Master Python for scalable, high-performance distributed applications, covering concurrency, queues, APIs, and optimization strategies.

python.tar.gz

Chapter2

Chapter7

Chapter5

Chapter6

Chapter3

Chapter7-without-etcd

Chapter8-with-etcd

Chapter9

Chapter9-gabbi

Chapter10-heroku

Chapter10-aws_eb

Chapter11_Tox_integration

Chapter11_Tox_integration-pifpaf

Chapter11_pifpaf_fixtures

Chapter12_caching

Chapter13_Performance

Chapter13_Performace_KCacheGrind

Chapter5-rq-dashboard

Chapter5-celery-flower

Chapter10-gcloud

Chapter2-zsh

Chapter13_Performace_KCacheGrind-copy

Chapter11_Tox_integration-pifpaf-postgresql

Celery-Project1_Sol

Celery-Project1_Sol2

Python, in all of its greatness, is often dismissed when needing to write performant and distributed applications. It’s considered to be slow and not suited for the task. In this course, you will find that with the right implementation of Python, you can write applications that scale horizontally, perform well, and are distributed. 

To kick things off, you’ll learn about CPU scaling, concurrency, and event loops, all of which are crucial for implementing a distributed system. After that, you’ll move on to queue-based distribution, lock management, and group memberships, which are fundamental concepts for maintaining availability and consistency in distributed applications.

In the last half, you’ll learn how to build a REST API, how to deploy your app to a PaaS, and how to optimize your application's performance.

By the end of this course, you’ll be more productive with Python, you’ll be able to write faster applications that are distributed, and you’ll have a great new skill that is highly coveted.

The Hacker's Guide to Scaling Python

## Problem

You are going to crack a 2 digit pin code in the following exercise. This pin code is used to open the locker of a bank.

However, there is a security system deployed at the bank locker that pin cannot be entered twice within **one** second. So, if anyone wants to crack it, they would have to wait one second after every wrong attempt.

Your task is to crack the pin code using the library `tenacity`. The skeleton code is provided, and the `crackPassword()` function is also implemented, which generates a random 2 digit number and check if this is the pin.

The hacker knows that they can try every combination from 11 to 99. However, they believe that they can crack it faster by trying randomly.

Please use the coding playground to complete the task provided below.

> To run the code below, press the Run button and run the command `python tenacity-test.py`.

# Problem

You are going to crack a 2 digit pin code in the following exercise. This pin code is used to open the locker of a bank.

However, there is a security system deployed at the bank locker that pin cannot be entered twice within **one** second. So, if anyone wants to crack it, they would have to wait one second after every wrong attempt.

Your task is to crack the pin code using the library `tenacity`. The skeleton code is provided, and the `crackPassword()` function is also implemented, which generates a random 2 digit number and check if this is the pin.

The hacker knows that they can try every combination from 11 to 99. However, they believe that they can crack it faster by trying randomly.

Please use the coding playground to complete the task provided below.

> To run the code below, press the Run button and run the command `python tenacity-test.py`.

Test your skills on designing a system for failure detection by solving the exercise in this lesson.

Coding Challenge: Designing for Failure

Scaling

CPU Scaling

Event Loops

Functional Programming

Queue-Based Distribution

Designing for Failure

Create a Web Crawler

Project Walkthrough

Lock Management

Group Membership

REST Interfaces

Deploying on PaaS

Testing Distributed Systems

Caching

Performance

Conclusion

Coding Challenge: Designing for Failure

Problem