It does't seems to be working if the hashtag is not in english and hashtag without any post yet

[jamezun]

Appreciate your hardwork! I am trying to make it work but I only have limited programing skills.. I never use python before so its hard for me to figure out what the problem is.

Problems:
1] I got attribute error whenever my hashtag is non-english (e.g chinese, korean)
2] I got index error when the hashtag does not exisit or number of post is 0 (sometime you might want to test some hashtag which may turn out nobody else has used before)

Is there any way to fix it? I edited the code a bit to make it run

# coding=utf8

from selenium import webdriver
from bs4 import BeautifulSoup
import pandas as pd
import datetime


driver = webdriver.Chrome()

# Extract description of a post from Instagram link
#driver.get('https://www.instagram.com/p/BiRnjDsFKzl/')
#soup = BeautifulSoup(driver.page_source,"lxml")
#desc = " "

#for item in soup.findAll('a'):
#    desc= desc + " " + str(item.string)

# Extract tag list from Instagram post description
#taglist = desc.split()
#taglist = [x for x in taglist if x.startswith('#')]
#index = 0
#while index < len(taglist):
#    taglist[index] = taglist[index].strip('#')
#    index += 1

# (OR) Copy-paste your tag list manually here
taglist = ['korea', '데일리룩'']
print(taglist)


# Define dataframe to store hashtag information
tag_df  = pd.DataFrame(columns = ['Hashtag', 'Number of Posts', 'Posting Freq (mins)'])

# Loop over each hashtag to extract information
for tag in taglist:
    
    driver.get('https://www.instagram.com/explore/tags/'+str(tag))
    soup = BeautifulSoup(driver.page_source,"lxml")
 
    # Extract current hashtag name
    tagname = tag
    # Extract total number of posts in this hashtag
    # NOTE: Class name may change in the website code
    # Get the latest class name by inspecting web code

    try:
        nposts = soup.find('span', {'class': 'g47SY'}).text
        
    
        if nposts !='0':
         
            try: # Extract all post links from 'explore tags' page
                # Needed to extract post frequency of recent posts
                myli = []
                for a in soup.find_all('a', href=True):
                    myli.append(a['href'])

                # Keep link of only 1st and 9th most recent post 
                newmyli = [x for x in myli if x.startswith('/p/')]
                del newmyli[:9]
                del newmyli[9:]
                del newmyli[1:8]

                timediff = []

                # Extract the posting time of 1st and 9th most recent post for a tag
                for j in range(len(newmyli)):
                    driver.get('https://www.instagram.com'+str(newmyli[j]))
                    soup = BeautifulSoup(driver.page_source,"lxml")

                    for i in soup.findAll('time'):
                        if i.has_attr('datetime'):
                            timediff.append(i['datetime'])
                            #print(i['datetime'])

                # Calculate time difference between posts
                # For obtaining posting frequency
                datetimeFormat = '%Y-%m-%dT%H:%M:%S.%fZ'
                print(timediff)
                diff = datetime.datetime.strptime(timediff[0], datetimeFormat)\
                    - datetime.datetime.strptime(timediff[1], datetimeFormat)
                pfreq= int(diff.total_seconds()/(9*60))
                
                # Add hashtag info to dataframe
                tag_df.loc[len(tag_df)] = [tagname, nposts, pfreq]
            
                
             
            except IndexError:
                pfreq = 'ERROR'
                print("INDEX ERROR")
        
        else:
            pfreq = 0  
            nposts = 0   
            tag_df.loc[len(tag_df)] = [tagname, nposts, pfreq]
    
    except AttributeError: 
        
        nposts = 0
        pfreq =0    
        print("ATTRIBUTE ERROR")        
        tag_df.loc[len(tag_df)] = [tagname, nposts, pfreq]
       
        
    
driver.quit()

# Check the final dataframe
print(tag_df)

# CSV output for hashtag analysis
tag_df.to_csv('hashtag_list.csv', encoding='utf-8')