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MySQL for Python

You're reading from   MySQL for Python Integrating MySQL and Python can bring a whole new level of productivity to your applications. This practical tutorial shows you how with examples and explanations that clarify even the most difficult concepts.

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Product type Paperback
Published in Sep 2010
Publisher Packt
ISBN-13 9781849510189
Length 440 pages
Edition 1st Edition
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Author (1):
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Albert Lukaszewski Albert Lukaszewski
Author Profile Icon Albert Lukaszewski
Albert Lukaszewski
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Table of Contents (20) Chapters Close

MySQL for Python
Credits
About the Author
About the Reviewers
Preface
1. Getting Up and Running with MySQL for Python FREE CHAPTER 2. Simple Querying 3. Simple Insertion 4. Exception Handling 5. Results Record-by-Record 6. Inserting Multiple Entries 7. Creating and Dropping 8. Creating Users and Granting Access 9. Date and Time Values 10. Aggregate Functions and Clauses 11. SELECT Alternatives 12. String Functions 13. Showing MySQL Metadata 14. Disaster Recovery Index

Subqueries


The WHERE clause reduces the amount of data through a simple filtering process and HAVING filters the results. But MySQL also provides more robust ways of narrowing the data from which results are culled. Normally, MySQL processes a query against a database that is resident on disk. Subqueries, however, are nested SELECT statements that result in a table of results against which the main query is processed. Once the main query is processed against the results of the subquery, the latter is purged from memory.

Up to this point, if we needed to take the results from one query and use it as input for another query, we might feel constrained to use two SELECT statements and manually transfer the data. Here, however, subqueries do that for us.

For example, let's say that we wanted to find the title of every movie done by actors with the surname CHASE. The sakila database does not provide this information in one table. Using a series of SELECT statements, we would first need to retrieve...

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