Common Python Coding Mistakes and How to Avoid Them

Python, heralded for its simplicity and readability, has emerged to become one of the most popular programming languages in the world. While it is generally easier to learn and code, even experienced developers can fall into some common traps and mistakes. This article aims to highlight the most frequent coding mistakes made by Pythonistas, and provide tips and solutions to avoid them. Let’s dive in!

1. Improper Indentation

Python uses indentation to define control and loop constructs. This makes Python’s approach different from languages which use braces to define such constructs like C++ or Java.

Python codes that are not correctly indented throw “IndentationError: expected an indented block” error.

# Incorrect
def some_func():
print("Hello, World!")

# Correct
def some_func():
  print("Hello, World!")

To prevent such mistakes, ensure you use a consistent number of spaces (conventionally four) or a tab for each indentation level.

2. Misunderstanding Python Scope Rules

Many beginners don’t have a perfect understanding of how Python scopes work, leading to encountering UnboundLocalError.

This happens because Python doesn’t allow functions to access variables that aren’t in the global scope or haven’t been passed in as arguments.

# Incorrect
x = 10
def some_func():
  x += 5
  print(x)

# Correct
x = 10
def some_func(x):
  x += 5
  print(x)

To avoid this, pass the variable as an argument to the function or declare it as a global variable.

3. Ignoring Python naming conventions

Python uses snake_case as the naming convention. Ignoring this and using camelCase or other conventions may not affect your code, but it’s considered bad practice. To maintain the readability and maintainability of your code, stick to Pythonic naming conventions.

# Incorrect
def SomeFunc(): 
  pass

# Correct
def some_func(): 
  pass

Follow PEP8, the official Python style guide, for maintaining good coding style.

4. Misusing expressions as defaults for function arguments

A common Python pitfall is to use a mutable object as a default value for a function argument. The problem is that the default values for function arguments are evaluated only once when the function is defined, not each time the function is called.

# Incorrect
def add_to(num, target=[]):
  target.append(num)
  return target

# Correct
def add_to(num, target=None):
  if target is None:
    target = []
  target.append(num)
  return target

To avoid this mistake, never use mutable objects as default argument values.

5. Not Using with to Open Files

File operations like open, write, or close can raise an IOError. If the file isn’t closed properly, it can cause data loss or corruption. So, it is very important to close a file after performing operations.

Python provides the with keyword, which makes sure the file is properly closed after performing operations, even if an error was raised.

# Incorrect
file = open('file_path', 'r')
print(file.read())
file.close()

# Correct
with open('file_path', 'r') as file:
  print(file.read())

6. Improper use of == and is

While both == and is are used for checking equality, there is a fundamental difference. == checks if the values are equal, while is checks if they point to the same object in memory.

# Incorrect
list1 = []
list2 = []
print(list1 is list2)  # Prints False

# Correct
list1 = []
list2 = []
print(list1 == list2)  # Prints True

Be sure to understand which type of comparison you want before choosing the operator.

7. Ignoring Errors and Exceptions

Ignoring or not properly handling errors and exceptions can lead to unexpected program behavior. It’s always a good practice to handle exceptions appropriately.

# Incorrect
try:
  some_code()
except:
  pass

# Correct
try:
  some_code()
except Exception as e:
  print(e)

In the correct example, if some_code() throws an exception, it will be caught and printed. This way, you won’t be ignoring potential problems in your program.

8. Incorrect use of loops

Python’s for loop is actually a for-each loop, which gives beginner C/C++ programmers a hard time.

# Incorrect
for i in len(some_list):
  print(some_list[i])

# Correct
for elem in some_list:
  print(elem)

Remember in Python, for directly iterates over elements, unlike C/C++ where the index is used.

9. Mutable default arguments

A common Python pitfall is to use a mutable object as a default value for a function argument. The problem is that the default values for function arguments are evaluated only once at function definition time, which means that modifications to the default value are persistent across function calls.

# Incorrect
def append_to(element, to=[]):
    to.append(element)
    return to

# Correct
def append_to(element, to=None):
    if to is None:
        to = []
    to.append(element)
    return to

Always use None as the default value for arguments that are supposed to be mutable and instantiate them in the function body.

Conclusion

While Python’s syntax is easier to understand and implement, beginners and even seasoned developers can make these common mistakes. However, these are not unforgivable errors but rather stepping stones in your path to becoming a more competent and resourceful Python developer. So keep coding, learning, improving, and remember the real programmer is the one who learns from his/her past mistakes!

References: – Official Python Documentation – Official Python Style Guide – PEP8 – Python Scope & the LEGB Rule by Sven Kreiss – The Hitchhiker’s Guide to Python