Reference library

Dictionaries & sets

Key–value maps, uniqueness, counting, grouping, and fast lookups.

14 matches
Dictionaries & sets easy

Build adjacency dict graph from edges in Python

Convert a list of edges into an undirected adjacency dictionary, mapping each node to its neighbors, with sorted output.

graph adjacency dictionary
Python
def build_adjacency_dict(edges):
    graph = {}
    for u, v in edges:
        if u not in graph:
            graph[u] = []
        if v not in graph:
            graph[v] = []
        graph[u].append(v)
        graph[v].append(u)
    return graph

if __name__ == "__main__":
    edges = [(1, 2), (2, 3), (3, 4), (4, 1)…
13 0 Open
Dictionaries & sets easy

Convert namedtuple to dict with asdict in Python

Convert a namedtuple instance into an ordinary dictionary using the asdict function from the collections module's namedtuple utility.

namedtuple dict asdict
Python
from collections import namedtuple, asdict

def main():
    # Define a namedtuple for a person
    Person = namedtuple("Person", ["name", "age", "city"])
    person = Person(name="Alice", age=30, city="New York")
    
    # Convert namedtuple to dict
    person_dict = asdict(person)
    
    print("Original namedtuple…
12 0 Open
Dictionaries & sets easy

How to Aggregate Order Data with Sets and Dictionaries in Python

Combine sets and dictionaries to find unique products and total quantities from a list of orders in Python.

sets dictionaries data aggregation
Python
def find_unique_products(orders):
    """Return set of all products ordered across multiple orders."""
    all_products = set()
    for order in orders:
        all_products.update(order.get("items", []))
    return all_products


def product_summary(orders):
    """Build a dictionary mapping each product to its total…
13 0 Open
Dictionaries & sets easy

How to Build a Gradebook with Python Dictionaries and Sets

Create a gradebook dictionary from student names and grades, find top students with a set comprehension, and add extra credit with a dict comprehension.

dictionaries sets comprehensions
Python
def build_gradebook(students, grades):
    """Create a dictionary mapping student names to their grades."""
    return dict(zip(students, grades))


def find_top_students(gradebook, passing_grade=60):
    """Return a set of students with grades at or above the passing grade."""
    return {name for name, grade in grad…
12 0 Open
Dictionaries & sets easy

How to Compute Set Union of Tags from Multiple Items in Python

Collect all unique tags from a list of dictionaries using set union with update() in Python.

set union tags dictionaries
Python
items = [
    {"id": 1, "tags": {"python", "web"}},
    {"id": 2, "tags": {"web", "api", "sql"}},
    {"id": 3, "tags": {"python", "data"}},
]


def get_union_of_tags(item_list):
    all_tags = set()
    for item in item_list:
        all_tags.update(item["tags"])
    return all_tags


if __name__ == "__main__":
    u…
14 0 Open
Dictionaries & sets easy

How to Count Tags with Sets and Dictionaries in Python

Count tag frequencies and collect unique tags from a list of dictionaries using Counter and sets in Python.

collections counter sets
Python
from collections import Counter
import json


def count_tags(entries):
    """Count tag frequencies across a list of entry dicts, using sets/dicts."""
    tag_counter = Counter()
    all_tags = set()
    for entry in entries:
        tags = set(entry["tags"])
        all_tags.update(tags)
        tag_counter.update(ta…
11 0 Open
Dictionaries & sets easy

How to Create a Dict from Two Parallel Lists in Python (zip)

Build a dictionary by pairing elements from two parallel lists using Python's built-in zip function and dict constructor.

dictionary zip lists
Python
keys = ["name", "age", "city"]
values = ["Alice", 30, "New York"]

result = dict(zip(keys, values))
print(result)
13 0 Open
Dictionaries & sets easy

How to Extract Data by Category in Python with Dictionaries and Sets

Use set comprehensions and a defaultdict to extract product names by category and compute total prices per category from a list of dictionaries.

dictionaries sets comprehensions
Python
from collections import defaultdict

# Sample data: products with categories and prices
product_data = [
    {"name": "Apple", "category": "fruit", "price": 0.50},
    {"name": "Banana", "category": "fruit", "price": 0.30},
    {"name": "Carrot", "category": "vegetable", "price": 0.80},
    {"name": "Bread", "category…
12 0 Open
Dictionaries & sets easy

How to Index a List of Records by Unique ID in Python

Build a dictionary that maps each record's unique id to the record itself from a list of dictionaries.

dictionary index records
Python
from typing import List, Dict, Any

def index_by_id(records: List[Dict[str, Any]], id_field: str = "id") -> Dict[Any, Dict[str, Any]]:
    """Build a dictionary mapping each record's unique id to the record itself."""
    return {record[id_field]: record for record in records}

if __name__ == "__main__":
    sample_re…
15 0 Open
Dictionaries & sets medium

How to Recursively Remove None Values from Nested Dictionaries in Python

Recursively removes all None values from nested dictionaries and lists while preserving non-None data.

dictionaries recursion data-cleaning
Python
def prune_none(obj):
    if isinstance(obj, dict):
        return {
            k: prune_none(v)
            for k, v in obj.items()
            if v is not None and prune_none(v) is not None
        }
    elif isinstance(obj, list):
        pruned = [prune_none(item) for item in obj]
        pruned = [item for item i…
15 0 Open
Dictionaries & sets easy

How to Remove Banned Words from a Set in Python

Filter a vocabulary set by removing banned words using the .difference() method.

sets set difference filtering
Python
vocabulary = {"apple", "banana", "cherry", "date", "elderberry"}
banned_words = {"banana", "date", "fig"}

# Remove banned words using set difference
allowed_words = vocabulary.difference(banned_words)

print("Original vocabulary:", sorted(vocabulary))
print("Banned words:", sorted(banned_words))
print("Allowed words …
16 0 Open
Dictionaries & sets easy

How to Use Counter for Most Common Elements in Python

This code demonstrates how to find the most frequent elements in a list using Python's Counter class from the collections module.

collections counter frequency
Python
from collections import Counter

def most_common_elements(items, n=1):
    """Return the n most common elements and their counts."""
    counter = Counter(items)
    return counter.most_common(n)

if __name__ == "__main__":
    data = ["apple", "banana", "apple", "orange", "banana", "apple", "grape"]
    print(most_co…
13 0 Open
Dictionaries & sets easy

How to Use MappingProxyType to Create Immutable Dict Views in Python

Create a read-only, immutable view of a dictionary using MappingProxyType from the types module, while the original dict stays mutable.

mappingproxytype dict immutable
Python
from types import MappingProxyType

config = {"debug": True, "port": 8080}

# Create an immutable read-only view of the dict
read_only_config = MappingProxyType(config)

print(f"Read-only value: {read_only_config['debug']}")
print(f"Dict is mapping: {isinstance(read_only_config, dict)}")

# Original dict can still be …
13 0 Open
Dictionaries & sets medium

Traverse Nested Dict Paths Depth-First in Python

Recursively walk a nested dictionary depth-first and yield each full path from root to leaf as lists.

recursion generators nested-dicts
Python
def depth_first_paths(node, path=None):
    if path is None:
        path = []
    
    if not isinstance(node, dict):
        yield path + [node]
        return
    
    for key, value in node.items():
        new_path = path + [key]
        if isinstance(value, dict):
            yield from depth_first_paths(value, …
13 0 Open

Browse by section

Each section groups closely related Python snippets.

Dictionaries & sets — Python code examples

What you will find here

This page collects dictionaries & sets snippets — short, copy-ready Python you can paste into our free online IDE and run without installing anything. Each sample includes a plain-English explanation and the full source code.

Samples vs tutorials and challenges

Samples are quick reference — one concept per page. For step-by-step teaching, use our Python tutorials. To test yourself, try quizzes or coding challenges. Clean up style with the Python formatter.