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Python MariaDB – Where Clause using PyMySQL

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Where clause is used in MariaDB database to filter the data as per the condition required. You can fetch, delete or update a particular set of data in MariaDB database by using the where clause.

Syntax :

SELECT column1, column2, …. cloumnN FROM [TABLE NAME] WHERE [CONDITION];

The above syntax is used for displaying a certain set of data following the condition.

Example 1: Consider the following database named GFG and having a table name as a PRODUCT.

Schema of the Table:

Table data :

Where Clause In Python :

Steps to use where clause in Python is:

  1. First form a connection between MariaDB and Python program. It is done by importing pymysql package and using pymysql.connect() method, for passing the username, password, host (optional default: localhost) and, database (optional) as parameters to it.
  2. Now, create a cursor object on the connection object created above by using the cursor() method. A database cursor is a control structure that enables traversal over the records in a database.
  3. Then, execute the where clause statement by passing it through the execute() method.

Python3

import pymysql
  
# Create a connection object
# IP address of the MySQL database server
Host = "localhost"  
  
# User name of the database server
User = "user"       
  
# Password for the database user
Password = ""           
  
database = "GFG"
  
conn  = pymysql.connect(host=Host, user=User, password=Password, database)
  
# Create a cursor object
cur  = conn.cursor()
  
  
query = f"SELECT price,PRODUCT_TYPE FROM PRODUCT WHERE price > 10000"
  
cur.execute(query)
  
rows = cur.fetchall()
for row in rows :
    print(row)
  
conn.close()

                    

Output :

Example 2 :

Python3

import pymysql
  
# Create a connection object
  
conn  = pymysql.connect('localhost', 'user', 'password', 'database')
  
# Create a cursor object
cur  = conn.cursor()
  
  
query = f"SELECT * FROM PRODUCT WHERE PRODUCT_TYPE in ('Voice','DLC','CALL')"
  
cur.execute(query)
  
rows = cur.fetchall()
for row in rows :
    print(row)
  
conn.close()

                    

Output :



Last Updated : 14 Oct, 2020
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