# Infinite loading when importing libraries

**URL:** <https://discourse.jupyter.org/t/infinite-loading-when-importing-libraries/17152>\
**Category:** Kernels\
**Tags:** help-wanted\
**Created:** [December 7, 2022, 6:34pm UTC](https://discourse.jupyter.org/t/infinite-loading-when-importing-libraries/17152 "2022-12-07T18:34:16Z")\
**Posts on this page:** 9\
**Page:** 1

<div class="post-metadata">

**Author:** ![luis](https://avatars.discourse-cdn.com/v4/letter/l/3e96dc/32.png) [@luis](https://discourse.jupyter.org/u/luis)\
**Post date:** [December 7, 2022, 6:34pm UTC](https://discourse.jupyter.org/t/infinite-loading-when-importing-libraries/17152/1 "2022-12-07T18:34:16Z")

</div>

Hi!  
I am facing some issues when importing libraries, as the cell will stay loading [\*] and never end. When I start the notebook I can run any python code that doesn’t require external libraries, I can also import numpy, but importing scikit or matplot will end up in this never ending loading cell, that results in a dead kernel.

I have already tried recreating the environment and installing ipykernel to be able to choose the conda environment from the notebook, but it gives the same error. The libraries I am trying to import work perfectly on the environment using the terminal, and I just get this issue when using the notebook. I’ve also tried to import non-installed packages, and for those I do get an output saying that the package doesn’t exist.

I am running macOS 13.0.1 with M1 and conda 22.9.0

Jupyter-troubleshoot returns this:

```auto
$PATH:
	/opt/homebrew/opt/jpeg/bin
	/Users/johndoe/mambaforge/envs/envname/bin
	/Users/johndoe/mambaforge/condabin
	/opt/homebrew/bin
	/opt/homebrew/sbin
	/usr/local/bin
	/System/Cryptexes/App/usr/bin
	/usr/bin
	/bin
	/usr/sbin
	/sbin
	/Library/TeX/texbin
	/Library/Frameworks/Mono.framework/Versions/Current/Commands

sys.path:
	/Users/johndoe/mambaforge/envs/envname/bin
	/Users/johndoe/mambaforge/envs/envname/lib/python310.zip
	/Users/johndoe/mambaforge/envs/envname/lib/python3.10
	/Users/johndoe/mambaforge/envs/envname/lib/python3.10/lib-dynload
	/Users/johndoe/mambaforge/envs/envname/lib/python3.10/site-packages

sys.executable:
	/Users/johndoe/mambaforge/envs/envname/bin/python

sys.version:
	3.10.8 | packaged by conda-forge | (main, Nov 22 2022, 08:25:29) [Clang 14.0.6]

platform.platform():
	macOS-13.0.1-arm64-arm-64bit

which -a jupyter:
	/Users/johndoe/mambaforge/envs/envname/bin/jupyter

pip list:
	Package Version
	----------------------------- -----------
	anyio 3.6.2
	appnope 0.1.3
	argon2-cffi 21.3.0
	argon2-cffi-bindings 21.2.0
	asttokens 2.2.1
	attrs 22.1.0
	backcall 0.2.0
	backports.functools-lru-cache 1.6.4
	beautifulsoup4 4.11.1
	bleach 5.0.1
	cffi 1.15.1
	debugpy 1.6.4
	decorator 5.1.1
	defusedxml 0.7.1
	entrypoints 0.4
	executing 1.2.0
	fastjsonschema 2.16.2
	flit_core 3.8.0
	idna 3.4
	importlib-metadata 5.1.0
	importlib-resources 5.10.1
	ipykernel 6.17.1
	ipython 8.7.0
	ipython-genutils 0.2.0
	ipywidgets 8.0.3
	jedi 0.18.2
	Jinja2 3.1.2
	joblib 1.2.0
	jsonschema 4.17.3
	jupyter 1.0.0
	jupyter_client 7.4.8
	jupyter-console 6.4.4
	jupyter_core 5.1.0
	jupyter-events 0.5.0
	jupyter_server 2.0.0
	jupyter_server_terminals 0.4.2
	jupyterlab-pygments 0.2.2
	jupyterlab-widgets 3.0.4
	MarkupSafe 2.1.1
	matplotlib-inline 0.1.6
	mistune 2.0.4
	nbclassic 0.4.8
	nbclient 0.7.2
	nbconvert 7.2.6
	nbformat 5.7.0
	nest-asyncio 1.5.6
	notebook 6.5.2
	notebook_shim 0.2.2
	numpy 1.23.5
	packaging 21.3
	pandocfilters 1.5.0
	parso 0.8.3
	pexpect 4.8.0
	pickleshare 0.7.5
	pip 22.3.1
	pkgutil_resolve_name 1.3.10
	platformdirs 2.5.2
	prometheus-client 0.15.0
	prompt-toolkit 3.0.36
	psutil 5.9.4
	ptyprocess 0.7.0
	pure-eval 0.2.2
	pycparser 2.21
	Pygments 2.13.0
	pyparsing 3.0.9
	pyrsistent 0.19.2
	python-dateutil 2.8.2
	python-json-logger 2.0.1
	PyYAML 6.0
	pyzmq 24.0.1
	scikit-learn 1.1.3
	scipy 1.9.3
	Send2Trash 1.8.0
	setuptools 65.5.1
	six 1.16.0
	sniffio 1.3.0
	soupsieve 2.3.2.post1
	stack-data 0.6.2
	terminado 0.17.1
	threadpoolctl 3.1.0
	tinycss2 1.2.1
	tornado 6.2
	traitlets 5.6.0
	typing_extensions 4.4.0
	wcwidth 0.2.5
	webencodings 0.5.1
	websocket-client 1.4.2
	wheel 0.38.4
	widgetsnbextension 4.0.4
	zipp 3.11.0

conda list:
	# packages in environment at /Users/johndoe/mambaforge/envs/envname:
	#
	# Name Version Build Channel
	_ipython_minor_entry_point 8.7.0 hb6b4a82_0 conda-forge
	anyio 3.6.2 pyhd8ed1ab_0 conda-forge
	appnope 0.1.3 pyhd8ed1ab_0 conda-forge
	argon2-cffi 21.3.0 pyhd8ed1ab_0 conda-forge
	argon2-cffi-bindings 21.2.0 py310h8e9501a_3 conda-forge
	asttokens 2.2.1 pyhd8ed1ab_0 conda-forge
	attrs 22.1.0 pyh71513ae_1 conda-forge
	backcall 0.2.0 pyh9f0ad1d_0 conda-forge
	backports 1.0 pyhd8ed1ab_3 conda-forge
	backports.functools_lru_cache 1.6.4 pyhd8ed1ab_0 conda-forge
	beautifulsoup4 4.11.1 pyha770c72_0 conda-forge
	bleach 5.0.1 pyhd8ed1ab_0 conda-forge
	bzip2 1.0.8 h3422bc3_4 conda-forge
	ca-certificates 2022.9.24 h4653dfc_0 conda-forge
	cffi 1.15.1 py310h2399d43_2 conda-forge
	debugpy 1.6.4 py310h0f1eb42_0 conda-forge
	decorator 5.1.1 pyhd8ed1ab_0 conda-forge
	defusedxml 0.7.1 pyhd8ed1ab_0 conda-forge
	entrypoints 0.4 pyhd8ed1ab_0 conda-forge
	executing 1.2.0 pyhd8ed1ab_0 conda-forge
	flit-core 3.8.0 pyhd8ed1ab_0 conda-forge
	idna 3.4 pyhd8ed1ab_0 conda-forge
	importlib-metadata 5.1.0 pyha770c72_0 conda-forge
	importlib_resources 5.10.1 pyhd8ed1ab_0 conda-forge
	ipykernel 6.17.1 pyh736e0ef_0 conda-forge
	ipython 8.7.0 pyhd1c38e8_0 conda-forge
	ipython_genutils 0.2.0 py_1 conda-forge
	ipywidgets 8.0.3 pyhd8ed1ab_0 conda-forge
	jedi 0.18.2 pyhd8ed1ab_0 conda-forge
	jinja2 3.1.2 pyhd8ed1ab_1 conda-forge
	joblib 1.2.0 pyhd8ed1ab_0 conda-forge
	jsonschema 4.17.3 pyhd8ed1ab_0 conda-forge
	jupyter 1.0.0 py310hbe9552e_8 conda-forge
	jupyter_client 7.4.8 pyhd8ed1ab_0 conda-forge
	jupyter_console 6.4.4 pyhd8ed1ab_0 conda-forge
	jupyter_core 5.1.0 py310hbe9552e_0 conda-forge
	jupyter_events 0.5.0 pyhd8ed1ab_0 conda-forge
	jupyter_server 2.0.0 pyhd8ed1ab_0 conda-forge
	jupyter_server_terminals 0.4.2 pyhd8ed1ab_0 conda-forge
	jupyterlab_pygments 0.2.2 pyhd8ed1ab_0 conda-forge
	jupyterlab_widgets 3.0.4 pyhd8ed1ab_0 conda-forge
	libblas 3.9.0 16_osxarm64_openblas conda-forge
	libcblas 3.9.0 16_osxarm64_openblas conda-forge
	libcxx 14.0.6 h2692d47_0 conda-forge
	libffi 3.4.2 h3422bc3_5 conda-forge
	libgfortran 5.0.0 11_3_0_hd922786_26 conda-forge
	libgfortran5 11.3.0 hdaf2cc0_26 conda-forge
	liblapack 3.9.0 16_osxarm64_openblas conda-forge
	libopenblas 0.3.21 openmp_hc731615_3 conda-forge
	libsodium 1.0.18 h27ca646_1 conda-forge
	libsqlite 3.40.0 h76d750c_0 conda-forge
	libzlib 1.2.13 h03a7124_4 conda-forge
	llvm-openmp 15.0.6 h7cfbb63_0 conda-forge
	markupsafe 2.1.1 py310h8e9501a_2 conda-forge
	matplotlib-inline 0.1.6 pyhd8ed1ab_0 conda-forge
	mistune 2.0.4 pyhd8ed1ab_0 conda-forge
	nbclassic 0.4.8 pyhd8ed1ab_0 conda-forge
	nbclient 0.7.2 pyhd8ed1ab_0 conda-forge
	nbconvert 7.2.6 pyhd8ed1ab_0 conda-forge
	nbconvert-core 7.2.6 pyhd8ed1ab_0 conda-forge
	nbconvert-pandoc 7.2.6 pyhd8ed1ab_0 conda-forge
	nbformat 5.7.0 pyhd8ed1ab_0 conda-forge
	ncurses 6.3 h07bb92c_1 conda-forge
	nest-asyncio 1.5.6 pyhd8ed1ab_0 conda-forge
	notebook 6.5.2 pyha770c72_1 conda-forge
	notebook-shim 0.2.2 pyhd8ed1ab_0 conda-forge
	numpy 1.23.5 py310h5d7c261_0 conda-forge
	openssl 3.0.7 h03a7124_1 conda-forge
	packaging 21.3 pyhd8ed1ab_0 conda-forge
	pandoc 2.19.2 hce30654_1 conda-forge
	pandocfilters 1.5.0 pyhd8ed1ab_0 conda-forge
	parso 0.8.3 pyhd8ed1ab_0 conda-forge
	pexpect 4.8.0 pyh1a96a4e_2 conda-forge
	pickleshare 0.7.5 py_1003 conda-forge
	pip 22.3.1 pyhd8ed1ab_0 conda-forge
	pkgutil-resolve-name 1.3.10 pyhd8ed1ab_0 conda-forge
	platformdirs 2.5.2 pyhd8ed1ab_1 conda-forge
	prometheus_client 0.15.0 pyhd8ed1ab_0 conda-forge
	prompt-toolkit 3.0.36 pyha770c72_0 conda-forge
	prompt_toolkit 3.0.36 hd8ed1ab_0 conda-forge
	psutil 5.9.4 py310h8e9501a_0 conda-forge
	ptyprocess 0.7.0 pyhd3deb0d_0 conda-forge
	pure_eval 0.2.2 pyhd8ed1ab_0 conda-forge
	pycparser 2.21 pyhd8ed1ab_0 conda-forge
	pygments 2.13.0 pyhd8ed1ab_0 conda-forge
	pyparsing 3.0.9 pyhd8ed1ab_0 conda-forge
	pyrsistent 0.19.2 py310h8e9501a_0 conda-forge
	python 3.10.8 h3ba56d0_0_cpython conda-forge
	python-dateutil 2.8.2 pyhd8ed1ab_0 conda-forge
	python-fastjsonschema 2.16.2 pyhd8ed1ab_0 conda-forge
	python-json-logger 2.0.1 pyh9f0ad1d_0 conda-forge
	python_abi 3.10 3_cp310 conda-forge
	pyyaml 6.0 py310h8e9501a_5 conda-forge
	pyzmq 24.0.1 py310hc407298_1 conda-forge
	readline 8.1.2 h46ed386_0 conda-forge
	scikit-learn 1.1.3 py310ha00a7cd_1 conda-forge
	scipy 1.9.3 py310ha0d8a01_2 conda-forge
	send2trash 1.8.0 pyhd8ed1ab_0 conda-forge
	setuptools 65.5.1 pyhd8ed1ab_0 conda-forge
	six 1.16.0 pyh6c4a22f_0 conda-forge
	sniffio 1.3.0 pyhd8ed1ab_0 conda-forge
	soupsieve 2.3.2.post1 pyhd8ed1ab_0 conda-forge
	stack_data 0.6.2 pyhd8ed1ab_0 conda-forge
	terminado 0.17.1 pyhd1c38e8_0 conda-forge
	threadpoolctl 3.1.0 pyh8a188c0_0 conda-forge
	tinycss2 1.2.1 pyhd8ed1ab_0 conda-forge
	tk 8.6.12 he1e0b03_0 conda-forge
	tornado 6.2 py310h8e9501a_1 conda-forge
	traitlets 5.6.0 pyhd8ed1ab_0 conda-forge
	typing_extensions 4.4.0 pyha770c72_0 conda-forge
	tzdata 2022g h191b570_0 conda-forge
	wcwidth 0.2.5 pyh9f0ad1d_2 conda-forge
	webencodings 0.5.1 py_1 conda-forge
	websocket-client 1.4.2 pyhd8ed1ab_0 conda-forge
	wheel 0.38.4 pyhd8ed1ab_0 conda-forge
	widgetsnbextension 4.0.4 pyhd8ed1ab_0 conda-forge
	xz 5.2.6 h57fd34a_0 conda-forge
	yaml 0.2.5 h3422bc3_2 conda-forge
	zeromq 4.3.4 hbdafb3b_1 conda-forge
	zipp 3.11.0 pyhd8ed1ab_0 conda-forge

conda env:
	name: envname
	channels:
	  - conda-forge
	dependencies:
	  - _ipython_minor_entry_point=8.7.0=hb6b4a82_0
	  - anyio=3.6.2=pyhd8ed1ab_0
	  - appnope=0.1.3=pyhd8ed1ab_0
	  - argon2-cffi=21.3.0=pyhd8ed1ab_0
	  - argon2-cffi-bindings=21.2.0=py310h8e9501a_3
	  - asttokens=2.2.1=pyhd8ed1ab_0
	  - attrs=22.1.0=pyh71513ae_1
	  - backcall=0.2.0=pyh9f0ad1d_0
	  - backports=1.0=pyhd8ed1ab_3
	  - backports.functools_lru_cache=1.6.4=pyhd8ed1ab_0
	  - beautifulsoup4=4.11.1=pyha770c72_0
	  - bleach=5.0.1=pyhd8ed1ab_0
	  - bzip2=1.0.8=h3422bc3_4
	  - ca-certificates=2022.9.24=h4653dfc_0
	  - cffi=1.15.1=py310h2399d43_2
	  - debugpy=1.6.4=py310h0f1eb42_0
	  - decorator=5.1.1=pyhd8ed1ab_0
	  - defusedxml=0.7.1=pyhd8ed1ab_0
	  - entrypoints=0.4=pyhd8ed1ab_0
	  - executing=1.2.0=pyhd8ed1ab_0
	  - flit-core=3.8.0=pyhd8ed1ab_0
	  - idna=3.4=pyhd8ed1ab_0
	  - importlib-metadata=5.1.0=pyha770c72_0
	  - importlib_resources=5.10.1=pyhd8ed1ab_0
	  - ipykernel=6.17.1=pyh736e0ef_0
	  - ipython=8.7.0=pyhd1c38e8_0
	  - ipython_genutils=0.2.0=py_1
	  - ipywidgets=8.0.3=pyhd8ed1ab_0
	  - jedi=0.18.2=pyhd8ed1ab_0
	  - jinja2=3.1.2=pyhd8ed1ab_1
	  - joblib=1.2.0=pyhd8ed1ab_0
	  - jsonschema=4.17.3=pyhd8ed1ab_0
	  - jupyter=1.0.0=py310hbe9552e_8
	  - jupyter_client=7.4.8=pyhd8ed1ab_0
	  - jupyter_console=6.4.4=pyhd8ed1ab_0
	  - jupyter_core=5.1.0=py310hbe9552e_0
	  - jupyter_events=0.5.0=pyhd8ed1ab_0
	  - jupyter_server=2.0.0=pyhd8ed1ab_0
	  - jupyter_server_terminals=0.4.2=pyhd8ed1ab_0
	  - jupyterlab_pygments=0.2.2=pyhd8ed1ab_0
	  - jupyterlab_widgets=3.0.4=pyhd8ed1ab_0
	  - libblas=3.9.0=16_osxarm64_openblas
	  - libcblas=3.9.0=16_osxarm64_openblas
	  - libcxx=14.0.6=h2692d47_0
	  - libffi=3.4.2=h3422bc3_5
	  - libgfortran=5.0.0=11_3_0_hd922786_26
	  - libgfortran5=11.3.0=hdaf2cc0_26
	  - liblapack=3.9.0=16_osxarm64_openblas
	  - libopenblas=0.3.21=openmp_hc731615_3
	  - libsodium=1.0.18=h27ca646_1
	  - libsqlite=3.40.0=h76d750c_0
	  - libzlib=1.2.13=h03a7124_4
	  - llvm-openmp=15.0.6=h7cfbb63_0
	  - markupsafe=2.1.1=py310h8e9501a_2
	  - matplotlib-inline=0.1.6=pyhd8ed1ab_0
	  - mistune=2.0.4=pyhd8ed1ab_0
	  - nbclassic=0.4.8=pyhd8ed1ab_0
	  - nbclient=0.7.2=pyhd8ed1ab_0
	  - nbconvert=7.2.6=pyhd8ed1ab_0
	  - nbconvert-core=7.2.6=pyhd8ed1ab_0
	  - nbconvert-pandoc=7.2.6=pyhd8ed1ab_0
	  - nbformat=5.7.0=pyhd8ed1ab_0
	  - ncurses=6.3=h07bb92c_1
	  - nest-asyncio=1.5.6=pyhd8ed1ab_0
	  - notebook=6.5.2=pyha770c72_1
	  - notebook-shim=0.2.2=pyhd8ed1ab_0
	  - numpy=1.23.5=py310h5d7c261_0
	  - openssl=3.0.7=h03a7124_1
	  - packaging=21.3=pyhd8ed1ab_0
	  - pandoc=2.19.2=hce30654_1
	  - pandocfilters=1.5.0=pyhd8ed1ab_0
	  - parso=0.8.3=pyhd8ed1ab_0
	  - pexpect=4.8.0=pyh1a96a4e_2
	  - pickleshare=0.7.5=py_1003
	  - pip=22.3.1=pyhd8ed1ab_0
	  - pkgutil-resolve-name=1.3.10=pyhd8ed1ab_0
	  - platformdirs=2.5.2=pyhd8ed1ab_1
	  - prometheus_client=0.15.0=pyhd8ed1ab_0
	  - prompt-toolkit=3.0.36=pyha770c72_0
	  - prompt_toolkit=3.0.36=hd8ed1ab_0
	  - psutil=5.9.4=py310h8e9501a_0
	  - ptyprocess=0.7.0=pyhd3deb0d_0
	  - pure_eval=0.2.2=pyhd8ed1ab_0
	  - pycparser=2.21=pyhd8ed1ab_0
	  - pygments=2.13.0=pyhd8ed1ab_0
	  - pyparsing=3.0.9=pyhd8ed1ab_0
	  - pyrsistent=0.19.2=py310h8e9501a_0
	  - python=3.10.8=h3ba56d0_0_cpython
	  - python-dateutil=2.8.2=pyhd8ed1ab_0
	  - python-fastjsonschema=2.16.2=pyhd8ed1ab_0
	  - python-json-logger=2.0.1=pyh9f0ad1d_0
	  - python_abi=3.10=3_cp310
	  - pyyaml=6.0=py310h8e9501a_5
	  - pyzmq=24.0.1=py310hc407298_1
	  - readline=8.1.2=h46ed386_0
	  - scikit-learn=1.1.3=py310ha00a7cd_1
	  - scipy=1.9.3=py310ha0d8a01_2
	  - send2trash=1.8.0=pyhd8ed1ab_0
	  - setuptools=65.5.1=pyhd8ed1ab_0
	  - six=1.16.0=pyh6c4a22f_0
	  - sniffio=1.3.0=pyhd8ed1ab_0
	  - soupsieve=2.3.2.post1=pyhd8ed1ab_0
	  - stack_data=0.6.2=pyhd8ed1ab_0
	  - terminado=0.17.1=pyhd1c38e8_0
	  - threadpoolctl=3.1.0=pyh8a188c0_0
	  - tinycss2=1.2.1=pyhd8ed1ab_0
	  - tk=8.6.12=he1e0b03_0
	  - tornado=6.2=py310h8e9501a_1
	  - traitlets=5.6.0=pyhd8ed1ab_0
	  - typing_extensions=4.4.0=pyha770c72_0
	  - tzdata=2022g=h191b570_0
	  - wcwidth=0.2.5=pyh9f0ad1d_2
	  - webencodings=0.5.1=py_1
	  - websocket-client=1.4.2=pyhd8ed1ab_0
	  - wheel=0.38.4=pyhd8ed1ab_0
	  - widgetsnbextension=4.0.4=pyhd8ed1ab_0
	  - xz=5.2.6=h57fd34a_0
	  - yaml=0.2.5=h3422bc3_2
	  - zeromq=4.3.4=hbdafb3b_1
	  - zipp=3.11.0=pyhd8ed1ab_0
	prefix: /Users/johndoe/mambaforge/envs/envname

```

---

<div class="post-metadata">

**Author:** ![erkin98](https://yyz1.discourse-cdn.com/flex031/user_avatar/discourse.jupyter.org/erkin98/32/5263_2.png) [@erkin98](https://discourse.jupyter.org/u/erkin98)\
**Post date:** [December 8, 2022, 7:44am UTC](https://discourse.jupyter.org/t/infinite-loading-when-importing-libraries/17152/2 "2022-12-08T07:44:35Z")

</div>

remove your env, install with python 3.10, then install jupyter with mamba, not with a pip, and install packages that you mentioned with mamba as well

---

<div class="post-metadata">

**Author:** ![luis](https://avatars.discourse-cdn.com/v4/letter/l/3e96dc/32.png) [@luis](https://discourse.jupyter.org/u/luis)\
**Post date:** [December 8, 2022, 8:17am UTC](https://discourse.jupyter.org/t/infinite-loading-when-importing-libraries/17152/3 "2022-12-08T08:17:31Z")

</div>

Okay, so I did exactly that with the following commands:

```auto
>> conda create -n jupyter python=3.10

>> conda activate jupyter
>> conda install -c conda-forge jupyterlab
>> conda install -c conda-forge numpy
>> conda install -c conda-forge scikit-learn
>> conda install -c conda-forge matplotlib

```

and the issue still persists after launching Jupyter-lab and opening a notebook that has more libraries than numpy. I checked the output of conda install, and it seems to be installing the correct libraries for the m1 as packages are prepended with “conda-forge/osx-arm64”.

The issue is still the same, if I run anything on the terminal, it’ll work, but on the notebook it won’t finish importing the libraries:

```auto
Python 3.10.8 | packaged by conda-forge | (main, Nov 22 2022, 08:25:29) [Clang 14.0.6] on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>> from sklearn.datasets import load_breast_cancer
>>> X, y = load_breast_cancer(return_X_y=True)
>>> X
array([[1.799e+01, 1.038e+01, 1.228e+02, ..., 2.654e-01, 4.601e-01,
        1.189e-01],
       [2.057e+01, 1.777e+01, 1.329e+02, ..., 1.860e-01, 2.750e-01,
        8.902e-02],
       [1.969e+01, 2.125e+01, 1.300e+02, ..., 2.430e-01, 3.613e-01,
        8.758e-02],
       ...,
       [1.660e+01, 2.808e+01, 1.083e+02, ..., 1.418e-01, 2.218e-01,
        7.820e-02],
       [2.060e+01, 2.933e+01, 1.401e+02, ..., 2.650e-01, 4.087e-01,
        1.240e-01],
       [7.760e+00, 2.454e+01, 4.792e+01, ..., 0.000e+00, 2.871e-01,
        7.039e-02]])
>>> y
array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1,
       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0,
       0, 0, 1, 0, 1, 1, 1, 1, 1, 0, 0, 1, 0, 0, 1, 1, 1, 1, 0, 1, 0, 0,
       1, 1, 1, 1, 0, 1, 0, 0, 1, 0, 1, 0, 0, 1, 1, 1, 0, 0, 1, 0, 0, 0,
       1, 1, 1, 0, 1, 1, 0, 0, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 1, 1, 0, 1,
       1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 1, 1, 1, 0, 0, 1, 0, 1, 0,
       0, 1, 0, 0, 1, 1, 0, 1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1,
       1, 1, 0, 1, 1, 1, 1, 0, 0, 1, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 1,
       1, 0, 1, 1, 0, 0, 0, 1, 0, 1, 0, 1, 1, 1, 0, 1, 1, 0, 0, 1, 0, 0,
       0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 1, 1, 0, 1, 0, 0, 0, 0, 1, 1, 0, 0,
       1, 1, 1, 0, 1, 1, 1, 1, 1, 0, 0, 1, 1, 0, 1, 1, 0, 0, 1, 0, 1, 1,
       1, 1, 0, 1, 1, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
       0, 0, 1, 1, 1, 1, 1, 1, 0, 1, 0, 1, 1, 0, 1, 1, 0, 1, 0, 0, 1, 1,
       1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 0, 1, 0, 1, 1, 1, 1, 1,
       1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1, 0, 1, 1, 1, 1, 0, 0,
       0, 1, 1, 1, 1, 0, 1, 0, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 0,
       0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 0, 0, 0, 1, 0, 0,
       1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 0, 0, 1, 1,
       1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 0, 1, 1, 0,
       1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 0, 1, 0, 1, 1, 1, 1,
       1, 0, 1, 1, 0, 1, 0, 1, 1, 0, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0,
       1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1,
       1, 1, 1, 0, 1, 0, 1, 1, 0, 1, 1, 1, 1, 1, 0, 0, 1, 0, 1, 0, 1, 1,
       1, 1, 1, 0, 1, 1, 0, 1, 0, 1, 0, 0, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1,
       1, 1, 1, 1, 1, 0, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
       1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 1])

```

and this is the output in the notebook:

 ![Screenshot](https://canada1.discourse-cdn.com/flex031/uploads/jupyter/original/2X/9/918b0ac93c83162a560462e431e259d7510991c7.png)

Also, I just realised that executing commands like %conda list will also have the same problem.

---

<div class="post-metadata">

**Author:** ![bollwyvl](https://yyz1.discourse-cdn.com/flex031/user_avatar/discourse.jupyter.org/bollwyvl/32/904_2.png) [@bollwyvl](https://discourse.jupyter.org/u/bollwyvl)\
**Post date:** [December 8, 2022, 11:34am UTC](https://discourse.jupyter.org/t/infinite-loading-when-importing-libraries/17152/4 "2022-12-08T11:34:02Z")

</div>

You can save some time, and get a more reproducible environment by creating/checking in an `environment.yml`:

```yaml
# environment.yml
channels:
  - conda-forge
  - nodefaults
dependencies:
  - python >=3.10,<3.11
  - jupyterlab
  - numpy
  - scikit-learn
  - matplotlib-base # avoid qt if you can, if having trouble

```

then, ideally use [`mamba`](https://github.com/mamba-org/mamba/) (win/fail faster, better error messages):

```bash
mamba env update -n jupyter --file environment.yml

```

If you’re still seeing issues, try scaling back the dependencies and rebuild (e.g. start with just `jupyterlab` and `python`) in the attempt to bisect what might be causing the issue.

Some other things that would help:

- a (redacted) log of a minimal kernel startup/run that demonstrates the condition
- the output of `conda info` (or `mamba info`)
- the output of `conda list` (or `mamba list`)

---

<div class="post-metadata">

**Author:** ![luis](https://avatars.discourse-cdn.com/v4/letter/l/3e96dc/32.png) [@luis](https://discourse.jupyter.org/u/luis)\
**Post date:** [December 8, 2022, 11:51am UTC](https://discourse.jupyter.org/t/infinite-loading-when-importing-libraries/17152/5 "2022-12-08T11:51:50Z")

</div>

I’ve tried, and I get the same problem. First I created the environment using the environment.yml you recommended and then I dropped matplotlib-base to try with scikit-learn, but the never ending loading cell still happens when importing scikit.

Creating the environment with only jupyterlab and python, and then running %pip list or %conda list in an empty notebook, also has the same problem of a never ending cell.

I don’t know which logs to share tbh, as the terminal doesn’t print any errors, it seems everything is working as usual, so unless there’s a debug mode or sth I am not aware of, it just shows the usual logs of kernel started/restarted/shutdown when I request such actions from the notebook and the usual saves.

conda info

```auto
     active environment : jupyter
    active env location : /Users/johndoe/mambaforge/envs/jupyter
            shell level : 2
       user config file : /Users/johndoe/.condarc
 populated config files : /Users/johndoe/mambaforge/.condarc
          conda version : 22.11.1
    conda-build version : not installed
         python version : 3.10.6.final.0
       virtual packages : __archspec=1=arm64
                          __osx=13.0.1=0
                          __unix=0=0
       base environment : /Users/johndoe/mambaforge (writable)
      conda av data dir : /Users/johndoe/mambaforge/etc/conda
  conda av metadata url : None
           channel URLs : https://conda.anaconda.org/conda-forge/osx-arm64
                          https://conda.anaconda.org/conda-forge/noarch
          package cache : /Users/johndoe/mambaforge/pkgs
                          /Users/johndoe/.conda/pkgs
       envs directories : /Users/johndoe/mambaforge/envs
                          /Users/johndoe/.conda/envs
               platform : osx-arm64
             user-agent : conda/22.11.1 requests/2.28.1 CPython/3.10.6 Darwin/22.1.0 OSX/13.0.1
                UID:GID : 501:20
             netrc file : None
           offline mode : False

```

conda list

```auto
# packages in environment at /Users/johndoe/mambaforge/envs/jupyter:
#
# Name Version Build Channel
_ipython_minor_entry_point 8.7.0 hb6b4a82_0 conda-forge
anyio 3.6.2 pyhd8ed1ab_0 conda-forge
appnope 0.1.3 pyhd8ed1ab_0 conda-forge
argon2-cffi 21.3.0 pyhd8ed1ab_0 conda-forge
argon2-cffi-bindings 21.2.0 py310h8e9501a_3 conda-forge
asttokens 2.2.1 pyhd8ed1ab_0 conda-forge
attrs 22.1.0 pyh71513ae_1 conda-forge
babel 2.11.0 pyhd8ed1ab_0 conda-forge
backcall 0.2.0 pyh9f0ad1d_0 conda-forge
backports 1.0 pyhd8ed1ab_3 conda-forge
backports.functools_lru_cache 1.6.4 pyhd8ed1ab_0 conda-forge
beautifulsoup4 4.11.1 pyha770c72_0 conda-forge
bleach 5.0.1 pyhd8ed1ab_0 conda-forge
brotlipy 0.7.0 py310h8e9501a_1005 conda-forge
bzip2 1.0.8 h3422bc3_4 conda-forge
ca-certificates 2022.12.7 h4653dfc_0 conda-forge
certifi 2022.12.7 pyhd8ed1ab_0 conda-forge
cffi 1.15.1 py310h2399d43_2 conda-forge
charset-normalizer 2.1.1 pyhd8ed1ab_0 conda-forge
comm 0.1.1 pyhd8ed1ab_0 conda-forge
cryptography 38.0.4 py310hfc83b78_0 conda-forge
debugpy 1.6.4 py310h0f1eb42_0 conda-forge
decorator 5.1.1 pyhd8ed1ab_0 conda-forge
defusedxml 0.7.1 pyhd8ed1ab_0 conda-forge
entrypoints 0.4 pyhd8ed1ab_0 conda-forge
executing 1.2.0 pyhd8ed1ab_0 conda-forge
flit-core 3.8.0 pyhd8ed1ab_0 conda-forge
idna 3.4 pyhd8ed1ab_0 conda-forge
importlib-metadata 5.1.0 pyha770c72_0 conda-forge
importlib_resources 5.10.1 pyhd8ed1ab_0 conda-forge
ipykernel 6.19.0 pyh736e0ef_0 conda-forge
ipython 8.7.0 pyhd1c38e8_0 conda-forge
ipython_genutils 0.2.0 py_1 conda-forge
jedi 0.18.2 pyhd8ed1ab_0 conda-forge
jinja2 3.1.2 pyhd8ed1ab_1 conda-forge
json5 0.9.5 pyh9f0ad1d_0 conda-forge
jsonschema 4.17.3 pyhd8ed1ab_0 conda-forge
jupyter_client 7.4.8 pyhd8ed1ab_0 conda-forge
jupyter_core 5.1.0 py310hbe9552e_0 conda-forge
jupyter_events 0.5.0 pyhd8ed1ab_0 conda-forge
jupyter_server 2.0.0 pyhd8ed1ab_0 conda-forge
jupyter_server_terminals 0.4.2 pyhd8ed1ab_0 conda-forge
jupyterlab 3.5.1 pyhd8ed1ab_0 conda-forge
jupyterlab_pygments 0.2.2 pyhd8ed1ab_0 conda-forge
jupyterlab_server 2.16.3 pyhd8ed1ab_0 conda-forge
libcxx 14.0.6 h2692d47_0 conda-forge
libffi 3.4.2 h3422bc3_5 conda-forge
libsodium 1.0.18 h27ca646_1 conda-forge
libsqlite 3.40.0 h76d750c_0 conda-forge
libzlib 1.2.13 h03a7124_4 conda-forge
markupsafe 2.1.1 py310h8e9501a_2 conda-forge
matplotlib-inline 0.1.6 pyhd8ed1ab_0 conda-forge
mistune 2.0.4 pyhd8ed1ab_0 conda-forge
nbclassic 0.4.8 pyhd8ed1ab_0 conda-forge
nbclient 0.7.2 pyhd8ed1ab_0 conda-forge
nbconvert 7.2.6 pyhd8ed1ab_0 conda-forge
nbconvert-core 7.2.6 pyhd8ed1ab_0 conda-forge
nbconvert-pandoc 7.2.6 pyhd8ed1ab_0 conda-forge
nbformat 5.7.0 pyhd8ed1ab_0 conda-forge
ncurses 6.3 h07bb92c_1 conda-forge
nest-asyncio 1.5.6 pyhd8ed1ab_0 conda-forge
notebook 6.5.2 pyha770c72_1 conda-forge
notebook-shim 0.2.2 pyhd8ed1ab_0 conda-forge
openssl 3.0.7 h03a7124_1 conda-forge
packaging 21.3 pyhd8ed1ab_0 conda-forge
pandoc 2.19.2 hce30654_1 conda-forge
pandocfilters 1.5.0 pyhd8ed1ab_0 conda-forge
parso 0.8.3 pyhd8ed1ab_0 conda-forge
pexpect 4.8.0 pyh1a96a4e_2 conda-forge
pickleshare 0.7.5 py_1003 conda-forge
pip 22.3.1 pyhd8ed1ab_0 conda-forge
pkgutil-resolve-name 1.3.10 pyhd8ed1ab_0 conda-forge
platformdirs 2.5.2 pyhd8ed1ab_1 conda-forge
prometheus_client 0.15.0 pyhd8ed1ab_0 conda-forge
prompt-toolkit 3.0.36 pyha770c72_0 conda-forge
psutil 5.9.4 py310h8e9501a_0 conda-forge
ptyprocess 0.7.0 pyhd3deb0d_0 conda-forge
pure_eval 0.2.2 pyhd8ed1ab_0 conda-forge
pycparser 2.21 pyhd8ed1ab_0 conda-forge
pygments 2.13.0 pyhd8ed1ab_0 conda-forge
pyopenssl 22.1.0 pyhd8ed1ab_0 conda-forge
pyparsing 3.0.9 pyhd8ed1ab_0 conda-forge
pyrsistent 0.19.2 py310h8e9501a_0 conda-forge
pysocks 1.7.1 pyha2e5f31_6 conda-forge
python 3.10.8 h3ba56d0_0_cpython conda-forge
python-dateutil 2.8.2 pyhd8ed1ab_0 conda-forge
python-fastjsonschema 2.16.2 pyhd8ed1ab_0 conda-forge
python-json-logger 2.0.1 pyh9f0ad1d_0 conda-forge
python_abi 3.10 3_cp310 conda-forge
pytz 2022.6 pyhd8ed1ab_0 conda-forge
pyyaml 6.0 py310h8e9501a_5 conda-forge
pyzmq 24.0.1 py310hc407298_1 conda-forge
readline 8.1.2 h46ed386_0 conda-forge
requests 2.28.1 pyhd8ed1ab_1 conda-forge
send2trash 1.8.0 pyhd8ed1ab_0 conda-forge
setuptools 65.5.1 pyhd8ed1ab_0 conda-forge
six 1.16.0 pyh6c4a22f_0 conda-forge
sniffio 1.3.0 pyhd8ed1ab_0 conda-forge
soupsieve 2.3.2.post1 pyhd8ed1ab_0 conda-forge
stack_data 0.6.2 pyhd8ed1ab_0 conda-forge
terminado 0.17.1 pyhd1c38e8_0 conda-forge
tinycss2 1.2.1 pyhd8ed1ab_0 conda-forge
tk 8.6.12 he1e0b03_0 conda-forge
tomli 2.0.1 pyhd8ed1ab_0 conda-forge
tornado 6.2 py310h8e9501a_1 conda-forge
traitlets 5.6.0 pyhd8ed1ab_0 conda-forge
typing_extensions 4.4.0 pyha770c72_0 conda-forge
tzdata 2022g h191b570_0 conda-forge
urllib3 1.26.13 pyhd8ed1ab_0 conda-forge
wcwidth 0.2.5 pyh9f0ad1d_2 conda-forge
webencodings 0.5.1 py_1 conda-forge
websocket-client 1.4.2 pyhd8ed1ab_0 conda-forge
wheel 0.38.4 pyhd8ed1ab_0 conda-forge
xz 5.2.6 h57fd34a_0 conda-forge
yaml 0.2.5 h3422bc3_2 conda-forge
zeromq 4.3.4 hbdafb3b_1 conda-forge
zipp 3.11.0 pyhd8ed1ab_0 conda-forge

```

---

<div class="post-metadata">

**Author:** ![luis](https://avatars.discourse-cdn.com/v4/letter/l/3e96dc/32.png) [@luis](https://discourse.jupyter.org/u/luis)\
**Post date:** [December 13, 2022, 2:50pm UTC](https://discourse.jupyter.org/t/infinite-loading-when-importing-libraries/17152/6 "2022-12-13T14:50:30Z")

</div>

I’ve also tried to use a completely clean install of macOS, and then install mamba and create a Jupyter environment with this exact environment.yml

```auto
channels:
  - conda-forge
  - nodefaults
dependencies:
  - python >=3.10,<3.11
  - jupyterlab
  - numpy
  - scikit-learn
  - matplotlib-base

```

and I am having the same problem again, the terminal doesn’t show any error at all aside the usual logging when opening a notebook, shutting down a kernel or restarting it…

---

<div class="post-metadata">

**Author:** ![luis](https://avatars.discourse-cdn.com/v4/letter/l/3e96dc/32.png) [@luis](https://discourse.jupyter.org/u/luis)\
**Post date:** [December 27, 2022, 11:25am UTC](https://discourse.jupyter.org/t/infinite-loading-when-importing-libraries/17152/7 "2022-12-27T11:25:06Z")

</div>

If anyone is facing this issue, I downgraded to python 3.9 and I am no longer facing this problem.

---

<div class="post-metadata">

**Author:** ![Sachin\_Agrawal](https://yyz1.discourse-cdn.com/flex031/user_avatar/discourse.jupyter.org/sachin_agrawal/32/10768_2.png) [@Sachin\_Agrawal](https://discourse.jupyter.org/u/Sachin_Agrawal)\
**Post date:** [August 21, 2023, 11:37pm UTC](https://discourse.jupyter.org/t/infinite-loading-when-importing-libraries/17152/8 "2023-08-21T23:37:18Z")

</div>

I ran into the same issue today. Was there any other resolution other than a downgrade from python 3.10 to 3.9? This seems to be limited to Jupyter - imports are fine in python & ipython terminal sessions.

---

<div class="post-metadata">

**Author:** ![NJT145](https://yyz1.discourse-cdn.com/flex031/user_avatar/discourse.jupyter.org/njt145/32/14141_2.png) [@NJT145](https://discourse.jupyter.org/u/NJT145)\
**Post date:** [July 20, 2024, 8:42pm UTC](https://discourse.jupyter.org/t/infinite-loading-when-importing-libraries/17152/9 "2024-07-20T20:42:41Z")

</div>

I have the same issue with python 3.9 when I try to import a py file. It gets forever to import it.  
**Update:** it seems that I have this issue when I run vscode as user with my miniforge env installed for all users. It seems to be a permission issue.