Python Optimization Introduction | Lecture Note - Edubirdie

University:
Boston University
Course:
MET CS 201 | Introduction to Programming
Academic year:

2024
Views:

350

Pages:

11
Author:

Beau Hendricks

Python Optimization Outline       Introduction Profiling Data Structures Syntax Parallelism Accelerators SCC Python Tutorials        Introduction to Python, Part one Introduction to Python, Part two Numerical and Scientific Computing in Python Python for Data Analysis Optimizing Python Data Visualization in Python Introduction to Python Scikit-learn Click on Interactive Apps/Desktop python3/3.6.9 python3/3.6.9 3 click When your desktop is ready click Connect to Desktop  Enter this command to create a directory in your home folder and to copy in tutorial files: /net/scc2/scratch/py_opt.sh Outline       Introduction Profiling Data Structures Syntax Generators Accelerators Optimization  What are you optimizing?      Run time Memory usage I/O (storage read/write) Code structure Algorithm selection  How do you decide when optimization is necessary?  What should be changed in a program during optimization?  Is Python fast? Why Bother to Optimize?  Computers aren’t getting much faster.  Easier access to data means there’s more computation possible than in the past.  Better code means you can get more done! Some words of wisdom: The Elements of Programming Style, by Brian W. Kernighan and P. J. Plauger, 1974.  Make it right before you make it faster.  Keep it right when you make it faster.  Make it clear before you make it faster.  simplicity and clarity are often of more value than the microseconds possibly saved by clever coding.  Fundamental improvements in performance are most often made by algorithm changes, not by tuning.

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