chisel
mypy
chisel | mypy | |
---|---|---|
25 | 112 | |
3,717 | 17,569 | |
1.1% | 0.9% | |
9.7 | 9.7 | |
7 days ago | 2 days ago | |
Scala | Python | |
Apache License 2.0 | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
chisel
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Calyx: Intermediate Language for Hardware Accelerators
My first instinct was to ask "Does this play well with CIRCT?" And thankfully they answer that right away in the README.
I'm personally of the opinion that there is a LOT of room for improvement in the hardware design tooling space, but a combination of market consolidation, huge pressure to meet deadlines, and an existing functional pipeline of Verilog/VHDL talent is preventing changes.
That's not to say "Verilog/VHDL are bad", because clearly they've been good enough to support nearly all of the wonderful designs powering today's devices. But it is to say, "the startup scene for hardware will continue to look anemic compared to the SaaS scene until someone gives me all of the niceties I have for building SaaS tools in software."
A huge amount of ideas (and entire designs) start off as software sims, which enables kernel/compiler engineers to start building out support for new hardware before it's manufactured.
There is some interesting work going on at SiFive building hardware with Chisel[1], as well as some interesting work lead by a professor at William and Mary to improve simulations[2].
1: https://www.chisel-lang.org
2: https://github.com/sarchlab/akita
- Chisel: A Modern Hardware Design Language
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I may be creating an abomination
Inspired by Scala. Which can do a whole lot more, and worse. The currently biggest competitor to decades old hardware description languages is a Scala DSL.
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An addressable little explored language gap: HDL - Hardware Description Languages, any language used for electronic circuit design, description, and specs
Already mentioned Chisel: https://www.chisel-lang.org/
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Trying to learn and work with FPGAs
I'm also a hobbyist. There are a number of alternative HDLs out there, and as hobbyists we can deviate more from the mainstream of (System)Verilog and VHDL if we desire, though you'll still need to be able to read them. In the past I've done Verilog, but lately I've been using SpinalHDL and have been really enjoying it. Its close relative Chisel also makes appearances in the RISC-V space.
- Alternate HDL language and Physical Design/EDA tools?
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Learning VDHL after knowing Verilog
What are your thoughts on other HDLs like Chisel or BlueSpec when it comes to better type checking?
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Learning Verilog and FPGA
I started playing with FPGAs and HDLs a couple years ago with no hardware design background (I'm mostly a software architect/engineer) and in the end found that a "higher-level" HDL suited me better.
I chose Chisel (https://www.chisel-lang.org/) an HDL based on Scala (technically a Scala DSL) which can provide many facilities to hardware generation.
I'd highly advise looking into it although also knowing Verilog helps a lot.
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If you keep clicking "Give 15 seconds" on Lichess, eventually it overflows to a negative number and you win
But some go further and ask "what if when we add a soldering station on top of it?"
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What universities have good PhD programmes in digital design?
In recent years Chisel HDL, RISC V, and SiFive came out of their architecture group, to name a few.
mypy
- The GIL can now be disabled in Python's main branch
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Polars – A bird's eye view of Polars
It's got type annotations and mypy has a discussion about it here as well: https://github.com/python/mypy/issues/1282
- Static Typing for Python
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Python 3.13 Gets a JIT
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
- Introducing Flask-Muck: How To Build a Comprehensive Flask REST API in 5 Minutes
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WeveAllBeenThere
In Python there is MyPy that can help with this. https://www.mypy-lang.org/
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It's Time for a Change: Datetime.utcnow() Is Now Deprecated
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
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What's New in Python 3.12
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
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Mypy 1.6 Released
# is fixed: https://github.com/python/mypy/issues/12987.
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Ask HN: Why are all of the best back end web frameworks dynamically typed?
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.
What are some alternatives?
SpinalHDL - Scala based HDL
pyright - Static Type Checker for Python
myhdl - The MyHDL development repository
ruff - An extremely fast Python linter and code formatter, written in Rust.
amaranth - A modern hardware definition language and toolchain based on Python
pyre-check - Performant type-checking for python.
cocotb - cocotb, a coroutine based cosimulation library for writing VHDL and Verilog testbenches in Python
black - The uncompromising Python code formatter
skywater-pdk - Open source process design kit for usage with SkyWater Technology Foundry's 130nm node.
pytype - A static type analyzer for Python code
bsc - Bluespec Compiler (BSC)
pydantic - Data validation using Python type hints