26. Design of CPython’s Compiler

26.1. Abstract

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

1. Parse source code into a parse tree (Parser/pgen.c)
2. Transform parse tree into an Abstract Syntax Tree (Python/ast.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.

26.2. Parse Trees

Python’s parser is an LL(1) parser mostly based off of the implementation laid out in the Dragon Book [Aho86].

The grammar file for Python can be found in Grammar/Grammar with the numeric value of grammar rules stored in Include/graminit.h. The numeric values for types of tokens (literal tokens, such as :, numbers, etc.) are kept in Include/token.h. The parse tree is made up of node * structs (as defined in Include/node.h).

Querying data from the node structs can be done with the following macros (which are all defined in Include/node.h):

CHILD(node *, int)

Returns the nth child of the node using zero-offset indexing

RCHILD(node *, int)

Returns the nth child of the node from the right side; use negative numbers!

NCH(node *)

Number of children the node has

STR(node *)

String representation of the node; e.g., will return : for a COLON token

TYPE(node *)

The type of node as specified in Include/graminit.h

REQ(node *, TYPE)

Assert that the node is the type that is expected

LINENO(node *)

retrieve the line number of the source code that led to the creation of the parse rule; defined in Python/ast.c

For example, consider the rule for ‘while’:

while_stmt: 'while' test ':' suite ['else' ':' suite]

The node representing this will have TYPE(node) == while_stmt and the number of children can be 4 or 7 depending on whether there is an ‘else’ statement. REQ(CHILD(node, 2), COLON) can be used to access what should be the first : and require it be an actual : token.

26.3. Abstract Syntax Trees (AST)

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:

module Python
{
      stmt = FunctionDef(identifier name, arguments args, stmt* body,
                          expr* decorators)
            | Return(expr? value) | Yield(expr value)
            attributes (int lineno)
}

The preceding example describes three different kinds of statements; function definitions, return statements, and yield statements. 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:

typedef struct _stmt *stmt_ty;

struct _stmt {
      enum { FunctionDef_kind=1, Return_kind=2, Yield_kind=3 } kind;
      union {
              struct {
                      identifier name;
                      arguments_ty args;
                      asdl_seq *body;
              } FunctionDef;

              struct {
                      expr_ty value;
              } Return;

              struct {
                      expr_ty value;
              } Yield;
      } v;
      int lineno;
 }

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.

26.4. 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().

26.5. 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.

26.6. 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.

26.7. 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_Compile() 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_Compile(); PySymtable_Build() and compiler_mod(). The former is in Python/symtable.c while the latter is in Python/compile.c.

PySymtable_Build() 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 argument

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

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

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

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

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 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)

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().

26.8. 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 Include/opcode.h. 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 Include/opcode.h).

Once the name/number pair has been chosen and entered in Include/opcode.h, you must also enter it into Lib/opcode.py and Doc/library/dis.rst.

With a new bytecode you must also change what is called the magic number for .pyc files. The variable MAGIC in Python/import.c contains the number. Changing this number will lead to all .pyc files with the old MAGIC to be recompiled by the interpreter on import.

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. But you will also need to change the ‘compiler’ package. The key files to do that are Lib/compiler/pyassem.py and Lib/compiler/pycodegen.py.

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.

26.9. Code Objects

The result of PyAST_Compile() 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().

26.10. 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.

  ceval.c

  Executes byte code (aka, eval loop).

  compile.c

  Emits bytecode based on the AST.

  symtable.c

  Generates a symbol table from AST.

  pyarena.c

  Implementation of the arena memory manager.

  import.c

  Home of the magic number (named MAGIC) for bytecode versioning

• 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

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

• Objects/

  codeobject.c

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

• Lib/

  opcode.py

  One of the files that must be modified if Include/opcode.h is.

26.11. 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.

26.12. References

[Aho86]

Alfred V. Aho, Ravi Sethi, Jeffrey D. Ullman. Compilers: Principles, Techniques, and Tools, https://www.amazon.com/exec/obidos/tg/detail/-/0201100886/104-0162389-6419108

[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)