Dictionaries & sets
Key–value maps, uniqueness, counting, grouping, and fast lookups.
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 List of Dictionaries by Key in Python
Sort a list of dictionaries by various keys (grade, age, name) using lambda, itemgetter, and extract unique sorted names into a set.
from operator import itemgetter
# Sample data: a list of dictionaries representing students
students = [
{"name": "Alice", "grade": 88, "age": 23},
{"name": "Bob", "grade": 95, "age": 22},
{"name": "Charlie", "grade": 78, "age": 24},
{"name": "Diana", "grade": 92, "age": 21}
]
# Sort by grade (descen…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)}")How to Use defaultdict(list) to Group Words by First Letter in Python
This code groups a list of words by their first letter using a defaultdict with a list factory, then prints each group sorted by initial.
from collections import defaultdict
def group_by_initial(words):
groups = defaultdict(list)
for word in words:
groups[word[0].upper()].append(word)
return dict(groups)
if __name__ == "__main__":
words = ["apple", "banana", "apricot", "blueberry", "cherry"]
result = group_by_initial(words)…How to Use defaultdict(set) in Python to Group Unique Values
Group key-value pairs into a dictionary of sets, automatically creating a new set for each key using defaultdict.
from collections import defaultdict
def track_groups(pairs):
groups = defaultdict(set)
for key, value in pairs:
groups[key].add(value)
return groups
if __name__ == "__main__":
data = [
("fruit", "apple"),
("fruit", "banana"),
("fruit", "apple"),
("veg", "carrot…How to Validate JSON Types per Key in Python
Load a JSON object and validate the type of each key against an expected schema, reporting missing or mismatched fields.
import json
from typing import Any, Dict, Type
def validate_json_types(data: Dict[str, Any], schema: Dict[str, Type]) -> Dict[str, str]:
"""Validate that each key in data matches the expected type in schema."""
errors = {}
for key, expected_type in schema.items():
if key not in data:
e…How to Validate Required Dict Keys in Python
Check whether a dictionary contains all required keys and return the list of missing ones using a simple list comprehension.
def find_missing_keys(data: dict, required_keys: list) -> list:
"""Return a list of required keys that are missing from the dictionary."""
return [key for key in required_keys if key not in data]
if __name__ == "__main__":
user_data = {
"name": "Alice",
"email": "alice@example.com",
…How to Validate Text and Count Words in Python
Count word frequencies, find unique and repeated words in a text using Python dictionaries and sets for beginner text validation.
def validate_text(text):
words = text.lower().split()
word_counts = {}
for word in words:
cleaned = word.strip('.,!?;:"\'')
if cleaned:
word_counts[cleaned] = word_counts.get(cleaned, 0) + 1
unique_words = set(word_counts.keys())
repeated_words = {word for word…How to convert string values to int or float in Python dicts
Recursively convert string values in nested dicts and lists to ints or floats when possible, leaving other strings untouched.
def coerce_str_values(data):
"""Recursively convert string values that look like ints or floats."""
if isinstance(data, dict):
return {key: coerce_str_values(val) for key, val in data.items()}
elif isinstance(data, list):
return [coerce_str_values(item) for item in data]
elif isinstance…How to count words and find unique words in Python
Build a beginner-friendly text processor that counts word frequencies, finds unique words, and identifies words with vowels using dictionaries and sets.
def text_processor(text):
words = text.lower().replace(",", "").replace(".", "").split()
word_count = {}
for word in words:
word_count[word] = word_count.get(word, 0) + 1
unique_words = set(words)
vowels = set("aeiou")
words_with_vowels = {word for word in unique_words if vowe…How to merge dictionaries and sets in Python
Merges multiple dictionaries with the ** unpacking operator and combines sets using union operations into a single structure.
def merge_dictionaries_and_sets(school_dict, teacher_dict, course_dict, student_sets):
"""
Merges multiple dictionaries and sets into a single combined structure.
Demonstrates dict unpacking and set union operations.
"""
# Merge all dictionaries using the unpacking operator (Python 3.9+)
merged…How to swap dict keys and values in Python when values are unique
Swap dict keys and values using a dict comprehension, with a guard that raises an error when values repeat.
def swap_dict_keys_values(d):
"""Swap keys and values in a dict, assuming values are unique."""
if len(set(d.values())) != len(d.values()):
raise ValueError("Values must be unique to swap keys and values")
return {v: k for k, v in d.items()}
if __name__ == "__main__":
original = {"a": 1, "b": …Multiset with Counter update and elements in Python
Demonstrates using collections.Counter as a multiset: updating counts with update() and iterating elements() to get repeated items.
from collections import Counter
multiset = Counter(['apple', 'banana', 'apple'])
multiset.update(['banana', 'cherry', 'apple'])
print("Elements after update:", sorted(multiset.elements()))
print("Counts:", dict(multiset))
print("Most common:", multiset.most_common(2))Parse Env Vars into Typed Dict in Python
Convert a list of environment variable names into a dictionary with automatically detected types (bool, int, float, or string), defaulting missing vars to None.
import os
from typing import Any, Dict
def parse_env_vars(env_names: list[str], env: Dict[str, str] | None = None) -> Dict[str, Any]:
"""Parse a list of environment variable names into a typed dict.
Each variable is parsed as:
- bool: "true"/"false" (case-insensitive)
- int: if it can be converted t…Serialize Python dict to JSON with custom default for datetime
Convert a Python dict containing datetime and set objects into JSON by providing a custom default serializer.
import json
from datetime import datetime
def custom_serializer(obj):
if isinstance(obj, datetime):
return obj.isoformat()
if isinstance(obj, set):
return list(obj)
return str(obj)
data = {
"name": "Alice",
"created_at": datetime(2024, 3, 15, 10, 30, 45),
"tags": {"python", "j…Text Processor with Dictionaries and Sets in Python
Build a simple text processor that counts word frequencies with a dictionary and tracks unique words with a set.
def analyze_text(text):
words = text.lower().split()
word_freq = {}
unique_words = set()
for word in words:
clean_word = word.strip('.,!?;:')
if clean_word:
word_freq[clean_word] = word_freq.get(clean_word, 0) + 1
unique_words.add(clean_word)
return…Browse by section
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Dictionaries & sets — Python code examples
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