What is the difference between the coding skillset of a data scientist and that of a SWE?

This page summarizes the projects mentioned and recommended in the original post on /r/datascience

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  • consul

    Consul is a distributed, highly available, and data center aware solution to connect and configure applications across dynamic, distributed infrastructure.

  • An SWE would likely guide the development and maintenance of any kind of SOA-based architecture, including writing and configuring the software to make it work. For example, a data scientist would not worry about using Polly for resiliency, or Consul for service discovery, and creating the libraries to use these systems.

  • Polly

    Polly is a .NET resilience and transient-fault-handling library that allows developers to express policies such as Retry, Circuit Breaker, Timeout, Bulkhead Isolation, and Fallback in a fluent and thread-safe manner. From version 6.0.1, Polly targets .NET Standard 1.1 and 2.0+.

  • An SWE would likely guide the development and maintenance of any kind of SOA-based architecture, including writing and configuring the software to make it work. For example, a data scientist would not worry about using Polly for resiliency, or Consul for service discovery, and creating the libraries to use these systems.

  • 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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  • If you didn't already see it, you might enjoy these slides.

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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