我试图使用python模拟包来模拟python请求模块。让我在下面的场景中工作的基本调用是什么?
在views.py中,我有一个函数,它每次都以不同的响应进行各种request .get()调用
def myview(request):
res1 = requests.get('aurl')
res2 = request.get('burl')
res3 = request.get('curl')
在我的测试类中,我想做类似的事情,但不能确定确切的方法调用
步骤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'
步骤2:
调用我的视图
步骤3:
验证响应包含'a response', 'b response', 'c response'
我如何完成第1步(模拟请求模块)?
使用requests_mock可以很容易地修补任何请求
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)
解决请求的一个可能的方法是使用库betamax,它记录所有的请求,之后如果你在相同的url中使用相同的参数发出请求,betamax将使用记录的请求,我一直在用它来测试网络爬虫,它节省了我很多时间。
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/
目前最简单的方法:
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
尝试使用响应库。以下是他们文档中的一个例子:
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"}'
相比于自己设置所有的mock,它提供了相当好的便利。
还有HTTPretty:
它不是特定于请求库,在某些方面更强大,尽管我发现它不太适合检查它拦截的请求,而响应则很容易
还有httmock。
最近,一个比古老的请求更受欢迎的新库是httpx,它增加了对异步的一等支持。httpx的模拟库是:https://github.com/lundberg/respx
对于那些不想为pytest安装额外库的人,这里有一个例子。我将在这里复制一些扩展,基于上面的例子:
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 ===============================