How should Python Ast abstract syntax tree be used?-Python Tutorial-php.cn

Introduction

Abstract Syntax Trees are abstract syntax trees. Ast is an intermediate product from Python source code to bytecode. With the help of the ast module, the source code structure can be analyzed from the perspective of a syntax tree.

In addition, we can not only modify and execute the syntax tree, but also unparse the syntax tree generated by Source into python source code. Therefore, ast leaves enough room for Python source code checking, syntax analysis, code modification, and code debugging.

1. Introduction to AST

The CPython interpreter officially provided by Python processes python source code as follows:

Parse source code into a parse tree (Parser/ pgen.c)
Transform parse tree into an Abstract Syntax Tree (Python/ast.c)
Transform AST into a Control Flow Graph (Python/compile.c)
Emit bytecode based on the Control Flow Graph (Python/compile.c)

The actual python code processing process is as follows:

Source code analysis--> Syntax tree- -> Abstract syntax tree (AST) --> Control flow graph --> Bytecode

The above process is applied after python2.5. Python source code is first parsed into a syntax tree, and then converted into an abstract syntax tree. In the abstract syntax tree we can see the syntax structure of python in the source code file.

Most of the time programming may not require the use of abstract syntax trees, but under specific conditions and requirements, AST has its own special convenience.

The following is a simple example of abstract syntax.

Module(body=[
    Print(
          dest=None,
          values=[BinOp( left=Num(n=1),op=Add(),right=Num(n=2))],
          nl=True,
 )])

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2. Create AST

2.1 Compile function

First, let’s briefly understand the compile function.

compile(source, filename, mode[, flags[, dont_inherit]])

##source -- String or AST (Abstract Syntax Trees) object. Generally, the entire py file content can be passed in to file.read().
filename -- The name of the code file, or some identifiable value if the code is not being read from a file.
#mode -- Specify the type of compiled code. Can be specified as exec, eval, single.
#flags -- Variable scope, local namespace, if provided, can be any mapping object.
flags and dont_inherit are used to control the flags when compiling source code.

func_def = \
"""
def add(x, y):
    return x + y
print add(3, 5)
"""

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Use Compile to compile and execute:

>>> cm = compile(func_def, '', 'exec')
>>> exec cm
>>> 8

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The above func_def is compiled by compile to get the bytecode, cm is the code object,

True == isinstance(cm, types.CodeType).

##compile(source, filename, mode, ast.PyCF_ONLY_AST) <==> ast.parse(source, filename='', mode='exec' )

2.2 Generate ast

Use the above func_def to generate ast.

r_node = ast.parse(func_def)
print astunparse.dump(r_node)    # print ast.dump(r_node)

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The following is the ast structure corresponding to func_def:

Module(body=[
    FunctionDef(
        name='add',
        args=arguments(
            args=[Name(id='x',ctx=Param()),Name(id='y',ctx=Param())],
            vararg=None,
            kwarg=None,
            defaults=[]),
        body=[Return(value=BinOp(
            left=Name(id='x',ctx=Load()),
            op=Add(),
            right=Name(id='y',ctx=Load())))],
        decorator_list=[]),
    Print(
        dest=None,
        values=[Call(
                func=Name(id='add',ctx=Load()),
                args=[Num(n=3),Num(n=5)],
                keywords=[],
                starargs=None,
                kwargs=None)],
        nl=True)
  ])

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Except ast .dump, there are many third-party libraries for dumping ast, such as astunparse, codegen, unparse, etc. These third-party libraries can not only display the AST structure in a better way, but also reversely export AST to python source code.

module Python version "$Revision$"
{
  mod = Module(stmt* body)| Expression(expr body)
  stmt = FunctionDef(identifier name, arguments args, stmt* body, expr* decorator_list)
        | ClassDef(identifier name, expr* bases, stmt* body, expr* decorator_list)
        | Return(expr? value)
        | Print(expr? dest, expr* values, bool nl)| For(expr target, expr iter, stmt* body, stmt* orelse)
  expr = BoolOp(boolop op, expr* values)
       | BinOp(expr left, operator op, expr right)| Lambda(arguments args, expr body)| Dict(expr* keys, expr* values)| Num(object n) -- a number as a PyObject.
       | Str(string s) -- need to specify raw, unicode, etc?| Name(identifier id, expr_context ctx)
       | List(expr* elts, expr_context ctx) 
        -- col_offset is the byte offset in the utf8 string the parser uses
        attributes (int lineno, int col_offset)
  expr_context = Load | Store | Del | AugLoad | AugStore | Param
  boolop = And | Or 
  operator = Add | Sub | Mult | Div | Mod | Pow | LShift | RShift | BitOr | BitXor | BitAnd | FloorDiv
  arguments = (expr* args, identifier? vararg, identifier? kwarg, expr* defaults)
}

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The above is part of the Abstract Grammar taken from the official website. During the actual traversal of ast Node, its properties are accessed according to the type of Node.

3. Traverse the AST

Python provides two ways to traverse the entire abstract syntax tree.

3.1 ast.NodeTransfer

Change the addition operation in the add function in func_def to subtraction, and add a call log for the function implementation.

  class CodeVisitor(ast.NodeVisitor):
      def visit_BinOp(self, node):
          if isinstance(node.op, ast.Add):
              node.op = ast.Sub()
          self.generic_visit(node)
      def visit_FunctionDef(self, node):
          print 'Function Name:%s'% node.name
          self.generic_visit(node)
          func_log_stmt = ast.Print(
              dest = None,
              values = [ast.Str(s = 'calling func: %s' % node.name, lineno = 0, col_offset = 0)],
              nl = True,
              lineno = 0,
              col_offset = 0,
          )
          node.body.insert(0, func_log_stmt)
  r_node = ast.parse(func_def)
  visitor = CodeVisitor()
  visitor.visit(r_node)
  # print astunparse.dump(r_node)
  print astunparse.unparse(r_node)
  exec compile(r_node, '', 'exec')

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Running results:

Function Name:add
def add(x, y):
    print 'calling func: add'
    return (x - y)
print add(3, 5)
calling func: add
-2

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3.2 ast.NodeTransformer

Using NodeVisitor mainly changes the AST structure by modifying the nodes on the syntax tree. NodeTransformer mainly replaces the AST in ast. node.

Since the add defined in func_def has been changed to a subtraction function, then we will be more thorough and change the function name, parameters and called functions in ast, and log the added function call The writing is more complicated, and I try to change it beyond recognition:-)

  class CodeTransformer(ast.NodeTransformer):
      def visit_BinOp(self, node):
          if isinstance(node.op, ast.Add):
              node.op = ast.Sub()
          self.generic_visit(node)
          return node
      def visit_FunctionDef(self, node):
          self.generic_visit(node)
          if node.name == 'add':
              node.name = 'sub'
          args_num = len(node.args.args)
          args = tuple([arg.id for arg in node.args.args])
          func_log_stmt = ''.join(["print 'calling func: %s', " % node.name, "'args:'", ", %s" * args_num % args])
          node.body.insert(0, ast.parse(func_log_stmt))
          return node
      def visit_Name(self, node):
          replace = {'add': 'sub', 'x': 'a', 'y': 'b'}
          re_id = replace.get(node.id, None)
          node.id = re_id or node.id
          self.generic_visit(node)
          return node
  r_node = ast.parse(func_def)
  transformer = CodeTransformer()
  r_node = transformer.visit(r_node)
  # print astunparse.dump(r_node)
  source = astunparse.unparse(r_node)
  print source
  # exec compile(r_node, '', 'exec')        # 新加入的node func_log_stmt 缺少lineno和col_offset属性
  exec compile(source, '', 'exec')
  exec compile(ast.parse(source), '', 'exec')

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Result:

def sub(a, b):
    print 'calling func: sub', 'args:', a, b
    return (a - b)
print sub(3, 5)
calling func: sub args: 3 5
-2
calling func: sub args: 3 5
-2

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The difference between the two can be clearly seen in the code. I won’t go into details here.

4.AST application

AST module is rarely used in actual programming, but it is very meaningful as an auxiliary source code checking method; syntax checking, debugging errors, special field detection wait.

The above adding call log information to the function is a way to debug the python source code, but in reality we traverse and modify the source code by parse the entire python file.

4.1 Chinese character detection

The following is the unicode encoding range of Chinese, Japanese and Korean characters

CJK Unified Ideographs

Range : 4E00— 9FFF

Number of characters: 20992
Languages: chinese, japanese, korean, vietnamese
Use unicode range

\u4e00 - \u9fff

To identify Chinese characters, note that this range does not include Chinese characters (e.g. u';' == u'\uff1b'). The following is a class that determines whether a string contains Chinese characters CNCheckHelper:

  class CNCheckHelper(object):
      # 待检测文本可能的编码方式列表
      VALID_ENCODING = ('utf-8', 'gbk')
      def _get_unicode_imp(self, value, idx = 0):
          if idx < len(self.VALID_ENCODING):
              try:
                  return value.decode(self.VALID_ENCODING[idx])
              except:
                  return self._get_unicode_imp(value, idx + 1)
      def _get_unicode(self, from_str):
          if isinstance(from_str, unicode):
              return None
          return self._get_unicode_imp(from_str)
      def is_any_chinese(self, check_str, is_strict = True):
          unicode_str = self._get_unicode(check_str)
          if unicode_str:
              c_func = any if is_strict else all
              return c_func(u'\u4e00' <= char <= u'\u9fff' for char in unicode_str)
          return False

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The interface is_any_chinese has two judgment modes. Strict detection can be checked as long as it contains Chinese strings, and non-strict detection must contain all Chinese characters.

下面我们利用ast来遍历源文件的抽象语法树，并检测其中字符串是否包含中文字符。

  class CodeCheck(ast.NodeVisitor):
      def __init__(self):
          self.cn_checker = CNCheckHelper()
      def visit_Str(self, node):
          self.generic_visit(node)
          # if node.s and any(u'\u4e00' <= char <= u'\u9fff' for char in node.s.decode('utf-8')):
          if self.cn_checker.is_any_chinese(node.s, True):
              print 'line no: %d, column offset: %d, CN_Str: %s' % (node.lineno, node.col_offset, node.s)
  project_dir = './your_project/script'
  for root, dirs, files in os.walk(project_dir):
      print root, dirs, files
      py_files = filter(lambda file: file.endswith('.py'), files)
      checker = CodeCheck()
      for file in py_files:
          file_path = os.path.join(root, file)
          print 'Checking: %s' % file_path
          with open(file_path, 'r') as f:
              root_node = ast.parse(f.read())
              checker.visit(root_node)

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上面这个例子比较的简单，但大概就是这个意思。

关于CPython解释器执行源码的过程可以参考官网描述：PEP 339

4.2 Closure 检查

一个函数中定义的函数或者lambda中引用了父函数中的local variable，并且当做返回值返回。特定场景下闭包是非常有用的，但是也很容易被误用。

关于python闭包的概念可以参考我的另一篇文章：理解Python闭包概念

这里简单介绍一下如何借助ast来检测lambda中闭包的引用。代码如下：

  class LambdaCheck(ast.NodeVisitor):
      def __init__(self):
          self.illegal_args_list = []
          self._cur_file = None
          self._cur_lambda_args = []
      def set_cur_file(self, cur_file):
          assert os.path.isfile(cur_file)， cur_file
          self._cur_file = os.path.realpath(cur_file)
      def visit_Lambda(self, node):
          """
          lambda 闭包检查原则：
          只需检测lambda expr body中args是否引用了lambda args list之外的参数
          """
          self._cur_lambda_args =[a.id for a in node.args.args]
          print astunparse.unparse(node)
          # print astunparse.dump(node)
          self.get_lambda_body_args(node.body)
          self.generic_visit(node)
      def record_args(self, name_node):
          if isinstance(name_node, ast.Name) and name_node.id not in self._cur_lambda_args:
              self.illegal_args_list.append((self._cur_file, 'line no:%s' % name_node.lineno, 'var:%s' % name_node.id))
      def _is_args(self, node):
          if isinstance(node, ast.Name):
              self.record_args(node)
              return True
          if isinstance(node, ast.Call):
              map(self.record_args, node.args)
              return True
          return False
      def get_lambda_body_args(self, node):
          if self._is_args(node): return
          # for cnode in ast.walk(node):
          for cnode in ast.iter_child_nodes(node):
              if not self._is_args(cnode):
                  self.get_lambda_body_args(cnode)

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遍历工程文件：

  project_dir = './your project/script'
  for root, dirs, files in os.walk(project_dir):
      py_files = filter(lambda file: file.endswith('.py'), files)
      checker = LambdaCheck()
      for file in py_files:
          file_path = os.path.join(root, file)
          checker.set_cur_file(file_path)
          with open(file_path, 'r') as f:
              root_node = ast.parse(f.read())
              checker.visit(root_node)
      res = '\n'.join([' ## '.join(info) for info in checker.illegal_args_list])
      print res

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由于Lambda(arguments args, expr body)中的body expression可能非常复杂，上面的例子中仅仅处理了比较简单的body expr。可根据自己工程特点修改和扩展检查规则。为了更加一般化可以单独写一个visitor类来遍历lambda节点。

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