


How Does Python\'s `__import__` Differ from Standard `import` When Importing Modules from String Variables?
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:
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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:
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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:
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This method provides a more consistent and straightforward way to import modules from string variables.
Note:
- When importing from subfolders (e.g., ./feature/email.py), the importlib syntax becomes importlib.import_module("feature.email").
- Before Python 3.3, the presence of an __init__.py file in the folder was necessary for imports using importlib.import_module.
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