Was really excited to upgrade but the async safety check makes the ORM unusable in a Jupyter Notebook.
https://stackoverflow.com/questions/59119396/how-to-use-djan...
https://forum.djangoproject.com/t/is-there-a-way-to-disable-...
Django 3
41–50 of 196 posts
Re: Django 3
#42I have been using FastAPI for the last two months (which also is an ASGI server and makes full use of annotations and type hints with mypy) and the experience has been incredible. ( https://fastapi.tiangolo.com/ ) If Django can now also support annotations and async code I dream of an scenario where apis can be built using this two elements. Does anybody know a good resource to learn/catch up with this release?
I recommend the release notes for each version, starting with the one right after the last version you’ve used.
There’s a couple reasons:
1. you get a breakdown of all the new features, which only takes a few minutes to kind of quickly go through each version and decide which bits you care about
2. you get a list of backwards-incompatible changes, which resolves any upgrade regressions, as long as you’re not using internal APIs that have changed
Re: Django 3
#43Earlier quoted context omitted.
I mean, what kind of performance issues were you running into? You're not going to get maximum performance out of a python program, generally. But unless your python program is using 100% cpu that's not really an issue, and there are very few cases where I'm using python and it's CPU that's slowing down the program. Mostly it ends up being some kind of IO. If you're looking to do complicated mathematical operations,…
In my experience most people creating CRUD websites with Django will hit a CPU bottleneck.
IME database always bottlenecks first.
Re: Django 3
#44[deleted]
Re: Django 3
#45Does Python still have performance issues? That's always been my concern when considering its adoption.
Yes and no. The Python interpreter/bytecode-VM is not as fast as it could be, because only a few people work on it. PyPy is great, but not drop in. Lack of funding is the proximate cause, of course, but that's just masking the ultimate cause of lack of interest. Because people use Python as a glue, just like PHP, or Node. To do the heavy lifting you have many options. (Even in Python, you can just use Cython, use FFI to call out to anything with A C interface, like Rust, or C++, or C. Many Python packages do exactly that, wrap a battle tested old native lib.)
That said the Python VM is a well optimized beast, it's very dynamic, you can monkey patch anything and everything at runtime on-the-fly. This is of course what makes it hard to speed up, too many things to "check for overloadedness" when doing anything. A JIT could help, but that's a lot of work. (Hence why PyPy took a decade, and the whole Python C API compatibility problem is still there - PyPy can only JIT the Py parts.)
Anyway. With that much dynamic stuff and with the VM and the language already well tuned for concurrent memory safety its 'async' story is great and performant. (Like NodeJS'.)
So Python is great for orchestrating whatever you need to handle requests. And if you want to scale up, just spin up more instances. (Just like with Java, but you don't have to think much about the overhead garbage collection, because CPython uses simple reference counting.)
Finally, my concern with Python was the lack of static typing, which made any large project hard to manage. (And resulted in a lot of boilerplate tests and excessive defensive coding.) But mypy is great, and with that it's a joy to work in Python. (Just like TypeScript made the JS world exponentially much more saner.)
Re: Django 3
#46Re: Django 3
#47Re: Django 3
#48Earlier quoted context omitted.
I mean, what kind of performance issues were you running into? You're not going to get maximum performance out of a python program, generally. But unless your python program is using 100% cpu that's not really an issue, and there are very few cases where I'm using python and it's CPU that's slowing down the program. Mostly it ends up being some kind of IO. If you're looking to do complicated mathematical operations,…
In my experience most people creating CRUD websites with Django will hit a CPU bottleneck.
Your experience is very much unlike my own. Every project I’ve seen hit issues with the database (e.g. unindexed queries, changing data access patterns) first, followed by I/O (especially other services like S3, search, etc.), and RAM usage before CPU became a major factor.
It’s possible, of course, but I’ve usually seen it as a symptom of not having a good culture around monitoring and troubleshooting — e.g. I remember someone porting an entire site to Jinja2 alleging performance wins, and it’s true that template rendering got (IIRC) 10-15% faster but they’d missed that 99.999% of the total runtime was being taken up by unoptimized database access generating many thousands of queries.
Re: Django 3
#49Does Python still have performance issues? That's always been my concern when considering its adoption.
Yes. If you can afford the CPU power, by all means go with Python. Otherwise just don't. Instagram can afford it so it works fine for them. Reddit can't, so their site is always slow or down.
And you know it is becouse of python reddit is often slow or down? Or are you just blaming pythin without any actual data on the underlying reasons?
Re: Django 3
#50I have been using FastAPI for the last two months (which also is an ASGI server and makes full use of annotations and type hints with mypy) and the experience has been incredible. ( https://fastapi.tiangolo.com/ ) If Django can now also support annotations and async code I dream of an scenario where apis can be built using this two elements. Does anybody know a good resource to learn/catch up with this release?
How hard was the learning curve? What are the main benefits over Django?