PathWeave

PathWeave is a visual 6-month study planner for DSA + Math/ML interview prep.
It turns a long checklist into a more navigable board so you can track progress day by day without endless scrolling.

Intention

• Make a large preparation plan feel manageable.
• Keep daily decisions simple: one main task, clear reason, clear learning target.
• Blend structure (months, topics, review cadence) with flexibility (filters, progress state, quick navigation).
• Keep the app lightweight and easy to host as static files.

What It Does

• Builds a 180-day plan from plan.json.
• Maps DSA tasks from dsa_dump.json.
• Renders days in a snake-board layout for compact navigation.
• Shows richer details in a dedicated panel on selection.
• Supports filters:
  • Month
  • DSA topic
  • Math topic
• Tracks progress in localStorage:
  • Task completion
  • Active month (defaults to Month 1)
• Keeps offline-safe data loading via embedded fallbacks:
  • plan-data.js
  • dsa-data.js

Data Design

dsa_dump.json items are normalized to:

• id
• topic
• title
• url
• difficulty (easy|medium|hard|unknown)
• priority (core|stretch)

The app normalizes and validates data at runtime (URL cleanup, schema checks, dedupe).

Project Structure

• index.html — app shell
• styles.css — UI styling and responsive layout
• app.js — rendering, filtering, progress, data loading
• plan.json — month-by-month plan
• dsa_dump.json — DSA source data
• plan-data.js / dsa-data.js — fallback embedded datasets

Run Locally

You can open index.html directly, but serving over HTTP is recommended:

python -m http.server 5500

Then open:

http://localhost:5500

Deploy

This is a static frontend and can be deployed on:

• GitHub Pages
• Netlify
• Vercel (static)

Roadmap Ideas

• View switch: snake board / classic list
• Difficulty-aware day balancing
• Search by problem title
• Import/export progress JSON