python抽象语法树

Abstract Syntax Tree is a very strong features in Python. Python AST module allows us to interact with Python code itself and modify it.

抽象语法树是Python中非常强大的功能。 Python AST模块允许我们与Python代码本身进行交互并对其进行修改。

Python AST模块 (Python AST Module)

With the Python AST module, we can do a lot of things like modifying Python code and inspect it. The code can be parsed and modified before it is compiled to bytecode form. It is important to understand that each Abstract Syntax Tree represents each element in our Python code as an object. We will understand this in detail in the coming sections. Let’s try the real code.

使用Python AST模块，我们可以做很多事情，例如修改Python代码并检查它。 在将代码编译为bytecode形式之前，可以对其进行解析和修改。 重要的是要理解，每个抽象语法树都将Python代码中的每个元素表示为一个对象。 我们将在接下来的部分中详细了解这一点。 让我们尝试真正的代码。

代码编译模式 (Modes for Code Compilation)

As we mentioned mode in the last script above, there are three modes in which Python code can be compiled. They are:

正如我们在上面的最后一个脚本中提到的mode一样，可以在三种模式下编译Python代码。 他们是：

• exec: We can execute normal Python code using this mode.exec ：我们可以使用这种模式执行普通的Python代码。
• eval: To evaluate Python’s expressions, this mode will return the result fo the expression after evaluation.eval ：要求值Python的表达式，此模式将在求值后返回表达式的结果。
• single: This mode works just like Python shell which execute one statement at a time.single ：此模式的工作方式类似于Python Shell，一次执行一个语句。

执行代码 (Executing code)

We can use AST module to execute Python code. Here is a sample program:

我们可以使用AST模块执行Python代码。 这是一个示例程序：

import astcode = ast.parse("print('Hello world!')")
print(code)exec(compile(code, filename="", mode="exec"))

Let’s see the output for this program:

As mentioned above, we used exec mode here.

让我们看一下该程序的输出：

如上所述，我们在这里使用了exec模式。

评估Python表达式 (Evaluating Python Expression)

Based on the second mode we mentioned above, AST can be used to evaluate a Python expression and get the response of the expression. Let’s look at a code snippet:

基于我们上面提到的第二种模式，AST可用于评估Python表达式并获取该表达式的响应。 让我们看一下代码片段：

import astexpression = '6 + 8'
code = ast.parse(expression, mode='eval')print(eval(compile(code, '', mode='eval')))

Let’s see the output for this program:

It is also possible to see the AST which was formed for the above expression, just add this line with above script:

让我们看一下该程序的输出：

也可以看到为上述表达式形成的AST，只需在上面的脚本中添加以下行即可：

print(ast.dump(code))

This is what it gives:

这就是它的作用：

构造多行AST (Constructing multi-line ASTs)

Till now, we made a single line ASTs and in the last example, we also saw how they look using the dump. Now, we will make a transform multi-line Python code to an AST. Here is a sample program:

到现在为止，我们只做了一行AST，在最后一个示例中，我们还看到了使用转储的外观。 现在，我们将多行Python代码转换为AST。 这是一个示例程序：

import asttree = ast.parse('''
fruits = ['grapes', 'mango']
name = 'peter'for fruit in fruits:print('{} likes {}'.format(name, fruit))
''')print(ast.dump(tree))

Let’s see the output for this program:

We can visit each node by modifying the script:

让我们看一下该程序的输出：

我们可以通过修改脚本来访问每个节点：

import astclass NodeVisitor(ast.NodeVisitor):def visit_Str(self, tree_node):print('{}'.format(tree_node.s))class NodeTransformer(ast.NodeTransformer):def visit_Str(self, tree_node):return ast.Str('String: ' + tree_node.s)tree_node = ast.parse('''
fruits = ['grapes', 'mango']
name = 'peter'for fruit in fruits:print('{} likes {}'.format(name, fruit))
''')NodeTransformer().visit(tree_node)
NodeVisitor().visit(tree_node)

Let’s see the output for this program:

The Visitor class we made above implement methods that are called for each AST nodes whereas with Transformer class, it first calls the corresponding method for node and finally replaces it with the return value of the method. We can execute the methods here by adding this line:

让我们看一下该程序的输出：

我们上面制作的Visitor 类实现了为每个AST节点调用的方法，而对于Transformer类，它首先为节点调用相应的方法，最后将其替换为该方法的返回值。 我们可以通过添加以下行来在此处执行方法：

tree_node = ast.fix_missing_locations(tree_node)
exec(compile(tree_node, '', 'exec'))

Now the output will be:

现在的输出将是：

何时使用Python AST模块？ (When to use Python AST Module?)

Many automation testing tools, code coverage tools rely on the power of the Abstract Syntax Trees to parse the source code and find the possible flaws and errors in the code. Apart from this, ASTs are also used in:

许多自动化测试工具，代码覆盖率工具依靠抽象语法树的功能来解析源代码并查找代码中可能存在的缺陷和错误。 除此之外，AST还用于：

• Making IDEs intelligent and making a feature everyone knows as intellisense.制作的IDE智能化和制作特点大家都知道智能感知 。
• Tools like Pylint uses ASTs to perform static code analysis像Pylint这样的工具使用AST执行静态代码分析
• Custom Python interpreters自定义Python解释器

结论 (Conclusion)

In this lesson, we studied the AST module which is used to evaluate and modify the Python’s code in your program.

在本课程中，我们研究了AST模块，该模块用于评估和修改程序中的Python代码。

Reference: API Doc

参考： API文档

翻译自: https://www.journaldev.com/19243/python-ast-abstract-syntax-tree

python抽象语法树