Python List Operations

Utilities for working with Python lists including chunking, filtering, sorting, and transformations

Python List Operations

Python lists are versatile data structures. This collection provides utilities for common list operations that you’ll use in everyday programming.

Split List into Chunks

Divide a list into smaller chunks of a specified size:

from math import ceil

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

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

Or split into a specific number of chunks:

from math import ceil

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

chunk_into_n([1, 2, 3, 4, 5, 6, 7], 4) # [[1, 2], [3, 4], [5, 6], [7]]

Get First and Last Elements

Head of a list

Get the first element safely:

def first(lst):
  return lst[0] if lst else None

first([1, 2, 3]) # 1
first([]) # None

Last element

Get the last element safely:

def last(lst):
  return lst[-1] if lst else None

last([1, 2, 3]) # 3
last([]) # None

Initial elements

Get all elements except the last:

def initial(lst):
  return lst[:-1]

initial([1, 2, 3]) # [1, 2]
initial([]) # []

Tail of a list

Get all elements except the first:

def tail(lst):
  return lst[1:]

tail([1, 2, 3]) # [2, 3]
tail([1]) # []
tail([]) # []

Filter Unique Values

Filter duplicate values from a list:

from collections import Counter

def filter_unique(lst):
  return [item for item, count in Counter(lst).items() if count > 1]

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

Or get only unique values:

from collections import Counter

def filter_non_unique(lst):
  return [item for item, count in Counter(lst).items() if count == 1]

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

Practical Use Cases

Pagination

Use chunk() to paginate data:

users = ['Alice', 'Bob', 'Charlie', 'David', 'Eve', 'Frank']
page_size = 2
pages = chunk(users, page_size)
# [['Alice', 'Bob'], ['Charlie', 'David'], ['Eve', 'Frank']]

Safe Access

Use first() and last() to avoid index errors:

results = search_database(query)
top_result = first(results)  # Returns None if no results

Data Cleaning

Remove duplicates while preserving order:

from collections import Counter

data = [1, 2, 2, 3, 1, 4]
cleaned = filter_non_unique(data)  # [3, 4]

Next Steps

Dictionaries

Learn about dictionary operations

Strings

Explore string manipulation utilities