PyData Global 2022

David Barrett

After earning his Ph.D., David Barrett has been teaching and applying results from computer-science research to engineer solutions for large-scale software problems for the last twenty years. His expertise includes machine learning, software systems, networks, databases, programming languages and compiler-construction. He has presented talks at peer-reviewed academic conferences on data layouts and retrieval scheduling for multimedia, and dynamic memory allocation for programming languages. He has also presented on document databases, and software vulnerabilities at NoSQLNow and the Open Source Summit.

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Sessions

12-01
18:30
30min
Text to Data: Make Your Code Malleable, Not Brittle
David Barrett, Martha L Escobar-Molano

Extracting the highly valuable data from unstructured text often results in hard-to-read, brittle, difficult-to-maintain code. The problem is that using regular expressions directly embedded in the program control flow does not provide the best level of abstraction. We propose a query language (based on the tuple relational calculus) that facilitates data extraction. Developers can explicitly express their intent declaratively, making their code much easier to write, read, and maintain.

Talk Track I