7.12 Deep Copies

  • When sharing mutable values, sometimes it’s necessary to create a deep copy of the original data
  • Especially important in multi-core programming, where separate parts of your program could attempt to modify your data at the same time, possibly corrupting it
  • array method copy returns a new array object with an independent copy of the original array's data
In [1]:
import numpy as np
In [2]:
numbers = np.arange(1, 6)
In [3]:
numbers
Out[3]:
array([1, 2, 3, 4, 5])
In [4]:
numbers2 = numbers.copy()
In [5]:
numbers2
Out[5]:
array([1, 2, 3, 4, 5])
In [6]:
numbers[1] *= 10
In [7]:
numbers
Out[7]:
array([ 1, 20,  3,  4,  5])
In [8]:
numbers2
Out[8]:
array([1, 2, 3, 4, 5])

Module copy—Shallow vs. Deep Copies for Other Types of Python Objects

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