30 Essential Python Tricks to Boost Your Coding Skills

Learning Python quickly comes from hands‑on mini‑projects; the following thirty minimal tasks provide practical examples for beginners and useful snippets for experienced developers.

1. Duplicate element detection

Checks whether a list contains duplicate elements by comparing its length to the length of a set built from the list.

def all_unique(lst):
    return len(lst) == len(set(lst))

x = [1,1,2,2,3,2,3,4,5,6]
y = [1,2,3,4,5]
all_unique(x)  # False
all_unique(y)  # True

2. Anagram (character composition) check

Determines whether two strings consist of the same characters using collections.Counter.

from collections import Counter

def anagram(first, second):
    return Counter(first) == Counter(second)

anagram("abcd3", "3acdb")  # True

3. Memory size of a variable

Uses sys.getsizeof to report the memory consumption of an integer.

import sys
variable = 30
print(sys.getsizeof(variable))  # 24

4. Byte size of a string

Returns the number of bytes a UTF‑8 encoded string occupies.

def byte_size(string):
    return len(string.encode('utf-8'))

byte_size('')          # 0
byte_size('Hello World')  # 11

5. Print a string N times without a loop

Leverages Python’s string multiplication to repeat a string.

n = 2
s = "Programming"
print(s * n)  # ProgrammingProgramming

6. Capitalize the first letter of each word

Uses the title() method to title‑case a sentence.

s = "programming is awesome"
print(s.title())  # Programming Is Awesome

7. Chunk a list into fixed‑size pieces

Splits a list into sub‑lists of a given size using ceil and map.

from math import ceil

def chunk(lst, size):
    return list(map(lambda x: lst[x*size:x*size+size], range(0, ceil(len(lst)/size))))

chunk([1,2,3,4,5], 2)  # [[1, 2], [3, 4], [5]]

8. Compact a list by removing falsy values

Filters out False, None, 0, empty strings, etc., using filter(bool, …).

def compact(lst):
    return list(filter(bool, lst))

compact([0, 1, False, 2, '', 3, 'a', 's', 34])  # [1, 2, 3, 'a', 's', 34]

9. Unpack paired lists into separate tuples

Uses zip(*array) to transpose a list of pairs.

array = [['a','b'], ['c','d'], ['e','f']]
transposed = zip(*array)
print(list(transposed))  # [('a', 'c', 'e'), ('b', 'd', 'f')]

10. Chain comparisons in a single expression

Shows how Python can compare multiple values without repeating variables.

a = 3
print(2 < a < 8)   # True
print(1 == a < 2)  # False

11. Join a list with commas

Concatenates list elements into a single string separated by commas.

hobbies = ["basketball", "football", "swimming"]
print("My hobbies are: " + ", ".join(hobbies))
# My hobbies are: basketball, football, swimming

12. Count vowels using a regular expression

Counts occurrences of a, e, i, o, u (case‑insensitive) in a string.

import re

def count_vowels(s):
    return len(re.findall(r'[aeiou]', s, re.IGNORECASE))

count_vowels('foobar')  # 3
count_vowels('gym')     # 0

13. Decapitalize the first character

Ensures the first character of a string is lower‑case while leaving the rest unchanged.

def decapitalize(string):
    return string[:1].lower() + string[1:]

decapitalize('FooBar')  # 'fooBar'

14. Flatten a nested list (shallow)

Recursively expands one level of nesting into a flat list.

def spread(arg):
    ret = []
    for i in arg:
        if isinstance(i, list):
            ret.extend(i)
        else:
            ret.append(i)
    return ret

def deep_flatten(lst):
    result = []
    result.extend(spread(list(map(lambda x: deep_flatten(x) if type(x) == list else x, lst))))
    return result

deep_flatten([1, [2], [[3], 4], 5])  # [1, 2, 3, 4, 5]

15. List difference

Returns elements present in the first list but not in the second.

def difference(a, b):
    set_a = set(a)
    set_b = set(b)
    return list(set_a.difference(set_b))

difference([1,2,3], [1,2,4])  # [3]

16. Difference by applying a function

Applies a function to the second list before computing the difference.

def difference_by(a, b, fn):
    b = set(map(fn, b))
    return [item for item in a if fn(item) not in b]

from math import floor
difference_by([2.1, 1.2], [2.3, 3.4], floor)  # [1.2]

17. Chain function calls in one line

Demonstrates conditional selection of a function and immediate invocation.

def add(a, b):
    return a + b

def subtract(a, b):
    return a - b

a, b = 4, 5
print((subtract if a > b else add)(a, b))  # 9

18. Check for duplicates in a list

Returns True if a list contains any repeated elements.

def has_duplicates(lst):
    return len(lst) != len(set(lst))

has_duplicates([1,2,3,4,5,5])  # True
has_duplicates([1,2,3,4,5])   # False

19. Merge two dictionaries (Python 3.5+)

Shows two ways to combine dictionaries: using dict.update and the unpacking operator **.

def merge_two_dicts(a, b):
    c = a.copy()
    c.update(b)
    return c

a = {'x':1, 'y':2}
b = {'y':3, 'z':4}
print(merge_two_dicts(a, b))  # {'x': 1, 'y': 3, 'z': 4}

# Using dictionary unpacking (Python 3.5+)
def merge_dictionaries(a, b):
    return {**a, **b}

print(merge_dictionaries(a, b))  # {'x': 1, 'y': 3, 'z': 4}

20. Convert two lists into a dictionary

Pairs keys and values with zip and builds a dictionary.

def to_dictionary(keys, values):
    return dict(zip(keys, values))

keys = ["a", "b", "c"]
values = [2, 3, 4]
print(to_dictionary(keys, values))  # {'a': 2, 'b': 3, 'c': 4}

21. Enumerate a list with index

Uses enumerate to access both index and element while iterating.

lst = ["a", "b", "c", "d"]
for index, element in enumerate(lst):
    print("Value", element, "Index", index)
# Value a Index 0
# Value b Index 1
# Value c Index 2
# Value d Index 3

22. Measure execution time of a code block

Records start and end timestamps with time.time() and computes the elapsed time.

import time
start_time = time.time()
# Example computation
c = 1 + 2
print(c)  # 3
end_time = time.time()
print("Time:", end_time - start_time)

23. try … else clause

Executes the else block only when no exception is raised.

try:
    2 * 3
except TypeError:
    print("An exception was raised")
else:
    print("Thank God, no exceptions were raised.")
# Thank God, no exceptions were raised.

24. Most frequent element in a list

Finds the element that appears most often using max with list.count.

def most_frequent(lst):
    return max(set(lst), key=lst.count)

lst = [1,2,1,2,3,2,1,4,2]
print(most_frequent(lst))  # 2

25. Palindrome check

Normalizes a string by removing non‑alphanumeric characters and comparing it to its reverse.

def palindrome(string):
    from re import sub
    s = sub(r'[\W_]', '', string.lower())
    return s == s[::-1]

print(palindrome('taco cat'))  # True

26. Arithmetic without if‑else using a dictionary

Maps operator symbols to functions from the operator module.

import operator
action = {
    "+": operator.add,
    "-": operator.sub,
    "/": operator.truediv,
    "*": operator.mul,
    "**": pow,
}
print(action['-'](50, 25))  # 25

27. Shuffle a list (Fisher‑Yates)

Creates a new list with elements randomly reordered.

from copy import deepcopy
from random import randint

def shuffle(lst):
    temp = deepcopy(lst)
    m = len(temp)
    while m:
        m -= 1
        i = randint(0, m)
        temp[m], temp[i] = temp[i], temp[m]
    return temp

print(shuffle([1,2,3]))  # e.g., [2, 3, 1]

28. Fully flatten a nested list

Recursively expands all sub‑lists into a single flat list.

def spread(arg):
    ret = []
    for i in arg:
        if isinstance(i, list):
            ret.extend(i)
        else:
            ret.append(i)
    return ret

print(spread([1,2,3,[4,5,6],[7],8,9]))  # [1,2,3,4,5,6,7,8,9]

29. Swap two values without a temporary variable

Returns the values in reversed order.

def swap(a, b):
    return b, a

a, b = -1, 14
print(swap(a, b))  # (14, -1)

30. Dictionary get with default value

Uses dict.get(key, default) to provide a fallback when the key is missing.

d = {'a': 1, 'b': 2}
print(d.get('c', 3))  # 3

Original source: http://dwz.date/bYre – Author: Fatos Morina