https://haillk.github.io/categories/Python/ Recent content in Python on Haillk-Blog Hugo -- gohugo.io zh-CN Thu, 02 Apr 2020 22:10:12 +0800 https://haillk.github.io/post/Python/%E5%85%B3%E9%94%AE%E5%AD%97%E5%8F%82%E6%95%B0/ Thu, 02 Apr 2020 22:10:12 +0800 https://haillk.github.io/post/Python/%E5%85%B3%E9%94%AE%E5%AD%97%E5%8F%82%E6%95%B0/ <p>*每天都有新体验</p> https://haillk.github.io/post/Python/%E5%81%8F%E5%87%BD%E6%95%B0/ Thu, 02 Apr 2020 21:59:53 +0800 https://haillk.github.io/post/Python/%E5%81%8F%E5%87%BD%E6%95%B0/ <p>*每天都有新体验 偏函数</p> https://haillk.github.io/post/Python/%E4%BD%8D%E8%BF%90%E7%AE%97/ Thu, 02 Apr 2020 17:02:18 +0800 https://haillk.github.io/post/Python/%E4%BD%8D%E8%BF%90%E7%AE%97/ <p>*每天都有新体验</p> https://haillk.github.io/post/Python/init_call/ Fri, 20 Mar 2020 22:44:20 +0800 https://haillk.github.io/post/Python/init_call/ _init_()和_call_() _init_()相当于类的构造器 _call_()： ​ Python中的函数是一级对象，也就是说函数的引用可以作为输入传递到其他函 https://haillk.github.io/post/Python/with-as/ Tue, 10 Mar 2020 00:09:42 +0800 https://haillk.github.io/post/Python/with-as/ with语句，对于实现需要设置，事后做清理工作，with语句就能很好的处理： 在不用with语句： 1 2 3 4 5 file = open(&#34;/temp&#34;) try: data = file.read() finally: file.close() 使用with语句： 1 2 with open(&#34;/tmp/fs&#34;) as file: data = file.read() https://haillk.github.io/post/Python/%E5%8F%8C%E5%86%92%E5%8F%B7%E5%92%8Czip%E5%87%BD%E6%95%B0/ Mon, 17 Feb 2020 20:05:10 +0800 https://haillk.github.io/post/Python/%E5%8F%8C%E5%86%92%E5%8F%B7%E5%92%8Czip%E5%87%BD%E6%95%B0/ https://haillk.github.io/post/Python/leetcode-%E6%9C%80%E4%B8%8D%E5%B8%B8%E7%94%A8%E5%8D%95%E8%AF%8D/ Sat, 15 Feb 2020 19:11:16 +0800 https://haillk.github.io/post/Python/leetcode-%E6%9C%80%E4%B8%8D%E5%B8%B8%E7%94%A8%E5%8D%95%E8%AF%8D/ <p>python可以获取列表中单词出现的次数。<code>words.count(word)</code></p> https://haillk.github.io/post/Python/%E6%95%B0%E6%8D%AE%E7%BB%93%E6%9E%84%E5%92%8C%E7%AE%97%E6%B3%95/ Thu, 13 Feb 2020 12:38:33 +0800 https://haillk.github.io/post/Python/%E6%95%B0%E6%8D%AE%E7%BB%93%E6%9E%84%E5%92%8C%E7%AE%97%E6%B3%95/ https://haillk.github.io/post/Python/yield%E5%AE%8C%E5%85%A8%E8%A7%A3%E8%AF%BB/ Fri, 27 Dec 2019 02:15:34 +0800 https://haillk.github.io/post/Python/yield%E5%AE%8C%E5%85%A8%E8%A7%A3%E8%AF%BB/ https://haillk.github.io/post/Python/python3%E9%87%8Cgbk%E7%9A%84encode%E9%94%99%E8%AF%AF/ Fri, 27 Dec 2019 01:32:19 +0800 https://haillk.github.io/post/Python/python3%E9%87%8Cgbk%E7%9A%84encode%E9%94%99%E8%AF%AF/ https://haillk.github.io/post/Python/%E5%AE%89%E8%A3%85%E6%9B%B4%E6%96%B0pip/ Fri, 20 Dec 2019 19:38:40 +0800 https://haillk.github.io/post/Python/%E5%AE%89%E8%A3%85%E6%9B%B4%E6%96%B0pip/ https://haillk.github.io/post/Python/selenium%E5%AE%89%E8%A3%85%E4%BD%BF%E7%94%A8/ Sun, 15 Dec 2019 00:49:02 +0800 https://haillk.github.io/post/Python/selenium%E5%AE%89%E8%A3%85%E4%BD%BF%E7%94%A8/ selenium能真是的模拟打开一个浏览器，模拟鼠标事件，提供选择器，控制cookie等等。 安装 由于使用了conda,安装就很方便了。 conda install selenium 安装chrome驱动 https://haillk.github.io/post/Python/scrapy%E5%B8%B8%E7%94%A8%E5%91%BD%E4%BB%A4/ Sat, 14 Dec 2019 22:21:47 +0800 https://haillk.github.io/post/Python/scrapy%E5%B8%B8%E7%94%A8%E5%91%BD%E4%BB%A4/ 新建一个工程 scrapy startproject spider_name 构建爬虫 scrapy genspider name domain 运行爬虫 scrapy runspider 爬虫名称 启动项目 scrapy crawl xxx https://haillk.github.io/post/Python/anaconda%E5%B8%B8%E7%94%A8%E5%91%BD%E4%BB%A4/ Sat, 14 Dec 2019 22:02:22 +0800 https://haillk.github.io/post/Python/anaconda%E5%B8%B8%E7%94%A8%E5%91%BD%E4%BB%A4/ 查看虚拟环境 1 2 3 4 5 6 7 8 9 10 11 12 13 14 ##创建虚拟环境 conda create -n env-name python=X.X ##切换虚拟环境 conda activate env-name ##关闭虚拟环境 deactivate ##删除虚拟环境 conda remove -n env-name --all ##查看存在的虚拟环境 conda env list https://haillk.github.io/post/Python/windows%E5%AE%89%E8%A3%85scrapy/ Tue, 10 Dec 2019 18:29:22 +0800 https://haillk.github.io/post/Python/windows%E5%AE%89%E8%A3%85scrapy/ Windows通过pip安装scrapy Scrapy需要超多的依赖，而pip instarll scrapy并不会下载好全部依赖。我在安装twisted时出现问题。 1 error: Microsoft Visual C++ 14.0 is https://haillk.github.io/post/Python/debian%E5%AE%89%E8%A3%85python38/ Sat, 07 Dec 2019 22:19:52 +0800 https://haillk.github.io/post/Python/debian%E5%AE%89%E8%A3%85python38/ 源码安装 1、安装依赖包 1 sudo apt-get install build-essential python-dev python-setuptools python-pip python-smbus build-essential libncursesw5-dev libgdbm-dev libc6-dev zlib1g-dev libsqlite3-dev tk-dev libssl-dev openssl libffi-dev 2、下载python3.8源码 1 2 3 4 5 6 7 ##更新 sudo apt-get update ##下载 wget https://www.python.org/downloads/release/python-380/ ##解压 tar -xvf Python-3.8.0.tar.xz cd Python-3.8.0/ 3、配置，编