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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

Helpful ways to nuance an INSERT statement


Like SELECT has other helpful quantifiers to weed through the data being returned, INSERT has ways of nuancing the origin of the data to be inserted as well as the timing and conditions of the insertion. The three most common ways of altering the way MySQL processes an INSERT statement are:

  • INSERT...SELECT...

  • INSERT DELAYED...

  • INSERT...ON DUPLICATE KEY UPDATE...

In the following section, we take each one in turn.

INSERT...SELECT...

Using INSERT...SELECT... we can tell MySQL to draw from different tables without having to draw them into Python or to set a variable in MySQL. It functions on the following syntactic template:

INSERT INTO <target table>(target column name) SELECT <source column name> FROM <source table>;

By default, the SELECT phrase of the sentence is greedy and will return as many hits as it can. As with a generic SELECT statement, however, we can restrict the hits returned using WHERE. See the Other helpful quantifiers section...

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