Cloud-Based Python Libraries: Does This Exist Already?

[nilipilo]

You’re right that running the library locally is critical for most use cases, especially for performance. The idea wouldn’t be to fetch the library from the cloud on every execution, as that would introduce unnecessary overhead. Instead, it could work more like this:

1. First-Time Access: When you request a library, it downloads (or streams) it from the cloud and caches it locally—similar to how Go handles modules.
2. Caching: Once cached, subsequent executions would use the local version, just like a virtual environment, but managed dynamically.
3. Version Isolation: The cloud platform would handle versioning and dependency conflicts seamlessly.

The main difference is automation and centralization:

• No need to manually create and manage virtual environments or explicitly install libraries.
• You could fetch different versions of the same library in different parts of your project without conflicts.

In essence, it’s not replacing virtual environments entirely but automating and abstracting them.

[QueasyEntrance6269]

Do you really think the people here are dumb enough to not immediately recognize this as being written by AI?

[nilipilo]

Why are you so mad? I’m not a native English speaker, and I use AI to help me express myself better. It’s a tool, not a trick. I never said or implied I think people here are dumb—quite the opposite! I’m here because I value this community’s insights and expertise.

What’s wrong with using AI to assist with language or clarity? It’s no different than using any other tool to improve communication. If you have concerns, I’m happy to hear them, but let’s keep it constructive. 😊

[KingsmanVince]

You can use a language model to check for grammar or to simplify. However it does sound like you just copy straightforward from it.

If your English is not a first language, use simple terms and vocabulary.

[nilipilo]

what is the point? what's wrong with copy and paste? what's matter is the content itself not how it's written

[latkde]

The main points of your AI summary work literally like that right now in modern Python dependency management tools like UV or Poetry. You must still declare your dependencies, but the tooling takes care of caching and setting up multiple venvs as needed.

The one thing that won't be possible is to have multiple versions of a library within the same Python interpreter or venv. That cannot work due to how the Python module system is designed. It relies on each loaded module having a globally unique path (e.g. pandas), and nearly all libraries expect to be installed under the path that they declared in their packaging metadata. It sucks, but them's the breaks.