Dictionaries & sets
Key–value maps, uniqueness, counting, grouping, and fast lookups.
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 Normalize Data with Dictionaries and Sets in Python
Normalize dictionary entries to a fixed set of keys and extract unique values using sets in Python.
def normalize_entry(entry: dict, valid_keys: set) -> dict:
result = {}
for key in valid_keys:
result[key] = entry.get(key, "")
return result
def unique_values(entries: list[dict], key: str) -> set:
return {entry.get(key) for entry in entries if entry.get(key) is not None}
if __name__ == "__…How to Parse Data Into Dictionaries and Sets in Python
Parses raw student strings into a dictionary of lists and finds unique courses using a set.
from collections import defaultdict
def parse_students(raw_data):
"""Parse raw student strings into a dictionary of lists."""
parsed = defaultdict(list)
for entry in raw_data:
name, _, course = entry.partition(":")
parsed[course.strip()].append(name.strip())
return dict(parsed)
def fi…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.
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…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 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 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 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 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 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…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…Unflatten Dot Keys to Nested Dict in Python
Convert a flat dictionary with dot-separated keys into a nested dictionary structure using recursive setdefault loops.
def unflatten_dot_keys(flat_dict):
result = {}
for flat_key, value in flat_dict.items():
parts = flat_key.split(".")
current = result
for part in parts[:-1]:
current = current.setdefault(part, {})
current[parts[-1]] = value
return result
if __name__ == "__main_…Validate dictionary data with sets in Python
Validate a dictionary against required keys and allowed value sets, returning a list of validation errors.
def validate_data(data, required_keys, allowed_values=None):
"""
Validate a dictionary against required keys and optional allowed value sets.
Returns a list of validation errors (empty list if valid).
"""
errors = []
# Check for missing required keys
missing = set(required_keys) - set(…Browse by section
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