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

About Micropyramid

Micropyramid is a software development and cloud consulting partner for enterprise businesses across the world. We work on python, Django, Salesforce, Angular, Reactjs, React Native, MySQL, PostgreSQL, Docker, Linux, Ansible, git, amazon web services. We are Amazon and salesforce consulting partner with 5 years of cloud architect experience. We develop e-commerce, retail, banking, machine learning, CMS, CRM web and mobile applications.

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