sqlite3
— DB-API 2.0 interface for SQLite databases¶
Source code: Lib/sqlite3/
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)
('2006-01-05', 'BUY', 'RHAT', 100, 35.14)
('2006-03-28', 'BUY', 'IBM', 1000, 45.0)
('2006-04-06', 'SELL', 'IBM', 500, 53.0)
('2006-04-05', 'BUY', 'MSFT', 1000, 72.0)
See also
- https://www.sqlite.org
The SQLite web page; the documentation describes the syntax and the available data types for the supported SQL dialect.
- https://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.
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
does not include the type, i. e. if you use something like'as "Expiration date [datetime]"'
in your SQL, then we will parse out everything until the first'['
for the column name and strip the preceeding space: the column name would simply be “Expiration date”.
-
sqlite3.
connect
(database[, timeout, detect_types, isolation_level, check_same_thread, factory, cached_statements, uri])¶ Opens a connection to the SQLite database file database. By default returns a
Connection
object, unless a custom factory is given.database is a path-like object giving the pathname (absolute or relative to the current working directory) of the database file to be opened. 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
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. Due to SQLite behaviour, types can’t be detected for generated fields (for examplemax(data)
), even when detect_types parameter is set. In such case, the returned type isstr
.By default, check_same_thread is
True
and only the creating thread may use the connection. If setFalse
, the returned connection may be shared across multiple threads. When using multiple threads with the same connection writing operations should be serialized by the user to avoid data corruption.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.If uri is true, database is interpreted as a URI. This allows you to specify options. For example, to open a database in read-only mode you can use:
db = sqlite3.connect('file:path/to/database?mode=ro', uri=True)
More information about this feature, including a list of recognized options, can be found in the SQLite URI documentation.
Raises an auditing event
sqlite3.connect
with argumentdatabase
.Changed in version 3.4: Added the uri parameter.
Changed in version 3.7: database can now also be a path-like object, not only a string.
-
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 typename and the name of the type in your query are matched in case-insensitive manner.
-
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, float, str or bytes.
-
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 = 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 as 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 set to
True
. Afterwards, you will get tracebacks from callbacks onsys.stderr
. UseFalse
to disable the feature again.
Connection Objects¶
-
class
sqlite3.
Connection
¶ A SQLite database connection has the following attributes and methods:
-
isolation_level
¶ Get or set the current default isolation level.
None
for autocommit mode or one of “DEFERRED”, “IMMEDIATE” or “EXCLUSIVE”. See section Controlling Transactions for a more detailed explanation.
-
in_transaction
¶ True
if a transaction is active (there are uncommitted changes),False
otherwise. Read-only attribute.New in version 3.2.
-
cursor
(factory=Cursor)¶ The cursor method accepts a single optional parameter factory. If supplied, this must be a callable returning an instance of
Cursor
or its subclasses.
-
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 a cursor object by calling the
cursor()
method, calls the cursor’sexecute()
method with the parameters given, and returns the cursor.
-
executemany
(sql[, parameters])¶ This is a nonstandard shortcut that creates a cursor object by calling the
cursor()
method, calls the cursor’sexecutemany()
method with the parameters given, and returns the cursor.
-
executescript
(sql_script)¶ This is a nonstandard shortcut that creates a cursor object by calling the
cursor()
method, calls the cursor’sexecutescript()
method with the given sql_script, and returns the cursor.
-
create_function
(name, num_params, func, *, deterministic=False)¶ 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 (if num_params is -1, the function may take any number of arguments), and func is a Python callable that is called as the SQL function. If deterministic is true, the created function is marked as deterministic, which allows SQLite to perform additional optimizations. This flag is supported by SQLite 3.8.3 or higher,
NotSupportedError
will be raised if used with older versions.The function can return any of the types supported by SQLite: bytes, str, int, float and
None
.Changed in version 3.8: The deterministic parameter was added.
Example:
import sqlite3 import hashlib def md5sum(t): return hashlib.md5(t).hexdigest() con = sqlite3.connect(":memory:") con.create_function("md5", 1, md5sum) cur = con.cursor() cur.execute("select md5(?)", (b"foo",)) print(cur.fetchone()[0]) con.close()
-
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 (if num_params is -1, the function may take any number of arguments), and afinalize
method which will return the final result of the aggregate.The
finalize
method can return any of the types supported by SQLite: bytes, str, int, float andNone
.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]) con.close()
-
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): if string1 == string2: return 0 elif string1 < string2: return 1 else: return -1 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
withNone
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.Returning a non-zero value from the handler function will terminate the currently executing query and cause it to raise an
OperationalError
exception.
-
set_trace_callback
(trace_callback)¶ Registers trace_callback to be called for each SQL statement that is actually executed by the SQLite backend.
The only argument passed to the callback is the statement (as string) that is being executed. The return value of the callback is ignored. Note that the backend does not only run statements passed to the
Cursor.execute()
methods. Other sources include the transaction management of the Python module and the execution of triggers defined in the current database.Passing
None
as trace_callback will disable the trace callback.New in version 3.3.
-
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 3.2.
import sqlite3 con = sqlite3.connect(":memory:") # enable extension loading con.enable_load_extension(True) # Load the fulltext search extension con.execute("select load_extension('./fts3.so')") # alternatively you can load the extension using an API call: # con.load_extension("./fts3.so") # disable extension loading again con.enable_load_extension(False) # example from SQLite wiki con.execute("create virtual table recipe using fts3(name, ingredients)") con.executescript(""" insert into recipe (name, ingredients) values ('broccoli stew', 'broccoli peppers cheese tomatoes'); insert into recipe (name, ingredients) values ('pumpkin stew', 'pumpkin onions garlic celery'); insert into recipe (name, ingredients) values ('broccoli pie', 'broccoli cheese onions flour'); insert into recipe (name, ingredients) values ('pumpkin pie', 'pumpkin sugar flour butter'); """) for row in con.execute("select rowid, name, ingredients from recipe where name match 'pie'"): print(row) con.close()
-
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 3.2.
-
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"]) con.close()
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 tostr
and thesqlite3
module will return Unicode objects forTEXT
. If you want to return bytestrings instead, you can set it tobytes
.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() AUSTRIA = "\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 = bytes cur.execute("select ?", (AUSTRIA,)) row = cur.fetchone() assert type(row[0]) is bytes # 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 appends "foo" to all strings con.text_factory = lambda x: x.decode("utf-8") + "foo" cur.execute("select ?", ("bar",)) row = cur.fetchone() assert row[0] == "barfoo" con.close()
-
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.
Example:
# Convert file existing_db.db to SQL dump file dump.sql import sqlite3 con = sqlite3.connect('existing_db.db') with open('dump.sql', 'w') as f: for line in con.iterdump(): f.write('%s\n' % line) con.close()
-
backup
(target, *, pages=- 1, progress=None, name='main', sleep=0.250)¶ This method makes a backup of a SQLite database even while it’s being accessed by other clients, or concurrently by the same connection. The copy will be written into the mandatory argument target, that must be another
Connection
instance.By default, or when pages is either
0
or a negative integer, the entire database is copied in a single step; otherwise the method performs a loop copying up to pages pages at a time.If progress is specified, it must either be
None
or a callable object that will be executed at each iteration with three integer arguments, respectively the status of the last iteration, the remaining number of pages still to be copied and the total number of pages.The name argument specifies the database name that will be copied: it must be a string containing either
"main"
, the default, to indicate the main database,"temp"
to indicate the temporary database or the name specified after theAS
keyword in anATTACH DATABASE
statement for an attached database.The sleep argument specifies the number of seconds to sleep by between successive attempts to backup remaining pages, can be specified either as an integer or a floating point value.
Example 1, copy an existing database into another:
import sqlite3 def progress(status, remaining, total): print(f'Copied {total-remaining} of {total} pages...') con = sqlite3.connect('existing_db.db') bck = sqlite3.connect('backup.db') with bck: con.backup(bck, pages=1, progress=progress) bck.close() con.close()
Example 2, copy an existing database into a transient copy:
import sqlite3 source = sqlite3.connect('existing_db.db') dest = sqlite3.connect(':memory:') source.backup(dest)
Availability: SQLite 3.6.11 or higher
New in version 3.7.
-
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:
import sqlite3 con = sqlite3.connect(":memory:") cur = con.cursor() cur.execute("create table people (name_last, age)") who = "Yeltsin" age = 72 # This is the qmark style: cur.execute("insert into people values (?, ?)", (who, age)) # And this is the named style: cur.execute("select * from people where name_last=:who and age=:age", {"who": who, "age": age}) print(cur.fetchone()) con.close()
execute()
will only execute a single SQL statement. If you try to execute more than one statement with it, it will raise aWarning
. 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 seq_of_parameters. The
sqlite3
module also allows using an iterator yielding parameters instead of a sequence.import sqlite3 class IterChars: def __init__(self): self.count = ord('a') def __iter__(self): return self def __next__(self): if self.count > ord('z'): raise StopIteration self.count += 1 return (chr(self.count - 1),) # this is a 1-tuple con = sqlite3.connect(":memory:") cur = con.cursor() cur.execute("create table characters(c)") theIter = IterChars() cur.executemany("insert into characters(c) values (?)", theIter) cur.execute("select c from characters") print(cur.fetchall()) con.close()
Here’s a shorter example using a generator:
import sqlite3 import string def char_generator(): for c in string.ascii_lowercase: yield (c,) con = sqlite3.connect(":memory:") cur = con.cursor() cur.execute("create table characters(c)") cur.executemany("insert into characters(c) values (?)", char_generator()) cur.execute("select c from characters") print(cur.fetchall()) con.close()
-
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 an instance of
str
.Example:
import sqlite3 con = sqlite3.connect(":memory:") cur = con.cursor() cur.executescript(""" create table person( firstname, lastname, age ); create table book( title, author, published ); insert into book(title, author, published) values ( 'Dirk Gently''s Holistic Detective Agency', 'Douglas Adams', 1987 ); """) con.close()
-
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.
-
close
()¶ Close the cursor now (rather than whenever
__del__
is called).The cursor will be unusable from this point forward; a
ProgrammingError
exception will be raised if any operation is attempted with the cursor.
-
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
or aREPLACE
statement using theexecute()
method. For operations other thanINSERT
orREPLACE
or whenexecutemany()
is called,lastrowid
is set toNone
.If the
INSERT
orREPLACE
statement failed to insert the previous successful rowid is returned.Changed in version 3.6: Added support for the
REPLACE
statement.
-
arraysize
¶ Read/write attribute that controls the number of rows returned by
fetchmany()
. The default value is 1 which means a single row would be fetched per call.
-
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
-
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.-
keys
()¶ This method returns a list of column names. Immediately after a query, it is the first member of each tuple in
Cursor.description
.
Changed in version 3.5: Added support of slicing.
-
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)
<class 'sqlite3.Row'>
>>> tuple(r)
('2006-01-05', 'BUY', 'RHAT', 100.0, 35.14)
>>> len(r)
5
>>> r[2]
'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
Exceptions¶
-
exception
sqlite3.
Error
¶ The base class of the other exceptions in this module. It is a subclass of
Exception
.
-
exception
sqlite3.
DatabaseError
¶ Exception raised for errors that are related to the database.
-
exception
sqlite3.
IntegrityError
¶ Exception raised when the relational integrity of the database is affected, e.g. a foreign key check fails. It is a subclass of
DatabaseError
.
-
exception
sqlite3.
ProgrammingError
¶ Exception raised for programming errors, e.g. table not found or already exists, syntax error in the SQL statement, wrong number of parameters specified, etc. It is a subclass of
DatabaseError
.
-
exception
sqlite3.
OperationalError
¶ Exception raised for errors that are related to the database’s operation and not necessarily under the control of the programmer, e.g. an unexpected disconnect occurs, the data source name is not found, a transaction could not be processed, etc. It is a subclass of
DatabaseError
.
-
exception
sqlite3.
NotSupportedError
¶ Exception raised in case a method or database API was used which is not supported by the database, e.g. calling the
rollback()
method on a connection that does not support transaction or has transactions turned off. It is a subclass ofDatabaseError
.
SQLite and Python types¶
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 |
---|---|
|
|
|
|
|
|
|
|
|
This is how SQLite types are converted to Python types by default:
SQLite type |
Python type |
---|---|
|
|
|
|
|
|
|
depends on |
|
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.
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, float, str, bytes.
There are two ways to enable the sqlite3
module to adapt a custom Python
type to one of the supported ones.
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:
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 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
.
import sqlite3
class Point:
def __init__(self, x, y):
self.x, self.y = x, y
def __conform__(self, protocol):
if protocol is sqlite3.PrepareProtocol:
return "%f;%f" % (self.x, self.y)
con = sqlite3.connect(":memory:")
cur = con.cursor()
p = Point(4.0, -3.2)
cur.execute("select ?", (p,))
print(cur.fetchone()[0])
con.close()
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()
.
import sqlite3
class Point:
def __init__(self, x, y):
self.x, self.y = x, y
def adapt_point(point):
return "%f;%f" % (point.x, point.y)
sqlite3.register_adapter(Point, adapt_point)
con = sqlite3.connect(":memory:")
cur = con.cursor()
p = Point(4.0, -3.2)
cur.execute("select ?", (p,))
print(cur.fetchone()[0])
con.close()
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.
import sqlite3
import datetime
import time
def adapt_datetime(ts):
return time.mktime(ts.timetuple())
sqlite3.register_adapter(datetime.datetime, adapt_datetime)
con = sqlite3.connect(":memory:")
cur = con.cursor()
now = datetime.datetime.now()
cur.execute("select ?", (now,))
print(cur.fetchone()[0])
con.close()
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 bytes
object, no
matter under which data type you sent the value to SQLite.
def convert_point(s):
x, y = map(float, s.split(b";"))
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.
import sqlite3
class Point:
def __init__(self, x, y):
self.x, self.y = x, y
def __repr__(self):
return "(%f;%f)" % (self.x, self.y)
def adapt_point(point):
return ("%f;%f" % (point.x, point.y)).encode('ascii')
def convert_point(s):
x, y = list(map(float, s.split(b";")))
return Point(x, y)
# Register the adapter
sqlite3.register_adapter(Point, adapt_point)
# Register the converter
sqlite3.register_converter("point", convert_point)
p = Point(4.0, -3.2)
#########################
# 1) Using declared types
con = sqlite3.connect(":memory:", detect_types=sqlite3.PARSE_DECLTYPES)
cur = con.cursor()
cur.execute("create table test(p point)")
cur.execute("insert into test(p) values (?)", (p,))
cur.execute("select p from test")
print("with declared types:", cur.fetchone()[0])
cur.close()
con.close()
#######################
# 1) Using column names
con = sqlite3.connect(":memory:", detect_types=sqlite3.PARSE_COLNAMES)
cur = con.cursor()
cur.execute("create table test(p)")
cur.execute("insert into test(p) values (?)", (p,))
cur.execute('select p as "p [point]" from test')
print("with column names:", cur.fetchone()[0])
cur.close()
con.close()
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.
import sqlite3
import datetime
con = sqlite3.connect(":memory:", detect_types=sqlite3.PARSE_DECLTYPES|sqlite3.PARSE_COLNAMES)
cur = con.cursor()
cur.execute("create table test(d date, ts timestamp)")
today = datetime.date.today()
now = datetime.datetime.now()
cur.execute("insert into test(d, ts) values (?, ?)", (today, now))
cur.execute("select d, ts from test")
row = cur.fetchone()
print(today, "=>", row[0], type(row[0]))
print(now, "=>", row[1], type(row[1]))
cur.execute('select current_date as "d [date]", current_timestamp as "ts [timestamp]"')
row = cur.fetchone()
print("current_date", row[0], type(row[0]))
print("current_timestamp", row[1], type(row[1]))
con.close()
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.
Controlling Transactions¶
The underlying sqlite3
library operates in autocommit
mode by default,
but the Python sqlite3
module by default does not.
autocommit
mode means that statements that modify the database take effect
immediately. A BEGIN
or SAVEPOINT
statement disables autocommit
mode, and a COMMIT
, a ROLLBACK
, or a RELEASE
that ends the
outermost transaction, turns autocommit
mode back on.
The Python sqlite3
module by default issues a BEGIN
statement
implicitly before a Data Modification Language (DML) statement (i.e.
INSERT
/UPDATE
/DELETE
/REPLACE
).
You can control which kind of BEGIN
statements sqlite3
implicitly
executes via the isolation_level parameter to the connect()
call, or via the isolation_level
property of connections.
If you specify no isolation_level, a plain BEGIN
is used, which is
equivalent to specifying DEFERRED
. Other possible values are IMMEDIATE
and EXCLUSIVE
.
You can disable the sqlite3
module’s implicit transaction management by
setting isolation_level
to None
. This will leave the underlying
sqlite3
library operating in autocommit
mode. You can then completely
control the transaction state by explicitly issuing BEGIN
, ROLLBACK
,
SAVEPOINT
, and RELEASE
statements in your code.
Changed in version 3.6: sqlite3
used to implicitly commit an open transaction before DDL
statements. This is no longer the case.
Using sqlite3
efficiently¶
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.
import sqlite3
persons = [
("Hugo", "Boss"),
("Calvin", "Klein")
]
con = sqlite3.connect(":memory:")
# Create the table
con.execute("create table person(firstname, lastname)")
# Fill the table
con.executemany("insert into person(firstname, lastname) values (?, ?)", persons)
# Print the table contents
for row in con.execute("select firstname, lastname from person"):
print(row)
print("I just deleted", con.execute("delete from person").rowcount, "rows")
# close is not a shortcut method and it's not called automatically,
# so the connection object should be closed manually
con.close()
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:
import sqlite3
con = sqlite3.connect(":memory:")
con.row_factory = sqlite3.Row
cur = con.cursor()
cur.execute("select 'John' as name, 42 as age")
for row in cur:
assert row[0] == row["name"]
assert row["name"] == row["nAmE"]
assert row[1] == row["age"]
assert row[1] == row["AgE"]
con.close()
Using the connection as a context manager¶
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:
import sqlite3
con = sqlite3.connect(":memory:")
con.execute("create table person (id integer primary key, firstname varchar unique)")
# Successful, con.commit() is called automatically afterwards
with con:
con.execute("insert into person(firstname) values (?)", ("Joe",))
# con.rollback() is called after the with block finishes with an exception, the
# exception is still raised and must be caught
try:
with con:
con.execute("insert into person(firstname) values (?)", ("Joe",))
except sqlite3.IntegrityError:
print("couldn't add Joe twice")
# Connection object used as context manager only commits or rollbacks transactions,
# so the connection object should be closed manually
con.close()
Footnotes