Enthought Canopy is a comprehensive Python analysis environment that provides easy installation of over 450 core scientific analytic and Python packages, creating a robust platform you can explore, develop, and visualize on. In addition to its pre-built, tested Python distribution, Enthought Canopy has valuable tools for iterative data analysis, visualization and application development including:
Plus, Canopy works seamlessly with the NEW Enthought Python Training on Demand for a hands-on, interactive learning experience.
A comprehensive, Python-based analysis desktop and Python distribution, Canopy provides an open, intuitive environment for scientific and analytic computing. Since it's Python, your algorithms, scripts and programs will never be locked into a proprietary language. And with the analysis desktop, data analysis, scripting and plotting are more straightforward.
Python functionality spans from desktop algorithm development and testing to web server application development.
With the Canopy desktop and Python distribution, data ingestion, manipulation and analysis are simplified, and algorithm prototyping and testing are streamlined.
As a comprehensive Python-based analysis environment, Canopy puts powerful, yet cost-effective tools in the hands of analysts, scientists and engineers. As a robust application platform, it streamlines technical computing application development and deployment for your organization and for your customers.
With the popular, intuitive Python language and the comprehensive Canopy application platform, your organization can deploy new applications, algorithms and analysis tools much faster than with standard software languages and platforms. Users, especially power users, can extend and innovate with scripting and open platform APIs, driving the creation and sharing of innovative techniques and tools.
Unlike proprietary analysis languages and tools, Canopy offers the customized analytical environment we need, built on open source Python. Using it, we are able to research investment opportunities in an efficient and flexible manner.
I am thoroughly enjoying Canopy. I have been using it about 2 weeks, and it is far and away the best IDE I've found for Python (I've tested perhaps 12 in the past year). It has been especially helpful in prototyping my scientific computing research.
Canopy allows me the ability to inspect and plot the contents of my data structures as I craft the code to manipulate their contents. The Canopy pop-ups that appear when a function is entered have also saved me a lot of time and helpfully remind me how particular keyword arguments are named. A long time text editor Python coder, I am now an enthusiastic Canopy convert.
I wanted to let you know how pleased I am with your Enthought Canopy Python distribution. Most of my academic research requires large-scale data analysis on several clusters. After our last server upgrade I lost the functionality of many packages and spent hours, without any luck, trying to get it back up and running. Searching the web I came across Enthought, and I couldn't believe how easy it was to install with all my favorite packages! Thanks again and I will definitely be recommending your services to others in my field.
Formed in 2009, the Archive Team (not to be confused with the archive.org Archive-It Team) is a rogue archivist collective dedicated to saving copies of rapidly dying or deleted websites for the sake of history and digital heritage. The group is 100% composed of volunteers and interested parties, and has expanded into a large amount of related projects for saving online and digital history.
