Remove second parser module example; it referred to non-readily-available example files, and this kind of discovery is much better done with the AST nowadays anyway.
This commit is contained in:
Georg Brandl
parent
fc9794a8fc
commit
047e486c45
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@ -317,22 +317,8 @@ ST objects have the following methods:
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Same as ``st2tuple(st, line_info, col_info)``.
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.. _st-examples:
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Examples
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--------
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.. index:: builtin: compile
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The parser modules allows operations to be performed on the parse tree of Python
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source code before the :term:`bytecode` is generated, and provides for inspection of the
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parse tree for information gathering purposes. Two examples are presented. The
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simple example demonstrates emulation of the :func:`compile` built-in function
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and the complex example shows the use of a parse tree for information discovery.
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Emulation of :func:`compile`
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^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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Example: Emulation of :func:`compile`
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-------------------------------------
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While many useful operations may take place between parsing and bytecode
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generation, the simplest operation is to do nothing. For this purpose, using
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@ -366,320 +352,3 @@ readily available functions::
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def load_expression(source_string):
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st = parser.expr(source_string)
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return st, st.compile()
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Information Discovery
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^^^^^^^^^^^^^^^^^^^^^
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.. index::
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single: string; documentation
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single: docstrings
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Some applications benefit from direct access to the parse tree. The remainder
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of this section demonstrates how the parse tree provides access to module
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documentation defined in docstrings without requiring that the code being
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examined be loaded into a running interpreter via :keyword:`import`. This can
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be very useful for performing analyses of untrusted code.
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Generally, the example will demonstrate how the parse tree may be traversed to
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distill interesting information. Two functions and a set of classes are
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developed which provide programmatic access to high level function and class
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definitions provided by a module. The classes extract information from the
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parse tree and provide access to the information at a useful semantic level, one
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function provides a simple low-level pattern matching capability, and the other
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function defines a high-level interface to the classes by handling file
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operations on behalf of the caller. All source files mentioned here which are
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not part of the Python installation are located in the :file:`Demo/parser/`
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directory of the distribution.
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The dynamic nature of Python allows the programmer a great deal of flexibility,
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but most modules need only a limited measure of this when defining classes,
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functions, and methods. In this example, the only definitions that will be
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considered are those which are defined in the top level of their context, e.g.,
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a function defined by a :keyword:`def` statement at column zero of a module, but
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not a function defined within a branch of an :keyword:`if` ... :keyword:`else`
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construct, though there are some good reasons for doing so in some situations.
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Nesting of definitions will be handled by the code developed in the example.
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To construct the upper-level extraction methods, we need to know what the parse
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tree structure looks like and how much of it we actually need to be concerned
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about. Python uses a moderately deep parse tree so there are a large number of
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intermediate nodes. It is important to read and understand the formal grammar
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used by Python. This is specified in the file :file:`Grammar/Grammar` in the
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distribution. Consider the simplest case of interest when searching for
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docstrings: a module consisting of a docstring and nothing else. (See file
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:file:`docstring.py`.) ::
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"""Some documentation.
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"""
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Using the interpreter to take a look at the parse tree, we find a bewildering
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mass of numbers and parentheses, with the documentation buried deep in nested
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tuples. ::
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>>> import parser
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>>> import pprint
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>>> st = parser.suite(open('docstring.py').read())
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>>> tup = st.totuple()
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>>> pprint.pprint(tup)
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(257,
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(264,
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(265,
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(266,
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(267,
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(307,
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(287,
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(288,
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(289,
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(290,
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(292,
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(293,
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(294,
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(295,
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(296,
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(297,
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(298,
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(299,
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(300, (3, '"""Some documentation.\n"""'))))))))))))))))),
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(4, ''))),
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(4, ''),
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(0, ''))
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The numbers at the first element of each node in the tree are the node types;
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they map directly to terminal and non-terminal symbols in the grammar.
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Unfortunately, they are represented as integers in the internal representation,
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and the Python structures generated do not change that. However, the
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:mod:`symbol` and :mod:`token` modules provide symbolic names for the node types
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and dictionaries which map from the integers to the symbolic names for the node
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types.
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In the output presented above, the outermost tuple contains four elements: the
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integer ``257`` and three additional tuples. Node type ``257`` has the symbolic
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name :const:`file_input`. Each of these inner tuples contains an integer as the
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first element; these integers, ``264``, ``4``, and ``0``, represent the node
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types :const:`stmt`, :const:`NEWLINE`, and :const:`ENDMARKER`, respectively.
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Note that these values may change depending on the version of Python you are
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using; consult :file:`symbol.py` and :file:`token.py` for details of the
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mapping. It should be fairly clear that the outermost node is related primarily
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to the input source rather than the contents of the file, and may be disregarded
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for the moment. The :const:`stmt` node is much more interesting. In
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particular, all docstrings are found in subtrees which are formed exactly as
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this node is formed, with the only difference being the string itself. The
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association between the docstring in a similar tree and the defined entity
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(class, function, or module) which it describes is given by the position of the
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docstring subtree within the tree defining the described structure.
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By replacing the actual docstring with something to signify a variable component
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of the tree, we allow a simple pattern matching approach to check any given
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subtree for equivalence to the general pattern for docstrings. Since the
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example demonstrates information extraction, we can safely require that the tree
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be in tuple form rather than list form, allowing a simple variable
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representation to be ``['variable_name']``. A simple recursive function can
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implement the pattern matching, returning a Boolean and a dictionary of variable
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name to value mappings. (See file :file:`example.py`.) ::
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def match(pattern, data, vars=None):
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if vars is None:
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vars = {}
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if isinstance(pattern, list):
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vars[pattern[0]] = data
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return True, vars
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if not instance(pattern, tuple):
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return (pattern == data), vars
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if len(data) != len(pattern):
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return False, vars
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for pattern, data in zip(pattern, data):
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same, vars = match(pattern, data, vars)
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if not same:
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break
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return same, vars
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Using this simple representation for syntactic variables and the symbolic node
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types, the pattern for the candidate docstring subtrees becomes fairly readable.
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(See file :file:`example.py`.) ::
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import symbol
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import token
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DOCSTRING_STMT_PATTERN = (
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symbol.stmt,
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(symbol.simple_stmt,
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(symbol.small_stmt,
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(symbol.expr_stmt,
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(symbol.testlist,
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(symbol.test,
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(symbol.and_test,
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(symbol.not_test,
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(symbol.comparison,
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(symbol.expr,
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(symbol.xor_expr,
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(symbol.and_expr,
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(symbol.shift_expr,
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(symbol.arith_expr,
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(symbol.term,
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(symbol.factor,
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(symbol.power,
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(symbol.atom,
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(token.STRING, ['docstring'])
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)))))))))))))))),
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(token.NEWLINE, '')
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))
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Using the :func:`match` function with this pattern, extracting the module
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docstring from the parse tree created previously is easy::
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>>> found, vars = match(DOCSTRING_STMT_PATTERN, tup[1])
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>>> found
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True
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>>> vars
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{'docstring': '"""Some documentation.\n"""'}
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Once specific data can be extracted from a location where it is expected, the
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question of where information can be expected needs to be answered. When
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dealing with docstrings, the answer is fairly simple: the docstring is the first
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:const:`stmt` node in a code block (:const:`file_input` or :const:`suite` node
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types). A module consists of a single :const:`file_input` node, and class and
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function definitions each contain exactly one :const:`suite` node. Classes and
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functions are readily identified as subtrees of code block nodes which start
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with ``(stmt, (compound_stmt, (classdef, ...`` or ``(stmt, (compound_stmt,
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(funcdef, ...``. Note that these subtrees cannot be matched by :func:`match`
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since it does not support multiple sibling nodes to match without regard to
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number. A more elaborate matching function could be used to overcome this
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limitation, but this is sufficient for the example.
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Given the ability to determine whether a statement might be a docstring and
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extract the actual string from the statement, some work needs to be performed to
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walk the parse tree for an entire module and extract information about the names
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defined in each context of the module and associate any docstrings with the
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names. The code to perform this work is not complicated, but bears some
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explanation.
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The public interface to the classes is straightforward and should probably be
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somewhat more flexible. Each "major" block of the module is described by an
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object providing several methods for inquiry and a constructor which accepts at
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least the subtree of the complete parse tree which it represents. The
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:class:`ModuleInfo` constructor accepts an optional *name* parameter since it
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cannot otherwise determine the name of the module.
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The public classes include :class:`ClassInfo`, :class:`FunctionInfo`, and
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:class:`ModuleInfo`. All objects provide the methods :meth:`get_name`,
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:meth:`get_docstring`, :meth:`get_class_names`, and :meth:`get_class_info`. The
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:class:`ClassInfo` objects support :meth:`get_method_names` and
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:meth:`get_method_info` while the other classes provide
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:meth:`get_function_names` and :meth:`get_function_info`.
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Within each of the forms of code block that the public classes represent, most
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of the required information is in the same form and is accessed in the same way,
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with classes having the distinction that functions defined at the top level are
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referred to as "methods." Since the difference in nomenclature reflects a real
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semantic distinction from functions defined outside of a class, the
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implementation needs to maintain the distinction. Hence, most of the
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functionality of the public classes can be implemented in a common base class,
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:class:`SuiteInfoBase`, with the accessors for function and method information
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provided elsewhere. Note that there is only one class which represents function
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and method information; this parallels the use of the :keyword:`def` statement
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to define both types of elements.
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Most of the accessor functions are declared in :class:`SuiteInfoBase` and do not
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need to be overridden by subclasses. More importantly, the extraction of most
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information from a parse tree is handled through a method called by the
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:class:`SuiteInfoBase` constructor. The example code for most of the classes is
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clear when read alongside the formal grammar, but the method which recursively
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creates new information objects requires further examination. Here is the
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relevant part of the :class:`SuiteInfoBase` definition from :file:`example.py`::
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class SuiteInfoBase:
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_docstring = ''
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_name = ''
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def __init__(self, tree = None):
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self._class_info = {}
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self._function_info = {}
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if tree:
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self._extract_info(tree)
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def _extract_info(self, tree):
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# extract docstring
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if len(tree) == 2:
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found, vars = match(DOCSTRING_STMT_PATTERN[1], tree[1])
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else:
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found, vars = match(DOCSTRING_STMT_PATTERN, tree[3])
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if found:
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self._docstring = eval(vars['docstring'])
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# discover inner definitions
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for node in tree[1:]:
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found, vars = match(COMPOUND_STMT_PATTERN, node)
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if found:
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cstmt = vars['compound']
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if cstmt[0] == symbol.funcdef:
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name = cstmt[2][1]
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self._function_info[name] = FunctionInfo(cstmt)
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elif cstmt[0] == symbol.classdef:
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name = cstmt[2][1]
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self._class_info[name] = ClassInfo(cstmt)
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After initializing some internal state, the constructor calls the
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:meth:`_extract_info` method. This method performs the bulk of the information
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extraction which takes place in the entire example. The extraction has two
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distinct phases: the location of the docstring for the parse tree passed in, and
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the discovery of additional definitions within the code block represented by the
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parse tree.
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The initial :keyword:`if` test determines whether the nested suite is of the
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"short form" or the "long form." The short form is used when the code block is
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on the same line as the definition of the code block, as in ::
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def square(x): "Square an argument."; return x ** 2
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while the long form uses an indented block and allows nested definitions::
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def make_power(exp):
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"Make a function that raises an argument to the exponent `exp`."
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def raiser(x, y=exp):
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return x ** y
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return raiser
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When the short form is used, the code block may contain a docstring as the
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first, and possibly only, :const:`small_stmt` element. The extraction of such a
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docstring is slightly different and requires only a portion of the complete
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pattern used in the more common case. As implemented, the docstring will only
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be found if there is only one :const:`small_stmt` node in the
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:const:`simple_stmt` node. Since most functions and methods which use the short
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form do not provide a docstring, this may be considered sufficient. The
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extraction of the docstring proceeds using the :func:`match` function as
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described above, and the value of the docstring is stored as an attribute of the
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:class:`SuiteInfoBase` object.
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After docstring extraction, a simple definition discovery algorithm operates on
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the :const:`stmt` nodes of the :const:`suite` node. The special case of the
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short form is not tested; since there are no :const:`stmt` nodes in the short
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form, the algorithm will silently skip the single :const:`simple_stmt` node and
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correctly not discover any nested definitions.
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Each statement in the code block is categorized as a class definition, function
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or method definition, or something else. For the definition statements, the
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name of the element defined is extracted and a representation object appropriate
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to the definition is created with the defining subtree passed as an argument to
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the constructor. The representation objects are stored in instance variables
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and may be retrieved by name using the appropriate accessor methods.
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The public classes provide any accessors required which are more specific than
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those provided by the :class:`SuiteInfoBase` class, but the real extraction
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algorithm remains common to all forms of code blocks. A high-level function can
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be used to extract the complete set of information from a source file. (See
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file :file:`example.py`.) ::
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def get_docs(fileName):
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import os
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import parser
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source = open(fileName).read()
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basename = os.path.basename(os.path.splitext(fileName)[0])
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st = parser.suite(source)
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return ModuleInfo(st.totuple(), basename)
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This provides an easy-to-use interface to the documentation of a module. If
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information is required which is not extracted by the code of this example, the
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code may be extended at clearly defined points to provide additional
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capabilities.
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