| Type conversions |
| ################ |
| |
| Apart from enabling cross-language function calls, a fundamental problem |
| that a binding tool like pybind11 must address is to provide access to |
| native Python types in C++ and vice versa. There are three fundamentally |
| different ways to do this—which approach is preferable for a particular type |
| depends on the situation at hand. |
| |
| 1. Use a native C++ type everywhere. In this case, the type must be wrapped |
| using pybind11-generated bindings so that Python can interact with it. |
| |
| 2. Use a native Python type everywhere. It will need to be wrapped so that |
| C++ functions can interact with it. |
| |
| 3. Use a native C++ type on the C++ side and a native Python type on the |
| Python side. pybind11 refers to this as a *type conversion*. |
| |
| Type conversions are the most "natural" option in the sense that native |
| (non-wrapped) types are used everywhere. The main downside is that a copy |
| of the data must be made on every Python ↔ C++ transition: this is |
| needed since the C++ and Python versions of the same type generally won't |
| have the same memory layout. |
| |
| pybind11 can perform many kinds of conversions automatically. An overview |
| is provided in the table ":ref:`conversion_table`". |
| |
| The following subsections discuss the differences between these options in more |
| detail. The main focus in this section is on type conversions, which represent |
| the last case of the above list. |
| |
| .. toctree:: |
| :maxdepth: 1 |
| |
| overview |
| strings |
| stl |
| functional |
| chrono |
| eigen |
| custom |
| |
