sqlite3
--- SQLite 資料庫的 DB-API 2.0 介面¶原始碼:Lib/sqlite3/
SQLite is a C library that provides a lightweight disk-based database that doesn't require a separate server process and allows accessing the database using a nonstandard variant of the SQL query language. Some applications can use SQLite for internal data storage. It's also possible to prototype an application using SQLite and then port the code to a larger database such as PostgreSQL or Oracle.
The sqlite3
module was written by Gerhard Häring. It provides an SQL interface
compliant with the DB-API 2.0 specification described by PEP 249, and
requires SQLite 3.15.2 or newer.
此文件包含四個主要章節:
教學 教導如何使用 sqlite3
模組。
Reference 描述此模組定義的類別與函式。
How-to guides 詳細說明如何處理特定工作。
解釋 深入提供交易 (transaction) 控制的背景。
也參考
The SQLite web page; the documentation describes the syntax and the available data types for the supported SQL dialect.
Tutorial, reference and examples for learning SQL syntax.
PEP 由 Marc-André Lemburg 撰寫。
In this tutorial, you will create a database of Monty Python movies
using basic sqlite3
functionality.
It assumes a fundamental understanding of database concepts,
including cursors and transactions.
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")
The returned Connection
object con
represents the connection to the on-disk database.
In order to execute SQL statements and fetch results from SQL queries,
we will need to use a database cursor.
Call con.cursor()
to create the Cursor
:
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
>>> new_con.close()
You've now created an SQLite database using the sqlite3
module,
inserted data and retrieved values from it in multiple ways.
也參考
進一步參考 How-to guides:
解釋 for in-depth background on transaction control.
Open a connection to an SQLite database.
database (path-like object) -- The path to the database file to be opened.
You can pass ":memory:"
to create an SQLite database existing only
in memory, and open a connection
to it.
timeout (float) -- How many seconds the connection should wait before raising
an OperationalError
when a table is locked.
If another connection opens a transaction to modify a table,
that table will be locked until the transaction is committed.
Default five seconds.
detect_types (int) -- Control whether and how data types not
natively supported by SQLite
are looked up to be converted to Python types,
using the converters registered with register_converter()
.
Set it to any combination (using |
, bitwise or) of
PARSE_DECLTYPES
and PARSE_COLNAMES
to enable this.
Column names takes precedence over declared types if both flags are set.
By default (0
), type detection is disabled.
isolation_level (str | None) -- Control legacy transaction handling behaviour.
See Connection.isolation_level
and
Transaction control via the isolation_level attribute for more information.
Can be "DEFERRED"
(default), "EXCLUSIVE"
or "IMMEDIATE"
;
or None
to disable opening transactions implicitly.
Has no effect unless Connection.autocommit
is set to
LEGACY_TRANSACTION_CONTROL
(the default).
check_same_thread (bool) -- If True
(default), ProgrammingError
will be raised
if the database connection is used by a thread
other than the one that created it.
If False
, the connection may be accessed in multiple threads;
write operations may need to be serialized by the user
to avoid data corruption.
See threadsafety
for more information.
factory (Connection) -- A custom subclass of Connection
to create the connection with,
if not the default Connection
class.
cached_statements (int) -- The number of statements that sqlite3
should internally cache for this connection, to avoid parsing overhead.
By default, 128 statements.
uri (bool) -- If set to True
, database is interpreted as a
URI with a file path
and an optional query string.
The scheme part must be "file:"
,
and the path can be relative or absolute.
The query string allows passing parameters to SQLite,
enabling various How to work with SQLite URIs.
autocommit (bool) -- Control PEP 249 transaction handling behaviour.
See Connection.autocommit
and
Transaction control via the autocommit attribute for more information.
autocommit currently defaults to
LEGACY_TRANSACTION_CONTROL
.
The default will change to False
in a future Python release.
引發一個附帶引數 database
的稽核事件 sqlite3.connect
。
引發一個附帶引數 connection_handle
的稽核事件 sqlite3.connect/handle
。
在 3.4 版的變更: 新增 uri 參數。
在 3.7 版的變更: database can now also be a path-like object, not only a string.
在 3.10 版的變更: 新增 sqlite3.connect/handle
稽核事件。
在 3.12 版的變更: 新增 autocommit 參數。
在 3.13 版的變更: 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.
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.
範例:
>>> sqlite3.complete_statement("SELECT foo FROM bar;")
True
>>> sqlite3.complete_statement("SELECT foo")
False
This function may be useful during command-line input
to determine if the entered text seems to form a complete SQL statement,
or if additional input is needed before calling execute()
.
See runsource()
in Lib/sqlite3/__main__.py
for real-world use.
Enable or disable callback tracebacks.
By default you will not get any tracebacks in user-defined functions,
aggregates, converters, authorizer callbacks etc. If you want to debug them,
you can call this function with flag set to True
. Afterwards, you
will get tracebacks from callbacks on sys.stderr
. Use False
to disable the feature again.
備註
Errors in user-defined function callbacks are logged as unraisable exceptions.
Use an unraisable hook handler
for
introspection of the failed callback.
Register an adapter callable to adapt the Python type type into an SQLite type. The adapter is called with a Python object of type type as its sole argument, and must return a value of a type that SQLite natively understands.
Register the converter callable to convert SQLite objects of type
typename into a Python object of a specific type.
The converter is invoked for all SQLite values of type typename;
it is passed a bytes
object and should return an object of the
desired Python type.
Consult the parameter detect_types of
connect()
for information regarding how type detection works.
Note: typename and the name of the type in your query are matched case-insensitively.
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.
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.
備註
Generated fields (for example MAX(p)
) are returned as str
.
Use PARSE_COLNAMES
to enforce types for such queries.
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 query column name must be wrapped in double quotes ("
)
and the type name must be wrapped in square brackets ([]
).
SELECT MAX(p) as "p [point]" FROM test; ! will look up converter "point"
This flag may be combined with PARSE_DECLTYPES
using the |
(bitwise or) operator.
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
)
String constant stating the supported DB-API level. Required by the DB-API.
Hard-coded to "2.0"
.
String constant stating the type of parameter marker formatting expected by
the sqlite3
module. Required by the DB-API. Hard-coded to
"qmark"
.
備註
The named
DB-API parameter style is also supported.
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 執行緒模式 |
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 |
在 3.11 版的變更: Set threadsafety dynamically instead of hard-coding it to 1
.
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 to
sqlite3
. Today, it carries no meaning or practical value.
Version number of this module as a tuple
of integers
.
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 to
sqlite3
. Today, it carries no meaning or practical value.
These constants are used for the Connection.setconfig()
and getconfig()
methods.
The availability of these constants varies depending on the version of SQLite Python was compiled with.
在 3.12 版被加入.
也參考
SQLite docs: Database Connection Configuration Options
Each open SQLite database is represented by a Connection
object,
which is created using sqlite3.connect()
.
Their main purpose is creating Cursor
objects,
and Transaction control.
在 3.13 版的變更: A ResourceWarning
is emitted if close()
is not called before
a Connection
object is deleted.
An SQLite database connection has the following attributes and methods:
Create and return a Cursor
object.
The cursor method accepts a single optional parameter factory. If
supplied, this must be a callable returning
an instance of Cursor
or its subclasses.
Open a Blob
handle to an existing
BLOB.
table (str) -- The name of the table where the blob is located.
column (str) -- The name of the column where the blob is located.
row (str) -- The name of the row where the blob is located.
readonly (bool) -- Set to True
if the blob should be opened without write
permissions.
Defaults to False
.
name (str) -- The name of the database where the blob is located.
Defaults to "main"
.
OperationalError -- When trying to open a blob in a WITHOUT ROWID
table.
備註
The blob size cannot be changed using the Blob
class.
Use the SQL function zeroblob
to create a blob with a fixed size.
在 3.11 版被加入.
Commit any pending transaction to the database.
If autocommit
is True
, or there is no open transaction,
this method does nothing.
If autocommit
is False
, a new transaction is implicitly
opened if a pending transaction was committed by this method.
Roll back to the start of any pending transaction.
If autocommit
is True
, or there is no open transaction,
this method does nothing.
If autocommit
is False
, a new transaction is implicitly
opened if a pending transaction was rolled back by this method.
Close the database connection.
If autocommit
is False
,
any pending transaction is implicitly rolled back.
If autocommit
is True
or LEGACY_TRANSACTION_CONTROL
,
no implicit transaction control is executed.
Make sure to commit()
before closing
to avoid losing pending changes.
Create a new Cursor
object and call
execute()
on it with the given sql and parameters.
Return the new cursor object.
Create a new Cursor
object and call
executemany()
on it with the given sql and parameters.
Return the new cursor object.
Create a new Cursor
object and call
executescript()
on it with the given sql_script.
Return the new cursor object.
Create or remove a user-defined SQL function.
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.
在 3.8 版的變更: 新增 deterministic 參數。
範例:
>>> 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()
在 3.13 版的變更: Passing name, narg, and func as keyword arguments is deprecated. These parameters will become positional-only in Python 3.15.
Create or remove a user-defined SQL aggregate function.
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.
範例:
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()
在 3.13 版的變更: Passing name, n_arg, and aggregate_class as keyword arguments is deprecated. These parameters will become positional-only in Python 3.15.
Create or remove a user-defined aggregate window function.
name (str) -- The name of the SQL aggregate window function to create or remove.
num_params (int) -- The number of arguments the SQL aggregate window function can accept.
If -1
, it may take any number of arguments.
aggregate_class (class | None) --
A class that must implement the following methods:
step()
: Add a row to the current window.
value()
: Return the current value of the aggregate.
inverse()
: Remove a row from the current window.
finalize()
: Return the final result of the aggregate as
a type natively supported by SQLite.
The number of arguments that the step()
and value()
methods
must accept is controlled by num_params.
Set to None
to remove an existing SQL aggregate window function.
NotSupportedError -- If used with a version of SQLite older than 3.25.0, which does not support aggregate window functions.
在 3.11 版被加入.
範例:
# 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 a collation named name using the collating function callable.
callable is passed two string
arguments,
and it should return an integer
:
1
if the first is ordered higher than the second
-1
if the first is ordered lower than the second
0
if they are ordered equal
The following example shows a reverse sorting collation:
def collate_reverse(string1, string2):
if string1 == string2:
return 0
elif string1 < string2:
return 1
else:
return -1
con = sqlite3.connect(":memory:")
con.create_collation("reverse", collate_reverse)
cur = con.execute("CREATE TABLE test(x)")
cur.executemany("INSERT INTO test(x) VALUES(?)", [("a",), ("b",)])
cur.execute("SELECT x FROM test ORDER BY x COLLATE reverse")
for row in cur:
print(row)
con.close()
Remove a collation function by setting callable to None
.
在 3.11 版的變更: The collation name can contain any Unicode character. Earlier, only ASCII characters were allowed.
Call this method from a different thread to abort any queries that might
be executing on the connection.
Aborted queries will raise an OperationalError
.
Register callable authorizer_callback to be invoked
for each attempt to access a column of a table in the database.
The callback should return one of SQLITE_OK
,
SQLITE_DENY
, or SQLITE_IGNORE
to signal how access to the column should be handled
by the underlying SQLite library.
The first argument to the callback signifies what kind of operation is to be
authorized. The second and third argument will be arguments or None
depending on the first argument. The 4th argument is the name of the database
("main", "temp", etc.) if applicable. The 5th argument is the name of the
inner-most trigger or view that is responsible for the access attempt or
None
if this access attempt is directly from input SQL code.
Please consult the SQLite documentation about the possible values for the first
argument and the meaning of the second and third argument depending on the first
one. All necessary constants are available in the sqlite3
module.
Passing None
as authorizer_callback will disable the authorizer.
在 3.11 版的變更: Added support for disabling the authorizer using None
.
在 3.13 版的變更: Passing authorizer_callback as a keyword argument is deprecated. The parameter will become positional-only in Python 3.15.
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.
在 3.13 版的變更: Passing progress_handler as a keyword argument is deprecated. The parameter will become positional-only in Python 3.15.
Register callable trace_callback to be invoked for each SQL statement that is actually executed by the SQLite backend.
The only argument passed to the callback is the statement (as
str
) that is being executed. The return value of the callback is
ignored. Note that the backend does not only run statements passed to the
Cursor.execute()
methods. Other sources include the
transaction management of the
sqlite3
module and the execution of triggers defined in the current
database.
Passing None
as trace_callback will disable the trace callback.
備註
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.
在 3.3 版被加入.
在 3.13 版的變更: Passing trace_callback as a keyword argument is deprecated. The parameter will become positional-only in Python 3.15.
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.
備註
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.
引發一個附帶引數 connection
、enabled
的稽核事件 sqlite3.enable_load_extension
。
在 3.2 版被加入.
在 3.10 版的變更: 加入 sqlite3.enable_load_extension
稽核事件。
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 an SQLite extension from a shared library.
Enable extension loading with enable_load_extension()
before
calling this method.
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.
引發一個附帶引數 connection
、path
的稽核事件 sqlite3.load_extension
。
在 3.2 版被加入.
在 3.10 版的變更: 加入 sqlite3.load_extension
稽核事件。
在 3.12 版的變更: 新增 entrypoint 參數。
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.
filter (str | None) -- An optional LIKE
pattern for database objects to dump, e.g. prefix_%
.
If None
(the default), all database objects will be included.
範例:
# 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()
在 3.13 版的變更: 新增 filter 參數。
Create a backup of an SQLite database.
Works even if the database is being accessed by other clients or concurrently by the same connection.
target (Connection) -- The database connection to save the backup to.
pages (int) -- The number of pages to copy at a time.
If equal to or less than 0
,
the entire database is copied in a single step.
Defaults to -1
.
progress (callback | None) -- If set to a callable,
it is invoked with three integer arguments for every backup iteration:
the status of the last iteration,
the remaining number of pages still to be copied,
and the total number of pages.
Defaults to None
.
name (str) -- The name of the database to back up.
Either "main"
(the default) for the main database,
"temp"
for the temporary database,
or the name of a custom database as attached using the
ATTACH DATABASE
SQL statement.
sleep (float) -- The number of seconds to sleep between successive attempts to back up remaining pages.
Example 1, copy an existing database into another:
def progress(status, remaining, total):
print(f'Copied {total-remaining} of {total} pages...')
src = sqlite3.connect('example.db')
dst = sqlite3.connect('backup.db')
with dst:
src.backup(dst, pages=1, progress=progress)
dst.close()
src.close()
Example 2, copy an existing database into a transient copy:
src = sqlite3.connect('example.db')
dst = sqlite3.connect(':memory:')
src.backup(dst)
dst.close()
src.close()
在 3.7 版被加入.
Get a connection runtime limit.
category (int) -- The SQLite limit category to be queried.
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
在 3.11 版被加入.
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.
category (int) -- The SQLite limit category to be set.
limit (int) -- The value of the new limit. If negative, the current limit is unchanged.
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
在 3.11 版被加入.
Query a boolean connection configuration option.
op (int) -- A SQLITE_DBCONFIG code.
在 3.12 版被加入.
Set a boolean connection configuration option.
op (int) -- A SQLITE_DBCONFIG code.
enable (bool) -- True
if the configuration option should be enabled (default);
False
if it should be disabled.
在 3.12 版被加入.
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.
備註
This method is only available if the underlying SQLite library has the serialize API.
在 3.11 版被加入.
Deserialize a serialized
database into a
Connection
.
This method causes the database connection to disconnect from database
name, and reopen name as an in-memory database based on the
serialization contained in data.
OperationalError -- If the database connection is currently involved in a read transaction or a backup operation.
DatabaseError -- If data does not contain a valid SQLite database.
OverflowError -- If len(data)
is larger than 2**63 - 1
.
備註
This method is only available if the underlying SQLite library has the deserialize API.
在 3.11 版被加入.
This attribute controls PEP 249-compliant transaction behaviour.
autocommit
has three allowed values:
False
: Select PEP 249-compliant transaction behaviour,
implying that sqlite3
ensures a transaction is always open.
Use commit()
and rollback()
to close transactions.
This is the recommended value of autocommit
.
True
: Use SQLite's autocommit mode.
commit()
and rollback()
have no effect in this mode.
LEGACY_TRANSACTION_CONTROL
:
Pre-Python 3.12 (non-PEP 249-compliant) transaction control.
See isolation_level
for more details.
This is currently the default value of autocommit
.
Changing autocommit
to False
will open a new transaction,
and changing it to True
will commit any pending transaction.
更多詳情請見 Transaction control via the autocommit attribute。
備註
The isolation_level
attribute has no effect unless
autocommit
is LEGACY_TRANSACTION_CONTROL
.
在 3.12 版被加入.
This read-only attribute corresponds to the low-level SQLite autocommit mode.
True
if a transaction is active (there are uncommitted changes),
False
otherwise.
在 3.2 版被加入.
Controls the legacy transaction handling mode of sqlite3
.
If set to None
, transactions are never implicitly opened.
If set to one of "DEFERRED"
, "IMMEDIATE"
, or "EXCLUSIVE"
,
corresponding to the underlying SQLite transaction behaviour,
implicit transaction management is performed.
If not overridden by the isolation_level parameter of connect()
,
the default is ""
, which is an alias for "DEFERRED"
.
備註
Using autocommit
to control transaction handling is
recommended over using isolation_level
.
isolation_level
has no effect unless autocommit
is
set to LEGACY_TRANSACTION_CONTROL
(the default).
The initial row_factory
for Cursor
objects created from this connection.
Assigning to this attribute does not affect the row_factory
of existing cursors belonging to this connection, only new ones.
Is None
by default,
meaning each row is returned as a tuple
.
A callable that accepts a bytes
parameter
and returns a text representation of it.
The callable is invoked for SQLite values with the TEXT
data type.
By default, this attribute is set to str
.
Return the total number of database rows that have been modified, inserted, or deleted since the database connection was opened.
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)
A Cursor
instance has the following attributes and methods.
Execute a single SQL statement, optionally binding Python values using placeholders.
sql (str) -- 單一個 SQL 陳述式。
parameters (dict
| sequence) -- Python values to bind to placeholders in sql.
A dict
if named placeholders are used.
A sequence if unnamed placeholders are used.
See How to use placeholders to bind values in SQL queries.
ProgrammingError -- If sql contains more than one SQL statement.
If autocommit
is
LEGACY_TRANSACTION_CONTROL
,
isolation_level
is not None
,
sql is an INSERT
, UPDATE
, DELETE
, or REPLACE
statement,
and there is no open transaction,
a transaction is implicitly opened before executing sql.
Deprecated since version 3.12, will be removed in version 3.14: DeprecationWarning
is emitted if
named placeholders are used
and parameters is a sequence instead of a dict
.
Starting with Python 3.14, ProgrammingError
will
be raised instead.
Use executescript()
to execute multiple SQL statements.
For every item in parameters, repeatedly execute the parameterized DML SQL statement sql.
Uses the same implicit transaction handling as execute()
.
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.
ProgrammingError -- If sql contains more than one SQL statement, or is not a DML statement.
範例:
rows = [
("row1",),
("row2",),
]
# cur 是一個 sqlite3.Cursor 物件
cur.executemany("INSERT INTO data VALUES(?)", rows)
備註
Any resulting rows are discarded, including DML statements with RETURNING clauses.
Deprecated since version 3.12, will be removed in version 3.14: DeprecationWarning
is emitted if
named placeholders are used
and the items in parameters are sequences
instead of dict
s.
Starting with Python 3.14, ProgrammingError
will
be raised instead.
Execute the SQL statements in sql_script.
If the autocommit
is
LEGACY_TRANSACTION_CONTROL
and there is a pending transaction,
an implicit COMMIT
statement is executed first.
No other implicit transaction control is performed;
any transaction control must be added to sql_script.
sql_script must be a string
.
範例:
# cur 是一個 sqlite3.Cursor 物件
cur.executescript("""
BEGIN;
CREATE TABLE person(firstname, lastname, age);
CREATE TABLE book(title, author, published);
CREATE TABLE publisher(name, address);
COMMIT;
""")
If row_factory
is None
,
return the next row query result set as a tuple
.
Else, pass it to the row factory and return its result.
Return None
if no more data is available.
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.
Return all (remaining) rows of a query result as a list
.
Return an empty list if no rows are available.
Note that the arraysize
attribute can affect the performance of
this operation.
Close 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.
Required by the DB-API. Does nothing in sqlite3
.
Required by the DB-API. Does nothing in sqlite3
.
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.
Read-only attribute that provides the SQLite database Connection
belonging to the cursor. A Cursor
object created by
calling con.cursor()
will have a
connection
attribute that refers to con:
>>> con = sqlite3.connect(":memory:")
>>> cur = con.cursor()
>>> cur.connection == con
True
>>> con.close()
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.
Read-only attribute that provides the row id of the last inserted row. It
is only updated after successful INSERT
or REPLACE
statements
using the execute()
method. For other statements, after
executemany()
or executescript()
, or if the insertion failed,
the value of lastrowid
is left unchanged. The initial value of
lastrowid
is None
.
備註
Inserts into WITHOUT ROWID
tables are not recorded.
在 3.6 版的變更: 新增 REPLACE
陳述式的支援。
Read-only attribute that provides the number of modified rows for
INSERT
, UPDATE
, DELETE
, and REPLACE
statements;
is -1
for other statements,
including CTE queries.
It is only updated by the execute()
and executemany()
methods,
after the statement has run to completion.
This means that any resulting rows must be fetched in order for
rowcount
to be updated.
Control how a row fetched from this Cursor
is represented.
If None
, a row is represented as a tuple
.
Can be set to the included sqlite3.Row
;
or a callable that accepts two arguments,
a Cursor
object and the tuple
of row values,
and returns a custom object representing an SQLite row.
Defaults to what Connection.row_factory
was set to
when the Cursor
was created.
Assigning to this attribute does not affect
Connection.row_factory
of the parent connection.
A Row
instance serves as a highly optimized
row_factory
for Connection
objects.
It supports iteration, equality testing, len()
,
and mapping access by column name and index.
Two Row
objects compare equal
if they have identical column names and values.
更多詳情請見 How to create and use row factories。
Return a list
of column names as strings
.
Immediately after a query,
it is the first member of each tuple in Cursor.description
.
在 3.5 版的變更: 新增對切片的支援。
在 3.11 版被加入.
A Blob
instance is a file-like object
that can read and write data in an SQLite BLOB.
Call len(blob)
to get the size (number of bytes) of the blob.
Use indices and slices for direct access to the blob data.
Use the Blob
as a context manager to ensure that the blob
handle is closed after use.
con = sqlite3.connect(":memory:")
con.execute("CREATE TABLE test(blob_col blob)")
con.execute("INSERT INTO test(blob_col) VALUES(zeroblob(13))")
# Write to our blob, using two write operations:
with con.blobopen("test", "blob_col", 1) as blob:
blob.write(b"hello, ")
blob.write(b"world.")
# Modify the first and last bytes of our blob
blob[0] = ord("H")
blob[-1] = ord("!")
# Read the contents of our blob
with con.blobopen("test", "blob_col", 1) as blob:
greeting = blob.read()
print(greeting) # outputs "b'Hello, world!'"
con.close()
Close 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 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 to the blob at the current offset. This function cannot
change the blob length. Writing beyond the end of the blob will raise
ValueError
.
Return the current access position of the blob.
Set the current access position of the blob to offset. The origin
argument defaults to os.SEEK_SET
(absolute blob positioning).
Other values for origin are os.SEEK_CUR
(seek relative to the
current position) and os.SEEK_END
(seek relative to the blob’s
end).
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.
The exception hierarchy is defined by the DB-API 2.0 (PEP 249).
This exception is not currently raised by the sqlite3
module,
but may be raised by applications using sqlite3
,
for example if a user-defined function truncates data while inserting.
Warning
is a subclass of Exception
.
The base class of the other exceptions in this module.
Use this to catch all errors with one single except
statement.
Error
is a subclass of Exception
.
If the exception originated from within the SQLite library, the following two attributes are added to the exception:
The numeric error code from the SQLite API
在 3.11 版被加入.
The symbolic name of the numeric error code from the SQLite API
在 3.11 版被加入.
Exception raised for misuse of the low-level SQLite C API.
In other words, if this exception is raised, it probably indicates a bug in the
sqlite3
module.
InterfaceError
is a subclass of Error
.
Exception raised for errors that are related to the database.
This serves as the base exception for several types of database errors.
It is only raised implicitly through the specialised subclasses.
DatabaseError
is a subclass of Error
.
Exception raised for errors caused by problems with the processed data,
like numeric values out of range, and strings which are too long.
DataError
is a subclass of DatabaseError
.
Exception raised for errors that are related to the database's operation,
and not necessarily under the control of the programmer.
For example, the database path is not found,
or a transaction could not be processed.
OperationalError
is a subclass of DatabaseError
.
Exception raised when the relational integrity of the database is affected,
e.g. a foreign key check fails. It is a subclass of DatabaseError
.
Exception raised when SQLite encounters an internal error.
If this is raised, it may indicate that there is a problem with the runtime
SQLite library.
InternalError
is a subclass of DatabaseError
.
Exception raised for sqlite3
API programming errors,
for example supplying the wrong number of bindings to a query,
or trying to operate on a closed Connection
.
ProgrammingError
is a subclass of DatabaseError
.
Exception raised in case a method or database API is not supported by the
underlying SQLite library. For example, setting deterministic to
True
in create_function()
, if the underlying SQLite library
does not support deterministic functions.
NotSupportedError
is a subclass of DatabaseError
.
SQLite natively supports the following types: NULL
, INTEGER
,
REAL
, TEXT
, BLOB
.
The following Python types can thus be sent to SQLite without any problem:
Python type |
SQLite type |
---|---|
|
|
|
|
|
|
|
|
|
This is how SQLite types are converted to Python types by default:
SQLite type |
Python type |
---|---|
|
|
|
|
|
|
|
depends on |
|
The type system of the sqlite3
module is extensible in two ways: you can
store additional Python types in an SQLite database via
object adapters,
and you can let the sqlite3
module convert SQLite types to
Python types via converters.
備註
The default adapters and converters are deprecated as of Python 3.12. Instead, use the Adapter and converter recipes and tailor them to your needs.
The deprecated default adapters and converters consist of:
An adapter for datetime.date
objects to strings
in
ISO 8601 format.
An adapter for datetime.datetime
objects to strings in
ISO 8601 format.
A converter for declared "date" types to
datetime.date
objects.
A converter for declared "timestamp" types to
datetime.datetime
objects.
Fractional parts will be truncated to 6 digits (microsecond precision).
備註
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()
.
在 3.12 版之後被棄用.
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.
Print CLI help.
Print underlying SQLite library version.
在 3.12 版被加入.
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()
備註
PEP 249 numeric placeholders are not supported. If used, they will be interpreted as named placeholders.
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.
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()
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()
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.
備註
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()
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)
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()
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.
備註
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()
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.
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()
備註
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
.
By default, sqlite3
uses str
to adapt SQLite values
with the TEXT
data type.
This works well for UTF-8 encoded text, but it might fail for other encodings
and invalid UTF-8.
You can use a custom text_factory
to handle such cases.
Because of SQLite's flexible typing, it is not uncommon to encounter table
columns with the TEXT
data type containing non-UTF-8 encodings,
or even arbitrary data.
To demonstrate, let's assume we have a database with ISO-8859-2 (Latin-2)
encoded text, for example a table of Czech-English dictionary entries.
Assuming we now have a Connection
instance con
connected to this database,
we can decode the Latin-2 encoded text using this text_factory
:
con.text_factory = lambda data: str(data, encoding="latin2")
For invalid UTF-8 or arbitrary data in stored in TEXT
table columns,
you can use the following technique, borrowed from the Unicode HOWTO:
con.text_factory = lambda data: str(data, errors="surrogateescape")
備註
The sqlite3
module API does not support strings
containing surrogates.
也參考
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.
autocommit
attribute¶The recommended way of controlling transaction behaviour is through
the Connection.autocommit
attribute,
which should preferably be set using the autocommit parameter
of connect()
.
It is suggested to set autocommit to False
,
which implies PEP 249-compliant transaction control.
This means:
sqlite3
ensures that a transaction is always open,
so connect()
, Connection.commit()
, and Connection.rollback()
will implicitly open a new transaction
(immediately after closing the pending one, for the latter two).
sqlite3
uses BEGIN DEFERRED
statements when opening transactions.
Transactions should be committed explicitly using commit()
.
Transactions should be rolled back explicitly using rollback()
.
An implicit rollback is performed if the database is
close()
-ed with pending changes.
Set autocommit to True
to enable SQLite's autocommit mode.
In this mode, Connection.commit()
and Connection.rollback()
have no effect.
Note that SQLite's autocommit mode is distinct from
the PEP 249-compliant Connection.autocommit
attribute;
use Connection.in_transaction
to query
the low-level SQLite autocommit mode.
Set autocommit to LEGACY_TRANSACTION_CONTROL
to leave transaction control behaviour to the
Connection.isolation_level
attribute.
See Transaction control via the isolation_level attribute for more information.
isolation_level
attribute¶備註
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
.
在 3.6 版的變更: sqlite3
used to implicitly commit an open transaction before DDL
statements. This is no longer the case.
在 3.12 版的變更: The recommended way of controlling transactions is now via the
autocommit
attribute.