"array" — Efficient arrays of numeric values
********************************************

======================================================================

This module defines an object type which can compactly represent an
array of basic values: characters, integers, floating point numbers.
Arrays are sequence types and behave very much like lists, except that
the type of objects stored in them is constrained.  The type is
specified at object creation time by using a *type code*, which is a
single character.  The following type codes are defined:

+-------------+----------------------+---------------------+-------------------------+---------+
| Type code   | C Type               | Python Type         | Minimum size in bytes   | Notes   |
|=============|======================|=====================|=========================|=========|
| "'b'"       | signed char          | int                 | 1                       |         |
+-------------+----------------------+---------------------+-------------------------+---------+
| "'B'"       | unsigned char        | int                 | 1                       |         |
+-------------+----------------------+---------------------+-------------------------+---------+
| "'u'"       | wchar_t              | Unicode character   | 2                       | (1)     |
+-------------+----------------------+---------------------+-------------------------+---------+
| "'h'"       | signed short         | int                 | 2                       |         |
+-------------+----------------------+---------------------+-------------------------+---------+
| "'H'"       | unsigned short       | int                 | 2                       |         |
+-------------+----------------------+---------------------+-------------------------+---------+
| "'i'"       | signed int           | int                 | 2                       |         |
+-------------+----------------------+---------------------+-------------------------+---------+
| "'I'"       | unsigned int         | int                 | 2                       |         |
+-------------+----------------------+---------------------+-------------------------+---------+
| "'l'"       | signed long          | int                 | 4                       |         |
+-------------+----------------------+---------------------+-------------------------+---------+
| "'L'"       | unsigned long        | int                 | 4                       |         |
+-------------+----------------------+---------------------+-------------------------+---------+
| "'q'"       | signed long long     | int                 | 8                       |         |
+-------------+----------------------+---------------------+-------------------------+---------+
| "'Q'"       | unsigned long long   | int                 | 8                       |         |
+-------------+----------------------+---------------------+-------------------------+---------+
| "'f'"       | float                | float               | 4                       |         |
+-------------+----------------------+---------------------+-------------------------+---------+
| "'d'"       | double               | float               | 8                       |         |
+-------------+----------------------+---------------------+-------------------------+---------+

Notes:

1. It can be 16 bits or 32 bits depending on the platform.

   Changed in version 3.9: "array('u')" now uses "wchar_t" as C type
   instead of deprecated "Py_UNICODE". This change doesn’t affect to
   its behavior because "Py_UNICODE" is alias of "wchar_t" since
   Python 3.3.

   Deprecated since version 3.3, will be removed in version 4.0.

The actual representation of values is determined by the machine
architecture (strictly speaking, by the C implementation).  The actual
size can be accessed through the "itemsize" attribute.

The module defines the following type:

class array.array(typecode[, initializer])

   A new array whose items are restricted by *typecode*, and
   initialized from the optional *initializer* value, which must be a
   list, a *bytes-like object*, or iterable over elements of the
   appropriate type.

   If given a list or string, the initializer is passed to the new
   array’s "fromlist()", "frombytes()", or "fromunicode()" method (see
   below) to add initial items to the array.  Otherwise, the iterable
   initializer is passed to the "extend()" method.

   Raises an auditing event "array.__new__" with arguments "typecode",
   "initializer".

array.typecodes

   A string with all available type codes.

Array objects support the ordinary sequence operations of indexing,
slicing, concatenation, and multiplication.  When using slice
assignment, the assigned value must be an array object with the same
type code; in all other cases, "TypeError" is raised. Array objects
also implement the buffer interface, and may be used wherever *bytes-
like objects* are supported.

The following data items and methods are also supported:

array.typecode

   The typecode character used to create the array.

array.itemsize

   The length in bytes of one array item in the internal
   representation.

array.append(x)

   Append a new item with value *x* to the end of the array.

array.buffer_info()

   Return a tuple "(address, length)" giving the current memory
   address and the length in elements of the buffer used to hold
   array’s contents.  The size of the memory buffer in bytes can be
   computed as "array.buffer_info()[1] * array.itemsize".  This is
   occasionally useful when working with low-level (and inherently
   unsafe) I/O interfaces that require memory addresses, such as
   certain "ioctl()" operations.  The returned numbers are valid as
   long as the array exists and no length-changing operations are
   applied to it.

   Note:

     When using array objects from code written in C or C++ (the only
     way to effectively make use of this information), it makes more
     sense to use the buffer interface supported by array objects.
     This method is maintained for backward compatibility and should
     be avoided in new code.  The buffer interface is documented in
     Buffer Protocol.

array.byteswap()

   “Byteswap” all items of the array.  This is only supported for
   values which are 1, 2, 4, or 8 bytes in size; for other types of
   values, "RuntimeError" is raised.  It is useful when reading data
   from a file written on a machine with a different byte order.

array.count(x)

   Return the number of occurrences of *x* in the array.

array.extend(iterable)

   Append items from *iterable* to the end of the array.  If
   *iterable* is another array, it must have *exactly* the same type
   code; if not, "TypeError" will be raised.  If *iterable* is not an
   array, it must be iterable and its elements must be the right type
   to be appended to the array.

array.frombytes(s)

   Appends items from the string, interpreting the string as an array
   of machine values (as if it had been read from a file using the
   "fromfile()" method).

   New in version 3.2: "fromstring()" is renamed to "frombytes()" for
   clarity.

array.fromfile(f, n)

   Read *n* items (as machine values) from the *file object* *f* and
   append them to the end of the array.  If less than *n* items are
   available, "EOFError" is raised, but the items that were available
   are still inserted into the array. *f* must be a real built-in file
   object; something else with a "read()" method won’t do.

array.fromlist(list)

   Append items from the list.  This is equivalent to "for x in list:
   a.append(x)" except that if there is a type error, the array is
   unchanged.

array.fromunicode(s)

   Extends this array with data from the given unicode string.  The
   array must be a type "'u'" array; otherwise a "ValueError" is
   raised.  Use "array.frombytes(unicodestring.encode(enc))" to append
   Unicode data to an array of some other type.

array.index(x)

   Return the smallest *i* such that *i* is the index of the first
   occurrence of *x* in the array.

array.insert(i, x)

   Insert a new item with value *x* in the array before position *i*.
   Negative values are treated as being relative to the end of the
   array.

array.pop([i])

   Removes the item with the index *i* from the array and returns it.
   The optional argument defaults to "-1", so that by default the last
   item is removed and returned.

array.remove(x)

   Remove the first occurrence of *x* from the array.

array.reverse()

   Reverse the order of the items in the array.

array.tobytes()

   Convert the array to an array of machine values and return the
   bytes representation (the same sequence of bytes that would be
   written to a file by the "tofile()" method.)

   New in version 3.2: "tostring()" is renamed to "tobytes()" for
   clarity.

array.tofile(f)

   Write all items (as machine values) to the *file object* *f*.

array.tolist()

   Convert the array to an ordinary list with the same items.

array.tounicode()

   Convert the array to a unicode string.  The array must be a type
   "'u'" array; otherwise a "ValueError" is raised. Use
   "array.tobytes().decode(enc)" to obtain a unicode string from an
   array of some other type.

When an array object is printed or converted to a string, it is
represented as "array(typecode, initializer)".  The *initializer* is
omitted if the array is empty, otherwise it is a string if the
*typecode* is "'u'", otherwise it is a list of numbers.  The string is
guaranteed to be able to be converted back to an array with the same
type and value using "eval()", so long as the "array" class has been
imported using "from array import array". Examples:

   array('l')
   array('u', 'hello \u2641')
   array('l', [1, 2, 3, 4, 5])
   array('d', [1.0, 2.0, 3.14])

See also:

  Module "struct"
     Packing and unpacking of heterogeneous binary data.

  Module "xdrlib"
     Packing and unpacking of External Data Representation (XDR) data
     as used in some remote procedure call systems.

  The Numerical Python Documentation
     The Numeric Python extension (NumPy) defines another array type;
     see http://www.numpy.org/ for further information about Numerical
     Python.
