import io import operator import re import zlib from html import unescape from urllib.parse import urlencode, urljoin import tldextract from bs4 import BeautifulSoup from lxml.html import etree, HtmlElement, fromstring, tostring from urllib3 import get_host from common.log import logger from crawler.defaults import ( USELESS_TAG, USELESS_ATTR, TAGS_CAN_BE_REMOVE_IF_EMPTY, VALID_WORDS, VOID_WORDS, PAGE_TEXT_CHECK_WORDS, PAGE_TEXT_FILTER_WORDS ) from predict_bidding_model import exists_ztb def err_details(worker): worker_exception = worker.exception() if worker_exception: logger.exception("Worker return exception: {}".format(worker_exception)) return worker def split_domain(val: str): if re.match(r'\d+', val) is None: return re.split(r'[\\.:]', val) return [val] def extract_host(url): """ # >>> base_url = extract_host('http://192.168.3.207:8080/') """ _s, _h, _p = get_host(url) return f"{_s}://{_h}/" if _p is None else f"{_s}://{_h}:{_p}/" def extract_domain(url): """ 抽取一级域名,使用点连接域和后缀字段(如果提供的域名是ipv4,就返回ipv4;) # >>> extract_domain('http://192.168.3.207:8080/') 192.168.3.207 # >>> extract_domain('http://forums.bbc.co.uk') 'bbc.co.uk' """ ext = tldextract.extract(url) return ext.registered_domain or ext.ipv4 def extract_fqdn(url): """返回一个完全限定的域名""" ext = tldextract.extract(url) return ext.fqdn or ext.ipv4 def extract_page_title(source): node = '' try: element = html2element(source) node = element.xpath('/html/head/title/text()|//title/text()') except etree.ParserError: pass if len(node) > 1: return "".join(";".join(node).split()) return "".join("".join(node).split()) def is_url(url): """判断url格式""" _regex = re.compile( r'^(?:http|ftp)s?://' # http:// or https:// r'(?:(?:[A-Z0-9](?:[A-Z0-9-]{0,61}[A-Z0-9])?\.)+(?:[A-Z]{2,6}\.?|[A-Z0-9-]{2,}\.?)|' # domain... r'localhost|' # localhost... r'\d{1,3}\.\d{1,3}\.\d{1,3}\.\d{1,3})' # ...or ip r'(?::\d+)?' # optional port r'(?:/?|[/?]\S+)$', re.IGNORECASE) return re.match(_regex, url) is not None def is_contains(val: str, feature: str): if operator.contains(val, feature): return True return False def is_domain(domain): ext = tldextract.extract(domain) if not ext.domain: return False return True def label_split(val): # '~`!#$%^&*()_+-=|\';"":/.,?><~·!@#¥%……&*()——+-=“:’;、。,?》{《}】【\n\]\[ ' result = re.split(r'[- _,,\\.|-「」【】??!!/、] *', val) result = [v for v in result if len(v) > 0] return result def join_url(url: str, parameters: dict): """ 拼接url与所带参数 :param url: 链接 :param parameters: 参数 :return: 拼接后的url """ _data = '?' + urlencode(parameters) return urljoin(url, _data) def extract_text(source: str): soup = BeautifulSoup(source, "lxml") return soup.get_text() def verify_text(val: str, length=50): """检查数字、字母、中文的个数""" if val is None: return False sub_pattern = ['<[^>]+>', '[^0-9a-zA-Z\u4e00-\u9fa5]+'] for pattern in sub_pattern: val = re.sub(pattern, '', val) # 若文本长度小于指定文本长度(length),表示页面内容无详情内容 if len(val) < length: '''无效文本''' return False '''有效文本''' return True def clean_whitespace(text: str): """清洗空白符 \n=换行 \r=回车 \v=垂直制表符 \f=换页""" obj = io.StringIO() for i in text: # 不要剔除 "" 和 "\t" 空白符,保持页面标签名称与属性分离 if i not in '\n\r\v\f': obj.write(i) return obj.getvalue() def clean_html(source): html_str = re.sub('\ufeff|\xa0|\u3000|\x00', '', source) html_str = re.sub('', '', html_str) # 清除注释 html_str = re.sub(r']*>[\s\S]*?', '', html_str) # 清除样式 html_str = re.sub(r']*>[\s\S]*?', '', html_str) # 清除js html_str = re.sub('', '', html_str) html_str = re.sub(r'<\?xml.*?>', '', html_str) html_str = re.sub(r'<[!]DOCTYPE.*?>', '', html_str) html_str = clean_whitespace(html_str) return html_str def html2element(source: str, base_url=None) -> HtmlElement: html_str = clean_html(source) if len(html_str) == 0: # 防止清洗页面垃圾标签,导致fromstring抛出lxml.etree.ParserError html_str = '''''' return fromstring(html_str, base_url=base_url) def element2html(element: HtmlElement) -> str: return unescape(tostring(element, encoding="utf-8").decode()) def iter_node(element: HtmlElement, depth=1): yield element, depth depth += 1 for sub_element in element: if isinstance(sub_element, HtmlElement): yield from iter_node(sub_element, depth) # print('退出', depth) def remove_node(node: HtmlElement): """ this is a in-place operation, not necessary to return :param node: :return: """ parent = node.getparent() if parent is not None: node.drop_tree() # parent.remove(node) def drop_tag(node: HtmlElement): """ only delete the tag, but merge its text to parent. :param node: :return: """ parent = node.getparent() if parent is not None: node.drop_tag() def is_empty_element(node: HtmlElement): return not node.getchildren() and not node.text def normalize_node(element: HtmlElement): etree.strip_elements(element, *USELESS_TAG, with_tail=False) # 节点预处理,删除节点与更新节点的操作在同一循环发生时,更新节点的操作不会生效,原因:? # 空节点合并、噪声节点剔除 for node, _ in iter_node(element): if node.tag.lower() in TAGS_CAN_BE_REMOVE_IF_EMPTY and is_empty_element(node): remove_node(node) if node.tag.lower() == 'p': etree.strip_tags(node, 'span') etree.strip_tags(node, 'strong') # if a div tag does not contain any sub node, it could be converted to p node. if node.tag.lower() == 'div' and not node.getchildren(): node.tag = 'p' if node.tag.lower() == 'span' and not node.getchildren(): node.tag = 'p' # remove empty p tag if node.tag.lower() == 'p' and not node.xpath('.//img'): if not (node.text and node.text.strip()): drop_tag(node) # Delete inline styles style = node.get('style') if style: del node.attrib['style'] # Obsolete scroll property if node.tag.lower() == 'marquee': remove_node(node) # 删除包含干扰属性的节点(完全匹配) for node, _ in iter_node(element): attr = (node.get('id') or node.get('class')) if attr: if attr.lower() in USELESS_ATTR: remove_node(node) break def pre_parse(element): normalize_node(element) return element def check_text_by_words(val: str): for word in VOID_WORDS: search = re.search(word, val) if search is not None: return False for keyword in VALID_WORDS: search = re.search(keyword, val) if search is not None: return True return False def check_page_by_words(val: str): if 7 < len(val) < 100: for word in PAGE_TEXT_FILTER_WORDS: search = re.search(word, val) if search is not None: return False for keyword in PAGE_TEXT_CHECK_WORDS: search = re.search(keyword, val) if search is not None: return True return False def predict_bidding_model(item: dict): result = {**item} predict_result = exists_ztb(item) predict = any({v for _, v in predict_result.items()}) result['predict'] = int(predict) return result def compress_str(content, level=9): return zlib.compress(content.encode(encoding='utf-8'), level=level)