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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

Lambda Function
An anonymous, single-expression function defined inline using the lambda keyword.
PIP
The standard package installer for Python, used to install and manage third-party libraries from PyPI.
Python Iterator Protocol
The interface requiring __iter__() and __next__() methods, enabling objects to be used in for loops and other iteration contexts.
Python Packaging with Poetry
A modern dependency management and packaging tool for Python that simplifies project setup, versioning, and publishing.
Magic Methods
Special double-underscore methods that define how Python objects behave with built-in operations and functions.
Dataclass
A decorator that automatically generates __init__, __repr__, __eq__, and other special methods for classes that mainly store data.
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