"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   | threadsafety      | SQLITE_THREADSAFE      | DB-API 2.0 meaning              |
   | mode               |                   |                        |                                 |
   |====================|===================|========================|=================================|
   | 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 (Uniform Resource Identifier) 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 (Binary Large OBject) 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 (Common Table
      Expression) 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 (Binary Large OBject). 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
      (End of File) 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] 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.
