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:mod:`parser` --- Access Python parse trees
===========================================
.. module:: parser
:synopsis: Access parse trees for Python source code.
.. moduleauthor:: Fred L. Drake, Jr. <fdrake@acm.org>
.. sectionauthor:: Fred L. Drake, Jr. <fdrake@acm.org>
.. Copyright 1995 Virginia Polytechnic Institute and State University and Fred
L. Drake, Jr. This copyright notice must be distributed on all copies, but
this document otherwise may be distributed as part of the Python
distribution. No fee may be charged for this document in any representation,
either on paper or electronically. This restriction does not affect other
elements in a distributed package in any way.
.. index:: single: parsing; Python source code
The :mod:`parser` module provides an interface to Python's internal parser and
byte-code compiler. The primary purpose for this interface is to allow Python
code to edit the parse tree of a Python expression and create executable code
from this. This is better than trying to parse and modify an arbitrary Python
code fragment as a string because parsing is performed in a manner identical to
the code forming the application. It is also faster.
.. note::
From Python 2.5 onward, it's much more convenient to cut in at the Abstract
Syntax Tree (AST) generation and compilation stage, using the :mod:`ast`
module.
There are a few things to note about this module which are important to making
use of the data structures created. This is not a tutorial on editing the parse
trees for Python code, but some examples of using the :mod:`parser` module are
presented.
Most importantly, a good understanding of the Python grammar processed by the
internal parser is required. For full information on the language syntax, refer
to :ref:`reference-index`. The parser
itself is created from a grammar specification defined in the file
:file:`Grammar/Grammar` in the standard Python distribution. The parse trees
stored in the ST objects created by this module are the actual output from the
internal parser when created by the :func:`expr` or :func:`suite` functions,
described below. The ST objects created by :func:`sequence2st` faithfully
simulate those structures. Be aware that the values of the sequences which are
considered "correct" will vary from one version of Python to another as the
formal grammar for the language is revised. However, transporting code from one
Python version to another as source text will always allow correct parse trees
to be created in the target version, with the only restriction being that
migrating to an older version of the interpreter will not support more recent
language constructs. The parse trees are not typically compatible from one
version to another, whereas source code has always been forward-compatible.
Each element of the sequences returned by :func:`st2list` or :func:`st2tuple`
has a simple form. Sequences representing non-terminal elements in the grammar
always have a length greater than one. The first element is an integer which
identifies a production in the grammar. These integers are given symbolic names
in the C header file :file:`Include/graminit.h` and the Python module
:mod:`symbol`. Each additional element of the sequence represents a component
of the production as recognized in the input string: these are always sequences
which have the same form as the parent. An important aspect of this structure
which should be noted is that keywords used to identify the parent node type,
such as the keyword :keyword:`if` in an :const:`if_stmt`, are included in the
node tree without any special treatment. For example, the :keyword:`if` keyword
is represented by the tuple ``(1, 'if')``, where ``1`` is the numeric value
associated with all :const:`NAME` tokens, including variable and function names
defined by the user. In an alternate form returned when line number information
is requested, the same token might be represented as ``(1, 'if', 12)``, where
the ``12`` represents the line number at which the terminal symbol was found.
Terminal elements are represented in much the same way, but without any child
elements and the addition of the source text which was identified. The example
of the :keyword:`if` keyword above is representative. The various types of
terminal symbols are defined in the C header file :file:`Include/token.h` and
the Python module :mod:`token`.
The ST objects are not required to support the functionality of this module,
but are provided for three purposes: to allow an application to amortize the
cost of processing complex parse trees, to provide a parse tree representation
which conserves memory space when compared to the Python list or tuple
representation, and to ease the creation of additional modules in C which
manipulate parse trees. A simple "wrapper" class may be created in Python to
hide the use of ST objects.
The :mod:`parser` module defines functions for a few distinct purposes. The
most important purposes are to create ST objects and to convert ST objects to
other representations such as parse trees and compiled code objects, but there
are also functions which serve to query the type of parse tree represented by an
ST object.
.. seealso::
Module :mod:`symbol`
Useful constants representing internal nodes of the parse tree.
Module :mod:`token`
Useful constants representing leaf nodes of the parse tree and functions for
testing node values.
.. _creating-sts:
Creating ST Objects
-------------------
ST objects may be created from source code or from a parse tree. When creating
an ST object from source, different functions are used to create the ``'eval'``
and ``'exec'`` forms.
.. function:: expr(source)
The :func:`expr` function parses the parameter *source* as if it were an input
to ``compile(source, 'file.py', 'eval')``. If the parse succeeds, an ST object
is created to hold the internal parse tree representation, otherwise an
appropriate exception is raised.
.. function:: suite(source)
The :func:`suite` function parses the parameter *source* as if it were an input
to ``compile(source, 'file.py', 'exec')``. If the parse succeeds, an ST object
is created to hold the internal parse tree representation, otherwise an
appropriate exception is raised.
.. function:: sequence2st(sequence)
This function accepts a parse tree represented as a sequence and builds an
internal representation if possible. If it can validate that the tree conforms
to the Python grammar and all nodes are valid node types in the host version of
Python, an ST object is created from the internal representation and returned
to the called. If there is a problem creating the internal representation, or
if the tree cannot be validated, a :exc:`ParserError` exception is raised. An
ST object created this way should not be assumed to compile correctly; normal
exceptions raised by compilation may still be initiated when the ST object is
passed to :func:`compilest`. This may indicate problems not related to syntax
(such as a :exc:`MemoryError` exception), but may also be due to constructs such
as the result of parsing ``del f(0)``, which escapes the Python parser but is
checked by the bytecode compiler.
Sequences representing terminal tokens may be represented as either two-element
lists of the form ``(1, 'name')`` or as three-element lists of the form ``(1,
'name', 56)``. If the third element is present, it is assumed to be a valid
line number. The line number may be specified for any subset of the terminal
symbols in the input tree.
.. function:: tuple2st(sequence)
This is the same function as :func:`sequence2st`. This entry point is
maintained for backward compatibility.
.. _converting-sts:
Converting ST Objects
---------------------
ST objects, regardless of the input used to create them, may be converted to
parse trees represented as list- or tuple- trees, or may be compiled into
executable code objects. Parse trees may be extracted with or without line
numbering information.
.. function:: st2list(st[, line_info])
This function accepts an ST object from the caller in *st* and returns a
Python list representing the equivalent parse tree. The resulting list
representation can be used for inspection or the creation of a new parse tree in
list form. This function does not fail so long as memory is available to build
the list representation. If the parse tree will only be used for inspection,
:func:`st2tuple` should be used instead to reduce memory consumption and
fragmentation. When the list representation is required, this function is
significantly faster than retrieving a tuple representation and converting that
to nested lists.
If *line_info* is true, line number information will be included for all
terminal tokens as a third element of the list representing the token. Note
that the line number provided specifies the line on which the token *ends*.
This information is omitted if the flag is false or omitted.
.. function:: st2tuple(st[, line_info])
This function accepts an ST object from the caller in *st* and returns a
Python tuple representing the equivalent parse tree. Other than returning a
tuple instead of a list, this function is identical to :func:`st2list`.
If *line_info* is true, line number information will be included for all
terminal tokens as a third element of the list representing the token. This
information is omitted if the flag is false or omitted.
.. function:: compilest(st[, filename='<syntax-tree>'])
.. index::
builtin: exec
builtin: eval
The Python byte compiler can be invoked on an ST object to produce code objects
which can be used as part of a call to the built-in :func:`exec` or :func:`eval`
functions. This function provides the interface to the compiler, passing the
internal parse tree from *st* to the parser, using the source file name
specified by the *filename* parameter. The default value supplied for *filename*
indicates that the source was an ST object.
Compiling an ST object may result in exceptions related to compilation; an
example would be a :exc:`SyntaxError` caused by the parse tree for ``del f(0)``:
this statement is considered legal within the formal grammar for Python but is
not a legal language construct. The :exc:`SyntaxError` raised for this
condition is actually generated by the Python byte-compiler normally, which is
why it can be raised at this point by the :mod:`parser` module. Most causes of
compilation failure can be diagnosed programmatically by inspection of the parse
tree.
.. _querying-sts:
Queries on ST Objects
---------------------
Two functions are provided which allow an application to determine if an ST was
created as an expression or a suite. Neither of these functions can be used to
determine if an ST was created from source code via :func:`expr` or
:func:`suite` or from a parse tree via :func:`sequence2st`.
.. function:: isexpr(st)
.. index:: builtin: compile
When *st* represents an ``'eval'`` form, this function returns true, otherwise
it returns false. This is useful, since code objects normally cannot be queried
for this information using existing built-in functions. Note that the code
objects created by :func:`compilest` cannot be queried like this either, and
are identical to those created by the built-in :func:`compile` function.
.. function:: issuite(st)
This function mirrors :func:`isexpr` in that it reports whether an ST object
represents an ``'exec'`` form, commonly known as a "suite." It is not safe to
assume that this function is equivalent to ``not isexpr(st)``, as additional
syntactic fragments may be supported in the future.
.. _st-errors:
Exceptions and Error Handling
-----------------------------
The parser module defines a single exception, but may also pass other built-in
exceptions from other portions of the Python runtime environment. See each
function for information about the exceptions it can raise.
.. exception:: ParserError
Exception raised when a failure occurs within the parser module. This is
generally produced for validation failures rather than the built-in
:exc:`SyntaxError` raised during normal parsing. The exception argument is
either a string describing the reason of the failure or a tuple containing a
sequence causing the failure from a parse tree passed to :func:`sequence2st`
and an explanatory string. Calls to :func:`sequence2st` need to be able to
handle either type of exception, while calls to other functions in the module
will only need to be aware of the simple string values.
Note that the functions :func:`compilest`, :func:`expr`, and :func:`suite` may
raise exceptions which are normally thrown by the parsing and compilation
process. These include the built in exceptions :exc:`MemoryError`,
:exc:`OverflowError`, :exc:`SyntaxError`, and :exc:`SystemError`. In these
cases, these exceptions carry all the meaning normally associated with them.
Refer to the descriptions of each function for detailed information.
.. _st-objects:
ST Objects
----------
Ordered and equality comparisons are supported between ST objects. Pickling of
ST objects (using the :mod:`pickle` module) is also supported.
.. data:: STType
The type of the objects returned by :func:`expr`, :func:`suite` and
:func:`sequence2st`.
ST objects have the following methods:
.. method:: ST.compile([filename])
Same as ``compilest(st, filename)``.
.. method:: ST.isexpr()
Same as ``isexpr(st)``.
.. method:: ST.issuite()
Same as ``issuite(st)``.
.. method:: ST.tolist([line_info])
Same as ``st2list(st, line_info)``.
.. method:: ST.totuple([line_info])
Same as ``st2tuple(st, line_info)``.
.. _st-examples:
Examples
--------
.. index:: builtin: compile
The parser modules allows operations to be performed on the parse tree of Python
source code before the :term:`bytecode` is generated, and provides for inspection of the
parse tree for information gathering purposes. Two examples are presented. The
simple example demonstrates emulation of the :func:`compile` built-in function
and the complex example shows the use of a parse tree for information discovery.
Emulation of :func:`compile`
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
While many useful operations may take place between parsing and bytecode
generation, the simplest operation is to do nothing. For this purpose, using
the :mod:`parser` module to produce an intermediate data structure is equivalent
to the code ::
>>> code = compile('a + 5', 'file.py', 'eval')
>>> a = 5
>>> eval(code)
10
The equivalent operation using the :mod:`parser` module is somewhat longer, and
allows the intermediate internal parse tree to be retained as an ST object::
>>> import parser
>>> st = parser.expr('a + 5')
>>> code = st.compile('file.py')
>>> a = 5
>>> eval(code)
10
An application which needs both ST and code objects can package this code into
readily available functions::
import parser
def load_suite(source_string):
st = parser.suite(source_string)
return st, st.compile()
def load_expression(source_string):
st = parser.expr(source_string)
return st, st.compile()
Information Discovery
^^^^^^^^^^^^^^^^^^^^^
.. index::
single: string; documentation
single: docstrings
Some applications benefit from direct access to the parse tree. The remainder
of this section demonstrates how the parse tree provides access to module
documentation defined in docstrings without requiring that the code being
examined be loaded into a running interpreter via :keyword:`import`. This can
be very useful for performing analyses of untrusted code.
Generally, the example will demonstrate how the parse tree may be traversed to
distill interesting information. Two functions and a set of classes are
developed which provide programmatic access to high level function and class
definitions provided by a module. The classes extract information from the
parse tree and provide access to the information at a useful semantic level, one
function provides a simple low-level pattern matching capability, and the other
function defines a high-level interface to the classes by handling file
operations on behalf of the caller. All source files mentioned here which are
not part of the Python installation are located in the :file:`Demo/parser/`
directory of the distribution.
The dynamic nature of Python allows the programmer a great deal of flexibility,
but most modules need only a limited measure of this when defining classes,
functions, and methods. In this example, the only definitions that will be
considered are those which are defined in the top level of their context, e.g.,
a function defined by a :keyword:`def` statement at column zero of a module, but
not a function defined within a branch of an :keyword:`if` ... :keyword:`else`
construct, though there are some good reasons for doing so in some situations.
Nesting of definitions will be handled by the code developed in the example.
To construct the upper-level extraction methods, we need to know what the parse
tree structure looks like and how much of it we actually need to be concerned
about. Python uses a moderately deep parse tree so there are a large number of
intermediate nodes. It is important to read and understand the formal grammar
used by Python. This is specified in the file :file:`Grammar/Grammar` in the
distribution. Consider the simplest case of interest when searching for
docstrings: a module consisting of a docstring and nothing else. (See file
:file:`docstring.py`.) ::
"""Some documentation.
"""
Using the interpreter to take a look at the parse tree, we find a bewildering
mass of numbers and parentheses, with the documentation buried deep in nested
tuples. ::
>>> import parser
>>> import pprint
>>> st = parser.suite(open('docstring.py').read())
>>> tup = st.totuple()
>>> pprint.pprint(tup)
(257,
(264,
(265,
(266,
(267,
(307,
(287,
(288,
(289,
(290,
(292,
(293,
(294,
(295,
(296,
(297,
(298,
(299,
(300, (3, '"""Some documentation.\n"""'))))))))))))))))),
(4, ''))),
(4, ''),
(0, ''))
The numbers at the first element of each node in the tree are the node types;
they map directly to terminal and non-terminal symbols in the grammar.
Unfortunately, they are represented as integers in the internal representation,
and the Python structures generated do not change that. However, the
:mod:`symbol` and :mod:`token` modules provide symbolic names for the node types
and dictionaries which map from the integers to the symbolic names for the node
types.
In the output presented above, the outermost tuple contains four elements: the
integer ``257`` and three additional tuples. Node type ``257`` has the symbolic
name :const:`file_input`. Each of these inner tuples contains an integer as the
first element; these integers, ``264``, ``4``, and ``0``, represent the node
types :const:`stmt`, :const:`NEWLINE`, and :const:`ENDMARKER`, respectively.
Note that these values may change depending on the version of Python you are
using; consult :file:`symbol.py` and :file:`token.py` for details of the
mapping. It should be fairly clear that the outermost node is related primarily
to the input source rather than the contents of the file, and may be disregarded
for the moment. The :const:`stmt` node is much more interesting. In
particular, all docstrings are found in subtrees which are formed exactly as
this node is formed, with the only difference being the string itself. The
association between the docstring in a similar tree and the defined entity
(class, function, or module) which it describes is given by the position of the
docstring subtree within the tree defining the described structure.
By replacing the actual docstring with something to signify a variable component
of the tree, we allow a simple pattern matching approach to check any given
subtree for equivalence to the general pattern for docstrings. Since the
example demonstrates information extraction, we can safely require that the tree
be in tuple form rather than list form, allowing a simple variable
representation to be ``['variable_name']``. A simple recursive function can
implement the pattern matching, returning a Boolean and a dictionary of variable
name to value mappings. (See file :file:`example.py`.) ::
def match(pattern, data, vars=None):
if vars is None:
vars = {}
if isinstance(pattern, list):
vars[pattern[0]] = data
return True, vars
if not instance(pattern, tuple):
return (pattern == data), vars
if len(data) != len(pattern):
return False, vars
for pattern, data in zip(pattern, data):
same, vars = match(pattern, data, vars)
if not same:
break
return same, vars
Using this simple representation for syntactic variables and the symbolic node
types, the pattern for the candidate docstring subtrees becomes fairly readable.
(See file :file:`example.py`.) ::
import symbol
import token
DOCSTRING_STMT_PATTERN = (
symbol.stmt,
(symbol.simple_stmt,
(symbol.small_stmt,
(symbol.expr_stmt,
(symbol.testlist,
(symbol.test,
(symbol.and_test,
(symbol.not_test,
(symbol.comparison,
(symbol.expr,
(symbol.xor_expr,
(symbol.and_expr,
(symbol.shift_expr,
(symbol.arith_expr,
(symbol.term,
(symbol.factor,
(symbol.power,
(symbol.atom,
(token.STRING, ['docstring'])
)))))))))))))))),
(token.NEWLINE, '')
))
Using the :func:`match` function with this pattern, extracting the module
docstring from the parse tree created previously is easy::
>>> found, vars = match(DOCSTRING_STMT_PATTERN, tup[1])
>>> found
True
>>> vars
{'docstring': '"""Some documentation.\n"""'}
Once specific data can be extracted from a location where it is expected, the
question of where information can be expected needs to be answered. When
dealing with docstrings, the answer is fairly simple: the docstring is the first
:const:`stmt` node in a code block (:const:`file_input` or :const:`suite` node
types). A module consists of a single :const:`file_input` node, and class and
function definitions each contain exactly one :const:`suite` node. Classes and
functions are readily identified as subtrees of code block nodes which start
with ``(stmt, (compound_stmt, (classdef, ...`` or ``(stmt, (compound_stmt,
(funcdef, ...``. Note that these subtrees cannot be matched by :func:`match`
since it does not support multiple sibling nodes to match without regard to
number. A more elaborate matching function could be used to overcome this
limitation, but this is sufficient for the example.
Given the ability to determine whether a statement might be a docstring and
extract the actual string from the statement, some work needs to be performed to
walk the parse tree for an entire module and extract information about the names
defined in each context of the module and associate any docstrings with the
names. The code to perform this work is not complicated, but bears some
explanation.
The public interface to the classes is straightforward and should probably be
somewhat more flexible. Each "major" block of the module is described by an
object providing several methods for inquiry and a constructor which accepts at
least the subtree of the complete parse tree which it represents. The
:class:`ModuleInfo` constructor accepts an optional *name* parameter since it
cannot otherwise determine the name of the module.
The public classes include :class:`ClassInfo`, :class:`FunctionInfo`, and
:class:`ModuleInfo`. All objects provide the methods :meth:`get_name`,
:meth:`get_docstring`, :meth:`get_class_names`, and :meth:`get_class_info`. The
:class:`ClassInfo` objects support :meth:`get_method_names` and
:meth:`get_method_info` while the other classes provide
:meth:`get_function_names` and :meth:`get_function_info`.
Within each of the forms of code block that the public classes represent, most
of the required information is in the same form and is accessed in the same way,
with classes having the distinction that functions defined at the top level are
referred to as "methods." Since the difference in nomenclature reflects a real
semantic distinction from functions defined outside of a class, the
implementation needs to maintain the distinction. Hence, most of the
functionality of the public classes can be implemented in a common base class,
:class:`SuiteInfoBase`, with the accessors for function and method information
provided elsewhere. Note that there is only one class which represents function
and method information; this parallels the use of the :keyword:`def` statement
to define both types of elements.
Most of the accessor functions are declared in :class:`SuiteInfoBase` and do not
need to be overridden by subclasses. More importantly, the extraction of most
information from a parse tree is handled through a method called by the
:class:`SuiteInfoBase` constructor. The example code for most of the classes is
clear when read alongside the formal grammar, but the method which recursively
creates new information objects requires further examination. Here is the
relevant part of the :class:`SuiteInfoBase` definition from :file:`example.py`::
class SuiteInfoBase:
_docstring = ''
_name = ''
def __init__(self, tree = None):
self._class_info = {}
self._function_info = {}
if tree:
self._extract_info(tree)
def _extract_info(self, tree):
# extract docstring
if len(tree) == 2:
found, vars = match(DOCSTRING_STMT_PATTERN[1], tree[1])
else:
found, vars = match(DOCSTRING_STMT_PATTERN, tree[3])
if found:
self._docstring = eval(vars['docstring'])
# discover inner definitions
for node in tree[1:]:
found, vars = match(COMPOUND_STMT_PATTERN, node)
if found:
cstmt = vars['compound']
if cstmt[0] == symbol.funcdef:
name = cstmt[2][1]
self._function_info[name] = FunctionInfo(cstmt)
elif cstmt[0] == symbol.classdef:
name = cstmt[2][1]
self._class_info[name] = ClassInfo(cstmt)
After initializing some internal state, the constructor calls the
:meth:`_extract_info` method. This method performs the bulk of the information
extraction which takes place in the entire example. The extraction has two
distinct phases: the location of the docstring for the parse tree passed in, and
the discovery of additional definitions within the code block represented by the
parse tree.
The initial :keyword:`if` test determines whether the nested suite is of the
"short form" or the "long form." The short form is used when the code block is
on the same line as the definition of the code block, as in ::
def square(x): "Square an argument."; return x ** 2
while the long form uses an indented block and allows nested definitions::
def make_power(exp):
"Make a function that raises an argument to the exponent `exp`."
def raiser(x, y=exp):
return x ** y
return raiser
When the short form is used, the code block may contain a docstring as the
first, and possibly only, :const:`small_stmt` element. The extraction of such a
docstring is slightly different and requires only a portion of the complete
pattern used in the more common case. As implemented, the docstring will only
be found if there is only one :const:`small_stmt` node in the
:const:`simple_stmt` node. Since most functions and methods which use the short
form do not provide a docstring, this may be considered sufficient. The
extraction of the docstring proceeds using the :func:`match` function as
described above, and the value of the docstring is stored as an attribute of the
:class:`SuiteInfoBase` object.
After docstring extraction, a simple definition discovery algorithm operates on
the :const:`stmt` nodes of the :const:`suite` node. The special case of the
short form is not tested; since there are no :const:`stmt` nodes in the short
form, the algorithm will silently skip the single :const:`simple_stmt` node and
correctly not discover any nested definitions.
Each statement in the code block is categorized as a class definition, function
or method definition, or something else. For the definition statements, the
name of the element defined is extracted and a representation object appropriate
to the definition is created with the defining subtree passed as an argument to
the constructor. The representation objects are stored in instance variables
and may be retrieved by name using the appropriate accessor methods.
The public classes provide any accessors required which are more specific than
those provided by the :class:`SuiteInfoBase` class, but the real extraction
algorithm remains common to all forms of code blocks. A high-level function can
be used to extract the complete set of information from a source file. (See
file :file:`example.py`.) ::
def get_docs(fileName):
import os
import parser
source = open(fileName).read()
basename = os.path.basename(os.path.splitext(fileName)[0])
st = parser.suite(source)
return ModuleInfo(st.totuple(), basename)
This provides an easy-to-use interface to the documentation of a module. If
information is required which is not extracted by the code of this example, the
code may be extended at clearly defined points to provide additional
capabilities.
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