Python MongoDB PIP Installation using PyMongo Simplified 101

Last Modified: December 29th, 2022

Python MongoDB PIP Installation_FI

One of the common challenges that every growing business faces are the ability to efficiently handle the exponentially growing data. Apart from the Traditional Relational Databases, organizations are now using Document-oriented Open-source NoSQL Databases. There are several NoSQL databases out there, but MongoDB is the most commonly used, and it is available both as a Cloud Service and for Deployment on Self-Managed Systems.

In this article, you will gain information about MongoDB PIP Installation. You will also gain a holistic understanding of MongoDB, Python, their key features, and the steps for Python MongoDB PIP Installation using PyMongo. Read along to find out in-depth information about undergoing Python MongoDB PIP Installation using PyMongo.

Table of Contents

What is MongoDB?

MongoDB PIP Install: MongoDB Logo
Image Source

MongoDB is a NoSQL database that was developed by MongoDB inc, which is schema-free. It was designed and created using c++ and javascript allowing for higher connectivity. It uses a collection of Documents and has an option for creating schemas as well. It doesn’t follow the same structure of a traditional database wherein the data is stored in form of rows.

Since general RDBMS are easier to use same is the case with MongoDB. MongoDB uses a NoSQL platform making it easier for individuals having less or no prior programming knowledge. MongoDB processes the data in a semi-structured format, allowing for processing large volumes of data in one go simultaneously. It can be hosted on mostly all the cloud platforms be it Google’s Cloud, Microsoft Azure, or even Amazons’ Web Services.

MongoDB uses Binary JSON and MQL as an alternative to SQL. BSON allows for data types such as the floating-point, long, date, and many more that are not supported by regular JSON. MQL offers additional capabilities when compared to regular SQL making it more relevant for MongoDB as it processes JSON-type documents.

When using MongoDB, you will need to extract insights from the data. Such insights can facilitate data-driven decision-making. MongoDB doesn’t have all the tools that you may need for that. That’s why you may need a tool like Python. Python is a powerful programming language for data analytics. It is compatible with many data analysis tools and libraries. The good thing is that MongoDB and Python can be integrated through PyMongo. In this article, we will be discussing how to use MongoDB pip install Python using PyMongo. 

To install MongoDB click here.

Key Features of MongoDB

MongoDB PIP Install: MongoDB Architecture
Image Source

Main features of MongoDB which make it unique are:

1) High Performance

Data operations on MongoDB are fast and easy because of their NoSQL nature. Data can be quickly stored, manipulated, and retrieved without any compromise on data integrity.

2) Scalability

In the Big Data era, MongoDB data can be distributed across a cluster of machines quickly and equally, free of bulkiness. The scalability of MongoDB handles a growing amount of data capably. Sharding is a process in MongoDB used to horizontally scale the data across multiple servers when the size of data increases.

3) Availability

Data is highly available with MongoDB as it makes multiple copies of the same data and sends copies of data across different servers. In case any server fails, data can be retrieved from another server without delay.

4) Flexibility

MongoDB can easily be combined with different Database Management Systems, both SQL and NoSQL types. Document-oriented structure makes MongoDB schema dynamically flexible and different types of data can be easily stored and manipulated.

To learn more about MongoDB, click this link.

What is Python?

MongoDB PIP Install: Python Logo
Image Source

Python is a versatile general-purpose Programming Language. Its small learning curve coupled with its robustness has made it one of the most popular Programming Languages ​​today. It is the go-to choice of developers for Website and Software Development, Automation, Data Analysis, Data Visualization, and much more. Moreover, its straightforward syntax allows Accountants, Scientists to utilize it for daily tasks. The Python Programming Language serves as the key integral tool in the field of Data Science for performing complex Statistical Calculations, creating Machine Learning Algorithms, etc. 

Python Programming Language is also renowned for its ability to generate a variety of Data Visualizations like Bar Charts, Column Charts, Pie Charts,  and 3D Charts. Furthermore, it offers a rich set of libraries that facilitates advanced Machine Learning programs in a faster and simpler manner. 

Key Features of Python

MongoDB PIP Install: Python Features
Image Source

The following features are responsible for Python Programming Language’s popularity today:

  • Beginner Friendly: The Python Programming Language offers a hassle-free environment for developers. Its straightforward workflow is suitable for everyone and entry-level coders are drawn to it. Moreover, you can use and distribute its open-source codes for commercial purposes free of cost.
  • Robust Applications: Its simple syntax operates on natural human-readable language making it the go-to choice of projects on Python Programming Language, which is faster as compared to other Programming Languages. Furthermore, its versatile nature makes it the ideal choice for Web Development and Machine Learning projects.
  • Large Communities: Due to Python’s immense popularity, a huge active community of programmers is available online that contributes to this language’s modules and libraries. Moreover, this vast support community is ready to help in case you or any other coder gets stuck in a programming issue. You can easily get suggestions and solutions by posting your issue on these community pages.

You can understand more about the Python Programming Language by visiting here.

Simplify MongoDB ETL with Hevo’s No-code Data Pipeline

A fully managed No-code Data Pipeline platform like Hevo Data helps you integrate and load data from 100+ different sources (including 40+ free sources) such as MongoDB to a Data Warehouse or Destination of your choice in real-time in an effortless manner. Hevo with its minimal learning curve can be set up in just a few minutes allowing the users to load data without having to compromise performance. Its strong integration with umpteenth sources allows users to bring in data of different kinds in a smooth fashion without having to code a single line. 

Its completely automated pipeline offers data to be delivered in real-time without any loss from source to destination. Its fault-tolerant and scalable architecture ensure that the data is handled in a secure, consistent manner with zero data loss and supports different forms of data. The solutions provided are consistent and work with different Business Intelligence (BI) tools as well.

Get Started with Hevo for Free

Check out why Hevo is the Best:

  • Secure: Hevo has a fault-tolerant architecture that ensures that the data is handled in a secure, consistent manner with zero data loss.
  • Schema Management: Hevo takes away the tedious task of schema management & automatically detects the schema of incoming data and maps it to the destination schema.
  • Minimal Learning: Hevo, with its simple and interactive UI, is extremely simple for new customers to work on and perform operations.
  • Hevo Is Built To Scale: As the number of sources and the volume of your data grows, Hevo scales horizontally, handling millions of records per minute with very little latency.
  • Incremental Data Load: Hevo allows the transfer of data that has been modified in real-time. This ensures efficient utilization of bandwidth on both ends.
  • Live Support: The Hevo team is available round the clock to extend exceptional support to its customers through chat, email, and support calls.
  • Live Monitoring: Hevo allows you to monitor the data flow and check where your data is at a particular point in time.
Sign up here for a 14-Day Free Trial!

Python MongoDB PIP Installation using PyMongo 

A Python-MongoDB combination can be a good technology stack. It will make it easy for you to perform various MongoDB tasks from Python. You can also take advantage of data analytics tools and libraries compatible with Python to analyze your MongoDB data. 

Python is also a good tool for Data Visualization. It is compatible with libraries such as Seaborn and Matplotlib which are good for data visualization. This will make it even easier for you to extract insights from your MongoDB data. 

To establish a connection from Python to MongoDB, you can use PyMongo, which is a Python wrapper created for MongoDB. By using Python and MongoDB, you will be able to create, update, and query MongoDB collections using a few lines of code. 

1) Install MongoDB

The process of MongoDB PIP Installation will start by installing MongoDB.

  • Step 1: You can visit the downloads page of the official MongoDB website using the following URL:
  • Step 2: Download the MSI package for the MongoDB community server. 
MongoDB PIP Install: Download MongoDB
Image Source
  • Step 3: Double-click the downloaded MSI package to start the installation process. MongoDB will guide you through simple on-screen instructions until the installation process completes.
  • Step 4: In most cases, you will only be required to click a “Next” button and you will be moved to the next step. 
  • Step 5: Ensure that you choose a complete installation instead of a custom installation. You will also be prompted to accept the terms of the license agreement.
MongoDB PIP Install: Installing MongoDB
Image Source: Self
  • Step 6: Once the installation process completes, you should verify whether the process was successful.
  • Step 7: Find the mongo.exe file under program files and double-click it. It should open the Mongo Shell as shown below:
Image Source: Self
  • Step 8: The output on the shell shows that the MongoDB Server is running. It confirms that the installation of MongoDB was successful. If you get errors, you can get help from online MongoDB forums. 
  • Step 9: To access the Mongo Shell from the command prompt of your OS, you may have to set the path environment variable. 

If you are using a Linux distribution such as Ubuntu, you can install MongoDB via the terminal. First, update the system by running the following command:

sudo apt-get update

Then install MongoDB by running the following command:

sudo apt-get install -y mongodb-org

The command will install MongoDB in your Linux system. 

2) Install Python

Before you get into installing Python MongoDB PIP install PyMongo, you have to install Python.

Now that you have MongoDB, you can go ahead and install Python. Most Linux distributions come installed with Python, so you don’t have to worry. Windows users should download and install Python on their computers. 

  • Step 1: Visit the downloads page of Python’s official website on the following URL: There are different versions for various Operating Systems. You can get the latest version of Python for your operating system.
  • Step 2: Once the download process completes, double-click the installer to start the installation process. You will be guided through simple on-screen instructions on how to install Python until the process completes. 

3) MongoDB pip Install PyMongo

In the process of MongoDB PIP Installation, you have to install PyMongo.

PyMongo is the driver to help you run interactions between Python and MongoDB. There are many other drivers, but PyMongo is the official Python driver for MongoDB. Python comes with a Package manager known as pip which you can use to install PyMongo. So, if you have installed Python, you already have pip.

You can run this command to install PyMongo:

pip install pymongo

The command should install PyMongo in your Python environment. 

That is how you can install PyMongo using pip. Next, you will be demonstrating how to use the PyMongo driver to connect Python to MongoDB. 

4) Use PyMongo to Connect Python to MongoDB

Suppose you want to verify that everything is okay by connecting Python and MongoDB using PyMongo. And you want to know more about the databases running on our MongoDB installation. Then you can connect to MongoDB and issue a query to return this information. 

  • Step 1: First, import PyMongo using Python’s import statement:
import pymongo
  • Step 2: Now, you can write and run the following script:
conn = pymongo.MongoClient("mongodb://localhost:27017/")

The script should return the list of databases running on your MongoDB Server as shown below:

Image Source: Self

That is how you can undergo Python MongoDB pip installation using PyMongo. 


In this article, you have learned about MongoDB PIP Installation using PyMongo. This article also provided information on MongoDB, Python, their key features, and the steps for Python MongoDB PIP Installation using PyMongo in detail. For further information on MongoDB Replica Set Configuration, MongoDB Compass Windows Installation, MongoDB Count Method, you can visit the following links.

Hevo Data, a No-code Data Pipeline provides you with a consistent and reliable solution to manage data transfer between a variety of sources and a wide variety of Desired Destinations with a few clicks.

Visit our Website to Explore Hevo

Hevo Data with its strong integration with 100+ data sources (including 40+ Free Sources) allows you to not only export data from your desired data sources & load it to the destination of your choice but also transform & enrich your data to make it analysis-ready. Hevo also allows integrating data from non-native sources using Hevo’s in-built Webhooks Connector. You can then focus on your key business needs and perform insightful analysis using BI tools. 

Want to give Hevo a try?

Sign Up for a 14-day free trial and experience the feature-rich Hevo suite first hand. You may also have a look at the amazing price, which will assist you in selecting the best plan for your requirements.

Share your experience of understanding MongoDB PIP Installation using PyMongo in the comment section below! We would love to hear your thoughts.

Nicholas Samuel
Freelance Technical Content Writer, Hevo Data

Skilled in freelance writing within the data industry, Nicholas is passionate about unraveling the complexities of data integration and data analysis through informative content for those delving deeper into these subjects.

No-code Data Pipeline for MongoDB