Lecture#2

High performance computing for non-programmers

Glib Ivashkevych

junior researcher, NSC KIPT

Lecture #2:

Python programming language: Overview

cross-platform simple to learn general-purpose flexible & extendable

Huge standard library

Tons of third-party packages Documentation

Is used for:

scripting in VFX science & engineering system administration

Youtube, Google, Instagram, DropBox NASA, CERN

Philips, ILM and more

In computing:

glue layer GUI

code generation & prototyping

Python has a lot of tools for scientific computing: NumPy, SciPy, SymPy, scikit-learn

Scripting Compiled

language instructions are	language instructions are
executed one by one	compiled to assembly
flexible, but slow	rigid, but fast
allow for very fast	development cycle is usually
development cycle	longer

perfect for	perfect for
complex automation	performance

How Python code is executed

execution

	“compilation”	Python
file.py	file.pyc	Virtual
		Machine

source

code bytecode

Python type system

Dynamic,

variables are references

no definitions, created automatically

but strong typing

objects have type

+ garbage collector

x == y

x is y

x

“some string”

y

True True

x == y

x is y

x

y

“some string”

“some string”

True False

Mutable vs Immutable

Mutable objects can be changed lists, dictionaries, sets, byte arrays

can be changed in-place

Immutable objects can not be changed once created

numbers, strings, tuples

new object is created at each reassignment