Reference library

Python Code Samples

Copy-ready Python snippets by topic and difficulty — short, focused, and runnable in the browser editor.

2 matches
ML engineering pipelines easy

Load CSV Training Data Without Pandas in Python

This code loads a CSV file into a list of dictionaries using only the standard library, ideal for small ML training data without heavy dependencies.

csv data-loading standard-library
Python
import csv
from pathlib import Path

def load_csv(path):
    """Load CSV file into list of dicts without pandas."""
    rows = []
    with open(path, newline='', encoding='utf-8') as f:
        reader = csv.DictReader(f)
        for row in reader:
            rows.append(dict(row))
    return rows

if __name__ == "__m…
13 0 Open
Database scaling & optimization easy

How to Batch Load JSON Data in Python for Database Optimization

This code parses JSON data into records and loads them in batches to simulate efficient database insertion, reducing load and improving performance.

json batching database
Python
import json
import time

def parse_and_load(data, batch_size=100):
    """
    Parse JSON data and batch-load into a list of dicts.
    Demonstrates batching for database efficiency.
    """
    records = json.loads(data)
    batches = []

    for i in range(0, len(records), batch_size):
        batch = records[i:i + …
12 0 Open

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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

  1. Pick a topic section — strings, lists, files, functions, and more
  2. Open a sample, read How it works, and copy the code block
  3. 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.