How to overcome Error when pip installing okta? - python

I'm working with Python 3.8.9 and I need to use the Okta package. I try to install it as their documentation suggests: pip install okta, but I get this error:
...
Failed to build aiohttp yarl multidict frozenlist
ERROR: Could not build wheels for aiohttp, yarl, multidict, frozenlist which use PEP 517 and cannot be installed directly
Any idea how to fix this issue?

Perhaps try upgrading pip then attempt installing again:
pip install --upgrade pip
pip install okta

Related

Unable to install discord py with pip

i have python 3.11 downloaded, and i installed pip with it.
however, i can't install discord py with
py -3 -m pip install -U discord.py
i've tried a few other ways, still didn't work.
in the end it says:
note: This error originates from a subprocess, and is likely not a problem with pip.
ERROR: Failed building wheel for yarl
Failed to build multidict yarl
ERROR: Could not build wheels for multidict, yarl, which is required to install pyproject.toml-based projects
there are a few other errors throughout the process.
Hmmm, it seems it might be a problem due to dependencies to yarl and multidict (happens). I've had the same problem with itertools, and even opencv taking extremely long to build with a non-upgraded pip version!
Have you tried upgrading pip? Same problem with those libraries' dependencies.
pip3 install --upgrade pip
If pip direct installation doesn't work, try cloning the git repo:
$ pip install git+https://github.com/Rapptz/discord.py
You can try pip install discord.py
You could also try pip install discord

pip3 install mlagents causing error because of h5py>=2.9.0

I'm trying to install this package to use it with unity
mlagents 0.29.0
https://pypi.org/project/mlagents/
pip3 install mlagents
Note: i have a mac
I'm getting this error
ERROR: Some build dependencies for h5py>=2.9.0 from https://files.pythonhosted.org/packages/56/c7/9410b3802f456c702f6e0ccebf82e628f42a30921f61a232e26e424d95d4/h5py-3.5.0.tar.gz (from mlagents) conflict with the backend dependencies: numpy==1.22.3 is incompatible with numpy ==1.19.3; python_version>='3.9'.
I also tried this command
pip3 install mlagents --use-feature=2020-resolver
didn't work
Found out that h5py removed setup dependencies and newer version now should be able to be installed. Try this:
pip3 install h5py==3.7.0
and then
pip3 install mlagents
I fixed the problem by running this command
pip3.8 install mlagents
pip3.8 not pip3

Unable To Run AzureML Experiment with SDK - Failed to Build Wheel for pynacl / Exit status:1

I am trying to run a AzureML Experiment using sdk (following a Udemy course). When I try to use the Experiment.submit function the experiment prepares and then fails with the following error messages:
ERROR: Command errored out with exit status 1
ERROR: Failed building wheel for pynacl
ERROR: Could not build wheels for pynacl which use PEP 517 and cannot be installed directly
The Azure env as created within my anaconda navigator for a short period of time and then gets removed.
Does anyone know how I can get around this? Any help would be really appreciated.
To resolve ERROR: Could not build wheels for pynacl which use PEP 517 and cannot be installed directly this error, try either of the following ways:
Install missing dependencies:
sudo apt install libpython3-dev build-essential
Upgrade pip:
pip3 install --upgrade pip
Upgrade pip with setuptools wheel:
pip3 install --upgrade pip setuptools wheel
Reinstall PEP517:
pip3 install p5py
pip3 install PEP517
You can refer to ERROR: Could not build wheels for scipy which use PEP 517 and cannot be installed directly, Could not build wheels for _ which use PEP 517 and cannot be installed directly - Easy Solution and failed building wheel for pynacl

pip install ecapture creates an error. How do I solve this?

I cannot install ecapture 0.1.8
Python version: 3.9.6
pip: 21.2.2
I am using Windows 10
I typed pip install ecapture
and got a whole bunch of collecting and installing messages, then this.:
ERROR: Failed building wheel for scikit-image
Failed to build scikit-image
ERROR: Could not build wheels for scikit-image which use PEP 517 and cannot be installed directly
I also tried installing scikit-image and wheel individually but that didn't work. Does anyone know how to help?
I used pip3 install ecapture --no-binary :all: and installed ecapture version 0.0.8 instead of 0.1.8
1 upload from https://pypi.org/project/ecapture/#files
2 download ecapture-0.1.8-py3-none-any.whl
3 open cmd go to download directory cd C:\Users\me\Downloads (in my PC)
4 pip install ecapture-0.1.8-py3-none-any.whl

downgrading pip package in virtualenv

I set up a virtualenv and am trying to install a package where I get the error:
error: chardet 4.0.0 is installed but chardet<4.0,>=2.0 is required by {'aiohttp'}
Thus I tried to downgrade:
$ pip3 install --upgrade chardet==3.0.0
Collecting chardet==3.0.0
Using cached chardet-3.0.0-py2.py3-none-any.whl (133 kB)
Installing collected packages: chardet
Attempting uninstall: chardet
Found existing installation: chardet 4.0.0
Uninstalling chardet-4.0.0:
Successfully uninstalled chardet-4.0.0
Successfully installed chardet-3.0.0
Still when I try to install my package I get:
error: chardet 4.0.0 is installed but chardet<4.0,>=2.0 is required by {'aiohttp'}
I also tried to first uninstall the existing version:
pip3 uninstall chardet
But I still receive the error:
error: chardet 4.0.0 is installed but chardet<4.0,>=2.0 is required by {'aiohttp'}
Executing these steps I would expect chardet to downgrade to version 3.0.0 and my package to install. Is there a different way to do this without touching my packages outside of the venv?
Pipdeptree output:
$ pipdeptree
pipdeptree==2.0.0
- pip [required: >=6.0.0, installed: 21.0.1]
pkg-resources==0.0.0
setuptools==53.0.0
wheel==0.36.2
Edit:
downgrading indeed worked as expected. I got the error because the package I tried to install required sudo rights and thus by executing it as sudo I left the virtual environment. Downgrading the package globally let me install the package although I wanted to avoid this.
Try using pipdeptree, it displays installed packages as a dependency tree, there you can find a bug in chardet with different versions specified.

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