Con commit python что это

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Для чего нужен commit, connection, cursor и close?

Для каких нужд используется cur.close() , conn.commit() , conn.close ? В чём их отличия?

Например conn.commit() , как указано в примере, применяет изменения. Но кажется логичнее, что за это будет отвечать курсор, потому как именно он является итератором по данным.

Судя по той же документации, правильный шаблон использования будет примерно такой:

Что тут имеется в виду.

• connection живёт столько, сколько нужно вам для ваших операций, если у вас операции с базой идут подряд — connection не надо закрывать и переоткрывать; но если вы поработали с базой, а потом у вас перерыв — вы, например, перемалываете какие-то данные и пока базу не пишете и не читаете, то connection лучше закрыть, чтобы она ушла в пул и другим процессам, работающим с базой, хватило этих самых connection ; и да — connection лучше закрывать в конце работы с ней и делать это наверняка (через try/finally ), чтобы точно освободить связанные с ней ресурсы
• transaction лучше создавать и закрывать с помощью блока with conn: — если не будет брошено исключение в течении работы блока with , то будет автоматически сделан commit , а если будет исключение — будет выполнен rollback ; в одном блоке транзакции нужно объединять некий неразрывный блок работы с базой, который должен быть откачен целиком в случае неудачи, а в случае успешного завершения запись данных этого блока опять же должна представлять из себя в базе фрагмент данных, который ничего не поломает, будучи записанным в базу сам по себе
• cursor — похоже, в приведённом мной шаблоне использования это просто объект, который позволяет выполнять любые операции записи/чтения внутри одной транзакции и он сам закроется по окончании блока with conn.cursor() as curs:

Немного странно, что в приведённом вами примере без with курсор получается закрывается уже после commit , видимо, можно делать и так и так. Если курсор не закрывать самому, то он, видимо, остаётся открытым всё время существования connection . Но опять же, согласно документации, лучше курсор обязательно закрыть (и удобнее сделать это неявно с помощью блока with ), чтобы он точно освободил какие-то ресурсы, которые на него выделены. Хотя, наверняка, закрытие connection и так освободит все ресурсы.

В общем, мне кажется, тут есть довольно большая свобода выбора шаблона, однако, блоки with позволяют более чётко разделить этапы работы программы с базой, если таковые этапы имеют место быть.

P.S. Конкретно по вашим вопросам отдельно:

Я напихал в БД 20000 записей при помощи 100 батчей. Нужно ли мне создавать новое соединение?

Если вы работаете с базой непрерывно, то новое соединение создавать не нужно.

А курсор? При этом, я считаю, что у меня будут ещё записи.

Опять же — это зависит от того, планируете ли вы держать и дальше открытым соединение, можно ли вашу работу записывать в базу по частям, и какой шаблон работы с базой вы выберете. При непрерывной работе с базой похоже можно открыть соединение и курсор один раз, а потом, при необходимости, делать коммиты после каждого куска выполненной работы (если она в вашем случае может быть записана в базу этими кусками и ничего при этом не поломается).

12.6. sqlite3 — DB-API 2.0 interface for SQLite databases¶

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:

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:

The data you’ve saved is persistent and is available in subsequent sessions:

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 https://xkcd.com/327/ for humorous example of what can go wrong).

Instead, use the DB-API’s parameter substitution. Put ? as 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. (Other database modules may use a different placeholder, such as %s or :1 .) For example:

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:

https://github.com/ghaering/pysqlite The pysqlite web page – sqlite3 is developed externally under the name “pysqlite”. https://www.sqlite.org The SQLite web page; the documentation describes the syntax and the available data types for the supported SQL dialect. http://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.

12.6.1. Module functions and constants¶

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

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

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

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

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.

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 is only the first word of the column name, i. e. if you use something like ‘as "x [datetime]"’ in your SQL, then we will parse out everything until the first blank for the column name: the column name would simply be “x”.

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.

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:

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

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.

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 the case of typename and the name of the type in your query must match!

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:

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.

12.6.2. Connection Objects¶

A SQLite database connection has the following attributes and methods:

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

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

New in version 3.2.

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

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.

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

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!

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.

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 ) ¶

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.

The function can return any of the types supported by SQLite: bytes, str, int, float and None .

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 .

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”:

To remove a collation, call create_collation with None as callable:

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.

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.

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.

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.

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.

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.

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.

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:

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

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.

12.6.3. Cursor Objects¶

A Cursor instance has the following attributes and methods.

Executes an SQL statement. The SQL statement may be parameterized (i. e. placeholders instead of SQL literals). The sqlite3 module supports two kinds of placeholders: question marks (qmark style) and named placeholders (named style).

Here’s an example of both styles:

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 an 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.

Here’s a shorter example using a generator :

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 .

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

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.

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 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.

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.

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.

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.

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.

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:

12.6.4. Row Objects¶

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.

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:

Now we plug Row in:

12.6.5. Exceptions¶

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 .

12.6.6. SQLite and Python types¶

12.6.6.1. 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:

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

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.

12.6.6.2. 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.

12.6.6.2.1. 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:

Now you want to store the point in a single SQLite column. First you’ll have to choose one of the supported types first 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 .

12.6.6.2.2. 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() .

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.

12.6.6.3. 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.

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.

Converter functions always get called with a bytes object, no matter under which data type you sent the value to SQLite.

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.

12.6.6.4. 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.

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.

12.6.7. Controlling Transactions¶

By default, the sqlite3 module opens transactions 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 (or none at all) via the isolation_level parameter to the connect() call, or via the isolation_level property of connections.

If you want autocommit mode, then set isolation_level to None .

Otherwise leave it at its default, which will result in a plain “BEGIN” statement, or set it to one of SQLite’s supported isolation levels: “DEFERRED”, “IMMEDIATE” or “EXCLUSIVE”.

The current transaction state is exposed through the Connection.in_transaction attribute of the connection object.

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

12.6.8. Using sqlite3 efficiently¶

12.6.8.1. 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.

12.6.8.2. 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:

12.6.8.3. 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:

12.6.9. Common issues¶

12.6.9.1. Multithreading¶

Older SQLite versions had issues with sharing connections between threads. That’s why the Python module disallows sharing connections and cursors between threads. If you still try to do so, you will get an exception at runtime.

The only exception is calling the interrupt() method, which only makes sense to call from a different thread.

sqlite3 — DB-API 2.0 interface for SQLite databases¶

SQLite is a C library that provides a lightweight disk-based database that doesn’t require a separate server process and allows accessing the database using a nonstandard variant of the SQL query language. Some applications can use SQLite for internal data storage. It’s also possible to prototype an application using SQLite and then port the code to a larger database such as PostgreSQL or Oracle.

The sqlite3 module was written by Gerhard Häring. It provides an SQL interface compliant with the DB-API 2.0 specification described by PEP 249, and requires SQLite 3.7.15 or newer.

This document includes four main sections:

Tutorial teaches how to use the sqlite3 module.

Reference describes the classes and functions this module defines.

How-to guides details how to handle specific tasks.

Explanation provides in-depth background on transaction control.

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

Tutorial, reference and examples for learning SQL syntax.

PEP 249 — Database API Specification 2.0

PEP written by Marc-André Lemburg.

Tutorial¶

In this tutorial, you will create a database of Monty Python movies using basic sqlite3 functionality. It assumes a fundamental understanding of database concepts, including cursors and transactions.

First, we need to create a new database and open a database connection to allow sqlite3 to work with it. Call sqlite3.connect() to create a connection to the database tutorial.db in the current working directory, implicitly creating it if it does not exist:

The returned Connection object con represents the connection to the on-disk database.

In order to execute SQL statements and fetch results from SQL queries, we will need to use a database cursor. Call con.cursor() to create the Cursor :

Now that we’ve got a database connection and a cursor, we can create a database table movie with columns for title, release year, and review score. For simplicity, we can just use column names in the table declaration – thanks to the flexible typing feature of SQLite, specifying the data types is optional. Execute the CREATE TABLE statement by calling cur.execute(. ) :

We can verify that the new table has been created by querying the sqlite_master table built-in to SQLite, which should now contain an entry for the movie table definition (see The Schema Table for details). Execute that query by calling cur.execute(. ) , assign the result to res , and call res.fetchone() to fetch the resulting row:

We can see that the table has been created, as the query returns a tuple containing the table’s name. If we query sqlite_master for a non-existent table spam , res.fetchone() will return None :

Now, add two rows of data supplied as SQL literals by executing an INSERT statement, once again by calling cur.execute(. ) :

The INSERT statement implicitly opens a transaction, which needs to be committed before changes are saved in the database (see Transaction control for details). Call con.commit() on the connection object to commit the transaction:

We can verify that the data was inserted correctly by executing a SELECT query. Use the now-familiar cur.execute(. ) to assign the result to res , and call res.fetchall() to return all resulting rows:

The result is a list of two tuple s, one per row, each containing that row’s score value.

Now, insert three more rows by calling cur.executemany(. ) :

Notice that ? placeholders are used to bind data to the query. Always use placeholders instead of string formatting to bind Python values to SQL statements, to avoid SQL injection attacks (see How to use placeholders to bind values in SQL queries for more details).

We can verify that the new rows were inserted by executing a SELECT query, this time iterating over the results of the query:

Each row is a two-item tuple of (year, title) , matching the columns selected in the query.

Finally, verify that the database has been written to disk by calling con.close() to close the existing connection, opening a new one, creating a new cursor, then querying the database:

You’ve now created an SQLite database using the sqlite3 module, inserted data and retrieved values from it in multiple ways.

How-to guides for further reading:

• How to use placeholders to bind values in SQL queries

• How to adapt custom Python types to SQLite values

• How to convert SQLite values to custom Python types

• How to use the connection context manager

• How to create and use row factories

Explanation for in-depth background on transaction control.

Reference¶

Module functions¶

Open a connection to an SQLite database.

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

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

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

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

check_same_thread (bool) – If True (default), ProgrammingError will be raised if the database connection is used by a thread other than the one that created it. If False , the connection may be accessed in multiple threads; write operations may need to be serialized by the user to avoid data corruption. See threadsafety for more information.

factory (Connection) – A custom subclass of Connection to create the connection with, if not the default Connection class.

cached_statements (int) – The number of statements that sqlite3 should internally cache for this connection, to avoid parsing overhead. By default, 128 statements.

Raises an auditing event sqlite3.connect with argument database .

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

New in version 3.4: The uri parameter.

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

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

Return True if the string statement appears to contain one or more complete SQL statements. No syntactic verification or parsing of any kind is performed, other than checking that there are no unclosed string literals and the statement is terminated by a semicolon.

This function may be useful during command-line input to determine if the entered text seems to form a complete SQL statement, or if additional input is needed before calling execute() .

sqlite3. enable_callback_tracebacks ( flag , / ) ¶

Enable or disable callback tracebacks. By default you will not get any tracebacks in user-defined functions, aggregates, converters, authorizer callbacks etc. If you want to debug them, you can call this function with flag set to True . Afterwards, you will get tracebacks from callbacks on sys.stderr . Use False to disable the feature again.

Register an unraisable hook handler for an improved debug experience:

Register an adapter callable to adapt the Python type type into an SQLite type. The adapter is called with a Python object of type type as its sole argument, and must return a value of a type that SQLite natively understands .

sqlite3. register_converter ( typename , converter , / ) ¶

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

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

Module constants¶

Pass this flag value to the detect_types parameter of connect() to look up a converter function by using the type name, parsed from the query column name, as the converter dictionary key. The type name must be wrapped in square brackets ( [] ).

This flag may be combined with PARSE_DECLTYPES using the | (bitwise or) operator.

Pass this flag value to the detect_types parameter of connect() to look up a converter function using the declared types for each column. The types are declared when the database table is created. sqlite3 will look up a converter function using the first word of the declared type as the converter dictionary key. For example:

This flag may be combined with PARSE_COLNAMES using the | (bitwise or) operator.

sqlite3. SQLITE_OK ¶ sqlite3. SQLITE_DENY ¶ sqlite3. SQLITE_IGNORE ¶

Flags that should be returned by the authorizer_callback callable passed to Connection.set_authorizer() , to indicate whether:

Access is allowed ( SQLITE_OK ),

The SQL statement should be aborted with an error ( SQLITE_DENY )

The column should be treated as a NULL value ( SQLITE_IGNORE )

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

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

The named DB-API parameter style is also supported.

Version number of the runtime SQLite library as a string .

Version number of the runtime SQLite library as a tuple of integers .

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

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

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

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

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

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:mod:`sqlite3` — DB-API 2.0 interface for SQLite databases

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 :mod:`!sqlite3` module was written by Gerhard Häring. It provides an SQL interface compliant with the DB-API 2.0 specification described by PEP 249, and requires SQLite 3.7.15 or newer.

This document includes four main sections:

teaches how to use the :mod:`!sqlite3` module. describes the classes and functions this module defines. details how to handle specific tasks. provides in-depth background on transaction control.

In this tutorial, you will create a database of Monty Python movies using basic :mod:`!sqlite3` functionality. It assumes a fundamental understanding of database concepts, including cursors and transactions.

First, we need to create a new database and open a database connection to allow :mod:`!sqlite3` to work with it. Call :func:`sqlite3.connect` to create a connection to the database :file:`tutorial.db` in the current working directory, implicitly creating it if it does not exist:

The returned :class:`Connection` object con represents the connection to the on-disk database.

In order to execute SQL statements and fetch results from SQL queries, we will need to use a database cursor. Call :meth:`con.cursor() <Connection.cursor>` to create the :class:`Cursor` :

Now that we’ve got a database connection and a cursor, we can create a database table movie with columns for title, release year, and review score. For simplicity, we can just use column names in the table declaration — thanks to the flexible typing feature of SQLite, specifying the data types is optional. Execute the CREATE TABLE statement by calling :meth:`cur.execute(. ) <Cursor.execute>` :

We can verify that the new table has been created by querying the sqlite_master table built-in to SQLite, which should now contain an entry for the movie table definition (see The Schema Table for details). Execute that query by calling :meth:`cur.execute(. ) <Cursor.execute>` , assign the result to res , and call :meth:`res.fetchone() <Cursor.fetchone>` to fetch the resulting row:

We can see that the table has been created, as the query returns a :class:`tuple` containing the table’s name. If we query sqlite_master for a non-existent table spam , :meth:`!res.fetchone()` will return None :

Now, add two rows of data supplied as SQL literals by executing an INSERT statement, once again by calling :meth:`cur.execute(. ) <Cursor.execute>` :

The INSERT statement implicitly opens a transaction, which needs to be committed before changes are saved in the database (see :ref:`sqlite3-controlling-transactions` for details). Call :meth:`con.commit() <Connection.commit>` on the connection object to commit the transaction:

We can verify that the data was inserted correctly by executing a SELECT query. Use the now-familiar :meth:`cur.execute(. ) <Cursor.execute>` to assign the result to res , and call :meth:`res.fetchall() <Cursor.fetchall>` to return all resulting rows:

The result is a :class:`list` of two :class:`!tuple` s, one per row, each containing that row’s score value.

Notice that ? placeholders are used to bind data to the query. Always use placeholders instead of :ref:`string formatting <tut-formatting>` to bind Python values to SQL statements, to avoid SQL injection attacks (see :ref:`sqlite3-placeholders` for more details).

We can verify that the new rows were inserted by executing a SELECT query, this time iterating over the results of the query:

Each row is a two-item :class:`tuple` of (year, title) , matching the columns selected in the query.

Finally, verify that the database has been written to disk by calling :meth:`con.close() <Connection.close>` to close the existing connection, opening a new one, creating a new cursor, then querying the database:

You’ve now created an SQLite database using the :mod:`!sqlite3` module, inserted data and retrieved values from it in multiple ways.

Each open SQLite database is represented by a Connection object, which is created using :func:`sqlite3.connect` . Their main purpose is creating :class:`Cursor` objects, and :ref:`sqlite3-controlling-transactions` .

An SQLite database connection has the following attributes and methods:

A Cursor object represents a database cursor which is used to execute SQL statements, and manage the context of a fetch operation. Cursors are created using :meth:`Connection.cursor` , or by using any of the :ref:`connection shortcut methods <sqlite3-connection-shortcuts>` .

Cursor objects are :term:`iterators <iterator>` , meaning that if you :meth:`

Cursor.execute` a SELECT query, you can simply iterate over the cursor to fetch the resulting rows:

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

A :class:`!Row` instance serves as a highly optimized :attr:`

Connection.row_factory` for :class:`Connection` objects. It supports iteration, equality testing, :func:`len` , and :term:`mapping` access by column name and index.

Two :class:`!Row` objects compare equal if they have identical column names and values.

A :class:`Blob` instance is a :term:`file-like object` that can read and write data in an SQLite :abbr:`BLOB (Binary Large OBject)` . Call :func:`len(blob) <len>` to get the size (number of bytes) of the blob. Use indices and :term:`slices <slice>` for direct access to the blob data.

Use the :class:`Blob` as a :term:`context manager` to ensure that the blob handle is closed after use.

The PrepareProtocol type’s single purpose is to act as a PEP 246 style adaption protocol for objects that can :ref:`adapt themselves <sqlite3-conform>` to :ref:`native SQLite types <sqlite3-types>` .

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

SQLite and Python types

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

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

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

The type system of the :mod:`!sqlite3` module is extensible in two ways: you can store additional Python types in an SQLite database via :ref:`object adapters <sqlite3-adapters>` , and you can let the :mod:`!sqlite3` module convert SQLite types to Python types via :ref:`converters <sqlite3-converters>` .

Default adapters and converters (deprecated)

The default adapters and converters are deprecated as of Python 3.12. Instead, use the :ref:`sqlite3-adapter-converter-recipes` and tailor them to your needs.

The deprecated default adapters and converters consist of:

• An adapter for :class:`datetime.date` objects to :class:`strings <str>` in ISO 8601 format.
• An adapter for :class:`datetime.datetime` objects to strings in ISO 8601 format.
• A converter for :ref:`declared <sqlite3-converters>` «date» types to :class:`datetime.date` objects.
• A converter for declared «timestamp» types to :class:`datetime.datetime` objects. Fractional parts will be truncated to 6 digits (microsecond precision).

The default «timestamp» converter ignores UTC offsets in the database and always returns a naive :class:`datetime.datetime` object. To preserve UTC offsets in timestamps, either leave converters disabled, or register an offset-aware converter with :func:`register_converter` .

The :mod:`!sqlite3` module can be invoked as a script, using the interpreter’s :option:`-m` switch, in order to provide a simple SQLite shell. The argument signature is as follows:

Type .quit or CTRL-D to exit the shell.

How to use placeholders to bind values in SQL queries

SQL operations usually need to use values from Python variables. However, beware of using Python’s string operations to assemble queries, as they are vulnerable to SQL injection attacks. For example, an attacker can simply close the single quote and inject OR TRUE to select all rows:

Instead, use the DB-API’s parameter substitution. To insert a variable into a query string, use a placeholder in the string, and substitute the actual values into the query by providing them as a :class:`tuple` of values to the second argument of the cursor’s :meth:`

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 :term:`sequence` whose length must match the number of placeholders, or a :exc:`ProgrammingError` is raised. For the named style, parameters must be an instance of a :class:`dict` (or a subclass), which must contain keys for all named parameters; any extra items are ignored. Here’s an example of both styles:

PEP 249 numeric placeholders are not supported. If used, they will be interpreted as named placeholders.

How to adapt custom Python types to SQLite values

SQLite supports only a limited set of data types natively. To store custom Python types in SQLite databases, adapt them to one of the :ref:`Python types SQLite natively understands <sqlite3-types>` .

There are two ways to adapt Python objects to SQLite types: letting your object adapt itself, or using an adapter callable. The latter will take precedence above the former. For a library that exports a custom type, it may make sense to enable that type to adapt itself. As an application developer, it may make more sense to take direct control by registering custom adapter functions.

How to write adaptable objects

Suppose we have a :class:`!Point` class that represents a pair of coordinates, x and y , in a Cartesian coordinate system. The coordinate pair will be stored as a text string in the database, using a semicolon to separate the coordinates. This can be implemented by adding a __conform__(self, protocol) method which returns the adapted value. The object passed to protocol will be of type :class:`PrepareProtocol` .

How to register adapter callables

The other possibility is to create a function that converts the Python object to an SQLite-compatible type. This function can then be registered using :func:`register_adapter` .

How to convert SQLite values to custom Python types

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

Let’s go back to the :class:`!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 :class:`!Point` object from it.

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

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

• Implicit: set detect_types to :const:`PARSE_DECLTYPES`
• Explicit: set detect_types to :const:`PARSE_COLNAMES`
• Both: set detect_types to sqlite3.PARSE_DECLTYPES | sqlite3.PARSE_COLNAMES . Column names take precedence over declared types.

The following example illustrates the implicit and explicit approaches:

Adapter and converter recipes

This section shows recipes for common adapters and converters.

How to use connection shortcut methods

Connection.executescript` methods of the :class:`Connection` class, your code can be written more concisely because you don’t have to create the (often superfluous) :class:`Cursor` objects explicitly. Instead, the :class:`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 :class:`Connection` object.

How to use the connection context manager

A :class:`Connection` object can be used as a context manager that automatically commits or rolls back open transactions when leaving the body of the context manager. If the body of the :keyword:`with` statement finishes without exceptions, the transaction is committed. If this commit fails, or if the body of the with statement raises an uncaught exception, the transaction is rolled back. If :attr:`

Connection.autocommit` is False , a new transaction is implicitly opened after committing or rolling back.

If there is no open transaction upon leaving the body of the with statement, or if :attr:`

Connection.autocommit` is True , the context manager does nothing.

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

How to work with SQLite URIs

Some useful URI tricks include:

• Open a database in read-only mode:

• Do not implicitly create a new database file if it does not already exist; will raise :exc:`

• Create a shared named in-memory database:

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

How to create and use row factories

By default, :mod:`!sqlite3` represents each row as a :class:`tuple` . If a :class:`!tuple` does not suit your needs, you can use the :class:`sqlite3.Row` class or a custom :attr:`

While :attr:`!row_factory` exists as an attribute both on the :class:`Cursor` and the :class:`Connection` , it is recommended to set :class:`Connection.row_factory` , so all cursors created from the connection will use the same row factory.

:class:`!Row` provides indexed and case-insensitive named access to columns, with minimal memory overhead and performance impact over a :class:`!tuple` . To use :class:`!Row` as a row factory, assign it to the :attr:`!row_factory` attribute:

Queries now return :class:`!Row` objects:

You can create a custom :attr:`

Cursor.row_factory` that returns each row as a :class:`dict` , with column names mapped to values:

Using it, queries now return a :class:`!dict` instead of a :class:`!tuple` :

The following row factory returns a :term:`named tuple` :

With some adjustments, the above recipe can be adapted to use a :class:`

dataclasses.dataclass` , or any other custom class, instead of a :class:`

:mod:`!sqlite3` offers multiple methods of controlling whether, when and how database transactions are opened and closed. :ref:`sqlite3-transaction-control-autocommit` is recommended, while :ref:`sqlite3-transaction-control-isolation-level` retains the pre-Python 3.12 behaviour.

Transaction control via the autocommit attribute

The recommended way of controlling transaction behaviour is through the :attr:`Connection.autocommit` attribute, which should preferably be set using the autocommit parameter of :func:`connect` .

It is suggested to set autocommit to False , which implies PEP 249-compliant transaction control. This means: