Our great sponsors
gcc | Poetry | |
---|---|---|
81 | 377 | |
8,704 | 29,397 | |
1.9% | 2.3% | |
9.9 | 9.6 | |
1 day ago | 2 days ago | |
C | Python | |
GNU General Public License v3.0 only | MIT License |
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.
gcc
-
C++ Safety, in Context
> It's true, this was a CVE in Rust and not a CVE in C++, but only because C++ doesn't regard the issue as a problem at all. The problem definitely exists in C++, but it's not acknowledged as a problem, let alone fixed.
Can you find a link that substantiates your claim? You're throwing out some heavy accusations here that don't seem to match reality at all.
Case in point, this was fixed in both major C++ libraries:
https://github.com/gcc-mirror/gcc/commit/ebf6175464768983a2d...
https://github.com/llvm/llvm-project/commit/4f67a909902d8ab9...
So what C++ community refused to regard this as an issue and refused to fix it? Where is your supporting evidence for your claims?
- Std: Clamp generates less efficient assembly than std:min(max,std:max(min,v))
-
Converting the Kernel to C++
Somewhat related: In 2020 gcc bumped the requirement for bootstrapping to be a C++11 compiler [0]. Would have been fun to see the kernel finally adopt C++14 as the author suggested.
I don't think that Linus will allow this since he just commented that he will allow rust in drivers and major subsystems [1].
I do found it pretty funny that even Linus is also not writing any rust code, but is reading rust code.
I would have hoped see more answers or see something in here from actual kernel developers.
0: https://github.com/gcc-mirror/gcc/commit/5329b59a2e13dabbe20...
-
Understanding Objective-C by transpiling it to C++
> They’re saying that a lot of the restrictions makes things much harder than other languages. Hence the general problem rust has where a lot of trivial tasks in other languages are extremely challenging.
Like what? So far the discussion has revolved around rewriting a linked list, which people generally shouldn't ever need to do because it's included in the standard lib for most languages. And it's a decidedly nontrivial task to do as well as the standard lib when you don't sacrifice runtime overhead to be able to handwave object lifecycle management.
- C++: https://github.com/gcc-mirror/gcc/blob/master/libstdc%2B%2B-...
- Rust: https://doc.rust-lang.org/beta/src/alloc/collections/linked_...
> No need to get defensive, no one is arguing that rust doesn’t do a lot of things well.
That's literally what bsaul is arguing in another comment. :)
> You’re talking up getting a safe implementation in C, but what matters is “can I get the same level of safety with less complexity in any language”, and the answer is yes: Java and c# implementations of a thread safe linked list are trivial.
Less perceived complexity. In Java and C# you're delegating the responsibility of lifecycle management to garbage collectors. For small to medium scale web apps, the added complexity will be under the hood and you won't have to worry about it. For extreme use cases, the behavior and overhead of the garbage collector does became relevant.
If you factor in the code for the garbage collector that Java and C# depend on, the code complexity will tilt dramatically in favor of C++ or Rust.
However, it's going to be non-idiomatic to rewrite a garbage collector in Java or C# like it is to rewrite a linked list in Rust. If we consider the languages as they're actually used, rather than an academic scenario which mostly crops up when people expect the language to behave like C or Java, the comparison is a lot more favorable than you're framing it as.
> If I wanted I could do it in c++ though the complexity would be more than c# and Java it would be easier than rust.
You can certainly write a thread-safe linked list in C++, but then the enforcement of any assumptions you made about using it will be a manual burden on the user. This isn't just a design problem you can solve with more code - C++ is incapable of expressing the same restrictions as Rust, because doing so would break compatibility with C++ code and the language constructs needed to do so don't exist.
So it's somewhat apples and oranges here. Yes, you may have provided your team with a linked list, but it will either
-
Committing to Rust for Kernel Code
GCC is also written in C++, and has had C++ deps since 2013:
https://github.com/gcc-mirror/gcc/blob/master/gcc/c/c-parser...
- Spitbol 360: an implementation of SNOBOL4 for IBM 360 compatible computers
-
are most computer programming languages public domain, or do their creators get a say in what you do with them?
Compliers/Interpreters are also very commonly open source (here is the source code for a popular C compiler). That means you can even modify the compiler's code and change its behavior if you wanted to.
- Learn to write production quality STL like classes
-
Which compiler is conforming here?
according to this commit, the story here seems to be much more interessting than I initially anticipated.
-
My favorite C compiler flags during development
For a more detailed explanation, see [2]. (Also the inspiration for the above example,)
[1] https://en.m.wikipedia.org/wiki/Transitive_relation
[2] https://github.com/gcc-mirror/gcc/commit/50ddbd0282e06614b29...
Poetry
-
Understanding Dependencies in Programming
You can manage dependencies in Python with the package manager pip, which comes pre-installed with Python. Pip allows you to install and uninstall Python packages, and it uses a requirements.txt file to keep track of which packages your project depends on. However, pip does not have robust dependency resolution features or isolate dependencies for different projects; this is where tools like pipenv and poetry come in. These tools create a virtual environment for each project, separating the project's dependencies from the system-wide Python environment and other projects.
-
Implementing semantic image search with Amazon Titan and Supabase Vector
Poetry provides packaging and dependency management for Python. If you haven't already, install poetry via pip:
-
From Kotlin Scripting to Python
Poetry
-
How to Enhance Content with Semantify
The Semantify repository provides an example Astro.js project. Ensure you have poetry installed, then build the project from the root of the repository:
-
Uv: Python Packaging in Rust
Has anyone else been paying attention to how hilariously hard it is to package PyTorch in poetry?
-
Boring Python: dependency management (2022)
Based on this comment 5 days ago[0], it's working? I'm not sure didn't dig in too far but based on that comment it seems fair to say that it's not fully Poetry's fault because torch removed hashes (which poetry needs to be effective) for a while only recently adding it back in.
Not sure where I would stand if I fully investigated it tho.
[0] https://github.com/python-poetry/poetry/issues/6409#issuecom...
-
Fun with Avatars: Crafting the core engine | Part. 1
We will be running this project in Python 3.10 on Mac/Linux, and we will use Poetry to manage our dependencies. Later, we will bundle our app into a container using docker for deployment.
-
Python Packaging, One Year Later: A Look Back at 2023 in Python Packaging
Here are the two main packaging issues I run into, specifically when using Poetry:
1) Lack of support for building extension modules (as mentioned by the article). There is a workaround using an undocumented feature [0], which I've tried, but ultimately decided it was not the right approach. I still use Poetry, but build the extension as a separate step in CI, rather than kludging it into Poetry.
2) Lack of support for offline installs [1], e.g. being able to download the dependencies, copy them to another machine, and perform the install from the downloaded dependencies (similar to using "pip --no-index --find-links=."). Again, you can work around this (by using "poetry export --with-credentials" and "pip download" for fetching the dependencies, then firing up pypiserver [2] to run a local PyPI server on the offline machine), but ideally this would all be a first class feature of Poetry, similar to how it is in pip.
I don't have the capacity to create Pull Requests for addressing these issues with Poetry, and I'm very grateful for the maintainers and those who do contribute. Instead, on the linked issues I share my notes on the matter, in the hope that it may at least help others and potentially get us closer to a solution.
Regardless, I'm sticking with Poetry for now. Though to be fair, the only other Python packaging tools I've used extensively are Pipenv and pip/setuptools. It's time consuming to thoroughly try out these other packaging tools, and is generally lower priority than developing features/fixing bugs, so it's helpful to read about the author's experience with these other tools, such as PDM and Hatch.
[0] https://github.com/python-poetry/poetry/issues/2740
-
Introducing Flama for Robust Machine Learning APIs
We believe that poetry is currently the best tool for this purpose, besides of being the most popular one at the moment. This is why we will use poetry to manage the dependencies of our project throughout this series of posts. Poetry allows you to declare the libraries your project depends on, and it will manage (install/update) them for you. Poetry also allows you to package your project into a distributable format and publish it to a repository, such as PyPI. We strongly recommend you to learn more about this tool by reading the official documentation.
-
How do you resolve dependency conflicts?
I started using poetry. The problem is poetry will not install if there is dependency conflict and there is no way to ignore: github
What are some alternatives?
CMake - Mirror of CMake upstream repository
Pipenv - Python Development Workflow for Humans.
rtl8192eu-linux-driver - Drivers for the rtl8192eu chipset for wireless adapters (D-Link DWA-131 rev E1 included!)
PDM - A modern Python package and dependency manager supporting the latest PEP standards
llvm-project - The LLVM Project is a collection of modular and reusable compiler and toolchain technologies.
hatch - Modern, extensible Python project management
STL - MSVC's implementation of the C++ Standard Library.
pyenv - Simple Python version management
cobol-on-wheelchair - Micro web-framework for COBOL
pip-tools - A set of tools to keep your pinned Python dependencies fresh.
qemu
virtualenv - Virtual Python Environment builder