Our Biggest ActivePython Release EVER

ActivePython Release Data Science and Web App Dev Packages

Today is a great day for ActivePython users. We've just included another 200 packages in our distribution making it the most comprehensive release of ActivePython to date. It's like we have a microcosm of the whole ecosystem in our distribution. There are over one hundred thousand Python packages and we have picked the best two hundred. You don't need to go looking for what's the best crypto library or web framework...you can now find it in ActivePython. This new distribution is available starting with 2.7.13 and 3.5.3 on all major platforms with 3.6 to come out later in the year.

In the past three months, we've taken our distributions and brought them up to date with the latest versions the Python core team has produced in the 2.7, 3.5 and 3.6 series. On top of that, we've been able to expand our offering to our users since we added many of the top 10 packages along with the best testing and code quality packages back in January of this year. However, in this release we've greatly increased the breadth of packages that we think are the best in the ecosystem, producing a distribution that both the community and commercial users will enjoy.

Over 200 Packages Included: Data Science, Big Data, Web App Dev + More

While I won't list all 200 packages, I've highlighted some at the end of the blog. This ActivePython distribution release bundles the most popular packages for data science, big data, web application development, security, as well as developer utility packages. In addition, as we do in all our releases, we ship the latest OpenSSL version. We've also provided the fantastic cryptography library which includes great recipes for many of your security requirements around application development. We know how important security is to our customers so keeping our distribution up to date is essential.

Python covers a lot of ground, but for any major use case we'll have the package you need in this release. That's the ultimate goal--to give ActivePython users the latest, vetted, and stable packages that are in the Python ecosystem for almost any major use case. Whether you're building a web application, transforming data, connecting to API services, or deploying your app on AWS, this distribution has your covered. You get that once installed, out-of-the-box experience--deploy to your local servers, desktop, cloud, or put it in a Docker container. There are a myriad of ways you can consume ActivePython, but the nice thing is that you get a consistent experience across all major platforms (and Big Iron too!).

Oh did we mention our upgraded offline and online documentation? We’ve brought in all the documentation for the language combined with the release notes, and links to sources of documentation for all the packages we ship. All of this is in an easy to consume HTML format available online or offline.

Going Forward

Going forward we are looking to expand our package list for more use cases. There are some really great advances in machine learning that we want to include as well as offering more in the visualization space. On top of that, we will also bundle more web frameworks, database connectors, and web services packages.

Like every ecosystem and language, change is constantly happening so we're always staying on top of latest trends...learning about what the best practices and best packages are in the ecosystem. We put in the groundwork so when you need to solve that next big problem, we’ve got the best-in-class, safe, appropriately licensed package to help you build the solution. We’ve set a very rapid cadence for ActivePython in 2017, with multiple releases in the first quarter, and we are following that up with multiple releases in the second quarter. If you are looking for a solid Python distribution that moves with the times, ActivePython has you covered.

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Check out some of the packages included in this release!

Data Science/Big Data

  • pandas (data analysis)
  • NumPy (multi-dimensional arrays)
  • SciPy (algorithms to use with numpy)
  • HDF5 (store & manipulate data)
  • Matplotlib (data visualization)
  • IPython (powerful shell)
  • scikit-learn (machine learning)

 

  • PyTables (managing HDF5 datasets)
  • HDFS (C/C++ wrapper for Hadoop)
  • pymongo (MongoDB driver)
  • SQLAlchemy (Python SQL Toolkit)
  • redis (Redis access libraries)
  • pyMySQL (MySQL connector)

Web Application Development

  • Django (web framework)
  • Flask (web framework - microservices)
  • Tornado (web framework and networking)
  • requests (web dev library)
  • AWS SDK (Amazon cloud)

Code Quality/Testing

  • pytest (testing)
  • nose (testing)
  • pyflakes (code quality)
  • flake8 (code quality)
  • coverage (test coverage)

Security:

  • cryptography (recipes and primitives)
  • pyOpenSSL (python interface to OpenSSL)
  • passlib (password hashing)
  • requests-oauthlib (Oauth support)
  • ecdsa (cryptographic signature)

Dev Tools:

  • pytz (time zone library)
  • PyYAML(YAML support)
  • py (code gen, API control, ini file parsing)
  • lxml (processing XML/HTML)
  • cffi (C code interface)