A first attempt to implement guards was the readonly PoC (fork of CPython 3.5) which registered callbacks to notify all guards. The problem is that modifying a watched dictionary gets a complexity of O(n) where n is the number of registered guards.
readonly adds a
modified flag to types and a
readonly property to
dictionaries. The guard was notified with the modified key to decide to disable
or not the optimization.
More information: READONLY.txt
Thread on the python-ideas mailing list: Make Python code read-only.
The project was mostly developed in May 2014. The project is now dead, replaced with FAT Python.
This fork on CPython 3.5 adds a machinery to be notified when the Python code is modified. Modules, classes (types) and functions are tracked. At the first modification, a callback is called with the object and the modified attribute.
This machinery should help static optimizers. See this article for more information: https://haypo-notes.readthedocs.io/faster_cpython.html
Examples of such optimizers:
- astoptimizer project: replace a function call by its result during the AST compilation
- Learn types of function paramters and local variables, and then compile Python (byte)code to machine code specialized for these types (like Cython)
Issues with read-only code¶
- Currently, it’s not possible to allow again to modify a module, class or function to keep my implementation simple. With a registry of callbacks, it may be possible to enable again modification and call code to disable optimizations.
- PyPy implements this but thanks to its JIT, it can optimize again the modified code during the execution. Writing a JIT is very complex, I’m trying to find a compromise between the fast PyPy and the slow CPython. Add a JIT to CPython is out of my scope, it requires too much modifications of the code.
- With read-only code, monkey-patching cannot be used anymore. It’s annoying to run tests. An obvious solution is to disable read-only mode to run tests, which can be seen as unsafe since tests are usually used to trust the code.
- The sys module cannot be made read-only because modifying sys.stdout and sys.ps1 is a common use case.
- The warnings module tries to add a __warningregistry__ global variable in the module where the warning was emited to not repeat warnings that should only be emited once. The problem is that the module namespace is made read-only before this variable is added. A workaround would be to maintain these dictionaries in the warnings module directly, but it becomes harder to clear the dictionary when a module is unloaded or reloaded. Another workaround is to add __warningregistry__ before making a module read-only.
- Lazy initialization of module variables does not work anymore. A workaround is to use a mutable type. It can be a dict used as a namespace for module modifiable variables.
- The interactive interpreter sets a “_” variable in the builtins namespace. I have no workaround for this. The “_” variable is no more created in read-only mode. Don’t run the interactive interpreter in read-only mode.
- It is not possible yet to make the namespace of packages read-only. For example, “import encodings.utf_8” adds the symbol “utf_8” to the encodings namespace. A workaround is to load all submodules before making the namespace read-only. This cannot be done for some large modules. For example, the encodings has a lot of submodules, only a few are needed.
- Python API:
- new function.__modified__ and type.__modified__ properties: False by default, becomes True when the object is modified
- new module.is_modified() method
- new module.set_initialized() method
- C API:
- PyDictObject: new “int ma_readonly;” field
- PyTypeObject: a new “int tp_modified;” field
- PyFunctionObject: new “int func_module;” and “int func_initialized;” fields
- PyModuleObject: new “int md_initialized;” field
Modified modules, classes and functions¶
- It’s common to modify the following attributes of the sys module:
- sys.ps1, sys.ps2
- sys.stdin, sys.stdout, sys.stderr
- “import encodings.latin_1” sets “latin_1” attribute in the namespace of the “encodings” module.
- The interactive interpreter sets the “_” variable in builtins.
- warnings: global variable __warningregistry__ set in modules
- functools.wraps() modifies the wrapper to copy attributes of the wrapped function
- builtins modified in initstdio(): builtins.open modified
- sys modified in initstdio(): sys.__stdin__ modified
- structseq: types are created modified; same issue with _ast types (Python-ast.c)
- module, type and function __dict__:
- Drop dict.setreadonly()
- Decide if it’s better to use dict.setreadonly() or a new subclass (ex: “dict_maybe_readonly” or “namespace”).
- Read only dict: add a new ReadOnlyError instead of ValueError?
- sysmodule.c: PyDict_DelItemString(FlagsType.tp_dict, “__new__”) doesn’t mark FlagsType as modified
- Getting func.__dict__ / module.__dict__ marks the function/module as modified, this is wrong. Use instead a mapping marking the function as modified when the mapping is modified.
- module.__dict__ is read-only: similar issue for functions.
- Import submodule. Example: “import encodings.utf_8” modifies “encoding” to set a new utf_8 attribute
TODO: Specialized functions¶
- module and type attribute values:
- (“module”, “os”, OS_CHECKSUM)
- (“attribute”, “os.path”)
- (“module”, “path”, PATH_CHECKSUM)
- (“attribute”, “path.isabs”)
- (“function”, “path.isabs”)
- function attributes
- set of function parameter types (passed as indexed or keyword arguments)
- 1: application.py is compiled. Function A depends on os.path.isabs, function B depends on project.DEBUG
- 2: application is started, “import os.path”
- 3: os.path.isabs is modified
- 4: optimized application.py is loaded
- 5: project.DEBUG is modified
When the function is created, os.path.isabs was already modified compared to the OS_CHECKSUM.
Example of environments¶
- The function calls “os.path.isabs”:
- rely on “os.path” attribute
- rely on “os.path.isabs” attribute
- rely on “os.path.isabs” function attributes (except __doc__)
- The function “def mysum(x, y):” has two parameters
- x type is int and y type is int
- or: x type is str and y type is str
- (“type is”: check the exact type, not a subclass)
- The function uses “project.DEBUG” constant
- rely on “project.DEBUG” attribute
Content of a function¶
- classic attributes: doc, etc.
- multiple versions of the code:
- required environment of the code
Create a function¶
- build the environment
- register on module, type and functions modification
Callback when then environment is modified¶
Call a function¶