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SQLALCHEMY UNIT TESTS

Basic Test Running

Tox is used to run the test suite fully. For basic test runs against a single Python interpreter:

tox

Advanced Tox Options

For more elaborate CI-style test running, the tox script provided will run against various Python / database targets. For a basic run against Python 2.7 using an in-memory SQLite database:

tox -e py38-sqlite

The tox runner contains a series of target combinations that can run against various combinations of databases. The test suite can be run against SQLite with "backend" tests also running against a PostgreSQL database:

tox -e py38-sqlite-postgresql

Or to run just "backend" tests against a MySQL databases:

tox -e py38-mysql-backendonly

Running against backends other than SQLite requires that a database of that vendor be available at a specific URL. See "Setting Up Databases" below for details.

The pytest Engine

The tox runner is using pytest to invoke the test suite. Within the realm of pytest, SQLAlchemy itself is adding a large series of option and customizations to the pytest runner using plugin points, to allow for SQLAlchemy's multiple database support, database setup/teardown and connectivity, multi process support, as well as lots of skip / database selection rules.

Running tests with pytest directly grants more immediate control over database options and test selection.

A generic pytest run looks like:

pytest -n4

Above, the full test suite will run against SQLite, using four processes. If the "-n" flag is not used, the pytest-xdist is skipped and the tests will run linearly, which will take a pretty long time.

The pytest command line is more handy for running subsets of tests and to quickly allow for custom database connections. Example:

pytest --dburi=postgresql+psycopg2://scott:tiger@localhost/test  test/sql/test_query.py

Above will run the tests in the test/sql/test_query.py file (a pretty good file for basic "does this database work at all?" to start with) against a running PostgreSQL database at the given URL.

The pytest frontend can also run tests against multiple kinds of databases at once - a large subset of tests are marked as "backend" tests, which will be run against each available backend, and additionally lots of tests are targeted at specific backends only, which only run if a matching backend is made available. For example, to run the test suite against both PostgreSQL and MySQL at the same time:

pytest -n4 --db postgresql --db mysql

Setting Up Databases

The test suite identifies several built-in database tags that run against a pre-set URL. These can be seen using --dbs:

$ pytest --dbs
Available --db options (use --dburi to override)
             default    sqlite:///:memory:
            firebird    firebird://sysdba:masterkey@localhost//Users/classic/foo.fdb
             mariadb    mariadb://scott:tiger@192.168.0.199:3307/test
               mssql    mssql+pyodbc://scott:tiger^5HHH@mssql2017:1433/test?driver=ODBC+Driver+13+for+SQL+Server
       mssql_pymssql    mssql+pymssql://scott:tiger@ms_2008
               mysql    mysql://scott:tiger@127.0.0.1:3306/test?charset=utf8mb4
              oracle    oracle://scott:tiger@127.0.0.1:1521
             oracle8    oracle://scott:tiger@127.0.0.1:1521/?use_ansi=0
              pg8000    postgresql+pg8000://scott:tiger@127.0.0.1:5432/test
          postgresql    postgresql://scott:tiger@127.0.0.1:5432/test
postgresql_psycopg2cffi postgresql+psycopg2cffi://scott:tiger@127.0.0.1:5432/test
             pymysql    mysql+pymysql://scott:tiger@127.0.0.1:3306/test?charset=utf8mb4
              sqlite    sqlite:///:memory:
         sqlite_file    sqlite:///querytest.db

Note that a pyodbc URL must be against a hostname / database name combination, not a DSN name when using the multiprocessing option; this is because the test suite needs to generate new URLs to refer to per-process databases that are created on the fly.

What those mean is that if you have a database running that can be accessed by the above URL, you can run the test suite against it using --db <name>.

The URLs are present in the setup.cfg file. You can make your own URLs by creating a new file called test.cfg and adding your own [db] section:

# test.cfg file
[db]
my_postgresql=postgresql://username:pass@hostname/dbname

Above, we can now run the tests with my_postgresql:

pytest --db my_postgresql

We can also override the existing names in our test.cfg file, so that we can run with the tox runner also:

# test.cfg file
[db]
postgresql=postgresql://username:pass@hostname/dbname

Now when we run tox -e py27-postgresql, it will use our custom URL instead of the fixed one in setup.cfg.

Database Configuration

Step one, the database chosen for tests must be entirely empty. A lot of what SQLAlchemy tests is creating and dropping lots of tables as well as running database introspection to see what is there. If there are pre-existing tables or other objects in the target database already, these will get in the way. A failed test run can also be followed by

a run that includes the "--dropfirst" option, which will try to drop

all existing tables in the target database.

The above paragraph changes somewhat when the multiprocessing option is used, in that separate databases will be created instead, however in the case of Postgresql, the starting database is used as a template, so the starting database must still be empty. See below for example configurations using docker.

The test runner will by default create and drop tables within the default database that's in the database URL, unless the multiprocessing option is in use via the pytest "-n" flag, which invokes pytest-xdist. The multiprocessing option is enabled by default when using the tox runner. When multiprocessing is used, the SQLAlchemy testing framework will create a new database for each process, and then tear it down after the test run is complete. So it will be necessary for the database user to have access to CREATE DATABASE in order for this to work. Additionally, as mentioned earlier, the database URL must be formatted such that it can be rewritten on the fly to refer to these other databases, which means for pyodbc it must refer to a hostname/database name combination, not a DSN name.

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 and mssql)

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:

POSTGRESQL: To enable unicode testing with JSONB, create the
database with UTF8 encoding::

    postgres=# create database test with owner=scott encoding='utf8' template=template0;

To include tests for HSTORE, create the HSTORE type engine::

    postgres=# \c test;
    You are now connected to database "test" as user "postgresql".
    test=# create extension hstore;
    CREATE EXTENSION

Full-text search configuration should be set to English, else
several tests of ``.match()`` will fail. This can be set (if it isn't so
already) with:

 ALTER DATABASE test SET default_text_search_config = 'pg_catalog.english'

For two-phase transaction support, the max_prepared_transactions
configuration variable must be set to a non-zero value in postgresql.conf.
See
https://www.postgresql.org/docs/current/runtime-config-resource.html#GUC-MAX-PREPARED-TRANSACTIONS
for further background.

ORACLE: a user named "test_schema" is created in addition to the default
user.

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;

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

Docker Configurations

The SQLAlchemy test can run against database running in Docker containers. This ensures that they are empty and that their configuration is not influenced by any local usage.

The following configurations are just examples that developers can use to quickly set up a local environment for SQLAlchemy development. They are NOT intended for production use!

PostgreSQL configuration:

# only needed if a local image of postgres is not already present
docker pull postgres:12

# create the container with the proper configuration for sqlalchemy
docker run --rm -e POSTGRES_USER='scott' -e POSTGRES_PASSWORD='tiger' -e POSTGRES_DB='test' -p 127.0.0.1:5432:5432 -d --name postgres postgres:12-alpine

# configure the database
sleep 10
docker exec -ti postgres psql -U scott -c 'CREATE SCHEMA test_schema; CREATE SCHEMA test_schema_2;' test
# this last command is optional
docker exec -ti postgres sed -i 's/#max_prepared_transactions = 0/max_prepared_transactions = 10/g' /var/lib/postgresql/data/postgresql.conf

# To stop the container. It will also remove it.
docker stop postgres

MySQL configuration:

# only needed if a local image of mysql is not already present
docker pull mysql:8

# create the container with the proper configuration for sqlalchemy
docker run --rm -e MYSQL_USER='scott' -e MYSQL_PASSWORD='tiger' -e MYSQL_DATABASE='test' -e MYSQL_ROOT_PASSWORD='password' -p 127.0.0.1:3306:3306 -d --name mysql mysql:8 --character-set-server=utf8mb4 --collation-server=utf8mb4_unicode_ci

# configure the database
sleep 20
docker exec -ti mysql mysql -u root -ppassword -D test -w -e "GRANT ALL ON *.* TO scott@'%'; CREATE DATABASE test_schema CHARSET utf8mb4; CREATE DATABASE test_schema_2 CHARSET utf8mb4;"

# To stop the container. It will also remove it.
docker stop mysql

MariaDB configuration:

# only needed if a local image of MariaDB is not already present
docker pull mariadb

# create the container with the proper configuration for sqlalchemy
docker run --rm -e MYSQL_USER='scott' -e MYSQL_PASSWORD='tiger' -e MYSQL_DATABASE='test' -e MYSQL_ROOT_PASSWORD='password' -p 127.0.0.1:3306:3306 -d --name mariadb mariadb --character-set-server=utf8mb4 --collation-server=utf8mb4_unicode_ci

# configure the database
sleep 20
docker exec -ti mariadb mysql -u root -ppassword -D test -w -e "GRANT ALL ON *.* TO scott@'%'; CREATE DATABASE test_schema CHARSET utf8mb4; CREATE DATABASE test_schema_2 CHARSET utf8mb4;"

# To stop the container. It will also remove it.
docker stop mariadb

MSSQL configuration:

# only needed if a local image of mssql is not already present
docker pull mcr.microsoft.com/mssql/server:2019-CU1-ubuntu-16.04

# create the container with the proper configuration for sqlalchemy
# it will use the Developer version
docker run --rm -e 'ACCEPT_EULA=Y' -e 'SA_PASSWORD=yourStrong(!)Password' -p 127.0.0.1:1433:1433 -d --name mssql mcr.microsoft.com/mssql/server:2019-CU2-ubuntu-16.04

# configure the database
sleep 20
docker exec -it mssql /opt/mssql-tools/bin/sqlcmd -S localhost -U sa -P 'yourStrong(!)Password' -Q "sp_configure 'contained database authentication', 1; RECONFIGURE; CREATE DATABASE test CONTAINMENT = PARTIAL; ALTER DATABASE test SET ALLOW_SNAPSHOT_ISOLATION ON; ALTER DATABASE test SET READ_COMMITTED_SNAPSHOT ON; CREATE LOGIN scott WITH PASSWORD = 'tiger^5HHH'; ALTER SERVER ROLE sysadmin ADD MEMBER scott;"
docker exec -it mssql /opt/mssql-tools/bin/sqlcmd -S localhost -U sa -P 'yourStrong(!)Password' -d test -Q "CREATE SCHEMA test_schema"
docker exec -it mssql /opt/mssql-tools/bin/sqlcmd -S localhost -U sa -P 'yourStrong(!)Password' -d test -Q "CREATE SCHEMA test_schema_2"

# To stop the container. It will also remove it.
docker stop mssql

NOTE: with this configuration the url to use is not the default one configured in setup, but mssql+pymssql://scott:tiger^5HHH@127.0.0.1:1433/test. It can be used with pytest by using --db docker_mssql.

CONFIGURING LOGGING

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:

$ ./pytest test/orm/test_unitofwork.py -s \
  --log-debug=sqlalchemy.pool --log-info=sqlalchemy.engine

Above we add the pytest "-s" flag so that standard out is not suppressed.

DEVELOPING AND TESTING NEW DIALECTS

See the file README.dialects.rst for detail on dialects.