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Enthought Canopy
Enthought Canopy
  • One-Click Python Deployment
  • Analysis Environment
  • Development Platform
  • Integrated Training on Demand
Enthought PyXLL


The Power of Python in Excel

  • Create powerful Excel add-ins
  • Easily deploy to others
  • Mitigate risk through version control
Enthought Python Training on Demand
Enthought Training on Demand

Enthought Python Training on Demand takes our proven Python curriculum taught to thousands of scientists, engineers and analysts over the last decade and delivers it in a convenient, flexible online format.

Enthought Scientific Software Consulting and Application Development

Software Consulting and
Application Development

Our data analysis, data visualization, and data processing expertise can help you:

  • Turn ideas into results
  • Translate data into actionable insight
  • Fast track innovation

Enthought's mission is to significantly improve the way scientific computing is accomplished by providing powerful tools for quantitative data analysis and visualization.


Python Consulting and Application Development

For more than a decade Enthought has helped solve technical computing challenges in industries such as energy, industrial control, consumer products, technology, finance, aerospace, and more. See how we can help you too.

See sample custom Python applications


Corporate Python Training

Corporate Python Training

Have a team transitioning to Python from another language such as R or MATLAB? Need to level the Python skill set across a group for better productivity?

Concurrency and Parallelism in Python

NEW! Concurrency and Parallelism in Python

In this one-day workshop, we explain how the GIL works (and why), introduce a number of concurrency techniques that allow you to increase the computational performance of Python programs, and discuss common pitfalls and best practices.

NEW! Pandas Crash Course

Pandas provides a powerful toolset for working with data - including reading and writing files in a variety of formats, data cleaning, data exploration, manipulating and transforming data, data modeling and analysis, and visualization.


NEW! Enthought Canopy Data Import Tool

This new tool allows you to easily import .csv / structured text files and perform common (and time-consuming!) data manipulation and cleaning tasks through a graphical interface, while capturing the interaction as Python (Pandas) code for re-use. See the new features and download a free 7 day trial.

PyXLL 3.0: New Real Time Data Stream Capabilities and More

PyXLL is an Excel add-in that enables you to extend Excel using nothing but Python code. The new PyXLL 3.0 release adds even more features, including the ability to turn an Excel spreadsheet into a live data stream dashboard and Excel ribbon integration for an intuitive user experience. See the new features in PyXLL 3.0 and download a free 30 day trial.


Canopy Geoscience
Data Analysis Environment

Canopy Geoscience integrates data I/O, visualization, and programming in an easy-to-use environment. Geoscientific data is accessible from an embedded Python environment, and can be analyzed, modified, and immediately visualized with simple Python commands. See the latest release details.

Virtual Core
CT and Photo Core Analysis

Virtual Core automates aspects of core description for geologists and petrophysicists, drastically reducing the time and effort required for core description. Its unified visualization interface displays cleansed whole-core CT data alongside core photographs and well logs. See the latest release details.


See playlist of talks and tutorials from SciPy 2015

Scientific Computing with Python Conference, July 11-17

Register Now

SciPy 2016, the 15th annual Scientific Computing with Python conference, will be held July 11-17, 2016 in Austin, Texas. The annual SciPy Conference brings together over 650 participants from industry, academia, and government to showcase their latest projects, learn from skilled users and developers, and collaborate on code development.

The full program will consist of 2 days of tutorials (July 11-12), 3 days of talks (July 13-15), and 2 days of developer sprints (July 16-17). Learn more on the conference website.

Major topic tracks include: Scientific Computing in Python, Python in Data Science, and High Performance Computing. Mini-symposia will include the applications of Python in: Earth and Space Science, Engineering, Medicine and Biology, Social Sciences, Special Purpose Databases, Case Studies in Industry, Education, Reproducibility.

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