本文主要是介绍HttpRunner3源码阅读：2. 模型定义，对大家解决编程问题具有一定的参考价值，需要的程序猿们随着小编来一起学习吧！

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

1. Text => str / 文本
2. List => list / 列表
3. 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。

这篇关于HttpRunner3源码阅读：2. 模型定义的文章就介绍到这儿，希望我们推荐的文章对大家有所帮助，也希望大家多多支持为之网！