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You're reading from  Apache Superset Quick Start Guide

Product typeBook
Published inDec 2018
Reading LevelIntermediate
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ISBN-139781788992244
Edition1st Edition
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Shashank Shekhar
Shashank Shekhar
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Shashank Shekhar

Shashank Shekhar is a data analyst and open source enthusiast. He has contributed to Superset and pymc3 (the Python Bayesian machine learning library), and maintains several public repositories on machine learning and data analysis projects of his own on GitHub. He heads up the data science team at HyperTrack, where he designs and implements machine learning algorithms to obtain insights from movement data. Previously, he worked at Amino on claims data. He has worked as a data scientist in Silicon Valley for 5 years. His background is in systems engineering and optimization theory, and he carries that perspective when thinking about data science, biology, culture, and history.
Read more about Shashank Shekhar

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Alpha and gamma – building blocks for custom roles

We will manage user permissions using alpha, gamma, and customized roles. In superset_config.py, only one email ID should be whitelisted for registration. We will need more Google accounts to register for testing different permissions. You can put in any regex pattern in the whitelist field. Suffixes such as @amino.com are commonly used to allow users from a specific email domain to register on the web app. If a Google account email address matches the pattern specified in whitelist, it will be able to register itself.

We will modify superset_config.py so that a Google account with any email can register. Moving forward, new users will be assigned a Gamma role with no default permissions on any data source. In order to do that, we will modify two lines in the file:

# Modification 1
# Assigns Gamma role for new registered...
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Apache Superset Quick Start Guide
Published in: Dec 2018Publisher: ISBN-13: 9781788992244

Author (1)

author image
Shashank Shekhar

Shashank Shekhar is a data analyst and open source enthusiast. He has contributed to Superset and pymc3 (the Python Bayesian machine learning library), and maintains several public repositories on machine learning and data analysis projects of his own on GitHub. He heads up the data science team at HyperTrack, where he designs and implements machine learning algorithms to obtain insights from movement data. Previously, he worked at Amino on claims data. He has worked as a data scientist in Silicon Valley for 5 years. His background is in systems engineering and optimization theory, and he carries that perspective when thinking about data science, biology, culture, and history.
Read more about Shashank Shekhar