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fmasanori / raspa_cnj.py
Last active April 26, 2019 19:13
Raspa os mandados da BNMP
import requests
import json
import pymongo
connection = pymongo.MongoClient("mongodb://localhost")
db = connection.bnmp
mandados_mongoDB = db.mandados
cabeçalho = {
'Host': 'www.cnj.jus.br',
@fmasanori
fmasanori / pets.txt
Created November 4, 2017 10:06
Nomes de Gatos e Cachorros
https://gist.github.com/fmasanori/ee2b554ee6e05f298d5014bcbf730fd7
Cats
Abdul Abel Abelarda Abelardo Abelhinha Abigail Abner Abu Acacia Ace Acerola Adda Adonis Adrik Adry Afrodite Agapi Agostinho Agripina(o) Aiara Aícha Aika(o) Aiki Aila Aileen Aima Aimee Aislan Aiwa Akan Akaya Akenaton Akesa Alanis Alec Alecrim Aleetza Alef Alegria Aleluia Alemã Alemão Aleska Alex Alf Alfa Alface Algodão Alice Alicia Alika Alina Alisson Alita Alladim Alma Almôndega Aloha Alone Alpha Alphi Alvinha Amapola Amaral Amarula Amaya Ambar Amber Ameli Amendoim Amie Amiga(o) Amigão Amiguinha(o) Amin Amira Amon Amor Amora Amoreko Amoroso Amy Anakin Anda Andie Andora Andy Angel Angra Angus Anjinha Anjinho Anúbis Anukh Apache Apagão Aphou Apiá Apoena Apolo Apple April Aquiles Arã Arabi Aragon Aramis Aranha Arashi Archie Arena Aretha Argos Ariadne Ariel Ariela Arine Aristóteles Arkan Armani Aroeira Aron Arrepio Arteira Artemis Arthur Aruan Aruane Aruck Aruska Ashley Aska Asla Aslam Aspen Asrama Assombroso Aster Asterix Asthar Astolfo As
@fmasanori
fmasanori / Analisa_salarios_UFRJ.py
Created October 24, 2017 19:05
Analisa os dados raspados dos Vencimentos da UFRJ
f = open('UFRJ.txt')
dic = {}
for linha in f:
id_servidor, nome, valor = linha.strip().split(',')
dic[id_servidor] = [nome, float(valor)]
f.close()
def salário(a): return a[1][1]
maiores = sorted(dic.items(), key=salário, reverse=True)
for f in maiores[:50]:
@fmasanori
fmasanori / Raspa_salarios_UFRJ.py
Last active July 12, 2018 20:40
Raspa 15 mil vencimentos da UFRJ e mostra os maiores
import requests
from bs4 import BeautifulSoup as bs
u = 'http://www.portaldatransparencia.gov.br/servidores/OrgaoLotacao-ListaServidores.asp?CodOS=15000&DescOS=MINISTERIO%20DA%20EDUCACAO&CodOrg=26245&DescOrg=UNIVERSIDADE%20FEDERAL%20DO%20RIO%20DE%20JANEIRO&Pagina='
base = 'http://www.portaldatransparencia.gov.br/'
def extrai_valor(u):
j = u.find('=') + 1
k = u.find('&', j)
id_servidor = u[j: k]
import os
import csv
linhas = 0
def extrai_valores(t):
k = 1
while True:
j = k
k = t.find(' ', k)
k += 1
import PyPDF2
import os
import os.path
def traduz(f):
pdfFileObj = open(f, 'rb')
try:
pdfReader = PyPDF2.PdfFileReader(pdfFileObj)
except:
print (f, 'corrompido')
@fmasanori
fmasanori / Emendas.py
Last active February 2, 2020 05:59
Baixa as Emendas da ALESP de 01.01.2010 até 31.12.2014 (uma legislatura)
import requests
from bs4 import BeautifulSoup as bs
from urllib.request import urlretrieve
u1 = 'https://www.al.sp.gov.br/alesp/pesquisa-proposicoes/?direction=acima&lastPage=5167&currentPage='
u2 = '&act=detalhe&idDocumento=&rowsPerPage=10&currentPageDetalhe=1&tpDocumento=&method=search&text=&natureId=4005&legislativeNumber=&legislativeYear=&natureIdMainDoc=loa&anoDeExercicio=&legislativeNumberMainDoc=&legislativeYearMainDoc=&strInitialDate=01%2F01%2F2010&strFinalDate=31%2F12%2F2014&author=&supporter=&politicalPartyId=&tipoDocumento=&stageId=&strVotedInitialDate=&strVotedFinalDate='
base = 'https://www.al.sp.gov.br'
def baixa_pdf(u, nome):
url = base + u
fim = nome.find('-') - 1
nome = nome.replace('/', '-')
@fmasanori
fmasanori / pdf2txt.py
Created August 9, 2017 00:25
pdf2txt
#!/usr/bin/env python
"""
Converts PDF text content (though not images containing text) to plain text, html, xml or "tags".
"""
import sys
import logging
import six
import pdfminer.settings
pdfminer.settings.STRICT = False
@fmasanori
fmasanori / Pet Names.py
Last active November 15, 2017 21:44
Lista de nomes de Pets
import requests
from bs4 import BeautifulSoup as bs
import string
pets = []
for pet in ('Gatos', 'Caes'):
for letra in string.ascii_uppercase:
for k in (1, 2, 3):
u = 'https://www.bayerpet.com.br/%s/lista-nomes/%s%s' %(pet, letra, str(k))
p = requests.get(u)
@fmasanori
fmasanori / 100 melhores livros segundo Le Monde.py
Created July 5, 2017 13:12
100 melhores livros segundo o Le Monde
#Laura Maia e Letícia Barreto
import requests
from bs4 import BeautifulSoup
url='https://pt.wikipedia.org/wiki/Os_100_livros_do_s%C3%A9culo_segundo_Le_Monde'
soup = BeautifulSoup(requests.get(url).text, 'html.parser')
nome=[nome.string.strip()
for nome in soup.findAll('i')]
ranking=[rank.string