Develop Reference

Why is Jupyter Notebook failing to load JavaScript (thinking, I am using JupyterLab)?

What I'm trying to do
I'm writing a Python (version==3.8.X) script for interactive visualization of molecules, which is working perfectly fine in VS Code but not in classical Jupyter Notebooks anymore (it did though just 2 weeks ago). For its practical use case with my employer it needs to be able to be run in Jupyter Notebook but it seems impossible for me to set Jupyter up the correct way on my personal machine (Arch Linux) as well as work stations at work (Ubuntu Linux) even though I've had both running fine lately.
Information I've collected
These are two screenshots of the outputs of the exact same cell (same file), when using Jupyter Notebook and here in VS Code.
Output of jupyter nbextension list:
Known nbextensions:
config dir: /home/lnrd/.jupyter/nbconfig
notebook section
nbextensions_configurator/config_menu/main enabled
- Validating: problems found:
- require? X nbextensions_configurator/config_menu/main
contrib_nbextensions_help_item/main enabled
- Validating: OK
jupyter-js-widgets/extension enabled
- Validating: OK
jupyterlab disabled
tree section
nbextensions_configurator/tree_tab/main enabled
- Validating: problems found:
- require? X nbextensions_configurator/tree_tab/main
config dir: /home/lnrd/.local/etc/jupyter/nbconfig
notebook section
ipyevents/extension enabled
- Validating: OK
nbextensions_configurator/config_menu/main enabled
- Validating: problems found:
- require? X nbextensions_configurator/config_menu/main
jupyter-js-widgets/extension enabled
- Validating: OK
tree section
nbextensions_configurator/tree_tab/main enabled
- Validating: problems found:
- require? X nbextensions_configurator/tree_tab/main
config dir: /etc/jupyter/nbconfig
notebook section
jupyter-js-widgets/extension enabled
- Validating: OK
Output of jupyter troubleshoot. I'm unsure about the meaning of the sys.<var> paths and where those are configured. I do understand $PATH, how it's configured and what it means for software in my OS. I guess pip list here is equal to py310 -m pip list.
I'm guessing the sys.<var> references the python kernel which Jupyter is running
I unsuccessfully tried setting up and using my py38 install as kernel (sys.version within the notebook then gave me 3.8.X) but errors had been the same
even with py38 as kernel, jupyter notebook --debug output (see below) had been looking for files in py310 directories. Maybe I've just made a mistake setting up the py38 kernel correctly but maybe not.
when using jupyter nbextension enable sometimes I've used the --py and --user flags and sometimes didn't - could this have been an issue?
$PATH:
/home/lnrd/bin
/usr/local/sbin
/usr/local/bin
/usr/sbin
/usr/bin
/sbin
/bin
/usr/games
/usr/local/games
/usr/bin/site_perl
/usr/bin/vendor_perl
/usr/bin/core_perl
/home/lnrd/.local/bin
sys.path:
/usr/bin
/usr/lib/python310.zip
/usr/lib/python3.10
/usr/lib/python3.10/lib-dynload
/home/lnrd/.local/lib/python3.10/site-packages
/usr/lib/python3.10/site-packages
sys.executable:
/usr/bin/python
sys.version:
3.10.9 (main, Dec 19 2022, 17:35:49) [GCC 12.2.0]
platform.platform():
Linux-6.1.8-arch1-1-x86_64-with-glibc2.36
which -a jupyter:
/usr/sbin/jupyter
/usr/bin/jupyter
/sbin/jupyter
/bin/jupyter
/home/lnrd/.local/bin/jupyter
pip list:
Package Version
--------------------------------- -----------
aiohttp 3.7.4.post0
aiohttp-retry 2.8.3
alabaster 0.7.13
amqp 5.1.1
antlr4-python3-runtime 4.9.3
anyio 3.6.2
anytree 2.8.0
appdirs 1.4.4
apptools 5.2.0
argon2-cffi 21.3.0
argon2-cffi-bindings 21.2.0
arrow 1.2.3
ase 3.22.1
astroid 2.13.3
asttokens 2.2.1
async-generator 1.10
async-timeout 3.0.1
asyncssh 2.12.0
atpublic 3.1.1
attrs 22.2.0
autocommand 2.2.2
autopep8 1.6.0
Babel 2.11.0
backcall 0.2.0
beautifulsoup4 4.11.1
billiard 3.6.4.0
bleach 6.0.0
breezy 3.3.2
Brlapi 0.8.4
btrfsutil 6.1.3
CacheControl 0.12.11
celery 5.2.7
certifi 2022.12.7
cffi 1.15.1
chardet 4.0.0
click 8.1.3
click-didyoumean 0.3.0
click-plugins 1.1.1
click-repl 0.2.0
colorama 0.4.6
comm 0.1.2
commonmark 0.9.1
configobj 5.1.0.dev0
contextlib2 21.6.0
cryptography 39.0.0
cssselect 1.2.0
cycler 0.11.0
Cython 0.29.33
debugpy 1.6.6
decorator 5.1.1
defusedxml 0.7.1
deprecation 2.1.0
dictdiffer 0.9.0
dill 0.3.6
discord 1.7.3
discord.py 1.7.3
diskcache 5.4.0
distlib 0.3.6
distro 1.8.0
dnspython 2.2.1
docutils 0.19
dpath 2.0.6
dscribe 1.2.2
dulwich 0.20.46
dvc-data 0.8.0
dvc-http 2.19.1
dvc-objects 0.2.2
dvc-render 0.0.10
dvc-task 0.1.2
dvclive 0.10.0
entrypoints 0.4
envisage 6.1.0
evdev 1.6.1
executing 1.2.0
fastbencode 0.1
fastjsonschema 2.16.2
flake8 4.0.1
flatten-dict 0.4.2
flufl.lock 7.1.1
fonttools 4.29.1
fqdn 1.5.1
fsspec 2022.8.2
funcy 1.17
future 0.18.2
gitdb 4.0.9
GitPython 3.1.27
grandalf 0.6
greenlet 1.1.2
html5lib 1.1
hydra-core 1.2.0
idna 3.4
imagesize 1.4.1
importlib-metadata 5.0.0
inflect 6.0.2
ipyevents 2.0.1
ipykernel 6.20.2
ipython 8.9.0
ipython-genutils 0.2.0
ipywidgets 8.0.4
isoduration 20.11.0
isort 5.11.4
jaraco.context 4.2.0
jaraco.functools 3.5.2
jaraco.text 3.11.0
jedi 0.18.2
Jinja2 3.1.2
joblib 1.2.0
json5 0.9.12
jsonpointer 2.3
jsonschema 4.17.3
jupyter 1.0.0
jupyter_client 8.0.1
jupyter-console 6.4.4
jupyter-contrib-core 0.4.2
jupyter_core 5.1.5
jupyter-events 0.6.3
jupyter-nbextensions-configurator 0.6.1
jupyter_packaging 0.12.3
jupyter-server 1.23.5
jupyter_server_terminals 0.4.4
jupyterlab 3.5.3
jupyterlab-pygments 0.2.2
jupyterlab_server 2.19.0
jupyterlab-widgets 3.0.5
kiwisolver 1.3.2
kombu 5.2.4
lazy-object-proxy 1.9.0
ledfx 0.10.7
lensfun 0.3.3
libfdt 1.6.1
lit 15.0.7.dev0
llvmlite 0.39.1
louis 3.24.0
lxml 4.9.2
Markdown 3.4.1
markdown-it-py 2.1.0
MarkupSafe 2.1.2
matplotlib 3.5.1
matplotlib-inline 0.1.6
mayavi 4.8.1
mccabe 0.6.1
mdurl 0.1.2
merge3 0.0.12
meson 1.0.0
mistune 2.0.4
more-itertools 9.0.0
msgpack 1.0.4
multidict 6.0.2
mypy 0.942
mypy-extensions 0.4.3
nanotime 0.5.2
natsort 8.1.0
nbclassic 0.5.1
nbclient 0.7.2
nbconvert 7.2.9
nbformat 5.7.3
nest-asyncio 1.5.6
netsnmp-python 1.0a1
networkx 2.8.6
notebook 6.5.2
notebook_shim 0.2.2
nspektr 0.4.0
numba 0.56.4
numpy 1.22.4
omegaconf 2.2.3
ordered-set 4.1.0
packaging 23.0
pandas 1.5.1
pandocfilters 1.5.0
parso 0.8.3
pathspec 0.9.0
patiencediff 0.2.12
pep517 0.13.0
pexpect 4.8.0
pickleshare 0.7.5
Pillow 9.4.0
pip 22.3.1
platformdirs 2.6.2
pluggy 1.0.0
ply 3.11
progress 1.6
prometheus-client 0.16.0
prompt-toolkit 3.0.36
psutil 5.9.4
ptyprocess 0.7.0
pure-eval 0.2.2
pwquality 1.4.5
py3Dmol 1.8.1
PyAudio 0.2.11
pybind11 2.10.1
pycairo 1.23.0
pycodestyle 2.10.0
pycparser 2.21
pydantic 1.10.4
pydocstyle 6.1.1
pydot 1.4.2
pyface 7.4.2
pyflakes 3.0.1
pygit2 1.10.1
Pygments 2.14.0
PyGObject 3.42.2
pygtrie 2.5.0
pylint 2.15.10
pyls-isort 0.2.2
pylsp-mypy 0.5.7
PyNaCl 1.5.0
pynvim 0.4.3
pyOpenSSL 23.0.0
pyparsing 3.0.9
PyQt5 5.15.6
PyQt5-Qt5 5.15.2
PyQt5-sip 12.9.1
PyQt6 6.4.1
PyQt6-sip 13.4.1
pyqtgraph 0.13.1
pyrsistent 0.19.3
python-dateutil 2.8.2
python-dotenv 0.20.0
python-json-logger 2.0.4
python-lsp-jsonrpc 1.0.0
python-lsp-server 1.4.1
python-xlib 0.31
pytz 2022.7
pyxdg 0.28
PyYAML 6.0
pyzmq 25.0.0
qtconsole 5.4.0
QtPy 2.3.0
rdkit 2022.9.3
requests 2.28.1
requests-unixsocket 0.3.0
resolvelib 0.9.0
retrying 1.3.3
rfc3339-validator 0.1.4
rfc3986-validator 0.1.1
rfc3987 1.3.8
rich 13.3.1
rope 1.0.0
ruamel.yaml 0.17.21
ruamel.yaml.clib 0.2.6
scikit-learn 1.1.3
scipy 1.8.0
scmrepo 0.1.1
Send2Trash 1.8.0
setproctitle 1.3.2
setuptools 65.6.3
shiboken6 6.4.2
shiboken6-generator 6.4.2
shortuuid 1.0.9
shtab 1.5.5
simplejson 3.18.0
six 1.16.0
smmap 5.0.0
sniffio 1.3.0
snowballstemmer 2.2.0
soupsieve 2.3.2.post1
sparse 0.13.0
Sphinx 5.3.0
sphinxcontrib-applehelp 1.0.4
sphinxcontrib-devhelp 1.0.2
sphinxcontrib-htmlhelp 2.0.0
sphinxcontrib-jsmath 1.0.1
sphinxcontrib-qthelp 1.0.3
sphinxcontrib-serializinghtml 1.1.5
stack-data 0.6.2
tabulate 0.8.10
TBB 0.2
team 1.0
tenacity 8.1.0
terminado 0.17.1
terminator 2.1.2
testpath 0.6.0
threadpoolctl 3.1.0
tinycss2 1.2.1
toml 0.10.2
tomli 2.0.1
tomlkit 0.11.6
tornado 6.2
tqdm 4.64.1
traitlets 5.8.1
traits 6.4.1
traitsui 7.4.2
trove-classifiers 2023.1.20
typing_extensions 4.4.0
uc-micro-py 1.0.1
ujson 5.2.0
uri-template 1.2.0
urllib3 1.26.12
validate 5.1.0.dev0
validate-pyproject 0.12.1
vimiv 0.8.0
vine 5.0.0
voluptuous 0.13.1
vtk 9.2.2
wcwidth 0.2.6
webcolors 1.12
webencodings 0.5.1
websocket-client 1.5.0
wheel 0.38.4
widgetsnbextension 4.0.5
wrapt 1.14.1
wslink 1.9.1
wxPython 4.2.0
yapf 0.32.0
yarl 1.7.2
youtube-dl 2021.12.17
zc.lockfile 2.0
zipp 3.12.0
Output of jupyter notebook --debug shows this one line containing status 404. I suspect this should lead me somewhere but I'm unsure what to do with this information:
[W <time> NotebookApp] 404 GET /static/components/marked/lib/marked.js (127.0.0.1) 34.030000ms referer=http://localhost:8888/tree
What I've tried to fix this
gone through all config files in all jupyter --paths to check if jupyter-js-widgets=true
Used py38 and py310 kernels
with <py> as py38=/usr/bin/python3.8 and py310=/usr/bin/python3.10 i have
<py> -m pip install --upgrade jupyter notebook ipywidgets widgetsnbextension jupyter_contrib_nbextensions jupyter-js-widgets-nbextension
<py> -m pip install --force-reinstall jupyter notebook ipywidgets widgetsnbextension jupyter_contrib_nbextensions jupyter-js-widgets-nbextension
executing jupyter contrib nbextension install
disabling and enabling different jupyter nbextensions
JupyterLab
pip installing JupyterLab, enabling it and executing jupyterlab extension install py3dmol as suggested by error message from screenshot
uninstalling and disabling JupyterLab again because I hadn't used it when the code ran in Jupyter Notebook originally

Python traitlets package warring and permission denied in vscode interactive windows

OS: Arch linux(termux proot)
Python version: 3.10.8
My error message as follow
Visual Studio Code (1.73.1, undefined, desktop)
Jupyter Extension Version: 2022.9.1303220346.
Python Extension Version: 2022.18.2.
Workspace folder /home/jack/Documents/Medical-segmentation
info 15:00:11.430: ZMQ install verified.
User belongs to experiment group 'jupyterTestcf'
User belongs to experiment group 'jupyterEnhancedDataViewer'
info 15:00:12.217: LSP Notebooks experiment is disabled -- not in treatment group
info 15:00:13.731: Got empty env vars with python /bin/python in 1275ms
info 15:00:13.731: Got env vars ourselves faster /bin/python with env var count 59 in 1276ms
info 15:00:13.768: Process Execution: > /bin/python -m pip list
> /bin/python -m pip list
info 15:00:22.102: Starting interactive window for resource '/home/jack/Documents/Medical-segmentation/snakes/example2.py'
info 15:00:22.512: Preferred Remote kernel for Interactive-1.interactive is undefined
info 15:00:25.004: Process Execution: > /bin/python ~/.vscode/extensions/ms-toolsai.jupyter-2022.9.1303220346/pythonFiles/normalizeSelection.py
> /bin/python ~/.vscode/extensions/ms-toolsai.jupyter-2022.9.1303220346/pythonFiles/normalizeSelection.py
info 15:00:25.022: Starting Jupyter Session startUsingPythonInterpreter, .jvsc74a57bd0e7370f93d1d0cde622a1f8e1c04877d8463912d04d973331ad4851f04de6915a./bin/python./bin/python.-m#ipykernel_launcher (Python Path: , EnvType: Global, EnvName: '', Version: 3.10.8) for 'Interactive-1.interactive' (disableUI=false)
info 15:00:25.024: Computing working directory for resource '/home/jack/Documents/Medical-segmentation/snakes/example2.py'
info 15:00:25.054: Got env vars ourselves faster /bin/python with env var count 59 in 2ms
info 15:00:25.108: Process Execution: > /bin/python -c "import ipykernel; print(ipykernel.__version__); print("5dc3a68c-e34e-4080-9c3e-2a532b2ccb4d"); print(ipykernel.__file__)"
> /bin/python -c "import ipykernel; print(ipykernel.__version__); print("5dc3a68c-e34e-4080-9c3e-2a532b2ccb4d"); print(ipykernel.__file__)"
info 15:00:25.266: Got env vars ourselves faster /bin/python with env var count 59 in 14ms
info 15:00:25.266: Got env vars ourselves faster /bin/python with env var count 59 in 6ms
info 15:00:25.308: Process Execution: > /bin/python -m ipykernel_launcher --ip=127.0.0.1 --stdin=9003 --control=9001 --hb=9000 --Session.signature_scheme="hmac-sha256" --Session.key=b"a946baa0-e0d4-41d4-b72d-1eed7330e6f9" --shell=9002 --transport="tcp" --iopub=9004 --f=/home/jack/.local/share/jupyter/runtime/kernel-v2-32230pKMrdOglR18w.json
> /bin/python -m ipykernel_launcher --ip=127.0.0.1 --stdin=9003 --control=9001 --hb=9000 --Session.signature_scheme="hmac-sha256" --Session.key=b"a946baa0-e0d4-41d4-b72d-1eed7330e6f9" --shell=9002 --transport="tcp" --iopub=9004 --f=/home/jack/.local/share/jupyter/runtime/kernel-v2-32230pKMrdOglR18w.json
info 15:00:25.308: Process Execution: cwd: ~/Documents/Medical-segmentation/snakes
cwd: ~/Documents/Medical-segmentation/snakes
info 15:00:25.823: Registering dummy command feature
info 15:00:27.946: ipykernel version & path 6.18.0, /usr/lib/python3.10/site-packages/ipykernel/__init__.py for /bin/python
info 15:00:29.175: Got empty env vars with python /bin/python in 4123ms
info 15:00:29.176: Got empty env vars with python /bin/python in 3924ms
info 15:00:29.176: Got empty env vars with python /bin/python in 3916ms
warn 15:00:33.920: StdErr from Kernel Process /usr/lib/python3.10/site-packages/traitlets/traitlets.py:2412: FutureWarning: Supporting extra quotes around strings is deprecated in traitlets 5.0. You can use 'hmac-sha256' instead of '"hmac-sha256"' if you require traitlets >=5.
warn(
warn 15:00:33.921: StdErr from Kernel Process /usr/lib/python3.10/site-packages/traitlets/traitlets.py:2366: FutureWarning: Supporting extra quotes around Bytes is deprecated in traitlets 5.0. Use 'a946baa0-e0d4-41d4-b72d-1eed7330e6f9' instead of 'b"a946baa0-e0d4-41d4-b72d-1eed7330e6f9"'.
warn(
warn 15:00:33.964: StdErr from Kernel Process Permission denied (src/ip_resolver.cpp:542)
error 15:00:33.979: Disposing kernel process due to an error o [Error]: The kernel died. Error: /usr/lib/python3.10/site-packages/traitlets/traitlets.py:2412: FutureWarning: Supporting extra quotes around strings is deprecated in traitlets 5.0. You can use 'hmac-sha256' instead of '"hmac-sha256"' if you require traitlets >=5.
warn(
/usr/lib/python3.10/site-packages/traitlets/traitlets.py:2366: FutureWarning: Supporting extra quotes around Bytes is deprecated in traitlets 5.0. Use 'a946baa0-e0d4-41d4-b72d-1eed7330e6f9' instead of 'b"a946baa0-e0d4-41d4-b72d-1eed7330e6f9"'.
warn(
Permission denied (src/ip_resolver.cpp:542)... View Jupyter [log](command:jupyter.viewOutput) for further details.
at ChildProcess.<anonymous> (/home/jack/.vscode/extensions/ms-toolsai.jupyter-2022.9.1303220346/out/extension.node.js:2:2195101)
at ChildProcess.emit (node:events:538:35)
at Process.ChildProcess._handle.onexit (node:internal/child_process:291:12) {
category: 'kerneldied',
kernelConnectionMetadata: {
kind: 'startUsingPythonInterpreter',
kernelSpec: {
specFile: '/home/jack/.vscode/extensions/ms-toolsai.jupyter-2022.9.1303220346/temp/jupyter/kernels/python3108jvsc74a57bd0e7370f93d1d0cde622a1f8e1c04877d8463912d04d973331ad4851f04de6915a/kernel.json',
interpreterPath: '/bin/python',
isRegisteredByVSC: 'registeredByNewVersionOfExt',
name: 'python3108jvsc74a57bd0e7370f93d1d0cde622a1f8e1c04877d8463912d04d973331ad4851f04de6915a',
argv: [Array],
language: 'python',
executable: 'python',
display_name: 'Python 3.10.8 64-bit',
metadata: [Object],
env: {}
},
I encounter this error message but I does not have any issue in another termux proot system. I remove all python and packages and reinstall. It didn't work for me.
11/24 updated:
It's weird because I look to another system by using pip list. It's the same version with I currently use system.
Package Version
---------------------- -----------
aiohttp 3.8.3
aiohttp-socks 0.7.1
aiorpcX 0.22.1
aiosignal 1.2.0
anyio 3.6.2
appdirs 1.4.4
argon2-cffi 21.3.0
argon2-cffi-bindings 21.2.0
asttokens 2.1.0
async-generator 1.10
async-timeout 4.0.2
attrs 22.1.0
autocommand 2.2.2
Babel 2.11.0
backcall 0.2.0
beautifulsoup4 4.11.1
bitstring 3.1.9
black 22.10.0
bleach 5.0.1
build 0.9.0
certifi 2022.9.24
cffi 1.15.1
chardet 5.0.0
charset-normalizer 3.0.0
click 8.1.3
codespell 0.0.0
comm 0.1.0
commonmark 0.9.1
contourpy 1.0.6
cryptography 38.0.1
cycler 0.11.0
Cython 0.29.32
debugpy 1.6.3
decorator 5.1.1
defusedxml 0.7.1
deprecation 2.1.0
dnspython 2.2.1
docopt 0.6.2
docutils 0.19
ecdsa 0.18.0
Electrum 4.3.1
entrypoints 0.4
executing 1.2.0
fastjsonschema 2.16.2
flake8 5.0.4
flake8-black 0.3.3
flake8-isort 5.0.0
fonttools 4.38.0
frozenlist 1.3.1
future 0.18.2
greenlet 1.1.3.post0
idna 3.4
imageio 2.22.4
imutils 0.5.4
inflect 6.0.2
installer 0.5.1
ipykernel 6.18.0
ipython 8.6.0
ipython-genutils 0.2.0
isort 5.10.1
jaraco.context 4.1.2
jaraco.functools 3.5.2
jaraco.text 3.11.0
jedi 0.18.1
Jinja2 3.1.2
json5 0.9.10
jsonrpclib-pelix 0.4.3.2
jsonschema 4.17.1
jupyter_client 7.4.7
jupyter_core 5.0.0
jupyter_packaging 0.12.3
jupyter-server 1.23.3
jupyterlab 3.5.0
jupyterlab-pygments 0.2.2
jupyterlab_server 2.16.3
kiwisolver 1.4.4
lxml 4.9.1
mackup 0.8.36
markdown-it-py 2.1.0
MarkupSafe 2.1.1
matplotlib 3.6.2
matplotlib-inline 0.1.6
mccabe 0.7.0
mdurl 0.1.2
mistune 2.0.4
more-itertools 9.0.0
msgpack 1.0.4
multidict 6.0.2
mypy-extensions 0.4.3
mysql-connector-python 8.0.31
nbclassic 0.4.8
nbclient 0.7.0
nbconvert 7.2.5
nbformat 5.7.0
nest-asyncio 1.5.6
networkx 2.8.8
nibabel 4.0.2
notebook 6.5.2
notebook_shim 0.2.2
numpy 1.23.4
ordered-set 4.1.0
packaging 21.3
pandas 1.5.1
pandocfilters 1.5.0
parso 0.8.3
pathspec 0.10.1
pbkdf2 1.3
pep517 0.13.0
pexpect 4.8.0
pickleshare 0.7.5
pikaur 1.13
Pillow 9.3.0
pip 22.3
platformdirs 2.5.2
pluggy 1.0.0
ply 3.11
portalocker 2.6.0
progressbar2 4.2.0
prometheus-client 0.15.0
prompt-toolkit 3.0.33
protobuf 4.21.7
psutil 5.9.4
ptyprocess 0.7.0
pure-eval 0.2.2
pyaes 1.6.1
pyalpm 0.10.6
pycodestyle 2.9.1
pycparser 2.21
pycryptodomex 3.12.0
pydantic 1.10.2
pyflakes 2.5.0
Pygments 2.13.0
pynvim 0.4.3
pyparsing 3.0.9
PyQt5 5.15.7
PyQt5-sip 12.11.0
pyrsistent 0.19.2
PySocks 1.7.1
python-dateutil 2.8.2
python-dotenv 0.21.0
python-lsp-jsonrpc 1.0.0
python-lsp-server 1.5.0
python-socks 2.0.3
python-utils 3.4.5
pytz 2022.5
pytz-deprecation-shim 0.1.0.post0
PyWavelets 1.4.1
pyzmq 24.0.1
qrcode 7.3.1
regex 2022.10.31
requests 2.28.1
requests-unixsocket 0.3.0
ruamel.yaml 0.17.21
ruamel.yaml.clib 0.2.7
scikit-image 0.19.3
scipy 1.9.3
Send2Trash 1.8.0
setuptools 63.2.0
Shapely 1.8.2
six 1.16.0
sniffio 1.3.0
soupsieve 2.3.2.post1
SQLAlchemy 1.4.43
stack-data 0.6.1
TBB 0.2
terminado 0.17.0
testpath 0.6.0
tifffile 2022.10.10
tinycss2 1.2.1
toml 0.10.2
tomli 2.0.1
tomlkit 0.11.6
tornado 6.2
traitlets 5.5.0
trove-classifiers 2022.10.19
typing_extensions 4.4.0
tzdata 2022.6
tzlocal 4.2
uc-micro-py 1.0.1
ujson 5.5.0
urllib3 1.26.12
validate-pyproject 0.10.1
wcwidth 0.2.5
webencodings 0.5.1
websocket-client 1.4.1
wheel 0.37.1
yarl 1.8.1

Open your vscode and reinstall the Python and Jupyter Notebook extensions.
Reinstall ipykernel package in the terminal.
At the same time, this issue also proposes other solutions.
Added:
I encountered the same problem with traitlets==4.3.3. I updated it by using pip install traitlets and it's version is 5.5.0 to solve this problem.

I didn't find a way to fix this within Arch itself, but I believe it has something to do with how Arch saves sockets to systemd, which is not accessible in proot, thus the permission denied error. However, as termux can run ipykernel successfully, and you have access to termux directories in proot arch, you can simply do this:
create venv in termux home: python -m venv env-name
activate venv in termux: source ~/env-name/bin/activate
install ipykernel: pip install ipykernel
activate venv in arch: source /data/data/com.termux/files/home/env-name/bin/activate
add venv as kernel: python -m ipykernel install --user --name env-name
select kernel in vscode

Ipympl outputs "Error displaying widget: model not found" when running Jupyter Lab in a pipenv

OS: Ubuntu 18.04.6 LTS
Installation:
After running into this issue trying to use pipenv install jupyterlab, I install everything using pip install from within a fresh pipenv shell using Python 3.8.0.
pipenv shell
pip install --upgrade pip
pip install numpy matplotlib jupyterlab ipympl
You can find the Jupyter Lab install doc here.
Running pip list outputs:
Package Version
-------------------- ---------
anyio 3.5.0
argon2-cffi 21.3.0
argon2-cffi-bindings 21.2.0
asttokens 2.0.5
attrs 21.4.0
Babel 2.9.1
backcall 0.2.0
black 21.12b0
bleach 4.1.0
certifi 2021.10.8
cffi 1.15.0
charset-normalizer 2.0.10
click 8.0.3
cycler 0.11.0
debugpy 1.5.1
decorator 5.1.1
defusedxml 0.7.1
entrypoints 0.3
executing 0.8.2
fonttools 4.28.5
idna 3.3
importlib-resources 5.4.0
ipykernel 6.7.0
ipympl 0.8.7
ipython 8.0.1
ipython-genutils 0.2.0
ipywidgets 7.6.5
jedi 0.18.1
Jinja2 3.0.3
json5 0.9.6
jsonschema 4.4.0
jupyter-client 7.1.1
jupyter-core 4.9.1
jupyter-server 1.13.3
jupyterlab 3.2.8
jupyterlab-pygments 0.1.2
jupyterlab-server 2.10.3
jupyterlab-widgets 1.0.2
kiwisolver 1.3.2
MarkupSafe 2.0.1
matplotlib 3.5.1
matplotlib-inline 0.1.3
mistune 0.8.4
mypy-extensions 0.4.3
nbclassic 0.3.5
nbclient 0.5.10
nbconvert 6.4.0
nbformat 5.1.3
nest-asyncio 1.5.4
notebook 6.4.7
numpy 1.22.1
packaging 21.3
pandocfilters 1.5.0
parso 0.8.3
pathspec 0.9.0
pexpect 4.8.0
pickleshare 0.7.5
Pillow 9.0.0
pip 21.3.1
pkg_resources 0.0.0
platformdirs 2.4.1
prometheus-client 0.12.0
prompt-toolkit 3.0.24
ptyprocess 0.7.0
pure-eval 0.2.1
pycparser 2.21
Pygments 2.11.2
pyparsing 3.0.7
pyrsistent 0.18.1
python-dateutil 2.8.2
pytz 2021.3
pyzmq 22.3.0
requests 2.27.1
Send2Trash 1.8.0
setuptools 60.5.0
six 1.16.0
sniffio 1.2.0
stack-data 0.1.4
terminado 0.12.1
testpath 0.5.0
tomli 1.2.3
tornado 6.1
traitlets 5.1.1
typing_extensions 4.0.1
urllib3 1.26.8
wcwidth 0.2.5
webencodings 0.5.1
websocket-client 1.2.3
wheel 0.37.1
widgetsnbextension 3.5.2
zipp 3.7.0
Notably jupyterlab==3.2.8, matplotlib==3.5.1 and ipympl==0.8.7 satisfy the version lookup table
Now running jupyter lab --ip 0.0.0.0 --no-browser from inside the pipenv shell (--ip 0.0.0.0 --no-browser because I'm accessing the notebook on a different machine).
Opening a new notebook with the default Python 3 (ipykernel) kernel, creating two cells
from matplotlib import pyplot as plt
import ipympl # Confirming it is being found by the kernel
%matplotlib widget
# Example found from https://stackoverflow.com/questions/50149562/jupyterlab-interactive-plot
plt.figure()
x = [1,2,3]
y = [4,5,6]
plt.plot(x,y)
plt.show()
Running both cells gives me the common Error message:
Error displaying widget: model not found
What I've already tried:
This question
Where I downgrade:
ipywidgets==7.0.0
ipympl==0.2.1
matplotlib==3.2.0
And install
jupyter labextension install jupyter-matplotlib#0.3.0
No change, same error.
Edit: Using Jupyter Notebook instead of of Jupyter Lab, which means pip install jupyter instead of jupyterlab fixes the issue.
Its what I'll do in lieu of an answer here, but would still like to know if anyone has a straightforward fix for Jupyter Lab.

Error "Numpy.ndarray size changed, may indicate binary incompatibility. Expected 88 from C header, got 80 from PyObject."

I got this error file while following this tutorial: https://www.youtube.com/watch?v=yqkISICHH-U
So far I have created a training dataset to feed into Tensorflow. I am using transfer learning on one of the pre-trained TensorFlow object recognition models. I get the error when I attempt to train the model with my new dataset. This is a picture of the full error message that shows up.
I attempted to solve the problem by trying the following:
Reinstalling Numpy
Installing Numpy 1.20.x
Installing Numpy 1.18.x
Reinstalling pycocotools
When I installed Numpy 1.20.x the error went away and was replaced with a separate error: notimplementederror: cannot convert a symbolic Tensor (cond_2/strided:0) to a numpy array. This seemed to be a compatibility issue between Tensorflow and Numpy 1.20.x. When debugging this error, I found that everyone solved it by downgrading their Numpy to 1.19.x. However, in my case I am still left with the first error.
I am using python 3.8.9 with anaconda.
Here are the packages I have installed: https://pastebin.com/BNW8tU2A
(tfod) (base) C:\Users\piper\python\Tensorflow\TFODCourse>pip list
Package Version Location
----------------------- ------------------- ---------------------------------------------------------------------------
absl-py 0.13.0
astunparse 1.6.3
backcall 0.2.0
cachetools 4.2.2
certifi 2021.5.30
charset-normalizer 2.0.3
colorama 0.4.4
cycler 0.10.0
Cython 0.29.24
debugpy 1.3.0
decorator 5.0.9
flatbuffers 1.12
gast 0.4.0
gin-config 0.4.0
google-auth 1.33.1
google-auth-oauthlib 0.4.4
google-cloud-bigquery 1.21.0
google-pasta 0.2.0
grpcio 1.34.1
h5py 3.1.0
idna 3.2
ipykernel 6.0.3
ipython 7.25.0
ipython-genutils 0.2.0
jedi 0.18.0
jupyter-client 6.1.12
jupyter-core 4.7.1
keras-nightly 2.5.0.dev2021032900
Keras-Preprocessing 1.1.2
kiwisolver 1.3.1
lvis 0.5.3
lxml 4.6.3
Markdown 3.3.4
matplotlib 3.2.0
matplotlib-inline 0.1.2
numpy 1.19.5
oauthlib 3.1.1
object-detection 0.1
opencv-python 4.5.3.56
opt-einsum 3.3.0
pandas 1.3.0
parso 0.8.2
pickleshare 0.7.5
Pillow 8.3.1
pip 21.1.3
prompt-toolkit 3.0.19
protobuf 3.17.3
pyasn1 0.4.8
pyasn1-modules 0.2.8
pycocotools 2.0.2
Pygments 2.9.0
pyparsing 2.4.7
PyQt5 5.15.4
PyQt5-Qt5 5.15.2
PyQt5-sip 12.9.0
python-dateutil 2.8.2
pytz 2021.1
pywin32 225
PyYAML 5.4.1
pyzmq 22.1.0
requests 2.26.0
requests-oauthlib 1.3.0
rsa 4.7.2
scipy 1.7.0
setuptools 49.2.1
six 1.15.0
slim 0.1 c:\users\piper\python\tensorflow\tfodcourse\tensorflow\models\research\slim
tensorboard 2.5.0
tensorboard-data-server 0.6.1
tensorboard-plugin-wit 1.8.0
tensorflow 2.5.0
tensorflow-addons 0.13.0
tensorflow-estimator 2.5.0
tensorflow-gpu 2.5.0
termcolor 1.1.0
tf-models-official 2.5.0
tf-slim 1.1.0
tornado 6.1
traitlets 5.0.5
typeguard 2.12.1
typing-extensions 3.7.4.3
urllib3 1.26.6
wcwidth 0.2.5
Werkzeug 2.0.1
wget 3.2
wheel 0.36.2
wrapt 1.12.1
Any help would be appreciated!
So I solved the issue by reinstalling pycocotools with the --no-cache-dir flag. So I did:
pip uninstall pycocotools
pip install --no-cache-dir pycocotools
This completely solved the issue.

I had the same problem with python3.6 in a virtual environment.
Reinstalling with the --no-cache-dir flag didn't solve the problem.
I solved the problem by starting from fresh in a virtual environment with python3.7

Why does my jupyter kernel die running in a virtual environment when importing numpy?

I am working in a virtual environment that I set up using conda. What I would like to do is open up a new Jupyter notebook and work within the notebook using this virtual environment. However, I think I am missing some sort of necessary package within my virtual environment.
When I launch Jupyter notebook from Terminal (currently using OSX 10.13.6), I can see the option to open a new notebook with the Python (virtualEnvironment) in the New button at the top right of the screen.
When I open a new notebook as Python (virtualEnvironment), everything looks good, so I try to run the following in the first cell:
import numpy as np
I get the following error message in Jupyter as a pop-up window:
Kernal restarting: The kernel appears to have died. It will restart automatically.
I know that some aspects of the Jupyter notebook are working because I can run the following in the first cell, no problem:
from IPython.display import display, Math
display(Math('\\text{This is latex formatting:} \\quad x + 2y = 3j + 4'))
Does anyone have any ideas about what might be causing the kernel to die?
Here are all of the packages in the virtual envronment:
# packages in environment at /opt/anaconda3/envs/virtualEnvironment:
#
# Name Version Build Channel
appnope 0.1.0 py37_0
attrs 19.3.0 py_0 conda-forge
backcall 0.1.0 py37_0
blas 1.0 mkl
bleach 3.1.5 pyh9f0ad1d_0 conda-forge
brotlipy 0.7.0 py37h9bfed18_1000 conda-forge
ca-certificates 2020.4.5.1 hecc5488_0 conda-forge
certifi 2020.4.5.1 py37hc8dfbb8_0 conda-forge
cffi 1.14.0 py37h356ff06_0 conda-forge
chardet 3.0.4 py37hc8dfbb8_1006 conda-forge
cryptography 2.9.2 py37he655712_0 conda-forge
decorator 4.4.2 py_0
defusedxml 0.6.0 py_0 conda-forge
entrypoints 0.3 py37_0
idna 2.9 py_1 conda-forge
importlib-metadata 1.6.0 py37hc8dfbb8_0 conda-forge
importlib_metadata 1.6.0 0 conda-forge
intel-openmp 2019.4 233
ipykernel 5.1.4 py37h39e3cac_0
ipython 7.13.0 py37h5ca1d4c_0
ipython_genutils 0.2.0 py37_0
jedi 0.17.0 py37_0
jinja2 2.11.2 pyh9f0ad1d_0 conda-forge
json5 0.9.0 py_0 conda-forge
jsonschema 3.2.0 py37hc8dfbb8_1 conda-forge
jupyter_client 6.1.3 py_0
jupyter_core 4.6.3 py37_0
jupyterlab 2.1.2 py_0 conda-forge
jupyterlab_server 1.1.1 py_0 conda-forge
libcxx 4.0.1 hcfea43d_1
libcxxabi 4.0.1 hcfea43d_1
libedit 3.1.20181209 hb402a30_0
libffi 3.2.1 h6de7cb9_1006 conda-forge
libgfortran 3.0.1 h93005f0_2
libsodium 1.0.16 h3efe00b_0
markupsafe 1.1.1 py37h9bfed18_1 conda-forge
mistune 0.8.4 py37h9bfed18_1001 conda-forge
mkl 2019.4 233
mkl-service 2.3.0 py37hfbe908c_0
mkl_fft 1.0.15 py37h5e564d8_0
mkl_random 1.1.0 py37ha771720_0
nbconvert 5.6.1 py37hc8dfbb8_1 conda-forge
nbformat 5.0.6 py_0 conda-forge
ncurses 6.2 h0a44026_1
notebook 6.0.3 py37_0 conda-forge
numpy 1.18.1 py37h7241aed_0
numpy-base 1.18.1 py37h6575580_1
openssl 1.1.1g h0b31af3_0 conda-forge
packaging 20.1 py_0 conda-forge
pandas 1.0.3 py37h6c726b0_0
pandoc 2.9.2.1 0 conda-forge
pandocfilters 1.4.2 py_1 conda-forge
parso 0.7.0 py_0
patsy 0.5.1 py37_0
pexpect 4.8.0 py37_0
pickleshare 0.7.5 py37_0
pip 20.0.2 py37_1
prometheus_client 0.7.1 py_0 conda-forge
prompt-toolkit 3.0.4 py_0
prompt_toolkit 3.0.4 0
ptyprocess 0.6.0 py37_0
pycparser 2.20 py_0 conda-forge
pygments 2.6.1 py_0
pyopenssl 19.1.0 py_1 conda-forge
pyparsing 2.4.7 pyh9f0ad1d_0 conda-forge
pyrsistent 0.16.0 py37h9bfed18_0 conda-forge
pysocks 1.7.1 py37hc8dfbb8_1 conda-forge
python 3.7.7 hc70fcce_0_cpython
python-dateutil 2.8.1 py_0
python_abi 3.7 1_cp37m conda-forge
pytz 2020.1 py_0
pyzmq 18.1.1 py37h0a44026_0
readline 8.0 h1de35cc_0
requests 2.23.0 pyh8c360ce_2 conda-forge
scipy 1.2.1 py37h1410ff5_0
send2trash 1.5.0 py_0 conda-forge
setuptools 46.1.3 py37_0
six 1.14.0 py37_0
sqlite 3.31.1 h5c1f38d_1
statsmodels 0.11.0 py37h1de35cc_0
terminado 0.8.3 py37hc8dfbb8_1 conda-forge
testpath 0.4.4 py_0 conda-forge
tk 8.6.8 ha441bb4_0
tornado 6.0.4 py37h1de35cc_1
traitlets 4.3.3 py37_0
urllib3 1.25.9 py_0 conda-forge
wcwidth 0.1.9 py_0
webencodings 0.5.1 py_1 conda-forge
wheel 0.34.2 py37_0
xz 5.2.5 h1de35cc_0
zeromq 4.3.1 h0a44026_3
zipp 3.1.0 py_0 conda-forge
zlib 1.2.11 h1de35cc_3
I previously tried to solve this problem using the answers from this question: Conda environments not showing up in Jupyter Notebook. I cannot figure out what the problem is in my current situation.
Other information that might be valuable: if I start a new Jupyter notebook in my normal environment, numpy imports just fine. This is the first moment when I have had a problem with the kernel dying. I have never built a virtual environment from scratch like this before; I installed ipython, ipykernel, and jupyter using conda via Terminal. I installed statsmodels using pip. Maybe using pip was my mistake?
Could this be a PATH issue? I had downloaded the GUI version of anaconda before. When I prompt terminal
echo $PATH
These paths are printed:
/Users/RZ/anaconda3/bin:
/opt/anaconda3/condabin:
/usr/local/bin:
/usr/bin:
/bin:
/usr/sbin:
/sbin:
/usr/texbin:
/opt/X11/bin:
/usr/local/git/bin
More recently I have performed the following:
when I run:
jupyter nbextension list
I get this as an output:
Known nbextensions:
config dir: /Users/Rentazilla/anaconda3/etc/jupyter/nbconfig
tree section
nb_conda/tree disabled
Is this the issue? maybe nb_conda/tree was disabled incorrectly. According to at least one link on the Jupyter notebook github (https://github.com/jupyter/notebook/issues/1716) both nbextension list and serverextension should be disabled.
5/14/20
All right, so after many hours of trying a million different things, I came up with a solution that is working but I don't think its very pretty.
Not sure what to do yesterday, I decided to uninstall and reinstall conda. I used the full method detailed at https://docs.anaconda.com/anaconda/install/uninstall/
and uninstalled all anaconda3 folders and reinstalled conda using the latest miniconda installer.
Then I made a new conda environment:
conda create -n py3 ipykernel ipython jupyter_client jupyter_core traitlets ipython_genutils
Next I installed nb_conda_kernels in the base environment. Then I proceeded to install numpy, sympy, matplotlib, stats models, and jupyter_lab in the py3 environment.
I noticed that jupyter still sees some old environments as kernels; I need to get rid of them. For now I am only keeping the base environment and the py3 environment
I noticed that jupyter was using the wrong path for its kernels so I changed that
This did not fix the issue. I down graded python to 3.7.7 on the base and py3 environments. That did not fix the issue either. So I tried running some basic commands in python using the terminal. I found that running import numpy caused python to crash and gave the output Illegal Instruction: 4. Some searching online led me to this page:
https://apple.stackexchange.com/questions/387935/python-quit-working-and-now-i-get-illegal-instruction-4-message
I decided to try and downgrade numpy as well: conda install -n py3 numpy=1.17
I decided to test a file named test1.py using python via Terminal containing the following script:
num = int(input("Enter a number: "))
import numpy as np
print(num)
import sys
print(sys.version)
which I copied down based on the answer in the previous link. This ran just fine. Running with:
python -u -m trace -t test1.py
however in the terminal gave a ridiculously long stream of information.
Downgrading numpy to 1.18.5 solved the problem, at least for now.

The jupyter notebook github issues suggest uninstalling jupyter and reinstalling: https://github.com/jupyter/notebook/issues/1892#issuecomment-260403964
Regarding using multiple conda environments with jupyter, here is what I typically do:
Install nb_conda_kernels in the base environment
conda install -n base nb_conda_kernels
Install ipykernel in any conda environment that should be accessible in jupyter
conda install -n ENVNAME ipykernel
When using conda environments, it's best to use conda install when possible. statsmodels is available in conda, so you should conda install it.

The GitHub page says to uninstall ipykernel and then re-install it.