19.python的编码问题

时间:2022-10-04 08:02:49

  在正式说明之前,先给大家一个参考资料:戳这里

  文章的内容参考了这篇资料,并加以总结,为了避免我总结的不够完善,或者说出现什么错误的地方,有疑问的地方大家可以看看上面那篇文章。

  以下说明是针对于python2.x版本,因为在python3.x中默认使用的是Unicode。

  下面开始讲python中的编码问题,首先,我们看看编码有哪些。

  1. ASCII

  ASCII是用一个字节表示字符,而一个字节由八位二进制组成,所以能产生2**8=256种变化,在计算机刚诞生的年代,用来表示大小写的26个英文字母,外加一些符号之类的还是绰绰有余的。这也是python2.x中默认使用的编码,所以在python2.x中默认不能使用中文,除非使用编码声明。

  2. MBCS

  随着时代的发展,ASCII就太够用了,计算机不能只显示英文吧,那样实在太low。此时,大家看到ASCII码中还有没用完的,所以都想占用剩下的部分,但是剩下的部分还是不够,例如我们中文那么多肯定是不够用的,所以此时又扩展了一下,一个字节不行,我就用两个。而又为了兼容ASCII码,有定义了这样一套规则:如果第一个字节是\x80以下,则仍然表示ASCII字符;而如果是\x80以上,则跟下一个字节一起(共两个字节)表示一个字符,然后跳过下一个字节,继续往下判断。例如GB...和BIG...之类的都遵循这样的规则。

  但是,这样还是实在太乱了,此时IBM跳了出来,大喊一声:这些东西都要统一进行管理!!所以弄出了代码页的概念,将这些字符集都收录了起来,并进行了分页,而这些分页的总称就叫MBCS,例如GBK在936页,所以又叫cp936。而大家都是使用的双字节,所以也称为DBCS。

  但很明显,MBCS里面收集和各样的字符集,但是你不能说你要使用MBCS这个字符集编码,里面存了怎么多种,到底是要用哪种,你不说清楚我总不能随机给你一种吧。所以必须要进行指定,但是这个工作已经由操作系统自己完成了(linux不支持),而操作系统有时根据地区的不同而选择的。例如简体中文版的,就选GBK,其他国家的又会有不同,具体按版本而定。所以,一旦在python的编码声明中使用MBCS/BDCS,在进行过系统或跨地区运行的时候,报错也是在所难免的。所以编码声明中一定要具体的指定,例如我们常用的utf-8,这样就不会因为系统和地区的差异而造成各种编码的错误。

  在windows中,微软又为它起了个别名,叫ANSI,其实就是MBSC,大家知道就好了。

  3.Unicode

  虽然MBSC一定程度上解决了编码混乱的问题,但还是特点的编码只能显示特点的字符。这样要开发一种适配多国语言的程序就变得非常困难,此时人们在想,有没有一种编码能搞到所以的字符。大家研究了一番之后,Unicode就此诞生。干脆大家都不要在ASCII上拓展来拓展去,搞得各种版本如此混乱。以后大家都用两个字节保存算了,这样就有了256*256=65536种字符可以表示了,总归是够用了吧。这就是UCS-2标准了。后来还有人说不够用的,那么干脆翻一倍,用四个字节表示,256**4=4294967296,就算将来表示外星文字也能撑一段时间了吧。当然现在常用的还是UCS-2标准的。

  UCS(Unicode Character Set)还仅仅是字符对应码位的一张表而已(也就是表示字节),比如"汉"这个字的码位是6C49。字符具体如何传输和储存则是由UTF(UCS Transformation Format)来负责(也就是保存字节)。(注意:表示字节≠保存字节,也就是虽然我用了2个字节表示字符,但是我保存的时候不一定就直接保存用来表示的那个字节)

  刚开始都是直接使用UCS的码位来保存,这就是UTF-16,比如,"汉"直接使用\x6C\x49保存(UTF-16-BE),或是倒过来使用\x49\x6C保存(UTF-16-LE)。但美国佬后来不愿意了,我原来用ASCII只有1个字节就能搞到,现在却要两个字节,足足长了一倍呀。一倍是什么概念,四舍五入那是将近一个亿呀。真当我磁盘空间不用钱呀,为了满足这个述求,就诞生了UTF-8。

  UTF-8是一种很别扭的编码,具体表现在他是变长的,并且兼容ASCII,ASCII字符使用1字节表示。但有得必有失,在UTF-8中,东亚的文字是用三个字节表示的,包括中文,一些不常用的字符更是用四个字节表示。于是别的国家保存的成本变高了,而美国佬却变低了。又再次坑了别人,满足了自己。但是没办法,谁叫人家是计算机界的老大呢?

什么是BOM

  当一个文本编辑要打开一个文件时,它表示懵逼了。世间编码如此之多,我究竟要用什么哪种编码去解码呀?你总得告诉我吧!

  此时,UTF就进入了BOM来表示编码。所谓的BOM就是文件使用编码的标识符,就和python的编码声明一样,告诉文本编辑器我用的是什么编码,下面的你都用那个编码去解码就行。

  同样的,只有文本编辑器在文件开头的地方读到了关于BOM的描述,就能够进行正确的界面了。

  下面是一些BOM的总结:

  BOM_UTF8 '\xef\xbb\xbf'
  BOM_UTF16_LE '\xff\xfe'
  BOM_UTF16_BE '\xfe\xff'

  同样了,为了我们自己编辑的文件的编码也能被正确识别,我们也要写入BOM,一般由编辑器完成。但不写也可以,只有在打开文件的时候自己手动选择用什么去解码也是可以的。

  但是,还有一种叫UTF-8无BOM模式的,这又是什么鬼。

  因为UTF-8实在太流行了,所以文本编辑器默认会首先用UTF-8进行解码。即使是保存时默认使用ANSI(MBCS)的记事本,在读取文件时也是先使用UTF-8测试编码,如果可以成功解码,则使用UTF-8解码。记事本这个别扭的做法造成了一个BUG:如果你新建文本文件并输入"姹塧"然后使用ANSI(MBCS)保存,再打开就会变成"汉a"。)

  下用一幅图来总结:

aaarticlea/png;base64,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" alt="" />

  此时,有些人会在MBCS和UCS-2之间迷糊,大家都是两个字节表示,又有什么不同?

  MBCS是各自拓展的,有就是说很可能相同的二进制表示MBCS会出现不同的结果,而Unicode是统一拓展,保证了每种二进制表示都对应唯一一个字符,保证了唯一性,也就提高了兼容能力。


  

  ok,在讲完字符编码的问题之后,现在再来看一下:

   # coding:gbk 和 # coding= utf-8 之类的编码声明对python而言到底意味着什么。

  这里插播一个小技巧:

   # coding : utf-8 或者这样 # coding = utf-8 的声明方式是会报错的,这里并不是说是特点的=或者:的问题,而是空格的问题,在coding和符号之间是不能有空格的,但在符号和utf-8之类的编码名称间是运行0个或多个空格的,#和coding间也是运行0个或多个空格的。我也不知道为什么,但实际就是报错了。

#! /usr/bin/env python
#coding = utf-8
print '中文'

  这里coding和=号一个空格:

aaarticlea/png;base64,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" alt="" />

  报错了。

#! /usr/bin/env python
#coding= utf-8
print '中文'

  coding和=之间没空格:

aaarticlea/png;base64,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" alt="" />

  正常执行。

  不清楚是我IDE的问题还是python本来的语法是这样规定的,但其实很少有地方谈及这个地方的语法,所以这里提及一下,最后自己实验一下。

   # -*- coding: utf-8 -*- 的写法也是一样的。

  好了,一下进入正题:

#! /usr/bin/env python
# coding= utf-8
print '中文'
print str('中文')
print repr('中文')
print repr(u'中文')

aaarticlea/png;base64,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" alt="" />

  这里顺便解释一下str()函数和repr()函数在创建或转换字符串上的区别,str()得到是一个对人类可读性比较好的字符串,而print也是默认调用这个函数的。而repr()是创建或转换字符串时,得到是对机器可读性更好的字符串,就是这里得到是其编码。

  下面是另一种编码的输出:

#! /usr/bin/env python
# coding= gbk
print '中文'
print str('中文')
print repr('中文')
print repr(u'中文')

aaarticlea/png;base64,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" alt="" /> 

  前面两个是乱码,不过这里是我IDE的问题,我的IDE默认是用UTF-8的。

aaarticlea/png;base64,iVBORw0KGgoAAAANSUhEUgAAASoAAABUCAIAAAC6B+19AAAJXklEQVR4nO2dTU/cSBrH6yuhNp+FZGjlayANA42DFKJIK9IXSomiKBmrE05z2b6BRgjRjrhmtdOzbMMyDGBPj1ar1VzmOAe/1Ltfuk2Vm/7/lENcLj+uMvVzlQ39NIkBAI4grhsAwPIC/QBwBvQDwBnQDwBnzKLfoEsI8fwwiqJBlxBCuoMoarxlFeHbEIW+57o9Eq26VsBENB72e/3h2PaPRtYvGyWM7kBuk2lIhb6XlD9QW9W2eX44s35Vejo/TvTbO/pZ/adWi6LxsN/byej1h+NlvTUspH4Vy5tCq59QocX6NR65gL2jn/8UKdAvsNu2OWlJm5tqhkk/eQRnI5uQ7kB7RxfGcncQy+M7DZjGSYN0a7U1CyiM5oLZj2+AJKqpp2mh54fZofmBQnfMHaxyrYrOojs2jmPx5CU/9US/H3SIV6AVQ7kWLWnzQ+vHTzCROlGU6qc7hDPE8xJPava5hn6lk1tRT9Pmcc2WKhd0sMK1qnqW/NjcSV1HVHL9pDmwin5RFAa9dEXa6wVheiNLaoZBr6euUflD+sNxFjWK00VdEEaRFOGn+5+kgFKQLGx/OAxYZL5tYjP4+EmFpF9qy/Ud5NustEQqfP33I1Mz6lJNPzbsI3FDmEA0d2vPD9ku4vlhNpL067Eoe3zUtlVrlFG/rNgUtvBGk/w/vVXwD5jscFMHK1yrkrOox2ZXtuIPldfvMMOkX/7sl49vNubCoMfJkw9WMYhwSCwNZVE/yeeeMOLTR6+IHRMGvV4vCLM4iT36aUcOaGi5sYOsncaWCH20ufjMB0jSATZczPrxh/Cb+eLT1KAkpvYGX0s/ccIgRDlpyeJT7FHWav014TerXKvis+QxlYUru0sU/1Bnnv2ysRdJFQpGm3RIXKhfHkHeDIMdkexewJtQrp8aXz2RvoOcaJqWqH20r5/4wFNt9stGPKtXpl9sNrDW4lMayqaz1NJPM/spHaxyraqcRe0sc7Dw6sXZm8+Ks1+ZfkWDXj0knlU/w5rWgn794Vic59SWWNePwY0LuVinXz4rFT77zTX7zfbsp7xMKvg1hiJGjWe/CtfKeBbh2OTRkFuUcuep8qOdZfZT12bp85JZv2wBl/x/mD77pdqMh/1eFf24IHEch4F2HVhh8Rmkd1vzeQ0dFBaf2paIfbSpX8zdej1/YFp88m/tlFDym09ta6o9+1V+8ymM5rn0k6MVv/ksu1ZFZ9Eey5+nwuIzYbY3n4WvXvTnTUY+X3887KcrtyCoMvvxQbi3Jhr98uD66SgISlte/upFaUlBHxt+9QJaQqYc/kqmEnNOR7x+NoF+LaL07wqAiTn1y1+sNtuqUqBfi1B/e+q6RQvDzPolrzq1v1OxAPQDwBnQDwBnQD8AnAH9AHAG9APAGdAPAGdAPwCcAf0AcAb0A8AZ0A8AZ0A/AJwB/QBwBvSzDW0xrq/N0gH9rEIp/aPFJM1zfZGWCOhnD0rp/1sP5kCbQD97UEr/13qgn00WWL9o0OUyZdpO5D4DlNL/th7oZxONfsmojlmaSl02IfOuihXmZxH1+51jOj18RlZ3z6es5Hx3dXX3fDo9fEZknh1Op+e7q1zJ6u75dPq7CF/l2aG8twrQzybl+uUpD5JMCMmmtEultML85Po93CmahVL6G0ccf+oS7/mXmJV8ee55z7/EMVeh+4ltfnnuke6n+DcDcfypS9IK2X+NlU1AP5vU0C9Ok+0lqfKgX20opRHH/f1gnXj+6J6VjHzP80f391yF9QHbHPkeWR/cRwb4+mrwikA/m9TUj/k3i35RYoxf9OVB2akNKTSlXGBs8ZnnzyyO7/m+syUrpfSO4/Y2WCfeztktKznb8byds9tbrsJ6wDbPdjyyHtzemUkC3N3dJYdKe33f39jY2Nvbe/Xq1d7e3sbGxosXL6Q60M8mc+nHCyIF0VaIsvVrnE6kLP8sn1FPKsnSXkdSAuy0kqyfPj6/Znao368cNzfff0M626c3rOR0u9PZPr254Sp88z3bPN3usCva2T79VYGvoVYIw/Dg4ODt27efP39+8+bNwcFBGIZSHehnkxn0E4a8KW7R7BfmJmQpnMU1pFTC9JLKhVcv3OxXGN/hkpVS+gvH9fXHp6SzdXLNSk62Op2tk+trrsLTj2zzZKtDnn68FiOkrm2dJPvTgMkuvnLCaDTa39/f399//fr1aDT6RQH62aSmfvmIt61fkUgLpN9/OK6ufvyuQ558uGIlH56Qznc/Xl1lFT48IU8+sE25vkSyO99MgqnVRqPRy5cvR6ORNgj0s0ndN5/84G5IP2FxOPCz7zQQFp/cV94ZlpFm/dq0+LwUOd5cIWTt/WRyeXk5mbxfI2Rl8zjfO5m8X8v2Xl5eTibHmytk7f3k0sDkeHOFrGwes2imymdnZ6Yg0M8mdX7vpywIpX18EG0FrR6x8O0lmu+F1n57ifISxaifGN/xq5d/K7xbY/1c+faI33Vx8W6NrL27uMg2j75dIWvvLtQg7BAuXHFNE9DPJgv8Vy+z4Xbx+a/WA/1s8vj1i6LQ94RJ1dX3llBKx60H+tnk8esXi1/N5/A7gyil/2w90M8mS6Ffe6CU/qPFwD3LQD+rfP369YE/sD4Xri/P0gH9AHAG9APAGdAPAGdAPwCcAf0AcAb0s43rt5tFuL42Swf0swpFnk/AAf3sQZHnE4hAP3tQ5PkEIk3qtygJ/2JHSQop8nwCEVk/6XN6tVKVNTWUH2uOUIo8n0BEqx//KdUHHJqmj8w/1iSFFHk+gUiRfjH3yfeHYAn1U9JyIs/nUlNJv8yHQTfPGqFLBpEnfYh1qTulws7O31gEKdXSI80RSpHnE4hUWnxmD2P6z4yzPJzGnCtJqZrPs2j24w3KT7rQOUIp8nwCkeJXL/q8ZsY8nIJoAp4fahIK1ll8PoIcoRR5PoFIyeKTKyzWj1uiRhor1KPUsMXljyBHKEWeTyAyk36mPJziQo5b6cmFWT7PufVbqByhFHk+gcgs+sWG1xvCqxduDcu8VfJ5pgW6WVF5SbLwOUIp8nwCkcb/6qX5X5G3h/kXn66zeJYD/WzSpH75+8IGY7ql2RyhFHk+gUgz+mXrukc49TWYI5QizycQwScerEKR5xNwQD+rIM8n4IF+ADgD+gHgDOgHgDOgHwDOgH4AOAP6AeAM6AeAM6AfAM6AfgA4A/oB4AzoB4Az/gIb8uZnIAqaegAAAABJRU5ErkJggg==" alt="" />

  这里改成GBK再试试。

aaarticlea/png;base64,iVBORw0KGgoAAAANSUhEUgAAAXoAAABSCAIAAADVSogoAAAJfklEQVR4nO2dTW/bNhjH+ZWCqJ/FTWP0awRYtzpqgaYoMKS+hGhRBE0FpzntMt9SFMMQq+i1w+oty1vzJqbDMAy77LiD3vgqU5ZNydH/hx1smqIoZvyZD+XqIQwAAJxA6u4AAKAtQDcAAEdANwAAR0A3AABHVNXNoEsI8fwwiqJBlxBCuoMomknPpoDvQxT6Xt39kWjUWAET0XjY7/WHY/xpZk+RbtJZkdMdyH8D0xQKfS8un1O/1b55fji1bmyutDq16GZj/zf1P7VaFI2H/d56Sq8/HLdVhdDN/JiZbizLZ4VWN0KFButm5i0XsLH/238iBboJ3PatIg3pc0O6sRDY6EaeselMJqQ70H5jC3O3O2DyfE4aTNpJGumW6nfaoDB7C1Y3fAckMZmuNCn0/DA9NDtQuBzzBdqMVdFZdMcyxsSTT/i/PNbNDzrEEVi8OdOQPjekGwtBqdUNP1VM5Rrd6A7hjOB5sRdK9buUbiYuXoquNOke122pcsEFWoyV7VmyYzMH6S5EJdONtMax0U0UhUEvibB6vSBMxB3XDINeT425+EP6w3HaasSSICUIo0hq4fP1Z6lBqZG02f5wGOQt830Tu8G3H1eIr0vtuf4C+T4rPZEKn/+4b+oGUCmvm3yaR+IbYYGg+Tb2/DD/iHh+mM4cfXwRpds/dn2L56hBN2mxqdlCscavEzXyG0T54aYLtBirCWdRj01H1vIPzOtmL8Wkm2zvJpvP+RwLgx4ni2xyio0IhzBp6oq6kfzVE2Z4snUS5ceEQa/XC8K0ndgW+mWF3KCh58YLzPtp7IlwjVjdWFM6mMomBGNMmB5m3fCH8G+zYKq4A9ov8FK6ERcEhCgnnRBMiVeU9lo/Jvxbm7EqPkvWphKI5VYs+AuyCqubdK5FUoWC2SUdwgp1k7Ugvw2DdZHUffzMn6wbtX31RPoL5MSi6Yl6jdCNNVPqRtywsFvdpDM8rzdJN8xsnFLBlDR1La+0WASa1Y1ygTZjZXMW9WJz5xSOHkvvTFmubibppmiSq4ewaXVjiNEc6KY/HIvrGLUn0E0Fyt2Z4uaBXKzTTbbqKNy7qbS6mW7vRtn8LritroigxN6NxVgZzyIcG2/tcEEWdx6bP/M0qxs11kj2O8y6SQOS+PUw2btJNDEe9ns2uuEaYYyFgTausQimguTbxXxewwUKwZS2J+I1QjfWlNYN475aPX9gCqb4uypKU/KdKf3ZrfZurO9MCbO3km7k1orvTE0aq6KzaI/lz2MRTMVMd2eqcKtYf954pvP1x8N+EokEgc3qhm+E2+XV6CZrXL/cCIKJPZ+8Vaz0pOAasVU8EfwjhgUgVQx+hWxFxeUGrxswW6CbhjLxd4zAREXdZDe+ZtsrwKCbxqL+eqnuHi0MU+smvhWlvccPZgJ0AwBwBHQDAHAEdAMAcAR0AwBwBHQDAHAEdAMAcAR0AwBwBHQDAHAEdAMAcAR0AwBwBHQDAHAEdAMAcAR0Uye0buoeANAuoJvaoJT+WzdxH+oeCdAWoJt6oJT+0wywxgHOgG7qgVL6dzOAboAzboluokGXy9TkOjHuFFBK/2oG0A1wxgTdxLOY5WmSdE//Nn9kWaE6i6ibPxW+fv34+E42Svf3vn6Ny/fuc4N35/FHrvz+XvI6OfT+ntpsMdANcEY53WSPsIyfbBm/lT5SmVihOplu5neK2UIpvRFhHx55hHR3WfKW7Xa9Rx8Yu7m52e0S79GHuHy3S0h3N3sd12csLmY35YFugDOm1A1Lkp/EqUugm9JQSiOO6+uR75HVwXWkY7BKPH8Uv47rZeWrg+vr68EqySuUBboBzqigm9w30+gmig3hZ6mUQq5cyD1gTOEk5SrIg6ksf1Nx+57v1xaCUUqvOC4P1j1v/eDy8kpHsEq89YOrq6vLy4N1j6wGl1n5anCw7iWfqvi+v7a2trGx8ezZs42NjbW1tSdPnkh1oBvgjJnphheC1Ii2QpTGYyxZKOX53vgMJ1JJmlYzkhJsJpVk3ejb52PAGnVzwXH+5h5Zfvjz+fnFxcX5zw+Xk5G69+b8/OLi4s09bvTSank5VyIRhuHW1tbLly/fvn374sWLra2tMAylOtANcEZF3QhT3NRI0eomzGZ+miJSjImkklwnUrmwVcytbgrbrzEEo5R+4TjbWSHL3/10dpaXnO2skJWds7MvX77EH+Y1ufKVnbOdFSIdyzMajTY3Nzc3N58/fz4ajdQK0A1wRgXdZDPctW6KxLFAujnlODl5fZcsf/v+RCy5+/rk5PT0NP5MrZnUOHn/7TIhd1+fGhiNRk+fPh2NRtpPoRvgjCp3pvjJPCPdCMHOwE9zYgvBVOK4grDIrJsmBVPHIu8eLBGy9ODdUfz26Gi7QzrbR0fHx8fbHbL04F1Svt0hXHln+yitTEhn+9jAwcGB6SPoBjhj2t/dKAGO9BnfiLaCVgcs2WcRdoWNW8X8nrJvtboR2695q/gPhcP9b5a4YVr6Zj8uf9XhR6/z6vAwK++8Sl4fHr7qxMekn1oC3QBn3JJfFU9HvcHU780AugHOaJduoij0PWHRxN8FcwmldNwMoBvgjHbphgnBVG2uYYxRSn9tBtANcEbrdNMcKKW/1A1cA1wC3dTGp0+f5vysvsnUPQagXUA3AABHQDcAAEdANwAAR0A3AABHQDcAAEdAN3VS940p3JkCToFuaoMizxRoGdBNPVDkmQLtA7qpB4o8U6B9zEs3i5KAhdWUNIYizxRoH0W6kZ5TUyqVwqym7m3NUUWRZwq0j4m64Z9KNcepaHok4G1NGkORZwq0D1vdMO7JfvOghbpBninQNkrrJp3/g272FFDdwz2zh3gyXeooqXB5/fu8BenR6Lc0RxVFninQPkoHU+lmiv6ZeHkeKOMzg+NSNZ9U0eqGN0Z20oXOUUWRZwq0D/utYn3eBWMeKEEsAp4fahK8lAmmbkGOKoo8U6B9lAimuMJi3XAhV6SxgHqU2mxx+S3IUUWRZwq0j8q6MeWBEgMTLnKRC9N8UpV1s1A5qijyTIH2UVU3zLAdK2wVczFZ7ikln1RSoFv1KJu6C5+jiiLPFGgfc/1V8ex/ktccqgdTdSeYSoBugDPmpZvsfs6c2nfPbHNUUeSZAu1j9rpJ45RbuLSZYY4qijxToH3gX4TXBkWeKdAyoJvaQJ4p0DagGwCAI6AbAIAjoBsAgCOgGwCAI6AbAIAjoBsAgCOgGwCAI6AbAIAjoBsAgCP+B8FdmxM6gfgZAAAAAElFTkSuQmCC" alt="" />

aaarticlea/png;base64,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" alt="" />

  又可以了。

  这里再次引入一个问题,什么是文件保存编码,什么是代码运行编码。

aaarticlea/png;base64,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" alt="" />

aaarticlea/png;base64,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" alt="" />

  还是不能,那再改一下。

aaarticlea/png;base64,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" alt="" />

aaarticlea/png;base64,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" alt="" />

  这样又可以了。

  其实保存编码,也就是IDE Encoding设置的是在磁盘中保存和打开的时候的编码。假设我使用的是windows的文本编辑器写的代码,也就是用ANSI保存的,如何我再用其他编码打开就会出现乱码,这无关运行的事。而运行编码是则是影响python交互界面的编码,我在前面的python的第一个程序中也说过这个问题,我用windows的cmd运行一个python文件,为什么我在python中声明了可以使用中文的utf-8,却在输出显示的时候还是出现了乱码?这是因为虽然python输出的utf-8的编码,但是cmd这个家伙默认是用GBK去解码的,所以出现了显示上的乱码。但这并不是真正的乱码,换用一个支持utf-8的显示环境就可以了。

  好,题外话多了些,但这些小的错误可能会让人纠结很久都解决不了,所以这里还是提及一下的好。

  下面进入正题,看下面的现象:

  utf-8:

aaarticlea/png;base64,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" alt="" />

  gbk:

  aaarticlea/png;base64,iVBORw0KGgoAAAANSUhEUgAAALQAAAAxCAIAAAD80hQOAAADKUlEQVR4nO2ay3XDIBBFKUsNmXKoxjQTlZKFs5D4zQcLWZIhevdokYPNQOABI/PMCwAF8+0OgH6BOIBKEsfvNOEZ6LlaHBe0Bw6hN3F4a6w/uzv/ihNHrD9xTG7OC2Y3kRKV2U3GaCP1hTjvGjkkDh+x4+hLHNKANY1iWkbLDGeTvC9OCJOq9qCOvHunSaM3cYi0DEAYNW/DdBZyaY0zu2mtnK3Pr6vDW31jO5QBxNEyit4a+9QqfBSnG3V4a6y9JjMbQRxF0uXtussvf5DiaTL2+fLWWEePlZ1xPK+6JQ471UJJIYf2OItGL0rbxxBHORrLZj+7B8sDZhcmNUwCWZ3NcWRxbIgTjzeSHJT5Y2Mcb5dvQxwFZDhSTlF+Go8DZVKb40jHSkOcvCSyoz88CA10BqOIIx+nsMKSAsIsemvWFabsHI1xxIR0W5y4Yzj6WjHPLf0hcVilMxlGHGlnXQ9uKVewNiTy8axmKd++ODxz3BKHvAKL6313HKFPBzOOOOiWu5v/Gud4BhIHuBqIA6hAHEAF4gAqEAdQ+YI48Az0XCoOAAgQB1D5RBz3MQ7e5z8t+Ewc+42D+8hsgqe3lXOi4a9ndotDnJztM1Zdi+mSgn+pzYdXXptkceMFSHafypwaxkzu51oZdsXBOcfGgaza6TLbRLiDLatuNheWlsTna/ae3/WFGKkt70KRv+FZknF0QrpFHW/sdLqRh5S8aYt/zMVR8YWQu/g7slUcca2/9dCSuWW1JDudZNR7kenNbIKSKZC2JVkSvXs82K16PFeoCt09z5KM7TtH4cWqLSnZ01mx08lGvXLhFzZBxRRI3GKCJTFNeDxPQofoPgNtnCIO+VxIE8bsdIJRjzkptNYrbVUsiXl/NKPyHd9dCe3iEJJE7auVWuLOsRr1SjteaeZjrVfaIpbEn3xn8tYsJTFcsSfd9IcNQkNCuiYGyainU2aNtBa30xVvnOXuQnID3nqtLWZJTLFZ0298yHfkpJ/PrzTY9WvmGx3crQAViAOoQBxABeIAKhAHUIE4gArEAVQgDqACcQAViAOoQBxABeIAKhAHUIE4gMofXvJuXQooJR4AAAAASUVORK5CYII=" alt="" />

  我们可以发现,随着python编码声明的不同,其字符串的编码也不同,所以我们得出一个结论:

  python中的编码声明影响的是普通字符串的编码,也是就用工程函数str()或者单纯的引号创建的出来的字符串。是随着编码声明的不同而不同的。

  此时再看一下这个现象:

aaarticlea/png;base64,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" alt="" />

aaarticlea/png;base64,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" alt="" />

  发现Unicode字符串无论在上面情况下都是一样的,因为它永远采用的是Unicode进行编码,不管你声明的到底是什么。

  Unicode字符串的创建,也就是Unicode对象的创建可以使用工厂函数unicode()或者在引号前面加个u。

  所以,我们可以得出一个在python进行编码转换的规则:

aaarticlea/png;base64,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" alt="" />

  再总体扩展一下:

aaarticlea/png;base64,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" alt="" />

  只要python支持的字符集,都能够用这样的逻辑在python的内部进行编码转换。

  只要知道了这些,那么在文件处理中就能避免许多错误了,关于python的文件处理我们下篇再讲。