Write maintainable, production-ready pipelines using Jupyter or your favorite text editor. Develop locally, deploy to the cloud. ☁️ (by ploomber)

Ploomber Alternatives

Similar projects and alternatives to ploomber

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a better ploomber alternative or higher similarity.

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Reviews and mentions

Posts with mentions or reviews of ploomber. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-08-08.
  • [Jupyter blog] Ploomber: Maintainable and Collaborative Pipelines in Jupyter | 2021-09-01
    This is Eduardo from Ploomber. I am thrilled to announce that our guest post is live on the Jupyter blog! The post summarizes how Ploomber streamlines building maintainable data pipelines with Jupyter. Let me know what you think!
  • how does one manage a large project with Jupyter notebook? | 2021-08-30
    I have an open-source project to do this :)
  • [D] Productionalizing machine learning pipelines for small teams
    I wrote a detailed survey on this. However, I'm biased since I have a project of my own: Ploomber.
  • [D] Why aren't workflow management tools used to ensure reproducibility in the ML world?
    The open-source project I'm working on aims to close this gap, allowing practitioners to use Jupyter for interactive data exploration but still produce reproducible workflows.
  • Going from running an ETL script on a Jupyter notebook locally, to deploying it in scalable containers - suggestions for learning resources?
    This is the exact use case that an open-source tool I'm working on is aimed to solve, I'd be interested in learning more about your use case to see how my tool can help. Please reach out if you need an extra hand!
  • notebooks: do you love them or do you hate them?
    ploomber (notebook pipeline orchestration) - disclaimer: I'm the author
  • Does Netflix use Jupyter Notebooks in production?
    If you want to adopt this workflow, check out the project I'm working on, which uses papermill under the hood to build multi-stage pipelines. It implements the workflow I described but broken it down into several steps to exploit parallelization and favor maintainability.
  • Scheduling tools for ETL and ML flow
    If you want the longer version. Take a look at the survey I made on workflow management tools. Also check out Ploomber, the project I'm working on, which is tailored for DS/ML workflows.
  • The modern way to run notebooks on the cloud
    Take a look at Ploomber (Disclaimer: I'm the author). It allows you to create multi-stage pipelines where each stage can be a notebook (but also supports scripts and functions). Kind of dbt for Python/Notebooks. I've been working on support for AWS Batch. I'm expecting to release a stable version in 2-3 weeks.
  • Data as a build system ?
  • Want to move away from Alteryx and looking for a viable alternative.
    It sounds like Ploomber is a good fit :) (Disclaimer: I'm the author).
  • What is the best structured ds project you have seen?
    It uses Ploomber which is a workflow orchestrator similar to Kedro.
  • Alternatives to Make for data science ?
    Hi, check out Ploomber (Disclaimer: I'm the creator), it's much simpler and powerful than using Make for reporting: you simply define a source (function, script, or notebook) and products (output files). Here's an example of a pipeline definition. Here's a binder link for you to play out with it without installing anything (may take a minute or two to load).
  • [D] Incremental builds for ML pipelines
    A few orchestrators have this feature: Ploomber (which I'm developing), DVC, drake (in R), but others don't: dagster, kedro, prefect. Surprisingly, users from the latter group do not seem to miss (or maybe be aware of) that feature.
  • [D] Why ML should be written as pipelines from the get-go
    2) My impression is that ZenML (and a few other frameworks) are more comparable to sklearn.Pipeline than to workflow orchestrators like Ploomber (which I'm developing), DVC or Kedro. So you need both: a workflow orchestrator to pull and clean the data and something like ZenML to pre-process it and train. Is this right? Am I missing anything?


Basic ploomber repo stats
2 days ago

ploomber/ploomber is an open source project licensed under Apache License 2.0 which is an OSI approved license.

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