tuninglib VS etl

Spirick Tuning is a C++ class and template library for performance critical applications. Platforms: MS Windows/Linux Version 1.48 of the TuningLib is published as an open source project on GitHub. github.com/spirick/tuninglib

If you can't use the STL because of exceptions: https://www.etlcpp.com/

You can also use ETL (https://www.etlcpp.com)

Use ETL for embedded standard library functionality: https://www.etlcpp.com/

The best choice here is use embedded Template Library: https://www.etlcpp.com/

If you can't get C++23, expected it's implemented in the ETL (it's also just a really amazing library for this kind of stuff - highly recommend!).

I want to use some of C++ std library classes/functions in my embedded system library project that I'm writing. However as the environment has limited ressources I don't want to have use or expose classes or functions that do the following: * Dynamic memory allocations * RTTI * Runtime exceptions I will be rewriting some basic container and algorithms according to my needs. I know that there are other re writes of STL like ESTL but I don't want to have any external dependencies So my question is can I somehow compile/package a fork of C++ std library that only include embedded systems friendly classes such as: - array - tuple - variant - type_traits Etc This compiled library must be completely standalone. The compiler that I use can support upto C++17 standard.

I will never not recommend the Embedded Template Library

STL containers use dynamic memory allocation which is often a no-no in embedded contexts. there is the ETL https://www.etlcpp.com/ but I haven't used it!