pybind/pybind11

Not clear how to expose existing C++ vector as numpy array

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#1,042 opened on Aug 30, 2017

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 (37 comments) (27 reactions) (0 assignees)C++ (14,677 stars) (2,005 forks)batch import
enhancementhelp wanted

Description

This is a question of documentation rather than an issue. I can't find any example of the following very common scenario:

std::vector<int> some_func();
...
// We want to expose returned std::vector as a numpy array without copying
m.def("some_func", []() -> py::array {
   auto data = some_func();
   // What to do with data?? Map it with Eigen (then return what?), wrap somehow with py::buffer (how?)
})

I don't know the answer. It would be very nice to have this explained in docs since this scenario if rather common.

Contributor guide

Tech stack
pythoncpp
Domain
documentationapi
Issue type
documentation
DifficultyEstimated implementation difficulty for a new contributor, from 1 for very small changes to 5 for expert-level work.
3
Estimated timeA rough time range for an experienced contributor to investigate, implement, test, and prepare a pull request.
1-3 hours
Activity statusHow available the issue appears right now: fresh, active, stale, blocked, or waiting on maintainer input.
stale
ClarityHow clearly the issue explains the expected change, acceptance criteria, and next step.
clear
Prerequisites
Basic C++ and pybind11numpy basics
Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.
60
Research direction
Review the existing pybind11 documentation for numpy integration and check comments in the issue for any progress or workarounds. Look at the pybind11 source code for py::array and buffer protocol examples. The goal is to write a clear example showing how to create a py::array from an existing std::vector without copying, using the buffer info or direct memory mapping. Address the common pattern in the issue body and provide a minimal working example.