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.
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?
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.
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 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 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 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.
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.
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.