Ploomber Alternatives

ploomber reviews and mentions

• Show HN: JupySQL – a SQL client for Jupyter (ipython-SQL successor)
  2 projects | news.ycombinator.com | 6 Dec 2023

  - 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!

• Runme – Interactive Runbooks Built with Markdown
  7 projects | news.ycombinator.com | 24 Aug 2023

  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

• Rant: Jupyter notebooks are trash.
  6 projects | /r/datascience | 24 Jan 2023

  Develop notebook-based pipelines

• Who needs MLflow when you have SQLite?
  5 projects | news.ycombinator.com | 16 Nov 2022

  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.

• New to large SW projects in Python, best practices to organize code
  1 project | /r/Python | 11 Nov 2022

  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.

• A three-part series on deploying a Data Science Platform on AWS
  1 project | /r/dataengineering | 4 Nov 2022

  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
  3 projects | /r/IPython | 3 Nov 2022
• Is Colab still the place to go?
  1 project | /r/deeplearning | 2 Nov 2022

  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!

• Alternatives to nextflow?
  6 projects | /r/bioinformatics | 26 Oct 2022

  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

• Saving log files
  1 project | /r/docker | 26 Oct 2022

  That's what we do for lineage with https://ploomber.io/

• A note from our sponsor - SaaSHub
  www.saashub.com | 13 May 2025

  SaaSHub helps you find the best software and product alternatives Learn more →