Replies: 6 comments 7 replies
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@kunwp1 Thanks. If possible, it will be good to include a diagram visualize these two options. |
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I created a prototype of the plugin in my personal repository: https://github.com/kunwp1/texera-r-plugin I suggest the following plan:
In parallel, we have an ongoing effort to support multiple ports for R UDF operators. Once the repository is in its final location and the integration is in place, we can proceed with that work. Let me know if you have any comments! |
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I agree with this plan. @Yicong-Huang What do you think? |
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I am OK for both methods. The option 1 is kind of short term, easy to implement, but harder to maintain. The option 2 is more standard, in main texera code we could detect if the r-plugin library is installed or not, and only invoke R UDF if it is installed. I am not sure if we want to publish it to pypy though: I'd prefer to publish pytexera first if that's a goal. We could make it installable with |
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Sounds good. I will rename the repo to |
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One quick question about the license for the |
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We're moving R language support to a separate optional plugin due to licensing requirements. We chose a standalone library approach over patch files for better maintainability and user experience.
The Problem
rpy2for R supportrpy2is licensed under GPLv2Two Options Evaluated
Option 1: Patch Files ❌
Create a separate repo with patch files that users apply to main Texera.
Why we rejected this:
Option 2: Standalone Plugin ✅ CHOSEN
Create a pip-installable Python package in a separate repository.
# Installation pip install git+https://github.com/Texera/texera-r-plugin.gitWhy we chose this:
Key Points
Performance
No degradation. The plugin runs in-process, same as before:
Backwards Compatibility
Existing R workflows work without modification. Only change: users must install the plugin.
Migration
For R users:
For non-R users:
No action needed. Plugin is optional.
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