FunctionalPlus VS pybind11

Hoogle is really amazing!

Inspired by it, I implemented something similar for FunctionalPlus (a functional-programming library for C++): https://www.editgym.com/fplus-api-search/

I'd love to see more projects taking this path too. :)

You can get a feel for it on its api search site: as an example, enter these queries:

I use a library called FunctionalPlus daily.

As idiomatic, I will try to adopt as much as possible purely functional programming in C++ by using https://github.com/Dobiasd/FunctionalPlus . Do you have by any chance any alternative suggestion?

Any project CML file that is more complex than this is mismanaged and needs fixing asap. There is absolutely no reason to make CML files describing requirements of a library substantially more complex other than if you have a vendetta against yourself, package maintainers and your users.

FunctionalPlus - 30 lines for usage requirements + 60 for install rules: just simple commands creating a target, setting properties and defining install rules. Hmm, nothing unholy here.

Another option is to use a superbuild CML where you can do all the nasty, platform specific things. Example of a superbuild CML.

You can copy this project structure: https://github.com/Dobiasd/FunctionalPlus

I'm investigating using C++ to build a REST server, and would love to know of people's experiences with Crow-- or whether they would recommend something else as a "medium-level" abstraction C++ web server. As background, I started off experimenting with Python/FastAPI, which is great, but there is too much friction to translate from pybind11-exported C++ objects to the format that FastAPI expects, and, of course, there are inherent performance limitations using Python, which could impact scaling up if the project were to be successful.

I have a C++ function computing a large tensor which I would like to return to Python as a NumPy array via pybind11.

This is based on the Google Ink Stroke Modeler C++ library, and using pybind11 to make it available on python.

pybind11 makes it easy to call C++ from Python if you want to mix.

If you've never used Pybind before these pybind tests[1] and this repo[2] have good examples you can crib to get started (in addition to the docs). Once you handle passing/returning/creating the main data types (list, tuple, dict, set, numpy array) the first time, then it's mostly smooth sailing.

Pybind offers a lot of functionality, but core "good parts" I've found useful are (a) use a numpy array in Python and pass it to a C++ method to work on, (b) pass your python data structure to pybind and then do work on it in C++ (some copy overhead), and (c) Make a class/struct in C++ and expose it to Python (so no copying overhead and you can create nice cache-aware structs, etc.).

[1] https://github.com/pybind/pybind11/blob/master/tests/test_py...

I have a python module for which the logic is written in C++ and I use pybind11 to expose the objects and functions to Python.

Reading from Python requires a wrapper, using pybind11 this is fairly done.

Also I can highly recommend starting using C++ to augment your Python code, i.e. find the parts that are slow or undoable in Python and write those in C++ then expose them as Python functions. You can use https://github.com/pybind/pybind11 to call C++ code from Python.