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Ask HN: Is Python integration necessary for a commercially-viable data product?

  • 1 points
  • 7 days ago

  • @mattewong
  • Created a post

Ask HN: Is Python integration necessary for a commercially-viable data product?


@PaulHoule 7 days

Replying to @mattewong 🎙

In what sense? A lot of people like to do data analysis with jupyter, pandas, scikit-learn, etc. They don't need to be treated like children with half-baked "integrations", instead they know how to read industry standard data files

https://pandas.pydata.org/docs/user_guide/io.html

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@mattewong 7 days

Replying to @mattewong 🎙

(re "data product", say for example, Cockroach DB which I have no affiliation with and already has a python integration)

With platforms like DataBricks and Airflow that are heavily inclined towards python, it feels somewhat unavoidable to offer a python "import myproduct" option. But, is it truly necessary to be part of that python ecosystem to survive as a data product?

I know: python has a vibrant community, it's a virtuous cycle because every data lib is in python and therefore every data platform / analyst uses it etc, why would you ever not want to just add your product to that ecosystem etc. I get that, but that's also why I'm asking the question

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@Jugurtha 6 days

Replying to @mattewong 🎙

Expose a "REST" API and webhooks and you can have practically as many clients or "integrations" as you want.

Here are design principles:

- Anything you can do with point and click, you must be able to do with an API call.

- It should theoretically be possible to clone your product using its API.

- Users can be anything (people, systems, your own product). For example, our product is built using a plugin architecture, our subsystems hit our API.

- Someone interested in an event should get that event and be able to subscribe to it. (Again, users can be people or systems, and that event could be the basis of some downstream actions).

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