tidyquery VS ecto

tidyquery

> SQL is a perfect language for analytics.

Slightly off topic, but I strongly agree with this statement and wonder why the languages used for a lot of data science work (R, Python) don't have such a strong focus on SQL.

It might just be my brain, but SQL makes so much logical sense as a query language and, with small variances, is used to directly query so many databases.

In R, why learn the data.tables (OK, speed) or dplyr paradigms, when SQL can be easily applied directly to dataframes? There are libraries to support this like sqldf[1], tidyquery[2] and duckdf[3] (author). And I'm sure the situation is similar in Python.

This is not a post against great libraries like data.table and dplyr, which I do use from time to time. It's more of a question about why SQL is not more popular as the query language de jour for data science.

[1] https://cran.r-project.org/web/packages/sqldf/index.html

[2] https://github.com/ianmcook/tidyquery

[3] https://github.com/phillc73/duckdf

To ruin the party, deterministic UUID generation is exactly what UUID v5 is designed for. And since Ecto does not validate UUIDs against their specs, you might as well use uuid again and do:

To me this looks a lot like ecto https://github.com/elixir-ecto/ecto

Is there a significant difference?

Ecto database driver use-case

When it comes to building microservices, Go has the advantage of being easier to deploy and tighter integration with gRPC. On the other hand, Elixir will provide a more expressive layer to communicate with the database through Ecto.

May I ask why CouchDB though? Is it for the offline support?

Phoenix comes with its own database tool called Ecto[0] which is excellent, and it uses Postgres by default. If you're not intended to leverage CouchDB for offline support you should go Postgres without a second thought.

That said, I'm also curious about how to implement offline support with Phoenix in a nice and trivial way.

[0] https://github.com/elixir-ecto/ecto

The best would be to set aside at least 40 minutes of study a day. Being 20 minutes focused on the core of the language, solving problems and a website that can help you a lot and exercism. Another 20 minutes some of the core frameworks like: Phoenix, Ecto, Enum

This is a testiment to the value and productivity of Phoenix, but the resulting code is just basic CRUD. The views are tied 1:1 with their database-backed Ecto schemas. One thing to note is that Phoenix generates DDD-style contexts. This is unlike Rails, which would produce a typical ActiveRecord sprawl: bloated models directly being accessed and lazily queried across the entire application.

Ecto uses prewalk to count the number of interpolations within a given expression.

I've used my share of data access libraries and patterns (e.g. hibernate, activerecord, ecto, ...). The only time I've been happy is when I use raw SQL for non-dynamic SQL and a lightweight query builder for everything else.

I feel like I always run into some thing that at best isn't intuitive to express/read and at worse, cannot be expressed. If I remember correctly, when I was learning Elixir/Ecto, https://github.com/elixir-ecto/ecto/issues/1616 issue and the lack of lateral join support caused me issues.

Want to create a user?

"insert into users (id, name, status) values ($1, $2, $3)"

Our query builder takes pretty raw SQL fragments:

    q = Query.new()