sqlite3
--- DB-API 2.0 interface for SQLite databases¶
Code source : Lib/sqlite3/
SQLite est une bibliothèque C qui fournit une base de données légère sur disque ne nécessitant pas de processus serveur et qui utilise une variante (non standard) du langage de requête SQL pour accéder aux données. Certaines applications peuvent utiliser SQLite pour le stockage de données internes. Il est également possible de créer une application prototype utilisant SQLite, puis de modifier le code pour utiliser une base de données plus robuste telle que PostgreSQL ou 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 3.15.2 or newer.
Ce document inclus 4 sections principales :
tutoriel sqlite3 explique comment utiliser le module
sqlite3
.référence sqlite3 décrit les classes et les fonctions que ce module définit.
guide sqlite3 détaille comment gérer des tâches spécifiques.
explications sqlite3 propose un contexte détaillé du contrôle de transaction.
Voir aussi
- https://www.sqlite.org
Dans la page Web de SQLite, la documentation décrit la syntaxe et les types de données disponibles qui sont pris en charge par cette variante SQL.
- https://www.w3schools.com/sql/
Tutoriel, référence et exemples pour apprendre la syntaxe SQL.
- PEP 249 — Spécifications de l'API 2.0 pour la base de données
PEP écrite par Marc-André Lemburg.
Tutoriel¶
Dans ce tutoriel, vous allez créer une base de données des films des Monty Python en utilisant les fonctionnalités de base de sqlite3
. Cela nécessite une compréhension élémentaire des concepts des bases de données, notamment les curseurs et les transactions.
Tout d’abord, nous devons créer une nouvelle base de données et ouvrir une connexion à la base de données pour permettre à sqlite3
de travailler avec elle. Appelez sqlite3.connect()
pour créer une connexion à la base de données tutorial.db
dans le répertoire de travail actuel, en la créant implicitement si elle n’existe pas :
import sqlite3
con = sqlite3.connect("tutorial.db")
L’objet Connection
renvoyé — con
— représente la connexion à la base de données sur disque.
Afin d’exécuter les instructions SQL et de récupérer les résultats des requêtes SQL, nous devrons utiliser un curseur de base de données. Appelez con.cursor()
pour créer la Cursor
:
cur = con.cursor()
Maintenant que nous avons une connexion à la base de données et un curseur, nous pouvons créer une table movie
avec des colonnes pour le titre, l’année de sortie et la note de la critique. Pour plus de simplicité, nous pouvons simplement utiliser les noms des colonnes dans la déclaration de la table — grâce à la fonctionnalité de typage flexible de SQLite, spécifier les types de données est facultatif. Exécutez l’instruction CREATE TABLE
en appelant cur.execute(…)
:
cur.execute("CREATE TABLE movie(title, year, score)")
Nous pouvons vérifier que la nouvelle table a été créée en interrogeant la table sqlite_master
intégrée à SQLite, qui devrait maintenant contenir une entrée pour la définition de la table movie
(voir le schéma Table pour plus de détails). Exécutez cette requête en appelant cur.execute(…)
, affectez le résultat à res
, et appelez res.fetchone()
pour récupérer la ligne résultante :
>>> 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
:
>>> res = cur.execute("SELECT name FROM sqlite_master WHERE name='spam'")
>>> res.fetchone() is None
True
Maintenant, ajoutez deux lignes de données en tant que littéraux SQL en exécutant une instruction INSERT
, une fois encore en appelant 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)
""")
L’instruction INSERT
ouvre implicitement une transaction, qui doit être validée avant que les modifications ne soient enregistrées dans la base de données (voir contrôle des transactions SQL pour plus de détails). Appelez con.commit()
sur l’objet de connexion pour valider la transaction :
con.commit()
Nous pouvons vérifier que les données ont été insérées correctement en exécutant une requête SELECT
. Utilisez la désormais familière cur.execute(…)
pour affecter le résultat à res
, et appelez res.fetchall()
pour retourner toutes les lignes résultantes :
>>> res = cur.execute("SELECT score FROM movie")
>>> res.fetchall()
[(8.2,), (7.5,)]
Le résultat est une liste
de deux tuple
s, une par ligne, chacun contenant la valeur score
de cette ligne.
Maintenant, insérez trois lignes supplémentaires en appelant 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.
Remarquez que les marqueurs ?
sont utilisés pour lier les data
à la requête. Utilisez toujours les marqueurs au lieu d’expressions formatées pour lier les valeurs Python aux instructions SQL, afin d’éviter les injections SQL (voir placeholder SQL pour plus de détails).
Nous pouvons vérifier que les nouvelles lignes ont été insérées en exécutant une requête SELECT
, cette fois-ci en itérant sur les résultats de la requête :
>>> 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")
Chaque ligne est un tuple
de deux éléments (année, titre)
, correspondant aux colonnes sélectionnées dans la requête.
Enfin, vérifiez que la base de données a été écrite sur le disque en appelant con.close()
pour fermer la connexion existante, en ouvrir une nouvelle, créer un nouveau curseur, puis interroger la base de données :
>>> 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()
Vous avez maintenant créé une base de données SQLite à l’aide du module sqlite3
, inséré des données et récupéré des valeurs de plusieurs façons.
Voir aussi
guide sqlite3 pour une lecture plus poussée :
explications sqlite3 pour un contexte détaillé du contrôle de transaction.
Références¶
Fonctions du module¶
- 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)¶
Ouvrez une connexion à une base de données SQLite.
- Paramètres:
database (path-like object) -- Le chemin d’accès au fichier de la base de données à ouvrir. Passez
":memory :"
pour créer une base de données SQLite existant uniquement en mémoire, et ouvrir une connexion à celle-ci.timeout (float) -- Le temps (en secondes) que la connexion doit attendre avant de lever une
OperationalError
, si la table est verrouillée. Si une autre connexion ouvre une transaction pour modifier la table, celle-ci sera verrouillée jusqu’à ce que cette transaction soit validée. Par défaut, cinq secondes.detect_types (int) -- Contrôle si et comment les types de données non nativement pris en charge par SQLite sont recherchés pour être convertis en types Python, en utilisant les convertisseurs enregistrés avec
register_converter()
. Définissez-le à n’importe quelle combinaison (en utilisant|
, opérateurs bit-à-bit OR) dePARSE_DECLTYPES
etPARSE_COLNAMES
pour activer ceci. Les noms de colonnes ont la priorité sur les types déclarés si les deux drapeaux sont activés. Les types ne peuvent pas être détectés pour les champs générés (par exemplemax(data)
), même si le paramètre detect_types est activé ;str
sera retourné à la place. Par défaut (0
), la détection des types est désactivée.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"
; orNone
to disable opening transactions implicitly. Has no effect unlessConnection.autocommit
is set toLEGACY_TRANSACTION_CONTROL
(the default).check_same_thread (bool) -- Si
True
(par défaut),ProgrammingError
sera levée si la connexion à la base de données est utilisée par un thread autre que celui qui l’a créée. SiFalse
, la connexion peut être utilisée par plusieurs threads ; les opérations d’écriture devront peut-être être sérialisées par l’utilisateur pour éviter la corruption des données. Voirsécurité des threads
pour plus d’informations.factory (Connection) -- Une sous-classe personnalisée de
Connection
pour créer la connexion, si ce n’est pas la classe par défautConnection
.cached_statements (int) -- Le nombre d’instructions que
sqlite3
doit mettre en cache en interne pour cette connexion, afin d’éviter les surcharges d’analyse. Par défaut, 128 instructions.uri (bool) -- Si elle a pour valeur
True
, la base de données est interprétée comme un URI avec un chemin d’accès au fichier et une chaîne de requête facultative. La partie schéma doit être"file:"
, et le chemin peut être relatif ou absolu. La chaîne d’interrogation permet de passer des paramètres à SQLite, ce qui permet d’activer diverses astuces d’URI sqlite3.autocommit (bool) -- Control PEP 249 transaction handling behaviour. See
Connection.autocommit
and Transaction control via the autocommit attribute for more information. autocommit currently defaults toLEGACY_TRANSACTION_CONTROL
. The default will change toFalse
in a future Python release.
- Type renvoyé:
Raises an auditing event
sqlite3.connect
with argumentdatabase
.Raises an auditing event
sqlite3.connect/handle
with argumentconnection_handle
.Modifié dans la version 3.4: Added the uri parameter.
Modifié dans la version 3.7: database peut maintenant aussi être un objet de type chemin, et pas seulement une chaîne de caractères.
Modifié dans la version 3.10: Added the
sqlite3.connect/handle
auditing event.Modifié dans la version 3.12: Added the autocommit parameter.
Modifié dans la version 3.13: Positional use of the parameters timeout, detect_types, isolation_level, check_same_thread, factory, cached_statements, and uri is deprecated. They will become keyword-only parameters in Python 3.15.
- sqlite3.complete_statement(statement)¶
Renvoie
True
si la déclaration de la chaîne semble contenir une ou plusieurs déclarations SQL complètes. Aucune vérification syntaxique ou analyse syntaxique d’aucune sorte n’est effectuée, si ce n’est la vérification qu’il n’y a pas de chaîne littérale non fermée et que l’instruction se termine par un point-virgule.Exemple :
>>> sqlite3.complete_statement("SELECT foo FROM bar;") True >>> sqlite3.complete_statement("SELECT foo") False
Cette fonction peut être utile pendant la saisie en ligne de commande pour déterminer si le texte saisi semble former une instruction SQL complète, ou si une saisie supplémentaire est nécessaire avant d’appeler
execute()
.See
runsource()
in Lib/sqlite3/__main__.py for real-world use.
- sqlite3.enable_callback_tracebacks(flag, /)¶
Activer ou désactiver les traces des fonctions de rappel. Par défaut, vous n’obtiendrez pas de traces de pile d’appels dans les fonctions définies par l’utilisateur, les agrégats, les convertisseurs, les fonctions de rappel des mécanismes d’autorisation, etc. Si vous voulez les déboguer, vous pouvez appeler cette fonction avec flag à
True
. Ensuite, vous obtiendrez les traces des fonctions de rappel sursys.stderr
. UtilisezFalse
pour désactiver à nouveau cette fonctionnalité.Note
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, /)¶
Enregistre un adaptateur callable pour adapter le type Python type en un type SQLite. L'adaptateur est appelé avec un objet Python de type type comme seul argument, et doit retourner une valeur d'un type que SQLite comprend nativement.
- sqlite3.register_converter(typename, converter, /)¶
Enregistrer le convertisseur callable pour convertir les objets SQLite de type typename en un objet Python d'un type spécifique. Le convertisseur est invoqué pour toutes les valeurs SQLite de type typename ; on lui passe un objet
bytes
et il doit retourner un objet du type Python désiré. Consultez le paramètre detect_types deconnect()
pour plus d'informations sur le fonctionnement de la détection de type.Remarque : typename et le nom du type dans votre requête sont comparés sans tenir compte de la casse.
Fonctions et constantes du module¶
- 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.
- 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"
.Note
The
named
DB-API parameter style is also supported.
- 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:Single-thread: In this mode, all mutexes are disabled and SQLite is unsafe to use in more than a single thread at once.
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.
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
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
Modifié dans la 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.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 tosqlite3
. Today, it carries no meaning or practical value.
- sqlite3.version_info¶
Version number of this module as a
tuple
ofintegers
. This is not the version 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 tosqlite3
. 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()
andgetconfig()
methods.The availability of these constants varies depending on the version of SQLite Python was compiled with.
Ajouté dans la version 3.12.
Voir aussi
- 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 usingsqlite3.connect()
. Their main purpose is creatingCursor
objects, and Transaction control.Modifié dans la version 3.13: A
ResourceWarning
is emitted ifclose()
is not called before aConnection
object is deleted.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 ofCursor
or its subclasses.
- blobopen(table, column, row, /, *, readonly=False, name='main')¶
Open a
Blob
handle to an existing BLOB.- Paramètres:
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 toFalse
.name (str) -- The name of the database where the blob is located. Defaults to
"main"
.
- Lève:
OperationalError -- When trying to open a blob in a
WITHOUT ROWID
table.- Type renvoyé:
Note
The blob size cannot be changed using the
Blob
class. Use the SQL functionzeroblob
to create a blob with a fixed size.Ajouté dans la version 3.11.
- commit()¶
Commit any pending transaction to the database. If
autocommit
isTrue
, or there is no open transaction, this method does nothing. Ifautocommit
isFalse
, 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
isTrue
, or there is no open transaction, this method does nothing. Ifautocommit
isFalse
, a new transaction is implicitly opened if a pending transaction was rolled back by this method.
- close()¶
Close the database connection. If
autocommit
isFalse
, any pending transaction is implicitly rolled back. Ifautocommit
isTrue
orLEGACY_TRANSACTION_CONTROL
, no implicit transaction control is executed. Make sure tocommit()
before closing to avoid losing pending changes.
- execute(sql, parameters=(), /)¶
Create a new
Cursor
object and callexecute()
on it with the given sql and parameters. Return the new cursor object.
- executemany(sql, parameters, /)¶
Create a new
Cursor
object and callexecutemany()
on it with the given sql and parameters. Return the new cursor object.
- executescript(sql_script, /)¶
Create a new
Cursor
object and callexecutescript()
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.
- Paramètres:
name (str) -- The 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.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.
Modifié dans la version 3.8: Added the deterministic parameter.
Exemple :
>>> 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()
Modifié dans la version 3.13: Passing name, narg, and func as keyword arguments is deprecated. These parameters will become positional-only in Python 3.15.
- create_aggregate(name, n_arg, aggregate_class)¶
Create or remove a user-defined SQL aggregate function.
- Paramètres:
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) --
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.
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.
Exemple :
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()
Modifié dans la version 3.13: Passing name, n_arg, and aggregate_class as keyword arguments is deprecated. These parameters will become positional-only in Python 3.15.
- create_window_function(name, num_params, aggregate_class, /)¶
Create or remove a user-defined aggregate window function.
- Paramètres:
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()
andvalue()
methods must accept is controlled by num_params.Set to
None
to remove an existing SQL aggregate window function.
- Lève:
NotSupportedError -- If used with a version of SQLite older than 3.25.0, which does not support aggregate window functions.
Ajouté dans la version 3.11.
Exemple :
# 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 aninteger
:1
if the first is ordered higher than the second-1
if the first is ordered lower than the second0
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
.Modifié dans la 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
, orSQLITE_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 orNone
if this access attempt is directly from input SQL code.Please consult the SQLite documentation about the possible values for the first argument and the meaning of the second and third argument depending on the first one. All necessary constants are available in the
sqlite3
module.Passing
None
as authorizer_callback will disable the authorizer.Modifié dans la version 3.11: Added support for disabling the authorizer using
None
.Modifié dans la version 3.13: Passing authorizer_callback as a keyword argument is deprecated. The parameter will become positional-only in Python 3.15.
- 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.Modifié dans la version 3.13: Passing progress_handler as a keyword argument is deprecated. The parameter will become positional-only in Python 3.15.
- 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 theCursor.execute()
methods. Other sources include the transaction management of thesqlite3
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.Ajouté dans la version 3.3.
Modifié dans la version 3.13: Passing trace_callback as a keyword argument is deprecated. The parameter will become positional-only in Python 3.15.
- 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 argumentsconnection
,enabled
.Ajouté dans la version 3.2.
Modifié dans la 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.- Paramètres:
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 argumentsconnection
,path
.Ajouté dans la version 3.2.
Modifié dans la version 3.10: Added the
sqlite3.load_extension
auditing event.Modifié dans la version 3.12: Added the entrypoint parameter.
- iterdump(*, filter=None)¶
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.- Paramètres:
filter (str | None) -- An optional
LIKE
pattern for database objects to dump, e.g.prefix_%
. IfNone
(the default), all database objects will be included.
Exemple :
# 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()
Voir aussi
Modifié dans la version 3.13: Ajout du paramètre filter.
- 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.
- Paramètres:
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 theATTACH 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()
Ajouté dans la version 3.7.
Voir aussi
- getlimit(category, /)¶
Get a connection runtime limit.
- Paramètres:
category (int) -- The SQLite limit category to be queried.
- Type renvoyé:
- Lève:
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
Ajouté dans la 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.
- Paramètres:
category (int) -- The SQLite limit category to be set.
limit (int) -- The value of the new limit. If negative, the current limit is unchanged.
- Type renvoyé:
- Lève:
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
Ajouté dans la version 3.11.
- getconfig(op, /)¶
Query a boolean connection configuration option.
- Paramètres:
op (int) -- A SQLITE_DBCONFIG code.
- Type renvoyé:
Ajouté dans la version 3.12.
- setconfig(op, enable=True, /)¶
Set a boolean connection configuration option.
- Paramètres:
op (int) -- A SQLITE_DBCONFIG code.
enable (bool) --
True
if the configuration option should be enabled (default);False
if it should be disabled.
Ajouté dans la 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.- Paramètres:
name (str) -- The database name to be serialized. Defaults to
"main"
.- Type renvoyé:
Note
This method is only available if the underlying SQLite library has the serialize API.
Ajouté dans la version 3.11.
- deserialize(data, /, *, name='main')¶
Deserialize a
serialized
database into aConnection
. 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.- Paramètres:
- Lève:
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 than2**63 - 1
.
Note
This method is only available if the underlying SQLite library has the deserialize API.
Ajouté dans la 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 thatsqlite3
ensures a transaction is always open. Usecommit()
androllback()
to close transactions.This is the recommended value of
autocommit
.True
: Use SQLite's autocommit mode.commit()
androllback()
have no effect in this mode.LEGACY_TRANSACTION_CONTROL
: Pre-Python 3.12 (non-PEP 249-compliant) transaction control. Seeisolation_level
for more details.This is currently the default value of
autocommit
.
Changing
autocommit
toFalse
will open a new transaction, and changing it toTrue
will commit any pending transaction.See Transaction control via the autocommit attribute for more details.
Note
The
isolation_level
attribute has no effect unlessautocommit
isLEGACY_TRANSACTION_CONTROL
.Ajouté dans la 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.Ajouté dans la version 3.2.
- isolation_level¶
Controls the legacy transaction handling mode of
sqlite3
. If set toNone
, 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 usingisolation_level
.isolation_level
has no effect unlessautocommit
is set toLEGACY_TRANSACTION_CONTROL
(the default).
- row_factory¶
The initial
row_factory
forCursor
objects created from this connection. Assigning to this attribute does not affect therow_factory
of existing cursors belonging to this connection, only new ones. IsNone
by default, meaning each row is returned as atuple
.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 theTEXT
data type. By default, this attribute is set tostr
.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 usingConnection.cursor()
, or by using any of the connection shortcut methods.Cursor objects are iterators, meaning that if you
execute()
aSELECT
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.
- Paramètres:
sql (str) -- A single SQL statement.
parameters (
dict
| sequence) -- Python values to bind to placeholders in sql. Adict
if named placeholders are used. A sequence if unnamed placeholders are used. See How to use placeholders to bind values in SQL queries.
- Lève:
ProgrammingError -- If sql contains more than one SQL statement.
If
autocommit
isLEGACY_TRANSACTION_CONTROL
,isolation_level
is notNone
, sql is anINSERT
,UPDATE
,DELETE
, orREPLACE
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 adict
. 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()
.- Paramètres:
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.
- Lève:
ProgrammingError -- If sql contains more than one SQL statement, or is not a DML statement.
Exemple :
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 ofdict
s. Starting with Python 3.14,ProgrammingError
will be raised instead.
- executescript(sql_script, /)¶
Execute the SQL statements in sql_script. If the
autocommit
isLEGACY_TRANSACTION_CONTROL
and there is a pending transaction, an implicitCOMMIT
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
.Exemple :
# 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
isNone
, return the next row query result set as atuple
. Else, pass it to the row factory and return its result. ReturnNone
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 thearraysize
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. ACursor
object created by callingcon.cursor()
will have aconnection
attribute that refers to con:>>> con = sqlite3.connect(":memory:") >>> cur = con.cursor() >>> cur.connection == con True >>> 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
orREPLACE
statements using theexecute()
method. For other statements, afterexecutemany()
orexecutescript()
, or if the insertion failed, the value oflastrowid
is left unchanged. The initial value oflastrowid
isNone
.Note
Inserts into
WITHOUT ROWID
tables are not recorded.Modifié dans la version 3.6: Added support for the
REPLACE
statement.
- rowcount¶
Read-only attribute that provides the number of modified rows for
INSERT
,UPDATE
,DELETE
, andREPLACE
statements; is-1
for other statements, including CTE queries. It is only updated by theexecute()
andexecutemany()
methods, after the statement has run to completion. This means that any resulting rows must be fetched in order forrowcount
to be updated.
- row_factory¶
Control how a row fetched from this
Cursor
is represented. IfNone
, a row is represented as atuple
. Can be set to the includedsqlite3.Row
; or a callable that accepts two arguments, aCursor
object and thetuple
of row values, and returns a custom object representing an SQLite row.Defaults to what
Connection.row_factory
was set to when theCursor
was created. Assigning to this attribute does not affectConnection.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 optimizedrow_factory
forConnection
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 asstrings
. Immediately after a query, it is the first member of each tuple inCursor.description
.
Modifié dans la version 3.5: Added support of slicing.
Blob objects¶
- class sqlite3.Blob¶
Ajouté dans la version 3.11.
A
Blob
instance is a file-like object that can read and write data in an SQLite BLOB. Calllen(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 areos.SEEK_CUR
(seek relative to the current position) andos.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 usingsqlite3
, for example if a user-defined function truncates data while inserting.Warning
is a subclass ofException
.
- 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 ofException
.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
Ajouté dans la version 3.11.
- sqlite_errorname¶
The symbolic name of the numeric error code from the SQLite API
Ajouté dans la 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 ofError
.
- 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 ofError
.
- 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 ofDatabaseError
.
- 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 ofDatabaseError
.
- 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 ofDatabaseError
.
- 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 closedConnection
.ProgrammingError
is a subclass ofDatabaseError
.
- 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
increate_function()
, if the underlying SQLite library does not support deterministic functions.NotSupportedError
is a subclass ofDatabaseError
.
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:
Type Python |
SQLite type |
---|---|
|
|
|
|
|
|
|
|
|
This is how SQLite types are converted to Python types by default:
SQLite type |
Type Python |
---|---|
|
|
|
|
|
|
|
depends on |
|
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 tostrings
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()
.
Obsolète depuis la 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.
Ajouté dans la 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
>>> con.close()
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 Guide Unicode:
con.text_factory = lambda data: str(data, errors="surrogateescape")
Note
The sqlite3
module API does not support strings
containing surrogates.
Voir aussi
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, soconnect()
,Connection.commit()
, andConnection.rollback()
will implicitly open a new transaction (immediately after closing the pending one, for the latter two).sqlite3
usesBEGIN 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
.
Modifié dans la version 3.6: sqlite3
used to implicitly commit an open transaction before DDL
statements. This is no longer the case.
Modifié dans la version 3.12: The recommended way of controlling transactions is now via the
autocommit
attribute.