Open daeh opened 1 year ago
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❯ jupyter troubleshoot $PATH: ~/software/anaconda3/envs/ve_iaa_pytorch/bin ~/software/anaconda3/condabin ~/software/texlive/bin/x86_64-linux ~/software/node-v12.14.0-linux-x64/bin /cm/shared/openmind/gcc/11.1.0/bin /usr/lib64/qt-3.3/bin ~/me/zsh/bin ~/me/vim/bin ~/me/tmux/bin ~/me/git/bin /usr/local/bin /usr/bin ~/bin /usr/local/sbin /usr/sbin sys.path: ~/software/anaconda3/envs/ve_iaa_pytorch/bin ~/software/anaconda3/envs/ve_iaa_pytorch/lib/python310.zip ~/software/anaconda3/envs/ve_iaa_pytorch/lib/python3.10 ~/software/anaconda3/envs/ve_iaa_pytorch/lib/python3.10/lib-dynload ~/software/anaconda3/envs/ve_iaa_pytorch/lib/python3.10/site-packages sys.executable: ~/software/anaconda3/envs/ve_iaa_pytorch/bin/python sys.version: 3.10.9 | packaged by conda-forge | (main, Feb 2 2023, 20:20:04) [GCC 11.3.0] platform.platform(): Linux-3.10.0-1062.el7.x86_64-x86_64-with-glibc2.17 which -a jupyter: ~/software/anaconda3/envs/ve_iaa_pytorch/bin/jupyter pip list: Package Version ----------------------------- ----------- aiofiles 22.1.0 aiosqlite 0.18.0 anyio 3.6.2 argon2-cffi 21.3.0 argon2-cffi-bindings 21.2.0 asttokens 2.2.1 attrs 22.2.0 autopep8 2.0.2 Babel 2.12.1 backcall 0.2.0 backports.functools-lru-cache 1.6.4 beautifulsoup4 4.11.2 bleach 6.0.0 brotlipy 0.7.0 certifi 2022.12.7 cffi 1.15.1 charset-normalizer 2.1.1 colorama 0.4.6 comm 0.1.2 contourpy 1.0.7 cryptography 39.0.2 cycler 0.11.0 debugpy 1.6.6 decorator 5.1.1 defusedxml 0.7.1 dill 0.3.6 entrypoints 0.4 executing 1.2.0 fastjsonschema 2.16.3 flit_core 3.8.0 fonttools 4.39.0 idna 3.4 importlib-metadata 6.0.0 importlib-resources 5.12.0 ipykernel 6.21.3 ipython 8.11.0 ipython-genutils 0.2.0 jedi 0.18.2 Jinja2 3.1.2 joblib 1.2.0 json5 0.9.5 jsonschema 4.17.3 jupyter_client 8.0.3 jupyter_core 5.2.0 jupyter-events 0.6.3 jupyter_server 2.4.0 jupyter_server_fileid 0.8.0 jupyter_server_terminals 0.4.4 jupyter_server_ydoc 0.6.1 jupyter-ydoc 0.2.2 jupyterlab 3.6.1 jupyterlab-pygments 0.2.2 jupyterlab_server 2.20.0 kiwisolver 1.4.4 libtmux 0.21.0 MarkupSafe 2.1.2 matplotlib 3.7.1 matplotlib-inline 0.1.6 mistune 2.0.5 munkres 1.1.4 nbclassic 0.5.3 nbclient 0.7.2 nbconvert 7.2.9 nbformat 5.7.3 nest-asyncio 1.5.6 notebook 6.5.3 notebook_shim 0.2.2 numpy 1.24.2 packaging 23.0 pandas 1.5.3 pandocfilters 1.5.0 parso 0.8.3 patsy 0.5.3 pexpect 4.8.0 pickleshare 0.7.5 Pillow 9.4.0 pip 23.0.1 pkgutil_resolve_name 1.3.10 platformdirs 3.1.1 pooch 1.7.0 prometheus-client 0.16.0 prompt-toolkit 3.0.38 psutil 5.9.4 ptyprocess 0.7.0 pure-eval 0.2.2 pycodestyle 2.10.0 pycparser 2.21 Pygments 2.14.0 pyOpenSSL 23.0.0 pyparsing 3.0.9 pyrsistent 0.19.3 PySocks 1.7.1 python-dateutil 2.8.2 python-json-logger 2.0.7 pytz 2022.7.1 PyYAML 6.0 pyzmq 25.0.0 requests 2.28.2 rfc3339-validator 0.1.4 rfc3986-validator 0.1.1 scikit-learn 1.2.2 scipy 1.10.1 seaborn 0.12.2 Send2Trash 1.8.0 setuptools 67.6.0 six 1.16.0 sniffio 1.3.0 soupsieve 2.3.2.post1 stack-data 0.6.2 statsmodels 0.13.5 terminado 0.17.1 threadpoolctl 3.1.0 tinycss2 1.2.1 tmuxp 1.27.0 tomli 2.0.1 torch 1.13.1 tornado 6.2 traitlets 5.9.0 typing_extensions 4.5.0 unicodedata2 15.0.0 urllib3 1.26.15 wcwidth 0.2.6 webencodings 0.5.1 websocket-client 1.5.1 wheel 0.38.4 y-py 0.5.9 ypy-websocket 0.8.2 zipp 3.15.0 conda list: # packages in environment at ~/software/anaconda3/envs/ve_iaa_pytorch: # # Name Version Build Channel _libgcc_mutex 0.1 conda_forge conda-forge _openmp_mutex 4.5 2_kmp_llvm conda-forge aiofiles 22.1.0 pyhd8ed1ab_0 conda-forge aiosqlite 0.18.0 pyhd8ed1ab_0 conda-forge anyio 3.6.2 pyhd8ed1ab_0 conda-forge argon2-cffi 21.3.0 pyhd8ed1ab_0 conda-forge argon2-cffi-bindings 21.2.0 py310h5764c6d_3 conda-forge asttokens 2.2.1 pyhd8ed1ab_0 conda-forge attrs 22.2.0 pyh71513ae_0 conda-forge autopep8 2.0.2 pyhd8ed1ab_0 conda-forge babel 2.12.1 pyhd8ed1ab_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 4.11.2 pyha770c72_0 conda-forge blas 2.116 mkl conda-forge blas-devel 3.9.0 16_linux64_mkl conda-forge bleach 6.0.0 pyhd8ed1ab_0 conda-forge brotli 1.0.9 h166bdaf_8 conda-forge brotli-bin 1.0.9 h166bdaf_8 conda-forge brotlipy 0.7.0 py310h5764c6d_1005 conda-forge bzip2 1.0.8 h7f98852_4 conda-forge ca-certificates 2022.12.7 ha878542_0 conda-forge certifi 2022.12.7 pyhd8ed1ab_0 conda-forge cffi 1.15.1 py310h255011f_3 conda-forge charset-normalizer 2.1.1 pyhd8ed1ab_0 conda-forge colorama 0.4.6 pypi_0 pypi comm 0.1.2 pyhd8ed1ab_0 conda-forge contourpy 1.0.7 py310hdf3cbec_0 conda-forge cryptography 39.0.2 py310h34c0648_0 conda-forge cycler 0.11.0 pyhd8ed1ab_0 conda-forge debugpy 1.6.6 py310heca2aa9_0 conda-forge decorator 5.1.1 pyhd8ed1ab_0 conda-forge defusedxml 0.7.1 pyhd8ed1ab_0 conda-forge dill 0.3.6 pyhd8ed1ab_1 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 fonttools 4.39.0 py310h1fa729e_0 conda-forge freetype 2.12.1 hca18f0e_1 conda-forge icu 70.1 h27087fc_0 conda-forge idna 3.4 pyhd8ed1ab_0 conda-forge importlib-metadata 6.0.0 pyha770c72_0 conda-forge importlib_metadata 6.0.0 hd8ed1ab_0 conda-forge importlib_resources 5.12.0 pyhd8ed1ab_0 conda-forge ipykernel 6.21.3 pyh210e3f2_0 conda-forge ipython 8.11.0 pyh41d4057_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 joblib 1.2.0 pyhd8ed1ab_0 conda-forge json5 0.9.5 pyh9f0ad1d_0 conda-forge jsonschema 4.17.3 pyhd8ed1ab_0 conda-forge jupyter_client 8.0.3 pyhd8ed1ab_0 conda-forge jupyter_core 5.2.0 py310hff52083_0 conda-forge jupyter_events 0.6.3 pyhd8ed1ab_0 conda-forge jupyter_server 2.4.0 pyhd8ed1ab_0 conda-forge jupyter_server_fileid 0.8.0 pyhd8ed1ab_0 conda-forge jupyter_server_terminals 0.4.4 pyhd8ed1ab_1 conda-forge jupyter_server_ydoc 0.6.1 pyhd8ed1ab_0 conda-forge jupyter_ydoc 0.2.2 pyhd8ed1ab_0 conda-forge jupyterlab 3.6.1 pyhd8ed1ab_0 conda-forge jupyterlab_pygments 0.2.2 pyhd8ed1ab_0 conda-forge jupyterlab_server 2.20.0 pyhd8ed1ab_0 conda-forge kiwisolver 1.4.4 py310hbf28c38_1 conda-forge lcms2 2.15 haa2dc70_1 conda-forge ld_impl_linux-64 2.40 h41732ed_0 conda-forge lerc 4.0.0 h27087fc_0 conda-forge libblas 3.9.0 16_linux64_mkl conda-forge libbrotlicommon 1.0.9 h166bdaf_8 conda-forge libbrotlidec 1.0.9 h166bdaf_8 conda-forge libbrotlienc 1.0.9 h166bdaf_8 conda-forge libcblas 3.9.0 16_linux64_mkl conda-forge libdeflate 1.17 h0b41bf4_0 conda-forge libffi 3.4.2 h7f98852_5 conda-forge libgcc-ng 12.2.0 h65d4601_19 conda-forge libgfortran-ng 12.2.0 h69a702a_19 conda-forge libgfortran5 12.2.0 h337968e_19 conda-forge libhwloc 2.9.0 hd6dc26d_0 conda-forge libiconv 1.17 h166bdaf_0 conda-forge libjpeg-turbo 2.1.5.1 h0b41bf4_0 conda-forge liblapack 3.9.0 16_linux64_mkl conda-forge liblapacke 3.9.0 16_linux64_mkl conda-forge libnsl 2.0.0 h7f98852_0 conda-forge libpng 1.6.39 h753d276_0 conda-forge libsodium 1.0.18 h36c2ea0_1 conda-forge libsqlite 3.40.0 h753d276_0 conda-forge libstdcxx-ng 12.2.0 h46fd767_19 conda-forge libtiff 4.5.0 hddfeb54_5 conda-forge libtmux 0.21.0 pypi_0 pypi libuuid 2.32.1 h7f98852_1000 conda-forge libwebp-base 1.3.0 h0b41bf4_0 conda-forge libxcb 1.13 h7f98852_1004 conda-forge libxml2 2.10.3 h7463322_0 conda-forge libzlib 1.2.13 h166bdaf_4 conda-forge llvm-openmp 15.0.7 h0cdce71_0 conda-forge markupsafe 2.1.2 py310h1fa729e_0 conda-forge matplotlib-base 3.7.1 py310he60537e_0 conda-forge matplotlib-inline 0.1.6 pyhd8ed1ab_0 conda-forge mistune 2.0.5 pyhd8ed1ab_0 conda-forge mkl 2022.1.0 h84fe81f_915 conda-forge mkl-devel 2022.1.0 ha770c72_916 conda-forge mkl-include 2022.1.0 h84fe81f_915 conda-forge munkres 1.1.4 pyh9f0ad1d_0 conda-forge nbclassic 0.5.3 pyhb4ecaf3_3 conda-forge nbclient 0.7.2 pyhd8ed1ab_0 conda-forge nbconvert 7.2.9 pyhd8ed1ab_0 conda-forge nbconvert-core 7.2.9 pyhd8ed1ab_0 conda-forge nbconvert-pandoc 7.2.9 pyhd8ed1ab_0 conda-forge nbformat 5.7.3 pyhd8ed1ab_0 conda-forge ncurses 6.3 h27087fc_1 conda-forge nest-asyncio 1.5.6 pyhd8ed1ab_0 conda-forge notebook 6.5.3 pyha770c72_0 conda-forge notebook-shim 0.2.2 pyhd8ed1ab_0 conda-forge numpy 1.24.2 py310h8deb116_0 conda-forge openjpeg 2.5.0 hfec8fc6_2 conda-forge openssl 3.0.8 h0b41bf4_0 conda-forge packaging 23.0 pyhd8ed1ab_0 conda-forge pandas 1.5.3 py310h9b08913_0 conda-forge pandoc 2.19.2 h32600fe_2 conda-forge pandocfilters 1.5.0 pyhd8ed1ab_0 conda-forge parso 0.8.3 pyhd8ed1ab_0 conda-forge patsy 0.5.3 pyhd8ed1ab_0 conda-forge pexpect 4.8.0 pyh1a96a4e_2 conda-forge pickleshare 0.7.5 py_1003 conda-forge pillow 9.4.0 py310h065c6d2_2 conda-forge pip 23.0.1 pyhd8ed1ab_0 conda-forge pkgutil-resolve-name 1.3.10 pyhd8ed1ab_0 conda-forge platformdirs 3.1.1 pyhd8ed1ab_0 conda-forge pooch 1.7.0 pyhd8ed1ab_0 conda-forge prometheus_client 0.16.0 pyhd8ed1ab_0 conda-forge prompt-toolkit 3.0.38 pyha770c72_0 conda-forge prompt_toolkit 3.0.38 hd8ed1ab_0 conda-forge psutil 5.9.4 py310h5764c6d_0 conda-forge pthread-stubs 0.4 h36c2ea0_1001 conda-forge ptyprocess 0.7.0 pyhd3deb0d_0 conda-forge pure_eval 0.2.2 pyhd8ed1ab_0 conda-forge pycodestyle 2.10.0 pyhd8ed1ab_0 conda-forge pycparser 2.21 pyhd8ed1ab_0 conda-forge pygments 2.14.0 pyhd8ed1ab_0 conda-forge pyopenssl 23.0.0 pyhd8ed1ab_0 conda-forge pyparsing 3.0.9 pyhd8ed1ab_0 conda-forge pyrsistent 0.19.3 py310h1fa729e_0 conda-forge pysocks 1.7.1 pyha2e5f31_6 conda-forge python 3.10.9 he550d4f_0_cpython conda-forge python-dateutil 2.8.2 pyhd8ed1ab_0 conda-forge python-fastjsonschema 2.16.3 pyhd8ed1ab_0 conda-forge python-json-logger 2.0.7 pyhd8ed1ab_0 conda-forge python_abi 3.10 3_cp310 conda-forge pytorch 1.13.1 py3.10_cpu_0 pytorch pytorch-mutex 1.0 cpu pytorch pytz 2022.7.1 pyhd8ed1ab_0 conda-forge pyyaml 6.0 py310h5764c6d_5 conda-forge pyzmq 25.0.0 py310h059b190_0 conda-forge readline 8.1.2 h0f457ee_0 conda-forge requests 2.28.2 pyhd8ed1ab_0 conda-forge rfc3339-validator 0.1.4 pyhd8ed1ab_0 conda-forge rfc3986-validator 0.1.1 pyh9f0ad1d_0 conda-forge scikit-learn 1.2.2 py310h209a8ca_0 conda-forge scipy 1.10.1 py310h8deb116_0 conda-forge seaborn 0.12.2 hd8ed1ab_0 conda-forge seaborn-base 0.12.2 pyhd8ed1ab_0 conda-forge send2trash 1.8.0 pyhd8ed1ab_0 conda-forge setuptools 67.6.0 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 statsmodels 0.13.5 py310hde88566_2 conda-forge tbb 2021.8.0 hf52228f_0 conda-forge terminado 0.17.1 pyh41d4057_0 conda-forge threadpoolctl 3.1.0 pyh8a188c0_0 conda-forge tinycss2 1.2.1 pyhd8ed1ab_0 conda-forge tk 8.6.12 h27826a3_0 conda-forge tmuxp 1.27.0 pypi_0 pypi tomli 2.0.1 pyhd8ed1ab_0 conda-forge tornado 6.2 py310h5764c6d_1 conda-forge traitlets 5.9.0 pyhd8ed1ab_0 conda-forge typing-extensions 4.5.0 hd8ed1ab_0 conda-forge typing_extensions 4.5.0 pyha770c72_0 conda-forge tzdata 2022g h191b570_0 conda-forge unicodedata2 15.0.0 py310h5764c6d_0 conda-forge urllib3 1.26.15 pyhd8ed1ab_0 conda-forge wcwidth 0.2.6 pyhd8ed1ab_0 conda-forge webencodings 0.5.1 py_1 conda-forge websocket-client 1.5.1 pyhd8ed1ab_0 conda-forge wheel 0.38.4 pyhd8ed1ab_0 conda-forge xorg-libxau 1.0.9 h7f98852_0 conda-forge xorg-libxdmcp 1.1.3 h7f98852_0 conda-forge xz 5.2.6 h166bdaf_0 conda-forge y-py 0.5.9 py310h4426083_0 conda-forge yaml 0.2.5 h7f98852_2 conda-forge ypy-websocket 0.8.2 pyhd8ed1ab_0 conda-forge zeromq 4.3.4 h9c3ff4c_1 conda-forge zipp 3.15.0 pyhd8ed1ab_0 conda-forge zstd 1.5.2 h3eb15da_6 conda-forge conda env: name: ve_iaa_pytorch channels: - pytorch - conda-forge - defaults dependencies: - _libgcc_mutex=0.1=conda_forge - _openmp_mutex=4.5=2_kmp_llvm - aiofiles=22.1.0=pyhd8ed1ab_0 - aiosqlite=0.18.0=pyhd8ed1ab_0 - anyio=3.6.2=pyhd8ed1ab_0 - argon2-cffi=21.3.0=pyhd8ed1ab_0 - argon2-cffi-bindings=21.2.0=py310h5764c6d_3 - asttokens=2.2.1=pyhd8ed1ab_0 - attrs=22.2.0=pyh71513ae_0 - autopep8=2.0.2=pyhd8ed1ab_0 - babel=2.12.1=pyhd8ed1ab_1 - backcall=0.2.0=pyh9f0ad1d_0 - backports=1.0=pyhd8ed1ab_3 - backports.functools_lru_cache=1.6.4=pyhd8ed1ab_0 - beautifulsoup4=4.11.2=pyha770c72_0 - blas=2.116=mkl - blas-devel=3.9.0=16_linux64_mkl - bleach=6.0.0=pyhd8ed1ab_0 - brotli=1.0.9=h166bdaf_8 - brotli-bin=1.0.9=h166bdaf_8 - brotlipy=0.7.0=py310h5764c6d_1005 - bzip2=1.0.8=h7f98852_4 - ca-certificates=2022.12.7=ha878542_0 - certifi=2022.12.7=pyhd8ed1ab_0 - cffi=1.15.1=py310h255011f_3 - charset-normalizer=2.1.1=pyhd8ed1ab_0 - comm=0.1.2=pyhd8ed1ab_0 - contourpy=1.0.7=py310hdf3cbec_0 - cryptography=39.0.2=py310h34c0648_0 - cycler=0.11.0=pyhd8ed1ab_0 - debugpy=1.6.6=py310heca2aa9_0 - decorator=5.1.1=pyhd8ed1ab_0 - defusedxml=0.7.1=pyhd8ed1ab_0 - dill=0.3.6=pyhd8ed1ab_1 - entrypoints=0.4=pyhd8ed1ab_0 - executing=1.2.0=pyhd8ed1ab_0 - flit-core=3.8.0=pyhd8ed1ab_0 - fonttools=4.39.0=py310h1fa729e_0 - freetype=2.12.1=hca18f0e_1 - icu=70.1=h27087fc_0 - idna=3.4=pyhd8ed1ab_0 - importlib-metadata=6.0.0=pyha770c72_0 - 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@daeh Is there a fix for this?
Hi! In the stackoverflow question, someone suggested setting LAB_TOKEN="test".
I just tried changing --LabApp.token=''
to --LabApp.token='test'
in my Dockerfile and then re-build the Jupyter container with docker-compose up --build, and it seems to fix the problem!
Use jupyter-notebook
command instead of jupyter-server
to provide the remote API.
The jupyter-server
/ VSCode Jupyter connectivity is horribly broken.
The latest versions I found which worked:
Notes:
rm -rf ~/.ipython ~/.jupyter
when experimenting with the server-side versions.Hi everyone! Sorry for not getting back to you sooner.
Jupyter-Server v1 was a stateless single-user server. With the introduction of real-time collaboration in JupyterLab, we needed to track different users connecting to the same instance. For this reason, in Jupyter-Server v2, we introduced a new identity API. This identity API was designed to enable third-party extensions to swap the IdentityProvider.
The default implementation of Jupyter-Server is a stateless single-user server yet. With the default authorization, you can configure the server to use a password or a token, but it is the same for every user. Furthermore, since this is a stateless server, the default implementation of the identity provider uses cookies to track sessions, assuming every new session is a different user and generating random anonymous user identities. You can find more information here.
If you are using the default implementation, every time a client connects (either using a password or token authentication), we check whether there is a cookie with a user identity. If the cookie is absent, we generate a new random identity for that client and store it in a cookie.
To avoid generating a new user for each request, you must habilitate cookies in your client. I'm not entirely sure, but VS code might have a flag to enable cookies for remote sessions.
thanks for the detailed explainer, @hbcarlos
Am I interpreting this right --- that you don't see a fix for anon token-auth coming from jupyter-server? Rather you're advising us to take the issue up with VS Code?
Am I interpreting this right --- that you don't see a fix for anon token-auth coming from jupyter-server? Rather you're advising us to take the issue up with VS Code?
I think your interpretation is correct, but I would like first to further discuss and get inputs from other on this. I will try to join next week jupyter server dev meeting to have more opinions on this.
Am I interpreting this right --- that you don't see a fix for anon token-auth coming from jupyter-server? Rather you're advising us to take the issue up with VS Code?
Hi @daeh. I'm sorry for not getting back to you sooner. I'm very busy at the moment.
It was not. Actually, I've been trying to reproduce the issue by following your description. Unfortunately, I'm not able to reproduce it. This is what I tried:
I used VSCode as a client to open a local notebook and connect to a remote kernel running on Jupyter Server on a different machine (the remote server is on the same network as my laptop).
ssh -L 8888:192.168.1.2:8888 x@192.168.1.2
.jupyter-server --no-browser --port=8888 --ip="192.168.1.2"
http://127.0.0.1:8888/?token=<token>
This works as expected. It does not generate multiple users.
I connected to a JupyterLab instance in a remote server using ssh port forwarding.
ssh -L 8888:192.168.1.2:8888 x@192.168.1.2
.jupyter-lab --no-browser
http://127.0.0.1:8888/?token=<token>
This works as expected. It does not generate multiple users.
I was using: VSCode: 1.77.1 VSCode Jupyter extension: v2023.3.1201040234 Jupyter Server: 2.5.0 JupyterLab: 3.6.3
Can you confirm you are using the latest version of VSCode and VSCode Jupyter extension?
If that's the case, is your remote Jupyter server running under a proxy?
I have tested on my vscode connecting a notebook to a running jupyter server and it looks working fine as a user (I can run the notebook cells). The server log show the following, is that expected?
[I 2023-04-13 16:53:16.962 ServerApp] Generating new user for token-authenticated request: ecac822e57df40bdb76a6ba2f69509db
[I 2023-04-13 16:53:22.015 ServerApp] Generating new user for token-authenticated request: 22024ab735fc4ea497b01add51435bfd
[I 2023-04-13 16:53:22.016 ServerApp] Generating new user for token-authenticated request: 50c7eaae6cb14dc4a1d4f026d19d8ca7
[I 2023-04-13 16:53:26.904 ServerApp] Generating new user for token-authenticated request: 059c6e773aee4c479983670e1f0c7294
[I 2023-04-13 16:53:26.967 ServerApp] Generating new user for token-authenticated request: e745099bf9ad410aab9ed2f9c6a8738a
This previous has been run on VSCode Version: 1.76.2 (Universal) (Date: 2023-03-14T17:54:09.061Z (4 wks ago)) and jupyter server 2.6.0.dev0
@daeh We discussed it again during the server weekly meeting. This is an issue with VSCode, not with Jupiter Server. Jupyter Server uses cookies to authenticate clients, as described in the documentation. Once you logged in with the token, the server will set a cookie, and the token is no longer necessary.
For servers with token-authentication enabled, the URL in the above listing will include the token, so you can copy and paste that URL into your browser to login. If a server has no token (e.g. it has a password or has authentication disabled), the URL will not include the token argument. Once you have visited this URL, a cookie will be set in your browser and you won’t need to use the token again, unless you switch browsers, clear your cookies, or start a Jupyter server on a new port.
I finally managed to reproduce it. In VSCode, there are two ways of connecting to a remote kernel. The first one and the one described in the VSCode documentation is by setting the URL, including the token, to a running Jupyter Server http://<ip-address>:<port>/?token=<token>
. Using the method, VSCode will ignore the cookie and use the token for each request. Since the cookie is the one with the anonymous user information, the server will create a new random name on each request.
The second option consists of setting the URL without the token, then VSC will show another prompt requesting the token. In this case, VSCode will store the cookie and use it on each request.
In case somebody from the VSCode looks at this, one theory about what's happening is that when the user is presented with the challenge/response for authentication, the extension holds on to the cookies generated by the server, but when the extension receives a valid response by passing in the token, the extension might not be respecting the sessions cookies set by the server.
So for end users who experience this behavior, the current workaround is to not pass the URL containing the token to VSCode and instead allow the extension to ask them for it – until this issue is resolved upstream.
@hbcarlos
This is an issue with VSCode, not with Jupiter Server.
I think so, and report it to https://github.com/microsoft/vscode-jupyter/issues/13345
What is the name of the cookie that Jupyter Server sets to track sessions? I am running the server behind a proxy and some cookies are stripped by the proxy. So I want to make sure that these session cookies are not stripped and they go through.
I checked the links to the documentation and the cookie name is not mentioned as far as I can tell.
Description
It's possible that I'm just doing something wrong but this behavior seems related to other issues so I'm posting it as a bug.
I'm using SSH port forwarding to execute code from VS code on a mac with a remote jupyter kernel on a Centos HPC. I was previously using
jupyter notebook --no-browser --port=$ipnport --ip=$ipnip
and a notebook token. I updated to jupyter-server v2 and now when I connect to the remote kernel, the server makes a new user every second or so, for as long as the connection is open:This looks to be related to #1033, as well as https://github.com/jupyterlab/jupyterlab/issues/13432, both of which were resolved by #1076. But I seem to not be the only one experiencing this issue recently (e.g. https://github.com/jupyter/docker-stacks/issues/1892 , https://github.com/NorESMhub/noresm-land-sites-platform/issues/169 , https://stackoverflow.com/questions/75830256/jupyter-spam-with-generating-new-user-for-token-authenticated-request-in-logs )
Reproduce
I'm using
c.IdentityProvider.token = '...'
in.jupyter/jupyter_server_config.py
andjupyter server --no-browser --port=$ipnport --ip=$ipnip
to open the connection.I have tried numerous other configs but nothing seems to change the behavior. E.g.
jupyter lab --no-browser --port=$ipnport --ip=$ipnip --ServerApp.password='' --ServerApp.jpserver_extensions="nbclassic=False" --ServerApp.tornado_settings='{"headers": {"Content-Security-Policy": "frame-ancestors *"}}'
shows the same behavior.Expected behavior
For jupyter server to create one user when the connection is established rather than a new user every second-ish.
Context
The troubleshooting output is too long to fit here, I'll post below
Command Line Output