Debugging in python

These libraries help you with Python development the debugger enables you to step through code, analyze stack frames and set breakpoints etc., and the profilers run code and give you a detailed breakdown of execution times, allowing you to identify bottlenecks in your programs.Python Training in Bangalore debugging in Python can be approached through various methods and tools Here are some key strategies and tools for effective debugging

Basic Debugging Techniques

01. Understanding the problem

02. Backtracing

03. Using debugging tools

04. Breakpoints and stepping

05. Binary search

06. Rubber ducking

07. Log analysis

08. Clustering bugs

09. Take breaks

10.Take notes for learning

Raising Exceptions

Best Python Training in Bangalore Raising exceptions in Python is an essential technique for handling errors and special conditions in a controlled manner is a technique for interrupting the normal flow of execution in a program, signaling that some exceptional circumstance has arisen, and returning directly to an enclosing part of the program that was designated to react to that circumstance.

Getting the Traceback as a String

When Python encounters an error, it produces a treasure trove of error information called the traceback. The traceback includes the error message,the line number of the line that caused the error, and the sequence of the function calls that led to the error. This sequence of calls is called the call stack.Python Course in Bangalore

Assertions

An assertion is a sanity check to make sure your code isn’t doing something

obviously wrong. These sanity checks are performed by assert statements. If

the sanity check fails, then an AssertionError exception is raised. In code, an

assert statement consists of the following:

• The assert keyword

• A condition (that is, an expression that evaluates to True or False)

• A comma

• A string to display when the condition is False

Using an Assertion in a Traffic Light Simulation

Python with Python Training in Bangalore Using assertions in a traffic light simulation can help ensure that the traffic light operates within expected parameters and transitions correctly. Assertions are used to check conditions that should logically hold true during execution and can serve as an early debugging tool by catching errors during development.

Disabling Assertions

Assertions can be disabled by passing the -O option when running Python.This is good for when you have finished writing and testing your program and don’t want it to be slowed down by performing sanity checks (although most of the time assert statements do not cause a noticeable speed differ-ence). Assertions are for development, not the final product. By the time you hand off your program to someone else to run, it should be free of bugs and not require the sanity checks. See Appendix B for details about how to launch your probably-not-insane programs with the -O option.

Logging

If you’ve ever put a print() statement in your code to output some variable’s value while your program is running, you’ve used a form of logging to debug your code. Logging is a great way to understand what’s happening in your program and in what order its happening.Python Training Course Certification in Bangalore Python’s logging module makes it easy to create a record of custom messages that you write. These log mes-sages will describe when the program execution has reached the logging function call and list any variables you have specified at that point in time.On the other hand, a missing log message indicates a part of the code was skipped and never executed.

Disabling Logging

After you’ve debugged your program, you probably don’t want all these log messages cluttering the screen. The logging.disable() function disables these so that you don’t have to go into your program and remove all the log-ging calls by hand. You simply pass logging.disable() a logging level, and it will suppress all log messages at that level or lower. So if you want to disable logging entirely, just add logging.disable(logging.CRITICAL) to your program.

Conclusion

 In 2024 Python is a dynamic and influential language that can significantly enhance your programming skills and career prospects. Through Nearlearn, you have built a strong foundation in Python, setting the stage for further growth and exploration in the world of programming. Continue to practice, experiment, and innovate with Python to fully harness its capabilities and achieve your professional goals.