#501 A Nod to Sir-Mix-Alot

0:00Calvin Hendryx-Parker Hello and welcome to Python Bytes, where we deliver Python news and headlines directly to your earbuds. This is episode 501, recorded October 20th, 2026. I'm Calvin Hendryx-Parker.

0:11Michael Kennedy And I'm Michael Kennedy.

0:12Calvin Hendryx-Parker Great to have you, Michael. This show is sponsored through by us, our continual support through our own work. Actually, check out Michael's great work over at the Talk Python community. He's got some great new courses up, some really cool stuff. Some people who've been collaborating on the various courses that are on Talk Python.

0:31Calvin Hendryx-Parker And then if you want to support Six Feet Up, so I'm co-founder and Six Feet Up CTO, and we do really fun projects with people who've got hard problems and need cool things solved. So check out sixfeetup.com and then connect with us over on the socials. You can find Michael and myself over on the various regulars, Mastodon, Bluesky X, and LinkedIn.

0:51Calvin Hendryx-Parker And then the show itself is on Mastodon Bluesky X. And then you can also join us for the live stream. So if you're here with us right now, you're on the live stream. We're at pythonbytes.fm/live. And then if you want the handcrafted, not handcrafted, but the bespoke show notes delivered to your inbox, the artisanal show notes delivered to your inbox, join our friends of the show list and we will never share your email.

1:17Calvin Hendryx-Parker But if we wanted to take a pause, Michael,

1:19Michael Kennedy what would that look like? Maybe a little nod, a little nod,

1:22Calvin Hendryx-Parker A little nod, if you will.

1:24Michael Kennedy Oh, yeah. A little nod. So let's talk about notebooks. Now, I don't know how you work. I could take a guess. But I don't know how if you've got a problem and you're like debugging it. And you're like, oh, I'm not really sure what I'm going to do here. There's different things. There's the time-tested print location 1.

1:47Michael Kennedy Now I'm in location 1A. Now I'm location, you know, the bisection method of like you just start printing out stuff all around the area you're trying to understand. And, you know, there's a place for that. But maybe we got better tools. I don't know.

2:00Calvin Hendryx-Parker I would hope so. I mean, I remember the day I discovered PDB and the magic.

2:05Michael Kennedy Yeah, exactly. Set a breakpoint. Let's go in.

2:07Calvin Hendryx-Parker Yeah.

2:07Michael Kennedy Yeah. You could use, you know, VS Code, PyCharm, one of them, and run it in a debugger potentially. But there's this project called Nod, Notebooks on Demand. So if your style of exploration is notebooks already and you're writing some code and you're like, oh, this part is not working. I need to kind of debug it. I need to understand it. I need to play with it.

2:28Michael Kennedy Then you can use this nod or notebook on demand, which is super cool by Eric Rahn. And the advantages that I see here are if I'm somehow able to explore my code with a notebook, it's not just a debugger will let you sort of see what's there, step forward, step backwards. but you can actually explore different ideas.

2:46Michael Kennedy Like, well, what if I had a function that did this? Or what if I actually had a query that ran it differently? Let me write that and see what happens. So here's how this works. What you do is you import nodpy and you get the notebook. Then whenever you want to basically set a break point, you just say notebook.

3:03Michael Kennedy I don't know, break. I might do import notebook as notebook break or something. But anyway, you just call notebook and that will pause your code And it fires up or attaches to a Jupyter notebook. So you've got to install a Jupyter extension that basically lets it listen for these incoming events. And when they do, it will break into a notebook instead of to a debugger.

3:24Michael Kennedy And you're just in your function as a cell. You can run your function. You can explore it. There's the other functions that are nearby that you can play with. You can write other pieces, right? Like a new cell. You could write a new cell and then go play with that. What do you think?

3:38Calvin Hendryx-Parker I love it. I think folks who are used to notebooks but are a little intimidated by, say, the debugger, this is way more of a natural feel. It's weird because notebooks break your mind a little bit because you can run the cells out of order. You can jump back up and go to a previous thing and play there and come back down and play here.

3:57Calvin Hendryx-Parker And so you can kind of lose yourself a little bit. But this gives people that capability to express that creativity and debugging by using various cells to play.

4:08Michael Kennedy It's interesting, like when you're the most stressed out and things are the most not working, being in a comfortable place makes a bigger difference than I think just looking at a calm time from the outside. Why is this not working? Like, oh, OK, but this thing, this thing, I'm really comfortable. Let's go.

4:22Michael Kennedy And now I understand, right? Like a friend of mine had this saying about debugging and code, about basically code complexity in general. I'll share people like Jason said, debugging is always a little bit harder than writing code. you know because there's all the complexities of what's going on so if you write code that's at the limit of your capability of like understanding complexity or like the situation then you might not be able to debug it right it's like yeah you should always leave a little bit of a buffer in there of of that and i feel like this takes that down a notch right because it gives you a better understanding during that harder debugging time yeah well it was like the difference between

5:03Calvin Hendryx-Parker going from PDB to, say, PyCharm for a debugger. I remember in PDB, traversing up the call stack and down into things just required you kind of holding a lot of that in your head. You didn't get a good visual model of it, where if you use PyCharm, you could just kind of click through the stack and you see the rest of the stack still sitting on the screen. There's the call stack right there.

5:21Michael Kennedy Exactly. You can just see it.

5:22Calvin Hendryx-Parker Yeah. And so this gives you that same comfort level and visual anchoring when debugging. So I love the fact that they have built this for the notebook natives

5:33Michael Kennedy I agree. And I believe there's a couple other out there. But one of the things that's interesting about this one is the markdown cells become comments, cells become new lines, and the notebooks you can just throw away because they get saved into the source file if you want. So if you run it again, it kind of recreates the exploration that you set up.

5:53Calvin Hendryx-Parker Oh, that's really nice. It can persist from run to run.

5:57Michael Kennedy Yeah. So it's a pretty new project. Don't expect it to be super polished. But people well, check it out. I think it's certainly worth a try.

6:04Calvin Hendryx-Parker Yeah, it looks really cool. We should definitely check that out.

6:07Michael Kennedy Definitely. Over to you.

6:08Calvin Hendryx-Parker All right. Well, are you ready for the new thing, the hot new release of Polars? Polars 2.0 has shipped. And streaming engine is on by default. There's a lot of new features. That was the reason for the major bump in version is because there's going to be some changes and some things you're going to need to do as you upgrade to your new version of Polars.

6:31Calvin Hendryx-Parker But one other thing to mention here is really, really important is the performance. I know we've mentioned in previous episodes, we've talked about Polars performance versus things like DuckDB. And in the blog post of the release here by Richie, they've got some performance numbers here because SQL is a first class citizen now in the Polars environment.

6:51Calvin Hendryx-Parker So if you are doing things like you would have done in DuckDB, for example, maybe you're more comfortable there because of the SQL environment, and you love the speed of DuckDB, look at these numbers. This is on some AWS instances here on a C7 4X large, 16 vCPUs and 32 giga RAM.

7:07Michael Kennedy That is a large.

7:08Calvin Hendryx-Parker That is a very large. They're running two different benchmarks here, the TPCH SF10 and the SF100. And you can see here, Polars completes it in 3.2 seconds compared to DuckDBDB, which is fast. I mean, we all know compared to what we read in our, went over in the last episode, DuckDB is at 4.44 seconds on that same benchmark.

7:30Calvin Hendryx-Parker And then they basically did the DS version of that benchmark as well and saw that we've got Polars at 12.59 seconds where the current release of DuckDB is at 15.92. The alpha of DuckDB 2.0 still slower at 14.3. That's not saying don't use DuckDB but I'm just saying Polars is making a real run for performance here with some of the new enhancements.

7:50Calvin Hendryx-Parker That streaming capability really minimizes memory usage. And when you do use heavy memory on these various pullers examples, you'll get the new, well, new, basically the out of core or spill to disk is on by default. So if you start hitting, for example, by default, it's set to 80% of your RAM usage, it will spill out to disk for these larger operations.

8:15Calvin Hendryx-Parker And it supports joins and group buys are not supported yet. They're planned but not shipped, but it does support sort window functions and many expressions. So those things will actually continue running even if you would have gotten an out of memory or maybe the Ohm killer would have come and killed your process.

8:33Calvin Hendryx-Parker You can actually make these bigger datasets work by leveraging that spill to disk feature of it.

8:40Michael Kennedy What a neat idea because the examples you got on the screen do have a lot of memory, but at the same time, memory is expensive even before all this crazy stuff, right? Relative to how much you can have. Like memory on a server is more expensive than an NVMe disk that is not as fast, but still really fast.

8:59Calvin Hendryx-Parker But still pretty darn fast. I mean, you're basically kind of going back a couple of years in memory technology, but you're gaining the ability to finish the work.

9:07Michael Kennedy So I think that may be more important. Yeah, exactly. A little detail. Oh, all of a sudden I went from 16 gigs of RAM to 500 and I don't know, 30 or whatever, right?

9:17Calvin Hendryx-Parker Yep. Yeah, so one of the things here, again, I mentioned the streaming engine is on by default, but that has a side effect. So one of the things you need to consider when you're upgrading your code from 1.0 or the one version to the two version is that order of operations or order of the data is not guaranteed in the streaming version unless you set maintaining order to true.

9:35Calvin Hendryx-Parker So there's certain row level or row order default operations that might want that. Be sure you check out the upgrading guide before you switch up to 2.0. And then there's also the new map data type called map type. So it's now the arrow map type supported in the Polars map data type. So if you're in the arrows game, which is actually kind of cool because arrow gives you that in-memory transportable data type that you can move between various processes, Polars now supports the map type there, which is basically like a dictionary that's super powered in the Polars world.

10:12Calvin Hendryx-Parker That's kind of the big, big news here. There's last words, I don't know, coming out in months, but I think the benchmarks are the thing speaks for itself on this release. It is incredibly fast performance. This is another thing I just I love about the Python community is people may claim Python slow and maybe should be using Go or Rust. I don't know. I think you can there's lots of great work going on to make sure that Python is still a first class citizen and maintains that performance that is needed to do great production work with these tools.

10:45Michael Kennedy Yeah. If you've got a large scale application so frequently it's There's a little part of it that is performance critical and 90% of it that's not as well. And you can bring different tools to bear on that 10%. Yep.

10:59Calvin Hendryx-Parker Yep. There's an upgrade guide. So if you go to the Polars documentation under the releases upgrade slash two. So make sure you check that out before performing any kind of an update or point your LLM agent at that upgrade guide and say, make it happen. You probably get better results by doing that.

11:14Michael Kennedy Yes. A hundred percent you will.

11:16Calvin Hendryx-Parker Yeah.

11:16Michael Kennedy Yeah. I'm sure you will. So to your performance comment, I don't think that this had anything to do with free threaded Python or any concurrency on the consumer side.

11:26Calvin Hendryx-Parker No, I don't think so. Nope, not yet.

11:28Michael Kennedy But it certainly looks like Holders itself internally is using multiple threads. Otherwise, why would you get a much better result on the much larger server, right? Unless it's just pure memory. So you're still in a sense, this is like...

11:41Calvin Hendryx-Parker Yeah, number cores wouldn't matter unless you're using that. Yeah, exactly. Exactly.

11:44Michael Kennedy So it's like, hey, we don't have this great threading story, or do we? We don't have this great threading story on Python, but still, here's the part where you actually care.

11:53Calvin Hendryx-Parker Yep.

11:53Michael Kennedy You know, jamming on it anyway. All right. So pick the right libraries.

11:57Calvin Hendryx-Parker And that'd be good. Speaking of performance, Michael, what have we cached more?

12:01Michael Kennedy Would you say if you could cache a lot?

12:03Calvin Hendryx-Parker I love that name of this project.

12:06Michael Kennedy Django cache a lot. Yeah. A little bit of CERM makes a lot. A real throwback, right?

12:12Calvin Hendryx-Parker I'm here for it all day long. I am.

12:13Michael Kennedy So am I. Oh my gosh, what a music genre that was back in the day. That was fun. So this project, 1.4 thousand stars, called Django Cash-A-Lot. I think we've got to just throw it out there, the requisite joke. Three things, two, I already broke it. There's two things that are hard in computer science.

12:33Calvin Hendryx-Parker Right.

12:34Michael Kennedy Naming things, cache and validation and off by one errors, right?

12:37Calvin Hendryx-Parker Yeah.

12:37Michael Kennedy But the fact that cache and validation is like one of the first two before the joke even goes off the rails, is it's interesting because it absolutely is not easy. So there's different types of caching that you might want to do. One way to cache is just I'm going to put some kind of front end or pre-compute or something in front of a page.

12:58Michael Kennedy So like on this page, it's got the issues, counts, it's got the number of watchers, the forks, all that kind of stuff. GitHub could just say, well, we're just going to pre-render all of that stuff. And when you ask, here are your bytes back, right? That's probably the most effective, but it also has a lot of challenges.

13:15Michael Kennedy For example, what if a new issue comes up while I'm sitting on this page? Should that refresh? Maybe. What about my little picture up here? If you just straight up cache the whole thing, Calvin logs in. He doesn't want to see me, and I certainly don't want him accessing my stuff. You know what I mean?

13:30Michael Kennedy So there's just a lot of issues with caching that much. So one way you can cache that's really interesting is just say, well, what if everything I asked for the database was already, the queries were ran, the results were given back, they were parsed, and they were turned into ORM objects, and then those things were held on to, right?

13:48Michael Kennedy That could be a much better option where you say, give me the details of this page, that part is cached, give me the details of the user, that part is not cached, and then render it, right? So that's kind of where this thing lives. It basically caches your ORM queries, and then here's the joke part. Hopefully this part is not the joke, but there's a part that is challenging, the invalidation. So this automatically invalidates them, which I think is pretty interesting.

14:15Michael Kennedy Notices when your tables change or something like that. And hey, this cache is now invalid.

14:19Calvin Hendryx-Parker That's really, really nice.

14:21Michael Kennedy Yeah.

14:22Calvin Hendryx-Parker Because otherwise you're spending all the time and mechanics to figure that out.

14:25Michael Kennedy Yeah. You know, sometimes you've got to subscribe to changes if your database server gives you those kinds of things. I don't know. It's pretty tricky.

14:39Calvin Hendryx-Parker So the edge cases are here though there's probably still some not funness i believe it plugs into

14:44Michael Kennedy the django um just caching built-in caching yeah stuff right for the orm because it points out hey if you have multiple servers doing the caching i know multiple web servers and i bet servers also would just mean web workers as in web garden anyway with a common cache server uh server make sure they have their clock synchronized because they're gonna have to use uh each other's numbers and so on.

15:08Calvin Hendryx-Parker But that seems like a solved problem these days. If you don't have clock synchronization, you've got lots of other problems happening too.

15:14Michael Kennedy Exactly. Exactly.

15:16Calvin Hendryx-Parker SSL or TLS won't work.

15:17Michael Kennedy Details.

15:18Calvin Hendryx-Parker Details.

15:19Michael Kennedy Also, if you run a script that somehow changes the database outside of that, so it needs to run manage.py. So I imagine that what's happening is there's a last modified on the cache server. And every time you run a query, it goes, when was this last modified? And if that changes, then it's just going to do a full query.

15:36Michael Kennedy Otherwise, it'll just keep pulling. I'll bet you that that's it. Because otherwise, if you just use the ORM directly through this other script, it would have changed it. But you've got to run this manage pi command on it. That's what I'm guessing.

15:47Calvin Hendryx-Parker You've got to be in the Django world, the Django machinery for it.

15:51Michael Kennedy Exactly.

15:52Calvin Hendryx-Parker I've had this problem before. If you run Redis caches in Redis command, like Redis through Django, like accessing it, not just as a cache, but using it directly. and you try and do something outside of that Redis, there's some subtleties there that you've got to be really, really careful of. So it sounds like this is similar.

16:08Michael Kennedy Yeah, yeah. It's using Django ORM technology, not the database technology or the cache technology, right? Like I said, like subscribing to changes to a table or whatever. So one of the things that Warren's about is if you have a high rate of database modifications, then that'll keep invalidating your cache.

16:26Michael Kennedy So maybe it won't help that much.

16:29Calvin Hendryx-Parker The win, maybe a lose.

16:31Michael Kennedy Exactly. You're just adding complexity, but maybe every read effectively is going to just run anyway. So there's a couple of limits. People can check them out, different setups and so on. But I think it's a cool project. So yeah.

16:45Calvin Hendryx-Parker If you're looking to kind of gain a performance gain real quick there, that's an easy one to try and see if it fits your use case.

16:53Michael Kennedy Caching is such a bit of magic tixie dust that you can sprinkle on. But the challenge is it's the complexity and the invalidation. Yeah.

17:01Calvin Hendryx-Parker Yeah, because you don't want to serve the stale data like you mentioned at the beginning. Yeah. That's interesting. Performance is tricky. Cash it. Yeah. Yeah, performance is tricky. And speaking of performance, some people may think asynchronous is the answer to all things in performance. But Carlton Gibson actually had a good bit of work done at the Django on the Med sprint.

17:23Calvin Hendryx-Parker So if you're not familiar with code sprints, people get together from time to time and will work on the open source projects. And one of the outcomes from the latest sprint was a lot of work toward making async with transaction atomic come to Django, hopefully in 6.2, which would be pretty incredible because that's the next release of Django.

17:41Calvin Hendryx-Parker And this is one of the pieces that's been missing for a while in the Django ecosystem is the ability to use the ORM in an asynchronous fashion. Because currently ORM, you have to still wrap it with async to async version of that. And so he's got some example code here showing basically what this is all about.

18:00Calvin Hendryx-Parker But this is also a very, very tricky problem. Asynchronous operations and concurrency, where multiple things can happen in any order, don't combine well typically with database transactions, which are necessarily well ordered, as he mentions here in the blog post. There's a PR open as of, I think, yesterday and today with no approvals and no milestones yet.

18:21Calvin Hendryx-Parker So if you're excited about transactions and the Django ecosystem and ORMs, you may want to go check out the current work that Carlton did based on this sprint. He made quite a bit of forward progress. And again, I think that this is not an easy problem or else it would have been solved long ago. We've had asynchronous views in Django now for years and years.

18:42Calvin Hendryx-Parker And I think that, like I mentioned here, Django has required using the ORM's sync API for transactions specifically. If you aren't using a transaction, if you didn't wrap it in a begin and a commit, which is what you kind of put a wrap a transaction into because you're running multiple SQL commands at one time or multiple ORM operations at one time, you have to use this sync to async wrapper to make that all go correctly.

19:05Calvin Hendryx-Parker But now if we get this async with transaction atomic, Django, it could actually make this work. I just think that he puts a little ad in here for the Django on the Med sprint, which I highly recommend people going to sprints. It's a really great way to get involved in the community. But if you wanna be able to use this version of the code, There's again a PR.

19:24Calvin Hendryx-Parker You can check out the thread. You can see how it works for your specific workloads. I think a lot of this is going to be workload specific and you're heading into kind of extreme performance area here when you're talking about asynchronous operations on transactions. This could be a big win for your specific workloads.

19:42Calvin Hendryx-Parker It could also be a big headache if it doesn't operate as expected or you're not paying close enough attention to the order of operations for some of these things, which it goes over with in the post. It's a really good post. They had a fun time there on the Mediterranean. Not terrible going for bicycle rides along the sea.

19:57Michael Kennedy That looks all right.

19:58Calvin Hendryx-Parker They got quite a bit of work done. He actually had, it looks like he collaborated with Caleb Haddington, who wrote a book on that. So you actually click over here, the Using Async in Python. So someone who knew quite a bit about the async story in Python. And so they spent literally three days working through this and ended up with a pull request against the ASGIE ref and on the Django bits to make this all go.

20:23Calvin Hendryx-Parker That's pretty optimistic. It seems like the right brains got together at the right time, which is again the reason why we do things like sprints where people get together in person in the same place, and usually they're in pretty nice places, to work on awesome code like this. So you can see here, again, pretty extensive, a couple poll requests for people to go review, and lots of thanks, and lots of great things happened at Django on the Met.

20:45Calvin Hendryx-Parker So I don't know, how do you feel about asynchronous transactions to a database?

20:49Michael Kennedy I feel okay with it, I think. I think I feel okay with it. I had Calvin, I had Carlton, sorry, Carlton. I had Carlton on.

20:58Calvin Hendryx-Parker He and I look the same.

21:00Michael Kennedy Yeah, I know. Well, it's the C. So I had him on to talk about updates to Django's async story. And it sounds like Django's async story is really strong these days. It's just down to a couple of little hard problems to solve, like transactions. I'm a big fan of async. I think it unlocks a bunch of different deployment stories and operational stories that are really powerful.

21:26Michael Kennedy It doesn't always solve a ton of problems, but it can. Yeah,

21:30Calvin Hendryx-Parker well, I feel like this keeps Django more than relevant in today's day and age of things like FastAPI and everyone basically touting full asynchronous stories. Django is still a very, very valid option when it comes to a web framework. And Frank Wiles and I did a presentation at this year's DjangoCon comparing FastAPI with Django and Ninja, which Ninja is an API layer on top of Django that does async really, really well.

21:56Calvin Hendryx-Parker and the performance is obviously FastAPI still faster, but the performance is really, really good for Django if you're using things like Ninja because it leverages this asynchronous capabilities that folks like Carlton have worked really, really hard to make sure that Django has a good story for.

22:11Michael Kennedy Yeah. You were talking about Django Ninja, right?

22:13Calvin Hendryx-Parker Yeah, yeah, Django Ninja.

22:14Michael Kennedy Yeah, which is super neat. Yeah, the analogous to FastAPI. So I think it's really powerful. One thing I would throw out there though, this is not even necessarily related to async, but it could be in the mix here. So if you're worried about transactions and performance, and this is a big caveat, but if it's true, and you're using ORMs, you could use a design pattern called optimistic concurrency, which itself is already a pretty interesting thing.

22:42Michael Kennedy Like ORMs don't necessarily always work that well with transactions.

22:47Calvin Hendryx-Parker Right.

22:47Michael Kennedy Because I'm going to do a query, I'm going to get a user object. I'll return that user object to some other part of the code. If it makes a change to it, it needs to save it. Like you don't want to let the entire request run within a single transaction, right? These need to be like, I'm doing the data stuff and then I'm done.

23:01Michael Kennedy But if you say like, well, we're going to enforce concurrency by just like the beginning of a web request and the end of the web request becomes a transaction. You're just saying I'm having a single threaded process end to end, which is not great. So optimistic concurrency puts a last modified hash on the result.

23:16Michael Kennedy And when you try to save it, it's going to say update the username to name where the modified hash is equal to the one that I have. And if that changes, like, oh, it was changed behind you, you know, you could catch that, requery it, make the, you know what I mean? Like that can get you some better concurrency and some better safety if you're using an ORM, right?

23:34Michael Kennedy Like that's a pretty big story. But I don't know. There's a lot going on here. I don't know how I feel about ASync transactions because I try to avoid using too many transactions already. Usually you don't.

23:45Calvin Hendryx-Parker But, you know, if you're running a bank, you want them. Right. things can get out of order and, and then you could end up with a strange right history based on performance. If some slow query opens the first transaction and there's a fast one that comes behind it, making a right, you've got to make sure you handle that.

24:00Calvin Hendryx-Parker So it looks like we're working on it.

24:02Michael Kennedy Yeah. Yeah. And you got to start talking like transaction, uh, concurrency levels within trans, like read committed, read uncommitted, all the different things you can set on a database. It gets, all right. I always, that part's still hard.

24:14Calvin Hendryx-Parker That part's still hard.

24:14Michael Kennedy I can't do it. We just got to talk. Let's just talk about something. Let's go talk about our extras.

24:18Calvin Hendryx-Parker How about some extras, Michael? What do you got?

24:19Michael Kennedy Well, let's see here. I already got them all queued up. So first extra, this comes to us from Christian Klaus, as you can see here, right now here, at Mike C. Kennedy, FYI update on Calvin's first topic, free threaded wheels for polars.

24:36Calvin Hendryx-Parker Oh, wow. Very quick.

24:37Michael Kennedy So we've already got, well, there's a very interesting story and people out there may know a little better than I do. So I only have like very sparse GitHub comments to go on. So please give me some leeway to get it right here. So this is an open issue to add free-threaded wheels, like add the A-B-I-T wheels to PyPI.

24:57Michael Kennedy So it says currently Polars builds on the free-threaded Python build. So you can use it, but there's no binary wheels. It's going to be like a slow install build or rust and so on. But to be clear, you can use Polars 2 on free-threaded Python. Just the installing of it is a bit tricky. So this issue is like, can we make that better?

25:19Michael Kennedy It's open. That's the part that's interesting, that it's not closed. But if you go down here somewhere, if I look for PyPI, it says, however, before we can do it, we still have to wait on getting more space from PyPI because PyPI has said that you're using too much space and we're not going to allow you to upload anything anymore.

25:39Calvin Hendryx-Parker That's a new one.

25:40Michael Kennedy So you can see the request here. If you jump over to it and you wait for GitHub, because GitHub has become slow the last few years, not on a red sentence fault. But over on PyPI, it says, project limit request, pullers runtime compatibility, 50 gigabytes, please. And it's asking for, this is by Richie Vink, the creator, as you mentioned before.

26:02Michael Kennedy And it said, help, we can't upload anymore. So this is an interesting problem because...

26:07Calvin Hendryx-Parker Yeah, obviously they're trying to avoid abuse of PyPI.

26:10Michael Kennedy Right. And just trying to pay for it. You know, they're asking for 50 gigs. That's a lot of space. At the same time, if you have a popular project that has a big binary built component like the rest part of this, and you want to support all the different things, right? I want to support free threaded wheels on ARM, you know, like all the different things that you might build for that starts to explode out into a bunch of combinatorial options that take a lot of space.

26:36Michael Kennedy right so i'm sympathetic to it somebody it's just i don't know i can't remember where it was um so it's like do do we really need pi pi yes you really need it to be or do do we really no do we really need old releases on pi pi i'm like yes yes yes you do please anyway thank you christian klaus for sending this in this is um it's about polars it ties into your items but it's also just

26:59Calvin Hendryx-Parker an interesting difficulty of the day you know there's still things going on behind the scenes

27:04Michael Kennedy absolutely okay two more things i want to cover real quick let's do this one next so i've i started working on these write-ups that are basically telling like guides visual guides to talk python episodes that tell this the technical story of what the episode was about so for example we've got let's see the probably the funnest one is this eve because it's a game so it's got maybe 10 to 15 graphics.

27:31Michael Kennedy Got a nice little reader view. You can do like full screen or you can,

27:35Calvin Hendryx-Parker you know,

27:36Michael Kennedy a little, it's like a little Instapaper-ish because it's, it's a decent amount of reading. So it goes through and it says, you know, okay, what is this? It talks about like the problem with nice pictures, tells the story of, of what all the, what's going on. And just, it has this like visual storytelling component of each, um, of each episode.

27:55Michael Kennedy And so I've been working on this. I don't have that many out. I think I've got six out, but I just, I was fascinated with like, could I make a visual storytelling thing? That's just not, it's not just narration, right? It's, it's, let's look at the different things discussed in the episode and kind of make a technical article out of them.

28:12Calvin Hendryx-Parker Yeah. Well, and people learn differently. Some people want to hear the podcast. Some people want to read the blog posts and some people would love this visual representation, which is, I like how it themed or how you theme the graphics, you know, in line with Eve, you know, as opposed to. Yeah.

28:25Michael Kennedy Thanks. There's a bunch of really cool graphics in here.

28:29Calvin Hendryx-Parker It's very sci-fi looking.

28:31Michael Kennedy Yeah. And each one's a little bit of a different theme. I'll go to the one that we just did together, the state of the art in Python. And it's got some really interesting pictures. Check it out. If you just go to Talk Python, hover over episodes, it drops into the visual guides and you can go and see all of them.

28:50Michael Kennedy Like I said, there's a handful of them.

28:51Calvin Hendryx-Parker It's not just a podcast anymore.

28:53Michael Kennedy No, it's so much more.

28:55Calvin Hendryx-Parker So much more. And you've got so much more.

28:59Michael Kennedy Then, remember how I lamented? And I wish I knew this. Two people sent this in. Nick Moua. Hey, Nick. And Raphael Bosen and said, Michael, you kind of went off on PEP 824 about like, why is it just so focused? Couldn't it have this other thing that you wanted? And you're like, no, I don't really want it.

29:16Michael Kennedy What are you talking about? You're insane. Well, if I had just gone back at one in PEP numbers, 8pep823 is in fact that null coalescing operator that I was looking for right like a.b question mark dot c d is the complicated sort of deal here that if I'm trying to access something in a chain like x.y.z.whatever if any of those is none I need to just stop and say it's none or stop and raise an exception like that that that is not none type has no attribute whatever this is what that's about. So that's pretty interesting.

29:51Michael Kennedy And I think I'm here for it.

29:53Calvin Hendryx-Parker Nice.

29:53Michael Kennedy Yeah. Last thing. And this

29:54Calvin Hendryx-Parker one is, it's a big one. This is really fun.

29:58Michael Kennedy This is really, yeah, this is a big one. So I'm launching Talk Python membership, and I'm hoping that we can create a really nice community over there that has a couple of aspects. So I've been thinking for a long time, like, couldn't I offer something like a little bit more for people, listeners of the podcast and this podcast too, that's one thing I could offer that seems super obvious, like, hey, you get ad free episodes, or you get episodes ahead of time.

30:21Michael Kennedy It's like, well, you know, that's great, but that's not that great of it. Like that's not a huge benefit. So sure, Talk Python membership does come with ads, but I wanted to see what else I could offer. So it comes with a nice Discord community. A bunch of the Talk Python guests are already in the community.

30:36Michael Kennedy So you can come hang out with many of the people that you've heard on the show.

30:40Calvin Hendryx-Parker Yeah.

30:40Michael Kennedy Calvin, for example.

30:41Calvin Hendryx-Parker It's been one of the reasons I've now keeping Discord open more regularly. That's awesome. There's enough gravitational pull because of the work you're doing there I've keep it open now.

30:50Michael Kennedy Thank you. That's awesome. Yeah, I do too. And it's really, really, it's a neat area to be in. And if you're not a gamer, just Discord is easier. It's easier than Slack.

30:58Calvin Hendryx-Parker It's not just for gamers. It's actually just an easier Slack. I agree.

31:02Michael Kennedy And one of the main things I wanted to focus on is live events. So it comes with a meetup. If you would like to go to a Python meetup or a regional conference or something like that, but your area doesn't have one, you can't make it, or you just want to go to more, You could go and I'm running a monthly tech session where it's like a conference style presentation, but then sort of a mix and mingle, just hang out on Discord video channels with whoever gave the presentation and everyone else, me included.

31:31Michael Kennedy So all those things. And I'm also going to add a preview, like a summary type of thing to the episode. So a separate sidecar podcast feed. Like here's an hour and 20 minute podcast episode, but here's a four minute. What's it about? kind of the cliff notes. And if you find that interesting, then you can go listen to the full one, right?

31:51Michael Kennedy Kind of let you, you know, protect your time a little bit, but keep up on the ones that, I don't know, you don't have the time to listen.

31:56Calvin Hendryx-Parker I love it. I'm here for it. I'm all about community. And so this is a great, great move. I'm glad you're doing this.

32:01Michael Kennedy Thanks. Thank you so much. So folks, support all the work. Talkpython.fm. Click on membership right at the top. Check it out. Be part of it. Hope you're there.

32:09Calvin Hendryx-Parker Cool. Well, thank you for all that. That's an amazing extra to end on there for you. I've got a couple extras that we want is the fact that Jazz Band is shutting down. That was announced back in March, but there was a renewed discussion a week ago here on Reddit. And one of the things that came out of that is, by the way, there's Django Commons for things like what Jazz Band used to do.

32:30Calvin Hendryx-Parker So if you wanted to come out and have a place where you can find kind of more of the Commons supported projects for Django, make sure you check out django-commons.org. You can join the Commons, you can see the projects, you can see here, you know, pretty heavy hitter projects, Django Valkey, so support for Valkey, things like Tailwind CLI, DRF stuff.

32:52Calvin Hendryx-Parker One of my favorites, Django FSM 2 is now part of the Commons projects. So tons more that are joining in there, all one home, which means they have a nice, safe place to live. So check out the Django Commons. The other thing, this is not necessarily Python related, but boy, is it an awesome, fun little tool I found.

33:10Calvin Hendryx-Parker Since I'm doing more and more of my agentic work on remote machines and a lot of the output maybe markdown files, I would love to have a very rich way to view markdown in the terminal. So I went and searched for a TUI slash CLI markdown navigator and I found TreeMD. I believe it is in Rust. Rust? Yeah, 99.2% Rust.

33:32Calvin Hendryx-Parker But it is a really nice markdown viewer, which gives you obviously mouse usage. A lot of the TUI apps, the big benefit is you can use the mouse in your terminal. It gives you an outline. It gives you obviously a rich rendering. If your terminal supports images, it will see inline images inside the markdown files.

33:51Calvin Hendryx-Parker Wow. Yeah,

33:52Michael Kennedy that's cool.

33:52Calvin Hendryx-Parker See by their screenshot doesn't show that off because that's actually a really fancy feature of this. You can jump in the outline. I'll make that bigger maybe. Yeah, there you go. You can jump in the outline to various sections. You can also pre-filter a markdown file from the command line to say, show me all the Rust snippets or Python code snippets in there.

34:11Calvin Hendryx-Parker And then it'll basically filter the document down to just those snippets and give you a navigator of the various snippets. Cause you're like, I'm looking for a code sample in this markdown. Just show me only those pieces. And you can do that with a tree MD. So I know again, it's not a, not a Python tool, but boy, is it a part of my new productivity toolkit of great things that I have installed to basically remote work remotely with my agents and the outputs that are coming from them.

34:36Calvin Hendryx-Parker So another cool thing that I'll mention, remote documents. You can type treeMD and like a GitHub repo reference to owner slash repo, and it will get to open the readme immediately. Or you can just put in any URL to a raw markdown file on the web, and it's now open in your local viewer in your command line.

34:54Calvin Hendryx-Parker So you can be remote. You know, I've been doubling down on my usage of herdr and my framework desktop that's over here so that I can run my Pi sessions on my CloudCo sessions. And now I can view all my markdown files.

35:06Michael Kennedy so that was a cool one i think it's a great a great find it looks really nice so two things first one thing i've learned there are so many projects by running this show there are so many projects out there that are a UI focused sort of thing and they sometimes don't even have one screenshot what are you doing you're literally the thing you're about this you are about pictures why do you have no picture right there's only words here and it's got themes too oh yeah i love it like nine different

35:32Calvin Hendryx-Parker themes. Yeah.

35:34Michael Kennedy And the other, I think, is our mission is to bring tools to Python developers, not necessarily. I don't think they don't have to be Python tools. It doesn't have to be written in, compiled in or whatever, Python, in order for it to be something awesome that we can use. So I think it's great.

35:49Calvin Hendryx-Parker Cool. All right, Michael.

35:51Michael Kennedy Would you say that it looks good for you? It does look good. Oh, no, it started playing. All right, so the joke this week comes to us from this guy named Calvin sent this in to me. No, Calvin shared this with me earlier, and it's, boy, this thing captures the zeitgeist so well, doesn't it? It's called Looks Good to Me, LGTM, Claude Opus 5.5.

36:16Michael Kennedy It starts on a Friday. It's this kinetic typography, a lot of moving words sort of interesting. Really well done, I think, on the graphics. And it talks about basically the story of the manager who gets super psyched about AI and just makes everyone use it.

36:34Calvin Hendryx-Parker Yeah. So go give it a listen. It's a fun little music video. I believe it was generated by AI itself, too, which is kind of fun.

36:40Michael Kennedy Oh, it's got to be. It's got to be. Very meta. You've got to be careful because once you go down this path, I believe it will send you down a path of other Opus 5 videos. I'll set the stage. So there's a Slack. I mean, it's not actually Slack, but you know it's Slack. and Brad, VP of Velocity, Vice President of Velocity.

37:00Michael Kennedy Hey team, quick one. Before the weekend, leadership is super excited about AI. Off it goes. It's like, ooh. Give it a listen. You'll definitely laugh. It's very fun.

37:11Calvin Hendryx-Parker You'll get a giggle.

37:12Michael Kennedy Yeah, you will. You know what? I think this is a perfect bookend as well, Calvin. We started with Sir Mix-a-Lot and we end with LGTM. Let's go.

37:22Calvin Hendryx-Parker Looks good to me. All right, Michael. This episode looks good to me. Let's give it a wrap.

37:28Michael Kennedy Let's give it a wrap. Oh, my gosh. All right. Bye, all.

37:31Calvin Hendryx-Parker See y'all later.