New locals() documentation

The heart of this proposal is to revise the documentation for the locals() builtin to read as follows:

Return a mapping object representing the current local symbol table, with variable names as the keys, and their currently bound references as the values.

At module scope, as well as when using exec() or eval() with a single namespace, this function returns the same namespace as globals().

At class scope, it returns the namespace that will be passed to the metaclass constructor.

When using exec() or eval() with separate local and global namespaces, it returns the local namespace passed in to the function call.

In all of the above cases, each call to locals() in a given frame of execution will return the same mapping object. Changes made through the mapping object returned from locals() will be visible as bound, rebound, or deleted local variables, and binding, rebinding, or deleting local variables will immediately affect the contents of the returned mapping object.

At function scope (including for generators and coroutines), each call to locals() instead returns a fresh dictionary containing the current bindings of the function’s local variables and any nonlocal cell references. In this case, name binding changes made via the returned dict are not written back to the corresponding local variables or nonlocal cell references, and binding, rebinding, or deleting local variables and nonlocal cell references does not affect the contents of previously returned dictionaries.

There would also be a versionchanged note for the release making this change:

In prior versions, the semantics of mutating the mapping object returned from locals() were formally undefined. In CPython specifically, the mapping returned at function scope could be implicitly refreshed by other operations, such as calling locals() again, or the interpreter implicitly invoking a Python level trace function. Obtaining the legacy CPython behaviour now requires explicit calls to update the initially returned dictionary with the results of subsequent calls to locals().

For reference, the current documentation of this builtin reads as follows:

Update and return a dictionary representing the current local symbol table. Free variables are returned by locals() when it is called in function blocks, but not in class blocks.

Note: The contents of this dictionary should not be modified; changes may not affect the values of local and free variables used by the interpreter.

(In other words: the status quo is that the semantics and behaviour of locals() are formally implementation defined, whereas the proposed state after this PEP is that the only implementation defined behaviour will be that associated with whether or not the implementation emulates the CPython frame API, with the behaviour in all other cases being defined by the language and library references)

Module scope

At module scope, as well as when using exec() or eval() with a single namespace, locals() must return the same object as globals(), which must be the actual execution namespace (available as inspect.currentframe().f_locals in implementations that provide access to frame objects).

Variable assignments during subsequent code execution in the same scope must dynamically change the contents of the returned mapping, and changes to the returned mapping must change the values bound to local variable names in the execution environment.

To capture this expectation as part of the language specification, the following paragraph will be added to the documentation for locals():

At module scope, as well as when using exec() or eval() with a single namespace, this function returns the same namespace as globals().

This part of the proposal does not require any changes to the reference implementation - it is standardisation of the current behaviour.

Class scope

At class scope, as well as when using exec() or eval() with separate global and local namespaces, locals() must return the specified local namespace (which may be supplied by the metaclass __prepare__ method in the case of classes). As for module scope, this must be a direct reference to the actual execution namespace (available as inspect.currentframe().f_locals in implementations that provide access to frame objects).

Variable assignments during subsequent code execution in the same scope must change the contents of the returned mapping, and changes to the returned mapping must change the values bound to local variable names in the execution environment.

The mapping returned by locals() will not be used as the actual class namespace underlying the defined class (the class creation process will copy the contents to a fresh dictionary that is only accessible by going through the class machinery).

For nested classes defined inside a function, any nonlocal cells referenced from the class scope are not included in the locals() mapping.

To capture this expectation as part of the language specification, the following two paragraphs will be added to the documentation for locals():

When using exec() or eval() with separate local and global namespaces, [this function] returns the given local namespace.

At class scope, it returns the namespace that will be passed to the metaclass constructor.

This part of the proposal does not require any changes to the reference implementation - it is standardisation of the current behaviour.

Function scope

At function scope, interpreter implementations are granted significant freedom to optimise local variable access, and hence are NOT required to permit arbitrary modification of local and nonlocal variable bindings through the mapping returned from locals().

Historically, this leniency has been described in the language specification with the words “The contents of this dictionary should not be modified; changes may not affect the values of local and free variables used by the interpreter.”

This PEP proposes to change that text to instead say:

At function scope (including for generators and coroutines), each call to locals() instead returns a fresh dictionary containing the current bindings of the function’s local variables and any nonlocal cell references. In this case, name binding changes made via the returned dict are not written back to the corresponding local variables or nonlocal cell references, and binding, rebinding, or deleting local variables and nonlocal cell references does not affect the contents of previously returned dictionaries.

This part of the proposal does require changes to the CPython reference implementation, as CPython currently returns a shared mapping object that may be implicitly refreshed by additional calls to locals(), and the “write back” strategy currently used to support namespace changes from trace functions also doesn’t comply with it (and causes the quirky behavioural problems mentioned in the Motivation above).

Summary of proposed implementation-specific changes

• Changes are made as necessary to provide the updated Python level semantics
• Two new functions are added to the stable ABI to replicate the updated behaviour of the Python locals() builtin:

PyObject * PyLocals_Get();
PyLocals_Kind PyLocals_GetKind();

• One new function is added to the stable ABI to efficiently get a snapshot of the local namespace in the running frame:

PyObject * PyLocals_GetCopy();

• Corresponding frame accessor functions for these new public APIs are added to the CPython frame C API
• On optimised frames, the Python level f_locals API will return dynamically created read/write proxy objects that directly access the frame’s local and closure variable storage. To provide interoperability with the existing PyEval_GetLocals() API, the proxy objects will continue to use the C level frame locals data storage field to hold a value cache that also allows for storage of arbitrary additional keys. Additional details on the expected behaviour of these fast locals proxy objects are covered below.
• No C API function is added to get access to a mutable mapping for the local namespace. Instead, PyObject_GetAttrString(frame, "f_locals") is used, the same API as is used in Python code.
• PyEval_GetLocals() remains supported and does not emit a programmatic warning, but will be deprecated in the documentation in favour of the new APIs that don’t rely on returning a borrowed reference
• PyFrame_FastToLocals() and PyFrame_FastToLocalsWithError() remain supported and do not emit a programmatic warning, but will be deprecated in the documentation in favour of the new APIs that don’t require direct access to the internal data storage layout of frame objects
• PyFrame_LocalsToFast() always raises RuntimeError(), indicating that PyObject_GetAttrString(frame, "f_locals") should be used to obtain a mutable read/write mapping for the local variables.
• The trace hook implementation will no longer call PyFrame_FastToLocals() implicitly. The version porting guide will recommend migrating to PyFrame_GetLocals() for read-only access and PyObject_GetAttrString(frame, "f_locals") for read/write access.

Providing the updated Python level semantics

The implementation of the locals() builtin is modified to return a distinct copy of the local namespace for optimised frames, rather than a direct reference to the internal frame value cache updated by the PyFrame_FastToLocals() C API and returned by the PyEval_GetLocals() C API.

Resolving the issues with tracing mode behaviour

The current cause of CPython’s tracing mode quirks (both the side effects from simply installing a tracing function and the fact that writing values back to function locals only works for the specific function being traced) is the way that locals mutation support for trace hooks is currently implemented: the PyFrame_LocalsToFast function.

When a trace function is installed, CPython currently does the following for function frames (those where the code object uses “fast locals” semantics):

1. Calls PyFrame_FastToLocals to update the frame value cache
2. Calls the trace hook (with tracing of the hook itself disabled)
3. Calls PyFrame_LocalsToFast to capture any changes made to the frame value cache

This approach is problematic for a few different reasons:

• Even if the trace function doesn’t mutate the value cache, the final step resets any cell references back to the state they were in before the trace function was called (this is the root cause of the bug report in [1])
• If the trace function does mutate the value cache, but then does something that causes the value cache to be refreshed from the frame, those changes are lost (this is one aspect of the bug report in [3])
• If the trace function attempts to mutate the local variables of a frame other than the one being traced (e.g. frame.f_back.f_locals), those changes will almost certainly be lost (this is another aspect of the bug report in [3])
• If a reference to the frame value cache (e.g. retrieved via locals()) is passed to another function, and that function mutates the value cache, then those changes may be written back to the execution frame if a trace hook is installed

The proposed resolution to this problem is to take advantage of the fact that whereas functions typically access their own namespace using the language defined locals() builtin, trace functions necessarily use the implementation dependent frame.f_locals interface, as a frame reference is what gets passed to hook implementations.

Instead of being a direct reference to the internal frame value cache historically returned by the locals() builtin, the Python level frame.f_locals will be updated to instead return instances of a dedicated fast locals proxy type that writes and reads values directly to and from the fast locals array on the underlying frame. Each access of the attribute produces a new instance of the proxy (so creating proxy instances is intentionally a cheap operation).

Despite the new proxy type becoming the preferred way to access local variables on optimised frames, the internal value cache stored on the frame is still retained for two key purposes:

• maintaining backwards compatibility for and interoperability with the PyEval_GetLocals() C API
• providing storage space for additional keys that don’t have slots in the fast locals array (e.g. the __return__ and __exception__ keys set by pdb when tracing code execution for debugging purposes)

With the changes in this PEP, this internal frame value cache is no longer directly accessible from Python code (whereas historically it was both returned by the locals() builtin and available as the frame.f_locals attribute). Instead, the value cache is only accessible via the PyEval_GetLocals() C API and by directly accessing the internal storage of a frame object.

Fast locals proxy objects and the internal frame value cache returned by PyEval_GetLocals() offer the following behavioural guarantees:

• changes made via a fast locals proxy will be immediately visible to the frame itself, to other fast locals proxy objects for the same frame, and in the internal value cache stored on the frame (it is this last point that provides PyEval_GetLocals() interoperability)
• changes made directly to the internal frame value cache will never be visible to the frame itself, and will only be reliably visible via fast locals proxies for the same frame if the change relates to extra variables that don’t have slots in the frame’s fast locals array
• changes made by executing code in the frame will be immediately visible to all fast locals proxy objects for that frame (both existing proxies and newly created ones). Visibility in the internal frame value cache cache returned by PyEval_GetLocals() is subject to the cache update guidelines discussed in the next section

As a result of these points, only code using PyEval_GetLocals(), PyLocals_Get(), or PyLocals_GetCopy() will need to be concerned about the frame value cache potentially becoming stale. Code using the new frame fast locals proxy API (whether from Python or from C) will always see the live state of the frame.

Fast locals proxy implementation details

Each fast locals proxy instance has a single internal attribute that is not exposed as part of the Python runtime API:

• frame: the underlying optimised frame that the proxy provides access to

In addition, proxy instances use and update the following attributes stored on the underlying frame or code object:

• _name_to_offset_mapping: a hidden mapping from variable names to fast local storage offsets. This mapping is lazily initialized on the first frame read or write access through a fast locals proxy, rather than being eagerly populated as soon as the first fast locals proxy is created. Since the mapping is identical for all frames running a given code object, a single copy is stored on the code object, rather than each frame object populating its own mapping
• locals: the internal frame value cache returned by the PyEval_GetLocals() C API and updated by the PyFrame_FastToLocals() C API. This is the mapping that the locals() builtin returns in Python 3.10 and earlier.

__getitem__ operations on the proxy will populate the _name_to_offset_mapping on the code object (if it is not already populated), and then either return the relevant value (if the key is found in either the _name_to_offset_mapping mapping or the internal frame value cache), or else raise KeyError. Variables that are defined on the frame but not currently bound also raise KeyError (just as they’re omitted from the result of locals()).

As the frame storage is always accessed directly, the proxy will automatically pick up name binding and unbinding operations that take place as the function executes. The internal value cache is implicitly updated when individual variables are read from the frame state (including for containment checks, which need to check if the name is currently bound or unbound).

Similarly, __setitem__ and __delitem__ operations on the proxy will directly affect the corresponding fast local or cell reference on the underlying frame, ensuring that changes are immediately visible to the running Python code, rather than needing to be written back to the runtime storage at some later time. Such changes are also immediately written to the internal frame value cache to make them visible to users of the PyEval_GetLocals() C API.

Keys that are not defined as local or closure variables on the underlying frame are still written to the internal value cache on optimised frames. This allows utilities like pdb (which writes __return__ and __exception__ values into the frame’s f_locals mapping) to continue working as they always have. These additional keys that do not correspond to a local or closure variable on the frame will be left alone by future cache sync operations. Using the frame value cache to store these extra keys (rather than defining a new mapping that holds only the extra keys) provides full interoperability with the existing PyEval_GetLocals() API (since users of either API will see extra keys added by users of either API, rather than users of the new fast locals proxy API only seeing keys added via that API).

An additional benefit of storing only the variable value cache on the frame (rather than storing an instance of the proxy type), is that it avoids creating a reference cycle from the frame back to itself, so the frame will only be kept alive if another object retains a reference to a proxy instance.

Note: calling the proxy.clear() method has a similarly broad impact as calling PyFrame_LocalsToFast() on an empty frame value cache in earlier versions. Not only will the frame local variables be cleared, but also any cell variables accessible from the frame (whether those cells are owned by the frame itself or by an outer frame). This can clear a class’s __class__ cell if called on the frame of a method that uses the zero-arg super() construct (or otherwise references __class__). This exceeds the scope of calling frame.clear(), as that only drop’s the frame’s references to cell variables, it doesn’t clear the cells themselves. This PEP could be a potential opportunity to narrow the scope of attempts to clear the frame variables directly by leaving cells belonging to outer frames alone, and only clearing local variables and cells belonging directly to the frame underlying the proxy (this issue affects PEP 667 as well, as the question relates to the handling of cell variables, and is entirely independent of the internal frame value cache).

Changes to the stable C API/ABI

Unlike Python code, extension module functions that call in to the Python C API can be called from any kind of Python scope. This means it isn’t obvious from the context whether locals() will return a snapshot or not, as it depends on the scope of the calling Python code, not the C code itself.

This means it is desirable to offer C APIs that give predictable, scope independent, behaviour. However, it is also desirable to allow C code to exactly mimic the behaviour of Python code at the same scope.

To enable mimicking the behaviour of Python code, the stable C ABI would gain the following new functions:

PyObject * PyLocals_Get();
PyLocals_Kind PyLocals_GetKind();

PyLocals_Get() is directly equivalent to the Python locals() builtin. It returns a new reference to the local namespace mapping for the active Python frame at module and class scope, and when using exec() or eval(). It returns a shallow copy of the active namespace at function/coroutine/generator scope.

PyLocals_GetKind() returns a value from the newly defined PyLocals_Kind enum, with the following options being available:

• PyLocals_DIRECT_REFERENCE: PyLocals_Get() returns a direct reference to the local namespace for the running frame.
• PyLocals_SHALLOW_COPY: PyLocals_Get() returns a shallow copy of the local namespace for the running frame.
• PyLocals_UNDEFINED: an error occurred (e.g. no active Python thread state). A Python exception will be set if this value is returned.

Since the enum is used in the stable ABI, an additional 31-bit value is set to ensure that it is safe to cast arbitrary signed 32-bit signed integers to PyLocals_Kind values.

This query API allows extension module code to determine the potential impact of mutating the mapping returned by PyLocals_Get() without needing access to the details of the running frame object. Python code gets equivalent information visually through lexical scoping (as covered in the new locals() builtin documentation).

To allow extension module code to behave consistently regardless of the active Python scope, the stable C ABI would gain the following new function:

PyObject * PyLocals_GetCopy();

PyLocals_GetCopy() returns a new dict instance populated from the current locals namespace. Roughly equivalent to dict(locals()) in Python code, but avoids the double-copy in the case where locals() already returns a shallow copy. Akin to the following code, but doesn’t assume there will only ever be two kinds of locals result:

locals = PyLocals_Get();
if (PyLocals_GetKind() == PyLocals_DIRECT_REFERENCE) {
    locals = PyDict_Copy(locals);
}

The existing PyEval_GetLocals() API will retain its existing behaviour in CPython (mutable locals at class and module scope, shared dynamic snapshot otherwise). However, its documentation will be updated to note that the conditions under which the shared dynamic snapshot get updated have changed.

The PyEval_GetLocals() documentation will also be updated to recommend replacing usage of this API with whichever of the new APIs is most appropriate for the use case:

• Use PyLocals_Get() (optionally combined with PyDictProxy_New()) for read-only access to the current locals namespace. This form of usage will need to be aware that the copy may go stale in optimised frames.
• Use PyLocals_GetCopy() for a regular mutable dict that contains a copy of the current locals namespace, but has no ongoing connection to the active frame.
• Use PyLocals_Get() to exactly match the semantics of the Python level locals() builtin.
• Query PyLocals_GetKind() explicitly to implement custom handling (e.g. raising a meaningful exception) for scopes where PyLocals_Get() would return a shallow copy rather than granting read/write access to the locals namespace.
• Use implementation specific APIs (e.g. PyObject_GetAttrString(frame, "f_locals")) if read/write access to the frame is required and PyLocals_GetKind() returns something other than PyLocals_DIRECT_REFERENCE.

Changes to the public CPython C API

The existing PyEval_GetLocals() API returns a borrowed reference, which means it cannot be updated to return the new shallow copies at function scope. Instead, it will continue to return a borrowed reference to an internal dynamic snapshot stored on the frame object. This shared mapping will behave similarly to the existing shared mapping in Python 3.10 and earlier, but the exact conditions under which it gets refreshed will be different. Specifically, it will be updated only in the following circumstance:

• any call to PyEval_GetLocals(), PyLocals_Get(), PyLocals_GetCopy(), or the Python locals() builtin while the frame is running
• any call to PyFrame_GetLocals(), PyFrame_GetLocalsCopy(), _PyFrame_BorrowLocals(), PyFrame_FastToLocals(), or PyFrame_FastToLocalsWithError() for the frame
• any operation on a fast locals proxy object that updates the shared mapping as part of its implementation. In the initial reference implementation, those operations are those that are intrinsically O(n) operations (len(flp), mapping comparison, flp.copy() and rendering as a string), as well as those that refresh the cache entries for individual keys.

Requesting a fast locals proxy will not implicitly update the shared dynamic snapshot, and the CPython trace hook handling will no longer implicitly update it either.

(Note: even though PyEval_GetLocals() is part of the stable C API/ABI, the specifics of when the namespace it returns gets refreshed are still an interpreter implementation detail)

The additions to the public CPython C API are the frame level enhancements needed to support the stable C API/ABI updates:

PyLocals_Kind PyFrame_GetLocalsKind(frame);
PyObject * PyFrame_GetLocals(frame);
PyObject * PyFrame_GetLocalsCopy(frame);
PyObject * _PyFrame_BorrowLocals(frame);

PyFrame_GetLocalsKind(frame) is the underlying API for PyLocals_GetKind().

PyFrame_GetLocals(frame) is the underlying API for PyLocals_Get().

PyFrame_GetLocalsCopy(frame) is the underlying API for PyLocals_GetCopy().

_PyFrame_BorrowLocals(frame) is the underlying API for PyEval_GetLocals(). The underscore prefix is intended to discourage use and to indicate that code using it is unlikely to be portable across implementations. However, it is documented and visible to the linker in order to avoid having to access the internals of the frame struct from the PyEval_GetLocals() implementation.

The PyFrame_LocalsToFast() function will be changed to always emit RuntimeError, explaining that it is no longer a supported operation, and affected code should be updated to use PyObject_GetAttrString(frame, "f_locals") to obtain a read/write proxy instead.

In addition to the above documented interfaces, the draft reference implementation also exposes the following undocumented interfaces:

PyTypeObject _PyFastLocalsProxy_Type;
#define _PyFastLocalsProxy_CheckExact(self) Py_IS_TYPE(op, &_PyFastLocalsProxy_Type)

This type is what the reference implementation actually returns from PyObject_GetAttrString(frame, "f_locals") for optimized frames (i.e. when PyFrame_GetLocalsKind() returns PyLocals_SHALLOW_COPY).

Reducing the runtime overhead of trace hooks

As noted in [9], the implicit call to PyFrame_FastToLocals() in the Python trace hook support isn’t free, and could be rendered unnecessary if the frame proxy read values directly from the frame instead of getting them from the mapping.

As the new frame locals proxy type doesn’t require separate data refresh steps, this PEP incorporates Victor Stinner’s proposal to no longer implicitly call PyFrame_FastToLocalsWithError() before calling trace hooks implemented in Python.

Code using the new fast locals proxy objects will have the dynamic locals snapshot implicitly refreshed when accessing methods that need it, while code using the PyEval_GetLocals() API will implicitly refresh it when making that call.

The PEP necessarily also drops the implicit call to PyFrame_LocalsToFast() when returning from a trace hook, as that API now always raises an exception.

Changing locals() to return independent snapshots at function scope

The locals() builtin is a required part of the language, and in the reference implementation it has historically returned a mutable mapping with the following characteristics:

• each call to locals() returns the same mapping object
• for namespaces where locals() returns a reference to something other than the actual local execution namespace, each call to locals() updates the mapping object with the current state of the local variables and any referenced nonlocal cells
• changes to the returned mapping usually aren’t written back to the local variable bindings or the nonlocal cell references, but write backs can be triggered by doing one of the following:
  • installing a Python level trace hook (write backs then happen whenever the trace hook is called)
  • running a function level wildcard import (requires bytecode injection in Py3)
  • running an exec statement in the function’s scope (Py2 only, since exec became an ordinary builtin in Python 3)

Originally this PEP proposed to retain the first two of these properties, while changing the third in order to address the outright behaviour bugs that it can cause.

In [7] Nathaniel Smith made a persuasive case that we could make the behaviour of locals() at function scope substantially less confusing by retaining only the second property and having each call to locals() at function scope return an independent snapshot of the local variables and closure references rather than updating an implicitly shared snapshot.

As this revised design also made the implementation markedly easier to follow, the PEP was updated to propose this change in behaviour, rather than retaining the historical shared snapshot.

Keeping locals() as a snapshot at function scope

As discussed in [7], it would theoretically be possible to change the semantics of the locals() builtin to return the write-through proxy at function scope, rather than switching it to return independent snapshots.

This PEP doesn’t (and won’t) propose this as it’s a backwards incompatible change in practice, even though code that relies on the current behaviour is technically operating in an undefined area of the language specification.

Consider the following code snippet:

def example():
    x = 1
    locals()["x"] = 2
    print(x)

Even with a trace hook installed, that function will consistently print 1 on the current reference interpreter implementation:

>>> example()
1
>>> import sys
>>> def basic_hook(*args):
...     return basic_hook
...
>>> sys.settrace(basic_hook)
>>> example()
1

Similarly, locals() can be passed to the exec() and eval() builtins at function scope (either explicitly or implicitly) without risking unexpected rebinding of local variables or closure references.

Provoking the reference interpreter into incorrectly mutating the local variable state requires a more complex setup where a nested function closes over a variable being rebound in the outer function, and due to the use of either threads, generators, or coroutines, it’s possible for a trace function to start running for the nested function before the rebinding operation in the outer function, but finish running after the rebinding operation has taken place (in which case the rebinding will be reverted, which is the bug reported in [1]).

In addition to preserving the de facto semantics which have been in place since PEP 227 introduced nested scopes in Python 2.1, the other benefit of restricting the write-through proxy support to the implementation-defined frame object API is that it means that only interpreter implementations which emulate the full frame API need to offer the write-through capability at all, and that JIT-compiled implementations only need to enable it when a frame introspection API is invoked, or a trace hook is installed, not whenever locals() is accessed at function scope.

Returning snapshots from locals() at function scope also means that static analysis for function level code will be more reliable, as only access to the frame machinery will allow rebinding of local and nonlocal variable references in a way that is hidden from static analysis.

What happens with the default args for eval() and exec()?

These are formally defined as inheriting globals() and locals() from the calling scope by default.

There isn’t any need for the PEP to change these defaults, so it doesn’t, and exec() and eval() will start running in a shallow copy of the local namespace when that is what locals() returns.

This behaviour will have potential performance implications, especially for functions with large numbers of local variables (e.g. if these functions are called in a loop, calling globals() and locals() once before the loop and then passing the namespace into the function explicitly will give the same semantics and performance characteristics as the status quo, whereas relying on the implicit default would create a new shallow copy of the local namespace on each iteration).

(Note: the reference implementation draft PR has updated the locals() and vars(), eval(), and exec() builtins to use PyLocals_Get(). The dir() builtin still uses PyEval_GetLocals(), since it’s only using it to make a list from the keys).

Additional considerations for eval() and exec() in optimized scopes

Note: while implementing PEP 667, it was noted that neither that PEP nor this one clearly explained the impact the locals() changes would have on code execution APIs like exec() and eval(). This section was added to this PEP’s rationale to better describe the impact and explain the intended benefits of the change.

When exec() was converted from a statement to a builtin function in Python 3.0 (part of the core language changes in PEP 3100), the associated implicit call to PyFrame_LocalsToFast() was removed, so it typically appears as if attempts to write to local variables with exec() in optimized frames are ignored:

>>> def f():
...     x = 0
...     exec("x = 1")
...     print(x)
...     print(locals()["x"])
...
>>> f()
0
0

In truth, the writes aren’t being ignored, they just aren’t being copied from the dictionary cache back to the optimized local variable array. The changes to the dictionary are then overwritten the next time the dictionary cache is refreshed from the array:

>>> def f():
...     x = 0
...     locals_cache = locals()
...     exec("x = 1")
...     print(x)
...     print(locals_cache["x"])
...     print(locals()["x"])
...
>>> f()
0
1
0

The behaviour becomes even stranger if a tracing function or another piece of code invokes PyFrame_LocalsToFast() before the cache is next refreshed. In those cases the change is written back to the optimized local variable array:

>>> from sys import _getframe
>>> from ctypes import pythonapi, py_object, c_int
>>> _locals_to_fast = pythonapi.PyFrame_LocalsToFast
>>> _locals_to_fast.argtypes = [py_object, c_int]
>>> def f():
...     _frame = _getframe()
...     _f_locals = _frame.f_locals
...     x = 0
...     exec("x = 1")
...     _locals_to_fast(_frame, 0)
...     print(x)
...     print(locals()["x"])
...     print(_f_locals["x"])
...
>>> f()
1
1
1

This situation was more common in Python 3.10 and earlier versions, as merely installing a tracing function was enough to trigger implicit calls to PyFrame_LocalsToFast() after every line of Python code. However, it can still happen in Python 3.11+ depending on exactly which tracing functions are active (e.g. interactive debuggers intentionally do this so that changes made at the debugging prompt are visible when code execution resumes).

All of the above comments in relation to exec() apply to any attempt to mutate the result of locals() in optimized scopes, and are the main reason that the locals() builtin docs contain this caveat:

Note: The contents of this dictionary should not be modified; changes may not affect the values of local and free variables used by the interpreter.

While the exact wording in the library reference is not entirely explicit, both exec() and eval() have long used the results of calling globals() and locals() in the calling Python frame as their default execution namespace.

This was historically also equivalent to using the calling frame’s frame.f_globals and frame.f_locals attributes, but this PEP maps the default namespace arguments for exec() and eval() to globals() and locals() in the calling frame in order to preserve the property of defaulting to ignoring attempted writes to the local namespace in optimized scopes.

This poses a potential compatibility issue for some code, as with the previous implementation that returns the same dict when locals() is called multiple times in function scope, the following code usually worked due to the implicitly shared local variable namespace:

def f():
    exec('a = 0')  # equivalent to exec('a = 0', globals(), locals())
    exec('print(a)')  # equivalent to exec('print(a)', globals(), locals())
    print(locals())  # {'a': 0}
    # However, print(a) will not work here
f()

With locals() in an optimised scope returning the same shared dict for each call, it was possible to store extra “fake locals” in that dict. While these aren’t real locals known by the compiler (so they can’t be printed with code like print(a)), they can still be accessed via locals() and shared between multiple exec() calls in the same function scope. Furthermore, because they’re not real locals, they don’t get implicitly updated or removed when the shared cache is refreshed from the local variable storage array.

When the code in exec() tries to write to an existing local variable, the runtime behaviour gets harder to predict:

def f():
    a = None
    exec('a = 0')  # equivalent to exec('a = 0', globals(), locals())
    exec('print(a)')  # equivalent to exec('print(a)', globals(), locals())
    print(locals())  # {'a': None}
f()

print(a) will print None because the implicit locals() call in exec() refreshes the cached dict with the actual values on the frame. This means that, unlike the “fake” locals created by writing back to locals() (including via previous calls to exec()), the real locals known by the compiler can’t easily be modified by exec() (it can be done, but it requires both retrieving the frame.f_locals attribute to enable writes back to the frame, and then invoking PyFrame_LocalsToFast(), as shown using ctypes above).

As noted in the Motivation section, this confusing side effect happens even if the local variable is only defined after the exec() calls:

>>> def f():
...     exec("a = 0")
...     exec("print('a' in locals())") # Printing 'a' directly won't work
...     print(locals())
...     a = None
...     print(locals())
...
>>> f()
False
{}
{'a': None}

Because a is a real local variable that is not currently bound to a value, it gets explicitly removed from the dictionary returned by locals() whenever locals() is called prior to the a = None line. This removal is intentional, as it allows the contents of locals() to be updated correctly in optimized scopes when del statements are used to delete previously bound local variables.

As noted in the ctypes example, the above behavioural description may be invalidated if the CPython PyFrame_LocalsToFast() API gets invoked while the frame is still running. In that case, the changes to a might become visible to the running code, depending on exactly when that API is called (and whether the frame has been primed for locals modification by accessing the frame.f_locals attribute).

As described above, two options were considered to replace this confusing behaviour:

• make locals() return write-through proxy instances (similar to frame.f_locals)
• make locals() return genuinely independent snapshots so that attempts to change the values of local variables via exec() would be consistently ignored without any of the caveats noted above.

The PEP chooses the second option for the following reasons:

• returning independent snapshots in optimized scopes preserves the Python 3.0 change to exec() that resulted in attempts to mutate local variables via exec() being ignored in most cases
• the distinction between “locals() gives an instantaneous snapshot of the local variables in optimized scopes, and read/write access in other scopes” and “frame.f_locals gives read/write access to the local variables in all scopes, including optimized scopes” allows the intent of a piece of code to be clearer than it would be if both APIs granted full read/write access in optimized scopes, even when write access wasn’t needed or desired
• in addition to improving clarity for human readers, ensuring that name rebinding in optimized scopes remains lexically visible in the code (as long as the frame introspection APIs are not accessed) allows compilers and interpreters to apply related performance optimizations more consistently
• only Python implementations that support the optional frame introspection APIs will need to provide the new write-through proxy support for optimized frames

With the semantic changes to locals() in this PEP, it becomes much easier to explain the behavior of exec() and eval(): in optimized scopes, they will never implicitly affect local variables; in other scopes, they will always implicitly affect local variables. In optimized scopes, any implicit assignment to the local variables will be discarded when the code execution API returns, since a fresh copy of the local variables is used on each invocation.

Retaining the internal frame value cache

Retaining the internal frame value cache results in some visible quirks when frame proxy instances are kept around and re-used after name binding and unbinding operations have been executed on the frame.

The primary reason for retaining the frame value cache is to maintain backwards compatibility with the PyEval_GetLocals() API. That API returns a borrowed reference, so it must refer to persistent state stored on the frame object. Storing a fast locals proxy object on the frame creates a problematic reference cycle, so the cleanest option is to instead continue to return a frame value cache, just as this function has done since optimised frames were first introduced.

With the frame value cache being kept around anyway, it then further made sense to rely on it to simplify the fast locals proxy mapping implementation.

Note: the fact PEP 667 doesn’t use the internal frame value cache as part of the write-through proxy implementation is the key Python level difference between the two PEPs.

Changing the frame API semantics in regular operation

Note: when this PEP was first written, it predated the Python 3.11 change to drop the implicit writeback of the frame local variables whenever a tracing function was installed, so making that change was included as part of the proposal.

Earlier versions of this PEP proposed having the semantics of the frame f_locals attribute depend on whether or not a tracing hook was currently installed - only providing the write-through proxy behaviour when a tracing hook was active, and otherwise behaving the same as the historical locals() builtin.

That was adopted as the original design proposal for a couple of key reasons, one pragmatic and one more philosophical:

• Object allocations and method wrappers aren’t free, and tracing functions aren’t the only operations that access frame locals from outside the function. Restricting the changes to tracing mode meant that the additional memory and execution time overhead of these changes would be as close to zero in regular operation as we can possibly make them.
• “Don’t change what isn’t broken”: the current tracing mode problems are caused by a requirement that’s specific to tracing mode (support for external rebinding of function local variable references), so it made sense to also restrict any related fixes to tracing mode

However, actually attempting to implement and document that dynamic approach highlighted the fact that it makes for a really subtle runtime state dependent behaviour distinction in how frame.f_locals works, and creates several new edge cases around how f_locals behaves as trace functions are added and removed.

Accordingly, the design was switched to the current one, where frame.f_locals is always a write-through proxy, and locals() is always a snapshot, which is both simpler to implement and easier to explain.

Regardless of how the CPython reference implementation chooses to handle this, optimising compilers and interpreters also remain free to impose additional restrictions on debuggers, such as making local variable mutation through frame objects an opt-in behaviour that may disable some optimisations (just as the emulation of CPython’s frame API is already an opt-in flag in some Python implementations).

Continuing to support storing additional data on optimised frames

One of the draft iterations of this PEP proposed removing the ability to store additional data on optimised frames by writing to frame.f_locals keys that didn’t correspond to local or closure variable names on the underlying frame.

While this idea offered some attractive simplification of the fast locals proxy implementation, pdb stores __return__ and __exception__ values on arbitrary frames, so the standard library test suite fails if that functionality no longer works.

Accordingly, the ability to store arbitrary keys was retained, at the expense of certain operations on proxy objects being slower than could otherwise be (since they can’t assume that only names defined on the code object will be accessible through the proxy).

It is expected that the exact details of the interaction between the fast locals proxy and the f_locals value cache on the underlying frame will evolve over time as opportunities for improvement are identified.

Historical semantics at function scope

The current semantics of mutating locals() and frame.f_locals in CPython are rather quirky due to historical implementation details:

• actual execution uses the fast locals array for local variable bindings and cell references for nonlocal variables
• there’s a PyFrame_FastToLocals operation that populates the frame’s f_locals attribute based on the current state of the fast locals array and any referenced cells. This exists for three reasons:
  • allowing trace functions to read the state of local variables
  • allowing traceback processors to read the state of local variables
  • allowing locals() to read the state of local variables
• a direct reference to frame.f_locals is returned from locals(), so if you hand out multiple concurrent references, then all those references will be to the exact same dictionary
• the two common calls to the reverse operation, PyFrame_LocalsToFast, were removed in the migration to Python 3: exec is no longer a statement (and hence can no longer affect function local namespaces), and the compiler now disallows the use of from module import * operations at function scope
• however, two obscure calling paths remain: PyFrame_LocalsToFast is called as part of returning from a trace function (which allows debuggers to make changes to the local variable state), and you can also still inject the IMPORT_STAR opcode when creating a function directly from a code object rather than via the compiler

This proposal deliberately doesn’t formalise these semantics as is, since they only make sense in terms of the historical evolution of the language and the reference implementation, rather than being deliberately designed.

Proposing several additions to the stable C API/ABI

Historically, the CPython C API (and subsequently, the stable ABI) has exposed only a single API function related to the Python locals builtin: PyEval_GetLocals(). However, as it returns a borrowed reference, it is not possible to adapt that interface directly to supporting the new locals() semantics proposed in this PEP.

An earlier iteration of this PEP proposed a minimalist adaptation to the new semantics: one C API function that behaved like the Python locals() builtin, and another that behaved like the frame.f_locals descriptor (creating and returning the write-through proxy if necessary).

The feedback [8] on that version of the C API was that it was too heavily based on how the Python level semantics were implemented, and didn’t account for the behaviours that authors of C extensions were likely to need.

The broader API now being proposed came from grouping the potential reasons for wanting to access the Python locals() namespace from an extension module into the following cases:

• needing to exactly replicate the semantics of the Python level locals() operation. This is the PyLocals_Get() API.
• needing to behave differently depending on whether writes to the result of PyLocals_Get() will be visible to Python code or not. This is handled by the PyLocals_GetKind() query API.
• always wanting a mutable namespace that has been pre-populated from the current Python locals() namespace, but not wanting any changes to be visible to Python code. This is the PyLocals_GetCopy() API.
• always wanting a read-only view of the current locals namespace, without incurring the runtime overhead of making a full copy each time. This isn’t readily offered for optimised frames due to the need to check whether names are currently bound or not, so no specific API is being added to cover it.

Historically, these kinds of checks and operations would only have been possible if a Python implementation emulated the full CPython frame API. With the proposed API, extension modules can instead ask more clearly for the semantics that they actually need, giving Python implementations more flexibility in how they provide those capabilities.

Comparison with PEP 667

NOTE: the comparison below is against PEP 667 as it was in December 2021. It does not reflect the state of PEP 667 as of April 2024 (when this PEP was withdrawn in favour of proceeding with PEP 667).

PEP 667 offers a partially competing proposal for this PEP that suggests it would be reasonable to eliminate the internal frame value cache on optimised frames entirely.

These changes were originally offered as amendments to PEP 558, and the PEP author rejected them for three main reasons:

• the initial claim that PyEval_GetLocals() was unfixable because it returns a borrowed reference was simply false, as it is still working in the PEP 558 reference implementation. All that is required to keep it working is to retain the internal frame value cache and design the fast locals proxy in such a way that it is reasonably straightforward to keep the cache up to date with changes in the frame state without incurring significant runtime overhead when the cache isn’t needed. Given that this claim is false, the proposal to require that all code using the PyEval_GetLocals() API be rewritten to use a new API with different refcounting semantics fails PEP 387’s requirement that API compatibility breaks should have a large benefit to breakage ratio (since there’s no significant benefit gained from dropping the cache, no code breakage can be justified). The only genuinely unfixable public API is PyFrame_LocalsToFast() (which is why both PEPs propose breaking that).
• without some form of internal value cache, the API performance characteristics of the fast locals proxy mapping become quite unintuitive. len(proxy), for example, becomes consistently O(n) in the number of variables defined on the frame, as the proxy has to iterate over the entire fast locals array to see which names are currently bound to values before it can determine the answer. By contrast, maintaining an internal frame value cache potentially allows proxies to largely be treated as normal dictionaries from an algorithmic complexity point of view, with allowances only needing to be made for the initial implicit O(n) cache refresh that runs the first time an operation that relies on the cache being up to date is executed.
• the claim that a cache-free implementation would be simpler is highly suspect, as PEP 667 includes only a pure Python sketch of a subset of a mutable mapping implementation, rather than a full-fledged C implementation of a new mapping type integrated with the underlying data storage for optimised frames. PEP 558’s fast locals proxy implementation delegates heavily to the frame value cache for the operations needed to fully implement the mutable mapping API, allowing it to re-use the existing dict implementations of the following operations:
  • __len__
  • __str__
  • __or__ (dict union)
  • __iter__ (allowing the dict_keyiterator type to be reused)
  • __reversed__ (allowing the dict_reversekeyiterator type to be reused)
  • keys() (allowing the dict_keys type to be reused)
  • values() (allowing the dict_values type to be reused)
  • items() (allowing the dict_items type to be reused)
  • copy()
  • popitem()
  • value comparison operations

Of the three reasons, the first is the most important (since we need compelling reasons to break API backwards compatibility, and we don’t have them).

However, after reviewing PEP 667’s proposed Python level semantics, the author of this PEP eventually agreed that they would be simpler for users of the Python locals() API, so this distinction between the two PEPs has been eliminated: regardless of which PEP and implementation is accepted, the fast locals proxy object always provides a consistent view of the current state of the local variables, even if this results in some operations becoming O(n) that would be O(1) on a regular dictionary (specifically, len(proxy) becomes O(n), since it needs to check which names are currently bound, and proxy mapping comparisons avoid relying on the length check optimisation that allows differences in the number of stored keys to be detected quickly for regular mappings).

Due to the adoption of these non-standard performance characteristics in the proxy implementation, the PyLocals_GetView() and PyFrame_GetLocalsView() C APIs were also removed from the proposal in this PEP.

This leaves the only remaining points of distinction between the two PEPs as specifically related to the C API:

• PEP 667 still proposes completely unnecessary C API breakage (the programmatic deprecation and eventual removal of PyEval_GetLocals(), PyFrame_FastToLocalsWithError(), and PyFrame_FastToLocals()) without justification, when it is entirely possible to keep these working indefinitely (and interoperably) given a suitably designed fast locals proxy implementation
• the fast locals proxy handling of additional variables is defined in this PEP in a way that is fully interoperable with the existing PyEval_GetLocals() API. In the proxy implementation proposed in PEP 667, users of the new frame API will not see changes made to additional variables by users of the old API, and changes made to additional variables via the old API will be overwritten on subsequent calls to PyEval_GetLocals().
• the PyLocals_Get() API in this PEP is called PyEval_Locals() in PEP 667. This function name is a bit strange as it lacks a verb, making it look more like a type name than a data access API.
• this PEP adds PyLocals_GetCopy() and PyFrame_GetLocalsCopy() APIs to allow extension modules to easily avoid incurring a double copy operation in frames where PyLocals_Get() already makes a copy
• this PEP adds PyLocals_Kind, PyLocals_GetKind(), and PyFrame_GetLocalsKind() to allow extension modules to identify when code is running at function scope without having to inspect non-portable frame and code object APIs (without the proposed query API, the existing equivalent to the new PyLocals_GetKind() == PyLocals_SHALLOW_COPY check is to include the CPython internal frame API headers and check if _PyFrame_GetCode(PyEval_GetFrame())->co_flags & CO_OPTIMIZED is set)

The Python pseudo-code below is based on the implementation sketch presented in PEP 667 as of the time of writing (2021-10-24). The differences that provide the improved interoperability between the new fast locals proxy API and the existing PyEval_GetLocals() API are noted in comments.

As in PEP 667, all attributes that start with an underscore are invisible and cannot be accessed directly. They serve only to illustrate the proposed design.

For simplicity (and as in PEP 667), the handling of module and class level frames is omitted (they’re much simpler, as _locals is the execution namespace, so no translation is required).

NULL: Object # NULL is a singleton representing the absence of a value.

class CodeType:

    _name_to_offset_mapping_impl: dict | NULL
    ...

    def __init__(self, ...):
        self._name_to_offset_mapping_impl = NULL
        self._variable_names = deduplicate(
            self.co_varnames + self.co_cellvars + self.co_freevars
        )
        ...

    def _is_cell(self, offset):
        ... # How the interpreter identifies cells is an implementation detail

    @property
    def _name_to_offset_mapping(self):
        "Mapping of names to offsets in local variable array."
        if self._name_to_offset_mapping_impl is NULL:

            self._name_to_offset_mapping_impl = {
                name: index for (index, name) in enumerate(self._variable_names)
            }
        return self._name_to_offset_mapping_impl

class FrameType:

    _fast_locals : array[Object] # The values of the local variables, items may be NULL.
    _locals: dict | NULL # Dictionary returned by PyEval_GetLocals()

    def __init__(self, ...):
        self._locals = NULL
        ...

    @property
    def f_locals(self):
        return FastLocalsProxy(self)

class FastLocalsProxy:

    __slots__ "_frame"

    def __init__(self, frame:FrameType):
        self._frame = frame

    def _set_locals_entry(self, name, val):
        f = self._frame
        if f._locals is NULL:
            f._locals = {}
        f._locals[name] = val

    def __getitem__(self, name):
        f = self._frame
        co = f.f_code
        if name in co._name_to_offset_mapping:
            index = co._name_to_offset_mapping[name]
            val = f._fast_locals[index]
            if val is NULL:
                raise KeyError(name)
            if co._is_cell(offset)
                val = val.cell_contents
                if val is NULL:
                    raise KeyError(name)
            # PyEval_GetLocals() interop: implicit frame cache refresh
            self._set_locals_entry(name, val)
            return val
        # PyEval_GetLocals() interop: frame cache may contain additional names
        if f._locals is NULL:
            raise KeyError(name)
        return f._locals[name]

    def __setitem__(self, name, value):
        f = self._frame
        co = f.f_code
        if name in co._name_to_offset_mapping:
            index = co._name_to_offset_mapping[name]
            kind = co._local_kinds[index]
            if co._is_cell(offset)
                cell = f._locals[index]
                cell.cell_contents = val
            else:
                f._fast_locals[index] = val
        # PyEval_GetLocals() interop: implicit frame cache update
        # even for names that are part of the fast locals array
        self._set_locals_entry(name, val)

    def __delitem__(self, name):
        f = self._frame
        co = f.f_code
        if name in co._name_to_offset_mapping:
            index = co._name_to_offset_mapping[name]
            kind = co._local_kinds[index]
            if co._is_cell(offset)
                cell = f._locals[index]
                cell.cell_contents = NULL
            else:
                f._fast_locals[index] = NULL
        # PyEval_GetLocals() interop: implicit frame cache update
        # even for names that are part of the fast locals array
        if f._locals is not NULL:
            del f._locals[name]

    def __iter__(self):
        f = self._frame
        co = f.f_code
        for index, name in enumerate(co._variable_names):
            val = f._fast_locals[index]
            if val is NULL:
                continue
            if co._is_cell(offset):
                val = val.cell_contents
                if val is NULL:
                    continue
            yield name
        for name in f._locals:
            # Yield any extra names not defined on the frame
            if name in co._name_to_offset_mapping:
                continue
            yield name

    def popitem(self):
        f = self._frame
        co = f.f_code
        for name in self:
            val = self[name]
        # PyEval_GetLocals() interop: implicit frame cache update
        # even for names that are part of the fast locals array
        del name
        return name, val

    def _sync_frame_cache(self):
        # This method underpins PyEval_GetLocals, PyFrame_FastToLocals
        # PyFrame_GetLocals, PyLocals_Get, mapping comparison, etc
        f = self._frame
        co = f.f_code
        res = 0
        if f._locals is NULL:
            f._locals = {}
        for index, name in enumerate(co._variable_names):
            val = f._fast_locals[index]
            if val is NULL:
                f._locals.pop(name, None)
                continue
            if co._is_cell(offset):
                if val.cell_contents is NULL:
                    f._locals.pop(name, None)
                    continue
            f._locals[name] = val

    def __len__(self):
        self._sync_frame_cache()
        return len(self._locals)

Note: the simplest way to convert the earlier iterations of the PEP 558 reference implementation into a preliminary implementation of the now proposed semantics is to remove the frame_cache_updated checks in affected operations, and instead always sync the frame cache in those methods. Adopting that approach changes the algorithmic complexity of the following operations as shown (where n is the number of local and cell variables defined on the frame):

• __len__: O(1) -> O(n)
• value comparison operations: no longer benefit from O(1) length check shortcut
• __iter__: O(1) -> O(n)
• __reversed__: O(1) -> O(n)
• keys(): O(1) -> O(n)
• values(): O(1) -> O(n)
• items(): O(1) -> O(n)
• popitem(): O(1) -> O(n)

The length check and value comparison operations have relatively limited opportunities for improvement: without allowing usage of a potentially stale cache, the only way to know how many variables are currently bound is to iterate over all of them and check, and if the implementation is going to be spending that many cycles on an operation anyway, it may as well spend it updating the frame value cache and then consuming the result. These operations are O(n) in both this PEP and in PEP 667. Customised implementations could be provided that are faster than updating the frame cache, but it’s far from clear that the extra code complexity needed to speed these operations up would be worthwhile when it only offers a linear performance improvement rather than an algorithmic complexity improvement.

The O(1) nature of the other operations can be restored by adding implementation code that doesn’t rely on the value cache being up to date.

Keeping the iterator/iterable retrieval methods as O(1) will involve writing custom replacements for the corresponding builtin dict helper types, just as proposed in PEP 667. As illustrated above, the implementations would be similar to the pseudo-code presented in PEP 667, but not identical (due to the improved PyEval_GetLocals() interoperability offered by this PEP affecting the way it stores extra variables).

popitem() can be improved from “always O(n)” to “O(n) worst case” by creating a custom implementation that relies on the improved iteration APIs.

To ensure stale frame information is never presented in the Python fast locals proxy API, these changes in the reference implementation will need to be implemented before merging.

The current implementation at time of writing (2021-10-24) also still stores a copy of the fast refs mapping on each frame rather than storing a single instance on the underlying code object (as it still stores cell references directly, rather than check for cells on each fast locals array access). Fixing this would also be required before merging.