在Python中创建依赖图 [英] Creating Dependency Graphs in Python

问题描述

我继承了一个巨大的代码库，需要对其进行一些小的更改。我想知道是否有实用程序可以解析python代码并提供函数之间的依赖关系，就像我对函数进行更改一样，我想确保自己不会破坏其他函数，所以如果我能在类似该图的图中看到它

I have inherited a huge codebase that I need to make some small changes into. I was wondering if there are utilities that would parse python code and give dependencies between functions, as in if I make changes to a function I want to be sure that I dont break other functions, so if I could see in a graph like diagram it would make my life easier.

推荐答案

• 通常，依赖性是为模块/包导入定义的。



• 您正在寻找可视化的呼叫流程。

  • Usually "dependency" is defined for module / package import.

  • What you are looking for is a visualizing call flow.

    
    
    • http://pycallgraph.slowchop.com/
    
    
    • http://pycallgraph.slowchop.com/

    您仍然不能保证不会破坏功能：）

    You can still not guarantee that you will not break functionality :)

    我的经验和解决方案：

    很多次，我发现呼叫流数据不堪重负，并且图表过于复杂。
    所以我通常做的是对该函数感兴趣的跟踪调用流程。

    Many a times, I found the call flow data overwhelming and the diagram too complex. So what i usually do is trace call flow partially for the function, I am interested in.

    这是通过利用sys.settrace（。 。）功能。在将调用流作为文本数据生成之后，我使用graphviz生成了一个调用图。

    This is done by utilizing the sys.settrace(...) function. After generating the call flows as textual data, I generate a call graph using graphviz.

    
    
    • http://docs.python.org/library/sys.html
    
    
    • 通话追踪
    
    
    • 生成图形，请使用 networkX 中的graphviz解决方案。
    
    
    • http://docs.python.org/library/sys.html
    • On call tracing
    • For generating graphs, use graphviz solutions from networkX.

    然后我的零散解决方案效果更好。只需插入代码，然后在要跟踪的函数上使用装饰器即可。您会看到延迟出现的差距，但是可以解决。您不会直接获得完整的图片。

    Then my piecemeal solution works better. Just insert the code and use the decorator on a function that you want to trace. You will see gaps where deferred comes into picture but that can be worked out. You will not get the complete picture directly.

    我一直在尝试这样做，并制作了很少有文章可以帮助您理解。

    I have been trying to do that and made a few post that works on that understanding.

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