What is Stream?
Who uses Stream?
Why developers like Stream?
Here are some stack decisions, common use cases and reviews by members of with Stream in their tech stack.
I use Stream because I used to process collections of objects and bit lazy by nature to write long codes.
Stay updated with FinanceDraft to get the latest and leading finance industry new, business news, economy news from all around the globe on our site. Check out the latest news headlines. Stream
Here are some stack decisions, common use cases and reviews by companies and developers who chose Stream in their tech stack.
Winds 2.0 is an open source Podcast/RSS reader developed by Stream with a core goal to enable a wide range of developers to contribute.
The capability of style customization is one a large deal breaker for frontend SDKs. To solve this, we decided to use styled-components in our SDK, which makes it easy to add support for themes on top of our existing components. This practice reduces the maintenance effort for stylings of custom components and keeps the overall codebase clean.
Dubsmash's very small engineering team has always made a point to spend its resources on solving product questions rather than managing & running underlying infrastructure.
We recently started using Stream for building activity feeds in various forms and shapes. Using Stream we are able to rapidly iterate on features like newsfeeds, trending feeds and more while making sure everything runs smooth and snappy in the background. With their advanced ranking algorithms and their recent transition from Python to Go, we are able to change our feeds ranking on the fly and gauge user impact immediately!
Here at Stream, we recently build a powerful CLI to support our Feeds & Chat products. In doing so, we learned a lot about best practices when crafting a positive developer experience in the command line. Quick findings:
For inspiration, look at the functionality that Zeit and Heroku provide within their CLI to make for an awesome developer command line “experience”.
If your API/CLI requires data persistence, store that data in a cache directory that is specific to your CLI. Load this using a util file as we do at Stream. Also, note that the fs-extra package will come in handy for this type of thing (even though support is built into Oclif).
Oclif is the way to go, especially if you’re building a large CLI, as opposed to a single-command CLI. If you’re building a single-command CLI you can still use Oclif, just make sure to specify that it’s a single-command API when you’re scaffolding your CLI.
Don’t want to use a framework? That’s okay! The package minimist provides argument parsing in the command line and can easily be used within your project.
Use prompts, when you can, with enquirer or another package of your choosing. Users should be walked through the requirements of the command and asked for the data the command needs in order to execute properly. Note that this should never be required (e.g. let the user bypass the prompt if they pass the correct arguments).
Use colors when possible to make your CLI a little easier on the eye. Chalk serves as a great tool for this. If you have response data that is well enough structured, don’t just print it out to the user (unless that’s what they specify). Instead, drop it in a table using
Always allow the user to specify the output type (e.g. JSON), but default to a message that is human-readable.
Keep it fast! For time-consuming tasks such as file uploads or commands that require multiple API calls, we recommend showing a loading indicator to let the user know that work is being done in the background. If you’re looking for a package on npm, we recommend checking out ora.
The full blog post can be found here: https://medium.com/@nparsons08/crafting-a-command-line-experience-that-developers-love-68657b20c28d
As we strive to show fresh, popular and relevant content to our users, one of the problems we faced when developing Stack Decisions was to show a feed with more than one activity type. We show Decisions, News Articles, and Stories on our feed and composing them in a single feed proved to be a challenge.
We solved this problem using Stream's personalization feature to build a scalable activity feed. As the parameters that determine popularity vary for different activity types, Stream helped us normalize the popularity scores and aggregate the feed.
- Activity, Notification & Personalized Feeds
- Real-Time Chat
- Multi-Region Support
- High Availability
- SDKs & Components