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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

Chapter 11. SELECT Alternatives

We have already seen how to restrict the data that MySQL returns by using a WHERE clause. Rather than retrieve the entire table and sort through it in Python, we passed the burden onto the server. Using WHERE restricted the number of rows that match. This is just like when we specify columns instead of using an asterisk after SELECT—it saves us from receiving the entire record for every match.

WHERE causes MySQL to ignore any row that does not match our selection. Specifying the columns then indicates to MySQL, which parts of the affected rows to return. In addition to WHERE, MySQL supports other ways of narrowing one's returns. It also allows us to match and complement the data using other tables, including combining tables or results from different queries.

In this chapter, we will see:

  • How we can restrict results using WHERE and HAVING, and what the differences are between them

  • When it is best to use WHERE and when one might use HAVING

  • How to create temporary...

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