PEP: 339 Title: Design of the CPython Compiler Version: $Revision$
Last-Modified: $Date$ Author: Brett Cannon <brett@python.org> Status:
Withdrawn Type: Informational Content-Type: text/x-rst Created:
02-Feb-2005 Post-History:

Note

This PEP has been withdrawn and moved to the Python developer's guide.

Abstract

Historically (through 2.4), compilation from source code to bytecode
involved two steps:

1.  Parse the source code into a parse tree (Parser/pgen.c)
2.  Emit bytecode based on the parse tree (Python/compile.c)

Historically, this is not how a standard compiler works. The usual steps
for compilation are:

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)

Starting with Python 2.5, the above steps are now used. This change was
done to simplify compilation by breaking it into three steps. The
purpose of this document is to outline how the latter three steps of the
process works.

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.

Parse Trees

Python's parser is an LL(1) parser mostly based on 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 are 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 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/token.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

To tie all of this 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 if there is an 'else'
statement. To access what should be the first ':' and require it be an
actual ':' token, (REQ(CHILD(node, 2), COLON).

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, 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.

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 needs to
only 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().

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 what 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:

-   

    asdl_seq_new()

        Allocate memory for an asdl_seq for the specified length

-   

    asdl_seq_GET()

        Get item held at a specific position in an asdl_seq

-   

    asdl_seq_SET()

        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.

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.

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()

        add a specified opcode

-   

    ADDOP_I()

        add an opcode that takes an argument

-   

    ADDOP_O(struct compiler *c, int op, PyObject *type, PyObject *obj)

        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()

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

-   

    ADDOP_JABS()

        create an absolute jump to a basic block

-   

    ADDOP_JREL()

        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, 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:

-   

    NEW_BLOCK()

        create block and set it as current

-   

    NEXT_BLOCK()

        basically NEW_BLOCK() plus jump from current block

-   

    compiler_new_block()

        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 file is created. All of this is
handled by calling assemble() .

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.

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) is 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_EvalFrameEx().

Important Files

-   Parser/
    -   

        Python.asdl

            ASDL syntax file

    -   

        asdl.py

            "An implementation of the Zephyr Abstract Syntax Definition
            Language." Uses SPARK to parse the ASDL files.

    -   

        asdl_c.py

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

    -   

        spark.py

            SPARK parser generator
-   Python/
    -   

        Python-ast.c

            Creates C structs corresponding to the ASDL types. Also
            contains code for marshaling AST nodes (core ASDL types have
            marshaling 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 marshaling
            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.

    -   compiler/
        -   

            pyassem.py

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

        -   

            pycodegen.py

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

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.

References



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  sentence-end-double-space: t fill-column: 80 End:

Aho86

    Alfred V. Aho, Ravi Sethi, Jeffrey D. Ullman.
    Compilers: Principles, Techniques, and Tools,
    http://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://legacy.python.org/workshops/1998-11/proceedings/papers/montanaro/montanaro.html)

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

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