fleet-management

REST API of a Fleet Management Software to query the locations of the vehicles of a taxi company.

• Technical Details:

  • Used Python and Django to build the API.
  • Implemented queues with RabbitMQ for optimizing asynchronous tasks.
  • Utilized Celery for background processing.
  • Implemented automated testing with Pytest.
  • Used Docker to run RabbitMQ.
  • Performance optimization strategies, including creating indexes on the location table, table partitioning, and progressive data querying.
  • Endpoint for exporting locations in Excel format, with email notification to the user upon completion of processing.

• Results:

  • Significant reduction in endpoint response times through database optimizations and efficient queries.
  • Improved user experience with optimized response times.
  • Implementation of a robust export to Excel functionality, allowing users to obtain detailed reports.
  • Enhanced scalability and performance of the application using asynchronous processing with Celery and RabbitMQ.

Installation

Install my-project with npm

  git clone git@github.com:lourdilene/django-5-fleet-management.git
  cd my-project
  pip install -r requirements.txt

Make migrations

  python manage.py makemigrations

Migrate

  python manage.py migrate

Run server

  python manage.py runserver

Installing and Run RabbitMQ

  # latest RabbitMQ 3.13
  docker run -it --rm --name rabbitmq -p 5672:5672 -p 15672:15672 rabbitmq:3.13-management

Runing Celery

  celery -A fleet_management worker -l info

Runing Tests

  pytest

Features

🔗 Links

🛠 Skills

Python3, Django, Queue, RabbitMQ, ORM, REST API.

Tools

• [Pytest]