Python循环语句 if while for
流程控制:
if 条件1:
缩进的代码块 (注意缩进4个空格)
elif 条件2:
缩进的代码块
elif 条件3:
缩进的代码块
......
else:
缩进的代码块
注意1:(相同的代码块儿,同一级别,通过缩进的上下对应级别来控制运行顺序)
注意2:(if语句里面如果一个条件成立,及不会执行下面条件)
今日练习:(即注意事项)
第一:求1-100之间和
res=0
num=1
while num <= 100:
res+=num # res=res+num 0+1=1 1+2=3 3+3=6 ...
num+=1 # num=num+1
print(res) #
注意点:python的缩进严重影响你输出的结果,如果print(res)没有和while对齐,其实是每循环一次会求和一次,结果如下
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" alt="" />
正确的书写方式为:
res=0
num=1
while num <= 100:
res+=num # 每次如何运算的 res=res+num 0+1=1 1+2=3 3+3=6 ...
num+=1 # num=num+1
print(res)
aaarticlea/png;base64,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" alt="" /> 第二:输出乘法口诀
for henghang in range(1,10): # 1 2 3 4 思路:henghang和shuhang对应的值
for shuhang in range(1,i+1): # 1 12 123 1234
print('%s*%s=%s'%(henghang,shuhang,henghang*shuhang),end=" ")
print( )
注意点1:python的缩进严重影响你输出的结果,如果print()没有和第二个for对齐,结果显示格式其实是不一样的:
aaarticlea/png;base64,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" alt="" />
正确的写法:
for i in range(1,10): # 1 2 3 4
for j in range(1,i+1): # 1 12 123 1234
print('%s*%s=%s'%(i,j,i*j),end=" ")
print( )
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" alt="" />
第三:用for循环取出下面list列表、字典dict的值(常用于从多个数据中取值)
names=["zhangsan","lisi","wangwu","zhaoliu"]
user_info={"name":"zhangsan","age":21,"sex":"male","address":"sh"}
for x in names:
print(x) #取出所有names里面所有人的名字
for y in user_info: #y="age"
print(y) #取出所有user_info里面的key值
for y in user_info: #y="age"
print(y,user_info[y]) #取出所有user_info里面的key和value值
最后1个的输出结果如下:
aaarticlea/png;base64,iVBORw0KGgoAAAANSUhEUgAAAk8AAACKCAYAAACzfa5AAAAAAXNSR0IArs4c6QAAAARnQU1BAACxjwv8YQUAAAAJcEhZcwAADsQAAA7EAZUrDhsAAB2lSURBVHhe7d0NcE1n/gfwH/EWb1E0WERCvdWW6LYVGk0Tr7Ek1YmMjpfJmi3tDvWSzDDDqO6wi1Jm14zJNslike6s1RK66mUnBktpynpfb1thlRIEES8N///3l3PS6/acm5w4N5X4fmYy55znnvvc5zz3nOf+zvM8N7daxKu9HwoRERERlcn/B0+RDJ6IiIiIyqjacx06MngiIiIiKqNqkVHRJcHT7Zv5cvfuXWOLiIiIiLxVN5ZEREREVAYMnoiIiIgcYPBERERE5ACDJyIiIiIHfrLgKS4uTurWrWtsuWvIkCEyefJkY6vyqMgy+7P+PU2cONFY8+25556TYcOGyfTp042UsomKipIJEyYYWxV3XN6etPp0itej/3Tq1EnGjx9vbD0+tm/OuF3/niq6ffNkdVy+9nfK3/lXdq4ET7/61a9k8eLFJX+jRo0yHrF3+vRpeeGFF4ytYu+++25JHjNmzJD27dsbjzhTs2ZNadOmjbHlPrfK6e3UqVPGmv9Z1b8/4HXK6v79+/Lss88aW2VTu3ZtadeunbFVccflze51kfbBBx/I73//e3nnnXeM1PJzUp9O+LPe/H09+lt52jdPAwcOlD179rB9q8D2zZNZ//5Q0e2bJ6vj8rW/U/7KHzdpaBMrO1eCp7/85S+6nDJliixbtkxPktKcOHFCOnbsaGwV+/jjj3WZkpIiGzdulDfffFO3nVq7dq2x5h9uldNbVlaWsVY+Q4cONdZKZ1X/5eXrdTds2GCs/cBqfzSsn332mbFVdps3bzbWirl5XE7YvW5CQoL8+c9/lt/97ndSo0YNI7X8rOrTzpNyPvj7evS38rRvpi5duugHTk5ODtu3CmzfTJ71X15PUvtmsjsuu/2d8mf+6IELCgoytiovV4Kn77//Xpf169eXpKQkyc7O1m3Tb37zG2PtB2iA8OZ4fqCY+WB56NAhadq0qW7/lKzuFNwuZ0BAgDRu3FheeeUVI8W55s2bS/fu3Y2t0lnVf3nYva7dMTktp1NuHZdTdq9bq1YtadCggdy8eVP++c9/GqnOOT1HnrTzoTIrT/tmGjBggHzxxRfy8OFDtm8V2L6ZPOu/PJ609s30uMdVGn/lj7qpV6+esVW5BYSEhs0y1uX+vbtSVFRkbDmDLr7o6GhdX7NmjS5N+/btM9YeFRwcrB8u3333nZFSnA/etJdfflmaNWsmO3fu1PTZs2dL//79ZevWrTJ37lwZPHiwbNq0SVq0aCFjx46VN954Qxo1aiRHjx7V/ZHPtWvXdHy2bdu2JRE05naMHj1aYmNjpWXLlnLgwAHtlh4zZow+lpeXpw0kXhfH8/bbb0uTJk2kd+/e0rlzZ813165dluW0ywfCwsLkvffe0zHj3NxcuX79uqYDLsARI0boEscEoaGhOt4cExMj58+fl6tXr2q61fEiT5QTH34oF/7MfDA/AmVCPij/3r17NR286x/d9SNHjtTneq6j3IMGDdIAAGP8GDLYv3+/z9eNjIzUO4wePXqUpPna3+SdZlcPGI9HWfDeov49n+N9XBh+QL5btmzR18ewi7m/Vf52x+srH7A6n9H4JCYmyjPPPKPnwoMHDzTd6n30df5Y1SeeO3z4cO0Gx9DSrVu35H//+59r54Nd/mB1PRYWFtq+Ltatrker68Ku/n2xeh/N9wu9atOmTStpM+z29wX5OG3fMAzaoUOHR3qKkA/bt4pp37zrv6q0b1bnld3+VucD2J1v4K/8cV4hDT3x/fr1e+SYrDhtf0rLz22uThifOXOmsVY2//nPf6Rr167G1g8WLVqkF8X69euNlOK8zTs+VBjmkMBbb70lX3/9tbz//vs/mvCan58vCxcu1DfehDdg3rx5kpqaKuHh4Zp28eJFrfg6derIlStXZNWqVZpuvt62bdt0nBddlri4Td7ltMsH0PWNbmvs690N/uWXX8pvf/tbY6sYhnsyMzMlPT1d4uPjjVTr492+fbtMmjRJ17E01yEiIkLS0tK0/rwbfe/6x34ms+seUN/oZi0oKNAPJHTpgq/X3bFjh57gnnztb8euHrC+bt26H/UCgPdx/fGPf9Q6xo0BxvCXLFliPGKdv93x+soHrM5n9DYtXbpUP3jw3pms3kdf549Vff773//WD5iTJ0/K8uXL9W4R3Dof7PIHq+uxtPfX6nq0ui7s6t8Xq/cRk3MPHz4sd+7c0eEVz8m6dueVL07bN6sPT2D7VjHtm3f9V5X2zeq8stvf6nwAu/MN/JU/Ak6cM/fu3dP00jhtfyqaq8HTjRs39IOirBPKvvnmGwkJCZFq1aoZKcVw0mGionmXBbhjR1dpw4YN9e/SpUuajm5SRLRoIFesWKFppuPHj8vly5elevUfDhMXCOYuJCYmGimidxxoZAHR/7lz53Td7LJEo4HXxtKTdznt8gFE6wcPHtTHse7Nu3sUvQC4q0xOTtZ1k6/jtYIGAyct7ua8x5m96x9DNyaz6x7M40N9og4869Pf7OoBQwm4O7SasOl9XNgH+//85z+X559//pGJq1b52x2vr3zA6nzu1auX7ofGBc8zWb2Pvs4fK//97391icYFr4HhwdI4OR985W93PfpidT1aXRflOd+s3kdc66tXr9ZeD5Qf2yar/UvjpH3D8ASCbAx7eWP75v/2zar+q0L7Znde2e1vdT6A3fnmz/wR/GDuJwJUwBLtqB232x+3uXKWmPMkcNKhWw1dvWWBCwoXP7p8wTMfK3jzML8AlWlCN+eLL76oww1mtzrujACViz8w0xBBZ2Rk6IcZmJNkzdf0fG3zud5LfNsFrMpplQ/gTg3dyrhLxHpp0C2OMmLSJsprsjpeE04odMF79h4EBgZqI4S7Qu9vCXnXPyCPn/3sZ9o9C3jMfF+s6hOsXhfMfb3n0djtb+6HYzPZ1QPuutG1bJbTXILVce3evVu793E348kqf1/Ha5cPWL0uusBxrLiD8vzwtnsf7c4fsKvPVq1aaV3iWDy5cT6AXf5W1yN4v66v69HquijtfLNi9T6iscWwCnpQ+vTp88iHk915ZcUsD96TsrRvCD4xpOB99+6ZjxW2b+60b3b1D8ijsrZvvo7Lrj20Ox/A+3zzd/4IxvGHIXTA0vMGwo7T9qeiuDLnady4cRqZIrKMiYnROROeHy44QLt5AYgaMe6LqB9jv5gbgiEOdPV6w50PPoz+8Y9/aEMPaOzxBqJxxLg/7hwWLFigj+Euplu3brrs27evnhQYl8X4KOZnoAEw32xE/oBjQB2cOXNGTySUBc/3/HvppZf0ovUuJ7qQrfIBRMYYv0UD88knn+h8BU/miYt5BoD9MaaOseQLFy7oPAKwOl4Tjg2P4bnm6+KuG+P5PXv21P2PHTum6SbP+ofWrVvr/t9++62uo55xVwc4du/6BKvXxfg/xsgBx4X6Pnv2rG5b7Y/3xPwqP8bD0dBgropdPSAQQX3ih6zxoYgGyzwG8D4u5INt74bBKv+PPvpIH7M6Xrt8TN6vizsrdIPjA+HTTz8teb+s3kdf549dfSJv7IfrDnMUPOdbuXE++Mrf6noE79f1dT1iH+/rwlf927UlVu/j/PnztTcCAS/m52Bej/m+We1vx2n7hvYBdYAPdE9s3yqmfbOrf6jM7RsmWtsdl117iP29zwfz3w94n2++6s2N/AFBlzl8jjr+6quv5Pbt27bXdXnan4pSLTIquuRVb9/M18qpSPi2B07eOXPmGCn2sC8+hMwLsCrABYyLBicBLqCKHrt1Uv+VyU91XBX5umiA8UGKOzgMc7jBs/yl5V8Vr0c3YBgGXyowA9Cyqor1+VO0b+Wt/yed28flfb75O3+nnvT25ycPnspq6tSpOmaNSbueY9eVHb7pgQYGd1x/+9vfSsZ5iUqDbwzhTg9DSR9++KGR6h5f+VfV6/GnwvaNKpK/zzc38n/S259KEzwRERERPQl+PCOQiIiIiGwxeCIiIiJygMETERERkQMMnoiIiIgcYPBERERE5ACDJyIiIiIHGDwREREROVAlgyf8EvjkyZONLSIiIiL3VMngCT9s2aZNG2OLiIiIyD1VMnjCDwgSERER+cNPFjzhR/2IiIiIKhtXftsOP/7YpEkTWb9+vQwbNkxOnjwp6enp+lhcXJz06NFDatWqJUeOHJFly5ZJdHS0xMfHy759+yQoKEhu3bolLVq0kHnz5kloaKiMHDlSf1F55cqVcurUKc3HzowZM6Rp06bGlsikSZN0uXjxYsnMzJShQ4fKmTNn5E9/+pOmW5XHV/lff/116du3r1SvXl1/HbyoqEiWLl2q86peffVVefDggaYvWbJE93eaPxEREVUurvQ8bd26VYOggoICDVq6dOliPCIaGCEoSk1NlfDwcE3Lzs7W5bZt26Rdu3ayefNmDZ4gISFBgx4EFwiwSoNAJDk5WX+xe+PGjUZqsfz8fFm4cKF06tTJSLEuj6/y9+/fX5YvXy5paWn66+AInCAiIkLTZs6cKWvWrNE0cJo/ERERVS6uBE9Hjx7V5fHjx+XixYvaS2NCwDBlyhRJTEw0UkQePizu7MK+AQEBujQFBwfLhAkTNCDCemk+//xzee211zSfgwcPGqnFUJ7Lly+XWh5f5c/JyZGkpCQZN26c7Ny500gVDZwiIyNl7NixGhiZnOZPRERElYsrn+IYYgMEMPiDOnXq6BK9RxkZGdoTAx07dizZx3uJoCIvL0/3TUlJ0eeVBj1At2/fln/9618azID52mUtj6/yd+3aVebOnStTp06VrKwsTYPAwEBZsWKFpo0aNcpIdZ4/ERERVS4BIaFhs4x1uX/vrs7pceqjjz7SZfPmzaVbt266xDyhTZs2ScuWLWXw4MFSWFiowRGCiYYNG0r79u11P88/zB/atWuXzguKjY3VuUS5ubmatx3MJ3rhhRd0eA09Wnv27JEFCxboY8izLOUxe4ms9m/VqpX06tVLwsLCNJBq0KCBnDt3TkaMGCGDBg2Snj17au/UsWPHNA+n+RMREVHl4sqE8apszpw5Ov/q7NmzEhISosN306ZNMx4lIiKipw2Dp1LExMRIVFSU1K9fX27cuKGT3bdv3248SkRERE8bBk9EREREDvBrX0REREQOMHgiIiIicoDBExEREZEDDJ6IiIiIHGDwREREROQAgyciIiIiBxg8ERERETnA4ImIiIjIgUoTPOH362bNmiWzZ8/WHwM24bfmfvGLX8jkyZONFCIiIiL/qTTBU+/evWXRokXy97//XX9414Qf2Y2OjpY2bdoYKURERET+U2mCp7y8PMnPz5dDhw7Jw4clvygjJ0+elAULFhhbRERERP7l2m/bxcXFSY8ePaRWrVpy5MgRWbZsmaa//vrr0rdvX6levbpcuHBBioqKZOnSpRIaGiojR46UGjVqyMqVK+XUqVO6f2m6du0qzZo1ky1bthgpxRYvXiyTJk0ytoiIiIj8w7Wep1u3bsm8efMkNTVVwsPDjVSR/v37y/LlyyUtLU1at26tgRMkJCRIZmampKenS3x8vKaVpmHDhhIUFPSjwImIiIioorgWPBUUFMiUKVMkMTHRSCmWk5MjSUlJMm7cONm5c6eRKhIcHCwTJkyQ5ORkXS9NYGCghISEyI4dO6RevXpGKhEREVHFci14Qu9RRkaG9jxBx44ddYlhtrlz58rUqVMlKytL0wBzmLBvSkqKPq80CLAOHz4s1apVk9dee81ILda4cWNdYjiPiIiIyJ8CQkLDZhnrcv/eXZ2TVB4tW7bUb8EVFhbq/CYET3v27JFWrVpJr169JCwsTAMp/GuBc+fOyaVLl2TYsGESGxurc6Fyc3ONnKx98MEHMnDgQP2rW7eu7Nq1S9O7d+8uEydO1HV8I+/69ety/vx53SYiIiJym2sTxu3MmTNH5zWdPXtWh90wfDdt2jTjUSIiIqLKxe/BU0xMjERFRUn9+vXlxo0bkp2dLdu3bzceJSIiIqpc/B48EREREVUlleafZBIRERE9CRg8ERERETnA4ImIiIjIAQZPRERERA4weCIiIiJygMETERERkQMMnoiIiIgcqLLB03PPPac//zJ9+nQjhYiIiOjxVemep/v378uzzz5rbBERERE9viobPJ06dUo+++wzY4uIiIjIHZUmeGIPEhERET0JXPttuyFDhsirr74qDx48kAsXLsiSJUs0PTQ0VEaOHCk1atSQlStXao/Q4sWL9bE//OEPMm7cOKldu7ZMmjRJ06xER0dLfHy87Nu3T4KCguTWrVvSokULmTdvnsTFxUmPHj2kVq1acuTIEVm2bJnxrGJ4Lc+8rcpDREREVFau9TxFRERIWlqazJw5U9asWWOkiiQkJEhmZqakp6drAASYxH348GG5c+eObNiwodRJ3dnZ2brctm2btGvXTjZv3qzBEyCQQhCVmpoq4eHhmuaLVXmIiIiIysq14AmBU2RkpIwdO1Z7h0zBwcEyYcIESU5O1nUoKCiQ1atXy4gRI7TnB9u+PHxY3Dl28eJFCQgI0KUJz50yZYokJiYaKb5ZlYeIiIiorFwLngIDA2XFihWSlZUlo0aNMlJF8vLytFcoJSVFMjIyNK1BgwY61LZo0SLp06dPqUEMAiarZfXq1bX3CPniNaBjx466BAzNAYb0TFblISIiIiqrgJDQsFnGuty/d1eKioqMLWfQizRo0CDp2bOn5OTkyLFjxzT90qVL+v+WYmNjdS5Ubm6uzJ8/X3undu/eLUlJSdK7d2/ZtGmT7m+lf//+0r59e2nevPkjf5hfhaG/wYMHS2FhoQZTCJ727Nmjae+8844+v1+/fhpInThxwrI8RERERGXl2oRxIiIioqdBlf0/T0RERET+wOCJiIiIyAEGT0REREQOMHgiIiIicoDBExEREZEDDJ6IiIiIHGDwREREROQAgyciIiIiBxg8ERERETlQYcFTVFSU/iCvN7v0J8GQIUNk8uTJxhYRERFRBQZPtWvXlnbt2hlbP7BLfxLUrFlT2rRpY2wRERERVWDwtHnzZmPtUXbpT4K1a9caa0RERETFOOeJiIiIyIGAkNCwWca63L93V4qKiowtZ+Li4mT06NESGxsrLVu2lAMHDmh6p06dZOLEidK2bVtp1qyZbNq0yTa9ffv2MmbMGM0rLy9PkpKSZOfOnbp/aGiojB8/XmJiYuT8+fNy9epVTce8JDwH6Z07d5a9e/f6TLdjt//AgQPl2rVrOi8LZc3JydF0IiIiejq51vN069YtmTdvnqSmpkp4eLiRKhIfHy/r1q2T7OxsI6WYVfrFixc1iKpTp45cuXJFVq1aZTwikpCQIJmZmZKenq7PNUVEREhaWprMnDlT1qxZY6Tap9vxtX9+fr4sXLhQAz4iIiJ6urkWPBUUFMiUKVMkMTHRSCnWtGlT2b9/v5w+fdpIKWaVfvPmTTl8+LCuo3fp3Llzug7BwcHa+5OcnKzrJgQ8kZGRMnbsWAkKCjJS7dPt+Nr/+PHjcvnyZalenaOcRERETzvXogH0BmVkZGjPE3Ts2FGX6LXp0KGDDnmBubRLNwMU70AFw3jIOyUlRV/HFBgYKCtWrJCsrCwZNWqUkWqfbsdqf/SAQUBAgP6BmUZERERPJ9fmPGGe0+DBg6WwsFADHwRPe/bs0R6p4cOHy927d7XH6MGDB9qTY5XeqFEj7VmCAQMGaFnOnDmj25cuXZJhw4bpnKoLFy5Ibm6upo8YMUIGDRokPXv21PlIx44d85lux2r/BQsW6GPNmzeXbt266bJv374l87aIiIjo6VMtMir6obEut2/mazBDRERERNY4iYeIiIjIAQZPRERERA4weCIiIiJygMETERERkQMMnoiIiIgcYPBERERE5ACDJyIiIiIHGDwREREROcDgiYiIiMgBBk9EREREDjB4IiIiInKAwRMRERGRAwyeiIiIiBxg8ERERETkAIMnIiIiIgcYPBERERE5wOCJiIiIyAEGT0REREQOMHgiIiIicoDBExEREZEDDJ6IiIiIHGDwREREROQAgyciIiIiBxg8ERERETnA4ImIiIjIAQZPRERERA4weCIiIiJygMETERERkQMMnjw8//zzMmfOHBk9erSR8oOJEycaa2VTlv2HDBkikydPNraciYqKkgkTJhhb5efvcjrltJ7d4lZ9EhFR1edK8PTuu+/K4sWL9W/GjBnSvn1745HKZfDgwZKRkSGtW7c2Un5w+vRpY61syrJ/zZo1pU2bNsaWM7Vr15Z27doZW+Xn73I65bSe3fK49dm4cWOZPn26/jVp0sRIJSKiqsiV4Onjjz/WZUpKimzcuFHefPNN3a5smjZtKt988432PnnbsGGDsVY2Zdl/7dq1xppzmzdvNtYej1U5hw4daqwVe5xyOlWW8vjD49Zn37595euvv5Yvv/xS14mIqOpyJXj6/vvvS5aHDh3SIKQyqlWrlhQVFRlbxQICArRX4ZVXXjFSfHO6/0/FrpzNmzeX7t27G1sV50krj1MdOnSQr776Svbv36/rRERUdQWEhIbNMtbl/r27PwoeymrgwIHyxRdfyMsvvyzNmjWTnTt36vDdmDFjJC4uTvLy8iQpKUnTISwsTN577z2da5KbmyvXr1/X9BYtWsjYsWPljTfekEaNGsnRo0c1PTQ0VMaPHy8xMTFy/vx5uXr1qqZjPg5eA+mdO3eWvXv3+ky30q9fPy0L4Dg2bdqk6xAZGSnDhg2THj16lKRj30GDBsnNmzd1jg6GtPChCVb7g1158HrXrl3T+TZt27aVnJwcTbc73k6dOulrYl/Us+dreMMwakhIiL4GAhA859e//rU+x6qceC/efvttHcLCczzrwq6cdqzKj/IgnxMnTsi0adN0mNTM32l57NidP3bnm1192tW/nV/+8pfaa3bnzh2JjY2VrVu3Go8QEVFV4+qE8UWLFmmQsH79et2+ePGifhjVqVNHrly5IqtWrdJ0wNBeVlaW7us5zPfWW2/p8Mf7778vdevWNVJFEhISJDMzU9LT0yU+Pt5IFYmIiJC0tDSZOXOmrFmzxki1T7eyZcsWmTRpkq6bS9OOHTtk9uzZxlYxfDAGBQVJQUGBBgRdunQxHrHeH3yVJz8/XxYuXKgf5Ca748X6unXrJDs720ix9+mnn8qBAwfk888/14ABPSPID6zKuX379kfqwbsurMppx6r8mA90+PBhDTAQaGDbVJ7yWLE7f+zON7v6tKt/X6pVq6Z/RERUtbkaPOHDDRPGzbt99MzgwxJw937u3DldB9zlHzx4UB/HugnDNLt27dIP2BUrVhipIsHBwdrrkZycrOsmBCTotUBvAwIak126G8zjO378uAaI1auXXo2+yoN8Ll++/Eg+dseLIVH0cpVlYjWCpfDwcP0WYa9evTQIMN+P8rAqpx2r8iPYXL16tYwYMUJOnTql226zO3/szje7+rSrfzs419HThfcW60REVHW5EjzVqFFDl1Yfqmaa92PoicLwFXoxsG7C8MiLL76o84+io6ONVNFhv9TUVJ2Ujm/EmQIDA/VDEr0Ko0aNMlLt0+1gzo3n0pOZZh6nuUS6+Rh610ze+4NVecznWOVjd7zo/cGcGgwzgbm0guAE35TDt8jQG4MA9uHDh8aj1uWEBw8e6DfGunbtqtu+ymnHqvwNGjTQYTn0UPbp0+dHQUlZy+OL3fljd77Z1add/ds5efKkvPTSSzo8inUiIqq6XJnzhLkhzzzzjM5xwreNTBiqwp07DBgwQPM+c+aMbl+6dEmGDx+uH2iffPKJzqcB9GyghwQfrphXg54dwP6YE4P5JBcuXNBhKEAvBuYf9ezZU/c/duyYz3Qr+MDEcBqgnPXq1SvZH3NkzP891L9/fyksLCzZRi9Ht27ddIlvWGGI0mr/s2fPWpZnwYIFup9VPnbHi4AI9Xb37l0NPhBYoEfIDo7lyJEj8t1332nwZAYOduWEli1b6nuAMuD98lVOO1blnz9/vvbM7N69W+e/9e7duyQPJ+Xxxdf5Y3W+2dWnXf3b+fbbb3VuX6tWreSvf/2rlp+IiKqmapFR0SVdEbdv5uuHCBERERFZc2XYjoiIiOhpweCJiIiIyAEGT0REREQOMHgiIiIicoDBExEREZEDDJ6IiIiIykzk/wBz8udAdz1iMgAAAABJRU5ErkJggg==" alt="" />
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