# `sqlite3` — DB-API 2.0 interface for SQLite databases

Source code: 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 3.7.15 or newer.

To use the module, start by creating a `Connection` object that represents the database. Here the data will be stored in the `example.db` file:

    import sqlite3
    con = sqlite3.connect('example.db')

The special path name `:memory:` can be provided to create a temporary database in RAM.

Once a `Connection` has been established, create a `Cursor` object and call its `execute()` method to perform SQL commands:

    cur = con.cursor()

    # Create table
    cur.execute('''CREATE TABLE stocks
                   (date text, trans text, symbol text, qty real, price real)''')

    # Insert a row of data
    cur.execute("INSERT INTO stocks VALUES ('2006-01-05','BUY','RHAT',100,35.14)")

    # Save (commit) the changes
    con.commit()

    # We can also close the connection if we are done with it.
    # Just be sure any changes have been committed or they will be lost.
    con.close()

The saved data is persistent: it can be reloaded in a subsequent session even after restarting the Python interpreter:

    import sqlite3
    con = sqlite3.connect('example.db')
    cur = con.cursor()

To retrieve data after executing a SELECT statement, either treat the cursor as an iterator, call the cursor’s `fetchone()` method to retrieve a single matching row, or call `fetchall()` to get a list of the matching rows.

This example uses the iterator form:

    >>> for row in cur.execute('SELECT * FROM stocks ORDER BY price'):
            print(row)

    ('2006-01-05', 'BUY', 'RHAT', 100, 35.14)
    ('2006-03-28', 'BUY', 'IBM', 1000, 45.0)
    ('2006-04-06', 'SELL', 'IBM', 500, 53.0)
    ('2006-04-05', 'BUY', 'MSFT', 1000, 72.0)

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 (see the xkcd webcomic for a humorous example of what can go wrong):

    # Never do this -- insecure!
    symbol = 'RHAT'
    cur.execute("SELECT * FROM stocks WHERE symbol = '%s'" % symbol)

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. For the named style, it can be either a sequence or `dict` instance. The length of the sequence must match the number of placeholders, or a `ProgrammingError` is raised. If a `dict` is given, it must contain keys for all named parameters. Any extra items are ignored. Here’s an example of both styles:

    import sqlite3

    con = sqlite3.connect(":memory:")
    cur = con.cursor()
    cur.execute("create table lang (name, first_appeared)")

    # This is the qmark style:
    cur.execute("insert into lang values (?, ?)", ("C", 1972))

    # The qmark style used with executemany():
    lang_list = [
        ("Fortran", 1957),
        ("Python", 1991),
        ("Go", 2009),
    ]
    cur.executemany("insert into lang values (?, ?)", lang_list)

    # And this is the named style:
    cur.execute("select * from lang where first_appeared=:year", {"year": 1972})
    print(cur.fetchall())

    con.close()

See also

https://www.sqlite.org

  The SQLite web page; the documentation describes the syntax and the available data types for the supported SQL dialect.

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

  Tutorial, reference and examples for learning SQL syntax.

PEP 249 - Database API Specification 2.0

  PEP written by Marc-André Lemburg.

## Module functions and constants

sqlite3.apilevel

  String constant stating the supported DB-API level. Required by the DB-API. Hard-coded to `"2.0"`.

sqlite3.paramstyle

  String constant stating the type of parameter marker formatting expected by the `sqlite3` module. Required by the DB-API. Hard-coded to `"qmark"`.

  Note

  The `sqlite3` module supports both `qmark` and `numeric` DB-API parameter styles, because that is what the underlying SQLite library supports. However, the DB-API does not allow multiple values for the `paramstyle` attribute.

sqlite3.version

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

sqlite3.version_info

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

sqlite3.sqlite_version

  The version number of the run-time SQLite library, as a string.

sqlite3.sqlite_version_info

  The version number of the run-time SQLite library, as a tuple of integers.

sqlite3.threadsafety

  Integer constant required by the DB-API 2.0, stating the level of thread safety the `sqlite3` module supports. This attribute is set based on the default threading mode the underlying SQLite library is compiled with. The SQLite threading modes are:

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

  > 2. Multi-thread: In this mode, SQLite can be safely used by multiple threads provided that no single database connection is used simultaneously in two or more threads.

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

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

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

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

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.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.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.

  Parameters

    - database (path-like object) – The path to the database file to be opened. Pass `":memory:"` to open a connection to a database that is in RAM instead of on disk.

    - timeout (float) – How many seconds the connection should wait before raising an exception, if the database is locked by another connection. If another connection opens a transaction to modify the database, it will be locked until that transaction is committed. Default five seconds.

    - detect_types (int) – Control whether and how data types not natively supported by SQLite are looked up to be converted to Python types, using the converters registered with `register_converter()`. Set it to any combination (using `|`, bitwise or) of `PARSE_DECLTYPES` and `PARSE_COLNAMES` to enable this. Column names takes precedence over declared types if both flags are set. Types cannot be detected for generated fields (for example `max(data)`), even when the detect_types parameter is set; `str` will be returned instead. By default (`0`), type detection is disabled.

    - isolation_level (str | None) – The `isolation_level` of the connection, controlling whether and how transactions are implicitly opened. Can be `"DEFERRED"` (default), `"EXCLUSIVE"` or `"IMMEDIATE"`; or `None` to disable opening transactions implicitly. See Controlling Transactions for more.

    - check_same_thread (bool) – If `True` (default), only the creating thread may use the connection. If `False`, the connection may be shared across multiple threads; if so, write operations should be serialized by the user to avoid data corruption.

    - 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 SQLite URI tricks.

  Return type

    sqlite3.Connection

  Raises an auditing event `sqlite3.connect` with argument `database`.

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

  New in version 3.4: The uri parameter.

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

  New in version 3.10: The `sqlite3.connect/handle` auditing event.

sqlite3.register_converter(typename, converter, /)

  Register the converter callable to convert SQLite objects of type typename into a Python object of a specific type. The converter is invoked for all SQLite values of type typename; it is passed a `bytes` object and should return an object of the desired Python type. Consult the parameter detect_types of `connect()` for information regarding how type detection works.

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

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.complete_statement(statement)

  Returns `True` if the string statement contains one or more complete SQL statements terminated by semicolons. It does not verify that the SQL is syntactically correct, only that there are no unclosed string literals and the statement is terminated by a semicolon.

  This can be used to build a shell for SQLite, as in the following example:

      # A minimal SQLite shell for experiments

      import sqlite3

      con = sqlite3.connect(":memory:")
      con.isolation_level = None
      cur = con.cursor()

      buffer = ""

      print("Enter your SQL commands to execute in sqlite3.")
      print("Enter a blank line to exit.")

      while True:
          line = input()
          if line == "":
              break
          buffer += line
          if sqlite3.complete_statement(buffer):
              try:
                  buffer = buffer.strip()
                  cur.execute(buffer)

                  if buffer.lstrip().upper().startswith("SELECT"):
                      print(cur.fetchall())
              except sqlite3.Error as e:
                  err_msg = str(e)
                  err_code = e.sqlite_errorcode
                  err_name = e.sqlite_errorname
                  print(f"{err_name} ({err_code}): {err_msg}")
              buffer = ""

      con.close()

sqlite3.enable_callback_tracebacks(flag, /)

  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.

  Register an `unraisable hook handler` for an improved debug experience:

      >>> import sqlite3
      >>> sqlite3.enable_callback_tracebacks(True)
      >>> cx = sqlite3.connect(":memory:")
      >>> cx.set_trace_callback(lambda stmt: 5/0)
      >>> cx.execute("select 1")
      Exception ignored in: <function <lambda> at 0x10b4e3ee0>
      Traceback (most recent call last):
        File "<stdin>", line 1, in <lambda>
      ZeroDivisionError: division by zero
      >>> import sys
      >>> sys.unraisablehook = lambda unraisable: print(unraisable)
      >>> cx.execute("select 1")
      UnraisableHookArgs(exc_type=<class 'ZeroDivisionError'>, exc_value=ZeroDivisionError('division by zero'), exc_traceback=<traceback object at 0x10b559900>, err_msg=None, object=<function <lambda> at 0x10b4e3ee0>)
      <sqlite3.Cursor object at 0x10b1fe840>

## Connection Objects

class sqlite3.Connection

  An SQLite database connection has the following attributes and methods:

  isolation_level

    This attribute controls the transaction handling performed by `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"`.

  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.

    New in version 3.2.

  cursor(factory=Cursor)

    The cursor method accepts a single optional parameter factory. If supplied, this must be a callable returning an instance of `Cursor` or its subclasses.

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

    Open a `Blob` handle to the BLOB located in table name table, column name column, and row index row of database name. When readonly is `True` the blob is opened without write permissions. Trying to open a blob in a `WITHOUT ROWID` table will raise `OperationalError`.

    Note

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

    New in version 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])

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

  executemany(sql[, parameters])

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

  executescript(sql_script)

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

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

    Creates a user-defined function that you can later use from within SQL statements under the function name name. narg is the number of parameters the function accepts (if narg is -1, the function may take any number of arguments), and func is a Python callable that is called as the SQL function. If deterministic is true, the created function is marked as deterministic, which allows SQLite to perform additional optimizations. This flag is supported by SQLite 3.8.3 or higher, `NotSupportedError` will be raised if used with older versions.

    The function can return any of the types natively supported by SQLite.

    Changed in version 3.8: The deterministic parameter was added.

    Example:

        import sqlite3
        import hashlib

        def md5sum(t):
            return hashlib.md5(t).hexdigest()

        con = sqlite3.connect(":memory:")
        con.create_function("md5", 1, md5sum)
        cur = con.cursor()
        cur.execute("select md5(?)", (b"foo",))
        print(cur.fetchone()[0])

        con.close()

  create_aggregate(name, /, n_arg, aggregate_class)

    Creates a user-defined aggregate function.

    The aggregate class must implement a `step` method, which accepts the number of parameters n_arg (if n_arg is -1, the function may take any number of arguments), and a `finalize` method which will return the final result of the aggregate.

    The `finalize` method can return any of the types natively supported by SQLite.

    Example:

        import sqlite3

        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.cursor()
        cur.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, /)

    Creates user-defined aggregate window function name.

    aggregate_class must implement the following methods:

    - `step`: adds a row to the current window

    - `value`: returns the current value of the aggregate

    - `inverse`: removes a row from the current window

    - `finalize`: returns the final value of the aggregate

    `step` and `value` accept num_params number of parameters, unless num_params is `-1`, in which case they may take any number of arguments. `finalize` and `value` can return any of the types natively supported by SQLite. Call `create_window_function()` with aggregate_class set to `None` to clear window function name.

    Aggregate window functions are supported by SQLite 3.25.0 and higher. `NotSupportedError` will be raised if used with older versions.

    New in version 3.11.

    Example:

        # Example taken from https://www.sqlite.org/windowfunctions.html#udfwinfunc
        import sqlite3

        class WindowSumInt:
            def __init__(self):
                self.count = 0

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

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

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

            def finalize(self):
                """Returns 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)

    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:

        import sqlite3

        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.cursor()
        cur.execute("create table test(x)")
        cur.executemany("insert into test(x) values (?)", [("a",), ("b",)])
        cur.execute("select x from test order by x collate reverse")
        for row in cur:
            print(row)
        con.close()

    Remove a collation function by setting callable to `None`.

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

  interrupt()

    You can call this method from a different thread to abort any queries that might be executing on the connection. The query will then abort and the caller will get an exception.

  set_authorizer(authorizer_callback)

    This routine registers a callback. The callback is invoked for each attempt to access a column of a table in the database. The callback should return `SQLITE_OK` if access is allowed, `SQLITE_DENY` if the entire SQL statement should be aborted with an error and `SQLITE_IGNORE` if the column should be treated as a NULL value. These constants are available in the `sqlite3` module.

    The first argument to the callback signifies what kind of operation is to be authorized. The second and third argument will be arguments or `None` depending on the first argument. The 4th argument is the name of the database (“main”, “temp”, etc.) if applicable. The 5th argument is the name of the inner-most trigger or view that is responsible for the access attempt or `None` if this access attempt is directly from input SQL code.

    Please consult the SQLite documentation about the possible values for the first argument and the meaning of the second and third argument depending on the first one. All necessary constants are available in the `sqlite3` module.

    Passing `None` as authorizer_callback will disable the authorizer.

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

  set_progress_handler(progress_handler, n)

    This routine registers a callback. The callback is 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)

    Registers trace_callback to be called 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.

    Note

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

    New in version 3.3.

  enable_load_extension(enabled, /)

    This routine allows/disallows the SQLite engine to load SQLite extensions from shared libraries. 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.

    Loadable extensions are disabled by default. See 1.

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

    New in version 3.2.

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

        import sqlite3

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

        # enable extension loading
        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, /)

    This routine loads an SQLite extension from a shared library. You have to enable extension loading with `enable_load_extension()` before you can use this routine.

    Loadable extensions are disabled by default. See 1.

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

    New in version 3.2.

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

  row_factory

    You can change this attribute to a callable that accepts the cursor and the original row as a tuple and will return the real result row. This way, you can implement more advanced ways of returning results, such as returning an object that can also access columns by name.

    Example:

        import sqlite3

        def dict_factory(cursor, row):
            d = {}
            for idx, col in enumerate(cursor.description):
                d[col[0]] = row[idx]
            return d

        con = sqlite3.connect(":memory:")
        con.row_factory = dict_factory
        cur = con.cursor()
        cur.execute("select 1 as a")
        print(cur.fetchone()["a"])

        con.close()

    If returning a tuple doesn’t suffice and you want name-based access to columns, you should consider setting `row_factory` to the highly optimized `sqlite3.Row` type. `Row` provides both index-based and case-insensitive name-based access to columns with almost no memory overhead. It will probably be better than your own custom dictionary-based approach or even a db_row based solution.

  text_factory

    Using this attribute you can control what objects are returned for the `TEXT` data type. By default, this attribute is set to `str` and the `sqlite3` module will return `str` objects for `TEXT`. If you want to return `bytes` instead, you can set it to `bytes`.

    You can also set it to any other callable that accepts a single bytestring parameter and returns the resulting object.

    See the following example code for illustration:

        import sqlite3

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

        AUSTRIA = "Österreich"

        # by default, rows are returned as str
        cur.execute("select ?", (AUSTRIA,))
        row = cur.fetchone()
        assert row[0] == AUSTRIA

        # but we can make sqlite3 always return bytestrings ...
        con.text_factory = bytes
        cur.execute("select ?", (AUSTRIA,))
        row = cur.fetchone()
        assert type(row[0]) is bytes
        # the bytestrings will be encoded in UTF-8, unless you stored garbage in the
        # database ...
        assert row[0] == AUSTRIA.encode("utf-8")

        # we can also implement a custom text_factory ...
        # here we implement one that appends "foo" to all strings
        con.text_factory = lambda x: x.decode("utf-8") + "foo"
        cur.execute("select ?", ("bar",))
        row = cur.fetchone()
        assert row[0] == "barfoo"

        con.close()

  total_changes

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

  iterdump()

    Returns an iterator to dump the database in an SQL text format. Useful when saving an in-memory database for later restoration. This function provides the same capabilities as the `.dump` command in the sqlite3 shell.

    Example:

        # Convert file existing_db.db to SQL dump file dump.sql
        import sqlite3

        con = sqlite3.connect('existing_db.db')
        with open('dump.sql', 'w') as f:
            for line in con.iterdump():
                f.write('%s\n' % line)
        con.close()

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

    This method makes a backup of an SQLite database even while it’s being accessed by other clients, or concurrently by the same connection. The copy will be written into the mandatory argument target, that must be another `Connection` instance.

    By default, or when pages is either `0` or a negative integer, the entire database is copied in a single step; otherwise the method performs a loop copying up to pages pages at a time.

    If progress is specified, it must either be `None` or a callable object that will be executed at each iteration with three integer arguments, respectively the status of the last iteration, the remaining number of pages still to be copied and the total number of pages.

    The name argument specifies the database name that will be copied: it must be a string containing either `"main"`, the default, to indicate the main database, `"temp"` to indicate the temporary database or the name specified after the `AS` keyword in an `ATTACH DATABASE` statement for an attached database.

    The sleep argument specifies the number of seconds to sleep by between successive attempts to backup remaining pages, can be specified either as an integer or a floating point value.

    Example 1, copy an existing database into another:

        import sqlite3

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

        con = sqlite3.connect('existing_db.db')
        bck = sqlite3.connect('backup.db')
        with bck:
            con.backup(bck, pages=1, progress=progress)
        bck.close()
        con.close()

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

        import sqlite3

        source = sqlite3.connect('existing_db.db')
        dest = sqlite3.connect(':memory:')
        source.backup(dest)

    New in version 3.7.

  getlimit(category, /)

    Get a connection run-time limit. category is the limit category to be queried.

    Example, query the maximum length of an SQL statement:

        import sqlite3
        con = sqlite3.connect(":memory:")
        lim = con.getlimit(sqlite3.SQLITE_LIMIT_SQL_LENGTH)
        print(f"SQLITE_LIMIT_SQL_LENGTH={lim}")

    New in version 3.11.

  setlimit(category, limit, /)

    Set a connection run-time limit. category is the limit category to be set. limit is the new limit. If the new limit is a negative number, the limit is unchanged.

    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.

    Example, limit the number of attached databases to 1:

        import sqlite3
        con = sqlite3.connect(":memory:")
        con.setlimit(sqlite3.SQLITE_LIMIT_ATTACHED, 1)

    New in version 3.11.

  serialize(*, name='main')

    This method serializes 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.

    name is the database to be serialized, and defaults to the main database.

    Note

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

    New in version 3.11.

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

    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. Deserialization will raise `OperationalError` if the database connection is currently involved in a read transaction or a backup operation. `OverflowError` will be raised if `len(data)` is larger than `2**63 - 1`, and `DatabaseError` will be raised if data does not contain a valid SQLite database.

    Note

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

    New in version 3.11.

## Cursor Objects

class sqlite3.Cursor

  A `Cursor` instance has the following attributes and methods.

  execute(sql, parameters=(), /)

    Execute an SQL statement. Values may be bound to the statement using placeholders.

    `execute()` will only execute a single SQL statement. If you try to execute more than one statement with it, it will raise a `ProgrammingError`. Use `executescript()` if you want to execute multiple SQL statements with one call.

    If `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.

  executemany(sql, seq_of_parameters, /)

    Execute a parameterized SQL command against all parameter sequences or mappings found in the sequence seq_of_parameters. It is also possible to use an iterator yielding parameters instead of a sequence. Uses the same implicit transaction handling as `execute()`.

        import sqlite3

        class IterChars:
            def __init__(self):
                self.count = ord('a')

            def __iter__(self):
                return self

            def __next__(self):
                if self.count > ord('z'):
                    raise StopIteration
                self.count += 1
                return (chr(self.count - 1),) # this is a 1-tuple

        con = sqlite3.connect(":memory:")
        cur = con.cursor()
        cur.execute("create table characters(c)")

        theIter = IterChars()
        cur.executemany("insert into characters(c) values (?)", theIter)

        cur.execute("select c from characters")
        print(cur.fetchall())

        con.close()

    Here’s a shorter example using a generator:

        import sqlite3
        import string

        def char_generator():
            for c in string.ascii_lowercase:
                yield (c,)

        con = sqlite3.connect(":memory:")
        cur = con.cursor()
        cur.execute("create table characters(c)")

        cur.executemany("insert into characters(c) values (?)", char_generator())

        cur.execute("select c from characters")
        print(cur.fetchall())

        con.close()

  executescript(sql_script, /)

    Execute multiple SQL statements at once. If there is a pending transaciton, an implicit `COMMIT` statement is executed first. No other implicit transaction control is performed; any transaction control must be added to sql_script.

    sql_script must be a `string`.

    Example:

        import sqlite3

        con = sqlite3.connect(":memory:")
        cur = con.cursor()
        cur.executescript("""
            create table person(
                firstname,
                lastname,
                age
            );

            create table book(
                title,
                author,
                published
            );

            insert into book(title, author, published)
            values (
                'Dirk Gently''s Holistic Detective Agency',
                'Douglas Adams',
                1987
            );
            """)
        con.close()

  fetchone()

    Fetches the next row of a query result set, returning a single sequence, or `None` when no more data is available.

  fetchmany(size=cursor.arraysize)

    Fetches the next set of rows of a query result, returning a list. An empty list is returned when no more rows are available.

    The number of rows to fetch per call is specified by the size parameter. If it is not given, the cursor’s arraysize determines the number of rows to be fetched. The method should try to fetch as many rows as indicated by the size parameter. If this is not possible due to the specified number of rows not being available, fewer rows may be returned.

    Note there are performance considerations involved with the size parameter. For optimal performance, it is usually best to use the arraysize attribute. If the size parameter is used, then it is best for it to retain the same value from one `fetchmany()` call to the next.

  fetchall()

    Fetches all (remaining) rows of a query result, returning a list. Note that the cursor’s arraysize attribute can affect the performance of this operation. An empty list is returned when no rows are available.

  close()

    Close the cursor now (rather than whenever `__del__` is called).

    The cursor will be unusable from this point forward; a `ProgrammingError` exception will be raised if any operation is attempted with the cursor.

  setinputsizes(sizes, /)

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

  setoutputsize(size, column=None, /)

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

  rowcount

    Read-only attribute that provides the number of modified rows for `INSERT`, `UPDATE`, `DELETE`, and `REPLACE` statements; is `-1` for other statements, including CTE queries. It is only updated by the `execute()` and `executemany()` methods.

  lastrowid

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

    Note

    Inserts into `WITHOUT ROWID` tables are not recorded.

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

  arraysize

    Read/write attribute that controls the number of rows returned by `fetchmany()`. The default value is 1 which means a single row would be fetched per call.

  description

    This read-only attribute 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.

  connection

    This read-only attribute provides the SQLite database `Connection` used by the `Cursor` object. 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

## Row Objects

class sqlite3.Row

  A `Row` instance serves as a highly optimized `row_factory` for `Connection` objects. It tries to mimic a tuple in most of its features.

  It supports mapping access by column name and index, iteration, representation, equality testing and `len()`.

  If two `Row` objects have exactly the same columns and their members are equal, they compare equal.

  keys()

    This method returns a list of column names. Immediately after a query, it is the first member of each tuple in `Cursor.description`.

  Changed in version 3.5: Added support of slicing.

Let’s assume we initialize a table as in the example given above:

    con = sqlite3.connect(":memory:")
    cur = con.cursor()
    cur.execute('''create table stocks
    (date text, trans text, symbol text,
     qty real, price real)''')
    cur.execute("""insert into stocks
                values ('2006-01-05','BUY','RHAT',100,35.14)""")
    con.commit()
    cur.close()

Now we plug `Row` in:

    >>> con.row_factory = sqlite3.Row
    >>> cur = con.cursor()
    >>> cur.execute('select * from stocks')
    <sqlite3.Cursor object at 0x7f4e7dd8fa80>
    >>> r = cur.fetchone()
    >>> type(r)
    <class 'sqlite3.Row'>
    >>> tuple(r)
    ('2006-01-05', 'BUY', 'RHAT', 100.0, 35.14)
    >>> len(r)
    5
    >>> r[2]
    'RHAT'
    >>> r.keys()
    ['date', 'trans', 'symbol', 'qty', 'price']
    >>> r['qty']
    100.0
    >>> for member in r:
    ...     print(member)
    ...
    2006-01-05
    BUY
    RHAT
    100.0
    35.14

## Blob Objects

New in version 3.11.

class sqlite3.Blob

  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.

      import sqlite3

      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 are `os.SEEK_CUR` (seek relative to the current position) and `os.SEEK_END` (seek relative to the blob’s end).

## PrepareProtocol Objects

class sqlite3.PrepareProtocol

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

## Exceptions

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

exception sqlite3.Warning

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

exception sqlite3.Error

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

  sqlite_errorcode

    The numeric error code from the SQLite API

    New in version 3.11.

  sqlite_errorname

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

    New in version 3.11.

exception sqlite3.InterfaceError

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

exception sqlite3.DatabaseError

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

exception sqlite3.DataError

  Exception raised for errors caused by problems with the processed data, like numeric values out of range, and strings which are too long. `DataError` is a subclass of `DatabaseError`.

exception sqlite3.OperationalError

  Exception raised for errors that are related to the database’s operation, and not necessarily under the control of the programmer. For example, the database path is not found, or a transaction could not be processed. `OperationalError` is a subclass of `DatabaseError`.

exception sqlite3.IntegrityError

  Exception raised when the relational integrity of the database is affected, e.g. a foreign key check fails. It is a subclass of `DatabaseError`.

exception sqlite3.InternalError

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

exception sqlite3.ProgrammingError

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

exception sqlite3.NotSupportedError

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

## SQLite and Python types

### Introduction

SQLite natively supports the following types: `NULL`, `INTEGER`, `REAL`, `TEXT`, `BLOB`.

The following Python types can thus be sent to SQLite without any problem:

Python type | SQLite type
--- | ---
`None` | `NULL`
`int` | `INTEGER`
`float` | `REAL`
`str` | `TEXT`
`bytes` | `BLOB`

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

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

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

### Using adapters to store custom Python types in SQLite databases

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.

#### Letting your object adapt itself

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`.

    import sqlite3

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

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

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

    p = Point(4.0, -3.2)
    cur.execute("select ?", (p,))
    print(cur.fetchone()[0])

    con.close()

#### Registering an adapter callable

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()`.

    import sqlite3

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

    def adapt_point(point):
        return "%f;%f" % (point.x, point.y)

    sqlite3.register_adapter(Point, adapt_point)

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

    p = Point(4.0, -3.2)
    cur.execute("select ?", (p,))
    print(cur.fetchone()[0])

    con.close()

### Converting SQLite values to custom Python types

Writing an adapter lets you convert from custom Python types to SQLite values. To be able to convert from SQLite values to custom Python types, we use converters.

Let’s go back to the `Point` class. We stored the x and y coordinates separated via semicolons as strings in SQLite.

First, we’ll define a converter function that accepts the string as a parameter and constructs a `Point` object from it.

Note

Converter functions are always passed a `bytes` object, no matter the underlying SQLite data type.

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

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

- Implicit: set detect_types to `PARSE_DECLTYPES`

- Explicit: set detect_types to `PARSE_COLNAMES`

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

The following example illustrates the implicit and explicit approaches:

    import sqlite3

    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}".encode("utf-8")

    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()

### 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.

Note

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

### 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)

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

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

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

## Controlling Transactions

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. Use the `commit()` and `rollback()` methods to respectively commit and roll back pending transactions. You can choose the underlying SQLite transaction behaviour — that is, whether and what type of `BEGIN` statements `sqlite3` implicitly executes – via the `isolation_level` attribute.

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

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

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

## SQLite URI tricks

Some useful URI tricks include:

- Open a database in read-only mode:

      con = sqlite3.connect("file:template.db?mode=ro", uri=True)

- 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)

- Create a shared named in-memory database:

      con1 = sqlite3.connect("file:mem1?mode=memory&cache=shared", uri=True)
      con2 = sqlite3.connect("file:mem1?mode=memory&cache=shared", uri=True)
      con1.execute("create table t(t)")
      con1.execute("insert into t values(28)")
      con1.commit()
      rows = con2.execute("select * from t").fetchall()

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

## Using `sqlite3` efficiently

### Using shortcut methods

Using the nonstandard `execute()`, `executemany()` and `executescript()` methods of the `Connection` object, 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.

    import sqlite3

    langs = [
        ("C++", 1985),
        ("Objective-C", 1984),
    ]

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

    # Create the table
    con.execute("create table lang(name, first_appeared)")

    # Fill the table
    con.executemany("insert into lang(name, first_appeared) values (?, ?)", langs)

    # 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,
    # so the connection object should be closed manually
    con.close()

### Accessing columns by name instead of by index

One useful feature of the `sqlite3` module is the built-in `sqlite3.Row` class designed to be used as a row factory.

Rows wrapped with this class can be accessed both by index (like tuples) and case-insensitively by name:

    import sqlite3

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

    cur = con.cursor()
    cur.execute("select 'John' as name, 42 as age")
    for row in cur:
        assert row[0] == row["name"]
        assert row["name"] == row["nAmE"]
        assert row[1] == row["age"]
        assert row[1] == row["AgE"]

    con.close()

### Using the connection as a 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.

Note

The context manager neither implicitly opens a new transaction nor closes the connection.

    import sqlite3

    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()

Footnotes

1(1,2)

  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.