I am having issues with a specific kernel dying no matter the code I attempt to run.
I have jupyter notebooks installed in my base environment, so that when opening a script, I can toggle between environments (kernels) of my choosing via ipykernel. I can open Jupyter Notebooks and change the kernel from the default (Python 3) to the environment I want (named myenv). However, if I try to run any cell with the myenv kernel, I get the error message:
Kernel appears to have died. It will restart automatically.
The cell I was attempting to run was this:
from scipy import interpolate
import xarray as xr
import numpy as np
import proplot as pplt
%config InlineBackend.figure_format = 'retina'
import warnings
warnings.filterwarnings('ignore')
I tried running even simpler commands like just
import numpy, but the same error persists, despite having the previously specified packages installed.
Here is the conda list for my base environment:
WARNING conda.core.prefix_data:_load_site_packages(294): Problem reading non-conda package record at lib/python3.9/site-packages/webencodings-0.5.1-py2.7.egg-info/PKG-INFO. Please verify that you still need this, and if so, that this is still installed correctly. Reinstalling this package may help.
WARNING conda.core.prefix_data:_load_site_packages(294): Problem reading non-conda package record at lib/python3.9/site-packages/ipython_genutils-0.2.0-py2.7.egg-info/PKG-INFO. Please verify that you still need this, and if so, that this is still installed correctly. Reinstalling this package may help.
WARNING conda.core.prefix_data:_load_site_packages(294): Problem reading non-conda package record at lib/python3.9/site-packages/pip-21.2.4-py3.9.egg-info/PKG-INFO. Please verify that you still need this, and if so, that this is still installed correctly. Reinstalling this package may help.
# packages in environment at /Users/savannahferretti/Documents/PYTHON/Miniconda:
#
# Name Version Build Channel
appnope 0.1.2 py39hecd8cb5_1001
argon2-cffi 21.3.0 pyhd3eb1b0_0
argon2-cffi-bindings 21.2.0 py39hca72f7f_0
asttokens 2.0.5 pyhd3eb1b0_0
attrs 21.4.0 pyhd3eb1b0_0
backcall 0.2.0 pyhd3eb1b0_0
beautifulsoup4 4.11.1 py39hecd8cb5_0
bleach 4.1.0 pyhd3eb1b0_0
brotlipy 0.7.0 py39h9ed2024_1003
ca-certificates 2022.4.26 hecd8cb5_0
certifi 2022.6.15 py39hecd8cb5_0
cffi 1.15.0 py39hc55c11b_1
charset-normalizer 2.0.4 pyhd3eb1b0_0
conda 4.13.0 py39hecd8cb5_0
conda-package-handling 1.8.1 py39hca72f7f_0
cryptography 37.0.1 py39hf6deb26_0
debugpy 1.5.1 py39he9d5cce_0
decorator 5.1.1 pyhd3eb1b0_0
defusedxml 0.7.1 pyhd3eb1b0_0
entrypoints 0.4 py39hecd8cb5_0
executing 0.8.3 pyhd3eb1b0_0
icu 58.2 h0a44026_3
idna 3.3 pyhd3eb1b0_0
ipykernel 6.9.1 py39hecd8cb5_0
ipython 8.4.0 py39hecd8cb5_0
ipython_genutils 0.2.0 pyhd3eb1b0_1
jedi 0.18.1 py39hecd8cb5_1
jinja2 3.0.3 pyhd3eb1b0_0
jsonschema 4.4.0 py39hecd8cb5_0
jupyter_client 7.2.2 py39hecd8cb5_0
jupyter_contrib_core 0.4.0 pyhd8ed1ab_0 conda-forge
jupyter_contrib_nbextensions 0.5.1 pyhd8ed1ab_2 conda-forge
jupyter_core 4.10.0 py39hecd8cb5_0
jupyter_highlight_selected_word 0.2.0 py39h6e9494a_1005 conda-forge
jupyter_latex_envs 1.4.6 pyhd8ed1ab_1002 conda-forge
jupyter_nbextensions_configurator 0.4.1 py39h6e9494a_2 conda-forge
jupyterlab_pygments 0.1.2 py_0
libcxx 12.0.0 h2f01273_0
libffi 3.3 hb1e8313_2
libiconv 1.16 hca72f7f_2
libsodium 1.0.18 h1de35cc_0
libxml2 2.9.14 hbf8cd5e_0
libxslt 1.1.35 h5b33f42_0
lxml 4.9.1 py39h65b224f_0
markupsafe 2.1.1 py39hca72f7f_0
matplotlib-inline 0.1.2 pyhd3eb1b0_2
mistune 0.8.4 py39h9ed2024_1000
nbclient 0.5.13 py39hecd8cb5_0
nbconvert 6.4.4 py39hecd8cb5_0
nbformat 5.3.0 py39hecd8cb5_0
ncurses 6.3 hca72f7f_3
nest-asyncio 1.5.5 py39hecd8cb5_0
notebook 6.4.11 py39hecd8cb5_0
openssl 1.1.1q hca72f7f_0
packaging 21.3 pyhd3eb1b0_0
pandocfilters 1.5.0 pyhd3eb1b0_0
parso 0.8.3 pyhd3eb1b0_0
pexpect 4.8.0 pyhd3eb1b0_3
pickleshare 0.7.5 pyhd3eb1b0_1003
pip 22.1.2 py39hecd8cb5_0
prometheus_client 0.13.1 pyhd3eb1b0_0
prompt-toolkit 3.0.20 pyhd3eb1b0_0
ptyprocess 0.7.0 pyhd3eb1b0_2
pure_eval 0.2.2 pyhd3eb1b0_0
pycosat 0.6.3 py39h9ed2024_0
pycparser 2.21 pyhd3eb1b0_0
pygments 2.11.2 pyhd3eb1b0_0
pyopenssl 22.0.0 pyhd3eb1b0_0
pyparsing 3.0.4 pyhd3eb1b0_0
pyrsistent 0.18.0 py39hca72f7f_0
pysocks 1.7.1 py39hecd8cb5_0
python 3.9.12 hdfd78df_0
python-dateutil 2.8.2 pyhd3eb1b0_0
python-fastjsonschema 2.15.1 pyhd3eb1b0_0
python.app 3 py39hca72f7f_0
python_abi 3.9 2_cp39 conda-forge
pyyaml 6.0 py39hca72f7f_1
pyzmq 23.2.0 py39he9d5cce_0
readline 8.1.2 hca72f7f_1
requests 2.28.1 py39hecd8cb5_0
ruamel_yaml 0.15.100 py39h9ed2024_0
send2trash 1.8.0 pyhd3eb1b0_1
setuptools 61.2.0 py39hecd8cb5_0
six 1.16.0 pyhd3eb1b0_1
soupsieve 2.3.1 pyhd3eb1b0_0
sqlite 3.38.5 h707629a_0
stack_data 0.2.0 pyhd3eb1b0_0
terminado 0.13.1 py39hecd8cb5_0
testpath 0.6.0 py39hecd8cb5_0
tk 8.6.12 h5d9f67b_0
tornado 6.1 py39h9ed2024_0
tqdm 4.64.0 py39hecd8cb5_0
traitlets 5.1.1 pyhd3eb1b0_0
typing-extensions 4.1.1 hd3eb1b0_0
typing_extensions 4.1.1 pyh06a4308_0
tzdata 2022a hda174b7_0
urllib3 1.26.9 py39hecd8cb5_0
wcwidth 0.2.5 pyhd3eb1b0_0
webencodings 0.5.1 py39hecd8cb5_1
wheel 0.37.1 pyhd3eb1b0_0
xz 5.2.5 hca72f7f_1
yaml 0.2.5 haf1e3a3_0
zeromq 4.3.4 h23ab428_0
zlib 1.2.12 h4dc903c_2
(base) savannahferretti#dhcp-v057-073 ~ %
And for my myenv environment:
WARNING conda.core.prefix_data:_load_site_packages(294): Problem reading non-conda package record at lib/python3.9/site-packages/pyzmq-19.0.2-py3.9.egg-info/PKG-INFO. Please verify that you still need this, and if so, that this is still installed correctly. Reinstalling this package may help.
WARNING conda.core.prefix_data:_load_site_packages(294): Problem reading non-conda package record at lib/python3.9/site-packages/pandas-1.2.4-py3.9.egg-info/PKG-INFO. Please verify that you still need this, and if so, that this is still installed correctly. Reinstalling this package may help.
# packages in environment at /Users/savannahferretti/Documents/PYTHON/Miniconda/envs/myenv:
#
# Name Version Build Channel
appnope 0.1.2 py39hecd8cb5_1001
asttokens 2.0.5 pyhd3eb1b0_0
backcall 0.2.0 pyhd3eb1b0_0
blas 1.0 mkl
bokeh 2.4.3 py39hecd8cb5_0
bottleneck 1.3.5 py39h67323c0_0
brotli 1.0.9 hb1e8313_2
brotlipy 0.7.0 py39h9ed2024_1003
bzip2 1.0.8 h1de35cc_0
c-ares 1.18.1 hca72f7f_0
ca-certificates 2022.4.26 hecd8cb5_0
cartopy 0.18.0 py39h1cfd036_1
certifi 2022.6.15 py39hecd8cb5_0
cffi 1.15.0 py39hc55c11b_1
cftime 1.5.1.1 py39h67323c0_0
click 8.0.4 py39hecd8cb5_0
cloudpickle 2.0.0 pyhd3eb1b0_0
cryptography 37.0.1 py39hf6deb26_0
curl 7.82.0 hca72f7f_0
cycler 0.11.0 pyhd3eb1b0_0
cytoolz 0.11.0 py39h9ed2024_0
dask 2022.5.0 py39hecd8cb5_0
dask-core 2022.5.0 py39hecd8cb5_0
debugpy 1.5.1 py39he9d5cce_0
decorator 5.1.1 pyhd3eb1b0_0
distributed 2022.5.0 py39hecd8cb5_0
entrypoints 0.4 py39hecd8cb5_0
executing 0.8.3 pyhd3eb1b0_0
fonttools 4.25.0 pyhd3eb1b0_0
freetype 2.11.0 hd8bbffd_0
fsspec 2022.3.0 py39hecd8cb5_0
geos 3.8.0 hb1e8313_0
giflib 5.2.1 haf1e3a3_0
glob2 0.7 pyhd3eb1b0_0
hdf4 4.2.13 h39711bb_2
hdf5 1.10.6 hdbbcd12_0
heapdict 1.0.1 pyhd3eb1b0_0
idna 3.3 pyhd3eb1b0_0
intel-openmp 2021.4.0 hecd8cb5_3538
ipykernel 6.9.1 py39hecd8cb5_0
ipython 8.4.0 py39hecd8cb5_0
jedi 0.18.1 py39hecd8cb5_1
jinja2 3.0.3 pyhd3eb1b0_0
jpeg 9e hca72f7f_0
jupyter_client 7.2.2 py39hecd8cb5_0
jupyter_core 4.10.0 py39hecd8cb5_0
kiwisolver 1.4.2 py39he9d5cce_0
krb5 1.19.2 hcd88c3b_0
lcms2 2.12 hf1fd2bf_0
libcurl 7.82.0 h6dfd666_0
libcxx 12.0.0 h2f01273_0
libedit 3.1.20210910 hca72f7f_0
libev 4.33 h9ed2024_1
libffi 3.3 hb1e8313_2
libgfortran 3.0.1 h93005f0_2
libnetcdf 4.8.1 h24cb85c_1
libnghttp2 1.46.0 ha29bfda_0
libpng 1.6.37 ha441bb4_0
libsodium 1.0.18 h1de35cc_0
libssh2 1.10.0 h0a4fc7d_0
libtiff 4.2.0 hdb42f99_1
libwebp 1.2.2 h56c3ce4_0
libwebp-base 1.2.2 hca72f7f_0
libzip 1.8.0 h272c8d6_0
locket 1.0.0 py39hecd8cb5_0
lz4 3.1.3 py39h9ed2024_0
lz4-c 1.9.3 h23ab428_1
markupsafe 2.1.1 py39hca72f7f_0
matplotlib 3.4.3 py39h6e9494a_2 conda-forge
matplotlib-base 3.4.3 py39h0a11d32_0
matplotlib-inline 0.1.2 pyhd3eb1b0_2
mkl 2021.4.0 hecd8cb5_637
mkl-service 2.4.0 py39h9ed2024_0
mkl_fft 1.3.1 py39h4ab4a9b_0
mkl_random 1.2.2 py39hb2f4e1b_0
msgpack-python 1.0.3 py39haf03e11_0
munkres 1.1.4 py_0
ncurses 6.3 hca72f7f_3
nest-asyncio 1.5.5 py39hecd8cb5_0
netcdf4 1.5.7 py39h4a1dd59_1
numexpr 2.8.3 py39h2e5f0a9_0
numpy 1.22.3 py39h2e5f0a9_0
numpy-base 1.22.3 py39h3b1a694_0
openssl 1.1.1q hca72f7f_0
packaging 21.3 pyhd3eb1b0_0
pandas 1.4.3 py39he9d5cce_0
parso 0.8.3 pyhd3eb1b0_0
partd 1.2.0 pyhd3eb1b0_1
pexpect 4.8.0 pyhd3eb1b0_3
pickleshare 0.7.5 pyhd3eb1b0_1003
pillow 9.2.0 py39hde71d04_1
pip 22.1.2 py39hecd8cb5_0
proj 7.0.1 hdb716b3_1
prompt-toolkit 3.0.20 pyhd3eb1b0_0
proplot 0.9.5 pyhd8ed1ab_1 conda-forge
psutil 5.9.0 py39hca72f7f_0
ptyprocess 0.7.0 pyhd3eb1b0_2
pure_eval 0.2.2 pyhd3eb1b0_0
pycparser 2.21 pyhd3eb1b0_0
pygments 2.11.2 pyhd3eb1b0_0
pyopenssl 22.0.0 pyhd3eb1b0_0
pyparsing 3.0.4 pyhd3eb1b0_0
pyshp 2.1.3 pyhd3eb1b0_0
pysocks 1.7.1 py39hecd8cb5_0
python 3.9.12 hdfd78df_1
python-dateutil 2.8.2 pyhd3eb1b0_0
python_abi 3.9 2_cp39 conda-forge
pytz 2022.1 py39hecd8cb5_0
pyyaml 6.0 py39hca72f7f_1
pyzmq 23.2.0 py39he9d5cce_0
readline 8.1.2 hca72f7f_1
scipy 1.7.3 py39h8c7af03_0
setuptools 61.2.0 py39hecd8cb5_0
shapely 1.7.1 py39h9250791_0
six 1.16.0 pyhd3eb1b0_1
sortedcontainers 2.4.0 pyhd3eb1b0_0
sqlite 3.38.5 h707629a_0
stack_data 0.2.0 pyhd3eb1b0_0
tblib 1.7.0 pyhd3eb1b0_0
tk 8.6.12 h5d9f67b_0
toolz 0.11.2 pyhd3eb1b0_0
tornado 6.1 py39h9ed2024_0
traitlets 5.1.1 pyhd3eb1b0_0
typing-extensions 4.1.1 hd3eb1b0_0
typing_extensions 4.1.1 pyh06a4308_0
tzdata 2022a hda174b7_0
urllib3 1.26.9 py39hecd8cb5_0
wcwidth 0.2.5 pyhd3eb1b0_0
wheel 0.37.1 pyhd3eb1b0_0
xarray 0.20.1 pyhd3eb1b0_1
xz 5.2.5 hca72f7f_1
yaml 0.2.5 haf1e3a3_0
zeromq 4.3.4 h23ab428_0
zict 2.1.0 py39hecd8cb5_0
zlib 1.2.12 h4dc903c_2
zstd 1.5.2 hcb37349_0
Any help on this is appreciated. Thank you!
Related
we are currently using JupyterHub for our team of mostly non programmers. ( Zero to JupyterHub with Kubernetes).
We want to use voila to provide the notebooks as web apps. We have installed it on the server and it runs with a reverse proxy (jupyter-server-proxy), witch works fine.
However, Voila does not display everything from the notebooks. Markdown, HTML elements, normal output and plots (Seaborn) are displayed without problems.
Unfortunately, no ipywidgets are displayed. Instead, only an empty output is displayed.
I also tried nbconvert alone with jupyter nbconvert --to html with the same result.
This is what I get with voila:
Voila output
This is what I get with only nbconvert:
enter image description here
absl-py 1.3.0
aiohttp 3.8.3
aiosignal 1.3.1
alembic 1.8.1
altair 4.2.0
anyio 3.6.2
appmode 0.8.0
argon2-cffi 21.3.0
argon2-cffi-bindings 21.2.0
asn1crypto 1.5.1
asttokens 2.1.0
astunparse 1.6.3
async-generator 1.10
async-timeout 4.0.2
attrs 22.1.0
Babel 2.11.0
backcall 0.2.0
backports.functools-lru-cache 1.6.4
beautifulsoup4 4.11.1
bleach 5.0.1
blinker 1.5
bokeh 3.0.1
boto3 1.26.5
botocore 1.29.6
Bottleneck 1.3.5
branca 0.6.0
brotlipy 0.7.0
cached-property 1.5.2
cachetools 5.2.0
certifi 2022.9.24
certipy 0.1.3
cffi 1.15.1
charset-normalizer 2.1.1
click 8.1.3
cloudpickle 2.2.0
colorama 0.4.6
conda 22.9.0
conda-package-handling 1.9.0
contourpy 1.0.6
cryptography 38.0.3
cycler 0.11.0
Cython 0.29.32
cytoolz 0.12.0
dask 2022.10.0
debugpy 1.6.3
decorator 5.1.1
defusedxml 0.7.1
dill 0.3.6
distributed 2022.10.0
ecdsa 0.18.0
enbw-aop-client 0.20221027.1
entrypoints 0.4
entsoe-py 0.5.8
envs 1.4
et-xmlfile 1.0.1
executing 1.2.0
fastjsonschema 2.16.2
filelock 3.8.0
Flask 2.2.2
flatbuffers 2.0
flit_core 3.8.0
fonttools 4.38.0
frozenlist 1.3.3
fsspec 2022.10.0
gast 0.4.0
geographiclib 1.52
geopy 2.2.0
gitdb 4.0.9
GitPython 3.1.29
gmpy2 2.1.2
google-auth 2.14.0
google-auth-oauthlib 0.4.6
google-pasta 0.2.0
gravis 0.1.0
greenlet 2.0.1
grpcio 1.47.1
h11 0.14.0
h5py 3.7.0
HeapDict 1.0.1
idna 3.4
imagecodecs 2022.9.26
imageio 2.22.0
importlib-metadata 5.0.0
importlib-resources 5.10.0
ipykernel 6.17.1
ipyleaflet 0.17.2
ipympl 0.9.2
ipython 8.6.0
ipython-genutils 0.2.0
ipywidgets 8.0.2
itsdangerous 2.1.2
jedi 0.18.1
Jinja2 3.1.2
jmespath 1.0.1
joblib 1.2.0
json5 0.9.10
jsonschema 4.17.0
jupyter_client 7.4.1
jupyter_core 5.0.0
jupyter-server 1.23.1
jupyter-server-mathjax 0.2.6
jupyter-server-proxy 3.2.2
jupyter-telemetry 0.1.0
jupyterhub 3.0.0
jupyterlab 3.5.0
jupyterlab-git 0.39.3
jupyterlab-pygments 0.2.2
jupyterlab_server 2.16.2
jupyterlab-widgets 3.0.3
keras 2.10.0
Keras-Preprocessing 1.1.2
kiwisolver 1.4.4
libmambapy 1.0.0
llvmlite 0.39.1
locket 1.0.0
lxml 4.9.1
lz4 4.0.2
Mako 1.2.3
mamba 1.0.0
Markdown 3.4.1
MarkupSafe 2.1.1
matplotlib 3.6.2
matplotlib-inline 0.1.6
mistune 2.0.4
mpmath 1.2.1
msgpack 1.0.4
multidict 6.0.2
munkres 1.1.4
nbclassic 0.4.8
nbclient 0.7.0
nbconvert 6.4.5
nbdime 3.1.1
nbformat 5.7.0
nbtools 21.12
nest-asyncio 1.5.6
networkx 2.8.8
neurolab 0.3.5
notebook 6.5.2
notebook_shim 0.2.2
ntlm-auth 1.5.0
numba 0.56.3
numexpr 2.8.3
numpy 1.23.4
oauthlib 3.2.2
openpyxl 3.0.10
opt-einsum 3.3.0
oscrypto 1.2.1
outcome 1.2.0
packaging 21.3
pamela 1.0.0
pandas 1.5.1
pandocfilters 1.5.0
parso 0.8.3
partd 1.3.0
patsy 0.5.3
pexpect 4.8.0
pickleshare 0.7.5
Pillow 9.2.0
pip 22.3.1
pkgutil_resolve_name 1.3.10
platformdirs 2.5.3
plotly 5.11.0
pretty-html-table 0.9.11
prometheus-client 0.15.0
prompt-toolkit 3.0.32
protobuf 4.21.9
psutil 5.9.4
ptyprocess 0.7.0
pure-eval 0.2.2
pyarrow 9.0.0
pyasn1 0.4.8
pyasn1-modules 0.2.7
pycognito 2022.4.0
pycosat 0.6.4
pycparser 2.21
pycryptodomex 3.15.0
pycurl 7.45.1
pydantic 1.10.2
Pygments 2.13.0
PyJWT 2.6.0
pyOpenSSL 22.1.0
pyparsing 3.0.9
pyproj 3.4.0
pyrsistent 0.19.2
PySocks 1.7.1
python-dateutil 2.8.2
python-jose 3.3.0
python-json-logger 2.0.1
pytz 2022.6
pytz-deprecation-shim 0.1.0.post0
pyu2f 0.1.5
PyWavelets 1.3.0
PyYAML 6.0
pyzmq 24.0.1
requests 2.28.1
requests-ntlm 1.1.0
requests-oauthlib 1.3.1
requests-toolbelt 0.10.1
rpy2 3.5.1
rsa 4.9
ruamel.yaml 0.17.21
ruamel.yaml.clib 0.2.7
ruamel-yaml-conda 0.15.80
s3transfer 0.6.0
scikit-image 0.19.3
scikit-learn 1.1.3
scipy 1.9.3
seaborn 0.12.1
selenium 4.6.0
Send2Trash 1.8.0
setuptools 65.5.1
SharePlum 0.5.1
simpervisor 0.4
simplegeneric 0.8.1
six 1.16.0
smmap 3.0.5
sniffio 1.3.0
snowflake-connector-python 2.8.1
sortedcontainers 2.4.0
soupsieve 2.3.2.post1
SQLAlchemy 1.4.43
stack-data 0.6.0
statsmodels 0.13.5
sympy 1.11.1
tables 3.7.0
tblib 1.7.0
tenacity 8.1.0
tensorboard 2.10.1
tensorboard-data-server 0.6.0
tensorboard-plugin-wit 1.8.1
tensorflow 2.10.0
tensorflow-estimator 2.10.0
termcolor 2.1.0
terminado 0.17.0
terminaltables 3.1.10
testpath 0.6.0
threadpoolctl 3.1.0
tifffile 2022.10.10
tinycss2 1.2.1
tomli 2.0.1
toolz 0.12.0
tornado 6.2
tqdm 4.64.1
traitlets 5.5.0
traittypes 0.2.1
trash-cli 0.22.10.20
trio 0.21.0
trio-websocket 0.9.2
typing_extensions 4.4.0
tzdata 2022.6
tzlocal 4.2
unicodedata2 15.0.0
urllib3 1.26.12
usp.common.data 5.1.0
usp.common.util 0.0.1
voila 0.4.0
wcwidth 0.2.5
webencodings 0.5.1
websocket-client 1.4.2
websockets 10.4
Werkzeug 2.2.2
wheel 0.38.3
widgetsnbextension 4.0.3
wrapt 1.14.1
wsproto 1.2.0
xlrd 2.0.1
XlsxWriter 3.0.3
xyzservices 2022.9.0
yarl 1.8.1
zict 2.2.0
zipp 3.10.0
I already tried different versions of nbconvert and have Save Widget State Automatically on true.
Does anyone have an idea?
The Jupyter docs recommend using conda to install jupyter, if the runtime python is version 3.5 or lower. Installation is pretty straightforward with conda.
Follow Anaconda’s instructions for downloading and installing the Python 3.5 version.
$ conda install jupyter
$ pip list | grep ipython
ipython 7.29.0
ipython-genutils 0.2.0
$ ipython notebook --ip=0.0.0.0
This question is to discover if it's possible to install a 3.5 compatible jupyter using only pip, and without conda.
Given the following environment:
$ python --version
Python 3.5.2
$ sudo apt-get install python3-pip
$ pip3 --version
pip 8.1.1 from /usr/lib/python3/dist-packages (python 3.5)
Installing ipython is possible with the following restrictions:
$ python3 -m pip install ipython==7.9 traitlets==4.3.3 jedi==0.17.2
Jupyter, however, doesn't install gracefully.
The following allows for installation:
pip3 install jupyter ipython==7.9 traitlets==4.3.3 jedi==0.17.2 pyzmq==20 argon2-cffi==21.1.0
But at runtime, jupyter crashes:
File "/home/vagrant/.local/lib/python3.5/site-packages/ipython_genutils/importstring.py", line 31, in import_item
module = __import__(package, fromlist=[obj])
File "/home/vagrant/.local/lib/python3.5/site-packages/notebook/__init__.py", line 27, in <module>
from .nbextensions import install_nbextension
File "/home/vagrant/.local/lib/python3.5/site-packages/notebook/nbextensions.py", line 15, in <module>
from jupyter_core.paths import (
File "/home/vagrant/.local/lib/python3.5/site-packages/jupyter_core/__init__.py", line 1, in <module>
from .version import version_info, __version__
File "/home/vagrant/.local/lib/python3.5/site-packages/jupyter_core/version.py", line 21
_suffix_ = f'.dev{version_info.serial}'
Is it possible to install a 3.5 friendly jupyter using pip?
Resources
pyzmq https://github.com/jupyter/notebook/issues/5961
iPython Versions
https://github.com/ipython/ipython/blob/master/README.rst
IPython 7.10+ supports Python 3.6 and above.
When using Python 2.7, please install IPython 5.x LTS Long Term Support version.
Python 3.3 and 3.4 were supported up to IPython 6.x.
Python 3.5 was supported with IPython 7.0 to 7.9.
traitlets vs. python 3.5
Traitlets 5 uses f-strings in code, not compatible with Python 3.5
uninstall the traitlets 5.0.3 version, and install 4.3.3 version
https://githubmemory.com/repo/ipython/traitlets/issues/620
argon2-cffi vs. python 3.5
https://packagegalaxy.com/python/argon2-cffi
It targets Python 3.6 and newer, and PyPy3.
The last version that works with Python 2.7 is 20.1.0, and the last version that works with Python 3.5 is 21.1.0.
jedi vs. python 3.5
https://jedi.readthedocs.io/en/latest/docs/changelog.html
0.17.2 (2020-07-17)
This will be the last release that supports Python 2 and Python 3.5. 0.18.0 will be Python 3.6+.
Calling macOS experts...
Appreciate your help into looking at this issue on pod install on flutter-- details are here
command used
/usr/local/bin/pod install --verbose
CocoaPods : 1.9.1
Ruby : ruby 2.6.3p62 (2019-04-16 revision 67580) [universal.x86_64-darwin19]
RubyGems : 3.1.2
Host : Mac OS X 10.15.4 (19E266)
Xcode : 11.4 (11E146)
Git : git version 2.24.1 (Apple Git-126)
Ruby lib dir : /System/Library/Frameworks/Ruby.framework/Versions/2.6/usr/lib
cocoapods-deintegrate : 1.0.4
cocoapods-plugins : 1.0.0
cocoapods-search : 1.0.0
cocoapods-stats : 1.1.0
cocoapods-trunk : 1.4.1
cocoapods-try : 1.1.0
ERROR
RuntimeError - [Xcodeproj] Unknown object version.
/Library/Ruby/Gems/2.6.0/gems/xcodeproj-1.15.0/lib/xcodeproj/project.rb:227:in
2 steps to fix..
gem install cocoapods --pre
gem install mygem --user-install
and voila. your problems for days is solved...
What could help:
gem install cocoapods --pre
and maybe
gem update
If it doesn't help, check if your project format is correct:
Sources: https://github.com/CocoaPods/CocoaPods/issues/7697
https://github.com/CocoaPods/CocoaPods/issues/7458
Ubuntu installation gets stuck very early on. Current list of packages and confirmation that Tesseract and Leptonica seems to be installed correctly. Any clues appreciated?
(venv) ubuntu#ip$ pip install tesserocr
Collecting tesserocr
Using cached
https://files.pythonhosted.org/packages/f8/6d/4e81e041f33a4419e59edcb1dbdf3c
56e9393f60f5ef531381bd67a1339b/tesserocr-2.3.1.tar.gz
Installing collected packages: tesserocr
Running setup.py install for tesserocr ... \
Package Version
--------------- -------
click 6.7
Cython 0.28.5
dominate 2.3.1
Flask 1.0.2
Flask-Bootstrap 3.3.7.1
Flask-Login 0.4.1
Flask-WTF 0.14.2
ghostscript 0.6
gunicorn 19.9.0
itsdangerous 0.24
Jinja2 2.10
MarkupSafe 1.0
Pillow 5.2.0
pip 18.0
pkg-resources 0.0.0
setuptools 20.7.0
visitor 0.1.3
Werkzeug 0.14.1
WTForms 2.2.1
(venv) ubuntu#ip-172-26-9-100:~/apa$ tesseract -v
tesseract 3.04.01
leptonica-1.73
libgif 5.1.2 : libjpeg 8d (libjpeg-turbo 1.4.2) : libpng 1.2.54 : libtiff 4.0.6 : zlib 1.
2.8 : libwebp 0.4.4 : libopenjp2 2.1.0
Problem resolved after rebooting the machine. Not sure why this worked, other than I'd installed a lot of packages to get to this stage, and maybe something required a restart to complete the installation? If anyone can explain the problem, I'd be interested to understand why that might be?
If I 'source activate' a non-root environment (in my case "data"), then launch Jupyter notebook, the env seems to switch to root. I can tell because if I try to open a new python notebook, the dropdown under New says Python [Root]. I am also unable to import packages in my env, but not in root.
(data) Edwards-MacBook-Pro:~ mango$ conda list
# packages in environment at /Users/mango/anaconda/envs/data:
#
boto 2.42.0 py35_0
bz2file 0.98 py35_0
cycler 0.10.0 py35_0
freetype 2.5.5 1
gensim 0.12.4 np111py35_0
libpng 1.6.22 0
matplotlib 1.5.1 np111py35_0
mkl 11.3.3 0
numpy 1.11.1 py35_0
openssl 1.0.2i 0
pandas 0.18.1 np111py35_0
pip 8.1.2 py35_0
pyparsing 2.1.4 py35_0
pyqt 4.11.4 py35_4
python 3.5.2 0
python-dateutil 2.5.3 py35_0
pytz 2016.6.1 py35_0
qt 4.8.7 4
readline 6.2 2
requests 2.11.1 py35_0
scikit-learn 0.17.1 np111py35_2
scipy 0.18.1 np111py35_0
seaborn 0.7.1 py35_0
setuptools 27.2.0 py35_0
sip 4.18 py35_0
six 1.10.0 py35_0
smart_open 1.3.4 py35_0
sqlite 3.13.0 0
tk 8.5.18 0
wheel 0.29.0 py35_0
xz 5.2.2 0
zlib 1.2.8 3
(data) Edwards-MacBook-Pro:~ mango$ ipython
Python 3.5.2 |Anaconda custom (x86_64)| (default, Jul 2 2016, 17:52:12)
Type "copyright", "credits" or "license" for more information.
IPython 4.2.0 -- An enhanced Interactive Python.
? -> Introduction and overview of IPython's features.
%quickref -> Quick reference.
help -> Python's own help system.
object? -> Details about 'object', use 'object??' for extra details.
In [1]: import seaborn
---------------------------------------------------------------------------
ImportError Traceback (most recent call last)
<ipython-input-1-085c0287ecb5> in <module>()
----> 1 import seaborn
ImportError: No module named 'seaborn'
In [2]:
The same behavior occurs with gensim, so it is not just seaborn.
I managed to solve the issue. Conda installs the [root] environment with ipython and jupyter. If you create an env, those are not available by default. So when creating and env, either be sure to list those packages explicitly, or clone root. Cloning root may make a bulkier env and it may be less desirable for production, but better for a sandbox context.
I discovered this issue by trying the same test above with python and finding that my packages indicated that I was in the data env. I then decided to try the Anaconda Navigator program with conda install anaconda-navigator. While I like a cli, this GUI based program seems like a better way to manage packages.