Question: I am trying to run from ydata_profiling import ProfileReport profile = ProfileReport(merged_data) profile.to_notebook_iframe()  in jupyter notebook. But I am getting an error: AttributeError: module 'numba' has no attribute 'generated_jit' I am running jupyter notebook in Docker container with requirements listed below: numpy==1.24.3 pandas==1.4.1 scikit-learn==1.4.1.post1 pyyaml==6.0 dvc==3.48.4 mlflow==2.11.1 seaborn==0.11.2 matplotlib==3.5.1 boto3==1.18.60 jupyter==1.0.0 pandoc==2.3 ydata-profiling==4.7.0 numba==0.59.1  I am using WSL Ubuntu in Visual Studio Code. Tried to build Docker image several times now with different versions of libraries. EDIT: Adding Traceback:  AttributeError Traceback (most recent call last) Cell In[3], line 1 ----> 1 from ydata_profiling import ProfileReport 3 profile = ProfileReport(merged_data) 4 profile.to_notebook_iframe() File /usr/local/lib/python3.11/site-packages/ydata_profiling/__init__.py:14 10 warnings.simplefilter("ignore", category=NumbaDeprecationWarning) 12 import importlib.util # isort:skip # noqa ---> 14 from ydata_profiling.compare_reports import compare # isort:skip # noqa 15 from ydata_profiling.controller import pandas_decorator # isort:skip # noqa 16 from ydata_profiling.profile_report import ProfileReport # isort:skip # noqa File /usr/local/lib/python3.11/site-packages/ydata_profiling/compare_reports.py:12 10 from ydata_profiling.model import BaseDescription 11 from ydata_profiling.model.alerts import Alert ---> 12 from ydata_profiling.profile_report import ProfileReport 15 def _should_wrap(v1: Any, v2: Any) -> bool: 16 if isinstance(v1, (list, dict)): File /usr/local/lib/python3.11/site-packages/ydata_profiling/profile_report.py:25 23 from tqdm.auto import tqdm 24 from typeguard import typechecked ---> 25 from visions import VisionsTypeset 27 from ydata_profiling.config import Config, Settings, SparkSettings 28 from ydata_profiling.expectations_report import ExpectationsReport File /usr/local/lib/python3.11/site-packages/visions/__init__.py:4 1 """Core functionality""" 3 from visions import types, typesets, utils ----> 4 from visions.backends import * 5 from visions.declarative import create_type 6 from visions.functional import ( 7 cast_to_detected, 8 cast_to_inferred, 9 detect_type, 10 infer_type, 11 ) File /usr/local/lib/python3.11/site-packages/visions/backends/__init__.py:9 6 try: 7 import pandas as pd ----> 9 import visions.backends.pandas 10 from visions.backends.pandas.test_utils import pandas_version 12 if pandas_version[0] < 1: File /usr/local/lib/python3.11/site-packages/visions/backends/pandas/__init__.py:2 1 import visions.backends.pandas.traversal ----> 2 import visions.backends.pandas.types File /usr/local/lib/python3.11/site-packages/visions/backends/pandas/types/__init__.py:3 1 import visions.backends.pandas.types.boolean 2 import visions.backends.pandas.types.categorical ----> 3 import visions.backends.pandas.types.complex 4 import visions.backends.pandas.types.count 5 import visions.backends.pandas.types.date File /usr/local/lib/python3.11/site-packages/visions/backends/pandas/types/complex.py:7 5 from visions.backends.pandas.series_utils import series_not_empty, series_not_sparse 6 from visions.backends.pandas.types.float import string_is_float ----> 7 from visions.backends.shared.parallelization_engines import pandas_apply 8 from visions.types.complex import Complex 9 from visions.types.string import String File /usr/local/lib/python3.11/site-packages/visions/backends/shared/__init__.py:1 ----> 1 from . import nan_handling, parallelization_engines, utilities File /usr/local/lib/python3.11/site-packages/visions/backends/shared/nan_handling.py:34 30 # TODO: There are optimizations here, just have to define precisely the desired missing ruleset in the 31 # generated jit 32 if has_numba: ---> 34 @nb.generated_jit(nopython=True) 35 def is_missing(x): 36 """ 37 Return True if the value is missing, False otherwise. 38 """ 39 if isinstance(x, nb.types.Float): AttributeError: module 'numba' has no attribute 'generated_jit' 

Answer: The top API level function numba.decorated_jit is deprecated and removed from numba version>=0.59.0. I suggest to install last version where numba.decorated_jit is and that is numba==0.58.1