def updateWeightsByJson(userId, categoryWeights):
print("invoked")
catWeights = json.loads(categoryWeights)
#print(catWeights['nature'])
incStr = {
"$inc": {
"categories.landmark": catWeights['landmark'],
"categories.nature": catWeights['nature'],
"categories.shopping": catWeights['shopping'],
"categories.theatre": catWeights['theatre'],
"categories.restaurant": catWeights['restaurant']
}
}
#incStr = '''{"$inc":{"'''
#for key,value in catWeights.items():
#print (key,value)
#incStr += "categories."+key+":"+value
#incStr +='''}'''
#print(incStr)
conn = MongoConnection()
user_coll = conn.getUsersCollection()
row = user_coll.update_one({"userId": userId}, incStr)
if (row.acknowledged):
print("Weights updated successfully")
return row.acknowledged
def fetchPlacesbyCategoriesDuration(categories, duration):
catArr = categories.lower().split(",")
inQry = {"category": {"$in": catArr}}
dbConn = MongoConnection()
places_coll = dbConn.getPlacesCollection()
places = places_coll.find(inQry)
locations = []
validLocations = []
currDuration = 0
#print(places.count())
if (places):
for aPlace in places:
locations.append(aPlace)
shuffleList(locations)
for aLoc in locations:
print(aLoc['name'], aLoc['duration'])
if ((currDuration + aLoc['duration']) < duration):
currDuration += aLoc['duration']
validLocations.append(aLoc)
else:
break
print(currDuration)
print([aPlace['name'] for aPlace in validLocations])
def fetchUser(userId):
query = {"userId": userId}
conn = MongoConnection()
user_coll = conn.getUsersCollection()
row = user_coll.find_one(query)
#print (row)
return row
def insertUser(name,
age,
gender,
budget=0,
duration=0,
visited={},
prefCategories=""):
landmark = nature = shopping = theatre = restaurant = 0
for aCat in prefCategories.split(","):
#print(aCat)
if (aCat == "landmark"):
landmark = 1
elif (aCat == "nature"):
nature = 1
elif (aCat == "shopping"):
shopping = 1
elif (aCat == "theatre"):
theatre = 1
else:
restaurant = 1
'''print("landmark",landmark)
print("nature",nature)
print("shopping",shopping)
print("theatre",theatre)
print("restaurant",restaurant)'''
userId = randint(1000, 9999)
categories = {
"landmark": landmark,
"nature": nature,
"shopping": shopping,
"theatre": theatre,
"restaurant": restaurant
}
userDetails = {
"userId": userId,
"name": name,
"age": age,
"gender": gender,
"avgBudget": budget,
"avgDuration": duration,
"visited": visited,
"categories": categories
}
conn = MongoConnection()
print(conn.dummy())
user_coll = conn.getUsersCollection()
row = user_coll.insert_one(userDetails)
print(row.inserted_id)
if (row.acknowledged):
return userId
def fetchPlacesByCategories(categories):
inQry = {"category": {"$in": categories}}
dbConn = MongoConnection()
places_coll = dbConn.getPlacesCollection()
places = places_coll.find(inQry)
locations = []
if (places):
for aPlace in places:
locations.append(aPlace)
return shuffleList(locations)
def updateWeights(userId, landmarkWeight, natureWeight, shopWeight,
theatreWeight, restoWeight):
print("categories.landmark", landmarkWeight, "categories.natureWeight",
natureWeight, "categories.shopWeight", shopWeight,
"categories.theatreWeight", theatreWeight, "categories.restoWeight",
restoWeight)
incStr = {
"$inc": {
"categories.landmark": landmarkWeight,
"categories.nature": natureWeight,
"categories.shopping": shopWeight,
"categories.theatre": theatreWeight,
"categories.restaurant": restoWeight
}
}
conn = MongoConnection()
user_coll = conn.getUsersCollection()
user_coll.update_one({"userId": userId}, incStr)
def fetchPlacesByCategoriesBudget(categories, budget):
current_app.logger.info(categories)
current_app.logger.info(budget)
query = dict()
query["category"] = {"$in": categories}
query["Price"] = {"$lte": budget}
#print(query)
dbConn = MongoConnection()
places_coll = dbConn.getPlacesCollection()
current_app.logger.info(query)
places = places_coll.find(query, {
"_id": 0,
"suitableAge": 0,
"location": 0,
"wayToGetThere": 0
})
locations = []
if (places):
for aPlace in places:
locations.append(aPlace)
return shuffleList(locations)
def fetchCategoryWeightsForSimilarUsers(age, gender, avgBudget, avgDuration):
#age = 60
#avgBudget = '10'
#avgDuration = '6'
#gender = 'M'
match_query = {
"$match": {
"age": {
"$gte": age - 5,
"$lte": age + 5
},
"gender": gender,
"avgBudget": str(avgBudget + 1),
"avgDuration": str(avgDuration)
}
}
group_query = {
"$group": {
"_id": 0,
"landmark": {
"$avg": "$categories.landmark"
},
"nature": {
"$avg": "$categories.nature"
},
"restaurant": {
"$avg": "$categories.restaurant"
},
"shopping": {
"$avg": "$categories.shopping"
},
"theatre": {
"$avg": "$categories.theatre"
}
}
}
project_query = {
"$project": {
"_id": 0,
"landmark": {
"$ceil": "$landmark"
},
"nature": {
"$ceil": "$nature"
},
"restaurant": {
"$ceil": "$restaurant"
},
"shopping": {
"$ceil": "$shopping"
},
"theatre": {
"$ceil": "$theatre"
}
}
}
pipeline = [match_query, group_query]
current_app.logger.info(pipeline)
#print(pipeline)
conn = MongoConnection()
#sprint(aColl for aColl in conn.db.list_collections())
user_coll = conn.db[DUMMY_USERS_DB]
row = user_coll.aggregate(pipeline)
val = list(row)
#print(val)
return val