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How to Parse Function Signatures in Python with inspect
Extract a function's parameter names, kinds, defaults, annotations, and return type using Python's built-in inspect module.
import inspect
def example_function(a: int, b: str = "default", *args, c: float = 1.5, **kwargs) -> bool:
"""An example function with various parameter types."""
return True
def parse_signature(func):
"""Parse a function's signature using the inspect module."""
sig = inspect.signature(func)
param…Create a Local File Versioning System Using Pure Python
Track file changes locally by copying versions with SHA-256 hashes and JSON metadata using only the Python standard library.
import os
import shutil
import hashlib
import json
import time
from pathlib import Path
class LocalFileVersioning:
def __init__(self, target_dir="versioned_files", versions_dir="versions"):
self.target_dir = Path(target_dir)
self.versions_dir = Path(versions_dir)
self.metadata_file = self.…Create a Python Tool That Generates Professional Excel Dashboards
Generate a professional sales dashboard in an Excel workbook with styled headers, a bar chart, and formatted number cells using the openpyxl library.
import openpyxl
from openpyxl.chart import BarChart, Reference
from openpyxl.styles import Font, PatternFill, Alignment, Border, Side
from openpyxl.utils import get_column_letter
def create_sales_dashboard(workbook_path: str) -> None:
"""Generate a professional sales dashboard in an Excel workbook."""
wb = op…How to Generate an Inventory Report of All Files in Python
Walk a directory tree, collect metadata for every file, and write a CSV inventory report using Python's os, pathlib, and csv modules.
import os
import csv
from pathlib import Path
from datetime import datetime
def generate_inventory_report(root_dir: str = "/", output_file: str = "inventory_report.csv"):
headers = ["File Path", "Size (bytes)", "Last Modified", "File Type"]
rows = []
start_time = datetime.now()
for dirpath, dirna…Read Parquet-Like Columnar CSV Chunks in Python
A Python generator that reads a CSV file column-by-column, yielding dictionary chunks where each key points to a list of values—mirroring how Parquet stores data columnar.
```python
import csv
from pathlib import Path
from typing import Iterator, List
def read_parquet_like_columnar(csv_path: str, column_names: List[str], chunk_size: int = 2) -> Iterator[dict]:
"""Read CSV data in columnar chunks, similar to how parquet stores columns."""
csv_file = Path(csv_path)
with csv_f…Scrape HTML Tables and Convert Them to CSV Using Beautiful Soup in Python
Scrape a Wikipedia table with Beautiful Soup and write the data to a CSV file using the csv module.
import requests
from bs4 import BeautifulSoup
import csv
url = "https://en.wikipedia.org/wiki/List_of_countries_by_GDP_(nominal)"
response = requests.get(url)
soup = BeautifulSoup(response.text, 'html.parser')
tables = soup.find_all('table', {'class': 'wikitable'})
if tables:
target_table = tables[2]
rows =…Build a Case-Insensitive Dict with a Wrapper Class in Python
Create a custom dict subclass that treats keys as case-insensitive by normalizing them to lowercase, with a full set of common dict methods.
class CaseInsensitiveDict:
def __init__(self, data=None):
self._data = {}
if data:
self.update(data)
def __setitem__(self, key, value):
self._data[str(key).lower()] = value
def __getitem__(self, key):
return self._data[str(key).lower()]
def __delitem__(sel…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,
…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 Implement Disjoint Set Union Find in Python
Implement a Disjoint Set Union-Find data structure using a Python dictionary for parent tracking, with path compression and connectivity checks.
class DisjointSet:
def __init__(self):
self.parent = {}
def find(self, x):
# Path compression
if self.parent[x] != x:
self.parent[x] = self.find(self.parent[x])
return self.parent[x]
def union(self, x, y):
# Initialize if not present
if x not in…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…LRU Cache with OrderedDict in Python
Implement an LRU cache using collections.OrderedDict to track insertion order and evict the least-recently-used item when capacity is exceeded.
from collections import OrderedDict
class LRUCache:
def __init__(self, capacity):
self.capacity = capacity
self.cache = OrderedDict()
def get(self, key):
if key not in self.cache:
return -1
self.cache.move_to_end(key)
return self.cache[key]
def put(sel…How to Build a Linked List Node Class in Python
Create a Node class and a LinkedList class with insert, remove, and display methods to manage a singly linked list.
class Node:
def __init__(self, data):
self.data = data
self.next = None
class LinkedList:
def __init__(self):
self.head = None
def insert(self, data):
new_node = Node(data)
if not self.head:
self.head = new_node
else:
current = self.…How to Create a Data Splitter Class in Python
This code defines a DataSplitter class that splits data by index, into chunks, or by a predicate, demonstrating OOP principles in Python.
class DataSplitter:
def __init__(self, data):
self.data = list(data)
def split_by_index(self, index):
return self.data[:index], self.data[index:]
def split_into_chunks(self, chunk_size):
return [self.data[i:i + chunk_size] for i in range(0, len(self.data), chunk_size)]
…How to Use __getstate__ and __setstate__ for Pickle in Python
Customize Python object serialization with the pickle __getstate__ and __setstate__ hooks to control exactly what data is stored and how it is restored.
import pickle
class Temperature:
def __init__(self, celsius):
self.celsius = celsius
def __getstate__(self):
"""Customize what gets pickled."""
state = self.__dict__.copy()
# Convert to Fahrenheit for storage (simulate transformation)
state['fahrenheit'] = (self.celsiu…Unit of Work Pattern: Track Changes, Commit, and Rollback in Python
This code defines a UnitOfWork class that tracks operations (add) and supports commit to apply changes and rollback to revert them, using a dataclass-based logger.
from dataclasses import dataclass, field
from typing import Any, Callable, List, Tuple
@dataclass
class UnitOfWork:
log: List[Tuple[str, Callable, tuple, dict]] = field(default_factory=list)
def track(self, operation: str, fn: Callable, *args, **kwargs):
self.log.append((operation, fn, args, kwargs)…How to Find the n Smallest Items in a Large List with heapq in Python
This code demonstrates how to efficiently extract the n smallest items from a large list using Python's heapq module and a manual max-heap approach.
import heapq
def n_smallest_iterable(data, n):
"""Return the n smallest items without loading the whole list."""
if n <= 0:
return []
return heapq.nsmallest(n, data)
def n_smallest_manual(data, n):
"""Return the n smallest using a heap, O(n log k) time."""
if n <= 0:
return []
…Implement Insert Delete GetRandom O(1) in Python
Build a RandomizedSet class that supports insert, delete, and get_random in average O(1) time using a list and a dictionary mapping values to indices.
import random
class RandomizedSet:
def __init__(self):
self.values = []
self.index_map = {}
def insert(self, val):
if val in self.index_map:
return False
self.index_map[val] = len(self.values)
self.values.append(val)
return True
def delete(self…Build a Generator Pipeline in Python: Filter Then Map
Create a lazy data pipeline by chaining generator functions that read, filter, map, and write data step by step.
def read_data():
return ["a", "bb", "ccc", "dd", "eeeee", "f"]
def filter_short(words):
return (word for word in words if len(word) >= 2)
def map_to_upper(words):
return (word.upper() for word in words)
def write_data(words):
for word in words:
print(word)
if __name__ == "__main__":
…How to Build a Data Helper for LLM Prompts in Python
A beginner-friendly helper class that flattens nested dictionaries, formats prompt templates, and safely parses JSON for AI/LLM pipelines.
import json
from typing import Any, Dict, List, Optional
class DataHelper:
"""Simple helper class for working with data in AI/LLM pipelines."""
def __init__(self, data: Optional[Dict[str, Any]] = None) -> None:
self.data = data or {}
def flatten(self, prefix: str = "") -> Dict[str, Any]…Track GitHub Repository Growth in Python
A Python dashboard that fetches and displays GitHub repository statistics including stars, forks, creation date, and recent star activity using the GitHub API.
import requests
import json
from datetime import datetime, timedelta
def track_repo_growth(owner, repo):
url = f"https://api.github.com/repos/{owner}/{repo}"
headers = {"Accept": "application/vnd.github.v3+json"}
response = requests.get(url, headers=headers)
data = response.json()
name = data…Automatically Download the Latest Software Release from GitHub with Python
Use the GitHub API to fetch the latest release metadata and download the first asset (binary or archive) to a local directory.
import requests
import sys
from pathlib import Path
def download_latest_release(owner: str, repo: str, output_dir: str = ".") -> None:
"""Download the latest release asset from a GitHub repository."""
url = f"https://api.github.com/repos/{owner}/{repo}/releases/latest"
response = requests.get(url)
res…Build a Python Utility That Verifies Backup Integrity Automatically
Automatically compute and verify SHA-256 checksums of backup files using a JSON manifest to detect missing or corrupted data.
import hashlib
import os
import json
def compute_checksum(filepath, algorithm='sha256'):
"""Compute checksum for the given file."""
hash_func = hashlib.new(algorithm)
with open(filepath, 'rb') as f:
for chunk in iter(lambda: f.read(4096), b''):
hash_func.update(chunk)
return hash_f…How to Compare Two GitHub Repositories and Highlight Differences in Python
Fetch metadata from two GitHub repositories using the GitHub API and compare key attributes like stars, forks, license, and language, printing any differences.
import requests
import json
from pathlib import Path
def fetch_repo_data(owner, repo_name):
"""Fetch repository metadata from GitHub API."""
url = f"https://api.github.com/repos/{owner}/{repo_name}"
response = requests.get(url)
response.raise_for_status()
return response.json()
def compare_repos(…Browse by section
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Guide: free Python code samples library
Copy-ready Python snippets for learners and developers
PythonSkillset code samples are short, focused examples organised by topic and difficulty. Every snippet is server-rendered HTML — readable by search engines and easy to copy. Open any sample, read the notes, copy the code, then press Try in editor to run it in the browser with Pyodide.
How to use this library
- Pick a topic section — strings, lists, files, functions, and more
- Open a sample, read How it works, and copy the code block
- Run it in the IDE, tweak values, then take a related quiz or tutorial lesson
Samples vs tutorials and challenges
Samples are quick reference — one concept per page. For step-by-step teaching, use our Python tutorials. To test yourself, try quizzes or coding challenges. Clean up style with the Python formatter.