Types of Errors in Python: Learn with Practical Examples

Common Error Types

1. Syntax Errors

Python has a simple syntax. However, whether you are learning Python for the first time or have a solid background in another programming language, you may encounter some things it needs to enable. Non-standard letter, word, and symbol arrangements cause syntax mistakes in computer source code. These problems prevent compilers and interpreters from translating code into executable form, which is necessary for the program to work or produce the expected outcome.

Common causes of Syntax errors

• Punctuation errors (parentheses, brackets, braces, quotations, commas, colons)
• Misspelled or missing keywords
• Illegal characters in variable names
• Incorrect indentation
• Improper use of the assignment operator (=)

Example:

x = 6
if x == 6
print("x is 6")

Output:

File "c:\Users\name\OneDrive\Desktop\sample.py", line 3

If x == 6

^

SyntaxError: expected ':'

The sample.py file has a SyntaxError on line 3.

Solution:

The if statement on line 3 lacks a colon (:), causing a SyntaxError. The right code should be:

x = 6

if x == 6:

print("x is 6")

2. Runtime Errors

Python Runtime errors occur when an unforeseen condition prevents the program from proceeding. Runtime issues are challenging to reproduce and debug. The two main tasks of a runtime problem are finding their cause and adjusting the code to address or avoid them.

a. NameError

The Python interpreter raises a Name error when it cannot find a variable or function name in the scope. It can happen if you misspell a variable or function name, use it before it's defined, or reference it outside the scope.

Tips to follow:

• Ensure proper spelling and capitalization of variable and function names.
• Discover name issues using Python's built-in debugging tools, such as print statements.

Example:

my_variable = 10
print(my_vairable)

Output:

The variable name my_variable was misspelled as my_vairable.

Solution:

my_variable = 5

print(my_variable)

b. Type Error

A Type error is raised when a Python action or function is called on an invalid object. It occurs when performing arithmetic or logical operations on incompatible data types or supplying the wrong kind of function arguments.

Tips to follow:

• Use type annotations to specify expected data types in code.
• Utilize Python's built-in type-checking facilities, like typing modules.
• Create unit tests to verify proper data handling in code.

Example:

x = "4"
y = 6
result = x + y

Output:

It's impossible to concatenate a string and an integer.

Solution:

x = "4"

y = 6

result = int(x) + y

First, transform the string to an integer using int() before adding.

c. Index error

Python throws an Index error when we access an out-of-range index of a string, list, or tuple. 

Tips to follow:

• Ensure proper index values for your series.
• Consider using Python's built-in methods like len to calculate sequence length before accessing items.
• Consider using try and except blocks to gently handle index problems.

Example:

my_list = [1, 2, 3, 4, 5]
print(my_list[6])

Output:

This example attempts to retrieve an item at index 6, which is outside the list.

Solution:

my_list = [1, 2, 3, 4, 5]

print(my_list[4])

Here, we access index 4, which is in the list.

Also Read: Indexing in Python

d. Attribute Error

An Attribute error is raised in Python when you try to access an object's undefined attribute or method. This can happen if you misspell an attribute or method name or attempt to access one that needs to be specified for your object type. Understanding attribute types and how they work is crucial to avoid attribute errors. Ensure you're accessing attributes correctly and not trying to access non-existent attributes.

Example:

my_list = [1, 2, 3]
my_list.append(4)
my_list.add(5)

Output:

This example uses the add() method, which lists don't have.

Solution:

my_list = [1, 2, 3]

my_list.append(4)

Here, we add a list item using append().

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3. Logical Errors

Fixing logical flaws is the most challenging task when the software runs without crashing but delivers an inaccurate result. A program logic fault causes the error. Neither syntactic nor runtime errors will occur, so no error message will appear. Some tools can identify questionable code that may cause unexpected behavior. Still, you must find the problem by reviewing all relevant code.

Reasons for Logical errors:

• Misusing variable names 
• Indenting blocks incorrectly 
• Integer division instead of floating point division 
• Incorrect operator precedence
• Creating boolean expression mistakes 
• Off-by-one and other numerical errors

Example:

def calculate_factorial(n):
result = 1
for i in range(1, n):
result = result * i
return result
print(calculate_factorial(5))

Output:

24

This sample calculates the factorial of n using calculate_factorial(). For example, for n = 5, it runs without error but outputs 24 instead of 120. 

Solution:

To solve this logical problem, we must include n in the for loop range. The correct code is:

def calculate_factorial(n):

result = 1

for i in range(1, n+1):

result = result * i

return result

print(calculate_factorial(5))

Output:

120

Error Handling

Debugging and error handling in Python require knowledge of error kinds. Syntax problems can be found and fixed during compilation, while Runtime errors require try-except blocks. Python programmers can build robustness by understanding how to handle various failures.

Try-except Block

Python error handling uses try-except blocks to catch and manage exceptions that could crash or act unexpectedly. The try-except block is Python's primary exception handler. The try block raises exceptions, and the except block manages them.

Example:

a = 20
b = 0
c = a/b
Except ZeroDivisionError:
print("Cannot divide by zero!")

Output:

You cannot divide by zero!

In the try block, dividing a number by zero throws a ZeroDivisionError. If an exception occurs, the except block outputs a user-friendly message to the console.

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Conclusion

You can become a more confident and productive coder by identifying and fixing these Python errors. Consider joining Simplilearn's Python program to enhance your Python development skills further and become a professional. You can opt for Simplilearn’s Python Certification Course to learn the basics of Python, data operations, conditional statements, shell scripting, and Django. This certification course will give you hands-on development experience and prepare you for an exciting career as a Python professional.

FAQs

1. How do I identify a Syntax Error in my Python code?

The traceback provides numerous features to assist you in finding the Python SyntaxError in your code:

• The filename where the interpreter encountered improper syntax.
• The code line number and reproduced line where the fault occurred.
• A caret (^) should be placed under the replicated code. It shows where the code is wrong.
• Error message after SyntaxError exception type. It helps identify syntactic errors.

2. Why do I get a Name Error, and how can I avoid it?

When Python tries to use a variable without a definition or value, a NameError: name 'x' is not defined, and an issue is raised. Make sure the variable is defined and assigned a value before using it to fix the Python NameError: name 'x' is not a defined problem. Correct case and spelling should be used to reference the variable.

3. How can I handle Index errors in Python?

Use try-except to handle "IndexError" in Python. The try block contains code that may cause the issue, and the except block handles it. This construct lets you gracefully manage Python errors and prevent program crashes.

4. What are the best practices for handling exceptions in Python?

Tips for writing clean, robust exception handling:

• Small, concentrated try blocks for effective exception handling.
• Catch particular exceptions instead of generic Exception classes to distinguish failures.
• Include custom error messages in unless blocks for failures.
• Reliable execution of cleanup code sections using the final clause.
• Create exception classes for specific application contexts.
• Use try-except blocks only when necessary.