Common Python Programming Errors
How to avoid them!
Why is Python popular?
Python is a simple language with deceptively tricky problems. Python programming may have bugs or errors when misused. When these errors happen, a simple program that could run an ATM can malfunction, causing what happened to TSB in 2018, causing massive problems and eventually the resignation of their CEO, not to mention the lockout problems where people couldn’t access their money. “6 mistakes every Python beginner should avoid while coding” covers the basics: what version of Python you are running, misunderstanding Python functions, indentation mistakes, and inappropriate naming of variables. These errors are typically caused by simple human errors and will cause problems in the code.
Types of errors
Python has different error codes, such as syntax, type, and runtime errors. A complete list of error types can be found here. The mistakes listed are common in beginning Python users, and I ran into them constantly. What can get highly annoying is when these errors compound on each other, creating a Texas-sized headache! Therefore, in our analysis of common mistakes, we will also review common errors associated with these mistakes.
1: Python version
The version of Python you are running matters. Just as Windows 95 isn’t Windows XP, older versions of Python aren’t new versions of Python. The coding can be different, such as the print functions. In Python 2.0, print is executed as print “hello” whereas, in Python 3.0, the same is run as a print(“hello”). The easiest fix is also the remedy; keep your stuff up to date! The error codes span widely since the literal version of Python being run will alter commands.
2: Misunderstanding program functions
Misunderstanding program functions are a problem; If we enter int(input(henry)), we will get an error since int is for integers; If we were to identify a function as “def: naptime” and then use a bunch of random variables that aren’t tied to that function, the function won’t run that variable. If certain variables are not in a function or loop, the loop/function will enter an endless loop. Therefore, the apparent errors here include the type error (the type of variable doesn’t fit the command), runtime error (running an infinite loop), value error, and the list goes on. To avoid this problem, ensure you understand what you’re putting into the program and the commands you wish to execute. Here is another more complex example under the same title as this one.
3: Bad indenting
Indentation is essential; if we run our if/else program without indenting correctly, we risk syntax error. If our elseif is indented with another inner function, but at the same indent, the program also won’t read that correctly. A function may not even run if we don’t exert proper Indentation methods. Indent correctly and uniformly, and we can move past the problem caused by random, sporadic indenting and miss that pesky indentation error and syntax error.
4: Improper naming
Inappropriate naming is a problem since Python is a very technical program. Without proper naming, Python won’t be able to use what is given in the variable. Apples and apples are different, dale isn’t Dale, and 4 isn’t 4.00000001. For this reason, ensure our programs are named correctly and that the program can run that variable correctly. This way, we can avoid name errors by providing the name is within the scope of that command, and we can also make sure the names are correct in our lists/dictionaries to dodge syntax errors and runtime errors.
More information on common mistakes/errors by coders
Programmers will often need to manually find errors in their program that Python doesn’t pick up since, technically, Python commands execute “properly”- meaning yes, Python will do what it’s told. However, the desired result isn’t what is given- like asking for a late’ and getting apple juice. More examples of errors and what happens can be found by clicking here.
What is a bug?
Bugs are a perfect example of an error needing to be found by manual means- why did you get apple juice when you wanted a late’? These are the hardest to find since Python won’t tell you it’s an error but will run the command! Before you know it, your code is nonsense, and let those headaches ensue! Bugs ultimately act as errors, and remedying them is the same.
Error correction procedures
Proper error remedying technique is paramount to program stability. While the above mistakes are common, all errors stem from roughly three things. Some code is immediately fixable, while others are subtle. The programmer is rushed because of deadlines, writing long, difficult-to-read code, or simply human. This way, proper code editing must be understood; often, Python errors come before the error is found and delivered to the developer. To fix erroneous code, consider the following techniques: coding in parts, understanding Python functions, and simplifying the code.
Coding in parts
Coding in parts helps with one central question: where is my error? A code can work, and then we put in another part of the code which isn’t working. Perhaps the codes are not able to work together? Or is the code written weird? By coding in parts, we can also work in parts, isolate errors to a specific area of code, and save hours, days, and months of difficulty.
Understand Python functions
By understanding Python functions, we will write proper code. Knowing the difference between dictionaries, lists and tuples can save hours of headache. Knowing we write if statements with a condition and an indented effect will ensure the program works correctly. Knowing how to write a function will prevent later slip-ups that take time and money to repair.
Keep it simple!
Finally, simplifying the code will ensure the code is more readable. Writing the code in shorthand after writing it out will give the ability to test that part, ensure it works, and condense the code so it can be read, understood, and studied for errors.
Technology is always and forever surging forward. The technical landscape created by Python, its predecessors, and its future inheritors will evolve, and eventually, what happened to C++ will happen to Java and Python. As we understand how Python works, we too can appreciate its role in this technological world, business, social media, and all aspects of our life.
Either bugs or actual Python errors can and should be fixed to deliver a clean, finished code! We can take the first steps to resolve the issues and make functional, profitable code by recognizing problems. However, the ultimate strategy to find our solutions is the same with any program- Run it! If our program backfires, returns errors, or gives general questionable material for the goal of said program, perhaps it’s time to diagnose our program.