Python 简介

官方指南及文档

  Python2.7官方指南(中文版):http://pan.baidu.com/s/1dDm18xr

Python3.4官方指南(中文版):http://pan.baidu.com/s/1kTrDXIZ

  初学者建议按照入门指南来学习,关键一定要按照例子写代码;这里用 Notepad++ 来快速编写、调试运行代码

Python 帮助文档:在线 https://docs.python.org/3/   本地(安装Python时已默认保存该文档)

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" 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" 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基础语法简介

运行脚本及编码

      由于Python源代码也是一个文本文件,所以,当你的源代码中包含中文的时候,在保存源代码时,就需要务必指定保存为UTF-8编码。当Python解释器读取源代码时,为了让它按UTF-8编码读取,我们通常在文件开头写上这两行:


# !/usr/bin/env python
# -*- coding:utf-8 -*-

      第一行注释是为了告诉Linux/OS X系统,这是一个Python可执行程序,Windows系统会忽略这个注释;

      第二行注释是为了告诉Python解释器,按照UTF-8编码读取源代码,否则,你在源代码中写的中文输出可能会有乱码。

      如果你使用Notepad++进行编辑,除了要加上# -*- coding: utf-8 -*-外,中文字符串必须是Unicode字符串

      ( 字符编码 具体详见 Python学习(四)数据结构 —— str

注释

 # 注释以 # 字符起始,直至实际的行尾;代码中注释不会被Python解释;文本字符串中的#仅表示#
# this is the first comment
SPAM = 1 # and this is the second comment
STRING = "# This is not a comment" # and this is the third comment
''' 前后三个单引号可进行多行注释
通常是对函数、对象的说明
注释代码仍以 # 为主
'''

  (Note: 使用IDE的注释快捷键,可方便注释/去注释多行代码;如 Notepad++ 是 "Ctrl +Q" )

赋值

 # " = " 用于变量赋值;变量直接赋值,无须定义变量类型; 无须定义变量的数据类型
a = 20
# n # 该条报错!变量在使用前必须赋值,否则会出错
x = y = z = 1 # 可将同一个值赋给多个变量

    第三行代码若执行,会报错,显示如下:

    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" alt="" />

    在Python中,变量名没有类型,但对象有;变量名只是对对象的引用(内部实现为指针)

    变量命名规则及惯例

    语法:   (下划线或字母)+(任意数目的字母、数字或下划线)
        变量名必须以下划线或字母开头,而后面接任意数目的字母、数字或下划线。

    区分大小写: SPAM和spam不同
    禁止使用保留字

      命名惯例:

以单一下划线开头的变量名(_X)不会被 from module import *语句导入
前后有下划线的变量名(_X_)是系统定义的变量名,对解释器有特殊意义
以双下划线开头,但结尾没有双下划线的变量名(__X)是类的本地(“压缩”)变量
通过交互模式运行时,只有单个下划线的变量名(_)会保存最后表达式的结果

简单的输入、输出

 # 简单的输入输出
raw_input("Please input: ") # Python2.x raw_input()
# input("Please input: ") # Python3.x input()
print "hello world" # Python2.x 可以不用加()
print("hello world") # Python3.x 必须要加(),不然会报错! Python3.x print() 会是空行,而Python2.x print() 则会显示(),须注意!
# print("This is "Note"") # 该条报错!需对"转义

    运行输入后,显示  aaarticlea/png;base64,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" alt="" />    raw_input("Please input: ")  括号内为显示的字符串,用户可输入

                                     通常会对用户输入赋值,   如 a = raw_input("Please input: ")

    运行输出后,显示  aaarticlea/png;base64,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" alt="" />     print("hello world")  括号内为输出的内容

      Note: Python 2.x    raw_input(Please input: )    print "hello world"   与 Python 3.x 有不同;copy 网上代码若运行报错,有可能就是版本问题

    

    关于特殊字符及Unicode
 # 关于特殊字符及Unicode
print("This is \"Note\"") # \ 转义
print("This is\nNote") # \n 换行
print ("Hello"+u"\u0020"+"World") # u'xxxx':Python2.x unicode对象 = 直接在字符串前加u关键字
print("Hello\u0020World") # Python2.x 直接输出 Hello\u0020World ,Python3.x 会输出 Hello World

    字符串若包含 " 等,解释器会引起混淆,需转义;另,\n 表示换行

    从Python 3.0开始所有的字符串都支持Unicode(参考 http://www.unicode.org

Unicode 的先进之处在于为每一种现代或古代使用的文字系统中出现的每一个字符都提供了统一的序列号。之前,文字系统中的字符只能有 256 种可能的顺序。通过代码页分界映射。文本绑定到映射文字系统的代码页。这在软件国际化的时候尤其麻烦(通常写作 i18n —— ’i’ + 18 个字符 + ’n’ )。Unicode 解决了为所有的文字系统设置一个独立代码页的难题。

语法规则

# 例一:Fibonacci数列
a,b = 0,1 # 变量也可这么赋值,但不建议
while b < 30:
print(b)
a,b = b,a+b       # 相当于 a=b b = a+b

    运行后如图: aaarticlea/png;base64,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" alt="" /> 该代码输出了一段 Fibonacci数列 ,使用了while的循环语句,暂时不理解无妨,仅感受下Python的语法格式

    需要注意的是:缩进

    Python开发者有意让违反了缩进规则的程序不能通过编译,以此来强制程序员养成良好的编程习惯。并且Python语言利用缩进表示语句块的开始和退出(Off-side规则),而非使用花括号或者某种关键字。增加缩进表示语句块的开始,而减少缩进则表示语句块的退出。缩进成为了语法的一部分。同样的如 if 语句如下:

    根据PEP的规定,必须使用4个空格来表示每级缩进(不清楚4个空格的规定如何,在实际编写中可以自定义空格数,但是要满足每级缩进间空格数相 等)。使用Tab字符和其它数目的空格虽然都可以编译通过,但不符合编码规范。支持Tab字符和其它数目的空格仅仅是为兼容很旧的的Python程序和某些有问题的编辑程序。

 # 例二:简单if
a = 2
if a>1:
print("a>1") # if 无执行语句会报错,若需实现if条件下print,参考如下 a = 0
if a>1:
print("a>1")
print("a!=1") # 该语句始终会执行,因为缩进并不在if条件下

    例二 直接执行会报错,  aaarticlea/png;base64,iVBORw0KGgoAAAANSUhEUgAAAp0AAACWCAIAAAAT76SDAAAgAElEQVR4nO29a3Ac15nfPaVvbypvvW9SW6l82Hiz3viycbzasla2KVti3igSl6a5tAyQkCjTlZgWIEt2NhItU5QsMRQJUhIlkxLt1WvB3pUIe0mCFMAbAJIgCIAgcRvMHYPbYO73+326ey5IPvRMT09fTp/uGXBA8vnXv1A9PafPec7pnv7hOd3To+r6pz+44gW9l9J52CYZa92i1rgJjZvQlp3jWOfO6TyEzk3o3IS+7JyYdS6utc4szxnaGrYdXM86s7POrKbyt7zgymlcOa2L0LlJnYfSefJ6X17vK+h9BYO/aAgUDYGiMVAyBkrG4GrVgaoNItYz9pet41nL2Leq9a1qvCW2ZytWe6qeYXnaXZpieZK2qzTpKk2wfJu2s3SL5XHGjrJvVjxmL47aiyO2Au0b1vzwCnV9mRxaJq8tEVcWcoPz2QFzZsCc6Z9LXzalLhmTF43Ji8bkBUOC4/P6OMfVt/g2Jss2VN0n5PPGlJgvGNOyfNGUEfVcFuFL5pwyX54nsLxA3oMW7y/+0LGX+xfIgUVqYJEaWCAHFsjBRerKUv7qcoHxNUvxmqU4tFIStRXX1xvkYb5tKI/wba96lG1Hjcd4vsk2+yRQOS3cpu0q3a49h0y4SpOuyhmm9rQz7amafXZSe0pqb0nNOo/N0mc2X0njK2m5XtX5uKdH9pmTXojlVlt/2BHL5L1xqtakN07WLks5RtCOZvJHj/8mQxaZNYw9sVzVUUxnI2ny1+3/LWw22z87Q9v52Rl37xl37ylf7yl/76lg76lw36lw36lY36l436l436mklBN9/8x2vLJhrO9UuO9UqO9UsPeUv/eUt/eUp++0u7fH1dvj6O1x9PYEZmd3PP6fE0TJHCyZQyVVKFXQeynGcuheZrbWQ2g9hK7snM5D6Gl7CYOXMHgJo5cwegijl3GOY4NH1Hp3ludM1a6qdVVnta4sjX+tM6txZrWunIZBu5sso93LRXuZ62XLgbo40XW1RNf6VunDHZPoNNSnMYkuBnUe0WmP2otl24oj1sLwSn54JX/dQtFcv7qYY6P98lz6kil1sYJ2hu58ojNcFyA6m+tSUF8LuqMA32iu39d0l+qvgqHrXyDZdKfRLoPu2FxvIN0F0I4E/A1ButuE0C6L7s6yx2vPD2J0n0TQ3S2AdlG6+wTpvipJ91hutXVX47n+9q9OpIW4XkN3OVz/8EfPBk0my6luy6lu26lu+6lu55lu15lu95lu35luf8/JYM/JcM/JcM/J2NmT8bMn42c/TYo7fvbT+NlPEhXHzn4SO/tp9Oyn0Z6T4Z6ToZ6T/p6T/p6TvjPd7jPdrp5u1+k/OE7/wX76Dyun/xCYmtr+/307TnM9WFItBin5XCfKUK/gvEJxUs+A3EuYfITJR8z5iDk/MecjzD7S7CPNPoLtOUl7cxybvNmyPTU2erJGd9bozpb/IXBlda6M3p3VubI6d07nymndhM6d07lJnYfUeSk9i+t6f9Hgr3LdwOK6GNFxoC5M9ArXcdJ0xpNCUL/NMmaOXs7UHaUxmuu24qitOGIr3hDmenZgPtNvzvSb0zVcNyQuihP9vD7ep4+LQl2fYBNdEurA9bvSwHVJtIvQXRjtdvHc3S6P7rd4ZtP9Ngbdp93CifuMWOIunLsL0J3D9UiackUIV5TlSM4VyVVe5qqOIJylHU6Sh9/7MJGlmDWuSNYVzrrC2eP/cLK1rQPhY7/+xBlK03ZUHErkPvjhdr9Ot/Bp19KnXZZPuywnu2wnu+wnu5zdXe7uLnd3l7+7y9/dFeruCnd/HO3+ONb9cbz743j3x7/e+zpT+a/3vh47+dvf7P1lzZru38a6fxvp/m2o+7fh7q5gd5e/u8tXqdbZ3WXv7rJ1/26l+3crJ3+3fPJ3nlu3Wh7bUOW6wSuX61Wis/Jy0uAljT6SxjnNcrOfnA+Q8wFyIUAuBMjFAMHxgl+J5/25eZ+Azb6cucr+nInGvCdncGcNnpzenStfDvCQeg+p91J6X17vyxt4XDewuI5JdD7UuRPvLKLP0q4lumCOPs2Ze69N0wVzdEyij9GnA1txpGI2168tk1eXiCuLucEy19P95vTludQlU5noiEy9r2JRqFe4Lolz4PpdbOC60tz9BstiXFdAdwbw47ysXVnuLkZ3JnFXC03LC9Odd/6kuR5KENZApuxgxhrMWANpayBtC2ZswYw1kLYFyy6vD6RtgfIyyynawQRx8N3j8QzFrLEGUlZ/yupPtbZ1lEqlVXG1tnWs+BIcB+LZ409/z6eeMX98Yv7jEwsfn1j4+ISl64Sl64St64S964Sr64S764S364S/68Ng14ehrg/DXR/QbtnRzrTY2tZxYs9ezppQ1/FQ1/FQ1weBrg/8XR/6uj50d51wd51wdp2wd52wdp2w/O6EpevXi12/Xuz69ULXr92jI09teLjKdb03L4frhLYW6gzRTT5yzk/O+Qizn5z3V1geJJeC5FKIXA6Sy0HSEqoxvRLHSwGC5ZygF/25RX9uwV9hvC8358uZvDmjJ0fTXe/J0Zf5dR5S7yb17JTdX6TRbvAXDWW01w11fo7OQN1XOfTxoD7lEknTsWfdx1hEH6s9HZS5TqPdWri+kr++kuejnZ2vC3K9T8hcolfcp0/cLVy/Q1fZ7zO64w8d++XdeJVdbu5+g+cG0p05IYyLAB5Fd+S0PNZFd58o3TmJO811byRjdkardkXNrui8q/xyvrJML8y7omZnZL5iM8v0S1cotf/w++FkrrI+zLi1rWN1dfV/i6u1rWPOEZqz19gZTBz93ibX7dua94/o3j9ieP+I4f0jc8eOmI8dXjh2eOlY58qxTuuxTsfxTufxTs/xTu/xTu/xQ/7jh/zHDx3/Hy8xjdIgL5VKdFvbn37++P94yXf8oO/4Qc/xQ+7jh5zHO53HO+3HO63HOi3HOpeOdS4cO2w+dnju/SPGX71t/NXb+l+9bbt25e8eejCeK80Fi3K5Xp1+Z6BuZEHdHCDpHH0xSC7SOA9RljC1EqZWwqS1Dq+EqrYECTEvB4ml8kxAbsFPzPsJc2Um31S+YE8YPJWU3VPmuoHmug+L6+i5d9TEOytTZ/6fFZt1n+YRnbaCHB1BdNo3aKjbisM01y3565b8tWXy6iJxZSE3MJ/tN2cuz6G4Lkj0Ktc5OGcMXAeu32dcx8nd+Vyv0l2I65KAF6Q7c66QTXdk7i44LS+WuGv4aPeVz6I0112hlMEWErPRFjJyl4MGW9BoCxptQYM1SL8s2xp0BpNvHDoajGUM1qDBGjRYA4wZxG5/+nnODDy9vrWtQ7/iL9tSXnAE4ke3Pu4cH1MfOaA+ckBz5IDuyAHDOwdM7+w3vbN/4Z39S+/ut7y733p0v/3oftfR/e6j+91H93uP7vce3e95d//xn/1PNtoZqB/76d+73n3Dc/RN19E3XUffdB590350v/3ofsvR/ZZ39y+9u3/hnf2md/Yb39lvOHJA//Zb2rffmn37rZWBy9/966/Ec0U5XBeHuokF9YUAVc7RWUS3RihbhLJHKHuEckRrbI9gO0wytol7JURYQhXAB8tT/fM+wuyjJ+cJk4cweAlDGeqU3ps3+PIGf8HgK+p9xXLWLsL1eq6mCxCdthDUBYlezdQV5OgOAaIzp4Mq11cKwyuF65b8kCV/bYm8skgMIrmOwHnZurgo1IHrwPX7mOsItN+wiqL9BpLrstL3GrQ3KndHXnTHmJYvX3HX+lejudXWXR2OQEJrCYhZtxLQrdS81Fr8CNv98dfeescfTVfW+Bi3tnXE4/FEItHa1jG76NEseTVLHs2Sh72eWcnY5ou9s/kxx+iNqQOvTx14febA67MHXtcefF1/cJ/h4D7zwX0Lh/YtHdpn6dxn7dzn6Nzn7Nzn7Nznrth1aN+xF37GNJFIJLY//fyvXviZ89Crrs5XXZ2vOjpfdXS+au981dq5z9q5b6lz39KhfQuH9pkP7jMc3Kc7uE974HXNW79Uv/XL6bd+uXzp/He++mVRrjN0P/bhR7K8EKAWg9RSiLKEKUuIRfQyxfOOKOVUakekahbvSbatIcJWTu4JS4iwhMilALEYoGfmCbM3N+clTB7C6CEMXkLvIQ3e6lV2va+g8xZ0vqKuQne9v6T3l2qgXg/RfdWDGwF1BNEnXKUJRbPu/AS95kRgK92wFW9Yy76+Uhiy5K+vFK4tU1dF0H7JlLpgTF4wJukJdkGcs92ri3OJLpPr64Huirkuj+5NJ/Gd4vp9e5UdE/DCdLeX3UC636xF+1rTHedueZ1vNZZbbdnVoV32fjZq5Lh31PjiywfRt7n99OWDvaOGGo/op82O51/+5YLd3zdq6B3RV6zrHdG1tnX4/f5AINDa1nFuWPPZDS1tzvqzw5qzw5pzw5pzw5qz1zWTRtsvP/8nxj982vO3j372t4/2bn70wuZHL29+dGDzt69u+fb1Ld8a3fLIre8+cnvrI9NbH9FsfUS39RFDrd9uaWnZ0U43QbdypKVFzyqg27phduuGma0bprZuuL31kbHvPjKy5ZHrW751dcu3BzZ/++LmR89vfrTvO4/1bn5s5vh73/qTfxnPFk2BwlywiOK6ackh5uf3fcD+e+zDjxaC1FKQotN0S5iyhl3/+NQDVT11cTZGOaNk2QsXtj7wwNYzzto12z9dIKtrxt574IH3rkRJR5R0zF/4bqWm7552OiKkIzLz5gNsHR0IE/YIyUJ7+cI8PSdv9hFzvtyclzB5CaOHMHjIyg2DElxHX0pHXE1XQnS3KNHpT1djiU6bJvqwtTgszvXLFa5fNKUuorleS/Re4DpwHbgun+432OZxHRPwknS/ybnijs7deTfMi9Fd2UV3Nt2judWWXR2zi54zw/oentm3mInd5tYzrKu1dsJoa3/p9Xmb7+wNXc+wtmJNz7Cmta3D5XK73e7Wtnb2/wctO9qZ9WeuqU9fm6F95trM6aszt/Qrr33u/zF8+o+n/ss3ev7LN84+/o3ex79x4fFvXHr864NPfP3aEw/feOKhm08+NL7poclND6k3PaTZ9JCO5bef+l7Ljnan083I5XK3trUfeep72koZzaavzWz62tSmr01s+tr4podGnnxo+ImHrj3x8OATX7/0+Nf7Hv/GZ49/4+zj3zj7+Den3nt7w7/6v2iumwIFlcFX0HvzfLof+/CjmVkNpo99+BGdrC/TmXo4b4u4/nGb6junnfYIZY84P9mmeuCw2hWjaF/pVKlUKpXq6JVYJSlfuLhF1fLpAitNHzuqUh29EqWcCxe3PqB6Y4y0hwl72PHJtncHI6QjMvOGSvXGGGEP58qOEPYwYQsTtjBpDZErIcJSvdxeno03eXJGOmWn7/irXGXX+fI6b0HrLdBc1/nKXMd/2ozE/XEM1BmiVzzlQabpzP/LLK7fahDRR1ipwDAL7TTXabQPLhIDC7n++exlc+bSXPrSXFqY67wcvVeS64roLgj4OzYbrxjwMBtfP9fZL8tor8zGM3SnAU9zvYF0v2OAXwu6I55pc5PnBs7Mo+mOvp8umiu17GrXLHp6hg1nhg1nhg09LLfsaI9GozFxtbZ1nB3W0+6pLEyYylw/d0N/dlhXsfbssLa1rcNqtdlsNquVa1qtbe09Q7Nnrs2euTZ7+pr69DX1mWvq24aV1/7s/zWe/Kczj284+/iGc/91Q98TGy4+seHSE98cfPKbQ09+/camh8f/9uFbmx+e2vywevPDms0P6yo+8tRTLTvaV1bK9W9/up0JoLWt/chTT9HFNJv/Zmbz30xv/puJzX8zvvnhkb99ePjJh689+fXBJ7956Ylvnn9iQ+8TG8791w1nH98w/f7bG/71v4hnCya/ONd1XurYhx+psMVw3cLi+j9tU20546IvpTtvHlWpjl6NUe4Y5Y6p31Sp3rxJ/6VcUcoVpVwVrpdfRilXhevMQjmPjxDOKOmM0lwnHRHGZa5bQ0Q5ZQ8Sy0FyMUAs+ol5X87sI+Y8OZOXMHrLd8/p3GT5lgIW1ytZe0nnLyn/Gpt4ml5DdA9q4n1NiT5SO8XH4fqQJX/Nkr+6TElzHUl04DpwHbiumO43+BbiuuLcXeDhdEpzd2W31InRneb67IKnZ9jYM2zsuVH22RvGszeMLTva3W4PQq1t7eduGGifHTacHTacGzZMmOwdL78xbw98dsNwblhPm6Z7a1vH0tIyQq1t7Weva3qGND1DmjMV3zZY933+T4z/3H12y8azWzf2bt3Yt3Xjpb/bOLBt49VtG4e2bRzZtnF828bb2zZOPrVR/dRjmu8/pvv+o7RbdrQvLpYr3/50++Htra1t7XQMS0vLrW3tdDHN9x+d+f6jU089NvHUY+PbNo5t23hj28ahbRsHt23s37bx0t9t7Nu6sXfrxrNbN6pPvLfhT/5vFtf9XK7rFHF9KUgtB6tct7O47oxR7nEW1yuMv9qpUnVWkvjFi1tULZ8uUkxO77p5lE7oXYsXt6hUW3pc1Sl6FteZNY4I6YiSTMpezdf9xIK//M03kzdr8uQMHvqJtkT5Vn8PpfVQWk9e48lrvQWtr6D1FrS+otZX1PlLOn+pkffH8aA+6UZNvNfc9157q0v9OfoNIbRftxaHVgq0abRfWSL5aL9oSl0wJC8YkvQ9cYI4XyO6N/ceujsxId90Et8pruPTnTN0/Nl4effQrW+uMxbgOpO4i9BdHuAbQXfJG+bxp+WZ++lormuXfOdG5s6NmMseLftnPz/U2taO8M9+fuiz0Tm2z43MTc05n9+zf8Ee/GzExPGrb32IrvDVAx+cGzawfXZYP2Gyv/rFf2s6e6p3x5a+ti0X2rZcatsy0LZlsO07Q23fubFz88izm8af3TTx7KaZXZvUuzZpdm3SVXz4maeZyg8/87TmB08e2fkMew1dTLtrk3rXppldT048++StZ58ce/bJkZ2bhp/ZfK3tO4Nt3+lv23KpbcuFti19bVvUH5341r/5V7FMweCjTH4e13U8rtP337MpznlZ5TqTr0cqXO9xOWN5Z0z9vx5QqTpn3THKHXOd3KZSdaorgG85uUi5Y5R78eJ3K8tcrsfodP8B+nK7q+yZN1UqFXN5/fCMM0rRKTt9lZ3+RlyV6/4y142enMFDP3gup3MTOvp7+Wyue2u4rvWV1pDo/AfOiOfoAg94bxDRaV+3Fq+LcH1wkRiYz5W5bkpfNKYuGqtc7wOuA9eB62uTuItyHYl2WXQXfbB8Pbl7HRfdNd5SNFfa+dzfz5qdF8aXe28u9d5c6mO5d2yxb2yxd2yRXjg/ttjH8nnaNxcvsHz+5uL0vPf5nx9YcoTP31y4UOu+MXPfmPn8mPn8mLlv1Nw3au4dMfeOmPsq7h2Z6xutvqTXTM25fvkfP2e+8NnF3W2Xdrf1724b3N029FzbUHvbSHvbWMeO8Y4dEx07pl/YoX5hu+6FFt2LLYYXW0wvtphebDHWml5jYJler3uxRfdiy8wLrTMvtE78ZPutju3jHTtGOnbcaG8bam+79lzbwO62/t1t/R3Pak7+/rF/+29orhv9eZXBX6BN053DdQbh9AL7ryTXP9lWBa/qkNody1f4rXrzZnVC/rs9LjbXBfL1GOWKkc4oeaVTRSOc4fqbY4QzQjgihCNCsrluFeL6nDdn9GSN5WfP5bQu2qTWTWjclMZNzbopjbfAWOsr0hd7+BPvbKjziS458T5Z6wm3jBy9ajTRxafcBTL1ihm003S/ZslfW85fXaKuLJKDC0S/OXt5LnPJVEZ7+bFxd5zrDaT7HZ6Nlzch33Qe3ynAyxo6gdn4RWpgkeLPxrPpLgz4u4TuwoAXuk9eGd3HGDc8d8ebluejPZotdex5c1K3dG3W2T9p53qq7IGp8pqBKfvglH2A7UnbwKRtcKrsgUmbZin44t7OFXd8YNI6MGkd5HlgcmVwcmWA44mVgYmV/glL1bdpL88u+t548AtLg/1XX+q49lLH0MsdQy93jOxpH9vTPr6n/fYrz03vfU699znt3t26fbuNr+02vbbb9PrueXGbaz33+m7j67tNr+3W7vuRdt+PZvf+eGbvj6f3Pnf7lefG97SP7Gkf2dNON3rj9T3qs2e3fenzsUze4KUMPkpl9BfZXGfozuE6J1/nrKevrwvMw5922sOkI0K6onlXjHLHKG1Pi4qVZ6tUKtW2i5oY5YpVLrdXuK7paam8VXGUdM6f36J6YP+Y6Dx8+fp6qHYenn78nDdn8GQN7qy+/MMwOY0zp3ESaiehdpGzLmrWRWk8BY2nMOspzHrKaNd4y3THhLqMNJ0heuWL6Zhp+k32R1HORXQE0floH7IUaDNoH5jP0Wi/aEpfNKUvGFMX5NMdBXjI2u9trjeO7uzEHecb7fcA17lX3MW/BdcouvMBz6Y7zi11ohfdpRJ3X2r12O/Pdv7qH4y22JjRf13nu6b1XtN6h0R8HWUPbZM9+j9ff8ceSFfWuLnW1C5r3Nc17qFZ1/WKh2adbBut4QNf/4+W4aGRN14ZefOVsTf3jO/fc3v/nskDe2YO7FG/tUd3cI/h4MumzpfNh19eOPLSwpGXlo/8vQXDyxXPH/n7+SMvmQ+/ZDr8suHgS9qDL2kPvjzz1sszB/ZM7t8zvn/P+Ft7J945YPznk6f//663nt0Zyxb0XtLgFeO6B5Wv83l/7MOPFgPUUlDovrkIRX9z3VVJ0FWdanou3RklnTePqip3z105pFI98P6V8n1z6jdVqi1nXK4o5Rp7/4HD5U1cCxe2qFo+XRC+b64C9TLX6cfPLfiJ+fJzacpc17noX33NzTqzamduxpFTOwm1k1S7qFl3ftaTZ7iu8RY13mLlRk28NF0B0Tk/3ILM0ccQUMcmOuLHIq+vFGnzuT64QPTP5y6bs8B14DpwvSlcl352jVLAc04smHTH+YE4Nt0lv+lO030+VFp0Btv++wv/650PZ4xLzjBhC+UY20MEyzl7dU0O7X0Hj8XSVOVllutg1h6sXeY6Yw9m7IGq3330r4NLS5aBi9aBi7aBC/bBC/bBC87BC67BC+6rF9xXL/iH+vxDfcGhvtBQX2ioLyxk/voQy8GhvsBQn3+ozzfU673W67p63jV43jVYbss+NKi+dKH7gxNbv/qXiw7/cojSeQiDl1IZAyWjv8ihO8N1weycjXl6geH6cohaCbG+53bGxTyRxhWlp9ZbPlmgnDHGzk+2qVSH1M4o5aS/DlfRltPOyqNsSPXpFibDf2OMcFS+51Yt/cD2f5pnJ+ukJUgsV54pa64+Sjard2e1rqzGmZl1ZNWO7IwjO2PPzjhz0w5ixkmqXZTaTdFcV5fpXuU65453sTRdmuhu3q+xuaQm3oWIXp17ryNBr7py1mDQTtP92nL+2nL+yhI1uEgOLBD987lLlZSdpntTuH4nZuOB7neQ6w281s7/RjvqcjvQvfaKuwK64+bu4s+x4aPd4CXtwfRHpwZefPVQy652njtq3d6yq711V0frro6WXe2tYn529/Yf/Lj12d1I/wjLO3/UuvNH//1Lf/q9L/y77/2HP/3ef/jTp77wp0998d+1fPFzLV/6s9Yv/9n2v/z327/y+R1f+Yu2//QXbV/9wtN/9YWdf/XFnQ9+aeeDX9r54JefffDLOxn/dXnh6Qe//Ezty6cf/HLbg1/a8Vdf2v7VL7b+py+0fOUvvv+Vv3jqLz//vS//+d996d9v/eLntn7xcz/+2pc/+G/POIJJkzulpX/ezEtKcx1H9PPmOLfE28KULZp3RPOOWN4ZzdOEpi+E17h8dZyeSyfsjOkn0kSr32Eru5Kg20IE2/QjZq21X16nk3Vz+ddfKsm6KzvLcN2enbZnpx25KXtuusJ1tTuvrnB9lua6F+uL6Vyi10J9QjBNr0Bd9Gkz/H+l2dfUG0p0PtevWQrXLIWrwHXgOnB9nXGd+bWYhtCdc6eOIN3R192VX3QXSdznwyV/qhTJFMvO8l2quBjJFqPZUrS6XDZ7me1IphilzXkrU4hmCpFMIcpyRMTRTL7qtKgjLNeupyJpKpKhImkqkqIiqcrLlBynqUgmvxQgZp1ZjSunded0HoLFdV+B9V32vAKuV6fiQ5Q1nLdG8rZI3k6jPZp3RChnNC9k1vNiORZ+fKyw6UydPQO/GCAWfDmzt/yrbnp3RufKaFzZWUdmxp6ZsWWm7dlpW2bSlpmyZydtuSl7btpBTjtJtSs/46LU7oLaXVB7CrPeotpTLN/TIeeL6eiJ99scole4XvPddDGc20ujtqoVz7ojfmBqaKVIm0b7NUuBjXaYjb9D99A1HcN3lu6yho5ZrqK99hvtMh4dfzdz/Q7TXTR3l39LnfS0fO39dGpvNbNiPcpmVeujb2qufn1J6yvpaNPfVa48mIRrL/2k0bL1voLOm6/aV16ofBeaNqn1kJrqD5eTGjehcRMaV47xLGNnlrG64uoaR4bxjD1NW+2omlnJcoqx2p5W29P05rNO2mW0o7guy2Y/yaCdvjHeEqZWGLrT9I0KWeq3XsR+5YX7m29h/jPmcmZ6+t1dgbozM1sexMy0LTNly0zZMpO2zKQtO2nLTdpzU3ZiykFOO6lpFzXjzldcUHuK6tpL6YJp+nQ9RHeWbjqlZ935RBdL1pXhfLhyEuFzncnaaa5fYt1AB1wHrgPXm8t1abpjAJ7/FZuGzcxjXHRH3C3PcF1dya/4aNdUbnDWVRivraBdW4Pz6vPHtDTXWWiv4bo3rxXnOm0FXGfoLsh1NtoVcH3Wma1wnTaP7rW/7UbpPJSWXqg8wcbgJY1eyuSj5nzUnI+s/PI6tRjk0L0MeGuYEjeH0JVfZZXycpBYrvyAG+s33KppusGd1bsyOldm1lkewWl7ZsqWmbSmJ63pCWt60pa5bc1MWLMTZboTUw5yyknTPT/tzk+78zPuwoynyHlkktgTYaUn3p1cqFca4DAAACAASURBVN9kQ90hj+gCD4+rj+gcrvPRzqTsHLSz8XzXzcbDPXTrgeuNmo0XvIfu3p6NbwjdBbmOT3clt9RhfBdOzaM7H+1VxvuruTuDdvp5JDTdtb6CtkzxIvPAEjbd2Vm7toJ2Ft1JxhW6E1VzuM6iu9ohgHZ01o7mugjdsxqXGNdp8+hOd4z+grveS9G/imb0UkYfZfJRc/5augeopSC1VHluvISDJOMl2gEC4cVaL5R/t638fbY5Tw3RtU4a6ukZe3ralp6ypies6Qlr+vZK+vZK+tZK+vZK5vZK5rY1e9uanWDQ7qCmnNSUKz/tyk+7CzOe4rS7yLCcDXXcO96F0nQu0VnGJDrbyoiOOImw6U4D/upynj0bD1n7nftG+70H+IZm7ZdFni9772ftInRXPDm/tnRXOi2v9nBnTGm61z5efpVNdyZx17HorqvQnUnc+WjnZ+1aoaydPSfPz9q5gBeiO86cvIKsXQnXq2j3kHoPqfeSBi9poOnuJed8JEP3eT81H6AWAhSdxC8ESFH7CY7nxW2m7at6rnLHexnn7qzOlWURPTPjSE/b0lM2hugpmui3LOlxS+rWSvrWSuYWjXZbbsJGTNiJKQc16aSmnPkpV37aXZh2F6fdxenaWXfMiXdJoo9xiE5bDtFFM3XsBB2f6zAbD1wHrt8VXFeWviPm5Bty3R2T7sLT8t7SDA/tNXT3VmbmeYk7k7VraZaXE3eBrJ2dpuNwncnaaYRLcF0I7Yg5+fq4zqN7uVdCXGcm5LUeSsemu4c0ekmjl2QATzN+zk+aK2bWC5lgbPLmBG0s39xetYFheeV298o32TIzdI5uT0/ZyrPut1fSt1dSt1ZSt1bS45b0+HLq5nLq5nJq3FJG+y1r9rY1d9tGTNrJCQc56aCmXPlJV37KVZhyFabcxSl3cdJVLB98Ine8y7iULgZ1BxbRUdfU68C5INeZqXjEbHzD6L4+Z+Phh1zvCNcbPhuPS/d7aza+zvRd7GY6WffMy77ojnG3vJpPdxba6SfRMs8Qq+W68Jx89fHhDNprE3ct26LX2quz8bNCWbuazXXenLwY15EWpbsMrtf2h9K4KS1tD6n1kPRvqOg9hN5DGmh7y4yv2kcafaTBS/Ctp+3JVe3OcqyrkJtthuIaZ+W/FUdm1pFhcD5lZYieook+bkmNL6fGLalxSxnqN5dTNy3pcUtm3JIZX8ncsuZu23ITdnLCQU44qAknNenMTzjzk67ClKs4SdtdmnQX1yRNr83UJXN0Aa43guiSXKdn44HrwHXg+t3CdVl0R9wnr5Du4om7IN0lfhROJHFn/zpc9WY6dNbu5ZqduCvjOj9rr/C71g3i+owE1wNFY6BmNl7oRv8q2jl0LwPeTejchN5N6D1Ehfek3kPqPESN3YTOTWj5djEPb89pnFna5esQjhpzxmjGnpmxl2+Loz2xkp6o4Jw2k6CPLafGWAtjy6mby+mblvRNS3p8JTu+kr1lzd2yEbdt5G0HNeGgJpz5CWd+wlmYdBUnauiu5OY4CaKzHySHR/SyraUbDSI6gu4018Vm49fbN9rvDNdhNr7hdK9nNr5/gWTPxnMm5CV+yBXozuP6mtPdqeRueeabxpzEvUp3b+2t8oJcL//QlzDaa+6bE6A78h66SuLOno0XoLtI1o4B+Bquz6C5bvDL43rF7K/0lQmtYdFa485xzb9v0JWbddZ+N4DuHv2Nc5anhTxlS08y8+20aZxbuNl5meVLybHqcmpsOX3Tkh5bTt+0ZG5asuPW3C0rcctG3rKTt+zkhDN/25GfcBYmXMUJZ3GCpjvexLtCogtxHU10PtcbcvpAcF3s6+zAdeA6cH09c10S8Hyu35ncvd7EncV1zs+601zXeKtc1/AydQ7aa1leXdbQBORxfdbF5fqsJNdFsnZJrk/bUtM2XK6XjIGSP10KZUqhdDGULgZppwp8B8ScFHNerv0JCtO+OOWt2MM4RtJ28x0t2xWtLrujpJv+kfgY5Y7n3fG8J17wxAueRMGTKHiTRU+yWPlb4tsjZLekE1W75Douamej7WAcK9K2Rwv2aMEWLdgieWv5C43USphifU2RsIQISxDPITFLf92R8YqoKdkOI5wXtDVSpwtYjt5bluiv7KGzRbm2Rwv2aNEeLTKHriNWdMRKjhjrqK7DDf+sKXdCoWWfeRI1Jy5RC53xBM+THqEzqjdZ8iVLvpSw/ZW//lTJnxZwQMjBdCnIWgimSwEGc9imSSdNQz7RJEzVGAd8CdKfIP0J0hMjGbqrTMFVDtQD6dV/PH3+hz97HQwGg8Fg8Pp31x/OeWIUjXYBrocypR/+7HX8h8iCQCAQCARqlEiSdLvdfr8/Go3GWUokEvRfRslkMpVKhUKhXT99zRcngesgEAgEAq07KeU6QV9rB66DQCAQCLSOpJjr07YK12kD10EgEAgEaroaw3Vj3VwfFRK/gNgm9QwBuwZmWTIeWZUr2FZsq4Z0uSESGxy5I9ao/ciprf4a6ulX/UfOndH6j5DW3RIno7suYI7u3uDZkdfTC/Tnd+3GR6xdWeeTBnDd2Aiuq6T2x9qNr1i7nJolWxEroCxCxFZ3+COHM+zMS7kfKsmdrixgnA3XtF9i2ypQA/f1Gn2CEJU3sKo7fNhzmla2VZ0Br2l/0ZXLCr5Z+0VQCj6qmLXhrK9TYsHL7VQ9XJ+2pVRGhuvBVWNw1dAgrquwj5XG7jnM4RutCCeShh8Bd/gEJ9gcf6DQZXAq5x8AyrqJuaGsfsn9XCnbBD/OBtaz1vU3qp47fNjX326dAa91f9fbfm+UGvW5a1QNipvDWRaTGNfT6XQ2m02n03K4HmgY10d553f8Tzu6vFjTYu3y16tqz/joYDjx4PQLZz3O/hZ8C70tfr84FeKPBmaZUZ4w+8sPBnOIGtsvRLtyg8SME13VKE9iVXHWI1bijMz6jFNQOPXwA0bHI9lfnGAU9JffkOBQCIaBUz9mu6PY+ws9DoLxC3aTeclZUCyxQcMcH7HycptGdFZQglxPpVLZbParX/0qG+1SXA80hutiQyDWGfyd3dh40FuJrcHvGma/EJULvqWgHnTl/GpVrKFTYUissOTKesZBWb/EokL0i19tQ8ZfQVVikbPH//6JExE2p7xkNzHbrSck/HbxhwUdCX7wkjWMViQZjKAUDHUDVef4KA5SbE+xBxMhPtdpqH/uc597+OGHn332WQbt/O+vV7geqHot8nWxfgquH+VJQSQ48WBuyK+HsywWZ/3HjeBbCupBVChYrVgX0OIXlqyznnFQ1i/FPeJUyGkFJ0j8ftVTrWDH79U40WGj1ytoV25IiHbZ4hTGHxb8DuL3SzBUFcb+QkjBUDdQ6N5hBsnfX8oaRb/FFofrNNT//M//fPPmzfv27XvvvfcOHz5Mo12E64FVjkOZ1YZcX8d8F/Mga2w8kjtJ8viTPChlHTf4myioRzAqzgjgdAFdITp+yfJyx0FBv3C6IxmqZADohuR2X1bfxeJUMCB3S5zoVhCbK2hXbkiS7Qquxx8WdLX4wePXiRkM5iYKqlIgzN41MDD0JpgVcriezWa3b9++d+/e3//+9729vYODgyMjIwMDA9lsVvh5c+uZ63XubH7NnLfQlTMFBEOSjFPBccOvZ5SleupB1ymrX4huyq2znnFY637JjR8zSMyQ8PsiVg9OzDjjuf7jlCyvuC1+u4L9lQxJVlv4m4g1J/kSZ3zE2sIcH8xNZI2nWP04m0iuxxlwnKZxxgcnbMF8nS/BfL2RXEfsoVGe8NfLDQPRqILa2BvyK+G/i9kvsfIqjM+SWHl+heh+8ePk1485YojygusbNQ6y+jXKE36nxOJXEKFknOja+IUFu4mIU6zwXR0noh6xeFRreRxitivWX7F4JNsdFdpfYh1Ex4loEectsfKC8Uv2C12/ZGHOVnLHBx08ZqNyg6/3+fANzNdBayH8Q+He1r03DugerZ/+3i1x3hnd+f7e7SPcqOPnbh8HWQKu35uS9U/iPax7dRzE+rXe+nu3xLnWalZ/7/ZxhuNHmRRzfRq4DgKBQCDQelM9XJ8GroNAtPh5g2QmsdaphuL6cTaUVTk/2VJWj6xWGlv5mtapWPXsBbmb32OS23fM8utkSBvMdQNwHXT3axQpsU0k14gVQLfCWcaP6o5xXTIexMsGngfxdwF6/+LvOPzA5DaBX3M9hQXX4KueyJsrBUcg5tGFX9uajnM919e5XDcA10H3nBr7sZdbLaJwA+vnbyi5OfrMOMoDOfsMpeCsigij/vOj5Eji1y+2UlaLmFLcTf4CupV6A11nwt8d6B2NWbniqOoRSZJqtfrcuXO/rdXHH39M/2XU09Oj1Wprn0tT4bqBZeA66F4S5udN1rlb7mdYsDy6EkkCSTYkWT+i5CiP65JRIdrCFOYuQI8MPyRlB4Cs8VEgwUGTu2dxwmjIrlk/UnwEonco4i3MVho7ziRJnjt3zuPx5Cqiv7AejUbD4WgoFA4GQz6f3+Fw6vXGzz77TIDrhruK6406ifCr4pwLcA4UBceHsrbuRjH9ktVBsfOd4lFCbyV4dkCfMkblnFVxWhTsL7oGzPWIkeT0l7MJf41YtQ08dHGalowHszaxfYoujNj1YvtR8PgRrAd/p+McQpjVKha60Tsgua0j9p0KOaSY+6ixo0GS5EcffcQQPZVKJ5LJeDzhdnsdDpfV5lhethqMc+O3Jk0m82/+4Tfc++EN9zTX0bsB/XnDaUWsGOJDLlig6R+StRDTKbm7TGy/KBslzE0E9xe6hnp2GeJkIVkt+tDCfAs/AMVnOmVCV8j5BDEHhuAa9Ob4YfC3wtkFmMctZ2wRZRCBobeVLKNAsj6MDYlhFE+yCnN6IbiMOeCNHWea68xD5RKJZCwWj0SiVqtjaWllfmHJZJqfmp4dG7ut1xs5XL/H74dHHHmCb/EPCwWtCB4uOPXjt3hXCP35UVBVnU1LBoNYI9j6KMYZRCV+1h7FOJuIBTzKO94QkfCLoQMQjJPTF0R/5UqyTpz68ZseRe5TsTr5W+G0KBkzU2AUeaioeHtZMEhEQ/iF10KKjw1EhZJrMDdEFJA74I0dZ4brmUwmmUzRUA8Gw0vLK2bzosEwp9EYJifVo6O3dDoDm+tNfi4N+5jmHLWctzibIFYi1vPfEouKsyDWrmBfJJtA7/uGfwCaK7H9iC6PP5iYMXAW0CVHpT7Y6JBwjiuEEFUJBlaP2P2VG8zaCb8hdpycXuDUjGiIPw78I4GzO8QGjd8K5r5ml+H0EbMXgmXE4hFslPMWPzyxlYj1OAHjd0clskdwNpQsI7avZW2rWHVz3d+0fJ1/GHGWBQ8FweNG8i1EDcoCRr+lrImGHPfrR5z9KHcr9kvFJwVZH3tOYbFtOe8KNoe5Hh2P2MuGHCSI/qpq+84Z/1Eh1R+PqkH9wqwf53jgLyMOp3qOW0QB9AGMM2KIA4lZw9ndnGXBXgj2V/KtOoWuVqwVwSNWcnPBkcfZU5IlcaSM6/4EqXZk1jXX2YeU2FaISgS3Ra9Hxyl4KIhVqOxQbuAHYD0IsRNxtkKskRUDZ0FBo4IfbLEjAR0GvhCnCcFQJcXfhFMhuglEXxpy0MqKXEGXJXshWZj/lx8Yeo2sLgjGI2sTsZ4i4uQvs9tF9E6sEsQ4yBK6fkRb7K1wWhGsU3BZbFucwpKqi+sOmuu01xnXcbZCb4g+1jEHXTIw/JX4Dd0DGhUS/oboNfgxCC4LVo74WApui7+SHwnOyPAHQbIVzHf5/eX0FDEUku8qk1i7OJXj9BdT6GoRQarqO25xiikbHMEyiDjFlgWrHeUd1ZJvNVaSNY/WHtiYdarED3j0gEiuwVfdXGcy9WDZ9x7XBSvEPNrQgYlVIvdQXrtDv4lCj7/kVog1+FUJLksWVtV+vMV2MeZKyUgQhxBbkq2g38IJSay//I+VWGzsMnIjkTXOaOG0iC4meDwgtuK3KxkJv065exZnkHFGgx2A4DJ6K/SGzEsFQ4TZuqoRB61YVZx6MLeqU2yuZzLZTIb+qfWU3x/0eHwul8dud5lM84JcVzsyzec6Z5QR4y64Y9AHInoXYh5V+M2JBYlTv2Sxu06CgyZZXnD/Khgi/pGAeClWgP8XUYPYSnQ9mFWxX6JbwYkHUSEiGPz48fcXZtNiK/kLYpvgt8i8xe6FYEOckrKOW1njL7YeZ5Aly/CDVyHjR/SXXUBwE8GqJLsguQnOGswCTHcESyKqldsRtNhcz+WIbz3yyO4f/ejVvXtpf3D8+Pm+PovFxr1vLkHOcLleoXtT8nUQqIGS/JyjCwgWlqxBbKWKd9bD3EpMcpuWXM+JDX3+xYxfwUcbvx5+MIpPvjgEQoyVMqGPJQXjgN+WYIEmnofrbFpx8JLjyd7RbMmqULE4XG9/7rlPP/nkQkXDw8MzMzNiXJ9pItdxRgoEUiA0XPlHHQdmYh94nHMxommxMPA/AogmBOsUq59fj9gaxfEr+1DjBM+pn7MgOURi7Sp4qayPKqmRF6scPQ6YzQm+ixjntVY9Y6gsZvQRIvgS8blAbF6n6p2HNwVWGd/hfB0EargUE0Vyc/TpHr/peiio7LQi2aIsNtcTP1r46JLbWckI8TurqgMqsprGjKRR9a9/NepfEMUjqaBaxVI2D+9PkLPOWq7f+Xl4EAgEAoFAHCmbh+dy/Z58jiwIBAKBQHedlM7DU7PO7Kwzq+JAHbgOAoFAIFATpXQentK4shpXtub6Ou3wvcX1e+byEggEAoHuB3G4/taBA+f7+m5UNDk5aTAYBLk+66S5Hlzl+F7iehNv9QSBQCAQSIHqnoe/d7nOEB3QDgKBQKC7RUqfI0tpnFnNPcx1DssB7SAQCAS6K6SE6y+yuD4XXOX43uA6CAQCgUB3o5Tn6/R9c8B1EAgEAoHWj5RxPZCgtK6sFrgOAoFAINC6UgO4bq41cB0EAoFAoGZJMdd1rqzOlVXNhVbNFUO+DgKBQCBQc8VwPZ1OJxLJSCQaCoUDgeDCwrLJNK/TGdVq7e2J6RsjN2u4nqR07pzWzeI6k7hHgOsgEAgEAjVJNNczmQwN9WAw5PcHvV6/yWTW6QzqWe3k5MzN8YnhG2PCXC8n66x5eOA6CAQCgUDNEkmSp0+f9ng8yWQyFotHIpFwOBIKha1W2/LyytKyZXFxaX5+cW5ufnpa/cc//pHNdZ07qzLzrq8D10EgEAgEapZIkpycnDx9+vRv/uE3aP/xj38cGhricn2edX2ddiQLXAeBQCAQqDkiSdLtdvv9/mg0GmcpkUjQfxklk8lUKkVzPZikDJ6c3pNTmYHrIBAIBAKtGynkeipv8BJ6D6GaD61yDFwHgUAgEKhZUpqv541ewgBcB4FAIBBoXamefN3oJVQL4dWF8Oo8y8B1EAgEAoGaJWVcD6XyRjbX2Y5WuD7KEn5A6+0nz+sMZlRIDQvuPlazBvNuOZ4x20UUa8gRC8c8CHTnpZjrJh9pEuB67Ty8so90/ScCuZsjyjckmNHan3ytp7Z7UsrG5K7gurJN+DUo2wpnQ3Sxhh//IBBorVUX132EajG8yjY7X1c1ievKMirFzTW9fsmm1/lZVXGE679rtO7w8Sx3Q+A6CHSPSSHX0/k5PznnI1SLkdWyefPwKqGP9GitcN6SXIlYL7ceyfJy4+EMAnuBWc8pILhesl1+eZVMriPq57/kLEjGKRm/snpwuobTrmQlCuqR1S+cwjj1KOgaujy6fvz1YrWBQKCGS3G+Pucn5/ykaimyuhReXWKl7DhcX7tlwUY5klUeUVhWPPxTHvOS85bgepz+8pvAF3796E0Ujw9mPIh6FPdRVj04g9DAZbHwGjg+6E3q7C/7paxxBoFAiqWM6+F03uwnzX5SRUOd7bXgOlvo8oKNClYlWV6ycgXx8NfzT3mC6yXr5xeTpVGeBN/lr+Qsi9WDCEzwLZx6MDvbqHoEC+PUyV+WFc+dGR+xTRT0FxGqZDAgEKh+Keb6fICc95Oq5cjqUq2jubXK13HqEdtEbnmxdxXEjNMFyfXK4sc/n+IMwijGrpTbWbG3cOrB6ZqC/YVfoYL6FfRrTcdHchMF/RWrX9Y4g0AgxaqH62aa64zXmuuY5xTB84jc8oIB1xkP81JwvVh5ufXztxJ7V279OENRz/jI3Rana42qR7DCOmNeD+MjuUmd/VUWEggEqkeKub4QIBcCtVynHcuhvr8u+fkXO4XJOlnwyyPqlyzPeVdWPPxK2AGgG1XVCtGuYHm5kuwXumuSIeF0Dac8fxgx+8Uuz+8IuhJ+fyXrQRcTLCwWz9qND6ekYPyctyTbFRsEnHhAIFD9Usb1SCa/GKQWg5TKEl21RFeXGbO4Drq3BedoEAgEWodqDNerBq7fHxJL2kAgEAjUXCnjejSTX6K5vhJd5Ri4DgKBQCBQs6SU64WlUH4pSKlWYqtlV1J2Sa5LXvCTVV6sAE4eqaxm9Ftyg1EcPAgEAoFAfNXF9VBeZY2tWqOrVla+HmfdNyfYpFyuy90EMUXMvxVI8M4gnHYle8e5e0hWPcB1EAgEAimTYq4vh/PLYZrrtY4TNd9zYxbqQSkO1xF1StaGgDRTIWdBsC0xlkv+E8BpDr8vIBAIBAKxpZjrlnDeEs6rbHyu5wS4zhYOpFXY/wrgQ1qsDKK8JLbRBdh9QVco2SkQCAQCgXDUAK5zzM7X2UITmr8eP8dFF0C0jv6/QbBmnPLs+Pl/BeOU7BQIBAKBQDhSxvVYprASya+E8yp7fNUeX7XRjq3aYqsJEa4zQkOLj0A0/zC5rkDo/zM4K9H/Fkj+i8Bfw68QBAKBQCBJKeR6tmCN5K2RvMoRX7XXmuY6H3KY3JLFaQVclxWGIJvR0JXssqxocQqAQCAQCMSoXq47E6sO2vGyE0L3zeGLgZ8kgCWLIYAt2C5iJb8qdHnEMrpRfu8ENwSBQCAQSFDKuB7PFuzRgj2aVzkTq2w7EqtJEa5jJq8IDAsuI9AoKHz8898aFfpPQqxdxP8E6DiB6CAQCARSLOVcjxXs0YLKlVx1Jcqm0Y7gOqdtPvX5xdA1SFaLUx6ncn5skv8HiP0VLC9ZPwgEAoFAOFLG9USu4IwVnLGCyp1cpe2iXV++zt9E7C3ESkmuiwlROcNdxIb8aPlvSZJbrDYQCAQCgXCklOtFV7zoirO47q4k7srydbGVgrksuhJMIuIUk/tPBua2YuUl/+FA/AuCrnONyoNAIBBovaluridKtF2046UkUfrhT2u4jkh2+QHhrxR7C/0fgKx/NTjxY7aC0xCnPKJdycIIrV15wb0J/xCAQCBQ06WE6y++lsgVXPGCK1ZQeRIlTwXttJNEaReL68y5HhPAYsXQtJasVrAewWXOSgTaOZVzwCb5D4QYCDH/IWiugOsgEAi0PqWA6z9guB7Pq7yJkqfWKaK066ev0bWjOcfBAGIlf5m/FZo0iH8vEAUE/xWQbAJRElFebOX6hCW6ayAQCARqlhRxfV8yV3DH8+54XuVJFD2JoidZpBfciWKKKP3gxdf4LSGALbhSkBMNwd76ZJJYDE0PTFDrcwxBIBAIpIDrz77A4ro3UfAmCh6WU0TxBy/sa3a/QCAQCAS6H6WE6z95NZkreOJ5T5wqc51N9xRRfPaFV5vdLxAIBAKB7kcp4PrOn+xlcz3vjZftiec98XyKKO78yd5m9wsEAoFAoPtRCrj+zPO/SOby3jjliVEqX5nrFOMUUdj5/C+a3S8QCAQCge5HKeF6xyupXN4bJ71xUuVLULS99N84lSYKz3S80ux+gUAgEAh0P0oB159u/3kql/fGSB+b64yB6yAQCAQCNUuKue6Lk744qQok84z9ybw/mc+QReA6CAQCgUBNkTKup4l8IEEFEpQqkKQCScqfqDoD+ToIBAKBQE1SPVz3J0hVsJysU2XAJ6kMCVwHgUAgEKg5qitfT1KqYDIfTFK0abQD10EgEAgEapaUcT1D5INJMpikVKFUPkg7WTZcXweBQCAQqFmqg+tUKEmpwul8OJUPsZwFroNAIBAI1CQp5no4RYVTFa7TBq6DQCAQCNRc1cv1SDofrjVwHQQCgUCgZkkp1wtVrnPQnqWA6yAQCAQCNUfKuZ7OR9J5VSSTp9HOAB64DgKBQCBQs6SM61myQHNcFc0UGEcyhUimkAOug0AgEAjUJCnmOo1yFf0smkAqX37eXDIPz5sDgUAgEKhZUvxcGn+C9CdI1awjM+vIqB2ZGdr2jD9BAddBIBAIBGqKlHHdHyfU9tSMLaW6Op+8Yk4MzsX75+IDc/EBY9wWIoDrIBAIBAI1Rcq4bgtlB43RQVNUNTiXGDDGB4yxy8bYZUPskiFmDRHPdPy82f0CgUAgEOh+lCKu77EGs/2GyIAhohowxQdM8cvG2GVj7KIhdtEQWwGug0AgEAjUJCnkeijbb4xeNkRUg8Z4vzHWb4xd0kcv6aMX9dGVUO6ZduA6CAQCgUBNkBKuP1fO1y/rw6oBY6yfnoHXRy/poxeA6yAQCAQCNU+KuX5ZT3N9Lj5gjF82xi8ZYhcNsYt6mIcHgUAgEKhpUjYPvxLMXjZELxujqkFTYsCYGDAmLhsTlw2JS/r4CtwPDwKBQCBQk6TsfnhrMNdviPUbYqrBueSgKTlgSvYbk/3G5GVj0gpcB4FAIBCoSaqD6/EBQ1w1OJ8enE8PzKX759KX59KX51LWMPnM879odr9AIBAIBLofpYTrHa9YQ0S/KdlvSqquLGQG5zOD85kBc6bfnO43p61hcidwHQQCgUCgZkgB15/peMUWIgbNqYG5lOrqQvbqQvbKfJame785Y4tQO3+yt9n9AoFAIBDofpQSrj//C1uYHDSnB81p1dWF7JWFMtTprB24DgKBQCBQs1Qf11Oqq/PZK/OZKxWoD8xlbGFq5/PAdRAIBAKBmiBF8/C/sIXIkngLzgAAAV1JREFUwbn04FxadWU+U751zpymr6/bwhRcXweBQCAQqClSfH19YC41MJdSDZpTg3OpgbkkfR/dZVPSGiKf6QCug0AgEAjUBCn6ntsr1hDRb0z0GxOqflOi35S4bIhfqhieSwMCgUAgULOk7PvrK8HcJUPskiGmqjw+NnpRF72gi17QRVeCuafh+fAgEAgEAjVDCrje9tweSzB7UR+9oIuoLupi57XR89roeW3kvDbSq4lYArm25/Y0u18gEAgEAt2PUsD1HT9+eTmQ7dNG+jRhVZ8m2qeJ9mkivZrwZ5rwZ7Ph5UB2x4+B6yAQCAQCNUEKuL5998vL/sxnmvC52ZCqVxPt1UR6NZFzmjBt4DoIBAKBQM2SMq4v+TPnZsPnNGE218teDuSA6yAQCAQCNUX1cT2i6tXGerWxzyo+p40tB4kdz8F9cyAQCAQCNUFKuP7jPUv+7DlN9Jw2+n8Aox/DjTi3yqcAAAAASUVORK5CYII=" alt="" />

    一定需要注意语句格式上代码行的缩进,但即使不报错也不代表程序不出错,若例二中,若要求  print("a!=1")  仅在 a>1 的情况下执行

    该处代码应由

 a = 0
if a>1:
print("a>1")
print("a!=1")   # 该语句始终会执行,因为缩进并不在if条件下

    改为

 a = 0
if a>1:
print("a>1")
print("a!=1") # 该语句仅if成立条件下执行

控制语句

       仅介绍,具体参阅后续章节

if语句,当条件成立时运行语句块。经常与else, elif(相当于else if) 配合使用。
for语句,遍历列表、字符串、字典、集合等迭代器,依次处理迭代器中的每个元素。
while语句,当条件为真时,循环运行语句块。
try语句。与except,finally配合使用处理在程序运行中出现的异常情况。
class语句。用于定义类型。
def语句。用于定义函数和类型的方法。
pass语句。表示此行为空,不运行任何操作。
assert语句。用于程序调适阶段时测试运行条件是否满足。
with语句。Python2.6以后定义的语法,在一个场景中运行语句块。比如,运行语句块前加密,然后在语句块运行退出后解密。
yield语句。在迭代器函数内使用,用于返回一个元素。自从Python 2.5版本以后。这个语句变成一个运算符。
raise语句。制造一个错误。
import语句。导入一个模块或包。
from import语句。从包导入模块或从模块导入某个对象。
import as语句。将导入的对象赋值给一个变量。
in语句。判断一个对象是否在一个字符串/列表/元组里。

数据结构

       仅介绍,具体参阅后续章节

Python采用动态类型系统。在编译的时候,Python不会检查对象是否拥有被调用的方法或者属性,而是直至运行时,才做出检查。所以操作对象时可能会抛出异常。不过,虽然Python采用动态类型系统,它同时也是强类型的。Python禁止没有明确定义的操作, 比如数字加字符串。
与其它面向对象语言一样,Python允许程序员定义类型。构造一个对象只需要像函数一样调用类型即可。类型本身也是特殊类型type的对象(type类型本身也是type对象),这种特殊的设计允许对类型进行反射编程。
Python内置丰富的数据类型。与Java、C++相比,这些数据类型有效地减少代码的长度。下面这个列表简要地描述了Python内置数据类型(适用于Python 3.x):

除了各种数据类型,Python语言还用类型来表示函数、模块、类型本身、对象的方法、编译后的Python代码、运行时信息等等。因此,Python具备很强的动态性。

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" 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表达式

      仅介绍,具体参阅后续章节

Python的表达式写法与C/C++类似。只是在某些写法有所差别
算术运算符与C/C++类似。+, -, *, /, //, **, ~, %分别表示加法或者取正、减法或者取负、乘法、除法、整除、乘方、取补、取模。>>, <<表示右移和左移。&, |, ^表示二进制的AND, OR, XOR运算。>, <, ==, !=, <=, >=用于比较两个表达式的值,分别表示大于、小于、等于、不等于、小于等于、大于等于。在这些运算符里面,~, |, ^, &, <<, >>必须应用于整数。
使用and, or, not表示逻辑运算
区分列表(list)和元组(tuple)两种类型;支持列表切割(list slices)
一些Python特有的方法,如 range()  lambda 等
 

函数

  仅介绍,具体参阅后续章节

Python的函数支持递归、默认参数值、可变参数,但不支持函数重载。为了增强代码的可读性,可以在函数后书写“文档字符串”(Documentation Strings,或者简称docstrings),用于解释函数的作用、参数的类型与意义、返回值类型与取值范围等。可以使用内置函数help()打印出函数的使用帮助。比如: help(randint)

 # 函数示例
def my_fun1():
print("hi")
my_fun1() # 调用函数
def my_fun2(a): # 函数可带参数, 参数可为多个
if(a>2):
print(">2")
my_fun2(3)
 

对象

  仅介绍,具体参阅后续章节

 # 对象示例
class User(object): # Python2.x 需在()内加object;Python3.x 不用加object
def __init__(self,name): # 类似于构造函数
self.name=name
def print_name(self):
print(self.name) u = User("John") # u为一 User对象
print(u.name) # 输出对象属性
User.print_name(u) # 调用print_name()函数

类库

Python拥有一个强大的标准库。Python语言的核心只包含数字、字符串、列表、字典、文件等常见类型和函数,而由Python标准库提供了系统管理、网络通信、文本处理、数据库接口、图形系统、XML处理等额外的功能。Python标准库命名接口清晰、文档良好,很容易学习和使用。 如引用,需import,如引入算数模块 import math 
Python社区提供了大量的第三方模块,使用方式与标准库类似。它们的功能无所不包,覆盖科学计算、Web开发、数据库接口、图形系统多个领域,并且大多成熟而稳定。第三方模块可以使用Python或者C语言编写。SWIG,SIP常用于将C语言编写的程序库转化为Python模块。Boost C++ Libraries包含了一组库,Boost.Python,使得以 Python 或 C++ 编写的程序能互相调用。借助于拥有基于标准库的大量工具、能够使用低级语言如C和可以作为其他库接口的C++,Python已成为一种强大的应用于其他语言与工具之间的胶水语言。

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