Python Code Tutorials

This article compares ClickHouse and PostgreSQL for big data modeling, examining their approaches, advantages, and disadvantages. It aims to guide businesses in choosing the right database system for effectively managing and leveraging big data.

Learn how to use Python to scrape Google search results and review ratings. Track changes over time to monitor SEO, online reputation, and competitor activity.

Discover the key differences between nearshore and offshore software development. Learn which model offers the best balance of cost, quality, and collaboration for your project.

Learn how to use DuckDB in Python for lightning-fast SQL analytics on CSV, Parquet, and JSON files. Covers installation, querying, hybrid Pandas/Polars workflows, and performance tips.

Learn how text embeddings work in Python using Sentence Transformers. Generate embeddings, compare semantic similarity, and visualize the embedding space with PCA, t-SNE, heatmaps, and dimension analysis.

Build a fully local semantic search engine in Python using FAISS and Sentence Transformers. Learn how embeddings work, index vectors, run semantic queries, and visualize the embedding space with PCA.

Learn how to build a Python tool that scans directories, finds duplicate files by SHA256 hash, and calculates reclaimable disk space. Features Rich progress bars, tables, and a clean CLI experience.

Learn how to automate Excel reports with Python using openpyxl. Create professional spreadsheets with charts, formulas, conditional formatting, and styled dashboards — all from Python. Complete real-world sales report project included.

A quick guide to setting up Python on macOS, covering installation, tools (IDEs), virtual environments, learning resources, and basic best practices for a secure and efficient workflow.

Learn how to build a cross-platform website blocker in Python that modifies the hosts file to block distracting sites. Includes scheduling with cron and Task Scheduler. Pure standard library — no pip install needed.

Learn how to build a Python tool that scans job postings, detects in-demand tech skills using regex, ranks them by demand, and visualizes the results with matplotlib. Practical, extensible, and ready for real datasets.