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insta.py
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from instagrapi import Client
import pymongo
from pymongo import MongoClient
import dns
import time
import datetime
from sentiment import *
client = pymongo.MongoClient("mongodb+srv://KokilaReddy:[email protected]/Sociolitic?retryWrites=true&w=majority")
db = client.Social_media_data
Instagram = db.instagram
Insta_count = db.instagram_count
Total_count = db.total_count
cl = Client()
cl.login("socio_litic", "Sociolitic")
def insta(search,amount = 200):
top_medias = cl.hashtag_medias_top(search, amount=100)
for media in top_medias:
result = media.dict()
if (db.instagram.find({"shortcode":result['code']}).count() > 0)== False:
shortcode = result['code']
postid = result['pk']
userid = result['user']['pk']
url = result['thumbnail_url']
created_at = result['taken_at']
if (result['location']!= None):
location = result['location']['name']
lat = result['location']['lat']
lng = result['location']['lng']
else:
location = None
lat = None
lng = None
comment_count = result['comment_count']
like_count = result['like_count']
user_name = result['user']['full_name']
caption_text = result['caption_text']
Sentiment = sentiment_analysis(caption_text)
insta_data = {
"publishedTime": created_at ,
"postId": postid,
"userId": userid,
"username": user_name,
"location": location,
"lat": lat,
"lng": lng,
"caption": caption_text,
"image_url": url,
"shortcode" : shortcode,
"likes": int(like_count),
"comment_count":int(comment_count),
"tag" : search,
"sentiment":Sentiment,
"createdAt": datetime.datetime.now(), "updatedAt": datetime.datetime.now()
}
if Sentiment == "Positive":
pos = 1
neg = 0
neu = 0
elif Sentiment == "Negative":
pos = 0
neg = 1
neu = 0
else:
pos = 0
neg = 0
neu = 1
Instagram.insert_one(insta_data)
count_data = {
"tag" : search,
"Total_reviews": 1,
"positive":pos,
"negative":neg,
"neutral":neu,
"createdAt": datetime.datetime.now(),
"updatedAt": datetime.datetime.now()
}
if (db.instagram_count.find({'tag':search}).count() > 0)== False:
Insta_count.insert_one(count_data)
else :
tum_cnt = db.instagram_count.find_one({'tag':search})
reviews = tum_cnt["Total_reviews"]
positive = tum_cnt["positive"]
negative = tum_cnt["negative"]
neutral = tum_cnt["neutral"]
updated_count_data ={
"$set":
{"Total_reviews": reviews+1,
"positive":positive+pos,
"negative":negative+neg,
"neutral":neutral+neu,
"updatedAt": datetime.datetime.now()
}
}
Insta_count.update_one(tum_cnt,updated_count_data)
if (db.total_count.find({'tag':search}).count() > 0)== False:
Total_count.insert_one(count_data)
else:
ttl_cnt = db.total_count.find_one({'tag':search})
reviews = ttl_cnt["Total_reviews"]
positive = ttl_cnt["positive"]
negative = ttl_cnt["negative"]
neutral = ttl_cnt["neutral"]
updated_total_count_data ={
"$set":
{"Total_reviews": reviews+1,
"positive":positive+pos,
"negative":negative+neg,
"neutral":neutral+neu,
"updatedAt": datetime.datetime.now()
}
}
Total_count.update_one(ttl_cnt,updated_total_count_data)
recent_medias = cl.hashtag_medias_recent(search,amount)
for media in recent_medias:
result = media.dict()
if (db.instagram.find({"shortcode":result['code']}).count() > 0)== False:
shortcode = result['code']
postid = result['pk']
userid = result['user']['pk']
url = result['thumbnail_url']
created_at = result['taken_at']
if (result['location']!= None):
location = result['location']['name']
lat = result['location']['lat']
lng = result['location']['lng']
else:
location = None
lat = None
lng = None
comment_count = result['comment_count']
like_count = result['like_count']
user_name = result['user']['full_name']
caption_text = result['caption_text']
Sentiment = sentiment_analysis(caption_text)
insta_data = {
"publishedTime": created_at ,
"postId": postid,
"userId": userid,
"username": user_name,
"location": location,
"lat": lat,
"lng": lng,
"caption": caption_text,
"image_url": url,
"shortcode" : shortcode,
"likes": int(like_count),
"comment_count":int(comment_count),
"tag" : search,
"sentiment":Sentiment,
"createdAt": datetime.datetime.now(), "updatedAt": datetime.datetime.now()
}
if Sentiment == "Positive":
pos = 1
neg = 0
neu = 0
elif Sentiment == "Negative":
pos = 0
neg = 1
neu = 0
else:
pos = 0
neg = 0
neu = 1
Instagram.insert_one(insta_data)
count_data = {
"tag" : search,
"Total_reviews": 1,
"positive":pos,
"negative":neg,
"neutral":neu,
"createdAt": datetime.datetime.now(),
"updatedAt": datetime.datetime.now()
}
if (db.instagram_count.find({'tag':search}).count() > 0)== False:
Insta_count.insert_one(count_data)
else :
tum_cnt = db.instagram_count.find_one({'tag':search})
reviews = tum_cnt["Total_reviews"]
positive = tum_cnt["positive"]
negative = tum_cnt["negative"]
neutral = tum_cnt["neutral"]
updated_count_data ={
"$set":
{"Total_reviews": reviews+1,
"positive":positive+pos,
"negative":negative+neg,
"neutral":neutral+neu,
"updatedAt": datetime.datetime.now()
}
}
Insta_count.update_one(tum_cnt,updated_count_data)
if (db.total_count.find({'tag':search}).count() > 0)== False:
Total_count.insert_one(count_data)
else:
ttl_cnt = db.total_count.find_one({'tag':search})
reviews = ttl_cnt["Total_reviews"]
positive = ttl_cnt["positive"]
negative = ttl_cnt["negative"]
neutral = ttl_cnt["neutral"]
updated_total_count_data ={
"$set":
{"Total_reviews": reviews+1,
"positive":positive+pos,
"negative":negative+neg,
"neutral":neutral+neu,
"updatedAt": datetime.datetime.now()
}
}
Total_count.update_one(ttl_cnt,updated_total_count_data)
return "Done"
# import requests
# import json
# import pandas as pd
# import pymongo
# from pymongo import MongoClient
# import dns
# import time
# from datetime import datetime
# from dateutil.parser import parse
#
# client = pymongo.MongoClient("mongodb+srv://KokilaReddy:[email protected]/Sociolitic?retryWrites=true&w=majority")
# db = client.Social_media_data
# Insta = db.instagram
#
# def insta(q):
# try:
# url = "http://localhost:8000/search/"+q
# response = requests.request("GET", url)
# response = json.loads(response.text)
# publishedTime= []
# postId = []
# userId = []
# isvideo = []
# url = []
# caption = []
# accessibility_caption = []
# likes = []
# views = []
# comment_count = []
# source = []
# tag = []
# shortcode = []
#
# for item in response:
# publishedTime.append(item['node']['taken_at_timestamp'])
# postId.append(item['node']['id'])
# caption.append(item['node']['edge_media_to_caption']['edges'][0]['node']['text'])
# userId.append(item['node']['owner']['id'])
# likes.append(item['node']['edge_liked_by']['count'])
# isvideo.append(item['node']['is_video'])
# accessibility_caption.append(item['node']['accessibility_caption'])
# url.append(item['node']['display_url'])
# shortcode.append(item['node']['shortcode'])
# if 'video_view_count' in item['node']:
# views.append(item['node']['video_view_count'])
# Views= int(item['node']['video_view_count'])
# else:
# views.append("null")
# Views = "NIL"
# comment_count.append(item['node']['edge_media_to_comment']['count'])
# tag.append(q)
# insta_data = {
# "created_date": datetime.datetime.utcnow(),
# "publishedTime": datetime.fromtimestamp(item['node']['taken_at_timestamp']).strftime('%Y-%m-%d %H:%M:%S') ,
# "postId": str(item['node']['id']),
# "userId": str(item['node']['owner']['id']),
# "caption": item['node']['edge_media_to_caption']['edges'][0]['node']['text'],
# "url": str(item['node']['display_url']),
# "shortcode" : item['node']['shortcode'],
# "likes": int(item['node']['edge_liked_by']['count']),
# "views" : Views,
# "is_video" : item['node']['is_video'],
# "accessibility_caption":item['node']['accessibility_caption'],
# "comment_count":int(item['node']['edge_media_to_comment']['count']),
# "tag" : q,
# "createdAt": datetime.datetime.now(), "updatedAt": datetime.datetime.now()
# }
# if (db.instagram.find(insta_data).count() > 0)== False:
# Insta.insert_one(insta_data)
#
# insta_dict = {'publishedTime':publishedTime,'postId':postId,'userId':userId,'caption':caption,'url':url,'shortcode':shortcode,'likes':likes,'views':views,'is_video':isvideo,'accessibility_caption':accessibility_caption,'comment_count':comment_count,'tag':tag}
# df=pd.DataFrame(insta_dict)
# json_=df.to_json(orient="records")
# return json_
#
# except:
# return "error"