Exercise: Parallelizing Heavy Calculations

Understand how to parallelize CPU-intensive calculations using Python's multiprocessing tools. This lesson guides you in creating process pools, using Pool.map to distribute tasks, and optimizing performance beyond Python's threading limits.

We'll cover the following...

Problem statement
Task requirements
Constraints

1.Get Started

2.Orientation and First Code

3.Variables, Types, and Expressions

4.Flow Control

5.Data Collections

6.Functions and Scope

7.Comprehensions and Functional Tools

Mini Project

8.The Python Object Model

9.Organizing Code with Modules

10.Creating and Using Classes

11.Object Relationships and Data Model

12.Error Handling and Debugging

13.Testing and Code Quality

14.Working with Files

15.Iterators and Generators

Mini Project

16.Working with Data and APIs

17.Managing Packages and Environments

18.Parallel and Concurrent Programming

19.Asynchronous Programming

20.Advanced Functions and Decorators

21.Introspection and Type-Level Metaprogramming

22.Building and Distributing Applications

Mini Project

23.Wrapping Up

Exercise: Parallelizing Heavy Calculations

Problem statement