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 a SQL interface compliant with the DB-API 2.0 specification described by PEP 249. To use the module, you must first create 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')
 You can also supply the special name :memory: to create a database in RAM. Once you have a Connection, you can 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 data you’ve saved is persistent and is available in subsequent sessions: import sqlite3
con = sqlite3.connect('example.db')
cur = con.cursor()
 To retrieve data after executing a SELECT statement, you can 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)
 Usually your SQL operations will need to use values from Python variables. You shouldn’t assemble your query using Python’s string operations because doing so is insecure; it makes your program vulnerable to an SQL injection attack (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. Put a placeholder wherever you want to use a value, and then provide a tuple of values as the second argument to 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 (lang_name, lang_age)")

# This is the qmark style:
cur.execute("insert into lang values (?, ?)", ("C", 49))

# The qmark style used with executemany():
lang_list = [
    ("Fortran", 64),
    ("Python", 30),
    ("Go", 11),
]
cur.executemany("insert into lang values (?, ?)", lang_list)

# And this is the named style:
cur.execute("select * from lang where lang_name=:name and lang_age=:age",
            {"name": "C", "age": 49})
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.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.PARSE_DECLTYPES
This constant is meant to be used with the detect_types parameter of the connect() function. Setting it makes the sqlite3 module parse the declared type for each column it returns. It will parse out the first word of the declared type, i. e. for “integer primary key”, it will parse out “integer”, or for “number(10)” it will parse out “number”. Then for that column, it will look into the converters dictionary and use the converter function registered for that type there.

sqlite3.PARSE_COLNAMES
This constant is meant to be used with the detect_types parameter of the connect() function. Setting this makes the SQLite interface parse the column name for each column it returns. It will look for a string formed [mytype] in there, and then decide that ‘mytype’ is the type of the column. It will try to find an entry of ‘mytype’ in the converters dictionary and then use the converter function found there to return the value. The column name found in Cursor.description does not include the type, i. e. if you use something like 'as "Expiration date [datetime]"' in your SQL, then we will parse out everything until the first '[' for the column name and strip the preceeding space: the column name would simply be “Expiration date”.

sqlite3.connect(database[, timeout, detect_types, isolation_level, check_same_thread, factory, cached_statements, uri])
Opens a connection to the SQLite database file database. By default returns a Connection object, unless a custom factory is given. database is a path-like object giving the pathname (absolute or relative to the current working directory) of the database file to be opened. You can use ":memory:" to open a database connection to a database that resides in RAM instead of on disk. When a database is accessed by multiple connections, and one of the processes modifies the database, the SQLite database is locked until that transaction is committed. The timeout parameter specifies how long the connection should wait for the lock to go away until raising an exception. The default for the timeout parameter is 5.0 (five seconds). For the isolation_level parameter, please see the isolation_level property of Connection objects. SQLite natively supports only the types TEXT, INTEGER, REAL, BLOB and NULL. If you want to use other types you must add support for them yourself. The detect_types parameter and the using custom converters registered with the module-level register_converter() function allow you to easily do that. detect_types defaults to 0 (i. e. off, no type detection), you can set it to any combination of PARSE_DECLTYPES and PARSE_COLNAMES to turn type detection on. Due to SQLite behaviour, types can’t be detected for generated fields (for example max(data)), even when detect_types parameter is set. In such case, the returned type is str. By default, check_same_thread is True and only the creating thread may use the connection. If set False, the returned connection may be shared across multiple threads. When using multiple threads with the same connection writing operations should be serialized by the user to avoid data corruption. By default, the sqlite3 module uses its Connection class for the connect call. You can, however, subclass the Connection class and make connect() use your class instead by providing your class for the factory parameter. Consult the section SQLite and Python types of this manual for details. The sqlite3 module internally uses a statement cache to avoid SQL parsing overhead. If you want to explicitly set the number of statements that are cached for the connection, you can set the cached_statements parameter. The currently implemented default is to cache 100 statements. If uri is true, database is interpreted as a URI. This allows you to specify options. For example, to open a database in read-only mode you can use: db = sqlite3.connect('file:path/to/database?mode=ro', uri=True)
 More information about this feature, including a list of recognized options, can be found in the SQLite URI documentation. Raises an auditing event sqlite3.connect with argument database.  Changed in version 3.4: Added the uri parameter.   Changed in version 3.7: database can now also be a path-like object, not only a string.

sqlite3.register_converter(typename, callable)
Registers a callable to convert a bytestring from the database into a custom Python type. The callable will be invoked for all database values that are of the type typename. Confer the parameter detect_types of the connect() function for how the type detection works. Note that typename and the name of the type in your query are matched in case-insensitive manner.

sqlite3.register_adapter(type, callable)
Registers a callable to convert the custom Python type type into one of SQLite’s supported types. The callable callable accepts as single parameter the Python value, and must return a value of the following types: int, float, str or bytes.

sqlite3.complete_statement(sql)
Returns True if the string sql 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:
            print("An error occurred:", e.args[0])
        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.
 Connection Objects
class sqlite3.Connection
A SQLite database connection has the following attributes and methods:
isolation_level
Get or set the current default isolation level. None for autocommit mode or one of “DEFERRED”, “IMMEDIATE” or “EXCLUSIVE”. See section Controlling Transactions for a more detailed explanation.

in_transaction
True if a transaction is active (there are uncommitted changes), False otherwise. Read-only attribute.  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.

commit()
This method commits the current transaction. If you don’t call this method, anything you did since the last call to commit() is not visible from other database connections. If you wonder why you don’t see the data you’ve written to the database, please check you didn’t forget to call this method.

rollback()
This method rolls back any changes to the database since the last call to commit().

close()
This closes the database connection. Note that this does not automatically call commit(). If you just close your database connection without calling commit() first, your changes will be lost!

execute(sql[, parameters])
This is a nonstandard shortcut that creates a cursor object by calling the cursor() method, calls the cursor’s execute() method with the parameters given, and returns the cursor.

executemany(sql[, parameters])
This is a nonstandard shortcut that creates a cursor object by calling the cursor() method, calls the cursor’s executemany() method with the parameters given, and returns the cursor.

executescript(sql_script)
This is a nonstandard shortcut that creates a cursor object by calling the cursor() method, calls the cursor’s executescript() method with the given sql_script, and returns the cursor.

create_function(name, num_params, func, *, deterministic=False)
Creates a user-defined function that you can later use from within SQL statements under the function name name. num_params is the number of parameters the function accepts (if num_params 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 supported by SQLite: bytes, str, int, float and None.  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, num_params, aggregate_class)
Creates a user-defined aggregate function. The aggregate class must implement a step method, which accepts the number of parameters num_params (if num_params 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 supported by SQLite: bytes, str, int, float and None. 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_collation(name, callable)
Creates a collation with the specified name and callable. The callable will be passed two string arguments. It should return -1 if the first is ordered lower than the second, 0 if they are ordered equal and 1 if the first is ordered higher than the second. Note that this controls sorting (ORDER BY in SQL) so your comparisons don’t affect other SQL operations. Note that the callable will get its parameters as Python bytestrings, which will normally be encoded in UTF-8. The following example shows a custom collation that sorts “the wrong way”: 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()
 To remove a collation, call create_collation with None as callable: con.create_collation("reverse", None)

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.

set_progress_handler(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 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 string) 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 Python module and the execution of triggers defined in the current database. Passing None as trace_callback will disable 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.  New in version 3.2.  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 a 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.  New in version 3.2.

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 Unicode objects for TEXT. If you want to return bytestrings 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 = "\xd6sterreich"

# by default, rows are returned as Unicode
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 a 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)
 Availability: SQLite 3.6.11 or higher  New in version 3.7.

 Cursor Objects
class sqlite3.Cursor
A Cursor instance has the following attributes and methods.
execute(sql[, parameters])
Executes 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 Warning. Use executescript() if you want to execute multiple SQL statements with one call.

executemany(sql, seq_of_parameters)
Executes a parameterized SQL command against all parameter sequences or mappings found in the sequence seq_of_parameters. The sqlite3 module also allows using an iterator yielding parameters instead of a sequence. 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)
This is a nonstandard convenience method for executing multiple SQL statements at once. It issues a COMMIT statement first, then executes the SQL script it gets as a parameter. sql_script can be an instance of str. 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.

rowcount
Although the Cursor class of the sqlite3 module implements this attribute, the database engine’s own support for the determination of “rows affected”/”rows selected” is quirky. For executemany() statements, the number of modifications are summed up into rowcount. As required by the Python DB API Spec, the rowcount attribute “is -1 in case no executeXX() has been performed on the cursor or the rowcount of the last operation is not determinable by the interface”. This includes SELECT statements because we cannot determine the number of rows a query produced until all rows were fetched. With SQLite versions before 3.6.5, rowcount is set to 0 if you make a DELETE FROM table without any condition.

lastrowid
This read-only attribute provides the rowid of the last modified row. It is only set if you issued an INSERT or a REPLACE statement using the execute() method. For operations other than INSERT or REPLACE or when executemany() is called, lastrowid is set to None. If the INSERT or REPLACE statement failed to insert the previous successful rowid is returned.  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
 Exceptions
exception sqlite3.Warning
A subclass of Exception.

exception sqlite3.Error
The base class of the other exceptions in this module. It is a subclass of Exception.

exception sqlite3.DatabaseError
Exception raised for errors that are related to the database.

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.ProgrammingError
Exception raised for programming errors, e.g. table not found or already exists, syntax error in the SQL statement, wrong number of parameters specified, etc. It 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, e.g. an unexpected disconnect occurs, the data source name is not found, a transaction could not be processed, etc. It is a subclass of DatabaseError.

exception sqlite3.NotSupportedError
Exception raised in case a method or database API was used which is not supported by the database, e.g. calling the rollback() method on a connection that does not support transaction or has transactions turned off. It 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 a 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 additional Python types in SQLite databases As described before, SQLite supports only a limited set of types natively. To use other Python types with SQLite, you must adapt them to one of the sqlite3 module’s supported types for SQLite: one of NoneType, int, float, str, bytes. There are two ways to enable the sqlite3 module to adapt a custom Python type to one of the supported ones. Letting your object adapt itself This is a good approach if you write the class yourself. Let’s suppose you have a class like this: class Point:
    def __init__(self, x, y):
        self.x, self.y = x, y
 Now you want to store the point in a single SQLite column. First you’ll have to choose one of the supported types to be used for representing the point. Let’s just use str and separate the coordinates using a semicolon. Then you need to give your class a method __conform__(self, protocol) which must return the converted value. The parameter protocol will be 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 type to the string representation and register the function with 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()
 The sqlite3 module has two default adapters for Python’s built-in datetime.date and datetime.datetime types. Now let’s suppose we want to store datetime.datetime objects not in ISO representation, but as a Unix timestamp. import sqlite3
import datetime
import time

def adapt_datetime(ts):
    return time.mktime(ts.timetuple())

sqlite3.register_adapter(datetime.datetime, adapt_datetime)

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

now = datetime.datetime.now()
cur.execute("select ?", (now,))
print(cur.fetchone()[0])

con.close()
 Converting SQLite values to custom Python types Writing an adapter lets you send custom Python types to SQLite. But to make it really useful we need to make the Python to SQLite to Python roundtrip work. Enter 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 always get called with a bytes object, no matter under which data type you sent the value to SQLite.  def convert_point(s):
    x, y = map(float, s.split(b";"))
    return Point(x, y)
 Now you need to make the sqlite3 module know that what you select from the database is actually a point. There are two ways of doing this:  Implicitly via the declared type Explicitly via the column name  Both ways are described in section Module functions and constants, in the entries for the constants PARSE_DECLTYPES and PARSE_COLNAMES. The following example illustrates both approaches. import sqlite3

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

    def __repr__(self):
        return "(%f;%f)" % (self.x, self.y)

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

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

# Register the adapter
sqlite3.register_adapter(Point, adapt_point)

# Register the converter
sqlite3.register_converter("point", convert_point)

p = Point(4.0, -3.2)

#########################
# 1) Using declared types
con = sqlite3.connect(":memory:", detect_types=sqlite3.PARSE_DECLTYPES)
cur = con.cursor()
cur.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()

#######################
# 1) Using column names
con = sqlite3.connect(":memory:", detect_types=sqlite3.PARSE_COLNAMES)
cur = con.cursor()
cur.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. Controlling Transactions The underlying sqlite3 library operates in autocommit mode by default, but the Python sqlite3 module by default does not. autocommit mode means that statements that modify the database take effect immediately. A BEGIN or SAVEPOINT statement disables autocommit mode, and a COMMIT, a ROLLBACK, or a RELEASE that ends the outermost transaction, turns autocommit mode back on. The Python sqlite3 module by default issues a BEGIN statement implicitly before a Data Modification Language (DML) statement (i.e. INSERT/UPDATE/DELETE/REPLACE). You can control which kind of BEGIN statements sqlite3 implicitly executes via the isolation_level parameter to the connect() call, or via the isolation_level property of connections. If you specify no isolation_level, a plain BEGIN is used, which is equivalent to specifying DEFERRED. Other possible values are IMMEDIATE and EXCLUSIVE. You can disable the sqlite3 module’s implicit transaction management by setting isolation_level to None. This will leave the underlying sqlite3 library operating in autocommit mode. You can then completely control the transaction state by explicitly issuing BEGIN, ROLLBACK, SAVEPOINT, and RELEASE statements in your code.  Changed in version 3.6: sqlite3 used to implicitly commit an open transaction before DDL statements. This is no longer the case.  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

persons = [
    ("Hugo", "Boss"),
    ("Calvin", "Klein")
    ]

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

# Create the table
con.execute("create table person(firstname, lastname)")

# Fill the table
con.executemany("insert into person(firstname, lastname) values (?, ?)", persons)

# Print the table contents
for row in con.execute("select firstname, lastname from person"):
    print(row)

print("I just deleted", con.execute("delete from person").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 Connection objects can be used as context managers that automatically commit or rollback transactions. In the event of an exception, the transaction is rolled back; otherwise, the transaction is committed: import sqlite3

con = sqlite3.connect(":memory:")
con.execute("create table person (id integer primary key, firstname varchar unique)")

# Successful, con.commit() is called automatically afterwards
with con:
    con.execute("insert into person(firstname) values (?)", ("Joe",))

# 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 person(firstname) values (?)", ("Joe",))
except sqlite3.IntegrityError:
    print("couldn't add Joe 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 Mac OS X) have SQLite libraries which are compiled without this feature. To get loadable extension support, you must pass --enable-loadable-sqlite-extensions to configure.


sqlite3.complete_statement(sql)
Returns True if the string sql 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:
            print("An error occurred:", e.args[0])
        buffer = ""

con.close()


sqlite3.connect(database[, timeout, detect_types, isolation_level, check_same_thread, factory, cached_statements, uri])
Opens a connection to the SQLite database file database. By default returns a Connection object, unless a custom factory is given. database is a path-like object giving the pathname (absolute or relative to the current working directory) of the database file to be opened. You can use ":memory:" to open a database connection to a database that resides in RAM instead of on disk. When a database is accessed by multiple connections, and one of the processes modifies the database, the SQLite database is locked until that transaction is committed. The timeout parameter specifies how long the connection should wait for the lock to go away until raising an exception. The default for the timeout parameter is 5.0 (five seconds). For the isolation_level parameter, please see the isolation_level property of Connection objects. SQLite natively supports only the types TEXT, INTEGER, REAL, BLOB and NULL. If you want to use other types you must add support for them yourself. The detect_types parameter and the using custom converters registered with the module-level register_converter() function allow you to easily do that. detect_types defaults to 0 (i. e. off, no type detection), you can set it to any combination of PARSE_DECLTYPES and PARSE_COLNAMES to turn type detection on. Due to SQLite behaviour, types can’t be detected for generated fields (for example max(data)), even when detect_types parameter is set. In such case, the returned type is str. By default, check_same_thread is True and only the creating thread may use the connection. If set False, the returned connection may be shared across multiple threads. When using multiple threads with the same connection writing operations should be serialized by the user to avoid data corruption. By default, the sqlite3 module uses its Connection class for the connect call. You can, however, subclass the Connection class and make connect() use your class instead by providing your class for the factory parameter. Consult the section SQLite and Python types of this manual for details. The sqlite3 module internally uses a statement cache to avoid SQL parsing overhead. If you want to explicitly set the number of statements that are cached for the connection, you can set the cached_statements parameter. The currently implemented default is to cache 100 statements. If uri is true, database is interpreted as a URI. This allows you to specify options. For example, to open a database in read-only mode you can use: db = sqlite3.connect('file:path/to/database?mode=ro', uri=True)
 More information about this feature, including a list of recognized options, can be found in the SQLite URI documentation. Raises an auditing event sqlite3.connect with argument database.  Changed in version 3.4: Added the uri parameter.   Changed in version 3.7: database can now also be a path-like object, not only a string.


class sqlite3.Connection
A SQLite database connection has the following attributes and methods:
isolation_level
Get or set the current default isolation level. None for autocommit mode or one of “DEFERRED”, “IMMEDIATE” or “EXCLUSIVE”. See section Controlling Transactions for a more detailed explanation.

in_transaction
True if a transaction is active (there are uncommitted changes), False otherwise. Read-only attribute.  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.

commit()
This method commits the current transaction. If you don’t call this method, anything you did since the last call to commit() is not visible from other database connections. If you wonder why you don’t see the data you’ve written to the database, please check you didn’t forget to call this method.

rollback()
This method rolls back any changes to the database since the last call to commit().

close()
This closes the database connection. Note that this does not automatically call commit(). If you just close your database connection without calling commit() first, your changes will be lost!

execute(sql[, parameters])
This is a nonstandard shortcut that creates a cursor object by calling the cursor() method, calls the cursor’s execute() method with the parameters given, and returns the cursor.

executemany(sql[, parameters])
This is a nonstandard shortcut that creates a cursor object by calling the cursor() method, calls the cursor’s executemany() method with the parameters given, and returns the cursor.

executescript(sql_script)
This is a nonstandard shortcut that creates a cursor object by calling the cursor() method, calls the cursor’s executescript() method with the given sql_script, and returns the cursor.

create_function(name, num_params, func, *, deterministic=False)
Creates a user-defined function that you can later use from within SQL statements under the function name name. num_params is the number of parameters the function accepts (if num_params 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 supported by SQLite: bytes, str, int, float and None.  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, num_params, aggregate_class)
Creates a user-defined aggregate function. The aggregate class must implement a step method, which accepts the number of parameters num_params (if num_params 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 supported by SQLite: bytes, str, int, float and None. 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_collation(name, callable)
Creates a collation with the specified name and callable. The callable will be passed two string arguments. It should return -1 if the first is ordered lower than the second, 0 if they are ordered equal and 1 if the first is ordered higher than the second. Note that this controls sorting (ORDER BY in SQL) so your comparisons don’t affect other SQL operations. Note that the callable will get its parameters as Python bytestrings, which will normally be encoded in UTF-8. The following example shows a custom collation that sorts “the wrong way”: 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()
 To remove a collation, call create_collation with None as callable: con.create_collation("reverse", None)

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.

set_progress_handler(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 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 string) 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 Python module and the execution of triggers defined in the current database. Passing None as trace_callback will disable 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.  New in version 3.2.  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 a 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.  New in version 3.2.

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 Unicode objects for TEXT. If you want to return bytestrings 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 = "\xd6sterreich"

# by default, rows are returned as Unicode
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 a 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)
 Availability: SQLite 3.6.11 or higher  New in version 3.7.


backup(target, *, pages=-1, progress=None, name="main", sleep=0.250)
This method makes a backup of a 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)
 Availability: SQLite 3.6.11 or higher  New in version 3.7.


close()
This closes the database connection. Note that this does not automatically call commit(). If you just close your database connection without calling commit() first, your changes will be lost!


commit()
This method commits the current transaction. If you don’t call this method, anything you did since the last call to commit() is not visible from other database connections. If you wonder why you don’t see the data you’ve written to the database, please check you didn’t forget to call this method.


create_aggregate(name, num_params, aggregate_class)
Creates a user-defined aggregate function. The aggregate class must implement a step method, which accepts the number of parameters num_params (if num_params 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 supported by SQLite: bytes, str, int, float and None. 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_collation(name, callable)
Creates a collation with the specified name and callable. The callable will be passed two string arguments. It should return -1 if the first is ordered lower than the second, 0 if they are ordered equal and 1 if the first is ordered higher than the second. Note that this controls sorting (ORDER BY in SQL) so your comparisons don’t affect other SQL operations. Note that the callable will get its parameters as Python bytestrings, which will normally be encoded in UTF-8. The following example shows a custom collation that sorts “the wrong way”: 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()
 To remove a collation, call create_collation with None as callable: con.create_collation("reverse", None)


create_function(name, num_params, func, *, deterministic=False)
Creates a user-defined function that you can later use from within SQL statements under the function name name. num_params is the number of parameters the function accepts (if num_params 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 supported by SQLite: bytes, str, int, float and None.  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()


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.


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.  New in version 3.2.  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()


execute(sql[, parameters])
This is a nonstandard shortcut that creates a cursor object by calling the cursor() method, calls the cursor’s execute() method with the parameters given, and returns the cursor.


executemany(sql[, parameters])
This is a nonstandard shortcut that creates a cursor object by calling the cursor() method, calls the cursor’s executemany() method with the parameters given, and returns the cursor.


executescript(sql_script)
This is a nonstandard shortcut that creates a cursor object by calling the cursor() method, calls the cursor’s executescript() method with the given sql_script, and returns the cursor.


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.


in_transaction
True if a transaction is active (there are uncommitted changes), False otherwise. Read-only attribute.  New in version 3.2.


isolation_level
Get or set the current default isolation level. None for autocommit mode or one of “DEFERRED”, “IMMEDIATE” or “EXCLUSIVE”. See section Controlling Transactions for a more detailed explanation.


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()


load_extension(path)
This routine loads a 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.  New in version 3.2.


rollback()
This method rolls back any changes to the database since the last call to commit().


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.


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.


set_progress_handler(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 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 string) 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 Python module and the execution of triggers defined in the current database. Passing None as trace_callback will disable the trace callback.  New in version 3.3.


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 Unicode objects for TEXT. If you want to return bytestrings 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 = "\xd6sterreich"

# by default, rows are returned as Unicode
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.


class sqlite3.Cursor
A Cursor instance has the following attributes and methods.
execute(sql[, parameters])
Executes 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 Warning. Use executescript() if you want to execute multiple SQL statements with one call.

executemany(sql, seq_of_parameters)
Executes a parameterized SQL command against all parameter sequences or mappings found in the sequence seq_of_parameters. The sqlite3 module also allows using an iterator yielding parameters instead of a sequence. 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)
This is a nonstandard convenience method for executing multiple SQL statements at once. It issues a COMMIT statement first, then executes the SQL script it gets as a parameter. sql_script can be an instance of str. 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.

rowcount
Although the Cursor class of the sqlite3 module implements this attribute, the database engine’s own support for the determination of “rows affected”/”rows selected” is quirky. For executemany() statements, the number of modifications are summed up into rowcount. As required by the Python DB API Spec, the rowcount attribute “is -1 in case no executeXX() has been performed on the cursor or the rowcount of the last operation is not determinable by the interface”. This includes SELECT statements because we cannot determine the number of rows a query produced until all rows were fetched. With SQLite versions before 3.6.5, rowcount is set to 0 if you make a DELETE FROM table without any condition.

lastrowid
This read-only attribute provides the rowid of the last modified row. It is only set if you issued an INSERT or a REPLACE statement using the execute() method. For operations other than INSERT or REPLACE or when executemany() is called, lastrowid is set to None. If the INSERT or REPLACE statement failed to insert the previous successful rowid is returned.  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


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.


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.


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


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.


execute(sql[, parameters])
Executes 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 Warning. Use executescript() if you want to execute multiple SQL statements with one call.


executemany(sql, seq_of_parameters)
Executes a parameterized SQL command against all parameter sequences or mappings found in the sequence seq_of_parameters. The sqlite3 module also allows using an iterator yielding parameters instead of a sequence. 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)
This is a nonstandard convenience method for executing multiple SQL statements at once. It issues a COMMIT statement first, then executes the SQL script it gets as a parameter. sql_script can be an instance of str. 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()


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.


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.


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


lastrowid
This read-only attribute provides the rowid of the last modified row. It is only set if you issued an INSERT or a REPLACE statement using the execute() method. For operations other than INSERT or REPLACE or when executemany() is called, lastrowid is set to None. If the INSERT or REPLACE statement failed to insert the previous successful rowid is returned.  Changed in version 3.6: Added support for the REPLACE statement.


rowcount
Although the Cursor class of the sqlite3 module implements this attribute, the database engine’s own support for the determination of “rows affected”/”rows selected” is quirky. For executemany() statements, the number of modifications are summed up into rowcount. As required by the Python DB API Spec, the rowcount attribute “is -1 in case no executeXX() has been performed on the cursor or the rowcount of the last operation is not determinable by the interface”. This includes SELECT statements because we cannot determine the number of rows a query produced until all rows were fetched. With SQLite versions before 3.6.5, rowcount is set to 0 if you make a DELETE FROM table without any condition.


exception sqlite3.DatabaseError
Exception raised for errors that are related to the database.


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.


exception sqlite3.Error
The base class of the other exceptions in this module. It is a subclass of Exception.


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.NotSupportedError
Exception raised in case a method or database API was used which is not supported by the database, e.g. calling the rollback() method on a connection that does not support transaction or has transactions turned off. It 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, e.g. an unexpected disconnect occurs, the data source name is not found, a transaction could not be processed, etc. It is a subclass of DatabaseError.


sqlite3.PARSE_COLNAMES
This constant is meant to be used with the detect_types parameter of the connect() function. Setting this makes the SQLite interface parse the column name for each column it returns. It will look for a string formed [mytype] in there, and then decide that ‘mytype’ is the type of the column. It will try to find an entry of ‘mytype’ in the converters dictionary and then use the converter function found there to return the value. The column name found in Cursor.description does not include the type, i. e. if you use something like 'as "Expiration date [datetime]"' in your SQL, then we will parse out everything until the first '[' for the column name and strip the preceeding space: the column name would simply be “Expiration date”.


sqlite3.PARSE_DECLTYPES
This constant is meant to be used with the detect_types parameter of the connect() function. Setting it makes the sqlite3 module parse the declared type for each column it returns. It will parse out the first word of the declared type, i. e. for “integer primary key”, it will parse out “integer”, or for “number(10)” it will parse out “number”. Then for that column, it will look into the converters dictionary and use the converter function registered for that type there.


exception sqlite3.ProgrammingError
Exception raised for programming errors, e.g. table not found or already exists, syntax error in the SQL statement, wrong number of parameters specified, etc. It is a subclass of DatabaseError.


sqlite3.register_adapter(type, callable)
Registers a callable to convert the custom Python type type into one of SQLite’s supported types. The callable callable accepts as single parameter the Python value, and must return a value of the following types: int, float, str or bytes.


sqlite3.register_converter(typename, callable)
Registers a callable to convert a bytestring from the database into a custom Python type. The callable will be invoked for all database values that are of the type typename. Confer the parameter detect_types of the connect() function for how the type detection works. Note that typename and the name of the type in your query are matched in case-insensitive manner.


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.


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


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.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.


exception sqlite3.Warning
A subclass of Exception.


class ssl.AlertDescription
enum.IntEnum collection of ALERT_DESCRIPTION_* constants.  New in version 3.6.


ssl.ALERT_DESCRIPTION_HANDSHAKE_FAILURE
ssl.ALERT_DESCRIPTION_INTERNAL_ERROR
ALERT_DESCRIPTION_*
Alert Descriptions from RFC 5246 and others. The IANA TLS Alert Registry contains this list and references to the RFCs where their meaning is defined. Used as the return value of the callback function in SSLContext.set_servername_callback().  New in version 3.4.


exception ssl.CertificateError
An alias for SSLCertVerificationError.  Changed in version 3.7: The exception is now an alias for SSLCertVerificationError.


ssl.CERT_NONE
Possible value for SSLContext.verify_mode, or the cert_reqs parameter to wrap_socket(). Except for PROTOCOL_TLS_CLIENT, it is the default mode. With client-side sockets, just about any cert is accepted. Validation errors, such as untrusted or expired cert, are ignored and do not abort the TLS/SSL handshake. In server mode, no certificate is requested from the client, so the client does not send any for client cert authentication. See the discussion of Security considerations below.


ssl.CERT_OPTIONAL
Possible value for SSLContext.verify_mode, or the cert_reqs parameter to wrap_socket(). In client mode, CERT_OPTIONAL has the same meaning as CERT_REQUIRED. It is recommended to use CERT_REQUIRED for client-side sockets instead. In server mode, a client certificate request is sent to the client. The client may either ignore the request or send a certificate in order perform TLS client cert authentication. If the client chooses to send a certificate, it is verified. Any verification error immediately aborts the TLS handshake. Use of this setting requires a valid set of CA certificates to be passed, either to SSLContext.load_verify_locations() or as a value of the ca_certs parameter to wrap_socket().


ssl.CERT_REQUIRED
Possible value for SSLContext.verify_mode, or the cert_reqs parameter to wrap_socket(). In this mode, certificates are required from the other side of the socket connection; an SSLError will be raised if no certificate is provided, or if its validation fails. This mode is not sufficient to verify a certificate in client mode as it does not match hostnames. check_hostname must be enabled as well to verify the authenticity of a cert. PROTOCOL_TLS_CLIENT uses CERT_REQUIRED and enables check_hostname by default. With server socket, this mode provides mandatory TLS client cert authentication. A client certificate request is sent to the client and the client must provide a valid and trusted certificate. Use of this setting requires a valid set of CA certificates to be passed, either to SSLContext.load_verify_locations() or as a value of the ca_certs parameter to wrap_socket().


ssl.cert_time_to_seconds(cert_time)
Return the time in seconds since the Epoch, given the cert_time string representing the “notBefore” or “notAfter” date from a certificate in "%b %d %H:%M:%S %Y %Z" strptime format (C locale). Here’s an example: >>> import ssl
>>> timestamp = ssl.cert_time_to_seconds("Jan  5 09:34:43 2018 GMT")
>>> timestamp
1515144883
>>> from datetime import datetime
>>> print(datetime.utcfromtimestamp(timestamp))
2018-01-05 09:34:43
 “notBefore” or “notAfter” dates must use GMT (RFC 5280).  Changed in version 3.5: Interpret the input time as a time in UTC as specified by ‘GMT’ timezone in the input string. Local timezone was used previously. Return an integer (no fractions of a second in the input format)


ssl.CHANNEL_BINDING_TYPES
List of supported TLS channel binding types. Strings in this list can be used as arguments to SSLSocket.get_channel_binding().  New in version 3.3.


ssl.create_default_context(purpose=Purpose.SERVER_AUTH, cafile=None, capath=None, cadata=None)
Return a new SSLContext object with default settings for the given purpose. The settings are chosen by the ssl module, and usually represent a higher security level than when calling the SSLContext constructor directly. cafile, capath, cadata represent optional CA certificates to trust for certificate verification, as in SSLContext.load_verify_locations(). If all three are None, this function can choose to trust the system’s default CA certificates instead. The settings are: PROTOCOL_TLS, OP_NO_SSLv2, and OP_NO_SSLv3 with high encryption cipher suites without RC4 and without unauthenticated cipher suites. Passing SERVER_AUTH as purpose sets verify_mode to CERT_REQUIRED and either loads CA certificates (when at least one of cafile, capath or cadata is given) or uses SSLContext.load_default_certs() to load default CA certificates. When keylog_filename is supported and the environment variable SSLKEYLOGFILE is set, create_default_context() enables key logging.  Note The protocol, options, cipher and other settings may change to more restrictive values anytime without prior deprecation. The values represent a fair balance between compatibility and security. If your application needs specific settings, you should create a SSLContext and apply the settings yourself.   Note If you find that when certain older clients or servers attempt to connect with a SSLContext created by this function that they get an error stating “Protocol or cipher suite mismatch”, it may be that they only support SSL3.0 which this function excludes using the OP_NO_SSLv3. SSL3.0 is widely considered to be completely broken. If you still wish to continue to use this function but still allow SSL 3.0 connections you can re-enable them using: ctx = ssl.create_default_context(Purpose.CLIENT_AUTH)
ctx.options &= ~ssl.OP_NO_SSLv3
   New in version 3.4.   Changed in version 3.4.4: RC4 was dropped from the default cipher string.   Changed in version 3.6: ChaCha20/Poly1305 was added to the default cipher string. 3DES was dropped from the default cipher string.   Changed in version 3.8: Support for key logging to SSLKEYLOGFILE was added.


ssl.DER_cert_to_PEM_cert(DER_cert_bytes)
Given a certificate as a DER-encoded blob of bytes, returns a PEM-encoded string version of the same certificate.


ssl.enum_certificates(store_name)
Retrieve certificates from Windows’ system cert store. store_name may be one of CA, ROOT or MY. Windows may provide additional cert stores, too. The function returns a list of (cert_bytes, encoding_type, trust) tuples. The encoding_type specifies the encoding of cert_bytes. It is either x509_asn for X.509 ASN.1 data or pkcs_7_asn for PKCS#7 ASN.1 data. Trust specifies the purpose of the certificate as a set of OIDS or exactly True if the certificate is trustworthy for all purposes. Example: >>> ssl.enum_certificates("CA")
[(b'data...', 'x509_asn', {'1.3.6.1.5.5.7.3.1', '1.3.6.1.5.5.7.3.2'}),
 (b'data...', 'x509_asn', True)]
 Availability: Windows.  New in version 3.4.


ssl.enum_crls(store_name)
Retrieve CRLs from Windows’ system cert store. store_name may be one of CA, ROOT or MY. Windows may provide additional cert stores, too. The function returns a list of (cert_bytes, encoding_type, trust) tuples. The encoding_type specifies the encoding of cert_bytes. It is either x509_asn for X.509 ASN.1 data or pkcs_7_asn for PKCS#7 ASN.1 data. Availability: Windows.  New in version 3.4.


ssl.get_default_verify_paths()
Returns a named tuple with paths to OpenSSL’s default cafile and capath. The paths are the same as used by SSLContext.set_default_verify_paths(). The return value is a named tuple DefaultVerifyPaths:
cafile - resolved path to cafile or None if the file doesn’t exist,
capath - resolved path to capath or None if the directory doesn’t exist,
openssl_cafile_env - OpenSSL’s environment key that points to a cafile,
openssl_cafile - hard coded path to a cafile,
openssl_capath_env - OpenSSL’s environment key that points to a capath,
openssl_capath - hard coded path to a capath directory  Availability: LibreSSL ignores the environment vars openssl_cafile_env and openssl_capath_env.  New in version 3.4.


ssl.get_server_certificate(addr, ssl_version=PROTOCOL_TLS, ca_certs=None)
Given the address addr of an SSL-protected server, as a (hostname, port-number) pair, fetches the server’s certificate, and returns it as a PEM-encoded string. If ssl_version is specified, uses that version of the SSL protocol to attempt to connect to the server. If ca_certs is specified, it should be a file containing a list of root certificates, the same format as used for the same parameter in SSLContext.wrap_socket(). The call will attempt to validate the server certificate against that set of root certificates, and will fail if the validation attempt fails.  Changed in version 3.3: This function is now IPv6-compatible.   Changed in version 3.5: The default ssl_version is changed from PROTOCOL_SSLv3 to PROTOCOL_TLS for maximum compatibility with modern servers.


ssl.HAS_ALPN
Whether the OpenSSL library has built-in support for the Application-Layer Protocol Negotiation TLS extension as described in RFC 7301.  New in version 3.5.


ssl.HAS_ECDH
Whether the OpenSSL library has built-in support for the Elliptic Curve-based Diffie-Hellman key exchange. This should be true unless the feature was explicitly disabled by the distributor.  New in version 3.3.