Dictionaries & sets
Key–value maps, uniqueness, counting, grouping, and fast lookups.
How to Find Keys with Matching Values in Two Dictionaries in Python
Find dictionary keys where both dictionaries have the exact same value by iterating over key-value pairs and comparing them.
def find_matching_values(dict1, dict2):
"""Return list of keys that have the same value in both dicts."""
matches = []
for key, value in dict1.items():
if key in dict2 and dict2[key] == value:
matches.append(key)
return matches
if __name__ == "__main__":
# Example usage
di…How to Find Symmetric Difference Between Two Python Sets
Compute elements unique to each set and build a flag dictionary showing membership across two Python sets.
def symmetric_difference_with_flags(set_a, set_b):
"""Return elements in either set but not both, grouped by which set they came from."""
only_in_a = set_a - set_b
only_in_b = set_b - set_a
print(f"Only in A: {only_in_a}")
print(f"Only in B: {only_in_b}")
print(f"Symmetric difference: {onl…How to Find the Intersection of Permission Sets in Python
This code defines a function that takes a list of permission sets and returns a set containing only the permissions common to all sets, with a short-circuit for empty results.
from typing import Set
def intersect_permissions(permission_sets: list[Set[str]]) -> Set[str]:
"""
Given a list of permission sets, return the common permissions
present in every set.
"""
if not permission_sets:
return set()
common = permission_sets[0]
for perm_set in permissi…How to Group Data by Category in Python with a Split Data Helper
This code groups a list of (category, item) pairs into a dictionary where each key is a category and each value is a list of items belonging to that category.
def split_data(categories):
"""
Group data items into buckets based on a key function.
Returns a dict where keys are bucket names and values are lists of items.
"""
buckets = {}
for category, item in categories:
if category not in buckets:
buckets[category] = []
buck…How to Group a List of Dictionaries by Key in Python
Group a list of dictionaries by a specified key field using dict.setdefault to build a dictionary of lists.
def group_by_key(records, key):
grouped = {}
for record in records:
grouped.setdefault(record[key], []).append(record)
return grouped
if __name__ == "__main__":
data = [
{"name": "Alice", "dept": "engineering"},
{"name": "Bob", "dept": "sales"},
{"name": "Carol", "dept"…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.
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…How to Invert a Dictionary in Python Safely
Swap dictionary keys and values while detecting duplicate values to prevent silent data loss.
def invert_dict_safely(d):
inverted = {}
for key, value in d.items():
if value not in inverted:
inverted[value] = key
else:
raise ValueError(f"Duplicate value '{value}' would cause data loss")
return inverted
if __name__ == "__main__":
sample = {"a": 1, "b": 2,…How to Map Dictionary Values with a Transformation Function in Python
Create a reusable function that applies a transformation to every value in a dictionary and returns a new dict.
def transform_dict_values(d, func):
"""Apply a transformation function to every value in a dictionary."""
return {key: func(value) for key, value in d.items()}
if __name__ == "__main__":
original = {"a": 1, "b": 2, "c": 3}
doubled = transform_dict_values(original, lambda x: x * 2)
print(doubled)
…How to Merge Dictionaries and Find Unique Keys in Python
Merge two dictionaries with update(), then use sets to find all unique keys and the keys shared between both dictionaries.
def merge_and_unique(dict1, dict2):
merged = dict1.copy()
merged.update(dict2)
unique_keys = set(merged.keys())
common_keys = set(dict1.keys()) & set(dict2.keys())
return merged, unique_keys, common_keys
if __name__ == "__main__":
fruits = {"apple": 3, "banana": 5, "orange": 2}
more_fruit…How to Merge Two Dictionaries in Python with the Spread Operator
Merge two Python dictionaries into one new dict using the ** unpacking (spread) operator, with later keys overriding earlier ones.
def merge_two_dicts(dict1: dict, dict2: dict) -> dict:
"""Merge two dictionaries using the spread operator pattern."""
# The ** operator unpacks key-value pairs, later keys overwrite earlier ones
merged = {**dict1, **dict2}
return merged
if __name__ == "__main__":
# Example usage with overlapping…How to Normalize Data in Python with Dictionaries and Sets
Normalize a list of dicts by keeping selected keys, stripping/lowercasing strings, and extracting unique sorted values using set comprehension.
def normalize_data(data, keys):
"""
Normalize a list of dictionaries by keeping only specified keys
and converting values to proper types.
"""
normalized = []
for item in data:
clean_item = {}
for key in keys:
value = item.get(key)
if isinstance(value, st…How to Pickle a Python Dict and Load It Back
Save a dictionary to a binary file with pickle.dump() and reload it with pickle.load(), showing the round trip and type preservation.
import pickle
data = {"name": "Alice", "scores": [87, 92, 95], "active": True}
print("Original dict:", data)
with open("safe_demo.pkl", "wb") as f:
pickle.dump(data, f)
with open("safe_demo.pkl", "rb") as f:
loaded = pickle.load(f)
print("Loaded dict:", loaded)
print("Type:", type(loaded).__name__)
print(…How to Remove Banned Words from a Set in Python
Filter a vocabulary set by removing banned words using the .difference() method.
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 …How to Set Nested Dict Value Creating Missing Keys in Python
Set a value deep inside a nested dictionary, automatically creating any missing intermediate dicts along the path.
def set_nested_value(d, keys, value):
"""
Set a value in a nested dict, creating missing intermediate keys.
Args:
d: The dict to modify
keys: Iterable of keys forming the path (e.g., ['a', 'b', 'c'])
value: The value to set at the final key
"""
current = d
for key i…How to Sort Dictionary Keys Alphabetically in Python
This code returns a list of dictionary keys sorted alphabetically, using a case-insensitive comparison while preserving the original insertion order for keys that are equal.
data = {
"banana": 3,
"apple": 1,
"Cherry": 5,
"date": 2,
"apple": 4,
"Fig": 6,
"banana": 2,
}
def sort_dict_keys_alphabetically(d):
"""Return a list of keys sorted alphabetically (case-insensitive), stable for duplicates."""
return sorted(d.keys(), key=lambda k: k.lower())
if __n…How to Sort a Python Dictionary by Value Descending
Sort dictionary items by their values in descending order and return a new dictionary.
def sort_dict_by_value_desc(d):
return dict(sorted(d.items(), key=lambda item: item[1], reverse=True))
if __name__ == "__main__":
sample = {"apple": 5, "banana": 2, "cherry": 8, "date": 8}
result = sort_dict_by_value_desc(sample)
print(result)How to Subtract Counters in Python for Bag Differences
Use the Counter class's subtraction operator to compute bag differences, removing items and counts that appear in one multiset but not the other.
from collections import Counter
def subtract_counters(bag1, bag2):
"""Return the difference of two Counters (bag1 - bag2)."""
return bag1 - bag2
if __name__ == "__main__":
inventory = Counter(apples=10, bananas=5, oranges=3)
sold = Counter(apples=4, bananas=2, grapes=2)
remaining = subtract_count…How to Transform a List of Dictionaries with Sets in Python
Normalize a list of dict records — cleaning names, extracting unique tags with sets, and building a standardized result.
def transform_data(raw_records):
"""Transform a list of dict records into normalized data with sets for unique values."""
normalized = []
unique_names = set()
all_tags = set()
for record in raw_records:
# Normalize name to lowercase and strip whitespace
name = record.get("name"…How to Use ChainMap for Layered Config Lookup in Python
This code demonstrates using collections.ChainMap to combine multiple dictionaries into a single layered lookup, where earlier maps override later ones.
from collections import ChainMap
defaults = {"theme": "light", "lang": "en", "debug": False}
user = {"lang": "de", "auto_save": True}
runtime = {"debug": True}
config = ChainMap(runtime, user, defaults)
if __name__ == "__main__":
print("theme:", config["theme"])
print("lang:", config["lang"])
print("deb…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.
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…How to Use Dictionaries and Sets in Python for Beginners
Demonstrates Python dictionary operations and set operations with examples, including access, modification, defaults, and set algebra.
def demonstrate_collections():
# Dictionary basics
student = {
"name": "Alice",
"age": 20,
"courses": ["Math", "Physics"]
}
print("Dictionary:", student)
# Access and modify
student["age"] = 21
student["grade"] = "A"
print("Modified:", student)
# Get with d…How to Use Dictionaries and Sets in Python for Beginners
Introduces Python dictionaries and sets with practical examples including creating, modifying, and performing set operations, plus a word-frequency counter.
def demonstrate_dict_sets():
# Create a dictionary with basic info
person = {
"name": "Alice",
"age": 30,
"city": "New York"
}
print("Dictionary:", person)
# Access and modify dictionary values
person["age"] = 31
person["email"] = "alice@example.com"
print("Afte…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.
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 …How to Use a Frozenset as a Dict Key in Python
Demonstrates using an immutable frozenset as a hashable dictionary key, including equality and lookup with differently-ordered elements.
frozen = frozenset({"a", "b", "c"})
mapping = {frozen: "set as hashable key"}
other_frozen = frozenset(["c", "b", "a"])
print(f"Are keys equal? {frozen == other_frozen}")
print(f"Lookup with different order: {mapping[other_frozen]}")
print(f"Hash matches: {hash(frozen) == hash(other_frozen)}")Browse by section
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Dictionaries & sets — Python code examples
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