pypar | scalable parallelism using the message passing interface
kandi X-RAY | pypar Summary
kandi X-RAY | pypar Summary
PyPar is a python library that provides efficient and scalable parallelism using the message passing interface (MPI) to handle big data and highly computational problems.
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Top functions reviewed by kandi - BETA
- Distribute an iterable
- Distributes the elements in an iterable
- Generate a distributed distributed slice of the given iterable
- R Calculates a cyclic region
- Calculates the number of a complex point
- Get the supported flags
- Calculate the MC - PI correlation coefficient
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pypar Examples and Code Snippets
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Trending Discussions on pypar
QUESTION
I want to bind with the class from third party library. The class have some pure virtual functions but the destructor is protected and virtual.
In order to bind the class, I have to write a derived class that overrides the pure virtual functions (https://pybind11.readthedocs.io/en/stable/advanced/classes.html)
so the code is like this
...ANSWER
Answered 2019-May-22 at 10:53std::unique_ptr
and std::shared_ptr
are smart pointers supported by pybind out of box. Both of them require destructor to be public.
The simplest solution would be to write intermediate class with public destructor and expose it with pybind11.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
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Install pypar
You can use pypar like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
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