I am having some trouble with dependencies within my python conda environement. I need to have both libraries Tornado x msgpack-rpc-python. However both seems to be not compatible.
Here are the errors I am receiving:
ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.
nbclassic 0.4.8 requires tornado>=6.1, but you have tornado 4.5.3 which is incompatible.
jupyter-server 1.21.0 requires tornado>=6.1.0, but you have tornado 4.5.3 which is incompatible.
jupyter-client 7.4.7 requires tornado>=6.2, but you have tornado 4.5.3 which is incompatible.
ipyparallel 8.4.1 requires tornado>=5.1, but you have tornado 4.5.3 which is incompatible.
ipykernel 6.15.2 requires tornado>=6.1, but you have tornado 4.5.3 which is incompatible.
HOWEVER when I try to upgrate tornado I get this error:
ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of **the following dependency conflicts.
msgpack-rpc-python 0.4.1 requires tornado<5,>=3, but you have tornado 6.2 which is incompatible.**
I also tried to downgrade the list above(jupyter client, ..) however the environnement turn out to be unsustainable and non functional. I tried several times to create a new environment but no luck , I suppose I am doing things wrong but not sure what to do??
I have been trying to find a solution to this circular problem but I have been stuck on it for a long long time and getting out of ideas. I have downloaded Synk to help out but it is telling me the same thing is still a circular solution : updagrate tornado.
Background information:
Linux
Ubuntu 20.04
Coding in Visual Studio
Environment py38 (3.8.15)
Any help is appreciated!!
Thanks so much,
Related
When I run my requirements.txt file I get the following error messages
ERROR: Cannot install PyJWT==2.0.0 and djangorestframework-jwt==1.11.0 because these package versions have conflicting dependencies.
The conflict is caused by:
The user requested PyJWT==2.0.0
djangorestframework-jwt 1.11.0 depends on PyJWT<2.0.0 and >=1.5.2
To fix this you could try to:
1. loosen the range of package versions you've specified
2. remove package versions to allow pip attempt to solve the dependency conflict
ERROR: ResolutionImpossible: for help visit https://pip.pypa.io/en/latest/user_guide/#fixing-conflicting-dependencies
The two dependencies are written like the following:
PyJWT==2.0.0
djangorestframework-jwt==1.11.0
But what I'm most confused about is the error messages part saying: djangorestframework-jwt 1.11.0 depends on PyJWT<2.0.0 and >=1.5.2
Wouldn't the PyJWT version 2.0.0 be good enough?
This kind of conflict is a pain in the ass.
Pip says that the version must be between PyJWT<2.0.0 and >=1.5.2, sou you can use the exact 2.0.0.
Downgrade it to PyJWT==1.7.1 and it should works!
I've successfully deployed many updates over the past weeks on google cloud platform, but I went to perform a standard deployment today and received this error:
found incompatible dependencies: "packaging 21.2 has requirement pyparsing<3,>=2.0.2, but you have pyparsing 3.0.5."
I tried installing different versions of pyparsing to resolve the issue but none worked with all other dependencies. Are recent updates to pyparsing causing an issue?
Pyparsing versions compatible with packing 21.2 are versions <3 and > 2.0.2.
you can install 2.4.7 which is the immediate version before version 3.
You can install 2.4.7 by using command pip install pyparsing=2.4.7
When downloading numpy I encountered a failure at the end,
ERROR: Could not install packages due to an OSError: [WinError 2] The system cannot find the file specified: 'c:\\python310\\Scripts\\f2py.exe' -> 'c:\\python310\\Scripts\\f2py.exe.deleteme'
and while installing aitextgen i received this error:
ERROR: Cannot install aitextgen==0.3.0, aitextgen==0.4.0, aitextgen==0.4.1, aitextgen==0.5.0, aitextgen==0.5.1 and aitextgen==0.5.2 because these package versions have conflicting dependencies.`
The conflict is caused by:
aitextgen 0.5.2 depends on torch>=1.6.0
aitextgen 0.5.1 depends on torch>=1.6.0
aitextgen 0.5.0 depends on torch>=1.6.0
aitextgen 0.4.1 depends on torch>=1.6.0
aitextgen 0.3.0 depends on torch>=1.6.0
No idea what's causing this. I've reinstalled Python using chocolatey. Is it an issue involving an installation path? Any help is greatly appreciated.I installed these using the pip3 install [module] method.
If I judge your path to python correctly:
c:\\python310\\
Then you have python 3.10 installed. This is at this point only a beta version, not even officially released.
aitextgen 0.5.2 depends on torch>=1.6.0
The issue here is that torch only has whl files available on pypi and only up to python 3.9. You will face this problem often, as it will take some time, probably after the release scheduled in october to have official support for many python modules.
You options:
Install an earlier version of python - this is probably your best option. You probably don't depend on any specific python 3.10 features
Download and compile torch from source - this will be both tricky, esspecially on windows and is also not guaranteed to work. There is at this point no official support for python 3.10 from torch. You will probably also have to solve a similar problem for other modules when sitcking with pyhon 3.10
I am trying to install cuckoo sandbox(malware analysis tool).
I am doing pip install -U cuckoo as stated in cuckoo documentation, but it gives me following error
pandas 0.23.3 has requirement python-dateutil>=2.5.0, but you'll have python-dateutil 2.4.2 which is incompatible
So I thought maybe there is some package named python-dateutil and pandas is using its some version which is >= 2.5.0 but cuckoo needs its 2.4.2 version, so to not cause instability it's not getting installed.
So I thought of creating a virtualenv venv and install cuckoo in that. As there are no pandas in venv/lib/python2.7/site-packages installing a previous version of python-dateutil shouldn't be a problem. But again I am getting the same error. I am not getting where is the problem.
I have been following the installation guide from http://machinelearningmastery.com/setup-python-environment-machine-learning-deep-learning-anaconda/
I got & am using:
conda 4.3.22
Python 3.5.3 :: Anaconda 4.4.0 (32-bit)
scipy: 0.19.0
numpy: 1.12.1
matplotlib: 2.0.2
pandas: 0.20.1
statsmodels: 0.8.0
sklearn: 0.18.2
I successfully installed theano & keras. HOWEVER, I FAIL at installing tensorflow. Please HELP.
I created a conda ‘tensorflow’ environment with python 3.5. With command
『pip install –ignore-installed –upgrade https://storage.googleapis.com/tensorflow/windows/cpu/tensorflow-1.2.1-cp35-cp35m-win_amd64.whl』
I got ERROR saying
『tensorflow-1.2.1-cp35-cp35m-win_amd64.whl is not a supported wheel on this platform』
So i changed to version 1.0.1 and same error.
Version 1.1.0 also same error.
So i deactivated the environment, and type command
『conda install -c conda-forge tensorflow』
I got ERROR
『PackageNotFoundError: Package missing in current win-32 channels』
Instead it says the close match found is “xtensor” which i know is a C++ library that I'm not looking for.
Is it because I’m using a 32-bit Windows 10?
So I also tried running the following :
『python -m pip install –upgrade tensorflow』
and got ERROR of
『Could not find a version that satisfies the requirement tensorflow (from versions: ) No matching distribution found for tensorflow』
What more requirements do i need for this?
I tried 『pip3 install tensorflow』 but somehow it could not recognized ‘pip3’. So i type 『where pip3』 and it could not find files for the given pattern. So i type『where python』. It ouput the directory of my python. Then checked if it’s already put under the path inside the environmental variable. And it has. But i still couldn't use pip3 command.
I have tried all the solutions provided from people having similar problem with me and none of them work.
This question has been answered here.
In short, yes, TensorFlow does not support 32-bit platforms. Although if you only plan on writing abstract high-level Keras code then Theano will do just fine.