Lua语法基础教程（下篇）
今天我们继续学习Lua语法基础教程，下篇。五、变量
5.1 number变量变量，可以看作是一个桶，在里面装你想要装的内容。这些内容可以是Lua包含的所有合法类型。例如：我想要新建一个桶，名叫bucket，在里面放入233这个数字，就可以像下面一样：data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAqIAAABVCAYAAACSCYZ7AAAHnUlEQVR4Ae3b0Y7aMBAFUP5p//+f4A3tC5UfRrVcL6Tb4uu0pxIKcUziTg7oTtReHv6ogAqogAqogAqogAqoQKACl8A1XVIFVEAFVEAFVEAFVEAFHoIoBCqgAiqgAiqgAiqgApEKCKKRsruoCqiACqiACqiACqiAIMqACqiACqiACqiACqhApAKX2+32uF6vXmrAAAMMMMAAAwwwsNTA5X6/Pz4/P73UgAEGGGCAAQYYYGCpgYsQKoQzwAADDDDAAAMMJAwIojqfpZ1PArlr+n**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
让我们试着自己新建几个变量吧！新建变量year，并将变量的值设置为1926新建变量month，并将变量的值设置为8新建变量day，并将变量的值设置为7data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAqMAAAFBCAYAAABD+6Z8AAAgAElEQVR4Ae3dXZLjuLEG0N5Tb9BLtt/seWkHriNvpdMAqaoSmWTxOEIBEn+kiFPSB43H/vXXX3/98fIMGGCAAQYYYIABBs428Pe///3Pr7Mv6nqgM8AAAwwwwAADDAwDwqhfhf0qzgADDDDAAAMMtBkQRuFrw2dHbEfMAAMMMMAAA8KoMCqMMsAAAwwwwAADbQaEUfja8NkN2w0zwAADDDDAgDAqjAqjDDDAAAMMMMBAmwFhFL42fHbDdsMMMMAAAwwwIIwKo8IoAwwwwAADDDDQZkAYha8Nn92w3TADDDDAAAMMCKPCqDDKAAMMMMAAAwy0GRBG4WvDZzdsN8wAAwwwwAADwqgwKowywAADDDDAAANtBoRR+Nrw2Q3bDTPAAAMMMMCAMCqMCqMMMMAAAwwwwECbAWEUvjZ8dsN2wwwwwAADDDDw2DD662+/dkPY6PNKv/yH9Nn+eex3j7977a+MH2P2Xt99X3vj9+57r31v/tH+yhyzPrO6V66njw9nBhhggIGnGHhsGB0LPAsKoy5eX0Ewm3M2T1zjlXI2flb36rVnY6Pus3Pk/vn4q/PFuM+Ws2uPOVb1Mf9or6/aFvO8MleMjXJvTPRT+tJhgAEGGHiqgceF0Ro88vlAsBcecv/oW+vy+Vmw8r28cs18j68ez+aN60bb3nn0O6L8yrVfHRP9oqz3H/Wj3HvVsc59ATHAAAMMPNnA48LoWOwIDrHw+TwfR/uqnPXNdfl4Ncc76ut16vkr16hj6vlqjtFv77Ua+476vWvn9tn1Rvuor2XtG+21Ps5X7av6GKf0BcQAAwww8HQDjwyjY9EjJEQZEOp51Ncy+o1y71XHvvM87qPOuapf9av94zzKOu5q56v7XNXH/Uf7rBx1s1eMjTL61POoz2X0UfryYYABBhhg4D8GHhdGczCoxwNFrRvnMyyv1K/6zOb7Sl2df+98do0YE2X0yef5OLeP+s+8YuwR5ewex3VW9XEP0V7LVXvURzkbF3XRJ8pVfbQrfTExwAADDDzRwOPC6N4i58CQj/O4Wj/OV6887l3Hca06X72v0b7qG20xRx27d/7dcTH+XWW935h3VV/bo99eGeNqGeNG/Theveo45754GGCAAQaebuA2YXT15R4hYK99ttAxNrflunxc+8T1cv04Xo2p/aJvzLMqZ+NWdZ+99mqeWf1q7tV95/rZfO+u27q/rWvFuK0y3ssr84w+MVftv6qv/Zz7YmKAAQYYeJKB24TRdy1KBItZOa6RA0M+nl0/2mdzRd1s3FF1cT+fmT/uc6vcmq9ec+98a67Ptm3d86qtXiPu99Wyjo/zGD/OV9fOfWKc0hcOAwwwwMDTDTwujOYFn4WDXJePZ+Nm7bO6PPbI469eezVuVZ/fw+iz98r9V8cxx6p9r351r6v6mC/aXy1jXC1j/KjPx7nfqj73cexLiQEGGGDgaQYeGUYjFNRyLH7U1eMKI/qNcu9Vxx51Hvf0lfnr2Hr+6pzfGfedsav7e3XO2i/OV2W9XvQb9eN49arjnPvSYYABBhh4uoHHhdEaGgJA1Ec56vNx9Ity1baqj3FHlt+99hgfr1fuM/q+Ur463yv9ap9x/VoX51tttU/uG8ejjNfoH/UxNspcn4+jfWts7uPYlxIDDDDAwNMMPC6M5gWuoWHvPMZGvyijfpSzutx+5PFXrz3G1bGzulfuvc7zypjR56hxr8yb+4zj/Mr3H/W5Lo7rHFGfy9wn1zv2xcMAAwww8GQDjwyjESpyOMjHAeKVujzX6jjmi3LVb6s+xm6VY/xWe27L18r19XjVL9e/elznjvMxPo4/U74ybq/PXnu9n1X/qB/l3qvO6dyXEAMMMMDAkw08Mow+ecG9dx94DDDAAAMMMHAlA8LoX0BeCaR74ZEBBhhggIFnGRBGhdEv/SNyHxTP+qCw3tabAQYYYOAoA8KoMCqMMsAAAwwwwAADbQaEUfja8B21wzKv3TsDDDDAAAP3MSCMCqPCKAMMMMAAAwww0GZAGIWvDZ9d6312rdbKWjHAAAMMHGVAGBVGhVEGGGCAAQYYYKDNgDAKXxu+o3ZY5rV7Z4ABBhhg4D4GhFFhVBhlgAEGGGCAAQbaDAij8LXhs2u9z67VWlkrBhhggIGjDAijwqgwygADDDDAAAMMtBkQRuFrw3fUDsu8du8MMMAAAwzcx4AwKowKowwwwAADDDDAQJsBYRS+Nnx2rffZtVora8UAAwwwcJQBYVQYFUYZYIABBhhggIE2A8IofG34jtphmdfunQEGGGCAgfsYEEaFUWGUAQYYYIABBhhoMyCMwteGz671PrtWa2WtGGCAAQaOMiCMCqPCKAMMMMAAAwww0GZAGIWvDd9ROyzz2r0zwAADDDBwHwPCqDAqjDLAAAMMMMAAA20GhFH42vDZtd5n12qtrBUDDDDAwFEGhFFhVBhlgAEGGGCAAQbaDAij8LXhO2qHZV67dwYYYIABBu5jQBgVRoVRBhhggAEGGGCgzYAwCl8bPrvW++xarZW1YoABBhg4yoAwKowKowwwwAADDDDAQJsBYRS+NnxH7bDMa/fOAAMMMMDAfQwIo8KoMMoAAwwwwAADDLQZEEbha8Nn13qfXau1slYMMMAAA0cZEEaFUWGUAQYYYIABBhhoMyCMwteG76gdlnnt3hlggAEGGLiPAWFUGBVGGWCAAQYYYICBNgPCKHxt+Oxa77NrtVbWigEGGGDgKAPCqDAqjDLAAAMMMMAAA20GhFH42vAdtcMyr907AwwwwAAD9zEgjAqjwigDDDDAAAMMMNBmQBi9OL7fv39v4hjt8ZrtAqMtylmfUbfXvhqn/j47T2tlrRhggAEGrmhAGL1oGI1wOMoVnNq2dz7mqX1q3ax9dX31PtQYYIABBhhg4LsGhNGLhtFY2K1wOGvLdfl4Nd+sT/RV+oBhgAEGGGCAgaMN3CaMjtAUr3gocZ4DVa7L9TFmlLnPVv2qXx5Tj/OYelz7vnI+5lj1m7XN6vL42h7no4xX7u/YhxADDDDAAAMMHGngNmF0PIQITvmB5Lp8HH1q3d55XCf3y8cx71nl1rVr2zivdfk+Z22zMbN+eR7HPpQYYIABBhhg4F0GbhVGx5vOQSkf17Z4QLVP1Ef/WfusLo8783jvXkZ7vOI9ze5vNc+sflY3m1OdDyIGGGCAAQYY+K6BHxdGI5jlsj6kaBv1s+A1q6tzrM5j7lm5GrNV/9l7mfWf1cU1Z22zuuiv9KHDAAMMMMAAA+80cLswOt78CEuzwDSrqw+r9qnnMX8d13U+u7+te6n963kdO2uf1dVxzn0QMcAAAwwwwMA7DPz4MFqDVT4fx/k8HuisLtrOLvfuJbfn43Gf9fzVutm4s9+36/mAY4ABBhhg4BkGbhtGV0BHkMqvWb9oH22z46gb5Wz8GXX5HuJ4dd1Ve9TXcjZP7jNrV/eMDwTrbJ0ZYIABBs428OPC6NkP0PX80TLAAAMMMMAAA183cKswGr/eWfCvL7hn59kxwAADDDDAwJUM3CqMXunBuRd/yAwwwAADDDDAwPcNCKMX/78Dhfz7yD1Dz5ABBhhggIHrGhBGhdG2f0nLB8N1PxisjbVhgAEGGDjLgDAqjAqjDDDAAAMMMMBAmwFhFL42fGftuFzH7p4BBhhggIHrGhBGhVFhlAEGGGCAAQYYaDMgjMLXhs8u9bq7VGtjbRhggAEGzjIgjAqjwigDDDDAAAMMMNBmQBiFrw3fWTsu17G7Z4ABBhhg4LoGhFFhVBhlgAEGGGCAAQbaDAij8LXhs0u97i7V2lgbBhhggIGzDAijwqgwygADDDDAAAMMtBkQRuFrw3fWjst17O4ZYIABBhi4rgFhVBgVRhlggAEGGGCAgTYDwih8bfjsUq+7S7U21oYBBhhg4CwDwqgwKowywAADDDDAAANtBoRR+NrwnbXjch27ewYYYIABBq5rQBgVRoVRBhhggAEGGGCgzYAwCl8bPrvU6+5SrY21YYABBhg4y4AwKowKowwwwAADDDDAQJsBYRS+Nnxn7bhcx+6eAQYYYICB6xoQRoVRYZQBBhhggAEGGGgzIIzC14bPLvW6u1RrY20YYIABBs4yIIwKo8IoAwwwwAADDDDQZkAYha8N31k7Ltexu2eAAQYYYOC6BoRRYVQYZYABBhhggAEG2gwIo/C14bNLve4u1dpYGwYYYICBswwIo8KoMMoAAwwwwAADDLQZEEbha8N31o7LdezuGWCAAQYYuK4BYVQYFUYZYIABBhhggIE2A8IofG347FKvu0u1NtaGAQYYYOAsA8KoMCqMMsAAAwwwwAADbQaEUfja8J2143Idu3sGGGCAAQaua0AYFUaFUQYYYIABBhhgoM2AMApfGz671OvuUq2NtWGAAQYYOMuAMPrJMPr79+8/43XWArmODwMGGGCAAQYY+MkGhNFPhtGB4UphNMJxlD8Zq/fmw5gBBhhggIGfZ0AYXYTRrcC51XbmH8nsPmZ1Z96Ta/28Dwlrak0ZYIABBo40IIwKo/4rBwsDR/7hmdsHOwMMMMAAA/8xcJswOn7xq6/VIka/2p7r43iUuV+uj+PcPo5jTLTHee23Os/j6vFqzKx+dt1Z3WysOh+CDDDAAAMMMHAFA7cJo+NhRdCqZX6Q0Zb71/bcZ6tfHpePx/hX5shjjjqOe4nyqOuY1wcWAwwwwAADDBxh4EeF0RoQxwOrdfV81mdVFwvw6hzR/8gy30s+PvKa5vZhxAADDDDAAAPvMiCMTgLreLhbwW7WNqtbLdLou3qtxszqZ9ec1c3GqvMhwgADDDDAAANXMCCMLoLnVqibtc3qjl7g2TVndUffh/l9mDHAAAMMMMDAVw38qDA6HkIOY/k4HtBX6uqYel6vG9c6urzKfRz9Ps3vA44BBhhggIGfa+A2YXQErwhfuYzjjDT3ndXnMdE318WYaIvzUUZd7j+ry2OOPM7Xzvd05DXN/XM/EKyttWWAAQYYONvAbcLo2Q/G9fwxMsAAAwwwwAADxxsQRv0Pnv/X/86qP7rj/+g8Y8+YAQYYYICBDwPCqDAqjDLAAAMMMMAAA20GhFH42vDZFX7sCj0Lz4IBBhhg4KkGhFFhVBhlgAEGGGCAAQbaDAij8LXhe+oO0Pv26wcDDDDAAAMfBoRRYVQYZYABBhhggAEG2gwIo/C14bMr/NgVehaeBQMMMMDAUw0Io8KoMMoAAwwwwAADDLQZEEbha8P31B2g9+3XDwYYYIABBj4MCKPCqDDKAAMMMMAAAwy0GRBG4WvDZ1f4sSv0LDwLBhhggIGnGhBGhVFhlAEGGGCAAQYYaDMgjMLXhu+pO0Dv268fDDDAAAMMfBgQRoVRYZQBBhhggAEGGGgzIIzC14bPrvBjV+hZeBYMMMAAA081IIwKo8IoAwwwwAADDDDQZkAYha8N31N3gN63Xz8YYIABBhj4MCCMCqPCKAMMMMAAAwww0GZAGIWvDZ9d4ceu0LPwLBhggAEGnmpAGBVGhVEGGGCAAQYYYKDNgDAKXxu+p+4AvW+/fjDAAAMMMPBhQBgVRoVRBhhggAEGGGCgzYAwCl8bPrvCj12hZ+FZMMAAAww81YAwKowKowwwwAADDDDAQJsBYRS+NnxP3QF63379YIABBhhg4MOAMCqMCqMMMMAAAwwwwECbAWEUvjZ8doUfu0LPwrNggAEGGHiqAWFUGBVGGWCAAQYYYICBNgPCKHxt+J66A/S+/frBAAMMMMDAhwFhVBgVRhlggAEGGGCAgTYDwih8bfjsCj92hZ6FZ8EAAwww8FQDwqgwKowywAADDDDAAANtBoRR+NrwPXUH6H379YMBBhhggIEPA8KoMCqMMsAAAwwwwAADbQaEUfja8NkVfuwKPQvPggEGGGDgqQaEUWFUGGWAAQYYYIABBtoMCKPwteF76g7Q+/brBwMMMMAAAx8Gbh1Gf//+/We8LOjHgnoWngUDDDDAAAMM3MnArcPoeNB3DaMRpGt5Jzzu1YcdAwwwwAADDHzXgDDa9I/pZyF6VvfdBTbehwQDDDDAAAMMXNmAMNoURisKQdQHRTXhnAkGGGCAgScYuF0Yrf9Yu4a43F4XcNY2q6vj8nnuX49zv88cj3k+019fH04MMMAAAwww8FMM3CqMzkJbrsvHY4Hq+Wfqzlzg2X2eeX3X8oHGAAMMMMAAA10GflQYzQ9xBLxVyMv1+TiPP/P4Cvdw5vt1LR94DDDAAAMMMBAGflwYHcEuwl2U8WajzPX5ONq3ytF/9doat2r77PVX86j3R80AAwwwwAADdzTwo8JoDXb1PC9QBMpc13G8dY8d9+OaPsgYYIABBhhg4EwDtw6jNVDmYFfb6kPda6/9jzrP93zUNczrQ4UBBhhggAEGrmrgVmF0PMQIkRHi4jwecD7Px9EeZYyP867yKvfR9f5d14cjAwwwwAADzzZwuzD6LrBC4LPhv8uReThigAEGGGDgewYeF0a3fi2F6XuYPD/PjwEGGGCAAQY+a+BxYfSzD0h/f1QMMMAAAwwwwMBxBoTRi/zfgUJ+HHLP1rNlgAEGGGDgugaEUWHU/xUpAwwwwAADDDDQZkAYha8Nn13qdXep1sbaMMAAAwycZUAYFUaFUQYYYIABBhhgoM2AMApfG76zdlyuY3fPAAMMMMDAdQ0Io8KoMMoAAwwwwAADDLQZEEbha8Nnl3rdXaq1sTYMMMAAA2cZEEaFUWGUAQYYYIABBhhoMyCMwteG76wdl+vY3TPAAAMMMHBdA8KoMCqMMsAAAwwwwAADbQaEUfja8NmlXneXam2sDQMMMMDAWQaEUWFUGGWAAQYYYIABBtoMCKPwteE7a8flOnb3DDDAAAMMXNeAMCqMCqMMMMAAAwwwwECbAWEUvjZ8dqnX3aVaG2vDAAMMMHCWAWFUGBVGGWCAAQYYYICBNgPCKHxt+M7acbmO3T0DDDDAAAPXNSCMCqPCKAMMMMAAAwww0GZAGIWvDZ9d6nV3qdbG2jDAAAMMnGVAGBVGhVEGGGCAAQYYYKDNgDAKXxu+s3ZcrmN3zwADDDDAwHUNCKPCqDDKAAMMMMAAAwy0GRBG4WvDZ5d63V2qtbE2DDDAAANnGRBGhVFhlAEGGGCAAQYYaDMgjMLXhu+sHZfr2N0zwAADDDBwXQPCqDAqjDLAAAMMMMAAA20GhFH42vDZpV53l2ptrA0DDDDAwFkGhFFhVBhlgAEGGGCAAQbaDAij8LXhO2vH5Tp29wwwwAADDFzXgDAqjAqjDDDAAAMMMMBAmwFhFL42fHap192lWhtrwwADDDBwlgFhVBgVRhlggAEGGGCAgTYDjw2jv/726y0PfczzzrnO2oWsrvOd9/LVsfEMt8rV/Ub97Nqzuug/K2f9Z3Wzser8gsAAAwwwwMDXDAijf/31f2FyhI7Vq+LK/XJbrs/HuU8cj/Y4jvLVutE/z793HPO/Us7u4ZVx0ecr4/OYfPyZOb86Lq4xynfMkedz/LUPJc/Nc2OAAQaeZUAYnfwsPwsl+Q9j1T6rn9WNuWb1r9ble3nncVw/yq25R5/Pvlbz1evtndd5av9on91ftNUy5piNqXV1rPNnfWhab+vNAAMMvNfA48JoDRYRQjKsWd0r7bNxs7ox16z+1bp8L+86rteu53vXqf3r+db40XfvtRo/Gzf6zq4/q4t5V22r+hinfO8HkufpeTLAAAPPM/C4MBrIt0LGVtsYv2qf1c/qVnPM+s7q4j28q1xdY1Wfrxt9ooy2OI8y6t9d1vnHea2La27V57aYY1bGXMrnfVhac2vOAAMMHGNAGP3iP6avQWUAzYEmwM7qom+dY3Uecx1R1vvbO6/3EP2jjPZ8no+jfZSj/rOvPD7myHWra8365ro8Lh+/Onfu5/iYDyvP1XNlgAEGfqaBx4fRWfCY1eU/gFX7rH5Wl+fKx5/pm8d95Xhca3a9Vd2qPq5d2/fOY9wo9/rW9lfH1nH1fDXP6Ld65TGOf+aHonW1rgwwwMC5Bm4TRlfhIALGXnuFFf1r/TiPOWdtW+2zcbO6z8671T/ex6pcjV3Vv3q/r/aL62z1X917ro95apn7xHHuM+riPB9HXZS5LR9H+yhX9bmP43M/wDxvz5sBBhi4v4HbhNF3YRuBIl6rOfdCx6p9Vv9q3biXWd+t+tX9f6d+dQ+rOUf/vddqbNTXa+6dx7hR7vXN7fk4z1HnGf1WrzrO+f0/BK2hNWSAAQZ6DTwujAa4V4NJ9M9lHhuhZbTn+uj/at1q/FZ9XOOd5ex+9+ZfjVnV1/lGv71XHRPn9Rr1PPqN8tW2Vb9Vfb6G494PNM/f82eAAQbuZ0AY/ea/wJTR57AyjuOV+4zj3C+3fbY+j33X8eoe9uav4+r53vjc/pmxtW89f3XePG4cr155Psf3+8CzZtaMAQYYuJ4BYfSLYXSGOQeaWXvUrfp9tj7me2e5uodXrjHGxuuV/qNP9H+lnM05xuX6ev6VttUcq/p8DcfX+5CzJtaEAQYYuLYBYfQLYXSF+tWwMvp99rW65rvrX30P+brxXvbqcvvW8WfuIa6dy9XcW/Pmtnyc51rV5z6Or/2BZ32sDwMMMHA9A48LoyNQxKuCjPqvho6vjqv3Uc/rvPk+Xz2uc67O67W2+sW1V31GffSZzZvbXj2u16rz1vN8D3VsPo9xr9xHHuf4eh9q1sSaMMAAA/cy8LgwCui9gFov68UAAwwwwMDPNiCMTv4xPfQ/G731tb4MMMAAAwxcx4AwKoz+178A5I/zOn+c1sJaMMAAAww8wYAwKowKowwwwAADDDDAQJsBYRS+NnxP2O15j37VYIABBhhgYNuAMCqMCqMMMMAAAwwwwECbAWEUvjZ8dorbO0XPx/NhgAEGGHiCAWFUGBVGGWCAAQYYYICBNgPCKHxt+J6w2/Me/arBAAMMMMDAtgFhVBgVRhlggAEGGGCAgTYDwih8bfjsFLd3ip6P58MAAwww8AQDwqgwKowywAADDDDAAANtBoRR+NrwPWG35z36VYMBBhhggIFtA8KoMCqMMsAAAwwwwAADbQaEUfja8Nkpbu8UPR/PhwEGGGDgCQaEUWFUGGWAAQYYYIABBtoMCKPwteF7wm7Pe/SrBgMMMMAAA9sGhFFhVBhlgAEGGGCAAQbaDAij8LXhs1Pc3il6Pp4PAwwwwMATDAijwqgwygADDDDAAAMMtBkQRuFrw/eE3Z736FcNBhhggAEGtg0Io8KoMMoAAwwwwAADDLQZEEbha8Nnp7i9U/R8PB8GGGCAgScYEEaFUWGUAQYYYIABBhhoMyCMwteG7wm7Pe/RrxoMMMAAAwxsGxBGhVFhlAEGGGCAAQYYaDMgjMLXhs9OcXun6Pl4PgwwwAADTzAgjAqjwigDDDDAAAMMMNBmQBiFrw3fE3Z73qNfNRhggAEGGNg2IIwKo8IoAwwwwAADDDDQZkAYha8Nn53i9k7R8/F8GGCAAQaeYEAYFUaFUQYYYIABBhhgoM2AMApfG74n7Pa8R79qMMAAAwwwsG1AGBVGhVEGGGCAAQYYYKDNgDAKXxs+O8XtnaLn4/kwwAADDDzBgDAqjAqjDDDAAAMMMMBAmwFh9CR8v3//blvkJ+yqrvIerbNfMa5i0X2wyAADdzHwyDD669efP+N11iIJKN/7QBjP74hneOS8Z9lyne/Z8vw8PwYYYKDfgDB68C+jR4SoJ/7hHPUc7zbvE9fee+7/orAG1oABBo408Mgw+q4H+sqvq0eFnXe9h6vNs3peq/rv3v/d5v3u+zXeFwoDDDDAwNUMCKPf+GV0L4weFXSuhuid97N6Zqv67177qHnHfR0593fft/G+jBhggAEGrmLgNmE0//c84ziHwVpXz+OBr+pHe7Tl41EXY6OMfrmMtlyuwsioj1f0j/M8Jtfl+hgzytxnq37VL4+px3lMHNc++XzWJ9fF8SjzuHGc2+I494kx0Rbnuc8rx3l8HNdxUV+vMauf1cV8dXzUK30BMMAAAwww8GHgNmF0LFqEv7yANSzWPrU9xm7V17Z6vjdHtG+FkVlbrsvHq/lqn3o+xo26XJ+PY96tMvrXso6J9rhmbh9tuX3WJ/rXfrm+ttXz6LsqZ/1r3WfPx7XqmLj+qj7alR8fRJ6FZ8EAAww818DtwmjFWoNiPa/943zVb1Y/qxvzrOrjGnthJLfn4zG+nq/q8rU+OybGbpUxZy3zmGhb1e21r8bt1c/mzWPq8az/rC7GjbZZe67LxzEuyq226KN87oevtbf2DDDAwH8MCKPlvzM6C5izugFoVR+49sJIbs/HY/w4n71i7iijT4yJ+ijrvFH/ahnja5nHR9uqbq99NW6vfjZvHlOPZ/1XdVEfZZ4r1+Xj3Gccb7XVvs59KTHAAAMMPNWAMHpgGB2o9gLJaJ/1mdVVpLVPPX/l+nXOeh5z1jL3i7ZV3V77atxe/WzePKYez/rXur3zmHP0q32jbZRbbbmfY18+DDDAAANPN3C7MFp/jdw7Xy1wHRf9ZvWzutE/1+fjmGuUe6FkFWpm42pdPv/MPPX+8jy5Ld9/9Ily1S+PiT6zMbO6Ojb3ycereUefWb/P9M/jt+bbaqvvI66v9IXDAAMMMMDA/xq4XRgdiziCX7xiUeM8l9GWy9wex9Ee56Pcqou2UcaYXFePc8D5bFuEntUc0T7mnR1H3Wp8jKv3FfUxLpdxXMeM+toWdbl+Vpfnivaoi/NX5sh9Ynwu61xxPusz6mbtUZ/H5OO9e8h9Hf/vh5Jn4pkwwAADzzJwyzB6R6SrgLKqP/M9XuEe3vV+z3ovq+us6t/1/szzrA9o6229GWDgCQZuE0bjF8j8q+WdF2iElisElyvcw7vW8Yz3cpV1e9czM48vOgYYYICBbgO3CaPdD8r1/bEywAADDDDAAAPvNyCMln+bHrL3I/NMPVMGGGCAAQYYWFxVkUoAAANiSURBVBkQRoXR//+XtVZI1PsAYYABBhhggIGjDAijwqgwygADDDDAAAMMtBkQRuFrw3fUDsu8du8MMMAAAwzcx4AwKowKowwwwAADDDDAQJsBYRS+Nnx2rffZtVora8UAAwwwcJQBYVQYFUYZYIABBhhggIE2A8IofG34jtphmdfunQEGGGCAgfsYEEaFUWGUAQYYYIABBhhoMyCMwteGz671PrtWa2WtGGCAAQaOMiCMCqPCKAMMMMAAAwww0GZAGIWvDd9ROyzz2r0zwAADDDBwHwPCqDAqjDLAAAMMMMAAA20GhFH42vDZtd5n12qtrBUDDDDAwFEGhFFhVBhlgAEGGGCAAQbaDAij8LXhO2qHZV67dwYYYIABBu5jQBgVRoVRBhhggAEGGGCgzYAwCl8bPrvW++xarZW1YoABBhg4yoAwKowKowwwwAADDDDAQJsBYRS+NnxH7bDMa/fOAAMMMMDAfQwIo8KoMMoAAwwwwAADDLQZEEbha8Nn13qfXau1slYMMMAAA0cZEEaFUWGUAQYYYIABBhhoMyCMwteG76gdlnnt3hlggAEGGLiPAWFUGBVGGWCAAQYYYICBNgPCKHxt+Oxa77NrtVbWigEGGGDgKAPCqDAqjDLAAAMMMMAAA20GhFH42vAdtcMyr907AwwwwAAD9zEgjAqjwigDDDDAAAMMMNBmQBiFrw2fXet9dq3WyloxwAADDBxlQBgVRoVRBhhggAEGGGCgzYAwCl8bvqN2WOa1e2eAAQYYYOA+BoRRYVQYZYABBhhggAEG2gwIo/C14bNrvc+u1VpZKwYYYICBowwIo8KoMMoAAwwwwAADDLQZEEbha8N31A7LvHbvDDDAAAMM3MeAMCqMCqMMMMAAAwwwwECbAWEUvjZ8dq332bVaK2vFAAMMMHCUAWFUGBVGGWCAAQYYYICBNgPCKHxt+I7aYZnX7p0BBhhggIH7GBBGhVFhlAEGGGCAAQYYaDMgjMLXhs+u9T67VmtlrRhggAEGjjDwz3/+888//vGPP79GIvXyDBhggAEGGGCAAQbONDCC6L/+9a8/v/74jyfgCXgCnoAn4Al4Ap6AJ9D0BITRpgfvsp6AJ+AJeAKegCfgCXgCf/wyCoEn4Al4Ap6AJ+AJeAKeQN8T+DeWi1nvD71fUgAAAABJRU5ErkJggg==
5.2 了解nilnil类型表示没有任何有效值，只要是没有声明的值，它就是nil比如我打印一个没有声明的值，便会输出nil：data:image/png;base64,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
这里需要你思考一下，运行以下代码，将会输出什么结果？data:image/png;base64,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***T9EiXBlggAEGGGCAAQaGGygdWnq0/vlR7nx8fPzeWMrVjzFggAEGGGCAAQYYGGmgxGnp0frnd6DWB26NgBEwAkbACBgBI2AEjMDsERCos2fA8Y2AETACRsAIGAEjYAT+GIH/AEzoH4WUpULpAAAAAElFTkSuQmCC
5.3 赋值语句赋值是改变一个变量值的最基本的方法。如下面一样，使用等号对左边的变量进行赋值data:image/png;base64,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
Lua可以对多个变量同时赋值，变量用逗号分开，赋值语句右边的值会依次赋给左边的变量。data:image/png;base64,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
当左右值的数量不一致时，Lua会进行下面的设定：变量个数 > 值的个数：按变量个数补足nil变量个数 < 值的个数：多余的值会被忽略下面的例子可以展示这种设定：data:image/png;base64,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***7I9+f3NjUu5/yXdYUmfuWs7f74Frzs05AwwwsN6A8DoTXtuQEsdl234KyDhf41xTFv3UfdT7cf7sbbmn+Jx9L0dcf8Q5OOJ7u8b6h64xNIYMMMDAOgPC68LwuiasRKhbsu2B7l27V9Zre3TZqPe19Tjc5XtuPW76W/fANn7GjwEGGPjzIbwuCK8lqMSnoIn92NaQSll9PLW/tF5cr+3nlfZt2z2PR76vuLeyjU89FlEW9epz7f6SOm0bx/6mwwADDDDAwHoDlw2vdRBp9wuctqw+7sEq56O8tx9lsY26U9ul9Ur7Xt1e2dS1jiwf9b5iHNv7a4+j3tyY9drNtXF+/QPLGBpDBhhggIHLhtetcddhpezXn3KtOB/buH57/E55r49eWfR95nbU+ypj0ru3pWXtmPbatXUce8AywAADDDCwvQHhdeaPDQS6ElYisMS2nIv9dlu3i/16G/XrsrLfK19a1vZ1xnHvXs+4j941e/e2tKztr9eureN4+weWMTWmDDDAAAPC60x4LSElPvGDiePYlvKyX2/rurFfb6N+XVb2e+VLy9q+zjju3esZ99G7Zu/elpa1/fXatXUce8AywAADDDCwvQHhdSa8Bro6rPT2oyy2vXZRVrZtvTi3pHyqTvRx5jbbvfXut1fWjumSOm0bx9s/wIypMWWAAQbuZ0B43Si8xo+nDTXl+NVP9NVuo5+2fITjuLd6O8J9xT307qstq49jP9rHNsrrbZyzvd8D1JybcwYYYOB4A8LrivAaAabAjf2yXQN5bfs119b2+B+gMTfmDDDAAAMMvGZAeF0YXsF6DZbxMl4MMMAAAwwwsIcB4VV4XfWmeA+U+vSwY4ABBhhggIEpA8Kr8Cq8MsAAAwwwwAADaQwIr7CmwTq1AlNudc4AAwwwwMB9DAivwqvwygADDDDAAAMMpDEgvMKaBqtV9X1W1ebaXDPAAAMMTBkQXoVX4ZUBBhhggAEGGEhjQHiFNQ3WqRWYcqtzBhhggAEG7mNAeBVehVcGGGCAAQYYYCCNAeEV1jRYrarvs6o21+aaAQYYYGDKgPAqvAqvDDDAAAMMMMBAGgPCK6xpsE6twJRbnTPAAAMMMHAfA8Kr8Cq8MsAAAwwwwAADaQwIr7CmwWpVfZ9Vtbk21wwwwAADUwaEV+FVeGWAAQYYYIABBtIYEF5hTYN1agWm3OqcAQYYYICB+xgQXoVX4ZUBBhhggAEGGEhjQHiFNQ1Wq+r7rKrNtblmgAEGGJgyILwKr8IrAwwwwAADDDCQxoDwCmsarFMrMOVW5wwwwAADDNzHgPAqvAqvDDDAAAMMMMBAGgPCK6xpsFpV32dVba7NNQMMMMDAlAHhVXgVXhlggAEGGGCAgTQGhFdY02CdWoEptzpngAEGGGDgPgaEV+FVeGWAAQYYYIABBtIYEF5hTYPVqvo+q2pzba4ZYIABBqYMCK/Cq/DKAAMMMMAAAwykMSC8wpoG69QKTLnVOQMMMMAAA/cxILwKr8IrAwwwwAADDDCQxoDwCmsarFbV91lVm2tzzQADDDAwZUB4FV6FVwYYYIABBhhgII0B4RXWNFinVmDKrc4ZYIABBhi4jwHhVXgVXhlggAEGGGCAgTQGhFdY02C1qr7Pqtpcm2sGGGCAgSkDwqvwKrwywAADDDDAAANpDAivsKbBOrUCU251zgADDDDAwH0MDBNef37/enx9fXv8+JVn8D8/Px/l4wezfM6yjFmW+2RvuT1jZawYYICBaxgYILz+fHz/+np8//Hj8S1ZeC0/giuG172/05b9b9lX+1Dbqu/ST/1pr+P4Gg9T82geGWCAgWMMnB5ef37/623rL+H1SPS9YHZUwOpde+q7T9U94l6nrv3Kvfb66JVN9an8mAehcTbODDDAQB4Dp4fXv7EIr4f+8YNnAerZub/na8WfFX6l/7m6c+fX3O+rfffqLy1bc5/a5nngmitzxQADDKw3cPnwWsJDfPYAE+EkrhHHS69Vt2v3l/YR9er2UTa1fXafz85N9fdKefS/5H6j7lT/c+en2i0pj76X3GfpL+rP9b203lw/zq9/ABpDY8gAAwzkM3Dp8NqGhPZ4C7Clz7bf9niL68z10V6zPS7tS9nUp+6/17Y+v3Y/7qHup75mnO9t6zZlv27Xnlt7HNev+2mvF3V627pd7Lfto9w238PTnJkzBhhg4BwDlw6vNaoIF3XZFvu9MNIr2+JaS/tY8l2f3eOzc0vv4Vm9Xv+9stLHVHn0P3c+6r2z7fXdK4u+n50rdebORz+25zwMjbtxZ4ABBnIYuHx4LYEhQkNst8TZ67NXNnXNUnfqM9Vmqjz6Kefn7uHZ+Wfnpq79Snmv/17Z2u/xyj316vbuqVcWbd89F+1tczw0zZN5YoABBs41cHp4/fXj2+Prq/w3Xu***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**BZN7MGwMMMMDAlAHhdSa8toEyjuuQFvtlkON8PeBryqLP+hp136PsL/2Oo9yv+/BQZIABBhhgIKcB4XVheO2Fs6XoI3gu2T7rc809POt3i3O9e+uVbXEtfeR82Jg388YAAwwwsIUB4XVBeK1DZxn0+rgNaO3x1CQtrVe3f6dN3f7o/Wz3e/T4uJ6HOAMMMMAAA68buGx4LcFp6lOgTJ2bClx1eW8/ymI7h3Fpvbqfd9rU7Y/cz3SvR46La73+kDJmxowBBhhgoDZw2fBaf8kt9uswVvbrT+k/zsc2rtkev1teXyP6GHU79Z1HvV/35aHIAAMMMMBAHgPC68wfGwjMJZBFKIttORf77bZuF/v1NurXZWV/qnzuXNvPWcfP7v+se3LdPA8kc2WuGGCAAQbmDAivM+G1hLH4xGDGcWxLedmvt3Xd2K+3Ub8uK/tT5XPn2n7OOH5272fcj2t6ADLAAAMMMHA9A8LrTHgN9HUw6+1HWWx77aKsbNt6cW6q/FmbaHvmtnffvbIz79G1r/cAM6fmlAEGGLifAeF1o/AaP542sJXjVz/RV2x77ePcKNvePZayUe7Pfdzv4WbOzTkDDDBwTQPC64rwGoGt/Dhif21gW9veD/WaP1Tzal4ZYIABBhj4PwPC68LwCoyHBgMMMMAAAwwwcL4B4VV49Y/2GWCAAQYYYICBNAaEV1jTYLXaPX+1aw7MAQMMMMDA2QaEV+FVeGWAAQYYYIABBtIYEF5hTYP17JWe63vbwAADDDDAwPkGhFfhVXhlgAEGGGCAAQbSGBBeYU2D1Wr3/NWuOTAHDDDAAANnGxBehVfhlQEGGGCAAQYYSGNAeIU1DdazV3qu720DAwwwwAAD5xsQXoVX4ZUBBhhggAEGGEhjQHiFNQ1Wq93zV7vmwBwwwAADDJxtQHgVXoVXBhhggAEGGGAgjQHhFdY0WM9e6bm+tw0MMMAAAwycb0B4FV6FVwYYYIABBhhgII0B4RXWNFitds9f7ZoDc8AAAwwwcLYB4VV4FV4ZYIABBhhggIE0BoRXWNNgPXul5/reNjDAAAMMMHC+AeFVeBVeGWCAAQYYYICBNAaEV1jTYLXaPX+1aw7MAQMMMMDA2QaEV+FVeGWAAQYYYIABBtIYEF5hTYP17JWe63vbwAADDDDAwPkGhFfhVXhlgAEGGGCAAQbSGBBeYU2D1Wr3/NWuOTAHDDDAAANnGxBehVfhlQEGGGCAAQYYSGNAeHRNgzMAABHuSURBVIU1DdazV3qu720DAwwwwAAD5xsQXoVX4ZUBBhhggAEGGEhjQHiFNQ1Wq93zV7vmwBwwwAADDJxtQHgVXoVXBhhggAEGGGAgjQHhFdY0WM9e6bm+tw0MMMAAAwycb0B4FV6FVwYYYIABBhhgII0B4RXWNFitds9f7ZoDc8AAAwwwcLYB4VV4FV4ZYIABBhhggIE0BoRXWNNgPXul5/reNjDAAAMMMHC+AeFVeBVeGWCAAQYYYICBNAaEV1jTYLXaPX+1aw7MAQMMMMDA2QaEV+FVeGWAAQYYYIABBtIYEF5hTYP17JWe63vbwAADDDDAwPkGBgivvx4/vn09vr7++nz/mSZMfX5+PsoH5PMhmwNzwAADDDDAwD0MnB5ef/349vj249dfAfDn4/vXV3U8/iTcNbwK7uPb9BA3RwwwwAADVzRwenhtB/Xn96/HV7K3r+13uPpxHdjr/at/b9/P3wQYYIABBhg434DwuvLPvN4tvPW+b6/Mj/v8H7c5MAcMMMAAA1c0MFZ4/fn98fX17fHj13bYSrCKzx4TGMEtrhHHe1yr9Pnudep27f4r99r7fr2yV/pUdzvvxtJYMsAAAwxc3cA44fXXj8e3r6/H95/boWtDVXu8xeSWPtt+2+MtrlP6aPttj7e6zrN+etfslT3rw7ntjBtLY8kAAwwwcDcDY4TXv4Lr//+LW9tDLAFrj5DV67NXthbWHn2+c0+9++iVvdO3Ntu7N6bGlAEGGGDgagbOD687B9cSrCJcxXbLSez12Stbe821fZb2U59X7q13H72yV/pU14OVAQYYYIABBpYaOD28/u9/XSD+G69/b7f5c69tqGqPlw7Ss3q9Pntlz/pYcm6PPpdct63Tu49eWdvOsYcSAwwwwAADDGxh4PTwusWXmOqjDlVlvz4ubXplU31Nlbd9Rr91/S2uM9VvfZ2j9uvvXO8fdX3X8fBjgAEGGGDgvgYuHV4L7Do41vuBfm34ij7rbfRdb9deJ/qau07U23sb97H3dfR/34eTuTf3DDDAAAM9A5cPr70vXZdtFSrrPnv7R12nd21lfvwMMMAAAwwwcBUDtw6vRwXKo65zFZS+hwcsAwwwwAADDEwZuHV4nRoU5X4wDDDAAAMMMMDAmAaE15X/e1iwx4RtXswLAwwwwAAD1zQgvAqvDz/ua/64zat5ZYABBhi4ogHhVXgVXhlggAEGGGCAgTQGhFdY02C94urRd/JWhAEGGGCAgdcMCK/Cq/DKAAMMMMAAAwykMSC8wpoGq5XpaytT42W8GGCAAQauaEB4FV6FVwYYYIABBhhgII0B4RXWNFivuHr0nbwVYYABBhhg4DUDwqvwKrwywAADDDDAAANpDAivsKbBamX62srUeBkvBhhggIErGhBehVfhlQEGGGCAAQYYSGNAeIU1DdYrrh59J29FGGCAAQYYeM2A8Cq8Cq8MMMAAAwwwwEAaA8IrrGmwWpm+tjI1XsaLAQYYYOCKBoRX4VV4ZYABBhhggAEG0hgQXmFNg/WKq0ffyVsRBhhggAEGXjMgvAqvwisDDDDAAAMMMJDGgPAKaxqsVqavrUyNl/FigAEGGLiiAeFVeBVeGWCAAQYYYICBNAaEV1jTYL3i6tF38laEAQYYYICB1wwIr8Kr8MoAAwwwwAADDKQxILzCmgarlelrK1PjZbwYYIABBq5oQHgVXoVXBhhggAEGGGAgjQHhFdY0WK+4evSdvBVhgAEGGGDgNQPCq/AqvDLAAAMMMMAAA2kMCK+wpsFqZfraytR4GS8GGGCAgSsaEF6FV+GVAQYYYIABBhhIY0B4hTUN1iuuHn0nb0UYYIABBhh4zYDwKrwKrwwwwAADDDDAQBoDwiusabBamb62MjVexosBBhhg4IoGhFfhVXhlgAEGGGCAAQbSGBBeYU2D9YqrR9/JWxEGGGCAAQZeMyC8Cq/CKwMMMMAAAwwwkMaA8Doo1s/PzzSIYsWY8Z7j3m1fW/UaL+PFAAMMMHCWAeF1QXj9+Hg8yueoSdojBJY+9+i3HZMjrtFe07EHKAMMMMAAA/cxILwOFl73DH979l0/NI66Tn1N+/d5aJlrc80AAwzc24DwuiC8bvUjWfL2ds/gt2ff9RgddZ36mvbv/SAz/+afAQYYuI8B4XWg8Lp36Nu7//rBceS16uvav8/Dy1ybawYYYOCeBi4bXus/pxr79ZvPtqw9jh/EVHk5H+fq/VIWbWMb9eptnKu3c4GvnI9P3W7pfvQffcTx0vZ1vbk+1vRdX8f+PR9M5t28M8AAAwxMGbhseC1fOMJi/eXbcNnWac9H22fl7bn2eK6POP8s8LXn2uPo49m2tGnbtcfP2se5tk17XOr1yqK9rQcSAwwwwAADDLxr4PLhtR2YNli2x239OJ6q1yvvlZV+psrjGksDX6m3tG70Xba9Nr2yuk27v7T+0npt/449zBhggAEGGGDgmQHhtfOP+XsDNhU8e+W9stLnVHlcby7wlfNRJ7bRdsm216ZX9qyvpfWX1nt2Lec8vBhggAEGGGCgNSC8DhRey+RMhb62vD1uJ7Z33GvTK+u1jbIl9ZfUif5sPZQYYIABBhhg4BUDlw+v7dvOueOpwWvbRb1eea+s1K/L6/3oq2yngl9dXvbr42jXltX9Rp1nZb1+2/q9ftrrtse9PpR5UDHAAAMMMMDAOwYuH17LoJSgGJ8YpDiut3Gu3tbnYz/Ox3HZPiuLc2Ubbeqydn8q/NXhst6P9lPt6vPRLrZxLrZzfdT1en0sbR/92HpwMcAAAwwwwMArBm4RXl8ZkFHqvhMC32nTft81faxp296HYw8yBhhggAEGGOgZuGx4jTec9VvR3gBcpWyL4LhFH1cZT9/DA5MBBhhggIExDVw2vAI3JjjzYl4YYIABBhhgYI0B4fXA/z3smonS1g+dAQYYYIABBhj48yG8Cq9//8tmfhAeigwwwAADDDAwugHhVXgVXhlggAEGGGCAgTQGhFdY02AdfSXo/rytYIABBhhgYH8DwqvwKrwywAADDDDAAANpDAivsKbBajW7/2rWGBtjBhhggIHRDQivwqvwygADDDDAAAMMpDEgvMKaBuvoK0H3520FAwwwwAAD+xsQXoVX4ZUBBhhggAEGGEhjQHiFNQ1Wq9n9V7PG2BgzwAADDIxuQHgVXoVXBhhggAEGGGAgjQHhFdY0WEdfCbo/bysYYIABBhjY34DwKrwKrwwwwAADDDDAQBoDwiusabBaze6/mjXGxpgBBhhgYHQDwqvwKrwywAADDDDAAANpDAivsKbBOvpK0P15W8EAAwwwwMD+BoRX4VV4ZYABBhhggAEG0hgQXmFNg9Vqdv/VrDE2xgwwwAADoxsQXoVX4ZUBBhhggAEGGEhjQHiFNQ3W0VeC7s/bCgYYYIABBvY3ILwKr8IrAwwwwAADDDCQxoDwCmsarFaz+69mjbExZoABBhgY3YDwKrwKrwwwwAADDDDAQBoDwiusabCOvhJ0f95WMMAAAwwwsL8B4VV4FV4ZYIABBhhggIE0BoRXWNNgtZrdfzVrjI0xAwwwwMDoBoRX4VV4ZYABBhhggAEG0hgQXmFNg3X0laD787aCAQYYYICB/Q0Ir8Kr8MoAAwwwwAADDKQxILzCmgar1ez+q1ljbIwZYIABBkY3ILwKr8IrAwwwwAADDDCQxoDwCmsarKOvBN2ftxUMMMAAAwzsb0B4FV6FVwYYYIABBhhgII0B4XUB1o//fExO6LNzz1Zf77Z71qdz+6/2jLExZoABBhhg4FwDwuuK8BoBNLZTmHvnl5ZN9an83B+O8Tf+DDDAAAMMnGNAeJ0JryVk1p+A2obP9jjqlW3v3NKyup/s++U79753fK84/6xO1B15G99j6h7jfPbvOfX9lJ/zMDfuxp0BBu5iQHidCa8FQhsy2uPA8kp5r26vLPqO+5irU9cfbb/c+5L7X1JntO9W389dvmf9ne37myYDDDDAwFEGhNeZ8NoGqTiOgFJvy6TF+XoC15RFP3Uf9X6cv9L26t8v5uou3zO+r62/sTHAAAMMbGFAeF0YXtcEjdJ26ac3qb1r98p6bTOWXfm71fNxl+9Zf2f7/sbFAAMMMLDWgPC6ILyWkBGfMuCxH9t6EkpZfTy1v7ReXK/t55X2bdutj+txiP32/qbKe/fStu3VOaMsvkO5duy39zpV3rvftm2vjjIPeQYYYIABBv5p4LLhtQ4R7X5B0JbVxz0k5XyU9/ajLLZRd2q7tF5p36vbK5u61hHl5X7ae2qPp75Le3+9dm2ds47v8j3PGl/X/ecD2ngYDwYYYODfBi4bXree7DpQRYCJbblWnI9tXL89fqe810evLPo+Y9u7n6Vl7f322rV1zjru3dvSsvaee+3aOo7//dAyJsaEAQYYuLcB4XXmjw3ED6QEjQgbsS3nYr/d1u1iv95G/bqs7PfKl5a1fR15vPQee/Xa+1xSp21z1HHv3paWtffYa9fWcXzvB7T5N/8MMMDAvw0IrzPhtQSM+ASgOI5tKS/79bauG/v1NurXZWW/V760rO3ryOOl99ir197nkjptm6OOe/e2tKy9x167to7jfz+0jIkxYYABBu5tQHidCa/xA6mDRm8/ymLbaxdlZdvWi3NLyqfqRB9nbHv3tLSsvd9eu7bOWce9e1ta1t5zr11bx/G9H9Dm3/wzwAAD/zYgvG4UXgNXG0jK8auf6KvdRj9t+dnHcV9lG/fSltXHsR91Yxvl9TbOjbDt3VdbVh/HfnvvUV5v2zqO//2wMibGhAEGGGCgGBBeV4TXCB9lIGO/bNf8uNa2X3NtbT0UGGCAAQYYYGB0A8LrwvA6+kS6Pw8bBhhggAEGGLiDAeFVeF31pvgOPxLf0d8MGGCAAQYYGMeA8Cq8Cq8MMMAAAwwwwEAaA8IrrGmwWvWOs+o1F+aCAQYYYOAsA8Kr8Cq8MsAAAwwwwAADaQwIr7CmwXrWCs91vV1ggAEGGGBgHAPCq/AqvDLAAAMMMMAAA2kMCK+wpsFq1TvOqtdcmAsGGGCAgbMMCK/Cq/DKAAMMMMAAAwykMSC8wpoG61krPNf1doEBBhhggIFxDAivwqvwygADDDDAAAMMpDEgvMKaBqtV7zirXnNhLhhggAEGzjIgvAqvwisDDDDAAAMMMJDGgPAKaxqsZ63wXNfbBQYYYIABBsYxILwKr8IrAwwwwAADDDCQxoDwCmsarFa946x6zYW5YIABBhg4y4DwKrwKrwwwwAADDDDAQBoDwiusabCetcJzXW8XGGCAAQYYGMeA8Cq8Cq8MMMAAAwwwwEAaA8IrrGmwWvWOs+o1F+aCAQYYYOAsA8Kr8Cq8MsAAAwwwwAADaQwIr7CmwXrWCs91vV1ggAEGGGBgHAPCq/AqvDLAAAMMMMAAA2kMCK+wpsFq1TvOqtdcmAsGGGCAgbMMCK/Cq/DKAAMMMMAAAwykMSC8wpoG61krPNf1doEBBhhggIFxDAivwqvwygADDDDAAAMMpDEgvMKaBqtV7zirXnNhLhhggAEGzjIgvAqvwisDDDDAAAMMMJDGgPAKaxqsZ63wXNfbBQYYYIABBsYxILwKr8IrAwwwwAADDDCQxoDwCmsarFa946x6zYW5YIABBhg4y4DwKrwKrwwwwAADDDDAQBoDwiusabCetcJzXW8XGGCAAQYYGMeA8Cq8Cq8MMMAAAwwwwEAaA8IrrGmwWvWOs+o1F+aCAQYYYOAsA8Kr8Cq8MsAAAwwwwAADaQwIr7CmwXrWCs91vV1ggAEGGGBgHAPCq/AqvDLAAAMMMMAAA2kMCK+wpsFq1TvOqtdcmAsGGGCAgbMMCK/Cq/DKAAMMMMAAAwykMSC8wpoG61krPNf1doEBBhhggIFxDAivwqvwygADDDDAAAMMpDHwUnj97bffHr///nuaL2eVNM4qyVyYCwYYYIABBhhYa6Dk0JJH278+2oI4/uOPP/63QUm8PsaAAQYYYIABBhhg4EgDJbiWPNr+NRle24qOjYARMAJGwAgYASNgBIzA2SMgvJ49A65vBIyAETACRsAIGAEjsHgEhNfFQ6WiETACRsAIGAEjYASMwNkjILyePQOubwSMgBEwAkbACBgBI7B4BP4HHeu0TowWASIAAAAASUVORK5CYII=
这里需要你思考一下，运行以下代码，将会输出什么结果？data:image/png;base64,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
5.4 交换变量这部分需要你自己完成一个任务：已知下面的代码，并且已知a和b的值，请在交换他们的值，使打印输出12 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
5.5 输出变量我们已经知道了，在Lua中，可以使用print函数来打印你想要得到的结果。同时在上一节，我们学会了新建变量和设置变量的值。让我们试着输出某个变量吧！使用print函数，输出已知变量。 我们已知变量num为某个数字，试着输出它的值吧！data:image/png;base64,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
5.6 算数运算符运算符是一个特殊的符号，用于告诉解释器执行特定的数学或逻辑运算。上一节中，新建的数字变量，我们称之为number类型的变量。本节我们来学习使用算术运算符，如下所示：data:image/png;base64,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***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
我们可以通过以下实例来理解算术运算符的应用：data:image/png;base64,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***W01zQADDDDAAAPCqrAqrDLAAAMMMMAAA2UNCKtwls***W01zQADDDDAAAPCqrAqrDLAAAMMMMAAA2UNCKtwls***W01zQADDDDAAAPCqrAqrDLAAAMMMMAAA2UNCKtwls***W01zQADDDDAAAPCqrAqrDLAAAMMMMAAA2UNCKtwls***W01zQADDDDAAAPCqrAqrDLAAAMMMMAAA2UNCKtwls***W01zQADDDDAAAPCqrAqrDLAAAMMMMAAA2UNCKtwls***W01zQADDDDAAAPCqrAqrDLAAAMMMMAAA2UNCKtwls***W01zQADDDDAAAPCqrAqrDLAAAMMMMAAA2UNCKtwls***W01zQADDDDAAAPCqrAqrDLAAAMMMMAAA2UNCKtwls***W01zQADDDDAAAPCqrAqrDLAAAMMMMAAA2UNCKtwls***W01zQADDDDAAAPCqrAqrDLAAAMMMMAAA2UNCKtwls***W01zQADDDDAAAPCqrAqrDLAAAMMMMAAA2UNCKtwls***W01zQADDDDAAAPCqrAqrDLAAAMMMMAAA2UNCKtwls***W01zQADDDDAAAPCqrAqrDLAAAMMMMAAA2UNCKtwls***W01zQADDDDAAAPCqrAqrDLAAAMMMMAAA2UNCKtwls***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
你需要完成下面的任务：已知，一个长方体的长宽高分别为a、b、c（单位米），且这个物体重量为m（单位克）请打印出物体的密度（单位g/m³）注：密度计算公式 密度 = 质量 / 体积data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAqsAAADACAYAAAAjtypBAAAVxklEQVR4Ae3d267jtrIF0PVP/YP55PRbd17WBjdQnQJD6uJrmRoBDEkUSdnFsZxJ7+Ccr2//qIAKqIAKqIAKqIAKqEDRCnwVfV/elgqogAqogAqogAqogAp8C6sQqIAKqIAKqIAKqIAKlK2AsFp2abwxFVABFVABFVABFVABYZUBFVABFVABFVABFVCBshUQVssujTemAiqgAiqgAiqgAiogrDKgAiqgAiqgAiqgAipQtgLCatml8cZUQAVUQAVUQAVUQAWEVQZUQAVUQAVUQAVUQAXKVuBPWP39+/f3z58/v//++28vNWCAAQYYYIABBhh4qYGWQ1se7f/5E1Zbh1+/fn3/888/XmrAAAMMMMAAAwww8FIDLYe2PNr/8yestl9UBVVBnQEGGGCAAQYYYOBdBloe7f8RVu2abFIYYIABBhhggIESBoRVEEtAfNduzXP9UsAAAwwwwEBtA8KqsCqsMsAAAwwwwAADZQ0Iq3CWxWmnW3una32sDwMMMMDAKwwIq8KqsMoAAwwwwAADDJQ1IKzCWRbnK3ZrnuFXAQYYYIABBmobEFaFVWGVAQYYYIABBhgoa0BYhbMsTjvd2jtd62N9GGCAAQZeYUBYFVaFVQYYYIABBhhgoKwBYRXOsjhfsVvzDL8KMMAAAwwwUNuAsCqsCqsMMMAAAwwwwEBZA8IqnGVx2unW3ulaH+vDAAMMMPAKA8KqsCqsMsAAAwwwwAADZQ0Iq3CWxfmK3Zpn+FWAAQYYYICB2gaEVWFVWGWAAQYYYIABBsoaEFbhLIvTTrf2Ttf6WB8GGGCAgVcYEFaF1UuG1a+/vqafe+te/0d5pm8/Nq4fMUfM5ehfHAwwwAADqxkQVoXVaWhbDXv+PLOAOGvPY/vzW8Y8Y45+Ttf+hcUAAwwwsIIBYTWF1R8/fny31woL6zNsf0GNAuaoLdex3T/7yuPb+dnxe++pn9/19rqrj/owwAADn2dAWE1htQFeMaze+5kixMfxlj/0GBvHW+Z45Jg+BPbXo2cd6ZPHne2fxzr/vC9Ta2bNGGCAgecYEFYXDqsRDNvx1j+g0dhR29b8o/6jtq05Hn0vB8l8vvWcvt/Z637uNn726vu6fs4XoLqqKwMMMFDfgLC6cFiNP8B7guFo7KgtnjU6jvqP2kZjn9XWB80zz5kFzNx+ZL7Ze5i1H5lTn/pfutbIGjHAAAPnDCwXVlsIitctGCJExRxxfetcMc+Z8TFmdDwzT/S95zPEHPl473z3js/v5cx5DpNHz7fm70Nlf701tt3beg97Y90/90WnXurFAAMMfK6BpcJqH4L66yNQ25h+XH99dJ7c75Y58vh7zh/57HvmamNvGb8X6vbuj2qXg2U+H/XV9rlfcNbO2jHAAAOfb2CpsJpB3hqMRmFq1Jaf1Z+f7d+Pf/T1o95PtXnuqVMfUPvrrblb373XveNj/q153Pv8L2BraA0ZYICBfQPLhdUWqCJUxfEMhNGYUdvWnGf793O18bNX3/fI9b3vpz3jEXPk9/ro+fLcR85H4XTUNpqr77d33c/R9+/vx/XRftHfcf8LT43UiAEGGPg8A0uF1T4A9ddHgI7GjNq25jrbf2uuR9y79/08Y/y9c95bl1kQnLXn5/V99q7z2Hae+7fz/hX9c79oc/y8L1lrZs0YYICB+wwsG1ZbGOoD0aitB9SPafdz25E5+jGj6/65z7zO7z8/58hnGY3NbY+YI7+nV51HEIxjfu6obXY/+sax9cvneVyc5/v5vB/b34vxjvd96amf+jHAAAOfZWCpsNrw5fCUzwNmDlrRlo8xJh/z/Xa+N0f035oj+jzzmJ8f5/3z9j5LjOuPeZ69OVrfrfF5rledtyC4FQbP3h/NNWprny+3x3PyMWqQ+0Wb42d9wVov68UAAwzcb2C5sLqH4kiwesUce8941f2r1uOWIDgKlHmd8v04z/fj/Mizt8bHPI73fwGqoRoywAAD9Q1cKqxeNZjN/hDVo/4f6GzttFs7BhhggIGrGLhUWL3KovqcvsAYYIABBhhgYBUDwmr3/251lYX1OXxJMcAAAwwwwMAKBoRVYfV7Bcg+gy9kBhhggAEG1jQgrAqrwioDDDDAAAMMMFDWgLAKZ1mcdshr7pCtq3VlgAEGGDhjQFgVVoVVBhhggAEGGGCgrAFhFc6yOM/suvS1S2eAAQYYYGBNA8KqsCqsMsAAAwwwwAADZQ0Iq3CWxWmHvOYO2bpaVwYYYICBMwaEVWFVWGWAAQYYYIABBsoaEFbhLIvzzK5LX7t0BhhggAEG1jQgrAqrwioDDDDAAAMMMFDWgLAKZ1mcdshr7pCtq3VlgAEGGDhjQFgVVoVVBhhggAEGGGCgrAFhFc6yOM/suvS1S2eAAQYYYGBNA8KqsCqsMsAAAwwwwAADZQ0Iq3CWxWmHvOYO2bpaVwYYYICBMwaEVWFVWGWAAQYYYIABBsoaEFbhLIvzzK5LX7t0BhhggAEG1jQgrAqrwioDDDDAAAMMMFDWgLAKZ1mcdshr7pCtq3VlgAEGGDhjQFgVVoVVBhhggAEGGGCgrAFhFc6yOM/suvS1S2eAAQYYYGBNA8KqsCqsMsAAAwwwwAADZQ0Iq3CWxWmHvOYO2bpaVwYYYICBMwaEVWFVWGWAAQYYYIABBsoaEFbhLIvzzK5LX7t0BhhggAEG1jQgrAqrwioDDDDAAAMMMFDWgLAKZ1mcdshr7pCtq3VlgAEGGDhjQFgVVoVVBhhggAEGGGCgrAFhFc6yOM/suvS1S2eAAQYYYGBNA8KqsCqsMsAAAwwwwAADZQ0Iq3CWxWmHvOYO2bpaVwYYYICBMwaEVWFVWGWAAQYYYIABBsoaEFbhLIvzzK7r0/p+/fX13b9mn6HvN7qejdXu1wsGGGCAgU83IKwKq8LqEw2MgmVrO/PFkfvn85hj1Bb3HP1LigEGGGDg0w0Iq08MKp+Ow/t/zhfc2XDZ99+7tm7PWTd1VVcGGGDgPQaE1SeG1R8/fmz+gtbu7/Xxh/GeP4xH1L2FyrOv0XOPzDEap+1z7Vg7a8cAAwz8a0BYfUJYjRC6FUTzvXwO5784V61F/8voqp/T51rfsjW2xgww8AoDwuoTwmos3CyEjtpHbTGP42d/Gdz6y+iRcX0fVj7bivWzfgwwwMB/DSwTVlvY619nF7wfn6/PztX6t/GjcaP2UdtorLb/Iq5ek/6X1L3r/vPs9e/v9+Ndf54Za2bNGGCAgX8NLBNW26JG4OuP71rweB/980fto7Z+nOt/4T6zFi38zV7tubN7s9C41T/ubX2e6LN13Brv3mvcqLM6M8AAA88xIKz6zwCGv/76g3vcH1wLmbmee9e5bzvf69/f78e7ftxaqqVaMsAAA683IKymsNp+3Zy9bsE5+7V01D5qu+WZxrz+j2iv5i1M7r225tgbK6zWW/Ot9XTPejHAAAPnDAirKaw+Gs8sgI7aR22Pfj/mO/fH8ax63Rsu7x3/rM9l3hq+rIN1YICB1QwIq28Iqw1RDqf5fDVgV/88R34VjT6jWsW9I8fReG3+pcUAAwww8OkGlgmrLfBF6MvHOH/lQsV7ycfR8+P+6J62db9cWvC8Z33vHX/Ps41d16W1tbYMMFDVwDJhtWqBva/r/vEf+TW075O99PeOXOfxzq9rz9pbewYYWMmAsPrE/wxgJSg+iy8+BhhggAEGGHiHAWFVWL3rf5J+B1rP9GXJAAMMMMDAdQwIq8KqsMoAAwwwwAADDJQ1IKzCWRanXfN1ds3W2lozwAADDMwMCKvCqrDKAAMMMMAAAwyUNSCswlkW52yHpd3umwEGGGCAgesYEFaFVWGVAQYYYIABBhgoa0BYhbMsTrvm6+yarbW1ZoABBhiYGRBWhVVhlQEGGGCAAQYYKGtAWIWzLM7ZDku73TcDDDDAAAPXMSCsCqvCKgMMMMAAAwwwUNaAsApnWZx2zdfZNVtra80AAwwwMDMgrAqrwioDDDDAAAMMMFDWgLAKZ1mcsx2WdrtvBhhggAEGrmNAWBVWhVUGGGCAAQYYYKCsAWEVzrI47Zqvs2u21taaAQYYYGBmQFgVVoVVBhhggAEGGGCgrAFhFc6yOGc7LO123wwwwAADDFzHgLAqrAqrDDDAAAMMMMBAWQPCKpxlcdo1X2fXbK2tNQMMMMDAzICwKqwKqwwwwAADDDDAQFkDwiqcZXHOdlja7b4ZYIABBhi4jgFhVVgVVhlggAEGGGCAgbIGhFU4y+K0a77OrtlaW2sGGGCAgZkBYVVYFVYZYIABBhhggIGyBoRVOMvinO2wtNt9M8AAAwwwcB0DwqqwKqwywAADDDDAAANlDQircJbFadd8nV2ztbbWDDDAAAMzA8KqsCqsMsAAAwwwwAADZQ0Iq3CWxTnbYWm3+2aAAQYYYOA6BoRVYVVYZYABBhhggAEGyhoQVuEsi9Ou+Tq7ZmttrRlggAEGZgaEVWFVWGWAAQYYYIABBsoaEFbhLItztsPSbvfNAAMMMMDAdQwIq4Ow+vXX1zTAbd3LfzhH++Uxs/M21yPmu3WOflx/PXvf0T7qP2qL/qPjqP+obTS2b7t1XJ7nEXPk+Zxf50vXWltrBhhg4JwBYXUQVhuiHEba+ew1A3d0fO6X58rPm7XP+vTvP8aPnjVqi/5x7Pv019Fvdhz1H7XNxrf2Uf9RW56j3T/7yuP3zveevzfe/XNfVuqlXgwwwMA1DQirB8Jq/uM4GlC2+m3di2fN+ozaH93Wv4d+/nY9esW4/tiPb/dHbf24uJ713XsPs3Exb3/c6j961qytn9f1Nb9crbt1Z4ABBh5jQFidhNUMbBZKRuFm1DfP1c5H4472GY19dFu8l5g3jvm9R1t/jLFxjPsxtl3PXjEmH0d9Y67cb9a21ye/v75vvs798nn0GbXFPcfHfFmpozoywAAD1zQgrB4Iq/mP42go2eq3dS+eNeszan90W34Pbe78yvfaeTw7jnE/jmfbY1wc+/Htum+b9W3t0TeOe20xV3+M5x459mNdX/PL1bpbdwYYYOAxBoTVLqzmMNKQ5evZ+Qhj6ztqjzln96J99KzZ2NGzRuNnbfHM/hjzxjHfj7b+2PeJ+6P20b3cr533ffrr3H90L9riGP3769Gzom9/7+zYPI/zx3xxqaM6MsAAA9cxIKx2YTXwjwJJ3DtyjPFxzGNGbfl+O5/1GbWP2vr5tubc69***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
六、字符串6.1 string 类型变量字符串（即string），就是一串文本数据，可以存储你要的文本。在第二节中，print出的数据就是一个字符串。Lua 语言中字符串可以使用以下三种方式来表示：单引号间的一串字符双引号间的一串字符[[和]]间的一串字符你可以参考下面的例子来深入理解：data:image/png;base64,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**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***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***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
接下来你需要完成下面的练习：新建三个变量s1、s2、s3分别存入字符串数据：str、abc、233，使输出打印正确data:image/png;base64,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***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
6.2 转义字符在上一节中，我们学习了如何声明字符串。但是我们有时候会遇到一些特殊的问题，如：如何输出单引号和双引号？如何输出回车换行？也许我们可以用下面的方式简单规避，输出单引号时，声明字符串用双引号括起来，像下面这样data:image/png;base64,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
同理，输出双引号时，声明字符串用单引号括起来，像下面这样data:image/png;base64,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
但是，这样会出现一个问题：如何同时显示单引号和双引号？这里就需要转义字符登场了。转义字符用于表示不能直接显示的字符，比如后退键、回车键、等。以 \ 开头的都是转义字符，下面时常用的转义字符格式：data:image/png;base64,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**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
例如，如果我们想给str赋值一个单引号，一个双引号（'"），那么我们可以这样写：data:image/png;base64,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
下面需要你来完成一个简单的任务：新建一个变量str，给str赋值为ab\cd"ef'g\h]]并打印出来data:image/png;base64,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
6.3 string拼接字符串和字符串可以相加吗？可以！我们可以用拼接符号来将两个独立的字符串拼起来。我们使用..来表示字符串拼接符号，如下面的示例代码：data:image/png;base64,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
下面你要完成这个任务：已知三个字符串变量s1、s2、s3请将他们按顺序拼接起来，存入all，并使用print输出结果data:image/png;base64,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**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
6.4 number转string上面一节学习了如何拼接字符串，这个方法固然很好用，但是有时候我们会遇到一个需求，那就是把number类型的变量和string类型的变量拼接起来，组成一个新的string比如下面的变量n和s，如何拼接起来呢？data:image/png;base64,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
我们可以直接将number类型的变量n转换成string类型的值，这样就可以拼接了使用tostring(value)函数即可实现这一操作：data:image/png;base64,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
下面你要完成这个任务：已知三个变量n1、s、n2然后将他们按顺序拼接起来，存入变量result，使输出结果正确小提示：在某些情况下，Lua会自动将number类型转换成string类型data:image/png;base64,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
6.5 string转number上面一节学习了如何将number转成string，这一节我们来学习如何将string转成number比如下面的变量s，存储的内容是一个字符串，但是代表了一个数字，如何转成number再与n相加计算呢？data:image/png;base64,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
我们可以直接将string类型的变量s转换成number类型的值，这样就可以计算了使用tonumber(value)函数即可实现这一操作：data:image/png;base64,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
下面你要完成这个任务：已知三个字符串变量s1、s2、s3，其内容均为纯数字请计算他们的算术和，赋值给新建的变量result，使下面代码输出正确结果data:image/png;base64,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
七、逻辑运算
7.1 布尔型和比较运算布尔型（boolean）只有两个可选值：true（真） 和 false（假）Lua 把 false 和 nil 看作是false，其他的都为true（包括0这个值，也是相当于true）Lua 中也有许多的关系运算符，用于比较大小或比较是否相等，符号及其含义如下表：data:image/png;base64,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**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**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**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**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***SfTf6X/W85f/5r83zzGRNHqIHJXY0AG5dc4NvpB7BocXmF8XLONvTq/CnZZ1NvlqbkcCOlW5lC+tB/87tuXxtv74brVTS+5yuSh90XaP8J62zeZ7mbBeu/xoqPj8nYpWOIeafdQir1UGKRiwHl6bfaW7yezR6byS7JtGP9O8VloOLaEe2KPxFTtW9uvRerVGj4jT7zh5gwRvzQ/GnPG+X/5Jf8oKeRRh5nwCg84ZJ3ubP0W/xv/xDVNX/mNRZtLo97dmzANSPJBnZfstvL1nPttf0PBelw41vhLNE1BUoPmPFnpkOs21YawsPZ4ji0wNoSV2+focs6csuB6IyekWHyrDRy5q+soZONAaTa0Grvtw3X7tudXE+PYkmhtcpEkVN+Q6EMqSCnzq8iJp3heLNhDJdnYvcmRd/Lx1eqrlDDNPUzMVHW5zl0NbJph7WPsi+wvG6eNtukiHFCezsXfq4fdvcXLeX7V2OKBHp5gh/9Na34jnmKu//iz9Gs/mIJFyx62Vc4YjpEbOW/Z/dt/vC8TwqvsQXWe5AI37MtWljM2ivir/JksLVlkezHWjhtfRY6a4XCozS1mYOEo+W4lr5SxrYyj+z/FnLEr+1L7INoRc6vyeYiE8Ge6NOvRXwTIsZ/o7I2JlumRr2zNdvF3WI9srNXNGm/v77lOAdcG2575aex5Cfw/IYhDsOvALosHmWbDlHtrjTN0cQ/TtTUm7+WkLxtcsy6HUFNQhcOqt1mSgsiJq3eJUDb7YL7LONmRdNmOgapzv8YkkfMK1s7WsJo9VLbiZet+a4H2VXtnz9UZsRgsO8q+kDcYK7EjNAKvJj5l7s43CiJPXmPMNYfaRBH91fFyYb4o+0hzHRWIAiLc1592xfHbe1amx1eXSzNCXUgxZgroKMMWn2pavl/eOAYbh3PaNeIc4+si+ULmQU7krpkX4bZhc4u+3+9pNz/LFIf5Pfg/6ejk+Ryn4t+w571cGfsM62K3nHmur3fEhDC+g1dbs1GwzjrNJpTune+cINmkEribH42siA2y2nff8kV9Z8M4ci7VJW4kd/M4i012yea0dkVdR98NNMlN7LKFQFTBjK1qqQ0fbIrj0sEmOlWf1Sdb4740V3QJ9ogcV6+qiNuSud16JrnpyWmOPZzroSK6dTIlMdpXby32hUZe2kN/WabN38TNT1hybhEZjxIv0Z4z80WK1ZTXUtvGdUG/3jCFw3TsO2+I1xc6xt1LmIsFEoezrLp4lRzh+D7JHuRZNR7/izee65WC9eH8rQotOQzVRv86c9O6trC8aL2Jpx8xwdnCaViEOtrsGetM393191/mTUV60jCb/OUHZ97BY1l4BWjvn1qw7rblribcal8kSNY3I3TBZ80B/7DxcmG+sFz2Fp6SEydyTOer784ZnQLndlzIPC87G8v9pzfyAMV5sLLXJPy/l9hDjKdgfQg3YgQEIAABCEAAAhB4XAIUrI/rWyyDAAQgAAEIQAACD0GAgvUh3IgREIAABCAAAQhA4HEJULA+rm+xDAIQgAAEIAABCDwEAQrWh3AjRkAAAhCAAAQgAIHHJUDB+ri+xTIIQAACEIAABCDwEAQoWB/CjRgBAQhAAAIQgAAEHpcABevj+hbLIAABCEAAAhCAwEMQoGB9CDdiBAQgAAEIQAACEHhcAhSsj+tbLIMABCAAAQhAAAIPQYCC9SHciBEQgAAEIAABCEDgcQlQsD6ub7EMAhCAAAQgAAEIPAQBCtaHcCNGQAACEIAABCAAgcclQMH6uL7FMghAAAIQgAAEIPAQBChYH8KNGAEBCEAAAhCAAAQelwAF6+P6FssgAAEIQAACEIDAQxCgYH0IN2IEBCAAAQhAAAIQeFwCFKyP61ssgwAEIAABCEAAAg9BgIL1IdyIERCAAAQgAAEIQOBxCVCwPq5vsQwCEIAABCAAAQg8BAEK1odwI0ZAAAIQgAAEIACBxyVAwfq4vsUyCEAAAhCAAAQg8BAEKFgfwo0YAQEIQAACEIAABB6XAAXr4/oWyyAAAQhAAAIQgMBDEKBgfQg3YgQEIAABCEAAAhB4XAIUrI/rWyyDAAQgAAEIQAACD0GAgvUh3IgREIAABCAAAQhA4HEJULA+rm+xDAIQgAAEIAABCDwEAQrWh3AjRkAAAhCAAAQgAIHHJUDB+ri+xTIIQAACEIAABCDwEAQoWB/CjRgBAQhAAAIQgAAEHpcABevj+hbLIAABCEAAAhCAwEMQoGB9CDdiBAQgAAEIQAACEHhcAhSsj+tbLIMABCAAAQhAAAIPQYCC9SHciBEQgAAEIAABCEDgcQlQsD6ub7EMAhCAAAQgAAEIPAQBCtaHcCNGQAACEIAABCAAgcclMFWwhkH8gwExQAwQA8QAMUAMEAPEwK1iQJfjf+gL2hCAAAQgAAEIQAACEDgagf8PEeZhKvylfo8AAAAASUVORK5CYII=
我们可以通过以下实例来更加透彻的理解关系运算符的应用：data:image/png;base64,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**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
下面问题来了，运行以下代码，将会输出什么结果？请自行思考data:image/png;base64,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
7.2 逻辑运算符逻辑运算符基于布尔型的值来进行计算，并给出结果，下表列出了 Lua 语言中的常用逻辑运算符：data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAqkAAAEUCAYAAAAImq/xAAAgAElEQVR4Ae2da24jt9KGv23kp9cWIDAwewkGA69jAmcd49lB/p4gs4n+wMtLFotk62LZ6m49B5ijbjYvVU8VyVeUrPzfwv8gAAEIQAACEIAABCCwMQL/tzF7MAcCEIAABCAAAQhAAAILIpUkgAAEIAABCEAAAhDYHAFE6uZCgkEQgAAEIAABCEAAAohUcgACEIAABCAAAQhAYHMEEKmbCwkGQQACEIAABCAAAQggUskBCEAAAhCAAAQgAIHNEUCkbi4kGAQBCEAAAhCAAAQg0IjUf/75Z+EfDMgBcoAcIAfIAXKAHCAH7pkDQaJ3IvXRdHsIAP+DAAQgAAEIQAACENgGAWkzRCoidRsZiRUQgAAEIAABCEBgWeKn+gEEIhWRyoSAAAQgAAEIQAACmyHASWoOhUBsJjIYAgEIQAACEIAABB6YgLQZJ6mcpD7wNMB1CEAAAhCAAAS2RgCRmiMiEFsLEPZAAAIQgAAEIACBRyQgbcZJKiepj5j/+AwBCEAAAhCAwEYJIFJzYARio3HCLAhAAAIQgAAEIPBQBKTNOEnlJPWhEh9nIQABCEAAAhDYNgFEao6PQGw7XFgHAQhAAAIQgAAEHoOAtBknqZykPkbG4yUEIAABCEAAArsggEjNYRKIXUQNIyEAAQhAAAIQgMDBCUibcZLKSerBUx33IAABCEAAAhDYEwFEao6WQOwpeNgKAQhAAAIQgAAEjkpA2ux9J6n/vi7PT0/L05fX5Zcj9fbtaXl6elpefroH5fbX8vol1Qn11v+9LG+l3W0vBOJdvf58qfZ/u9TSzGHA8F020RgCEIAABCAAAQjskIC02TtE6kxkPi+vP7N47cTn8/L6r2ipvS3Ts/wqEfy0YZFabKxCey7Mk19RwEuUmvbPf0vqvy0vkd0KG4eKWwhAAAIQgAAEIHAEAu8Wqb/+fi4npbpOIsuIT4nV4emiqVeEq0NbBNw2Rar8fnrKYrLY+7RUwTnzyQjQchKb/fT3rgtuIQABCEAAAhCAwFEJvFO**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
我们可以通过以下实例来更加透彻的理解逻辑运算符的应用：data:image/png;base64,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
下面问题来了，运行以下代码，将会输出什么结果？data:image/png;base64,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
7.3 检验大小（自测题）题目：如果已知number变量n，那么如果需要判断n是否符合下面的条件：3<n≤10</n≤10以下四行判断代码，正确的是？（返回true即表示变量n符合要求）data:image/png;base64,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
八、分支判断
8.1 条件判断上面一节学习了布尔类型，那么这个需要用到哪里呢？我们需要用它来进行某些判断。在Lua中，可以使用if语句来进行判断，如下面所举例的代码，可以判断n是否为小于10的数：data:image/png;base64,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
我们整理一下，实际上if语句就是如下结构：data:image/png;base64,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***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
下面是你需要完成的事：已知变量n，请判断n是否为奇数，如果是，请给n的值加上1如果你觉得有难度，请查看下面的提示：求出n除以2的余数：n % 2给n的值加上1：n = n + 1data:image/png;base64,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**//r3Ssx8ANTzUel2/6q9zUr9nbtaMcqxbrV311/W1fu/8XP8rexxds47Ver3erfcw1uXV19X2PfvXdWfr9+xf59b6uFZvn72+eZ/zh82z9qwZuIaBtw+p9R/PB+WsL2PfXdZrf8K3qM8MDI/sNdZkXco847RTpv+ovGfu2CfzU9a+o+tkrK5LXy3reK3XOaM+xvorc47WZU72qO1aP7tHXdPrR3v0sdqu9bFnb/fraF/jj5Pn6DkywMDbh1SIfx5xDwmjfet15jn1fY/W5Hp9TvZImfHeTn/K7HdrXuaPss+te6zqR+vrWK3XvWp/rc/eS8b7WPp7OZt35tp9n94+s0e9dubXfdKXso6p//xngHvunjPAwE8YEFKf+I/7f+KBuYYPBgYYYIABBhj4BANCqpD68L+T+gm/IH5GfwgYYIABBhh4jQEhVUgVUhlggAEGGGCAge0MCKlQbofSifU1J1b33X1ngAEGGNjJgJAqpAqpDDDAAAMMMMDAdgaEVCi3Q7nTKc578a0CAwwwwAADrzEgpAqpQioDDDDAAAMMMLCdASEVyu1QOrG+5sTqvrvvDDDAAAM7GRBShVQhlQEGGGCAAQYY2M6AkArldih3OsV5L75VYIABBhhg4DUGhFQhVUhlgAEGGGCAAQa2MyCkQrkdSifW15xY3Xf3nQEGGGBgJwNCqpAqpDLAAAMMMMAAA9sZEFKh3A7lTqc478W3CgwwwAADDLzGgJAqpAqpDDDAAAMMMMDAdgaEVCi3Q+nE+poTq/vuvjPAAAMM7GRASBVShVQGGGCAAQYYYGA7A0IqlNuh3OkU5734VoEBBhhggIHXGBBShVQhlQEGGGCAAQYY2M6AkArldiidWF9zYnXf3XcGGGCAgZ0MCKlCqpDKAAMMMMAAAwxsZ0BIhXI7lDud4rwX3yowwAADDDDwGgNCqpAqpDLAAAMMMMAAA9sZEFKh3A6lE+trTqzuu/vOAAMMMLCTASFVSBVSGWCAAQYYYICB7QwIqVBuh3KnU5z34lsFBhhggAEGXmNASBVShVQGGGCAAQYYYGA7A0IqlNuhdGJ9zYnVfXffGWCAAQZ2MiCkCqlCKgMMMMAAAwwwsJ0BIRXK7VDudIrzXnyrwAADDDDAwGsMCKlCqpDKAAMMMMAAAwxsZ0BIhXI7lE6srzmxuu/uOwMMMMDATgaEVCFVSGWAAQYYYIABBrYzIKRCuR3KnU5x3otvFRhggAEGGHiNASH1Q0LqP//pTw+H0VtrvzI+1h6tPxobHxq3xvPBMps368v8Xs7mzvr6Ou3XfLC57+47Awww8P4GhNQXh9Q//vhjGh4TgFJ+9Zft3n3q/FU976mOz/r6+GjnlflHZV+fuav+jNdyNnfWV9fU+mzurK+uqfXMTVnHvlJf+fnKnta+/we7Z+gZMsDAFQwIqSWk/vr1+/d4/dSDXQWMBJmU976fse7e1+wauX4v+9yM1/5cf/RlvJd1fq9n/T1l3yPtXDftlLO9M1bLrJ/N7311Xep1ffqeWa4cPfMa9vIHjwEGGGDgpw0IqS8KqUfB4tmhJvs9imu2vvbVeq6RvlHm1cfS/s4y167luN5o9+vO+lZzj/pX+6727/MfaR95emQ/a/wxYoABBhh4tQEhtYTUZz2MM9/GrkJFgkzKr76n2T6zvn6dMWf1GnPrHrWefWpfrfe1mT8rx7rZq8/t+9fxPpb96pzU+9zR3+enPSuzTy2zZ8o69sz6ytMzr2Evf7AYYIABBn7SgJD6gpD6k4FiFo5mfUfoZvNrX61nn9E3e43xWf9qj+yXMvNSZr+M97LOe3Ru3aPW67VW/XXOd9d/0tV3/yz294eQAQYYYODtQ2r990hTr99k9r7ezi/Bqn+MZ6zWR1/Wpsy8Wmaslo+GiRGEEoZST7vun3rmpJ3yaE3m1HI2v/bVetbVvlof47Vd61mbcjaWvpR9v6xNWef1uUdjWT9bM9bNXnXNs+rDSryknna/xqq/z9P2wc8AAwww8A4G3j6kjpucUFhveA+RfU4fz9qj/j7W27f2yPhXwkTCUfYaZQ9btS9jWTcr616zevaoY7Wv1jMnfaPMq4+NduZlrJZZ18u+7t49+jXSXu1T+2s96/r7qf3PqCec1r1mhmZ9dY26P0oMMMAAA+9k4DIhtd/0HiB7u89PezVv1j/rG/us+nONr4SJWUjqfbVd67n+rC9joxzjR6/MyZrZfllf52ZeyjqWvWpZ56U/fSnv3aOu62v7WL9m5o95s1fmP7uceTnb9+z3Yj9/4BhggAEGfsqAkNr+ndRVwJz1z/rGg1v156HOAkbGbpWzIDXryz6zsVlf5vdyNbf213rW177Ueznmpi/rajkbS1/Ke/eo6+q1jvapa2q9rl/11zmP1mdezvY9ek3r/BFigAEGGHi1ASH1BSF1PPRZyDiDYRaGZn3ZazY268v8Xp6ZO5tT+2p97F/btT679hjvr3v3qPveul6dm3pd099LbWf+s8uZld7X289+D/bzx4oBBhhg4KcNXCak9m8vb7VXN7qvy7xZ/6xvzK/9tZ69RvloqKiBKfvN+o7GjuZn3Si/Mq+urfW+bx+7df3Z/Flf9uljvZ15/X2t+lfrV/11n1l9OLhlYTbe+3p7di19/sAwwAADDLyTgcuE1HHTRyDMKw8h7VpmrJZ1PPWMpz3Ko76MjTJral+v3xssRhDKK3ulvQpJdfyonv1SrvbLeC1nc2d9Y03v7+1H9r21xxivr3qNWl/tU/tr/czaOmdVP3IwxvLK+rSzLmXGlf4IMcAAAwxcwcClQuo7PpDvDhirUHV0r86uGfPy6vulv5ezeb0v7bG21rPXUV/GUtY9Rl9vp2/W3/fI9Y/KrLmn/IqBr6y95z2a6w8eAwwwwMBPG3j7kJpvLOu3nD99E13PL+6jBoRMdh61Yx07DDBwdQNvH1Kv/oD8fD6EGGCAAQYYYOATDQip7b/d/4kI/Mw+/BhggAEGGGBgNwNCqpD63//e5244vR8fmAwwwAADDHyuASFVSBVSGWCAAQYYYICB7QwIqVBuh9Kp+XNPzZ69Z88AAwwwEANCqpAqpDLAAAMMMMAAA9sZEFKh3A5lTlBKp2kGGGCAAQY+14CQKqQKqQwwwAADDDDAwHYGhFQot0Pp1Py5p2bP3rNngAEGGIgBIVVIFVIZYIABBhhggIHtDAipUG6HMicopdM0AwwwwAADn2tASBVShVQGGGCAAQYYYGA7A0IqlNuhdGr+3FOzZ+/ZM8AAAwzEgJAqpAqpDDDAAAMMMMDAdgaEVCi3Q5kTlNJpmgEGGGCAgc81IKQKqUIqAwwwwAADDDCwnQEhFcrtUDo1f+6p2bP37BlggAEGYkBIFVKFVAYYYIABBhhgYDsDQiqU26HMCUrpNM0AAwwwwMDnGhBShVQhlQEGGGCAAQYY2M6AkArldiidmj/31OzZe/YMMMAAAzEgpAqpQioDDDDAAAMMMLCdASEVyu1Q5gSldJpmgAEGGGDgcw0IqUKqkMoAAwwwwAADDGxnQEiFcjuUTs2fe2r27D17BhhggIEYEFKFVCGVAQYYYIABBhjYzoCQCuV2KHOCUjpNM8AAAwww8LkGhFQhVUhlgAEGGGCAAQa2MyCkQrkdSqfmzz01e/aePQMMMMBADAipQqqQygADDDDAAAMMbGdASIVyO5Q5QSmdphlggAEGGPhcA0KqkCqkMsAAAwwwwAAD2xkQUqHcDqVT8+eemj17z54BBhhgIAaEVCFVSGWAAQYYYIABBrYzIKQ+gP**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
8.2 多条件判断上面一节学习了简单的if语句写法，这一节我们来学习多条件分支语句在Lua中，可以使用if语句来进行判断，同时可以使用else语句，表示多个分支判断data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAqwAAAF6CAYAAADcTQqfAAAgAElEQVR4Ae3d3a7jOLIm0Hyn/f7v1HVX1Td7wAZiEBWHlORtpTIkrwYMUfyTk1z2/ugpnPn17X9WwApYAStgBayAFbACVqDxCvxq/N68NStgBayAFbACVsAKWAEr8C2wQmAFrIAVsAJWwApYASvQegUE1tbb481ZAStgBayAFbACVsAKCKwMWAErYAWsgBWwAlbACrRegX8F1n/++ef7r7/++v7Pf/7jZQ0YYIABBhhggAEGLjUwcujIo/V//wqso9Pff//9/d///t**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
举个例子，比如有一个数字n：当它大于等于0、小于5时，输出太小，当它大于等于5、小于10时，输出适中，当它大于等于10时，输出太大，那么代码就像如下这样：data:image/png;base64,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***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***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***zf35tYIABBhhg4PkGhFPhVDhlgAEGGGCAAQbKGBBOYSyD0W70+btRa2yNGWCAAQaqGxBOhVPhlAEGGGCAAQYYKGNAOIWxDMbqOzn359cGBhhggAEGnm9AOBVOhVMGGGCAAQYYYKCMAeEUxjIY7Uafvxu1xtaYAQYYYKC6AeFUOBVOGWCAAQYYYICBMgaEUxjLYKy+k3N/fm1ggAEGGGDg+QaEU+FUOGWAAQYYYIABBsoYEE5hLIPRbvT5u1FrbI0ZYIABBqob+Ec4/euvv4QVgZUBBhhggAEGGGDg5QZaDv3zzz9/+v99tYqWWP1ZAwYYYIABBhhggIFXGmg59O+//+6z6c/Xb2dOrIAVsAJWwApYAStgBazAG1fg/wABY6aK2cuLGQAAAABJRU5ErkJggg==
注意：else和elseif都是可选的，可有可无，但是end不能省略下面是你需要完成的事：已知变量n，请判断n是否为奇数，如果是，请给n的值加上1如果不是，请将n的值改为原来的两倍data:image/png;base64,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**Btl7d9bo87buq59ca/cPuqrV4x/djnzcrTt2e/Fen6hMcAAAwycZUAonfxj+fHwZ0Fz1rYamzdwFihy/1Y9B6QYN2vb6tsaH/OiXI3N7bk+mxf9tRxjoy3m1TL6o6z9e2vUefU6r7fqy+25fmRuHnNvfeblaNu99zTPLx0GGGCAgW4DQukJoXRs8ixUHNn8WSiatcVas75ZW4yv5ZGxszG5LdfH+vk617fufXTc1hr13ntjoz/fe9RXrxj/7HJmpbbV62e/B+v55cQAAwwwcLaBlw2l9a+We9erB1vnxbhZ+6xtjM/tuR5rjfLeEJEDUqw3a9vq2xof80b5yLg8N9frurVvdf+j4/L8eq/ZdR6/ukduz/Ujc/OYWX042LMw669t9Xp2L21+oTDAAAMMvJKBlw2l4yGPABiveOhxncvoy2Xuj3r0x/Uot9qib5QxJ7fV+q1BYgSieMVacb0VlvKYVT3Wi3K1XvTncjZ21jbm1PZ6HevW9nG99Yp5tZzNqWPiut5z1n5kTMw7Wm45GH3xivXiOuZFGf1Kv3QYYIABBt7BwEuH0lfcgO8OFKsQtfWsjs4Z4+JV14v2Ws7G1bbZ9Vhn1j7abumbjY33uLd+jNsqV2tstT9i4JG5W+9Jn19oDDDAAAPdBl4ulMZfJPNfMbsfovv7IB81IFSyctSKcawwwMCnGXi5UPppG+Tn9aXEAAMMMMAAA59gQCh9wv+b0U+A4mf0hcgAAwwwwAAD32lAKBVKl//u5nfCs7YvNgYYYIABBhjIBoRSoVQoZYABBhhggAEG2g0IpRC2I8ynJHWnZgYYYIABBj7TgFAqlAqlDDDAAAMMMMBAuwGhFMJ2hE7En3kitu/2nQEGGGAgGxBKhVKhlAEGGGCAAQYYaDcglELYjjCfktSdmhlggAEGGPhMA0KpUCqUMsAAAwwwwAAD7QaEUgjbEToRf+aJ2L7bdwYYYICBbEAoFUqFUgYYYIABBhhgoN2AUAphO8J8SlJ3amaAAQYYYOAzDQilQqlQygADDDDAAAMMtBsQSiFsR+hE/JknYvtu3xlggAEGsgGhVCgVShlggAEGGGCAgXYDQimE7QjzKUndqZkBBhhggIHPNCCUCqVCKQMMMMAAAwww0G5AKIWwHaET8WeeiO27fWeAAQYYyAaEUqFUKGWAAQYYYIABBtoNCKUQtiPMpyR1p2YGGGCAAQY+04BQKpQKpQwwwAADDDDAQLsBoRTCdoROxJ95Irbv9p0BBhhgIBsQSoVSoZQBBhhggAEGGGg3IJRC2I4wn5LUnZoZYIABBhj4TANCqVAqlDLAAAMMMMAAA+0GhFII2xE6EX/midi+23cGGGCAgWxAKBVKhVIGGGCAAQYYYKDdgFAKYTvCfEpSd2pmgAEGGGDgMw0IpUKpUMoAAwwwwAADDLQbEEohbEfoRPyZJ2L7bt8ZYIABBrIBoVQoFUoZYIABBhhggIF2A0IphO0I8ylJ3amZAQYYYICBzzQglAqlQikDDDDAAAMMMNBuQCiFsB2hE/Fnnojtu31ngAEGGMgGhFKhVChlgAEGGGCAAQbaDQilELYjzKckdadmBhhggAEGPtOAUCqUCqUMMMAAAwwwwEC7AaEUwnaETsSfeSK27/adAQYYYCAbEEqFUqGUAQYYYIABBhhoNyCUQtiOMJ+S1J2aGWCAAQYY+EwDQqlQKpQywAADDDDAAAPtBoRSCNsROhF/5onYvtt3BhhggIFsQCgVSoVSBhhggAEGGGCg1cBvv/329euvv37F/36MhOrlGTDAAAMMMMAAAwycaWAE0t9//z0y6dePP2oqnoAn4Al4Ap6AJ+AJeAKeQNMTEEqbHrzbegKegCfgCXgCnoAn4An89wkIpf99FmqegCfgCXgCnoAn4Al4Ak1P4H8Bzb0R5EuGOrUAAAAASUVORK5CYII=
8.3 判断三角形合法性（自测题）你需要使用前面几章的知识，来完成下面的题目已知三个number类型的变量a、b、c，分别代表三根木棒的长度请判断，使用这三根木棒，是否可以组成一个三角形（两短边之和大于第三边）如果可以组成，就打印出truedata:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAqUAAACCCAYAAAB/7rGVAAAQ5UlEQVR4Ae3dzW7kNhYGUL9TXjAv6QfIrjcNdGcRdPfGA2Zyk4sLUmKV5WJJPgPUkOKfVKxj+2MFk3n5/v3727dv37zsAQMMMMAAAwwwwMBDDbQc+***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
8.4 if的判断依据（自测题）我们在前面了解到，Lua 把 false 和 nil 看作是false，其他的都为true（包括0这个值，也是相当于true）那么问题来了，执行下面的代码，将会输出什么？data:image/png;base64,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**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
九、函数
9.1 初识函数
函数是指一段在一起的、可以做某一件事儿的程序，也叫做子程序。在前面的内容中，我们已经接触过了函数的调用，这个函数就是前面用到了很多次的print(...)。调用函数只需要按下面的格式即可：函数名(参数1,参数2,参数3,......)为何要使用函数？因为很多事情都是重复性操作，我们使用函数，可以快速完成这些操作下面我们举一个最简单的函数例子，这个函数没有传入参数、没有返回值它实现了一个简单的功能，就是输出Hello world!：https://file1.**/web3/M00/05/54/wKgZO2d-VWyAG_LSAAAWBv8dEgs845.png这个函数名为hello，我们可以按下面的方法进行调用（执行）：https://file1.**/web3/M00/05/54/wKgZO2d-VZSAUMAbAAAbEv18fIY158.png这行代码会输出Hello world!。同时，在Lua中，函数也是一种变量类型，也就是说，hello实际上也是一个变量，里面存储的是一个函数，我们可以用下面的代码来理解：https://file1.**/web3/M00/05/49/wKgZPGd-VcaAErWjAABCTLOb1SU643.png因为函数只是个变量，你甚至在一开始可以这样声明hello函数：https://file1.**/web3/M00/05/54/wKgZO2d-VgaABgYeAAAbqq2V5Oc402.png下面你需要做一件简单的事情：新建一个函数变量biu，使其执行后会打印biubiubiu这个字符串新建一个函数变量pong，使其与biu指向的函数相同https://file1.**/web3/M00/05/4A/wKgZPGd-VimAbmdlAAArvx8pcM0859.png
9.2 local变量
之前我们创建的变量，都是全局变量，这种变量在代码运行周期从头到尾，都不会被销毁，而且随处都可调用。但是当我们代码量增加，很多时候大量新建全局变量会导致内存激增，我们需要一种可以临时使用、并且可以自动销毁释放内存资源的变量，要怎么解决呢？我们可以使用local标志来新建临时变量，使用local创建一个局部变量，与全局变量不同，局部变量只在被声明的那个代码块内有效。参考下面的代码：https://file1.**/web3/M00/05/4A/wKgZPGd-Vj-ALCviAAAptIddp-M523.png上面的代码中，n就是一个局部变量，它只在这个funcion中有效，并且函数运行完后会自动回收这部分的内存。我们应该尽可能的使用局部变量，以方便lua虚拟机自动回收内存空间，同时减少资源占用提高运行速度。下面请阅读以下代码，思考一下，正确的输出结果是什么：https://file1.**/web3/M00/05/54/wKgZO2d-VmCAWmG1AAAgtp9gLfA992.png
9.3 函数参数
在前几章的使用中，我们知道函数是可以传入参数的，如print(123)那么，我们如何编写可以传入参数的函数呢？可以按下面的模板来写https://file1.**/web3/M00/05/54/wKgZO2d-Vn6AOh9rAAAYJqPSL3g605.png这里传入的参数，等价于在函数内部新建了一个local的变量，修改这些数据不会影响外部的数据（除了后面还没有讲到的table等类型）举个例子，比如下面的函数，可以实现打印出两个传入值的和：https://file1.**/web3/M00/05/4A/wKgZPGd-VpWACGWLAAAgTf9YxBg942.png这段代码其实等价于：https://file1.**/web3/M00/05/54/wKgZO2d-VrCAOhZCAAAkCCy8eI4216.png下面问题来了，请设计一个函数p，可以按下面的调用方式来打印出物体的密度：https://file1.**/web3/M00/05/54/wKgZO2d-VtKAE-xcAABfTNxhbLc357.png
9.4 函数返回值
在前面的代码中，我们实现了一个函数，输入变量a、b，函数会自动输出两个数值的和。但是一般来说，我们的需求远远不止这些，我们可能需要一个如下功能的函数：执行函数，输入两个值，获取这两个值的和如果还是按上面几节的内容，我们只会输出这个值，并不能把这个值传递给其他的变量进行后续使用，如何解决这个需求呢？我们可以使用函数的返回值来实现这个需求，结合上面的需求，我们可以用下面的代码实现：https://file1.**/web3/M00/05/4A/wKgZPGd-VvmAec4bAAAo2R3t4YQ468.png这里的return表示返回一个值，并且立刻结束这个函数的运行同时，和输入值可以有多个一样，返回值也可以有多个https://file1.**/web3/M00/05/54/wKgZO2d-VxWAby2jAAA1huFtYwI555.png下面问题来了，请设计一个函数p，可以按下面的调用方式来返回出物体的密度，返回值为number类型：https://file1.**/web3/M00/05/4A/wKgZPGd-V0KAZ2zkAABbxUGtpB8491.png
9.5 判断三角形合法性2（自测题）
你需要使用前面几章的知识，来完成下面的题目已知三个number类型的变量，分别代表三根木棒的长度请判断，使用这三根木棒，是否可以组成一个三角形（两短边之和大于第三边）请新建一个函数triangle，并可以用如下形式调用（如果可以组成，就返回true）：https://file1.**/web3/M00/05/54/wKgZO2d-V3iAUDUTAAAq7Txa7sM642.png
9.6 返回多个值（自测题）
你需要使用前面几章的知识，来完成下面的题目已知2个number类型的变量，分别代表一个长方体的长和宽请计算这个长方形的周长和面积请新建一个函数rectangle，并可以用如下形式调用：https://file1.**/web3/M00/05/54/wKgZO2d-V5OAI_UVAAA2QLD8r1c631.png
十、table
10.1 认识数组数组，使用一个变量名，存储一系列的值很多语言中都有数组这个概念，在Lua中，我们可以使用table（表）来实现这个功能在Lua中，table是一个一系列元素的集合，使用大括号进行表示，其中的元素之间以逗号分隔，类似下面的代码：https://file1.**/web3/M00/05/54/wKgZO2d-V7uAGLAfAAAIfZjdE5Q844.png我们可以直接使用元素的下标，来访问、或者对该元素进行赋值操作。在上面的table变量t中，第一个元素的下标是1，第二个是2，以此类推。我们可以用变量名+中括号，中括号里加上下标，来访问或更改这个元素，如下面的例子：https://file1.**/web3/M00/05/4A/wKgZPGd-V9KAQDXlAABI8y0myvE347.png以上就是table最简单的一个例子了，就是当作数组来用（注意，一般语言中的数组基本都为不可变长度，这里的table为可变长度）下面你需要完成：新建一个table，名为cards，存入1-10十个数字将第3个元素与第7个元素交换将第9个元素与第2个元素交换增加第11个变量，值为23https://file1.**/web3/M00/05/4A/wKgZPGd-V_qAO6T2AAAPddGV6Xw616.png
10.2 简单table上一节里，我们将table来表示数组，实际上，table中可以包括任意类型的数据比如我们可以在table中放置number和string数据，类似下面的代码：https://file1.**/web3/M00/05/4A/wKgZPGd-WBCAJDhwAAALYk_WR1E480.png我们甚至能在里面放function变量https://file1.**/web3/M00/05/4A/wKgZPGd-WCuAAnyCAABD0Fkns_w489.png这些table访问每个元素的方式仍然是直接用下标，并且也能用下标来进行修改下面你需要完成：新建一个table，名为funcList，并实现以下功能调用funcList(a,b)，返回a和b的乘积调用funcList(a,b)，返回a减b的差调用funcList(a)，返回a的相反数（-a）https://file1.**/web3/M00/05/54/wKgZO2d-WE6ASkd9AABDwWO9LUg924.png
10.3 table下标在前两节，我们的table都只是一些简单的List（列表），每个元素的下标都是自动从1排列的实际上，Lua中，下标可以直接在声明时进行指定，像下面这样：https://file1.**/web3/M00/05/4A/wKgZPGd-WHiAAZ3nAABNq9v09f0016.png下面你需要：新建一个变量t，并按下面的格式声明下标为1的元素，值为123（number）下标为13的元素，值为"abc"（string）下标为666的元素，值为"666"（string）https://file1.**/web3/M00/05/54/wKgZO2d-WJuAUPOwAAAghS8nuo4560.png
10.4 下标进阶在上一节，我们学习了如何自定义下标，其实在Lua中，下标也可以是字符串，如下面的例子https://file1.**/web3/M00/05/54/wKgZO2d-WM2ATVmMAABOj-5Rq0I620.png可见，在使用string作为下标时，table的灵活性提升了一个数量级。string作为下标时，也可以动态赋值：https://file1.**/web3/M00/05/4A/wKgZPGd-WPGAQSg9AAAVv9yC7yU151.png下面你需要完成：新建table变量t下标为apple的元素，值为123（number）下标为banana的元素，值为"abc"（string）下标为1@1的元素，值为"666"（string）https://file1.**/web3/M00/05/54/wKgZO2d-WRSAOA4LAAAqwh-XeEo929.png
10.5 table小测验下面的代码，将会打印什么？https://file1.**/web3/M00/05/54/wKgZO2d-WTGATlw8AABHjRYiw2A386.png
10.6 table小测验2下面的代码，将会打印什么？https://file1.**/web3/M00/05/54/wKgZO2d-WVKAfCKRAABGi48Kcp0236.png
10.7 Lua全局变量与table在前面我们知道了，在table中，可以直接用table名[下标]或table名.string下标来访问元素实际上，在Lua中，所有的全局变量全部被存放在了一个大table中，这个table名为：_G我们可以用下面的例子来示范：https://file1.**/web3/M00/05/4A/wKgZPGd-WXGAT_R3AAA9JP08xyM928.png现在，你明白为什么说万物基于table了吧？你需要完成下面的任务：已知有一个全局变量，名为@#$请新建一个变量result将@#$变量里的值赋值给resulthttps://file1.**/web3/M00/05/4A/wKgZPGd-WZGAHq8wAAAThg4yP2U001.png
10.8 table小测试3请新建一个名为t的table，满足以下要求t可获得number类型数据100t.num可获得number类型数据12t.abc可获得string类型数据abcdt.a.b.c可获得number类型数据789https://file1.**/web3/M00/05/55/wKgZO2d-WauASxaXAAA2-tDEDc0565.png
10.9 table.concattable.concat (table [, sep [, i [, j ] ] ])将元素是string或者number类型的table，每个元素连接起来变成字符串并返回。可选参数sep，表示连接间隔符，默认为空。i和j表示元素起始和结束的下标。下面是例子：https://file1.**/web3/M00/05/4A/wKgZPGd-Wc6AGZR_AAAhq6cLJt8965.png请完成下面的任务：已知table变量t，将t中的结果全部连起来间隔符使用,并使用print打印出来https://file1.**/web3/M00/05/4A/wKgZPGd-WeSANOHjAAARulRzhyI925.png
10.10 table删减table.insert (table, value)在（数组型）表 table 的 pos 索引位置插入 value，其它元素向后移动到空的地方。pos 的默认值是表的长度加一，即默认是插在表的最后。table.remove (table [, pos])在表 table 中删除索引为 pos（pos 只能是 number 型）的元素，并返回这个被删除的元素，它后面所有元素的索引值都会减一。pos 的默认值是表的长度，即默认是删除表的最后一个元素。下面是例子：https://file1.**/web3/M00/05/4A/wKgZPGd-WgCAHpBDAABphDOe8SQ096.png请完成下面的任务：已知table变量t，去除t中的第一个元素然后这时，在t的第三个元素前，加上一个number变量，值为810https://file1.**/web3/M00/05/4A/wKgZPGd-WiSAOqQ8AAAbbp7uj6o962.png
十一、循环
11.1 while循环在实际功能实现中，经常会遇到需要循环运行的代码，比如从1到100填充table数据，我们可以直接用循环语句来实现我们首先来学习while这个循环语法，整体的格式如下：https://file1.**/web3/M00/05/55/wKgZO2d-Wj-AH39qAAAS0MR86aA733.png下面举一个例子，我们计算从1加到100的结果：https://file1.**/web3/M00/05/55/wKgZO2d-WleABdl4AAAhoFV4Uq0815.png上面的代码，就是当num≤100时，result不断地加num，并且num每次循环后自己加1理解了上面的代码，我们来完成下面一个简单的任务吧：已知两个number类型的变量min和max请计算从min与max之间，所有3的倍数的和打印出结果https://file1.**/web3/M00/05/4A/wKgZPGd-Wm2AIsixAAAkuxL_tEM122.png
11.2 for循环for循环在某些程度上，和while循环很相似，但是for循环可以更加简洁地表达中间累积的量我们首先来学习for这个循环语法，整体的格式如下：https://file1.**/web3/M00/05/4B/wKgZPGd-WouAJicEAAASyWxV35Q633.png其中，步长可以省略，默认为1临时变量名可以直接在代码区域使用（但不可更改），每次循环会自动加步长值，并且在到达结束值后停止循环下面举一个例子，我们计算从1加到100的结果：https://file1.**/web3/M00/05/4B/wKgZPGd-WqGATQfqAAAZJYrrFOM875.png上面的代码，就是当i≤100时，result不断地加i，并且i每次循环后增加1理解了上面的代码，我们来完成下面一个简单的任务吧：已知两个number类型的变量min和max请计算从min与max之间，所有7的倍数的和打印出结果https://file1.**/web3/M00/05/4B/wKgZPGd-Wr2ALJeeAAAc7hV0As8965.png
11.3 中断循环前面我们学习了循环语句，有些时候循环运行到一半，我们不想再继续运行了，怎么办呢？我们可以在一个循环体中使用break，来立即结束本次循环，继续运行下面的代码比如像下面这样，计算1-100相加途中，小于100的最大的和：https://file1.**/web3/M00/05/4B/wKgZPGd-WtWAG4ESAAApDN23A2o912.png可以看见，当发现和大于100后，代码立即把result的值还原到了加上当前数字之前的状态，并且调用break语句，立即退出了本次循环在while中，我们也可以使用break:https://file1.**/web3/M00/05/55/wKgZO2d-WvOAEzoYAAAvXc_nWwY401.png我们在这里直接使用了死循环（因为while的继续运行判断依据始终为true），整体逻辑也和之前for的代码一致，当发现和大于100后，代码立即把result的值还原到了加上当前数字之前的状态，并且调用break语句，立即退出了本次循环现在你需要完成一项任务：请求出小于变量max的13的倍数的最大值（max大于0）并将结果打印出来本题理论上不用循环就能实现，但是为了练习一下技巧，请用for循环来实现https://file1.**/web3/M00/05/4B/wKgZPGd-WwuAVzpRAAAXW4lSi1A561.png
11.4 循环测试题1（自测题）前面我们学习了循环语句，我们需要完成下面的任务我们知道，print函数可以打印一行完整的输出那么，已知变量a，请打印出下面的结果：（a为大于0的整数，且需要输出a行数据，数据从1开始，每行与上一行的差为2）https://file1.**/web3/M00/05/4B/wKgZPGd-WyCAXXpKAAAZRk_59SY172.png做题区域：https://file1.**/web3/M00/05/4B/wKgZPGd-WzmALjsZAAAYy5z6Muo014.png
11.5 循环测试题2（自测题）我们需要完成下面的任务那么，已知变量a，请打印出下面的结果：（a为大于0的整数，且需要输出a行数据，第一行为一个，后面每行多一个）https://file1.**/web3/M00/05/4B/wKgZPGd-W1KAXtbCAAAZd5jPmv0653.png做题区域：https://file1.**/web3/M00/05/55/wKgZO2d-W2eAQylSAAAY-OybII8110.png
11.6 循环测试题3（自测题）我们需要完成下面的任务那么，已知变量a，请打印出下面的结果：（a为大于0的整数，且需要输出a行数据，按图示规律输出）https://file1.**/web3/M00/05/4B/wKgZPGd-W36AZXHJAAAyEkhlGDg261.png做题区域：https://file1.**/web3/M00/05/4B/wKgZPGd-W5qAPBWsAAAX3NHUCL0725.png
11.7 循环测试题4（自测题）有一只猴子，第一天摘了若干个桃子 ，当即吃了一半，但还觉得不过瘾 ，就又多吃了一个。第2天早上又将剩下的桃子吃掉一半，还是觉得不过瘾，就又多吃了两个。以后每天早上都吃了前一天剩下的一半加天数个（例如，第5天吃了前一天剩下的一半加5个）。到第n天早上再想吃的时候，就只剩下一个桃子了。那么，已知变量a为最后一天的天数，请打印出第一天的桃子数。如：a为5时，输出114做题区域：https://file1.**/web3/M00/05/4B/wKgZPGd-W7KAcjbmAAAYA7zsilc439.png
十二、详解string库
12.1 string.sub
接下来几节会讲解string库的各种接口https://file1.**/web3/M00/05/55/wKgZO2d-W8qADW7tAAAH7bvZgP8737.png
返回字符串 s 中，从索引 i 到索引 j 之间的子字符串。i 可以为负数，表示倒数第几个字符。当 j 缺省时，默认为 -1，也就是字符串 s 的最后位置。当索引 i 在字符串 s 的位置在索引 j 的后面时，将返回一个空字符串。下面是例子：https://file1.**/web3/M00/05/55/wKgZO2d-W9-AFOOKAAAtrBoY2kE504.png
值得注意的是，我们可以使用冒号来简化语法，像下面这样：https://file1.**/web3/M00/05/4B/wKgZPGd-W_eAFrXqAAAbY0TLrig314.png
请完成下面的任务：已知字符串变量s，请分别打印出（每种一行）：s从第4个字符开始，到最后的值s从第1个字符开始，到倒数第3个字符的值s从倒数第5个字符开始，到倒数第2个字符的值https://file1.**/web3/M00/05/4B/wKgZPGd-XA6AH_yIAAAW71FRH9g532.png
12.2 string.repstring.rep(s, n)返回字符串 s 的 n 次拷贝。示例代码：https://file1.**/web3/M00/05/4B/wKgZPGd-XCWAZ8_yAAAQ1JDCOOs122.png
print(string.rep("abc", 3))--输出结果：--abcabcabc请完成下面的任务：打印一行数据，数据内容为810个114514https://file1.**/web3/M00/05/4B/wKgZPGd-XDiAUhHOAAAKG2FHDmE177.png
12.3 string.lenstring.len(s)接收一个字符串，返回它的长度。示例代码：https://file1.**/web3/M00/05/4B/wKgZPGd-XFCAM1U9AAAgHChIcos015.png
请完成下面的任务：新建一个变量s，使数据内容为810个114514并打印出字符串s的长度https://file1.**/web3/M00/05/4B/wKgZPGd-XG-ABzb1AAALGjQqlUY742.png
12.4 大小写转换string.lower(s)接收一个字符串 s，返回一个把所有大写字母变成小写字母的字符串。string.upper(s)接收一个字符串 s，返回一个把所有小写字母变成大写字母的字符串。示例代码：https://file1.**/web3/M00/05/55/wKgZO2d-XIiAD6IFAAAvR_ILD9Q931.png
请完成下面的任务：已知一个变量s，打印出全是大写字母的s字符串https://file1.**/web3/M00/05/4B/wKgZPGd-XKCAAIUnAAANZuklA1I173.png
12.5 string.formatstring.format(formatstring, ...)按照格式化参数formatstring，返回后面...内容的格式化版本。编写格式化字符串的规则与标准 c 语言中 printf 函数的规则基本相同：它由常规文本和指示组成，这些指示控制了每个参数应放到格式化结果的什么位置，及如何放入它们。一个指示由字符%加上一个字母组成，这些字母指定了如何格式化参数，例如d用于十进制数、x用于十六进制数、o用于八进制数、f用于浮点数、s用于字符串等。示例代码：https://file1.**/web3/M00/05/4B/wKgZPGd-XLmARiI7AAA-wqh8JbQ823.png
请完成下面的任务：已知一个变量n，为number类型整数打印出n:连上n值的字符串https://file1.**/web3/M00/05/55/wKgZO2d-XNaATCXrAAAL3ifrLfs813.png
12.6 string的本质这一节我们来讲解字符串的本质字符串，是用来存储一串字符的，但是它的本质就是一串数字。如何用一串数字来代表一串字符呢？在计算机中，每一个符号都对应着一个数字，但是在讲解这个知识之前，我们了解一下补充知识：https://file1.**/web3/M00/05/55/wKgZO2d-XOyAMEU4AAAbra103X0874.png
接下来，你需要了解，每一个符号都对应着一个数字，比如：0对应着0x30、1对应着0x31 a对应着0x61、b对应着0x62 A对应着0x41、B对应着0x42上面的编码规则，我们称之为ascii码，具体想了解可以打开下面的网址查看：http://ascii.911cha.com/当然，1字节最大为0xff，即256，只能存下一部分符号，大部分的中文按某些编码，一个中文占用2或3个字节计算机如何解析这些数据，我们不需要了解，当你知道了上面的知识后，你应该可以理解下面的描述：https://file1.**/web3/M00/05/4B/wKgZPGd-XRCAXFL3AAARztOWQAI813.png
同时，lua的字符串中可以保存任何数值，即使是0x00这种不代表任何含义的数，也可以保存https://file1.**/web3/M00/05/4B/wKgZPGd-XSeAYIkQAAAXT6tVaBU227.png
比如下面的描述：https://file1.**/web3/M00/05/55/wKgZO2d-XUSAYanJAAAqqREpGVA781.png
下面你需要思考一个问题：一串字符串数据如下，它的实际内容是什么（指人能看见的字符串内容，如abcd）？0x62,0x61,0x6e,0x61,0x6e,0x61
12.7 string.char
string.char (...)接收 0 个或更多的整数（整数范围：0~255），返回这些整数所对应的 ASCII 码字符组成的字符串。当参数为空时，默认是一个 0。如果上一章节有认真学习过了的话，这段话应该是很好理解的。实质上就是把计算机认识的一串数字，变成字符串变量，并且字符串内的数据就是要存的那串数据。示例代码：https://file1.**/web3/M00/05/4B/wKgZPGd-XVyAOvEkAAAr8WXai88284.png
请完成下面的任务：已知一个字符串的每个字符在数组t中按顺序排列请根据t的值，打印出字符串内容（一行数据）注：这个字符串存储的不一定是可见的字符https://file1.**/web3/M00/05/4B/wKgZPGd-XYKAfcfwAAAYAgvf5Ic023.png
12.8 string.bytestring.byte(s [, i [, j ] ])返回字符 s、s、s、······、s 所对应的 ASCII 码。i 的默认值为 1，即第一个字节,j 的默认值为 i 。这个函数功能刚好和前面的string.char相反，是提取字符串中实际的数值。示例代码：https://file1.**/web3/M00/05/55/wKgZO2d-XZaAIt34AAAriniteQA521.png
请完成下面的任务：已知字符串s请把s中代表的数据，全部相加，并打印出来https://file1.**/web3/M00/05/55/wKgZO2d-XauAHbryAAAUB0mtmPk209.png
12.9 string.findstring.find(s, p [, init [, plain] ])这个函数会在字符串s中，寻找匹配p字符串的数据。如果成功找到，那么会返回p字符串在s字符串中出现的开始位置和结束位置；如果没找到，那么就返回nil。第三个参数init默认为1，表示从第几个字符开始匹配，当init为负数时，表示从s字符串的倒数第-init个字符处开始匹配。第四个参数plain默认为false，当其为true时，只会把p看成一个字符串对待。可能你会奇怪，第四个参数有什么存在的必要吗？p不是本来就应该是个字符串吗？ 实际上，lua中的匹配默认意义是正则匹配，同时，这里的正则与其它语言也有些许不同。由于篇幅有限，本节和下面的几节涉及匹配内容时，均不会考虑正则的使用方法，Lua正则教程将会在最后几节单独详细地列出来。第四个参数为true时，便不会使用正则功能。示例代码：https://file1.**/web3/M00/05/55/wKgZO2d-XcWAOBuAAAA7OcgbmTM773.png
请完成下面的任务：已知字符串s，里面有很多相同的字符串请找出字符串s中，所有字符串awsl的位置使用print打印结果，结果一行一个如字符串12awslawslaw，输出3和7https://file1.**/web3/M00/05/55/wKgZO2d-XeaAf05FAAAV9y708vo798.png
12.10 string.gsubstring.gsub(s, p, r [, n])将目标字符串s中所有的子串p替换成字符串r。可选参数n，表示限制替换次数。返回值有两个，第一个是被替换后的字符串，第二个是替换了多少次。特别提示：这个函数的目标字符串s，也是支持正则的下面是例子：https://file1.**/web3/M00/05/4B/wKgZPGd-Xf2ABL02AAAjRyGxJH4180.png
同样的，我们也可以使用冒号来简化语法，像下面这样：https://file1.**/web3/M00/05/55/wKgZO2d-XheAWIySAAAPT-EdrAU944.png
请完成下面的任务：已知字符串变量s，请分别打印出（每种一行）：把字符串s中，前5个a，替换为b把字符串s中，前3个c，替换为xxx把结果打印出来，一行数据https://file1.**/web3/M00/05/4B/wKgZPGd-Xi6AKu6sAAAU1Rmw6tY834.png
十三、跨文件调用
在编写代码时，随着逻辑逐渐复杂，我们的代码量也会变大。虽然有函数可以把一部分代码逻辑封装起来，但是所有代码都放到一个文件里，显然也不是个好办法。所以我们需要将一些代码放到不同文件中，通过文件来区分这些代码的功能。比如我们有下面这个函数：https://file1.**/web3/M00/05/4B/wKgZPGd-XkSAZ7GgAAA9HwD6yT8227.png
我们新建一个文件叫tools.lua，把这个函数放进去，现在，整个文件如下面这样：tools.luahttps://file1.**/web3/M00/05/4B/wKgZPGd-XnSAQQCUAABT62EYdeY543.png
现在，我们封装的这个函数就能在其他文件里被调用了，具体代码如下：https://file1.**/web3/M00/05/55/wKgZO2d-XpOAA6TMAAAUx2RgZXk961.png
当调用了require接口后，Lua虚拟机会自动加载你调用的文件，执行文件的内容，然后返回你文件里return的结果。为了更好地理解这段话，我们可以看下面两个文件，其中run.lua是被运行的那个入口文件test.luahttps://file1.**/web3/M00/05/4B/wKgZPGd-XrCARZUqAABgneUyIoA570.png
run.luahttps://file1.**/web3/M00/05/55/wKgZO2d-Xt6AS5nvAAAsFJqLS3Q094.png
同时，每个文件最多只会被require一次，如果有多个require，只有第一次会执行。
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