extract_data:str):ifextract_data:extract_data=extract_dataifisinstance(extract_data,dict)elsejson.loads(extract_data)forkey,valinextract_data.items():value=jsonpath(response,val)[0]setattr(HandleAttr,key,value)else:print("Excel中该字段为空,无需提取数据")...
def __extract_data_from_json(self): try: #将Excel表格中的数据转换为python对象 rules = json.loads(self.case['extract']) except Exception as e: logger.exception('用例【{}】的extract字段数据:{}格式不正确'.format(self.case['title'], self.case['extract'])) raise e # 循环取值 for rule ...
extract_element_from_json(data, ["familyMembers", "name"]) 1. api 提取元素 import requests url = "http://ip-api.com/json" response = requests.request("GET", url) data = response.json() extract_element_from_json(data, ["status"]) 1. 2. 3. 4. 5. 6. 7. 8. 9. 就是这么简...
status=500)returnjson_response(body={'success':True})# fare una class base view# e spostare in una nuova funzione rest# def load_isoedimlid(request, layername):# def load_isoediml(request, layername):# layer = _resolve_layer(request, layername, 'base.change_layer', _...
response = requests.get(url) soup = BeautifulSoup(response.text, 'html.parser') # Your code here to extract relevant data from the website``` 说明: 此Python脚本利用requests和BeautifulSoup库从网站上抓取数据。它获取网页内容并使用BeautifulSoup解析HTML。您可以自定义脚本来提取特定数据,例如标题、产品信息...
"https://rebuyengine.com/api/v1/custom/id/37597? key=c30f8541bcce849905613e432e4c7c9170829adf...
request.data['patient_id'] = patient_id subrecord.update_from_dict(request.data, request.user)returnjson_response( subrecord.to_dict(request.user), status_code=status.HTTP_201_CREATED ) 开发者ID:mattstibbs,项目名称:opal,代码行数:30,代码来源:api.py ...
from urllib.request import urlopen context = ssl._create_unverified_context() # HTTP请求 request = Request(url = "http://jxdxsw.com", method="GET", headers= {"Host": "jxdxsw.com"}, data=None) # HTTP响应 response = urlopen(request, context=content) ...
python import scrapy class MySpider(scrapy.Spider): name ='myspider' allowed_domains =[''] start_urls =[''] def parse(self, response): data_list = response.css('.data-item') for data in data_list: item = MyItem() item['name']= data.css('.name::text').extract_first() item[...
response = requests.get(url) data = response.json() # Step 4: Extract the desired information from the JSON response results = [] for item in data['items']: result = { 'name': item['name'], 'stars': item['stargazers_count'], ...