Related
I am running OSX Catalina. After downloading Anaconda, I'm having trouble downloading external packages. I tried in both the GUI and the terminal, but the process keeps getting stuck at "Solving environment".
I understand creating a new environment can be a workaround, but I would rather fix the issue at hand.
Any ideas?
The following steps may work to resolve the issue.
conda config --remove channels conda-forge
conda config --add channels conda-forge
if it doesn't work then try this
conda update conda
if nothing works try seeing this github solution, it worked for many.
use this:
conda config --set channel_priority strict
pay attention that it is channel_priority and not priority_channel
running
conda config --set channel_priority flexible
worked for me
Update, still ran into some issues so I found Mamba, and oh my god my life changed conda is the worst package manager ever
all my issues were solved when I used mamba
# install mamba
conda install -n base conda-forge::mamba
# use mamba
mamba install pandas
Please, check that python is actually listed in environment.yml or conda create -n your_environment --file requirements.txt python=3.7.
Otherwise, conda is traversing all versions of python available.
Check that Python is listed.
for updated conda version over 4.12.0 'Libmamba' with advantages like:
Improve conda’s resolving speeds by 50-80%*
Maximize backwards compatibility so as to not break any current
functionality
Build the plugin infrastructure for others to create custom solvers
are mentioned in Anaconda's official blog post, A Faster Solver for Conda: Libmamba
so for making libmamba your default solver(make sure your conda version is 4.12):
conda install -n base conda-libmamba-solver
and to try it temporarily:conda create -n demo --experimental-solver=libmamba --dry-run install <some package>
It might be taking long because of package version conflicts. My solution was to install some packages using pip instead of conda install.
For example:
pip install tensorflow
Try this in a new environment so it doesn't mess up your existing ones.
conda config --remove channels conda-forge
conda config --set channel_priority flexible
This fixed the problem with the solving environment step. After that I was able to update packages (such as conda and anaconda) and sort out various dependency issues.
I've had this issue running macOS Monterey, with conda taking an age to solve the environment, failing, and causing immense frustration.
My first suggestion would be to install Mamba [1], of which you have two options. If conda does work, but just takes a long time, you can try
conda install mamba -n base -c conda-forge
If conda won't install anything at all, you can try uninstalling anaconda3 using conda install anaconda-clean, then anaconda-clean --yes, then rm -rf anaconda3,rm -rf ~/anaconda3 and rm -rf ~/opt/anaconda3. From there, download the Mambaforge .sh file [1], and run
bash ~/Downloads/Mambaforge-MacOSX-x86_64.sh
Follow the install, and treat mamba exactly how you would treat conda. Then it's simply a matter of selecting your interpreter in your IDE of choice! You'll find that mamba is way faster.
Failing this, you can try using which pip, and then pip install [your package]. I wouldn't advise this one for lots of packages, as you are essentially bypassing the dependancy check, however for small things, it should work fine. Try it, and uninstall it if you get any clashes. Happy fixing!
I had similar problems trying to install external packages such as graph-tools and I solved it by creating a new environment. I know you prefer other options but it's the only thing that worked for me.
I was having the same issue while creating my conda environment using environment.yml file.
conda env create -f environment.yml
My issue was fixed by updating conda and setting channel priority to strict:
conda update conda
conda config --set channel_priority strict
set conda-forge highest priority, remove defaults channel
conda config --add channels bioconda
conda config --add channels conda-forge
conda config --remove channels defaults
conda config --set channel_priority strict
make sure most your package from conda-forge, not defaults.
If it doesn't work, try
conda update --all
conda clean -a //use with caution
The following works for me.
Spin-off on https://github.com/conda/conda/issues/11919
Instead of waiting (maybe hours) to resolve SAT (A well-known NP-Complete problem) environment, it would be helpful for you to install the faster Conda resolver (https://www.anaconda.com/blog/a-faster-conda-for-a-growing-community). Just so you know, the resolver is not installed by default with Anaconda, so you need to install it manually.
sudo conda update -n base conda
sudo conda install -n base conda-libmamba-solver
conda config --set solver libmamba
Rerun conda install
conda install pytorch torchvision torchaudio pytorch-cuda=11.7 \
-c pytorch -c nvidia
I hope you find it useful.
you may also want to check your ~/.conda directory permissions. I installed conda on my MacOS using Homebrew and for some reason this directory had only read/write permissions for root. After changing the permissions and following the instructions from above, everything works smooth and fast now
upgrading conda base package has fixed it.
ref : https://docs.conda.io/projects/conda/en/latest/user-guide/install/rpm-debian.html
Sounds very simple but make sure you're in your environment
conda activate <Your Environment>
i had the same problem when i tried to install packages for my env i tried the conda env update -f environment.yml even doesn't worked (in yml file i have name: tf2 that i point to update my env still doesnt upgraded)
but now which i tried this it worked :d
conda activate tf2
conda env update -n tf2 -f environment.yml --prune
After some reading I found out the .condarc file is not created by default (is stated by the official Anaconda documentation. So what I did is delete de .condarc file and then used the following command
conda config --set channel_priority flexible
And then it got unstuck
Then I tried conda update conda just to test it, and everything worked again.
For other weary travelers: if you find conda taking hours to solve an environment, try install packages one at a time. Works like a miracle.
Another solution that may not have been mentioned is that the dependencies that you may want to install within your conda env are already installed.
Using conda-list within your env you may confirm.
With a package such as tethys platform they did not mentioned this and i was left wondering why my conda install process kept getting stuck at the solving stage. Late into the night bingo checked into my env and sure enough the dependencies where already installed. Now can progress to my next phase.
I faced the same issue for tensorflow and solved it by doing the next:
create new environment conda create -n tf tensorflow
moved to the new environemnt conda activate tf
downloaded my package there.
it worked and solved the issue, I think this happened due to not completing a previous install and got stuck in the middle.
Try installing ANACONDA3 2019-3.
I had similar issues but after installing the above version of anaconda they were all fixed.
Choose one:
Start fresh with a new Anaconda installation. Pay attention during
installation to make sure that your install path is a subfolder of
your home folder, such as /Users/me/anaconda3
Start fresh using the
.sh installer instead of the .pkg installer. This installer makes it
simpler to choose the destination path, and gives you more choice on
how you want your shell to behave.
check out the link for more details
This is another answer for environment failure, but for windows OS
This fixed the hang for me. Although the install went on to fail.
conda config --set priority_channel strict
I tried to update or install new packages from anaconda and lately, this message has appeared:
The environment is inconsistent, please check the package plan carefully
The following package are causing the inconsistency:
- defaults/win-32::anaconda==5.3.1=py37_0
done
I tried with conda clean --all and then conda update --all but it persists.
Conda Info
active environment : base
active env location : C:\Users\NAME\Continuum
shell level : 1
user config file : C:\Users\NAME\.condarc
populated config files : C:\Users\NAME\.condarc
conda version : 4.6.11
conda-build version : 3.17.7
python version : 3.7.3.final.0
base environment : C:\Users\NAME\Continuum (writable)
channel URLs : https://repo.anaconda.com/pkgs/main/win-32
https://repo.anaconda.com/pkgs/main/noarch
https://repo.anaconda.com/pkgs/free/win-32
https://repo.anaconda.com/pkgs/free/noarch
https://repo.anaconda.com/pkgs/r/win-32
https://repo.anaconda.com/pkgs/r/noarch
https://repo.anaconda.com/pkgs/msys2/win-32
https://repo.anaconda.com/pkgs/msys2/noarch
package cache : C:\Users\NAME\Continuum\pkgs
C:\Users\NAME\.conda\pkgs
C:\Users\NAME\AppData\Local\conda\conda\pkgs
envs directories : C:\Users\NAME\Continuum\envs
C:\Users\NAME\.conda\envs
C:\Users\NAME\AppData\Local\conda\conda\envs
platform : win-32
user-agent : conda/4.6.11 requests/2.21.0 CPython/3.7.3 Windows/10 Windows/10.0.17763
administrator : False
netrc file : None
offline mode : False
I had faced the same problem. Simply running
conda install anaconda
solved the problem for me.
saw this on Google Groups
This message was added in conda 4.6.9, previously there was no indication when conda detected an inconsistent environment unless conda was run in debug mode. It is likely that your environment was inconsistent for some time but the upgrade to conda made it visible. The best option it to run "conda install package_name" for the inconsistent packages to let conda try to restore consistency.
and it really works for me.
Maybe you should try conda install anaconda in your situation.
The inconsistencies are caused due to different versions of the packages, and their clashing dependencies.
conda update --all
This command updates all the packages, and then conda solves the inconsistency on its own.
Had this same problem and none of the other solutions worked for me. Ended up having to uninstall and reinstall conda, then reinstall all of my libraries.
Ultimate solutions:
conda activate base
conda install anaconda
conda update --all
Works on Windows 10 and Ubuntu 18.04 (credits to #MF.OX for ubuntu).
Removed following problems for me:
The environment is inconsistent
WARNING conda.base.context:use_only_tar_bz2(632)
If the other solutions don't work, reverting the environment can fix this.
Use conda list --revisions, pick a revision number, and use conda install --revision [#] going back step-by-step until everything works again.
Given a situation like the following,
> conda update -c intel --all
Collecting package metadata: done
Solving environment: |
The environment is inconsistent, please check the package plan carefully
The following packages are causing the inconsistency:
- intel/win-64::ipython==6.3.1=py36_3
- intel/win-64::prompt_toolkit==1.0.15=py36_2
done
As mentioned in other answers, the idea is to have some sort of re-installation to occur for the inconsistent packages.
Thus, with a few copy-&-paste's, you could:
> conda install intel/win-64::ipython==6.3.1=py36_3
Collecting package metadata: done
Solving environment: /
The environment is inconsistent, please check the package plan carefully
The following packages are causing the inconsistency:
- intel/win-64::ipython==6.3.1=py36_3
- intel/win-64::prompt_toolkit==1.0.15=py36_2
done
## Package Plan ##
environment location: c:\conda
added / updated specs:
- ipython
The following NEW packages will be INSTALLED:
jedi intel/win-64::jedi-0.12.0-py36_2
parso intel/win-64::parso-0.2.0-py36_2
pygments intel/win-64::pygments-2.2.0-py36_5
wcwidth intel/win-64::wcwidth-0.1.7-py36_6
Proceed ([y]/n)? y
Preparing transaction: done
Verifying transaction: done
Executing transaction: done
(and you would have to repeat for all the packages)
My “Shortcut”
Alternatively, cook up an (ugly) one-liner (this should work for Windows as well as other platforms)
Note: by "ORIGINAL_COMMAND", I'm referring to any command that gives you the error message (without any other side-effects, ideally)
<ORIGINAL_COMMAND> 2>&1 | python -c "import sys,re,conda.cli; conda.cli.main('conda','install','-y',*re.findall(r'^\s*-\s*(\S+)$',sys.stdin.read(),re.MULTILINE))"
Expanding the above one-liner:
from re import findall, MULTILINE
from sys import stdin
from conda.cli import main
main(
"conda", "install", "-y",
"--force", # Maybe add a '--force'/'--force-reinstall' (I didn't add it for the one-liner above)
*findall(r"^\s*-\s*(\S+)$", stdin.read(), MULTILINE) # Here are the offenders
)
I was getting an environment is inconsistent error when I tried to update my base conda environment. I'm using miniconda. Unfortunately, none of the answers above worked for me.
What did work for me was:
conda activate base
conda install conda --force-reinstall
conda install conda --force-reinstall
conda update --all
(Yes, for some reason it was necessary to run conda install conda --force-reinstall twice!)
The command conda install -c anaconda anaconda did the trick for me. For my setup, I need to specify the channel otherwise it would not work. After running the command in the terminal, I was prompted to update a list of packages that was found to be inconsistent. Without this step, I was not able to install or update any packages with conda install <package_name> or conda update <package_name respectively.
What worked for me was to
`conda remove <offending_packagename>`,
`conda update --all`
and then finally
`conda install <offending_packagename>`.
I had this problem for ages. The conda install anaconda might work, but it takes just way too long -- more than 24 hours on my machine.
Here is a solution that worked for me in under 5 minutes:
Remove all the unneeded packages -- being careful to leave the ones that are essential for conda to operate.
Then, use conda install anaconda.
But how?? there is a lot of them!
This is what I have done:
Make a fresh envinroment with python, fairly bare-bone. then, list the packages in there:
conda create -n fresh python
conda activate fresh
conda list
Save the output, you will need it.
1b. go back to the base envinroment:
conda deactivate
use the following snippet to generate a conda command that will remove all the inconsistent packages:
(good packages are)
exclusion_text = '''
_libgcc_mutex 0.1 main
_openmp_mutex 4.5 1_gnu
anyio 2.2.0 py39h06a4308_1
argon2-cffi 20.1.0 py39h27cfd23_1
async_generator 1.10 pyhd3eb1b0_0
...
... and more! get this from a good environment.
Note the usage of triple quotes (''') to use a multiline-string in python.
bad_packages_text = '''
- https://repo.continuum.io/pkgs/main/linux-64/networkx-2.1-py36_0.tar.bz2/linux-64::networkx==2.1=py36_0
- https://repo.continuum.io/pkgs/main/linux-64/spyder-3.2.6-> py36_0.tar.bz2/linux-64::spyder==3.2.6=py36_0
py36h4c697fb_0.tar.bz2/linux-64::jdcal==1.3=py36h4c697fb_0
- defaults/noarch::jupyterlab_server==1.1.4=py_0
- defaults/linux-64::argh==0.26.2=py37_0
...
... and more! get this by copy-pasting the "The following packages are causing the inconsistency." message.
then, in python, process this:
exclusions = [line.split(' ')[0] for line in exclusion_text_lines if line !='']
bad_packages_lines = bad_packages_text.split('\n')
bad_packages = [line.split('::')[1].split('==')[0] for line in bad_packages_lines if line!='']
exclusions.append('conda') # make sure!
exclusions.append('tqdm')
finally, construct the life-saving command:
command_line = 'conda remove '
for bad_package in bad_packages:
if bad_package not in exclusions:
command_line = f'{command_line} {bad_package}'
command_line
Since in solving the environment, all the packages on the remove list can be ignored, conda no longer needs to consider their versions, and the process is fast.
Possibly someone can refactor this method to make it easier -- or better yet, upgrade conda to enable quick reset base command.
This worked for me -- it took me longer to write this post than to execute these actions.
Good luck!
To those of us who have miniconda and can't/don't want to install anaconda: the accepted answer works when adapted.
conda install conda
conda update --all
Would have commented, but my rep is too low.
conda install anaconda
conda clean --all
conda update --all
fix the problem for me
To solve this message I had to run conda update --all in my base environment three times after each other.
Every time the number of inconsistent packages decreased until conda said:
# All requested packages already installed.
I'm on macOS Big Sur 11.6 using conda version 4.10.3.
In my case, none of the above worked. But this did the trick in less than a minute:
1- I downloaded again the lastest installer (miniconda in my case)
2- Run the installer with the -u option:
bash Miniconda3-py39_xxxx-Linux-x86_64.sh -u
3- Answer yes to all questions and let the installer finish
4- Then I could run conda update conda -all
Hope this helps...
You probably installed anaconda with python 2.7 but later you used python 3.x. Thus, you are getting an error message. In my case, I solved the problem by activating anaconda with python 2.7:
conda create --name py2 python=2.7
Try to have a look to the environment management
https://docs.conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html
By using something along the lines
conda create --name astra python=3.5
conda activate astra
conda install -c astra-toolbox astra-toolbox
You can see that you can even specify target python version. Now play with the new packages installed. When unsatisfied, you can always do
conda deactivate
conda env remove -n astra
If you install everything to the base env and something gets broken, then probably better is not to install conda at all and go with default python managing it through pip.
In my environment.
1.
conda install anaconda
conda update --all
Then it works correctly.
To install to my own directory I can use
pip install --user package
Alternatively I can use
conda install package
How do I ask conda to install to my home directory since conda does not take a --user flag?
Installing pip packages to $HOME folder
I don't think it's possible. Use virtual environments (conda create).
See -p option here:
-p PATH, --prefix PATH
Full path to environment prefix.
So to install to, say, local under your home directory, do:
conda install -p $HOME/local packagename
Note, however, this is not a "clean" install as it adds a bunch of conda-related files.
To install conda packages on your own directory you can follow these steps:
Create a blank environment
conda create -y -n my-conda-env
Replace the name my-conda-env with any name you want to give the environment.
Activate the environment
source activate my-conda-env
Don't forget to replace my-conda-env with the name you gave the conda environment from the previous step
Install your package
conda install -c bioconda epa-ng
And that's it, the package should be installed on your own directory
Simply:
sudo conda install -c conda-forge package
Or:
sudo chmod -R 777 ./
conda install -c conda-forge package
I don't know of an exact match for the --user flag, but a reasonable analogue is to use a virtual environment.
What I do when I have to install to a shared CentOS server where I don't have admin access:
First I run
conda env list
will list all conda virtual environments and display the path to each. Once you have the environment created and can see it in the conda env list, copy the path to the environment.
If you need to create one, you can do that with conda create or by running anaconda-navigator and using the GUI.
Activate your environment (if not active) with
conda activate [environment_name]
or
activate [environment_name]
depending on your system (most linux systems use the first, Windows and CentOS use the latter).
Now you can use
conda install -p [environment_path] [package_name]
and you are off to the races.
This is really a work around; it's not the best but it does install the package to the selected virtual environment.
The current Anaconda Install Individual Edition, when run in a linux local account, installs in a local directory. So all the subsequent installs should install there, too.
According to the documentation:
--use-local
I create a conda environment without specifying any packages using the following command:
conda create --name test_env
I can then use all the packages in the root environment inside test_env (but they do not appear in the outputs of conda list and conda env export). This is already unexpected to me but the real problems begin when I then install something inside that environment, e.g.:
conda install pywavelets
Afterwards, pywavelets is usable but all the other packages which are no dependencies of pywavelets disappear inside the environment (e.g. pandas). I don't understand why that happens. Does anybody have an explanation for that?
More importantly, what does this mean for best practices for working with conda environments? Should I always create my environments specifying at least python (conda create --name test_env python)? However, then I have to install everything by hand in that environment which is quite cumbersome. So, my idea now is to specify anaconda for all environments I create:
conda create --name test_env anaconda
The disadvantage, however, is that the list of dependencies listed by conda list and conda env export gets unnecessarily long (e.g. even listing the Anaconda Navigator). Does anybody have a better solution for this?
The reason you can use all the packages from the root environment when you don't specify a Python version during environment creation is because you're actually using the root environment's Python executable! You can check with which python or python -c "import sys; print(sys.executable)". See also my other answer here.
When you install pywavelets, one of the dependencies is (probably) Python, so a new Python executable is installed into your environment. Therefore, when you run Python, it only picks up the packages that are installed in the test_env.
If you want all of the packages from another environment, you can create a file that lists all the packages and then use that file to create a new environment, as detailed in the Conda docs: https://conda.io/docs/user-guide/tasks/manage-environments.html#building-identical-conda-environments
To summarize
conda list --explicit > spec-file.txt
conda create --name myenv --file spec-file.txt
or to install into an existing environment
conda install --name myenv --file spec-file.txt
Since that's just a text file, you can edit and remove any packages that you don't want.
I'm using iPython from the Anaconda distribution and I want to know how to check the version of some of the libraries from Terminal (using Mac), for example scikit_learn, but don't know the commands...
could someone advise? Thanks!
With anaconda, you can find information about the version with the following command:
conda list <package name>
for instance:
conda list scipy
will return (on my system, from my default environment)
# packages in environment at /Users/reblochonmasque/anaconda3:
#
scipy 0.15.1 np19py34_0
for your specific question, use:
conda list scikit-learn
To find what versions are available for your system, use:
conda info scikit-learn
if you find that you need to update the library, first update conda
conda update conda
then, updating anaconda will update all your libraries (those installed by conda)
conda update anaconda
if you only want to update this specific library (but you may have to deal with dependencies)
conda update -n <environment name> scikit_learn
If you ever need to revert to a previous version:
first find out the history of the versions you updated to
conda list -r scikit-learn
then choose the revision you want to revert to (the number will be from the list given by the command above):
conda install --revision=4 scikit-learn