GeezerVison

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@youknowdot Please replace the #[pyfunction(with_module)] option and the PyMethodFlags::BIND_MODULE flag in this PR with the design below. The Clinic layout part of this PR is unaffected.

Why

In CPython every module-level C function receives its module as the first C argument (m_self); there is no opt-in. That is why every module function's __text_signature__ starts with $module (math.sqrt, _imp.exec_builtin, binascii.a2b_base64 all report ($module, ...) and __self__ is the module). A per-function option plus a Rust-only method flag emulates that with extra metadata instead of making it the structure.

Design

1. Every module function receives its module. Internally, a #[pyfunction] in a #[pymodule] always gets its defining module as the receiver.
2. Transport it like vm, not through FuncArgs. Pass the module out of band, the way &VirtualMachine is passed beside FuncArgs today: either an extra parameter of the native call ABI (PyNativeFn is currently Fn(&VirtualMachine, FuncArgs, Callee)) or a field of Callee; your choice. Do not use args.prepend_arg(...) for module functions: functions that do not use the module must pay nothing on the hot path. Method receivers keep their current path; this change is for module functions only.
3. Declare it by type, injected like vm. In the #[pyfunction] macro, if the first Rust parameter is PyRef<PyModule> or &Py<PyModule>, it is the receiver and is excluded from the Python signature. Otherwise the generated binding accepts the receiver and drops it. This must be matched syntactically in the macro: PyRef<PyModule> already implements the argument-conversion traits, so an IntoPyNativeFn impl keyed on it would overlap with the generic one. Decide how aliases such as PyModuleRef are handled (recognize them explicitly or reject them with a clear error) instead of silently treating them as a Python argument.
4. A leading module parameter is always the receiver. _imp.exec_builtin and _imp.exec_dynamic (crates/vm/src/stdlib/_imp.rs) currently take the target module as their only parameter; rewrite them as (_imp: PyRef<PyModule>, mod: PyRef<PyModule>) so the first is the receiver and the second is the Python argument.
5. Merge module_object into zelf. With a receiver always present, PyNativeFunction keeps a single zelf. Remove module_object and with_module_object, and update Py<PyModule>::__init_methods and the other users (function/method.rs, stdlib/builtins.rs, stdlib/_lsprof.rs, vm/compile.rs, builtins/builtin_func.rs). PyNativeFunction::call must then tell a module receiver (out of band) from a method receiver (prepended) without adding work for module functions.
6. binascii. The decoders just declare module: PyRef<PyModule> as their first parameter; no option, no flag. Remove with_module from ALLOWED_NAMES and drop BIND_MODULE.

Must stay identical

• __self__, __module__, __qualname__, repr(), __reduce__, ==/hash of module functions, including the _imp.exec_builtin(sys) and defining-module __self__ regression checks you already added.
• __text_signature__ keeps the $module prefix; the receiver never appears as a Python parameter.
• No new per-call cost for module functions that do not take the receiver.

Validation

Workspace and CAPI tests, strict Clippy for both, the existing signature/binascii snippets on CPython 3.15 and RustPython, and test_binascii test_inspect test_builtin test_importlib. Please also report a quick before/after micro-benchmark of a module function that does not take the module (for example math.sqrt in a tight loop).

— commented by Claude