Django Developers Survey 2026

Speaker 1: Hi, welcome to another episode of Django Chat, a special summer edition on the Django Survey. I'm Will Vincent with Carlton Gibson. Hey Carlton.

Speaker 2: Hello Will. What are we doing in summer? That's crazy. We normally have it off.

Speaker 1: No, I know. I was trying I'm trying to be become European and it's not working. But we're doing it for good reason. So the Django survey it came out in May. The results are here and we're going to discuss it. So links in the notes, but we're going to talk about high highlights because it's worth saying this is the only objective measure we have of the Django community. Maybe you you're on the steering council. Like speak to how important is the survey?

Speaker 2: Well historically it's been very important. So I mean um the Redis back end for the DB for the caching for instance. um you know in the survey it was like you know 70% of people using Redis uh for caching and we haven't gotten a back end in the in um Django itself and it was this regular thing was is it is it Django Redis or is it Django Reddit's cache and which one was it? And you you remember and then you start a new project two years later and you can't remember what you what you remembered last time, and so you have to go and do all this research about which one to use. Anyway, that that came out, and so we had a Google Summer Code project. We had the had the Reddish backend and that came out of it directly. Why? Because well the survey said, you know, we're all using Redis, and then it's this makes a really good argument for having it in Django. That's just one example. There's

Speaker 2: a lot of things.

Speaker 1: Yeah, well in some companies too. MongoDB had uh official back end and um said directly you know we had Jib on the podcast, you know it was due to seeing how well it ranked uh on the survey. So so yeah, so we should say so we know that there's there's millions of downloads of Django there were 3500 people who filled this out, which is a little less than historic, but not that much less. I think it was about 4,600 last year. So small sample size, but it's global. Like which was nice to see, right? There wasn't one big dominant country. I think if I look at the stats, India was 15%, the US 10%, Germany at 5%, and then a very long tail. So that was really good. Yeah, but also

Speaker 2: Middle Eastern Africa came popped up there over ten percent as well. So that was I think in one of the sections higher than the US and I I would've like to see the EU as one thing. Yep.

Speaker 1: Well we can we can update the survey next year. I say that because for better or for worse I've had a heavy hand on it. over the years. Um but yes, we'll fix that.

Speaker 2: It's funny 'cause the EU isn't really one country, but it kind of you know, you think of it.

Speaker 1: I mean does Brita does Britain does Britain count? You know, 'cause I get in trouble saying DjangoCon Europe versus DjangoCon EU. You know Europeans are sensitive about these things. I just don't want to even say either word.

Speaker 2: Yeah, no, I think call it Jank on Europe, because then we could go to Turkey or we could go to Britain, we could go around

Speaker 1: Is Turkey Turkey part of Europe?

Speaker 2: Well part of Turkey's part of Europe, certainly.

Speaker 1: So the last thing to say about who filled it out is uh Um 43% two years or less of coding, but 41% six plus years of coding. So I think that's fairly representative. You know, it's not the people that we see at Django Cons who tend to be more experienced. but it's a pretty good mix of people. So we're gonna use these to talk about Django and is this perfect? No. Is it the best measurements we have? Yes. Because otherwise we're just looking at PyPI download downloads which who knows how accurate those are.

Speaker 2: But also to lots of people who are um a good proportion of people two years two years or less of coding, that means there's new people coming into Django. A nice thing to see as well.

Speaker 1: Yes. And again, we don't currently track who visits Django Project. com in any sort of real way. There's efforts around that. But we're really flying blind in terms of where, who, what. Um so this is it. This and the Yeah, no, I mean it

Speaker 2: it is alright. Historically there was a discussion about adding telemetry to uh to Jango. Of course nobody wants to do that. And then in the current climate, I don't think, you know, we wouldn't anyone go anywhere near that at the moment. So, you know, there is no there is no way. We other than reaching out and saying, come on, fill in the survey, what can we do? I don't know. Anyway, let's get this kill.

Speaker 1: Let's dive in. Okay. And I should mention there'll be an official blog post I've I've written the link to as well with highlights, but we're just gonna go through so positives versions. I'll let you start with you. So People report being overwhelmingly on the latest versions. It's 49% on 6. 0. This was filled out, um, came out in May. So that's very promising. Um, 30% on 5. 2. And only a small percentage on four whatever. So that's fantastic.

Speaker 2: Yes, because historically it wasn't the case, right? Back in the day it was, oh, I'm still running one point three, I'm still running one point five, I'm still running one point seven. Okay. I think you know the success of the um schedule release the the you know the stable release schedule every eight months um you know that's that's and the the stability guarantees and the the guarantee application policy, all of that has mean meant over the last few years it's become very easy to upgrade Jang and we've started to bring more of the community with us. And I think when we see these kind of numbers, I think that's a real um you know uh confirmation that the effort that we put in is worthwhile. So that's super to see I think.

Speaker 1: Because it's a huge amount of work by the fellows, by the community. Um And it's seems to be paying off, right? I mean, I can't remember the last really bad breaking change. I mean, and if something is deprecated, it's a long, long, long, long time. You know, there shouldn't be any surprises at this point.

Speaker 2: Yeah, no. And i it yeah, it's good. And we are yeah, Django's a stable project, but we still manage to make those changes, we still manage to bring in all the you know, all the new features we can talk about all the exciting things of you know every rate.

Speaker 1: Yeah, I think we're well, we're gonna have podcasts on that. But I mean uh like one thing to mention is uh and again you can see in the Django News newsletter there's double digit pull requests merged into core every single week.

Speaker 2: Yeah.

Speaker 1: Like it is on top of new features with every feature release. You know, we'll try not to get too much into that. But an async We're gonna talk about that in a minute. You know, so it's it's very, very active despite being mature.

Speaker 2: Yeah, and you look at six point zero, which is the latest release uh well, six point one 's just popped out, but the latest release as the survey was taken, we've got Django tasks, we've got template partials mostly. You know, these are big these are big changes right so you know we b I think we balance it really well anyway

Speaker 1: I think we're doing a great job Carlton you know what do you think yeah yeah well

Speaker 2: yeah I think we're great let's just pat ourselves on the back

Speaker 1: All right, let's let's go down the list. So databases. Um Postgres is still dominant. SQLite very popular. I d you know, uh of course SQLite is popular just because that's the default for local development and getting started. There is stuff. I mean I did a a talk on deployment at EuroPython and I'll be doing one at DjangoCon US and there is a movement to deploy with SQLite. Um historically there's some issues around multi-connections, but I don't know if that's a thing other than or people are just like, eh, I'm gonna use SQLite or Postgres unless I'm reason to use something else.

Speaker 2: Yeah, I mean I I still think choosing to deploy with SQLite is the you know is the spicy is the spicy option, even though the patterns are more established now. You know, I I personally would so I I would use Postgres in almost every circumstance because even if you've got a small BPS, you can run a small Postgres there and it it's fine. But yes, I see a lot of people who are excited by you know not running a separate server, not running a separate process, not you know, there's a lot of juice in it. And the patterns now are well established. Adam Hill put it all up into a um a a single package where you just uh you know pip install your your I can't remember the name of the package exactly install the apps and then it configures your your SQLite exactly how it needs to be.

Speaker 2: And for a lot of deployments, that is perfectly fine. But there's still you know issues with short-lived readers, there's still issues with backups, there's still issues. I still think it's a spicy choice personally

Speaker 1: Yeah, yeah, yeah. Um okay, backends API, API. So this was interesting. There's, well, let's say, so Django Rest framework is dominant. 73 You know, Django Ninja is there at 17%. It's the same patterns, forms, serializers for validation. You know, it's it's still being used. used, it's still popular. Um I know some people are working on next generation serializers and updates. Yeah

Speaker 2: there might be something to come at some point in the future. But there's no rush. Like DRF's not going anyway. It's nice and stable. It's nice and doing its thing. said like 70 odd percent using DRF still like that's phenomenal and you know for the that for the um for the serializing the pi pydentic are you how are you using are you using forms are you using serializers validation are you using pydentic one option well 20 percent were using pyden down here well that's almost the same as 17 who are using Django Ninja so there's like you know if you're using one you're using the other but most people just just aren't what I thought was interesting in these figures well API first well you know is it API first. Well, only about half of people were using um Django as an API solution. And out of those, half were using it as the back end for a For a single page application, the other half were API only.

Speaker 2: But then half of people are j are building server-server server-rendered apps sending out templates.

Speaker 1: Well, right. That's the thing. There's a bifurcation, and really it's swung back to Towards sprinkling in the interactivity with HTMX. jQuery is still there. You know, React and HTMX are pretty much tied at this point. Um, template partials. Thank you, Carlton. Yeah, there's there's ways to, you know, and And that's what I tell people is that if you know you need to go full API, you know, you're a team, fine. But if you're starting out, like you don't have to, like just baby iterate your way there. Because it is a big leap. And if you're an individual or a small team, it's it's more of a maintenance burden than just having it all in the same place.

Speaker 2: I think it's significantly more complicated to build an application with a React front end on top of an API than it is to build a server rendered template based application. So in this economy, you know, it's not zero interest rates anymore. We we can't necessarily export a team with, you know, two front-end developers, two back-end developers, you know. uh and all the all the um coordination tax between them. I think you know going back to the the old what the old school ways of doing it I think there's a lot of economic sense in that which I think is what uh drives it and HTMX is phenomenal. They've got new version four just being released as we speak. Um you know I w I was amazed when I saw the numbers and I saw, you know, basically HTMX and React neck and neck

Speaker 2: Nick, you know, I think React had a couple of points in front, but like they're basically third each.

Speaker 1: And I think, you know, HTMX was uh sorry, don't have the numbers quite I don't want to stare at them like like five percent in twenty twenty one so it's really just zoomed up and I I always felt there was an an education and a communication problem but it seems like people are People know about it now, you know, because I remember even a couple of years ago, I mean, Carson Gross, the creator of HTMX, gave a talk at DjangoCon US recently, keynote. And And I was talking to someone after at DjangoCon who'd seen the keynote who said, I never heard of HTMX before his talk. You know?

Speaker 2: Right. Okay.

Speaker 1: So you can know you never can assume. that people know about a thing. But

Speaker 2: No, I mean you can't I mean a lot there was one thing further d like much further down the survey which I thought was lovely was that twenty five percent of respondents said it was like how do you keep up with Django News Do you read the blogs, you listen to the podcast, you get the newsletter? 25% of people said, no, none of that. I don't keep up with it at all. So there's there's a massive chunk of our user base that are just using Django and happily doing their thing. They're not engaging with the the news around what's new in Django.

Speaker 1: Oh no. If I ever po poke my head up and go to a a professional event which is rare, I I still think n single digit percent know what the software Django Software Foundation is, know about fellows. Like the it's just like, well, Django just appears like Python, like Water, you know. Um you know.

Speaker 2: So but

Speaker 1: yeah, so that's a good thing in the abstract, but it's an important to remember, like it can be insular even know, uh but you know, we can always communicate better and just on the mission on

Speaker 2: on the front and stuff I wanted to just pick up little But uh CSS frameworks, those questions. Bootstrap still number one. You know, it's still there. Number one bootstrap. Then Tailwind close behind, and then planes plain plain CSS, just only two points back, right? So there was a sort of split Bootstrap, Tailwind, or you know, vanilla basically. And then there was others, the long tail of other options.

Speaker 1: Yeah, there's I mean Tailwind, you know, we recall, Tailwind was this revelation and people really got excited. And I I still use it for a lot of projects, but I use Bootstrap too. I mean it's it's how much CSS do you want to write? And okay, now we I'll I'll say the words since we're a few minutes in, you know, AI, I think especially for web developers, AI and CSS, you know, it doesn't certainly doesn't replace a good front-end engineer, but you can do more. um than you could before. And so I suspect the pure CSS is partly that because if you really dive into it, you want a framework for your CSS. Like it's it's its own, right? You spent you can spend a career on CSS alone.

Speaker 2: Yeah, if you're a if you're a a a jobbing jang or then to use a framework give you to give you some structure around you know your style decoration It's

Speaker 1: easier for someone to come in. So yeah, so I th I think if anything, peop there's a not a pushback against Tailwind, because Tailwind's still very popular, but it's a heavy it's a heavy framework. Um

Speaker 2: well you've got a the the the big annoyance of it is you still need a boot build tool, right? So when I'm using it, I run it through compressor and compressor run runs the tool, but I've still got to have that pre-processor. in place. Whereas if you're just using van vanilla CSS, you just write the CSS and or you know you can get a tool to help you write it if you don't know what's what's

Speaker 1: Yep, agree. Um, well, to finish up on front end, so Django templating language still 80%. Ginja is in the teens. This is Very stable. Um maybe it speaks to things like template partials. You know, the templating language is mature, but there are innovations. Um Um yeah, I don't know. I I guess maybe I thought there would be more action here, but it seems like it's the layer on top, it's the HTMX that is enabling the stable base to be sufficient for people.

Speaker 2: Well also I think there was a like when Ginger first came along, it was a lot faster because a lot of the cost is in passing. template um yeah it might be slightly faster to render um but not significantly the the the the way it's faster is with the parsing but um for many versions now um we've had um the template

Speaker 1: Yes, that 's a good thing. Which

Speaker 2: it gets rid of the passing step. So you know it's passed once the first time the template's loaded and then it's available for every other time. And so the the speed difference is negligible these days. And then it just comes down to this style question about well, do you want to basically be able to write Python in your templates? And You know, if you do, then ginger 's more powerful.

Speaker 1: Yeah.

Speaker 2: And some people like that, but obviously not enough to drive the community as a whole away from the DTR.

Speaker 1: had a suspicion that you know fast API which uses Jinja primarily would lead people who come to Django to prefer the template that they're you know templating engine that they're used to. to but um that's something I'm curious about so if I I suspect that might happen because look I know we're Django pilled here but like fast API is big the community is growing Um I hope there's more crossovers, because it's pretty different lanes at the moment.

Speaker 2: I suspect that the choice of template language is kind of Kinda like the choice of cutlery. It doesn't really matter. You're just gonna go with whatever's given to you.

Speaker 1: We have to fight about tools, yeah.

Speaker 2: Um

Speaker 1: well to to to abstract From tools, let's talk about async. Um, so I'll tee it up and then you can go. So this was really encouraging. So 35% said yes, they're using async, 39% said they're planning to, only 26% Said no interest in async. And then of those, 51% said they were using async views in some capacity, 50% channels. Um this is all heartening. And you're doing a lot directly on this. So Yeah, yeah, yeah.

Speaker 2: So I'm still I am still on the coalface pushing forward the async story as fast as we can. We've um what's nice about 51% using um async views. What that means is that they're using the the async story within Django itself rather than say channels. And channels is great, channels is brilliant, but the the reason to keep using it really is um WebSocket support because

Speaker 1: um

Speaker 2: jang uh Django's because of the nature of it Django's not gonna probably have WebSocket supporting call itself so why would you keep keep with channels assuming assuming everything is rosy in the in the land of um Django cause async story. Why would you use channels? Well you'd use it for async. So 50% using it and that tied in with the the numbers from are you using WebSockets? versus service and events, it's like, yeah. So if you're using more or less if you're using uh WebSockets, you're using channels, and that's why. Um, but that people are using async fuse. I think that's um fantastic because for years we had, oh it's not quite ready, we've just recently updated the topic guide. Look, the API is complete. The the remaining issues around async are um you know async issues or Python issues or or whatever I recently chatted to Michael Kennedy on Talk Python about this.

Speaker 2: But it 's um it's yeah it's it's it's there, it's ready. The other thing that's come along is uh free f free threading. We've just got the um Django test suite passing with free threading. There's a new version of ASGIREF out which fixes um a leak in local that was there that was stopping that happen. So I I honestly think over the next couple of years we're gonna see an awful lot of the bet the long-term bets that Django has made over the last decade essentially they're going to come to fruition as free trading rolls out. We're going to get rid of things like guild contention because that's where people see it. Is they um because we throw a lot of work into the thread, which you have to do, you're doing CPU bound work, but we throw work into threads. And you know, if you do that at small scale, no problem. But eventually you hit guild contention

Speaker 2: and what you what you need is uh the the free threading build of Python to enable those threads to run separately and you get truly parallel work. And I think we're going to see a lot of performance wins for Jenga over the next, you know, 3. 15s coming, 3. 16, 3. 17, I think over the next two, three years, it's going to be a very happy time for us in Django Land.

Speaker 1: And I think part of it is, of course, I think about the education aspect is just having blog posts, repos, examples. Of you're doing it this way, now you can do it that way. I mean, yeah, we can I I I guess we don't have a note on it, but you know, that's one of the things that emerges also from the survey in the AI category. is the docs are still number one, but AI is number two, um, followed by YouTube.

Speaker 2: Right.

Speaker 1: So you know that's good if it helps people uncover things in the docs. And be become educated that way, but um, you know, I want to be positive about it, but it's a big shift. You know, stack overflow has fallen off a cliff. That makes sense. Um, but you know, as a Creator, you know, look, Adam Johnson is still doing multiple posts a week. Like there are people putting out stuff, but you know, for myself, there's less of a if it's just gonna get scooped up up and put into training data and there's no link, it's harder to justify the time to create these things.

Speaker 2: Yeah, no, absolutely. I think I think, you know, my my take here is we have to wait and see. how the you know the bubble plays out. I think there's a there's clearly there's new technology, clearly it's superly super capable, but it's clearly being subsidized by billions and billions of dollars. which in a non-sustainable way. So how does that play out? And so I think for individual creators or individual developers, I think we need to just keep our heads down and survive to see what hap what happens once once it's played out because these tools are useful but they're not if if the ability to subsidize them to the extent to the tune of billions of dollars a year disappears well how freely available are they going to be. So I mean one of the topics is uh you know was AI usage. And so AI is clearly a thing.

Speaker 2: 50% of people are uh are using it. Um

Speaker 1: well sorry uh eighty five percent are using it uh Daily or weekly. Um

Speaker 2: ,

Speaker 1: fifty fifty-eight percent daily, twenty-seven percent several times a week. So that's eighty-five percent using it at least once a week. week and only 10% said none.

Speaker 2: Sure, but yeah, I mean so but what does that using mean? So 50% 30% said they're using chat, 30% said they mu they using um code generation so it's a bit like you know what does it mean uh I did I did somebody ask um chat GPT for oh how do I do this in Django that counts as using it once a week right now

Speaker 1: no no it's interesting when we for the survey now Next year we need we want to tease this out. You know, how what is, you know, what does using AI mean? Are you, you know, we saw like one of the big things is CLI usage is is pretty high. Um, now is that because everyone's running agents? in the terminal. Um, you know, I s you know, so we want to tease out what models are using, what agents are you using, and then I guess, you know, how much are you using it, and then what are you asking it to do, right? Because it was something like 27% said they're doing, you know, let it run, mul multi-files, go crazy. But most, the majority are still saying nope, or they're saying that like have it run. Manually review it. You know, so more of like a managed AI usage than you know just hordes of agents replacing what you're doing.

Speaker 1: Those some people are doing that. You know, friends we know are doing that.

Speaker 2: Yeah, no, no, no. Yeah. I mean look, th th there's a whole there's a whole spectrum here, right? But what's not clear from the figures? So everybody's like not everybody, but a lot large number of people are in clearly engaged in it. Everybody's heard of it. But to what what plans do they have? Like what access do they have? Have they got, you know a an a a plan a paid plan such that they can do significant amounts of agent work or is it you know actually I've only got a free quota where I can chat to it a bit and then work and that detail isn't bought out. Um and my sort of point to go back to your point about creating, what I'd like to see, what I'd like us to get to is the point where the the economic bubble aspect that we're currently in has has floated away. And the long term, look, you will expect to pay this for that has become kind of clear.

Speaker 2: And I think at that point we'll be able to judge much more effectively. w what usage we're going to start to see because you know if it's if it's thousands and thousands and thousands a month for you know your an agent I don't know that many people are going to be able to afford that

Speaker 1: Yeah, and there's that pricing stuff hasn't come yet. I mean, one thing I noticed being at the big Python conferences is last year it was are you using AI, what models are you using? This year everyone's using it. It's how do you make the most of it? So agents, harnesses, but also costs, you know, c and yeah, that hasn't fully played out. I mean, I would love to see more content from the community. You know, there's There's people like Peter Granstaff is running, he's got a very powerful local computer. He's running local models. You can use OLAM or LM Studio to use newer models like Kimi and the cloud. Um I hope the community can be can talk more about what what we're using um because yeah like are you using it yeah what does that mean we still haven't teased that out I mean I'm personally

Speaker 1: And my colleague Paul Everett is very excited about what Apple's doing with MLX, which is modified memory and the M5 chips and M7 chips. if you're you doing agentic flows the constraint is not compute it's memory you have to store everything in there and that is very expensive and so if you can do it on your laptop you know with 128 gigabytes of of RAM or these things coming down the line, then you can not just own your data, but you can run a you know open weight Chinese probably model and you know just have it running for forever. Because I guess the interesting thing is the models they're still in sorry, let me finish this thought and then you go. The models are still improving a little bit, but what's really improved, the reason they've gotten better is these agentic flows. where they keep trying, you know, already with ChatGPT, it's like, how many times do you want me to try?

Speaker 1: How many tokens do you want to burn? And it's like, yeah, it's better, but like at what cost? Okay, I'm done.

Speaker 2: Go. Okay, but like you just said you just said words like M five, M seven, a hundred and twenty eight gigs of

Speaker 1: Everyone can afford these, right? Everyone can afford five thousand dollar.

Speaker 2: Exactly. This is no more affordable for the majority of people than you know a a a a you know an API costs thousands of dollars a month token subscription right it uh or token

Speaker 1: well yeah and we all right so as as a last bit yeah like anthropic's gonna release its figures. Everyone I know who says they know something says that anthropic is minting money on inference, right? Because the question is always, oh, they're subsidizing it. Well, how much is being subsidized? But you know, right now it's a better deal in general to like use an API than to run it all yourself. But that surely has to switch because you you it's unsustainable to to spend thousands of dollars a month and

Speaker 2: I mean there's a nice uh George Orwell quote about um uh about uh the newspapers in Spain. It's like in most countries you you know, um you'll see the different takes on the same news, you know, like what the the the the left paper will say one thing, the right paper will say another. But in Spain it's like two different w worlds, they'll just say totally different things. And you know, you've just said that uh people say that then they're making money on inference, but you you read some posts like that, but you also read other posts where they're just hemorrhaging billions of dollars a ton of things.

Speaker 1: Oh yeah, there's you know

Speaker 2: , so what to believe.

Speaker 1: I know.

Speaker 2: Anyway, anyway.

Speaker 1: One thing from

Speaker 2: all of this tooling section I want to just go is that 75% of people were still using IDEs. VS Code 47%, PyCharm 26%. That's three quarters. still using the IDE. So it's not that we've all abandoned our editors and jumped into the terminal and just driving clock cord.

Speaker 1: Yeah. Well it's all up for grabs. I mean it's it's the you know and I can speak Speak personally, you know, at JetBrains on PyCharm, we're rolling out constant features and try to think, you know, what is the what does a modern IDE look like? You know, it is interesting that the you know these AI-first IDE So cursors still around that they're being acquired. Windsurf got consumed. You know, it's really just unclear. And now there's these agents, so you can pop in whatever model. You know, Hermes is written in Python. It will generate skills for you in the back end. Now skills are sexy and interesting. They're just markdown files. Um, so all right, let's not get too far afield, but we need to tease this out. And I think you know i guess the last thing i would say is web flows do work very well with ai so like a lot of my colleagues are data science jupy

Speaker 1: you can still use it but just with the cells and everything it's not quite as is smooth but for web flows you know you can ask it to build you an Instagram clone and it'll give you something. Is it good? Not without a lot of guidance and knowledge. You know you still I s I think you know if you could build it yourself you can build manually you can build it faster with AI but you just gotta be know how to do it manually um and otherwise you'll just get so far afield quickly

Speaker 2: you still gotta maintain

Speaker 1: Okay, or or leave.

Speaker 2: Yeah, I'd leave. I've moved on to the next country. Anyway, let's get back to the thing.

Speaker 1: Okay, go on. Uh please session. Well my take

Speaker 2: my take on this the interesting, yeah, mo was most people still using a monolith, still on a VPS, still using NGX, still. you know, still that as your front end for static files. You know, the as bog standard as bog standard could be. And then for the database, there was a nice split. 33% self-managing that database and 30% managing data. So you know there's this nice divide between like, yeah, do you use an RDS or a crunchy data or a host, you know, a managed database, or are you or are you running it yourself? I I thought that was lovely.

Speaker 1: And I've realized too, like the word manage. carries a lot of water in the database section because I was talking with Vercel and Render and all these services, you know, not to not to name a specific company, but But you can s call something managed and you just spin up a Docker container and do backups every once in a while. It's managed. You know, the marketing team's happy. Put it on the homepage. But if you're running a big important business and you have command compliance and all the rest, you know, that type of managed is a whole separate thing. And so

Speaker 2: let me give you an example. So over the summer, what have I been? Well I've done a bit of maintenance and uh Two I did um two big RDS updates in a day and one was for a very serious project that you know has to stay up and I ru I I did their own lovely green blue thing and it's just delightful you know it it spins up the the the blue it's uh you know it sets up a logical recruit replication does all this and then you can check it all again your application and you just go, yeah, switch, switch is it fine, make sure everything's okay. Then you delete the old one. Wonderful. Took me best part of you know three, four hours to actually go through the whole process and get it done. And then the second one, it doesn't matter if it has two minutes of down. downtime so no let's just up but upgrade the instance in place and both were totally appropriate um for the for the application

Speaker 2: okay had like two minutes of downtime on the on the the other one. But the the the first service couldn't take that two minutes of downtime. So you know the difference between something which took me basically less than an hour and took me all morning is that difference in caliber and what's nice about RDS, it's a very serious service. It has all the options in the world. And it's you can anywhere on that spectrum you can be. You if that's what a you know those are the kind of checkboxes I'm looking for in manage service. Yeah, if it's if you're just spinning me up a Docker instance, well I can do that myself.

Speaker 1: Yeah. And yeah, I I just think if it's anything serious, I want someone else to manage it. some capacity unless it's a toy project. People people disagree with that, but I just like what's the cost of messing it up? Um is what I think.

Speaker 2: It's the backups. It's the backups. It's the restores. It's the do you know what this went down and there's there it was an hour ago and now I can put it back. That is, you know, you've got to be a very serious um Postgres admin to be able to do point in time replication yourself, right? Restoration.

Speaker 1: Well not to get too gossipy, but Vercel had a booth at Europython. And you know they're they're sponsoring EuroPython. Python, they're you know they're they're killing it and they've historically been known as front end next. js deployment. So you you'd have a Django backend hosted on let's say Heroku, though you wouldn't use them anymore, and then front end Vercell now has the option of full stack, so just put it all in there and you can do all the branching and all the stuff that they're happy about. The one thing they don't have is a managed database. And I sort of pushed them on that I was like well it would be nice if you had you know render has this railway has this Heroku has this you know we that's how we got into this discussion of what does manage mean. A lot of the team especially the team that was there at the conference came from from edge db which and moved over to Vercel and so they were really doing this. So they knew oh no

Speaker 1: we have no interest in

Speaker 2: getting into the

Speaker 1: I mean databases you know you give a not a response if someone's like doing databases. Like

Speaker 2: scary.

Speaker 1: Exactly. All right. Okay. that you like about Django. And it's the heavy hitters. Models, which is sort of our ORM by proxy, admin auth.

Speaker 2: Yeah.

Speaker 1: There's a long tail. I mean, you know, I think most people if push to shove would say say the ORM or the admin, that has to be in the top three, five for sure.

Speaker 2: Um

Speaker 1: you know it's still, you know, fast API doesn't Have an ORM, it doesn't have admin, you know, like we can attest, it's not a trivial thing to just spin up. Um So that's good. Stability. Starting projects, people are still. This is actually interesting to me. So 75% said they use the start project command. I kind of thought more people would maybe just go let AI take the wheel. But it you know, based on the responses, people are starting manually and then adding AI in afterwards. They're not just green. field, you know, command line, build me this app.

Speaker 2: But here's my question, right? So why would you ever have a a um A random token generator do something which you already have a deterministic tool for. Right? If you haven't got a deterministic tool to build something, then asking you know the Clanker to come up with something, that's brilliant. But if you've got a deterministic tool, what benefit at all is there in having the LLM do it

Speaker 1: Yeah. Well here we get to you know there's things like you know with tooling like rough is super super popular at 43%. So you have a deterministic tool that will walk right through or you can toss it it into your LLM. You know, like I do think there's sort of this pushback of like, wait, like we can already do these things. We can already check types. We can already check linting. You know, we don't need to not just pay the cost, wait for it, but it's non-deterministic. You know, it's like it's really, really good, but it's not a hundred percent, you know.

Speaker 2: But I mean surely you have the the the the the agent use these talks you say look when creating a project use start project use this template uh and when linting use rough or use so what i thought was interesting with the rough there was rough was at 43

Speaker 1: Yeah, I mean look, r I use Ruff. Ruff is great. It's not just the speed. incorporating things you know black is you know rough sort of black is still has usage but like rough is kind of one tool to do it all um you know so Ven versus UV your favorite topic You know, Venva's still for managing virtual environments, 63%. UV is 43 %. So UV is definitely growing. Um we do have to, you know, we will see They they you know they're still that team is still putting out updates. They're now working at open API, so you would assume that's not gonna be their main focus. Um but I don't, you know I don't want to detract from the amazing work that they did for the community.

Speaker 1: And, you know, but I don't think we don't want to give up everything in favor of these rough builds

Speaker 2: well i'm i'm uh i'm you know just as a business risk perspective i'm not gonna put my faith in a um vc bank

Speaker 1: It's not VC. Well, I guess the one VC back.

Speaker 2: But the like the the point being that um as nice as the individuals in the project are, you know, Charlie Marshall had his very nice person don't know him Karl Mayette he's a you know former former Django alumni you know uh these are lovely wonderful people but the dull hand of economic determinism owns their project. And so just from a personal perspective or a and a business risk perspective, I'm not gonna um tie myself to their mast.

Speaker 1: Yeah, it's not the hardest thing to swap out. though. You know, I think that's

Speaker 2: you're absolutely right, but it's not also not the hardest it's not the you know, what does it bring? Like so VM and PIP, you know, perfect. Use the community tools that you know, this this the stable, long right long lasting um open option.

Speaker 1: I do think not to you know not not to just be like a fanboy for UV. I do think the pi, you know, it does more than than just uh virtual environments. You know, the Python package management. Okay, there's a deep discussion around how they do that, but it does make it easier, especially for newcomers. That is a real advancement. But all right,

Speaker 2: no, but the one the one um thing about UV that I like is the Python installation map management. So I actually created a PSA um in CLI tool too that I used that does the same thing, but in Python.

Speaker 1: I mean it's brilliant and it's faster because they have their own versions and you know Py It it's it's definitely yeah. All right, let's let's let's blast through. So caching, Redis is still king, fifty-three percent, no surprises there. It will be, you know, we had um, you know, Django Tab. Like maybe there's some you know Redis is this Yeah, I don't know. What do you think?

Speaker 2: I th yeah, I think the only reason not to use Redis is if you don't need it. Um and You can cache in the ORM and likely that's fast enough. So if you say you're running po you've got Postgres, if caching in Postgres is you know, good enough for you. Just use that and that's one less thing in your stack to be to be run. Because you know, if you as soon as you spin up Reddit, you've got one more service, one more thing. Yeah, one more you know chunk of RAM being used, etc. If you if you exhaust caching in the DB and you're like, do you know what I need something faster? Okay, Redis is there for you and you know it seems like the the option memcached uh doesn't look like it's gonna end up being compatible with uh free threaded Python so it's a little bit it's like

Speaker 2: oh okay is that is that ever gonna catch up there so I think Redis is probably the the the go-to in in memory choice. There is another one. What was it called? Ah so no. I'll have to look it up, but it was another um cache that was um claimed to be faster and used um in process and whatnot. But you know, it didn't show up in the survey results. So

Speaker 1: maybe what maybe it maybe it wasn't was it I don't know we should check if it was asked. All right, moving on. Types. So this was kind of interesting. So big percentage of people claim they're using them. No clear tool there's so all these type checkers this is something the Python team is working a lot on you know what's our default we want to support all of them but to your point you said before we started recording it seems like it's basically whatever's built into the IDE.

Speaker 2: Yeah, well that was one of the questions. It's like one of the answers was the top answer of what type checker we're using is the one the IDE or the tool provides so it's like you know it it whatever it is that VS Code and PyCharm turn on that's what people are using for their type checking which is fine

Speaker 1: yeah I yes for for the end user it doesn't really matter Um testing. A lot of people said they were testing, which is great. So

Speaker 2: for CI, yeah, for CI and C D.

Speaker 1: So it's easier to do CI and

Speaker 2: Well no it's not concerns. It's like I think the one thing now that is stopping um a mass flight from GitHub is the um GitHub Actions. I think they're the only people offering um free, essentially free um CI that kind of works. And I think as soon as A solution appears. As soon as it's like, oh, we could do our CI that way, I think we will see a big tidal wave out because of But where, right? I mean

Speaker 1: Codeberg is making a big stand on non-AI.

Speaker 2: Yeah, but people can you can spin up a four GO, you can s you can And like it's not actually hard to host your own GitHub um bare repos and whatnot. It's

Speaker 1: but it's hard and it's hard enough, right? I mean that's the point. As long as it's free and it works pretty well it's just like do I wanna have to fiddle with something else like no

Speaker 2: no i i entirely entirely but like i know i i don't know if they still have it but uh jet brains did have a a a Yeah, Team City hosting. Yeah, Team City um solution. I think there are plenty of them out there. And but it's what's for me what keeps the critical mass. What ki what's the inertia that stops people moving oh I'll just we'll move the company over to this hosted version. We'll we'll host our own one in the office for that. What stops that being the the the solution? I think GitHub Actions is the answer. just a sort of conjecture about the the the the state of the

Speaker 1: I mean I think it's a brilliant business move. I don't know that you know the costs and everything else but look if something free and works. Um you know.

Speaker 2: Yeah, yeah. No, it look, it's great. We've we've loved you know, we've had it for years. It's just interesting that's the big one and we'll see. You know, maybe I'm wrong. Maybe, you know, compared to a peer and people stick with GitHub but I can I could quite easily see there being a kind of cascade effect as as soon as as soon as that one linchpin breaks, yeah

Speaker 1: people go, oh

Speaker 2: do you know what let's jump ship.

Speaker 1: There needs to be a business model, you know, related to it, right? Because no one's gonna do a startup to compete, you know, like

Speaker 2: who's gonna

Speaker 1: yeah. Anyways, but yes, I mean

Speaker 2: the reason what the reason why GitHub got bought out, right, was is cause they couldn't keep going. That's why they needed somebody like Microsoft to come and take them under their wing and say, yeah, we'll keep funding you forever, basically.

Speaker 1: Well, and you know, this is this is public, you know, with uh The amount of repos generated by AI, you know, the just the cost to to Microsoft of running GitHub are exploding. You know, you could also say they're training data for models is growing. Yeah, I don't know. It's a hard hard to say. All right. So let's let's wrap this up. What I I 'll give my quick take and then you can give the deep insights. I think you know Jable Django remains a stable core. There's a lot of movement around tooling both in the Python world and AI. But Django, I think, is well placed and people seem to be, you know, they're using the latest versions, they're using mostly the things I think you and I would recommend.

Speaker 1: to people. And the last thing is we have as ever this communication problem. You know, what percentage of people know about the new features repo? You know, how do people find their things? You know, You've cited 25% said nothing. You know, um, I do want to shout out the Django Board is doing a lot of work to post more regularly on the the blog. And And there were community booths at PyCon US and EuroPython staffed by lovely Django members, you know, doing it for free. Jeff Triplett, our president, has mentioned they're they're doing a search for an executive director. He's managed to find funding for that. But it's a little bit of, you know, we can complain about it, but in terms of what's going to happen, we're we're we're waiting on

Speaker 1: more people power.

Speaker 2: Yeah. Oh I think too well.

Speaker 1: What what do you think? No we we we do great. I mean look we do great. Like I if we saw that people were like on old versions and just Totally checked out. What we see is people are like, yeah, Django 's a core tool and I fiddle around the edges, but if you know what it does for you, you're like, why would I use something else?

Speaker 2: Yeah, yeah. And I, you know, I was when I spoke to Michael Kennedy uh, you know, a little while ago, I meant we um the the COVID pandem pandemic came up and you know It was something that struck me that um it really hit did hit the the community hard. And for a few years after this it's taken us a long well, it's taken us a long time to recover. But I look around at the community now and I think, yeah, it really is. Going strongly. It's it's in a good place, and and that's lovely to see. Um, and I think technically we're in a a wonderful position. I'm really, really excited about uh free threading company

Speaker 1: Django and the med, there'll be some discussions around

Speaker 2: Well Django and the Med, I've got a secret project to uh work on async cursors. for the uh ORM. So we'll see if we get that. But yeah, there's also a a list of projects that I've that um to help um boost the free threading readiness of Django. Um there are a few cases where um we do things that start up to populate registries and things like that. Well those need to be done before you enable multiple threads, right? Otherwise they there could be race concerns. conditions and whatnot. So there are there are the test suite passes with uh free threading, but there may be cases where there are races that we haven't bolted, you know, we haven't eliminated yet so we can't really say oh yeah just go and fire it off but over the next few releases we should see those issues ironed out and then I think Django's in a really exciting place.

Speaker 2: Um you know we talked about serialization and the API story that's coming forward. I think, you know, we just need to see how these AI tools roll out. I think we're still in the, you know, the early days. And I'd I'd really want us to be in a position where the economics side of it is is settled so we can see actually what's the realistic cost that people would expect to face because then I think we could answer questions about well okay how much are we going to use these tools. You know, if they are more expensive than a junior developer, well I'd just rather have a junior developer. But if they're obviously much cheaper, then I would rather not

Speaker 1: Yeah and I I guess the last thing I would say is the The plight of the junior developer is real. Um, it is very hard to get hired as a junior. I've had many, many people at consultancies at big companies just say, We have no juniors. And everyone can say this is a problem coming down the line, but um, you know, if if you're a manager and you're used to just dealing with pull requests that you def for defined scopes, well, AI can do a version of it and it's cheaper than a junior dev who will get trained up and leave in two years. I mean to give one take on it. So

Speaker 2: yeah. I mean currently the until yeah no

Speaker 1: currently. Currently yeah.

Speaker 2: Un until we see the subsidies around pricing going away. So I you know, if you get a subscription and you go to use it, it's like well you've used, you know, eight times your subscription value in the last hour. It's like hang on.

Speaker 1: Well, and I I will say something. Negative about cursor, they just uh hid ha like the pricing of tokens so you can't see the spend anymore because you know it's it's a lever you can pull and

Speaker 2: Yeah, but the the the the the the example that that we saw came through um recently was um github copilot you know microsoft got so many things called copilot, you don't know what's what.

Speaker 1: Everything everything AI is copilot for them, yeah.

Speaker 2: But right. But they went from a fixed cost to token billing and people were getting, you know thousands and thousands of dollar bills at the end of that month and we're shocked because oh we've built that we built these workflows around using Copilot at a fixed cost and now suddenly it's a total

Speaker 1: Yeah. Well I gotta put on my company hat. You know, JetBrains made that move in the fall because they saw that coming and said, look, we're we as a company can't subsidize this. It's going that way. There was a little pushback, but people People got on board. I mean look, the challenge is also jet, you know, anyone building around these models, they change too fast. So so JetBrains is doing things about like we have all this great static analysis that we do. Can we separate the intelligence of the IDEs into a headless, um, you know, something headless and then feed that into the models? And can we be more efficient and better? And yes, we can, but We'll do it for one model and then the next model three months later completely changes that. So it's it's just building on quicksand and yeah, until it stays

Speaker 1: stabilizes out it's very hard to

Speaker 2: Okay so let me bring this back to to Django right we've got this idea about using boring tech and what's one of the notions in that essay is um about innovation tokens. Well what is an innovation token? You spend it on an unknown technology. Well back in the day it would have been using Mongo or using CouchDB instead of, you know a a relational database. Well, these days it might be well building or building with all this new AI tooling that we don't know what's going. Well there's your innovation token being spent because those things are changing all the time. Well, what's your your solid known foundation around which you can experiment with these things? Well it's Jang.

Speaker 1: Yeah, it's Python. You know, look, Python. For all the internal stuff, Python is growing and relatively stable and in a great place compared to other languages. Okay, good. All right. We we went on. Uh do check out the links. Links, the survey will be live, the blog post will be live. Um Give us feedback. We're gonna do the survey again next year and um hopefully not ask all AI questions, but ask better questions to un to tease out what is actual usage in the community and what

Speaker 2: it would be nice to dig in dig in and find what's actually going on there that would be nice to find out. Anyway.

Speaker 1: All right. Well thanks everyone. So DjangoChat. com, we will be back in the fall, September, with our regularly scheduled programming. But this was a special episode. Thanks for listening. We'll see you next time. Bye-bye.

Speaker 2: Bye-bye.