windmill
ploomber
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windmill | ploomber | |
---|---|---|
86 | 121 | |
8,305 | 3,355 | |
4.6% | 1.1% | |
10.0 | 7.8 | |
4 days ago | about 1 month ago | |
Svelte | 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.
windmill
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Show HN: Strada – Cloud IDE for Connecting SaaS APIs
Look very similar to the script builder portion of https://github.com/windmill-labs/windmill, but not open-source, not self-hostable, and without open-source integrations (https://hub.windmill.dev/)
disclaimer: I'm founder of ^
- Ask HN: Is There a Zapier for APIs?
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Postgres as Queue
If you need a job queue on Postgres, https://windmill.dev provide an all-integrated developer platform with a Pg queue at its core that support jobs defined in python/typescript/sql
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A list of SaaS, PaaS and IaaS offerings that have free tiers of interest to devops and infradev
windmill.dev - Windmill is an open-source developer platform to quickly build production-grade multi-step automation and internal apps from minimal Python and Typescript scripts. As a free user, you can create and be a member of at most three non-premium workspaces.
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Airplane acquired by Airtable and is shutting down
For an alternative to airplane.dev, you can checkout Windmill.
https://github.com/windmill-labs/windmill
"Open-source developer infrastructure for internal tools (APIs, background jobs, workflows and UIs). Self-hostable alternative to Airplane, Pipedream, Superblocks and a simplified Temporal with autogenerated UIsm and custom UIs to trigger workflows and scripts as internal apps.
Scripts are turned into sharable UIs automatically, and can be composed together into flows or used into richer apps built with low-code. Supported script languages supported are: Python, TypeScript, Go, Bash, SQL, and GraphQL. "
If you search HN, you'll find the creator of Windmill comment on comparisons to airplane.dev:
https://hn.algolia.com/?dateRange=all&page=0&prefix=false&qu...
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Pipe Dreams: The life and times of Yahoo Pipes
https://windmill.dev is a self-hostable OSS alternative to pipedream
(disclaimer: I'm founder)
- Deno Cron
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Show HN: Windmill – fastest open-source workflow engine – the how
While most of the software is under the AGPLv3, the Commercial License section of the README [0] implies that the company takes on a fairly broad interpretation of the AGPL.
In particular, the line "[...] to build a feature on top of Windmill, to comply with AGPLv3 your product must be AGPLv3 [...]" seems to imply the company aligns with the stance taken by Google and other companies: that even calling the application via API is enough to trigger copyleft [1].
This implies that if I were to build a sign-up form that triggers a Windmill workflow in the backend, my entire application would either need to be AGPLv3 or I would need a commercial license.
That's perfectly reasonable, as it means any non-AGPL use will have to contribute back to Windmill via a commercial license. However, it does mean positioning this as an "Fully Open-source" alternative to Airflow is only technically correct. This is much closer in practice to "source available" than how most developers would think as "open source".
If this isn't how Windmill wants their license interpreted, I highly encourage clarifying things.
[0] https://github.com/windmill-labs/windmill#commercial-license
Yes it goes in that direction, however note that you can already do this in a not too hard way.
Our openflow spec is both open-source and has a full openapi definition: https://github.com/windmill-labs/windmill/blob/main/openflow...
you can use that to generate client sdks in any languages and build your own dag with it. That's what one of our customer did building a reactflow to openflow library: https://github.com/Devessier/reactflow-to-windmill
It's not as good as the decorator way but we move fast and if you still have interest for it we could prioritize it (and ask for feedbacks :))
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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Ploomber Cloud - Parametrizing and running notebooks in the cloud in parallel
We started with an open-source framework to help data practitioners make their work reproducible. However, after months of building and learning from our community, we realized that many needed help with the setup: getting Python installed, getting dependencies, running experiments locally, etc.
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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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"Do I need to know {insert advanced math} to get a Data Science job?" [Rant]
btw, you can export Ploomber to Argo and Airflow!
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Running Jupyter notebooks in parallel
As a second option, we will use Ploomber with serial execution, which also has a Python API that allows us to execute different notebooks using the NotebookRunner function:
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How do you deal with parallelising parts of an ML pipeline especially on Python?
I also recommend checking ploomber out, this open source can help you build code as templates, parallelize it and parameterize it. There are also some reporting and debugging tools in there!
What are some alternatives?
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.
papermill - 📚 Parameterize, execute, and analyze notebooks
dagster - An orchestration platform for the development, production, and observation of data assets.
dvc - 🦉 ML Experiments and Data Management with Git
argo - Workflow Engine for Kubernetes
MLflow - Open source platform for the machine learning lifecycle
automatisch - The open source Zapier alternative. Build workflow automation without spending time and money.
nbdev - Create delightful software with Jupyter Notebooks
plasmic - Visual builder for React. Build apps, websites, and content. Integrate with your codebase.
budibase - Budibase is an open-source low code platform that helps you build internal tools in minutes 🚀
docker-airflow - Docker Apache Airflow
fastapi-dramatiq-data-ingestion - Sample project showing reliable data ingestion application using FastAPI and dramatiq