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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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WorkOS
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I guess one good example (that was mentioned just yesterday here on HN) would be Flask vs FastAPI: https://news.ycombinator.com/item?id=31953470 - "There are no open issues or pull requests on Flask "
Quick count finds that FastAPI has 48422 lines of code, while Flask has 9995. Flask just achieved "Zero standing issues/PRs" while FastAPI has 1.1K open issues and ~500 open PRs.
Large surface area/API quickly leads to be overwhelmed when you're trying to maintain it. Adding new features/fixing existing ones becomes harder as well.
Best bet to make sure something is maintainable over time is to add as little as possible to it, and if you really have to, make sure you're also removing something at the same time.
Otherwise you need a massive team just to be able to "survive" and not making things rot.
There is this blogpost as well about the "half-life of code": https://erikbern.com/2016/12/05/the-half-life-of-code.html
Someone run that tool on the Clojure codebase as well, and it really shows how well the Clojure codebase has been written, as most code that was initially written is still there and does what it needs, without having to be rewritten.
If you're not familiar with lisps in general, it might be hard to grok the differences between lisp-macros (as used in Clojure) and "normal" macros you see in other languages.
But, if you are familiar already, and just wanna see examples of neat macros that makes the API nicer than what a function could provide, here are a few:
- https://github.com/clojure/core.async/blob/master/examples/w...
- https://github.com/weavejester/compojure
- https://github.com/ptaoussanis/timbre
- https://github.com/krisajenkins/yesql
If you're not familiar with lisps in general, it might be hard to grok the differences between lisp-macros (as used in Clojure) and "normal" macros you see in other languages.
But, if you are familiar already, and just wanna see examples of neat macros that makes the API nicer than what a function could provide, here are a few:
- https://github.com/clojure/core.async/blob/master/examples/w...
- https://github.com/weavejester/compojure
- https://github.com/ptaoussanis/timbre
- https://github.com/krisajenkins/yesql
If you're not familiar with lisps in general, it might be hard to grok the differences between lisp-macros (as used in Clojure) and "normal" macros you see in other languages.
But, if you are familiar already, and just wanna see examples of neat macros that makes the API nicer than what a function could provide, here are a few:
- https://github.com/clojure/core.async/blob/master/examples/w...
- https://github.com/weavejester/compojure
- https://github.com/ptaoussanis/timbre
- https://github.com/krisajenkins/yesql
If you're not familiar with lisps in general, it might be hard to grok the differences between lisp-macros (as used in Clojure) and "normal" macros you see in other languages.
But, if you are familiar already, and just wanna see examples of neat macros that makes the API nicer than what a function could provide, here are a few:
- https://github.com/clojure/core.async/blob/master/examples/w...
- https://github.com/weavejester/compojure
- https://github.com/ptaoussanis/timbre
- https://github.com/krisajenkins/yesql
I don't know, the community in general tend to use macros that are well written. I keep seeing core.async being used (`go`) in Clojure projects, and also various macros for writing HTTP servers (compojure being a popular one which main code interface is a macro `defroutes`).
ClojureScript projects also routinely add support for making asynchronous code look synchronous (like `async/await` in vanilla JavaScript) via macros. shadow-cljs's `js-await` being one of the well-written ones: https://github.com/thheller/shadow-cljs/blob/49fb078b834e64f...
Usage:
(defn my-async-fn [foo]
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