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Bank Statement Analyser: Turns raw PDF bank statements into structured spending data
Built a CLI tool that parses FNB PDF bank statements, extracts every transaction, and stores them in a local SQLite database, automatically categorizing spending across 50+ built-in merchant mappings so patterns are visible by category and month instead of buried in a PDF. Implemented SHA-256 file hashing so re-imported statements are automatically skipped rather than duplicated.
The network for creativity
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📋 Docket — Task Management Application
Docket is a responsive task-management web application built with Python, Flask, and SQLite. It allows users to create, edit, complete, delete, search, and filter tasks while keeping data persistently stored in a database. I designed a clean, paper-ledger-inspired interface with responsive layouts, task progress tracking, feedback notifications, and custom error handling. The project also demonstrates CRUD development, database management, server-side validation, and production deployment with Gunicorn and Render.
𝗙𝗶𝗻𝗮𝗻𝗰𝗶𝗮𝗹 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝘀 𝗵𝗮𝘃𝗲 𝗱𝗼𝘇𝗲𝗻𝘀 𝗼𝗳 𝗳𝗲𝗮𝘁𝘂𝗿𝗲𝘀, 𝗯𝘂𝘁 𝗹𝗮𝗻𝗱𝗶𝗻𝗴 𝗽𝗮𝗴𝗲𝘀 𝘀𝗵𝗼𝘂𝗹𝗱𝗻'𝘁 𝗳𝗲𝗲𝗹 𝗰𝗿𝗼𝘄𝗱𝗲𝗱.
Here is a breakdown of how I organized Banka’s features using modular card UI to keep navigation smooth and intuitive.
𝗖𝗼𝗿𝗲 𝗙𝗼𝗰𝘂𝘀: Simplifying complex banking and payment features into easy-to-digest visual cards.
𝗞𝗲𝘆 𝗧𝗮𝗸𝗲𝗮𝘄𝗮𝘆𝘀 𝘁𝗼 𝗛𝗶𝗴𝗵𝗹𝗶𝗴𝗵𝘁: 𝗕𝗲𝗻𝘁𝗼 𝗚𝗿𝗶𝗱 / 𝗖𝗮𝗿𝗱 𝗟𝗮𝘆𝗼𝘂𝘁: Breaking down diverse offerings like instant transfers, airtime top-ups, and card management into clean, distinct visual modules rather than walls of text.
𝗠𝗼𝗰𝗸𝘂𝗽 𝗖𝗼𝗻𝘁𝗲𝘅𝘁𝘂𝗮𝗹𝗶𝘇𝗮𝘁𝗶𝗼𝗻: Placing real UI app screens inside feature cards so users immediately understand how the feature works on mobile.
𝗖𝗮𝗿𝗱 𝗖𝗼𝗻𝘁𝗿𝗼𝗹 𝗦𝗲𝗰𝘁𝗶𝗼𝗻: Highlighting dedicated UI cards for advanced features like digital card freezing/unfreezing options to show security control upfront.
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This is a clean design, Nicely Done
PTSR Wiki: a canon archive platform on Django
My own project. Not a Fandom clone and not a wiki builder: a platform where every article has a type, a status and a canon level, and where changes go through a draft. The cover is a real screenshot of the running app, not a mockup.
What works:
Draft creation, editor, submission for review. Published pages are visible to everyone; drafts only to the author and the archive team.
Revisions: every save creates a record with the Markdown, rendered HTML, a content hash and a status snapshot.
Markdown renders on the server and is cleaned through bleach, so someone else's script never reaches an article.
Namespaces, page types and canon levels are seeded by one idempotent command.
Front page statistics are counted from the database, not typed in by hand.
Stack: Python, Django, SQLite, Django Templates, bleach.
What is not there yet: a diff between revisions, a review queue, categories and backlinks. Those are the next stages, not skipped details.
