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What is the Difference? Python vs ActivePython vs Anaconda Compared

Python Distributions Compared: Python vs ActivePython vs Anaconda

Diving into the Python world, one might come across a variety of distributions: Python, ActivePython, and Anaconda, to name a few. Each one has its own set of perks and nuances, but how do you decide which is the best fit for your project? Let's dissect these Python distributions, weigh their pros and cons, and hopefully, help you make an informed choice.

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What are Python Distributions and Why Should I Care?

Before we deep-dive into the comparison of ActivePython, Python, and Anaconda, it's crucial to understand what exactly a Python distribution is. A Python distribution is a version of Python that comes bundled with additional packages and tools to simplify and enhance your Python coding experience. These packages can range from general-purpose libraries to data science-specific modules and everything in between.

Python: The Original Core

The first port of call for many developers is, the home of the Python Software Foundation. They are responsible for creating and releasing new versions of Python. This distribution forms the backbone of many applications due to its versatility and wide range of applications.

One of the key aspects of Python from is the Python Package Index (PyPI), a repository of software developed and shared by the Python community. The Python core itself is typically obtained from, with third-party packages sourced from PyPI.

Here's a simple example of installing a package (numpy) from PyPI using pip, Python's package manager:

pip install numpy

ActivePython: Streamlined Startup for Commercial Applications

ActivePython, by ActiveState, is a pre-built version of Python that comes bundled with many popular packages from PyPI. This distribution's main selling point is its capacity to speed up and simplify project startup, making it a popular choice for commercial applications.

ActivePython also offers its own package manager, the State Tool. The State Tool is currently in beta, but it adds an additional layer of convenience for developers.

Let's look at an example of how to install a package using the State Tool:

state packages add ActiveState/ActivePython-3.8/numpy

Anaconda: A Data Scientist's Best Friend

Anaconda, like ActivePython, is a pre-built Python distribution that comes packaged with several popular Python libraries. Anaconda, however, specifically targets data science applications.

Anaconda's unique selling point is its focus on data science and machine learning applications. It also utilizes Conda, a package manager that simplifies the installation of several data science packages. For instance, installing numpy using Conda would be:

conda install numpy

Anaconda's pricing structure has been a point of discussion recently, with changes leaning towards a cost for their curated open source distribution. Despite this, for non-commercial data science applications, Anaconda's Python ecosystem remains free to use.

ActivePython vs Python vs Anaconda: A Tabular Comparison

To give you a more direct comparison, let's tabulate the characteristics of these three distributions:

Pre-built DistributionsPython coresMultiple ActivePython distributionsAnaconda/MiniConda
UsageGeneral-purposeGeneral-purposeData Science focused
Package ManagerPipStateTool
Package RepositoryPython Package Index (PyPI)ActiveState's repositoryAnaconda's repository
PricingFreeFree with paid options for enterprisesFree (Anaconda Individual Edition), Paid (Anaconda Team Edition, Enterprise Edition)

Which One Should You Choose?

The choice of Python distribution primarily depends on the nature of your project.

  • Python from is ideal for beginners and general-purpose programming. It provides a clean and minimal setup, allowing developers to manually pick and choose the packages they want.

  • ActivePython is a better choice for commercial applications, especially when you need a fast start-up. With its pre-built distributions, it can save time and effort in setting up complex development environments.

  • Anaconda is perfect for data science projects, offering many pre-installed libraries for data analysis and machine learning. It is also beneficial for academics and researchers working in the field of data science.

Remember, there's no definitive answer as to which distribution is better. The best one for you depends on your specific needs, your level of expertise, the kind of project you're working on, and the tools you require. Therefore, it's recommended to spend some time understanding the specificities of each distribution and matching them to your needs before making a decision.

Frequently Asked Questions

1. What is the difference between ActivePython and Python?

ActivePython is a version of Python provided by ActiveState, bundled with additional packages and libraries. It offers convenience and streamlined setup, making it suitable for commercial applications. Python from, on the other hand, provides the core Python language and relies on third-party package installations.

2. Is ActivePython necessary if I have already installed Python?

ActivePython is not essential if you already have Python installed. It is an alternative distribution that provides additional packages and libraries. However, if you require a simplified setup or support for specific platforms, ActivePython can be a valuable choice.

3. How does ActivePython compare to Anaconda?

ActivePython and Anaconda serve different purposes. ActivePython focuses on commercial applications, providing convenience and support. Anaconda, on the other hand, is tailored for data science applications, offering a comprehensive ecosystem with pre-installed libraries. The choice between them depends on your specific project requirements and use case.