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app.py
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app.py
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from flask import Flask, jsonify, request, send_from_directory
import omdb;
from pymongo import MongoClient
import math;
import datetime
import hashlib
from flask_uploads import (UploadSet, configure_uploads, IMAGES,
UploadNotAllowed)
from sklearn.cluster import KMeans
import numpy as np
import sys
import pyfpgrowth
# App
UPLOADED_PHOTOS_DEST = '/tmp/photolog'
ALLOWED_EXTENSIONS = set(['txt', 'pdf', 'png', 'jpg', 'jpeg', 'gif'])
app = Flask(__name__, static_url_path='')
# Global Vars
omdb.api._client.params_map['apikey'] = 'apikey'
omdb.set_default('apikey', '26029d08')
photos = UploadSet('photos', IMAGES,default_dest=lambda app:app.instance_path)
configure_uploads(app, photos)
count = 0
user_count = 0
batch_size = 12
client = MongoClient('mongodb://localhost:27017/')
mydb = client['movie_database']
user_rating_matrix = []
movie_index_dict = {}
user_index_dict = {}
transactions = []
genres = []
lastCall = 0;
recommendation = {
"predicted_numpy_matrix" : np.array(user_rating_matrix)
}
def init_user_rating_matrix():
user_rating_cursor = mydb.user_ratings.find()
for user_rating_item in user_rating_cursor:
insert_into_matrix(user_rating_item.get("user_id"), user_rating_item.get("movie_id"), user_rating_item.get("rating"))
print "[info] Loading initial user matrix complete"
def convert_to_numpy(list_matrix):
max_len = len(max(list_matrix,key=len))
for list_item in list_matrix:
current_len = len(list_item)
for i in xrange(max_len - current_len):
list_item.append(0)
return np.array(list_matrix)
def key_from_value(value, dict):
for key in dict.keys():
if(dict.get(key) == value):
return key
def matrix_factorization(R, P, Q, K, steps=5000, alpha=0.0002, beta=0.02):
Q = Q.T
for step in xrange(steps):
for i in xrange(len(R)):
for j in xrange(len(R[i])):
if R[i][j] > 0:
eij = R[i][j] - np.dot(P[i,:],Q[:,j])
for k in xrange(K):
P[i][k] = P[i][k] + alpha * (2 * eij * Q[k][j] - beta * P[i][k])
Q[k][j] = Q[k][j] + alpha * (2 * eij * P[i][k] - beta * Q[k][j])
eR = np.dot(P,Q)
e = 0
for i in xrange(len(R)):
for j in xrange(len(R[i])):
if R[i][j] > 0:
e = e + pow(R[i][j] - np.dot(P[i,:],Q[:,j]), 2)
for k in xrange(K):
e = e + (beta/2) * (pow(P[i][k],2) + pow(Q[k][j],2))
if e < 0.001:
break
return P, Q.T
def predict_numpy_matrix():
print "[info] Predictng numpy matrix"
R = convert_to_numpy(user_rating_matrix)
N = len(R)
M = len(R[0])
K = 5
P = np.random.rand(N,K)
Q = np.random.rand(M,K)
nP, nQ = matrix_factorization(R, P, Q, K)
nR = np.dot(nP, nQ.T)
nR = np.around(nR, decimals = 3)
recommendation["predicted_numpy_matrix"] = nR
print "[Done] Predictng numpy matrix"
def insert_into_matrix(user_id, movie_id, rating):
matrix_len = len(user_rating_matrix)
user_index = get_item_index(user_id, user_index_dict)
movie_index = get_item_index(movie_id, movie_index_dict)
if user_index >= matrix_len:
itr_count = user_index - matrix_len + 1
for i in xrange(itr_count):
user_rating_matrix.append([])
tempArray = user_rating_matrix[user_index]
tempArray_len = len(tempArray)
if movie_index < tempArray_len:
tempArray[movie_index] = rating
else:
itr_count = movie_index - tempArray_len
for i in xrange(itr_count):
tempArray.append(0)
tempArray.append(rating)
user_rating_matrix[user_index] = tempArray
def get_item_index(item_id, dict):
if item_id in dict.keys():
return dict[item_id]
else:
current_length = len(dict)
dict[item_id] = current_length
return current_length
# Routes
@app.route('/_uploads/photos/<path:path>')
def send_js(path):
return send_from_directory('instance', path)
@app.route('/')
def index():
return "Hello, World!"
@app.route('/login', methods=['POST'])
def login():
print "I do came here.."
content = request.get_json(force=True)
print request
print content
username = content.get("username", None)
password = content.get("password", None)
password = computeMD5hash(password)
print username
user = mydb.users.find_one({"_id" : username, "password" : password});
if user :
valid = True;
return jsonify({"valid" : valid, "mod" : user.get("moderator")})
else:
return jsonify({"valid" : False})
@app.route('/rateMovie', methods=["POST"])
def rateMovie():
content = request.get_json(force=True)
print content
username = content.get("username", None)
movie_id = content.get("movie_id", None)
valid_user = mydb.users.find_one({"_id" : username});
valid_movie = mydb.movies.find_one({"_id": movie_id})
if not valid_user or not valid_movie:
return jsonify({"message" : "Invalid User or Movie"})
rating = content.get("rating", 0)
if username and movie_id and rating :
rating_item = mydb.user_ratings.find_one({"user_id" : username, "movie_id" : movie_id});
if rating_item :
mydb.user_ratings.update_one({"_id" : rating_item.get("_id")}, {"$set": {"rating" : rating, "time_stamp" : datetime.datetime.now().isoformat()}})
createActivity(valid_user.get("profile_url"),username, "rated", valid_movie.get("title"), rating)
else:
mydb.user_ratings.insert_one({"user_id" : username, "movie_id" : movie_id,"rating": rating, "time_stamp" : datetime.datetime.now().isoformat()})
createActivity(valid_user.get("profile_url"),username, "rated", valid_movie.get("title"), rating)
insert_into_matrix(username, movie_id, rating)
convert_to_numpy(user_rating_matrix)
return jsonify({"message" : "success"})
else:
return jsonify({"message" : "failure"})
@app.route('/register', methods=["POST"])
def register():
content = request.get_json(force=True)
print content
username = content.get("username", None)
password = content.get("password", None)
moderator = content.get("moderator", False)
print moderator
url = content.get("profile_url", None)
if request.method == 'POST' and 'photo' in request.files:
filename = photos.save(request.files['photo'])
url = photos.url(filename)
password = computeMD5hash(password)
if moderator :
moderator = True
user = mydb.users.find_one({"_id" : username});
if user:
return jsonify({"message" : "User Already Exists!"})
else :
valid = True
mydb.users.insert_one({
"_id" : username,
"password" : password,
"moderator" : moderator,
"time_stamp" : datetime.datetime.now().isoformat(),
"profile_url" : url
})
return jsonify({"message" : "success"})
@app.route('/save_movie/<string:id>')
def saveMovie(id):
result = mydb.movies.find({"_id" : id})
if count_iterable(result) < 1:
movieInfo = omdb.imdbid(id)
movieInfo["_id"] = movieInfo["imdb_id"]
movieInfo["time_stamp"] = datetime.datetime.now().isoformat();
mydb.movies.insert_one(movieInfo)
print movieInfo.title +" Inserted!"
calculate_movies_count();
return jsonify({"message" : "success"})
@app.route('/recommend/<string:id>')
def recommend(id):
global lastCall
lastCall += 1
i = get_item_index(id, user_index_dict)
if i >= len(user_rating_matrix):
return jsonify({"movies":[], "message" : "Insufficient movies"})
print str(i) + " <<>> " + str(len(recommendation["predicted_numpy_matrix"]) )
print str(lastCall) + " <<LastCall>> "
if(lastCall % 10 == 0 or i >= len(recommendation["predicted_numpy_matrix"])):
print "Re Calculating"
predict_numpy_matrix()
else:
print "Re Using"
nR = recommendation["predicted_numpy_matrix"]
a = nR[i].tolist()
max_i = np.argsort(a)[::-1]
result = []
max_i = max_i.tolist()
total_movies = 0
for index in max_i:
if total_movies > 5:
break
if user_rating_matrix[i][index] == 0:
if a[index] > 2.5:
total_movies = total_movies + 1
movie_id = key_from_value(index, movie_index_dict)
movie = mydb.movies.find_one({"_id" : movie_id})
if a[index] > 5:
movie["predicted_rating"] = 5
else:
movie["predicted_rating"] = a[index]
result.append(movie)
return jsonify({"movies" : result})
@app.route('/delete_movie/<string:id>')
def deleteMovie(id):
result = mydb.movies.find({"_id" : id})
if count_iterable(result) > 0:
movieInfo = omdb.imdbid(id)
movieInfo["_id"] = movieInfo["imdb_id"]
mydb.movies.delete_many({"_id" : id})
print movieInfo.title +" Deleted!"
calculate_movies_count();
return jsonify({"message" : "success"})
@app.route('/movies/<int:page_no>')
def get_movies(page_no ):
if get_movies_count() < 1:
calculate_movies_count();
if request.args :
username = request.args.get("username", None)
print username
ratedMovies = []
if username:
movie_iter = mydb.user_ratings.find({"user_id" : username})
for movie in movie_iter:
print movie
ratedMovies.append(movie)
movies = mydb.movies.find().sort("time_stamp", -1).skip((page_no - 1) * batch_size).limit(batch_size)
result = []
for movie in movies:
rating_item = isInArray(ratedMovies, movie, "movie_id", "_id")
if rating_item:
movie["user_rating"]=rating_item.get("rating")
result.append(movie)
return jsonify({"count": get_movies_count(), "movies": result})
@app.route('/users/<int:page_no>')
def get_users(page_no ):
if get_users_count() < 1:
calculate_users_count();
users = mydb.users.find().sort("time_stamp", -1).skip((page_no - 1) * batch_size).limit(batch_size)
result = []
for user in users:
result.append(user)
return jsonify({"count": get_users_count(), "users": result})
@app.route('/fpRecommender/<string:id>')
def getFPRecommendations(id):
enrichedRecList = []
minsup = 3
if request.args and request.args.get("minsup"):
minsup = request.args.get("minsup")
recommendations = fpRecommender(id, int(minsup))
movies_sample = []
for recommendation in recommendations:
enrichedRec = []
for movie in recommendation.get("reason", []):
enrichedRec.append(mydb.movies.find_one({"_id" : movie})["title"])
if(len(enrichedRec) > 1):
enrichedRecList.append({
"reason" : enrichedRec,
"movies" : recommendation.get("movies", [])
})
movies_sample = concatWithoutDuplicates(movies_sample, recommendation.get("movies", []))
print movies_sample
enrichedMoviesSample = []
for movie in movies_sample:
enrichedMoviesSample.append(mydb.movies.find_one({"_id" : movie}))
labels = formClusters(n_cl = 2, movies = enrichedMoviesSample).labels_
return jsonify({"recommendation" : enrichedRecList, "movie_sample" : enrichedMoviesSample, "labels" : labels.tolist()})
@app.route('/similar/<string:id>')
def getSimilar(id):
movies_c = mydb.movies.find();
movie_sample = []
index = 0;
i = 0;
for movie in movies_c:
if movie["_id"] == id:
index = i
print "selected index " + str(index)
i += 1
movie_sample.append(movie)
print i;
n_c = i/5;
print n_c
labels = formClusters(n_cl = n_c, movies = movie_sample).labels_
print labels
class_m = labels[index]
result = []
i = 0
for l in labels:
if l == class_m and index != i:
result.append(movie_sample[i])
i += 1
return jsonify(result)
def concatWithoutDuplicates(list1, list2):
return list1 + list(set(list2) - set(list1))
def updateTransactions(minsup):
transactions = []
users = mydb.users.find();
for user in users:
movie_id_list = [];
ratings = mydb.user_ratings.find({"user_id" : user.get("_id"), "rating" : {"$gt" : 2.9}})
for rating in ratings:
movie_id_list.append(rating.get("movie_id"))
if(len(movie_id_list) > 0):
transactions.append(movie_id_list)
size = 0;
itemsets = pyfpgrowth.find_frequent_patterns(transactions, minsup)
patterns = []
for itemset in itemsets:
if(len(itemset) > 1):
patterns.append(itemset)
return patterns
def intersect(a, b):
return list(set(a) & set(b))
def difference(a,b):
return list(set(a).symmetric_difference(set(b)))
def fpRecommender(user_id, minsup):
ratings = mydb.user_ratings.find({"user_id" : user_id, "rating" : {"$gt" : 2.9}})
user_movies = []
recommended_movies = []
for rating in ratings:
user_movies.append(rating.get("movie_id"))
patterns = updateTransactions(minsup)
for pattern in patterns:
intersection = intersect(user_movies, pattern)
if(len(intersection) > 0 and len(intersection) < len(pattern)):
print float(len(intersection))/len(pattern)
if(float(len(intersection))/len(pattern) > 0.4):
diff = difference(pattern, intersection)
recommendation = {
"reason" : intersection,
"movies" : diff
}
recommended_movies.append(recommendation)
return recommended_movies
@app.route('/movie/<string:id>')
def get_movie(id):
movie = mydb.movies.find_one({"_id" : id})
return jsonify(movie)
@app.route('/search_movies')
def search_movies():
search_string = ""
response = []
print "hello"
if request.args and request.args.get("s"):
search_string = request.args.get("s")
auto_store = request.args.get("auto_store")
result = omdb.search_movie(search_string)
for movie in result:
try:
print movie.title
movie["_id"] = movie["imdb_id"]
if movie["poster"].endswith(".jpg"):
response.append(movie)
alreadyExists = mydb.movies.find({"_id" : movie["imdb_id"]})
alreadyExists = count_iterable(alreadyExists) > 0
if(not alreadyExists and auto_store == "1"):
print "going to save a movie " + movie["_id"]
movieInfo = omdb.imdbid(movie["_id"])
movieInfo["_id"] = movieInfo["imdb_id"]
movieInfo["time_stamp"] = datetime.datetime.now().isoformat();
mydb.movies.insert_one(movieInfo)
print movieInfo.title +" Inserted!"
calculate_movies_count();
if alreadyExists:
movie.stored = "true";
else:
movie.stored = "false";
except Exception as e:
print "Exception has occured"
print str(e)
return jsonify(response)
# Helpers
def count_iterable(i):
return sum(1 for e in i)
def get_users_count():
return user_count;
def get_movies_count():
return count;
def calculate_movies_count():
global count;
count = math.ceil(mydb.movies.count() / float(batch_size));
print count;
def calculate_users_count():
global user_count;
user_count = math.ceil(mydb.users.count() / float(batch_size));
print user_count;
def computeMD5hash(string):
m = hashlib.md5()
m.update(string.encode('utf-8'))
return m.hexdigest()
@app.route('/upload', methods=['GET','POST'])
def upload():
if request.method == 'POST' and 'photo' in request.files:
filename = photos.save(request.files['photo'])
return jsonify({"message" : "success", "url" : photos.url(filename)})
else:
return jsonify({"message" : "invalid"})
@app.route('/activities', methods=['GET'])
def get_activites():
username = None
if request.args:
username = request.args("username", None)
result = []
if username:
activity_iter = mydb.activity.find({"user_id" : username}).sort("time_stamp",-1).limit(20);
for activity in activity_iter:
result.append(activity)
else:
activity_iter = mydb.activity.find().sort("time_stamp",-1).limit(20);
for activity in activity_iter:
activity["_id"] = "[HIDDEN]"
result.append(activity)
return jsonify({"activities" : result})
# Main
def isInArray(source, target, id1, id2):
for sourceItem in source:
if(sourceItem.get(id1) == target.get(id2)):
return sourceItem
else:
return False
def createActivity(userImage, username, verb,moviename, rating):
mydb.activity.insert_one({
"profile_url" : userImage,
"username" : username,
"verb" : verb,
"moviename" : moviename,
"rating" : rating,
"time_stamp" : datetime.datetime.now().isoformat()
})
def transformMovie(movie):
movie_genre = movie["genre"].split(", ")
#Sci-Fi, Crime, Mystery, Thriller, Action, Comedy , Adventure, Drama, Horror, Family Short Animation rating, year, runtime
movie_t = []
genres = ["Sci-Fi", "Crime", "Thriller", "Action", "Comedy","Adventure","Drama","Horror","Family","Short","Animation"]
for genre in genres:
if(genre in movie_genre):
movie_t.append(1)
else:
movie_t.append(0)
if movie["imdb_rating"] != "N/A":
movie_t.append(float(movie["imdb_rating"])/ 10)
else:
movie_t.append(0)
movie_t.append(int(movie["year"]) / 2017)
if movie["runtime"] != "N/A":
movie_t.append(int(movie["runtime"].split(" ")[0])/ 160)
else:
movie_t.append(0)
return movie_t
def formClusters(n_cl = 2,movies = []):
movies_a = []
for movie in movies:
movies_a.append(transformMovie(movie))
x = np.array(movies_a)
kmeans = KMeans(n_clusters=n_cl, random_state=0).fit(x)
return kmeans
if __name__ == '__main__':
init_user_rating_matrix()
#updateTransactions()
app.run(host='0.0.0.0', debug = True)
def isInArray(source, target, id1, id2):
print target
for sourceItem in source:
print sourceItem
if(sourceItem.get(id1) == target.get(id2)):
return sourceItem
else:
return False