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>save a requirements.txt pipenv https://packaging.python.org/tutorials/managing-dependencies... https://dev.to/yukinagae/your-first-guide-to-getting-started...
Please do not use `pipenv`, use `poetry` or plain old `pip` instead. 1. https://news.ycombinator.com/item?id=18612590
Point about "Official tool" is valid
Others seems strange to me
I'd add to my comment something like "Try it. If you like it - use it"
Thank you for link
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Windows will probably be done in a year, but it's hard to say. Hardest part is finding people who want to work on windows support xD
No kidding. (I wasn't complaining btw nor was I even focused on OS support, I was curious about which arches people use it on). What are the popular use cases - either ones driving current development or ones where it's best suited?
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hi Aaron, We did exactly what works for you into a open source python library, github.com/bentoml/bentoml. It packages your model for you into a standardized format, that you can use it in multiply serving scenarios online serving with api endpoint, offline serving with spark udf, CLI access or import it as python module. It also helps you deploy to different platform such as lambda, sagemaker and others. Our value i…
It's been great seeing this space fill out with solutions in the last year. MLFlow[1] is another open source solution I have my eyes on. BentoML looks more cohesive than our homegrown solution because it targets a more general case. One of the things I would miss switching to BentoML would be automatic requirements generation. We use pipreqs[2] to generate a requirements.txt given a model instance. Any thoughts on th…
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Any inputs on Argo workflows vs Kubeflow vs MLFlow? Which is better suited?
Kubeflow, unless I’m missing some things, is for Tensorflow pipelines, if you’re not using TF, or it’s not the only thing you use, it’s not ideal. I thought MlFlow was a spark thing, and were trying to migrate off of spark/DataBricks due to the resources inefficiencies of Spark (at our scale) and maintenance nightmare that python notebooks are causing us. Argo is just a container workflow tool, not ML specific. We’re…