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Python List Operations

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

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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]]

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Get First and Last Elements

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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

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Last element

Get the last element safely: 
def last(lst):
  return lst[-1] if lst else None

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

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Initial elements

Get all elements except the last: 
def initial(lst):
  return lst[:-1]

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

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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([]) # []

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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]

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Practical Use Cases

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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']]

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Safe Access

Use first() and last() to avoid index errors: 
results = search_database(query)
top_result = first(results)  # Returns None if no results

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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]

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Next Steps

Dictionaries

Learn about dictionary operations

Strings

Explore string manipulation utilities

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