diff --git a/python_course_2018.ipynb b/python_course_2018.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..fafc1cf40c7e0e090e2b2be57ae8f6eb0cb89dab
--- /dev/null
+++ b/python_course_2018.ipynb
@@ -0,0 +1,1431 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "False"
+ ]
+ },
+ "execution_count": 1,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "1 == 2"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "True"
+ ]
+ },
+ "execution_count": 2,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "1 == 1"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "True"
+ ]
+ },
+ "execution_count": 3,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "1 is 1"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "140184959628256"
+ ]
+ },
+ "execution_count": 4,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "id(1)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "True"
+ ]
+ },
+ "execution_count": 5,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "a = 1\n",
+ "b = 1\n",
+ "a is b"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "False"
+ ]
+ },
+ "execution_count": 7,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "a = 257\n",
+ "b = 257\n",
+ "a is b"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 8,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def name():\n",
+ " print(\"ciao\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 9,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "ciao\n"
+ ]
+ }
+ ],
+ "source": [
+ "name()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 20,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def hello(name):\n",
+ " print(f\"ciao {name:05d}!\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 21,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "ciao 00012!\n"
+ ]
+ }
+ ],
+ "source": [
+ "hello(12)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 22,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "'12'"
+ ]
+ },
+ "execution_count": 22,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "\"%d\" % 12"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 23,
+ "metadata": {},
+ "outputs": [
+ {
+ "ename": "TypeError",
+ "evalue": "hello() missing 1 required positional argument: 'name'",
+ "output_type": "error",
+ "traceback": [
+ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+ "\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
+ "\u001b[0;32m<ipython-input-23-a75d7781aaeb>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mhello\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
+ "\u001b[0;31mTypeError\u001b[0m: hello() missing 1 required positional argument: 'name'"
+ ]
+ }
+ ],
+ "source": [
+ "hello()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 30,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def hello(name, phrase=\"ciao {name}!\"):\n",
+ " print(phrase.format(name=name))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 31,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "ciao jenny!\n"
+ ]
+ }
+ ],
+ "source": [
+ "hello(\"jenny\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 33,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def hello(phrase=\"ciao {name}!\", *names):\n",
+ " for name in names:\n",
+ " print(phrase.format(name=name))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 34,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "pietro\n",
+ "pietro\n"
+ ]
+ }
+ ],
+ "source": [
+ "hello(\"pietro\", \"bart\", \"mauro\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 35,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "ciao pietro!\n",
+ "ciao bart!\n",
+ "ciao mauro!\n"
+ ]
+ }
+ ],
+ "source": [
+ "def hello(*names):\n",
+ " for name in names:\n",
+ " print(\"ciao {name}!\".format(name=name))\n",
+ " \n",
+ "hello(\"pietro\", \"bart\", \"mauro\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 42,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "ciao pietro! ciao pietro! ciao pietro! \n",
+ "ciao bart! ciao bart! ciao bart! \n",
+ "ciao mauro! ciao mauro! ciao mauro! \n"
+ ]
+ }
+ ],
+ "source": [
+ "def hello(names: list, repeat : int =3):\n",
+ " for name in names:\n",
+ " print(\"ciao {name}! \".format(name=name) * repeat)\n",
+ " \n",
+ "hello([\"pietro\", \"bart\", \"mauro\"])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 43,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "diz = dict(pietro=1982, )"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 44,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "1982"
+ ]
+ },
+ "execution_count": 44,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "diz[\"pietro\"]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 45,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "class Rectangle():\n",
+ " def __init__(self, a: float, b: float):\n",
+ " self.a = a\n",
+ " self.b = b"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 46,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "rect0 = Rectangle(2, 3)\n",
+ "rect1 = Rectangle(4, 5)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 47,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "{<__main__.Rectangle at 0x7f7f4d750710>: 0,\n",
+ " <__main__.Rectangle at 0x7f7f4d7505f8>: 1}"
+ ]
+ },
+ "execution_count": 47,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "{rect0: 0, rect1: 1}"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 48,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "{__main__.Rectangle: 1}"
+ ]
+ },
+ "execution_count": 48,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "{Rectangle: 0, Rectangle: 1}"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 49,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "'asjcvbvjwe'"
+ ]
+ },
+ "execution_count": 49,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "\"asjc\" + \"vbvjwe\""
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 50,
+ "metadata": {},
+ "outputs": [
+ {
+ "ename": "TypeError",
+ "evalue": "can only concatenate str (not \"int\") to str",
+ "output_type": "error",
+ "traceback": [
+ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+ "\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
+ "\u001b[0;32m<ipython-input-50-ccdfa72cd790>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0;34m\"asjc\"\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0;36m2\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
+ "\u001b[0;31mTypeError\u001b[0m: can only concatenate str (not \"int\") to str"
+ ]
+ }
+ ],
+ "source": [
+ "\"asjc\" + 2"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 51,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "'=================================================='"
+ ]
+ },
+ "execution_count": 51,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "\"=\" * 50"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 52,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "['a', 'b', 'c', 'd']"
+ ]
+ },
+ "execution_count": 52,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "['a', 'b'] + ['c', 'd'] "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 53,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "['a', 'b', 'a', 'b']"
+ ]
+ },
+ "execution_count": 53,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "['a', 'b'] * 2"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 60,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def hello(**kwargs):\n",
+ " for k, v in kwargs.items():\n",
+ " print(f\"key: {k}, value: {v}\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 55,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "key: pietro, value: urs\n",
+ "key: bart, value: remote_sensing\n"
+ ]
+ }
+ ],
+ "source": [
+ "hello(pietro=\"urs\", bart=\"remote_sensing\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 56,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def hello(pietro=\"urs\", bart=\"remote_sensing\"):\n",
+ " print(f\"key: pietro, value: {pietro}\")\n",
+ " print(f\"key: bart, value: {bart}\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 57,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "key: pietro, value: urs\n",
+ "key: bart, value: remote_sensing\n"
+ ]
+ }
+ ],
+ "source": [
+ "hello()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 58,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "mydict = dict(pietro=\"urs\", bart=\"remote_sensing\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 59,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "{'pietro': 'urs', 'bart': 'remote_sensing'}"
+ ]
+ },
+ "execution_count": 59,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "mydict"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 62,
+ "metadata": {},
+ "outputs": [
+ {
+ "ename": "TypeError",
+ "evalue": "hello() takes 0 positional arguments but 1 was given",
+ "output_type": "error",
+ "traceback": [
+ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+ "\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
+ "\u001b[0;32m<ipython-input-62-84ba45c67bcd>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mhello\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmydict\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
+ "\u001b[0;31mTypeError\u001b[0m: hello() takes 0 positional arguments but 1 was given"
+ ]
+ }
+ ],
+ "source": [
+ "hello(mydict)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 63,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "a = \"fjd\"\n",
+ "b = \"jrhdfj\""
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 64,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "140184737090560"
+ ]
+ },
+ "execution_count": 64,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "id(a)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 65,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "140184737128888"
+ ]
+ },
+ "execution_count": 65,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "id(b)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 66,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "140184737112560"
+ ]
+ },
+ "execution_count": 66,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "id(a+b)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 67,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "a = [1, 2, 3]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 68,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "140184737120328"
+ ]
+ },
+ "execution_count": 68,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "id(a)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 75,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "a.append(['a', 'b'])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 76,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "[1, 2, 3, 'a', 'b', ['a', 'b']]"
+ ]
+ },
+ "execution_count": 76,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "a"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 77,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "140184737120328"
+ ]
+ },
+ "execution_count": 77,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "id(a)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 80,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def append(value, mylist=[]):\n",
+ " mylist.append(value)\n",
+ " return mylist"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 83,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "[2]"
+ ]
+ },
+ "execution_count": 83,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "append(2, [])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 85,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def mylongwork(value, _cache={}):\n",
+ " if value not in _cache:\n",
+ " _cache[value] = abs(value)\n",
+ " return _cache[value]\n",
+ " "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 94,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def func0(a, par=None):\n",
+ " par = [] if par is None else par\n",
+ " def func1(b):\n",
+ " return a * b\n",
+ " return func1\n",
+ " "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 98,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "15"
+ ]
+ },
+ "execution_count": 98,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "f1 = func0(3)\n",
+ "f1(5)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 87,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "{'a': 1, 'b': 1}"
+ ]
+ },
+ "execution_count": 87,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "{k: v for k, v in [('a', 1), ('b', 1)]}"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 93,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "[1, 9, 25, 49, 81]"
+ ]
+ },
+ "execution_count": 93,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "mylist = [i*i for i in range(10) if i % 2]\n",
+ "mylist"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 92,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "[1, 9, 25, 49, 81]"
+ ]
+ },
+ "execution_count": 92,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "mylist = []\n",
+ "for i in range(10):\n",
+ " if i % 2:\n",
+ " mylist.append(i*i)\n",
+ "mylist"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 103,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from functools import lru_cache\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 104,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "@lru_cache(maxsize=32)\n",
+ "def fib_cached(n):\n",
+ " if n < 2:\n",
+ " return n\n",
+ " return fib_cached(n-1) + fib_cached(n-2)\n",
+ "\n",
+ "def fib_std(n):\n",
+ " if n < 2:\n",
+ " return n\n",
+ " return fib_std(n-1) + fib_std(n-2)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 105,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "15.8 ms ± 310 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n"
+ ]
+ }
+ ],
+ "source": [
+ "%timeit fib_std(24)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 106,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "106 ns ± 8.54 ns per loop (mean ± std. dev. of 7 runs, 10000000 loops each)\n"
+ ]
+ }
+ ],
+ "source": [
+ "%timeit fib_cached(24)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 115,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from time import time\n",
+ "\n",
+ "def mydec(func, *args, **kwargs):\n",
+ " start = time()\n",
+ " value = func(*args, **kwargs)\n",
+ " stop = time()\n",
+ " print(f\"It tooks {stop - start}s...\")\n",
+ " return value"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 116,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "It tooks 9.489059448242188e-05s...\n"
+ ]
+ },
+ {
+ "data": {
+ "text/plain": [
+ "144"
+ ]
+ },
+ "execution_count": 116,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "mydec(fib_std, 12)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 118,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def mydec(func):\n",
+ " def wrapper(*args, **kwargs):\n",
+ " start = time()\n",
+ " value = func(*args, **kwargs)\n",
+ " stop = time()\n",
+ " print(f\"It tooks {stop - start}s...\")\n",
+ " return value\n",
+ " return wrapper"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 119,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "@mydec\n",
+ "def fib_std(n):\n",
+ " if n < 2:\n",
+ " return n\n",
+ " return fib_std(n-1) + fib_std(n-2)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 120,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "It tooks 9.5367431640625e-07s...\n",
+ "It tooks 1.1920928955078125e-06s...\n",
+ "It tooks 0.00012040138244628906s...\n",
+ "It tooks 7.152557373046875e-07s...\n",
+ "It tooks 0.00048065185546875s...\n",
+ "It tooks 2.384185791015625e-07s...\n",
+ "It tooks 2.384185791015625e-07s...\n",
+ "It tooks 3.743171691894531e-05s...\n",
+ "It tooks 0.0005590915679931641s...\n",
+ "It tooks 2.384185791015625e-07s...\n",
+ "It tooks 2.384185791015625e-07s...\n",
+ "It tooks 3.0994415283203125e-05s...\n",
+ "It tooks 2.384185791015625e-07s...\n",
+ "It tooks 6.270408630371094e-05s...\n",
+ "It tooks 0.0006537437438964844s...\n"
+ ]
+ },
+ {
+ "data": {
+ "text/plain": [
+ "5"
+ ]
+ },
+ "execution_count": 120,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "fib_std(5)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 121,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import numpy as np"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 123,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "array(object, dtype=None, copy=True, order='K', subok=False, ndmin=0)\n",
+ "\n",
+ " Create an array.\n",
+ "\n",
+ " Parameters\n",
+ " ----------\n",
+ " object : array_like\n",
+ " An array, any object exposing the array interface, an object whose\n",
+ " __array__ method returns an array, or any (nested) sequence.\n",
+ " dtype : data-type, optional\n",
+ " The desired data-type for the array. If not given, then the type will\n",
+ " be determined as the minimum type required to hold the objects in the\n",
+ " sequence. This argument can only be used to 'upcast' the array. For\n",
+ " downcasting, use the .astype(t) method.\n",
+ " copy : bool, optional\n",
+ " If true (default), then the object is copied. Otherwise, a copy will\n",
+ " only be made if __array__ returns a copy, if obj is a nested sequence,\n",
+ " or if a copy is needed to satisfy any of the other requirements\n",
+ " (`dtype`, `order`, etc.).\n",
+ " order : {'K', 'A', 'C', 'F'}, optional\n",
+ " Specify the memory layout of the array. If object is not an array, the\n",
+ " newly created array will be in C order (row major) unless 'F' is\n",
+ " specified, in which case it will be in Fortran order (column major).\n",
+ " If object is an array the following holds.\n",
+ "\n",
+ " ===== ========= ===================================================\n",
+ " order no copy copy=True\n",
+ " ===== ========= ===================================================\n",
+ " 'K' unchanged F & C order preserved, otherwise most similar order\n",
+ " 'A' unchanged F order if input is F and not C, otherwise C order\n",
+ " 'C' C order C order\n",
+ " 'F' F order F order\n",
+ " ===== ========= ===================================================\n",
+ "\n",
+ " When ``copy=False`` and a copy is made for other reasons, the result is\n",
+ " the same as if ``copy=True``, with some exceptions for `A`, see the\n",
+ " Notes section. The default order is 'K'.\n",
+ " subok : bool, optional\n",
+ " If True, then sub-classes will be passed-through, otherwise\n",
+ " the returned array will be forced to be a base-class array (default).\n",
+ " ndmin : int, optional\n",
+ " Specifies the minimum number of dimensions that the resulting\n",
+ " array should have. Ones will be pre-pended to the shape as\n",
+ " needed to meet this requirement.\n",
+ "\n",
+ " Returns\n",
+ " -------\n",
+ " out : ndarray\n",
+ " An array object satisfying the specified requirements.\n",
+ "\n",
+ " See Also\n",
+ " --------\n",
+ " empty_like : Return an empty array with shape and type of input.\n",
+ " ones_like : Return an array of ones with shape and type of input.\n",
+ " zeros_like : Return an array of zeros with shape and type of input.\n",
+ " full_like : Return a new array with shape of input filled with value.\n",
+ " empty : Return a new uninitialized array.\n",
+ " ones : Return a new array setting values to one.\n",
+ " zeros : Return a new array setting values to zero.\n",
+ " full : Return a new array of given shape filled with value.\n",
+ "\n",
+ "\n",
+ " Notes\n",
+ " -----\n",
+ " When order is 'A' and `object` is an array in neither 'C' nor 'F' order,\n",
+ " and a copy is forced by a change in dtype, then the order of the result is\n",
+ " not necessarily 'C' as expected. This is likely a bug.\n",
+ "\n",
+ " Examples\n",
+ " --------\n",
+ " >>> np.array([1, 2, 3])\n",
+ " array([1, 2, 3])\n",
+ "\n",
+ " Upcasting:\n",
+ "\n",
+ " >>> np.array([1, 2, 3.0])\n",
+ " array([ 1., 2., 3.])\n",
+ "\n",
+ " More than one dimension:\n",
+ "\n",
+ " >>> np.array([[1, 2], [3, 4]])\n",
+ " array([[1, 2],\n",
+ " [3, 4]])\n",
+ "\n",
+ " Minimum dimensions 2:\n",
+ "\n",
+ " >>> np.array([1, 2, 3], ndmin=2)\n",
+ " array([[1, 2, 3]])\n",
+ "\n",
+ " Type provided:\n",
+ "\n",
+ " >>> np.array([1, 2, 3], dtype=complex)\n",
+ " array([ 1.+0.j, 2.+0.j, 3.+0.j])\n",
+ "\n",
+ " Data-type consisting of more than one element:\n",
+ "\n",
+ " >>> x = np.array([(1,2),(3,4)],dtype=[('a','<i4'),('b','<i4')])\n",
+ " >>> x['a']\n",
+ " array([1, 3])\n",
+ "\n",
+ " Creating an array from sub-classes:\n",
+ "\n",
+ " >>> np.array(np.mat('1 2; 3 4'))\n",
+ " array([[1, 2],\n",
+ " [3, 4]])\n",
+ "\n",
+ " >>> np.array(np.mat('1 2; 3 4'), subok=True)\n",
+ " matrix([[1, 2],\n",
+ " [3, 4]])\n"
+ ]
+ }
+ ],
+ "source": [
+ "print(np.array.__doc__)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 130,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "class Rectangle():\n",
+ " x : int = 100 # class attribute\n",
+ "\n",
+ " def __init__(self, a, b):\n",
+ " self.a = a # \n",
+ " self.b = b\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 132,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "rect0 = Rectangle(2, 4)\n",
+ "rect1 = Rectangle(5, 6)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 139,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "rect0.y = 4000"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 134,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "100"
+ ]
+ },
+ "execution_count": 134,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "rect1.x"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 140,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "rect0.__class__.y = 5000"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 141,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "5000"
+ ]
+ },
+ "execution_count": 141,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "rect1.y"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 142,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "4000"
+ ]
+ },
+ "execution_count": 142,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "rect0.y"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 151,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "class Rectangle():\n",
+ " def __init__(self, a: float, b: float):\n",
+ " self.a = a # \n",
+ " self.b = b\n",
+ " \n",
+ " def area(self):\n",
+ " return self.a * self.b\n",
+ " \n",
+ " def __repr__(self):\n",
+ " return f\"Rectangle(a={self.a}, b={self.b})\"\n",
+ " \n",
+ " def __add__(self, other):\n",
+ " return Rectangle(a=self.a + other.a, b=self.b + other.b)\n",
+ " \n",
+ " \n",
+ " \n",
+ "rect0 = Rectangle(2, 4)\n",
+ "rect1 = Rectangle(5, 6)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 149,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "8"
+ ]
+ },
+ "execution_count": 149,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "rect0.area()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 152,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "Rectangle(a=7, b=10)"
+ ]
+ },
+ "execution_count": 152,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "rect0 + rect1"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "A complete list of magic methods is available here:\n",
+ "\n",
+ "https://rszalski.github.io/magicmethods/"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.7.0"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}