More transcript corrections.

Author: mikeckennedy

transcripts/284.txt

@@ -1,4 +1,4 @@
-00:00:00 2020 will be one for the history books, won't it? I've put together a great group to look back on 2020 from the Python perspective. Join me along with sessile Philip Enos montani. j. Miller, Paul Everett, Reuben Lerner, Matt Harrison and Brian Aachen for a lighthearted and fun look back on the major Python events of 2020. This is talk Python to me, Episode 297, recorded November 30 2020. Happy New Year, everyone, and thanks for listening. Welcome to talk Python to me, a weekly podcast on Python, the language, the libraries, the ecosystem, and the personalities. This is your host, Michael Kennedy, follow me on Twitter, where I'm at m Kennedy, and keep up with the show and listen to past episodes at talk python.fm and follow the show on Twitter via at talk Python. So let's go ahead and just kick off this episode. This one is a little bit different than the standard show everyone here has been a guest and a great guest. And some of you even repeat guests, some of your repeat guests and scheduled for more episodes even hinted enough. But let's go ahead and kick it off. So this is going to be a year in review. There's a bunch of us here, seven or eight of us. And I just do a quick introduction. Let me just welcome you individually on you could say you know a couple sentences about who you are, and whatnot. Some people know and then we're just going to get into what you thought was the most interesting, impactful thing of the year. And I have some software to help me do that. So let me run it here. darnay. Me, I will go back to that. Well, let me welcome you all, then we'll get through this. So Jay J. Miller, welcome to talk with me again.
+00:00:00 2020 will be one for the history books, won't it? I've put together a great group to look back on 2020 from the Python perspective. Join me along with sessile Philip Ines montani. j. Miller, Paul Everett, Reuben Lerner, Matt Harrison and Brian Aachen for a lighthearted and fun look back on the major Python events of 2020. This is talk Python to me, Episode 297, recorded November 30 2020. Happy New Year, everyone, and thanks for listening. Welcome to talk Python to me, a weekly podcast on Python, the language, the libraries, the ecosystem, and the personalities. This is your host, Michael Kennedy, follow me on Twitter, where I'm at m Kennedy, and keep up with the show and listen to past episodes at talk python.fm and follow the show on Twitter via at talk Python. So let's go ahead and just kick off this episode. This one is a little bit different than the standard show everyone here has been a guest and a great guest. And some of you even repeat guests, some of your repeat guests and scheduled for more episodes even hinted enough. But let's go ahead and kick it off. So this is going to be a year in review. There's a bunch of us here, seven or eight of us. And I just do a quick introduction. Let me just welcome you individually on you could say you know a couple sentences about who you are, and whatnot. Some people know and then we're just going to get into what you thought was the most interesting, impactful thing of the year. And I have some software to help me do that. So let me run it here. darnay. Me, I will go back to that. Well, let me welcome you all, then we'll get through this. So Jay J. Miller, welcome to talk with me again.
 
 00:01:28 Happy to be here. I haven't been a guest in like three years. So
 
@@ -26,7 +26,7 @@
 
 00:02:42 Oh, hold up. Find on workout. A picture of me on the cover. Of course,
 
-00:02:47 that of course. Yeah. That was when you're working out preparing for the Olympics. Precisely. Precisely. Yeah, exactly. So we'll be sure to link to your book and some of your courses as well. Enos welcome from the other side of the world.
+00:02:47 that of course. Yeah. That was when you're working out preparing for the Olympics. Precisely. Precisely. Yeah, exactly. So we'll be sure to link to your book and some of your courses as well. Ines welcome from the other side of the world.
 
 00:02:58 Yeah, I'm currently in Australia. Escape the EU lockdowns and I'm here. Yeah. Happy to be back. I think I've been on a few of your podcasts, but it's always my favorite podcasts. So thank you.
 
@@ -144,7 +144,7 @@
 
 00:15:57 Yeah, it's also the whole aspect of the, you know, the previous like Microsoft and Java and sort of, I guess, big money behind those sorts of languages, and like the early 2000s, pushing them, and then I think community and to the point of like, developer gave developers what they wanted, rather than maybe, say, enterprise II languages. And then I think there's a whole confluence of other other things that happened as well. But it is kind of crazy, right? That like one of the top if not the top languages, right now. They're almost 30 years old. And it's got issues, it's got warts and whatnot, but it's it's a thriving language and, you know, without significant big companies behind it, right, that it's competing with companies that thrown millions of dollars into development of these things.
 
-00:16:46 Yeah, absolutely. And Matt and Enos, you two are on the data science side. And I think the data science and computational folks are the ones that poured the gas on the fire and really made it take off. And that's not where the growth necessarily completely is. But I think that gave it a serious kick.
+00:16:46 Yeah, absolutely. And Matt and Ines, you two are on the data science side. And I think the data science and computational folks are the ones that poured the gas on the fire and really made it take off. And that's not where the growth necessarily completely is. But I think that gave it a serious kick.
 
 00:17:01 Yeah, no, no, actually, I because I get asked about this a lot like, oh, what what do you think made Python the language for machine learning data science and AI? My theory is actually that a Python, of course, was lucky that it was in a right place at the right time. But I think actually, it's one because it's a general purpose language. People can come from other fields of Python into machine learning data science, for example, like what did people do before, if you look at kind of, you know, these surveys of what to use Python for before, it's a lot of web stuff, you can build kind of anything in Python. And I think that's what makes it so appealing, and much more appealing than, let's say, like an AI language. And that's also, in my opinion, why a lot of these attempts at making an AI language haven't taken off. And people are like, now Python is great. Yeah. So yeah, it's fast enough, it's usable enough. But I think the general purpose is really is what kind of got it over the edge there. And a
 
@@ -452,5 +452,5 @@
 
 01:08:11 I actually, like I kept hearing about Raspberry Pi. And so I decided to order one recently. And I haven't done anything with it. I like just came a few days ago. But I'm looking at this game like oh my God, this little card here that cost me less than $100. a lot less than that is more powerful than the computer I use to run my entire business for years and years and years. It's just astonishing to me.
 
-01:08:32 Yeah. So I think that's probably a good place to round out the show. Like the future is so exciting. And in some ways, we're like kind of living there. Right? Some of these things that are coming out are so amazing. And I just want to say thank you all to you all for being here. You're all doing such amazing work and it truly humbling. You all took time from crazy schedules from traveling from weird locations to just be here and make this whole event happen. This has been another episode of talk Python to me. Our guests on this episode word sessile. Philip, Enos amantani. j. Miller, Paul Everett, Reuben Lerner, Matt Harrison and Brian Aachen, thank you all for being on the show. It's been brought to you by us over at Talk Python Training. Do you want to level up your Python? Well, if you're just getting started, try our Python for the absolute beginner course. Or if you're looking for something more advanced, check out our new async course that digs into all the different types of async programming that you can do in Python. And if you're interested in more than one of these, be sure to check out our everything bundle. It's like a subscription that never expires. Whatever you're interested in, taking one of our courses or recommending one of our courses is the best way that you can support the podcast. Thank you. Be sure to subscribe to the show. Just open your favorite podcast app and search for Python. We should be right at the top. You can also find the iTunes feed at slash iTunes in the direct RSS feed at slash RSS on talk python.fm. This is your host, Michael Kennedy. Thank you so much for listening. I really appreciate it. Now get out there. And write some Python code
+01:08:32 Yeah. So I think that's probably a good place to round out the show. Like the future is so exciting. And in some ways, we're like kind of living there. Right? Some of these things that are coming out are so amazing. And I just want to say thank you all to you all for being here. You're all doing such amazing work and it truly humbling. You all took time from crazy schedules from traveling from weird locations to just be here and make this whole event happen. This has been another episode of talk Python to me. Our guests on this episode word sessile. Philip, Ines amantani. j. Miller, Paul Everett, Reuben Lerner, Matt Harrison and Brian Aachen, thank you all for being on the show. It's been brought to you by us over at Talk Python Training. Do you want to level up your Python? Well, if you're just getting started, try our Python for the absolute beginner course. Or if you're looking for something more advanced, check out our new async course that digs into all the different types of async programming that you can do in Python. And if you're interested in more than one of these, be sure to check out our everything bundle. It's like a subscription that never expires. Whatever you're interested in, taking one of our courses or recommending one of our courses is the best way that you can support the podcast. Thank you. Be sure to subscribe to the show. Just open your favorite podcast app and search for Python. We should be right at the top. You can also find the iTunes feed at slash iTunes in the direct RSS feed at slash RSS on talk python.fm. This is your host, Michael Kennedy. Thank you so much for listening. I really appreciate it. Now get out there. And write some Python code