Installing EasyMySQL

pip install easymysql

If you encounter an error due to having an older version of Python, you can use:

pip3 install easymysql

Connecting to the Database

#!/usr/bin/python

from easymysql.mysql import mysql

my = mysql('localhost','user_db','pass_db','db_name')

Inserting Data

Inserting data is extremely easy; you only need to provide two parameters: the table name and an array with the data to insert:

my.insert('table_name',{
	'field_1':'value_1',
	'field_2':'value_2',
	'field_3':'value_3',
})

The array uses a Key-Value format where the key corresponds to the table field name, and the value is the value to be inserted.

Updating Data

Updating data is similar to inserting, but this time you need to pass three parameters: the table name, an array with the data to update (Key-Value format), and a third parameter specifying the WHERE clause, either as a Key-Value array or a SQL string:

my.update("table_name",{
	"field_1":"value_1",
	"field_2":"value_2",
	"field_3":"value_3",
	"id":300
€)

The third parameter, if given as an array, will generate a standard SQL string concatenated with AND. For example:

my.update('table_name',{
	'field_1':'value_1'
},{
	'field_2':'value_2',
	'field_3':'value_3'
})

This translates to:

UPDATE table_name SET field_1=value_1 WHERE field_2='value_2' AND field_3='value_3'

Alternatively, if the third parameter is a string:

my.update('table_name',{
	'field_1':'value_1',
	'field_2':'value_2',
	'field_3':'value_3',
},
	'field_2=value_2 OR field_3=value_3
)

This translates to:

UPDATE table_name SET field_1=value_1,field_2=value_2,field_3=value_3 WHERE field_2='value_2' OR field_3='value_3'

Querying and Listing Data

The SELECT function works similarly to the previous cases. You provide the table name, an optional WHERE condition as an array or string, and optionally an ORDER clause as the third parameter. To filter data:

lst = my.select('table_name', {'field_1': value_1})

lst = my.select('table_name', "field_1='value_1'")

If there's only one result:

[{'field_1': 'value_1', 'field_2': 'value_2','field_3':'value_3'}]

If there are multiple results:

[{'field_1': 'value_1', 'field_2': 'value_2','field_3':'value_3'},
{'field_1': 'value4', 'field_2': 'value_5','field_3':'value_6'},
{'field_1': 'value_7', 'field_2': 'value_8','field_3':'value_9'}]

You can also use standard SQL WHERE clauses with LIKE, OR, >, <, etc.:
lst = my.select('table_name', "field_1 LIKE '%value%')

 ORDER Clause

Technically, the ORDER clause can include any SQL statement that follows the WHERE clause:
lst = my.select('table_name', "field_1 LIKE '%value%',order='LIMIT 10')
lst = my.select('table_name', "field_1 LIKE '%value%',order='LIMIT 1,10')
lst = my.select('table_name', "field_1 LIKE '%value%',order='ORDER BY id DESC')
lst = my.select('table_name', "field_1 LIKE '%value%',order='ORDER BY id DESC LIMIT 5')
lst = my.select('table_name', "field_1 LIKE '%value%',order='ORDER BY id DESC LIMIT 1,10')

Iterating Through Data

To iterate through the data, simply use a for loop:
lst = my.select('table_name')

for item in lst:
    print(item)

for item in lst:
    print(item['field_1'])
    print(item['field_2'])
    print(item['field_3'])