Loading README.md 0 → 100644 +59 −0 Original line number Diff line number Diff line SharedArray python/numpy extension ================================== This is a simple python extension that lets you share numpy arrays with other processes on the same computer. It uses posix shared memory internally and therefore should work on most operating systems. Usage ----- ### `SharedArray.create(name, shape, dtype=float)` This function creates an array in shared memory identified by `name`. The `shape` and `dtype` arguments are the same as the numpy function `numpy.zeros()`. The returned array is initialized to zero. The shared memory block holding the content of the array will not be deleted when this array is destroyed, either implicitly or explicitly by calling `del`, it will simply be detached from the current process. To delete a shared array use the `SharedArray.delete()` function. ### `SharedArray.attach(name)` This function attaches an array previously created in shared memory and identified by `name`. The shared memory block holding the content of the array will not be deleted when this array is destroyed, either implicitly or explicitly by calling `del`, it will simply be detached from the current process. To delete a shared array use the `SharedArray.delete()` function. ### `SharedArray.delete(name)` This function destroys an array previously created in shared memory and identified by `name`. After calling `delete`, the array will not be attachable anymore, but currents attachments will not be affected. Requirements ------------ * Python 2.7 or 3+ * Numpy 1.8 * Posix shared memory interface SharedArray uses the posix shm interface (`shm_open` and `shm_unlink`) and so should work on most operating systems that follow the posix standards (Linux, *BSD, etc.). Installation ------------ The extension uses the `distutils` python package that should be familiar to most python users. * To test the extension directly from the source tree, without installing, type `python setup.py build_ext --inplace`. You can then start python or ipython from the same directory and `import SharedArray`. * To build and install the extension, type `python setup.py build` followed by `sudo python setup.py install`. Loading
README.md 0 → 100644 +59 −0 Original line number Diff line number Diff line SharedArray python/numpy extension ================================== This is a simple python extension that lets you share numpy arrays with other processes on the same computer. It uses posix shared memory internally and therefore should work on most operating systems. Usage ----- ### `SharedArray.create(name, shape, dtype=float)` This function creates an array in shared memory identified by `name`. The `shape` and `dtype` arguments are the same as the numpy function `numpy.zeros()`. The returned array is initialized to zero. The shared memory block holding the content of the array will not be deleted when this array is destroyed, either implicitly or explicitly by calling `del`, it will simply be detached from the current process. To delete a shared array use the `SharedArray.delete()` function. ### `SharedArray.attach(name)` This function attaches an array previously created in shared memory and identified by `name`. The shared memory block holding the content of the array will not be deleted when this array is destroyed, either implicitly or explicitly by calling `del`, it will simply be detached from the current process. To delete a shared array use the `SharedArray.delete()` function. ### `SharedArray.delete(name)` This function destroys an array previously created in shared memory and identified by `name`. After calling `delete`, the array will not be attachable anymore, but currents attachments will not be affected. Requirements ------------ * Python 2.7 or 3+ * Numpy 1.8 * Posix shared memory interface SharedArray uses the posix shm interface (`shm_open` and `shm_unlink`) and so should work on most operating systems that follow the posix standards (Linux, *BSD, etc.). Installation ------------ The extension uses the `distutils` python package that should be familiar to most python users. * To test the extension directly from the source tree, without installing, type `python setup.py build_ext --inplace`. You can then start python or ipython from the same directory and `import SharedArray`. * To build and install the extension, type `python setup.py build` followed by `sudo python setup.py install`.
