lowdefy VS postgresql-replicant

I'm really enjoying reading through the docs and the tutorial. We've created Lowdefy, a config web-stack which makes it really simple to build quite advanced web apps. We're writing everything in YAML, but it has it's limitations, specifically when doing config type checking and IDE extensions that go beyond just YAML.

I've been looking for a way to have typed objects in the config to do config suggestions and type checking.. PKL looks like it can do this for us. And with the JSON output we might even be able to get there with minimal effort.

Is there anyone here with some PKL experience that would be willing to answer some technical questions re the use of PKL for more advanced, nested config?

See Lowdefy:

https://lowdefy.com/

https://github.com/lowdefy/lowdefy

Awsome! With Lowdefy we tried to build a low-code framework that works like code. We’ve developed a schema in which to define applications and we’ve built all kinds of apps for enterprise customers. Massive, advanced CRM systems, call centre solutions, ticketing systems, a light MRP, all kinds of survey apps and so many dashboards. Even our docs and our website are Lowdefy apps!

Give Lowdefy a try and reach out it you have any questions or want to see what is possible :) (We need to invest a lot more into content and examples, bootstapping is a grind!)

https://github.com/lowdefy/lowdefy

Also add Lowdefy onto the list https://github.com/lowdefy/lowdefy

co-founder here :)

100% this. And yes, good documentation takes a lot of investment but it pays off like compound interest. But with that done, it becomes even more important not to pull the carpet for no good reason, you are building a tower and documentation is at the foundation.

We’ve built Lowdefy [1] as an open source project and documented it with all effort, 200 pages of docs. I often forget why or how something works and then jump to the docs. This investment keeps on paying of as we use Lowdefy to build customer apps, new devs in the team typically take less than two week to get up to speed and start making contributions, the sharp ones, just a two or three days.

This year, we’re extended our documentation onto customer apps aswell, with flow diagrams, state machine definitions, detailed field level explication schema definitions, and end user test procedures. The key here for this documentation is detail. It should be easier to reach for the docs and the the answer, than to dive in the code and interpret it.

1 - https://github.com/lowdefy/lowdefy

https://github.com/lowdefy/lowdefy Co-Founder here.

Check out https://lowdefy.com/ they even have a sample survey app as one of their examples.

You can build an app that would do this

Lowdefy is a low code tool that uses AG Grid as a block component, allowing you to create apps which render data in AG Grid without a lot of coding knowledge. There is a Lowdefy example using AG Grid here.

Shameless plug, also check out Lowdefy - https://github.com/lowdefy/lowdefy

I’m also going to jump in here and say try Lowdefy https://github.com/lowdefy/lowdefy - co-founder here.

We take a different angle and believe that low code should still work like code. We focus on a developer first approach.

You can use a library like https://github.com/agentultra/postgresql-replicant or similar to hook in a data plane and use PostgREST as a data plane.

Your business logic works on the event stream that comes from the WAL.

I wrote postgresql-replicant [0] in order to do this. It’s not a novel idea. It lets you read the logical replication stream.

On top of this library you can do all sorts of things: replicate data to Kafka or SQS, write a web socket server to publish changes to clients, etc.

[0] https://github.com/agentultra/postgresql-replicant

https://github.com/agentultra/postgresql-replicant — stream delta changes from a PostgreSQL database. Not a novel concept or implementation but this library doesn’t exist in Haskell and that’s a shame because Haskell has lots of great libraries for working with streams.

https://github.com/agent ultra/DataVersion — type-directed data migration library. I needed to migrate some data in a document database that had no schema with years of data in it to a format that had a schema. I leveraged some other stuff to achieve it but this library was a key piece to being confident that the transformations were correct and complete. Migrated the database and backfill it with a Lambda function using this library.

Those are just the most recent ones.

On my stream at https://twitch.tv/agentultra I've been working on a library to stream changes out of a PostgreSQL database. We've had to figure out how to use low-level libpq bindings, concurrency primitives, serializing and deserializing binary messages, etc. You can find the library here: https://github.com/agentultra/postgresql-replicant

You can star the repo and report issues at: https://github.com/agentultra/postgresql-replicant -- new contributors are welcome! I'm still working out a contribution guide, it's still super early on the project. I can be found here and on the FP Slack (https://fpchat-invite.herokuapp.com/) and on the FP Zulip (https://funprog.zulipchat.com)