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This article mainly introduces "how to use open source visualization tools to understand Python code". In daily operations, I believe many people have doubts about how to use open source visualization tools to understand Python code. Xiaobian consulted all kinds of materials and sorted out simple and easy-to-use methods of operation. I hope it will be helpful for you to answer the doubts of "how to use open source visualization tools to understand Python code". Next, please follow the editor to study!

The VizTracer tool can visualize and track Python code, giving you a deeper understanding of how it works.

As the Python project becomes larger and more complex, it becomes challenging to understand it. Even if you write the whole project on your own, you can't fully know how the project works. In order to better understand your code, debugging and analyzing your code becomes critical.

VizTracer is a tool that helps you understand Python code by tracking and visualizing the execution of the code. Without making any changes to the source code, VizTracer can record the entry / exit of the function, function parameters / return values, and any variables, and then display the data through Trace-Viewer using the intuitive Google front-end interface.

Here is an example of running a Monte Carlo tree search:

Monte Carlo tree search visualization

Each function is recorded and visualized in a stack on the timeline so that you can see what happens when the program is running. You can zoom in to see the details of any particular point:

Zooming in on VizTracer visualization

VizTracer can also record function parameters and return values automatically. You can click the function entry and view the details:

Viewing VizTracer details

Or you can create an entirely new signal and use it to record variables. For example, this shows the cost value when performing a gradient drop:

VizTracer gradient descent

Compared with other tools with complex settings, VizTracer is very easy to use and does not have any dependencies. You can install it from pip:

Pip install viztracer

You can also track your program (the name of your script) by typing:

Viztracer

VizTracer will generate a HTML report in your working directory, which you can open in your Chrome browser.

VizTracer also provides other advanced features, such as filters, which you can use to filter out functions you don't want to track and get clearer reports. For example, to include only the functions in the file, you need:

Viztracer include_files. /-- run

Record function parameters and return values:

Viztracer-log_function_args-log_return_value

Record any variable that matches a regular expression:

# log variables starts with aviztracer-- log_var a.*-- run

You can get other features by making minor changes to the source code, such as custom events to record values and objects.

VizTracer also includes a virtual debugger (vdb) that can debug VizTracer log files. You can debug your running code with vdb (very similar to pdb) so that you can understand the code flow. Usefully, it also supports backtracking because it knows what happened.

Unlike some prototypes, VizTracer implements its core in pure C, which greatly reduces overhead and brings it to a level similar to cProfile.

VizTracer is open source, released under the Apache 2.0 license, and supports all common operating system platforms (Linux, macOS, and Windows). You can learn more about it on GitHub and access the source code.

At this point, the study on "how to use open source visualization tools to understand Python code" is over. I hope to be able to solve your doubts. The collocation of theory and practice can better help you learn, go and try it! If you want to continue to learn more related knowledge, please continue to follow the website, the editor will continue to work hard to bring you more practical articles!

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