zmq.rs - A brief history of concurrency in Rust

Jan 15, 2015Download as PPTX, PDF0 likes782 views

This document summarizes the history of concurrency approaches used in the Rust zmq.rs library. It started with a unified 1:1 threading model but later switched to using M:N threading to allow more flexibility. It discusses green threads, native threads, the libgreen and green-rs crates, and how the project will move to using the mio crate for asynchronous I/O instead of libgreen. The goal is to rewrite zmq.rs to follow the C++ ZeroMQ design of using a few worker threads each with an event loop and manually mapping sockets to workers.

zmq.rs
A brief history of concurrency in Rust
https://github.com/zeromq/zmq.rs

http://zeromq.org/

rust-zmq
https://github.com/erickt/rust-zmq

libgreen
Optional runtime on top of libuv in Rust. There’s also libnative.

green thread
or
micro thread
or
coroutine

for example
while True:
future = socket.recv(1024)
data = yield from future
print(data)
future = socket.send(data)
status = yield from future

native thread
• OS-managed
• preemptive
• thousands
• low latency
green thread
• user-managed
• cooperative
• hundreds of thousands
• depends

4 green threads,
http://stackoverflow.com/questions/22621514

in 2 OS threads
http://stackoverflow.com/questions/22621514

Overview of zmq.rs
Socket
Acceptor 1
Acceptor 2
Connector
1
Connector
2
Connector
3
Stream 1
Stream 2
Stream 3

1:1 became default
M:N remained optional

Issues with the unity
of 1:1 and M:N
• Cost is huge, to keep a unified interface
• Lost a lot of possibilities and flexibility
• libgreen is not green

libgreen -> green-rs
https://github.com/alexcrichton/green-rs

concurrency ->
• 1:1
• mio
• generator
• green-rs
• …more

https://github.com/carll
erche/mio

next steps in zmq.rs
• Rewrite with MIO
• Follow the design of libzmq in C++
• A few worker threads, each with an event loop
• Sockets mapped to workers manually

zmq.rs
A brief history of concurrency in Rust
https://github.com/zeromq/zmq.rs
Thank you!
http://about.me/fantix
rust.cc 中文社区 QQ 群：144605258

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TestMigrationsInPy: A Dataset of Test Migrations from Unittest to Pytest (MSR...Andre Hora

Unittest and pytest are the most popular testing frameworks in Python. Overall, pytest provides some advantages, including simpler assertion, reuse of fixtures, and interoperability. Due to such benefits, multiple projects in the Python ecosystem have migrated from unittest to pytest. To facilitate the migration, pytest can also run unittest tests, thus, the migration can happen gradually over time. However, the migration can be timeconsuming and take a long time to conclude. In this context, projects would benefit from automated solutions to support the migration process. In this paper, we propose TestMigrationsInPy, a dataset of test migrations from unittest to pytest. TestMigrationsInPy contains 923 real-world migrations performed by developers. Future research proposing novel solutions to migrate frameworks in Python can rely on TestMigrationsInPy as a ground truth. Moreover, as TestMigrationsInPy includes information about the migration type (e.g., changes in assertions or fixtures), our dataset enables novel solutions to be verified effectively, for instance, from simpler assertion migrations to more complex fixture migrations. TestMigrationsInPy is publicly available at: https://github.com/altinoalvesjunior/TestMigrationsInPy.

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GitHub Actions (GA) has become the de facto tool that developers use to automate software workflows, seamlessly building, testing, and deploying code. Yet when GA fails, it disrupts development, causing delays and driving up costs. Diagnosing failures becomes especially challenging because error logs are often long, complex and unstructured. Given these difficulties, this study explores the potential of large language models (LLMs) to generate correct, clear, concise, and actionable contextual descriptions (or summaries) for GA failures, focusing on developers’ perceptions of their feasibility and usefulness. Our results show that over 80% of developers rated LLM explanations positively in terms of correctness for simpler/small logs. Overall, our findings suggest that LLMs can feasibly assist developers in understanding common GA errors, thus, potentially reducing manual analysis. However, we also found that improved reasoning abilities are needed to support more complex CI/CD scenarios. For instance, less experienced developers tend to be more positive on the described context, while seasoned developers prefer concise summaries. Overall, our work offers key insights for researchers enhancing LLM reasoning, particularly in adapting explanations to user expertise. https://arxiv.org/abs/2501.16495

Mastering Fluent Bit: Ultimate Guide to Integrating Telemetry Pipelines with ...Eric D. Schabell

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