I am trying to mock a bigtable call in my unit test by declaring fixtures like so:
#pytest.fixture()
def bigtableMock():
bigtableMock = Mock(spec=google.cloud.bigtable.table.Table)
yield bigtableMock
#pytest.fixture()
def bigtableInstanceMock(bigtableMock):
bigtableInstanceMock = Mock(spec=google.cloud.bigtable.instance.Instance)
bigtableInstanceMockAttrs = {'table': bigtableMock}
bigtableInstanceMock.configure_mock(**bigtableInstanceMockAttrs)
yield bigtableInstanceMock
#pytest.fixture()
def myDao(bigtableInstanceMock):
yield MyDao(bigtableInstanceMock)
I mock the read_rows function like so:
def mockReadRowsFuncWith1Dto(testDto):
mockTableRowData = {}
mockTableRowData['columnFamily'] = asDict(testDto)
rowDataMock = MagicMock()
rowDataMock.__iter__.return_value = [mockTableRowData]
rowDataMock.__len__ = 1
def mockReadRowsFunc(startKey, endKey, limit, end_inclusive):
return rowDataMock
return mockReadRowsFunc
When I call my test function:
def test_read_table(
myDao,
testDto,
bigtableMock
):
bigtableMock.read_rows = mockReadRowsFuncWith1Dto(testDto)
samp = bigtableMock.read_rows(
startKey="asdf",
endKey="sadf",
limit=1,
end_inclusive=True
)
print(f"\test data {samp}")
myDao.readTable(...)
Inside myDao.readTable I call read_rows like so:
tableRows: PartialRowData = self.table.read_rows(
start_key=startKey,
end_key=endKey,
limit=10,
end_inclusive=True
)
However, I do not get the magicMock return that I expect inside readTable, tableRows:<Mock name='mock.table().read_rows()' id='4378752480'>, whereas in the test function I can print out the Magic mock: test data <MagicMock id='4413191168'>. Regardless of the print statement or not, I can never invoke the correct mocked read_rows function. What am I doing wrong?
The problem in my case was that the fixture for bigtableMock was different between test_read_table and the fixture for myDao. I modified my test cases to include the table mocking inside the bigtableMock like so:
#pytest.fixture(read_row_data, mock_append_row)
def bigtableMock():
bigtableMock = Mock(spec=google.cloud.bigtable.table.Table)
bigtableMock.read_rows.return_value = [read_row_data]
bigtableMock.append_row.return_value = mock_append_row
yield bigtableMock
I am trying to use Pythons mock package to mock Pythons requests module. What are the basic calls to get me working in below scenario?
In my views.py, I have a function that makes variety of requests.get() calls with different response each time
def myview(request):
res1 = requests.get('aurl')
res2 = request.get('burl')
res3 = request.get('curl')
In my test class I want to do something like this but cannot figure out exact method calls
Step 1:
# Mock the requests module
# when mockedRequests.get('aurl') is called then return 'a response'
# when mockedRequests.get('burl') is called then return 'b response'
# when mockedRequests.get('curl') is called then return 'c response'
Step 2:
Call my view
Step 3:
verify response contains 'a response', 'b response' , 'c response'
How can I complete Step 1 (mocking the requests module)?
This is how you can do it (you can run this file as-is):
import requests
import unittest
from unittest import mock
# This is the class we want to test
class MyGreatClass:
def fetch_json(self, url):
response = requests.get(url)
return response.json()
# This method will be used by the mock to replace requests.get
def mocked_requests_get(*args, **kwargs):
class MockResponse:
def __init__(self, json_data, status_code):
self.json_data = json_data
self.status_code = status_code
def json(self):
return self.json_data
if args[0] == 'http://someurl.com/test.json':
return MockResponse({"key1": "value1"}, 200)
elif args[0] == 'http://someotherurl.com/anothertest.json':
return MockResponse({"key2": "value2"}, 200)
return MockResponse(None, 404)
# Our test case class
class MyGreatClassTestCase(unittest.TestCase):
# We patch 'requests.get' with our own method. The mock object is passed in to our test case method.
#mock.patch('requests.get', side_effect=mocked_requests_get)
def test_fetch(self, mock_get):
# Assert requests.get calls
mgc = MyGreatClass()
json_data = mgc.fetch_json('http://someurl.com/test.json')
self.assertEqual(json_data, {"key1": "value1"})
json_data = mgc.fetch_json('http://someotherurl.com/anothertest.json')
self.assertEqual(json_data, {"key2": "value2"})
json_data = mgc.fetch_json('http://nonexistenturl.com/cantfindme.json')
self.assertIsNone(json_data)
# We can even assert that our mocked method was called with the right parameters
self.assertIn(mock.call('http://someurl.com/test.json'), mock_get.call_args_list)
self.assertIn(mock.call('http://someotherurl.com/anothertest.json'), mock_get.call_args_list)
self.assertEqual(len(mock_get.call_args_list), 3)
if __name__ == '__main__':
unittest.main()
Important Note: If your MyGreatClass class lives in a different package, say my.great.package, you have to mock my.great.package.requests.get instead of just 'request.get'. In that case your test case would look like this:
import unittest
from unittest import mock
from my.great.package import MyGreatClass
# This method will be used by the mock to replace requests.get
def mocked_requests_get(*args, **kwargs):
# Same as above
class MyGreatClassTestCase(unittest.TestCase):
# Now we must patch 'my.great.package.requests.get'
#mock.patch('my.great.package.requests.get', side_effect=mocked_requests_get)
def test_fetch(self, mock_get):
# Same as above
if __name__ == '__main__':
unittest.main()
Enjoy!
Try using the responses library. Here is an example from their documentation:
import responses
import requests
#responses.activate
def test_simple():
responses.add(responses.GET, 'http://twitter.com/api/1/foobar',
json={'error': 'not found'}, status=404)
resp = requests.get('http://twitter.com/api/1/foobar')
assert resp.json() == {"error": "not found"}
assert len(responses.calls) == 1
assert responses.calls[0].request.url == 'http://twitter.com/api/1/foobar'
assert responses.calls[0].response.text == '{"error": "not found"}'
It provides quite a nice convenience over setting up all the mocking yourself.
There's also HTTPretty:
It's not specific to requests library, more powerful in some ways though I found it doesn't lend itself so well to inspecting the requests that it intercepted, which responses does quite easily
There's also httmock.
A new library gaining popularity recently over the venerable requests is httpx, which adds first-class support for async. A mocking library for httpx is: https://github.com/lundberg/respx
Here is what worked for me:
import mock
#mock.patch('requests.get', mock.Mock(side_effect = lambda k:{'aurl': 'a response', 'burl' : 'b response'}.get(k, 'unhandled request %s'%k)))
I used requests-mock for writing tests for separate module:
# module.py
import requests
class A():
def get_response(self, url):
response = requests.get(url)
return response.text
And the tests:
# tests.py
import requests_mock
import unittest
from module import A
class TestAPI(unittest.TestCase):
#requests_mock.mock()
def test_get_response(self, m):
a = A()
m.get('http://aurl.com', text='a response')
self.assertEqual(a.get_response('http://aurl.com'), 'a response')
m.get('http://burl.com', text='b response')
self.assertEqual(a.get_response('http://burl.com'), 'b response')
m.get('http://curl.com', text='c response')
self.assertEqual(a.get_response('http://curl.com'), 'c response')
if __name__ == '__main__':
unittest.main()
this is how you mock requests.post, change it to your http method
#patch.object(requests, 'post')
def your_test_method(self, mockpost):
mockresponse = Mock()
mockpost.return_value = mockresponse
mockresponse.text = 'mock return'
#call your target method now
Here is a solution with requests Response class. It is cleaner IMHO.
import json
from unittest.mock import patch
from requests.models import Response
def mocked_requests_get(*args, **kwargs):
response_content = None
request_url = kwargs.get('url', None)
if request_url == 'aurl':
response_content = json.dumps('a response')
elif request_url == 'burl':
response_content = json.dumps('b response')
elif request_url == 'curl':
response_content = json.dumps('c response')
response = Response()
response.status_code = 200
response._content = str.encode(response_content)
return response
#mock.patch('requests.get', side_effect=mocked_requests_get)
def test_fetch(self, mock_get):
response = requests.get(url='aurl')
assert ...
If you want to mock a fake response, another way to do it is to simply instantiate an instance of the base HttpResponse class, like so:
from django.http.response import HttpResponseBase
self.fake_response = HttpResponseBase()
I started out with Johannes Farhenkrug's answer here and it worked great for me. I needed to mock the requests library because my goal is to isolate my application and not test any 3rd party resources.
Then I read up some more about python's Mock library and I realized that I can replace the MockResponse class, which you might call a 'Test Double' or a 'Fake', with a python Mock class.
The advantage of doing so is access to things like assert_called_with, call_args and so on. No extra libraries are needed. Additional benefits such as 'readability' or 'its more pythonic' are subjective, so they may or may not play a role for you.
Here is my version, updated with using python's Mock instead of a test double:
import json
import requests
from unittest import mock
# defube stubs
AUTH_TOKEN = '{"prop": "value"}'
LIST_OF_WIDGETS = '{"widgets": ["widget1", "widget2"]}'
PURCHASED_WIDGETS = '{"widgets": ["purchased_widget"]}'
# exception class when an unknown URL is mocked
class MockNotSupported(Exception):
pass
# factory method that cranks out the Mocks
def mock_requests_factory(response_stub: str, status_code: int = 200):
return mock.Mock(**{
'json.return_value': json.loads(response_stub),
'text.return_value': response_stub,
'status_code': status_code,
'ok': status_code == 200
})
# side effect mock function
def mock_requests_post(*args, **kwargs):
if args[0].endswith('/api/v1/get_auth_token'):
return mock_requests_factory(AUTH_TOKEN)
elif args[0].endswith('/api/v1/get_widgets'):
return mock_requests_factory(LIST_OF_WIDGETS)
elif args[0].endswith('/api/v1/purchased_widgets'):
return mock_requests_factory(PURCHASED_WIDGETS)
raise MockNotSupported
# patch requests.post and run tests
with mock.patch('requests.post') as requests_post_mock:
requests_post_mock.side_effect = mock_requests_post
response = requests.post('https://myserver/api/v1/get_widgets')
assert response.ok is True
assert response.status_code == 200
assert 'widgets' in response.json()
# now I can also do this
requests_post_mock.assert_called_with('https://myserver/api/v1/get_widgets')
Repl.it links:
https://repl.it/#abkonsta/Using-unittestMock-for-requestspost#main.py
https://repl.it/#abkonsta/Using-test-double-for-requestspost#main.py
This worked for me, although I haven't done much complicated testing yet.
import json
from requests import Response
class MockResponse(Response):
def __init__(self,
url='http://example.com',
headers={'Content-Type':'text/html; charset=UTF-8'},
status_code=200,
reason = 'Success',
_content = 'Some html goes here',
json_ = None,
encoding='UTF-8'
):
self.url = url
self.headers = headers
if json_ and headers['Content-Type'] == 'application/json':
self._content = json.dumps(json_).encode(encoding)
else:
self._content = _content.encode(encoding)
self.status_code = status_code
self.reason = reason
self.encoding = encoding
Then you can create responses :
mock_response = MockResponse(
headers={'Content-Type' :'application/json'},
status_code=401,
json_={'success': False},
reason='Unauthorized'
)
mock_response.raise_for_status()
gives
requests.exceptions.HTTPError: 401 Client Error: Unauthorized for url: http://example.com
One possible way to work around requests is using the library betamax, it records all requests and after that if you make a request in the same url with the same parameters the betamax will use the recorded request, I have been using it to test web crawler and it save me a lot time.
import os
import requests
from betamax import Betamax
from betamax_serializers import pretty_json
WORKERS_DIR = os.path.dirname(os.path.abspath(__file__))
CASSETTES_DIR = os.path.join(WORKERS_DIR, u'resources', u'cassettes')
MATCH_REQUESTS_ON = [u'method', u'uri', u'path', u'query']
Betamax.register_serializer(pretty_json.PrettyJSONSerializer)
with Betamax.configure() as config:
config.cassette_library_dir = CASSETTES_DIR
config.default_cassette_options[u'serialize_with'] = u'prettyjson'
config.default_cassette_options[u'match_requests_on'] = MATCH_REQUESTS_ON
config.default_cassette_options[u'preserve_exact_body_bytes'] = True
class WorkerCertidaoTRT2:
session = requests.session()
def make_request(self, input_json):
with Betamax(self.session) as vcr:
vcr.use_cassette(u'google')
response = session.get('http://www.google.com')
https://betamax.readthedocs.io/en/latest/
Can you use requests-mock instead?
Suppose your myview function instead takes a requests.Session object, makes requests with it, and does something to the output:
# mypackage.py
def myview(session):
res1 = session.get("http://aurl")
res2 = session.get("http://burl")
res3 = session.get("http://curl")
return f"{res1.text}, {res2.text}, {res3.text}"
# test_myview.py
from mypackage import myview
import requests
def test_myview(requests_mock):
# set up requests
a_req = requests_mock.get("http://aurl", text="a response")
b_req = requests_mock.get("http://burl", text="b response")
c_req = requests_mock.get("http://curl", text="c response")
# test myview behaviour
session = requests.Session()
assert myview(session) == "a response, b response, c response"
# check that requests weren't called repeatedly
assert a_req.called_once
assert b_req.called_once
assert c_req.called_once
assert requests_mock.call_count == 3
You can also use requests_mock with frameworks other than Pytest - the documentation is great.
I will add this information since I had a hard time figuring how to mock an async api call.
Here is what I did to mock an async call.
Here is the function I wanted to test
async def get_user_info(headers, payload):
return await httpx.AsyncClient().post(URI, json=payload, headers=headers)
You still need the MockResponse class
class MockResponse:
def __init__(self, json_data, status_code):
self.json_data = json_data
self.status_code = status_code
def json(self):
return self.json_data
You add the MockResponseAsync class
class MockResponseAsync:
def __init__(self, json_data, status_code):
self.response = MockResponse(json_data, status_code)
async def getResponse(self):
return self.response
Here is the test. The important thing here is I create the response before since init function can't be async and the call to getResponse is async so it all checked out.
#pytest.mark.asyncio
#patch('httpx.AsyncClient')
async def test_get_user_info_valid(self, mock_post):
"""test_get_user_info_valid"""
# Given
token_bd = "abc"
username = "bob"
payload = {
'USERNAME': username,
'DBNAME': 'TEST'
}
headers = {
'Authorization': 'Bearer ' + token_bd,
'Content-Type': 'application/json'
}
async_response = MockResponseAsync("", 200)
mock_post.return_value.post.return_value = async_response.getResponse()
# When
await api_bd.get_user_info(headers, payload)
# Then
mock_post.return_value.post.assert_called_once_with(
URI, json=payload, headers=headers)
If you have a better way of doing that tell me but I think it's pretty clean like that.
The simplest way so far:
from unittest import TestCase
from unittest.mock import Mock, patch
from .utils import method_foo
class TestFoo(TestCase):
#patch.object(utils_requests, "post") # change to desired method here
def test_foo(self, mock_requests_post):
# EXPLANATION: mocked 'post' method above will return some built-in mock,
# and its method 'json' will return mock 'mock_data',
# which got argument 'return_value' with our data to be returned
mock_data = Mock(return_value=[{"id": 1}, {"id": 2}])
mock_requests_post.return_value.json = mock_data
method_foo()
# TODO: asserts here
"""
Example of method that you can test in utils.py
"""
def method_foo():
response = requests.post("http://example.com")
records = response.json()
for record in records:
print(record.get("id"))
# do other stuff here
For those, who don't want to install additional libs for pytest, there is an example. I will duplicate it here with some extension, based on examples above:
import datetime
import requests
class MockResponse:
def __init__(self, json_data, status_code):
self.json_data = json_data
self.status_code = status_code
self.elapsed = datetime.timedelta(seconds=1)
# mock json() method always returns a specific testing dictionary
def json(self):
return self.json_data
def test_get_json(monkeypatch):
# Any arguments may be passed and mock_get() will always return our
# mocked object, which only has the .json() method.
def mock_get(*args, **kwargs):
return MockResponse({'mock_key': 'mock_value'}, 418)
# apply the monkeypatch for requests.get to mock_get
monkeypatch.setattr(requests, 'get', mock_get)
# app.get_json, which contains requests.get, uses the monkeypatch
response = requests.get('https://fakeurl')
response_json = response.json()
assert response_json['mock_key'] == 'mock_value'
assert response.status_code == 418
assert response.elapsed.total_seconds() == 1
============================= test session starts ==============================
collecting ... collected 1 item
test_so.py::test_get_json PASSED [100%]
============================== 1 passed in 0.07s ===============================
Using requests_mock is easy to patch any requests
pip install requests-mock
from unittest import TestCase
import requests_mock
from <yourmodule> import <method> (auth)
class TestApi(TestCase):
#requests_mock.Mocker()
def test_01_authentication(self, m):
"""Successful authentication using username password"""
token = 'token'
m.post(f'http://localhost/auth', json= {'token': token})
act_token =auth("user", "pass")
self.assertEqual(act_token, token)
To avoid installing other dependencies you should create a fake response. This FakeResponse could be a child of Response (I think this is a good approach because it's more realistic) or just a simple class with the attributes you need.
Simple Fake class
class FakeResponse:
status_code = None
def __init__(self, *args, **kwargs):
self.status_code = 500
self.text = ""
Child of Response
class FakeResponse(Response):
encoding = False
_content = None
def __init__(*args, **kwargs):
super(FakeResponse).__thisclass__.status_code = 500
# Requests requires to be not be None, if not throws an exception
# For reference: https://github.com/psf/requests/issues/3698#issuecomment-261115119
super(FakeResponse).__thisclass__.raw = io.BytesIO()
Just a helpful hint to those that are still struggling, converting from urllib or urllib2/urllib3 to requests AND trying to mock a response- I was getting a slightly confusing error when implementing my mock:
with requests.get(path, auth=HTTPBasicAuth('user', 'pass'), verify=False) as url:
AttributeError: __enter__
Well, of course, if I knew anything about how with works (I didn't), I'd know it was a vestigial, unnecessary context (from PEP 343). Unnecessary when using the requests library because it does basically the same thing for you under the hood. Just remove the with and use bare requests.get(...) and Bob's your uncle.
For pytest users there is a convinient fixture from https://pypi.org/project/pytest-responsemock/
For example to mock GET to http://some.domain you can:
def test_me(response_mock):
with response_mock('GET http://some.domain -> 200 :Nice'):
response = send_request()
assert result.ok
assert result.content == b'Nice'
I will demonstrate how to detach your programming logic from the actual external library by swapping the real request with a fake one that returns the same data. In your view if external api call then this process is best
import pytest
from unittest.mock import patch
from django.test import RequestFactory
#patch("path(projectname.appname.filename).requests.post")
def test_mock_response(self, mock_get, rf: RequestFactory):
mock_get.return_value.ok = Mock(ok=True)
mock_get.return_value.status_code = 400
mock_get.return_value.json.return_value = {you can define here dummy response}
request = rf.post("test/", data=self.payload)
response = view_name_view(request)
expected_response = {
"success": False,
"status": "unsuccessful",
}
assert response.data == expected_response
assert response.status_code == 400
If using pytest:
>>> import pytest
>>> import requests
>>> def test_url(requests_mock):
... requests_mock.get('http://test.com', text='data')
... assert 'data' == requests.get('http://test.com').text
Taken from the official documentation
I have sample code and test:
def outer():
inner_response = inner(param1)
def inner(something):
queryset_response = something.object.filter(foo="bar",
foo1="bar1") #this should get a reponse when testing.
response_list = []
for count, queryset_res in enumerate(queryset_response):
response_list.append(queryset_response[count].data)
#get response for data in this line.
return response_list
I wanna test this situation using mock and probably return list of queryset using mock if possible.
def setup():
something = mock.Mock()
def test_outer():
# what should be done to the below line work so that
# response_list.append gets some value.
something.objects.filter()[0].data = "some string"
# Also is it possible to return queryset as like shown below.
something.objects.filter().return_value = <queryset> # list of objects in queryset.
i used a mock and returned namedtuple to make it behave like queryset and use (.) dot to access the data set. I could make a class and used it same way.
def test_func():
something = mock.Mock()
key = collections.namedtuple('key', 'data')
response = key('some_string')
something.objects.filter.return_value = [response]
this is kinda mocking django as gloo said, my ex-engineers decided to opt in that way.
You shouldn't be mocking the result of a filter as that would be like unit testing django itself. Instead, you should be testing your own functions that will call Model.object.filter. You can create the objects you will be working with in the setup of your unit test, and assert that when you call your function, the expected result is the same as those objects. For example:
def my_own_function(foo, foo1):
queryset_response = Something.objects.filter(foo=foo, foo1=foo1)
store = queryset_response[0].data
return store
and in your unit test:
def test_my_own_function():
data = "mydata"
sample_obj = Something.objects.create(foo="bar", foo1="bar1", data=data)
result = my_own_function("bar", "bar1")
self.assertEqual(result, data)
How do you write a fixture (a method) that yields/returns parameterized test parameters?
For instance, I have a test as the following:
#pytest.mark.parametrize(
"input,expected",
[("hello", "hello"),
("world", "world")])
def test_get_message(self, input, expected):
assert expected == MyClass.get_message(input)
Instead of having input and expected to be passed via #pytest.mark.parametrize, I am interested in an approach as the following:
#pytest.fixture(scope="session")
def test_messages(self):
# what should I write here to return multiple
# test case with expected value for each?
pass
def test_get_message(self, test_messages):
expected = test_messages["expected"] # somehow extracted from test_messages?
input = test_messages["input"] # somehow extracted from test message?
assert expected == MyClass.get_message(input)
To move the parameters into a fixture, you can use fixture params:
#pytest.fixture(params=[("hello", "hello"),
("world", "world")], scope="session")
def test_messages(self, request):
return request.param
def test_get_message(self, test_messages):
input = test_messages[0]
expected = test_messages[1]
assert expected == MyClass.get_message(input)
You can also put the params into a separate function (same as wih parametrize), e.g.
def get_test_messages():
return [("hello", "hello"), ("world", "world")]
#pytest.fixture(params=get_test_messages(), scope="session")
def test_messages(self, request):
return request.param
To me, it seems you want to return an array of dicts:
#pytest.fixture(scope="session")
def test_messages():
return [
{
"input": "hello",
"expected": "world"
},
{
"input": "hello",
"expected": "hello"
}
]
To use it in a test case, you would need to iterate over the array:
def test_get_message(self, test_messages):
for test_data in test_messages:
input = test_data["input"]
expected = test_data["expected"]
assert input == expected
But I not sure if this is the best approach, because it's still considered as only one test case, and so it will show up as only one test case in the output/report.