sqlite3 — Interface DB-API 2.0 para bancos de dados SQLite

Código-fonte: Lib/sqlite3/

SQLite é uma biblioteca C que fornece um banco de dados leve baseado em disco que não requer um processo de servidor separado e permite acessar o banco de dados usando uma variante não padrão da linguagem de consulta SQL. Algumas aplicações podem usar SQLite para armazenamento interno de dados. Também é possível prototipar uma aplicação usando SQLite e, em seguida, portar o código para um banco de dados maior, como PostgreSQL ou Oracle.

O módulo sqlite3 foi escrito por Gerhard Häring. Ele fornece uma interface SQL compatível com a especificação DB-API 2.0 descrita pela PEP 249 e requer SQLite 3.7.15 ou mais recente.

Esse documento inclui quatro seções principais:

  • Tutorial ensina como usar o módulo sqlite3.

  • Referência descreve as classes e funções que este módulo define.

  • Guias de como fazer detalha como lidar com tarefas específicas.

  • Explicação fornece informações detalhadas sobre controle de transações.

Ver também

https://www.sqlite.org

A página web do SQLite; a documentação descreve a sintaxe e os tipos de dados disponíveis para o dialeto SQL suportado.

https://www.w3schools.com/sql/

Tutoriais, referências e exemplos para aprender a sintaxe SQL.

PEP 249 - Especificação 2.0 da API de banco de dados

PEP escrita por Marc-André Lemburg.

Tutorial

Neste tutorial, você criará um banco de dados de filmes do Monty Python usando a funcionalidade básica sqlite3. Ele pressupõe uma compreensão fundamental dos conceitos de banco de dados, incluindo cursores e transações.

Primeiro, precisamos criar um novo banco de dados e abrir uma conexão com o banco de dados para permitir que sqlite3 funcione com ele. Chame sqlite3.connect() para criar uma conexão com o banco de dados tutorial.db no diretório de trabalho atual, criando-o implicitamente se ele não existir:

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

O objeto Connection con retornado representa a conexão com o banco de dados em disco.

Para executar instruções SQL e buscar resultados de consultas SQL, precisaremos usar um cursor de banco de dados. Chame con.cursor() para criar o Cursor:

cur = con.cursor()

Agora que temos uma conexão com o banco de dados e um cursor, podemos criar uma tabela de banco de dados movie com colunas para título, ano de lançamento e pontuação da revisão. Para simplificar, podemos apenas usar nomes de colunas na declaração da tabela - graças ao recurso tipagem flexível do SQLite, especificar os tipos de dados é opcional. Execute a instrução CREATE TABLE chamando cur.execute(...):

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

Podemos verificar se a nova tabela foi criada consultando a tabela embutida sqlite_master no SQLite, que agora deve conter uma entrada para a definição da tabela movie (veja The Schema Table para detalhes). Execute essa consulta chamando cur.execute(...), atribua o resultado a res e chame res.fetchone() para buscar a linha resultante:

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

Podemos ver que a tabela foi criada, pois a consulta retorna uma tuple contendo o nome da tabela. Se consultarmos sqlite_master por uma tabela inexistente spam, res.fetchone() retornará None:

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

Agora, adicione duas linhas de dados fornecidos como literais SQL executando uma instrução INSERT, mais uma vez chamando cur.execute(...):

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

A instrução INSERT abre implicitamente uma transação, que precisa ser confirmada antes que as alterações sejam salvas no banco de dados (veja Controle de transações para detalhes). Chame con.commit() no objeto de conexão para confirmar a transação:

con.commit()

Podemos verificar que os dados foram inseridos corretamente executando uma consulta SELECT. Use o já conhecido cur.execute(...) para atribuir o resultado a res e chame res.fetchall() para retornar todas as linhas resultantes.

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

O resultado é uma list de duas tuples, uma por linha, cada uma contendo o valor score dessa linha.

Agora, insira mais três linhas chamando 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.

Observe que espaços reservados ? são usados para vincular data à consulta. Sempre use espaços reservados em vez de formatação de string para vincular valores Python a instruções SQL, para evitar ataques de injeção de SQL (consulte How to use placeholders to bind values in SQL queries para mais detalhes).

Podemos verificar que as novas linhas foram inseridas executando uma consulta SELECT, desta vez iterando sobre os resultados da consulta.

>>> 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")

Cada linha é uma tuple de dois itens (year, title), correspondendo às colunas selecionadas na consulta.

Finalmente, verifique se o banco de dados foi gravado no disco chamando con.close() para fechar a conexão existente, abrir uma nova, criar um novo cursor e, em seguida, consultar o banco de dados.

>>> 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()

Você agora criou um banco de dados SQLite usando o módulo sqlite3, inseriu dados e recuperou valores dele de várias maneiras.

Ver também

Referência

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.

Parâmetros:

  • 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.

  • 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.

  • 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.

  • isolation_level (str | None) – Control legacy transaction handling behaviour. See Connection.isolation_level and Controle de transação através do atributo isolation_level 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).

  • 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.

  • factory (Connection) – A custom subclass of Connection to create the connection with, if not the default Connection class.

  • cached_statements (int) – The number of statements that sqlite3 should internally cache for this connection, to avoid parsing overhead. By default, 128 statements.

  • 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.

  • autocommit (bool) – Control PEP 249 transaction handling behaviour. See Connection.autocommit and Controle de transações através do atributo autocommit for more information. autocommit currently defaults to LEGACY_TRANSACTION_CONTROL. The default will change to False in a future Python release.

Tipo de retorno:

Connection

Raises an auditing event sqlite3.connect with argument database.

Raises an auditing event sqlite3.connect/handle with argument connection_handle.

Alterado na versão 3.4: Adicionado o parâmetro uri.

Alterado na versão 3.7: database can now also be a path-like object, not only a string.

Alterado na versão 3.10: Added the sqlite3.connect/handle auditing event.

Alterado na versão 3.12: Added the autocommit parameter.

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.

Por exemplo:

>>> 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().

See runsource() in Lib/sqlite3/__main__.py for real-world use.

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.

Nota

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

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.

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.

Note: typename and the name of the type in your query are matched case-insensitively.

Constantes do módulo

sqlite3.LEGACY_TRANSACTION_CONTROL

Set autocommit to this constant to select old style (pre-Python 3.12) transaction control behaviour. See Controle de transação através do atributo isolation_level for more information.

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 ([]).

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.

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:

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:

  • Access is allowed (SQLITE_OK),

  • The SQL statement should be aborted with an error (SQLITE_DENY)

  • 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".

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".

Nota

The named DB-API parameter style is also supported.

sqlite3.sqlite_version

Version number of the runtime SQLite library as a string.

sqlite3.sqlite_version_info

Version number of the runtime SQLite library 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:

  1. Single-thread: In this mode, all mutexes are disabled and SQLite is unsafe to use in more than a single thread at once.

  2. 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.

  3. Serialized: In serialized mode, SQLite can be safely used by multiple threads with no restriction.

The mappings from SQLite threading modes to DB-API 2.0 threadsafety levels are 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

Alterado na versão 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.

Descontinuado desde a versão 3.12, será removido na versão 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.

sqlite3.version_info

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

Descontinuado desde a versão 3.12, será removido na versão 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.

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.

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

Novo na versão 3.12.

Ver também

https://www.sqlite.org/c3ref/c_dbconfig_defensive.html

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 Controle de transações.

Ver também

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.

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

Open a Blob handle to an existing BLOB.

Parâmetros:

  • table (str) – The name of the table where the blob is located.

  • column (str) – The name of the column where the blob is located.

  • row (str) – The name of the row where the blob is located.

  • readonly (bool) – Set to True if the blob should be opened without write permissions. Defaults to False.

  • name (str) – The name of the database where the blob is located. Defaults to "main".

Levanta:

OperationalError – When trying to open a blob in a WITHOUT ROWID table.

Tipo de retorno:

Blob

Nota

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

Novo na versão 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.

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.

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.

execute(sql, parameters=(), /)

Create a new Cursor object and call execute() on it with the given sql and parameters. Return the new cursor object.

executemany(sql, parameters, /)

Create a new Cursor object and call executemany() on it with the given sql and parameters. Return the new cursor object.

executescript(sql_script, /)

Create a new Cursor object and call executescript() on it with the given sql_script. Return the new cursor object.

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

Create or remove a user-defined SQL function.

Parâmetros:

  • name (str) – O nome da função SQL.

  • narg (int) – The number of arguments the SQL function can accept. If -1, it may take 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.

  • deterministic (bool) – If True, the created SQL function is marked as deterministic, which allows SQLite to perform additional optimizations.

Levanta:

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

Alterado na versão 3.8: Added the deterministic parameter.

Exemplo:

>>> 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.

Parâmetros:

  • name (str) – The 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.

  • aggregate_class (class | None) –

    Uma classe deve implementar os seguintes métodos:

    The number of arguments that the step() method must accept is controlled by n_arg.

    Set to None to remove an existing SQL aggregate function.

Exemplo:

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.

Parâmetros:

  • 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) –

    Uma classe que deve implementar os seguintes métodos:

    • 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.

Levanta:

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

Novo na versão 3.11.

Exemplo:

# 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.

Alterado na versão 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.

Alterado na versão 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)

Register callable trace_callback to be invoked for each SQL statement that is actually executed by the SQLite backend.

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.

Nota

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.

Novo na versão 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.

Nota

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.

Novo na versão 3.2.

Alterado na versão 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.

Parâmetros:

  • 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.

Novo na versão 3.2.

Alterado na versão 3.10: Added the sqlite3.load_extension auditing event.

Alterado na versão 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.

Exemplo:

# 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('%s\n' % line)
con.close()

Ver também

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.

Parâmetros:

  • 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()

Novo na versão 3.7.

Ver também

How to handle non-UTF-8 text encodings

getlimit(category, /)

Get a connection runtime limit.

Parâmetros:

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

Tipo de retorno:

int

Levanta:

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

Novo na versão 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.

Parâmetros:

  • category (int) – The SQLite limit category to be set.

  • limit (int) – The value of the new limit. If negative, the current limit is unchanged.

Tipo de retorno:

int

Levanta:

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

Novo na versão 3.11.

getconfig(op, /)

Query a boolean connection configuration option.

Parâmetros:

op (int) – A SQLITE_DBCONFIG code.

Tipo de retorno:

bool

Novo na versão 3.12.

setconfig(op, enable=True, /)

Set a boolean connection configuration option.

Parâmetros:

  • op (int) – A SQLITE_DBCONFIG code.

  • enable (bool) – True if the configuration option should be enabled (default); False if it should be disabled.

Novo na versão 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.

Parâmetros:

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

Tipo de retorno:

bytes

Nota

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

Novo na versão 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.

Parâmetros:

  • data (bytes) – A serialized database.

  • name (str) – The database name to deserialize into. Defaults to "main".

Levanta:

Nota

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

Novo na versão 3.11.

autocommit

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

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

See Controle de transações através do atributo autocommit for more details.

Nota

The isolation_level attribute has no effect unless autocommit is LEGACY_TRANSACTION_CONTROL.

Novo na versão 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.

Novo na versão 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".

Nota

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.

Parâmetros:
Levanta:

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.

Descontinuado desde a versão 3.12, será removido na versão 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().

Parâmetros:
Levanta:

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

Exemplo:

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

Nota

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

Descontinuado desde a versão 3.12, será removido na versão 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.

Exemplo:

# 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.

Nota

Inserts into WITHOUT ROWID tables are not recorded.

Alterado na versão 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.

Alterado na versão 3.5: Added support of slicing.

Blob objects

class sqlite3.Blob

Novo na versão 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.

Exceções

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

Novo na versão 3.11.

sqlite_errorname

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

Novo na versão 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:

Tipo Python

Tipo SQLite

None

NULL

int

INTEGER

float

REAL

str

TEXT

bytes

BLOB

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

Tipo SQLite

Tipo Python

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)

Nota

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:

Nota

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().

Obsoleto desde a versão 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.

Novo na versão 3.12.

Guias de como fazer

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()

Nota

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.

Nota

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.

Nota

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()

Nota

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")

Nota

The sqlite3 module API does not support strings containing surrogates.

Ver também

Unicode HOWTO

Explicação

Controle de transações

sqlite3 oferece vários métodos para controlar se, quando e como as transações do banco de dados são abertas e fechadas. Controle de transações através do atributo autocommit é recomendado, enquanto Controle de transação através do atributo isolation_level mantém o comportamento pré-Python 3.12.

Controle de transações através do atributo autocommit

A forma recomendada de controlar o comportamento da transação é através do atributo Connection.autocommit, que deve ser preferencialmente definido usando o parâmetro autocommit de connect().

É sugerido definir autocommit como False, o que implica controle de transação compatível com a PEP 249. Isso significa:

  • sqlite3 garante que uma transação esteja sempre aberta, então connect(), Connection.commit() e Connection.rollback() abrirão implicitamente uma nova transação (imediatamente após fechando a pendência, para as duas últimas). sqlite3 usa instruções BEGIN DEFERRED ao abrir transações.

  • Transações devem ser executadas explicitamente usando commit().

  • Transações devem ser revertidas explicitamente usando rollback().

  • Uma reversão implícita é executada se o banco de dados estiver em estado close() com alterações pendentes.

Defina autocommit como True para ativar o modo autocommit do SQLite. Neste modo, Connection.commit() e Connection.rollback() não têm efeito. Observe que o modo autocommit do SQLite é distinto do atributo Connection.autocommit compatível com PEP 249; use Connection.in_transaction para consultar o modo de confirmação automática do SQLite de baixo nível.

Defina autocommit como LEGACY_TRANSACTION_CONTROL para deixar o comportamento de controle de transação para o atributo Connection.isolation_level. Veja Controle de transação através do atributo isolation_level para mais informações.

Controle de transação através do atributo isolation_level

Nota

A forma recomendada de controlar transações é através do atributo autocommit. Veja Controle de transações através do atributo autocommit.

Se Connection.autocommit estiver definido como LEGACY_TRANSACTION_CONTROL (o padrão), o comportamento da transação é controlado usando o atributo Connection.isolation_level. Caso contrário, isolation_level não tem efeito.

Se o atributo de conexão isolation_level não for None, novas transações são abertas implicitamente antes de execute() e executemany() executa instruções INSERT, UPDATE, DELETE ou REPLACE; para outras instruções, nenhuma manipulação de transação implícita é executada. Use os métodos commit() e rollback() para fazer commit e reverter respectivamente transações pendentes. Você pode escolher o comportamento subjacente de transação do SQLite – isto é, se e que tipo de instruções BEGIN do sqlite3 são executadas implicitamente – através do atributo isolation_level.

Se isolation_level estiver definido como None, nenhuma transação será aberta implicitamente. Isso deixa a biblioteca SQLite subjacente no modo autocommit, mas também permite que o usuário execute sua própria manipulação de transações usando instruções SQL explícitas. O modo de autocommit da biblioteca SQLite subjacente pode ser consultado usando o atributo in_transaction.

O método executescript() compromete implicitamente qualquer transação pendente antes da execução do script SQL fornecido, independentemente do valor de isolation_level.

Alterado na versão 3.6: sqlite3 costumava fazer commit de forma implícita de uma transação aberta antes das instruções DDL. Este não é mais o caso.

Alterado na versão 3.12: A forma recomendada de controlar transações agora é através do atributo autocommit.