Java & Python Full Stack Development Workshop — Mahendra College of Engineering, Salem, Tamil Nadu

Java & Python Full Stack Development Workshop — Mahendra College of Engineering, Salem, Tamil Nadu

Duration: Multi-day intensive (campus block schedule; typically 10–12 full lab days equivalent)Delivery: Paired programming blocks · Live coding reviews · Shared monorepo samplesCover (placeholder): /images/workshops/mahendra-college-fullstack.jpg

Design intent: two languages, one engineering mindset

Industry teams rarely standardise on a single language. This workshop deliberately exposed participants to two backend ecosystems so they could compare:

• Contract-first APIs (OpenAPI mindset) regardless of runtime
• Shared persistence models and migration discipline
• Testing pyramids (unit vs integration trade-offs) in both stacks

Java track — what we went deep on

• Spring Boot service boundaries, DTO validation, exception translation
• Spring Data repositories, fetch strategies, and “avoid the N+1” patterns (introductory)
• Packaging a service with profiles (dev, prod) and externalised configuration

Python track — what we went deep on

• Typed Python habits, virtual environments, and packaging basics
• FastAPI-style routing and dependency injection (conceptual mapping to Spring DI)
• Pydantic models for request/response parity with Java DTOs
• Async vs sync endpoints: when not to async (pragmatic guidance)

Front end (shared)

• React app consuming both backends behind a simple gateway pattern discussion
• Auth flows compared: cookie session vs bearer token trade-offs (high level + lab)

Data layer (shared)

• Normalisation refresher, FK constraints, indexes for common access paths
• Transactions: isolation intuition and “lost update” story using a classroom exercise

DevOps & quality (light but real)

• docker compose to run DB + backends + front end locally (participants followed a checklist)
• GitHub Actions sketch: build on push, artefact mindset (no full production deploy)

Placement preparation (embedded)

• One dual-stack story for interviews: “same feature in Java and Python—what changed?”
• Portfolio README template: problem, constraints, design, trade-offs, metrics you would measure

Capstone options (teams chose one theme)

1. Library / inventory — borrowing workflow + admin analytics slice2. Support ticket lite — SLA fields, assignment, audit trail

Prerequisites

Data structures at introductory level, basic SQL, and comfort with installing JDK + Python tooling on laptops.

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Seed content for demonstration.