Learn how to dramatically speed up your workflow by generating large amounts of HTML using CSS style selectors. In this video, we specifically look at generating HTML, but Emmet offers other functionality to help you work faster.
Let’s skip the database and build the ability to like any model in Laravel, using Redis. Traditionally you’d reach for the database for this kind of thing, but as you load more models and start performing checks within relationships — things begin to slow down. With a key-value store like Redis, tracking users who have liked comments (or anything) keeps everything ridiculously fast.
Effortlessly handle large file uploads in your Inertia/Vue apps with chunked, resumable uploading. We’ll cover the entire upload process for the client and server, display a progress bar, then add the ability to pause, resume and cancel uploads. From there, you’ll be able to handle huge file uploads anywhere in your applications.
Let’s build an app to capture and record your webcam (or screen) directly from the browser, store it, and provide a link that can be shared to anyone for them to watch. Completely from scratch, we’ll hook into the browser APIs for recording, send the video to our backend for encoding, generate still images with FFmpeg, and produce a sharable link that can be sent to anyone for them to view.
If you need to log unique views in Laravel, you might reach for a database table to track IP addresses or another unique piece of data. Let's take a look at speeding things up both in performance and complexity by using Redis and the HyperLogLog probabilistic data structure. Once we're done, we'll set up a period command to sync views back to the database for easy ordering, and then create a trait to share functionality between other models.
Let’s learn how wire:stream can help us stream ChatGPT responses as they arrive, by building a chat interface with Livewire. Each message we send and receive will be shown in chat history. It even remembers the conversation context. Sure, there are a ton of ChatGPT wrappers out there, but by the end of this course, you’ll have wire:stream in your toolkit for future projects.