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Python单元测试的9个技巧

转载 作者：qq735679552 更新时间：2022-09-28 22:32:09 37 4
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前言

requests是python知名的http爬虫库，同样简单易用，是python开源项目的TOP10.

pytest是python的单元测试框架，简单易用，在很多知名项目中应用。requests是python知名的http爬虫库，同样简单易用，是python开源项目的TOP10。关于这2个项目，之前都有过介绍，本文主要介绍requests项目如何使用pytest进行单元测试，会达到下面3个目标:

  • 熟练pytest的使用
  • 学习如何对项目进行单元测试
  • 深入requests的一些实现细节

本文分如下几个部分

  • requests项目单元测试状况
  • 简单工具类如何测试
  • request-api如何测试
  • 底层API测试

1、requests项目单元测试状况

requests的单元测试代码全部在 tests 目录，使用 pytest.ini 进行配置。测试除pytest外，还需要安装

  。

库名 描述
httpbin 一个使用flask实现的http服务，可以客户端定义http响应，主要用于测试http协议
pytest-httpbin pytest的插件，封装httpbin的实现
pytest-mock pytest的插件，提供mock
pytest-cov pytest的插件，提供覆盖率

  。

上述依赖 master 版本在requirement-dev文件中定义;2.24.0版本会在pipenv中定义.

测试用例使用make命令，子命令在Makefile中定义, 使用make ci运行所有单元测试结果如下

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$ make ci
pytest tests - - junitxml = report.xml
= = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = test session starts = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = =
platform linux - - Python 3.6 . 8 , pytest - 3.10 . 1 , py - 1.10 . 0 , pluggy - 0.13 . 1
rootdir: / home / work6 / project / requests, inifile: pytest.ini
plugins: mock - 2.0 . 0 , httpbin - 1.0 . 0 , cov - 2.9 . 0
collected 552 items                                                                                                                                                                                                               
 
tests / test_help.py ...                                                                                                                                                                                                      [  0 % ]
tests / test_hooks.py ...                                                                                                                                                                                                     [  1 % ]
tests / test_lowlevel.py ...............                                                                                                                                                                                      [  3 % ]
tests / test_packages.py ...                                                                                                                                                                                                  [  4 % ]
tests / test_requests.py .................................................................................................................................................................................................... [ 39 % ]
127.0 . 0.1 - - [ 10 / Aug / 2021 08 : 41 : 53 ] "GET /stream/4 HTTP/1.1" 200 756
. 127.0 . 0.1 - - [ 10 / Aug / 2021 08 : 41 : 53 ] "GET /stream/4 HTTP/1.1" 500 59
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Exception happened during processing of request from ( '127.0.0.1' , 46048 )
Traceback (most recent call last):
   File "/usr/lib64/python3.6/wsgiref/handlers.py" , line 138 , in run
     self .finish_response()
x.........................................................................................                                                                                                                                 [ 56 % ]
tests / test_structures.py ....................                                                                                                                                                                               [ 59 % ]
tests / test_testserver.py ......s....                                                                                                                                                                                        [ 61 % ]
tests / test_utils.py ..s................................................................................................................................................................................................ssss [ 98 % ]
ssssss.....                                                                                                                                                                                                                 [ 100 % ]
 
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - generated xml file : / home / work6 / project / requests / report.xml - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
= = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = 539 passed, 12 skipped, 1 xfailed in 64.16 seconds = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = =

可以看到requests在1分钟内，总共通过了539个测试用例，效果还是不错。使用 make coverage 查看单元测试覆盖率

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$ make coverage
- - - - - - - - - - - coverage: platform linux, python 3.6 . 8 - final - 0 - - - - - - - - - - -
Name                          Stmts   Miss  Cover
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
requests / __init__.py             71     71     0 %
requests / __version__.py          10     10     0 %
requests / _internal_utils.py      16      5    69 %
requests / adapters.py            222     67    70 %
requests / api.py                  20     13    35 %
requests / auth.py                174     54    69 %
requests / certs.py                 4      4     0 %
requests / compat.py               47     47     0 %
requests / cookies.py             238    115    52 %
requests / exceptions.py           35     29    17 %
requests / help .py                 63     19    70 %
requests / hooks.py                15      4    73 %
requests / models.py              455    119    74 %
requests / packages.py             16     16     0 %
requests / sessions.py            283     67    76 %
requests / status_codes.py         15     15     0 %
requests / structures.py           40     19    52 %
requests / utils.py               465    170    63 %
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
TOTAL                          2189    844    61 %
Coverage XML written to file coverage.xml

结果显示requests项目总体覆盖率61%，每个模块的覆盖率也清晰可见.

单元测试覆盖率使用代码行数进行判断，Stmts显示模块的有效行数，Miss显示未执行到的行。如果生成html的报告，还可以定位到具体未覆盖到的行;pycharm的coverage也有类似功能.

tests下的文件及测试类如下表

  。

文件 描述
compat python2和python3兼容
conftest pytest配置
test_help,test_packages,test_hooks,test_structures 简单测试类
utils.py 工具函数
test_utils 测试工具函数
test_requests 测试requests
testserver\server 模拟服务
test_testserver 模拟服务测试
test_lowlevel 使用模拟服务测试模拟网络测试

  。

2、简单工具类如何测试

2.1 test_help 实现分析

先从最简单的test_help上手，测试类和被测试对象命名是对应的。先看看被测试的模块help.py。这个模块主要是2个函数 info 和 _implementation

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import idna
 
def _implementation():
     ...
     
def info():
     ...
     system_ssl = ssl.OPENSSL_VERSION_NUMBER
     system_ssl_info = {
         'version' : '%x' % system_ssl if system_ssl is not None else ''
     }
     idna_info = {
         'version' : getattr (idna, '__version__' , ''),
     }
     ...
     return {
         'platform' : platform_info,
         'implementation' : implementation_info,
         'system_ssl' : system_ssl_info,
         'using_pyopenssl' : pyopenssl is not None ,
         'pyOpenSSL' : pyopenssl_info,
         'urllib3' : urllib3_info,
         'chardet' : chardet_info,
         'cryptography' : cryptography_info,
         'idna' : idna_info,
         'requests' : {
             'version' : requests_version,
         },
     }

info提供系统环境的信息， _implementation是其内部实现，以下划线*_*开头。再看测试类test_help

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from requests. help import info
 
def test_system_ssl():
     """Verify we're actually setting system_ssl when it should be available."""
     assert info()[ 'system_ssl' ][ 'version' ] ! = ''
 
class VersionedPackage( object ):
     def __init__( self , version):
         self .__version__ = version
 
def test_idna_without_version_attribute(mocker):
     """Older versions of IDNA don't provide a __version__ attribute, verify
     that if we have such a package, we don't blow up.
     """
     mocker.patch( 'requests.help.idna' , new = None )
     assert info()[ 'idna' ] = = { 'version' : ''}
 
def test_idna_with_version_attribute(mocker):
     """Verify we're actually setting idna version when it should be available."""
     mocker.patch( 'requests.help.idna' , new = VersionedPackage( '2.6' ))
     assert info()[ 'idna' ] = = { 'version' : '2.6' }

首先从头部的导入信息可以看到，仅仅对info函数进行测试，这个容易理解。info测试通过，自然覆盖到_implementation这个内部函数。这里可以得到单元测试的第1个技巧:仅对public的接口进行测试 。

test_idna_without_version_attribute和test_idna_with_version_attribute均有一个mocker参数，这是pytest-mock提供的功能，会自动注入一个mock实现。使用这个mock对idna模块进行模拟 。

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# 模拟空实现
mocker.patch( 'requests.help.idna' , new = None )
# 模拟版本2.6
mocker.patch( 'requests.help.idna' , new = VersionedPackage( '2.6' ))

可能大家会比较奇怪，这里patch模拟的是 requests.help.idna , 而我们在help中导入的是 inda 模块。这是因为在requests.packages中对inda进行了模块名重定向

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for package in ( 'urllib3' , 'idna' , 'chardet' ):
     locals ()[package] = __import__ (package)
     # This traversal is apparently necessary such that the identities are
     # preserved (requests.packages.urllib3.* is urllib3.*)
     for mod in list (sys.modules):
         if mod = = package or mod.startswith(package + '.' ):
             sys.modules[ 'requests.packages.' + mod] = sys.modules[mod]

使用mocker后，idna的__version__信息就可以进行控制，这样info中的idna结果也就可以预期。那么可以得到第2个技巧:使用mock辅助单元测试 。

2.2 test_hooks 实现分析

我们继续查看hooks如何进行测试

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from requests import hooks
 
def hook(value):
     return value[ 1 :]
 
@pytest .mark.parametrize(
     'hooks_list, result' , (
         (hook, 'ata' ),
         ([hook, lambda x: None , hook], 'ta' ),
     )
)
def test_hooks(hooks_list, result):
     assert hooks.dispatch_hook( 'response' , { 'response' : hooks_list}, 'Data' ) = = result
 
def test_default_hooks():
     assert hooks.default_hooks() = = { 'response' : []}

hooks模块的2个接口default_hooks和dispatch_hook都进行了测试。其中default_hooks是纯函数，无参数有返回值，这种函数最容易测试，仅仅检查返回值是否符合预期即可。dispatch_hook会复杂一些，还涉及对回调函数(hook函数)的调用

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def dispatch_hook(key, hooks, hook_data, * * kwargs):
     """Dispatches a hook dictionary on a given piece of data."""
     hooks = hooks or {}
     hooks = hooks.get(key)
     if hooks:
         # 判断钩子函数
         if hasattr (hooks, '__call__' ):
             hooks = [hooks]
         for hook in hooks:
             _hook_data = hook(hook_data, * * kwargs)
             if _hook_data is not None :
                 hook_data = _hook_data
     return hook_data

pytest.mark.parametrize提供了2组参数进行测试。第一组参数hook和ata很简单，hook是一个函数，会对参数裁剪，去掉首位，ata是期望的返回值。test_hooks的response的参数是Data，所以结果应该是ata。第二组参数中的第一个参数会复杂一些，变成了一个数组，首位还是hook函数，中间使用一个匿名函数，匿名函数没有返回值，这样覆盖到 if _hook_data is not None: 的旁路分支。执行过程如下

  • hook函数裁剪Data首位，剩余ata
  • 匿名函数不对结果修改，剩余ata
  • hook函数继续裁剪ata首位，剩余ta

经过测试可以发现dispatch_hook的设计十分巧妙，使用pipeline模式，将所有的钩子串起来，这是和事件机制不一样的地方。细心的话，我们可以发现 if hooks: 并未进行旁路测试，这个不够严谨，有违我们的第3个技巧

测试尽可能覆盖目标函数的所有分支 。

2.3 test_structures 实现分析

LookupDict的测试用例如下

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class TestLookupDict:
 
     @pytest .fixture(autouse = True )
     def setup( self ):
         """LookupDict instance with "bad_gateway" attribute."""
         self .lookup_dict = LookupDict( 'test' )
         self .lookup_dict.bad_gateway = 502
 
     def test_repr( self ):
         assert repr ( self .lookup_dict) = = "<lookup 'test'>"
 
     get_item_parameters = pytest.mark.parametrize(
         'key, value' , (
             ( 'bad_gateway' , 502 ),
             ( 'not_a_key' , None )
         )
     )
 
     @get_item_parameters
     def test_getitem( self , key, value):
         assert self .lookup_dict[key] = = value
 
     @get_item_parameters
     def test_get( self , key, value):
         assert self .lookup_dict.get(key) = = value

可以发现使用setup方法配合@pytest.fixture，给所有测试用例初始化了一个lookup_dict对象;同时pytest.mark.parametrize可以在不同的测试用例之间复用的，我们可以得到第4个技巧

使用pytest.fixture复用被测试对象，使用pytest.mark.parametriz复用测试参数 。

通过TestLookupDict的test_getitem和test_get可以更直观的了解LookupDict的get和__getitem__方法的作用

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class LookupDict( dict ):
     ...
     def __getitem__( self , key):
         # We allow fall-through here, so values default to None
         return self .__dict__.get(key, None )
 
     def get( self , key, default = None ):
         return self .__dict__.get(key, default)
  • get自定义字典，使其可以使用 get 方法获取值
  • __getitem__自定义字典，使其可以使用 [] 符合获取值

CaseInsensitiveDict的测试用例在test_structures和test_requests中都有测试，前者主要是基础测试，后者偏向业务使用层面，我们可以看到这两种差异:

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class TestCaseInsensitiveDict:
 
# 类测试
 
def test_repr( self ):
 
assert repr ( self .case_insensitive_dict) = = "{'Accept': 'application/json'}"
 
def test_copy( self ):
 
copy = self .case_insensitive_dict.copy()
 
assert copy is not self .case_insensitive_dict
 
assert copy = = self .case_insensitive_dict
 
class TestCaseInsensitiveDict:
 
# 使用方法测试
 
def test_delitem( self ):
 
cid = CaseInsensitiveDict()
 
cid[ 'Spam' ] = 'someval'
 
del cid[ 'sPam' ]
 
assert 'spam' not in cid
 
assert len (cid) = = 0
 
def test_contains( self ):
 
cid = CaseInsensitiveDict()
 
cid[ 'Spam' ] = 'someval'
 
assert 'Spam' in cid
 
assert 'spam' in cid
 
assert 'SPAM' in cid
 
assert 'sPam' in cid
 
assert 'notspam' not in cid

借鉴上面的测试方法，不难得出第5个技巧

可以从不同的层面对同一个对象进行单元测试 。

后面的test_lowlevel和test_requests也应用了这种技巧 。

2.4 utils.py

utils中构建了一个可以写入env的生成器(由yield关键字提供)，可以当上下文装饰器使用

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import contextlib
 
import os
 
@contextlib .contextmanager
 
def override_environ( * * kwargs):
 
save_env = dict (os.environ)
 
for key, value in kwargs.items():
 
if value is None :
 
del os.environ[key]
 
else :
 
os.environ[key] = value
 
try :
 
yield
 
finally :
 
os.environ.clear()
 
os.environ.update(save_env)

下面是使用方法示例

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# test_requests.py
 
kwargs = {
 
var: proxy
 
}
 
# 模拟控制proxy环境变量
 
with override_environ( * * kwargs):
 
proxies = session.rebuild_proxies(prep, {})
 
def rebuild_proxies( self , prepared_request, proxies):
 
bypass_proxy = should_bypass_proxies(url, no_proxy = no_proxy)
 
def should_bypass_proxies(url, no_proxy):
 
...
 
get_proxy = lambda k: os.environ.get(k) or os.environ.get(k.upper())
 
...

得出第6个技巧：涉及环境变量的地方，可以使用上下文装饰器进行模拟多种环境变量 。

2.5 utils测试用例

utils的测试用例较多，我们选择部分进行分析。先看to_key_val_list函数

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# 对象转列表
 
def to_key_val_list(value):
 
if value is None :
 
return None
 
if isinstance (value, ( str , bytes, bool , int )):
 
raise ValueError( 'cannot encode objects that are not 2-tuples' )
 
if isinstance (value, Mapping):
 
value = value.items()
 
return list (value)

对应的测试用例TestToKeyValList

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class TestToKeyValList:
 
@pytest .mark.parametrize(
 
'value, expected' , (
 
([( 'key' , 'val' )], [( 'key' , 'val' )]),
 
((( 'key' , 'val' ), ), [( 'key' , 'val' )]),
 
({ 'key' : 'val' }, [( 'key' , 'val' )]),
 
( None , None )
 
))
 
def test_valid( self , value, expected):
 
assert to_key_val_list(value) = = expected
 
def test_invalid( self ):
 
with pytest.raises(ValueError):
 
to_key_val_list( 'string' )

重点是test_invalid中使用pytest.raise对异常的处理

第7个技巧：使用pytest.raises对异常进行捕获处理 。

TestSuperLen介绍了几种进行IO模拟测试的方法

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class TestSuperLen:
 
@pytest .mark.parametrize(
 
'stream, value' , (
 
(StringIO.StringIO, 'Test' ),
 
(BytesIO, b 'Test' ),
 
pytest.param(cStringIO, 'Test' ,
 
marks = pytest.mark.skipif( 'cStringIO is None' )),
 
))
 
def test_io_streams( self , stream, value):
 
"""Ensures that we properly deal with different kinds of IO streams."""
 
assert super_len(stream()) = = 0
 
assert super_len(stream(value)) = = 4
 
def test_super_len_correctly_calculates_len_of_partially_read_file( self ):
 
"""Ensure that we handle partially consumed file like objects."""
 
s = StringIO.StringIO()
 
s.write( 'foobarbogus' )
 
assert super_len(s) = = 0
 
@pytest .mark.parametrize(
 
'mode, warnings_num' , (
 
( 'r' , 1 ),
 
( 'rb' , 0 ),
 
))
 
def test_file( self , tmpdir, mode, warnings_num, recwarn):
 
file_obj = tmpdir.join( 'test.txt' )
 
file_obj.write( 'Test' )
 
with file_obj. open (mode) as fd:
 
assert super_len(fd) = = 4
 
assert len (recwarn) = = warnings_num
 
def test_super_len_with_tell( self ):
 
foo = StringIO.StringIO( '12345' )
 
assert super_len(foo) = = 5
 
foo.read( 2 )
 
assert super_len(foo) = = 3
 
def test_super_len_with_fileno( self ):
 
with open (__file__, 'rb' ) as f:
 
length = super_len(f)
 
file_data = f.read()
 
assert length = = len (file_data)

使用StringIO来模拟IO操作，可以配置各种IO的测试。当然也可以使用BytesIO/cStringIO, 不过单元测试用例一般不关注性能，StringIO简单够用.

pytest提供tmpdir的fixture，可以进行文件读写操作测试 。

可以使用__file__来进行文件的只读测试，__file__表示当前文件，不会产生副作用.

第8个技巧：使用IO模拟配合进行单元测试 。

2.6 request-api如何测试

requests的测试需要httpbin和pytest-httpbin，前者会启动一个本地服务，后者会安装一个pytest插件，测试用例中可以得到httpbin的fixture，用来操作这个服务的URL.

  。

类 功能
TestRequests requests业务测试
TestCaseInsensitiveDict 大小写不敏感的字典测试
TestMorselToCookieExpires cookie过期测试
TestMorselToCookieMaxAge cookie大小
TestTimeout 响应超时的测试
TestPreparingURLs URL预处理
... 一些零碎的测试用例

  。

坦率的讲：这个测试用例内容庞大，达到2500行。看起来是针对各种业务的零散case，我并没有完全理顺其组织逻辑。我选择一些感兴趣的业务进行介绍, 先看TimeOut的测试

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TARPIT = 'http://10.255.255.1'
 
class TestTimeout:
 
def test_stream_timeout( self , httpbin):
 
try :
 
requests.get(httpbin( 'delay/10' ), timeout = 2.0 )
 
except requests.exceptions.Timeout as e:
 
assert 'Read timed out' in e.args[ 0 ].args[ 0 ]
 
@pytest .mark.parametrize(
 
'timeout' , (
 
( 0.1 , None ),
 
Urllib3Timeout(connect = 0.1 , read = None )
 
))
 
def test_connect_timeout( self , timeout):
 
try :
 
requests.get(TARPIT, timeout = timeout)
 
pytest.fail( 'The connect() request should time out.' )
 
except ConnectTimeout as e:
 
assert isinstance (e, ConnectionError)
 
assert isinstance (e, Timeout)

test_stream_timeout利用httpbin创建了一个延迟10s响应的接口，然后请求本身设置成2s，这样可以收到一个本地timeout的错误。test_connect_timeout则是访问一个不存在的服务，捕获连接超时的错误.

TestRequests都是对requests的业务进程测试，可以看到至少是2种

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class TestRequests:
 
def test_basic_building( self ):
 
req = requests.Request()
 
req.url = 'http://kennethreitz.org/'
 
req.data = { 'life' : '42' }
 
pr = req.prepare()
 
assert pr.url = = req.url
 
assert pr.body = = 'life=42'
 
def test_path_is_not_double_encoded( self ):
 
request = requests.Request( 'GET' , "http://0.0.0.0/get/test case" ).prepare()
 
assert request.path_url = = ' / get / test % 20case
 
...
 
def test_HTTP_200_OK_GET_ALTERNATIVE( self , httpbin):
 
r = requests.Request( 'GET' , httpbin( 'get' ))
 
s = requests.Session()
 
s.proxies = getproxies()
 
r = s.send(r.prepare())
 
assert r.status_code = = 200
 
ef test_set_cookie_on_301( self , httpbin):
 
s = requests.session()
 
url = httpbin( 'cookies/set?foo=bar' )
 
s.get(url)
 
assert s.cookies[ 'foo' ] = = 'bar'
  • 对url进行校验，只需要对request进行prepare，这种情况下，请求并未发送，少了网络传输，测试用例会更迅速
  • 需要响应数据的情况，需要使用httbin构建真实的请求-响应数据

3、底层API测试

testserver构建一个简单的基于线程的tcp服务，这个tcp服务具有__enter__和__exit__方法，还可以当一个上下文环境使用.

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class TestTestServer:
 
def test_basic( self ):
 
"""messages are sent and received properly"""
 
question = b "success?"
 
answer = b "yeah, success"
 
def handler(sock):
 
text = sock.recv( 1000 )
 
assert text = = question
 
sock.sendall(answer)
 
with Server(handler) as (host, port):
 
sock = socket.socket()
 
sock.connect((host, port))
 
sock.sendall(question)
 
text = sock.recv( 1000 )
 
assert text = = answer
 
sock.close()
 
def test_text_response( self ):
 
"""the text_response_server sends the given text"""
 
server = Server.text_response_server(
 
"HTTP/1.1 200 OK\r\n" +
 
"Content-Length: 6\r\n" +
 
"\r\nroflol"
 
)
 
with server as (host, port):
 
r = requests.get( 'http://{}:{}' . format (host, port))
 
assert r.status_code = = 200
 
assert r.text = = u 'roflol'
 
assert r.headers[ 'Content-Length' ] = = '6'

test_basic方法对Server进行基础校验，确保收发双方可以正确的发送和接收数据。先是客户端的sock发送question，然后服务端在handler中判断收到的数据是question，确认后返回answer，最后客户端再确认可以正确收到answer响应。test_text_response方法则不完整的测试了http协议。按照http协议的规范发送了http请求，Server.text_response_server会回显请求。下面是模拟浏览器的锚点定位不会经过网络传输的testcase

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def test_fragment_not_sent_with_request():
 
"""Verify that the fragment portion of a URI isn't sent to the server."""
 
def response_handler(sock):
 
req = consume_socket_content(sock, timeout = 0.5 )
 
sock.send(
 
b 'HTTP/1.1 200 OK\r\n'
 
b 'Content-Length: ' + bytes( len (req)) + b '\r\n'
 
b '\r\n' + req
 
)
 
close_server = threading.Event()
 
server = Server(response_handler, wait_to_close_event = close_server)
 
with server as (host, port):
 
url = 'http://{}:{}/path/to/thing/#view=edit&token=hunter2' . format (host, port)
 
r = requests.get(url)
 
raw_request = r.content
 
assert r.status_code = = 200
 
headers, body = raw_request.split(b '\r\n\r\n' , 1 )
 
status_line, headers = headers.split(b '\r\n' , 1 )
 
assert status_line = = b 'GET /path/to/thing/ HTTP/1.1'
 
for frag in (b 'view' , b 'edit' , b 'token' , b 'hunter2' ):
 
assert frag not in headers
 
assert frag not in body
 
close_server. set ()

可以看到请求的path是 /path/to/thing/#view=edit&token=hunter2，其中 # 后面的部分是本地锚点，不应该进行网络传输。上面测试用例中，对接收到的响应进行判断，鉴别响应头和响应body中不包含这些关键字.

结合requests的两个层面的测试，我们可以得出第9个技巧

构造模拟服务配合测试 。

小结:

简单小结一下，从requests的单元测试实践中，可以得到下面9个技巧

  1. 仅对public的接口进行测试
  2. 使用mock辅助单元测试
  3. 测试尽可能覆盖目标函数的所有分支
  4. 使用pytest.fixture复用被测试对象，使用pytest.mark.parametriz复用测试参数
  5. 可以从不同的层面对同一个对象进行单元测试
  6. 涉及环境变量的地方，可以使用上下文装饰器进行模拟多种环境变量
  7. 使用pytest.raises对异常进行捕获处理
  8. 使用IO模拟配合进行单元测试
  9. 构造模拟服务配合测试

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原文链接：https://developer.51cto.com/art/202109/683755.htm?utm_source=tuicool&utm_medium=referral 。

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