2014-08-21 17:20:57 +08:00
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2014-09-02 04:46:28 +08:00
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9.24 解析与分析Python源码
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2014-08-21 17:20:57 +08:00
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问题
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2015-09-28 15:14:36 +08:00
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你想写解析并分析Python源代码的程序。
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2015-04-27 17:28:33 +08:00
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2014-08-21 17:20:57 +08:00
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解决方案
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2015-09-28 15:14:36 +08:00
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大部分程序员知道Python能够计算或执行字符串形式的源代码。例如:
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2015-04-27 17:28:33 +08:00
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.. code-block:: python
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>>> x = 42
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>>> eval('2 + 3*4 + x')
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56
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>>> exec('for i in range(10): print(i)')
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>>>
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2015-09-28 15:14:36 +08:00
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尽管如此,``ast`` 模块能被用来将Python源码编译成一个可被分析的抽象语法树(AST)。例如:
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2015-04-27 17:28:33 +08:00
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.. code-block:: python
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>>> import ast
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>>> ex = ast.parse('2 + 3*4 + x', mode='eval')
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>>> ex
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<_ast.Expression object at 0x1007473d0>
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>>> ast.dump(ex)
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"Expression(body=BinOp(left=BinOp(left=Num(n=2), op=Add(),
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right=BinOp(left=Num(n=3), op=Mult(), right=Num(n=4))), op=Add(),
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right=Name(id='x', ctx=Load())))"
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>>> top = ast.parse('for i in range(10): print(i)', mode='exec')
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>>> top
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<_ast.Module object at 0x100747390>
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>>> ast.dump(top)
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"Module(body=[For(target=Name(id='i', ctx=Store()),
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iter=Call(func=Name(id='range', ctx=Load()), args=[Num(n=10)],
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keywords=[], starargs=None, kwargs=None),
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body=[Expr(value=Call(func=Name(id='print', ctx=Load()),
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args=[Name(id='i', ctx=Load())], keywords=[], starargs=None,
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kwargs=None))], orelse=[])])"
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>>>
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2015-09-28 15:14:36 +08:00
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分析源码树需要你自己更多的学习,它是由一系列AST节点组成的。
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分析这些节点最简单的方法就是定义一个访问者类,实现很多 ``visit_NodeName()`` 方法,
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``NodeName()`` 匹配那些你感兴趣的节点。下面是这样一个类,记录了哪些名字被加载、存储和删除的信息。
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2015-04-27 17:28:33 +08:00
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.. code-block:: python
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import ast
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class CodeAnalyzer(ast.NodeVisitor):
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def __init__(self):
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self.loaded = set()
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self.stored = set()
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self.deleted = set()
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def visit_Name(self, node):
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if isinstance(node.ctx, ast.Load):
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self.loaded.add(node.id)
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elif isinstance(node.ctx, ast.Store):
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self.stored.add(node.id)
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elif isinstance(node.ctx, ast.Del):
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self.deleted.add(node.id)
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# Sample usage
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if __name__ == '__main__':
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# Some Python code
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code = '''
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for i in range(10):
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print(i)
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del i
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'''
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# Parse into an AST
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top = ast.parse(code, mode='exec')
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# Feed the AST to analyze name usage
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c = CodeAnalyzer()
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c.visit(top)
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print('Loaded:', c.loaded)
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print('Stored:', c.stored)
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print('Deleted:', c.deleted)
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2015-09-28 15:14:36 +08:00
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如果你运行这个程序,你会得到下面这样的输出:
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2015-04-27 17:28:33 +08:00
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.. code-block:: python
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Loaded: {'i', 'range', 'print'}
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Stored: {'i'}
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Deleted: {'i'}
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2015-09-28 15:14:36 +08:00
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最后,AST可以通过 ``compile()`` 函数来编译并执行。例如:
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2015-04-27 17:28:33 +08:00
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.. code-block:: python
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>>> exec(compile(top,'<stdin>', 'exec'))
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0
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>>>
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2014-08-21 17:20:57 +08:00
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----------
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讨论
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2015-09-28 15:14:36 +08:00
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当你能够分析源代码并从中获取信息的时候,你就能写很多代码分析、优化或验证工具了。
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例如,相比盲目的传递一些代码片段到类似 ``exec()`` 函数中,你可以先将它转换成一个AST,
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然后观察它的细节看它到底是怎样做的。
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你还可以写一些工具来查看某个模块的全部源码,并且在此基础上执行某些静态分析。
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2015-04-27 17:28:33 +08:00
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2015-09-28 15:14:36 +08:00
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需要注意的是,如果你知道自己在干啥,你还能够重写AST来表示新的代码。
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下面是一个装饰器例子,可以通过重新解析函数体源码、
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重写AST并重新创建函数代码对象来将全局访问变量降为函数体作用范围,
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2015-04-27 17:28:33 +08:00
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.. code-block:: python
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# namelower.py
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import ast
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import inspect
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# Node visitor that lowers globally accessed names into
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# the function body as local variables.
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class NameLower(ast.NodeVisitor):
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def __init__(self, lowered_names):
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self.lowered_names = lowered_names
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def visit_FunctionDef(self, node):
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# Compile some assignments to lower the constants
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code = '__globals = globals()\n'
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code += '\n'.join("{0} = __globals['{0}']".format(name)
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for name in self.lowered_names)
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code_ast = ast.parse(code, mode='exec')
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# Inject new statements into the function body
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node.body[:0] = code_ast.body
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# Save the function object
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self.func = node
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# Decorator that turns global names into locals
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def lower_names(*namelist):
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def lower(func):
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srclines = inspect.getsource(func).splitlines()
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# Skip source lines prior to the @lower_names decorator
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for n, line in enumerate(srclines):
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if '@lower_names' in line:
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break
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src = '\n'.join(srclines[n+1:])
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# Hack to deal with indented code
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if src.startswith((' ','\t')):
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src = 'if 1:\n' + src
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top = ast.parse(src, mode='exec')
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# Transform the AST
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cl = NameLower(namelist)
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cl.visit(top)
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# Execute the modified AST
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temp = {}
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exec(compile(top,'','exec'), temp, temp)
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# Pull out the modified code object
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func.__code__ = temp[func.__name__].__code__
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return func
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return lower
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2015-09-28 15:14:36 +08:00
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为了使用这个代码,你可以像下面这样写:
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2015-04-27 17:28:33 +08:00
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.. code-block:: python
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INCR = 1
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@lower_names('INCR')
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def countdown(n):
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while n > 0:
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n -= INCR
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2015-09-28 15:14:36 +08:00
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装饰器会将 ``countdown()`` 函数重写为类似下面这样子:
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2015-04-27 17:28:33 +08:00
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.. code-block:: python
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def countdown(n):
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__globals = globals()
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INCR = __globals['INCR']
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while n > 0:
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n -= INCR
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2015-09-28 15:14:36 +08:00
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在性能测试中,它会让函数运行快20%
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2015-04-27 17:28:33 +08:00
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2015-09-28 15:14:36 +08:00
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现在,你是不是想为你所有的函数都加上这个装饰器呢?或许不会。
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但是,这却是对于一些高级技术比如AST操作、源码操作等等的一个很好的演示说明
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2015-04-27 17:28:33 +08:00
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2015-09-28 15:14:36 +08:00
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本节受另外一个在 ``ActiveState`` 中处理Python字节码的章节的启示。
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使用AST是一个更加高级点的技术,并且也更简单些。参考下面一节获得字节码的更多信息。
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2015-04-27 17:28:33 +08:00
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