RStudio Server
ploomber
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RStudio Server | ploomber | |
---|---|---|
54 | 121 | |
4,545 | 3,369 | |
1.5% | 0.9% | |
9.9 | 7.8 | |
7 days ago | 17 days ago | |
Java | Python | |
GNU General Public License v3.0 or later | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
RStudio Server
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RStudio: Integrated development environment (IDE) for R
This particular issue should be resolved in the latest daily builds of RStudio. The underlying issue here was a conda patch included in the conda-provided builds of R, which interfered with the way RStudio attempted to load R. Please see https://github.com/rstudio/rstudio/issues/13184#issuecomment... for more details.
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Random error to subset dataframe... no clue why
It is a bug that was introduced in RStudio 2023.06.0 Build 421. See Error with 'cacheKey' in .rs.WorkingDataEnv and .rs.CachedDataEnv. The current advice is to ignore or add options(rstudio.help.showDataPreview = FALSE) to your ~/.Rprofile ... so RStudio can ignore it for you.
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Version 5.4.0
A quick google for details from other app: https://github.com/rstudio/rstudio/wiki/Writing-Good-Feature-Requests :)
- R markdown knit to html window size
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FPS drops while using Anki on Win11
solution found here: https://github.com/rstudio/rstudio/issues/9367
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RStudio is painfully slow when connected to my company's VPN
u/acemachine123, if you’re using Rmarkdown or Rprojects over a network drive, connected by VPN, it’s going to be slow like u/ThatDeadDude said. Best thing you can do is thumbs up the issue here https://github.com/rstudio/rstudio/issues/10417 and use an Rscript file instead.
- How do I easily create a Flatpak from 2 sources?
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Fonts: cannot select installed font
Hey! I can not select the Noto Sans Mono font in RStudio's Editor Font options, despite it being installed in my system, as you can see in the picture. RStudio only offers me "Noto Color Emoji" instead. When looking for this online, I only found this: https://github.com/rstudio/rstudio/issues/9512, but I am not sure if this really a related issue. Or does RStudio not support TrueType fonts? I can't find anything about this after a quick search
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Updated RStudio to the latest version and I have an annoying problem with the file explorer
Next (2023.03) changelog - https://github.com/rstudio/rstudio/blob/main/version/news/NEWS-2023.03.0-cherry-blossom.md .
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After reinstalling RStudio, the dark mode is not working properly anymore. Do you have any tips on how I can fix it?
for example in this post they have dark menus aswell
ploomber
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Show HN: JupySQL – a SQL client for Jupyter (ipython-SQL successor)
- One-click sharing powered by Ploomber Cloud: https://ploomber.io
Documentation: https://jupysql.ploomber.io
Note that JupySQL is a fork of ipython-sql; which is no longer actively developed. Catherine, ipython-sql's creator, was kind enough to pass the project to us (check out ipython-sql's README).
We'd love to learn what you think and what features we can ship for JupySQL to be the best SQL client! Please let us know in the comments!
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Runme – Interactive Runbooks Built with Markdown
For those who don't know, Jupyter has a bash kernel: https://github.com/takluyver/bash_kernel
And you can run Jupyter notebooks from the CLI with Ploomber: https://github.com/ploomber/ploomber
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Rant: Jupyter notebooks are trash.
Develop notebook-based pipelines
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Who needs MLflow when you have SQLite?
Fair point. MLflow has a lot of features to cover the end-to-end dev cycle. This SQLite tracker only covers the experiment tracking part.
We have another project to cover the orchestration/pipelines aspect: https://github.com/ploomber/ploomber and we have plans to work on the rest of features. For now, we're focusing on those two.
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New to large SW projects in Python, best practices to organize code
I recommend taking a look at the ploomber open source. It helps you structure your code and parameterize it in a way that's easier to maintain and test. Our blog has lots of resources about it from testing your code to building a data science platform on AWS.
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A three-part series on deploying a Data Science Platform on AWS
Developing end-to-end data science infrastructure can get complex. For example, many of us might have struggled to try to integrate AWS services and deal with configuration, permissions, etc. At Ploomber, we’ve worked with many companies in a wide range of industries, such as energy, entertainment, computational chemistry, and genomics, so we are constantly looking for simple solutions to get them started with Data Science in the cloud.
- Ploomber Cloud - Parametrizing and running notebooks in the cloud in parallel
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Is Colab still the place to go?
If you like working locally with notebooks, you can run via the free tier of ploomber, that'll allow you to get the Ram/Compute you need for the bigger models as part of the free tier. Also, it has the historical executions so you don't need to remember what you executed an hour later!
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Alternatives to nextflow?
It really depends on your use cases, I've seen a lot of those tools that lock you into a certain syntax, framework or weird language (for instance Groovy). If you'd like to use core python or Jupyter notebooks I'd recommend Ploomber, the community support is really strong, there's an emphasis on observability and you can deploy it on any executor like Slurm, AWS Batch or Airflow. In addition, there's a free managed compute (cloud edition) where you can run certain bioinformatics flows like Alphafold or Cripresso2
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Saving log files
That's what we do for lineage with https://ploomber.io/
What are some alternatives?
JupyterLab - JupyterLab computational environment.
Kedro - Kedro is a toolbox for production-ready data science. It uses software engineering best practices to help you create data engineering and data science pipelines that are reproducible, maintainable, and modular.
Code-Server - VS Code in the browser
papermill - 📚 Parameterize, execute, and analyze notebooks
vscode-R - R Extension for Visual Studio Code
dagster - An orchestration platform for the development, production, and observation of data assets.
Eclipse Che - Kubernetes based Cloud Development Environments for Enterprise Teams
dvc - 🦉 ML Experiments and Data Management with Git
Hakatime - Wakatime server implementation & analytics dashboard
argo - Workflow Engine for Kubernetes
ICEcoder - Browser code editor awesomeness
MLflow - Open source platform for the machine learning lifecycle