Release: 1.2.19 | Release Date: April 15, 2019

# SQLAlchemy 1.2 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://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. These URLs follow RFC-1738, and usually can include username, password, hostname, database name 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.

As the URL is like any other URL, special characters such as those that may be used in the password need to be URL encoded. Below is an example of a URL that includes the password `"kx%jj5/g"`:

    postgresql+pg8000://dbuser:kx%25jj5%2Fg@pghost10/appdb

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

    >>> import urllib.parse
    >>> urllib.parse.quote_plus("kx%jj5/g")
    'kx%25jj5%2Fg'

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. pg8000 is also available as a pure-Python substitute:

    # 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 mysql-python as the default DBAPI. There are many MySQL DBAPIs available, including MySQL-connector-python and OurSQL:

    # 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.

### 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

`sqlalchemy.``create_engine`(*args, **kwargs)

  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://scott:tiger@localhost/test")

  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://scott:tiger@hostname/dbname",
                                  encoding='latin1', 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

    - case_sensitive=True – if False, result column names will match in a case-insensitive fashion, that is, `row['SomeColumn']`.

    - 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.

    - convert_unicode=False –

      if set to True, causes all `String` datatypes to act as though the `String.convert_unicode` flag has been set to `True`, regardless of a setting of `False` on an individual `String` type. This has the effect of causing all `String` -based columns to accommodate Python Unicode objects directly as though the datatype were the `Unicode` type.

      Note

      SQLAlchemy’s unicode-conversion flags and features only apply to Python 2; in Python 3, all string objects are Unicode objects. For this reason, as well as the fact that virtually all modern DBAPIs now support Unicode natively even under Python 2, the `Engine.convert_unicode` flag is inherently a legacy feature.

      Note

      This flag does not imply that SQLAlchemy’s unicode-conversion services will be used, as all modern DBAPIs already handle unicode natively; in most cases it only indicates that the `String` datatype will return Python unicode objects, rather than plain strings. The `String` datatype itself has additional options to force the usage of SQLAlchemy’s unicode converters.

      Note

      This flag does not impact “raw” SQL statements that have no typing information set up; that is, if the `String` datatype is not used, no unicode behavior is implied.

      See also

      `String.convert_unicode` - the flag local to the `String` datatype has additional options which can force unicode handling on a per-type basis.

    - 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.

    - 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 –

      The SQL compilation strategy to use when rendering an IN or NOT IN expression for `ColumnOperators.in_()` where the right-hand side is an empty set. This is a string value that may be one of `static`, `dynamic`, or `dynamic_warn`. The `static` strategy is the default, and an IN comparison to an empty set will generate a simple false expression “1 != 1”. The `dynamic` strategy behaves like that of SQLAlchemy 1.1 and earlier, emitting a false expression of the form “expr != expr”, which has the effect of evaluting to NULL in the case of a null expression. `dynamic_warn` is the same as `dynamic`, however also emits a warning when an empty set is encountered; this because the “dynamic” comparison is typically poorly performing on most databases.

      New in version 1.2: Added the `empty_in_strategy` setting and additionally defaulted the behavior for empty-set IN comparisons to a static boolean expression.

    - encoding –

      Defaults to `utf-8`. This is the string encoding used by SQLAlchemy for string encode/decode operations which occur within SQLAlchemy, outside of the DBAPI. Most modern DBAPIs feature some degree of direct support for Python `unicode` objects, what you see in Python 2 as a string of the form `u'some string'`. For those scenarios where the DBAPI is detected as not supporting a Python `unicode` object, this encoding is used to determine the source/destination encoding. It is not used for those cases where the DBAPI handles unicode directly.

      To properly configure a system to accommodate Python `unicode` objects, the DBAPI should be configured to handle unicode to the greatest degree as is appropriate - see the notes on unicode pertaining to the specific target database in use at Dialects.

      Areas where string encoding may need to be accommodated outside of the DBAPI include zero or more of:

      - the values passed to bound parameters, corresponding to the `Unicode` type or the `String` type when `convert_unicode` is `True`;

      - the values returned in result set columns corresponding to the `Unicode` type or the `String` type when `convert_unicode` is `True`;

      - the string SQL statement passed to the DBAPI’s `cursor.execute()` method;

      - the string names of the keys in the bound parameter dictionary passed to the DBAPI’s `cursor.execute()` as well as `cursor.setinputsizes()` methods;

      - the string column names retrieved from the DBAPI’s `cursor.description` attribute.

      When using Python 3, the DBAPI is required to support all of the above values as Python `unicode` objects, which in Python 3 are just known as `str`. In Python 2, the DBAPI does not specify unicode behavior at all, so SQLAlchemy must make decisions for each of the above values on a per-DBAPI basis - implementations are completely inconsistent in their behavior.

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

    - implicit_returning=True – When `True`, a RETURNING- compatible construct, if available, will be used to fetch newly generated primary key values when a single row INSERT statement is emitted with no existing returning() clause. This applies to those backends which support RETURNING or a compatible construct, including PostgreSQL, Firebird, Oracle, Microsoft SQL Server. Set this to `False` to disable the automatic usage of RETURNING.

    - isolation_level –

      this string parameter is interpreted by various dialects in order to affect the transaction isolation level of the database connection. The parameter essentially accepts some subset of these string arguments: `"SERIALIZABLE"`, `"REPEATABLE_READ"`, `"READ_COMMITTED"`, `"READ_UNCOMMITTED"` and `"AUTOCOMMIT"`. Behavior here varies per backend, and individual dialects should be consulted directly.

      Note that the isolation level can also be set on a per-`Connection` basis as well, using the `Connection.execution_options.isolation_level` feature.

      See also

      `Connection.default_isolation_level` - view default level

      `Connection.execution_options.isolation_level` - set per `Connection` isolation level

      SQLite Transaction Isolation

      PostgreSQL Transaction Isolation

      MySQL Transaction Isolation

      Setting Transaction Isolation Levels - for the ORM

    - 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` is used instead.

    - 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.

    - 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.

    - 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

      `Pool.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`.

    - plugins –

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

      New in version 1.2.3.

    - strategy='plain' –

      selects alternate engine implementations. Currently available are:

      - the `threadlocal` strategy, which is described in Using the Threadlocal Execution Strategy;

      - the `mock` strategy, which dispatches all statement execution to a function passed as the argument `executor`. See example in the FAQ.

    - executor=None – a function taking arguments `(sql, *multiparams, **params)`, to which the `mock` strategy will dispatch all statement execution. Used only by `strategy='mock'`.

`sqlalchemy.``engine_from_config`(configuration, prefix='sqlalchemy.', **kwargs)

  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.

`sqlalchemy.engine.url.``make_url`(name_or_url)

  Given a string or unicode instance, produce a new URL instance.

  The given string is parsed according to the RFC 1738 spec. If an existing URL object is passed, just returns the object.

class `sqlalchemy.engine.url.``URL`(drivername, username=None, password=None, host=None, port=None, database=None, query=None)

  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 is an RFC-1738-style string.

  All initialization parameters are available as public attributes.

  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.

    - host – The name of the host.

    - port – The port number.

    - database – The database name.

    - query – A dictionary of options to be passed to the dialect and/or the DBAPI upon connect.

  `get_dialect`()

    Return the SQLAlchemy database dialect class corresponding to this URL’s driver name.

  `translate_connect_args`(names=[], **kw)

    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.

## 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

Custom arguments used when issuing the `connect()` call to the underlying DBAPI may be issued in three distinct ways. String-based arguments can be passed directly from the URL string as query arguments:

    db = create_engine('postgresql://scott:tiger@localhost/test?argument1=foo&argument2=bar')

If SQLAlchemy’s database connector is aware of a particular query argument, it may convert its type from string to its proper type.

`create_engine()` also takes an argument `connect_args` which is an additional dictionary that will be passed to `connect()`. This can be used when arguments of a type other than string are required, and SQLAlchemy’s database connector has no type conversion logic present for that parameter:

    db = create_engine('postgresql://scott:tiger@localhost/test', connect_args = {'argument1':17, 'argument2':'bar'})

The most customizable connection method of all is to pass a `creator` argument, which specifies a callable that returns a DBAPI connection:

    def connect():
        return psycopg.connect(user='scott', host='localhost')

    db = create_engine('postgresql://', creator=connect)

## 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.

The `echo` flags present as keyword arguments to `create_engine()` and others as well as the `echo` property on `Engine`, when set to `True`, will first attempt to ensure that logging is enabled. Unfortunately, the `logging` module provides no way of determining if output has already been configured (note we are referring to if a logging configuration has been set up, not just that the logging level is set). For this reason, any `echo=True` flags will result in a call to `logging.basicConfig()` using sys.stdout as the destination. It also sets up a default format using the level name, timestamp, and logger name. Note that this configuration has the affect of being configured in addition to any existing logger configurations. Therefore, when using Python logging, ensure all echo flags are set to False at all times, to avoid getting duplicate log lines.

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 “logging_name” and “pool_logging_name” keyword arguments with `sqlalchemy.create_engine()`.

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).