Faster Python Services

1h 24mAdvanced2018-03-23

Authors

Miki Tebeka

CEO at 353Solutions

Course details

Sometimes, the difference between a good Python application and a great one isn't found in the code; it's in the services that support your software. In this course, instructor Miki Tebeka introduces Python optimization tips and techniques to develop and run more efficient sites and applications. Learn how to find bottlenecks, stress test your code, use caching algorithms, "cheat" effectively, distribute work on one or more machines, and pick the right transport and encoding methods. He also introduces load balancers and powerful server frameworks for HTTP and TCP, and shows how to serve static content. Plus, learn how to monitor performance of your projects and set up alerts, so you'll know when a system or service fails.

Learning objectives
Tools of the trade
Caching
Cheating
Distributing work
Writing servers
Choosing a server framework
Processes such as monitoring

Skills covered

AdvancedPythonProgramming LanguagesOpen SourceSoftware Development

Concepts

0. Introduction

01 - Welcome
02 - What you should know

1. Tools of the Trade

03 - Always profile first
04 - General tips
05 - strace
06 - Stressing

2. Caching

07 - Overview
08 - Bloom filter

3. Cheating

09 - When approximation is good enough
10 - Cheating example

4. Distributing Work

11 - Amdahl's Law
12 - Example - Threads
13 - Beyond single machine

5. Writing Servers

14 - The C10K problem
15 - asyncio
16 - Choosing transportation
17 - Choosing serialization format
18 - Compression

6. Server Frameworks

19 - How to choose a framework
20 - HTTP servers
21 - TCP servers
22 - Load balancers
23 - Serving static content

7. Process

24 - Why do we need process
25 - Monitoring
26 - Alerting

Conclusion

27 - Next steps