import pymongo
from bson.code import Code

class MongoDBConnector:
    def __init__(self, dbname, host='localhost', port=27017):
        self.host = host
        self.port = port
        self.dbname = dbname

    def openConnection(self):
        self.client = pymongo.MongoClient(host=self.host, port=self.port)
        self.db = self.client[self.dbname]

    def closeConection(self):
    	self.client.close()

    def getRecords(self, collection, filter=None, projection=None):
        if projection is None and not filter is None:
            return self.db[collection].find(filter=filter)
        elif not projection is None and filter is None:
            return self.db[collection].find(projection=projection)
        elif projection is None and filter is None:
            return self.db[collection].find()
        return self.db[collection].find(filter=filter, projection=projection)

    def getRecord(self, collection, filter=None, projection=None):
        if projection is None and not filter is None:
            return self.db[collection].find_one(filter=filter)
        elif not projection is None and filter is None:
            return self.db[collection].find_one(projection=projection)
        elif projection is None and filter is None:
            return self.db[collection].find_one()
        return self.db[collection].find_one(filter=filter, projection=projection)

    def execAggreation(self, collection, pipeline):
        return self.db[collection].aggregate(pipeline=pipeline)

    def execMapReduce(self, collection, mapper, reducer, out, query=None):
        self.db[out].drop()
        if query is None:
            return self.db[collection].map_reduce(mapper, reducer, out)
        return self.db[collection].map_reduce(mapper, reducer, out, query=query)


if __name__ == '__main__':
    dbname = "BD"
    db = MongoDBConnector(dbname=dbname)
    collection = "documents"
    
    filter = { "$text": 
        { 
            "$search": "coffee", 
            "$language": "english", 
            "$caseSensitive": False, 
            "$diacriticSensitive": False 
        } 
    }
    projection = { "lemmaText": 1 }
    db.openConnection()
    print("Test 1")
    doc = db.getRecord(collection, filter, projection)
    print(doc)
    print("Test 2")
    doc = db.getRecord(collection, filter=filter)
    print(doc)
    print("Test 3")
    doc = db.getRecord(collection, projection=projection)
    print(doc)
    print("Test 4")
    doc = db.getRecord(collection)
    print(doc)
    db.closeConection()

    # Exeplu folosire index geospatial.

    filter = { "geoLocation": { "$near": [25, 25] } }
    projection = {"geoLocation": 1, "lemmaText": 1 }
    db.openConnection()
    docs = db.getRecords(collection, filter, projection)
    for doc in docs:
        print(doc)
    db.closeConection()

    # Exemplu Aggregation Pipeline

    q = {"gender": "male"}
    pipeline = [
                    { "$match": q },
                    { "$project": { "words": { "$split": ["$lemmaText", " "]}}},
                    { "$unwind": "$words" },
                    { "$group": { "_id": "$words", "counts": { "$sum": 1 } } }
        ]

    db.openConnection()
    docs = db.execAggreation(collection, pipeline)
    for doc in docs:
        print(doc)
    db.closeConection()

    # Exemplu MapReduce
    mapper = Code("""
        function() {
            var tokens = this.lemmaText.split(" ");
            for (var idx=0; idx<tokens.length; idx++){
                emit(tokens[idx], 1);
            }
        }
        """)

    reducer = Code("""
        function(key, values) {
            return Array.sum(values);
        }
        """)

    q = {"gender": "female"}
    out_collection = "wordCounts"
    db.openConnection()
    docs = db.execMapReduce(collection, mapper, reducer, out_collection, q)
    for doc in docs.find():
        print(doc)
    db.closeConection()