Book Image

MySQL for Python

By : Albert Lukaszewski
Book Image

MySQL for Python

By: Albert Lukaszewski

Overview of this book

Python is a dynamic programming language, which is completely enterprise ready, owing largely to the variety of support modules that are available to extend its capabilities. In order to build productive and feature-rich Python applications, we need to use MySQL for Python, a module that provides database support to our applications. Although you might be familiar with accessing data in MySQL, here you will learn how to access data through MySQL for Python efficiently and effectively.This book demonstrates how to boost the productivity of your Python applications by integrating them with the MySQL database server, the world's most powerful open source database. It will teach you to access the data on your MySQL database server easily with Python's library for MySQL using a practical, hands-on approach. Leaving theory to the classroom, this book uses real-world code to solve real-world problems with real-world solutions.The book starts by exploring the various means of installing MySQL for Python on different platforms and how to use simple database querying techniques to improve your programs. It then takes you through data insertion, data retrieval, and error-handling techniques to create robust programs. The book also covers automation of both database and user creation, and administration of access controls. As the book progresses, you will learn to use many more advanced features of Python for MySQL that facilitate effective administration of your database through Python. Every chapter is illustrated with a project that you can deploy in your own situation.By the end of this book, you will know several techniques for interfacing your Python applications with MySQL effectively so that powerful database management through Python becomes easy to achieve and easy to maintain.
Table of Contents (20 chapters)
MySQL for Python
Credits
About the Author
About the Reviewers
Preface
Index

Why?


There are a number of reasons why one might opt to process records individually or at least in smaller chunks. Three of the most compelling reasons are:

  • Limits of computing resources

  • Network latency

  • Pareto's principle

From the perspective of efficiency, any one of these reasons is good enough to warrant retrieval of smaller amounts of data. We look at each in greater detail in the following section.

Computing resources

Despite Moore's law holding true for many years now, it is coming under increasing pressure as a trend and cannot be presumed to hold true indefinitely. While one may have a budget with numbers so big that it looks like a phone directory, one's resources are only faster or more powerful on a comparative scale.

Note

Moore's law states that the number of transistors that one is able to fit on an integrated circuit will double every two years.

This law is not much of a natural law as a business observation was made by Gordon Moore, co-founder of Intel. He did not state in such absolute...