javascript 闭包内部机制

2023-08-29 23:12:40

在初学JavaScript函数式编程的时候，经常会出现令人出乎意料的结果，而原因，大都是由于不理解JavaScript闭包引起的；理解JavaScript的闭包，可以从JavaScript的闭包内部机制出发。

函数：

function creatFunctions() {

  var result = [];

  for (var i = 0; i < 10; i++) {

    result[i] = function () {

      return i

    };

  }

  return result;

};

console.log(creatFunctions())

结果：

0: function creatFunctions/result[i]()

1: function creatFunctions/result[i]()

2: function creatFunctions/result[i]()

3: function creatFunctions/result[i]()

4: function creatFunctions/result[i]()

5: function creatFunctions/result[i]()

6: function creatFunctions/result[i]()

7: function creatFunctions/result[i]()

8: function creatFunctions/result[i]()

9: function creatFunctions/result[i]()

这个函数会返回一组数组，应该每个函数都应该返回对应的值；而出现结果的原因就在于闭包不是立即执行的。

1、闭包的概念

JavaScript高设中，闭包是指有权访问另一个函数作用域的中的变量的函数，创建闭包的形式，就是在函数的内部创建另一个函数。

function makeFunc() {

    var name = "Mozilla";

    function displayName() {

        alert(name);

    }

    return displayName;

}

var myFunc = makeFunc();

myFunc();//MDN

displayName就是一个闭包。

2、闭包的内部机制

闭包的内部机制在于理解作用域链，函数的执行环境，变量对象和活动对象；

函数被调用时会创建一个执行环境，在执行环境中初始化该函数的活动对象、变量对象、和作用域链。其中，作用域链是指向当前执行环境可访问的变量对象的指针，是一个由内而外的过程。以上述函数为例；

由于所有函数的执行环境底层都是在全局执行环境中，JavaScript在运行时，首先初始化活动对象，即函数自带的arguments、this变量；全局变量makeFunc、myFunc会绑定到变量对象上；该执行环境初始化之后会推入栈中，此后会初始化函数makeFunc的局部变量，读取局部变量'name'；内部函数displayName的函数声明；值得注意的是，每个执行环境的内部属性[[scope]] 保存当前执行环境可访问的变量对象，由内而外，即内部函数始终可以访问外部函数直到全局环境的所有变量，而外部环境是无法读取内部函数变量对象的；这是由于作用域链中定义的。

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ir1SpPT081b94832oB7sYnn3yisLAwSTfnKMvsp5nyeg3RX4MU/RxFTe63Gi7EvLy8rFLOdyaGY6WmpspisahUqVJZrluwWCy2T5IpKSm5Xl+UnevXr+vnn39Wy5Yts6yzWCyyWq23vdD7fjl69KgeeeQRJmPLJ5mjlfTzO5d5c9fcbsBstVpltVqzfPV97969euqpp+zCTkpKir7//nt17NhRV65c0e7du9W/f/9st0s/R15l9vOjR486LJcQiAAUagQioPgrDIEo55tKAQAAGASBCAAAGB6BCAAAGB6BCAAAGB6BCAAAGB6BCAAAGB6BCAAAGB6BCAAAGB6BCAAAGF6xmKkaAAAUfcxUDQAA4EDF4m73jkyUAPJX5kgw/RwovgrDGR9GiAAAgOERiAAAgOERiAAAgOERiAAAgOERiAAAgOERiAAAgOERiAAAgOERiAAAgOERiAAAgOERiAAAgOERiAAAgOERiAAAgOERiAAAgOERiAAAgOERiAAAgOERiAAAgOERiAAAgOERiAAAgOERiAAAgOERiAAAgOERiAAAgOERiAAAgOERiAAAgOERiAAAgOERiAAAgOERiAAAgOERiAAAgOERiAAAgOERiAAAgOERiAAAgOERiAAAgOERiAAAgOERiAAAgOERiAAAgOERiAAAgOERiAAAgOERiAAAgOERiAAAgOERiAAAgOERiAAAgOERiAAAgOERiAAAgOERiAAAgOERiAAAgOERiAAAgOGVdHQBwJ3w9PQ8bDKZWji6DhQ8Ly8vq6NrAO6W1Wo9eOzYMR9H14GcMUKEIoUwBKAoMplMHRxdA26PESIUSUePHjU5ugYUjMyRIf7NUVQxulk0MEIEAAAMj0AEAAAMj0AEAAAMj0AEAAAMj0AEAAAMj0AEAAAMj0AEAAAMj0AEAAAMj0AEAAAMj0AEAAAMj0AEAAAMj3uZodDy8PB4qGTJkpOzW+fl5fX3W5+np6fPOn78eHTBVAYAKG4IRCi0GjVqFHvmzJmeJpPJLZvVr2Y+sFqtcY0aNRp1/PjxAqwOAFCccMoMhdZnn32W4eTk9HkemgZ/9tlnGfleEACg2CIQoVCzWCxb89AsL20AAMgRgQiFmpOT0zdWqzXhNk3iH3jggW8KrCAAQLFEIEKhFh4enmYymbbfpsn2gwcPphdYQQCAYolAhELPZDLleErMycmJ02UAgHtGIEKhd/ny5a8kJWWzKikxMXF/QdcDACh+CEQo9M6cOXPDarWGZLNq55kzZ24UeEEAgGKHQIQiIYfTZpwuAwDcFwQiFAkmk+kLSSm3LEoxmUx7HVUPAKB4IRChSAgPD0+RtCfzuclk2v1/ywAAuGcEIhQZVqvVdoosjxM2AgCQJwQiFBkuLi67Mh+7urruul1bAADuBIEIRcbhw4eTJIVI2hkaGnrF0fUAAIoP7naPomaryWSyOroIAEDxQiAyCE9Pz8Mmk6mFo+u4H6xWq7y8vFY6uo57ZbVaDx47dszH0XUYXXHqG8gd/Q454ZSZQfALv/AxmUwdHF0D6BtGQ79DThghMpjw8HBHlwBJZrPZ0SXgL+gbxR/9DrfDCBEAADA8AhEAADA8AhEAADA8AhEAADA8AhEAADA8AhEAADA8AhEAADA8AhEAADA8AhEAADA8AhEAADA8AhEAADA8AhEAADA8AhEAADA8AhEAADA8AhEAADA8AhEAADA8AhEAADA8AhEAADA8AhEAADA8AhEAADA8AhEAADA8AhEAADA8AhEAADA8AhEAADA8AhEAADA8AhEAADA8AhEAADA8AhEAFELr16/XhQsXHF0GYBglHV0AjC0iIkL+/v46dOiQXF1d7+q1t6pfv742b958HysEHCM+Pl7//Oc/NWHChBzbdOnSRXXr1s12XXp6ujIyMrRq1ar8KhEoVghEKPLuJkwBhUVcXFyWYH/hwgVVq1ZNkrR582bb40x79uwpqPIAwyAQAYADubm5ac+ePbJYLDp37pzq1q0rb29vW+hp3ry5du/erXPnzqlOnToOrhYovriGCHclIiJCZrNZO3fuVOfOndWlSxcdOXJE69atk4+Pjzp16qRvv/3W1v7IkSMaOHCgWrZsqe7duyssLCzb7X788cfq3Lmzzp07J0lKTU3Vhx9+KB8fH7Vt21bvvvuukpOT81RbSkpKlmWpqam2x4cPH9bAgQPVqlUr9evXTydPnrS1t1gsWrlypXr06KGWLVuqa9euduuB+23OnDlauHBhtusuXLig0aNHKzQ0VJL09ttva+jQobp48aLS09Oz/bl69apOnDihoUOHKiQkJE//73Pqp3fa3++m3wKORiDCPTlz5oy2bdumVq1a6b333lNUVJR27dqlDh06aP78+bZ2V69e1eTJk3Xo0CF16NBBs2fPzrKtzZs3Kzg4WMuWLVPt2rUlSbNmzdKvv/6qjRs3KiQkRJcuXVJQUNB9qT04OFiLFi3Sl19+qerVq2vmzJm2dQsWLFBwcLBmzpyp0NBQffzxx6pYseJ92S/wVx999JFOnz6twMDAbNe7ublp4cKFmjFjhr766ivNnz9fK1asUHh4uFasWJHtz6ZNm2zru3XrZtvW7f7f59ZP89rf87PfAvmFQIR70r9/f7m6uqpr165KSEiQv7+/XF1d1aVLF507d04ZGRmSJB8fH7m7uysyMlLlypVTTEyM0tPTbds5cOCAli5dqsWLF6t+/fqSpEuXLmn37t2aOHGi3NzcVLFiRQ0aNEj79++3q+Gpp56S2WyW2WzWvHnz8lz76NGjVaVKFVWoUEF+fn46ffq0LBaLrly5ok2bNmnq1Kl64oknVLJkSbm7u6tGjRr34R0D7CUkJCg2NlZLlixRmTJlJEmvv/66bf348eMlSQ8//LDmz5+vw4cP29Z5e3tr+PDhtp+/Pr81CGXK6f+9lHs/zUt/z2u/BQobriHCPckcNcm8qLlKlSqSpFKlSkmSMjIyVKJECS1evFg7duyQh4eHbV3mL2FJWrhwoTp37qzGjRvblp0/f15Wq1UDBgzIst+0tDTb479eVB0REZGn2itXrmx7XL58eVmtVqWnpysmJkYZGRlq1KhRnrYD3ItKlSppzpw58vX11bVr13Tt2jVVqlRJa9assbVZtGiROnbsqICAALs+cjdy+n/v4uKSaz/NS3/Prd86OzvfU/1AfiEQId9FR0dr5cqV+uyzz+Tu7q6wsDDt3bvXrs0HH3ygN998Uw0aNNALL7wg6eYfCknatWuXqlevnuf9ubi4SJKuX79u+8V9J9cvPPjgg5Kks2fP3vMfHyCv9uzZo/j4eL344ouaNm2aWrZsKUmKjIzU2LFjNXjw4CyvqVatmpYvX2573q1btyzP8yov/TQv7rbfAo7GKTPku8wh99jYWCUlJWnDhg1Z2jz22GOaM2eOgoKCtHv3bkk3r5vw8vLSvHnzFBcXp4yMDJ0+fVpHjhy57f7q1asnV1dXhYSESJJu3Lhh92k7N25ubmrXrp0CAwN1+vRpZWRk6NSpU4qJicnzNoC7UblyZQUFBWnatGn69ttvtX//fr311luaMmWK3N3ds7RPSEiwO0UWHx9v97xEiRJ53nde+mle3G2/BRyNQIR8V69ePfn5+WncuHEaMmSIWrdunW271q1ba/LkyZo+fboOHjwo6eY3b5ycnNS3b1+1adNG06ZNk9Vqve3+SpUqpcDAQG3ZskU9evTQyJEjc9xnTgIDA9W0aVONHDlSbdu21bRp03Tjxo072gZwNx5//HENHTpUb731liZMmKDRo0fLbDbbtUlOTtbw4cP12GOP3XZbbm5uGj58eJ72m9d+mhd3028BRzM5uoB74eXlZZWko0ePFunjKAiZ71V4eLijS4Fk+wPH/93c5Xc/d3TfyJx/6OTJkwoPD1doaKhq1Kihfv366fLly1q3bp2cnZ3VvHlzNWrUSDVr1tSyZctkMmV9O06ePJltSOratav69u1bEIdTqDmq3/G3KneF4T3iGiIAcKA///xTY8aMUYMGDdSiRQu9/PLLdtfe9OvXTxEREfrhhx/09ddfq2zZslqxYkW2gQjA3SMQAYADubm5adu2bbdt07RpUzVt2rSAKgKMiWuIAACA4RGIAACA4RGIAACA4RGIAACA4RGIAACA4RGIAACA4RGIAACA4RGIAACA4RGIAACA4RGIAACA4RGIAACA4RGIAACA4RGIAACA4RGIAACA4RGIAACA4RGIAACA4RGIAACA4RGIAACA4RGIAACA4RGIAACA4RGIAACA4RGIAACA4RGIAACA4RGIAADIAw8Pj2pms9nV0XUgf5R0dAEAABRWnp6eNU0mUy9JfSS1t1qtjSSdcXBZyAcEIgAAbuHp6VlXUh+TydRHkrckk4NLQgEgEBmM2Wx2dAlAoUTfMLYnnniiYcmSJftYrdY+kvjPYEAEIgCAEZnMZnOT/wtAfSQ1sVqtjq4JDkQgMpjw8HBHlwAxGlEY0TeKv8x+5+np+b6Tk1Mfq9Xa8C4285uXl9f9LQyFAt8yAwAYislkYigIWTBCBAAwlKNHj74naXKzZs0aWyyWzFNmTfP48gZHjx69o2+ZeXl5EcCKAAIRAMCIrD/++OMJSSckTX/yyScblChRIvOi6mYOrg0OQCACABjeTz/99JukDyR94OnpWddkMvW2Wq19TCZTa/G1e0MgEAEAcItjx45FSVogaYHZbK4hqdf/jRx1cGhhyFcEIgAAchAeHh4raamkpR4eHtWcnZ2THV0T8geBCACAPDh+/PgFR9eA/MPX7gEAgOERiAAAgOERiAAAgOERiAAAgOERiAAAgOERiAAAgOERiAAAgOERiAAAgOERiAAAgOERiAAAgOERiAAAgOERiAAAgOERiAAAWVy/ft3RJQAFikAEAAYUFxenmJgYSVL79u0lSZGRkbp48aJSUlLUoUMHpaamOrJEoECVdHQBAID7IzPYZOfq1atq3769goKCJEmHDh3Svn379I9//EOSZLVaFRgYqFGjRik9PV116tSRi4tLgdQNFAYEIgAoJr755pssy6KiohQUFKTr169r+PDhtuW9e/fWwYMHFRsbK0n65Zdf9PDDD8tsNisoKEgeHh4FVjdQGBCIAKAYiIiIUK1atZScnKw6depIkhYsWKDvv/9eo0aNUtOmTVWxYkVFRESoadOm6tu3ryRp1KhRSklJ0ZQpUyRJ33//vXbv3i0XFxd169ZNV69eVVpamsaOHatevXo57PiA/MY1RABQxGVkZMjf31/R0dF64403tH79elmtVm3evFkbNmxQenq6hgwZovDwcPn7+ysjI0PBwcFasGCBqlSpohIlSujZZ5/V2rVr9fvvvysxMVGrV69WSEiIBg4cqD59+hCGUOwRiACgmPDw8NCqVat06tQpXbhwQdLNi6d37dql5cuXq0WLFpKk1NRULV68WDNmzNDkyZNVqlQpNWjQQCNGjND58+fVrFkzRUZGSrp5oXX9+vUddkxAQSEQAUAxUrZsWTVu3Fhff/21JCksLExms1lVq1a1tXF2dtZjjz2mTz75RJs2bdKUKVPk4+OjJUuWaOzYsXr66ad16NAhZWRk6Mcff5TZbHbU4QAFhkAEAMXEli1b5Ofnp7i4OHXt2lWS1LlzZ0VHR6tv3762kGQymbR06VL17t1bGzdutD3+29/+psTERPn4+OiLL77QZ599ppo1a6pWrVqOPCygQHBRNQqtiIgI+fv72y2rX7++Nm/e7JiCgEKuatWqWrZsmapWraqUlBRJUoUKFTRx4kT9+9//1tWrV21tV65cqYEDByo4OFh169bVyZMnFRAQoAoVKsjJyUlt27bV3LlztWDBAkcdDlCgCEQo9A4dOiRXV1dHlwEUeu3bt1d0dLRat26tEiVKqHPnzrZ1jRs3tmubnJysJk2aKCAgQD179tSqVasUEBAgJycnWSwWJScnSxKTM8IwCEQAUIw89NBD+v7773NtV7NmTc2YMUMLFy5UUFCQSpcurVOnTqlJkyaaOXOmEhMTFffJHpIAACAASURBVBQUpMmTJyspKUm9e/cugOoBx+EaItx3ERERMpvN2rlzpzp37qwuXbroyJEjWrdunXx8fNSpUyd9++23SkhIUKtWrRQaGmp77fXr19WuXTuFhYXluv3MUwK3LktNTbU9Pnz4sAYOHKhWrVqpX79+OnnypK29xWLRypUr1aNHD7Vs2VJdu3a1Ww8URe3bt8/1R7o5OhQQEGALOdu3b9ff//533bhxQyNHjlRiYqIWL16sDh06aN68eVq4cKG2bdvmyEMD8h0jRMg3Z86c0bZt2zRnzhy999578vHx0a5du7RgwQLNnz9f27Ztk4+Pj3bv3q02bdpIkvbv36+KFSuqVatWOnHixD3tPzg4WIsWLZKLi4smT56smTNnav369ZJuTlj3zTffaObMmWrcuLHOnj2rMmXK3PMxA45QokQJhYeH56mt2WxWuXLl9Mwzz2jSpEkqXbq0JKlSpUqqX7++mjRpIk9PT5lMJklSq1attHnzZj344IP5Vj9QGDBChHzTv39/ubq6qmvXrkpISJC/v79cXV3VpUsXnTt3ThkZGerbt68OHjxoG+3ZuXOnevfubftlLElPPfWUzGazzGaz5s2bl+f9jx49WlWqVFGFChXk5+en06dPy2Kx6MqVK9q0aZOmTp2qJ554QiVLlpS7u7tq1Khx398DoLAJDw9XiRIl1K5dO1sYupWXl5dd/5MkNzc37muGYo8RIuSbihUrSpLtgugqVapIkkqVKiXp5uy6ZrNZNWrU0IEDB2Q2m/Xzzz9r9uzZdtv560XVERERedp/5cqVbY/Lly8vq9Wq9PR0xcTEKCMjQ40aNbr7gwMAFCuMEMHh+vbtq127dikkJERPP/10rkPzmZ9Ur1+/bluW+Y2YvMjc/tmzZ++iWgBAcUQggsM999xzOnHihLZv364+ffrk2r5evXpydXVVSEiIJOnGjRtas2ZNnvfn5uamdu3aKTAwUKdPn1ZGRoZOnTqlmJiYuz4GAEDRRiCCw5UvX14+Pj4qU6aMvLy8cm1fqlQpBQYGasuWLerRo4dGjhyp1q1b39E+AwMD1bRpU40cOVJt27bVtGnTdOPGjbs9BCDPbv1GZFxcnHr27CmLxXLP27v1W5d3u4033njjtvUCxRnXEOG+a9q0qd03XnJ7LkmnT5/OMjqUXbtM7dq1U7t27eyWDRo0KMfX/XWZq6urJk2apEmTJt3BkQH3l5ubW6H6OvuxY8cUEhKibt26OboUoMAxQgSHunz5sjZv3qz4+Hj16NHD0eUAhvbSSy8pKChICQkJji4FKHAEIjjUs88+qw0bNmj+/PncngPFUlJSksaNG6fWrVurW7duOnz4sG3dX093bdy4UZ07d5a3t7dtionMNqGhoerbt6+8vb31xhtvKDExMdv9HTlyRAMHDlTLli3VvXt3hYWF5XkS1P79++vhhx/WBx98kOPxZLf9W+vMbULWTKmpqfrwww/l4+Ojtm3b6t13372jL0cA9xuBCA4VFhamzz//XE2bNnV0KUC+CAgI0OXLl7Vjxw6tXLkyx1nYo6OjNXfuXM2aNUv79++Xr6+v3fodO3Zo+fLl2r59uy5evKi5c+dmu52rV69q8uTJOnTokDp06KDZs2erUqVKtklQM906CWomk8mkgIAAHTp0SPv378/z9m+VOSFrq1at9N577ykqKkq7du1Shw4dNH/+fFu7WbNm6ddff9XGjRsVEhKiS5cuKSgo6PZvJpCPCEQAkE8SEhL07bff6s0331SVKlVUpUoVDRs2LNu2zs7OMplMOn/+vFxdXbPcjPW1115TpUqVVK1aNfn7+9uNttzKx8dH7u7uioyMVLly5RQTE6P09PQ8TYIqSXXr1tXIkSP1wQcfKCkpKc/bz5SXCVkvXbqk3bt3a+LEiXJzc1PFihU1aNCgHEMYUBC4qBoA8klcXJwkqU6dOrZl5cqVy7atm5ubZs6cqYULF2rt2rWaNGmSPD09beurVatme1y1alWlpKRk++20xYsXa8eOHfLw8LBNgmqxWPI0CWqmF198Ufv379e8efP0wgsv5Gn7mfIyIev58+dltVo1YMCALPtOS0uTs7NztnUB+YlABAD5JDP8XLhwwfY4MyRlx9fXVx07dtSiRYs0fvx47du3z7YuOTnZFjKioqJUrVo1OTnZD/JHR0dr5cqV+uyzz+Tu7q6wsDDt3bvXtj5zEtTY2NjbToLq5OSkadOmacCAAXrooYfyvP28qlSpkiRp165dql69+h2/HsgPnDIDgHxSu3Ztubu7a/HixUpKSlJMTIxWr16dbdvY2Fj99NNPMplMql27tlJTU2W1Wm3rP/74Y129elVRUVFasWKFunfvnmUbmaeuYmNjlZSUpA0bNtitv5NJUOvVq6dXX31VK1euzPP288rNzU1eXl6aN2+e4uLilJGRodOnT+vIkSN3tT3gfiAQAUA++uCDD3Tx4kV16tRJEyZMUO/evbNtl5GRoRkzZqhNmzbauHGjZs2aZXd9j4eHh3r27KnBgwfL29tbr7zySpZt1KtXT35+fho3bpyGDBmSZcLSO50EdciQIXrkkUfyvP07MWfOHDk5Oalv375q06aNpk2bZhcAgYJmyr1J4eXl5WWVpKNHjxbp4ygIme9VThMdomCZzWZJ/N/Ni/zu54W9b0RERMjf3z/LTY7vlp+fn3r27Ck/P7/7UF3R4qh+x9+q3BWG94hriADAAC5fvqy9e/cyCSqQAwIRABjAs88+q+rVqzMJKpADAhEAFGK3u6ffnchpQkgAN3FRNQAAMDwCEQAAMDwCEQAAMDwCEQAAMDwCEQAAMDwCEQAAMDwCEQAAMDwCEQAAMDwCEQAAMDwCEQAAMDwCEQAAMDwCEQAAMDwCEQAAMDwCEQAAMDwCEQAAMDwCEQAAMLySji4ABctsNju6BAAACh1GiAzCarUedHQNsGe1Wo84ugYAwE2MEBnEsWPHfBxdA1CYMXoKGBsjRAAAwPAYIQIASeHh4Y4uAfmMUUDcDiNEAADA8AhEAADA8AhEAADA8AhEAADA8AhEAADA8AhEAADA8AhEAADA8AhEAADA8AhEAADA8AhEAADA8AhEAADA8AhEAIAsrl+/7ugSgAJFIAKAYujAgQP6+eefc1wfFxenmJgYSVL79u0lSZGRkbp48aJSUlLUoUMHpaamFkitQGFAIAKAYmbLli366KOP5OrqKklas2aNTpw4Ydfm0KFDmjFjhu251WpVYGCgoqKiFBERoTp16sjFxaVA6wYciUAEAMXEtWvXNGfOHB08eFCrV69WgwYNlJ6eroYNG+qtt97S2rVrbW179+4tZ2dnxcbGSpJ++eUXPfzwwzKbzfruu+/k4eHhqMMAHKKkowsAANwfkyZN0qFDh/Tggw/qhRdekIuLi8qUKSNXV1e5u7tr69atio2N1bhx49S3b19J0qhRo5SSkqIpU6ZIkr7//nvt3r1bLi4u6tatm65evaq0tDSNHTtWvXr1cuThAfmKQAQAxcS0adPk4uIiV1dXTZs2TfXq1ZO/v79tfUpKii5cuCBJCg4OVlRUlAIDA/Xf//5Xzz77rAYNGqTPP/9ciYmJ+uKLL1S1alV98sknSk5OJgyh2CMQAUAx8Pzzz9sex8bGqkKFCjp27Jg+//xzxcfHq3Tp0ipbtqwkydnZWe3bt9dPP/2kgIAADR48WA0aNNCIESP0xBNPqFmzZoqMjFTVqlUVGRmp1q1bO+qwgAJDIAKAYmD79u2yWq36+9//rn/961/6+OOP5ezsrC+++EK1a9fW+++/r1mzZqlhw4ayWq3av3+/Ro0apaCgIE2ZMkU+Pj5q1qyZypcvr02bNunQoUNq3ry5fvzxR73++uuOPjwg3xGIAKAYOHv2rAIDA1WpUiXNnTtXO3fu1IYNG9SmTRs9/fTTmjFjhsaPHy8fHx+9+OKLWrp0qT7++GOdO3dOYWFhWrp0qSRpxYoV8vHx0YABA1S7dm3VrFlTtWrVcvDRAfmPb5kBQBEXHR2tV199VZ06dZLFYtGLL76oc+fOadmyZercubPGjRun3377TevWrdONGzfUr18/LViwQOnp6QoODlZwcLACAwNVsmRJVahQQdWqVVPbtm01d+5cDRs2zNGHBxQIRogAoIh76KGHtH37drm4uOjRRx/VmDFjFBoaqnfeeUdlypTRyy+/rEaNGmnLli0aM2aMxowZo/j4eDVp0kQBAQHq2bOnVq1apYCAADk5OclisSg5OVmSmJwRhsEIEQAUAy4uLvryyy8VGBioV199VdHR0QoICNDs2bP1888/a9CgQZIkJycnlSpVSjVr1tSMGTPUuHFjBQUFKTk5WadOnVJ6erqmT5+uxMREBQUFadq0aQoODnbw0QH5jxEiACgmvLy89Oijj6pUqVIKDQ3VkiVLdPr0aT3//PNau3atKlWqJElKTk7W3LlzFR4ervbt22v79u26dOmSQkNDNXLkSJUpU0aLFy+Wq6ur5s2bpwkTJsjJyUk9e/Z08BEC+YdABADFxNq1a7V3716VKVNGzZs3l5+fn5o1ayZnZ2e7duXKldMzzzyjSZMmqXTp0pKkSpUqqX79+mrSpIk8PT1lMpkkSa1atdLmzZv14IMPFvjxAAWJQAQAxcSgQYM0fPhw2z3Mbqddu3bZLvfy8sqyzM3N7Z5rAwo7AhEAFBNVqlRxdAlAkcVF1QAAwPAIRAAAwPAIRAAAwPAIRACAO3b27Fn16tWLiRtRbBCIAAB37PLlyzp79qyjywDuGwIRAOSTI0eOaODAgWrZsqW6d++usLAwSVJERITMZrN27Nihp59+WvPmzZMkJSYmauzYsfL29lb37t21YsUKmc1mpaam2l6TkpJi237mslvX79y5U507d1aXLl105MgRrVu3Tj4+PurUqZO+/fZb22tTU1P14YcfysfHR23bttW7775ru11H5rYOHz6sgQMHqlWrVurXr59Onjxpe72/v78kydvbW2az2bZ848aN6ty5s7y9vW3HlZM+ffro008/vbc3GbhPCEQAkE+uXr2qyZMn69ChQ+rQoYNmz55tt/7w4cPauXOnRowYIUkKCAjQlStXtHPnTq1YsUKHDh26432eOXNG27ZtU6tWrfTee+8pKipKu3btUocOHTR//nxbu1mzZunXX3/Vxo0bFRISokuXLikoKMhuW8HBwVq0aJG+/PJLVa9eXTNnzrStW7lypSQpLCxM4eHhkm7eZHbu3LmaNWuW9u/fL19f39vW+vzzz8vT0/OOjxHIDwQiAMgnPj4+cnd3V2RkpMqVK6eYmBilp6fb1g8ZMkRly5ZVuXLldOnSJX333XcaM2aMqlSpoqpVq+qVV1654332799frq6u6tq1qxISEuTv7y9XV1d16dJF586dU0ZGhi5duqTdu3dr4sSJcnNzU8WKFTVo0CDt37/fblujR49WlSpVVKFCBfn5+en06dOyWCw57tvZ2Vkmk0nnz5+Xq6urGjdufNtahwwZku1EkIAjMDEjAOSTxYsXa8eOHfLw8FCpUqUkyS5QPPTQQ7bH58+flyTVrVvXtqx8+fJ3vM+KFStKkm226szJGjP3n5GRofPnz8tqtWrAgAFZXp+WlmZ7XLlyZbtarFar0tPT5eLiku2+3dzcNHPmTC1cuFBr167VpEmTGAFCkUEgAoB8EB0drZUrV+qzzz6Tu7u7wsLCtHfvXrs2mfcLk27eX0ySLly4YHscFxdnW58ZQq5fv24LO5nX/NypzJu87tq1S9WrV7+rbeTE19dXHTt21KJFizR+/Hjt27fvvm4fyC+cMgOAfJB5aiw2NlZJSUnasGHDbdvXrl1b9evX1+LFi5WUlKSYmBitXr3atr5evXpydXVVSEiIJOnGjRtas2bNXdXm5uYmLy8vzZs3T3FxccrIyNDp06d15MiRPG+jQoUKkqSffvpJSUlJkm4e608//SSTyaTatWsrNTVVVqs1x22EhobqP//5z10dA3C/EYgAIB/Uq1dPfn5+GjdunIYMGaLWrVvn+po5c+YoPj5enTt31sSJE9WrVy9JUsmSJVWqVCkFBgZqy5Yt6tGjh0aOHJmnbd5uX05OTurbt6/atGmjadOm3Ta8/FXdunXVu3dvjRkzRn369JF083TcjBkz1KZNG23cuFGzZs2yGwX7q+nTp+vGjRt3fQwA/o+Xl5fVy8sr7z0YQJGT3/08c/uF0Y4dO6y+vr6OLiNfREdHW5977rkC3aej/mbwtyp3heE9YoQIAAqJAwcOKCYmRhkZGTpx4oSWL1+u559/3tFl5Yvjx4+rQ4cOji4DsOGiagAoJKKiovThhx/q0qVLqlKlirp166Zhw4Y5uqx84evrm+s8RUBBIhABQCHx0ksv6aWXXnJ0GYAhccoMAAAYHoEIAIqQ9evX68KFC44uAyh2OGUGAEVIfHy8/vnPf2rChAk5tunSpYvdjNe3Sk9PV0ZGhlatWnXb/URERMjf31+HDh2yTQR5q7i4OL366qsKDg6WkxOfrVH0EYgAoBCKi4uz3VE+04ULF1StWjVJ0ubNm22PM+3Zs+eu9nX27FmNGTNGmzZtyvG2HH/l5uambdu23dX+gMKIQAQAhZCbm5v27Nkji8Wic+fOqW7duvL29raFnubNm2v37t06d+6c6tSpc0/7unz5ss6ePXs/ygaKLMY5AaAQmzNnjhYuXJjtugsXLmj06NEKDQ2VJL399tsaOnSoLl68qPT09Gx/rl69qhMnTmjo0KG224BkjkR5e3vLbDbb7eP48eMaOHCgWrVqpRdeeEERERGSbp5SM5vNSklJkSRt3LhRnTt3lre3t+bNm5cfbwWQrxghAoBC6qOPPtLp06e1dOnSbNe7ublp4cKFGjFihMaNG6f58+ff1X5Wrlwpf39/hYWFZTlltnnzZn300UcqXbq0pkyZolmzZmnTpk12baKjozV37lwtW7ZMTZo00e+//35XdQCORCACgEIoISFBsbGxWrJkicqUKSNJev31123rx48fL0l6+OGHNX/+fG3btk0dO3aUdHOkp2nTpra2ERERds//+9//2kaHcjNmzBjbtUoDBgzQ6NGjZbFY7No4OzvLZDLp/PnzatGihRo3bnwXRww4FoEIAAqhSpUqac6cOfL19dW1a9d07do1VapUye4O94sWLVLHjh0VEBCQbyGkatWqtsdly5aV1WpVenq6XRs3NzfNnDlTCxcu1Nq1azVp0iR5enrmSz1AfiEQAUAhtmfPHsXHx+vFF1/UtGnT1LJlS0lSZGSkxo4dq8GDB2d5TbVq1bR8+XLb827dumV5fr/5+vqqY8eOWrRokcaPH699+/bd930A+YlABACFXOXKlRUUFKR33nlHkyZNUlpamhYuXKiAgAC5u7tnaZ+QkKDhw4fbnsfHx9s9L1GihF37ChUqSJJ++uknPfroo7bneRUbG6u4uDg1adJEtWvXVmpqqqxWq0wm0x1tB3AkAhEAFAGPP/64hg4dqrfeeksmk0nvv/9+lm+EJScn6+2339Zjjz122225ublp+PDhtlGjunXrqnfv3hozZozKlSt3x6M7GRkZmjFjhmJiYlSrVi3NmjWLMIQip0j/j/Xy8rJK0tGjR4v0cQDIWX7388zth4eH58fm71rm/EMnT55UeHi4QkNDVaNGDfXr10+XL1/WunXr5OzsrObNm6tRo0aqWbOmli1blm0QOXnyZLYhqWvXrurbt29BHE6hkBkgC/pvBn+rclcY3iNGiACgEPrzzz81ZswYNWjQQC1atNDLL7+s6tWr29b369dPERER+uGHH/T111+rbNmyWrFiBSMzwF0iEAFAIZSXW2M0bdrU7uv0AO4eM1UDAADDIxABAADDIxABAADDIxABAADDIxABAADDIxABAADDIxABAADDIxABAADDIxABAADDIxABAADDIxABAADD415mAKD/3QkdgDExQgTA0KxW60FH14CCY7Vajzi6BhROjBABMLRjx475OLoGAI7HCBEAADA8AhEAADA8AhEAADA8AhEAADA8AhEAADA8AhEAADA8AhEAADA8AhEAADA8AhEAADA8AhEAADA8AhEAADA8AhEAADA8AhEAADA8AhEAADA8AhEAADA8AhEAADA8AhEAADA8AhEAADA8AhEAADA8AhEAADA8AhEAADA8AhEAADA8AhEAADA8AhEAADA8AhEAADA8AhEAADA8AhEAADA8AhEAADA8AhEAADA8AhEAADA8AhEAADA8AhEAADA8AhEAADA8AhEAADA8AhEAADC8ko4uAAAcydPT87DJZGrh6DpQMKxW68Fjx475OLoOFD6MEAEwNMKQsZhMpg6OrgGFEyNEACApPDzc0SUgn5nNZkeXgEKMESIAAGB4BCIAAGB4BCIAAGB4BCIAAGB4BCIAAGB4BCIAAGB4BCIAAGB4BCIAAGB4BCIAAGB4BCIAAGB4BCIAAGB4BCIAAGB4BCIAAGB4BCIAAGB4BCIAAGB4BCIAAGB4BCIAAGB4BCIAAGB4BCIAAGB4BCIAAGB4BCIAAGB4BCIAAGB4BCIAAGB4BCIAAGB4BCIAAGB4BCIAAGB4BCIAAGB4BCIAKGKSkpKyXX7hwoUCrgQoPghEAHCfREVFaezYsZJuhpMBAwbky366d++e7fKePXsqMjJSb7/9tv7880/b8sTERG3evFmSdObMGZ0+fdq27osvvtC///3vfKkTKEpKOroAACguvvrqK1WqVEmStG/fPj322GO3bZ+amipvb2+VK1fObnlycrLdsuTkZB05ckQlSpS47fZKlCihhx9+WB07dtSWLVv02muv2eo6deqUpJuhbfXq1Vq1apUkaefOnRo/fvydHShQDBGIAOA+sFqt2rlzp6ZNmyaLxaItW7bo0qVLCgsLy9K2U6dOevvttyVJTk5O+uabb2zrMjIy1KJFC7tlZrM52336+vraPb927Zqee+452/OyZctq8ODB2rx5s/78808dPnxYQUFBioqK0saNG/XPf/5TSUlJGjFihO0106dPV4sWLe7uTQCKMAIRANwHYWFhiomJ0ZNPPqldu3apcuXK+vzzz9W8eXP961//ypd97tmzx+55p06dtHXrVrm6utqW7dy5UyVKlNCBAwdkMpkkSf/4xz/00EMP6dFHH9WePXt07do1zZgxI19qBIoKriECgPtg+fLlkqQrV65o8eLFev311/P0OovFoqefftr206lTJ0myW5Zp+PDh8vX11dWrV7OMDklS6dKldf36dbtln3zyicqUKaPu3burW7duioqKUqNGjVS2bFmFhoaqbdu2+u6777Jsa+PGjercubO8vb01b948u3pXrlypHj16qGXLluratatOnjwpSUpLS9PSpUvVrVs327pPPvlEFotFkhQRESGz2azQ0FD17dtX3t7eeuONN5SYmGjbfmpqqj788EP5+Piobdu2evfdd5WcnJyn9xK4F4wQAcA92rt3r65duybp5imvQYMG6YknnrCt/2t4Wblypdzc3CTdPGV24MAB27rMU2a3Lss8ZZYZutq3b689e/aoW7duttGglJQUubq66sqVK0pISNCECRO0adMmzZo1Sx4eHnr66ad14MAB9e7dW2fPntWPP/6osLAwDRs2LMvxREdHa+7cuVq2bJmaNGmi33//3bZuwYIF+uabbzRz5kw1btxYZ8+eVZkyZSRJgYGB+uWXXzR//ny5u7vrl19+0cSJE5Wenm67nkmSduzYoeXLlys9PV1vvvmm5s6dq8DAQEnSrFmzFB0drY0bN6pUqVKaNGmSgoKCFBAQcKf/LDny8vKy3reNodhghAgA7tH27dv1yiuvSJIqVqyoQYMG2a3fs2eP3U9mGMrIyJCzs/M97Xvz5s22b5BVqFBB8fHxWrBggZo1a6aSJUvKw8PDrn1wcLAqVKggSYqPj1fPnj115coV+fr6ytfXV0lJSXJ2dpbJZNL58+fl6uqqxo0bS7o5+rVp0yZNnTpVTzzxhEqWLCl3d3fVqFFDiYmJCgkJ0XvvvaeGDRva9j1ixAgFBwfb1fDaa6+pUqVKqlatmvz9/fXtt99Kki5duqTdu3dr4sSJcnNzs72X+/fvv6f3qJBIdXQBuD1GiADgHg0fPlxPPvmkJk2adEevu3HjhlJTU22nyW6V3bLs9OvXz/a4UqVKWrZsmU6cOKGpU6dKkrp16ybpZpjp1q2bPvnkE1v7zGuQnn76abvrkSpUqKCZM2dq4cKFWrt2rSZNmiRPT0/FxMQoIyNDjRo1ylJHbGysrFar3N3d7ZbXqVNHCQkJttNmklStWjXb46pVqyolJUUWi0Xnz5+X1WrNdrqCtLS0ew6Pt8h6vjGfmUym3wp6n7gzBCIAuEdPPvnkXb0uKSlJjRo10rp162zLMk+Z7du3z7Ysp2+ZSbKNDr3wwguqXr269u/fr2HDhtlGoUJCQiTdDD2ZjzNlnsrLHCGSJHd3dy1ZskS+vr7q2LGjFi1apPHjx2vfvn168MEHJUlnz561jRplqlq1qqSbX+tv0qSJbXl0dLTc3Nzk5PS/ExLJycm2U31RUVGqVq2anJycbFMW7Nq1S9WrV7/9m3cPjh49+kW+bRxFFqfMACCfZZ6OyvwJDw+XJMXExKhWrVp3tK309HSlpaX9//bu36XKPQ7g+OccLmKBSBEIYfhjr0FrCQkuLRkNEc4VCUIF1eCQgQ2SkdFiKDWEf0FDS2vcJQKhcohAIyNKqskWk+w8njuEh8qL91f3nu79vF6TPkePH8/05vt8n+eJ4eHh2r2EIiJu3LgRDQ0NsX379ujv74/Z2dna31lz//79WFhYqH2/dgqvqamp9vXk5GS8efMmZmZmolQqxY4dO2JlZSWq1Wq0tLTEvn37YnR0NObm5qIoipidnY2FhYXYtm1b7N+/P0ZHR+PZs2dRFEU8efIkuUJZ7gAABKVJREFUbt68GUePHv1qjomJiVhaWoqXL1/G1NRU7UaTLS0t0dXVFdeuXYt3795FURQxNzcX09PTf+ozgr/CChHAP+zby+PXzMzMrFtp2ciFCxfi4cOH0dvbG52dnTE1NRXz8/Px+vXraGxsjPn5+WhqaoqiKGJmZibm5uaiu7s7lpeX48OHD3Hv3r04cOBAVCqVuHz5cpw8ebK26vOloihiZGSkFmyXLl2qXbI/Ojoa4+PjcerUqVhaWor29vbahuiRkZGYmJiI06dPx/v376O1tTWOHz8efX19X73/rl274vDhw/Hx48fo7e2t7b+KiBgbG4srV65EX19ffPr0KTo7O+Ps2bN/+DOCv0oQAdRBpVKJu3fvxsTExG++Xq1WoyiKWFxcjHK5HKVSKY4cORIXL16MxsbGePHiRczOzkZfX1+0tbXF2NhY7N27N96+fRuTk5OxvLwcHR0dEfH5MSJ79uyJ8+fPx/DwcNy+fTvu3LkTx44di6WlpWhoaIje3t4oiiIOHToUZ86cWbcRes3mzZtjaGjoN/dLNTY2xuDgYAwODm74vx88eHBdJK3ZunVrXL16dcPfh3+CIAL4Tvr7+//QsYiIp0+fRmtra7S3t391vFQqxaZNm2J1dTV6enqiUqlET09PlMvl2L17d+3nOjo6asGzuLgYz58/j/Hx8VhZWYlz587Fq1ev4sSJExER0dbWFtevX49SqRRDQ0PR3NwcAwMDMTAwEBGf7/2zuroa5XL5e25chv8UQQTwnXz5CIyNjkV8Pm305Q0P15TL5dqNEh88eBCVSuV3I2XLli1x69atiPj8uI4v9xatWTvl1dzcvO61hoaGDd8fMhBEAHXy7UNdv1Uqlf5XKzY7d+5ct9EbfhSuMgMA0hNEAEB6gggASE8QAQDpCSIAID1BBACkJ4gAgPQEEQCQniACANITRABAeoIIAEhPEAEA6QkiACA9QQQApCeIAID0BBEAkJ4gAgDSE0QAQHqCCABITxABAOkJIgAgPUEEAKQniACA9AQRAJCeIAIA0hNEAEB6P9V7AIAfQXd3d71HAOrIChGQWrVa/aXeM/DvqVar0/WegR+TFSIgtcePH/9c7xmA+rNCBACkJ4gAgPQEEQCQniACANITRABAeoIIAEhPEAEA6QkiACA9QQQApCeIAID0BBEAkJ4gAgDSE0QAQHqCCABITxABAOkJIgAgPUEEAKQniACA9AQRAJCeIAIA0hNEAEB6gggASE8QAQDpCSIAID1BBACkJ4gAgPQEEQCQniACANITRABAeoIIAEhPEAEA6QkiACA9QQQApCeIAID0BBEAkJ4gAgDSE0QAQHqCCABITxABAOkJIgAgPUEEAKQniACA9AQRAJCeIAIA0hNEAEB6gggASE8QAQDpCSIAID1BBACkJ4gAgPQEEQCQniACANIr1XuAv6Orq6ta7xkAgO/j0aNHdeuS//QKUbVa/aXeMwAAf1+1Wp2u9wwAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAADwP/craqqh0sOPQQUAAAAASUVORK5CYIIA" alt="" />

一般函数在执行完成后，会销毁其执行环境，只保留全局执行环境中变量；但是在闭包中，由于闭包并不是立即执行，而是保存着内部函数执行需要的所有变量，包括内部变量和外部变量；在需要时再执行；函数执行完毕后；由于内部匿名函数的作用于链依然引用这个活动对象；因此活动对象仍然会保存在内存中。

3、闭包的缺陷

闭包只是对函数内部的活动对象的保留，JavaScript中对变量只能保存一个定义；即 i 只能保存一个值，也就是上例中 i=10；闭包不是立即执行，当闭包执行时；向上搜索函数用到的所有变量，而内存中保存的是最后一次i的值；因此 i=10；

闭包会引用包含它函数的作用域，因此比普通函数占用更多的内存。

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