"Bad file descriptor" error when upgrading numpy on a-Shell - numpy

I installed a-Shell on my iPad(8th gen), it came with very nice python packages and it allowed me to run Jupyter notebook smoothly. But a lot of packages are outdated and my problem is with numpy.
When I use:
pip3 install numpy --upgarde
or
pip3 install numpy --upgarde --ignore-installed
It gives me the following:
OSError: [Errno 9] Bad file descriptor
note: This error originates from a subprocess, and is likely not a problem with pip.
Does file access permissions has to do anything with this problem?
One solution I found is to remove and re-install python, but I don't want to do that.
Thanks.

Related

Can't install lxml on pip

I can't install lxml on pip or pip3
I tried run the code on python3.11
import pandas as pd
data = pd.read_html("https://zh.wikipedia.org/zh-hans/%E6%81%92%E7%94%9F%E6%8C%87%E6%95%B8")
It occurred a Import Error.
"ImportError: lxml not found, please install it"
So I tried to install the lxml. "pip install lxml"
However, it cannot be install.
** note: This error originates from a subprocess, and is likely not a problem with pip.
error: legacy-install-failure
× Encountered error while trying to install package.
╰─> lxml
note: This is an issue with the package mentioned above, not pip.
hint: See above for output from the failure.**
And then, I had download the lxml-4.9.9-pp38-....whl
and entered "pip install c:/......." and it said whl is not a supported wheel on this platform.
Could someone do me a favor?

Cannot pip udate numpy

I want to update numpy from 1.19.1 to 1.19.2. So I did the following command:
pip install --upgrade numpy
However, I received the following error message:
ERROR: Could not install packages due to an EnvironmentError: [Errno 2] No such file or directory: '/userdata/data-dlin/.conda/envs/mybase/lib/python3.7/site-packages/numpy-1.19.1.dist-info/RECORD'
I went to the directory and found the RECORD file was indeed missing. How do I fix the error?
Uninstalling numpy (pip uninstall numpy), then deleting the entire folder
(python environment)/lib/site-packages/numpy-1.19.X.dist-info
And reinstalling numpy (pip install numpy) fixed it for me.

Issue while installing Tensorflow via Jupyter Notebook

WARNING: pip is being invoked by an old script wrapper. This will fail in a future version of pip.
Please see https://github.com/pypa/pip/issues/5599 for advice on fixing the underlying issue.
To avoid this problem you can invoke Python with '-m pip' instead of running pip directly.
ERROR: Could not install packages due to an EnvironmentError: [WinError 5] Access is denied: 'c:\\programdata\\anaconda3\\lib\\site-packages\\~-mpy\\core\\multiarray.cp37-win_amd64.pyd'
Consider using the `--user` option or check the permissions.
Although when I tried python -m pip install tensorflow in command prompt it installed the packagen, when I am trying to import Keras in Jupyter notebook I am getting above error.
It looks like you are on Windows. Open your command prompt as administrator and then type python -m pip install tensorflow --user. Let me know if this fixed your issue.

TensorFlow pip installation issue: cannot import name 'descriptor'

I'm seeing the following error when installing TensorFlow:
ImportError: Traceback (most recent call last):
File ".../graph_pb2.py", line 6, in
from google.protobuf import descriptor as _descriptor
ImportError: cannot import name 'descriptor'
This error signals a mismatch between protobuf and TensorFlow versions.
Take the following steps to fix this error:
Uninstall TensorFlow.
Uninstall protobuf (if protobuf is installed).
Reinstall TensorFlow, which will also install the correct protobuf dependency.
I faced the similar issue, after trial and error, I used the below logic to run the program:
pip install --upgrade --no-deps --force-reinstall tensorflow
This will make sure to uninstall and reinstall the program from fresh. It works!
I would be extra careful before uninstalling/reinstalling other packages such as protobuf. What I think would most likely be the issue is difference in versions. As of writing this, the most recent release of python is 3.7 while tensorflow is only compatible up to 3.6.
If you're using a 3rd party distribution like Anaconda, this can get hidden from you. In this case I would recommend creating a new environment in Anaconda, with python 3.6 and then installing tensorflow: https://conda.io/projects/conda/en/latest/user-guide/getting-started.html#managing-python
Try this:
pip uninstall protobuf
brew install protobuf
mkdir -p
/Users/alexeibendebury/Library/Python/2.7/lib/python/site-packages
echo 'import site;
site.addsitedir("/usr/local/lib/python2.7/site-packages")' >>
/Users/alexeibendebury/Library/Python/2.7/lib/python/site-packages/homebrew.pth

Theano fails due to NumPy Fortran mixup under Ubuntu

I installed Theano on my machine, but the nosetests break with a Numpy/Fortran related error message. For me it looks like Numpy was compiled with a different Fortran version than Theano. I already reinstalled Theano (sudo pip uninstall theano + sudo pip install --upgrade --no-deps theano) and Numpy / Scipy (apt-get install --reinstall python-numpy python-scipy), but this did not help.
What steps would you recommend?
Complete error message:
ImportError: ('/home/Nick/.theano/compiledir_Linux-2.6.35-31-generic-x86_64-with-Ubuntu-10.10-maverick--2.6.6/tmpIhWJaI/0c99c52c82f7ddc775109a06ca04b360.so: undefined symbol: _gfortran_st_write_done'
My research:
The Installing SciPy / BuildingGeneral page about the undefined symbol: _gfortran_st_write_done' error:
If you see an error message
ImportError: /usr/lib/atlas/libblas.so.3gf: undefined symbol: _gfortran_st_write_done
when building SciPy, it means that NumPy picked up the wrong Fortran compiler during build (e.g. ifort).
Recompile NumPy using:
python setup.py build --fcompiler=gnu95
or whichever is appropriate (see python setup.py build --help-fcompiler).
But:
Nick#some-serv2:/usr/local/lib/python2.6/dist-packages/numpy$ python setup.py build --help-fcompiler
This is the wrong setup.py file to run
Used software versions:
scipy 0.10.1 (scipy.test() works)
NumPy 1.6.2 (numpy.test() works)
theano 0.5.0 (several tests fails with undefined symbol: _gfortran_st_write_done')
python 2.6.6
Ubuntu 10.10
[UPDATE]
So I removed numpy and scipy from my system with apt-get remove and using find -name XXX -delete of what was left.
Than I installed numpy and scipy from the github sources with sudo python setpy.py install.
Afterwards I entered again sudo pip uninstall theano and sudo pip install --upgrade --no-deps theano.
Error persists :/
I also tried the apt-get source ... + apt-get build-dep ... approach, but for my old Ubuntu (10.10) it installs too old version of numpy and scipy for theano: ValueError: numpy >= 1.4 is required (detected 1.3.0 from /usr/local/lib/python2.6/dist-packages/numpy/__init__.pyc)
I had the same problem, and after reviewing the source code, user212658's answer seemed like it would work (I have not tried it). I then looked for a way to deploy user212658's hack without modifying the source code.
Put these lines in your theanorc file:
[blas]
ldflags = -lblas -lgfortran
This worked for me.
Have you tried to recompile NumPy from the sources?
I'm not familiar with the Ubuntu package system, so I can't check what's in your dist-packages/numpy. With a clean archive of the NumPy sources, you should have a setup.py at the same level as the directories numpy, tools and benchmarks (among others). I'm pretty sure that's the one you want to use for a python setup.py build.
[EDIT]
Now that you have recompiled numpy with the proper --fcompiler option, perhaps could you try to do the same with Theano, that is, compiling directly from sources without relying on a apt-get or even pip. You should have a better control on the build process that way, which will make debugging/trying to find a solution easier.
I had the same problem. The solution I found is to add a hack in theano/gof/cmodule.py to link against gfortran whenever 'blas' is in the libs. That fixed it.
class GCC_compiler(object):
...
#staticmethod
def compile_str(module_name, src_code, location=None,
include_dirs=None, lib_dirs=None, libs=None,
preargs=None):
...
cmd.extend(['-l%s' % l for l in libs])
if 'blas' in libs:
cmd.append('-lgfortran')
A better fix is to remove atlas and install openblas. openblas is faster then atlas. Also, openblas don't request gfortran and is the one numpy was linked with. So it will work out of the box.