ipyparallel
Tutorial
Reference
examples
Changelog
API Reference
GitHub
Overview and getting started
Starting the IPython controller and engines
IPython’s Direct interface
Parallel Magic Commands
The IPython task interface
The AsyncResult object
Parallel examples
Tutorial
¶
Overview and getting started
Examples
Introduction
Architecture overview
Getting Started
Starting the IPython controller and engines
General considerations
Managing
Clusters
Configuring an IPython cluster
IPython’s Direct interface
Starting the IPython controller and engines
Creating a
DirectView
Quick and easy parallelism
Calling Python functions
Moving Python objects around
Other things to look at
Parallel Magic Commands
The Magics
Multiple Active Views
Engines as Kernels
The IPython task interface
Creating a
LoadBalancedView
Quick and easy parallelism
Dependencies
Retries and Resubmit
Schedulers
More details
The AsyncResult object
Beyond stdlib AsyncResult and Future
Metadata
Map results are iterable!
Parallel examples
150 million digits of pi
Conclusion
Using IPython for parallel computing
Overview and getting started