Home Backend Development Python Tutorial Related uses of array array module in Python

Related uses of array array module in Python

Apr 16, 2018 pm 05:03 PM
array python module

Arrays are not a standard data structure built into Python, but with the array module we can also use array structures in Python. Below we will explain in detail the related uses of the array array module in Python

Initialization
array instantiation can provide a parameter to describe the allowed data type, and can also have an initial data sequence stored in the array.

import array
import binascii
s = 'This is the array.'
a = array.array('c', s)
print 'As string:', s
print 'As array :', a
print 'As hex  :', binascii.hexlify(a)
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The array is configured to contain a sequence of bytes, initialized with a simple string.

>>> ================================ RESTART ================================
>>> 
As string: This is the array.
As array : array('c', 'This is the array.')
As hex  : 54686973206973207468652061727261792e
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Processing arrays
Similar to other python sequences, arrays can be expanded and processed in the same way .

import array
import pprint
a = array.array('i', xrange(3))
print 'Initial :', a
a.extend(xrange(3))
print 'Extended:', a
print 'slice: :', a[2:5]
print 'Itetator:'
print list(enumerate(a))
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Supported operations include sharding, iteration, and adding elements to the end.

>>> ================================ RESTART ================================
>>> 
Initial : array('i', [0, 1, 2])
Extended: array('i', [0, 1, 2, 0, 1, 2])
slice: : array('i', [2, 0, 1])
Itetator:
[(0, 0), (1, 1), (2, 2), (3, 0), (4, 1), (5, 2)]
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Arrays and Files
Arrays can be converted into arrays using dedicated built-in methods for efficient reading/writing of files. The contents are written to a file or an array is read from a file.

import array
import binascii
import tempfile

a = array.array('i', xrange(5))
print 'A1: ',a
output = tempfile.NamedTemporaryFile()
a.tofile(output.file)
output.flush

with open(output.name, 'rb') as input:
  raw_input = input.read()
  print 'Raw Contents:', binascii.hexlify(raw_data)

  input.seek(0)
  a2 = array.array('i')
  a2.fromfile(input, len(a))
  print 'A2: ', a2
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Candidate byte order
If the data in the array does not use the inherent Byte order, or the order needs to be swapped before sending to a system with a different byte order, it is possible to convert the entire array in Python without iterating through each element.

import array
import binascii

def to_hex(a):
  chars_per_item = a.itemsize * 2
  hex_version = binascii.hexlify(a)
  num_chunks = len(hex_version) / chars_per_item
  for i in xrange(num_chunks):
    start = i * chars_per_item
    end = start + chars_per_item
    yield hex_version[start:end]

a1 = array.array('i', xrange(5))
a2 = array.array('i', xrange(5))
a2.byteswap()

fmt = '%10s %10s %10s %10s'
print fmt % ('A1_hex', 'A1', 'A2_hex', 'A2')
print fmt % (('-' * 10,) * 4)
for value in zip(to_hex(a1), a1, to_hex(a2), a2):
  print fmt % value
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byteswap() will swap the byte order of the elements in the C array, which is much more efficient than looping through data in python.

>>> ================================ RESTART ================================
>>> 
  A1_hex     A1   A2_hex     A2
---------- ---------- ---------- ----------
 00000000     0  00000000     0
 01000000     1  00000001  16777216
 02000000     2  00000002  33554432
 03000000     3  00000003  50331648
 04000000     4  00000004  67108864
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