#226 Building Flask APIs for data scientists

#226 Building Flask APIs for data scientists

Update: 2019-08-234
Share

Description

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: alanpryorjr.com

AJ's direct email: apryor6@gmail.com

AJ on LinkedIn: linkedin.com

American Tire Distributors blog: medium.com

Job at ATD: Submit your resume to: CoEHiring@ATD-US.com

Flaskerize CLI: github.com/apryor6/flaskerize

Flask_accepts: github.com/apryor6/flask_accepts

Example project using the API structure: github.com/apryor6/flask_api_example

See AJ speak @ Data Science North Carolina 2019, 40% off with code AJP40: dsncconf.com

Presentation on advanced Flask: speakerdeck.com

Original artcile regarding Flask structure: alanpryorjr.com


Sponsors



Linode

Rollbar

Talk Python Training
Comments 
loading
00:00
00:00
1.0x

0.5x

0.8x

1.0x

1.25x

1.5x

2.0x

3.0x

#226 Building Flask APIs for data scientists

#226 Building Flask APIs for data scientists

Michael Kennedy (@mkennedy)