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HomeBackend DevelopmentPython TutorialTop or Lazy Imports in Python: Which Is More Efficient?

Top or Lazy Imports in Python: Which Is More Efficient?

Import Statements at the Top or Within Modules: Efficiency Concerns

PEP 8 mandates the placement of import statements at the beginning of a file, prompting the question of whether it is more effective to import modules only when needed.

Performance Comparison

Consider the following code:

class SomeClass(object):

    def not_often_called(self):
        from datetime import datetime
        self.datetime = datetime.now()

versus:

from datetime import datetime

class SomeClass(object):

    def not_often_called(self):
        self.datetime = datetime.now()

While module importing is rapid, it is not instantaneous. Therefore:

  • Import statements at the top: A minor cost incurred only once.
  • Lazy imports: Causes every function call to take longer.

Efficiency Considerations

Prioritize import statements at the beginning of the file for efficiency if performance is a concern. Only consider lazy imports within functions if profiling reveals a performance gain.

Legitimate Reasons for Lazy Imports

Although deferred importing is generally inefficient, there are valid scenarios:

  • Optional libraries: Avoid importing libraries not always available.
  • __init__.py plugins: Prevent importing plugins that may not be used.

In summary, place imports at the top of modules for efficiency unless there are compelling reasons for lazy loading, such as optional libraries or inactive plugins.

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