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Copy-ready Python snippets by topic and difficulty — short, focused, and runnable in the browser editor.
How to Watch a Folder and Convert New Images in Python
Watch a folder for new files and mock-convert images by copying and renaming them in an output directory.
import time
import hashlib
from pathlib import Path
from datetime import datetime
def mock_convert_image(source: Path, dest_dir: Path) -> Path:
"""Mock image conversion: copy bytes and add .converted suffix."""
dest = dest_dir / f"{source.stem}.converted{source.suffix}"
dest.write_bytes(source.read_bytes(…How to automatically organize your Downloads folder by file type in Python
This script scans the Downloads folder and moves files into sub-folders based on their extensions (e.g., Images, Documents, Videos).
import os
import shutil
from pathlib import Path
def organize_downloads_folder(downloads_path=None):
if downloads_path is None:
downloads_path = str(Path.home() / "Downloads")
if not os.path.exists(downloads_path):
print(f"Path {downloads_path} does not exist.")
return
fi…How to rename music files by ID3 tags in Python
Renames MP3 files in a folder using artist and title extracted from ID3 tags, with a mock fallback that parses filenames.
import os
import re
from pathlib import Path
def sanitize_filename(name: str) -> str:
return re.sub(r'[<>:"/\\|?*]', '_', name).strip()
def rename_mp3_from_id3(path: Path) -> None:
for f in path.glob("*.mp3"):
# Mock ID3 extraction: derive artist/title from filename
stem = f.stem
if "…Python: Archive Old Logs by Compressing Gzip by Age
A Python script that finds .log files older than a specified age and compresses them into .gz archives while removing the originals.
import gzip
import os
import shutil
from pathlib import Path
def archive_logs(log_dir: str, max_age_days: int) -> list[str]:
"""Compress log files older than max_age_days into .gz archives.
Returns a list of compressed file paths.
"""
cutoff = time.time() - max_age_days * 86400
compressed = …Rename Files in Folder with Numeric Prefix in Python
Renames all files in a folder by adding a sequential numeric prefix (e.g., 01_, 02_) to each filename using pathlib.
from pathlib import Path
def rename_with_numeric_prefix(folder_path):
folder = Path(folder_path)
for index, file_path in enumerate(folder.iterdir(), start=1):
if file_path.is_file():
new_name = f"{index:02d}_{file_path.name}"
new_path = file_path.with_name(new_name)
…Rotate API keys in Python by updating an .env template
Replace an old API key with a new one inside an .env template file, with a guard for missing keys.
import json
from pathlib import Path
def rotate_api_keys(env_template_path: Path, old_key: str, new_key: str) -> None:
"""Replace an old API key with a new one in an .env template file."""
content = env_template_path.read_text()
if old_key not in content:
print(f"Error: '{old_key}' not found in {e…Attach Source File Metadata to Records in Python
Add a source filename field to each record in a list by merging a new key into every dictionary using a dict unpacking comprehension.
from pathlib import Path
import json
def attach_source_metadata(records, source_file):
"""Attach source filename metadata to each record."""
return [
{**record, "source": Path(source_file).name}
for record in records
]
if __name__ == "__main__":
source = "/data/raw/customers.csv"
…How to Build a Simple Data Pipeline in Python
A beginner-friendly data pipeline that loads JSON, filters records by a field value, and aggregates counts per category.
import json
from pathlib import Path
def load_json(filepath: str | Path) -> list[dict]:
"""Load a JSON file containing a list of records."""
with Path(filepath).open("r", encoding="utf-8") as f:
return json.load(f)
def filter_records(records: list[dict], field: str, value) -> list[dict]:
"""Kee…How to Partition Output Files by Date Key in Python
Group output files into a dictionary partitioned by a YYYYMMDD date key extracted from the filename prefix.
from pathlib import Path
from collections import defaultdict
def partition_files_by_date(directory: str) -> dict:
"""Partition output files by date key extracted from filename (YYYYMMDD prefix)."""
path = Path(directory)
partitions = defaultdict(list)
for file in path.iterdir():
if file.i…How to Process CSV Data in Python with a Data Helper
Build a beginner-friendly data helper in Python that loads a CSV file, filters rows by a condition, and summarizes numeric fields.
import csv
from pathlib import Path
DATA = [
{"name": "Alice", "score": 88, "passed": True},
{"name": "Bob", "score": 42, "passed": False},
{"name": "Carol", "score": 95, "passed": True},
]
def load_csv(file_path: Path) -> list[dict]:
with file_path.open(newline="", encoding="utf-8") as f:
r…How to create a dated snapshot path for a dataset in Python
Generate a versioned directory path combining a base directory, dataset name, and today's date, ready for creating snapshots in data pipelines.
import datetime
import os
from pathlib import Path
def snapshot_path(base_dir: str, dataset_name: str) -> Path:
"""Return a dated snapshot path for a dataset under a base directory."""
today = datetime.date.today().isoformat()
return Path(base_dir) / dataset_name / today
if __name__ == "__main__":
…How to Mock git sparse-checkout Paths in Python
Simulates git sparse-checkout configuration by writing desired paths to the sparse-checkout file without running git commands.
import subprocess
from pathlib import Path
import tempfile
def configure_sparse_checkout(repo_dir: Path, paths: list[str]) -> list[str]:
"""Simulate sparse checkout configuration by returning the paths that would be set."""
sparse_checkout_file = repo_dir / ".git" / "info" / "sparse-checkout"
sparse_chec…Create a Cloud Storage Helper Class in Python
Build a simple local file-based helper class that mimics cloud storage operations like save, load, and list JSON objects.
import datetime
import json
from pathlib import Path
class CloudDataHelper:
"""Simple helper for reading/writing JSON files in a cloud-style folder."""
def __init__(self, base_dir: str = "cloud_storage"):
self.base_dir = Path(base_dir)
self.base_dir.mkdir(exist_ok=True)
def save_json(se…Create a Data Helper Class for Beginners in Python
A simple Python class to read and write JSON and CSV files from a local directory, ideal for automating data workflows in cloud environments.
import json
from pathlib import Path
class DataHelper:
"""Simple helper for reading and writing common data files."""
def __init__(self, directory="data"):
self.directory = Path(directory)
self.directory.mkdir(exist_ok=True)
def save_json(self, filename, data):
filepath =…How to Create a JSON Data Helper in Python
A beginner-friendly DataHelper class that safely reads and writes JSON files with timestamps to a local data directory.
from datetime import datetime
from pathlib import Path
import json
class DataHelper:
"""Simple helper for reading/writing JSON files safely."""
def __init__(self, base_dir="data"):
self.base_dir = Path(base_dir)
self.base_dir.mkdir(exist_ok=True)
def save(self, filename, data):
…How to Design a Cloud Data Helper Class in Python
A beginner-friendly Python helper class that saves, loads, and aggregates JSON records locally, simulating cloud-style data handling.
import json
from pathlib import Path
from datetime import datetime
class CloudDataHelper:
"""Beginner-friendly helper for working with cloud-based JSON data."""
def __init__(self, base_dir="cloud_data"):
self.base_dir = Path(base_dir)
self.base_dir.mkdir(exist_ok=True)
def save_record(s…Data Conversion Helper Functions in Python
A set of beginner-friendly helper functions to convert between JSON strings and Python data, parse dates, and read/write files using pathlib.
from datetime import datetime
from pathlib import Path
import json
def to_json(data, indent=2):
"""Convert Python data to pretty-printed JSON string."""
return json.dumps(data, indent=indent, default=str)
def from_json(json_string):
"""Parse JSON string back into Python data."""
return json.loads(jso…How to Load and Inspect CSV Data with a Dataclass Helper in Python
This code defines a DataHelper dataclass that reads a CSV file into a list of dictionaries and prints basic dataset information.
from pathlib import Path
from dataclasses import dataclass
from typing import Any
@dataclass
class DataHelper:
"""Simple helper for loading and inspecting CSV data."""
filepath: Path
def load_csv(self, *, delimiter: str = ",") -> list[dict[str, Any]]:
"""Read CSV into a list of dictionaries."""
…How to Load and Inspect Data Files in Python
A beginner-friendly DataLoader dataclass that loads JSON or text files and provides methods to preview and inspect the data.
from dataclasses import dataclass, field
from pathlib import Path
import json
from typing import Any, Dict, List
@dataclass
class DataLoader:
"""Simple helper to load and inspect data files for beginners."""
path: Path
data: Any = field(init=False, default=None)
def __post_init__(self) -> None:
…How to Load and Save CSV and JSON Files in Python
A beginner-friendly data helper that loads or saves CSV and JSON files using only the Python standard library, with automatic format detection from the file extension.
from pathlib import Path
import json
import csv
def load_data(file_path):
"""Load CSV or JSON data from disk based on file extension."""
path = Path(file_path)
if path.suffix == ".json":
with path.open() as f:
return json.load(f)
elif path.suffix == ".csv":
with path.open(…How to Mock a pyenv Local Version File in Python
Read and write a mock .python-version file using the pathlib module and tempfile for isolated testing.
import json
import tempfile
from pathlib import Path
def read_pyenv_local(directory: Path) -> str:
"""Read the .python-version file in the given directory."""
version_file = directory / ".python-version"
if not version_file.exists():
return "no-version-file"
return version_file.read_text().st…How to Parse and Extract Nested Data in Python
Load JSON files with Path and recursively extract values by key from nested Python structures using modern typing and standard library.
import json
from pathlib import Path
from typing import Any, Dict, List, Union
def load_data(filepath: Union[str, Path]) -> Union[Dict[str, Any], List[Any]]:
"""Load JSON data from a file with modern Path handling."""
path = Path(filepath)
if not path.exists():
raise FileNotFoundError(f"File not f…How to Read the Python Path from VS Code settings.json in Python
This code loads VS Code's settings.json file and extracts the python.defaultInterpreterPath value, with a mock demonstration for testing.
import json
from pathlib import Path
from unittest.mock import patch
def read_vscode_python_path(settings_path: Path) -> str:
"""Extract python.defaultInterpreterPath from VS Code settings.json."""
with open(settings_path, "r") as f:
settings = json.load(f)
return settings.get("python", {}).get("d…How to Save and Load JSON Files in Python
Create a simple data helper to save Python dictionaries as pretty-printed JSON files and load them back reliably using pathlib and the stdlib json module.
import json
from pathlib import Path
from typing import Any
def save_json(data: Any, filename: str) -> None:
"""Save data as pretty-printed JSON to the current directory."""
path = Path(filename)
with path.open("w", encoding="utf-8") as f:
json.dump(data, f, indent=2, ensure_ascii=False)
def lo…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.