Topic: Python Exception Handling — Managing Errors Gracefully
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Why Handle Exceptions?
• To prevent your program from crashing unexpectedly.
• To provide meaningful error messages or recovery actions.
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Basic Try-Except Block
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Catching Multiple Exceptions
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Using Else and Finally
• else block runs if no exceptions occur.
• finally block always runs, used for cleanup.
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Raising Exceptions
• You can raise exceptions manually using raise.
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Custom Exceptions
• Create your own exception classes by inheriting from Exception.
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Summary
• Use try-except to catch and handle errors.
• Use else and finally for additional control.
• Raise exceptions to signal errors.
• Define custom exceptions for specific needs.
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#Python #ExceptionHandling #Errors #Debugging #ProgrammingTips
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Why Handle Exceptions?
• To prevent your program from crashing unexpectedly.
• To provide meaningful error messages or recovery actions.
---
Basic Try-Except Block
try:
result = 10 / 0
except ZeroDivisionError:
print("Cannot divide by zero!")
---
Catching Multiple Exceptions
try:
x = int(input("Enter a number: "))
result = 10 / x
except (ValueError, ZeroDivisionError) as e:
print(f"Error occurred: {e}")
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Using Else and Finally
• else block runs if no exceptions occur.
• finally block always runs, used for cleanup.
try:
file = open("data.txt", "r")
data = file.read()
except FileNotFoundError:
print("File not found.")
else:
print("File read successfully.")
finally:
file.close()
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Raising Exceptions
• You can raise exceptions manually using raise.
def check_age(age):
if age < 0:
raise ValueError("Age cannot be negative.")
check_age(-1)
---
Custom Exceptions
• Create your own exception classes by inheriting from Exception.
class MyError(Exception):
pass
def do_something():
raise MyError("Something went wrong!")
try:
do_something()
except MyError as e:
print(e)
---
Summary
• Use try-except to catch and handle errors.
• Use else and finally for additional control.
• Raise exceptions to signal errors.
• Define custom exceptions for specific needs.
---
#Python #ExceptionHandling #Errors #Debugging #ProgrammingTips
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In Python programming exams, follow these structured steps to solve problems methodically, staying focused and avoiding panic: Start by reading the problem twice to clarify inputs, outputs, and constraints—write them down simply. Break it into small sub-problems (e.g., "handle edge cases first"), plan pseudocode or a flowchart on paper, then implement step-by-step with test cases for each part, debugging one issue at a time while taking deep breaths to reset if stuck.
This approach builds confidence—practice on platforms like LeetCode to make it habit! #python #problemsolving #codingexams #debugging #interviewtips
👉 @DataScience4
# Example: Solve "Find max in list" problem step-by-step
# Step 1: Understand - Input: list of nums; Output: max value; Constraints: empty list?
def find_max(numbers):
if not numbers: # Step 2: Handle edge case (empty list)
return None # Or raise ValueError
max_val = numbers # Step 3: Initialize with first element
for num in numbers[1:]: # Step 4: Loop through rest (sub-problem: compare)
if num > max_val:
max_val = num
return max_val # Step 5: Return result
# Step 6: Test cases
print(find_max([3, 1, 4, 1, 5])) # Output: 5
print(find_max([])) # Output: None
print(find_max()) # Output: 10
# If stuck: Comment code to trace, or simplify (e.g., use max() built-in first to verify)
This approach builds confidence—practice on platforms like LeetCode to make it habit! #python #problemsolving #codingexams #debugging #interviewtips
👉 @DataScience4
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