models.py
昨天体验的时候我们分别执行了
httprunner -h,httprunner startproject demo,httprunner run demo,但是源码中其调用了其他文件中的方法所以暂时先不分析cli.py了,先从根本开始models.py
可用资料
typing[类型提示]: https://docs.python.org/zh-cn/3/library/typing.html
pydantic[类型校验]: https://pydantic-docs.helpmanual.io/
用上这两个库就有点强类型语言的味儿了
泛型: https://docs.python.org/zh-cn/3/library/typing.html#generics
枚举: https://docs.python.org/zh-cn/3/library/enum.html
导包分析
import os # 系统包
from enum import Enum # 枚举类
from typing import Any # Any 表示 任意类型
from typing import Dict # dict 的泛型版本。
from typing import Text # Text 是 str 的别名
from typing import Union # 联合类型；Union[X, Y] 的意思是，非 X 即 Y
from typing import Callable # 可调类型； Callable[[int], str] 是把（int）转为 str 的函数。
from typing import List # list 的泛型版本。
from pydantic import BaseModel # pydantic定义对象的基类
from pydantic import Field # pydantic 中 字段扩展定义
from pydantic import HttpUrl # 校验url地址的
类型别名定义
该系列中个人对类型的看法/叫法如下
- Text => str / 文本
- List => list / 列表
- Dict => dict / 字典
Name = Text # Name 的本质 其实就是 Text(Text 本质又是 str)
Url = Text
BaseUrl = Union[HttpUrl, Text] # 是url 或者 Text 两者之一
VariablesMapping = Dict[Text, Any] # key 是 Text ，value 是任意类型
FunctionsMapping = Dict[Text, Callable] # key 是 Text， value是可调用对象
Headers = Dict[Text, Text] # key 是 str， value 也是 str
Cookies = Dict[Text, Text] # 同上
Verify = bool # 布尔类型
Hooks = List[Union[Text, Dict[Text, Text]]] # 列表，列表中的元素是 str 或者 key，value 都是 str
Export = List[Text] # 列表,列表中元素是 str
Validators = List[Dict] # 列表，列表中元素是 字典
Env = Dict[Text, Any] # 字典 key 是 str， value 是任意类型
请求方法
# 枚举类，其中属性是 Text类型
class MethodEnum(Text, Enum):
GET = "GET"
POST = "POST"
PUT = "PUT"
DELETE = "DELETE"
HEAD = "HEAD"
OPTIONS = "OPTIONS"
PATCH = "PATCH"
其余模型
避免篇幅过长，这里直接复制源代码 附上注释
class TConfig(BaseModel):
"""测试配置模型"""
name: Name
verify: Verify = False
base_url: BaseUrl = ""
# Text: prepare variables in debugtalk.py, ${gen_variables()}
# 变量
variables: Union[VariablesMapping, Text] = {}
parameters: Union[VariablesMapping, Text] = {}
# setup_hooks: Hooks = []
# teardown_hooks: Hooks = []
export: Export = []
path: Text = None
weight: int = 1
class TRequest(BaseModel):
"""测试请求模型"""
"""requests.Request model"""
method: MethodEnum # 这里的类型是前面定义的请求方法枚举
url: Url
# 查询参数
params: Dict[Text, Text] = {}
headers: Headers = {}
# alias 是别名， json 数据
req_json: Union[Dict, List, Text] = Field(None, alias="json")
# data 数据 - 表单
data: Union[Text, Dict[Text, Any]] = None
cookies: Cookies = {}
timeout: float = 120
# 允许重定向
allow_redirects: bool = True
# 安全验证
verify: Verify = False
upload: Dict = {} # used for upload files
class TStep(BaseModel):
"""测试步骤模型"""
name: Name
# 步骤可以是一个请求模型
request: Union[TRequest, None] = None
# 用例
testcase: Union[Text, Callable, None] = None
# 变量
variables: VariablesMapping = {}
setup_hooks: Hooks = []
teardown_hooks: Hooks = []
# used to extract request‘s response field
# 提取响应字段
extract: VariablesMapping = {}
# used to export session variables from referenced testcase
# 导出字段
export: Export = []
# 验证器
validators: Validators = Field([], alias="validate")
# 验证脚本
validate_script: List[Text] = []
class TestCase(BaseModel):
"""测试用例模型 = 测试配置 + 测试步骤"""
config: TConfig
teststeps: List[TStep]
class ProjectMeta(BaseModel):
"""项目配置模型"""
# debugtalk.py 文件内容
debugtalk_py: Text = "" # debugtalk.py file content
debugtalk_path: Text = "" # debugtalk.py file path
# .env 文件路径
dot_env_path: Text = "" # .env file path
# 在 debugtalk.py 中定义的函数
functions: FunctionsMapping = {} # functions defined in debugtalk.py
env: Env = {}
# 项目根目录
RootDir: Text = os.getcwd() # project root directory (ensure absolute), the path debugtalk.py located
class TestsMapping(BaseModel):
"""测试集合"""
project_meta: ProjectMeta
testcases: List[TestCase]
class TestCaseTime(BaseModel):
"""测试用例时间"""
start_at: float = 0
start_at_iso_format: Text = ""
duration: float = 0
class TestCaseInOut(BaseModel):
"""测试用例输入输出"""
# 输入参数
config_vars: VariablesMapping = {}
# 导出参数
export_vars: Dict = {}
class RequestStat(BaseModel):
"""请求状态"""
content_size: float = 0
response_time_ms: float = 0
elapsed_ms: float = 0
class AddressData(BaseModel):
"""地址数据"""
client_ip: Text = "N/A"
client_port: int = 0
server_ip: Text = "N/A"
server_port: int = 0
class RequestData(BaseModel):
"""请求数据模型"""
method: MethodEnum = MethodEnum.GET
url: Url
headers: Headers = {}
cookies: Cookies = {}
body: Union[Text, bytes, List, Dict, None] = {}
class ResponseData(BaseModel):
"""响应数据模型"""
status_code: int
headers: Dict
cookies: Cookies
encoding: Union[Text, None] = None
content_type: Text
body: Union[Text, bytes, List, Dict]
class ReqRespData(BaseModel):
"""请求响应数据模型"""
request: RequestData
response: ResponseData
class SessionData(BaseModel):
"""会话数据"""
"""request session data, including request, response, validators and stat data"""
success: bool = False
# in most cases, req_resps only contains one request & response
# while when 30X redirect occurs, req_resps will contain multiple request & response
req_resps: List[ReqRespData] = []
stat: RequestStat = RequestStat()
address: AddressData = AddressData()
validators: Dict = {}
class StepData(BaseModel):
"""步骤数据模型"""
"""teststep data, each step maybe corresponding to one request or one testcase"""
success: bool = False
name: Text = "" # teststep name
data: Union[SessionData, List[‘StepData‘]] = None
export_vars: VariablesMapping = {}
StepData.update_forward_refs()
class TestCaseSummary(BaseModel):
"""测试用例结果"""
name: Text
success: bool
case_id: Text
time: TestCaseTime
in_out: TestCaseInOut = {}
log: Text = ""
step_datas: List[StepData] = []
class PlatformInfo(BaseModel):
httprunner_version: Text
python_version: Text
platform: Text
class TestCaseRef(BaseModel):
name: Text
base_url: Text = ""
testcase: Text
variables: VariablesMapping = {}
class TestSuite(BaseModel):
"""测试套件"""
config: TConfig
testcases: List[TestCaseRef]
class Stat(BaseModel):
"""结果集状态"""
total: int = 0
success: int = 0
fail: int = 0
class TestSuiteSummary(BaseModel):
"""测试套件结果收集"""
success: bool = False
stat: Stat = Stat()
time: TestCaseTime = TestCaseTime()
platform: PlatformInfo
testcases: List[TestCaseSummary]
最后
上述内容个人理解,如有错误欢迎指出交流。