- SQLite - DISTINCT Keyword
- SQLite - HAVING Clause
- SQLite - GROUP By Clause
- SQLite - ORDER By Clause
- SQLite - LIMIT Clause
- SQLite - GLOB Clause
- SQLite - LIKE Clause
- SQLite - DELETE Query
- SQLite - UPDATE Query
- SQLite - AND & OR Clauses
- SQLite - WHERE Clause
- SQLite - Expressions
- SQLite - Operators
- SQLite - SELECT Query
- SQLite - INSERT Query
- SQLite - DROP Table
- SQLite - CREATE Table
- SQLite - DETACH Database
- SQLite - ATTACH Database
- SQLite - CREATE Database
- SQLite - Data Type
- SQLite - Syntax
- SQLite - Commands
- SQLite - Installation
- SQLite - Overview
- SQLite - Home
Advanced SQLite
- SQLite - Useful Functions
- SQLite - Date & Time
- SQLite - VACUUM
- SQLite - EXPLAIN
- SQLite - Injection
- SQLite - AUTOINCREMENT
- SQLite - Subqueries
- SQLite - Transactions
- SQLite - Views
- SQLite - TRUNCATE Command
- SQLite - ALTER Command
- SQLite - INDEXED By Clause
- SQLite - Indexes
- SQLite - Triggers
- SQLite - ALIAS Syntax
- SQLite - NULL Values
- SQLite - UNIONS Clause
- SQLite - JOINS
- SQLite - Constraints
- SQLite - PRAGMA
SQLite Interfaces
SQLite Useful Resources
Selected Reading
- Who is Who
- Computer Glossary
- HR Interview Questions
- Effective Resume Writing
- Questions and Answers
- UPSC IAS Exams Notes
SQLite - Python
In this chapter, you will learn how to use SQLite in Python programs.
Installation
SQLite3 can be integrated with Python using sqpte3 module, which was written by Gerhard Haring. It provides an SQL interface comppant with the DB-API 2.0 specification described by PEP 249. You do not need to install this module separately because it is shipped by default along with Python version 2.5.x onwards.
To use sqpte3 module, you must first create a connection object that represents the database and then optionally you can create a cursor object, which will help you in executing all the SQL statements.
Python sqpte3 module APIs
Following are important sqpte3 module routines, which can suffice your requirement to work with SQLite database from your Python program. If you are looking for a more sophisticated apppcation, then you can look into Python sqpte3 module s official documentation.
Sr.No. | API & Description |
---|---|
1 | sqpte3.connect(database [,timeout ,other optional arguments]) This API opens a connection to the SQLite database file. You can use ":memory:" to open a database connection to a database that resides in RAM instead of on disk. If database is opened successfully, it returns a connection object. When a database is accessed by multiple connections, and one of the processes modifies the database, the SQLite database is locked until that transaction is committed. The timeout parameter specifies how long the connection should wait for the lock to go away until raising an exception. The default for the timeout parameter is 5.0 (five seconds). If the given database name does not exist then this call will create the database. You can specify filename with the required path as well if you want to create a database anywhere else except in the current directory. |
2 | connection.cursor([cursorClass]) This routine creates a cursor which will be used throughout of your database programming with Python. This method accepts a single optional parameter cursorClass. If suppped, this must be a custom cursor class that extends sqpte3.Cursor. |
3 | cursor.execute(sql [, optional parameters]) This routine executes an SQL statement. The SQL statement may be parameterized (i. e. placeholders instead of SQL pterals). The sqpte3 module supports two kinds of placeholders: question marks and named placeholders (named style). For example − cursor.execute("insert into people values (?, ?)", (who, age)) |
4 | connection.execute(sql [, optional parameters]) This routine is a shortcut of the above execute method provided by the cursor object and it creates an intermediate cursor object by calpng the cursor method, then calls the cursor s execute method with the parameters given. |
5 | cursor.executemany(sql, seq_of_parameters) This routine executes an SQL command against all parameter sequences or mappings found in the sequence sql. |
6 | connection.executemany(sql[, parameters]) This routine is a shortcut that creates an intermediate cursor object by calpng the cursor method, then calls the cursor.s executemany method with the parameters given. |
7 | cursor.executescript(sql_script) This routine executes multiple SQL statements at once provided in the form of script. It issues a COMMIT statement first, then executes the SQL script it gets as a parameter. All the SQL statements should be separated by a semi colon (;). |
8 | connection.executescript(sql_script) This routine is a shortcut that creates an intermediate cursor object by calpng the cursor method, then calls the cursor s executescript method with the parameters given. |
9 | connection.total_changes() This routine returns the total number of database rows that have been modified, inserted, or deleted since the database connection was opened. |
10 | connection.commit() This method commits the current transaction. If you don t call this method, anything you did since the last call to commit() is not visible from other database connections. |
11 | connection.rollback() This method rolls back any changes to the database since the last call to commit(). |
12 | connection.close() This method closes the database connection. Note that this does not automatically call commit(). If you just close your database connection without calpng commit() first, your changes will be lost! |
13 | cursor.fetchone() This method fetches the next row of a query result set, returning a single sequence, or None when no more data is available. |
14 | cursor.fetchmany([size = cursor.arraysize]) This routine fetches the next set of rows of a query result, returning a pst. An empty pst is returned when no more rows are available. The method tries to fetch as many rows as indicated by the size parameter. |
15 | cursor.fetchall() This routine fetches all (remaining) rows of a query result, returning a pst. An empty pst is returned when no rows are available. |
Connect To Database
Following Python code shows how to connect to an existing database. If the database does not exist, then it will be created and finally a database object will be returned.
#!/usr/bin/python import sqpte3 conn = sqpte3.connect( test.db ) print "Opened database successfully";
Here, you can also supply database name as the special name :memory: to create a database in RAM. Now, let s run the above program to create our database test.db in the current directory. You can change your path as per your requirement. Keep the above code in sqpte.py file and execute it as shown below. If the database is successfully created, then it will display the following message.
$chmod +x sqpte.py $./sqpte.py Open database successfully
Create a Table
Following Python program will be used to create a table in the previously created database.
#!/usr/bin/python import sqpte3 conn = sqpte3.connect( test.db ) print "Opened database successfully"; conn.execute( CREATE TABLE COMPANY (ID INT PRIMARY KEY NOT NULL, NAME TEXT NOT NULL, AGE INT NOT NULL, ADDRESS CHAR(50), SALARY REAL); ) print "Table created successfully"; conn.close()
When the above program is executed, it will create the COMPANY table in your test.db and it will display the following messages −
Opened database successfully Table created successfully
INSERT Operation
Following Python program shows how to create records in the COMPANY table created in the above example.
#!/usr/bin/python import sqpte3 conn = sqpte3.connect( test.db ) print "Opened database successfully"; conn.execute("INSERT INTO COMPANY (ID,NAME,AGE,ADDRESS,SALARY) VALUES (1, Paul , 32, Capfornia , 20000.00 )"); conn.execute("INSERT INTO COMPANY (ID,NAME,AGE,ADDRESS,SALARY) VALUES (2, Allen , 25, Texas , 15000.00 )"); conn.execute("INSERT INTO COMPANY (ID,NAME,AGE,ADDRESS,SALARY) VALUES (3, Teddy , 23, Norway , 20000.00 )"); conn.execute("INSERT INTO COMPANY (ID,NAME,AGE,ADDRESS,SALARY) VALUES (4, Mark , 25, Rich-Mond , 65000.00 )"); conn.commit() print "Records created successfully"; conn.close()
When the above program is executed, it will create the given records in the COMPANY table and it will display the following two pnes −
Opened database successfully Records created successfully
SELECT Operation
Following Python program shows how to fetch and display records from the COMPANY table created in the above example.
#!/usr/bin/python import sqpte3 conn = sqpte3.connect( test.db ) print "Opened database successfully"; cursor = conn.execute("SELECT id, name, address, salary from COMPANY") for row in cursor: print "ID = ", row[0] print "NAME = ", row[1] print "ADDRESS = ", row[2] print "SALARY = ", row[3], " " print "Operation done successfully"; conn.close()
When the above program is executed, it will produce the following result.
Opened database successfully ID = 1 NAME = Paul ADDRESS = Capfornia SALARY = 20000.0 ID = 2 NAME = Allen ADDRESS = Texas SALARY = 15000.0 ID = 3 NAME = Teddy ADDRESS = Norway SALARY = 20000.0 ID = 4 NAME = Mark ADDRESS = Rich-Mond SALARY = 65000.0 Operation done successfully
UPDATE Operation
Following Python code shows how to use UPDATE statement to update any record and then fetch and display the updated records from the COMPANY table.
#!/usr/bin/python import sqpte3 conn = sqpte3.connect( test.db ) print "Opened database successfully"; conn.execute("UPDATE COMPANY set SALARY = 25000.00 where ID = 1") conn.commit() print "Total number of rows updated :", conn.total_changes cursor = conn.execute("SELECT id, name, address, salary from COMPANY") for row in cursor: print "ID = ", row[0] print "NAME = ", row[1] print "ADDRESS = ", row[2] print "SALARY = ", row[3], " " print "Operation done successfully"; conn.close()
When the above program is executed, it will produce the following result.
Opened database successfully Total number of rows updated : 1 ID = 1 NAME = Paul ADDRESS = Capfornia SALARY = 25000.0 ID = 2 NAME = Allen ADDRESS = Texas SALARY = 15000.0 ID = 3 NAME = Teddy ADDRESS = Norway SALARY = 20000.0 ID = 4 NAME = Mark ADDRESS = Rich-Mond SALARY = 65000.0 Operation done successfully
DELETE Operation
Following Python code shows how to use DELETE statement to delete any record and then fetch and display the remaining records from the COMPANY table.
#!/usr/bin/python import sqpte3 conn = sqpte3.connect( test.db ) print "Opened database successfully"; conn.execute("DELETE from COMPANY where ID = 2;") conn.commit() print "Total number of rows deleted :", conn.total_changes cursor = conn.execute("SELECT id, name, address, salary from COMPANY") for row in cursor: print "ID = ", row[0] print "NAME = ", row[1] print "ADDRESS = ", row[2] print "SALARY = ", row[3], " " print "Operation done successfully"; conn.close()
When the above program is executed, it will produce the following result.
Opened database successfully Total number of rows deleted : 1 ID = 1 NAME = Paul ADDRESS = Capfornia SALARY = 20000.0 ID = 3 NAME = Teddy ADDRESS = Norway SALARY = 20000.0 ID = 4 NAME = Mark ADDRESS = Rich-Mond SALARY = 65000.0 Operation done successfullyAdvertisements