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How to Check Data Type and Inspect Dictionaries and Sets in Python
Inspect dictionaries and sets by printing their contents, types, and sizes using a small helper function.
def check_data(data):
"""Helper to inspect dictionaries and sets."""
if isinstance(data, dict):
print(f"Dictionary with {len(data)} keys")
for key, value in data.items():
print(f" {key}: {value} ({type(value).__name__})")
elif isinstance(data, set):
print(f"Set with {le…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.
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…How to Count Co-occurrence Pairs in Python with Nested Dictionaries
This code counts how often any two items appear together in the same group, using a nested defaultdict keyed by item pairs.
from itertools import combinations
from collections import defaultdict
def count_cooccurrences(items_per_group):
cooccurrence = defaultdict(lambda: defaultdict(int))
for group in items_per_group:
for a, b in combinations(sorted(group), 2):
cooccurrence[a][b] += 1
cooccurrence[b…How to Count Elements and Find Duplicates in a Python List
Count occurrences of each element in a list, extract unique values, and identify duplicates using Python dictionaries and sets.
def analyze_counts(data):
"""Count elements, return unique values, and find duplicates."""
# Count occurrences using a dictionary
counts = {}
for item in data:
counts[item] = counts.get(item, 0) + 1
# Alternative compact approach with set
unique_items = set(data)
# Fi…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.
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…How to Count Word Frequencies in Python
Count how often each word appears in a string and list the unique words using Python dictionaries and sets.
def text_processor(text):
words = text.lower().split()
word_count = {}
for word in words:
word_count[word] = word_count.get(word, 0) + 1
unique_words = set(words)
return word_count, unique_words
if __name__ == "__main__":
sample_text = "The quick brown fox jumps over the lazy dog and t…How to Count Words and Find Common Words in Python with Dictionaries and Sets
Build a simple text processor that counts unique words with dictionaries and finds common words across text halves using sets.
def process_text(text):
"""Process text: count unique words with counts, find common words."""
words = text.lower().replace(",", "").replace(".", "").split()
word_counts = {}
for word in words:
word_counts[word] = word_counts.get(word, 0) + 1
total_words = len(words)
unique_wo…How to Diff Two Dicts in Python: Added, Removed, and Changed Keys
Compare two dictionaries and report added, removed, and changed keys using Python's set operations on dict keys.
def diff_dicts(old: dict, new: dict) -> dict:
"""Compare two dicts and report added, removed, and changed keys."""
added = {k: new[k] for k in new.keys() - old.keys()}
removed = {k: old[k] for k in old.keys() - new.keys()}
common_keys = old.keys() & new.keys()
changed = {k: (old[k], new[k]) for k …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.
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…How to Filter a List of Dictionaries by Category in Python
Filter a list of dictionaries to include only records whose category is in an allowed set.
def filter_data(records, categories):
"""Return only records whose category is in the allowed set."""
allowed = set(categories)
filtered = []
for record in records:
if record["category"] in allowed:
filtered.append(record)
return filtered
if __name__ == "__main__":
data = …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 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 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 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)
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