We are pleased to announce the release of a new conda distribution for Python. This is a command line tool for installing and updating Python packages, and is intended to be an improvement over pip and easy_install, with better dependency resolution and simpler installation of binary extensions.
conda is open source, so you can inspect its contents, and because it has a large community, you can find help if you get stuck. But the main reason people use conda is that it makes complex package management tasks simple.
If you are new to Python, I recommend starting with Anaconda, which includes all the packages needed for scientific computing in Python in one convenient installer. If you already have Python installed, then simply type “conda install numpy” at the command line to get started.
We are excited to announce the release of a new conda distribution for Python, the cross-platform, language-agnostic package and environment manager. The first major release of conda is now available; this distribution includes many improvements over previous versions:
Simpler installation. Conda is now included with Anaconda and Miniconda.
Faster and more reliable than pip.
Fully support Python 2 and 3, plus many other languages.
Works on Windows, OS X, and Linux.
Conda is open source under the BSD license.
The Anaconda Distribution has always been free, and will remain free. This is a core value of ours. We also have and will continue to invest heavily in our open source community efforts through conda-forge, ${GITHUB_ORG}, anaconda.org, and more. None of this is changing.
Our goals for the new distribution are simple:
* **Make it easy to get started with Python**: It should be easier for people using Python for the first time to find and use key packages like NumPy, pandas, and Matplotlib; or for advanced users who want to install a large set of libraries quickly and easily without having to worry about compatibility issues between multiple packages.
* **Continuing to support existing users**: The new distribution should not break existing Anaconda users’ workflows or force them to learn how to do things a different way than they used to.
* **Supporting both Python 2 & 3**: Both versions of Python are still widely used today, especially in the scientific Python community, so our distribution needs to support both versions at least until 2020 (when Python 2 will reach its official End-of-Life).
We chose Conda as
A few people have asked me about a new Python distribution from Continuum Analytics. It’s called Anaconda, and it’s the new package manager for Python. The main advantage of Anaconda is that it brings a lot of value-added tools for data science to the Python ecosystem.
Anaconda is built on top of the conda package management system (more on what a package management system is in a second). I’ve been working with Continuum on conda since late 2012. While there are many good language-agnostic package managers out there (e.g., NPM, Ruby Gems), there hasn’t really been one for Python that was expressive enough to handle all of the needs of numerical and scientific computing.
Why do we need yet another Python distribution?
The main motivation behind Anaconda is that we needed a way to distribute our Python software at Continuum Analytics so that:
When we introduced the Python Package Distribution Guide a few months ago, we said that the next step would be to create a Python Package Distribution Tool. Today, we are announcing the first release of Anaconda, a new distribution of Python that will make package management and environment management easier for everyone who uses Python.
Conda is both a tool and a language. A new package management tool, conda, makes it easy to install and manage Python packages as well as packages in other programming languages like R. Conda is also a powerful language that can be used to solve complex problems with simple, declarative statements. For example:
conda install numpy scipy matplotlib ipython-notebook pandas
will install NumPy, SciPy, Matplotlib, IPython Notebook and Pandas on your system with one command. The same command can be used to create an environment containing these packages:
conda create -n myenv numpy scipy matplotlib ipython-notebook pandas
The result is an environment called myenv containing all of these packages. The environment can then be activated using:
source activate myenv
This will update your shell so that when you run python it runs within the my
Anaconda Distribution 5.2 was released on February 20th, 2018. This is the first version of Anaconda to include Python 3.6 by default, as well as some exciting new features. The open source release of Anaconda Distribution 5.2 includes conda 4.5 and Python 3.6 by default; other components such as NumPy, Pandas and Jupyter are also updated to their latest versions at the time of writing (February 2018).
The major change in this release is that we now include the conda-forge channel in our default search path for packages. This means that you can install the “bleeding edge” of thousands of open source projects by just typing “conda install
This means that it will be easier for you to find and use popular packages that are maintained by a group rather than an individual (for example, tqdm). It also means that if you need a package that is not yet available via conda-forge (for example, tensorflow), then it should be easy to create a new version of that package with conda-build and share it with your colleagues
The Python community has been plagued by package versioning and management issues for a long time, and this problem is only getting worse. In the past few years there has been a lot of effort put into improving the situation, with varying degrees of success.
Continuum Analytics is proud to announce Anaconda, a new distribution of the Python programming language that is designed to make life easier for both developers and users of Python-based applications. Unlike other distributions, we also release Anaconda into the public domain for free; no strings attached.
Among other features, Anaconda includes an easy-to-use graphical user interface that allows you to quickly install and manage packages from a wide variety of sources. It also comes with a built-in package manager, so you can manage your installations without ever leaving the application. In addition to those features, Anaconda has several other perks such as: