4 Python Coding Errors That Are Killing Your Speed

1. Using Inefficient Data Structures

Error: Using lists where sets or dictionaries would be more efficient (e.g., membership checks).

Fix: Replace lists with sets for faster membership testing or dictionaries for faster key lookups.

# Inefficient
my_list = [1, 2, 3, 4, 5]
item = 3
if item in my_list:
    print("Item found")

# Efficient
my_set = {1, 2, 3, 4, 5}
item = 3
if item in my_set:
    print("Item found")

Item found
Item found

2. Excessive Function Calls

Error: Calling functions repeatedly in performance-critical code, especially in loops.

Fix: Use local variables or inline code where function calls are unnecessary.

# Inefficient
def process_item(item):
    print(item)

my_list = [1, 2, 3, 4, 5]
for i in range(len(my_list)):
    process_item(my_list[i])

# Efficient
def process_item(item):
    print(item)

items = [1, 2, 3, 4, 5]
for item in items:
    process_item(item)

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