status-desktop VS mypy

In the meantime, desktop already exists but it's just at the finish line w.r.t. good enough feature set and performance to launch broadly. Go check it out at https://github.com/status-im/status-desktop. This recent tweet also highlights some of the massive performance improvements the desktop team is focused on (which will also immediately be available to the mobile app): https://twitter.com/ethstatus/status/1662857323889524739

The application consists of the combined efforts of the Status organisation and community contributors, you can follow our development at github.com/status-im/ — you're welcome to contribute as well! If you're running into any bugs, we'd love it if you could file an issue in our mobile or desktop repositories.

For those looking for a no-censorship-ever-of-any-kind alternative, consider Status:

https://status.im/get/

If you don't need or want a crypto wallet or dapp browser, then simply don't use those parts of the app.

Relevant specs:

https://specs.status.im/

https://rfc.vac.dev/

Relevant repos:

https://github.com/status-im/status-react

https://github.com/status-im/status-desktop

There are trade-offs, for sure: since there's (deliberately) no integration with contacts lists (address books) of the OS or other apps, your social circle probably isn't using the app already, or in any case isn't discoverable.

The public chats facility has turned out to be too spam-prone for "well known" / advertised chats, e.g. #status. However, if you create a public chat that has some unguessable component (e.g. #myfriends-a9e72ab5) and you share it with friends (even lots) in a reasonably private context, then the chances of it being spammed are quite low. Note that public chats, while "public", are still E2EE, using the chat's name as the basis for a symmetric key.

1-to-1 and private group chats are highly secure; the latter have a max size, and depending on their size and your device, sending messages can be a little slow.

Creating a robust alternative to the existing public chats facility has involved a lot of work: the forthcoming Communities features provides a discord-like facility whereby founders/admins of communities can take advantage of various mechanisms for moderation and governing membership. The Communities feature can already be enabled in advanced preferences of both mobile and desktop apps, but note it's a WIP.

The moderation mechanisms for communities don't undermine the no-censorship principle of Status because:

(1) Any user can create a community.

(2) A community's rules are managed by those with a stake in the community, there's no override by Status-the-org nor anyone else.

(3) The underlying nodes of the network form a decentralized p2p network, i.e. there's no central actor/authority that controls the flow of messages.

Re: (3), running a Status node should be easy and incentivized.

The "incentivized" aspect is a challenging problem and not solved yet. Long story short, engineering an incentivized decentralized messaging network (not a blockchain!) is harder than incentivizing a blockchain network.

That being said, the "easy" aspect isn't too difficult to solve, sneak peek:

https://github.com/status-im/status-node

Finally, with pertinent laws and regulations in flux across the globe, there could come a day when binaries aren't readily available (from app stores, GitHub, etc.), but thankfully there's always `git clone` and `make`.

Disclosure: I'm a core contributor at Status.

My only big issue is that it does talk to googleusercontent.com. Not sure how that can fit with privacy. Heres the github issue.

Current numbers re: adoption were discussed in Status' most recent Town Hall: https://www.youtube.com/watch?v=98wsQe6hHHs&t=365s

As for dev support: Status has teams of full-time devs working on various projects related to the mobile[1] and desktop[2] (beta) apps, as well projects that are related to the larger Ethereum ecosystem, e.g. nimbus-eth2[3]. Our teams aren't particularly large, but are working steadily to squash bugs and add/improve features. We also have teams dedicated to UX and design.

[1] https://github.com/status-im/status-react

[2] https://github.com/status-im/status-desktop

[3] https://github.com/status-im/nimbus-eth2

It's got type annotations and mypy has a discussion about it here as well: https://github.com/python/mypy/issues/1282

There is already an AOT compiler for Python: Nuitka[0]. But I don't think it's much faster.

And then there is mypyc[1] which uses mypy's static type annotations but is only slightly faster.

And various other compilers like Numba and Cython that work with specialized dialects of Python to achieve better results, but then it's not quite Python anymore.

[0] https://nuitka.net/

[1] https://github.com/python/mypy/tree/master/mypyc

In Python there is MyPy that can help with this. https://www.mypy-lang.org/

It's funny you should say this.

Reading this article prompted me to future-proof a program I maintain for fun that deals with time; it had one use of utcnow, which I fixed.

And then I tripped over a runtime type problem in an unrelated area of the code, despite the code being green under "mypy --strict". (and "100% coverage" from tests, except this particular exception only occured in a "# pragma: no-cover" codepath so it wasn't actually covered)

It turns out that because of some core decisions about how datetime objects work, `datetime.date.today() < datetime.datetime.now()` type-checks but gives a TypeError at runtime. Oops. (cause discussed at length in https://github.com/python/mypy/issues/9015 but without action for 3 years)

One solution is apparently to use `datetype` for type annotations (while continuing to use `datetime` objects at runtime): https://github.com/glyph/DateType

PEP 695 is great. I've been using mypy every day at work in last couple years or so with very strict parameters (no any type etc) and I have experience writing real life programs with Rust, Agda, and some Haskell before, so I'm familiar with strict type systems. I'm sure many will disagree with me but these are my very honest opinions as a professional who uses Python types every day:

* Some types are better than no types. I love Python types, and I consider them required. Even if they're not type-checked they're better than no types. If they're type-checked it's even better. If things are typed properly (no any etc) and type-checked that's even better. And so on...

* Having said this, Python's type system as checked by mypy feels like a toy type system. It's very easy to fool it, and you need to be careful so that type-checking actually fails badly formed programs.

* The biggest issue I face are exceptions. Community discussed this many times [1] [2] and the overall consensus is to not check exceptions. I personally disagree as if you have a Python program that's meticulously typed and type-checked exceptions still cause bad states and since Python code uses exceptions liberally, it's pretty easy to accidentally go to a bad state. E.g. in the linked github issue JukkaL (developer) claims checking things like "KeyError" will create too many false positives, I strongly disagree. If a function can realistically raise a "KeyError" the program should be properly written to accept this at some level otherwise something that returns type T but 0.01% of the time raises "KeyError" should actually be typed "Raises[T, KeyError]".

* PEP 695 will help because typing things particularly is very helpful. Often you want to pass bunch of Ts around but since this is impractical some devs resort to passing "dict[str, Any]"s around and thus things type-check but you still get "KeyError" left and right. It's better to have "SomeStructure[T]" types with "T" as your custom data type (whether dataclass, or pydantic, or traditional class) so that type system has more opportunities to reject bad programs.

* Overall, I'm personally very optimistic about the future of types in Python!

[1] https://github.com/python/mypy/issues/1773

# is fixed: https://github.com/python/mypy/issues/12987.

You probably already know but you can add type hints and then check for consistency with https://github.com/python/mypy in python.

Modern Python with things like https://learnpython.com/blog/python-match-case-statement/ + mypy + Ruff for linting https://github.com/astral-sh/ruff can get pretty good results.

I found typed dataclasses (https://docs.python.org/3/library/dataclasses.html) in python using mypy to give me really high confidence when building data representations.