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.
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.
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 to be parsed correctly.. Below
is an example of a URL that includes the password "kx%jj5/g"
, where the
percent sign and slash characters are represented as %25
and %2F
,
respectively:
postgresql+pg8000://dbuser:kx%25jj5%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%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.
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.
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 and MariaDB.
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.
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 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.
Object Name | Description |
---|---|
|
Create a new |
|
Create a “mock” engine used for echoing DDL. |
|
Create a new Engine instance using a configuration dictionary. |
|
Given a string or unicode instance, produce a new URL instance. |
Represent the components of a URL used to connect to a database. |
sqlalchemy.
create_engine
(url, **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")
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://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.
case_sensitive¶ –
if False, result column names
will match in a case-insensitive fashion, that is,
row['SomeColumn']
.
Deprecated since version 1.4: The create_engine.case_sensitive
parameter is deprecated and will be removed in a future release. Applications should work with result column names in a case sensitive fashion.
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.
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.
Deprecated since version 1.3: The create_engine.convert_unicode
parameter
is deprecated and will be removed in a future release.
All modern DBAPIs now support Python Unicode directly and this
parameter is unnecessary.
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.
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.
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 DBAPIs own encoding facilities.
Note
The encoding
parameter deals only with in-Python
encoding issues that were prevalent with many DBAPIs under Python
2. Under Python 3 it is mostly unused. For DBAPIs that require
client encoding configurations, such as those of MySQL and Oracle,
please consult specific dialect documentation for details.
All modern DBAPIs that work in Python 3 necessarily feature direct
support for Python unicode strings. Under Python 2, this was not
always the case. For those scenarios where the DBAPI is detected as
not supporting a Python unicode
object under Python 2, 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, nearly always under Python 2 only, 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
Connection.execution_options()
future¶ –
Use the 2.0 style Engine
and
Connection
API.
New in version 1.4.
See also
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¶ – 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
PostgreSQL Transaction Isolation
Setting Transaction Isolation Levels / DBAPI AUTOCOMMIT - for the ORM
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
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.
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
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
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
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
0¶ – 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.
See also
New in version 1.4.
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.
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.
create_mock_engine
(url, executor, **kw)¶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://', dump)
metadata.create_all(engine, checkfirst=False)
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 DDLElement
, which can then be compiled into a
string using DDLElement.compile()
.
New in version 1.4: - the create_mock_engine()
function replaces
the previous “mock” engine strategy used with
create_engine()
.
sqlalchemy.engine.
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.
sqlalchemy.engine.
URL
(*arg, **kw)¶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.
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.
URL
contains the following attributes:
driver – database backend and driver name, such as
postgresql+psycopg2
username – username string
password – password, which is normally a string but may
also be any object that has a __str__()
method.
host – string hostname
port – integer port number
database – string database name
query – an immutable mapping representing the query string. contains strings for keys and either strings or tuples of strings for values.
Class signature
sqlalchemy.engine.URL.
drivername
str¶database backend and driver name, such as
postgresql+psycopg2
sqlalchemy.engine.URL.
username
str¶username string
sqlalchemy.engine.URL.
password
str¶password, which is normally a string but may also be any
object that has a __str__()
method.
sqlalchemy.engine.URL.
host
str¶string hostname
sqlalchemy.engine.URL.
port
int¶integer port number
sqlalchemy.engine.URL.
database
str¶string database name
sqlalchemy.engine.URL.
query
Mapping[str, Union[str, Sequence[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://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
:
sqlalchemy.engine.URL.
classmethod create
(drivername: str, username: Optional[str] = None, password: Optional[Union[str, object]] = None, host: Optional[str] = None, port: Optional[int] = None, database: Optional[str] = None, query: Mapping[str, Union[str, Sequence[str]]] = {}) → URL¶Create a new URL
object.
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. May be a string or an object that
can be stringified with str()
.
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.
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.
sqlalchemy.engine.URL.
difference_update_query
(names: Sequence[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.
sqlalchemy.engine.URL.
get_backend_name
()¶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.
sqlalchemy.engine.URL.
get_dialect
()¶Return the SQLAlchemy Dialect
class corresponding
to this URL’s driver name.
sqlalchemy.engine.URL.
get_driver_name
()¶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.
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://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',)})
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.
hide_password¶ – Defaults to True. The password is not shown in the string unless this is set to False.
sqlalchemy.engine.URL.
set
(drivername: Optional[str] = None, username: Optional[str] = None, password: Optional[Union[str, object]] = None, host: Optional[str] = None, port: Optional[int] = None, database: Optional[str] = None, query: Optional[Mapping[str, Union[str, Sequence[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
.
new URL
object.
New in version 1.4.
See also
sqlalchemy.engine.URL.
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.
sqlalchemy.engine.URL.
update_query_dict
(query_parameters: Mapping[str, Union[str, Sequence[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://user:pass@host/dbname")
>>> url = url.update_query_dict({"alt_host": ["host1", "host2"], "ssl_cipher": "/path/to/crt"})
>>> str(url)
'postgresql://user:pass@host/dbname?alt_host=host1&alt_host=host2&ssl_cipher=%2Fpath%2Fto%2Fcrt'
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.
sqlalchemy.engine.URL.
update_query_pairs
(key_value_pairs: Sequence[Tuple[str, 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://user:pass@host/dbname")
>>> url = url.update_query_pairs([("alt_host", "host1"), ("alt_host", "host2"), ("ssl_cipher", "/path/to/crt")])
>>> str(url)
'postgresql://user:pass@host/dbname?alt_host=host1&alt_host=host2&ssl_cipher=%2Fpath%2Fto%2Fcrt'
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.
sqlalchemy.engine.URL.
update_query_string
(query_string: str, append: bool = False) → sqlalchemy.engine.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://user:pass@host/dbname")
>>> url = url.update_query_string("alt_host=host1&alt_host=host2&ssl_cipher=%2Fpath%2Fto%2Fcrt")
>>> str(url)
'postgresql://user:pass@host/dbname?alt_host=host1&alt_host=host2&ssl_cipher=%2Fpath%2Fto%2Fcrt'
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.
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.
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.
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.
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)
.
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://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.
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://user:pass@hostname/dbname")
@event.listens_for(engine, "do_connect")
def receive_do_connect(dialect, conn_rec, cargs, cparams):
cparams['connection_factory'] = MyConnectionFactory
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://user:pass@hostname/dbname"
)
@event.listens_for(engine, "connect")
def connect(dbapi_connection, connection_record):
cursor = dbapi_connection.cursor()
cursor.execute("SET some session variables")
cursor.close()
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://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
.
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).
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.
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 ()
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,)
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]
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