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Build adjacency dict graph from edges in Python
Convert a list of edges into an undirected adjacency dictionary, mapping each node to its neighbors, with sorted output.
def build_adjacency_dict(edges):
graph = {}
for u, v in edges:
if u not in graph:
graph[u] = []
if v not in graph:
graph[v] = []
graph[u].append(v)
graph[v].append(u)
return graph
if __name__ == "__main__":
edges = [(1, 2), (2, 3), (3, 4), (4, 1)…Build an OrderedDict insertion order demo in Python 3
Demonstrate how OrderedDict preserves insertion order, how updates keep position, and how re-insertion moves keys to the end.
from collections import OrderedDict
def demo_ordered_dict():
# Create an OrderedDict and insert items in a specific order
ordered = OrderedDict()
ordered['banana'] = 3
ordered['apple'] = 2
ordered['cherry'] = 5
ordered['date'] = 1
print("Insertion order preserved:")
for key, value in …Check Invertible Mapping for Duplicate Values in Python
Detect duplicate values among (key, value) pairs to ensure the mapping is invertible, using a dictionary for O(1) lookups.
def invertible_after_dedup(pairs):
"""
Check whether a set of (key, value) pairs is invertible,
i.e., no duplicate values exist for different keys.
"""
seen = {}
for key, value in pairs:
if value in seen and seen[value] != key:
return False, f"Duplicate value '{value}' for k…Compare Two Dictionaries in Python
Compare two dictionaries by finding common keys, unique keys, and value differences using Python's set operations.
def compare_data(dict1, dict2):
"""Compare two dictionaries and summarize similarities/differences."""
keys1 = set(dict1.keys())
keys2 = set(dict2.keys())
common_keys = keys1 & keys2
only_in_first = keys1 - keys2
only_in_second = keys2 - keys1
print(f"Common keys ({len(common_keys…Convert Lists and Dictionaries to Sets in Python
Convert lists of pairs into dictionaries and lists or dictionaries into sets using simple helper functions.
def convert_to_dict(data):
"""Convert list of tuples or lists into a dictionary."""
return dict(data)
def convert_to_set(data):
"""Convert list or dictionary into a set of its keys/values."""
if isinstance(data, dict):
return set(data.keys())
return set(data)
def convert_collection(data…Convert namedtuple to dict with asdict in Python
Convert a namedtuple instance into an ordinary dictionary using the asdict function from the collections module's namedtuple utility.
from collections import namedtuple, asdict
def main():
# Define a namedtuple for a person
Person = namedtuple("Person", ["name", "age", "city"])
person = Person(name="Alice", age=30, city="New York")
# Convert namedtuple to dict
person_dict = asdict(person)
print("Original namedtuple…Count Word Frequency in Python with dict
Count how often each word appears in a text using Python's collections.Counter and regular expressions.
from collections import Counter
import re
def count_word_frequency(text):
"""Count frequency of each word in text (case-insensitive)."""
words = re.findall(r"\b\w+\b", text.lower())
return dict(Counter(words))
if __name__ == "__main__":
sample_text = "The quick brown fox jumps over the lazy dog. The …Count Words in Python with Dictionaries and Sets
Text analysis example that counts total words, finds unique words with a set, and tallies character frequencies with a dictionary.
def analyze_text(text: str) -> dict:
"""Count words, find unique words, and show common characters."""
words = text.lower().split()
word_count = len(words)
unique_words = set(words)
char_counts = {}
for word in words:
for char in word:
if char.isalpha():
…Count word frequency in Python with dict and Counter
Count how often each word appears in a string using Counter, converted to a plain dict, and print results alphabetically.
from collections import Counter
import re
def count_word_frequency(text):
words = re.findall(r'\b\w+\b', text.lower())
return dict(Counter(words))
if __name__ == "__main__":
sample_text = "The quick brown fox jumps over the lazy dog. The dog barks, and the fox runs."
frequency = count_word_frequency(…Filter Dictionary Keys by Prefix in Python
Use a dict comprehension to build a new dictionary containing only keys that start with a given prefix.
def filter_dict_keys(data, prefix="temp_"):
"""
Filter a dictionary by keeping only keys that start with a given prefix.
Uses a dict comprehension to build a new dictionary.
"""
if not isinstance(data, dict):
raise ValueError("data must be a dictionary")
return {key: value for key, valu…Find All Leaf Paths in a Nested Dict in Python
Recursively traverse a nested dictionary and yield every leaf path as a list of keys, including paths to empty dictionaries.
def find_leaf_paths(data, path=None):
if path is None:
path = []
if not isinstance(data, dict) or not data:
yield path
return
for key, value in data.items():
yield from find_leaf_paths(value, path + [key])
if __name__ == "__main__":
nested = {
"a": 1,
…Flatten a Nested Dict to Dot Notation Keys in Python
Recursively flatten a nested dictionary into a flat dictionary with dot-separated keys using a small recursive function.
def flatten_dict(nested, parent_key='', sep='.'):
items = {}
for key, value in nested.items():
new_key = f"{parent_key}{sep}{key}" if parent_key else key
if isinstance(value, dict):
items.update(flatten_dict(value, new_key, sep))
else:
items[new_key] = value
…Get Nested Dict Value with Default in Python
Access values deep inside a nested dictionary using a dotted path string, returning a default when any key is missing.
def get_nested(d, path, default=None):
"""Walk a nested dict along a dotted path, returning default if missing."""
current = d
for key in path.split("."):
if isinstance(current, dict) and key in current:
current = current[key]
else:
return default
return current
…Group Data by Key in Python with Dictionaries and Sets
Group items into a dictionary of sets using a key function, a beginner-friendly pattern for organizing data by categories.
def group_data(items, key_func):
"""Group items into a dictionary of sets based on a key function."""
grouped = {}
for item in items:
key = key_func(item)
if key not in grouped:
grouped[key] = set()
grouped[key].add(item)
return grouped
if __name__ == "__main__":
…How to Aggregate Order Data with Sets and Dictionaries in Python
Combine sets and dictionaries to find unique products and total quantities from a list of orders in Python.
def find_unique_products(orders):
"""Return set of all products ordered across multiple orders."""
all_products = set()
for order in orders:
all_products.update(order.get("items", []))
return all_products
def product_summary(orders):
"""Build a dictionary mapping each product to its total…How to Build a Gradebook with Python Dictionaries and Sets
Create a gradebook dictionary from student names and grades, find top students with a set comprehension, and add extra credit with a dict comprehension.
def build_gradebook(students, grades):
"""Create a dictionary mapping student names to their grades."""
return dict(zip(students, grades))
def find_top_students(gradebook, passing_grade=60):
"""Return a set of students with grades at or above the passing grade."""
return {name for name, grade in grad…How to Build a TTL Cache Dict in Python
Create a dictionary subclass that automatically expires keys after a fixed time-to-live using timestamps.
import time
class TTLDict(dict):
def __init__(self, ttl, *args, **kwargs):
self.ttl = ttl
self._expires = {}
super().__init__(*args, **kwargs)
def __setitem__(self, key, value):
super().__setitem__(key, value)
self._expires[key] = time.time() + self.ttl
def __geti…How to Build a Two-Way Dictionary in Python
Implement a BiDict class that supports both forward key-to-value and reverse value-to-key lookups with a simple add, delete, and update API.
class BiDict:
def __init__(self, data=None):
self.forward = {}
self.backward = {}
if data:
self.update(data)
def update(self, data):
for key, value in data.items():
self[key] = value
def __setitem__(self, key, value):
self.forward[key] = val…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 Convert a Counter to a Plain Dict with Sorted Items in Python
This code converts a collections.Counter into a regular dictionary with items sorted by key, useful for stable, readable output.
from collections import Counter
def counter_to_sorted_dict(counter):
"""Convert a Counter to a plain dict with sorted items."""
return dict(sorted(counter.items()))
if __name__ == "__main__":
# Example usage
data = Counter(['apple', 'banana', 'apple', 'cherry', 'banana', 'date', 'apple'])
print("…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…Browse by section
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