<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:sy="http://purl.org/rss/1.0/modules/syndication/" xmlns:media="http://search.yahoo.com/mrss/"><channel><title>Guide on Shaowen Chen's Website</title><link>https://www.chenshaowen.com/en/tags/guide/</link><description>Recent content in Guide on Shaowen Chen's Website</description><generator>Hugo -- gohugo.io</generator><language>en</language><copyright>&amp;copy;2016 - {year}, All Rights Reserved.</copyright><lastBuildDate>Thu, 15 Nov 2018 00:00:00 +0000</lastBuildDate><sy:updatePeriod>weekly</sy:updatePeriod><atom:link href="https://www.chenshaowen.com/en/tags/guide/atom.xml" rel="self" type="application/rss+xml"/><item><title>Django Full-Stack Optimization Guide</title><link>https://www.chenshaowen.com/en/blog/django-full-stack-optimization-guide.html</link><pubDate>Thu, 15 Nov 2018 00:00:00 +0000</pubDate><atom:modified>Thu, 15 Nov 2018 00:00:00 +0000</atom:modified><guid>https://www.chenshaowen.com/en/blog/django-full-stack-optimization-guide.html</guid><description>As the data volume exploded, the system responded very slowly. We carried out a series of optimizations on the application, and the system&amp;rsquo;s response time improved by an order of magnitude. Overall, optimizations in file compression and faster network access gave a noticeable boost to frontend performance, while optimizations in stored procedures, caching, and logic code gave a noticeable boost to backend performance.</description><dc:creator>微信公众号</dc:creator><category>Django</category><category>Python</category><category>Optimization</category><category>Frontend</category><category>Backend</category><category>Guide</category><category>R&amp;D</category></item></channel></rss>