25. Design of CPython’s Compiler

25.1. Abstract

In CPython, the compilation from source code to bytecode involves several steps:

  1. Tokenize the source code (Parser/tokenizer.c)

  2. Parse the stream of tokens into an Abstract Syntax Tree (Parser/parser.c)

  3. Transform AST into a Control Flow Graph (Python/compile.c)

  4. Emit bytecode based on the Control Flow Graph (Python/compile.c)

The purpose of this document is to outline how these steps of the process work.

This document does not touch on how parsing works beyond what is needed to explain what is needed for compilation. It is also not exhaustive in terms of the how the entire system works. You will most likely need to read some source to have an exact understanding of all details.

25.2. Parsing

As of Python 3.9, Python’s parser is a PEG parser of a somewhat unusual design (since its input is a stream of tokens rather than a stream of characters as is more common with PEG parsers).

The grammar file for Python can be found in Grammar/python.gram. The definitions for literal tokens (such as :, numbers, etc.) can be found in Grammar/Tokens. Various C files, including Parser/parser.c are generated from these (see Changing CPython’s Grammar).

25.3. Abstract Syntax Trees (AST)

Green Tree Snakes

See also Green Tree Snakes - the missing Python AST docs by Thomas Kluyver.

The abstract syntax tree (AST) is a high-level representation of the program structure without the necessity of containing the source code; it can be thought of as an abstract representation of the source code. The specification of the AST nodes is specified using the Zephyr Abstract Syntax Definition Language (ASDL) [Wang97].

The definition of the AST nodes for Python is found in the file Parser/Python.asdl.

Each AST node (representing statements, expressions, and several specialized types, like list comprehensions and exception handlers) is defined by the ASDL. Most definitions in the AST correspond to a particular source construct, such as an ‘if’ statement or an attribute lookup. The definition is independent of its realization in any particular programming language.

The following fragment of the Python ASDL construct demonstrates the approach and syntax:

  1. module Python
  2. {
  3.     stmt = FunctionDef(identifier name, arguments args, stmt* body,
  4.                        expr* decorators)
  5.            | Return(expr? value) | Yield(expr? value)
  6.            attributes (int lineno)
  7. }

The preceding example describes two different kinds of statements and an expression: function definitions, return statements, and yield expressions. All three kinds are considered of type stmt as shown by | separating the various kinds. They all take arguments of various kinds and amounts.

Modifiers on the argument type specify the number of values needed; ? means it is optional, * means 0 or more, while no modifier means only one value for the argument and it is required. FunctionDef, for instance, takes an identifier for the name, arguments for args, zero or more stmt arguments for body, and zero or more expr arguments for decorators.

Do notice that something like ‘arguments’, which is a node type, is represented as a single AST node and not as a sequence of nodes as with stmt as one might expect.

All three kinds also have an ‘attributes’ argument; this is shown by the fact that ‘attributes’ lacks a ‘|’ before it.

The statement definitions above generate the following C structure type:

  1. typedef struct _stmt *stmt_ty;
  3. struct _stmt {
  4.       enum { FunctionDef_kind=1, Return_kind=2, Yield_kind=3 } kind;
  5.       union {
  6.               struct {
  7.                       identifier name;
  8.                       arguments_ty args;
  9.                       asdl_seq *body;
  10.               } FunctionDef;
  12.               struct {
  13.                       expr_ty value;
  14.               } Return;
  16.               struct {
  17.                       expr_ty value;
  18.               } Yield;
  19.       } v;
  20.       int lineno;
  21.  }

Also generated are a series of constructor functions that allocate (in this case) a stmt_ty struct with the appropriate initialization. The kind field specifies which component of the union is initialized. The FunctionDef() constructor function sets ‘kind’ to FunctionDef_kind and initializes the name, args, body, and attributes fields.

25.4. Memory Management

Before discussing the actual implementation of the compiler, a discussion of how memory is handled is in order. To make memory management simple, an arena is used. This means that a memory is pooled in a single location for easy allocation and removal. What this gives us is the removal of explicit memory deallocation. Because memory allocation for all needed memory in the compiler registers that memory with the arena, a single call to free the arena is all that is needed to completely free all memory used by the compiler.

In general, unless you are working on the critical core of the compiler, memory management can be completely ignored. But if you are working at either the very beginning of the compiler or the end, you need to care about how the arena works. All code relating to the arena is in either Include/pyarena.h or Python/pyarena.c.

PyArena_New() will create a new arena. The returned PyArena structure will store pointers to all memory given to it. This does the bookkeeping of what memory needs to be freed when the compiler is finished with the memory it used. That freeing is done with PyArena_Free(). This only needs to be called in strategic areas where the compiler exits.

As stated above, in general you should not have to worry about memory management when working on the compiler. The technical details have been designed to be hidden from you for most cases.

The only exception comes about when managing a PyObject. Since the rest of Python uses reference counting, there is extra support added to the arena to cleanup each PyObject that was allocated. These cases are very rare. However, if you’ve allocated a PyObject, you must tell the arena about it by calling PyArena_AddPyObject().

25.5. Parse Tree to AST

The AST is generated from the parse tree (see Python/ast.c) using the function PyAST_FromNode().

The function begins a tree walk of the parse tree, creating various AST nodes as it goes along. It does this by allocating all new nodes it needs, calling the proper AST node creation functions for any required supporting functions, and connecting them as needed.

Do realize that there is no automated nor symbolic connection between the grammar specification and the nodes in the parse tree. No help is directly provided by the parse tree as in yacc.

For instance, one must keep track of which node in the parse tree one is working with (e.g., if you are working with an ‘if’ statement you need to watch out for the ‘:’ token to find the end of the conditional).

The functions called to generate AST nodes from the parse tree all have the name ast_for_*xx* where xx is the grammar rule that the function handles (alias_for_import_name is the exception to this). These in turn call the constructor functions as defined by the ASDL grammar and contained in Python/Python-ast.c (which was generated by Parser/asdl_c.py) to create the nodes of the AST. This all leads to a sequence of AST nodes stored in asdl_seq structs.

Function and macros for creating and using asdl_seq * types as found in Python/asdl.c and Include/asdl.h are as follows:

_Py_asdl_seq_new(Py_ssize_t, PyArena *)

Allocate memory for an asdl_seq for the specified length

asdl_seq_GET(asdl_seq *, int)

Get item held at a specific position in an asdl_seq

asdl_seq_SET(asdl_seq *, int, stmt_ty)

Set a specific index in an asdl_seq to the specified value

asdl_seq_LEN(asdl_seq *)

Return the length of an asdl_seq

If you are working with statements, you must also worry about keeping track of what line number generated the statement. Currently the line number is passed as the last parameter to each stmt_ty function.

25.6. Control Flow Graphs

A control flow graph (often referenced by its acronym, CFG) is a directed graph that models the flow of a program using basic blocks that contain the intermediate representation (abbreviated “IR”, and in this case is Python bytecode) within the blocks. Basic blocks themselves are a block of IR that has a single entry point but possibly multiple exit points. The single entry point is the key to basic blocks; it all has to do with jumps. An entry point is the target of something that changes control flow (such as a function call or a jump) while exit points are instructions that would change the flow of the program (such as jumps and ‘return’ statements). What this means is that a basic block is a chunk of code that starts at the entry point and runs to an exit point or the end of the block.

As an example, consider an ‘if’ statement with an ‘else’ block. The guard on the ‘if’ is a basic block which is pointed to by the basic block containing the code leading to the ‘if’ statement. The ‘if’ statement block contains jumps (which are exit points) to the true body of the ‘if’ and the ‘else’ body (which may be NULL), each of which are their own basic blocks. Both of those blocks in turn point to the basic block representing the code following the entire ‘if’ statement.

CFGs are usually one step away from final code output. Code is directly generated from the basic blocks (with jump targets adjusted based on the output order) by doing a post-order depth-first search on the CFG following the edges.

25.7. AST to CFG to Bytecode

With the AST created, the next step is to create the CFG. The first step is to convert the AST to Python bytecode without having jump targets resolved to specific offsets (this is calculated when the CFG goes to final bytecode). Essentially, this transforms the AST into Python bytecode with control flow represented by the edges of the CFG.

Conversion is done in two passes. The first creates the namespace (variables can be classified as local, free/cell for closures, or global). With that done, the second pass essentially flattens the CFG into a list and calculates jump offsets for final output of bytecode.

The conversion process is initiated by a call to the function PyAST_CompileObject() in Python/compile.c. This function does both the conversion of the AST to a CFG and outputting final bytecode from the CFG. The AST to CFG step is handled mostly by two functions called by PyAST_CompileObject(); PySymtable_BuildObject() and compiler_mod(). The former is in Python/symtable.c while the latter is in Python/compile.c.

PySymtable_BuildObject() begins by entering the starting code block for the AST (passed-in) and then calling the proper symtable_visit_*xx* function (with xx being the AST node type). Next, the AST tree is walked with the various code blocks that delineate the reach of a local variable as blocks are entered and exited using symtable_enter_block() and symtable_exit_block(), respectively.

Once the symbol table is created, it is time for CFG creation, whose code is in Python/compile.c. This is handled by several functions that break the task down by various AST node types. The functions are all named compiler_visit_*xx* where xx is the name of the node type (such as stmt, expr, etc.). Each function receives a struct compiler * and *xx*_ty where xx is the AST node type. Typically these functions consist of a large ‘switch’ statement, branching based on the kind of node type passed to it. Simple things are handled inline in the ‘switch’ statement with more complex transformations farmed out to other functions named compiler_*xx* with xx being a descriptive name of what is being handled.

When transforming an arbitrary AST node, use the VISIT() macro. The appropriate compiler_visit_*xx* function is called, based on the value passed in for <node type> (so VISIT(*c*, expr, *node*) calls compiler_visit_expr(*c*, *node*)). The VISIT_SEQ() macro is very similar, but is called on AST node sequences (those values that were created as arguments to a node that used the ‘*’ modifier). There is also VISIT_SLICE() just for handling slices.

Emission of bytecode is handled by the following macros:

ADDOP(struct compiler *, int)

add a specified opcode

ADDOP_I(struct compiler *, int, Py_ssize_t)

add an opcode that takes an integer argument

ADDOP_O(struct compiler *, int, PyObject *, TYPE)

add an opcode with the proper argument based on the position of the specified PyObject in PyObject sequence object, but with no handling of mangled names; used for when you need to do named lookups of objects such as globals, consts, or parameters where name mangling is not possible and the scope of the name is known; TYPE is the name of PyObject sequence (names or varnames)

ADDOP_N(struct compiler *, int, PyObject *, TYPE)

just like ADDOP_O, but steals a reference to PyObject

ADDOP_NAME(struct compiler *, int, PyObject *, TYPE)

just like ADDOP_O, but name mangling is also handled; used for attribute loading or importing based on name

ADDOP_LOAD_CONST(struct compiler *, PyObject *)

add the LOAD_CONST opcode with the proper argument based on the position of the specified PyObject in the consts table.

ADDOP_LOAD_CONST_NEW(struct compiler *, PyObject *)

just like ADDOP_LOAD_CONST_NEW, but steals a reference to PyObject

ADDOP_JABS(struct compiler *, int, basicblock *)

create an absolute jump to a basic block

ADDOP_JREL(struct compiler *, int, basicblock *)

create a relative jump to a basic block

Several helper functions that will emit bytecode and are named compiler_*xx*() where xx is what the function helps with (list, boolop, etc.). A rather useful one is compiler_nameop(). This function looks up the scope of a variable and, based on the expression context, emits the proper opcode to load, store, or delete the variable.

As for handling the line number on which a statement is defined, this is handled by compiler_visit_stmt() and thus is not a worry.

In addition to emitting bytecode based on the AST node, handling the creation of basic blocks must be done. Below are the macros and functions used for managing basic blocks:

NEXT_BLOCK(struct compiler *)

create an implicit jump from the current block to the new block

compiler_new_block(struct compiler *)

create a block but don’t use it (used for generating jumps)

compiler_use_next_block(struct compiler *, basicblock *block)

set a previously created block as a current block

Once the CFG is created, it must be flattened and then final emission of bytecode occurs. Flattening is handled using a post-order depth-first search. Once flattened, jump offsets are backpatched based on the flattening and then a PyCodeObject is created. All of this is handled by calling assemble().

25.8. Introducing New Bytecode

Sometimes a new feature requires a new opcode. But adding new bytecode is not as simple as just suddenly introducing new bytecode in the AST -> bytecode step of the compiler. Several pieces of code throughout Python depend on having correct information about what bytecode exists.

First, you must choose a name and a unique identifier number. The official list of bytecode can be found in Lib/opcode.py. If the opcode is to take an argument, it must be given a unique number greater than that assigned to HAVE_ARGUMENT (as found in Lib/opcode.py).

Once the name/number pair has been chosen and entered in Lib/opcode.py, you must also enter it into Doc/library/dis.rst, and regenerate Include/opcode.h and Python/opcode_targets.h by running make regen-opcode regen-opcode-targets.

With a new bytecode you must also change what is called the magic number for .pyc files. The variable MAGIC_NUMBER in Lib/importlib/_bootstrap_external.py contains the number. Changing this number will lead to all .pyc files with the old MAGIC_NUMBER to be recompiled by the interpreter on import. Whenever MAGIC_NUMBER is changed, the ranges in the magic_values array in PC/launcher.c must also be updated. Changes to Lib/importlib/_bootstrap_external.py will take effect only after running make regen-importlib. Running this command before adding the new bytecode target to Python/ceval.c will result in an error. You should only run make regen-importlib after the new bytecode target has been added.

Finally, you need to introduce the use of the new bytecode. Altering Python/compile.c and Python/ceval.c will be the primary places to change. You must add the case for a new opcode into the ‘switch’ statement in the stack_effect() function in Python/compile.c. If the new opcode has a jump target, you will need to update macros and ‘switch’ statements in Python/peephole.c. If it affects a control flow or the block stack, you may have to update the frame_setlineno() function in Objects/frameobject.c. Lib/dis.py may need an update if the new opcode interprets its argument in a special way (like FORMAT_VALUE or MAKE_FUNCTION).

If you make a change here that can affect the output of bytecode that is already in existence and you do not change the magic number constantly, make sure to delete your old .py(c|o) files! Even though you will end up changing the magic number if you change the bytecode, while you are debugging your work you will be changing the bytecode output without constantly bumping up the magic number. This means you end up with stale .pyc files that will not be recreated. Running find . -name '*.py[co]' -exec rm -f '{}' + should delete all .pyc files you have, forcing new ones to be created and thus allow you test out your new bytecode properly. Run make regen-importlib for updating the bytecode of frozen importlib files. You have to run make again after this for recompiling generated C files.

25.9. Code Objects

The result of PyAST_CompileObject() is a PyCodeObject which is defined in Include/code.h. And with that you now have executable Python bytecode!

The code objects (byte code) are executed in Python/ceval.c. This file will also need a new case statement for the new opcode in the big switch statement in _PyEval_EvalFrameDefault().

25.10. Important Files

  • Parser/

    Python.asdl

    ASDL syntax file

    asdl.py

    Parser for ASDL definition files. Reads in an ASDL description and parses it into an AST that describes it.

    asdl_c.py

    “Generate C code from an ASDL description.” Generates Python/Python-ast.c and Include/Python-ast.h.

  • Python/

    Python-ast.c

    Creates C structs corresponding to the ASDL types. Also contains code for marshalling AST nodes (core ASDL types have marshalling code in asdl.c). “File automatically generated by Parser/asdl_c.py”. This file must be committed separately after every grammar change is committed since the __version__ value is set to the latest grammar change revision number.

    asdl.c

    Contains code to handle the ASDL sequence type. Also has code to handle marshalling the core ASDL types, such as number and identifier. Used by Python-ast.c for marshalling AST nodes.

    ast.c

    Converts Python’s parse tree into the abstract syntax tree.

    ast_opt.c

    Optimizes the AST.

    ast_unparse.c

    Converts the AST expression node back into a string (for string annotations).

    ceval.c

    Executes byte code (aka, eval loop).

    compile.c

    Emits bytecode based on the AST.

    symtable.c

    Generates a symbol table from AST.

    peephole.c

    Optimizes the bytecode.

    pyarena.c

    Implementation of the arena memory manager.

    wordcode_helpers.h

    Helpers for generating bytecode.

    opcode_targets.h

    One of the files that must be modified if Lib/opcode.py is.

  • Include/

    Python-ast.h

    Contains the actual definitions of the C structs as generated by Python/Python-ast.c. “Automatically generated by Parser/asdl_c.py”.

    asdl.h

    Header for the corresponding Python/ast.c.

    ast.h

    Declares PyAST_FromNode() external (from Python/ast.c).

    code.h

    Header file for Objects/codeobject.c; contains definition of PyCodeObject.

    symtable.h

    Header for Python/symtable.c. struct symtable and PySTEntryObject are defined here.

    pyarena.h

    Header file for the corresponding Python/pyarena.c.

    opcode.h

    One of the files that must be modified if Lib/opcode.py is.

  • Objects/

    codeobject.c

    Contains PyCodeObject-related code (originally in Python/compile.c).

    frameobject.c

    Contains the frame_setlineno() function which should determine whether it is allowed to make a jump between two points in a bytecode.

  • Lib/

    opcode.py

    Master list of bytecode; if this file is modified you must modify several other files accordingly (see “Introducing New Bytecode”)

    importlib/_bootstrap_external.py

    Home of the magic number (named MAGIC_NUMBER) for bytecode versioning.

25.11. Known Compiler-related Experiments

This section lists known experiments involving the compiler (including bytecode).

Skip Montanaro presented a paper at a Python workshop on a peephole optimizer 1.

Michael Hudson has a non-active SourceForge project named Bytecodehacks 2 that provides functionality for playing with bytecode directly.

An opcode to combine the functionality of LOAD_ATTR/CALL_FUNCTION was created named CALL_ATTR 3. Currently only works for classic classes and for new-style classes rough benchmarking showed an actual slowdown thanks to having to support both classic and new-style classes.

25.12. References

Wang97

Daniel C. Wang, Andrew W. Appel, Jeff L. Korn, and Chris S. Serra. The Zephyr Abstract Syntax Description Language. In Proceedings of the Conference on Domain-Specific Languages, pp. 213–227, 1997.

1

Skip Montanaro’s Peephole Optimizer Paper (https://drive.google.com/open?id=0B2InO7qBBGRXQXlDM3FVdWZxQWc)

2

Bytecodehacks Project (http://bytecodehacks.sourceforge.net/bch-docs/bch/index.html)

3

CALL_ATTR opcode (https://bugs.python.org/issue709744)