def download_stay_picinfo(): #Downloads picture locally as jpg img, MIGHT be useful if we are doing local image classification....but I rather gcloud classify with url if needed
print('Extracting Top 5 Stay Information..')
url=[]
url=get_stay_url()
print('Downloading Pics uploaded by host..')
i=0
k=0
while (i<5):
r.url(url[i+k])
r.click('//*[@id="FMP-target"]')
j=0
while (1):
j=j+1
print(f'Downloading Homestay {i+1} Photo {j}')
r.wait(0.4)
#r.snap('//div[@data-testid="photo-viewer-slideshow-desktop"]/div/div/div/div/div/img',f"data/{i+1}/{j}.jpg") #fastest but not perfect
if (r.exist('//div[@data-testid="photo-viewer-slideshow-desktop"]/div/div/div/div/div/img/@src') == True):
dl_link=r.read('//div[@data-testid="photo-viewer-slideshow-desktop"]/div/div/div/div/div/img/@src')
r.download(dl_link,f'data/{i+1}/{j}.jpg')
print(f'Homestay {i+1} Photo {j} downloaded!')
else:
i=i-1 #Detects Whales (Airbnb Plus spoils the format alot)
k=k+1 #Compensating Constant k
print("WHALE detected, adding one more loop..")
if (r.exist('/html/body/div[9]/div/div/div/div/div[3]/div/div[2]/button') == False or j >= 15): break #Max 15 photos
r.click('/html/body/div[9]/div/div/div/div/div[3]/div/div[2]/button')
i=i+1
r.click('/html/body/div[9]/div/div/div/section/div/div[1]/div/button')
print('Done.')
import pyautogui as ui
import rpa
import pandas as pd
rpa.init()
rpa.url('http://rpachallenge.com/')
window = ui.getActiveWindow()
window.maximize()
ui.sleep(5)
rpa.download('http://rpachallenge.com/assets/downloadFiles/challenge.xlsx',
'challenge.xlsx')
ui.sleep(2)
df = pd.DataFrame(pd.read_excel(r'challenge.xlsx', sheet_name='Sheet1'))
rpa.click('/html/body/app-root/div[2]/app-rpa1/div/div[1]/div[6]/button')
for row in df.itertuples():
rpa.type('//*[@ng-reflect-name="labelFirstName"]', row[1])
rpa.type('//*[@ng-reflect-name="labelLastName"]', row[2])
rpa.type('//*[@ng-reflect-name="labelCompanyName"]', row[3])
rpa.type('//*[@ng-reflect-name="labelRole"]', row[4])
rpa.type('//*[@ng-reflect-name="labelAddress"]', row[5])
rpa.type('//*[@ng-reflect-name="labelEmail"]', row[6])
rpa.type('//*[@ng-reflect-name="labelPhone"]', str(row[7]))
rpa.click('/html/body/app-root/div[2]/app-rpa1/div/div[2]/form/input')
ui.sleep(1)
ui.sleep(5)
def download_workbook(file_name):
r.download('http://rpachallenge.com/assets/downloadFiles/challenge.xlsx',
f'{file_name}')
return file_name
# http://www.rpachallenge.com/
import rpa
import pyautogui
import pandas
import os
rpa.init()
rpa.url('http://www.rpachallenge.com/')
pyautogui.sleep(7)
janela = pyautogui.getActiveWindow()
janela.maximize()
rpa.download('http://www.rpachallenge.com/assets/downloadFiles/challenge.xlsx',
'desafio.xlsx')
pyautogui.sleep(2)
dados = pandas.read_excel('desafio.xlsx', sheet_name='Sheet1')
colunas = [
'First Name', 'Last Name ', 'Company Name', 'Role in Company', 'Address',
'Email', 'Phone Number'
]
data_frame = pandas.DataFrame(dados, columns=colunas)
for row in data_frame.itertuples():
print(row)
rpa.type('//*[@ng-reflect-name="labelFirstName"]', row[1])
rpa.type('//*[@ng-reflect-name="labelLastName"]', row[2])
import rpa as r
from openpyxl import load_workbook
r.init() #Inicialization
r.url('http://www.rpachallenge.com') # Access URL
r.download('http://www.rpachallenge.com/assets/downloadFiles/challenge.xlsx',
'challenge.xlsx') # Download File
wb = load_workbook(filename='challenge.xlsx', read_only=True) # Open file
ws = wb.active
r.type('Start', '[enter]')
lista = [
"FirstName", "LastName", "CompanyName", "Role", "Address", "Email", "Phone"
]
for i in range(2, 12):
cont = 0
for j in range(1, 8):
cell_obj = ws.cell(row=i, column=j)
r.type("//*[@ng-reflect-name=\"label{}\"]".format(lista[cont]),
str(cell_obj.value))
cont += 1
r.type('submit', '[enter]')