How to Build a Django-Unfold Admin Dashboard with Custom Models, Filters, Actions, and KPIs
This tutorial guides users through building an advanced Django-Unfold admin dashboard. It covers installation, configuration, and customization with various features like custom models, filters, and KPIs.
This tutorial provides a comprehensive guide to building an advanced Django-Unfold admin dashboard.
It begins with the essential steps of installing Django, Django-Unfold, and all necessary dependencies. Following this, users will learn to create a new Django project and integrate a shop application.
The tutorial then delves into configuring Unfold to achieve a modern administration theme. This includes setting up custom sidebar navigation, dashboard callbacks, and implementing product badges.
Further customization options are explored, such as integrating tabs, filters, and actions. The guide also covers creating a bespoke admin homepage to enhance functionality and user experience.
Related articles
Build real agentic apps using CUGA: two dozen working examples on a lightweight harness
CUGA, IBM's open-source Agent Harness, simplifies building agentic applications by handling infrastructure, allowing developers to focus on tools and prompts. It offers pre-assembled components for planning, execution, and state management, significantly reducing development time. CUGA has topped agent benchmarks like AppWorld and WebArena.
OpenAI launches new initiative to help find and patch open source bugs
OpenAI has launched "Patch the Planet," a new initiative in partnership with cybersecurity firm Trail of Bits, to enhance the security of open-source projects. This program aims to assist maintainers in identifying and patching bugs, utilizing OpenAI's AI-powered security tools while reducing the burden on project teams.
PP-OCRv6 on Hugging Face: 50-Language OCR from 1.5M to 34.5M Parameters
Baidu has released PP-OCRv6, an advanced optical character recognition (OCR) model supporting 50 languages. Available on Hugging Face, this version significantly improves accuracy and efficiency across various parameter sizes, from 1.5 million to 34.5 million, marking a substantial leap in multilingual OCR technology.