Transcript: Django Developers Survey 2026

I'm Will Vincent with Carlton Gibson.

Hey, Carlton.

Hello, Will.

That's crazy.

We normally have it all.

I was trying I'm trying to 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 highlights because it's worth saying this is the only objective measure we have of the Django community.

Maybe you're on the steering council.

Like speak to how important is the survey?

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 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 Redis cache?

And which one was it?

And you you remember 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 who had the Redis 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.

Um that's just one example.

MongoDB had uh official backend 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 a day.

There were 3,500 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.

Um 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 but also

So that was like one of the sections higher than the US.

And I I would have liked to see the EU as one thing.

Yeah.

I say that because for better or for worse, I've had a heavy hand on it over the years.

Um yes, we'll fix that.

You know, because 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.

But uh yeah.

All right, so let's dive in.

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 downloads, which who knows how accurate those are.

There's efforts around that, but we're really flying blind in terms of where, who, what.

Um, so this is it.

This is a good thing.

Yeah, no, I

Historically, there was a discussion about adding telemetry to Django.

Of course, nobody wants to do that.

And then in the current climate, I don't even, you know, we wouldn't anyone go anywhere near that at the moment.

So, you know.

We other than reaching out and saying, Come on, fill in the survey.

But what can we do?

I don't know.

Anyway, let's get this guy.

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.

Back in the day, it was, oh, I'm still running 1.3, I'm still running 1.5, I'm still running 1.7.

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 this the stability guarantees and the deprecation policy, all of that has mean meant that 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 to see.

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.

And it 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 yeah.

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.

Yeah.

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.

Uh, well, 6.1's just popped out, but the latest release as the survey was taken, we've got Django tasks, we've got template partials merchant.

You know, these are big, these are big changes, right?

So, you know, we battle I think we balance it really well.

You know, what do you think?

Yeah, yeah,

Let's just pat ourselves on the back.

So databases.

Um, Postgres is still dominant, SQLite, very popular.

I just 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, um, 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 have a reason to use something else.

Yeah, yeah, yeah.

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 single package where you just uh you know pip install your your I can't remember the name of the package exactly, install that, and then it configures your your SQLite exactly how it needs to be.

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, there's it's I still think it's a spicy choice, personally.

Yeah, yeah, yeah.

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 yeah, it's still being used, it's still popular.

Um I know some people are working on next generation serializers and updates.

Yeah, yeah, yeah.

Like DRF's not going anywhere.

It's nice and stable, it's nice and doing its thing.

As you said, like 70 odd percent using DRF still.

Like, that's phenomenal.

And you know, for the um for the serializing, the Pydantic, are you how are you using?

Are you using forms?

Are you using serializers validation?

Are you using Pydantic one option?

Well, 20% were using Pydantic.

Well, that's almost the same as 17% who were using Django Ninja.

So there's like, you know, if you're using one, you're using the other.

But most people just aren't.

What I thought was interesting in these figures, well, API first, well, yeah, how 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 single page application, the other half were API owned.

But then half of people are building server-server server-rendered apps sending out templates.

There's a bifurcation, and really it's swung back 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.

I think it's

So in this economy, you know, it's not server interest rates anymore.

We we can't necessarily afford a team with, you know, two front-end developers, two back-end developers, you know, and all the all the um coordination tax between them.

I think, you know, going back to the the old 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 I was amazed when I saw the numbers and I saw, you know, basically HTMX and React neck and neck.

You know, I think React had a couple of points in front, but like they're basically third each.

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 years ago, I mean, Carson Gross, the creator of HTMX, gave a talk at DjangoCon US recently, keynote.

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?

Right, okay.

I mean, a lot there was one thing further, like much further down the survey, which I thought was lovely, was that 25% of respondents said it was like, how do you keep up with Django news?

Do you read the blog, do you listen to the podcast, do 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, and they're not engaging with the the news around what's new in Django in any way whatsoever.

Like that it's just like, well, Django just appears like Python, like water, you know.

Yeah.

Um but that yeah, so that's a good thing in the abstract, but it's an important to remember, like it can be insular, you know, uh, but you know, we can always communicate better and put it in.

There's a question.

Bootstrap's still number one after, you know, I mean still there, number one bootstrap.

Then tailwind close behind, and then planes, plains, plain CSS, just only two points back, right?

So there's sort of split bootstrap, tailwind, or you know, vanilla basically.

And then there was others, the long tail of other options.

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 word 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 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?

Use but you can spend a career on CSS alone.

But yeah, if you're if you're a a jobbing jang or then to use a framework give you to give you some structure around you know your style that prices

So yeah, so I th I think if anything, people 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 Well,

So 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.

Um whereas if you're just using vanilla 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 what.

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 yeah, I don't know.

Um yeah, it might be slightly faster to render, um, but not significantly.

The way it's faster is with the parsing.

But um for many versions now um we've had um the template cache in place.

Um it gets rid of the parsing step.

And so the the speed difference is essentially negligible these days.

Um 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.

If you and some people like that, but obviously not enough to drive the community as a whole away from the DTL.

But um that's something I'm curious about.

So I I suspect that might happen because look, I know we're Django pills here, but like Fast API is big, the community's growing.

Um I hope there's more crossovers because it's pretty different lanes at the moment.

It doesn't really matter.

Uh you're just gonna go with whatever's given to the case.

Um well to to to abstract from tools, let's talk about async.

Um so I'll team 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 I'm still I am still on the coal face 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.

Um and channels is great, channels is brilliant, but the the reason to keep using it really is um WebSocket support because um Djang uh Django's because of the nature of it, Django's not gonna probably have WebSocket support in core itself.

So why would you keep keep with channels?

Assuming assuming everything is rosy in the in the land of um Django core's async story, why would you use channels where 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 views.

I think that's um uh 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 TalkPython about this, 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 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 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 gonna come to fruition as free threading rolls out.

We're gonna 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.

And what you what you need is a the free threading build of Python to enable those threads to run separately and you get truly parallel work.

And I think we're gonna see a lot of performance wins for Django over the next, you know, 3.15's coming, 3.16, 3.17, I think over the next two, three years, it's gonna be a very happy time for us in Django land.

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, followed by YouTube.

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.

Like there are people putting out stuff but you know for myself there's less of a if it's just going to get scooped up and put into training data and there's no link, it's harder to justify the time to to create these things.

I think there's a there's clearly there's new technology clearly it's super leak 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 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 you know was AI usage.

And so AI is clearly a thing.

50% of people are are are using it.

it was 50%

So 50% 30% said they're using chat 30% said they m they're using um code generation so it's a bit like you know what does it mean?

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

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 multi 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.

Though some people are doing that you know friends we have already

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 floated away and the long term look you will expect to pay this for that has become kind of clear.

And I think at that point we'll be able to judge much more effectively 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 you're an agent I don't know that many people are going to be able to afford that.

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 people like Peter Grandstaff um is running he's got a very powerful local computer he's running local models um you can use Olam or LM Studio to use newer models like Kimi and the cloud I hope the community can be can talk more about what what we're using because yeah like are you using it yeah what does that mean?

We still haven't teased that out I mean I'm personally and my colleague Paul Everett is very excited about what Apple's doing with MLX which is um modified memory and the M5 chips and M7 chips basically because if you're 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 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 ChatGBT it's like how many times do you want me to try?

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.

Go.

Uh it 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

It's like in most countries you know um you'll see the different takes on the same news you know like what the the the left paper will say one thing the right paper will say another but in Spain it's like two different 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 of there's well we're gonna have what to believe I know anyway anyway one thing from the whole 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.

I mean it's it's the you know and I can 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 IDEs so cursor is still around that they're being acquired Windsurf got consumed you know it's really just un 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 Jupiter you can still use it but just with the cells and everything it's not quite as 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 think you know if you could build it yourself you can build manually you can build it faster with AI but you just you gotta be know how to do it manually um and otherwise you'll just get so far afield quickly.

Anyway let's get back to the thing to the second moment okay go on

You know, the as bog standard as bog standard could be.

And then for the database, there was a nice split.

33% self-managing their database and 30% managed.

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, managed database, or are you are you running it yourself.

I I thought that was lovely.

That the whole section.

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 compliance and all the rest, you know, that type of managed is a whole separate thing.

And so

So over the summer, what have I been?

Well, I've done a bit of maintenance.

And uh 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 wrote I I did their own the lovely green blue thing.

And it's just delightful.

You know, it it spins up the the blue, it's uh you know, it sets up the logical replication, does all this, and then you could check it all against your application, and you just go, yeah, switch, switch is it fine, make sure everything's okay.

Then you just 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 downtime.

So no, let's just upgrade the instance in place.

And both were totally appropriate for the application had like two minutes of downtime on the on the the other one.

But the the first service couldn't take that two minutes of downtime.

So yeah, yeah, 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 you've that's what a you know, those are the kind of checkboxes I'm looking for in a managed service.

Yeah, if it's if you're just spinning me up a Docker instance, well, I can do that myself.

Uh people people disagree with that, but I just what's the cost of messing it up?

Um, is what I think.

But anyway,

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.

And you know, they're they're sponsoring EuroPython, 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 there.

Uh Vercel 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 EdgeDB, which and moved over to Vercell.

And so they were really doing this.

So they knew, oh no, we have no interest in the data.

Yeah, yeah, yeah.

They've lived that thing.

Um, scary.

Scary, exactly.

All right, okay.

Um, what one other thing that came out is um, you know, we asked the question of the three most important bits that you like about Django.

And it's the heavy hitters, models, which is sort of our ORM by proxy, admin auth.

Yeah.

There's a long tail.

All the rest, yeah.

That has to be in the top three, five for sure.

Yeah.

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.

Um, starting projects, people are still.

This is actually interesting to me.

Uh so 75% said they use the start project command.

Um, 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 Greenfield, you know, command line, build me this app.

So why would you ever have a a um a random token generator um 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?

Yeah.

So you have a deterministic tool that will walk right through, or you can toss 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 100%, you know.

You say, look, when creating a project, you 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 a 43% versus 17 for flake now.

So yeah, you know, I think the ecosystem is moving across.

Rough is great.

It's not just the speed, they they're 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, Venv is 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.

And, you know, but I don't think we don't want to give up everything in favor of these Rust built.

But the like the the point being that um as nice as the individuals in the project are, you know, Charlie Marshall, I've heard he's a very nice person, don't know him.

Karl Mayak, 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 uh and a business risk perspective, I'm not gonna um tie myself to their mast.

I think that's part of the.

Like so VM and PIP, you know, perfect.

Use the community tools.

You know, this this the stable, long like long-lasting, um open option.

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.

Um, so the w

So I actually created a uh a PSA um in CLI tool too that I used that does the same thing, but in Python.

All right, let's let's let's blast through.

So caching, Redis is still king, 53%.

No surprises there.

It will be, you know, we had um, you know, Django tasks, like maybe there's some, you know, Redis is this yeah, I don't know.

What do you think?

Um and you can cache in the ORM and likely that's fast enough.

So if you say you're running 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 Redis, 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, yeah, it 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, 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.

Um there is another one uh what was it called uh 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 processing one uh ah but you know it didn't show up in the survey results so well

're using them uh no clear tool there's so all these type checkers this is something the PySharm 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 you know

So it's like you know if whatever it is that VS Code and PyChamp turn on, that's what people are using for their type check which is fine.

Testing a lot of people said they were testing which is great.

I know you have a point to make so 51% said 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 there's like oh we could do our CI that way I think we will see a big tidal wave out because of the degradation.

As long as it's free and it works pretty well it's just like do I want to have to fiddle with something else?

Like no.

We'll we'll host our own one in the office for that.

You know what stops that being the the the solution I think GitHub Actions is the answer.

That's just a sort of conjecture about the the the the state of the

I don't know that you know the costs and everything else but look if something free and works um you know

's jump ship.

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

You know you could also say their training data for models is growing.

Yeah it's a hard hard to say um all right so let's let's wrap this up what I I I'll give my quick take and then you can give the deep insights um I think you know jabel Django remains a stable core there's a lot of movement around tooling um 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

to people um 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 um you know you 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 um you know there were community booths uh at PyCon US and EuroPython staffed by lovely Django members, you know, doing it for free.

I guess you know uh 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 waiting on more people power.

Yeah.

'm really really excited about uh free threading coming through I I just think that's gonna be

es and things like that well those need to be done before you enable multiple threads right otherwise there could be race 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 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.

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 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?

Yeah 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.

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 do 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 I you know if you get a subscription and you go to usage it's like well you've used you know eight times your subscription value in the last hour it's like hang on.

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 changed too fast.

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 stabilizes out, it's very hard to okay.

Okay, we've got this idea about 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 Couch TB instead of you know a relational database.

Well, these days it might be well 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 solid known foundation around which you can experiment with these things?

Well, it's Jang.

Yeah, it's Python.

For all the internal stuff, Python is growing and relatively stable and in a great place compared to other languages.

Okay, good.

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.

That would be nice to find out.

Anyway.

All right.

Well, thanks everyone.

We will be back in the fall, September, with our regularly scheduled programming, but this was a special episode.

Uh, thanks for listening.

We'll see you next time.

Bye bye.

Bye bye.