Schemathesis is a tool for testing your web applications built with Open API / Swagger specifications.
It reads the application schema and generates test cases which will ensure that your application is compliant with its schema.
The application under test could be written in any language, the only thing you need is a valid API schema in a supported format.
Supported specification versions:
- Swagger 2.0
- Open API 3.0.x
More API specifications will be added in the future.
Built with:
Inspired by wonderful swagger-conformance project.
If you are looking for more information, then there is an article about Schemathesis: https://code.kiwi.com/schemathesis-property-based-testing-for-api-schemas-52811fd2b0a4
To install Schemathesis via pip
run the following command:
pip install schemathesis
Gitter: https://gitter.im/kiwicom/schemathesis
There are two basic ways to use Schemathesis:
CLI is pretty simple to use and requires no coding, in-code approach gives more flexibility.
The schemathesis
command can be used to perform Schemathesis test cases:
schemathesis run https://example.com/api/swagger.json
If your application requires authorization then you can use --auth
option for Basic Auth and --header
to specify
custom headers to be sent with each request.
To filter your tests by endpoint name, HTTP method or Open API tags you could use -E
, -M
, -T
options respectively.
CLI supports passing options to hypothesis.settings
. All of them are prefixed with --hypothesis-
:
schemathesis run --hypothesis-max-examples=1000 https://example.com/api/swagger.json
To speed up the testing process Schemathesis provides -w/--workers
option for concurrent test execution:
schemathesis run -w 8 https://example.com/api/swagger.json
In the example above all tests will be distributed among 8 worker threads.
If you'd like to test your web app (Flask or AioHTTP for example) then there is --app
option for you:
schemathesis run --app=importable.path:app /swagger.json
You need to specify an importable path to the module where your app instance resides and a variable name after :
that points
to your app. Note, app factories are not supported. The schema location could be:
- A full URL;
- An existing filesystem path;
- In-app endpoint with schema.
This method is significantly faster for WSGI apps, since it doesn't involve network.
For the full list of options, run:
schemathesis --help
# Or
schemathesis run --help
Schemathesis CLI also available as a docker image
docker run kiwicom/schemathesis:stable run http://example.com/schema.json
To run it against localhost server add --network=host
parameter:
docker run --network="host" kiwicom/schemathesis:stable run http://127.0.0.1/schema.json
Sometimes you need to execute custom code before the CLI run, for example setup an environment,
register custom string format strategies or modify Schemathesis behavior in runtime you can use --pre-run
hook:
schemathesis --pre-run importable.path.to.module run https://example.com/api/swagger.json
NOTE. This option should be passed before the run
part.
The passed value will be processed as an importable Python path, where you can execute your code. An example - https://github.com/kiwicom/schemathesis#custom-string-strategies
To add a new check for the Schemathesis CLI there is a special function
import schemathesis
@schemathesis.register_check
def new_check(response, case):
# some awesome assertions!
pass
The registered check should accept a response
with requests.Response
/ schemathesis.utils.WSGIResponse
type and
case
with schemathesis.models.Case
type.
After registration, your checks will be available in Schemathesis CLI and you can use them via -c
command line option.
schemathesis --pre-run module.with.checks run -c new_check https://example.com/api/swagger.json
To examine your application with Schemathesis you need to:
- Setup & run your application, so it is accessible via the network;
- Write a couple of tests in Python;
- Run the tests via
pytest
.
Suppose you have your application running on http://0.0.0.0:8080
and its
schema is available at http://0.0.0.0:8080/swagger.json
.
A basic test, that will verify that any data, that fit into the schema will not cause any internal server error could look like this:
# test_api.py
import requests
import schemathesis
schema = schemathesis.from_uri("http://0.0.0.0:8080/swagger.json")
@schema.parametrize()
def test_no_server_errors(case):
# `requests` will make an appropriate call under the hood
response = case.call() # use `call_wsgi` if you used `schemathesis.from_wsgi`
# You could use built-in checks
case.validate_response(response)
# Or assert the response manually
assert response.status_code < 500
It consists of four main parts:
- Schema preparation;
schemathesis
package provides multiple ways to initialize the schema -from_path
,from_dict
,from_uri
,from_file
andfrom_wsgi
. - Test parametrization;
@schema.parametrize()
generates separate tests for all endpoint/method combination available in the schema. - A network call to the running application;
case.call
does it. - Verifying a property you'd like to test; In the example, we verify that any app response will not indicate a server-side error (HTTP codes 5xx).
NOTE. Look for from_wsgi
usage below
Run the tests:
pytest test_api.py
Other properties that could be tested:
- Any call will be processed in <50 ms - you can verify the app performance;
- Any unauthorized access will end with 401 HTTP response code;
Each test function should have the case
fixture, that represents a single test case.
Important Case
attributes:
method
- HTTP methodformatted_path
- full endpoint pathheaders
- HTTP headersquery
- query parametersbody
- request body
You can use them manually in network calls or can convert to a dictionary acceptable by requests.request
:
import requests
schema = schemathesis.from_uri("http://0.0.0.0:8080/swagger.json")
@schema.parametrize()
def test_no_server_errors(case):
kwargs = case.as_requests_kwargs()
response = requests.request(**kwargs)
For each test, Schemathesis will generate a bunch of random inputs acceptable by the schema. This data could be used to verify that your application works in the way as described in the schema or that schema describes expected behavior.
By default, there will be 100 test cases per endpoint/method combination.
To limit the number of examples you could use hypothesis.settings
decorator on your test functions:
from hypothesis import settings
@schema.parametrize()
@settings(max_examples=5)
def test_something(client, case):
...
To narrow down the scope of the schemathesis tests it is possible to filter by method or endpoint:
@schema.parametrize(method="GET", endpoint="/pet")
def test_no_server_errors(case):
...
The acceptable values are regexps or list of regexps (matched with re.search
).
Schemathesis supports making calls to WSGI-compliant applications instead of real network calls, in this case the test execution will go much faster.
app = Flask("test_app")
@app.route("/schema.json")
def schema():
return {...}
@app.route("/v1/users", methods=["GET"])
def users():
return jsonify([{"name": "Robin"}])
schema = schemathesis.from_wsgi("/schema.json", app)
@schema.parametrize()
def test_no_server_errors(case):
response = case.call_wsgi()
assert response.status_code < 500
If the schema contains parameters examples, then they will be additionally included in the generated cases.
paths:
get:
parameters:
- in: body
name: body
required: true
schema: '#/definitions/Pet'
definitions:
Pet:
additionalProperties: false
example:
name: Doggo
properties:
name:
type: string
required:
- name
type: object
With this Swagger schema example, there will be a case with body {"name": "Doggo"}
. Examples handled with
example
decorator from Hypothesis, more info about its behavior is here.
If you'd like to test only examples provided in the schema, you could utilize --hypothesis-phases=explicit
CLI option:
$ schemathesis run --hypothesis-phases=explicit https://example.com/api/swagger.json
Or add this decorator to your test if you use Schemathesis in your Python tests:
from hypothesis import settings, Phase
...
@schema.parametrize()
@settings(phases=[Phase.explicit])
def test_api(case):
...
NOTE. Schemathesis does not support examples in individual properties that are specified inside Schema Object. But examples in Parameter Object, Media Type Object and Schema Object are supported. See below:
...
paths:
/users:
parameters:
- in: query
name: foo
example: bar # SUPPORTED!
schema:
type: string
example: spam # SUPPORTED!
post:
requestBody:
content:
application/json:
schema:
type: object
properties:
foo:
type: string
example: bar # NOT SUPPORTED!
For convenience you can explore the schemas and strategies manually:
>>> import schemathesis
>>> schema = schemathesis.from_uri("http://0.0.0.0:8080/petstore.json")
>>> endpoint = schema["/v2/pet"]["POST"]
>>> strategy = endpoint.as_strategy()
>>> strategy.example()
Case(
path='/v2/pet',
method='POST',
path_parameters={},
headers={},
cookies={},
query={},
body={
'name': '\x15.\x13\U0008f42a',
'photoUrls': ['\x08\U0009f29a', '\U000abfd6\U000427c4', '']
},
form_data={}
)
Schema instances implement Mapping
protocol.
If you want to customize how data is generated, then you can use hooks of two types:
- Global, which are applied to all schemas;
- Schema-local, which are applied only for specific schema instance;
Each hook accepts a Hypothesis strategy and should return a Hypothesis strategy:
import schemathesis
def global_hook(strategy):
return strategy.filter(lambda x: x["id"].isdigit())
schemathesis.hooks.register("query", hook)
schema = schemathesis.from_uri("http://0.0.0.0:8080/swagger.json")
def schema_hook(strategy):
return strategy.filter(lambda x: int(x["id"]) % 2 == 0)
schema.register_hook("query", schema_hook)
There are 6 places, where hooks can be applied and you need to pass it as the first argument to schemathesis.hooks.register
or schema.register_hook
:
- path_parameters
- headers
- cookies
- query
- body
- form_data
It might be useful if you want to exclude certain cases that you don't want to test, or modify the generated data, so it will be more meaningful for the application - add existing IDs from the database, custom auth header, etc.
NOTE. Global hooks are applied first.
If you have a schema that is not available when the tests are collected, for example it is build with tools
like apispec
and requires an application instance available, then you can parametrize the tests from a pytest fixture.
# test_api.py
import schemathesis
schema = schemathesis.from_pytest_fixture("fixture_name")
@schema.parametrize()
def test_api(case):
...
In this case the test body will be used as a sub-test via pytest-subtests
library.
NOTE: the used fixture should return a valid schema that could be created via schemathesis.from_dict
or other
schemathesis.from_
variations.
If you're looking for a way to extend schemathesis
or reuse it in your own application, then runner
module might be helpful for you.
It can run tests against the given schema URI and will do some simple checks for you.
from schemathesis import runner
events = runner.prepare("http://127.0.0.1:8080/swagger.json")
for event in events:
# do something with event
runner.prepare
creates a generator that yields events of different kinds - BeforeExecution
, AfterExecution
, etc.
They provide a lot of useful information about what happens during tests, but handling of these events is your responsibility.
You can take some inspiration from Schemathesis CLI implementation.
See full description of events in the source code.
If you want to use Schemathesis CLI with your custom checks, look at this section
The built-in checks list includes the following:
- Not a server error. Asserts that response's status code is less than 500;
- Status code conformance. Asserts that response's status code is listed in the schema;
- Content type conformance. Asserts that response's content type is listed in the schema;
- Response schema conformance. Asserts that response's content conforms to the declared schema;
You can provide your custom checks to the execute function, the check is a callable that accepts one argument of requests.Response
type.
from datetime import timedelta
from schemathesis import runner, models
def not_too_long(response, case: models.Case):
assert response.elapsed < timedelta(milliseconds=300)
events = runner.prepare("http://127.0.0.1:8080/swagger.json", checks=[not_too_long])
for event in events:
# do something with event
Some string fields could use custom format and validators,
e.g. card_number
and Luhn algorithm validator.
For such cases it is possible to register custom strategies:
- Create
hypothesis.strategies.SearchStrategy
object - Optionally provide predicate function to filter values
- Register it via
schemathesis.register_string_format
strategy = strategies.from_regex(r"\A4[0-9]{15}\Z").filter(luhn_validator)
schemathesis.register_string_format("visa_cards", strategy)
Schemathesis supports Python's built-in unittest
framework out of the box,
you only need to specify strategies for hypothesis.given
:
from unittest import TestCase
from hypothesis import given
import schemathesis
schema = schemathesis.from_uri("http://0.0.0.0:8080/petstore.json")
new_pet_strategy = schema["/v2/pet"]["POST"].as_strategy()
class TestSchema(TestCase):
@given(case=new_pet_strategy)
def test_pets(self, case):
response = case.call()
assert response.status_code < 500
To avoid obscure and hard to debug errors during test runs Schemathesis validates input schemas for conformance with the relevant spec.
If you'd like to disable this behavior use --validate-schema=false
in CLI and validate_schema=False
argument in loaders.
For the full documentation, please see https://schemathesis.readthedocs.io/en/latest/ (WIP)
Or you can look at the docs/
directory in the repository.
First, you need to prepare a virtual environment with poetry.
Install poetry
(check out the installation guide) and run this command inside the project root:
poetry install
For simpler local development Schemathesis includes a aiohttp
-based server with the following endpoints in Swagger 2.0 schema:
/api/success
- always returns{"success": true}
/api/failure
- always returns 500/api/slow
- always returns{"slow": true}
after 250 ms delay/api/unsatisfiable
- parameters for this endpoint are impossible to generate/api/invalid
- invalid parameter definition. Usesint
instead ofinteger
/api/flaky
- returns 1/1 ratio of 200/500 responses/api/multipart
- accepts multipart data/api/teapot
- returns 418 status code, that is not listed in the schema/api/text
- returnsplain/text
responses, which are not declared in the schema/api/malformed_json
- returns malformed JSON withapplication/json
content type header
To start the server:
./test_server.sh 8081
It is possible to configure available endpoints via --endpoints
option.
The value is expected to be a comma separated string with endpoint names (success
, failure
, slow
, etc):
./test_server.sh 8081 --endpoints=success,slow
Then you could use CLI against this server:
schemathesis run http://127.0.0.1:8081/swagger.yaml
================================== Schemathesis test session starts =================================
platform Linux -- Python 3.7.4, schemathesis-0.12.2, hypothesis-4.39.0, hypothesis_jsonschema-0.9.8
rootdir: /
hypothesis profile 'default' -> database=DirectoryBasedExampleDatabase('/.hypothesis/examples')
Schema location: http://127.0.0.1:8081/swagger.yaml
Base URL: http://127.0.0.1:8081
Specification version: Swagger 2.0
collected endpoints: 2
GET /api/slow . [ 50%]
GET /api/success . [100%]
============================================== SUMMARY ==============================================
not_a_server_error 2 / 2 passed PASSED
========================================= 2 passed in 0.29s =========================================
You could run tests via tox
:
tox -p all -o
or pytest
in your current environment:
pytest test/ -n auto
Any contribution in development, testing or any other area is highly appreciated and useful to the project.
Please, see the CONTRIBUTING.rst file for more details.
Schemathesis supports Python 3.6, 3.7 and 3.8.
The code in this project is licensed under MIT license.
By contributing to schemathesis
, you agree that your contributions
will be licensed under its MIT license.