partial_path(path, components=3)
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print(f"{path}:{linenum}:{msg}")
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def _print_warning(old: str, doc: str, frame: int = 1) -> None:
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return print_deprecation_warning(f"{old} is deprecated: {doc}", frame=frame + 1)
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def _print_replacement_warning(old: str, new: str, frame: int = 1) -> None:
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doc = f"please use '{new}'" if new else "please implement your own"
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_print_warning(old, doc, frame=frame + 1)
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def _get_remapped_and_replacement(
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mixin: DeprecatedNamesMixin | DeprecatedNamesMixinForModule, name: str
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) -> tuple[str, str | None]:
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if some_tuple := mixin._deprecated_attributes.get(name):
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return some_tuple
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remapped = mixin._deprecated_aliases.get(name) or stringcase.snakecase(name)
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if remapped == name:
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raise AttributeError
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return (remapped, remapped)
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class DeprecatedNamesMixin:
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"Expose instance methods/vars as camelCase for legacy callers."
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# deprecated name -> new name
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_deprecated_aliases: dict[str, str] = {}
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# deprecated name -> [new internal name, new name shown to user]
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_deprecated_attributes: dict[str, tuple[str, str | None]] = {}
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# TYPE_CHECKING check is required for https://github.com/python/mypy/issues/13319
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if not TYPE_CHECKING:
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def __getattr__(self, name: str) -> Any:
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try:
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remapped, replacement = _get_remapped_and_replacement(self, name)
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out = getattr(self, remapped)
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except AttributeError:
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raise AttributeError(
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f"'{self.__class__.__name__}' object has no attribute '{name}'"
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) from None
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_print_replacement_warning(name, replacement)
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return out
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@classmethod
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def register_deprecated_aliases(cls, **kwargs: DeprecatedAliasTarget) -> None:
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"""Manually add aliases that are not a simple transform.
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Either pass in a method, or a tuple of (variable, "variable"). The
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latter is required because we want to ensure the provided arguments
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are valid symbols, and we can't get a variable's name easily.
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"""
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cls._deprecated_aliases = {k: _target_to_string(v) for k, v in kwargs.items()}
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@classmethod
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def register_deprecated_attributes(
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cls,
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**kwargs: tuple[DeprecatedAliasTarget, DeprecatedAliasTarget | None],
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) -> None:
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"""Manually add deprecated attributes without exact substitutes.
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Pass a tuple of (alias, replacement), where alias is the attribute's new
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name (by convention: snakecase, prepended with '_legacy_'), and
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replacement is any callable to be used instead in new code or None.
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Also note the docstring of `register_deprecated_aliases`.
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E.g. given `def oldFunc(args): return new_func(additionalLogic(args))`,
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rename `oldFunc` to `_legacy_old_func` and call
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`register_deprecated_attributes(oldFunc=(_legacy_old_func, new_func))`.
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"""
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cls._deprecated_attributes = {
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k: (_target_to_string(v[0]), _target_to_string(v[1]))
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for k, v in kwargs.items()
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}
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class DeprecatedNamesMixinForModule:
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"""Provides the functionality of DeprecatedNamesMixin for modules.
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It can be invoked like this:
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```
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_deprecated_names = DeprecatedNamesMixinForModule(globals())
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_deprecated_names.register_deprecated_aliases(...
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_deprecated_names.register_deprecated_attributes(...
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if not TYPE_CHECKING:
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def __getattr__(name: str) -> Any:
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return _deprecated_names.__getattr__(name)
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```
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See DeprecatedNamesMixin for more documentation.
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"""
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def __init__(self, module_globals: dict[str, Any]) -> None:
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self.module_globals = module_globals
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self._deprecated_aliases: dict[str, str] = {}
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self._deprecated_attributes: dict[str, tuple[str, str | None]] = {}
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if not TYPE_CHECKING:
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def __getattr__(self, name: str) -> Any:
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try:
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remapped, replacement = _get_remapped_and_replacement(self, name)
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out = self.module_globals[remapped]
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except (AttributeError, KeyError):
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raise AttributeError(
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f"Module '{self.module_globals['__name__']}' has no attribute '{name}'"
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) from None
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# skip an additional frame as we are called from the module `__getattr__`
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_print_replacement_warning(name, replacement, frame=2)
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return out
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def register_deprecated_aliases(self, **kwargs: DeprecatedAliasTarget) -> None:
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self._deprecated_aliases = {k: _target_to_string(v) for k, v in kwargs.items()}
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def register_deprecated_attributes(
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self,
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**kwargs: tuple[DeprecatedAliasTarget, DeprecatedAliasTarget | None],
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) -> None:
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self._deprecated_attributes = {
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k: (_target_to_string(v[0]), _target_to_string(v[1]))
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for k, v in kwargs.items()
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}
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def deprecated(replaced_by: Callable | None = None, info: str = "") -> Callable:
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"""Print a deprecation warning, telling users to use `replaced_by`, or show `doc`."""
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def decorator(func: Callable) -> Callable:
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@functools.wraps(func)
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def decorated_func(*args: Any, **kwargs: Any) -> Any:
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if info:
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_print_warning(f"{func.__name__}()", info)
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else:
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_print_replacement_warning(func.__name__, replaced_by.__name__)
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return func(*args, **kwargs)
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return decorated_func
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return decorator
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def deprecated_keywords(**replaced_keys: str) -> Callable:
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"""Pass `oldKey="new_key"` to map the former to the latter, if passed to the
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decorated function as a key word, and print a deprecation warning.
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"""
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def decorator(func: Callable) -> Callable:
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@functools.wraps(func)
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def decorated_func(*args: Any, **kwargs: Any) -> Any:
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updated_kwargs = {}
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for key, val in kwargs.items():
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if replacement := replaced_keys.get(key):
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_print_replacement_warning(key, replacement)
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updated_kwargs[replacement or key] = val
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return func(*args, **updated_kwargs)
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return decorated_func
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return decorator
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