SQLALCHEMY UNIT TESTS
SQLAlchemy unit tests by default run using Python's built-in sqlite3 module. If running on Python 2.4, pysqlite must be installed.
Unit tests are run using nose. Nose is available at:
SQLAlchemy implements a nose plugin that must be present when tests are run. This plugin is invoked when the test runner script provided with SQLAlchemy is used.
NOTE: - the nose plugin is no longer installed by setuptools as of version 0.7 ! Use "python setup.py test" or "./sqla_nose.py".
RUNNING TESTS VIA SETUP.PY
A plain vanilla run of all tests using sqlite can be run via setup.py:
$ python setup.py test
The -v flag also works here:
$ python setup.py test -v
RUNNING ALL TESTS
To run all tests:
If you're running the tests on Microsoft Windows, then there is an additional argument that must be passed to ./sqla_nose.py:
> ./sqla_nose.py --first-package-wins
This is required because nose's importer will normally evict a package from sys.modules if it sees a package with the same name in a different location. Setting this argument disables that behavior.
Assuming all tests pass, this is a very unexciting output. To make it more interesting:
$ ./sqla_nose.py -v
RUNNING INDIVIDUAL TESTS
Any directory of test modules can be run at once by specifying the directory path:
$ ./sqla_nose.py test/dialect
Any test module can be run directly by specifying its module name:
$ ./sqla_nose.py test.orm.test_mapper
To run a specific test within the module, specify it as module:ClassName.methodname:
$ ./sqla_nose.py test.orm.test_mapper:MapperTest.test_utils
COMMAND LINE OPTIONS
Help is available via --help:
$ ./sqla_nose.py --help
The --help screen is a combination of common nose options and options which the SQLAlchemy nose plugin adds. The most commonly SQLAlchemy-specific options used are '--db' and '--dburi'.
Tests will target an in-memory SQLite database by default. To test against another database, use the --dburi option with any standard SQLAlchemy URL:
Use an empty database and a database user with general DBA privileges. The test suite will be creating and dropping many tables and other DDL, and preexisting tables will interfere with the tests.
Several tests require alternate usernames or schemas to be present, which are used to test dotted-name access scenarios. On some databases such as Oracle or Sybase, these are usernames, and others such as Postgresql and MySQL they are schemas. The requirement applies to all backends except SQLite and Firebird. The names are:
test_schema test_schema_2 (only used on Postgresql)
Please refer to your vendor documentation for the proper syntax to create these namespaces - the database user must have permission to create and drop tables within these schemas. Its perfectly fine to run the test suite without these namespaces present, it only means that a handful of tests which expect them to be present will fail.
Additional steps specific to individual databases are as follows:
MYSQL: Default storage engine should be "MyISAM". Tests that require "InnoDB" as the engine will specify this explicitly. ORACLE: a user named "test_schema" is created. The primary database user needs to be able to create and drop tables, synonyms, and constraints within the "test_schema" user. For this to work fully, including that the user has the "REFERENCES" role in a remote schema for tables not yet defined (REFERENCES is per-table), it is required that the test the user be present in the "DBA" role: grant dba to scott; SYBASE: Similar to Oracle, "test_schema" is created as a user, and the primary test user needs to have the "sa_role". It's also recommended to turn on "trunc log on chkpt" and to use a separate transaction log device - Sybase basically seizes up when the transaction log is full otherwise. A full series of setup assuming sa/master: disk init name="translog", physname="/opt/sybase/data/translog.dat", size="10M" create database sqlalchemy on default log on translog="10M" sp_dboption sqlalchemy, "trunc log on chkpt", true sp_addlogin scott, "tiger7" sp_addlogin test_schema, "tiger7" use sqlalchemy sp_adduser scott sp_adduser test_schema grant all to scott sp_role "grant", sa_role, scott Sybase will still freeze for up to a minute when the log becomes full. To manually dump the log:: dump tran sqlalchemy with truncate_only MSSQL: Tests that involve multiple connections require Snapshot Isolation ability implemented on the test database in order to prevent deadlocks that will occur with record locking isolation. This feature is only available with MSSQL 2005 and greater. You must enable snapshot isolation at the database level and set the default cursor isolation with two SQL commands: ALTER DATABASE MyDatabase SET ALLOW_SNAPSHOT_ISOLATION ON ALTER DATABASE MyDatabase SET READ_COMMITTED_SNAPSHOT ON MSSQL+zxJDBC: Trying to run the unit tests on Windows against SQL Server requires using a test.cfg configuration file as the cmd.exe shell won't properly pass the URL arguments into the nose test runner.
If you'll be running the tests frequently, database aliases can save a lot of typing. The --dbs option lists the built-in aliases and their matching URLs:
$ ./sqla_nose.py --dbs Available --db options (use --dburi to override) mysql mysql://scott:firstname.lastname@example.org:3306/test oracle oracle://scott:email@example.com:1521 postgresql postgresql://scott:firstname.lastname@example.org:5432/test [...]
To run tests against an aliased database:
$ ./sqla_nose.py --db=postgresql
To customize the URLs with your own users or hostnames, create a file called test.cfg at the top level of the SQLAlchemy source distribution. This file is in Python config format, and contains a [db] section which lists out additional database configurations:
Your custom entries will override the defaults and you'll see them reflected in the output of --dbs.
SQLAlchemy logs its activity and debugging through Python's logging package. Any log target can be directed to the console with command line options, such as:
$ ./sqla_nose.py test.orm.unitofwork --log-info=sqlalchemy.orm.mapper \ --log-debug=sqlalchemy.pool --log-info=sqlalchemy.engine
This would log mapper configuration, connection pool checkouts, and SQL statement execution.
BUILT-IN COVERAGE REPORTING
Coverage is tracked using Nose's coverage plugin. See the nose documentation for details. Basic usage is:
$ ./sqla_nose.py test.sql.test_query --with-coverage
BIG COVERAGE TIP !!! There is an issue where existing .pyc files may store the incorrect filepaths, which will break the coverage system. If coverage numbers are coming out as low/zero, try deleting all .pyc files.
DEVELOPING AND TESTING NEW DIALECTS
See the new file README.dialects.rst for detail on dialects.