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Python Intermediate

What is Python Profiling?

Measuring where Python code spends time and memory to identify performance bottlenecks and optimization opportunities.

Python profilers help identify slow code paths. cProfile (built-in) records function call counts and cumulative times — run with python -m cProfile script.py. line_profiler provides line-by-line timing with @profile decorator. memory_profiler tracks memory usage per line. py-spy samples running processes without code modification. For web applications, Django Debug Toolbar and Flask-Profiler show per-request metrics. Key metrics include total time, cumulative time per function, call count, and memory allocation. Common bottlenecks include unnecessary database queries (N+1), inefficient loops (use vectorized operations), excessive object creation, and blocking I/O in async code.

Related Terms

Python Property
A built-in decorator that lets you define methods that behave like attributes, enabling controlled access to instance data.
Python Interpreter
The program that reads and executes Python code, translating it into machine instructions at runtime.
Django
A high-level web framework that follows the batteries-included philosophy, providing ORM, admin, auth, and more out of the box.
List Comprehension
A concise syntax for creating new lists by applying an expression to each item in an existing iterable.
Python Package
A directory containing Python modules and an __init__.py file, providing a way to organize and distribute reusable code.
Enum
A built-in class for creating enumerated constants — named groups of related values that improve code readability.
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