pg.167

.vscode/settings.json

@@ -0,0 +1,3 @@
+{
+    "python.formatting.provider": "black"
+}

Part_3-Fuctions_as_Objects/Chap_5-First_Class_Functions/ex_5_21__factorial_with_reduced_and_anonymous.py

@@ -0,0 +1,4 @@
+from functools import reduce
+
+def fact(n):
+    return reduce(lambda a, b: a*b, range(1, n+1))

Part_3-Fuctions_as_Objects/Chap_5-First_Class_Functions/ex_5_22__factorial_with_reduced_and_operator.py

@@ -0,0 +1,5 @@
+from functools import reduce
+from operator import mul
+
+def fact(n):
+    return reduce(mul, range(1, n+1))

Part_3-Fuctions_as_Objects/Chap_5-First_Class_Functions/ex_5_23a__metro_data.py

@@ -0,0 +1,7 @@
+metro_data = [
+    ('Tokyo', 'JP', 36.933, (35.689722, 139.691667)),
+    ('Delhi NCR', 'IN', 21.935, (28.613889, 77.208889)),
+    ('Mexico City', 'MX', 20.142, (19.433333, -99.133333)),
+    ('New York-Newark', 'US', 20.104, (40.808611, -74.020386)),
+    ('Sao Paulo', 'BR', 19.649, (-23.547778, -46.635833)),
+]

Part_3-Fuctions_as_Objects/Chap_5-First_Class_Functions/ex_5_23b__demo_of_itemgetter.ipynb

@@ -0,0 +1,82 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "source": [
+    "from operator import itemgetter\n",
+    "from ex_5_23a__metro_data import metro_data\n",
+    "for city in sorted(metro_data, key=itemgetter(1)):\n",
+    "    print(city)"
+   ],
+   "outputs": [
+    {
+     "output_type": "stream",
+     "name": "stdout",
+     "text": [
+      "('Sao Paulo', 'BR', 19.649, (-23.547778, -46.635833))\n",
+      "('Delhi NCR', 'IN', 21.935, (28.613889, 77.208889))\n",
+      "('Tokyo', 'JP', 36.933, (35.689722, 139.691667))\n",
+      "('Mexico City', 'MX', 20.142, (19.433333, -99.133333))\n",
+      "('New York-Newark', 'US', 20.104, (40.808611, -74.020386))\n"
+     ]
+    }
+   ],
+   "metadata": {}
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "source": [
+    "cc_name = itemgetter(1, 0)\n",
+    "for city in metro_data:\n",
+    "    print(cc_name(city))"
+   ],
+   "outputs": [
+    {
+     "output_type": "stream",
+     "name": "stdout",
+     "text": [
+      "('JP', 'Tokyo')\n",
+      "('IN', 'Delhi NCR')\n",
+      "('MX', 'Mexico City')\n",
+      "('US', 'New York-Newark')\n",
+      "('BR', 'Sao Paulo')\n"
+     ]
+    }
+   ],
+   "metadata": {}
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "source": [],
+   "outputs": [],
+   "metadata": {}
+  }
+ ],
+ "metadata": {
+  "orig_nbformat": 4,
+  "language_info": {
+   "name": "python",
+   "version": "3.8.10",
+   "mimetype": "text/x-python",
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "pygments_lexer": "ipython3",
+   "nbconvert_exporter": "python",
+   "file_extension": ".py"
+  },
+  "kernelspec": {
+   "name": "python3",
+   "display_name": "Python 3.8.10 64-bit ('python-fluent': pyenv)"
+  },
+  "interpreter": {
+   "hash": "37f590f6de04d9a834de345867b5912e86fd172250c2636cb0473472171768e6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

Part_3-Fuctions_as_Objects/Chap_5-First_Class_Functions/ex_5_24__attrgetter_on_namedtuple.ipynb

@@ -0,0 +1,180 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "source": [
+    "from collections import namedtuple\n",
+    "from ex_5_23a__metro_data import metro_data\n",
+    "LatLong = namedtuple('LatLong', 'lat long')\n",
+    "Metropolis = namedtuple('Metropolis', 'name cc pop coord')\n",
+    "metro_areas = [Metropolis(name, cc, pop, LatLong(lat, long))\n",
+    "    for name, cc, pop, (lat, long) in metro_data]\n",
+    "metro_areas[0]"
+   ],
+   "outputs": [
+    {
+     "output_type": "execute_result",
+     "data": {
+      "text/plain": [
+       "Metropolis(name='Tokyo', cc='JP', pop=36.933, coord=LatLong(lat=35.689722, long=139.691667))"
+      ]
+     },
+     "metadata": {},
+     "execution_count": 3
+    }
+   ],
+   "metadata": {}
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "source": [
+    "metro_areas[0].coord.lat"
+   ],
+   "outputs": [
+    {
+     "output_type": "execute_result",
+     "data": {
+      "text/plain": [
+       "35.689722"
+      ]
+     },
+     "metadata": {},
+     "execution_count": 4
+    }
+   ],
+   "metadata": {}
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "source": [
+    "from operator import attrgetter\n",
+    "name_lat = attrgetter('name', 'coord.lat')\n",
+    "\n",
+    "for city in sorted(metro_areas, key=attrgetter('coord.lat')):\n",
+    "    print(name_lat(city))"
+   ],
+   "outputs": [
+    {
+     "output_type": "stream",
+     "name": "stdout",
+     "text": [
+      "('Sao Paulo', -23.547778)\n",
+      "('Mexico City', 19.433333)\n",
+      "('Delhi NCR', 28.613889)\n",
+      "('Tokyo', 35.689722)\n",
+      "('New York-Newark', 40.808611)\n"
+     ]
+    }
+   ],
+   "metadata": {}
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "source": [
+    "import operator\n",
+    "[name for name in dir(operator) if not name.startswith('_')]"
+   ],
+   "outputs": [
+    {
+     "output_type": "execute_result",
+     "data": {
+      "text/plain": [
+       "['abs',\n",
+       " 'add',\n",
+       " 'and_',\n",
+       " 'attrgetter',\n",
+       " 'concat',\n",
+       " 'contains',\n",
+       " 'countOf',\n",
+       " 'delitem',\n",
+       " 'eq',\n",
+       " 'floordiv',\n",
+       " 'ge',\n",
+       " 'getitem',\n",
+       " 'gt',\n",
+       " 'iadd',\n",
+       " 'iand',\n",
+       " 'iconcat',\n",
+       " 'ifloordiv',\n",
+       " 'ilshift',\n",
+       " 'imatmul',\n",
+       " 'imod',\n",
+       " 'imul',\n",
+       " 'index',\n",
+       " 'indexOf',\n",
+       " 'inv',\n",
+       " 'invert',\n",
+       " 'ior',\n",
+       " 'ipow',\n",
+       " 'irshift',\n",
+       " 'is_',\n",
+       " 'is_not',\n",
+       " 'isub',\n",
+       " 'itemgetter',\n",
+       " 'itruediv',\n",
+       " 'ixor',\n",
+       " 'le',\n",
+       " 'length_hint',\n",
+       " 'lshift',\n",
+       " 'lt',\n",
+       " 'matmul',\n",
+       " 'methodcaller',\n",
+       " 'mod',\n",
+       " 'mul',\n",
+       " 'ne',\n",
+       " 'neg',\n",
+       " 'not_',\n",
+       " 'or_',\n",
+       " 'pos',\n",
+       " 'pow',\n",
+       " 'rshift',\n",
+       " 'setitem',\n",
+       " 'sub',\n",
+       " 'truediv',\n",
+       " 'truth',\n",
+       " 'xor']"
+      ]
+     },
+     "metadata": {},
+     "execution_count": 8
+    }
+   ],
+   "metadata": {}
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "source": [],
+   "outputs": [],
+   "metadata": {}
+  }
+ ],
+ "metadata": {
+  "orig_nbformat": 4,
+  "language_info": {
+   "name": "python",
+   "version": "3.8.10",
+   "mimetype": "text/x-python",
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "pygments_lexer": "ipython3",
+   "nbconvert_exporter": "python",
+   "file_extension": ".py"
+  },
+  "kernelspec": {
+   "name": "python3",
+   "display_name": "Python 3.8.10 64-bit ('python-fluent': pyenv)"
+  },
+  "interpreter": {
+   "hash": "37f590f6de04d9a834de345867b5912e86fd172250c2636cb0473472171768e6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

Part_3-Fuctions_as_Objects/Chap_5-First_Class_Functions/ex_5_25__demo_of_methodcaller.ipynb

@@ -0,0 +1,79 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "source": [
+    "from operator import methodcaller\n",
+    "s = 'The time has come'\n",
+    "upcase = methodcaller('upper')\n",
+    "upcase(s)"
+   ],
+   "outputs": [
+    {
+     "output_type": "execute_result",
+     "data": {
+      "text/plain": [
+       "'THE TIME HAS COME'"
+      ]
+     },
+     "metadata": {},
+     "execution_count": 1
+    }
+   ],
+   "metadata": {}
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "source": [
+    "hiphanate = methodcaller('replace', ' ', '-')\n",
+    "hiphanate(s)"
+   ],
+   "outputs": [
+    {
+     "output_type": "execute_result",
+     "data": {
+      "text/plain": [
+       "'The-time-has-come'"
+      ]
+     },
+     "metadata": {},
+     "execution_count": 2
+    }
+   ],
+   "metadata": {}
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "source": [],
+   "outputs": [],
+   "metadata": {}
+  }
+ ],
+ "metadata": {
+  "orig_nbformat": 4,
+  "language_info": {
+   "name": "python",
+   "version": "3.8.10",
+   "mimetype": "text/x-python",
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "pygments_lexer": "ipython3",
+   "nbconvert_exporter": "python",
+   "file_extension": ".py"
+  },
+  "kernelspec": {
+   "name": "python3",
+   "display_name": "Python 3.8.10 64-bit ('python-fluent': pyenv)"
+  },
+  "interpreter": {
+   "hash": "37f590f6de04d9a834de345867b5912e86fd172250c2636cb0473472171768e6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}