MongoDB and Python

Prerequisite : MongoDB : An introduction

MongoDB is a cross-platform, document oriented database that works on the concept of collections and documents. MongoDB offers high speed, high availability, and high scalability.
The next question which arises in the mind of the people is “Why MongoDB”? There are several reasons for this. These are listed below.

  1. It supports hierarchical data structure (Please refer docs for details)
  2. It supports associate arrays like Dictionaries in Python.
  3. Built-in Python drivers to connect python-application with Database. Example- PyMongo
  4. It is designed for Big Data.
  5. Deployment of MongoDB is very easy.

While comparing MongoDB with RDBMS, we got to the following conclusion.

PyMongo Installation

Python has a native library for MongoDB. The name of the available library is “PyMongo”. To import this, execute the following command:

import pymongo    

Create a connection

The very first after importing the module is to create a MongoClient.

from pymongo import MongoClient
client = MongoClient()

After this, connect to the default host and port. Connection to the host and port is done explicitly. The following command is used to connect the MongoClient on the localhost which runs on port number 27017.
client = MongoClient(‘host’, port_number)
example:- client = MongoClient(‘localhost’, 27017)

It can also be done using the following command:

client = MongoClient(“mongodb://localhost:27017/”)

Accessing the database

Using MongoDB, we can use dictionary style access to access databases on the MongoClient instances.

mydatabase = client[‘name_of_the_database’]

If there is no previously created database with this name, MongoDB will implicitly create one for the user. Note that the name of the database fill won’t tolerate any dash (-) used in it. The names like my-Table will raise an error. So, underscore are permitted to use in the name.

Accessing the Collection

Collections are equivalent to Tables in RDBMS. We access a collection in PyMongo in the same way as we access the Tables in the RDBMS. To access the table, say table name “myTable” of the database, say “mydatabase”.

mycollection = mydatabase[‘myTable’]
MongoDB store the database in the form of dictionaries as shown:
title: 'MongoDB and Python', 
description: 'MongoDB is no SQL database', 
tags: ['mongodb', 'database', 'NoSQL'], 
viewers: 104 

‘_id’ is the special key which get automatically added if the programmer forgets to add explicitly. _id is the 12 bytes hexadecimal number which assures the uniqueness of every inserted document.


Insert the data using insert method()

We normally use insert() method document into our collections. Say, we wish to enter the data named as record into the ’myTable’ of ‘mydatabase’.

rec = mydatabase.myTable.insert(record)

The whole code looks likes this when needs to be implemented.

# importing module
from pymongo import MongoClient

# creation of MongoClient

# Connect with the portnumber and host
client = MongoClient(“mongodb://localhost:27017/”)

# Access database
mydatabase = client[‘name_of_the_database’]

# Access collection of the database

# dictionary to be added in the database
title: 'MongoDB and Python', 
description: 'MongoDB is no SQL database', 
tags: ['mongodb', 'database', 'NoSQL'], 
viewers: 104 

# inserting the data in the database
rec = mydatabase.myTable.insert(record)

Querying in MongoDB

There are certain query functions which are used to filer the data in the database. The two most commonly used functions are:

  1. find()
  2. count()


find() is used to get more than one single document as a result of query.

for i in mydatabase.myTable.find({title: 'MongoDB and Python'})

This will output all the documents in the myTable of mydatabase whose title is ‘MongoDB and Python’.


count() is used to get the numbers of documents with the name as passed int he parameters.

print(mydatabase.myTable.count({title: 'MongoDB and Python'}))

This will output the numbers of documents in the myTable of mydatabase whose title is ‘MongoDB and Python’.

These two query functions can be summed to give a give the most filtered result as shown below.

print(mydatabase.myTable.find({title: 'MongoDB and Python'}).count())

This article is contributed by Rishabh Bansal. If you like GeeksforGeeks and would like to contribute, you can also write an article using or mail your article to See your article appearing on the GeeksforGeeks main page and help other Geeks.

Please write comments if you find anything incorrect, or you want to share more information about the topic discussed above.

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