13. sqlite3
— DB-API 2.0 interface for SQLite databases¶
Contents
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.
The sqlite3 module was written by Gerhard Häring. It 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
example.db
file:
import sqlite3
conn = sqlite3.connect('example.db')
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 connection if we are done with it.
# Just be sure any changes have been committed or they will be lost.
conn.close()
The data you’ve saved is persistent and is available in subsequent sessions:
import sqlite3
conn = sqlite3.connect('example.db')
c = conn.cursor()
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 (see https://xkcd.com/327/ for humorous example of what can go wrong).
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 = 'RHAT'
c.execute("SELECT * FROM stocks WHERE symbol = '%s'" % symbol)
# Do this instead
t = ('RHAT',)
c.execute('SELECT * FROM stocks WHERE symbol=?', t)
print c.fetchone()
# Larger example that inserts many records at a time
purchases = [('2006-03-28', 'BUY', 'IBM', 1000, 45.00),
('2006-04-05', 'BUY', 'MSFT', 1000, 72.00),
('2006-04-06', 'SELL', 'IBM', 500, 53.00),
]
c.executemany('INSERT INTO stocks VALUES (?,?,?,?,?)', purchases)
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:
>>> for row in c.execute('SELECT * FROM stocks ORDER BY price'):
print row
(u'2006-01-05', u'BUY', u'RHAT', 100, 35.14)
(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'MSFT', 1000, 72.0)
See also
- https://github.com/ghaering/pysqlite
- The pysqlite web page – sqlite3 is developed externally under the name “pysqlite”.
- https://www.sqlite.org
- The SQLite web page; the documentation describes the syntax and the available data types for the supported SQL dialect.
- http://www.w3schools.com/sql/
- Tutorial, reference and examples for learning SQL syntax.
- PEP 249 - Database API Specification 2.0
- PEP written by Marc-André Lemburg.
13.1. Module functions and constants¶
-
sqlite3.
version
¶ The version number of this module, as a string. This is not the version of the SQLite library.
-
sqlite3.
version_info
¶ The version number of this module, as a tuple of integers. This is not the version of the SQLite library.
-
sqlite3.
sqlite_version
¶ The version number of the run-time SQLite library, as a string.
-
sqlite3.
sqlite_version_info
¶ The version number of the run-time SQLite library, as a tuple of integers.
-
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, detect_types, isolation_level, check_same_thread, factory, cached_statements])¶ 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 ofConnection
objects.SQLite natively supports only the types TEXT, INTEGER, REAL, 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
andPARSE_COLNAMES
to turn type detection on.By default, the
sqlite3
module uses itsConnection
class for the connect call. You can, however, subclass theConnection
class and makeconnect()
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:
-
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 set to
True
. Afterwards, you will get tracebacks from callbacks onsys.stderr
. UseFalse
to disable the feature again.
13.2. Connection Objects¶
-
class
sqlite3.
Connection
¶ A SQLite database connection has the following attributes and methods:
-
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.
-
cursor
([cursorClass])¶ The cursor method accepts a single optional parameter cursorClass. If supplied, this must be a custom cursor class that extends
sqlite3.Cursor
.
-
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. 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.
-
close
()¶ This closes the database connection. Note that this does not automatically call
commit()
. If you just close your database connection without callingcommit()
first, your changes will be lost!
-
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.
-
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.
-
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.
-
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:
-
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 afinalize
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:
-
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”:
To remove a collation, call
create_collation
with None as callable:con.create_collation("reverse", None)
-
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.
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 andSQLITE_IGNORE
if the column should be treated as a NULL value. These constants are available in thesqlite3
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 orNone
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.
-
set_progress_handler
(handler, n)¶ 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.New in version 2.6.
-
enable_load_extension
(enabled)¶ This routine allows/disallows the SQLite engine to load SQLite extensions from shared libraries. SQLite extensions can define new functions, aggregates or whole new virtual table implementations. One well-known extension is the fulltext-search extension distributed with SQLite.
Loadable extensions are disabled by default. See [1].
New in version 2.7.
-
load_extension
(path)¶ This routine loads a SQLite extension from a shared library. You have to enable extension loading with
enable_load_extension()
before you can use this routine.Loadable extensions are disabled by default. See [1].
New in version 2.7.
-
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:
If returning a tuple doesn’t suffice and you want name-based access to columns, you should consider setting
row_factory
to the highly-optimizedsqlite3.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.
-
text_factory
¶ Using this attribute you can control what objects are returned for the
TEXT
data type. By default, this attribute is set tounicode
and thesqlite3
module will return Unicode objects forTEXT
. If you want to return bytestrings instead, you can set it tostr
.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:
-
total_changes
¶ Returns the total number of database rows that have been modified, inserted, or deleted since the database connection was opened.
-
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.
Example:
# Convert file existing_db.db to SQL dump file dump.sql import sqlite3, os con = sqlite3.connect('existing_db.db') with open('dump.sql', 'w') as f: for line in con.iterdump(): f.write('%s\n' % line)
-
13.3. Cursor Objects¶
-
class
sqlite3.
Cursor
¶ A
Cursor
instance has the following attributes and methods.-
execute
(sql[, parameters])¶ Executes an SQL statement. The SQL statement may be parameterized (i. e. placeholders instead of SQL literals). The
sqlite3
module supports two kinds of placeholders: question marks (qmark style) and named placeholders (named style).Here’s an example of both styles:
execute()
will only execute a single SQL statement. If you try to execute more than one statement with it, it will raise a Warning. Useexecutescript()
if you want to execute multiple SQL statements with one call.
-
executemany
(sql, seq_of_parameters)¶ Executes an SQL command against all parameter sequences or mappings found in the sequence sql. The
sqlite3
module also allows using an iterator yielding parameters instead of a sequence.Here’s a shorter example using a generator:
-
executescript
(sql_script)¶ This is a nonstandard convenience method for executing multiple SQL statements at once. It issues a
COMMIT
statement first, then executes the SQL script it gets as a parameter.sql_script can be a bytestring or a Unicode string.
Example:
-
fetchone
()¶ Fetches the next row of a query result set, returning a single sequence, or
None
when no more data is available.
-
fetchmany
([size=cursor.arraysize])¶ Fetches the next set of rows of a query result, returning a list. An empty list is returned when no more rows are available.
The number of rows to fetch per call is specified by the size parameter. If it is not given, the cursor’s arraysize determines the number of rows to be fetched. The method should try to fetch as many rows as indicated by the size parameter. If this is not possible due to the specified number of rows not being available, fewer rows may be returned.
Note there are performance considerations involved with the size parameter. For optimal performance, it is usually best to use the arraysize attribute. If the size parameter is used, then it is best for it to retain the same value from one
fetchmany()
call to the next.
-
fetchall
()¶ Fetches all (remaining) rows of a query result, returning a list. Note that the cursor’s arraysize attribute can affect the performance of this operation. An empty list is returned when no rows are available.
-
rowcount
¶ Although the
Cursor
class of thesqlite3
module implements this attribute, the database engine’s own support for the determination of “rows affected”/”rows selected” is quirky.For
executemany()
statements, the number of modifications are summed up intorowcount
.As required by the Python DB API Spec, the
rowcount
attribute “is -1 in case noexecuteXX()
has been performed on the cursor or the rowcount of the last operation is not determinable by the interface”. This includesSELECT
statements because we cannot determine the number of rows a query produced until all rows were fetched.With SQLite versions before 3.6.5,
rowcount
is set to 0 if you make aDELETE FROM table
without any condition.
-
lastrowid
¶ This read-only attribute provides the rowid of the last modified row. It is only set if you issued an
INSERT
statement using theexecute()
method. For operations other thanINSERT
or whenexecutemany()
is called,lastrowid
is set toNone
.
-
description
¶ This read-only attribute provides the column names of the last query. To remain compatible with the Python DB API, it returns a 7-tuple for each column where the last six items of each tuple are
None
.It is set for
SELECT
statements without any matching rows as well.
-
connection
¶ This read-only attribute provides the SQLite database
Connection
used by theCursor
object. ACursor
object created by callingcon.cursor()
will have aconnection
attribute that refers to con:>>> con = sqlite3.connect(":memory:") >>> cur = con.cursor() >>> cur.connection == con True
-
13.4. Row Objects¶
-
class
sqlite3.
Row
¶ A
Row
instance serves as a highly optimizedrow_factory
forConnection
objects. It tries to mimic a tuple in most of its features.It supports mapping access by column name and index, iteration, representation, equality testing and
len()
.If two
Row
objects have exactly the same columns and their members are equal, they compare equal.Changed in version 2.6: Added iteration and equality (hashability).
-
keys
()¶ This method returns a list of column names. Immediately after a query, it is the first member of each tuple in
Cursor.description
.New in version 2.6.
-
Let’s assume we initialize a table as in the example given above:
conn = sqlite3.connect(":memory:")
c = conn.cursor()
c.execute('''create table stocks
(date text, trans text, symbol text,
qty real, price real)''')
c.execute("""insert into stocks
values ('2006-01-05','BUY','RHAT',100,35.14)""")
conn.commit()
c.close()
Now we plug Row
in:
>>> conn.row_factory = sqlite3.Row
>>> c = conn.cursor()
>>> c.execute('select * from stocks')
<sqlite3.Cursor object at 0x7f4e7dd8fa80>
>>> r = c.fetchone()
>>> type(r)
<type 'sqlite3.Row'>
>>> r
(u'2006-01-05', u'BUY', u'RHAT', 100.0, 35.14)
>>> len(r)
5
>>> r[2]
u'RHAT'
>>> r.keys()
['date', 'trans', 'symbol', 'qty', 'price']
>>> r['qty']
100.0
>>> for member in r:
... print member
...
2006-01-05
BUY
RHAT
100.0
35.14
13.5. SQLite and Python types¶
13.5.1. Introduction¶
SQLite natively supports the following types: NULL
, INTEGER
,
REAL
, TEXT
, BLOB
.
The following Python types can thus be sent to SQLite without any problem:
Python type | SQLite type |
---|---|
None |
NULL |
int |
INTEGER |
long |
INTEGER |
float |
REAL |
str (UTF8-encoded) |
TEXT |
unicode |
TEXT |
buffer |
BLOB |
This is how SQLite types are converted to Python types by default:
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 |
The type system of the sqlite3
module is extensible in two ways: you can
store additional Python types in a SQLite database via object adaptation, and
you can let the sqlite3
module convert SQLite types to different Python
types via converters.
13.5.2. Using adapters to store additional Python types in SQLite databases¶
As described before, SQLite supports only a limited set of types natively. To use other Python types with SQLite, you must adapt them to one of the sqlite3 module’s supported types for SQLite: one of NoneType, int, long, float, str, unicode, buffer.
There are two ways to enable the sqlite3
module to adapt a custom Python
type to one of the supported ones.
13.5.2.1. Letting your object adapt itself¶
This is a good approach if you write the class yourself. Let’s suppose you have a class like this:
class Point(object):
def __init__(self, x, y):
self.x, self.y = x, y
Now you want to store the point in a single SQLite column. First you’ll have to
choose one of the supported types first to be used for representing the point.
Let’s just use str and separate the coordinates using a semicolon. Then you need
to give your class a method __conform__(self, protocol)
which must return
the converted value. The parameter protocol will be PrepareProtocol
.
13.5.2.2. Registering an adapter callable¶
The other possibility is to create a function that converts the type to the
string representation and register the function with register_adapter()
.
Note
The type/class to adapt must be a new-style class, i. e. it must have
object
as one of its bases.
The sqlite3
module has two default adapters for Python’s built-in
datetime.date
and datetime.datetime
types. Now let’s suppose
we want to store datetime.datetime
objects not in ISO representation,
but as a Unix timestamp.
13.5.3. Converting SQLite values to custom Python types¶
Writing an adapter lets you send custom Python types to SQLite. But to make it really useful we need to make the Python to SQLite to Python roundtrip work.
Enter converters.
Let’s go back to the Point
class. We stored the x and y coordinates
separated via semicolons as strings in SQLite.
First, we’ll define a converter function that accepts the string as a parameter
and constructs a Point
object from it.
Note
Converter functions always get called with a string, no matter under which data type you sent the value to SQLite.
def convert_point(s):
x, y = map(float, s.split(";"))
return Point(x, y)
Now you need to make the sqlite3
module know that what you select from
the database is actually a point. There are two ways of doing this:
- Implicitly via the declared type
- Explicitly via the column name
Both ways are described in section Module functions and constants, in the entries
for the constants PARSE_DECLTYPES
and PARSE_COLNAMES
.
The following example illustrates both approaches.
13.5.4. Default adapters and converters¶
There are default adapters for the date and datetime types in the datetime module. They will be sent as ISO dates/ISO timestamps to SQLite.
The default converters are registered under the name “date” for
datetime.date
and under the name “timestamp” for
datetime.datetime
.
This way, you can use date/timestamps from Python without any additional fiddling in most cases. The format of the adapters is also compatible with the experimental SQLite date/time functions.
The following example demonstrates this.
If a timestamp stored in SQLite has a fractional part longer than 6 numbers, its value will be truncated to microsecond precision by the timestamp converter.
13.6. Controlling Transactions¶
By default, the sqlite3
module opens transactions implicitly before a
Data Modification Language (DML) statement (i.e.
INSERT
/UPDATE
/DELETE
/REPLACE
), and commits transactions
implicitly before a non-DML, non-query statement (i. e.
anything other than SELECT
or the aforementioned).
So if you are within a transaction and issue a command like CREATE TABLE
...
, VACUUM
, PRAGMA
, the sqlite3
module will commit implicitly
before executing that command. There are two reasons for doing that. The first
is that some of these commands don’t work within transactions. The other reason
is that sqlite3 needs to keep track of the transaction state (if a transaction
is active or not).
You can control which kind of BEGIN
statements sqlite3 implicitly executes
(or none at all) via the isolation_level parameter to the connect()
call, or via the isolation_level
property of connections.
If you want autocommit mode, then set isolation_level
to None.
Otherwise leave it at its default, which will result in a plain “BEGIN” statement, or set it to one of SQLite’s supported isolation levels: “DEFERRED”, “IMMEDIATE” or “EXCLUSIVE”.
13.7. Using sqlite3
efficiently¶
13.7.1. Using shortcut methods¶
Using the nonstandard execute()
, executemany()
and
executescript()
methods of the Connection
object, your code can
be written more concisely because you don’t have to create the (often
superfluous) Cursor
objects explicitly. Instead, the Cursor
objects are created implicitly and these shortcut methods return the cursor
objects. This way, you can execute a SELECT
statement and iterate over it
directly using only a single call on the Connection
object.
13.7.2. Accessing columns by name instead of by index¶
One useful feature of the sqlite3
module is the built-in
sqlite3.Row
class designed to be used as a row factory.
Rows wrapped with this class can be accessed both by index (like tuples) and case-insensitively by name:
13.7.3. Using the connection as a context manager¶
New in version 2.6.
Connection objects can be used as context managers that automatically commit or rollback transactions. In the event of an exception, the transaction is rolled back; otherwise, the transaction is committed:
13.8. Common issues¶
13.8.1. Multithreading¶
Older SQLite versions had issues with sharing connections between threads. That’s why the Python module disallows sharing connections and cursors between threads. If you still try to do so, you will get an exception at runtime.
The only exception is calling the interrupt()
method, which
only makes sense to call from a different thread.
Footnotes
[1] | (1, 2) The sqlite3 module is not built with loadable extension support by default, because some platforms (notably Mac OS X) have SQLite libraries which are compiled without this feature. To get loadable extension support, you must modify setup.py and remove the line that sets SQLITE_OMIT_LOAD_EXTENSION. |