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)?


当前回答

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)

其他回答

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 ===============================

如果你想模拟一个假响应,另一种方法是简单地实例化一个基本HttpResponse类的实例,如下所示:

from django.http.response import HttpResponseBase

self.fake_response = HttpResponseBase()