11.13. `sqlite3` — DB-API 2.0 interface for SQLite databases¶

New in version 2.5:

New in version 2.5.

SQLite is a C library that provides a lightweight disk-based database that doesn’t require a separate server process and allows accessing the database using a nonstandard variant of the SQL query language. Some applications can use SQLite for internal data storage. It’s also possible to prototype an application using SQLite and then port the code to a larger database such as PostgreSQL or Oracle.

sqlite3 was written by Gerhard Häring and provides a SQL interface compliant with the DB-API 2.0 specification described by PEP 249.

To use the module, you must first create a Connection object that represents the database. Here the data will be stored in the /tmp/example file:

conn = sqlite3.connect('/tmp/example')

You can also supply the special name :memory: to create a database in RAM.

Once you have a Connection, you can create a Cursor object and call its execute() method to perform SQL commands:

c = conn.cursor()

# Create table
c.execute('''create table stocks
(date text, trans text, symbol text,
 qty real, price real)''')

# Insert a row of data
c.execute("""insert into stocks
          values ('2006-01-05','BUY','RHAT',100,35.14)""")

# Save (commit) the changes
conn.commit()

# We can also close the cursor if we are done with it
c.close()

Usually your SQL operations will need to use values from Python variables. You shouldn’t assemble your query using Python’s string operations because doing so is insecure; it makes your program vulnerable to an SQL injection attack.

Instead, use the DB-API’s parameter substitution. Put ? as a placeholder wherever you want to use a value, and then provide a tuple of values as the second argument to the cursor’s execute() method. (Other database modules may use a different placeholder, such as %s or :1.) For example:

# Never do this -- insecure!
symbol = 'IBM'
c.execute("... where symbol = '%s'" % symbol)

# Do this instead
t = (symbol,)
c.execute('select * from stocks where symbol=?', t)

# Larger example
for t in [('2006-03-28', 'BUY', 'IBM', 1000, 45.00),
          ('2006-04-05', 'BUY', 'MSOFT', 1000, 72.00),
          ('2006-04-06', 'SELL', 'IBM', 500, 53.00),
         ]:
    c.execute('insert into stocks values (?,?,?,?,?)', t)

To retrieve data after executing a SELECT statement, you can either treat the cursor as an iterator, call the cursor’s fetchone() method to retrieve a single matching row, or call fetchall() to get a list of the matching rows.

This example uses the iterator form:

>>> c = conn.cursor()
>>> c.execute('select * from stocks order by price')
>>> for row in c:
...    print row
...
(u'2006-01-05', u'BUY', u'RHAT', 100, 35.140000000000001)
(u'2006-03-28', u'BUY', u'IBM', 1000, 45.0)
(u'2006-04-06', u'SELL', u'IBM', 500, 53.0)
(u'2006-04-05', u'BUY', u'MSOFT', 1000, 72.0)
>>>

11.13.1. Module functions and constants¶

sqlite3.PARSE_DECLTYPES¶

This constant is meant to be used with the detect_types parameter of the connect() function.

Setting it makes the sqlite3 module parse the declared type for each column it returns. It will parse out the first word of the declared type, i. e. for “integer primary key”, it will parse out “integer”, or for “number(10)” it will parse out “number”. Then for that column, it will look into the converters dictionary and use the converter function registered for that type there.

sqlite3.PARSE_COLNAMES¶

This constant is meant to be used with the detect_types parameter of the connect() function.

Setting this makes the SQLite interface parse the column name for each column it returns. It will look for a string formed [mytype] in there, and then decide that ‘mytype’ is the type of the column. It will try to find an entry of ‘mytype’ in the converters dictionary and then use the converter function found there to return the value. The column name found in Cursor.description is only the first word of the column name, i. e. if you use something like 'as "x [datetime]"' in your SQL, then we will parse out everything until the first blank for the column name: the column name would simply be “x”.

sqlite3.connect(database[, timeout, isolation_level, detect_types, factory])¶

Opens a connection to the SQLite database file database. You can use ":memory:" to open a database connection to a database that resides in RAM instead of on disk.

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).

For the isolation_level parameter, please see the Connection.isolation_level property of Connection objects.

SQLite natively supports only the types TEXT, INTEGER, FLOAT, BLOB and NULL. If you want to use other types you must add support for them yourself. The detect_types parameter and the using custom converters registered with the module-level register_converter() function allow you to easily do that.

detect_types defaults to 0 (i. e. off, no type detection), you can set it to any combination of PARSE_DECLTYPES and PARSE_COLNAMES to turn type detection on.

By default, the sqlite3 module uses its Connection class for the connect call. You can, however, subclass the Connection class and make connect() use your class instead by providing your class for the factory parameter.

Consult the section SQLite and Python types of this manual for details.

The sqlite3 module internally uses a statement cache to avoid SQL parsing overhead. If you want to explicitly set the number of statements that are cached for the connection, you can set the cached_statements parameter. The currently implemented default is to cache 100 statements.

sqlite3.register_converter(typename, callable)¶: Registers a callable to convert a bytestring from the database into a custom Python type. The callable will be invoked for all database values that are of the type typename. Confer the parameter detect_types of the connect() function for how the type detection works. Note that the case of typename and the name of the type in your query must match!

sqlite3.register_adapter(type, callable)¶: Registers a callable to convert the custom Python type type into one of SQLite’s supported types. The callable callable accepts as single parameter the Python value, and must return a value of the following types: int, long, float, str (UTF-8 encoded), unicode or buffer.

sqlite3.complete_statement(sql)¶

Returns True if the string sql contains one or more complete SQL statements terminated by semicolons. It does not verify that the SQL is syntactically correct, only that there are no unclosed string literals and the statement is terminated by a semicolon.

This can be used to build a shell for SQLite, as in the following example:

# A minimal SQLite shell for experiments

import sqlite3

con = sqlite3.connect(":memory:")
con.isolation_level = None
cur = con.cursor()

buffer = ""

print "Enter your SQL commands to execute in sqlite3."
print "Enter a blank line to exit."

while True:
    line = raw_input()
    if line == "":
        break
    buffer += line
    if sqlite3.complete_statement(buffer):
        try:
            buffer = buffer.strip()
            cur.execute(buffer)

            if buffer.lstrip().upper().startswith("SELECT"):
                print cur.fetchall()
        except sqlite3.Error, e:
            print "An error occurred:", e.args[0]
        buffer = ""

con.close()

sqlite3.enable_callback_tracebacks(flag)¶: By default you will not get any tracebacks in user-defined functions, aggregates, converters, authorizer callbacks etc. If you want to debug them, you can call this function with flag as True. Afterwards, you will get tracebacks from callbacks on sys.stderr. Use False to disable the feature again.

11.13.2. Connection Objects¶

class sqlite3.Connection¶: A SQLite database connection has the following attributes and methods:

Connection.isolation_level¶: Get or set the current isolation level. None for autocommit mode or one of “DEFERRED”, “IMMEDIATE” or “EXCLUSIVE”. See section Controlling Transactions for a more detailed explanation.

Connection.cursor([cursorClass])¶: The cursor method accepts a single optional parameter cursorClass. If supplied, this must be a custom cursor class that extends sqlite3.Cursor.

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 from other database connections. If you wonder why you don’t see the data you’ve written to the database, please check you didn’t forget to call this method.

Connection.rollback()¶: This method rolls back any changes to the database since the last call to commit().

Connection.close()¶: This closes the database connection. Note that this does not automatically call commit(). If you just close your database connection without calling commit() first, your changes will be lost!

Connection.execute(sql[, parameters])¶: This is a nonstandard shortcut that creates an intermediate cursor object by calling the cursor method, then calls the cursor’s execute method with the parameters given.

Connection.executemany(sql[, parameters])¶: This is a nonstandard shortcut that creates an intermediate cursor object by calling the cursor method, then calls the cursor’s executemany method with the parameters given.

Connection.executescript(sql_script)¶: This is a nonstandard shortcut that creates an intermediate cursor object by calling the cursor method, then calls the cursor’s executescript method with the parameters given.

Connection.create_function(name, num_params, func)¶

Creates a user-defined function that you can later use from within SQL statements under the function name name. num_params is the number of parameters the function accepts, and func is a Python callable that is called as the SQL function.

The function can return any of the types supported by SQLite: unicode, str, int, long, float, buffer and None.

Example:

import sqlite3
import md5

def md5sum(t):
    return md5.md5(t).hexdigest()

con = sqlite3.connect(":memory:")
con.create_function("md5", 1, md5sum)
cur = con.cursor()
cur.execute("select md5(?)", ("foo",))
print cur.fetchone()[0]

Connection.create_aggregate(name, num_params, aggregate_class)¶

Creates a user-defined aggregate function.

The aggregate class must implement a step method, which accepts the number of parameters num_params, and a finalize method which will return the final result of the aggregate.

The finalize method can return any of the types supported by SQLite: unicode, str, int, long, float, buffer and None.

Example:

import sqlite3

class MySum:
    def __init__(self):
        self.count = 0

    def step(self, value):
        self.count += value

    def finalize(self):
        return self.count

con = sqlite3.connect(":memory:")
con.create_aggregate("mysum", 1, MySum)
cur = con.cursor()
cur.execute("create table test(i)")
cur.execute("insert into test(i) values (1)")
cur.execute("insert into test(i) values (2)")
cur.execute("select mysum(i) from test")
print cur.fetchone()[0]

Connection.create_collation(name, callable)¶

Creates a collation with the specified name and callable. The callable will be passed two string arguments. It should return -1 if the first is ordered lower than the second, 0 if they are ordered equal and 1 if the first is ordered higher than the second. Note that this controls sorting (ORDER BY in SQL) so your comparisons don’t affect other SQL operations.

Note that the callable will get its parameters as Python bytestrings, which will normally be encoded in UTF-8.

The following example shows a custom collation that sorts “the wrong way”:

import sqlite3

def collate_reverse(string1, string2):
    return -cmp(string1, string2)

con = sqlite3.connect(":memory:")
con.create_collation("reverse", collate_reverse)

cur = con.cursor()
cur.execute("create table test(x)")
cur.executemany("insert into test(x) values (?)", [("a",), ("b",)])
cur.execute("select x from test order by x collate reverse")
for row in cur:
    print row
con.close()

To remove a collation, call create_collation with None as callable:

con.create_collation("reverse", None)

Connection.interrupt()¶: You can call this method from a different thread to abort any queries that might be executing on the connection. The query will then abort and the caller will get an exception.

Connection.set_authorizer(authorizer_callback)¶

This routine registers a callback. The callback is invoked for each attempt to access a column of a table in the database. The callback should return SQLITE_OK if access is allowed, SQLITE_DENY if the entire SQL statement should be aborted with an error and SQLITE_IGNORE if the column should be treated as a NULL value. These constants are available in the sqlite3 module.

The first argument to the callback signifies what kind of operation is to be authorized. The second and third argument will be arguments or None depending on the first argument. The 4th argument is the name of the database (“main”, “temp”, etc.) if applicable. The 5th argument is the name of the inner-most trigger or view that is responsible for the access attempt or None if this access attempt is directly from input SQL code.

Please consult the SQLite documentation about the possible values for the first argument and the meaning of the second and third argument depending on the first one. All necessary constants are available in the sqlite3 module.

Connection.set_progress_handler(handler, n)¶

New in version 2.6:

New in version 2.6.

This routine registers a callback. The callback is invoked for every n instructions of the SQLite virtual machine. This is useful if you want to get called from SQLite during long-running operations, for example to update a GUI.

If you want to clear any previously installed progress handler, call the method with None for handler.

Connection.row_factory¶

You can change this attribute to a callable that accepts the cursor and the original row as a tuple and will return the real result row. This way, you can implement more advanced ways of returning results, such as returning an object that can also access columns by name.

Example:

import sqlite3

def dict_factory(cursor, row):
    d = {}
    for idx, col in enumerate(cursor.description):
        d[col[0]] = row[idx]
    return d

con = sqlite3.connect(":memory:")
con.row_factory = dict_factory
cur = con.cursor()
cur.execute("select 1 as a")
print cur.fetchone()["a"]

If returning a tuple doesn’t suffice and you want name-based access to columns, you should consider setting row_factory to the highly-optimized sqlite3.Row type. Row provides both index-based and case-insensitive name-based access to columns with almost no memory overhead. It will probably be better than your own custom dictionary-based approach or even a db_row based solution.

Connection.text_factory¶

Using this attribute you can control what objects are returned for the TEXT data type. By default, this attribute is set to unicode and the sqlite3 module will return Unicode objects for TEXT. If you want to return bytestrings instead, you can set it to str.

For efficiency reasons, there’s also a way to return Unicode objects only for non-ASCII data, and bytestrings otherwise. To activate it, set this attribute to sqlite3.OptimizedUnicode.

You can also set it to any other callable that accepts a single bytestring parameter and returns the resulting object.

See the following example code for illustration:

import sqlite3

con = sqlite3.connect(":memory:")
cur = con.cursor()

# Create the table
con.execute("create table person(lastname, firstname)")

AUSTRIA = u"\xd6sterreich"

# by default, rows are returned as Unicode
cur.execute("select ?", (AUSTRIA,))
row = cur.fetchone()
assert row[0] == AUSTRIA

# but we can make sqlite3 always return bytestrings ...
con.text_factory = str
cur.execute("select ?", (AUSTRIA,))
row = cur.fetchone()
assert type(row[0]) == str
# the bytestrings will be encoded in UTF-8, unless you stored garbage in the
# database ...
assert row[0] == AUSTRIA.encode("utf-8")

# we can also implement a custom text_factory ...
# here we implement one that will ignore Unicode characters that cannot be
# decoded from UTF-8
con.text_factory = lambda x: unicode(x, "utf-8", "ignore")
cur.execute("select ?", ("this is latin1 and would normally create errors" +
                         u"\xe4\xf6\xfc".encode("latin1"),))
row = cur.fetchone()
assert type(row[0]) == unicode

# sqlite3 offers a built-in optimized text_factory that will return bytestring
# objects, if the data is in ASCII only, and otherwise return unicode objects
con.text_factory = sqlite3.OptimizedUnicode
cur.execute("select ?", (AUSTRIA,))
row = cur.fetchone()
assert type(row[0]) == unicode

cur.execute("select ?", ("Germany",))
row = cur.fetchone()
assert type(row[0]) == str

Connection.total_changes¶: Returns the total number of database rows that have been modified, inserted, or deleted since the database connection was opened.

Connection.iterdump¶

Returns an iterator to dump the database in an SQL text format. Useful when saving an in-memory database for later restoration. This function provides the same capabilities as the .dump command in the sqlite3 shell.

New in version 2.6:

New in version 2.6.

Python type	SQLite type
`None`	`NULL`
`int`	`INTEGER`
`long`	`INTEGER`
`float`	`REAL`
`str` (UTF8-encoded)	`TEXT`
`unicode`	`TEXT`
`buffer`	`BLOB`

SQLite type	Python type
`NULL`	`None`
`INTEGER`	`int` or `long`, depending on size
`REAL`	`float`
`TEXT`	depends on `text_factory`, `unicode` by default
`BLOB`	`buffer`

11.13. `sqlite3` — DB-API 2.0 interface for SQLite databases¶

11.13.1. Module functions and constants¶

11.13.2. Connection Objects¶

11.13.3. Cursor Objects¶

11.13.4. Row Objects¶

11.13.5. SQLite and Python types¶

11.13.5.1. Introduction¶

11.13.5.2. Using adapters to store additional Python types in SQLite databases¶

11.13.5.2.1. Letting your object adapt itself¶

11.13.5.2.2. Registering an adapter callable¶

11.13.5.3. Converting SQLite values to custom Python types¶

11.13.5.4. Default adapters and converters¶

11.13.6. Controlling Transactions¶

11.13.7. Using `sqlite3` efficiently¶

11.13.7.1. Using shortcut methods¶

11.13.7.2. Accessing columns by name instead of by index¶

11.13.7.3. Using the connection as a context manager¶

Table Of Contents

Related Topics

This Page

11.13. sqlite3 — DB-API 2.0 interface for SQLite databases¶

11.13.1. Module functions and constants¶

11.13.2. Connection Objects¶

11.13.3. Cursor Objects¶

11.13.4. Row Objects¶

11.13.5. SQLite and Python types¶

11.13.5.1. Introduction¶

11.13.5.2. Using adapters to store additional Python types in SQLite databases¶

11.13.5.2.1. Letting your object adapt itself¶

11.13.5.2.2. Registering an adapter callable¶

11.13.5.3. Converting SQLite values to custom Python types¶

11.13.5.4. Default adapters and converters¶

11.13.6. Controlling Transactions¶

11.13.7. Using sqlite3 efficiently¶

11.13.7.1. Using shortcut methods¶

11.13.7.2. Accessing columns by name instead of by index¶

11.13.7.3. Using the connection as a context manager¶

11.13. `sqlite3` — DB-API 2.0 interface for SQLite databases¶

11.13.7. Using `sqlite3` efficiently¶