nestjs-graphql-python-microservices

Outcome is to learn & implement nestjs, graphql, python and docker

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NestJS + GraphQL + Python Microservices Roadmap

A step-by-step 8-week roadmap to master NestJS, GraphQL, and Python microservices, fully Dockerized.
By the end, you'll have a production-ready backend stack with MongoDB, Redis caching, and optional ML/image processing services.

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Tech Stack

• Backend: NestJS, GraphQL (Apollo)
• Microservices: Python (FastAPI)
• Database: MongoDB (Mongoose)
• Cache & Messaging: Redis, Optional RabbitMQ
• Containerization: Docker & Docker Compose

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8-Week Roadmap

Week 1 – NestJS Fundamentals (Task Tracker API)

Goal: Learn NestJS structure, modules, services, and basic GraphQL CRUD.

Tasks & Subtasks:

1. Setup Project

   • Install NestJS CLI.
   • Scaffold project: nest new task-tracker.
   • Add GraphQL module (code-first).
   • Setup MongoDB with Mongoose.

2. Create Modules & Services

   • Create TaskModule.
   • Create TaskService with CRUD methods.
   • Create TaskResolver with queries/mutations.

3. GraphQL Implementation

   • Define Task schemas using Mongoose.
   • Implement createTask, getTasks, updateTask, deleteTask.
   • Test queries in GraphQL Playground.

4. Docker Practice

   • Write basic Dockerfile for NestJS.
   • Build image & run container.
   • Verify GraphQL Playground inside container.

Optional Bonus: Add pagination & filtering.

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Week 2 – GraphQL Deep Dive (User & Task Relationship)

Goal: Master GraphQL queries, relationships, and nested resolvers.

Tasks & Subtasks:

1. User Module

   • Create UserModule and UserService.
   • Add User schema and relationships to Task.

2. Resolvers

   • Add getUserTasks(userId) query.
   • Implement nested resolvers for task details.

3. Input Validation

   • Use class-validator decorators.
   • Handle errors gracefully in GraphQL.

4. Docker

   • Add MongoDB container via Docker Compose.
   • Connect NestJS container to MongoDB service.
   • Test queries from NestJS container.

Optional Bonus: Fix N+1 problem using DataLoader.

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Week 3 – Authentication & Authorization (JWT Auth)

Goal: Secure GraphQL APIs.

Tasks & Subtasks:

1. JWT Auth Setup

   • Install Passport.js + JWT packages.
   • Configure JWT strategy and guards.

2. User Auth

   • Implement signup & login mutations.
   • Hash passwords using bcrypt.
   • Add me query for authenticated user.

3. Role-based Access

   • Add roles (e.g., admin, user).
   • Create @Roles() decorator.
   • Protect queries/mutations.

4. Docker

   • Use .env for JWT secret inside container.
   • Rebuild NestJS image with updated config.

Optional Bonus: Add refresh tokens & password reset mutation.

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Week 4 – Caching & Middleware

Goal: Improve performance with caching and interceptors.

Tasks & Subtasks:

1. Integrate Redis

   • Add Redis client to NestJS.
   • Cache GraphQL query results.

2. Middleware & Interceptors

   • Logging middleware for requests.
   • Interceptor to transform responses.
   • Rate limiting middleware.

3. Docker

   • Add Redis container in Docker Compose.
   • Connect NestJS container to Redis service.
   • Test cache persistence across container restarts.

Optional Bonus: Add custom decorators to inject metadata for logging.

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Week 5 – Python Microservice (FastAPI Analytics)

Goal: Connect Python microservice to NestJS for analytics.

Tasks & Subtasks:

1. Python FastAPI Setup

   • Scaffold FastAPI project.
   • Create /analyze route.
   • Define Pydantic models for input/output.

2. NestJS Integration

   • Add Axios module in NestJS.
   • Create service to call Python /analyze endpoint.
   • Expose GraphQL query getUserAnalytics.

3. Docker

   • Write Dockerfile for Python service.
   • Add Python container to Docker Compose.
   • Verify NestJS ↔ Python container communication.

Optional Bonus: Use RabbitMQ or Redis Streams for async communication.

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Week 6 – File Upload & Background Processing

Goal: Handle file uploads and background processing with Python.

Tasks & Subtasks:

1. GraphQL File Upload

   • Add Upload scalar.
   • Implement uploadImage(file: Upload) mutation.

2. Python Image Processing

   • Script to resize/compress images (Pillow/OpenCV).
   • Store processed images in volume or S3.

3. Background Jobs

   • Setup Bull (Redis-based queue).
   • Send image processing tasks to queue.
   • Python worker picks up job and returns result.

4. Docker

   • Mount local folder as volume for image storage.
   • Ensure Python container can access volume.
   • Test full workflow in Docker Compose.

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Week 7 – Real-time Notifications

Goal: Implement WebSockets and GraphQL subscriptions.

Tasks & Subtasks:

1. NestJS WebSocket Gateway

   • Setup WebSocket gateway.
   • Create onTaskUpdated subscription.

2. Broadcasting Events

   • Trigger events when tasks are created/updated.
   • Test multiple clients subscribing.

3. Python Integration (Optional ML)

   • Python service predicts notifications.
   • NestJS broadcasts ML suggestions via subscription.

4. Docker

   • Verify WebSocket communication between containers.
   • Ensure Redis pub/sub works across containers.

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Week 8 – Capstone: Full Stack Integration

Goal: Build a fully Dockerized, production-ready microservice stack.

Tasks & Subtasks:

1. NestJS GraphQL Gateway

   • Aggregate multiple subgraphs (tasks, users, recommendations).

2. Python ML Service

   • Serve movie recommendations via ML model.
   • FastAPI route returns recommendations.

3. Docker Compose Orchestration

   • NestJS container
   • Python ML service container
   • MongoDB
   • Redis
   • Optional RabbitMQ
   • Setup networks, volumes, env files.

4. Testing

   • Test getRecommendedMovies(userId) query.
   • Test caching, subscriptions, and analytics pipelines.

5. Optional Frontend

   • Minimal React/Angular dashboard to visualize recommendations & notifications.

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Running the Stack with Docker

1. Copy .env.example to .env and configure variables.
2. Build and start all services:

docker-compose up --build