How to Install Python 3.9 with Conda: A Comprehensive Guide

In this blog, learn how to easily install Python 3.9 with Conda, empowering your data science endeavors with its versatility and rich library ecosystem.

Python is a versatile language that has become a staple in the data science community. Its simplicity and robust library ecosystem make it an excellent choice for data analysis, machine learning, and more. In this tutorial, we’ll guide you through the process of installing Python 3.9 using Conda, a popular package, dependency, and environment manager.

What is Conda?

Conda is an open-source, cross-platform package manager that simplifies the installation of software packages and their dependencies. It’s especially useful in the data science field, where managing complex dependencies can be a daunting task. Conda also allows you to create isolated environments, ensuring that different projects can have their own dependencies without interfering with each other.

Why Python 3.9?

Python 3.9 comes with several enhancements and optimizations that make it a great choice for data scientists. It includes features like the new parser, improved time zone support, and more flexible decorators, among others.

Step-by-Step Guide to Installing Python 3.9 with Conda

Step 1: Install Conda

If you haven’t installed Conda yet, you can download it from the official Anaconda website. Choose the version that suits your operating system (Windows, macOS, or Linux). After downloading, follow the instructions provided to install Conda on your machine.

Step 2: Update Conda

Before installing Python 3.9, it’s a good idea to ensure that Conda is up-to-date. Open your terminal or command prompt and type the following command:

conda update conda

Step 3: Create a New Conda Environment with Python 3.9

Now, let’s create a new Conda environment and install Python 3.9 in it. Replace myenv with the name you want for your environment:

conda create -n myenv python=3.9

Optionally, you can use the –yes flag to automatically approve the installation of dependencies:

conda create -n myenv python=3.9 --yes

Step 4: Activate the New Environment

To start using the new environment and Python 3.9, you need to activate it. Use the following command:

For Windows

conda activate myenv

For MacOS/Linux

source activate myenv

Step 5: Verify the Python Version

To ensure that Python 3.9 was installed correctly, you can check the Python version:

python --version

This command should return Python 3.9.x, confirming that Python 3.9 is installed and ready to use.

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Common Errors and Troubleshooting:

Conda command not found

If you encounter the error message stating "Conda command not found" it’s crucial to ensure that Conda is seamlessly integrated into your system’s PATH variable during the installation process. To resolve this issue, revisit the installation steps and confirm that the appropriate PATH modifications have been made.

Unable to activate the virtual environment

Take a moment to double-check the environment name you assigned during its creation. Typos or discrepancies in the name can prevent successful activation. If the environment was not created as intended, recreate it, ensuring accurate naming conventions.

PackageNotFound error during Python installation

To resolve this, cross-verify the Python version mentioned in the installation command with the available versions in the Conda repository. If there is a mismatch, update the installation command to use an available Python version, ensuring compatibility and successful installation.


Conda is a powerful tool that simplifies the management of software packages and their dependencies. With this guide, you should now be able to install Python 3.9 using Conda and start leveraging its features for your data science projects.

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