Python Fundamentals: String, List, Dictionary Operations and Common Techniques

1. String reversal – Use slicing or reduce to reverse a string.

# Using slicing to reverse a string
original_str = "hello"
reversed_str = original_str[::-1]
print("Reversed string:", reversed_str)  # Output: olleh

# Using reduce to reverse a string
from functools import reduce
reversed_str = reduce(lambda x, y: y + x, original_str)
print("Reversed string:", reversed_str)  # Output: olleh

2. Palindrome check – Compare a string with its reversed version.

def is_palindrome(s):
    return s == s[::-1]

test_str = "madam"
if is_palindrome(test_str):
    print(f"{test_str} is a palindrome.")
else:
    print(f"{test_str} is not a palindrome.")

3. Word case transformations – capitalize(), title(), and upper() methods.

original_str = "hello world"
capitalized_str = original_str.capitalize()
print("Capitalize:", capitalized_str)  # Hello world

title_str = original_str.title()
print("Title:", title_str)  # Hello World

upper_str = original_str.upper()
print("Upper:", upper_str)  # HELLO WORLD

4. Splitting and stripping strings – split() returns a list; strip() removes surrounding whitespace.

sentence = "hello world this is python"
words = sentence.split()
print("Words:", words)

trimmed_str = "   hello world   ".strip()
print("Trimmed:", trimmed_str)

5. Joining a list of strings – Use " ".join(list).

words = ["hello", "world", "this", "is", "python"]
sentence = " ".join(words)
print("Joined:", sentence)

6. Finding unique elements – Convert to set for strings or lists.

unique_chars = set("hello")
print("Unique chars:", unique_chars)

unique_items = set([1, 2, 2, 3, 4, 4, 5])
print("Unique items:", unique_items)

7. Repeating elements – List multiplication or addition.

# Multiplication
repeated_list = [1, 2] * 3
print("Repeated:", repeated_list)

# Addition
repeated_list = [1, 2] + [1, 2] + [1, 2]
print("Repeated:", repeated_list)

8. List comprehensions and flattening – Generate new lists or flatten nested lists.

# Generate squares
squares = [x ** 2 for x in range(5)]
print("Squares:", squares)

# Flatten nested list
nested_list = [[1, 2], [3, 4], [5, 6]]
flattened = [item for sublist in nested_list for item in sublist]
print("Flattened:", flattened)

9. Deep flattening – Use iteration_utilities.deepflatten or a recursive function.

from iteration_utilities import deepflatten
nested = [1, [2, [3, 4], 5], 6]
flattened = list(deepflatten(nested))
print("Deep flattened:", flattened)

def flatten(lst):
    result = []
    for item in lst:
        if isinstance(item, list):
            result.extend(flatten(item))
        else:
            result.append(item)
    return result

print("Recursive flatten:", flatten(nested))

10. Variable swapping – Tuple unpacking or a temporary variable.

# Direct swap
a, b = 5, 10
a, b = b, a
print("Swapped:", a, b)

# Using temp variable
temp = a
a = b
b = temp
print("Swapped with temp:", a, b)

11. Enumerate index‑value pairs – enumerate() over an iterable.

fruits = ["apple", "banana", "cherry"]
for index, fruit in enumerate(fruits):
    print(f"Index: {index}, Fruit: {fruit}")

12. Measuring execution time – Use time.time() before and after code.

import time
start = time.time()
# Core code
time.sleep(2)
end = time.time()
print("Execution time:", end - start, "seconds")

13. Checking object memory size – sys.getsizeof().

import sys
print("Int size:", sys.getsizeof(10))
print("String size:", sys.getsizeof("hello"))
print("List size:", sys.getsizeof([1,2,3]))

14. Merging dictionaries – Dictionary unpacking or update().

# Unpacking merge
merged = {**{'a':1,'b':2}, **{'b':3,'c':4}}
print("Merged:", merged)

# Using update
d1 = {'a':1,'b':2}
d2 = {'b':3,'c':4}
d1.update(d2)
print("Updated:", d1)

15. Random sampling – random.sample() selects unique elements.

import random
items = list(range(1,11))
sample = random.sample(items, 5)
print("Sampled:", sample)

16. Checking list uniqueness – Compare length with set() length.

items = [1,2,3,4,5]
print("Unique?", len(items) == len(set(items)))

17. Fibonacci sequence – Generator function using yield.

def fibonacci(n):
    a, b = 0, 1
    while a < n:
        yield a
        a, b = b, a + b

for num in fibonacci(10):
    print(num)

18. List average – sum() divided by len().

numbers = [1,2,3,4,5]
avg = sum(numbers) / len(numbers)
print("Average:", avg)

19. Prime number test – Check divisibility up to square root.

def is_prime(n):
    if n <= 1:
        return False
    for i in range(2, int(n**0.5)+1):
        if n % i == 0:
            return False
    return True

print(is_prime(17))

20. Character frequency – collections.Counter counts occurrences.

from collections import Counter
text = "hello world"
print(Counter(text))

21. List intersection – Use set & to find common elements.

list1 = [1,2,3,4,5]
list2 = [4,5,6,7,8]
common = set(list1) & set(list2)
print("Common:", common)

22. Sorting a dictionary by value – sorted() with lambda.

scores = {'Alice':95,'Bob':85,'Charlie':90}
sorted_scores = sorted(scores.items(), key=lambda x: x[1], reverse=True)
print(sorted_scores)

23. Deleting a key from a dictionary – pop() or del.

scores = {'Alice':95,'Bob':85,'Charlie':90}
removed = scores.pop('Bob')
print(scores, removed)

del scores['Charlie']
print(scores)

24. File existence check – os.path.exists().

import os
if os.path.exists('example.txt'):
    print('File exists')
else:
    print('File does not exist')

25. Reading a file line by line – with open() and iteration.

with open('example.txt', 'r', encoding='utf-8') as f:
    for line in f:
        print('Line:', line.strip())

26. Converting list elements to a string – map(str, list) and join().

numbers = [1,2,3,4,5]
joined = ", ".join(map(str, numbers))
print(joined)

The article concludes that mastering these core Python syntax details—from basic string, list, and dictionary operations to exception handling, timing, memory inspection, generators, and file I/O—significantly boosts programming efficiency and code readability.