Python: Deeper Insights into Machine Learning by 2017

Python: Deeper Insights into Machine Learning by 2017

Author:2017
Language: eng
Format: epub
Publisher: Packt Publishing


Data from databases

We generally interact with databases via a query language. One of the most popular query languages is MySQL. Python has a database specification, PEP 0249, which creates a consistent way to work with numerous database types. This makes the code we write more portable across databases and allows a richer span of database connectivity. To illustrate how simple this is, we are going to use the mysql.connector class as an example. MySQL is one of the most popular database formats, with a straight forward, human-readable query language. To practice using this class, you will need to have a MySQL server installed on your machine. This is available from https://dev.mysql.com/downloads/mysql/.

This should also come with a test database called world, which includes statistical data on world cities.

Ensure that the MySQL server is running, and run the following code:

import mysql.connector from mysql.connector import errorcode cnx = mysql.connector.connect(user='root', password='password', database='world', buffered=True) cursor=cnx.cursor(buffered=True) query=("select * from city where population > 1000000 order by population") cursor.execute(query) worldList=[] for (city) in cursor: worldList.append([city[1],city[4]]) cursor.close() cnx.close()



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