| 01. Parallel Programming In Python Intro-en-US.vtt | 22.6 KB | ||
| 01. Parallel Programming In Python Intro.mp4 | 175.2 MB | ||
| 02. Threading In Python-en-US.vtt | 26.9 KB | ||
| 02. Threading In Python.mp4 | 111.1 MB | ||
| 03. Creating a Threading Class-en-US.vtt | 20 KB | ||
| 03. Creating a Threading Class.mp4 | 86.9 MB | ||
| 04. Created a Wikipedia Reader-en-US.vtt | 18.2 KB | ||
| 04. Created a Wikipedia Reader.mp4 | 119.6 MB | ||
| 05. Creating a Yahoo Finance Reader-en-US.vtt | 19.1 KB | ||
| 05. Creating a Yahoo Finance Reader.mp4 | 134.8 MB | ||
| 06. Queues and Master Scheduler-en-US.vtt | 20.1 KB | ||
| 06. Queues and Master Scheduler.mp4 | 110.7 MB | ||
| 07. Creating a Postgres Worker-en-US.vtt | 26.1 KB | ||
| 07. Creating a Postgres Worker.mp4 | 156.8 MB | ||
| 08. Integrating the Postgres Worker-en-US.vtt | 26.2 KB | ||
| 08. Integrating the Postgres Worker.mp4 | 186.4 MB | ||
| 09. Yaml File Intro-en-US.vtt | 25.9 KB | ||
| 09. Yaml File Intro.mp4 | 138.4 MB | ||
| 10. Creating a Yaml Reader-en-US.vtt | 39.6 KB | ||
| 10. Creating a Yaml Reader.mp4 | 261.7 MB | ||
| 11. Improving Our Wiki Worker-en-US.vtt | 35.9 KB | ||
| 11. Improving Our Wiki Worker.mp4 | 258.5 MB | ||
| 12. Improving All Workers and adding Monitoring-en-US.vtt | 39.2 KB | ||
| 12. Improving All Workers and adding Monitoring.mp4 | 249 MB | ||
| 13. Final Program Cleanup-en-US.vtt | 10 KB | ||
| 13. Final Program Cleanup.mp4 | 54 MB | ||
| Bonus Resources.txt | 307.2 B | ||
| Get Bonus Downloads Here.url | 204.8 B | ||
| ▲ 28 total files | |||
Parallel Programming in Python
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.99 GB | Duration: 4h 9m
In this course you'll learn how to created multi-threaded programs in Python, so that you can make your programs run even faster.
We'll go through an introduction first of where potential speed bottlenecks come from as well as how we could solve these issues, and then we'll dive directly into the technical content and build out a multi-threaded program together that grabs data from the internet, parses, and saves it into a local database.
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