CODEWITHSUNDEEP
pythonmongodbpymongo
user12913302
user12913302

Reputation:

Using Pymongo Upsert to Update or Create a Document in MongoDB using Python

I have a dataframe that contains data I want to upload into MongoDB. Below is the data:

    MongoRow = pd.DataFrame.from_dict({'school': {1: schoolID}, 'student': {1: student}, 'date': {1: dateToday}, 'Probability': {1: probabilityOfLowerThanThreshold}})

                     school                   student        date  Probability
1  5beee5678d62101c9c4e7dbb  5bf3e06f9a892068705d8420  2020-03-27     0.000038

I have the following code which checks if a row in mongo contains the same student ID and date, if it doesn't then it adds the row:

def getPredictions(school):
    schoolDB = DB[school['database']['name']]
    schoolPredictions = schoolDB['session_attendance_predicted']
    Predictions = schoolPredictions.aggregate([{
        '$project': {
            'school': '$school',
            'student':'$student',
            'date':'$date'
        }        
    }])
    return list(Predictions)
Predictions = getPredictions(school)
Predictions = pd.DataFrame(Predictions)

schoolDB = DB[school['database']['name']]
collection = schoolDB['session_attendance_predicted']
import json

for i in Predictions.index:
    schoolOld = Predictions.loc[i,'school']
    studentOld = Predictions.loc[i,'student']
    dateOld = Predictions.loc[i,'date']
    if(studentOld == student and date == dateOld):
        print("Student Exists")
        #UPDATE THE ROW WITH NEW VALUES
    else:
        print("Student Doesn't Exist")
        records = json.loads(df.T.to_json()).values()
        collection.insert(records)

However if it does exist, I want it to update the row with the new values. Does anyone know how to do this? I have looked at pymongo upsert but I'm not sure how to use it. Can anyone help?

'''''''UPDATE'''''''

The above is partly working now, however, I am now getting an error with the following code:

dateToday = datetime.datetime.combine(dateToday, datetime.time(0, 0))

MongoRow = pd.DataFrame.from_dict({'school': {1: schoolID}, 'student': {1: student}, 'date': {1: dateToday}, 'Probability': {1: probabilityOfLowerThanThreshold}})
data_dict = MongoRow.to_dict()

for i in Predictions.index:
    print(Predictions)
    collection.replace_one({'student': student, 'date': dateToday}, data_dict, upsert=True)

Error:

InvalidDocument: documents must have only string keys, key was 1

Upvotes: 13

Views: 35055

Answers (2)

melchoir55
melchoir55

Reputation: 7276

Probably a number of people are going to be confused by the accepted answer as it suggests using replace_one with the upsert flag.

Upserting means 'Updated or Insert' (Up = update and sert= insert). For most people looking to 'upsert', they should be using update_one with the upsert flag.

For example:

collection.update_one({'matchable_field': field_data_to_match}, {"$set": upsertable_data}, upsert=True)

Upvotes: 22

Belly Buster
Belly Buster

Reputation: 8814

To upsert you cannot use insert() (deprecated) insert_one() or insert_many(). You must use one of the collection level operators that supports upserting.

To get started I would point you towards reading the dataframe line by line and using replace_one() on each line. There are more advanced ways of doing this but this is the easiest.

Your code will look a bit like:

collection.replace_one({'Student': student, 'Date': date}, record, upsert=True)

Upvotes: 10

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