187 lines
5.8 KiB
Python
187 lines
5.8 KiB
Python
# -*- coding: utf-8 -*-
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"""6338003821AdvComProgFinalProjectServer_v1.1.ipynb
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Automatically generated by Colaboratory.
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Original file is located at
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https://colab.research.google.com/drive/1B0ihZ275Hw0V034W4eFtKc-wxwkg7iLS
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"""
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! pip install pymongo[srv]
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! pip install flask_ngrok
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! pip install flask_cors
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# Write all of your functions in this cell
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from flask import Flask,request,flash, request, redirect, url_for, Response,jsonify
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from flask_ngrok import run_with_ngrok
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from flask_cors import CORS, cross_origin
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import pymongo
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import json
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import os
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from werkzeug.utils import secure_filename
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import pandas as pd
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UPLOAD_FOLDER = './'
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ALLOWED_EXTENSIONS = {'txt', 'csv','json'}
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app = Flask(__name__)
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app.config['UPLOAD_FOLDER'] = UPLOAD_FOLDER
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CORS(app, support_credentials=True)
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run_with_ngrok(app)
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client = pymongo.MongoClient("mongodb+srv://colabtest:2hdgQn0vCCJoxhY6@cluster0.s3zvk.mongodb.net/?retryWrites=true&w=majority")
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def allowed_file(filename):
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return '.' in filename and \
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filename.rsplit('.', 1)[1].lower() in ALLOWED_EXTENSIONS
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@app.route('/')
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def greeting():
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return "<H1>Greetings, traveller</H1>"
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#http://7ab7-34-73-174-138.ngrok.io/insert?dbname=data&collectionname=testdata&web=com.burbn.instagram&cat=photos
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@app.route('/insert')
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def insert_db():
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try:
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dbname=request.args.get("dbname")
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collectionname=request.args.get("collectionname")
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web=request.args.get("web")
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cat=request.args.get("cat")
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db=client[dbname]
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r=db[collectionname].insert({"accessor":{"identifier":web,"identifierType":"bundleID"},"category":cat,"identifier":"SELF-INSERT","kind":"intervalBegin","timeStamp":"2021-11-26T0:0:0.000+07:00","type":"access"})
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return jsonify('Success')
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except:
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print('Fail')
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return jsonify('Failure')
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#https://b443-34-125-209-50.ngrok.io/find?web=com.hammerandchisel.discord
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@app.route('/find')
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def find():
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web=request.args.get("web")
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collection_data=client.data.data2
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r = collection_data.find_one({"accessor":{"identifier":web,"identifierType":"bundleID"}})
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if str(r) == "None":
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res={}
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else:
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res = {'web':r['accessor']['identifier'],'category':r['category'],'time':r['timeStamp'],'type':r['type']}
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print(res)
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return jsonify(res)
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#https://b443-34-125-209-50.ngrok.io/filter?cat=photos
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@app.route('/filter')
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def filter():
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#min=request.args.get("min")
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#max=request.args.get("max")
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#min = int(min)
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#max = int(max)
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cat=request.args.get("cat")
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ls = []
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collection_data=client.data.data2
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matches = list(collection_data.find({'category':cat},{'_id': False}).sort([('timeStamp', pymongo.DESCENDING)]))
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test = collection_data.find_one({'category':cat},{'_id': False})
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for match in matches:
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res = {'web':match['accessor']['identifier'],'category':match['category'],'time':match['timeStamp'],'type':match['type']}
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ls.append(res)
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res = {'data':ls}
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if str(test) == "None":
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res = {'data':[]}
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return jsonify(res)
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@app.route('/alldata')
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def get_data():
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dp = list(collection_data2.find().sort([('timeStamp', pymongo.DESCENDING)]))
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df = json_normalize(dp)
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df.rename(columns = {'accessor.identifier':'iden'}, inplace = True)
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dff = pd.pivot_table(df,index='iden',columns='category',aggfunc='count')
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dfff = dff['_id']
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dffff = dfff
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dffff = dffff.fillna(0, downcast='infer')
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dffff['all'] = dffff['camera']+dffff['kTCCServicePhotosAdd']+dffff['location']+dffff['mediaLibrary']+dffff['microphone']+dffff['photos']
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dffff.sort_values(by=['all'], inplace=True, ascending=False)
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dfffff=dffff.to_json(orient='table')
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temp = json.loads(dfffff)['data']
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dfffff = json.dumps(temp)
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return jsonify(dfffff)
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app.run()
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collection_data = client.data.data
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r = collection_data.find_one({"accessor":{"identifier":"com.burbn.instagram","identifierType":"bundleID"}})
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#collection_data.find_one({"category":"photos"})
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res = {'web':r['accessor']['identifier'],'category':r['category'],'time':r['timeStamp'],'type':r['type']}
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res
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r['accessor']['identifier']
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r['category']
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r['timeStamp']
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collection_data.find_one({"accessor":{"identifier":"com.burbn.instagram","identifierType":"bundleID"}})
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collection_data=client.data.data
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ls = []
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matches = list(collection_data.find({'category':'photos'}).sort([('timeStamp', pymongo.DESCENDING)]))
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for match in matches:
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res = {'web':match['accessor']['identifier'],'category':match['category'],'time':match['timeStamp'],'type':match['type']}
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ls.append(res)
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res = {'data':ls}
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res
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match['accessor']['identifier']
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collection_data2 = client.data.data2
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test = list(collection_data2.find({'category':'photos'}).sort([('timeStamp', pymongo.DESCENDING)]))
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test
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import pandas as pd
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from pandas import DataFrame
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from pandas.io.json import json_normalize
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dp = list(collection_data2.find().sort([('timeStamp', pymongo.DESCENDING)]))
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df = json_normalize(dp)
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df
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df.rename(columns = {'accessor.identifier':'iden'}, inplace = True)
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dff = pd.pivot_table(df,index='iden',columns='category',aggfunc='count')
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dfff = dff['_id']
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dffff = dfff
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dffff = dffff.fillna(0, downcast='infer')
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dffff['all'] = dffff['camera']+dffff['kTCCServicePhotosAdd']+dffff['location']+dffff['mediaLibrary']+dffff['microphone']+dffff['photos']
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dffff.sort_values(by=['all'], inplace=True, ascending=False)
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dffff.to_json(orient='index')
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dffff
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dfffff=dffff.to_json(orient='table')
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temp = json.loads(dfffff)['data']
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dfffff = json.dumps(temp)
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dfffff
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df.keys()
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collection_data.aggregate([{ 'sortByCount': "$tags" }])
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dffff
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import pandas as pd
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import seaborn as sb
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import matplotlib.pyplot as plt
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import plotly.express as px
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dp = list(collection_data2.find().sort([('timeStamp', pymongo.DESCENDING)]))
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df = json_normalize(dp)
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fig = px.bar(df,x='timeStamp',y='category')
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fig3 = px.density_heatmap(df,x='accessor.identifier',y='category',z='type', histfunc="avg",nbinsx=4000, nbinsy=500, color_continuous_scale="solar")
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fig3.show()
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fig.show()
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df.keys() |