How bladerunneryao/leetcode works
This is a personal NeetCode/LeetCode study wiki, not an application with a single runtime pipeline. Its principal loop is to consult the study map and review queue, solve a problem, assess the solution, and preserve reusable learning in the wiki and index. The README also documents raw-problem ingestion, practice scaffolding, notebooks, and history lookup. The supplied tree exposes solution files and scripts but not most wiki content; those documented areas are shown with null paths. Source samples show standalone solution implementations, not calls between them.
Main entry points: python Python solutions · prepare_neetcode.py Practice scaffolding · validate_repository.py Metadata validation · ingest_neetcode_raw.py Raw ingestion
Components 13
Study workflow
- Study and review
Knowledge base
- Study map and queue
- Problem facts
- Reusable patterns
- Learning history
Practice and tools
- Python solutions
solutions/python - Problem notebooks
Repository scripts
- Raw ingestion
scripts/ingest_neetcode_raw.py - Practice scaffolding
scripts/prepare_neetcode.py - Dashboard generation
scripts/generate_dashboard.py - Metadata validation
scripts/validate_repository.py
Other components
- Learner / Pi Agent
- LeetCode
Connections 16
- Learner / Pi Agent → Study and review: starts or resumes
- Study and review → Study map and queue: checks review queue
- Study and review → Problem facts: consults problem facts
- Study and review → Python solutions: works on problem
- Python solutions → LeetCode: submits for feedback
- Learner / Pi Agent → Study and review: requests assessment
- Study and review → Reusable patterns: records patterns
- Study and review → Study map and queue: updates map
- Study and review → Learning history: records progress
- Study and review → Problem notebooks: experiments when requested
- Raw ingestion → Problem facts: ingests batches
- Practice scaffolding → Python solutions: creates scaffolds
- Practice scaffolding → Problem notebooks: creates notebooks
- Dashboard generation → Study map and queue: generates dashboard
- Metadata validation → Study map and queue: checks consistency
- Metadata validation → Python solutions: checks metadata