re.findall()匹配问题
本帖最后由 Py与C。。。 于 2021-8-4 11:14 编辑我用requests爬下来这样一段源码：
{"filters":[],"red":"花","ret_type":"poemline-multi","ret_array":[{"dynasty":["唐"],"type":["poemline"],"literature_author":["李白"],"name":["杨花落尽子规啼，闻道龙标过五溪"],"source_poem":["闻王昌龄左迁龙标遥有此寄"],"display_name":["杨花落尽子规啼，闻道龙标过五溪"],"sid":["40ef283d7ad94206b9fb18a11049b1b2"],"source_poem_sid":["d6f4091694a544d085602c9c4a08ab23"],"source_poem_body":["杨花落尽子规啼，闻道龙标过五溪。 我寄愁心与明月，随君直到夜郎西。"]},{"dynasty":["唐"],"type":["poemline"],"literature_author":["王维"],"name":["人闲桂花落，夜静春山空"],"source_poem":["鸟鸣涧"],"display_name":["人闲桂花落，夜静春山空"],"sid":["d252c73ce28144bcb9876da1129e81d3"],"source_poem_sid":["d6f4091694a544d085602c9c4a08ab23"],"source_poem_body":["杨花落尽子规啼，闻道龙标过五溪。 我寄愁心与明月，随君直到夜郎西。"]}],"extra":{"entity-num":62857,"return-num":20,"total-page":200},"ad":[],"highlight":"蹄"}
我想要display_name里面的内容，于是我用re.findall(r'"display_name":["(.*?)"]',html)来匹配，可匹配不到，返回的是空列表，加re.S也不行。
有谁知道这是怎么回事吗？麻烦帮忙解决一下{:10_266:} 本帖最后由 大马强 于 2021-8-4 11:20 编辑
https://static01.imgkr.com/temp/df0ac88cb50e45029aa5b012e8612574.jpg
中括号好像有特殊含义，用.*?忽略
正则网站 再给你一个正则网址https://regex101.com/r/fNsbUH/1/ 大马强 发表于 2021-8-4 11:18
中括号好像有特殊含义，用.*?忽略
用\转义一下就好了像这样re.findall(r'\"display_name\":\[\"(.*?)\"\]',html) data = {"filters":[],"red":"花","ret_type":"poemline-multi","ret_array":[{"dynasty":["唐"],"type":["poemline"],"literature_author":["李白"],"name":["杨花落尽子规啼，闻道龙标过五溪"],"source_poem":["闻王昌龄左迁龙标遥有此寄"],"display_name":["杨花落尽子规啼，闻道龙标过五溪"],"sid":["40ef283d7ad94206b9fb18a11049b1b2"],"source_poem_sid":["d6f4091694a544d085602c9c4a08ab23"],"source_poem_body":["杨花落尽子规啼，闻道龙标过五溪。 我寄愁心与明月，随君直到夜郎西。"]},{"dynasty":["唐"],"type":["poemline"],"literature_author":["王维"],"name":["人闲桂花落，夜静春山空"],"source_poem":["鸟鸣涧"],"display_name":["人闲桂花落，夜静春山空"],"sid":["d252c73ce28144bcb9876da1129e81d3"],"source_poem_sid":["d6f4091694a544d085602c9c4a08ab23"],"source_poem_body":["杨花落尽子规啼，闻道龙标过五溪。 我寄愁心与明月，随君直到夜郎西。"]}],"extra":{"entity-num":62857,"return-num":20,"total-page":200},"ad":[],"highlight":"蹄"}
print(data["ret_array"]["display_name"])
直接用字典的方法完不成吗 ？ 1q23w31 发表于 2021-8-4 11:25
直接用字典的方法完不成吗 ？
他这个应该是reuqests获取的，需要用json转一下的，比如：
re = requests.post('https://abcdefg',json=data)
data=json.loads(re.content)
#或者用这样
#data=re.json() 2012277033 发表于 2021-8-4 11:23
用\转义一下就好了像这样
报错了{:10_277:}：data:image/png;base64,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