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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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.
The first port of call for many developers is Python.org, 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 Python.org 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 Python.org, 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, 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, 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.
To give you a more direct comparison, let's tabulate the characteristics of these three distributions:
|Pre-built Distributions||Python cores||Multiple ActivePython distributions||Anaconda/MiniConda|
|Usage||General-purpose||General-purpose||Data Science focused|
|Package Repository||Python Package Index (PyPI)||ActiveState's repository||Anaconda's repository|
|Pricing||Free||Free with paid options for enterprises||Free (Anaconda Individual Edition), Paid (Anaconda Team Edition, Enterprise Edition)|
The choice of Python distribution primarily depends on the nature of your project.
Python from Python.org 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.
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 python.org, on the other hand, provides the core Python language and relies on third-party package installations.
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.
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.