Importing Modules from String Variables Using "__import__": Differences from Normal Import Statements
In Python, the import function allows one to dynamically import modules from a string variable. However, this can lead to unexpected results compared to using regular import statements.
Consider the following example:
import matplotlib.text as text x = dir(text) # Get attributes of matplotlib.text i = __import__('matplotlib.text') y = dir(i) # Get attributes of the imported module j = __import__('matplotlib') z = dir(j) # Get attributes of matplotlib
A comparison of the resulting lists reveals that the y object contains a mixture of attributes from matplotlib and matplotlib.text, while it lacks the desired information about the main classes from matplotlib.text.
This behavior is explained by the import function's mechanism. By default, it imports the top-level module specified by the string argument. In this case, "matplotlib.text" refers to the matplotlib.text module, but import imports matplotlib instead.
To address this issue, you can provide an empty string as the third argument to __import__, as seen in the following modified code:
i = __import__('matplotlib.text', fromlist=['']) y = dir(i) # Get attributes of matplotlib.text
This will cause import to import the matplotlib.text module specifically, resulting in y containing the desired list of attributes.
An alternative approach is to use Python 3.1's importlib module:
import importlib i = importlib.import_module("matplotlib.text") y = dir(i) # Get attributes of matplotlib.text
This method provides a more consistent and straightforward way to import modules from string variables.
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