playwright+Pytest+UI 自动化分成设计框架

from playwright.sync_api import expect, Page
from Config.config import Config
import os,time


class BasePage:

    def __init__(self, page: Page):
        self.page = page

    def _goto_url(self, url):
        """打开网页"""
        self.page.goto(url)

    def _click(self, locator, frame_locator=None):
        """
        点击元素
        :param locator: 传入元素定位器
        :param frame_locator: 传入frame框架的的定位器，如果没有传入，则一般点击
        :return:
        """
        try:
            if frame_locator is not None:
                self.page.frame_locator(frame_locator).locator(locator).click()
            else:
                self.page.click(locator)
        except Exception as e:
            print(e)

    def click_text(self, text):
        """
        点击指定文本内容的元素
        :param text: 文本
        :return:
        """
        try:
            self.page.get_by_text(text).click()
        except Exception as e:
            print(e)


    def hover(self, locator, frame_locator=None):
        """
        定位目标元素，并执行鼠标悬停操作
        :param locator: 传入元素定位器
        :param frame_locator: 传入frame框架的的定位器，如果没有传入，则一般点击
        :return:
        """
        try:
            if frame_locator is not None:
                self.page.frame_locator(frame_locator).locator(locator).hover()
            else:
                self.page.hover(locator)
        except Exception as e:
            print(e)


    # def _fill(self, locator, value, frame_locator=None):
    #     """
    #     定位元素，输入内容
    #     :param locator:传入元素定位器
    #     :param value:传入输入的值
    #     :param frame_locator: 传入frame框架
    #     :return:
    #     """
    #     try:
    #         if frame_locator is not None:
    #             self.page.frame_locator(selector=frame_locator).locator(selector_or_locator=locator).fill(value)
    #         else:
    #             self.page.fill(selector=locator, value=value)
    #     except Exception as e:
    #         print(e)

    def type(self, locator, value, frame_locator=None):
        """
        模拟人工输入，一个键一个键的输入
        :param locator:传入元素定位器
        :param value:传入输入的值
        :param frame_locator: 传入frame框架
        :return:
        """
        try:
            if frame_locator is not None:
                self.page.frame_locator(selector=frame_locator).locator(selector_or_locator=locator).type(text=value,
                                                                                                          delay=50)
            else:
                self.page.type(selector=locator, text=value, delay=50)
        except Exception as e:
            print(e)


    def file(self, locator, files, frame_locator=None):
        """
        上传文件的方法
        :param locator: 定位器
        :param files: 单个文件名，或者列表存放多个文件
        :param frame_locator: iframe框架定位器，如果没有就不传
        :return:
        """
        try:
            if frame_locator is not None:
                self.page.frame_locator(frame_locator).locator(locator).set_input_files(files=files)
            else:
                self.page.locator(locator).set_input_files(files=files)
        except Exception as e:
            print(e)

    def choose_file_from_custom_button(self, button_selector, file_path):
        # 如果不是input输入框，必须点开文件框的情况（selenium上没法实现的操作）
        # 使用expect_file_chooser()来等待文件选择器出现
        try:
            with self.page.expect_file_chooser() as fc_info:
                self.page.locator(button_selector).click()
            # 获取文件选择器对象并设置文件路径
            file_chooser = fc_info.value.set_files(file_path)
            return file_chooser
        except Exception as e:
            print(e)

    def ele_to_be_visible(self, locator):
        """断言元素可见"""
        return expect(self.page.locator(locator)).to_be_visible()

    def _ele_to_be_visible_force(self, locator, frame_locator=None, timout: int = 5):
        """强制等待某个元素可见"""
        ele = None
        if frame_locator is not None:
            ele = self.page.frame_locator(frame_locator).locator(locator)
        else:
            ele = self.page.locator(locator)
        for t in range(0, timout):
            self.page.wait_for_timeout(500)
            if ele.is_visible():
                break
        else:
            raise Exception("元素未找到!")

    def select_option_by_keyword(self, dropdown_locator, option_locator, keyword):
        """下拉选项操作"""
        try:
            # 点击下拉框，展开选项
            self.click(dropdown_locator)
            time.sleep(1)
            print(f"文本内容为：{keyword}")
            # 定位选项列表
            options = self.page.query_selector_all(option_locator)
            print(f"options为：{options}")
            # 遍历选项并选择匹配的关键字
            for option in options:
                print(f"option为：{option}")
                # assert keyword in option.text_content(), f"{option.text_content()} 不包含关键字 {keyword}"
                text = option.evaluate('(element) => element.textContent')
                print(f"option.text为：{text}")
                if keyword in text:
                    print("进入了判断")
                    option.click()
                    print("点击完成")
                    break
        except Exception as e:
            print(e)

    def _ele_is_checked(self, selector):
        """判断元素是否被选选中"""
        return self.page.is_checked(selector)

    def _browser_operation(self, reload=False, forward=False, back=False):
        """浏览器操作，reload 刷新，forward 前进，back 后退"""
        if reload:
            self.page.reload()
        if back:
            self.page.go_back()
        if forward:
            self.page.go_forward()

    def screenshot(self, path, full_page=True, locator=None):
        """截图功能，默认截取全屏，如果传入定位器表示截取元素"""
        if locator is not None:
            self.page.locator(locator).screenshot(path=path)
            return path
        self.page.screenshot(path=path, full_page=full_page)
        return path

    def _del_auth(self):
        auth_path = Config.auth_dir + os.path.sep + "auth.json"
        if os.path.exists(auth_path):
            os.remove(auth_path)

    # def ocr_image(image_path):
    #     ocr = ddddocr.DdddOcr(show_ad=False)  # 实例化 OCR 对象
    #     with open(image_path, 'rb') as f:  # 打开图片
    #         img_bytes = f.read()  # 读取图片内容
    #     result = ocr.classification(img_bytes)  # 进行 OCR 分类
    #     return result