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
Just wondering as what is the right way to update Anaconda and Conda installation and virtual environments. Here is my confusion step by step:
When I run command conda update anaconda, it updates/downgrades alot of packages.
Then I ran conda update conda, which again updates/downgrades some packages.
Next, I ran conda update --update-all it starts downgrading/upgrading different packages.
Lastly, just to make sure that everything's updated, I ran conda update anaconda again. I was expecting a message like Everything's up to date but to my surprise it was again showing a huge list of packages that needed to be updated/downgraded again?
What am I doing wrong here? It appears to me as if I am going in circles with these commands. Any help?
You're not doing anything wrong per se, but it just doesn't make much sense to ever run conda update anaconda and conda update --all right after each other on the same env - they represent two completely different configurations.
Update Anaconda
Anaconda is a Python distribution that bundles together a ton of packages. Presumably, a bunch of testing goes into verifying that all the package versions and builds are compatible with each other. Because this takes time to do, the Anaconda team only releases new distributions (i.e., a new anaconda version) every couple months or so. If you want a stable set of packages that have been tested for interoperability, then do conda update anaconda.
Update All
In between Anaconda releases, new versions of many packages are still released on the Anaconda channel, and if you run conda update --all you're going to inevitably get ahead of the versions specified in the anaconda bundle. If you want the newest individual package releases and don't mind potentially working with package builds that aren't thoroughly tested for integration, then run conda update --all.
It may be worth noting that people who prioritize having access to the latest versions of packages often seem to prefer Conda Forge, because it tends to have more frequent package releases. However, in my opinion, there's almost no point to installing Anaconda if you're going to switch most packages to Conda Forge anyway. Instead, just install Miniconda and only install what you want from Conda Forge at the start.
Update None
Personally, I will rarely run conda update on an env once I've harden the requirements for a project. Every time you update an env, you risk breaking code that you've already written. Instead, Conda makes it quite easy to create new envs, and if they have a lot of overlap with other envs, then the envs can be quite light due to sharing packages across envs via hardlinking.
Update Conda
The one exception to everything above is the conda package, which is the very infrastructure you're using to manage packages and envs. That, one should update just like any other package manager (e.g., a pip or a homebrew).
Found the answers in this useful post by Anaconda
Keeping Anaconda Up To Date
Below is a question that gets asked so often that I decided it would be helpful to publish an answer explaining the various ways in which Anaconda can be kept up to date. The question was originally asked on StackOverflow.
I have Anaconda installed on my computer and I’d like to update it. In
Navigator I can see that there are several individual packages that
can be updated, but also an anaconda package that sometimes has a
version number and sometimes says custom. How do I proceed?
The Answer
What 95% of People Actually Want
In most cases what you want to do when you say that you want to update Anaconda is to execute the command:
conda update --all
This will update all packages in the current environment to the latest version—with the small print being that it may use an older version of some packages in order to satisfy dependency constraints (often this won’t be necessary and when it is necessary the package plan solver will do its best to minimize the impact).
This needs to be executed from the command line, and the best way to get there is from Anaconda Navigator, then the “Environments” tab, then click on the triangle beside the root environment, selecting “Open Terminal”:
This operation will only update the one selected environment (in this case, the root environment). If you have other environments you’d like to update you can repeat the process above, but first click on the environment. When it is selected there is a triangular marker on the right (see image above, step 3). Or, from the command line, you can provide the environment name (-n envname) or path (-p /path/to/env). For example, to update your dspyr environment from the screenshot above:
conda update -n dspyr --all
Update Individual Packages
If you are only interested in updating an individual package then simply click on the blue arrow or blue version number in Navigator, e.g. for astroid or astropy in the screenshot above, and this will tag those packages for an upgrade. When you are done you need to click the “Apply” button:
Or from the command line:
conda update astroid astropy
Updating Just the Packages in the Standard Anaconda Distribution
If you don’t care about package versions and just want “the latest set of all packages in the standard Anaconda Distribution, so long as they work together,” then you should take a look at this gist.
Why Updating the Anaconda Package is Almost Always a Bad Idea
In most cases, updating the Anaconda package in the package list will have a surprising result—you may actually downgrade many packages (in fact, this is likely if it indicates the version as custom). The gist above provides details.
Leverage conda Environments
Your root environment is probably not a good place to try and manage an exact set of packages—it is going to be a dynamic working space with new packages installed and packages randomly updated. If you need an exact set of packages, create a conda environment to hold them. Thanks to the conda package cache and the way file linking is used, doing this is typically fast and consumes very little additional disk space. For example:
conda create -n myspecialenv -c bioconda -c conda-forge python=3.5 pandas beautifulsoup seaborn nltk
The conda documentation has more details and examples.
pip, PyPI, and setuptools?
None of this is going to help with updating packages that have been installed from PyPI via pip, or any packages installed using python setup.py install. conda list will give you some hints about the pip-based Python packages you have in an environment, but it won’t do anything special to update them.
Commercial Use of Anaconda or Anaconda Enterprise
It’s pretty much exactly the same story, with the exception that you may not be able to update the root environment if it was installed by someone else (say, to /opt/anaconda/latest). If you’re not able to update the environments you are using, you should be able to clone and then update:
conda create -n myenv --clone root
conda update -n myenv --all
The other way in is simply,
anaconda-navigator
The resulting GUI image is below, the only difference with respect to this question is where you see "Installed", there is a drop down menu for for "Updatable" and therein you simply click the dependencies for updating for any given environment.
General info
I'm sure everyone knows this, but for anyone who doesn't Anaconda navigator is a point and click GUI already part of the Anaconda and is simply brilliant for managing, installing, updating and deleting all the dependencies.
With respect to the question it is great for managing all the dependencies inside new envs, creating new envs, loading new channels. It works great remotely via X11 if you have Anaconda loaded on a remote cluster/server.
The bonus for me is that I've never known it fail.
conda install conda=4.8.2
works, as it installs a specific version and '''/''' will not spn for long.
I'm working on Anaconda by making multiple environments in it. I have made an environment camelot and now I want to install different libraries in this environment. So for example to install pandas in this environment,
I'm writing:
conda install pandas
or
conda install -c conda-forge camelot-py
Then it gives me this error:
python.exe-Entry Point Not Found
The procedure entry point OPENSSL_sk_new_reserve could not be
located in the dynamic link library.
C:\Users\abc\Anaconda3\Library\bin\libssl11_-x64.dll
First I thought it may be because of the environment variable, thus I set an environment variable for Python, but this did not resolve the issue.
as it is suggested in here I could solve this problem by copying libssl-1_1-x64 dlls in Anaconda/DLLS to Anaconda/Library/bin (probably replacing it)
I got the same issue while updating Anaconda navigator, and got it over by replacing the file libssl-1_1-x64.dll in Anaconda3/Library/bin with the one from Anaconda3/DLLs.
As mentioned by an Anaconda maintainer here ...
moving libssl dlls around like that is really not advisable. Those
DLLs are duplicated because you have something fishy going on in your
packages. There should not be any openssl DLLs in the DLLs folder.
They should be in Library/bin
By looking at the JSON files in the conda-meta directory I found out that DLLs\libssl-1_1-x64.dll was installed by the python 3.7.0 package, and Library\bin\libssl-1_1-x64.dll was installed by the openssl package. After further investigation I found out that Python 3.7.0 does not install OpenSSL as a separate package, but Python 3.7.1 (and later) does.
Typically upgrading Python goes as expected, but if you somehow end up with both python 3.7.0 and openssl packages installed simultaneously there will be two libssl-1_1-x64.dll files and your Anaconda distribution will be broken. (You can easily verify this with the conda list command.)
I think the best way to fix it is therefore:
Rename Library\bin\libssl-1_1-x64.dll to Library\bin\libssl-1_1-x64.dll.org (your are going to need it later.)
Copy DLLs\libssl-1_1-x64.dll to Library\bin\libssl-1_1-x64.dll
Update Python to version 3.7.1 or higher, for instance with conda update python. This will remove the DLLs\libssl-1_1-x64.dll file.
Delete the current Library\bin\libssl-1_1-x64.dll file.
Rename Library\bin\libssl-1_1-x64.dll.org back to Library\bin\libssl-1_1-x64.dll. This is necessary because I got HTTP errors in the next step otherwise.
Reinstall OpenSSL with conda install openssl --force-reinstall to ensure it's up to date again.
I had the exact same issue, and it also just started today. Kind of destroyed my entire work day, tbh...
I accidentally did a conda install ... in my base environment, and it updated conda and a handful of other modules. (Conda went from 4.5.12 to 4.7.10, in my case.) Anyway, after I rolled it back, things are working as expected again.
If this is what's causing your issue, here's a fix.
conda list --revisions
conda install --revision 1 (In my case "rev 1" was my most recent, stable base environment.)
(More details about this: https://sriramjaju.github.io/2018-05-30-2-minute-recipe-how-to-rollback-your-conda-environment/)
Now I'm worried that I've inadvertently configured something in a way that isn't compatible with the newest version of conda.
Edit: Don't follow this last suggestion if you're doing anything other than playing around in a conda environment to test-drive modules. See this and this.
Lastly, if you really need to install modules and do some work ASAP, pip install [module name] was still working for me before I thought to do the reversion thing.
My problem was same. I just uninstalled anaconda, and install it again. And the problem solved.
I was receiving the same following error while updating spyder and conda package.
python.exe-Entry Point Not Found
The procedure entry point OPENSSL_sk_new_reserve could not be
located in the dynamic link library.
C:\Users\abc\Anaconda3\Library\bin\libssl11_-x64.dll
solution:
I did replace libssl-1_1-x64 dlls from Anaconda/DLLs to
Anaconda/Library/bins as suggested here.
Before opening Anaconda Navigator desktop app, I updated conda in Anaconda Prompt using conda update conda. conda successfully updated.
Then I have updated spyder using conda update spyder command in
Anaconda Prompt. spyder updated and running successfully.
For those still having similar issues with libssl11_-x64.dll or other .dll files:
Use pip install instead if you can!
I had the same issue today with libcrypto-1_1-x64.dll when trying to install plotly using
conda install -c plotly plotly
This prompts a downgrade for anaconda, and in turn raises the error:
OPENSSL_sk_new_reserve [...] libcrypto-1_1-x64.dll
Instead, using for example
pip install plotly==4.1.0
works like a charm!
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.
I am trying to install pandas_datareader in Anaconda prompt by running the following command as per the official documentation:
conda install -c anaconda pandas-datareader
I am getting the error - "Solving environment : Failed" as shown below
I am connected to internet.
I found some links which said I needed to downgrade my Conda AND Python versions, so I tried that too, but it again says "Solving environment : Failed"
Also tried running the following command in Anaconda prompt,
pip install pandas_datareader
and it gave the error:
Could not find a version that satisfies the requirement pandas_datareader (from versions: )
No matching distribution found for pandas_datareader
Can someone please help here?
Config Details
Conda version : 4.5.12
Python version : 3.7
OS : Windows 10
PyPI Installation
The correct line for installing with PyPI is
pip install pandas-datareader
Note that the package name uses a hyphen (pandas-datareader), which is different from the underscore (pandas_datareader) that is used when importing.
Conda Installation
It's hard to answer this outright without more information. Other Windows 10 users who are behind proxies have reported the same error on Issue #764, which includes potential solutions.
Changing Python Version? No
I am skeptical that you would need to downgrade Python. You can easily test whether this is true without having to actually do it. Namely, if you really did need to change your Python version, then the following command would correctly solve the environment:
conda create --dry-run -n test-pd-dr anaconda::pandas-datareader
whereas this one would fail:
conda create --dry-run -n test-pd-dr python=3.7 anaconda::pandas-datareader
I expect they'd both fail. The first one attempts to create any environment with the only constraint being that it include pandas-datareader, whereas the second one additionally adds the constraint to use the same Python minor version you report. If they both fail, it's something else.
Also, changing Python versions is base env is risky (it can break your Conda if done incorrectly) and requires following specific directions from Anaconda.
Use the following command in Conda Prompt:
conda install -c anaconda pandas-datareader