def rpa_process(to_date, preferred_time, from_date, phone_number, token):
t.init()
t.url("https://sangam-test-website.herokuapp.com/change_input")
util.wait_for_pageload('//button[@id="btnsubmit"]')
t.click('//input[@id="txtHandNo"]')
t.type('//input[@name="txtHandNo"]', phone_number)
t.click('//button[@id="btnsubmit"]')
util.wait_for_pageload('//button[@id="btnsubmit"]')
from_date_obj = from_date
from_date = from_date.strftime("%d/%m/%Y")
t.click('//label[contains(.,"' + str(from_date) + '")]')
to_date_obj = to_date
hour = to_date.hour
minute = to_date.minute
to_date = to_date.strftime("%d/%m/%Y")
t.click('//input[@name="txtDateTimePicker"]')
t.type('//input[@name="txtDateTimePicker"]', to_date)
t.click('//div[@class="filter-option-inner-inner"]')
t.click('//a[@role= "option"][.=' + str(hour) + ']')
t.click('//select[@id="ddlMin"]')
t.click('//a[@role= "option"][.=' + str(minute) + ']')
t.click('//button[@id="btnsubmit"]')
t.close()
change_appointment_slot(from_date_obj, to_date_obj, token)
def propertydata(project_name):
t.close()
t.init()
project_url = f'https://www.propertyguru.com.sg/property-for-sale?market=residential&freetext={project_name}&newProject=all'
t.url(project_url)
wait_for_pageload('//div[@class="header-wrapper"]')
num_result_ad = 3
# load main page, get detail page url link
url = [''] * num_result_ad
for n in [x for x in range(1, num_result_ad + 1)
if x != 4 and x != 8]: # skip 4th and 8th advertisement
wait_for_pageload(
f'(//div[@class="listing-widget-new"]/div[{n}]/div[1]/div[2]/div[1]/div[1]/h3/a/@href)'
)
url[n - 1] = read_if_present(
f'(//div[@class="listing-widget-new"]/div[{n}]/div[1]/div[2]/div[1]/div[1]/h3/a/@href)'
)
print(f"{n}. url = " + url[n - 1])
property_title = [''] * num_result_ad
id = [''] * num_result_ad
pdf = [''] * num_result_ad
pdf_link = [''] * num_result_ad
for n in [x for x in range(1, num_result_ad + 1) if x != 4 and x != 8]:
t.url("https://www.propertyguru.com.sg" + url[n - 1])
wait_for_pageload('//h1[@class="h2"]')
property_title[n - 1] = read_if_present('//h1[@class="h2"]')
print(f"{n}. property_title = " + property_title[n - 1])
id[n - 1] = read_if_present(
'//*[@id="details"]/div/div[1]/div[2]/div[10]/div/div[2]')
print(f"{n}. id = " + id[n - 1])
pdf[n - 1] = read_if_present(
'//*[@id="sticky-right-col"]/div[3]/a[2]/@href')
pdf_link[n - 1] = 'https://www.propertyguru.com.sg' + pdf[n - 1]
print(f"{n}. pdf_link = " + pdf_link[n - 1])
property_info = {
'property_title': property_title,
'url': ['https://www.propertyguru.com.sg' + x for x in url],
'id': id,
'pdf_link': pdf_link,
}
df = DataFrame(property_info,
columns=['property_title', 'id', 'url', 'pdf_link'])
df.to_excel('Property Monitor.xlsx', encoding='utf8', index=None)
print('======== Property Monitor.xlsx saved ==========')
print(f'======== Monitoring every {interval} second ==========')
def rpa_process(lmp_date, doctor_name, preferred_time, phone_number,
patient_name, symptoms, email, sub_id):
hour = preferred_time.hour
minute = preferred_time.minute
checkup_dates = []
day_list = [
45, 75, 105, 135, 165, 195, 210, 225, 240, 255, 262, 269, 275, 280
]
week_list = [6, 10, 14, 18, 22, 26, 28, 30, 32, 34, 36, 37, 38, 39]
for day in day_list:
checkup = lmp_date + timedelta(days=day)
checkup = str(checkup.day) + "/" + str(checkup.month) + "/" + str(
checkup.year)
checkup_dates.append(checkup)
t.init()
for index, i in enumerate(checkup_dates):
t.url("https://sangam-test-website.herokuapp.com/")
util.wait_for_pageload('//button[@id="btnsubmit"]')
t.click('//input[@class="form-control"]')
t.type('//input[@name="name"]', patient_name)
t.click('//input[@id="email"]')
t.type('//input[@name="email"]', email)
symptoms = "Pregnancy checkup after week " + str(week_list[index])
t.type('//textarea', symptoms)
t.click('//input[@id="txtHandNo"]')
t.type('//input[@name="txtHandNo"]', phone_number)
t.click('//div[@class="filter-option-inner-inner"]')
t.click('//a[@role= "option"][.=' + str(hour) + ']')
t.click('//select[@id="ddlMin"]')
t.click('//a[@role= "option"][.=' + str(minute) + ']')
t.click('//input[@name="txtDateTimePicker"]')
t.type('//input[@name="txtDateTimePicker"]', i)
t.click('//select[@id="txtSpecificDoc"]')
t.click('//a[@role= "option"][.="' + str(doctor_name) + '"]')
t.click('//button[@id="btnsubmit"]')
t.close()
request_url = "https://sangam-test-website.herokuapp.com/get_future_appointments?email=" + str(
email)
future_appointments = requests.get(request_url)
book_calendar_slot(future_appointments.json()['data'], sub_id)
def get_shoe(shoe, g, email):
gender = g
# print('[nike]',gender)
t.init(visual_automation=True)
t.url('https://www.nike.com/sg/')
t.type('//input[@id = "TypeaheadSearchInput"]', shoe + " shoes")
t.click('//button[@class = "btn-search z2 bg-transparent"]')
t.wait(3)
if gender == " men":
t.click('(//span[contains(@class,"filter-item")])[1]')
elif gender == " women":
t.click('(//span[contains(@class,"filter-item")])[2]')
t.wait(1)
count = t.count('//a[@class ="product-card__link-overlay"]')
# print('[nike]',count)
details = []
if count != 0:
for i in range(0, min(count, 3)):
k = i + 1
name = t.read(f'(//a[@class = "product-card__link-overlay"])[{k}]')
price = t.read(f'(//div[@data-test="product-price"])[{k}]')
img = t.read(
f'(//div[contains(@class, "product-card__hero")]/picture/img)[{k}]/@src'
)
link = t.read(f'(//a[contains(@class,"product-card")])[{k}]/@href')
# print('[nike]',name , price, img)
details.append({
"email": email,
"name": name,
"price": price,
"img": img,
"Company": "Nike",
"link": link
})
else:
details.append({
"email": email,
"name": "NA",
"price": "NA",
"img": "NA",
"Company": "Nike",
"link": "NA"
})
# print(details)
return details
def check_availability(reservation_date,reservation_time,party_size,restaurant_name):
try:
#Convert User Defined Values to System Usable Values
reservation_day=reservation_date.split('/')[0]
reservation_month =reservation_date.split('/')[1]
reservation_month=int(reservation_month)-1
reservation_year =reservation_date.split('/')[2]
reservation_time_int=int(reservation_time)
start_time_hr= reservation_time[:2]
if reservation_time_int>1159:
if start_time_hr!="12":
start_time_hr=int(start_time_hr)-12
start_time_option = str(start_time_hr)+":"+reservation_time[2:4]+" pm"
else:
start_time_option = str(start_time_hr)+":"+reservation_time[2:4]+" am"
#Booking Parameters
chope_url ='https://www.chope.co/singapore-restaurants/category/restaurant/'
t.init()
t.url(chope_url)
t.wait(10)
#Date Field
t.click(f"(//span[contains(@class,'input-group-addon icon-calendar')])[1]")
t.wait(7)
boolean_flag=1
while boolean_flag:
if t.present(f"//td[@data-handler='selectDay'and @data-year='{reservation_year}' and @data-month='{reservation_month}']/a[text()='{reservation_day}']"):
t.click(f"//td[@data-handler='selectDay'and @data-year='{reservation_year}' and @data-month='{reservation_month}']/a[text()='{reservation_day}']")
boolean_flag=0
else:
t.click('//a[@title="Next"]')
t.click(f"//td[@data-handler='selectDay'and @data-month='{reservation_month}']/a[text()='{reservation_day}']")
#Time Field
t.select(f"//select[contains(@id,'time-field')]",start_time_option)
#Number of Diners Field
t.click(f"(//span[contains(@class,'input-group-addon icon-person')])[1]")
t.select(f"//select[contains(@id,'adults')]",party_size)
#Restaurant Field
t.type(f"//select[contains(@id,'sb-sel-restaurant')]",restaurant_name)
t.click('//button[@id="btn-search"]')
t.wait(5)
if t.present(f"//div[@class='alert alert-danger']"):
print('Not Available')
return 0
else:
print ('Available')
return 1
except:
print('Error')
return 'Reservation Unsuccessful. Unforunately, the restaurant was not able to accomodate your reservation.'
def run():
conn = util.create_connection("./db/news.db")
site = util.getSiteByName(conn, "New York Times")
site_url = site[0][2]
site_id = site[0][0]
t.init(visual_automation = True, chrome_browser = True)
t.url(site_url)
t.wait(10)
df = catchContent()
df = util.fixImgLink(df,"https://cf-templates-fghyux9ggb7t-ap-southeast-1.s3-ap-southeast-1.amazonaws.com/NewYorkTimes.png")
df = util.fixSummary(df)
t.wait(20)
t.close()
util.updateNews(conn, site_id, df)
def run():
conn = util.create_connection("./db/news.db")
site = util.getSiteByName(conn, "Today Online")
site_url = site[0][2]
site_id = site[0][0]
t.init(visual_automation=True, chrome_browser=True)
t.url(site_url)
t.wait(2)
t.hover('//div[@class="container footer-main"]')
t.wait(6)
df = catchContent()
t.wait(20)
t.close()
util.updateNews(conn, site_id, df)
def history_data(url_prefix, start_page=1):
curr_page = 1
curr_doc = 1
try:
t.init()
page_file = get_max_page(url_prefix)
with open(page_file, 'r') as f:
max_page = int(f.read()) + 1 # 拿到最大page，加1因为python index是开区间；
os.remove(page_file)
for page_num in range(start_page, max_page):
curr_page = page_num
count_values_file = get_count_values(page_num, url_prefix)
with open(count_values_file, 'r') as f: # 拿到每一页的item数量；
count_values = int(f.read().split(':')[-1]) + 1
os.remove(count_values_file)
for i in range(1, count_values):
if os.path.exists('complete_log'+str(url_prefix.split('/')[-2])+'.txt'):
with open('complete_log' + str(url_prefix.split('/')[-2]) + '.txt', 'r') as f:
start_doc = f.read().split(',')[1]
if i < int(start_doc):
continue
else:
pass
curr_doc = i
flag, time, content_url, file_name = read_content(page_num, url_prefix, i)
if '.html' not in flag:
# 当直接跳到需要下载的文件的时候：需要提供 当前url，time后缀，目前的文件index
direct_download(content_url, time, i)
else: # 当没有直接下载的时候,需要读取网页
# 读取网页
read_text_content(content_url, file_name, page_num, i, time, url_prefix)
#顺利完成了item的循环，当前页完成，complete log翻页，start doc放在1;如果page_num已经是count - 1，就不用做事情了。
if page_num != max_page - 1:
with open('complete_log' + str(url_prefix.split('/')[-2]) + '.txt', 'w') as f:
f.write(str(page_num+1) + ',' + str(1))
else:
pass
t.close()
return True
except: #如果检测到错误
with open('complete_log' + str(url_prefix.split('/')[-2]) + '.txt', 'w') as f:
f.write(str(curr_page) + ',' + str(curr_doc)) #留点
t.close()
return False
def getFlightExcel(info,ind):
flight_main, time_lst, code_lst, dur_lst, ind = getFlightInfo(info['dates'], ind)
#print(flight_main['Details'])
print(code_lst)
print(dur_lst)
print(time_lst)
k = len(info['dates'])
q = len(info['city'])
flight_lst = []
for i in range(k):
if i == (k-1) and i > 0 and q == k:
flight_lst.append(info['dates'][i])
flight = info['city'][i] + '-' + info['city'][0]
flight_lst.append(flight)
else:
flight_lst.append(info['dates'][i])
flight = info['city'][i] + '-' + info['city'][i + 1]
flight_lst.append(flight)
print(flight_lst)
###Compare Price with Expedia (Hyperlink/Multi to be added)
for j in range(2):
t.close()
t.init()
t.wait(0.5)
flight_search(info)
t.wait(5)
flight_main['Flight Info'][j] = flight_lst
price_exp, url_exp = getExpFlightPrice(code_lst[k*j:k*(j+1)], time_lst[k*j:k*(j+1)], dur_lst[k*j:k*(j+1)])
print(price_exp)
print(url_exp)
print(flight_main['Price'])
if price_exp < flight_main['Price'][j]:
if price_exp != 0:
flight_main['Price'][j] = price_exp
flight_main['Hyperlink'][j] = url_exp
print(flight_main['Price'])
print(flight_main['Hyperlink'])
return flight_main
def rpa_process(from_date, phone_number, token):
t.init()
t.url("https://sangam-test-website.herokuapp.com/cancel_input")
util.wait_for_pageload('//button[@id="btnsubmit"]')
t.click('//input[@id="txtHandNo"]')
t.type('//input[@name="txtHandNo"]', phone_number)
t.click('//button[@id="btnsubmit"]')
util.wait_for_pageload('//button[@id="btnsubmit"]')
from_date_obj = from_date
from_date = from_date.strftime("%d/%m/%Y")
t.click('//label[contains(.,"' + str(from_date) + '")]')
t.click('//button[@id="btnsubmit"]')
t.close()
cancel_appointment_slot(from_date_obj, token)
def flight_search(flight_request):
search_dt = dt.today()
request_id = flight_request['Request_ID']
info = flight_request['Request_Details']
t.init()
t.url('https://www.skyscanner.com.sg/')
tu.wait_for_pageload('//input[@id="fsc-trip-type-selector-return"]')
fill_search(info)
ind = 0
flight_main = getFlightExcel(info, ind)
t.wait(10.0)
t.close()
flight_main.update({
'Request_ID': request_id,
'Search_Datetime': search_dt
})
dbf.newFlightDeals(flight_main)
outFile = dbf.export_FlightDeals(request_id, search_dt)
return outFile
def gethistorylist(input):
# 获取xxxx年的数据
input = str(input)
date_start = input + '-08-01' #一年开始的日期 （试一试10天的）
date_end = input + '-12-31' #一年结束的日期
#初始化页面
t.init()
#输入url进入
t.url("http://bank.jrj.com.cn/bankpro/data.shtml?type=1")
#等5秒网页加载
t.wait(5)
#鼠标放上去，点击精简选项
t.hover(element_identifier='//*[@id="fxr"]')
t.click(element_identifier='//*[@id="zksq"]')
#鼠标移动到发行日期上，点击文本栏，输入发行日日期为今日，点击搜索
t.hover(element_identifier='//*[@id="fxr"]')
t.click(element_identifier='//*[@id="fxr"]')
t.type(element_identifier='//*[@id="fxr"]', text_to_type=date_start)
#再点击，确保日期不会遮住底下的搜索按钮
t.click(element_identifier='//*[@id="fxr"]')
t.hover(element_identifier='//*[@class="ipf01"]')
t.click(element_identifier='//*[@class="ipf01"]')
#把展示的尺寸设置为50个产品每页：
t.hover(element_identifier='//*[@data-pagesize="50"]')
t.click(element_identifier='//*[@data-pagesize="50"]')
#点击以发行日升序排行，等价于"倒过来取"
t.hover(element_identifier='//*[@data-sort = "sell_org_date"]')
t.click(element_identifier='//*[@data-sort = "sell_org_date"]')
#当下一页没有被disable的时候,有以下超参数
page_curr = 1 #当前页面index
value_dict = {} #存放data
max_page = 1 #最大的页面数记录
#存放列名
name_list = ['序号', '综合评级', 'url']
for col_name in name_list:
value_dict.setdefault(col_name, []) #初始化空数据集
#当可以翻页，或数据只有一页的时候，进行循环
stop_flag = False
#当当前页面不是最后一页，或只有一页时，都进行如下循环
while (t.read(element_identifier=
'//div[@id = "pagefoot"]//a[@class = "cur pf-disabled"]')
== str(page_curr)) or (page_curr == 1):
if stop_flag == True: #如果没有今年的数据，就没必要翻页了
break
max_page = page_curr
#每页的数据量大小（row number）
count_values = int(
t.count(element_identifier='//tbody[@id = "content"]//tr')
) + 1 # python从0开始
#爬取页面所有一个table里的值
filename = str(input) + str("_") + str(page_curr) + "history_data.csv"
t.wait(1) #等1秒，万一加载错误了
t.table(
element_identifier='//div[@class = "table-s1 tab-s2 w100"]//table',
filename_to_save=filename)
#爬取当前页面 (只有title和href）
for i in range(1, count_values):
# 判定条件：如果是今年内(小于今年12-31或等于12-31的)，全都要
if str(
t.read(element_identifier='//tbody[@id = "content"]//tr[' +
str(i) + ']//td[@class = "px"]')) <= date_end:
# print("number {} is running".format(str(i)))
#爬取产品名称作为primary key，之后join用：
# 产品序号
value_dict[name_list[0]].append(
t.read(element_identifier='//tbody[@id = "content"]//tr[' +
str(i) + ']/td[2]'))
# 综合评级
value_dict[name_list[1]].append(
t.read(element_identifier='//tbody[@id = "content"]//tr[' +
str(i) + ']//td[12]//i/@title'))
# url
value_dict[name_list[2]].append(
t.read(element_identifier='//tbody[@id = "content"]//tr[' +
str(i) + ']//a/@href'))
else: # 如果已经超过今年的数据了，此线程结束，flag置true, while循环结束
stop_flag = True
# print("thread stops here..")
break
# 翻页
page_curr += 1
# print("turn the page..")
# 鼠标模拟移动，并点击翻页
t.hover(element_identifier='//*[@href="' + str(page_curr) + '"]')
t.click(element_identifier='//*[@href="' + str(page_curr) + '"]')
# #关闭tagui流
t.close()
#输出格式为："今年年份.csv"
hist_data = pd.DataFrame(value_dict)
#双格式（csv + xlsx 输出）
hist_data.to_csv(input + ".csv", encoding='UTF-8', index=False)
return max_page
def getdailyincrement(str_to_append):
#初始化页面
t.init()
#输入url进入
t.url("http://bank.jrj.com.cn/bankpro/data.shtml?type=1")
#等5秒反应
t.wait(15)
#鼠标放上去，点击精简选项
t.hover(element_identifier='//*[@id="fxr"]')
t.click(element_identifier='//*[@id="zksq"]')
#鼠标移动到发行日期上，点击文本栏，输入发行日日期为今日，点击搜索
t.hover(element_identifier='//*[@id="fxr"]')
t.click(element_identifier='//*[@id="fxr"]')
t.type(element_identifier='//*[@id="fxr"]', text_to_type=str_to_append)
#再点击，确保日期不会遮住底下的搜索按钮
t.click(element_identifier='//*[@id="fxr"]')
t.hover(element_identifier='//*[@class="ipf01"]')
t.click(element_identifier='//*[@class="ipf01"]')
#把展示的尺寸设置为50个产品每页：
t.hover(element_identifier='//*[@data-pagesize="50"]')
t.click(element_identifier='//*[@data-pagesize="50"]')
#当下一页没有被disable的时候,有以下超参数
page_curr = 1 #当前页面index
value_dict = {} #存放data
count = 1 #csv 命名用
#存放列名
name_list = ['序号', '综合评级', 'url']
for col_name in name_list:
value_dict.setdefault(col_name, []) #初始化空数据集
#当可以翻页，或数据只有一页的时候，进行循环
while (t.read(element_identifier=
'//div[@id = "pagefoot"]//a[@class = "cur pf-disabled"]')
== str(page_curr)) or (page_curr == 1):
#每页的数据量大小（row number）
count_values = int(
t.count(element_identifier='//tbody[@id = "content"]//tr')
) + 1 # python从0开始
# 爬取页面所有一个table里的值
if str(
t.read(element_identifier='//tbody[@id = "content"]//tr[' +
str(count_values - 1) +
']//td[@class = "px"]')) > str_to_append:
# print("direct continue..")
# 翻页
page_curr += 1
# 鼠标模拟移动，并点击翻页
t.hover(element_identifier='//*[@href="' + str(page_curr) + '"]')
t.click(element_identifier='//*[@href="' + str(page_curr) + '"]')
continue
filename = str(count) + "daily_data.csv"
count += 1
t.wait(1) # 等1秒，万一加载错误了
t.table(
element_identifier='//div[@class = "table-s1 tab-s2 w100"]//table',
filename_to_save=filename)
count_values = int(
t.count(element_identifier='//tbody[@id = "content"]//tr')
) + 1 # python从0开始
for i in range(1, count_values):
# 判定条件：如果是今天刚发行的，拿到所有主页面上的数据；
#如果最下面那条数据都大于今天，就直接翻页
if str(
t.read(element_identifier='//tbody[@id = "content"]//tr[' +
str(count_values - 1) +
']//td[@class = "px"]')) > str_to_append:
# print("direct break..")
break
else:
if str(
t.read(
element_identifier='//tbody[@id = "content"]//tr['
+ str(i) +
']//td[@class = "px"]')) == str_to_append:
#序号
value_dict[name_list[0]].append(
t.read(
element_identifier='//tbody[@id = "content"]//tr['
+ str(i) + ']/td[2]'))
#综合评级
value_dict[name_list[1]].append(
t.read(
element_identifier='//tbody[@id = "content"]//tr['
+ str(i) + ']//td[12]//i/@title'))
#url
value_dict[name_list[2]].append(
t.read(
element_identifier='//tbody[@id = "content"]//tr['
+ str(i) + ']//a/@href'))
else: #如果不是今天增量，什么都不做
pass
# print("turn the page..")
# 翻页
page_curr += 1
# 鼠标模拟移动，并点击翻页
t.hover(element_identifier='//*[@href="' + str(page_curr) + '"]')
t.click(element_identifier='//*[@href="' + str(page_curr) + '"]')
#关闭tagui流
t.close()
#输出格式为："今日日期.csv"
today_data = pd.DataFrame(value_dict)
today_data.to_csv(str_to_append + ".csv", index=False, encoding='UTF-8')
return count - 1
def make_reservation(reservation_date,reservation_time,party_size,restaurant_name,first_name,last_name,email_address,phone_number):
try:
#Convert User Defined Values to System Usable Values
reservation_day=reservation_date.split('/')[0]
reservation_month =reservation_date.split('/')[1]
reservation_month=int(reservation_month)-1
reservation_year =reservation_date.split('/')[2]
reservation_time_int=int(reservation_time)
start_time_hr= reservation_time[:2]
if reservation_time_int>1159:
if start_time_hr!="12":
start_time_hr=int(start_time_hr)-12
start_time_option = str(start_time_hr)+":"+reservation_time[2:4]+" pm"
else:
start_time_option = str(start_time_hr)+":"+reservation_time[2:4]+" am"
#Booking Parameters
chope_url ='https://www.chope.co/singapore-restaurants/category/restaurant/'
t.init()
t.url(chope_url)
t.wait(10)
#Date Field
t.click(f"(//span[contains(@class,'input-group-addon icon-calendar')])[1]")
t.wait(7)
boolean_flag=1
while boolean_flag:
if t.present(f"//td[@data-handler='selectDay'and @data-year='{reservation_year}' and @data-month='{reservation_month}']/a[text()='{reservation_day}']"):
t.click(f"//td[@data-handler='selectDay'and @data-year='{reservation_year}' and @data-month='{reservation_month}']/a[text()='{reservation_day}']")
boolean_flag=0
else:
t.click('//a[@title="Next"]')
t.click(f"//td[@data-handler='selectDay'and @data-month='{reservation_month}']/a[text()='{reservation_day}']")
#Time Field
t.select(f"//select[contains(@id,'time-field')]",start_time_option)
#Number of Diners Field
t.click(f"(//span[contains(@class,'input-group-addon icon-person')])[1]")
t.select(f"//select[contains(@id,'adults')]",party_size)
#Restaurant Field
t.type(f"//select[contains(@id,'sb-sel-restaurant')]",restaurant_name)
t.click('//button[@id="btn-search"]')
t.wait(5)
#Secondary Page to Confirm Timing
t.click(f"//a[contains(@rname,'{restaurant_name}') and text()='{start_time_option}']")
t.wait(5)
t.click(f"//input[@id='btn_sub' and @value='Book Now']")
t.wait(5)
#Booking Confirmation
t.popup('https://book.chope.co/')
#First Name
t.type('//input[@id="forename"]',first_name)
#Last Name
t.type('//input[@id="surname"]',last_name)
#Email
t.type('//input[@id="email"]',email_address)
#Phone Number
t.type('//input[@id="telephone"]',phone_number)
#Agree Terms & Conditions
if t.present(f"//input[@name='agree_term_conditions']"):
t.click(f"//input[@name='agree_term_conditions']")
#Confirm Booking
t.click(f"//button[@id='check_book_now']")
t.wait(5)
t.close()
print('Success')
schedule_reservation(reservation_date,reservation_time,party_size,restaurant_name,first_name,sample_restaurant_address)
return 'Reservation Successful'
except:
print('Error')
return 'Reservation Unsuccessful. Unforunately, the restaurant was not able to accomodate your reservation.'
def compliance_data(url_prefix):
t.init() #
init_url = url_prefix + '1.html'
t.url(init_url) #初始url
max_page = int(
t.read(element_identifier='//td[@class = "Normal"]').split('/')
[1]) + 1 #最大page数量
for page_num in range(1, max_page):
t.url(url_prefix + str(page_num) + '.html')
print("现在所在页面 {}".format(page_num))
t.wait(5)
# 拿到value
count_values = t.count(
element_identifier='//td[@colspan = "2"]//table') + 1
today = datetime.datetime.today()
today = str(today.date())
# today = '2018-04-24'
if t.read(element_identifier=
'//td[@colspan = "2"]//table[1]//span[@class = "hui12"]'
) < today:
print("今日无增量")
break
print("页面有{}个文件".format(count_values - 1))
t.wait(5)
for i in range(1, count_values):
t.url(url_prefix + str(page_num) + '.html')
if t.read(element_identifier='//td[@colspan = "2"]//table[' +
str(i) + ']//span[@class = "hui12"]') < today:
t.close()
exit(1)
file_name = t.read(
element_identifier='//td[@colspan = "2"]//table[' + str(i) +
']') + str('.txt')
prefix = 'http://www.pbc.gov.cn'
content_url = prefix + t.read(
element_identifier='//td[@colspan = "2"]//table[' + str(i) +
']//a/@href')
if 'cnhttp' in content_url:
content_url = content_url[21:] # 不知道为什么会出错这个
t.url(content_url)
text = t.read(element_identifier='//div[@id = "zoom"]')
with open(file_name, 'w') as f:
f.write(text)
print("文件{} 是文档。".format(i))
continue
t.url(content_url) #进入二级目录
#获取pdf的数量，pdf的名字和pdf应该有的名字
t.wait(2)
pdf_count = t.count(
element_identifier='//div[@id = "zoom"]//a/@href')
if pdf_count == 0: ##如果是正常的txt文件
# 取到列表
print("文件{} 是文档。".format(i))
# 取text
if t.read(element_identifier='//div[@id = "zoom"]') != '':
text = t.read(element_identifier='//div[@id = "zoom"]')
with open(file_name, 'w') as f:
f.write(text)
elif t.read(element_identifier='//td[@class = "p1"]') != '':
text = t.read(element_identifier='//td[@class = "p1"]')
with open(file_name, 'w') as f:
f.write(text)
else:
print("write files fails...")
elif ('pdf' in t.read(
element_identifier='//div[@id = "zoom"]//a/@href')):
print("文件{} 含有 {} 个pdf。".format(i, pdf_count))
pdf_count += 1 #python从0开始，所以至少有一个pdf count
for j in range(1, pdf_count):
#取pdf的名字
if t.read(element_identifier='//div[@id = "zoom"]//p[' +
str(j) + ']//a/@href') != '':
print("当前是第{}个pdf。。".format(j))
pdf_name = t.read(
element_identifier='//div[@id = "zoom"]//p[' +
str(j) + ']//a/@href').split('/')[-1]
#取合规名
pdf_name_to_change = t.read(
element_identifier='//div[@id = "zoom"]//p[' +
str(j) + ']//a')
#下载
prefix = 'http://www.pbc.gov.cn'
t.url(prefix + t.read(
element_identifier='//div[@id = "zoom"]//p[' +
str(j) + ']//a/@href'))
wait_seconds = 1
total_seconds = 0
while os.path.exists(pdf_name) == False:
t.wait(wait_seconds)
total_seconds += wait_seconds
if total_seconds > 30:
print('download fails')
break
os.rename(pdf_name, pdf_name_to_change) #改名
t.url(content_url) #返回二级目录
else:
print("不合规，当文档处理！不读了！！！")
# 取text
if t.read(element_identifier='//div[@id = "zoom"]'
) != '':
text = t.read(
element_identifier='//div[@id = "zoom"]')
with open(file_name, 'w') as f:
f.write(text)
elif t.read(element_identifier='//td[@class = "p1"]'
) != '':
text = t.read(
element_identifier='//td[@class = "p1"]')
with open(file_name, 'w') as f:
f.write(text)
else:
print("write files fails...")
t.url(url_prefix + str(page_num) + '.html')
break
else:
print("文件{} 含有 {} 个pdf。".format(i, pdf_count))
print("含有其他format的href，当文档处理！不读了！！！")
# 取text
if t.read(element_identifier='//div[@id = "zoom"]') != '':
text = t.read(element_identifier='//div[@id = "zoom"]')
with open(file_name, 'w') as f:
f.write(text)
elif t.read(element_identifier='//td[@class = "p1"]') != '':
text = t.read(element_identifier='//td[@class = "p1"]')
with open(file_name, 'w') as f:
f.write(text)
else:
print("write files fails...")
t.url(url_prefix + str(page_num) + '.html')
break
t.close()
import tagui as t
import os
import PIL.Image as im
import logging
def findAllFile(base):
for root, ds, fs in os.walk(base):
for f in fs:
yield f
t.close()
logging.basicConfig(filename = "log.txt")
srcDirectory = "OrgImage"
t.init(visual_automation = True)
for target in findAllFile(srcDirectory):
target_image = 'OrgImage/' + target
t.url('https://www.bing.com')
t.click('//div[@id="sb_sbi"]/img')
t.upload("input.fileinput",target_image)
t.wait(3)
succDownload = False
image_nums = t.count('//a[@class="richImgLnk"]')
print(image_nums)
if t.click('//li[contains(string(),"Pages")]') == False:
image_nums = 0
def getblanklist():
#初始化页面
t.init()
#输入url进入
t.url("http://bank.jrj.com.cn/bankpro/data.shtml?type=1")
#直接开始搜索，不需要任何筛选条件
t.click(element_identifier='//*[@id="fxr"]')
t.hover(element_identifier='//*[@class="ipf01"]')
t.click(element_identifier='//*[@class="ipf01"]')
#把展示的尺寸设置为50个产品每页：
t.hover(element_identifier='//*[@data-pagesize="50"]')
t.click(element_identifier='//*[@data-pagesize="50"]')
#点击以发行日升序排行，等价于"倒过来取"，这样发行日为空的会在最前面
t.hover(element_identifier='//*[@data-sort = "sell_org_date"]')
t.click(element_identifier='//*[@data-sort = "sell_org_date"]')
#当下一页没有被disable的时候,有以下超参数
page_curr = 1 #当前页面index
max_page = 1 # 最大的页面数记录
# 存放列名
value_dict = {} # 存放data
name_list = ['序号', '综合评级', 'url']
for col_name in name_list:
value_dict.setdefault(col_name, []) # 初始化空数据集
#当可以翻页，或数据只有一页的时候，进行循环
stop_flag = False # 初始化一个flag，flag = true代表我们需要的数据已经取完了，没必要再翻页了
while (t.read(element_identifier=
'//div[@id = "pagefoot"]//a[@class = "cur pf-disabled"]')
== str(page_curr)) or (page_curr == 1):
if stop_flag == True: #如果没有空白数据了，就没必要翻页了
break
max_page = page_curr
#每页的数据量大小（row number）
count_values = int(
t.count(element_identifier='//tbody[@id = "content"]//tr')
) + 1 # python从0开始
# 爬取页面所有一个table里的值
filename = str(page_curr) + "blank_date.csv"
t.wait(1) # 等1秒，万一加载错误了
t.table(
element_identifier='//div[@class = "table-s1 tab-s2 w100"]//table',
filename_to_save=filename)
#爬取当前页面 (只有title和href）
for i in range(1, count_values):
# 判定条件：如果发行日是空(--)，进入此if
if str(
t.read(element_identifier='//tbody[@id = "content"]//tr[' +
str(i) + ']//td[@class = "px"]')) == '--':
# print("number {} is running".format(str(i)))
# 序号
value_dict[name_list[0]].append(
t.read(element_identifier='//tbody[@id = "content"]//tr[' +
str(i) + ']/td[2]'))
# 综合评级
value_dict[name_list[1]].append(
t.read(element_identifier='//tbody[@id = "content"]//tr[' +
str(i) + ']//td[12]//i/@title'))
# url
value_dict[name_list[2]].append(
t.read(element_identifier='//tbody[@id = "content"]//tr[' +
str(i) + ']//a/@href'))
else: # 如果不再是空值-- ，此线程结束，flag置true, while循环结束
stop_flag = True
# print("thread stops here..")
break
# 翻页
page_curr += 1
# print("turn the page..")
# 鼠标模拟移动，并点击翻页
t.hover(element_identifier='//*[@href="' + str(page_curr) + '"]')
t.click(element_identifier='//*[@href="' + str(page_curr) + '"]')
# #关闭tagui流
t.close()
#
# 输出格式为："blank_date.csv"
hist_data = pd.DataFrame(value_dict)
hist_data.to_csv("blank_date.csv", index=False, encoding='UTF-8')
return max_page
def history_data(url_prefix):
t.init()
init_url = url_prefix + '1.html'
t.url(init_url)
max_page = int(
t.read(element_identifier='//td[@class = "Normal"]').split('/')[1]) + 1
for page_num in range(1, max_page):
#主页面
t.url(url_prefix + str(page_num) + '.html')
print("现在所在页面 {}".format(page_num))
t.wait(5)
#拿到value
count_values = t.count(
element_identifier='//td[@colspan = "2"]//table') + 1
today = datetime.datetime.today()
today = str(today.date())
if t.read(element_identifier=
'//td[@colspan = "2"]//table[1]//span[@class = "hui12"]'
) < today:
print("今日无增量")
break
print("页面有{}个文件".format(count_values - 1))
t.wait(5)
for i in range(1, count_values):
t.url(url_prefix + str(page_num) + '.html')
if t.read(element_identifier='//td[@colspan = "2"]//table[' +
str(i) + ']//span[@class = "hui12"]') < today:
break
if '.html' in t.read(
element_identifier='//td[@colspan = "2"]//table[' +
str(i) + ']//a/@href'):
#取到列表
print("文件{} 是文档。".format(i))
file_name = t.read(
element_identifier='//td[@colspan = "2"]//table[' +
str(i) + ']') + str('.txt')
prefix = 'http://www.pbc.gov.cn'
content_url = prefix + t.read(
element_identifier='//td[@colspan = "2"]//table[' +
str(i) + ']//td//a/@href')
# 点击url
if content_url == 'http://www.pbc.gov.cnhttp://www.pbc.gov.cn/goutongjiaoliu/113456/113469/3487563/index.html':
content_url = 'http://www.pbc.gov.cn/goutongjiaoliu/113456/113469/3487563/index.html' #不知道为什么会出错这个
t.url(content_url)
# 取text
if t.read(element_identifier='//div[@id = "zoom"]') != '':
text = t.read(element_identifier='//div[@id = "zoom"]')
with open(file_name, 'w') as f:
f.write(text)
elif t.read(element_identifier='//td[@class = "p1"]') != '':
text = t.read(element_identifier='//td[@class = "p1"]')
with open(file_name, 'w') as f:
f.write(text)
else:
print("write files fails...")
elif '.doc' in t.read(
element_identifier='//td[@colspan = "2"]//table[' +
str(i) + ']//a/@href'):
# 取到数据
print("文件{} 是下载doc。".format(i))
file_name = t.read(
element_identifier='//td[@colspan = "2"]//table[' +
str(i) + ']//a/@href').split('/')[-1]
prefix = 'http://www.pbc.gov.cn'
content_url = prefix + t.read(
element_identifier='//td[@colspan = "2"]//table[' +
str(i) + ']//a/@href')
t.url(content_url)
wait_seconds = 1
total_seconds = 0
while os.path.exists(file_name) == False:
t.wait(wait_seconds)
total_seconds += wait_seconds
if total_seconds > 30:
print('download fails')
break
else:
print("unknown format..")
print("爬好一次，返回页面 {}".format(page_num))
#close out
t.close()
def gethistorylist(inputyear):
# 获取xxxx年的数据
input = inputyear
date_start = input + '-01-01' #一年开始的日期 （试一试10天的）
date_end = input + '-12-31' #一年结束的日期
#初始化页面
t.init()
#输入url进入
t.url("http://bank.jrj.com.cn/bankpro/data.shtml?type=1")
#鼠标放上去，点击精简选项
t.hover(element_identifier='//*[@id="fxr"]')
t.click(element_identifier='//*[@id="zksq"]')
#鼠标移动到发行日期上，点击文本栏，输入发行日日期为今日，点击搜索
t.hover(element_identifier='//*[@id="fxr"]')
t.click(element_identifier='//*[@id="fxr"]')
t.type(element_identifier='//*[@id="fxr"]', text_to_type=date_start)
#再点击，确保日期不会遮住底下的搜索按钮
t.click(element_identifier='//*[@id="fxr"]')
t.hover(element_identifier='//*[@class="ipf01"]')
t.click(element_identifier='//*[@class="ipf01"]')
#把展示的尺寸设置为50个产品每页：
t.hover(element_identifier='//*[@data-pagesize="50"]')
t.click(element_identifier='//*[@data-pagesize="50"]')
#点击以发行日升序排行，等价于"倒过来取"
t.hover(element_identifier='//*[@data-sort = "sell_org_date"]')
t.click(element_identifier='//*[@data-sort = "sell_org_date"]')
#当下一页没有被disable的时候,有以下超参数
page_curr = 1 #当前页面index
value_dict = {} #存放data
#存放列名
name_list = [
'序号', '产品名称', '发行银行', '委托货币', '发行日', '停售日', '管理期(天)', '预期收益率', '到期收益率',
'与同期储蓄比', '综合评级', 'url'
]
for col_name in name_list:
value_dict.setdefault(col_name, []) #初始化空数据集
#当可以翻页，或数据只有一页的时候，进行循环
stop_flag = False
#当当前页面不是最后一页，或只有一页时，都进行如下循环
while (t.read(element_identifier=
'//div[@id = "pagefoot"]//a[@class = "cur pf-disabled"]')
== str(page_curr)) or (page_curr == 1):
if stop_flag == True: #如果没有今年的数据，就没必要翻页了
break
#每页的数据量大小（row number）
count_values = int(
t.count(element_identifier='//tbody[@id = "content"]//tr')
) + 1 # python从0开始
#爬取当前页面
for i in range(1, count_values):
# 判定条件：如果是今年内(小于今年12-31或等于12-31的)，全都要
if str(
t.read(element_identifier='//tbody[@id = "content"]//tr[' +
str(i) + ']//td[@class = "px"]')) <= date_end:
# 序号
value_dict[name_list[0]].append(
t.read(element_identifier='//tbody[@id = "content"]//tr[' +
str(i) + ']/td[2]'))
# 产品名称
value_dict[name_list[1]].append(
t.read(element_identifier='//tbody[@id = "content"]//tr[' +
str(i) + ']/td[3]'))
# 发行银行
value_dict[name_list[2]].append(
t.read(element_identifier='//tbody[@id = "content"]//tr[' +
str(i) + ']/td[4]'))
# 委托货币
value_dict[name_list[3]].append(
t.read(element_identifier='//tbody[@id = "content"]//tr[' +
str(i) + ']/td[5]'))
# 发行日
value_dict[name_list[4]].append(
t.read(element_identifier='//tbody[@id = "content"]//tr[' +
str(i) + ']/td[6]'))
# 停售日
value_dict[name_list[5]].append(
t.read(element_identifier='//tbody[@id = "content"]//tr[' +
str(i) + ']/td[7]'))
# 管理期（天）
value_dict[name_list[6]].append(
t.read(element_identifier='//tbody[@id = "content"]//tr[' +
str(i) + ']/td[8]'))
# 预期收益率
value_dict[name_list[7]].append(
t.read(element_identifier='//tbody[@id = "content"]//tr[' +
str(i) + ']/td[9]'))
# 到期收益率
value_dict[name_list[8]].append(
t.read(element_identifier='//tbody[@id = "content"]//tr[' +
str(i) + ']/td[10]'))
# 与同期储蓄比
value_dict[name_list[9]].append(
t.read(element_identifier='//tbody[@id = "content"]//tr[' +
str(i) + ']/td[11]'))
# 综合评级
value_dict[name_list[10]].append(
t.read(element_identifier='//tbody[@id = "content"]//tr[' +
str(i) + ']//td[12]//i/@title'))
# url
value_dict[name_list[11]].append(
t.read(element_identifier='//tbody[@id = "content"]//tr[' +
str(i) + ']//a/@href'))
else: # 如果已经超过今年的数据了，此线程结束，flag置true, while循环结束
stop_flag = True
print("thread stops here..")
break
# 翻页
page_curr += 1
print("turn the page..")
# 鼠标模拟移动，并点击翻页
t.hover(element_identifier='//*[@href="' + str(page_curr) + '"]')
t.click(element_identifier='//*[@href="' + str(page_curr) + '"]')
# #关闭tagui流
t.close()
#输出格式为："今年年份.csv"
hist_data = pd.DataFrame(value_dict)
#双格式（csv + xlsx 输出）
hist_data.to_csv(input + ".csv", index=False, encoding='UTF-8')
hist_data.to_excel(input + ".xlsx", index=False, encoding='UTF-8')
#gethistorylist('2003')
def history_data_daily(url_prefix):
t.init() #
init_url = url_prefix + '1.html'
t.url(init_url) # 初始url
max_page = int(t.read(element_identifier='//td[@class = "Normal"]').split('/')[1]) + 1 # 最大page数量
for page_num in range(1, max_page):
t.url(url_prefix + str(page_num) + '.html')
print("现在所在页面 {}".format(page_num))
t.wait(5)
# 拿到value
count_values = t.count(element_identifier='//td[@colspan = "2"]//table') + 1
today = datetime.datetime.today()
today = str(today.date())
# today = '2018-04-24'
if t.read(element_identifier='//td[@colspan = "2"]//table[1]//span[@class = "hui12"]') < today:
print("今日无增量")
break
print("页面有{}个文件".format(count_values - 1))
t.wait(5)
for i in range(1, count_values):
t.url(url_prefix + str(page_num) + '.html')
if t.read(element_identifier='//td[@colspan = "2"]//table['+str(i)+']//span[@class = "hui12"]') < today:
t.close()
exit(1)
file_name = t.read(element_identifier='//td[@colspan = "2"]//table[' + str(i) + ']')
file_name = file_name[:-10] + str("_") + file_name[-10:] + str('.txt')
time = file_name[-14:-4]
prefix = 'http://www.pbc.gov.cn'
content_url = prefix + t.read(
element_identifier='//td[@colspan = "2"]//table[' + str(i) + ']//a/@href')
if '.html' not in t.read(element_identifier='//td[@colspan = "2"]//table[' + str(i) + ']//a/@href'):
# 当直接跳到需要下载的文件的时候
if 'cnhttp' in content_url:
content_url = content_url[21:] # 不知道为什么会出错这个
# 取到数据
print("文件{} 是直接下载文件。".format(i))
file_name = t.read(element_identifier='//td[@colspan = "2"]//table[' + str(i) + ']//a/@href')
suffix = file_name.split('.')[-1]
file_name = file_name.split('/')[-1]
t.url(content_url)
wait_seconds = 1
total_seconds = 0
while os.path.exists(file_name) == False:
t.wait(wait_seconds)
total_seconds += wait_seconds
if total_seconds > 30:
print('download fails')
break
os.rename(file_name, file_name[:-(len(suffix)+1)] + "_" + time +'.'+file_name[-(len(suffix)+1):])
else:
# 取到数据
print("文件{} 是直接下载文件。".format(i))
file_name = t.read(element_identifier='//td[@colspan = "2"]//table[' + str(i) + ']//a/@href')
suffix = file_name.split('.')[-1]
file_name = file_name.split('/')[-1]
t.url(content_url)
wait_seconds = 1
total_seconds = 0
while os.path.exists(file_name) == False:
t.wait(wait_seconds)
total_seconds += wait_seconds
if total_seconds > 30:
print('download fails')
break
os.rename(file_name, file_name[:-(len(suffix)+1)] + "_" + time +'.'+file_name[-(len(suffix)+1):])
else: # 当没有直接下载的时候
if 'cnhttp' in content_url:
content_url = content_url[21:] # 不知道为什么会出错这个
t.url(content_url)
else:
t.url(content_url)
# 获取pdf的数量，pdf的名字和pdf应该有的名字
t.wait(2)
pdf_count = t.count(element_identifier='//div[@id = "zoom"]//a/@href')
if pdf_count == 0: ##如果是正常的txt文件
# 取到列表
print("文件{} 是文档。".format(i))
# 取text
if t.read(element_identifier='//div[@id = "zoom"]') != '':
text = t.read(element_identifier='//div[@id = "zoom"]')
with open(file_name, 'w') as f:
f.write(text)
elif t.read(element_identifier='//td[@class = "p1"]') != '':
text = t.read(element_identifier='//td[@class = "p1"]')
with open(file_name, 'w') as f:
f.write(text)
else:
print("write files fails...")
else:
# 取text
if t.read(element_identifier='//div[@id = "zoom"]') != '':
text = t.read(element_identifier='//div[@id = "zoom"]')
with open(file_name, 'w') as f:
f.write(text)
elif t.read(element_identifier='//td[@class = "p1"]') != '':
text = t.read(element_identifier='//td[@class = "p1"]')
with open(file_name, 'w') as f:
f.write(text)
else:
print("write files fails...")
print("文件{} 含有 {} 个文件要下载。".format(i, pdf_count))
pdf_count += 1 # python从0开始，所以至少有一个pdf count
current_count = 0
for j in range(1, pdf_count):
# 取pdf的名字
if '.htm' not in t.read(element_identifier='//div[@id = "zoom"]//p//a/@href'):
print("当前是第{}个文件。。".format(j))
p_count = t.count(element_identifier='//div[@id = "zoom"]//p')
while current_count <= p_count:
if t.read(element_identifier='//div[@id = "zoom"]//p[last()-' + str(current_count) + ']//a') != '':
#如果取到了
print("这个p有!")
pdf_name = t.read(element_identifier='//div[@id = "zoom"]//p[last()-' + str(current_count) + ']//a/@href')
# 取合规名
pdf_name_to_change = t.read(element_identifier='//div[@id = "zoom"]//p[last()-' + str(current_count) + ']//a')
# 下载
suffix = pdf_name.split('.')[-1]
pdf_name = pdf_name.split('/')[-1]
prefix = 'http://www.pbc.gov.cn'
download_link = prefix + t.read(element_identifier='//div[@id = "zoom"]//p[last()-' + str(current_count) + ']//a/@href')
if 'cnhttp' in download_link:
t.url(t.read(element_identifier='//div[@id = "zoom"]//p[last()-' + str(current_count) + ']//a/@href'))
else:
t.url(download_link)
wait_seconds = 1
total_seconds = 0
while os.path.exists(pdf_name) == False:
t.wait(wait_seconds)
total_seconds += wait_seconds
if total_seconds > 30:
print('download fails')
break
os.rename(pdf_name, pdf_name_to_change) # 改名
os.rename(pdf_name_to_change,
pdf_name_to_change[:-(len(suffix)+1)] + '_' + time + pdf_name_to_change[-(len(suffix)+1):])
t.url(content_url) # 返回二级目录
current_count += 1
break
else:
current_count += 1
print("这个p没有")
else:
print("是个网页，当文档处理！")
prefix = 'http://www.pbc.gov.cn'
download_link = prefix + t.read(
element_identifier='//div[@id = "zoom"]//p[' + str(j) + ']//a/@href')
if 'cnhttp' in download_link:
t.url(t.read(element_identifier='//div[@id = "zoom"]//p[' + str(j) + ']//a/@href'))
else:
t.url(download_link)
# 取text
if t.read(element_identifier='//div[@id = "zoom"]') != '':
text = t.read(element_identifier='//div[@id = "zoom"]')
with open(file_name, 'w') as f:
f.write(text)
elif t.read(element_identifier='//td[@class = "p1"]') != '':
text = t.read(element_identifier='//td[@class = "p1"]')
with open(file_name, 'w') as f:
f.write(text)
else:
print("write files fails...")
t.close()
def propertydata_update(project_name):
df1 = pd.read_excel('Property Monitor.xlsx')
t.close()
t.init()
project_url = f'https://www.propertyguru.com.sg/property-for-sale?market=residential&freetext={project_name}&newProject=all'
print(project_url)
t.url(project_url)
wait_for_pageload('//div[@class="header-wrapper"]')
num_result_ad = 3
# load main page, get detail page url link
url = [''] * num_result_ad
id = [''] * num_result_ad
for n in [x for x in range(1, num_result_ad + 1)
if x != 4 and x != 8]: # skip 4th and 8th advertisement
wait_for_pageload(
f'(//div[@class="listing-widget-new"]/div[{n}]/div[1]/div[2]/div[1]/div[1]/h3/a/@href)'
)
url[n - 1] = read_if_present(
f'(//div[@class="listing-widget-new"]/div[{n}]/div[1]/div[2]/div[1]/div[1]/h3/a/@href)'
)
print(f"{n}. url = " + url[n - 1])
id[n - 1] = read_if_present(
f'(//*[@id="wrapper-inner"]/section[1]/div[2]/div[1]/div[2]/div[2]/section/div[2]/div[{n}]/@data-listing-id)'
)
print(f'searching: {id}') # ['22036842', '21725956', '20648962']
id_int = list(df1['id'])
id_str = list()
for n in id_int:
id_str.append(str(n))
print(id_str)
new_url = list()
for n in id:
if n not in id_str:
print(f'new property found: {n}')
u = f"https://www.propertyguru.com.sg/listing/{n}/for-sale-{project_name}"
new_url.append(u)
if new_url == []:
return print(f'======== no new property found! ==========')
print(f'======== new property found==========')
property_title = [''] * len(new_url)
pdf = [''] * len(new_url)
pdf_link = [''] * len(new_url)
for (n, i) in zip(new_url, range(1, len(new_url) + 1)):
t.url(n)
wait_for_pageload('//h1[@class="h2"]')
property_title[i - 1] = read_if_present('//h1[@class="h2"]')
print(f"{i}. property_title = " + property_title[i - 1])
pdf[i - 1] = read_if_present(
'//*[@id="sticky-right-col"]/div[3]/a[2]/@href')
pdf_link[i - 1] = 'https://www.propertyguru.com.sg' + pdf[i - 1]
print(f"{i}. pdf_link = " + pdf_link[i - 1])
property_info = {
'property_title': property_title,
'url': ['https://www.propertyguru.com.sg' + x for x in url],
'id': id,
'pdf_link': pdf_link,
}
df2 = DataFrame(property_info,
columns=['property_title', 'id', 'url', 'pdf_link'])
new_df = pd.concat([df1, df2])
new_df.to_excel('Property Monitor.xlsx', encoding='utf8', index=None)
print('======== Property Monitor.xlsx update ==========')
pdf_filename = download_pdf(property_title, pdf_link, id)
mail_subscription(input_email, input_name, pdf_filename)
def open_email(self):
t.init(visual_automation=False)
self.login()
import tagui as t
import datetime
import os
import urllib.request
if not os.path.exists(r'C:\Users\garv2\Desktop\SBI'): #SBI
os.makedirs(r'C:\Users\garv2\Desktop\SBI')
if not os.path.exists(r'C:\Users\garv2\Desktop\PNB'): #PNB
os.makedirs(r'C:\Users\garv2\Desktop\PNB')
if not os.path.exists(r'C:\Users\garv2\Desktop\INDIAN BANK'): #Indian Bank
os.makedirs(r'C:\Users\garv2\Desktop\INDIAN BANK')
if not os.path.exists(r'C:\Users\garv2\Desktop\INDIAN OVERSEAS BANK'): #Indian OVERSEAS Bank
os.makedirs(r'C:\Users\garv2\Desktop\INDIAN OVERSEAS BANK')
t.init(visual_automation = True,chrome_browser = True)
today=datetime.datetime.now()
yesterday=today -datetime.timedelta(days=1)
sdate=yesterday.strftime('%d/%m/%Y')
edate=today.strftime('%d/%m/%Y')
filename=today.strftime('%d.%m.%Y %H.%M.%S')
directory=os.getcwd()
t.url("https://corp.onlinesbi.com?saral/login.htm")
t.wait(5)
t.keyboard('[tab]')
t.wait(1)
t.keyboard('[esc]')
t.wait(1)
t.keyboard('[tab]')
t.wait(1)
t.keyboard('[esc]')
t.wait(2)
t.click('//*[@id="banking"]/div[2]/div/div/div/a')
def get_shoe(shoe_name, g, email):
"""
Get shoe details from jdsports.com.sg
:param shoe_name: name of the shoe to search for
:param gender: gender of the subscriber
:param email: email id of the subscriber
:return: details, list of shoe details.
"""
details = []
t.init(visual_automation=True)
t.url('https://www.jdsports.com.sg/')
t.wait(5)
final_command = shoe_name + " shoes" + '[enter]'
t.keyboard('[esc]')
t.type('//input[@id = "srchInput"]', final_command)
#t.click('//input[@id ="srchButton"]')
t.wait(3)
if g == ' men':
if t.read(
'(//a[@data-e2e="plp-filterMenu-catItem"]/span)[contains(.,"Men")]'
):
t.click('(//a[@data-e2e="plp-filterMenu-catItem"]/span)[1]')
count = t.count(
'//ul[@id="productListMain"]//li[@class="productListItem "]')
t.wait(3)
if count != 0:
for i in range(1, min(count, 4)):
price = t.read(f'(//span[@class="pri"])[{i}]')
name = t.read(f'(//span[@class="itemTitle"])[{i}]')
img = t.read(
f'(//a[@class="itemImage"]/picture/img/@srcset)[{i}]')
link = "https://www.jdsports.com.sg" + t.read(
f'(//span[@class = "itemTitle"])[{i}]/a/@href')
details.append({
"email": email,
"name": name,
"price": price,
"img": img,
"Company": "JD",
"link": link
})
else:
details.append({
"email": email,
"name": "NA",
"price": "NA",
"img": "NA",
"Company": "JD",
"link": "NA"
})
elif g == ' women':
if t.read(
'(//a[@data-e2e="plp-filterMenu-catItem"]/span)[contains(.,"Women")]'
):
t.click(
'(//a[@data-e2e="plp-filterMenu-catItem"]/span)[.="Women"]')
count = t.count(
'//ul[@id="productListMain"]//li[@class="productListItem "]')
t.wait(3)
if count != 0:
for i in range(1, min(count, 4)):
price = t.read(f'(//span[@class="pri"])[{i}]')
name = t.read(f'(//span[@class="itemTitle"])[{i}]')
img = t.read(
f'(//a[@class="itemImage"]/picture/img/@srcset)[{i}]')
link = "https://www.jdsports.com.sg" + t.read(
f'(//span[@class = "itemTitle"])[{i}]/a/@href')
details.append({
"email": email,
"name": name,
"price": price,
"img": img,
"Company": "JD",
"link": link
})
else:
details.append({
"email": email,
"name": "NA",
"price": "NA",
"img": "NA",
"Company": "JD",
"link": "NA"
})
else:
count = t.count(
'//ul[@id="productListMain"]//li[@class="productListItem "]')
t.wait(3)
if count != 0:
for i in range(1, min(count, 4)):
price = t.read(f'(//span[@class="pri"])[{i}]')
name = t.read(f'(//span[@class="itemTitle"])[{i}]')
img = t.read(
f'(//a[@class="itemImage"]/picture/img/@srcset)[{i}]')
link = "https://www.jdsports.com.sg" + t.read(
f'(//span[@class = "itemTitle"])[{i}]/a/@href')
details.append({
"email": email,
"name": name,
"price": price,
"img": img,
"Company": "JD",
"link": link
})
else:
details.append({
"email": email,
"name": "NA",
"price": "NA",
"img": "NA",
"Company": "JD",
"link": "NA"
})
#t.close()
if len(details) == 0:
details.append({
"email": email,
"name": "NA",
"price": "NA",
"img": "NA",
"Company": "JD",
"link": "NA"
})
# print("JD BOT",details)
return details
# Sample script to search on Yahoo, take screenshot of results and visit DuckDuckgo
# TagUI for Python's simple and powerful API makes digital process automation fun!
# pip install tagui to install, pip install tagui --upgrade for latest version
# to use in Jupyter notebook, Python script or interactive shell
import tagui as t
# use init() to start TagUI, it autoruns setup() to download TagUI
# default init(visual_automation = False, chrome_browser = True)
t.init()
# use url('your_url') to go to web page, url() returns current URL
t.url('https://ca.yahoo.com')
# use type() to enter text into an UI element or x, y location
# '[enter]' = enter key, '[clear]' = clear field
t.type('search-box', 'github')
# use read() to fetch and return text from UI element
search_text = t.read('search-box')
# use echo() to print to output, same as Python print()
t.echo(search_text)
# use click() to click on an UI element or x, y location
# rclick() = right-click, dclick() = double-click
t.click('search-button')
# use wait() to wait for a number of seconds
# default wait() is 5 seconds
for multiple selection: t.read(//div[@class="r"])[0]/a/@href')
select by content: //h2[contains(.,"Selector")]
select by id: //*[@id="abc"]
t.present() to check whether some element exist or not
chrome plugin: xpath helper
https://devhints.io/xpath
'''
#--------------demo 1 -----------------------------
'''
t.init()
t.url('https://google.com')
print("test_tagui ok!")
t.type('//input[@name="q"]', 'weather[enter]')
t.type('//input[@name="q"]', '[clear]')
temp = t.read('//span[@id="wob_pp"]')
'''
#------------demo 2 --------------------------------
t.url(
'https://www.goodreads.com/list/show/17347.Books_that_ll_help_you_deliver_stunning_presentations'
def get_property(input_email, input_name, prefer1, prefer2, prefer3, input_loc,
input_size, input_price, input_bed, input_floor):
"""
:param input_email: user email
:param input_name: user name
:param prefer1:
:param prefer2:
:param prefer3:
:param input_loc: location name input_loc = ['Orchard', 'River Valley','Eunos']
:param input_size: square feet
:param input_price:
:param input_bed:
:param input_floor:
:return:
"""
# chatbot input
input_area = list()
if input_loc in ['Cecil', 'Raffles Place', 'Marina']:
input_area.append('D01')
elif input_loc in ['Chinatown', 'Tanjong Pagar']:
input_area.append('D02')
elif input_loc in ['Alexandra', 'Queenstown', 'Tiong Bahru']:
input_area.append('D03')
elif input_loc in ['Harbourfront', 'Telok Blangah', 'Mount Faber']:
input_area.append('D04')
elif input_loc in ['Buona Vista', 'Pasir Panjang', 'Clementi']:
input_area.append('D05')
elif input_loc in ['City Hall', 'Clarke Quay']:
input_area.append('D06')
elif input_loc in ['Beach Road', 'Bugis', 'Golden Mile']:
input_area.append('D07')
elif input_loc in ['Farrer Park', 'Little India']:
input_area.append('D08')
elif input_loc in ['Orchard', 'River Valley']:
input_area.append('D09')
elif input_loc in ['Balmoral', 'Holland', 'Bukit Timah']:
input_area.append('D10')
elif input_loc in ['Newton', 'Novena', 'Thomson']:
input_area.append('D11')
elif input_loc in ['Balestier', 'Toa Payoh', 'Serangoon']:
input_area.append('D12')
elif input_loc in ['Macpherson', 'Braddell']:
input_area.append('D13')
elif input_loc in ['Sims', 'Geylang', 'Paya Lebar']:
input_area.append('D14')
elif input_loc in ['Joo Chiat', 'Marine Parade', 'Katong']:
input_area.append('D15')
elif input_loc in ['Bedok', 'Upper East Coast', 'Siglap']:
input_area.append('D16')
elif input_loc in ['Flora', 'Changi', 'Loyang']:
input_area.append('D17')
elif input_loc in ['Pasir Ris', 'Tampines']:
input_area.append('D18')
elif input_loc in ['Serangoon Gardens', 'Punggol', 'Sengkang']:
input_area.append('D19')
elif input_loc in ['Ang Mo Kio', 'Bishan', 'Thomson']:
input_area.append('D20')
elif input_loc in ['Clementi Park', 'Upper Bukit Timah', 'Ulu Pandan']:
input_area.append('D21')
elif input_loc in ['Boon Lay', 'Jurong', 'Tuas']:
input_area.append('D22')
elif input_loc in [
'Dairy Farm', 'Bukit Panjang', 'Choa Chu Kang', 'Hillview',
'Bukit Batok'
]:
input_area.append('D23')
elif input_loc in ['Lim Chu Kang', 'Tengah', 'Kranji']:
input_area.append('D24')
elif input_loc in ['Admiralty', 'Woodlands']:
input_area.append('D25')
elif input_loc in ['Mandai', 'Upper Thomson']:
input_area.append('D26')
elif input_loc in ['Sembawang', 'Yishun']:
input_area.append('D27')
elif input_loc in ['Seletar', 'Yio Chu Kang']:
input_area.append('D28')
print(input_area)
input_type = [
'condo'
] # HDB, condo, landed (only single choice is supported in propertyguru)
input_minsize = [str(input_size * 0.8)] # square feet @ modified
input_maxsize = [str(input_size * 1.2)] # square feet @ modified
input_minprice = [str(input_price * 0.5)] # $ @ modified
input_maxprice = [str(input_price * 1.5)] # $ @ modified
input_bed = [str(input_bed)] # 0 to 5 bedroom, 0 stands for studio, @
input_floor = [
str(input_floor)
] # ground, low, mid, high, penthouse (only single choice is supported in propertyguru @
# url transfer
def url_area():
url_area = ''
for n in input_area:
url_area += f'district_code%5B%5D={n}&'
return url_area
def url_type():
if 'HDB' in input_type:
url_type = 'property_type=H&'
if 'condo' in input_type:
url_type = 'property_type=N&'
if 'landed' in input_type:
url_type = 'property_type=L&'
return url_type
def url_minsize():
url_minsize = ''.join(input_minsize)
return f'minsize={url_minsize}&'
def url_maxsize():
url_maxsize = ''.join(input_maxsize)
return f'maxsize={url_maxsize}&'
def url_minprice():
url_minprice = ''.join(input_minprice)
return f'minprice={url_minprice}&'
def url_maxprice():
url_maxprice = ''.join(input_maxprice)
return f'maxprice={url_maxprice}&'
def url_bed():
url_bed = ''
for n in input_bed:
url_bed += f'beds%5B%5D={n}&'
return url_bed
def url_floor():
url_floor = ''
if 'ground' in input_floor:
url_floor = 'floor_level=GND&'
if 'low' in input_floor:
url_floor = 'floor_level=LOW&'
if 'mid' in input_floor:
url_floor = 'floor_level=MID&'
if 'high' in input_floor:
url_floor = 'floor_level=HIGH&'
if 'penthouse' in input_floor:
url_floor = 'floor_level=PENT&'
return url_floor
url_main = f'https://www.propertyguru.com.sg/property-for-sale?market=residential&{url_type()}{url_area()}{url_minprice()}{url_maxprice()}{url_bed()}{url_minsize()}{url_maxsize()}{url_floor()}newProject=all'
print('main page url link: ' + url_main)
# tagui scrape
t.init()
t.url(url_main)
result = wait_for_mainpageload('//div[@class="header-wrapper"]')
if result == 0:
print(' no result found')
mail_notfound(input_email, input_name, input_loc, input_size,
input_price, input_bed, input_floor)
# restart BuyerAgent.py
python = sys.executable
os.execl(python, python, *sys.argv)
num_result = t.count('//div[@class="header-wrapper"]')
num_result_ad = num_result + 2
# num_result_ad = 6 # for test
print("num of property in this page without ad = ", num_result)
print("num of property in this page including ad = ", num_result_ad)
# load main page, get detail page url link
url = [''] * num_result_ad
for n in [x for x in range(1, num_result_ad + 1)
if x != 4 and x != 8]: # skip 4th and 8th advertisement
wait_for_pageload(
f'(//div[@class="listing-widget-new"]/div[{n}]/div[1]/div[2]/div[1]/div[1]/h3/a/@href)'
)
url[n - 1] = read_if_present(
f'(//div[@class="listing-widget-new"]/div[{n}]/div[1]/div[2]/div[1]/div[1]/h3/a/@href)'
)
print(f"{n}. url = " + url[n - 1])
# load detail page
property_title = [''] * num_result_ad
type = [''] * num_result_ad
area = [''] * num_result_ad
bedroom = [''] * num_result_ad
bathroom = [''] * num_result_ad
price = [''] * num_result_ad
total = [''] * num_result_ad
address = [''] * num_result_ad
postcode = [''] * num_result_ad
region = [''] * num_result_ad
floor = [''] * num_result_ad
furnish = [''] * num_result_ad
description = [''] * num_result_ad
feature = [''] * num_result_ad
image1 = [''] * num_result_ad
image2 = [''] * num_result_ad
image3 = [''] * num_result_ad
id = [''] * num_result_ad
pdf = [''] * num_result_ad
pdf_link = [''] * num_result_ad
for n in [x for x in range(1, num_result_ad + 1) if x != 4 and x != 8]:
t.url("https://www.propertyguru.com.sg" + url[n - 1])
wait_for_pageload('//h1[@class="h2"]')
property_title[n - 1] = read_if_present('//h1[@class="h2"]')
print(f"{n}. property_title = " + property_title[n - 1])
type[n - 1] = read_if_present(
'//*[@id="condo-profile"]/div/div/div/div/div[1]/div/div/div[1]/div/div[2]'
)
print(f"{n}. type = " + type[n - 1])
area[n - 1] = read_if_present(
'//*[@id="details"]/div/div[1]/div[2]/div[3]/div/div[2]')
print(f"{n}. area = " + area[n - 1])
bedroom[n - 1] = read_if_present(
'//*[@id="overview"]/div/div/div/section/div[1]/div[2]/div[1]/span'
)
print(f"{n}. bedroom = " + bedroom[n - 1])
bathroom[n - 1] = read_if_present(
'//*[@id="overview"]/div/div/div/section/div[1]/div[2]/div[2]/span'
)
print(f"{n}. bathroom = " + bathroom[n - 1])
total[n - 1] = read_if_present(
'//*[@id="overview"]/div/div/div/section/div[1]/div[1]/div[1]/span[2]'
)
print(f"{n}. total price = " + total[n - 1])
price[n - 1] = read_if_present(
'//*[@id="overview"]/div/div/div/section/div[1]/div[2]/div[4]/div/span[2]'
)
print(f"{n}. price = " + price[n - 1])
address[n - 1] = read_if_present(
'//*[@id="overview"]/div/div/div/section/div[1]/div[3]/div/div[2]/div[1]/span[1]'
)
print(f"{n}. address = " + address[n - 1])
postcode[n - 1] = read_if_present(
'//*[@id="overview"]/div/div/div/section/div[1]/div[3]/div/div[2]/div[1]/span[2]'
)
print(f"{n}. postalcode = " + postcode[n - 1])
region[n - 1] = read_if_present(
'//*[@id="overview"]/div/div/div/section/div[1]/div[3]/div/div[2]/div[1]/span[3]'
)
print(f"{n}. region = " + region[n - 1])
floor[n - 1] = read_if_present(
'//*[@id="details"]/div/div[1]/div[2]/div[9]/div/div[2]')
print(f"{n}. floor = " + floor[n - 1])
furnish[n - 1] = read_if_present(
'//*[@id="details"]/div/div[1]/div[2]/div[7]/div/div[2]')
print(f"{n}. furnish = " + furnish[n - 1])
description[n - 1] = read_if_present('//*[@id="details"]/div/div[2]')
print(f"{n}. description = " + description[n - 1])
feature[n - 1] = read_if_present('//*[@id="facilities"]')
print(f"{n}. feature = " + feature[n - 1])
image1[n - 1] = read_if_present(
'//*[@id="carousel-photos"]/div[2]/div/div[1]/span/img/@src')
print(f"{n}. image1 = " + image1[n - 1])
image2[n - 1] = read_if_present(
'//*[@id="carousel-photos"]/div[2]/div/div[2]/span/img/@src')
print(f"{n}. image2 = " + image2[n - 1])
image3[n - 1] = read_if_present(
'//*[@id="carousel-photos"]/div[2]/div/div[3]/span/img/@src')
print(f"{n}. image3 = " + image3[n - 1])
pdf[n - 1] = read_if_present(
'//*[@id="sticky-right-col"]/div[3]/a[2]/@href')
pdf_link[n - 1] = 'https://www.propertyguru.com.sg' + pdf[n - 1]
print(f"{n}. pdf_link = " + pdf_link[n - 1])
id[n - 1] = read_if_present(
'//*[@id="details"]/div/div[1]/div[2]/div[10]/div/div[2]')
print(f"{n}. id = " + id[n - 1])
property_info = {
'property_title': property_title,
'url': ['https://www.propertyguru.com.sg' + x for x in url],
'type': type,
'area': area,
'total price': total,
'price': price,
'bedroom': bedroom,
'bathroom': bathroom,
'address': address,
'postcode': postcode,
'region': region,
'floor': floor,
'furnish': furnish,
'description': description,
'feature': feature,
'image1': image1,
'image2': image2,
'image3': image3,
'id': id,
'pdf_link': pdf_link,
}
df = DataFrame(property_info,
columns=[
'property_title', 'id', 'pdf_link', 'type', 'area',
'total price', 'price', 'bedroom', 'bathroom',
'address', 'postcode', 'region', 'floor', 'furnish',
'description', 'feature', 'url', 'image1', 'image2',
'image3'
])
df.to_excel('property_info.xlsx', encoding='utf8', index=None)
print('======== property_info.xlsx saved ==========')
# from propertySearcher_util import download_image
download_image(id, image1, image2, image3)
# from propertySearcher_util import classify_image
filtered_id, filtered_cluster = classify_image(df, prefer1, prefer2,
prefer3)
print(df)
# generate image filtered df, sorted by filtered_id
filtered_df = df[df['id'].isin(filtered_id)]
# write image cluster column into df
filtered_df['image'] = filtered_cluster
print(filtered_df)
# save to excel
filtered_df.to_excel('property_info_image.xlsx',
encoding='utf8',
index=None)
print('======== generate data for pdf downloader ==========')
property_title = filtered_df[
'property_title'] # filtered_df = pd.read_excel('property_info_filtered.xlsx')
print(list(property_title))
pdf_link = filtered_df['pdf_link']
print(list(pdf_link))
pdf_id = filtered_df['id']
print(list(pdf_id))
# from propertySearcher_util import download_pdf
pdf_filename = download_pdf(
property_title, pdf_link, pdf_id
) # pdf_filename = property_title + pdf_id, pdf_filename for email attachment
# from propertySearcher_util import classify_text
features_selected = classify_text(filtered_df, 3, 6)
# edit dataframe
filtered_df['Key Features'] = features_selected
filtered_df = filtered_df.drop(columns=[
'pdf_link', 'description', 'feature', 'image1', 'image2', 'image3'
])
# save to excel
filtered_df.to_excel('Property_info_text.xlsx',
encoding='utf8',
index=None)
# from propertySearcher_util import edit_excel
edit_excel('Property_info_text.xlsx')
print('============ excel saved ============')
# from propertySearcher_util import mail_shortlist
mail_shortlist(input_email, input_name, pdf_filename)
def url2png(url):
t.init()
t.url(url)
# t.type('q', 'decentralization[enter]')
t.snap('page', 'results-' + str(uuid.uuid1()) + '.png')
t.close()
def get_shoe(shoe, gender, email):
t.init(visual_automation=True)
t.url("https://www.farfetch.com/sg/")
details = []
if gender == ' men':
t.click('(//span[@class="tabs__span"])[.="Men"]')
t.type('//input[@class="js-searchboxABTest force-ltr"]',
shoe + " Shoes")
t.click('//form[@class="ff-search"]/button')
t.wait(3)
count = t.count('(//li[@data-test="productCard"])')
if count != 0:
for i in range(1, min(count, 4)):
name = t.read(
f'(//li[@data-test="productCard"])[{i}]//div[@data-test="information"]/p'
)
price = t.read(
f'(//li[@data-test="productCard"])[{i}]//div[@data-test="information"]/div'
).replace('$', '')
if 'Off' in price:
price = price.split('Off')[1]
img = t.read(
f'(//li[@data-test="productCard"])[{i}]//img/@src')
link = "https://www.farfetch.com" + t.read(
f'(//li[@data-test="productCard"])[{i}]/a/@href')
details.append({
"email": email,
"name": name,
"price": price,
"img": img,
"Company": "Farfetch",
"link": link
})
# print(f"name: {name}, price: {price} img_source = {img}")
else:
details.append({
"email": email,
"name": "NA",
"price": "NA",
"img": "NA",
"Company": "Farfetch",
"link": "NA"
})
elif gender == ' women':
t.click('(//span[@class="tabs__span"])[.="Women"]')
t.type('//input[@class="js-searchboxABTest force-ltr"]',
shoe + " Shoes")
t.click('//form[@class="ff-search"]/button')
t.wait(3)
count = t.count('(//li[@data-test="productCard"])')
if count != 0:
for i in range(1, min(count, 4)):
name = t.read(
f'(//li[@data-test="productCard"])[{i}]//div[@data-test="information"]/p'
)
price = t.read(
f'(//li[@data-test="productCard"])[{i}]//div[@data-test="information"]/div'
).replace('$', '')
if 'Off' in price:
price = price.split('Off')[1]
img = t.read(
f'(//li[@data-test="productCard"])[{i}]//img/@src')
link = "https://www.farfetch.com" + t.read(
f'(//li[@data-test="productCard"])[{i}]/a/@href')
details.append({
"email": email,
"name": name,
"price": price,
"img": img,
"Company": "Farfetch",
"link": link
})
# print(f"name: {name}, price: {price} img_source = {img}")
else:
details.append({
"email": email,
"name": "NA",
"price": "NA",
"img": "NA",
"Company": "Farfetch",
"link": "NA"
})
else:
t.type('//input[@class="js-searchboxABTest force-ltr"]',
shoe + " Shoes")
t.click('//form[@class="ff-search"]/button')
t.wait(3)
count = t.count('(//li[@data-test="productCard"])')
if count != 0:
for i in range(1, min(count, 4)):
name = t.read(
f'(//li[@data-test="productCard"])[{i}]//div[@data-test="information"]/p'
)
price = t.read(
f'(//li[@data-test="productCard"])[{i}]//div[@data-test="information"]/div'
).replace('$', '')
if 'Off' in price:
price = price.split('Off')[1]
img = t.read(
f'(//li[@data-test="productCard"])[{i}]//img/@src')
link = "https://www.farfetch.com" + t.read(
f'(//li[@data-test="productCard"])[{i}]/a/@href')
details.append({
"email": email,
"name": name,
"price": price,
"img": img,
"Company": "Farfetch",
"link": link
})
# print(f"name: {name}, price: {price} img_source = {img}")
else:
details.append({
"email": email,
"name": "NA",
"price": "NA",
"img": "NA",
"Company": "Farfetch",
"link": "NA"
})
t.close()
return details