Parallel Tasks in a Pool of Threads and Processes

In this video, we will discuss a super interesting topic in Python - concurrent.futures (ThreadPoolExecutor and ProcessPoolExecutor).

It allows us to run numerous tasks at the same time via threads or processes, making our programs faster and more efficient.

We can use one of two classes:
- ThreadPoolExecutor
- ProcessPoolExecutor.

The ThreadPoolExecutor is useful for I/O-bound operations such as reading files or sending network requests. ProcessPoolExecutor is more suited for CPU-intensive operations, such as mathematical computations.

Chapters:
⏩ 0:00 What is concurrent.futures in Python
⏩ 0:37 How to use it
⏩ 0:59 Example
⏩ 1:24 Why should we use it
⏩ 1:42 ThreadPoolExecutor - real-world example
⏩ 1:58 ProcessPoolExecutor - real-world example
⏩ 2:19 Outro

✨More on 2MinutesPy👇👇

▶️ Different ways to achieve Concurrency in Python? https://youtu.be/HeDSLdr3yx8

▶️ asyncio in Python - Async/Await: https://youtu.be/3E-Ym2mbSCc

▶️ Race Condition and How to Solve it - threading.Lock: https://youtu.be/7vH7Ho4eMVQ

▶️Python Threading in 2 Minutes: https://youtu.be/KbrUfPEwt78

▶️ Global Interpreter Lock (GIL) in Python? https://youtu.be/bHFz94fe0Co

Subscribe to https://www.youtube.com/channel/UCbcD3tpv7kIQU2cp5F9KJNA for more such videos.

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