# array - Converting sequences

This module provides various functions and classes to access sequences and buffer-style objects in different ways. It also provides conversion routines to improve the interoperability of sequences with :mod:ctypes data types.

## Providing read-write access for sequential data

Two classes allow you to access sequential data in different ways. The :class:CTypesView provides byte-wise access to iterable objects and allows you to convert the object representation to matching byte-widths for :mod:ctypes or other modules.

Depending on the the underlying object and the chosen size of each particular item of the object, the :class:CTypesView allows you to operate directly on different representations of the object's contents.

>>> text = bytearray("Hello, I am a simple ASCII string!")
>>> ctview = CTypesView(text, itemsize=1)
>>> ctview.view[0] = 0x61
>>> print(text)
aello, I am a simple ASCII string!"
>>> ctview.to_uint16()[3] = 0x6554
>>> print(text)
aello,Te am a simple ASCII string!"


The snippet above provides a single-byte sized view on a :func:bytearray object. Afterwards, the first item of the view is changed, which causes a change on the :func:bytearray, on the first item as well, since both, the :class:CTypesView and the :func:bytearray provide a byte-wise access to the contents.

By using :meth:CTypesView.to_uint16(), we change the access representation to a 2-byte unsigned integer :mod:ctypes pointer and change the fourth 2-byte value, I to something else.

>>> text = bytearray("Hello, I am a simple ASCII string!")
>>> ctview = CTypesView(text, itemsize=2)
>>> ctview.view[0] = 0x61
>>> print(text)
aello, I am a simple ASCII string!"
>>> ctview.to_uint16()[3] = 0x6554
>>> print(text)
aello,Te am a simple ASCII string!"


If the encapsuled object does not provide a (writeable) :func:buffer interface, but is iterable, the :class:CTypesView will create an internal copy of the object data using Python's :mod:array module and perform all operations on that copy.

>>> mylist = [18, 52, 86, 120, 154, 188, 222, 240]
>>> ctview = CTypesView(mylist, itemsize=1, docopy=True)
>>> print(ctview.object)
array('B', [18, 52, 86, 120, 154, 188, 222, 240])
>>> ctview.view[3] = 0xFF
>>> print(mylist)
[18, 52, 86, 120, 154, 188, 222, 240]
>>> print(ctview.object)
array('B', [18, 52, 86, 255, 154, 188, 222, 240])


As for directly accessible objects, you can define your own itemsize to be used. If the iterable does not provide a direct byte access to their contents, this won't have any effect except for resizing the item widths.

>>> mylist = [18, 52, 86, 120, 154, 188, 222, 240]
>>> ctview = CTypesView(mylist, itemsize=4, docopy=True)
>>> print(ctview.object)
array('I', [18L, 52L, 86L, 120L, 154L, 188L, 222L, 240L])


## Accessing data over multiple dimensions

The second class, :class:MemoryView provides an interface to access data over multiple dimensions. You can layout and access a simple byte stream over e.g. two or more axes, providing a greater flexibility for functional operations and complex data.

Let's assume, we are reading image data from a file stream into some buffer object and want to access and manipulate the image data. Images feature two axes, one being the width, the other being the height, defining a rectangular graphics area.

When we read all data from the file, we have an one-dimensional view of the image graphics. The :class:MemoryView allows us to define a two-dimensional view over the image graphics, so that we can operate on both, rows and columns of the image.

>>> imagedata = bytearray("some 1-byte graphics data")
>>> view = MemoryView(imagedata, 1, (5, 5))
>>> print(view)
[[s, o, m, e,  ], [1, -, b, y, t], [e,  , g, r, a], [p, h, i, c, s], [ , d, a, t, a]]
>>> for row in view:
...     print(row)
...
[s, o, m, e,  ]
[1, -, b, y, t]
[e,  , g, r, a]
[p, h, i, c, s]
[ , d, a, t, a]
>>> for row in view:
...    row[1] = "X"
...    print row
...
[s, X, m, e,  ]
[1, X, b, y, t]
[e, X, g, r, a]
[p, X, i, c, s]
[ , X, a, t, a]
>>> print(imagedata)
sXme 1XbyteXgrapXics Xata


On accessing a particular dimension of a :class:MemoryView, a new :class:MemoryView is created, if it does not access a single element.

>>> firstrow = view[0]
>>> type(firstrow)
<class 'mule.array.MemoryView'>
>>> type(firstrow[0])
<type 'bytearray'>


A :class:MemoryView features, similar to Python's builtin :class:memoryview, dimensions and strides, accessible via the :attr:MemoryView.ndim and :attr:MemoryView.strides attributes.

>>> view.ndim
2
>>> view.strides
(5, 5)


The :attr:MemoryView.strides, which have to be passed on creating a new :class:MemoryView, define the layout of the data over different dimensions. In the example above, we created a 5x5 two-dimensional view to the image graphics.

>>> twobytes = MemoryView(imagedata, 2, (5, 1))
>>> print(twobytes)
[[sX, me,  1, Xb, yt], [eX, gr, ap, Xi, cs]]