How to Handle Single and List Objects in PYBIND11 Function Arguments Efficiently

Discover how to effectively bind functions in PYBIND11 to accept a single object or a list of objects, enhancing your C+ + to Python interoperability.
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Understanding PYBIND11: Getting Single or List Objects in Function Arguments

When working with PYBIND11, you may encounter a common problem: how to bind a function that accepts both a single object and a list of objects. This can be particularly challenging when dealing with keywords and arguments specified in calls from Python to C+ + . In this blog, we'll discuss how to effectively handle these scenarios in a PYBIND11 binded C+ + function.

The Scenario

Suppose you have a function that takes multiple arguments and keyword arguments. Here’s how the function looks in C+ + :

[[See Video to Reveal this Text or Code Snippet]]

The Challenge

While this function works nicely when called with arguments like status=[MultiFlags.Complete], the problem arises when you want it to also accept status=MultiFlags.Complete. This requires a more flexible input handling system, and you might find it hard to understand how to implement this logic using PYBIND11.

The Solution

To effectively manage the variability in input types, you can use a try-catch block to gracefully handle the casting of kwargs. Here’s how to implement this:

Step-by-Step Implementation

Initial Setup: First, you still want to check the key_name just like before, but now you need to handle the possibility that the user could pass in either a single MultiFlags object or a list of objects.

Implement Try-Catch: Use try-catch to attempt casting to a vector first, and if it fails, then you catch the error and handle the single object case. Update the code as follows:

[[See Video to Reveal this Text or Code Snippet]]

Explanation

Casting Attempt: The first attempt tries to cast kv.second to a std::vector<MultiFlags>. If it succeeds, there is no further action needed.

Error Handling: If a py::cast_error occurs, this means the type was not a list but a single MultiFlags element. In this case, we catch the error and perform a second cast, placing the single element into a vector.

Conclusion

By integrating a try-catch block into your PYBIND11 function binding, you can efficiently manage multiple types of input without losing the robust functionality you want in your C+ + code. This technique allows for greater flexibility in your input handling, paving the way for a smoother user experience when integrating Python and C+ + .

Whether you're developing a complex application or just starting with PYBIND11, handling such cases will enhance the usability and robustness of your functions.

With this knowledge, you're now equipped to improve your function bindings in PYBIND11!

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