Python Consulting and Application Development

For more than fifteen years, Enthought has helped solve technical computing challenges in industries such as energy, manufacturing, biotechnology, aerospace, consumer products, technology, finance, and more. See how we can help you too.

Training Courses

Since 2008, Enthought has trained thousands of scientists, engineers, data scientists, analysts, developers, and other technical professionals throughout the world in the Python programming language.

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? We specialize in corporate Python training.

2017 Open Training Classes

Register for one of our 2017 open training classes. Classes include:
Python for Data Science, Python for Scientists and EngineersPython for Data Analysis, Python Foundations, and the Pandas Mastery Workshop.

Pandas Mastery Workshop

Pandas provides a powerful toolset for working with data – including reading and writing files, data cleaning, data exploration, manipulating and transforming data, data modeling and analysis, and visualization.

Enthought Software Products

Enthought Deployment Server

The Enthought Deployment Server provides enterprise-grade tools that groups and organizations using Python need, including: secure, onsite access to a private copy of the proven 450+ package Enthought Python Distributioncentralized management and control of packages and Python installations, private repositories for sharing and deployment of proprietary Python packages, and support for the software development workflow with Continuous Integration and development, testing, and production repositories.

Python Integration Toolkit for LabVIEW

LabVIEW is a software platform made by National Instruments, used widely in industry for test and measurement applications. Now, Enthought’s new Python Integration Toolkit for LabVIEW seamlessly brings the power of the Python ecosystem of scientific and engineering tools to LabVIEW. See how it works and download a free 30 day trial.

Python for Excel (PyXLL)

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 Data Import Tool

The Canopy Data Import 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.

Enthought Oil & Gas Software

Enthought’s oil & gas software allows easy exploration of your data in 2D or 3D. Data is accessible from an embedded Python environment, and can be analyzed, modified, and immediately visualized using simple Python commands.

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.

Enthought News & Events

SciPy 2017, the 16th annual Scientific Computing with Python conference, was held on July 10-16, 2017 in Austin, Texas with participants from industry, academia, and government who showcased their latest projects, learned from skilled users and developers, and collaborated in code development.

Major topic tracks included: Machine Learning & AI and  SciPy Tools. Mini-Symposia tracks included: Astronomy; Biology, Biophysics and Biostatistics; Computational Science and Numerical Techniques; Data Science; Earth, Ocean and Geoscience; Materials Science and Engineering; Neuroscience; and Open Data and Reproducibility.