docs/speed_python: Add many more details on memoryviews.
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@ -85,18 +85,31 @@ elements in contiguous memory locations. Once again to avoid memory allocation i
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code these should be pre-allocated and passed as arguments or as bound objects.
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When passing slices of objects such as ``bytearray`` instances, Python creates
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a copy which involves allocation. This can be avoided using a ``memoryview``
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object:
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a copy which involves allocation of the size proportional to the size of slice.
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This can be alleviated using a ``memoryview`` object. ``memoryview`` itself
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is allocated on heap, but is a small, fixed-size object, regardless of the size
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of slice it points too.
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.. code:: python
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ba = bytearray(100)
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func(ba[3:10]) # a copy is passed
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mv = memoryview(ba)
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func(mv[3:10]) # a pointer to memory is passed
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ba = bytearray(10000) # big array
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func(ba[30:2000]) # a copy is passed, ~2K new allocation
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mv = memoryview(ba) # small object is allocated
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func(mv[30:2000]) # a pointer to memory is passed
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A ``memoryview`` can only be applied to objects supporting the buffer protocol - this
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includes arrays but not lists.
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includes arrays but not lists. Small caveat is that while memoryview object is live,
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it also keeps alive the original buffer object. So, memoryviews isn't universal
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panacea. For instance, in the example above, if you are done with 10K buffer and
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just need those bytes 30:2000 from it, it may be better to make a slice, and let
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the 10K buffer go (be ready for garbage collection), instead of making a
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long-living memoryview and keeping 10K blocked for GC.
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Nonetheless, ``memoryview`` is indispensable for advanced preallocated buffer
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management. ``.readinto()`` method discussed above puts data at the beginning
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of buffer and fills in entire buffer. What if you need to put data in the
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middle of existing buffer? Just create a memoryview into the needed section
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of buffer and pass it to ``.readinto()``.
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Identifying the slowest section of code
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---------------------------------------
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