Understanding Stack Traces and Control Flow in Python

After learning to raise and catch exceptions, we took a step deeper — into how Python handles control flow when something goes wrong.

This meant examining how the call stack unwinds, how tracebacks are generated, and how to debug problems with greater precision.

Step 1 — What Is a Stack Trace?

A stack trace (or traceback) is Python’s way of telling you: “Here’s what happened, and here’s where.”

When an exception is raised and not caught, Python shows:

The file and line where the error occurred
The function calls that led there
The type and message of the exception

Example:

Traceback (most recent call last):
  File "main.py", line 15, in <module>
    run()
  File "main.py", line 10, in run
    process()
  File "main.py", line 6, in process
    raise ValueError("Bad input")
ValueError: Bad input

Step 2 — Following the Call Chain

We practiced tracing how control flows through a series of function calls:

def a():
    b()

def b():
    c()

def c():
    raise RuntimeError("Something went wrong")

a()

Even if the error is in c(), the traceback shows the full call chain: a → b → c.

This is essential when debugging large systems.

Step 3 — Catching and Logging Errors

We used traceback to capture the full stack trace as a string for logging:

import traceback

try:
    a()
except Exception:
    err = traceback.format_exc()
    log_error(err)

This is especially useful in long-running systems (like servers) where you don’t want to crash but do want a record.

Step 4 — Reraising Exceptions

Sometimes, you want to catch an exception temporarily, then re-raise it:

try:
    dangerous_operation()
except SomeError:
    log("Something went wrong")
    raise  # Propagate up

This preserves the original traceback and lets higher levels decide what to do.

Key Insight

When an exception is raised:

Python suspends the current function
It checks for an except block in that scope
If none, it goes up the call stack
If still unhandled, it prints the traceback and stops the program

Understanding this flow is vital for writing robust, debuggable code.