什么是函数，函数说白了就是将一系列代码封装起来，实现代码的重用。

　　什么是代码重用？

　　假设我有这样的需求：

　　但是我还是觉得太麻烦了，每次想吃饭的时候都要重复这样的步骤。此时，我希望有这样的机器：

　　aaarticlea/png;base64,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" alt="" />

　   将重复的工作封装到一起，我们只要向机器里放入东西，就能得到我们想要的。

　　这也就是所谓的代码重用。

自定义函数

　　知道了函数是干什么用的之后，我们就开始学习自定义函数，也就是动手来造这个神奇的机器。

　　看代码示例：

def dfb(a):

    '''一系列操作'''

    return '一碗%s饭' %a

a = dfb('米')
b = dfb('米')

print a
print b

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

　　这样我们就得到了两碗饭，真是方便快捷。

　　现在来解释里面都有什么：

　　1. def 是python的关键字，是专门用来自定义函数的。

　　2. dfb是函数名，用来以后调用的。

　　3.(a)中的a为函数的参数，为函数里面的操作提供数据的。

　　4.return用来返回一个对象，这个对象可以是函数的处理结果，也可以是函数的处理状态等等。

1.def

　　没什么好解释的，语法规定。

2.函数名

　　函数名就类似于变量名。

　　例如我写了一个函数，但我不调用它，那会怎么样。

def dfb(a):

    '''一系列操作'''

    return '一碗%s饭' %a

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

　　什么也没有输出，那是不是意味着函数不存在呢？

　　我们看看内存里有没有：

print id(dfb)

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

　　很明显，函数在内存中，能够找得到。

　　所以，当我们定义一个函数的时候，python就会将函数加载到内存中，只不过不调用的时候，函数内部的代码就不执行。

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

　　很明显，和变量赋值原理差不多，所以要注意一个问题：如果函数名和变量名冲突了，相当于重新赋值。而python解释是从上到下的，也就是说此时谁在下面谁占用这个变量名。剩下的那个就只能在内存中等待垃圾回收了。

def dfb(a):

    '''一系列操作'''

    return '一碗%s饭' %a

dfb = 1

print dfb

　　aaarticlea/png;base64,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" alt="" />

print dfb()

　　aaarticlea/png;base64,iVBORw0KGgoAAAANSUhEUgAAAd0AAABmCAIAAAABJdw7AAARJklEQVR4nO2dz7Hrug2H2U1aYAlpxCzDriDcefVSQbS9XGQmCzcRz5unCuImmIVEiiTAP5IlmT73982dM+fokiAIUTAEyYSwAAAAekJ8WgEAAAAR8MsAANAXe/jl8SHlY3xXylOJqxCD2UEhQv8anoMZxA522GWsl5ZlYz5V3dQtbT5Bq513X1G7GuS41XLmOvxOqn55un5uQtyEeubb3HVgZqNcF3FTK5bJplU1PqS4xmMFOs+nP9VwK705gpazEzVWZj47ythR39s6blTMnY6c0crGfOlL9dJtaXM+4dyr7LuiXlruJW3VLDqR/HOo+OVR36V+WWutfar8R1zQzM6Np9U2PmRx2Y36EfzvhjUaXJlmcKHHUzudjRNHNGzlbQ0PpPHszCxBip/FYdMJA6LxIQV7HZ5kzPgMHtvL2rXB4OdXFD/TeBZ72vA4yT+Iil8Ow8zAFmQxpYmCRr+cyNmwRsMuaffo5G1MZbyv4XG8Ws/O3JgGsAdNJw6IzCDUoJio/Bxjbhtls25rg8GPr6jqasm16U3yj6Lil9vnb1Ri7jC3MP+pzBTV3oQYfs2/TP8WN6H1XYjbEtvOaYrJAc35uLTN1JDE7DpuEGpo1FWIQamrk3OGhhFMr7se44Rj1IayZnVGQQrjl5fUUxznzqM7m5j5YL5XOtZk9vj+epIm71IMf+i7EHcpr0IOF3mdLeaHWxQmVk3bcPrEZ/BXZhZzPsfnwZjz3mSNeO5PJa5KDULclBry5/SponVIVmZuLLo2qEFoG5/0mz4m2ZkmZ7BqDXb1ni85XQaVq7tzt76bX7ZmCDKV1GUsN9pGUwfh/7w6O07HXUi4RLu0jbVsmsI8UneWanhVJpZ8pIYxPtT1g06eK0yY0jYJ7X45F6QUAmc6+lOJq2DvikpjzXKMcj43tJgYftmnmi+86Wfu7oe1asvdDCMnM4uCZP4sk3xFNHejpokPZnyasWTVdB1yR+KxqD5UbXaNXV2clL3L5EL+jDVKq/dkyQmNV3e/rMhj2PFVnE/5ZDvXaYb8XUzBX5RcSXDNLxhVvkQZOcdpyNnqSj7zJ99UbhPyaj07acYz54mSOC4ZPef1SNSWjpXE1NHov+Y/w5+JkmWdycd/eofR4LuXEKx99Iyc+L5B6kf8xkXBqqsWUu6/6AltOYPxQSY/zn22VVbvuZKzkypf3f2y5rlf7cF9kCjIRlKCXUbmmVmIbJwStRn13Ru6lmNNNKQRxyEacgQudfanLi5Y7vdpm5S2s8MGKUvEOqnqn5Sm81pGZ7wD1ysea3xc3EfmFD8uks0gdvbLVB+bP4NEcvQsJOlVOMtlO1+VThYYtSqV3DJWe7wcrrFZQ+ZKWWZK8+MZa9jC6j1TMqXx6u6X9vfkqjeMPlHgutC7bzPEga1rqZ7LR6V6RjkgJt8Utvnn35cP2BuXQmU1nBrcpXRZpwM19K4nJsr0+RvVJ5dfLr+hWDs73OsBaUaVfd8uHD1I6gX2Ib34YDnKvBvr4lM1KHEV8h8uAzv/DJKq6fOJyKppm8wswjPIz8Lnu4eLvAYvVl45a4T55VgOZ2ejBmNfxgRjpef0qfVTR+swXpk5nflnD/Gpp+vHSWNOIn8GuTap5MzqPU0y/1nbcnX3y77f96N3HBFcbuFkvIa5gPrjGu7Lme+K/s7vpe449+pNep7aa6k1fsw7y19/dZ/zPezn8jy0D+YH91F83ZeG4PeErMwWfFp2ly9PfT0/4OrG/hgAANAX8MsAANAX8MsAANAX8MsAANAX8MsAANAX8MsAANAX8MsAANAXP9svB98CBp8BpwCA1XzKL5tBiOv6UhlPtaJXw17xP5+XlrfY1PRIS6/thDuYAAAaqPjlp1r2Ot37e5TRtpv794I7WKBGazHjthPEgA9IAFZR8csPbfz1me4z/y7H+uU3dhmIeGl9RP27c0c/1S8zOsdFEwAAZWrx8rz9l3paa43Z1UMd6pf3ivV2ixk/OvqZfpntlRz8rFUB6J2W/HJwFRk1px1HfQ/yj1M6Mtpu0m0leQ12R76LsO7CVPct2m2lQY4L3iuJ5kXnl5ZXIe9SXOVlkMHOLqk+S9Lm6kr6LDkcdqyMNajkmjXmbPtDy8Ua1dEzkhkb7uSXqeRmi8ERA7CClX55/lNc0/1r/R6r0y9+w8HwiPNBQYG2eWf75UhVjvfL5es81Hna+dX/jPVhRi/MnR0osQadaas13Oa+oebl0bP2qcnZ4JfLQ5Qlwy8DsIJtfplcYy5Qumav2GV/b9Imjcdb5FQ3NAyeNU1Cwp+Z0ee4Nakh2v4BUJ3pSmtsGZ3aMKfA+jwGL7nBYngGC8AadvHL7sio72mc658CBRVdxtFFiJmItSTH10S5VB7xu7JFGb/MxMuPqH08tWxunVqDzrTRGnm/nB09a5/AhqySb8TLi+RWiyVVgAAAZap+eXxIPoEYRaxTplVeBpm2TPK5Yab4oc0kfLloa3KmhOZU8Kv6du0UMk9Z0UEp/3NWKc0CzzON3wh002fDvZw1aDa5Yo05fL4qs+Ssq6PnJMc2/NMlhX2bFzlC4dvEkv/XaDEmWEZaA4AS+L4fOBScAgBW87P9MgAAfB/wywAA0BfwywAA0BfwywAA0BfwywAA0BfwywAA0BfwywAA0BfwywAA0Bf9++XpK8vBF5cBABvB1fQdHOeXo+/abq9LNH2L972Nb7S0p22bUxnLWCGs1Nn/H3Xpf9vbfIRGO4+6YoS17GuQ41bLmeuQZ/3VlLlyf8a+5I2MD5n1XXtWXAvYwS9nak3RL+BuseZUJCUplTJd2NO/6voatRVqdohCWTta2dZxA/NY1lprjeIvwtxx/7+1nfKa2pxPOPcqZSOsZUeDrJpFJ5LbYa+mBrjNud7/er3fIma1W3hndDNsWXll31X3bLV9iVN2iZeDTdpK9trpU84s61vLmnsdrXQuWMv56vW/7EwwlrVWZULCo0ZPMJtG2dbLpnOvcpIRCrAzTWaxow2Pk3wGR8Sny1aIJ5YZ2zyRd/3y2qF39MtmEOpZqjW1z9kNffForF+oivML4Z2jb8C2fJ9wrCk4Ulx8dNDou4yyWbe1d+jnGGGtAsksdrThcZJP4Qi/vGqf8V0YH3LzKO/7ZRsUwaizl1+O70eizSrDZvERWm+pymiltI3NoztH3zGQoKXLh/hmZkmPzNkSaY37JduL3KVO8aAKVJ2Tqhcrpf1DzRLkxUphXd2oaJQ53yLtRVqRa8PpY9SS5BHS/iczC98skixi+Q3WiOY+Wins5WKFsFrzcvy5kMHoWloRHMmOlcgJtAr25ScJLndk8oz8TEkOqmyNJRvmTtP4CckhiQ29nNCeW6Pt+MpNr26uCpqtXt3h1uH1PXsDXdpGJ4RF2dtry7m9beV9LpM0Dx3XsWv2bM2Z/b3j5fQgbbboSGoptQzVnKRLPLjvSH8Juyhrw+dI9DEdq0AylvtzCXDMfFUsyW7lDpr4UyEUbtw1Vm5D9eHkJLNYJpiT7GZhVN4aZO7TR5FSwa1Mxqqm4Ug0FtWHqk3H8gmEwkzJLHhrUMmKPHI8U3ICZ8PZCYz28tZz0eq1TKugNVzdfuvwy+W+Ll6ujt7SpaW2XHBkRV2hwtxb7wz2zS+XDzLWvK1M/CeL1eQ/e5IMpu8YSpjjCBX/KRaPwD7oT3rRscLoxm3BHwmkP9nZ5XROVKL65OSEqHimLaOzcpK5a2m1TsXmrNryS9ka1DiNZzA5SPPddBRBLJZ+QpwrOTepsOX0MakvmyPlWZ2Ga5m6reare3V+uTp6tVdjbbmWX1h93q0+/EG/TGsptQzV9NCPLmL/AoDyd+6us8/9LS8JjMvNfrJgaC86lgruT71kqefYTZlZbPgzUTL5s9SG6LO0Ga0ZmS5hAymyvfy8VJDrSOSwdhYqOjUFq3qfxZyd/Fi+DTUIO5YPHoO6K/xMWROlNnSSR22VsaPmlDleMoXa0LoQIX9z35wYXe2Xq1d35MFdxaJt+jT6ZdqyWlvOHTEqrcO5HKHjsnM/+7lfXGhq1mEpsORTSDdal4jWW2ogSYxORFEJm4M2aUjCpIldSk5I+5dhohimFxlLB+lg5fU0s9iLtOJvVgirtJXup9SLen64eSC1/Nc//mBUYpPdPg2dm4XXR6slFcsnuCfHzcrh7Dxqa6zVSf4hToxqPY8VzkLK4liJPgGRmyZjLUc4+yTPG0Jy1hDS/uWSuWN4is+UzIXhkQ2XwcrZj3oKkbly06s7UwWtdnV7yUHtx4aUZuPohSkr01xbbh7uqtTgJjK/sOyONHq2j7wn1xeqFCB88Vi9sePc1eZHUuadx1nWHnkGT14brA2LL5L29q2/3vT5JF/ml5en0viHf/i38h/4FnCuAACgL+CXAQCgL+CXAQCgL+CXAQCgL+CXAQCgL+CXAQCgL+CXAQCgL+CXKX4X6T02/wYAgJX05pd33ImVVH9xX4781695b0B2oHA/wDfrVwEAwAZ688v7hqihl/f7vZpBqP/mPgCII47cNAAAHE9vfrmJl9ZtMXV5Lz7GLz9VuIvK1PC0IjcAAGDtd/rl9lzHWr/cfhAAAI7iJL88lV0ZlNsNz+/IN2+sN29peqtWiAl2+Stt6BdXfwn34gv3UV30WUaEXwYAfJjT4mW3+/Wy57QZkl2b54PVCjFVR0mrv/CSY31ykuGXAQCncqZfLhRioc1yvXIdy2M1Suae8uGVDADAuZzpl5MaLW/7ZWMy3plWf2ElJ/pMh1VSUvelZfokEAAAjuRUv3yXrvpLkCa+B6Vybk0VYlzlqkIYm1R/cW8uB8OZhzYPmZSxsRbvLwMAPs35eYz+wff9AACf5Lz3MW7MUz4AAAAp3/j+MgAA/GTglwEAoC/glwEAoC/glwEAoC/glwEAoC/glwEAoC/glwEAoC9+E7+817davujbMQCAb+W38cvMV1o2OFlWTq1LdkvSg7x81x8e056roUHoEQJjw4ZeAHwrFb88fU/vJmr7UdTYS84m3DZG9Pi6r1nn5FTJOcrxIY9wK/1/fZwapH2PwFW9APhKKn75oY1f/U/9ztW+XELvyTmb5ppVBfZ0H3vo8/HR4ZcBKFGLl12h0uK+mi1MQr7uzn0XyTuq91lPdFyaHn4ZgIWW/HKy93G0V+dVqH8nNaIm5gJR/sbfbdqZlIxydaT+y1aWSuTk2mxgx5pVFGbuxD6pArSX9duTzpmfFn2o2CCJlNk3ips71afRGonOQRGvYD/Vul8mvdrqflEbAvCFrPXLNnz25TIStCaTT8X6xjRepnWk6JGgIlSp+tQ2dqlZReF1JjWrEuHUYuND+n2oV+nTVPmbdEnmTmfRIorq3FhxploPoaXuF7UhAF/JBr9sX1pOtVPDWIZeRbTO6Sxkzoe03Mw2Vp/axi41qwpiq8ozNyK8xbI6t8zLuoi4EEU26rwp2+AC7XztGO5I2quxNtim+xsAOmOLX57CovgyS2Kr4NWFcYyrRvm3BVr8Mht7fsIvr8itszpzNav4eNlbzMee4dO2Fn3SeT1ciZa86ejci/FyqYJXorPrUqqBy+hMerE2zMXL3oYAfCVVv+yKNiU3hlEdPBPViJr7RXnG9D05WkeKrSzl5IT5ZabNBme9Y80qCskvZ2pWxWqTzKxXMphsTZ90XkuXfK/M3JlcbWsFLyaTLi+DFFep/3SJY9/mRY7QXv8jNuR7URsC8IVs/F7JU63NYAJCFEICAMDMWr8cvI/hQI2olfhXU/DaAACA4Tf5HjYAAHwN8MsAANAX8MsAANAX8MsAANAX8MsAANAX8MsAANAX8MsAANAX8MsAANAX8MsAANAX8MsAANAX8MsAANAX8MsAANAX/wfOyKxDWOpM5wAAAABJRU5ErkJggg==" alt="" />

　　那么函数名的命名有什么要求吗？

　　函数名的要求比变量名严格一点，除了遵守变量名的要求之外，还不能够使用数字。

　　所以函数名只能使用字母和下划线（_）,同时还要避开python的关键字。

　　另外，在pep8标准中，函数名提倡都要小写。

2.函数的作用域

　　参数函数的一大重难点，很多人不明白所谓的形参和实参到底是怎么回事。

　　要明白其中的区别，首先还解释函数的作用域是什么回事。

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" alt="" />

　　所谓的函数作用域，就是这样。

　　python在执行函数里面的代码的时候，会将其放在一个新的环境中。这个新环境就像一个虚拟机，虚拟机能够访问和修改本机中数据，前提是该数据是可修改的，但是python在函数调用完毕之后会自动销毁这个环境。但是，如果我们在函数中试图修改一个不可变的数据，也就是进行重新赋值的行为的话。

DEBUG = True

a = []

b = 123

def test():

    if DEBUG:

        a.append(1)

        b = 321　　#重新赋值，先进行对象创建在进行引用更新。

test()

print a

print b

　aaarticlea/png;base64,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" alt="" />

　　就像这样，我们在函数内可以访问到全局变量，也可以对可修改类型进行修改，但是当我们试图为变量b重新赋值时，却发现没用效果。

　　因为函数在运行完毕之后就被销毁了，而在函数里面新建的对象也跟着被销毁了。所以我们为b重新赋值，打算新建一个对象来改变其引用时，却发现该对象在出了函数以后就消失了，这样b岂不是没有引用了？python不会让这样的事情发生，所以就引入了作用域，函数内部创建的对象和外部是隔离的，互不影响的。

　　所以作用域问题单纯只是针对对象新建问题。

　　也就是在函数内新建的对象会放到一个盒子中，这些对象只在函数内有效，且与外层对象隔离，所以做到了就算变量名冲突，在函数内的赋值也不会影响到外面的变量。

　　函数内的变量就是局部变量，外部的就是全局变量。所以在函数中定义的变量，也就是局部变量，只在函数内部有效。

2.形参和实参

　　形参，字面意思，指的是形式上的。

　　实参，则是实际上的。

　　看下面这个例子。

a = 123

def dfb(a):

    '''一系列操作'''

    return '一碗%s饭' %a

b = '米'

print dfb(b)

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

　　我们传参的时候，相当于在函数内部进行了 a = b 的操作。

　　因为函数是有作用域的，虽然外部的a=123，但是函数内部是相对于a=b='米'，是一个局部变量。

　　而局部变量在函数执行完毕就销毁了，所以它是形式上的，仅仅只是函数内部处理时用的，更像是一个标记，所以称为形参。而当我们调用函数时，实际给的参数，如这里的 dfb(b) 中的b这个实际的参数，是实际在内存中有的，所以就称为实参。

2.global

　　如果我要强制在函数里面进行全局变量的声明怎么办?

a = 123

def dfb(a):

    '''一系列操作'''

    b = 1

    return '一碗%s饭' %a

dfb('米')

print b

　　aaarticlea/png;base64,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*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" alt="" />

　　此时可以使用global关键字:

a = 123

def dfb(a):

    '''一系列操作'''

    global b  #我先声明我要创建一个全局变量b

    b = 1   #然后我再为b赋值

    return '一碗%s饭' %a

dfb('米')

print b

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

　　这样就可以在函数内创建全局变量了。

　　此时有机智的同学就要问了，那我在函数内部声明的全局变量和之前的冲突，是不是会重新赋值呢？

　　答案：是的。

　　但要注意一个问题：

a = 123

def dfb(a):

    '''一系列操作'''

    global a    #我声明全局变量a，想要覆盖之前的赋值，而传参的时候，相对于进行了a=b的操作

    return '一碗%s饭' %a

b = '米'

print dfb(b)

　　然而报错了：

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

　　说明我们不能将形式参数声明为全局的。

　　那我们改一下形式参数的名称：

a = 123

def dfb(c):

    '''一系列操作'''

    global a    #我声明全局变量a，想要覆盖之前的赋值

    a = c

    return '一碗%s饭' %a

b = '米'

dfb(b)

print a

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

　　可以了，说明我们的思路是正确的，在函数内声明全局变量确实会覆盖已经有的变量。

3.传参

　　传参是函数的又一大重点和难点。

　　传参是为了能使函数适用更多的情况，我们在上面的示例中都写列带参数的函数，是不是说函数一定要参数才行呢？

def test():

    print '然而我并没有参数'

test()

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

　　可以看出没有参数也是可以的，只是没有参数的时候，无论怎么调用得到的结果都是一样的，灵活性太低，所以为了提高灵活性，就有了参数存在的必要。

　　而参数又分为普通参数，默认参数，动态参数，下面逐一说明。

1.普通参数

def test(a,b,c):

    print a

    print b

    print c

test(1,2,3)

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

　　可以看出参数是按照顺序传递进去的，这种写法就叫普通函数。

　　但是这里有一个问题：

def test(a,b,c):

    print a

    print b

    print c

test(1,2)

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

　　本来要传3个参数的，但是我仅传了2个，这样就报错了。但我不想这样，我希望当我不传参数的时候，参数有一个默认的值，此时就需要默认参数了。

2.默认参数

def test(a,b,c=3):

    print a

    print b

    print c

test(1,2)

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

　　传参就相当于为形参赋上实参的值，你给了参数，我就按顺序执行 a = 1 ,b = 2,但此时c已经赋值为3了，所以就算不传，参数的数量也够了。

　　当然也可以将参数传够， text(1,2,3) 就相当于为c重新赋值了。这样就能达到你传了参数就按照传的参数来处理，而没传就按默认的值处理。

　　所以我们可以为全部的参数都设置默认值。

　　但是可能会出现这样的情况：

def test(a=1,b,c=3):

    print a

    print b

    print c

test(1,2)

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

　　并不允许这样的写法，因为这样没有默认值的参数很难处理，所以当默认参数和普通参数同时存在时，要将普通参数放在前面：

def test(b,a=1,c=3):

    print a

    print b

    print c

test(1,2)

aaarticlea/png;base64,iVBORw0KGgoAAAANSUhEUgAAAbcAAABRCAIAAADen3+XAAAGrElEQVR4nO3dy3WrOBjAcZWlEqaRqAxcwWjn1UwHbKO9q2BDB26CWfDS80N2gPgO/9+5JyfJlYVefEgCO2oAAJSp3y4AAHw0oiQASH4cJfuH1o/+p7l0RjVKte6n+eR8fgnP4Vq1Qzvscqyn1XJjdma7qWvS/Ibadt59RO3aIMeNljPH4U7kKDmO5ptSN2W6cpq79SrtzPwSdTMvdNpbfdw/tGrCY3llnjojLuG7Pu20rOmdILFxU+8YN/T2XvfCNws2d0ep0eTGfNqvzROpJs35/Lpv2ndEPa3eK7eXavEhOR9IipK9vWv7HIZhGDpTDv9esmFKPPZ9/9DiIOjtw/vfN0aMd564dr4sd3Yus5uzS0pY68clPFBl70zWC/hSi8Oq408W+odW2bPipMYMe/DYVw3DqxOl3x9R+ZqGtdizDY/L+UhSlPSnYF7Jkq6Nl7SVUTLK540R478kfnnQlG8uun9ewuM8a3tnSpxO7g6qTjhZcK0yrcnMWM9pzPeO8nbZXp0o/fqI2hwtpTSflvOxpChZXxpnosr7q+DpR+PGGd9NqfZ7+mb8t5601t6Vuq3zvmlBPYaDaR8nTjMmTOazNkzgl9CZRqnWmGbO54wSBjKvuts+3KgK0qReGSvBBTwTJddNknAOOB19bhM3/bL8qvhYY7OHK8ExN33Xqv3H3pW6a90o3X7pZmqx5XBrgZNWjdPkyhP24HehFtPOw7Jjk+n3qtYI694Z1RjTKnUzpi33aWeCcZiMzNKx0rGRNkiaZtmeGi9a2ZpGPbjZGtnRe37O8TDYOLtfDbL7RMnBtd4OV3oCr0tCZ9PTdfmxmWs1/n6eLq0zwTTNMGQX1O4RB5e4hI1xYc5HljC0TAOXg45xxN9oS9NE6qNk6QIuTCrTo3dGNSq7YpCONeXjzBwB/RZT7ffQmek0GL+WVgbZVq2Z6WfyKdRCyDnfy8nKOqi7M2PFW9d3rpdaNR6Hud+Ex0rLkxY7O8aaedZSXIHlpsOF1pBG78k5RyrP7hfUrriH/inmLjf9HMhcW55vC2evdGJ7Z+DKGfmEyeRzXAlzbdUk18MxUshpfM/a3ol3ykpxIZrjREcvxaBkRhMfK5pvBkf/nn70v0aFlMucXIzj2XdFJF2nJ/VHL+QTzqm1fYR3sYVWfWkglf4r7dCaHgx/mdlXzV1pNkbvuTkXKyWf3S+ovnuzdTPUW9IWZxkq26muKwyL7DU8SNPb+1Ltrb25qITp1fiQEuZ4AW6KbvM1c12Zpmlidb2TvYCvs7mxqMv9rrhe69Ez52ruVeGx+sfXfAEb51Zrzq5VO0fJtDxDuQeTnIM99OhVQi/L7dwYGw2wtFXTnGuOVT+X9MfYVMLMmbLWNN1XLbTGIIzeM3NOVZ7dL6h8EmhzabMsaeeXpOtE14aTvjml6dbLiOmCvYPMPoWf5t+/1ovPLbf1li3hmOCu9bxbcWAJl0AQCnaIliVVl9uXlJ/B2uqd3C3XeCcu+0SRf3RvM8hrn+RV+YlksGPrhnnuZlqjGqX/nnfupq/eZly8rx20apymUAu/B/O1WPZJ2y/deI+ONbnW8Pclw3xy7exM64anc96x4j7trO1sMA7DkVkqc37POuz6dPzMuWU6Md+DuTRxzoXRe1rO+Stfzdn9gh3fe5POjQO5VfDJlhKWJpu/XsJ9nfls2h/5HNxOdqz75nKybOvBuy3/m2ck9z+7T3iHYrfeY/oM083QYO75WSXENSUjs8aynbfLWyf+eEec3byPGwAkREkAkBAlAUBClAQACVESACRESQCQECUBQEKUBAAJURIAJGKU7K1WE96XAuCaxE9O+5rf8uQMcRLANcmfwut9qChREsAlVe1L9lZr3kkP4JK2oyQhEsCVbURJZxQhEsCVyX/RQXt/L8GyLwngguS7Nx6mlAAuiafKAUBClAQACVESACRESQCQECUBQEKUBAAJURIAJERJAJAQJQFAQpQEAAlREgAk21HSGT5/F8B1iVHSGf7mDYCL25xL8rccAFwaURIAJERJAJAQJQFAQpQEAEnNPW7ucwO4Lp4qBwAJURIAJERJAJAQJQFAQpQEAAlREgAkREkAkBAlAUBClAQACVESACRESQCQ8D5uAJBIUdJo24/f9VYTJwFcUt2Km49PA3BVNZ8vyXobwHUxlwQASeU9bsIkgIuqu3vjjFq+B4ArqXwSiIkkgIviqXIAkBAlAUBClAQACVESACRESQCQECUBQEKUBAAJURIAJERJAJAQJQFAQpQEAAlREgAk/wGpN8PzlMPUvgAAAABJRU5ErkJggg==" alt="" />

　　之所以要规定这样写，是因为要配合传参的方法：我们可以显式地规定哪个值是传给哪个参数的：

def test(b,a=1,c=3):

    print a

    print b

    print c

test(a=1,b=2,c=3)

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

　　如果是这样的显式传参的话，传参的顺序是任意的。也就是 text(a=1,c=3,b=2) 也可以，反正最后赋值的结果是一样的。

　　但是，如果是普通传参和显式传参配合使用时，就必须将默认传参放在开头： text(2,a=1,c=3,) 普通的按顺序传，显式可以不按顺序传。这也就是我们在写函数的时候要求普通的参数都放在前面，默认的参数都放在后面，就是为了和这里对应。

3.动态参数

　　因为我们的函数最后可能并不是只有自己用，而是给用户或其他人调用，但是其他人不一定了解我这里接受多少个参数。

　　传少了我们可以使用默认参数来解决，但是传多了怎么办，一旦传多了就报错用户体验就不好了，为了提高函数的适应能力，就出现了动态参数。

def test(a,*args,**kwargs):

    print a

test(1,2,c=3)

aaarticlea/png;base64,iVBORw0KGgoAAAANSUhEUgAAAdEAAAAmCAIAAAAUQTbZAAAFoklEQVR4nO2bwZXrKgyGKcslvEaGMpwKHrus7uuA7bBPFd64gzThtzDYCATGia147vzfuWfOnQwWQhKykB01AQAAkEIdJml8dN1jfFfKoFWvlHVHaJRyfQ1lcFYdYIdD5nqarm7MQW+bumXMJ2i18+ERdahBzosWyTi8Eo05d94bN6VuSg/lMXcTmdDpcIm66R0h8FLEjI9O9XSuSGfv2lTDV7naJm/xDhmsnfeOdtNo7m0XvqhYcEfJaHVjPs3X5rZsGSNPvPZNjo2op+mOkrZrFReRfHWacu5o7p15TtM0TYMu35qiYZMfPEfS+OiqITWaR/TXF+Iv2nXOhpJhMEFnF8RlGrbytoYn0ugdz1pcLKs4bTlxITM+OsXuMSFjUg+ee9U07S3iPh9R/ErpKo604XmSL09Tzo3Lw2idWaCkh/fGnJvIeSH+4kvSy4ljXmwvvK/heTxbveMH54XnScuhhYyzSlvNVNMyxnxtlpd121vEfTyiNqOlNOZqkn8ATTm3fW1OJ6aMz/v+V+3mavSmlP32/5n/rSnAmLtSt7Um9a2DObn4/lc6Zh6Y1dqGDog1dLpXymrdBzkSGhKYq+5mpA0+MiZnT+SR4oLJuWs7iNanfvZgE+c/LF+VzjWbnZ55Z2ndvVP2j7krde+6XnX2q+u9xZbpVoUzq6ZjOH2oB78Lq/A9lqU3xfi9yRp07YNWvdZWqZvWtuzTQZM4zCKzNFceG7lB8jFLI26+BbIrTTy4aQ02euUlp2Gwsbs/krIPzrmTs1FnME8H6+HXmXzzL7/2wUbz56GUW6vUfMw0sa0D90hTVaphrx2VfKaGlKVEXSads1LcoMzHJLTn3FJxUSl489kHrXrFnmZqc3k5Tod8GltM2e9p0H5TzT9LpxbWqi2nEEZOYRUVybyXsx4CWbvT88KtGwc31qyaxiH3CZ0r1ydXm42xPtRAxdMhV6oXrFGLXmHJCY27W5rdvYVpfFZ1rTsypEVnyyeLSi6opYloP684Xd9+jJzzNORs1Wf36jnv1MfEPFu9k3YYS1kmqb+S2UsZLau20rmSWpjM/u1/jX8mStZ1zm7t6cmgIS+vpVP77AU5tN7vzIO+mVCx6q5AKv0pd2iLB+mHTD+au29tRK+s5OKi6rtbmv3P0LYecEeH92IFpNgQcUMhyNj6gowZzX0x4lZPM9EwrxRO0ZAjSpc+V4b7+XoGz8ektHmHLS7WSnNWdXnqmK5rnZ3Z+dxVdK7x8RVuh3Pdt0p2Vh2cc3N9prIHM8nk2UNyVcXLdTv32iQBlls1l9wyV3udG8eY15DZKetK8350wRpTJXolJec07m5p9r4rtnmIWw7v4ZL8ROwsLUjDSD2stzg9kJ4L09+Jx/z3z3pjvHEtS1bDecC960KX50QNl7RCIZ215fA4cP3c+lt6W97hHqOnHUz2nbN49qiJFtknu4ovckmn202hrtRWq151/4aOp/8ZNTHT5wHEqumYwipiD/KrWPrL9qvro5cLe84acT+XyuHs7LR109O5aK7Up4MxgyFxSCOzpDPf66euz+MnSGOcyHuQG5NKLkSvmGT+Ptqyu6U57jsRK/kpgMCd94VZNCwVwh/X8Fgk34X8ve9dHrr2zYNzma1XM7f4a97JvejuPiPnlhjW54bXwD/gJnXxtTQEv5MsMltY2qCHfPHnx3PZ3S2ZcwEA4LeDnAsAAHIg5wIAgBzIuQAAIAdyLgAAyIGcCwAAciDnAgCAHMi5AAAgB3IuAADIsSPnOv3xb3AAAMDPpi3nOq2UUgo5FwAA3qK9znUaORcAAN4DORcAAORAzgUAADmQcwEAQA7kXAAAkGPXewt4dwEAAN4C34kAAAA5kHMBAEAO5FwAAJADORcAAORAzgUAADmQcwEAQA7kXAAAkAM5FwAA5EDOBQAAOf4HQXBBWjAxvR4AAAAASUVORK5CYII=" alt="" />

　　这样函数的适应性就更高了，那么这里的 *args 和 **kwargs 分别是什么意思。

　　我们先来看去是什么类型：

def test(a,*args,**kwargs):

    print type(args),type(kwargs)

test(1,2,c=3)

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

　　它们是元祖和字典，这里注意前面的*号只是表示这个是什么类型的，*表示元祖，**代表字典，而真正的变量名是*后面的。这里并没有规定一定要用args命名元祖，kwargs命名字典。但是这是个规范的写法，为的是让别的程序员能一眼看出这是个什么东西。

　　接下来我们看看里面存的是什么：

def test(a,*args,**kwargs):

   print args

   print kwargs

test(1,2,c=3)

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

　　它将默认传参方式多传的值放在一个元祖里，而用显式传参多传的用其参数名为键，参数值为值，组成了字典。

　　你可以无视它们，也可以将处理它们，赋值操作也好，循环也好，成员判断也好，各种需要看个人。

4.return

　　当函数遇到return语句时，表示函数执行完毕，此时返回一个对象，然后销毁函数的执行环境。

　　但是你在上面的示例中看到也有这样的写法：

def test():

    print '我并没写return'

test()

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

　　发现没有return语句还是能执行的，在调用的时候输出了东西，执行一遍后也停止了。

　　注意，在函数内没有写return语句的时候，默认return的是一个空对象。也就是就算没写，python内部也做了处理。

　　此时，有部分人分不清函数的输出和返回值的区别。

　　这样说吧，在函数里print之类的操作能够输出内容，是因为虽然函数的执行环境是独立的，但代码还是有效的。外部能进行的操作，函数内部也可以。但是并不是所有的函数在执行完毕后都有如此明显的输出效果，此时我们需要查看函数是否成功，或者说我放了米进去，你操作一番之后总要把饭给我拿出来吧。

　　这就是函数中return的意义。返回一个对象。这个对象可以是对执行状态的说明，也可以是处理后的结果等等。

def test():

    '''一系列操作'''

    return '搞定了'

test()

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

　　但运行还是没看到东西。

　　那是因为函数虽然返回了对象，但是这个对象还在内存中，你并没有把它拿出了，当然什么也看不到。

print test()

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

　　这样就看到了，当然你可以进行变量的赋值，如 a = test() ,之后调用变量a就行了。当然返回结果多用True和False代表成功和失败，然后可以和条件控制语句配合使用。

def test():

    '''一系列操作'''

print test()

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

　　当然不写就默认返回空对象None了。

def test(a,b):

    c = a + b

    return c

print test(1,2)

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

　　返回处理后的结果也是可以的，反正看个人需求。

　　最后，虽说遇到return代表函数结束，但并意味着一个函数里面只有一个return。

def test(a,b):

    if a != 0:

        return a + b

    return 'a不能为0'

print test(1,2)

print test(0,2)

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

　　可以配合条件控制语句实现不同情况返回不同的对象，这样就函数就能处理更多的情况了。

匿名函数：

　　有些情况下，我只想用函数处理一下很简单的业务，这个时候完整地写一个函数感觉会增大代码量，此时可以使用匿名函数进行处理。

　　python 使用 lambda 来创建匿名函数：

　　1.lambda只是一个表达式，函数体比def简单很多。

　　2.lambda的主体是一个表达式，而不是一个代码块。仅仅能在lambda表达式中封装有限的逻辑进去。

　　3.lambda函数拥有自己的命名空间，且不能访问自有参数列表之外或全局命名空间里的参数。

　　4.虽然lambda函数看起来只能写一行，却不等同于C或C++的内联函数，后者的目的是调用小函数时不占用栈内存从而增加运行效率。

语法：

lambda [arg1 [,arg2,.....argn]]:expression

示例：

# 可写函数说明

sum = lambda arg1, arg2: arg1 + arg2

# 调用sum函数

print "相加后的值为 : ", sum( 10, 20 )

print "相加后的值为 : ", sum( 20, 20 )

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

　　虽说是匿名函数，但是还是需要将其赋给一个变量，否则无法调用。而匿名函数里面的变量也是局部变量，和完整的函数也没有什么区别。

　　匿名函数建议只在处理简单功能的时候使用，太过复杂的还是使用完整的函数吧。

pass语句

　　Python pass是空语句，是为了保持程序结构的完整性。pass 不做任何事情，一般用做占位语句。

def test():

    pass    #我想要用这个函数处理某些事，但我暂时没想好怎么写，就先占个坑

　　当然，不仅函数可以使用，流程控制中也可以使用。

if a <= 10:

    pass

else:

    print 'a大于10'

　　还是那句话，仅起占位的作用。但对于某些语法结构来说，必须要有子语句的存在，所以pass在这个时候就很有用了。

　　另外，pass也表示什么都不做。

　　关于自定义函数就先说到这里，如有什么错误和需要补充的后面会相应修改。