fundamentals/collections.ipynb

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    "* Ref: [Introduction to Python's Collections Module](https://stackabuse.com/introduction-to-pythons-collections-module/)\n",
    "\n",
    "Collections in Python are containers that are used to **store collections of data**, for example, **list, dict, set, tuple etc**. These are built-in collections. Several modules have been developed that provide additional data structures to store collections of data. One such module is the Python collections module.\n",
    "\n",
    "Python collections module was introduced to improve the functionalities of the built-in collection containers. Python collections module was first introduced in its 2.4 release. This tutorial is based on its latest stable release (3.7 version).\n",
    "\n",
    "* Ref: [collections](https://www.liaoxuefeng.com/wiki/0014316089557264a6b348958f449949df42a6d3a2e542c000/001431953239820157155d21c494e5786fce303f3018c86000#0)\n",
    "\n",
    "Some commonly used collections data structures are introduced as follows:\n",
    "\n",
    "- `Counter` (dict)\n",
    "- `defaultdict` (dict)\n",
    "- `OrderedDict` (dict)\n",
    "- `deque` (list)\n",
    "- `ChainMap` (dict)\n",
    "- `namedtuple` (tuple)"
   ]
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      "text/plain": [
       "Counter({'p': 1, 'r': 2, 'o': 1, 'g': 2, 'a': 1, 'm': 2, 'i': 1, 'n': 1})"
      ]
     },
     "execution_count": 1,
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   "source": [
    "# Counter，a subclass of dictionary object\n",
    "from collections import Counter\n",
    "\n",
    "# namely, Counter is a counter\n",
    "c = Counter()\n",
    "# cnt is the object of Counter class\n",
    "# and Counter is the subclass of dict\n",
    "for ch in 'programming':\n",
    "    c[ch] = c[ch] + 1 # character as key\n",
    "    \n",
    "c"
   ]
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     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-2-0125ef5f70da>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m     10\u001b[0m \u001b[0mdict1\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m{\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;34m'a'\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;36m2\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;34m'b'\u001b[0m\u001b[1;33m}\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     11\u001b[0m \u001b[0mdict1\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 12\u001b[1;33m \u001b[0mdict1\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m3\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;31m# key does not exist\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;31mKeyError\u001b[0m: 3"
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   "source": [
    "# defaultdict，works exactly like a python dictionary, \n",
    "# except for it does not throw KeyError when you try to access a non-existent key.\n",
    "from collections import defaultdict\n",
    "\n",
    "dd = defaultdict(lambda: 'N/A')\n",
    "dd['key1'] = 'abc'\n",
    "dd['key1'] # key1存在\n",
    "dd['key2'] # key2不存在，返回默认值\n",
    "\n",
    "dict1 = {1:'a',2:'b'}\n",
    "dict1[1]\n",
    "dict1[3] # key does not exist"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "OrderedDict([('a', 1), ('b', 2), ('c', 3)])"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# OrderedDict\n",
    "# 使用dict时，Key是无序的。在对dict做迭代时，我们无法确定Key的顺序。如果要保持Key的顺序，可以用OrderedDict\n",
    "# OrderedDict的Key会按照插入的顺序排列，不是Key本身排序\n",
    "\n",
    "from collections import OrderedDict\n",
    "\n",
    "d = dict([('a', 1), ('b', 2), ('c', 3)])  # dict 的key无序\n",
    "d\n",
    "\n",
    "od = OrderedDict([('a', 1), ('b', 2), ('c', 3)])\n",
    "od"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "deque(['y', 'a', 'b', 'c', 'x'])"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# deque\n",
    "# list线性存储，索引访问快，插入删除慢\n",
    "# 引入deque，实现双向插入和删除，适用于队列和栈\n",
    "from collections import deque\n",
    "\n",
    "q = deque(['a', 'b', 'c'])\n",
    "q.append('x')\n",
    "q.appendleft('y')\n",
    "q"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
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     "output_type": "stream",
     "text": [
      "[{'a': 1, 'b': 2}, {'c': 3, 'b': 4}]\n"
     ]
    }
   ],
   "source": [
    "# ChainMap\n",
    "# ChainMap可以把一组dict串起来并组成一个逻辑上的dict。\n",
    "# ChainMap本身也是一个dict，但是查找的时候，会按照顺序在内部的dict依次查找。\n",
    "from collections import ChainMap\n",
    "\n",
    "dict1 = { 'a' : 1, 'b' : 2 }  \n",
    "dict2 = { 'c' : 3, 'b' : 4 }  \n",
    "chain_map = ChainMap(dict1, dict2)  \n",
    "print(chain_map.maps)  "
   ]
  },
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   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
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     "data": {
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       "1"
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     "execution_count": 6,
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   "source": [
    "# namedtuple\n",
    "# namedtuple是一个函数，它用来创建一个自定义的tuple对象，\n",
    "# 并且规定了tuple元素的个数，并可以用属性而不是索引来引用tuple的某个元素。\n",
    "from collections import namedtuple\n",
    "\n",
    "Point = namedtuple('Point', ['x', 'y'])\n",
    "p = Point(1, 2)\n",
    "p.x"
   ]
  }
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