Developing with Keystone

Setup

Get your development environment set up according to Setting up a Keystone development environment. The instructions from here will assume that you have installed keystone into a virtualenv. If you chose not to, simply exclude “tools/with_venv.sh” from the example commands below.

Configuring Keystone

keystone requires a configuration file. There is a sample configuration file that can be used to get started:

$ cp etc/keystone.conf.sample etc/keystone.conf

The defaults are enough to get you going, but you can make any changes if needed.

Running Keystone

To run the keystone Admin and API server instances, use:

$ tools/with_venv.sh bin/keystone-all

this runs keystone with the configuration the etc/ directory of the project. See Configuring Keystone for details on how Keystone is configured. By default, keystone is configured with SQL backends.

Interacting with Keystone

You can interact with Keystone through the command line using keystone-manage which allows you to initialize keystone, etc.

You can also interact with Keystone through its REST API. There is a python keystone client library python-keystoneclient which interacts exclusively through the REST API, and which keystone itself uses to provide its command-line interface.

When initially getting set up, after you’ve configured which databases to use, you’re probably going to need to run the following to your database schema in place:

$ bin/keystone-manage db_sync

Database Schema Migrations

Keystone uses SQLAlchemy-migrate to migrate the SQL database between revisions. For core components, the migrations are kept in a central repository under keystone/common/sql/migrate_repo.

Extensions should be created as directories under keystone/contrib. An extension that requires SQL migrations should not change the common repository, but should instead have its own repository. This repository must be in the extension’s directory in keystone/contrib/<extension>/migrate_repo. In addition, it needs a subdirectory named versions. For example, if the extension name is my_extension then the directory structure would be keystone/contrib/my_extension/migrate_repo/versions/. For the migration to work, both the migrate_repo and versions subdirectories must have __init__.py files. SQLAlchemy-migrate will look for a configuration file in the migrate_repo named migrate.cfg. This conforms to a key/value ini file format. A sample configuration file with the minimal set of values is:

[db_settings]
repository_id=my_extension
version_table=migrate_version
required_dbs=[]

The directory keystone/contrib/example contains a sample extension migration.

Migrations must be explicitly run for each extension individually. To run a migration for a specific extension, run keystone-manage --extension <name> db_sync.

Initial Sample Data

There is an included script which is helpful in setting up some initial sample data for use with keystone:

$ OS_SERVICE_TOKEN=ADMIN tools/with_venv.sh tools/sample_data.sh

Notice it requires a service token read from an environment variable for authentication. The default value “ADMIN” is from the admin_token option in the [DEFAULT] section in etc/keystone.conf.

Once run, you can see the sample data that has been created by using the python-keystoneclient command-line interface:

$ tools/with_venv.sh keystone --os-token ADMIN --os-endpoint http://127.0.0.1:35357/v2.0/ user-list

Testing

Running Tests

Before running tests, you should have tox installed and available in your environment (in addition to the other external dependencies in Setting up a Keystone development environment):

$ pip install tox

Note

You may need to perform both the above operation and the next inside a python virtualenv, or prefix the above command with sudo, depending on your preference.

To execute the full suite of tests maintained within Keystone, simply run:

$ tox

This iterates over multiple configuration variations, and uses external projects to do light integration testing to verify the Identity API against other projects.

Note

The first time you run tox, it will take additional time to build virtualenvs. You can later use the -r option with tox to rebuild your virtualenv in a similar manner.

To run tests for one or more specific test environments (for example, the most common configuration of Python 2.7 and PEP-8), list the environments with the -e option, separated by spaces:

$ tox -e py27,pep8

See tox.ini for the full list of available test environments.

Running with PDB

Using PDB breakpoints with tox and testr normally doesn’t work since the tests just fail with a BdbQuit exception rather than stopping at the breakpoint.

To run with PDB breakpoints during testing, use the debug tox environment rather than py27. Here’s an example, passing the name of a test since you’ll normally only want to run the test that hits your breakpoint:

$ tox -e debug keystone.tests.test_auth.AuthWithToken.test_belongs_to

For reference, the debug tox environment implements the instructions here: https://wiki.openstack.org/wiki/Testr#Debugging_.28pdb.29_Tests

Test Structure

Not all of the tests in the tests directory are strictly unit tests. Keystone intentionally includes tests that run the service locally and drives the entire configuration to achieve basic functional testing.

For the functional tests, an in-memory key-value store is used to keep the tests fast.

Within the tests directory, the general structure of the tests is a basic set of tests represented under a test class, and then subclasses of those tests under other classes with different configurations to drive different backends through the APIs.

For example, test_backend.py has a sequence of tests under the class IdentityTests that will work with the default drivers as configured in this projects etc/ directory. test_backend_sql.py subclasses those tests, changing the configuration by overriding with configuration files stored in the tests directory aimed at enabling the SQL backend for the Identity module.

Likewise, test_keystoneclient.py takes advantage of the tests written against KeystoneClientTests to verify the same tests function through different drivers and releases of the Keystone client.

The class CompatTestCase does the work of checking out a specific version of python-keystoneclient, and then verifying it against a temporarily running local instance to explicitly verify basic functional testing across the API.

Testing Schema Migrations

The application of schema migrations can be tested using SQLAlchemy Migrate’s built-in test runner, one migration at a time.

Warning

This may leave your database in an inconsistent state; attempt this in non-production environments only!

This is useful for testing the next migration in sequence (both forward & backward) in a database under version control:

python keystone/common/sql/migrate_repo/manage.py test \
--url=sqlite:///test.db \
--repository=keystone/common/sql/migrate_repo/

This command references to a SQLite database (test.db) to be used. Depending on the migration, this command alone does not make assertions as to the integrity of your data during migration.

Writing Tests

To add tests covering all drivers, update the relevant base test class (test_backend.py, test_legacy_compat.py, and test_keystoneclient.py).

To add new drivers, subclass the test_backend.py (look towards test_backend_sql.py or test_backend_kvs.py for examples) and update the configuration of the test class in setUp().

Further Testing

devstack is the best way to quickly deploy keystone with the rest of the OpenStack universe and should be critical step in your development workflow!

You may also be interested in either the OpenStack Continuous Integration Project or the OpenStack Integration Testing Project.

LDAP Tests

LDAP has a fake backend that performs rudimentary operations. If you are building more significant LDAP functionality, you should test against a live LDAP server. Devstack has an option to set up a directory server for Keystone to use. Add ldap to the ENABLED_SERVICES environment variable, and set environment variables KEYSTONE_IDENTITY_BACKEND=ldap and KEYSTONE_CLEAR_LDAP=yes in your localrc file.

The unit tests can be run against a live server with keystone/tests/_ldap_livetest.py. The default password is test but if you have installed devstack with a different LDAP password, modify the file keystone/tests/backend_liveldap.conf to reflect your password.

Translated responses

The Keystone server can provide error responses translated into the language in the Accept-Language header of the request. In order to test this in your development environment, there’s a couple of things you need to do.

  1. Build the message files. Run the following command in your keystone directory:

    $ python setup.py compile_catalog

This will generate .mo files like keystone/locale/[lang]/LC_MESSAGES/[lang].mo

  1. When running Keystone, set the KEYSTONE_LOCALEDIR environment variable to the keystone/locale directory. For example:

    $ KEYSTONE_LOCALEDIR=/opt/stack/keystone/keystone/locale keystone-all

Now you can get a translated error response:

$ curl -s -H "Accept-Language: zh" http://localhost:5000/notapath | python -mjson.tool
{
    "error": {
        "code": 404,
        "message": "\u627e\u4e0d\u5230\u8cc7\u6e90\u3002",
        "title": "Not Found"
    }
}

Caching Layer

The caching layer is designed to be applied to any manager object within Keystone via the use of the on_arguments decorator provided in the keystone.common.cache module. This decorator leverages dogpile.cache caching system to provide a flexible caching backend.

It is recommended that each of the managers have an independent toggle within the config file to enable caching. The easiest method to utilize the toggle within the configuration file is to define a caching boolean option within that manager’s configuration section (e.g. identity). Once that option is defined you can pass function to the on_arguments decorator with the named argument should_cache_fn. In the keystone.common.cache module, there is a function called should_cache_fn, which will provide a reference, to a function, that will consult the global cache enabled option as well as the specific manager’s caching enable toggle.

Note

If a section-specific boolean option is not defined in the config section specified when calling should_cache_fn, the returned function reference will default to enabling caching for that manager.

Example use of cache and should_cache_fn (in this example, token is the manager):

from keystone.common import cache
SHOULD_CACHE = cache.should_cache_fn('token')

@cache.on_arguments(should_cache_fn=SHOULD_CACHE)
def cacheable_function(arg1, arg2, arg3):
    ...
    return some_value

With the above example, each call to the cacheable_function would check to see if the arguments passed to it matched a currently valid cached item. If the return value was cached, the caching layer would return the cached value; if the return value was not cached, the caching layer would call the function, pass the value to the SHOULD_CACHE function reference, which would then determine if caching was globally enabled and enabled for the token manager. If either caching toggle is disabled, the value is returned but not cached.

It is recommended that each of the managers have an independent configurable time-to-live (TTL). If a configurable TTL has been defined for the manager configuration section, it is possible to pass it to the cache.on_arguments decorator with the named-argument expiration_time. For consistency, it is recommended that this option be called cache_time and default to None. If the expiration_time argument passed to the decorator is set to None, the expiration time will be set to the global default (expiration_time option in the [cache] configuration section.

Example of using a section specific cache_time (in this example, identity is the manager):

from keystone.common import cache
SHOULD_CACHE = cache.should_cache_fn('identity')

@cache.on_arguments(should_cache_fn=SHOULD_CACHE,
                    expiration_time=CONF.identity.cache_time)
def cachable_function(arg1, arg2, arg3):
    ...
    return some_value

For cache invalidation, the on_arguments decorator will add an invalidate method (attribute) to your decorated function. To invalidate the cache, you pass the same arguments to the invalidate method as you would the normal function.

Example (using the above cacheable_function):

def invalidate_cache(arg1, arg2, arg3):
    cacheable_function.invalidate(arg1, arg2, arg3)

Warning

The on_arguments decorator does not accept keyword-arguments/named arguments. An exception will be raised if keyword arguments are passed to a caching-decorated function.

Note

In all cases methods work the same as functions except if you are attempting to invalidate the cache on a decorated bound-method, you need to pass self to the invalidate method as the first argument before the arguments.

dogpile.cache based Key-Value-Store (KVS)

The dogpile.cache based KVS system has been designed to allow for flexible stores for the backend of the KVS system. The implementation allows for the use of any normal dogpile.cache cache backends to be used as a store. All interfacing to the KVS system happens via the KeyValueStore object located at keystone.common.kvs.KeyValueStore.

To utilize the KVS system an instantiation of the KeyValueStore class is needed. To accquire a KeyValueStore instantiation use the keystone.common.kvs.get_key_value_store factory function. This factory will either create a new KeyValueStore object or retrieve the already instantiated KeyValueStore object by the name passed as an argument. The object must be configured before use. The KVS object will only be retrievable with the get_key_value_store function while there is an active reference outside of the registry. Once all references have been removed the object is gone (the registry uses a weakref to match the object to the name).

Example Instantiation and Configuration:

kvs_store = kvs.get_key_value_store('TestKVSRegion')
kvs_store.configure('openstack.kvs.Memory', ...)

Any keyword arguments passed to the configure method that are not defined as part of the KeyValueStore object configuration are passed to the backend for further configuration (e.g. memcache servers, lock_timeout, etc).

The memcached backend uses the Keystone manager mechanism to support the use of any of the provided dogpile.cache memcached backends (BMemcached, pylibmc, and basic Memcached). By default the standard Memcache backend is used. Currently the Memcache URLs come from the servers option in the [memcache] configuration section of the Keystone config.

Example configuring the KVS system to use memcached and a specific dogpile.cache memcached backend:

kvs_store = kvs.get_key_value_store('TestKVSRegion')
kvs_store.configure('openstack.kvs.Memcached', dogpile_cache_backend='MemcachedBackend')

Once a KVS object has been instantiated the method of interacting is the same as most memcache implementations:

kvs_store = kvs.get_key_value_store('TestKVSRegion')
kvs_store.configure(...)
# Set a Value
kvs_store.set(<Key>, <Value>)
# Retrieve a value:
retrieved_value = kvs_store.get(<key>)
# Delete a key/value pair:
kvs_store.delete(<key>)
# multi-get:
kvs_store.get_multi([<key>, <key>, ...])
# multi-set:
kvs_store.set_multi(dict(<key>=<value>, <key>=<value>, ...))
# multi-delete
kvs_store.delete_multi([<key>, <key>, ...])

There is a global configuration option to be aware of (that can be set in the [kvs] section of the Keystone configuration file): enable_key_mangler can be set top false, disabling the use of key_manglers (modification of the key when saving to the backend to help prevent collisions or exceeding key size limits with memcached).

Note

The enable_key_mangler option in the [kvs] section of the Keystone configuration file is not the same option (and does not affect the cache-layer key manglers) from the option in the [cache] section of the configuration file. Similarly the [cache] section options relating to key manglers has no bearing on the [kvs] objects.

Warning

Setting the enable_key_mangler option to False can have detrimental effects on the KeyValueStore backend. It is recommended that this value is not set to False except for debugging issues with the dogpile.cache backend itself.

Any backends that are to be used with the KeyValueStore system need to be registered with dogpile. For in-tree/provided backends, the registration should occur in keystone/common/kvs/__init__.py. For backends that are developed out of tree, the location should be added to the backends option in the [kvs] section of the Keystone configuration:

[kvs]
backends = backend_module1.backend_class1,backend_module2.backend_class2

All registered backends will receive the “short name” of “openstack.kvs.<class name>” for use in the configure method on the KeyValueStore object. The <class name> of a backend must be globally unique.

Building the Documentation

The documentation is generated with Sphinx uning the tox command. To create HTML docs and man pages:

$ tox -e docs

The results are in the docs/build/html and docs/build/man directories respectively.