sqlite3 — DB-API 2.0 interface for SQLite databases

2024-07-12

sqlite3 — DB-API 2.0 interface for SQLite databases — Python 3.12.4 documentation

`sqlite3` — DB-API 2.0 interface for SQLite databases
sqlite3 — DB-API 2.0 interface to the SQLite database

Source code: Lib/sqlite3/ Source code location：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.
SQLite is a C library that provides a lightweight disk-based database that does not require a separate server process and allows access to the database using a nonstandard variant of the SQL query language. Some applications can use SQLite for internal data storage. In addition, SQLite can be used to prototype an application before migrating the code to a larger database such as PostgreSQL or Oracle.

The sqlite3 module was written by Gerhard Häring. It provides an SQL interface compliant with the DB-API 2.0 specification described by PEP 249, and requires SQLite 3.7.15 or newer.
sqlite3 moduleWritten by Gerhard Häring. It provides a SQL interface compliant with the DB-API 2.0 specification described by PEP 249, and requires SQLite version 3.7.15 or higher.

This document includes four main sections:

Tutorial teaches how to use the sqlite3 module. TutorialPart of it teaches how to use the sqlite3 module.
Reference describes the classes and functions this module defines.
refer toThe <module> section describes the classes and functions defined by this module.
How-to guides details how to handle specific tasks.
Operation GuideSections detail how to handle specific tasks.
Explanation provides in-depth background on transaction control.
explainThe section provides an in-depth background on transaction control.

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.
The SQLite web page; its documentation describes the syntax of the supported SQL dialects and the available data types.

SQL TutorialSQL Tutorial

Tutorial, reference and examples for learning SQL syntax.
Learn SQL syntax with tutorials, references, and examples.

PEP 249- Database API Specification 2.0 PEP 249 - Database API Specification 2.0

PEP written by Marc-André Lemburg.

Tutorial Tutorial

In this tutorial, you will create a database of Monty Python movies using basic sqlite3 functionality. It assumes a fundamental understanding of database concepts, including cursors and transactions.
In this tutorial, you will use basic sqlite3 functionality to create a database about Monty Python movies. This tutorial assumes that you have basic knowledge of database concepts, including cursors and transactions.

First, we need to create a new database and open a database connection to allow sqlite3 to work with it. Call sqlite3.connect() to create a connection to the database tutorial.db in the current working directory, implicitly creating it if it does not exist:
First, we need to create a new database and open a database connection so that sqlite3 can interact with it. Call sqlite3.connect() to create a connection to the tutorial.db database in the current working directory, implicitly and gently creating it if the database does not exist:


import sqlite3
con = sqlite3.connect("tutorial.db")

The returned Connection object con represents the connection to the on-disk database.
The returned Connection object (named con in this example) represents the connection to the database on disk.

In order to execute SQL statements and fetch results from SQL queries, we will need to use a database cursor. Call con.cursor() to create the Cursor:
In order to execute SQL statements and get results from SQL queries, we need to use a database cursor. Call con.cursor() to create a Cursor:

cur = con.cursor()

Now that we’ve got a database connection and a cursor, we can create a database table movie with columns for title, release year, and review score. For simplicity, we can just use column names in the table declaration – thanks to the flexible typing feature of SQLite, specifying the data types is optional. Execute the CREATE TABLE statement by calling cur.execute(...):
Now that we have a database connection and a cursor, we can create a database table called movie with columns such as title, release year, and review score. To simplify things, we can use the column names directly in the table declaration - due to the flexible typing feature of SQLite, specifying the data type is optional. Execute the CREATE TABLE statement by calling cur.execute(...):

cur.execute("CREATE TABLE movie(title, year, score)")

We can verify that the new table has been created by querying the sqlite_master table built-in to SQLite, which should now contain an entry for the movie table definition (see The Schema Table for details). Execute that query by calling cur.execute(...), assign the result to res, and call res.fetchone() to fetch the resulting row:
We can verify that the new table was created by querying SQLite's built-in sqlite_master table, which should now contain an entry for the movie table definition (see the schema table for details). Execute this query by calling cur.execute(...) , assigning the result to res , and calling res.fetchone() to fetch the resulting row:

>>>


>>> res = cur.execute("SELECT name FROM sqlite_master")
>>> res.fetchone()
('movie',)

We can see that the table has been created, as the query returns a tuple containing the table’s name. If we query sqlite_master for a non-existent table spam, res.fetchone() will return None:
We can see that the table was created successfully because the query returned a tuple containing the table name. If we query sqlite_master for a table that does not exist (such as spam), then res.fetchone() will return None.

>>>


>>> res = cur.execute("SELECT name FROM sqlite_master WHERE name='spam'")
>>> res.fetchone() is None
True

Now, add two rows of data supplied as SQL literals by executing an INSERT statement, once again by calling cur.execute(...):
Now, add two rows of data by executing an INSERT statement (again calling cur.execute(...) ), which is provided as SQL literals:


cur.execute("""
    INSERT INTO movie VALUES
        ('Monty Python and the Holy Grail', 1975, 8.2),
        ('And Now for Something Completely Different', 1971, 7.5)
""")

The INSERT statement implicitly opens a transaction, which needs to be committed before changes are saved in the database (see Transaction control for details). Call con.commit() on the connection object to commit the transaction:
The INSERT statement implicitly starts a transaction automatically, which needs to be committed before the changes are saved to the database (see Transaction Control for details). Call con.commit() on the connection object to commit the transaction:

con.commit()

We can verify that the data was inserted correctly by executing a SELECT query. Use the now-familiar cur.execute(...) to assign the result to res, and call res.fetchall() to return all resulting rows:
We can verify that the data was inserted correctly by executing a SELECT query. Use the now familiar cur.execute(...) to assign the result to res and call res.fetchall() to return all result rows:

>>>


>>> res = cur.execute("SELECT score FROM movie")
>>> res.fetchall()
[(8.2,), (7.5,)]

The result is a list of two tuples, one per row, each containing that row’s score value.
The result is a list of two tuples, one for each row and one for the score value for that row.

Now, insert three more rows by calling cur.executemany(...):
Now, insert three more rows by calling cur.executemany(...):


data = [
    ("Monty Python Live at the Hollywood Bowl", 1982, 7.9),
    ("Monty Python's The Meaning of Life", 1983, 7.5),
    ("Monty Python's Life of Brian", 1979, 8.0),
]
cur.executemany("INSERT INTO movie VALUES(?, ?, ?)", data)
con.commit()  # Remember to commit the transaction after executing INSERT.

Notice that ? placeholders are used to bind data to the query. Always use placeholders instead of string formatting to bind Python values to SQL statements, to avoid SQL injection attacks (see How to use placeholders to bind values in SQL queries for more details).
Note that the ? placeholder is used here to bind the data into the query. Always use placeholders instead of string formatting to bind Python values into SQL statements to avoid SQL injection attacks (see "How to use placeholders to bind values in SQL queries" for more details).

We can verify that the new rows were inserted by executing a SELECT query, this time iterating over the results of the query:
We can verify that the new row was inserted by executing a SELECT query, this time we will iterate over the query results:

>>>


>>> for row in cur.execute("SELECT year, title FROM movie ORDER BY year"):
...     print(row)
(1971, 'And Now for Something Completely Different')
(1975, 'Monty Python and the Holy Grail')
(1979, "Monty Python's Life of Brian")
(1982, 'Monty Python Live at the Hollywood Bowl')
(1983, "Monty Python's The Meaning of Life")

Each row is a two-item tuple of (year, title), matching the columns selected in the query.
Each row is a two-element tuple (year, title), which matches the columns selected in the query.

Finally, verify that the database has been written to disk by calling con.close() to close the existing connection, opening a new one, creating a new cursor, then querying the database:
Finally, by callingcon.close()To close the existing database connection, ensure that the database has been written to disk. Then, open a new connection, create a new cursor, and query the database to verify that the data has been successfully written.

>>>


>>> con.close()
>>> new_con = sqlite3.connect("tutorial.db")
>>> new_cur = new_con.cursor()
>>> res = new_cur.execute("SELECT title, year FROM movie ORDER BY score DESC")
>>> title, year = res.fetchone()
>>> print(f'The highest scoring Monty Python movie is {title!r}, released in {year}')
The highest scoring Monty Python movie is 'Monty Python and the Holy Grail', released in 1975
>>> new_con.close()

You’ve now created an SQLite database using the sqlite3 module, inserted data and retrieved values from it in multiple ways.
You have now usedsqlite3The module creates a SQLite database and inserts data and retrieves values from it in various ways.

Reference Parameter Description：

Module functions

sqlite3.connect(database, timeout=5.0, detect_types=0, isolation_level='DEFERRED', check_same_thread=True, factory=sqlite3.Connection, cached_statements=128, uri=False, *, autocommit=sqlite3.LEGACY_TRANSACTION_CONTROL)

Open a connection to an SQLite database. This function is used to open a connection to a SQLite database.

Parameters:

database (path-like object) – The path to the database file to be opened. You can pass ":memory:" to create an SQLite database existing only in memory, and open a connection to it.database (path-like object)
database (path-like object) — This is the path to the database file to open. You can pass":memory:"To create a SQLite database that exists only in memory, and open a .database (path-like object) connected to it.
timeout (float) – How many seconds the connection should wait before raising an OperationalError when a table is locked. If another connection opens a transaction to modify a table, that table will be locked until the transaction is committed. Default five seconds.timeout (float) — When the table is locked, the connection throwsOperationalErrorHow many seconds should be waited before closing the table. If another connection opens a transaction to modify the table, then the table will be locked until the transaction is committed. The default value is five seconds.
detect_types (int) – Control whether and how data types not natively supported by SQLite are looked up to be converted to Python types, using the converters registered with register_converter(). Set it to any combination (using |, bitwise or) of PARSE_DECLTYPES and PARSE_COLNAMES to enable this. Column names takes precedence over declared types if both flags are set. Types cannot be detected for generated fields (for example max(data)), even when the detect_types parameter is set; str will be returned instead. By default (0), type detection is disabled.
detect_types (int)— Controls whether and how to find data types that are not natively supported by SQLite so that they can be usedregister_converter()Registered converters convert them to Python types. Set it toPARSE_DECLTYPESandPARSE_COLNAMESAny combination of (using bitwise or|) to enable this feature. If both flags are set, then Column Name Will take precedence overstatement For spawn zones, these types cannot be detected (e.g.max(data)), even if you setdetect_typesparameters; instead it will returnstrType. By default (0), type detection is disabled.

Insert here
In this passage, who is the subject of are looked up to?
In this English, the subject of "are looked up to" is those "data types not natively supported by SQLite". This sentence means that by usingregister_converter()Registered converters to find and convert data types that are not natively supported by SQLite to Python types. So, the subject is those specific data types that need to be found and converted.

isolation_level (str | None) – Control legacy transaction handling behaviour. See Connection.isolation_level and Transaction control via the isolation_level attribute for more information. Can be "DEFERRED" (default), "EXCLUSIVE" or "IMMEDIATE"; or None to disable opening transactions implicitly. Has no effect unless Connection.autocommit is set to LEGACY_TRANSACTION_CONTROL (the default).
isolation_level(string | None) – Controls legacy transaction behavior. For more information, seeConnection.isolation_leveland “throughisolation_levelAttribute Control Transactions". Can be"DEFERRED"(default value),"EXCLUSIVE"or"IMMEDIATE"; or set toNoneTo disable the implicit automatic opening of transactions.Connection.autocommitSet asLEGACY_TRANSACTION_CONTROL(default), otherwise this setting has no effect.
check_same_thread (bool) – If True (default), ProgrammingError will be raised if the database connection is used by a thread other than the one that created it. If False, the connection may be accessed in multiple threads; write operations may need to be serialized by the user to avoid data corruption. See threadsafety for more information.
check_same_thread(Boolean value) – If set toTrue(default), an error message is raised when a database connection is used by a thread other than the one that created it.ProgrammingErrorException. If set toFalse, multiple threads are allowed to access the connection; however, users may need to serialize (continuously) write operations themselves to avoid data corruption. For more information, seethreadsafetyinstruction of.
factory (Connection) – A custom subclass of Connection to create the connection with, if not the default Connection class.
factory (Connection) – If you do not use the defaultConnectionclass, specify a customConnectionThis parameter allows you to customize the behavior of the database connection according to specific needs or extensions.
cached_statements (int) – The number of statements that sqlite3 should internally cache for this connection, to avoid parsing overhead. By default, 128 statements.
cached_statements (int) – sqlite3The number of statements that should be cached internally for this connection to avoid parsing overhead. By default, 128 statements are cached. This parameter allows you to tune the cache size to optimize performance or memory usage.
uri (bool) – If set to True, database is interpreted as a URI with a file path and an optional query string. The scheme part must be "file:", and the path can be relative or absolute. The query string allows passing parameters to SQLite, enabling various How to work with SQLite URIs.
uri (bool) – If set toTrue,butdatabaseInterpreted as a Uniform Resource Identifier (URI) with a file path and an optional query string. The scheme portion of the URImustThe path is "file:", and can be relative or absolute. The query string allows passing parameters to SQLite, enabling various ways of working with SQLite URIs. This allows more complex database connection options, such as setting read-only mode, specifying cache sizes, etc.
autocommit (bool) – Control PEP 249 transaction handling behaviour. See Connection.autocommit and Transaction control via the autocommit attribute for more information. autocommit currently defaults to LEGACY_TRANSACTION_CONTROL. The default will change to False in a future Python release.
autocommit (bool) – Controls transaction behavior in accordance with PEP 249. For more information, seeConnection.autocommitand "Controlling Transactions with the autocommit Property". Currently,autocommitThe default value is set toLEGACY_TRANSACTION_CONTROL, which means it follows the legacy transaction control behavior of the Python Database API specification (PEP 249). However, in a future version of Python, the default will change toFalse, which means that transactions are not automatically committed by default, requiring users to explicitly control the start and end of transactions.

Please note,*The parameter is used as a separator between positional parameters and keyword parameters in a function definition, indicatingautocommitAll arguments after it must be keyword arguments.

Return type: Return Type：

Connection

Raises an auditing event sqlite3.connect with argument database.
sqlite3.connect: When usingdatabaseThrown when parameters are connected to the database.

Raises an auditing event sqlite3.connect/handle with argument connection_handle.
sqlite3.connect/handle: When the connection handle (connection_handle) is created.

Changed in version 3.4: Added the uri parameter.
In version 3.4: AddeduriParameter that allows the database file to be specified using the URI format.

Changed in version 3.7: database can now also be a path-like object, not only a string.
In version 3.7:databaseThe argument can now be a path-like object, not just a string.

Changed in version 3.10: Added the sqlite3.connect/handle auditing event.
In version 3.10: Addedsqlite3.connect/handleAudit event that is fired when a connection handle is created.

Changed in version 3.12: Added the autocommit parameter.
In version 3.12: AddedautocommitParameters that allow finer control over the autocommit behavior of transactions.

sqlite3.complete_statement(statement)

Return True if the string statement appears to contain one or more complete SQL statements. No syntactic verification or parsing of any kind is performed, other than checking that there are no unclosed string literals and the statement is terminated by a semicolon.
If the stringstatementAppears to contain one or more complete SQL statements, then returnsTrueNo syntax validation or parsing is done, other than checking that there are no unclosed string literals and that statements are terminated with a semicolon.

For example: Example

>>>


>>> sqlite3.complete_statement("SELECT foo FROM bar;")
True
>>> sqlite3.complete_statement("SELECT foo")
False

This function may be useful during command-line input to determine if the entered text seems to form a complete SQL statement, or if additional input is needed before calling execute().
This function may be useful during command line input to help determine whether the text entered looks like a complete SQL statement or not.execute()Whether additional input was required before.

See runsource() in Lib/sqlite3/__main__.py for real-world use.
In practical applications, you can refer toLib/sqlite3/__main__.pymiddlerunsource()function to understand its usage.

sqlite3.enable_callback_tracebacks(flag, /)

Enable or disable callback tracebacks. 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 on sys.stderr. Use False to disable the feature again.
Enable or disable callback tracing. By default, you won't get any tracebacks in user-defined functions, aggregate functions, converters, authorization callbacks, etc. If you want to debug them, you can call this function and setflagSet asTrueAfter that, you will be able tosys.stderrGet trace information from the callback. UseFalseto disable this feature again.

Note

Errors in user-defined function callbacks are logged as unraisable exceptions. Use an unraisable hook handler for introspection of the failed callback.
Errors in user-defined function callbacks are logged as uncaught exceptions. Use the unraisable hook handler to perform introspection on failed callbacks.

This means that when errors occur in callbacks to SQLite's user-defined functions (such as aggregate functions, scalar functions, etc.), these errors are not raised like normal Python exceptions and can be caught by try-except blocks. Instead, they are caught by SQLite or Python's sqlite3 module and logged in some way (usually written to the log or standard error output), but will not interrupt the execution of the program (unless the error is very serious).

To inspect and debug these uncaught exceptions, you can set up an "uncaught hook handler". This handler is a function that Python calls when an uncaught exception occurs, passing it the exception information as a parameter. In this way, you can write code in the handler function to log or inspect these exceptions to help diagnose the problem.

Please note that the specific implementation may vary depending on the version of Python and the implementation details of the sqlite3 module. Therefore, it is recommended to consult the latest Python documentation or the documentation of the sqlite3 module to learn how to set up and use uncaught hook handlers.

**sqlite3.register_adapter(type, adapter, /)**

Register an adapter callable to adapt the Python type type into an SQLite type. The adapter is called with a Python object of type type as its sole argument, and must return a value of a type that SQLite natively understands.
Register an adapter callable object to convert PythontypeThe type is adapted to a type that SQLite can understand natively. This adapter function is implemented in Python as atypeIt is called with an object of type as its only argument, and must return a value of a type natively supported by SQLite.

It should be noted that the "typeTypes can be a bit misleading, because we don’t usually use Python’s built-intypeObjects (that is, types themselves) are stored directly in the database. More commonly, we want to adapt Python objects (which may be instances of custom types) into a format that SQLite can store. However, if you really need to deal withtypeThe object itself (although this is rarely used in practice), you need to write an adapter to convert it to some form that SQLite can store, such as a string representing the name of the type.

However, a more common use case is to provide custom Python types or built-in types such asdatetime、decimal.Decimaletc.) so that they can be correctly stored and retrieved by the SQLite database.

For example, if you have a custom Python classMyClass, and you want to store its instances in a SQLite database, you can write an adapter to convert an instance of this class to a string (or other type) that can be stored in SQLite, and then write a converter to convert the string backMyClassInstance of .

However, for this question, if you just want to process PythontypeIf you want to store objects (i.e. metadata about the type), you could probably write an adapter to return the name of the type (as a string), but this is generally not a common practice when storing objects in a database.

sqlite3.register_converter(typename, converter, /)

Register the converter callable to convert SQLite objects of type typename into a Python object of a specific type. The converter is invoked for all SQLite values of type typename; it is passed a bytes object and should return an object of the desired Python type. Consult the parameter detect_types of connect() for information regarding how type detection works.
Registers a **converter** callable object to convert SQLite data of typetypenameFor all typestypenameSQLite value, this converter is called; it receives abytesobject as an argument and should return an object of the desired Python type. For more information on how type detection works, seeconnect()Functiondetect_typesparameter.

Note: typename and the name of the type in your query are matched case-insensitively.
Notice：typenameThe names of the types in the query are matched in a case-insensitive manner.

Module constants

sqlite3.LEGACY_TRANSACTION_CONTROL

Set autocommit to this constant to select old style (pre-Python 3.12) transaction control behaviour. See Transaction control via the isolation_level attribute for more information.
WillautocommitSet this constant to select the old-style (pre-Python 3.12) transaction control behavior. For more information, see "isolation_levelAttributes control transactions".

sqlite3.PARSE_COLNAMES

Pass this flag value to the detect_types parameter of connect() to look up a converter function by using the type name, parsed from the query column name, as the converter dictionary key. The type name must be wrapped in square brackets ([]).
Pass this flag value toconnect()Functiondetect_typesparameter to find the converter function by looking up the type name resolved from the column name as a key in the converter dictionary. The type name must be enclosed in square brackets ([]).

SELECT p as "p [point]" FROM test;  ! will look up converter "point"

This flag may be combined with PARSE_DECLTYPES using the | (bitwise or) operator.
This flag can be used|(Bitwise OR) Operator ANDPARSE_DECLTYPESIn conjunction with.

sqlite3.PARSE_DECLTYPES

Pass this flag value to the detect_types parameter of connect() to look up a converter function using the declared types for each column. The types are declared when the database table is created. sqlite3 will look up a converter function using the first word of the declared type as the converter dictionary key. For example:
Pass this flag value toconnect()Functiondetect_typesparameter so that the converter function is looked up using the types declared for each column in the database. These types are declared when the database table is created.sqlite3The converter function will be looked up using the first word in the declared type as the key to the converters dictionary. For example:


CREATE TABLE test(
   i integer primary key,  ! will look up a converter named "integer"
   p point,                ! will look up a converter named "point"
   n number(10)            ! will look up a converter named "number"
 )

This flag may be combined with PARSE_COLNAMES using the | (bitwise or) operator.

sqlite3.SQLITE_OK

sqlite3.SQLITE_DENY

sqlite3.SQLITE_IGNORE

Flags that should be returned by the authorizer_callback callable passed to Connection.set_authorizer(), to indicate whether:
Pass toConnection.set_authorizer()ofauthorizer_callbackFlags that the callable should return to indicate:

Access is allowed (SQLITE_OK), access is allowed (SQLITE_OK）
The SQL statement should be aborted with an error (SQLITE_DENY)
The SQL statement should be aborted due to an error (SQLITE_DENY）
The column should be treated as a NULL value (SQLITE_IGNORE)
The column should be treated as a NULL value (SQLITE_IGNORE）

sqlite3.apilevel

String constant stating the supported DB-API level. Required by the DB-API. Hard-coded to "2.0".
The two string constants aresqlite3The modules are defined in the Python Database API specification (DB-API).

sqlite3.paramstyle

String constant stating the type of parameter marker formatting expected by the sqlite3 module. Required by the DB-API. Hard-coded to "qmark".
This string constant specifies thesqlite3The type of parameter marker formatting expected by the module. This is required by the DB-API (Database Application Programming Interface) specification. It is hardcoded as"qmark", which means that when constructing SQL queries, parameter markers should be represented by question marks (?).

Note

The named DB-API parameter style is also supported.

sqlite3.sqlite_version

Version number of the runtime SQLite library as a string.
The version number of the SQLite runtime library, expressed as a string.

sqlite3.sqlite_version_info

Version number of the runtime SQLite library as a tuple of integers.
The version number of the SQLite runtime library, expressed as a tuple of integers.

sqlite3.threadsafety

Integer constant required by the DB-API 2.0, stating the level of thread safety the sqlite3 module supports. This attribute is set based on the default threading mode the underlying SQLite library is compiled with. The SQLite threading modes are:
Integer constant required by DB-API 2.0 indicatingsqlite3The thread safety level supported by the module. This property is set according to the default thread mode used when the underlying SQLite library is compiled. SQLite's thread modes include:

Single-thread: In this mode, all mutexes are disabled and SQLite is unsafe to use in more than a single thread at once.
Single-thread: In this mode, all mutexes are disabled and SQLite is not safe for use by multiple threads at the same time.
Multi-thread: In this mode, SQLite can be safely used by multiple threads provided that no single database connection is used simultaneously in two or more threads.
Multi-thread: In this mode, SQLite can be safely used by multiple threads, provided that any single database connection is not used simultaneously in two or more threads.
Serialized: In serialized mode, SQLite can be safely used by multiple threads with no restriction.
Serialized: In serialized mode, SQLite can be safely used by multiple threads without any restrictions.

The mappings from SQLite threading modes to DB-API 2.0 threadsafety levels are as follows:
The mapping of SQLite's thread modes to DB-API 2.0 thread safety levels is as follows:

SQLite threading mode	threadsafety	SQLITE_THREADSAFE	DB-API 2.0 meaning
single-thread	0	0	Threads may not share the module
multi-thread	1	2	Threads may share the module, but not connections
serialized	3	1	Threads may share the module, connections and cursors

Changed in version 3.11: Set threadsafety dynamically instead of hard-coding it to 1.

sqlite3.version

Version number of this module as a string. This is not the version of the SQLite library.
The version number of this module, expressed as a string.noThe version number of the SQLite library.

Deprecated since version 3.12, will be removed in version 3.14: This constant used to reflect the version number of the pysqlite package, a third-party library which used to upstream changes to sqlite3. Today, it carries no meaning or practical value.
Deprecated since version 3.12, will be removed in version 3.14: This constant was used to reflectpysqliteThe version number of the package,pysqliteIs a third-party library that has been upstreamsqlite3Commit your changes. Now it has no real meaning or practical value.

sqlite3.version_info

Version number of this module as a tuple of integers. This is not the version of the SQLite library.

sqlite3.SQLITE_DBCONFIG_DEFENSIVE

sqlite3.SQLITE_DBCONFIG_DQS_DDL

sqlite3.SQLITE_DBCONFIG_DQS_DML

sqlite3.SQLITE_DBCONFIG_ENABLE_FKEY

sqlite3.SQLITE_DBCONFIG_ENABLE_FTS3_TOKENIZER

sqlite3.SQLITE_DBCONFIG_ENABLE_LOAD_EXTENSION

sqlite3.SQLITE_DBCONFIG_ENABLE_QPSG

sqlite3.SQLITE_DBCONFIG_ENABLE_TRIGGER

sqlite3.SQLITE_DBCONFIG_ENABLE_VIEW

sqlite3.SQLITE_DBCONFIG_LEGACY_ALTER_TABLE

sqlite3.SQLITE_DBCONFIG_LEGACY_FILE_FORMAT

sqlite3.SQLITE_DBCONFIG_NO_CKPT_ON_CLOSE

sqlite3.SQLITE_DBCONFIG_RESET_DATABASE

sqlite3.SQLITE_DBCONFIG_TRIGGER_EQP

sqlite3.SQLITE_DBCONFIG_TRUSTED_SCHEMA

sqlite3.SQLITE_DBCONFIG_WRITABLE_SCHEMA

These constants are used for the Connection.setconfig() and getconfig() methods.
These constants are used forConnection.setconfig()andgetconfig()method.

The availability of these constants varies depending on the version of SQLite Python was compiled with.
The availability of these constants depends on the version of SQLite that SQLitePython was compiled with.

Added in version 3.12.

SQLite docs: Database Connection Configuration Options

Connection objects

class sqlite3.Connection

Each open SQLite database is represented by a Connection object, which is created using sqlite3.connect(). Their main purpose is creating Cursor objects, and Transaction control.

See also

An SQLite database connection has the following attributes and methods:

cursor(factory=Cursor)

Create and return a Cursor object. The cursor method accepts a single optional parameter factory. If supplied, this must be a callable returning an instance of Cursor or its subclasses.
Creates and returns aCursorobject.cursorMethod accepts an optional single parameterfactoryIf provided, this argument must be a callable object that returns aCursoror an instance of its subclasses.

blobopen(table, column, row, /, , readonly=False, name='main'*)

Open a Blob handle to an existing BLOB.

Parameters:

table (str) – The name of the table where the blob is located.
The name of the table that contains the BLOB data.
column (str) – The name of the column where the blob is located.
The name of the column containing the BLOB data.
row (str) – The name of the row where the blob is located.
The name of the row (or more accurately, the row identifier) that contains the BLOB data.
readonly (bool) – Set to True if the blob should be opened without write permissions. Defaults to False.
If set to True, indicates that the BLOB should be opened without write permission. Defaults to False, which allows both reading and writing.
name (str) – The name of the database where the blob is located. Defaults to "main".
The name of the database containing the BLOB data. Defaults to "main", which is the default database name in SQLite.

Raises:

OperationalError – When trying to open a blob in a WITHOUT ROWID table.
When trying withoutROWOccurs when opening BLOB data in a table with ID.

Return type:

Blob

Note

The blob size cannot be changed using the Blob class. Use the SQL function zeroblob to create a blob with a fixed size.

Added in version 3.11.

commit()

Commit any pending transaction to the database. If autocommit is True, or there is no open transaction, this method does nothing. If autocommit is False, a new transaction is implicitly opened if a pending transaction was committed by this method.
Commits any pending transactions to the database. Ifautocommitis True, or there is no open transaction, this method does nothing.autocommitis False, and this method commits a pending transaction, a new transaction is implicitly started.

rollback()

Roll back to the start of any pending transaction. If autocommit is True, or there is no open transaction, this method does nothing. If autocommit is False, a new transaction is implicitly opened if a pending transaction was rolled back by this method.
Roll back to the start of any pending transaction. Ifautocommitis True, or there is no open transaction, this method does nothing.autocommitis False, and this method rolls back a pending transaction, a new transaction is implicitly started.

close()

Close the database connection. If autocommit is False, any pending transaction is implicitly rolled back. If autocommit is True or LEGACY_TRANSACTION_CONTROL, no implicit transaction control is executed. Make sure to commit() before closing to avoid losing pending changes.
Close the database connection. Ifautocommitis False, any pending transactions are implicitly rolled back.autocommitTrue orLEGACY_TRANSACTION_CONTROL(legacy transaction control), no implicit transaction control is performed. Make sure to callcommit()to avoid losing pending changes.

execute(sql, parameters=(), /)

Create a new Cursor object and call execute() on it with the given sql and parameters. Return the new cursor object.
Create a newCursorobject and call it on itexecute()method, passing in the givensqlstatement and parameters. Returns this newCursorobject.

executemany(sql, parameters, /)

Create a new Cursor object and call executemany() on it with the given sql and parameters. Return the new cursor object.
Create a newCursorobject and call it on itexecutemany()method, passing in the givensqlA sequence of statements and parameters. This allows multiple sets of parameters to be executed at once. Returns this newCursorobject.

executescript(sql_script, /)

Create a new Cursor object and call executescript() on it with the given sql_script. Return the new cursor object.
Create a newCursorobject and call it on itexecutescript()method, passing in the given SQL script. This allows the execution of multiple SQL statements separated by semicolons in the script. Return this newCursorobject.

create_function(name, narg, func, , deterministic=False*)

Create or remove a user-defined SQL function.
Creates or removes a user-defined SQL function.

Parameters:

name (str) – The name of the SQL function.
name(str) – Name of the SQL function.
narg (int) – The number of arguments the SQL function can accept. If -1, it may take any number of arguments.
narg(int) – The number of arguments the SQL function can accept. If -1, it means it can accept any number of arguments.
func (callback | None) – A callable that is called when the SQL function is invoked. The callable must return a type natively supported by SQLite. Set to None to remove an existing SQL function.
func(callback | None) – This callable object (callback) will be executed when the SQL function is called. This callable object must return a type that SQLite natively supports. If set to None, the existing SQL function will be removed.
deterministic (bool) – If True, the created SQL function is marked as deterministic, which allows SQLite to perform additional optimizations.
deterministic(bool) – If True, marks created SQL functions as deterministic, which enables SQLite to perform additional optimizations.

Raises:

NotSupportedError – If deterministic is used with SQLite versions older than 3.8.3.

Changed in version 3.8: Added the deterministic parameter.

Example:

>>>


>>> import hashlib
>>> def md5sum(t):
...     return hashlib.md5(t).hexdigest()
>>> con = sqlite3.connect(":memory:")
>>> con.create_function("md5", 1, md5sum)
>>> for row in con.execute("SELECT md5(?)", (b"foo",)):
...     print(row)
('acbd18db4cc2f85cedef654fccc4a4d8',)
>>> con.close()

create_aggregate(name, n_arg, aggregate_class)

Create or remove a user-defined SQL aggregate function.
Creates or removes a user-defined SQL aggregate function.

Parameters:

name (str) – The name of the SQL aggregate function.
name(str) – Name of the SQL aggregate function.
n_arg (int) – The number of arguments the SQL aggregate function can accept. If -1, it may take any number of arguments.
The number of arguments that the SQL aggregate function can accept. If -1, it means it can accept any number of arguments.
aggregate_class (class | None) –

A class must implement the following methods:
A class must implement the following methods:
- step(): Add a row to the aggregate.
- finalize(): Return the final result of the aggregate as a type natively supported by SQLite.
  finalize(): This method is used to return the final result of the aggregation.
The number of arguments that the step() method must accept is controlled by n_arg.
step()The number of parameters a method must accept is determined byn_argcontrol.

Set to None to remove an existing SQL aggregate function.
Set asNoneto remove existing SQL aggregate functions.

Example:


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.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_window_function(name, num_params, aggregate_class, /)

Create or remove a user-defined aggregate window function.

Parameters:

name (str) – The name of the SQL aggregate window function to create or remove.
num_params (int) – The number of arguments the SQL aggregate window function can accept. If -1, it may take any number of arguments.
aggregate_class (class | None) –

A class that must implement the following methods:
- step(): Add a row to the current window.
- value(): Return the current value of the aggregate.
- inverse(): Remove a row from the current window.
- finalize(): Return the final result of the aggregate as a type natively supported by SQLite.
The number of arguments that the step() and value() methods must accept is controlled by num_params.

Set to None to remove an existing SQL aggregate window function.

Raises:

NotSupportedError – If used with a version of SQLite older than 3.25.0, which does not support aggregate window functions.

Added in version 3.11.

Example:

# Example taken from https://www.sqlite.org/windowfunctions.html#udfwinfunc
class WindowSumInt:
    def __init__(self):
        self.count = 0

    def step(self, value):
        """Add a row to the current window."""
        self.count += value

    def value(self):
        """Return the current value of the aggregate."""
        return self.count

    def inverse(self, value):
        """Remove a row from the current window."""
        self.count -= value

    def finalize(self):
        """Return the final value of the aggregate.

        Any clean-up actions should be placed here.
        """
        return self.count


con = sqlite3.connect(":memory:")
cur = con.execute("CREATE TABLE test(x, y)")
values = [
    ("a", 4),
    ("b", 5),
    ("c", 3),
    ("d", 8),
    ("e", 1),
]
cur.executemany("INSERT INTO test VALUES(?, ?)", values)
con.create_window_function("sumint", 1, WindowSumInt)
cur.execute("""
    SELECT x, sumint(y) OVER (
        ORDER BY x ROWS BETWEEN 1 PRECEDING AND 1 FOLLOWING
    ) AS sum_y
    FROM test ORDER BY x
""")
print(cur.fetchall())
con.close()

create_collation(name, callable, /)

Create a collation named name using the collating function callable. callable is passed two string arguments, and it should return an integer:

1 if the first is ordered higher than the second
-1 if the first is ordered lower than the second
0 if they are ordered equal

The following example shows a reverse sorting collation:

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.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()

Remove a collation function by setting callable to None.

Changed in version 3.11: The collation name can contain any Unicode character. Earlier, only ASCII characters were allowed.

interrupt()

Call this method from a different thread to abort any queries that might be executing on the connection. Aborted queries will raise an OperationalError.

set_authorizer(authorizer_callback)

Register callable authorizer_callback to be invoked for each attempt to access a column of a table in the database. The callback should return one of SQLITE_OK, SQLITE_DENY, or SQLITE_IGNORE to signal how access to the column should be handled by the underlying SQLite library.

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.

Passing None as authorizer_callback will disable the authorizer.

Changed in version 3.11: Added support for disabling the authorizer using None.

set_progress_handler(progress_handler, n)

Register callable progress_handler to be 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 progress_handler.

Returning a non-zero value from the handler function will terminate the currently executing query and cause it to raise a DatabaseError exception.

set_trace_callback(trace_callback)

The only argument passed to the callback is the statement (as str) 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 sqlite3 module and the execution of triggers defined in the current database.

Passing None as trace_callback will disable the trace callback.

Note

Exceptions raised in the trace callback are not propagated. As a development and debugging aid, use enable_callback_tracebacks() to enable printing tracebacks from exceptions raised in the trace callback.

Added in version 3.3.

enable_load_extension(enabled, /)

Enable the SQLite engine to load SQLite extensions from shared libraries if enabled is True; else, disallow loading SQLite extensions. 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.

Note

The sqlite3 module is not built with loadable extension support by default, because some platforms (notably macOS) have SQLite libraries which are compiled without this feature. To get loadable extension support, you must pass the --enable-loadable-sqlite-extensions option to configure.

Raises an auditing event sqlite3.enable_load_extension with arguments connection, enabled.

Added in version 3.2.

Changed in version 3.10: Added the sqlite3.enable_load_extension auditing event.

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)

load_extension(path, /, *, entrypoint=None)

Load an SQLite extension from a shared library. Enable extension loading with enable_load_extension() before calling this method.

Parameters:

path (str) – The path to the SQLite extension.
entrypoint (str | None) – Entry point name. If None (the default), SQLite will come up with an entry point name of its own; see the SQLite docs Loading an Extension for details.

Raises an auditing event sqlite3.load_extension with arguments connection, path.

Added in version 3.2.

Changed in version 3.10: Added the sqlite3.load_extension auditing event.

Changed in version 3.12: Added the entrypoint parameter.

iterdump()

Return an iterator to dump the database as SQL source code. Useful when saving an in-memory database for later restoration. Similar to the .dump command in the sqlite3 shell.

Example:

# Convert file example.db to SQL dump file dump.sql
con = sqlite3.connect('example.db')
with open('dump.sql', 'w') as f:
    for line in con.iterdump():
        f.write('%sn' % line)
con.close()

See also

How to handle non-UTF-8 text encodings

backup(target, *, pages=-1, progress=None, name='main', sleep=0.250)

Create a backup of an SQLite database.

Works even if the database is being accessed by other clients or concurrently by the same connection.

Parameters:

target (Connection) – The database connection to save the backup to.
pages (int) – The number of pages to copy at a time. If equal to or less than 0, the entire database is copied in a single step. Defaults to -1.
progress (callback | None) – If set to a callable, it is invoked with three integer arguments for every backup iteration: the status of the last iteration, the remaining number of pages still to be copied, and the total number of pages. Defaults to None.
name (str) – The name of the database to back up. Either "main" (the default) for the main database, "temp" for the temporary database, or the name of a custom database as attached using the ATTACH DATABASE SQL statement.
sleep (float) – The number of seconds to sleep between successive attempts to back up remaining pages.

Example 1, copy an existing database into another:

def progress(status, remaining, total):
    print(f'Copied {total-remaining} of {total} pages...')

src = sqlite3.connect('example.db')
dst = sqlite3.connect('backup.db')
with dst:
    src.backup(dst, pages=1, progress=progress)
dst.close()
src.close()

Example 2, copy an existing database into a transient copy:

src = sqlite3.connect('example.db')
dst = sqlite3.connect(':memory:')
src.backup(dst)
dst.close()
src.close()

Added in version 3.7.

See also

How to handle non-UTF-8 text encodings

getlimit(category, /)

Get a connection runtime limit.

Parameters:

category (int) – The SQLite limit category to be queried.

Return type:

int

Raises:

ProgrammingError – If category is not recognised by the underlying SQLite library.

Example, query the maximum length of an SQL statement for Connection con (the default is 1000000000):

>>>

>>> con.getlimit(sqlite3.SQLITE_LIMIT_SQL_LENGTH)
1000000000

Added in version 3.11.

setlimit(category, limit, /)

Set a connection runtime limit. Attempts to increase a limit above its hard upper bound are silently truncated to the hard upper bound. Regardless of whether or not the limit was changed, the prior value of the limit is returned.

Parameters:

category (int) – The SQLite limit category to be set.
limit (int) – The value of the new limit. If negative, the current limit is unchanged.

Return type:

int

Raises:

ProgrammingError – If category is not recognised by the underlying SQLite library.

Example, limit the number of attached databases to 1 for Connection con (the default limit is 10):

>>>

>>> con.setlimit(sqlite3.SQLITE_LIMIT_ATTACHED, 1)
10
>>> con.getlimit(sqlite3.SQLITE_LIMIT_ATTACHED)
1

Added in version 3.11.

getconfig(op, /)

Query a boolean connection configuration option.

Parameters:

op (int) – A SQLITE_DBCONFIG code.

Return type:

bool

Added in version 3.12.

setconfig(op, enable=True, /)

Set a boolean connection configuration option.

Parameters:

op (int) – A SQLITE_DBCONFIG code.
enable (bool) – True if the configuration option should be enabled (default); False if it should be disabled.

Added in version 3.12.

serialize(*, name='main')

Serialize a database into a bytes object. For an ordinary on-disk database file, the serialization is just a copy of the disk file. For an in-memory database or a “temp” database, the serialization is the same sequence of bytes which would be written to disk if that database were backed up to disk.

Parameters:

name (str) – The database name to be serialized. Defaults to "main".

Return type:

bytes

Note

This method is only available if the underlying SQLite library has the serialize API.

Added in version 3.11.

deserialize(data, /, *, name='main')

Deserialize a serialized database into a Connection. This method causes the database connection to disconnect from database name, and reopen name as an in-memory database based on the serialization contained in data.

Parameters:

data (bytes) – A serialized database.
name (str) – The database name to deserialize into. Defaults to "main".

Raises:

OperationalError – If the database connection is currently involved in a read transaction or a backup operation.
DatabaseError – If data does not contain a valid SQLite database.
OverflowError – If len(data) is larger than 2**63 - 1.

Note

This method is only available if the underlying SQLite library has the deserialize API.

Added in version 3.11.

autocommit

This attribute controls PEP 249-compliant transaction behaviour. autocommit has three allowed values:

False: Select PEP 249-compliant transaction behaviour, implying that sqlite3 ensures a transaction is always open. Use commit() and rollback() to close transactions.

This is the recommended value of autocommit.
True: Use SQLite’s autocommit mode. commit() and rollback() have no effect in this mode.
LEGACY_TRANSACTION_CONTROL: Pre-Python 3.12 (non-PEP 249-compliant) transaction control. See isolation_level for more details.

This is currently the default value of autocommit.

Changing autocommit to False will open a new transaction, and changing it to True will commit any pending transaction.

See Transaction control via the autocommit attribute for more details.

Note

The isolation_level attribute has no effect unless autocommit is LEGACY_TRANSACTION_CONTROL.

Added in version 3.12.

in_transaction

This read-only attribute corresponds to the low-level SQLite autocommit mode.

True if a transaction is active (there are uncommitted changes), False otherwise.

Added in version 3.2.

isolation_level

Controls the legacy transaction handling mode of sqlite3. If set to None, transactions are never implicitly opened. If set to one of "DEFERRED", "IMMEDIATE", or "EXCLUSIVE", corresponding to the underlying SQLite transaction behaviour, implicit transaction management is performed.

If not overridden by the isolation_level parameter of connect(), the default is "", which is an alias for "DEFERRED".

Note

Using autocommit to control transaction handling is recommended over using isolation_level. isolation_level has no effect unless autocommit is set to LEGACY_TRANSACTION_CONTROL (the default).

row_factory

The initial row_factory for Cursor objects created from this connection. Assigning to this attribute does not affect the row_factory of existing cursors belonging to this connection, only new ones. Is None by default, meaning each row is returned as a tuple.

See How to create and use row factories for more details.

text_factory

A callable that accepts a bytes parameter and returns a text representation of it. The callable is invoked for SQLite values with the TEXT data type. By default, this attribute is set to str.

See How to handle non-UTF-8 text encodings for more details.

total_changes

Return the total number of database rows that have been modified, inserted, or deleted since the database connection was opened.

Cursor objects

A Cursor object represents a database cursor which is used to execute SQL statements, and manage the context of a fetch operation. Cursors are created using Connection.cursor(), or by using any of the connection shortcut methods.

Cursor objects are iterators, meaning that if you execute() a SELECT query, you can simply iterate over the cursor to fetch the resulting rows:
for row in cur.execute("SELECT t FROM data"):
    print(row)

class sqlite3.Cursor

A Cursor instance has the following attributes and methods.

execute(sql, parameters=(), /)

Execute a single SQL statement, optionally binding Python values using placeholders.

Parameters:

sql (str) – A single SQL statement.
parameters (dict | sequence) – Python values to bind to placeholders in sql. A dict if named placeholders are used. A sequence if unnamed placeholders are used. See How to use placeholders to bind values in SQL queries.

Raises:

ProgrammingError – If sql contains more than one SQL statement.

If autocommit is LEGACY_TRANSACTION_CONTROL, isolation_level is not None, sql is an INSERT, UPDATE, DELETE, or REPLACE statement, and there is no open transaction, a transaction is implicitly opened before executing sql.

Deprecated since version 3.12, will be removed in version 3.14: DeprecationWarning is emitted if named placeholders are used and parameters is a sequence instead of a dict. Starting with Python 3.14, ProgrammingError will be raised instead.

Use executescript() to execute multiple SQL statements.

executemany(sql, parameters, /)

For every item in parameters, repeatedly execute the parameterized DML SQL statement sql.

Uses the same implicit transaction handling as execute().

Parameters:

sql (str) – A single SQL DML statement.
parameters (iterable) – An iterable of parameters to bind with the placeholders in sql. See How to use placeholders to bind values in SQL queries.

Raises:

ProgrammingError – If sql contains more than one SQL statement, or is not a DML statement.

Example:

rows = [
    ("row1",),
    ("row2",),
]
# cur is an sqlite3.Cursor object
cur.executemany("INSERT INTO data VALUES(?)", rows)

Note

Any resulting rows are discarded, including DML statements with RETURNING clauses.

Deprecated since version 3.12, will be removed in version 3.14: DeprecationWarning is emitted if named placeholders are used and the items in parameters are sequences instead of dicts. Starting with Python 3.14, ProgrammingError will be raised instead.

executescript(sql_script, /)

Execute the SQL statements in sql_script. If the autocommit is LEGACY_TRANSACTION_CONTROL and there is a pending transaction, an implicit COMMIT statement is executed first. No other implicit transaction control is performed; any transaction control must be added to sql_script.

sql_script must be a string.

Example:

# cur is an sqlite3.Cursor object
cur.executescript("""
    BEGIN;
    CREATE TABLE person(firstname, lastname, age);
    CREATE TABLE book(title, author, published);
    CREATE TABLE publisher(name, address);
    COMMIT;
""")

fetchone()

If row_factory is None, return the next row query result set as a tuple. Else, pass it to the row factory and return its result. Return None if no more data is available.

fetchmany(size=cursor.arraysize)

Return the next set of rows of a query result as a list. Return an empty list if no more rows are available.

The number of rows to fetch per call is specified by the size parameter. If size is not given, arraysize determines the number of rows to be fetched. If fewer than size rows are available, as many rows as are available are 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()

Return all (remaining) rows of a query result as a list. Return an empty list if no rows are available. Note that the arraysize attribute can affect the performance of this operation.

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.

setinputsizes(sizes, /)

Required by the DB-API. Does nothing in sqlite3.

setoutputsize(size, column=None, /)

Required by the DB-API. Does nothing in sqlite3.

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.

connection

Read-only attribute that provides the SQLite database Connection belonging to the cursor. A Cursor object created by calling con.cursor() will have a connection attribute that refers to con:

>>>

>>> con = sqlite3.connect(":memory:")
>>> cur = con.cursor()
>>> cur.connection == con
True
>>> con.close()

description

Read-only attribute that 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.

lastrowid

Read-only attribute that provides the row id of the last inserted row. It is only updated after successful INSERT or REPLACE statements using the execute() method. For other statements, after executemany() or executescript(), or if the insertion failed, the value of lastrowid is left unchanged. The initial value of lastrowid is None.

Note

Inserts into WITHOUT ROWID tables are not recorded.

Changed in version 3.6: Added support for the REPLACE statement.

rowcount

Read-only attribute that provides the number of modified rows for INSERT, UPDATE, DELETE, and REPLACE statements; is -1 for other statements, including CTE queries. It is only updated by the execute() and executemany() methods, after the statement has run to completion. This means that any resulting rows must be fetched in order for rowcount to be updated.

row_factory

Control how a row fetched from this Cursor is represented. If None, a row is represented as a tuple. Can be set to the included sqlite3.Row; or a callable that accepts two arguments, a Cursor object and the tuple of row values, and returns a custom object representing an SQLite row.

Defaults to what Connection.row_factory was set to when the Cursor was created. Assigning to this attribute does not affect Connection.row_factory of the parent connection.

See How to create and use row factories for more details.

Row objects

class sqlite3.Row

A Row instance serves as a highly optimized row_factory for Connection objects. It supports iteration, equality testing, len(), and mapping access by column name and index.

Two Row objects compare equal if they have identical column names and values.

See How to create and use row factories for more details.

keys()

Return a list of column names as strings. Immediately after a query, it is the first member of each tuple in Cursor.description.

Changed in version 3.5: Added support of slicing.

Blob objects

class sqlite3.Blob

Added in version 3.11.

A Blob instance is a file-like object that can read and write data in an SQLite BLOB. Call len(blob) to get the size (number of bytes) of the blob. Use indices and slices for direct access to the blob data.

Use the Blob as a context manager to ensure that the blob handle is closed after use.

con = sqlite3.connect(":memory:")
con.execute("CREATE TABLE test(blob_col blob)")
con.execute("INSERT INTO test(blob_col) VALUES(zeroblob(13))")

# Write to our blob, using two write operations:
with con.blobopen("test", "blob_col", 1) as blob:
    blob.write(b"hello, ")
    blob.write(b"world.")
    # Modify the first and last bytes of our blob
    blob[0] = ord("H")
    blob[-1] = ord("!")

# Read the contents of our blob
with con.blobopen("test", "blob_col", 1) as blob:
    greeting = blob.read()

print(greeting)  # outputs "b'Hello, world!'"
con.close()

close()

Close the blob.

The blob will be unusable from this point onward. An Error (or subclass) exception will be raised if any further operation is attempted with the blob.

read(length=-1, /)

Read length bytes of data from the blob at the current offset position. If the end of the blob is reached, the data up to EOF will be returned. When length is not specified, or is negative, read() will read until the end of the blob.

write(data, /)

Write data to the blob at the current offset. This function cannot change the blob length. Writing beyond the end of the blob will raise ValueError.

tell()

Return the current access position of the blob.

seek(offset, origin=os.SEEK_SET, /)

Set the current access position of the blob to offset. The origin argument defaults to os.SEEK_SET (absolute blob positioning). Other values for origin are os.SEEK_CUR (seek relative to the current position) and os.SEEK_END (seek relative to the blob’s end).

PrepareProtocol objects

class sqlite3.PrepareProtocol

The PrepareProtocol type’s single purpose is to act as a PEP 246 style adaption protocol for objects that can adapt themselves to native SQLite types.

Exceptions

The exception hierarchy is defined by the DB-API 2.0 (PEP 249).

exception sqlite3.Warning

This exception is not currently raised by the sqlite3 module, but may be raised by applications using sqlite3, for example if a user-defined function truncates data while inserting. Warning is a subclass of Exception.

exception sqlite3.Error

The base class of the other exceptions in this module. Use this to catch all errors with one single except statement. Error is a subclass of Exception.

If the exception originated from within the SQLite library, the following two attributes are added to the exception:

sqlite_errorcode

The numeric error code from the SQLite API

Added in version 3.11.

sqlite_errorname

The symbolic name of the numeric error code from the SQLite API

Added in version 3.11.

exception sqlite3.InterfaceError

Exception raised for misuse of the low-level SQLite C API. In other words, if this exception is raised, it probably indicates a bug in the sqlite3 module. InterfaceError is a subclass of Error.

exception sqlite3.DatabaseError

Exception raised for errors that are related to the database. This serves as the base exception for several types of database errors. It is only raised implicitly through the specialised subclasses. DatabaseError is a subclass of Error.

exception sqlite3.DataError

Exception raised for errors caused by problems with the processed data, like numeric values out of range, and strings which are too long. DataError 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. For example, the database path is not found, or a transaction could not be processed. OperationalError is a subclass of DatabaseError.

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.InternalError

Exception raised when SQLite encounters an internal error. If this is raised, it may indicate that there is a problem with the runtime SQLite library. InternalError is a subclass of DatabaseError.

exception sqlite3.ProgrammingError

Exception raised for sqlite3 API programming errors, for example supplying the wrong number of bindings to a query, or trying to operate on a closed Connection. ProgrammingError is a subclass of DatabaseError.

exception sqlite3.NotSupportedError

Exception raised in case a method or database API is not supported by the underlying SQLite library. For example, setting deterministic to True in create_function(), if the underlying SQLite library does not support deterministic functions. NotSupportedError is a subclass of DatabaseError.

SQLite and Python types

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`
float	`REAL`
str	`TEXT`
bytes	`BLOB`

This is how SQLite types are converted to Python types by default:

SQLite type	Python type
`NULL`	`None`
`INTEGER`	int
`REAL`	float
`TEXT`	depends on text_factory, str by default
`BLOB`	bytes

The type system of the sqlite3 module is extensible in two ways: you can store additional Python types in an SQLite database via object adapters, and you can let the sqlite3 module convert SQLite types to Python types via converters.

Default adapters and converters (deprecated)

Note

The default adapters and converters are deprecated as of Python 3.12. Instead, use the Adapter and converter recipes and tailor them to your needs.

The deprecated default adapters and converters consist of:

An adapter for datetime.date objects to strings in ISO 8601 format.
An adapter for datetime.datetime objects to strings in ISO 8601 format.
A converter for declared “date” types to datetime.date objects.
A converter for declared “timestamp” types to datetime.datetime objects. Fractional parts will be truncated to 6 digits (microsecond precision).

Note

The default “timestamp” converter ignores UTC offsets in the database and always returns a naive datetime.datetime object. To preserve UTC offsets in timestamps, either leave converters disabled, or register an offset-aware converter with register_converter().

Deprecated since version 3.12.

Command-line interface

The sqlite3 module can be invoked as a script, using the interpreter’s -m switch, in order to provide a simple SQLite shell. The argument signature is as follows:

python -m sqlite3 [-h] [-v] [filename] [sql]

Type .quit or CTRL-D to exit the shell.

-h, --help

Print CLI help.

-v, --version

Print underlying SQLite library version.

Added in version 3.12.

How-to guides

How to use placeholders to bind values in SQL queries

SQL operations usually need to use values from Python variables. However, beware of using Python’s string operations to assemble queries, as they are vulnerable to SQL injection attacks. For example, an attacker can simply close the single quote and inject OR TRUE to select all rows:

>>>

>>> # Never do this -- insecure!
>>> symbol = input()
' OR TRUE; --
>>> sql = "SELECT * FROM stocks WHERE symbol = '%s'" % symbol
>>> print(sql)
SELECT * FROM stocks WHERE symbol = '' OR TRUE; --'
>>> cur.execute(sql)

Instead, use the DB-API’s parameter substitution. To insert a variable into a query string, use a placeholder in the string, and substitute the actual values into the query by providing them as a tuple of values to the second argument of the cursor’s execute() method.

An SQL statement may use one of two kinds of placeholders: question marks (qmark style) or named placeholders (named style). For the qmark style, parameters must be a sequence whose length must match the number of placeholders, or a ProgrammingError is raised. For the named style, parameters must be an instance of a dict (or a subclass), which must contain keys for all named parameters; any extra items are ignored. Here’s an example of both styles:

con = sqlite3.connect(":memory:")
cur = con.execute("CREATE TABLE lang(name, first_appeared)")

# This is the named style used with executemany():
data = (
    {"name": "C", "year": 1972},
    {"name": "Fortran", "year": 1957},
    {"name": "Python", "year": 1991},
    {"name": "Go", "year": 2009},
)
cur.executemany("INSERT INTO lang VALUES(:name, :year)", data)

# This is the qmark style used in a SELECT query:
params = (1972,)
cur.execute("SELECT * FROM lang WHERE first_appeared = ?", params)
print(cur.fetchall())
con.close()

Note

PEP 249 numeric placeholders are not supported. If used, they will be interpreted as named placeholders.

How to adapt custom Python types to SQLite values

SQLite supports only a limited set of data types natively. To store custom Python types in SQLite databases, adapt them to one of the Python types SQLite natively understands.

There are two ways to adapt Python objects to SQLite types: letting your object adapt itself, or using an adapter callable. The latter will take precedence above the former. For a library that exports a custom type, it may make sense to enable that type to adapt itself. As an application developer, it may make more sense to take direct control by registering custom adapter functions.

How to write adaptable objects

Suppose we have a Point class that represents a pair of coordinates, x and y, in a Cartesian coordinate system. The coordinate pair will be stored as a text string in the database, using a semicolon to separate the coordinates. This can be implemented by adding a __conform__(self, protocol) method which returns the adapted value. The object passed to protocol will be of type PrepareProtocol.

class Point:
    def __init__(self, x, y):
        self.x, self.y = x, y

    def __conform__(self, protocol):
        if protocol is sqlite3.PrepareProtocol:
            return f"{self.x};{self.y}"

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

cur.execute("SELECT ?", (Point(4.0, -3.2),))
print(cur.fetchone()[0])
con.close()

How to register adapter callables

The other possibility is to create a function that converts the Python object to an SQLite-compatible type. This function can then be registered using register_adapter().

class Point:
    def __init__(self, x, y):
        self.x, self.y = x, y

def adapt_point(point):
    return f"{point.x};{point.y}"

sqlite3.register_adapter(Point, adapt_point)

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

cur.execute("SELECT ?", (Point(1.0, 2.5),))
print(cur.fetchone()[0])
con.close()

How to convert SQLite values to custom Python types

Writing an adapter lets you convert from custom Python types to SQLite values. To be able to convert from SQLite values to custom Python types, we use 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 are always passed a bytes object, no matter the underlying SQLite data type.

def convert_point(s):
    x, y = map(float, s.split(b";"))
    return Point(x, y)

We now need to tell sqlite3 when it should convert a given SQLite value. This is done when connecting to a database, using the detect_types parameter of connect(). There are three options:

Implicit: set detect_types to PARSE_DECLTYPES
Explicit: set detect_types to PARSE_COLNAMES
Both: set detect_types to sqlite3.PARSE_DECLTYPES | sqlite3.PARSE_COLNAMES. Column names take precedence over declared types.

The following example illustrates the implicit and explicit approaches:

class Point:
    def __init__(self, x, y):
        self.x, self.y = x, y

    def __repr__(self):
        return f"Point({self.x}, {self.y})"

def adapt_point(point):
    return f"{point.x};{point.y}"

def convert_point(s):
    x, y = list(map(float, s.split(b";")))
    return Point(x, y)

# Register the adapter and converter
sqlite3.register_adapter(Point, adapt_point)
sqlite3.register_converter("point", convert_point)

# 1) Parse using declared types
p = Point(4.0, -3.2)
con = sqlite3.connect(":memory:", detect_types=sqlite3.PARSE_DECLTYPES)
cur = con.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()

# 2) Parse using column names
con = sqlite3.connect(":memory:", detect_types=sqlite3.PARSE_COLNAMES)
cur = con.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()

Adapter and converter recipes

This section shows recipes for common adapters and converters.

import datetime
import sqlite3

def adapt_date_iso(val):
    """Adapt datetime.date to ISO 8601 date."""
    return val.isoformat()

def adapt_datetime_iso(val):
    """Adapt datetime.datetime to timezone-naive ISO 8601 date."""
    return val.isoformat()

def adapt_datetime_epoch(val):
    """Adapt datetime.datetime to Unix timestamp."""
    return int(val.timestamp())

sqlite3.register_adapter(datetime.date, adapt_date_iso)
sqlite3.register_adapter(datetime.datetime, adapt_datetime_iso)
sqlite3.register_adapter(datetime.datetime, adapt_datetime_epoch)

def convert_date(val):
    """Convert ISO 8601 date to datetime.date object."""
    return datetime.date.fromisoformat(val.decode())

def convert_datetime(val):
    """Convert ISO 8601 datetime to datetime.datetime object."""
    return datetime.datetime.fromisoformat(val.decode())

def convert_timestamp(val):
    """Convert Unix epoch timestamp to datetime.datetime object."""
    return datetime.datetime.fromtimestamp(int(val))

sqlite3.register_converter("date", convert_date)
sqlite3.register_converter("datetime", convert_datetime)
sqlite3.register_converter("timestamp", convert_timestamp)

How to use connection shortcut methods

Using the execute(), executemany(), and executescript() methods of the Connection class, 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.

# Create and fill the table.
con = sqlite3.connect(":memory:")
con.execute("CREATE TABLE lang(name, first_appeared)")
data = [
    ("C++", 1985),
    ("Objective-C", 1984),
]
con.executemany("INSERT INTO lang(name, first_appeared) VALUES(?, ?)", data)

# Print the table contents
for row in con.execute("SELECT name, first_appeared FROM lang"):
    print(row)

print("I just deleted", con.execute("DELETE FROM lang").rowcount, "rows")

# close() is not a shortcut method and it's not called automatically;
# the connection object should be closed manually
con.close()

How to use the connection context manager

A Connection object can be used as a context manager that automatically commits or rolls back open transactions when leaving the body of the context manager. If the body of the with statement finishes without exceptions, the transaction is committed. If this commit fails, or if the body of the with statement raises an uncaught exception, the transaction is rolled back. If autocommit is False, a new transaction is implicitly opened after committing or rolling back.

If there is no open transaction upon leaving the body of the with statement, or if autocommit is True, the context manager does nothing.

Note

The context manager neither implicitly opens a new transaction nor closes the connection. If you need a closing context manager, consider using contextlib.closing().

con = sqlite3.connect(":memory:")
con.execute("CREATE TABLE lang(id INTEGER PRIMARY KEY, name VARCHAR UNIQUE)")

# Successful, con.commit() is called automatically afterwards
with con:
    con.execute("INSERT INTO lang(name) VALUES(?)", ("Python",))

# 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 lang(name) VALUES(?)", ("Python",))
except sqlite3.IntegrityError:
    print("couldn't add Python twice")

# Connection object used as context manager only commits or rollbacks transactions,
# so the connection object should be closed manually
con.close()

How to work with SQLite URIs

Some useful URI tricks include:

Open a database in read-only mode:

>>>

>>> con = sqlite3.connect("file:tutorial.db?mode=ro", uri=True)
>>> con.execute("CREATE TABLE readonly(data)")
Traceback (most recent call last):
OperationalError: attempt to write a readonly database

Do not implicitly create a new database file if it does not already exist; will raise OperationalError if unable to create a new file:

>>>

>>> con = sqlite3.connect("file:nosuchdb.db?mode=rw", uri=True)
Traceback (most recent call last):
OperationalError: unable to open database file

Create a shared named in-memory database:

db = "file:mem1?mode=memory&cache=shared"
con1 = sqlite3.connect(db, uri=True)
con2 = sqlite3.connect(db, uri=True)
with con1:
    con1.execute("CREATE TABLE shared(data)")
    con1.execute("INSERT INTO shared VALUES(28)")
res = con2.execute("SELECT data FROM shared")
assert res.fetchone() == (28,)

con1.close()
con2.close()

More information about this feature, including a list of parameters, can be found in the SQLite URI documentation.

How to create and use row factories

By default, sqlite3 represents each row as a tuple. If a tuple does not suit your needs, you can use the sqlite3.Row class or a custom row_factory.

While row_factory exists as an attribute both on the Cursor and the Connection, it is recommended to set Connection.row_factory, so all cursors created from the connection will use the same row factory.

Row provides indexed and case-insensitive named access to columns, with minimal memory overhead and performance impact over a tuple. To use Row as a row factory, assign it to the row_factory attribute:

>>>

>>> con = sqlite3.connect(":memory:")
>>> con.row_factory = sqlite3.Row

Queries now return Row objects:

>>>

>>> res = con.execute("SELECT 'Earth' AS name, 6378 AS radius")
>>> row = res.fetchone()
>>> row.keys()
['name', 'radius']
>>> row[0]         # Access by index.
'Earth'
>>> row["name"]    # Access by name.
'Earth'
>>> row["RADIUS"]  # Column names are case-insensitive.
6378
>>> con.close()

Note

The FROM clause can be omitted in the SELECT statement, as in the above example. In such cases, SQLite returns a single row with columns defined by expressions, e.g. literals, with the given aliases expr AS alias.

You can create a custom row_factory that returns each row as a dict, with column names mapped to values:

def dict_factory(cursor, row):
    fields = [column[0] for column in cursor.description]
    return {key: value for key, value in zip(fields, row)}

Using it, queries now return a dict instead of a tuple:

>>>

>>> con = sqlite3.connect(":memory:")
>>> con.row_factory = dict_factory
>>> for row in con.execute("SELECT 1 AS a, 2 AS b"):
...     print(row)
{'a': 1, 'b': 2}
>>> con.close()

The following row factory returns a named tuple:

from collections import namedtuple

def namedtuple_factory(cursor, row):
    fields = [column[0] for column in cursor.description]
    cls = namedtuple("Row", fields)
    return cls._make(row)

namedtuple_factory() can be used as follows:

>>>

>>> con = sqlite3.connect(":memory:")
>>> con.row_factory = namedtuple_factory
>>> cur = con.execute("SELECT 1 AS a, 2 AS b")
>>> row = cur.fetchone()
>>> row
Row(a=1, b=2)
>>> row[0]  # Indexed access.
1
>>> row.b   # Attribute access.
2
>>> con.close()

With some adjustments, the above recipe can be adapted to use a dataclass, or any other custom class, instead of a namedtuple.

How to handle non-UTF-8 text encodings

By default, sqlite3 uses str to adapt SQLite values with the TEXT data type. This works well for UTF-8 encoded text, but it might fail for other encodings and invalid UTF-8. You can use a custom text_factory to handle such cases.

Because of SQLite’s flexible typing, it is not uncommon to encounter table columns with the TEXT data type containing non-UTF-8 encodings, or even arbitrary data. To demonstrate, let’s assume we have a database with ISO-8859-2 (Latin-2) encoded text, for example a table of Czech-English dictionary entries. Assuming we now have a Connection instance con connected to this database, we can decode the Latin-2 encoded text using this text_factory:

con.text_factory = lambda data: str(data, encoding="latin2")

For invalid UTF-8 or arbitrary data in stored in TEXT table columns, you can use the following technique, borrowed from the Unicode HOWTO:

con.text_factory = lambda data: str(data, errors="surrogateescape")

Note

The sqlite3 module API does not support strings containing surrogates.

See also

Unicode HOWTO

Explanation

Transaction control

sqlite3 offers multiple methods of controlling whether, when and how database transactions are opened and closed. Transaction control via the autocommit attribute is recommended, while Transaction control via the isolation_level attribute retains the pre-Python 3.12 behaviour.

Transaction control via the `autocommit` attribute

The recommended way of controlling transaction behaviour is through the Connection.autocommit attribute, which should preferably be set using the autocommit parameter of connect().

It is suggested to set autocommit to False, which implies PEP 249-compliant transaction control. This means:

sqlite3 ensures that a transaction is always open, so connect(), Connection.commit(), and Connection.rollback() will implicitly open a new transaction (immediately after closing the pending one, for the latter two). sqlite3 uses BEGIN DEFERRED statements when opening transactions.
Transactions should be committed explicitly using commit().
Transactions should be rolled back explicitly using rollback().
An implicit rollback is performed if the database is close()-ed with pending changes.

Set autocommit to True to enable SQLite’s autocommit mode. In this mode, Connection.commit() and Connection.rollback() have no effect. Note that SQLite’s autocommit mode is distinct from the PEP 249-compliant Connection.autocommit attribute; use Connection.in_transaction to query the low-level SQLite autocommit mode.

Set autocommit to LEGACY_TRANSACTION_CONTROL to leave transaction control behaviour to the Connection.isolation_level attribute. See Transaction control via the isolation_level attribute for more information.

Transaction control via the `isolation_level` attribute

Note

The recommended way of controlling transactions is via the autocommit attribute. See Transaction control via the autocommit attribute.

If Connection.autocommit is set to LEGACY_TRANSACTION_CONTROL (the default), transaction behaviour is controlled using the Connection.isolation_level attribute. Otherwise, isolation_level has no effect.

If the connection attribute isolation_level is not None, new transactions are implicitly opened before execute() and executemany() executes INSERT, UPDATE, DELETE, or REPLACE statements; for other statements, no implicit transaction handling is performed. Use the commit() and rollback() methods to respectively commit and roll back pending transactions. You can choose the underlying SQLite transaction behaviour — that is, whether and what type of BEGIN statements sqlite3 implicitly executes – via the isolation_level attribute.

If isolation_level is set to None, no transactions are implicitly opened at all. This leaves the underlying SQLite library in autocommit mode, but also allows the user to perform their own transaction handling using explicit SQL statements. The underlying SQLite library autocommit mode can be queried using the in_transaction attribute.

The executescript() method implicitly commits any pending transaction before execution of the given SQL script, regardless of the value of isolation_level.

Changed in version 3.6: sqlite3 used to implicitly commit an open transaction before DDL statements. This is no longer the case.

Changed in version 3.12: The recommended way of controlling transactions is now via the autocommit attribute.

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