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How can you effectively debug a Python program that is crashing or freezing?

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Debugging a Python program that is crashing or freezing can be a frustrating and time-consuming task, especially if you don't have a clear strategy or the right tools. In this article, you will learn some effective methods and tips to identify and fix the common causes of Python errors, such as syntax errors, logic errors, exceptions, memory leaks, and compatibility issues.

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1 Use print statements

One of the simplest and most widely used techniques to debug a Python program is to use print statements to display the values of variables, expressions, or messages at different points of the code. This can help you to check the flow of the code, locate the source of the error, and verify the expected output. However, print statements can also clutter the code, slow down the execution, and be difficult to remove. Therefore, you should use them sparingly and only for quick and simple debugging.

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Aadit Jain

Data Specialist | Alation Data Analyst Advocate | Alation Data Steward | Alation Data Governance | Python Certified Entry-Level Programmer | LTIMindtree Certified Agile Practioner(LCAP) | Alation User Brilliance Badge
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In these testing scenarios, you have to start with only one test-case by restricting your developed code with executing the only test-case by printing the results at every stage of your code(Whether in loops or if-else). Please refrain using while loop extensively. Try to solve the problem without using while loop(if it is possible). Please use comments to track the progress of your written code and use logical names for your variables defined.

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Jayakrishnan Unnikrishnapillai

Sr Software Engineer | Java, Python | Agile | Digital Commerce | Retail | Cloud Enthusiast
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Insert print statements at different points in your code to track the flow of execution. This can help identify where the program crashes or hangs. But this should be used for quick troubleshooting; in all other cases should be using the log statements instead of print statements.

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2 Use a debugger

A debugger is a tool that allows you to execute a Python program step by step, inspect the values and types of variables, set breakpoints, watch expressions, and modify the code on the fly. A debugger can help you to find and fix errors more efficiently and accurately than print statements, as well as to explore and understand the code better. There are many debuggers available for Python, such as pdb, ipdb, PyCharm, VS Code, and PyDev. You can choose the one that suits your preferences and needs, and learn how to use its features and commands.

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Carlos Eduardo Brand?o Loureiro

Full Stack Engineer
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Perfeito, acho que aqui n?o tenho muito a adicionar, o pouco que conhe?o já falaram, se depois disso ainda n?o consegui ae podemos tentar uma outra abordagem.

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Jayakrishnan Unnikrishnapillai

Sr Software Engineer | Java, Python | Agile | Digital Commerce | Retail | Cloud Enthusiast
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Utilize Python's built-in debugger, pdb. You can insert breakpoints in your code to pause execution and inspect variables, helping you identify the root cause of the issue. If comfortable, try using external debugging tools like pdb++, PyCharm, or VSCode with integrated debugging features for a more visual and interactive debugging experience.

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3 Use logging

Logging is a technique that involves recording the events and messages that occur during the execution of a Python program to a file or a console. Logging can help you to track the history and progress of the code, diagnose the causes and effects of errors, and monitor the performance and behavior of the program. Logging is more flexible and configurable than print statements, as you can control the level, format, destination, and frequency of the log messages. You can use the built-in logging module in Python or other third-party libraries, such as loguru, to implement logging in your code.

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Jayakrishnan Unnikrishnapillai

Sr Software Engineer | Java, Python | Agile | Digital Commerce | Retail | Cloud Enthusiast
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Log statements are useful in troubleshooting any kind of issues; it records the program behavior during execution. but it comes handy when the issue occurs intermittently.

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4 Use unit tests

Unit tests are pieces of code that test the functionality and correctness of a specific part of a Python program, such as a function, a class, or a module. Unit tests can help you to debug a Python program by verifying that each part works as expected, detecting any errors or bugs before they affect the whole program, and ensuring that any changes or modifications do not break the existing code. You can use the built-in unittest module in Python or other frameworks, such as pytest, nose, or doctest, to write and run unit tests for your code.

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5 Use profiling

Profiling is a technique that measures the execution time and memory usage of a Python program or a part of it. Profiling can help you to debug a Python program by identifying the bottlenecks, inefficiencies, and leaks that cause the program to crash or freeze, and by suggesting ways to optimize and improve the performance and resource management of the code. You can use the built-in cProfile or profile modules in Python or other tools, such as line_profiler, memory_profiler, or py-spy, to perform profiling on your code.

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Jayakrishnan Unnikrishnapillai

Sr Software Engineer | Java, Python | Agile | Digital Commerce | Retail | Cloud Enthusiast
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Use tools like memory_profiler to profile memory usage and identify potential memory leaks or excessive memory consumption in your application. Considerably easy to use this tool.

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6 Use cross-platform and cross-language tools

Sometimes, a Python program may crash or freeze due to compatibility issues with the operating system, the interpreter, the libraries, or the other languages that it interacts with. To debug such issues, you need to use tools that can work across different platforms and languages, and that can provide you with detailed and relevant information about the error. Some examples of such tools are gdb, valgrind, pyflame, and py-spy. You can use these tools to inspect the stack traces, memory dumps, performance metrics, and other aspects of the Python program and its environment.

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7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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How can you effectively debug a Python program that is crashing or freezing?

1

2

3

4

5

6

7

1 Use print statements

2 Use a debugger

3 Use logging

4 Use unit tests

5 Use profiling

6 Use cross-platform and cross-language tools

7 Here’s what else to consider

System Development

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How can you effectively debug a Python program that is crashing or freezing?

1

2

3

4

5

6

7

1 Use print statements

2 Use a debugger

3 Use logging

4 Use unit tests

5 Use profiling

6 Use cross-platform and cross-language tools

7 Here’s what else to consider

System Development

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