


Top or Bottom: Where Should I Place My Python Imports for Optimal Performance?
The Location of Import Statements: Top or Bottom?
PEP 8 emphasizes placing imports at the beginning of modules, prioritizing clarity and consistency. However, a counterargument arises: wouldn't it be more efficient to defer imports until necessary, especially for infrequently used classes or functions?
Consider the following two examples:
class SomeClass(object): def not_often_called(self): from datetime import datetime self.datetime = datetime.now()
from datetime import datetime class SomeClass(object): def not_often_called(self): self.datetime = datetime.now()
The question arises – which approach is more efficient?
Import Performance
Although module imports are swift, they are not instantaneous. Hence:
- Placing imports at the module's inception poses a negligible cost incurred only once.
- Restricting imports within functions prolongs the execution time of those functions.
Therefore, for optimal efficiency, it is wise to locate imports at the top of modules. Nonetheless, moving imports within functions can be considered when profiling reveals noticeable performance benefits.
Reasons for Lazy Imports
Beyond efficiency concerns, lazy imports find justification in certain scenarios:
- Optional Library Support: When code paths rely on optional libraries, import failures can be avoided by using lazy imports.
- Plugin Initialization: Imports in plugin initialization scripts may not be actively utilized, making lazy imports appropriate.
In summary, while PEP 8's guideline to position imports at the beginning of modules ensures consistency and readability, performance considerations may sometimes warrant lazy imports. However, such decisions should be based on profiling data to identify bottlenecks and optimize performance efficiently.
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