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The Hacker's Guide to Scaling Python

Gain insights into Python's scalability, concurrency, and distribution. Learn about CPU scaling, event loops, queue-based distribution, and building REST APIs to optimize and deploy high-performance applications.

Advanced

99 Lessons

8h 30min

Certificate of Completion

AI-POWERED

Explanations

AI-POWERED

Explanations

This course includes

1 Project

155 Playgrounds

13 Quizzes

Course Overview

Course Content

Recommendations

Course Overview

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 ...Show More

Python, in all of its greatness, is often dismissed when needing to write performant and distributed applications. It’s consider...Show More

Course Content

Scaling

5 Lessons

Step through scaling Python applications using multithreading, distributing systems, and service-oriented architecture.

Introduction to Scaling

Scaling Across CPUs

Distributed Systems

Service-Oriented Architecture

Quiz on Scaling

CPU Scaling

9 Lessons

Walk through CPU scaling techniques using threads, processes, futures, and optimization tools.

Introduction to CPU Scaling

Using Threads

Using Processes

Using Futures

Advanced Futures Usage

Daemon Processes

Mehdi Abaakouk on CPU Scaling

Quiz on Scaling Across CPUs

Coding Challenge: Scaling Across CPUs

Event Loops

7 Lessons

Work your way through event loops, asynchronous code, and efficient network management using asyncio.

Introduction to Event Loops

Basic Pattern: Blocking Events

Using Asyncio

Server And Client

Naoki Inada on asyncio

Quiz: Event Loops

Coding Challenge: Event Loops

Functional Programming

5 Lessons

Grasp the fundamentals of functional programming in Python, its toolkit, and practical applications.

Introduction to Functional Programming

Functional Programming Toolkit: Maps, Filters, and More

Functional Programming Toolkit: "next", "first", and "itertools"

Quiz: Functional Programming

Coding Challenge: Functional Programming

Queue-Based Distribution

10 Lessons

Dig into Python's queue-based distribution, focusing on RQ and Celery for scalability.

Introduction to Queue-Based Distribution

Celery

Celery: Handling Failures

Celery: Chaining Tasks

Celery: Multiple Queues

Celery: Monitoring

Joshua Harlow on Task Distribution

Quiz: Queue-Based Distribution

Coding Challenge: Queue-Based Distribution

Designing for Failure

5 Lessons

Tackle exception handling, retry strategies, and Tenacity for robust Python applications.

Introduction to Designing for Failure

Naive Retrying

Retrying with Tenacity

Quiz: Designing for Failure

Coding Challenge: Designing for Failure

Create a Web Crawler

Project

Project Walkthrough

1 Lessons

Practice using Celery and Redis to efficiently manage and process tasks.

Project Solution Review

Lock Management

9 Lessons

Step through managing locks to ensure safe access and prevent data corruption.

Introduction to Lock Management

Thread Locks

Processes Locks

Processes Locks: Multiprocessing Locks

Processes Locks: Inter-Processes Locks

Using etcd for Distributed Locking

Using Tooz Locking Abstraction

Quiz: Lock Management

Coding Challenge: Lock Management

10.

Group Membership

9 Lessons

Unpack the core of managing group membership in distributed systems using the Tooz library.

Introduction to Group Membership

Creating, Joining and Leaving Groups

Using Capabilities

Using Watchers Callbacks

Consistent Hash Rings

Partitioner

Alexys Jacob-Monier on Cluster Management

Quiz: Group Membership

Coding Challenge: Group Membership

11.

REST Interfaces

11 Lessons

Master the steps to build scalable and efficient REST APIs with Python frameworks.

Rest Interfaces in Python

The WSGI Protocol

Streaming Data

Using ETag

Asynchronous HTTP API

Fast HTTP Client

Comparison Between Fast HTTP Clients

Testing REST API

Chris Dent on HTTP

Quiz: Building REST API

Coding Challenge: Building REST API

12.

Deploying on PaaS

7 Lessons

Break down the steps to deploying Python applications on various PaaS platforms.

Introduction to Deploying on PaaS

Quiz: Deploying on PaaS

13.

Testing Distributed Systems

5 Lessons

Map out the steps for testing, environment setup, and service management in distributed systems.

Introduction to Testing Distributed Systems

Setting Up Environments with tox

Manage External Services with pifpaf

Using Fixtures with pifpaf

Quiz: Testing Distributed Systems

14.

Caching

7 Lessons

Investigate caching to enhance Python app performance, covering local, memoization, and distributed methods.

Introduction to Caching

Local Caching

Memoization

Distributed Caching

Jason Myers on Databases

Quiz: Caching

Coding Challenge: Caching

15.

Performance

8 Lessons

Master the steps to optimize Python performance through profiling, disassembling code, and efficient memory use.

Introduction to performance optimization

Memory and CPU Profiling

Profiling Strategy and a Case

Zero-Copy

Disassembling Code

Victor Stinner on Performance

Quiz: Performance

Coding Challenge: Performance

16.

Conclusion

1 Lessons

Engage in practical projects to apply your scalable Python skills confidently.

Conclusive Remarks

Course Author

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