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Title: NLP-Interview-Notes/python at main · turned123/NLP-Interview-Notes · GitHub

Open Graph Title: NLP-Interview-Notes/python at main · turned123/NLP-Interview-Notes

X Title: NLP-Interview-Notes/python at main · turned123/NLP-Interview-Notes

Description: 本项目是作者们根据个人面试和经验总结出的自然语言处理(NLP)面试准备的学习笔记与资料，该资料目前包含 自然语言处理各领域的 面试题积累。 - NLP-Interview-Notes/python at main · turned123/NLP-Interview-Notes

Open Graph Description: 本项目是作者们根据个人面试和经验总结出的自然语言处理(NLP)面试准备的学习笔记与资料，该资料目前包含 自然语言处理各领域的 面试题积累。 - turned123/NLP-Interview-Notes

X Description: 本项目是作者们根据个人面试和经验总结出的自然语言处理(NLP)面试准备的学习笔记与资料，该资料目前包含 自然语言处理各领域的 面试题积累。 - turned123/NLP-Interview-Notes

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https://github.com/turned123/NLP-Interview-Notes/tree/main/python#关于-python--的那些你不知道的事
https://github.com/km1994/nlp_paper_studyhttps://github.com/km1994/nlp_paper_study
【关于 python 】 的那些你不知道的事https://github.com/turned123/NLP-Interview-Notes/tree/main/python#%E5%85%B3%E4%BA%8E-python--%E7%9A%84%E9%82%A3%E4%BA%9B%E4%BD%A0%E4%B8%8D%E7%9F%A5%E9%81%93%E7%9A%84%E4%BA%8B
一、什么是*args 和 **kwargs？https://github.com/turned123/NLP-Interview-Notes/tree/main/python#%E4%B8%80%E4%BB%80%E4%B9%88%E6%98%AFargs-%E5%92%8C-kwargs
1.1 为什么会有 *args 和 **kwargs？https://github.com/turned123/NLP-Interview-Notes/tree/main/python#11-%E4%B8%BA%E4%BB%80%E4%B9%88%E4%BC%9A%E6%9C%89-args-%E5%92%8C-kwargs
1.2 *args 和 **kwargs 的用途是什么？https://github.com/turned123/NLP-Interview-Notes/tree/main/python#12-args-%E5%92%8C-kwargs-%E7%9A%84%E7%94%A8%E9%80%94%E6%98%AF%E4%BB%80%E4%B9%88
1.3 *args 是什么？https://github.com/turned123/NLP-Interview-Notes/tree/main/python#13-args-%E6%98%AF%E4%BB%80%E4%B9%88
1.4 **kwargs是什么？https://github.com/turned123/NLP-Interview-Notes/tree/main/python#14-kwargs%E6%98%AF%E4%BB%80%E4%B9%88
1.5 *args 与 **kwargs 的区别是什么？https://github.com/turned123/NLP-Interview-Notes/tree/main/python#15-args-%E4%B8%8E-kwargs-%E7%9A%84%E5%8C%BA%E5%88%AB%E6%98%AF%E4%BB%80%E4%B9%88
二、什么是装饰器？https://github.com/turned123/NLP-Interview-Notes/tree/main/python#%E4%BA%8C%E4%BB%80%E4%B9%88%E6%98%AF%E8%A3%85%E9%A5%B0%E5%99%A8
2.1 装饰器是什么？https://github.com/turned123/NLP-Interview-Notes/tree/main/python#21-%E8%A3%85%E9%A5%B0%E5%99%A8%E6%98%AF%E4%BB%80%E4%B9%88
2.2 装饰器怎么用？https://github.com/turned123/NLP-Interview-Notes/tree/main/python#22-%E8%A3%85%E9%A5%B0%E5%99%A8%E6%80%8E%E4%B9%88%E7%94%A8
三、Python垃圾回收（GC）https://github.com/turned123/NLP-Interview-Notes/tree/main/python#%E4%B8%89python%E5%9E%83%E5%9C%BE%E5%9B%9E%E6%94%B6gc
3.1 垃圾回收算法有哪些？https://github.com/turned123/NLP-Interview-Notes/tree/main/python#31-%E5%9E%83%E5%9C%BE%E5%9B%9E%E6%94%B6%E7%AE%97%E6%B3%95%E6%9C%89%E5%93%AA%E4%BA%9B
3.2 引用计数（主要）是什么？https://github.com/turned123/NLP-Interview-Notes/tree/main/python#32-%E5%BC%95%E7%94%A8%E8%AE%A1%E6%95%B0%E4%B8%BB%E8%A6%81%E6%98%AF%E4%BB%80%E4%B9%88
3.3 标记-清除是什么？https://github.com/turned123/NLP-Interview-Notes/tree/main/python#33-%E6%A0%87%E8%AE%B0-%E6%B8%85%E9%99%A4%E6%98%AF%E4%BB%80%E4%B9%88
3.4 分代回收是什么？https://github.com/turned123/NLP-Interview-Notes/tree/main/python#34-%E5%88%86%E4%BB%A3%E5%9B%9E%E6%94%B6%E6%98%AF%E4%BB%80%E4%B9%88
四、python的sorted函数对字典按key排序和按value排序https://github.com/turned123/NLP-Interview-Notes/tree/main/python#%E5%9B%9Bpython%E7%9A%84sorted%E5%87%BD%E6%95%B0%E5%AF%B9%E5%AD%97%E5%85%B8%E6%8C%89key%E6%8E%92%E5%BA%8F%E5%92%8C%E6%8C%89value%E6%8E%92%E5%BA%8F
4.1 python 的sorted函数是什么？https://github.com/turned123/NLP-Interview-Notes/tree/main/python#41-python-%E7%9A%84sorted%E5%87%BD%E6%95%B0%E6%98%AF%E4%BB%80%E4%B9%88
4.2 python 的sorted函数举例说明？https://github.com/turned123/NLP-Interview-Notes/tree/main/python#42-python-%E7%9A%84sorted%E5%87%BD%E6%95%B0%E4%B8%BE%E4%BE%8B%E8%AF%B4%E6%98%8E
五、直接赋值、浅拷贝和深度拷贝https://github.com/turned123/NLP-Interview-Notes/tree/main/python#%E4%BA%94%E7%9B%B4%E6%8E%A5%E8%B5%8B%E5%80%BC%E6%B5%85%E6%8B%B7%E8%B4%9D%E5%92%8C%E6%B7%B1%E5%BA%A6%E6%8B%B7%E8%B4%9D
5.1 概念介绍https://github.com/turned123/NLP-Interview-Notes/tree/main/python#51-%E6%A6%82%E5%BF%B5%E4%BB%8B%E7%BB%8D
5.2 介绍https://github.com/turned123/NLP-Interview-Notes/tree/main/python#52-%E4%BB%8B%E7%BB%8D
5.3 变量定义流程https://github.com/turned123/NLP-Interview-Notes/tree/main/python#53-%E5%8F%98%E9%87%8F%E5%AE%9A%E4%B9%89%E6%B5%81%E7%A8%8B
5.3 赋值https://github.com/turned123/NLP-Interview-Notes/tree/main/python#53-%E8%B5%8B%E5%80%BC
5.4 浅拷贝https://github.com/turned123/NLP-Interview-Notes/tree/main/python#54-%E6%B5%85%E6%8B%B7%E8%B4%9D
5.5 深度拷贝https://github.com/turned123/NLP-Interview-Notes/tree/main/python#55--%E6%B7%B1%E5%BA%A6%E6%8B%B7%E8%B4%9D
5.6 核心：不可变对象类型 and 可变对象类型https://github.com/turned123/NLP-Interview-Notes/tree/main/python#56-%E6%A0%B8%E5%BF%83%E4%B8%8D%E5%8F%AF%E5%8F%98%E5%AF%B9%E8%B1%A1%E7%B1%BB%E5%9E%8B-and-%E5%8F%AF%E5%8F%98%E5%AF%B9%E8%B1%A1%E7%B1%BB%E5%9E%8B
5.6.1 不可变对象类型https://github.com/turned123/NLP-Interview-Notes/tree/main/python#561-%E4%B8%8D%E5%8F%AF%E5%8F%98%E5%AF%B9%E8%B1%A1%E7%B1%BB%E5%9E%8B
5.6.2 可变对象类型https://github.com/turned123/NLP-Interview-Notes/tree/main/python#562-%E5%8F%AF%E5%8F%98%E5%AF%B9%E8%B1%A1%E7%B1%BB%E5%9E%8B
六、进程、线程、协程https://github.com/turned123/NLP-Interview-Notes/tree/main/python#%E5%85%AD%E8%BF%9B%E7%A8%8B%E7%BA%BF%E7%A8%8B%E5%8D%8F%E7%A8%8B
6.1 进程https://github.com/turned123/NLP-Interview-Notes/tree/main/python#61-%E8%BF%9B%E7%A8%8B
6.1.1 什么是进程？https://github.com/turned123/NLP-Interview-Notes/tree/main/python#611-%E4%BB%80%E4%B9%88%E6%98%AF%E8%BF%9B%E7%A8%8B
6.1.2 进程间如何通信？https://github.com/turned123/NLP-Interview-Notes/tree/main/python#612-%E8%BF%9B%E7%A8%8B%E9%97%B4%E5%A6%82%E4%BD%95%E9%80%9A%E4%BF%A1
6.2 线程https://github.com/turned123/NLP-Interview-Notes/tree/main/python#62-%E7%BA%BF%E7%A8%8B
6.2.1 什么是线程？https://github.com/turned123/NLP-Interview-Notes/tree/main/python#621-%E4%BB%80%E4%B9%88%E6%98%AF%E7%BA%BF%E7%A8%8B
6.2.2 线程间如何通信？https://github.com/turned123/NLP-Interview-Notes/tree/main/python#622-%E7%BA%BF%E7%A8%8B%E9%97%B4%E5%A6%82%E4%BD%95%E9%80%9A%E4%BF%A1
6.3 进程 vs 线程https://github.com/turned123/NLP-Interview-Notes/tree/main/python#63-%E8%BF%9B%E7%A8%8B-vs-%E7%BA%BF%E7%A8%8B
6.3.1 区别https://github.com/turned123/NLP-Interview-Notes/tree/main/python#631-%E5%8C%BA%E5%88%AB
6.3.2 应用场景https://github.com/turned123/NLP-Interview-Notes/tree/main/python#632-%E5%BA%94%E7%94%A8%E5%9C%BA%E6%99%AF
6.4 协程https://github.com/turned123/NLP-Interview-Notes/tree/main/python#64-%E5%8D%8F%E7%A8%8B
6.4.1 什么是协程？https://github.com/turned123/NLP-Interview-Notes/tree/main/python#641-%E4%BB%80%E4%B9%88%E6%98%AF%E5%8D%8F%E7%A8%8B
6.4.2 协程的优点？https://github.com/turned123/NLP-Interview-Notes/tree/main/python#642-%E5%8D%8F%E7%A8%8B%E7%9A%84%E4%BC%98%E7%82%B9
七、全局解释器锁https://github.com/turned123/NLP-Interview-Notes/tree/main/python#%E4%B8%83%E5%85%A8%E5%B1%80%E8%A7%A3%E9%87%8A%E5%99%A8%E9%94%81
7.1 什么是全局解释器锁？https://github.com/turned123/NLP-Interview-Notes/tree/main/python#71-%E4%BB%80%E4%B9%88%E6%98%AF%E5%85%A8%E5%B1%80%E8%A7%A3%E9%87%8A%E5%99%A8%E9%94%81
7.2 GIL有什么作用？https://github.com/turned123/NLP-Interview-Notes/tree/main/python#72-gil%E6%9C%89%E4%BB%80%E4%B9%88%E4%BD%9C%E7%94%A8
7.3 GIL有什么影响？https://github.com/turned123/NLP-Interview-Notes/tree/main/python#73-gil%E6%9C%89%E4%BB%80%E4%B9%88%E5%BD%B1%E5%93%8D
7.4 如何避免GIL带来的影响？https://github.com/turned123/NLP-Interview-Notes/tree/main/python#74-%E5%A6%82%E4%BD%95%E9%81%BF%E5%85%8Dgil%E5%B8%A6%E6%9D%A5%E7%9A%84%E5%BD%B1%E5%93%8D
参考https://github.com/turned123/NLP-Interview-Notes/tree/main/python#%E5%8F%82%E8%80%83
https://github.com/turned123/NLP-Interview-Notes/tree/main/python#一什么是args-和-kwargs
https://github.com/turned123/NLP-Interview-Notes/tree/main/python#11-为什么会有-args-和-kwargs
https://github.com/turned123/NLP-Interview-Notes/tree/main/python#12-args-和-kwargs-的用途是什么
https://github.com/turned123/NLP-Interview-Notes/tree/main/python#13-args-是什么
https://github.com/turned123/NLP-Interview-Notes/tree/main/python#14-kwargs是什么
https://github.com/turned123/NLP-Interview-Notes/tree/main/python#15-args-与-kwargs-的区别是什么
https://github.com/turned123/NLP-Interview-Notes/tree/main/python#二什么是装饰器
https://github.com/turned123/NLP-Interview-Notes/tree/main/python#21-装饰器是什么
https://github.com/turned123/NLP-Interview-Notes/tree/main/python#22-装饰器怎么用
https://github.com/turned123/NLP-Interview-Notes/tree/main/python#三python垃圾回收gc
https://github.com/turned123/NLP-Interview-Notes/tree/main/python#31-垃圾回收算法有哪些
https://github.com/turned123/NLP-Interview-Notes/tree/main/python#32-引用计数主要是什么
https://github.com/turned123/NLP-Interview-Notes/tree/main/python#33-标记-清除是什么
https://github.com/turned123/NLP-Interview-Notes/tree/main/python#34-分代回收是什么
https://github.com/turned123/NLP-Interview-Notes/tree/main/python#四python的sorted函数对字典按key排序和按value排序
https://github.com/turned123/NLP-Interview-Notes/tree/main/python#41-python-的sorted函数是什么
https://github.com/turned123/NLP-Interview-Notes/tree/main/python#42-python-的sorted函数举例说明
https://github.com/turned123/NLP-Interview-Notes/blob/main/python/img/%E5%BE%AE%E4%BF%A1%E6%88%AA%E5%9B%BE_20201104224302.png
https://github.com/turned123/NLP-Interview-Notes/blob/main/python/img/%E5%BE%AE%E4%BF%A1%E6%88%AA%E5%9B%BE_20201104224402.png
https://github.com/turned123/NLP-Interview-Notes/tree/main/python#五直接赋值浅拷贝和深度拷贝
https://github.com/turned123/NLP-Interview-Notes/tree/main/python#51-概念介绍
https://github.com/turned123/NLP-Interview-Notes/tree/main/python#52-介绍
https://github.com/turned123/NLP-Interview-Notes/tree/main/python#53-变量定义流程
https://github.com/turned123/NLP-Interview-Notes/tree/main/python#53-赋值
https://github.com/turned123/NLP-Interview-Notes/blob/main/python/img/%E5%BE%AE%E4%BF%A1%E6%88%AA%E5%9B%BE_20210221224625.png
https://github.com/turned123/NLP-Interview-Notes/tree/main/python#54-浅拷贝
https://github.com/turned123/NLP-Interview-Notes/blob/main/python/img/%E5%BE%AE%E4%BF%A1%E6%88%AA%E5%9B%BE_20210221224952.png
https://github.com/turned123/NLP-Interview-Notes/tree/main/python#55--深度拷贝
https://github.com/turned123/NLP-Interview-Notes/blob/main/python/img/%E5%BE%AE%E4%BF%A1%E6%88%AA%E5%9B%BE_20210221225331.png
https://github.com/turned123/NLP-Interview-Notes/tree/main/python#56-核心不可变对象类型-and-可变对象类型
https://github.com/turned123/NLP-Interview-Notes/tree/main/python#561-不可变对象类型
https://github.com/turned123/NLP-Interview-Notes/tree/main/python#562-可变对象类型
https://github.com/turned123/NLP-Interview-Notes/tree/main/python#六进程线程协程
https://github.com/turned123/NLP-Interview-Notes/tree/main/python#61-进程
https://github.com/turned123/NLP-Interview-Notes/tree/main/python#611-什么是进程
https://github.com/turned123/NLP-Interview-Notes/tree/main/python#612-进程间如何通信
https://github.com/turned123/NLP-Interview-Notes/tree/main/python#62-线程
https://github.com/turned123/NLP-Interview-Notes/tree/main/python#621-什么是线程
https://github.com/turned123/NLP-Interview-Notes/tree/main/python#622-线程间如何通信
https://github.com/turned123/NLP-Interview-Notes/tree/main/python#63-进程-vs-线程
https://github.com/turned123/NLP-Interview-Notes/tree/main/python#631-区别
https://github.com/turned123/NLP-Interview-Notes/tree/main/python#632-应用场景
https://github.com/turned123/NLP-Interview-Notes/tree/main/python#64-协程
https://github.com/turned123/NLP-Interview-Notes/tree/main/python#641-什么是协程
https://github.com/turned123/NLP-Interview-Notes/tree/main/python#642-协程的优点
https://github.com/turned123/NLP-Interview-Notes/tree/main/python#七全局解释器锁
https://github.com/turned123/NLP-Interview-Notes/tree/main/python#71-什么是全局解释器锁
https://github.com/turned123/NLP-Interview-Notes/tree/main/python#72-gil有什么作用
https://github.com/turned123/NLP-Interview-Notes/tree/main/python#73-gil有什么影响
https://github.com/turned123/NLP-Interview-Notes/tree/main/python#74-如何避免gil带来的影响
https://github.com/turned123/NLP-Interview-Notes/tree/main/python#参考
*args 和 **kwargs的用法https://www.jianshu.com/p/d993b2a88e73
理解 Python 装饰器看这一篇就够了https://foofish.net/python-decorator.html
Python垃圾回收（GC）三层心法,你了解到第几层？https://juejin.im/post/6844903629556547598
Python垃圾回收机制！非常实用https://zhuanlan.zhihu.com/p/83251959
python的sorted函数对字典按key排序和按value排序https://blog.csdn.net/tangtanghao511/article/details/47810729
Python中的赋值(复制)、浅拷贝与深拷贝https://zhuanlan.zhihu.com/p/54011712
Python 直接赋值、浅拷贝和深度拷贝解析https://www.runoob.com/w3cnote/python-understanding-dict-copy-shallow-or-deep.html
Python中 进程 线程 协程 (多任务概念/重点)https://v3u.cn/book/p4.html
全局解释器锁https://v3u.cn/book/p5.html
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