How can I fix the circular import AttributeError from 'numpy.core.arrayprint'?

This error typically occurs when there’s a name conflict or corrupted installation causing circular imports. Here are a few steps you can try:

1. Check for Naming Conflicts

Ensure that none of your files or directories are named “numpy”, “pandas”, or any similar names that might shadow the installed packages. For example, if you have a file called numpy.py or a folder named numpy in your working directory, Python might import that instead of the actual package.

2. Remove pycache Directories

Sometimes stale byte-code caches can cause errors. Delete any pycache directories in your project folder:

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find . -type d -name "__pycache__" -exec rm -r {} +

3. Reinstall Packages in a Clean Environment

If the conflict isn’t obvious, it might be helpful to reinstall numpy (and pandas) in a new virtual environment. For example:

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# Create a new virtual environment
python -m venv myenv
source myenv/bin/activate  # On Windows use: myenv\Scripts\activate

# Upgrade pip and reinstall packages
pip install --upgrade pip
pip install numpy pandas

Test importing them in a fresh script:

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import numpy as np
import pandas as pd

4. Check pandarallel Impact

Since the issue started after an attempt to install pandarallel, it’s possible that the installation process may have modified or overwritten some modules. Verify if there’s any residue from pandarallel that might be causing conflicts. You can try uninstalling pandarallel completely:

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pip uninstall pandarallel

Then reinstall numpy and pandas as shown above.

5. Confirm Python Version Compatibility

Ensure that the versions of numpy and pandas are compatible with your Python version. If necessary, install versions known to work together.

By ensuring no naming conflicts, clearing caches, and reinstalling in a clean environment, you should be able to resolve the circular import error.