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Open Source Project of the Week – IPython
The IPython Notebook is a web-based interactive computational environment where
you can combine code execution, text, mathematics, plots and rich media into a single
document - ipython.org

The visual and interactive computing environment, IPython. Source: ipython.org
IPython, which is not an allusion to the Apple product line, takes upon itself the ambitious goal of making
scientific education, development and research environments more interactive and consequently more
reproducible. To put it more bluntly IPython (with a little help from its friends Sage and Mathics) offers an
open source community backed alternative to computing environments like Wolfram Mathematica, Maple and
Matlab.
Don’t believe us? Sample this
Fernando Perez, the creator of IPython wrote this blog detailing about the history behind its formation and
community, check it out here. The IPython github page is a great place to start getting acquainted with it as
well, be sure to check out their collection of notebooks published by the community. Some of my personal
favourites include the Machine Learning Tutorial by Hannes Schulz and Andreas Muller, Learn Data
Science byNitin Borwankar and Lectures on Quantum Mechanics and Quantum Optics using QuTiP by J.R.
Johnasson.
If you are working in scientific computing, computer science education, data science or research, IPython is
your friendly neighbourhood open source hero. So without much ado give IPython a test run today, and we
will be back next week with another prolific open source project.
Peace, Love and Open Source.

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Open source project of the week

  • 1. Open Source Project of the Week – IPython The IPython Notebook is a web-based interactive computational environment where you can combine code execution, text, mathematics, plots and rich media into a single document - ipython.org The visual and interactive computing environment, IPython. Source: ipython.org IPython, which is not an allusion to the Apple product line, takes upon itself the ambitious goal of making scientific education, development and research environments more interactive and consequently more reproducible. To put it more bluntly IPython (with a little help from its friends Sage and Mathics) offers an open source community backed alternative to computing environments like Wolfram Mathematica, Maple and Matlab. Don’t believe us? Sample this Fernando Perez, the creator of IPython wrote this blog detailing about the history behind its formation and community, check it out here. The IPython github page is a great place to start getting acquainted with it as well, be sure to check out their collection of notebooks published by the community. Some of my personal favourites include the Machine Learning Tutorial by Hannes Schulz and Andreas Muller, Learn Data Science byNitin Borwankar and Lectures on Quantum Mechanics and Quantum Optics using QuTiP by J.R. Johnasson. If you are working in scientific computing, computer science education, data science or research, IPython is your friendly neighbourhood open source hero. So without much ado give IPython a test run today, and we will be back next week with another prolific open source project. Peace, Love and Open Source.