django-stubs VS prql

Pyright doesn't work with Django, as Django's so dynamic that it requires a plugin to infer all types correctly. Sadly, even mypy with plugins is a mess to get set up in vscode, especially if you want it to use the same config as you use for ci checks from the command line.

We use mypy + [django-stubs](https://github.com/typeddjango/django-stubs) (in a huge Django + drf project at day job) which includes a plugin for mypy allowing it to recognize all reverse relations and manager methods. Mypy is still really rough around the edges. The cli args are poorly documented, and how they correspond to declarations in a mypy.ini / pyproject.toml is mysterious. Match-statements still have bugs even a year after release. Exclusion of untyped / partially typed files and packages we've had to solve with grep filtering mypy's output for our whitelisted set of files, as it's been unable to separate properly between errors you care about (in your own codebase) and errors in others code (dependencies, untypable dynamic python packages etc).

The largest issue IMO is that mypy tried to adapt a java / OOP style way of type system onto python, instead of recognizing the language's real power within duck typing and passing structural types around. Typescript chose the right approach here, modelling javascript the way it is actually written, favoring structural over nominal typing, instead of the archaic and now left-behind way of Java-style OOP that has influenced mypy.

There was a recently accepted PEP which allowed for limited dataclass transforms, enough to cover the @attr.s usecase for both mypy and pyright, but nowhere near expressive enough to cover django's models and ORM sadly. It's probably impossible / undesirable to allow for such rich plugins, so i see the future for proper pluginless typing to be more akin to how pydantic / normal dataclasses solve typing, by starting with a specification of the types, deriving its runtime implementation, instead of plugins having to reverse the type representation of a custom DSL.

You can annotate the manager and get some typing help in the editor. And there’s django-stubs which helps a little when running mypy. It’s not as good as pycharm though.

https://github.com/typeddjango/django-stubs/tree/master

> Yes, there are type stubs for these libraries but they’re either forced to be more strict, preventing use of dynamism, or opt for being less strict but allowing you to use all the library features, at the cost of safety.

There are type stubs for Django that somewhat avoid these compromises: https://github.com/typeddjango/django-stubs

To be able to do this they have to use a Mypy plugin though. And even then it's still far from perfect.

Mypy together with this plug-in gives you typing for django. https://github.com/TypedDjango/django-stubs

Have you looked at stubs for Django?

> I completely attribute this to SQL being difficult or "backwards" to parse. I mean backwards in the way that in SQL you start with what you want first (the SELECT) rather than what you have and widdling it down.

> The turning point for me was to just accept SQL for what it is.

Or just write PRQL and compile it to SQL

https://github.com/PRQL/prql

Hey HN! We’ve built Pretzel, an open-source data exploration and visualization tool that runs fully in the browser and can handle large files (200 MB CSV on my 8gb MacBook air is snappy). It’s also reactive - so if, for example, you change a filter, all the data transform blocks after it re-evaluate automatically. You can try it here: https://pretzelai.github.io/ (static hosted webpage) or see a demo video here: https://www.youtube.com/watch?v=73wNEun_L7w

You can play with the demo CSV that’s pre-loaded (GitHub data of text-editor adjacent projects) or upload your own CSV/XLSX file. The tool runs fully in-browser—you can disconnect from the internet once the website loads—so feel free to use sensitive data if you like.

Here’s how it works: You upload a CSV file and then, explore your data as a series of successive data transforms and plots. For example, you might: (1) Remove some columns; (2) Apply some filters (remove nulls, remove outliers, restrict time range etc); (3) Do a pivot (i.e, a group-by but fancier); (4) Plot a chart; (5) Download the chart and the the transformed data. See screenshot: https://imgur.com/a/qO4yURI

In the UI, each transform step appears as a “Block”. You can always see the result of the full transform in a table on the right. The transform blocks are editable - for instance in the example above, you can go to step 2, change some filters and the reactivity will take care of re-computing all the cells that follow, including the charts.

We wanted Pretzel to run locally in the browser and be extremely performant on large files. So, we parse CSVs with the fastest CSV parser (uDSV: https://github.com/leeoniya/uDSV) and use DuckDB-Wasm (https://github.com/duckdb/duckdb-wasm) to do all the heavy lifting of processing the data. We also wanted to allow for chained data transformations where each new block operates on the result of the previous block. For this, we’re using PRQL (https://prql-lang.org/) since it maps 1-1 with chained data transform blocks - each block maps to a chunk of PRQL which when combined, describes the full data transform chain. (PRQL doesn’t support DuckDB’s Pivot statement though so we had to make some CTE based hacks).

There’s also an AI block: This is the only (optional) feature that requires an internet connection but we’re working on adding local model support via Ollama. For now, you can use your own OpenAI API key or use an AI server we provide (GPT4 proxy; it’s loaded with a few credits), specify a transform in plain english and get back the SQL for the transform which you can edit.

Our roadmap includes allowing API calls to create new columns; support for an SQL block with nice autocomplete features, and a Python block (using Pyodide to run Python in the browser) on the results of the data transforms, much like a jupyter notebook.

There’s two of us and we’ve only spent about a week coding this and fixing major bugs so there are still some bugs to iron out. We’d love for you to try this and to get your feedback!

> Looks like PRQL doesn't have a Go library so I guess they just really wanted something in Go?

There's some C bindings and the example in the README shows integration with Go:

https://github.com/PRQL/prql/tree/main/prqlc/bindings/prqlc-...

Can someone tell me why PRQL is better? I went here: https://github.com/PRQL/prql

It looks nice, but what's the strengths compared to SQL?

PRQL [1] is a compile-to-SQL relational querying language that puts FROM first.

[1] https://prql-lang.org

https://prql-lang.org/ might be an answer for this. As a cross-database pipelined language, it would allow RAG to be intermixed with the query, and the syntax may(?) be more reliable to generate