Guido van Rossum: Python and the Future of Programming | Lex Fridman Podcast #341

can you imagine possible features. that python 4.0 might have that would. necessitate the creation of the new 4.0. given the amount of. pain and joy. suffering and Triumph that was involved. in the move between version 2 and. version 3. the following is a conversation with. Guido van Rossum his second time on this. podcast he is the creator of the Python.

programming language and is Python's. Emeritus pdfo benevolent dictator for. life this is the Lex Friedman podcast to. support it please check out our sponsors. in the description and now dear friends. here's Guido and Russell. python 3.11 is coming out very soon init. C python claimed to be 10 to 60 percent. faster how did you pull that off and. what's C python C python is the last.

python implementation standing also the. first one that was ever created the. original python implementation that I. started over 30 years ago so what does. it mean that python the programming. language is implemented in another. programming language called C what kind. of audience do you have in mind here. people who know programming no there's. somebody on a boat that's into fishing. and have never heard about programming. but also some world-class programmers. you're gonna have to speak to both. imagine a boat with two people one of.

them has not heard about programming is. really into phishing and the other one. is like uh an incredible Silicon Valley. programmer that's programmed in. everything C C plus plus python rust. Java it knows the entire history of. programming languages so you're gonna. have to speak to both I imagine that. boat in the middle of the ocean yes I'm. gonna please the guy who knows how to. fish first yes please. he seems like the most useful in the. middle of the ocean you got you gotta.

make him mad I'm sure he has a cell. phone so uh he's probably very. suspicious about what goes on in that. cell phone but he must have heard that. inside his cell phone is a tiny computer. and a programming language is computer. code that tells the computer what to do. it's a very low level. language it's zeros and ones and then. there's assembly and then oh yeah we. don't talk about these really low levels. because those just confuse people I mean.

when we're talking about human language. we're not usually talking about vocal. tracts and how you position your tongue. I was talking yesterday about how when. you have a Chinese person and they speak. English uh this is a bit of a stereotype. they often don't know or they they can't. can't seem to make the difference well. between an l and an r and I have a. theory about that and I've never checked. this with linguists. uh that it probably has to do with the.

fact that in Chinese there is not really. a difference and it could be that there. are Regional variations in how China. native Chinese speakers pronounce that. one sound that. sounds to L to some like L to some of. them like R to others so it's both the. sounds you produce with your mouth. throughout the history of your life and. what you're used to listening to I mean. every language has that Russian has. exactly the Slavic languages have sounds.

like the letters. like uh Americans or English speakers. don't seem to know the sounds. they seemed uncomfortable with that. sound yeah so I'm sure oh yes okay so. we're not we're not going to the shapes. of tongues and the sounds that the mouth. can make fine words similarly we're not. going into the ones and zeros or machine. language I would say a programming. language is a list of instructions like.

a cookbook recipe. that sort of tells you how to do a. certain thing like make a sandwich well. acquire a loaf of bread cut it in slices. uh take two slices uh put mustard on one. put the jelly on the other or something. then add the meat then add the cheese. I've heard that science teachers can. actually uh do great stuff with recipes. like that and trying to interpret their.

students instructions incorrectly until. the students are completely unambiguous. about it. with language see that's the difference. between. natural languages and programming. languages I think ambiguity is a feature. not a bug in human spoken languages like. uh. that's the dance of communication. between humans. well for lawyers ambiguity certainly is. a feature. uh for plenty of other cases uh the.

ambiguity is is not much of a feature. but we work around it of course well. what's more important is context. so with context the Precision of the. statement becomes more and more concrete. right but you know when you say I love. you to a person that matters a lot to. you the person doesn't try to compile. that statement and return an error. saying please define love. right no but I imagine that my wife and.

my son uh interpret it very differently. yes even though it's the same three. words but imprecisely still. oh for sure. lawyers never had a lot of follow-up. questions for you nevertheless the. context is already different different. in that case yes fair enough so that's. that's a programming language is uh. ability to unambiguously State a recipe. actually let's go back let's go to Pepe.

you go through and pepe the style guide. for python code some ideas of what this. language should look like. feel like read like and the big idea. there is that code readability counts. what does that mean to you and how do we. achieve it so this recipe should be. readable that's a thing between. programmers. because on the one hand we always. explain the concept of programming. language as computers need instructions.

and computers are very dumb and they. need very precise instructions because. they don't have much context in in fact. they have lots of context but their. their context is very different. but what we've seen emerge during the. development of software starting in the. probably in the late 40s. is that software is a very social. activity a software developer is not a. mad scientist who sits alone in his lab.

writing brilliant code. software is developed by teams of people. uh even the Mad scientists sitting alone. in his lap can type fast enough to. produce enough code so that by the time. he's done with his coding he still. remembers what the first few lines he. wrote mean so even the mad scientist. coding alone in his lab would would be. sort of wise to. adopt conventions on how to format.

the instructions that he gives to the. computer so that the thing is there is a. difference between a cookbook recipe and. a computer program. The cookbook recipe the the author of. The cookbook writes it once. and then is printed in 100 000 copies. and then lots of people in their. kitchens try to recreate that recipe. that that particular.

pie or dish from the recipe and so there. the. the goal of the cookbook author is to. make it clear. to the human reader of the recipe the. human amateur Chef in most cases. when you're writing a computer program. you have two audiences at once. it needs to. tell the computer what to do.

but it also is useful if that program is. readable by other programmers. because computer software unlike the. typical recipe for a cherry pie is so. complex. that you don't get all of it right at. once. you end up with the activity of. debugging and you end up with the. activity of so debugging is.

trying to figure out why your code. doesn't run the way you thought it. should run that means brother could be. stupid little errors or it could be big. logical errors it could be anything. spiritual yeah it could be anything from. a typo to uh a wrong choice of algorithm. to. building something that does what you. tell it to do but that's not useful. yeah it seems to work really well 99 of. the time but does weird things one.

percent of the time on some edge cases. that's pretty much all software nowadays. all good software right well yeah for. for bad software that that 99 goes down. a lot so but it's not just about the. complexity of the program it's like you. said it is a social endeavor. in that you're constantly improving that. recipe for the cherry pie but you're. sort of you're in a group of people. improving that recipe or the mad.

scientist is improving the recipe that. he created a year ago and making it. better. or adding adding something he decides. that he wants a I don't know he wants. some decoration on his pie or icing or. so there's broad philosophical things. and there's specific advice on style so. first of all the thing that people first. experience when they look up python. there is a it is very readable.

but there's also like a spatial. structure to it. can you explain the indentation style of. python and what is the magic to it space. bases are important for readability of. any kind of text. if you take a cookbook recipe. and you remove all the sort of. all the bullets and other markup. and you just crunch all the text. together maybe you leave the spaces. between the words but that's all you.

leave. when you're in the kitchen trying to. figure out oh what are the ingredients. and what are the steps. and where does this step end and the. next step begin you're going to have a. hard time if it's if it's just one solid. block of text. on the other hand what what a typical. cookbook does if the paper is not too. expensive. each recipe starts on its own page maybe. there's a picture next to it the list of. ingredients comes first.

uh there's a standard notation the. there's there's shortcuts so that you. don't have to sort of write two. sentences on how you have to cut the. onion because there are only three ways. that people ever cut onions in a kitchen. small medium and in slices or something. like that. right none of my examples make any sense. to real Cooks of course but yeah. we're talking to programmers with a. metaphor of cooking I love it.

um but there is a strictness to the. spacing that python defines so there's. some. a looser thing some stricter things but. the four spaces for the. for the indentation is really. interesting it it really. um it really defines what the language. looks and feels like because indentation. sort of taking a block of text and then. having inside that block of text. a smaller block of text that is indented.

further as sort of a group it's it's. it's like you have a a bulleted list. in a complex business document and. inside some of the bullets are other. bulleted lists you will indent those too. if each bulleted list is indented. several inches then at two levels deep. there's no no space left on the page to. put any of the words of the text so you. can't indent too far on the other hand. if you don't indent at all you can tell.

whether something is a top level bullet. or a second level bullet or a third. level bullet so you have to have. some compromise and uh based on Ancient. conventions. and the sort of the typical width of a. computer screen in the 80s. uh and all sorts of things sort of. we we came up with sort of four spaces. as a compromise I mean there there are.

groups there are large groups of people. who code with uh two spaces per indent. level for example the Google style guide. uh all the Google python code and I. think also all the Google C plus plus. code is indented with only two spaces. per block if you're not used to that. it's harder to at a glance. understand the code because the the sort. of the the high level structure is. determined by the indentation on the.

other hand there are there are other. programming languages where the. indentation is uh eight spaces or a. whole tab stop in in sort of classic. Unix and to me that looks weird because. you you sort of after three indent. levels you've you've got no room left. well there's some languages where the. indentation is a recommendation. it's a stylistic one the code compiles. even without any indentation. and then python really indentations a.

fundamental part of the language right. it doesn't have to be four spaces so you. you can code python with two spaces per. block or or six Paces or 12 if you. really want to go wild but. sort of everything. that belongs to the same block needs to. be indented the same way. in practice in most other languages. people recommend doing that anyway if. you look at. C or rust or C plus plus.

all those languages Java don't have a. requirement of indentation. but except in extreme cases. they're just as anal about having their. code properly indented so any IDE that. the syntax highlighting that works with. Java or C plus they will yell at you. aggressively if you don't do proper. indentation they'd suggests the proper.

indentation for you like uh in C you. type a few words and then you type a. curly brace which there is their notion. of sort of begin and an indented block. uh then you hit return and then it. automatically indents four or eight. spaces depending on uh your your style. preferences or how your editor is. configured was there a possible Universe. in which you considered having braces in. Python absolutely yeah well there's a 60.

40 70 30 in your head uh uh what was the. trade-off for a long time I was actually. convinced that the indentation was just. better. uh. without context I would still claim that. indentation is better. uh it reduces clutter however. as I started to say earlier context is.

almost everything. and in the context of coding. most programmers are familiar with. multiple languages even if they're only. good at one or two. and apart from Python and maybe Fortran. I don't know how that's written these. days anymore but all the other languages. Java rust CC plus plus JavaScript. typescript Perl are all using curly. braces uh to sort of indicate blocks and.

so python is the odd one out so it's a. radical idea do you still as a radical. Renegade revolutionary do you still. stand behind this idea of space of uh. indentation versus braces. like what what can you dig into it a. little bit more. why you still stand behind indentation. because context is not the whole story. history in in a sense provides more. context so for python.

there's no chance that we can switch. python is using curly braces for. something else dictionaries mostly. we would get in trouble if we wanted to. switch just like you couldn't redefine C. to use indentation. even if you agree that it that. indentation sort of. in a Greenfield environment would be. better. you can't change that kind of thing in a.

language yeah it's hard enough to reach. agreement over over much more Minor. Details maybe I mean in the past in. Python we did have a big debate about. test versus spaces and four spaces. versus fewer or more. and we sort of came up with. a recommended standard and sort of. options for people who want to be. different. but yes I guess the thought experiment.

I'd like you to consider is if you could. travel back through time when the when. the compatibility is not an issue and he. started python all over again. can you make the case for uh indentation. still. well it frees up a pair of. matched brackets of which there are. never enough in the world. uh for other purposes. really makes the language slightly. sort of.

easier to grasp for people who don't. already know. another programming language. because the sort of one of the things. and I I mostly got this from my mentors. who were. taught me programming language design in. the earlier 80s when you're teaching. programming. for for the the total newbie who has not. coded before in not in any other.

language. uh a whole bunch of Concepts in. programming are very alien or. sort of. new and and maybe very interesting but. also distracting and confusing and there. are many different things you have to. learn you have to sort of. in a typical. 13-week programming course you have to. if it's like really. learning to program from scratch you.

have to cover algorithms you have to. cover data structures you have to cover. syntax you have to cover variables Loops. functions recursion classes. Expressions operators there are so many. Concepts if you you sort of. if you can spend a little less time. having to worry about the syntax. the the classic example was often.

oh the compiler complains every time I. put a semicolon in the wrong place or I. forget to put a semicolon. uh python doesn't have semicolons in. that sense so you can't forget them and. you're also not. sort of misled into putting them where. they don't belong because you don't. learn about them in the first place. the flip side of that is forcing the. strictness onto the beginning programmer.

to teach them that programming is a. values attention to details you don't. get to just write the way you write in. English they have other details that. they have to pay attention to so I think. they'll they'll still get the message. about uh. paying attention to details the. interesting design choice so I still. program quite a bit in PHP and I'm sure. there's other languages like this but. the dollar sign before a variable. that was always an annoying thing for me.

it didn't quite fit into my. understanding of why this is good for a. programming language I'm not sure if you. ever thought about that one. that is a historical thing there is a. whole lineage of programming languages. PHP is one Pearl was one. on the union shell. uh is one of the oldest or or all the. different shells. the dollar was invented for that purpose.

because a very earliest shells had a. notion of scripting but they did not. have a notion of parameterizing the. scripting. right and so a script is just a few. lines of text. where each line of text is a command. that is read by a very primitive command. processor that then sort of takes the. first word on the line as the name of a. program and passes all the all the rest.

of the line as text into the program for. the program to figure out what to do. with as arguments. and so by the time scripting was. slightly more mature than the very first. script. there was a convention that just like. the first word of line is uh the name of. the program the following words. uh could be names of files.

input.text. output.html things like that. the next thing that happens is oh it. would actually be really nice if we. could have variables and especially. parameters for scripts parameters are. usually what starts this process. but now you have a problem because you. can't just. say the parameters are x y and z. and so now we we call say let's say x is.

the input file and Y is the output file. and let's forget about Z for now I have. my program. and I write program X Y well that. already has a meaning because that. presumably means. X itself is the file. it's a file name it's not a variable. name. uh and so. the inventors of of things like the. unique shell and I'm sure job command. language in at IBM before that.

uh. had to use. something that made it clear to the. script processor. here is an X that is not actually the. name of a file which you just pass. through to the to the program you're. running here is an X that is the name of. a variable yeah and. when you're writing a script processor. you try to keep it as simple as possible.

because at as certainly in the 50s and. 60s. uh the thing that interprets the script. was itself a very had to be a very small. program because it had to fit in a very. small part of memory and so saying oh. just look at each character and if you. see a dollar sign you jump to another. section of the code and then you gobble. up characters or say until the next. space or something and you say that's. the variable name.

and so it was was sort of. invented as. a clever way to make parsing of things. that contain but contain both variable. and fixed parts. very easy in a very simple script. processor it also helps even then it. also helps the human. author and the human reader of the. the script. to quickly see oh.

20 lines down in the script I see a. reference to x y z Oh it has a dollar in. front of it so now we know that x y z. must be one of the parameters of the. script well this is fascinating several. things to say which is. the leftovers from the simple script. processor languages are now in code. bases like behind Facebook or behind. most of the back end I think php's. probably still runs most of the back end. of the internet oh yeah yeah I think. there's a lot of it in Wikipedia too for. example yeah it's funny that those.

decisions are not funny it's fascinating. that those decisions permeate Through. Time. just like biological systems right. I mean that the sort of the inner. workings of DNA. have been stable for well I don't know. how long it was like 300 million years. half a billion years yeah and there. there are all sorts of weird quirks. there. that don't make a lot of sense if you. were to design. a system like self-replicating molecules.

from scratch but that system has a lot. of interesting resilience it has. redundancy that results like it messes. up in interesting ways that still is. resilient when you look at the system. level of the organism code doesn't. necessarily have that a program a. computer programming code you'd be. surprised. how much resilience modern code has. I mean if you if you look at the number.

of bugs per line of code. even in in very well tested. code that in practice works just fine. there are actually lots of things that. don't work fine. and there are error correcting or. self-correcting mechanisms at many. levels including probably the user of. the code well in the end the user who. sort of is told well you got to reboot. your your PC is part of that system and.

a slightly uh less drastic thing is. reload the page which we all know how to. do without thinking about it when. something weird happens you you try to. reload a few times before you say oh. there's something really weird okay or. try to click the button again if the. first time didn't work. well yeah that we should all have. learned not to do that because that's. probably just gonna turn the light back.

off yeah true so do it three times. that's the that's the right lesson so uh. and I wonder how many people actually. like the dollar sign like you said it is. documentation so to me it's whatever the. opposite of syntactic sugar is syntactic. poison to me it is such a pain in the. ass that I have to type in a dollar shot. also super error prone. so it's not self-documenting it's it's.

like a bug generating thing it is a kind. of documentation that's the pro and the. con is it's a source of a lot of bugs. but actually I have to ask you um. this is a really interesting idea of. bugs per line of code. if you look at all the computer systems. out there from the code that runs. nuclear weapons to the code that runs. all the amazing companies that you've. been involved with and not the code that. runs Twitter and Facebook and Dropbox. and Google and Microsoft Windows and so.

on. and we like laid out. wouldn't that be a cool like table bugs. per line of code and what would that. let's let's put like actual companies. aside do you think we'd be surprised by. the number we see there for all these. companies. that depends on whether you've ever read. about research that's been done in this. area before. and. I didn't know the the re the the last.

time I. I saw some research like that that was. probably in the 90s and the research. might have been done in the 80s but the. the conclusion was across a wide range. of different software different. languages. different companies. different development styles. the number of bugs is always. I think it's in the order of about one. bug per thousand lines in sort of.

mature software that that is considered. interesting as good as it gets can I. give you some facts here there's a lot. of good papers so you said mature. software right so here's uh. a report from a uh like programming. analytics company. now this is from a developer perspective. let me just say what it says because. this is very weird and surprising on. average a developer creates 70 bugs per.

1000 lines of code. 15 bugs per 1000 lines of code find. their way to the customers. but this is in the software they've oh I. was I was wrong by an order okay there. fixing a bug takes 30 times longer than. writing a line of code. that I can believe yeah 75 of a. developers time is spent on debugging. um that's for an average developer that. they Analyze This 15. argue.

1500 hours a year in us alone. 113 billion dollars to spend annually on. identifying and fixing bugs. imagine this is marketing literature for. someone who claims to have a golden. bullet or a silver bullet that makes all. that investment in fixing bugs go away. but that that is usually yeah not going. to yeah that's not gonna happen well. they're uh I mean they're referencing a. lot of stuff of course but it is a page.

uh that is you know there's a contact us. button at the bottom presumably if you. just spend a little bit less than 100. billion dollars we're willing to solve. the problem for you. right and there's also a report on stock. exchanges stack overflow on the exact. same topic but when I open it up at the. moment the page says stack Overflow is. currently offline for maintenance oh. it's ironic yes uh by the way their. error page is awesome anyway. I mean can you believe that number of.

bugs oh absolutely isn't that scary that. 70 bucks per 1000 lines of code so even. 10 bucks per thousand lives well that's. about one bug after every 15 lines and. that's when you're first typing it in. yeah from a developer but like how many. bugs are going to be found. if you're if you're typing well the. development process is extremely. iterative yeah typically you don't make. a plan for what software you're going to.

release a year from now yeah uh and work. out all the details because actually all. the details uh themselves consist. they're sort of compose a program. and that's that. being a program all your plans will have. bugs in them too and inaccuracies. uh but what what you actually do is. you do a bunch of typing and I'm I'm. actually really I'm a really bad typist.

that just I've never learned to type. with 10 fingers. how many do you use. well I could use all 10 of them but not. very well. but I I never I never took a talking. class and I never sort of corrected that. so the first time I I seriously learned. I had to learn the layout of a qwerty. keyboard. was actually in college in my first. programming classes where we used Punch. Cards.

and so. with my two fingers I sort of pecked out. my code. watch anyone. give you a little coding demonstration. they'll have to produce like four lines. of code. and now see how many times they use the. backspace key yeah because they made a. mistake and and. and some people especially when when. someone else is looking.

will will backspace over 20 30 40. characters to fix a typo earlier in a. line if you're. if you're slightly more experienced of. course you use your arrow buttons to go. or your mouse to but the mouse is. usually slower than uh than the arrows. but a lot of people when they type a 20. character word which is not unusual and. they realize they made us made a mistake. at the start of the word the backspace.

over the whole thing. and then retype it and sometimes it. takes three four times to get it right. so. I don't know what your definition of bug. is arguably mistyping a word and then. correcting it immediately is not a bug. on the other hand you you already. do sort of lose time and every once in a. while there's sort of a typo that you. don't get in that process. and now you've you've typed like 10.

lines of code. uh and some were in the middle of it you. don't know where yet is a typo or maybe. a thinko where you you forgot that you. had to initialize a variable or. something but those are two different. things and I would say yes you have to. actually run the code to discover that. typo but forgetting to initialize a. variable is a fundamentally different. thing because that thing can go. undiscovered uh that depends on the. language in Python it will not right in.

sort of modern compilers are usually. pretty good at catching that even. even foresee so for that specific thing. but actually deeper. it might there might be another variable. that has initialized but logically. speaking the one you meant related yep. it's like name the same but it's a. different thing and you forgot to. initialize uh whatever some counter or. some some basic variable they're using I. can tell that you've coded yes by the.

way I should mention that I use the. Kinesis keyboard. which has the backspace under the thumb. and one of the biggest reasons I use. that keyboard is because you realize in. order to use the backspace on a usual. keyboard you have to stretch your pinky. out. and like the the for most normal. keyboards the Backspaces under the pinky. and so I don't know if people realize. the pain they go through in their life.

because of the backspace keep being so. far away so with the Kinesis it's right. under the thumb so you don't have to. actually move your hands the backspace. and the delivery what do you do if. you're ever not with your own keyboard. and you have to use someone else's PC. keyboard that has a standard layout so. first of all it turns out that you can. actually go your whole life always. having the keyboard. with you so this well except for that. that little tablet that you're using so.

we're note taking right now right uh. yeah so it's very inefficient. note-taking but I'm not I'm just looking. stuff up but in most cases I would be. actually using the keyboard here right. now I just don't anticipate you have to. calculate how much typing do you. anticipate if I anticipate quite a bit. then I'll just I have a keyboard. and the same same with I mean. the embarrassing. of accepted being the weirdo that I am. but you know when I go on an airplane.

and I anticipate to do programming or a. lot of typing I will have a laptop that. will put pull out a Kinesis keyboard in. addition to the laptop and it's just who. I am you have to you have to accept who. you are. um but also it's a you know for a lot of. people. for me certainly there's a comfort space. where there's a certain kind of setups. that are maximized productivity and. um it's like some people have a warm.

blanket that they like. when they watch a movie I like the. Kinesis keyboard takes me to uh a place. of focus and I still mostly I I'm trying. to make sure I use the state-of-the-art. IDS for everything but my comfort place. just like the Kinesis keyboard is still. emacs. so. I still use I still I mean that's one of. some of the debates I have with myself. about everything from a technology.

perspective. is how much to hold on to the tools. you're comfortable with versus how much. to invest in using modern tools and the. signal that the communities provide you. with is the noisy one because a lot of. people year to year get excited about. new tools and you have to make a. prediction are these tools defining a. new generation or something that will. transform programming or is this just a. fad that will pass certainly with. JavaScript Frameworks and front and the.

back end of the web there's a lot of. different styles that came and went I. remember learning um what was it called. the action script I remember for flash. um you know learning how to program in. Flash uh learning how to design doing. graphic animation all that kind of stuff. in Flash same with Java applets I. remember creating quite a lot of java. applets thinking that this potentially. defines the future of the web and it did. not well you know in most cases like.

that the particular technology. eventually gets replaced. but. many of the concepts that the technology. introduced or made accessible first. are preserved of course. because yeah we're not using Java. applets anymore but the notion of. reactive web pages. that sort of contain little bits of code.

that respond directly to. something you do like pressing a button. or a link or hovering even. uh is has certainly not gone away. and that those animations that were made. painfully. complicated with flesh. I mean flash was an innovation when it. first came up. and when it was replaced by JavaScript. equivalence.

stuff. it was a somewhat better way to do. animations but those animations are. still there not all of them. but but sort of. again there is an evolution and often so. often with technology. the the sort of the technology that was. eventually thrown away or replaced. was still essential to to sort of. get started there wouldn't be jet planes. without propeller planes.

I bet you but from a user perspective. yes from the feature set yes but I from. a programmer perspective it feels like. all the time I've spent. with actionscript all the time I spent. with Java on the applet side for the GUI. development I well no Java I have to. push back that was useful that because. it transfers but the Flash doesn't. transfer so some things you learn and. invest time in what yeah what what you.

learned this the skill you picked up. learning action script yeah. was sort of it was perhaps. a super valuable skill at the time you. picked it up if if you if you learned. action script early enough but. that skill is no longer. in demand well that's the calculation. you have to make when you're learning.

new things like today people start. learning programming today I'm trying to. to see what are the new languages to try. what are the new uh systems to try that. what are the new IDs to try to to keep. keep improving because that's why we. start when we're young right. but that seems very true to me that that. when you're young you have your whole. life ahead of you and your you're. allowed to make mistakes in fact you. should you should feel encouraged to to.

do a bit of stupid stuff yeah try not to. get yourself killed or seriously maimed. but try stuff that. deviate from from what everybody else is. doing. and like nine out of ten times you'll. just learn why everybody else is not. doing that or why everybody else is. doing it some other way and one out of. ten times you sort of. you discover something that's better or.

that's that somehow works I mean there. are all sorts of crazy things that were. invented. uh by accident by people trying trying. stuff together. that's great advice to try random stuff. make a lot of mistakes once you're. married with kids you're probably going. to uh be a little more risk-averse. because now there's more at stake and. you've already hopefully had some time. where you where you were experimenting. with crazy shit I like how marriage and. kids solidifies their choice of.

programming language how does that the. robber Frost poem with the The Road Less. taken which I think is misinterpreted by. most people but anyway I I feel like the. choices you make early on. especially if you go all in they're. going to define the rest of your life's. trajectory in a way that. like you basically are picking a camp so. uh you know there's if you invest a lot. in PHP if you invest a lot in.net if you. invest a lot in JavaScript.

you're going to stick there. you that's that's your life Journey. only as far as that technology remains. relevant yes yes I mean if if at age 16. you learn coding in C. and by the time you're 26 C is like a. dead language. then there's still time to switch.

there's probably some kind of Survivor. bias or whatever it's called in in sort. of your observation that that you pick a. camp because there are many different. camps to pick and if you pick dot net. then then you can Coast for the rest of. your life because that technology is now. so ubiquitous of course that it's even. if it's if it's bound to die it's going. to take a very long time well for me.

personally. I had a very difficult in my own head. Brave leap that I had to take relevant. to our discussion which is most of my. life I programmed in C and C plus plus. and so uh having that hammer everything. looked like a nail. so I would literally even do scripting. in C plus plus like I would create. programs that do script like things and. uh when I first came to Google and and. before then it became already before.

tensorflow before all of that there was. a growing realization that c plus is not. the right tool for machine learning we. could talk about why that is it's. unclear why that is a lot of things. has to do with community and culture and. how it emerges and stuff like that but. for me they decided to take the leap to. python like all out basically switched. completely from C plus plus except for a. highly performant robotics applications. there were still uh.

there's still a culture of C plus plus. in in the space of robotics. that was a big leap. like I had to you know like like people. have like existential crises or midlife. crises or whatever you have to realize. almost like walking away from uh from a. person you love. um because I was sure that c plus would. have to be a lifelong companion for a. lot of problems I would want to solve C. plus would be there and it was a. question to say well that might not be. the case because sibo spots is still one.

of the most popular languages in the. world one of the most used one of the. most dependent on it's also still. evolving quite a bit I mean. that that is not a sort of a fossilizing. community yes they they are doing great. Innovative work actually a lot but yet. the sort of their Innovations are hard. to follow if you're not already a. hardcore C plus plus user well this was. the thing it pulls you in it's a rabbit. hole I was a hardcore the all meta.

programming template programming like I. I would start using the modern C plus. plus as it developed right not just the. not just the shared pointer and the. garbage collection that makes it easier. for you to work with some of the flaws. but the detail like The Meta programming. the the crazy stuff that's that's coming. out there but then you have to just. empirically look and step back and say. what language am I more productive in. sorry to say what language do I enjoy my.

life with more. and uh readability and able to think. through and all that kind of stuff that. those questions are harder to ask when. you already have. a loved one which in my case was C plus. plus and then there's python uh like. that Meme was is the the grass is. greener on the other side am I just. infatuated with a new fad new cool thing. or is this actually going to make my. life better and I think a lot of people.

face that kind of decision it was a. difficult decision for me. um when I made it at this time it's an. obvious switch if you're into machine. learning but at that time it wasn't. quite yet so obvious so it was a risk. and you know you have the same kind of. stuff with um. I still because of my connection to. Wordpress. I still do a lot of back-end programming. in PHP uh. and the question is you know node.js. python do you switch to do you switch.

back into any of those. programming there's the case for node.js. for me well more and more and more of. the front end it runs in JavaScript. um and fascinating cool stuff is known. as JavaScript maybe use the same. programming language for the back end as. well. uh the case for python for the back end. is well you're doing so much programming. outside of the web in Python so maybe. use Python for the back end and then the. case for PHP well most of the web still.

runs in PHP. you have a lot of experience with PHP. why uh fix something that's not broken. those are my own personal struggles but. I think they reflect the struggles of a. lot of people and with different. programming languages with different. problems they're trying to solve it's a. weird one and there there's not a single. answer right because depending on how. much time you have to learn new stuff. where you are in your life what what.

you're currently working on who you want. to work with what communities you like. yeah there's not one right choice. maybe if you if you sort of. if you can look back 20 years you can. say well that whole detour through. action script was a waste of time. but. nobody could know that. so you can you can beat yourself up over. that. uh you just need to accept that not. every choice you make.

is going to be perfect maybe sort of. keep Plan B in the back of your mind. uh but don't don't overthink it don't. don't try to sort of don't don't create. a spreadsheet with like where you're. trying to estimate well if I learn this. language I expect to make x million. dollars in a lifetime and if I learn. that language I expect to make why a. million dollars in a lifetime and which.

Which is higher and what which has more. risk and where's the chance that it's. like picking picking a stock. kind of kind of but uh. I think with stocks you can do. diversifying your investment as good. with productivity in life. boy that spreadsheet is possible to. construct. like if you actually carefully analyze.

what your interest in life are where you. think you can maximally impact the world. there really is better and worse choices. for a programming language that are not. just about the syntax but about the. community about where you predict the. community's headed. what large systems are programmed in. that but can you create that spreadsheet. because that sort of you're mentioning a. whole bunch of inputs that go into that. spreadsheet where you have to estimate. things that are very hard to measure and.

even harder I mean they're they're hard. to measure. retroactively and they're even harder to. predict like what is the better. community. well better is is one of those. incredibly difficult words what's better. for you is not better for someone else. no but we're not doing a public speech. about what's better we're doing a. personal spiritual journey I can. determine a circle of friends. circle circle one and circle two and I.

can have a bunch of parties with one and. a bunch of parties with two and then. right down or to take a mental note of. what made me happier right and that you. know you have if you're a machine. learning person you want to say Okay I. want to build a large company that does. that is grounded in machine learning but. also has a sexy interface that has a. large impact on the world what languages. do I use you look at what Facebook is. using you look at what Twitter is using. then you look at performance more newer.

languages like rust or you look at. languages that have taken that most the. community uses in the machine learning. space that's Python and you can like. think through you can hang out and think. through it and it's it's always a invest. and the the level of activity of the. community is also really interesting. like you said C plus plus and python are. super active in terms of the development. of the language itself. but do you think that you can make. objective choices there no no but.

there's a gut you build up like don't. you don't you believe in that gut. feeling everything is very subjective. and yes you most certainly can have a. gut feeling and your gut can also be. wrong that's why there are billions of. people because they're not all right I. mean clearly there are more people. living in the Bay Area who have plans to. sort of create a Google sized company. then there's room in the world for. Google sized companies and they're gonna. have to Duke it out in the market the.

space and there's many more choices than. just the programming language speaking. of which let's go back to the boat with. the with the fisherman who's tuned out. long ago I talked to the programmer. let's jump around and go back to see. python that we tried to Define as the. reference implementation and one of the. big things that's coming out in 3.11. what's the right way we tend to say 3.11. because it really was like we went 3.8. 3.9 3.10 3.11 and we're planning to go.

up to 3.99 99 what happens after 99. probably just 3.100 what if I make it. there okay. and go all the way to 420. I got it. forever python V3 we'll talk about four. but more for fun. so 3.11 is coming out one of the big. sexy things in it is it'll be much. faster so how did you beyond hiring a. great team or working with a great team.

make it faster what are some ideas. uh that may makes it faster. it has to do with Simplicity of software. versus performance. and so even though C is known to be a. low-level language which is. great for writing sort of. a high performance language interpreter. when I originally started python or C. python.

I. didn't expect there would be. great success and fame in my future. uh so I. I try to get something working. and useful. uh in about three months. and so I I sort of I cut corners. I borrowed ideas left and right when it. comes to language design as well as.

implementation. uh I also wrote much of the code as. simple as it could be. and. they're they're like. there are many things that you can code. more efficiently by adding more code. it's a bit of a sort of a time space. trade-off. where you can compute a certain thing. from a small number of inputs.

uh and every time you get presented with. new input. uh you do the whole computation from the. top. that can be simple looking code it's. easy to understand it's easy to reason. about that you can you can tell quickly. that it's correct in at least in the. sort of mathematical sense of correct. uh because it's implemented in C maybe. it performs relatively well.

but over time as sort of. as the requirements for that code and. the need for performance. go up. you might be able to rewrite that same. algorithm. using more memory maybe remember. previous results. so you don't have to recompute. everything from scratch like the the. classic example is Computing prime. numbers. like.

is 10 a prime number. well you sort of is it divisible by two. is it divisible by three is it divisible. by four and we go all the way to is it. divisible by 9. and it is not well. actually 10 is divisible by two so there. we stop but say 11. it's divisible by. ten the answer is nine is no ten times. in a row so now we know 11 is a prime. number. on the other hand if we already know. that 2 3 5 and 7 are prime numbers and.

you know a little bit about the. mathematics of how prime numbers work. you know that if you have a rough. estimate for the square root of 11 you. don't actually have to check is it. divisible by four or is it divisible by. five you all you have to check in the. case of 11 is is it divisible by 2 is it. divisible by three. because take 12. if it's divisible by 4 well 12 divided. by 4 is 3 so you you should have come.

across the question is it divisible by 3. first. so if you know basically nothing about. prime numbers except the definition. maybe you go for X from 2. through n minus 1 is n divisible by X. and then at the end if you got uh all. no's uh for every single one of those. questions you know oh it must be a prime. number well the first thing is you can.

stop iterating when you find a yes. answer. and the second is you can also stop. iterating when you have have reached. the square root of n because you know. that if it has a divisor larger than. than the square root did not also have a. divisor smaller than the square root. then you say oh except for two we don't. need to bother with checking for even. numbers because all even numbers are. divisible by two so if it's divisible by.

four. we would already have come across the. question is it divisible by two and so. now you go special case check is a. divisible by two and then you just check. three five seven eleven. uh and so now you've you've sort of. reduced your search Pace by 50 Again by. by skipping all the even numbers I kept. for two. if you think a bit more about it or you. just. read in your book about the history of. math one of the first algorithms ever.

written down. all you have to do is check is it. divisible by any of the previous prime. numbers that are smaller than the square. root. and before you get to a better algorithm. than that. you have to have several phds in in. discrete math so that's as much as I. know so of course that same story. applies to a lot of other algorithms. string matching is a good example.

of uh how to come up with an efficient. algorithm and sometimes yeah the more. efficient algorithm is not so much more. complex than the inefficient one but. that's an art and it's not always the. case in the general cases the more. performant the algorithm the more. complex it's going to be there's a. there's a kind of trade-off the simpler. algorithms are also the ones that people. invent first. because when you're looking for a. solution. you look at the simplest way to get.

there first. and so if there is a simple solution. even if it's not the best solution not. the fastest or the memory most memory. efficient or whatever. a a simple solution and simple is is. fairly subjective but mathematicians. have also thought about sort of what is. a good definition for simple in the case. of algorithms. uh but the simpler the simpler Solutions.

tend to be. easier to follow for other programmers. who haven't made a study of a particular. field and when I when I started with. python I I was a good programmer in. general I knew sort of basic data. structures I knew the C language pretty. well. but there were many areas where I was. only somewhat familiar with the state of. the art. and so I I picked.

in many cases the simplest way I could. solve a particular sub problem because. when you when you're designing and. implementing a language you have to like. you've many hundreds of little problems. to solve. and you have to have solutions for every. one of them before you can can sort of. say I've invented a programming language. first of all so see python what kind of. things does it do it's an interpreter it.

takes in this readable language that we. talked about that is python what is it. supposed to do The Interpreter basically. it's it's sort of a recipe for. understanding recipes. so instead of a recipe that says bake me. a cake we have a recipe for. well given. the text of a program. how do we run that program and and that.

is sort of the recipe for building a. computer the recipe for the Baker and. the chef yeah what are the. algorithmically tricky things that. happen to be low-hanging fruit that. could be improved on maybe throughout. the history of python but also now how. is it possible that 3.11 in year 2022. it's possible to get such a big. performance Improvement. we focused.

on a few areas where we we still felt. there was low hanging fruit. the biggest one is actually The. Interpreter itself. and this has to do with details of Pi. how python is defined so I didn't know. if the fisherman is going to follow this. story he already he already jumped off. the boat his uh he's he's this yeah. stupid python is actually even though. it's always called an interpreted.

language it's there's also a compiler in. there it just doesn't compile to machine. code it compiles to bytecode which is. sort of code for an imaginary computer. that is called the python interpreter so. it's compiling code that is more easily. digestible by The Interpreter or is. digestible at all it is the code that is. digested by The Interpreter that's the. compiler we tweaked very minor bits of. the compiler almost all the work was. done in The Interpreter.

because. when you have a program you compile it. once and then you run the code a whole. bunch of times. or maybe there's one function in the in. the code that gets run many times. now I know that that sort of people who. who know this field are expecting me to. at some point say we built adjusting. time compiler actually we didn't we just. made The Interpreter uh a little more.

efficient what's adjust in time compiler. that is a thing from the Java World. although it's now applied to almost all. uh programming languages especially. interpreted ones so you see the compile. inside python not like a just-in-time. compiler but is it compiler that creates. by code that is then. fed to The Interpreter and the compiler. was there something interesting to say. about the compiler it's interesting that. you haven't changed that tweak that at.

all or much we changed some parts of the. byte code. but not very much and so we only had to. change the parts of the compiler where. we decided that the the breakdown of a. Python program in bytecode instructions. had to be slightly different. but. that did that didn't gain us the. performance uh improvements that. performance improvements were like.

making The Interpreter faster in part by. sort of. removing the fat from some internal data. structures used by The Interpreter but. uh the the key idea is an Adaptive. specializing interpreter. let's go what is adaptive about it what. is specialized about it well let me. first talk about the specializing part. because the Adaptive part is the sort of.

the second order effect but they're both. important so bytecode. is a bunch of machine instructions but. it's an imaginary machine but the. machine can do things like call a. function. add two numbers. print value. those are sort of typical instructions. in Python. uh and if we take the example of adding. two numbers. actually in Python the language there's.

no such thing as adding two numbers. there's just an the the compiler. doesn't know that you're adding two. numbers you might as well be adding two. strings or two lists. uh or two instances of some user-defined. class that happen to implement this. operator called add. that's a very interesting and and fairly. powerful mathematical concept it's. mostly a user interface trick because it.

means that. a certain category of functions. can be written using a symbols single. symbol the plus sign. and sort of a bunch of other functions. can be written using another single. symbol the multiply sign. uh so if we take addition the way. traditionally in Python the ad byte code. was executed is. pointers pointers and more pointers so.

first we we have two objects an object. is basically a pointer to a bunch of. memory that contains more pointers. pointers all the way down. not quite but there there are a lot of. them so to simplify a bit uh we look up. in one of the objects. what is the type of that object and does. that object type Define an add operation. and so you can imagine that there is a.

sort of a type integer that knows how to. add itself to another integer and there. is a type floating Point number that. knows how to add itself. to another floating Point number. and the integers and floating Point. numbers are sort of important I think. mostly historically because in the first. computers. uh you use the sort of the same bit. pattern when interpreted as a floating.

Point number had a very different value. than we interpret it as an integer can I. ask a dumb question here please do given. the basics of ant and float and add who. carries the knowledge of how to add two. integers is it the integer it's the type. integer versus it's the type integer and. the type float what about the operator. is the operator. just exists as a platonic form possessed. by uh the operator is more like.

it's an index in a list of functions. that the integer type defines. and so the integer type. is really a collection of functions and. there is an add function and there's a. multiply function and there are like 30. other functions for other operations. there's a power function for example. and. you can imagine that.

in in memory there is a distinct slot. for the add operations let's say the add. operation is the first operation of a. type and the multiply is the second. operation of a type. so now we take the integer type and we. take the floating Point type. in both cases the add operation is the. first slot and multiplies the second. slot but. each slot contains a function and the.

functions are different because the the. add to integers function interprets the. bit patterns as integers that add to. float. function interprets the the same bit. pattern as. as a floating Point number and then. there is the string. data type which again interprets the the. bit pattern as a. the address of a sequence of characters.

there are lots of lies in that story but. that's. that's sort of a basic idea I can tell I. could tell the fact the fake news and. the fabrication going on here at the. table but uh where's the optimization is. it on the operator is it a different so. inside the integer optimization is the. observation that. in a particular line of code. so now you you write your little Python.

program and you write a function and. that function sort of takes a bunch of. inputs and at some point it adds two of. the inputs together. now I bet you even if you call your. function a thousand times. that all those calls are likely all. going to be about integers because maybe. your program is all about integers or. maybe. on that particular line of code where. there's that plus operator.

every time the program hits that line. the variables A and B that b are being. added together happen to be strings. and so what we do is instead of having. this single byte code that says here's. an ad operation and the implementation. of add is fully generic it looks at the. object from the object it looks at the. type then it takes the type and it looks. at looks of the function pointer then it. calls the function now the function has.

to be has to look at the other argument. and it has to double check that the. other argument has the right type. and then there's a bunch of error. checking before it can actually. just go ahead and add the two bit. patterns in the right way. what we do is. every time we execute an ad instruction. like that. we we keep a little note of. in the end after.

we hit the code that that did the. addition. for a particular type what type was it. and then after a few times through that. code if it's this if it's the same type. all the time. uh we say oh so this add operation even. though it's the generic ad operation it. might as well be the add integer. operation and add integer operation is.

uh much more efficient because it just. says. assume that A and B are integers do the. addition operation do it right there. inline and produce the result. and the big lie here is that in Python. even if you have great evidence that in. the past it was always too integers that. you were adding at some point in the. future that same line of code could.

still be hit with two floating points or. two strings or maybe a string and an. integer it's not a great lie that's just. the fact of life. I didn't account for what what should. happen in that case in in the way I told. the story there is some accounting and. and so what we actually have to do is. when we have the add integer operation. we still have to check. are the two arguments in fact integers.

we applied some tricks to make those. checks efficient. and we know statistically that the. outcome is almost always yes they were. they are both integers. uh and so we quickly make that check and. then we proceed with the the sort of add. integer operation and then there is a. fallback mechanism where we say. oops one of them wasn't an integer. now we're going to pretend that there. was just the fully generic ad operation.

we wasted a few Cycles believing it was. what was going to be two integers and. then we had to back up but we didn't. waste that much time and statistically. uh most of the time. basically we were sort of. hoping that most of the time we guess. right because if we if it turns out that. we guessed wrong too often. uh or we didn't have a good guess at all.

uh things might actually end up running. a little slower. so someone with armed with this. knowledge. and a copy of the implementation someone. could easily construct a counter example. where they say oh I have a program and. then now it runs five times as slow in. Python 311 than it did in Python 310. but that's a very unrealistic program. that's that's just like an extreme fluke. it's a fun reverse engineering task.

though oh yeah so there's uh. well people like fun yes so there's some. presumably heuristic. of what defines a momentum. of uh saying you know you seem to be. working adding two integers not two. generic types uh so how do you figure. out that heuristic I think that the. heuristic is actually we assume that the. weather tomorrow is going to be the same.

as the weather today so you don't need. two days of the weather no. that is already so much better than than. guessing randomly that so how do you. find this idea. hey I wonder if instead of adding to. generic types we uh we start assuming. that the weather tomorrow is the same as. the weather today. where do you find the idea for that. because that ultimately. for you to do that you have to kind of.

understand how people are using the. language right python is not the first. language to do a thing like this this is. a fairly well-known trick especially. from. other interpreted languages that had. reason to be sped up we occasionally. look at papers about hhvm which is for. Facebook's uh. efficient compiler for uh PHP there are. tricks known from the jvm and.

sometimes it just comes from Academia. and so the trick here is that the type. itself doesn't the variable doesn't know. what type it is. so this is not a statically typed. language where you can. this is a trick that is especially. important for uh for interpreted. languages with Dynamic typing because. if. if the compiler could read in the source.

these X and Y that we're adding our. integers the compiler can just insert. the single add machine code that. Hardware machine instruction that exists. on every CPU and ditto for floats. uh but because in Python you don't. generally declare your the types of your. variables you you don't even declare the. existence of your variables they just. spring into existence when you first. assign them which.

is really cool and and sort of helps. those beginners because there's less. bookkeeping they have to learn how to do. before they can start playing around. with code but it makes the the in. interpretation of the code less. efficient and so we're we're sort of. trying to. to make the interpretation more. efficient without losing the the super. Dynamic nature of the language that's.

always the challenge 3.5 got the pep 484. type hints. what is Type hinting and is it used by. The Interpreter the hints or is it just. syntactic sugar so the type hints is an. optional mechanism that people can use. and it's especially popular with sort of. larger companies that have very large. code bases written in Python do you. think of it as almost like documentation.

saying these two variables are this type. more than documentation I mean so it. it is a sub language of python where. where you can express the types of. variables so here's a variable and it's. an integer and here's an argument to. this function and it's a string and here. is a function that returns a list of. strings but that's not checked when you. run the code but. exactly there there is a separate piece. of software called a static type Checker.

that reads all your source code without. executing it and things long and hard. about. what it looks from just reading the code. that code might be doing. and double checks if that makes sense if. you take the types as annotated into. account so this is something you're. supposed to run as you develop it's like. a linter yeah that's definitely a. development tool but the type. annotations currently are not used for.

uh speeding up The Interpreter and there. are a number of reasons uh many people. don't use them. even when they do use them uh they. sometimes contain lies where the static. type Checker says everything's fine. I cannot prove that this integer is ever. not an integer but at runtime somehow. someone manages to violate that.

assumption. and The Interpreter. ends up doing just fine if we started. enforcing type annotations in Python. many python programs would no longer. work. and some python programs wouldn't even. be possible because they're too dynamic. and so we made we made a choice of not. using the annotations there there is a. possible future where eventually. three four five releases in the future.

we could start using those annotations. to sort of. provide hints because we can we can. still say well the source code leads us. to believe that these X and Y are both. integers and so we can generate an add. an add integer instruction. but we can still have a fallback that. says oh if the if somehow the code code.

at runtime provided something else maybe. it provided two decimal numbers. we can still use that generic ad. operation as a fallback but we're not. there is there currently a mechanism or. do you see something like that where you. can almost add like an assert. inside a function that says please check. that my type hints are actually mapping. to reality sort of like insert manual. static typing there are third-party.

libraries that uh are in that business. so it's possible to do that kind of. thing it's possible to for a third party. library to take a hint. and enforce it it seems like a tricky. thing what what well what we actually do. is and this I think this is a fairly. unique feature in Python the type hints. can be introspected at runtime so while. the program is running. they mean python is a very.

introspectable language you can look at. a variable and ask yourself what did. what is the type of this this variable. and if that baby that variable happens. to refer to a function you can ask what. are the arguments to the function. and nowadays you can also ask what are. the type annotations for the function so. the type annotations are there inside. the variable as it's at runtime they're. mostly associated with the function. object not with each individual variable.

but uh right you can sort of map from. from the arguments to the variables and. that's what a third-party Library can. have exactly and the problem with that. is that all that extra runtime type. checking. uh is going to slow your code down. instead of speed it up I think uh to. reference this. uh sales pitchy blog post that says 75. of developers time to spend on debugging. I would say that in some cases that. might be okay it might be okay to pay.

the cost of performance. for the catching of the types the type. errors. and in most cases doing it. statically before you ship your code to. production is more efficient than doing. it at runtime piecemeal yeah. can you tell me about. m-y-p-y my pie project. what is it what's the mission and in. general what is the future of static.

typing in Python. well so my pie uh was started by a. Finnish uh developer ukulele. so many cool things out of Finland I. gotta say just that part of the world I. guess people have nothing better to do. in those long cold Winters yeah I don't. know I think Yuka lived in England when. he invented uh that stuff actually but. my pie is the original static type. checker for Python and the the type.

annotations that were introduced with. pep484. were sort of developed. together with the the static type. Checker and in fact Yuka had first. invented a different syntax that wasn't. quite compatible with python. and uh yukai and I sort of met at the. python conference in I think in 2013. and we we sort of came up with a.

compromise syntax. that would not require any changes to. python. and that would let my pie sort of be an. add-on static type checker for python. just out of curiosity was it like double. colon or something what was he proposing. that would break python I think he was. using angular brackets for uh types like. in C plus plus or uh Java generics yeah. you can't use angular brackets in Python.

it would be too tricky. for attempt well we the the key thing is. that we already had uh you know a Syntax. for annotations we just didn't know what. to use them for yet. so type annotations were just the sort. of most logical thing to to use that. existing dummy Syntax for. so but there was no there was no Syntax. for uh defining generics.

directly syntactically in the language. my pie literally meant my version of. python where my it refers to Yuka. he had a parser that translated my pie. into python by like doing the type. checks. and then removing the annotations and. all the angular brackets from the. positions where where he was using them.

but a preprocessor model doesn't work. very well with the typical workflow of. uh python development projects. that's funny I mean that could have been. another major split if it became. successful like uh if you watch. typescript versus JavaScript. is it like a split in the community over. types right that seems to be stabilizing. now it's not necessarily a split there. are certainly plenty of people who don't. use typescript but.

just use the original JavaScript. notation just like there are many people. in the python world who don't use type. annotations and don't use static type. Checkers now I know but there is a bit. of a split between typescript and. JavaScript old school JavaScript AES. whatever well in the JavaScript world. transpilers are sort of the standard way. of working anyway which is why. typescript being a transpiler itself is. not a big deal. and transplants for people who don't.

know it's what's exactly the thing you. said with my pies it's the code I guess. you call it pre-processing code that. translates from one language to the. other and that's part of the culture. part of the workflow of the JavaScript. community so that's right at the same. time. an interesting development in the. JavaScript slash typescript world at the. moment is that. there is a proposal under consideration. it's only a stage one proposal. that proposes to add a feature to.

JavaScript where just like python it. will ignore certain syntax. when running the JavaScript code. and what it ignores is more or less a. superset of The typescript annotation. syntax. interesting so that would mean that. eventually if you wanted to you could. take typescript. uh and you could shove it directly into.

a JavaScript interpreter without. transplation. the interesting thing in the JavaScript. world at least the web browser world. the web browsers have changed how they. deploy and uh they they sort of update. their JavaScript engines. much more quickly than they used to in. the the early days and so there's much. less of a need for. translation in JavaScript itself because.

most browsers just support the most. recent version of ecmascript just on a. tangent of a tangent do you see if you. will recommend somebody use a thing. would you recommend typescript or. JavaScript. I would recommend a typescript just. because of the strictness of the typing. it's an enormously helpful extra tool. that helps you sort of. keep your head straight about. what your code is actually doing.

I mean it's it's it it helps with. editing your code it helps with ensuring. that your code. is not too incorrect. and it's actually. quite compatible with JavaScript never. mind this syntactic sort of hack that is. still years in the future. but. any library that is written in pure. JavaScript can still be used from. typescript programs and also the other.

way around you can write a library in. typescript and then export it in a form. that is totally consumable by JavaScript. that sort of compatibility is is sort of. the key to this to the success of. typescript. yeah just to look at it as almost like a. biological system that's evolving it's. fascinating to see JavaScript evolve the. way it does well maybe we should. consider that biological systems are. just the Engineering Systems too right.

yes but very advanced. with more history. but it's almost like the most visceral. in the JavaScript world because there's. just so much code written in JavaScript. that for its history was messy if you. talk about bugs per line of code I just. feel like JavaScript. eats the cake or whatever the. terminology is it beats python by a lot. in terms of number of bugs meaning like. way more bugs in JavaScript and then and.

then the obviously the browsers the. develop I mean just there's so much. active development it feels a lot more. like Evolution where a bunch of stuff is. born and dies and there's. experimentation and debates versus. python is more. um all that stuff is happening but. there's just a longer history of stable. working giant software systems written. in python versus JavaScript is just a. giant beautiful I would say mess of code.

it's very different culture and. to some extent differences in culture. are random but to some extent they the. differences have to do with the. environment yeah uh and the fact that. JavaScript is primarily. the language for uh developing web. applications especially the client side. and the fact that it's basically the. only language for developing web.

applications. makes that Community sort of just have a. different nature than the community of. other languages. plus the graphical component. um and the fact that they're deploying. it on all kinds of uh shapes of screens. and devices and all that kind of stuff. it just creates a beautiful chaos anyway. back to my fight. so what okay you you met you talked. about a syntax that could work. where does it currently stand.

what's the future of static typing in. Python. it is still controversial but it is much. more accepted than when my pi and pep. 484 were were young. what's the connection between uh pep 484. type hints and my pie my pie. was the original static type Checker so. it might buy quickly evolved from yuka's. own variant of python to a static type.

checker for Python and uh sort of Pep. 484 that that was it like. a very productive year where like many. hundreds of messages were exchanged. debating that merits. of every aspect of of that pep. and so my pie is a static type checker. for python it is itself written in. Python. most. additional static typing features that.

we introduced in the time since three. six. uh we're also prototyped through my pie. my pie being an open source project with. a very small number of maintainers. it was successful enough that people. said the aesthetic type checking stuff. for python is actually worth an. investment for our company. nice but. somehow they chose not to support.

making my pie faster say or adding new. features to my Pi but both Google and. Facebook and later Microsoft developed. their own static type Checker I think. Facebook was one of the first. they decided that they wanted to use the. same technology that they had. successfully used for hhvm.

because they they sort of they had a. bunch of compiler writers and and sort. of static type checking experts who had. written the hhvm compiler and it was a. big success within the company. and they had done it in a certain way. sort of. they wrote a big highly parallel. application in an obscure language named. o camel which is apparently mostly very. good for a writing static type checkers.

interesting yeah I have a lot of. questions about how to write a static. type Checker then that's very confusing. Facebook wrote their version and they've. worked on it in secret for about a year. and then they came clean and went open. source. uh Google in the meantime was developing. something called Pi type which was. mostly. interesting because it as you may have. heard they have one gigantic mono repo.

so all the code is checked into a single. repository Facebook has a different. approach so Facebook developed pyre. which which was written in O camel which. worked well with Facebook's development. workflow. and Google developed something they. called Pi type which was actually itself. written in Python. uh and it was meant to sort of fit well. in. their static type checking needs in.

Google's gigantic mono repo so Google. wasn't one giant got it so the just to. clarify this static type checker. philosophically is a thing that's. supposed to exist outside of the. language itself and it's just a workflow. like a debugger for the book it's a. linter for people who don't know a. linter maybe you can correct me but it. it's the thing that runs through the. code continuously. pre-processing to find issues based on.

style documentation I mean there's all. kinds of linters right you can check. that what usual things does a linger do. maybe check that you haven't too many. characters in a single line linters. often do static analysis where they try. to point out things that are likely. mistakes but not incorrect according to. the language specification like maybe. you have a variable that you never use.

for the compiler that is valid you might. sort of you might be planning to use it. in future version of the of the code and. the compiler might just optimize it out. but the compiler is not going to tell. you hey you're never using this variable. a linter will tell you that variable is. not used maybe there's a typo somewhere. else where you meant to use it but you. accidentally use something else or there. are a number of sort of common scenarios. and A linter is often.

a a big collection of little heuristics. where by looking at the combination of. how your code is laid out maybe how it's. indented maybe the comment structure. uh but also just. things like definition of names use of. names. it'll tell you likely things that are. wrong and in some cases linters are are. really style checkers.

uh for python there are a number of. linters that check things like. do you use the the pep 8. recommended naming scheme for your. functions and classes and variables. because like classes start with an. uppercase and the rest starts with a. lowercase and. there's like differences there and so. the linter can tell you hey you have a. class that uh whose first letter is not. an uppercase letter and that's just I.

just find it annoying if I wanted that. to be an uppercase letter I I would have. typed an uppercase letter but other. people find it very comforting that if. the linter is no longer complaining. about their code that they have followed. all the style rules maybe it's a fast. way for a new developer joining a team. to learn the style rules right yeah. there's definitely that but the best use. of linter is probably. not so much to to sort of. enforce team uniformity but to actually.

help Developers. catch bugs that the compilers for. whatever reason don't catch and there's. lots of that in Python and so uh but a. static type checker. focuses on a particular aspect of the. linting which. I mean it might probably doesn't care. how you name your classes and variables. uh. but it is meticulous about when you say.

that there was an integer here and. you're passing a string there it will. tell you hey that string is not an. integer so something's wrong either. either you were incorrect when you said. it was an integer or you're incorrect. when you're passing into string if this. is a race of static type Checkers is. somebody winning as you said it's. interesting that the companies didn't. choose to invest in this uh centralized. development. of my pie is is there a future for my.

pie. what do you see as the oh well one of. the companies went out and everybody. uses like uh Pi type whatever Google's. is called well Microsoft is hoping that. uh Microsoft's horse in that race called. pyrite is going to win by right right. like r i g h t correct yeah my my all my. word processors tend to typo correct. that as pyrite the name of the I don't.

know what it is. some kind of semi-precious metal all. right. I love it okay so okay that's the. Microsoft hope but it okay so let me ask. the question a different way is there. going to be ever a future whereas the. static type Checker gets integrated into. the language. nobody is currently excited about. doing any work towards that that doesn't. mean that five or ten years from now.

the situation isn't. different. uh. at the moment. all the static type checkers. uh still evolve at a much higher speed. than Python and its annotation syntax. evolve you get a new release of python. once a year those are the only times. that you can introduce new annotation.

syntax and there's there are always. people who invent new new annotation. syntax that they're trying to push. uh and worse. once we've all agreed that we are going. to put some new syntax in we can never. take it back. at least a sort of deprecating an. existing feature takes many releases. because you have to assume that people. started using it as soon as we announced. it. and then you can't take it away from.

them right away you have to start. telling them well this will go away but. we're not gonna commit tell you that. it's an error yet and then later it's. going to be a warning and then. eventually three releases in the future. maybe we remove it. on the other hand the typical static. type checker. still has a release like. every month every two months certainly. many times a year.

uh some type Checkers also include a. bunch of. experimental ideas that aren't official. standard python syntax yet yeah uh the. static type Checkers also just get. better at discovering. things that that sort of are unspecified. by the language but that sort of could. make sense and so each static type. Checker actually has its sort of strong. and weak points so it's cool it's like a.

laboratory of experiments yep Microsoft. Google and all and you get to see and. you see that everywhere right because. there's not one single uh JavaScript in. engine either there is one in Chrome. there is one in Safari there's one in. Firefox. but that said you said there's not. interest I think there is a lot of. interest in type hinting right. um in the pep 484. actually like how. many people use that do you have a sense. how many people use because it's.

optional it's the sugar I can't put a. number on it but. from the number of packages that do. interesting things with it at runtime. and the fact that there are like. now three or four very mature type. checkers. that each have their their segment of. the market and oh and then there is a. pie charm which has a sort of more. heuristic based type Checker that also. supports the same syntax.

my assumption is that. many many people developing python. software professionally. for some kind of. production situation are using a static. type checker especially any anybody who. has a continuous integration cycle. probably has a. one of the steps in in there their. testing routine that that happens for. basically every every commit.

uh is run a static type checker and in. most in most cases that will be my pie. so I think it's pretty popular topic. according to this webpage. 20 to 30 percent of Python 3 code bases. are using type hints. wow I wonder how they measured that did. they just scan all of GitHub. yeah that's what it looks like yeah they. did a quick sentence all of but like a.

random sampling. so you mentioned pie charm let me ask. you the uh the big subjective question. what's the best IDE for Python and. you're extremely biased now that you're. with Microsoft. um is it pie charm vs code Vim or emex. historically I actually uh started out. with using Vim but when it was still. called VI. uh for a very long time I think from the.

early 80s to uh. I'd say two years ago. I was emacs user nice between I'd say. 2013 and 2018. I dabbled with pie charm. uh mostly because it had. had a couple of features I mean. pie charm. is like deriving an 18-wheeler truck.

whereas emacs is more. foreign. driving uh your comfortable Toyota car. that's that's that that you've had for a. hundred thousand miles and you know what. every little rattle of the car means. I was very comfortable in emacs uh but. there were certain things it couldn't do. it wasn't very good at at sort of at. least the way I had configured it.

I didn't have very good Tooling in emacs. for finding a definition of a function. got it when I was at Dropbox. exploring a 5 million line python code. base. uh just grabbing all that code for where. they're where is there a class Fubar. Well turns out that if you grab all five. million lines of code there are many. classes with the same name. and so pycharm sort of once once you've.

fired it up and once it's indexed your. repository uh was very helpful but as. soon as I had to edit code I would jump. back to emex and do all my editing there. because I could type much faster and. switch between files when I was when I. knew which file I wanted much much. quicker and I never really got used to. the the whole pie charm user interface. yeah I feel torn in that same kind of. way because I've used pycharm off and on.

exactly in that same way. and I feel like I'm just being an old. grumpy man. for not learning how to quickly switch. between files and all that kind of stuff. I feel like that has to do with. shortcuts that has to do with um I mean. you just have to get accustomed just. like with touch typing yeah you have to. just want to to learn that I mean if you. don't need it much you don't need touch. typing either you can type with two. fingers just fine in the short term but. in the long term your life will become. better psychologically and productivity.

wise if you learn how to type with 10. fingers if you do a lot of keyboard. input before everyone emails and stuff. right like you look at the the next 20. 30 years of your life you have to. anticipate where technology is going. um do you want to invest in handwriting. notes probably not more and more people. are doing uh typing versus handwriting. notes so you can anticipate that so. there's no reason to actually practice. handwriting there's more reason to. practice typing.

you can actually estimate back to the. spreadsheet the number of. paragraphs sentences or words you write. for the rest of your life. yes I mean all of that is not actual. like converting to a spreadsheet but. it's a gut feeling like I have the same. kind of gut feeling about books I've. almost exclusively switched to Kindle. now so ebook readers. even though I still love and probably.

always will the smell the feel of a. physical book. and. you the reason I switched to Kindle is. like all right well this is really. Paving the future is going to be digital. in terms of consuming books and content. of that nature so you should get you. know you should let your brain get. accustomed to that experience. in that same way it feels like pie charm. or vs code I think pycharm is is the the. most sort of sophisticated featureful uh.

python ID it feels like I should. probably at some point very soon switch. entire like I'm not allowed to use. anything else for python than this ID or. vs code it doesn't matter but walk away. from emacs for this particular. application because I think I'm limiting. myself in the same way that using two. fingers for typing is limiting myself. it's um this is a therapy session this. isn't I'm not even asking questions.

but I'm sure a lot of people are not. going to stop you uh. I I think that that sort of everybody. has to decide for themselves which one. they want to to invest more time in. I actually. ended up giving vs code a very tentative. try when I started out at Microsoft and. really liking it. and it sort of it took me a while before. I realized why that was.

but and and I think that actually the. founders of vs code may not necessarily. agree with me on this. but to me vs code is in a sense the. spiritual successor of emacs. because. as you probably know as an old emacs. hack. the the key part of emacs is that it. it's mostly written in in lisp. and that that sort of new features of of.

emacs usually update all the list. packages and add new list packages and. oh yeah there's also. some very obscure thing improved in the. part that's not in lisp. but that's usually not why I would. upgrade to a new version of emacs. there's a core implementation. that that sort of. can read a file and it can put bits on. the screen and it can sort of manage.

memory and buffers and then what makes. it an editor full of features is all the. list packages and of course the design. of how the list packages interact with. each other and with that that sort of. that base layer of of the the core. immutable engine without almost. everything in that core engine in emacs. case can still be overridden or replaced. and so.

vs code has a similar architecture where. there is like. a base engine that you have no control. over. I mean it's open source but nobody. except the people who work on that part. changes it much. uh and it has a sort of a package. manager. and a whole series of interfaces for.

packages and an additional series of. conventions for how packages should. interact with the lower layers and with. each other. and Powerful primitive operations that. let you. move the cursor around or select pieces. of text or delete pieces of text or. interact with the keyboard and mouse and. what other peripherals you have. and and so the sort of the the extreme.

extensibility and the package ecosystem. that you that you see in vs code is a is. a mirror of very similar architectural. features in emacs well I'll have to give. it a serious try because uh as far as. sort of the hype and the excitement in. the general programming Community vs. code seems to dominate the interesting. thing about. pie charm and. uh what is it PHP storm which are these.

jet brains uh specific IDs that are. designed for one programming language. it's interesting to. when an ID is specialized right they're. usually actually just specializations of. IntelliJ because underneath it's all the. same. editing Engine with different. veneer on top. where in vs code. many things you do.

require. loading third-party extensions. in pycharm it is possible to have. third-party extensions but it is it is a. struggle to create one yes and it's not. part of the culture all that kind of. stuff yeah we that I remember that it. might have been five years ago or so we. were trying to get some better my Pi. integration into pie charm because my. pie is sort of python tooling and.

pycharm. had had its own. type checking heuristic thing that we. wanted to replace with uh something. based on my pie because that was what we. were using in the company and it for the. for the guy who was writing that. by charm extension it was really a. struggle to to sort of find. documentation and get the development. workflow going and and debug his code.

and all that so that that was was not a. pleasant experience. let me talk to you about parallelism. in your post titled reasoning about. async IO semaphore. you talk about a fast food restaurant. Silicon Valley that has only one table. is this a real thing I just wanted to. ask you about that is that just like a. metaphor you're using or is that an. actual restaurant in Silicon Valley it. was it was a metaphor of course okay. I can imagine such a restaurant so for. people who don't then read the thing you.

should you should but it was uh. idea of a restaurant where there's only. one table and you show up one at a time. and you're prepared and I actually. looked it up and there is restaurants. like this throughout the world and it. just seems like a fascinating idea you. stand in line you show up there's one. table. they um they ask you all kinds of. questions they cook just for you that's. fascinating it sounds like you'd find.

places like that in Tokyo it sounds like. a very Japanese thing or in the Bay Area. there are proper places that probably. more or less work like that but I've. never eaten at such a place the. fascinating thing is you propose is the. fast food this is all for a burger it. was one of my rare sort of more literary. or poetic moments where I thought I'll. I'll just open with a crazy example to. catch your attention and the rest is. very dry stuff about uh locks and.

semaphores and how uh semaphore is a. generalization of a lock well it was. very poetic and well delivered and it. actually made me wonder if it's real or. not because you don't make that explicit. and it feels like it could be true and. in fact I wouldn't be surprised if. somebody like listens to this and knows. exactly a restaurant like this in. Silicon Valley anyway can we step back. and can you just talk about parallelism. concurrency threading. asynchronous all these different terms. what is it sort of a high philosophical.

level the the fisherman is back in the. boat well the idea is if the fisherman. has uh two fishing rods. uh since fishing is mostly a matter of. waiting for a fish to nibble well it. depends on how you do it actually but if. you had two if if you're doing the style. of fishing where you sort of you you. throw it out and then you let it sit for. a while until maybe you see a nibble one. fisherman can easily run two or three or.

four. fishing rods and so as long as you can. afford the equipment you can catch four. times as many fish by. a small investment in four fishing rods. and so since your time you sort of say. you have all Saturday to go fishing if. you can catch four times as much fish. you have a much higher productivity and. that's actually I think how deep sea. fishing is done you could just have a. rod and you put in a hole so you could. have many rods uh what is there an.

interesting difference between. parallelism and concurrency. and asynchronous is there one subset of. the other to you like how do you think. about these terms in the computer World. there is a big difference when people. are talking about parallelism uh like a. parallel computer. that's usually really. several complete CPUs that are sort of. tied together and and.

share something like memory or an i o. bus. uh concurrency can be a much more. abstract concept. where. you have the illusion that things happen. simultaneously but what the computer. actually does is. it spends a little time running some. this program for a while and then it. spends some time running that program. for a while and then spending some time. for the third program for a while.

the parallelism is the reality and. concurrency is part reality part. illusion yeah parallelism typically. implies that there is multiple copies of. the hardware. you write that implementing. synchronization Primitives is hard in. that blog post and you talk about locks. and semaphores why is it hard to. implement synchronization Primitives. because at the conscious level our.

brains are not trained to to sort of. keep track of multiple things at the. same time like obviously you can walk. and chew gum at the same time. because they're both activities that. require only a little bit of your. conscious. activity but try balancing your. checkbook. and watching a murder mystery on TV yeah. you'll mix up the digits or you'll miss.

an essential clue on in the TV show. so why does it matter that the. programmer the human. is uh is bad because the programmer is. at least with the current state of the. art is responsible for. writing the code correctly and it's hard. enough. to keep track of. a recipe that you just. execute one step at a time. chop the carrots then peel the potatoes.

mix the icing you need your whole brain. when you're when you're reading a piece. of code what what is going on okay we're. we're loading the number of mermaids in. variable a and the number of mermen in. variable B and now we take the average. or whatever. metaphor to Metaphor I like it you have. to keep in your head what is an a what. is in B what is in C uh hopefully you.

have better names. and that is challenging enough. if you have two different. pieces of code that are are sort of. being executed. simultaneously weather is using the. parallel or the concurrent. approach. if like. a is the number of fishermen and B is. the number of programmers.

but in another part of the code a is the. number of mermaids and B is the number. of merman. and somehow that's the same variable if. you do it sequentially if first you do. your mermaid mer people computation and. then you do your people in the boat. computation it doesn't matter that the. variables are called A and B and that is. literally the same variable because you. you're done with one use of that. variable but when you mix them together. suddenly.

the number of more people replaces the. number of fishermen and your computation. goes dramatically wrong and there's all. kinds of ordering. of operations that could result in the. assignment of those variables and so you. have to anticipate all possible. orderings and you think you're smart and. you'll put a lock around it and in. practice in terms of bugs per lineup per. a thousand lines of code. this is an area where everything is.

worse so a lock is a mechanism by which. you forbid only one. Chef can access the oven at a time. something like that and then semaphores. allow you to do what multiple ovens. that's not the bad idea because if. you're sort of. if you're preparing if you're baking. cakes and you have multiple people all. baking cakes but there's only one oven. yeah then maybe you can tell that the. oven is in use but maybe it's preheating.

uh and so you have to maybe maybe you. make a sign that says oven and use. uh and you flip the sign over and it. says often is free when you're done. baking your cake. uh that's a lock that's sort of and and. what do you do when you have two ovens. or maybe you have ten ovens do you you. can put a separate sign on each oven or. maybe you can sort of someone who comes. in wants to see at a glance. and maybe there's an electronic sign.

that says uh there are still five ovens. available. uh or maybe they're already. three people waiting for an oven so you. can. if you see an oven that's not in use. it's already reserved for someone else. who got in line first. and that's sort of what what what the. restaurant metaphor was trying to. explain yeah and so you're now tasks. you're sitting as a designer of python. with a team of brilliant core developers.

and have to try to figure out to what. degree can any of these ideas be. integrated and not so maybe this is a. good time to ask what is async IO. and how has it evolved since Python 3.4. wow yeah so we had this really old. library for for doing things. concurrently especially things that had. to do with IO and uh networking i o was. especially uh sort of a popular topic.

and. in the python standard Library we had a. brief period where there was lots of. development and I think it was late 90s. maybe early 2000s and like. two little modules were added that were. the state of the Art of Doing. asynchronous IO or sort of non-blocking. AIO which means that you can keep.

multiple network connections open and. sort of service them all in parallel. like a typical web server does so iOS. input and outputs you're writing either. to the network network connection or. reading and writing to a hard drive the. story also possible and you can do uh. the ideas you could do to multiple while. also doing computation. process of running some code that does. some fancy stuff yeah like when you're. writing a web server when a request.

comes in a user sort of needs to see a. particular web page. uh you have to find that page maybe in. the database and format it properly and. send it back to the client and. there's a lot of waiting waiting for the. database waiting for the network and so. you can handle hundreds or thousands or. millions of requests. concurrently on one machine anyway waste. of doing that in Python were kind of. stagnated and uh.

I forget it might have been around. 2012 2014. uh when someone for the umpteenth time. actually said these async chat and async. core modules that you have in the. standard Library are not quite enough to. solve my particular problem. can we add one tiny little feature and. everybody said no that stuff is not too. but you're not supposed to use that.

stuff write your own using uh. third-party library and then everybody. started a debate about what the rights. third-party library was. and somehow I I felt that. that was actually a cue for well maybe. we need a better state of the art. module in the standard library for for. multiplexing input output from different. sources you could say that it spiraled. out of control a little bit it was at.

the time it was the largest python. enhancement proposal that was ever. proposed. and you were deeply involved with that. at the time I was very much involved. with that I was like the lead architect. uh I ended up. talking to people who had already. developed Syria's third-party libraries. that did similar things and sort of. taking ideas from them and. getting their feedback on my design and.

eventually we put it in the standard. library and after a few years I got. distracted I think the thing the big. thing that distracted me was actually. type annotations. but other people kept it alive and. kicking and it's been quite successful. actually yeah. in the world of python web clients so. initially what are some of the design. challenges there in that debate for the. pep and what are some things that got. rejected what are some things that got. accepted to stand out to you.

there are a couple of different ways you. can handle parallel i o and this happens. sort of at an architectural level in. operating systems as well like Windows. prefers to do it one way and Unix. prefers to do it the other way. you sort of. you have an object that represents a. network endpoint say a connection with a. web browser that your client. and say you're you're waiting for an.

incoming request two fundamental. approaches are. okay I'm waiting for an incoming request. I'm doing something else come wake me up. or of course sort of come tell me when. uh something interesting happened like a. packet came in on that network. connection. and the other Paradigm is. we're on a team of a whole bunch of. people with maybe a little mind and we. we can only manage one web connection at.

a time so. I'm just sitting. looking at this this web connection and. I'm just blocked until something comes. in and then uh I'm already waiting for. it. uh I get I get the data I process the. data and then I go back to the top and. say no sort of I'm waiting for the next. packet those are about the two paradigms. one is.

a paradigm where there is sort of. notionally a threat of control whether. it's an actual operating system thread. or more an abstraction in async IO we. call them tasks. but a task in async IO or a thread in. other contexts is devoted to one thing. and it has Logic for all the stages like. when it's a web request like. first wait wait for the first line of. the web request parse it because then.

you know if it's a get or a post or a. put or whatever or an error uh then wait. until you have a bunch of lines until. there's a blank line then parse that as. headers and then interpret that and then. wait for the rest of the data to come in. if there is any more that you request. expect that sort of standard web stuff. and the other thing is and there's. always endless debate about which. approach is more efficient and which.

approach is more error prone. where I just have a whole bunch of. stacks in front of me and uh whenever. a packet comes in I sort of look at the. number of the pack that there's some. number on the packet and I say oh that. packet goes on this pile. and then I can do a little bit and then. sort of that pile provides my context. and as soon as I'm done with with the. processing I sort of. I can forget everything about what's.

going on because the next packet will. come in from some random other client. and it's that pile or this pile. uh and every time a pile is maybe empty. or full or whatever the criteria is I. can toss it away or use it for a new. space but. several traditional third-party. libraries for asynchronous i o. processing in Python shows the model of. a callback. and that's that's the idea where you. have a bunch of different stacks of.

paper in front of you and every time. someone gives you a piece gives you new. sheet you decide which stack it belongs. to. and that leads to a certain style of. spaghetti code that. I find sort of aesthetically. not pleasing and I I was sort of never. very successful and I had heard many. stories about people who were also. sort of complaining about that style of.

coding. uh it was very prevalent in JavaScript. at the time at least because it was like. how the JavaScript event Loop basically. works and so I thought well the. task-based model where each task has a. bunch of logic we had mechanisms in the. Python language that we could easily. reuse for for that and I thought I want. to build a whole library for. asynchronous networking i o.

uh and all the other things that may. need to be done asynchronously. uh based on that Paradigm and so I just. chose a paradigm and tried to see how. far I could get with that and it turns. out that it's pretty good paradigm so. people enjoy that kind of Paradigm. programming for asynchronous Io relative. to callbacks. okay beautiful so how does that all.

interplay with. the infamous Gill the goal the global. interpreter lock. maybe can you say what the Gill is and. how does the dance beautifully with Ace. in Kyle. the global interpreter lock. solves the problem that python. originally was not written with either. asynchronous or or parallelism in mind. at all there was no concurrency in the. language there was no parallelism there. were no threads.

only a small number of years into. Python's initial development. all the new cool operating systems like. uh Sun OS and silicon graphics irex and. then eventually posix and windows all. came with threading libraries. that lets you do multiple things in. parallel and there is a certain. certain sort of principle which is the. operating system handles the threads for.

you. and the program can pretend that there. are as many CPUs as as there are threads. in the program. uh and those CPUs were completely. independently. and if you don't have enough CPUs the. operating system sort of simulates those. extra CPUs on the other hand if you have. enough CPUs you can get a lot of work.

done by deploying those multiple CPUs. but python wasn't written. to to do that. uh and so. as libraries for for multi-threading. were added to C. but every operating system vendor was. adding their own version of that. we thought and maybe we were wrong but. at the time we thought well we quickly.

want to be able to support these. multiple threads. because they seemed at the time in the. early 90s when they were new at least to. me. they seemed a cool interesting. programming Paradigm and one of the. things that that python at least at the. time. felt was nice about the language was. that we could give a. safe version of all kinds of cool new. operating system toys to the python. programmer like I remember.

one or two years before threading I I. had spent some time adding networking. sockets. uh to Python and they were very literal. translation of the networking sockets. that were in the BSD operating system so. Unix BSD. but the nice thing was if you're using. sockets from python then all the things. you can do wrong with sockets in C would. automatically give you a clear error.

message instead of just ending up with a. malfunctioning hanging program. and so we thought well we'll do the same. thing with threading. but we didn't really want to rewrite The. Interpreter. to be thread safe because that that was. was like. that would be a very complex refactoring. of all The Interpreter code and all the. runtime code because all the objects. were written with the assumption that.

there is only one thread and so we said. okay well we'll take our losses we'll. provide something that looks like. threads. and as long as you only have a single. CPU on your computer which most. computers at the time did. uh it feels just like threads because. the the whole idea of of multiple. threads in the OS was that even if your. computer only had one CPU you could. still fire up at many threads as you.

wanted well within reason maybe 10 or 12. not 5000. uh and so we thought we had conquered. the. the abstraction of threads pretty well. because multi core uh CPUs were were not. in in most python programmers hands. anyway. and then of course a couple of more. iterations of Moore's Law and computers. getting faster and at some point.

uh the chip designers decided that they. couldn't make the CPUs faster but they. could still make them smaller and so. they could put multiple CPUs on one chip. and suddenly there was all this pressure. about. do things in parallel and that's where. the the solution we had in Python didn't. work. and that's that's sort of the moment. that the Gill became. became infamous.

because the guilt the guilt was the. solution we used to sort of. take this single interpreter and share. it between all the different operating. system threats that you could create and. so as long as the the hardware. physically only had one CPU that was all. fine. and then as Hardware vendors were. suddenly telling us all oh you got to. paralyze everything's got to be. paralyzed. people started saying oh uh but we can.

use multiple threads in Python and uh. then they discovered oh but actually all. threads run on a single single core yeah. I mean is there a way is there ideas for. in the future to remove. the global interpreter log Gill like. maybe multiple sub interpreters some. tricky. interpreters on top of interpreters kind. of thing yeah there there are a couple. of possible uh Futures there the the.

most likely future is that we'll get. multiple sub interpreters. which each run a completely independent. Python program nice uh but they're. they're still some benefit of. of sort of faster communication between. those programs but it's also managing. for you this running a multiple python. programs yeah so it's hidden from you.

right the it's it's hidden from you but. you have to spend more time. communicating between those programs. because the sort of. the attractive. thing about the multi-threaded model is. that the threads can share objects at. the same time that's also the downfall. of the multi-threaded programming model. because when you do share objects. you were and you didn't necessarily.

intend to share them or uh there were. aspects of those objects that. that were not reusable you get all kinds. of concurrency bugs and so. the reason I wrote that little blog post. about semaphores was that concurrency. bugs are just harder it would be nice if. python had uh no Global interpreter lock. and it had the so-called free threading.

but it would also cause a lot more. software bugs. uh the interesting thing is that there. is still a possible future where we are. actually going to or where we could. experiment at least with that. because there is a guy working for. Facebook who has developed a fork of C. python. that he called the no-gill. interpreter where he removed the Gill.

and made a whole bunch of optimizations. so that the the single threaded case. doesn't run too much slower. uh and multi-threaded case will actually. uh use all the cores that you have. and so that that would be an interesting. possibility. if we would be willing as a python core. developers to actually.

uh maintain that code indefinitely. and if we're willing to put up with the. additional complexity of The Interpreter. and the additional sort of overhead for. the single threaded case and I'm. personally not convinced. that. there are enough people. uh needing the speed of multiple threads. with their python programs.

that it's worth to sort of. take that performance hit and that. complexity hit. and I I feel that the Gill actually is. pretty nice. Goldilocks point between no threads and. uh all threads all the time but not. everybody agrees on that so that is. definitely a possible future the sub. interpreters look like a fairly safe bet. for 312 so say a year from now a year so.

the goal is to do a new version every. year. yeah for python let me ask you perhaps a. fun question but there's a philosophy. dude to will there ever be a python 4.0. now before you say it's currently a joke. and probably not I'm gonna go to 3.99 or. 3.99 999. can you imagine possible features.

that python 4.0 might have that would. necessitate the creation of the new 4.0. given the amount of. pain and joy. suffering and Triumph that was involved. in the move between version 2 and. version three. yeah well we're we. as a community and as a core development. team we have a large amount of painful.

memories about the Python 3 transition. uh which is one reason that sort of. everybody is happy that we've decided. there's not going to be a 4.0 at least. not anytime soon and if there is going. to be one it would will sort of plan the. transition very differently because. clearly we underestimated the pain the.

transition. cost for our users in the Python 3 case. and. had we known we could have sort of. designed Python 3 somewhat differently. without making it any worse. we just thought that we had a good plan. but we we we underestimated where. what what sort of the users were capable. of when it comes to that kind of. transition by the way I think we talked.

way before like a year and a half before. the uh python 2 officially. end of life end of life oh yeah. what was that what was your memory of. the end of life did you shed a tear on. January 1st 2020 did was there. everyone's standing alone our team had. basically moved on years before. yeah it was it was purely it was a. little symbolic moment. uh to signal to the the remaining users.

that. there was no longer going to be any new. releases or support for python 2 7. did you shed a single tier while looking. out over the horizon. I'm not not a very poetic person and I. don't shed tears like that but no. yeah we we actually had planned a party. but the party was planned for uh the.

python the U.S python conference that. year which would never happened of. course because of the pandemic oh is it. like in March yeah the conference was uh. going to be I think late April that year. oh. so that that was a very difficult. decision to cancel it but. they did so anyway if we're going to. have a python 4 we're going to have to. have both a different reason for for. having that.

and a different process for managing the. transition can you imagine a possible. process that so so I think you're. implying that if there is a 4.0 in some. ways it would break back compatibility. well so. here is here is a concrete thought I've. had and I'm not unique but not everyone. agrees with this so this is definitely a. personal opinion. if we were to try something like that no.

Guild python. uh. my expectation is that. it would feel. just different enough. at least for the the part of the Python. ecosystem that. is heavily based on C extensions. and that is like the entire machine. learning data science Scientific Python.

world is all based on C extensions for. python. and so. those people would likely feel the pain. the most. because they even if we don't change. anything about the syntax of the. language and the semantics of the. language when you're writing python code. we we could even say suppose that after. python say 3 19 instead of 320 we'll.

have 4.0 suppose that's the time when we. flip the switch to 4.0 will will not. have a gill. imagine it was like that. so. I would probably say. that particular year the release that we. named 4.0 will be syntactically it will. not have any new syntactical features no. new modules in the standard Library no.

new built-in functions. everything will be at the python level. will be purely compatible with python. 3.19. however. extension modules. will have to make a change they all have. to be recompiled they will not have the. same. binary interface. uh. the semantics and and apis for for some.

things that are frequently accessed by C. extensions will be different and so for. a pure python user. 4.0 would be a breeze except that there. are very few pure python users left. because everybody who is using python. for something significant is using. third-party extensions they're like I. don't know several hundreds of thousands.

of third-party extensions on uh the Pi. Pi service. and I'm not saying they're old they're. all good but there is a large list of. extensions that would have to do work. and some of those extensions are. currently already low on maintainers and. they're struggling to keep afloat so. there you can give a huge heads up to. them if you go to 4.0 to really keep. developing it yeah we'd probably have to.

do something like. several years before who knows maybe. five years earlier like 3.15 we would. have to say and and I'm just making the. the specific numbers up but we at some. point we'd have to say foreign. python could be an option. it might be a compile time option. uh. if you want to use no Guild python you.

have to recompile python from source for. your platform using your tool set. all you have to do is change one. configuration variable and then you just. run make. or configure and make and it will build. it for you. but now you also have to use the the. no-gill compatible versions of all. extension modules you want to use. and so as long as many extension modules. don't have fully functional.

sort of variants that work within the. no-gill world. that's not a very practical thing for. python users but it would allow. extension Developers. to test the waters see what they need to. syntactically to be able to compile at. all maybe they're using. functions that are defined by the Python. 3 runtime that won't be in the python 4. runtime those functions will not work.

they'll have to find an alternative. uh but they can experiment with that and. sort of write test applications and that. would be a way to transition and that. that could be a series of releases where. the python 4 is more and more imminent. uh we have supported more and more. third-party extension modules to have. solid support that works for no Guild.

python for that new API. uh and then sort of python python 4.0 is. like the official moment that the mayor. comes out and cuts the ribbon and is now. a python uh now the sort of no-gill mode. is the default and maybe the only mode. there is. the internet wants to know from Reddit. uh it it's uh it's a small and fun. question there's many fun questions but.

uh out of the Pi Pi packages Pi Pi. packages uh do you have uh do you have. ones you like do you in your opinion. other must have Pi Pi libraries or ones. you use all the time constantly oh my. that. I should really have a standard answer. for that question but like a positive. standard answer but my current standard. answer is that I'm not a big user of. third-party packages. when I write python code I'm usually.

developing some tooling around building. python itself. and the last thing we want is. dependencies on third-party packages so. I I tend to just use the standard. library and that's where your focus is. that's where your mind is. but do you do you keep an eye of what's. out there to understand where the. standard Library could be moving should. be moving it's a good kind of landscape. of what's missing from the same Library.

well usually when something's missing. from the standard Library nowadays uh. it is a relatively new idea and there is. a third party implementation or maybe. possibly multiple third-party. implementations but they evolve at a. much higher rate than they could when. they're in the standard Library so they. it would be a big reduction in in.

activity to. incorporate things like that in the. standard Library so I I like that there. is a lively package ecosystem and that. sort of recent Trends in the standard. Library are actually that we're doing. the occasional spring cleaning where. we're just. we're we're. choosing some. modules that have not had a lot of. change in a long time and that maybe.

would be better off not existing at all. at this point because there might be a. better third party. alternative anyway and we're sort of. slowly removing those that often those. are things that I sort of. I spiked somewhere in 1992 or 1993 and. if you look look through the commit. history it's very sad like.

all cosmetic changes like changes in the. indentation style or uh the name of this. other standard Library module got. changed or like like nothing nothing of. any substance the API is identical to. what it was 20 years ago. So speaking of packages they have a. a lot of impact on a lot of people's. lives does it make sense to you why. python has become the primary the. dominant language for the machine. learning community so packages like uh.

Pi torch tensorflow second learn and. even like the lower level stuff like. numpy sci-fi pandas matplotlib with. visualization can you like does it make. sense to you why it uh. uh permeated the entire data science. machine learning AI community. well it's. part of it is an effect that's as simple. as. we're all driving on the right side of. the road right. uh it's compatibility yeah it's it's in.

and and and and part of it is uh. not not quite as as as fundamental as. driving on the right side of the road. which you have to do for for safety. reasons I mean you have to agree on. something. every they they could have picked. JavaScript or Pearl there was there was. a time in the early 2000s that it really. looked like Pearl was going to dominate. like biosciences.

because DNA search was all based on. regular expressions and pearl has the. fastest and most comprehensive regular. expression engine still does. I spent quite a long time with pearl. that was another letting go. letting go of this kind of uh data. processing uh system yeah the reasons. why python. became the lingua Franca of the. scientific code and and. machine learning learning in particular.

and data science. it really had a lot to do with. anything was better than C or C plus. plus. recently a guy who worked at Lawrence. Livermore National Laboratories in the. the sort of computing division. wrote me his his Memoirs and and he had. his his own view of how he helped.

something he called computational. steering into existence. and this was the idea that you you take. libraries that in in his days were. written in Fortran that that solved. Universal mathematical problems. uh and those libraries still work but uh. the scientists that use the libraries. use them to solve continuously different.

specific applications and answer. different questions and so those poor. scientists. were. were required to to use say Fortran. because Fortran was the library the. language that the library was written in. and then the scientist would have to. write an application that sort of uses. the library to solve a particular. equation or set off. of answer a set of questions and the.

safe same for C plus plus. because of and there's there's. interoperability so the dusty decks are. written either in C plus plus or Fortran. uh. and so Paul DuBois was one of the people. who. I think in the mid 90s. saw that that you needed a higher level. language. for the scientists. to to sort of tie together the.

fundamental mathematical algorithms of. linear algebra and and other stuff. and so. gradually some libraries started. appearing that did very fundamental. stuff with arrays of numbers in Python I. mean when I first created python I was. not expecting it to be used for arrays. of numbers much I thought that was like. an outdated data type. and everything was like objects and.

strings and like python was good and. fast at string manipulation and objects. obviously but arrays of numbers were not. very efficient in the multi-dimensional. arrays didn't even exist in the language. at all. uh but there were people who realized. that python had extensibility. that was flexible enough that they could. write. third-party packages that did support.

large arrays of numbers and operations. on them very efficiently. and somehow they got a foothold. through sort of different. parts of the scientific Community I I. remember that the Hubble Space Telescope. people in Baltimore Were Somehow big. python fans in the late 90s. and at various points. small improvements were made and more. people got in touch with using python to.

derive these libraries. of interesting uh algorithms and like. once once you have a bunch of scientists. who are working on similar problems say. they're all working on stuff that that. com data that comes in from the Hubble. Space Telescope but they're looking at. different things some some are looking. at stars in this galaxy other are. looking at galaxies the math is. completely different but the the. underlying.

libraries are still the same. and so they Exchange. code they say well I wrote this Python. program or I wrote a python library to. solve this class of problems. and the other guys either say oh I can. use that Library 2 or if you make a few. changes I can use that Library too. why why start from scratch in Pearl or. JavaScript. where there's not that infrastructure.

for arrays of numbers yet whereas in. Python you have it and so more and more. scientists at different places doing. different. different work. discovered Python and then then people. who had an idea for an important new. fundamental Library decided oh python is. is actually already known to our users. so. let's use python as the user interface I. think that's how tensor I imagine at.

least that's how tensorflow ended up. with python as the user interflow. interface right but with tensorflow. there's a deeper history of what the. community is it's not just like what. packages it needs it's like what the. community leans on for programming. language because tensorflow. uh had a prior library that was internal. to Google but there was also competing. machine learning Frameworks like thiano.

Cafe they were in Python there was some. Scala. um some other languages but python was. really dominating it. and it's interesting because. um there's other languages from the. engineering space like Matlab. that a lot of people used but different. design choices by the company by the. core developers led to it not spreading. and one of the choices of Matlab. uh by math works is to not make it open.

source right or yeah not you know having. people pay it was a very expensive. product and so uh universities. especially disliked it because it was a. price per seat I I remember hearing. yeah but I think that's not why it. failed or it failed to spread I think. the universities didn't like it but they. would still pay for it. the thing is it didn't feed into that. GitHub open source. uh packages culture so like and that's.

somehow a precondition for um for viral. spreading the hacker culture like the. tinkerer culture uh with python it feels. like you can build a package from. scratch or solve a particular problem. and get excited about sharing that. package with others and that creates an. excitement about a language I tend to. like Python's approach to open source in. particular because it's sort of. it's almost egalitarium.

uh there's there's little hierarchy. there's there's obviously some because. the like you only need to decide whether. you drive on the left or the right side. of the road sometimes. but there is a lot of access for people. with little power you don't have to work. for a big tech company to make a. difference in the python world. uh we have affordable events that really. care about community and support people.

and sort of the community is is. it's like a big deal at our conferences. and in in the BSF when the psf funds. events it's always about. growing the community the psf funds very. little development. they that they do some but most of the. develop most of the money that the psf. forks out.

uh is to community. fostering things. So speaking of egalitarian last time we. talked four years ago it was just after. you stepped down from your role as the. benevolent dictator for life pdfo. looking back what are your insights and. lessons. you learn from that experience about. python developer Community about human. nature about human civilization. life itself oh my uh.

I probably held on to the position too. long. I remember being just. extremely stressed for a long time. and. it wasn't very clear to me. what was leading what was causing the. stress. and looking back. uh.

I I should have sort of. relinquished my central role as bdfl. sooner. what were the pros and cons of the bdfl. role like what were the you not. relinquishing it what what are the. benefits of that for the community and. what are the drawbacks well the the. benefits for the community would be. things like. uh. Clarity of vision and sort of.

a clear Direction because I I had. certain ideas in in mind when I created. Python and well I sort of let myself be. influenced by many other ideas as python. evolved and became. more successful and more complex and. more used. I also stuck to certain principles and.

it's still hard to say what are Python's. core principles. but the fact that I was playing that. role and sort of always very active. grew the community in a certain way. it modeled to the community how to think. about. how to how to solve a certain problem. well. that was a source of stress but it was. also beneficial it was a source of. stress for me personally but it was.

beneficial for the community because uh. people people sort of. over time had. learned how I was thinking and could. predict. yeah but how how I would decide about a. particular issue and not always. perfectly of course but there was like. there wasn't a lot of jerking around. like this year we're all this year the. Democrats are in power and we're doing.

these kind of things and now the. Republicans are in power and they roll. all that back and do those kind of. things. there is a clear fairly straight path. ahead. and so fortunately the the successor. structure with the steering Council. has has sort of found a similar way of. of leading the community. in a fairly steady Direction without. stagnating and and for me personally. it's more fun because there are there.

are things I can just ignore. yeah oh yeah there's a bug in. multi-processing let someone else decide. whether that's important to solve or not. I'll I'll stick to typing in the async. io and the faster interpreter yeah it. allows you to focus a little bit more. yeah. uh what are interesting differences in. culture if you can comment on between. Google Dropbox and Microsoft from our. Python Programming perspective all.

places you've been to the positive. is there a difference or is it just. about people and there's great people. everywhere or is there culture. differences. sort of Dropbox is much smaller than the. other two in your list yeah so that. that is a big difference the set of. products they provide is more it's. narrower so they're more focused smaller. code base yeah and and Dropbox sort of.

at least during the time I was there. had the tendency of sort of. making a big plan putting the whole. company behind that plan for a year and. then evaluate and then suddenly find. that. everything was wrong about the plan and. then they had to do something completely. different. so there were there was like. the annual engineering reorg was was. sort of an unpleasant tradition that.

Dropbox because like oh there's a new VP. of engineering and so now all the. directors are being reshuffled and this. guy was in charge of of. infrastructure one year and the next. year he was made in charge of I don't. know product development. it's fascinating because like you don't. think about these companies internally. but I you know Dropbox to me from the. very beginning was one of my favorite uh. Services there's certain like programs. and online services that.

make me happy make me more efficient and. all that kind of stuff but one of the. powers of those kinds of services they. disappear they you're not supposed to. think about how it all works but it's. incredible to me that you can sync stuff. effortlessly. across so many machines so quickly and. like don't have to worry about conflicts. they they take care of the you know as a. person that comes from version. repositories and all that kind of stuff. or merge is super difficult and uh just.

keeping different versions different. files is very tricky the fact that they. could take care of that is just I don't. know the the engineering behind the. scenes must be super difficult both on. the computer infrastructure and the. software a lot of internal sort of. hand-wringing about things like that but. the the product itself always worked. very smoothly yeah it does but there's. probably a lot of lessons to that you. can have a lot of turmoil inside on the. engineering side but If the product is.

good the product is good and don't maybe. don't mess with that either it is you. know when it's good. keep it's like with Google focus on the. search and the ads. right like and the money will come yeah. and make sure that's done extremely well. and don't forget what you do extremely. well and in what ways do you provide. value and happiness to the world make. sure you do that well. um is there something else to say about. Google and Microsoft Microsoft has said.

a very fascinating shift recently with. the new CEO uh what you know recent CEO. with purchasing GitHub. embracing open source culture embracing. the developer culture is pretty. interesting to see that's like why I. joined Microsoft. I mean after after retiring and thinking. that I would stay retired for the rest. of my life which of course was a. ridiculous thought but that I was I was. I was done working for a bit and then.

the pandemic made me realize that work. work can also provide a source of. fulfillment. keep you keep you out of trouble. uh Microsoft is a very interesting. company because it has this incredible. very long and varied history and this. amazing catalog of products that many of. which also date way back. I mean.

I've been been talking to a bunch of. excel people lately and Excel is like 35. years old yeah and they can still read. spreadsheets that that they might find. on an old floppy Drive. yeah there's man they built so many. incredible tools through the years. Excel one of the great shames of my life. is that I've never learned how to use.

Excel well I mean it just always felt. like so many features are there it's. similar with ideas like pie charm. it feels like I I converge quickly to. the dumbest way to use a thing to get. the job done when clearly there's so. much more power at your fingertips. yeah but there's I I do think there's. probably expert users of Excel and oh. that Excel is a cash cow actually oh it. actually brings in money oh yeah a lot. of the engineering sort of if you look.

deep inside Excel. there's some very good engineering very. very impressive stuff. okay now I need to definitely learn it's. a little better I had issues because I'm. a keyboard person so I had issues coming. up with shortcuts I mean Microsoft. sometimes. uh it's changed over the years but. sometimes they kind of want to make. things easier for you on the surface and. therefore make it harder for like uh.

people that like to have shortcuts and. all that kind of stuff to optimize their. workflow now Excel is probably people. are probably yelling at me and it's like. no Excel probably has a lot of ways to. optimize work in fact I keep discovering. that there are many features in Excel. that only exists at keyboard shortcuts. yeah that's the sense I have and now. like I'm embarrassed that it's just you. just have to know what they are yeah. that's that's like there's no logic or. or Reason to the assignment of the.

keyboard shortcuts because they they go. back even longer than 35 years. can you maybe comment about Sachin Adela. and how hard it is for CEO to sort of. pivot a company towards open source or. develop a culture is there something you. could see about like how what's the role. of leadership in such a. pivot and definition of a new vision. I've never met him but uh I hear. he's just a really sharp.

thinker. but he also has an incredible business. sense. he took the organization that had very. solid pieces but that was also. struggling. with all sorts of shameful things. especially the Steve Ballmer time. I imagine in part through his personal. charm and thinking and of course the the. great trust that that the the rest of.

the leadership has in him he managed to. to Really Turn the company around and. sort of. change it from from openly hostile to. open source. to to actively embracing open source and. that doesn't mean that suddenly Excel is. going to go open source but that means. that there's room for a product like vs. code which is open source. yeah that's fascinating it gives me. faith that large companies with good.

leadership can grow can expand can. change and pivot and so on develop. because it gets harder and harder as the. company gets large. um you wrote a blog post in response to. a person looking for advice about. whether with the Cs degree to choose a. nine to five job or to become an. entrepreneur it's an interesting. question if you just think from first. principles right now somebody has took a. few years in programming has loved. software engineering in some sense.

creating python is an entrepreneurial. endeavor. that's a choice that a lot of people. that are good programmers have to make. do I work for. a big company or do I create something. new. or you can work for a big company and. create something new there. oh inside the yeah I mean big companies. have individuals who create new stuff.

that eventually grows big all the time. and if you're the person that creates a. new thing and grows big you you'll have. a chance to move up quickly in the. company to run that thing. if that's your aspiration what what what. can also happen is that. someone is brilliant engineer and sort. of builds a great first version of a. product. and has no aspirations. to then become a manager and grow the.

team from five people to 20 people to. 100 people to a thousand people and. be in charge of hiring and meetings and. they move on to. inventing another crazy thing inside the. same company or sometimes they. they found a startup or they moved to a. different great large or small company. there's all sorts of models. and sometimes people sort of do have.

this whole trajectory from engineer. buckling down writing code. not nine to five but more like. noon till midnight. seven days a week. and coming up with a product and sort of. staying in charge I mean if you take. drew a house and dropbox's founder he is. still the CEO. and at least when when I was there he.

had not checked out or anything he was. he was good CEO but he had started out. as the technical inventor or co-inventor. yeah and so he was someone who. I don't know if he always aspired that I. think when when he was 16 he already. started a company so maybe maybe he did. but he sort of. it turned out that that he had he did. have the the personal sort of skill set.

needed to to grow and and stay on top. and other people sort of. our brilliant engineers and horrible at. management I I count myself at least in. the second category so you're you're. your first love and still your love is. to be the quote unquote individual. contributor so the programmer. do you have advice for a programming. beginner on How to Learn Python the.

right way. find something you actually want to do. with it. if you say. I want to learn skill X. that's not enough motivation you need to. pick something. and it can be it can be a crazy problem. you want to solve it can be completely. unrealistic.

but something that that challenges you. in into actually learning. coding in in some language. and there's so many projects out there. you can look for like that that doesn't. have to be some big ambitious thing it. could be writing a small bot if you're. into social media you can write a read. about or a Twitter bot or uh or some. aspect of automating some as something. that you do every single day processing. files all that kind of stuff nowadays.

you can take machine learning components. and and sort of. plug those things together so cool stuff. with them so that's actually a really. good example so if you're interested in. machine learning the state of machine. learning is such that like a a tutorial. that takes an hour can get you to start. using uh pre-trained models to do. something super cool and that's a good. way to Learn Python because you learn. just enough to run this model and that's. like a sneaky way to get get in there to.

figure out how to import stuff how to. write basic i o. how to run functions and I'm not sure if. it's the best way to learn the basics of. python but it could be nice to just get. fall in love first and then figure out. the basics right yeah you can't expect. to Learn Python from a one hour video. recording blanking out on the name of of. someone who. who wrote a very funny blog post where.

he said. I see all these ads for things like. Learn Python in 10 days or so and he. said the goal should be Learn Python in. 10 years that's hilarious but I. completely disagree with that I think. the criticism behind that is that. the the places just like the blog post. from earlier the places that tell you. you learn python in five minutes or 10. minutes they're actually usually really.

bad tutorials so the thing is I do. believe that you can learn a thing. in an hour to like get some interesting. quick like it hooks you I mean this but. it just takes a tremendous amount of. skill to be that kind of educator. Richard Feynman was able to condense a. lot of ideas and physics in a very short. amount of time but that takes a deep. deep understanding and so yes of course. the actual I think the 10 the 10 years. is about the experience the pain along.

the way and there's something you have. to practice you can memorize the syntax. but well I couldn't but maybe maybe. someone else can but that doesn't make. you a coder yeah actually coding has. changed in fascinating ways because so. much of uh coding is copying pasting. from stack Overflow and then adjusting. which is another way of coding and I. don't want to talk down to that kind of. style of coding because it's kind of. nicely efficient but you know where that. is going.

I use it every day and it really yeah it. writes a lot of code for me and usually. it's slightly wrong but it still saves. me typing because all I have to do is. like change one word in a line of text. that otherwise it it generated perfectly. and like how many times are you looking. for like oh what was I doing this. morning I was looking for a begin marker.

and I look was looking for an end marker. and so begin is. blah blah blah search for begin this is. the begin token and then the next line I. type e and it it completes the whole. line with end instead of begin that's a. very simple example sometimes it it sort. of. if I name my function right it writes a. 5 or 10 line function.

and you know python enough to very. quickly then detect the issues so it. becomes a really good dance partner then. it doesn't save me a lot of thinking but. since I'm a poor typist I'm very much. appreciative of all the all the typing. it does for me. much better actually than the the. previous generation of suggestions that. are also still built in vs code. uh where when you hit like a DOT.

it it tries to guess what the type is of. the variable to the left of the dot and. then it gives you a list a pop-down menu. of what the attributes of that object. are but copilot is much much smoother. than that well it's fascinating to hear. that you use GitHub copilot uh do you. think do you worry about the future of. that. um did the automatic code generation. the increasing amount of that kind of. capability are programmers.

jobs threatened or is there still a. significant role for human our. programmers jobs threatened by the. existence of stack overflow. I don't think so it helps you take care. of the boring stuff and you shouldn't. try to use it to do something that you. have no way of understanding what you're. doing yet. a tool like that is always best when the. question you're asking is please remind.

me of how I do this. which I. I could do I could look up how to do it. but right now I've forgotten whether the. method is called Foo or bar or how you. what the shape of the API is does it use. a builder object or a Constructor or a. factory or. uh something else and what are the. parameters it serves that role it's like.

a great assistant. but the creative work of sort of. deciding what you want what you want the. code to do is is totally yours. what do you think is the future of. python in the next 10 20 50 years 100. years you look forward you ever think. about you ever imagine a future. of human civilization or living inside. the metaverse. on Mars. humanoid robots everywhere what part. does python play in that.

it'll eventually become sort of a legacy. language uh that plays an important role. but that that most people have never. heard of and uh don't need to know about. just like. all kinds of. basic structures in in. biology like mitochondria. so it permeates all of life all of. digital life but people just build on. top of it and they only know the stuff. that's on top of it yeah.

you guys you build layers of. abstractions I mean most programmers. nowadays. rarely need to do binary arithmetic. right. yeah or even think about it or even. learn about it or they could go quite. far without knowing I started. building little digital circuits out of. nand gates that I built myself with. transistors and resistors so I'd sort of.

I feel very blessed that. with with that start when I was a. teenager. I I learned some of the basic at least. Concepts. that that go into building a computer. and I sort of every part. I have some understanding what. what it's for and why it's there and how. it works and I can forget about all that. most of the time but I sort of.

I enjoy knowing oh if you go deeper you. at some point you get to uh nand Gates. and have others and shift registers and. when it comes to the point of how do you. how do you actually make a chip out of. silicon I have no idea that's just magic. to me. but you enjoy knowing that you can walk. a while towards the lower and lower. layers but you don't need to. it's nice the other day as a sort of.

a mental exercise I was trying to figure. out if I could build a. a flip-flop circuit out of uh relays. it was just sort of. trying to remember oh how does it really. relay work yeah there's like this. electromagnetic. force that pulls a switch open or shut. uh and you can have have like it can. open one switch and another shut another.

and. uh you can have multiple contacts that. go at once and how many relays do I. really need to sort of represent one bit. of information can really just feed on. itself there was I don't think I I got. to the final solution but it was fun. that I. I could still do a little bit of problem. solving and thinking at that level. and it's cool how we build on top of. each other so there's people that are.

just you you stood on the shoulders of. giants and there's others will stand on. your shoulders and it's it's a giant. beautiful hire yeah I feel I sort of. cover covered this middle layer of the. technology stack where and sort of. Peters out glow the. the level of of nand gates. and at the at the top I sort of I lose. track when it gets to machine learning. and then eventually the machine learning. will build higher and higher layers that.

will help us understand the lowest layer. of the physics and thereby the universe. figures out how. it itself Works maybe maybe not. yeah I did I mean it's it's possible I. mean if you think of human consciousness. if that's even the right concept. it's it's interesting that that sort of. we have this super parallel brain that. does all these. incredible parallel operations like.

image recognition. I recognize your face does you huge. amount of processing that goes on in. parallel there's lots of nerves between. my eyes and my brain. and the brain does a whole bunch of. stuff all at once because it's actually. a really slow circuits but there are. many of them that all work together. on the other hand when I'm speaking. everything is completely sequential. I I have to sort of string words.

together one at a time. and when I'm thinking about stuff when. I'm when I'm understanding the world. I'm also thinking of everything like one. step at a time. and so we we've we've sort of we've got. all this this incredible. parallel circuitry in our brains and. eventually we use that to simulate a. single threaded much much higher level.

interpreter. uh it's exactly I mean that's the. illusion of it that's the illusion. of it for us that it's a single. sequential set of thoughts and all of. that came from a single cell through the. process of embryogenesis so DNA is the. code. DNA holds the entirety of the code the. information and how to use that. information to build up an organism the. entire like. the arms how is it built yeah the brain.

it's so it's you don't buy a computer. you buy like uh you buy a a seed a. diagram and then you plant the computer. and it builds itself in almost the same. way and then does the computation and. then is uh eventually dies. it gets stale but gives birth to Young. computers. more and more and gives them lessons but. they figure stuff out on their own and. over time it goes on that way and those.

computers when they go to college try to. figure out how to program and they built. their own little computers they're. increasingly more intelligent. increasingly higher and higher levels of. abstractions isn't it interesting that. that you sort of you see the same thing. appearing at different levels though. because you have like. cells that that create new cells. and and eventually that builds a whole.

organism but then the animal or the. plant or the human. has its own mechanism of replication. that that is is sort of connected in a. very complicated way to the mechanism of. replication of the cells and then if you. if you look inside the cell if you see. how DNA and proteins are are connected. then there is yet another completely. different mechanism whereby proteins are.

mass produced. using enzymes and and and a little bit. of code from from DNA and of course. viruses break into it at that level. and while the mechanisms might be. different it seems like the nature of. the mechanism is the same and it carries. across natural languages and programming. languages. humans. uh maybe even human civilizations or.

intelligent civilizations. and then all the way down to uh the. single cell organism it is it is. fascinating to see what abstraction. levels are built on top of individual. humans yeah and how you have like whole. societies. that that sort of have a similar. self-preservation. I don't know what it is Instinct nature. abstraction. as the individuals have and the cells.

have and they self-replicate and breed. in different ways it's hard for us. humans to introspect it because we were. very focused on our particular layer of. abstraction but from an alien. perspective looking on Earth they'll. they'll probably see the higher level. organism of human civilization. as part of this bigger organism of life. on Earth itself in fact that could be an. organism just alone just life life life. on Earth.

uh this has been a wild both. philosophical and Technical conversation. Guido you're you're an amazing human. being you're you're gracious enough to. talk to me when I was first doing this. podcast or one of the earliest first. people I've talked to uh somebody I. admired for a long time it's just a huge. honor that you did it at that time and. you do it again you're awesome thank you. Lex. thanks for listening to this. conversation with Guido Ben Rossum to. support this podcast please check out. our sponsors in the description and now.

let me leave you some words from Oscar. Wilde experience is the name that. everyone gives to their mistakes. thank you for listening and hope to see. you next time.