<?xml version="1.0" encoding="UTF-8"?><rss xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:atom="http://www.w3.org/2005/Atom" version="2.0"><channel><title><![CDATA[RSS Feed]]></title><description><![CDATA[RSS Feed]]></description><link>https://ecency.com</link><image><url>https://ecency.com/logo512.png</url><title>RSS Feed</title><link>https://ecency.com</link></image><generator>RSS for Node</generator><lastBuildDate>Wed, 27 May 2026 19:12:36 GMT</lastBuildDate><atom:link href="https://ecency.com/created/lxml/rss.xml" rel="self" type="application/rss+xml"/><item><title><![CDATA[LXML官方文档翻译]]></title><description><![CDATA[翻译说明 官方文档网址： lxml是处理xml和html的python库。 我翻译的主要目的是学习，因为我从网上搜索，没有找到合适的材料。基于此，我只翻译我认为最重要的信息，并不完备，请大家谅解。 介绍 lxml使用了libxml2和libxslt，既性能出色又易于使用，其API兼容著名的ElementTree，并且还要优于它。支持的Python版本：2.6~3.6。 支持此项目]]></description><link>https://ecency.com/cn/@brysj22952/lxml</link><guid isPermaLink="true">https://ecency.com/cn/@brysj22952/lxml</guid><category><![CDATA[cn]]></category><dc:creator><![CDATA[brysj22952]]></dc:creator><pubDate>Mon, 30 Jul 2018 14:38:51 GMT</pubDate></item><item><title><![CDATA[Web Scraping in Python]]></title><description><![CDATA[I'm writing the post as a recap of what I uncovered while learning to scraping web pages for content on the Internet. I did a lot of research and it all started here. Priceconomics sells data crawling]]></description><link>https://ecency.com/python/@epearson/web-scraping-in-python</link><guid isPermaLink="true">https://ecency.com/python/@epearson/web-scraping-in-python</guid><category><![CDATA[python]]></category><dc:creator><![CDATA[epearson]]></dc:creator><pubDate>Fri, 23 Mar 2018 18:25:33 GMT</pubDate><enclosure url="https://i.ecency.com/p/EEEoA8oLaAxvDZG9qYrsSvDqYeABF1GqkXYm2VenKuKSVSxiKm6GZ9xKcarzvnUq3dH3FCMHSbqkxEJg8VhnhLzdeZJxbc27KLRZAgEP7BGSvD79okMELQYePSSTiyKtc1oK91kixiB52gtRfhJ1c?format=match&amp;mode=fit" length="0" type="false"/></item></channel></rss>