James Powell: So you want to be a Python expert? | PyData Seattle 2017
PyData6 HN recommenders · recommended in 6 months, 2020–2026
talk · intermediate · evergreen · 2020–2026 on HN
James Powell's nearly two-hour PyData talk builds up Python's data model, decorators, generators and context managers, coding live in Vim. It aims to take intermediate programmers toward real Python expertise.
HN calls it one of the best technical talks and the clearest explanation of decorators, generators and context managers.
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6 comments from Hacker News
Another good (and entertaining) resource is James Powell's talk "So you want to be a Python expert" [1], the best explanation I've seen of decorators, generators and context managers. Good intro to the Python data (object) model too. [1] ▶ this video
I don't even use python. But this python expert video was absolutely amazing done by a true pro. James Powell ▶ this video
I work professionally in C/C++ and the instances I needed to use Python I always felt like I was missing the core understanding of the language and was writing C in a different syntax. I found James Powell's PyData 2017 talk "So you want to be a Python expert?" ( ▶ this video ) to be incredible at helping me to gain that core understanding of the language. It's legitimately the best technical talk I think I've seen and I can't recommend it highly enough.
Understanding Python's data model helped me become a better software engineer. I'd recommend watching this PyData talk (James Powell: So you want to be a Python expert? | PyData Seattle 2017 - ▶ this video ) and then using the official doc as a reference which is also fun to read: link
James Powell frequently gives very deep Python talks at conferences like Pydata, and shows you his coding approach in real time on Vim. Plenty of them are on YouTube and are worth a watch. This one [1] entitled "So you want to be a Python expert?" has almost half a million views! [1] ▶ this video
I recommend any of the talks by James Powell at PyData. For example this one ▶ this video Edit: maybe this one on Numpy may be more relevant: link