Dictionaries & sets
Key–value maps, uniqueness, counting, grouping, and fast lookups.
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 Parse Query String to Dict with Duplicate Keys in Python
Convert a URL query string into a Python dictionary, merging duplicate keys into lists while keeping single values as scalars.
from urllib.parse import parse_qs
def parse_query_to_dict(query_string):
parsed = parse_qs(query_string, keep_blank_values=True)
return {key: values if len(values) > 1 else values[0] for key, values in parsed.items()}
if __name__ == "__main__":
query = "name=John&name=Jane&age=30&city=&city=Paris&empty…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 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 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 Serialize a Dictionary to a Query String in Python
Convert a Python dictionary into a URL-encoded query string using the standard library's urllib.parse.urlencode function.
import urllib.parse
def dict_to_query_string(params):
"""Serialize a dictionary to a URL query string."""
return urllib.parse.urlencode(params)
if __name__ == "__main__":
data = {
"name": "Alice Johnson",
"age": 30,
"city": "New York",
"interests": ["coding", "hiking"]
…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 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…Browse by section
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