tigerbeetle
PyOxidizer
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tigerbeetle | PyOxidizer | |
---|---|---|
44 | 28 | |
6,534 | 5,156 | |
45.5% | - | |
9.9 | 0.0 | |
7 days ago | 21 days ago | |
Zig | Rust | |
Apache License 2.0 | Mozilla Public License 2.0 |
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.
tigerbeetle
- Factor is faster than Zig
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The Raft Consensus Algorithm
Maelstrom [1], a workbench for learning distributed systems from the creator of Jepsen, includes a simple (model-checked) implementation of Raft and an excellent tutorial on implementing it.
Raft is a simple algorithm, but as others have noted, the original paper includes many correctness details often brushed over in toy implementations. Furthermore, the fallibility of real-world hardware (handling memory/disk corruption and grey failures), the requirements of real-world systems with tight latency SLAs, and a need for things like flexible quorum/dynamic cluster membership make implementing it for production a long and daunting task. The commit history of etcd and hashicorp/raft, likely the two most battle-tested open source implementations of raft that still surface correctness bugs on the regular tell you all you need to know.
The tigerbeetle team talks in detail about the real-world aspects of distributed systems on imperfect hardware/non-abstracted system models, and why they chose viewstamp replication, which predates Paxos but looks more like Raft.
[1]: https://github.com/jepsen-io/maelstrom/
[2]: https://github.com/tigerbeetle/tigerbeetle/blob/main/docs/DE...
- Fastest Branchless Binary Search
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CWE Top Most Dangerous Software Weaknesses
> There is no reason to use a memory unsafe language anymore, except legacy codebases, and that is also slowly but surely diminishing. I'm still yet to hear this amazingly compelling reason that you just need memory unsafe languages. In terms of cost/benefits analysis, memory unsafety is literally all costs.
Tell that to the authors of new memory unsafe languages (like Zig) and creators of new project in those languages (like https://tigerbeetle.com) :(
- Problems of C, and how Zig addresses them
- File for Divorce from LLVM
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Zap – fast back ends in Zig
Seeing this, and the use of zig for https://github.com/tigerbeetledb/tigerbeetle I wonder if zig might become a good tradeoff vs rust for servers if in long term it's more readable and maintainable and with a different approach to quality.
I would also be interested to hear the compile time, binary size and memory usage of those example apps.
Looks like the underlying facil.io library hasn't seen any commits since 2021, so that's a bit of a red flag. https://github.com/boazsegev/facil.io
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Significant examples of Zig software (June 2023)?
About three years ago, we had a thread called "Significant examples of Zig software?". Some time has passed, and there have been fairly large Zig code bases that have surfaced since, such as TigerBeetle (cc /u/eatonphil), or adoption at places like Uber.
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I think Zig is hard but worth it
This is basically what I've come to do in the Zig scripts I write at work.
It took a bit of getting used to when I joined but we agreed as a team to have all meaningful scripts written in Zig not bash (for one, bash doesn't work on Windows without WSL and we need to support Windows builds/testing/etc.).
It makes about as much sense as any other cross-platform scripting option once I got used to it!
Some examples:
Docs generation: https://github.com/tigerbeetledb/tigerbeetle/blob/main/src/c...
Integration testing sample code: https://github.com/tigerbeetledb/tigerbeetle/blob/main/src/c...
Running a command wrapped in a TigerBeetle server run: https://github.com/tigerbeetledb/tigerbeetle/blob/main/src/c...
PyOxidizer
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Show HN: Pywebview 5
Bundling Python isn't too bad if you find the right tools for it.
I really like https://github.com/indygreg/python-build-standalone and https://github.com/indygreg/PyOxidizer
A bundled, built standalone Python can be 16 to 32MB (including the full standard library, which you can strip down to just the bits you use to save size). Not tiny, but probably not worth switching programming languages over.
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Why do you enjoy systems programming languages?
But really, I would suggest thinking about what you want to build before "how" or "with which tool" - one of the signs of a person becoming a good engineer is having an array of tools at their disposal and being able to choose a correct tool for the correct task. Rust also excels in integrating with other languages - with JS via WebAssembly (a bit of self-promotion, for example), with Elixir via Rustler, with Python via PyO3 and PyOxidizer, etc. So you absolutely can start writing a frontend app with JS, or a distributed system with Elixir, or a data processing/ML app with Python and use Rust to speed up critical parts of those. Or, in reverse, you can start with Rust & add new capabilities to whatever you're building, that being a frontend, a resilient chat interface, or an ML model.
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List of Python compilers
Thank you, although this is not exactly on topic. I'd not heard of PyOxidizer, but it appears to have the same goal as PyInstaller, py2exe, and cx_Freeze -- as the PyOxidizer readme says, it produces
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Buck2, a large scale build tool written in Rust by Meta, is now available
Here is some example Github Action from PyOxidizer as a Kickstarter: https://github.com/indygreg/PyOxidizer/blob/main/.github/workflows/build-exe.yml
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Mitogen speedup (the actual value)
A starting point to try out binary modules by the way would be https://github.com/indygreg/PyOxidizer - could already have benefits by rolling in all dependencies of modules (so no more pip/apt/dnf/... installs on target hosts). Setting this up should be relatively straightforward and could probably be automated enough to even manage to build binary modules for all modules in the community ansible distribution eventually.
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What are different ways to make a Python exe besides py-to-exe?
PyOxidizer might be another option.
- Used "Py To EXE" and It Showed KeyLogger as One of Viruses
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A Completely Open-Source Implementation of Apple Code Signing and Notarization
XAR signing is effectively just an RFC 5652 CMS signature plus some minimal data structure manipulation. Code at https://github.com/indygreg/PyOxidizer/blob/faa7dfcea5d66bf5....
Mach-O and bundles, by contrast, require a myriad of additional data structures requiring thousands of lines of code to support. To my knowledge, nobody else has implemented signing of these far-more-complicated primitives. (Existing Mach-O signing solutions just do ad-hoc signing and/or don't handle Mach-O in the context of a bundle.)
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5 Useful Database Command Line Tools
Written in pure Python, but IRedis was packaged into a single binary with PyOxidizer, you can use cURL to download and run, it just works, even you don't have a Python interpreter.
What are some alternatives?
PyInstaller - Freeze (package) Python programs into stand-alone executables
Nuitka - Nuitka is a Python compiler written in Python. It's fully compatible with Python 2.6, 2.7, 3.4, 3.5, 3.6, 3.7, 3.8, 3.9, 3.10, and 3.11. You feed it your Python app, it does a lot of clever things, and spits out an executable or extension module.
pyarmor - A tool used to obfuscate python scripts, bind obfuscated scripts to fixed machine or expire obfuscated scripts.
pynsist - Build Windows installers for Python applications
py2exe - modified py2exe to support unicode paths
dh-virtualenv - Python virtualenvs in Debian packages
py2app
Eel - A little Python library for making simple Electron-like HTML/JS GUI apps
Poetry - Python packaging and dependency management made easy
maturin - Build and publish crates with pyo3, rust-cpython and cffi bindings as well as rust binaries as python packages
packaging - Core utilities for Python packages
zig - General-purpose programming language and toolchain for maintaining robust, optimal, and reusable software.