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Scientific and Parallel Computing Using IPython

Wearing my research-scientist’s hat I can honestly assert that Python’s strength in scientific programming is one of its glories, and maybe less appreciated than it should be. That makes series like unpingo’s
Scientific and parallel computing using IPython pure gold for its target audience. Combining the power and flexibility of the enhanced IPython interpreter with some of the industrial strength Python scientific, numeric and graphing libraries creates a superbly flexible and efficient scientific programming set-up. Check out these vids, rather superb as ever.

The series has five videos:

  • Introducing and setting up IPython on a Windows PC
  • Getting around and using the IPython interpreter
  • Using on-line documentation for a short case study on computing integrals
  • Subclassing and using the Python language for scientific computing
  • Using doctest and docstrings in customized classes
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