ImportError: cannot import name 'bool' from 'numpy'

Not specified by the original author.

How to fix ImportError: cannot import name 'bool' from 'numpy'

Stop importing the alias. In your own code replace from numpy import bool with the builtin bool (or np.bool_ if you need the numpy scalar type). If the error comes from a library you do not own (chumpy is the classic carrier), upgrade that library, or pin numpy<1.24 as a stopgap. numpy 1.24 removed the old aliases np.bool, np.int, np.float and friends for good.

The exact error

ImportError: cannot import name 'bool' from 'numpy'

Fix it

1. Find the bad import: grep -rn "from numpy import" --include=*.py . and look for bool, int, float, complex, object, unicode, str. Expected: you see the exact line raising the error

2. In your own code, swap the alias for the builtin: from numpy import bool goes away, just use bool. Only keep numpy's np.bool_ if you truly need the numpy scalar. Expected: import succeeds on numpy>=1.24

3. If the traceback points inside a third-party package (chumpy is the classic), upgrade that package; if no fixed release exists, pin numpy<1.24 in your requirements. Expected: pip shows numpy 1.23.x and the import works

When this applies

the traceback shows from numpy import bool (or int, float, complex, object, unicode, str) and you run numpy 1.24 or newer

When this does NOT apply

the error is ModuleNotFoundError: No module named 'numpy' (numpy is not installed) or a binary/ABI mismatch error

Versions

numpy >= 1.24, Python 3.8+

Why it happens

numpy deprecated these aliases in 1.20 and removed them in 1.24. Old code and old libraries still import them.

Edge cases

np.bool_ still exists and is fine to use. Pinning numpy<1.24 is a band-aid; the real fix is updating the importing code.

Asked about: ImportError: cannot import name 'bool' from 'numpy' (gh:jxyjxyw/stereo-inertial-poser (README known-issues)). The verified fix: Stop importing the alias. In your own code replace from numpy import bool with the builtin bool (or np.bool_ if you need the numpy scalar type). If the error comes from a library you do not own (chumpy is the classic carrier), upgrade that library, or pin numpy<1.24 as a stopgap. numpy 1.24 removed the old aliases np.bool, np.int, np.float and friends for good. Full thread: https://github.com/jxyjxyw/stereo-inertial-poser/blob/HEAD/README.md

Not specified by the original author.

TL;DR: VisibleDeprecationWarning was removed in numpy 2.0, so from numpy import VisibleDeprecationWarning cannot work anymore. Replace it with Python's builtin warnings module. If you cannot change the code, pin numpy below 2.0 as a stopgap.

The error

ImportError: cannot import name 'VisibleDeprecationWarning' from 'numpy'

Fix it

1. Find every place the removed name is imported:

   grep -rn "VisibleDeprecationWarning" [your project dir]

   Expected: a list of files doing from numpy import VisibleDeprecationWarning.

2. Replace the import with the stdlib warnings module:

   import warnings

   and where the code raised or filtered it, use warnings.warn(msg, DeprecationWarning) or the builtin DeprecationWarning class. Expected: no remaining references to the numpy import.

3. Re-run the import that failed. Expected: it imports cleanly.

4. If you cannot edit the code (a pinned third-party package), downgrade numpy instead:

   pip install "numpy<2.0"

   Expected: the old import works again.

When this applies

Use this when the traceback points at from numpy import VisibleDeprecationWarning and numpy 2.x is installed.

When it does not apply

If the error names a different removed symbol (np.float, np.unicode_, np.asfarray), each needs its own replacement. If numpy is still 1.x, something else is wrong.

Compatibility

numpy 2.0 and later. VisibleDeprecationWarning existed through numpy 1.26.

Root cause

NumPy 2.0 did a long-planned cleanup of deprecated names. VisibleDeprecationWarning was a thin subclass of UserWarning, so the stdlib warnings module plus DeprecationWarning is the intended replacement.

Edge cases

Some libraries vendored the name; upgrading the library to a numpy-2-compatible release is better than patching. If tests filter on the warning class, update the filter to DeprecationWarning too.

A user running numpy 2.0.2 hit ImportError: cannot import name 'VisibleDeprecationWarning' from 'numpy' when importing a package whose code did from numpy import VisibleDeprecationWarning. The verified answer: numpy 2.0 removed VisibleDeprecationWarning along with other deprecated names, so the import must go. The accepted fix was replacing it with Python's builtin warnings module (import warnings and use DeprecationWarning), which the reporter confirmed fixed the numpy 2.0 issues. Full thread: https://github.com/llnl/qnd/issues/17

Not specified by the original author.

TL;DR

For "ImportError: cannot import name 'Mistral' from 'mistralai'": check which Python your notebook kernel uses with sys.executable and compare it to which pip, then reinstall with python -m pip install mistralai using that exact interpreter. Restart the Jupyter kernel after reinstalling so it picks up the new package.

ImportError: cannot import name 'Mistral' from 'mistralai'

Steps

1. Importing the client failed with ImportError: cannot import name 'Mistral' from 'mistralai' even though the package appeared installed. The reporter had installed mistralai with conda, which gave the old 0.x release, and then with pip, which gave 1.x, and was running the code inside a Jupyter notebook. The maintainer could not reproduce it with a clean setup, which pointed at the environment rather than the package. Restarting the Jupyter kernel so it picked up the pip-installed 1.x package made the import work.
2. This import error almost always means your interpreter is loading a different mistralai than you think, commonly the old 0.x from conda when pip installed 1.x. Check which Python your notebook kernel uses with sys.executable and compare it to which pip, then reinstall with python -m pip install mistralai using that exact interpreter. Restart the Jupyter kernel after reinstalling so it picks up the new package. The reporter in this case just needed the kernel restart once the right version was in place.

When to use

You are seeing this: The maintainer could not reproduce it with a clean setup, which pointed at the environment rather than the package. Use this skill when you run into "ImportError: cannot import name Mistral from mistralai after mixing conda and pip installs".

When not to use

If your error message or symptom does not match what is described above, this is probably not your fix. Search for your exact error text instead of forcing this one to fit.

Versions

No specific versions are mentioned in the source material, so treat the fix as generally applicable and check the examples against whatever you have installed.

Why this happens

The original report does not dig into a root cause. It documents the symptom and the fix that resolved it.

Question: Importing the client failed with ImportError: cannot import name 'Mistral' from 'mistralai' even though the package appeared installed. The reporter had installed mistralai with conda, which gave the old 0.x release, and then with pip, which gave 1.x, and was running the code inside a Jupyter notebook. The maintainer could not reproduce it with a clean setup, which pointed at the environment rather than the package. Restarting the Jupyter kernel so it picked up the pip-installed 1.x package made the import work.

Verified resolution: This import error almost always means your interpreter is loading a different mistralai than you think, commonly the old 0.x from conda when pip installed 1.x. Check which Python your notebook kernel uses with sys.executable and compare it to which pip, then reinstall with python -m pip install mistralai using that exact interpreter. Restart the Jupyter kernel after reinstalling so it picks up the new package. The reporter in this case just needed the kernel restart once the right version was in place. Source: https://github.com/mistralai/client-python/issues/211

Thread: https://vectle.com/threads/thr_gdmokGmfY3t-HLB3o6mwuA