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How to Group Data by Category in Python
Group a list of (category, value) tuples into a dictionary of lists using the setdefault method.
def group_by_category(data):
"""Group list of (category, value) tuples into dictionaries of lists."""
groups = {}
for category, value in data:
groups.setdefault(category, []).append(value)
return groups
if __name__ == "__main__":
items = [
("fruit", "apple"),
("veg", "carro…How to Process Lines of Text in Python
Strip whitespace, split a multi-line string, count words per line, and print structured summaries using basic string methods and loops.
text = """ Python is great!
Coding is fun.
Python skills help you grow. """
lines = text.strip().splitlines()
line_count = len(lines)
processed = []
for line in lines:
stripped = line.strip()
word_count = len(stripped.split())
processed.append({
"original": line,
"stripped": stripp…How to Build an Error Code Enum in Python
Define an API error code enum with descriptions and build structured error payloads for HTTP responses.
from enum import Enum
class APIErrorCode(Enum):
SUCCESS = 0
BAD_REQUEST = 400
UNAUTHORIZED = 401
FORBIDDEN = 403
NOT_FOUND = 404
CONFLICT = 409
INTERNAL_ERROR = 500
def describe_error(code):
descriptions = {
APIErrorCode.SUCCESS: "Request completed successfully",
APIE…Use pprint for Nested Structure Debug Output in Python
Pretty-print nested dictionaries and lists with pprint for readable, organized debug output.
from pprint import pprint
def build_nested_structure():
"""Create a sample nested data structure for demonstration."""
return {
"project": "DataPipeline",
"config": {
"inputs": ["raw_1.json", "raw_2.json"],
"processing": {
"steps": ["clean", "transform",…Compare Two Folder Structures and Find Differences in Python
Walks two directories using os.walk, builds sets of relative paths, and prints items that exist in only one folder.
import os
def compare_folders(path1, path2):
"""
Compare the file/folder structure of two directories and print differences.
"""
def get_structure(root):
structure = set()
for dirpath, dirnames, filenames in os.walk(root):
rel_path = os.path.relpath(dirpath, root)
…Convert File Data to a Dictionary in Python
This function scans a directory and converts each file's metadata (name, size, extension) into a structured dictionary for easy access.
from pathlib import Path
def convert_files_data(directory: str) -> dict:
data = {}
base = Path(directory)
if not base.exists():
return data
for file in base.iterdir():
if file.is_file():
data[file.name] = {
"size": file.stat().st_size,
"exten…How to Load a YAML Subset in Python Without PyYAML
Parse a flat, key-value YAML file with the Python standard library (re and pathlib), handling comments, quotes, and inline comments while skipping nested structures.
import re
from pathlib import Path
def load_yaml_subset(path):
"""Load a flat YAML file (key: value) without external dependencies."""
data = {}
with open(path, 'r', encoding='utf-8') as f:
for line in f:
# Skip empty lines and comments
line = line.strip()
if no…How to Parse JSON, TXT, and CSV Files in Python
This code provides simple functions to read and parse JSON, text, and CSV files using Python's standard library, returning native data structures.
import json
from pathlib import Path
def parse_json_file(filepath):
"""Read and parse a JSON file, returning its contents."""
path = Path(filepath)
with path.open('r', encoding='utf-8') as f:
return json.load(f)
def parse_txt_lines(filepath):
"""Read a text file and return non-empty stripped …How to Write Simple XML Documents with ElementTree in Python
Create well-structured XML documents in memory using Python's built-in ElementTree module, complete with nested elements, attributes, and text content.
import xml.etree.ElementTree as ET
def create_xml_document():
# Create root element
root = ET.Element("catalog")
# Create a book element with attributes and children
book1 = ET.SubElement(root, "book", id="bk101")
ET.SubElement(book1, "author").text = "Gambardella, Matthew"
ET.SubElement(…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 Create a Dict from Two Parallel Lists in Python (zip)
Build a dictionary by pairing elements from two parallel lists using Python's built-in zip function and dict constructor.
keys = ["name", "age", "city"]
values = ["Alice", 30, "New York"]
result = dict(zip(keys, values))
print(result)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 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 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…Graph Class with Adjacency Dict in Python
Build an undirected graph class using a dictionary of adjacency lists with methods to add vertices, edges, remove edges, and query neighbors.
class Graph:
def __init__(self):
self.adjacency = {}
def add_vertex(self, vertex):
if vertex not in self.adjacency:
self.adjacency[vertex] = []
def add_edge(self, u, v):
self.add_vertex(u)
self.add_vertex(v)
self.adjacency[u].append(v)
self.adja…How to Build a Class Method Alternative Constructor from Dict in Python
Use a classmethod alternative constructor to build a Book instance from a dictionary with sensible defaults.
class Book:
def __init__(self, title, author, pages):
self.title = title
self.author = author
self.pages = pages
@classmethod
def from_dict(cls, data):
"""Alternative constructor that builds a Book from a dictionary."""
return cls(
title=data["title"],
…How to Build a Fluent Interface with the Builder Pattern in Python
Learn to implement a fluent builder pattern in Python by chaining methods that return self, enabling readable object construction.
class Pizza:
def __init__(self):
self.size = None
self.toppings = []
self.crust = None
def set_size(self, size):
self.size = size
return self
def add_topping(self, topping):
self.toppings.append(topping)
return self
def set_crust(self, crust):
…How to Implement a Queue Class in Python Using deque
Build a FIFO queue class in Python backed by the collections.deque container with enqueue, dequeue, peek, and size methods.
from collections import deque
class Queue:
def __init__(self):
self._items = deque()
def enqueue(self, item):
self._items.append(item)
def dequeue(self):
if self.is_empty():
raise IndexError("dequeue from empty queue")
return self._items.popleft()
…How to Implement a Stack Class in Python
A complete Stack class implemented with a Python list, featuring push, pop, peek, is_empty, size, and a readable string representation.
class Stack:
def __init__(self):
self._items = []
def push(self, item):
"""Add an item to the top of the stack."""
self._items.append(item)
def pop(self):
"""Remove and return the top item. Raises IndexError if empty."""
if self.is_empty():
raise IndexE…How to Build a Coordinate Grid with Nested Loops in Python
Generate a 2D list of (row, col) coordinate pairs using nested loops and return the grid structure.
def build_coordinate_grid(rows, cols):
"""Build a 2D grid of (row, col) coordinates using nested loops."""
grid = []
for r in range(rows):
row = []
for c in range(cols):
row.append((r, c))
grid.append(row)
return grid
if __name__ == "__main__":
grid = build_coo…How to Heapify a List into a Min Heap with heapq in Python
Convert any list into a valid min heap in-place using Python's heapq.heapify(), then pop the smallest element to verify heap order.
import heapq
data = [5, 3, 8, 1, 9, 2, 7, 4, 6]
print("Original list:", data)
heapq.heapify(data)
print("Min heap:", data)
popped = heapq.heappop(data)
print("Smallest element popped:", popped)
print("Heap after pop:", data)Implement Queue Using Two Stacks in Python
Python class that implements a FIFO queue using two stacks, with enqueue, dequeue, peek, and emptiness checks.
class QueueUsingStacks:
def __init__(self):
self.stack_in = []
self.stack_out = []
def enqueue(self, value):
self.stack_in.append(value)
def dequeue(self):
if not self.stack_out:
while self.stack_in:
self.stack_out.append(self.stack_in.pop())
…Implement a Stack Using List Push Pop in Python
A minimal Stack class built on a Python list, with push, pop, peek, is_empty, and size methods, including empty-stack guards.
class Stack:
def __init__(self):
self.items = []
def push(self, item):
self.items.append(item)
def pop(self):
if self.is_empty():
raise IndexError("pop from empty stack")
return self.items.pop()
def peek(self):
if self.is_empty():
raise…Browse by section
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