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Backport PR #5535: fix n^2 performance issue in coalesce_streams preprocessor...
Backport PR #5535: fix n^2 performance issue in coalesce_streams preprocessor for n consecutive stream outputs, `\r` fix would be compiled n times, and applied to each ith output (n-i) times. - move pattern to module level - apply replacement after coalescing outputs An example notebook from nbviewer with ~1k outputs that was taking 90 seconds to render now takes 3 seconds.

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Parallel Computing

IPython includes an architecture and library for interactive parallel computing. The enables Python functions, along with their arguments, to be run in parallel a multicore CPU, cluster or cloud using a simple Python API.

Tutorials

  • [Data Publication API](Data Publication API.ipynb)

Examples

  • [Monitoring an MPI Simulation - 1](Monitoring an MPI Simulation - 1.ipynb)
  • [Monitoring an MPI Simulation - 2](Monitoring an MPI Simulation - 2.ipynb)
  • [Parallel Decorator and map](Parallel Decorator and map.ipynb)
  • [Parallel Magics](Parallel Magics.ipynb)
  • [Using Dill](Using Dill.ipynb)
  • [Using MPI with IPython Parallel](Using MPI with IPython Parallel.ipynb)
  • [Monte Carlo Options](Monte Carlo Options.ipynb)

Non-notebook examples

This directory also contains examples that are regular Python (.py) files.

More substantial examples can be found in subdirectories:

In [2]:
%run ../utils/list_subdirs.ipy