MiniTwitter

MiniTwitter is a simple gRPC-based microservice application designed to simulate basic Twitter-like functionality. The project implements a server-client architecture where users can send and retrieve short messages (tweets) through defined gRPC methods. This project demonstrates practical usage of gRPC in Python, including the server-side logic, client interactions, and test automation.

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Features

• Send Messages: Clients can send short text messages (tweets) to the server.
• Retrieve Messages: Clients can fetch the latest messages up to a specified limit.
• In-Memory Storage: Messages are stored in memory for simplicity.
• gRPC Communication: Protocol Buffers are used to define data and service communication.
• CI/CD: Automated testing and linting through GitHub Actions.
• Logging System: A logs/ folder is used for debugging and tracking system behavior.
• High Test Coverage: Over 90% code coverage with pytest.
• Linting: pylint reports 10/10 for both client.py and server.py.

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Architecture

The MiniTwitter project is built with the following components:

• Server:
  • Implements gRPC services to handle incoming requests from clients.
  • Stores all messages in a simple in-memory list.
• Client:
  • Provides a command-line interface (CLI) for users to send and retrieve messages.
• Protocol Buffers:
  • minitwitter.proto defines the gRPC methods and message structures.
• Tests:
  • Unit tests for client and server functionality ensure the reliability of gRPC methods.

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Getting Started

Prerequisites

• Python 3.9 or higher
• pip (Python package manager)
• gRPC tools (grpcio and grpcio-tools)

Installation

1. Clone the repository:

   git clone https://github.com/MlCHAL-S/MiniTwitter.git
   cd MiniTwitter

2. Set up a virtual environment:

   python -m venv .venv
   source .venv/bin/activate   # On Windows: .venv\Scripts�ctivate

3. Install dependencies:

   pip install -r requirements.txt

4. Generate gRPC code (if needed):

   python -m grpc_tools.protoc -Iproto --python_out=. --grpc_python_out=. proto/minitwitter.proto

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Running the Application

Set PYTHONPATH

export PYTHONPATH=src:$PYTHONPATH

Starting the Server

To start the MiniTwitter server, run:

python -m src.server.server

The server listens on localhost:50051 for gRPC connections.

Running the Client

To start the MiniTwitter client, run:

python -m src.client.client

The client provides a simple CLI for interacting with the server:

• SEND <message>: Send a tweet to the server.
• GET <number>: Retrieve the last <number> messages.
• EXIT: Exit the client application.

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Testing

Running Tests

The project includes unit tests for both client and server. To run all tests, use:

pytest

Coverage

The tests validate:

• Correct functionality of gRPC methods (sendMessage, getMessages).
• Interaction between client and server using mocked gRPC stubs.

Tests cover over 90% of the code:

Name                   Stmts   Miss  Cover   Missing
----------------------------------------------------
src/client/client.py      39      5    87%   73-78
src/server/server.py      26      1    96%   77
----------------------------------------------------
TOTAL                     65      6    91%

Linting

The project follows PEP8 coding standards. pylint results:

client.py: 10/10
server.py: 10/10

Deployment

Infrastructure as Code (Terraform)

Infrastructure is managed with Terraform:

• main.tf: Defines AWS resources (VPC, EC2, Security Groups).
• vars.tf: Configurable parameters.
• output.tf: Stores deployment details.

Initialize Terraform:

terraform init

Using Ansible

To deploy the MiniTwitter server using Ansible:

ansible-playbook -i ansible/inventory.ini ansible/config.yaml

Running the Client

Once the server is deployed and running, you can start the client by running:

python -m src.client.client <server_ip>

Replace <server_ip> with the actual IP address of your deployed server.

Continuous Integration (CI)

CI is handled with GitHub Actions (.github/workflows/ci.yaml):

• Runs on pull requests to main.
• Steps include:
  • Code checkout
  • Python environment setup
  • Dependency installation
  • Linting with pylint
  • Running tests with pytest

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Contributors

• MlCHAL-S
• olivblvck
• KubaSienski

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Documentation

For a detailed explanation, refer to the full documentation.