Algorithms & data structures
Classic patterns — search, sort, stacks, queues, and practical complexity-aware code.
Find Common Elements in List of Lists in Python
Return elements that appear in every sublist of a nested list, preserving duplicates with Counter intersection.
from collections import Counter
def common_elements(list_of_lists):
"""Return elements present in every sublist."""
if not list_of_lists:
return []
counts = Counter(list_of_lists[0])
for sublist in list_of_lists[1:]:
counts &= Counter(sublist)
return list(counts.elements())
if _…Find Elements in One Python List but Not Another
Return a new list containing only the elements from list A that are not present in list B, preserving duplicates and order.
def difference_elements(a, b):
"""Return elements present in list a but not in list b."""
set_b = set(b)
return [item for item in a if item not in set_b]
if __name__ == "__main__":
a = [1, 2, 3, 4, 5, 3, 2]
b = [2, 4, 6]
result = difference_elements(a, b)
print(f"A: {a}")
print(f"B: {b…How to Remove Duplicates in Python Preserving Order
Removes duplicate items from a list while keeping the first occurrence order intact using a set for fast membership checks.
def remove_duplicates_preserving_order(items):
seen = set()
result = []
for item in items:
if item not in seen:
seen.add(item)
result.append(item)
return result
if __name__ == "__main__":
sample = [3, 1, 2, 1, 3, 4, 2, 5]
unique_items = remove_duplicates_preserv…Browse by section
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Algorithms & data structures — Python code examples
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