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all_funcs.py

@@ -0,0 +1,373 @@
+import validators
+from selectorlib import Extractor
+import requests 
+import json 
+import time
+import csv
+from dateutil.parser import parse
+import sys, os
+import re
+from datetime import date, datetime
+import numpy as np
+import math
+import concurrent.futures
+import boto3
+import botocore 
+from io import StringIO
+import pandas as pd
+import streamlit as st
+import streamlit.components.v1 as components
+import base64
+import uuid
+#import pyperclip
+#from IPython.core.display import HTML
+from bokeh.plotting import figure
+import plotly.express as px
+import plotly.graph_objects as go
+
+
+# In[2]:
+
+
+AWS_ACCESS_KEY_ID = 'AKIA4WLULVFKDGROP37L'
+AWS_SECRET_ACCESS_KEY = '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'
+
+s3 = boto3.client("s3", 
+                  region_name='ap-south-1', 
+                  aws_access_key_id=AWS_ACCESS_KEY_ID, 
+                  aws_secret_access_key=AWS_SECRET_ACCESS_KEY)
+
+res = boto3.resource("s3",
+                     region_name='ap-south-1',
+                     aws_access_key_id=AWS_ACCESS_KEY_ID,
+                     aws_secret_access_key=AWS_SECRET_ACCESS_KEY)
+def getrate(df):
+    ind_time_diff = []
+    ind_rating = []
+    ind_helped = []
+    count_of_day = 0
+    count_of_five_star = 0
+    
+    #print(min(df['date']))
+    
+    df['date'] = pd.to_datetime(df.date, infer_datetime_format = True)
+    df['date'] = df['date'].apply(lambda x: pd.Timestamp(x).strftime('%Y-%m-%d'))
+    df.sort_values(by = 'date', inplace = True, ascending=True)
+    #df.to_csv('data.csv', index=False)
+    df = df.query('verified == 1')
+    df_len = len(df)
+    d0 = parse(min(df['date']))
+    d1 = parse(max(df['date']))
+    today = parse(date.today().strftime("%Y-%m-%d"))
+    for i in df["date"].values:
+        ind_time_diff.append((today-parse(i)).days)
+    for i in ind_time_diff:
+        if i <=100:
+            count_of_day+=1
+    #print(count_of_day)
+    ind_hun_days = ind_time_diff[len(ind_time_diff)-count_of_day:]
+    for i in range(0, len(df['rating'].values)):
+        if df['rating'].values[i] == None or df['rating'].values[i] == "" or df['rating'].values[i] == "None":
+            ind_rating.append(0)
+        else:  
+            ind_rating.append(float(df['rating'].values[i])/5)
+    ind_rating_count_of_day = [i*5 for i in ind_rating[len(ind_time_diff)-count_of_day:]]
+    for i in ind_rating_count_of_day:
+        if i == 5:
+            count_of_five_star += 1
+    ind_verified = df['verified'].values
+    for i in range(0, len(df['helped'].values)):
+        if df['helped'].values[i] == None:
+            ind_helped.append(1)
+        else:
+            if str(df['helped'].values[i]).isdigit() == True:
+                ind_helped.append(int(df['helped'].values[i]) + 1)
+            else:
+                df['helped'].values[i] = df['helped'].values[i].split(",")
+                df['helped'].values[i] = "".join(df['helped'].values[i])
+                ind_helped.append(int(df['helped'].values[i]) + 1)
+        
+    deltaT = abs((d1-d0).days)
+    if deltaT == 0:
+        deltaT = 1
+    #print(deltaT)
+    rate = (df_len/deltaT)
+    #revenue = rate * int(p[1])
+    #print(df_len)
+    """print(df['date'])
+    print(d0, d1, deltaT)
+    print(int(p[1]))
+    print(revenue)"""
+
+    return df_len, deltaT, rate, ind_time_diff, ind_rating, ind_verified, ind_helped, count_of_day, count_of_five_star, ind_hun_days
+#p = ["", "1"]
+#df_len, deltaT, rate, revenue = getrate(p)
+
+
+# In[4]:
+
+
+def recordlinks(name, df_len, deltaT, rate, url):
+    to_insert = {
+        'product': name,
+        'num_reviews': df_len,
+        'deltaT': deltaT,
+        'rate': rate,
+        'url': url,
+        }
+    df = pd.read_csv('datalist.csv')
+    with open('datalist.csv', 'a', newline="") as savefile:
+        writer = csv.DictWriter(savefile, fieldnames=["product", 'num_reviews', "deltaT", "rate", "url"])
+        writer.writerow(to_insert)
+    print("Saved Data!")
+
+
+# In[5]:
+
+
+def scrape(url, e):    
+    headers = {
+        'authority': 'www.amazon.in',
+        'pragma': 'no-cache',
+        'cache-control': 'no-cache',
+        'dnt': '1',
+        'upgrade-insecure-requests': '1',
+        'user-agent': 'Mozilla/5.0 (X11; CrOS x86_64 8172.45.0) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/51.0.2704.64 Safari/537.36',
+        'accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,image/apng,*/*;q=0.8,application/signed-exchange;v=b3;q=0.9',
+        'sec-fetch-site': 'none',
+        'sec-fetch-mode': 'navigate',
+        'sec-fetch-dest': 'document',
+        'accept-language': 'en-GB,en-US,en-IN;q=0.9,en;q=0.8',
+    }
+
+    r = requests.get(url, headers=headers)
+    if r.status_code > 500:
+        if "To discuss automated access to Amazon data please contact" in r.text:
+            print("Page %s was blocked by Amazon. Please try using better proxies %d\n"%(url, r.status_code))
+        else:
+            print("Page %s must have been blocked by Amazon as the status code was %d"%(url,r.status_code))
+        return None
+    #print(e.extract(r.text)["product_title"])
+    return e.extract(r.text)
+
+
+# In[6]:
+
+
+def finding_data(data, url):
+    
+    if data:
+        for r in data['reviews']:
+            if r["title"] == None:
+                r["title"] = "None"
+            r["product"] = data["product_title"]
+            r['url'] = url
+            try:
+                r['rating'] = r['rating'].split(' out of')[0]
+            except:
+                r['rating'] = "None"
+            
+            date_posted = r['date'].split('on ')[-1]
+            r['date'] = parse(date_posted).strftime('%m-%d-%Y')
+            if r['helped'] != None:
+                r['helped'] = r['helped'].split(" ")[0]
+                if r['helped'] == "One":
+                    r['helped'] = "1"
+            else:
+                r['helped'] = 0
+            if r['verified'] != None:
+                r['verified'] = r['verified'].split(" ")[0]
+                if r['verified'] == "Verified":
+                    r['verified'] = "1"
+            else:
+                r['verified'] = "0"
+            
+                
+        
+    #print(data)
+    return data
+            
+# In[7]:
+
+# In[8]:
+
+
+def get_nextpage(data):
+    return "https://www.amazon.in"+data["next_page"]
+
+
+# In[9]:
+
+
+def clear_none():
+    #df = pd.read_csv('datalist.csv')
+    #df.dropna(axis="rows", how="any", inplace = True)
+    #df.to_csv('datalist.csv', index=False)
+    with open('data.csv', 'w+', encoding="utf-8", errors="ignore") as outfile:
+        writer = csv.DictWriter(outfile, fieldnames=["title","content","date", "author","rating","product","url", "verified", "helped"])
+        writer.writeheader()
+    outfile.close()
+#clear_none()
+
+
+# In[27]:
+
+
+def get_details(link):
+    weight = 0
+    count = 0
+    details = scrape(link, price_e)
+    while details['amazon_given_rating'] == None and count < 15:
+        details = scrape(link, price_e)
+        print("count: " + str(count))
+        count += 1
+
+    if details["price"] == None:
+        details["price"] = ["", "1"]
+    else:
+        if "x" in details["price"]:
+            details["price"] = details["price"].split("\xa0")
+            details["price"][1] = details["price"][1].split(",")
+            details["price"][1] = ["".join(details["price"][1])]
+            details["price"][1] = details["price"][1][0].split(".")[0]
+        else:
+            details["price"] = list(details["price"])
+            details["price"].pop(0)
+            details["price"] = "".join(details["price"])
+            #print(details["price"])
+    
+    if details["amazon_given_rating"] == None:
+        amazon_rating = "-"
+    else:
+        amazon_rating = details["amazon_given_rating"].split(" out")[0]
+        
+    if (details['info'] == None) and (details['info2'] != None):
+        details['info'] = details['info2']
+        details['info2'] = None
+        
+    if details['info'] != None:
+        info = details['info']
+        #weight = info.split("Weight ")[1][0]
+    print(amazon_rating)
+    print(details)
+
+    
+    
+        
+    
+    return details["price"], amazon_rating
+
+
+# In[28]:
+
+
+def relative_rates(timediff, allrating, allverified, all_helped):
+    sum_list = []
+    temp_arr = []
+    for i in range(0, len(all_helped)):
+        temp_arr.append(max(all_helped[i]))
+    norm_fact = max(temp_arr)
+    #print(temp_arr)
+    
+    for i in range(0, len(timediff)):
+        for j in range(0, len(timediff[i])):
+            if int(allverified[i][j]) != 1:
+                timediff[i][j] = round((np.exp(-(timediff[i][j]**(1/4))) * allrating[i][j] * (all_helped[i][j]/norm_fact) * 0.1), 5)
+            else:
+                timediff[i][j] = round((np.exp(-(timediff[i][j]**(1/4))) * allrating[i][j] * (all_helped[i][j]/norm_fact)), 5)
+    for i in range(0, len(timediff)):
+        sum_list.append(round(sum(timediff[i]), 5))
+    return sum_list
+
+
+# In[29]:
+
+# In[30]:
+
+
+def find_all_links(link, num):
+    link = link.split("?")
+    all_links = []
+    num_pages = math.ceil(int(num)/10)
+    for page in range(0, num_pages):
+        link[1] = "pageNumber=" + str(page+1)
+        temp_data = {"next_page": "?".join(link)}
+        finallink = get_nextpage(temp_data)
+        all_links.append(finallink)
+    return all_links
+        
+
+
+# In[31]:
+
+
+def upload(res, asin, file_name):
+    file_name = asin + ".csv"
+    bucket = "productreviewsdata"
+    res.Bucket(bucket).upload_file("data.csv", "alldata/"+file_name)
+
+
+# In[32]:
+
+
+def find_asin(link):
+    link = link.split("/")
+    for i in range(0, len(link)):
+        if link[i] == "product-reviews":
+            asin = link[i+1]
+        if link[i] == "dp":
+            asin=link[i+1][0:10]
+        if link[i] == "product":
+            asin=link[i+1][0:10]
+    return asin
+
+
+# In[33]:
+
+
+def get_total_reviews(data):
+    data['total_reviews'] = data['total_reviews'].split("| ")
+    data['total_reviews'] = data['total_reviews'][1].split(" ")[0].split(",")
+    data["total_reviews"] = int(''.join(data["total_reviews"]))
+    return data["total_reviews"]
+
+def myFunc(e):
+    return e["Our Rating"]
+def list_down():
+    all_the_asin = []
+    for l in range(0, len(st.session_state.linksFinal)):
+        col1, col2= st.columns([2, 0.5])
+        exp = col1.expander(st.session_state.linksFinal[l].split("/ref")[0])
+        col2.button("X", key=str(l))
+        ASIN = find_asin(st.session_state.linksFinal[l])
+        all_the_asin.append(ASIN)
+        the_link = """https://ws-in.amazon-adsystem.com/widgets/q?ServiceVersion=20070822&OneJS=1&Operation=GetAdHtml&MarketPlace=IN&source=ss&ref=as_ss_li_til&ad_type=product_link&tracking_id=universalcont-21&language=en_IN&marketplace=amazon&region=IN&placement="""+ASIN+"""&asins="""+ASIN+"""&show_border=true&link_opens_in_new_window=true"""
+        with exp:
+            components.iframe(the_link, height=240, width=120)
+    
+    
+          
+    #print(globals()["col"])
+    #print(globals()["col_an"])
+    #for n, val in enumerate(st.session_state["final"]):
+     #   globals()["var%d"%n] = val
+
+def create_vars(func_col):
+    for n, val in enumerate(func_col):
+        globals()["var%d"%n] = val
+    for n in range(0, len(func_col)):
+        with globals()["var"+str(n)]:
+            try:
+                ASIN = find_asin(st.session_state.linksFinal[n])
+                the_link = """https://ws-in.amazon-adsystem.com/widgets/q?ServiceVersion=20070822&OneJS=1&Operation=GetAdHtml&MarketPlace=IN&source=ss&ref=as_ss_li_til&ad_type=product_link&tracking_id=universalcont-21&language=en_IN&marketplace=amazon&region=IN&placement="""+ASIN+"""&asins="""+ASIN+"""&show_border=true&link_opens_in_new_window=true"""
+                components.iframe(the_link, height=240, width=120)
+                st.button("X", key=str(n))
+            except Exception as e:
+                 st.write(e)
+def create_graph(fig, df):
+    df['date'] = pd.to_datetime(df.date, infer_datetime_format = True)
+    df['date'] = df['date'].apply(lambda x: pd.Timestamp(x).strftime('%Y-%m-%d'))
+    df.sort_values(by = 'date', inplace = True, ascending=True)
+    y_data = [i+1 for i in range(0, len(df))]
+    fig.add_trace(go.Scatter(x=df["date"], y=y_data, name=list(set(df["product"]))[0][0:20]+"..."))
+    return fig

app.py

@@ -0,0 +1,153 @@
+import streamlit as st
+import uuid
+import boto3
+import botocore
+import streamlit.components.v1 as components
+from streamlit_autorefresh import st_autorefresh
+import requests
+from all_funcs import *
+from create_table import *
+AWS_ACCESS_KEY_ID = 'AKIA4WLULVFKDGROP37L'
+AWS_SECRET_ACCESS_KEY = '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'
+
+s3 = boto3.client("s3", 
+                  region_name='ap-south-1', 
+                  aws_access_key_id=AWS_ACCESS_KEY_ID, 
+                  aws_secret_access_key=AWS_SECRET_ACCESS_KEY)
+
+res = boto3.resource("s3",
+                     region_name='ap-south-1',
+                     aws_access_key_id=AWS_ACCESS_KEY_ID,
+                     aws_secret_access_key=AWS_SECRET_ACCESS_KEY)
+st.markdown("""
+<style>
+#MainMenu{visibility: hidden;} 
+td.css-57lzw8:nth-of-type(4){}
+footer, label.css-zyb2jl, img.css-1jhkrss, button.css-bl767a {visibility: hidden;}
+.copy-button{color:red;}
+
+</style>
+
+""", unsafe_allow_html=True)
+
+if "iden" not in st.session_state:
+    st.session_state["iden"] = None
+    st.session_state["sesInBucket"] = None
+    st.session_state['dataInBucket'] = None
+    st.session_state['linksFinal'] = []
+    st.session_state['editLinks'] = []
+    st.session_state['chosen'] = ""
+    st.session_state["refresh"] = ""
+    
+id_place_con = st.sidebar.container()
+    
+def from_session():
+    already_in_body = st.session_state.dataInBucket
+    sessions_here = already_in_body.split(",")
+    a = []
+    indices = [("Comparison "+ str(num)) for num in range(1, len(sessions_here)+1)]
+    comparison_data_con = st.sidebar.container()
+    with comparison_data_con:
+        chosen = st.selectbox("Choose Session:", indices)
+        a = list(set(sessions_here[indices.index(chosen)].split("\n")))
+        a.remove("")
+        if st.session_state["refresh"] == True:
+                st.session_state.linksFinal = []
+        if chosen != st.session_state.chosen:
+            st.session_state.chosen = chosen
+            st.session_state["a"] = a
+            st.session_state["linksFinal"] = a
+    return sessions_here
+
+def main():
+    #if "hey" not in st.session_state:
+    count = st_autorefresh(interval=1, limit=2, key="hey")
+    #st.write(st.session_state)
+    id_place_con.text("Comparison ID:")
+    id_place_con.code(st.session_state.iden.replace(".txt", ""))
+    id_place_con.download_button("Download ID", st.session_state.iden.replace(".txt", ""), file_name="Session ID.txt")
+    id_place_con.warning("Keep Comparison ID to access and save your comparisons.")
+    id_place_con.markdown("<hr>", unsafe_allow_html=True)
+    if st.session_state.sesInBucket==True:
+        sessions_here = from_session()
+    else:
+        sessions_here = []
+    #st.write(st.session_state.linksFinal)
+    if len(st.session_state) > 1:
+        for k in st.session_state:
+            if st.session_state[k] == True and k.isdigit():
+                st.session_state["linksFinal"].pop(int(k))
+    
+    with st.sidebar.form(key='my_form'):
+        placeholder = st.empty()
+        s = placeholder.text_input(label='Enter URL')
+        submit = st.form_submit_button(label='Submit')
+        if submit:
+            try:
+                check_paste = requests.get(s)
+                if s in st.session_state["linksFinal"] or s.find("amazon.in") == -1:
+                    pass
+                else:
+                    st.session_state["linksFinal"].append(s)
+                
+            except:
+                st.error('Not a valid URL')
+    conf1, refre1 = st.sidebar.columns([1, 1])
+    confirm = conf1.button("Compare")
+    refresh = refre1.button("Empty List", key="refresh")
+    if refresh:
+        st.session_state.linksFinal = []
+
+    if len(st.session_state.linksFinal) == 0:
+            pass
+    else: 
+        exp=st.expander("Expand", expanded=True)
+        with exp:
+            create_vars(st.columns(len(st.session_state.linksFinal)))
+    if confirm:
+        string = create_table(st.session_state.linksFinal)
+        save_data_in_session(string, st.session_state.sesInBucket, sessions_here)
+        #count = st_autorefresh(interval=1, limit=2)
+if st.session_state.iden != None:
+    main()
+    
+else:
+    enter_it = st.sidebar.container()
+    lol2 = st.sidebar.container()
+    create_it = st.sidebar.container()
+    with enter_it:
+        textPlace = st.empty()
+        produce_error = st.empty()
+        enter_uni_id = textPlace.text_input("Enter Comparison ID if you have one:")
+        if enter_uni_id == "":
+            pass
+        else:
+            try:
+                check_iden = s3.get_object(Bucket="productreviewsdata", Key="sessions/"+enter_uni_id+".txt")
+                st.session_state.iden = enter_uni_id + ".txt"
+                st.session_state.sesInBucket = True
+                st.session_state.dataInBucket = already_in_body = check_iden["Body"].read().decode()
+                textPlace.empty()
+                produce_error.empty()
+            except Exception as e:
+                produce_error.error("Comparison ID not found!")
+            
+    with lol2:
+        or_thing = st.empty()
+        or_thing.write("OR")
+    with create_it:
+        create_it_button = st.empty()
+        thing = create_it_button.button("Create Comparison ID")
+        if thing == True:
+            iden = str(uuid.uuid4())
+            st.session_state["iden"] = iden + ".txt"
+            st.session_state.sesInBucket = False
+    if st.session_state.iden != None:
+        textPlace.empty()
+        or_thing.empty()
+        create_it_button.empty()
+        produce_error.empty()
+        main()
+            
+
+    

create_table.py

@@ -0,0 +1,206 @@
+import validators
+from selectorlib import Extractor
+import requests 
+import json 
+import time
+import csv
+from dateutil.parser import parse
+import sys, os
+import re
+from datetime import date, datetime
+import numpy as np
+import math
+import concurrent.futures
+import boto3
+import botocore 
+from io import StringIO
+import pandas as pd
+import streamlit as st
+import streamlit.components.v1 as components
+import base64
+import uuid
+#import pyperclip
+#from IPython.core.display import HTML
+from bokeh.plotting import figure
+import plotly.express as px
+import plotly.graph_objects as go
+from all_funcs import *
+
+
+def create_table(theurls):
+    e = Extractor.from_yaml_file('selectors.yml')
+    all_five_star = []
+    all_time_diff = []
+    all_hun_days = []
+    all_rating = []
+    all_verified = []
+    all_helped = []
+    urls_used = []
+    product_names = []
+    all_reviews = []
+    all_amazon_ratings = []
+    all_count_of_day = []
+    string = ""
+    fig = go.Figure()
+    prime = False
+    today = parse(date.today().strftime("%Y-%m-%d"))
+    url_dataframe = pd.DataFrame()
+    
+    spin = st.empty()
+    stat = st.empty()
+    print(theurls)
+    for i in theurls:
+        try:
+            asin = find_asin(i)
+            print(asin)
+            if len(asin) != 10:
+                raise ValueError
+        except:
+            st.error("ASIN NUMBER NOT FOUND IN URL! PLEASE CHECK FORMAT OF URL")
+            prime = False
+            break
+        file_name = asin+'.csv'
+        print(file_name)
+        try:
+            df = s3.get_object(Bucket='productreviewsdata', Key="alldata/"+file_name) 
+            body = df["Body"].read().decode('utf-8')
+            df_data = pd.read_csv(StringIO(body))
+            try:
+                title = list(set(df_data["product"]))[0]
+                print(list(set(df_data["title"])))
+                if list(set(df_data["title"]))[0] == "-":
+                    st.error(title + " has 0 reviews. Please remove it from your list and try again!")
+                    break
+                    
+            except IndexError:
+                string = string + "https://www.amazon.in/product-reviews/"+asin+"\n"
+                break
+            stat.info("Getting " + title + "....")
+            product_names.append(title)
+            try:
+                all_amazon_ratings.append(str(list(set(df_data["amazon_rating"]))[0]))
+            except:
+                all_amazon_ratings.append("-")
+            urls_used.append(list(set(df_data["url"]))[0])
+            string = string+list(set(df_data["url"]))[0]+"\n"
+            #st.write(df_data)
+            if len(df_data)==0:
+                pass
+                    #string = string + "https://www.amazon.in/product-reviews/"+asin+"\n"
+                    #st.write(string)
+            else:
+                fig = create_graph(fig, df_data)
+                df_len, deltaT, rate, ind_time_diff, ind_rating, ind_verified, ind_helped, count_of_day, count_of_five_star, ind_hun_days = getrate(df_data)
+                #print(df_len)
+                all_reviews.append(str(df_len))
+                all_time_diff.append(ind_time_diff)
+                all_rating.append(ind_rating)
+                all_verified.append(ind_verified)
+                all_helped.append(ind_helped)
+                all_count_of_day.append(count_of_day)
+                all_five_star.append(count_of_five_star)
+                all_hun_days.append(ind_hun_days)
+                prime=True
+                
+        except botocore.exceptions.ClientError:
+            st.info("Request sent for " + asin)
+            create_df = pd.DataFrame({"title":[], "content": [], 'date':[], "author": [], "rating":[], "product":[], "url":[], "verified":[], "helped": [], "amazon_rating": []})
+            bucket = 'productreviewsdata'
+            csv_buffer = StringIO()
+            create_df.to_csv(csv_buffer, index=False)
+            res.Object(bucket, 'alldata/'+asin+'.csv').put(Body=csv_buffer.getvalue())
+            string = string + "https://www.amazon.in/product-reviews/"+asin+"\n"
+            prime=False
+    dataf = pd.DataFrame({'Product': [],
+                          'Our Rating': [],
+                          'Total Verified Purchases': [],
+                          'No. of Verified Purchases in last 100 days':[],
+                          'No. of Verified Purchases that have 5 stars in the last 100 days':[],
+                          'Amazon Rating': [],
+                          'URL': []})
+        
+    if prime and len(all_time_diff) == len(st.session_state["linksFinal"]):
+        fig.update_layout(
+            title="Graph of reviews",
+            xaxis_title="Date",
+            yaxis_title="No. of Reviews",
+            legend_title="Products",
+            font=dict(
+                family="Courier New, monospace",
+                color="black"))
+        rates = relative_rates(all_time_diff, all_rating, all_verified, all_helped)
+        for record in range(0, len(urls_used)):
+            #dataf.append([product_names[record], all_reviews[record], rates[record], all_amazon_ratings[record]])
+            
+            to_insert = {
+                        'Product': product_names[record][:70]+"...",
+                        'Our Rating': rates[record],
+                        'Total Verified Purchases': all_reviews[record],
+                        'No. of Verified Purchases in last 100 days': str(all_count_of_day[record]),
+                        'No. of Verified Purchases that have 5 stars in the last 100 days': str(all_five_star[record]),
+                        'Amazon Rating': all_amazon_ratings[record],
+                        'URL': urls_used[record]
+                        }
+            dataf = dataf.append(to_insert, ignore_index=True)
+        dataf = dataf.sort_values(by=['Our Rating'], ascending=False)
+        dataf.set_index('Product', inplace=True)
+        stat.empty()
+        #st.table(dataf.style.format({"Total Reviews": "{:.0f}"}))
+        
+        st.table(dataf)
+        st.plotly_chart(fig)
+        #st.dataframe(dataf)
+    else:
+        stat.empty()
+        #reqs_spin.empty()
+        spin.info("Your request is being processed...")
+        
+        time.sleep(10)
+    #st.write(string)
+    return string
+
+def save_data_in_session(string, prime_session, sessions_here):
+    if prime_session ==True:
+        s_check = string.split("\n")
+        try:
+            while True:
+                s_check.remove("")
+        except ValueError:
+            pass
+        print("THIS")
+        print(s_check)
+        if len(s_check) != len(st.session_state.linksFinal):
+            pass
+        else:
+            for ses in sessions_here:
+                ses_check = ses.split("\n")
+                try:
+                    while True:
+                        ses_check.remove("")
+                except ValueError:
+                    pass
+                print("ses_check")
+                print(ses_check)
+                if set(s_check) == set(ses_check):
+                    break
+            else:
+                print("HIIIIIIIIIIIIII")
+                string = st.session_state.dataInBucket+",\n"+string
+                st.success("Session Saved")
+                res.Object('productreviewsdata', 'sessions/'+st.session_state["iden"]).put(Body=string)
+    
+    else:
+        s_check = string.split("\n")
+        try:
+            while True:
+                s_check.remove("")
+        except ValueError:
+            pass
+        if len(s_check) !=len(st.session_state.linksFinal):
+            pass
+        else:
+            st.success("Session Saved")
+            res.Object('productreviewsdata', 'sessions/'+st.session_state["iden"]).put(Body=string)
+    
+    
+    

requirements.txt

@@ -0,0 +1,7 @@
+python-dateutil
+requests
+selectorlib
+numpy
+boto3
+pandas
+streamlit