Release: 2.0.31 | Release Date: June 18, 2024

# SQLAlchemy 2.0 Documentation

# Engine Configuration

The `Engine` is the starting point for any SQLAlchemy application. It’s “home base” for the actual database and its DBAPI, delivered to the SQLAlchemy application through a connection pool and a `Dialect`, which describes how to talk to a specific kind of database/DBAPI combination.

The general structure can be illustrated as follows:

Where above, an `Engine` references both a `Dialect` and a `Pool`, which together interpret the DBAPI’s module functions as well as the behavior of the database.

Creating an engine is just a matter of issuing a single call, `create_engine()`:

    from sqlalchemy import create_engine

    engine = create_engine("postgresql+psycopg2://scott:tiger@localhost:5432/mydatabase")

The above engine creates a `Dialect` object tailored towards PostgreSQL, as well as a `Pool` object which will establish a DBAPI connection at `localhost:5432` when a connection request is first received. Note that the `Engine` and its underlying `Pool` do not establish the first actual DBAPI connection until the `Engine.connect()` or `Engine.begin()` methods are called. Either of these methods may also be invoked by other SQLAlchemy `Engine` dependent objects such as the ORM `Session` object when they first require database connectivity. In this way, `Engine` and `Pool` can be said to have a lazy initialization behavior.

The `Engine`, once created, can either be used directly to interact with the database, or can be passed to a `Session` object to work with the ORM. This section covers the details of configuring an `Engine`. The next section, Working with Engines and Connections, will detail the usage API of the `Engine` and similar, typically for non-ORM applications.

## Supported Databases

SQLAlchemy includes many `Dialect` implementations for various backends. Dialects for the most common databases are included with SQLAlchemy; a handful of others require an additional install of a separate dialect.

See the section Dialects for information on the various backends available.

## Database URLs

The `create_engine()` function produces an `Engine` object based on a URL. The format of the URL generally follows RFC-1738, with some exceptions, including that underscores, not dashes or periods, are accepted within the “scheme” portion. URLs typically include username, password, hostname, database name fields, as well as optional keyword arguments for additional configuration. In some cases a file path is accepted, and in others a “data source name” replaces the “host” and “database” portions. The typical form of a database URL is:

    dialect+driver://username:password@host:port/database

Dialect names include the identifying name of the SQLAlchemy dialect, a name such as `sqlite`, `mysql`, `postgresql`, `oracle`, or `mssql`. The drivername is the name of the DBAPI to be used to connect to the database using all lowercase letters. If not specified, a “default” DBAPI will be imported if available - this default is typically the most widely known driver available for that backend.

### Escaping Special Characters such as @ signs in Passwords

When constructing a fully formed URL string to pass to `create_engine()`, special characters such as those that may be used in the user and password need to be URL encoded to be parsed correctly.. This includes the @ sign.

Below is an example of a URL that includes the password `"kx@jj5/g"`, where the “at” sign and slash characters are represented as `%40` and `%2F`, respectively:

    postgresql+pg8000://dbuser:kx%40jj5%2Fg@pghost10/appdb

The encoding for the above password can be generated using urllib.parse:

    >>> import urllib.parse
    >>> urllib.parse.quote_plus("kx@jj5/g")
    'kx%40jj5%2Fg'

The URL may then be passed as a string to `create_engine()`:

    from sqlalchemy import create_engine

    engine = create_engine("postgresql+pg8000://dbuser:kx%40jj5%2Fg@pghost10/appdb")

As an alternative to escaping special characters in order to create a complete URL string, the object passed to `create_engine()` may instead be an instance of the `URL` object, which bypasses the parsing phase and can accommodate for unescaped strings directly. See the next section for an example.

Changed in version 1.4: Support for `@` signs in hostnames and database names has been fixed. As a side effect of this fix, `@` signs in passwords must be escaped.

### Creating URLs Programmatically

The value passed to `create_engine()` may be an instance of `URL`, instead of a plain string, which bypasses the need for string parsing to be used, and therefore does not need an escaped URL string to be provided.

The `URL` object is created using the `URL.create()` constructor method, passing all fields individually. Special characters such as those within passwords may be passed without any modification:

    from sqlalchemy import URL

    url_object = URL.create(
        "postgresql+pg8000",
        username="dbuser",
        password="kx@jj5/g",  # plain (unescaped) text
        host="pghost10",
        database="appdb",
    )

The constructed `URL` object may then be passed directly to `create_engine()` in place of a string argument:

    from sqlalchemy import create_engine

    engine = create_engine(url_object)

See also

`URL`

`URL.create()`

### Backend-Specific URLs

Examples for common connection styles follow below. For a full index of detailed information on all included dialects as well as links to third-party dialects, see Dialects.

#### PostgreSQL

The PostgreSQL dialect uses psycopg2 as the default DBAPI. Other PostgreSQL DBAPIs include pg8000 and asyncpg:

    # default
    engine = create_engine("postgresql://scott:tiger@localhost/mydatabase")

    # psycopg2
    engine = create_engine("postgresql+psycopg2://scott:tiger@localhost/mydatabase")

    # pg8000
    engine = create_engine("postgresql+pg8000://scott:tiger@localhost/mydatabase")

More notes on connecting to PostgreSQL at PostgreSQL.

#### MySQL

The MySQL dialect uses mysqlclient as the default DBAPI. There are other MySQL DBAPIs available, including PyMySQL:

    # default
    engine = create_engine("mysql://scott:tiger@localhost/foo")

    # mysqlclient (a maintained fork of MySQL-Python)
    engine = create_engine("mysql+mysqldb://scott:tiger@localhost/foo")

    # PyMySQL
    engine = create_engine("mysql+pymysql://scott:tiger@localhost/foo")

More notes on connecting to MySQL at MySQL and MariaDB.

#### Oracle

The Oracle dialect uses cx_oracle as the default DBAPI:

    engine = create_engine("oracle://scott:tiger@127.0.0.1:1521/sidname")

    engine = create_engine("oracle+cx_oracle://scott:tiger@tnsname")

More notes on connecting to Oracle at Oracle.

#### Microsoft SQL Server

The SQL Server dialect uses pyodbc as the default DBAPI. pymssql is also available:

    # pyodbc
    engine = create_engine("mssql+pyodbc://scott:tiger@mydsn")

    # pymssql
    engine = create_engine("mssql+pymssql://scott:tiger@hostname:port/dbname")

More notes on connecting to SQL Server at Microsoft SQL Server.

#### SQLite

SQLite connects to file-based databases, using the Python built-in module `sqlite3` by default.

As SQLite connects to local files, the URL format is slightly different. The “file” portion of the URL is the filename of the database. For a relative file path, this requires three slashes:

    # sqlite://<nohostname>/<path>
    # where <path> is relative:
    engine = create_engine("sqlite:///foo.db")

And for an absolute file path, the three slashes are followed by the absolute path:

    # Unix/Mac - 4 initial slashes in total
    engine = create_engine("sqlite:////absolute/path/to/foo.db")

    # Windows
    engine = create_engine("sqlite:///C:\\path\\to\\foo.db")

    # Windows alternative using raw string
    engine = create_engine(r"sqlite:///C:\path\to\foo.db")

To use a SQLite `:memory:` database, specify an empty URL:

    engine = create_engine("sqlite://")

More notes on connecting to SQLite at SQLite.

#### Others

See Dialects, the top-level page for all additional dialect documentation.

## Engine Creation API

Object Name | Description
--- | ---
create_engine(url, **kwargs) | Create a new `Engine` instance.
create_mock_engine(url, executor, **kw) | Create a “mock” engine used for echoing DDL.
create_pool_from_url(url, **kwargs) | Create a pool instance from the given url.
engine_from_config(configuration[, prefix], **kwargs) | Create a new Engine instance using a configuration dictionary.
make_url(name_or_url) | Given a string, produce a new URL instance.
URL | Represent the components of a URL used to connect to a database.

function sqlalchemy.create_engine(url: str | _url.URL, **kwargs: Any) → Engine

  Create a new `Engine` instance.

  The standard calling form is to send the URL as the first positional argument, usually a string that indicates database dialect and connection arguments:

      engine = create_engine("postgresql+psycopg2://scott:tiger@localhost/test")

  Note

  Please review Database URLs for general guidelines in composing URL strings. In particular, special characters, such as those often part of passwords, must be URL encoded to be properly parsed.

  Additional keyword arguments may then follow it which establish various options on the resulting `Engine` and its underlying `Dialect` and `Pool` constructs:

      engine = create_engine("mysql+mysqldb://scott:tiger@hostname/dbname",
                                  pool_recycle=3600, echo=True)

  The string form of the URL is `dialect[+driver]://user:password@host/dbname[?key=value..]`, where `dialect` is a database name such as `mysql`, `oracle`, `postgresql`, etc., and `driver` the name of a DBAPI, such as `psycopg2`, `pyodbc`, `cx_oracle`, etc. Alternatively, the URL can be an instance of `URL`.

  `**kwargs` takes a wide variety of options which are routed towards their appropriate components. Arguments may be specific to the `Engine`, the underlying `Dialect`, as well as the `Pool`. Specific dialects also accept keyword arguments that are unique to that dialect. Here, we describe the parameters that are common to most `create_engine()` usage.

  Once established, the newly resulting `Engine` will request a connection from the underlying `Pool` once `Engine.connect()` is called, or a method which depends on it such as `Engine.execute()` is invoked. The `Pool` in turn will establish the first actual DBAPI connection when this request is received. The `create_engine()` call itself does not establish any actual DBAPI connections directly.

  See also

  Engine Configuration

  Dialects

  Working with Engines and Connections

  Parameters:

    - connect_args – a dictionary of options which will be passed directly to the DBAPI’s `connect()` method as additional keyword arguments. See the example at Custom DBAPI connect() arguments / on-connect routines.

    - creator –

      a callable which returns a DBAPI connection. This creation function will be passed to the underlying connection pool and will be used to create all new database connections. Usage of this function causes connection parameters specified in the URL argument to be bypassed.

      This hook is not as flexible as the newer `DialectEvents.do_connect()` hook which allows complete control over how a connection is made to the database, given the full set of URL arguments and state beforehand.

      See also

      `DialectEvents.do_connect()` - event hook that allows full control over DBAPI connection mechanics.

      Custom DBAPI connect() arguments / on-connect routines

    - echo=False –

      if True, the Engine will log all statements as well as a `repr()` of their parameter lists to the default log handler, which defaults to `sys.stdout` for output. If set to the string `"debug"`, result rows will be printed to the standard output as well. The `echo` attribute of `Engine` can be modified at any time to turn logging on and off; direct control of logging is also available using the standard Python `logging` module.

      See also

      Configuring Logging - further detail on how to configure logging.

    - echo_pool=False –

      if True, the connection pool will log informational output such as when connections are invalidated as well as when connections are recycled to the default log handler, which defaults to `sys.stdout` for output. If set to the string `"debug"`, the logging will include pool checkouts and checkins. Direct control of logging is also available using the standard Python `logging` module.

      See also

      Configuring Logging - further detail on how to configure logging.

    - empty_in_strategy –

      No longer used; SQLAlchemy now uses “empty set” behavior for IN in all cases.

      Deprecated since version 1.4: The `create_engine.empty_in_strategy` keyword is deprecated, and no longer has any effect. All IN expressions are now rendered using the “expanding parameter” strategy which renders a set of boundexpressions, or an “empty set” SELECT, at statement executiontime.

    - enable_from_linting –

      defaults to True. Will emit a warning if a given SELECT statement is found to have un-linked FROM elements which would cause a cartesian product.

      New in version 1.4.

      See also

      Built-in FROM linting will warn for any potential cartesian products in a SELECT statement

    - execution_options – Dictionary execution options which will be applied to all connections. See `Connection.execution_options()`

    - future –

      Use the 2.0 style `Engine` and `Connection` API.

      As of SQLAlchemy 2.0, this parameter is present for backwards compatibility only and must remain at its default value of `True`.

      The `create_engine.future` parameter will be deprecated in a subsequent 2.x release and eventually removed.

      New in version 1.4.

      Changed in version 2.0: All `Engine` objects are “future” style engines and there is no longer a `future=False` mode of operation.

      See also

      SQLAlchemy 2.0 - Major Migration Guide

    - hide_parameters –

      Boolean, when set to True, SQL statement parameters will not be displayed in INFO logging nor will they be formatted into the string representation of `StatementError` objects.

      New in version 1.3.8.

      See also

      Configuring Logging - further detail on how to configure logging.

    - implicit_returning=True – Legacy parameter that may only be set to True. In SQLAlchemy 2.0, this parameter does nothing. In order to disable “implicit returning” for statements invoked by the ORM, configure this on a per-table basis using the `Table.implicit_returning` parameter.

    - insertmanyvalues_page_size –

      number of rows to format into an INSERT statement when the statement uses “insertmanyvalues” mode, which is a paged form of bulk insert that is used for many backends when using executemany execution typically in conjunction with RETURNING. Defaults to 1000, but may also be subject to dialect-specific limiting factors which may override this value on a per-statement basis.

      New in version 2.0.

      See also

      “Insert Many Values” Behavior for INSERT statements

      Controlling the Batch Size

      `Connection.execution_options.insertmanyvalues_page_size`

    - isolation_level –

      optional string name of an isolation level which will be set on all new connections unconditionally. Isolation levels are typically some subset of the string names `"SERIALIZABLE"`, `"REPEATABLE READ"`, `"READ COMMITTED"`, `"READ UNCOMMITTED"` and `"AUTOCOMMIT"` based on backend.

      The `create_engine.isolation_level` parameter is in contrast to the `Connection.execution_options.isolation_level` execution option, which may be set on an individual `Connection`, as well as the same parameter passed to `Engine.execution_options()`, where it may be used to create multiple engines with different isolation levels that share a common connection pool and dialect.

      Changed in version 2.0: The `create_engine.isolation_level` parameter has been generalized to work on all dialects which support the concept of isolation level, and is provided as a more succinct, up front configuration switch in contrast to the execution option which is more of an ad-hoc programmatic option.

      See also

      Setting Transaction Isolation Levels including DBAPI Autocommit

    - json_deserializer –

      for dialects that support the `JSON` datatype, this is a Python callable that will convert a JSON string to a Python object. By default, the Python `json.loads` function is used.

      Changed in version 1.3.7: The SQLite dialect renamed this from `_json_deserializer`.

    - json_serializer –

      for dialects that support the `JSON` datatype, this is a Python callable that will render a given object as JSON. By default, the Python `json.dumps` function is used.

      Changed in version 1.3.7: The SQLite dialect renamed this from `_json_serializer`.

    - label_length=None –

      optional integer value which limits the size of dynamically generated column labels to that many characters. If less than 6, labels are generated as “_(counter)”. If `None`, the value of `dialect.max_identifier_length`, which may be affected via the `create_engine.max_identifier_length` parameter, is used instead. The value of `create_engine.label_length` may not be larger than that of `create_engine.max_identfier_length`.

      See also

      `create_engine.max_identifier_length`

    - logging_name –

      String identifier which will be used within the “name” field of logging records generated within the “sqlalchemy.engine” logger. Defaults to a hexstring of the object’s id.

      See also

      Configuring Logging - further detail on how to configure logging.

      `Connection.execution_options.logging_token`

    - max_identifier_length –

      integer; override the max_identifier_length determined by the dialect. if `None` or zero, has no effect. This is the database’s configured maximum number of characters that may be used in a SQL identifier such as a table name, column name, or label name. All dialects determine this value automatically, however in the case of a new database version for which this value has changed but SQLAlchemy’s dialect has not been adjusted, the value may be passed here.

      New in version 1.3.9.

      See also

      `create_engine.label_length`

    - max_overflow=10 – the number of connections to allow in connection pool “overflow”, that is connections that can be opened above and beyond the pool_size setting, which defaults to five. this is only used with `QueuePool`.

    - module=None – reference to a Python module object (the module itself, not its string name). Specifies an alternate DBAPI module to be used by the engine’s dialect. Each sub-dialect references a specific DBAPI which will be imported before first connect. This parameter causes the import to be bypassed, and the given module to be used instead. Can be used for testing of DBAPIs as well as to inject “mock” DBAPI implementations into the `Engine`.

    - paramstyle=None – The paramstyle to use when rendering bound parameters. This style defaults to the one recommended by the DBAPI itself, which is retrieved from the `.paramstyle` attribute of the DBAPI. However, most DBAPIs accept more than one paramstyle, and in particular it may be desirable to change a “named” paramstyle into a “positional” one, or vice versa. When this attribute is passed, it should be one of the values `"qmark"`, `"numeric"`, `"named"`, `"format"` or `"pyformat"`, and should correspond to a parameter style known to be supported by the DBAPI in use.

    - pool=None – an already-constructed instance of `Pool`, such as a `QueuePool` instance. If non-None, this pool will be used directly as the underlying connection pool for the engine, bypassing whatever connection parameters are present in the URL argument. For information on constructing connection pools manually, see Connection Pooling.

    - poolclass=None – a `Pool` subclass, which will be used to create a connection pool instance using the connection parameters given in the URL. Note this differs from `pool` in that you don’t actually instantiate the pool in this case, you just indicate what type of pool to be used.

    - pool_logging_name –

      String identifier which will be used within the “name” field of logging records generated within the “sqlalchemy.pool” logger. Defaults to a hexstring of the object’s id.

      See also

      Configuring Logging - further detail on how to configure logging.

    - pool_pre_ping –

      boolean, if True will enable the connection pool “pre-ping” feature that tests connections for liveness upon each checkout.

      New in version 1.2.

      See also

      Disconnect Handling - Pessimistic

    - pool_size=5 – the number of connections to keep open inside the connection pool. This used with `QueuePool` as well as `SingletonThreadPool`. With `QueuePool`, a `pool_size` setting of 0 indicates no limit; to disable pooling, set `poolclass` to `NullPool` instead.

    - pool_recycle=-1 –

      this setting causes the pool to recycle connections after the given number of seconds has passed. It defaults to -1, or no timeout. For example, setting to 3600 means connections will be recycled after one hour. Note that MySQL in particular will disconnect automatically if no activity is detected on a connection for eight hours (although this is configurable with the MySQLDB connection itself and the server configuration as well).

      See also

      Setting Pool Recycle

    - pool_reset_on_return='rollback' –

      set the `Pool.reset_on_return` parameter of the underlying `Pool` object, which can be set to the values `"rollback"`, `"commit"`, or `None`.

      See also

      Reset On Return

    - pool_timeout=30 –

      number of seconds to wait before giving up on getting a connection from the pool. This is only used with `QueuePool`. This can be a float but is subject to the limitations of Python time functions which may not be reliable in the tens of milliseconds.

    - pool_use_lifo=False –

      use LIFO (last-in-first-out) when retrieving connections from `QueuePool` instead of FIFO (first-in-first-out). Using LIFO, a server-side timeout scheme can reduce the number of connections used during non- peak periods of use. When planning for server-side timeouts, ensure that a recycle or pre-ping strategy is in use to gracefully handle stale connections.

      > New in version 1.3.

      > See also

      > Using FIFO vs. LIFO

      > Dealing with Disconnects

    - plugins –

      string list of plugin names to load. See `CreateEnginePlugin` for background.

      New in version 1.2.3.

    - query_cache_size –

      size of the cache used to cache the SQL string form of queries. Set to zero to disable caching.

      The cache is pruned of its least recently used items when its size reaches N * 1.5. Defaults to 500, meaning the cache will always store at least 500 SQL statements when filled, and will grow up to 750 items at which point it is pruned back down to 500 by removing the 250 least recently used items.

      Caching is accomplished on a per-statement basis by generating a cache key that represents the statement’s structure, then generating string SQL for the current dialect only if that key is not present in the cache. All statements support caching, however some features such as an INSERT with a large set of parameters will intentionally bypass the cache. SQL logging will indicate statistics for each statement whether or not it were pull from the cache.

      Note

      some ORM functions related to unit-of-work persistence as well as some attribute loading strategies will make use of individual per-mapper caches outside of the main cache.

      See also

      SQL Compilation Caching

      New in version 1.4.

    - use_insertmanyvalues –

      True by default, use the “insertmanyvalues” execution style for INSERT..RETURNING statements by default.

      New in version 2.0.

      See also

      “Insert Many Values” Behavior for INSERT statements

function sqlalchemy.engine_from_config(configuration: Dict[str, Any], prefix: str = 'sqlalchemy.', **kwargs: Any) → Engine

  Create a new Engine instance using a configuration dictionary.

  The dictionary is typically produced from a config file.

  The keys of interest to `engine_from_config()` should be prefixed, e.g. `sqlalchemy.url`, `sqlalchemy.echo`, etc. The ‘prefix’ argument indicates the prefix to be searched for. Each matching key (after the prefix is stripped) is treated as though it were the corresponding keyword argument to a `create_engine()` call.

  The only required key is (assuming the default prefix) `sqlalchemy.url`, which provides the database URL.

  A select set of keyword arguments will be “coerced” to their expected type based on string values. The set of arguments is extensible per-dialect using the `engine_config_types` accessor.

  Parameters:

    - configuration – A dictionary (typically produced from a config file, but this is not a requirement). Items whose keys start with the value of ‘prefix’ will have that prefix stripped, and will then be passed to `create_engine()`.

    - prefix – Prefix to match and then strip from keys in ‘configuration’.

    - kwargs – Each keyword argument to `engine_from_config()` itself overrides the corresponding item taken from the ‘configuration’ dictionary. Keyword arguments should not be prefixed.

function sqlalchemy.create_mock_engine(url: str | URL, executor: Any, **kw: Any) → MockConnection

  Create a “mock” engine used for echoing DDL.

  This is a utility function used for debugging or storing the output of DDL sequences as generated by `MetaData.create_all()` and related methods.

  The function accepts a URL which is used only to determine the kind of dialect to be used, as well as an “executor” callable function which will receive a SQL expression object and parameters, which can then be echoed or otherwise printed. The executor’s return value is not handled, nor does the engine allow regular string statements to be invoked, and is therefore only useful for DDL that is sent to the database without receiving any results.

  E.g.:

      from sqlalchemy import create_mock_engine

      def dump(sql, *multiparams, **params):
          print(sql.compile(dialect=engine.dialect))

      engine = create_mock_engine('postgresql+psycopg2://', dump)
      metadata.create_all(engine, checkfirst=False)

  Parameters:

    - url – A string URL which typically needs to contain only the database backend name.

    - executor – a callable which receives the arguments `sql`, `*multiparams` and `**params`. The `sql` parameter is typically an instance of `ExecutableDDLElement`, which can then be compiled into a string using `ExecutableDDLElement.compile()`.

  New in version 1.4: - the `create_mock_engine()` function replaces the previous “mock” engine strategy used with `create_engine()`.

  See also

  How can I get the CREATE TABLE/ DROP TABLE output as a string?

function sqlalchemy.engine.make_url(name_or_url: str | URL ) → URL

  Given a string, produce a new URL instance.

  The format of the URL generally follows RFC-1738, with some exceptions, including that underscores, and not dashes or periods, are accepted within the “scheme” portion.

  If a `URL` object is passed, it is returned as is.

  See also

  Database URLs

function sqlalchemy.create_pool_from_url(url: str | URL, **kwargs: Any) → Pool

  Create a pool instance from the given url.

  If `poolclass` is not provided the pool class used is selected using the dialect specified in the URL.

  The arguments passed to `create_pool_from_url()` are identical to the pool argument passed to the `create_engine()` function.

  New in version 2.0.10.

class sqlalchemy.engine.URL

  Represent the components of a URL used to connect to a database.

  URLs are typically constructed from a fully formatted URL string, where the `make_url()` function is used internally by the `create_engine()` function in order to parse the URL string into its individual components, which are then used to construct a new `URL` object. When parsing from a formatted URL string, the parsing format generally follows RFC-1738, with some exceptions.

  A `URL` object may also be produced directly, either by using the `make_url()` function with a fully formed URL string, or by using the `URL.create()` constructor in order to construct a `URL` programmatically given individual fields. The resulting `URL` object may be passed directly to `create_engine()` in place of a string argument, which will bypass the usage of `make_url()` within the engine’s creation process.

  Changed in version 1.4: The `URL` object is now an immutable object. To create a URL, use the `make_url()` or `URL.create()` function / method. To modify a `URL`, use methods like `URL.set()` and `URL.update_query_dict()` to return a new `URL` object with modifications. See notes for this change at The URL object is now immutable.

  See also

  Database URLs

  `URL` contains the following attributes:

  - `URL.drivername`: database backend and driver name, such as `postgresql+psycopg2`

  - `URL.username`: username string

  - `URL.password`: password string

  - `URL.host`: string hostname

  - `URL.port`: integer port number

  - `URL.database`: string database name

  - `URL.query`: an immutable mapping representing the query string. contains strings for keys and either strings or tuples of strings for values.

  Members

  create(), database, difference_update_query(), drivername, get_backend_name(), get_dialect(), get_driver_name(), host, normalized_query, password, port, query, render_as_string(), set(), translate_connect_args(), update_query_dict(), update_query_pairs(), update_query_string(), username

  Class signature

  class `sqlalchemy.engine.URL` (`builtins.tuple`)

  classmethod `sqlalchemy.engine.URL.` create(drivername: str, username: str | None = None, password: str | None = None, host: str | None = None, port: int | None = None, database: str | None = None, query: Mapping[str, Sequence[str] | str] = {}) → URL

    Create a new `URL` object.

    See also

    Database URLs

    Parameters:

      - drivername – the name of the database backend. This name will correspond to a module in sqlalchemy/databases or a third party plug-in.

      - username – The user name.

      - password –

        database password. Is typically a string, but may also be an object that can be stringified with `str()`.

        Note

        The password string should not be URL encoded when passed as an argument to `URL.create()`; the string should contain the password characters exactly as they would be typed.

        Note

        A password-producing object will be stringified only once per `Engine` object. For dynamic password generation per connect, see Generating dynamic authentication tokens.

      - host – The name of the host.

      - port – The port number.

      - database – The database name.

      - query – A dictionary of string keys to string values to be passed to the dialect and/or the DBAPI upon connect. To specify non-string parameters to a Python DBAPI directly, use the `create_engine.connect_args` parameter to `create_engine()`. See also `URL.normalized_query` for a dictionary that is consistently string->list of string.

    Returns:

      new `URL` object.

    New in version 1.4: The `URL` object is now an immutable named tuple. In addition, the `query` dictionary is also immutable. To create a URL, use the `make_url()` or `URL.create()` function/ method. To modify a `URL`, use the `URL.set()` and `URL.update_query()` methods.

  attribute `sqlalchemy.engine.URL.` database: str | None

    database name

  method `sqlalchemy.engine.URL.` difference_update_query(names: Iterable[str]) → URL

    Remove the given names from the `URL.query` dictionary, returning the new `URL`.

    E.g.:

        url = url.difference_update_query(['foo', 'bar'])

    Equivalent to using `URL.set()` as follows:

        url = url.set(
            query={
                key: url.query[key]
                for key in set(url.query).difference(['foo', 'bar'])
            }
        )

    New in version 1.4.

    See also

    `URL.query`

    `URL.update_query_dict()`

    `URL.set()`

  attribute `sqlalchemy.engine.URL.` drivername: str

    database backend and driver name, such as `postgresql+psycopg2`

  method `sqlalchemy.engine.URL.` get_backend_name() → str

    Return the backend name.

    This is the name that corresponds to the database backend in use, and is the portion of the `URL.drivername` that is to the left of the plus sign.

  method `sqlalchemy.engine.URL.` get_dialect(_is_async: bool = False) → Type[ Dialect ]

    Return the SQLAlchemy `Dialect` class corresponding to this URL’s driver name.

  method `sqlalchemy.engine.URL.` get_driver_name() → str

    Return the backend name.

    This is the name that corresponds to the DBAPI driver in use, and is the portion of the `URL.drivername` that is to the right of the plus sign.

    If the `URL.drivername` does not include a plus sign, then the default `Dialect` for this `URL` is imported in order to get the driver name.

  attribute `sqlalchemy.engine.URL.` host: str | None

    hostname or IP number. May also be a data source name for some drivers.

  attribute `sqlalchemy.engine.URL.` normalized_query

    Return the `URL.query` dictionary with values normalized into sequences.

    As the `URL.query` dictionary may contain either string values or sequences of string values to differentiate between parameters that are specified multiple times in the query string, code that needs to handle multiple parameters generically will wish to use this attribute so that all parameters present are presented as sequences. Inspiration is from Python’s `urllib.parse.parse_qs` function. E.g.:

        >>> from sqlalchemy.engine import make_url
        >>> url = make_url("postgresql+psycopg2://user:pass@host/dbname?alt_host=host1&alt_host=host2&ssl_cipher=%2Fpath%2Fto%2Fcrt")
        >>> url.query
        immutabledict({'alt_host': ('host1', 'host2'), 'ssl_cipher': '/path/to/crt'})
        >>> url.normalized_query
        immutabledict({'alt_host': ('host1', 'host2'), 'ssl_cipher': ('/path/to/crt',)})

  attribute `sqlalchemy.engine.URL.` password: str | None

    password, which is normally a string but may also be any object that has a `__str__()` method.

  attribute `sqlalchemy.engine.URL.` port: int | None

    integer port number

  attribute `sqlalchemy.engine.URL.` query: immutabledict[str, Tuple[str, ...] | str]

    an immutable mapping representing the query string. contains strings for keys and either strings or tuples of strings for values, e.g.:

           >>> from sqlalchemy.engine import make_url
           >>> url = make_url("postgresql+psycopg2://user:pass@host/dbname?alt_host=host1&alt_host=host2&ssl_cipher=%2Fpath%2Fto%2Fcrt")
           >>> url.query
           immutabledict({'alt_host': ('host1', 'host2'), 'ssl_cipher': '/path/to/crt'})

        To create a mutable copy of this mapping, use the ``dict`` constructor::

           mutable_query_opts = dict(url.query)

    See also

    `URL.normalized_query` - normalizes all values into sequences for consistent processing

    Methods for altering the contents of `URL.query`:

    `URL.update_query_dict()`

    `URL.update_query_string()`

    `URL.update_query_pairs()`

    `URL.difference_update_query()`

  method `sqlalchemy.engine.URL.` render_as_string(hide_password: bool = True) → str

    Render this `URL` object as a string.

    This method is used when the `__str__()` or `__repr__()` methods are used. The method directly includes additional options.

    Parameters:

      hide_password – Defaults to True. The password is not shown in the string unless this is set to False.

  method `sqlalchemy.engine.URL.` set(drivername: str | None = None, username: str | None = None, password: str | None = None, host: str | None = None, port: int | None = None, database: str | None = None, query: Mapping[str, Sequence[str] | str] | None = None) → URL

    return a new `URL` object with modifications.

    Values are used if they are non-None. To set a value to `None` explicitly, use the `URL._replace()` method adapted from `namedtuple`.

    Parameters:

      - drivername – new drivername

      - username – new username

      - password – new password

      - host – new hostname

      - port – new port

      - query – new query parameters, passed a dict of string keys referring to string or sequence of string values. Fully replaces the previous list of arguments.

    Returns:

      new `URL` object.

    New in version 1.4.

    See also

    `URL.update_query_dict()`

  method `sqlalchemy.engine.URL.` translate_connect_args(names: List[str] | None = None, **kw: Any) → Dict[str, Any]

    Translate url attributes into a dictionary of connection arguments.

    Returns attributes of this url (host, database, username, password, port) as a plain dictionary. The attribute names are used as the keys by default. Unset or false attributes are omitted from the final dictionary.

    Parameters:

      - **kw – Optional, alternate key names for url attributes.

      - names – Deprecated. Same purpose as the keyword-based alternate names, but correlates the name to the original positionally.

  method `sqlalchemy.engine.URL.` update_query_dict(query_parameters: Mapping[str, str | List[str]], append: bool = False) → URL

    Return a new `URL` object with the `URL.query` parameter dictionary updated by the given dictionary.

    The dictionary typically contains string keys and string values. In order to represent a query parameter that is expressed multiple times, pass a sequence of string values.

    E.g.:

        >>> from sqlalchemy.engine import make_url
        >>> url = make_url("postgresql+psycopg2://user:pass@host/dbname")
        >>> url = url.update_query_dict({"alt_host": ["host1", "host2"], "ssl_cipher": "/path/to/crt"})
        >>> str(url)
        'postgresql+psycopg2://user:pass@host/dbname?alt_host=host1&alt_host=host2&ssl_cipher=%2Fpath%2Fto%2Fcrt'

    Parameters:

      - query_parameters – A dictionary with string keys and values that are either strings, or sequences of strings.

      - append – if True, parameters in the existing query string will not be removed; new parameters will be in addition to those present. If left at its default of False, keys present in the given query parameters will replace those of the existing query string.

    New in version 1.4.

    See also

    `URL.query`

    `URL.update_query_string()`

    `URL.update_query_pairs()`

    `URL.difference_update_query()`

    `URL.set()`

  method `sqlalchemy.engine.URL.` update_query_pairs(key_value_pairs: Iterable[Tuple[str, str | List[str]]], append: bool = False) → URL

    Return a new `URL` object with the `URL.query` parameter dictionary updated by the given sequence of key/value pairs

    E.g.:

        >>> from sqlalchemy.engine import make_url
        >>> url = make_url("postgresql+psycopg2://user:pass@host/dbname")
        >>> url = url.update_query_pairs([("alt_host", "host1"), ("alt_host", "host2"), ("ssl_cipher", "/path/to/crt")])
        >>> str(url)
        'postgresql+psycopg2://user:pass@host/dbname?alt_host=host1&alt_host=host2&ssl_cipher=%2Fpath%2Fto%2Fcrt'

    Parameters:

      - key_value_pairs – A sequence of tuples containing two strings each.

      - append – if True, parameters in the existing query string will not be removed; new parameters will be in addition to those present. If left at its default of False, keys present in the given query parameters will replace those of the existing query string.

    New in version 1.4.

    See also

    `URL.query`

    `URL.difference_update_query()`

    `URL.set()`

  method `sqlalchemy.engine.URL.` update_query_string(query_string: str, append: bool = False) → URL

    Return a new `URL` object with the `URL.query` parameter dictionary updated by the given query string.

    E.g.:

        >>> from sqlalchemy.engine import make_url
        >>> url = make_url("postgresql+psycopg2://user:pass@host/dbname")
        >>> url = url.update_query_string("alt_host=host1&alt_host=host2&ssl_cipher=%2Fpath%2Fto%2Fcrt")
        >>> str(url)
        'postgresql+psycopg2://user:pass@host/dbname?alt_host=host1&alt_host=host2&ssl_cipher=%2Fpath%2Fto%2Fcrt'

    Parameters:

      - query_string – a URL escaped query string, not including the question mark.

      - append – if True, parameters in the existing query string will not be removed; new parameters will be in addition to those present. If left at its default of False, keys present in the given query parameters will replace those of the existing query string.

    New in version 1.4.

    See also

    `URL.query`

    `URL.update_query_dict()`

  attribute `sqlalchemy.engine.URL.` username: str | None

    username string

## Pooling

The `Engine` will ask the connection pool for a connection when the `connect()` or `execute()` methods are called. The default connection pool, `QueuePool`, will open connections to the database on an as-needed basis. As concurrent statements are executed, `QueuePool` will grow its pool of connections to a default size of five, and will allow a default “overflow” of ten. Since the `Engine` is essentially “home base” for the connection pool, it follows that you should keep a single `Engine` per database established within an application, rather than creating a new one for each connection.

Note

`QueuePool` is not used by default for SQLite engines. See SQLite for details on SQLite connection pool usage.

For more information on connection pooling, see Connection Pooling.

## Custom DBAPI connect() arguments / on-connect routines

For cases where special connection methods are needed, in the vast majority of cases, it is most appropriate to use one of several hooks at the `create_engine()` level in order to customize this process. These are described in the following sub-sections.

### Special Keyword Arguments Passed to dbapi.connect()

All Python DBAPIs accept additional arguments beyond the basics of connecting. Common parameters include those to specify character set encodings and timeout values; more complex data includes special DBAPI constants and objects and SSL sub-parameters. There are two rudimentary means of passing these arguments without complexity.

#### Add Parameters to the URL Query string

Simple string values, as well as some numeric values and boolean flags, may be often specified in the query string of the URL directly. A common example of this is DBAPIs that accept an argument `encoding` for character encodings, such as most MySQL DBAPIs:

    engine = create_engine("mysql+pymysql://user:pass@host/test?charset=utf8mb4")

The advantage of using the query string is that additional DBAPI options may be specified in configuration files in a manner that’s portable to the DBAPI specified in the URL. The specific parameters passed through at this level vary by SQLAlchemy dialect. Some dialects pass all arguments through as strings, while others will parse for specific datatypes and move parameters to different places, such as into driver-level DSNs and connect strings. As per-dialect behavior in this area currently varies, the dialect documentation should be consulted for the specific dialect in use to see if particular parameters are supported at this level.

Tip

A general technique to display the exact arguments passed to the DBAPI for a given URL may be performed using the `Dialect.create_connect_args()` method directly as follows:

    >>> from sqlalchemy import create_engine
    >>> engine = create_engine(
    ...     "mysql+pymysql://some_user:some_pass@some_host/test?charset=utf8mb4"
    ... )
    >>> args, kwargs = engine.dialect.create_connect_args(engine.url)
    >>> args, kwargs
    ([], {'host': 'some_host', 'database': 'test', 'user': 'some_user', 'password': 'some_pass', 'charset': 'utf8mb4', 'client_flag': 2})

The above `args, kwargs` pair is normally passed to the DBAPI as `dbapi.connect(*args, **kwargs)`.

#### Use the connect_args dictionary parameter

A more general system of passing any parameter to the `dbapi.connect()` function that is guaranteed to pass all parameters at all times is the `create_engine.connect_args` dictionary parameter. This may be used for parameters that are otherwise not handled by the dialect when added to the query string, as well as when special sub-structures or objects must be passed to the DBAPI. Sometimes it’s just that a particular flag must be sent as the `True` symbol and the SQLAlchemy dialect is not aware of this keyword argument to coerce it from its string form as presented in the URL. Below illustrates the use of a psycopg2 “connection factory” that replaces the underlying implementation the connection:

    engine = create_engine(
        "postgresql+psycopg2://user:pass@hostname/dbname",
        connect_args={"connection_factory": MyConnectionFactory},
    )

Another example is the pyodbc “timeout” parameter:

    engine = create_engine(
        "mssql+pyodbc://user:pass@sqlsrvr?driver=ODBC+Driver+13+for+SQL+Server",
        connect_args={"timeout": 30},
    )

The above example also illustrates that both URL “query string” parameters as well as `create_engine.connect_args` may be used at the same time; in the case of pyodbc, the “driver” keyword has special meaning within the URL.

### Controlling how parameters are passed to the DBAPI connect() function

Beyond manipulating the parameters passed to `connect()`, we can further customize how the DBAPI `connect()` function itself is called using the `DialectEvents.do_connect()` event hook. This hook is passed the full `*args, **kwargs` that the dialect would send to `connect()`. These collections can then be modified in place to alter how they are used:

    from sqlalchemy import event

    engine = create_engine("postgresql+psycopg2://user:pass@hostname/dbname")

    @event.listens_for(engine, "do_connect")
    def receive_do_connect(dialect, conn_rec, cargs, cparams):
        cparams["connection_factory"] = MyConnectionFactory

#### Generating dynamic authentication tokens

`DialectEvents.do_connect()` is also an ideal way to dynamically insert an authentication token that might change over the lifespan of an `Engine`. For example, if the token gets generated by `get_authentication_token()` and passed to the DBAPI in a `token` parameter, this could be implemented as:

    from sqlalchemy import event

    engine = create_engine("postgresql+psycopg2://user@hostname/dbname")

    @event.listens_for(engine, "do_connect")
    def provide_token(dialect, conn_rec, cargs, cparams):
        cparams["token"] = get_authentication_token()

See also

Connecting to databases with access tokens - a more concrete example involving SQL Server

### Modifying the DBAPI connection after connect, or running commands after connect

For a DBAPI connection that SQLAlchemy creates without issue, but where we would like to modify the completed connection before it’s actually used, such as for setting special flags or running certain commands, the `PoolEvents.connect()` event hook is the most appropriate hook. This hook is called for every new connection created, before it is used by SQLAlchemy:

    from sqlalchemy import event

    engine = create_engine("postgresql+psycopg2://user:pass@hostname/dbname")

    @event.listens_for(engine, "connect")
    def connect(dbapi_connection, connection_record):
        cursor_obj = dbapi_connection.cursor()
        cursor_obj.execute("SET some session variables")
        cursor_obj.close()

### Fully Replacing the DBAPI `connect()` function

Finally, the `DialectEvents.do_connect()` event hook can also allow us to take over the connection process entirely by establishing the connection and returning it:

    from sqlalchemy import event

    engine = create_engine("postgresql+psycopg2://user:pass@hostname/dbname")

    @event.listens_for(engine, "do_connect")
    def receive_do_connect(dialect, conn_rec, cargs, cparams):
        # return the new DBAPI connection with whatever we'd like to
        # do
        return psycopg2.connect(*cargs, **cparams)

The `DialectEvents.do_connect()` hook supersedes the previous `create_engine.creator` hook, which remains available. `DialectEvents.do_connect()` has the distinct advantage that the complete arguments parsed from the URL are also passed to the user-defined function which is not the case with `create_engine.creator`.

## Configuring Logging

Python’s standard logging module is used to implement informational and debug log output with SQLAlchemy. This allows SQLAlchemy’s logging to integrate in a standard way with other applications and libraries. There are also two parameters `create_engine.echo` and `create_engine.echo_pool` present on `create_engine()` which allow immediate logging to `sys.stdout` for the purposes of local development; these parameters ultimately interact with the regular Python loggers described below.

This section assumes familiarity with the above linked logging module. All logging performed by SQLAlchemy exists underneath the `sqlalchemy` namespace, as used by `logging.getLogger('sqlalchemy')`. When logging has been configured (i.e. such as via `logging.basicConfig()`), the general namespace of SA loggers that can be turned on is as follows:

- `sqlalchemy.engine` - controls SQL echoing. Set to `logging.INFO` for SQL query output, `logging.DEBUG` for query + result set output. These settings are equivalent to `echo=True` and `echo="debug"` on `create_engine.echo`, respectively.

- `sqlalchemy.pool` - controls connection pool logging. Set to `logging.INFO` to log connection invalidation and recycle events; set to `logging.DEBUG` to additionally log all pool checkins and checkouts. These settings are equivalent to `pool_echo=True` and `pool_echo="debug"` on `create_engine.echo_pool`, respectively.

- `sqlalchemy.dialects` - controls custom logging for SQL dialects, to the extent that logging is used within specific dialects, which is generally minimal.

- `sqlalchemy.orm` - controls logging of various ORM functions to the extent that logging is used within the ORM, which is generally minimal. Set to `logging.INFO` to log some top-level information on mapper configurations.

For example, to log SQL queries using Python logging instead of the `echo=True` flag:

    import logging

    logging.basicConfig()
    logging.getLogger("sqlalchemy.engine").setLevel(logging.INFO)

By default, the log level is set to `logging.WARN` within the entire `sqlalchemy` namespace so that no log operations occur, even within an application that has logging enabled otherwise.

Note

The SQLAlchemy `Engine` conserves Python function call overhead by only emitting log statements when the current logging level is detected as `logging.INFO` or `logging.DEBUG`. It only checks this level when a new connection is procured from the connection pool. Therefore when changing the logging configuration for an already-running application, any `Connection` that’s currently active, or more commonly a `Session` object that’s active in a transaction, won’t log any SQL according to the new configuration until a new `Connection` is procured (in the case of `Session`, this is after the current transaction ends and a new one begins).

### More on the Echo Flag

As mentioned previously, the `create_engine.echo` and `create_engine.echo_pool` parameters are a shortcut to immediate logging to `sys.stdout`:

    >>> from sqlalchemy import create_engine, text
    >>> e = create_engine("sqlite://", echo=True, echo_pool="debug")
    >>> with e.connect() as conn:
    ...     print(conn.scalar(text("select 'hi'")))
    2020-10-24 12:54:57,701 DEBUG sqlalchemy.pool.impl.SingletonThreadPool Created new connection <sqlite3.Connection object at 0x7f287819ac60>
    2020-10-24 12:54:57,701 DEBUG sqlalchemy.pool.impl.SingletonThreadPool Connection <sqlite3.Connection object at 0x7f287819ac60> checked out from pool
    2020-10-24 12:54:57,702 INFO sqlalchemy.engine.Engine select 'hi'
    2020-10-24 12:54:57,702 INFO sqlalchemy.engine.Engine ()
    hi
    2020-10-24 12:54:57,703 DEBUG sqlalchemy.pool.impl.SingletonThreadPool Connection <sqlite3.Connection object at 0x7f287819ac60> being returned to pool
    2020-10-24 12:54:57,704 DEBUG sqlalchemy.pool.impl.SingletonThreadPool Connection <sqlite3.Connection object at 0x7f287819ac60> rollback-on-return

Use of these flags is roughly equivalent to:

    import logging

    logging.basicConfig()
    logging.getLogger("sqlalchemy.engine").setLevel(logging.INFO)
    logging.getLogger("sqlalchemy.pool").setLevel(logging.DEBUG)

It’s important to note that these two flags work independently of any existing logging configuration, and will make use of `logging.basicConfig()` unconditionally. This has the effect of being configured in addition to any existing logger configurations. Therefore, when configuring logging explicitly, ensure all echo flags are set to False at all times, to avoid getting duplicate log lines.

### Setting the Logging Name

The logger name of instance such as an `Engine` or `Pool` defaults to using a truncated hex identifier string. To set this to a specific name, use the `create_engine.logging_name` and `create_engine.pool_logging_name` with `sqlalchemy.create_engine()`; the name will be appended to the logging name `sqlalchemy.engine.Engine`:

    >>> import logging
    >>> from sqlalchemy import create_engine
    >>> from sqlalchemy import text
    >>> logging.basicConfig()
    >>> logging.getLogger("sqlalchemy.engine.Engine.myengine").setLevel(logging.INFO)
    >>> e = create_engine("sqlite://", logging_name="myengine")
    >>> with e.connect() as conn:
    ...     conn.execute(text("select 'hi'"))
    2020-10-24 12:47:04,291 INFO sqlalchemy.engine.Engine.myengine select 'hi'
    2020-10-24 12:47:04,292 INFO sqlalchemy.engine.Engine.myengine ()

Tip

The `create_engine.logging_name` and `create_engine.pool_logging_name` parameters may also be used in conjunction with `create_engine.echo` and `create_engine.echo_pool`. However, an unavoidable double logging condition will occur if other engines are created with echo flags set to True and no logging name. This is because a handler will be added automatically for `sqlalchemy.engine.Engine` which will log messages both for the name-less engine as well as engines with logging names. For example:

    from sqlalchemy import create_engine, text

    e1 = create_engine("sqlite://", echo=True, logging_name="myname")
    with e1.begin() as conn:
        conn.execute(text("SELECT 1"))

    e2 = create_engine("sqlite://", echo=True)
    with e2.begin() as conn:
        conn.execute(text("SELECT 2"))

    with e1.begin() as conn:
        conn.execute(text("SELECT 3"))

The above scenario will double log `SELECT 3`. To resolve, ensure all engines have a `logging_name` set, or use explicit logger / handler setup without using `create_engine.echo` and `create_engine.echo_pool`.

### Setting Per-Connection / Sub-Engine Tokens

New in version 1.4.0b2.

While the logging name is appropriate to establish on an `Engine` object that is long lived, it’s not flexible enough to accommodate for an arbitrarily large list of names, for the case of tracking individual connections and/or transactions in log messages.

For this use case, the log message itself generated by the `Connection` and `Result` objects may be augmented with additional tokens such as transaction or request identifiers. The `Connection.execution_options.logging_token` parameter accepts a string argument that may be used to establish per-connection tracking tokens:

    >>> from sqlalchemy import create_engine
    >>> e = create_engine("sqlite://", echo="debug")
    >>> with e.connect().execution_options(logging_token="track1") as conn:
    ...     conn.execute(text("select 1")).all()
    2021-02-03 11:48:45,754 INFO sqlalchemy.engine.Engine [track1] select 1
    2021-02-03 11:48:45,754 INFO sqlalchemy.engine.Engine [track1] [raw sql] ()
    2021-02-03 11:48:45,754 DEBUG sqlalchemy.engine.Engine [track1] Col ('1',)
    2021-02-03 11:48:45,755 DEBUG sqlalchemy.engine.Engine [track1] Row (1,)

The `Connection.execution_options.logging_token` parameter may also be established on engines or sub-engines via `create_engine.execution_options` or `Engine.execution_options()`. This may be useful to apply different logging tokens to different components of an application without creating new engines:

    >>> from sqlalchemy import create_engine
    >>> e = create_engine("sqlite://", echo="debug")
    >>> e1 = e.execution_options(logging_token="track1")
    >>> e2 = e.execution_options(logging_token="track2")
    >>> with e1.connect() as conn:
    ...     conn.execute(text("select 1")).all()
    2021-02-03 11:51:08,960 INFO sqlalchemy.engine.Engine [track1] select 1
    2021-02-03 11:51:08,960 INFO sqlalchemy.engine.Engine [track1] [raw sql] ()
    2021-02-03 11:51:08,960 DEBUG sqlalchemy.engine.Engine [track1] Col ('1',)
    2021-02-03 11:51:08,961 DEBUG sqlalchemy.engine.Engine [track1] Row (1,)

    >>> with e2.connect() as conn:
    ...     conn.execute(text("select 2")).all()
    2021-02-03 11:52:05,518 INFO sqlalchemy.engine.Engine [track2] Select 1
    2021-02-03 11:52:05,519 INFO sqlalchemy.engine.Engine [track2] [raw sql] ()
    2021-02-03 11:52:05,520 DEBUG sqlalchemy.engine.Engine [track2] Col ('1',)
    2021-02-03 11:52:05,520 DEBUG sqlalchemy.engine.Engine [track2] Row (1,)

### Hiding Parameters

The logging emitted by `Engine` also indicates an excerpt of the SQL parameters that are present for a particular statement. To prevent these parameters from being logged for privacy purposes, enable the `create_engine.hide_parameters` flag:

    >>> e = create_engine("sqlite://", echo=True, hide_parameters=True)
    >>> with e.connect() as conn:
    ...     conn.execute(text("select :some_private_name"), {"some_private_name": "pii"})
    2020-10-24 12:48:32,808 INFO sqlalchemy.engine.Engine select ?
    2020-10-24 12:48:32,808 INFO sqlalchemy.engine.Engine [SQL parameters hidden due to hide_parameters=True]