A reusable CSV validation script that checks for common data integrity issues: column presence, leading/trailing whitespace, duplicate entries, URL format, tag separator correctness, and newline endings. It uses a defensive parsing strategy and provides clear error messages with row numbers. This pattern can be extracted and applied to any curated CSV dataset where data cleanliness is critical (e.g., community lists, directories). The script is self-contained, requires only Python's standard library (`csv`), and can be run as a standalone linter.

A lightweight Python script that reads the CSV and outputs a formatted Markdown table. It demonstrates a clean pattern for generating documentation from structured data: it prints the static header and footer, then iterates over CSV rows to produce table rows. The script is idempotent and can be easily adapted for any dataset that needs a Markdown table representation. It uses `csv.DictReader` for clarity and prints directly to stdout, making it composable in shell pipelines (e.g., `python readme_render.py > README.md`).

A simple but effective script that converts the CSV blog list into an OPML (Outline Processor Markup Language) feed. It constructs the XML manually using string formatting and `quoteattr` for proper attribute escaping, producing a valid OPML 1.0 document. This pattern is reusable for any curated list of RSS feeds that needs an OPML export for feed reader subscriptions. The script is concise, uses only standard library modules, and demonstrates a low-dependency approach to XML generation.