Python Data Structures

items.append(value)

# Append item

items.extend([4, 5, 6])

# Extend list

items.insert(0, value)

# Insert at index

subset = items[1:4]

# Slice a list

reversed_items = items[::-1]

# Reverse slice copy

items.sort(key=str.lower, reverse=False)

# Sort in place

ordered = sorted(items)

# Sorted copy

items.remove(value)

# Remove by value

last = items.pop()

# Pop last item

count = items.count(value)

# Count occurrences

theme = settings.get("theme", "light")

# Get with default

items = grouped.setdefault(category, [])

# Set default

merged = defaults | overrides

# Merge dictionaries

config |= extra_config

# Dictionary update

for key, value in data.items():
    print(key, value)

# Iterate keys and values

squares = {n: n * n for n in range(5)}

# Dictionary comprehension

inverse = {value: key for key, value in mapping.items()}

# Invert mapping

combined = a | b

# Set union

common = a & b

# Set intersection

only_a = a - b

# Set difference

changed = a ^ b

# Symmetric difference

is_subset = a <= b

# Is subset

from collections import namedtuple
Point = namedtuple("Point", ["x", "y"])
p = Point(10, 20)

# Named tuple alternative

from collections import deque
queue = deque(["a", "b"])
queue.append("c")
item = queue.popleft()

# Deque as queue

from collections import Counter
counts = Counter(words)
common = counts.most_common(3)

# Counter frequencies

from collections import defaultdict
groups = defaultdict(list)
for user in users:
    groups[user["role"]].append(user)

# Defaultdict list grouping

import heapq
heap = []
heapq.heappush(heap, 5)
smallest = heapq.heappop(heap)

# Heap push and pop