Jupyter Scala VS pyright

Checkout almond

What about https://github.com/alexarchambault/plotly-scala and https://almond.sh/

I use Almond in JupyterLab, which has pretty solid code completion. In IntelliJ, you can create a scratch sc file and run lines of it in the Scala REPL. That's really convenient for code completion and I normally will use that when I'm testing something from a specific project.

The UI part. There's only the scala REPL. I think the closest is a scala kernel for Jupyter notebooks, check this out: https://almond.sh/

We have used https://almond.sh/ to create a Spark SQL interpreter using Jupyter Notebooks - plus a whole lot more which you can see here: https://arc.tripl.ai/tutorial

After seeing many companies writing ETL using code we decided it was too hard to manage at scale so provided this abstraction layer - which is heavily centered around expressing business logic in SQL - to standardise development (JupyterLab) and allow rapid deployments.

Pyright is a fast type checker meant for large Python source bases. It can run in a “watch” mode and performs fast incremental updates when files are modified.

However, I made it faster for my use-case by changing some settings. Neovim allows to have these settings in the setup function for LSP. I was trying to figure out how do I change these settings with doom emacs. Pyright docs suggest to have these settings in pyrightconfig.json.

Not exactly what you are looking for but maybe useful to others.

https://github.com/microsoft/pyright/blob/main/docs/mypy-com...

You can use pyright instead[0]. It is the FOSS version of pyright, but having some features missing.

[0]: https://github.com/microsoft/pyright

Unfortunately, pyright explicitly stated that they are not interested in inlay hints or other language server features, that those will only be added to pylance. That's why I added it myself instead of submitting a pull request to pyright. See https://github.com/microsoft/pyright/issues/4325

return { -- add pyright to lspconfig { "neovim/nvim-lspconfig", ---@class PluginLspOpts opts = { ---@type lspconfig.options servers = { -- Listed servers will be automatically loaded to buffers jsonls = { settings = { json = { format = { enable = true, }, }, validate = { enable = true }, }, }, pyright = { settings = { python = { analysis = { -- https://github.com/microsoft/pyright/blob/main/docs/settings.md autoSearchPaths = false, useLibraryCodeForTypes = true, diagnosticMode = "openFilesOnly", }, }, }, }, }, -- Add folding capability to use LSP for ufo plugin capabilities = { textDocument = { foldingRange = { dynamicRegistration = false, lineFoldingOnly = true, }, }, }, }, }, }

[{ "resource": "/Documents/Coding/VSCode/Projects/Photoeditor/PhotoEditor.py", "owner": "_generated_diagnostic_collection_name_#0", "code": { "value": "reportMissingModuleSource", "target": { "$mid": 1, "external": "https://github.com/microsoft/pyright/blob/main/docs/configuration.md#reportMissingModuleSource", "path": "/microsoft/pyright/blob/main/docs/configuration.md", "scheme": "https", "authority": "github.com", "fragment": "reportMissingModuleSource" } }, "severity": 4, "message": "Import \"requests\" could not be resolved from source", "source": "Pylance", "startLineNumber": 2, "startColumn": 8, "endLineNumber": 2, "endColumn": 16 }]

I don't use astro, but you can configure pyright by using a pyrightconfig.json or directly in the LSP configuration.

I prefer jedi over pyright as pyright has crippled documentation support outside of VSCode. I also found jedi is make correct suggestions based on inferred type in some situations where pyright would need type annotation to provide completions, pyright is significantly faster though. Jedi with mypy and flake8 is comparable to pyright I think, but unfortunately mypy wasn't working over tramp. Also isort wasn't working over tramp, but jedi, black, importmagic and flake8 all worked.