5 ms·

Show HN: Mineo.app – Better Python Notebooks

60 points by diegogm934 3y ago

Hello everyone, I would like to introduce our startup to HN: Mineo.app. Mineo.app is a production-ready SaaS Python notebook that provides a complete environment for building your data applications: Dashboards, Reports, and Data Pipelines based on Python notebooks. Key features: * Superpowered jupyter-compatible Python notebooks with extra goodies like: version control, commenting support, custom docker images, etc... enhanced with no code components that allow to create beautiful dashboards and reports. * Data Pipelines: Ability to schedule and run one or more notebooks. * Integrated file system to manage your files and projects with detailed permissions and groups. We have a freemium licensing model, so you can start using Mineo just by registering with your Github/Google/Microsoft account for free without a credit card. And it's free for educational purposes ;-) Diego.

esafak 3y ago
I think it was a little too early share but since you asked... Crafting workflows out of notebooks is a really bad idea; an anti-pattern. If you want to go down the road of "workflows for data scientists" look at https://featurebyte.com/ https://featurebyte.com/ Your messaging indicates you also want to appeal to business intelligence users, with their data exploration needs. In this space I give the crown to https://hex.tech/ https://hex.tech/ How are you going to be different or better? Also, you should fix your showcase so prospective users don't have to log in. I'll just nope out of your site. Have you considered going open core? That would make me look more favorably at your product given your lack of indisputable product- and technical superiority. And last but not least, I wish you success!
- diegogm934 3y ago
  Thanks for taking the time to evaluate the platform. Regarding hex tech, we are more focused on the BI side of the business, providing an integrated platform for deploying and publishing data applications based on notebooks and low-code components, rather than building another real-time notebook collaboration platform or a graph-based notebook like einblick or hex tech. We believe they represent a great opportunity to bridge the gap between data science notebooks and what final users expect: Dashboards and reports. As for releasing the platform as an open core, we've had internal discussions about this since the beginning of the project, and it's something we're seriously considering. Accessing the showcase without registering is something we definitely need to change, although it's free to register and all you need is a Google/Microsoft/Github account. Thanks for the feedback, esafak!
  - asimjalis 3y ago
    I was fine with basic signing up using GitHub or Google, but then the questionaire started and I lost interest. I would recommend making the initial exploration as friction-less as possible.
- westurner 3y ago
  > Crafting workflows out of notebooks is a really bad idea; an anti-pattern. If you want to go down the road of "workflows for data scientists" https://westurner.github.io/hnlog/ https://westurner.github.io/hnlog/ Ctrl-F "DVC" ( https://dvc.org/ https://dvc.org/ ) , https://westurner.github.io/hnlog/#comment-24261118 https://westurner.github.io/hnlog/#comment-24261118 "Ten Simple Rules for Reproducible Computational Research", “Ten Simple Rules for Creating a Good Data Management Plan”, PROV pygwalker https://github.com/Kanaries/pygwalker https://github.com/Kanaries/pygwalker : > PyGWalker: Turn your pandas dataframe into a Tableau-style User Interface for visual analysis "Generate code from GUI interactions; State restoration & Undo" https://github.com/Kanaries/pygwalker/issues/90 https://github.com/Kanaries/pygwalker/issues/90
  - westurner 3y ago
    The Scientific Method is testing, so testing (tests, assertions, fixtures) should be core to any scientific workflow system. - [ ] (It's not possible to run `!pytest` in a Jupyter notebook without installing an extension with JupyterLite in WASM onnly where there's not yet a terminal or even yet a slow-but-usable [cheerpx] webvm bridged to jupyter kernel WASM ~process-space.) awesome-jupyter#testing: https://github.com/markusschanta/awesome-jupyter#testing https://github.com/markusschanta/awesome-jupyter#testing ml-tooling/best-of-jupyter lists papermill/papermill under "Interactive Widgets/Visualization" https://github.com/ml-tooling/best-of-jupyter#interactive-widgets--visualization https://github.com/ml-tooling/best-of-jupyter#interactive-wi... "Markdown based notebooks" would store files next to the .ipynb.md, which implies a need for an MHTML/ZIP-like archive (for report notebook artifacts produced by scientific workflow systems with provenance metadata); but W3C Web Bundles avoid modifying linked resources with new specs: https://github.com/jupyter/enhancement-proposals/pull/103#issuecomment-1510418219 https://github.com/jupyter/enhancement-proposals/pull/103#is...
set92 3y ago
On my book, "better" being SaaS, not open source or letting your users download it is not a better option. Is merely another Deepnote, Google Colab... but not Jupyter Notebook
- diegogm934 3y ago
  Thanks set92 for your feedback! Our goal is not to replace Jupyter Notebook, it's a software that does what it claims to do in an excellent way. We are big fans of it. Our goal is to provide a platform to deploy and scale your notebooks and turn them into data applications that solve the real problems that occur in production environments, like access control, collaboration, version control, and many other things that are required to turn a notebook you're running in your computer into a product.

60 points by diegogm934 3y ago

esafak 3y ago

I think it was a little too early share but since you asked... Crafting workflows out of notebooks is a really bad idea; an anti-pattern. If you want to go down the road of "workflows for data scientists" look at https://featurebyte.com/ https://featurebyte.com/ Your messaging indicates you also want to appeal to business intelligence users, with their data exploration needs. In this space I give the crown to https://hex.tech/ https://hex.tech/ How are you going to be different or better? Also, you should fix your showcase so prospective users don't have to log in. I'll just nope out of your site. Have you considered going open core? That would make me look more favorably at your product given your lack of indisputable product- and technical superiority. And last but not least, I wish you success!

diegogm934 3y ago
Thanks for taking the time to evaluate the platform. Regarding hex tech, we are more focused on the BI side of the business, providing an integrated platform for deploying and publishing data applications based on notebooks and low-code components, rather than building another real-time notebook collaboration platform or a graph-based notebook like einblick or hex tech. We believe they represent a great opportunity to bridge the gap between data science notebooks and what final users expect: Dashboards and reports. As for releasing the platform as an open core, we've had internal discussions about this since the beginning of the project, and it's something we're seriously considering. Accessing the showcase without registering is something we definitely need to change, although it's free to register and all you need is a Google/Microsoft/Github account. Thanks for the feedback, esafak!
- asimjalis 3y ago
  I was fine with basic signing up using GitHub or Google, but then the questionaire started and I lost interest. I would recommend making the initial exploration as friction-less as possible.
westurner 3y ago
> Crafting workflows out of notebooks is a really bad idea; an anti-pattern. If you want to go down the road of "workflows for data scientists" https://westurner.github.io/hnlog/ https://westurner.github.io/hnlog/ Ctrl-F "DVC" ( https://dvc.org/ https://dvc.org/ ) , https://westurner.github.io/hnlog/#comment-24261118 https://westurner.github.io/hnlog/#comment-24261118 "Ten Simple Rules for Reproducible Computational Research", “Ten Simple Rules for Creating a Good Data Management Plan”, PROV pygwalker https://github.com/Kanaries/pygwalker https://github.com/Kanaries/pygwalker : > PyGWalker: Turn your pandas dataframe into a Tableau-style User Interface for visual analysis "Generate code from GUI interactions; State restoration & Undo" https://github.com/Kanaries/pygwalker/issues/90 https://github.com/Kanaries/pygwalker/issues/90
- westurner 3y ago
  The Scientific Method is testing, so testing (tests, assertions, fixtures) should be core to any scientific workflow system. - [ ] (It's not possible to run `!pytest` in a Jupyter notebook without installing an extension with JupyterLite in WASM onnly where there's not yet a terminal or even yet a slow-but-usable [cheerpx] webvm bridged to jupyter kernel WASM ~process-space.) awesome-jupyter#testing: https://github.com/markusschanta/awesome-jupyter#testing https://github.com/markusschanta/awesome-jupyter#testing ml-tooling/best-of-jupyter lists papermill/papermill under "Interactive Widgets/Visualization" https://github.com/ml-tooling/best-of-jupyter#interactive-widgets--visualization https://github.com/ml-tooling/best-of-jupyter#interactive-wi... "Markdown based notebooks" would store files next to the .ipynb.md, which implies a need for an MHTML/ZIP-like archive (for report notebook artifacts produced by scientific workflow systems with provenance metadata); but W3C Web Bundles avoid modifying linked resources with new specs: https://github.com/jupyter/enhancement-proposals/pull/103#issuecomment-1510418219 https://github.com/jupyter/enhancement-proposals/pull/103#is...

set92 3y ago

On my book, "better" being SaaS, not open source or letting your users download it is not a better option. Is merely another Deepnote, Google Colab... but not Jupyter Notebook

diegogm934 3y ago
Thanks set92 for your feedback! Our goal is not to replace Jupyter Notebook, it's a software that does what it claims to do in an excellent way. We are big fans of it. Our goal is to provide a platform to deploy and scale your notebooks and turn them into data applications that solve the real problems that occur in production environments, like access control, collaboration, version control, and many other things that are required to turn a notebook you're running in your computer into a product.