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Asked: 2024-09-26T12:24:02+05:30 In:

can’t adapt type ‘numpy.int64

I’m currently working on a data processing project using NumPy in Python, and I’ve run into a frustrating issue. I’m trying to manipulate some data arrays, but I keep getting an error message that says I “can’t adapt type ‘numpy.int64’.” This error pops up when I attempt to insert the values from my NumPy array into a database using SQLAlchemy.

I’ve checked my data types, and they all seem fine, but I suspect that the problem lies with how NumPy handles data types compared to standard Python types. I’ve seen that SQLAlchemy often works better with native Python types, so I tried converting the NumPy integers to regular Python integers using the `int()` function, but I’m still running into issues.

I’ve also looked into using the `.item()` method on my NumPy array, but I’m not entirely sure if that’s the right approach. Can anyone explain the underlying cause of this error and suggest a reliable way to convert my NumPy int values so that they can be successfully adapted for SQLAlchemy? It would really help if you could provide some code examples as well! Thanks in advance for your help!

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    2 Answers

    1. The error regarding “can’t adapt type ‘numpy.int64′” often arises when working with databases in Python, especially when using libraries like SQLAlchemy. This typically happens when trying to insert a value into a database that has a different expected type than what is provided. Specifically, ‘numpy.int64’ is a data type used by NumPy for representing integers, and it doesn’t directly match the Python built-in integer type. This discrepancy can lead to issues during database transactions or when performing operations that expect standard Python types for data adaptation.

      To resolve this issue, it’s crucial to convert the ‘numpy.int64’ type to a native Python integer before attempting to use it in database queries or other operations that may not support NumPy types. This can be done easily using the built-in `int()` function, which will convert the ‘numpy.int64’ to a standard Python integer. For example, if you have a variable `num` of type ‘numpy.int64’, you can use `int(num)` to adapt it properly. By ensuring that the data types match the expectations of the functions or libraries you are working with, you can avoid such adaptation errors and maintain smoother execution of your code.

    2. Looks like you’re hitting a snag with that numpy.int64 type! It’s a bit tricky sometimes, right? So if you’re getting an error like “can’t adapt type ‘numpy.int64’,” it usually means the code is trying to send a numpy integer to somewhere that doesn’t know what to do with it. Like, databases and some libraries don’t always recognize it as a normal integer.

      One quick fix? You can just convert it to a regular Python integer using int(). So, like:

      my_number = numpy_int_64_value
python_int = int(my_number)

      Now, you can use python_int instead, and that should smooth things out!

      Hope that helps a bit! Don’t beat yourself up; everyone starts somewhere!

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