{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "### Funções" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "def soma(a,b):\n", " print(a+b)\n", "\n" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "7\n" ] } ], "source": [ "soma(2,5)" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "def EPar(x):\n", " return (x%2==0)" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "False" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "EPar(13)" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "True" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "EPar(12)" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "import math as mt #importa o pacote math" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "def AreaTr(a,b,c):\n", " s=(a+b+c) #semiperímetro Formula de Heron\n", " A=mt.sqrt(s*(s-a)*(s-b)*(s-c))\n", " return A" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "257.93022312245614\n" ] } ], "source": [ "print(AreaTr(4,8,10))\n" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "['__doc__',\n", " '__file__',\n", " '__loader__',\n", " '__name__',\n", " '__package__',\n", " '__spec__',\n", " 'acos',\n", " 'acosh',\n", " 'asin',\n", " 'asinh',\n", " 'atan',\n", " 'atan2',\n", " 'atanh',\n", " 'ceil',\n", " 'comb',\n", " 'copysign',\n", " 'cos',\n", " 'cosh',\n", " 'degrees',\n", " 'dist',\n", " 'e',\n", " 'erf',\n", " 'erfc',\n", " 'exp',\n", " 'expm1',\n", " 'fabs',\n", " 'factorial',\n", " 'floor',\n", " 'fmod',\n", " 'frexp',\n", " 'fsum',\n", " 'gamma',\n", " 'gcd',\n", " 'hypot',\n", " 'inf',\n", " 'isclose',\n", " 'isfinite',\n", " 'isinf',\n", " 'isnan',\n", " 'isqrt',\n", " 'ldexp',\n", " 'lgamma',\n", " 'log',\n", " 'log10',\n", " 'log1p',\n", " 'log2',\n", " 'modf',\n", " 'nan',\n", " 'perm',\n", " 'pi',\n", " 'pow',\n", " 'prod',\n", " 'radians',\n", " 'remainder',\n", " 'sin',\n", " 'sinh',\n", " 'sqrt',\n", " 'tan',\n", " 'tanh',\n", " 'tau',\n", " 'trunc']" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "dir(mt)" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "120\n" ] } ], "source": [ "def fatorial(n):\n", " fat=1\n", " while n>1:\n", " fat *=n\n", " n -= 1\n", " return fat\n", "print(fatorial(5))" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "120\n" ] } ], "source": [ "def fatorial(n):\n", " if n==0 or n==1:\n", " return 1\n", " else:\n", " return n*fatorial(n-1)\n", " \n", "\n", "print(fatorial(5))" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [], "source": [ "def barra(n=30, caractere='*'): #valores default\n", " print(caractere*n)" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "******************************\n" ] } ], "source": [ "barra()" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "**********\n" ] } ], "source": [ "barra(10)" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "==================================================\n" ] } ], "source": [ "barra(50,\"=\")" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [], "source": [ "def soma(*args): #não é ponteiro, significa que pode ter vários argumentos\n", " s=0\n", " for x in args:\n", " s +=x\n", " return s\n" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "3\n" ] } ], "source": [ "print(soma(1,2))" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "87\n" ] } ], "source": [ "print(soma(1,4, 32,50))" ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Maior: 5\n", "Max: 9\n" ] } ], "source": [ "def imprimeMaior(mensagem,*numeros): #mensagem é obrigatorio \n", " maior = None #None quer dizer vazio ou nada\n", " for e in numeros: #para cada elemento e da lista de numeros faça\n", " if maior==None or maior < e:\n", " maior = e\n", " print(mensagem, maior)\n", "\n", "imprimeMaior(\"Maior: \",5,4,3,2,1)\n", "imprimeMaior(\"Max:\", *[1,7,9])" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Maximo: None\n" ] } ], "source": [ "imprimeMaior(\"Maximo: \")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Funções Lambda" ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "6\n" ] } ], "source": [ "a=lambda x: x*2\n", "print(a(3))" ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "5.0\n" ] } ], "source": [ "aumento=lambda a,b:(a*b/100)\n", "print(aumento(100,5))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Arquivos\n", "#### Entrada e saída" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Modo de abertura dos arquivos\n", "Modo Operação\n", "\n", "'r' leitura\n", "\n", "'w' escrita, apaga o conteudo se existir\n", "\n", "'a' escreve no fim, preserva conteudo, se existir\n", "\n", "'b' modo binario\n", "\n", "'+' atualização (leitura e escrita)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Criando e gravando" ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [], "source": [ "arquivo=open(\"numeros.txt\",\"w\")\n", "for linha in range (1,101):\n", " arquivo.write(\"%d\\n\" %linha)\n", "arquivo.close()" ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "_io.TextIOWrapper" ] }, "execution_count": 25, "metadata": {}, "output_type": "execute_result" } ], "source": [ "type(arquivo)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Lendo" ] }, { "cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "numeros.txt \u001b[0m\u001b[01;32mroleta.txt\u001b[0m*\n" ] } ], "source": [ "ls *.txt" ] }, { "cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "1\n", "\n", "2\n", "\n", "3\n", "\n", "4\n", "\n", "5\n", "\n", "6\n", "\n", "7\n", "\n", "8\n", "\n", "9\n", "\n", "10\n", "\n", "11\n", "\n", "12\n", "\n", "13\n", "\n", "14\n", "\n", "15\n", "\n", "16\n", "\n", "17\n", "\n", "18\n", "\n", "19\n", "\n", "20\n", "\n", "21\n", "\n", "22\n", "\n", "23\n", "\n", "24\n", "\n", "25\n", "\n", "26\n", "\n", "27\n", "\n", "28\n", "\n", "29\n", "\n", "30\n", "\n", "31\n", "\n", "32\n", "\n", "33\n", "\n", "34\n", "\n", "35\n", "\n", "36\n", "\n", "37\n", "\n", "38\n", "\n", "39\n", "\n", "40\n", "\n", "41\n", "\n", "42\n", "\n", "43\n", "\n", "44\n", "\n", "45\n", "\n", "46\n", "\n", "47\n", "\n", "48\n", "\n", "49\n", "\n", "50\n", "\n", "51\n", "\n", "52\n", "\n", "53\n", "\n", "54\n", "\n", "55\n", "\n", "56\n", "\n", "57\n", "\n", "58\n", "\n", "59\n", "\n", "60\n", "\n", "61\n", "\n", "62\n", "\n", "63\n", "\n", "64\n", "\n", "65\n", "\n", "66\n", "\n", "67\n", "\n", "68\n", "\n", "69\n", "\n", "70\n", "\n", "71\n", "\n", "72\n", "\n", "73\n", "\n", "74\n", "\n", "75\n", "\n", "76\n", "\n", "77\n", "\n", "78\n", "\n", "79\n", "\n", "80\n", "\n", "81\n", "\n", "82\n", "\n", "83\n", "\n", "84\n", "\n", "85\n", "\n", "86\n", "\n", "87\n", "\n", "88\n", "\n", "89\n", "\n", "90\n", "\n", "91\n", "\n", "92\n", "\n", "93\n", "\n", "94\n", "\n", "95\n", "\n", "96\n", "\n", "97\n", "\n", "98\n", "\n", "99\n", "\n", "100\n", "\n" ] } ], "source": [ "arquivo=open(\"numeros.txt\",\"r\") #abrindo para leitura\n", "for linha in arquivo.readlines(): #readlines lê todas as linhas, readline lê uma linha por vez\n", " print(linha)\n", "arquivo.close()" ] }, { "cell_type": "code", "execution_count": 28, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "['_CHUNK_SIZE',\n", " '__class__',\n", " '__del__',\n", " '__delattr__',\n", " '__dict__',\n", " '__dir__',\n", " '__doc__',\n", " '__enter__',\n", " '__eq__',\n", " '__exit__',\n", " '__format__',\n", " '__ge__',\n", " '__getattribute__',\n", " '__gt__',\n", " '__hash__',\n", " '__init__',\n", " '__init_subclass__',\n", " '__iter__',\n", " '__le__',\n", " '__lt__',\n", " '__ne__',\n", " '__new__',\n", " '__next__',\n", " '__reduce__',\n", " '__reduce_ex__',\n", " '__repr__',\n", " '__setattr__',\n", " '__sizeof__',\n", " '__str__',\n", " '__subclasshook__',\n", " '_checkClosed',\n", " '_checkReadable',\n", " '_checkSeekable',\n", " '_checkWritable',\n", " '_finalizing',\n", " 'buffer',\n", " 'close',\n", " 'closed',\n", " 'detach',\n", " 'encoding',\n", " 'errors',\n", " 'fileno',\n", " 'flush',\n", " 'isatty',\n", " 'line_buffering',\n", " 'mode',\n", " 'name',\n", " 'newlines',\n", " 'read',\n", " 'readable',\n", " 'readline',\n", " 'readlines',\n", " 'reconfigure',\n", " 'seek',\n", " 'seekable',\n", " 'tell',\n", " 'truncate',\n", " 'writable',\n", " 'write',\n", " 'write_through',\n", " 'writelines']" ] }, "execution_count": 28, "metadata": {}, "output_type": "execute_result" } ], "source": [ "dir(arquivo)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## arquivo.readlines() lê todas as linhas\n", "## arquivo.readline() lê linha" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Lendo parâmetros na linha de comando" ] }, { "cell_type": "code", "execution_count": 48, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Numero de parametros: 3\n", "Parametro 0 = /opt/anaconda3/lib/python3.6/site-packages/ipykernel_launcher.py\n", "Parametro 1 = -f\n", "Parametro 2 = /run/user/1000/jupyter/kernel-1088e419-8e03-4ee0-b783-fc704fbd298c.json\n" ] } ], "source": [ "import sys\n", "print(\"Numero de parametros: %d\" %len(sys.argv))\n", "for n,p in enumerate(sys.argv):\n", " print(\"Parametro %d = %s\" %(n,p))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Usando o pacote Pickle" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Serve para salvar objetos do jeito que estão" ] }, { "cell_type": "code", "execution_count": 42, "metadata": {}, "outputs": [], "source": [ "import pickle" ] }, { "cell_type": "code", "execution_count": 43, "metadata": {}, "outputs": [], "source": [ "Meuarquivo=open('test.pck','wb') # se colocar no 3.x só 'w' dará erro ao gravar\n", "pickle.dump(12.3,Meuarquivo) #despeja (grava) um float em Meuarquivo" ] }, { "cell_type": "code", "execution_count": 44, "metadata": {}, "outputs": [], "source": [ "pickle.dump([1,2,3],Meuarquivo) #despeja uma lista contendo 1,2 e 3\n", "Meuarquivo.close() " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Salvou um tipo float e um tipo lista" ] }, { "cell_type": "code", "execution_count": 45, "metadata": {}, "outputs": [], "source": [ "MeuArquivo=open('test.pck','rb')" ] }, { "cell_type": "code", "execution_count": 46, "metadata": {}, "outputs": [], "source": [ "x=pickle.load(MeuArquivo)" ] }, { "cell_type": "code", "execution_count": 47, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "12.3" ] }, "execution_count": 47, "metadata": {}, "output_type": "execute_result" } ], "source": [ "x" ] }, { "cell_type": "code", "execution_count": 48, "metadata": {}, "outputs": [], "source": [ "y=pickle.load(MeuArquivo)" ] }, { "cell_type": "code", "execution_count": 49, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[1, 2, 3]" ] }, "execution_count": 49, "metadata": {}, "output_type": "execute_result" } ], "source": [ "y" ] }, { "cell_type": "code", "execution_count": 61, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "['ADDITEMS',\n", " 'APPEND',\n", " 'APPENDS',\n", " 'BINBYTES',\n", " 'BINBYTES8',\n", " 'BINFLOAT',\n", " 'BINGET',\n", " 'BININT',\n", " 'BININT1',\n", " 'BININT2',\n", " 'BINPERSID',\n", " 'BINPUT',\n", " 'BINSTRING',\n", " 'BINUNICODE',\n", " 'BINUNICODE8',\n", " 'BUILD',\n", " 'DEFAULT_PROTOCOL',\n", " 'DICT',\n", " 'DUP',\n", " 'EMPTY_DICT',\n", " 'EMPTY_LIST',\n", " 'EMPTY_SET',\n", " 'EMPTY_TUPLE',\n", " 'EXT1',\n", " 'EXT2',\n", " 'EXT4',\n", " 'FALSE',\n", " 'FLOAT',\n", " 'FRAME',\n", " 'FROZENSET',\n", " 'FunctionType',\n", " 'GET',\n", " 'GLOBAL',\n", " 'HIGHEST_PROTOCOL',\n", " 'INST',\n", " 'INT',\n", " 'LIST',\n", " 'LONG',\n", " 'LONG1',\n", " 'LONG4',\n", " 'LONG_BINGET',\n", " 'LONG_BINPUT',\n", " 'MARK',\n", " 'MEMOIZE',\n", " 'NEWFALSE',\n", " 'NEWOBJ',\n", " 'NEWOBJ_EX',\n", " 'NEWTRUE',\n", " 'NONE',\n", " 'OBJ',\n", " 'PERSID',\n", " 'POP',\n", " 'POP_MARK',\n", " 'PROTO',\n", " 'PUT',\n", " 'PickleError',\n", " 'Pickler',\n", " 'PicklingError',\n", " 'PyStringMap',\n", " 'REDUCE',\n", " 'SETITEM',\n", " 'SETITEMS',\n", " 'SHORT_BINBYTES',\n", " 'SHORT_BINSTRING',\n", " 'SHORT_BINUNICODE',\n", " 'STACK_GLOBAL',\n", " 'STOP',\n", " 'STRING',\n", " 'TRUE',\n", " 'TUPLE',\n", " 'TUPLE1',\n", " 'TUPLE2',\n", " 'TUPLE3',\n", " 'UNICODE',\n", " 'Unpickler',\n", " 'UnpicklingError',\n", " '_Framer',\n", " '_Pickler',\n", " '_Stop',\n", " '_Unframer',\n", " '_Unpickler',\n", " '__all__',\n", " '__builtins__',\n", " '__cached__',\n", " '__doc__',\n", " '__file__',\n", " '__loader__',\n", " '__name__',\n", " '__package__',\n", " '__spec__',\n", " '_compat_pickle',\n", " '_dump',\n", " '_dumps',\n", " '_extension_cache',\n", " '_extension_registry',\n", " '_getattribute',\n", " '_inverted_registry',\n", " '_load',\n", " '_loads',\n", " '_test',\n", " '_tuplesize2code',\n", " 'bytes_types',\n", " 'codecs',\n", " 'compatible_formats',\n", " 'decode_long',\n", " 'dispatch_table',\n", " 'dump',\n", " 'dumps',\n", " 'encode_long',\n", " 'format_version',\n", " 'io',\n", " 'islice',\n", " 'load',\n", " 'loads',\n", " 'maxsize',\n", " 'pack',\n", " 'partial',\n", " 're',\n", " 'sys',\n", " 'unpack',\n", " 'whichmodule']" ] }, "execution_count": 61, "metadata": {}, "output_type": "execute_result" } ], "source": [ "dir(pickle)" ] }, { "cell_type": "code", "execution_count": 50, "metadata": {}, "outputs": [], "source": [ "# Criando duas funções\n", "\n", "# Função 1 - Recebe uma temperatura como parâmetro e retorna a temperatura em Fahrenheit\n", "def fahrenheit(T):\n", " return ((float(9)/5)*T + 32)\n", "\n", "# Função 2 - Recebe uma temperatura como parâmetro e retorna a temperatura em Celsius\n", "def celsius(T):\n", " return (float(5)/9)*(T-32)" ] }, { "cell_type": "code", "execution_count": 51, "metadata": {}, "outputs": [], "source": [ "# Criando uma lista\n", "temperaturas = [0, 22.5, 40, 100]" ] }, { "cell_type": "code", "execution_count": 52, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 52, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Aplicando a função a cada elemento da lista de temperaturas. \n", "# Em Python 3, a funçãp map() retornar um iterator\n", "map(fahrenheit, temperaturas)" ] }, { "cell_type": "code", "execution_count": 53, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[32.0, 72.5, 104.0, 212.0]" ] }, "execution_count": 53, "metadata": {}, "output_type": "execute_result" } ], "source": [ "list (map(fahrenheit,temperaturas))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Ver PythonFundamentos-master-Cap04-05 pasta Notebook\n", "### Ver PythonFundamentos-master-Cap04-06 pasta Notebook" ] }, { "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": "3.8.5" } }, "nbformat": 4, "nbformat_minor": 4 }