MongoDB CRUD operations with Python (Pymongo)

PyMongo is a Python distribution  that contains tools for working with MongoDB, So in this blog post let’s see some basic methods that perform CRUD operations to a collection.

Install pymongo:

pip install pymongo

Connecting  to with Database with PyMongo:

1. To perform CRUD operations first need to establish the connection using Mongo client 

>>> from pymongo import MongoClient
>>> client = MongoClient('localhost',27017)  # 27017 is the default port number for mongodb

2. Next step is to connect to the database (test).

db = client.test

3. Now retrieve the collection (person) from the database

col = db.person

Now we are ready to perform the actual CRUD operations.

CRUD Operations:


Mongo store the data in the form of JSON objects. So every record for a collection in mongo is called a document. If the collection does not currently exist, insert operations will create the collection. We can insert the documents into collection in 3 ways.

  • insert_one()
  • insert_many()
  • insert()

1. insert_one(): insert_one() inserts a single document into a collection.

      name: "John",
      salary: 100 ,

The above snippet returns the pymongo.results.InsertOneResult object:

<pymongo.results.InsertOneResult object at 0x7f8fbe7fb960>

2. insert_many(): insert_many() inserts multiple documents into a collection.

The following example inserts three new documents into the users collection. Each document has two fields name and salary. Since the documents do not specify an _id field, MongoDB adds the _id field with an ObjectId value to each document.

     { name: "Jeorge", salary: 100},
     { name: "Steve", salary: 100},
     { name: "David", salary: 100}

The method returns a pymongo.results.InsertManyResult object

<pymongo.results.InsertManyResult object at 0x7f8fbe7fb7d0>

3. insert(): insert() can be used to insert single or array or documents.

# single document
col.insert({ name: "Jeorge", salary: 100})

# array of documents
col.insert([{ name: "Jeorge", salary: 100}, { name: "Steve", salary: 100}])

insert() method returns all the Object ids of the documents that are inserted.

# return type of single document

# return type of multiple documents
[ObjectId('57611d4b1aa303032ad5ba9e'), ObjectId('57611d4b1aa30303sdd5ba9e')]


We can retrieve the documents from a collection using 2 methods.

  • find()
  • find_one()

1. find(): find() function will return with all the documents in that collection. By default it returns a cursor object.

<pymongo.cursor.Cursor object at 0x7f8fc1853890>

2. find_one(): find_one() returns the first document in the collection.

{u'salary': 100, u'_id': ObjectId('57611a711aa303032ad5ba9b'), u'name': u'John'}

We can filter the results by applying conditions on these methods as following

col.find_one({"name": "John"}) # returns object.
col.find({"name": "John"}) # returns cursor

U- Update:

We can update the documents from the collection with the following methods.

  • update()
  • update_one()
  • update_many()
  • replace_one()

The general syntax for all the above methods is

<method_name>(condition, update_or_replace_document, upsert=False, bypass_document_validation=False)


condition: A query that matches the document to replace.
update_or_replace_document: The new document.
upsert (optional): If True, perform an insert if no documents match the filter.
bypass_document_validation: (optional) If True, allows the write to opt-out of document level validation. Default is False.

Following are the snippets forh update(), update_one(), update_many() and replace_one(). All the methods will return UpdateResult object except update().

# update_one
>>> col.update_one({"name":"John"}, {"$set":{"name":"Joseph"}})
<pymongo.results.UpdateResult object at 0x7f8fbe7fb910>

# update_many
>>> col.update_many({"name":"John"}, {"$set":{"name":"Joseph"}})
<pymongo.results.UpdateResult object at 0x7f8fbe7fb7d0>

# update
>>> col.update({"name":"John"}, {"$set":{"name":"Jeorge"}})
{'updatedExisting': False, u'nModified': 0, u'ok': 1, u'n': 0}

>>> col.replace_one({"name":"John"}, {"name":"Jeorge"})
<pymongo.results.UpdateResult object at 0x7f8fbe7fb910>

D- Delete:

We can delete the documents in the collection using  the following methods.

  • delete_one()
  • delete_many()

Both these methods will return a DeleteResult object. The general syntax for the above methods is as follows.


Following are the examples how we use the delete_one() and delete_many() methods, both returns the DeleteResult object.

>>> col.delete_one({"name":"John"})
<pymongo.results.DeleteResult object at 0x7f8fbe7fba00>

>>> col.delete_many({"name":"John"})
<pymongo.results.DeleteResult object at 0x7f8fbe7fb960>

Posted On 20 December 2014 By MicroPyramid

Need any Help in your Project?Let's Talk

Latest Comments
How do I profile django application using django web profiler

When working with a large scale applications which includes many modules, we need to focus on the performance to give more user statisfaction, sustainability. To …

Continue Reading...
Multifactor Authentication with Django MFA using Google Authenticator

Use Django Multi-Factor Authentication method to verify user identity with more than one authentication methods. It can be used for user login, any transactional methods …

Continue Reading...
Celery Flower to monitor task queue

Celery is a task queue that is to built an asynchronous message passing system. It can be used as a bucket where programming tasks can …

Continue Reading...
Check test coverage in Django code with Coveralls

Coverage: It is a tool used for measuring the effectiveness of tests, showing the percentage of your codebase covered by tests.
Test Coverage is an important …

Continue Reading...
Full text search in mongodb

Full text search is a custom implementation created by the MongoDB developers as a specific index type

Full text search as an index type when …

Continue Reading...
MongoDB CRUD operations with Python (Pymongo)

MongoDB with Python - Connection establishment, Create, Update, Retrieve and Delete operations explained with sample code.

Continue Reading...
Advanced Querying in MongoDB

Advanced Queries of MongoDB: Inserting records to the database and retrieving data from database.
1. Wrapped Queries: Like, sort, limit, count.
2. Query Using Modifiers: set, increment, …

Continue Reading...

The group() command, Aggregation Framework and MapReduce are collectively aggregation features of MongoDB. group(): Group Performs simple aggregation operations on a collection documents. Group is …

Continue Reading...

Subscribe To our news letter

Subscribe and Stay Updated about our Webinars, news and articles on Django, Python, Machine Learning, Amazon Web Services, DevOps, Salesforce, ReactJS, AngularJS, React Native.
* We don't provide your email contact details to any third parties