elyra
jupyterlab-lsp
| elyra | jupyterlab-lsp | |
|---|---|---|
| 2 | 17 | |
| 1,773 | 1,732 | |
| 1.7% | 2.7% | |
| 6.4 | 9.4 | |
| 8 days ago | 9 days ago | |
| Python | TypeScript | |
| Apache License 2.0 | BSD 3-clause "New" or "Revised" License |
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.
elyra
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Introducing Elyra pipelines with custom component support
The Elyra open source project for JupyterLab aims to simplify common data science tasks. Its most popular feature is the Visual Pipeline Editor, which is used to create pipelines without the need for coding. You can run these pipelines in JupyterLab or on Kubeflow Pipelines or Apache Airflow.
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What's new in Elyra 2.0
During the past year we have received many suggestions and feedback from users like you. We appreciate your input and encourage you to stay involved. Open GitHub issues, reach out on gitter, post in our new forum, or join our weekly community meeting.
jupyterlab-lsp
- Does Jupyter labs or jupyter notebook have a way to expose python (or C++) objects?
- [D] Why is no one talking about the disadvantages of Colab ?
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Is there anything like a running Jupyter Kernel LSP?
I've recently seen JupyterLab LSP that bring the static analysis aspect of LSP to the notebook, and been wondering if there is anything similar that try to bridge a running kernel back into Neovim.
- Improving Jupyter Lab code entry and editing - recommendations?
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Alternatives to Rstudio
JupyterLab is optimised for handling R, Python and Julia. Code intelligence-wise it requires installing jupyterlab-lsp to get all the best features.
- Good examples of well formatted Jupyter notebooks?
- Jupyterlab-Lsp: Coding Assistance for JupyterLab Using Language Server Protocol
- IDE for data scientists
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Best debugging tool for python
Pylance is really a great LSP in VS Code and it's pretty fast, and Jupyter Lab has an LSP that is also great depending on your use case. VS Code has remote host support for Docker, VMs, etc. depending on what your plans are.
- JupyterLab LSP 3.8 (coding assistance, better autocompletion) released
What are some alternatives?
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
polynote - A better notebook for Scala (and more)
sagemaker-run-notebook - Tools to run Jupyter notebooks as jobs in Amazon SageMaker - ad hoc, on a schedule, or in response to events
Spyder - Official repository for Spyder - The Scientific Python Development Environment
argo - Workflow Engine for Kubernetes
ansible-language-server - 🚧 Ansible Language Server codebase is now included in vscode-ansible repository
ipyflow - A reactive Python kernel for Jupyter notebooks.
ydata-profiling - 1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.
airflow-docker - Source code of the Apache Airflow Tutorial for Beginners on YouTube Channel Coder2j (https://www.youtube.com/c/coder2j)
julia-snail - An Emacs development environment for Julia
debugger - A visual debugger for Jupyter notebooks, consoles, and source files
jupyter-black - Black formatter for Jupyter Notebook