gleam VS transport-site

Want a friendly language for building safe systems at scale? Gleam is here for you. It features modern and familiar syntax, that's reliable and scalable. Gleam runs on an Erlang virtual machine, and can run plenty of concurrent tasks. It comes with a compiler, build tool, formatter, editor integrations, and package manager all built in so you can get started right away. Congrats to the team on shipping your first major version 🙌.

While I love Clojure, I have to agree about tooling. I recently started using Gleam* and was impressed at how easy it was to get up and running with the CLI tool. I think this is an important part of getting people to adopt a language.

* https://gleam.run/

If you use languages that compile to WASM (such as Gleam https://gleam.run), and can also run Postgres via WASM, then it opens very interesting offline scenarios with codebases which are similar on both the client and the server, for instance.

Recently, Gleam has gained more popularity, and a lot of developers (including me) are learning it. At the time of this writing, it has exceeded 14k stars on GitHub; it grew really fast for the last month.

Oh, strange that github had a date of 2016 on this one: https://github.com/gleam-lang/gleam/issues/2

I was just going by that, though I do remember checking out gleam 5 years ago or so.

Re: macros, I really do think they’re a big deal and all the other newer languages I’ve used, such as Rust have some kind of macros or powerful meta programming features.

For older languages, a few, like Ruby have enough meta programmability to make nice DSLs, but many others don’t. Given the choice, I’d much rather have Elixir/Clojure style macros than other meta-programming facilities I’ve seen so far.

I had been only following this language with some interest, I guess this was born in gitlab not sure if the creator(s) still work there. This is what I'd have wanted golang to be (albeit with GC when you do not have clear lifetimes).

But how would you differentiate yourself from https://gleam.run which can leverage the OTP, I'd be more interested if we can adapt Gleam to graalvm isolates so we can leverage the JVM ecosystem.

I don't think the implementation itself is at fault, but yes, I do think that the design of dialyzer makes it an (at times) faulty type checker. The unfortunate reality of a type checker that fails sometimes is that it makes it mostly useless because you can never trust that it'll do the job.

To be clear, I've had it fail in a function where I've literally specced that very function to return a `binary` but I'm returning an `integer` in one of the cases. This is a very shallow context but it can still fail. Now add more functions, maybe one more `case`.

I think an entire rethink of type checking on the BEAM had to be done and that's why eqWalizer[0] was created and why Elixir is looking to add an actual sound, well-developed type checker. Gleam[1] I would assume is just a Hindley-Milner system so that's completely solid. `purerl`[2] is just PureScript for the BEAM so that's also Hindley-Milner, meaning it's solid. `purerl` has some performance issues caused by it compiling down to closures everywhere but if you can pay that cost it's actually pretty fantastic. With that said my bet for the best statically typed experience right now on the BEAM would be `gleam`.

0 - https://github.com/WhatsApp/eqwalizer

1 - https://gleam.run

2 - https://github.com/purerl/purerl

You can actually have "background jobs" in very different ways in Elixir.

> I want background work to live on different compute capacity than http requests, both because they have very different resources usage

In Elixir, because of the way the BEAM works (the unit of parallelism is much cheaper and consume a low amount of memory), "incoming http requests" and related "workers" are not as expensive (a lot less actually) compared to other stacks (for instance Ruby and Python), where it is quite critical to release "http workers" and not hold the connection (which is what lead to the creation of background job tools like Resque, DelayedJob, Sidekiq, Celery...).

This means that you can actually hold incoming HTTP connections a lot longer without troubles.

A consequence of this is that implementing "reverse proxies", or anything calling third party servers _right in the middle_ of your own HTTP call, is usually perfectly acceptable (something I've done more than a couple of times, the latest one powering the reverse proxy behind https://transport.data.gouv.fr - code available at https://github.com/etalab/transport-site/tree/master/apps/un...).

As a consequence, what would be a bad pattern in Python or Ruby (holding the incoming HTTP connection) is not a problem with Elixir.

> because I want to have state or queues in front of background work so there's a well-defined process for retry, error handling, and back-pressure.

Unless you deal with immediate stuff like reverse proxying or cheap "one off async tasks" (like recording a metric), there also are solutions to have more "stateful" background works in Elixir, too.

A popular background job queue is https://github.com/sorentwo/oban (roughly similar to Sidekiq at al), which uses Postgres.

It handles retries, errors etc.

But it's not the only solution, as you have other tools dedicated to processing, such as Broadway (https://github.com/dashbitco/broadway), which handles back-pressure, fault-tolerance, batching etc natively.

You also have more simple options, such as flow (https://github.com/dashbitco/flow), gen_stage (https://github.com/elixir-lang/gen_stage), Task.async_stream (https://hexdocs.pm/elixir/1.12/Task.html#async_stream/5) etc.

It allows to use the "right tool for the job" quite easily.

It is also interesting to note there is no need to "go evented" if you need to fetch data from multiple HTTP servers: it can happen in the exact same process (even: in a background task attached to your HTTP server), as done here https://transport.data.gouv.fr/explore (if you zoom you will see vehicle moving in realtime, and ~80 data sources are being polled every 10 seconds & broadcasted to the visitors via pubsub & websockets).

The Erlang "telemetry" module can even be used "applicatively" with good uses.

An example of that is a "caching reverse proxy" in use at https://transport.data.gouv.fr/, which helps protect data producers servers from excessive load from data consumers (which we manage for them).

"External" requests come to us (via proxy.transport.data.gouv.fr) and if the response is not in cache (for a configured TTL), we forward the request as an "internal" request to the target (3rd party) server.

The proxy uses "telemetry" to generate events for these internal/external queries, without knowing how they will be consumed (https://github.com/etalab/transport-site/blob/master/apps/un...).

The main app receives those events and does what it wants, in this case upserting metrics in the database (https://github.com/etalab/transport-site/blob/master/apps/tr...).

As a result, it's easy to use LiveView to create a real-time dashboard to show these metrics (https://jumpshare.com/s/rdGtTa47CzlcgOz4jsOI - low traffic at time of posting) or generate stats for the data producers which are behind the proxy.

It's all quite natural to do because it's really baked into the runtime!

We're using on the French national access point to transportation data (http://transport.data.gouv.fr/?locale=en, source code at https://github.com/etalab/transport-site) and we're not going to switch to another stack ^_^.

Plenty of use-cases are made easy by the stack, from regular web work, API (https://transport.data.gouv.fr/swaggerui) to proxying (https://github.com/etalab/transport-site/tree/master/apps/un...) to real-time maps (https://transport.data.gouv.fr/explore), clustered maps (https://transport.data.gouv.fr/explore/gtfs-stops), XML queries building (https://transport.data.gouv.fr/tools/siri-querier?endpoint_u...)...

The maintenance story is very good too.

With ML being added (Nx/Axon etc), and mobile apps being in the works (LiveViewNative), it has become my everyday language & stack.

> Yes, this is as bad as it looks: “success” isn’t even part of the schema. It’s in the examples, but not the actual schema definition.

Having gone through a pretty heavy overhaul of an "OpenAPI" (full code in Elixir at https://github.com/etalab/transport-site/pull/3351), I stumbled on that exact type of problem!

At the scale of nginx, having automatic verification that the examples (and the output of the API in general) match the specification would be great.

At our scale, here is what really helped me go through the rework (and ensure we do not regress too easily):

- setting additionalProperties to "false" to detect key field "rot"

- using "required: [x,y,z]" on everything, and by default specify "all the property keys", with an opt-out (so that each time a developer adds a field later, it is considered mandatory, unless otherwise specified)

- use tooling during the tests: "assert_schema" (with OpenAPISpex) to ensure our API endpoints responses pass the spec (additionalProperties: false helps ensure we get an exception in case of key field rot, again!)

- even more useful: crawl our production most important endpoints and tweak the spec until everything is green (an example of useful use of Task.async_stream in Elixir, by the way) https://github.com/etalab/transport-site/pull/3351/files#dif...

It can be super frustrating for users to live with the uncertainty of the response of an API for sure, and I was happy to discover the Elixir tooling (OpenAPISpex in particular) worked so nicely once I understood what I had to do.

Very convenient to parallelise HTTP queries (and without the need to go “evented”).

One recent example where I assert that API responses match our OpenAPI specifications here, for the curious:

https://github.com/etalab/transport-site/pull/3351/files#dif...

I've been a big fan of "Mix.install" since it was released!

I believe this made me use Elixir instead of Ruby (my natural scripting language) more and more.

I use it on a regular basis for my work on https://transport.data.gouv.fr/ (which is Elixir-based and open-source), as one can see at https://github.com/etalab/transport-site/tree/master/scripts.

What I like the most is that it helps me start ideas, experiments & data analysis with their own set of dependencies (without much care of "will this impact the main application?"), store those experiments in the same repo at the main application, and maybe later promote some of those experiments to the main application source code.

Concrete examples include:

I'm one of the 3 maintainers of the French open-data transportation access point (at https://transport.data.gouv.fr/?locale=en), which runs on top of Elixir & Phoenix.

I'm not a big fan of surveys and I'm not sure I've responded to this one actually, but: my current feeling around Phoenix is that it will be my go-to framework for anything web related for the years to come, but also Elixir will be, for larger topics (ML, embedded, data-viz, scripting, etc).

There are a number of important points (to my taste) that comes out of my use of Elixir & Phoenix :

- the maintenance story has been quite good (maintenance work is one of my main line of work since year 2k, I have used many stacks, including Java, .Net, RubyOnRails etc). Upgrades and refactoring & moving code around has been quite easy overall, once you get the stuff right (using Mox etc).

- Phoenix, Ecto & Elixir are a good "generalist web framework" for a lot of use

- Compared to some stacks (non-evented Ruby & Python, for instance), having a part of your app work as a proxy for domain-specific uses, is not a problem, and does not even require you to split that part from the main app (example at https://github.com/etalab/transport-site/tree/master/apps/un..., where we proxy/cache GTFS-RT protobuf & SIRI XML feeds behind rules, adding rate-limiting & hiding target server authentication schemes)

- Similarly, anything real-time is at least initially trivial. For instance, creating this real-time view of moving vehicles (https://transport.data.gouv.fr/explore) with 70+ GTFS-RT feeds has been quite easy (PR at https://github.com/etalab/transport-site/pull/2224). The server side is like "EventMachine done right", and the live updates are broadcasted to each client via web socket. No extra server (e.g. AnyCable) or anything is needed.

From a perf/ops POV, the amount of topics you do not even have to think about is quite important, which is very nice.

Overall I can see myself sticking to this stack for the next 15 years or so, without much worries (I've been coding since 1984 as a kid, so I have a good idea to know when to keep a framework around or not :P)

You can check this gov website : https://transport.data.gouv.fr/

transport.data.gouv.fr, the transport part of the french open data portal. Source code here: https://github.com/etalab/transport-site/.

Stripe, Shopify and GitHub are still largely relying on Ruby as far as I know (and while there are reimplementations of some services in some langages, I don't think C++ or Java have been publicly mentioned often).

That said, I think one important asset of Elixir (in my view) is not the raw performance, but the overall "total cost of ownership" (including maintenance work, and software is a lot of maintenance).

Being able to simplify architectures is something that is nicely done with Elixir, actually.

If a part of an app needs to play a "proxy" role (like here https://github.com/etalab/transport-site/tree/master/apps/un...), then I just add a component to the app, and I can keep the incoming connections under hand, all while issuing external queries etc.

If there is a need to do some rich interactive dashboards, I can use LiveView.

If I need to demonstrate some simple stuff, I can use "Mix.install" to create one-off scripts.

If I need to do more data-science, I can tap into LiveBook, VegaLite etc.

All this with a small team or as a solo developer, is quite great, much more than raw performance, in my eyes.