Run many iterations of Django across Docker Compose or Raspberry Pis to handle large amounts of time series data. Topics: ✅ Python & Django ✅ Setup Django Project ✅ Integrate Self-Hosted TimescaleDB with Django ✅ Integrate Timescale.com Cloud with Django ✅ Use TimescaleDB with django-timescaledb ✅ Integrate Django & Celery ✅ Django Celery Task to Generate Fake Data ✅ Using a Beat Server to run tasks on a schedule (e.g. every 5 seconds) ✅ Learn how to use Celery Task Queues for Individual Worker Nodes ✅ Run multiple Django instances through Docker Compose to emulate a multi-node production environment ✅ Docker Compose Watch to Auto Refresh Django Container ✅ Multi-Node Django+Celery Running on Docker Compose ✅ Configure Raspberry Pi OS for local network connection ✅ Use Ansible to Configure Pi Cluster for Django ✅ Integrate Production TimescaleDB across Docker Compose, Raspberry PIs, and a local Django project. ✅ TimescaleDB Queries and API Responses ✅ Visualizing Data with TimescaleDB and Chart.js ✅ Customize Python Decouple for multiple dotenv Environment Variable files 💽 Code: 🕹️ Links: - Blog Post for Dockerfile: - django-timescaledb package: If you like this course, consider: - SaaS Foundations -- Learn about integrating Django with Stripe, User Permissions, GitHub Actions, and much more: - Build Full Stack Web Apps in Pure Python with Reflex - A great challenge would be to use Reflex as a replacement for Next.js: Thank you to Timescale for sponsoring this cours |
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