Writing a locustfile

A locustfile is a normal python file. The only requirement is that it declares at least one class that inherits from the class User.

User class

A user class represents one user (or a swarming locust if you will). Locust will spawn one instance of the User class for each user that is being simulated. There are some common attributes that a User class may define.

wait_time attribute

A User’s wait_time method is an optional attribute used to determine how long a simulated user should wait between executing tasks. If no wait_time is specified, a new task will be executed as soon as one finishes.

There are three built in wait time functions:

  • constant for a fixed amount of time

  • between for a random time between a min and max value

  • constant_pacing for an adaptive time that ensures the task runs (at most) once every X seconds

For example, to make each user wait between 0.5 and 10 seconds between every task execution:

from locust import User, task, between

class MyUser(User):
    @task
    def my_task(self):
        print("executing my_task")

    wait_time = between(0.5, 10)

It’s also possible to declare your own wait_time method directly on your class. For example, the following User class would sleep for one second, then two, then three, etc.

class MyUser(User):
    last_wait_time = 0

    def wait_time(self):
        self.last_wait_time += 1
        return self.last_wait_time

    ...

weight attribute

If more than one user class exists in the file, and no user classes are specified on the command line, Locust will spawn an equal number of each of the user classes. You can also specify which of the user classes to use from the same locustfile by passing them as command line arguments:

$ locust -f locust_file.py WebUser MobileUser

If you wish to simulate more users of a certain type you can set a weight attribute on those classes. Say for example, web users are three times more likely than mobile users:

class WebUser(User):
    weight = 3
    ...

class MobileUser(User):
    weight = 1
    ...

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 in Locust’s web UI or on the command line, using the --host option, when locust is started.

If one declares a host attribute in the user class, it will be used in the case when no --host is specified on the command line or in the web request.

tasks attribute

A User class can have tasks declared as methods under it using the @task decorator, but one can also specify tasks using the tasks attribute which is described in more details below.

environment attribute

A reference to the environment in which the user is running. Use this to interact with the environment, or the runner which it contains. E.g. to stop the runner from a task method:

self.environment.runner.quit()

If run on a standalone locust instance, this will stop the entire run. If run on worker node, it will stop that particular node.

on_start and on_stop methods

Users (and TaskSets) can declare an on_start method and/or on_stop method. A User will call its on_start method when it starts running, and its on_stop method when it stops running. For a TaskSet, the on_start method is called when a simulated user starts executing that TaskSet, and on_stop is called when the simulated user stops executing that TaskSet (when interrupt() is called, or the user is killed).

Tasks

When a load test is started, an instance of a User class will be created for each simulated user and they will start running within their own green thread. When these users run they pick tasks that they execute, sleep for awhile, and then pick a new task and so on.

The tasks are normal python callables and - if we were load-testing an auction website - they could do stuff like “loading the start page”, “searching for some product”, “making a bid”, etc.

@task decorator

The easiest way to add a task for a User is by using the task decorator.

from locust import User, task, constant

class MyUser(User):
    wait_time = constant(1)

    @task
    def my_task(self):
        print("User instance (%r) executing my_task" % self)

@task takes an optional weight argument that can be used to specify the task’s execution ratio. In the following example task2 will have twice the chance of being picked as task1:

from locust import User, task, between

class MyUser(User):
    wait_time = between(5, 15)

    @task(3)
    def task1(self):
        pass

    @task(6)
    def task2(self):
        pass

tasks attribute

Another way to define the tasks of a User is by setting the tasks attribute.

The tasks attribute is either a list of Tasks, or a <Task : int> dict, where Task is either a python callable or a TaskSet class. If the task is a normal python function they receive a single argument which is the User instance that is executing the task.

Here is an example of a User task declared as a normal python function:

from locust import User, constant

def my_task(user):
    pass

class MyUser(User):
    tasks = [my_task]
    wait_time = constant(1)

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 task that looks like this:

{my_task: 3, another_task: 1}

my_task would be 3 times more likely to be executed than another_task.

Internally the above dict will actually be expanded into a list (and the tasks attribute is updated) that looks like this:

[my_task, my_task, my_task, another_task]

and then Python’s random.choice() is used pick tasks from the list.

@tag decorator

By tagging tasks using the @tag decorator, you can be picky about what tasks are executed during the test using the --tags and --exclude-tags arguments. Consider the following example:

from locust import User, constant, task, tag

class MyUser(User):
    wait_time = constant(1)

    @tag('tag1')
    @task
    def task1(self):
        pass

    @tag('tag1', 'tag2')
    @task
    def task2(self):
        pass

    @tag('tag3')
    @task
    def task3(self):
        pass

    @task
    def task4(self):
        pass

If you started this test with --tags tag1, only task1 and task2 would be executed during the test. If you started it with --tags tag2 tag3, only task2 and task3 would be executed.

--exclude-tags will behave in the exact opposite way. So, if you start the test with --exclude-tags tag3, only task1, task2, and task4 will be executed. Exclusion always wins over inclusion, so if a task has a tag you’ve included and a tag you’ve excluded, it will not be executed.

Events

If you want to run some setup code as part of your test, it is often enough to put it at the module level of your locustfile, but sometimes you need to do things at particular times in the run. For this need, Locust provides event hooks.

test_start and test_stop

If you need to run some code at the start or stop of a load test, you should use the test_start and test_stop events. You can set up listeners for these events at the module level of your locustfile:

from locust import events

@events.test_start.add_listener
def on_test_start(**kwargs):
    print("A new test is starting")

@events.test_stop.add_listener
def on_test_stop(**kwargs):
    print("A new test is ending")

When running Locust distributed the test_start and test_stop events will only be fired in the master node.

init

The init event is triggered at the beginning of each Locust process. This is especially useful in distributed mode where each worker process (not each user) needs a chance to do some initialization. For example, let’s say you have some global state that all users spawned from this process will need:

from locust import events
from locust.runners import MasterRunner

@events.init.add_listener
def on_locust_init(environment, **kwargs):
    if isinstance(environment.runner, MasterRunner):
        print("I'm on master node")
    else:
        print("I'm on a worker or standalone node")

other events

see extending locust using event hooks for other events and more examples of how to use them.

HttpUser class

HttpUser is the most commonly used User. It adds a client attribute which is used to make HTTP requests.

from locust import HttpUser, task, between

class MyUser(HttpUser):
    wait_time = between(5, 15)

    @task(4)
    def index(self):
        self.client.get("/")

    @task(1)
    def about(self):
        self.client.get("/about/")

client attribute / HttpSession

client is an instance of HttpSession. HttpSession is a subclass/wrapper for requests.Session, so its features are well documented and should be familiar to many. What HttpSession adds is mainly reporting of the request results into Locust (success/fail, response time, response length, name).

It contains methods for all HTTP methods: get, post, put, …

Just like requests.Session, it preserves cookies between requests so it can easily be used to log in to websites.

Make a POST request, look at the response and implicitly reuse any session cookies we got for a second request
response = self.client.post("/login", {"username":"testuser", "password":"secret"})
print("Response status code:", response.status_code)
print("Response text:", response.text)
response = self.client.get("/my-profile")

HttpSession catches any requests.RequestException thrown by Session (caused by connection errors, timeouts or similar), instead returning a dummy Response object with status_code set to 0 and content set to None.

Validating responses

Requests are considered successful if the HTTP response code is OK (<400), but it is often useful to do some additional validation of the response.

You can mark a request as failed by using the catch_response argument, a with-statement and a call to response.failure()

with self.client.get("/", catch_response=True) as response:
    if response.text != "Success":
        response.failure("Got wrong response")
    elif response.elapsed.total_seconds() > 0.5:
        response.failure("Request took too long")

You can also mark a request as successful, even if the response code was bad:

with self.client.get("/does_not_exist/", catch_response=True) as response:
    if response.status_code == 404:
        response.success()

You can even avoid logging a request at all by throwing an exception and then catching it outside the with-block. Or you can throw a locust exception, like in the example below, and let Locust catch it.

from locust.exception import RescheduleTask
...
with self.client.get("/does_not_exist/", catch_response=True) as response:
    if response.status_code == 404:
        raise RescheduleTask()

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 User’s statistics. This can be done by passing a name argument to the HttpSession's different request methods.

Example:

# Statistics for these requests will be grouped under: /blog/?id=[id]
for i in range(10):
    self.client.get("/blog?id=%i" % i, name="/blog?id=[id]")

HTTP Proxy settings

To improve performance, we configure requests to not look for HTTP proxy settings in the environment by setting requests.Session’s trust_env attribute to False. If you don’t want this you can manually set locust_instance.client.trust_env to True. For further details, refer to the documentation of requests.

TaskSets

TaskSets is a way to structure tests of hierarchial web sites/systems.

How to structure your test code

It’s important to remember that the locustfile.py is just an ordinary Python module that is imported by Locust. From this module you’re free to import other python code just as you normally would in any Python program. The current working directory is automatically added to python’s sys.path, so any python file/module/packages that resides in the working directory can be imported using the python import statement.

For small tests, keeping all of the test code in a single locustfile.py should work fine, but for larger test suites, you’ll probably want to split the code into multiple files and directories.

How you structure the test source code is of course entirely up to you, but we recommend that you follow Python best practices. Here’s an example file structure of an imaginary Locust project:

  • Project root

    • common/

      • __init__.py

      • auth.py

      • config.py

    • locustfile.py

    • requirements.txt (External Python dependencies is often kept in a requirements.txt)

A project with multiple different locustfiles could also keep them in a separate subdirectory:

  • Project root

    • common/

      • __init__.py

      • auth.py

      • config.py

    • locustfiles/

      • api.py

      • website.py

    • requirements.txt

With any of the above project structure, your locustfile can import common libraries using:

import common.auth