DIPs VS compact_str

Compare DIPs vs compact_str and see what are their differences.

compact_str

A memory efficient string type that can store up to 24* bytes on the stack (by ParkMyCar)
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DIPs compact_str
10 16
156 541
0.6% -
5.8 7.6
11 days ago 7 days ago
D Rust
Creative Commons Zero v1.0 Universal MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.

DIPs

Posts with mentions or reviews of DIPs. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-01-05.

compact_str

Posts with mentions or reviews of compact_str. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-02-22.

What are some alternatives?

When comparing DIPs and compact_str you can also consider the following projects:

crubit

smartstring - Compact inlined strings for Rust.

peps - Python Enhancement Proposals

smol_str

intellij-dlanguage - Intellij Plugin for the D Programming Language

openssh - Scriptable SSH through OpenSSH in Rust

proposals - ✍️ Tracking the status of Babel's implementation of TC39 proposals (may be out of date)

zero-copy-pads - Padding/aligning values without heap allocation

carbon-lang - Carbon Language's main repository: documents, design, implementation, and related tools. (NOTE: Carbon Language is experimental; see README)

rust - Empowering everyone to build reliable and efficient software.

Juleps - Julia Enhancement Proposals

perf-ninja-rs - Rust port of dendibakh/perf-ninja - an online course where you can learn and master the skill of low-level performance analysis and tuning.