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10.4: Sub packages

  • Page ID
    23725
  • \( \newcommand{\vecs}[1]{\overset { \scriptstyle \rightharpoonup} {\mathbf{#1}} } \)

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    Packages in Python can contain subpackages, essentially packages nested within them. These subpackages help in further organizing and categorizing functionalities, making the primary package modular and more manageable. One prime example of this hierarchical organization is seen in the numpy package. While numpy itself offers a vast array of numerical operations, it also includes subpackages like random to handle random number generation and related tasks.

    When you want to access a function from a subpackage, you have to traverse this hierarchy using the dot notation. If, for instance, you've imported numpy as np, to use a function within the random subpackage, you'd employ the syntax np.random.function_name. For example, to generate a random float between 0 and 1, you'd use np.random.rand().

    It's also worth noting that it's possible to import subpackages directly, streamlining the syntax a bit. For instance, you can write from numpy import random and then just use random.function_name without the np prefix. Alternatively, you can even combine the use of subpackages with the aliasing technique: import numpy.random as npr, allowing you to access random functions using npr.function_name.


    10.4: Sub packages is shared under a not declared license and was authored, remixed, and/or curated by LibreTexts.

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