====================== Writing a locustfile ====================== A locustfile is a normal python file. The only requirement is that it declares at least one class— let's call it the locust class—that inherits from the class Locust. The Locust class ================ A locust class represents one user (or a swarming locust if you will). Locust will spawn (hatch) one instance of the locust class for each user that is being simulated. There are a few attributes that a locust class should typically define. The :py:attr:`task_set ` attribute --------------------------------------------------------------- The :py:attr:`task_set ` attribute should point to a :py:class:`TaskSet ` class which defines the behaviour of the user and is described in more detail below. The *min_wait* and *max_wait* attributes ---------------------------------------- In addition to the task_set attribute, one usually wants to declare the *min_wait* and *max_wait* attributes. These are the minimum and maximum time respectively, in milliseconds, that a simulated user will wait between executing each task. *min_wait* and *max_wait* default to 1000, and therefore a locust will always wait 1 second between each task if *min_wait* and *max_wait* are not declared. With the following locustfile, each user would wait between 5 and 15 seconds between tasks:: from locust import Locust, TaskSet, task class MyTaskSet(TaskSet): @task def my_task(self): print "executing my_task" class MyLocust(Locust): task_set = MyTaskSet min_wait = 5000 max_wait = 15000 The *min_wait* and *max_wait* attributes can also be overridden in a TaskSet class. The *weight* attribute ---------------------- You can run two locusts from the same file like so:: locust -f locust_file.py WebUserLocust MobileUserLocust If you wish to make one of these locusts execute more often you can set a weight attribute on those classes. Say for example, web users are three times more likely than mobile users:: class WebUserLocust(Locust): weight = 3 .... class MobileUserLocust(Locust): weight = 1 .... The *host* attribute -------------------- The host attribute is a URL prefix (i.e. "http://google.com") to the host that is to be loaded. Usually, this is specified on the command line, using the :code:`--host` option, when locust is started. If one declares a host attribute in the locust class, it will be used in the case when no :code:`--host` is specified on the command line. TaskSet class ============= If the Locust class represents a swarming locust, you could say that the TaskSet class represents the brain of the locust. Each Locust class must have a *task_set* attribute set, that points to a TaskSet. A TaskSet is, like its name suggests, a collection of tasks. These tasks are normal python callables and—if we were load-testing an auction website—could do stuff like "loading the start page", "searching for some product" and "making a bid". When a load test is started, each instance of the spawned Locust classes will start executing their TaskSet. What happens then is that each TaskSet will pick one of its tasks and call it. It will then wait a number of milliseconds, chosen at random between the Locust class' *min_wait* and *max_wait* attributes (unless min_wait/max_wait have been defined directly under the TaskSet, in which case it will use its own values instead). Then it will again pick a new task to be called, wait again, and so on. Declaring tasks --------------- The typical way of declaring tasks for a TaskSet it to use the :py:meth:`task ` decorator. Here is an example:: from locust import Locust, TaskSet, task class MyTaskSet(TaskSet): @task def my_task(self): print "Locust instance (%r) executing my_task" % (self.locust) class MyLocust(Locust): task_set = MyTaskSet **@task** takes an optional weight argument that can be used to specify the task's execution ratio. In the following example *task2* will be executed twice as much as *task1*:: from locust import Locust, TaskSet, task class MyTaskSet(TaskSet): min_wait = 5000 max_wait = 15000 @task(3) def task1(self): pass @task(6) def task2(self): pass class MyLocust(Locust): task_set = MyTaskSet tasks attribute -------------- Using the @task decorator to declare tasks is a convenience, and usually the best way to do it. However, it's also possible to define the tasks of a TaskSet by setting the :py:attr:`tasks ` attribute (using the @task decorator will actually just populate the *tasks* attribute). The *tasks* attribute is either a list of python callables, or a ** dict. The tasks are python callables that receive one argument—the TaskSet class instance that is executing the task. Here is an extremely simple example of a locustfile (this locustfile won't actually load test anything):: from locust import Locust, TaskSet def my_task(l): pass class MyTaskSet(TaskSet): tasks = [my_task] class MyLocust(Locust): task_set = MyTaskSet If the tasks attribute is specified as a list, each time a task is to be performed, it will be randomly chosen from the *tasks* attribute. If however, *tasks* is a dict—with callables as keys and ints as values—the task that is to be executed will be chosen at random but with the int as ratio. So with a tasks that looks like this:: {my_task: 3, another_task:1} *my_task* would be 3 times more likely to be executed than *another_task*. TaskSets can be nested ---------------------- A very important property of TaskSets is that they can be nested, because real websites are usually built up in an hierarchical way, with multiple sub-sections. Nesting TaskSets will therefore allow us to define a behaviour that simulates users in a more realistic way. For example we could define TaskSets with the following structure: * Main user behaviour * Index page * Forum page * Read thread * Reply * New thread * View next page * Browse categories * Watch movie * Filter movies * About page The way you nest TaskSets is just like when you specify a task using the **tasks** attribute, but instead of referring to a python function, you refer to another TaskSet:: class ForumPage(TaskSet): @task(20) def read_thread(self): pass @task(1) def new_thread(self): pass @task(5) def stop(self): self.interrupt() class UserBehaviour(TaskSet): tasks = {ForumPage:10} @task def index(self): pass So in the above example, if the ForumPage would get selected for execution when the UserBehaviour TaskSet is executing, then the ForumPage TaskSet would start executing. The ForumPage TaskSet would then pick one of its own tasks, execute it, wait, and so on. There is one important thing to note about the above example, and that is the call to self.interrupt() in the ForumPage's stop method. What this does is essentially to stop executing the ForumPage task set and the execution will continue in the UserBehaviour instance. If we didn't have a call to the :py:meth:`interrupt() ` method somewhere in ForumPage, the Locust would never stop running the ForumPage task once it has started. But by having the interrupt function, we can—together with task weighting—define how likely it is that a simulated user leaves the forum. It's also possible to declare a nested TaskSet, inline in a class, using the :py:meth:`@task ` decorator, just like when declaring normal tasks:: class MyTaskSet(TaskSet): @task class SubTaskSet(TaskSet): @task def my_task(self): pass The on_start function --------------------- A TaskSet class can optionally declare an :py:meth:`on_start ` function. If so, that function is called when a simulated user starts executing that TaskSet class. Referencing the Locust instance, or the parent TaskSet instance --------------------------------------------------------------- A TaskSet instance will have the attribute :py:attr:`locust ` point to its Locust instance, and the attribute :py:attr:`parent ` point to its parent TaskSet (it will point to the Locust instance, in the base TaskSet). Making HTTP requests ===================== So far, we've only covered the task scheduling part of a Locust user. In order to actually load test a system we need to make HTTP requests. To help us do this, the :py:class:`HttpLocust ` class exists. When using this class, each instance gets a :py:attr:`client ` attribute which will be an instance of :py:attr:`HttpSession ` which can be used to make HTTP requests. .. autoclass:: locust.core.HttpLocust :members: client :noindex: When inheriting from the HttpLocust class, we can use its client attribute to make HTTP requests against the server. Here is an example of a locust file that can be used to load test a site with two URLs; **/** and **/about/**:: from locust import HttpLocust, TaskSet, task class MyTaskSet(TaskSet): @task(2) def index(self): self.client.get("/") @task(1) def about(self): self.client.get("/about/") class MyLocust(HttpLocust): task_set = MyTaskSet min_wait = 5000 max_wait = 15000 Using the above Locust class, each simulated user will wait between 5 and 15 seconds between the requests, and **/** will be requested twice as much as **/about/**. The attentive reader will find it odd that we can reference the HttpSession instance using *self.client* inside the TaskSet, and not *self.locust.client*. We can do this because the :py:class:`TaskSet ` class has a convenience property called client that simply returns self.locust.client. Using the HTTP client ---------------------- Each instance of HttpLocust has an instance of :py:class:`HttpSession ` in the *client* attribute. The HttpSession class is actually a subclass of :py:class:`requests.Session` and can be used to make HTTP requests, that will be reported to Locust's statistics, using the :py:meth:`get `, :py:meth:`post `, :py:meth:`put `, :py:meth:`delete `, :py:meth:`head `, :py:meth:`patch ` and :py:meth:`options ` methods. The HttpSession instance will preserve cookies between requests so that it can be used to log in to websites and keep a session between requests. The client attribute can also be referenced from the Locust instance's TaskSet instances so that it's easy to retrieve the client and make HTTP requests from within your tasks. Here's a simple example that makes a GET request to the */about* path (in this case we assume *self* is an instance of a :py:class:`TaskSet ` or :py:class:`HttpLocust ` class:: response = self.client.get("/about") print "Response status code:", response.status_code print "Response content:", response.content And here's an example making a POST request:: response = self.client.post("/login", {"username":"testuser", "password":"secret"}) Safe mode --------- The HTTP client is configured to run in safe_mode. What this does is that any request that fails due to a connection error, timeout, or similar will not raise an exception, but rather return an empty dummy Response object. The request will be reported as a failure in Locust's statistics. The returned dummy Response's *content* attribute will be set to None, and its *status_code* will be 0. Manually controlling if a request should be considered successful or a failure ------------------------------------------------------------------------------ By default, requests are marked as failed requests unless the HTTP response code is OK (2xx). Most of the time, this default is what you want. Sometimes however—for example when testing a URL endpoint that you expect to return 404, or testing a badly designed system that might return *200 OK* even though an error occurred—there's a need for manually controlling if locust should consider a request as a success or a failure. One can mark requests as failed, even when the response code is OK, by using the *catch_response* argument and a with statement:: with client.get("/", catch_response=True) as response: if response.content != "Success": response.failure("Got wrong response") Just as one can mark requests with OK response codes as failures, one can also use **catch_response** argument together with a *with* statement to make requests that resulted in an HTTP error code still be reported as a success in the statistics:: with client.get("/does_not_exist/", catch_response=True) as response: if response.status_code == 404: response.success() Grouping requests to URLs with dynamic parameters ------------------------------------------------- It's very common for websites to have pages whose URLs contain some kind of dynamic parameter(s). Often it makes sense to group these URLs together in Locust's statistics. This can be done by passing a *name* argument to the :py:class:`HttpSession's ` different request methods. Example:: # Statistics for these requests will be grouped under: /blog/?id=[id] for i in range(10): client.get("/blog?id=%i" % i, name="/blog?id=[id]") Common libraries ================= Often, people wish to group multiple locustfiles that share common libraries. In that case, it is important to define the *project root* to be the directory where you invoke locust, and it is suggested that all locustfiles live somewhere beneath the project root. A flat file structure works out of the box: * project root * ``commonlib_config.py`` * ``commonlib_auth.py`` * ``locustfile_web_app.py`` * ``locustfile_api.py`` * ``locustfile_ecommerce.py`` The locustfiles may import common libraries using, e.g. ``import commonlib_auth``. This approach does not cleanly separate common libraries from locust files, however. Subdirectories can be a cleaner approach (see example below), but locust will only import modules relative to the directory in which the running locustfile is placed. If you wish to import from your project root (i.e. the location where you are running the locust command), make sure to write ``sys.path.append(os.getcwd())`` in your locust file(s) before importing any common libraries---this will make the project root (i.e. the current working directory) importable. * project root * ``__init__.py`` * ``common/`` * ``__init__.py`` * ``config.py`` * ``auth.py`` * ``locustfiles/`` * ``__init__.py`` * ``web_app.py`` * ``api.py`` * ``ecommerce.py`` With the above project structure, your locust files can import common libraries using:: sys.path.append(os.getcwd()) import common.auth