Amulet is a set of tools designed to simplify the testing process for charm authors. Amulet aims to be a
Ultimately, Amulet is to testing as Charm Helpers are to charm hooks. While these tools are designed to help make test writing easier, much like charm helpers are designed to make hook writing easier, they are not required to write tests for charms. This library is offered as a completely optional set of tools for you to use.
By definition, An amulet can be any object but its most important characteristic is its alleged power to protect its owner from danger or harm.
By this definition, Amulet is designed to be a library which protects charm authors from having broken charms by making test writing easier.
Amulet is available as both a package and via pip. For source packages, see Github.
Amulet is available in the Juju Stable PPA for Ubuntu
sudo add-apt-repository ppa:juju/stable
sudo apt-get update
sudo apt-get install amulet
Amulet is available via Pip
sudo pip install amulet
Amulet is available via Pip
pip install amulet
Amulet is built with Python3, make sure it's installed prior to following these steps. While you can run Amulet from source, it's not recommended as it requires several changes to environment variables in order for Amulet to operate as it does in the packaged version.
To install Amulet from source, first get the source:
git clone https://github.com/juju/amulet.git
cd amulet
make sysdeps
Move in to the amulet
directory and run sudo python3 setup.py install
. You can also access the Python libraries; however, your PYTHONPATH
will need to be amended in order for it to find the amulet directory.
Get the source and build your developmenmt environment with:
git clone https://github.com/juju/amulet.git
cd amulet
make sysdeps
make install
juju bootstrap -e ec2
make test
Amulet comes packaged with several tools. In order to provide the most flexibility, Amulet offers both direct Python library access and generic access via a programmable API for other languages (for example, bash). Below are two examples of how each is implemented. Please refer to the developer documentation for precise examples of how each function is implemented.
Amulet is made available to Python via the Amulet module which you can import.
import amulet
The amulet
module seeds each module/command directly, so Deployment
is made available in amulet/deployer.py
is accessible directly from amulet
using
from amulet import Deployment
Though deployer
is also available in the event you wish to execute any of the helper functions
from amulet import deployer
d = deployer.Deployment()
A limited number of functions are made available through a generic forking API. The following examples assume you're using a BOURNE Shell, though this syntax could be used from within other languages with the same expected results.
Unlike the Python modules, only some of the functions of Amulet are available through this API, though efforts are being made to make the majority of the core functionality available.
This API follows the subcommand workflow, much like Git or Bazaar. Amulet makes an amulet
command available and each function is tied to a sub-command. To mimic the Python example you can create a a new Deployment by issuing the following command:
amulet deployment
Depending on the syntax and workflow for each function you can expect to provide either additional sub-commands, command-line flags, or a combination of the two.
Please refer to the Developer Documentation for a list of supported subcommands and the syntax to use each.
This section is designed to outline the core functions of Amulet. Again, please refer to the developer documentation for an exhaustive list of functions and methods.
The Deployer module houses several classes for interacting and setting up an environment. These classes and methods are outlined below
Deployment (amulet deployment
, from amulet import Deployment
) is an abstraction layer to the juju-deployer Juju plugin and a service lifecycle management tool. It's designed to allow an author to describe their deployment in simple terms:
import amulet
d = amulet.Deployment()
d.add('mysql')
d.add('mediawiki')
d.relate('mysql:db', 'mediawiki:db')
d.expose('mediawiki')
d.configure('mediawiki', {
title: "My Wiki",
skin: "Nostolgia"
})
d.setup()
That information is then translated to a Juju Deployer deployment file then, finally, juju-deployer
executes the described setup. Amulet strives to ensure it implements the correct version and syntax of Juju Deployer to avoid charm authors having to potentially intervene each time an update to juju-deployer is made.
~~Once an environment has been setup, deployer
can still drive the environment outside of of juju-deployer. So the same commands (add
, relate
, configure
,
expose
) will instead interact directly with the environment by using either the Juju API or the juju commands directly.~
Add a new service to the deployment schema.
service
Name of the service to deploycharm
If provided, will be the charm used. Otherwise service
is used as the charmunits
Number of units to deployconstraints
A dictionary that specifies the machine constraints.import amulet
d = amulet.Deployment()
d.add('wordpress')
d.add('second-wp', charm='wordpress')
d.add('personal-wp', charm='~marcoceppi/wordpress', units=2)
import amulet
from collections import OrderedDict
d = amulet.Deployment()
d.add('charm', units=2, constraints=OrderedDict([
("cpu-power", 0),
("cpu-cores", 4),
("mem", "512M")
]))
Change configuration options for a service
service
The service to configureoptions
Dict of optionsimport amulet
d = amulet.Deployment()
d.add('postgresql')
d.configure('postgresql', {'autovacuum': True, 'cluster_name': 'cname'})
Indicate if a service should be exposed after deployment
service
Name of service to exposeimport amulet
d = amulet.Deployment()
d.add('varnish')
d.expose('varnish')
Import an existing deployer object
deploy_cfg
Already parsed deployer yaml/json fileRelate two services together
args
service:relation
to be relatedIf more than two arguments are given, it's assumed they're to be added to the first argument as a relation.
import amulet
d = amulet.Deployment()
d.add('postgresql')
d.add('mysql')
d.add('wordpress')
d.add('mediawiki')
d.add('discourse')
d.relate('postgresql:db-admin', 'discourse:db')
d.relate('mysql:db', 'wordpress:db', 'mediawiki:database')
This will create the deployer mapping, create any sentries that are required, and execute juju-deployer with the generated mapping.
timeout
in seconds, how long to wait for setupimport amulet
d = amulet.Deployment()
d.add('wordpress')
d.add('mysql')
d.configure('wordpress', {
debug: True
})
d.relate('wordpress:db', 'mysql:db')
try:
d.setup(timeout=900)
except amulet.helpers.TimeoutError:
# Setup didn't complete before timeout
pass
Sentries are an additional service built in to the Deployment tool which allow an author the ability to dig deeper in to a deployment environment. This is done by adding a set of tools to each service/unit deployed via a subordinate charm and a final "relation sentry" charm is deployed which all relations are proxied through. In doing so you can inspect on each service/unit deployed as well as receive detailed information about what data is being sent by which units/service during a relation.
Sentries can be accessed from within your deployment using the sentry object. Using the above example from ## Deployer, each service and unit can be accessed using the following:
import amulet
d = amulet.Deployment()
d.add('mediawiki')
d.add('mysql')
d.setup()
d.sentry.unit['mysql/0']
d.sentry.unit['mediawiki/0']
Sentries provide several methods for which you can use to gather information about an environment. Again, please refer to the Developer Documentation for a complete list of endpoints available. The following are a few examples.
Here are a few examples of Amulet tests
#!/bin/bash
sudo apt-get install amulet python-requests
import os
import amulet
import requests
from .lib import helper
d = amulet.Deployment()
d.add('mysql')
d.add('wordpress')
d.relate('mysql:db', 'wordpress:db')
d.expose('wordpress')
try:
# Create the deployment described above, give us 900 seconds to do it
d.setup(timeout=900)
# Setup will only make sure the services are deployed, related, and in a
# "started" state. We can employ the sentries to actually make sure there
# are no more hooks being executed on any of the nodes.
d.sentry.wait()
except amulet.helpers.TimeoutError:
amulet.raise_status(amulet.SKIP, msg="Environment wasn't stood up in time")
except:
# Something else has gone wrong, raise the error so we can see it and this
# will automatically "FAIL" the test.
raise
# Shorten the names a little to make working with unit data easier
wp_unit = d.sentry.unit['wordpress/0']
mysql_unit = d.sentry.unit['mysql/0']
# WordPress requires user input to "finish" a setup. This code is contained in
# the helper.py file found in the lib directory. If it's not able to complete
# the WordPress setup we need to quit the test, not as failed per se, but as a
# SKIPed test since we can't accurately setup the environment
try:
helper.finish_setup(wp_unit.info['public-address'], password='amulet-test')
except:
amulet.raise_status(amulet.SKIP, msg="Unable to finish WordPress setup")
home_page = requests.get('http://%s/' % wp_unit.info['public-address'])
home_page.raise_for_status() # Make sure it's not 5XX error
import requests
def finish_setup(unit, user='admin', password=None):
h = {'User-Agent': 'Mozilla/5.0 Gecko/20100101 Firefox/12.0',
'Content-Type': 'application/x-www-form-urlencoded',
'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*',
'Accept-Encoding': 'gzip, deflate'}
r = requests.post('http://%s/wp-admin/install.php?step=2' % unit,
headers=h, data={'weblog_title': 'Amulet Test %s' % unit,
'user_name': user, 'admin_password': password,
'admin_email': 'test@example.tld',
'admin_password2': password,
'Submit': 'Install WordPress'})
r.raise_for_status()