Python is frequently praised for its beginner-friendly characteristics, but it comes with its own set of hurdles that can confuse even the most conscientious of students. If we’re honest, the majority of errors students encounter while completing their Python assignments aren’t mysterious or complex – they’re shockingly mundane, and avoidable!
The same few mistakes are repeated again and again. Whether it’s an unattended colon, a misspelled variable, or a rogue list index, the possibility of debugging sometimes turns into hours if you have no idea of what to be looking for!
This article breaks down the 10 common Python errors that students run into, with simple examples and simple resolutions. In a strict sense, this article will be like a debugging checklist for you; a list that not only helps you troubleshoot your problems, but also makes you a better coder and more confident programmer!
Still, if you face any issues while working on your Python coding homework, you can always get Python Homework assistance from our experts online.
10 Most Common Python Errors in Student Assignments (And Quick Fixes)
In this section, we will break down the 10 most frequent Python errors that students run into, with simple examples and simple resolutions.
1. Indentation Errors
An Indentation error is caused by not lining up the code properly. Python uses indentation to distinguish between blocks of code. If the code isn’t consistent or missing indentation altogether, the execution will break immediately.
Most modern code editors can automatically manage indentation for you, especially if you’re using one of the best IDEs for Python programming.
Example:
for i in range(5):
print(i)
Now, instead of rewriting this function in another script, you can simply import the strings_utils module to use in another script:
This may seem alright with one quick review. But not even Python will take that and will throw an IndentationError since the print() statement is not properly aligned.
How to fix it:
for i in range(5):
print(i)
Quick tips:
* Always use the same number of spaces (4 usually) for each indentation level.
* Avoid mixing tabs and spaces — usually the source of inconsistencies and invisible issues.
* Leverage your code editor. The majority of code editors, especially VS Code and PyCharm, can usually handle indentation automatically if you have set it up correctly.
2. NameError: Name is Not Defined
A NameError occurs when we attempt to reference a variable or function that does not yet exist. This is commonly seen due to a typo, or attempting to execute something out of order, or assuming that a variable you know exists is created.
It’s important to properly define and reference your variables, especially when working with Python structures like lists and their indexes.
Example:
print(my_var)
In this case, NameError will be raised because my_var has not been created or assigned a value before use.
How to fix it:
my_var = 10
print(my_var)
Quick tips:
- Define variables before you use them.
- Watch out for any spelling/case errors.
- If you are using a function/variable from another file, always make sure you import it correctly.
3. TypeError: Unsupported Operand Types
You will be given this error when you are trying to use an operator on types that are not compatible. A very common example is when you try to do the addition operator + on a string and an integer.
Example:
result = '5' + 10
Here you will raise a TypeError, because Python does not know how to add a string directly to an integer.
How to fix it:
result = int('5') + 10
Quick tips:
- Use type conversion when needed (int(), str(), or float())
- Recognize that user input usually comes as strings.
- Use type() to check types when you are debugging.
4. IndexError: List Index Out of Range
You’re going to see this error when you try to access an element at a position that does not exist in a list. Usually, if you have done this, you did not realize that you had gone past the actual length of the list.
Example:
my_list = [1, 2, 3]
print(my_list[5])
This will crash because you’re looking for the item at index 5, but the list only has 3 items (at positions 0, 1, and 2).
How to fix it:
my_list = [1, 2, 3]
print(my_list[5])
Quick tips:
- Remember that list indices start at 0, not 1.
- You should also look at the length of the list before accessing an index using len(my_list).
- You should also look for loops like for i in range(len(my_list)), again to avoid this error by being sure you’re inside the limits of the list.
5. KeyError: Key Not in Dictionary
This error will occur when you attempt to create a dictionary access and the key does not exist. Lists would give an IndexError if you accessed out of range, but a dictionary will raise a KeyError in the event of accessing a missing key.
Example:
my_dict = {'name': 'Alice'}
print(my_dict['age'])
In this case, we get a KeyError because we don’t have the key ‘age’ in the dictionary.
How to fix it:
print(my_dict.get('age', 'Not Found'))
Quick tips:
- When attempting to access a key, use .get() with a default value.
- Before accessing a key, check if one exists using ‘key’ in the dict.
- If your keys are dynamic or user-generated, validate for existence before attempting access.
6. ZeroDivisionError: Dividing by Zero
This one is very clear-cut- if you try to divide any number by zero, Python will raise a ZeroDivisionError. This is a standard error, especially when passing in user-input values or values you haven’t checked properly.
Example:
denominator = 0
result = 10 / denominator
Now, Python will stop the program here, because dividing by zero isn’t permitted in mathematics, and Python isn’t going to let you pass at that either.
How to fix it:
denominator = 0
if denominator != 0:
result = 10 / denominator
else:
print("Cannot divide by zero.")
Quick tips:
- Always check your denominators before performing divisions.
- Use conditional statements to avoid crashing unexpectedly.
- For more complicated situations, you can always use try-except statements to catch and deal with an error more gracefully.
7. SyntaxError: Expected Colon
Coming across a missing colon error is one of the most common types of errors to make, so it is also one of the easiest to overlook. Certain statements in Python expect a colon to follow them — if, for, or while statements and function definitions being the most common cases. A simple omission of a colon can prevent your entire script from running.
Example:
x = 10
if x == 10
print("x is 10")
Python will throw a SyntaxError here because the if statement is missing a proper enclosure with a colon.
How to fix it:
x = 10
if x == 10
print("x is 10")
Quick tips:
- Make a point of putting a colon at the end of if, elif, else, for, while, def, and class statements.
- If you are unsure, your editor will usually help you out; many will highlight syntax issues in real-time.
- Reading your code line by line out loud often helps to catch simple misses like this.
8. ValueError: Invalid Literal
A ValueError occurs when a function receives the correct type of input, but the value doesn’t make sense. The most common case is converting a string to a number, but the string isn’t a valid number.
Example:
number = int(‘abc’)
Here, Python throws a ValueError because ‘abc’ can’t be converted into an integer — it’s not a number.
How to fix it:
try:
number = int('abc')
except ValueError:
print("Invalid input.")
Quick tips:
- Use try-except blocks for input conversion.
- Validate data before converting it, especially if it’s from user input or a third party.
- If you have input from a file or form, expect nothing to be clean.
9. AttributeError: Object Has No Attribute
This error occurs whenever you try to use a method or attribute that simply does not exist for the object you are working on. In most cases, it means you used another object you thought was similar, or you made a typo.
Example:
my_list = [1, 2, 3]
my_list.push(4)
Python will throw an AttributeError because lists don’t have the push() method — this method is used in a programming language like JavaScript. You should call append() in Python.
How to fix it:
my_list = [1, 2, 3]
my_list.append(4)
Quick tips:
- Use dir(object) to check what methods and attributes are available.
- Make sure to check your spelling and case sensitivity — Python is case sensitive.
- Make sure you are calling methods on the right type of object.
10. ImportError: Module Not Found
You usually see this when Python cannot find the module you imported. This will typically happen when you have misspelled the module name, it doesn’t exist, or you forgot to install the third-party package.
Example:
import maths
Here, you will get an ImportError because the correct module name is math and not maths!
How to fix it:
import maths
Quick tips:
- Make sure you double-check for spelling and capitalization in a module name.
- If you’re importing external packages, make sure you install them using the command pip install package_name.
- You can see which modules you have available in your environment by entering pip list.
Conclusion:
There are going to be many kinds of mistakes you will come across as a Python programmer. They all have a solution, once you learn what to look for as mistakes. Hopefully, recognizing the most common Python mistakes early on will save you hours sorting out simple bugs and let you spend more time building cool stuff that works.
To strengthen your Python skills and reduce the chance of repeating common errors, you can try out these beginner-friendly Python project ideas that reinforce concepts through practical coding.
Key Takeaways:
- Python error messages typically tell you exactly what the mistake is – don’t ignore it.
- Details, details, details: be aware of indentation, colons, and data types.
- Use exploratory coding to focus on small chunks of code and immediately catch problems.
- The good news is that with a good editor (IDE you can write a script that puts your Python errors in it, to look at later in long code, and/or an IDE, you can avoid most of this problem before it even happens.
- Asking for help from a community is of critical importance, as well as debugging. Debug code will make you a better programmer – the times you practice will get you better (and faster).
Keep looking for new ways or explore and learn the different examples from books or websites, keep your patience, test your code, and don’t be afraid to break something (this is the only way).
