Coroutines are generalization of subroutines. they are used for cooperative multitasking where a process voluntarily yield(give away) control periodically or when idle in order to enable multiple applications to be run simultaneously. compare to thread, coroutine is context-swtich in User space by programming language or by programmer itself, but thread is managed by OS. but anyway, do you know how Python implements coroutine? or how can it yield control away and lately resume back?

A simple usage example

The Internal

References

coroutine in python

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看到这篇文章的时候，内心是崩溃的，里面说的bad practice我们目前项目中都有，一个不落。就像写出了非Pythonic的代码，它没有validate Python Grammer，可以正常工作，但就是维护起来费劲。所以说在正确的前提下，我们要尽量在工程中做到这些Best Pracice说到的东西。

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Python have builtin implementation for dict, which is used to store key-value and also provided other related operations. Due to it is an frequenctly used basic data type, here I will use pure Python implement an dict.

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To speedup the IO related operations in our project, we use Gevent and patch_all in Django. but it also makes project more complicated, especially when a new maintainer trying to figure out how the multi-threading process works without knowing the patch. So Guido van Rossum once said: when you use gevent in your project, once after patch, god knows what will happen later. i.e Patch it and Pray!!! and also for other reasons, this way isn’t a Pythonic way. here in this post, let’s see how it works, why it is bad.

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Gunicorn 是一个Python Web Server实现，兼容WSGI协议。其迁移自Ruby世界的Unicorn。在我们的生产环境中，有大量使用Gunicorn作为Web 服务器，所以本文分析Gunicorn的相关几个问题： Server model，Async worker.

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Let’s build a wsgi server ground up with sockets, multi-processing or Select/Poll/Epoll. to achive this, you need familiar with Python’s socket programming, Python’s cucurreny model, Linux Non-blocking I/O.

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突然看到Omed Habib的文章：A performance analysis of Python wsgi servers，觉得Bjoern确实可以用在我们项目中，用来替代现有Gunicorn。因此将原文翻译至此，希望更多可以帮助更多人。btw，Bjoern是一个用C和Libuv实现的轻量化WSGI服务器，各方面评测目前基本都处于领先的位置。

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项目中经常使用Redis作为cache方案，但是你知道为什么Redis作为一种缓存速度如此快？为什么ttl能expire掉你的key？本文来分析这些东西。

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以前只有MySQL, 后来出了很多各种类型的数据库，比如Mongodb，Influxdb，cassandra等，不管哪种数据库，都需要使用索引算法来快速搜索数据。那么我们来看看MySQL使用索引的算法。

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经常听到同事说Python服务性能不好，要去拥抱Go。但是细想，技术里面没有银弹，在某些场景下，他诚然没有编译型语言快。我们的服务都是一些I/O为主的，大部分的时间可能都是在等待网络I/O，如果换成任何一种编译型语言，难道就没有这种I/O等待了吗？再比如Instagram，Youtube，Dropbox等都在大规模使用Python，为什么人家的服务不会像蜗牛一样呢？自己的Py 服务性能差，我还能做什么呢？
本篇来分析为什么目前Django的服务没有我们预想的好？能做些什么来改进？

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