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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

Changing queries dynamically


But what if the user does not want to submit a precise query but needs a list of the possibilities? There are a couple of ways to clarify the search. We could first keep a list of the common search queries. This is something done often by the likes of Google and Yahoo!. This works very well with large datasets served through web servers because it uses a static list of terms and simply culls them out. For more dedicated applications, one can use MySQL's pattern matching ability to present known options on-the-fly.

Pattern matching in MySQL queries

Where Python's regular expression engine is very robust, MySQL supports the two following metacharacters for forming regular expressions:

  • %: Zero or more characters matched in aggregate

  • _ : Any single character matched individually

Pattern matching is always a matter of comparison. Therefore, with either of these, never use operators of equality.

SELECT * FROM menu WHERE name = 's%'; 		        WRONG
SELECT * FROM menu WHERE...
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