Monitor performance issues & errors in your code

Building Flask APIs for data scientists

Episode #226, published Fri, Aug 23, 2019, recorded Mon, Aug 5, 2019

If you're a data scientist, how do you deliver your analysis and your models to the people who need them? A really good option is to serve them over Flask as an API. But there are some special considerations you might keep in mind. How should you structure this API? What type of project structures work best for data science and Flask web apps? That and much more on this episode of Talk Python To Me with guest AJ Pryor.

Links from the show

AJ on Twitter: @pryor_aj
AJ's blog:
AJ's direct email:
AJ on LinkedIn:
American Tire Distributors blog:
Job at ATD: Submit your resume to:
Flaskerize CLI:
Example project using the API structure:
See AJ speak @ Data Science North Carolina 2019, 40% off with code AJP40:
Presentation on advanced Flask:
Original artcile regarding Flask structure:
Episode transcripts:

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AJ Pryor
AJ Pryor
AJ is a data scientist, full stack developer, and Ph.D. physicist with expertise in high-performance computing and software engineering who focuses on driving business value through conception and strategic deployment of data-driven applications. He believes in all things testing, is always halfway through some sort of online course, and spends perhaps too much time slacking his coworkers about interesting new technologies or ideas.

AJ currently serves the role of Principal Data Scientist at American Tire Distributors and lives near Charlotte, NC with his wife and (rapidly growing) family. In addition to data science and web development, he is interested in football (go Jackets!) as well as the guitar and piano.
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