python調(diào)用Kafka構(gòu)建完整實(shí)例分析與應(yīng)用

作者：沂水寒城 2020-06-04 12:15:08

開發(fā)

后端

Kafka 這里應(yīng)用端給出的方案是使用kafka來做，但是這個(gè)我在之前沒有接觸過，所以沒有頭緒，就想著在本機(jī)搭建一下kafka的環(huán)境，來去熟悉整個(gè)操作過程。

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近期遇到一個(gè)需求就是我們需要把當(dāng)前比較耗費(fèi)資源的接口開發(fā)成異步通訊的機(jī)制，簡(jiǎn)單來說就是有一個(gè)消息隊(duì)列來不停地進(jìn)行消息的集中分發(fā)與任務(wù)處理，這里應(yīng)用端給出的方案是使用kafka來做，但是這個(gè)我在之前沒有接觸過，所以沒有頭緒，就想著在本機(jī)搭建一下kafka的環(huán)境，來去熟悉整個(gè)操作過程。

接下來就先開始kafka環(huán)境的安裝。kafka的安裝需要依賴于zooeleeper模塊，雖然說kafka自帶了zooeleeper模塊，但是網(wǎng)上清一色的教程都說還是需要自己手動(dòng)提前去安裝zooeleeper模塊才行的，所以這里的第一步就是安裝zooeleeper模塊，下載地址在這里：

  
 
 
 
   
  
  
  http://mirror.bit.edu.cn/apache/zookeeper/zookeeper-3.4.14/

我下載的是3.4.14版本的：

安裝的話是很簡(jiǎn)單的，直接解壓縮到本地，之后按照下面的步驟進(jìn)行操作即可：

  
 
 
 
   
  
  
  1、解壓后進(jìn)入目錄conf下，將“zoo_sample.cfg”重命名為“zoo.cfg”  
   
  
  
  （zookeeper的默認(rèn)端口是2181，如需改變可以在對(duì)zoo.cfg進(jìn)行編輯）  
   
  
  
  2、進(jìn)入bin目錄下，點(diǎn)擊zkServer.cmd運(yùn)行  
   
  
  
  3、命令行顯示如下，表示運(yùn)行成功

安裝和啟動(dòng)成功zooeleeper模塊后，就可以下載和安裝kafka模塊了，這里需要注意一下下載合適的版本才可以的，網(wǎng)上很多教程都是比較早的了，所以給出來的版本信息可能找不到了也可能不再合適了，這里我是摸索進(jìn)行嘗試安裝了，在第一次安裝失敗之后，我查了很多教程，后面發(fā)現(xiàn)自己安裝的scala不對(duì)，這里需要注意的就是kafka是基于scala編寫的，所以想要成功安裝kafka就必須保證scala成功安裝好了。

下載kafka另一個(gè)比較重要的點(diǎn)或者是需要注意的點(diǎn)就是需要下載和安裝二進(jìn)制的文件，這里我的下載鏈接如下：

  
 
 
 
   
  
  
  http://kafka.apache.org/downloads

我下載的是下面的版本:

下載到本地后，直接解壓縮即可，結(jié)果截圖如下所示：

進(jìn)入到當(dāng)前目錄后，打開CMD窗口，執(zhí)行下面的命令：

  
 
 
 
   
  
  
  .\bin\windows\kafka-server-start.bat .\config\server.properties

不出意外，只要前面的環(huán)境條件都滿足了，這里應(yīng)該是可以正常啟動(dòng)的，終端會(huì)輸出一大堆密密麻麻的日志。

到這里kafka就安裝成功了，下面就可以進(jìn)行自己的使用了。

這里簡(jiǎn)單說一下，在編寫程序的時(shí)候遇到了一些問題，報(bào)錯(cuò)如下：

  
 
 
 
   
  
  
  Exception in thread kafka-python-producer-1-network-thread (most likely raised during interpreter sh

解決上面的報(bào)錯(cuò)需要處理兩個(gè)地方，分別如下：

1、修改系統(tǒng)hosts文件

進(jìn)入 C:\Windows\System32\drivers\etc 下以管理者身份打開hosts文件
在后面新增一行內(nèi)容 127.0.0.1 localhost
保存退出

2、修改kafka對(duì)應(yīng)的配置文件

進(jìn)入到 config 文件夾下面
打開 server.properties
在文件第31行 #listeners=PLAINTEXT://:9092 下面加入下面兩行內(nèi)容

  
 
 
 
   
  
  
  advertised.listeners = PLAINTEXT://localhost:9092  
   
  
  
  advertised.listeners = PLAINTEXT://127.0.0.1:9092

保存退出

效果圖如下所示：

處理完上面兩個(gè)部分就可以了，接下來我們基于Python來開發(fā)對(duì)應(yīng)的實(shí)例。

實(shí)例一：

這個(gè)是官方提供的實(shí)例，比較簡(jiǎn)單，主要是編寫對(duì)應(yīng)的生產(chǎn)者和消費(fèi)者，下面是具體的代碼實(shí)現(xiàn)：

生產(chǎn)者代碼：

  
 
 
 
   
  
  
  #!usr/bin/env python  
   
  
  
  #encoding:utf-8  
   
  
  
  from __future__ import division  
   
  
  
  '''  
   
  
  
  __Author__:沂水寒城  
   
  
  
  功能：kafka 學(xué)習(xí)實(shí)例  
   
  
  
  '''  
   
  
  
  from kafka import KafkaConsumer,KafkaProducer  
   
  
  
  producer=KafkaProducer(bootstrap_servers='localhost:9092')  
   
  
  
  msg="HelloWorld".encode('utf-8')  
   
  
  
  print(msg)  
   
  
  
  producer = KafkaProducer(bootstrap_servers='localhost:9092')  
   
  
  
  producer.send('demo',msg,partition=0)  
   
  
  
  producer.close()

消費(fèi)者代碼：

  
 
 
 
   
  
  
  #!usr/bin/env python  
   
  
  
  #encoding:utf-8  
   
  
  
  from __future__ import division  
   
  
  
  '''  
   
  
  
  __Author__:沂水寒城  
   
  
  
  功能：  kafka 消費(fèi)者  
   
  
  
  '''  
   
  
  
  from kafka import KafkaConsumer  
   
  
  
  consumer=KafkaConsumer('demo',bootstrap_servers=['localhost:9092'])  
   
  
  
  for msg in consumer:  
   
  
  
      info="%s:%d:%d: key=%s  value=%s" % (msg.topic, msg.partition, msg.offset, msg.key, msg.value)  
   
  
  
      print info

接下來在終端啟動(dòng)消費(fèi)者，然后執(zhí)行生產(chǎn)者，觀察消費(fèi)者終端的輸出：

可以看到，生產(chǎn)者發(fā)出對(duì)應(yīng)的demo Topic之后，消費(fèi)者消費(fèi)了這個(gè)Topic產(chǎn)生的數(shù)據(jù)，這是一個(gè)比較簡(jiǎn)單的實(shí)例應(yīng)用。

實(shí)例二：

這部分主要是貼合自己的應(yīng)用來構(gòu)建的實(shí)例，這里需要傳輸?shù)氖莏son數(shù)據(jù)對(duì)象，下面是具體的代碼實(shí)現(xiàn)：

生產(chǎn)者代碼：

  
 
 
 
   
  
  
  #!usr/bin/env python  
   
  
  
  #encoding:utf-8  
   
  
  
  from __future__ import division  
   
  
  
  '''  
   
  
  
  __Author__:沂水寒城  
   
  
  
  功能：kafka 學(xué)習(xí)實(shí)例  
   
  
  
  '''  
   
  
  
  import json  
   
  
  
  import base64  
   
  
  
  import datetime  
   
  
  
  from kafka import KafkaProducer  
   
  
  
  TS=str(datetime.datetime.now().strftime('%Y%m%d%H%M%S'))  
   
  
  
  files = {  
   
  
  
          "name": TS,  
   
  
  
          "data": base64.b64encode(open('demo.png', "rb").read())  
   
  
  
          }  
   
  
  
  producer = KafkaProducer(  
   
  
  
                              value_serializer=lambda v: json.dumps(v).encode('utf-8'),  
   
  
  
                              bootstrap_servers='localhost:9092'  
   
  
  
                           ) 
   
  
  
  for i in range(3):  
   
  
  
      print 'i: ', files  
   
  
  
      producer.send('D', files)  
   
  
  
  producer.close()

消費(fèi)者代碼：

  
 
 
 
   
  
  
  #!usr/bin/env python  
   
  
  
  #encoding:utf-8  
   
  
  
  from __future__ import division  
   
  
  
  '''  
   
  
  
  __Author__:沂水寒城  
   
  
  
  功能：  kafka 消費(fèi)者  
   
  
  
  '''  
   
  
  
  import sys  
   
  
  
  import json  
   
  
  
  from kafka import KafkaConsumer  
   
  
  
  KAFKA_TOPIC = 'D'  
   
  
  
  KAFKA_BROKERS = 'localhost:9092'  
   
  
  
  consumer = KafkaConsumer(bootstrap_servers=KAFKA_BROKERS,auto_offset_reset='earliest')  
   
  
  
  consumer.subscribe([KAFKA_TOPIC])  
   
  
  
  try:  
   
  
  
      for message in consumer:  
   
  
  
          print(message.value)  
   
  
  
  except KeyboardInterrupt:  
   
  
  
      sys.exit()

接下來在終端啟動(dòng)消費(fèi)者，然后執(zhí)行生產(chǎn)者，生產(chǎn)者的輸出如下：

  
 
 
 
   
  
  
  i:  {'data': '/9j/4AAQSkZJRgABAQEAYABgAAD/2wBDAAgGBgcGBQgHBwcJCQgKDBQNDAsLDBkSEw8UHRofHh0aHBwgJC4nICIsIxwcKDcpLDAxNDQ0Hyc5PTgyPC4zNDL/2wBDAQkJCQwLDBgNDRgyIRwhMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjL/wAARCAFNAfQDASIAAhEBAxEB/8QAHAAAAgMBAQEBAAAAAAAAAAAAAAECAwQFBgcI/8QARhAAAQQBAgMFBQYEAgkEAgMAAQACAxEEEiEFMUETIlFhcQYUMoGRI0KhscHRFVJicjPhBxZDRFSSovDxJGNzgjRTRbLC/8QAGgEBAQADAQEAAAAAAAAAAAAAAAECAwQFBv/EAC4RAAICAQQCAQMEAQQDAAAAAAABAhEDBBIhMUFRBRMVIhQyYXGBQlKxwZGh8P/aAAwDAQACEQMRAD8A+vIQhZGoEIQgBNJCAaEkIQaEk0A0dUkIBjkmooQpJCSLQDTUbRaAkhK00ICEWhCghCLQAmkgIQaEkIUaEkIA9U9kkWgGkhK0A0kJX9EINJFpIUeyEkWgBCEkINCSEKCEIQAhCEAIQkgGhJCAaEkKAEISQDSQlaAaSLSQDSKElQCEWhLBYhJNQDtCSFQNCSFANCEKgEItCAEIQgGhJCAaEk0AIQkgJItK0WgJWlaVoQDQkUICSLUUICVoUbRaAlaL3StFoBotRKLQDtK0IQAhCSAaEkIBpIQgBCEIAQhJANBSQgBCEIAQhJANJCVqAlaVpWlaAlaVpJIBoSQgHaSEIAQkhACEIVsE07UUWoB2mop2gGmo9U0A0JWi0A0JIQEkKKaAaEkKgaEJKAaEkWgGhCSAaEIQAhCEAIQhAO0JItANJCEAIQhUAhCEAIRaSgGhJCAEIStANCSLQDQkhANJJCAaLUbQgHaEkIAQkhANJCLQAhJCALRaVotANCjeyLQDtK0WkgHaFGwhClqEkKEGhJNANFpIQErRajaaAaLSQqCVo6KNotQEkWlaEA01G0ICSLUbRaAkhRtFoCSFG00A0JWi0A0JIQDQlaLQDQlaEA0JWi1QNCVoUA0rSRugGi0kkA0WkhAFppIQDSSQgGi0kIBpIQgBCVoQDSQlaAaLStIlAO0Wo2i0A7StK0KlGklaEA7RaSEAISQgLLRaihQErTBUbTBQhJCVotANNJCAaEkWgGnaSEA0JIQDQkhANCSEA0JIQDQkhCDtCSEKNCSEBK0WopoB2kkmgBCSaAEJIQDQkhANFpIQDtJK0IBoSQgGkki0A7QlaVoCSSVotAMnZK0rStAStIlJFoUdpJIQDSQhAFoStCAaSLStANJFpWqQaFG0ICy0JIUKStFqKdoB2naihAStO1C07QErpO1C07QhK01C0+qAki1G0WgJIUbTtANFpWi0A0WlaLQDRaXNFoBoQkgHaajaaAaEr3SvZAStFqNotANO1FFoBoSJRaAaErSJQErS6JWlaAlaLVE+RFjROlmkDGNFkkrzWT7fcMgf3Y5ZGDZztgR8ilEtHq7XOy+PcLwpHxT5sQmZ8UTTqeOtUFjb7SNzWA8HwsjPJAPaBvZxN9Xu2+lr5X7dDinBvaeHMy8PGhgyIiT7o4lr7Pfsmu/yN+hWM20uOzZjipPno+uY/tJwrKI0ZbW3/wDsBb+PJdJkjJW6o3te08i0ghfJuGmBuJEzHOthYHNc7ewevquvw3iM3CsxuQ0ufEe7LH/M3xA8QvOh8h+e2a4PRn8d+G6D5PolotU4+TFlwMngkD43CwQrF6adq0eY01wxotJCAEIStANFpIQAi0JIBoSQgGklaLQDtIlJCEsLQkhUAhJCAsRaVotQo0WlaLQEkWki0BJCSLQDQkmgHaErQgGi0kICQKLUbQhCVotJFoB2i0kIB2i0rQgHaLStCAdotJCAdotJCAlaLUbQgHaLWTP4jicLw35edkMggZze89fADmT5BcZvta+Ya8T2a9oMmI/DI3C0B3mNRBQHpLRa8a/25f73Ljy8OPDuxAdIc9/eDT4MZZvcbLXge2WJl4XbviLSyg8Ne3n4tBIJCl80P5PT2kTsfBeM4n/pBw8YFuLHrI+9IaH0Xk5faTj3tJMYMCHIyf6YW0xvqeQ+ay67Jd9H0rP9o+GcOBEuS17x9yPvFeO4t/pJLbZiMbEOQJ7ziqMD/R1xPNIk4zxBuMw84cfvv+buQ/Fex4T7J8E4KQ7EwWGYf7eb7R/1PL5AKX6LXtnz6HD9rPah4kjxpI4Xf7fKdobXle5+QXU4b/oulOV2vGeJtljDwexxmnvjzLuXyC+kXZskk+aFOyql0RYxkUbI42tZGwBrGNFBoHIAdAvPe3HBG8e9l8mED7eD7eEjmHNG4+YsL0SRc0VqIAvqeaNWqLGVOz4n7OylmPDC4nU2xR8/0teitczK4WOF8WymgBjWTu0vcQBV2AtYyYXPc1srCW8+8F4GbFNzbSPocWWEYJNnQ4fxOfhORqhdcTzvGfhPl+xXuOH8Sx+JQdpA7cfGw82nz/dfO9Ub7jLmkkcg4E14rNLxXL4NkQZcTgGROuYk/Ez/AD5LdpdRPHJQl0aNXp4ZYucez6xaFwfZ/wBq8H2gjk7MthnjfoMLpASb3BHja7tr2U01aPFlBxdSGlaLStUg0JWkhB2i0kILHaVpIQDSQhACEkIAQhJANCVoVBK0JIUA7TUbTtANFpIQEgU1BNAStFqNp2gJWhRtFoCSErRe6AaajaLQDtNRtCAlaFFCAklaLStASQo2hASQop2gGhK0rpAStYOLcWg4RhunmD5HgEshjFvefLwHmsHFePxYsMrWhzRRHa69JHm0cyV5P3trpZJWwiR7hTH5Bc6gefW/yHryWvJljjVyZsx4p5HUUbcfCj9pa4v7WTNhiZvh4DJzH2Tf53UQ4uPTrX0WHicvs42YY+PBLbt9U/EJiCP7Q8/isnukJrUwHe+XVVSY0bJGytjYTe5IGw8l50/kL4ij0ofHUrbNEcuJDqbA/Eh1M7M9kwN1N8CQNx6rjxcOyMgzRz8QgiDpbZMXF9NJ37oF8q28QuyGiuv1VZa/tNWoaP5dI/NcsNS4ys656VSjt8f0aeHcF9kMEtkzJcvik/P7SItj+Tf3JXpYva3h0A93xsGZkDB3QxjWN+Q5LxcmdiRM7R88Wgv0Ag33vDbqs0nHsOOJ8jWzSNZIIyWsoavCz6LrWszS/bA5HosMf3TPfO9sY/uYTz/dJ+wVLvbCY/DhRj1e4/oF8/d7SMGjTjlodrbb3cnN6bc72WZnHc3Je1sbWM147pG6Y9R1C+dnlssvrap+EjD6OkXls+iO9rc4/DDA3/6k/qqHe0/FDyfE30iC+aHi+ZPiSvOW/uGNxbYY43s6q+6u/wAAmfLw4iV8hkbI4ESXbRews8/VY5suoxx3ORnhxabJLaonp3e0PFXEH3sgdQ1jRf4LFnZmVnxtZNkS011jvnmsB7UZhe1pLKDTZoev4lbYsbIyTpggllJ/kaSuV6jPLhSOxabBHlxRzcrHkmD36mFx52zmVgkyJYMSSTIa0BxAfYDhXK17OD2Y4nIxznshjNEtbJJuT4bA0vn3F+JZ0WfLw/Pxn4QYdMjI/jHnfUenNbMcMy5kuzCc8MuIvlejqe7DMxWZEMbIcxguGVgHyBrm09R5rQ50XF+Ete5lNlZTmn7p5OHyKq4d9nA0MeJYyLa8dU8IiLOzMXk1594jB8HbO/6h+K0Td3Xg2wjtSvzwzz3Bzk8J9pIMTto8dzsiLTPMTpaQ7Zx8q2rzX6BJ8OS+Je0GCzJ4e/I5Swt1td6L0/sD7ZmcN4LxR+mdndhkeef9J/RevpcqyQvyeNrcTxTrwfRrRaSLXUcgIRaSAaEkIAQlaLQDRaVpWgGSi1G0WgolaiSlaEKO0KKEIWWi1C0IWidoUbRaEolaajYTtASQo2mgGhK0WgJItRTQDRaSEA0JWhAO07UUICVotRtFoCVotRTtAO0WootAStFqNpoALg0EuNAbkry/GeNgRve0yPiBDY4ojvK48h+vkN+oV/Hc9ksToGShsDLM7+hAFkHyHM16dV5bt3z1lOa5peCIWO5sYfvH+p3M+Gw6Lnz51ijZ0afTvNKjJJh9vKZc54yMk2D/ACRj+Vo/dV4jjDNJikOod9l8q8AtpoBYph2oEkbuzljNDbxH4grw5ZZZH+R78cUccVtXRdNkxxM1vc1ouhqcG2pgh7AejgvJZ+Nn5nEGDHHaSRMMji7YANIO/Sui9Hw/JflRdtLG6MyEu0Oddf5LdLBGOLfZpjnnLLsrgcmSccFhDjTdQIH4KPDcySVmSJ4i0MLKkcRz8ApZcZdu2gapcrFwJBmZEkzyGSsEZt1AC7289gpp9lPcNQp/jt9md/Cs8xZ2GzGqN2R2sMjngCwf1B/BXH2enk96a+SFjJ3BwIBLmm79PFenxYJ+IP0YsRmcN7ZuPryXaxfZTKfvkTRwj+VveP7LbCeon+xGqcNNj/ezw+NwCGN7Xvme57Je0GhoaLrlXgtePwLBa6NsWMZHxk6LJcRZtfQsf2Z4dBu9j5nf1u2+gXVhhix26YYmRt8GNAW9aXPPmc6OeWswQ4hCzwuF7LZTg3ssGPHaBQLwG7enNdrH9k27HJynO/piFD6n9l6RK1vhosS5lz/Zzz12WX7eP6MOPwXh2NRZisc4fek7x/Fb+Qrp4JIXVGEYqoqjllOU3cnY15/2p9lcX2kwqcBFmxNPYzgf9LvFp/Dmu+hVpNUyRk4u0fAoZs3gGfJiZkEjNLqkhfsR5j9+RXYy5DkQQZmC4GaK9DjyLSN2u8uXpzX0z2j9nML2jwexyBomYD2M7R3oz+o8QvkGRjcS9kuKvxMuLunci+7K3+Zp/wC/Arzs+nae5Hq6fUqS2s6V5XEoI4H4r4Y3V2sjntIcBvTa534+Cwca4XkEuz42tbMx1ns9rb0PqvQ4WRBlY7ZcdwLD8iD4EdCtJaHAtIsHouBZ5Y52lVHdLBHJCm7s6vsL7ZM4zjNwM6QDOjFNc4/4o/f817a18G4nwnKwM12VgRSPaAXHswSWedBfU/YjjcvHPZ1k07rmieYnu8a5Fe7iyxyxUkfP5cMsU9jPS2hRtFrYa6JJEqNoQtErStK0IAJtCSEAWhJCAaEkIBoStCAdoSQgHaLSQgHaLSQgJWnaii0BO07Vdp2hCdotQtO0FE0KAKLQE7RajaLQEkWo2naAdotK7WXFzG5IyXs3ZFK6MEdaAv8AG0sqi2m/CNiVpXtfii0INCVotAO1RmZAxcSSY82jbzPRXLh8fzRAOWoQN7Ut/mdyY35kj6oDznEZu2kdhkfZ32bz41Tn/iWt+RWZ79by49VAMcxpOvW8dy+jjdud83En5oaXOFvADjzrkvA1uXfkaXSPodFi+njTfbGQsr4dL3SXY00B4LUqMp4bEVyo7H0KHHMPA83LoA5LxjMPlzdX4JYsbnCOKONz5HDuxsbbj8l238Gys12DwuABseJEHZEjvhbI/vH1NdF6rhnCsThUHZ47O8RT5Xbvf6n9OS9b9LKdQfCR4/6uOPdLtt/+jz2H7J5OQA/NnGM0/wCzjpz/AJnkPxXaxfZvhOIQ4YjZXj7851n8dvwXVtFrsx6bHDpHDk1WXJ2wADWhrQA0cgBQHyTSukrW80EkWo2EWgJWlajaC5BRK0WoWhBRK0Wo2hCkrXM43wTC4/gOxMxm3OORvxRu8Qf06roIUavhhOnaPiHEOH8S9jeLdnNTo37sePgmb5eB/Jeiws2LOxmzQk0ebTzafAr3XHOBYXH8A4uWzcWYpW/FG7xH6jqvj+bh8U9j+KCPJaKdu1zd45m+IPj+S8zVaW+UetpdV4Z64ZLsWWOeOQsmYdUZHO/28fJdkmSx7QcHiAmA05+E3lIB1H9Q5g9QvN4OdBxDHEsRBrm082ldPh3EX8Pze2ja8t+GRvR7fLzHRc2lzPDPbLo6dVhWeG6Pf/J7XBz8fiWHHl4sgfFILB8PEHwIWi15fIaeCTnjXDR2vDMin5cDB8P/ALrB+YXo4J4sqBk8MjZIpGhzXNOxC9xOzwWqZai0kKkHaSLStANFpWlaAlaVpWi0A7StK0rQErQooQE0WvMt9u+CE06TIafOE/oVY3234Af99c31hd+ylotM9FeyFxB7W8BP/wDJxD1Dh+itZ7TcEk+HieP8yR+iWSmdZNc5vHeEu+HieIa/90K1vFeHPNNz8Un/AOZv7q2i8mxUzZcME0ML31JMaY0cz5+iTczFf8OVA70laf1XPn4fE/jMGezJibpIL2l96um2+yjfHBswxg2/qOlT/wDPg66FFrg74XA+htSo+B+ipqC0FwHVZOJcQi4XgyZc9lrKAaObidgF4HO/0gZDcjR2TmNIuN0cQc0HzvohLPo3bs1hoN3urA4HkvmvDeP8U4lDlzRz4zpcZgl7HsC0PHUatWx2Xu+FZLMrChnjLjHIxrm6ue4B/VCnQtFqNoQErRaimgORx/izsDGEUViaUGn1s0dd/FU+zzm4vs3LPICGapZSfFoHMfRdXNw4OIYxx8hpLCQdjRBHUHoubnZkDMLieE1zWmPFfpYGFtDQa3Ox+S1tVO2zteeH6T6MY/ldt/8ABZAONZOPFkDOw4BIwPEPupeGgiwNWoEn5KzRx9v+88Lk/ugkb+TirOH5UJ4XjHWDUEfwn+gLHN7RcM4eY4MjKZEdPd7V+7gNr81luOKqNHacebzx+Fyf2zyt/NpR73xlvxcJx3f/AB5w/VgVUftNwqX4M7Hd6SBaWcXw5N2zNPoQU3IUVu4nxCNpdLwOfS0WSzKidt9QvD8Q4ll5E0hnjkY8090b9juaZprY/ePlpXteI58cuMIYZBrleGEn7o6leGkkjyuNe9afihLmA9GWBGP+Xf8A+y1Z5qONyNuCG/IolzbEbQdiBVBP8E629EL5tu3Z9OlSoFPh+O3M4xBHJ/gRntZT0DWjUfypRYx8srY42lz3mmtHUr0cPDmYcIwmEGWZzYZHjqT35PkGgD5+a7NFgeSab6Rx63OsUKXbOzw1rhhNkkFSTEzP9Xb/AJUPktVpE+VeSVr3z58laLSQgHaLSQgGi1FFoBoSQgHaLSStANFpWi0A7QlaLQDWHi3CcPjXD34WdFrjduCPiY7+Zp6FbbWPiHFsDhcD5c3KiiDW6tJcNTvRvMqOvJU3fB8b4vwbinsZxUEuD4Hn7KYCmSjwPgfJd3h/FoM+Fr2uDXcnMPNp/Za+If6ReD8UxMnCzOD5EkD9mB0jd/A/0n0XzyB02HMMjGlLZWi6cNj5Lhz6eOTo9DBqJQ7PrvA+Jtw5xizuHu0xppcdmOP6FZ5uLYnshxp8Ec4k4ZK4mSBnediyHfYeB8Oi+eT8YfnZGOWOEFNIfqNgE86KlxPHzsbFjkgkfqcSX00Gj0rr4rLTycIqEnyYaiKySc4Lg+ss9sOEyZEELJJS6aqJZWm+V7ru2vjfsPwyTK9pMWXMkc9jSX6DtZAtp9L6L7Fa7E7OFqnRK0rStCoHaLSSQDQkhANK0JdEAWhRtCA+DOneTZaQfFSbkOA+HY87HMLqQGh3Te33gjQ/QWO+K9tui596OnYcoZLm0wDa9gFZ20g1U0sN8ndF0tDtLi6AO08thsqJXtksRQMJuvhuwm+ybKMzMkgbtsfVS95GxLfKzum9nauJaxsYH9NpiDWwd3UDvtyS0KYHKho6WAeOynDmQb6m6fNVCCIOp8W5GxaU5MaMNsDcHfvdFeBybY8uJm8Urwf6TRSdxZ8RPZZeQCR0kd+6x+6Rt3Gsi+hPJL3SHVRD+XPV1RUics2y8dnycU48+ZkPY/dwe8kAjkQFyS+VwLe0HzWr3aBuzg6+Y7yYxI9LtG9b7nkst6Mdns08I4qeFRTBkLJXTCnufzqtgu9w32yzcDh+LjtggLI4msBcDuAOpvmvLMDwRVBpHhS2cKOHHKx3EYJJcbSWODHU5p6Eengo5UrCjbPVj2+zW7+64rrP3S791pxf9IYIPveBQ6Oik2Hra8txbhYwZYZYJu3w52l0chFH0Pmuc1lvq632HO0U2+UXYvJ9Ii9u+HSOowTM2uyQrpPbfhMcbnXIXAEhtAX8180dG6OybaeXI/sqJ3MLNAc0l9N5G9yqpMjgj17/AGr4gcDGna1/vU0wjk7ScvibsTbWitPMDr+qoyMziWdgzmfOGkRkOa2EDUAORK5r26cfhrNrcXTH5uIH4NXQk7vCp3f+24/gslzyaJunSPScE7Vns/E6aZ8jnkkF5um7AAeWy8N7ZwSZ/tG2GNod2GK0m/6nFe+xm9jwnBiPMQMv1IteI4hMw+1vEy9wGhsUY3/ptRGTPHZfDMiIEnHNNFkgclzHMmxzdys62CQvb8ScxmFM4vPwnY+ax8Bnj4jM/tYnNhx2B8hO4I6D1JVsxUmnweh4PjTYfAcWCeWQzSMMkpe4ktMgO3/1jDj6kLQ3fiDHEBrnxOdQ6DUKHyGy0sDpMNskh774y5w83vAA+TY6WayeKs/+Bx/6gvN1mS/wXpnr6LHX5v2jV0r8EiqpZHRua1gD5JNmhxoCud+S4vFuJ5GOW4dRdtM2rhebYPHcdd152LBLI0o+T0smeONNy8Hs8aaPg3AX8cIjmmfTMZhOxJNfofkFyvZTj2RP7UR42dmOkbIyQxh4/wBo6jselgUuTnytZ7LcM4bFHD2TZHz6oshxeHcjqBArd34Lpf6PeFskyncVkk7Us1NYHN3jdy5+NX8qX0GHHHHBRifO5ssss3KR9JtO1C9kWtxqJE0oPlYytTgBdbqMklNd5BVSShtWN3A0gNQNotUxu2ABJA6lWWgJWlaz5OZj4jGuyJmRBxoFx5lVycRxWaD7zBpPMmQbCuaA2Wi1nOZjDH7f3iPsf59QpTM0bQwmRoD/AIST8XogLbRaobkwOeWNmjLwaLQ4Xfgp9ozbvt3FjfmgJ2i1Frg4AtIIPIgotAStFqNoQGLjOc7h3BM3MYLfDC5zQf5qofivhORlT52XLlZczp55HW97uZK+h/6TuMugxIOENjNZFTOk1DcNJGmvWja+YtffLYHna05HbN+NUi8sDhsDaccgHdfZI6JMeWnfcFWAsktrqafMrUbSh0ba1150Fth4nM/JbLJMTIABuKAH7rL2Qa7vAk81AiN4J0nSPLdP5H8H0HC9p8PI9qcTiOXOMcNxxHMXXWoNI2rne31XucDjvDeJzOhw8kSSNbqLdJG3zXwuAjtQ4bgC234r1Pse4/604J1EEucD590rfBvyc00lyj62hR1JErYYE7StQtFoCRKNShaEBK0rNpJWgJWhRtCA+Q4r3OZTGtcDz1Cj/mryMtrSWdmD4Bv+agYuy0Oht4I1CjzC140UhIe9tvPI8q8lw2dtGNzMp9P7SO3cw1h3UzFJFGCAwk8wNv8Av0W5+PK7Z0bdPIVtSgcORptoZ+KbmKRyjjzSObTnizz2+icuPKwFtAO6m+i2SwZVF0bdLrurv9Flmx8lxaXvLZHHr/3yVTZHRXC2pg0g1/ULCtdCycuYyINAA06RV781c6IsaztZNLxvqGycUsUsjTZDOTXN+87zRtkVFZiZ2bSRvyJUmwk6Q0anuNADku9F7K5UmntsiDHiIGoWXPr0AofVdRvBYWyEuzvswAGRti2YB4WtM86izfDC5Js8s72c1Pt2fEwXelrS6lpZwLCjI1ZE7njnpY1v7r0zOGYTHWZp314ABNuBgE0GznxJfX6KT1uOLSjyWGjyNPdweb/hXDBdxTv/ALpq/ILGyPFgxsg+6RueyZ7Wl9mhew5r2PuGBX+A9390h/RUTwcMx9hw7HPjYv8ANH8lhXSJH4/LLtnz3O4nkRZWKxugQMNCKhpB8aXQbnyg6mRxNPi2MBd6b+GPzg08GxZAWAbxDu7ndaRFwzSB/CsYAbUG0r9yxL/Sx9szPyeZdxHII+5/yBZs3iubBiufG8AjwaNl60QcJfdcMh28CR+qqnweCTERS8MaQ6zQkeOXoVkvksPpmD+Mz+0edx8p2cIsiV4trfvHp0H4ldLJeP4NOWmx2TtwbXRZwvgccbmN4e9rXcwJnfuoSYHBsfEeGY04Y0F2gzEg+N/RPuWHxZPtea+aO4H3BB5QsH/SF8j9q5nf61cQaHaftQLPTujdfVI5sGNjY2mYhvw6nkkfMrz+T7Lez+RkTZcvvUjnan6HTd3Vz51f4rGPyOLyZy+Ny+DxPGOJQPw3Y8ZEjqbb2nY+K9Dwrh5w8LEw2tp7wMjIvq8mmN+S6X+pns0/JhyY5cyNrad2WsOa4897FrtQ8N4dFkyZHvk7nvN24N2NUPp0Uya/E4VF8lxaDJGdyXByZMxsc/YNBLC5rWV1a0aGn5nW70IUXBruLRgix2BP/UF1HcE4URK1s5DXu1BtUGeFAFA4RjDK94/iJLg3TXZiqvlzXHmz45y3L1R24MOTHFRfuzj8TzI8CWHIl3DWSU3+Z1CgvI4mUX8SGZlU98soab5W79AF1/a6R3vXu9gxx1po8wd7+a4mRiP9xw3NvU6TWfK6r8l6OjxKONSfbR5utzuWVx8JnUyXkCVzQNTnaGhvlt+dr23sPmQwzZfDQQ11MexrjetwbpeR5bAryHDsb3rikEANtj77l0c/Gk4blYuVjPLJNRbY6HmPyK6nNRaic0Y7k5H1a6buQuZx3ib+GYbXxNa6V79LQ7lysrhcL9r2TZDYc+PsXOcNLm2WE+HiCq/abOblSQ9mSWRhwrz8fRbItM1zTSPSS5L5MTWNIDmBzaN3YCJJX9pEGNJbpJ8+QXAxuJ4v8MbjumAnjjr/ACC1fxXHEsbW5DaaCC6jQ2Cos70MnctXhwJpcWDiWNTwZm6dyCLoq08Uwu0N5TQCKsXY/BQHmeL5+Rm5U5msQx32bAKoHYH5rj2GtBBvyIWvMBkbJM+ZxeXbB7t3N6fNYucZod4bn0WaNL7L4ZQH71pBvQTQK1NyNUXZAy6wbYNezB5LLjwu7XvBg5C3HlYtam4hIe8va553ppCFVlUb2R999itxtz/zVTsmZ72uMrjpGltm6Hgt82LPD2/ZaZGuZp3bZDfEee3RYsaB8jtNFpPwnluioc9Hf9lMyZ2U/Gc8mPQX6fA7L1mpeT4PgOw8lmRraHEVorejzvzXppJRFGXHoLpYszjdclpduFi4nxWHhcAklDnF1hrW9aVY4nC97auupK8p/pIzHRcPxI4jTnudbq5NroVHwjNK3R8+9oOKScX4vPmTuL9Z0tHQAcgFzy+gO6Aa2B5pyENiBHIm91mkcBpFgHnfitHZ09GlriSengrS3U0F3x+XIrHG4BwBKk6Ug96iByUaLZrZKWuDXchyvorY4u1mGhwr73oqIW9rEZXuDI7qyOZ8ldizCGehZYdtXLZRLkrfBdkDsmte2hp2DSu/7Jax7R8PlkAH2m17VYIXm35Ha5DT9y/qF6HhkwgzMeTVWiRpv5hbV3Zzy6o+vAotc6Hi+LPIWx3XMmqWmTLhiFueBtdLaazRaVrEOJwknUdLehKi3iuO5+m3AeJCA3oWVufjvdpbJvdciocQfNHBqiBBHPogNqRNLy/8RmicRHK9rCd9RsrHk8QnlY9j5XGLmfMBWiHqncRxGuo5DL9UL5g72rxRXZwOc3xDh+yFr+pEz2S9G6XGa5oMb3EDfSTQ8wrIog4hpOnvWN+SjFIQ6rBB8t1NzacRXTkuM7DW6Ds4xI1xsi+dqLJNZ3II5FUBxAIF1SQaQ4EDfrsnALy8hn2jAHHYHmFny4BkxDRQkadr6hXblhAvfoqaLX2Bd+CEIua33bRKx2oDu2eR/IqXC4HanOmLSWDWAG8jyG/qVbqBbR5rXw+ITMfG06XSPaLI6bkrDLKoM2YY3NGh3FZnNYGPhHeDQDZJG1/+U8HNmyJ5Q6SOSNoBBjaQASeV9dlNvBGRnfMncS0g8havxcBuMwt7aR4PLXWy4s04baXZ24oz3W+iZcpB9MvkXH8FLsGV8R+qzySN1934RsFwNnalZdrpc3Lk1yLQZKaVjdu4rCzdGNGVt++u/wDiH/8AYqvN4h7qGtYAZDvR+6PNWXpzXkjYRC/qVxM6URRzZk+4aNRHj4D8gujDBTlyac03GPBLJ9oXYob20rGFwtrWR6jXj5BYZPa+r09u75NaP1XOxuAcV41jniMfYuErn1qkokt5gCtgOij/AKscTMDJmjGdG4sFjIb3S7lfgvahocSXKPEnr8l8M1u9r8r7kbv/ALS/sF2uFcQyuJ8JysjIa1rRbWaSTdDe7Xj8/hGbw10DciNt5AJiLHh4dRrmPNexjycDh2Kzg3bj3tsVFmk7kizvVLn1mLHjilCPP/R1aLNkySbnLj/s7l81CU/ZSf2H8kXuVGX/AAJN/uH8l4/k9gnE2oWf2j8lMA80mf4bB/SPyT1AbBY2BG3fIp0ldWi6pUHl/auBpycZ5Olsg0OPhRu/oVhE7nymEspgOoO8hyA/Bek48yR3DHOhdI2RhBBjFu8F5xuQ6OCVs0DJNXcY6Rpa5p8QRXXoQvoNBkUsKXo+a+Rw7c7fhnT4CxxbkZBYae4BrjyIHgutnzRycP7UOaXwvZJXiAd/wJWXgk+JHweAdrr3fRaL2DjShxLOxm4sjImF75GkVVBvmT81tkt0zCNQgX52FE9j+zIbYthBWeHJdIwtlYNQ5lOEdtw7HnaebAHAb0f+wqaL8cStAJBonoVcctjJkipo0tawkuBr1Vobr5PP0VUMzNIt2nr6LS1ttGlwPUEHkF0Kd9HM8e3sg7WwCmnfkhjpIzrAc0+SkTqqnF3S7SYae4aiBRI3vdGyxhudIg5va70R8lUGsDgA51k+G66UX2wpppukEBorbx+arkxXggjulxq65LW8yTo6Y6K1bZn0CP7rvHdM7DZvPxSkyHRPDXtIcAbBUsebtiDtuXNsjb1WxSbVmnJi2T2LkrM8wJ0lw2qgUmGQitNdfktDma3Fgc3UOe4Sf3Y6Gwut+ZV3X0YvG4v8kJmRK1+tjnBzfvA8lY7OzXnUZZDq527mqmMYHadXd6n9FcZYq3oV49FHIKJW6TI6vcAPNcD2iGRPE0nW+uVusb+q6+VPO+J/u7I9Q+FshOn5kLm5mQ2443tDr57E/RYvlcmUUk7R4zIkdCXxTRvjffIiljLrjDS7vDqurxnEjg4gWlz3MqxZs14WtXBsDDzMWRuTjtJBNPsgi+VeiiSK2zgOkL6dyc081pgyIXFzcp0rWkd3swDv52u/L7HQuOrHy3tHRsrNV/SkD2QgDAH5Umsj7kYr8VaRNzOHHkRiN8RyS1t6mDTbSfPqFoije8aWHUDvbTsuhlezHDcKJkmTxJ8QcaFgG/ILo43sjjRW+LiOQNPxBumlGkZKTOO3HlYQ0x6h5OXbwR207Q+PSI6ku7G3L8VKbhcUQGnJldWxL2i/wV8TocLFt3dBNueDZd4bIkkR2zpw5ssffDgxx5gbqc/GpmRGSSfZo5aRfovN5fEnykCDtGNveqs/PosLHP3MzBtyJdusZZfRlHF7O3/rLO6d7zFIGVQ1O3Py6LBl8Tzs1rmOypNFWGMdpvy2WUmzTG2L+8VcH6G6rA9AtTySZtUIrwUvy8sESzy5Bcyi2nk0ei6GFxzNie6SSfIMjtnana2uroQSsDnEOsEBv/fJIPDzTBY8a2U3Mu1Ps6WT7Q5szC3utvqxtE/PosAyMh4e900m537xUdtwBt41zQbAAHMdEc2+2FFLoqp8YDY2Na3oGtQp9swbF8l/0tFfihS2KR6V73CwSGk711Ci2Qu1HcGtiXdfBbfdnlupzu6eekDkkcUgEBxII6bboDG0yAja9v5lNzZWV368Kcrw3SKJbZ33HMK8PjAOwaCPu72gM7Z3tYN9xzBNole4vaQSWnfY0tPYRSNPffprcNdsqm4+hxIleQfO6/BSgEYfqLtIvkCDz9VeJWwM79Ns38W34qYgBApw35Us+biSSY4ZCLdqsm6passVKNPo24ZuMrXZZ/FcZgBMzRfLvj90o+NYkjowzIY50hpg7Qd4+A3XnP4RnxyMdocaIsCQWP8ANZ8bhHE48jFfJj22N47WnjvN1NIr0r8FxS0+H/eehHUZuE4HuBO9x3aW+tKqabIb3mR2z+Ygm/olqJJVbuIvxCQzXXUg0F5y76PThV9WaA+Ut740lJ577gOVqr3h0/edqvzVobYUsxMsguaTzjaPxK857VSdjhQRkCny25viGjl+K9Id8iRp2pjeXqVmyOHxZTdE+mUDkJGAhdWDIsc1KXg5tRjeTG4x7Z4fB9o+JcNxfdsaSJsYLiLiaXDVsd1qPtnxdxg1OxyYHNdHcA2IFBdmX2WwpQXGLsj/AO3IR+G6xS+xxpzYcl7R1D2gg/RezH5DC+3R4svj8y6Vj4TlZXtJx2HKzRGW4bNVsbQJJ26nrv8AJdzM4Rivy38RPaduBdau7dVy9EuBcKHCcExOcHyvcXPcBt5D6Lfkf/jSDxH6rytTqnPM3F8dHrabSqGFRkueyZHeKjMax5f7HfkpO2d81CffGm/sd+S5PJ2+C4E6GjyCYSaO6PQJrFv0Shkkpbp9EabI2URQJ3YRsdQVpJPM36qp22n+4KVq2SrF2UfIRsA8A0Kh/DsR0mt2OzVd2LFrSCnstkc049SZrlhxy/dFHGOJJjTuGO+NrNdgOvu36dOqocZ3TTY8pYH7OLmcnCyF18mNtTOobs036mlkyWBmfhyjute10J9asfkvcw5d8Ezw82JQkyvGhLGUXh3j3OX1UjAYTqY5wBG7RyPyVkkZLD2bjuKvqFLHjkMJa5wdXI1zWxNmml0xNc9zeRHoNkmQau+HfCfGlpYNHdu73FLNNLJG4sion05rL6kibIp2UuxoRI55k5nlZNeQVXuT2/A6UC7sOpbGttjHllB3zorcMdsTCTkRveKGht2L2WueoWP9zKse7pHAexpl7N5eC7k9zrB8ldE+SFvYgOa076SbFrp52NjuYTHkRTGwHBoO3napmxIGQF0eUJJGbFug+NHdY/q4tJX2ZfRad0ZBJIx+vSfIFWD7QB2ob+PitOPiMlxRK+RzQXFtAeFfupx4UEZfU0h10aI5L0cOk1E4KUI8P+jg1HyGmhNwyz5X9mN5bGO8TR8Em6HN1d5w6gH81py8Zhha4PJJNAuWR2phaWgN2pwO+y0ZVkxS2T7N+GWLNBTx8oT5GhgppG9Ak7WvLvbnOz9T5g5gfVX06bLv5UgdG+OpGb2dINgj81wsjIOJlP7UjvtvY7rBSbNu1Lo5uQ4yZMjR3gDQL+dLscGYDFG4Ci7d1D8F5qSR0sjpG90XYs2V6TgOVjuiEb5C17bJB6+nifJZvhGC5Z3O1a06SyiDRsrkcb4+/FZ7vjgDI2OrRYa359VzM3jE2ZKXR3E3kB5fuuaW3Kbs0bJPVVSsmwedn5nFHRHKeHdk2mBrKG/PkrmZGXO9gdkSWwU0tOnl6c0MjBdTyBY2Hir2aG2wFok8BzWLmZKBeM6csMT8l5eeWmrCZGgB7nG/5nbkqkQMjOottx3vqpR1kPdIPgGw1bLW3ZsSoZfNNI3SHiMcyTRWjax4BRaAbA6ndWEBjCSa/ZY2ZIVhosjr0TJ1MDj3R5qLO/Tzek8hSbiDz5eiAVavmpBmgEDw6IYbPyS7TfZu4QDIa2h18yoPLAwjWKHxJdqzUQHW/rXRUtbrfYbZG4PmgLA0AcqQk4BprVfmd0KkPoToi00By5hVuNAWC29q8FtOTHGQH6rAsX94eH+SqfLC8lzSHfeojcIY2ZC5riGkizytVugFkAtsb0aVryJX6ms0nr03TEbXNb2jhqFfEOqAoERYbo3XMKVuIJNm+RHRaGxNO7XkHpR5qiWGZriabd7c9lATDjQ793sBSrmyGxxEh+je7BoKTW7ntY3UOoJU9ERBA0+ba/NYyW5UzOEnFpoxjiBd8OTXpJaYz5OmQ4n+5WHh2A4kvxIe9ztgVT+A8NnhdHHEI3Hk+NxDm/iuSekT6Z3R1zXaJnMc+g6Uu9TasbkjSWuYx7T/ADC1ym+ybY2AHieW5w5kBoB+Sg72cyA4mPikzW+DowSPxWh6GV/jI3x+QiuaOuZ7GzQ0eAV4ma2HUTyXDbwHijG3HxZhcDykhIFfIqpvCeP9q9j8zGDW0Q8l3evn9FgtBO7tFevxnaii97yXP95fBTWCmsa6zv4+CnPiyQvLffJq8TEwX6Lj/wAF43RIz8U3saa9H8K42SB77DuaNRPNLJ6PNutNURa3FXNnTMTwR/6yTfb4Gfsn2LwR/wCskN/0M/Zc4cE41Y1Z+OAfCJ136KnJwczEc0ZXGceIOaXBzoyLrnzKy/SZf4H63D/J2ewef97k/wCVn7JPxy9ha7KkLTz2YP0XPx+Fyvbqk4s6QOrSYmtHPlzJteb49mcV4NnGMy3jvJML3EEuArmBySOiyt0q/wDv8CWuwpc2e37N3/EO+jf2SfBrjcx2Q+nAg7N5fRfM/wDWbP8A/wBo+il/rFxBx/xx8wsl8dn9ow+44P5PpgjdX/5Un0b+yNB/4mT/AKf2XzdvHc4xOLp3a/u0NvmoHjvEuk5v+1V/G5vaJ9yw+mfS9B/4mT6t/ZAv/iZPq39l8x/jufR1ZJBvYBqvwc7jHEstuNjS6pHXQcQOXmVPtuXu0PuWH0z6OWNdV5Mho38Tf2U9LP8AiZf+Zv7Lkng7cfDfJPl5UkjIy5xjkABIFnajsvL42dK6XAD8xzu1f9sA7kNQAG3Laykfj8kumiy+RxR7TPe6Wf8AEy/8w/ZB0j/eJf8AmH7LhcExHZeLKcuU9sJ3NA7bTpaOhCqZjSQ+0gwcidz4Htc9lPqxRrfypPt+Rtq1wH8jipOnydrLm0RNa0vmcXAgahe30Sp2Q2ISMLdDg8BxBNgdKPmrHYWHjTaA7ZrKdqfZsnrforY2wNADHsLmkm3Pv5ei6cEPpwo4881kyX4KSSHAAmvRM01pIcRfgealJ7vHJ38uJu10Tag6fhoI15cZJ5EG6PyW9OzQV6jzBP1UXted2OrcHcK/RiEhoymudz0jn8lHVjsaS+SjW9JYoG24Achd0tMuY6Rhj7GBvI6mspxrztZNWMG92R7qog6diVWJ2OfIGvc4+gAH4rRmjGXLXRsxp2jdkZTpmhro4m73bIwLVWRlzzRFjqDRvWgD8VijzYpbbHI99DcGthfNWiZzm2yLevvH9FjsgnwujKnSs6fCZ2xYjnvi7SpXDSfMDdbxnRdmR7oQe11ggDld1yXmyZ3wkNa1tO3og/dCjDFI1h7sZfV6nX+C93B8hDFjUHG6/k8HUfGZM2VzjNK/4s6nGsntoo5Gx6AHU5pHPZcX3hj9XZG9vhOxC0MEjo5dXZ6tTR3t/H90nRFjrfLERtQ01S5NTmjlnuSo79Lgnhx7JO2Zp5GmPZpaR1teL4vKZp7a4npd/gu/xDKkMzrl+xbsGjYOPiuG+ESPLiCAdwK3WqDpm+S4o5zm6CGgg3+C047JAy7cB4FT7EREd0aidwOgVmK6WR0mqINDTQ3v5LNvgxUVfIjjBxBeb3uvNAicHlt8+QAG3mVv7IBgs2Tz8k/d2O2qhzd5la9xlRjIdGNMbmySci53IK2GMMBDGi+p8SpQ4kUZc9rQ0VvZS++RqLRy0j80syLYmuc2nGx1dX5KZvSGigPyRGSaFgAbUpF7GuqiSOVrEow3u7trz6rBC45WUWFzuzZ3t/v/APha5AZY9LnFrTz0868PJSiLI46j06elbqog5ZRGzW5wYxvMkKAcZN+TTW9KTwA3eiegKiyMi9+vMmwoUkTQppACjqI2B2A+qHOBdt0HNVg2dVoCgRiHtZAT9odz+y0g9nGKcSOlKiRpcLuyeTfBQ7J2NEY2ykucSa6K9josMo1HcnzQubKZi891p890LPaYbj7G58UjdnNsg/EP2VEjRBGdLmuBHLVuuF2mVWn3fJZ/dHpJHoptikDS4wzH0r9Vrsy2nSE8ekAG6G4PModOC3Ygg7c+S48zcprbggaTqoh7wLCqDOIkjUIG+QfYv5JY2nbfK2AN7UdBuFJuc0ja69ei88MfizidU+Kxo33YSSm7E4kW3/Eodv5cc/qECR6b3hjgNt3eHiq3ZEUp0BgO1kk0LXCj4flDX2/Ez3m8mQV9PNRZwg6qHE8wiqvS39SoXad8ODRZaDe25tR7eMAU7QTt4rlRcNij/wB+zCRtekH/AP0rTiRbls+Rv/M1o/VBtOm3MjbsZWEjmSonOiaT97odItc4QljSWTZBcTVChQ9bVboGAt0tm0j4g6iT87ULTOoOIw/ejcBdDcbpniWK3cOLfIgLm+5Yznh7w1xrayNvoqsjHx2xy6Wgt7M6RqPMA/ghWuDy3HvazKzOIk4OVPBjsbpaI5C2z1JC4+RxPic40zcQyngHkZTX5qtkTjEA7Yk1uOa6/DMHFzojrd2cjDTrcAD9V08ROapSOQzNz2fBm5Q9JnfuqcifKy3A5E0sxaKBkcXEeW69eOCcPZv75GfLW0fqoM4Xga+/IxnmZWm/oosi7K8burPL4etko0lzHA6gQSCCOq6mbnZefA2PMc2fSNLHyMBcy/By7buFcLDCO11f2us/JcbJiLXOYdLt6roie52kGtqpnDfjvbI4NaSByKmyGWrIK3lpABbtfOggsdq7rgCdzYWy2a6RmZH3Teq0+zJ3GpWM7V250/RSIlFfD9EslGUxOLgBsD4rVDE+B2tru9VX/wCEwX7anNo391XsadOrVR8gFG2VUmHacQynNjlzJ3D4WgPNf5ro8OxIGZel3dcKa0dS7qscfaGtDqfvWyv0yQgG2lzTtW1/NYST6M012dnEny25ckLnlkzHFul4FnzB62F2XMzWDv6eXJzd/rS8nk5M0zGyPj7OcfC5ria/78F2+Ae0M0rhiZDKeBQLXBuschzNE+SwuRsqJ1PdocwAzxMkfdk0AbSfg5DYjDDLpxnCi13MDwBC15sOZiA9vwySJwANl0e1+hWPD4q2SXso3tyJDyj7eO/lvv6Kpyj0a54seWt/NcmZvCIpA1r3F5aK7wddJjguMCKD2nqAy7WvJzJJNuyMJH3jK3x8FzxxZ9nUWbcyH3zWlqSOlOLNLOHtFBrXaRy1GvyWluGAKDW34uddLmO4o7QXaQQBew/RDOLE7NiYaO5Cx5MvxOp/DW3rqBzvEuoqMfDYYyXtjga83ZEllYP4zQ/wHeZ0BM8WF7Nr0CjjZU0joNxY2E0IQCKOyk2JoujFXQBi544uB0sevNVt4yH6Qfs3kWWnevmpsLuOrGGxNc0Fgt13pT1tvYArk/xV5H+I2vHTyWaPjQnJ1SujFWCQN1ntZipJHeEmku32cbsBcjiPFzGahmIYObhsSfI+C5GVxeaRuhpdZ5kdFkii1sc9z9R6+aqj7MXL0Z8mYvla8k1ZNXQ+aQBmkNHzujanLV7m6O1KIaHg6iQPAFbEzAiG63FztgOYIVjHs1U3bck0fxSYwOGkDujk0KbnNxCDoDnnbc0o+QjS0lsLdXIcrCoM9uJFhpFC1QcqWZ9Gm/0np+KmNTmjVWk7m7BP7JQGHskcdZJIOzQfzU4mGgTsedqpgc1oJA3OzWbfVXgua0F3KuQCAfdY6viBNjzU42hvMCz4BJzwH7mm9Cdr8kg8PNA0fFQoi1rnFxIcbqrQGl1araGi69EGPSQRGdPNzq5KmYPkPdLm14HZAaNPbPoG6O9KEzm7NbyHh1VcObDhRObJJbyaAO5Py8FQGuklEz5dIskNI5n0SuRfBpBNEWLvp0QTpNfW/wAlW0Wfs3DRzLgLtS1l9vDSQOpCAG6pNRe0b7bDoqxBpqnkjz3pTiBDxqfbnbAdVYA0y0+YahtQsb+qXROyoQj7u462hN04je5pabvpKAELKmODW/2hcGUS4TXVXYPzSb7QGFmidj3yEW1zTt8wuW+KnkkgA9VCVpLyCKNbbWrtiLkdp/G3ueGMx2A1eouJH0VbvaCZwawMijJ5vaSf/C5Jma2TUPjYOazOmlje1vcc0uvUR+BTYhvZ2JuPcQDnABlN21BvNUv47xGSmCSh1c0ALLLokfrM0Wk77fvaqjdchaxtirJ57qpR9Ebl7Nv8Xz43UJSTXM9EDiWc0UyZxB3OrffxVMbMUMuXLLHu2oAbLO0F8eijJW5ra/VWk/BLfs6L+KZhAMc7yarUd0xxvMjha1uQ+/5iVgjifICJXBlcmc9v2WWXIb9pE06gep6V4KKKfgOTXJ1v41mUAMmWnGtWofkrDxCX3XU7Ilkkc4jTr6eYXnXPDmh97jkpF0khtjH8vi3pZbERZGdyHiDonU6SQEVRDth8lCeR0snatneaB5O3rwXNEchjLpn0Ts1oSExY+27OI0g+A8Apt9Fc+OTXHG2RsDS7S/U4EnnRHgu17NgwTZLXnTYbRL2t5E/zLj8NlZO8tncBIB3b8fPwXZwh2eVI3s4pNTa+1NAb9PNSb8CPs9Ec+KyCYmg7AnIjF/ssWNkAT3JmgMFlt5bKPyG6yufA+qxIPAlziK/HdVNy3id+Np4cYydm6nG/MDkCtcafkzla8Hdmy8V0TmDiLeW15Rbv03AteU4gwOyZD2rX6zqtkhkB2HU7ldmSbswC5uK0nrRcvN8Yy3jJa5jmODr7zGlo6dFnj46MMqvsZidyDTuFDsnCxXJYxlTE957ifAHkqpJ5u0sueG3y8Vt5NVI6LYyDyPLwSewkigfouYWW424+QLjQVbpXxG6Ab0NlKDo6ogfqsNJ25EK5kTwwGj4VS5kOSJmuaYwB1LTRA8loi7SJzJYyT4X18QlvyFFeDoQxP7UDSTRBWmRx3GknfdcLLlfBIYtZ8Q5j+YKjFxnMiaGOeJY+VSC9vXmpTfJE0uDtudqaI38rPxH5q/A7aPikUkYtp2DWP0WD0s+a5DM33luoN09CPAro48o7KNpLK1f7TlRI5rW1zybk2o8Hs5OJcSkfq9w7Rz26XE5Nkj5DyWDGmycLL9/ZiaJ4pBpx5Mq9/ECqr5rLjS48TD9phBzdhomP4LFnY2NPnOyIhhFh0l5c95IPWyNgpH+iy/s9LPxLOme6R2I23myDkdetUuBknTlPEg7MvOosLwa9CtUD+HOimbPkwRu7PVEWlxGoHly5EWufxHIbk5PawSRhgDQdDTvW3Xqp4LZU58TLLpabe29H8VPU4FrNTQXcml3NZHHtNL3aXNHiar0Vc8kcBJcA5ziNg3V+KhbNTZJ2zGOQRnflq/MKBkkEm7QGE7aTYd81ihe5+U57YaJ3DjzAWyLW0BxLiRuB4+SrVBckmS3LqZG7bYC0PyO8OTr2c07AD1VLsyOSbsQwl24PX/wqyT2ZZZbY7oLQTXl+6UDUAyc9xg0fePIH91RJFkSF1viefEkV/kqe0qONpIYGigSe9SrGS2O2B2w+VK16BpjhnLdbnNcb5B1D0CT5nBp7JxcOo0cisuaQGNn0CUDYC+XnSvxnSQs7V8jow8W4HwSuLJ5ohFI3J1NlbpB2BBJryVsYBPQmu6Ca38Uah2bnhzQw7Na5wbt4kc0CpGd6Q0w2SBY+g5qMVZf9myJpaA6R4rUKWSSI03U4NJ3sHZWxMLmulaAWHm7qfVQjgfIyQRkih8b99vCgiKUDJe+YRwEtv4nad1dE5zW08Fzied39VDsg52kOcCTsWM015quOxO+IP1Fm19SSsuGTo6EYppstAAu3D9E+yEga+d7g0bnpam1zICO7uG/ET+Kt04c9as1pf4Hla12zPajG2eEynSXAjZoIu/NKbJZHpbuSXUbG486V080mBEQYGTtJ5huk/Tw81zxma3U/WTdaTuGg9AskvJg2WtyHyyljXu7Ibep8lbJIANBNOPIBDW9Gtq+g3+SBrZKY3R2bsFp5nwKCiOhgDuYeRz2NKYe2Ro0tJDNhbCN1F7nxlpmie2x8I5hNjQGuLgdThyLuXp0tCkKYQ0iaqJ1joD4I96DIy1sUlA7F33/l0UHu+z0hhcG8gDW/p15pRSMLWtsCUmqcbIHghCTH9lTnaQ8ii0/us82WGBzmx63dQ0WtJZHrHaxCQnlbiK9P80OgeIT7ttvdcjXqnFl5SMDIWTsEkpIe4cgLQtsDsmNhBxS4E2KIG3zQs+TGkZhnNDQWvGxq6sHyWZ/EHOmOkXHfLr9V7B3D+FkC4GV5C1FmLgs37CFp3prW3QWCnH0ZOMn5PKRQue98r3RsY/fQ4/jak4kNLY2iQnYBpsFerjbhscQcWJvWzG0fNWh0dgdia6aW8x6AK/UGzwePbgH/AA34oDzuGgbn52ptPYl1Q97YG+dhenMeO7U9ruRqq5HwIIVJwYi3U9rj/cwAf5J9S+xsro8qzFle8ufI2MEncm/xV7cU62gucW9bG34Lu+6zxlo93Y0m/v02lXLG6w3sWNfXidwn1LIsdHHeAxvZiIHf4u8C759VB2Nj1XYZBfyJbs2/QrrCNu7NW48Bv6J+7wsZUbCwEbk2f/CqnRHA52LF2bHui+zsDmRzVjOwY12uWRwds4Nq/qtPYPi+0Yxjj4OZqKxyvfMO80Dr3IwB+Ct2KpEBw1+RGXHK7rtx3Tsofw7smveXNc0CgS0/VWMdKQWjtCB0qlPWR8cf1tW2Y7UUwYUXZdoC8PNijyXSw8uSOFzZZMdjhtqlF2FiZO1urYhrtyPAqwtkcDqjeP7dNfij57IuDaMwMYezmxHAnf7K/wA0fxVv3ZMQTgm3iIb/AC0/quW/U1otslHl3mID5GyuFOtvNplbX+aKNFcrOt/FJCRqzGsb0044Nf8ASuRxjIikyg90zpHBo0nRpP0Wh0jnMo9iL/8AfFrmZcRflOLzvsL1ahy6FZR/kwkVsyYm7HU3rytDsqN4t4JPIDlsj3Q9Aa9FP3PlbT9Fl+JPyKWzRgfmOaTpWGiBVeVrR7lRrSVNmAXchQ80uIqTMrHtaC4ENPorYslrAQHOA50R18QVd7hvvspDhrnC2/gFN0RtkjK97JHauvWwqa7xXSHDJBzKY4e6qoWimhskZsOYMcWOGxI3HRbzO3toWNLbJ5VddbpZH4pbYNj5KMbRC/tHOBq9JBoqNJuzJWltZ6fCbC7DypsigImjToFEuOw28PFc6XJkMzmtdG1riOUR39SsPbw+7vd2r9YIAbr5psmY89m3DldJV7TOJAHkAsVForkjvcPljfmRxzsa6J1g6WgHlt0V8UbXW5pLmEnSXsDXaelgcl5iPIZJIGNhNk18brC9Zw/MdFjMjDYpoWbNY9lgfXdYtUqZknbtB2BBHdYG9dkCAl1NYwtBo2tsAx5IdMonbLd62G21/af3Vw4bPLvjfbjl3PiHq00fpawM/wCzliCNklkDvEUKuk+zBeAYmHmfNbTgzNJa7uOHMOsEfJNmESAHPHnusbRkonO7KPUS7GHiDtss2VhRzlul00TxyLF2jw8k0HivAlTbw4tA723LZNyG08u7hZ127KyHf3RilVJweKaQOfJK6QciG0F7AYNH4C7z8VY3AfWzWt9RdK/UY+mjxg4VJRbFmyNJ3IMZP4ql+BkguJyWyOG7NYIA+q90cDdxd2emvCjazS8HjyMhhlh1M3DnF1Eeg6gqrIRwPFFs/wAL3NY7mRsCfNPVMJLL3AM56Rz+fRewz+DzytBxi1lDSdVglcvKhy8VsMcGMJd6f2UZNV5oppja0YYJonsAMTjISSQ400fNQMUYYB2rmDnbDdrq5GDk47ZSxv2ZZtpsEeN+K4kkuiPSYJQ47HUwgJ30Wkuy9rJHT01+uJvxv5HfxUojGzIdHDjOeX/ea2zXqqsXHkmiMjS5p56SCb81bBMcUkSAkPJJcQQfkqzHjsyzNlPEXMdHKDzaKsDzV0mHI2MObIwNINk8x8ldl8QxW4x7Id7m2j59VzH52zS97QCNgiTfQ4XZpdHII3PZKMjpTdjXgFJuloaNLHkinNLuRWeHtQO1iDuzd1Au/MJunx5NewY921j7x81aZOC12oMaGluqybFUPRKV8kPxhutwoBp5fupYUTX5D3Pc14Y2miuXyTyppBK2LTRPIHdPNAkyE6S0lz3H4dRsUs8ORJIdOkaA4g2NrHktIyo2GwHawBpa1pIvrXirH5GJPG3WxznNNu00PwUHKKS9mrtHscXOG5ftt4BBgyBFrii1uPwt+E+u6240jHU5gFtN6ify8EpOIRRh7nPbY+7ZJKw3O+jNR4Odjx5OrVkRvc57i486b6rUIpsef7aZj2kW1ukCh4uWc8TmzJHllMZGBu3xTklhcTJI/tTXeiYDt81nT8mF+ma5Mhpd3g0+Bu9kLP7rhTAPGWACPhEoAb5boUKepe3CiJ004/qq2G7AjArnsAqBjFxaGwMLhzOnZSGLIxxL7Y09A3Zajd/gTJxOS2CJrnDnRH6qRjcQwPe9tH4Qa/EKQdksFRN7v9pT7LLldZBH9ra/NWiWIiOKPRES3zaKJ+aok3BL3keLgaPzWj3DKLjpeQP6gE24GS29Rb9NvwVVEdmEwgEkSPAPPfmq3QsLficSLO66pwZasbnyeaUfcX6S18Qd13KcDk4OPG33pxeWkOPUc/2XRkbEWdzsw4eCu9zgYzWMfQN9Xe018lm7aJmpoNULBs7D1SxRjdA55PxAHqAf2UnYxc0i+18aBW2PspdLo5mWRycSl7xF2rY5I5DZoOaSG/JLFHO91DzV6TXMO5KR4RMW6g55bXPfZbXYzJAHGE0HfemDQrmdjI5zHO2aNyJNgruJtOMOFRW65dJ6i7KlJwWfKhYyOXut5AgbLr9iHH7KqP3uZKYhkYL7UhpNUG/qm9+B9NHnv9WZ6J7Ybf0qEfs5JLZErgB4sq/ReoE4jc0PjLyfEcvNU5PEHMbUcAoHqKB+aLLMjwwOMPZkxBr3zu6GgButcPDmE6S0h17kkEH/ADXTi4zcdlrrI8Bt+Cxl0sz9cIA3+n4Kb5Psv04rovHBInNsOJcPQ2sM/CZonnso5XNBFF9Bp/FaG5ma0gRNjJFU0ts/PzWhuVxbtGmKWMt/2jXRC78BXT1S2KXg47oXxkRPje033nOIoelKEtOP2TXFjRRPif2Xcnl4q88zGLujDe3hzWP3HLLi9/2hqyOy38qRMpjge8ENdFtewABK1Nx9crnCORt/d2qlBuHmNkY83GL+8yvwV8HCcovMkE0rK2onu+t80AzHGyi6JzRvueQCk2PtQ3swHk+AB2+S6DNccYGX2TnjeyLseaDi48jQ7GaWHfvtHLzWNmVGeLhYkP2sRa0daoO9CUpuF4RcQ7HaBfMjV87XTgxJQ7UXh7SKN9fxWqOOVoP2QAqviu03MbUzjYnCeGyscBCDI3dsgbyA9FNnCWlzp8EFjGinSk7edk/kvU8DGNFxfHmyogyFrt3EbjzNeaftZ7PHG4iMjB+xhnaJGvu2v8dr2W3uG6zTajPbR4cB8UzjJHC6M2HPDd3LpQR484L4jCOtb2qXx5MTyMgs0ctWsBqGcOilsxOAeBWov/YrU2bUkbu1gjB7SJ/d5OaNh5qcOXBKR2UjgWiwDbT67rmNh4ljN0yfawjlyc6z181W8aidL9yebiIyFC2enHEnyRCCaKPIYORlYC4ejuf4q6LCxc0hmMRjzkf4c7hpe7yd09D9V5mKPMa6Nzct0jNjpcbHounG1wIL6b6WVlb88kpeC+WJ8Er4pGCORhpzC3cFLtWg0BfypegyIX5/sycyQtdNiStYXkbmMit/GqG68/Ix2nU010oG1Jw2vgQnuXICXeuVbjYlQ7dxvTZPiOaXeb/f15KRkLa+0onoRSxoysYkkPR4s70VOLtTbnh3pYUo3RkDU+iR4gpn3UbCbfyN0jHIwxxs67vffZQewtsukv1KuZECbDyfU81o7KMt7zb+axXZkzkxgtfppgG9VurOyc8G9B322v8ANdAxtvugjeuYQ6IijZNeOyzMDky8NfMQ7U4AbgtABO3iuXlcDdkNa6YZHedZaatnn6eS9I5zdQt5vVWzXFPtCObvSmkn6K7mibUeWh9lYnA6JZQ0GyK5/I81CT2WIyQz3HtccuDRK6QAm+oF/gvTGHtXh4kdpohzNFWfO90p8SWTFe+ERGUcoy8d76kKqbI4ROL/AKqRRMDTklsDNmgGq8lhd7NYsUJMEfbNILmFrwN/nuvWYEOY/EjORCY5gTqAe3bw6+FKp7JGZFzSMdHyawR07n/NajnIKETxp4Lndm2SOJ0ZF7OG3luFklxcowODYmdsf9oX8hfTwXvHPY7usAIuq1Hc+q42fwqbKy2luayBzxqbCI+9tzo35LJT9hw9Hmm4ubFkNfM2gNmtYbNqDcXH7WR03aW42GtdVnwXt2xzxRNY4Rt0N2d8uqrMGQacyVofpABB06vHx2KLIR4zw7tpOzxw+MPO5INAeqrOM+aJ0Yyo2P30gA279gvcux4omSxywExlttldyB8NisLeF48jizNf7lHIPsiXhwu+RN2NlmpejBp+TzEOIYMYsdDqJBOppq/orMbiPukL5nY9uJ0kxihXS12P4ZhMnezHyRK9jjR18+myc3BT2XcidI4E6mukAAHiFdy8kUGujhO4rjuNuxogeurmhdJ/DMk0IsBwYBt3m7oS4ipHsGs0AB2hoG3L8lD3bW4EuaN73uys2O8yC203vFu+/LqtUuNoEbi5rrG40rnOiyQgZFHZc1g38vzUTkQMYSZgWjwdSkMWOVzTTRQ32u1NsLQCDThfVoSkLMwy4HWSDQ68ypHMaWHR3h1ptrYI2sbYa30pJ0pjFACyeaAxMmlmcWQtksDcFhAVpgyybNj6K2XKljFtIojlSrZkyPO5HyCAjJhSZDA2UAjwI/VUN4HjRk9xoHM2ef4rYyVz26i51eAKmexbbuyJPm5LZODGOG4ZtrhFQ6cgUHEw27tEXr0pamQxSyH7JrTyJA3Vpx4w4bE2DW6cjg4rsPEJ1CMAA2QKb9QkBBITHG0ANFAtaDp8loy3sil0dnZdzcDRWaDIZGWtZG5uoc9fX6JbLwXMx8SF75WM0uoWTISPpdLHnGNtVPtfeYdw3z2W7Ge6RryHFpby3vmoyamSMaSw6rvuBWwcUOHMxkGtudFXMZ2pDjrLKvS0WV2G5L2Ocxwa4ACtqpAynl4u9Lzs26pLJRyYsSUSMeBKAdgwiyETxtZCdbch4cTvR7q7cbzI91kiz0WxkdEt1vOw3Lj4JYZ5uGPBJ1l8rW7AEbkV5WuyySEhrWQzvI0957CPqtxiYzU7Te/oUtUbiAI6sXz/AMkbIiJjxi7V2Ic++dUrA6INAa0kjnQFqGoH7qsDwHABgCwszodsd90gjxCRbE9pDqo8wXc0yGveWlgUJGiNwA3B6K2QkGwhlWD4eCQoDkPQclWBrfpFNBHQK0xCNl2SeSAQeCKDGnx7qZfXIBo8OShH3nc6APILXBBDK7eP1s2rTI3RVAZXyAag1pNDqvacWbjcL9lIsPOa+d027ADVu579RSyezOPA3iMTmxCy6he9Kn2lc6Tjs7JHFwiOlgPQHddcUsePd7OSTeTIovweTfHBMHN7EFvLSW2q28Lxy/W3DYHHntuV05GDWWtJaauwf0Wd0sjaDnk+lBcrOm2QZAANNNaG/Klnm4Zj5BBkYx4G+x3WwEyVuQL8U3saKBs34qcLoy58nNdw1zQTHIQPMdPRS9xlbRbkgC+QZ9VpLi0U2huqJJ3R0aDt63tS2U63Bp5cPKDe2D4nnS+N4trx4EdVkzuCu4LxfKx/e5p4y4PZ2gqmncV9fwWeLKc7TQLTfMFeg4445Xs9wziLz/6hznY73V8QbuCfMcluTcoNejVJbZp+zhgEA2NvG1Bxie06mbjqXLG6d9lpPJVtnkJ5jbfktVM28F+jELqc87dGkKbYsRrqDCPAXShHUjtTmsNf0qdR9IwDfiUsnBpbHE2tJc31KuMbS3/EdaUUMbqa5t+dlBa1jiADsPFa2zMr0hraa/qTRcVS1xieQwve477OsD9lc6FrjZJHoVVIxsQ5WsrBb2stAueG30BHP1UDN2fIEmugslQZokbZZV/ymirjojFhm5rryUANfK/d9gdEpZIjG5r+8DzB/dUzzuAKoY0yaQ4g34jkgssdM95IY2qPgroYZXSAkEt8jzTx4RTnEgkGuXNao2tbsAPojYXJhhOJNxCQQvcciJul7RsOf5rV7pcolcxoeAWhxokDwC0UQTuPoqpHVZpSygIi2wXtczrbASfW1nnEjCXsotqtJYKb5qqfIcKA2JNWFQxxAO5PTms0jFicXuqSR93zDRR/ZUS4+HO8ukjEjSKLXNsX+i1tdWk15LUGN32HjuFbohzYsXEjex0WOIpW/DIxxBafJbow2TIEuWH5Emka3Oe5muhQsg81fHDG8AFgHpa0NxIYwDTiDtROw8+Sy3MxpEWY2AS5zXZcepxOglslehNbIWlkDNKFLY2o/9k=', 'name': '20200326203003'} 
 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2tbMx1ns9rb0PqvQ4WRBlY7ZcdwLD8iD4EdCtJaHAtIsHouBZ5Y52lVHdLBHJCm7s6vsL7ZM4zjNwM6QDOjFNc4/4o/f817a18G4nwnKwM12VgRSPaAXHswSWedBfU/YjjcvHPZ1k07rmieYnu8a5Fe7iyxyxUkfP5cMsU9jPS2hRtFrYa6JJEqNoQtErStK0IAJtCSEAWhJCAaEkIBoStCAdoSQgHaLSQgHaLSQgJWnaii0BO07Vdp2hCdotQtO0FE0KAKLQE7RajaLQEkWo2naAdotK7WXFzG5IyXs3ZFK6MEdaAv8AG0sqi2m/CNiVpXtfii0INCVotAO1RmZAxcSSY82jbzPRXLh8fzRAOWoQN7Ut/mdyY35kj6oDznEZu2kdhkfZ32bz41Tn/iWt+RWZ79by49VAMcxpOvW8dy+jjdud83En5oaXOFvADjzrkvA1uXfkaXSPodFi+njTfbGQsr4dL3SXY00B4LUqMp4bEVyo7H0KHHMPA83LoA5LxjMPlzdX4JYsbnCOKONz5HDuxsbbj8l238Gys12DwuABseJEHZEjvhbI/vH1NdF6rhnCsThUHZ47O8RT5Xbvf6n9OS9b9LKdQfCR4/6uOPdLtt/+jz2H7J5OQA/NnGM0/wCzjpz/AJnkPxXaxfZvhOIQ4YjZXj7851n8dvwXVtFrsx6bHDpHDk1WXJ2wADWhrQA0cgBQHyTSukrW80EkWo2EWgJWlajaC5BRK0WoWhBRK0Wo2hCkrXM43wTC4/gOxMxm3OORvxRu8Qf06roIUavhhOnaPiHEOH8S9jeLdnNTo37sePgmb5eB/Jeiws2LOxmzQk0ebTzafAr3XHOBYXH8A4uWzcWYpW/FG7xH6jqvj+bh8U9j+KCPJaKdu1zd45m+IPj+S8zVaW+UetpdV4Z64ZLsWWOeOQsmYdUZHO/28fJdkmSx7QcHiAmA05+E3lIB1H9Q5g9QvN4OdBxDHEsRBrm082ldPh3EX8Pze2ja8t+GRvR7fLzHRc2lzPDPbLo6dVhWeG6Pf/J7XBz8fiWHHl4sgfFILB8PEHwIWi15fIaeCTnjXDR2vDMin5cDB8P/ALrB+YXo4J4sqBk8MjZIpGhzXNOxC9xOzwWqZai0kKkHaSLStANFpWlaAlaVpWi0A7StK0rQErQooQE0WvMt9u+CE06TIafOE/oVY3234Af99c31hd+ylotM9FeyFxB7W8BP/wDJxD1Dh+itZ7TcEk+HieP8yR+iWSmdZNc5vHeEu+HieIa/90K1vFeHPNNz8Un/AOZv7q2i8mxUzZcME0ML31JMaY0cz5+iTczFf8OVA70laf1XPn4fE/jMGezJibpIL2l96um2+yjfHBswxg2/qOlT/wDPg66FFrg74XA+htSo+B+ipqC0FwHVZOJcQi4XgyZc9lrKAaObidgF4HO/0gZDcjR2TmNIuN0cQc0HzvohLPo3bs1hoN3urA4HkvmvDeP8U4lDlzRz4zpcZgl7HsC0PHUatWx2Xu+FZLMrChnjLjHIxrm6ue4B/VCnQtFqNoQErRaimgORx/izsDGEUViaUGn1s0dd/FU+zzm4vs3LPICGapZSfFoHMfRdXNw4OIYxx8hpLCQdjRBHUHoubnZkDMLieE1zWmPFfpYGFtDQa3Ox+S1tVO2zteeH6T6MY/ldt/8ABZAONZOPFkDOw4BIwPEPupeGgiwNWoEn5KzRx9v+88Lk/ugkb+TirOH5UJ4XjHWDUEfwn+gLHN7RcM4eY4MjKZEdPd7V+7gNr81luOKqNHacebzx+Fyf2zyt/NpR73xlvxcJx3f/AB5w/VgVUftNwqX4M7Hd6SBaWcXw5N2zNPoQU3IUVu4nxCNpdLwOfS0WSzKidt9QvD8Q4ll5E0hnjkY8090b9juaZprY/ePlpXteI58cuMIYZBrleGEn7o6leGkkjyuNe9afihLmA9GWBGP+Xf8A+y1Z5qONyNuCG/IolzbEbQdiBVBP8E629EL5tu3Z9OlSoFPh+O3M4xBHJ/gRntZT0DWjUfypRYx8srY42lz3mmtHUr0cPDmYcIwmEGWZzYZHjqT35PkGgD5+a7NFgeSab6Rx63OsUKXbOzw1rhhNkkFSTEzP9Xb/AJUPktVpE+VeSVr3z58laLSQgHaLSQgGi1FFoBoSQgHaLSStANFpWi0A7QlaLQDWHi3CcPjXD34WdFrjduCPiY7+Zp6FbbWPiHFsDhcD5c3KiiDW6tJcNTvRvMqOvJU3fB8b4vwbinsZxUEuD4Hn7KYCmSjwPgfJd3h/FoM+Fr2uDXcnMPNp/Za+If6ReD8UxMnCzOD5EkD9mB0jd/A/0n0XzyB02HMMjGlLZWi6cNj5Lhz6eOTo9DBqJQ7PrvA+Jtw5xizuHu0xppcdmOP6FZ5uLYnshxp8Ec4k4ZK4mSBnediyHfYeB8Oi+eT8YfnZGOWOEFNIfqNgE86KlxPHzsbFjkgkfqcSX00Gj0rr4rLTycIqEnyYaiKySc4Lg+ss9sOEyZEELJJS6aqJZWm+V7ru2vjfsPwyTK9pMWXMkc9jSX6DtZAtp9L6L7Fa7E7OFqnRK0rStCoHaLSSQDQkhANK0JdEAWhRtCA+DOneTZaQfFSbkOA+HY87HMLqQGh3Te33gjQ/QWO+K9tui596OnYcoZLm0wDa9gFZ20g1U0sN8ndF0tDtLi6AO08thsqJXtksRQMJuvhuwm+ybKMzMkgbtsfVS95GxLfKzum9nauJaxsYH9NpiDWwd3UDvtyS0KYHKho6WAeOynDmQb6m6fNVCCIOp8W5GxaU5MaMNsDcHfvdFeBybY8uJm8Urwf6TRSdxZ8RPZZeQCR0kd+6x+6Rt3Gsi+hPJL3SHVRD+XPV1RUics2y8dnycU48+ZkPY/dwe8kAjkQFyS+VwLe0HzWr3aBuzg6+Y7yYxI9LtG9b7nkst6Mdns08I4qeFRTBkLJXTCnufzqtgu9w32yzcDh+LjtggLI4msBcDuAOpvmvLMDwRVBpHhS2cKOHHKx3EYJJcbSWODHU5p6Eengo5UrCjbPVj2+zW7+64rrP3S791pxf9IYIPveBQ6Oik2Hra8txbhYwZYZYJu3w52l0chFH0Pmuc1lvq632HO0U2+UXYvJ9Ii9u+HSOowTM2uyQrpPbfhMcbnXIXAEhtAX8180dG6OybaeXI/sqJ3MLNAc0l9N5G9yqpMjgj17/AGr4gcDGna1/vU0wjk7ScvibsTbWitPMDr+qoyMziWdgzmfOGkRkOa2EDUAORK5r26cfhrNrcXTH5uIH4NXQk7vCp3f+24/gslzyaJunSPScE7Vns/E6aZ8jnkkF5um7AAeWy8N7ZwSZ/tG2GNod2GK0m/6nFe+xm9jwnBiPMQMv1IteI4hMw+1vEy9wGhsUY3/ptRGTPHZfDMiIEnHNNFkgclzHMmxzdys62CQvb8ScxmFM4vPwnY+ax8Bnj4jM/tYnNhx2B8hO4I6D1JVsxUmnweh4PjTYfAcWCeWQzSMMkpe4ktMgO3/1jDj6kLQ3fiDHEBrnxOdQ6DUKHyGy0sDpMNskh774y5w83vAA+TY6WayeKs/+Bx/6gvN1mS/wXpnr6LHX5v2jV0r8EiqpZHRua1gD5JNmhxoCud+S4vFuJ5GOW4dRdtM2rhebYPHcdd152LBLI0o+T0smeONNy8Hs8aaPg3AX8cIjmmfTMZhOxJNfofkFyvZTj2RP7UR42dmOkbIyQxh4/wBo6jselgUuTnytZ7LcM4bFHD2TZHz6oshxeHcjqBArd34Lpf6PeFskyncVkk7Us1NYHN3jdy5+NX8qX0GHHHHBRifO5ssss3KR9JtO1C9kWtxqJE0oPlYytTgBdbqMklNd5BVSShtWN3A0gNQNotUxu2ABJA6lWWgJWlaz5OZj4jGuyJmRBxoFx5lVycRxWaD7zBpPMmQbCuaA2Wi1nOZjDH7f3iPsf59QpTM0bQwmRoD/AIST8XogLbRaobkwOeWNmjLwaLQ4Xfgp9ozbvt3FjfmgJ2i1Frg4AtIIPIgotAStFqNoQGLjOc7h3BM3MYLfDC5zQf5qofivhORlT52XLlZczp55HW97uZK+h/6TuMugxIOENjNZFTOk1DcNJGmvWja+YtffLYHna05HbN+NUi8sDhsDaccgHdfZI6JMeWnfcFWAsktrqafMrUbSh0ba1150Fth4nM/JbLJMTIABuKAH7rL2Qa7vAk81AiN4J0nSPLdP5H8H0HC9p8PI9qcTiOXOMcNxxHMXXWoNI2rne31XucDjvDeJzOhw8kSSNbqLdJG3zXwuAjtQ4bgC234r1Pse4/604J1EEucD590rfBvyc00lyj62hR1JErYYE7StQtFoCRKNShaEBK0rNpJWgJWhRtCA+Q4r3OZTGtcDz1Cj/mryMtrSWdmD4Bv+agYuy0Oht4I1CjzC140UhIe9tvPI8q8lw2dtGNzMp9P7SO3cw1h3UzFJFGCAwk8wNv8Av0W5+PK7Z0bdPIVtSgcORptoZ+KbmKRyjjzSObTnizz2+icuPKwFtAO6m+i2SwZVF0bdLrurv9Flmx8lxaXvLZHHr/3yVTZHRXC2pg0g1/ULCtdCycuYyINAA06RV781c6IsaztZNLxvqGycUsUsjTZDOTXN+87zRtkVFZiZ2bSRvyJUmwk6Q0anuNADku9F7K5UmntsiDHiIGoWXPr0AofVdRvBYWyEuzvswAGRti2YB4WtM86izfDC5Js8s72c1Pt2fEwXelrS6lpZwLCjI1ZE7njnpY1v7r0zOGYTHWZp314ABNuBgE0GznxJfX6KT1uOLSjyWGjyNPdweb/hXDBdxTv/ALpq/ILGyPFgxsg+6RueyZ7Wl9mhew5r2PuGBX+A9390h/RUTwcMx9hw7HPjYv8ANH8lhXSJH4/LLtnz3O4nkRZWKxugQMNCKhpB8aXQbnyg6mRxNPi2MBd6b+GPzg08GxZAWAbxDu7ndaRFwzSB/CsYAbUG0r9yxL/Sx9szPyeZdxHII+5/yBZs3iubBiufG8AjwaNl60QcJfdcMh28CR+qqnweCTERS8MaQ6zQkeOXoVkvksPpmD+Mz+0edx8p2cIsiV4trfvHp0H4ldLJeP4NOWmx2TtwbXRZwvgccbmN4e9rXcwJnfuoSYHBsfEeGY04Y0F2gzEg+N/RPuWHxZPtea+aO4H3BB5QsH/SF8j9q5nf61cQaHaftQLPTujdfVI5sGNjY2mYhvw6nkkfMrz+T7Lez+RkTZcvvUjnan6HTd3Vz51f4rGPyOLyZy+Ny+DxPGOJQPw3Y8ZEjqbb2nY+K9Dwrh5w8LEw2tp7wMjIvq8mmN+S6X+pns0/JhyY5cyNrad2WsOa4897FrtQ8N4dFkyZHvk7nvN24N2NUPp0Uya/E4VF8lxaDJGdyXByZMxsc/YNBLC5rWV1a0aGn5nW70IUXBruLRgix2BP/UF1HcE4URK1s5DXu1BtUGeFAFA4RjDK94/iJLg3TXZiqvlzXHmz45y3L1R24MOTHFRfuzj8TzI8CWHIl3DWSU3+Z1CgvI4mUX8SGZlU98soab5W79AF1/a6R3vXu9gxx1po8wd7+a4mRiP9xw3NvU6TWfK6r8l6OjxKONSfbR5utzuWVx8JnUyXkCVzQNTnaGhvlt+dr23sPmQwzZfDQQ11MexrjetwbpeR5bAryHDsb3rikEANtj77l0c/Gk4blYuVjPLJNRbY6HmPyK6nNRaic0Y7k5H1a6buQuZx3ib+GYbXxNa6V79LQ7lysrhcL9r2TZDYc+PsXOcNLm2WE+HiCq/abOblSQ9mSWRhwrz8fRbItM1zTSPSS5L5MTWNIDmBzaN3YCJJX9pEGNJbpJ8+QXAxuJ4v8MbjumAnjjr/ACC1fxXHEsbW5DaaCC6jQ2Cos70MnctXhwJpcWDiWNTwZm6dyCLoq08Uwu0N5TQCKsXY/BQHmeL5+Rm5U5msQx32bAKoHYH5rj2GtBBvyIWvMBkbJM+ZxeXbB7t3N6fNYucZod4bn0WaNL7L4ZQH71pBvQTQK1NyNUXZAy6wbYNezB5LLjwu7XvBg5C3HlYtam4hIe8va553ppCFVlUb2R999itxtz/zVTsmZ72uMrjpGltm6Hgt82LPD2/ZaZGuZp3bZDfEee3RYsaB8jtNFpPwnluioc9Hf9lMyZ2U/Gc8mPQX6fA7L1mpeT4PgOw8lmRraHEVorejzvzXppJRFGXHoLpYszjdclpduFi4nxWHhcAklDnF1hrW9aVY4nC97auupK8p/pIzHRcPxI4jTnudbq5NroVHwjNK3R8+9oOKScX4vPmTuL9Z0tHQAcgFzy+gO6Aa2B5pyENiBHIm91mkcBpFgHnfitHZ09GlriSengrS3U0F3x+XIrHG4BwBKk6Ug96iByUaLZrZKWuDXchyvorY4u1mGhwr73oqIW9rEZXuDI7qyOZ8ldizCGehZYdtXLZRLkrfBdkDsmte2hp2DSu/7Jax7R8PlkAH2m17VYIXm35Ha5DT9y/qF6HhkwgzMeTVWiRpv5hbV3Zzy6o+vAotc6Hi+LPIWx3XMmqWmTLhiFueBtdLaazRaVrEOJwknUdLehKi3iuO5+m3AeJCA3oWVufjvdpbJvdciocQfNHBqiBBHPogNqRNLy/8RmicRHK9rCd9RsrHk8QnlY9j5XGLmfMBWiHqncRxGuo5DL9UL5g72rxRXZwOc3xDh+yFr+pEz2S9G6XGa5oMb3EDfSTQ8wrIog4hpOnvWN+SjFIQ6rBB8t1NzacRXTkuM7DW6Ds4xI1xsi+dqLJNZ3II5FUBxAIF1SQaQ4EDfrsnALy8hn2jAHHYHmFny4BkxDRQkadr6hXblhAvfoqaLX2Bd+CEIua33bRKx2oDu2eR/IqXC4HanOmLSWDWAG8jyG/qVbqBbR5rXw+ITMfG06XSPaLI6bkrDLKoM2YY3NGh3FZnNYGPhHeDQDZJG1/+U8HNmyJ5Q6SOSNoBBjaQASeV9dlNvBGRnfMncS0g8havxcBuMwt7aR4PLXWy4s04baXZ24oz3W+iZcpB9MvkXH8FLsGV8R+qzySN1934RsFwNnalZdrpc3Lk1yLQZKaVjdu4rCzdGNGVt++u/wDiH/8AYqvN4h7qGtYAZDvR+6PNWXpzXkjYRC/qVxM6URRzZk+4aNRHj4D8gujDBTlyac03GPBLJ9oXYob20rGFwtrWR6jXj5BYZPa+r09u75NaP1XOxuAcV41jniMfYuErn1qkokt5gCtgOij/AKscTMDJmjGdG4sFjIb3S7lfgvahocSXKPEnr8l8M1u9r8r7kbv/ALS/sF2uFcQyuJ8JysjIa1rRbWaSTdDe7Xj8/hGbw10DciNt5AJiLHh4dRrmPNexjycDh2Kzg3bj3tsVFmk7kizvVLn1mLHjilCPP/R1aLNkySbnLj/s7l81CU/ZSf2H8kXuVGX/AAJN/uH8l4/k9gnE2oWf2j8lMA80mf4bB/SPyT1AbBY2BG3fIp0ldWi6pUHl/auBpycZ5Olsg0OPhRu/oVhE7nymEspgOoO8hyA/Bek48yR3DHOhdI2RhBBjFu8F5xuQ6OCVs0DJNXcY6Rpa5p8QRXXoQvoNBkUsKXo+a+Rw7c7fhnT4CxxbkZBYae4BrjyIHgutnzRycP7UOaXwvZJXiAd/wJWXgk+JHweAdrr3fRaL2DjShxLOxm4sjImF75GkVVBvmT81tkt0zCNQgX52FE9j+zIbYthBWeHJdIwtlYNQ5lOEdtw7HnaebAHAb0f+wqaL8cStAJBonoVcctjJkipo0tawkuBr1Vobr5PP0VUMzNIt2nr6LS1ttGlwPUEHkF0Kd9HM8e3sg7WwCmnfkhjpIzrAc0+SkTqqnF3S7SYae4aiBRI3vdGyxhudIg5va70R8lUGsDgA51k+G66UX2wpppukEBorbx+arkxXggjulxq65LW8yTo6Y6K1bZn0CP7rvHdM7DZvPxSkyHRPDXtIcAbBUsebtiDtuXNsjb1WxSbVmnJi2T2LkrM8wJ0lw2qgUmGQitNdfktDma3Fgc3UOe4Sf3Y6Gwut+ZV3X0YvG4v8kJmRK1+tjnBzfvA8lY7OzXnUZZDq527mqmMYHadXd6n9FcZYq3oV49FHIKJW6TI6vcAPNcD2iGRPE0nW+uVusb+q6+VPO+J/u7I9Q+FshOn5kLm5mQ2443tDr57E/RYvlcmUUk7R4zIkdCXxTRvjffIiljLrjDS7vDqurxnEjg4gWlz3MqxZs14WtXBsDDzMWRuTjtJBNPsgi+VeiiSK2zgOkL6dyc081pgyIXFzcp0rWkd3swDv52u/L7HQuOrHy3tHRsrNV/SkD2QgDAH5Umsj7kYr8VaRNzOHHkRiN8RyS1t6mDTbSfPqFoije8aWHUDvbTsuhlezHDcKJkmTxJ8QcaFgG/ILo43sjjRW+LiOQNPxBumlGkZKTOO3HlYQ0x6h5OXbwR207Q+PSI6ku7G3L8VKbhcUQGnJldWxL2i/wV8TocLFt3dBNueDZd4bIkkR2zpw5ssffDgxx5gbqc/GpmRGSSfZo5aRfovN5fEnykCDtGNveqs/PosLHP3MzBtyJdusZZfRlHF7O3/rLO6d7zFIGVQ1O3Py6LBl8Tzs1rmOypNFWGMdpvy2WUmzTG2L+8VcH6G6rA9AtTySZtUIrwUvy8sESzy5Bcyi2nk0ei6GFxzNie6SSfIMjtnana2uroQSsDnEOsEBv/fJIPDzTBY8a2U3Mu1Ps6WT7Q5szC3utvqxtE/PosAyMh4e900m537xUdtwBt41zQbAAHMdEc2+2FFLoqp8YDY2Na3oGtQp9swbF8l/0tFfihS2KR6V73CwSGk711Ci2Qu1HcGtiXdfBbfdnlupzu6eekDkkcUgEBxII6bboDG0yAja9v5lNzZWV368Kcrw3SKJbZ33HMK8PjAOwaCPu72gM7Z3tYN9xzBNole4vaQSWnfY0tPYRSNPffprcNdsqm4+hxIleQfO6/BSgEYfqLtIvkCDz9VeJWwM79Ns38W34qYgBApw35Us+biSSY4ZCLdqsm6passVKNPo24ZuMrXZZ/FcZgBMzRfLvj90o+NYkjowzIY50hpg7Qd4+A3XnP4RnxyMdocaIsCQWP8ANZ8bhHE48jFfJj22N47WnjvN1NIr0r8FxS0+H/eehHUZuE4HuBO9x3aW+tKqabIb3mR2z+Ygm/olqJJVbuIvxCQzXXUg0F5y76PThV9WaA+Ut740lJ577gOVqr3h0/edqvzVobYUsxMsguaTzjaPxK857VSdjhQRkCny25viGjl+K9Id8iRp2pjeXqVmyOHxZTdE+mUDkJGAhdWDIsc1KXg5tRjeTG4x7Z4fB9o+JcNxfdsaSJsYLiLiaXDVsd1qPtnxdxg1OxyYHNdHcA2IFBdmX2WwpQXGLsj/AO3IR+G6xS+xxpzYcl7R1D2gg/RezH5DC+3R4svj8y6Vj4TlZXtJx2HKzRGW4bNVsbQJJ26nrv8AJdzM4Rivy38RPaduBdau7dVy9EuBcKHCcExOcHyvcXPcBt5D6Lfkf/jSDxH6rytTqnPM3F8dHrabSqGFRkueyZHeKjMax5f7HfkpO2d81CffGm/sd+S5PJ2+C4E6GjyCYSaO6PQJrFv0Shkkpbp9EabI2URQJ3YRsdQVpJPM36qp22n+4KVq2SrF2UfIRsA8A0Kh/DsR0mt2OzVd2LFrSCnstkc049SZrlhxy/dFHGOJJjTuGO+NrNdgOvu36dOqocZ3TTY8pYH7OLmcnCyF18mNtTOobs036mlkyWBmfhyjute10J9asfkvcw5d8Ezw82JQkyvGhLGUXh3j3OX1UjAYTqY5wBG7RyPyVkkZLD2bjuKvqFLHjkMJa5wdXI1zWxNmml0xNc9zeRHoNkmQau+HfCfGlpYNHdu73FLNNLJG4sion05rL6kibIp2UuxoRI55k5nlZNeQVXuT2/A6UC7sOpbGttjHllB3zorcMdsTCTkRveKGht2L2WueoWP9zKse7pHAexpl7N5eC7k9zrB8ldE+SFvYgOa076SbFrp52NjuYTHkRTGwHBoO3napmxIGQF0eUJJGbFug+NHdY/q4tJX2ZfRad0ZBJIx+vSfIFWD7QB2ob+PitOPiMlxRK+RzQXFtAeFfupx4UEZfU0h10aI5L0cOk1E4KUI8P+jg1HyGmhNwyz5X9mN5bGO8TR8Em6HN1d5w6gH81py8Zhha4PJJNAuWR2phaWgN2pwO+y0ZVkxS2T7N+GWLNBTx8oT5GhgppG9Ak7WvLvbnOz9T5g5gfVX06bLv5UgdG+OpGb2dINgj81wsjIOJlP7UjvtvY7rBSbNu1Lo5uQ4yZMjR3gDQL+dLscGYDFG4Ci7d1D8F5qSR0sjpG90XYs2V6TgOVjuiEb5C17bJB6+nifJZvhGC5Z3O1a06SyiDRsrkcb4+/FZ7vjgDI2OrRYa359VzM3jE2ZKXR3E3kB5fuuaW3Kbs0bJPVVSsmwedn5nFHRHKeHdk2mBrKG/PkrmZGXO9gdkSWwU0tOnl6c0MjBdTyBY2Hir2aG2wFok8BzWLmZKBeM6csMT8l5eeWmrCZGgB7nG/5nbkqkQMjOottx3vqpR1kPdIPgGw1bLW3ZsSoZfNNI3SHiMcyTRWjax4BRaAbA6ndWEBjCSa/ZY2ZIVhosjr0TJ1MDj3R5qLO/Tzek8hSbiDz5eiAVavmpBmgEDw6IYbPyS7TfZu4QDIa2h18yoPLAwjWKHxJdqzUQHW/rXRUtbrfYbZG4PmgLA0AcqQk4BprVfmd0KkPoToi00By5hVuNAWC29q8FtOTHGQH6rAsX94eH+SqfLC8lzSHfeojcIY2ZC5riGkizytVugFkAtsb0aVryJX6ms0nr03TEbXNb2jhqFfEOqAoERYbo3XMKVuIJNm+RHRaGxNO7XkHpR5qiWGZriabd7c9lATDjQ793sBSrmyGxxEh+je7BoKTW7ntY3UOoJU9ERBA0+ba/NYyW5UzOEnFpoxjiBd8OTXpJaYz5OmQ4n+5WHh2A4kvxIe9ztgVT+A8NnhdHHEI3Hk+NxDm/iuSekT6Z3R1zXaJnMc+g6Uu9TasbkjSWuYx7T/ADC1ym+ybY2AHieW5w5kBoB+Sg72cyA4mPikzW+DowSPxWh6GV/jI3x+QiuaOuZ7GzQ0eAV4ma2HUTyXDbwHijG3HxZhcDykhIFfIqpvCeP9q9j8zGDW0Q8l3evn9FgtBO7tFevxnaii97yXP95fBTWCmsa6zv4+CnPiyQvLffJq8TEwX6Lj/wAF43RIz8U3saa9H8K42SB77DuaNRPNLJ6PNutNURa3FXNnTMTwR/6yTfb4Gfsn2LwR/wCskN/0M/Zc4cE41Y1Z+OAfCJ136KnJwczEc0ZXGceIOaXBzoyLrnzKy/SZf4H63D/J2ewef97k/wCVn7JPxy9ha7KkLTz2YP0XPx+Fyvbqk4s6QOrSYmtHPlzJteb49mcV4NnGMy3jvJML3EEuArmBySOiyt0q/wDv8CWuwpc2e37N3/EO+jf2SfBrjcx2Q+nAg7N5fRfM/wDWbP8A/wBo+il/rFxBx/xx8wsl8dn9ow+44P5PpgjdX/5Un0b+yNB/4mT/AKf2XzdvHc4xOLp3a/u0NvmoHjvEuk5v+1V/G5vaJ9yw+mfS9B/4mT6t/ZAv/iZPq39l8x/jufR1ZJBvYBqvwc7jHEstuNjS6pHXQcQOXmVPtuXu0PuWH0z6OWNdV5Mho38Tf2U9LP8AiZf+Zv7Lkng7cfDfJPl5UkjIy5xjkABIFnajsvL42dK6XAD8xzu1f9sA7kNQAG3Laykfj8kumiy+RxR7TPe6Wf8AEy/8w/ZB0j/eJf8AmH7LhcExHZeLKcuU9sJ3NA7bTpaOhCqZjSQ+0gwcidz4Htc9lPqxRrfypPt+Rtq1wH8jipOnydrLm0RNa0vmcXAgahe30Sp2Q2ISMLdDg8BxBNgdKPmrHYWHjTaA7ZrKdqfZsnrforY2wNADHsLmkm3Pv5ei6cEPpwo4881kyX4KSSHAAmvRM01pIcRfgealJ7vHJ38uJu10Tag6fhoI15cZJ5EG6PyW9OzQV6jzBP1UXted2OrcHcK/RiEhoymudz0jn8lHVjsaS+SjW9JYoG24Achd0tMuY6Rhj7GBvI6mspxrztZNWMG92R7qog6diVWJ2OfIGvc4+gAH4rRmjGXLXRsxp2jdkZTpmhro4m73bIwLVWRlzzRFjqDRvWgD8VijzYpbbHI99DcGthfNWiZzm2yLevvH9FjsgnwujKnSs6fCZ2xYjnvi7SpXDSfMDdbxnRdmR7oQe11ggDld1yXmyZ3wkNa1tO3og/dCjDFI1h7sZfV6nX+C93B8hDFjUHG6/k8HUfGZM2VzjNK/4s6nGsntoo5Gx6AHU5pHPZcX3hj9XZG9vhOxC0MEjo5dXZ6tTR3t/H90nRFjrfLERtQ01S5NTmjlnuSo79Lgnhx7JO2Zp5GmPZpaR1teL4vKZp7a4npd/gu/xDKkMzrl+xbsGjYOPiuG+ESPLiCAdwK3WqDpm+S4o5zm6CGgg3+C047JAy7cB4FT7EREd0aidwOgVmK6WR0mqINDTQ3v5LNvgxUVfIjjBxBeb3uvNAicHlt8+QAG3mVv7IBgs2Tz8k/d2O2qhzd5la9xlRjIdGNMbmySci53IK2GMMBDGi+p8SpQ4kUZc9rQ0VvZS++RqLRy0j80syLYmuc2nGx1dX5KZvSGigPyRGSaFgAbUpF7GuqiSOVrEow3u7trz6rBC45WUWFzuzZ3t/v/APha5AZY9LnFrTz0868PJSiLI46j06elbqog5ZRGzW5wYxvMkKAcZN+TTW9KTwA3eiegKiyMi9+vMmwoUkTQppACjqI2B2A+qHOBdt0HNVg2dVoCgRiHtZAT9odz+y0g9nGKcSOlKiRpcLuyeTfBQ7J2NEY2ykucSa6K9josMo1HcnzQubKZi891p890LPaYbj7G58UjdnNsg/EP2VEjRBGdLmuBHLVuuF2mVWn3fJZ/dHpJHoptikDS4wzH0r9Vrsy2nSE8ekAG6G4PModOC3Ygg7c+S48zcprbggaTqoh7wLCqDOIkjUIG+QfYv5JY2nbfK2AN7UdBuFJuc0ja69ei88MfizidU+Kxo33YSSm7E4kW3/Eodv5cc/qECR6b3hjgNt3eHiq3ZEUp0BgO1kk0LXCj4flDX2/Ez3m8mQV9PNRZwg6qHE8wiqvS39SoXad8ODRZaDe25tR7eMAU7QTt4rlRcNij/wB+zCRtekH/AP0rTiRbls+Rv/M1o/VBtOm3MjbsZWEjmSonOiaT97odItc4QljSWTZBcTVChQ9bVboGAt0tm0j4g6iT87ULTOoOIw/ejcBdDcbpniWK3cOLfIgLm+5Yznh7w1xrayNvoqsjHx2xy6Wgt7M6RqPMA/ghWuDy3HvazKzOIk4OVPBjsbpaI5C2z1JC4+RxPic40zcQyngHkZTX5qtkTjEA7Yk1uOa6/DMHFzojrd2cjDTrcAD9V08ROapSOQzNz2fBm5Q9JnfuqcifKy3A5E0sxaKBkcXEeW69eOCcPZv75GfLW0fqoM4Xga+/IxnmZWm/oosi7K8burPL4etko0lzHA6gQSCCOq6mbnZefA2PMc2fSNLHyMBcy/By7buFcLDCO11f2us/JcbJiLXOYdLt6roie52kGtqpnDfjvbI4NaSByKmyGWrIK3lpABbtfOggsdq7rgCdzYWy2a6RmZH3Teq0+zJ3GpWM7V250/RSIlFfD9EslGUxOLgBsD4rVDE+B2tru9VX/wCEwX7anNo391XsadOrVR8gFG2VUmHacQynNjlzJ3D4WgPNf5ro8OxIGZel3dcKa0dS7qscfaGtDqfvWyv0yQgG2lzTtW1/NYST6M012dnEny25ckLnlkzHFul4FnzB62F2XMzWDv6eXJzd/rS8nk5M0zGyPj7OcfC5ria/78F2+Ae0M0rhiZDKeBQLXBuschzNE+SwuRsqJ1PdocwAzxMkfdk0AbSfg5DYjDDLpxnCi13MDwBC15sOZiA9vwySJwANl0e1+hWPD4q2SXso3tyJDyj7eO/lvv6Kpyj0a54seWt/NcmZvCIpA1r3F5aK7wddJjguMCKD2nqAy7WvJzJJNuyMJH3jK3x8FzxxZ9nUWbcyH3zWlqSOlOLNLOHtFBrXaRy1GvyWluGAKDW34uddLmO4o7QXaQQBew/RDOLE7NiYaO5Cx5MvxOp/DW3rqBzvEuoqMfDYYyXtjga83ZEllYP4zQ/wHeZ0BM8WF7Nr0CjjZU0joNxY2E0IQCKOyk2JoujFXQBi544uB0sevNVt4yH6Qfs3kWWnevmpsLuOrGGxNc0Fgt13pT1tvYArk/xV5H+I2vHTyWaPjQnJ1SujFWCQN1ntZipJHeEmku32cbsBcjiPFzGahmIYObhsSfI+C5GVxeaRuhpdZ5kdFkii1sc9z9R6+aqj7MXL0Z8mYvla8k1ZNXQ+aQBmkNHzujanLV7m6O1KIaHg6iQPAFbEzAiG63FztgOYIVjHs1U3bck0fxSYwOGkDujk0KbnNxCDoDnnbc0o+QjS0lsLdXIcrCoM9uJFhpFC1QcqWZ9Gm/0np+KmNTmjVWk7m7BP7JQGHskcdZJIOzQfzU4mGgTsedqpgc1oJA3OzWbfVXgua0F3KuQCAfdY6viBNjzU42hvMCz4BJzwH7mm9Cdr8kg8PNA0fFQoi1rnFxIcbqrQGl1araGi69EGPSQRGdPNzq5KmYPkPdLm14HZAaNPbPoG6O9KEzm7NbyHh1VcObDhRObJJbyaAO5Py8FQGuklEz5dIskNI5n0SuRfBpBNEWLvp0QTpNfW/wAlW0Wfs3DRzLgLtS1l9vDSQOpCAG6pNRe0b7bDoqxBpqnkjz3pTiBDxqfbnbAdVYA0y0+YahtQsb+qXROyoQj7u462hN04je5pabvpKAELKmODW/2hcGUS4TXVXYPzSb7QGFmidj3yEW1zTt8wuW+KnkkgA9VCVpLyCKNbbWrtiLkdp/G3ueGMx2A1eouJH0VbvaCZwawMijJ5vaSf/C5Jma2TUPjYOazOmlje1vcc0uvUR+BTYhvZ2JuPcQDnABlN21BvNUv47xGSmCSh1c0ALLLokfrM0Wk77fvaqjdchaxtirJ57qpR9Ebl7Nv8Xz43UJSTXM9EDiWc0UyZxB3OrffxVMbMUMuXLLHu2oAbLO0F8eijJW5ra/VWk/BLfs6L+KZhAMc7yarUd0xxvMjha1uQ+/5iVgjifICJXBlcmc9v2WWXIb9pE06gep6V4KKKfgOTXJ1v41mUAMmWnGtWofkrDxCX3XU7Ilkkc4jTr6eYXnXPDmh97jkpF0khtjH8vi3pZbERZGdyHiDonU6SQEVRDth8lCeR0snatneaB5O3rwXNEchjLpn0Ts1oSExY+27OI0g+A8Apt9Fc+OTXHG2RsDS7S/U4EnnRHgu17NgwTZLXnTYbRL2t5E/zLj8NlZO8tncBIB3b8fPwXZwh2eVI3s4pNTa+1NAb9PNSb8CPs9Ec+KyCYmg7AnIjF/ssWNkAT3JmgMFlt5bKPyG6yufA+qxIPAlziK/HdVNy3id+Np4cYydm6nG/MDkCtcafkzla8Hdmy8V0TmDiLeW15Rbv03AteU4gwOyZD2rX6zqtkhkB2HU7ldmSbswC5uK0nrRcvN8Yy3jJa5jmODr7zGlo6dFnj46MMqvsZidyDTuFDsnCxXJYxlTE957ifAHkqpJ5u0sueG3y8Vt5NVI6LYyDyPLwSewkigfouYWW424+QLjQVbpXxG6Ab0NlKDo6ogfqsNJ25EK5kTwwGj4VS5kOSJmuaYwB1LTRA8loi7SJzJYyT4X18QlvyFFeDoQxP7UDSTRBWmRx3GknfdcLLlfBIYtZ8Q5j+YKjFxnMiaGOeJY+VSC9vXmpTfJE0uDtudqaI38rPxH5q/A7aPikUkYtp2DWP0WD0s+a5DM33luoN09CPAro48o7KNpLK1f7TlRI5rW1zybk2o8Hs5OJcSkfq9w7Rz26XE5Nkj5DyWDGmycLL9/ZiaJ4pBpx5Mq9/ECqr5rLjS48TD9phBzdhomP4LFnY2NPnOyIhhFh0l5c95IPWyNgpH+iy/s9LPxLOme6R2I23myDkdetUuBknTlPEg7MvOosLwa9CtUD+HOimbPkwRu7PVEWlxGoHly5EWufxHIbk5PawSRhgDQdDTvW3Xqp4LZU58TLLpabe29H8VPU4FrNTQXcml3NZHHtNL3aXNHiar0Vc8kcBJcA5ziNg3V+KhbNTZJ2zGOQRnflq/MKBkkEm7QGE7aTYd81ihe5+U57YaJ3DjzAWyLW0BxLiRuB4+SrVBckmS3LqZG7bYC0PyO8OTr2c07AD1VLsyOSbsQwl24PX/wqyT2ZZZbY7oLQTXl+6UDUAyc9xg0fePIH91RJFkSF1viefEkV/kqe0qONpIYGigSe9SrGS2O2B2w+VK16BpjhnLdbnNcb5B1D0CT5nBp7JxcOo0cisuaQGNn0CUDYC+XnSvxnSQs7V8jow8W4HwSuLJ5ohFI3J1NlbpB2BBJryVsYBPQmu6Ca38Uah2bnhzQw7Na5wbt4kc0CpGd6Q0w2SBY+g5qMVZf9myJpaA6R4rUKWSSI03U4NJ3sHZWxMLmulaAWHm7qfVQjgfIyQRkih8b99vCgiKUDJe+YRwEtv4nad1dE5zW08Fzied39VDsg52kOcCTsWM015quOxO+IP1Fm19SSsuGTo6EYppstAAu3D9E+yEga+d7g0bnpam1zICO7uG/ET+Kt04c9as1pf4Hla12zPajG2eEynSXAjZoIu/NKbJZHpbuSXUbG486V080mBEQYGTtJ5huk/Tw81zxma3U/WTdaTuGg9AskvJg2WtyHyyljXu7Ibep8lbJIANBNOPIBDW9Gtq+g3+SBrZKY3R2bsFp5nwKCiOhgDuYeRz2NKYe2Ro0tJDNhbCN1F7nxlpmie2x8I5hNjQGuLgdThyLuXp0tCkKYQ0iaqJ1joD4I96DIy1sUlA7F33/l0UHu+z0hhcG8gDW/p15pRSMLWtsCUmqcbIHghCTH9lTnaQ8ii0/us82WGBzmx63dQ0WtJZHrHaxCQnlbiK9P80OgeIT7ttvdcjXqnFl5SMDIWTsEkpIe4cgLQtsDsmNhBxS4E2KIG3zQs+TGkZhnNDQWvGxq6sHyWZ/EHOmOkXHfLr9V7B3D+FkC4GV5C1FmLgs37CFp3prW3QWCnH0ZOMn5PKRQue98r3RsY/fQ4/jak4kNLY2iQnYBpsFerjbhscQcWJvWzG0fNWh0dgdia6aW8x6AK/UGzwePbgH/AA34oDzuGgbn52ptPYl1Q97YG+dhenMeO7U9ruRqq5HwIIVJwYi3U9rj/cwAf5J9S+xsro8qzFle8ufI2MEncm/xV7cU62g                                                

                                                網(wǎng)站欄目：Python調(diào)用kafka構(gòu)建完整實(shí)例分析與應(yīng)用                                                

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python調(diào)用Kafka構(gòu)建完整實(shí)例分析與應(yīng)用

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