Welcome!

Scrivere codice Python efficiente

Logan Thomas

Scientific Software Technical Trainer, Enthought

Course overview

Your code should be a tool used to gain insights
- Not something that leaves you waiting for results
In this course, you will learn:
- How to write clean, fast, and efficient Python code
- How to profile your code for bottlenecks
- How to eliminate bottlenecks and bad design patterns

Defining efficient

Writing efficient Python code
- Minimal completion time (fast runtime)
- Minimal resource consumption (small memory footprint)

alt="Equation with a stopwatch next to an arrow pointing down plus a memory stick next to an arrow pointing down equalling the word efficient"

Defining Pythonic

Writing efficient Python code
- Focus on readability
- Using Python's constructs as intended (i.e., Pythonic)

# Non-Pythonic
doubled_numbers = []

for i in range(len(numbers)):
    doubled_numbers.append(numbers[i] * 2)

# Pythonic
doubled_numbers = [x * 2 for x in numbers]

The Zen of Python by Tim Peters

Beautiful is better than ugly.
Explicit is better than implicit.
Simple is better than complex.
Complex is better than complicated.
Flat is better than nested.
Sparse is better than dense.
Readability counts.
Special cases aren't special enough to break the rules.
Although practicality beats purity.
Errors should never pass silently.
Unless explicitly silenced.
In the face of ambiguity, refuse the temptation to guess.
...

Things you should know

Data types typically used in Data Science
- Data Types for Data Science
Writing and using your own functions
- Python Data Science Toolbox (Part 1)
Anonymous functions (lambda expressions)
- Python Data Science Toolbox (Part 1)
Writing and using list comprehensions
- Python Data Science Toolbox (Part 2)

Let's get started!

Scrivere codice Python efficiente