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:

../_images/sqla_engine_arch.png

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() method is called, or an operation which is dependent on this method such as Engine.execute() is invoked. 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

As the URL is like any other URL, 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'

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.

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.

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: Union[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.

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.

  • 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.

  • 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.

  • 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.

  • 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.

  • listeners – A list of one or more PoolListener objects which will receive connection pool events.

  • 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.

  • 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.

  • 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).

  • 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.

  • 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.

  • 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.

    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.

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: 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().

function sqlalchemy.engine.make_url(name_or_url: Union[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

class sqlalchemy.engine.URL

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

This object is suitable to be passed directly to a create_engine() call. The fields of the URL are parsed from a string by the make_url() function. The string format of the URL generally follows RFC-1738, with some exceptions.

To create a new URL object, use the make_url() function. To construct a URL programmatically, use the URL.create() constructor.

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:

Class signature

class sqlalchemy.engine.URL (builtins.tuple)

classmethod sqlalchemy.engine.URL.create(drivername: str, username: Optional[str] = None, password: Optional[str] = None, host: Optional[str] = None, port: Optional[int] = None, database: Optional[str] = None, query: Mapping[str, Union[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

    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: Optional[str]

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.

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: Optional[str]

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: Optional[str]

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

attribute sqlalchemy.engine.URL.port: Optional[int]

integer port number

attribute sqlalchemy.engine.URL.query: immutabledict[str, Union[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: Optional[str] = None, username: Optional[str] = None, password: Optional[str] = None, host: Optional[str] = None, port: Optional[int] = None, database: Optional[str] = None, query: Optional[Mapping[str, Union[Sequence[str], str]]] = 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.

method sqlalchemy.engine.URL.translate_connect_args(names: Optional[List[str]] = 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, Union[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.

method sqlalchemy.engine.URL.update_query_pairs(key_value_pairs: Iterable[Tuple[str, Union[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.

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.

attribute sqlalchemy.engine.URL.username: Optional[str]

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 extend 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():

>>> from sqlalchemy import create_engine
>>> from sqlalchemy import text
>>> e = create_engine("sqlite://", echo=True, 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 ()

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("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("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("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]