smart_open VS rxsci

We’re using smart_open, which is an amazing library that lets you open objects in S3 (and other cloud object stores) as if they’re files on your filesystem. It’s obviously critical that we’re able to seek to an arbitrary position in an S3 file without first downloading the whole thing. We’ll assume you’re using Poetry, but you should be able to follow along with any other package manager:

If you didn’t follow along with the first article in this series, you should be able to follow this article with your own dataset as long as you install smart_open and Meadowrun. smart_open is an amazing library that lets you open objects in S3 (and other cloud object stores) as if they’re files on your filesystem, and Meadowrun makes it easy to run your Python code on the cloud.

I see that you're primarily looking into Python work, so I'd recommend `smart_open` as a nice, compact way to get started.

https://github.com/RaRe-Technologies/smart_open

You want smart_open. It gives you a (more complete) file-like interface to many different storage systems, including s3. You can read and seek as needed.

See also smart_open: https://github.com/RaRe-Technologies/smart_open which might be more user-friendly? Never used it myself but it was on HN before. Discussion on their bugtracker: https://github.com/RaRe-Technologies/smart_open/issues/579

This is more verbose but much more flexible. Typically this allowed me to implement a set of operators for data science: https://github.com/maki-nage/rxsci. I think this would not have been possible with RxPY v1.