**attributeerror: module numpy has no attribute bool is an error that occurs if you are working with Python’s numpy module. Do you know that,** in this case, the interpreter fails to recognize the bool data type? Scroll through this blog to learn more about the error.

## Reasons for the error

A user gets this error for a couple of reasons. Some of them are:

- Numpy’s version is old.
- Any other package that is being used in the code may be incompatible with the version of numpy.

## Resolving the error

You can adopt the following methods to resolve the error.

### Update numpy to the latest version.

Check the version of numpy using the version command. If it is not the most upgraded one, you need to upgrade it.

```
import numpy as np
print(np.__version__)
```

### Check other packages

Here, you need to get an insight into the packages currently present in your code and whether they support Numpy’s latest version or not. You can downgrade numpy if other libraries can’t be updated. So first, you need to uninstall the current numpy library and then install the downgraded version of numpy.

```
python -m pip uninstall numpy
python -m pip install numpy==1.23.1
```

### Use bool_ instead of `bool`

bool_ attribute works similar to bool. If you are still getting an error with bool, you should definitely go for bool_ attribute. bool_ basically works as replacement of bool.

```
import numpy as np
np_bool = np.bool_(True)
print(np_bool)
```

**So Output will be:**

```
True
```

**Use **a different data type

You can use Python’s bool straightaway. It is built-in.

```
import numpy as np
python_bool = True
print(python_bool)
```

**Use another NumPy library**

Other NumPy libraries are also available. SciPy and Pandas are two such libraries which support usage of bool.

### Use astype(bool)

If the numpy function doesn’t work, you can use astype(bool). It has a similar functionality like bool.

```
import numpy as np
a= np.array([1, 2])
final = a.astype(bool)
print(final)
```

### Make use of a virtual environment

It separates your Python environment from the system environment. Once you have created a virtual environment, then install numpy.

```
python -m venv venv
#activate the environment
source venv/bin/activate
```

**After activation, you need to install numpy**

```
pip install numpy
```

### Solving the error in Anaconda

In the conda environment, one of the installed libraries may not be compatible with the existing numpy version. The best option is to downgrade the numpy version. Also, create a new conda environment and then install the libraries.

```
conda create -n conda-env python=3.8 -y
conda activate conda-env
(conda-env) python -m pip install -e
```

### Solving the error in pycharm

If the above solutions don’t work, try installing numpy again with no dependencies. Check the following code to understand how this works:

```
pip install –upgrade –no-deps numpy
```

### Solving the error with TensorFlow

For tensorflow, changing the numpy version to 1.23.5 will fetch you the right solution. So, in a nutshell, you need to downgrade numpy using the above-mentioned code.

## Other tips while working with bool

These tips can be handy to you while you are working with bool.

- Check the code
- Go through typo errors.
- In the case of a virtual environment, check whether numpy has been installed there.
- Utilize a debugger to see which statement is creating the error.

## FAQS

**Which version of Numpy removed the bool attribute?**

Version 1.24.0 of numpy doesn’t have a bool attribute.

## Conclusion

This blog elaborates on the** attributeerror: module numpy has no attribute bool** error in Python. It explains why this error occurs. Apart from this, several methods of overcoming the bool attribute error have been explained. These will definitely help to resolve the error. The blog covers some tips that are centered on working efficiently with bool.