Accessing the database provides a simple and uniform interface to the database that you want to work with, whether it is PostgreSQL, MySQL, SQLite or any other. It doesn’t try to build layers between you and your database. Rather, it tries to make it easy to perform common tasks, and get out of your way when you need to do more advanced things.

Create database object

The first thing to work with databases from is to create a create a database object with web.database(). It returns database object, which has convenient methods for you to use.

Make sure that you have appropriate database library installed (psycopg2 for PostgreSQL, MySQLdb for MySQL, sqlite3 for SQLite).

db = web.database(dbn='postgres', db='dbname', user='username', pw='password')

dbn for MySQL is mysql and sqlite for SQLite. SQLite doesn’t take user pw parameters.

Multiple databases

Working with more databases is not at all difficult with Here’s what you do.

db1 = web.database(dbn='postgres', db='dbname1', user='username1', pw='password2')
db2 = web.database(dbn='postgres', db='dbname2', user='username2', pw='password2')

And use db1, db2 to access those databases respectively.


web.database() returns an object which provide you all the functionality to insert, select, update and delete data from your database. For each of the methods on db below, you can pass _test=True to see the SQL statement rather than executing it.


# Insert an entry into table 'user'
userid = db.insert('user', firstname="Bob", lastname="Smith", joindate=web.SQLLiteral("NOW()"))

The first argument is the table name and the rest of them are set of named arguments which represent the fields in the table. If values are not given, the database may create default values or issue a warning.

For bulk insertion rather than inserting record by record, use Multiple Inserts rather.


The select method is used for selecting rows from the database. It returns a web.iterbetter object, which can be looped through.

To select all the rows from the user table, you would simply do

users ='user')

For the real world use cases, select method takes vars, what, where, order, group, limit, offset, and _test optional parameters.

users ='users', where="id>100")

To prevent SQL injection attacks, you can use $key in where clause and pass the vars which has { ‘key’: value }.

vars = dict(name="Bob")
results ='users', where="name = $name", vars=vars, _test=True)
>>> results
<sql: "SELECT * FROM users WHERE name = 'Bob'">


The update method accepts same kind of arguments as Select. It returns the number of rows updated.

num_updated  = db.update('users', where="id = 10", firstname = "Foo")


The delete method returns the number of rows deleted. It also accepts “using” and “vars” parameters. See Selecting for more details on vars.

num_deleted = db.delete('users', where="id=10")

Multiple Inserts

The multiple_insert method on the db object allows you to do that. All that’s needed is to prepare a list of dictionaries, one for each row to be inserted, each with the same set of keys and pass it to multiple_insert along with the table name. It returns the list of ids of the inserted rows.

The value of db.supports_multiple_insert tells you if your database supports multiple inserts.

values = [{"name": "foo", "email": ""}, {"name": "bar", "email": ""}]
db.multiple_insert('person', values=values)

Advanced querying

Many a times, there is more to do with the database, rather than the simple operations which can be done by insert, select, delete and update - Things like your favorite (or scary) joins, counts etc. All these are possible with query method, which also takes vars.

results = db.query("SELECT COUNT(*) AS total_users FROM users")
print results[0].total_users # prints number of entries in 'users' table

Joining tables

results = db.query("SELECT * FROM entries JOIN users WHERE entries.author_id =")


The database object has a method transaction which starts a new transaction and returns the transaction object. The transaction object can be used to commit or rollback that transaction. It is also possible to have nested transactions.

From Python 2.5 onwards, which support with statements, you would do

with db.transaction():
    userid = db.insert('users', name='foo')
    authorid = db.insert('authors', userid=userid)

For earlier versions of Python, you can do

t = db.transaction()
    userid = db.insert('users', name='foo')
    authorid = db.insert('authors', userid=userid)