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August 22-23, 2017: Training
August 23-25, 2017: Tutorials & Conference
New York, NY

Using Magic Functions to Build a Full, Multi-Threaded SQL Client

Moderated by: Timothy Dobbins

Who is this presentation for?

SQL Developers, Software Engineers, Data Scientists, BI analysts

Prerequisite knowledge

Basic SQL, Basic Python

What you'll learn

After this talk, attendees will be able to use a SQL client that merges their SQL and Python environments so they can pass variables between the two without a wrapper like SQLAlchemy.

Description

SQLCell is a magic function that executes raw, parallel, parameterized SQL queries with the ability to accept python variables as parameters, switch between engines with a click of a button, execute queries outside of a transaction block (to execute VACUUM, CREATE , and DROP statements), produce an intuitive heatmap-like query plan sankey graph with D3.js to highlight slow points in query; all while concurrently running Python code.

Among the features listed above, SQLCell also offers:
• inline editing of values, column names, and data types through the UI
• support for psql metacommands
• pg_dump support
• optional Bootstrap-Notify notifications for finished queries
• returns data as pandas DataFrame or SQLAlchemy RowProxy
• writes results to a file with parameter or through a UI button
• ability to assign results of SQL output to a Python variable
• heatmap-like query plan table (and graph) to highlight slow points in queries

This project is optimized for PostgreSQL but I’m in the process of optimizing it for MySQL too.