Python Socket,How to Create Socket Server? - 网络编程实例

文章出自:Python socket – network programming tutorial by Silver Moon

原创译文,如有版权问题请联系删除。

Network programing in Python:

Part2: Programing sockets servers.

在所有的通信实例中,都分为Client 和Server. 其中:Client是请求的发起点,Server是使用Socket接收传入的值并且提供返回数据。

  Server的职能如下:

  1>.创建/打开一个socket

  2>.绑定IP地址(端口) (Bind IP with port)

  3>.监听请求的连接(Listen for incoming conecting)

  4>.同意连接(Accpect connecting)

  5>.读取/发送

  OK,到此,我们明白了server要做什么和怎么做(上面所描述的代码执行的顺序也是不能随意修改的)。在上一节点Part1中,我们已经掌握如何创建和打开一个socket,

接下来我们就要学习如何绑定和监听。

  Bind a socket:  

#!/usr/bin/python
import socket #for sockets
import sys #for exit HOST = '' #HOST name or IP address
PORT = 7001 #remote port s = socket.socket(socket.AF_INET,socket.SOCK_STREAM)
print ('Socket created') try:
s.bind((HOST,PORT))
except socket.error as msg:
print ('Bind failed. Error Code : ' + str(msg[0]) + ' Message ' + msg[1])
sys.exit()
print ('Socket bind complete')

  现在,利用IP地址和端口的绑定已经完成了,在绑定之前,你必须确保所有的请求方的数据能够通过这个端口被访问,接下来开始监听连接,当然不排除多个不同的程序监听同一个端口的情况。(如何处理这样的情况??!)

  Listen for incoming connections:

  成功绑定之后,要监听这个连接,方法:socket_listen用来监听,只需要在bind()成功后加上如下代码即可:  

#listen connecting
s.listen(10) #why we input 10, you can read manual about listen function
print('Socket now listening')

  Accept connection:

  方法: socket_accpect用来接收请求。  

#!/usr/bin/python
import socket #for sockets
import sys #for exit HOST = '' #HOST name or IP address
PORT = 7001 #remote port s = socket.socket(socket.AF_INET,socket.SOCK_STREAM)
print ('Socket created') #bind ip/port
try:
s.bind((HOST,PORT))
except socket.error as msg:
print ('Bind failed. Error Code : ' + str(msg[0]) + ' Message ' + msg[1])
sys.exit() print ('Socket bind complete') #listen connecting
s.listen(10)
print('Socket now listening') #wait to accept a connection - blocking call
conn, addr = s.accept() #display client information
print ('Connected with ' + addr[0] + ':' + str(addr[1]))

  结果输出:

  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6x6hVevcKrN3iNqDxZewk28OoNXr3Gq1dY5QotXyZKxLGJUh8tX2LlK6xyhVWusOoVVr3GBsVI0PIVWr5CK9dY9QavvcTrr1KNV6nGj6nm7wkav081fp9s/Ig3XuG1H7DqS7RykyB8nct48TJWIIiCjeIlcF9ipatY6RpoSbx8E3sLwCm5iZWBilzDhatI4TKU64VyvVC2F8z1Q7lLgvxVqHAdBk5J8SZSfBkp3oQK16H8VTB3Gcj2/UDCk20P3naTg7vsWNuGdmxYx4J2zWjPmOga4l1drKuJdlTRjhLuKCIdWah9FmxLAy2Jv3HqrQvdtRPQw+YoHTtAZ1r5xFU5cdcE3rrQ1zz1t0SBtjjYEQMHwt8SehsCT5XvLPPsxSNrnmPOcsxZYAV4jvKx645UDDX5Cdt64q4eOysDg8Kx5Li2wpG9BKSC764RMaI7Vrh0p+nqrp146sAL4buqPEeJa82DqkAQHzR+j52V29q8TeKVROhtDQTp1N8ZYkgJyLCSwDMcWaoOwkSkxSxwbaUjR/nYVTvxNk8DHXH4EmgDsIBnMFCIttDb4DvLHHOGqUWpisjOWWBL4tsQe9ZOXWtC19qpe13k2RB7NyX+7bPgjiy8p4hSlDGKMkpRRilKeE8R2ZWHd85D22eB7fPgriy8p4CB9SeVIEpRwruy0LbUvyH2rIvcQ4CavVtS35bEtyn2bojc66euNaFzHZxd6Fw/dW+IvVvSADg19SJO1yQYOpypxxlAmbQoQ4sydfiBIXVoTA+cErY5yzKlD/RJhhYF8kNTxWlqhK5G9jUoQ4cfGNMsc5ZjK/Kc1RNv8zTQlYT70sjVefRGFvtBHn/1F4Yi/koe++HtxN+J4t0oAcjrXNxFlbhF/TY0KIEWfUWAvYIs0YoZLhnDBWMobwjlDaG8QHTuCcCeQOQNYG8Q9gZh6YVJqjRKlUYu/1TjirsTZS9a9eP1YKoRybSi+U6s0ENKfbR8hVeuktUrvHKZrF0RVEmIPdep2nWqfpOq36TrL9P1l6n6dbJ6laxc4uU+Vu6hxW6i0EkUOmixixa7aKmHlftYuY9XUvufQR9zk8nqNckVXgG60kdLvUSxmyh2kUIbKbQThW6i2EOLQGaGKPUSxR5S7CKFbqLYSxR7iSLQoWu89jJV/yHdfJVu/j7d+n2m9ftM6/9Ot36fbv4+1fwx1XiF137Aqzdo+SpR6seL/XihF8t3o/luNNeFcx0414nmOtF8N5rvRQu9aKEXK/RjhX5MMzcCzYqAcgxFwGJFsg+meB0rXkeLV5F8P5zrBTOdYKYdzLQDmU4g0w5musFML5TthXKg8/+K6C8pXIfzV6FcP5jtBTJdf6rtTbY8eMOF1l1Yw4k2HWjTnmjakKYVaZmRlineNESbOrihDtcvwg1FsC4L1M/8NYmvJvJUBK4y31Hi2fNH1izblGYZk4fGJMuQYhnTLFOabc5wrDmurcBzlI4JtWic+ppCX1PgrvEdZZ6twLXk2Mb0gR7f16L7GsJqkIGR2+jEIGx97KrwHOUjW5FrzRMBFj3OABZHjx8aboMqZH8paJBmDo2pQyLqQkY/gBQ5K0S4xpQ50ONMHcbU3QZqDoFJsuTB4BxieKKjfGQv8eyDUTTVO70Id4PprwdMQBjHWuBY8mxzjmXKHBhSTB1OmEtThmXJc22lY1dN4GuJgQ8xUIjIlTjYPfU1Be7qkS1/oMOoivCW2L16Yls+Ni9wjXNs/SxLN8fWz3OM81zTIs+yzLetCpxAM9aBKT91rgkdKyf25WPrIs88KAOsPyEDp641gWP52LLANc6ytDMHmpkDzcyhZuZQO3OonWXp5tn6Ba5hgWOYZ+vnWLrZQw0oM3uonT3UzrH0C1zT0rFtReBcF3k2Jf7t8yBwbvbkkV15eEcW2pWF9hQRykWMpgLuSIKuTuxrEnRVnKKAd86DWxLfptizKfZuir2bEt/WWWBXHqZcxOgalGlIsa2FY1dV6GuDr+g8eiOPv1IgPyqQHxWJvzTkyCvFu0i8E+W7uXgNlEB1F/UAjEAzhBZ7pcVv0eGvIDNcMobyugCYEJfS+FI6g/nm5cvrmz/AzcuXap3xzOBzRPOuWNGbKPmxSjBZC6cb0Wwrnrc+HoHIv5nzcg8v9/ByDyvbnoxATzRdrNTDyj2s3MPL+P5n0O3f/VN7pY+Vu1ixgxbaiXwrnmvGc814vonkW4lCm1QLlHYf+oiNgkqwcg8t99BiFy12EoVOotCO51vxXDOWbcQyjVi2Ec+14vkWkm8jhTZS6CCFDpJvx/Ot2MUUeZlT4nwrnu8ghS5a7mOV61Td82wEgj47czXzB7+EPuHnM80f080f081XqcYPePUaq1wlir14oRvLt6PZFpxphNONcLoRStUB4XQjnG5GMq1IphXJtiPZdkQ5MwJNn+Y6kVwnkuvAuS6c68L5LpzvDRPJd0OZTjDd9CcbPrzmw2s+vO7D6z684Us2/alWIN0OZjrBTDeU64Vz/XCuH8r2gpluIN32pVpevOHB6m605kpUXWjNkag5kJotXrPGaqZYzQhX9eGKNlRWB0pKf1HmLZ55CmJXXuTMCew5vjVzZE5xjPihHmVo4/SLKFURocjDVEWEpozSLmJ0NcLQogf65IExxTJnONb8kaPEd1X4zgrPVuRacmxT+kCP72sStIvonjy8Kw9TlDBVFadrbmMjh8ZBv2sWhM5BDISpwxiaBE0Voygiu7LQ7nloTx6hKmM0FUIET7QYGUtBaKoYRQlTlDD1IkYjG6SHxjTbnOXaClxrnmVMM7Qo7SIGQiUUBQxiNVRVnK5G9rUoQ4cxQTRGT4RrDg1pcG2DjlnOnQkKg0tNHeiTZIyeRJcEqrCvQelqhHYRo6nIhrYhzTLnjhzlE0/jNNCVhC+HokyX4kBb6K3znSWOOb2vim1LvSvH5nmWduZANbmvnKDKxinn41TZBE3xgq6cZKimD7SzLP0817jANc1zjfMcwxxbN8vSTh+opxgXL+iKF3TlFFM1c6id4xjmOaCAfo6lmzlQT9IVY5Sz59unTzeFzwBbp8+2RaM74tFdydje2RjlbGxPOrorHt0RjW6LRrfFozvisV3pGOX8BV05xdTMsvTzXPPSsXXlxLF26loXuddOXWtC56rAsSpwrIvcGxLf1llg+zy4fR7cOQ/unAe3pf4NkXv1xLZ0ZFrgGklMS8fWVaFzQ+LbkYWpKoRpSHNtpRNvUxTsSSJX59GXcuRHZeL3ysTvlehfGgOpUP4E6Du5eDeq18B+VGE/qt9AMwAn0A6hw3/UJX/UJX+EjOG8LpDWeHCVG71wJZTOhNFkiSdys3TdHEM7f6BZYKuXjlTRaLLZqGczmWwm02jUKRI3ReJW64wSrdMaTtsjGWc050UKPrQcxKthF+9DCPrwIB7PtZB8K6GeGRmzoIV2otBKFFpW1i+hUXOi0EoU2mihjRYT9PvQxxwsWblMVpL7n0HQuBUrdtBCK5FvxnP1WKYWTddimXo8a/x+BHp00UTyTSSPUD+FPjqMJ8hqE4UWkm8h+WY814xnG7FMPZquwakKnKrAqSqcrkXTtWimPgycNjz8mKtPVSKpyO49CHpmjGab8Xw7UexilUvZ5AgEQdBnUnfzx4x5eeQX5+7Wj+nmq3Tjh2T9JV65Qkt9pNCJ5ppwph5J1ULJSgArB9CyHy0RYJUAXtHufwZ9fKRJ1oLJWlA2OQK94KdqwWQ9kKoHU/VgqhlKN0PpVijTDmXa4Ww7nO2EMu1AqunHa1604kmUPImSGym5kZI7UXYnql6s5sXrvmRjSCo6gXTbn2r6kg0vXvegNTdadSUqTqTsiJft8bI9VrFGKya4ZAgXdYGC2p9TejJyd1rqwEU2TGhB+SaUZ0xw9PFDTXRfFaEpQ3sy/7bUs3HqXBPY107s60LHxqlrQ+Tekni3z0CoAaapYvta9MCQYptzHHOOZUwf6HGGNkFXxfbk4e0z/4bIQ0Yn/NvnwR1ZeE9ORLRpF3Ei4KCK01RxEAPZU4R3z4NbEt+GyLUmsK+e2NeEzg2RZ1Ps25L6t6WB7bPAznlwG0RgRO61U+f6qes2+qGM0tUJpg5nmdKHxhRDm6Aq4Z3zwJbEuynxboo9GyLPhtizKfFuSf2gqp3z0K4stCsL78kje3KYoogCQaKrE/sadF+LgfjJviaxr0nQ1Qj1IkZRwHvyMDhqAPhcFEUURO2JAvIwRRmlqhC6BmUa0mxrgeesCn1tUbA36IkVh7qnvuaJq8Kz5Q/1GEUeXBfY5g/VkzTZ+J5kdPv06cbJ4/WTJxuCp5vCZ1ui5zuS0b2zcarsBV35Yl85QVdMUGXjwKzviJ9tnT7dEDzdEDzbFo3uSseo5+NU2cDoP98SPl47frjE/maO+dXM/tcz+1/PMr6eZXwzd/DtwuGDRfbDZc6jZe7DZc6DJfaDRdaDRfaDJfbDJe7DZe7jNf6zLdHY7tk4TTHJUE0faufY+oUj0+KReYFQKf08x7B4ZF7i21YEzlWha03oXBM614SOFb51kWucPdRM7ismqLIJmmyCJp+gyScZF7Ms/SLPuip0bZ0FaerEoSl37KoJ/R1x6PIMvpEjr/5SFWJYJP7DdEL1LpF4h05o8R8hfTCr8SVVroTCEVfYYzJbVG80I2jxX5alv16X/Ovu6ed0wVeH/GAQbdarwwpBVzjVOuOpymb2Y5Ygbg+nXdGsJ573JwLbH0Pv74ciwC5navFsHcnVkVw9nq3Hs7W4l/cRdH/PA3Y2kHyc9in0EQsBTgaumR2Bps8KrUS+iQB5SFUI0vpHI9AjZS2WqcWyUco96EMmHMvW71KLZWrRdBVOVSLJUgQvhrBiGC9G8FIkWX6NMF4KYcUgVghhRf3+fehjjiFdj2WbSKGDaudG7ovlx78CCpFt+UZHoGcmUiFqN1jlMlHsxnLNaKYeSVaDWDmQKPqQvC+e98ZznljOE8t543kvUlDT7kMfsVRo0Zco+s4mRqBxXqLoTZS8iZIXLfnQih+r+vFqgNCMRijdDKYafrzmRctupOiK5V2xvDOad0TzzmjeGSu64iU3UnajFS9W8+ENf6rpTzZ9eMOH171YzYNW3WjFnai4kLIzXrJHS7ZoyQIXzZGiIZTX+bMqT0rhws9sqMiCCAxRni7C1YRZqtCBMrAv91PP3Ntix4bQtsY3Lx0Z59m6uUP17IF6jqWdJ0yAiWw/Ojcl3h1ZiKqKMXQYQ4eDeAJNCe/JQlsS77rQuXxsXeKZl46ty3zbisCxKiRiIyDIcAexd0Ps2RC514TOFb518cg0z9LNHWrn2foFjnHxyLzIsyzxLEvHluVj69KxZfHIBNrO8xz9Is+ycuJYF3m2pIE9eYSmQpg6nKnDaBfR3fPAhsi9JrCv8G3Lx5ZFnnnxyLzIMy/xzKCqZb5t5cS+euJYEzjXT92bYt+WBEgREI/wriwMNGlb6t+S+DZEnjWhc/XEvnJiWzmxr5zYV04cqwIyTA+OlQa2pX4gQrvy8J4ySlUj+7rkIelGCIcGdJ36WyfuGs9e5FoyTC2yI/Wu8EzT+/KxHdHzTcHjVd7DJc6DRfaDJc7D5aNHK7zv1/hPNgRPt06fb4ufA0nYFD7dOHm8dvxo5ejBEue7hcNvF1gPljiPVniP1/mP10++Xzt+tHL0aJnz3cLh1zP0z1/s/WZ089fP13/9fOM3o5u/Gd367dj27yZ2P5+kfDlF+2qa9uU07csp2pdT1C+naF9N07+aYXw9y/xukf1o9fjJpvD5rnSMKpugKyYZF9MH6pkDzTRTNcm4eLGvmNxXTh9oZoFy8CyLR+bFI9Mi1zjP1k0zLiYo56Pbp882BEDDnm4Kn2+Lx2mK6QPtwpFl9dSzq4AZ+tSRoyLwtUXB/hl8LY//JSvEayLxn6UTP+1PQPpARuPBL5xxuS0qs8LnlohKo0fQ4rPDi9/sCv7LBvPvtvb+bm8zGESb9Vomk8lk0o1G/dBkPnLr1DqjUGkx+lvm6q4AACAASURBVBIWP2oLJZ2RtCua8VoO34fubdqKIawYSZbhVCWarsTS1Vha9/0I9FBeiaZCe59AHzBCsXQ1lqnFs1Hqp9BHrDhW6uClLqaZGYGmaaxfQtCUOFuLpStwsmzcvw/d+ZsQpcJ796APGNxHZJDooaISTVei6UpU8eI2vvVYFUrkQ2j+5MkI9Ji1/TGx+32qP4QWgmg+kMgHkGwg4d/+GHqfHowkq9FMI563PBn55X742nX8K+gzibv5KtP6UTk9Ak15080f0o2XyVqafh/6kCUYnP1vqH5f/OLrEei9XZcbTrvglBNWfDUyfM3Qe3set2h0BHq+tneP2PUBUxHLu+NFDxJc/3hQ8LNNR92HVTxW9nvQvZW9UbKaZ4eRjB3OOqJ5Z6zgipfcidDtUR9xlWjlgvYZBH26aim7kTLn8QgEjR/GSrZoYPHDwUXsc5zouRURm2CBLnSk8rOU3gOZe//cRZE6tkW2DYF5lWdY5GjmDlXTDMUL2vkEVTq+J52gnr+gySf3yfAFWz/PNS7xrWun7q2zIOUiRlMj1IsYVQlT5OGdM/+GyLXCty5wDHMs3RxbP8cxzHMM81zjwpF5kQdMM8ES37rEH/qXZ57n6GcP1FP7ikmafJKumNxXTu1fTDFUUwzVNFM9zVRPM1VTjIvJfeULumKScTHL0i0cmZdPHOti7/Z5iHoRZWhRhjZBUUS2pb51oWP52Azs1MyhZpqpGkIN4uxzLP08x7h4ZFnh29YEzjWBa13oWj91b5y610/da0LnqsC+wrcNlGmWpQXR+VmWbpaln+cYl4BKnbo3RN5NsW9T4tuS+oBCUJRRqjqxr8MPTVmuvcR314dnRQi8jWNn+ciaY5tS++rolti9xNVPUs9GN0+erPEeLrG/nT/4epb5zdzBt/OH3y2wHyxxHq4cfb96/Hj9ZNj6P1hkfTt/8PUs48tp+pfT9K8Iz4D17QLrm/mDr2cZX83Qv5jc++3o1r88Xf2nR4v/7cH8Pz5c+KdHi//0/dJ/f7z8z09Xf/1847djW/86vk0wtv2v4zu/m9j9/AXl80nqlzP7pEicPt+RjBF+jPwFXT5Builje2cTdMUUUzXD0s2y9XMs3RxLO3eomWZcTFDORrdOH6/yHi1zHi5zAd+v8Z/vSCZoyulD3RLfvnUWomtxjq104m2Jgj1p5K9OIf5fkop/i05A+kBG7cGVDlIhrDBQiL9doH80u/Hpyuovthb/ljILfIhMJg18CGFYIYlJ1TqjQGkxeROWAGoL4o5wygVnPKLREWiUnygE0WIYK0aS5WgKoH00Aj2UlWC8CJ9PjHzMMabKsXQ1loFBvAgrdrCi9ckIBI1Z0IL58Qj0ITMSS1fgpObhCPTgvBjBNQ+IjVIED+58AkHQp9uOUiRZEj4dgT5m65MlWDYxAn264yiFsWIIVX03Ar1P8QSRLP/xCARB30qyASSroX4KQc/5SNaPZP0Swv5+e1YIYaVwshLN1MVjIx+xUbx67eIBhfgh03yViZ/dgxYUjR/S9ZfJapp2H4KgX+y5G5FkNXg2MQJBX4uyF7v3IOgpO5x0hHHZ9ifQ+/uySFq+dw/6gCmLZpyRtFP4fASCoO/kjnDKrt//OQR9Icw4o96VjyDokdqTKPmwimb/Mwh6cYSWPVb2exAEfcA8i2RsYcXnI9DPtpy2cMYWydrhnCPmX/kIeo8S9KBVDxpZ/xh6jxp0IyXu4xHoe43byn0P+nTFUnHEQ0sfQj/b9ZvCOb3fPfUe9L8sWSRmWKgPH2v8bIWbceagSWx7Isu20LjO169wNYusi1mmfJIqnaCIx3ZFz7aEz7aEo9siEKeeoMpe0BWTDNX0gWaWbVji29fFvl05TLmIUZRRiiICFGL91LnMM8+xtANbPMVUTx+oQafoHFs/z9bPsfVzbP0sWw8CFAtc4+KRaYFrmD3UTO0rJihn47uS8T0pMD0ElPNxyvk45XyMQkTMx2myKaZ6jmNc4tvXRJ7t8yD1IsbQYgwtChRiTWBf4pnm2boZpuoFXT5BJQ/fOxujkB9n/2KaqZlj6Re55uVj2wrfvsK3r/BtK3wbEK0FrnGerR+O9U/Q5C/oisl95eS+apqpmWcbl3jWVYFrfRATOwvsyEJ7oA9GizENKZY5N1CIwSBd4EBwLFmWEaer4C2Ra5Gje0GVPt/gP149erjI+maO+fUM460i8f3q8aOVo4d35eGLScrnLyhfTNGATnw1y/hymvbFJOXzid3fjhHy8A/fzvz9N9P/9ZuZf/h29h++m/vHhwv//fulf366+uvn678ZHTgWW78d2/7X8d3fTex9/oLy5TT9m/nDhyu8JxvCZ9vi0R3J2J50nHI2Tjkb25U83xGB/gxSJNTTB5rpA/UMUz3DVE3RFWO7kmcbgu+XuQ8WWQ8WWd8tsr5bYD9cPnq6eTpGkU0xNQs866Y0QNOgHFvpxNM8DXT/GhTi310k/gSX4o/TCUgfyKo9uNKJKOwxuT0mt8eAQnyysH5/bfmXOwu/os38n4cTwIcYRJngEgyXYLXOKLywmnyoJYDbQklnZKAQ9zat+SBaCKKFCF6CkyR4EcaLEbwYwTUPR6CHsnI0VYllItR70O3fmAUtttFCy8r6BfQJz5SuwLLxkY9YOqwQxtQPRqDvzgphrBDGAjufQO/T/WG8GMaL4fPxEWhMiJeET0egp9oIXgpjhRCa19LuQR8yNfEM//sR6JHSH8/44xm/5eB96JMNc8YfzxJ7EO/mxxAEjQuSVVg5OXKPbyv1BgrhavyQbvyQbmSZv4A+4WVS9Ru8mqbdhz48jEczjXCyGsSCmx9D7+153LDiqxHoCwHuCNlXPoC+EOCOcFK+cw/6gHEeSTnCSfvJ0xHoyWEItwVxa9C+9D70sy2H3cD8OfTJiinvRoreRNmPG74dgb4+K7ut7Pege8uGrD2SsYXSzO9GoG9l1lDaCkTCePjzu44V9L3WjZRciAb4Ll9Kyi6k7LBwXy/2uURiigh0QZ7Keyhz0KVWisi8IzBs8vWrR5pF9sUcUz5Nl47viEZ3hM83T55unDzdOHm6JXwORIJyNk49n6ApXuxfzBzqFo+t6yLvjjxCuYhRLqJUJUxVRnbPAxsi1/KxeY6lmWJcTDGUoL3/Yl85ybiYYqqJUTQHGmBHpg81syzdHEe/wDXOc/QzB+opumKCIh3bEY/uiEe3xc+3Rc+2RSCu8nxXMrorGd2Vju5JR/ekEzT59IFmnmtaPnGsi307sjBNFWfqiSjTzpl/XehY5plAoGOcej66K3m+I36+I362LXq+Ix7E9KcY6lmWfoFrXgEKcWxbPrYuH1uWeOYFrmGO9D8m95UTNDlQqUHv8RRTPcc2LvFsa0L3pti3JQ3snAeB90BTIftajGFIHZqyHGuR56yA2RjkMNk631UdUojolti1xNVP0s5GtwRP149BaAhow7fzh98usL5b5Dxc5oJw0+M1/vervEfL3IdL7O8WDr+ZY341Tf9ikvr5C8oXk9Qvp+lfzux/OU3/Yor6+Yu9343v/GZ0858JhZj9+2+m/+u3QwrxeOmfn67+enTjt2Nbvx0nvIffvdj7fJLy+ST1iynaVzOMbxdYwIcgFGJXMrYnHduVPN8WPd0UPl7nP9k4eb4jHqOcv9hXTgKfj6GaZlxM0RXje9Lnm4LHK0cPlzgPlzgPljggDvZ0SzRGld9RCGvxr0ohfkIk/iNCT39IJyBDKKf1p1Vu7MKVuHChFy4UKMRnm0t/uzf3v+9P/R1r/L/wngaDaGOoH+LlzfXLm2vQDwHkwR5JueCMO5r1xi++HYH+huoLJPJBtBDGihG8OCwSEbwI48XTpyPQU200VYllYMo96KPDOFrsYKUOVuxgxTZWbKP+k4+gz/Zc4d1PoA/o/vCfpBDJUhgvhtCClvYpUIjj70egR0pfLO2LpX3mg/ehT9bNGV8844tn/fGsH8kFbOwPoE+3nZHde9Abfwvy+stU/aWL9yvovthRu8ErqYFCRFLVEBYiFCKa4TwcgR7I7YKnI9CTw3DSEU4RChFO2cNJYn8ItwYxS4BQCJue+XPokxVj3h0vetCKj1CIitvKeQ+6t2LM2iMZWzjNfDACfSu3hFLWcMYaydqMhz+H7q2YSy6k7EYrbqTiQsoupOxCQqsfQRAEfSkuO2Ilu4n9M+jevC5vCuZ0vpTKjcvtiNQMC/Qhnsp3KHfRpTaqyLIjNG7y9atczSL7YpYhm6RKxndFY9unz7aETzeFt/KwKx2jnE/Q5C/2lZMM9Sxbv8S3b0h8u4oolRzqTlfFKIrwltizwreClvsgIgRa61NM1VsVYp5jWCB9iGnGxQuabGJPOrYrGd2RPN8RP98WP98ZaMPZGGGg5ZOMi1k26O10b0oDewqYrkmASWR0VXxPFtwUuVf51gWOfoapmqCej5IVPtsWP9+RjFHOJ2iKSYZq5lA3zzEuH9vWBK71U/ea0LV6QvZeHBnn2frZQ+0089aBmKARzscUQzVzqFvgmldOnBti3/ZZaDAXga5OkOP9cxxb8chRGQ4xEVk63DWeo8S15tjG5L46BvohZhiK8T0x6Kb+fvXo0TL30fLRo+WjRytHj1Z4j0FXxObp083TpxuCJ+v8x6u8R8vcB4usb+cOvp7Z/2qa/hXohZ5jgvjSl1PULyaBSGz885OVf3q0+I+DKNOjxf/xePlfnq39ZnTzXyd2Pp/c+2KK+uU07asZ+lez+1/N7gNH5Ju5wwdL3O/X+ERv+e5AIcTPwXWuHT9e5z/bOh3bk47TFC/2L6YYqmmmauZAPc24eEE9H9sRP9sQPFnjP1njP17jP17jP90Uju2dvdi/mGHp/zqjTH+kSPwn6gRkihT0wZzGl9J4kxpvSuNLA4X4FXXm/zh48X9xRv+e//i/nT4IBtF6jVSIer3f77VbLTCWyQbGMsFZdzTnjef9SEFDuw9C80SgSTYx8lQDgkUPZYRURF3cD6EJUXqoH6LYxUpdrAhEooMWWpLREeiT+x9A40K8FMGLYUwDFCKEFUNYYOcT6AN6IIKXIngpfD4+AorJJkYg6IGsHMFLIUz93Qj0PtUXQHL8x8CHyPrjWcKHsOT8ktG/oXj9SD6AFvhPRyBoQpiqRbPNeL6DFHtY5cpx9CvovthevcFrN3jtBq+6no78LT18g1VS1PsQBE2Lss1Iuq7b/wyCPl23FLzxvNt08B70yc8/gH6+7XREUg44LdsFPkTaEUnZBc9GoKeHoaQtlLQGHUvvQz/bdtkjnpUPIehDlgIpedGqZv8XEDTJw6pEpMiUt8M5WyRz8GAE+k5uDbmXPoB+tu2xwf7ljyDoQ7Y8UXWjNe6T+6vWqjtR4Twegb7XOsUTI9CnS8aiDQ4sfgBB7x+ehnK6QGb3648nZNiZNX5qhPnaIEfpZZ676FLHnsi6LTCtHeuXOJq5A+X0vuwF9XycCC4TwYRBQGaKCYJF+oUjy+qpe/s8RFUh+1psX4uBDgC6KrZzHlg/dYLwzuyhduZAM8VUgeAD6MaYG44ygRATz7zMty4dWxa4hjmWdoapmt5XTtIVL2jyCapsnCKboBJjYED3wxQTRLr0izzLqtC5IfHvyCJUVZyhw8GsXYYWpSrhnTPfxqlz+dg8x9ZN7SsnaLIJqmycKhunnE9Q5ZP7F9MHmjmWfuHIvMK3r5+6QW/zlgQMxHKtCRwrfNsSz0IGmoAzoZ5mqmcOQMTMsHBkXjlxboh8O+dhCphNRk57PjRl2JY8117iOat8d10AskoEumTCj7bA2+C7Kjx7gWPJHOgSFHlwXehY4OhmGMpJunyCcja6KwFe1PNt0bMt0fNt0eiOZHRPOkY5H6Ocj+5JR3clo9ui55vCJ+v871eOiJ7tRfaDJc6DJe6DJc53i6xvFw6/mWN+PbP/xSQVOBO/fr7xG6KnevO3Y9ufv9j7cpr29Szj24WD7xZZD5bYD5e5D1eIDgPQT/547eTp1unoLnHqcer5OPV8jALGUAmfbJw82RAAH2KCriR+nUPtHFs3x9JOM1STNPn43tkYaGcAKLJJhmqGvJF25TBDn+LaKwJfSxTsSf8Keqr/JJH4Azrx79dFMSwSkBkuGyMFfTCnC+b0obwhVFBpDaEIPi/iL0h4S2ecFRlrTXHgcoUGClGv1bqddqPRUOuMZzqPHc45o3l3rOBFij60FEDLQawUdHA/GDTBP+YYUhU4pXs4Aj2Ug+GnlWg6sncPeqSsIzkwlimOAoUodbEiMRkCUU2NQBD0TAenypFkKYyXBE9Br8G4IBnc+QT6YD9IjEqSTYxA48JkJZKqGBi30yvep4Ee6QL/8Qj0vSqQyAcSeb+V9T50b8OaDyQK/CeD3uQJQaoaSdfhbDOabyPFLlq+tHH/FrovslWIFCBo5ersxchHnBRaTlHvQx+OzQw+47eyqh8t+xJFD+Jf+wiCoHsrhowTzjrhrNN0AOI8P992O4TPR6Bnh5G0LZy2hYGtd9vhnCOqGurWnjpONn143W07eg/6dMVcdETztkju4MEI9J3CEvYsfQD9bNtng/OOmGZw1HvUiAutcR+PQNAEG6k4kTLr+xEIGj+IFi2w+ndksf913a10p2QOTGJBhAaYpw2xL/wMmYd25toV2zcFltVj4xJXN89Szx6oppmqacbFFONiinFx26nL1s9zjAtH5sVj64rAuSkN7Cmi+1qMaUgxiVkCOEOToCgiWxLvmsC+fGxZPDIRAyKJzmrTIs+8BMYm8SyLxxZysJN9VehYFThW+NYlnnmRa1ggpm6B6V1qcpIXYZdBv/cy37YqdG1IfNvnYYoyRtegB4YU25Jjm7MHepyuilPkoW2Jd13oWD62zLP1M+REMFKrDAtH5uVj26rAtSH2bp8FwZjXPXlk5zxITGwWedZPXasCxzLftnRsXeSZF7imBa5pkQeu3L4qcG2KfTvnYaoyTlej5LSPNMuc5VgLR/bysavG9zQEvtapv0MkZQr2RCDXiK914q4dO0pH1hzLgNMu4G2pd/XEusg1zLN1s4ca4LgAJ4wUSOUkQzXFVE8z1VMM1dT+xeS+4gVNNr53NrojfrYpBCOFnm4Kn26ePt0UPtkQPFk/ebx2/P3q0cMlzncLh9/MMr+e2f96hvH1DBjtyvxukfVwmfv92vGTjZOnm4JnW8Ln26fPCSdS8GT95MntCFrZOE1OeIR0xQu6fJx6BmJNozviMQrZWU3eKmBEExizMHOgBp1S00z19IFm9lA3zzUtgRtJ4qdcxA+MGXIsU08auZbFf/hLnTH3JnLk1R/JO6fa/bkT7n5iqh1kiVXN0bIJLpngkgkum6NVpVr/6tUP3U6z2252281et9vrtnud1vXV5c31Vb/f63Q6rVaz1WqqdcZzo98ZK7qRkidR9mOVAF4N4rVwshpO1SKpGhjtGiXmIhDEMrVYph7LNiyHv4Du8a35FpgEN5hDh5V6WKmLFjsJEGhy16LpKpyuwqlqJFUBwKkqAbG/CqcH1OB0DRQOJythvBzCyyGsHMRKJEVyoxzEyiG8EgIXnG7AmWY014rlO/FCDyn1E+WrRPmKSMtRukyUrxLa+RFoTlpOUe5DH7LQaL4LZ1vhdDOUagSTNT9W9aGVo8cj0CONO15wxQuuWMEVKziHcMTyjugQsYIjVnTGy65ExYPVvHjTn2r5Uy1fsunFam606kIqjnjJHi1Y4bw1krfCeSuct0ULtmjREa84E1U31vBgTQ/WALjRuitRcyIVR7xsi5VssbIlWjbDJWO4qA8WtIG82pdTujPnjqTYip4Y4zw9zFKHmMoATebZk7q2RI51oXXtxLzEMy3yjItHpkXSoN+ODSUn9JJRHRRYQzLrTvpAj9PV8T15eEvqG+RvWBU4VgSOVYFzTehaP3Wtnw6nfHgt64NnQ+RaFzrXBA4y1GO9hW9b5ttXBI41MNxI7N0+C+7KI5SLOF2DMvVJlinDtRIz5phalK6KUYjJGe7VE/syn6gHyNKqwLl+6tkU+4A2UC/i+xoUZDeiqeK0iyiY/bAjC22fBbak/k2xF0zyWL9Ng0EcS1MhDC0+mA/IBilDQL4NUh5A0iFJuA9y9omDPVGgI/Q2TlzVY0eRY84wdShVGdmW+jZOXevkGKrlYwuYdjDHNpAKbVrkWe6MKOUYZg+100zVJF35gqYAFvwFXfmCrpgA0kKVjVPOgcNBqAjJs03h6LZodE86Tj2foIMeeMUk0XskH6fKyF59UpwONMA/AGO6Zg7UU0zV5L5yknExfaCZZenmgUd4bF05sYNZEasnDvA7LvEsy+BeIt51rYu8m1L/rjxC12Asc47nrJEKcXUee/mfniTjPxJZ7Ic/iXdm7/izEni8NXsHZEXqlnjNEqtaYjVLvGZFGpwTiVpnfBOtwaw3WbV602APmyeUW0PAtPnxWiBZD4FZxOkmnGnAmUY004xlm7FsI55rxrNNMLEZgOTbiYL18cgvqX4ilwZevsSJZBt9rNxHSxjtPgSNWWK5VizbiGUb0cxdsm+lebudacCZOpyuR1I1QHhAcrBdD6fqkUwjkmlGsi04247mO7FCN17sx0uX8dIlUrqMFy/jxX682I8Xr+KlFOU+9Eib2rsPfcjCooVeNN+NZDvhTDuUbgVTzYBscgS6v26redGqB6140Io7UXEnKq5ExZUou4gNEqTiSlRdiZoLrXnwhjfZ8qXagUw3kOn6yMwZbrTuTNQc8Yo9VrbFSvZY2RYr2+MVe7ziTNRdaMONtzzJNknLjbdcaMOJ1u2Jmi1ascUq1mjFDFeMkbIhXNaFyppgSRUoyD1ZqTMtsuEnZuzIEGfrogfqCF0ZosmDu2f+bal3S+zZlHiIHAkS35ZkMGeNnCggj4A2O9OQGpp+nOdYcmxThqnH6WqEooB3ZaFdWWjnPLh9Ftw+Cw5PUtuVh3fl4T15ZE8RAbnhBnniiBln58GdswAxF2EIkHpoRxbaBfPvbqcup0A6OZAJg23OHhpSTB1KV8epyuiePAys/HA9O+ehPXmE6FLWYEx9kpjvbcwcEhnxyDnSqjj1IkZRRgd5JgYJ9YCuMPXJQ2OWbc5zLMRqCkeO8jEILnmbQl+bzFo6pBChnijQEfqaAk+N7ywf2fIsE5gHHh3+BoAyrYvAuFsgse51kXdD7N0QeTZEHiDDqyDrxhHh4iwcmRaOzAtHpoUj0wLXNJjXNnuomznQzBDjhkG4TD1LjmBeuG0TmBePTPNEL712yHUD1ZITSo6tSzzLIs8MZs8tHVtXTuxg4suG2LMp8W2D30vqBxmfbm8niX9bGtg5D+3KInsKmKZGmIYUx1o4dtUEIMXhX2jyvp8GJOz6k3h7KsA/NyHga9kAIRvSuCXRsCdahkjp3IZIzbDEFBYZgkKdX6jzC7U+odYv1PpFer/EGJSaQ2eWsMwKm8M5NwqyQTSCqWYo0wpn2pFsG861orl2NNeK5drxfDuea8fBRqEdz3eQQgcpdBPFbqI4nFmPAC1f2rj/GwRB0D2BudCJ5dqxXCuWa0WzrWi2Gc02o9nBv61orhXLtWK5dizXjpLA2RZJE8424UwzAkg3ImkyN0a6AfQsnG6GM80wkRijE8kROTCihT4ALvTgQg/O98AyFdHiZbSQ3P0U+uAQi+R7kVwvnO2Fst1g2vrdCARB0DeyphdvePC6B6t7sJobrblQ4tVF/utK1IAwuLCGC2u4saYbb3qSbU+q6013vemuN9X14G031nRhDWei7kBq9njVRmKPV+1IzZFoOLGmC2+7kh0CsFYr1nQkGrZ4zRqvWWI1U7RqhKsGuKqPVLThiiZUUQVLcl/xzJMXO7NCe+rYgvNMGMeQONAiDHWcrorSLmCKEqYqYYoSpiijIM0nSABHU8WJrDuaBEOLHRjSLHOOWJCAzDLNseRYRO4NlK5G6GqEpiJTtqkQsAfUsK9J7GtQkFGDgNiZIIoRR8VoFzHabTpSMhepJkHkMR3KiT1YHeG1LE/76tdzmtJAnlQNytCCfE0ZtjnHsRa4ViLJEsiVTaTZMCSZ+iSRpW5w5aD3RTfIdQrSRg2ntq7x3fUTb1MAFoQg054PEsSe+ttCb/PEU+e7Kjx7kWPJsYxppg4b/hJAfpE9eWTnPLQDpFEW3iVzIgF2ZeGds+CWhPByCMTeITzA+1kTutYEzlWBY/XEsXpiXzmxrxJ+oWtd5N4Qe24BExgHjhfftnJiJ2Y+Cl1AA4iaxQNH0EfOnw/tysOEgoI0sQoi9wm55/YnoGtQhi7JMmWJ7FXeptDfFgW7klD/ThrtyF8+knD/z+MticQjf4Czd3MOE4A15hog9bct0bSjLbAysw1pWGI1E1wGS1IbwiVDpGiMlM3RijVWtQHzhDZcWMONN714w5ds+VPtYKYdynTCmU4k24Gz7SiRwK4Ty3ViuU4sT1LokvTihR5S7JMpvvsI0VrvgwLRfAfOdeBc+w7ZdiTbhrNtOAve7cC5DpH46DUyrTBJCJBuhVKtUKoVTLWCafI13Qqm26FMh6QbynZD2W4oR2wEM91gphvMdkPZXijXC4E8SNkeyJQXyHR96a4v1fGlOp5ky4O33HjThTVcaMOJNhxow5EgGd4e7Lldn6PtxDsuvOMCK5uiLQfatCcaNqRhidcsMcLVM8dqlljNEq9bkIY10bKhbTvWsaMdO9om1tBGmpZ4wxyrGaNVY7RqgKt6uKqNVDXhqjpUVYWqykBF7iudeYpiV/7UnjuxZXiWNNeUYhuTLAN+oAd57lCGFiUXJwDgIO8QSEMEUniyyNStg0VsjogcdjmWKXP41vxF+uTBUCqkd5A8MIBi4HCcqSfPfvcaDt7IpHSrEDaQSo9Y8+DAkAIpsocruVODJcexFo5ItTsi11RgDy/mY8yQggFIE4eDVIDW4pFtOPH1IANgnVh07PUFi5oCQh6qyiOxzgAAEjdJREFUx84y71bV0sNfAlOH72tv/ZhbkR7OjgfeVYKwGJEw/C2QcrIrC+/KQoTkAK9uyJ8j3Dh5GGRVApPegfXfkvq3zgKEOygLDR1CticuYlRV7FbCQQvgLkO3Fs7UJUGicrY5x7UVCa/L0xhOz/5XxeuLa/0piN7k37ZmEVgfonkrD4BEC1glc7RigstGuGyMlI2RsilaMUerlnjdjtRJhWi6saYHb3mTLV+q5U+1A+kOoRPZTjjbCec6kSyRqI6kOwDOdeF8L0o22OE8oBfJ94gy2W442wln2wSZduh1gE0n/023SYtPELgLiPL7ky0y3N/yJVu+FPmaahOk2+Rq2G1vsu1Ntj1JsNHxpsg2fqrrSXbBCtig/e7EWk6sRVr25sA5syJ1K9IYYEEaFqRhBhtxsN20IC0r0rIgLWuiZUm0zEjLjDTNSMMUb5hidWO0BvwAA1w1wDUDXDNE68ZYwxhvgEWtTfEmwBhvGGMNQ7Suh6s6uKoDwnCrDVVFoCr3V868ZamndOoqCp0Fvj1/bMvxrDmuOcM2ZdimDMuYYhlTdxeZIZaauc3vb3pjvbMhq0pkOTUPrQfwFrIgfx/BT5W85bVrYBHLn90m9yYW1ATejJXwA9i33SR3IbMH3n4QQmCK5McZ+kTkgmvElZPXfytOb6wPOrSuzjtWIXXdpjH/f9o78+e2jSyP40/b3dnaqZ3Z2UkysaTZ3WST8chVk9nKJnb2n9mqqWxtnLEtW5FtWfdFHTwA8BTvE6DEGycPkLJ/mh8aAHEThOSQkt+nvqUCm43Xr5vke+imiFaT62P9aCjpraxJ2GVDxtXMb4p/2S/opY3Ohb/so7yCpmh53cRO/6xmYS2lZIK0slMFygRqGiiot1ZE1xP/d1iW9x0yy6feJ3H8HhvP/9CteZUbuc98M9GZyOueuGMZN+W13wDVeQ9ULFgQ9FtVo4ecP8eiDHGaaZ+oSndOs8xZjgnkuWCBCxa4UJHDizxR4smyEC4LEUqMUmKMEmOUGKfFOC3Gq2KiKt9dziw5vl905Wv2i17iwlSN7iZoMUGLcbor29QoRokxeqwoJUbVuF8RoxUxWhEiGoUrfLjCh8t8uMyTqkroQCBLAlESiDJPlHi8JOAlHi/yIXljJXl7pWBRQFfrKJUGC0KgIPgLgr/An+WRuNMsd5plT7LsMVKGPc6MD3xIadaXYY8y7FGG82W4ozR3lOGOMtxRljvKcocZ7jDNHqbYwxRzmGL2U539pBLrkVKd/SRzkGJV7ct/mf0Ug+rsJNo7ifZ2vL2VaG/GWpux9kastR5tvY60XoabPxHNVby+Eqo/C9SfBi6f+NEmCpePTy4ea2L3Y1sZ4vJ4Q2PtlmfjypY602hc2bK+jQ+KEWUP55rBDc1WmmY7xtPljqiJITDu13jLaJQkNNIOxXhHT50p7Y6hup1Bn6g7gyo7gGqHQs2dprkLmvoYNgiiNLvC6Sdt6lm6csO0rKwt/P6w/P2hfNdCZWFQWR7cU7LOQen7g5KxCRT9ra8wDBcZ+lQtb6fhcivsO66nhh1kPemZQbiTVsZqr+DtFaK9QrQxFOm0SSJQ4Px5zp/jznLMaZY5zXZOs4yqsyzjz7P+AhvIK3vSFfhQkcdLPFEWiLJAloVwRQhXRHT1Ha2Mc0ZMvUKndIVqlI/KIV6MUIIsQ3wvW4i0F1EaCy8JeFHAiwLaeDVY5FGSC6IVtjwfyPMB5cJfvtjPcWc57jTHnuTYkxx7muNOctxJjj+RD2QdZ9FlO7pyZw/T7GGaOUgzB6mx9lPMfpLZTzF7KWYvyewlmd0ks4sOzhUlmd0ks5Nkds6ZnXNmJ8HsJJjtRGc7IV/7b8XbW/HOVkxRvLMVZ7bina2ERmiWEG+jfLARbb2JtNYjrfWwnBjWyNYq0XxBNJ7jjZVgYyVYfxaoPwnU/uqv/agmCY1+dFJNDYt/1d4lW7PRsa7mZE2sLLtnYVmz67LOGZdNa8510GNjvtHmObM17f3D1ZxR16WfgNFbfcqUpW5YrdkxVD8VQ7MNJZfodhg9rv7/iZWOzZWnTznKDMDxYsL+IkMzhtpZoDKZM+/F/aFIv4PsdfXEoKCTno7VxEIlEX3xoCpQlFMFyhP+HHumKs+iRZJAng8U+QCKs/IG1wJeEnAlKJNlkSyLRFmUg3VFlegsoiKir1uJsohSDlEWcLPQBf5YAl7iQ0iyV7K0yc9iqScn6yTHnWRlHSvyycs1sg7T7FEGXd1zB0gp7iDF7afY/RS7l2R3kc5l7ZyzO+dKiE90thLMVpzZijObGm3EOzrFOm8UrevUXo+116M6vVZkXR5pvYq0XoVbr8Ktl+HWWrj1E9laJVoviNYLovUcb66Ems9CjaehxtNg40mw/iRYf+KvP9FGLreyfFNOdbob+9488dIL48dpvNzU+NGQCE1pwDbHODQ9nvRoZdyGWpc8zmqPrfLcY31216tmkk1NzXzrB4vVuYsfdFNMJb4bx8RZdetBU14IN4Hszmv6T+IEPTEo6CSUJDC80sMrvVBJlFUUg4rkqKqREmoFpGBRDJZkhUpiqNQNleQ9L3E1yldEojIunKiQQYpjQUtpEpv8Ja3im1+js7xwJi/r86d5/lRZsj/J8cdZ/jjL+7K8L8v5sso6T4Y7TMs6SLMHKXZPJ24vxaHj3ZScFXaS7E6S3T5nt8/ZLaQEu6loI8FuxNk3itZjjKrXqqLMK5Neqoqo6ryMdNacFdbpp3BnlWyvku0XZPsF2X5OtJ8TbbTnz4o6xwy1nt3ErPbOaxaXk+rXKqarQo+X2A3VptmsdYq1TnhGf5RRasqa0rGn6tc2oPf5fntqUMhJGEkNCGqA8gRe7oVkdUPlrj4Wi8GiGDBoXKEbKnbRWarwsXpmhUqTFUQqjhUwyV/s+otdf6HrL3TP9DrV6CSvSjzJi8c5AcmXE3xZWUdZ4TCDxB9k+IM0f5Dm99L8XprfTfK7SW5Ho+0kv33Ob53zW+f85jm/meA2E9xGgttIcG/istYT3Do6kMW+jrGvYxzSK6Qo+yrKvjRpLYLEKQfsWoT5yVlhnVZ1Yl+QjKrnSISslVujjo3el+VnOrXRwVO8jWS1fNwxriaP1fKktk1znTnUe32t9S+EVuOnbu79MEd6j6+XQVYfASxclUhqQFB9otLDK71L7qopyGrcnJpjvW0Kb5sWJRaabJk3qq5RzSDu6tIsFml0oVcViRlVmRHNjGhmqIpihjTaXpsZUZ0hUkWvsrVGZpXMag8tVfQk5Wfh86zRrB1wkJS/vprXk87aMD/7MRnLtTMjk272hXDZ6C3VLF9iLFwdktSAqPTxcu+Su/rfH14s/PEh0qIiueT+t0j3FC3c/3bhvqby8sPF5UcGLal68GjpwXcm/Y+jzPVd6tFkLT9aMnlrpYeLy6ahcCHtgCwtW/Zd1uLyd/atOzylrWOWm65ZGrF9dupXQe/S0tQW7N4zk89atJLemu7NoKmgK5Ff/eWHi8sPF5YfLmgeavRocdm6RYORBb3Mxm0qGLrgYUy0nzXPnynPcvkBt33hxh9Dh4GSx8dNo6AphJHUgKj0QuVuqCg2+Kt7978x3/waAAAA+BDBy71gUUA/gKhz0u+++HrWHgEAAADzQaDA+3PMSarpSzYumf5Hn301a48AAACA+eA00/Yl6wfR6l6EqrbE3/x+edYeAQAAAPPBUeJyL1LZxgsbgWylzv3zp19gGObT4Nny9S3cUj7YjgMAcNfYi1S2Qvn109RLX6J40fmnj/5dG91uJElMe4rn5t4H3vyBDAEAwF1gG8+/OUutHUZX98hCtfWL3yzNMEPMW2D17M+8dQQAAMALm4HMq+P46h65sh3KU42///U9h+hmt/rkXG53bKjvMzHReWc7mClST+W/gz9u7LjxHwAAYK7Z8KfXjmLPd/FnW4EcVf+7X93DbFbStSVujrUPp63vBvftOvtgZ9OumodxAAAAuJW8OUutHcVe7BLaDIFwCJcuo6FPg2XhTWUIu3Yxq2wx0SXnJuzsuBwTAACAW8Mbf/rVcXx1P/x8F8/TjX/4lwU3Uc9lNDSHaZf13TCtHbv6Dr7dlB0AAIBbyWYwt36aWjuKrR5Eihetf/zt76+TIRwirJtsYVnHjutE9mn9v+Y4AAAA3Ep2iNJmMLd+ln59kizVmF9+8hnm9Rtpy/DqEEAd4rjL8OrcroNxO/8xmyQx7TiY7QAAANw+DmLV3XBlmyhthQpUg//Vwh9m7REAAAAwHxwnG0eJ2kHsYj9arba6//pvD2btEQAAADAfnOWYk0znON3ypVqXzODjz/88a48AAACA+SBYFAIFwZ/nz3JcnRt++iXc/RsAAADAMAzDcKqPl/uhcjdY6jaEq4X7387aIwAAAGA+IKsSSUsENcArg6b4dmn50aw9AgAAAOaDcHVE0kOClghaaorvlh58N2uPAAAAgPkgfDEilSTR7MoZwuEnBe65voVr2p+29fftsAdP5sEZAAA+XMxzCG1gupEkMe0pN2XfW+vzE5SncmZ+3AYA4O4QpockLRGURFCDpvh2thnifdf/+Q1eB/fOzJXbAADcHUhaImmJqAyISr8pvl168Mgh3NitfjiX2x0b6vtMTHTerr4b+27suGl3Yrldv9Rju3avad/BTwAAAFegf2QiKn05Qyw/whxvRuT+GDMFQff1XeJgytm4S3+manTi8VRD4d5/O7en7RcAAIARkpYIekBQfYLqN8Ur7X+7eoiwBnwaLAvdRDoHbiTCThtJ7epMtOm7iQzhftwc6gMAALiCrMoZAqd6TfHKsMp0zaiqDY5T1XeJhwjruS8TnZxo03kopvLfjUvTDiYAAIARTYaw+B7iOsd2T7mp7zK6eY6w7sO0+0YnHjt337P/mIuxdTmeAAAAOkh6QNADgkarTG+XHui+h7CMWS7LDSXmY8uwZVduxhAWLZvWPjUxwpqrOTc91ThYPjQ76eC/Q7uWg+BcHwAAYDIkPZCThCZDAD8PELsBAJhrwrSEkgRJQ4b4WYELfAAA5h2Slkh6QFAD5RdzkCEAAAAADMNMGWIR7u0KAAAAIMJVKVyVUJ5oQYYAAAAAVMLVoZohmuLbxeWHs/YIAAAAmA/UDIFWmRb+CBkCAAAAwDBMO4eg+k3h7b37D7Eb+jebO/CPOs7jMKve3fZRBQDg1hCpSmFaCtMSQfUbwtW9+9+af6Ll2biH0+cw9t1IhrjBfkGGAADgZwJlCJIaEJV+Q7j69A/fzDBDzGfsu75X89kvAACACYQvpDAtkXSfqPQa/Oh3X/63QzizW3VxLrc7NtT3mXD23KGyg327hxMbmmjfQ7/c1J/WvmX9qfoLAAAgE6lKYXpAUj28LNb50SdffI053uTH/bH24bT13TCtP57bsqvpYNBNWx58nqrdiXYAAAAmEK4OSKpPVHp4uVvnh5/853+pT3mIRAZ8GiwLPUdtl/5YHqt/XbZlV9Nc7r4mZj8OE8fWYdCmsgMAADCBCD0g6R5Z6YVKQp2TPv78z54jrxltUJ6qvhs8+2l2yX1D3srdBHrLcjcnXvM1AgAAsCVCD0iqT5S7oSJf56SPPvvKc+TF3AUvN/XdRLTr+DNVxLSr7DJS27XrwX9v7apM7ioAAICWMN0nKz2iLAaLbJ2Vfvsff8Km/CbWrtxQYj52CH9uwpnLyGh5ylRNmK25KXfTL4dxm9gvy77Y9ctlfwEAAHRE6AFJ9ciyGCpwdW6AMgRwB3CTOQAAAJyIVgdhqkeUxVCRq3PSR59Bhrg7OMxpAAAAJoMyBFkR8RJf56WPP/9q1h4BAAAA80GsKkWq/TDdJcpiU//frgAAAMAHTexCil4MInQvTHVbwujTL7+etUcAAADAfBC/lGIXUrTaj9D9lnh17/43s/YIAAAAmA/il8P4pRS/GMSqg3YX9ocAAAAAFBK1YbwmxS8HsctBuwt7zAEAAAAK57VhojZMXEqJS6nTfbf0APapBgAAADAMw7Dz2vC8NkxcDuOXw07v3dKD72btEQAAADAfJOvDZH2YqA0TNcgQAAAAgIZkfZSsj9BMgoEMAQAAAKigDIFmEkwfMgQAAACgkGqMUo1Rsj5M1iSmB99UAwAAAArpxihVH6bQHAIyBAAAAKCSbgzTKEPUhkzv3eIyZAgAAAAAwzAMyzRGmcYopawywS/mAAAAAJlMc5RujNL1YaouMf13cNcNAAAAAPE3hpoFpQRp5a8AAAAASUVORK5CYII=" alt="" />

  现在程序已经开始等待请求数据从port 7001, 不要关闭程序,让它保持运行,我们看看会得到什么...

  Receving/send Data:  

#!/usr/bin/python
import socket #for sockets
import sys #for exit HOST = '' #HOST name or IP address
PORT = 7001 #remote port s = socket.socket(socket.AF_INET,socket.SOCK_STREAM)
print ('Socket created') #bind ip/port
try:
s.bind((HOST,PORT))
except socket.error as msg:
print ('Bind failed. Error Code : ' + str(msg[0]) + ' Message ' + msg[1])
sys.exit() print ('Socket bind complete') #listen connecting
s.listen(10)
print('Socket now listening') #wait to accept a connection - blocking call
conn, addr = s.accept() #display client information
print ('Connected with ' + addr[0] + ':' + str(addr[1])) #now keep talking with the client
data = conn.recv(1024)
print(data)
conn.sendall(data) #close and dispoiled socket
conn.close()
s.close()

  然后连接到这台server,需要注意的是如果防火墙开启,要注意设置的端口是否可以安全访问。如果答案是肯定的,你将看到:

  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" alt="" />

  现在我们已经完成了一个绑定/监听/同意请求的一个完整连接,但是你会发现,在代码执行完成并返回'Hello'后会退出,这样的设计是效率非常低下的,实际上我们的很多逻辑是在接收完成数据后才执行的。

  在现实使用的应用场景中,我们的server需要的是 Keep running non-stop, 有一种方法就是将Accpect()方法放在循环中,这样的话它将会一直接收客户端发来的请求。  

  Live Server:

  顾名思义,一直运行(监听客户端请求并同意处理请求)。  

#!/usr/bin/python
import socket #for sockets
import sys #for exit HOST = '' #HOST name or IP address
PORT = 7001 #remote port s = socket.socket(socket.AF_INET,socket.SOCK_STREAM)
print ('Socket created') #bind ip/port
try:
s.bind((HOST,PORT))
except socket.error as msg:
print ('Bind failed. Error Code : ' + str(msg[0]) + ' Message ' + msg[1])
sys.exit() print ('Socket bind complete') #listen connecting
s.listen(10)
print('Socket now listening') #simple way as server
#-------------------------------------------------------
#wait to accept a connection - blocking call
#conn, addr = s.accept() ##display client information
#print ('Connected with ' + addr[0] + ':' + str(addr[1])) ##now keep talking with the client
#data = conn.recv(1024)
#------------------------------------------------------- #liver server, always running
#-------------------------------------------------------
#now keep talking with the client
while 1:
#wait to accept a connection - blocking call
conn, addr = s.accept()
print ('Connected with ' + addr[0] + ':' + str(addr[1]))
data = conn.recv(1024)
#reply = 'OK...' + data
if not data:
break conn.sendall(data)
print(data)
#-------------------------------------------------------
#close and dispoiled socket
conn.close()
s.close()

  输出结果:

  server:

  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  client:

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" alt="" />

  到目前为止,我们做的不错,但是这个不是一个有效的网络通信实例,server端的代码在一个循环中同意client的请求并回应给他们,然后并没有针对接收到的请求的数据做任何的处理,同时它也没有能力处理同一时间的多个请求,现在我们就来处理这个问题。

  Handling Connections:

  想要处理每个请求连接,我们需要一个独立的代码处理逻辑和一*立的服务器,有一种办法就是使用多线程,主服务器同意请求然后创建一个线程去管理这个请求,然后服务器返回在继续处理其他请求。  

#!/usr/bin/python
import socket #for sockets
import sys #for exit
import threading
# from thread import * HOST = '' #HOST name or IP address
PORT = 7001 #remote port s = socket.socket(socket.AF_INET,socket.SOCK_STREAM)
print ('Socket created') #bind ip/port
try:
s.bind((HOST,PORT))
except socket.error as msg:
print ('Bind failed. Error Code : ' + str(msg[0]) + ' Message ' + msg[1])
sys.exit() print ('Socket bind complete') #listen connecting
s.listen(10)
print('Socket now listening') #simple way as server
#-------------------------------------------------------
#wait to accept a connection - blocking call
#conn, addr = s.accept() ##display client information
#print ('Connected with ' + addr[0] + ':' + str(addr[1])) ##now keep talking with the client
#data = conn.recv(1024)
#------------------------------------------------------- #liver server, always running
#-------------------------------------------------------
#now keep talking with the client
#while 1:
# #wait to accept a connection - blocking call
# conn, addr = s.accept()
# print ('Connected with ' + addr[0] + ':' + str(addr[1]))
# data = conn.recv(1024)
# #reply = 'OK...' + data
# if not data:
# break # conn.sendall(data)
# print(data)
##------------------------------------------------------- #Function for handling connections. This will be used to create threads
def clientthread(conn):
#Sending message to connected client
conn.send('Welcome to the server. Type something and hit enter\n') #send only takes string #infinite loop so that function do not terminate and thread do not end.
while True: #Receiving from client
data = conn.recv(1024)
reply = 'OK...' + data
if not data:
break conn.sendall(reply) #came out of loop
conn.close() #now keep talking with the client
while 1:
#wait to accept a connection - blocking call
conn, addr = s.accept()
print ('Connected with ' + addr[0] + ':' + str(addr[1])) #start new thread takes 1st argument as a function name to be run, second is the tuple of arguments to the function.
#start_new_thread(clientthread ,(conn,))
  threading._start_new_thread(clientthread ,(conn,)) #close and dispoiled socket
conn.close()
s.close()

  输出结果:

  server:

  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" 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  Client:

  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" alt="" />

  So,现在我们拥有了一个server,它是一个很棒的学你说话的机器人,HAHA

  Conclusion:

  截至目前,我相信你已经掌握了在Python中基础的socket网络编程,你可以尝试创建其他的社交客户端或与其相近的实例。至此,放学。不会再讲5分钟。

  Bug fix:

  开发环境: Python3.4 + ptvs

  以上代码均已通过测试,当然不排除Python版本不一样的情况,实际上我也在原作者的基础上修改了很多,如果有bug的话,欢迎指正。  

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