I analyzed 1835 hospital price lists so you didn't have to

This page summarizes the projects mentioned and recommended in the original post on news.ycombinator.com

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  • price-transparency-guide

    The technical implementation guide for the tri-departmental price transparency rule.

  • The health insurance companies are now required to publish this and in fact the rule went into effect July 1 2022.

    Look up price transparency by CMS (the data will be published in this format: https://github.com/CMSgov/price-transparency-guide)

    Note: the data being published by payors in machine readable format (MRF) is MASSIVE - terrabytes of data. Example: https://transparency-in-coverage.uhc.com/

  • mumps-examples

    This is a collection of M scripts for learning purposes. The examples in this tutorial are run with GT.M.

  • From the context I'm guessing MUMPS, and it kinda seems to resemble it, if it had more line breaks: https://github.com/programarivm/mumps-examples/blob/f160bfb6...

  • WorkOS

    The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.

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  • polars

    Dataframes powered by a multithreaded, vectorized query engine, written in Rust

  • This study uses polars [0][1] -- a new Data Science library written in Rust (core) with bindings to Python and Javascript. Perfect replacement for pandas. Polars' claims to fame are speed (faster than pretty much anything out there [2][3]), low memory pressure (very visible when comparing to pandas) and consistent API across Rust, Python, JS.

    [0] https://www.pola.rs/

    [1] https://github.com/pola-rs/polars

    [2] https://h2oai.github.io/db-benchmark/

    [3] https://www.pola.rs/benchmarks.html

  • db-benchmark

    reproducible benchmark of database-like ops

  • This study uses polars [0][1] -- a new Data Science library written in Rust (core) with bindings to Python and Javascript. Perfect replacement for pandas. Polars' claims to fame are speed (faster than pretty much anything out there [2][3]), low memory pressure (very visible when comparing to pandas) and consistent API across Rust, Python, JS.

    [0] https://www.pola.rs/

    [1] https://github.com/pola-rs/polars

    [2] https://h2oai.github.io/db-benchmark/

    [3] https://www.pola.rs/benchmarks.html

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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