sqlite3
— DB-API 2.0 interface for SQLite databases¶
Вихідний код: Lib/sqlite3/
SQLite — це бібліотека C, яка надає легку дискову базу даних, яка не потребує окремого серверного процесу та дозволяє отримувати доступ до бази даних за допомогою нестандартного варіанту мови запитів SQL. Деякі програми можуть використовувати SQLite для внутрішнього зберігання даних. Також можна створити прототип програми за допомогою SQLite, а потім перенести код у більшу базу даних, таку як PostgreSQL або Oracle.
The sqlite3
module was written by Gerhard Häring. It provides an SQL interface
compliant with the DB-API 2.0 specification described by PEP 249, and
requires SQLite 3.7.15 or newer.
Цей документ включає в себе 4 головні розділи:
sqlite3-tutorial`вчить як використовувати :mod:!sqlite3` модуль.
Посилання описує класи і функції, які визначає цей модуль
How-to guides деталі як вирішувати певні задачі.
Пояснення надає поглиблений контекст контролю транзакцій.
Дивись також
- https://www.sqlite.org
Веб-сторінка SQLite; документація описує синтаксис і доступні типи даних для підтримуваного діалекту SQL.
- https://www.w3schools.com/sql/
Підручник, довідник і приклади для вивчення синтаксису SQL.
- PEP 249 - Специфікація API бази даних 2.0
PEP, написаний Марком-Андре Лембургом.
Підручник¶
На цьому курсі Ви створите базу данних фільмів Монті Пайтон використовуючи базовий функціонал sqlite3
. Це передбачає фундаментальне розуміння концепту баз данних, включаючи cursors і transactions.
First, we need to create a new database and open
a database connection to allow sqlite3
to work with it.
Call sqlite3.connect()
to create a connection to
the database tutorial.db
in the current working directory,
implicitly creating it if it does not exist:
import sqlite3
con = sqlite3.connect("tutorial.db")
Поверненний Connection
об’єкт con
відображає з’єднання з базою данних на диску.
Щоб виконувати SQL викази і отримувати результати із запитів SQL, нам знадобиться використовувати курсор бази даних. Викличте con.cursor()
, щоб створити Cursor
:
cur = con.cursor()
Now that we’ve got a database connection and a cursor,
we can create a database table movie
with columns for title,
release year, and review score.
For simplicity, we can just use column names in the table declaration –
thanks to the flexible typing feature of SQLite,
specifying the data types is optional.
Execute the CREATE TABLE
statement
by calling cur.execute(...)
:
cur.execute("CREATE TABLE movie(title, year, score)")
We can verify that the new table has been created by querying
the sqlite_master
table built-in to SQLite,
which should now contain an entry for the movie
table definition
(see The Schema Table for details).
Execute that query by calling cur.execute(...)
,
assign the result to res
,
and call res.fetchone()
to fetch the resulting row:
>>> 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
Now, add two rows of data supplied as SQL literals
by executing an INSERT
statement,
once again by calling 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)
""")
The INSERT
statement implicitly opens a transaction,
which needs to be committed before changes are saved in the database
(see Transaction control for details).
Call con.commit()
on the connection object
to commit the transaction:
con.commit()
We can verify that the data was inserted correctly
by executing a SELECT
query.
Use the now-familiar cur.execute(...)
to
assign the result to res
,
and call res.fetchall()
to return all resulting rows:
>>> res = cur.execute("SELECT score FROM movie")
>>> res.fetchall()
[(8.2,), (7.5,)]
The result is a list
of two tuple
s, one per row,
each containing that row’s score
value.
Now, insert three more rows by calling
cur.executemany(...)
:
data = [
("Monty Python Live at the Hollywood Bowl", 1982, 7.9),
("Monty Python's The Meaning of Life", 1983, 7.5),
("Monty Python's Life of Brian", 1979, 8.0),
]
cur.executemany("INSERT INTO movie VALUES(?, ?, ?)", data)
con.commit() # Remember to commit the transaction after executing INSERT.
Notice that ?
placeholders are used to bind data
to the query.
Always use placeholders instead of string formatting
to bind Python values to SQL statements,
to avoid SQL injection attacks
(see How to use placeholders to bind values in SQL queries for more details).
We can verify that the new rows were inserted
by executing a SELECT
query,
this time iterating over the results of the query:
>>> for row in cur.execute("SELECT year, title FROM movie ORDER BY year"):
... print(row)
(1971, 'And Now for Something Completely Different')
(1975, 'Monty Python and the Holy Grail')
(1979, "Monty Python's Life of Brian")
(1982, 'Monty Python Live at the Hollywood Bowl')
(1983, "Monty Python's The Meaning of Life")
Each row is a two-item tuple
of (year, title)
,
matching the columns selected in the query.
Finally, verify that the database has been written to disk
by calling con.close()
to close the existing connection, opening a new one,
creating a new cursor, then querying the database:
>>> 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
You’ve now created an SQLite database using the sqlite3
module,
inserted data and retrieved values from it in multiple ways.
Дивись також
How-to guides for further reading:
Пояснення for in-depth background on transaction control.
Посилання¶
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)¶
Open a connection to an SQLite database.
- Параметри:
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) ofPARSE_DECLTYPES
andPARSE_COLNAMES
to enable this. Column names takes precedence over declared types if both flags are set. Types cannot be detected for generated fields (for examplemax(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) – The
isolation_level
of the connection, controlling whether and how transactions are implicitly opened. Can be"DEFERRED"
(default),"EXCLUSIVE"
or"IMMEDIATE"
; orNone
to disable opening transactions implicitly. See Transaction control for more.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. IfFalse
, the connection may be accessed in multiple threads; write operations may need to be serialized by the user to avoid data corruption. Seethreadsafety
for more information.factory (Connection) – A custom subclass of
Connection
to create the connection with, if not the defaultConnection
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.
- Тип повернення:
Викликає подію аудиту
sqlite3.connect
з аргументомбаза даних
.Викликає подію аудиту
sqlite3.connect/handle
з аргументомconnection_handle
.Змінено в версії 3.4: Додано параметр uri.
Змінено в версії 3.7: database тепер також може бути path-like object, а не лише рядком.
Змінено в версії 3.10: Додано подію аудиту
sqlite3.connect/handle
.
- 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.Наприклад:
>>> 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()
.
- 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 onsys.stderr
. UseFalse
to disable the feature again.Register an
unraisable hook handler
for an improved debug experience:>>> sqlite3.enable_callback_tracebacks(True) >>> con = sqlite3.connect(":memory:") >>> def evil_trace(stmt): ... 5/0 >>> con.set_trace_callback(evil_trace) >>> def debug(unraisable): ... print(f"{unraisable.exc_value!r} in callback {unraisable.object.__name__}") ... print(f"Error message: {unraisable.err_msg}") >>> import sys >>> sys.unraisablehook = debug >>> cur = con.execute("SELECT 1") ZeroDivisionError('division by zero') in callback evil_trace Error message: None
- 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 ofconnect()
for information regarding how type detection works.Note: typename and the name of the type in your query are matched case-insensitively.
Module constants¶
- 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¶
Рядкова константа, що вказує підтримуваний рівень DB-API. Потрібний для DB-API. Жорстко закодований на
"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"
.Примітка
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
Змінено в версії 3.11: Set threadsafety dynamically instead of hard-coding it to
1
.
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.Підключення до бази даних SQLite має такі атрибути та методи:
- 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.- Параметри:
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"
.
- Викликає:
OperationalError – When trying to open a blob in a
WITHOUT ROWID
table.- Тип повернення:
Примітка
The blob size cannot be changed using the
Blob
class. Use the SQL functionzeroblob
to create a blob with a fixed size.Нове в версії 3.11.
- commit()¶
Commit any pending transaction to the database. If there is no open transaction, this method is a no-op.
- rollback()¶
Roll back to the start of any pending transaction. If there is no open transaction, this method is a no-op.
- close()¶
Close the database connection. Any pending transaction is not committed implicitly; make sure to
commit()
before closing to avoid losing pending changes.
- execute(sql, parameters=(), /)¶
Створіть новий об’єкт
Cursor
і викличтеexecute()
для нього з заданими sql і параметрами. Повернути новий об’єкт курсору.
- executemany(sql, parameters, /)¶
Створіть новий об’єкт
Cursor
і викличтеexecutemany()
для нього з заданими sql і параметрами. Повернути новий об’єкт курсору.
- executescript(sql_script, /)¶
Створіть новий об’єкт
Cursor
і викличтеexecutescript()
для нього за допомогою заданого sql_script. Повернути новий об’єкт курсору.
- create_function(name, narg, func, *, deterministic=False)¶
Create or remove a user-defined SQL function.
- Параметри:
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.
- Викликає:
NotSupportedError – If deterministic is used with SQLite versions older than 3.8.3.
Змінено в версії 3.8: Added the deterministic parameter.
приклад:
>>> 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',)
- create_aggregate(name, n_arg, aggregate_class)¶
Create or remove a user-defined SQL aggregate function.
- Параметри:
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.
приклад:
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.
- Параметри:
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.
- Викликає:
NotSupportedError – If used with a version of SQLite older than 3.25.0, which does not support aggregate window functions.
Нове в версії 3.11.
приклад:
# 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())
- create_collation(name, callable, /)¶
Створіть зіставлення під назвою name за допомогою функції зіставлення callable. callable передається два аргументи
string
, і він має повернутиціле число
:1
, якщо перший впорядкований вище за другий-1
, якщо перший впорядкований нижче другого0
, якщо вони в порядку рівності
У наступному прикладі показано порівняння зворотного сортування:
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
.Змінено в версії 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.Змінено в версії 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 an
OperationalError
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 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.Примітка
Винятки, викликані зворотним викликом трасування, не поширюються. Як допомога при розробці та налагодженні використовуйте
enable_callback_tracebacks()
, щоб увімкнути друк трасування з винятків, викликаних у зворотному виклику трасування.Нове в версії 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.Примітка
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.Викликає подію аудиту
sqlite3.enable_load_extension
з аргументамиconnection
,enabled
.Нове в версії 3.2.
Змінено в версії 3.10: Додано подію аудиту sqlite3.enable_load_extension.
con.enable_load_extension(True) # Load the fulltext search extension con.execute("select load_extension('./fts3.so')") # alternatively you can load the extension using an API call: # con.load_extension("./fts3.so") # disable extension loading again con.enable_load_extension(False) # example from SQLite wiki con.execute("CREATE VIRTUAL TABLE recipe USING fts3(name, ingredients)") con.executescript(""" INSERT INTO recipe (name, ingredients) VALUES('broccoli stew', 'broccoli peppers cheese tomatoes'); INSERT INTO recipe (name, ingredients) VALUES('pumpkin stew', 'pumpkin onions garlic celery'); INSERT INTO recipe (name, ingredients) VALUES('broccoli pie', 'broccoli cheese onions flour'); INSERT INTO recipe (name, ingredients) VALUES('pumpkin pie', 'pumpkin sugar flour butter'); """) for row in con.execute("SELECT rowid, name, ingredients FROM recipe WHERE name MATCH 'pie'"): print(row) con.close()
- load_extension(path, /)¶
Load an SQLite extension from a shared library located at path. Enable extension loading with
enable_load_extension()
before calling this method.Викликає подію аудиту
sqlite3.load_extension
з аргументамиconnection
,path
.Нове в версії 3.2.
Змінено в версії 3.10: Додано подію аудиту
sqlite3.load_extension
.
- 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.приклад:
# 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()
Дивись також
- 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.
- Параметри:
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)
Нове в версії 3.7.
Дивись також
- getlimit(category, /)¶
Get a connection runtime limit.
- Параметри:
category (int) – The SQLite limit category to be queried.
- Тип повернення:
- Викликає:
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
Нове в версії 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.
- Параметри:
category (int) – The SQLite limit category to be set.
limit (int) – The value of the new limit. If negative, the current limit is unchanged.
- Тип повернення:
- Викликає:
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
Нове в версії 3.11.
- 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.- Параметри:
name (str) – The database name to be serialized. Defaults to
"main"
.- Тип повернення:
Примітка
This method is only available if the underlying SQLite library has the serialize API.
Нове в версії 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.- Параметри:
- Викликає:
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
.
Примітка
This method is only available if the underlying SQLite library has the deserialize API.
Нове в версії 3.11.
- 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.Нове в версії 3.2.
- isolation_level¶
This attribute controls the transaction handling performed by
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"
.
- 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¶
Екземпляр
Cursor
має такі атрибути та методи.- execute(sql, parameters=(), /)¶
Execute a single SQL statement, optionally binding Python values using placeholders.
- Параметри:
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.
- Викликає:
ProgrammingError – If sql contains more than one SQL statement.
If
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.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()
.- Параметри:
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.
- Викликає:
ProgrammingError – If sql contains more than one SQL statement, or is not a DML statement.
приклад:
rows = [ ("row1",), ("row2",), ] # cur is an sqlite3.Cursor object cur.executemany("INSERT INTO data VALUES(?)", rows)
Примітка
Any resulting rows are discarded, including DML statements with RETURNING clauses.
- executescript(sql_script, /)¶
Execute the SQL statements in sql_script. If 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
.приклад:
# 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.Зауважте, що з параметром size пов’язані міркування щодо продуктивності. Для оптимальної продуктивності зазвичай найкраще використовувати атрибут arraysize. Якщо використовується параметр size, то найкраще, щоб він зберігав те саме значення від одного виклику
fetchmany()
до наступного.
- 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()¶
Закрийте курсор зараз (а не під час кожного виклику
__del__
).Курсор стане непридатним для використання з цього моменту; виняток
ProgrammingError
буде викликано, якщо будь-яка операція буде виконана з курсором.
- 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¶
Атрибут читання/запису, який контролює кількість рядків, які повертає
fetchmany()
. Значення за замовчуванням дорівнює 1, що означає, що за виклик буде отримано один рядок.
- 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
- 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
.Він також встановлений для операторів
SELECT
без будь-яких відповідних рядків.
- 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
.Примітка
Вставки в таблиці
БЕЗ ROWID
не записуються.Змінено в версії 3.6: Додано підтримку оператора REPLACE.
- 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
.
Змінено в версії 3.5: Додана підтримка нарізки.
Blob objects¶
- class sqlite3.Blob¶
Нове в версії 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!'"
- 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.
Винятки¶
Ієрархія винятків визначається 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¶
Базовий клас інших винятків у цьому модулі. Використовуйте це, щоб перехопити всі помилки за допомогою одного оператора
except
.Error
є підкласомException
.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
Нове в версії 3.11.
- sqlite_errorname¶
The symbolic name of the numeric error code from the SQLite API
Нове в версії 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¶
Виняток створено для помилок, пов’язаних із базою даних. Це служить базовим винятком для кількох типів помилок бази даних. Він виникає лише неявно через спеціалізовані підкласи.
DatabaseError
є підкласомError
.
- exception sqlite3.DataError¶
Виняток створено для помилок, спричинених проблемами з обробленими даними, як-от числові значення поза межами діапазону та надто довгі рядки.
DataError
є підкласомDatabaseError
.
- exception sqlite3.OperationalError¶
Виняток створено для помилок, які пов’язані з роботою бази даних і не обов’язково знаходяться під контролем програміста. Наприклад, шлях до бази даних не знайдено або транзакцію не вдалося обробити.
OperationalError
є підкласомDatabaseError
.
- exception sqlite3.IntegrityError¶
Виняток виникає, коли порушується реляційна цілісність бази даних, наприклад. не вдається перевірити зовнішній ключ. Це підклас
DatabaseError
.
- exception sqlite3.InternalError¶
Виняток виникає, коли SQLite стикається з внутрішньою помилкою. Якщо це виникає, це може означати, що існує проблема з бібліотекою SQLite під час виконання.
InternalError
є підкласомDatabaseError
.
- 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
.
Типи SQLite і Python¶
SQLite спочатку підтримує такі типи: NULL
, INTEGER
, REAL
, TEXT
, BLOB
.
Таким чином, такі типи Python можна без будь-яких проблем надсилати до SQLite:
Тип Python |
Тип SQLite |
---|---|
|
|
|
|
|
|
|
|
|
Ось як типи SQLite перетворюються на типи Python за замовчуванням:
Тип SQLite |
Тип Python |
---|---|
|
|
|
|
|
|
|
залежить від |
|
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¶
There are default adapters for the date and datetime types in the datetime module. They will be sent as ISO dates/ISO timestamps to SQLite.
The default converters are registered under the name «date» for
datetime.date
and under the name «timestamp» for
datetime.datetime
.
This way, you can use date/timestamps from Python without any additional fiddling in most cases. The format of the adapters is also compatible with the experimental SQLite date/time functions.
The following example demonstrates this.
import sqlite3
import datetime
con = sqlite3.connect(":memory:", detect_types=sqlite3.PARSE_DECLTYPES|sqlite3.PARSE_COLNAMES)
cur = con.cursor()
cur.execute("create table test(d date, ts timestamp)")
today = datetime.date.today()
now = datetime.datetime.now()
cur.execute("insert into test(d, ts) values (?, ?)", (today, now))
cur.execute("select d, ts from test")
row = cur.fetchone()
print(today, "=>", row[0], type(row[0]))
print(now, "=>", row[1], type(row[1]))
cur.execute('select current_date as "d [date]", current_timestamp as "ts [timestamp]"')
row = cur.fetchone()
print("current_date", row[0], type(row[0]))
print("current_timestamp", row[1], type(row[1]))
con.close()
If a timestamp stored in SQLite has a fractional part longer than 6 numbers, its value will be truncated to microsecond precision by the timestamp converter.
Примітка
Конвертер «міток часу» за замовчуванням ігнорує зміщення UTC у базі даних і завжди повертає простий об’єкт datetime.datetime
. Щоб зберегти зміщення UTC у мітках часу, залиште конвертери вимкненими або зареєструйте конвертер із зсувом за допомогою register_converter()
.
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 should 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())
Примітка
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])
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])
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.
Примітка
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])
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 there is no open transaction upon leaving the body of the with
statement,
the context manager is a no-op.
Примітка
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,)
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
Примітка
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}
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
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 Юнікод HOWTO:
con.text_factory = lambda data: str(data, errors="surrogateescape")
Примітка
The sqlite3
module API does not support strings
containing surrogates.
Дивись також
Пояснення¶
Transaction control¶
The sqlite3
module does not adhere to the transaction handling recommended
by PEP 249.
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
.
Змінено в версії 3.6: sqlite3
used to implicitly commit an open transaction before DDL
statements. This is no longer the case.