Tugba Ozkan
Reputation: 61
How to pulling actual data from multiple pages of website with using Selenium,Beautiful Soup ,Pandas?
I am new for pulling data using Python . I want to do excel file as pulling tables from website.
The website url : "https://seffaflik.epias.com.tr/transparency/piyasalar/gop/arz-talep.xhtml"
In this webpage ,there are tables at seperately pages for hours data.Due to one hour includes around 500 datas so pages are divided.
I want to pull all data for each hour.
But my mistake is pulling same table even if page changes.
I am using beautiful soup,pandas ,selenium libraries. I will show you my codes for explaning myself.
import requests
r = requests.get('https://seffaflik.epias.com.tr/transparency/piyasalar/gop/arz-talep.xhtml')
from bs4 import BeautifulSoup
source = BeautifulSoup(r.content,"lxml")
metin =source.title.get_text()
source.find("input",attrs={"id":"j_idt206:txt1"})
from selenium import webdriver
from selenium.webdriver.common.keys import Keys
import pandas as pd
tarih = source.find("input",attrs={"id":"j_idt206:date1_input"})["value"]
import datetime
import time
x = datetime.datetime.now()
today = datetime.date.today()
# print(today)
tomorrow = today + datetime.timedelta(days = 1)
tomorrow = str(tomorrow)
words = tarih.split('.')
yeni_tarih = '.'.join(reversed(words))
yeni_tarih =yeni_tarih.replace(".","-")
def tablo_cek():
tablo = source.find_all("table")#sayfadaki tablo
dfs = pd.read_html(str(tablo))#tabloyu dataframe e çekmek
dfs.append(dfs)#tabloya yeni çekilen tabloyu ekle
print(dfs)
return tablo
if tomorrow == yeni_tarih :
print(yeni_tarih == tomorrow)
driver = webdriver.Chrome("C:/Users/tugba.ozkan/AppData/Local/SeleniumBasic/chromedriver.exe")
driver.get("https://seffaflik.epias.com.tr/transparency/piyasalar/gop/arz-talep.xhtml")
time.sleep(1)
driver.find_element_by_xpath("//select/option[@value='96']").click()
time.sleep(1)
user = driver.find_element_by_name("j_idt206:txt1")
nextpage = driver.find_element_by_xpath("//a/span[@class ='ui-icon ui-icon-seek-next']")
num=0
while num < 24 :
user.send_keys(num) #saate veri gönder
driver.find_element_by_id('j_idt206:goster').click() #saati uygula
nextpage = driver.find_element_by_xpath("//a/span[@class ='ui-icon ui-icon-seek-next']")#o saatteki next page
nextpage.click() #next page e geç
user = driver.find_element_by_name("j_idt206:txt1") #tekrar getiriyor saat yerini
time.sleep(1)
tablo_cek()
num = num + 1 #saati bir arttır
user.clear() #saati sıfırla
else:
print("Güncelleme gelmedi")
In this situation :
nextpage = driver.find_element_by_xpath("//a/span[@class ='ui-icon ui-icon-seek-next']")#o saatteki next page
nextpage.click()
when python clicks the button to go to next page ,the next page show then it needs to pull next table as shown table. But it doesn't work. At the output I saw appended table that is same values.Like this : This is my output :
[ Fiyat (TL/MWh) Talep (MWh) Arz (MWh)
0 0 25.0101 19.15990
1 1 24.9741 19.16390
2 2 24.9741 19.18510
3 85 24.9741 19.18512
4 86 24.9736 19.20762
5 99 24.9736 19.20763
6 100 24.6197 19.20763
7 101 24.5697 19.20763
8 300 24.5697 19.20768
9 301 24.5697 19.20768
10 363 24.5697 19.20770
11 364 24.5497 19.20770
12 400 24.5497 19.20771
13 401 24.5297 19.20771
14 498 24.5297 19.20773
15 499 24.5297 19.36473
16 500 24.5297 19.36473
17 501 24.4097 19.36473
18 563 24.4097 19.36475
19 564 24.3897 19.36475
20 999 24.3897 19.36487
21 1000 24.3097 19.36487
22 1001 24.1897 19.36487
23 1449 24.1897 19.36499, [...]]
[ Fiyat (TL/MWh) Talep (MWh) Arz (MWh)
0 0 25.0101 19.15990
1 1 24.9741 19.16390
2 2 24.9741 19.18510
3 85 24.9741 19.18512
4 86 24.9736 19.20762
5 99 24.9736 19.20763
6 100 24.6197 19.20763
7 101 24.5697 19.20763
8 300 24.5697 19.20768
9 301 24.5697 19.20768
10 363 24.5697 19.20770
11 364 24.5497 19.20770
12 400 24.5497 19.20771
13 401 24.5297 19.20771
14 498 24.5297 19.20773
15 499 24.5297 19.36473
16 500 24.5297 19.36473
17 501 24.4097 19.36473
18 563 24.4097 19.36475
19 564 24.3897 19.36475
20 999 24.3897 19.36487
21 1000 24.3097 19.36487
22 1001 24.1897 19.36487
23 1449 24.1897 19.36499, [...]]
[ Fiyat (TL/MWh) Talep (MWh) Arz (MWh)
0 0 25.0101 19.15990
1 1 24.9741 19.16390
2 2 24.9741 19.18510
3 85 24.9741 19.18512
4 86 24.9736 19.20762
5 99 24.9736 19.20763
6 100 24.6197 19.20763
7 101 24.5697 19.20763
8 300 24.5697 19.20768
9 301 24.5697 19.20768
10 363 24.5697 19.20770
11 364 24.5497 19.20770
12 400 24.5497 19.20771
13 401 24.5297 19.20771
14 498 24.5297 19.20773
15 499 24.5297 19.36473
16 500 24.5297 19.36473
17 501 24.4097 19.36473
18 563 24.4097 19.36475
19 564 24.3897 19.36475
20 999 24.3897 19.36487
21 1000 24.3097 19.36487
22 1001 24.1897 19.36487
23 1449 24.1897 19.36499, [...]]
[ Fiyat (TL/MWh) Talep (MWh) Arz (MWh)
0 0 25.0101 19.15990
1 1 24.9741 19.16390
2 2 24.9741 19.18510
3 85 24.9741 19.18512
4 86 24.9736 19.20762
5 99 24.9736 19.20763
6 100 24.6197 19.20763
7 101 24.5697 19.20763
8 300 24.5697 19.20768
9 301 24.5697 19.20768
10 363 24.5697 19.20770
11 364 24.5497 19.20770
12 400 24.5497 19.20771
13 401 24.5297 19.20771
14 498 24.5297 19.20773
15 499 24.5297 19.36473
16 500 24.5297 19.36473
17 501 24.4097 19.36473
18 563 24.4097 19.36475
19 564 24.3897 19.36475
20 999 24.3897 19.36487
21 1000 24.3097 19.36487
22 1001 24.1897 19.36487
23 1449 24.1897 19.36499, [...]]
Upvotes: 0
Views: 122
Answers (2)
chitown88
Reputation: 28630
I will also offer up another solution as you can pull that data directly from the requests. It also gives you the option of how many to pull per page (and you can iterate through each page), however, if you set that limit high enough, you can get it all in 1 request. So there are about 400+ rows, I set the limit to 1000, then you only need page 0:
import requests
from bs4 import BeautifulSoup
import pandas as pd
url = 'https://seffaflik.epias.com.tr/transparency/piyasalar/gop/arz-talep.xhtml'
headers = {'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/88.0.4324.104 Safari/537.36'}
page = '0'
payload = {
'javax.faces.partial.ajax': 'true',
'javax.faces.source': 'j_idt206:dt',
'javax.faces.partial.execute': 'j_idt206:dt',
'javax.faces.partial.render': 'j_idt206:dt',
'j_idt206:dt': 'j_idt206:dt',
'j_idt206:dt_pagination': 'true',
'j_idt206:dt_first': page,
'j_idt206:dt_rows': '1000',
'j_idt206:dt_skipChildren': 'true',
'j_idt206:dt_encodeFeature': 'true',
'j_idt206': 'j_idt206',
'j_idt206:date1_input': '04.02.2021',
'j_idt206:txt1': '0',
'j_idt206:dt_rppDD': '1000'
}
rows = []
hours = list(range(0,24))
for hour in hours:
payload.update({'j_idt206:txt1':str(hour)})
response = requests.get(url, headers=headers, params=payload)
soup = BeautifulSoup(response.text.replace('![CDATA[',''), 'lxml')
columns = ['Fiyat (TL/MWh)', 'Talep (MWh)', 'Arz (MWh)', 'hour']
trs = soup.find_all('tr')
for row in trs:
data = row.find_all('td')
data = [x.text for x in data] + [str(hour)]
rows.append(data)
df = pd.DataFrame(rows, columns=columns)
Output:
print(df)
Fiyat (TL/MWh) Talep (MWh) Arz (MWh)
0 0,00 25.113,70 17.708,10
1 0,01 25.077,69 17.712,10
2 0,02 25.077,67 17.723,10
3 0,85 25.076,57 17.723,12
4 0,86 25.076,05 17.746,12
.. ... ... ...
448 571,01 19.317,10 29.529,60
449 571,80 19.316,86 29.529,60
450 571,90 19.316,83 29.529,70
451 571,99 19.316,80 29.529,70
452 572,00 19.316,80 29.540,70
[453 rows x 3 columns]
To find this just takes a little investigative work. If you go to Dev Tools -> Network -> XHR, you try to see if the data is somewhere embedded in those requests (see image). If you find it there, go to Headers tab and you can get the url and parameters at the bottom.
MOST cases you'll see the data is returned in a nice json format. Not the case here. It was returned in a slightly different way with xml, so need a tad extra work to pull out the tags and such. But not impossible.
Upvotes: 1
chitown88
Reputation: 28630
That's because you pull the initial html here source = BeautifulSoup(r.content,"lxml"), and then keep rendering that content.
You need to pull the html for each page that you go to. It's just a matter of adding 1 line. I commented where I added it:
import requests
r = requests.get('https://seffaflik.epias.com.tr/transparency/piyasalar/gop/arz-talep.xhtml')
from bs4 import BeautifulSoup
source = BeautifulSoup(r.content,"lxml")
metin =source.title.get_text()
source.find("input",attrs={"id":"j_idt206:txt1"})
from selenium import webdriver
from selenium.webdriver.common.keys import Keys
import pandas as pd
tarih = source.find("input",attrs={"id":"j_idt206:date1_input"})["value"]
import datetime
import time
x = datetime.datetime.now()
today = datetime.date.today()
# print(today)
tomorrow = today + datetime.timedelta(days = 1)
tomorrow = str(tomorrow)
words = tarih.split('.')
yeni_tarih = '.'.join(reversed(words))
yeni_tarih =yeni_tarih.replace(".","-")
def tablo_cek():
source = BeautifulSoup(driver.page_source,"lxml") #<-- get the current html
tablo = source.find_all("table")#sayfadaki tablo
dfs = pd.read_html(str(tablo))#tabloyu dataframe e çekmek
dfs.append(dfs)#tabloya yeni çekilen tabloyu ekle
print(dfs)
return tablo
if tomorrow == yeni_tarih :
print(yeni_tarih == tomorrow)
driver = webdriver.Chrome("C:/chromedriver_win32/chromedriver.exe")
driver.get("https://seffaflik.epias.com.tr/transparency/piyasalar/gop/arz-talep.xhtml")
time.sleep(1)
driver.find_element_by_xpath("//select/option[@value='96']").click()
time.sleep(1)
user = driver.find_element_by_name("j_idt206:txt1")
nextpage = driver.find_element_by_xpath("//a/span[@class ='ui-icon ui-icon-seek-next']")
num=0
tablo_cek() #<-- need to get that data before moving to next page
while num < 24 :
user.send_keys(num) #saate veri gönder
driver.find_element_by_id('j_idt206:goster').click() #saati uygula
nextpage = driver.find_element_by_xpath("//a/span[@class ='ui-icon ui-icon-seek-next']")#o saatteki next page
nextpage.click() #next page e geç
user = driver.find_element_by_name("j_idt206:txt1") #tekrar getiriyor saat yerini
time.sleep(1)
tablo_cek()
num = num + 1 #saati bir arttır
user.clear() #saati sıfırla
else:
print("Güncelleme gelmedi")
Output:
True
[ Fiyat (TL/MWh) Talep (MWh) Arz (MWh)
0 0 25.11370 17.70810
1 1 25.07769 17.71210
2 2 25.07767 17.72310
3 85 25.07657 17.72312
4 86 25.07605 17.74612
.. ... ... ...
91 10000 23.97000 17.97907
92 10001 23.91500 17.97907
93 10014 23.91500 17.97907
94 10015 23.91500 17.97907
95 10100 23.91499 17.97909
[96 rows x 3 columns], [...]]
[ Fiyat (TL/MWh) Talep (MWh) Arz (MWh)
0 10101 23.91499 18.04009
1 10440 23.91497 18.04015
2 10999 23.91493 18.04025
3 11000 23.89993 18.04025
4 11733 23.89988 18.04039
.. ... ... ...
91 23999 23.55087 19.40180
92 24000 23.55087 19.40200
93 24001 23.53867 19.40200
94 24221 23.53863 19.40200
95 24222 23.53863 19.40200
[96 rows x 3 columns], [...]]
[ Fiyat (TL/MWh) Talep (MWh) Arz (MWh)
0 24360 21.33871 19.8112
1 24499 21.33868 19.8112
2 24500 21.33868 19.8112
3 24574 21.33867 19.8112
4 24575 21.33867 19.8112
.. ... ... ...
91 29864 21.18720 20.3708
92 29899 21.18720 20.3708
93 29900 21.18720 20.3808
94 29999 21.18720 20.3808
95 30000 21.18530 20.3811
[96 rows x 3 columns], [...]]
Upvotes: 1
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