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)?
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 ===============================
我将添加这些信息，因为我很难弄清楚如何模拟异步api调用。
以下是我模拟异步调用所做的工作。
这是我想测试的函数
async def get_user_info(headers, payload):
return await httpx.AsyncClient().post(URI, json=payload, headers=headers)
您仍然需要MockResponse类
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
添加MockResponseAsync类
class MockResponseAsync:
def __init__(self, json_data, status_code):
self.response = MockResponse(json_data, status_code)
async def getResponse(self):
return self.response
下面是测试。这里重要的是，我之前创建了响应，因为init函数不能是异步的，对getResponse的调用是异步的，所以它都签出了。
@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)
如果你有更好的方法告诉我，不过我觉得这样很干净。
我将演示如何通过将真正的请求与返回相同数据的假请求交换来将编程逻辑与实际的外部库分离。在你看来，如果外部api调用，那么这个过程是最好的
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
