15 Python Debugging Interview Questions and Answers

Python debugging is a crucial skill for any developer, as it ensures code runs efficiently and correctly. Debugging in Python involves identifying, isolating, and fixing issues within the code, which can range from syntax errors to logical flaws. Mastery of debugging techniques not only improves code quality but also enhances problem-solving skills, making developers more effective and reliable.

This article offers a curated selection of Python debugging questions and answers to help you prepare for technical interviews. By familiarizing yourself with these scenarios, you’ll be better equipped to demonstrate your debugging proficiency and tackle real-world coding challenges with confidence.

Python Debugging Interview Questions and Answers

1. Explain the purpose of a debugger and how it differs from simple print statements for debugging.

A debugger allows developers to execute code step by step, inspect the program’s state, and identify issues. It offers features like breakpoints and call stack inspection, which are not available with print statements. Print statements can be effective for small scripts but become inefficient for larger programs.

Example:

Using print statements:

def add(a, b):
    print(f"a: {a}, b: {b}")  # Debugging with print
    return a + b

result = add(5, 3)
print(f"Result: {result}")

Using a debugger:

def add(a, b):
    return a + b

# Set a breakpoint here
result = add(5, 3)
print(f"Result: {result}")

With a debugger, you can set a breakpoint and inspect values without modifying the code, making the process cleaner and more efficient.

2. What is the difference between a syntax error and an exception? Provide examples of each.

A syntax error occurs when the Python parser encounters a statement that doesn’t conform to language rules, detected during parsing. For example:

# Syntax Error Example
if True print("Hello, World!")

An exception is an error during execution, even if syntax is correct. For example:

# Exception Example
a = 10 / 0

This raises a ZeroDivisionError during runtime.

3. How can you inspect the value of a variable at a specific point in your code using pdb?

To inspect a variable’s value using pdb, set a breakpoint and use the print or p command.

Example:

import pdb

def example_function(x, y):
    result = x + y
    pdb.set_trace()  # Set a breakpoint here
    result *= 2
    return result

example_function(3, 4)

At pdb.set_trace(), use p result to inspect the variable’s value.

4. Explain what a stack trace is and how it can be useful in debugging.

A stack trace provides a report of the call stack at the point of an exception, showing the sequence of function calls active at the time. This helps trace back through the code to identify the root cause.

Example:

def function_a():
    function_b()

def function_b():
    function_c()

def function_c():
    raise Exception("An error occurred")

try:
    function_a()
except Exception as e:
    import traceback
    print(traceback.format_exc())

The stack trace shows the sequence of calls, helping pinpoint the error’s origin.

5. How can you debug a memory leak in an application?

A memory leak occurs when memory isn’t released, causing increased usage over time. To debug, use tools like psutil or tracemalloc to monitor memory, memory_profiler or objgraph for detailed allocation info, and the gc module for garbage collection analysis. Tools like Pympler and Heapy offer advanced profiling and debugging capabilities.

6. How can you use conditional breakpoints in pdb to debug specific scenarios?

Conditional breakpoints in pdb pause execution only when conditions are met, useful for specific scenarios. Use the break command with a line number and condition.

Example:

import pdb

def find_even_numbers(numbers):
    even_numbers = []
    for number in numbers:
        pdb.set_trace()  # Set a breakpoint
        if number % 2 == 0:
            even_numbers.append(number)
    return even_numbers

numbers = [1, 2, 3, 4, 5, 6]
pdb.run('find_even_numbers(numbers)')

Set a conditional breakpoint with:

(Pdb) break 7, number == 4

Execution pauses when number equals 4.

7. How can you debug issues related to asynchronous code?

Debugging asynchronous code involves handling race conditions and timing issues. Techniques include detailed logging, breakpoints in IDEs, enabling asyncio debug mode, and using tools like aiomonitor.

Example:

import asyncio
import logging

logging.basicConfig(level=logging.DEBUG)

async def async_task(name, delay):
    logging.debug(f"Task {name} started")
    await asyncio.sleep(delay)
    logging.debug(f"Task {name} completed")

async def main():
    tasks = [
        async_task("A", 2),
        async_task("B", 1)
    ]
    await asyncio.gather(*tasks)

if __name__ == "__main__":
    asyncio.run(main(), debug=True)

8. How can you debug a Django application using the built-in Django debugger?

Django’s built-in debugger displays detailed error pages with stack traces and local variables when DEBUG is True. To enable it, set DEBUG = True in settings.py. Use pdb to set breakpoints and inspect the application state.

Example:

import pdb

def my_view(request):
    pdb.set_trace()  # Set a breakpoint here
    # Your code here

Execution pauses at pdb.set_trace(), allowing interaction with the debugger.

9. How can you use the pdb.set_trace() function to start a debugging session at a specific point in your code?

The pdb.set_trace() function pauses execution and starts a debugging session at a specific point. It allows inspection of variables and stepping through code.

Example:

import pdb

def add(a, b):
    pdb.set_trace()  # Start debugging session here
    return a + b

result = add(3, 5)
print(result)

Execution pauses at pdb.set_trace(), enabling inspection of a and b.

10. Explain how you would debug a script running inside a Docker container.

To debug a script in a Docker container:

1. Access the container with docker exec.

   docker exec -it <container_id> /bin/bash

2. Check logs with docker logs.

   docker logs <container_id>

3. Use debugging tools like pdb.

   import pdb; pdb.set_trace()

4. Verify environment variables with printenv.

   printenv

5. Inspect the filesystem with Unix commands.

6. Ensure network settings are correct using tools like curl.

11. How can you use remote debugging to debug an application running on a different machine?

Remote debugging allows debugging on a different machine, useful for production environments. Use libraries like ptvsd to set up remote debugging.

Example:

# On the remote machine
import ptvsd

ptvsd.enable_attach(address=('0.0.0.0', 5678))
ptvsd.wait_for_attach()

print("Remote debugging is now enabled.")

Connect from your local machine using an IDE configured to attach to the remote IP and port.

12. How do you use the inspect module to gain insights into live objects during debugging?

The inspect module provides functions to gather information about live objects, such as inspect.getmembers, inspect.getmodule, inspect.getsource, and inspect.signature.

Example:

import inspect

def example_function(a, b):
    return a + b

source_code = inspect.getsource(example_function)
print("Source Code:\n", source_code)

signature = inspect.signature(example_function)
print("Signature:\n", signature)

module = inspect.getmodule(example_function)
print("Module:\n", module)

13. What are some common pitfalls when using debuggers like pdb, and how can you avoid them?

Common pitfalls with debuggers like pdb include over-reliance, not setting breakpoints strategically, ignoring the call stack, skipping exceptions, and not using conditional breakpoints. Avoid these by complementing debugging with code reviews, setting strategic breakpoints, inspecting the call stack, handling exceptions, and using conditional breakpoints.

14. Explain how you would use the faulthandler module to debug crashes.

The faulthandler module helps debug crashes by printing tracebacks. Enable it to automatically print tracebacks on a crash, manually trigger a dump, or set a timeout for hanging programs.

Example:

import faulthandler
import time

faulthandler.enable()
faulthandler.dump_traceback()
faulthandler.dump_traceback_later(5)

time.sleep(10)

faulthandler.cancel_dump_traceback_later()

15. How can you use third-party debugging tools like PyCharm’s debugger or VSCode’s debugger effectively?

Third-party tools like PyCharm’s and VSCode’s debuggers offer features that enhance debugging. They provide a graphical interface for setting breakpoints, stepping through code, inspecting variables, and evaluating expressions.

PyCharm’s debugger:
– Integrated into the IDE for easy breakpoint setting.
– Supports conditional breakpoints.
– Variable explorer for inspecting and modifying values.
– Call stack window for tracing function calls.

VSCode’s debugger:
– Highly configurable with extensions.
– Supports conditional and logpoint breakpoints.
– Debug console for executing code in the current context.
– Watch window for monitoring variables or expressions.

To use these tools effectively:
– Set breakpoints strategically.
– Use conditional breakpoints for specific scenarios.
– Monitor program state with the variable explorer and watch window.
– Utilize the call stack to understand execution flow.