Tag Archives: Enthought Deployment Server

Webinar: A Tour of Enthought’s Latest Enterprise Python Solutions

When: Thursday, July 20, 2017, 11-11:45 AM CT (Live webcast)

What: A comprehensive overview and live demonstration of Enthought’s latest tools for Python for the enterprise with Enthought’s Chief Technical & Engineering Officer, Didrik Pinte

Who Should Attend: Python users (or those supporting Python users) who are looking for a universal solution set that is reliable and “just works”; scientists, engineers, and data science teams trying to answer the question “how can I more easily build and deploy my applications”; organizations looking for an alternative to MATLAB that is cost-effective, robust, and powerful

REGISTER  (if you can’t attend we’ll send all registrants a recording)


For over 15 years, Enthought has been empowering scientists, engineers, analysts, and data scientists to create amazing new technologies, to make new discoveries, and to do so faster and more effectively than they dreamed possible. Along the way, hand in hand with our customers in aerospace, biotechnology, finance, oil and gas, manufacturing, national laboratories, and more, we’ve continued to “build the science tools we wished we had,” and share them with the world.

For 2017, we’re pleased to announce the release of several major new products and tools, specifically designed to make Python more powerful and accessible for users like you who are building the future of science, engineering, artificial intelligence, and data analysis.

WHAT YOU’LL SEE IN THE WEBINAR

In this webinar, Enthought’s Chief Technical & Engineering Officer will share a comprehensive overview and live demonstration of Enthought’s latest products and how they provide the foundation for scientific computing and artificial intelligence applications with Python, including:

We’ll also walk through  specific use cases so you can quickly see how Enthought’s Enterprise Python tools can impact your workflows and productivity.

REGISTER  (if you can’t attend we’ll send all registrants a recording)


Presenter: Didrik Pinte, Chief Technical & Engineering Officer, Enthought

 

 

 

Related Blogs:

Blog: Enthought Announces Canopy 2.1: A Major Milestone Release for the Python Analysis Environment and Package Distribution (June 2017)

Blog: Enthought Presents the Canopy Platform at the 2017 American Institute of Chemical Engineers (AIChE) Spring Meeting (April 2017)

Blog: New Year, New Enthought Products (Jan 2017)

Product pages:

Enthought Announces Canopy 2.1: A Major Milestone Release for the Python Analysis Environment and Package Distribution

Python 3 and multi-environment support, new state of the art package dependency solver, and over 450 packages now available free for all users

Enthought Canopy logoEnthought is pleased to announce the release of Canopy 2.1, a significant feature release that includes Python 3 and multi-environment support, a new state of the art package dependency solver, and access to over 450 pre-built and tested scientific and analytic Python packages completely free for all users. We highly recommend that all current Canopy users upgrade to this new release.

Ready to dive in? Download Canopy 2.1 here.


For those currently familiar with Canopy, in this blog we’ll review the major new features in this exciting milestone release, and for those of you looking for a tool to improve your workflow with Python, or perhaps new to Python from a language like MATLAB or R, we’ll take you through the key reasons that scientists, engineers, data scientists, and analysts use Canopy to enable their work in Python.

First, let’s talk about the latest and greatest in Canopy 2.1!

  1. Support for Python 3 user environments: Canopy can now be installed with a Python 3.5 user environment. Users can benefit from all the Canopy features already available for Python 2.7 (syntax checking, debugging, etc.) in the new Python 3 environments. Python 3.6 is also available (and will be the standard Python 3 in Canopy 2.2).
  2. All 450+ Python 2 and Python 3 packages are now completely free for all users: Technical support, full installers with all packages for offline or shared installation, and the premium analysis environment features (graphical debugger and variable browser and Data Import Tool) remain subscriber-exclusive benefits. See subscription options here to take advantage of those benefits.
  3. Built in, state of the art dependency solver (EDM or Enthought Deployment Manager): the new EDM back end (which replaces the previous enpkg) provides additional features for robust package compatibility. EDM integrates a specialized dependency solver which automatically ensures you have a consistent package set after installation, removal, or upgrade of any packages.
  4. Environment bundles, which allow users to easily share environments directly with co-workers, or across various deployment solutions (such as the Enthought Deployment Server, continuous integration processes like Travis-CI and Appveyor, cloud solutions like AWS or Google Compute Engine, or deployment tools like Ansible or Docker). EDM environment bundles not only allow the user to replicate the set of installed dependencies but also support persistence for constraint modifiers, the list of manually installed packages, and the runtime version and implementation. Continue reading

New Year, New Enthought Products!

We’ve had a number of major product development efforts underway over the last year, and we’re pleased to share a lot of new announcements for 2017:

A New Chapter for the Enthought Python Distribution (EPD):
Python 3 and Intel MKL 2017

In 2004, Enthought released the first “Python: Enthought Edition,” a Python package distribution tailored for a scientific and analytic audience. In 2008 this became the Enthought Python Distribution (EPD), a self-contained installer with the "enpkg" command-line tool to update and manage packages. Since then, over a million users have benefited from Enthought’s tested, pre-compiled set of Python packages, allowing them to focus on their science by eliminating the hassle of setting up tools.

Enthought Python Distribution logo

Fast forward to 2017, and we now offer over 450 Python packages and a new era for the Enthought Python Distributionaccess to all of the packages in the new EPD is completely free to all users and includes packages and runtimes for both Python 2 and Python 3 with some exciting new additions. Our ever-growing list of packages includes, for example, the 2017 release of the MKL (Math Kernel Library), the fruit of an ongoing collaboration with Intel.

The New Enthought Deployment Server:
Secure, Onsite Access to EPD and Private Packages

enthought-deployment-server-centralized-management-illustration-v2

For those who are interested in having a private copy of the Enthought Python Distribution behind their firewall, as well as the ability to upload and manage internal private packages alongside it, we now offer the Enthought Deployment Server, an onsite version of the server we have been using for years to serve millions of Python packages to our users.

enthought-deployment-server-logoWith a local Enthought Deployment Server, your private copy will periodically synchronize with our master repository, on a schedule of your choosing, to keep you up to date with the latest releases. You can also set up private package repositories and control access to them using your existing LDAP or Active Directory service in a way that suits your organization.  We can even give you access to the packages (and their historical versions) inside of air-gapped networks! See our webinar introducing the Enthought Deployment Server.

Command Line Access to the New EPD and Flat Environments
via the Enthought Deployment Manager (EDM)

In 2013, we expanded the original EPD to introduce Enthought Canopy, coupling an integrated analysis environment with additional features such as a graphical package manager, documentation browser, and other user-friendly tools together with the Enthought Python Distribution to provide even more features to help “make science and analysis easy.”

With its MATLAB-like experience, Canopy has enabled countless engineers, scientists and analysts to perform sophisticated analysis, build models, and create cutting-edge data science algorithms. The all-in-one analysis platform for Python has also been widely adopted in organizations who want to provide a single, unified platform that can be used by everyone from data analysts to software engineers.

But we heard from a number of you that you also still wanted the capability to have flat, standalone environments not coupled to any editor or graphical tool. And we listened!  

enthought-deployment-manager-cli-screenshot2So last year, we finished building out our next-generation command-line tool that makes producing flat, standalone Python environments super easy.  We call it the Enthought Deployment Manager (or EDM for short), because it’s a tool to quickly deploy one or multiple Python environments with the full control over package versions and runtime environments.

EDM is also a valuable tool for use cases such as command line deployment on local machines or servers, web application deployment on AWS using Ansible and Amazon CloudFormation, rapid environment setup on continuous integration systems such as Travis-CI, Appveyor, or Jenkins/TeamCity, and more.

Finally, a new state-of-the-art package dependency solver included in the tool guarantees the consistency of your environment, and if your workflow requires switching between different environments, its sandboxed architecture makes it a snap to switch contexts.  All of this has also been designed with a focus on providing robust backward compatibility to our customers over time.  Find out more about EDM here.

Enthought Canopy 2.0:
Python 3 packages and New EDM Back End Infrastructure

Enthought Canopy LogoThe new Enthought Python Distribution (EPD) and Enthought Deployment Manager (EDM) will also provide additional benefits for Canopy.  Canopy 2.0 is just around the corner, which will be the first version to include Python 3 packages from EPD.

In addition, we have re-worked Canopy’s graphical package manager to use EDM as its back end, to take advantage of both the consistency and stability of the environments EDM provides, as well as its new package dependency solver.  By itself, this will provide a big boost in stability for users (ever found yourself wrapped up in a tangle of inconsistent package versions?).  Alongside the conversion of Canopy’s back end infrastructure to EDM, we have also included a substantial number of stability improvements and bug fixes.

Canopy’s Graphical Debugger adds external IPython kernel debugging support

On the integrated analysis environment side of Canopy, the graphical debugger and variable browser, first introduced in 2015, has gotten some nifty new features, including the ability to connect to and debug an external IPython kernel, in addition to a number of stability improvements.  (Weren’t aware you could connect to an external process?  Look for the context menu in the IPython console, use it to connect to the IPython kernel running, say, a Jupyter notebook, and debug away!)

Canopy Data Import Tool adds CSV exports and input file templates

Enthought Canopy Data Import ToolAlso, we’ve continued to add new features to the Canopy Data Import Tool since its initial release in May of 2016. The Data Import Tool allows users to quickly and easily import CSVs and other structured text files into Pandas DataFrames through a graphical interface, manipulate the data, and create reusable Python scripts to speed future data wrangling.

The latest version of the tool (v. 1.0.9, shipping with Canopy 2.0) has some nice new features like CSV exporting, input file templates, and more. See Enthought’s blog for some great examples of how the Data Import Tool speeds data loading, wrangling and analysis.

What to Look Forward to in 2017

So where are we headed in 2017?  We have put a lot of effort into building a strong foundation with our core suite of products, and now we’re focused on continuing to deliver new value (our enterprise users in particular have a number of new features to look forward to).  First up, for example, you can look for expanded capabilities around Python environments, making it easy to manage multiple environments, or even standardize and distribute them in your organization.  With the tremendous advancements in our core products that took place in 2016, there are a lot of follow-on features we can deliver. Stay tuned for updates!

Have a specific feature you’d like to see in one of Enthought’s products? E-mail our product team at canopy.support@enthought.com and tell us about it!

Webinar: Solving Enterprise Python Deployment Headaches with the New Enthought Deployment Server

See a recording of the webinar:

Built on 15 years of experience of Python packaging and deployment for Fortune 500 companies, the NEW Enthought Deployment Server provides enterprise-grade tools groups and organizations using Python need, including:

  1. Secure, onsite access to a private copy of the proven 450+ package Enthought Python Distribution
  2. Centralized management and control of packages and Python installations
  3. Private repositories for sharing and deployment of proprietary Python packages
  4. Support for the software development workflow with Continuous Integration and development, testing, and production repositories

In this webinar, Enthought’s product team demonstrates the key features of the Enthought Deployment Server and how it can take the pain out of Python deployment and management at your organization.

Who Should Watch this Webinar:

If you answer “yes” to any of the questions below, then you (or someone at your organization) should watch this webinar:

  1. Are you using Python in a high-security environment (firewalled or air gapped)?
  2. Are you concerned about how to manage open source software licenses or compliance management?
  3. Do you need multiple Python environment configurations or do you need to have consistent standardized environments across a group of users?
  4. Are you producing or sharing internal Python packages and spending a lot of effort on distribution?
  5. Do you have a “guru” (or are you the guru?) who spends a lot of time managing Python package builds and / or distribution?

In this webinar, we demonstrate how the Enthought Deployment Server can help your organization address these situations and more.