I am trying to install jupyter but I am encountering some error. When I run:
conda install -c anaconda jupyter
The resolver just takes forever and doesn't really get anywhere. When I instead try it with mamba:
mamba install -c anaconda jupyter
I get the following output:
Looking for: ['jupyter']
anaconda/linux-64 Using cache
anaconda/noarch Using cache
bioconda/linux-64 Using cache
bioconda/noarch Using cache
pkgs/main/noarch No change
pkgs/r/linux-64 No change
pkgs/main/linux-64 No change
pkgs/r/noarch No change
Pinned packages:
- python 3.9.*
Encountered problems while solving:
- nothing provides openssl >=1.1.1,<1.1.2.0a0 needed by python-2.7.15-h9bab390_2
The error says that "nothing provides openssl >=1.1.1,<1.1.2.0a0 needed by python-2.7.15-h9bab390_2". However, when I enter in 'conda list', I can see the following:
openssl 1.1.1s h0b41bf4_1 conda-forge
I'm pretty sure that 1.1.1 is >= 1.1.1, so what I have installed should meet the requirement, but it's not. When I type 'which openssl', I get:
~/.conda/envs/workingENV/bin/openssl
For python --version I get:
Python 3.9.15
I can confirm that typing 'conda update conda' and 'condate update --all' beforehand does not resolve this. I don't know if it's related, but when I type in one of these, I also get this warning (although the warning doesn't impede the completion of the commands execution):
Warning: 2 possible package resolutions (only showing differing packages):
- anaconda/linux-64::m4-1.4.18-h4e445db_0
- defaults/linux-64::m4-1.4.18-h4e445dbdone
The openssl indicates it came from Conda Forge. Conda Forge is a standalone channel and trying to mix in packages from Anaconda channels can lead to unexpected behavior. Try sticking to just the conda-forge channel, e.g.,
mamba install -c conda-forge jupyter
Note that a better setup is to have Jupyter (plus nb_conda_kernels) installed in a dedicated environment and only install ipykernel in the kernel environments.
I cannot easily create an environment with conda containing the NGS tools I want. I reinstalled conda to get a fresh start since I had many python packages in the base env. I also took the occasion to install the full anaconda3 instead of miniconda I had before now I have way enough space.
Although all the packages are available via bioconda the only 2 i can add to my env are fastqc and multiqc. Before that I could install sra-tools and fastqc in the base env with miniconda3.
Config: MacOS Monterey 12.1 M1 chip. migration from my old macbook air with the lastest time machine bkp. I uninstalled miniconda with the anaconda-clean procedure and after that I also removed a python 3.9.5 I had in the apps folder I had initially installed to start learning 1yr ago before knowing about conda.
Also to be mentioned in case it may help: anaconda-navigator was not installed by the Anaconda3-2022.05-MacOSX-arm64.pkg (sha256 integrity check was ok)
in following the check installation/navigator troubleshooting on anaconda website I came across an error upon launching spyder:
```(ModuleNotFoundError: No module named 'PyQt5.QtWebEngineWidgets')```
Does somebody know where this unability to find the packages comes?
Thank you for your help!
best, Daniel
Env creation command and console output:
(base) mymac:~ D________$ conda create --name ngstools fastqc multiqc sra-tools samtools bowtie2 hisat2 subread -c conda-forge -c bioconda -c bioconda/label/cf201901
Terminal output:
Collecting package metadata (current_repodata.json): done
Solving environment: failed with repodata from current_repodata.json, will retry with next repodata source.
Collecting package metadata (repodata.json): done
Solving environment: failed
PackagesNotFoundError: The following packages are not available from current channels:
hisat2
subread
bowtie2
samtools
sra-tools
Current channels:
https://conda.anaconda.org/conda-forge/osx-arm64
https://conda.anaconda.org/conda-forge/noarch
https://conda.anaconda.org/bioconda/osx-arm64
https://conda.anaconda.org/bioconda/noarch
https://conda.anaconda.org/bioconda/label/cf201901/osx-arm64
https://conda.anaconda.org/bioconda/label/cf201901/noarch
https://repo.anaconda.com/pkgs/main/osx-arm64
https://repo.anaconda.com/pkgs/main/noarch
https://repo.anaconda.com/pkgs/r/osx-arm64
https://repo.anaconda.com/pkgs/r/noarch
To search for alternate channels that may provide the conda package you're looking for, navigate to
https://anaconda.org
and use the search bar at the top of the page.
Prefatory Comments
That is not a configuration I would recommend to bioinformatics users with M1 machines at the moment. There is no support yet for osx-arm64 in Bioconda. I expect one would find the least configuration issues by having everything in emulation (osx-64) from the base. Or you can continue with the osx-arm64 base (as you have now), but create new environments with the subdir setting. The answer below shows steps in this direction.
Also, I would very much avoid Anaconda/Miniconda. Mambaforge base is what I recommend to all bioinformaticians. And set the Bioconda channels globally.
Lastly, only advanced users should use channel labels (e.g., bioconda/label/cf201901). I realize they automatically show up on Anaconda Cloud, but they are only ever applicable in specialized circumstances, which most users will never encounter.
Immediate workaround
If you want to keep the osx-arm64 base, then you'll need to create a osx-64 environment for the NGS tools. I recommend the following protocol for best practice:
## create empty environment
conda create -n ngstools
## activate environment
conda activate ngstools
## configure architecture
conda config --env --set subdir osx-64
## configure channels for Bioconda
conda config --env --add channels defaults
conda config --env --add channels bioconda
conda config --env --add channels conda-forge
## install packages
conda install fastqc multiqc sra-tools samtools bowtie2 hisat2 subread
It's convoluted and, until osx-arm64 sees full support, you'd have to do this for every environment that requires emulation and Bioconda. Hence, why I recommend instead that you reinstall a osx-64 base (Mambaforge), which would just work.
Is there a way to specify the architecture/platform when creating a new conda environment? Alternatively, how does conda detect its current architecture/platform when its run?
What I'm aiming to do is this: I'm running on an Apple Silicon laptop. My pre-existing environments are running fine through Rosetta2, but I'd like to start experimenting with python running natively on Apple Silicon. miniforge provides a conda-forge repository with Apple Silicon builds, and I can tell conda to use the conda-forge channel when I create an environment. But I'm not seeing a way to specify that I'd like this to be an arm64 environment rather than an x86_64 environment, other than starting from miniforge's installer.
Thanks in advance.
CONDA_SUBDIR=osx-arm64 conda create -n native numpy -c conda-forge will get you a osx-arm64 native env.
To make it permanent, do,
conda activate native
conda config --env --set subdir osx-arm64
How to configure python conda Environments for both arm64 and x86_64 on M1 Apple Silicon
Adding to the answers, it is possible to configure conda to use both osx-arm64(arm64) and osx-64(x86_64) architectures.
I found adding conda config --env --set subdir osx-arm64 changes the option globally which created issues for me. Some of my projects relied on python dependencies that were only supported in either one or the other architecture not both: specifically tensorflow.
Install Xcode:
xcode-select --install
Install miniforge3
Install miniforge3 by downloading the shell script from here: https://github.com/conda-forge/miniforge. Ensure you select arm64 (Apple Silicon) architecture. You may need to enable execution of the shell script with:
chmod +x Miniforge3-MacOSX-arm64.sh
Then execute is with:
sh Miniforge3-MacOSX-arm64.sh
Add shortcuts to ~/.zshrc or ~/.bashrc:
Add the following code to ~/.zshrc.
The code will add two shortcut functions to create either an osx-64 or osx-arm64 conda environment.
# Create x86 conda environment
create_x86_conda_environment () {
# example usage: create_x86_conda_environment myenv_x86 python=3.9
CONDA_SUBDIR=osx-64 conda create -n $#
conda activate $1
}
# Create ARM conda environment
create_ARM_conda_environment () {
# example usage: create_ARM_conda_environment myenv_x86 python=3.9
CONDA_SUBDIR=osx-arm64 conda create -n $#
conda activate $1
}
Create conda environment
Now to create a python 3.9.13 osx-64(x86_64) environment with the name env_x86:
create_x86_conda_environment env_x86 python=3.9.13
Alternatively for osx-arm64 (arm64) environment:
create_ARM_conda_environment env_ARM python3.9.13
Pip install packages
Once activated you can install packages accordingly. In my case I needed an arm64 environment to install tensorflow-macos.
conda install -c apple tensorflow-deps
pip install tensorflow-macos tensorflow-metal
Prerequisites
Have Conda installed (anaconda / miniconda / miniforge3)
Have a terminal (Terminal or iTerm app) running with rosetta (for x64)
Add shortcut to create the environment
what does this do?
This function checks which architecture your current shell is using.
e.g. if you're running a terminal with rosetta, it will run with x86
Base on the architecture, it will add a prefix to your environment name
x86: x86_{name}
arm64: arm64_{name}
Creates the Environment & Activates it
function
add the following function to ~/.zshrc or ~/.bashrc:
create_conda_env () {
arch_name="$(uname -m)"
echo "Creating $arch_name environment"
if [ "${arch_name}" = "x86_64" ]; then
arch_type=osx-64
env_prefix="x86_"
elif [ "${arch_name}" = "arm64" ]; then
arch_type=osx-arm64
env_prefix="arm64_"
else
echo "Unknown architecture: $arch_name"
exit -1
fi
echo "New environment name: $env_prefix$1"
CONDA_SUBDIR=$arch_type conda create -n $env_prefix$#
conda activate $env_prefix$1
}
How to use?
create_conda_env {name} python={version} {aditional packages (optional)}
replace name, version and add any additional packages
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