5.9 array -- Efficient arrays of numeric values

This module defines a new object type which can efficiently 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 
'c' char character 1
'b' signed char int 1
'B' unsigned char int 1
'h' signed short int 2
'H' unsigned short int 2
'i' signed int int 2
'I' unsigned int long 2
'l' signed long int 4
'L' unsigned long long 4
'f' float float 4
'd' double float 8

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 values stored for 'L' and 'I' items will be represented as Python long integers when retrieved, because Python's plain integer type cannot represent the full range of C's unsigned (long) integers.

The module defines the following function and type object:

array(typecode[, initializer])
Return a new array whose items are restricted by typecode, and initialized from the optional initializer value, which must be a list or a string. The list or string is passed to the new array's fromlist() or fromstring() method (see below) to add initial items to the array.

ArrayType
Type object corresponding to the objects returned by array().

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 buffer objects are supported.

Array objects support the following data items and methods:

typecode
The typecode character used to create the array.

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

append(x)
Append a new item with value x to the end of the 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 the Python/C API Reference Manual.

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.

count(x)
Return the number of occurences of x in the array.

extend(a)
Append array items from a to the end of the array. The two arrays must have exactly the same type code; if not, TypeError will be raised.

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.

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.

fromstring(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).

index(x)
Return the smallest i such that i is the index of the first occurence of x in the array.

insert(i, x)
Insert a new item with value x in the array before position i.

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.

read(f, n)
Deprecated since release 1.5.1. Use the fromfile() method.

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.

remove(x)
Remove the first occurence of x from the array.

reverse()
Reverse the order of the items in the array.

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

tolist()
Convert the array to an ordinary list with the same items.

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

write(f)
Deprecated since release 1.5.1. Use the tofile() method.

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

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 'c', 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 reverse quotes (``), so long as the array() function has been imported using from array import array. Examples:

array('l')
array('c', 'hello world')
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 Manual
The Numeric Python extension (NumPy) defines another array type; see http://numpy.sourceforge.net/ for further information about Numerical Python. (A PDF version of the NumPy manual is available at http://numpy.sourceforge.net/numdoc/numdoc.pdf.)
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