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Looks interesting! It's not obvious to me on the website what the pricing or licensing situation is with DBSnapper. How does that work? Thanks!


I added the pricing to the homepage, but also willing to discuss a custom arrangement as well. Right now you can use the Agent in standalone mode for free. I may choose to limit some of the features in the future but for now, I'd love for anyone to try it out and give feedback.


I will be adding that today, but the DBSnapper cloud is billed per month / per user. I'm also open to exploring a site licensing agreement that would work for you / your team.

Get in touch: joe@dbsnapper.com if you want to discuss!


Very excited to hear this! Congrats!


Obviously there is no actual model. ChatGPT is just tens of thousands of people writing responses to user's queries in realtime.


Would the licensing of Grist allow for building widgets/components to use it in dashboard tools like Streamlit, Jupyter, or Holoviz's Panel? Looks cool!


Pandas, Django, and Flask.


I’ve found the Python Speed [1] site an excellent resource for the quirks of working with Python in containers for data science use cases.

[1] https://www.pythonspeed.com


I've been wishing that JetBrains and Posit (nee RStudio) would adopt the devcontainer standard, but then I just read this article [1] about how MSFT is using VS Code's weird mix of open-source and proprietary components to fracture the market and ensure that any competitors who try to build off of VS Code are at a permanent disadvantage. Now I'm having second thoughts.

Devcontainers are a good example of their strategy. VS Code's source code is open source, but the devcontainers extension is not [2] and alternative vscode-in-the-browser providers are not able to use the devcontainers extension as they're not allowed to use the official VS Code extension marketplace.

[1] https://ghuntley.com/fracture/ [2] https://twitter.com/castrojo/status/1671544329402302464?s=20


I'm kind of obsessed with this space and have spent way too long setting up VS Code and RStudio IDEs on my homelab.

One area I struggle with when thinking about building container-based development environments is the best way to avoid mixing in your IDE specific dependencies with your project dependencies. I think some of the commercial tools do this, but I haven't gotten in set up well in my homelab.

I just came across two articles by a former GitPod employer who moved to Coder (these are the two main providers of open-source VS Code in the browser solutions). They're both really interesting.

The first is on how effectively Microsoft has used VS Code to fracture the market place to their advantage by strategically open-sourcing parts of VS Code while keeping many of its best features proprietary (Pylance, the python language server is a good example of this). https://ghuntley.com/fracture/

The second article is about why he thinks Coder's strategy is more promising than GitPod's prompting him to go work for them. It's not as detailed, but it touches on some of the parts of container-based development environments that I've found overly limiting. https://ghuntley.com/integrate/


Why does “pip install gcc” keep failing then? ;)

Conda isn’t perfect but takes on a lot of problems that pip doesn’t deal with at all. Regular conda is really slow these days but you can use mamba instead or just configure conda to use the libmamba solver and it’s much nicer.

The folks at prefix.dev seem to be building some pretty cool drop in replacements for conda too.


If you use conda there are extensions that can help with this by automatically registering any available conda environments that include ipykernel in your Jupyter Lab environment.

nb_conda_kernels is pretty reliable but not actively maintained. Gator from the mamba folks is new and still a bit rough around the edges but looks like it will be pretty slick eventually.

https://github.com/Anaconda-Platform/nb_conda_kernels

https://github.com/mamba-org/gator


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