💬 Messenger test task

A mini messenger application with the ability to send messages, store them in a database, and create group chats. Completed as part of a test assignment for the position of Backend developer.

📦 Functionality

• Connection via WebSocket
• Real-time text messaging
• Storing messages in PostgreSQL
• Tracking the reading of messages
• A REST endpoint for getting the message history
• Prevent duplicate messages when sending in parallel
• Swagger documentation
• Containerization with Docker

🚀 Quick Start

1. Copy the example environment file:

cp example.env .env

2. Build the Docker containers:

docker-compose build

3. Start the app:

docker-compose up

🌐 Interfaces

• Swagger UI: http://localhost:8000/docs
• pgAdmin: http://localhost:5050

🛠️ Seed Test Data Script

This script (seed_test_data.sh) automatically fills your PostgreSQL database with test data — including users, chats, participants, and messages.

⚙️ Setup

1. Create a .env file in the root directory and add the following content:

cp example.env .env

2. Make sure PostgreSQL client (psql) is installed:

On Ubuntu/Debian:

sudo apt install postgresql-client

On macOS (via Homebrew):

brew install libpq
brew link --force libpq

▶️ Usage

1. Make the script executable:

chmod +x seed_test_data.sh

2. Run the script:

./seed_test_data.sh

If everything is set up correctly, you’ll see:

✅ Messenger database has been successfully filled with test data.

📖 API Documentation

👤 Users

➕ Create User

• Endpoint: POST /users/
• Description: Creates a new user.
• Request Body (application/json):

{
  "name": "John Doe",
  "email": "[email protected]",
  "password": "securepassword"
}

• Response (200 OK):

{
  "id": "uuid",
  "name": "John Doe",
  "email": "[email protected]"
}

💬 Chats

➕ Create Chat

• Endpoint: POST /chats/
• Description: Creates a new chat.
• Request Body (application/json):

{
  "name": "Work Chat",
  "type": "group",
  "participantIds": ["uuid1", "uuid2"]
}

• Response (200 OK):

{
  "id": "uuid",
  "name": "Work Chat",
  "type": "group",
  "participantIds": ["uuid1", "uuid2"]
}

📜 Get Chats for User

• Endpoint: GET /chats/?user_id=uuid
• Description: Retrieves all chats the user is a part of.
• Response (200 OK):

[
  {
   "id": "uuid",
   "name": "Work Chat",
   "type": "group",
   "participantIds": ["uuid1", "uuid2"]
  }
]

➕ Add User to Chat

• Endpoint: POST /chats/{chat_id}/users/{user_id}
• Description: Adds a user to the specified chat.
• Response (200 OK):

{
  "id": "uuid",
  "name": "Work Chat",
  "type": "group",
  "participantIds": ["uuid1", "uuid2", "uuid3"]
}

✉️ Messages

📜 Get Message History

• Endpoint: GET /messages/history/{chat_id}
• Description: Retrieves the message history for a given chat.
• Query Parameters (optional):
  • limit: Number of messages to return (default: 100)
  • offset: Pagination offset (default: 0)
• Response (200 OK):

[
  {
   "id": "uuid",
   "chatId": "uuid",
   "senderId": "uuid",
   "text": "Hello!",
   "read": true,
   "createdAt": "2025-04-24T12:00:00Z",
   "updatedAt": "2025-04-24T12:00:00Z"
  }
]

---

🔗 WebSocket

💬 Chat Messaging

• Endpoint: ws://localhost:8000/messages/ws/{chat_id}/{user_id}
• Description: Opens a real-time WebSocket connection for sending and receiving messages in a chat.

📨 Message Types

1. Send a Message

• Sends a new chat message to all participants.
• Message Format:

  {
   "event": "message",
   "data": {
    "text": "Hey, how are you?"
   }
  }

2. Mark as Read

• Notifies the server that a message has been read.
• Message Format:

  {
   "event": "read",
   "data": {
    "message_id": "f2abadb9-6a60-44c4-8c74-01aa2f520bf8"
   }
  }

---

🧪 Tests:

To run the tests, load the dependencies using the pipenv package manager and run the command > pytest

1. Copy the sample environment file if you haven't done this before:

cp example.env .env

2. Create a new virtual environment and install dependencies:

pipenv shell
pipenv install --dev

3. Start the postgres container:

docker-compose up postgres

4. To run the project's tests, you can execute pytest from the root directory:

pytest

---

🛠️ Technologies Used

• FastAPI: Fast web framework for building APIs with Python.
• SQLAlchemy 2 (Async): ORM for Python with async support.
• Databases: Asynchronous database query library.
• PostgreSQL: Relational database management system used for storage.
• Docker: To run the project in a container.
• Docker Compose: To define and manage multi-container Docker applications.
• Pipenv: To manage project dependencies.