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Python
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Case study
Interview prep
- DSA discipline
- Pattern library
- Daily execution
A long-running practice repo: pattern-based reps, clear notes, and steady commits so difficulty curves stay predictable instead of cram-shaped.
Preview
Solutions, templates, and problem lists live in version control—open the repo for the full tree.
Technical Interview Preparation
Problems, writeups, and patterns are tracked in the repository.
Browse on GitHubImpact
Interview performance compounds from repetition and recall under time pressure. This repo encodes that habit: recurring motifs (two-pointer, graph search, DP states) get fresh passes so interview day feels like muscle memory, not novelty.
Architecture
Structure: problems grouped by pattern and difficulty, with solutions kept beside notes on edge cases and complexity.
Workflow: small, daily commits over burst cramming—history itself is a signal of consistency.
Tooling: Python for rapid iteration; tests or assertions where they lock in regressions.
Shipped
- Pattern-forward problem organization
- Readable solutions with complexity called out
- Steady contribution rhythm (visible on the contribution graph)
- Easy to extend with new problem themes