Debuggers reveal runtime behavior, essential for complex async or multi-threaded code.
← this item is applicable for steps 1, 2 of debugging
Debuggers are indispensable tools in the arsenal of a Python developer, especially when dealing with the intricacies of asynchronous or multi-threaded code. Unlike simple print statements that offer a static glimpse into the code's execution, debuggers provide a dynamic view, allowing developers to pause execution, inspect variables, and step through code line by line.
The below screenshot illustrates the use of VSCode’s inbuilt debugger that allows us to understand the importance of debuggers and debugging.
How to Use:
Note: If you are using VSCode or any other IDE the below steps might not be very relevant, as they illustrate the use of
pdb and how we can leverage it.- Choose Your Debugger: Python offers several debugger tools, like
pdb(Python Debugger),ipdb(an iPython-enhanced version of pdb), anddebugpy(for Visual Studio Code and other IDEs). Select one that best fits your development environment and needs.
- Setting Breakpoints: Define breakpoints in your code where you want the execution to pause. This can often be done directly within your IDE or by using the
breakpoint()function in Python 3.7 and above.
TheTechCruise.com Pyodide Terminalfor i in range(10):
breakpoint() # Execution will pause here
print(i)
- Inspecting and Stepping Through: Once execution is paused, use the debugger's commands to inspect variable values, step through code line by line, and resume execution. This allows you to observe the runtime behavior of your code and identify where things go awry.
Why Debuggers?
- Dynamic Inspection: Debuggers allow you to inspect the state of your program at any point during its execution. This is particularly valuable in async or multi-threaded environments where the program's state can change rapidly and unpredictably. As we can see from the above screenshot, on the left, in the
VARIABLESsection, we can see the state of variables AT THAT POINT OF EXECUTION/RUNTIME.
- Controlled Execution: With the ability to set breakpoints, you can pause your program's execution at critical points to examine the flow of control and the state of data. This granular control is crucial for dissecting complex behaviors and interactions that are difficult to trace otherwise. In the above screenshot, we added a
breakpointat line 56, where the execution halts. After we are done with our analysis, we can continue by clicking on the arrows in the floating menu.
- Efficiency in Debugging: Debuggers expedite the debugging process by providing advanced features like conditional breakpoints, watch expressions, and call stack inspection, enabling you to identify and solve issues more swiftly and accurately.
Conclusion:
Debuggers are a game-changer for navigating the complexities of modern Python applications. By providing a live view into the execution of your code, along with powerful controls for inspection and navigation, debuggers elevate your ability to diagnose and resolve issues efficiently. Whether you're untangling the concurrency of multi-threaded operations or tracking down elusive bugs in asynchronous code, a good debugger is your best ally.
