Python Code
Samples
Copy-ready Python snippets by topic and difficulty — short, focused, and runnable in the browser editor.
Sync only changed files between two folders in Python
This code compares two folders and copies only the new or modified files from source to destination, skipping unchanged ones by comparing SHA-256 hashes.
import hashlib
from pathlib import Path
import shutil
def file_hash(path: Path, chunk_size: int = 8192) -> str:
hasher = hashlib.sha256()
with path.open("rb") as f:
for chunk in iter(lambda: f.read(chunk_size), b""):
hasher.update(chunk)
return hasher.hexdigest()
def sync_files(src: s…Tail last N lines of growing log file in Python
Prints the last n lines of a log file and follows new content appended to it, polling for size changes.
import time
from pathlib import Path
def tail_log(file_path, n=10, poll_interval=1.0, timeout=10):
"""
Print the last n lines and follow new lines appended to a growing log file.
"""
path = Path(file_path)
# Read the last n lines from the current file
with path.open("r", encoding="utf-8") as f…Write CSV file with csv DictWriter in Python
Write a list of dictionaries to a CSV file using Python's csv.DictWriter, including a header row.
import csv
from pathlib import Path
fieldnames = ["name", "city", "age"]
rows = [
{"name": "Alice", "city": "New York", "age": 30},
{"name": "Bob", "city": "Los Angeles", "age": 25},
{"name": "Charlie", "city": "Chicago", "age": 35},
]
path = Path("people.csv")
with path.open("w", newline="") as csvfile:…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(…Parse CSV Data with a Python Class
Encapsulate CSV file loading and column/row access methods in a reusable DataParser class for beginners.
class DataParser:
def __init__(self, file_path):
self.file_path = file_path
self.data = []
def load_data(self):
with open(self.file_path, 'r') as file:
for line in file:
row = line.strip().split(',')
self.data.append(row)
return self.…Simplify a File Path in Python with a Stack
Uses a stack to normalize an absolute Unix path by handling '.', '..', and duplicate slashes.
from pathlib import PurePosixPath
def simplify_path(path: str) -> str:
tokens = path.split('/')
stack = []
for token in tokens:
if not token or token == '.':
continue
if token == '..':
if stack:
stack.pop()
else:
stack.append…Build a lazy generator to read file lines in Python
Create a generator function that yields file lines one at a time, avoiding loading the entire file into memory, and demonstrate its lazy processing.
def lazy_lines(filepath):
"""Yield lines from a file one at a time without loading the whole file into memory."""
with open(filepath, 'r', encoding='utf-8') as file:
for line in file:
yield line.rstrip('\n')
if __name__ == "__main__":
# Create a sample file to demonstrate
sample_c…How to Parse CSV Rows as Generator Dicts in Python
Reads a CSV file and yields each row as a dictionary one at a time using a generator, so the file is processed lazily.
import csv
from pathlib import Path
def csv_to_dicts(filepath):
with open(filepath, mode="r", newline="", encoding="utf-8") as file:
reader = csv.DictReader(file)
for row in reader:
yield row
if __name__ == "__main__":
sample_csv = Path("sample_data.csv")
sample_csv.write_text…Memory efficient map over large file in Python
A generator-based streaming map that processes a large file line by line without loading the whole file into memory.
import sys
def process_lines(file_path):
"""Memory-efficient map over a large file: yields processed lines."""
with open(file_path, 'r') as f:
for line in f:
# Example mapping: strip whitespace and uppercase
yield line.strip().upper()
if __name__ == "__main__":
# Use a sma…How to Log Prompts and Completions as JSONL Audit Files in Python
Read a JSONL file of LLM prompt–completion pairs, compute totals and averages, then write an audit summary with timestamps.
import json
from pathlib import Path
from datetime import datetime
def audit_jsonl(filepath):
logs = []
with open(filepath, encoding="utf-8") as f:
for line in f:
line = line.strip()
if not line:
continue
entry = json.loads(line)
logs.ap…How to Serialize Chat Messages to a JSON File in Python
Writes a list of chat message dicts to a JSON file with metadata like export time and message count.
import json
from pathlib import Path
from datetime import datetime
def serialize_messages(messages, output_path):
data = {
"exported_at": datetime.now().isoformat(),
"count": len(messages),
"messages": messages
}
Path(output_path).write_text(
json.dumps(data, indent=2, ensu…How to parse JSON in Python: A Beginner's Guide with Code Examples
This guide shows you how to parse JSON data in Python step by step, with practical code examples and expected outputs.
import json
from typing import Any, Dict, List, Optional
class DataHelper:
"""Beginner-friendly helper for common AI/LLM data tasks."""
def __init__(self, data: Optional[Dict[str, Any]] = None):
self.data = data or {}
def to_prompt(self, template: str) -> str:
"""Format a prompt…Automatically Clean Temporary Files from Applications Using Python
A Python script that safely deletes temporary files from common application temp directories across Windows, Linux, and macOS, tracking cleaned count and disk space.
import os
import shutil
import tempfile
import platform
def clean_application_temp_files():
"""Delete common temporary file locations safely."""
system = platform.system()
temp_dirs = []
if system == "Windows":
temp_dirs.extend([
os.path.join(os.getenv("LOCALAPPDATA"), "Temp"),
…Automatically Generate Charts from CSV Files with One Command
Read a CSV file with headers, extract the first two numeric columns, and save a matplotlib line chart as a PNG image.
import csv
import sys
from pathlib import Path
import matplotlib.pyplot as plt
def generate_chart(csv_path: str) -> None:
"""Read a CSV file with headers and plot the first two numeric columns."""
data = []
with open(csv_path, 'r', newline='') as f:
reader = csv.reader(f)
headers = next(re…Automatically Log CPU, RAM, and Disk Usage Every Minute in Python
This script logs CPU, RAM, and disk usage to a CSV file every 60 seconds using psutil and Python's standard library.
import psutil
import time
import csv
from pathlib import Path
LOG_FILE = Path("system_usage_log.csv")
INTERVAL_SECONDS = 60
def log_system_usage():
"""Write CPU, RAM, and disk usage to CSV every minute."""
file_exists = LOG_FILE.exists()
with open(LOG_FILE, mode="a", newline="") as f:
writer = cs…Batch Rename Hundreds of Files in Python
Rename all files with a given extension inside a folder using a sequential counter and a custom prefix.
import os
from pathlib import Path
def batch_rename_files(directory: str, prefix: str, extension: str = ".txt") -> None:
"""Rename all files with given extension in directory to prefix_{counter}.ext."""
path = Path(directory)
if not path.is_dir():
print(f"Directory '{directory}' does not exist.")
…Benchmark Disk Write Speed in Python with tempfile
Benchmark raw disk write performance by writing a temporary file in 1MB chunks and measuring throughput in MB/s.
import os
import tempfile
import time
def benchmark_write(size_mb=50):
size_bytes = size_mb * 1024 * 1024
chunk = b'x' * 1024 * 1024 # 1 MB chunk
with tempfile.NamedTemporaryFile(delete=True) as tmp:
start = time.perf_counter()
written = 0
while written < size_bytes:
…Benchmark File Read and Write Speed in Python
Measures file write and read throughput in MB/s by writing and reading a temporary file of a given size.
import os
import time
import tempfile
def benchmark_write(file_path, size_mb=100):
data = b'x' * (1024 * 1024) # 1 MB block
start = time.perf_counter()
with open(file_path, 'wb') as f:
for _ in range(size_mb):
f.write(data)
elapsed = time.perf_counter() - start
return size_mb …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…Build a Terminal Dashboard That Displays Real-Time System Performance in Python
A Python script that reads Linux system files to display a real-time terminal dashboard with CPU usage, memory usage, and CPU temperature.
import os, time, sys
from collections import deque
def get_cpu_temp():
try:
with open("/sys/class/thermal/thermal_zone0/temp") as f:
return round(int(f.read().strip()) / 1000, 1)
except:
return None
def get_mem_usage():
with open("/proc/meminfo") as f:
lines = f.readli…Build an M3U Playlist from Folder MP3s in Python
Scans a folder for MP3 files and writes a valid M3U playlist with absolute file URIs.
from pathlib import Path
import sys
def build_playlist(folder: str, output: str = "playlist.m3u") -> str:
folder_path = Path(folder)
if not folder_path.is_dir():
raise FileNotFoundError(f"Folder not found: {folder}")
mp3_files = sorted(folder_path.glob("*.mp3"))
if not mp3_files:
pri…Build an RSS feed from markdown blog posts in Python
Scans a folder of markdown files, extracts titles, dates, and excerpts, and generates a valid RSS 2.0 XML feed.
import re
from pathlib import Path
from xml.etree.ElementTree import Element, SubElement, tostring
from datetime import datetime, timezone
from xml.dom import minidom
def build_rss(blog_dir, site_url="https://example.com"):
feed = Element("rss", version="2.0")
channel = SubElement(feed, "channel")
SubElem…Bulk Rename Files in Python with Regex Replacement
Renames every file in a directory by applying a regex substitution to its filename using Python's stdlib re and pathlib.
import re
from pathlib import Path
def bulk_rename_regex(directory, pattern, replacement):
path = Path(directory)
renamed = []
for file in path.iterdir():
if file.is_file():
new_name = re.sub(pattern, replacement, file.name)
if new_name != file.name:
new_pat…Convert DOCX to Text by Unzipping XML in Python
Extract plain text from a .docx file by unzipping the container and parsing word/document.xml with regex, using only Python's standard library.
import zipfile
import re
from pathlib import Path
def docx_to_text_unzip_xml(docx_path: str) -> str:
"""Extract plain text from a .docx file by unzipping and parsing document.xml."""
docx_path = Path(docx_path)
if not docx_path.exists():
raise FileNotFoundError(f"File not found: {docx_path}")
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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.