Python incorporates a built-in module venv (from 'virtual environment'), which can create isolated sets of Python versions and affiliated packages. Note, however, that it is possible to install multiple versions of Python system-wide with pyenv and use its plugin pyenv-virtualenv to manage virtual environments on Unix.īoth Python and Anaconda offer solutions for virtual environment creation and package management. You cannot install both versions system-wide, but you can create isolated environments for each of these projects, activate them, and start coding. For example, you may have two projects: one using pandas 0.25 and the other pandas 1.5. In data science, and generally in programming, we use virtual environments to isolate package dependencies used in different projects so that they don't conflict with each other. I advise installing Anaconda and using Anaconda Command Prompt to run the commands on Windows. Please note that I am using Linux as my primary system as it is highly convenient for programming projects (together with macOS), so on Windows, the following commands may differ. Furthermore, we will discuss the differences between conda varieties (i.e., miniconda and mamba). In this article, we'll discuss how to use Anaconda to manage and install packages as well as when to use pip or conda. Thus, the main difference between Python and Anaconda is that the former is a programming language and the latter is software to install and manage Python and other programming languages (such as R).

In contrast, with Anaconda you get Python, R, 250+ pre-installed packages, data science tools, and the graphical user interface Anaconda Navigator.

So, when you install Python, you get a programming language and pip (available in Python 3.4+ and Python 2.7.9+), which enables a user to install additional packages available on Python Package Index (or PyPi). It also provides an alternative package manager called conda. It uses pip (a recursive acronym for 'Pip Installs Packages' or 'Pip Installs Python') as its package manager to automate installation, update, and package removal.Īnaconda is a distribution (a bundle) of Python, R, and other languages, as well as tools tailored for data science (i.e., Jupyter Notebook and RStudio). Python is a multi-purpose programming language used in everything from from machine learning to web design.

What are the key differences between Python and Anaconda? Here's what you need to know.

How to use conda on mac